content
stringlengths 1
1.04M
| input_ids
sequencelengths 1
774k
| ratio_char_token
float64 0.38
22.9
| token_count
int64 1
774k
|
|---|---|---|---|
from slothql.types.scalars import IntegerType, FloatType, StringType, BooleanType, IDType
from slothql.types.json import JsonStringType
from slothql.types.datetime import DateTimeType, DateType, TimeType
from .field import Field
| [
6738,
1017,
849,
13976,
13,
19199,
13,
1416,
282,
945,
1330,
34142,
6030,
11,
48436,
6030,
11,
10903,
6030,
11,
41146,
6030,
11,
4522,
6030,
198,
6738,
1017,
849,
13976,
13,
19199,
13,
17752,
1330,
449,
1559,
10100,
6030,
198,
6738,
1017,
849,
13976,
13,
19199,
13,
19608,
8079,
1330,
7536,
7575,
6030,
11,
7536,
6030,
11,
3862,
6030,
198,
6738,
764,
3245,
1330,
7663,
628,
628,
628,
628,
628
] | 3.4 | 70 |
import psycopg2
import json
import os
import sys
def create_tables():
""" create tables in the PostgreSQL database"""
commands = (
"""DROP TABLE main;
""",
"""
CREATE TABLE main (
package VARCHAR NOT NULL,
category VARCHAR NOT NULL,
downloads BIGINT NOT NULL,
description TEXT NOT NULL,
developer VARCHAR NOT NULL
);
""")
conn = None
try:
# read the connection parameters
params = "dbname='app_data' user='postgres' host='localhost' password='postgres'"
# connect to the PostgreSQL server
conn = psycopg2.connect(params)
cur = conn.cursor()
# create table one by one
for command in commands:
cur.execute(command)
# close communication with the PostgreSQL database server
cur.close()
# commit the changes
conn.commit()
except (Exception, psycopg2.DatabaseError) as error:
print(error)
finally:
if conn is not None:
conn.close()
if __name__ == '__main__':
create_tables()
read_jason(sys.argv[1]) | [
11748,
17331,
22163,
70,
17,
198,
11748,
33918,
198,
11748,
28686,
198,
11748,
25064,
198,
198,
4299,
2251,
62,
83,
2977,
33529,
198,
220,
220,
220,
37227,
2251,
8893,
287,
262,
2947,
47701,
6831,
37811,
198,
220,
220,
220,
9729,
796,
357,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
7707,
3185,
43679,
1388,
26,
198,
220,
220,
220,
220,
220,
220,
220,
13538,
1600,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
29244,
6158,
43679,
1388,
357,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
5301,
569,
31315,
1503,
5626,
15697,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
6536,
569,
31315,
1503,
5626,
15697,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
21333,
26746,
12394,
5626,
15697,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
6764,
40383,
5626,
15697,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
8517,
569,
31315,
1503,
5626,
15697,
198,
220,
220,
220,
220,
220,
220,
220,
5619,
198,
220,
220,
220,
220,
220,
220,
220,
13538,
4943,
628,
220,
220,
220,
48260,
796,
6045,
198,
220,
220,
220,
1949,
25,
198,
220,
220,
220,
220,
220,
220,
220,
1303,
1100,
262,
4637,
10007,
198,
220,
220,
220,
220,
220,
220,
220,
42287,
796,
366,
9945,
3672,
11639,
1324,
62,
7890,
6,
2836,
11639,
7353,
34239,
6,
2583,
11639,
36750,
6,
9206,
11639,
7353,
34239,
29653,
198,
220,
220,
220,
220,
220,
220,
220,
1303,
2018,
284,
262,
2947,
47701,
4382,
198,
220,
220,
220,
220,
220,
220,
220,
48260,
796,
17331,
22163,
70,
17,
13,
8443,
7,
37266,
8,
198,
220,
220,
220,
220,
220,
220,
220,
1090,
796,
48260,
13,
66,
21471,
3419,
198,
220,
220,
220,
220,
220,
220,
220,
1303,
2251,
3084,
530,
416,
530,
198,
220,
220,
220,
220,
220,
220,
220,
329,
3141,
287,
9729,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1090,
13,
41049,
7,
21812,
8,
198,
220,
220,
220,
220,
220,
220,
220,
1303,
1969,
6946,
351,
262,
2947,
47701,
6831,
4382,
198,
220,
220,
220,
220,
220,
220,
220,
1090,
13,
19836,
3419,
198,
220,
220,
220,
220,
220,
220,
220,
1303,
4589,
262,
2458,
198,
220,
220,
220,
220,
220,
220,
220,
48260,
13,
41509,
3419,
198,
220,
220,
220,
2845,
357,
16922,
11,
17331,
22163,
70,
17,
13,
38105,
12331,
8,
355,
4049,
25,
198,
220,
220,
220,
220,
220,
220,
220,
3601,
7,
18224,
8,
198,
220,
220,
220,
3443,
25,
198,
220,
220,
220,
220,
220,
220,
220,
611,
48260,
318,
407,
6045,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
48260,
13,
19836,
3419,
628,
198,
361,
11593,
3672,
834,
6624,
705,
834,
12417,
834,
10354,
198,
220,
220,
220,
2251,
62,
83,
2977,
3419,
198,
220,
220,
220,
1100,
62,
73,
888,
7,
17597,
13,
853,
85,
58,
16,
12962
] | 2.29783 | 507 |
import tensorflow as tf
import numpy
class GaussianBoundaryCondition(tf.keras.layers.Layer):
"""A simple module for applying an exponential boundary condition in N dimensions
Note that the exponent is *inside* of the power of 2 in the exponent.
This is to prevent divergence when it is trainable and goes negative.
Extends:
tf.keras.layers.Layer
"""
def __init__(self, n : int, exp : float=0.1, trainable : bool=True, dtype = tf.float64):
"""Initializer
Create a new exponentional boundary condition
Arguments:
n {int} -- Number of dimensions
Keyword Arguments:
exp {float} -- Starting value of exponents. Must be broadcastable to the number of dimensions (default: {1.0})
trainable {bool} -- Whether to allow the boundary condition to be trainable (default: {True})
"""
tf.keras.layers.Layer.__init__(self, dtype=dtype)
self.mean_subtract = True
if n < 1:
raise Exception("Dimension must be at least 1 for GaussianBoundaryCondition")
# This is the parameter controlling the shape of the exponent:
self.exponent = tf.Variable(exp, trainable=True, dtype=dtype)
self.exponent2 = tf.Variable(0.02, trainable=True, dtype=dtype)
@tf.function
| [
11748,
11192,
273,
11125,
355,
48700,
198,
11748,
299,
32152,
198,
198,
4871,
12822,
31562,
49646,
560,
48362,
7,
27110,
13,
6122,
292,
13,
75,
6962,
13,
49925,
2599,
198,
220,
220,
220,
37227,
32,
2829,
8265,
329,
11524,
281,
39682,
18645,
4006,
287,
399,
15225,
628,
220,
220,
220,
5740,
326,
262,
28622,
318,
1635,
48787,
9,
286,
262,
1176,
286,
362,
287,
262,
28622,
13,
198,
220,
220,
220,
770,
318,
284,
2948,
43366,
618,
340,
318,
4512,
540,
290,
2925,
4633,
13,
628,
220,
220,
220,
5683,
2412,
25,
198,
220,
220,
220,
220,
220,
220,
220,
48700,
13,
6122,
292,
13,
75,
6962,
13,
49925,
198,
220,
220,
220,
37227,
628,
220,
220,
220,
825,
11593,
15003,
834,
7,
944,
11,
299,
1058,
493,
11,
1033,
1058,
12178,
28,
15,
13,
16,
11,
4512,
540,
1058,
20512,
28,
17821,
11,
288,
4906,
796,
48700,
13,
22468,
2414,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
24243,
7509,
628,
220,
220,
220,
220,
220,
220,
220,
13610,
257,
649,
1033,
261,
1463,
282,
18645,
4006,
628,
220,
220,
220,
220,
220,
220,
220,
20559,
2886,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
299,
1391,
600,
92,
1377,
7913,
286,
15225,
628,
220,
220,
220,
220,
220,
220,
220,
7383,
4775,
20559,
2886,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1033,
1391,
22468,
92,
1377,
17962,
1988,
286,
1033,
3906,
13,
220,
12039,
307,
7025,
540,
284,
262,
1271,
286,
15225,
357,
12286,
25,
1391,
16,
13,
15,
30072,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
4512,
540,
1391,
30388,
92,
1377,
10127,
284,
1249,
262,
18645,
4006,
284,
307,
4512,
540,
357,
12286,
25,
1391,
17821,
30072,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
48700,
13,
6122,
292,
13,
75,
6962,
13,
49925,
13,
834,
15003,
834,
7,
944,
11,
288,
4906,
28,
67,
4906,
8,
628,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
32604,
62,
7266,
83,
974,
796,
6407,
628,
220,
220,
220,
220,
220,
220,
220,
611,
299,
1279,
352,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
5298,
35528,
7203,
29271,
3004,
1276,
307,
379,
1551,
352,
329,
12822,
31562,
49646,
560,
48362,
4943,
628,
198,
220,
220,
220,
220,
220,
220,
220,
1303,
770,
318,
262,
11507,
12755,
262,
5485,
286,
262,
28622,
25,
198,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
11201,
3471,
796,
48700,
13,
43015,
7,
11201,
11,
4512,
540,
28,
17821,
11,
288,
4906,
28,
67,
4906,
8,
198,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
11201,
3471,
17,
796,
48700,
13,
43015,
7,
15,
13,
2999,
11,
4512,
540,
28,
17821,
11,
288,
4906,
28,
67,
4906,
8,
628,
198,
220,
220,
220,
2488,
27110,
13,
8818,
198
] | 2.694501 | 491 |
# Copyright 2017 Google Inc.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
"""Simulate cost-optimal electrical grid construction under different policies.
Code contains GridElements: Power Sources, Demands and Storage. Grid
Elements are placed in different grid regions. Grid regions are
separated from each other so only sources with grid_region_id == x can
power Demands with grid_region_id == x
The costs of constructing GridElements are based upon:
nameplate_unit_cost: The cost to build one unit (e.g. Megawatt) of power.
variable_unit_cost: The cost to provide one unit of power over time.
(e.g. Megawatt-Hour)
The code simulates the grid over multiple time-slices. e.g. Hourly
over a one year period which would map to 24 * 365 = 8760 time-slices.
The code is based upon a linear-program which contains:
- An objective which is to minimize costs.
- Constraints which must be met before the solution can converge.
- conserve_power_constraint: Ensure that sum(power[t]) >=
demand[t] for all t in each grid-region
This code will work with any set of consistent units. For the
purposes of documentation, the units chosen are:
Power: Megawatts
Time: Hours
(Derived) Energy = Power * Time => Megawatt-Hours
Cost: Dollars ($)
CO2 Emissions: Tonnes
(Derived) CO2 Emitted per Energy => Tonnes / Megawatt-Hours
Carbon Tax: $ / Tonnes
"""
import logging
import numpy as np
from ortools.linear_solver import pywraplp
class Constraint(object):
"""Holds an LP Constraint object with extra debugging information.
Attributes:
constraint: underlying pywraplp.Constraint object
name: name of constraint
formula: hashtable that maps names of variables to coefficients
pywraplp.Constraint doesn't surface a list of variables/coefficients, so
we have to keep track ourselves.
"""
def __init__(self, lp, lower_bound, upper_bound, name=None, debug=False):
"""Initializes Constraint.
Args:
lp: LinearProgramContainer that wraps the LP solver which
creates the constraint.
lower_bound: (float) Lower bound on product between coeffs and variables.
upper_bound: (float) Upper bound on product between coeffs and variables.
name: Optional human readable string.
debug: Boolean which if set, logs constraint info.
"""
self.constraint = lp.solver.Constraint(lower_bound, upper_bound)
self.name = name
self.formula = {}
self.debug = debug
if self.debug:
logging.debug("CONSTRAINT: %f <= %s <= %f", lower_bound, name, upper_bound)
def set_coefficient(self, variable, coefficient):
"""Adds variable * coefficient to LP Coefficient.
Wraps pywrap.SetCoefficient(variable, coefficient) method and
saves variable, coefficient to formula dict.
After calling this method, Objective += variable * coefficient
Args:
variable: (Lp Variable) The Variable multiplicand.
coefficient: (float) The coefficient multiplicand.
"""
self.constraint.SetCoefficient(variable, coefficient)
self.formula[variable.name()] = coefficient
if self.debug:
logging.debug("%s += %s * %f", self.name, variable.name(), coefficient)
class Objective(object):
"""Holds an LP Objective object with extra debugging information.
Attributes:
objective: Underlying pywraplp.Objective object.
"""
def __init__(self, lp, minimize=True):
"""Initializes Objective.
Args:
lp: LinearProgramContainer that wraps the LP solver which
creates the Objective.
minimize: boolean, True if objective should be minimized
otherwise objective is maximizied.
"""
self.objective = lp.solver.Objective()
self.formula = {}
if minimize:
self.objective.SetMinimization()
else:
self.objective.SetMaximization()
def set_coefficient(self, variable, coefficient):
"""Adds variable * coefficient to LP Objective.
Wraps pywrap.SetCoefficient(variable, coefficient) method and
saves variable, coefficient to formula dict.
After calling this method, Objective += variable * coefficient
Args:
variable: (Lp Variable) The Variable multiplicand.
coefficient: (float) The coefficient multiplicand.
"""
self.objective.SetCoefficient(variable, coefficient)
self.formula[variable.name()] = coefficient
class GridDemand(object):
"""Simple place-holder object which represents load on the grid."""
def __init__(self, name, grid_region_id=0):
"""Initializes GridDemand object.
Args:
name: name of the demand object
grid_region_id: An int specifying the grid region of the demand.
Only sources with the same grid_region_id can power this demand.
"""
self.name = name
self.grid_region_id = grid_region_id
class GridSource(object):
"""Denotes Costs, co2, region, power and energy limitations of a power source.
Grid Sources may either be dispatchable or non-dispatchable.
- Dispatchable sources may power at any time, e.g. fossil fuel plants.
- Non-dispatchable sources are dependent on the environment to
generate power. e.g. Solar or Wind plants.
If there is a time-slice power profile indexed by the same name as
this source in LinearProgramContainer.profiles. The source is
considered Non-dispatchable. Otherwise, it is considered dispatchable.
Attributes:
name: (str) name of the object.
nameplate_unit_cost: (float) Cost to build a unit of
dispatchable power. ($ / Megawatt of capacity)
variable_unit_cost: (float) Cost to supply a unit of dispatchable power
per time. ($ / Megawatt-Hour)
grid_region_id: An int specifying the grid region of the source.
Only demands with the same grid_region_id can sink the power
from this source.
max_power: (float) Optional Maximum power which object can supply.
(Megawatt). Set < 0 if there is no limit.
max_energy: (float) Optional maximum energy which object can
supply. (Megawatt-Hours) Set < 0 if there is no limit.
co2_per_electrical_energy: (float) (Tonnes of CO2 / Megawatt Hour).
power_coefficient: (float) ratio of how much power is supplied by
object vs. how much power gets on the grid. 0 <
power_coefficient < 1. Nominally 1.0.
is_rps_source: Boolean which denotes if the source is included
in the Renewable Portfolio Standard.
solver: Either a _GridSourceDispatchableSolver or
_GridSourceNonDispatchableSolver. Used to setup LP
Constraints, Objectives and variables for the source and to
report results.
timeslice_variables: An array of LP variables, one per time-slice
of simulation. Array is mapped so that variable for
time-slice t is at index t.
e.g.
Variable for first time-slice is timeslice_variable[0].
Variable for last time-slice is timeslice_variable[-1].
Variable for time-slice at time t is timeslice_variable[t].
Only gets declared if GridSource is a DispatchableSource.
nameplate_variable: LP variable representing the nameplate or
maximum power the GridSource can output at any given
time.
"""
def __init__(
self,
name,
nameplate_unit_cost,
variable_unit_cost,
grid_region_id=0,
max_power=-1.0,
max_energy=-1.0,
co2_per_electrical_energy=0,
power_coefficient=1.0,
is_rps_source=False,
):
"""Sets characteristics of a GridSource object.
Args:
name: (str) name of the object.
nameplate_unit_cost: (float) Cost to build a unit of
dispatchable power. ($ / Megawatt of capacity)
variable_unit_cost: (float) Cost to supply a unit of dispatchable power
per time. ($ / Megawatt-Hour)
grid_region_id: An int specifying the grid region of the demand.
Only demands with the same grid_region_id can sink the power
from this source.
max_power: (float) Maximum power which object can supply. (Megawatt)
max_energy: (float) Maximum energy which object can
supply. (Megawatt-Hours)
co2_per_electrical_energy: (float) (Tonnes of CO2 / Megawatt Hour).
power_coefficient: (float) ratio of how much power is supplied by
object vs. how much power gets on the grid. 0 <
power_coefficient < 1. Nominally 1.0.
is_rps_source: Boolean which denotes if the source is included
in the Renewable Portfolio Standard.
"""
self.name = name
self.nameplate_unit_cost = nameplate_unit_cost
self.variable_unit_cost = variable_unit_cost
self.max_energy = max_energy
self.max_power = max_power
self.grid_region_id = grid_region_id
self.co2_per_electrical_energy = co2_per_electrical_energy
self.power_coefficient = power_coefficient
self.is_rps_source = is_rps_source
self.solver = None
self.timeslice_variables = None
self.nameplate_variable = None
def configure_lp_variables_and_constraints(self, lp):
"""Declare lp variables, and set constraints.
Args:
lp: The LinearProgramContainer.
Defers to self.solver which properly configures variables and
constraints in this object.
See Also:
_GridSourceDispatchableSolver, _GridSourceNonDispatchableSolver
"""
self.solver.configure_lp_variables_and_constraints(lp)
def post_process(self, lp):
"""Update lp post_processing result variables.
This is done post lp.solve() so that sanity data checks can be done
on RPS before returning results.
Args:
lp: The LinearProgramContainer where the post processing variables reside.
"""
if lp.rps_percent > 0.0 and self.is_rps_source:
lp.rps_total[self.grid_region_id] += self.get_solution_values()
else:
lp.non_rps_total[self.grid_region_id] += self.get_solution_values()
def get_solution_values(self):
"""Gets the linear program solver results.
Must be called after lp.solve() to ensure solver has properly
converged and has generated results.
Returns:
np.array of solutions for each timeslice variable.
"""
return self.solver.get_solution_values()
def get_nameplate_solution_value(self):
"""Gets the linear program solver results for nameplate.
Must be called after lp.solve() to ensure solver has properly
converged and has generated results.
Raises:
RuntimeError: If called before LinearProgramContainer.solve().
Returns:
Float value representing solved nameplate value.
"""
nameplate_variable = self.nameplate_variable
if nameplate_variable is None:
raise RuntimeError("Get_nameplate_solution_value called before solve().")
return nameplate_variable.solution_value()
class _GridSourceDispatchableSolver(object):
"""Power Source which can provide power at any time.
Attributes:
source: GridSource object where self generates LP variables
"""
def configure_lp_variables_and_constraints(self, lp):
"""Declare lp variables, and set constraints in grid_source.
Args:
lp: The LinearProgramContainer.
Variables Declared include:
- timeslice variables: represent how much power the source is
outputting at each time-slice.
- nameplate variable: represents the maximum power sourced.
The values of these variables are solved by the linear program to
optimize costs subject to some constraints.
The overall objective is to minimize cost. Herein, the overall
cost is increased by:
- nameplate cost: nameplate_unit_cost * nameplate variable
- variable cost: variable_unit_cost * sum(timeslice_variables)
- carbon cost: lp.carbon_tax * sum(timeslice_variables) *
co2_per_electrical_energy
Since variable and carbon costs accrue on a periodic basis, we
multiply them by lp.cost_of_money to make periodic and
one-time costs comparable.
Constraints created / modified here include:
- Maximum Energy: Ensure sum timeslice-variables < max_energy if
self.max_energy >= 0.
This constraint is only for sources where there are limits
to the total amount of generation which can be built.
E.g. There are only a limited number of places where one can
build hydropower.
- Maximum Power: Ensure no timeslice-variables > max_power if
self.max_power is >= 0.
This constraint is only for sources where there are limits
to the maximum amount of power which can be built.
E.g. hydropower which can only discharge at a maximum rate.
- Conserve Power: Ensure that sum(power) > demand for all
time-slices. Colloquially called "Keeping the Lights on."
- Ensure nameplate variable > power(t) for all t. We must make
sure that we've priced out a plant which can supply the
requested power.
"""
source = self.source
# setup LP variables.
source.timeslice_variables = lp.declare_timeslice_variables(
source.name, source.grid_region_id
)
source.nameplate_variable = lp.declare_nameplate_variable(
source.name, source.grid_region_id
)
solver = lp.solver
# Configure maximum energy if it is >= 0. Otherwise do not
# create a constraint.
max_energy_constraint = (
lp.constraint(0.0, source.max_energy) if source.max_energy >= 0 else None
)
# Configure maximum nameplate if it is >= 0. Otherwise do not
# create a constraint.
max_power = source.max_power
if max_power >= 0:
lp.constraint(0.0, max_power).set_coefficient(
source.nameplate_variable, 1.0
)
# Total_cost includes nameplate cost.
cost_objective = lp.minimize_costs_objective
cost_objective.set_coefficient(
source.nameplate_variable, source.nameplate_unit_cost
)
# Add timeslice variables to coefficients.
for t, var in enumerate(source.timeslice_variables):
# Total_cost also includes variable and carbon cost.
variable_coef = (
source.variable_unit_cost
+ source.co2_per_electrical_energy * lp.carbon_tax
) * lp.cost_of_money
cost_objective.set_coefficient(var, variable_coef)
# Keep the lights on at all times. Power_coefficient is usually
# 1.0, but is -1.0 for GridStorage.sink and discharge_efficiency
# for GridStorage.source.
lp.conserve_power_constraint[source.grid_region_id][t].set_coefficient(
var, source.power_coefficient
)
# Constrain rps_credit if needed.
if source.is_rps_source:
lp.rps_source_constraints[source.grid_region_id][t].set_coefficient(
var, source.power_coefficient
)
# Ensure total energy is less than source.max_energy.
if max_energy_constraint is not None:
max_energy_constraint.set_coefficient(var, 1.0)
# Ensure power doesn't exceed source.max_power.
if max_power >= 0:
lp.constraint(0.0, max_power).set_coefficient(var, 1.0)
# Nameplate must be bigger than largest power.
# If nameplate_unit_cost > 0, Cost Optimization will push
# Nameplate near max(timeslice_variables).
nameplate_constraint = lp.constraint(0.0, solver.infinity())
nameplate_constraint.set_coefficient(var, -1.0)
nameplate_constraint.set_coefficient(source.nameplate_variable, 1.0)
# Constrain maximum nameplate if max_power is set.
if source.max_power >= 0:
lp.constraint(0.0, source.max_power).set_coefficient(
source.nameplate_variable, 1.0
)
def get_solution_values(self):
"""Gets the linear program solver results.
Must be called after lp.solve() to ensure solver has properly
converged and has generated results.
Raises:
RuntimeError: If called before LinearProgramContainer.solve().
Returns:
np.array of solutions for each timeslice variable.
"""
timeslice_variables = self.source.timeslice_variables
if timeslice_variables is None:
raise RuntimeError("get_solution_values called before solve.")
return np.array([v.solution_value() for v in timeslice_variables])
class _GridSourceNonDispatchableSolver(object):
"""Power Source which can provide nameplate multiple of its profile.
Attributes:
source: GridSource object where self generates LP variables
profile: pandas Series which represents what fraction of the
nameplate the source can provide at any given time.
"""
def configure_lp_variables_and_constraints(self, lp):
"""Declare lp variables, and set constraints in grid_source.
Args:
lp: The LinearProgramContainer.
Variables Declared include:
- nameplate variable: represents the maximum power sourced.
The values of these variables are solved by the linear program to
optimize costs subject to some constraints.
The overall objective is to minimize cost. Herein, the overall
cost is increased by:
- nameplate cost: nameplate_unit_cost * nameplate variable
- variable cost: variable_unit_cost * nameplate variable * sum(profile)
- carbon cost: lp.carbon_tax * nameplate variable * sum(profile)
Since variable and carbon costs accrue on a yearly basis, we
multiply them by lp.cost_of_money to make yearly and
one-time costs comparable.
Constraints created / modified here include:
- Maximum Energy: Ensure nameplate * sum(profile) < max_energy if
self.max_energy >= 0.
This constraint is only for sources where there are limits
to the total amount of generation which can be built.
E.g. There are only a limited number of places where one can
build hydropower.
- Maximum Power: Ensure nameplate <= max_power if
self.max_power >= 0.
This constraint is only for sources where there are limits
to the maximum amount of power which can be built.
E.g. hydropower which can only discharge at a maximum rate.
- Conserve Power: Ensure that sum(power) > demand for all
time-slices. Colloquially called "Keeping the Lights on."
"""
source = self.source
# setup LP variables.
source.nameplate_variable = lp.declare_nameplate_variable(
source.name, source.grid_region_id
)
sum_profile = sum(self.profile)
# Configure maximum energy if it is >= 0. Otherwise do not
# create a constraint.
if source.max_energy >= 0:
lp.constraint(0.0, source.max_energy).set_coefficient(
source.nameplate_variable, sum_profile
)
# Configure maximum energy if it is >= 0. Otherwise do not
# create a constraint.
max_power = source.max_power
if max_power >= 0:
lp.constraint(0.0, max_power).set_coefficient(
source.nameplate_variable, 1.0
)
# Total_cost includes nameplate cost.
cost_objective = lp.minimize_costs_objective
cost_coefficient = source.nameplate_unit_cost + lp.cost_of_money * (
source.variable_unit_cost * sum_profile
+ source.co2_per_electrical_energy * sum_profile * lp.carbon_tax
)
cost_objective.set_coefficient(source.nameplate_variable, cost_coefficient)
# Add timeslice variables to coefficients.
for t, profile_t in enumerate(self.profile):
# Keep the lights on at all times.
try:
constraint = lp.conserve_power_constraint[source.grid_region_id]
except KeyError:
raise KeyError(
"No Demand declared in grid_region %d." % (source.grid_region_id)
)
constraint[t].set_coefficient(source.nameplate_variable, profile_t)
# Constrain rps_credit if needed.
if source.is_rps_source:
lp.rps_source_constraints[source.grid_region_id][t].set_coefficient(
source.nameplate_variable, profile_t
)
def get_solution_values(self):
"""Gets the linear program solver results.
Must be called after lp.solve() to ensure solver has properly
converged and has generated results.
Raises:
RuntimeError: If called before LinearProgramContainer.solve().
Returns:
np.array of solutions for each timeslice variable.
"""
nameplate_variable = self.source.nameplate_variable
if nameplate_variable is None:
raise RuntimeError("get_solution_values called before solve.")
return nameplate_variable.solution_value() * self.profile.values
class GridStorage(object):
"""Stores energy from the grid and returns it when needed subject to losses.
Attributes:
name: A string which is the name of the object.
storage_nameplate_cost: A float which is the cost per nameplate of
energy storage. E.g. The cost of batteries.
charge_nameplate_cost: A float which is the cost per nameplate
power to charge the storage. E.g. The rectifier cost to convert
an AC grid to DC storage.
discharge_nameplate_cost: A float which is the cost per nameplate
power to recharge the grid. E.g. The cost of a power inverter to
convert DC storage back to AC
grid_region_id: An int specifying the grid region of the storage.
The storage can only store energy generated by sources with the
same grid_region_id. Only demands with the same grid_region_id
can sink power from this.
charge_efficiency: A float ranging from 0.0 - 1.0 which describes
the energy loss between the grid and the storage element. 0.0
means complete loss, 1.0 means no loss.
storage_efficiency: A float ranging from 0.0 - 1.0 which describes
how much stored energy remains from previous stored energy after
one time-cycle. 1.0 means no loss. 0.0 means all stored energy
is lost.
discharge_efficiency: A float ranging from 0.0 - 1.0 which describes
the energy loss between storage and grid when recharging the grid.
0.0 means complete loss, 1.0 means no loss.
max_charge_power: A float which represents the maximum power that
can charge storage (calculated before any efficiency losses.).
A value < 0 means there is no charge power limit.
max_discharge_power: A float which represents the maximum power
that can discharge storage (calculated before any efficiency
losses.). A value < 0 means there is no discharge power limit.
max_storage: An optional float which represents the maximum energy
that can be stored. A value < 0 means there is no maximum
storage limit.
is_rps: Boolean; if true, keeps track of rps_credit as storage is
charged / discharged. Amount charging[t] is subtracted from
rps_credit[t] from rps_credit[t]. Amount discharging[t] is
added to rps_credit[t]. If false, no rps_credits are adjusted.
"""
def configure_lp_variables_and_constraints(self, lp):
"""Declare lp variables, and set constraints.
Args:
lp: LinearProgramContainer, contains lp solver and constraints.
"""
# Set up LP variables.
self.energy_variables = lp.declare_timeslice_variables(
self.name, self.grid_region_id
)
if self.storage_nameplate_cost:
self.energy_nameplate = lp.declare_nameplate_variable(
self.name, self.grid_region_id
)
# Set up source and configure LP variables.
self.source = GridSource(
name=self.name + " source",
nameplate_unit_cost=self.discharge_nameplate_cost,
variable_unit_cost=0.0,
grid_region_id=self.grid_region_id,
max_power=self.max_discharge_power,
co2_per_electrical_energy=0.0,
power_coefficient=self.discharge_efficiency,
is_rps_source=self.is_rps,
)
self.source.solver = _GridSourceDispatchableSolver(self.source)
self.source.configure_lp_variables_and_constraints(lp)
# Set up sink and configure LP variables.
self.sink = GridSource(
name=self.name + " sink",
nameplate_unit_cost=self.discharge_nameplate_cost,
variable_unit_cost=0.0,
grid_region_id=self.grid_region_id,
max_power=self.max_charge_power,
co2_per_electrical_energy=0.0,
power_coefficient=-1.0,
is_rps_source=self.is_rps,
)
self.sink.solver = _GridSourceDispatchableSolver(self.sink)
self.sink.configure_lp_variables_and_constraints(lp)
# Add energy nameplate costs to the objective. Other costs are
# added by source/sink.configure_lp_variables_and_constraints.
if self.storage_nameplate_cost:
nameplate = self.energy_nameplate
lp.minimize_costs_objective.set_coefficient(
nameplate, self.storage_nameplate_cost
)
# Constrain Energy Storage to be Energy Last time plus sink minus source.
# Storage is circular so variables at t=0 depend on variables at t=-1
# which is equivalent to last value in python indexing scheme.
variables = self.energy_variables
for t in lp.time_index_iterable:
# Ce = charge_efficiency,
# Se = storage_efficiency.
# Stored[i] = se * Stored[i-1] + ce * sink[i-1] - source[i-1]
# 0 = -Stored[i] + se * Stored[i-1] + ce * sink[i-1] - source[i-1]
c = lp.constraint(0.0, 0.0)
c.set_coefficient(variables[t], -1.0) # -Stored[i]
c.set_coefficient(variables[t - 1], self.storage_efficiency)
# Source and sink are relative to the grid, so opposite here:
# Sink adds to storage, source subtracts from storage.
c.set_coefficient(self.source.timeslice_variables[t - 1], -1.0)
c.set_coefficient(
self.sink.timeslice_variables[t - 1], self.charge_efficiency
)
# Ensure nameplate is larger than stored_value.
if self.storage_nameplate_cost:
nameplate_constraint = lp.constraint(0.0, lp.solver.infinity())
nameplate_constraint.set_coefficient(nameplate, 1.0)
nameplate_constraint.set_coefficient(variables[t], -1.0)
# Constrain maximum storage if max_storage >= 0
if self.max_storage >= 0.0:
max_storage_constraint = lp.constraint(0.0, self.max_storage)
max_storage_constraint.set_coefficient(variables[t], 1.0)
def post_process(self, lp):
"""Update lp post_processing result variables.
This is done post lp.solve() so that sanity data checks can be done
on RPS before returning results.
Args:
lp: The LinearProgramContainer where the post processing variables reside.
"""
sink_vals = self.sink.get_solution_values()
source_vals = self.source.get_solution_values() * self.discharge_efficiency
if self.is_rps:
lp.rps_total[self.grid_region_id] += source_vals - sink_vals
else:
lp.non_rps_total[self.grid_region_id] += source_vals - sink_vals
def get_nameplate_solution_value(self):
"""Gets the linear program solver results for nameplate.
Must be called after lp.solve() to ensure solver has properly
converged and has generated results.
Raises:
RuntimeError: If called before LinearProgramContainer.solve().
Returns:
Float value representing solved nameplate value.
"""
if self.storage_nameplate_cost:
nameplate_variable = self.energy_nameplate
if nameplate_variable is None:
raise RuntimeError(
"Get_nameplate_solution_value called before solve()."
)
return nameplate_variable.solution_value()
else:
return max(self.get_solution_values())
def get_solution_values(self):
"""Gets the linear program solver results.
Must be called after lp.solve() to ensure solver has properly
converged and has generated results.
Raises:
RuntimeError: If called before LinearProgramContainer.solve().
Returns:
np.array of solutions for each timeslice variable.
"""
timeslice_variables = self.energy_variables
if timeslice_variables is None:
raise RuntimeError("get_solution_values called before solve.")
return np.array([v.solution_value() for v in timeslice_variables])
class GridRecStorage(object):
"""Stores energy from the grid and returns it when needed subject to losses.
This is a wrapper around two GridStorage objects, one which stores
"clean" energy (is_rps) and one which stores "dirty" energy (not
is_rps). There is a need for both types of storage to keep track of
renewable energy credits.
Attributes:
name: A string which is the name of the object.
storage_nameplate_cost: A float which is the cost per nameplate of
energy storage. E.g. The cost of batteries.
charge_nameplate_cost: A float which is the cost per nameplate
power to charge the storage. E.g. The rectifier cost to convert
an AC grid to DC storage.
discharge_nameplate_cost: A float which is the cost per nameplate
power to recharge the grid. E.g. The cost of a power inverter to
convert DC storage back to AC
grid_region_id: An int specifying the grid region of the storage.
The storage can only store energy generated by sources with the
same grid_region_id. Only demands with the same grid_region_id
can sink power from this.
charge_efficiency: A float ranging from 0.0 - 1.0 which describes
the energy loss between the grid and the storage element. 0.0
means complete loss, 1.0 means no loss.
storage_efficiency: A float ranging from 0.0 - 1.0 which describes
how much stored energy remains from previous stored energy after
one time-cycle. 1.0 means no loss. 0.0 means all stored energy
is lost.
discharge_efficiency: A float ranging from 0.0 - 1.0 which describes
the energy loss between storage and grid when recharging the grid.
0.0 means complete loss, 1.0 means no loss.
max_charge_power: A float which represents the maximum power that
can charge storage (calculated before any efficiency losses.).
A value < 0 means there is no charge power limit.
max_discharge_power: A float which represents the maximum power
that can discharge storage (calculated before any efficiency
losses.). A value < 0 means there is no discharge power limit.
max_storage: An optional float which represents the maximum energy
that can be stored. A value < 0 means there is no maximum
storage limit.
rec_storage: GridStorage object which stores "clean" energy.
no_rec_storage: GridStorage object which stores "dirty" energy.
"""
def configure_lp_variables_and_constraints(self, lp):
"""Declare lp variables, and set constraints."""
# For rec_storage and no_rec_storage storage, set all costs to 0
# and with no limits. Calculate costs and limits after
# declaration.
self.rec_storage = GridStorage(
name=self.name + " REC_STORAGE",
storage_nameplate_cost=0,
grid_region_id=self.grid_region_id,
charge_efficiency=self.charge_efficiency,
discharge_efficiency=self.discharge_efficiency,
storage_efficiency=self.storage_efficiency,
is_rps=True,
)
self.no_rec_storage = GridStorage(
name=self.name + " NO_REC_STORAGE",
storage_nameplate_cost=0,
grid_region_id=self.grid_region_id,
charge_efficiency=self.charge_efficiency,
discharge_efficiency=self.discharge_efficiency,
storage_efficiency=self.storage_efficiency,
is_rps=False,
)
self.rec_storage.configure_lp_variables_and_constraints(lp)
self.no_rec_storage.configure_lp_variables_and_constraints(lp)
# Calculate costs and limits based on the sum of both rec_storage
# and no_rec_storage.
# Set up LP variables.
self.energy_variables = lp.declare_timeslice_variables(
self.name, self.grid_region_id
)
self.energy_nameplate = lp.declare_nameplate_variable(
self.name, self.grid_region_id
)
self.charge_nameplate = lp.declare_nameplate_variable(
self.name + " charge nameplate", self.grid_region_id
)
self.discharge_nameplate = lp.declare_nameplate_variable(
self.name + " discharge nameplate", self.grid_region_id
)
# Set limits if needed.
if self.max_storage >= 0:
lp.constraint(0.0, self.max_storage).set_coefficient(
self.energy_nameplate, 1.0
)
if self.max_charge_power >= 0:
lp.constraint(0.0, self.max_charge_power).set_coefficient(
self.charge_nameplate, 1.0
)
if self.max_discharge_power >= 0:
lp.constraint(0.0, self.max_discharge_power).set_coefficient(
self.discharge_nameplate, 1.0
)
# Add energy nameplate costs to the objective.
lp.minimize_costs_objective.set_coefficient(
self.energy_nameplate, self.storage_nameplate_cost
)
lp.minimize_costs_objective.set_coefficient(
self.charge_nameplate, self.charge_nameplate_cost
)
lp.minimize_costs_objective.set_coefficient(
self.discharge_nameplate, self.discharge_nameplate_cost
)
rec_storage_energy_variables = self.rec_storage.energy_variables
no_rec_storage_energy_variables = self.no_rec_storage.energy_variables
for t in lp.time_index_iterable:
# Ensure nameplate is >= sum(stored_values)[t].
nameplate_constraint = lp.constraint(0.0, lp.solver.infinity())
nameplate_constraint.set_coefficient(self.energy_nameplate, 1.0)
nameplate_constraint.set_coefficient(rec_storage_energy_variables[t], -1.0)
nameplate_constraint.set_coefficient(
no_rec_storage_energy_variables[t], -1.0
)
rec_storage_charge_variables = self.rec_storage.sink.timeslice_variables
no_rec_storage_charge_variables = (
self.no_rec_storage.sink.timeslice_variables
)
rec_storage_discharge_variables = (
self.rec_storage.source.timeslice_variables
)
no_rec_storage_discharge_variables = (
self.no_rec_storage.source.timeslice_variables
)
max_charge_constraint = lp.constraint(0.0, lp.solver.infinity())
max_charge_constraint.set_coefficient(self.charge_nameplate, 1.0)
max_charge_constraint.set_coefficient(rec_storage_charge_variables[t], -1.0)
max_charge_constraint.set_coefficient(
no_rec_storage_charge_variables[t], -1.0
)
max_charge_constraint.set_coefficient(
rec_storage_discharge_variables[t], 1.0
)
max_charge_constraint.set_coefficient(
no_rec_storage_discharge_variables[t], 1.0
)
max_discharge_constraint = lp.constraint(0.0, lp.solver.infinity())
max_discharge_constraint.set_coefficient(self.discharge_nameplate, 1.0)
max_discharge_constraint.set_coefficient(
rec_storage_charge_variables[t], 1.0
)
max_discharge_constraint.set_coefficient(
no_rec_storage_charge_variables[t], 1.0
)
max_discharge_constraint.set_coefficient(
rec_storage_discharge_variables[t], -1.0
)
max_discharge_constraint.set_coefficient(
no_rec_storage_discharge_variables[t], -1.0
)
def get_nameplate_solution_value(self):
"""Gets the linear program solver results for nameplate.
Must be called after lp.solve() to ensure solver has properly
converged and has generated results.
Raises:
RuntimeError: If called before LinearProgramContainer.solve().
Returns:
Float value representing solved nameplate value.
"""
if self.storage_nameplate_cost:
nameplate_variable = self.energy_nameplate
if nameplate_variable is None:
raise RuntimeError(
"Get_nameplate_solution_value called before solve()."
)
return nameplate_variable.solution_value()
else:
return max(self.get_solution_values())
class _GridTransmission(GridSource):
"""Shuttles power from one time-zone to another."""
def __init__(
self,
name,
nameplate_unit_cost,
source_grid_region_id=0,
sink_grid_region_id=1,
max_power=-1.0,
efficiency=1.0,
):
"""Init function.
Args:
name: String name of the object.
nameplate_unit_cost: (float) Cost to build a unit of
transmission capacity. ($ / Megawatt of capacity)
source_grid_region_id: An int specifying which grid_region
power gets power added.
sink_grid_region_id: An int specifying which grid_region
power gets power subtracted.
max_power: (float) Optional Maximum power which can be transmitted.
(Megawatt). Set < 0 if there is no limit.
efficiency: (float) ratio of how much power gets moved one
grid_region to the other grid_region. Acceptable values are
0. < efficiency < 1.
"""
super(_GridTransmission, self).__init__(
name,
nameplate_unit_cost=nameplate_unit_cost,
variable_unit_cost=0,
grid_region_id=source_grid_region_id,
max_power=max_power,
max_energy=-1,
co2_per_electrical_energy=0,
power_coefficient=efficiency,
)
self.sink_grid_region_id = sink_grid_region_id
self.solver = _GridSourceDispatchableSolver(self)
def configure_lp_variables_and_constraints(self, lp):
"""Declare lp variables, and set constraints.
Args:
lp: LinearProgramContainer, contains lp solver and constraints.
"""
super(_GridTransmission, self).configure_lp_variables_and_constraints(lp)
# Handle Constraints.
for t, var in enumerate(self.timeslice_variables):
sink_id = self.sink_grid_region_id
source_id = self.grid_region_id
# Whatever the super-class is sourcing in source_grid_region_id,
# sink it from sink_grid_region_id.
lp.conserve_power_constraint[sink_id][t].set_coefficient(var, -1.0)
if self.is_rps_source:
lp.rps_source_constraints[sink_id][t].set_coefficient(var, -1.0)
def post_process(self, lp):
"""Update lp post_processing result variables.
This is done so that sanity data checks can be done on RPS before
returning results.
Args:
lp: The LinearProgramContainer where the post processing variables reside.
"""
# Normal source post_process
super(_GridTransmission, self).post_process(lp)
# Sink post_process
sink_id = self.sink_grid_region_id
if lp.rps_percent > 0.0 and self.is_rps_source:
lp.rps_total[sink_id] -= self.get_solution_values()
else:
lp.non_rps_total[sink_id] -= self.get_solution_values()
class GridTransmission(object):
"""Transmits power bidirectionally between two grid_regions.
At interface level, transmitting from region-m to region-n is
identical to transmitting from region-n to region-m.
Attributes:
name: (str) name of the object.
nameplate_unit_cost: (float) Cost to build a unit of
transmission capacity. ($ / Megawatt of capacity)
grid_region_id_a: An int specifying one grid_region transmission
terminus
grid_region_id_b: An int specifying a different grid_region
transmission terminus
max_power: (float) Optional Maximum power which can be transmitted.
(Megawatt). Set < 0 if there is no limit.
efficiency: (float) ratio of how much power gets moved one
grid_region to the other grid_region. Acceptable values are
0. < efficiency < 1.
a_to_b: _GridTransmission object which moves dirty power from
grid_region_a to grid_region_b
b_to_a: _GridTransmission object which moves dirty power from
grid_region_b to grid_region_a
rec_a_to_b: _GridTransmission object which moves clean power
from grid_region_a to grid_region_b
rec_b_to_a: _GridTransmission object which moves clean power
from grid_region_b to grid_region_a
"""
def configure_lp_variables_and_constraints(self, lp):
"""Declare lp variables, and set constraints.
Args:
lp: LinearProgramContainer, contains lp solver and constraints.
"""
self.a_to_b = _GridTransmission(
self.name + " a_to_b",
0,
self.grid_region_id_b,
self.grid_region_id_a,
self.max_power,
self.efficiency,
)
self.b_to_a = _GridTransmission(
self.name + " b_to_a",
0,
self.grid_region_id_a,
self.grid_region_id_b,
self.max_power,
self.efficiency,
)
self.rec_a_to_b = _GridTransmission(
self.name + " rec a_to_b",
0,
self.grid_region_id_b,
self.grid_region_id_a,
self.max_power,
self.efficiency,
is_rps=True,
)
self.rec_b_to_a = _GridTransmission(
self.name + " rec b_to_a",
0,
self.grid_region_id_a,
self.grid_region_id_b,
self.max_power,
self.efficiency,
is_rps=True,
)
self.a_to_b.configure_lp_variables_and_constraints(lp)
self.b_to_a.configure_lp_variables_and_constraints(lp)
self.rec_a_to_b.configure_lp_variables_and_constraints(lp)
self.rec_b_to_a.configure_lp_variables_and_constraints(lp)
# Make sure nameplate >= sum(a_to_b) and nameplate >= sum(b_to_a)
self.nameplate_variable = lp.declare_nameplate_variable(
self.name, "%d_%d" % (self.grid_region_id_a, self.grid_region_id_b)
)
lp.minimize_costs_objective.set_coefficient(
self.nameplate_variable, self.nameplate_unit_cost
)
for t in lp.time_index_iterable:
# nameplate >= a_to_b[t] + rec_a_to_b[t] - b_to_a[t] - rec_b_to_a[t]
a_to_b_constraint = lp.constraint(0.0, lp.solver.infinity())
a_to_b_constraint.set_coefficient(self.nameplate_variable, 1.0)
a_to_b_constraint.set_coefficient(self.a_to_b.timeslice_variables[t], -1.0)
a_to_b_constraint.set_coefficient(
self.rec_a_to_b.timeslice_variables[t], -1.0
)
a_to_b_constraint.set_coefficient(self.b_to_a.timeslice_variables[t], 1.0)
a_to_b_constraint.set_coefficient(
self.rec_b_to_a.timeslice_variables[t], 1.0
)
# nameplate >= b_to_a[t] + rec_b_to_a[t] - a_to_b[t] - rec_a_to_b[t]
b_to_a_constraint = lp.constraint(0.0, lp.solver.infinity())
b_to_a_constraint.set_coefficient(self.nameplate_variable, 1.0)
b_to_a_constraint.set_coefficient(self.b_to_a.timeslice_variables[t], -1.0)
b_to_a_constraint.set_coefficient(
self.rec_b_to_a.timeslice_variables[t], -1.0
)
b_to_a_constraint.set_coefficient(self.a_to_b.timeslice_variables[t], 1.0)
b_to_a_constraint.set_coefficient(
self.rec_a_to_b.timeslice_variables[t], 1.0
)
def post_process(self, lp):
"""Update lp post_processing result variables.
This is done so that sanity data checks can be done on RPS before
returning results.
Args:
lp: The LinearProgramContainer where the post processing variables reside.
"""
self.a_to_b.post_process(lp)
self.b_to_a.post_process(lp)
self.rec_a_to_b.post_process(lp)
self.rec_b_to_a.post_process(lp)
def get_nameplate_solution_value(self):
"""Gets the linear program solver results for nameplate.
Must be called after lp.solve() to ensure solver has properly
converged and has generated results.
Raises:
RuntimeError: If called before LinearProgramContainer.solve().
Returns:
Float value representing solved nameplate value.
"""
nameplate_variable = self.nameplate_variable
if nameplate_variable is None:
raise RuntimeError("Get_nameplate_solution_value called before solve().")
return nameplate_variable.solution_value()
class LinearProgramContainer(object):
"""Instantiates and interfaces to LP Solver.
Example Usage:
Initialize: lp = LinearProgramContainer()
Add objects:
lp.add_demands(<GridDemand>)
lp.add_sources(<GridSource>)
lp.add_transmissions(<GridTransmission>)
lp.solve()
Attributes:
carbon_tax: The amount to tax 1 unit of co2 emissions.
cost_of_money: The amount to multiply variable costs by to
make yearly costs and fixed costs comparable.
profiles: time-series profiles indexed by name which map to
GridDemands and GridNonDispatchableSources.
number_of_timeslices: int representing one timeslice per profile index.
time_index_iterable: A simple int range from 0 - number_of_timeslices.
Constraints:
conserve_power_constraint: Dict keyed by grid_region_id. Value
is a list of LP Constraints which ensures that power > demand
at all times in all grid_regions.
minimize_costs_objective: The LP Objective which is to minimize costs.
rps_source_constraints: Dict keyed by grid_region_id. Value is a
list of LP Constraints which ensures that
rps_credit[grid_region, t] <= sum(rps_sources[grid_region, t])
rps_demand_constraints: Dict keyed by grid_region_id. Value is
a list of LP Constraints which ensures that
rps_credit[grid_region, t] <= demand[grid_region, t]
RPS Variables:
rps_credit_variables: Dict object keyed by grid_region_id. Value is a
list of rps_credit[grid_region, t] variables for calculating rps.
Post Processing Variables. Computed after LP converges:
rps_total: Dict object keyed by grid_region_id. Value is sum
(GridSource_power[grid_region, t]) of all rps sources.
non_rps_total: Dict object keyed by grid_region_id. Value is sum
(GridSource_power[grid_region, t]) of all non_rps sources.
adjusted_demand: Dict object keyed by grid_region_id. Value is
Demand[grid_region, t]
rps_credit_values: Dict object keyed by grid_region_id. Value is
rps_credit.value[grid_region, t]
Grid Elements:
demands: A list of GridDemand(s).
sources: A list of GridSource(s).
storage: A list of GridStorage(s).
transmission: A list of GridTransmission(s).
solver: The wrapped pywraplp.Solver.
solver_precision: A float representing estimated precision of the solver.
"""
def __init__(self, profiles):
"""Initializes LP Container.
Args:
profiles: Time-series pandas dataframe profiles indexed by name
which map to GridDemands and GridNonDispatchableSources.
Raises:
ValueError: If any value in profiles is < 0 or Nan / None.
"""
self.carbon_tax = 0.0
self.cost_of_money = 1.0
self.rps_percent = 0.0
self.profiles = profiles
# Constraints
self.conserve_power_constraint = {}
self.minimize_costs_objective = None
# RPS Constraints
self.rps_source_constraints = {}
self.rps_demand_constraints = {}
# RPS Variables
self.rps_credit_variables = {}
# Post Processing Variables
self.rps_total = {}
self.non_rps_total = {}
self.adjusted_demand = {}
self.total_demand = 0
self.rps_demand = 0
self.rps_credit_values = {}
self.demands = []
self.sources = []
self.storage = []
self.transmission = []
self.solver = None
self.solver_precision = 1e-3
# Validate profiles
if profiles is None:
raise ValueError("No profiles specified.")
if profiles.empty:
raise ValueError("No Data in Profiles.")
if profiles.isnull().values.any():
raise ValueError("Profiles may not be Null or None")
profiles_lt_0 = profiles.values < 0
if profiles_lt_0.any():
raise ValueError("Profiles must not be < 0.")
self.number_of_timeslices = len(profiles)
self.time_index_iterable = range(self.number_of_timeslices)
def add_demands(self, *demands):
"""Add all GridDemands in Args to self.demands."""
for d in demands:
self.demands.append(d)
def add_dispatchable_sources(self, *sources):
"""Verify source has no profile associated with it and add to self.sources.
Args:
*sources: arbitrary number of GridSources.
Raises:
KeyError: if Source has a profile associated with it which would
indicate the source was non-dispatchable instead of
dispatchable.
"""
for source in sources:
if source.name in self.profiles:
raise KeyError(
"Dispatchable Source %s has a profile associated with it"
% (source.name)
)
source.solver = _GridSourceDispatchableSolver(source)
self.sources.append(source)
def add_nondispatchable_sources(self, *sources):
"""Verify source has a profile associated with it and add to self.sources.
Args:
*sources: arbitrary number of GridSources.
Raises:
KeyError: if Source has no profile associated with it which would
indicate the source was dispatchable instead of
non-dispatchable.
"""
for source in sources:
if source.name not in self.profiles:
known_sources = ",".join(sorted(self.profiles.columns))
known_source_string = "Known sources are (%s)." % known_sources
raise KeyError(
"Nondispatchable Source %s has no profile. %s"
% (source.name, known_source_string)
)
source.solver = _GridSourceNonDispatchableSolver(
source, self.profiles[source.name]
)
self.sources.append(source)
def add_storage(self, *storage):
"""Add storage to lp."""
self.storage.extend(storage)
def add_transmissions(self, *transmission):
"""Add transmission to lp."""
self.transmission.extend(transmission)
def constraint(self, lower, upper, name=None, debug=False):
"""Build a new Constraint which with valid range between lower and upper."""
return Constraint(self, lower, upper, name, debug)
def _initialize_solver(self):
"""Initializes solver, declares objective and set constraints.
Solver is pywraplp.solver.
Objective is to minimize costs subject to constraints.
One constraint declared here is to ensure that
power[grid_region][t] > demand[grid_region][t] for all t and
grid_regions.
Also configures GridElements.
"""
self.solver = pywraplp.Solver(
"SolveEnergy", pywraplp.Solver.CLP_LINEAR_PROGRAMMING
)
self.minimize_costs_objective = Objective(self, minimize=True)
# Initialize GridDemands and GridSources
demand_sum = 0.0
for d in self.demands:
try:
profiles = self.profiles[d.name]
self.adjusted_demand[d.grid_region_id] = np.array(profiles.values)
except KeyError:
profile_names = str(self.profiles.keys())
error_string = (
"GridDemand %s. No profile found! Known profiles:(%s)"
% (d.name, profile_names)
)
raise KeyError(error_string)
self.conserve_power_constraint[d.grid_region_id] = [
self.constraint(
p,
self.solver.infinity(),
"Conserve Power gid:%d t:%d" % (d.grid_region_id, t),
)
for t, p in enumerate(profiles)
]
demand_sum += sum(profiles)
# Handle RPS which is tricky. It requires special credit
# variables[grid_region][time] and 3 constraints.
#
# Constraint #1:
# The overall goal is to have RPS exceed rps_percent of total
# demand. Given that:
# total_rps_credit := sum(rps_credit[g][t])
# total_demand := sum(demand[g][t])
#
# The constraint named total_rps_credit_gt_rps_percent_constraint
# is:
# total_rps_credit >= (self.rps_percent / 100) * total_demand
#
# Constraint #2:
# rps_credit[g][t] cannot exceed sum of rps_sources - sum of
# rps_sinks at each g,t. An example of rps_sink is the 'REC_STORAGE'
# part of GridRecStorage which stores rps energy off the grid only
# to put it back on the grid later as a rps_source. This is
# reflected in the constraint named
# rps_source_constraints[g][t]:
# rps_credit[g][t] <= sum(rps_sources[g][t]) - sum(rps_sinks[g][t])
#
# Constraint #3
# rps_credit[g][t] cannot exceed what can be used at each g,t. if
# rps_sources generate a Gigawatt at g,t = 0,0 and only 1MW can be
# used at g,t then we don't want to credit the unused 999 MW.
#
# The constraint named rps_demand_constraints is:
# rps_credit[g][t] <= demand[g][t]
#
self.total_demand = demand_sum
self.rps_demand = demand_sum * self.rps_percent / 100.0
solver = self.solver
total_rps_credit_gt_rps_percent_constraint = self.constraint(
self.rps_demand, solver.infinity()
)
for d in self.demands:
profiles = self.profiles[d.name]
if self.rps_percent > 0.0:
rps_credit_variables = self.declare_timeslice_variables(
"__rps_credit__", d.grid_region_id
)
else:
rps_credit_variables = [
solver.NumVar(
0.0, 0.0, "__bogus rps_credit__ %d %d" % (d.grid_region_id, t)
)
for t in self.time_index_iterable
]
rps_demand_constraints = []
rps_source_constraints = [
self.constraint(0.0, solver.infinity())
for t in self.time_index_iterable
]
self.rps_source_constraints[d.grid_region_id] = rps_source_constraints
self.rps_credit_variables[d.grid_region_id] = rps_credit_variables
for t in self.time_index_iterable:
# Sum(rps_credit[grid_region, t]) >= rps_percent * total demand.
total_rps_credit_gt_rps_percent_constraint.set_coefficient(
rps_credit_variables[t], 1.0
)
# Rps_credit[grid_region, t] <= demand[grid_region, t].
rps_credit_less_than_demand = self.constraint(
-solver.infinity(), profiles[t]
)
rps_credit_less_than_demand.set_coefficient(
rps_credit_variables[t], 1.0
)
rps_demand_constraints.append(rps_credit_less_than_demand)
# Rps_credit[grid_region, t] <= (sum(rps_sources[grid_region, t])
# Constraint also gets adjusted by _GridSource(Non)DispatchableSolver.
# configure_lp_variables_and_constraints
rps_source_constraints[t].set_coefficient(rps_credit_variables[t], -1.0)
self.rps_demand_constraints[d.grid_region_id] = rps_demand_constraints
# Configure sources and storage.
for s in self.sources + self.storage + self.transmission:
s.configure_lp_variables_and_constraints(self)
def solve(self):
"""Initializes and runs linear program.
This is the main routine to call after __init__.
Returns:
True if linear program gave an optimal result. False otherwise.
"""
self._initialize_solver()
status = self.solver.Solve()
converged = status == self.solver.OPTIMAL
if converged:
self._post_process()
return converged
def _post_process(self):
"""Generates data used for calculating consumed rps/non-rps values.
Also double-checks results to make sure they match constraints.
Raises:
RuntimeError: If double-checked results do not match constraints.
"""
# Initialize post_processing totals.
for d in self.demands:
# Total amount of rps_sources[g][t] power.
self.rps_total[d.grid_region_id] = np.zeros(self.number_of_timeslices)
# Total amount of non-rps_sources[g][t] power.
self.non_rps_total[d.grid_region_id] = np.zeros(self.number_of_timeslices)
for s in self.sources + self.storage + self.transmission:
s.post_process(self)
# Sanity error check results against constraints. If any of these
# get raised, it indicates a bug in the code.
solver_precision = self.solver_precision
sum_rps_credits = 0.0
for g_id in [d.grid_region_id for d in self.demands]:
power_deficit = self.adjusted_demand[g_id] - (
self.rps_total[g_id] + self.non_rps_total[g_id]
)
lights_kept_on = (power_deficit < solver_precision).all()
rps_credits = np.array(
[rcv.solution_value() for rcv in self.rps_credit_variables[g_id]]
)
sum_rps_credits += sum(rps_credits)
self.rps_credit_values[g_id] = rps_credits
rps_credit_gt_demand = (
rps_credits > self.adjusted_demand[g_id] + solver_precision
).all()
rps_credit_gt_rps_sources = (
rps_credits > self.rps_total[g_id] + solver_precision
).all()
storage_exceeds_demand = (
self.adjusted_demand[g_id] < -solver_precision
).all()
if not lights_kept_on:
raise DemandNotSatisfiedError(
"Demand not satisfied by %f for region %d"
% (max(power_deficit), g_id)
)
if rps_credit_gt_demand:
raise RpsExceedsDemandError(
"RPS Credits Exceed Demand for region %d" % g_id
)
if rps_credit_gt_rps_sources:
raise RpsCreditExceedsSourcesError(
"RPS Credits Exceed RPS Sources for region %d" % g_id
)
if storage_exceeds_demand:
raise StorageExceedsDemandError(
"Storage Exceeds Demand for region %d" % g_id
)
# Scale solver_precision by number of timeslices to get precision
# for a summed comparison.
sum_solver_precision = solver_precision * self.number_of_timeslices
if sum_solver_precision + sum_rps_credits < self.rps_demand:
raise RpsPercentNotMetError(
"Sum RPS credits (%f) < demand * (%f rps_percent) (%f)"
% (sum_rps_credits, float(self.rps_percent), self.rps_demand)
)
def declare_timeslice_variables(self, name, grid_region_id):
"""Declares timeslice variables for a grid_region.
Args:
name: String to be included in the generated variable name.
grid_region_id: Int which identifies which grid these variables affect.
Do Not call this function with the same (name, grid_region_id)
pair more than once. There may not be identically named variables
in the same grid_region.
Returns:
Array of lp variables, each which range from 0 to infinity.
Array is mapped so that variable for time-slice x is at index x.
e.g. variable for first time-slice is variable[0]. variable for
last time-slice is variable[-1]
"""
solver = self.solver
variables = []
for t in self.time_index_iterable:
var_name = "__".join(
[name, "grid_region_id", str(grid_region_id), "at_t", str(t)]
)
variables.append(solver.NumVar(0.0, solver.infinity(), var_name))
return variables
def declare_nameplate_variable(self, name, grid_region_id):
"""Declares a nameplate variable for a grid_region.
Args:
name: String to be included in the generated variable name.
grid_region_id: Stringifyable object which identifies which grid
these variables affect.
Do Not call this function with the same (name, grid_region_id)
pair more than once. There may not be identically named variables
in the same grid_region.
Returns:
A lp variable which values range from 0 to infinity.
"""
nameplate_name = "__".join(
[name, "grid_region_id", str(grid_region_id), "peak"]
)
solver = self.solver
return solver.NumVar(0.0, solver.infinity(), nameplate_name)
def extrapolate_cost(cost, discount_rate, time_span_1, time_span_2):
"""Extrapolate cost from one time span to another.
Args:
cost: cost incurred during time_span_1 (in units of currency)
discount_rate: rate that money decays, per year (as decimal, e.g., .06)
time_span_1: time span when cost incurred (in units of years)
time_span_2: time span to extrapolate cost (in units of years)
Returns:
Cost extrapolated to time_span_2, units of currency.
Model parameters are costs over time spans. For example, the demand
may be a time series that lasts 1 year. The variable cost to fulfill
that demand would then be for 1 year of operation. However, the
GridModel is supposed to compute the total cost over a longer time
span (e.g., 30 years).
If there were no time value of money, the extrapolated cost would be
the ratio of time_span_2 to time_span_1 (e.g., 30 in the
example). However, payments in the future are less costly than
payments in the present. We extrapolate the cost by first finding
the equivalent continuous stream of payments over time_span_1 that
is equivalent to the cost, then assume that stream of payments
occurs over time_span_2, instead.
"""
growth_rate = 1.0 + discount_rate
value_decay_1 = pow(growth_rate, -time_span_2)
value_decay_2 = pow(growth_rate, -time_span_1)
try:
return cost * (1.0 - value_decay_1) / (1.0 - value_decay_2)
except ZeroDivisionError:
return cost
| [
2,
15069,
2177,
3012,
3457,
13,
198,
2,
198,
2,
49962,
739,
262,
24843,
13789,
11,
10628,
362,
13,
15,
357,
1169,
366,
34156,
15341,
198,
2,
345,
743,
407,
779,
428,
2393,
2845,
287,
11846,
351,
262,
13789,
13,
198,
2,
921,
743,
7330,
257,
4866,
286,
262,
13789,
379,
198,
2,
198,
2,
220,
220,
220,
220,
2638,
1378,
2503,
13,
43073,
13,
2398,
14,
677,
4541,
14,
43,
2149,
24290,
12,
17,
13,
15,
198,
2,
198,
2,
17486,
2672,
416,
9723,
1099,
393,
4987,
284,
287,
3597,
11,
3788,
198,
2,
9387,
739,
262,
13789,
318,
9387,
319,
281,
366,
1921,
3180,
1,
29809,
1797,
11,
198,
2,
42881,
34764,
11015,
6375,
7102,
49828,
11053,
3963,
15529,
509,
12115,
11,
2035,
4911,
393,
17142,
13,
198,
2,
4091,
262,
13789,
329,
262,
2176,
3303,
15030,
21627,
290,
198,
2,
11247,
739,
262,
13789,
13,
198,
198,
37811,
8890,
5039,
1575,
12,
8738,
4402,
12278,
10706,
5103,
739,
1180,
4788,
13,
198,
198,
10669,
4909,
24846,
36,
3639,
25,
4333,
26406,
11,
1897,
1746,
290,
20514,
13,
220,
24846,
198,
36,
3639,
389,
4624,
287,
1180,
10706,
7652,
13,
220,
24846,
7652,
389,
198,
25512,
515,
422,
1123,
584,
523,
691,
4237,
351,
10706,
62,
36996,
62,
312,
6624,
2124,
460,
198,
6477,
1897,
1746,
351,
10706,
62,
36996,
62,
312,
6624,
2124,
198,
198,
464,
3484,
286,
30580,
24846,
36,
3639,
389,
1912,
2402,
25,
198,
220,
1438,
6816,
62,
20850,
62,
15805,
25,
383,
1575,
284,
1382,
530,
4326,
357,
68,
13,
70,
13,
8336,
707,
1078,
8,
286,
1176,
13,
198,
220,
7885,
62,
20850,
62,
15805,
25,
383,
1575,
284,
2148,
530,
4326,
286,
1176,
625,
640,
13,
198,
220,
220,
220,
357,
68,
13,
70,
13,
8336,
707,
1078,
12,
43223,
8,
198,
198,
464,
2438,
985,
15968,
262,
10706,
625,
3294,
640,
12,
82,
677,
274,
13,
220,
304,
13,
70,
13,
220,
19123,
306,
198,
2502,
257,
530,
614,
2278,
543,
561,
3975,
284,
1987,
1635,
21268,
796,
10083,
1899,
640,
12,
82,
677,
274,
13,
198,
198,
464,
2438,
318,
1912,
2402,
257,
14174,
12,
23065,
543,
4909,
25,
628,
220,
532,
1052,
9432,
543,
318,
284,
17775,
3484,
13,
198,
220,
532,
1482,
2536,
6003,
543,
1276,
307,
1138,
878,
262,
4610,
460,
47873,
13,
198,
220,
220,
220,
532,
45075,
62,
6477,
62,
1102,
2536,
2913,
25,
48987,
326,
2160,
7,
6477,
58,
83,
12962,
18189,
198,
220,
220,
220,
220,
220,
3512,
58,
83,
60,
329,
477,
256,
287,
1123,
10706,
12,
36996,
198,
198,
1212,
2438,
481,
670,
351,
597,
900,
286,
6414,
4991,
13,
220,
1114,
262,
198,
14225,
4832,
286,
10314,
11,
262,
4991,
7147,
389,
25,
628,
220,
4333,
25,
8336,
46684,
198,
220,
3862,
25,
19347,
198,
220,
357,
28532,
1572,
8,
6682,
796,
4333,
1635,
3862,
5218,
8336,
707,
1078,
12,
39792,
198,
220,
6446,
25,
45792,
45491,
198,
220,
7375,
17,
2295,
7717,
25,
16859,
2516,
628,
220,
357,
28532,
1572,
8,
7375,
17,
2295,
2175,
583,
6682,
5218,
16859,
2516,
1220,
8336,
707,
1078,
12,
39792,
198,
220,
23699,
9241,
25,
720,
1220,
16859,
2516,
198,
198,
37811,
198,
198,
11748,
18931,
198,
11748,
299,
32152,
355,
45941,
198,
198,
6738,
393,
31391,
13,
29127,
62,
82,
14375,
1330,
12972,
29988,
489,
79,
628,
628,
628,
628,
198,
4871,
1482,
2536,
2913,
7,
15252,
2599,
198,
220,
220,
220,
37227,
39,
10119,
281,
18470,
1482,
2536,
2913,
2134,
351,
3131,
28769,
1321,
13,
628,
220,
220,
220,
49213,
25,
198,
220,
220,
220,
220,
220,
220,
32315,
25,
10238,
12972,
29988,
489,
79,
13,
3103,
2536,
2913,
2134,
198,
220,
220,
220,
220,
220,
220,
1438,
25,
1438,
286,
32315,
198,
220,
220,
220,
220,
220,
220,
10451,
25,
20267,
540,
326,
8739,
3891,
286,
9633,
284,
44036,
628,
220,
220,
220,
12972,
29988,
489,
79,
13,
3103,
2536,
2913,
1595,
470,
4417,
257,
1351,
286,
9633,
14,
1073,
41945,
11,
523,
198,
220,
220,
220,
356,
423,
284,
1394,
2610,
6731,
13,
198,
220,
220,
220,
37227,
628,
220,
220,
220,
825,
11593,
15003,
834,
7,
944,
11,
300,
79,
11,
2793,
62,
7784,
11,
6727,
62,
7784,
11,
1438,
28,
14202,
11,
14257,
28,
25101,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
24243,
4340,
1482,
2536,
2913,
13,
628,
220,
220,
220,
220,
220,
220,
220,
943,
14542,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
300,
79,
25,
44800,
15167,
29869,
326,
27521,
262,
18470,
1540,
332,
543,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
8075,
262,
32315,
13,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2793,
62,
7784,
25,
357,
22468,
8,
16048,
5421,
319,
1720,
1022,
763,
14822,
82,
290,
9633,
13,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
6727,
62,
7784,
25,
357,
22468,
8,
20390,
5421,
319,
1720,
1022,
763,
14822,
82,
290,
9633,
13,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1438,
25,
32233,
1692,
31744,
4731,
13,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
14257,
25,
41146,
543,
611,
900,
11,
17259,
32315,
7508,
13,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
628,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
1102,
2536,
2913,
796,
300,
79,
13,
82,
14375,
13,
3103,
2536,
2913,
7,
21037,
62,
7784,
11,
6727,
62,
7784,
8,
198,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
3672,
796,
1438,
198,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
687,
4712,
796,
23884,
198,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
24442,
796,
14257,
628,
220,
220,
220,
220,
220,
220,
220,
611,
2116,
13,
24442,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
18931,
13,
24442,
7203,
10943,
2257,
3861,
12394,
25,
4064,
69,
19841,
4064,
82,
19841,
4064,
69,
1600,
2793,
62,
7784,
11,
1438,
11,
6727,
62,
7784,
8,
628,
220,
220,
220,
825,
900,
62,
1073,
16814,
7,
944,
11,
7885,
11,
35381,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
46245,
7885,
1635,
35381,
284,
18470,
1766,
16814,
13,
628,
220,
220,
220,
220,
220,
220,
220,
27323,
862,
12972,
37150,
13,
7248,
34,
2577,
5632,
7,
45286,
11,
35381,
8,
2446,
290,
198,
220,
220,
220,
220,
220,
220,
220,
16031,
7885,
11,
35381,
284,
10451,
8633,
13,
628,
220,
220,
220,
220,
220,
220,
220,
2293,
4585,
428,
2446,
11,
37092,
15853,
7885,
1635,
35381,
628,
220,
220,
220,
220,
220,
220,
220,
943,
14542,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
7885,
25,
357,
43,
79,
35748,
8,
383,
35748,
15082,
291,
392,
13,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
35381,
25,
357,
22468,
8,
383,
35381,
15082,
291,
392,
13,
628,
220,
220,
220,
220,
220,
220,
220,
37227,
628,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
1102,
2536,
2913,
13,
7248,
34,
2577,
5632,
7,
45286,
11,
35381,
8,
198,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
687,
4712,
58,
45286,
13,
3672,
3419,
60,
796,
35381,
628,
220,
220,
220,
220,
220,
220,
220,
611,
2116,
13,
24442,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
18931,
13,
24442,
7203,
4,
82,
15853,
4064,
82,
1635,
4064,
69,
1600,
2116,
13,
3672,
11,
7885,
13,
3672,
22784,
35381,
8,
628,
198,
4871,
37092,
7,
15252,
2599,
198,
220,
220,
220,
37227,
39,
10119,
281,
18470,
37092,
2134,
351,
3131,
28769,
1321,
13,
628,
220,
220,
220,
49213,
25,
198,
220,
220,
220,
220,
220,
9432,
25,
4698,
3157,
12972,
29988,
489,
79,
13,
10267,
425,
2134,
13,
198,
220,
220,
220,
37227,
628,
220,
220,
220,
825,
11593,
15003,
834,
7,
944,
11,
300,
79,
11,
17775,
28,
17821,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
24243,
4340,
37092,
13,
628,
220,
220,
220,
220,
220,
220,
220,
943,
14542,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
300,
79,
25,
44800,
15167,
29869,
326,
27521,
262,
18470,
1540,
332,
543,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
8075,
262,
37092,
13,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
17775,
25,
25131,
11,
6407,
611,
9432,
815,
307,
49491,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
4306,
9432,
318,
12991,
528,
798,
13,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
15252,
425,
796,
300,
79,
13,
82,
14375,
13,
10267,
425,
3419,
198,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
687,
4712,
796,
23884,
198,
220,
220,
220,
220,
220,
220,
220,
611,
17775,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
15252,
425,
13,
7248,
9452,
320,
1634,
3419,
198,
220,
220,
220,
220,
220,
220,
220,
2073,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
15252,
425,
13,
7248,
11518,
320,
1634,
3419,
628,
220,
220,
220,
825,
900,
62,
1073,
16814,
7,
944,
11,
7885,
11,
35381,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
46245,
7885,
1635,
35381,
284,
18470,
37092,
13,
628,
220,
220,
220,
220,
220,
220,
220,
27323,
862,
12972,
37150,
13,
7248,
34,
2577,
5632,
7,
45286,
11,
35381,
8,
2446,
290,
198,
220,
220,
220,
220,
220,
220,
220,
16031,
7885,
11,
35381,
284,
10451,
8633,
13,
628,
220,
220,
220,
220,
220,
220,
220,
2293,
4585,
428,
2446,
11,
37092,
15853,
7885,
1635,
35381,
628,
220,
220,
220,
220,
220,
220,
220,
943,
14542,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
7885,
25,
357,
43,
79,
35748,
8,
383,
35748,
15082,
291,
392,
13,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
35381,
25,
357,
22468,
8,
383,
35381,
15082,
291,
392,
13,
628,
220,
220,
220,
220,
220,
220,
220,
37227,
628,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
15252,
425,
13,
7248,
34,
2577,
5632,
7,
45286,
11,
35381,
8,
198,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
687,
4712,
58,
45286,
13,
3672,
3419,
60,
796,
35381,
628,
198,
4871,
24846,
42782,
7,
15252,
2599,
198,
220,
220,
220,
37227,
26437,
1295,
12,
13829,
2134,
543,
6870,
3440,
319,
262,
10706,
526,
15931,
628,
220,
220,
220,
825,
11593,
15003,
834,
7,
944,
11,
1438,
11,
10706,
62,
36996,
62,
312,
28,
15,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
24243,
4340,
24846,
42782,
2134,
13,
628,
220,
220,
220,
220,
220,
220,
220,
943,
14542,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1438,
25,
1438,
286,
262,
3512,
2134,
628,
220,
220,
220,
220,
220,
220,
220,
220,
220,
10706,
62,
36996,
62,
312,
25,
1052,
493,
31577,
262,
10706,
3814,
286,
262,
3512,
13,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
5514,
4237,
351,
262,
976,
10706,
62,
36996,
62,
312,
460,
1176,
428,
3512,
13,
628,
220,
220,
220,
220,
220,
220,
220,
37227,
628,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
3672,
796,
1438,
198,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
25928,
62,
36996,
62,
312,
796,
10706,
62,
36996,
62,
312,
628,
198,
4871,
24846,
7416,
7,
15252,
2599,
198,
220,
220,
220,
37227,
21306,
6421,
36845,
11,
763,
17,
11,
3814,
11,
1176,
290,
2568,
11247,
286,
257,
1176,
2723,
13,
628,
220,
220,
220,
24846,
26406,
743,
2035,
307,
27965,
540,
393,
1729,
12,
6381,
17147,
540,
13,
198,
220,
220,
220,
220,
220,
532,
35934,
540,
4237,
743,
1176,
379,
597,
640,
11,
304,
13,
70,
13,
12584,
5252,
6134,
13,
198,
220,
220,
220,
220,
220,
532,
8504,
12,
6381,
17147,
540,
4237,
389,
10795,
319,
262,
2858,
284,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
7716,
1176,
13,
304,
13,
70,
13,
12347,
393,
3086,
6134,
13,
628,
220,
220,
220,
1002,
612,
318,
257,
640,
12,
48369,
1176,
7034,
41497,
416,
262,
976,
1438,
355,
198,
220,
220,
220,
428,
2723,
287,
44800,
15167,
29869,
13,
5577,
2915,
13,
220,
383,
2723,
318,
198,
220,
220,
220,
3177,
8504,
12,
6381,
17147,
540,
13,
220,
15323,
11,
340,
318,
3177,
27965,
540,
13,
628,
220,
220,
220,
49213,
25,
198,
220,
220,
220,
220,
220,
1438,
25,
357,
2536,
8,
1438,
286,
262,
2134,
13,
198,
220,
220,
220,
220,
220,
1438,
6816,
62,
20850,
62,
15805,
25,
357,
22468,
8,
6446,
284,
1382,
257,
4326,
286,
198,
220,
220,
220,
220,
220,
220,
220,
27965,
540,
1176,
13,
220,
7198,
1220,
8336,
707,
1078,
286,
5339,
8,
628,
220,
220,
220,
220,
220,
7885,
62,
20850,
62,
15805,
25,
357,
22468,
8,
6446,
284,
5127,
257,
4326,
286,
27965,
540,
1176,
198,
220,
220,
220,
220,
220,
220,
220,
583,
640,
13,
7198,
1220,
8336,
707,
1078,
12,
43223,
8,
628,
220,
220,
220,
220,
220,
10706,
62,
36996,
62,
312,
25,
1052,
493,
31577,
262,
10706,
3814,
286,
262,
2723,
13,
198,
220,
220,
220,
220,
220,
220,
220,
5514,
8665,
351,
262,
976,
10706,
62,
36996,
62,
312,
460,
14595,
262,
1176,
198,
220,
220,
220,
220,
220,
220,
220,
422,
428,
2723,
13,
628,
220,
220,
220,
220,
220,
3509,
62,
6477,
25,
357,
22468,
8,
32233,
22246,
1176,
543,
2134,
460,
5127,
13,
198,
220,
220,
220,
220,
220,
220,
220,
357,
42672,
707,
1078,
737,
5345,
1279,
657,
611,
612,
318,
645,
4179,
13,
628,
220,
220,
220,
220,
220,
3509,
62,
22554,
25,
357,
22468,
8,
32233,
5415,
2568,
543,
2134,
460,
198,
220,
220,
220,
220,
220,
220,
220,
5127,
13,
357,
42672,
707,
1078,
12,
39792,
8,
5345,
1279,
657,
611,
612,
318,
645,
4179,
13,
628,
220,
220,
220,
220,
220,
763,
17,
62,
525,
62,
9509,
8143,
62,
22554,
25,
357,
22468,
8,
357,
35416,
2516,
286,
7375,
17,
1220,
8336,
707,
1078,
19123,
737,
628,
220,
220,
220,
220,
220,
1176,
62,
1073,
16814,
25,
357,
22468,
8,
8064,
286,
703,
881,
1176,
318,
14275,
416,
198,
220,
220,
220,
220,
220,
220,
220,
2134,
3691,
13,
703,
881,
1176,
3011,
319,
262,
10706,
13,
220,
657,
1279,
198,
220,
220,
220,
220,
220,
220,
220,
1176,
62,
1073,
16814,
1279,
352,
13,
220,
21198,
3289,
352,
13,
15,
13,
628,
220,
220,
220,
220,
220,
318,
62,
81,
862,
62,
10459,
25,
41146,
543,
43397,
611,
262,
2723,
318,
3017,
198,
220,
220,
220,
220,
220,
220,
220,
287,
262,
29479,
540,
4347,
13652,
8997,
13,
628,
220,
220,
220,
220,
220,
1540,
332,
25,
15467,
257,
4808,
41339,
7416,
49354,
540,
50,
14375,
393,
198,
220,
220,
220,
220,
220,
220,
220,
4808,
41339,
7416,
15419,
49354,
540,
50,
14375,
13,
220,
16718,
284,
9058,
18470,
198,
220,
220,
220,
220,
220,
220,
220,
1482,
2536,
6003,
11,
9515,
1083,
290,
9633,
329,
262,
2723,
290,
284,
198,
220,
220,
220,
220,
220,
220,
220,
989,
2482,
13,
628,
220,
220,
220,
220,
220,
1661,
75,
501,
62,
25641,
2977,
25,
1052,
7177,
286,
18470,
9633,
11,
530,
583,
640,
12,
48369,
198,
220,
220,
220,
220,
220,
220,
220,
286,
18640,
13,
220,
15690,
318,
27661,
523,
326,
7885,
329,
198,
220,
220,
220,
220,
220,
220,
220,
640,
12,
48369,
256,
318,
379,
6376,
256,
13,
198,
220,
220,
220,
220,
220,
220,
220,
304,
13,
70,
13,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
35748,
329,
717,
640,
12,
48369,
318,
1661,
75,
501,
62,
45286,
58,
15,
4083,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
35748,
329,
938,
640,
12,
48369,
318,
1661,
75,
501,
62,
45286,
58,
12,
16,
4083,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
35748,
329,
640,
12,
48369,
379,
640,
256,
318,
1661,
75,
501,
62,
45286,
58,
83,
4083,
198,
220,
220,
220,
220,
220,
220,
220,
5514,
3011,
6875,
611,
24846,
7416,
318,
257,
35934,
540,
7416,
13,
628,
220,
220,
220,
220,
220,
1438,
6816,
62,
45286,
25,
18470,
7885,
10200,
262,
1438,
6816,
393,
198,
220,
220,
220,
220,
220,
220,
220,
5415,
1176,
262,
24846,
7416,
460,
5072,
379,
597,
1813,
198,
220,
220,
220,
220,
220,
220,
220,
640,
13,
628,
220,
220,
220,
37227,
628,
220,
220,
220,
825,
11593,
15003,
834,
7,
198,
220,
220,
220,
220,
220,
220,
220,
2116,
11,
198,
220,
220,
220,
220,
220,
220,
220,
1438,
11,
198,
220,
220,
220,
220,
220,
220,
220,
1438,
6816,
62,
20850,
62,
15805,
11,
198,
220,
220,
220,
220,
220,
220,
220,
7885,
62,
20850,
62,
15805,
11,
198,
220,
220,
220,
220,
220,
220,
220,
10706,
62,
36996,
62,
312,
28,
15,
11,
198,
220,
220,
220,
220,
220,
220,
220,
3509,
62,
6477,
10779,
16,
13,
15,
11,
198,
220,
220,
220,
220,
220,
220,
220,
3509,
62,
22554,
10779,
16,
13,
15,
11,
198,
220,
220,
220,
220,
220,
220,
220,
763,
17,
62,
525,
62,
9509,
8143,
62,
22554,
28,
15,
11,
198,
220,
220,
220,
220,
220,
220,
220,
1176,
62,
1073,
16814,
28,
16,
13,
15,
11,
198,
220,
220,
220,
220,
220,
220,
220,
318,
62,
81,
862,
62,
10459,
28,
25101,
11,
198,
220,
220,
220,
15179,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
50,
1039,
9695,
286,
257,
24846,
7416,
2134,
13,
628,
220,
220,
220,
220,
220,
220,
220,
943,
14542,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1438,
25,
357,
2536,
8,
1438,
286,
262,
2134,
13,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1438,
6816,
62,
20850,
62,
15805,
25,
357,
22468,
8,
6446,
284,
1382,
257,
4326,
286,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
27965,
540,
1176,
13,
220,
7198,
1220,
8336,
707,
1078,
286,
5339,
8,
628,
220,
220,
220,
220,
220,
220,
220,
220,
220,
7885,
62,
20850,
62,
15805,
25,
357,
22468,
8,
6446,
284,
5127,
257,
4326,
286,
27965,
540,
1176,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
583,
640,
13,
7198,
1220,
8336,
707,
1078,
12,
43223,
8,
628,
220,
220,
220,
220,
220,
220,
220,
220,
220,
10706,
62,
36996,
62,
312,
25,
1052,
493,
31577,
262,
10706,
3814,
286,
262,
3512,
13,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
5514,
8665,
351,
262,
976,
10706,
62,
36996,
62,
312,
460,
14595,
262,
1176,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
422,
428,
2723,
13,
628,
220,
220,
220,
220,
220,
220,
220,
220,
220,
3509,
62,
6477,
25,
357,
22468,
8,
22246,
1176,
543,
2134,
460,
5127,
13,
357,
42672,
707,
1078,
8,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
3509,
62,
22554,
25,
357,
22468,
8,
22246,
2568,
543,
2134,
460,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
5127,
13,
357,
42672,
707,
1078,
12,
39792,
8,
628,
220,
220,
220,
220,
220,
220,
220,
220,
220,
763,
17,
62,
525,
62,
9509,
8143,
62,
22554,
25,
357,
22468,
8,
357,
35416,
2516,
286,
7375,
17,
1220,
8336,
707,
1078,
19123,
737,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1176,
62,
1073,
16814,
25,
357,
22468,
8,
8064,
286,
703,
881,
1176,
318,
14275,
416,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2134,
3691,
13,
703,
881,
1176,
3011,
319,
262,
10706,
13,
220,
657,
1279,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1176,
62,
1073,
16814,
1279,
352,
13,
220,
21198,
3289,
352,
13,
15,
13,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
318,
62,
81,
862,
62,
10459,
25,
41146,
543,
43397,
611,
262,
2723,
318,
3017,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
287,
262,
29479,
540,
4347,
13652,
8997,
13,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
628,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
3672,
796,
1438,
198,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
3672,
6816,
62,
20850,
62,
15805,
796,
1438,
6816,
62,
20850,
62,
15805,
198,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
45286,
62,
20850,
62,
15805,
796,
7885,
62,
20850,
62,
15805,
198,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
9806,
62,
22554,
796,
3509,
62,
22554,
198,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
9806,
62,
6477,
796,
3509,
62,
6477,
198,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
25928,
62,
36996,
62,
312,
796,
10706,
62,
36996,
62,
312,
198,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
1073,
17,
62,
525,
62,
9509,
8143,
62,
22554,
796,
763,
17,
62,
525,
62,
9509,
8143,
62,
22554,
198,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
6477,
62,
1073,
16814,
796,
1176,
62,
1073,
16814,
198,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
271,
62,
81,
862,
62,
10459,
796,
318,
62,
81,
862,
62,
10459,
628,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
82,
14375,
796,
6045,
628,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
22355,
75,
501,
62,
25641,
2977,
796,
6045,
198,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
3672,
6816,
62,
45286,
796,
6045,
628,
220,
220,
220,
825,
17425,
62,
34431,
62,
25641,
2977,
62,
392,
62,
1102,
2536,
6003,
7,
944,
11,
300,
79,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
37835,
533,
300,
79,
9633,
11,
290,
900,
17778,
13,
628,
220,
220,
220,
220,
220,
220,
220,
943,
14542,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
300,
79,
25,
383,
44800,
15167,
29869,
13,
628,
220,
220,
220,
220,
220,
220,
220,
2896,
364,
284,
2116,
13,
82,
14375,
543,
6105,
4566,
942,
9633,
290,
198,
220,
220,
220,
220,
220,
220,
220,
17778,
287,
428,
2134,
13,
628,
220,
220,
220,
220,
220,
220,
220,
4091,
4418,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
4808,
41339,
7416,
49354,
540,
50,
14375,
11,
4808,
41339,
7416,
15419,
49354,
540,
50,
14375,
628,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
82,
14375,
13,
11250,
495,
62,
34431,
62,
25641,
2977,
62,
392,
62,
1102,
2536,
6003,
7,
34431,
8,
628,
220,
220,
220,
825,
1281,
62,
14681,
7,
944,
11,
300,
79,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
10260,
300,
79,
1281,
62,
36948,
1255,
9633,
13,
628,
220,
220,
220,
220,
220,
220,
220,
770,
318,
1760,
1281,
300,
79,
13,
82,
6442,
3419,
523,
326,
34182,
1366,
8794,
460,
307,
1760,
198,
220,
220,
220,
220,
220,
220,
220,
319,
371,
3705,
878,
8024,
2482,
13,
628,
220,
220,
220,
220,
220,
220,
220,
943,
14542,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
300,
79,
25,
383,
44800,
15167,
29869,
810,
262,
1281,
7587,
9633,
26412,
13,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
628,
220,
220,
220,
220,
220,
220,
220,
611,
300,
79,
13,
81,
862,
62,
25067,
1875,
657,
13,
15,
290,
2116,
13,
271,
62,
81,
862,
62,
10459,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
300,
79,
13,
81,
862,
62,
23350,
58,
944,
13,
25928,
62,
36996,
62,
312,
60,
15853,
2116,
13,
1136,
62,
82,
2122,
62,
27160,
3419,
198,
220,
220,
220,
220,
220,
220,
220,
2073,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
300,
79,
13,
13159,
62,
81,
862,
62,
23350,
58,
944,
13,
25928,
62,
36996,
62,
312,
60,
15853,
2116,
13,
1136,
62,
82,
2122,
62,
27160,
3419,
628,
220,
220,
220,
825,
651,
62,
82,
2122,
62,
27160,
7,
944,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
38,
1039,
262,
14174,
1430,
1540,
332,
2482,
13,
628,
220,
220,
220,
220,
220,
220,
220,
12039,
307,
1444,
706,
300,
79,
13,
82,
6442,
3419,
284,
4155,
1540,
332,
468,
6105,
198,
220,
220,
220,
220,
220,
220,
220,
6718,
2004,
290,
468,
7560,
2482,
13,
628,
220,
220,
220,
220,
220,
220,
220,
16409,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
45941,
13,
18747,
286,
8136,
329,
1123,
1661,
75,
501,
7885,
13,
628,
220,
220,
220,
220,
220,
220,
220,
37227,
628,
220,
220,
220,
220,
220,
220,
220,
1441,
2116,
13,
82,
14375,
13,
1136,
62,
82,
2122,
62,
27160,
3419,
628,
220,
220,
220,
825,
651,
62,
3672,
6816,
62,
82,
2122,
62,
8367,
7,
944,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
38,
1039,
262,
14174,
1430,
1540,
332,
2482,
329,
1438,
6816,
13,
628,
220,
220,
220,
220,
220,
220,
220,
12039,
307,
1444,
706,
300,
79,
13,
82,
6442,
3419,
284,
4155,
1540,
332,
468,
6105,
198,
220,
220,
220,
220,
220,
220,
220,
6718,
2004,
290,
468,
7560,
2482,
13,
628,
220,
220,
220,
220,
220,
220,
220,
7567,
2696,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
43160,
12331,
25,
1002,
1444,
878,
44800,
15167,
29869,
13,
82,
6442,
22446,
628,
220,
220,
220,
220,
220,
220,
220,
16409,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
48436,
1988,
10200,
16019,
1438,
6816,
1988,
13,
628,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
1438,
6816,
62,
45286,
796,
2116,
13,
3672,
6816,
62,
45286,
628,
220,
220,
220,
220,
220,
220,
220,
611,
1438,
6816,
62,
45286,
318,
6045,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
5298,
43160,
12331,
7203,
3855,
62,
3672,
6816,
62,
82,
2122,
62,
8367,
1444,
878,
8494,
3419,
19570,
628,
220,
220,
220,
220,
220,
220,
220,
1441,
1438,
6816,
62,
45286,
13,
82,
2122,
62,
8367,
3419,
628,
198,
4871,
4808,
41339,
7416,
49354,
540,
50,
14375,
7,
15252,
2599,
198,
220,
220,
220,
37227,
13434,
8090,
543,
460,
2148,
1176,
379,
597,
640,
13,
628,
220,
220,
220,
49213,
25,
198,
220,
220,
220,
220,
220,
2723,
25,
24846,
7416,
2134,
810,
2116,
18616,
18470,
9633,
198,
220,
220,
220,
37227,
628,
220,
220,
220,
825,
17425,
62,
34431,
62,
25641,
2977,
62,
392,
62,
1102,
2536,
6003,
7,
944,
11,
300,
79,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
37835,
533,
300,
79,
9633,
11,
290,
900,
17778,
287,
10706,
62,
10459,
13,
628,
220,
220,
220,
220,
220,
220,
220,
943,
14542,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
300,
79,
25,
383,
44800,
15167,
29869,
13,
628,
220,
220,
220,
220,
220,
220,
220,
15965,
2977,
16691,
1144,
2291,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
532,
1661,
75,
501,
9633,
25,
2380,
703,
881,
1176,
262,
2723,
318,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
5072,
889,
379,
1123,
640,
12,
48369,
13,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
532,
1438,
6816,
7885,
25,
6870,
262,
5415,
1176,
18229,
13,
628,
220,
220,
220,
220,
220,
220,
220,
383,
3815,
286,
777,
9633,
389,
16019,
416,
262,
14174,
1430,
284,
198,
220,
220,
220,
220,
220,
220,
220,
27183,
3484,
2426,
284,
617,
17778,
13,
628,
220,
220,
220,
220,
220,
220,
220,
383,
4045,
9432,
318,
284,
17775,
1575,
13,
220,
3423,
259,
11,
262,
4045,
198,
220,
220,
220,
220,
220,
220,
220,
1575,
318,
3220,
416,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
532,
1438,
6816,
1575,
25,
1438,
6816,
62,
20850,
62,
15805,
1635,
1438,
6816,
7885,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
532,
7885,
1575,
25,
7885,
62,
20850,
62,
15805,
1635,
2160,
7,
22355,
75,
501,
62,
25641,
2977,
8,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
532,
6588,
1575,
25,
300,
79,
13,
29255,
62,
19290,
1635,
2160,
7,
22355,
75,
501,
62,
25641,
2977,
8,
1635,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
763,
17,
62,
525,
62,
9509,
8143,
62,
22554,
628,
220,
220,
220,
220,
220,
220,
220,
4619,
7885,
290,
6588,
3484,
697,
24508,
319,
257,
27458,
4308,
11,
356,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
29162,
606,
416,
300,
79,
13,
15805,
62,
1659,
62,
26316,
284,
787,
27458,
290,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
530,
12,
2435,
3484,
13975,
13,
628,
220,
220,
220,
220,
220,
220,
220,
1482,
2536,
6003,
2727,
1220,
9518,
994,
2291,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
532,
22246,
6682,
25,
48987,
2160,
1661,
75,
501,
12,
25641,
2977,
1279,
3509,
62,
22554,
611,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
9806,
62,
22554,
18189,
657,
13,
628,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
770,
32315,
318,
691,
329,
4237,
810,
612,
389,
7095,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
284,
262,
2472,
2033,
286,
5270,
543,
460,
307,
3170,
13,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
412,
13,
70,
13,
1318,
389,
691,
257,
3614,
1271,
286,
4113,
810,
530,
460,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1382,
7409,
1773,
789,
13,
628,
220,
220,
220,
220,
220,
220,
220,
220,
220,
532,
22246,
4333,
25,
48987,
645,
1661,
75,
501,
12,
25641,
2977,
1875,
3509,
62,
6477,
611,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
9806,
62,
6477,
318,
18189,
657,
13,
628,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
770,
32315,
318,
691,
329,
4237,
810,
612,
389,
7095,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
284,
262,
5415,
2033,
286,
1176,
543,
460,
307,
3170,
13,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
412,
13,
70,
13,
7409,
1773,
789,
543,
460,
691,
17655,
379,
257,
5415,
2494,
13,
628,
220,
220,
220,
220,
220,
220,
220,
220,
220,
532,
3515,
3760,
4333,
25,
48987,
326,
2160,
7,
6477,
8,
1875,
3512,
329,
477,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
640,
12,
82,
677,
274,
13,
220,
7778,
22696,
1927,
1444,
366,
44815,
262,
22661,
319,
526,
628,
220,
220,
220,
220,
220,
220,
220,
220,
220,
532,
48987,
1438,
6816,
7885,
1875,
1176,
7,
83,
8,
329,
477,
256,
13,
220,
775,
1276,
787,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1654,
326,
356,
1053,
19744,
503,
257,
4618,
543,
460,
5127,
262,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
9167,
1176,
13,
628,
220,
220,
220,
220,
220,
220,
220,
37227,
628,
220,
220,
220,
220,
220,
220,
220,
2723,
796,
2116,
13,
10459,
628,
220,
220,
220,
220,
220,
220,
220,
1303,
9058,
18470,
9633,
13,
198,
220,
220,
220,
220,
220,
220,
220,
2723,
13,
22355,
75,
501,
62,
25641,
2977,
796,
300,
79,
13,
32446,
533,
62,
22355,
75,
501,
62,
25641,
2977,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2723,
13,
3672,
11,
2723,
13,
25928,
62,
36996,
62,
312,
198,
220,
220,
220,
220,
220,
220,
220,
1267,
628,
220,
220,
220,
220,
220,
220,
220,
2723,
13,
3672,
6816,
62,
45286,
796,
300,
79,
13,
32446,
533,
62,
3672,
6816,
62,
45286,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2723,
13,
3672,
11,
2723,
13,
25928,
62,
36996,
62,
312,
198,
220,
220,
220,
220,
220,
220,
220,
1267,
628,
220,
220,
220,
220,
220,
220,
220,
1540,
332,
796,
300,
79,
13,
82,
14375,
628,
220,
220,
220,
220,
220,
220,
220,
1303,
17056,
495,
5415,
2568,
611,
340,
318,
18189,
657,
13,
220,
15323,
466,
407,
198,
220,
220,
220,
220,
220,
220,
220,
1303,
2251,
257,
32315,
13,
198,
220,
220,
220,
220,
220,
220,
220,
3509,
62,
22554,
62,
1102,
2536,
2913,
796,
357,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
300,
79,
13,
1102,
2536,
2913,
7,
15,
13,
15,
11,
2723,
13,
9806,
62,
22554,
8,
611,
2723,
13,
9806,
62,
22554,
18189,
657,
2073,
6045,
198,
220,
220,
220,
220,
220,
220,
220,
1267,
628,
220,
220,
220,
220,
220,
220,
220,
1303,
17056,
495,
5415,
1438,
6816,
611,
340,
318,
18189,
657,
13,
220,
15323,
466,
407,
198,
220,
220,
220,
220,
220,
220,
220,
1303,
2251,
257,
32315,
13,
198,
220,
220,
220,
220,
220,
220,
220,
3509,
62,
6477,
796,
2723,
13,
9806,
62,
6477,
198,
220,
220,
220,
220,
220,
220,
220,
611,
3509,
62,
6477,
18189,
657,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
300,
79,
13,
1102,
2536,
2913,
7,
15,
13,
15,
11,
3509,
62,
6477,
737,
2617,
62,
1073,
16814,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2723,
13,
3672,
6816,
62,
45286,
11,
352,
13,
15,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1267,
628,
220,
220,
220,
220,
220,
220,
220,
1303,
7472,
62,
15805,
3407,
1438,
6816,
1575,
13,
198,
220,
220,
220,
220,
220,
220,
220,
1575,
62,
15252,
425,
796,
300,
79,
13,
1084,
48439,
62,
15805,
82,
62,
15252,
425,
198,
220,
220,
220,
220,
220,
220,
220,
1575,
62,
15252,
425,
13,
2617,
62,
1073,
16814,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2723,
13,
3672,
6816,
62,
45286,
11,
2723,
13,
3672,
6816,
62,
20850,
62,
15805,
198,
220,
220,
220,
220,
220,
220,
220,
1267,
628,
220,
220,
220,
220,
220,
220,
220,
1303,
3060,
1661,
75,
501,
9633,
284,
44036,
13,
198,
220,
220,
220,
220,
220,
220,
220,
329,
256,
11,
1401,
287,
27056,
378,
7,
10459,
13,
22355,
75,
501,
62,
25641,
2977,
2599,
628,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1303,
7472,
62,
15805,
635,
3407,
7885,
290,
6588,
1575,
13,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
7885,
62,
1073,
891,
796,
357,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2723,
13,
45286,
62,
20850,
62,
15805,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1343,
2723,
13,
1073,
17,
62,
525,
62,
9509,
8143,
62,
22554,
1635,
300,
79,
13,
29255,
62,
19290,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1267,
1635,
300,
79,
13,
15805,
62,
1659,
62,
26316,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1575,
62,
15252,
425,
13,
2617,
62,
1073,
16814,
7,
7785,
11,
7885,
62,
1073,
891,
8,
628,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1303,
9175,
262,
7588,
319,
379,
477,
1661,
13,
220,
4333,
62,
1073,
16814,
318,
3221,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1303,
352,
13,
15,
11,
475,
318,
532,
16,
13,
15,
329,
24846,
31425,
13,
82,
676,
290,
17655,
62,
45888,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1303,
329,
24846,
31425,
13,
10459,
13,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
300,
79,
13,
5936,
3760,
62,
6477,
62,
1102,
2536,
2913,
58,
10459,
13,
25928,
62,
36996,
62,
312,
7131,
83,
4083,
2617,
62,
1073,
16814,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1401,
11,
2723,
13,
6477,
62,
1073,
16814,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1267,
628,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1303,
1482,
2536,
391,
374,
862,
62,
43082,
611,
2622,
13,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
611,
2723,
13,
271,
62,
81,
862,
62,
10459,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
300,
79,
13,
81,
862,
62,
10459,
62,
1102,
2536,
6003,
58,
10459,
13,
25928,
62,
36996,
62,
312,
7131,
83,
4083,
2617,
62,
1073,
16814,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1401,
11,
2723,
13,
6477,
62,
1073,
16814,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1267,
628,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1303,
48987,
2472,
2568,
318,
1342,
621,
2723,
13,
9806,
62,
22554,
13,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
611,
3509,
62,
22554,
62,
1102,
2536,
2913,
318,
407,
6045,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
3509,
62,
22554,
62,
1102,
2536,
2913,
13,
2617,
62,
1073,
16814,
7,
7785,
11,
352,
13,
15,
8,
628,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1303,
48987,
1176,
1595,
470,
7074,
2723,
13,
9806,
62,
6477,
13,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
611,
3509,
62,
6477,
18189,
657,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
300,
79,
13,
1102,
2536,
2913,
7,
15,
13,
15,
11,
3509,
62,
6477,
737,
2617,
62,
1073,
16814,
7,
7785,
11,
352,
13,
15,
8,
628,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1303,
6530,
6816,
1276,
307,
5749,
621,
4387,
1176,
13,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1303,
1002,
1438,
6816,
62,
20850,
62,
15805,
1875,
657,
11,
6446,
30011,
1634,
481,
4574,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1303,
6530,
6816,
1474,
3509,
7,
22355,
75,
501,
62,
25641,
2977,
737,
628,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1438,
6816,
62,
1102,
2536,
2913,
796,
300,
79,
13,
1102,
2536,
2913,
7,
15,
13,
15,
11,
1540,
332,
13,
10745,
6269,
28955,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1438,
6816,
62,
1102,
2536,
2913,
13,
2617,
62,
1073,
16814,
7,
7785,
11,
532,
16,
13,
15,
8,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1438,
6816,
62,
1102,
2536,
2913,
13,
2617,
62,
1073,
16814,
7,
10459,
13,
3672,
6816,
62,
45286,
11,
352,
13,
15,
8,
628,
220,
220,
220,
220,
220,
220,
220,
1303,
1482,
2536,
391,
5415,
1438,
6816,
611,
3509,
62,
6477,
318,
900,
13,
198,
220,
220,
220,
220,
220,
220,
220,
611,
2723,
13,
9806,
62,
6477,
18189,
657,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
300,
79,
13,
1102,
2536,
2913,
7,
15,
13,
15,
11,
2723,
13,
9806,
62,
6477,
737,
2617,
62,
1073,
16814,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2723,
13,
3672,
6816,
62,
45286,
11,
352,
13,
15,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1267,
628,
220,
220,
220,
825,
651,
62,
82,
2122,
62,
27160,
7,
944,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
38,
1039,
262,
14174,
1430,
1540,
332,
2482,
13,
628,
220,
220,
220,
220,
220,
220,
220,
12039,
307,
1444,
706,
300,
79,
13,
82,
6442,
3419,
284,
4155,
1540,
332,
468,
6105,
198,
220,
220,
220,
220,
220,
220,
220,
6718,
2004,
290,
468,
7560,
2482,
13,
628,
220,
220,
220,
220,
220,
220,
220,
7567,
2696,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
43160,
12331,
25,
1002,
1444,
878,
44800,
15167,
29869,
13,
82,
6442,
22446,
628,
220,
220,
220,
220,
220,
220,
220,
16409,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
45941,
13,
18747,
286,
8136,
329,
1123,
1661,
75,
501,
7885,
13,
628,
220,
220,
220,
220,
220,
220,
220,
37227,
628,
220,
220,
220,
220,
220,
220,
220,
1661,
75,
501,
62,
25641,
2977,
796,
2116,
13,
10459,
13,
22355,
75,
501,
62,
25641,
2977,
628,
220,
220,
220,
220,
220,
220,
220,
611,
1661,
75,
501,
62,
25641,
2977,
318,
6045,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
5298,
43160,
12331,
7203,
1136,
62,
82,
2122,
62,
27160,
1444,
878,
8494,
19570,
628,
220,
220,
220,
220,
220,
220,
220,
1441,
45941,
13,
18747,
26933,
85,
13,
82,
2122,
62,
8367,
3419,
329,
410,
287,
1661,
75,
501,
62,
25641,
2977,
12962,
628,
198,
4871,
4808,
41339,
7416,
15419,
49354,
540,
50,
14375,
7,
15252,
2599,
198,
220,
220,
220,
37227,
13434,
8090,
543,
460,
2148,
1438,
6816,
3294,
286,
663,
7034,
13,
628,
220,
220,
220,
49213,
25,
198,
220,
220,
220,
220,
220,
2723,
25,
24846,
7416,
2134,
810,
2116,
18616,
18470,
9633,
198,
220,
220,
220,
220,
220,
7034,
25,
19798,
292,
7171,
543,
6870,
644,
13390,
286,
262,
198,
220,
220,
220,
220,
220,
220,
220,
1438,
6816,
262,
2723,
460,
2148,
379,
597,
1813,
640,
13,
628,
220,
220,
220,
37227,
628,
220,
220,
220,
825,
17425,
62,
34431,
62,
25641,
2977,
62,
392,
62,
1102,
2536,
6003,
7,
944,
11,
300,
79,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
37835,
533,
300,
79,
9633,
11,
290,
900,
17778,
287,
10706,
62,
10459,
13,
628,
220,
220,
220,
220,
220,
220,
220,
943,
14542,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
300,
79,
25,
383,
44800,
15167,
29869,
13,
628,
220,
220,
220,
220,
220,
220,
220,
15965,
2977,
16691,
1144,
2291,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
532,
1438,
6816,
7885,
25,
6870,
262,
5415,
1176,
18229,
13,
628,
220,
220,
220,
220,
220,
220,
220,
383,
3815,
286,
777,
9633,
389,
16019,
416,
262,
14174,
1430,
284,
198,
220,
220,
220,
220,
220,
220,
220,
27183,
3484,
2426,
284,
617,
17778,
13,
628,
220,
220,
220,
220,
220,
220,
220,
383,
4045,
9432,
318,
284,
17775,
1575,
13,
220,
3423,
259,
11,
262,
4045,
198,
220,
220,
220,
220,
220,
220,
220,
1575,
318,
3220,
416,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
532,
1438,
6816,
1575,
25,
1438,
6816,
62,
20850,
62,
15805,
1635,
1438,
6816,
7885,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
532,
7885,
1575,
25,
7885,
62,
20850,
62,
15805,
1635,
1438,
6816,
7885,
1635,
2160,
7,
13317,
8,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
532,
6588,
1575,
25,
300,
79,
13,
29255,
62,
19290,
1635,
1438,
6816,
7885,
1635,
2160,
7,
13317,
8,
628,
220,
220,
220,
220,
220,
220,
220,
4619,
7885,
290,
6588,
3484,
697,
24508,
319,
257,
24169,
4308,
11,
356,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
29162,
606,
416,
300,
79,
13,
15805,
62,
1659,
62,
26316,
284,
787,
24169,
290,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
530,
12,
2435,
3484,
13975,
13,
628,
220,
220,
220,
220,
220,
220,
220,
1482,
2536,
6003,
2727,
1220,
9518,
994,
2291,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
532,
22246,
6682,
25,
48987,
1438,
6816,
1635,
2160,
7,
13317,
8,
1279,
3509,
62,
22554,
611,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
9806,
62,
22554,
18189,
657,
13,
628,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
770,
32315,
318,
691,
329,
4237,
810,
612,
389,
7095,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
284,
262,
2472,
2033,
286,
5270,
543,
460,
307,
3170,
13,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
412,
13,
70,
13,
1318,
389,
691,
257,
3614,
1271,
286,
4113,
810,
530,
460,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1382,
7409,
1773,
789,
13,
628,
220,
220,
220,
220,
220,
220,
220,
220,
220,
532,
22246,
4333,
25,
48987,
1438,
6816,
19841,
3509,
62,
6477,
611,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
9806,
62,
6477,
18189,
657,
13,
628,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
770,
32315,
318,
691,
329,
4237,
810,
612,
389,
7095,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
284,
262,
5415,
2033,
286,
1176,
543,
460,
307,
3170,
13,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
412,
13,
70,
13,
7409,
1773,
789,
543,
460,
691,
17655,
379,
257,
5415,
2494,
13,
628,
220,
220,
220,
220,
220,
220,
220,
220,
220,
532,
3515,
3760,
4333,
25,
48987,
326,
2160,
7,
6477,
8,
1875,
3512,
329,
477,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
640,
12,
82,
677,
274,
13,
220,
7778,
22696,
1927,
1444,
366,
44815,
262,
22661,
319,
526,
628,
220,
220,
220,
220,
220,
220,
220,
37227,
628,
220,
220,
220,
220,
220,
220,
220,
2723,
796,
2116,
13,
10459,
628,
220,
220,
220,
220,
220,
220,
220,
1303,
9058,
18470,
9633,
13,
198,
220,
220,
220,
220,
220,
220,
220,
2723,
13,
3672,
6816,
62,
45286,
796,
300,
79,
13,
32446,
533,
62,
3672,
6816,
62,
45286,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2723,
13,
3672,
11,
2723,
13,
25928,
62,
36996,
62,
312,
198,
220,
220,
220,
220,
220,
220,
220,
1267,
628,
220,
220,
220,
220,
220,
220,
220,
2160,
62,
13317,
796,
2160,
7,
944,
13,
13317,
8,
628,
220,
220,
220,
220,
220,
220,
220,
1303,
17056,
495,
5415,
2568,
611,
340,
318,
18189,
657,
13,
220,
15323,
466,
407,
198,
220,
220,
220,
220,
220,
220,
220,
1303,
2251,
257,
32315,
13,
198,
220,
220,
220,
220,
220,
220,
220,
611,
2723,
13,
9806,
62,
22554,
18189,
657,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
300,
79,
13,
1102,
2536,
2913,
7,
15,
13,
15,
11,
2723,
13,
9806,
62,
22554,
737,
2617,
62,
1073,
16814,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2723,
13,
3672,
6816,
62,
45286,
11,
2160,
62,
13317,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1267,
628,
220,
220,
220,
220,
220,
220,
220,
1303,
17056,
495,
5415,
2568,
611,
340,
318,
18189,
657,
13,
220,
15323,
466,
407,
198,
220,
220,
220,
220,
220,
220,
220,
1303,
2251,
257,
32315,
13,
198,
220,
220,
220,
220,
220,
220,
220,
3509,
62,
6477,
796,
2723,
13,
9806,
62,
6477,
198,
220,
220,
220,
220,
220,
220,
220,
611,
3509,
62,
6477,
18189,
657,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
300,
79,
13,
1102,
2536,
2913,
7,
15,
13,
15,
11,
3509,
62,
6477,
737,
2617,
62,
1073,
16814,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2723,
13,
3672,
6816,
62,
45286,
11,
352,
13,
15,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1267,
628,
220,
220,
220,
220,
220,
220,
220,
1303,
7472,
62,
15805,
3407,
1438,
6816,
1575,
13,
198,
220,
220,
220,
220,
220,
220,
220,
1575,
62,
15252,
425,
796,
300,
79,
13,
1084,
48439,
62,
15805,
82,
62,
15252,
425,
628,
220,
220,
220,
220,
220,
220,
220,
1575,
62,
1073,
16814,
796,
2723,
13,
3672,
6816,
62,
20850,
62,
15805,
1343,
300,
79,
13,
15805,
62,
1659,
62,
26316,
1635,
357,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2723,
13,
45286,
62,
20850,
62,
15805,
1635,
2160,
62,
13317,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1343,
2723,
13,
1073,
17,
62,
525,
62,
9509,
8143,
62,
22554,
1635,
2160,
62,
13317,
1635,
300,
79,
13,
29255,
62,
19290,
198,
220,
220,
220,
220,
220,
220,
220,
1267,
628,
220,
220,
220,
220,
220,
220,
220,
1575,
62,
15252,
425,
13,
2617,
62,
1073,
16814,
7,
10459,
13,
3672,
6816,
62,
45286,
11,
1575,
62,
1073,
16814,
8,
628,
220,
220,
220,
220,
220,
220,
220,
1303,
3060,
1661,
75,
501,
9633,
284,
44036,
13,
198,
220,
220,
220,
220,
220,
220,
220,
329,
256,
11,
7034,
62,
83,
287,
27056,
378,
7,
944,
13,
13317,
2599,
628,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1303,
9175,
262,
7588,
319,
379,
477,
1661,
13,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1949,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
32315,
796,
300,
79,
13,
5936,
3760,
62,
6477,
62,
1102,
2536,
2913,
58,
10459,
13,
25928,
62,
36996,
62,
312,
60,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2845,
7383,
12331,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
5298,
7383,
12331,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
366,
2949,
34479,
6875,
287,
10706,
62,
36996,
4064,
67,
526,
4064,
357,
10459,
13,
25928,
62,
36996,
62,
312,
8,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1267,
628,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
32315,
58,
83,
4083,
2617,
62,
1073,
16814,
7,
10459,
13,
3672,
6816,
62,
45286,
11,
7034,
62,
83,
8,
628,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1303,
1482,
2536,
391,
374,
862,
62,
43082,
611,
2622,
13,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
611,
2723,
13,
271,
62,
81,
862,
62,
10459,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
300,
79,
13,
81,
862,
62,
10459,
62,
1102,
2536,
6003,
58,
10459,
13,
25928,
62,
36996,
62,
312,
7131,
83,
4083,
2617,
62,
1073,
16814,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2723,
13,
3672,
6816,
62,
45286,
11,
7034,
62,
83,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1267,
628,
220,
220,
220,
825,
651,
62,
82,
2122,
62,
27160,
7,
944,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
38,
1039,
262,
14174,
1430,
1540,
332,
2482,
13,
628,
220,
220,
220,
220,
220,
220,
220,
12039,
307,
1444,
706,
300,
79,
13,
82,
6442,
3419,
284,
4155,
1540,
332,
468,
6105,
198,
220,
220,
220,
220,
220,
220,
220,
6718,
2004,
290,
468,
7560,
2482,
13,
628,
220,
220,
220,
220,
220,
220,
220,
7567,
2696,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
43160,
12331,
25,
1002,
1444,
878,
44800,
15167,
29869,
13,
82,
6442,
22446,
628,
220,
220,
220,
220,
220,
220,
220,
16409,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
45941,
13,
18747,
286,
8136,
329,
1123,
1661,
75,
501,
7885,
13,
628,
220,
220,
220,
220,
220,
220,
220,
37227,
628,
220,
220,
220,
220,
220,
220,
220,
1438,
6816,
62,
45286,
796,
2116,
13,
10459,
13,
3672,
6816,
62,
45286,
198,
220,
220,
220,
220,
220,
220,
220,
611,
1438,
6816,
62,
45286,
318,
6045,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
5298,
43160,
12331,
7203,
1136,
62,
82,
2122,
62,
27160,
1444,
878,
8494,
19570,
628,
220,
220,
220,
220,
220,
220,
220,
1441,
1438,
6816,
62,
45286,
13,
82,
2122,
62,
8367,
3419,
1635,
2116,
13,
13317,
13,
27160,
628,
198,
4871,
24846,
31425,
7,
15252,
2599,
198,
220,
220,
220,
37227,
1273,
2850,
2568,
422,
262,
10706,
290,
5860,
340,
618,
2622,
2426,
284,
9089,
13,
628,
220,
220,
220,
49213,
25,
198,
220,
220,
220,
220,
220,
1438,
25,
317,
4731,
543,
318,
262,
1438,
286,
262,
2134,
13,
198,
220,
220,
220,
220,
220,
6143,
62,
3672,
6816,
62,
15805,
25,
317,
12178,
543,
318,
262,
1575,
583,
1438,
6816,
286,
198,
220,
220,
220,
220,
220,
220,
220,
2568,
6143,
13,
220,
412,
13,
70,
13,
383,
1575,
286,
13591,
13,
198,
220,
220,
220,
220,
220,
3877,
62,
3672,
6816,
62,
15805,
25,
317,
12178,
543,
318,
262,
1575,
583,
1438,
6816,
198,
220,
220,
220,
220,
220,
220,
220,
1176,
284,
3877,
262,
6143,
13,
220,
412,
13,
70,
13,
383,
13621,
7483,
1575,
284,
10385,
198,
220,
220,
220,
220,
220,
220,
220,
281,
7125,
10706,
284,
6257,
6143,
13,
198,
220,
220,
220,
220,
220,
17655,
62,
3672,
6816,
62,
15805,
25,
317,
12178,
543,
318,
262,
1575,
583,
1438,
6816,
198,
220,
220,
220,
220,
220,
220,
220,
1176,
284,
27978,
262,
10706,
13,
220,
412,
13,
70,
13,
383,
1575,
286,
257,
1176,
40631,
353,
284,
198,
220,
220,
220,
220,
220,
220,
220,
10385,
6257,
6143,
736,
284,
7125,
198,
220,
220,
220,
220,
220,
10706,
62,
36996,
62,
312,
25,
1052,
493,
31577,
262,
10706,
3814,
286,
262,
6143,
13,
198,
220,
220,
220,
220,
220,
220,
220,
383,
6143,
460,
691,
3650,
2568,
7560,
416,
4237,
351,
262,
198,
220,
220,
220,
220,
220,
220,
220,
976,
10706,
62,
36996,
62,
312,
13,
220,
5514,
8665,
351,
262,
976,
10706,
62,
36996,
62,
312,
198,
220,
220,
220,
220,
220,
220,
220,
460,
14595,
1176,
422,
428,
13,
198,
220,
220,
220,
220,
220,
3877,
62,
45888,
25,
317,
12178,
12897,
422,
657,
13,
15,
532,
352,
13,
15,
543,
8477,
198,
220,
220,
220,
220,
220,
220,
220,
262,
2568,
2994,
1022,
262,
10706,
290,
262,
6143,
5002,
13,
220,
657,
13,
15,
198,
220,
220,
220,
220,
220,
220,
220,
1724,
1844,
2994,
11,
352,
13,
15,
1724,
645,
2994,
13,
198,
220,
220,
220,
220,
220,
6143,
62,
45888,
25,
317,
12178,
12897,
422,
657,
13,
15,
532,
352,
13,
15,
543,
8477,
198,
220,
220,
220,
220,
220,
220,
220,
703,
881,
8574,
2568,
3793,
422,
2180,
8574,
2568,
706,
198,
220,
220,
220,
220,
220,
220,
220,
530,
640,
12,
13696,
13,
220,
352,
13,
15,
1724,
645,
2994,
13,
657,
13,
15,
1724,
477,
8574,
2568,
198,
220,
220,
220,
220,
220,
220,
220,
318,
2626,
13,
198,
220,
220,
220,
220,
220,
17655,
62,
45888,
25,
317,
12178,
12897,
422,
657,
13,
15,
532,
352,
13,
15,
543,
8477,
198,
220,
220,
220,
220,
220,
220,
220,
262,
2568,
2994,
1022,
6143,
290,
10706,
618,
302,
31498,
262,
10706,
13,
198,
220,
220,
220,
220,
220,
220,
220,
657,
13,
15,
1724,
1844,
2994,
11,
352,
13,
15,
1724,
645,
2994,
13,
198,
220,
220,
220,
220,
220,
3509,
62,
10136,
62,
6477,
25,
317,
12178,
543,
6870,
262,
5415,
1176,
326,
198,
220,
220,
220,
220,
220,
220,
220,
460,
3877,
6143,
357,
9948,
49262,
878,
597,
9332,
9089,
15729,
198,
220,
220,
220,
220,
220,
220,
220,
317,
1988,
1279,
657,
1724,
612,
318,
645,
3877,
1176,
4179,
13,
198,
220,
220,
220,
220,
220,
3509,
62,
6381,
10136,
62,
6477,
25,
317,
12178,
543,
6870,
262,
5415,
1176,
198,
220,
220,
220,
220,
220,
220,
220,
326,
460,
17655,
6143,
357,
9948,
49262,
878,
597,
9332,
198,
220,
220,
220,
220,
220,
220,
220,
9089,
15729,
220,
317,
1988,
1279,
657,
1724,
612,
318,
645,
17655,
1176,
4179,
13,
198,
220,
220,
220,
220,
220,
3509,
62,
35350,
25,
1052,
11902,
12178,
543,
6870,
262,
5415,
2568,
198,
220,
220,
220,
220,
220,
220,
220,
326,
460,
307,
8574,
13,
220,
317,
1988,
1279,
657,
1724,
612,
318,
645,
5415,
198,
220,
220,
220,
220,
220,
220,
220,
6143,
4179,
13,
198,
220,
220,
220,
220,
220,
318,
62,
81,
862,
25,
41146,
26,
611,
2081,
11,
7622,
2610,
286,
374,
862,
62,
43082,
355,
6143,
318,
198,
220,
220,
220,
220,
220,
220,
220,
5047,
1220,
26476,
13,
220,
26308,
11642,
58,
83,
60,
318,
13284,
20216,
422,
198,
220,
220,
220,
220,
220,
220,
220,
374,
862,
62,
43082,
58,
83,
60,
422,
374,
862,
62,
43082,
58,
83,
4083,
220,
26308,
595,
31498,
58,
83,
60,
318,
198,
220,
220,
220,
220,
220,
220,
220,
2087,
284,
374,
862,
62,
43082,
58,
83,
4083,
220,
1002,
3991,
11,
645,
374,
862,
62,
66,
20696,
389,
12328,
13,
198,
220,
220,
220,
37227,
628,
220,
220,
220,
825,
17425,
62,
34431,
62,
25641,
2977,
62,
392,
62,
1102,
2536,
6003,
7,
944,
11,
300,
79,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
37835,
533,
300,
79,
9633,
11,
290,
900,
17778,
13,
628,
220,
220,
220,
220,
220,
220,
220,
943,
14542,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
300,
79,
25,
44800,
15167,
29869,
11,
4909,
300,
79,
1540,
332,
290,
17778,
13,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
628,
220,
220,
220,
220,
220,
220,
220,
1303,
5345,
510,
18470,
9633,
13,
198,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
22554,
62,
25641,
2977,
796,
300,
79,
13,
32446,
533,
62,
22355,
75,
501,
62,
25641,
2977,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
3672,
11,
2116,
13,
25928,
62,
36996,
62,
312,
198,
220,
220,
220,
220,
220,
220,
220,
1267,
628,
220,
220,
220,
220,
220,
220,
220,
611,
2116,
13,
35350,
62,
3672,
6816,
62,
15805,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
22554,
62,
3672,
6816,
796,
300,
79,
13,
32446,
533,
62,
3672,
6816,
62,
45286,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
3672,
11,
2116,
13,
25928,
62,
36996,
62,
312,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1267,
628,
220,
220,
220,
220,
220,
220,
220,
1303,
5345,
510,
2723,
290,
17425,
18470,
9633,
13,
198,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
10459,
796,
24846,
7416,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1438,
28,
944,
13,
3672,
1343,
366,
2723,
1600,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1438,
6816,
62,
20850,
62,
15805,
28,
944,
13,
6381,
10136,
62,
3672,
6816,
62,
15805,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
7885,
62,
20850,
62,
15805,
28,
15,
13,
15,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
10706,
62,
36996,
62,
312,
28,
944,
13,
25928,
62,
36996,
62,
312,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
3509,
62,
6477,
28,
944,
13,
9806,
62,
6381,
10136,
62,
6477,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
763,
17,
62,
525,
62,
9509,
8143,
62,
22554,
28,
15,
13,
15,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1176,
62,
1073,
16814,
28,
944,
13,
6381,
10136,
62,
45888,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
318,
62,
81,
862,
62,
10459,
28,
944,
13,
271,
62,
81,
862,
11,
198,
220,
220,
220,
220,
220,
220,
220,
1267,
198,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
10459,
13,
82,
14375,
796,
4808,
41339,
7416,
49354,
540,
50,
14375,
7,
944,
13,
10459,
8,
198,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
10459,
13,
11250,
495,
62,
34431,
62,
25641,
2977,
62,
392,
62,
1102,
2536,
6003,
7,
34431,
8,
628,
220,
220,
220,
220,
220,
220,
220,
1303,
5345,
510,
14595,
290,
17425,
18470,
9633,
13,
198,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
82,
676,
796,
24846,
7416,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1438,
28,
944,
13,
3672,
1343,
366,
14595,
1600,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1438,
6816,
62,
20850,
62,
15805,
28,
944,
13,
6381,
10136,
62,
3672,
6816,
62,
15805,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
7885,
62,
20850,
62,
15805,
28,
15,
13,
15,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
10706,
62,
36996,
62,
312,
28,
944,
13,
25928,
62,
36996,
62,
312,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
3509,
62,
6477,
28,
944,
13,
9806,
62,
10136,
62,
6477,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
763,
17,
62,
525,
62,
9509,
8143,
62,
22554,
28,
15,
13,
15,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1176,
62,
1073,
16814,
10779,
16,
13,
15,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
318,
62,
81,
862,
62,
10459,
28,
944,
13,
271,
62,
81,
862,
11,
198,
220,
220,
220,
220,
220,
220,
220,
1267,
198,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
82,
676,
13,
82,
14375,
796,
4808,
41339,
7416,
49354,
540,
50,
14375,
7,
944,
13,
82,
676,
8,
198,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
82,
676,
13,
11250,
495,
62,
34431,
62,
25641,
2977,
62,
392,
62,
1102,
2536,
6003,
7,
34431,
8,
628,
220,
220,
220,
220,
220,
220,
220,
1303,
3060,
2568,
1438,
6816,
3484,
284,
262,
9432,
13,
220,
3819,
3484,
389,
198,
220,
220,
220,
220,
220,
220,
220,
1303,
2087,
416,
2723,
14,
82,
676,
13,
11250,
495,
62,
34431,
62,
25641,
2977,
62,
392,
62,
1102,
2536,
6003,
13,
198,
220,
220,
220,
220,
220,
220,
220,
611,
2116,
13,
35350,
62,
3672,
6816,
62,
15805,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1438,
6816,
796,
2116,
13,
22554,
62,
3672,
6816,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
300,
79,
13,
1084,
48439,
62,
15805,
82,
62,
15252,
425,
13,
2617,
62,
1073,
16814,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1438,
6816,
11,
2116,
13,
35350,
62,
3672,
6816,
62,
15805,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1267,
628,
220,
220,
220,
220,
220,
220,
220,
1303,
1482,
2536,
391,
6682,
20514,
284,
307,
6682,
4586,
640,
5556,
14595,
20208,
2723,
13,
198,
220,
220,
220,
220,
220,
220,
220,
1303,
20514,
318,
18620,
523,
9633,
379,
256,
28,
15,
4745,
319,
9633,
379,
256,
10779,
16,
198,
220,
220,
220,
220,
220,
220,
220,
1303,
543,
318,
7548,
284,
938,
1988,
287,
21015,
6376,
278,
7791,
13,
198,
220,
220,
220,
220,
220,
220,
220,
9633,
796,
2116,
13,
22554,
62,
25641,
2977,
198,
220,
220,
220,
220,
220,
220,
220,
329,
256,
287,
300,
79,
13,
2435,
62,
9630,
62,
2676,
540,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1303,
20101,
796,
3877,
62,
45888,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1303,
1001,
796,
6143,
62,
45888,
13,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1303,
520,
1850,
58,
72,
60,
796,
384,
1635,
520,
1850,
58,
72,
12,
16,
60,
1343,
2906,
1635,
14595,
58,
72,
12,
16,
60,
532,
2723,
58,
72,
12,
16,
60,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1303,
657,
796,
532,
1273,
1850,
58,
72,
60,
1343,
384,
1635,
520,
1850,
58,
72,
12,
16,
60,
1343,
2906,
1635,
14595,
58,
72,
12,
16,
60,
532,
2723,
58,
72,
12,
16,
60,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
269,
796,
300,
79,
13,
1102,
2536,
2913,
7,
15,
13,
15,
11,
657,
13,
15,
8,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
269,
13,
2617,
62,
1073,
16814,
7,
25641,
2977,
58,
83,
4357,
532,
16,
13,
15,
8,
220,
1303,
532,
1273,
1850,
58,
72,
60,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
269,
13,
2617,
62,
1073,
16814,
7,
25641,
2977,
58,
83,
532,
352,
4357,
2116,
13,
35350,
62,
45888,
8,
628,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1303,
8090,
290,
14595,
389,
3585,
284,
262,
10706,
11,
523,
6697,
994,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1303,
311,
676,
6673,
284,
6143,
11,
2723,
34128,
82,
422,
6143,
13,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
269,
13,
2617,
62,
1073,
16814,
7,
944,
13,
10459,
13,
22355,
75,
501,
62,
25641,
2977,
58,
83,
532,
352,
4357,
532,
16,
13,
15,
8,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
269,
13,
2617,
62,
1073,
16814,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
82,
676,
13,
22355,
75,
501,
62,
25641,
2977,
58,
83,
532,
352,
4357,
2116,
13,
10136,
62,
45888,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1267,
628,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1303,
48987,
1438,
6816,
318,
4025,
621,
8574,
62,
8367,
13,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
611,
2116,
13,
35350,
62,
3672,
6816,
62,
15805,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1438,
6816,
62,
1102,
2536,
2913,
796,
300,
79,
13,
1102,
2536,
2913,
7,
15,
13,
15,
11,
300,
79,
13,
82,
14375,
13,
10745,
6269,
28955,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1438,
6816,
62,
1102,
2536,
2913,
13,
2617,
62,
1073,
16814,
7,
3672,
6816,
11,
352,
13,
15,
8,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1438,
6816,
62,
1102,
2536,
2913,
13,
2617,
62,
1073,
16814,
7,
25641,
2977,
58,
83,
4357,
532,
16,
13,
15,
8,
628,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1303,
1482,
2536,
391,
5415,
6143,
611,
3509,
62,
35350,
18189,
657,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
611,
2116,
13,
9806,
62,
35350,
18189,
657,
13,
15,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
3509,
62,
35350,
62,
1102,
2536,
2913,
796,
300,
79,
13,
1102,
2536,
2913,
7,
15,
13,
15,
11,
2116,
13,
9806,
62,
35350,
8,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
3509,
62,
35350,
62,
1102,
2536,
2913,
13,
2617,
62,
1073,
16814,
7,
25641,
2977,
58,
83,
4357,
352,
13,
15,
8,
628,
220,
220,
220,
825,
1281,
62,
14681,
7,
944,
11,
300,
79,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
10260,
300,
79,
1281,
62,
36948,
1255,
9633,
13,
628,
220,
220,
220,
220,
220,
220,
220,
770,
318,
1760,
1281,
300,
79,
13,
82,
6442,
3419,
523,
326,
34182,
1366,
8794,
460,
307,
1760,
198,
220,
220,
220,
220,
220,
220,
220,
319,
371,
3705,
878,
8024,
2482,
13,
628,
220,
220,
220,
220,
220,
220,
220,
943,
14542,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
300,
79,
25,
383,
44800,
15167,
29869,
810,
262,
1281,
7587,
9633,
26412,
13,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
628,
220,
220,
220,
220,
220,
220,
220,
14595,
62,
12786,
796,
2116,
13,
82,
676,
13,
1136,
62,
82,
2122,
62,
27160,
3419,
198,
220,
220,
220,
220,
220,
220,
220,
2723,
62,
12786,
796,
2116,
13,
10459,
13,
1136,
62,
82,
2122,
62,
27160,
3419,
1635,
2116,
13,
6381,
10136,
62,
45888,
628,
220,
220,
220,
220,
220,
220,
220,
611,
2116,
13,
271,
62,
81,
862,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
300,
79,
13,
81,
862,
62,
23350,
58,
944,
13,
25928,
62,
36996,
62,
312,
60,
15853,
2723,
62,
12786,
532,
14595,
62,
12786,
198,
220,
220,
220,
220,
220,
220,
220,
2073,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
300,
79,
13,
13159,
62,
81,
862,
62,
23350,
58,
944,
13,
25928,
62,
36996,
62,
312,
60,
15853,
2723,
62,
12786,
532,
14595,
62,
12786,
628,
220,
220,
220,
825,
651,
62,
3672,
6816,
62,
82,
2122,
62,
8367,
7,
944,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
38,
1039,
262,
14174,
1430,
1540,
332,
2482,
329,
1438,
6816,
13,
628,
220,
220,
220,
220,
220,
220,
220,
12039,
307,
1444,
706,
300,
79,
13,
82,
6442,
3419,
284,
4155,
1540,
332,
468,
6105,
198,
220,
220,
220,
220,
220,
220,
220,
6718,
2004,
290,
468,
7560,
2482,
13,
628,
220,
220,
220,
220,
220,
220,
220,
7567,
2696,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
43160,
12331,
25,
1002,
1444,
878,
44800,
15167,
29869,
13,
82,
6442,
22446,
628,
220,
220,
220,
220,
220,
220,
220,
16409,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
48436,
1988,
10200,
16019,
1438,
6816,
1988,
13,
628,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
611,
2116,
13,
35350,
62,
3672,
6816,
62,
15805,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1438,
6816,
62,
45286,
796,
2116,
13,
22554,
62,
3672,
6816,
628,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
611,
1438,
6816,
62,
45286,
318,
6045,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
5298,
43160,
12331,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
366,
3855,
62,
3672,
6816,
62,
82,
2122,
62,
8367,
1444,
878,
8494,
3419,
526,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1267,
628,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1441,
1438,
6816,
62,
45286,
13,
82,
2122,
62,
8367,
3419,
198,
220,
220,
220,
220,
220,
220,
220,
2073,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1441,
3509,
7,
944,
13,
1136,
62,
82,
2122,
62,
27160,
28955,
628,
220,
220,
220,
825,
651,
62,
82,
2122,
62,
27160,
7,
944,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
38,
1039,
262,
14174,
1430,
1540,
332,
2482,
13,
628,
220,
220,
220,
220,
220,
220,
220,
12039,
307,
1444,
706,
300,
79,
13,
82,
6442,
3419,
284,
4155,
1540,
332,
468,
6105,
198,
220,
220,
220,
220,
220,
220,
220,
6718,
2004,
290,
468,
7560,
2482,
13,
628,
220,
220,
220,
220,
220,
220,
220,
7567,
2696,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
43160,
12331,
25,
1002,
1444,
878,
44800,
15167,
29869,
13,
82,
6442,
22446,
628,
220,
220,
220,
220,
220,
220,
220,
16409,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
45941,
13,
18747,
286,
8136,
329,
1123,
1661,
75,
501,
7885,
13,
628,
220,
220,
220,
220,
220,
220,
220,
37227,
628,
220,
220,
220,
220,
220,
220,
220,
1661,
75,
501,
62,
25641,
2977,
796,
2116,
13,
22554,
62,
25641,
2977,
628,
220,
220,
220,
220,
220,
220,
220,
611,
1661,
75,
501,
62,
25641,
2977,
318,
6045,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
5298,
43160,
12331,
7203,
1136,
62,
82,
2122,
62,
27160,
1444,
878,
8494,
19570,
628,
220,
220,
220,
220,
220,
220,
220,
1441,
45941,
13,
18747,
26933,
85,
13,
82,
2122,
62,
8367,
3419,
329,
410,
287,
1661,
75,
501,
62,
25641,
2977,
12962,
628,
198,
4871,
24846,
6690,
31425,
7,
15252,
2599,
198,
220,
220,
220,
37227,
1273,
2850,
2568,
422,
262,
10706,
290,
5860,
340,
618,
2622,
2426,
284,
9089,
13,
628,
220,
220,
220,
770,
318,
257,
29908,
1088,
734,
24846,
31425,
5563,
11,
530,
543,
7000,
198,
220,
220,
220,
366,
27773,
1,
2568,
357,
271,
62,
81,
862,
8,
290,
530,
543,
7000,
366,
49075,
1,
2568,
357,
1662,
198,
220,
220,
220,
318,
62,
81,
862,
737,
220,
1318,
318,
257,
761,
329,
1111,
3858,
286,
6143,
284,
1394,
2610,
286,
198,
220,
220,
220,
15713,
2568,
10824,
13,
628,
220,
220,
220,
49213,
25,
198,
220,
220,
220,
220,
220,
1438,
25,
317,
4731,
543,
318,
262,
1438,
286,
262,
2134,
13,
198,
220,
220,
220,
220,
220,
6143,
62,
3672,
6816,
62,
15805,
25,
317,
12178,
543,
318,
262,
1575,
583,
1438,
6816,
286,
198,
220,
220,
220,
220,
220,
220,
220,
2568,
6143,
13,
220,
412,
13,
70,
13,
383,
1575,
286,
13591,
13,
198,
220,
220,
220,
220,
220,
3877,
62,
3672,
6816,
62,
15805,
25,
317,
12178,
543,
318,
262,
1575,
583,
1438,
6816,
198,
220,
220,
220,
220,
220,
220,
220,
1176,
284,
3877,
262,
6143,
13,
220,
412,
13,
70,
13,
383,
13621,
7483,
1575,
284,
10385,
198,
220,
220,
220,
220,
220,
220,
220,
281,
7125,
10706,
284,
6257,
6143,
13,
198,
220,
220,
220,
220,
220,
17655,
62,
3672,
6816,
62,
15805,
25,
317,
12178,
543,
318,
262,
1575,
583,
1438,
6816,
198,
220,
220,
220,
220,
220,
220,
220,
1176,
284,
27978,
262,
10706,
13,
220,
412,
13,
70,
13,
383,
1575,
286,
257,
1176,
40631,
353,
284,
198,
220,
220,
220,
220,
220,
220,
220,
10385,
6257,
6143,
736,
284,
7125,
198,
220,
220,
220,
220,
220,
10706,
62,
36996,
62,
312,
25,
1052,
493,
31577,
262,
10706,
3814,
286,
262,
6143,
13,
198,
220,
220,
220,
220,
220,
220,
220,
383,
6143,
460,
691,
3650,
2568,
7560,
416,
4237,
351,
262,
198,
220,
220,
220,
220,
220,
220,
220,
976,
10706,
62,
36996,
62,
312,
13,
220,
5514,
8665,
351,
262,
976,
10706,
62,
36996,
62,
312,
198,
220,
220,
220,
220,
220,
220,
220,
460,
14595,
1176,
422,
428,
13,
198,
220,
220,
220,
220,
220,
3877,
62,
45888,
25,
317,
12178,
12897,
422,
657,
13,
15,
532,
352,
13,
15,
543,
8477,
198,
220,
220,
220,
220,
220,
220,
220,
262,
2568,
2994,
1022,
262,
10706,
290,
262,
6143,
5002,
13,
220,
657,
13,
15,
198,
220,
220,
220,
220,
220,
220,
220,
1724,
1844,
2994,
11,
352,
13,
15,
1724,
645,
2994,
13,
198,
220,
220,
220,
220,
220,
6143,
62,
45888,
25,
317,
12178,
12897,
422,
657,
13,
15,
532,
352,
13,
15,
543,
8477,
198,
220,
220,
220,
220,
220,
220,
220,
703,
881,
8574,
2568,
3793,
422,
2180,
8574,
2568,
706,
198,
220,
220,
220,
220,
220,
220,
220,
530,
640,
12,
13696,
13,
220,
352,
13,
15,
1724,
645,
2994,
13,
657,
13,
15,
1724,
477,
8574,
2568,
198,
220,
220,
220,
220,
220,
220,
220,
318,
2626,
13,
198,
220,
220,
220,
220,
220,
17655,
62,
45888,
25,
317,
12178,
12897,
422,
657,
13,
15,
532,
352,
13,
15,
543,
8477,
198,
220,
220,
220,
220,
220,
220,
220,
262,
2568,
2994,
1022,
6143,
290,
10706,
618,
302,
31498,
262,
10706,
13,
198,
220,
220,
220,
220,
220,
220,
220,
657,
13,
15,
1724,
1844,
2994,
11,
352,
13,
15,
1724,
645,
2994,
13,
198,
220,
220,
220,
220,
220,
3509,
62,
10136,
62,
6477,
25,
317,
12178,
543,
6870,
262,
5415,
1176,
326,
198,
220,
220,
220,
220,
220,
220,
220,
460,
3877,
6143,
357,
9948,
49262,
878,
597,
9332,
9089,
15729,
198,
220,
220,
220,
220,
220,
220,
220,
317,
1988,
1279,
657,
1724,
612,
318,
645,
3877,
1176,
4179,
13,
198,
220,
220,
220,
220,
220,
3509,
62,
6381,
10136,
62,
6477,
25,
317,
12178,
543,
6870,
262,
5415,
1176,
198,
220,
220,
220,
220,
220,
220,
220,
326,
460,
17655,
6143,
357,
9948,
49262,
878,
597,
9332,
198,
220,
220,
220,
220,
220,
220,
220,
9089,
15729,
220,
317,
1988,
1279,
657,
1724,
612,
318,
645,
17655,
1176,
4179,
13,
198,
220,
220,
220,
220,
220,
3509,
62,
35350,
25,
1052,
11902,
12178,
543,
6870,
262,
5415,
2568,
198,
220,
220,
220,
220,
220,
220,
220,
326,
460,
307,
8574,
13,
220,
317,
1988,
1279,
657,
1724,
612,
318,
645,
5415,
198,
220,
220,
220,
220,
220,
220,
220,
6143,
4179,
13,
628,
220,
220,
220,
220,
220,
664,
62,
35350,
25,
24846,
31425,
2134,
543,
7000,
366,
27773,
1,
2568,
13,
198,
220,
220,
220,
220,
220,
645,
62,
8344,
62,
35350,
25,
24846,
31425,
2134,
543,
7000,
366,
49075,
1,
2568,
13,
198,
220,
220,
220,
37227,
628,
220,
220,
220,
825,
17425,
62,
34431,
62,
25641,
2977,
62,
392,
62,
1102,
2536,
6003,
7,
944,
11,
300,
79,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
37835,
533,
300,
79,
9633,
11,
290,
900,
17778,
526,
15931,
628,
220,
220,
220,
220,
220,
220,
220,
1303,
1114,
664,
62,
35350,
290,
645,
62,
8344,
62,
35350,
6143,
11,
900,
477,
3484,
284,
657,
198,
220,
220,
220,
220,
220,
220,
220,
1303,
290,
351,
645,
7095,
13,
220,
27131,
378,
3484,
290,
7095,
706,
198,
220,
220,
220,
220,
220,
220,
220,
1303,
14305,
13,
628,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
8344,
62,
35350,
796,
24846,
31425,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1438,
28,
944,
13,
3672,
1343,
366,
19644,
62,
2257,
1581,
11879,
1600,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
6143,
62,
3672,
6816,
62,
15805,
28,
15,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
10706,
62,
36996,
62,
312,
28,
944,
13,
25928,
62,
36996,
62,
312,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
3877,
62,
45888,
28,
944,
13,
10136,
62,
45888,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
17655,
62,
45888,
28,
944,
13,
6381,
10136,
62,
45888,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
6143,
62,
45888,
28,
944,
13,
35350,
62,
45888,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
318,
62,
81,
862,
28,
17821,
11,
198,
220,
220,
220,
220,
220,
220,
220,
1267,
628,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
3919,
62,
8344,
62,
35350,
796,
24846,
31425,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1438,
28,
944,
13,
3672,
1343,
366,
8005,
62,
38827,
62,
2257,
1581,
11879,
1600,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
6143,
62,
3672,
6816,
62,
15805,
28,
15,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
10706,
62,
36996,
62,
312,
28,
944,
13,
25928,
62,
36996,
62,
312,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
3877,
62,
45888,
28,
944,
13,
10136,
62,
45888,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
17655,
62,
45888,
28,
944,
13,
6381,
10136,
62,
45888,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
6143,
62,
45888,
28,
944,
13,
35350,
62,
45888,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
318,
62,
81,
862,
28,
25101,
11,
198,
220,
220,
220,
220,
220,
220,
220,
1267,
628,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
8344,
62,
35350,
13,
11250,
495,
62,
34431,
62,
25641,
2977,
62,
392,
62,
1102,
2536,
6003,
7,
34431,
8,
198,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
3919,
62,
8344,
62,
35350,
13,
11250,
495,
62,
34431,
62,
25641,
2977,
62,
392,
62,
1102,
2536,
6003,
7,
34431,
8,
628,
220,
220,
220,
220,
220,
220,
220,
1303,
27131,
378,
3484,
290,
7095,
1912,
319,
262,
2160,
286,
1111,
664,
62,
35350,
198,
220,
220,
220,
220,
220,
220,
220,
1303,
290,
645,
62,
8344,
62,
35350,
13,
628,
220,
220,
220,
220,
220,
220,
220,
1303,
5345,
510,
18470,
9633,
13,
198,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
22554,
62,
25641,
2977,
796,
300,
79,
13,
32446,
533,
62,
22355,
75,
501,
62,
25641,
2977,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
3672,
11,
2116,
13,
25928,
62,
36996,
62,
312,
198,
220,
220,
220,
220,
220,
220,
220,
1267,
628,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
22554,
62,
3672,
6816,
796,
300,
79,
13,
32446,
533,
62,
3672,
6816,
62,
45286,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
3672,
11,
2116,
13,
25928,
62,
36996,
62,
312,
198,
220,
220,
220,
220,
220,
220,
220,
1267,
628,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
10136,
62,
3672,
6816,
796,
300,
79,
13,
32446,
533,
62,
3672,
6816,
62,
45286,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
3672,
1343,
366,
3877,
1438,
6816,
1600,
2116,
13,
25928,
62,
36996,
62,
312,
198,
220,
220,
220,
220,
220,
220,
220,
1267,
628,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
6381,
10136,
62,
3672,
6816,
796,
300,
79,
13,
32446,
533,
62,
3672,
6816,
62,
45286,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
3672,
1343,
366,
17655,
1438,
6816,
1600,
2116,
13,
25928,
62,
36996,
62,
312,
198,
220,
220,
220,
220,
220,
220,
220,
1267,
628,
220,
220,
220,
220,
220,
220,
220,
1303,
5345,
7095,
611,
2622,
13,
198,
220,
220,
220,
220,
220,
220,
220,
611,
2116,
13,
9806,
62,
35350,
18189,
657,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
300,
79,
13,
1102,
2536,
2913,
7,
15,
13,
15,
11,
2116,
13,
9806,
62,
35350,
737,
2617,
62,
1073,
16814,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
22554,
62,
3672,
6816,
11,
352,
13,
15,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1267,
628,
220,
220,
220,
220,
220,
220,
220,
611,
2116,
13,
9806,
62,
10136,
62,
6477,
18189,
657,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
300,
79,
13,
1102,
2536,
2913,
7,
15,
13,
15,
11,
2116,
13,
9806,
62,
10136,
62,
6477,
737,
2617,
62,
1073,
16814,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
10136,
62,
3672,
6816,
11,
352,
13,
15,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1267,
628,
220,
220,
220,
220,
220,
220,
220,
611,
2116,
13,
9806,
62,
6381,
10136,
62,
6477,
18189,
657,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
300,
79,
13,
1102,
2536,
2913,
7,
15,
13,
15,
11,
2116,
13,
9806,
62,
6381,
10136,
62,
6477,
737,
2617,
62,
1073,
16814,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
6381,
10136,
62,
3672,
6816,
11,
352,
13,
15,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1267,
628,
220,
220,
220,
220,
220,
220,
220,
1303,
3060,
2568,
1438,
6816,
3484,
284,
262,
9432,
13,
198,
220,
220,
220,
220,
220,
220,
220,
300,
79,
13,
1084,
48439,
62,
15805,
82,
62,
15252,
425,
13,
2617,
62,
1073,
16814,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
22554,
62,
3672,
6816,
11,
2116,
13,
35350,
62,
3672,
6816,
62,
15805,
198,
220,
220,
220,
220,
220,
220,
220,
1267,
198,
220,
220,
220,
220,
220,
220,
220,
300,
79,
13,
1084,
48439,
62,
15805,
82,
62,
15252,
425,
13,
2617,
62,
1073,
16814,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
10136,
62,
3672,
6816,
11,
2116,
13,
10136,
62,
3672,
6816,
62,
15805,
198,
220,
220,
220,
220,
220,
220,
220,
1267,
198,
220,
220,
220,
220,
220,
220,
220,
300,
79,
13,
1084,
48439,
62,
15805,
82,
62,
15252,
425,
13,
2617,
62,
1073,
16814,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
6381,
10136,
62,
3672,
6816,
11,
2116,
13,
6381,
10136,
62,
3672,
6816,
62,
15805,
198,
220,
220,
220,
220,
220,
220,
220,
1267,
628,
220,
220,
220,
220,
220,
220,
220,
664,
62,
35350,
62,
22554,
62,
25641,
2977,
796,
2116,
13,
8344,
62,
35350,
13,
22554,
62,
25641,
2977,
198,
220,
220,
220,
220,
220,
220,
220,
645,
62,
8344,
62,
35350,
62,
22554,
62,
25641,
2977,
796,
2116,
13,
3919,
62,
8344,
62,
35350,
13,
22554,
62,
25641,
2977,
628,
220,
220,
220,
220,
220,
220,
220,
329,
256,
287,
300,
79,
13,
2435,
62,
9630,
62,
2676,
540,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1303,
48987,
1438,
6816,
318,
18189,
2160,
7,
301,
1850,
62,
27160,
38381,
83,
4083,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1438,
6816,
62,
1102,
2536,
2913,
796,
300,
79,
13,
1102,
2536,
2913,
7,
15,
13,
15,
11,
300,
79,
13,
82,
14375,
13,
10745,
6269,
28955,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1438,
6816,
62,
1102,
2536,
2913,
13,
2617,
62,
1073,
16814,
7,
944,
13,
22554,
62,
3672,
6816,
11,
352,
13,
15,
8,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1438,
6816,
62,
1102,
2536,
2913,
13,
2617,
62,
1073,
16814,
7,
8344,
62,
35350,
62,
22554,
62,
25641,
2977,
58,
83,
4357,
532,
16,
13,
15,
8,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1438,
6816,
62,
1102,
2536,
2913,
13,
2617,
62,
1073,
16814,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
645,
62,
8344,
62,
35350,
62,
22554,
62,
25641,
2977,
58,
83,
4357,
532,
16,
13,
15,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1267,
628,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
664,
62,
35350,
62,
10136,
62,
25641,
2977,
796,
2116,
13,
8344,
62,
35350,
13,
82,
676,
13,
22355,
75,
501,
62,
25641,
2977,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
645,
62,
8344,
62,
35350,
62,
10136,
62,
25641,
2977,
796,
357,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
3919,
62,
8344,
62,
35350,
13,
82,
676,
13,
22355,
75,
501,
62,
25641,
2977,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1267,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
664,
62,
35350,
62,
6381,
10136,
62,
25641,
2977,
796,
357,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
8344,
62,
35350,
13,
10459,
13,
22355,
75,
501,
62,
25641,
2977,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1267,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
645,
62,
8344,
62,
35350,
62,
6381,
10136,
62,
25641,
2977,
796,
357,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
3919,
62,
8344,
62,
35350,
13,
10459,
13,
22355,
75,
501,
62,
25641,
2977,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1267,
628,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
3509,
62,
10136,
62,
1102,
2536,
2913,
796,
300,
79,
13,
1102,
2536,
2913,
7,
15,
13,
15,
11,
300,
79,
13,
82,
14375,
13,
10745,
6269,
28955,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
3509,
62,
10136,
62,
1102,
2536,
2913,
13,
2617,
62,
1073,
16814,
7,
944,
13,
10136,
62,
3672,
6816,
11,
352,
13,
15,
8,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
3509,
62,
10136,
62,
1102,
2536,
2913,
13,
2617,
62,
1073,
16814,
7,
8344,
62,
35350,
62,
10136,
62,
25641,
2977,
58,
83,
4357,
532,
16,
13,
15,
8,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
3509,
62,
10136,
62,
1102,
2536,
2913,
13,
2617,
62,
1073,
16814,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
645,
62,
8344,
62,
35350,
62,
10136,
62,
25641,
2977,
58,
83,
4357,
532,
16,
13,
15,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1267,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
3509,
62,
10136,
62,
1102,
2536,
2913,
13,
2617,
62,
1073,
16814,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
664,
62,
35350,
62,
6381,
10136,
62,
25641,
2977,
58,
83,
4357,
352,
13,
15,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1267,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
3509,
62,
10136,
62,
1102,
2536,
2913,
13,
2617,
62,
1073,
16814,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
645,
62,
8344,
62,
35350,
62,
6381,
10136,
62,
25641,
2977,
58,
83,
4357,
352,
13,
15,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1267,
628,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
3509,
62,
6381,
10136,
62,
1102,
2536,
2913,
796,
300,
79,
13,
1102,
2536,
2913,
7,
15,
13,
15,
11,
300,
79,
13,
82,
14375,
13,
10745,
6269,
28955,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
3509,
62,
6381,
10136,
62,
1102,
2536,
2913,
13,
2617,
62,
1073,
16814,
7,
944,
13,
6381,
10136,
62,
3672,
6816,
11,
352,
13,
15,
8,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
3509,
62,
6381,
10136,
62,
1102,
2536,
2913,
13,
2617,
62,
1073,
16814,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
664,
62,
35350,
62,
10136,
62,
25641,
2977,
58,
83,
4357,
352,
13,
15,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1267,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
3509,
62,
6381,
10136,
62,
1102,
2536,
2913,
13,
2617,
62,
1073,
16814,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
645,
62,
8344,
62,
35350,
62,
10136,
62,
25641,
2977,
58,
83,
4357,
352,
13,
15,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1267,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
3509,
62,
6381,
10136,
62,
1102,
2536,
2913,
13,
2617,
62,
1073,
16814,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
664,
62,
35350,
62,
6381,
10136,
62,
25641,
2977,
58,
83,
4357,
532,
16,
13,
15,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1267,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
3509,
62,
6381,
10136,
62,
1102,
2536,
2913,
13,
2617,
62,
1073,
16814,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
645,
62,
8344,
62,
35350,
62,
6381,
10136,
62,
25641,
2977,
58,
83,
4357,
532,
16,
13,
15,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1267,
628,
220,
220,
220,
825,
651,
62,
3672,
6816,
62,
82,
2122,
62,
8367,
7,
944,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
38,
1039,
262,
14174,
1430,
1540,
332,
2482,
329,
1438,
6816,
13,
628,
220,
220,
220,
220,
220,
220,
220,
12039,
307,
1444,
706,
300,
79,
13,
82,
6442,
3419,
284,
4155,
1540,
332,
468,
6105,
198,
220,
220,
220,
220,
220,
220,
220,
6718,
2004,
290,
468,
7560,
2482,
13,
628,
220,
220,
220,
220,
220,
220,
220,
7567,
2696,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
43160,
12331,
25,
1002,
1444,
878,
44800,
15167,
29869,
13,
82,
6442,
22446,
628,
220,
220,
220,
220,
220,
220,
220,
16409,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
48436,
1988,
10200,
16019,
1438,
6816,
1988,
13,
628,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
611,
2116,
13,
35350,
62,
3672,
6816,
62,
15805,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1438,
6816,
62,
45286,
796,
2116,
13,
22554,
62,
3672,
6816,
628,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
611,
1438,
6816,
62,
45286,
318,
6045,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
5298,
43160,
12331,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
366,
3855,
62,
3672,
6816,
62,
82,
2122,
62,
8367,
1444,
878,
8494,
3419,
526,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1267,
628,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1441,
1438,
6816,
62,
45286,
13,
82,
2122,
62,
8367,
3419,
198,
220,
220,
220,
220,
220,
220,
220,
2073,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1441,
3509,
7,
944,
13,
1136,
62,
82,
2122,
62,
27160,
28955,
628,
198,
4871,
4808,
41339,
8291,
3411,
7,
41339,
7416,
2599,
198,
220,
220,
220,
37227,
2484,
15318,
829,
1176,
422,
530,
640,
12,
11340,
284,
1194,
526,
15931,
628,
220,
220,
220,
825,
11593,
15003,
834,
7,
198,
220,
220,
220,
220,
220,
220,
220,
2116,
11,
198,
220,
220,
220,
220,
220,
220,
220,
1438,
11,
198,
220,
220,
220,
220,
220,
220,
220,
1438,
6816,
62,
20850,
62,
15805,
11,
198,
220,
220,
220,
220,
220,
220,
220,
2723,
62,
25928,
62,
36996,
62,
312,
28,
15,
11,
198,
220,
220,
220,
220,
220,
220,
220,
14595,
62,
25928,
62,
36996,
62,
312,
28,
16,
11,
198,
220,
220,
220,
220,
220,
220,
220,
3509,
62,
6477,
10779,
16,
13,
15,
11,
198,
220,
220,
220,
220,
220,
220,
220,
9332,
28,
16,
13,
15,
11,
198,
220,
220,
220,
15179,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
31768,
2163,
13,
628,
220,
220,
220,
220,
220,
220,
220,
943,
14542,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1438,
25,
10903,
1438,
286,
262,
2134,
13,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1438,
6816,
62,
20850,
62,
15805,
25,
357,
22468,
8,
6446,
284,
1382,
257,
4326,
286,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
11478,
5339,
13,
220,
7198,
1220,
8336,
707,
1078,
286,
5339,
8,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2723,
62,
25928,
62,
36996,
62,
312,
25,
1052,
493,
31577,
543,
10706,
62,
36996,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1176,
3011,
1176,
2087,
13,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
14595,
62,
25928,
62,
36996,
62,
312,
25,
1052,
493,
31577,
543,
10706,
62,
36996,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1176,
3011,
1176,
13284,
20216,
13,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
3509,
62,
6477,
25,
357,
22468,
8,
32233,
22246,
1176,
543,
460,
307,
18307,
13,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
357,
42672,
707,
1078,
737,
5345,
1279,
657,
611,
612,
318,
645,
4179,
13,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
9332,
25,
357,
22468,
8,
8064,
286,
703,
881,
1176,
3011,
3888,
530,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
10706,
62,
36996,
284,
262,
584,
10706,
62,
36996,
13,
21699,
540,
3815,
389,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
657,
13,
1279,
9332,
1279,
352,
13,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
628,
220,
220,
220,
220,
220,
220,
220,
2208,
28264,
41339,
8291,
3411,
11,
2116,
737,
834,
15003,
834,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1438,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1438,
6816,
62,
20850,
62,
15805,
28,
3672,
6816,
62,
20850,
62,
15805,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
7885,
62,
20850,
62,
15805,
28,
15,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
10706,
62,
36996,
62,
312,
28,
10459,
62,
25928,
62,
36996,
62,
312,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
3509,
62,
6477,
28,
9806,
62,
6477,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
3509,
62,
22554,
10779,
16,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
763,
17,
62,
525,
62,
9509,
8143,
62,
22554,
28,
15,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1176,
62,
1073,
16814,
28,
45888,
11,
198,
220,
220,
220,
220,
220,
220,
220,
1267,
628,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
82,
676,
62,
25928,
62,
36996,
62,
312,
796,
14595,
62,
25928,
62,
36996,
62,
312,
628,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
82,
14375,
796,
4808,
41339,
7416,
49354,
540,
50,
14375,
7,
944,
8,
628,
220,
220,
220,
825,
17425,
62,
34431,
62,
25641,
2977,
62,
392,
62,
1102,
2536,
6003,
7,
944,
11,
300,
79,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
37835,
533,
300,
79,
9633,
11,
290,
900,
17778,
13,
628,
220,
220,
220,
220,
220,
220,
220,
943,
14542,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
300,
79,
25,
44800,
15167,
29869,
11,
4909,
300,
79,
1540,
332,
290,
17778,
13,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
628,
220,
220,
220,
220,
220,
220,
220,
2208,
28264,
41339,
8291,
3411,
11,
2116,
737,
11250,
495,
62,
34431,
62,
25641,
2977,
62,
392,
62,
1102,
2536,
6003,
7,
34431,
8,
628,
220,
220,
220,
220,
220,
220,
220,
1303,
33141,
1482,
2536,
6003,
13,
198,
220,
220,
220,
220,
220,
220,
220,
329,
256,
11,
1401,
287,
27056,
378,
7,
944,
13,
22355,
75,
501,
62,
25641,
2977,
2599,
628,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
14595,
62,
312,
796,
2116,
13,
82,
676,
62,
25928,
62,
36996,
62,
312,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2723,
62,
312,
796,
2116,
13,
25928,
62,
36996,
62,
312,
628,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1303,
15935,
262,
2208,
12,
4871,
318,
47015,
287,
2723,
62,
25928,
62,
36996,
62,
312,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1303,
14595,
340,
422,
14595,
62,
25928,
62,
36996,
62,
312,
13,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
300,
79,
13,
5936,
3760,
62,
6477,
62,
1102,
2536,
2913,
58,
82,
676,
62,
312,
7131,
83,
4083,
2617,
62,
1073,
16814,
7,
7785,
11,
532,
16,
13,
15,
8,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
611,
2116,
13,
271,
62,
81,
862,
62,
10459,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
300,
79,
13,
81,
862,
62,
10459,
62,
1102,
2536,
6003,
58,
82,
676,
62,
312,
7131,
83,
4083,
2617,
62,
1073,
16814,
7,
7785,
11,
532,
16,
13,
15,
8,
628,
220,
220,
220,
825,
1281,
62,
14681,
7,
944,
11,
300,
79,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
10260,
300,
79,
1281,
62,
36948,
1255,
9633,
13,
628,
220,
220,
220,
220,
220,
220,
220,
770,
318,
1760,
523,
326,
34182,
1366,
8794,
460,
307,
1760,
319,
371,
3705,
878,
198,
220,
220,
220,
220,
220,
220,
220,
8024,
2482,
13,
628,
220,
220,
220,
220,
220,
220,
220,
943,
14542,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
300,
79,
25,
383,
44800,
15167,
29869,
810,
262,
1281,
7587,
9633,
26412,
13,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
1303,
14435,
2723,
1281,
62,
14681,
198,
220,
220,
220,
220,
220,
220,
220,
2208,
28264,
41339,
8291,
3411,
11,
2116,
737,
7353,
62,
14681,
7,
34431,
8,
628,
220,
220,
220,
220,
220,
220,
220,
1303,
311,
676,
1281,
62,
14681,
198,
220,
220,
220,
220,
220,
220,
220,
14595,
62,
312,
796,
2116,
13,
82,
676,
62,
25928,
62,
36996,
62,
312,
198,
220,
220,
220,
220,
220,
220,
220,
611,
300,
79,
13,
81,
862,
62,
25067,
1875,
657,
13,
15,
290,
2116,
13,
271,
62,
81,
862,
62,
10459,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
300,
79,
13,
81,
862,
62,
23350,
58,
82,
676,
62,
312,
60,
48185,
2116,
13,
1136,
62,
82,
2122,
62,
27160,
3419,
198,
220,
220,
220,
220,
220,
220,
220,
2073,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
300,
79,
13,
13159,
62,
81,
862,
62,
23350,
58,
82,
676,
62,
312,
60,
48185,
2116,
13,
1136,
62,
82,
2122,
62,
27160,
3419,
628,
198,
4871,
24846,
8291,
3411,
7,
15252,
2599,
198,
220,
220,
220,
37227,
8291,
24883,
1176,
8406,
4154,
453,
1022,
734,
10706,
62,
2301,
507,
13,
628,
220,
220,
220,
1629,
7071,
1241,
11,
39573,
422,
3814,
12,
76,
284,
3814,
12,
77,
318,
198,
220,
220,
220,
10411,
284,
39573,
422,
3814,
12,
77,
284,
3814,
12,
76,
13,
628,
220,
220,
220,
49213,
25,
198,
220,
220,
220,
220,
220,
1438,
25,
357,
2536,
8,
1438,
286,
262,
2134,
13,
198,
220,
220,
220,
220,
220,
1438,
6816,
62,
20850,
62,
15805,
25,
357,
22468,
8,
6446,
284,
1382,
257,
4326,
286,
198,
220,
220,
220,
220,
220,
220,
220,
11478,
5339,
13,
220,
7198,
1220,
8336,
707,
1078,
286,
5339,
8,
198,
220,
220,
220,
220,
220,
10706,
62,
36996,
62,
312,
62,
64,
25,
1052,
493,
31577,
530,
10706,
62,
36996,
11478,
198,
220,
220,
220,
220,
220,
220,
220,
5651,
385,
198,
220,
220,
220,
220,
220,
10706,
62,
36996,
62,
312,
62,
65,
25,
1052,
493,
31577,
257,
1180,
10706,
62,
36996,
198,
220,
220,
220,
220,
220,
220,
220,
11478,
5651,
385,
198,
220,
220,
220,
220,
220,
3509,
62,
6477,
25,
357,
22468,
8,
32233,
22246,
1176,
543,
460,
307,
18307,
13,
198,
220,
220,
220,
220,
220,
220,
220,
357,
42672,
707,
1078,
737,
5345,
1279,
657,
611,
612,
318,
645,
4179,
13,
198,
220,
220,
220,
220,
220,
9332,
25,
357,
22468,
8,
8064,
286,
703,
881,
1176,
3011,
3888,
530,
198,
220,
220,
220,
220,
220,
220,
220,
10706,
62,
36996,
284,
262,
584,
10706,
62,
36996,
13,
21699,
540,
3815,
389,
198,
220,
220,
220,
220,
220,
220,
220,
657,
13,
1279,
9332,
1279,
352,
13,
198,
220,
220,
220,
220,
220,
257,
62,
1462,
62,
65,
25,
4808,
41339,
8291,
3411,
2134,
543,
6100,
11841,
1176,
422,
198,
220,
220,
220,
220,
220,
220,
220,
10706,
62,
36996,
62,
64,
284,
10706,
62,
36996,
62,
65,
198,
220,
220,
220,
220,
220,
275,
62,
1462,
62,
64,
25,
4808,
41339,
8291,
3411,
2134,
543,
6100,
11841,
1176,
422,
198,
220,
220,
220,
220,
220,
220,
220,
10706,
62,
36996,
62,
65,
284,
10706,
62,
36996,
62,
64,
198,
220,
220,
220,
220,
220,
664,
62,
64,
62,
1462,
62,
65,
25,
4808,
41339,
8291,
3411,
2134,
543,
6100,
3424,
1176,
198,
220,
220,
220,
220,
220,
220,
220,
422,
10706,
62,
36996,
62,
64,
284,
10706,
62,
36996,
62,
65,
198,
220,
220,
220,
220,
220,
664,
62,
65,
62,
1462,
62,
64,
25,
4808,
41339,
8291,
3411,
2134,
543,
6100,
3424,
1176,
198,
220,
220,
220,
220,
220,
220,
220,
422,
10706,
62,
36996,
62,
65,
284,
10706,
62,
36996,
62,
64,
198,
220,
220,
220,
37227,
628,
220,
220,
220,
825,
17425,
62,
34431,
62,
25641,
2977,
62,
392,
62,
1102,
2536,
6003,
7,
944,
11,
300,
79,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
37835,
533,
300,
79,
9633,
11,
290,
900,
17778,
13,
628,
220,
220,
220,
220,
220,
220,
220,
943,
14542,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
300,
79,
25,
44800,
15167,
29869,
11,
4909,
300,
79,
1540,
332,
290,
17778,
13,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
628,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
64,
62,
1462,
62,
65,
796,
4808,
41339,
8291,
3411,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
3672,
1343,
366,
257,
62,
1462,
62,
65,
1600,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
657,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
25928,
62,
36996,
62,
312,
62,
65,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
25928,
62,
36996,
62,
312,
62,
64,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
9806,
62,
6477,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
45888,
11,
198,
220,
220,
220,
220,
220,
220,
220,
1267,
628,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
65,
62,
1462,
62,
64,
796,
4808,
41339,
8291,
3411,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
3672,
1343,
366,
275,
62,
1462,
62,
64,
1600,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
657,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
25928,
62,
36996,
62,
312,
62,
64,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
25928,
62,
36996,
62,
312,
62,
65,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
9806,
62,
6477,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
45888,
11,
198,
220,
220,
220,
220,
220,
220,
220,
1267,
628,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
8344,
62,
64,
62,
1462,
62,
65,
796,
4808,
41339,
8291,
3411,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
3672,
1343,
366,
664,
257,
62,
1462,
62,
65,
1600,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
657,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
25928,
62,
36996,
62,
312,
62,
65,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
25928,
62,
36996,
62,
312,
62,
64,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
9806,
62,
6477,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
45888,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
318,
62,
81,
862,
28,
17821,
11,
198,
220,
220,
220,
220,
220,
220,
220,
1267,
628,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
8344,
62,
65,
62,
1462,
62,
64,
796,
4808,
41339,
8291,
3411,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
3672,
1343,
366,
664,
275,
62,
1462,
62,
64,
1600,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
657,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
25928,
62,
36996,
62,
312,
62,
64,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
25928,
62,
36996,
62,
312,
62,
65,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
9806,
62,
6477,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
45888,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
318,
62,
81,
862,
28,
17821,
11,
198,
220,
220,
220,
220,
220,
220,
220,
1267,
628,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
64,
62,
1462,
62,
65,
13,
11250,
495,
62,
34431,
62,
25641,
2977,
62,
392,
62,
1102,
2536,
6003,
7,
34431,
8,
198,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
65,
62,
1462,
62,
64,
13,
11250,
495,
62,
34431,
62,
25641,
2977,
62,
392,
62,
1102,
2536,
6003,
7,
34431,
8,
198,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
8344,
62,
64,
62,
1462,
62,
65,
13,
11250,
495,
62,
34431,
62,
25641,
2977,
62,
392,
62,
1102,
2536,
6003,
7,
34431,
8,
198,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
8344,
62,
65,
62,
1462,
62,
64,
13,
11250,
495,
62,
34431,
62,
25641,
2977,
62,
392,
62,
1102,
2536,
6003,
7,
34431,
8,
628,
220,
220,
220,
220,
220,
220,
220,
1303,
6889,
1654,
1438,
6816,
18189,
2160,
7,
64,
62,
1462,
62,
65,
8,
290,
1438,
6816,
18189,
2160,
7,
65,
62,
1462,
62,
64,
8,
628,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
3672,
6816,
62,
45286,
796,
300,
79,
13,
32446,
533,
62,
3672,
6816,
62,
45286,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
3672,
11,
36521,
67,
62,
4,
67,
1,
4064,
357,
944,
13,
25928,
62,
36996,
62,
312,
62,
64,
11,
2116,
13,
25928,
62,
36996,
62,
312,
62,
65,
8,
198,
220,
220,
220,
220,
220,
220,
220,
1267,
628,
220,
220,
220,
220,
220,
220,
220,
300,
79,
13,
1084,
48439,
62,
15805,
82,
62,
15252,
425,
13,
2617,
62,
1073,
16814,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
3672,
6816,
62,
45286,
11,
2116,
13,
3672,
6816,
62,
20850,
62,
15805,
198,
220,
220,
220,
220,
220,
220,
220,
1267,
628,
220,
220,
220,
220,
220,
220,
220,
329,
256,
287,
300,
79,
13,
2435,
62,
9630,
62,
2676,
540,
25,
628,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1303,
1438,
6816,
18189,
257,
62,
1462,
62,
65,
58,
83,
60,
1343,
664,
62,
64,
62,
1462,
62,
65,
58,
83,
60,
532,
275,
62,
1462,
62,
64,
58,
83,
60,
532,
664,
62,
65,
62,
1462,
62,
64,
58,
83,
60,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
257,
62,
1462,
62,
65,
62,
1102,
2536,
2913,
796,
300,
79,
13,
1102,
2536,
2913,
7,
15,
13,
15,
11,
300,
79,
13,
82,
14375,
13,
10745,
6269,
28955,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
257,
62,
1462,
62,
65,
62,
1102,
2536,
2913,
13,
2617,
62,
1073,
16814,
7,
944,
13,
3672,
6816,
62,
45286,
11,
352,
13,
15,
8,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
257,
62,
1462,
62,
65,
62,
1102,
2536,
2913,
13,
2617,
62,
1073,
16814,
7,
944,
13,
64,
62,
1462,
62,
65,
13,
22355,
75,
501,
62,
25641,
2977,
58,
83,
4357,
532,
16,
13,
15,
8,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
257,
62,
1462,
62,
65,
62,
1102,
2536,
2913,
13,
2617,
62,
1073,
16814,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
8344,
62,
64,
62,
1462,
62,
65,
13,
22355,
75,
501,
62,
25641,
2977,
58,
83,
4357,
532,
16,
13,
15,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1267,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
257,
62,
1462,
62,
65,
62,
1102,
2536,
2913,
13,
2617,
62,
1073,
16814,
7,
944,
13,
65,
62,
1462,
62,
64,
13,
22355,
75,
501,
62,
25641,
2977,
58,
83,
4357,
352,
13,
15,
8,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
257,
62,
1462,
62,
65,
62,
1102,
2536,
2913,
13,
2617,
62,
1073,
16814,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
8344,
62,
65,
62,
1462,
62,
64,
13,
22355,
75,
501,
62,
25641,
2977,
58,
83,
4357,
352,
13,
15,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1267,
628,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1303,
1438,
6816,
18189,
275,
62,
1462,
62,
64,
58,
83,
60,
1343,
664,
62,
65,
62,
1462,
62,
64,
58,
83,
60,
532,
257,
62,
1462,
62,
65,
58,
83,
60,
532,
664,
62,
64,
62,
1462,
62,
65,
58,
83,
60,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
275,
62,
1462,
62,
64,
62,
1102,
2536,
2913,
796,
300,
79,
13,
1102,
2536,
2913,
7,
15,
13,
15,
11,
300,
79,
13,
82,
14375,
13,
10745,
6269,
28955,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
275,
62,
1462,
62,
64,
62,
1102,
2536,
2913,
13,
2617,
62,
1073,
16814,
7,
944,
13,
3672,
6816,
62,
45286,
11,
352,
13,
15,
8,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
275,
62,
1462,
62,
64,
62,
1102,
2536,
2913,
13,
2617,
62,
1073,
16814,
7,
944,
13,
65,
62,
1462,
62,
64,
13,
22355,
75,
501,
62,
25641,
2977,
58,
83,
4357,
532,
16,
13,
15,
8,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
275,
62,
1462,
62,
64,
62,
1102,
2536,
2913,
13,
2617,
62,
1073,
16814,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
8344,
62,
65,
62,
1462,
62,
64,
13,
22355,
75,
501,
62,
25641,
2977,
58,
83,
4357,
532,
16,
13,
15,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1267,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
275,
62,
1462,
62,
64,
62,
1102,
2536,
2913,
13,
2617,
62,
1073,
16814,
7,
944,
13,
64,
62,
1462,
62,
65,
13,
22355,
75,
501,
62,
25641,
2977,
58,
83,
4357,
352,
13,
15,
8,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
275,
62,
1462,
62,
64,
62,
1102,
2536,
2913,
13,
2617,
62,
1073,
16814,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
8344,
62,
64,
62,
1462,
62,
65,
13,
22355,
75,
501,
62,
25641,
2977,
58,
83,
4357,
352,
13,
15,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1267,
628,
220,
220,
220,
825,
1281,
62,
14681,
7,
944,
11,
300,
79,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
10260,
300,
79,
1281,
62,
36948,
1255,
9633,
13,
628,
220,
220,
220,
220,
220,
220,
220,
770,
318,
1760,
523,
326,
34182,
1366,
8794,
460,
307,
1760,
319,
371,
3705,
878,
198,
220,
220,
220,
220,
220,
220,
220,
8024,
2482,
13,
628,
220,
220,
220,
220,
220,
220,
220,
943,
14542,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
300,
79,
25,
383,
44800,
15167,
29869,
810,
262,
1281,
7587,
9633,
26412,
13,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
628,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
64,
62,
1462,
62,
65,
13,
7353,
62,
14681,
7,
34431,
8,
198,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
65,
62,
1462,
62,
64,
13,
7353,
62,
14681,
7,
34431,
8,
198,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
8344,
62,
64,
62,
1462,
62,
65,
13,
7353,
62,
14681,
7,
34431,
8,
198,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
8344,
62,
65,
62,
1462,
62,
64,
13,
7353,
62,
14681,
7,
34431,
8,
628,
220,
220,
220,
825,
651,
62,
3672,
6816,
62,
82,
2122,
62,
8367,
7,
944,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
38,
1039,
262,
14174,
1430,
1540,
332,
2482,
329,
1438,
6816,
13,
628,
220,
220,
220,
220,
220,
220,
220,
12039,
307,
1444,
706,
300,
79,
13,
82,
6442,
3419,
284,
4155,
1540,
332,
468,
6105,
198,
220,
220,
220,
220,
220,
220,
220,
6718,
2004,
290,
468,
7560,
2482,
13,
628,
220,
220,
220,
220,
220,
220,
220,
7567,
2696,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
43160,
12331,
25,
1002,
1444,
878,
44800,
15167,
29869,
13,
82,
6442,
22446,
628,
220,
220,
220,
220,
220,
220,
220,
16409,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
48436,
1988,
10200,
16019,
1438,
6816,
1988,
13,
628,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
1438,
6816,
62,
45286,
796,
2116,
13,
3672,
6816,
62,
45286,
628,
220,
220,
220,
220,
220,
220,
220,
611,
1438,
6816,
62,
45286,
318,
6045,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
5298,
43160,
12331,
7203,
3855,
62,
3672,
6816,
62,
82,
2122,
62,
8367,
1444,
878,
8494,
3419,
19570,
628,
220,
220,
220,
220,
220,
220,
220,
1441,
1438,
6816,
62,
45286,
13,
82,
2122,
62,
8367,
3419,
628,
198,
4871,
44800,
15167,
29869,
7,
15252,
2599,
198,
220,
220,
220,
37227,
6310,
17096,
689,
290,
20314,
284,
18470,
4294,
332,
13,
628,
220,
220,
220,
17934,
29566,
25,
198,
220,
220,
220,
20768,
1096,
25,
300,
79,
796,
44800,
15167,
29869,
3419,
198,
220,
220,
220,
3060,
5563,
25,
198,
220,
220,
220,
220,
220,
300,
79,
13,
2860,
62,
9536,
1746,
7,
27,
41339,
42782,
43734,
198,
220,
220,
220,
220,
220,
300,
79,
13,
2860,
62,
82,
2203,
7,
27,
41339,
7416,
43734,
198,
220,
220,
220,
220,
220,
300,
79,
13,
2860,
62,
7645,
8481,
7,
27,
41339,
8291,
3411,
43734,
198,
220,
220,
220,
220,
220,
300,
79,
13,
82,
6442,
3419,
628,
220,
220,
220,
49213,
25,
198,
220,
220,
220,
220,
220,
6588,
62,
19290,
25,
383,
2033,
284,
1687,
352,
4326,
286,
763,
17,
8971,
13,
198,
220,
220,
220,
220,
220,
1575,
62,
1659,
62,
26316,
25,
383,
2033,
284,
29162,
7885,
3484,
416,
284,
198,
220,
220,
220,
220,
220,
220,
220,
787,
24169,
3484,
290,
5969,
3484,
13975,
13,
198,
220,
220,
220,
220,
220,
16545,
25,
640,
12,
25076,
16545,
41497,
416,
1438,
543,
3975,
284,
198,
220,
220,
220,
220,
220,
220,
220,
24846,
11522,
1746,
290,
24846,
15419,
49354,
540,
21188,
13,
198,
220,
220,
220,
220,
220,
1271,
62,
1659,
62,
22355,
677,
274,
25,
493,
10200,
530,
1661,
75,
501,
583,
7034,
6376,
13,
198,
220,
220,
220,
220,
220,
640,
62,
9630,
62,
2676,
540,
25,
317,
2829,
493,
2837,
422,
657,
532,
1271,
62,
1659,
62,
22355,
677,
274,
13,
628,
220,
220,
220,
220,
220,
1482,
2536,
6003,
25,
198,
220,
220,
220,
220,
220,
220,
220,
45075,
62,
6477,
62,
1102,
2536,
2913,
25,
360,
713,
1994,
276,
416,
10706,
62,
36996,
62,
312,
13,
11052,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
318,
257,
1351,
286,
18470,
1482,
2536,
6003,
543,
19047,
326,
1176,
1875,
3512,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
379,
477,
1661,
287,
477,
10706,
62,
2301,
507,
13,
628,
220,
220,
220,
220,
220,
220,
220,
17775,
62,
15805,
82,
62,
15252,
425,
25,
383,
18470,
37092,
543,
318,
284,
17775,
3484,
13,
628,
220,
220,
220,
220,
220,
220,
220,
374,
862,
62,
10459,
62,
1102,
2536,
6003,
25,
360,
713,
1994,
276,
416,
10706,
62,
36996,
62,
312,
13,
11052,
318,
257,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1351,
286,
18470,
1482,
2536,
6003,
543,
19047,
326,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
374,
862,
62,
43082,
58,
25928,
62,
36996,
11,
256,
60,
19841,
2160,
7,
81,
862,
62,
82,
2203,
58,
25928,
62,
36996,
11,
256,
12962,
628,
220,
220,
220,
220,
220,
220,
220,
374,
862,
62,
28550,
62,
1102,
2536,
6003,
25,
360,
713,
1994,
276,
416,
10706,
62,
36996,
62,
312,
13,
220,
11052,
318,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
257,
1351,
286,
18470,
1482,
2536,
6003,
543,
19047,
326,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
374,
862,
62,
43082,
58,
25928,
62,
36996,
11,
256,
60,
19841,
3512,
58,
25928,
62,
36996,
11,
256,
60,
628,
220,
220,
220,
220,
220,
371,
3705,
15965,
2977,
25,
198,
220,
220,
220,
220,
220,
220,
220,
374,
862,
62,
43082,
62,
25641,
2977,
25,
360,
713,
2134,
1994,
276,
416,
10706,
62,
36996,
62,
312,
13,
220,
11052,
318,
257,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1351,
286,
374,
862,
62,
43082,
58,
25928,
62,
36996,
11,
256,
60,
9633,
329,
26019,
374,
862,
13,
628,
220,
220,
220,
220,
220,
2947,
28403,
15965,
2977,
13,
220,
955,
17128,
706,
18470,
6718,
3212,
25,
198,
220,
220,
220,
220,
220,
220,
220,
374,
862,
62,
23350,
25,
360,
713,
2134,
1994,
276,
416,
10706,
62,
36996,
62,
312,
13,
220,
11052,
318,
2160,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
357,
41339,
7416,
62,
6477,
58,
25928,
62,
36996,
11,
256,
12962,
286,
477,
374,
862,
4237,
13,
628,
220,
220,
220,
220,
220,
220,
220,
1729,
62,
81,
862,
62,
23350,
25,
360,
713,
2134,
1994,
276,
416,
10706,
62,
36996,
62,
312,
13,
220,
11052,
318,
2160,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
357,
41339,
7416,
62,
6477,
58,
25928,
62,
36996,
11,
256,
12962,
286,
477,
1729,
62,
81,
862,
4237,
13,
628,
220,
220,
220,
220,
220,
220,
220,
12328,
62,
28550,
25,
360,
713,
2134,
1994,
276,
416,
10706,
62,
36996,
62,
312,
13,
220,
11052,
318,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
34479,
58,
25928,
62,
36996,
11,
256,
60,
628,
220,
220,
220,
220,
220,
220,
220,
374,
862,
62,
43082,
62,
27160,
25,
360,
713,
2134,
1994,
276,
416,
10706,
62,
36996,
62,
312,
13,
220,
11052,
318,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
374,
862,
62,
43082,
13,
8367,
58,
25928,
62,
36996,
11,
256,
60,
628,
220,
220,
220,
220,
220,
24846,
26632,
25,
198,
220,
220,
220,
220,
220,
220,
220,
8665,
25,
317,
1351,
286,
24846,
42782,
7,
82,
737,
198,
220,
220,
220,
220,
220,
220,
220,
4237,
25,
317,
1351,
286,
24846,
7416,
7,
82,
737,
198,
220,
220,
220,
220,
220,
220,
220,
6143,
25,
317,
1351,
286,
24846,
31425,
7,
82,
737,
198,
220,
220,
220,
220,
220,
220,
220,
11478,
25,
317,
1351,
286,
24846,
8291,
3411,
7,
82,
737,
628,
220,
220,
220,
220,
220,
1540,
332,
25,
383,
12908,
12972,
29988,
489,
79,
13,
50,
14375,
13,
198,
220,
220,
220,
220,
220,
1540,
332,
62,
3866,
16005,
25,
317,
12178,
10200,
6108,
15440,
286,
262,
1540,
332,
13,
198,
220,
220,
220,
37227,
628,
220,
220,
220,
825,
11593,
15003,
834,
7,
944,
11,
16545,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
24243,
4340,
18470,
43101,
13,
628,
220,
220,
220,
220,
220,
220,
220,
943,
14542,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
16545,
25,
3862,
12,
25076,
19798,
292,
1366,
14535,
16545,
41497,
416,
1438,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
543,
3975,
284,
24846,
11522,
1746,
290,
24846,
15419,
49354,
540,
21188,
13,
628,
220,
220,
220,
220,
220,
220,
220,
7567,
2696,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
11052,
12331,
25,
1002,
597,
1988,
287,
16545,
318,
1279,
657,
393,
18008,
1220,
6045,
13,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
628,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
29255,
62,
19290,
796,
657,
13,
15,
198,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
15805,
62,
1659,
62,
26316,
796,
352,
13,
15,
198,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
81,
862,
62,
25067,
796,
657,
13,
15,
628,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
5577,
2915,
796,
16545,
628,
220,
220,
220,
220,
220,
220,
220,
1303,
1482,
2536,
6003,
198,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
5936,
3760,
62,
6477,
62,
1102,
2536,
2913,
796,
23884,
198,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
1084,
48439,
62,
15805,
82,
62,
15252,
425,
796,
6045,
628,
220,
220,
220,
220,
220,
220,
220,
1303,
371,
3705,
1482,
2536,
6003,
198,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
81,
862,
62,
10459,
62,
1102,
2536,
6003,
796,
23884,
198,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
81,
862,
62,
28550,
62,
1102,
2536,
6003,
796,
23884,
628,
220,
220,
220,
220,
220,
220,
220,
1303,
371,
3705,
15965,
2977,
198,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
81,
862,
62,
43082,
62,
25641,
2977,
796,
23884,
628,
220,
220,
220,
220,
220,
220,
220,
1303,
2947,
28403,
15965,
2977,
198,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
81,
862,
62,
23350,
796,
23884,
198,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
13159,
62,
81,
862,
62,
23350,
796,
23884,
198,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
29117,
62,
28550,
796,
23884,
198,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
23350,
62,
28550,
796,
657,
198,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
81,
862,
62,
28550,
796,
657,
628,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
81,
862,
62,
43082,
62,
27160,
796,
23884,
628,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
9536,
1746,
796,
17635,
198,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
82,
2203,
796,
17635,
198,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
35350,
796,
17635,
198,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
7645,
3411,
796,
17635,
628,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
82,
14375,
796,
6045,
198,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
82,
14375,
62,
3866,
16005,
796,
352,
68,
12,
18,
628,
220,
220,
220,
220,
220,
220,
220,
1303,
3254,
20540,
16545,
198,
220,
220,
220,
220,
220,
220,
220,
611,
16545,
318,
6045,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
5298,
11052,
12331,
7203,
2949,
16545,
7368,
19570,
628,
220,
220,
220,
220,
220,
220,
220,
611,
16545,
13,
28920,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
5298,
11052,
12331,
7203,
2949,
6060,
287,
4415,
2915,
19570,
628,
220,
220,
220,
220,
220,
220,
220,
611,
16545,
13,
271,
8423,
22446,
27160,
13,
1092,
33529,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
5298,
11052,
12331,
7203,
15404,
2915,
743,
407,
307,
35886,
393,
6045,
4943,
628,
220,
220,
220,
220,
220,
220,
220,
16545,
62,
2528,
62,
15,
796,
16545,
13,
27160,
1279,
657,
198,
220,
220,
220,
220,
220,
220,
220,
611,
16545,
62,
2528,
62,
15,
13,
1092,
33529,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
5298,
11052,
12331,
7203,
15404,
2915,
1276,
407,
307,
1279,
657,
19570,
628,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
17618,
62,
1659,
62,
22355,
677,
274,
796,
18896,
7,
5577,
2915,
8,
198,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
2435,
62,
9630,
62,
2676,
540,
796,
2837,
7,
944,
13,
17618,
62,
1659,
62,
22355,
677,
274,
8,
628,
220,
220,
220,
825,
751,
62,
9536,
1746,
7,
944,
11,
1635,
9536,
1746,
2599,
628,
220,
220,
220,
220,
220,
220,
220,
37227,
4550,
477,
24846,
11522,
1746,
287,
943,
14542,
284,
2116,
13,
9536,
1746,
526,
15931,
198,
220,
220,
220,
220,
220,
220,
220,
329,
288,
287,
8665,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
9536,
1746,
13,
33295,
7,
67,
8,
628,
220,
220,
220,
825,
751,
62,
6381,
17147,
540,
62,
82,
2203,
7,
944,
11,
1635,
82,
2203,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
13414,
1958,
2723,
468,
645,
7034,
3917,
351,
340,
290,
751,
284,
2116,
13,
82,
2203,
13,
628,
220,
220,
220,
220,
220,
220,
220,
943,
14542,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1635,
82,
2203,
25,
14977,
1271,
286,
24846,
21188,
13,
628,
220,
220,
220,
220,
220,
220,
220,
7567,
2696,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
7383,
12331,
25,
611,
8090,
468,
257,
7034,
3917,
351,
340,
543,
561,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
7603,
262,
2723,
373,
1729,
12,
6381,
17147,
540,
2427,
286,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
27965,
540,
13,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
628,
220,
220,
220,
220,
220,
220,
220,
329,
2723,
287,
4237,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
611,
2723,
13,
3672,
287,
2116,
13,
5577,
2915,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
5298,
7383,
12331,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
366,
49354,
540,
8090,
4064,
82,
468,
257,
7034,
3917,
351,
340,
1,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
4064,
357,
10459,
13,
3672,
8,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1267,
628,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2723,
13,
82,
14375,
796,
4808,
41339,
7416,
49354,
540,
50,
14375,
7,
10459,
8,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
82,
2203,
13,
33295,
7,
10459,
8,
628,
220,
220,
220,
825,
751,
62,
77,
623,
8802,
963,
540,
62,
82,
2203,
7,
944,
11,
1635,
82,
2203,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
13414,
1958,
2723,
468,
257,
7034,
3917,
351,
340,
290,
751,
284,
2116,
13,
82,
2203,
13,
628,
220,
220,
220,
220,
220,
220,
220,
943,
14542,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1635,
82,
2203,
25,
14977,
1271,
286,
24846,
21188,
13,
628,
220,
220,
220,
220,
220,
220,
220,
7567,
2696,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
7383,
12331,
25,
611,
8090,
468,
645,
7034,
3917,
351,
340,
543,
561,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
7603,
262,
2723,
373,
27965,
540,
2427,
286,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1729,
12,
6381,
17147,
540,
13,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
628,
220,
220,
220,
220,
220,
220,
220,
329,
2723,
287,
4237,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
611,
2723,
13,
3672,
407,
287,
2116,
13,
5577,
2915,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1900,
62,
82,
2203,
796,
366,
553,
13,
22179,
7,
82,
9741,
7,
944,
13,
5577,
2915,
13,
28665,
82,
4008,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1900,
62,
10459,
62,
8841,
796,
366,
29870,
4237,
389,
37633,
82,
21387,
4064,
1900,
62,
82,
2203,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
5298,
7383,
12331,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
366,
45,
623,
8802,
963,
540,
8090,
4064,
82,
468,
645,
7034,
13,
4064,
82,
1,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
4064,
357,
10459,
13,
3672,
11,
1900,
62,
10459,
62,
8841,
8,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1267,
628,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2723,
13,
82,
14375,
796,
4808,
41339,
7416,
15419,
49354,
540,
50,
14375,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2723,
11,
2116,
13,
5577,
2915,
58,
10459,
13,
3672,
60,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1267,
628,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
82,
2203,
13,
33295,
7,
10459,
8,
628,
220,
220,
220,
825,
751,
62,
35350,
7,
944,
11,
1635,
35350,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
4550,
6143,
284,
300,
79,
526,
15931,
628,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
35350,
13,
2302,
437,
7,
35350,
8,
628,
220,
220,
220,
825,
751,
62,
7645,
8481,
7,
944,
11,
1635,
7645,
3411,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
4550,
11478,
284,
300,
79,
526,
15931,
628,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
7645,
3411,
13,
2302,
437,
7,
7645,
3411,
8,
628,
220,
220,
220,
825,
32315,
7,
944,
11,
2793,
11,
6727,
11,
1438,
28,
14202,
11,
14257,
28,
25101,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
15580,
257,
649,
1482,
2536,
2913,
543,
351,
4938,
2837,
1022,
2793,
290,
6727,
526,
15931,
198,
220,
220,
220,
220,
220,
220,
220,
1441,
1482,
2536,
2913,
7,
944,
11,
2793,
11,
6727,
11,
1438,
11,
14257,
8,
628,
220,
220,
220,
825,
4808,
36733,
1096,
62,
82,
14375,
7,
944,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
24243,
4340,
1540,
332,
11,
24183,
9432,
290,
900,
17778,
13,
628,
220,
220,
220,
220,
220,
220,
220,
4294,
332,
318,
12972,
29988,
489,
79,
13,
82,
14375,
13,
198,
220,
220,
220,
220,
220,
220,
220,
37092,
318,
284,
17775,
3484,
2426,
284,
17778,
13,
628,
220,
220,
220,
220,
220,
220,
220,
1881,
32315,
6875,
994,
318,
284,
4155,
326,
198,
220,
220,
220,
220,
220,
220,
220,
1176,
58,
25928,
62,
36996,
7131,
83,
60,
1875,
3512,
58,
25928,
62,
36996,
7131,
83,
60,
329,
477,
256,
290,
198,
220,
220,
220,
220,
220,
220,
220,
10706,
62,
2301,
507,
13,
628,
220,
220,
220,
220,
220,
220,
220,
4418,
4566,
942,
24846,
36,
3639,
13,
628,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
82,
14375,
796,
12972,
29988,
489,
79,
13,
50,
14375,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
366,
50,
6442,
28925,
1600,
12972,
29988,
489,
79,
13,
50,
14375,
13,
5097,
47,
62,
24027,
1503,
62,
4805,
7730,
24115,
44,
2751,
198,
220,
220,
220,
220,
220,
220,
220,
1267,
628,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
1084,
48439,
62,
15805,
82,
62,
15252,
425,
796,
37092,
7,
944,
11,
17775,
28,
17821,
8,
628,
220,
220,
220,
220,
220,
220,
220,
1303,
20768,
1096,
24846,
11522,
1746,
290,
24846,
21188,
198,
220,
220,
220,
220,
220,
220,
220,
3512,
62,
16345,
796,
657,
13,
15,
198,
220,
220,
220,
220,
220,
220,
220,
329,
288,
287,
2116,
13,
9536,
1746,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1949,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
16545,
796,
2116,
13,
5577,
2915,
58,
67,
13,
3672,
60,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
29117,
62,
28550,
58,
67,
13,
25928,
62,
36996,
62,
312,
60,
796,
45941,
13,
18747,
7,
5577,
2915,
13,
27160,
8,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2845,
7383,
12331,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
7034,
62,
14933,
796,
965,
7,
944,
13,
5577,
2915,
13,
13083,
28955,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
4049,
62,
8841,
796,
357,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
366,
41339,
42782,
4064,
82,
13,
1400,
7034,
1043,
0,
29454,
16545,
37498,
4,
82,
16725,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
4064,
357,
67,
13,
3672,
11,
7034,
62,
14933,
8,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1267,
628,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
5298,
7383,
12331,
7,
18224,
62,
8841,
8,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
5936,
3760,
62,
6477,
62,
1102,
2536,
2913,
58,
67,
13,
25928,
62,
36996,
62,
312,
60,
796,
685,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
1102,
2536,
2913,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
279,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
82,
14375,
13,
10745,
6269,
22784,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
366,
9444,
3760,
4333,
308,
312,
25,
4,
67,
256,
25,
4,
67,
1,
4064,
357,
67,
13,
25928,
62,
36996,
62,
312,
11,
256,
828,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1267,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
329,
256,
11,
279,
287,
27056,
378,
7,
5577,
2915,
8,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2361,
628,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
3512,
62,
16345,
15853,
2160,
7,
5577,
2915,
8,
628,
220,
220,
220,
220,
220,
220,
220,
1303,
33141,
371,
3705,
543,
318,
17198,
13,
220,
632,
4433,
2041,
3884,
198,
220,
220,
220,
220,
220,
220,
220,
1303,
9633,
58,
25928,
62,
36996,
7131,
2435,
60,
290,
513,
17778,
13,
198,
220,
220,
220,
220,
220,
220,
220,
1303,
198,
220,
220,
220,
220,
220,
220,
220,
1303,
1482,
2536,
2913,
1303,
16,
25,
198,
220,
220,
220,
220,
220,
220,
220,
1303,
383,
4045,
3061,
318,
284,
423,
371,
3705,
7074,
374,
862,
62,
25067,
286,
2472,
198,
220,
220,
220,
220,
220,
220,
220,
1303,
3512,
13,
220,
11259,
326,
25,
198,
220,
220,
220,
220,
220,
220,
220,
1303,
220,
220,
2472,
62,
81,
862,
62,
43082,
19039,
2160,
7,
81,
862,
62,
43082,
58,
70,
7131,
83,
12962,
198,
220,
220,
220,
220,
220,
220,
220,
1303,
220,
220,
2472,
62,
28550,
19039,
2160,
7,
28550,
58,
70,
7131,
83,
12962,
198,
220,
220,
220,
220,
220,
220,
220,
1303,
198,
220,
220,
220,
220,
220,
220,
220,
1303,
383,
32315,
3706,
2472,
62,
81,
862,
62,
43082,
62,
13655,
62,
81,
862,
62,
25067,
62,
1102,
2536,
2913,
198,
220,
220,
220,
220,
220,
220,
220,
1303,
318,
25,
198,
220,
220,
220,
220,
220,
220,
220,
1303,
220,
220,
2472,
62,
81,
862,
62,
43082,
18189,
357,
944,
13,
81,
862,
62,
25067,
1220,
1802,
8,
1635,
2472,
62,
28550,
198,
220,
220,
220,
220,
220,
220,
220,
1303,
198,
220,
220,
220,
220,
220,
220,
220,
1303,
1482,
2536,
2913,
1303,
17,
25,
198,
220,
220,
220,
220,
220,
220,
220,
1303,
374,
862,
62,
43082,
58,
70,
7131,
83,
60,
2314,
7074,
2160,
286,
374,
862,
62,
82,
2203,
532,
2160,
286,
198,
220,
220,
220,
220,
220,
220,
220,
1303,
374,
862,
62,
82,
2973,
379,
1123,
308,
11,
83,
13,
220,
1052,
1672,
286,
374,
862,
62,
82,
676,
318,
262,
705,
38827,
62,
2257,
1581,
11879,
6,
198,
220,
220,
220,
220,
220,
220,
220,
1303,
636,
286,
24846,
6690,
31425,
543,
7000,
374,
862,
2568,
572,
262,
10706,
691,
198,
220,
220,
220,
220,
220,
220,
220,
1303,
284,
1234,
340,
736,
319,
262,
10706,
1568,
355,
257,
374,
862,
62,
10459,
13,
220,
770,
318,
198,
220,
220,
220,
220,
220,
220,
220,
1303,
12548,
287,
262,
32315,
3706,
198,
220,
220,
220,
220,
220,
220,
220,
1303,
374,
862,
62,
10459,
62,
1102,
2536,
6003,
58,
70,
7131,
83,
5974,
198,
220,
220,
220,
220,
220,
220,
220,
1303,
220,
220,
374,
862,
62,
43082,
58,
70,
7131,
83,
60,
19841,
2160,
7,
81,
862,
62,
82,
2203,
58,
70,
7131,
83,
12962,
532,
2160,
7,
81,
862,
62,
82,
2973,
58,
70,
7131,
83,
12962,
198,
220,
220,
220,
220,
220,
220,
220,
1303,
198,
220,
220,
220,
220,
220,
220,
220,
1303,
1482,
2536,
2913,
1303,
18,
198,
220,
220,
220,
220,
220,
220,
220,
1303,
374,
862,
62,
43082,
58,
70,
7131,
83,
60,
2314,
7074,
644,
460,
307,
973,
379,
1123,
308,
11,
83,
13,
220,
611,
198,
220,
220,
220,
220,
220,
220,
220,
1303,
374,
862,
62,
82,
2203,
7716,
257,
19525,
707,
1078,
379,
308,
11,
83,
796,
657,
11,
15,
290,
691,
352,
14326,
460,
307,
198,
220,
220,
220,
220,
220,
220,
220,
1303,
973,
379,
308,
11,
83,
788,
356,
836,
470,
765,
284,
3884,
262,
21958,
36006,
29961,
13,
198,
220,
220,
220,
220,
220,
220,
220,
1303,
198,
220,
220,
220,
220,
220,
220,
220,
1303,
383,
32315,
3706,
374,
862,
62,
28550,
62,
1102,
2536,
6003,
318,
25,
198,
220,
220,
220,
220,
220,
220,
220,
1303,
220,
220,
374,
862,
62,
43082,
58,
70,
7131,
83,
60,
19841,
3512,
58,
70,
7131,
83,
60,
198,
220,
220,
220,
220,
220,
220,
220,
1303,
628,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
23350,
62,
28550,
796,
3512,
62,
16345,
198,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
81,
862,
62,
28550,
796,
3512,
62,
16345,
1635,
2116,
13,
81,
862,
62,
25067,
1220,
1802,
13,
15,
198,
220,
220,
220,
220,
220,
220,
220,
1540,
332,
796,
2116,
13,
82,
14375,
198,
220,
220,
220,
220,
220,
220,
220,
2472,
62,
81,
862,
62,
43082,
62,
13655,
62,
81,
862,
62,
25067,
62,
1102,
2536,
2913,
796,
2116,
13,
1102,
2536,
2913,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
81,
862,
62,
28550,
11,
1540,
332,
13,
10745,
6269,
3419,
198,
220,
220,
220,
220,
220,
220,
220,
1267,
628,
220,
220,
220,
220,
220,
220,
220,
329,
288,
287,
2116,
13,
9536,
1746,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
16545,
796,
2116,
13,
5577,
2915,
58,
67,
13,
3672,
60,
628,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
611,
2116,
13,
81,
862,
62,
25067,
1875,
657,
13,
15,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
374,
862,
62,
43082,
62,
25641,
2977,
796,
2116,
13,
32446,
533,
62,
22355,
75,
501,
62,
25641,
2977,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
366,
834,
81,
862,
62,
43082,
834,
1600,
288,
13,
25928,
62,
36996,
62,
312,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1267,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2073,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
374,
862,
62,
43082,
62,
25641,
2977,
796,
685,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1540,
332,
13,
33111,
19852,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
657,
13,
15,
11,
657,
13,
15,
11,
366,
834,
65,
519,
385,
374,
862,
62,
43082,
834,
4064,
67,
4064,
67,
1,
4064,
357,
67,
13,
25928,
62,
36996,
62,
312,
11,
256,
8,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1267,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
329,
256,
287,
2116,
13,
2435,
62,
9630,
62,
2676,
540,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2361,
628,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
374,
862,
62,
28550,
62,
1102,
2536,
6003,
796,
17635,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
374,
862,
62,
10459,
62,
1102,
2536,
6003,
796,
685,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
1102,
2536,
2913,
7,
15,
13,
15,
11,
1540,
332,
13,
10745,
6269,
28955,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
329,
256,
287,
2116,
13,
2435,
62,
9630,
62,
2676,
540,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2361,
628,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
81,
862,
62,
10459,
62,
1102,
2536,
6003,
58,
67,
13,
25928,
62,
36996,
62,
312,
60,
796,
374,
862,
62,
10459,
62,
1102,
2536,
6003,
628,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
81,
862,
62,
43082,
62,
25641,
2977,
58,
67,
13,
25928,
62,
36996,
62,
312,
60,
796,
374,
862,
62,
43082,
62,
25641,
2977,
628,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
329,
256,
287,
2116,
13,
2435,
62,
9630,
62,
2676,
540,
25,
628,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1303,
5060,
7,
81,
862,
62,
43082,
58,
25928,
62,
36996,
11,
256,
12962,
18189,
374,
862,
62,
25067,
1635,
2472,
3512,
13,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2472,
62,
81,
862,
62,
43082,
62,
13655,
62,
81,
862,
62,
25067,
62,
1102,
2536,
2913,
13,
2617,
62,
1073,
16814,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
374,
862,
62,
43082,
62,
25641,
2977,
58,
83,
4357,
352,
13,
15,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1267,
628,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1303,
371,
862,
62,
43082,
58,
25928,
62,
36996,
11,
256,
60,
19841,
3512,
58,
25928,
62,
36996,
11,
256,
4083,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
374,
862,
62,
43082,
62,
1203,
62,
14813,
62,
28550,
796,
2116,
13,
1102,
2536,
2913,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
532,
82,
14375,
13,
10745,
6269,
22784,
16545,
58,
83,
60,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1267,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
374,
862,
62,
43082,
62,
1203,
62,
14813,
62,
28550,
13,
2617,
62,
1073,
16814,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
374,
862,
62,
43082,
62,
25641,
2977,
58,
83,
4357,
352,
13,
15,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1267,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
374,
862,
62,
28550,
62,
1102,
2536,
6003,
13,
33295,
7,
81,
862,
62,
43082,
62,
1203,
62,
14813,
62,
28550,
8,
628,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1303,
371,
862,
62,
43082,
58,
25928,
62,
36996,
11,
256,
60,
19841,
357,
16345,
7,
81,
862,
62,
82,
2203,
58,
25928,
62,
36996,
11,
256,
12962,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1303,
1482,
2536,
2913,
635,
3011,
12328,
416,
4808,
41339,
7416,
7,
15419,
8,
49354,
540,
50,
14375,
13,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1303,
17425,
62,
34431,
62,
25641,
2977,
62,
392,
62,
1102,
2536,
6003,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
374,
862,
62,
10459,
62,
1102,
2536,
6003,
58,
83,
4083,
2617,
62,
1073,
16814,
7,
81,
862,
62,
43082,
62,
25641,
2977,
58,
83,
4357,
532,
16,
13,
15,
8,
628,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
81,
862,
62,
28550,
62,
1102,
2536,
6003,
58,
67,
13,
25928,
62,
36996,
62,
312,
60,
796,
374,
862,
62,
28550,
62,
1102,
2536,
6003,
628,
220,
220,
220,
220,
220,
220,
220,
1303,
17056,
495,
4237,
290,
6143,
13,
198,
220,
220,
220,
220,
220,
220,
220,
329,
264,
287,
2116,
13,
82,
2203,
1343,
2116,
13,
35350,
1343,
2116,
13,
7645,
3411,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
264,
13,
11250,
495,
62,
34431,
62,
25641,
2977,
62,
392,
62,
1102,
2536,
6003,
7,
944,
8,
628,
220,
220,
220,
825,
8494,
7,
944,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
24243,
4340,
290,
4539,
14174,
1430,
13,
628,
220,
220,
220,
220,
220,
220,
220,
770,
318,
262,
1388,
8027,
284,
869,
706,
11593,
15003,
834,
13,
628,
220,
220,
220,
220,
220,
220,
220,
16409,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
6407,
611,
14174,
1430,
2921,
281,
16586,
1255,
13,
220,
10352,
4306,
13,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
2116,
13557,
36733,
1096,
62,
82,
14375,
3419,
198,
220,
220,
220,
220,
220,
220,
220,
3722,
796,
2116,
13,
82,
14375,
13,
50,
6442,
3419,
198,
220,
220,
220,
220,
220,
220,
220,
6718,
2004,
796,
3722,
6624,
2116,
13,
82,
14375,
13,
3185,
51,
3955,
1847,
628,
220,
220,
220,
220,
220,
220,
220,
611,
6718,
2004,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2116,
13557,
7353,
62,
14681,
3419,
628,
220,
220,
220,
220,
220,
220,
220,
1441,
6718,
2004,
628,
220,
220,
220,
825,
4808,
7353,
62,
14681,
7,
944,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
8645,
689,
1366,
973,
329,
26019,
13529,
374,
862,
14,
13159,
12,
81,
862,
3815,
13,
628,
220,
220,
220,
220,
220,
220,
220,
4418,
4274,
12,
42116,
2482,
284,
787,
1654,
484,
2872,
17778,
13,
628,
220,
220,
220,
220,
220,
220,
220,
7567,
2696,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
43160,
12331,
25,
1002,
4274,
12,
26752,
2482,
466,
407,
2872,
17778,
13,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
628,
220,
220,
220,
220,
220,
220,
220,
1303,
20768,
1096,
1281,
62,
36948,
26310,
13,
198,
220,
220,
220,
220,
220,
220,
220,
329,
288,
287,
2116,
13,
9536,
1746,
25,
628,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1303,
7472,
2033,
286,
374,
862,
62,
82,
2203,
58,
70,
7131,
83,
60,
1176,
13,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
81,
862,
62,
23350,
58,
67,
13,
25928,
62,
36996,
62,
312,
60,
796,
45941,
13,
9107,
418,
7,
944,
13,
17618,
62,
1659,
62,
22355,
677,
274,
8,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1303,
7472,
2033,
286,
1729,
12,
81,
862,
62,
82,
2203,
58,
70,
7131,
83,
60,
1176,
13,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
13159,
62,
81,
862,
62,
23350,
58,
67,
13,
25928,
62,
36996,
62,
312,
60,
796,
45941,
13,
9107,
418,
7,
944,
13,
17618,
62,
1659,
62,
22355,
677,
274,
8,
628,
220,
220,
220,
220,
220,
220,
220,
329,
264,
287,
2116,
13,
82,
2203,
1343,
2116,
13,
35350,
1343,
2116,
13,
7645,
3411,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
264,
13,
7353,
62,
14681,
7,
944,
8,
628,
220,
220,
220,
220,
220,
220,
220,
1303,
2986,
414,
4049,
2198,
2482,
1028,
17778,
13,
220,
1002,
597,
286,
777,
198,
220,
220,
220,
220,
220,
220,
220,
1303,
651,
4376,
11,
340,
9217,
257,
5434,
287,
262,
2438,
13,
198,
220,
220,
220,
220,
220,
220,
220,
1540,
332,
62,
3866,
16005,
796,
2116,
13,
82,
14375,
62,
3866,
16005,
198,
220,
220,
220,
220,
220,
220,
220,
2160,
62,
81,
862,
62,
66,
20696,
796,
657,
13,
15,
198,
220,
220,
220,
220,
220,
220,
220,
329,
308,
62,
312,
287,
685,
67,
13,
25928,
62,
36996,
62,
312,
329,
288,
287,
2116,
13,
9536,
1746,
5974,
628,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1176,
62,
4299,
3628,
796,
2116,
13,
29117,
62,
28550,
58,
70,
62,
312,
60,
532,
357,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
81,
862,
62,
23350,
58,
70,
62,
312,
60,
1343,
2116,
13,
13159,
62,
81,
862,
62,
23350,
58,
70,
62,
312,
60,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1267,
628,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
7588,
62,
45089,
62,
261,
796,
357,
6477,
62,
4299,
3628,
1279,
1540,
332,
62,
3866,
16005,
737,
439,
3419,
628,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
374,
862,
62,
66,
20696,
796,
45941,
13,
18747,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
685,
6015,
85,
13,
82,
2122,
62,
8367,
3419,
329,
374,
33967,
287,
2116,
13,
81,
862,
62,
43082,
62,
25641,
2977,
58,
70,
62,
312,
11907,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1267,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2160,
62,
81,
862,
62,
66,
20696,
15853,
2160,
7,
81,
862,
62,
66,
20696,
8,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
81,
862,
62,
43082,
62,
27160,
58,
70,
62,
312,
60,
796,
374,
862,
62,
66,
20696,
628,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
374,
862,
62,
43082,
62,
13655,
62,
28550,
796,
357,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
374,
862,
62,
66,
20696,
1875,
2116,
13,
29117,
62,
28550,
58,
70,
62,
312,
60,
1343,
1540,
332,
62,
3866,
16005,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
6739,
439,
3419,
628,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
374,
862,
62,
43082,
62,
13655,
62,
81,
862,
62,
82,
2203,
796,
357,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
374,
862,
62,
66,
20696,
1875,
2116,
13,
81,
862,
62,
23350,
58,
70,
62,
312,
60,
1343,
1540,
332,
62,
3866,
16005,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
6739,
439,
3419,
628,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
6143,
62,
1069,
2707,
82,
62,
28550,
796,
357,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
29117,
62,
28550,
58,
70,
62,
312,
60,
1279,
532,
82,
14375,
62,
3866,
16005,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
6739,
439,
3419,
628,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
611,
407,
7588,
62,
45089,
62,
261,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
5298,
34479,
3673,
50,
17403,
798,
12331,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
366,
42782,
407,
11378,
416,
4064,
69,
329,
3814,
4064,
67,
1,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
4064,
357,
9806,
7,
6477,
62,
4299,
3628,
828,
308,
62,
312,
8,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1267,
628,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
611,
374,
862,
62,
43082,
62,
13655,
62,
28550,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
5298,
371,
862,
3109,
2707,
82,
42782,
12331,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
366,
49,
3705,
29501,
1475,
2707,
34479,
329,
3814,
4064,
67,
1,
4064,
308,
62,
312,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1267,
628,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
611,
374,
862,
62,
43082,
62,
13655,
62,
81,
862,
62,
82,
2203,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
5298,
371,
862,
23690,
3109,
2707,
82,
21188,
12331,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
366,
49,
3705,
29501,
1475,
2707,
371,
3705,
26406,
329,
3814,
4064,
67,
1,
4064,
308,
62,
312,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1267,
628,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
611,
6143,
62,
1069,
2707,
82,
62,
28550,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
5298,
20514,
3109,
2707,
82,
42782,
12331,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
366,
31425,
1475,
2707,
82,
34479,
329,
3814,
4064,
67,
1,
4064,
308,
62,
312,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1267,
628,
220,
220,
220,
220,
220,
220,
220,
1303,
21589,
1540,
332,
62,
3866,
16005,
416,
1271,
286,
1661,
677,
274,
284,
651,
15440,
198,
220,
220,
220,
220,
220,
220,
220,
1303,
329,
257,
32794,
7208,
13,
198,
220,
220,
220,
220,
220,
220,
220,
2160,
62,
82,
14375,
62,
3866,
16005,
796,
1540,
332,
62,
3866,
16005,
1635,
2116,
13,
17618,
62,
1659,
62,
22355,
677,
274,
198,
220,
220,
220,
220,
220,
220,
220,
611,
2160,
62,
82,
14375,
62,
3866,
16005,
1343,
2160,
62,
81,
862,
62,
66,
20696,
1279,
2116,
13,
81,
862,
62,
28550,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
5298,
371,
862,
31905,
3673,
9171,
12331,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
366,
13065,
371,
3705,
10824,
37633,
69,
8,
1279,
3512,
1635,
37633,
69,
374,
862,
62,
25067,
8,
37633,
69,
16725,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
4064,
357,
16345,
62,
81,
862,
62,
66,
20696,
11,
12178,
7,
944,
13,
81,
862,
62,
25067,
828,
2116,
13,
81,
862,
62,
28550,
8,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1267,
628,
220,
220,
220,
825,
13627,
62,
22355,
75,
501,
62,
25641,
2977,
7,
944,
11,
1438,
11,
10706,
62,
36996,
62,
312,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
37835,
3565,
1661,
75,
501,
9633,
329,
257,
10706,
62,
36996,
13,
628,
220,
220,
220,
220,
220,
220,
220,
943,
14542,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1438,
25,
10903,
284,
307,
3017,
287,
262,
7560,
7885,
1438,
13,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
10706,
62,
36996,
62,
312,
25,
2558,
543,
21079,
543,
10706,
777,
9633,
2689,
13,
628,
220,
220,
220,
220,
220,
220,
220,
2141,
1892,
869,
428,
2163,
351,
262,
976,
357,
3672,
11,
10706,
62,
36996,
62,
312,
8,
198,
220,
220,
220,
220,
220,
220,
220,
5166,
517,
621,
1752,
13,
220,
1318,
743,
407,
307,
1852,
1146,
3706,
9633,
198,
220,
220,
220,
220,
220,
220,
220,
287,
262,
976,
10706,
62,
36996,
13,
628,
220,
220,
220,
220,
220,
220,
220,
16409,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
15690,
286,
300,
79,
9633,
11,
1123,
543,
2837,
422,
657,
284,
37174,
13,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
15690,
318,
27661,
523,
326,
7885,
329,
640,
12,
48369,
2124,
318,
379,
6376,
2124,
13,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
304,
13,
70,
13,
7885,
329,
717,
640,
12,
48369,
318,
7885,
58,
15,
4083,
7885,
329,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
938,
640,
12,
48369,
318,
7885,
58,
12,
16,
60,
628,
220,
220,
220,
220,
220,
220,
220,
37227,
628,
220,
220,
220,
220,
220,
220,
220,
1540,
332,
796,
2116,
13,
82,
14375,
628,
220,
220,
220,
220,
220,
220,
220,
9633,
796,
17635,
198,
220,
220,
220,
220,
220,
220,
220,
329,
256,
287,
2116,
13,
2435,
62,
9630,
62,
2676,
540,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1401,
62,
3672,
796,
366,
834,
1911,
22179,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
685,
3672,
11,
366,
25928,
62,
36996,
62,
312,
1600,
965,
7,
25928,
62,
36996,
62,
312,
828,
366,
265,
62,
83,
1600,
965,
7,
83,
15437,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1267,
628,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
9633,
13,
33295,
7,
82,
14375,
13,
33111,
19852,
7,
15,
13,
15,
11,
1540,
332,
13,
10745,
6269,
22784,
1401,
62,
3672,
4008,
198,
220,
220,
220,
220,
220,
220,
220,
1441,
9633,
628,
220,
220,
220,
825,
13627,
62,
3672,
6816,
62,
45286,
7,
944,
11,
1438,
11,
10706,
62,
36996,
62,
312,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
37835,
3565,
257,
1438,
6816,
7885,
329,
257,
10706,
62,
36996,
13,
628,
220,
220,
220,
220,
220,
220,
220,
943,
14542,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1438,
25,
10903,
284,
307,
3017,
287,
262,
7560,
7885,
1438,
13,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
10706,
62,
36996,
62,
312,
25,
10903,
1958,
540,
2134,
543,
21079,
543,
10706,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
777,
9633,
2689,
13,
628,
220,
220,
220,
220,
220,
220,
220,
2141,
1892,
869,
428,
2163,
351,
262,
976,
357,
3672,
11,
10706,
62,
36996,
62,
312,
8,
198,
220,
220,
220,
220,
220,
220,
220,
5166,
517,
621,
1752,
13,
220,
1318,
743,
407,
307,
1852,
1146,
3706,
9633,
198,
220,
220,
220,
220,
220,
220,
220,
287,
262,
976,
10706,
62,
36996,
13,
628,
220,
220,
220,
220,
220,
220,
220,
16409,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
317,
300,
79,
7885,
543,
3815,
2837,
422,
657,
284,
37174,
13,
628,
220,
220,
220,
220,
220,
220,
220,
37227,
628,
220,
220,
220,
220,
220,
220,
220,
1438,
6816,
62,
3672,
796,
366,
834,
1911,
22179,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
685,
3672,
11,
366,
25928,
62,
36996,
62,
312,
1600,
965,
7,
25928,
62,
36996,
62,
312,
828,
366,
36729,
8973,
198,
220,
220,
220,
220,
220,
220,
220,
1267,
628,
220,
220,
220,
220,
220,
220,
220,
1540,
332,
796,
2116,
13,
82,
14375,
198,
220,
220,
220,
220,
220,
220,
220,
1441,
1540,
332,
13,
33111,
19852,
7,
15,
13,
15,
11,
1540,
332,
13,
10745,
6269,
22784,
1438,
6816,
62,
3672,
8,
628,
198,
4299,
36804,
27976,
62,
15805,
7,
15805,
11,
9780,
62,
4873,
11,
640,
62,
12626,
62,
16,
11,
640,
62,
12626,
62,
17,
2599,
198,
220,
220,
220,
37227,
11627,
2416,
27976,
1575,
422,
530,
640,
11506,
284,
1194,
13,
628,
220,
220,
220,
943,
14542,
25,
198,
220,
220,
220,
220,
220,
1575,
25,
1575,
23436,
1141,
640,
62,
12626,
62,
16,
357,
259,
4991,
286,
7395,
8,
198,
220,
220,
220,
220,
220,
9780,
62,
4873,
25,
2494,
326,
1637,
875,
592,
11,
583,
614,
357,
292,
32465,
11,
304,
13,
70,
1539,
764,
3312,
8,
198,
220,
220,
220,
220,
220,
640,
62,
12626,
62,
16,
25,
640,
11506,
618,
1575,
23436,
357,
259,
4991,
286,
812,
8,
198,
220,
220,
220,
220,
220,
640,
62,
12626,
62,
17,
25,
640,
11506,
284,
36804,
27976,
1575,
357,
259,
4991,
286,
812,
8,
628,
220,
220,
220,
16409,
25,
198,
220,
220,
220,
220,
220,
6446,
36804,
50027,
284,
640,
62,
12626,
62,
17,
11,
4991,
286,
7395,
13,
628,
220,
220,
220,
9104,
10007,
389,
3484,
625,
640,
32727,
13,
1114,
1672,
11,
262,
3512,
198,
220,
220,
220,
743,
307,
257,
640,
2168,
326,
20374,
352,
614,
13,
383,
7885,
1575,
284,
14658,
198,
220,
220,
220,
326,
3512,
561,
788,
307,
329,
352,
614,
286,
4905,
13,
2102,
11,
262,
198,
220,
220,
220,
24846,
17633,
318,
4385,
284,
24061,
262,
2472,
1575,
625,
257,
2392,
640,
198,
220,
220,
220,
11506,
357,
68,
13,
70,
1539,
1542,
812,
737,
628,
220,
220,
220,
1002,
612,
547,
645,
640,
1988,
286,
1637,
11,
262,
36804,
50027,
1575,
561,
307,
198,
220,
220,
220,
262,
8064,
286,
640,
62,
12626,
62,
17,
284,
640,
62,
12626,
62,
16,
357,
68,
13,
70,
1539,
1542,
287,
262,
198,
220,
220,
220,
1672,
737,
2102,
11,
7524,
287,
262,
2003,
389,
1342,
16378,
621,
198,
220,
220,
220,
7524,
287,
262,
1944,
13,
220,
775,
36804,
27976,
262,
1575,
416,
717,
4917,
198,
220,
220,
220,
262,
7548,
12948,
4269,
286,
7524,
625,
640,
62,
12626,
62,
16,
326,
198,
220,
220,
220,
318,
7548,
284,
262,
1575,
11,
788,
7048,
326,
4269,
286,
7524,
198,
220,
220,
220,
8833,
625,
640,
62,
12626,
62,
17,
11,
2427,
13,
628,
220,
220,
220,
37227,
198,
220,
220,
220,
3349,
62,
4873,
796,
352,
13,
15,
1343,
9780,
62,
4873,
198,
220,
220,
220,
1988,
62,
12501,
323,
62,
16,
796,
7182,
7,
27922,
62,
4873,
11,
532,
2435,
62,
12626,
62,
17,
8,
198,
220,
220,
220,
1988,
62,
12501,
323,
62,
17,
796,
7182,
7,
27922,
62,
4873,
11,
532,
2435,
62,
12626,
62,
16,
8,
628,
220,
220,
220,
1949,
25,
198,
220,
220,
220,
220,
220,
220,
220,
1441,
1575,
1635,
357,
16,
13,
15,
532,
1988,
62,
12501,
323,
62,
16,
8,
1220,
357,
16,
13,
15,
532,
1988,
62,
12501,
323,
62,
17,
8,
198,
220,
220,
220,
2845,
12169,
24095,
1166,
12331,
25,
198,
220,
220,
220,
220,
220,
220,
220,
1441,
1575,
198
] | 2.328012 | 28,627 |
import dedupe
import unittest
if __name__ == "__main__":
unittest.main()
| [
11748,
4648,
48722,
198,
11748,
555,
715,
395,
628,
198,
361,
11593,
3672,
834,
6624,
366,
834,
12417,
834,
1298,
198,
220,
220,
220,
555,
715,
395,
13,
12417,
3419,
198
] | 2.548387 | 31 |
#get_data.py
#234567890123456789012345678901234567890123456789012345678901234567890123456789
# Imports here
import torch
from torchvision import datasets, transforms
# The command line parser for train.py | [
2,
1136,
62,
7890,
13,
9078,
198,
2,
1954,
2231,
3134,
4531,
486,
1954,
2231,
3134,
4531,
486,
1954,
2231,
3134,
4531,
486,
1954,
2231,
3134,
4531,
486,
1954,
2231,
3134,
4531,
486,
1954,
2231,
3134,
4531,
486,
1954,
2231,
3134,
4531,
486,
1954,
2231,
3134,
4531,
198,
198,
2,
1846,
3742,
994,
198,
11748,
28034,
198,
6738,
28034,
10178,
1330,
40522,
11,
31408,
198,
198,
2,
383,
3141,
1627,
30751,
329,
4512,
13,
9078
] | 2.746667 | 75 |
"""create bed_capacity table
Revision ID: f8791d49d830
Revises: b84312f6532e
Create Date: 2020-11-26 15:22:19.299937
"""
from alembic import op
# revision identifiers, used by Alembic.
revision = 'f8791d49d830'
down_revision = '4fcda072e8c6'
branch_labels = None
depends_on = None
| [
37811,
17953,
3996,
62,
42404,
3084,
198,
198,
18009,
1166,
4522,
25,
277,
23,
3720,
16,
67,
2920,
67,
48341,
198,
18009,
2696,
25,
275,
23,
3559,
1065,
69,
2996,
2624,
68,
198,
16447,
7536,
25,
12131,
12,
1157,
12,
2075,
1315,
25,
1828,
25,
1129,
13,
1959,
2079,
2718,
198,
198,
37811,
198,
6738,
31341,
2022,
291,
1330,
1034,
198,
198,
2,
18440,
42814,
11,
973,
416,
9300,
2022,
291,
13,
198,
260,
10178,
796,
705,
69,
23,
3720,
16,
67,
2920,
67,
48341,
6,
198,
2902,
62,
260,
10178,
796,
705,
19,
16072,
6814,
2998,
17,
68,
23,
66,
21,
6,
198,
1671,
3702,
62,
23912,
1424,
796,
6045,
198,
10378,
2412,
62,
261,
796,
6045,
628,
198
] | 2.383333 | 120 |
# Copyright 2019 Jij Inc.
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
# http://www.apache.org/licenses/LICENSE-2.0
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import numpy as np
import openjij
class Response:
"""A class of response from samplers.
Args:
var_type (str):
Type of variables: 'SPIN' or 'BINARY' which mean {-1, 1} or {0, 1}.
indices (int):
Indices of `openjij.sampler.response.Response` object.
Attributes:
states (list):
States of the system.
energies (list):
Energies for the states.
q_states (list):
Quantum states of the system.
q_energies (list):
Quantum energies for the quantum states.
min_samples (list):
Samples with minimum energy.
info (dict):
Other information.
"""
def update_ising_states_energies(self, states, energies):
"""Update states and energies.
Args:
states (list):
Updated states.
energies (list):
Updated energies.
Attributes:
min_samples (dict):
Minimun energies, states, and number of occurrences.
"""
if self.var_type == openjij.SPIN:
self.states = states
else:
self.states = [
list(np.array((np.array(state) + 1)/2).astype(np.int)) for state in states]
self.energies = energies
self.min_samples = self._minimum_sample()
def update_trotter_ising_states_energies(self, trotter_states, q_energies):
"""Update quantum states and energies.
Args:
trotter_states (list):
Updated trotter states.
q_energies (list):
Updated quantum energies.
Attributes:
min_samples (dict):
Minimun energies, states, and number of occurrences.
"""
if self.var_type == openjij.SPIN:
self.q_states = list(np.array(trotter_states).astype(np.int))
else:
self.q_states = [[list(np.array((np.array(state) + 1)/2).astype(np.int))
for state in t_state] for t_state in trotter_states]
self.q_energies = q_energies
# save minimum energy of each trotter_state
min_e_indices = np.argmin(q_energies, axis=1)
self.energies = [q_e[min_ind]
for min_ind, q_e in zip(min_e_indices, q_energies)]
self.states = [list(t_state[min_ind]) for min_ind,
t_state in zip(min_e_indices, self.q_states)]
self.min_samples = self._minimum_sample()
@property
def samples(self):
"""Returns samples as list.
Returns:
list: all the samples.
"""
return [dict(zip(self.indices, state)) for state in self.states]
| [
2,
15069,
13130,
449,
2926,
3457,
13,
198,
198,
2,
49962,
739,
262,
24843,
13789,
11,
10628,
362,
13,
15,
357,
1169,
366,
34156,
15341,
198,
2,
345,
743,
407,
779,
428,
2393,
2845,
287,
11846,
351,
262,
13789,
13,
198,
2,
921,
743,
7330,
257,
4866,
286,
262,
13789,
379,
198,
198,
2,
220,
220,
220,
220,
2638,
1378,
2503,
13,
43073,
13,
2398,
14,
677,
4541,
14,
43,
2149,
24290,
12,
17,
13,
15,
198,
198,
2,
17486,
2672,
416,
9723,
1099,
393,
4987,
284,
287,
3597,
11,
3788,
198,
2,
9387,
739,
262,
13789,
318,
9387,
319,
281,
366,
1921,
3180,
1,
29809,
1797,
11,
198,
2,
42881,
34764,
11015,
6375,
7102,
49828,
11053,
3963,
15529,
509,
12115,
11,
2035,
4911,
393,
17142,
13,
198,
2,
4091,
262,
13789,
329,
262,
2176,
3303,
15030,
21627,
290,
198,
2,
11247,
739,
262,
13789,
13,
198,
198,
11748,
299,
32152,
355,
45941,
198,
11748,
1280,
73,
2926,
628,
198,
4871,
18261,
25,
198,
220,
220,
220,
37227,
32,
1398,
286,
2882,
422,
6072,
489,
364,
13,
628,
220,
220,
220,
943,
14542,
25,
198,
220,
220,
220,
220,
220,
220,
220,
1401,
62,
4906,
357,
2536,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
5994,
286,
9633,
25,
705,
4303,
1268,
6,
393,
705,
33,
1268,
13153,
6,
543,
1612,
1391,
12,
16,
11,
352,
92,
393,
1391,
15,
11,
352,
27422,
628,
220,
220,
220,
220,
220,
220,
220,
36525,
357,
600,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1423,
1063,
286,
4600,
9654,
73,
2926,
13,
37687,
20053,
13,
26209,
13,
31077,
63,
2134,
13,
628,
220,
220,
220,
49213,
25,
198,
220,
220,
220,
220,
220,
220,
220,
2585,
357,
4868,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1829,
286,
262,
1080,
13,
628,
220,
220,
220,
220,
220,
220,
220,
27598,
357,
4868,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
412,
25649,
444,
329,
262,
2585,
13,
628,
220,
220,
220,
220,
220,
220,
220,
10662,
62,
27219,
357,
4868,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
29082,
2585,
286,
262,
1080,
13,
628,
220,
220,
220,
220,
220,
220,
220,
10662,
62,
877,
70,
444,
357,
4868,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
29082,
27598,
329,
262,
14821,
2585,
13,
628,
220,
220,
220,
220,
220,
220,
220,
949,
62,
82,
12629,
357,
4868,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
3409,
2374,
351,
5288,
2568,
13,
628,
220,
220,
220,
220,
220,
220,
220,
7508,
357,
11600,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
3819,
1321,
13,
628,
220,
220,
220,
37227,
628,
220,
220,
220,
825,
4296,
62,
1710,
62,
27219,
62,
877,
70,
444,
7,
944,
11,
2585,
11,
27598,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
10260,
2585,
290,
27598,
13,
628,
220,
220,
220,
220,
220,
220,
220,
943,
14542,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2585,
357,
4868,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
19433,
2585,
13,
628,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
27598,
357,
4868,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
19433,
27598,
13,
628,
220,
220,
220,
220,
220,
220,
220,
49213,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
949,
62,
82,
12629,
357,
11600,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1855,
320,
403,
27598,
11,
2585,
11,
290,
1271,
286,
40279,
13,
628,
220,
220,
220,
220,
220,
220,
220,
37227,
628,
220,
220,
220,
220,
220,
220,
220,
611,
2116,
13,
7785,
62,
4906,
6624,
1280,
73,
2926,
13,
4303,
1268,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
27219,
796,
2585,
198,
220,
220,
220,
220,
220,
220,
220,
2073,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
27219,
796,
685,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1351,
7,
37659,
13,
18747,
19510,
37659,
13,
18747,
7,
5219,
8,
1343,
352,
20679,
17,
737,
459,
2981,
7,
37659,
13,
600,
4008,
329,
1181,
287,
2585,
60,
198,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
877,
70,
444,
796,
27598,
198,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
1084,
62,
82,
12629,
796,
2116,
13557,
39504,
62,
39873,
3419,
628,
220,
220,
220,
825,
4296,
62,
83,
10599,
353,
62,
1710,
62,
27219,
62,
877,
70,
444,
7,
944,
11,
4161,
83,
353,
62,
27219,
11,
10662,
62,
877,
70,
444,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
10260,
14821,
2585,
290,
27598,
13,
628,
220,
220,
220,
220,
220,
220,
220,
943,
14542,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
4161,
83,
353,
62,
27219,
357,
4868,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
19433,
4161,
83,
353,
2585,
13,
628,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
10662,
62,
877,
70,
444,
357,
4868,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
19433,
14821,
27598,
13,
628,
220,
220,
220,
220,
220,
220,
220,
49213,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
949,
62,
82,
12629,
357,
11600,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1855,
320,
403,
27598,
11,
2585,
11,
290,
1271,
286,
40279,
13,
628,
220,
220,
220,
220,
220,
220,
220,
37227,
628,
220,
220,
220,
220,
220,
220,
220,
611,
2116,
13,
7785,
62,
4906,
6624,
1280,
73,
2926,
13,
4303,
1268,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
80,
62,
27219,
796,
1351,
7,
37659,
13,
18747,
7,
83,
10599,
353,
62,
27219,
737,
459,
2981,
7,
37659,
13,
600,
4008,
198,
220,
220,
220,
220,
220,
220,
220,
2073,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
80,
62,
27219,
796,
16410,
4868,
7,
37659,
13,
18747,
19510,
37659,
13,
18747,
7,
5219,
8,
1343,
352,
20679,
17,
737,
459,
2981,
7,
37659,
13,
600,
4008,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
329,
1181,
287,
256,
62,
5219,
60,
329,
256,
62,
5219,
287,
4161,
83,
353,
62,
27219,
60,
198,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
80,
62,
877,
70,
444,
796,
10662,
62,
877,
70,
444,
198,
220,
220,
220,
220,
220,
220,
220,
1303,
3613,
5288,
2568,
286,
1123,
4161,
83,
353,
62,
5219,
198,
220,
220,
220,
220,
220,
220,
220,
949,
62,
68,
62,
521,
1063,
796,
45941,
13,
853,
1084,
7,
80,
62,
877,
70,
444,
11,
16488,
28,
16,
8,
198,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
877,
70,
444,
796,
685,
80,
62,
68,
58,
1084,
62,
521,
60,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
329,
949,
62,
521,
11,
10662,
62,
68,
287,
19974,
7,
1084,
62,
68,
62,
521,
1063,
11,
10662,
62,
877,
70,
444,
15437,
198,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
27219,
796,
685,
4868,
7,
83,
62,
5219,
58,
1084,
62,
521,
12962,
329,
949,
62,
521,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
256,
62,
5219,
287,
19974,
7,
1084,
62,
68,
62,
521,
1063,
11,
2116,
13,
80,
62,
27219,
15437,
198,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
1084,
62,
82,
12629,
796,
2116,
13557,
39504,
62,
39873,
3419,
628,
220,
220,
220,
2488,
26745,
198,
220,
220,
220,
825,
8405,
7,
944,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
35561,
8405,
355,
1351,
13,
628,
220,
220,
220,
220,
220,
220,
220,
16409,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1351,
25,
477,
262,
8405,
13,
628,
220,
220,
220,
220,
220,
220,
220,
37227,
628,
220,
220,
220,
220,
220,
220,
220,
1441,
685,
11600,
7,
13344,
7,
944,
13,
521,
1063,
11,
1181,
4008,
329,
1181,
287,
2116,
13,
27219,
60,
198
] | 2.219853 | 1,501 |
B() | [
198,
33,
3419
] | 1.333333 | 3 |
#
# add_numbers()
# x = add_numbers_version_01(20,30)
# print(x) # ?
# not returning anything to you
# add_numbers_version_01(50, 10)
# add_numbers_version_01(300, 29)
# add_numbers_version_01(20.78, 56.89)
# # Average of two numbers
# Add 2 nos and then divide the sum with nos. of value
# no_one = 50
# no_two = 60
# nos_sum = no_one + no_two
# nos_sum = add_numbers_version_01(50, 50) ### This particular line of code will throw error
# avg = nos_sum/2 # 50.0
# print(avg) ##
# nos_sum = add_numbers_version_01(40, 50) ### This particular line of code will throw error
# avg = nos_sum/2 # 50.0
# print(avg) ##
# nos_sum = add_numbers_version_01(140, 150) ### This particular line of code will throw error
# avg = nos_sum/2 # 50.0
# print(avg) ##
output = calculate_avg_of_two_numbers()
print(output)
output = calculate_avg_of_two_numbers_version_01(30, 30)
print(output)
output = calculate_avg_of_two_numbers_version_01(40, 50)
print(output)
output = calculate_avg_of_two_numbers_version_01(140, 150)
print(output)
output = calculate_avg_of_two_numbers_version_01(230, 30)
print(output)
| [
2,
220,
198,
198,
2,
751,
62,
77,
17024,
3419,
198,
198,
2,
2124,
796,
751,
62,
77,
17024,
62,
9641,
62,
486,
7,
1238,
11,
1270,
8,
198,
2,
3601,
7,
87,
8,
220,
1303,
5633,
628,
197,
2,
407,
8024,
1997,
284,
345,
220,
198,
198,
2,
751,
62,
77,
17024,
62,
9641,
62,
486,
7,
1120,
11,
838,
8,
198,
2,
751,
62,
77,
17024,
62,
9641,
62,
486,
7,
6200,
11,
2808,
8,
198,
2,
751,
62,
77,
17024,
62,
9641,
62,
486,
7,
1238,
13,
3695,
11,
7265,
13,
4531,
8,
628,
198,
2,
1303,
13475,
286,
734,
3146,
220,
198,
2,
3060,
362,
43630,
290,
788,
14083,
262,
2160,
351,
43630,
13,
286,
1988,
220,
198,
198,
2,
645,
62,
505,
796,
2026,
220,
198,
2,
645,
62,
11545,
796,
3126,
220,
198,
2,
43630,
62,
16345,
796,
645,
62,
505,
1343,
645,
62,
11545,
198,
198,
2,
43630,
62,
16345,
796,
751,
62,
77,
17024,
62,
9641,
62,
486,
7,
1120,
11,
2026,
8,
220,
220,
44386,
770,
1948,
1627,
286,
2438,
481,
3714,
4049,
198,
198,
2,
42781,
220,
796,
43630,
62,
16345,
14,
17,
220,
1303,
2026,
13,
15,
198,
198,
2,
3601,
7,
615,
70,
8,
220,
22492,
220,
198,
198,
2,
43630,
62,
16345,
796,
751,
62,
77,
17024,
62,
9641,
62,
486,
7,
1821,
11,
2026,
8,
220,
220,
44386,
770,
1948,
1627,
286,
2438,
481,
3714,
4049,
198,
198,
2,
42781,
220,
796,
43630,
62,
16345,
14,
17,
220,
1303,
2026,
13,
15,
198,
198,
2,
3601,
7,
615,
70,
8,
220,
22492,
220,
628,
198,
2,
43630,
62,
16345,
796,
751,
62,
77,
17024,
62,
9641,
62,
486,
7,
15187,
11,
6640,
8,
220,
220,
44386,
770,
1948,
1627,
286,
2438,
481,
3714,
4049,
198,
198,
2,
42781,
220,
796,
43630,
62,
16345,
14,
17,
220,
1303,
2026,
13,
15,
198,
198,
2,
3601,
7,
615,
70,
8,
220,
22492,
220,
628,
198,
198,
22915,
796,
15284,
62,
615,
70,
62,
1659,
62,
11545,
62,
77,
17024,
3419,
198,
4798,
7,
22915,
8,
628,
628,
198,
198,
22915,
796,
15284,
62,
615,
70,
62,
1659,
62,
11545,
62,
77,
17024,
62,
9641,
62,
486,
7,
1270,
11,
1542,
8,
198,
4798,
7,
22915,
8,
198,
198,
22915,
796,
15284,
62,
615,
70,
62,
1659,
62,
11545,
62,
77,
17024,
62,
9641,
62,
486,
7,
1821,
11,
2026,
8,
198,
4798,
7,
22915,
8,
198,
198,
22915,
796,
15284,
62,
615,
70,
62,
1659,
62,
11545,
62,
77,
17024,
62,
9641,
62,
486,
7,
15187,
11,
6640,
8,
198,
4798,
7,
22915,
8,
198,
198,
22915,
796,
15284,
62,
615,
70,
62,
1659,
62,
11545,
62,
77,
17024,
62,
9641,
62,
486,
7,
19214,
11,
1542,
8,
198,
4798,
7,
22915,
8,
628,
628
] | 2.456103 | 467 |
# Note:
# 1. Need dependency autoinstall
# 2. GDAL
import os
os.environ['PATH']
import gtfs2gmns as gg
gtfs_path = "H:\\ChromeDownload\\gtfscota"
gmns_path = "H:\\ChromeDownload\\gtfscota\\output"
node_transit,link_transit = gg.Convert_GTFS(gtfs_path,gmns_path) | [
2,
5740,
25,
198,
2,
352,
13,
10664,
20203,
8295,
17350,
198,
2,
362,
13,
27044,
1847,
198,
198,
11748,
28686,
198,
418,
13,
268,
2268,
17816,
34219,
20520,
198,
11748,
308,
83,
9501,
17,
39870,
5907,
355,
308,
70,
198,
198,
13655,
9501,
62,
6978,
796,
366,
39,
25,
6852,
1925,
5998,
10002,
6852,
13655,
69,
1416,
4265,
1,
198,
39870,
5907,
62,
6978,
796,
366,
39,
25,
6852,
1925,
5998,
10002,
6852,
13655,
69,
1416,
4265,
6852,
22915,
1,
198,
198,
17440,
62,
7645,
270,
11,
8726,
62,
7645,
270,
796,
308,
70,
13,
3103,
1851,
62,
38,
10234,
50,
7,
13655,
9501,
62,
6978,
11,
39870,
5907,
62,
6978,
8
] | 2.336283 | 113 |
import numpy as np
from .arpack import _arpack # type: ignore[attr-defined]
from . import eigsh
from scipy.sparse.linalg.interface import LinearOperator
from scipy.sparse import isspmatrix
from scipy.sparse.sputils import is_pydata_spmatrix
from scipy.sparse.linalg.eigen.lobpcg import lobpcg # type: ignore[no-redef]
arpack_int = _arpack.timing.nbx.dtype
__all__ = ['svds']
def svds(A, k=6, ncv=None, tol=0, which='LM', v0=None,
maxiter=None, return_singular_vectors=True,
solver='arpack', options=None):
"""
Partial singular value decomposition of a sparse matrix.
Compute the largest or smallest `k` singular values and corresponding
singular vectors of a sparse matrix `A`. The order in which the singular
values are returned is not guaranteed.
In the descriptions below, let ``M, N = A.shape``.
Parameters
----------
A : sparse matrix or LinearOperator
Matrix to decompose.
k : int, default: 6
Number of singular values and singular vectors to compute.
Must satisfy ``1 <= k < min(M, N)``.
ncv : int, optional
When ``solver='arpack'``, this is the number of Lanczos vectors
generated. See :ref:`'arpack' <sparse.linalg.svds-arpack>` for details.
When ``solver='lobpcg'``, this parameter is ignored.
tol : float, optional
Tolerance for singular values. Zero (default) means machine precision.
which : {'LM', 'SM'}
Which `k` singular values to find: either the largest magnitude ('LM')
or smallest magnitude ('SM') singular values.
v0 : ndarray, optional
The starting vector for iteration; see method-specific
documentation (:ref:`'arpack' <sparse.linalg.svds-arpack>` or
:ref:`'lobpcg' <sparse.linalg.svds-lobpcg>`) for details.
maxiter : int, optional
Maximum number of iterations; see method-specific
documentation (:ref:`'arpack' <sparse.linalg.svds-arpack>` or
:ref:`'lobpcg' <sparse.linalg.svds-lobpcg>`) for details.
return_singular_vectors : bool or str, optional
Singular values are always computed and returned; this parameter
controls the computation and return of singular vectors.
- ``True``: return singular vectors.
- ``False``: do not return singular vectors.
- ``"u"``: only return the left singular values, without computing the
right singular vectors (if ``N > M``).
- ``"vh"``: only return the right singular values, without computing
the left singular vectors (if ``N <= M``).
solver : str, optional
The solver used.
:ref:`'arpack' <sparse.linalg.svds-arpack>` and
:ref:`'lobpcg' <sparse.linalg.svds-lobpcg>` are supported.
Default: `'arpack'`.
options : dict, optional
A dictionary of solver-specific options. No solver-specific options
are currently supported; this parameter is reserved for future use.
Returns
-------
u : ndarray, shape=(M, k)
Unitary matrix having left singular vectors as columns.
If `return_singular_vectors` is ``"vh"``, this variable is not
computed, and ``None`` is returned instead.
s : ndarray, shape=(k,)
The singular values.
vh : ndarray, shape=(k, N)
Unitary matrix having right singular vectors as rows.
If `return_singular_vectors` is ``"u"``, this variable is not computed,
and ``None`` is returned instead.
Notes
-----
This is a naive implementation using ARPACK or LOBPCG as an eigensolver
on ``A.conj().T @ A`` or ``A @ A.conj().T``, depending on which one is more
efficient.
Examples
--------
Construct a matrix ``A`` from singular values and vectors.
>>> from scipy.stats import ortho_group
>>> from scipy.sparse import csc_matrix, diags
>>> from scipy.sparse.linalg import svds
>>> rng = np.random.default_rng()
>>> orthogonal = csc_matrix(ortho_group.rvs(10, random_state=rng))
>>> s = [0.0001, 0.001, 3, 4, 5] # singular values
>>> u = orthogonal[:, :5] # left singular vectors
>>> vT = orthogonal[:, 5:].T # right singular vectors
>>> A = u @ diags(s) @ vT
With only three singular values/vectors, the SVD approximates the original
matrix.
>>> u2, s2, vT2 = svds(A, k=3)
>>> A2 = u2 @ np.diag(s2) @ vT2
>>> np.allclose(A2, A.todense(), atol=1e-3)
True
With all five singular values/vectors, we can reproduce the original
matrix.
>>> u3, s3, vT3 = svds(A, k=5)
>>> A3 = u3 @ np.diag(s3) @ vT3
>>> np.allclose(A3, A.todense())
True
The singular values match the expected singular values, and the singular
values are as expected up to a difference in sign. Consequently, the
returned arrays of singular vectors must also be orthogonal.
>>> (np.allclose(s3, s) and
... np.allclose(np.abs(u3), np.abs(u.todense())) and
... np.allclose(np.abs(vT3), np.abs(vT.todense())))
True
"""
if which == 'LM':
largest = True
elif which == 'SM':
largest = False
else:
raise ValueError("which must be either 'LM' or 'SM'.")
if (not (isinstance(A, LinearOperator) or isspmatrix(A)
or is_pydata_spmatrix(A))):
A = np.asarray(A)
n, m = A.shape
if k <= 0 or k >= min(n, m):
raise ValueError("k must be between 1 and min(A.shape), k=%d" % k)
if isinstance(A, LinearOperator):
if n > m:
X_dot = A.matvec
X_matmat = A.matmat
XH_dot = A.rmatvec
XH_mat = A.rmatmat
else:
X_dot = A.rmatvec
X_matmat = A.rmatmat
XH_dot = A.matvec
XH_mat = A.matmat
dtype = getattr(A, 'dtype', None)
if dtype is None:
dtype = A.dot(np.zeros([m, 1])).dtype
else:
if n > m:
X_dot = X_matmat = A.dot
XH_dot = XH_mat = _herm(A).dot
else:
XH_dot = XH_mat = A.dot
X_dot = X_matmat = _herm(A).dot
XH_X = LinearOperator(matvec=matvec_XH_X, dtype=A.dtype,
matmat=matmat_XH_X,
shape=(min(A.shape), min(A.shape)))
# Get a low rank approximation of the implicitly defined gramian matrix.
# This is not a stable way to approach the problem.
if solver == 'lobpcg':
if k == 1 and v0 is not None:
X = np.reshape(v0, (-1, 1))
else:
X = np.random.RandomState(52).randn(min(A.shape), k)
eigvals, eigvec = lobpcg(XH_X, X, tol=tol ** 2, maxiter=maxiter,
largest=largest)
elif solver == 'arpack' or solver is None:
eigvals, eigvec = eigsh(XH_X, k=k, tol=tol ** 2, maxiter=maxiter,
ncv=ncv, which=which, v0=v0)
else:
raise ValueError("solver must be either 'arpack', or 'lobpcg'.")
# Gramian matrices have real non-negative eigenvalues.
eigvals = np.maximum(eigvals.real, 0)
# Use the sophisticated detection of small eigenvalues from pinvh.
t = eigvec.dtype.char.lower()
factor = {'f': 1E3, 'd': 1E6}
cond = factor[t] * np.finfo(t).eps
cutoff = cond * np.max(eigvals)
# Get a mask indicating which eigenpairs are not degenerately tiny,
# and create the re-ordered array of thresholded singular values.
above_cutoff = (eigvals > cutoff)
nlarge = above_cutoff.sum()
nsmall = k - nlarge
slarge = np.sqrt(eigvals[above_cutoff])
s = np.zeros_like(eigvals)
s[:nlarge] = slarge
if not return_singular_vectors:
return np.sort(s)
if n > m:
vlarge = eigvec[:, above_cutoff]
ularge = (X_matmat(vlarge) / slarge
if return_singular_vectors != 'vh' else None)
vhlarge = _herm(vlarge)
else:
ularge = eigvec[:, above_cutoff]
vhlarge = (_herm(X_matmat(ularge) / slarge)
if return_singular_vectors != 'u' else None)
u = (_augmented_orthonormal_cols(ularge, nsmall)
if ularge is not None else None)
vh = (_augmented_orthonormal_rows(vhlarge, nsmall)
if vhlarge is not None else None)
indexes_sorted = np.argsort(s)
s = s[indexes_sorted]
if u is not None:
u = u[:, indexes_sorted]
if vh is not None:
vh = vh[indexes_sorted]
return u, s, vh
| [
11748,
299,
32152,
355,
45941,
198,
198,
6738,
764,
5117,
441,
1330,
4808,
5117,
441,
220,
1303,
2099,
25,
8856,
58,
35226,
12,
23211,
60,
198,
6738,
764,
1330,
304,
328,
1477,
198,
198,
6738,
629,
541,
88,
13,
82,
29572,
13,
75,
1292,
70,
13,
39994,
1330,
44800,
18843,
1352,
198,
6738,
629,
541,
88,
13,
82,
29572,
1330,
1189,
4426,
265,
8609,
198,
6738,
629,
541,
88,
13,
82,
29572,
13,
82,
1996,
4487,
1330,
318,
62,
79,
5173,
1045,
62,
2777,
6759,
8609,
198,
6738,
629,
541,
88,
13,
82,
29572,
13,
75,
1292,
70,
13,
68,
9324,
13,
75,
672,
14751,
70,
1330,
6804,
14751,
70,
220,
1303,
2099,
25,
8856,
58,
3919,
12,
445,
891,
60,
198,
198,
5117,
441,
62,
600,
796,
4808,
5117,
441,
13,
16514,
278,
13,
46803,
87,
13,
67,
4906,
198,
834,
439,
834,
796,
37250,
21370,
9310,
20520,
628,
628,
198,
198,
4299,
38487,
9310,
7,
32,
11,
479,
28,
21,
11,
299,
33967,
28,
14202,
11,
284,
75,
28,
15,
11,
543,
11639,
31288,
3256,
410,
15,
28,
14202,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
3509,
2676,
28,
14202,
11,
1441,
62,
12215,
934,
62,
303,
5217,
28,
17821,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
1540,
332,
11639,
5117,
441,
3256,
3689,
28,
14202,
2599,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
43689,
18032,
1988,
26969,
9150,
286,
257,
29877,
17593,
13,
628,
220,
220,
220,
3082,
1133,
262,
4387,
393,
18197,
4600,
74,
63,
18032,
3815,
290,
11188,
198,
220,
220,
220,
18032,
30104,
286,
257,
29877,
17593,
4600,
32,
44646,
383,
1502,
287,
543,
262,
18032,
198,
220,
220,
220,
3815,
389,
4504,
318,
407,
11462,
13,
628,
220,
220,
220,
554,
262,
16969,
2174,
11,
1309,
7559,
44,
11,
399,
796,
317,
13,
43358,
15506,
13,
628,
220,
220,
220,
40117,
198,
220,
220,
220,
24200,
438,
198,
220,
220,
220,
317,
1058,
29877,
17593,
393,
44800,
18843,
1352,
198,
220,
220,
220,
220,
220,
220,
220,
24936,
284,
26969,
3455,
13,
198,
220,
220,
220,
479,
1058,
493,
11,
4277,
25,
718,
198,
220,
220,
220,
220,
220,
220,
220,
7913,
286,
18032,
3815,
290,
18032,
30104,
284,
24061,
13,
198,
220,
220,
220,
220,
220,
220,
220,
12039,
15959,
7559,
16,
19841,
479,
1279,
949,
7,
44,
11,
399,
8,
15506,
13,
198,
220,
220,
220,
299,
33967,
1058,
493,
11,
11902,
198,
220,
220,
220,
220,
220,
220,
220,
1649,
7559,
82,
14375,
11639,
5117,
441,
6,
15506,
11,
428,
318,
262,
1271,
286,
21534,
37925,
30104,
198,
220,
220,
220,
220,
220,
220,
220,
7560,
13,
4091,
1058,
5420,
25,
63,
6,
5117,
441,
6,
1279,
82,
29572,
13,
75,
1292,
70,
13,
21370,
9310,
12,
5117,
441,
29,
63,
329,
3307,
13,
198,
220,
220,
220,
220,
220,
220,
220,
1649,
7559,
82,
14375,
11639,
75,
672,
14751,
70,
6,
15506,
11,
428,
11507,
318,
9514,
13,
198,
220,
220,
220,
284,
75,
1058,
12178,
11,
11902,
198,
220,
220,
220,
220,
220,
220,
220,
309,
37668,
329,
18032,
3815,
13,
12169,
357,
12286,
8,
1724,
4572,
15440,
13,
198,
220,
220,
220,
543,
1058,
1391,
6,
31288,
3256,
705,
12310,
6,
92,
198,
220,
220,
220,
220,
220,
220,
220,
9022,
4600,
74,
63,
18032,
3815,
284,
1064,
25,
2035,
262,
4387,
14735,
19203,
31288,
11537,
198,
220,
220,
220,
220,
220,
220,
220,
393,
18197,
14735,
19203,
12310,
11537,
18032,
3815,
13,
198,
220,
220,
220,
410,
15,
1058,
299,
67,
18747,
11,
11902,
198,
220,
220,
220,
220,
220,
220,
220,
383,
3599,
15879,
329,
24415,
26,
766,
2446,
12,
11423,
198,
220,
220,
220,
220,
220,
220,
220,
10314,
357,
25,
5420,
25,
63,
6,
5117,
441,
6,
1279,
82,
29572,
13,
75,
1292,
70,
13,
21370,
9310,
12,
5117,
441,
29,
63,
393,
198,
220,
220,
220,
220,
220,
220,
220,
1058,
5420,
25,
63,
6,
75,
672,
14751,
70,
6,
1279,
82,
29572,
13,
75,
1292,
70,
13,
21370,
9310,
12,
75,
672,
14751,
70,
29,
63,
8,
329,
3307,
13,
198,
220,
220,
220,
3509,
2676,
1058,
493,
11,
11902,
198,
220,
220,
220,
220,
220,
220,
220,
22246,
1271,
286,
34820,
26,
766,
2446,
12,
11423,
198,
220,
220,
220,
220,
220,
220,
220,
10314,
357,
25,
5420,
25,
63,
6,
5117,
441,
6,
1279,
82,
29572,
13,
75,
1292,
70,
13,
21370,
9310,
12,
5117,
441,
29,
63,
393,
198,
220,
220,
220,
220,
220,
220,
220,
1058,
5420,
25,
63,
6,
75,
672,
14751,
70,
6,
1279,
82,
29572,
13,
75,
1292,
70,
13,
21370,
9310,
12,
75,
672,
14751,
70,
29,
63,
8,
329,
3307,
13,
198,
220,
220,
220,
1441,
62,
12215,
934,
62,
303,
5217,
1058,
20512,
393,
965,
11,
11902,
198,
220,
220,
220,
220,
220,
220,
220,
5573,
934,
3815,
389,
1464,
29231,
290,
4504,
26,
428,
11507,
198,
220,
220,
220,
220,
220,
220,
220,
6973,
262,
29964,
290,
1441,
286,
18032,
30104,
13,
628,
220,
220,
220,
220,
220,
220,
220,
532,
7559,
17821,
15506,
25,
1441,
18032,
30104,
13,
198,
220,
220,
220,
220,
220,
220,
220,
532,
7559,
25101,
15506,
25,
466,
407,
1441,
18032,
30104,
13,
198,
220,
220,
220,
220,
220,
220,
220,
532,
7559,
1,
84,
1,
15506,
25,
691,
1441,
262,
1364,
18032,
3815,
11,
1231,
14492,
262,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
826,
18032,
30104,
357,
361,
7559,
45,
1875,
337,
15506,
737,
198,
220,
220,
220,
220,
220,
220,
220,
532,
7559,
1,
85,
71,
1,
15506,
25,
691,
1441,
262,
826,
18032,
3815,
11,
1231,
14492,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
262,
1364,
18032,
30104,
357,
361,
7559,
45,
19841,
337,
15506,
737,
628,
220,
220,
220,
1540,
332,
1058,
965,
11,
11902,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
383,
1540,
332,
973,
13,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1058,
5420,
25,
63,
6,
5117,
441,
6,
1279,
82,
29572,
13,
75,
1292,
70,
13,
21370,
9310,
12,
5117,
441,
29,
63,
290,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1058,
5420,
25,
63,
6,
75,
672,
14751,
70,
6,
1279,
82,
29572,
13,
75,
1292,
70,
13,
21370,
9310,
12,
75,
672,
14751,
70,
29,
63,
389,
4855,
13,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
15161,
25,
4600,
6,
5117,
441,
6,
44646,
198,
220,
220,
220,
3689,
1058,
8633,
11,
11902,
198,
220,
220,
220,
220,
220,
220,
220,
317,
22155,
286,
1540,
332,
12,
11423,
3689,
13,
1400,
1540,
332,
12,
11423,
3689,
198,
220,
220,
220,
220,
220,
220,
220,
389,
3058,
4855,
26,
428,
11507,
318,
10395,
329,
2003,
779,
13,
628,
220,
220,
220,
16409,
198,
220,
220,
220,
35656,
198,
220,
220,
220,
334,
1058,
299,
67,
18747,
11,
5485,
16193,
44,
11,
479,
8,
198,
220,
220,
220,
220,
220,
220,
220,
791,
9331,
17593,
1719,
1364,
18032,
30104,
355,
15180,
13,
198,
220,
220,
220,
220,
220,
220,
220,
1002,
4600,
7783,
62,
12215,
934,
62,
303,
5217,
63,
318,
7559,
1,
85,
71,
1,
15506,
11,
428,
7885,
318,
407,
198,
220,
220,
220,
220,
220,
220,
220,
29231,
11,
290,
7559,
14202,
15506,
318,
4504,
2427,
13,
198,
220,
220,
220,
264,
1058,
299,
67,
18747,
11,
5485,
16193,
74,
35751,
198,
220,
220,
220,
220,
220,
220,
220,
383,
18032,
3815,
13,
198,
220,
220,
220,
410,
71,
1058,
299,
67,
18747,
11,
5485,
16193,
74,
11,
399,
8,
198,
220,
220,
220,
220,
220,
220,
220,
791,
9331,
17593,
1719,
826,
18032,
30104,
355,
15274,
13,
198,
220,
220,
220,
220,
220,
220,
220,
1002,
4600,
7783,
62,
12215,
934,
62,
303,
5217,
63,
318,
7559,
1,
84,
1,
15506,
11,
428,
7885,
318,
407,
29231,
11,
198,
220,
220,
220,
220,
220,
220,
220,
290,
7559,
14202,
15506,
318,
4504,
2427,
13,
628,
220,
220,
220,
11822,
198,
220,
220,
220,
37404,
198,
220,
220,
220,
770,
318,
257,
24354,
7822,
1262,
5923,
47,
8120,
393,
406,
9864,
5662,
38,
355,
281,
304,
328,
641,
14375,
198,
220,
220,
220,
319,
7559,
32,
13,
1102,
73,
22446,
51,
2488,
317,
15506,
393,
7559,
32,
2488,
317,
13,
1102,
73,
22446,
51,
15506,
11,
6906,
319,
543,
530,
318,
517,
198,
220,
220,
220,
6942,
13,
628,
220,
220,
220,
21066,
198,
220,
220,
220,
24200,
198,
220,
220,
220,
28407,
257,
17593,
7559,
32,
15506,
422,
18032,
3815,
290,
30104,
13,
628,
220,
220,
220,
13163,
422,
629,
541,
88,
13,
34242,
1330,
29617,
78,
62,
8094,
198,
220,
220,
220,
13163,
422,
629,
541,
88,
13,
82,
29572,
1330,
269,
1416,
62,
6759,
8609,
11,
2566,
3775,
198,
220,
220,
220,
13163,
422,
629,
541,
88,
13,
82,
29572,
13,
75,
1292,
70,
1330,
38487,
9310,
198,
220,
220,
220,
13163,
374,
782,
796,
45941,
13,
25120,
13,
12286,
62,
81,
782,
3419,
198,
220,
220,
220,
13163,
29617,
519,
20996,
796,
269,
1416,
62,
6759,
8609,
7,
1506,
78,
62,
8094,
13,
81,
14259,
7,
940,
11,
4738,
62,
5219,
28,
81,
782,
4008,
198,
220,
220,
220,
13163,
264,
796,
685,
15,
13,
18005,
11,
657,
13,
8298,
11,
513,
11,
604,
11,
642,
60,
220,
1303,
18032,
3815,
198,
220,
220,
220,
13163,
334,
796,
29617,
519,
20996,
58,
45299,
1058,
20,
60,
220,
220,
220,
220,
220,
220,
220,
220,
1303,
1364,
18032,
30104,
198,
220,
220,
220,
13163,
410,
51,
796,
29617,
519,
20996,
58,
45299,
642,
25,
4083,
51,
220,
220,
220,
220,
220,
1303,
826,
18032,
30104,
198,
220,
220,
220,
13163,
317,
796,
334,
2488,
2566,
3775,
7,
82,
8,
2488,
410,
51,
628,
220,
220,
220,
2080,
691,
1115,
18032,
3815,
14,
303,
5217,
11,
262,
311,
8898,
5561,
26748,
262,
2656,
198,
220,
220,
220,
17593,
13,
628,
220,
220,
220,
13163,
334,
17,
11,
264,
17,
11,
410,
51,
17,
796,
38487,
9310,
7,
32,
11,
479,
28,
18,
8,
198,
220,
220,
220,
13163,
317,
17,
796,
334,
17,
2488,
45941,
13,
10989,
363,
7,
82,
17,
8,
2488,
410,
51,
17,
198,
220,
220,
220,
13163,
45941,
13,
439,
19836,
7,
32,
17,
11,
317,
13,
83,
375,
1072,
22784,
379,
349,
28,
16,
68,
12,
18,
8,
198,
220,
220,
220,
6407,
628,
220,
220,
220,
2080,
477,
1936,
18032,
3815,
14,
303,
5217,
11,
356,
460,
22919,
262,
2656,
198,
220,
220,
220,
17593,
13,
628,
220,
220,
220,
13163,
334,
18,
11,
264,
18,
11,
410,
51,
18,
796,
38487,
9310,
7,
32,
11,
479,
28,
20,
8,
198,
220,
220,
220,
13163,
317,
18,
796,
334,
18,
2488,
45941,
13,
10989,
363,
7,
82,
18,
8,
2488,
410,
51,
18,
198,
220,
220,
220,
13163,
45941,
13,
439,
19836,
7,
32,
18,
11,
317,
13,
83,
375,
1072,
28955,
198,
220,
220,
220,
6407,
628,
220,
220,
220,
383,
18032,
3815,
2872,
262,
2938,
18032,
3815,
11,
290,
262,
18032,
198,
220,
220,
220,
3815,
389,
355,
2938,
510,
284,
257,
3580,
287,
1051,
13,
24982,
11,
262,
198,
220,
220,
220,
4504,
26515,
286,
18032,
30104,
1276,
635,
307,
29617,
519,
20996,
13,
628,
220,
220,
220,
13163,
357,
37659,
13,
439,
19836,
7,
82,
18,
11,
264,
8,
290,
198,
220,
220,
220,
2644,
220,
45941,
13,
439,
19836,
7,
37659,
13,
8937,
7,
84,
18,
828,
45941,
13,
8937,
7,
84,
13,
83,
375,
1072,
3419,
4008,
290,
198,
220,
220,
220,
2644,
220,
45941,
13,
439,
19836,
7,
37659,
13,
8937,
7,
85,
51,
18,
828,
45941,
13,
8937,
7,
85,
51,
13,
83,
375,
1072,
3419,
22305,
198,
220,
220,
220,
6407,
628,
220,
220,
220,
37227,
198,
220,
220,
220,
611,
543,
6624,
705,
31288,
10354,
198,
220,
220,
220,
220,
220,
220,
220,
4387,
796,
6407,
198,
220,
220,
220,
1288,
361,
543,
6624,
705,
12310,
10354,
198,
220,
220,
220,
220,
220,
220,
220,
4387,
796,
10352,
198,
220,
220,
220,
2073,
25,
198,
220,
220,
220,
220,
220,
220,
220,
5298,
11052,
12331,
7203,
4758,
1276,
307,
2035,
705,
31288,
6,
393,
705,
12310,
6,
19570,
628,
220,
220,
220,
611,
357,
1662,
357,
271,
39098,
7,
32,
11,
44800,
18843,
1352,
8,
393,
1189,
4426,
265,
8609,
7,
32,
8,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
393,
318,
62,
79,
5173,
1045,
62,
2777,
6759,
8609,
7,
32,
4008,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
317,
796,
45941,
13,
292,
18747,
7,
32,
8,
628,
220,
220,
220,
299,
11,
285,
796,
317,
13,
43358,
628,
220,
220,
220,
611,
479,
19841,
657,
393,
479,
18189,
949,
7,
77,
11,
285,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
5298,
11052,
12331,
7203,
74,
1276,
307,
1022,
352,
290,
949,
7,
32,
13,
43358,
828,
479,
28,
4,
67,
1,
4064,
479,
8,
628,
220,
220,
220,
611,
318,
39098,
7,
32,
11,
44800,
18843,
1352,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
611,
299,
1875,
285,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1395,
62,
26518,
796,
317,
13,
6759,
35138,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1395,
62,
6759,
6759,
796,
317,
13,
6759,
6759,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1395,
39,
62,
26518,
796,
317,
13,
81,
6759,
35138,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1395,
39,
62,
6759,
796,
317,
13,
81,
6759,
6759,
198,
220,
220,
220,
220,
220,
220,
220,
2073,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1395,
62,
26518,
796,
317,
13,
81,
6759,
35138,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1395,
62,
6759,
6759,
796,
317,
13,
81,
6759,
6759,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1395,
39,
62,
26518,
796,
317,
13,
6759,
35138,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1395,
39,
62,
6759,
796,
317,
13,
6759,
6759,
628,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
288,
4906,
796,
651,
35226,
7,
32,
11,
705,
67,
4906,
3256,
6045,
8,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
611,
288,
4906,
318,
6045,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
288,
4906,
796,
317,
13,
26518,
7,
37659,
13,
9107,
418,
26933,
76,
11,
352,
12962,
737,
67,
4906,
628,
220,
220,
220,
2073,
25,
198,
220,
220,
220,
220,
220,
220,
220,
611,
299,
1875,
285,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1395,
62,
26518,
796,
1395,
62,
6759,
6759,
796,
317,
13,
26518,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1395,
39,
62,
26518,
796,
1395,
39,
62,
6759,
796,
4808,
372,
76,
7,
32,
737,
26518,
198,
220,
220,
220,
220,
220,
220,
220,
2073,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1395,
39,
62,
26518,
796,
1395,
39,
62,
6759,
796,
317,
13,
26518,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1395,
62,
26518,
796,
1395,
62,
6759,
6759,
796,
4808,
372,
76,
7,
32,
737,
26518,
628,
220,
220,
220,
1395,
39,
62,
55,
796,
44800,
18843,
1352,
7,
6759,
35138,
28,
6759,
35138,
62,
55,
39,
62,
55,
11,
288,
4906,
28,
32,
13,
67,
4906,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2603,
6759,
28,
6759,
6759,
62,
55,
39,
62,
55,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
5485,
16193,
1084,
7,
32,
13,
43358,
828,
949,
7,
32,
13,
43358,
22305,
628,
220,
220,
220,
1303,
3497,
257,
1877,
4279,
40874,
286,
262,
31821,
5447,
14599,
666,
17593,
13,
198,
220,
220,
220,
1303,
770,
318,
407,
257,
8245,
835,
284,
3164,
262,
1917,
13,
198,
220,
220,
220,
611,
1540,
332,
6624,
705,
75,
672,
14751,
70,
10354,
628,
220,
220,
220,
220,
220,
220,
220,
611,
479,
6624,
352,
290,
410,
15,
318,
407,
6045,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1395,
796,
45941,
13,
3447,
1758,
7,
85,
15,
11,
13841,
16,
11,
352,
4008,
198,
220,
220,
220,
220,
220,
220,
220,
2073,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1395,
796,
45941,
13,
25120,
13,
29531,
9012,
7,
4309,
737,
25192,
77,
7,
1084,
7,
32,
13,
43358,
828,
479,
8,
628,
220,
220,
220,
220,
220,
220,
220,
304,
328,
12786,
11,
304,
328,
35138,
796,
6804,
14751,
70,
7,
55,
39,
62,
55,
11,
1395,
11,
284,
75,
28,
83,
349,
12429,
362,
11,
3509,
2676,
28,
9806,
2676,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
4387,
28,
28209,
8,
628,
220,
220,
220,
1288,
361,
1540,
332,
6624,
705,
5117,
441,
6,
393,
1540,
332,
318,
6045,
25,
198,
220,
220,
220,
220,
220,
220,
220,
304,
328,
12786,
11,
304,
328,
35138,
796,
304,
328,
1477,
7,
55,
39,
62,
55,
11,
479,
28,
74,
11,
284,
75,
28,
83,
349,
12429,
362,
11,
3509,
2676,
28,
9806,
2676,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
299,
33967,
28,
10782,
85,
11,
543,
28,
4758,
11,
410,
15,
28,
85,
15,
8,
628,
220,
220,
220,
2073,
25,
198,
220,
220,
220,
220,
220,
220,
220,
5298,
11052,
12331,
7203,
82,
14375,
1276,
307,
2035,
705,
5117,
441,
3256,
393,
705,
75,
672,
14751,
70,
6,
19570,
628,
220,
220,
220,
1303,
20159,
666,
2603,
45977,
423,
1103,
1729,
12,
31591,
304,
9324,
27160,
13,
198,
220,
220,
220,
304,
328,
12786,
796,
45941,
13,
47033,
7,
68,
328,
12786,
13,
5305,
11,
657,
8,
628,
220,
220,
220,
1303,
5765,
262,
13767,
13326,
286,
1402,
304,
9324,
27160,
422,
6757,
85,
71,
13,
198,
220,
220,
220,
256,
796,
304,
328,
35138,
13,
67,
4906,
13,
10641,
13,
21037,
3419,
198,
220,
220,
220,
5766,
796,
1391,
6,
69,
10354,
352,
36,
18,
11,
705,
67,
10354,
352,
36,
21,
92,
198,
220,
220,
220,
1779,
796,
5766,
58,
83,
60,
1635,
45941,
13,
69,
10951,
7,
83,
737,
25386,
198,
220,
220,
220,
45616,
796,
1779,
1635,
45941,
13,
9806,
7,
68,
328,
12786,
8,
628,
220,
220,
220,
1303,
3497,
257,
9335,
12739,
543,
304,
9324,
79,
3468,
389,
407,
25419,
1286,
7009,
11,
198,
220,
220,
220,
1303,
290,
2251,
262,
302,
12,
24071,
7177,
286,
11387,
276,
18032,
3815,
13,
198,
220,
220,
220,
2029,
62,
8968,
2364,
796,
357,
68,
328,
12786,
1875,
45616,
8,
198,
220,
220,
220,
299,
11664,
796,
2029,
62,
8968,
2364,
13,
16345,
3419,
198,
220,
220,
220,
299,
17470,
796,
479,
532,
299,
11664,
198,
220,
220,
220,
1017,
1376,
796,
45941,
13,
31166,
17034,
7,
68,
328,
12786,
58,
29370,
62,
8968,
2364,
12962,
198,
220,
220,
220,
264,
796,
45941,
13,
9107,
418,
62,
2339,
7,
68,
328,
12786,
8,
198,
220,
220,
220,
264,
58,
25,
77,
11664,
60,
796,
1017,
1376,
198,
220,
220,
220,
611,
407,
1441,
62,
12215,
934,
62,
303,
5217,
25,
198,
220,
220,
220,
220,
220,
220,
220,
1441,
45941,
13,
30619,
7,
82,
8,
628,
220,
220,
220,
611,
299,
1875,
285,
25,
198,
220,
220,
220,
220,
220,
220,
220,
410,
11664,
796,
304,
328,
35138,
58,
45299,
2029,
62,
8968,
2364,
60,
198,
220,
220,
220,
220,
220,
220,
220,
334,
11664,
796,
357,
55,
62,
6759,
6759,
7,
85,
11664,
8,
1220,
1017,
1376,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
611,
1441,
62,
12215,
934,
62,
303,
5217,
14512,
705,
85,
71,
6,
2073,
6045,
8,
198,
220,
220,
220,
220,
220,
220,
220,
410,
71,
11664,
796,
4808,
372,
76,
7,
85,
11664,
8,
198,
220,
220,
220,
2073,
25,
198,
220,
220,
220,
220,
220,
220,
220,
334,
11664,
796,
304,
328,
35138,
58,
45299,
2029,
62,
8968,
2364,
60,
198,
220,
220,
220,
220,
220,
220,
220,
410,
71,
11664,
796,
44104,
372,
76,
7,
55,
62,
6759,
6759,
7,
934,
469,
8,
1220,
1017,
1376,
8,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
611,
1441,
62,
12215,
934,
62,
303,
5217,
14512,
705,
84,
6,
2073,
6045,
8,
628,
220,
220,
220,
334,
796,
44104,
559,
5154,
276,
62,
1506,
261,
6636,
62,
4033,
82,
7,
934,
469,
11,
299,
17470,
8,
198,
220,
220,
220,
220,
220,
220,
220,
220,
611,
334,
11664,
318,
407,
6045,
2073,
6045,
8,
198,
220,
220,
220,
410,
71,
796,
44104,
559,
5154,
276,
62,
1506,
261,
6636,
62,
8516,
7,
85,
71,
11664,
11,
299,
17470,
8,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
611,
410,
71,
11664,
318,
407,
6045,
2073,
6045,
8,
628,
220,
220,
220,
39199,
62,
82,
9741,
796,
45941,
13,
22046,
419,
7,
82,
8,
198,
220,
220,
220,
264,
796,
264,
58,
9630,
274,
62,
82,
9741,
60,
198,
220,
220,
220,
611,
334,
318,
407,
6045,
25,
198,
220,
220,
220,
220,
220,
220,
220,
334,
796,
334,
58,
45299,
39199,
62,
82,
9741,
60,
198,
220,
220,
220,
611,
410,
71,
318,
407,
6045,
25,
198,
220,
220,
220,
220,
220,
220,
220,
410,
71,
796,
410,
71,
58,
9630,
274,
62,
82,
9741,
60,
628,
220,
220,
220,
1441,
334,
11,
264,
11,
410,
71,
198
] | 2.259536 | 3,749 |
from __future__ import absolute_import
__author__ = 'Shyue Ping Ong'
__copyright__ = 'Copyright 2013, The Materials Project'
__version__ = '0.1'
__maintainer__ = 'Shyue Ping Ong'
__email__ = '[email protected]'
__date__ = '1/24/14'
import os
from contextlib import contextmanager
@contextmanager
def cd(path):
"""
A Fabric-inspired cd context that temporarily changes directory for
performing some tasks, and returns to the original working directory
afterwards. E.g.,
with cd("/my/path/"):
do_something()
Args:
path: Path to cd to.
"""
cwd = os.getcwd()
os.chdir(path)
try:
yield
finally:
os.chdir(cwd) | [
6738,
11593,
37443,
834,
1330,
4112,
62,
11748,
198,
198,
834,
9800,
834,
796,
705,
2484,
88,
518,
34263,
48041,
6,
198,
834,
22163,
4766,
834,
796,
705,
15269,
2211,
11,
383,
24310,
4935,
6,
198,
834,
9641,
834,
796,
705,
15,
13,
16,
6,
198,
834,
76,
2913,
10613,
834,
796,
705,
2484,
88,
518,
34263,
48041,
6,
198,
834,
12888,
834,
796,
705,
506,
2777,
31,
1229,
21282,
13,
15532,
6,
198,
834,
4475,
834,
796,
705,
16,
14,
1731,
14,
1415,
6,
198,
198,
11748,
28686,
198,
198,
6738,
4732,
8019,
1330,
4732,
37153,
628,
198,
31,
22866,
37153,
198,
4299,
22927,
7,
6978,
2599,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
317,
37759,
12,
24194,
22927,
4732,
326,
13413,
2458,
8619,
329,
198,
220,
220,
220,
9489,
617,
8861,
11,
290,
5860,
284,
262,
2656,
1762,
8619,
198,
220,
220,
220,
12979,
13,
412,
13,
70,
1539,
628,
220,
220,
220,
220,
220,
220,
220,
351,
22927,
7203,
14,
1820,
14,
6978,
30487,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
466,
62,
18927,
3419,
628,
220,
220,
220,
943,
14542,
25,
198,
220,
220,
220,
220,
220,
220,
220,
3108,
25,
10644,
284,
22927,
284,
13,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
269,
16993,
796,
28686,
13,
1136,
66,
16993,
3419,
198,
220,
220,
220,
28686,
13,
354,
15908,
7,
6978,
8,
198,
220,
220,
220,
1949,
25,
198,
220,
220,
220,
220,
220,
220,
220,
7800,
198,
220,
220,
220,
3443,
25,
198,
220,
220,
220,
220,
220,
220,
220,
28686,
13,
354,
15908,
7,
66,
16993,
8
] | 2.521898 | 274 |
"""
Infinite evaluation loop going through the checkpoints in the model directory
as they appear and evaluating them. Accuracy and average loss are printed and
added as tensorboard summaries.
"""
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
from datetime import datetime
import json
import math
import os
import sys
import time
import tensorflow as tf
from tensorflow.examples.tutorials.mnist import input_data
from model import Model
from pgd_attack import LinfPGDAttack
# Global constants
with open('config.json') as config_file:
config = json.load(config_file)
num_eval_examples = config['num_eval_examples']
eval_batch_size = config['eval_batch_size']
eval_on_cpu = config['eval_on_cpu']
model_dir = config['model_dir']
# Set upd the data, hyperparameters, and the model
mnist = input_data.read_data_sets('MNIST_data', one_hot=False)
if eval_on_cpu:
with tf.device("/cpu:0"):
model = Model()
attack = LinfPGDAttack(model,
config['epsilon'],
config['k'],
config['a'],
config['random_start'],
config['loss_func'])
else:
model = Model()
attack = LinfPGDAttack(model,
config['epsilon'],
config['k'],
config['a'],
config['random_start'],
config['loss_func'])
global_step = tf.contrib.framework.get_or_create_global_step()
# Setting up the Tensorboard and checkpoint outputs
if not os.path.exists(model_dir):
os.makedirs(model_dir)
eval_dir = os.path.join(model_dir, 'eval')
if not os.path.exists(eval_dir):
os.makedirs(eval_dir)
last_checkpoint_filename = ''
already_seen_state = False
saver = tf.train.Saver()
summary_writer = tf.summary.FileWriter(eval_dir)
# A function for evaluating a single checkpoint
# Infinite eval loop
while True:
cur_checkpoint = tf.train.latest_checkpoint(model_dir)
# Case 1: No checkpoint yet
if cur_checkpoint is None:
if not already_seen_state:
print('No checkpoint yet, waiting ...', end='')
already_seen_state = True
else:
print('.', end='')
sys.stdout.flush()
time.sleep(10)
# Case 2: Previously unseen checkpoint
elif cur_checkpoint != last_checkpoint_filename:
print('\nCheckpoint {}, evaluating ... ({})'.format(cur_checkpoint,
datetime.now()))
sys.stdout.flush()
last_checkpoint_filename = cur_checkpoint
already_seen_state = False
evaluate_checkpoint(cur_checkpoint)
# Case 3: Previously evaluated checkpoint
else:
if not already_seen_state:
print('Waiting for the next checkpoint ... ({}) '.format(
datetime.now()),
end='')
already_seen_state = True
else:
print('.', end='')
sys.stdout.flush()
time.sleep(10)
| [
37811,
201,
198,
18943,
9504,
12660,
9052,
1016,
832,
262,
36628,
287,
262,
2746,
8619,
201,
198,
292,
484,
1656,
290,
22232,
606,
13,
33222,
290,
2811,
2994,
389,
10398,
290,
201,
198,
29373,
355,
11192,
273,
3526,
30114,
3166,
13,
201,
198,
37811,
201,
198,
6738,
11593,
37443,
834,
1330,
4112,
62,
11748,
201,
198,
6738,
11593,
37443,
834,
1330,
7297,
201,
198,
6738,
11593,
37443,
834,
1330,
3601,
62,
8818,
201,
198,
201,
198,
6738,
4818,
8079,
1330,
4818,
8079,
201,
198,
11748,
33918,
201,
198,
11748,
10688,
201,
198,
11748,
28686,
201,
198,
11748,
25064,
201,
198,
11748,
640,
201,
198,
201,
198,
11748,
11192,
273,
11125,
355,
48700,
201,
198,
6738,
11192,
273,
11125,
13,
1069,
12629,
13,
83,
44917,
82,
13,
10295,
396,
1330,
5128,
62,
7890,
201,
198,
201,
198,
6738,
2746,
1330,
9104,
201,
198,
6738,
279,
21287,
62,
20358,
1330,
5164,
69,
6968,
5631,
926,
441,
201,
198,
201,
198,
2,
8060,
38491,
201,
198,
4480,
1280,
10786,
11250,
13,
17752,
11537,
355,
4566,
62,
7753,
25,
201,
198,
220,
220,
220,
4566,
796,
33918,
13,
2220,
7,
11250,
62,
7753,
8,
201,
198,
22510,
62,
18206,
62,
1069,
12629,
796,
4566,
17816,
22510,
62,
18206,
62,
1069,
12629,
20520,
201,
198,
18206,
62,
43501,
62,
7857,
796,
4566,
17816,
18206,
62,
43501,
62,
7857,
20520,
201,
198,
18206,
62,
261,
62,
36166,
796,
4566,
17816,
18206,
62,
261,
62,
36166,
20520,
201,
198,
201,
198,
19849,
62,
15908,
796,
4566,
17816,
19849,
62,
15908,
20520,
201,
198,
201,
198,
2,
5345,
2325,
262,
1366,
11,
8718,
17143,
7307,
11,
290,
262,
2746,
201,
198,
10295,
396,
796,
5128,
62,
7890,
13,
961,
62,
7890,
62,
28709,
10786,
39764,
8808,
62,
7890,
3256,
530,
62,
8940,
28,
25101,
8,
201,
198,
201,
198,
361,
5418,
62,
261,
62,
36166,
25,
201,
198,
220,
220,
220,
351,
48700,
13,
25202,
7203,
14,
36166,
25,
15,
1,
2599,
201,
198,
220,
220,
220,
220,
220,
220,
220,
2746,
796,
9104,
3419,
201,
198,
220,
220,
220,
220,
220,
220,
220,
1368,
796,
5164,
69,
6968,
5631,
926,
441,
7,
19849,
11,
201,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
4566,
17816,
538,
18217,
261,
6,
4357,
201,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
4566,
17816,
74,
6,
4357,
201,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
4566,
17816,
64,
6,
4357,
201,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
4566,
17816,
25120,
62,
9688,
6,
4357,
201,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
4566,
17816,
22462,
62,
20786,
6,
12962,
201,
198,
17772,
25,
201,
198,
220,
220,
220,
2746,
796,
9104,
3419,
201,
198,
220,
220,
220,
1368,
796,
5164,
69,
6968,
5631,
926,
441,
7,
19849,
11,
201,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
4566,
17816,
538,
18217,
261,
6,
4357,
201,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
4566,
17816,
74,
6,
4357,
201,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
4566,
17816,
64,
6,
4357,
201,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
4566,
17816,
25120,
62,
9688,
6,
4357,
201,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
4566,
17816,
22462,
62,
20786,
6,
12962,
201,
198,
201,
198,
20541,
62,
9662,
796,
48700,
13,
3642,
822,
13,
30604,
13,
1136,
62,
273,
62,
17953,
62,
20541,
62,
9662,
3419,
201,
198,
201,
198,
2,
25700,
510,
262,
309,
22854,
3526,
290,
26954,
23862,
201,
198,
361,
407,
28686,
13,
6978,
13,
1069,
1023,
7,
19849,
62,
15908,
2599,
201,
198,
220,
220,
220,
28686,
13,
76,
4335,
17062,
7,
19849,
62,
15908,
8,
201,
198,
18206,
62,
15908,
796,
28686,
13,
6978,
13,
22179,
7,
19849,
62,
15908,
11,
705,
18206,
11537,
201,
198,
361,
407,
28686,
13,
6978,
13,
1069,
1023,
7,
18206,
62,
15908,
2599,
201,
198,
220,
220,
220,
28686,
13,
76,
4335,
17062,
7,
18206,
62,
15908,
8,
201,
198,
201,
198,
12957,
62,
9122,
4122,
62,
34345,
796,
10148,
201,
198,
282,
1493,
62,
15898,
62,
5219,
796,
10352,
201,
198,
201,
198,
82,
8770,
796,
48700,
13,
27432,
13,
50,
8770,
3419,
201,
198,
49736,
62,
16002,
796,
48700,
13,
49736,
13,
8979,
34379,
7,
18206,
62,
15908,
8,
201,
198,
201,
198,
201,
198,
2,
317,
2163,
329,
22232,
257,
2060,
26954,
201,
198,
201,
198,
201,
198,
2,
22380,
5418,
9052,
201,
198,
4514,
6407,
25,
201,
198,
220,
220,
220,
1090,
62,
9122,
4122,
796,
48700,
13,
27432,
13,
42861,
62,
9122,
4122,
7,
19849,
62,
15908,
8,
201,
198,
201,
198,
220,
220,
220,
1303,
8913,
352,
25,
1400,
26954,
1865,
201,
198,
220,
220,
220,
611,
1090,
62,
9122,
4122,
318,
6045,
25,
201,
198,
220,
220,
220,
220,
220,
220,
220,
611,
407,
1541,
62,
15898,
62,
5219,
25,
201,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
3601,
10786,
2949,
26954,
1865,
11,
4953,
2644,
3256,
886,
28,
7061,
8,
201,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1541,
62,
15898,
62,
5219,
796,
6407,
201,
198,
220,
220,
220,
220,
220,
220,
220,
2073,
25,
201,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
3601,
10786,
2637,
11,
886,
28,
7061,
8,
201,
198,
220,
220,
220,
220,
220,
220,
220,
25064,
13,
19282,
448,
13,
25925,
3419,
201,
198,
220,
220,
220,
220,
220,
220,
220,
640,
13,
42832,
7,
940,
8,
201,
198,
220,
220,
220,
1303,
8913,
362,
25,
29875,
29587,
26954,
201,
198,
220,
220,
220,
1288,
361,
1090,
62,
9122,
4122,
14512,
938,
62,
9122,
4122,
62,
34345,
25,
201,
198,
220,
220,
220,
220,
220,
220,
220,
3601,
10786,
59,
77,
9787,
4122,
1391,
5512,
22232,
2644,
220,
220,
37913,
30072,
4458,
18982,
7,
22019,
62,
9122,
4122,
11,
201,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
4818,
8079,
13,
2197,
3419,
4008,
201,
198,
220,
220,
220,
220,
220,
220,
220,
25064,
13,
19282,
448,
13,
25925,
3419,
201,
198,
220,
220,
220,
220,
220,
220,
220,
938,
62,
9122,
4122,
62,
34345,
796,
1090,
62,
9122,
4122,
201,
198,
220,
220,
220,
220,
220,
220,
220,
1541,
62,
15898,
62,
5219,
796,
10352,
201,
198,
220,
220,
220,
220,
220,
220,
220,
13446,
62,
9122,
4122,
7,
22019,
62,
9122,
4122,
8,
201,
198,
220,
220,
220,
1303,
8913,
513,
25,
29875,
16726,
26954,
201,
198,
220,
220,
220,
2073,
25,
201,
198,
220,
220,
220,
220,
220,
220,
220,
611,
407,
1541,
62,
15898,
62,
5219,
25,
201,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
3601,
10786,
33484,
1780,
329,
262,
1306,
26954,
2644,
220,
220,
37913,
30072,
220,
220,
45302,
18982,
7,
201,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
4818,
8079,
13,
2197,
3419,
828,
201,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
886,
28,
7061,
8,
201,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1541,
62,
15898,
62,
5219,
796,
6407,
201,
198,
220,
220,
220,
220,
220,
220,
220,
2073,
25,
201,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
3601,
10786,
2637,
11,
886,
28,
7061,
8,
201,
198,
220,
220,
220,
220,
220,
220,
220,
25064,
13,
19282,
448,
13,
25925,
3419,
201,
198,
220,
220,
220,
220,
220,
220,
220,
640,
13,
42832,
7,
940,
8,
201,
198
] | 2.146518 | 1,522 |
from unittest import TestCase
import pandas as pd
from pytz import UTC
from exchange_calendars.exchange_calendar_xbse import XBSEExchangeCalendar
from .test_exchange_calendar import ExchangeCalendarTestBase
| [
6738,
555,
715,
395,
1330,
6208,
20448,
198,
198,
11748,
19798,
292,
355,
279,
67,
198,
6738,
12972,
22877,
1330,
18119,
198,
198,
6738,
5163,
62,
9948,
44942,
13,
1069,
3803,
62,
9948,
9239,
62,
30894,
325,
1330,
1395,
4462,
36,
3109,
3803,
9771,
9239,
198,
198,
6738,
764,
9288,
62,
1069,
3803,
62,
9948,
9239,
1330,
12516,
9771,
9239,
14402,
14881,
628
] | 3.349206 | 63 |
# author: kagemeka
# created: 2019-11-06 12:47:30(JST)
import sys
# import collections
# import math
# import string
# import bisect
# import re
# import itertools
# import statistics
if __name__ == "__main__":
# execute only if run as a script
main()
| [
2,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1772,
25,
220,
479,
363,
368,
38001,
201,
198,
2,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2727,
25,
13130,
12,
1157,
12,
3312,
1105,
25,
2857,
25,
1270,
7,
41,
2257,
8,
201,
198,
11748,
25064,
201,
198,
201,
198,
2,
1330,
17268,
201,
198,
2,
1330,
10688,
201,
198,
2,
1330,
4731,
201,
198,
2,
1330,
47457,
478,
201,
198,
2,
1330,
302,
201,
198,
2,
1330,
340,
861,
10141,
201,
198,
2,
1330,
7869,
201,
198,
201,
198,
201,
198,
201,
198,
361,
11593,
3672,
834,
6624,
366,
834,
12417,
834,
1298,
201,
198,
220,
220,
220,
1303,
12260,
691,
611,
1057,
355,
257,
4226,
201,
198,
220,
220,
220,
1388,
3419,
201,
198
] | 2.075472 | 159 |
# This an autogenerated file
#
# Generated with PlotNode
from typing import Dict,Sequence,List
from dmt.entity import Entity
from dmt.blueprint import Blueprint
from .blueprints.plotnode import PlotNodeBlueprint
from typing import Dict
from sima.post.controlsignalinputslot import ControlSignalInputSlot
from sima.post.figuretemplate import FigureTemplate
from sima.post.inputslot import InputSlot
from sima.post.outputnode import OutputNode
from sima.post.outputslot import OutputSlot
from sima.post.traceconfiguration import TraceConfiguration
from sima.sima.scriptablevalue import ScriptableValue
class PlotNode(OutputNode):
"""
Keyword arguments
-----------------
name : str
(default "")
description : str
(default "")
_id : str
(default "")
scriptableValues : List[ScriptableValue]
x : int
(default 0)
y : int
(default 0)
h : int
(default 0)
w : int
(default 0)
controlSignalInputSlots : List[ControlSignalInputSlot]
inputSlot : InputSlot
figureTemplate : FigureTemplate
traces : List[TraceConfiguration]
fixed : bool
(default False)
title : str
(default "")
xLabel : str
(default "")
yLabel : str
(default "")
selectAll : bool
Will export all signals as plot(default False)
outputSlot : OutputSlot
createImages : bool
Create images and store these to disk. The output will then be the paths to the images(default True)
"""
@property
def blueprint(self) -> Blueprint:
"""Return blueprint that this entity represents"""
return PlotNodeBlueprint()
@property
def name(self) -> str:
""""""
return self.__name
@name.setter
def name(self, value: str):
"""Set name"""
self.__name = str(value)
@property
def description(self) -> str:
""""""
return self.__description
@description.setter
def description(self, value: str):
"""Set description"""
self.__description = str(value)
@property
def _id(self) -> str:
""""""
return self.___id
@_id.setter
def _id(self, value: str):
"""Set _id"""
self.___id = str(value)
@property
def scriptableValues(self) -> List[ScriptableValue]:
""""""
return self.__scriptableValues
@scriptableValues.setter
def scriptableValues(self, value: List[ScriptableValue]):
"""Set scriptableValues"""
if not isinstance(value, Sequence):
raise Exception("Expected sequense, but was " , type(value))
self.__scriptableValues = value
@property
def x(self) -> int:
""""""
return self.__x
@x.setter
def x(self, value: int):
"""Set x"""
self.__x = int(value)
@property
def y(self) -> int:
""""""
return self.__y
@y.setter
def y(self, value: int):
"""Set y"""
self.__y = int(value)
@property
def h(self) -> int:
""""""
return self.__h
@h.setter
def h(self, value: int):
"""Set h"""
self.__h = int(value)
@property
def w(self) -> int:
""""""
return self.__w
@w.setter
def w(self, value: int):
"""Set w"""
self.__w = int(value)
@property
def controlSignalInputSlots(self) -> List[ControlSignalInputSlot]:
""""""
return self.__controlSignalInputSlots
@controlSignalInputSlots.setter
def controlSignalInputSlots(self, value: List[ControlSignalInputSlot]):
"""Set controlSignalInputSlots"""
if not isinstance(value, Sequence):
raise Exception("Expected sequense, but was " , type(value))
self.__controlSignalInputSlots = value
@property
def inputSlot(self) -> InputSlot:
""""""
return self.__inputSlot
@inputSlot.setter
def inputSlot(self, value: InputSlot):
"""Set inputSlot"""
self.__inputSlot = value
@property
def figureTemplate(self) -> FigureTemplate:
""""""
return self.__figureTemplate
@figureTemplate.setter
def figureTemplate(self, value: FigureTemplate):
"""Set figureTemplate"""
self.__figureTemplate = value
@property
def traces(self) -> List[TraceConfiguration]:
""""""
return self.__traces
@traces.setter
def traces(self, value: List[TraceConfiguration]):
"""Set traces"""
if not isinstance(value, Sequence):
raise Exception("Expected sequense, but was " , type(value))
self.__traces = value
@property
def fixed(self) -> bool:
""""""
return self.__fixed
@fixed.setter
def fixed(self, value: bool):
"""Set fixed"""
self.__fixed = bool(value)
@property
def title(self) -> str:
""""""
return self.__title
@title.setter
def title(self, value: str):
"""Set title"""
self.__title = str(value)
@property
def xLabel(self) -> str:
""""""
return self.__xLabel
@xLabel.setter
def xLabel(self, value: str):
"""Set xLabel"""
self.__xLabel = str(value)
@property
def yLabel(self) -> str:
""""""
return self.__yLabel
@yLabel.setter
def yLabel(self, value: str):
"""Set yLabel"""
self.__yLabel = str(value)
@property
def selectAll(self) -> bool:
"""Will export all signals as plot"""
return self.__selectAll
@selectAll.setter
def selectAll(self, value: bool):
"""Set selectAll"""
self.__selectAll = bool(value)
@property
def outputSlot(self) -> OutputSlot:
""""""
return self.__outputSlot
@outputSlot.setter
def outputSlot(self, value: OutputSlot):
"""Set outputSlot"""
self.__outputSlot = value
@property
def createImages(self) -> bool:
"""Create images and store these to disk. The output will then be the paths to the images"""
return self.__createImages
@createImages.setter
def createImages(self, value: bool):
"""Set createImages"""
self.__createImages = bool(value)
| [
2,
770,
281,
1960,
519,
877,
515,
2393,
198,
2,
220,
198,
2,
2980,
515,
351,
28114,
19667,
198,
6738,
19720,
1330,
360,
713,
11,
44015,
594,
11,
8053,
198,
6738,
288,
16762,
13,
26858,
1330,
20885,
198,
6738,
288,
16762,
13,
17585,
4798,
1330,
39932,
198,
6738,
764,
17585,
17190,
13,
29487,
17440,
1330,
28114,
19667,
14573,
4798,
198,
6738,
19720,
1330,
360,
713,
198,
6738,
985,
64,
13,
7353,
13,
13716,
12683,
14414,
1996,
43384,
1330,
6779,
11712,
282,
20560,
38963,
198,
6738,
985,
64,
13,
7353,
13,
26875,
28243,
1330,
11291,
30800,
198,
6738,
985,
64,
13,
7353,
13,
15414,
43384,
1330,
23412,
38963,
198,
6738,
985,
64,
13,
7353,
13,
22915,
17440,
1330,
25235,
19667,
198,
6738,
985,
64,
13,
7353,
13,
22915,
43384,
1330,
25235,
38963,
198,
6738,
985,
64,
13,
7353,
13,
40546,
11250,
3924,
1330,
34912,
38149,
198,
6738,
985,
64,
13,
82,
8083,
13,
12048,
540,
8367,
1330,
12327,
540,
11395,
198,
198,
4871,
28114,
19667,
7,
26410,
19667,
2599,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
7383,
4775,
7159,
198,
220,
220,
220,
34400,
12,
198,
220,
220,
220,
1438,
1058,
965,
198,
220,
220,
220,
220,
220,
220,
220,
220,
357,
12286,
366,
4943,
198,
220,
220,
220,
6764,
1058,
965,
198,
220,
220,
220,
220,
220,
220,
220,
220,
357,
12286,
366,
4943,
198,
220,
220,
220,
4808,
312,
1058,
965,
198,
220,
220,
220,
220,
220,
220,
220,
220,
357,
12286,
366,
4943,
198,
220,
220,
220,
4226,
540,
40161,
1058,
7343,
58,
7391,
540,
11395,
60,
198,
220,
220,
220,
2124,
1058,
493,
198,
220,
220,
220,
220,
220,
220,
220,
220,
357,
12286,
657,
8,
198,
220,
220,
220,
331,
1058,
493,
198,
220,
220,
220,
220,
220,
220,
220,
220,
357,
12286,
657,
8,
198,
220,
220,
220,
289,
1058,
493,
198,
220,
220,
220,
220,
220,
220,
220,
220,
357,
12286,
657,
8,
198,
220,
220,
220,
266,
1058,
493,
198,
220,
220,
220,
220,
220,
220,
220,
220,
357,
12286,
657,
8,
198,
220,
220,
220,
1630,
11712,
282,
20560,
11122,
1747,
1058,
7343,
58,
15988,
11712,
282,
20560,
38963,
60,
198,
220,
220,
220,
5128,
38963,
1058,
23412,
38963,
198,
220,
220,
220,
3785,
30800,
1058,
11291,
30800,
198,
220,
220,
220,
20675,
1058,
7343,
58,
2898,
558,
38149,
60,
198,
220,
220,
220,
5969,
1058,
20512,
198,
220,
220,
220,
220,
220,
220,
220,
220,
357,
12286,
10352,
8,
198,
220,
220,
220,
3670,
1058,
965,
198,
220,
220,
220,
220,
220,
220,
220,
220,
357,
12286,
366,
4943,
198,
220,
220,
220,
2124,
33986,
1058,
965,
198,
220,
220,
220,
220,
220,
220,
220,
220,
357,
12286,
366,
4943,
198,
220,
220,
220,
331,
33986,
1058,
965,
198,
220,
220,
220,
220,
220,
220,
220,
220,
357,
12286,
366,
4943,
198,
220,
220,
220,
2922,
3237,
1058,
20512,
198,
220,
220,
220,
220,
220,
220,
220,
220,
2561,
10784,
477,
10425,
355,
7110,
7,
12286,
10352,
8,
198,
220,
220,
220,
5072,
38963,
1058,
25235,
38963,
198,
220,
220,
220,
2251,
29398,
1058,
20512,
198,
220,
220,
220,
220,
220,
220,
220,
220,
13610,
4263,
290,
3650,
777,
284,
11898,
13,
383,
5072,
481,
788,
307,
262,
13532,
284,
262,
4263,
7,
12286,
6407,
8,
198,
220,
220,
220,
37227,
628,
198,
220,
220,
220,
2488,
26745,
198,
220,
220,
220,
825,
30881,
7,
944,
8,
4613,
39932,
25,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
13615,
30881,
326,
428,
9312,
6870,
37811,
198,
220,
220,
220,
220,
220,
220,
220,
1441,
28114,
19667,
14573,
4798,
3419,
628,
198,
220,
220,
220,
2488,
26745,
198,
220,
220,
220,
825,
1438,
7,
944,
8,
4613,
965,
25,
198,
220,
220,
220,
220,
220,
220,
220,
13538,
15931,
15931,
198,
220,
220,
220,
220,
220,
220,
220,
1441,
2116,
13,
834,
3672,
628,
220,
220,
220,
2488,
3672,
13,
2617,
353,
198,
220,
220,
220,
825,
1438,
7,
944,
11,
1988,
25,
965,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
7248,
1438,
37811,
198,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
834,
3672,
796,
965,
7,
8367,
8,
628,
220,
220,
220,
2488,
26745,
198,
220,
220,
220,
825,
6764,
7,
944,
8,
4613,
965,
25,
198,
220,
220,
220,
220,
220,
220,
220,
13538,
15931,
15931,
198,
220,
220,
220,
220,
220,
220,
220,
1441,
2116,
13,
834,
11213,
628,
220,
220,
220,
2488,
11213,
13,
2617,
353,
198,
220,
220,
220,
825,
6764,
7,
944,
11,
1988,
25,
965,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
7248,
6764,
37811,
198,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
834,
11213,
796,
965,
7,
8367,
8,
628,
220,
220,
220,
2488,
26745,
198,
220,
220,
220,
825,
4808,
312,
7,
944,
8,
4613,
965,
25,
198,
220,
220,
220,
220,
220,
220,
220,
13538,
15931,
15931,
198,
220,
220,
220,
220,
220,
220,
220,
1441,
2116,
13,
17569,
312,
628,
220,
220,
220,
2488,
62,
312,
13,
2617,
353,
198,
220,
220,
220,
825,
4808,
312,
7,
944,
11,
1988,
25,
965,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
7248,
4808,
312,
37811,
198,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
17569,
312,
796,
965,
7,
8367,
8,
628,
220,
220,
220,
2488,
26745,
198,
220,
220,
220,
825,
4226,
540,
40161,
7,
944,
8,
4613,
7343,
58,
7391,
540,
11395,
5974,
198,
220,
220,
220,
220,
220,
220,
220,
13538,
15931,
15931,
198,
220,
220,
220,
220,
220,
220,
220,
1441,
2116,
13,
834,
12048,
540,
40161,
628,
220,
220,
220,
2488,
12048,
540,
40161,
13,
2617,
353,
198,
220,
220,
220,
825,
4226,
540,
40161,
7,
944,
11,
1988,
25,
7343,
58,
7391,
540,
11395,
60,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
7248,
4226,
540,
40161,
37811,
198,
220,
220,
220,
220,
220,
220,
220,
611,
407,
318,
39098,
7,
8367,
11,
45835,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
5298,
35528,
7203,
3109,
7254,
4726,
1072,
11,
475,
373,
366,
837,
2099,
7,
8367,
4008,
198,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
834,
12048,
540,
40161,
796,
1988,
628,
220,
220,
220,
2488,
26745,
198,
220,
220,
220,
825,
2124,
7,
944,
8,
4613,
493,
25,
198,
220,
220,
220,
220,
220,
220,
220,
13538,
15931,
15931,
198,
220,
220,
220,
220,
220,
220,
220,
1441,
2116,
13,
834,
87,
628,
220,
220,
220,
2488,
87,
13,
2617,
353,
198,
220,
220,
220,
825,
2124,
7,
944,
11,
1988,
25,
493,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
7248,
2124,
37811,
198,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
834,
87,
796,
493,
7,
8367,
8,
628,
220,
220,
220,
2488,
26745,
198,
220,
220,
220,
825,
331,
7,
944,
8,
4613,
493,
25,
198,
220,
220,
220,
220,
220,
220,
220,
13538,
15931,
15931,
198,
220,
220,
220,
220,
220,
220,
220,
1441,
2116,
13,
834,
88,
628,
220,
220,
220,
2488,
88,
13,
2617,
353,
198,
220,
220,
220,
825,
331,
7,
944,
11,
1988,
25,
493,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
7248,
331,
37811,
198,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
834,
88,
796,
493,
7,
8367,
8,
628,
220,
220,
220,
2488,
26745,
198,
220,
220,
220,
825,
289,
7,
944,
8,
4613,
493,
25,
198,
220,
220,
220,
220,
220,
220,
220,
13538,
15931,
15931,
198,
220,
220,
220,
220,
220,
220,
220,
1441,
2116,
13,
834,
71,
628,
220,
220,
220,
2488,
71,
13,
2617,
353,
198,
220,
220,
220,
825,
289,
7,
944,
11,
1988,
25,
493,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
7248,
289,
37811,
198,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
834,
71,
796,
493,
7,
8367,
8,
628,
220,
220,
220,
2488,
26745,
198,
220,
220,
220,
825,
266,
7,
944,
8,
4613,
493,
25,
198,
220,
220,
220,
220,
220,
220,
220,
13538,
15931,
15931,
198,
220,
220,
220,
220,
220,
220,
220,
1441,
2116,
13,
834,
86,
628,
220,
220,
220,
2488,
86,
13,
2617,
353,
198,
220,
220,
220,
825,
266,
7,
944,
11,
1988,
25,
493,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
7248,
266,
37811,
198,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
834,
86,
796,
493,
7,
8367,
8,
628,
220,
220,
220,
2488,
26745,
198,
220,
220,
220,
825,
1630,
11712,
282,
20560,
11122,
1747,
7,
944,
8,
4613,
7343,
58,
15988,
11712,
282,
20560,
38963,
5974,
198,
220,
220,
220,
220,
220,
220,
220,
13538,
15931,
15931,
198,
220,
220,
220,
220,
220,
220,
220,
1441,
2116,
13,
834,
13716,
11712,
282,
20560,
11122,
1747,
628,
220,
220,
220,
2488,
13716,
11712,
282,
20560,
11122,
1747,
13,
2617,
353,
198,
220,
220,
220,
825,
1630,
11712,
282,
20560,
11122,
1747,
7,
944,
11,
1988,
25,
7343,
58,
15988,
11712,
282,
20560,
38963,
60,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
7248,
1630,
11712,
282,
20560,
11122,
1747,
37811,
198,
220,
220,
220,
220,
220,
220,
220,
611,
407,
318,
39098,
7,
8367,
11,
45835,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
5298,
35528,
7203,
3109,
7254,
4726,
1072,
11,
475,
373,
366,
837,
2099,
7,
8367,
4008,
198,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
834,
13716,
11712,
282,
20560,
11122,
1747,
796,
1988,
628,
220,
220,
220,
2488,
26745,
198,
220,
220,
220,
825,
5128,
38963,
7,
944,
8,
4613,
23412,
38963,
25,
198,
220,
220,
220,
220,
220,
220,
220,
13538,
15931,
15931,
198,
220,
220,
220,
220,
220,
220,
220,
1441,
2116,
13,
834,
15414,
38963,
628,
220,
220,
220,
2488,
15414,
38963,
13,
2617,
353,
198,
220,
220,
220,
825,
5128,
38963,
7,
944,
11,
1988,
25,
23412,
38963,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
7248,
5128,
38963,
37811,
198,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
834,
15414,
38963,
796,
1988,
628,
220,
220,
220,
2488,
26745,
198,
220,
220,
220,
825,
3785,
30800,
7,
944,
8,
4613,
11291,
30800,
25,
198,
220,
220,
220,
220,
220,
220,
220,
13538,
15931,
15931,
198,
220,
220,
220,
220,
220,
220,
220,
1441,
2116,
13,
834,
26875,
30800,
628,
220,
220,
220,
2488,
26875,
30800,
13,
2617,
353,
198,
220,
220,
220,
825,
3785,
30800,
7,
944,
11,
1988,
25,
11291,
30800,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
7248,
3785,
30800,
37811,
198,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
834,
26875,
30800,
796,
1988,
628,
220,
220,
220,
2488,
26745,
198,
220,
220,
220,
825,
20675,
7,
944,
8,
4613,
7343,
58,
2898,
558,
38149,
5974,
198,
220,
220,
220,
220,
220,
220,
220,
13538,
15931,
15931,
198,
220,
220,
220,
220,
220,
220,
220,
1441,
2116,
13,
834,
2213,
2114,
628,
220,
220,
220,
2488,
2213,
2114,
13,
2617,
353,
198,
220,
220,
220,
825,
20675,
7,
944,
11,
1988,
25,
7343,
58,
2898,
558,
38149,
60,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
7248,
20675,
37811,
198,
220,
220,
220,
220,
220,
220,
220,
611,
407,
318,
39098,
7,
8367,
11,
45835,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
5298,
35528,
7203,
3109,
7254,
4726,
1072,
11,
475,
373,
366,
837,
2099,
7,
8367,
4008,
198,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
834,
2213,
2114,
796,
1988,
628,
220,
220,
220,
2488,
26745,
198,
220,
220,
220,
825,
5969,
7,
944,
8,
4613,
20512,
25,
198,
220,
220,
220,
220,
220,
220,
220,
13538,
15931,
15931,
198,
220,
220,
220,
220,
220,
220,
220,
1441,
2116,
13,
834,
34021,
628,
220,
220,
220,
2488,
34021,
13,
2617,
353,
198,
220,
220,
220,
825,
5969,
7,
944,
11,
1988,
25,
20512,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
7248,
5969,
37811,
198,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
834,
34021,
796,
20512,
7,
8367,
8,
628,
220,
220,
220,
2488,
26745,
198,
220,
220,
220,
825,
3670,
7,
944,
8,
4613,
965,
25,
198,
220,
220,
220,
220,
220,
220,
220,
13538,
15931,
15931,
198,
220,
220,
220,
220,
220,
220,
220,
1441,
2116,
13,
834,
7839,
628,
220,
220,
220,
2488,
7839,
13,
2617,
353,
198,
220,
220,
220,
825,
3670,
7,
944,
11,
1988,
25,
965,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
7248,
3670,
37811,
198,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
834,
7839,
796,
965,
7,
8367,
8,
628,
220,
220,
220,
2488,
26745,
198,
220,
220,
220,
825,
2124,
33986,
7,
944,
8,
4613,
965,
25,
198,
220,
220,
220,
220,
220,
220,
220,
13538,
15931,
15931,
198,
220,
220,
220,
220,
220,
220,
220,
1441,
2116,
13,
834,
87,
33986,
628,
220,
220,
220,
2488,
87,
33986,
13,
2617,
353,
198,
220,
220,
220,
825,
2124,
33986,
7,
944,
11,
1988,
25,
965,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
7248,
2124,
33986,
37811,
198,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
834,
87,
33986,
796,
965,
7,
8367,
8,
628,
220,
220,
220,
2488,
26745,
198,
220,
220,
220,
825,
331,
33986,
7,
944,
8,
4613,
965,
25,
198,
220,
220,
220,
220,
220,
220,
220,
13538,
15931,
15931,
198,
220,
220,
220,
220,
220,
220,
220,
1441,
2116,
13,
834,
88,
33986,
628,
220,
220,
220,
2488,
88,
33986,
13,
2617,
353,
198,
220,
220,
220,
825,
331,
33986,
7,
944,
11,
1988,
25,
965,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
7248,
331,
33986,
37811,
198,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
834,
88,
33986,
796,
965,
7,
8367,
8,
628,
220,
220,
220,
2488,
26745,
198,
220,
220,
220,
825,
2922,
3237,
7,
944,
8,
4613,
20512,
25,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
8743,
10784,
477,
10425,
355,
7110,
37811,
198,
220,
220,
220,
220,
220,
220,
220,
1441,
2116,
13,
834,
19738,
3237,
628,
220,
220,
220,
2488,
19738,
3237,
13,
2617,
353,
198,
220,
220,
220,
825,
2922,
3237,
7,
944,
11,
1988,
25,
20512,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
7248,
2922,
3237,
37811,
198,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
834,
19738,
3237,
796,
20512,
7,
8367,
8,
628,
220,
220,
220,
2488,
26745,
198,
220,
220,
220,
825,
5072,
38963,
7,
944,
8,
4613,
25235,
38963,
25,
198,
220,
220,
220,
220,
220,
220,
220,
13538,
15931,
15931,
198,
220,
220,
220,
220,
220,
220,
220,
1441,
2116,
13,
834,
22915,
38963,
628,
220,
220,
220,
2488,
22915,
38963,
13,
2617,
353,
198,
220,
220,
220,
825,
5072,
38963,
7,
944,
11,
1988,
25,
25235,
38963,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
7248,
5072,
38963,
37811,
198,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
834,
22915,
38963,
796,
1988,
628,
220,
220,
220,
2488,
26745,
198,
220,
220,
220,
825,
2251,
29398,
7,
944,
8,
4613,
20512,
25,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
16447,
4263,
290,
3650,
777,
284,
11898,
13,
383,
5072,
481,
788,
307,
262,
13532,
284,
262,
4263,
37811,
198,
220,
220,
220,
220,
220,
220,
220,
1441,
2116,
13,
834,
17953,
29398,
628,
220,
220,
220,
2488,
17953,
29398,
13,
2617,
353,
198,
220,
220,
220,
825,
2251,
29398,
7,
944,
11,
1988,
25,
20512,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
7248,
2251,
29398,
37811,
198,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
834,
17953,
29398,
796,
20512,
7,
8367,
8,
198
] | 2.39818 | 2,637 |
# pylint: disable=invalid-name
"""
Tests for photo.utils
"""
import uuid
from django.test import TestCase
from photo import utils
# pylint: disable=too-few-public-methods
class DummyInstance:
"""
Dummy instance object for passing into UploadToPathAndRename
"""
pk = None
class UploadToPathAndRenameTestCase(TestCase):
"""
Tests for utils.UploadToPathAndRename
"""
def test_extension_preserved(self):
"""
Verify that UploadToPathAndRename preserves file extensions.
"""
result = self.upload_to_path_and_rename(self.instance, "filename.jpg")
ext = result.split('.')[-1]
self.assertEqual(ext, 'jpg', "New filename has wrong extension")
def test_path_appended(self):
"""
Verify that UploadToPathAndRename appends specified path.
"""
result = self.upload_to_path_and_rename(self.instance, "filename.jpg")
path = result.split('/')[0]
self.assertEqual(path, 'test', "New filename has wrong path")
def test_instance_with_no_pk(self):
"""
Verify handling when instance does not have a primary key
"""
result = self.upload_to_path_and_rename(self.instance, "filename.jpg")
generated_uuid_string = result.split('/')[1].split('.')[0]
generated_uuid = uuid.UUID(generated_uuid_string, version=4)
self.assertNotEqual(generated_uuid, self.instance.pk,
"New filename did not get a random UUID")
def test_instance_with_uuid_pk(self):
"""
Verify handling when instance has a UUID primary key
"""
self.instance.pk = uuid.uuid4()
result = self.upload_to_path_and_rename(self.instance, "filename.jpg")
generated_uuid_string = result.split('/')[1].split('.')[0]
generated_uuid = uuid.UUID(generated_uuid_string, version=4)
self.assertEqual(generated_uuid, self.instance.pk,
"New filename does not match UUID of instance")
def test_insance_with_non_uuid_pk(self):
"""
Verify handling when instance has a non-UUID primary key
"""
self.instance.pk = "test"
with self.assertRaises(TypeError):
self.upload_to_path_and_rename(self.instance, "filename.jpg")
class StopTimeConversionTestCase(TestCase):
"""Tests for utils.StopTimeConversion."""
def test_exception_time_difference_in_stops(self):
"""
Verify exception for invalid values in
StopTimeConversion.time_difference_in_stops.
"""
with self.assertRaises(ValueError):
utils.StopTimeConversion.time_difference_in_stops(0, 1)
with self.assertRaises(ValueError):
utils.StopTimeConversion.time_difference_in_stops(1, 0)
with self.assertRaises(ValueError):
utils.StopTimeConversion.time_difference_in_stops(0, 0)
with self.assertRaises(ValueError):
utils.StopTimeConversion.time_difference_in_stops(-1, -1)
def test_exception_adjust_time_by_points(self):
"""
Verify exception for invalid values in
StopTimeConversion.adjust_time_by_points.
"""
with self.assertRaises(ValueError):
utils.StopTimeConversion.adjust_time_by_points(0, 1)
with self.assertRaises(ValueError):
utils.StopTimeConversion.adjust_time_by_points(-1, 1)
def test_exception_adjust_time_by_stops(self):
"""
Verify exception for invalid values in
StopTimeConversion.adjust_time_by_stops.
"""
with self.assertRaises(ValueError):
utils.StopTimeConversion.adjust_time_by_stops(0, 1)
with self.assertRaises(ValueError):
utils.StopTimeConversion.adjust_time_by_stops(-1, 1)
def test_time_difference_in_stops(self):
"""
Verify values returned by
StopTimeConversion.time_difference_in_stops.
"""
self.assertEqual(
utils.StopTimeConversion.time_difference_in_stops(6, 12), 1)
self.assertEqual(
utils.StopTimeConversion.time_difference_in_stops(12, 12), 0)
self.assertEqual(
utils.StopTimeConversion.time_difference_in_stops(12, 6), -1)
def test_time_difference_in_points(self):
"""
Verify values returned by
StopTimeConversion.time_difference_in_points.
"""
self.assertEqual(
utils.StopTimeConversion.time_difference_in_points(6, 12), 12)
self.assertEqual(
utils.StopTimeConversion.time_difference_in_points(12, 12), 0)
self.assertEqual(
utils.StopTimeConversion.time_difference_in_points(12, 6), -12)
def test_stop_difference_to_multiplier(self):
"""
Verify values returned by
StopTimeConversion.stop_difference_to_multiplier.
"""
self.assertEqual(
utils.StopTimeConversion.stop_difference_to_multiplier(1), 2)
self.assertEqual(
utils.StopTimeConversion.stop_difference_to_multiplier(0), 1)
self.assertEqual(
utils.StopTimeConversion.stop_difference_to_multiplier(-1), 0.5)
def test_point_difference_to_multiplier(self):
"""
Verify values returned by
StopTimeConversion.point_difference_to_multiplier.
"""
self.assertEqual(
utils.StopTimeConversion.point_difference_to_multiplier(12), 2)
self.assertEqual(
utils.StopTimeConversion.point_difference_to_multiplier(0), 1)
self.assertEqual(
utils.StopTimeConversion.point_difference_to_multiplier(-12), 0.5)
def test_adjust_time_by_stops(self):
"""
Verify values returned by
StopTimeConversion.adjust_time_by_stops.
"""
self.assertEqual(
utils.StopTimeConversion.adjust_time_by_stops(12, 1), 24)
self.assertEqual(
utils.StopTimeConversion.adjust_time_by_stops(12, 0), 12)
self.assertEqual(
utils.StopTimeConversion.adjust_time_by_stops(12, -1), 6)
def test_adjust_time_by_points(self):
"""
Verify values returned by
StopTimeConversion.adjust_time_by_points.
"""
self.assertEqual(
utils.StopTimeConversion.adjust_time_by_points(12, 12), 24)
self.assertEqual(
utils.StopTimeConversion.adjust_time_by_points(12, 0), 12)
self.assertEqual(
utils.StopTimeConversion.adjust_time_by_points(12, -12), 6)
def test_resize_print_enlarge(self):
"""
Verify values returned by StopTimeConversion.resize_print,
for a constant-aspect enlargement.
"""
old_print = {'x':4, 'y':6}
new_print = {'x':8, 'y':12}
self.assertEqual(
utils.StopTimeConversion.resize_print_in_stops(
old_print, new_print),
2)
def test_resize_print_same(self):
"""
Verify values returned by StopTimeConversion.resize_print,
for a constant-aspect print of same size.
"""
old_print = {'x':4, 'y':6}
new_print = {'x':4, 'y':6}
self.assertEqual(
utils.StopTimeConversion.resize_print_in_stops(
old_print, new_print),
0)
def test_resize_print_reduce(self):
"""
Verify values returned by StopTimeConversion.resize_print,
for a constant-aspect reduction.
"""
old_print = {'x':8, 'y':12}
new_print = {'x':4, 'y':6}
self.assertEqual(
utils.StopTimeConversion.resize_print_in_stops(
old_print, new_print),
- 2)
def test_resize_print_enlarge_high_aspect(self):
"""
Verify values returned by StopTimeConversion.resize_print,
for a higher-aspect ratio enlargement.
"""
old_print = {'x':4, 'y':6}
new_print = {'x':8, 'y':10}
self.assertEqual(
utils.StopTimeConversion.resize_print_in_stops(
old_print, new_print),
2)
def test_resize_print_same_high_aspect(self):
"""
Verify values returned by StopTimeConversion.resize_print,
for a higher-aspect ratio print of same size.
"""
old_print = {'x':4, 'y':6}
new_print = {'x':4, 'y':5}
self.assertEqual(
utils.StopTimeConversion.resize_print_in_stops(
old_print, new_print),
0)
def test_resize_print_reduce_high_aspect(self):
"""
Verify values returned by StopTimeConversion.resize_print,
for a higher-aspect ratio reduction.
"""
old_print = {'x':8, 'y':12}
new_print = {'x':4, 'y':5}
self.assertEqual(
utils.StopTimeConversion.resize_print_in_stops(
old_print, new_print),
- 2)
def test_resize_print_enlarge_low_aspect(self):
"""
Verify values returned by StopTimeConversion.resize_print,
for a lower-aspect ratio enlargement.
"""
old_print = {'x':4, 'y':6}
new_print = {'x':7, 'y':12}
self.assertEqual(
utils.StopTimeConversion.resize_print_in_stops(
old_print, new_print),
2)
def test_resize_print_same_low_aspect(self):
"""
Verify values returned by StopTimeConversion.resize_print,
for a lower-aspect ratio print of same size.
"""
old_print = {'x':4, 'y':6}
new_print = {'x':3, 'y':6}
self.assertEqual(
utils.StopTimeConversion.resize_print_in_stops(
old_print, new_print),
0)
def test_resize_print_reduce_low_aspect(self):
"""
Verify values returned by StopTimeConversion.resize_print,
for a higher-aspect ratio reduction.
"""
old_print = {'x':8, 'y':12}
new_print = {'x':3, 'y':6}
self.assertEqual(
utils.StopTimeConversion.resize_print_in_stops(
old_print, new_print),
- 2)
| [
2,
279,
2645,
600,
25,
15560,
28,
259,
12102,
12,
3672,
198,
37811,
198,
51,
3558,
329,
4590,
13,
26791,
198,
37811,
198,
11748,
334,
27112,
198,
198,
6738,
42625,
14208,
13,
9288,
1330,
6208,
20448,
198,
198,
6738,
4590,
1330,
3384,
4487,
628,
198,
2,
279,
2645,
600,
25,
15560,
28,
18820,
12,
32146,
12,
11377,
12,
24396,
82,
198,
4871,
360,
13513,
33384,
25,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
360,
13513,
4554,
2134,
329,
6427,
656,
36803,
2514,
15235,
1870,
49,
12453,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
279,
74,
796,
6045,
198,
198,
4871,
36803,
2514,
15235,
1870,
49,
12453,
14402,
20448,
7,
14402,
20448,
2599,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
30307,
329,
3384,
4487,
13,
41592,
2514,
15235,
1870,
49,
12453,
198,
220,
220,
220,
37227,
628,
220,
220,
220,
825,
1332,
62,
2302,
3004,
62,
18302,
8520,
7,
944,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
49899,
326,
36803,
2514,
15235,
1870,
49,
12453,
43759,
2393,
18366,
13,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
1255,
796,
2116,
13,
25850,
62,
1462,
62,
6978,
62,
392,
62,
918,
480,
7,
944,
13,
39098,
11,
366,
34345,
13,
9479,
4943,
198,
220,
220,
220,
220,
220,
220,
220,
1070,
796,
1255,
13,
35312,
10786,
2637,
38381,
12,
16,
60,
198,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
30493,
36,
13255,
7,
2302,
11,
705,
9479,
3256,
366,
3791,
29472,
468,
2642,
7552,
4943,
628,
220,
220,
220,
825,
1332,
62,
6978,
62,
1324,
1631,
7,
944,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
49899,
326,
36803,
2514,
15235,
1870,
49,
12453,
598,
2412,
7368,
3108,
13,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
1255,
796,
2116,
13,
25850,
62,
1462,
62,
6978,
62,
392,
62,
918,
480,
7,
944,
13,
39098,
11,
366,
34345,
13,
9479,
4943,
198,
220,
220,
220,
220,
220,
220,
220,
3108,
796,
1255,
13,
35312,
10786,
14,
11537,
58,
15,
60,
198,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
30493,
36,
13255,
7,
6978,
11,
705,
9288,
3256,
366,
3791,
29472,
468,
2642,
3108,
4943,
628,
220,
220,
220,
825,
1332,
62,
39098,
62,
4480,
62,
3919,
62,
79,
74,
7,
944,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
49899,
9041,
618,
4554,
857,
407,
423,
257,
4165,
1994,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
1255,
796,
2116,
13,
25850,
62,
1462,
62,
6978,
62,
392,
62,
918,
480,
7,
944,
13,
39098,
11,
366,
34345,
13,
9479,
4943,
198,
220,
220,
220,
220,
220,
220,
220,
7560,
62,
12303,
312,
62,
8841,
796,
1255,
13,
35312,
10786,
14,
11537,
58,
16,
4083,
35312,
10786,
2637,
38381,
15,
60,
198,
220,
220,
220,
220,
220,
220,
220,
7560,
62,
12303,
312,
796,
334,
27112,
13,
52,
27586,
7,
27568,
62,
12303,
312,
62,
8841,
11,
2196,
28,
19,
8,
198,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
30493,
3673,
36,
13255,
7,
27568,
62,
12303,
312,
11,
2116,
13,
39098,
13,
79,
74,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
366,
3791,
29472,
750,
407,
651,
257,
4738,
471,
27586,
4943,
628,
220,
220,
220,
825,
1332,
62,
39098,
62,
4480,
62,
12303,
312,
62,
79,
74,
7,
944,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
49899,
9041,
618,
4554,
468,
257,
471,
27586,
4165,
1994,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
39098,
13,
79,
74,
796,
334,
27112,
13,
12303,
312,
19,
3419,
198,
220,
220,
220,
220,
220,
220,
220,
1255,
796,
2116,
13,
25850,
62,
1462,
62,
6978,
62,
392,
62,
918,
480,
7,
944,
13,
39098,
11,
366,
34345,
13,
9479,
4943,
198,
220,
220,
220,
220,
220,
220,
220,
7560,
62,
12303,
312,
62,
8841,
796,
1255,
13,
35312,
10786,
14,
11537,
58,
16,
4083,
35312,
10786,
2637,
38381,
15,
60,
198,
220,
220,
220,
220,
220,
220,
220,
7560,
62,
12303,
312,
796,
334,
27112,
13,
52,
27586,
7,
27568,
62,
12303,
312,
62,
8841,
11,
2196,
28,
19,
8,
198,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
30493,
36,
13255,
7,
27568,
62,
12303,
312,
11,
2116,
13,
39098,
13,
79,
74,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
366,
3791,
29472,
857,
407,
2872,
471,
27586,
286,
4554,
4943,
628,
220,
220,
220,
825,
1332,
62,
1040,
590,
62,
4480,
62,
13159,
62,
12303,
312,
62,
79,
74,
7,
944,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
49899,
9041,
618,
4554,
468,
257,
1729,
12,
52,
27586,
4165,
1994,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
39098,
13,
79,
74,
796,
366,
9288,
1,
198,
220,
220,
220,
220,
220,
220,
220,
351,
2116,
13,
30493,
21762,
2696,
7,
6030,
12331,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
25850,
62,
1462,
62,
6978,
62,
392,
62,
918,
480,
7,
944,
13,
39098,
11,
366,
34345,
13,
9479,
4943,
198,
198,
4871,
13707,
7575,
3103,
9641,
14402,
20448,
7,
14402,
20448,
2599,
198,
220,
220,
220,
37227,
51,
3558,
329,
3384,
4487,
13,
19485,
7575,
3103,
9641,
526,
15931,
198,
220,
220,
220,
825,
1332,
62,
1069,
4516,
62,
2435,
62,
26069,
1945,
62,
259,
62,
301,
2840,
7,
944,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
49899,
6631,
329,
12515,
3815,
287,
198,
220,
220,
220,
220,
220,
220,
220,
13707,
7575,
3103,
9641,
13,
2435,
62,
26069,
1945,
62,
259,
62,
301,
2840,
13,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
351,
2116,
13,
30493,
21762,
2696,
7,
11395,
12331,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
3384,
4487,
13,
19485,
7575,
3103,
9641,
13,
2435,
62,
26069,
1945,
62,
259,
62,
301,
2840,
7,
15,
11,
352,
8,
198,
220,
220,
220,
220,
220,
220,
220,
351,
2116,
13,
30493,
21762,
2696,
7,
11395,
12331,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
3384,
4487,
13,
19485,
7575,
3103,
9641,
13,
2435,
62,
26069,
1945,
62,
259,
62,
301,
2840,
7,
16,
11,
657,
8,
198,
220,
220,
220,
220,
220,
220,
220,
351,
2116,
13,
30493,
21762,
2696,
7,
11395,
12331,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
3384,
4487,
13,
19485,
7575,
3103,
9641,
13,
2435,
62,
26069,
1945,
62,
259,
62,
301,
2840,
7,
15,
11,
657,
8,
198,
220,
220,
220,
220,
220,
220,
220,
351,
2116,
13,
30493,
21762,
2696,
7,
11395,
12331,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
3384,
4487,
13,
19485,
7575,
3103,
9641,
13,
2435,
62,
26069,
1945,
62,
259,
62,
301,
2840,
32590,
16,
11,
532,
16,
8,
628,
220,
220,
220,
825,
1332,
62,
1069,
4516,
62,
23032,
62,
2435,
62,
1525,
62,
13033,
7,
944,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
49899,
6631,
329,
12515,
3815,
287,
198,
220,
220,
220,
220,
220,
220,
220,
13707,
7575,
3103,
9641,
13,
23032,
62,
2435,
62,
1525,
62,
13033,
13,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
351,
2116,
13,
30493,
21762,
2696,
7,
11395,
12331,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
3384,
4487,
13,
19485,
7575,
3103,
9641,
13,
23032,
62,
2435,
62,
1525,
62,
13033,
7,
15,
11,
352,
8,
198,
220,
220,
220,
220,
220,
220,
220,
351,
2116,
13,
30493,
21762,
2696,
7,
11395,
12331,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
3384,
4487,
13,
19485,
7575,
3103,
9641,
13,
23032,
62,
2435,
62,
1525,
62,
13033,
32590,
16,
11,
352,
8,
628,
220,
220,
220,
825,
1332,
62,
1069,
4516,
62,
23032,
62,
2435,
62,
1525,
62,
301,
2840,
7,
944,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
49899,
6631,
329,
12515,
3815,
287,
198,
220,
220,
220,
220,
220,
220,
220,
13707,
7575,
3103,
9641,
13,
23032,
62,
2435,
62,
1525,
62,
301,
2840,
13,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
351,
2116,
13,
30493,
21762,
2696,
7,
11395,
12331,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
3384,
4487,
13,
19485,
7575,
3103,
9641,
13,
23032,
62,
2435,
62,
1525,
62,
301,
2840,
7,
15,
11,
352,
8,
198,
220,
220,
220,
220,
220,
220,
220,
351,
2116,
13,
30493,
21762,
2696,
7,
11395,
12331,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
3384,
4487,
13,
19485,
7575,
3103,
9641,
13,
23032,
62,
2435,
62,
1525,
62,
301,
2840,
32590,
16,
11,
352,
8,
628,
220,
220,
220,
825,
1332,
62,
2435,
62,
26069,
1945,
62,
259,
62,
301,
2840,
7,
944,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
49899,
3815,
4504,
416,
198,
220,
220,
220,
220,
220,
220,
220,
13707,
7575,
3103,
9641,
13,
2435,
62,
26069,
1945,
62,
259,
62,
301,
2840,
13,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
30493,
36,
13255,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
3384,
4487,
13,
19485,
7575,
3103,
9641,
13,
2435,
62,
26069,
1945,
62,
259,
62,
301,
2840,
7,
21,
11,
1105,
828,
352,
8,
198,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
30493,
36,
13255,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
3384,
4487,
13,
19485,
7575,
3103,
9641,
13,
2435,
62,
26069,
1945,
62,
259,
62,
301,
2840,
7,
1065,
11,
1105,
828,
657,
8,
198,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
30493,
36,
13255,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
3384,
4487,
13,
19485,
7575,
3103,
9641,
13,
2435,
62,
26069,
1945,
62,
259,
62,
301,
2840,
7,
1065,
11,
718,
828,
532,
16,
8,
628,
220,
220,
220,
825,
1332,
62,
2435,
62,
26069,
1945,
62,
259,
62,
13033,
7,
944,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
49899,
3815,
4504,
416,
198,
220,
220,
220,
220,
220,
220,
220,
13707,
7575,
3103,
9641,
13,
2435,
62,
26069,
1945,
62,
259,
62,
13033,
13,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
30493,
36,
13255,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
3384,
4487,
13,
19485,
7575,
3103,
9641,
13,
2435,
62,
26069,
1945,
62,
259,
62,
13033,
7,
21,
11,
1105,
828,
1105,
8,
198,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
30493,
36,
13255,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
3384,
4487,
13,
19485,
7575,
3103,
9641,
13,
2435,
62,
26069,
1945,
62,
259,
62,
13033,
7,
1065,
11,
1105,
828,
657,
8,
198,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
30493,
36,
13255,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
3384,
4487,
13,
19485,
7575,
3103,
9641,
13,
2435,
62,
26069,
1945,
62,
259,
62,
13033,
7,
1065,
11,
718,
828,
532,
1065,
8,
628,
220,
220,
220,
825,
1332,
62,
11338,
62,
26069,
1945,
62,
1462,
62,
47945,
959,
7,
944,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
49899,
3815,
4504,
416,
198,
220,
220,
220,
220,
220,
220,
220,
13707,
7575,
3103,
9641,
13,
11338,
62,
26069,
1945,
62,
1462,
62,
47945,
959,
13,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
30493,
36,
13255,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
3384,
4487,
13,
19485,
7575,
3103,
9641,
13,
11338,
62,
26069,
1945,
62,
1462,
62,
47945,
959,
7,
16,
828,
362,
8,
198,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
30493,
36,
13255,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
3384,
4487,
13,
19485,
7575,
3103,
9641,
13,
11338,
62,
26069,
1945,
62,
1462,
62,
47945,
959,
7,
15,
828,
352,
8,
198,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
30493,
36,
13255,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
3384,
4487,
13,
19485,
7575,
3103,
9641,
13,
11338,
62,
26069,
1945,
62,
1462,
62,
47945,
959,
32590,
16,
828,
657,
13,
20,
8,
628,
220,
220,
220,
825,
1332,
62,
4122,
62,
26069,
1945,
62,
1462,
62,
47945,
959,
7,
944,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
49899,
3815,
4504,
416,
198,
220,
220,
220,
220,
220,
220,
220,
13707,
7575,
3103,
9641,
13,
4122,
62,
26069,
1945,
62,
1462,
62,
47945,
959,
13,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
30493,
36,
13255,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
3384,
4487,
13,
19485,
7575,
3103,
9641,
13,
4122,
62,
26069,
1945,
62,
1462,
62,
47945,
959,
7,
1065,
828,
362,
8,
198,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
30493,
36,
13255,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
3384,
4487,
13,
19485,
7575,
3103,
9641,
13,
4122,
62,
26069,
1945,
62,
1462,
62,
47945,
959,
7,
15,
828,
352,
8,
198,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
30493,
36,
13255,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
3384,
4487,
13,
19485,
7575,
3103,
9641,
13,
4122,
62,
26069,
1945,
62,
1462,
62,
47945,
959,
32590,
1065,
828,
657,
13,
20,
8,
628,
220,
220,
220,
825,
1332,
62,
23032,
62,
2435,
62,
1525,
62,
301,
2840,
7,
944,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
49899,
3815,
4504,
416,
198,
220,
220,
220,
220,
220,
220,
220,
13707,
7575,
3103,
9641,
13,
23032,
62,
2435,
62,
1525,
62,
301,
2840,
13,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
30493,
36,
13255,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
3384,
4487,
13,
19485,
7575,
3103,
9641,
13,
23032,
62,
2435,
62,
1525,
62,
301,
2840,
7,
1065,
11,
352,
828,
1987,
8,
198,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
30493,
36,
13255,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
3384,
4487,
13,
19485,
7575,
3103,
9641,
13,
23032,
62,
2435,
62,
1525,
62,
301,
2840,
7,
1065,
11,
657,
828,
1105,
8,
198,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
30493,
36,
13255,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
3384,
4487,
13,
19485,
7575,
3103,
9641,
13,
23032,
62,
2435,
62,
1525,
62,
301,
2840,
7,
1065,
11,
532,
16,
828,
718,
8,
628,
220,
220,
220,
825,
1332,
62,
23032,
62,
2435,
62,
1525,
62,
13033,
7,
944,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
49899,
3815,
4504,
416,
198,
220,
220,
220,
220,
220,
220,
220,
13707,
7575,
3103,
9641,
13,
23032,
62,
2435,
62,
1525,
62,
13033,
13,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
30493,
36,
13255,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
3384,
4487,
13,
19485,
7575,
3103,
9641,
13,
23032,
62,
2435,
62,
1525,
62,
13033,
7,
1065,
11,
1105,
828,
1987,
8,
198,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
30493,
36,
13255,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
3384,
4487,
13,
19485,
7575,
3103,
9641,
13,
23032,
62,
2435,
62,
1525,
62,
13033,
7,
1065,
11,
657,
828,
1105,
8,
198,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
30493,
36,
13255,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
3384,
4487,
13,
19485,
7575,
3103,
9641,
13,
23032,
62,
2435,
62,
1525,
62,
13033,
7,
1065,
11,
532,
1065,
828,
718,
8,
628,
220,
220,
220,
825,
1332,
62,
411,
1096,
62,
4798,
62,
268,
11664,
7,
944,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
49899,
3815,
4504,
416,
13707,
7575,
3103,
9641,
13,
411,
1096,
62,
4798,
11,
198,
220,
220,
220,
220,
220,
220,
220,
329,
257,
6937,
12,
292,
806,
26537,
972,
13,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
1468,
62,
4798,
796,
1391,
6,
87,
10354,
19,
11,
705,
88,
10354,
21,
92,
198,
220,
220,
220,
220,
220,
220,
220,
649,
62,
4798,
796,
1391,
6,
87,
10354,
23,
11,
705,
88,
10354,
1065,
92,
198,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
30493,
36,
13255,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
3384,
4487,
13,
19485,
7575,
3103,
9641,
13,
411,
1096,
62,
4798,
62,
259,
62,
301,
2840,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1468,
62,
4798,
11,
649,
62,
4798,
828,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
362,
8,
628,
220,
220,
220,
825,
1332,
62,
411,
1096,
62,
4798,
62,
31642,
7,
944,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
49899,
3815,
4504,
416,
13707,
7575,
3103,
9641,
13,
411,
1096,
62,
4798,
11,
198,
220,
220,
220,
220,
220,
220,
220,
329,
257,
6937,
12,
292,
806,
3601,
286,
976,
2546,
13,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
1468,
62,
4798,
796,
1391,
6,
87,
10354,
19,
11,
705,
88,
10354,
21,
92,
198,
220,
220,
220,
220,
220,
220,
220,
649,
62,
4798,
796,
1391,
6,
87,
10354,
19,
11,
705,
88,
10354,
21,
92,
198,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
30493,
36,
13255,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
3384,
4487,
13,
19485,
7575,
3103,
9641,
13,
411,
1096,
62,
4798,
62,
259,
62,
301,
2840,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1468,
62,
4798,
11,
649,
62,
4798,
828,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
657,
8,
628,
220,
220,
220,
825,
1332,
62,
411,
1096,
62,
4798,
62,
445,
7234,
7,
944,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
49899,
3815,
4504,
416,
13707,
7575,
3103,
9641,
13,
411,
1096,
62,
4798,
11,
198,
220,
220,
220,
220,
220,
220,
220,
329,
257,
6937,
12,
292,
806,
7741,
13,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
1468,
62,
4798,
796,
1391,
6,
87,
10354,
23,
11,
705,
88,
10354,
1065,
92,
198,
220,
220,
220,
220,
220,
220,
220,
649,
62,
4798,
796,
1391,
6,
87,
10354,
19,
11,
705,
88,
10354,
21,
92,
198,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
30493,
36,
13255,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
3384,
4487,
13,
19485,
7575,
3103,
9641,
13,
411,
1096,
62,
4798,
62,
259,
62,
301,
2840,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1468,
62,
4798,
11,
649,
62,
4798,
828,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
532,
362,
8,
628,
220,
220,
220,
825,
1332,
62,
411,
1096,
62,
4798,
62,
268,
11664,
62,
8929,
62,
292,
806,
7,
944,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
49899,
3815,
4504,
416,
13707,
7575,
3103,
9641,
13,
411,
1096,
62,
4798,
11,
198,
220,
220,
220,
220,
220,
220,
220,
329,
257,
2440,
12,
292,
806,
8064,
26537,
972,
13,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
1468,
62,
4798,
796,
1391,
6,
87,
10354,
19,
11,
705,
88,
10354,
21,
92,
198,
220,
220,
220,
220,
220,
220,
220,
649,
62,
4798,
796,
1391,
6,
87,
10354,
23,
11,
705,
88,
10354,
940,
92,
198,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
30493,
36,
13255,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
3384,
4487,
13,
19485,
7575,
3103,
9641,
13,
411,
1096,
62,
4798,
62,
259,
62,
301,
2840,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1468,
62,
4798,
11,
649,
62,
4798,
828,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
362,
8,
628,
220,
220,
220,
825,
1332,
62,
411,
1096,
62,
4798,
62,
31642,
62,
8929,
62,
292,
806,
7,
944,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
49899,
3815,
4504,
416,
13707,
7575,
3103,
9641,
13,
411,
1096,
62,
4798,
11,
198,
220,
220,
220,
220,
220,
220,
220,
329,
257,
2440,
12,
292,
806,
8064,
3601,
286,
976,
2546,
13,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
1468,
62,
4798,
796,
1391,
6,
87,
10354,
19,
11,
705,
88,
10354,
21,
92,
198,
220,
220,
220,
220,
220,
220,
220,
649,
62,
4798,
796,
1391,
6,
87,
10354,
19,
11,
705,
88,
10354,
20,
92,
198,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
30493,
36,
13255,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
3384,
4487,
13,
19485,
7575,
3103,
9641,
13,
411,
1096,
62,
4798,
62,
259,
62,
301,
2840,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1468,
62,
4798,
11,
649,
62,
4798,
828,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
657,
8,
628,
220,
220,
220,
825,
1332,
62,
411,
1096,
62,
4798,
62,
445,
7234,
62,
8929,
62,
292,
806,
7,
944,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
49899,
3815,
4504,
416,
13707,
7575,
3103,
9641,
13,
411,
1096,
62,
4798,
11,
198,
220,
220,
220,
220,
220,
220,
220,
329,
257,
2440,
12,
292,
806,
8064,
7741,
13,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
1468,
62,
4798,
796,
1391,
6,
87,
10354,
23,
11,
705,
88,
10354,
1065,
92,
198,
220,
220,
220,
220,
220,
220,
220,
649,
62,
4798,
796,
1391,
6,
87,
10354,
19,
11,
705,
88,
10354,
20,
92,
198,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
30493,
36,
13255,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
3384,
4487,
13,
19485,
7575,
3103,
9641,
13,
411,
1096,
62,
4798,
62,
259,
62,
301,
2840,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1468,
62,
4798,
11,
649,
62,
4798,
828,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
532,
362,
8,
628,
220,
220,
220,
825,
1332,
62,
411,
1096,
62,
4798,
62,
268,
11664,
62,
9319,
62,
292,
806,
7,
944,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
49899,
3815,
4504,
416,
13707,
7575,
3103,
9641,
13,
411,
1096,
62,
4798,
11,
198,
220,
220,
220,
220,
220,
220,
220,
329,
257,
2793,
12,
292,
806,
8064,
26537,
972,
13,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
1468,
62,
4798,
796,
1391,
6,
87,
10354,
19,
11,
705,
88,
10354,
21,
92,
198,
220,
220,
220,
220,
220,
220,
220,
649,
62,
4798,
796,
1391,
6,
87,
10354,
22,
11,
705,
88,
10354,
1065,
92,
198,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
30493,
36,
13255,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
3384,
4487,
13,
19485,
7575,
3103,
9641,
13,
411,
1096,
62,
4798,
62,
259,
62,
301,
2840,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1468,
62,
4798,
11,
649,
62,
4798,
828,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
362,
8,
628,
220,
220,
220,
825,
1332,
62,
411,
1096,
62,
4798,
62,
31642,
62,
9319,
62,
292,
806,
7,
944,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
49899,
3815,
4504,
416,
13707,
7575,
3103,
9641,
13,
411,
1096,
62,
4798,
11,
198,
220,
220,
220,
220,
220,
220,
220,
329,
257,
2793,
12,
292,
806,
8064,
3601,
286,
976,
2546,
13,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
1468,
62,
4798,
796,
1391,
6,
87,
10354,
19,
11,
705,
88,
10354,
21,
92,
198,
220,
220,
220,
220,
220,
220,
220,
649,
62,
4798,
796,
1391,
6,
87,
10354,
18,
11,
705,
88,
10354,
21,
92,
198,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
30493,
36,
13255,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
3384,
4487,
13,
19485,
7575,
3103,
9641,
13,
411,
1096,
62,
4798,
62,
259,
62,
301,
2840,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1468,
62,
4798,
11,
649,
62,
4798,
828,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
657,
8,
628,
220,
220,
220,
825,
1332,
62,
411,
1096,
62,
4798,
62,
445,
7234,
62,
9319,
62,
292,
806,
7,
944,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
49899,
3815,
4504,
416,
13707,
7575,
3103,
9641,
13,
411,
1096,
62,
4798,
11,
198,
220,
220,
220,
220,
220,
220,
220,
329,
257,
2440,
12,
292,
806,
8064,
7741,
13,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
1468,
62,
4798,
796,
1391,
6,
87,
10354,
23,
11,
705,
88,
10354,
1065,
92,
198,
220,
220,
220,
220,
220,
220,
220,
649,
62,
4798,
796,
1391,
6,
87,
10354,
18,
11,
705,
88,
10354,
21,
92,
198,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
30493,
36,
13255,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
3384,
4487,
13,
19485,
7575,
3103,
9641,
13,
411,
1096,
62,
4798,
62,
259,
62,
301,
2840,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1468,
62,
4798,
11,
649,
62,
4798,
828,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
532,
362,
8,
198
] | 2.109238 | 4,806 |
# Copyright (c) 2021 - present, Timur Shenkao
# All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
##############################################################################
from typing import Optional
from python_code.helper.linked_lists import MultiDoubleListNode
# 430. Flatten a Multilevel Doubly Linked List https://leetcode.com/problems/flatten-a-multilevel-doubly-linked-list/
# You are given a doubly linked list, which contains nodes that have a next pointer, a previous pointer, and an
# additional child pointer. This child pointer may or may not point to a separate doubly linked list, also containing
# these special nodes. These child lists may have one or more children of their own, and so on, to produce a multilevel
# data structure.
# Given the head of the first level of the list, flatten the list so that all the nodes appear in a single-level, doubly
# linked list. Let curr be a node with a child list. The nodes in the child list should appear after curr and before
# curr.next in the flattened list.
# Return the head of the flattened list. The nodes in the list must have all of their child pointers set to null.
# The number of Nodes will not exceed 1000.
# 1 <= Node.val <= 105
| [
2,
15069,
357,
66,
8,
33448,
532,
1944,
11,
5045,
333,
22323,
4914,
78,
198,
2,
1439,
2489,
10395,
13,
198,
2,
198,
2,
49962,
739,
262,
24843,
13789,
11,
10628,
362,
13,
15,
357,
1169,
366,
34156,
15341,
198,
2,
345,
743,
407,
779,
428,
2393,
2845,
287,
11846,
351,
262,
13789,
13,
198,
2,
921,
743,
7330,
257,
4866,
286,
262,
13789,
379,
198,
2,
198,
2,
2638,
1378,
2503,
13,
43073,
13,
2398,
14,
677,
4541,
14,
43,
2149,
24290,
12,
17,
13,
15,
198,
2,
198,
2,
17486,
2672,
416,
9723,
1099,
393,
4987,
284,
287,
3597,
11,
3788,
198,
2,
9387,
739,
262,
13789,
318,
9387,
319,
281,
366,
1921,
3180,
1,
29809,
1797,
11,
198,
2,
42881,
34764,
11015,
6375,
7102,
49828,
11053,
3963,
15529,
509,
12115,
11,
2035,
4911,
393,
17142,
13,
198,
2,
4091,
262,
13789,
329,
262,
2176,
3303,
15030,
21627,
290,
198,
2,
11247,
739,
262,
13789,
13,
198,
29113,
29113,
7804,
4242,
2235,
198,
198,
6738,
19720,
1330,
32233,
198,
198,
6738,
21015,
62,
8189,
13,
2978,
525,
13,
25614,
62,
20713,
1330,
15237,
25628,
8053,
19667,
198,
198,
2,
35090,
13,
1610,
41769,
257,
7854,
576,
626,
5728,
36874,
7502,
276,
7343,
3740,
1378,
293,
316,
8189,
13,
785,
14,
1676,
22143,
14,
2704,
41769,
12,
64,
12,
16680,
576,
626,
12,
67,
12944,
306,
12,
25614,
12,
4868,
14,
198,
2,
921,
389,
1813,
257,
3385,
306,
6692,
1351,
11,
543,
4909,
13760,
326,
423,
257,
1306,
17562,
11,
257,
2180,
17562,
11,
290,
281,
198,
2,
3224,
1200,
17562,
13,
770,
1200,
17562,
743,
393,
743,
407,
966,
284,
257,
4553,
3385,
306,
6692,
1351,
11,
635,
7268,
198,
2,
777,
2041,
13760,
13,
2312,
1200,
8341,
743,
423,
530,
393,
517,
1751,
286,
511,
898,
11,
290,
523,
319,
11,
284,
4439,
257,
1963,
576,
626,
198,
2,
1366,
4645,
13,
198,
2,
11259,
262,
1182,
286,
262,
717,
1241,
286,
262,
1351,
11,
27172,
268,
262,
1351,
523,
326,
477,
262,
13760,
1656,
287,
257,
2060,
12,
5715,
11,
3385,
306,
198,
2,
6692,
1351,
13,
3914,
1090,
81,
307,
257,
10139,
351,
257,
1200,
1351,
13,
383,
13760,
287,
262,
1200,
1351,
815,
1656,
706,
1090,
81,
290,
878,
198,
2,
1090,
81,
13,
19545,
287,
262,
45096,
1351,
13,
198,
2,
8229,
262,
1182,
286,
262,
45096,
1351,
13,
383,
13760,
287,
262,
1351,
1276,
423,
477,
286,
511,
1200,
32007,
900,
284,
9242,
13,
198,
2,
383,
1271,
286,
399,
4147,
481,
407,
7074,
8576,
13,
198,
2,
352,
19841,
19081,
13,
2100,
19841,
13343,
628
] | 3.967816 | 435 |
#!/usr/bin/env python
"""Searches specified directory for miss named files."""
import os
class bcolors:
"""Color text in terminal."""
HEADER = '\033[95m'
OKBLUE = '\033[94m'
OKGREEN = '\033[92m'
WARNING = '\033[93m'
FAIL = '\033[91m'
ENDC = '\033[0m'
BOLD = '\033[1m'
UNDERLINE = '\033[4m'
class FileForensics:
"""Identify miss named files."""
def __init__(self):
"""Initialize object without processing any files."""
self.filelist = list()
def scan_dir(self, dir):
"""Scan dir looking for files and performs basic checks."""
import pathlib
import magic
for filename in find_all_files(dir):
self.filelist.append({
"filename": filename,
"mime": magic.from_file(filename, mime=True),
"size_bytes": os.path.getsize(filename),
"ext": pathlib.Path(filename).suffix
})
def get_lenght(self):
"""Return number of processed files."""
return len(self.filelist)
def get_big_files(self, size_threshold=10):
"""Return list of file bigger than X MB (size in MB)."""
for f in self.filelist:
if f["size_bytes"] > size_threshold*(1024*1024):
yield f["size_bytes"]/(1024*1024), f["mime"], f["filename"]
def get_keyword_files(
self,
filename_keywords="keywords",
read_size=1024*1024,
offset=50):
"""Return list of files matching keywords with matched information."""
import ahocorasick
A = ahocorasick.Automaton()
with open(filename_keywords, "r") as f:
while True:
word = f.readline()
if not word:
break
A.add_word(word.strip(), word.strip())
A.make_automaton()
for file in self.filelist:
with open(file["filename"], "r") as f:
matches = list()
buff = f.read(read_size)
for match in A.iter(buff):
pos_cur = match[0]
pos_start = max(match[0]-offset, 0)
pos_end = min(match[0]+offset, read_size)
offset_start = buff[
pos_start:pos_cur-len(match[1])+1
].find("\n")
offset_end = buff[pos_cur+1:pos_end].rfind("\n")
if offset_start >= offset:
offset_start = 0
if offset_end <= 0:
offset_end = offset
offset_end = offset - offset_end
matched_text = buff[
pos_start+offset_start:pos_cur-len(match[1])+1
] + \
bcolors.FAIL + \
buff[pos_cur-len(match[1])+1:pos_cur+1] + \
bcolors.ENDC + \
buff[pos_cur+1:pos_end-offset_end]
matches.append((matched_text.replace("\n", " "), match[1]))
if len(matches) > 0:
yield (file, matches)
def get_highentropy_files(self, ent_threshold=0.7):
"""Return list of files with higher entropy (encrypted, compressed)."""
import entropy
ignored_mimetypes = [
"application/x-shockwave-flash",
"application/x-font-",
"application/pdf",
"image/"
]
for file in self.filelist:
with open(file["filename"], "r") as f:
buff = f.read(1024*1024)
skip = False
for mime in ignored_mimetypes:
if file["mime"].startswith(mime):
skip = True
break
if not skip:
ent = entropy.shannon_entropy(buff)
if ent >= ent_threshold:
yield (file, ent)
def find_all_files(path):
"""Find all files in specified directory and yields them."""
for root, dirs, files in os.walk(os.path.join(path)):
for filename in files:
yield os.path.join(root, filename)
def main():
"""Analyze directory from command line looking for suspicious files."""
ff = FileForensics()
# ff.scan_dir("/Users/ns/notes") # FIXME
ff.scan_dir("/Users/ns/work/termination_data")
print "\n--- BIG FILES ---"
for (size, mime, filename) in ff.get_big_files():
print (bcolors.FAIL+"{:>10} MB"+bcolors.ENDC+" {:<20} {:<10}").\
format(size, mime, filename)
print "\n--- FOUND KEYWORDS ---"
for (file, matches) in ff.get_keyword_files():
print "{:<5} {:<20} ({:<10})".format(
len(matches), file["mime"], file["filename"])
for position, match in matches:
print "\t- {:<10} {:<10}".format(position, match)
print
print "\n--- HIGH ENTROPY FILES ---"
for (file, ent) in ff.get_highentropy_files():
print (bcolors.FAIL+"\t {:.2f}"+bcolors.ENDC+" ({:<10}) {:<10}").\
format(ent, file["mime"], file["filename"])
if __name__ == "__main__":
main()
| [
2,
48443,
14629,
14,
8800,
14,
24330,
21015,
198,
37811,
50,
451,
2052,
7368,
8619,
329,
2051,
3706,
3696,
526,
15931,
628,
198,
11748,
28686,
628,
198,
4871,
275,
4033,
669,
25,
198,
220,
220,
220,
37227,
10258,
2420,
287,
12094,
526,
15931,
628,
220,
220,
220,
39837,
1137,
796,
705,
59,
44427,
58,
3865,
76,
6,
198,
220,
220,
220,
7477,
9148,
8924,
796,
705,
59,
44427,
58,
5824,
76,
6,
198,
220,
220,
220,
7477,
43016,
796,
705,
59,
44427,
58,
5892,
76,
6,
198,
220,
220,
220,
39410,
796,
705,
59,
44427,
58,
6052,
76,
6,
198,
220,
220,
220,
9677,
4146,
796,
705,
59,
44427,
58,
6420,
76,
6,
198,
220,
220,
220,
23578,
34,
796,
705,
59,
44427,
58,
15,
76,
6,
198,
220,
220,
220,
347,
15173,
796,
705,
59,
44427,
58,
16,
76,
6,
198,
220,
220,
220,
35219,
24027,
796,
705,
59,
44427,
58,
19,
76,
6,
628,
198,
4871,
9220,
16351,
49242,
25,
198,
220,
220,
220,
37227,
33234,
1958,
2051,
3706,
3696,
526,
15931,
628,
220,
220,
220,
825,
11593,
15003,
834,
7,
944,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
24243,
1096,
2134,
1231,
7587,
597,
3696,
526,
15931,
198,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
7753,
4868,
796,
1351,
3419,
628,
220,
220,
220,
825,
9367,
62,
15908,
7,
944,
11,
26672,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
33351,
26672,
2045,
329,
3696,
290,
17706,
4096,
8794,
526,
15931,
198,
220,
220,
220,
220,
220,
220,
220,
1330,
3108,
8019,
198,
220,
220,
220,
220,
220,
220,
220,
1330,
5536,
628,
220,
220,
220,
220,
220,
220,
220,
329,
29472,
287,
1064,
62,
439,
62,
16624,
7,
15908,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
7753,
4868,
13,
33295,
15090,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
366,
34345,
1298,
29472,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
366,
76,
524,
1298,
5536,
13,
6738,
62,
7753,
7,
34345,
11,
285,
524,
28,
17821,
828,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
366,
7857,
62,
33661,
1298,
28686,
13,
6978,
13,
11407,
1096,
7,
34345,
828,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
366,
2302,
1298,
3108,
8019,
13,
15235,
7,
34345,
737,
37333,
844,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
32092,
628,
220,
220,
220,
825,
651,
62,
11925,
456,
83,
7,
944,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
13615,
1271,
286,
13686,
3696,
526,
15931,
198,
220,
220,
220,
220,
220,
220,
220,
1441,
18896,
7,
944,
13,
7753,
4868,
8,
628,
220,
220,
220,
825,
651,
62,
14261,
62,
16624,
7,
944,
11,
2546,
62,
400,
10126,
28,
940,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
13615,
1351,
286,
2393,
5749,
621,
1395,
10771,
357,
7857,
287,
10771,
21387,
15931,
198,
220,
220,
220,
220,
220,
220,
220,
329,
277,
287,
2116,
13,
7753,
4868,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
611,
277,
14692,
7857,
62,
33661,
8973,
1875,
2546,
62,
400,
10126,
9,
7,
35500,
9,
35500,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
7800,
277,
14692,
7857,
62,
33661,
8973,
29006,
35500,
9,
35500,
828,
277,
14692,
76,
524,
33116,
277,
14692,
34345,
8973,
628,
220,
220,
220,
825,
651,
62,
2539,
4775,
62,
16624,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2116,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
29472,
62,
2539,
10879,
2625,
2539,
10879,
1600,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1100,
62,
7857,
28,
35500,
9,
35500,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
11677,
28,
1120,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
13615,
1351,
286,
3696,
12336,
26286,
351,
14451,
1321,
526,
15931,
198,
220,
220,
220,
220,
220,
220,
220,
1330,
29042,
420,
41043,
624,
628,
220,
220,
220,
220,
220,
220,
220,
317,
796,
29042,
420,
41043,
624,
13,
38062,
13951,
3419,
198,
220,
220,
220,
220,
220,
220,
220,
351,
1280,
7,
34345,
62,
2539,
10879,
11,
366,
81,
4943,
355,
277,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
981,
6407,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1573,
796,
277,
13,
961,
1370,
3419,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
611,
407,
1573,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2270,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
317,
13,
2860,
62,
4775,
7,
4775,
13,
36311,
22784,
1573,
13,
36311,
28955,
628,
220,
220,
220,
220,
220,
220,
220,
317,
13,
15883,
62,
2306,
296,
13951,
3419,
628,
220,
220,
220,
220,
220,
220,
220,
329,
2393,
287,
2116,
13,
7753,
4868,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
351,
1280,
7,
7753,
14692,
34345,
33116,
366,
81,
4943,
355,
277,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
7466,
796,
1351,
3419,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
6940,
796,
277,
13,
961,
7,
961,
62,
7857,
8,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
329,
2872,
287,
317,
13,
2676,
7,
36873,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1426,
62,
22019,
796,
2872,
58,
15,
60,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1426,
62,
9688,
796,
3509,
7,
15699,
58,
15,
45297,
28968,
11,
657,
8,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1426,
62,
437,
796,
949,
7,
15699,
58,
15,
48688,
28968,
11,
1100,
62,
7857,
8,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
11677,
62,
9688,
796,
6940,
58,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1426,
62,
9688,
25,
1930,
62,
22019,
12,
11925,
7,
15699,
58,
16,
12962,
10,
16,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
20740,
19796,
7203,
59,
77,
4943,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
11677,
62,
437,
796,
6940,
58,
1930,
62,
22019,
10,
16,
25,
1930,
62,
437,
4083,
81,
19796,
7203,
59,
77,
4943,
628,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
611,
11677,
62,
9688,
18189,
11677,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
11677,
62,
9688,
796,
657,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
611,
11677,
62,
437,
19841,
657,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
11677,
62,
437,
796,
11677,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
11677,
62,
437,
796,
11677,
532,
11677,
62,
437,
628,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
14451,
62,
5239,
796,
6940,
58,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1426,
62,
9688,
10,
28968,
62,
9688,
25,
1930,
62,
22019,
12,
11925,
7,
15699,
58,
16,
12962,
10,
16,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2361,
1343,
3467,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
275,
4033,
669,
13,
7708,
4146,
1343,
3467,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
6940,
58,
1930,
62,
22019,
12,
11925,
7,
15699,
58,
16,
12962,
10,
16,
25,
1930,
62,
22019,
10,
16,
60,
1343,
3467,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
275,
4033,
669,
13,
1677,
9697,
1343,
3467,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
6940,
58,
1930,
62,
22019,
10,
16,
25,
1930,
62,
437,
12,
28968,
62,
437,
60,
628,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
7466,
13,
33295,
19510,
31409,
62,
5239,
13,
33491,
7203,
59,
77,
1600,
366,
366,
828,
2872,
58,
16,
60,
4008,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
611,
18896,
7,
6759,
2052,
8,
1875,
657,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
7800,
357,
7753,
11,
7466,
8,
628,
220,
220,
220,
825,
651,
62,
25196,
6925,
28338,
62,
16624,
7,
944,
11,
920,
62,
400,
10126,
28,
15,
13,
22,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
13615,
1351,
286,
3696,
351,
2440,
40709,
357,
43628,
11,
25388,
21387,
15931,
198,
220,
220,
220,
220,
220,
220,
220,
1330,
40709,
628,
220,
220,
220,
220,
220,
220,
220,
9514,
62,
76,
320,
2963,
12272,
796,
685,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
366,
31438,
14,
87,
12,
39563,
19204,
12,
34167,
1600,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
366,
31438,
14,
87,
12,
10331,
12,
1600,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
366,
31438,
14,
12315,
1600,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
366,
9060,
30487,
198,
220,
220,
220,
220,
220,
220,
220,
2361,
628,
220,
220,
220,
220,
220,
220,
220,
329,
2393,
287,
2116,
13,
7753,
4868,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
351,
1280,
7,
7753,
14692,
34345,
33116,
366,
81,
4943,
355,
277,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
6940,
796,
277,
13,
961,
7,
35500,
9,
35500,
8,
628,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
14267,
796,
10352,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
329,
285,
524,
287,
9514,
62,
76,
320,
2963,
12272,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
611,
2393,
14692,
76,
524,
1,
4083,
9688,
2032,
342,
7,
76,
524,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
14267,
796,
6407,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2270,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
611,
407,
14267,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
920,
796,
40709,
13,
1477,
8825,
62,
298,
28338,
7,
36873,
8,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
611,
920,
18189,
920,
62,
400,
10126,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
7800,
357,
7753,
11,
920,
8,
628,
198,
4299,
1064,
62,
439,
62,
16624,
7,
6978,
2599,
198,
220,
220,
220,
37227,
16742,
477,
3696,
287,
7368,
8619,
290,
19299,
606,
526,
15931,
198,
220,
220,
220,
329,
6808,
11,
288,
17062,
11,
3696,
287,
28686,
13,
11152,
7,
418,
13,
6978,
13,
22179,
7,
6978,
8,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
329,
29472,
287,
3696,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
7800,
28686,
13,
6978,
13,
22179,
7,
15763,
11,
29472,
8,
628,
198,
4299,
1388,
33529,
198,
220,
220,
220,
37227,
37702,
2736,
8619,
422,
3141,
1627,
2045,
329,
13678,
3696,
526,
15931,
198,
220,
220,
220,
31246,
796,
9220,
16351,
49242,
3419,
198,
220,
220,
220,
1303,
31246,
13,
35836,
62,
15908,
7203,
14,
14490,
14,
5907,
14,
17815,
4943,
220,
1303,
44855,
11682,
198,
220,
220,
220,
31246,
13,
35836,
62,
15908,
7203,
14,
14490,
14,
5907,
14,
1818,
14,
41382,
62,
7890,
4943,
628,
220,
220,
220,
3601,
37082,
77,
6329,
26746,
34020,
1546,
11420,
1,
198,
220,
220,
220,
329,
357,
7857,
11,
285,
524,
11,
29472,
8,
287,
31246,
13,
1136,
62,
14261,
62,
16624,
33529,
198,
220,
220,
220,
220,
220,
220,
220,
3601,
357,
65,
4033,
669,
13,
7708,
4146,
10,
1,
90,
25,
29,
940,
92,
10771,
1,
10,
65,
4033,
669,
13,
1677,
9697,
10,
1,
220,
220,
46110,
27,
1238,
92,
46110,
27,
940,
92,
11074,
59,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
5794,
7,
7857,
11,
285,
524,
11,
29472,
8,
628,
220,
220,
220,
3601,
37082,
77,
6329,
376,
15919,
35374,
45359,
5258,
11420,
1,
198,
220,
220,
220,
329,
357,
7753,
11,
7466,
8,
287,
31246,
13,
1136,
62,
2539,
4775,
62,
16624,
33529,
198,
220,
220,
220,
220,
220,
220,
220,
3601,
45144,
25,
27,
20,
92,
46110,
27,
1238,
92,
37913,
25,
27,
940,
30072,
1911,
18982,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
18896,
7,
6759,
2052,
828,
2393,
14692,
76,
524,
33116,
2393,
14692,
34345,
8973,
8,
198,
220,
220,
220,
220,
220,
220,
220,
329,
2292,
11,
2872,
287,
7466,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
3601,
37082,
83,
12,
46110,
27,
940,
92,
46110,
27,
940,
92,
1911,
18982,
7,
9150,
11,
2872,
8,
198,
220,
220,
220,
220,
220,
220,
220,
3601,
628,
220,
220,
220,
3601,
37082,
77,
6329,
34677,
12964,
5446,
3185,
56,
34020,
1546,
11420,
1,
198,
220,
220,
220,
329,
357,
7753,
11,
920,
8,
287,
31246,
13,
1136,
62,
25196,
6925,
28338,
62,
16624,
33529,
198,
220,
220,
220,
220,
220,
220,
220,
3601,
357,
65,
4033,
669,
13,
7708,
4146,
10,
1,
59,
83,
46110,
13,
17,
69,
36786,
10,
65,
4033,
669,
13,
1677,
9697,
10,
1,
37913,
25,
27,
940,
30072,
46110,
27,
940,
92,
11074,
59,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
5794,
7,
298,
11,
2393,
14692,
76,
524,
33116,
2393,
14692,
34345,
8973,
8,
628,
198,
361,
11593,
3672,
834,
6624,
366,
834,
12417,
834,
1298,
198,
220,
220,
220,
1388,
3419,
198
] | 1.917 | 2,747 |
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
openSMILE_dir_to_csv.py
Script to format openSMILE emobase *.csv output for a given set of files into a
single csv. Also returns the data as a pandas dataframe.
Created on Mon Jan 23 10:43:34 2017
Author:
– Jon Clucas, 2017 ([email protected])
© 2017, Child Mind Institute, Apache v2.0 License
"""
import argparse, csv, os, pandas as pd, subprocess
def oS_csv_reformat(oS_csv, first):
"""
Function to get features from openSMILE emobase configuration file csv
outputs.
Parameters
----------
csv_file : string
absolute path to a *.csv openSMILE output file
first : boolean
if this is the first csv of the set, `True`; otherwise, `False`
Returns
-------
data : pandas dataframe or list
if `first`, a dataframe with feature names, types, and csv values;
if !`first`, a list of csv values.
"""
print(oS_csv)
if first:
header = []
# type_header = []
temp_list = []
# initialize data_flag
data_flag = False
# read file
at_at = "@attribute "
with open(oS_csv, 'r') as f:
# open file for reading
reader = csv.reader(f)
for index, row in enumerate(reader):
if first:
header_element = ''.join(row)
if header_element.startswith(at_at):
he1, he2 = str(header_element.split(at_at)[1]).split(' ')
header.append(str(he1))
# if he2 != "unknown":
# type_header.append(str(he2))
# else:
# type_header.append("string")
if data_flag:
# read data row
temp_list.append(row)
if ''.join(row).startswith("@data"):
data_flag = True
if first:
data = pd.DataFrame(data=temp_list[1], index=header, columns=[
os.path.basename(oS_csv).rstrip('.csv').casefold(
)])
return(data)
else:
return(temp_list[1])
def oS_dir_to_csv(top_dir):
"""
Function collect all openSMILE output csv files in a given top-level
directory into a single csv file that also includes some summary columns
with one column for each csv in the original directory.
Parameters
----------
top_dir : string
absolute path to a directory of *.csv openSMILE output files
Outputs
-------
(top_dir + `/collected/all-collected.csv`) : csv file
a csv file containing all of the data from the input files and some
added summary columns
Returns
-------
collected_data : pandas dataframe
the exported *.csv as a pandas dataframe
"""
cols = []
col_dir = os.path.join(top_dir, "collected")
if not os.path.exists(col_dir):
os.makedirs(col_dir)
collected_data = None
for i, file in enumerate(os.listdir(top_dir)):
if file.casefold().endswith('.csv'.casefold()):
if i == 0:
collected_data = oS_csv_reformat(os.path.join(top_dir, file),
True)
else:
collected_data[os.path.basename(file).rstrip('.csv').casefold(
)] = oS_csv_reformat(os.path.join(top_dir,
file), False)
collected_data = collected_data.apply(pd.to_numeric, errors='coerce')
for index, column in enumerate(list(collected_data)):
if index > 0:
cols.append(column)
collected_data['mean'] = collected_data[cols].mean(axis=1)
collected_data['median'] = collected_data[cols].median(axis=1)
collected_data['std'] = collected_data[cols].std(axis=1)
collected_data['mad'] = collected_data[cols].mad(axis=1)
collected_data.sort_values(by='mad', axis=0, ascending=False, inplace=True)
collected_data.to_csv(os.path.join(col_dir, "all_collected.csv"))
return collected_data
# ============================================================================
if __name__ == '__main__':
main() | [
2,
48443,
14629,
14,
8800,
14,
24330,
21015,
18,
198,
2,
532,
9,
12,
19617,
25,
3384,
69,
12,
23,
532,
9,
12,
198,
37811,
198,
9654,
50,
8895,
2538,
62,
15908,
62,
1462,
62,
40664,
13,
9078,
198,
198,
7391,
284,
5794,
1280,
50,
8895,
2538,
795,
672,
589,
46866,
40664,
5072,
329,
257,
1813,
900,
286,
3696,
656,
257,
198,
29762,
269,
21370,
13,
4418,
5860,
262,
1366,
355,
257,
19798,
292,
1366,
14535,
13,
198,
198,
41972,
319,
2892,
2365,
2242,
838,
25,
3559,
25,
2682,
2177,
198,
198,
13838,
25,
198,
220,
220,
220,
220,
220,
220,
220,
784,
5966,
1012,
1229,
292,
11,
2177,
357,
46286,
13,
565,
1229,
292,
31,
9410,
10155,
13,
2398,
8,
198,
198,
16224,
2177,
11,
5932,
10175,
5136,
11,
24843,
410,
17,
13,
15,
13789,
198,
37811,
198,
198,
11748,
1822,
29572,
11,
269,
21370,
11,
28686,
11,
19798,
292,
355,
279,
67,
11,
850,
14681,
198,
198,
4299,
267,
50,
62,
40664,
62,
260,
18982,
7,
34049,
62,
40664,
11,
717,
2599,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
15553,
284,
651,
3033,
422,
1280,
50,
8895,
2538,
795,
672,
589,
8398,
2393,
269,
21370,
198,
220,
220,
220,
23862,
13,
628,
220,
220,
220,
40117,
198,
220,
220,
220,
24200,
438,
198,
220,
220,
220,
269,
21370,
62,
7753,
1058,
4731,
198,
220,
220,
220,
220,
220,
220,
220,
4112,
3108,
284,
257,
46866,
40664,
1280,
50,
8895,
2538,
5072,
2393,
628,
220,
220,
220,
717,
1058,
25131,
198,
220,
220,
220,
220,
220,
220,
220,
611,
428,
318,
262,
717,
269,
21370,
286,
262,
900,
11,
4600,
17821,
63,
26,
4306,
11,
4600,
25101,
63,
628,
220,
220,
220,
16409,
198,
220,
220,
220,
35656,
198,
220,
220,
220,
1366,
1058,
19798,
292,
1366,
14535,
393,
1351,
198,
220,
220,
220,
220,
220,
220,
220,
611,
4600,
11085,
47671,
257,
1366,
14535,
351,
3895,
3891,
11,
3858,
11,
290,
269,
21370,
3815,
26,
198,
220,
220,
220,
220,
220,
220,
220,
611,
5145,
63,
11085,
47671,
257,
1351,
286,
269,
21370,
3815,
13,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
3601,
7,
34049,
62,
40664,
8,
198,
220,
220,
220,
611,
717,
25,
198,
220,
220,
220,
220,
220,
220,
220,
13639,
796,
17635,
198,
220,
220,
220,
1303,
220,
220,
220,
2099,
62,
25677,
796,
17635,
198,
220,
220,
220,
20218,
62,
4868,
796,
17635,
198,
220,
220,
220,
1303,
41216,
1366,
62,
32109,
198,
220,
220,
220,
1366,
62,
32109,
796,
10352,
198,
220,
220,
220,
1303,
1100,
2393,
198,
220,
220,
220,
379,
62,
265,
796,
44212,
42348,
366,
198,
220,
220,
220,
351,
1280,
7,
34049,
62,
40664,
11,
705,
81,
11537,
355,
277,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
1303,
1280,
2393,
329,
3555,
198,
220,
220,
220,
220,
220,
220,
220,
9173,
796,
269,
21370,
13,
46862,
7,
69,
8,
198,
220,
220,
220,
220,
220,
220,
220,
329,
6376,
11,
5752,
287,
27056,
378,
7,
46862,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
611,
717,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
13639,
62,
30854,
796,
705,
4458,
22179,
7,
808,
8,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
611,
13639,
62,
30854,
13,
9688,
2032,
342,
7,
265,
62,
265,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
339,
16,
11,
339,
17,
796,
965,
7,
25677,
62,
30854,
13,
35312,
7,
265,
62,
265,
38381,
16,
35944,
35312,
10786,
705,
8,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
13639,
13,
33295,
7,
2536,
7,
258,
16,
4008,
198,
220,
220,
220,
220,
1303,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
611,
339,
17,
14512,
366,
34680,
1298,
198,
220,
220,
220,
220,
1303,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2099,
62,
25677,
13,
33295,
7,
2536,
7,
258,
17,
4008,
198,
220,
220,
220,
220,
1303,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2073,
25,
198,
220,
220,
220,
220,
1303,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2099,
62,
25677,
13,
33295,
7203,
8841,
4943,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
611,
1366,
62,
32109,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1303,
1100,
1366,
5752,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
20218,
62,
4868,
13,
33295,
7,
808,
8,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
611,
705,
4458,
22179,
7,
808,
737,
9688,
2032,
342,
7203,
31,
7890,
1,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1366,
62,
32109,
796,
6407,
198,
220,
220,
220,
611,
717,
25,
198,
220,
220,
220,
220,
220,
220,
220,
1366,
796,
279,
67,
13,
6601,
19778,
7,
7890,
28,
29510,
62,
4868,
58,
16,
4357,
6376,
28,
25677,
11,
15180,
41888,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
28686,
13,
6978,
13,
12093,
12453,
7,
34049,
62,
40664,
737,
81,
36311,
7,
4458,
40664,
27691,
7442,
11379,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1267,
12962,
198,
220,
220,
220,
220,
220,
220,
220,
1441,
7,
7890,
8,
198,
220,
220,
220,
2073,
25,
198,
220,
220,
220,
220,
220,
220,
220,
1441,
7,
29510,
62,
4868,
58,
16,
12962,
628,
198,
4299,
267,
50,
62,
15908,
62,
1462,
62,
40664,
7,
4852,
62,
15908,
2599,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
15553,
2824,
477,
1280,
50,
8895,
2538,
5072,
269,
21370,
3696,
287,
257,
1813,
1353,
12,
5715,
198,
220,
220,
220,
8619,
656,
257,
2060,
269,
21370,
2393,
326,
635,
3407,
617,
10638,
15180,
198,
220,
220,
220,
351,
530,
5721,
329,
1123,
269,
21370,
287,
262,
2656,
8619,
13,
628,
220,
220,
220,
40117,
198,
220,
220,
220,
24200,
438,
198,
220,
220,
220,
1353,
62,
15908,
1058,
4731,
198,
220,
220,
220,
220,
220,
220,
220,
4112,
3108,
284,
257,
8619,
286,
46866,
40664,
1280,
50,
8895,
2538,
5072,
3696,
628,
220,
220,
220,
25235,
82,
198,
220,
220,
220,
35656,
198,
220,
220,
220,
357,
4852,
62,
15908,
1343,
4600,
14,
4033,
12609,
14,
439,
12,
4033,
12609,
13,
40664,
63,
8,
1058,
269,
21370,
2393,
198,
220,
220,
220,
220,
220,
220,
220,
257,
269,
21370,
2393,
7268,
477,
286,
262,
1366,
422,
262,
5128,
3696,
290,
617,
198,
220,
220,
220,
220,
220,
220,
220,
2087,
10638,
15180,
628,
220,
220,
220,
16409,
198,
220,
220,
220,
35656,
198,
220,
220,
220,
7723,
62,
7890,
1058,
19798,
292,
1366,
14535,
198,
220,
220,
220,
220,
220,
220,
220,
262,
29050,
46866,
40664,
355,
257,
19798,
292,
1366,
14535,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
951,
82,
796,
17635,
198,
220,
220,
220,
951,
62,
15908,
796,
28686,
13,
6978,
13,
22179,
7,
4852,
62,
15908,
11,
366,
4033,
12609,
4943,
198,
220,
220,
220,
611,
407,
28686,
13,
6978,
13,
1069,
1023,
7,
4033,
62,
15908,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
28686,
13,
76,
4335,
17062,
7,
4033,
62,
15908,
8,
198,
220,
220,
220,
7723,
62,
7890,
796,
6045,
198,
220,
220,
220,
329,
1312,
11,
2393,
287,
27056,
378,
7,
418,
13,
4868,
15908,
7,
4852,
62,
15908,
8,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
611,
2393,
13,
7442,
11379,
22446,
437,
2032,
342,
7,
4458,
40664,
4458,
7442,
11379,
3419,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
611,
1312,
6624,
657,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
7723,
62,
7890,
796,
267,
50,
62,
40664,
62,
260,
18982,
7,
418,
13,
6978,
13,
22179,
7,
4852,
62,
15908,
11,
2393,
828,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
6407,
8,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2073,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
7723,
62,
7890,
58,
418,
13,
6978,
13,
12093,
12453,
7,
7753,
737,
81,
36311,
7,
4458,
40664,
27691,
7442,
11379,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
48600,
796,
267,
50,
62,
40664,
62,
260,
18982,
7,
418,
13,
6978,
13,
22179,
7,
4852,
62,
15908,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2393,
828,
10352,
8,
198,
220,
220,
220,
7723,
62,
7890,
796,
7723,
62,
7890,
13,
39014,
7,
30094,
13,
1462,
62,
77,
39223,
11,
8563,
11639,
1073,
263,
344,
11537,
198,
220,
220,
220,
329,
6376,
11,
5721,
287,
27056,
378,
7,
4868,
7,
4033,
12609,
62,
7890,
8,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
611,
6376,
1875,
657,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
951,
82,
13,
33295,
7,
28665,
8,
198,
220,
220,
220,
7723,
62,
7890,
17816,
32604,
20520,
796,
7723,
62,
7890,
58,
4033,
82,
4083,
32604,
7,
22704,
28,
16,
8,
198,
220,
220,
220,
7723,
62,
7890,
17816,
1150,
666,
20520,
796,
7723,
62,
7890,
58,
4033,
82,
4083,
1150,
666,
7,
22704,
28,
16,
8,
198,
220,
220,
220,
7723,
62,
7890,
17816,
19282,
20520,
796,
7723,
62,
7890,
58,
4033,
82,
4083,
19282,
7,
22704,
28,
16,
8,
198,
220,
220,
220,
7723,
62,
7890,
17816,
9937,
20520,
796,
7723,
62,
7890,
58,
4033,
82,
4083,
9937,
7,
22704,
28,
16,
8,
198,
220,
220,
220,
7723,
62,
7890,
13,
30619,
62,
27160,
7,
1525,
11639,
9937,
3256,
16488,
28,
15,
11,
41988,
28,
25101,
11,
287,
5372,
28,
17821,
8,
198,
220,
220,
220,
7723,
62,
7890,
13,
1462,
62,
40664,
7,
418,
13,
6978,
13,
22179,
7,
4033,
62,
15908,
11,
366,
439,
62,
4033,
12609,
13,
40664,
48774,
198,
220,
220,
220,
1441,
7723,
62,
7890,
198,
198,
2,
38093,
2559,
18604,
198,
361,
11593,
3672,
834,
6624,
705,
834,
12417,
834,
10354,
198,
220,
220,
220,
220,
220,
220,
220,
1388,
3419
] | 2.212573 | 1,877 |
# ClearML - Example of CatBoost training, saving model and loading model
#
import argparse
from catboost import CatBoostRegressor, Pool
from catboost.datasets import msrank
from clearml import Task
import numpy as np
from sklearn.model_selection import train_test_split
if __name__ == "__main__":
Task.init(project_name="examples", task_name="CatBoost simple example")
parser = argparse.ArgumentParser()
parser.add_argument("--iterations", default=200)
args = parser.parse_args()
main(args.iterations)
| [
2,
11459,
5805,
532,
17934,
286,
5181,
45686,
3047,
11,
8914,
2746,
290,
11046,
2746,
198,
2,
198,
11748,
1822,
29572,
198,
198,
6738,
3797,
39521,
1330,
5181,
45686,
8081,
44292,
11,
19850,
198,
6738,
3797,
39521,
13,
19608,
292,
1039,
1330,
13845,
43027,
198,
198,
6738,
1598,
4029,
1330,
15941,
198,
198,
11748,
299,
32152,
355,
45941,
198,
198,
6738,
1341,
35720,
13,
19849,
62,
49283,
1330,
4512,
62,
9288,
62,
35312,
628,
198,
198,
361,
11593,
3672,
834,
6624,
366,
834,
12417,
834,
1298,
198,
220,
220,
220,
15941,
13,
15003,
7,
16302,
62,
3672,
2625,
1069,
12629,
1600,
4876,
62,
3672,
2625,
21979,
45686,
2829,
1672,
4943,
198,
220,
220,
220,
30751,
796,
1822,
29572,
13,
28100,
1713,
46677,
3419,
198,
220,
220,
220,
30751,
13,
2860,
62,
49140,
7203,
438,
2676,
602,
1600,
4277,
28,
2167,
8,
198,
220,
220,
220,
26498,
796,
30751,
13,
29572,
62,
22046,
3419,
198,
220,
220,
220,
1388,
7,
22046,
13,
2676,
602,
8,
198
] | 3.206061 | 165 |
from django.template.defaultfilters import slugify
def slug_generator(sender, instance, *args, **kwargs):
''' capitalize first letter of each word and generates slug '''
instance.name = instance.name.title()
slug = slugify(instance.name)
exists = sender.objects.filter(slug=slug).exists()
if not exists:
instance.slug = slug
else:
instance.slug = "%s-%s" % (slug, instance.id)
| [
6738,
42625,
14208,
13,
28243,
13,
12286,
10379,
1010,
1330,
31065,
1958,
628,
198,
4299,
31065,
62,
8612,
1352,
7,
82,
2194,
11,
4554,
11,
1635,
22046,
11,
12429,
46265,
22046,
2599,
198,
220,
220,
705,
7061,
35160,
717,
3850,
286,
1123,
1573,
290,
18616,
31065,
705,
7061,
628,
220,
220,
4554,
13,
3672,
796,
4554,
13,
3672,
13,
7839,
3419,
198,
220,
220,
31065,
796,
31065,
1958,
7,
39098,
13,
3672,
8,
198,
220,
220,
7160,
796,
29788,
13,
48205,
13,
24455,
7,
6649,
1018,
28,
6649,
1018,
737,
1069,
1023,
3419,
198,
220,
220,
611,
407,
7160,
25,
198,
220,
220,
220,
220,
220,
4554,
13,
6649,
1018,
796,
31065,
198,
220,
220,
2073,
25,
198,
220,
220,
220,
220,
220,
4554,
13,
6649,
1018,
796,
36521,
82,
12,
4,
82,
1,
4064,
357,
6649,
1018,
11,
4554,
13,
312,
8,
628
] | 2.854167 | 144 |
# -*- coding: utf-8 -*-
import unittest
import os
import re
from iktomi.utils import html
from lxml.html import Element
from lxml import etree
import lxml.html as h
class TestSanitizer(unittest.TestCase):
'''Tests for sanitizer based on lxml'''
@unittest.skip('lxml does not provide css filtration')
def test_safe_css(self):
u'''Ensure that sanitizer does not remove safe css'''
self.attrs['allowed_attributes'].append('style')
res = self.sanitize('<p style="color: #000; background-color: red; font-size: 1.2em">p</p>')
assert 'color: #000; background-color: red; font-size: 1.2em' in res
@unittest.skip('not supported')
@unittest.skip('lxml does not provide css filtration')
def test_unsafe_css(self):
u'''Special test for html5: html5lib has very ultimate css cleanup with gauntlets'''
self.attrs['allowed_attributes'].append('style')
res = self.sanitize('<p style="background: url(javascript:void); '
'color: #000; width: e/**/xpression(alert());">p</p>')
self.assertEqual(res, '<p>p</p>')
def test_on_real_data(self):
'''
Compare with logged genshi output to ensure that there are no
new errors
'''
return None
skips = 10
if os.path.isdir('clean_html'):
self.attrs['string_callbacks'] = [html.remove_TinyMCE_trash,
html.strip_empty_tags_nested,
spaceless]
for dir, dirs, files in os.walk('clean_html'):
for file in filter(lambda x: x.endswith('.in'), files):
path = os.path.join(dir, file)
in_ = open(path, 'r').read().decode('utf-8')
out = open(path[:-3] + '.out', 'r').read().decode('utf-8')
out = html.remove_TinyMCE_trash(out) # Old sanitizer can't do this
#out = self.sanitize(out).strip()
res = self.sanitize(in_).strip()
if res != out:
if skips < 10:
print(in_, '\n----------\n', res + '---\n!=\n' + out + '---\n\n\n')
skips -= 1
if not skips:
return
#print "asserted"
@unittest.skip('lxml does not support this option')
# cannot create Cleaner with wrong parameters
| [
2,
532,
9,
12,
19617,
25,
3384,
69,
12,
23,
532,
9,
12,
198,
11748,
555,
715,
395,
198,
11748,
28686,
198,
11748,
302,
198,
6738,
220,
1134,
83,
12753,
13,
26791,
1330,
27711,
198,
6738,
300,
19875,
13,
6494,
1330,
11703,
198,
6738,
300,
19875,
1330,
2123,
631,
198,
11748,
300,
19875,
13,
6494,
355,
289,
198,
198,
4871,
6208,
15017,
3029,
263,
7,
403,
715,
395,
13,
14402,
20448,
2599,
198,
220,
220,
220,
705,
7061,
51,
3558,
329,
5336,
3029,
263,
1912,
319,
300,
19875,
7061,
6,
628,
220,
220,
220,
2488,
403,
715,
395,
13,
48267,
10786,
75,
19875,
857,
407,
2148,
269,
824,
1226,
83,
1358,
11537,
198,
220,
220,
220,
825,
1332,
62,
21230,
62,
25471,
7,
944,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
334,
7061,
6,
4834,
19532,
326,
5336,
3029,
263,
857,
407,
4781,
3338,
269,
824,
7061,
6,
198,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
1078,
3808,
17816,
40845,
62,
1078,
7657,
6,
4083,
33295,
10786,
7635,
11537,
198,
220,
220,
220,
220,
220,
220,
220,
581,
796,
2116,
13,
12807,
270,
1096,
10786,
27,
79,
3918,
2625,
8043,
25,
1303,
830,
26,
4469,
12,
8043,
25,
2266,
26,
10369,
12,
7857,
25,
352,
13,
17,
368,
5320,
79,
3556,
79,
29,
11537,
198,
220,
220,
220,
220,
220,
220,
220,
6818,
705,
8043,
25,
1303,
830,
26,
4469,
12,
8043,
25,
2266,
26,
10369,
12,
7857,
25,
352,
13,
17,
368,
6,
287,
581,
628,
220,
220,
220,
2488,
403,
715,
395,
13,
48267,
10786,
1662,
4855,
11537,
628,
220,
220,
220,
2488,
403,
715,
395,
13,
48267,
10786,
75,
19875,
857,
407,
2148,
269,
824,
1226,
83,
1358,
11537,
198,
220,
220,
220,
825,
1332,
62,
13271,
8635,
62,
25471,
7,
944,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
334,
7061,
6,
13409,
1332,
329,
27711,
20,
25,
27711,
20,
8019,
468,
845,
8713,
269,
824,
27425,
351,
308,
39695,
7061,
6,
198,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
1078,
3808,
17816,
40845,
62,
1078,
7657,
6,
4083,
33295,
10786,
7635,
11537,
198,
220,
220,
220,
220,
220,
220,
220,
581,
796,
2116,
13,
12807,
270,
1096,
10786,
27,
79,
3918,
2625,
25249,
25,
19016,
7,
37495,
25,
19382,
1776,
705,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
8043,
25,
1303,
830,
26,
9647,
25,
304,
35343,
14,
42372,
2234,
7,
44598,
35430,
5320,
79,
3556,
79,
29,
11537,
198,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
30493,
36,
13255,
7,
411,
11,
705,
27,
79,
29,
79,
3556,
79,
29,
11537,
628,
220,
220,
220,
825,
1332,
62,
261,
62,
5305,
62,
7890,
7,
944,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
705,
7061,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
27814,
351,
18832,
308,
641,
5303,
5072,
284,
4155,
326,
612,
389,
645,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
649,
8563,
198,
220,
220,
220,
220,
220,
220,
220,
705,
7061,
198,
220,
220,
220,
220,
220,
220,
220,
1441,
6045,
198,
220,
220,
220,
220,
220,
220,
220,
1341,
2419,
796,
838,
198,
220,
220,
220,
220,
220,
220,
220,
611,
28686,
13,
6978,
13,
9409,
343,
10786,
27773,
62,
6494,
6,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
1078,
3808,
17816,
8841,
62,
13345,
10146,
20520,
796,
685,
6494,
13,
28956,
62,
51,
3541,
44,
5222,
62,
2213,
1077,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
27711,
13,
36311,
62,
28920,
62,
31499,
62,
77,
7287,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
34752,
5321,
60,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
329,
26672,
11,
288,
17062,
11,
3696,
287,
28686,
13,
11152,
10786,
27773,
62,
6494,
6,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
329,
2393,
287,
8106,
7,
50033,
2124,
25,
2124,
13,
437,
2032,
342,
7,
4458,
259,
33809,
3696,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
3108,
796,
28686,
13,
6978,
13,
22179,
7,
15908,
11,
2393,
8,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
287,
62,
796,
1280,
7,
6978,
11,
705,
81,
27691,
961,
22446,
12501,
1098,
10786,
40477,
12,
23,
11537,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
503,
796,
1280,
7,
6978,
58,
21912,
18,
60,
1343,
45302,
448,
3256,
705,
81,
27691,
961,
22446,
12501,
1098,
10786,
40477,
12,
23,
11537,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
503,
796,
27711,
13,
28956,
62,
51,
3541,
44,
5222,
62,
2213,
1077,
7,
448,
8,
1303,
5706,
5336,
3029,
263,
460,
470,
466,
428,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1303,
448,
796,
2116,
13,
12807,
270,
1096,
7,
448,
737,
36311,
3419,
628,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
581,
796,
2116,
13,
12807,
270,
1096,
7,
259,
62,
737,
36311,
3419,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
611,
581,
14512,
503,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
611,
1341,
2419,
1279,
838,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
3601,
7,
259,
62,
11,
705,
59,
77,
35937,
59,
77,
3256,
581,
1343,
705,
6329,
59,
77,
0,
28,
59,
77,
6,
1343,
220,
503,
1343,
705,
6329,
59,
77,
59,
77,
59,
77,
11537,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1341,
2419,
48185,
352,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
611,
407,
1341,
2419,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1441,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1303,
4798,
366,
30493,
276,
1,
628,
220,
220,
220,
2488,
403,
715,
395,
13,
48267,
10786,
75,
19875,
857,
407,
1104,
428,
3038,
11537,
628,
198,
220,
220,
220,
1303,
2314,
2251,
5985,
263,
351,
2642,
10007,
628,
628
] | 1.97082 | 1,268 |
#!/usr/bin/env python
# from any given string, remove all vowels
# NON REGEX VERSION
sample_string='Sed ut perspiciatis unde omnis iste natus error sit voluptatem accusantium doloremque laudantium, totam rem aperiam, eaque ipsa quae ab illo inventore veritatis et quasi architecto beatae vitae dicta sunt explicabo. Nemo enim ipsam voluptatem quia voluptas sit aspernatur aut odit aut fugit, sed quia consequuntur magni dolores eos qui ratione voluptatem sequi nesciunt. Neque porro quisquam est, qui dolorem ipsum quia dolor sit amet, consectetur, adipisci velit, sed quia non numquam eius modi tempora incidunt ut labore et dolore magnam aliquam quaerat voluptatem. Ut enim ad minima veniam, quis nostrum exercitationem ullam corporis suscipit laboriosam, nisi ut aliquid ex ea commodi consequatur? Quis autem vel eum iure reprehenderit qui in ea voluptate velit esse quam nihil molestiae consequatur, vel illum qui dolorem eum fugiat quo voluptas nulla pariatur?'
en_vowels='aeiouAEIOU'
target_string = sample_string
for char in en_vowels:
target_string = target_string.replace(char,'')
print(target_string)
# REGEX VERSION
import re
vowels = re.compile(r'[aeiouAEIOU]')
print(vowels.sub('',sample_string)) | [
2,
48443,
14629,
14,
8800,
14,
24330,
21015,
198,
198,
2,
422,
597,
1813,
4731,
11,
4781,
477,
23268,
1424,
198,
198,
2,
44521,
23337,
6369,
44156,
2849,
198,
39873,
62,
8841,
11639,
50,
276,
3384,
2774,
16564,
5375,
271,
44192,
22284,
271,
318,
660,
299,
7240,
4049,
1650,
2322,
37623,
23900,
10458,
415,
1505,
288,
349,
29625,
4188,
28907,
415,
1505,
11,
2006,
321,
816,
257,
525,
1789,
11,
304,
18251,
220,
2419,
64,
627,
3609,
450,
2801,
78,
8067,
382,
3326,
270,
37749,
2123,
32551,
7068,
78,
307,
1045,
68,
9090,
3609,
8633,
64,
264,
2797,
1193,
291,
34748,
13,
22547,
78,
551,
320,
220,
2419,
321,
2322,
37623,
23900,
627,
544,
2322,
37623,
292,
1650,
355,
525,
77,
2541,
1960,
267,
5266,
1960,
31497,
270,
11,
10081,
627,
544,
4937,
2797,
333,
7842,
72,
288,
349,
2850,
304,
418,
45567,
36535,
68,
2322,
37623,
23900,
4726,
72,
299,
274,
979,
2797,
13,
3169,
4188,
16964,
305,
627,
271,
421,
321,
1556,
11,
45567,
288,
349,
29625,
220,
2419,
388,
627,
544,
288,
45621,
1650,
716,
316,
11,
369,
8831,
316,
333,
11,
31659,
271,
979,
11555,
270,
11,
10081,
627,
544,
1729,
997,
421,
321,
304,
3754,
953,
72,
10042,
64,
753,
312,
2797,
3384,
2248,
382,
2123,
288,
349,
382,
2153,
7402,
435,
1557,
321,
627,
25534,
265,
2322,
37623,
23900,
13,
7273,
551,
320,
512,
949,
8083,
8710,
1789,
11,
627,
271,
18216,
6582,
4208,
3780,
368,
334,
297,
321,
3990,
271,
2341,
66,
541,
270,
4827,
4267,
321,
11,
299,
23267,
3384,
435,
6394,
409,
304,
64,
13088,
72,
4937,
2541,
30,
2264,
271,
1960,
368,
11555,
304,
388,
1312,
495,
1128,
260,
258,
681,
270,
45567,
287,
304,
64,
2322,
37623,
378,
11555,
270,
1658,
325,
627,
321,
49413,
18605,
395,
33100,
4937,
2541,
11,
11555,
16116,
45567,
288,
349,
29625,
304,
388,
31497,
5375,
18658,
2322,
37623,
292,
9242,
64,
1582,
72,
2541,
8348,
198,
198,
268,
62,
85,
322,
1424,
11639,
3609,
72,
280,
14242,
40,
2606,
6,
198,
16793,
62,
8841,
796,
6291,
62,
8841,
198,
1640,
1149,
287,
551,
62,
85,
322,
1424,
25,
198,
197,
16793,
62,
8841,
796,
2496,
62,
8841,
13,
33491,
7,
10641,
4032,
11537,
198,
198,
4798,
7,
16793,
62,
8841,
8,
628,
198,
2,
23337,
6369,
44156,
2849,
198,
11748,
302,
198,
85,
322,
1424,
796,
302,
13,
5589,
576,
7,
81,
6,
58,
3609,
72,
280,
14242,
40,
2606,
60,
11537,
198,
4798,
7,
85,
322,
1424,
13,
7266,
10786,
3256,
39873,
62,
8841,
4008
] | 2.874704 | 423 |
# -*- coding: utf-8 -*-
# This file is part of CairoSVG
# Copyright © 2010-2012 Kozea
#
# This library is free software: you can redistribute it and/or modify it under
# the terms of the GNU Lesser General Public License as published by the Free
# Software Foundation, either version 3 of the License, or (at your option) any
# later version.
#
# This library is distributed in the hope that it will be useful, but WITHOUT
# ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
# FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License for more
# details.
#
# You should have received a copy of the GNU Lesser General Public License
# along with CairoSVG. If not, see <http://www.gnu.org/licenses/>.
"""
SVG Parser.
"""
# Fallbacks for Python 2/3 and lxml/ElementTree
# pylint: disable=E0611,F0401,W0611
try:
import lxml.etree as ElementTree
from lxml.etree import XMLSyntaxError as ParseError
HAS_LXML = True
except ImportError:
from xml.etree import ElementTree
from xml.parsers import expat
# ElementTree's API changed between 2.6 and 2.7
# pylint: disable=C0103
ParseError = getattr(ElementTree, 'ParseError', expat.ExpatError)
# pylint: enable=C0103
HAS_LXML = False
try:
from urllib import urlopen
import urlparse
except ImportError:
from urllib.request import urlopen
from urllib import parse as urlparse # Python 3
# pylint: enable=E0611,F0401,W0611
from .css import apply_stylesheets
# Python 2/3 compat
try:
basestring
except NameError:
basestring = str
class Node(dict):
"""SVG node with dict-like properties and children."""
def __init__(self, node, parent=None):
"""Create the Node from ElementTree ``node``, with ``parent`` Node."""
super(Node, self).__init__()
self.children = ()
self.root = False
self.tag = node.tag.split("}", 1)[-1]
self.text = node.text
# Handle the CSS
style = node.attrib.get("style")
if style:
for attribute in style.split(";"):
if ":" in attribute:
name, value = attribute.split(":", 1)
node.attrib[name.strip()] = value.strip()
del node.attrib["style"]
# Inherits from parent properties
if parent is not None:
items = parent.copy()
not_inherited = ("transform", "opacity")
if self.tag == "tspan":
not_inherited += ("x", "y")
for attribute in not_inherited:
if attribute in items:
del items[attribute]
# TODO: drop other attributes that should not be inherited
self.update(items)
self.url = parent.url
self.xml_tree = parent.xml_tree
self.parent = parent
self.update(dict(node.attrib.items()))
# Manage text by creating children
if self.tag == "text" or self.tag == "textPath":
self.children = self.text_children(node)
if not self.children:
self.children = tuple(
Node(child, self) for child in node
if isinstance(child.tag, basestring))
def text_children(self, node):
"""Create children and return them."""
children = []
for child in node:
children.append(Node(child, parent=self))
if child.tail:
anonymous = ElementTree.Element('tspan')
anonymous.text = child.tail
children.append(Node(anonymous, parent=self))
return list(children)
class Tree(Node):
"""SVG tree."""
def __init__(self, **kwargs):
"""Create the Tree from SVG ``text``."""
# Make the parameters keyword-only:
bytestring = kwargs.pop('bytestring', None)
file_obj = kwargs.pop('file_obj', None)
url = kwargs.pop('url', None)
parent = kwargs.pop('parent', None)
if bytestring is not None:
tree = ElementTree.fromstring(bytestring)
self.url = url
elif file_obj is not None:
tree = ElementTree.parse(file_obj).getroot()
self.url = getattr(file_obj, 'name', url)
elif url is not None:
if "#" in url:
url, element_id = url.split("#", 1)
else:
element_id = None
if parent and parent.url:
if url:
url = urlparse.urljoin(parent.url, url)
elif element_id:
url = parent.url
self.url = url
if url:
if urlparse.urlparse(url).scheme:
input_ = urlopen(url)
else:
input_ = url # filename
tree = ElementTree.parse(input_).getroot()
else:
tree = parent.xml_tree
if element_id:
iterator = (
tree.iter() if hasattr(tree, 'iter')
else tree.getiterator())
for element in iterator:
if element.get("id") == element_id:
tree = element
break
else:
raise TypeError(
'No input. Use one of bytestring, file_obj or url.')
apply_stylesheets(tree)
self.xml_tree = tree
super(Tree, self).__init__(tree, parent)
self.root = True
| [
2,
532,
9,
12,
19617,
25,
3384,
69,
12,
23,
532,
9,
12,
198,
2,
770,
2393,
318,
636,
286,
23732,
50,
43490,
198,
2,
15069,
10673,
3050,
12,
6999,
17634,
2736,
64,
198,
2,
198,
2,
770,
5888,
318,
1479,
3788,
25,
345,
460,
17678,
4163,
340,
290,
14,
273,
13096,
340,
739,
198,
2,
262,
2846,
286,
262,
22961,
12892,
263,
3611,
5094,
13789,
355,
3199,
416,
262,
3232,
198,
2,
10442,
5693,
11,
2035,
2196,
513,
286,
262,
13789,
11,
393,
357,
265,
534,
3038,
8,
597,
198,
2,
1568,
2196,
13,
198,
2,
198,
2,
770,
5888,
318,
9387,
287,
262,
2911,
326,
340,
481,
307,
4465,
11,
475,
42881,
198,
2,
15529,
34764,
56,
26,
1231,
772,
262,
17142,
18215,
286,
34482,
3398,
1565,
5603,
25382,
393,
376,
46144,
198,
2,
7473,
317,
16652,
2149,
37232,
33079,
48933,
13,
220,
4091,
262,
22961,
12892,
263,
3611,
5094,
13789,
329,
517,
198,
2,
3307,
13,
198,
2,
198,
2,
921,
815,
423,
2722,
257,
4866,
286,
262,
22961,
12892,
263,
3611,
5094,
13789,
198,
2,
1863,
351,
23732,
50,
43490,
13,
220,
1002,
407,
11,
766,
1279,
4023,
1378,
2503,
13,
41791,
13,
2398,
14,
677,
4541,
15913,
13,
198,
198,
37811,
198,
50,
43490,
23042,
263,
13,
198,
198,
37811,
198,
198,
2,
7218,
10146,
329,
11361,
362,
14,
18,
290,
300,
19875,
14,
20180,
27660,
198,
2,
279,
2645,
600,
25,
15560,
28,
36,
3312,
1157,
11,
37,
3023,
486,
11,
54,
3312,
1157,
198,
28311,
25,
198,
220,
220,
220,
1330,
300,
19875,
13,
316,
631,
355,
11703,
27660,
198,
220,
220,
220,
422,
300,
19875,
13,
316,
631,
1330,
23735,
13940,
41641,
12331,
355,
2547,
325,
12331,
198,
220,
220,
220,
33930,
62,
43,
55,
5805,
796,
6407,
198,
16341,
17267,
12331,
25,
198,
220,
220,
220,
422,
35555,
13,
316,
631,
1330,
11703,
27660,
198,
220,
220,
220,
422,
35555,
13,
79,
945,
364,
1330,
1033,
265,
198,
220,
220,
220,
1303,
11703,
27660,
338,
7824,
3421,
1022,
362,
13,
21,
290,
362,
13,
22,
198,
220,
220,
220,
1303,
279,
2645,
600,
25,
15560,
28,
34,
486,
3070,
198,
220,
220,
220,
2547,
325,
12331,
796,
651,
35226,
7,
20180,
27660,
11,
705,
10044,
325,
12331,
3256,
1033,
265,
13,
3109,
8071,
12331,
8,
198,
220,
220,
220,
1303,
279,
2645,
600,
25,
7139,
28,
34,
486,
3070,
198,
220,
220,
220,
33930,
62,
43,
55,
5805,
796,
10352,
198,
198,
28311,
25,
198,
220,
220,
220,
422,
2956,
297,
571,
1330,
19016,
9654,
198,
220,
220,
220,
1330,
19016,
29572,
198,
16341,
17267,
12331,
25,
198,
220,
220,
220,
422,
2956,
297,
571,
13,
25927,
1330,
19016,
9654,
198,
220,
220,
220,
422,
2956,
297,
571,
1330,
21136,
355,
19016,
29572,
220,
1303,
11361,
513,
198,
2,
279,
2645,
600,
25,
7139,
28,
36,
3312,
1157,
11,
37,
3023,
486,
11,
54,
3312,
1157,
628,
198,
6738,
764,
25471,
1330,
4174,
62,
47720,
258,
1039,
628,
198,
2,
11361,
362,
14,
18,
8330,
198,
28311,
25,
198,
220,
220,
220,
1615,
395,
1806,
198,
16341,
6530,
12331,
25,
198,
220,
220,
220,
1615,
395,
1806,
796,
965,
628,
198,
4871,
19081,
7,
11600,
2599,
198,
220,
220,
220,
37227,
50,
43490,
10139,
351,
8633,
12,
2339,
6608,
290,
1751,
526,
15931,
198,
220,
220,
220,
825,
11593,
15003,
834,
7,
944,
11,
10139,
11,
2560,
28,
14202,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
16447,
262,
19081,
422,
11703,
27660,
7559,
17440,
15506,
11,
351,
7559,
8000,
15506,
19081,
526,
15931,
198,
220,
220,
220,
220,
220,
220,
220,
2208,
7,
19667,
11,
2116,
737,
834,
15003,
834,
3419,
198,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
17197,
796,
7499,
628,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
15763,
796,
10352,
198,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
12985,
796,
10139,
13,
12985,
13,
35312,
7203,
92,
1600,
352,
38381,
12,
16,
60,
198,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
5239,
796,
10139,
13,
5239,
628,
220,
220,
220,
220,
220,
220,
220,
1303,
33141,
262,
17391,
198,
220,
220,
220,
220,
220,
220,
220,
3918,
796,
10139,
13,
1078,
822,
13,
1136,
7203,
7635,
4943,
198,
220,
220,
220,
220,
220,
220,
220,
611,
3918,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
329,
11688,
287,
3918,
13,
35312,
7203,
26033,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
611,
366,
11097,
287,
11688,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1438,
11,
1988,
796,
11688,
13,
35312,
7,
1298,
1600,
352,
8,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
10139,
13,
1078,
822,
58,
3672,
13,
36311,
3419,
60,
796,
1988,
13,
36311,
3419,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1619,
10139,
13,
1078,
822,
14692,
7635,
8973,
628,
220,
220,
220,
220,
220,
220,
220,
1303,
47025,
896,
422,
2560,
6608,
198,
220,
220,
220,
220,
220,
220,
220,
611,
2560,
318,
407,
6045,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
3709,
796,
2560,
13,
30073,
3419,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
407,
62,
259,
372,
863,
796,
5855,
35636,
1600,
366,
404,
4355,
4943,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
611,
2116,
13,
12985,
6624,
366,
912,
6839,
1298,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
407,
62,
259,
372,
863,
15853,
5855,
87,
1600,
366,
88,
4943,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
329,
11688,
287,
407,
62,
259,
372,
863,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
611,
11688,
287,
3709,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1619,
3709,
58,
42348,
60,
628,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1303,
16926,
46,
25,
4268,
584,
12608,
326,
815,
407,
307,
19552,
628,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
19119,
7,
23814,
8,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
6371,
796,
2560,
13,
6371,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
19875,
62,
21048,
796,
2560,
13,
19875,
62,
21048,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
8000,
796,
2560,
628,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
19119,
7,
11600,
7,
17440,
13,
1078,
822,
13,
23814,
3419,
4008,
628,
220,
220,
220,
220,
220,
220,
220,
1303,
1869,
496,
2420,
416,
4441,
1751,
198,
220,
220,
220,
220,
220,
220,
220,
611,
2116,
13,
12985,
6624,
366,
5239,
1,
393,
2116,
13,
12985,
6624,
366,
5239,
15235,
1298,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
17197,
796,
2116,
13,
5239,
62,
17197,
7,
17440,
8,
628,
220,
220,
220,
220,
220,
220,
220,
611,
407,
2116,
13,
17197,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
17197,
796,
46545,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
19081,
7,
9410,
11,
2116,
8,
329,
1200,
287,
10139,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
611,
318,
39098,
7,
9410,
13,
12985,
11,
1615,
395,
1806,
4008,
628,
220,
220,
220,
825,
2420,
62,
17197,
7,
944,
11,
10139,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
16447,
1751,
290,
1441,
606,
526,
15931,
198,
220,
220,
220,
220,
220,
220,
220,
1751,
796,
17635,
628,
220,
220,
220,
220,
220,
220,
220,
329,
1200,
287,
10139,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1751,
13,
33295,
7,
19667,
7,
9410,
11,
2560,
28,
944,
4008,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
611,
1200,
13,
13199,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
11614,
796,
11703,
27660,
13,
20180,
10786,
912,
6839,
11537,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
11614,
13,
5239,
796,
1200,
13,
13199,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1751,
13,
33295,
7,
19667,
7,
272,
6704,
11,
2560,
28,
944,
4008,
628,
220,
220,
220,
220,
220,
220,
220,
1441,
1351,
7,
17197,
8,
628,
198,
4871,
12200,
7,
19667,
2599,
198,
220,
220,
220,
37227,
50,
43490,
5509,
526,
15931,
198,
220,
220,
220,
825,
11593,
15003,
834,
7,
944,
11,
12429,
46265,
22046,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
16447,
262,
12200,
422,
45809,
7559,
5239,
15506,
526,
15931,
198,
220,
220,
220,
220,
220,
220,
220,
1303,
6889,
262,
10007,
21179,
12,
8807,
25,
198,
220,
220,
220,
220,
220,
220,
220,
416,
9288,
1806,
796,
479,
86,
22046,
13,
12924,
10786,
1525,
9288,
1806,
3256,
6045,
8,
198,
220,
220,
220,
220,
220,
220,
220,
2393,
62,
26801,
796,
479,
86,
22046,
13,
12924,
10786,
7753,
62,
26801,
3256,
6045,
8,
198,
220,
220,
220,
220,
220,
220,
220,
19016,
796,
479,
86,
22046,
13,
12924,
10786,
6371,
3256,
6045,
8,
198,
220,
220,
220,
220,
220,
220,
220,
2560,
796,
479,
86,
22046,
13,
12924,
10786,
8000,
3256,
6045,
8,
628,
220,
220,
220,
220,
220,
220,
220,
611,
416,
9288,
1806,
318,
407,
6045,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
5509,
796,
11703,
27660,
13,
6738,
8841,
7,
1525,
9288,
1806,
8,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
6371,
796,
19016,
198,
220,
220,
220,
220,
220,
220,
220,
1288,
361,
2393,
62,
26801,
318,
407,
6045,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
5509,
796,
11703,
27660,
13,
29572,
7,
7753,
62,
26801,
737,
1136,
15763,
3419,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
6371,
796,
651,
35226,
7,
7753,
62,
26801,
11,
705,
3672,
3256,
19016,
8,
198,
220,
220,
220,
220,
220,
220,
220,
1288,
361,
19016,
318,
407,
6045,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
611,
25113,
1,
287,
19016,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
19016,
11,
5002,
62,
312,
796,
19016,
13,
35312,
7203,
2,
1600,
352,
8,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2073,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
5002,
62,
312,
796,
6045,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
611,
2560,
290,
2560,
13,
6371,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
611,
19016,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
19016,
796,
19016,
29572,
13,
6371,
22179,
7,
8000,
13,
6371,
11,
19016,
8,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1288,
361,
5002,
62,
312,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
19016,
796,
2560,
13,
6371,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
6371,
796,
19016,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
611,
19016,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
611,
19016,
29572,
13,
6371,
29572,
7,
6371,
737,
15952,
1326,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
5128,
62,
796,
19016,
9654,
7,
6371,
8,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2073,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
5128,
62,
796,
19016,
220,
1303,
29472,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
5509,
796,
11703,
27660,
13,
29572,
7,
15414,
62,
737,
1136,
15763,
3419,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2073,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
5509,
796,
2560,
13,
19875,
62,
21048,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
611,
5002,
62,
312,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
41313,
796,
357,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
5509,
13,
2676,
3419,
611,
468,
35226,
7,
21048,
11,
705,
2676,
11537,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2073,
5509,
13,
1136,
48727,
28955,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
329,
5002,
287,
41313,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
611,
5002,
13,
1136,
7203,
312,
4943,
6624,
5002,
62,
312,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
5509,
796,
5002,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2270,
198,
220,
220,
220,
220,
220,
220,
220,
2073,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
5298,
5994,
12331,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
2949,
5128,
13,
5765,
530,
286,
416,
9288,
1806,
11,
2393,
62,
26801,
393,
19016,
2637,
8,
198,
220,
220,
220,
220,
220,
220,
220,
4174,
62,
47720,
258,
1039,
7,
21048,
8,
198,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
19875,
62,
21048,
796,
5509,
198,
220,
220,
220,
220,
220,
220,
220,
2208,
7,
27660,
11,
2116,
737,
834,
15003,
834,
7,
21048,
11,
2560,
8,
198,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
15763,
796,
6407,
198
] | 2.176844 | 2,522 |
from onegov.core.security import Private, Public
from onegov.form import FormCollection, FormDefinition
from onegov.org.forms.form_definition import FormDefinitionUrlForm
from onegov.org.views.form_definition import get_form_class, \
handle_new_definition, handle_edit_definition, handle_defined_form, \
handle_change_form_name
from onegov.town6 import TownApp
from onegov.town6.layout import FormEditorLayout, FormSubmissionLayout
@TownApp.form(model=FormDefinition, template='form.pt', permission=Public,
form=lambda self, request: self.form_class)
@TownApp.form(model=FormCollection, name='new', template='form.pt',
permission=Private, form=get_form_class)
@TownApp.form(model=FormDefinition, template='form.pt', permission=Private,
form=get_form_class, name='edit')
@TownApp.form(
model=FormDefinition, form=FormDefinitionUrlForm,
template='form.pt', permission=Private,
name='change-url'
)
| [
6738,
530,
9567,
13,
7295,
13,
12961,
1330,
15348,
11,
5094,
198,
6738,
530,
9567,
13,
687,
1330,
5178,
36307,
11,
5178,
36621,
198,
6738,
530,
9567,
13,
2398,
13,
23914,
13,
687,
62,
46758,
1330,
5178,
36621,
28165,
8479,
198,
6738,
530,
9567,
13,
2398,
13,
33571,
13,
687,
62,
46758,
1330,
651,
62,
687,
62,
4871,
11,
3467,
198,
220,
220,
220,
5412,
62,
3605,
62,
46758,
11,
5412,
62,
19312,
62,
46758,
11,
5412,
62,
23211,
62,
687,
11,
3467,
198,
220,
220,
220,
5412,
62,
3803,
62,
687,
62,
3672,
198,
6738,
530,
9567,
13,
12735,
21,
1330,
8329,
4677,
198,
6738,
530,
9567,
13,
12735,
21,
13,
39786,
1330,
5178,
17171,
32517,
11,
5178,
7004,
3411,
32517,
628,
198,
31,
38097,
4677,
13,
687,
7,
19849,
28,
8479,
36621,
11,
11055,
11639,
687,
13,
457,
3256,
7170,
28,
15202,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1296,
28,
50033,
2116,
11,
2581,
25,
2116,
13,
687,
62,
4871,
8,
628,
198,
31,
38097,
4677,
13,
687,
7,
19849,
28,
8479,
36307,
11,
1438,
11639,
3605,
3256,
11055,
11639,
687,
13,
457,
3256,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
7170,
28,
29067,
11,
1296,
28,
1136,
62,
687,
62,
4871,
8,
628,
198,
31,
38097,
4677,
13,
687,
7,
19849,
28,
8479,
36621,
11,
11055,
11639,
687,
13,
457,
3256,
7170,
28,
29067,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1296,
28,
1136,
62,
687,
62,
4871,
11,
1438,
11639,
19312,
11537,
628,
198,
31,
38097,
4677,
13,
687,
7,
198,
220,
220,
220,
2746,
28,
8479,
36621,
11,
1296,
28,
8479,
36621,
28165,
8479,
11,
198,
220,
220,
220,
11055,
11639,
687,
13,
457,
3256,
7170,
28,
29067,
11,
198,
220,
220,
220,
1438,
11639,
3803,
12,
6371,
6,
198,
8,
198
] | 3.006231 | 321 |
import cv2
from time import time
from random import randint
from object_manager import DefaultCircleManager, PackmanManager, MoovingCircleManager
from utils import log, Joint
from drawing import draw_objects
from config import config
| [
11748,
269,
85,
17,
198,
6738,
640,
1330,
640,
198,
6738,
4738,
1330,
43720,
600,
198,
6738,
2134,
62,
37153,
1330,
15161,
31560,
293,
13511,
11,
6400,
805,
13511,
11,
4270,
5165,
31560,
293,
13511,
198,
6738,
3384,
4487,
1330,
2604,
11,
16798,
198,
6738,
8263,
1330,
3197,
62,
48205,
198,
6738,
4566,
1330,
4566,
628,
628,
198
] | 4.103448 | 58 |
from __future__ import print_function, absolute_import, division
import sys
import os.path
import re
from contextlib import contextmanager
import subprocess
import numpy as np
from numba import unittest_support as unittest
from numba import config
from ..support import captured_stdout
from ..test_dispatcher import BaseCacheTest
class UfuncCacheTest(BaseCacheTest):
"""
Since the cache stats is not exposed by ufunc, we test by looking at the
cache debug log.
"""
here = os.path.dirname(__file__)
usecases_file = os.path.join(here, "cache_usecases.py")
modname = "ufunc_caching_test_fodder"
regex_data_saved = re.compile(r'\[cache\] data saved to')
regex_index_saved = re.compile(r'\[cache\] index saved to')
regex_data_loaded = re.compile(r'\[cache\] data loaded from')
regex_index_loaded = re.compile(r'\[cache\] index loaded from')
@contextmanager
def check_cache_saved(self, cachelog, count):
"""
Check number of cache-save were issued
"""
data_saved = self.regex_data_saved.findall(cachelog)
index_saved = self.regex_index_saved.findall(cachelog)
self.assertEqual(len(data_saved), count)
self.assertEqual(len(index_saved), count)
def check_cache_loaded(self, cachelog, count):
"""
Check number of cache-load were issued
"""
data_loaded = self.regex_data_loaded.findall(cachelog)
index_loaded = self.regex_index_loaded.findall(cachelog)
self.assertEqual(len(data_loaded), count)
self.assertEqual(len(index_loaded), count)
def check_ufunc_cache(self, usecase_name, n_overloads, **kwargs):
"""
Check number of cache load/save.
There should be one per overloaded version.
"""
mod = self.import_module()
usecase = getattr(mod, usecase_name)
# New cache entry saved
with self.capture_cache_log() as out:
new_ufunc = usecase(**kwargs)
cachelog = out.getvalue()
self.check_cache_saved(cachelog, count=n_overloads)
# Use cached version
with self.capture_cache_log() as out:
cached_ufunc = usecase(**kwargs)
cachelog = out.getvalue()
self.check_cache_loaded(cachelog, count=n_overloads)
return new_ufunc, cached_ufunc
# Note: DUFunc doesn't support parallel target yet
#
# The following test issue #2198 that loading cached (g)ufunc first
# bypasses some target context initialization.
#
if __name__ == '__main__':
unittest.main()
| [
6738,
11593,
37443,
834,
1330,
3601,
62,
8818,
11,
4112,
62,
11748,
11,
7297,
198,
198,
11748,
25064,
198,
11748,
28686,
13,
6978,
198,
11748,
302,
198,
6738,
4732,
8019,
1330,
4732,
37153,
198,
11748,
850,
14681,
198,
198,
11748,
299,
32152,
355,
45941,
198,
198,
6738,
997,
7012,
1330,
555,
715,
395,
62,
11284,
355,
555,
715,
395,
198,
6738,
997,
7012,
1330,
4566,
198,
198,
6738,
11485,
11284,
1330,
7907,
62,
19282,
448,
198,
6738,
11485,
9288,
62,
6381,
8071,
2044,
1330,
7308,
30562,
14402,
628,
198,
4871,
471,
20786,
30562,
14402,
7,
14881,
30562,
14402,
2599,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
4619,
262,
12940,
9756,
318,
407,
7362,
416,
334,
20786,
11,
356,
1332,
416,
2045,
379,
262,
198,
220,
220,
220,
12940,
14257,
2604,
13,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
994,
796,
28686,
13,
6978,
13,
15908,
3672,
7,
834,
7753,
834,
8,
198,
220,
220,
220,
779,
33964,
62,
7753,
796,
28686,
13,
6978,
13,
22179,
7,
1456,
11,
366,
23870,
62,
1904,
33964,
13,
9078,
4943,
198,
220,
220,
220,
953,
3672,
796,
366,
3046,
19524,
62,
66,
8103,
62,
9288,
62,
69,
35346,
1,
628,
220,
220,
220,
40364,
62,
7890,
62,
82,
9586,
796,
302,
13,
5589,
576,
7,
81,
6,
59,
58,
23870,
59,
60,
1366,
7448,
284,
11537,
198,
220,
220,
220,
40364,
62,
9630,
62,
82,
9586,
796,
302,
13,
5589,
576,
7,
81,
6,
59,
58,
23870,
59,
60,
6376,
7448,
284,
11537,
628,
220,
220,
220,
40364,
62,
7890,
62,
14578,
796,
302,
13,
5589,
576,
7,
81,
6,
59,
58,
23870,
59,
60,
1366,
9639,
422,
11537,
198,
220,
220,
220,
40364,
62,
9630,
62,
14578,
796,
302,
13,
5589,
576,
7,
81,
6,
59,
58,
23870,
59,
60,
6376,
9639,
422,
11537,
628,
220,
220,
220,
2488,
22866,
37153,
628,
220,
220,
220,
825,
2198,
62,
23870,
62,
82,
9586,
7,
944,
11,
269,
9636,
519,
11,
954,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
6822,
1271,
286,
12940,
12,
21928,
547,
4884,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
1366,
62,
82,
9586,
796,
2116,
13,
260,
25636,
62,
7890,
62,
82,
9586,
13,
19796,
439,
7,
66,
9636,
519,
8,
198,
220,
220,
220,
220,
220,
220,
220,
6376,
62,
82,
9586,
796,
2116,
13,
260,
25636,
62,
9630,
62,
82,
9586,
13,
19796,
439,
7,
66,
9636,
519,
8,
198,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
30493,
36,
13255,
7,
11925,
7,
7890,
62,
82,
9586,
828,
954,
8,
198,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
30493,
36,
13255,
7,
11925,
7,
9630,
62,
82,
9586,
828,
954,
8,
628,
220,
220,
220,
825,
2198,
62,
23870,
62,
14578,
7,
944,
11,
269,
9636,
519,
11,
954,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
6822,
1271,
286,
12940,
12,
2220,
547,
4884,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
1366,
62,
14578,
796,
2116,
13,
260,
25636,
62,
7890,
62,
14578,
13,
19796,
439,
7,
66,
9636,
519,
8,
198,
220,
220,
220,
220,
220,
220,
220,
6376,
62,
14578,
796,
2116,
13,
260,
25636,
62,
9630,
62,
14578,
13,
19796,
439,
7,
66,
9636,
519,
8,
198,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
30493,
36,
13255,
7,
11925,
7,
7890,
62,
14578,
828,
954,
8,
198,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
30493,
36,
13255,
7,
11925,
7,
9630,
62,
14578,
828,
954,
8,
628,
220,
220,
220,
825,
2198,
62,
3046,
19524,
62,
23870,
7,
944,
11,
779,
7442,
62,
3672,
11,
299,
62,
2502,
46030,
11,
12429,
46265,
22046,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
6822,
1271,
286,
12940,
3440,
14,
21928,
13,
198,
220,
220,
220,
220,
220,
220,
220,
1318,
815,
307,
530,
583,
50068,
2196,
13,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
953,
796,
2116,
13,
11748,
62,
21412,
3419,
198,
220,
220,
220,
220,
220,
220,
220,
779,
7442,
796,
651,
35226,
7,
4666,
11,
779,
7442,
62,
3672,
8,
198,
220,
220,
220,
220,
220,
220,
220,
1303,
968,
12940,
5726,
7448,
198,
220,
220,
220,
220,
220,
220,
220,
351,
2116,
13,
27144,
495,
62,
23870,
62,
6404,
3419,
355,
503,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
649,
62,
3046,
19524,
796,
779,
7442,
7,
1174,
46265,
22046,
8,
198,
220,
220,
220,
220,
220,
220,
220,
269,
9636,
519,
796,
503,
13,
1136,
8367,
3419,
198,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
9122,
62,
23870,
62,
82,
9586,
7,
66,
9636,
519,
11,
954,
28,
77,
62,
2502,
46030,
8,
628,
220,
220,
220,
220,
220,
220,
220,
1303,
5765,
39986,
2196,
198,
220,
220,
220,
220,
220,
220,
220,
351,
2116,
13,
27144,
495,
62,
23870,
62,
6404,
3419,
355,
503,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
39986,
62,
3046,
19524,
796,
779,
7442,
7,
1174,
46265,
22046,
8,
198,
220,
220,
220,
220,
220,
220,
220,
269,
9636,
519,
796,
503,
13,
1136,
8367,
3419,
198,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
9122,
62,
23870,
62,
14578,
7,
66,
9636,
519,
11,
954,
28,
77,
62,
2502,
46030,
8,
628,
220,
220,
220,
220,
220,
220,
220,
1441,
649,
62,
3046,
19524,
11,
39986,
62,
3046,
19524,
628,
198,
220,
220,
220,
1303,
5740,
25,
35480,
37,
19524,
1595,
470,
1104,
10730,
2496,
1865,
628,
628,
198,
220,
220,
220,
1303,
198,
220,
220,
220,
1303,
383,
1708,
1332,
2071,
1303,
17,
22337,
326,
11046,
39986,
357,
70,
8,
3046,
19524,
717,
198,
220,
220,
220,
1303,
17286,
274,
617,
2496,
4732,
37588,
13,
198,
220,
220,
220,
1303,
628,
198,
361,
11593,
3672,
834,
6624,
705,
834,
12417,
834,
10354,
198,
220,
220,
220,
555,
715,
395,
13,
12417,
3419,
198
] | 2.472779 | 1,047 |
"""
this is an attempt to convert a readable patt format (similar to the ones compatible with arbitrarypatterngenerator) into the 4-word format that can be cat into pattern generator v2
it reads pattfile written in the following format and generate the corresponding dpatt:
#triggered input_line use_table threshold_counts_per_second if_success_table if_failure_table time_to_trigger [bits to turn on(0-25)]
#sequential [repeat_table(at least 0)] use_table end_table time [bits to turn on(0-25)]
#conditional input_line use_table if_success_table trigger_width [bits to turn on(0-25)]
in this version,
1) internal counters 0 and 1 are always loaded with 10 and 100 to deal with '>3ms' and '>30ms' scale signal
counters 2 and 3 is used if sequential repeats (which means only two sequential can repeat currently)
2) toupper func is not implemented, so the comparison is case-sensitive
3) triggered accepts only 1-line pattern
4) hooks are not implemented yet
5) fixed directory to save dpatt
7) always start from row 0 and table 0
8) at sequential loops, the loading of counter will introduce a 10ns shift; if next-table existed, the additional line to jump to next-table will also introduce 10ns shift
9) conditional is implemented
10) check number of lines before the file is being cat'ed
updated on 10/7/2019
Update on 2/1/2020 by Chin Chean:
1) table_dic, table_lst, and rep_count are cleared every time generator is called from the GUI.
2) When uploading scripts multiple times, adding a config 0; at the start of the .word file might prevent crashing of device. This command is now appended on the generated file.
@author: Chang Hoong QO LAB, NUS
"""
mode_list = ['','.','triggered','sequential','conditional']
unit_list = ['','ns','us','ms']
error_list = ['no error (0)','invalid token (1)','too many sequential loop (2)', 'invalid output (3)', 'invalid number (4)', 'no unit found (5)', 'shorter than clock cycle (6)', 'repeated output warning (7)', 'invalid termination (8)','null error (9)','repeated table number (10)','multiple thresholds for same input (11)', 'pattern too long (12)']
table_dic = {} #contains information about address of each table for branching
table_lst = [] #contains all patterns to be applied
rep_count = [] #contains additional internal counters being used
# format of table_lst
# (if triggered) [table_no, success_table_no, fail_table_no, input_line, threshold_counts, num_clock_cycle, output] (7 components)
# (if sequential) [table_no, next_table, repeat, num_clock_cycle, output] (5 components)
# (if conditional) [table_no success_table_no, NULL, input_line, num_clock_cycle, output] (6 components)
# number of components can decide mode type
# 'output' consists of a two-element array (left right word)
# find token and return token_nb, ptr_in_str
# return the readout number + remaining string
# if number not found, output -1 and ''
# need old token so that 2nd line of sequential can be interpredated as sequential
# return the old token and the remaining argument
Max_cyclenumber_per_line = 65536
# output the remaining string
# should read duration and output bits
# output the remaining string
# should read input_line use_table threshold_counts_per_second if_success_table if_failure_table time_to_trigger [bits to turn on(0-25)]
# output the remaining string
# should read input_line use_table if_success_table if_failure_table time_to_trigger [bits to turn on(0-25)]
# return chain of str for this table, and the new addr_ptr
# if __name__ == '__main__':
# import argparse
# parser = argparse.ArgumentParser(description='Generate dpatt from patt')
# parser.add_argument('-i','--inputstr',type=str,default='load_atom_redu.patt')
# parser.add_argument('-o','--outputstr',type=str,default='isto.dat')
# args = parser.parse_args()
# pattfile = open(args.inputstr,'r')
# outputfile = open(args.outputstr,'w+')
#
# output = main(pattfile)
# outputfile.write(output)
#
# pattfile.close()
# outputfile.close()
#
# num_lines = sum(1 for line in open(args.outputstr,'r'))
# #print(num_lines-len(table_dic)-4) #for debugging
# if (num_lines-len(table_dic)-4) > 256:
# raise Exception(error_list[12])
| [
37811,
201,
198,
5661,
318,
281,
2230,
284,
10385,
257,
31744,
279,
1078,
5794,
357,
38610,
284,
262,
3392,
11670,
351,
14977,
33279,
8612,
1352,
8,
656,
262,
604,
12,
4775,
5794,
326,
460,
307,
3797,
656,
3912,
17301,
410,
17,
201,
198,
270,
9743,
279,
1078,
7753,
3194,
287,
262,
1708,
5794,
290,
7716,
262,
11188,
288,
79,
1078,
25,
201,
198,
197,
2,
2213,
328,
10446,
5128,
62,
1370,
779,
62,
11487,
11387,
62,
9127,
82,
62,
525,
62,
12227,
611,
62,
13138,
62,
11487,
611,
62,
32165,
495,
62,
11487,
640,
62,
1462,
62,
46284,
685,
9895,
284,
1210,
319,
7,
15,
12,
1495,
15437,
201,
198,
197,
2,
3107,
1843,
685,
44754,
62,
11487,
7,
265,
1551,
657,
15437,
779,
62,
11487,
886,
62,
11487,
640,
685,
9895,
284,
1210,
319,
7,
15,
12,
1495,
15437,
201,
198,
197,
2,
17561,
1859,
5128,
62,
1370,
779,
62,
11487,
611,
62,
13138,
62,
11487,
7616,
62,
10394,
685,
9895,
284,
1210,
319,
7,
15,
12,
1495,
15437,
201,
198,
259,
428,
2196,
11,
220,
201,
198,
16,
8,
5387,
21154,
657,
290,
352,
389,
1464,
9639,
351,
838,
290,
1802,
284,
1730,
351,
705,
29,
18,
907,
6,
290,
705,
29,
1270,
907,
6,
5046,
6737,
201,
198,
66,
15044,
362,
290,
513,
318,
973,
611,
35582,
29819,
357,
4758,
1724,
691,
734,
35582,
460,
9585,
3058,
8,
201,
198,
17,
8,
2819,
2848,
25439,
318,
407,
9177,
11,
523,
262,
7208,
318,
1339,
12,
30176,
201,
198,
18,
8,
13973,
18178,
691,
352,
12,
1370,
3912,
201,
198,
19,
8,
26569,
389,
407,
9177,
1865,
201,
198,
20,
8,
5969,
8619,
284,
3613,
288,
79,
1078,
201,
198,
22,
8,
1464,
923,
422,
5752,
657,
290,
3084,
657,
201,
198,
23,
8,
379,
35582,
23607,
11,
262,
11046,
286,
3753,
481,
10400,
257,
838,
5907,
6482,
26,
611,
1306,
12,
11487,
11196,
11,
262,
3224,
1627,
284,
4391,
284,
1306,
12,
11487,
481,
635,
10400,
838,
5907,
6482,
201,
198,
24,
8,
26340,
318,
9177,
201,
198,
940,
8,
2198,
1271,
286,
3951,
878,
262,
2393,
318,
852,
3797,
6,
276,
201,
198,
43162,
319,
838,
14,
22,
14,
23344,
201,
198,
201,
198,
10260,
319,
362,
14,
16,
14,
42334,
416,
22604,
2580,
272,
25,
201,
198,
16,
8,
3084,
62,
67,
291,
11,
3084,
62,
75,
301,
11,
290,
1128,
62,
9127,
389,
12539,
790,
640,
17301,
318,
1444,
422,
262,
25757,
13,
201,
198,
17,
8,
1649,
33794,
14750,
3294,
1661,
11,
4375,
257,
4566,
657,
26,
379,
262,
923,
286,
262,
764,
4775,
2393,
1244,
2948,
21899,
286,
3335,
13,
770,
3141,
318,
783,
598,
1631,
319,
262,
7560,
2393,
13,
201,
198,
201,
198,
31,
9800,
25,
22597,
9544,
506,
220,
1195,
46,
406,
6242,
11,
399,
2937,
201,
198,
37811,
201,
198,
201,
198,
14171,
62,
4868,
796,
37250,
41707,
2637,
4032,
2213,
328,
10446,
41707,
3107,
1843,
41707,
17561,
1859,
20520,
201,
198,
20850,
62,
4868,
796,
37250,
41707,
5907,
41707,
385,
41707,
907,
20520,
201,
198,
18224,
62,
4868,
796,
37250,
3919,
4049,
357,
15,
8,
41707,
259,
12102,
11241,
357,
16,
8,
41707,
18820,
867,
35582,
9052,
357,
17,
8,
3256,
705,
259,
12102,
5072,
357,
18,
8,
3256,
705,
259,
12102,
1271,
357,
19,
8,
3256,
705,
3919,
4326,
1043,
357,
20,
8,
3256,
705,
1477,
4337,
621,
8801,
6772,
357,
21,
8,
3256,
705,
45956,
515,
5072,
6509,
357,
22,
8,
3256,
705,
259,
12102,
19883,
357,
23,
8,
41707,
8423,
4049,
357,
24,
8,
41707,
45956,
515,
3084,
1271,
357,
940,
8,
41707,
48101,
40885,
329,
976,
5128,
357,
1157,
8,
3256,
705,
33279,
1165,
890,
357,
1065,
8,
20520,
201,
198,
201,
198,
201,
198,
11487,
62,
67,
291,
796,
23884,
197,
2,
3642,
1299,
1321,
546,
2209,
286,
1123,
3084,
329,
49526,
201,
198,
11487,
62,
75,
301,
796,
17635,
197,
2,
3642,
1299,
477,
7572,
284,
307,
5625,
201,
198,
7856,
62,
9127,
796,
17635,
197,
2,
3642,
1299,
3224,
5387,
21154,
852,
973,
201,
198,
2,
5794,
286,
3084,
62,
75,
301,
201,
198,
2,
357,
361,
13973,
8,
685,
11487,
62,
3919,
11,
1943,
62,
11487,
62,
3919,
11,
2038,
62,
11487,
62,
3919,
11,
5128,
62,
1370,
11,
11387,
62,
9127,
82,
11,
997,
62,
15750,
62,
13696,
11,
5072,
60,
357,
22,
6805,
8,
201,
198,
2,
357,
361,
35582,
8,
685,
11487,
62,
3919,
11,
1306,
62,
11487,
11,
9585,
11,
997,
62,
15750,
62,
13696,
11,
5072,
60,
357,
20,
6805,
8,
201,
198,
2,
357,
361,
26340,
8,
685,
11487,
62,
3919,
1943,
62,
11487,
62,
3919,
11,
15697,
11,
5128,
62,
1370,
11,
997,
62,
15750,
62,
13696,
11,
5072,
60,
357,
21,
6805,
8,
201,
198,
2,
1271,
286,
6805,
460,
5409,
4235,
2099,
201,
198,
2,
705,
22915,
6,
10874,
286,
257,
734,
12,
30854,
7177,
357,
9464,
826,
1573,
8,
201,
198,
201,
198,
2,
1064,
11241,
290,
1441,
11241,
62,
46803,
11,
50116,
62,
259,
62,
2536,
220,
201,
198,
201,
198,
2,
1441,
262,
1100,
448,
1271,
1343,
5637,
4731,
201,
198,
2,
611,
1271,
407,
1043,
11,
5072,
532,
16,
290,
10148,
201,
198,
197,
201,
198,
2,
761,
1468,
11241,
523,
326,
362,
358,
1627,
286,
35582,
460,
307,
987,
28764,
515,
355,
35582,
201,
198,
2,
1441,
262,
1468,
11241,
290,
262,
5637,
4578,
201,
198,
201,
198,
201,
198,
11518,
62,
15539,
268,
4494,
62,
525,
62,
1370,
796,
45021,
2623,
201,
198,
201,
198,
2,
5072,
262,
5637,
4731,
201,
198,
2,
815,
1100,
9478,
290,
5072,
10340,
201,
198,
201,
198,
2,
5072,
262,
5637,
4731,
201,
198,
2,
815,
1100,
5128,
62,
1370,
779,
62,
11487,
11387,
62,
9127,
82,
62,
525,
62,
12227,
611,
62,
13138,
62,
11487,
611,
62,
32165,
495,
62,
11487,
640,
62,
1462,
62,
46284,
685,
9895,
284,
1210,
319,
7,
15,
12,
1495,
15437,
201,
198,
201,
198,
2,
5072,
262,
5637,
4731,
201,
198,
2,
815,
1100,
5128,
62,
1370,
779,
62,
11487,
611,
62,
13138,
62,
11487,
611,
62,
32165,
495,
62,
11487,
640,
62,
1462,
62,
46284,
685,
9895,
284,
1210,
319,
7,
15,
12,
1495,
15437,
201,
198,
201,
198,
2,
1441,
6333,
286,
965,
329,
428,
3084,
11,
290,
262,
649,
37817,
62,
20692,
201,
198,
201,
198,
201,
198,
201,
198,
2,
611,
11593,
3672,
834,
6624,
705,
834,
12417,
834,
10354,
201,
198,
2,
220,
197,
11748,
1822,
29572,
201,
198,
2,
220,
197,
48610,
796,
1822,
29572,
13,
28100,
1713,
46677,
7,
11213,
11639,
8645,
378,
288,
79,
1078,
422,
279,
1078,
11537,
201,
198,
2,
220,
197,
48610,
13,
2860,
62,
49140,
10786,
12,
72,
41707,
438,
15414,
2536,
3256,
4906,
28,
2536,
11,
12286,
11639,
2220,
62,
37696,
62,
445,
84,
13,
79,
1078,
11537,
201,
198,
2,
220,
197,
48610,
13,
2860,
62,
49140,
10786,
12,
78,
41707,
438,
22915,
2536,
3256,
4906,
28,
2536,
11,
12286,
11639,
396,
78,
13,
19608,
11537,
201,
198,
2,
220,
197,
22046,
796,
30751,
13,
29572,
62,
22046,
3419,
201,
198,
2,
220,
197,
79,
1078,
7753,
796,
1280,
7,
22046,
13,
15414,
2536,
4032,
81,
11537,
201,
198,
2,
220,
197,
22915,
7753,
796,
1280,
7,
22046,
13,
22915,
2536,
4032,
86,
10,
11537,
201,
198,
2,
201,
198,
2,
220,
197,
22915,
796,
1388,
7,
79,
1078,
7753,
8,
201,
198,
2,
220,
197,
22915,
7753,
13,
13564,
7,
22915,
8,
201,
198,
2,
201,
198,
2,
220,
197,
79,
1078,
7753,
13,
19836,
3419,
201,
198,
2,
220,
197,
22915,
7753,
13,
19836,
3419,
201,
198,
2,
201,
198,
2,
220,
197,
22510,
62,
6615,
796,
2160,
7,
16,
329,
1627,
287,
1280,
7,
22046,
13,
22915,
2536,
4032,
81,
6,
4008,
201,
198,
2,
220,
197,
2,
4798,
7,
22510,
62,
6615,
12,
11925,
7,
11487,
62,
67,
291,
13219,
19,
8,
1303,
1640,
28769,
201,
198,
2,
220,
197,
361,
357,
22510,
62,
6615,
12,
11925,
7,
11487,
62,
67,
291,
13219,
19,
8,
1875,
17759,
25,
201,
198,
2,
220,
197,
197,
40225,
35528,
7,
18224,
62,
4868,
58,
1065,
12962,
201,
198
] | 3.13069 | 1,362 |
# Create your tasks here
from __future__ import absolute_import, unicode_literals
from celery import shared_task
import time
@shared_task
@shared_task | [
198,
2,
13610,
534,
8861,
994,
198,
6738,
11593,
37443,
834,
1330,
4112,
62,
11748,
11,
28000,
1098,
62,
17201,
874,
198,
6738,
18725,
1924,
1330,
4888,
62,
35943,
198,
11748,
640,
198,
198,
31,
28710,
62,
35943,
628,
198,
31,
28710,
62,
35943
] | 3.5 | 44 |
from rest_framework import serializers
from .models import Course | [
6738,
1334,
62,
30604,
1330,
11389,
11341,
198,
6738,
764,
27530,
1330,
20537
] | 5 | 13 |
# Copyright (c) 2017 The WebRTC project authors. All Rights Reserved.
#
# Use of this source code is governed by a BSD-style license
# that can be found in the LICENSE file in the root of the source
# tree. An additional intellectual property rights grant can be found
# in the file PATENTS. All contributing project authors may
# be found in the AUTHORS file in the root of the source tree.
"""Evaluation score abstract class and implementations.
"""
from __future__ import division
import logging
import os
import re
import subprocess
from . import data_access
from . import exceptions
from . import signal_processing
@EvaluationScore.RegisterClass
class AudioLevelPeakScore(EvaluationScore):
"""Peak audio level score.
Defined as the difference between the peak audio level of the tested and
the reference signals.
Unit: dB
Ideal: 0 dB
Worst case: +/-inf dB
"""
NAME = 'audio_level_peak'
@EvaluationScore.RegisterClass
class MeanAudioLevelScore(EvaluationScore):
"""Mean audio level score.
Defined as the difference between the mean audio level of the tested and
the reference signals.
Unit: dB
Ideal: 0 dB
Worst case: +/-inf dB
"""
NAME = 'audio_level_mean'
@EvaluationScore.RegisterClass
class PolqaScore(EvaluationScore):
"""POLQA score.
See http://www.polqa.info/.
Unit: MOS
Ideal: 4.5
Worst case: 1.0
"""
NAME = 'polqa'
@classmethod
def _ParseOutputFile(cls, polqa_out_filepath):
"""
Parses the POLQA tool output formatted as a table ('-t' option).
Args:
polqa_out_filepath: path to the POLQA tool output file.
Returns:
A dict.
"""
data = []
with open(polqa_out_filepath) as f:
for line in f:
line = line.strip()
if len(line) == 0 or line.startswith('*'):
# Ignore comments.
continue
# Read fields.
data.append(re.split(r'\t+', line))
# Two rows expected (header and values).
assert len(data) == 2, 'Cannot parse POLQA output'
number_of_fields = len(data[0])
assert number_of_fields == len(data[1])
# Build and return a dictionary with field names (header) as keys and the
# corresponding field values as values.
return {data[0][index]: data[1][index] for index in range(number_of_fields)}
| [
2,
15069,
357,
66,
8,
2177,
383,
5313,
49,
4825,
1628,
7035,
13,
1439,
6923,
33876,
13,
198,
2,
198,
2,
5765,
286,
428,
2723,
2438,
318,
21825,
416,
257,
347,
10305,
12,
7635,
5964,
198,
2,
326,
460,
307,
1043,
287,
262,
38559,
24290,
2393,
287,
262,
6808,
286,
262,
2723,
198,
2,
5509,
13,
1052,
3224,
9028,
3119,
2489,
7264,
460,
307,
1043,
198,
2,
287,
262,
2393,
28748,
15365,
13,
220,
1439,
14329,
1628,
7035,
743,
198,
2,
307,
1043,
287,
262,
37195,
20673,
2393,
287,
262,
6808,
286,
262,
2723,
5509,
13,
198,
198,
37811,
36,
2100,
2288,
4776,
12531,
1398,
290,
25504,
13,
198,
37811,
198,
198,
6738,
11593,
37443,
834,
1330,
7297,
198,
11748,
18931,
198,
11748,
28686,
198,
11748,
302,
198,
11748,
850,
14681,
198,
198,
6738,
764,
1330,
1366,
62,
15526,
198,
6738,
764,
1330,
13269,
198,
6738,
764,
1330,
6737,
62,
36948,
628,
198,
198,
31,
36,
2100,
2288,
26595,
13,
38804,
9487,
198,
4871,
13491,
4971,
6435,
461,
26595,
7,
36,
2100,
2288,
26595,
2599,
198,
220,
37227,
6435,
461,
6597,
1241,
4776,
13,
628,
220,
2896,
1389,
355,
262,
3580,
1022,
262,
9103,
6597,
1241,
286,
262,
6789,
290,
198,
220,
262,
4941,
10425,
13,
628,
220,
11801,
25,
30221,
198,
220,
41765,
25,
657,
30221,
198,
220,
33443,
1339,
25,
29694,
10745,
30221,
198,
220,
37227,
628,
220,
36751,
796,
705,
24051,
62,
5715,
62,
36729,
6,
628,
198,
31,
36,
2100,
2288,
26595,
13,
38804,
9487,
198,
4871,
22728,
21206,
4971,
26595,
7,
36,
2100,
2288,
26595,
2599,
198,
220,
37227,
5308,
272,
6597,
1241,
4776,
13,
628,
220,
2896,
1389,
355,
262,
3580,
1022,
262,
1612,
6597,
1241,
286,
262,
6789,
290,
198,
220,
262,
4941,
10425,
13,
628,
220,
11801,
25,
30221,
198,
220,
41765,
25,
657,
30221,
198,
220,
33443,
1339,
25,
29694,
10745,
30221,
198,
220,
37227,
628,
220,
36751,
796,
705,
24051,
62,
5715,
62,
32604,
6,
628,
198,
31,
36,
2100,
2288,
26595,
13,
38804,
9487,
198,
4871,
2165,
20402,
26595,
7,
36,
2100,
2288,
26595,
2599,
198,
220,
37227,
45472,
48,
32,
4776,
13,
628,
220,
4091,
2638,
1378,
2503,
13,
16104,
20402,
13,
10951,
11757,
628,
220,
11801,
25,
337,
2640,
198,
220,
41765,
25,
604,
13,
20,
198,
220,
33443,
1339,
25,
352,
13,
15,
198,
220,
37227,
628,
220,
36751,
796,
705,
16104,
20402,
6,
628,
220,
2488,
4871,
24396,
198,
220,
825,
4808,
10044,
325,
26410,
8979,
7,
565,
82,
11,
755,
20402,
62,
448,
62,
7753,
6978,
2599,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
23042,
274,
262,
20634,
48,
32,
2891,
5072,
39559,
355,
257,
3084,
19203,
12,
83,
6,
3038,
737,
628,
220,
220,
220,
943,
14542,
25,
198,
220,
220,
220,
220,
220,
755,
20402,
62,
448,
62,
7753,
6978,
25,
3108,
284,
262,
20634,
48,
32,
2891,
5072,
2393,
13,
628,
220,
220,
220,
16409,
25,
198,
220,
220,
220,
220,
220,
317,
8633,
13,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
1366,
796,
17635,
198,
220,
220,
220,
351,
1280,
7,
16104,
20402,
62,
448,
62,
7753,
6978,
8,
355,
277,
25,
198,
220,
220,
220,
220,
220,
329,
1627,
287,
277,
25,
198,
220,
220,
220,
220,
220,
220,
220,
1627,
796,
1627,
13,
36311,
3419,
198,
220,
220,
220,
220,
220,
220,
220,
611,
18896,
7,
1370,
8,
6624,
657,
393,
1627,
13,
9688,
2032,
342,
10786,
9,
6,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1303,
41032,
3651,
13,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2555,
198,
220,
220,
220,
220,
220,
220,
220,
1303,
4149,
7032,
13,
198,
220,
220,
220,
220,
220,
220,
220,
1366,
13,
33295,
7,
260,
13,
35312,
7,
81,
6,
59,
83,
10,
3256,
1627,
4008,
628,
220,
220,
220,
1303,
4930,
15274,
2938,
357,
25677,
290,
3815,
737,
198,
220,
220,
220,
6818,
18896,
7,
7890,
8,
6624,
362,
11,
705,
34,
34574,
21136,
20634,
48,
32,
5072,
6,
198,
220,
220,
220,
1271,
62,
1659,
62,
25747,
796,
18896,
7,
7890,
58,
15,
12962,
198,
220,
220,
220,
6818,
1271,
62,
1659,
62,
25747,
6624,
18896,
7,
7890,
58,
16,
12962,
628,
220,
220,
220,
1303,
10934,
290,
1441,
257,
22155,
351,
2214,
3891,
357,
25677,
8,
355,
8251,
290,
262,
198,
220,
220,
220,
1303,
11188,
2214,
3815,
355,
3815,
13,
198,
220,
220,
220,
1441,
1391,
7890,
58,
15,
7131,
9630,
5974,
1366,
58,
16,
7131,
9630,
60,
329,
6376,
287,
2837,
7,
17618,
62,
1659,
62,
25747,
38165,
198
] | 3.005229 | 765 |
ICAO = {
"Anaa": "NTGA",
"Apalachicola Regional": "KAAF",
"Malamala": "FAMD",
"Al Ain International": "OMAL",
"Atlantic City": "KACY",
"Albany International": "KBAL",
"Baise Youjiang": "ZGBS",
"Albuquerque International Sunport": "KABQ",
"RAF Abisko": "EAAK",
"RAF Leuchars": "EGQL",
"Santiago de Compostela": "LEST",
"Seve Ballesteros-Santander": "LEXJ",
}
| [
25241,
46,
796,
1391,
198,
220,
220,
220,
366,
2025,
7252,
1298,
366,
11251,
9273,
1600,
198,
220,
220,
220,
366,
32,
18596,
620,
291,
5708,
15994,
1298,
366,
42,
38540,
1600,
198,
220,
220,
220,
366,
15029,
321,
6081,
1298,
366,
37,
28075,
1600,
198,
220,
220,
220,
366,
2348,
31899,
4037,
1298,
366,
2662,
1847,
1600,
198,
220,
220,
220,
366,
41120,
2254,
1298,
366,
42,
43300,
1600,
198,
220,
220,
220,
366,
2348,
65,
1092,
4037,
1298,
366,
22764,
1847,
1600,
198,
220,
220,
220,
366,
34458,
786,
921,
39598,
1298,
366,
57,
38,
4462,
1600,
198,
220,
220,
220,
366,
2348,
36461,
4037,
3825,
634,
1298,
366,
42,
6242,
48,
1600,
198,
220,
220,
220,
366,
3861,
37,
2275,
1984,
78,
1298,
366,
36,
3838,
42,
1600,
198,
220,
220,
220,
366,
3861,
37,
1004,
794,
945,
1298,
366,
7156,
9711,
1600,
198,
220,
220,
220,
366,
50,
17096,
3839,
390,
3082,
455,
10304,
1298,
366,
43,
6465,
1600,
198,
220,
220,
220,
366,
4653,
303,
6932,
7834,
418,
12,
50,
415,
4066,
1298,
366,
2538,
55,
41,
1600,
198,
92,
628
] | 2.188172 | 186 |
import sys
import logging
import ply.lex
logger = logging.getLogger(__name__)
class Lexer(object):
'''
A Lexical analyzer for Python Typelanguage.
'''
def tokenize(self, string):
'''
Maps a string to an iterator over tokens. In other words: [char] -> [token]
'''
new_lexer = ply.lex.lex(module=self, debug=self.debug, errorlog=logger)
new_lexer.latest_newline = 0
new_lexer.input(string)
while True:
t = new_lexer.token()
if t is None: break
t.col = t.lexpos - new_lexer.latest_newline
yield t
# ============== PLY Lexer specification ==================
#
# This probably should be private but:
# - the parser requires access to `tokens` (perhaps they should be defined in a third, shared dependency)
# - things like `literals` might be a legitimate part of the public interface.
#
# Anyhow, it is pythonic to give some rope to hang oneself with :-)
literals = ['|', '(', ')', '{', '}', '[', ']', ':', '*', ',', ';']
reserved_words = { 'object': 'OBJECT' }
tokens = ['ID', 'TYVAR', 'ARROW', 'KWARG', 'ANY'] + reserved_words.values()
t_ARROW = r'->'
t_KWARG = r'\*\*'
t_ANY = r'\?\?'
t_ignore = ' \t'
def t_ID(self, t):
r'~?[a-zA-Z_][a-zA-Z0-9_]*'
if t.value[0] == '~':
t.type = 'TYVAR'
t.value = t.value[1:]
elif t.value in self.reserved_words:
t.type = self.reserved_words[t.value]
else:
t.type = 'ID'
return t
def t_newline(self, t):
r'\n'
t.lexer.lineno += 1
t.lexer.latest_newline = t.lexpos
if __name__ == '__main__':
logging.basicConfig()
lexer = Lexer(debug=True)
for token in lexer.tokenize(sys.stdin.read()):
print '%-20s%s' % (token.value, token.type)
| [
11748,
25064,
198,
11748,
18931,
198,
198,
11748,
35960,
13,
2588,
198,
198,
6404,
1362,
796,
18931,
13,
1136,
11187,
1362,
7,
834,
3672,
834,
8,
198,
198,
4871,
17210,
263,
7,
15252,
2599,
198,
220,
220,
220,
705,
7061,
198,
220,
220,
220,
317,
17210,
605,
4284,
9107,
329,
11361,
17134,
417,
9000,
13,
198,
220,
220,
220,
705,
7061,
628,
220,
220,
220,
825,
11241,
1096,
7,
944,
11,
4731,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
705,
7061,
198,
220,
220,
220,
220,
220,
220,
220,
20347,
257,
4731,
284,
281,
41313,
625,
16326,
13,
554,
584,
2456,
25,
685,
10641,
60,
4613,
685,
30001,
60,
198,
220,
220,
220,
220,
220,
220,
220,
705,
7061,
198,
220,
220,
220,
220,
220,
220,
220,
220,
198,
220,
220,
220,
220,
220,
220,
220,
649,
62,
2588,
263,
796,
35960,
13,
2588,
13,
2588,
7,
21412,
28,
944,
11,
14257,
28,
944,
13,
24442,
11,
4049,
6404,
28,
6404,
1362,
8,
198,
220,
220,
220,
220,
220,
220,
220,
649,
62,
2588,
263,
13,
42861,
62,
3605,
1370,
796,
657,
198,
220,
220,
220,
220,
220,
220,
220,
649,
62,
2588,
263,
13,
15414,
7,
8841,
8,
628,
220,
220,
220,
220,
220,
220,
220,
981,
6407,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
256,
796,
649,
62,
2588,
263,
13,
30001,
3419,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
611,
256,
318,
6045,
25,
2270,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
256,
13,
4033,
796,
256,
13,
2588,
1930,
532,
649,
62,
2588,
263,
13,
42861,
62,
3605,
1370,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
7800,
256,
628,
220,
220,
220,
1303,
796,
25609,
28,
9297,
56,
17210,
263,
20855,
36658,
28,
198,
220,
220,
220,
1303,
198,
220,
220,
220,
1303,
770,
2192,
815,
307,
2839,
475,
25,
198,
220,
220,
220,
1303,
220,
220,
532,
262,
30751,
4433,
1895,
284,
4600,
83,
482,
641,
63,
357,
28998,
484,
815,
307,
5447,
287,
257,
2368,
11,
4888,
20203,
8,
198,
220,
220,
220,
1303,
220,
220,
532,
1243,
588,
4600,
17201,
874,
63,
1244,
307,
257,
9829,
636,
286,
262,
1171,
7071,
13,
198,
220,
220,
220,
1303,
198,
220,
220,
220,
1303,
4377,
4919,
11,
340,
318,
21015,
291,
284,
1577,
617,
17182,
284,
8181,
27186,
351,
47226,
628,
220,
220,
220,
4187,
874,
796,
37250,
91,
3256,
29513,
3256,
705,
8,
3256,
705,
90,
3256,
705,
92,
3256,
44438,
3256,
705,
60,
3256,
705,
25,
3256,
705,
9,
3256,
46083,
3256,
705,
26,
20520,
198,
220,
220,
220,
220,
198,
220,
220,
220,
10395,
62,
10879,
796,
1391,
705,
15252,
10354,
705,
9864,
23680,
6,
1782,
628,
220,
220,
220,
16326,
796,
37250,
2389,
3256,
705,
9936,
53,
1503,
3256,
705,
26465,
3913,
3256,
705,
42,
16279,
38,
3256,
705,
31827,
20520,
1343,
10395,
62,
10879,
13,
27160,
3419,
628,
220,
220,
220,
256,
62,
26465,
3913,
796,
374,
6,
3784,
6,
198,
220,
220,
220,
256,
62,
42,
16279,
38,
796,
374,
6,
59,
9,
59,
9,
6,
198,
220,
220,
220,
256,
62,
31827,
796,
374,
6,
59,
30,
59,
8348,
198,
220,
220,
220,
256,
62,
46430,
796,
705,
3467,
83,
6,
628,
220,
220,
220,
825,
256,
62,
2389,
7,
944,
11,
256,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
374,
6,
93,
30,
58,
64,
12,
89,
32,
12,
57,
62,
7131,
64,
12,
89,
32,
12,
57,
15,
12,
24,
62,
60,
9,
6,
628,
220,
220,
220,
220,
220,
220,
220,
611,
256,
13,
8367,
58,
15,
60,
6624,
705,
93,
10354,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
256,
13,
4906,
796,
705,
9936,
53,
1503,
6,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
256,
13,
8367,
796,
256,
13,
8367,
58,
16,
47715,
198,
220,
220,
220,
220,
220,
220,
220,
1288,
361,
256,
13,
8367,
287,
2116,
13,
411,
8520,
62,
10879,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
256,
13,
4906,
796,
2116,
13,
411,
8520,
62,
10879,
58,
83,
13,
8367,
60,
198,
220,
220,
220,
220,
220,
220,
220,
2073,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
256,
13,
4906,
796,
705,
2389,
6,
628,
220,
220,
220,
220,
220,
220,
220,
1441,
256,
628,
220,
220,
220,
825,
256,
62,
3605,
1370,
7,
944,
11,
256,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
374,
6,
59,
77,
6,
198,
220,
220,
220,
220,
220,
220,
220,
256,
13,
2588,
263,
13,
2815,
23397,
15853,
352,
198,
220,
220,
220,
220,
220,
220,
220,
256,
13,
2588,
263,
13,
42861,
62,
3605,
1370,
796,
256,
13,
2588,
1930,
198,
198,
361,
11593,
3672,
834,
6624,
705,
834,
12417,
834,
10354,
198,
220,
220,
220,
18931,
13,
35487,
16934,
3419,
198,
220,
220,
220,
31191,
263,
796,
17210,
263,
7,
24442,
28,
17821,
8,
198,
220,
220,
220,
329,
11241,
287,
31191,
263,
13,
30001,
1096,
7,
17597,
13,
19282,
259,
13,
961,
3419,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
3601,
705,
33963,
1238,
82,
4,
82,
6,
4064,
357,
30001,
13,
8367,
11,
11241,
13,
4906,
8,
198
] | 2.119867 | 901 |
from output.models.nist_data.list_pkg.normalized_string.schema_instance.nistschema_sv_iv_list_normalized_string_length_5_xsd.nistschema_sv_iv_list_normalized_string_length_5 import NistschemaSvIvListNormalizedStringLength5
__all__ = [
"NistschemaSvIvListNormalizedStringLength5",
]
| [
6738,
5072,
13,
27530,
13,
77,
396,
62,
7890,
13,
4868,
62,
35339,
13,
11265,
1143,
62,
8841,
13,
15952,
2611,
62,
39098,
13,
77,
1023,
2395,
2611,
62,
21370,
62,
452,
62,
4868,
62,
11265,
1143,
62,
8841,
62,
13664,
62,
20,
62,
87,
21282,
13,
77,
1023,
2395,
2611,
62,
21370,
62,
452,
62,
4868,
62,
11265,
1143,
62,
8841,
62,
13664,
62,
20,
1330,
399,
1023,
2395,
2611,
50,
85,
45766,
8053,
26447,
1143,
10100,
24539,
20,
198,
198,
834,
439,
834,
796,
685,
198,
220,
220,
220,
366,
45,
1023,
2395,
2611,
50,
85,
45766,
8053,
26447,
1143,
10100,
24539,
20,
1600,
198,
60,
198
] | 2.633028 | 109 |
from __future__ import print_function
from orphics import maps,io,cosmology,catalogs
from pixell import enmap
import numpy as np
import os,sys
ifile = "paper/E-D56Clusters.fits"
#catalogs.convert_hilton_catalog_to_enplot_annotate_file('public_clusters.csv',ifile,radius=15,width=3,color='red')
catalogs.convert_hilton_catalog_to_enplot_annotate_file('paper/test_public_clusters.csv',ifile,radius=15,width=3,color='red')
| [
6738,
11593,
37443,
834,
1330,
3601,
62,
8818,
198,
6738,
393,
746,
873,
1330,
8739,
11,
952,
11,
6966,
29126,
11,
9246,
11794,
82,
198,
6738,
279,
844,
695,
1330,
551,
8899,
198,
11748,
299,
32152,
355,
45941,
198,
11748,
28686,
11,
17597,
198,
198,
361,
576,
796,
366,
20189,
14,
36,
12,
35,
3980,
2601,
13654,
13,
21013,
1,
198,
198,
2,
9246,
11794,
82,
13,
1102,
1851,
62,
71,
9044,
62,
9246,
11794,
62,
1462,
62,
268,
29487,
62,
34574,
378,
62,
7753,
10786,
11377,
62,
565,
13654,
13,
40664,
3256,
361,
576,
11,
42172,
28,
1314,
11,
10394,
28,
18,
11,
8043,
11639,
445,
11537,
198,
9246,
11794,
82,
13,
1102,
1851,
62,
71,
9044,
62,
9246,
11794,
62,
1462,
62,
268,
29487,
62,
34574,
378,
62,
7753,
10786,
20189,
14,
9288,
62,
11377,
62,
565,
13654,
13,
40664,
3256,
361,
576,
11,
42172,
28,
1314,
11,
10394,
28,
18,
11,
8043,
11639,
445,
11537,
628
] | 2.660377 | 159 |
import glfw
from glfw import gl
import numpy as np
def opengl_supported(major, minor):
'''Determines if opengl is supported for the version provided'''
assert glfw.core.init() != 0
version = (major, minor)
glfw.core.window_hint(glfw.CONTEXT_VERSION_MAJOR, major)
glfw.core.window_hint(glfw.CONTEXT_VERSION_MINOR, minor)
profile = glfw.OPENGL_ANY_PROFILE if version < (3, 2) else glfw.OPENGL_CORE_PROFILE
glfw.core.window_hint(glfw.OPENGL_PROFILE, profile)
# Setup forward compatibility if able
forward_compat = gl.FALSE if version < (3, 0) else gl.TRUE
glfw.core.window_hint(glfw.OPENGL_FORWARD_COMPAT, forward_compat)
# Keep the window invisible
glfw.core.window_hint(glfw.VISIBLE, gl.FALSE)
glfw.core.window_hint(glfw.FOCUSED, gl.FALSE)
win = glfw.create_window(title='test', width=1, height=1)
return win is not None
# TODO: Fill this out or automate it.
uniform_mapping = {
'vec1': gl.uniform_1f,
'vec2': gl.uniform_2f,
'vec3': gl.uniform_3f,
'vec4': gl.uniform_4f,
'mat4': gl.uniform_matrix_4fv,
}
| [
11748,
1278,
44482,
198,
6738,
1278,
44482,
1330,
1278,
198,
11748,
299,
32152,
355,
45941,
628,
198,
198,
4299,
1280,
4743,
62,
15999,
7,
22478,
11,
4159,
2599,
198,
220,
220,
220,
705,
7061,
35,
13221,
274,
611,
1280,
4743,
318,
4855,
329,
262,
2196,
2810,
7061,
6,
198,
220,
220,
220,
6818,
1278,
44482,
13,
7295,
13,
15003,
3419,
14512,
657,
198,
220,
220,
220,
2196,
796,
357,
22478,
11,
4159,
8,
198,
220,
220,
220,
1278,
44482,
13,
7295,
13,
17497,
62,
71,
600,
7,
70,
1652,
86,
13,
10943,
32541,
62,
43717,
62,
5673,
41,
1581,
11,
1688,
8,
198,
220,
220,
220,
1278,
44482,
13,
7295,
13,
17497,
62,
71,
600,
7,
70,
1652,
86,
13,
10943,
32541,
62,
43717,
62,
23678,
1581,
11,
4159,
8,
198,
220,
220,
220,
7034,
796,
1278,
44482,
13,
3185,
1677,
8763,
62,
31827,
62,
31190,
25664,
611,
2196,
1279,
357,
18,
11,
362,
8,
2073,
1278,
44482,
13,
3185,
1677,
8763,
62,
34,
6965,
62,
31190,
25664,
198,
220,
220,
220,
1278,
44482,
13,
7295,
13,
17497,
62,
71,
600,
7,
70,
1652,
86,
13,
3185,
1677,
8763,
62,
31190,
25664,
11,
7034,
8,
198,
220,
220,
220,
1303,
31122,
2651,
17764,
611,
1498,
198,
220,
220,
220,
2651,
62,
5589,
265,
796,
1278,
13,
37,
23719,
611,
2196,
1279,
357,
18,
11,
657,
8,
2073,
1278,
13,
5446,
8924,
198,
220,
220,
220,
1278,
44482,
13,
7295,
13,
17497,
62,
71,
600,
7,
70,
1652,
86,
13,
3185,
1677,
8763,
62,
13775,
39743,
62,
9858,
47,
1404,
11,
2651,
62,
5589,
265,
8,
198,
220,
220,
220,
1303,
220,
9175,
262,
4324,
14836,
198,
220,
220,
220,
1278,
44482,
13,
7295,
13,
17497,
62,
71,
600,
7,
70,
1652,
86,
13,
29817,
34563,
11,
1278,
13,
37,
23719,
8,
198,
220,
220,
220,
1278,
44482,
13,
7295,
13,
17497,
62,
71,
600,
7,
70,
1652,
86,
13,
37,
4503,
2937,
1961,
11,
1278,
13,
37,
23719,
8,
198,
220,
220,
220,
1592,
796,
1278,
44482,
13,
17953,
62,
17497,
7,
7839,
11639,
9288,
3256,
9647,
28,
16,
11,
6001,
28,
16,
8,
198,
220,
220,
220,
1441,
1592,
318,
407,
6045,
198,
198,
2,
16926,
46,
25,
220,
27845,
428,
503,
393,
43511,
340,
13,
198,
403,
6933,
62,
76,
5912,
796,
1391,
198,
220,
220,
220,
705,
35138,
16,
10354,
1278,
13,
403,
6933,
62,
16,
69,
11,
198,
220,
220,
220,
705,
35138,
17,
10354,
1278,
13,
403,
6933,
62,
17,
69,
11,
198,
220,
220,
220,
705,
35138,
18,
10354,
1278,
13,
403,
6933,
62,
18,
69,
11,
198,
220,
220,
220,
705,
35138,
19,
10354,
1278,
13,
403,
6933,
62,
19,
69,
11,
198,
220,
220,
220,
705,
6759,
19,
10354,
1278,
13,
403,
6933,
62,
6759,
8609,
62,
19,
69,
85,
11,
198,
92,
198
] | 2.307203 | 472 |
# Copyright 2014 The Chromium Authors. All rights reserved.
# Use of this source code is governed by a BSD-style license that can be
# found in the LICENSE file.
import sys
import os
import exceptions
import itertools
import re
def GetNinjaOutputDirectory(chrome_root):
"""Returns <chrome_root>/<output_dir>/(Release|Debug|<other>).
If either of the following environment variables are set, their
value is used to determine the output directory:
1. CHROMIUM_OUT_DIR environment variable.
2. GYP_GENERATOR_FLAGS environment variable output_dir property.
Otherwise, all directories starting with the word out are examined.
The configuration chosen is the one most recently generated/built.
"""
output_dirs = []
if ('CHROMIUM_OUT_DIR' in os.environ and
os.path.isdir(os.path.join(chrome_root, os.environ['CHROMIUM_OUT_DIR']))):
output_dirs = [os.environ['CHROMIUM_OUT_DIR']]
if not output_dirs:
generator_flags = os.getenv('GYP_GENERATOR_FLAGS', '').split(' ')
for flag in generator_flags:
name_value = flag.split('=', 1)
if (len(name_value) == 2 and name_value[0] == 'output_dir' and
os.path.isdir(os.path.join(chrome_root, name_value[1]))):
output_dirs = [name_value[1]]
if not output_dirs:
for f in os.listdir(chrome_root):
if re.match(r'out(\b|_)', f):
out = os.path.realpath(os.path.join(chrome_root, f))
if os.path.isdir(out):
output_dirs.append(os.path.relpath(out, start = chrome_root))
try:
return max(generate_paths(), key=approx_directory_mtime)
except ValueError:
raise exceptions.RuntimeError(
'Unable to find a valid ninja output directory.')
if __name__ == '__main__':
if len(sys.argv) != 2:
raise exceptions.RuntimeError('Expected a single path argument.')
print GetNinjaOutputDirectory(sys.argv[1])
| [
2,
15069,
1946,
383,
18255,
1505,
46665,
13,
1439,
2489,
10395,
13,
198,
2,
5765,
286,
428,
2723,
2438,
318,
21825,
416,
257,
347,
10305,
12,
7635,
5964,
326,
460,
307,
198,
2,
1043,
287,
262,
38559,
24290,
2393,
13,
628,
198,
11748,
25064,
198,
11748,
28686,
198,
11748,
13269,
198,
11748,
340,
861,
10141,
198,
11748,
302,
628,
198,
4299,
3497,
36091,
6592,
26410,
43055,
7,
46659,
62,
15763,
2599,
198,
220,
37227,
35561,
1279,
46659,
62,
15763,
29,
14,
27,
22915,
62,
15908,
29,
29006,
26362,
91,
27509,
91,
27,
847,
29,
737,
628,
220,
1002,
2035,
286,
262,
1708,
2858,
9633,
389,
900,
11,
511,
198,
220,
1988,
318,
973,
284,
5004,
262,
5072,
8619,
25,
198,
220,
220,
220,
352,
13,
32567,
2662,
41796,
62,
12425,
62,
34720,
2858,
7885,
13,
198,
220,
220,
220,
362,
13,
402,
48232,
62,
35353,
1137,
25633,
62,
38948,
50,
2858,
7885,
5072,
62,
15908,
3119,
13,
628,
220,
15323,
11,
477,
29196,
3599,
351,
262,
1573,
503,
389,
11068,
13,
628,
220,
383,
8398,
7147,
318,
262,
530,
749,
2904,
7560,
14,
18780,
13,
198,
220,
37227,
628,
220,
5072,
62,
15908,
82,
796,
17635,
198,
220,
611,
19203,
3398,
33676,
41796,
62,
12425,
62,
34720,
6,
287,
28686,
13,
268,
2268,
290,
198,
220,
220,
220,
220,
220,
28686,
13,
6978,
13,
9409,
343,
7,
418,
13,
6978,
13,
22179,
7,
46659,
62,
15763,
11,
28686,
13,
268,
2268,
17816,
3398,
33676,
41796,
62,
12425,
62,
34720,
20520,
4008,
2599,
198,
220,
220,
220,
5072,
62,
15908,
82,
796,
685,
418,
13,
268,
2268,
17816,
3398,
33676,
41796,
62,
12425,
62,
34720,
6,
11907,
198,
220,
611,
407,
5072,
62,
15908,
82,
25,
198,
220,
220,
220,
17301,
62,
33152,
796,
28686,
13,
1136,
24330,
10786,
31212,
47,
62,
35353,
1137,
25633,
62,
38948,
50,
3256,
10148,
737,
35312,
10786,
705,
8,
198,
220,
220,
220,
329,
6056,
287,
17301,
62,
33152,
25,
198,
220,
220,
220,
220,
220,
1438,
62,
8367,
796,
6056,
13,
35312,
10786,
28,
3256,
352,
8,
198,
220,
220,
220,
220,
220,
611,
357,
11925,
7,
3672,
62,
8367,
8,
6624,
362,
290,
1438,
62,
8367,
58,
15,
60,
6624,
705,
22915,
62,
15908,
6,
290,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
28686,
13,
6978,
13,
9409,
343,
7,
418,
13,
6978,
13,
22179,
7,
46659,
62,
15763,
11,
1438,
62,
8367,
58,
16,
60,
4008,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
5072,
62,
15908,
82,
796,
685,
3672,
62,
8367,
58,
16,
11907,
198,
220,
611,
407,
5072,
62,
15908,
82,
25,
198,
220,
220,
220,
329,
277,
287,
28686,
13,
4868,
15908,
7,
46659,
62,
15763,
2599,
198,
220,
220,
220,
220,
220,
611,
302,
13,
15699,
7,
81,
6,
448,
38016,
65,
91,
62,
8,
3256,
277,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
503,
796,
28686,
13,
6978,
13,
5305,
6978,
7,
418,
13,
6978,
13,
22179,
7,
46659,
62,
15763,
11,
277,
4008,
198,
220,
220,
220,
220,
220,
220,
220,
611,
28686,
13,
6978,
13,
9409,
343,
7,
448,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
5072,
62,
15908,
82,
13,
33295,
7,
418,
13,
6978,
13,
2411,
6978,
7,
448,
11,
923,
796,
32030,
62,
15763,
4008,
628,
220,
1949,
25,
198,
220,
220,
220,
1441,
3509,
7,
8612,
378,
62,
6978,
82,
22784,
1994,
28,
1324,
13907,
62,
34945,
62,
76,
2435,
8,
198,
220,
2845,
11052,
12331,
25,
198,
220,
220,
220,
5298,
13269,
13,
41006,
12331,
7,
198,
220,
220,
220,
220,
220,
705,
3118,
540,
284,
1064,
257,
4938,
37049,
5072,
8619,
2637,
8,
198,
198,
361,
11593,
3672,
834,
6624,
705,
834,
12417,
834,
10354,
198,
220,
611,
18896,
7,
17597,
13,
853,
85,
8,
14512,
362,
25,
198,
220,
220,
220,
5298,
13269,
13,
41006,
12331,
10786,
3109,
7254,
257,
2060,
3108,
4578,
2637,
8,
198,
220,
3601,
3497,
36091,
6592,
26410,
43055,
7,
17597,
13,
853,
85,
58,
16,
12962,
198
] | 2.757037 | 675 |
from tkinter import *
import PySimpleGUI as sg
window = Tk()
window.title("Kill Confirm Calculator")
global oppKilPer
promptLabel = Label(window, text="Select your Opponents Rival").grid(row=1, column=4)
promptLabel1 = Label(window, text="by clicking a Button").grid(row=2, column=4)
#Functions containing each characters different kill percent values
#calculation of final percent
#individual character buttons for users to choose
zetButton = Button(window, text="Zetterburn", command=zet)
zetButton.grid(row=2, column=3)
forsButton = Button(window, text="Forsburn", command=fors)
forsButton.grid(row=2, column=2)
claButton = Button(window, text="Clairen", command=cla)
claButton.grid(row=2, column=1)
orcButton = Button(window, text="Orcane", command=orc)
orcButton.grid(row=3, column=5)
etaButton = Button(window, text="Etalus", command=eta)
etaButton.grid(row=3, column=6)
ranButton = Button(window, text="Ranno", command=ran)
ranButton.grid(row=3, column=7)
wraButton = Button(window, text="Wrastor", command=wra)
wraButton.grid(row=2, column=5)
absaButton = Button(window, text="Absa", command=absa)
absaButton.grid(row=2, column=6)
ellButton = Button(window, text="Ellianna", command=ell)
ellButton.grid(row=2, column=7)
kraButton = Button(window, text="Kragg", command=kra)
kraButton.grid(row=3, column=3)
mayButton = Button(window, text="Maypul", command=may)
mayButton.grid(row=3, column=2)
sylButton = Button(window, text="Sylvanos", command=syl)
sylButton.grid(row=3, column=1)
oriButton = Button(window, text="Ori and Sein", command=ori)
oriButton.grid(row=4, column=3)
shoButton = Button(window, text="Shovel Knight", command=sho)
shoButton.grid(row=4, column=5)
#Entry widget for opponents percent
oppPercentLabel = Label(window, text="Enter your Opponents Percent").grid(row=6,column=4)
conOfPer = StringVar()
entPercent = Entry(window, width=20, textvariable=conOfPer).grid(row=7, column=4)
#result button that will display if the kill confirm was succesful
submitButton = Button(window, text="Result", command=calOppPer).grid(row=9, column=4)
window.mainloop()
| [
6738,
256,
74,
3849,
1330,
1635,
201,
198,
11748,
9485,
26437,
40156,
355,
264,
70,
201,
198,
17497,
796,
309,
74,
3419,
201,
198,
17497,
13,
7839,
7203,
27100,
7326,
2533,
43597,
4943,
201,
198,
201,
198,
20541,
1269,
42,
346,
5990,
201,
198,
201,
198,
16963,
457,
33986,
796,
36052,
7,
17497,
11,
2420,
2625,
17563,
534,
9385,
3906,
371,
2473,
11074,
25928,
7,
808,
28,
16,
11,
5721,
28,
19,
8,
201,
198,
16963,
457,
33986,
16,
796,
36052,
7,
17497,
11,
2420,
2625,
1525,
12264,
257,
20969,
11074,
25928,
7,
808,
28,
17,
11,
5721,
28,
19,
8,
201,
198,
201,
198,
2,
24629,
2733,
7268,
1123,
3435,
1180,
1494,
1411,
3815,
201,
198,
201,
198,
2,
9948,
14902,
286,
2457,
1411,
201,
198,
201,
198,
2,
43129,
2095,
12163,
329,
2985,
284,
3853,
220,
201,
198,
89,
316,
21864,
796,
20969,
7,
17497,
11,
2420,
2625,
57,
40088,
10899,
1600,
3141,
28,
89,
316,
8,
201,
198,
89,
316,
21864,
13,
25928,
7,
808,
28,
17,
11,
5721,
28,
18,
8,
201,
198,
69,
669,
21864,
796,
20969,
7,
17497,
11,
2420,
2625,
37,
669,
10899,
1600,
3141,
28,
69,
669,
8,
201,
198,
69,
669,
21864,
13,
25928,
7,
808,
28,
17,
11,
5721,
28,
17,
8,
201,
198,
565,
64,
21864,
796,
20969,
7,
17497,
11,
2420,
2625,
2601,
7626,
77,
1600,
3141,
28,
565,
64,
8,
201,
198,
565,
64,
21864,
13,
25928,
7,
808,
28,
17,
11,
5721,
28,
16,
8,
201,
198,
24449,
21864,
796,
20969,
7,
17497,
11,
2420,
2625,
5574,
66,
1531,
1600,
3141,
28,
24449,
8,
201,
198,
24449,
21864,
13,
25928,
7,
808,
28,
18,
11,
5721,
28,
20,
8,
201,
198,
17167,
21864,
796,
20969,
7,
17497,
11,
2420,
2625,
36,
39240,
385,
1600,
3141,
28,
17167,
8,
201,
198,
17167,
21864,
13,
25928,
7,
808,
28,
18,
11,
5721,
28,
21,
8,
201,
198,
2596,
21864,
796,
20969,
7,
17497,
11,
2420,
2625,
49,
1236,
78,
1600,
3141,
28,
2596,
8,
201,
198,
2596,
21864,
13,
25928,
7,
808,
28,
18,
11,
5721,
28,
22,
8,
201,
198,
29988,
21864,
796,
20969,
7,
17497,
11,
2420,
2625,
54,
5685,
273,
1600,
3141,
28,
29988,
8,
201,
198,
29988,
21864,
13,
25928,
7,
808,
28,
17,
11,
5721,
28,
20,
8,
201,
198,
8937,
64,
21864,
796,
20969,
7,
17497,
11,
2420,
2625,
24849,
64,
1600,
3141,
28,
8937,
64,
8,
201,
198,
8937,
64,
21864,
13,
25928,
7,
808,
28,
17,
11,
5721,
28,
21,
8,
201,
198,
695,
21864,
796,
20969,
7,
17497,
11,
2420,
2625,
30639,
666,
2616,
1600,
3141,
28,
695,
8,
201,
198,
695,
21864,
13,
25928,
7,
808,
28,
17,
11,
5721,
28,
22,
8,
201,
198,
74,
430,
21864,
796,
20969,
7,
17497,
11,
2420,
2625,
42,
81,
9460,
1600,
3141,
28,
74,
430,
8,
201,
198,
74,
430,
21864,
13,
25928,
7,
808,
28,
18,
11,
5721,
28,
18,
8,
201,
198,
11261,
21864,
796,
20969,
7,
17497,
11,
2420,
2625,
6747,
79,
377,
1600,
3141,
28,
11261,
8,
201,
198,
11261,
21864,
13,
25928,
7,
808,
28,
18,
11,
5721,
28,
17,
8,
201,
198,
1837,
75,
21864,
796,
20969,
7,
17497,
11,
2420,
2625,
50,
2645,
10438,
418,
1600,
3141,
28,
1837,
75,
8,
201,
198,
1837,
75,
21864,
13,
25928,
7,
808,
28,
18,
11,
5721,
28,
16,
8,
201,
198,
10145,
21864,
796,
20969,
7,
17497,
11,
2420,
2625,
46,
380,
290,
1001,
259,
1600,
3141,
28,
10145,
8,
201,
198,
10145,
21864,
13,
25928,
7,
808,
28,
19,
11,
5721,
28,
18,
8,
201,
198,
1477,
78,
21864,
796,
20969,
7,
17497,
11,
2420,
2625,
2484,
78,
626,
6700,
1600,
3141,
28,
1477,
78,
8,
201,
198,
1477,
78,
21864,
13,
25928,
7,
808,
28,
19,
11,
5721,
28,
20,
8,
201,
198,
2,
30150,
26295,
329,
7691,
1411,
220,
201,
198,
10365,
31905,
33986,
796,
36052,
7,
17497,
11,
2420,
2625,
17469,
534,
9385,
3906,
22512,
11074,
25928,
7,
808,
28,
21,
11,
28665,
28,
19,
8,
201,
198,
1102,
5189,
5990,
796,
10903,
19852,
3419,
201,
198,
298,
31905,
796,
21617,
7,
17497,
11,
9647,
28,
1238,
11,
2420,
45286,
28,
1102,
5189,
5990,
737,
25928,
7,
808,
28,
22,
11,
5721,
28,
19,
8,
201,
198,
220,
220,
220,
201,
198,
201,
198,
2,
20274,
4936,
326,
481,
3359,
611,
262,
1494,
6216,
373,
17458,
274,
913,
201,
198,
46002,
21864,
796,
20969,
7,
17497,
11,
2420,
2625,
23004,
1600,
3141,
28,
9948,
27524,
5990,
737,
25928,
7,
808,
28,
24,
11,
5721,
28,
19,
8,
201,
198,
201,
198,
17497,
13,
12417,
26268,
3419,
201,
198
] | 2.760618 | 777 |
import warnings
warnings.simplefilter(action='ignore', category=FutureWarning)
from Bio import SeqIO
from Bio.Seq import Seq
import numpy as np
import random
import itertools
from textwrap import wrap
from collections import defaultdict
if __name__ == '__main__':
# s = Seq('TTATGACCC')
# encoder = KMerEncoder(2, 50, 'constant')
# e = encoder.encode(s)
# print(s)
# print(encoder.char_to_int)
# print(e)
# encoder = KMerEncoder(3, 50, 'random')
# e = encoder.encode(s)
# print(s)
# print(encoder.char_to_int)
# print(e)
# encoder = OneHotEncoder(2, 50, 'constant')
# e = encoder.encode(s)
# print(s)
# print(encoder.char_to_int)
# print(e)
# from pprint import pprint
# e = RandomEncoder('../datasets/fixture.fasta')
# s = e.encode(2, 2)
# print(len(s))
# print(s)
# print()
# pprint(e.archieve)
from pprint import pprint
e = NoisyEncoder('../datasets/fixture.fasta')
s = e.encode(10)
pprint(s)
| [
198,
11748,
14601,
198,
40539,
654,
13,
36439,
24455,
7,
2673,
11639,
46430,
3256,
6536,
28,
29783,
20361,
8,
198,
198,
6738,
16024,
1330,
1001,
80,
9399,
198,
6738,
16024,
13,
4653,
80,
1330,
1001,
80,
198,
11748,
299,
32152,
355,
45941,
198,
11748,
4738,
198,
11748,
340,
861,
10141,
198,
6738,
2420,
37150,
1330,
14441,
198,
6738,
17268,
1330,
4277,
11600,
198,
220,
220,
220,
220,
198,
220,
220,
220,
220,
198,
220,
220,
220,
220,
198,
220,
220,
220,
220,
198,
220,
220,
220,
220,
220,
220,
220,
220,
628,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
628,
198,
198,
361,
11593,
3672,
834,
6624,
705,
834,
12417,
834,
10354,
198,
220,
220,
220,
1303,
264,
796,
1001,
80,
10786,
15751,
1404,
38,
2246,
4093,
11537,
198,
220,
220,
220,
1303,
2207,
12342,
796,
509,
13102,
27195,
12342,
7,
17,
11,
2026,
11,
705,
9979,
415,
11537,
198,
220,
220,
220,
1303,
304,
796,
2207,
12342,
13,
268,
8189,
7,
82,
8,
198,
220,
220,
220,
1303,
3601,
7,
82,
8,
198,
220,
220,
220,
1303,
3601,
7,
12685,
12342,
13,
10641,
62,
1462,
62,
600,
8,
198,
220,
220,
220,
1303,
3601,
7,
68,
8,
198,
220,
220,
220,
220,
198,
220,
220,
220,
1303,
2207,
12342,
796,
509,
13102,
27195,
12342,
7,
18,
11,
2026,
11,
705,
25120,
11537,
198,
220,
220,
220,
1303,
304,
796,
2207,
12342,
13,
268,
8189,
7,
82,
8,
198,
220,
220,
220,
1303,
3601,
7,
82,
8,
198,
220,
220,
220,
1303,
3601,
7,
12685,
12342,
13,
10641,
62,
1462,
62,
600,
8,
198,
220,
220,
220,
1303,
3601,
7,
68,
8,
198,
220,
220,
220,
220,
198,
220,
220,
220,
1303,
2207,
12342,
796,
1881,
21352,
27195,
12342,
7,
17,
11,
2026,
11,
705,
9979,
415,
11537,
198,
220,
220,
220,
1303,
304,
796,
2207,
12342,
13,
268,
8189,
7,
82,
8,
198,
220,
220,
220,
1303,
3601,
7,
82,
8,
198,
220,
220,
220,
1303,
3601,
7,
12685,
12342,
13,
10641,
62,
1462,
62,
600,
8,
198,
220,
220,
220,
1303,
3601,
7,
68,
8,
198,
220,
220,
220,
220,
198,
220,
220,
220,
1303,
422,
279,
4798,
1330,
279,
4798,
198,
220,
220,
220,
1303,
304,
796,
14534,
27195,
12342,
10786,
40720,
19608,
292,
1039,
14,
69,
9602,
13,
7217,
64,
11537,
198,
220,
220,
220,
1303,
264,
796,
304,
13,
268,
8189,
7,
17,
11,
362,
8,
198,
220,
220,
220,
1303,
3601,
7,
11925,
7,
82,
4008,
198,
220,
220,
220,
1303,
3601,
7,
82,
8,
198,
220,
220,
220,
1303,
3601,
3419,
198,
220,
220,
220,
1303,
279,
4798,
7,
68,
13,
998,
12311,
8,
198,
220,
220,
220,
220,
198,
220,
220,
220,
220,
198,
220,
220,
220,
422,
279,
4798,
1330,
279,
4798,
198,
220,
220,
220,
304,
796,
1400,
13560,
27195,
12342,
10786,
40720,
19608,
292,
1039,
14,
69,
9602,
13,
7217,
64,
11537,
198,
220,
220,
220,
264,
796,
304,
13,
268,
8189,
7,
940,
8,
628,
220,
220,
220,
279,
4798,
7,
82,
8,
198,
220,
220,
220,
220
] | 2.092486 | 519 |
import requests
from utils.time_utils import get_target_date_as_timestamp
if __name__ == "__main__":
main()
| [
11748,
7007,
198,
198,
6738,
3384,
4487,
13,
2435,
62,
26791,
1330,
651,
62,
16793,
62,
4475,
62,
292,
62,
16514,
27823,
628,
628,
628,
628,
198,
361,
11593,
3672,
834,
6624,
366,
834,
12417,
834,
1298,
198,
220,
220,
220,
1388,
3419,
198
] | 2.75 | 44 |
from __future__ import print_function
import sys
import traceback
import inspect
import types
from ConfigParser import ConfigParser
import os
from functools import partial
from pox.boot import _do_imports
from pox.core import core
from pox.lib.revent.revent import EventHalt
log = core.getLogger("ComponentLauncher")
CONFIG = ["debugger/component_launcher/component_config/",
"ext/debugger/component_launcher/component_config/",
"pox/ext/debugger/component_launcher/component_config/",
"adapters/pox/ext/debugger/component_launcher/component_config/"]
HIGHEST_PRIORITY = 1000000
# This function is stolen from pox/boot.py
| [
6738,
11593,
37443,
834,
1330,
3601,
62,
8818,
198,
198,
11748,
25064,
198,
11748,
12854,
1891,
198,
11748,
10104,
198,
11748,
3858,
198,
6738,
17056,
46677,
1330,
17056,
46677,
198,
11748,
28686,
198,
6738,
1257,
310,
10141,
1330,
13027,
198,
198,
6738,
745,
87,
13,
18769,
1330,
4808,
4598,
62,
320,
3742,
198,
6738,
745,
87,
13,
7295,
1330,
4755,
198,
6738,
745,
87,
13,
8019,
13,
260,
1151,
13,
260,
1151,
1330,
8558,
39,
2501,
628,
198,
6404,
796,
4755,
13,
1136,
11187,
1362,
7203,
21950,
46182,
2044,
4943,
198,
10943,
16254,
796,
14631,
24442,
1362,
14,
42895,
62,
38722,
2044,
14,
42895,
62,
11250,
14,
1600,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
366,
2302,
14,
24442,
1362,
14,
42895,
62,
38722,
2044,
14,
42895,
62,
11250,
14,
1600,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
366,
42557,
14,
2302,
14,
24442,
1362,
14,
42895,
62,
38722,
2044,
14,
42895,
62,
11250,
14,
1600,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
366,
324,
12126,
14,
42557,
14,
2302,
14,
24442,
1362,
14,
42895,
62,
38722,
2044,
14,
42895,
62,
11250,
14,
8973,
198,
39,
18060,
6465,
62,
4805,
41254,
9050,
796,
1802,
2388,
628,
628,
198,
2,
770,
2163,
318,
9909,
422,
745,
87,
14,
18769,
13,
9078,
628
] | 3.004545 | 220 |
from django.views.generic.base import RedirectView
from rest_framework.generics import RetrieveAPIView
from rest_framework.settings import api_settings
from wagtail.core.models import Page
from wagtail.core.views import serve as serve_page
from wagtail.documents.views.serve import serve as serve_doc
from wagtail.images.views.serve import ServeView, generate_signature
from wagtailnest.utils import (get_image_filter_spec, get_root_relative_url,
import_setting)
_permissions = {
name: import_setting(
'{}_PERMISSION_CLASSES'.format(name),
api_settings.DEFAULT_PERMISSION_CLASSES)
for name in ['PAGE', 'DOCUMENT', 'IMAGE']
}
class DraftRedirectView(RedirectView):
"""View that redirects to the correct URL for a draft."""
# pylint: disable=unused-argument
class RevisionRedirectView(RedirectView):
"""View that redirects to the correct URL for a revision."""
# pylint: disable=unused-argument
class PageServeView(RetrieveAPIView):
"""View which serves a rendered page."""
permission_classes = _permissions['PAGE']
# pylint: disable=no-self-use,arguments-differ
class DocumentServeView(RetrieveAPIView):
"""View which serves a document."""
permission_classes = _permissions['DOCUMENT']
# pylint: disable=no-self-use,arguments-differ
class ImageServeView(RetrieveAPIView):
"""View which serves an image."""
permission_classes = _permissions['IMAGE']
| [
6738,
42625,
14208,
13,
33571,
13,
41357,
13,
8692,
1330,
2297,
1060,
7680,
198,
6738,
1334,
62,
30604,
13,
8612,
873,
1330,
4990,
30227,
2969,
3824,
769,
198,
6738,
1334,
62,
30604,
13,
33692,
1330,
40391,
62,
33692,
198,
6738,
266,
363,
13199,
13,
7295,
13,
27530,
1330,
7873,
198,
6738,
266,
363,
13199,
13,
7295,
13,
33571,
1330,
4691,
355,
4691,
62,
7700,
198,
6738,
266,
363,
13199,
13,
15390,
2886,
13,
33571,
13,
2655,
303,
1330,
4691,
355,
4691,
62,
15390,
198,
6738,
266,
363,
13199,
13,
17566,
13,
33571,
13,
2655,
303,
1330,
35557,
7680,
11,
7716,
62,
12683,
1300,
198,
198,
6738,
266,
363,
13199,
77,
395,
13,
26791,
1330,
357,
1136,
62,
9060,
62,
24455,
62,
16684,
11,
651,
62,
15763,
62,
43762,
62,
6371,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1330,
62,
33990,
8,
198,
198,
62,
525,
8481,
796,
1391,
198,
220,
220,
220,
1438,
25,
1330,
62,
33990,
7,
198,
220,
220,
220,
220,
220,
220,
220,
705,
90,
92,
62,
18973,
44,
40373,
62,
31631,
1546,
4458,
18982,
7,
3672,
828,
198,
220,
220,
220,
220,
220,
220,
220,
40391,
62,
33692,
13,
7206,
38865,
62,
18973,
44,
40373,
62,
31631,
1546,
8,
198,
220,
220,
220,
329,
1438,
287,
37250,
4537,
8264,
3256,
705,
38715,
5883,
3525,
3256,
705,
3955,
11879,
20520,
198,
92,
628,
198,
4871,
13650,
7738,
1060,
7680,
7,
7738,
1060,
7680,
2599,
198,
220,
220,
220,
37227,
7680,
326,
18941,
82,
284,
262,
3376,
10289,
329,
257,
4538,
526,
15931,
628,
220,
220,
220,
1303,
279,
2645,
600,
25,
15560,
28,
403,
1484,
12,
49140,
628,
198,
4871,
46604,
7738,
1060,
7680,
7,
7738,
1060,
7680,
2599,
198,
220,
220,
220,
37227,
7680,
326,
18941,
82,
284,
262,
3376,
10289,
329,
257,
18440,
526,
15931,
628,
220,
220,
220,
1303,
279,
2645,
600,
25,
15560,
28,
403,
1484,
12,
49140,
628,
198,
4871,
7873,
50,
3760,
7680,
7,
9781,
30227,
2969,
3824,
769,
2599,
198,
220,
220,
220,
37227,
7680,
543,
9179,
257,
15111,
2443,
526,
15931,
628,
220,
220,
220,
7170,
62,
37724,
796,
4808,
525,
8481,
17816,
4537,
8264,
20520,
628,
220,
220,
220,
1303,
279,
2645,
600,
25,
15560,
28,
3919,
12,
944,
12,
1904,
11,
853,
2886,
12,
26069,
263,
628,
198,
4871,
16854,
50,
3760,
7680,
7,
9781,
30227,
2969,
3824,
769,
2599,
198,
220,
220,
220,
37227,
7680,
543,
9179,
257,
3188,
526,
15931,
628,
220,
220,
220,
7170,
62,
37724,
796,
4808,
525,
8481,
17816,
38715,
5883,
3525,
20520,
628,
220,
220,
220,
1303,
279,
2645,
600,
25,
15560,
28,
3919,
12,
944,
12,
1904,
11,
853,
2886,
12,
26069,
263,
628,
198,
4871,
7412,
50,
3760,
7680,
7,
9781,
30227,
2969,
3824,
769,
2599,
198,
220,
220,
220,
37227,
7680,
543,
9179,
281,
2939,
526,
15931,
628,
220,
220,
220,
7170,
62,
37724,
796,
4808,
525,
8481,
17816,
3955,
11879,
20520,
198
] | 2.882353 | 510 |
__source__ = 'https://leetcode.com/problems/cheapest-flights-within-k-stops/'
# Time: O()
# Space: O()
#
# Description: Leetcode # 787. Cheapest Flights Within K Stops
#
# There are n cities connected by m flights.
# Each fight starts from city u and arrives at v with a price w.
#
# Now given all the cities and flights,
# together with starting city src and the destination dst,
# your task is to find the cheapest price from src to dst with up to k stops.
# If there is no such route, output -1.
#
# Example 1:
# Input:
# n = 3, edges = [[0,1,100],[1,2,100],[0,2,500]]
# src = 0, dst = 2, k = 1
# Output: 200
# Explanation:
# The graph looks like this:
#
#
# The cheapest price from city 0 to city 2 with at most 1 stop costs 200, as marked red in the picture.
# Example 2:
# Input:
# n = 3, edges = [[0,1,100],[1,2,100],[0,2,500]]
# src = 0, dst = 2, k = 0
# Output: 500
# Explanation:
# The graph looks like this:
#
#
# The cheapest price from city 0 to city 2 with at most 0 stop costs 500, as marked blue in the picture.
# Note:
#
# The number of nodes n will be in range [1, 100], with nodes labeled from 0 to n - 1.
# The size of flights will be in range [0, n * (n - 1) / 2].
# The format of each flight will be (src, dst, price).
# The price of each flight will be in the range [1, 10000].
# k is in the range of [0, n - 1].
# There will not be any duplicated flights or self cycles.
#
import unittest
import collections
# 73,45% 44ms
from heapq import *
#96ms 22.03%
if __name__ == '__main__':
unittest.main()
Java = '''
# Thought: https://leetcode.com/problems/cheapest-flights-within-k-stops/solution/
# Approach #1: Maintain Cheapest To Target [Accepted]
# Complexity Analysis
# Time Complexity: O(E * K), where E is the length of flights.
# Space Complexity: O(n), the space used to store dis and pre.
# 6ms 100%
class Solution {
public int findCheapestPrice(int n, int[][] flights, int src, int dst, int K) {
int[][] dist = new int[2][n];
int INF = Integer.MAX_VALUE / 2;
Arrays.fill(dist[0], INF);
Arrays.fill(dist[1], INF);
dist[0][src] = dist[1][src] = 0;
for (int i = 0; i <= K; ++i)
for (int[] edge: flights)
dist[i&1][edge[1]] = Math.min(dist[i&1][edge[1]], dist[~i&1][edge[0]] + edge[2]);
return dist[K&1][dst] < INF ? dist[K&1][dst] : -1;
}
}
#
# Approach #2: Dijkstra's [Accepted]
# Complexity Analysis
# Time Complexity: O(E+nlogn), where E is the total number of flights.
# Space Complexity: O(n), the size of the heap.
#
# 4ms 100%
class Solution {
private class City implements Comparable<City>{
int id;
int costFromSrc;
int stopFromSrc;
public City(int id, int costFromSrc, int stopFromSrc){
this.id = id;
this.costFromSrc = costFromSrc;
this.stopFromSrc = stopFromSrc;
}
public boolean equals(City c){
if (c instanceof City) return this.id == c.id;
return false;
}
public int compareTo(City c){
return this.costFromSrc - c.costFromSrc;
}
}
public int findCheapestPrice(int n, int[][] flights, int src, int dst, int K) {
int[][] srcToDst = new int[n][n];
for (int i = 0; i < flights.length; i++) {
srcToDst[flights[i][0]][flights[i][1]] = flights[i][2];
}
PriorityQueue<City> minHeap = new PriorityQueue();
minHeap.offer(new City(src,0,0));
int[] cost = new int[n];
Arrays.fill(cost, Integer.MAX_VALUE);
cost[src] = 0;
int[] stop = new int[n];
Arrays.fill(stop, Integer.MAX_VALUE);
stop[src] = 0;
while(!minHeap.isEmpty()){
City curCity = minHeap.poll();
if (curCity.id == dst) return curCity.costFromSrc;
if (curCity.stopFromSrc == K + 1) continue;
int[] nexts = srcToDst[curCity.id];
for (int i = 0; i < n; i++) {
if (nexts[i] != 0) {
int newCost = curCity.costFromSrc + nexts[i];
int newStop = curCity.stopFromSrc + 1;
if (newCost < cost[i]) {
minHeap.offer(new City(i, newCost, newStop));
cost[i] = newCost;
} else if (newStop < stop[i]){
minHeap.offer(new City(i, newCost, newStop));
stop[i] = newStop;
}
}
}
}
return cost[dst] == Integer.MAX_VALUE? -1:cost[dst];
}
}
''' | [
834,
10459,
834,
796,
705,
5450,
1378,
293,
316,
8189,
13,
785,
14,
1676,
22143,
14,
2395,
35746,
12,
2704,
2337,
12,
33479,
12,
74,
12,
301,
2840,
14,
6,
198,
2,
3862,
25,
220,
440,
3419,
198,
2,
4687,
25,
440,
3419,
198,
2,
198,
2,
12489,
25,
1004,
316,
8189,
1303,
767,
5774,
13,
2580,
35746,
1610,
2337,
12511,
509,
520,
2840,
198,
2,
198,
2,
1318,
389,
299,
4736,
5884,
416,
285,
13956,
13,
198,
2,
5501,
1907,
4940,
422,
1748,
334,
290,
14443,
379,
410,
351,
257,
2756,
266,
13,
198,
2,
198,
2,
2735,
1813,
477,
262,
4736,
290,
13956,
11,
198,
2,
1978,
351,
3599,
1748,
12351,
290,
262,
10965,
29636,
11,
198,
2,
534,
4876,
318,
284,
1064,
262,
28918,
2756,
422,
12351,
284,
29636,
351,
510,
284,
479,
9911,
13,
198,
2,
1002,
612,
318,
645,
884,
6339,
11,
5072,
532,
16,
13,
198,
2,
198,
2,
17934,
352,
25,
198,
2,
23412,
25,
198,
2,
299,
796,
513,
11,
13015,
796,
16410,
15,
11,
16,
11,
3064,
38430,
16,
11,
17,
11,
3064,
38430,
15,
11,
17,
11,
4059,
11907,
198,
2,
12351,
796,
657,
11,
29636,
796,
362,
11,
479,
796,
352,
198,
2,
25235,
25,
939,
198,
2,
50125,
341,
25,
198,
2,
383,
4823,
3073,
588,
428,
25,
198,
2,
198,
2,
198,
2,
383,
28918,
2756,
422,
1748,
657,
284,
1748,
362,
351,
379,
749,
352,
2245,
3484,
939,
11,
355,
7498,
2266,
287,
262,
4286,
13,
198,
2,
17934,
362,
25,
198,
2,
23412,
25,
198,
2,
299,
796,
513,
11,
13015,
796,
16410,
15,
11,
16,
11,
3064,
38430,
16,
11,
17,
11,
3064,
38430,
15,
11,
17,
11,
4059,
11907,
198,
2,
12351,
796,
657,
11,
29636,
796,
362,
11,
479,
796,
657,
198,
2,
25235,
25,
5323,
198,
2,
50125,
341,
25,
198,
2,
383,
4823,
3073,
588,
428,
25,
198,
2,
198,
2,
198,
2,
383,
28918,
2756,
422,
1748,
657,
284,
1748,
362,
351,
379,
749,
657,
2245,
3484,
5323,
11,
355,
7498,
4171,
287,
262,
4286,
13,
198,
2,
5740,
25,
198,
2,
198,
2,
383,
1271,
286,
13760,
299,
481,
307,
287,
2837,
685,
16,
11,
1802,
4357,
351,
13760,
15494,
422,
657,
284,
299,
532,
352,
13,
198,
2,
383,
2546,
286,
13956,
481,
307,
287,
2837,
685,
15,
11,
299,
1635,
357,
77,
532,
352,
8,
1220,
362,
4083,
198,
2,
383,
5794,
286,
1123,
5474,
481,
307,
357,
10677,
11,
29636,
11,
2756,
737,
198,
2,
383,
2756,
286,
1123,
5474,
481,
307,
287,
262,
2837,
685,
16,
11,
33028,
4083,
198,
2,
479,
318,
287,
262,
2837,
286,
685,
15,
11,
299,
532,
352,
4083,
198,
2,
1318,
481,
407,
307,
597,
14184,
3474,
13956,
393,
2116,
16006,
13,
198,
2,
198,
11748,
555,
715,
395,
198,
11748,
17268,
198,
2,
8854,
11,
2231,
4,
5846,
907,
198,
6738,
24575,
80,
1330,
1635,
198,
198,
2,
4846,
907,
2534,
13,
3070,
4,
628,
198,
361,
11593,
3672,
834,
6624,
705,
834,
12417,
834,
10354,
198,
220,
220,
220,
555,
715,
395,
13,
12417,
3419,
198,
198,
29584,
796,
705,
7061,
198,
2,
27522,
25,
3740,
1378,
293,
316,
8189,
13,
785,
14,
1676,
22143,
14,
2395,
35746,
12,
2704,
2337,
12,
33479,
12,
74,
12,
301,
2840,
14,
82,
2122,
14,
198,
2,
38066,
1303,
16,
25,
337,
32725,
2580,
35746,
1675,
12744,
685,
38855,
276,
60,
198,
2,
19157,
414,
14691,
198,
2,
3862,
19157,
414,
25,
440,
7,
36,
1635,
509,
828,
810,
412,
318,
262,
4129,
286,
13956,
13,
198,
2,
4687,
19157,
414,
25,
440,
7,
77,
828,
262,
2272,
973,
284,
3650,
595,
290,
662,
13,
198,
198,
2,
718,
907,
1802,
4,
198,
4871,
28186,
1391,
198,
220,
220,
220,
1171,
493,
1064,
7376,
35746,
18124,
7,
600,
299,
11,
493,
58,
7131,
60,
13956,
11,
493,
12351,
11,
493,
29636,
11,
493,
509,
8,
1391,
198,
220,
220,
220,
220,
220,
220,
220,
493,
58,
7131,
60,
1233,
796,
649,
493,
58,
17,
7131,
77,
11208,
198,
220,
220,
220,
220,
220,
220,
220,
493,
45594,
796,
34142,
13,
22921,
62,
39488,
1220,
362,
26,
198,
220,
220,
220,
220,
220,
220,
220,
943,
20477,
13,
20797,
7,
17080,
58,
15,
4357,
45594,
1776,
198,
220,
220,
220,
220,
220,
220,
220,
943,
20477,
13,
20797,
7,
17080,
58,
16,
4357,
45594,
1776,
198,
220,
220,
220,
220,
220,
220,
220,
1233,
58,
15,
7131,
10677,
60,
796,
1233,
58,
16,
7131,
10677,
60,
796,
657,
26,
628,
220,
220,
220,
220,
220,
220,
220,
329,
357,
600,
1312,
796,
657,
26,
1312,
19841,
509,
26,
19969,
72,
8,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
329,
357,
600,
21737,
5743,
25,
13956,
8,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1233,
58,
72,
5,
16,
7131,
14907,
58,
16,
11907,
796,
16320,
13,
1084,
7,
17080,
58,
72,
5,
16,
7131,
14907,
58,
16,
60,
4357,
1233,
58,
93,
72,
5,
16,
7131,
14907,
58,
15,
11907,
1343,
5743,
58,
17,
36563,
628,
220,
220,
220,
220,
220,
220,
220,
1441,
1233,
58,
42,
5,
16,
7131,
67,
301,
60,
1279,
45594,
5633,
1233,
58,
42,
5,
16,
7131,
67,
301,
60,
1058,
532,
16,
26,
198,
220,
220,
220,
1782,
198,
92,
198,
198,
2,
198,
2,
38066,
1303,
17,
25,
360,
45961,
12044,
338,
685,
38855,
276,
60,
198,
2,
19157,
414,
14691,
198,
2,
3862,
19157,
414,
25,
440,
7,
36,
10,
21283,
2360,
828,
810,
412,
318,
262,
2472,
1271,
286,
13956,
13,
198,
2,
4687,
19157,
414,
25,
440,
7,
77,
828,
262,
2546,
286,
262,
24575,
13,
198,
2,
198,
198,
2,
604,
907,
1802,
4,
198,
4871,
28186,
1391,
198,
220,
220,
220,
2839,
1398,
2254,
23986,
22565,
540,
27,
14941,
29,
90,
198,
220,
220,
220,
220,
220,
220,
220,
493,
4686,
26,
198,
220,
220,
220,
220,
220,
220,
220,
493,
1575,
4863,
50,
6015,
26,
198,
220,
220,
220,
220,
220,
220,
220,
493,
2245,
4863,
50,
6015,
26,
628,
220,
220,
220,
220,
220,
220,
220,
1171,
2254,
7,
600,
4686,
11,
493,
1575,
4863,
50,
6015,
11,
493,
2245,
4863,
50,
6015,
19953,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
428,
13,
312,
796,
4686,
26,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
428,
13,
15805,
4863,
50,
6015,
796,
1575,
4863,
50,
6015,
26,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
428,
13,
11338,
4863,
50,
6015,
796,
2245,
4863,
50,
6015,
26,
198,
220,
220,
220,
220,
220,
220,
220,
1782,
628,
220,
220,
220,
220,
220,
220,
220,
1171,
25131,
21767,
7,
14941,
269,
19953,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
611,
357,
66,
4554,
1659,
2254,
8,
1441,
428,
13,
312,
6624,
269,
13,
312,
26,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1441,
3991,
26,
198,
220,
220,
220,
220,
220,
220,
220,
1782,
628,
220,
220,
220,
220,
220,
220,
220,
1171,
493,
8996,
2514,
7,
14941,
269,
19953,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1441,
428,
13,
15805,
4863,
50,
6015,
532,
269,
13,
15805,
4863,
50,
6015,
26,
198,
220,
220,
220,
220,
220,
220,
220,
1782,
198,
220,
220,
220,
1782,
628,
220,
220,
220,
1171,
493,
1064,
7376,
35746,
18124,
7,
600,
299,
11,
493,
58,
7131,
60,
13956,
11,
493,
12351,
11,
493,
29636,
11,
493,
509,
8,
1391,
198,
220,
220,
220,
220,
220,
220,
220,
493,
58,
7131,
60,
12351,
2514,
35,
301,
796,
649,
493,
58,
77,
7131,
77,
11208,
198,
220,
220,
220,
220,
220,
220,
220,
329,
357,
600,
1312,
796,
657,
26,
1312,
1279,
13956,
13,
13664,
26,
1312,
29577,
1391,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
12351,
2514,
35,
301,
58,
2704,
2337,
58,
72,
7131,
15,
60,
7131,
2704,
2337,
58,
72,
7131,
16,
11907,
796,
13956,
58,
72,
7131,
17,
11208,
198,
220,
220,
220,
220,
220,
220,
220,
1782,
628,
220,
220,
220,
220,
220,
220,
220,
34416,
34991,
27,
14941,
29,
949,
1544,
499,
796,
649,
34416,
34991,
9783,
198,
220,
220,
220,
220,
220,
220,
220,
949,
1544,
499,
13,
47895,
7,
3605,
2254,
7,
10677,
11,
15,
11,
15,
18125,
628,
220,
220,
220,
220,
220,
220,
220,
493,
21737,
1575,
796,
649,
493,
58,
77,
11208,
198,
220,
220,
220,
220,
220,
220,
220,
943,
20477,
13,
20797,
7,
15805,
11,
34142,
13,
22921,
62,
39488,
1776,
198,
220,
220,
220,
220,
220,
220,
220,
1575,
58,
10677,
60,
796,
657,
26,
198,
220,
220,
220,
220,
220,
220,
220,
493,
21737,
2245,
796,
649,
493,
58,
77,
11208,
198,
220,
220,
220,
220,
220,
220,
220,
943,
20477,
13,
20797,
7,
11338,
11,
34142,
13,
22921,
62,
39488,
1776,
198,
220,
220,
220,
220,
220,
220,
220,
2245,
58,
10677,
60,
796,
657,
26,
628,
220,
220,
220,
220,
220,
220,
220,
981,
7,
0,
1084,
1544,
499,
13,
271,
40613,
3419,
19953,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2254,
1090,
14941,
796,
949,
1544,
499,
13,
30393,
9783,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
611,
357,
22019,
14941,
13,
312,
6624,
29636,
8,
1441,
1090,
14941,
13,
15805,
4863,
50,
6015,
26,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
611,
357,
22019,
14941,
13,
11338,
4863,
50,
6015,
6624,
509,
1343,
352,
8,
2555,
26,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
493,
21737,
1306,
82,
796,
12351,
2514,
35,
301,
58,
22019,
14941,
13,
312,
11208,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
329,
357,
600,
1312,
796,
657,
26,
1312,
1279,
299,
26,
1312,
29577,
1391,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
611,
357,
19545,
82,
58,
72,
60,
14512,
657,
8,
1391,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
493,
649,
13729,
796,
1090,
14941,
13,
15805,
4863,
50,
6015,
1343,
1306,
82,
58,
72,
11208,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
493,
649,
19485,
796,
1090,
14941,
13,
11338,
4863,
50,
6015,
1343,
352,
26,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
611,
357,
3605,
13729,
1279,
1575,
58,
72,
12962,
1391,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
949,
1544,
499,
13,
47895,
7,
3605,
2254,
7,
72,
11,
649,
13729,
11,
649,
19485,
18125,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1575,
58,
72,
60,
796,
649,
13729,
26,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1782,
2073,
611,
357,
3605,
19485,
1279,
2245,
58,
72,
12962,
90,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
949,
1544,
499,
13,
47895,
7,
3605,
2254,
7,
72,
11,
649,
13729,
11,
649,
19485,
18125,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2245,
58,
72,
60,
796,
649,
19485,
26,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1782,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1782,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1782,
198,
220,
220,
220,
220,
220,
220,
220,
1782,
198,
220,
220,
220,
220,
220,
220,
220,
1441,
1575,
58,
67,
301,
60,
6624,
34142,
13,
22921,
62,
39488,
30,
532,
16,
25,
15805,
58,
67,
301,
11208,
198,
220,
220,
220,
1782,
198,
92,
198,
7061,
6
] | 2.209213 | 2,084 |
import json
import os
import tempfile
from modelstore.model_store import ModelStore
_DOMAIN_NAME = "example-model-file"
| [
11748,
33918,
198,
11748,
28686,
198,
11748,
20218,
7753,
198,
198,
6738,
2746,
8095,
13,
19849,
62,
8095,
1330,
9104,
22658,
198,
198,
62,
39170,
29833,
62,
20608,
796,
366,
20688,
12,
19849,
12,
7753,
1,
628,
628
] | 3.289474 | 38 |
import json
import os
import numpy as np
from tokenizers import BertWordPieceTokenizer
from transformers import BertTokenizer
class SquadExample:
"""
Process SQUAD dataset
"""
def read_data(filename, settings):
"""
Helper function to read and preprocess SQUAD data for training and validation with Keras.
:return: test, training data or validation data and nbr of examples
"""
slow_tokenizer = BertTokenizer.from_pretrained("bert-base-uncased")
save_path = "bert_base_uncased/"
if not os.path.exists(save_path):
os.makedirs(save_path)
slow_tokenizer.save_pretrained(save_path)
# Load the fast tokenizer from saved file
tokenizer = BertWordPieceTokenizer("bert_base_uncased/vocab.txt", lowercase=True)
with open(filename) as f: raw_train_data = json.load(f)
train_squad_examples = create_squad_examples(raw_train_data, tokenizer, settings)
x_train, y_train = create_inputs_targets(train_squad_examples)
return x_train, y_train, train_squad_examples
| [
11748,
33918,
198,
11748,
28686,
198,
11748,
299,
32152,
355,
45941,
198,
6738,
11241,
11341,
1330,
22108,
26449,
47,
8535,
30642,
7509,
198,
6738,
6121,
364,
1330,
22108,
30642,
7509,
628,
198,
4871,
11630,
16281,
25,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
10854,
45880,
2885,
27039,
198,
220,
220,
220,
37227,
628,
628,
198,
4299,
1100,
62,
7890,
7,
34345,
11,
6460,
2599,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
5053,
525,
2163,
284,
1100,
290,
662,
14681,
45880,
2885,
1366,
329,
3047,
290,
21201,
351,
17337,
292,
13,
198,
220,
220,
220,
1058,
7783,
25,
1332,
11,
3047,
1366,
393,
21201,
1366,
290,
299,
1671,
286,
6096,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
3105,
62,
30001,
7509,
796,
22108,
30642,
7509,
13,
6738,
62,
5310,
13363,
7203,
4835,
12,
8692,
12,
19524,
839,
4943,
198,
220,
220,
220,
3613,
62,
6978,
796,
366,
4835,
62,
8692,
62,
19524,
839,
30487,
198,
220,
220,
220,
611,
407,
28686,
13,
6978,
13,
1069,
1023,
7,
21928,
62,
6978,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
28686,
13,
76,
4335,
17062,
7,
21928,
62,
6978,
8,
198,
220,
220,
220,
3105,
62,
30001,
7509,
13,
21928,
62,
5310,
13363,
7,
21928,
62,
6978,
8,
628,
220,
220,
220,
1303,
8778,
262,
3049,
11241,
7509,
422,
7448,
2393,
198,
220,
220,
220,
11241,
7509,
796,
22108,
26449,
47,
8535,
30642,
7509,
7203,
4835,
62,
8692,
62,
19524,
839,
14,
18893,
397,
13,
14116,
1600,
2793,
7442,
28,
17821,
8,
198,
220,
220,
220,
351,
1280,
7,
34345,
8,
355,
277,
25,
8246,
62,
27432,
62,
7890,
796,
33918,
13,
2220,
7,
69,
8,
198,
220,
220,
220,
4512,
62,
16485,
324,
62,
1069,
12629,
796,
2251,
62,
16485,
324,
62,
1069,
12629,
7,
1831,
62,
27432,
62,
7890,
11,
11241,
7509,
11,
6460,
8,
198,
220,
220,
220,
2124,
62,
27432,
11,
331,
62,
27432,
796,
2251,
62,
15414,
82,
62,
83,
853,
1039,
7,
27432,
62,
16485,
324,
62,
1069,
12629,
8,
628,
220,
220,
220,
1441,
2124,
62,
27432,
11,
331,
62,
27432,
11,
4512,
62,
16485,
324,
62,
1069,
12629,
198
] | 2.858726 | 361 |
import os
import random
import numpy as np
import scipy.misc as misc
import imageio
from tqdm import tqdm
import cv2
from PIL import Image
import torch
import torch.nn.functional as F
IMG_EXTENSIONS = ['.jpg', '.JPG', '.jpeg', '.JPEG', '.png', '.PNG', '.ppm', '.PPM', '.bmp', '.BMP']
BINARY_EXTENSIONS = ['.npy']
BENCHMARK = ['Set5', 'Set14', 'B100', 'Urban100', 'Manga109', 'DIV2K', 'DF2K']
####################
# Files & IO
####################
####################
#for BD degradation#
####################
# image processing
# process on numpy image
####################
| [
11748,
28686,
198,
11748,
4738,
198,
11748,
299,
32152,
355,
45941,
198,
11748,
629,
541,
88,
13,
44374,
355,
12747,
198,
11748,
2939,
952,
198,
6738,
256,
80,
36020,
1330,
256,
80,
36020,
198,
11748,
269,
85,
17,
198,
6738,
350,
4146,
1330,
7412,
198,
198,
11748,
28034,
198,
11748,
28034,
13,
20471,
13,
45124,
355,
376,
198,
198,
3955,
38,
62,
13918,
16938,
11053,
796,
685,
4458,
9479,
3256,
45302,
41,
6968,
3256,
45302,
73,
22071,
3256,
45302,
12889,
7156,
3256,
45302,
11134,
3256,
45302,
47,
10503,
3256,
45302,
381,
76,
3256,
45302,
47,
5868,
3256,
45302,
65,
3149,
3256,
45302,
33,
7378,
20520,
198,
33,
1268,
13153,
62,
13918,
16938,
11053,
796,
685,
4458,
77,
9078,
20520,
198,
33,
1677,
3398,
44,
14175,
796,
37250,
7248,
20,
3256,
705,
7248,
1415,
3256,
705,
33,
3064,
3256,
705,
46667,
3064,
3256,
705,
44,
16484,
14454,
3256,
705,
33569,
17,
42,
3256,
705,
8068,
17,
42,
20520,
628,
198,
14468,
4242,
198,
2,
13283,
1222,
24418,
198,
14468,
4242,
628,
628,
628,
198,
14468,
4242,
198,
2,
1640,
28023,
27486,
2,
198,
198,
14468,
4242,
198,
2,
2939,
7587,
198,
2,
1429,
319,
299,
32152,
2939,
198,
14468,
4242,
628,
628
] | 2.930348 | 201 |
print("Entre com os dados de um trangulo")
lado1 = int(input("Lado 1: "))
lado2 = int(input("Lado 2: "))
lado3 = int(input("Lado 3: "))
if lado1 < lado2 + lado3 and lado2 < lado1 + lado3 and lado3 < lado1 + lado2:
if lado1 == lado2 == lado3:
print("Triângulo equilatero")
elif lado1 != lado2 != lado3 != lado1:
print("Triângulo escaleno")
else:
print("Triângulo isósceles")
else:
print("Os lados não foram um triangulo") | [
4798,
7203,
14539,
260,
401,
28686,
9955,
418,
390,
23781,
491,
648,
43348,
4943,
198,
75,
4533,
16,
796,
493,
7,
15414,
7203,
43,
4533,
352,
25,
366,
4008,
198,
75,
4533,
17,
796,
493,
7,
15414,
7203,
43,
4533,
362,
25,
366,
4008,
198,
75,
4533,
18,
796,
493,
7,
15414,
7203,
43,
4533,
513,
25,
366,
4008,
198,
361,
300,
4533,
16,
1279,
300,
4533,
17,
1343,
300,
4533,
18,
290,
300,
4533,
17,
1279,
300,
4533,
16,
1343,
300,
4533,
18,
290,
300,
4533,
18,
1279,
300,
4533,
16,
1343,
300,
4533,
17,
25,
198,
220,
220,
220,
611,
300,
4533,
16,
6624,
300,
4533,
17,
6624,
300,
4533,
18,
25,
198,
220,
220,
220,
220,
220,
220,
220,
3601,
7203,
14824,
22940,
782,
43348,
1602,
38601,
78,
4943,
198,
220,
220,
220,
1288,
361,
300,
4533,
16,
14512,
300,
4533,
17,
14512,
300,
4533,
18,
14512,
300,
4533,
16,
25,
198,
220,
220,
220,
220,
220,
220,
220,
3601,
7203,
14824,
22940,
782,
43348,
12221,
23397,
4943,
198,
220,
220,
220,
2073,
25,
198,
220,
220,
220,
220,
220,
220,
220,
3601,
7203,
14824,
22940,
782,
43348,
318,
10205,
82,
344,
829,
4943,
198,
17772,
25,
198,
220,
220,
220,
3601,
7203,
16748,
9717,
418,
299,
28749,
329,
321,
23781,
1333,
648,
43348,
4943
] | 2.110092 | 218 |
# -------------------------------------------------------------------- #
# game.py
# contains main game loop,
# including events, drawing, and update
# -------------------------------------------------------------------- #
# General imports:
import sys
# Game related imports:
import pygame
import pyscroll
import pytmx
from pygame.locals import *
# Local imports:
from constants import *
from player import Player
from scene import Scene
from solid_platform import Platform
# Events: processing input from user via keyboard, mouse, etc
# game logic/mechanics here. process user input
# Code for what is drawn on screen each frame here
# All this function's code could just be put into the draw() function,
# but I put it here because I'm tired of scrolling over it.
# TODO: rewrite debug drawing code so all text in in a list that is displayed within a for loop.
# TODO: that way we can add more debug outputs easily by appending them to the list
| [
2,
16529,
650,
1303,
198,
2,
983,
13,
9078,
198,
2,
220,
220,
4909,
1388,
983,
9052,
11,
198,
2,
197,
8201,
2995,
11,
8263,
11,
290,
4296,
198,
2,
16529,
650,
1303,
198,
198,
2,
3611,
17944,
25,
198,
11748,
25064,
198,
198,
2,
3776,
3519,
17944,
25,
198,
11748,
12972,
6057,
198,
11748,
279,
28349,
2487,
198,
11748,
12972,
17209,
87,
198,
6738,
12972,
6057,
13,
17946,
874,
1330,
1635,
198,
198,
2,
10714,
17944,
25,
198,
6738,
38491,
1330,
1635,
198,
6738,
2137,
1330,
7853,
198,
6738,
3715,
1330,
28315,
198,
6738,
4735,
62,
24254,
1330,
19193,
628,
220,
220,
220,
1303,
18715,
25,
7587,
5128,
422,
2836,
2884,
10586,
11,
10211,
11,
3503,
628,
220,
220,
220,
1303,
983,
9156,
14,
1326,
3147,
873,
994,
13,
1429,
2836,
5128,
628,
220,
220,
220,
1303,
6127,
329,
644,
318,
7428,
319,
3159,
1123,
5739,
994,
628,
220,
220,
220,
1303,
1439,
428,
2163,
338,
2438,
714,
655,
307,
1234,
656,
262,
3197,
3419,
2163,
11,
198,
220,
220,
220,
1303,
475,
314,
1234,
340,
994,
780,
314,
1101,
10032,
286,
28659,
625,
340,
13,
198,
220,
220,
220,
1303,
16926,
46,
25,
28183,
14257,
8263,
2438,
523,
477,
2420,
287,
287,
257,
1351,
326,
318,
9066,
1626,
257,
329,
9052,
13,
198,
220,
220,
220,
1303,
16926,
46,
25,
326,
835,
356,
460,
751,
517,
14257,
23862,
3538,
416,
598,
1571,
606,
284,
262,
1351,
198
] | 4.121339 | 239 |
# YOLOv5 🚀 by Ultralytics, GPL-3.0 license
"""
Auto-anchor utils
"""
import random
import numpy as np
import torch
import yaml
from tqdm import tqdm
from utils.general import LOGGER, colorstr, emojis
PREFIX = colorstr("AutoAnchor: ")
def kmean_anchors(
dataset="./data/coco128.yaml", n=9, img_size=640, thr=4.0, gen=1000, verbose=True
):
""" Creates kmeans-evolved anchors from training dataset
Arguments:
dataset: path to data.yaml, or a loaded dataset
n: number of anchors
img_size: image size used for training
thr: anchor-label wh ratio threshold hyperparameter hyp['anchor_t'] used for training, default=4.0
gen: generations to evolve anchors using genetic algorithm
verbose: print all results
Return:
k: kmeans evolved anchors
Usage:
from utils.autoanchor import *; _ = kmean_anchors()
"""
from scipy.cluster.vq import kmeans
thr = 1 / thr
if isinstance(dataset, str): # *.yaml file
with open(dataset, errors="ignore") as f:
data_dict = yaml.safe_load(f) # model dict
from utils.datasets import LoadImagesAndLabels
dataset = LoadImagesAndLabels(data_dict["train"], augment=True, rect=True)
# Get label wh
shapes = img_size * dataset.shapes / dataset.shapes.max(1, keepdims=True)
wh0 = np.concatenate([l[:, 3:5] * s for s, l in zip(shapes, dataset.labels)]) # wh
# Filter
i = (wh0 < 3.0).any(1).sum()
if i:
LOGGER.info(
f"{PREFIX}WARNING: Extremely small objects found. {i} of {len(wh0)} labels are < 3 pixels in size."
)
wh = wh0[(wh0 >= 2.0).any(1)] # filter > 2 pixels
# wh = wh * (np.random.rand(wh.shape[0], 1) * 0.9 + 0.1) # multiply by random scale 0-1
# Kmeans calculation
LOGGER.info(f"{PREFIX}Running kmeans for {n} anchors on {len(wh)} points...")
s = wh.std(0) # sigmas for whitening
k, dist = kmeans(wh / s, n, iter=30) # points, mean distance
assert (
len(k) == n
), f"{PREFIX}ERROR: scipy.cluster.vq.kmeans requested {n} points but returned only {len(k)}"
k *= s
wh = torch.tensor(wh, dtype=torch.float32) # filtered
wh0 = torch.tensor(wh0, dtype=torch.float32) # unfiltered
k = print_results(k, verbose=False)
# Plot
# k, d = [None] * 20, [None] * 20
# for i in tqdm(range(1, 21)):
# k[i-1], d[i-1] = kmeans(wh / s, i) # points, mean distance
# fig, ax = plt.subplots(1, 2, figsize=(14, 7), tight_layout=True)
# ax = ax.ravel()
# ax[0].plot(np.arange(1, 21), np.array(d) ** 2, marker='.')
# fig, ax = plt.subplots(1, 2, figsize=(14, 7)) # plot wh
# ax[0].hist(wh[wh[:, 0]<100, 0],400)
# ax[1].hist(wh[wh[:, 1]<100, 1],400)
# fig.savefig('wh.png', dpi=200)
# Evolve
npr = np.random
f, sh, mp, s = (
anchor_fitness(k),
k.shape,
0.9,
0.1,
) # fitness, generations, mutation prob, sigma
pbar = tqdm(
range(gen), desc=f"{PREFIX}Evolving anchors with Genetic Algorithm:"
) # progress bar
for _ in pbar:
v = np.ones(sh)
while (v == 1).all(): # mutate until a change occurs (prevent duplicates)
v = ((npr.random(sh) < mp) * random.random() * npr.randn(*sh) * s + 1).clip(
0.3, 3.0
)
kg = (k.copy() * v).clip(min=2.0)
fg = anchor_fitness(kg)
if fg > f:
f, k = fg, kg.copy()
pbar.desc = (
f"{PREFIX}Evolving anchors with Genetic Algorithm: fitness = {f:.4f}"
)
if verbose:
print_results(k, verbose)
return print_results(k)
| [
2,
575,
3535,
46,
85,
20,
12520,
248,
222,
416,
6172,
1373,
88,
14094,
11,
38644,
12,
18,
13,
15,
5964,
198,
37811,
198,
27722,
12,
3702,
273,
3384,
4487,
198,
37811,
198,
198,
11748,
4738,
198,
198,
11748,
299,
32152,
355,
45941,
198,
11748,
28034,
198,
11748,
331,
43695,
198,
6738,
256,
80,
36020,
1330,
256,
80,
36020,
198,
198,
6738,
3384,
4487,
13,
24622,
1330,
41605,
30373,
11,
3124,
2536,
11,
795,
13210,
271,
198,
198,
47,
31688,
10426,
796,
3124,
2536,
7203,
27722,
2025,
354,
273,
25,
366,
8,
628,
628,
198,
4299,
479,
32604,
62,
3702,
669,
7,
198,
220,
220,
220,
27039,
28,
1911,
14,
7890,
14,
66,
25634,
12762,
13,
88,
43695,
1600,
299,
28,
24,
11,
33705,
62,
7857,
28,
31102,
11,
5636,
28,
19,
13,
15,
11,
2429,
28,
12825,
11,
15942,
577,
28,
17821,
198,
2599,
198,
220,
220,
220,
37227,
7921,
274,
479,
1326,
504,
12,
1990,
5634,
43360,
422,
3047,
27039,
628,
220,
220,
220,
220,
220,
220,
220,
20559,
2886,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
27039,
25,
3108,
284,
1366,
13,
88,
43695,
11,
393,
257,
9639,
27039,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
299,
25,
1271,
286,
43360,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
33705,
62,
7857,
25,
2939,
2546,
973,
329,
3047,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
5636,
25,
18021,
12,
18242,
348,
8064,
11387,
8718,
17143,
2357,
5328,
17816,
3702,
273,
62,
83,
20520,
973,
329,
3047,
11,
4277,
28,
19,
13,
15,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2429,
25,
10439,
284,
18101,
43360,
1262,
8513,
11862,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
15942,
577,
25,
3601,
477,
2482,
628,
220,
220,
220,
220,
220,
220,
220,
8229,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
479,
25,
479,
1326,
504,
12572,
43360,
628,
220,
220,
220,
220,
220,
220,
220,
29566,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
422,
3384,
4487,
13,
23736,
3702,
273,
1330,
1635,
26,
4808,
796,
479,
32604,
62,
3702,
669,
3419,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
422,
629,
541,
88,
13,
565,
5819,
13,
85,
80,
1330,
479,
1326,
504,
628,
220,
220,
220,
5636,
796,
352,
1220,
5636,
628,
220,
220,
220,
611,
318,
39098,
7,
19608,
292,
316,
11,
965,
2599,
220,
1303,
46866,
88,
43695,
2393,
198,
220,
220,
220,
220,
220,
220,
220,
351,
1280,
7,
19608,
292,
316,
11,
8563,
2625,
46430,
4943,
355,
277,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1366,
62,
11600,
796,
331,
43695,
13,
21230,
62,
2220,
7,
69,
8,
220,
1303,
2746,
8633,
198,
220,
220,
220,
220,
220,
220,
220,
422,
3384,
4487,
13,
19608,
292,
1039,
1330,
8778,
29398,
1870,
17822,
1424,
628,
220,
220,
220,
220,
220,
220,
220,
27039,
796,
8778,
29398,
1870,
17822,
1424,
7,
7890,
62,
11600,
14692,
27432,
33116,
35016,
28,
17821,
11,
13621,
28,
17821,
8,
628,
220,
220,
220,
1303,
3497,
6167,
348,
198,
220,
220,
220,
15268,
796,
33705,
62,
7857,
1635,
27039,
13,
1477,
7916,
1220,
27039,
13,
1477,
7916,
13,
9806,
7,
16,
11,
1394,
67,
12078,
28,
17821,
8,
198,
220,
220,
220,
348,
15,
796,
45941,
13,
1102,
9246,
268,
378,
26933,
75,
58,
45299,
513,
25,
20,
60,
1635,
264,
329,
264,
11,
300,
287,
19974,
7,
1477,
7916,
11,
27039,
13,
23912,
1424,
8,
12962,
220,
1303,
348,
628,
220,
220,
220,
1303,
25853,
198,
220,
220,
220,
1312,
796,
357,
1929,
15,
1279,
513,
13,
15,
737,
1092,
7,
16,
737,
16345,
3419,
198,
220,
220,
220,
611,
1312,
25,
198,
220,
220,
220,
220,
220,
220,
220,
41605,
30373,
13,
10951,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
277,
1,
90,
47,
31688,
10426,
92,
31502,
25,
18111,
306,
1402,
5563,
1043,
13,
1391,
72,
92,
286,
1391,
11925,
7,
1929,
15,
38165,
14722,
389,
1279,
513,
17848,
287,
2546,
526,
198,
220,
220,
220,
220,
220,
220,
220,
1267,
198,
220,
220,
220,
348,
796,
348,
15,
58,
7,
1929,
15,
18189,
362,
13,
15,
737,
1092,
7,
16,
15437,
220,
1303,
8106,
1875,
362,
17848,
198,
220,
220,
220,
1303,
348,
796,
348,
1635,
357,
37659,
13,
25120,
13,
25192,
7,
1929,
13,
43358,
58,
15,
4357,
352,
8,
1635,
657,
13,
24,
1343,
657,
13,
16,
8,
220,
1303,
29162,
416,
4738,
5046,
657,
12,
16,
628,
220,
220,
220,
1303,
509,
1326,
504,
17952,
198,
220,
220,
220,
41605,
30373,
13,
10951,
7,
69,
1,
90,
47,
31688,
10426,
92,
28768,
479,
1326,
504,
329,
1391,
77,
92,
43360,
319,
1391,
11925,
7,
1929,
38165,
2173,
9313,
8,
198,
220,
220,
220,
264,
796,
348,
13,
19282,
7,
15,
8,
220,
1303,
43237,
5356,
329,
20542,
3101,
198,
220,
220,
220,
479,
11,
1233,
796,
479,
1326,
504,
7,
1929,
1220,
264,
11,
299,
11,
11629,
28,
1270,
8,
220,
1303,
2173,
11,
1612,
5253,
198,
220,
220,
220,
6818,
357,
198,
220,
220,
220,
220,
220,
220,
220,
18896,
7,
74,
8,
6624,
299,
198,
220,
220,
220,
10612,
277,
1,
90,
47,
31688,
10426,
92,
24908,
25,
629,
541,
88,
13,
565,
5819,
13,
85,
80,
13,
74,
1326,
504,
9167,
1391,
77,
92,
2173,
475,
4504,
691,
1391,
11925,
7,
74,
8,
36786,
198,
220,
220,
220,
479,
1635,
28,
264,
198,
220,
220,
220,
348,
796,
28034,
13,
83,
22854,
7,
1929,
11,
288,
4906,
28,
13165,
354,
13,
22468,
2624,
8,
220,
1303,
29083,
198,
220,
220,
220,
348,
15,
796,
28034,
13,
83,
22854,
7,
1929,
15,
11,
288,
4906,
28,
13165,
354,
13,
22468,
2624,
8,
220,
1303,
3684,
346,
4400,
198,
220,
220,
220,
479,
796,
3601,
62,
43420,
7,
74,
11,
15942,
577,
28,
25101,
8,
628,
220,
220,
220,
1303,
28114,
198,
220,
220,
220,
1303,
479,
11,
288,
796,
685,
14202,
60,
1635,
1160,
11,
685,
14202,
60,
1635,
1160,
198,
220,
220,
220,
1303,
329,
1312,
287,
256,
80,
36020,
7,
9521,
7,
16,
11,
2310,
8,
2599,
198,
220,
220,
220,
1303,
220,
220,
220,
220,
479,
58,
72,
12,
16,
4357,
288,
58,
72,
12,
16,
60,
796,
479,
1326,
504,
7,
1929,
1220,
264,
11,
1312,
8,
220,
1303,
2173,
11,
1612,
5253,
198,
220,
220,
220,
1303,
2336,
11,
7877,
796,
458,
83,
13,
7266,
489,
1747,
7,
16,
11,
362,
11,
2336,
7857,
16193,
1415,
11,
767,
828,
5381,
62,
39786,
28,
17821,
8,
198,
220,
220,
220,
1303,
7877,
796,
7877,
13,
25843,
3419,
198,
220,
220,
220,
1303,
7877,
58,
15,
4083,
29487,
7,
37659,
13,
283,
858,
7,
16,
11,
2310,
828,
45941,
13,
18747,
7,
67,
8,
12429,
362,
11,
18364,
11639,
2637,
8,
198,
220,
220,
220,
1303,
2336,
11,
7877,
796,
458,
83,
13,
7266,
489,
1747,
7,
16,
11,
362,
11,
2336,
7857,
16193,
1415,
11,
767,
4008,
220,
1303,
7110,
348,
198,
220,
220,
220,
1303,
7877,
58,
15,
4083,
10034,
7,
1929,
58,
1929,
58,
45299,
657,
60,
27,
3064,
11,
657,
4357,
7029,
8,
198,
220,
220,
220,
1303,
7877,
58,
16,
4083,
10034,
7,
1929,
58,
1929,
58,
45299,
352,
60,
27,
3064,
11,
352,
4357,
7029,
8,
198,
220,
220,
220,
1303,
2336,
13,
21928,
5647,
10786,
1929,
13,
11134,
3256,
288,
14415,
28,
2167,
8,
628,
220,
220,
220,
1303,
4319,
6442,
198,
220,
220,
220,
299,
1050,
796,
45941,
13,
25120,
198,
220,
220,
220,
277,
11,
427,
11,
29034,
11,
264,
796,
357,
198,
220,
220,
220,
220,
220,
220,
220,
18021,
62,
69,
3659,
7,
74,
828,
198,
220,
220,
220,
220,
220,
220,
220,
479,
13,
43358,
11,
198,
220,
220,
220,
220,
220,
220,
220,
657,
13,
24,
11,
198,
220,
220,
220,
220,
220,
220,
220,
657,
13,
16,
11,
198,
220,
220,
220,
1267,
220,
1303,
13547,
11,
10439,
11,
15148,
1861,
11,
264,
13495,
198,
220,
220,
220,
279,
5657,
796,
256,
80,
36020,
7,
198,
220,
220,
220,
220,
220,
220,
220,
2837,
7,
5235,
828,
1715,
28,
69,
1,
90,
47,
31688,
10426,
92,
36,
10396,
1075,
43360,
351,
42295,
978,
42289,
11097,
198,
220,
220,
220,
1267,
220,
1303,
4371,
2318,
198,
220,
220,
220,
329,
4808,
287,
279,
5657,
25,
198,
220,
220,
220,
220,
220,
220,
220,
410,
796,
45941,
13,
1952,
7,
1477,
8,
198,
220,
220,
220,
220,
220,
220,
220,
981,
357,
85,
6624,
352,
737,
439,
33529,
220,
1303,
4517,
378,
1566,
257,
1487,
8833,
357,
3866,
1151,
14184,
16856,
8,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
410,
796,
14808,
77,
1050,
13,
25120,
7,
1477,
8,
1279,
29034,
8,
1635,
4738,
13,
25120,
3419,
1635,
299,
1050,
13,
25192,
77,
46491,
1477,
8,
1635,
264,
1343,
352,
737,
15036,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
657,
13,
18,
11,
513,
13,
15,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1267,
198,
220,
220,
220,
220,
220,
220,
220,
14211,
796,
357,
74,
13,
30073,
3419,
1635,
410,
737,
15036,
7,
1084,
28,
17,
13,
15,
8,
198,
220,
220,
220,
220,
220,
220,
220,
277,
70,
796,
18021,
62,
69,
3659,
7,
10025,
8,
198,
220,
220,
220,
220,
220,
220,
220,
611,
277,
70,
1875,
277,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
277,
11,
479,
796,
277,
70,
11,
14211,
13,
30073,
3419,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
279,
5657,
13,
20147,
796,
357,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
277,
1,
90,
47,
31688,
10426,
92,
36,
10396,
1075,
43360,
351,
42295,
978,
42289,
25,
13547,
796,
1391,
69,
25,
13,
19,
69,
36786,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1267,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
611,
15942,
577,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
3601,
62,
43420,
7,
74,
11,
15942,
577,
8,
628,
220,
220,
220,
1441,
3601,
62,
43420,
7,
74,
8,
198
] | 2.114318 | 1,767 |
"""
SMTP.sendmail and SMTP.send_message method testing.
"""
import copy
import email.generator
import email.header
import pytest
from aiosmtplib import (
SMTPNotSupported,
SMTPRecipientsRefused,
SMTPResponseException,
SMTPStatus,
)
pytestmark = pytest.mark.asyncio()
async def test_rset_after_sendmail_error_response_to_mail(
smtp_client, smtpd_server, received_commands
):
"""
If an error response is given to the MAIL command in the sendmail method,
test that we reset the server session.
"""
async with smtp_client:
response = await smtp_client.ehlo()
assert response.code == SMTPStatus.completed
with pytest.raises(SMTPResponseException) as excinfo:
await smtp_client.sendmail(">foobar<", ["[email protected]"], "Hello World")
assert excinfo.value.code == SMTPStatus.unrecognized_parameters
assert received_commands[-1][0] == "RSET"
async def test_rset_after_sendmail_error_response_to_rcpt(
smtp_client, smtpd_server, received_commands
):
"""
If an error response is given to the RCPT command in the sendmail method,
test that we reset the server session.
"""
async with smtp_client:
response = await smtp_client.ehlo()
assert response.code == SMTPStatus.completed
with pytest.raises(SMTPRecipientsRefused) as excinfo:
await smtp_client.sendmail(
"[email protected]", [">not an addr<"], "Hello World"
)
assert excinfo.value.recipients[0].code == SMTPStatus.unrecognized_parameters
assert received_commands[-1][0] == "RSET"
async def test_rset_after_sendmail_error_response_to_data(
smtp_client,
smtpd_server,
smtpd_class,
smtpd_response_handler_factory,
monkeypatch,
error_code,
sender_str,
recipient_str,
message_str,
received_commands,
):
"""
If an error response is given to the DATA command in the sendmail method,
test that we reset the server session.
"""
response_handler = smtpd_response_handler_factory("{} error".format(error_code))
monkeypatch.setattr(smtpd_class, "smtp_DATA", response_handler)
async with smtp_client:
response = await smtp_client.ehlo()
assert response.code == SMTPStatus.completed
with pytest.raises(SMTPResponseException) as excinfo:
await smtp_client.sendmail(sender_str, [recipient_str], message_str)
assert excinfo.value.code == error_code
assert received_commands[-1][0] == "RSET"
| [
37811,
198,
12310,
7250,
13,
21280,
4529,
290,
9447,
7250,
13,
21280,
62,
20500,
2446,
4856,
13,
198,
37811,
198,
11748,
4866,
198,
11748,
3053,
13,
8612,
1352,
198,
11748,
3053,
13,
25677,
198,
198,
11748,
12972,
9288,
198,
198,
6738,
257,
4267,
16762,
489,
571,
1330,
357,
198,
220,
220,
220,
9447,
7250,
3673,
48181,
11,
198,
220,
220,
220,
9447,
51,
4805,
721,
541,
2334,
8134,
1484,
11,
198,
220,
220,
220,
9447,
51,
4805,
9774,
2591,
16922,
11,
198,
220,
220,
220,
9447,
7250,
19580,
11,
198,
8,
628,
198,
9078,
9288,
4102,
796,
12972,
9288,
13,
4102,
13,
292,
13361,
952,
3419,
628,
628,
628,
628,
628,
198,
198,
292,
13361,
825,
1332,
62,
81,
2617,
62,
8499,
62,
21280,
4529,
62,
18224,
62,
26209,
62,
1462,
62,
4529,
7,
198,
220,
220,
220,
895,
34788,
62,
16366,
11,
895,
83,
30094,
62,
15388,
11,
2722,
62,
9503,
1746,
198,
2599,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
1002,
281,
4049,
2882,
318,
1813,
284,
262,
8779,
4146,
3141,
287,
262,
3758,
4529,
2446,
11,
198,
220,
220,
220,
1332,
326,
356,
13259,
262,
4382,
6246,
13,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
30351,
351,
895,
34788,
62,
16366,
25,
198,
220,
220,
220,
220,
220,
220,
220,
2882,
796,
25507,
895,
34788,
62,
16366,
13,
17231,
5439,
3419,
198,
220,
220,
220,
220,
220,
220,
220,
6818,
2882,
13,
8189,
6624,
9447,
7250,
19580,
13,
785,
16838,
628,
220,
220,
220,
220,
220,
220,
220,
351,
12972,
9288,
13,
430,
2696,
7,
12310,
51,
4805,
9774,
2591,
16922,
8,
355,
2859,
10951,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
25507,
895,
34788,
62,
16366,
13,
21280,
4529,
7,
5320,
6513,
30973,
27,
1600,
14631,
9288,
31,
20688,
13,
785,
33116,
366,
15496,
2159,
4943,
628,
220,
220,
220,
220,
220,
220,
220,
6818,
2859,
10951,
13,
8367,
13,
8189,
6624,
9447,
7250,
19580,
13,
403,
26243,
1143,
62,
17143,
7307,
198,
220,
220,
220,
220,
220,
220,
220,
6818,
2722,
62,
9503,
1746,
58,
12,
16,
7131,
15,
60,
6624,
366,
6998,
2767,
1,
628,
198,
292,
13361,
825,
1332,
62,
81,
2617,
62,
8499,
62,
21280,
4529,
62,
18224,
62,
26209,
62,
1462,
62,
6015,
457,
7,
198,
220,
220,
220,
895,
34788,
62,
16366,
11,
895,
83,
30094,
62,
15388,
11,
2722,
62,
9503,
1746,
198,
2599,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
1002,
281,
4049,
2882,
318,
1813,
284,
262,
371,
8697,
51,
3141,
287,
262,
3758,
4529,
2446,
11,
198,
220,
220,
220,
1332,
326,
356,
13259,
262,
4382,
6246,
13,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
30351,
351,
895,
34788,
62,
16366,
25,
198,
220,
220,
220,
220,
220,
220,
220,
2882,
796,
25507,
895,
34788,
62,
16366,
13,
17231,
5439,
3419,
198,
220,
220,
220,
220,
220,
220,
220,
6818,
2882,
13,
8189,
6624,
9447,
7250,
19580,
13,
785,
16838,
628,
220,
220,
220,
220,
220,
220,
220,
351,
12972,
9288,
13,
430,
2696,
7,
12310,
51,
4805,
721,
541,
2334,
8134,
1484,
8,
355,
2859,
10951,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
25507,
895,
34788,
62,
16366,
13,
21280,
4529,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
366,
9288,
31,
20688,
13,
785,
1600,
685,
5320,
1662,
281,
37817,
27,
33116,
366,
15496,
2159,
1,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1267,
628,
220,
220,
220,
220,
220,
220,
220,
6818,
2859,
10951,
13,
8367,
13,
8344,
541,
2334,
58,
15,
4083,
8189,
6624,
9447,
7250,
19580,
13,
403,
26243,
1143,
62,
17143,
7307,
198,
220,
220,
220,
220,
220,
220,
220,
6818,
2722,
62,
9503,
1746,
58,
12,
16,
7131,
15,
60,
6624,
366,
6998,
2767,
1,
628,
198,
292,
13361,
825,
1332,
62,
81,
2617,
62,
8499,
62,
21280,
4529,
62,
18224,
62,
26209,
62,
1462,
62,
7890,
7,
198,
220,
220,
220,
895,
34788,
62,
16366,
11,
198,
220,
220,
220,
895,
83,
30094,
62,
15388,
11,
198,
220,
220,
220,
895,
83,
30094,
62,
4871,
11,
198,
220,
220,
220,
895,
83,
30094,
62,
26209,
62,
30281,
62,
69,
9548,
11,
198,
220,
220,
220,
21657,
17147,
11,
198,
220,
220,
220,
4049,
62,
8189,
11,
198,
220,
220,
220,
29788,
62,
2536,
11,
198,
220,
220,
220,
17800,
62,
2536,
11,
198,
220,
220,
220,
3275,
62,
2536,
11,
198,
220,
220,
220,
2722,
62,
9503,
1746,
11,
198,
2599,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
1002,
281,
4049,
2882,
318,
1813,
284,
262,
42865,
3141,
287,
262,
3758,
4529,
2446,
11,
198,
220,
220,
220,
1332,
326,
356,
13259,
262,
4382,
6246,
13,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
2882,
62,
30281,
796,
895,
83,
30094,
62,
26209,
62,
30281,
62,
69,
9548,
7203,
90,
92,
4049,
1911,
18982,
7,
18224,
62,
8189,
4008,
198,
220,
220,
220,
21657,
17147,
13,
2617,
35226,
7,
5796,
83,
30094,
62,
4871,
11,
366,
5796,
34788,
62,
26947,
1600,
2882,
62,
30281,
8,
628,
220,
220,
220,
30351,
351,
895,
34788,
62,
16366,
25,
198,
220,
220,
220,
220,
220,
220,
220,
2882,
796,
25507,
895,
34788,
62,
16366,
13,
17231,
5439,
3419,
198,
220,
220,
220,
220,
220,
220,
220,
6818,
2882,
13,
8189,
6624,
9447,
7250,
19580,
13,
785,
16838,
628,
220,
220,
220,
220,
220,
220,
220,
351,
12972,
9288,
13,
430,
2696,
7,
12310,
51,
4805,
9774,
2591,
16922,
8,
355,
2859,
10951,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
25507,
895,
34788,
62,
16366,
13,
21280,
4529,
7,
82,
2194,
62,
2536,
11,
685,
8344,
48137,
62,
2536,
4357,
3275,
62,
2536,
8,
628,
220,
220,
220,
220,
220,
220,
220,
6818,
2859,
10951,
13,
8367,
13,
8189,
6624,
4049,
62,
8189,
198,
220,
220,
220,
220,
220,
220,
220,
6818,
2722,
62,
9503,
1746,
58,
12,
16,
7131,
15,
60,
6624,
366,
6998,
2767,
1,
628,
628,
628,
628,
628,
628
] | 2.512695 | 1,024 |
from .tool.func import * | [
6738,
764,
25981,
13,
20786,
1330,
1635
] | 3.428571 | 7 |
"""
MOON PHASE CLOCK for Adafruit Matrix Portal: displays current time, lunar
phase and time of next moonrise or moonset. Requires WiFi internet access.
Written by Phil 'PaintYourDragon' Burgess for Adafruit Industries.
MIT license, all text above must be included in any redistribution.
BDF fonts from the X.Org project. Startup 'splash' images should not be
included in derivative projects, thanks. Tall splash images licensed from
123RF.com, wide splash images used with permission of artist Lew Lashmit
([email protected]). Rawr!
"""
# pylint: disable=import-error
import gc
import time
import math
import json
import board
import busio
import displayio
from rtc import RTC
from adafruit_matrixportal.network import Network
from adafruit_matrixportal.matrix import Matrix
from adafruit_bitmap_font import bitmap_font
import adafruit_display_text.label
import adafruit_lis3dh
try:
from secrets import secrets
except ImportError:
print('WiFi secrets are kept in secrets.py, please add them there!')
raise
# CONFIGURABLE SETTINGS ----------------------------------------------------
TWELVE_HOUR = True # If set, use 12-hour time vs 24-hour (e.g. 3:00 vs 15:00)
COUNTDOWN = False # If set, show time to (vs time of) next rise/set event
MONTH_DAY = True # If set, use MM/DD vs DD/MM (e.g. 31/12 vs 12/31)
BITPLANES = 6 # Ideally 6, but can set lower if RAM is tight
# SOME UTILITY FUNCTIONS AND CLASSES ---------------------------------------
def parse_time(timestring, is_dst=-1):
""" Given a string of the format YYYY-MM-DDTHH:MM:SS.SS-HH:MM (and
optionally a DST flag), convert to and return an equivalent
time.struct_time (strptime() isn't available here). Calling function
can use time.mktime() on result if epoch seconds is needed instead.
Time string is assumed local time; UTC offset is ignored. If seconds
value includes a decimal fraction it's ignored.
"""
date_time = timestring.split('T') # Separate into date and time
year_month_day = date_time[0].split('-') # Separate time into Y/M/D
hour_minute_second = date_time[1].split('+')[0].split('-')[0].split(':')
return time.struct_time(int(year_month_day[0]),
int(year_month_day[1]),
int(year_month_day[2]),
int(hour_minute_second[0]),
int(hour_minute_second[1]),
int(hour_minute_second[2].split('.')[0]),
-1, -1, is_dst)
def update_time(timezone=None):
""" Update system date/time from WorldTimeAPI public server;
no account required. Pass in time zone string
(http://worldtimeapi.org/api/timezone for list)
or None to use IP geolocation. Returns current local time as a
time.struct_time and UTC offset as string. This may throw an
exception on fetch_data() - it is NOT CAUGHT HERE, should be
handled in the calling code because different behaviors may be
needed in different situations (e.g. reschedule for later).
"""
if timezone: # Use timezone api
time_url = 'http://worldtimeapi.org/api/timezone/' + timezone
else: # Use IP geolocation
time_url = 'http://worldtimeapi.org/api/ip'
time_data = NETWORK.fetch_data(time_url,
json_path=[['datetime'], ['dst'],
['utc_offset']])
time_struct = parse_time(time_data[0], time_data[1])
RTC().datetime = time_struct
return time_struct, time_data[2]
def hh_mm(time_struct):
""" Given a time.struct_time, return a string as H:MM or HH:MM, either
12- or 24-hour style depending on global TWELVE_HOUR setting.
This is ONLY for 'clock time,' NOT for countdown time, which is
handled separately in the one spot where it's needed.
"""
if TWELVE_HOUR:
if time_struct.tm_hour > 12:
hour_string = str(time_struct.tm_hour - 12) # 13-23 -> 1-11 (pm)
elif time_struct.tm_hour > 0:
hour_string = str(time_struct.tm_hour) # 1-12
else:
hour_string = '12' # 0 -> 12 (am)
else:
hour_string = '{0:0>2}'.format(time_struct.tm_hour)
return hour_string + ':' + '{0:0>2}'.format(time_struct.tm_min)
# pylint: disable=too-few-public-methods
class MoonData():
""" Class holding lunar data for a given day (00:00:00 to 23:59:59).
App uses two of these -- one for the current day, and one for the
following day -- then some interpolations and such can be made.
Elements include:
age : Moon phase 'age' at midnight (start of period)
expressed from 0.0 (new moon) through 0.5 (full moon)
to 1.0 (next new moon).
midnight : Epoch time in seconds @ midnight (start of period).
rise : Epoch time of moon rise within this 24-hour period.
set : Epoch time of moon set within this 24-hour period.
"""
def __init__(self, datetime, hours_ahead, utc_offset):
""" Initialize MoonData object elements (see above) from a
time.struct_time, hours to skip ahead (typically 0 or 24),
and a UTC offset (as a string) and a query to the MET Norway
Sunrise API (also provides lunar data), documented at:
https://api.met.no/weatherapi/sunrise/2.0/documentation
"""
if hours_ahead:
# Can't change attribute in datetime struct, need to create
# a new one which will roll the date ahead as needed. Convert
# to epoch seconds and back for the offset to work
datetime = time.localtime(time.mktime(time.struct_time(
datetime.tm_year,
datetime.tm_mon,
datetime.tm_mday,
datetime.tm_hour + hours_ahead,
datetime.tm_min,
datetime.tm_sec,
-1, -1, -1)))
# strftime() not available here
url = ('https://api.met.no/weatherapi/sunrise/2.0/.json?lat=' +
str(LATITUDE) + '&lon=' + str(LONGITUDE) +
'&date=' + str(datetime.tm_year) + '-' +
'{0:0>2}'.format(datetime.tm_mon) + '-' +
'{0:0>2}'.format(datetime.tm_mday) +
'&offset=' + utc_offset)
print('Fetching moon data via', url)
# pylint: disable=bare-except
for _ in range(5): # Retries
try:
full_data = json.loads(NETWORK.fetch_data(url))
moon_data = full_data['location']['time'][0]
#print(moon_data)
# Reconstitute JSON data into the elements we need
self.age = float(moon_data['moonphase']['value']) / 100
self.midnight = time.mktime(parse_time(
moon_data['moonphase']['time']))
if 'moonrise' in moon_data:
self.rise = time.mktime(
parse_time(moon_data['moonrise']['time']))
else:
self.rise = None
if 'moonset' in moon_data:
self.set = time.mktime(
parse_time(moon_data['moonset']['time']))
else:
self.set = None
return # Success!
except:
# Moon server error (maybe), try again after 15 seconds.
# (Might be a memory error, that should be handled different)
time.sleep(15)
# ONE-TIME INITIALIZATION --------------------------------------------------
MATRIX = Matrix(bit_depth=BITPLANES)
DISPLAY = MATRIX.display
ACCEL = adafruit_lis3dh.LIS3DH_I2C(busio.I2C(board.SCL, board.SDA),
address=0x19)
_ = ACCEL.acceleration # Dummy reading to blow out any startup residue
time.sleep(0.1)
DISPLAY.rotation = (int(((math.atan2(-ACCEL.acceleration.y,
-ACCEL.acceleration.x) + math.pi) /
(math.pi * 2) + 0.875) * 4) % 4) * 90
LARGE_FONT = bitmap_font.load_font('/fonts/helvB12.bdf')
SMALL_FONT = bitmap_font.load_font('/fonts/helvR10.bdf')
SYMBOL_FONT = bitmap_font.load_font('/fonts/6x10.bdf')
LARGE_FONT.load_glyphs('0123456789:')
SMALL_FONT.load_glyphs('0123456789:/.%')
SYMBOL_FONT.load_glyphs('\u21A5\u21A7')
# Display group is set up once, then we just shuffle items around later.
# Order of creation here determines their stacking order.
GROUP = displayio.Group(max_size=10)
# Element 0 is a stand-in item, later replaced with the moon phase bitmap
# pylint: disable=bare-except
try:
FILENAME = 'moon/splash-' + str(DISPLAY.rotation) + '.bmp'
BITMAP = displayio.OnDiskBitmap(open(FILENAME, 'rb'))
TILE_GRID = displayio.TileGrid(BITMAP,
pixel_shader=displayio.ColorConverter(),)
GROUP.append(TILE_GRID)
except:
GROUP.append(adafruit_display_text.label.Label(SMALL_FONT, color=0xFF0000,
text='AWOO'))
GROUP[0].x = (DISPLAY.width - GROUP[0].bounding_box[2] + 1) // 2
GROUP[0].y = DISPLAY.height // 2 - 1
# Elements 1-4 are an outline around the moon percentage -- text labels
# offset by 1 pixel up/down/left/right. Initial position is off the matrix,
# updated on first refresh. Initial text value must be long enough for
# longest anticipated string later.
for i in range(4):
GROUP.append(adafruit_display_text.label.Label(SMALL_FONT, color=0,
text='99.9%', y=-99))
# Element 5 is the moon percentage (on top of the outline labels)
GROUP.append(adafruit_display_text.label.Label(SMALL_FONT, color=0xFFFF00,
text='99.9%', y=-99))
# Element 6 is the current time
GROUP.append(adafruit_display_text.label.Label(LARGE_FONT, color=0x808080,
text='12:00', y=-99))
# Element 7 is the current date
GROUP.append(adafruit_display_text.label.Label(SMALL_FONT, color=0x808080,
text='12/31', y=-99))
# Element 8 is a symbol indicating next rise or set
GROUP.append(adafruit_display_text.label.Label(SYMBOL_FONT, color=0x00FF00,
text='x', y=-99))
# Element 9 is the time of (or time to) next rise/set event
GROUP.append(adafruit_display_text.label.Label(SMALL_FONT, color=0x00FF00,
text='12:00', y=-99))
DISPLAY.show(GROUP)
NETWORK = Network(status_neopixel=board.NEOPIXEL, debug=False)
NETWORK.connect()
# LATITUDE, LONGITUDE, TIMEZONE are set up once, constant over app lifetime
# Fetch latitude/longitude from secrets.py. If not present, use
# IP geolocation. This only needs to be done once, at startup!
try:
LATITUDE = secrets['latitude']
LONGITUDE = secrets['longitude']
print('Using stored geolocation: ', LATITUDE, LONGITUDE)
except KeyError:
LATITUDE, LONGITUDE = (
NETWORK.fetch_data('http://www.geoplugin.net/json.gp',
json_path=[['geoplugin_latitude'],
['geoplugin_longitude']]))
print('Using IP geolocation: ', LATITUDE, LONGITUDE)
# Load time zone string from secrets.py, else IP geolocation for this too
# (http://worldtimeapi.org/api/timezone for list).
try:
TIMEZONE = secrets['timezone'] # e.g. 'America/New_York'
except:
TIMEZONE = None # IP geolocation
# Set initial clock time, also fetch initial UTC offset while
# here (NOT stored in secrets.py as it may change with DST).
# pylint: disable=bare-except
try:
DATETIME, UTC_OFFSET = update_time(TIMEZONE)
except:
DATETIME, UTC_OFFSET = time.localtime(), '+00:00'
LAST_SYNC = time.mktime(DATETIME)
# Poll server for moon data for current 24-hour period and +24 ahead
PERIOD = []
for DAY in range(2):
PERIOD.append(MoonData(DATETIME, DAY * 24, UTC_OFFSET))
# PERIOD[0] is the current 24-hour time period we're in. PERIOD[1] is the
# following 24 hours. Data is shifted down and new data fetched as days
# expire. Thought we might need a PERIOD[2] for certain circumstances but
# it appears not, that's changed easily enough if needed.
# MAIN LOOP ----------------------------------------------------------------
while True:
gc.collect()
NOW = time.time() # Current epoch time in seconds
# Sync with time server every ~12 hours
if NOW - LAST_SYNC > 12 * 60 * 60:
try:
DATETIME, UTC_OFFSET = update_time(TIMEZONE)
LAST_SYNC = time.mktime(DATETIME)
continue # Time may have changed; refresh NOW value
except:
# update_time() can throw an exception if time server doesn't
# respond. That's OK, keep running with our current time, and
# push sync time ahead to retry in 30 minutes (don't overwhelm
# the server with repeated queries).
LAST_SYNC += 30 * 60 # 30 minutes -> seconds
# If PERIOD has expired, move data down and fetch new +24-hour data
if NOW >= PERIOD[1].midnight:
PERIOD[0] = PERIOD[1]
PERIOD[1] = MoonData(time.localtime(), 24, UTC_OFFSET)
# Determine weighting of tomorrow's phase vs today's, using current time
RATIO = ((NOW - PERIOD[0].midnight) /
(PERIOD[1].midnight - PERIOD[0].midnight))
# Determine moon phase 'age'
# 0.0 = new moon
# 0.25 = first quarter
# 0.5 = full moon
# 0.75 = last quarter
# 1.0 = new moon
if PERIOD[0].age < PERIOD[1].age:
AGE = (PERIOD[0].age +
(PERIOD[1].age - PERIOD[0].age) * RATIO) % 1.0
else: # Handle age wraparound (1.0 -> 0.0)
# If tomorrow's age is less than today's, it indicates a new moon
# crossover. Add 1 to tomorrow's age when computing age delta.
AGE = (PERIOD[0].age +
(PERIOD[1].age + 1 - PERIOD[0].age) * RATIO) % 1.0
# AGE can be used for direct lookup to moon bitmap (0 to 99) -- these
# images are pre-rendered for a linear timescale (solar terminator moves
# nonlinearly across sphere).
FRAME = int(AGE * 100) % 100 # Bitmap 0 to 99
# Then use some trig to get percentage lit
if AGE <= 0.5: # New -> first quarter -> full
PERCENT = (1 - math.cos(AGE * 2 * math.pi)) * 50
else: # Full -> last quarter -> new
PERCENT = (1 + math.cos((AGE - 0.5) * 2 * math.pi)) * 50
# Find next rise/set event, complicated by the fact that some 24-hour
# periods might not have one or the other (but usually do) due to the
# Moon rising ~50 mins later each day. This uses a brute force approach,
# working backwards through the time periods to locate rise/set events
# that A) exist in that 24-hour period (are not None), B) are still in
# the future, and C) are closer than the last guess. What's left at the
# end is the next rise or set (and the inverse of the event type tells
# us whether Moon's currently risen or not).
NEXT_EVENT = PERIOD[1].midnight + 100000 # Force first match
for DAY in reversed(PERIOD):
if DAY.rise and NEXT_EVENT >= DAY.rise >= NOW:
NEXT_EVENT = DAY.rise
RISEN = False
if DAY.set and NEXT_EVENT >= DAY.set >= NOW:
NEXT_EVENT = DAY.set
RISEN = True
if DISPLAY.rotation in (0, 180): # Horizontal 'landscape' orientation
CENTER_X = 48 # Text along right
MOON_Y = 0 # Moon at left
TIME_Y = 6 # Time at top right
EVENT_Y = 26 # Rise/set at bottom right
else: # Vertical 'portrait' orientation
CENTER_X = 16 # Text down center
if RISEN:
MOON_Y = 0 # Moon at top
EVENT_Y = 38 # Rise/set in middle
TIME_Y = 49 # Time/date at bottom
else:
TIME_Y = 6 # Time/date at top
EVENT_Y = 26 # Rise/set in middle
MOON_Y = 32 # Moon at bottom
print()
# Update moon image (GROUP[0])
FILENAME = 'moon/moon' + '{0:0>2}'.format(FRAME) + '.bmp'
BITMAP = displayio.OnDiskBitmap(open(FILENAME, 'rb'))
TILE_GRID = displayio.TileGrid(BITMAP,
pixel_shader=displayio.ColorConverter(),)
TILE_GRID.x = 0
TILE_GRID.y = MOON_Y
GROUP[0] = TILE_GRID
# Update percent value (5 labels: GROUP[1-4] for outline, [5] for text)
if PERCENT >= 99.95:
STRING = '100%'
else:
STRING = '{:.1f}'.format(PERCENT + 0.05) + '%'
print(NOW, STRING, 'full')
# Set element 5 first, use its size and position for setting others
GROUP[5].text = STRING
GROUP[5].x = 16 - GROUP[5].bounding_box[2] // 2
GROUP[5].y = MOON_Y + 16
for _ in range(1, 5):
GROUP[_].text = GROUP[5].text
GROUP[1].x, GROUP[1].y = GROUP[5].x, GROUP[5].y - 1 # Up 1 pixel
GROUP[2].x, GROUP[2].y = GROUP[5].x - 1, GROUP[5].y # Left
GROUP[3].x, GROUP[3].y = GROUP[5].x + 1, GROUP[5].y # Right
GROUP[4].x, GROUP[4].y = GROUP[5].x, GROUP[5].y + 1 # Down
# Update next-event time (GROUP[8] and [9])
# Do this before time because we need uncorrupted NOW value
EVENT_TIME = time.localtime(NEXT_EVENT) # Convert to struct for later
if COUNTDOWN: # Show NEXT_EVENT as countdown to event
NEXT_EVENT -= NOW # Time until (vs time of) next rise/set
MINUTES = NEXT_EVENT // 60
STRING = str(MINUTES // 60) + ':' + '{0:0>2}'.format(MINUTES % 60)
else: # Show NEXT_EVENT in clock time
STRING = hh_mm(EVENT_TIME)
GROUP[9].text = STRING
XPOS = CENTER_X - (GROUP[9].bounding_box[2] + 6) // 2
GROUP[8].x = XPOS
if RISEN: # Next event is SET
GROUP[8].text = '\u21A7' # Downwards arrow from bar
GROUP[8].y = EVENT_Y - 2
print('Sets:', STRING)
else: # Next event is RISE
GROUP[8].text = '\u21A5' # Upwards arrow from bar
GROUP[8].y = EVENT_Y - 1
print('Rises:', STRING)
GROUP[9].x = XPOS + 6
GROUP[9].y = EVENT_Y
# Show event time in green if a.m., amber if p.m.
GROUP[8].color = GROUP[9].color = (0x00FF00 if EVENT_TIME.tm_hour < 12
else 0xC04000)
# Update time (GROUP[6]) and date (GROUP[7])
NOW = time.localtime()
STRING = hh_mm(NOW)
GROUP[6].text = STRING
GROUP[6].x = CENTER_X - GROUP[6].bounding_box[2] // 2
GROUP[6].y = TIME_Y
if MONTH_DAY:
STRING = str(NOW.tm_mon) + '/' + str(NOW.tm_mday)
else:
STRING = str(NOW.tm_mday) + '/' + str(NOW.tm_mon)
GROUP[7].text = STRING
GROUP[7].x = CENTER_X - GROUP[7].bounding_box[2] // 2
GROUP[7].y = TIME_Y + 10
DISPLAY.refresh() # Force full repaint (splash screen sometimes sticks)
time.sleep(5)
| [
37811,
198,
11770,
1340,
9370,
11159,
7852,
11290,
329,
1215,
1878,
4872,
24936,
25663,
25,
11298,
1459,
640,
11,
25572,
198,
40715,
290,
640,
286,
1306,
8824,
17163,
393,
31093,
316,
13,
26848,
24904,
5230,
1895,
13,
198,
198,
25354,
416,
4543,
705,
47,
2913,
7120,
17808,
6,
46744,
329,
1215,
1878,
4872,
20171,
13,
198,
36393,
5964,
11,
477,
2420,
2029,
1276,
307,
3017,
287,
597,
41425,
13,
198,
198,
33,
8068,
26806,
422,
262,
1395,
13,
46808,
1628,
13,
40472,
705,
22018,
1077,
6,
4263,
815,
407,
307,
198,
259,
10341,
287,
27255,
4493,
11,
5176,
13,
22676,
22870,
4263,
11971,
422,
198,
10163,
32754,
13,
785,
11,
3094,
22870,
4263,
973,
351,
7170,
286,
6802,
8260,
47137,
2781,
198,
7,
49663,
70,
19725,
31,
14816,
13,
785,
737,
16089,
81,
0,
198,
37811,
198,
198,
2,
279,
2645,
600,
25,
15560,
28,
11748,
12,
18224,
198,
11748,
308,
66,
198,
11748,
640,
198,
11748,
10688,
198,
11748,
33918,
198,
11748,
3096,
198,
11748,
1323,
952,
198,
11748,
3359,
952,
198,
6738,
374,
23047,
1330,
371,
4825,
198,
6738,
512,
1878,
4872,
62,
6759,
8609,
634,
282,
13,
27349,
1330,
7311,
198,
6738,
512,
1878,
4872,
62,
6759,
8609,
634,
282,
13,
6759,
8609,
1330,
24936,
198,
6738,
512,
1878,
4872,
62,
2545,
8899,
62,
10331,
1330,
1643,
8899,
62,
10331,
198,
11748,
512,
1878,
4872,
62,
13812,
62,
5239,
13,
18242,
198,
11748,
512,
1878,
4872,
62,
27999,
18,
34985,
198,
198,
28311,
25,
198,
220,
220,
220,
422,
13141,
1330,
13141,
198,
16341,
17267,
12331,
25,
198,
220,
220,
220,
3601,
10786,
31294,
10547,
13141,
389,
4030,
287,
13141,
13,
9078,
11,
3387,
751,
606,
612,
0,
11537,
198,
220,
220,
220,
5298,
198,
198,
2,
25626,
45570,
19146,
25823,
51,
20754,
20368,
19351,
198,
198,
34551,
3698,
6089,
62,
39,
11698,
796,
6407,
1303,
1002,
900,
11,
779,
1105,
12,
9769,
640,
3691,
1987,
12,
9769,
357,
68,
13,
70,
13,
513,
25,
405,
3691,
1315,
25,
405,
8,
198,
34,
28270,
41925,
796,
10352,
220,
1303,
1002,
900,
11,
905,
640,
284,
357,
14259,
640,
286,
8,
1306,
4485,
14,
2617,
1785,
198,
27857,
4221,
62,
26442,
796,
6407,
220,
220,
1303,
1002,
900,
11,
779,
20806,
14,
16458,
3691,
20084,
14,
12038,
357,
68,
13,
70,
13,
3261,
14,
1065,
3691,
1105,
14,
3132,
8,
198,
26094,
6489,
1565,
1546,
796,
718,
220,
220,
220,
220,
220,
1303,
40067,
718,
11,
475,
460,
900,
2793,
611,
13931,
318,
5381,
628,
198,
2,
41670,
19255,
4146,
9050,
29397,
4177,
11053,
5357,
42715,
1546,
20368,
26866,
198,
198,
4299,
21136,
62,
2435,
7,
16514,
395,
1806,
11,
318,
62,
67,
301,
10779,
16,
2599,
198,
220,
220,
220,
37227,
11259,
257,
4731,
286,
262,
5794,
575,
26314,
56,
12,
12038,
12,
16458,
4221,
39,
25,
12038,
25,
5432,
13,
5432,
12,
16768,
25,
12038,
357,
392,
198,
220,
220,
220,
220,
220,
220,
220,
42976,
257,
360,
2257,
6056,
828,
10385,
284,
290,
1441,
281,
7548,
198,
220,
220,
220,
220,
220,
220,
220,
640,
13,
7249,
62,
2435,
357,
2536,
457,
524,
3419,
2125,
470,
1695,
994,
737,
32677,
2163,
198,
220,
220,
220,
220,
220,
220,
220,
460,
779,
640,
13,
28015,
2435,
3419,
319,
1255,
611,
36835,
4201,
318,
2622,
2427,
13,
198,
220,
220,
220,
220,
220,
220,
220,
3862,
4731,
318,
9672,
1957,
640,
26,
18119,
11677,
318,
9514,
13,
1002,
4201,
198,
220,
220,
220,
220,
220,
220,
220,
1988,
3407,
257,
32465,
13390,
340,
338,
9514,
13,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
3128,
62,
2435,
796,
4628,
395,
1806,
13,
35312,
10786,
51,
11537,
220,
220,
220,
220,
220,
220,
220,
1303,
8621,
30748,
656,
3128,
290,
640,
198,
220,
220,
220,
614,
62,
8424,
62,
820,
796,
3128,
62,
2435,
58,
15,
4083,
35312,
10786,
12,
11537,
1303,
8621,
30748,
640,
656,
575,
14,
44,
14,
35,
198,
220,
220,
220,
1711,
62,
11374,
62,
12227,
796,
3128,
62,
2435,
58,
16,
4083,
35312,
10786,
10,
11537,
58,
15,
4083,
35312,
10786,
12,
11537,
58,
15,
4083,
35312,
7,
10354,
11537,
198,
220,
220,
220,
1441,
640,
13,
7249,
62,
2435,
7,
600,
7,
1941,
62,
8424,
62,
820,
58,
15,
46570,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
493,
7,
1941,
62,
8424,
62,
820,
58,
16,
46570,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
493,
7,
1941,
62,
8424,
62,
820,
58,
17,
46570,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
493,
7,
9769,
62,
11374,
62,
12227,
58,
15,
46570,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
493,
7,
9769,
62,
11374,
62,
12227,
58,
16,
46570,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
493,
7,
9769,
62,
11374,
62,
12227,
58,
17,
4083,
35312,
10786,
2637,
38381,
15,
46570,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
532,
16,
11,
532,
16,
11,
318,
62,
67,
301,
8,
628,
198,
4299,
4296,
62,
2435,
7,
2435,
11340,
28,
14202,
2599,
198,
220,
220,
220,
37227,
10133,
1080,
3128,
14,
2435,
422,
2159,
7575,
17614,
1171,
4382,
26,
198,
220,
220,
220,
220,
220,
220,
220,
645,
1848,
2672,
13,
6251,
287,
640,
6516,
4731,
198,
220,
220,
220,
220,
220,
220,
220,
357,
4023,
1378,
6894,
2435,
15042,
13,
2398,
14,
15042,
14,
2435,
11340,
329,
1351,
8,
198,
220,
220,
220,
220,
220,
220,
220,
393,
6045,
284,
779,
6101,
4903,
349,
5040,
13,
16409,
1459,
1957,
640,
355,
257,
198,
220,
220,
220,
220,
220,
220,
220,
640,
13,
7249,
62,
2435,
290,
18119,
11677,
355,
4731,
13,
770,
743,
3714,
281,
198,
220,
220,
220,
220,
220,
220,
220,
6631,
319,
21207,
62,
7890,
3419,
532,
340,
318,
5626,
7257,
7340,
6535,
15698,
11,
815,
307,
198,
220,
220,
220,
220,
220,
220,
220,
12118,
287,
262,
4585,
2438,
780,
1180,
14301,
743,
307,
198,
220,
220,
220,
220,
220,
220,
220,
2622,
287,
1180,
7445,
357,
68,
13,
70,
13,
581,
2395,
5950,
329,
1568,
737,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
611,
640,
11340,
25,
1303,
5765,
640,
11340,
40391,
198,
220,
220,
220,
220,
220,
220,
220,
640,
62,
6371,
796,
705,
4023,
1378,
6894,
2435,
15042,
13,
2398,
14,
15042,
14,
2435,
11340,
14,
6,
1343,
640,
11340,
198,
220,
220,
220,
2073,
25,
1303,
5765,
6101,
4903,
349,
5040,
198,
220,
220,
220,
220,
220,
220,
220,
640,
62,
6371,
796,
705,
4023,
1378,
6894,
2435,
15042,
13,
2398,
14,
15042,
14,
541,
6,
628,
220,
220,
220,
640,
62,
7890,
796,
49791,
13,
69,
7569,
62,
7890,
7,
2435,
62,
6371,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
33918,
62,
6978,
41888,
17816,
19608,
8079,
6,
4357,
37250,
67,
301,
6,
4357,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
37250,
315,
66,
62,
28968,
6,
11907,
8,
198,
220,
220,
220,
640,
62,
7249,
796,
21136,
62,
2435,
7,
2435,
62,
7890,
58,
15,
4357,
640,
62,
7890,
58,
16,
12962,
198,
220,
220,
220,
371,
4825,
22446,
19608,
8079,
796,
640,
62,
7249,
198,
220,
220,
220,
1441,
640,
62,
7249,
11,
640,
62,
7890,
58,
17,
60,
628,
198,
4299,
289,
71,
62,
3020,
7,
2435,
62,
7249,
2599,
198,
220,
220,
220,
37227,
11259,
257,
640,
13,
7249,
62,
2435,
11,
1441,
257,
4731,
355,
367,
25,
12038,
393,
47138,
25,
12038,
11,
2035,
198,
220,
220,
220,
220,
220,
220,
220,
1105,
12,
393,
1987,
12,
9769,
3918,
6906,
319,
3298,
17306,
3698,
6089,
62,
39,
11698,
4634,
13,
198,
220,
220,
220,
220,
220,
220,
220,
770,
318,
22224,
329,
705,
15750,
640,
4032,
5626,
329,
33970,
640,
11,
543,
318,
198,
220,
220,
220,
220,
220,
220,
220,
12118,
13869,
287,
262,
530,
4136,
810,
340,
338,
2622,
13,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
611,
17306,
3698,
6089,
62,
39,
11698,
25,
198,
220,
220,
220,
220,
220,
220,
220,
611,
640,
62,
7249,
13,
17209,
62,
9769,
1875,
1105,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1711,
62,
8841,
796,
965,
7,
2435,
62,
7249,
13,
17209,
62,
9769,
532,
1105,
8,
1303,
1511,
12,
1954,
4613,
352,
12,
1157,
357,
4426,
8,
198,
220,
220,
220,
220,
220,
220,
220,
1288,
361,
640,
62,
7249,
13,
17209,
62,
9769,
1875,
657,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1711,
62,
8841,
796,
965,
7,
2435,
62,
7249,
13,
17209,
62,
9769,
8,
1303,
352,
12,
1065,
198,
220,
220,
220,
220,
220,
220,
220,
2073,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1711,
62,
8841,
796,
705,
1065,
6,
1303,
657,
4613,
1105,
357,
321,
8,
198,
220,
220,
220,
2073,
25,
198,
220,
220,
220,
220,
220,
220,
220,
1711,
62,
8841,
796,
705,
90,
15,
25,
15,
29,
17,
92,
4458,
18982,
7,
2435,
62,
7249,
13,
17209,
62,
9769,
8,
198,
220,
220,
220,
1441,
1711,
62,
8841,
1343,
705,
32105,
1343,
705,
90,
15,
25,
15,
29,
17,
92,
4458,
18982,
7,
2435,
62,
7249,
13,
17209,
62,
1084,
8,
628,
198,
2,
279,
2645,
600,
25,
15560,
28,
18820,
12,
32146,
12,
11377,
12,
24396,
82,
198,
4871,
6869,
6601,
33529,
198,
220,
220,
220,
37227,
5016,
4769,
25572,
1366,
329,
257,
1813,
1110,
357,
405,
25,
405,
25,
405,
284,
2242,
25,
3270,
25,
3270,
737,
198,
220,
220,
220,
220,
220,
220,
220,
2034,
3544,
734,
286,
777,
1377,
530,
329,
262,
1459,
1110,
11,
290,
530,
329,
262,
198,
220,
220,
220,
220,
220,
220,
220,
1708,
1110,
1377,
788,
617,
39555,
602,
290,
884,
460,
307,
925,
13,
198,
220,
220,
220,
220,
220,
220,
220,
26632,
2291,
25,
198,
220,
220,
220,
220,
220,
220,
220,
2479,
220,
220,
220,
220,
220,
1058,
6869,
7108,
705,
496,
6,
379,
15896,
357,
9688,
286,
2278,
8,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
6241,
422,
657,
13,
15,
357,
3605,
8824,
8,
832,
657,
13,
20,
357,
12853,
8824,
8,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
284,
352,
13,
15,
357,
19545,
649,
8824,
737,
198,
220,
220,
220,
220,
220,
220,
220,
15896,
1058,
4551,
5374,
640,
287,
4201,
2488,
15896,
357,
9688,
286,
2278,
737,
198,
220,
220,
220,
220,
220,
220,
220,
4485,
220,
220,
220,
220,
1058,
4551,
5374,
640,
286,
8824,
4485,
1626,
428,
1987,
12,
9769,
2278,
13,
198,
220,
220,
220,
220,
220,
220,
220,
900,
220,
220,
220,
220,
220,
1058,
4551,
5374,
640,
286,
8824,
900,
1626,
428,
1987,
12,
9769,
2278,
13,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
825,
11593,
15003,
834,
7,
944,
11,
4818,
8079,
11,
2250,
62,
38204,
11,
3384,
66,
62,
28968,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
20768,
1096,
6869,
6601,
2134,
4847,
357,
3826,
2029,
8,
422,
257,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
640,
13,
7249,
62,
2435,
11,
2250,
284,
14267,
4058,
357,
48126,
657,
393,
1987,
828,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
290,
257,
18119,
11677,
357,
292,
257,
4731,
8,
290,
257,
12405,
284,
262,
31243,
15238,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
45023,
7824,
357,
14508,
3769,
25572,
1366,
828,
12395,
379,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
3740,
1378,
15042,
13,
4164,
13,
3919,
14,
23563,
15042,
14,
19155,
17163,
14,
17,
13,
15,
14,
22897,
341,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
611,
2250,
62,
38204,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1303,
1680,
470,
1487,
11688,
287,
4818,
8079,
2878,
11,
761,
284,
2251,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1303,
257,
649,
530,
543,
481,
4836,
262,
3128,
4058,
355,
2622,
13,
38240,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1303,
284,
36835,
4201,
290,
736,
329,
262,
11677,
284,
670,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
4818,
8079,
796,
640,
13,
12001,
2435,
7,
2435,
13,
28015,
2435,
7,
2435,
13,
7249,
62,
2435,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
4818,
8079,
13,
17209,
62,
1941,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
4818,
8079,
13,
17209,
62,
2144,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
4818,
8079,
13,
17209,
62,
76,
820,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
4818,
8079,
13,
17209,
62,
9769,
1343,
2250,
62,
38204,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
4818,
8079,
13,
17209,
62,
1084,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
4818,
8079,
13,
17209,
62,
2363,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
532,
16,
11,
532,
16,
11,
532,
16,
22305,
198,
220,
220,
220,
220,
220,
220,
220,
1303,
965,
31387,
3419,
407,
1695,
994,
198,
220,
220,
220,
220,
220,
220,
220,
19016,
796,
19203,
5450,
1378,
15042,
13,
4164,
13,
3919,
14,
23563,
15042,
14,
19155,
17163,
14,
17,
13,
15,
11757,
17752,
30,
15460,
11639,
1343,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
965,
7,
43,
1404,
2043,
52,
7206,
8,
1343,
705,
5,
14995,
11639,
1343,
965,
7,
43,
18494,
2043,
52,
7206,
8,
1343,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
5,
4475,
11639,
1343,
965,
7,
19608,
8079,
13,
17209,
62,
1941,
8,
1343,
705,
19355,
1343,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
90,
15,
25,
15,
29,
17,
92,
4458,
18982,
7,
19608,
8079,
13,
17209,
62,
2144,
8,
1343,
705,
19355,
1343,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
90,
15,
25,
15,
29,
17,
92,
4458,
18982,
7,
19608,
8079,
13,
17209,
62,
76,
820,
8,
1343,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
5,
28968,
11639,
1343,
3384,
66,
62,
28968,
8,
198,
220,
220,
220,
220,
220,
220,
220,
3601,
10786,
37,
7569,
278,
8824,
1366,
2884,
3256,
19016,
8,
198,
220,
220,
220,
220,
220,
220,
220,
1303,
279,
2645,
600,
25,
15560,
28,
49382,
12,
16341,
198,
220,
220,
220,
220,
220,
220,
220,
329,
4808,
287,
2837,
7,
20,
2599,
1303,
4990,
1678,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1949,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1336,
62,
7890,
796,
33918,
13,
46030,
7,
12884,
33249,
13,
69,
7569,
62,
7890,
7,
6371,
4008,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
8824,
62,
7890,
796,
1336,
62,
7890,
17816,
24886,
6,
7131,
6,
2435,
6,
7131,
15,
60,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1303,
4798,
7,
22977,
62,
7890,
8,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1303,
23419,
301,
3678,
19449,
1366,
656,
262,
4847,
356,
761,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
496,
796,
12178,
7,
22977,
62,
7890,
17816,
22977,
40715,
6,
7131,
6,
8367,
6,
12962,
1220,
1802,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
13602,
3847,
796,
640,
13,
28015,
2435,
7,
29572,
62,
2435,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
8824,
62,
7890,
17816,
22977,
40715,
6,
7131,
6,
2435,
20520,
4008,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
611,
705,
22977,
17163,
6,
287,
8824,
62,
7890,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
17163,
796,
640,
13,
28015,
2435,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
21136,
62,
2435,
7,
22977,
62,
7890,
17816,
22977,
17163,
6,
7131,
6,
2435,
20520,
4008,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2073,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
17163,
796,
6045,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
611,
705,
5908,
684,
316,
6,
287,
8824,
62,
7890,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
2617,
796,
640,
13,
28015,
2435,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
21136,
62,
2435,
7,
22977,
62,
7890,
17816,
5908,
684,
316,
6,
7131,
6,
2435,
20520,
4008,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2073,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
2617,
796,
6045,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1441,
1303,
16282,
0,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2845,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1303,
6869,
4382,
4049,
357,
25991,
828,
1949,
757,
706,
1315,
4201,
13,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1303,
357,
44,
432,
307,
257,
4088,
4049,
11,
326,
815,
307,
12118,
1180,
8,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
640,
13,
42832,
7,
1314,
8,
628,
198,
2,
16329,
12,
34694,
3268,
2043,
12576,
14887,
6234,
20368,
1783,
438,
198,
198,
41636,
7112,
55,
796,
24936,
7,
2545,
62,
18053,
28,
26094,
6489,
1565,
1546,
8,
198,
26288,
31519,
796,
36775,
7112,
55,
13,
13812,
198,
26861,
3698,
796,
512,
1878,
4872,
62,
27999,
18,
34985,
13,
43,
1797,
18,
41473,
62,
40,
17,
34,
7,
10885,
952,
13,
40,
17,
34,
7,
3526,
13,
50,
5097,
11,
3096,
13,
50,
5631,
828,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2209,
28,
15,
87,
1129,
8,
198,
62,
796,
15859,
3698,
13,
330,
7015,
341,
1303,
360,
13513,
3555,
284,
6611,
503,
597,
13693,
35186,
198,
2435,
13,
42832,
7,
15,
13,
16,
8,
198,
26288,
31519,
13,
10599,
341,
796,
357,
600,
19510,
7,
11018,
13,
39036,
17,
32590,
26861,
3698,
13,
330,
7015,
341,
13,
88,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
532,
26861,
3698,
13,
330,
7015,
341,
13,
87,
8,
1343,
10688,
13,
14415,
8,
1220,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
357,
11018,
13,
14415,
1635,
362,
8,
1343,
657,
13,
31360,
8,
1635,
604,
8,
4064,
604,
8,
1635,
4101,
198,
198,
43,
1503,
8264,
62,
37,
35830,
796,
1643,
8899,
62,
10331,
13,
2220,
62,
10331,
10786,
14,
10331,
82,
14,
2978,
85,
33,
1065,
13,
65,
7568,
11537,
198,
12310,
7036,
62,
37,
35830,
796,
1643,
8899,
62,
10331,
13,
2220,
62,
10331,
10786,
14,
10331,
82,
14,
2978,
85,
49,
940,
13,
65,
7568,
11537,
198,
23060,
10744,
3535,
62,
37,
35830,
796,
1643,
8899,
62,
10331,
13,
2220,
62,
10331,
10786,
14,
10331,
82,
14,
21,
87,
940,
13,
65,
7568,
11537,
198,
43,
1503,
8264,
62,
37,
35830,
13,
2220,
62,
10853,
746,
82,
10786,
486,
1954,
2231,
3134,
4531,
25,
11537,
198,
12310,
7036,
62,
37,
35830,
13,
2220,
62,
10853,
746,
82,
10786,
486,
1954,
2231,
3134,
4531,
25,
11757,
4,
11537,
198,
23060,
10744,
3535,
62,
37,
35830,
13,
2220,
62,
10853,
746,
82,
10786,
59,
84,
2481,
32,
20,
59,
84,
2481,
32,
22,
11537,
198,
198,
2,
16531,
1448,
318,
900,
510,
1752,
11,
788,
356,
655,
36273,
3709,
1088,
1568,
13,
198,
2,
8284,
286,
6282,
994,
15947,
511,
41228,
1502,
13,
198,
46846,
796,
3359,
952,
13,
13247,
7,
9806,
62,
7857,
28,
940,
8,
198,
2,
11703,
657,
318,
257,
1302,
12,
259,
2378,
11,
1568,
6928,
351,
262,
8824,
7108,
1643,
8899,
198,
2,
279,
2645,
600,
25,
15560,
28,
49382,
12,
16341,
198,
28311,
25,
198,
220,
220,
220,
34020,
1677,
10067,
796,
705,
22977,
14,
22018,
1077,
19355,
1343,
965,
7,
26288,
31519,
13,
10599,
341,
8,
1343,
45302,
65,
3149,
6,
198,
220,
220,
220,
36992,
33767,
796,
3359,
952,
13,
2202,
40961,
13128,
8899,
7,
9654,
7,
46700,
1677,
10067,
11,
705,
26145,
6,
4008,
198,
220,
220,
220,
31598,
2538,
62,
10761,
2389,
796,
3359,
952,
13,
35103,
41339,
7,
26094,
33767,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
17465,
62,
1477,
5067,
28,
13812,
952,
13,
10258,
3103,
332,
353,
22784,
8,
198,
220,
220,
220,
44441,
13,
33295,
7,
25621,
2538,
62,
10761,
2389,
8,
198,
16341,
25,
198,
220,
220,
220,
44441,
13,
33295,
7,
324,
1878,
4872,
62,
13812,
62,
5239,
13,
18242,
13,
33986,
7,
12310,
7036,
62,
37,
35830,
11,
3124,
28,
15,
87,
5777,
2388,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2420,
11639,
12298,
6684,
6,
4008,
198,
220,
220,
220,
44441,
58,
15,
4083,
87,
796,
357,
26288,
31519,
13,
10394,
532,
44441,
58,
15,
4083,
7784,
278,
62,
3524,
58,
17,
60,
1343,
352,
8,
3373,
362,
198,
220,
220,
220,
44441,
58,
15,
4083,
88,
796,
13954,
31519,
13,
17015,
3373,
362,
532,
352,
198,
2,
26632,
352,
12,
19,
389,
281,
19001,
1088,
262,
8824,
5873,
1377,
2420,
14722,
198,
2,
11677,
416,
352,
17465,
510,
14,
2902,
14,
9464,
14,
3506,
13,
20768,
2292,
318,
572,
262,
17593,
11,
198,
2,
6153,
319,
717,
14976,
13,
20768,
2420,
1988,
1276,
307,
890,
1576,
329,
198,
2,
14069,
14486,
4731,
1568,
13,
198,
1640,
1312,
287,
2837,
7,
19,
2599,
198,
220,
220,
220,
44441,
13,
33295,
7,
324,
1878,
4872,
62,
13812,
62,
5239,
13,
18242,
13,
33986,
7,
12310,
7036,
62,
37,
35830,
11,
3124,
28,
15,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2420,
11639,
2079,
13,
24,
4,
3256,
331,
10779,
2079,
4008,
198,
2,
11703,
642,
318,
262,
8824,
5873,
357,
261,
1353,
286,
262,
19001,
14722,
8,
198,
46846,
13,
33295,
7,
324,
1878,
4872,
62,
13812,
62,
5239,
13,
18242,
13,
33986,
7,
12310,
7036,
62,
37,
35830,
11,
3124,
28,
15,
87,
29312,
405,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2420,
11639,
2079,
13,
24,
4,
3256,
331,
10779,
2079,
4008,
198,
2,
11703,
718,
318,
262,
1459,
640,
198,
46846,
13,
33295,
7,
324,
1878,
4872,
62,
13812,
62,
5239,
13,
18242,
13,
33986,
7,
43,
1503,
8264,
62,
37,
35830,
11,
3124,
28,
15,
87,
1795,
1795,
1795,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2420,
11639,
1065,
25,
405,
3256,
331,
10779,
2079,
4008,
198,
2,
11703,
767,
318,
262,
1459,
3128,
198,
46846,
13,
33295,
7,
324,
1878,
4872,
62,
13812,
62,
5239,
13,
18242,
13,
33986,
7,
12310,
7036,
62,
37,
35830,
11,
3124,
28,
15,
87,
1795,
1795,
1795,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2420,
11639,
1065,
14,
3132,
3256,
331,
10779,
2079,
4008,
198,
2,
11703,
807,
318,
257,
6194,
12739,
1306,
4485,
393,
900,
198,
46846,
13,
33295,
7,
324,
1878,
4872,
62,
13812,
62,
5239,
13,
18242,
13,
33986,
7,
23060,
10744,
3535,
62,
37,
35830,
11,
3124,
28,
15,
87,
405,
5777,
405,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2420,
11639,
87,
3256,
331,
10779,
2079,
4008,
198,
2,
11703,
860,
318,
262,
640,
286,
357,
273,
640,
284,
8,
1306,
4485,
14,
2617,
1785,
198,
46846,
13,
33295,
7,
324,
1878,
4872,
62,
13812,
62,
5239,
13,
18242,
13,
33986,
7,
12310,
7036,
62,
37,
35830,
11,
3124,
28,
15,
87,
405,
5777,
405,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2420,
11639,
1065,
25,
405,
3256,
331,
10779,
2079,
4008,
198,
26288,
31519,
13,
12860,
7,
46846,
8,
198,
198,
12884,
33249,
796,
7311,
7,
13376,
62,
710,
404,
7168,
28,
3526,
13,
12161,
3185,
10426,
3698,
11,
14257,
28,
25101,
8,
198,
12884,
33249,
13,
8443,
3419,
198,
198,
2,
42355,
2043,
52,
7206,
11,
44533,
2043,
52,
7206,
11,
20460,
57,
11651,
389,
900,
510,
1752,
11,
6937,
625,
598,
10869,
198,
198,
2,
376,
7569,
32477,
14,
6511,
3984,
422,
13141,
13,
9078,
13,
1002,
407,
1944,
11,
779,
198,
2,
6101,
4903,
349,
5040,
13,
770,
691,
2476,
284,
307,
1760,
1752,
11,
379,
13693,
0,
198,
28311,
25,
198,
220,
220,
220,
42355,
2043,
52,
7206,
796,
13141,
17816,
15460,
3984,
20520,
198,
220,
220,
220,
44533,
2043,
52,
7206,
796,
13141,
17816,
6511,
3984,
20520,
198,
220,
220,
220,
3601,
10786,
12814,
8574,
4903,
349,
5040,
25,
46083,
42355,
2043,
52,
7206,
11,
44533,
2043,
52,
7206,
8,
198,
16341,
7383,
12331,
25,
198,
220,
220,
220,
42355,
2043,
52,
7206,
11,
44533,
2043,
52,
7206,
796,
357,
198,
220,
220,
220,
220,
220,
220,
220,
49791,
13,
69,
7569,
62,
7890,
10786,
4023,
1378,
2503,
13,
469,
20106,
1018,
259,
13,
3262,
14,
17752,
13,
31197,
3256,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
33918,
62,
6978,
41888,
17816,
469,
20106,
1018,
259,
62,
15460,
3984,
6,
4357,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
37250,
469,
20106,
1018,
259,
62,
6511,
3984,
6,
11907,
4008,
198,
220,
220,
220,
3601,
10786,
12814,
6101,
4903,
349,
5040,
25,
46083,
42355,
2043,
52,
7206,
11,
44533,
2043,
52,
7206,
8,
198,
198,
2,
8778,
640,
6516,
4731,
422,
13141,
13,
9078,
11,
2073,
6101,
4903,
349,
5040,
329,
428,
1165,
198,
2,
357,
4023,
1378,
6894,
2435,
15042,
13,
2398,
14,
15042,
14,
2435,
11340,
329,
1351,
737,
198,
28311,
25,
198,
220,
220,
220,
20460,
57,
11651,
796,
13141,
17816,
2435,
11340,
20520,
1303,
304,
13,
70,
13,
705,
18165,
14,
3791,
62,
49278,
6,
198,
16341,
25,
198,
220,
220,
220,
20460,
57,
11651,
796,
6045,
1303,
6101,
4903,
349,
5040,
198,
198,
2,
5345,
4238,
8801,
640,
11,
635,
21207,
4238,
18119,
11677,
981,
198,
2,
994,
357,
11929,
8574,
287,
13141,
13,
9078,
355,
340,
743,
1487,
351,
360,
2257,
737,
198,
2,
279,
2645,
600,
25,
15560,
28,
49382,
12,
16341,
198,
28311,
25,
198,
220,
220,
220,
360,
1404,
2767,
12789,
11,
18119,
62,
27977,
28480,
796,
4296,
62,
2435,
7,
34694,
57,
11651,
8,
198,
16341,
25,
198,
220,
220,
220,
360,
1404,
2767,
12789,
11,
18119,
62,
27977,
28480,
796,
640,
13,
12001,
2435,
22784,
705,
10,
405,
25,
405,
6,
198,
43,
11262,
62,
23060,
7792,
796,
640,
13,
28015,
2435,
7,
35,
1404,
2767,
12789,
8,
198,
198,
2,
12868,
4382,
329,
8824,
1366,
329,
1459,
1987,
12,
9769,
2278,
290,
1343,
1731,
4058,
198,
18973,
40,
3727,
796,
17635,
198,
1640,
24644,
287,
2837,
7,
17,
2599,
198,
220,
220,
220,
19878,
40,
3727,
13,
33295,
7,
31640,
6601,
7,
35,
1404,
2767,
12789,
11,
24644,
1635,
1987,
11,
18119,
62,
27977,
28480,
4008,
198,
2,
19878,
40,
3727,
58,
15,
60,
318,
262,
1459,
1987,
12,
9769,
640,
2278,
356,
821,
287,
13,
19878,
40,
3727,
58,
16,
60,
318,
262,
198,
2,
1708,
1987,
2250,
13,
6060,
318,
14869,
866,
290,
649,
1366,
11351,
1740,
355,
1528,
198,
2,
24264,
13,
27522,
356,
1244,
761,
257,
19878,
40,
3727,
58,
17,
60,
329,
1728,
5917,
475,
198,
2,
340,
3568,
407,
11,
326,
338,
3421,
3538,
1576,
611,
2622,
13,
628,
198,
2,
8779,
1268,
17579,
3185,
16529,
198,
198,
4514,
6407,
25,
198,
220,
220,
220,
308,
66,
13,
33327,
3419,
198,
220,
220,
220,
20229,
796,
640,
13,
2435,
3419,
1303,
9236,
36835,
640,
287,
4201,
628,
220,
220,
220,
1303,
35908,
351,
640,
4382,
790,
5299,
1065,
2250,
198,
220,
220,
220,
611,
20229,
532,
41894,
62,
23060,
7792,
1875,
1105,
1635,
3126,
1635,
3126,
25,
198,
220,
220,
220,
220,
220,
220,
220,
1949,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
360,
1404,
2767,
12789,
11,
18119,
62,
27977,
28480,
796,
4296,
62,
2435,
7,
34694,
57,
11651,
8,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
41894,
62,
23060,
7792,
796,
640,
13,
28015,
2435,
7,
35,
1404,
2767,
12789,
8,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2555,
1303,
3862,
743,
423,
3421,
26,
14976,
20229,
1988,
198,
220,
220,
220,
220,
220,
220,
220,
2845,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1303,
4296,
62,
2435,
3419,
460,
3714,
281,
6631,
611,
640,
4382,
1595,
470,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1303,
3031,
13,
1320,
338,
7477,
11,
1394,
2491,
351,
674,
1459,
640,
11,
290,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1303,
4574,
17510,
640,
4058,
284,
1005,
563,
287,
1542,
2431,
357,
9099,
470,
43334,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1303,
262,
4382,
351,
5100,
20743,
737,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
41894,
62,
23060,
7792,
15853,
1542,
1635,
3126,
1303,
1542,
2431,
4613,
4201,
628,
220,
220,
220,
1303,
1002,
19878,
40,
3727,
468,
21350,
11,
1445,
1366,
866,
290,
21207,
649,
1343,
1731,
12,
9769,
1366,
198,
220,
220,
220,
611,
20229,
18189,
19878,
40,
3727,
58,
16,
4083,
13602,
3847,
25,
198,
220,
220,
220,
220,
220,
220,
220,
19878,
40,
3727,
58,
15,
60,
796,
19878,
40,
3727,
58,
16,
60,
198,
220,
220,
220,
220,
220,
220,
220,
19878,
40,
3727,
58,
16,
60,
796,
6869,
6601,
7,
2435,
13,
12001,
2435,
22784,
1987,
11,
18119,
62,
27977,
28480,
8,
628,
220,
220,
220,
1303,
45559,
3810,
3463,
278,
286,
9439,
338,
7108,
3691,
1909,
338,
11,
1262,
1459,
640,
198,
220,
220,
220,
371,
1404,
9399,
796,
14808,
45669,
532,
19878,
40,
3727,
58,
15,
4083,
13602,
3847,
8,
1220,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
357,
18973,
40,
3727,
58,
16,
4083,
13602,
3847,
532,
19878,
40,
3727,
58,
15,
4083,
13602,
3847,
4008,
198,
220,
220,
220,
1303,
45559,
3810,
8824,
7108,
705,
496,
6,
198,
220,
220,
220,
1303,
657,
13,
15,
220,
796,
649,
8824,
198,
220,
220,
220,
1303,
657,
13,
1495,
796,
717,
3860,
198,
220,
220,
220,
1303,
657,
13,
20,
220,
796,
1336,
8824,
198,
220,
220,
220,
1303,
657,
13,
2425,
796,
938,
3860,
198,
220,
220,
220,
1303,
352,
13,
15,
220,
796,
649,
8824,
198,
220,
220,
220,
611,
19878,
40,
3727,
58,
15,
4083,
496,
1279,
19878,
40,
3727,
58,
16,
4083,
496,
25,
198,
220,
220,
220,
220,
220,
220,
220,
317,
8264,
796,
357,
18973,
40,
3727,
58,
15,
4083,
496,
1343,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
357,
18973,
40,
3727,
58,
16,
4083,
496,
532,
19878,
40,
3727,
58,
15,
4083,
496,
8,
1635,
371,
1404,
9399,
8,
4064,
352,
13,
15,
198,
220,
220,
220,
2073,
25,
1303,
33141,
2479,
7917,
1845,
633,
357,
16,
13,
15,
4613,
657,
13,
15,
8,
198,
220,
220,
220,
220,
220,
220,
220,
1303,
1002,
9439,
338,
2479,
318,
1342,
621,
1909,
338,
11,
340,
9217,
257,
649,
8824,
198,
220,
220,
220,
220,
220,
220,
220,
1303,
27668,
13,
3060,
352,
284,
9439,
338,
2479,
618,
14492,
2479,
25979,
13,
198,
220,
220,
220,
220,
220,
220,
220,
317,
8264,
796,
357,
18973,
40,
3727,
58,
15,
4083,
496,
1343,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
357,
18973,
40,
3727,
58,
16,
4083,
496,
1343,
352,
532,
19878,
40,
3727,
58,
15,
4083,
496,
8,
1635,
371,
1404,
9399,
8,
4064,
352,
13,
15,
628,
220,
220,
220,
1303,
317,
8264,
460,
307,
973,
329,
1277,
35847,
284,
8824,
1643,
8899,
357,
15,
284,
7388,
8,
1377,
777,
198,
220,
220,
220,
1303,
4263,
389,
662,
12,
26238,
329,
257,
14174,
1661,
38765,
357,
82,
6192,
5651,
1352,
6100,
198,
220,
220,
220,
1303,
1729,
2815,
11458,
1973,
16558,
737,
198,
220,
220,
220,
8782,
10067,
796,
493,
7,
11879,
1635,
1802,
8,
4064,
1802,
1303,
4722,
8899,
657,
284,
7388,
628,
220,
220,
220,
1303,
3244,
779,
617,
5192,
284,
651,
5873,
6578,
198,
220,
220,
220,
611,
317,
8264,
19841,
657,
13,
20,
25,
1303,
968,
4613,
717,
3860,
4613,
1336,
198,
220,
220,
220,
220,
220,
220,
220,
19878,
43960,
796,
357,
16,
532,
10688,
13,
6966,
7,
11879,
1635,
362,
1635,
10688,
13,
14415,
4008,
1635,
2026,
198,
220,
220,
220,
2073,
25,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1303,
6462,
4613,
938,
3860,
4613,
649,
198,
220,
220,
220,
220,
220,
220,
220,
19878,
43960,
796,
357,
16,
1343,
10688,
13,
6966,
19510,
11879,
532,
657,
13,
20,
8,
1635,
362,
1635,
10688,
13,
14415,
4008,
1635,
2026,
628,
220,
220,
220,
1303,
9938,
1306,
4485,
14,
2617,
1785,
11,
8253,
416,
262,
1109,
326,
617,
1987,
12,
9769,
198,
220,
220,
220,
1303,
9574,
1244,
407,
423,
530,
393,
262,
584,
357,
4360,
3221,
466,
8,
2233,
284,
262,
198,
220,
220,
220,
1303,
6869,
7396,
5299,
1120,
23550,
1568,
1123,
1110,
13,
770,
3544,
257,
33908,
2700,
3164,
11,
198,
220,
220,
220,
1303,
1762,
16196,
832,
262,
640,
9574,
284,
17276,
4485,
14,
2617,
2995,
198,
220,
220,
220,
1303,
326,
317,
8,
2152,
287,
326,
1987,
12,
9769,
2278,
357,
533,
407,
6045,
828,
347,
8,
389,
991,
287,
198,
220,
220,
220,
1303,
262,
2003,
11,
290,
327,
8,
389,
5699,
621,
262,
938,
4724,
13,
1867,
338,
1364,
379,
262,
198,
220,
220,
220,
1303,
886,
318,
262,
1306,
4485,
393,
900,
357,
392,
262,
34062,
286,
262,
1785,
2099,
4952,
198,
220,
220,
220,
1303,
514,
1771,
6869,
338,
3058,
17450,
393,
407,
737,
198,
220,
220,
220,
39726,
62,
20114,
3525,
796,
19878,
40,
3727,
58,
16,
4083,
13602,
3847,
1343,
1802,
830,
1303,
5221,
717,
2872,
198,
220,
220,
220,
329,
24644,
287,
17687,
7,
18973,
40,
3727,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
611,
24644,
13,
17163,
290,
39726,
62,
20114,
3525,
18189,
24644,
13,
17163,
18189,
20229,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
39726,
62,
20114,
3525,
796,
24644,
13,
17163,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
45698,
1677,
796,
10352,
198,
220,
220,
220,
220,
220,
220,
220,
611,
24644,
13,
2617,
290,
39726,
62,
20114,
3525,
18189,
24644,
13,
2617,
18189,
20229,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
39726,
62,
20114,
3525,
796,
24644,
13,
2617,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
45698,
1677,
796,
6407,
628,
220,
220,
220,
611,
13954,
31519,
13,
10599,
341,
287,
357,
15,
11,
11546,
2599,
1303,
6075,
38342,
705,
1044,
6794,
6,
12852,
198,
220,
220,
220,
220,
220,
220,
220,
33269,
1137,
62,
55,
796,
4764,
220,
220,
220,
220,
220,
1303,
8255,
1863,
826,
198,
220,
220,
220,
220,
220,
220,
220,
13070,
1340,
62,
56,
796,
657,
220,
220,
220,
220,
220,
220,
220,
220,
1303,
6869,
379,
1364,
198,
220,
220,
220,
220,
220,
220,
220,
20460,
62,
56,
796,
718,
220,
220,
220,
220,
220,
220,
220,
220,
1303,
3862,
379,
1353,
826,
198,
220,
220,
220,
220,
220,
220,
220,
49261,
62,
56,
796,
2608,
220,
220,
220,
220,
220,
220,
1303,
15648,
14,
2617,
379,
4220,
826,
198,
220,
220,
220,
2073,
25,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1303,
38937,
705,
634,
12907,
6,
12852,
198,
220,
220,
220,
220,
220,
220,
220,
33269,
1137,
62,
55,
796,
1467,
220,
220,
220,
220,
220,
1303,
8255,
866,
3641,
198,
220,
220,
220,
220,
220,
220,
220,
611,
45698,
1677,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
13070,
1340,
62,
56,
796,
657,
220,
220,
220,
220,
1303,
6869,
379,
1353,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
49261,
62,
56,
796,
4353,
220,
220,
1303,
15648,
14,
2617,
287,
3504,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
20460,
62,
56,
796,
5125,
220,
220,
220,
1303,
3862,
14,
4475,
379,
4220,
198,
220,
220,
220,
220,
220,
220,
220,
2073,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
20460,
62,
56,
796,
718,
220,
220,
220,
220,
1303,
3862,
14,
4475,
379,
1353,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
49261,
62,
56,
796,
2608,
220,
220,
1303,
15648,
14,
2617,
287,
3504,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
13070,
1340,
62,
56,
796,
3933,
220,
220,
220,
1303,
6869,
379,
4220,
628,
220,
220,
220,
3601,
3419,
628,
220,
220,
220,
1303,
10133,
8824,
2939,
357,
46846,
58,
15,
12962,
198,
220,
220,
220,
34020,
1677,
10067,
796,
705,
22977,
14,
22977,
6,
1343,
705,
90,
15,
25,
15,
29,
17,
92,
4458,
18982,
7,
10913,
10067,
8,
1343,
45302,
65,
3149,
6,
198,
220,
220,
220,
36992,
33767,
796,
3359,
952,
13,
2202,
40961,
13128,
8899,
7,
9654,
7,
46700,
1677,
10067,
11,
705,
26145,
6,
4008,
198,
220,
220,
220,
31598,
2538,
62,
10761,
2389,
796,
3359,
952,
13,
35103,
41339,
7,
26094,
33767,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
17465,
62,
1477,
5067,
28,
13812,
952,
13,
10258,
3103,
332,
353,
22784,
8,
198,
220,
220,
220,
31598,
2538,
62,
10761,
2389,
13,
87,
796,
657,
198,
220,
220,
220,
31598,
2538,
62,
10761,
2389,
13,
88,
796,
13070,
1340,
62,
56,
198,
220,
220,
220,
44441,
58,
15,
60,
796,
31598,
2538,
62,
10761,
2389,
628,
220,
220,
220,
1303,
10133,
1411,
1988,
357,
20,
14722,
25,
44441,
58,
16,
12,
19,
60,
329,
19001,
11,
685,
20,
60,
329,
2420,
8,
198,
220,
220,
220,
611,
19878,
43960,
18189,
7388,
13,
3865,
25,
198,
220,
220,
220,
220,
220,
220,
220,
19269,
2751,
796,
705,
3064,
4,
6,
198,
220,
220,
220,
2073,
25,
198,
220,
220,
220,
220,
220,
220,
220,
19269,
2751,
796,
705,
90,
25,
13,
16,
69,
92,
4458,
18982,
7,
18973,
43960,
1343,
657,
13,
2713,
8,
1343,
705,
4,
6,
198,
220,
220,
220,
3601,
7,
45669,
11,
19269,
2751,
11,
705,
12853,
11537,
198,
220,
220,
220,
1303,
5345,
5002,
642,
717,
11,
779,
663,
2546,
290,
2292,
329,
4634,
1854,
198,
220,
220,
220,
44441,
58,
20,
4083,
5239,
796,
19269,
2751,
198,
220,
220,
220,
44441,
58,
20,
4083,
87,
796,
1467,
532,
44441,
58,
20,
4083,
7784,
278,
62,
3524,
58,
17,
60,
3373,
362,
198,
220,
220,
220,
44441,
58,
20,
4083,
88,
796,
13070,
1340,
62,
56,
1343,
1467,
198,
220,
220,
220,
329,
4808,
287,
2837,
7,
16,
11,
642,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
44441,
29795,
4083,
5239,
796,
44441,
58,
20,
4083,
5239,
198,
220,
220,
220,
44441,
58,
16,
4083,
87,
11,
44441,
58,
16,
4083,
88,
796,
44441,
58,
20,
4083,
87,
11,
44441,
58,
20,
4083,
88,
532,
352,
1303,
3205,
352,
17465,
198,
220,
220,
220,
44441,
58,
17,
4083,
87,
11,
44441,
58,
17,
4083,
88,
796,
44441,
58,
20,
4083,
87,
532,
352,
11,
44441,
58,
20,
4083,
88,
1303,
9578,
198,
220,
220,
220,
44441,
58,
18,
4083,
87,
11,
44441,
58,
18,
4083,
88,
796,
44441,
58,
20,
4083,
87,
1343,
352,
11,
44441,
58,
20,
4083,
88,
1303,
6498,
198,
220,
220,
220,
44441,
58,
19,
4083,
87,
11,
44441,
58,
19,
4083,
88,
796,
44441,
58,
20,
4083,
87,
11,
44441,
58,
20,
4083,
88,
1343,
352,
1303,
5588,
628,
220,
220,
220,
1303,
10133,
1306,
12,
15596,
640,
357,
46846,
58,
23,
60,
290,
685,
24,
12962,
198,
220,
220,
220,
1303,
2141,
428,
878,
640,
780,
356,
761,
4591,
273,
31590,
20229,
1988,
198,
220,
220,
220,
49261,
62,
34694,
796,
640,
13,
12001,
2435,
7,
45,
13918,
62,
20114,
3525,
8,
1303,
38240,
284,
2878,
329,
1568,
198,
220,
220,
220,
611,
327,
28270,
41925,
25,
1303,
5438,
39726,
62,
20114,
3525,
355,
33970,
284,
1785,
198,
220,
220,
220,
220,
220,
220,
220,
39726,
62,
20114,
3525,
48185,
20229,
1303,
3862,
1566,
357,
14259,
640,
286,
8,
1306,
4485,
14,
2617,
198,
220,
220,
220,
220,
220,
220,
220,
20625,
3843,
1546,
796,
39726,
62,
20114,
3525,
3373,
3126,
198,
220,
220,
220,
220,
220,
220,
220,
19269,
2751,
796,
965,
7,
23678,
3843,
1546,
3373,
3126,
8,
1343,
705,
32105,
1343,
705,
90,
15,
25,
15,
29,
17,
92,
4458,
18982,
7,
23678,
3843,
1546,
4064,
3126,
8,
198,
220,
220,
220,
2073,
25,
1303,
5438,
39726,
62,
20114,
3525,
287,
8801,
640,
198,
220,
220,
220,
220,
220,
220,
220,
19269,
2751,
796,
289,
71,
62,
3020,
7,
20114,
3525,
62,
34694,
8,
198,
220,
220,
220,
44441,
58,
24,
4083,
5239,
796,
19269,
2751,
198,
220,
220,
220,
11961,
2640,
796,
33269,
1137,
62,
55,
532,
357,
46846,
58,
24,
4083,
7784,
278,
62,
3524,
58,
17,
60,
1343,
718,
8,
3373,
362,
198,
220,
220,
220,
44441,
58,
23,
4083,
87,
796,
11961,
2640,
198,
220,
220,
220,
611,
45698,
1677,
25,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1303,
7406,
1785,
318,
25823,
198,
220,
220,
220,
220,
220,
220,
220,
44441,
58,
23,
4083,
5239,
796,
705,
59,
84,
2481,
32,
22,
6,
1303,
5588,
2017,
15452,
422,
2318,
198,
220,
220,
220,
220,
220,
220,
220,
44441,
58,
23,
4083,
88,
796,
49261,
62,
56,
532,
362,
198,
220,
220,
220,
220,
220,
220,
220,
3601,
10786,
50,
1039,
25,
3256,
19269,
2751,
8,
198,
220,
220,
220,
2073,
25,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1303,
7406,
1785,
318,
371,
24352,
198,
220,
220,
220,
220,
220,
220,
220,
44441,
58,
23,
4083,
5239,
796,
705,
59,
84,
2481,
32,
20,
6,
1303,
3205,
2017,
15452,
422,
2318,
198,
220,
220,
220,
220,
220,
220,
220,
44441,
58,
23,
4083,
88,
796,
49261,
62,
56,
532,
352,
198,
220,
220,
220,
220,
220,
220,
220,
3601,
10786,
49,
2696,
25,
3256,
19269,
2751,
8,
198,
220,
220,
220,
44441,
58,
24,
4083,
87,
796,
11961,
2640,
1343,
718,
198,
220,
220,
220,
44441,
58,
24,
4083,
88,
796,
49261,
62,
56,
198,
220,
220,
220,
1303,
5438,
1785,
640,
287,
4077,
611,
257,
13,
76,
1539,
36505,
611,
279,
13,
76,
13,
198,
220,
220,
220,
44441,
58,
23,
4083,
8043,
796,
44441,
58,
24,
4083,
8043,
796,
357,
15,
87,
405,
5777,
405,
611,
49261,
62,
34694,
13,
17209,
62,
9769,
1279,
1105,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2073,
657,
87,
34,
3023,
830,
8,
628,
220,
220,
220,
1303,
10133,
640,
357,
46846,
58,
21,
12962,
290,
3128,
357,
46846,
58,
22,
12962,
198,
220,
220,
220,
20229,
796,
640,
13,
12001,
2435,
3419,
198,
220,
220,
220,
19269,
2751,
796,
289,
71,
62,
3020,
7,
45669,
8,
198,
220,
220,
220,
44441,
58,
21,
4083,
5239,
796,
19269,
2751,
198,
220,
220,
220,
44441,
58,
21,
4083,
87,
796,
33269,
1137,
62,
55,
532,
44441,
58,
21,
4083,
7784,
278,
62,
3524,
58,
17,
60,
3373,
362,
198,
220,
220,
220,
44441,
58,
21,
4083,
88,
796,
20460,
62,
56,
198,
220,
220,
220,
611,
25000,
4221,
62,
26442,
25,
198,
220,
220,
220,
220,
220,
220,
220,
19269,
2751,
796,
965,
7,
45669,
13,
17209,
62,
2144,
8,
1343,
31051,
6,
1343,
965,
7,
45669,
13,
17209,
62,
76,
820,
8,
198,
220,
220,
220,
2073,
25,
198,
220,
220,
220,
220,
220,
220,
220,
19269,
2751,
796,
965,
7,
45669,
13,
17209,
62,
76,
820,
8,
1343,
31051,
6,
1343,
965,
7,
45669,
13,
17209,
62,
2144,
8,
198,
220,
220,
220,
44441,
58,
22,
4083,
5239,
796,
19269,
2751,
198,
220,
220,
220,
44441,
58,
22,
4083,
87,
796,
33269,
1137,
62,
55,
532,
44441,
58,
22,
4083,
7784,
278,
62,
3524,
58,
17,
60,
3373,
362,
198,
220,
220,
220,
44441,
58,
22,
4083,
88,
796,
20460,
62,
56,
1343,
838,
628,
220,
220,
220,
13954,
31519,
13,
5420,
3447,
3419,
1303,
5221,
1336,
1128,
2913,
357,
22018,
1077,
3159,
3360,
16461,
8,
198,
220,
220,
220,
640,
13,
42832,
7,
20,
8,
198
] | 2.262004 | 8,393 |
from ignite.metrics.metric import Metric
from ignite.engine import Events
class MetricsLambda(Metric):
"""
Apply a function to other metrics to obtain a new metric.
The result of the new metric is defined to be the result
of applying the function to the result of argument metrics.
When update, this metric does not recursively update the metrics
it depends on. When reset, all its dependency metrics would be
resetted. When attach, all its dependencies would be automatically
attached.
Args:
f (callable): the function that defines the computation
args (sequence): Sequence of other metrics or something
else that will be fed to ``f`` as arguments.
Example:
.. code-block:: python
precision = Precision(average=False)
recall = Recall(average=False)
def Fbeta(r, p, beta):
return torch.mean((1 + beta ** 2) * p * r / (beta ** 2 * p + r + 1e-20)).item()
F1 = MetricsLambda(Fbeta, recall, precision, 1)
F2 = MetricsLambda(Fbeta, recall, precision, 2)
F3 = MetricsLambda(Fbeta, recall, precision, 3)
F4 = MetricsLambda(Fbeta, recall, precision, 4)
"""
| [
6738,
44794,
13,
4164,
10466,
13,
4164,
1173,
1330,
3395,
1173,
198,
6738,
44794,
13,
18392,
1330,
18715,
628,
198,
4871,
3395,
10466,
43,
4131,
6814,
7,
9171,
1173,
2599,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
27967,
257,
2163,
284,
584,
20731,
284,
7330,
257,
649,
18663,
13,
198,
220,
220,
220,
383,
1255,
286,
262,
649,
18663,
318,
5447,
284,
307,
262,
1255,
198,
220,
220,
220,
286,
11524,
262,
2163,
284,
262,
1255,
286,
4578,
20731,
13,
628,
220,
220,
220,
1649,
4296,
11,
428,
18663,
857,
407,
664,
1834,
2280,
4296,
262,
20731,
198,
220,
220,
220,
340,
8338,
319,
13,
1649,
13259,
11,
477,
663,
20203,
20731,
561,
307,
198,
220,
220,
220,
13259,
1513,
13,
1649,
10199,
11,
477,
663,
20086,
561,
307,
6338,
198,
220,
220,
220,
7223,
13,
628,
220,
220,
220,
943,
14542,
25,
198,
220,
220,
220,
220,
220,
220,
220,
277,
357,
13345,
540,
2599,
262,
2163,
326,
15738,
262,
29964,
198,
220,
220,
220,
220,
220,
220,
220,
26498,
357,
43167,
2599,
45835,
286,
584,
20731,
393,
1223,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2073,
326,
481,
307,
11672,
284,
7559,
69,
15506,
355,
7159,
13,
628,
220,
220,
220,
17934,
25,
628,
220,
220,
220,
11485,
2438,
12,
9967,
3712,
21015,
628,
220,
220,
220,
220,
220,
220,
220,
15440,
796,
39281,
7,
23913,
28,
25101,
8,
198,
220,
220,
220,
220,
220,
220,
220,
10014,
796,
44536,
7,
23913,
28,
25101,
8,
628,
220,
220,
220,
220,
220,
220,
220,
825,
376,
31361,
7,
81,
11,
279,
11,
12159,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1441,
28034,
13,
32604,
19510,
16,
1343,
12159,
12429,
362,
8,
1635,
279,
1635,
374,
1220,
357,
31361,
12429,
362,
1635,
279,
1343,
374,
1343,
352,
68,
12,
1238,
29720,
9186,
3419,
628,
220,
220,
220,
220,
220,
220,
220,
376,
16,
796,
3395,
10466,
43,
4131,
6814,
7,
37,
31361,
11,
10014,
11,
15440,
11,
352,
8,
198,
220,
220,
220,
220,
220,
220,
220,
376,
17,
796,
3395,
10466,
43,
4131,
6814,
7,
37,
31361,
11,
10014,
11,
15440,
11,
362,
8,
198,
220,
220,
220,
220,
220,
220,
220,
376,
18,
796,
3395,
10466,
43,
4131,
6814,
7,
37,
31361,
11,
10014,
11,
15440,
11,
513,
8,
198,
220,
220,
220,
220,
220,
220,
220,
376,
19,
796,
3395,
10466,
43,
4131,
6814,
7,
37,
31361,
11,
10014,
11,
15440,
11,
604,
8,
198,
220,
220,
220,
37227,
198
] | 2.821596 | 426 |
#!/usr/bin/python
# -*- coding:utf-8 -*-
"""
北邮人网关登录脚本：
使用方法：
登录：python loginBuptGw.py i
退出：python loginBuptGw.py o
"""
import urllib2
import urllib
import cookielib
import hashlib
import os
import re
import sys
reload(sys)
sys.setdefaultencoding('utf8')
uname = XXXXXX #请正确填写学号
upass = 'XXXXXX' #请正确填写密码
if __name__ == '__main__':
if len(sys.argv) < 2 or len(sys.argv) >= 3:
usage()
else:
if sys.argv[1] == "i":
u_pass = safe_md5(upass)
u_data = login(u_pass).decode('gbk','ignore').encode('utf-8')
#print u_data
check_success(u_data)
elif sys.argv[1] == "o":
quit()
else:
usage()
| [
2,
48443,
14629,
14,
8800,
14,
29412,
198,
2,
532,
9,
12,
19617,
25,
40477,
12,
23,
532,
9,
12,
198,
198,
37811,
198,
44293,
245,
165,
224,
106,
21689,
163,
121,
239,
17739,
111,
163,
247,
119,
37605,
243,
164,
226,
248,
17312,
105,
171,
120,
248,
198,
45635,
18796,
101,
43095,
37345,
243,
171,
120,
248,
198,
163,
247,
119,
37605,
243,
171,
120,
248,
29412,
17594,
33,
37623,
38,
86,
13,
9078,
1312,
198,
34460,
222,
49035,
118,
171,
120,
248,
29412,
17594,
33,
37623,
38,
86,
13,
9078,
267,
198,
37811,
198,
198,
11748,
2956,
297,
571,
17,
198,
11748,
2956,
297,
571,
198,
11748,
4255,
8207,
571,
198,
11748,
12234,
8019,
198,
11748,
28686,
198,
11748,
302,
198,
11748,
25064,
198,
260,
2220,
7,
17597,
8,
198,
17597,
13,
2617,
12286,
12685,
7656,
10786,
40477,
23,
11537,
198,
198,
403,
480,
796,
1395,
24376,
55,
220,
220,
220,
1303,
46237,
115,
29826,
96,
163,
94,
106,
161,
94,
104,
37863,
247,
27764,
99,
20998,
115,
198,
929,
562,
796,
705,
24376,
8051,
6,
220,
1303,
46237,
115,
29826,
96,
163,
94,
106,
161,
94,
104,
37863,
247,
43380,
228,
163,
254,
223,
198,
198,
361,
11593,
3672,
834,
6624,
705,
834,
12417,
834,
10354,
198,
197,
361,
18896,
7,
17597,
13,
853,
85,
8,
1279,
362,
393,
18896,
7,
17597,
13,
853,
85,
8,
18189,
513,
25,
198,
197,
197,
26060,
3419,
198,
197,
17772,
25,
198,
197,
197,
361,
25064,
13,
853,
85,
58,
16,
60,
6624,
366,
72,
1298,
198,
197,
197,
197,
84,
62,
6603,
796,
220,
3338,
62,
9132,
20,
7,
929,
562,
8,
198,
197,
197,
197,
84,
62,
7890,
796,
17594,
7,
84,
62,
6603,
737,
12501,
1098,
10786,
22296,
74,
41707,
46430,
27691,
268,
8189,
10786,
40477,
12,
23,
11537,
198,
197,
197,
197,
2,
4798,
334,
62,
7890,
198,
197,
197,
197,
9122,
62,
13138,
7,
84,
62,
7890,
8,
198,
197,
197,
417,
361,
25064,
13,
853,
85,
58,
16,
60,
6624,
366,
78,
1298,
198,
197,
197,
197,
47391,
3419,
198,
197,
197,
17772,
25,
198,
197,
197,
197,
26060,
3419,
628,
198
] | 1.734637 | 358 |
from scipy.interpolate import interp1d
import numpy as np
def vectorize(func_orig):
"""
A function that takes a function and
returns another that can fun on lists and arrays
:param func_orig: any functions
:return: vectorized function
"""
return func
def get_interp_extrapolate_functions(x, base_model, linear_deviations):
"""
Get the three interp/extrapolation model functions:
base function, deviates function, total model function
:param x: the x data
:param base_model: model model cvxpy expression
:param linear_deviations: list of completed linear_deviations objects
:return: base function, deviates function, total model function
"""
# TODO: this requires mapping to be given, make it work with matrix only
interp_base_model_func = interp1d(x, base_model.value, fill_value="extrapolate")
return vectorize(func_base), vectorize(func_deviates), vectorize(func)
| [
6738,
629,
541,
88,
13,
3849,
16104,
378,
1330,
987,
79,
16,
67,
198,
11748,
299,
32152,
355,
45941,
628,
198,
4299,
15879,
1096,
7,
20786,
62,
11612,
2599,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
317,
2163,
326,
2753,
257,
2163,
290,
198,
220,
220,
220,
5860,
1194,
326,
460,
1257,
319,
8341,
290,
26515,
198,
220,
220,
220,
1058,
17143,
25439,
62,
11612,
25,
597,
5499,
198,
220,
220,
220,
1058,
7783,
25,
15879,
1143,
2163,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
1441,
25439,
628,
198,
4299,
651,
62,
3849,
79,
62,
2302,
2416,
27976,
62,
12543,
2733,
7,
87,
11,
2779,
62,
19849,
11,
14174,
62,
7959,
40356,
2599,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
3497,
262,
1115,
987,
79,
14,
2302,
2416,
21417,
2746,
5499,
25,
198,
220,
220,
220,
220,
220,
220,
220,
2779,
2163,
11,
1614,
32820,
2163,
11,
2472,
2746,
2163,
198,
220,
220,
220,
1058,
17143,
2124,
25,
262,
2124,
1366,
198,
220,
220,
220,
1058,
17143,
2779,
62,
19849,
25,
2746,
2746,
269,
85,
87,
9078,
5408,
198,
220,
220,
220,
1058,
17143,
14174,
62,
7959,
40356,
25,
1351,
286,
5668,
14174,
62,
7959,
40356,
5563,
198,
220,
220,
220,
1058,
7783,
25,
220,
2779,
2163,
11,
1614,
32820,
2163,
11,
2472,
2746,
2163,
198,
220,
220,
220,
37227,
628,
220,
220,
220,
1303,
16926,
46,
25,
428,
4433,
16855,
284,
307,
1813,
11,
787,
340,
670,
351,
17593,
691,
198,
220,
220,
220,
987,
79,
62,
8692,
62,
19849,
62,
20786,
796,
987,
79,
16,
67,
7,
87,
11,
2779,
62,
19849,
13,
8367,
11,
6070,
62,
8367,
2625,
2302,
2416,
27976,
4943,
628,
220,
220,
220,
1441,
15879,
1096,
7,
20786,
62,
8692,
828,
15879,
1096,
7,
20786,
62,
7959,
32820,
828,
15879,
1096,
7,
20786,
8,
198
] | 3.091205 | 307 |
# uncompyle6 version 3.7.4
# Python bytecode 3.7 (3394)
# Decompiled from: Python 3.7.9 (tags/v3.7.9:13c94747c7, Aug 17 2020, 18:58:18) [MSC v.1900 64 bit (AMD64)]
# Embedded file name: T:\InGame\Gameplay\Scripts\Server\objects\decorative\__init__.py
# Compiled at: 2009-11-20 02:49:20
# Size of source mod 2**32: 106 bytes
pass | [
2,
34318,
2349,
21,
2196,
513,
13,
22,
13,
19,
198,
2,
11361,
18022,
8189,
513,
13,
22,
357,
2091,
5824,
8,
198,
2,
4280,
3361,
3902,
422,
25,
11361,
513,
13,
22,
13,
24,
357,
31499,
14,
85,
18,
13,
22,
13,
24,
25,
1485,
66,
24,
2857,
2857,
66,
22,
11,
2447,
1596,
12131,
11,
1248,
25,
3365,
25,
1507,
8,
685,
5653,
34,
410,
13,
48104,
5598,
1643,
357,
28075,
2414,
15437,
198,
2,
13302,
47238,
2393,
1438,
25,
309,
7479,
818,
8777,
59,
43241,
59,
7391,
82,
59,
10697,
59,
48205,
59,
12501,
36478,
59,
834,
15003,
834,
13,
9078,
198,
2,
3082,
3902,
379,
25,
3717,
12,
1157,
12,
1238,
7816,
25,
2920,
25,
1238,
198,
2,
12849,
286,
2723,
953,
362,
1174,
2624,
25,
15696,
9881,
198,
6603
] | 2.447761 | 134 |
import random
from unittest import TestCase
import peb
| [
11748,
4738,
198,
6738,
555,
715,
395,
1330,
6208,
20448,
198,
198,
11748,
613,
65,
628,
198
] | 3.411765 | 17 |
# Generated by Django 3.1.2 on 2020-11-04 15:53
from django.db import migrations, models
| [
2,
2980,
515,
416,
37770,
513,
13,
16,
13,
17,
319,
12131,
12,
1157,
12,
3023,
1315,
25,
4310,
198,
198,
6738,
42625,
14208,
13,
9945,
1330,
15720,
602,
11,
4981,
628
] | 2.84375 | 32 |
import argparse
import matplotlib
matplotlib.use('agg')
import csv
import json
import multiprocessing as mp
import os
import random
import re
import sys
from functools import partial
from operator import attrgetter, itemgetter
import networkx as nx
import numpy as np
import pandas as pd
import time
from sofa_aisi import *
from sofa_common import *
from sofa_config import *
from sofa_print import *
from matplotlib import pyplot as plt
import grpc
import potato_pb2
import potato_pb2_grpc
import socket
import random
import subprocess
from sofa_ml import hsg_v2
# input: pfv(performance feature vector), Pandas.DataFrame
# output: hint, docker_image
| [
11748,
1822,
29572,
198,
11748,
2603,
29487,
8019,
198,
6759,
29487,
8019,
13,
1904,
10786,
9460,
11537,
198,
11748,
269,
21370,
198,
11748,
33918,
198,
11748,
18540,
305,
919,
278,
355,
29034,
198,
11748,
28686,
198,
11748,
4738,
198,
11748,
302,
198,
11748,
25064,
198,
6738,
1257,
310,
10141,
1330,
13027,
198,
6738,
10088,
1330,
708,
81,
1136,
353,
11,
2378,
1136,
353,
198,
11748,
3127,
87,
355,
299,
87,
198,
11748,
299,
32152,
355,
45941,
198,
11748,
19798,
292,
355,
279,
67,
198,
11748,
640,
198,
6738,
34902,
62,
15152,
72,
1330,
1635,
198,
6738,
34902,
62,
11321,
1330,
1635,
198,
6738,
34902,
62,
11250,
1330,
1635,
198,
6738,
34902,
62,
4798,
1330,
1635,
198,
6738,
2603,
29487,
8019,
1330,
12972,
29487,
355,
458,
83,
198,
11748,
1036,
14751,
198,
11748,
21219,
62,
40842,
17,
198,
11748,
21219,
62,
40842,
17,
62,
2164,
14751,
198,
11748,
17802,
198,
11748,
4738,
198,
11748,
850,
14681,
198,
6738,
34902,
62,
4029,
1330,
289,
45213,
62,
85,
17,
628,
198,
2,
5128,
25,
279,
69,
85,
7,
26585,
3895,
15879,
828,
16492,
292,
13,
6601,
19778,
198,
2,
5072,
25,
9254,
11,
36253,
62,
9060,
220,
220,
628,
198
] | 3.340102 | 197 |
import MySQLdb
db = MySQLdb.connect("db", "root", "my-secret-pw", "bd_notes")
cursor = db.cursor()
global resultsExportEtudiants
resultsExportEtudiants = []
| [
11748,
33476,
9945,
198,
198,
9945,
796,
33476,
9945,
13,
8443,
7203,
9945,
1600,
366,
15763,
1600,
366,
1820,
12,
21078,
12,
79,
86,
1600,
366,
17457,
62,
17815,
4943,
198,
198,
66,
21471,
796,
20613,
13,
66,
21471,
3419,
198,
20541,
2482,
43834,
36,
83,
463,
17883,
198,
43420,
43834,
36,
83,
463,
17883,
796,
17635,
628
] | 2.758621 | 58 |
import abc
import asyncio
from typing import Any
from typing import Dict
from typing import Optional
from async_blp.enums import ErrorBehaviour
from async_blp.utils import log
# pylint: disable=ungrouped-imports
try:
import blpapi
except ImportError:
from async_blp.utils import env_test as blpapi
LOGGER = log.get_logger()
| [
11748,
450,
66,
198,
11748,
30351,
952,
198,
6738,
19720,
1330,
4377,
198,
6738,
19720,
1330,
360,
713,
198,
6738,
19720,
1330,
32233,
198,
198,
6738,
30351,
62,
2436,
79,
13,
268,
5700,
1330,
13047,
25267,
37716,
198,
6738,
30351,
62,
2436,
79,
13,
26791,
1330,
2604,
198,
198,
2,
279,
2645,
600,
25,
15560,
28,
2150,
3233,
276,
12,
320,
3742,
198,
28311,
25,
198,
220,
220,
220,
1330,
698,
79,
15042,
198,
16341,
17267,
12331,
25,
198,
220,
220,
220,
422,
30351,
62,
2436,
79,
13,
26791,
1330,
17365,
62,
9288,
355,
698,
79,
15042,
198,
198,
25294,
30373,
796,
2604,
13,
1136,
62,
6404,
1362,
3419,
628
] | 3.054545 | 110 |
import collections
from typing import Any, Dict, Tuple
def format_keyword(keyword: str, val: Any, lop_off: bool = True) -> Tuple[str, str]:
"""Function to reformat value `val` for `keyword` from python into nwchem-speak."""
# Transform string booleans into " "
if val is True:
return keyword.lower(), "true"
elif val is False:
return keyword.lower(), "false"
# complete hack
# if keyword.upper() == "MEMORY":
# return keyword.lower(), f"{val} byte"
elif isinstance(val, list): # if it is a list... join the list into a string ??? when is this in play
text = " ".join([str(v) for v in val])
elif isinstance(val, dict): # val is a dict... text is list
text = []
for k, v in val.items():
merge = [k]
merge.extend(str(v) if isinstance(v, (int, float)) else list(map(str, v)))
text.append(" ".join(merge))
text = " ".join(text)
else:
text = str(val)
if lop_off:
return keyword[7:].lower(), text
else:
return keyword.lower(), text
def format_keywords(keywords: Dict[str, Any]) -> str:
"""From NWCHEM-directed, non-default `keywords` dictionary, write a NWCHEM deck."""
grouped_options = rec_dd()
for group_key, val in keywords.items():
nesting = group_key.split("__")
if len(nesting) == 1:
key = nesting[0]
grouped_options["aaaglobal"][key] = val
elif len(nesting) == 2:
g1, key = nesting
grouped_options[g1][key] = val
elif len(nesting) == 3:
g1, g2, key = nesting
grouped_options[g1][g2][key] = val
else:
print(nesting)
raise ValueError("Nesting N!")
grouped_lines = {}
for group, opts in sorted(grouped_options.items()):
lines = []
group_level_lines = []
for key, val in grouped_options[group].items():
if isinstance(val, dict):
g2_level_lines = []
g2_level_lines.append(key.lower())
for k2, v2 in val.items():
line2 = " ".join(format_keyword(k2, v2, lop_off=False))
g2_level_lines.append(line2)
g2_level_lines = " ".join(g2_level_lines)
lines.append(g2_level_lines)
else:
line = " ".join(format_keyword(key, val, lop_off=False))
if group.lower() == "basis" and any(
[word in line for word in ["spherical", "cartesian", "print", "noprint", "rel"]]
):
group_level_lines.append(line)
else:
lines.append(line)
if group == "aaaglobal":
grouped_lines[group] = "\n".join(lines) + "\n"
else:
grouped_lines[group] = (
f"{group.lower()} " + " ".join(group_level_lines) + "\n " + "\n ".join(lines) + "\nend\n"
)
return "\n".join(grouped_lines.values()) + "\n"
| [
11748,
17268,
198,
6738,
19720,
1330,
4377,
11,
360,
713,
11,
309,
29291,
628,
198,
4299,
5794,
62,
2539,
4775,
7,
2539,
4775,
25,
965,
11,
1188,
25,
4377,
11,
300,
404,
62,
2364,
25,
20512,
796,
6407,
8,
4613,
309,
29291,
58,
2536,
11,
965,
5974,
198,
220,
220,
220,
37227,
22203,
284,
4975,
265,
1988,
4600,
2100,
63,
329,
4600,
2539,
4775,
63,
422,
21015,
656,
299,
86,
15245,
12,
47350,
526,
15931,
628,
220,
220,
220,
1303,
26981,
4731,
1489,
2305,
504,
656,
366,
366,
198,
220,
220,
220,
611,
1188,
318,
6407,
25,
198,
220,
220,
220,
220,
220,
220,
220,
1441,
21179,
13,
21037,
22784,
366,
7942,
1,
198,
220,
220,
220,
1288,
361,
1188,
318,
10352,
25,
198,
220,
220,
220,
220,
220,
220,
220,
1441,
21179,
13,
21037,
22784,
366,
9562,
1,
628,
220,
220,
220,
1303,
1844,
8156,
198,
220,
220,
220,
1303,
611,
21179,
13,
45828,
3419,
6624,
366,
44,
3620,
15513,
1298,
198,
220,
220,
220,
1303,
220,
220,
220,
1441,
21179,
13,
21037,
22784,
277,
1,
90,
2100,
92,
18022,
1,
628,
220,
220,
220,
1288,
361,
318,
39098,
7,
2100,
11,
1351,
2599,
220,
1303,
611,
340,
318,
257,
1351,
986,
4654,
262,
1351,
656,
257,
4731,
34913,
618,
318,
428,
287,
711,
198,
220,
220,
220,
220,
220,
220,
220,
2420,
796,
366,
27071,
22179,
26933,
2536,
7,
85,
8,
329,
410,
287,
1188,
12962,
198,
220,
220,
220,
1288,
361,
318,
39098,
7,
2100,
11,
8633,
2599,
220,
1303,
1188,
318,
257,
8633,
986,
2420,
318,
1351,
198,
220,
220,
220,
220,
220,
220,
220,
2420,
796,
17635,
198,
220,
220,
220,
220,
220,
220,
220,
329,
479,
11,
410,
287,
1188,
13,
23814,
33529,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
20121,
796,
685,
74,
60,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
20121,
13,
2302,
437,
7,
2536,
7,
85,
8,
611,
318,
39098,
7,
85,
11,
357,
600,
11,
12178,
4008,
2073,
1351,
7,
8899,
7,
2536,
11,
410,
22305,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2420,
13,
33295,
7203,
27071,
22179,
7,
647,
469,
4008,
198,
220,
220,
220,
220,
220,
220,
220,
2420,
796,
366,
27071,
22179,
7,
5239,
8,
198,
220,
220,
220,
2073,
25,
198,
220,
220,
220,
220,
220,
220,
220,
2420,
796,
965,
7,
2100,
8,
628,
220,
220,
220,
611,
300,
404,
62,
2364,
25,
198,
220,
220,
220,
220,
220,
220,
220,
1441,
21179,
58,
22,
25,
4083,
21037,
22784,
2420,
198,
220,
220,
220,
2073,
25,
198,
220,
220,
220,
220,
220,
220,
220,
1441,
21179,
13,
21037,
22784,
2420,
628,
198,
4299,
5794,
62,
2539,
10879,
7,
2539,
10879,
25,
360,
713,
58,
2536,
11,
4377,
12962,
4613,
965,
25,
198,
220,
220,
220,
37227,
4863,
21966,
3398,
3620,
12,
34762,
11,
1729,
12,
12286,
4600,
2539,
10879,
63,
22155,
11,
3551,
257,
21966,
3398,
3620,
6203,
526,
15931,
628,
220,
220,
220,
32824,
62,
25811,
796,
664,
62,
1860,
3419,
628,
220,
220,
220,
329,
1448,
62,
2539,
11,
1188,
287,
26286,
13,
23814,
33529,
198,
220,
220,
220,
220,
220,
220,
220,
46282,
796,
1448,
62,
2539,
13,
35312,
7203,
834,
4943,
198,
220,
220,
220,
220,
220,
220,
220,
611,
18896,
7,
77,
37761,
8,
6624,
352,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1994,
796,
46282,
58,
15,
60,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
32824,
62,
25811,
14692,
7252,
363,
75,
2572,
1,
7131,
2539,
60,
796,
1188,
198,
220,
220,
220,
220,
220,
220,
220,
1288,
361,
18896,
7,
77,
37761,
8,
6624,
362,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
308,
16,
11,
1994,
796,
46282,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
32824,
62,
25811,
58,
70,
16,
7131,
2539,
60,
796,
1188,
198,
220,
220,
220,
220,
220,
220,
220,
1288,
361,
18896,
7,
77,
37761,
8,
6624,
513,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
308,
16,
11,
308,
17,
11,
1994,
796,
46282,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
32824,
62,
25811,
58,
70,
16,
7131,
70,
17,
7131,
2539,
60,
796,
1188,
198,
220,
220,
220,
220,
220,
220,
220,
2073,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
3601,
7,
77,
37761,
8,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
5298,
11052,
12331,
7203,
45,
37761,
399,
2474,
8,
628,
220,
220,
220,
32824,
62,
6615,
796,
23884,
198,
220,
220,
220,
329,
1448,
11,
2172,
82,
287,
23243,
7,
8094,
276,
62,
25811,
13,
23814,
3419,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
3951,
796,
17635,
198,
220,
220,
220,
220,
220,
220,
220,
1448,
62,
5715,
62,
6615,
796,
17635,
198,
220,
220,
220,
220,
220,
220,
220,
329,
1994,
11,
1188,
287,
32824,
62,
25811,
58,
8094,
4083,
23814,
33529,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
611,
318,
39098,
7,
2100,
11,
8633,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
308,
17,
62,
5715,
62,
6615,
796,
17635,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
308,
17,
62,
5715,
62,
6615,
13,
33295,
7,
2539,
13,
21037,
28955,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
329,
479,
17,
11,
410,
17,
287,
1188,
13,
23814,
33529,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1627,
17,
796,
366,
27071,
22179,
7,
18982,
62,
2539,
4775,
7,
74,
17,
11,
410,
17,
11,
300,
404,
62,
2364,
28,
25101,
4008,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
308,
17,
62,
5715,
62,
6615,
13,
33295,
7,
1370,
17,
8,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
308,
17,
62,
5715,
62,
6615,
796,
366,
27071,
22179,
7,
70,
17,
62,
5715,
62,
6615,
8,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
3951,
13,
33295,
7,
70,
17,
62,
5715,
62,
6615,
8,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2073,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1627,
796,
366,
27071,
22179,
7,
18982,
62,
2539,
4775,
7,
2539,
11,
1188,
11,
300,
404,
62,
2364,
28,
25101,
4008,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
611,
1448,
13,
21037,
3419,
6624,
366,
12093,
271,
1,
290,
597,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
685,
4775,
287,
1627,
329,
1573,
287,
14631,
2777,
37910,
1600,
366,
26674,
35610,
1600,
366,
4798,
1600,
366,
77,
404,
22272,
1600,
366,
2411,
8973,
60,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
15179,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1448,
62,
5715,
62,
6615,
13,
33295,
7,
1370,
8,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2073,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
3951,
13,
33295,
7,
1370,
8,
198,
220,
220,
220,
220,
220,
220,
220,
611,
1448,
6624,
366,
7252,
363,
75,
2572,
1298,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
32824,
62,
6615,
58,
8094,
60,
796,
37082,
77,
1911,
22179,
7,
6615,
8,
1343,
37082,
77,
1,
198,
220,
220,
220,
220,
220,
220,
220,
2073,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
32824,
62,
6615,
58,
8094,
60,
796,
357,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
277,
1,
90,
8094,
13,
21037,
3419,
92,
366,
1343,
366,
27071,
22179,
7,
8094,
62,
5715,
62,
6615,
8,
1343,
37082,
77,
220,
366,
1343,
37082,
77,
220,
27071,
22179,
7,
6615,
8,
1343,
37082,
77,
437,
59,
77,
1,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1267,
628,
220,
220,
220,
1441,
37082,
77,
1911,
22179,
7,
8094,
276,
62,
6615,
13,
27160,
28955,
1343,
37082,
77,
1,
198
] | 2.052632 | 1,482 |
from common.file_tools import delete_old_files_directories
import time
| [
6738,
2219,
13,
7753,
62,
31391,
1330,
12233,
62,
727,
62,
16624,
62,
12942,
1749,
198,
11748,
640,
198
] | 3.736842 | 19 |
from smbus2 import SMBus
import time
# RPi Channel 1
channel = 1
bus = SMBus(channel)
# ADS1115 address and registers
address = 0x48
reg_config = 0x01
# Config value:
# - Single conversion
# - A0 input
# - 4.096V reference
config = [0xC2, 0xB3]
while True:
reg_conversion = 0x00
# Start conversion
bus.write_i2c_block_data(address, reg_config, config)
# Wait for conversion
time.sleep(0.01)
# Read 16-bit result
result = bus.read_i2c_block_data(address, reg_conversion, 2)
# Convert from 2-complement
value = ((result[0] & 0xFF) << 8) | (result[1] & 0xFF)
if value & 0x8000 != 0:
value -= 1 << 16
# Convert value to voltage
v = value * 4.096 / 32768
print("A0:", v)
# Wait a second to start again
time.sleep(1)
# ADS1115 address and registers
address = 0x48
reg_config = 0x01
reg_conversion = 0x01
# Start conversion
bus.write_i2c_block_data(address, reg_config, config)
# Wait for conversion
time.sleep(0.01)
# Read 16-bit result
result = bus.read_i2c_block_data(address, reg_conversion, 2)
# Convert from 2-complement
value = ((result[0] & 0xFF) << 8) | (result[1] & 0xFF)
if value & 0x8000 != 0:
value -= 1 << 16
# Convert value to voltage
v = value * 4.096 / 32768
print("A1:", v)
# Wait a second to start again
time.sleep(1)
| [
198,
6738,
895,
10885,
17,
1330,
9447,
16286,
198,
11748,
640,
198,
198,
2,
25812,
72,
11102,
352,
198,
17620,
796,
352,
198,
198,
10885,
796,
9447,
16286,
7,
17620,
8,
198,
2,
44784,
1157,
1314,
2209,
290,
28441,
198,
21975,
796,
657,
87,
2780,
198,
2301,
62,
11250,
796,
657,
87,
486,
198,
220,
198,
2,
17056,
1988,
25,
198,
2,
532,
14206,
11315,
198,
2,
532,
317,
15,
5128,
198,
2,
532,
604,
13,
2931,
21,
53,
4941,
198,
11250,
796,
685,
15,
87,
34,
17,
11,
657,
87,
33,
18,
60,
198,
198,
4514,
6407,
25,
198,
220,
842,
62,
1102,
9641,
796,
657,
87,
405,
628,
220,
1303,
7253,
11315,
198,
220,
1323,
13,
13564,
62,
72,
17,
66,
62,
9967,
62,
7890,
7,
21975,
11,
842,
62,
11250,
11,
4566,
8,
198,
220,
1303,
16314,
329,
11315,
198,
220,
640,
13,
42832,
7,
15,
13,
486,
8,
198,
220,
1303,
4149,
1467,
12,
2545,
1255,
198,
220,
1255,
796,
1323,
13,
961,
62,
72,
17,
66,
62,
9967,
62,
7890,
7,
21975,
11,
842,
62,
1102,
9641,
11,
362,
8,
198,
220,
1303,
38240,
422,
362,
12,
785,
26908,
198,
220,
1988,
796,
14808,
20274,
58,
15,
60,
1222,
657,
87,
5777,
8,
9959,
807,
8,
930,
357,
20274,
58,
16,
60,
1222,
657,
87,
5777,
8,
198,
220,
611,
1988,
1222,
657,
87,
33942,
14512,
657,
25,
198,
220,
220,
220,
1988,
48185,
352,
9959,
1467,
198,
220,
1303,
38240,
1988,
284,
15004,
198,
220,
410,
796,
1988,
1635,
604,
13,
2931,
21,
1220,
36203,
3104,
198,
220,
3601,
7203,
32,
15,
25,
1600,
410,
8,
198,
220,
1303,
16314,
257,
1218,
284,
923,
757,
198,
220,
640,
13,
42832,
7,
16,
8,
628,
220,
1303,
44784,
1157,
1314,
2209,
290,
28441,
198,
220,
2209,
796,
657,
87,
2780,
198,
220,
842,
62,
11250,
796,
657,
87,
486,
198,
220,
842,
62,
1102,
9641,
796,
657,
87,
486,
628,
220,
1303,
7253,
11315,
198,
220,
1323,
13,
13564,
62,
72,
17,
66,
62,
9967,
62,
7890,
7,
21975,
11,
842,
62,
11250,
11,
4566,
8,
198,
220,
1303,
16314,
329,
11315,
198,
220,
640,
13,
42832,
7,
15,
13,
486,
8,
198,
220,
1303,
4149,
1467,
12,
2545,
1255,
198,
220,
1255,
796,
1323,
13,
961,
62,
72,
17,
66,
62,
9967,
62,
7890,
7,
21975,
11,
842,
62,
1102,
9641,
11,
362,
8,
198,
220,
1303,
38240,
422,
362,
12,
785,
26908,
198,
220,
1988,
796,
14808,
20274,
58,
15,
60,
1222,
657,
87,
5777,
8,
9959,
807,
8,
930,
357,
20274,
58,
16,
60,
1222,
657,
87,
5777,
8,
198,
220,
611,
1988,
1222,
657,
87,
33942,
14512,
657,
25,
198,
220,
220,
220,
1988,
48185,
352,
9959,
1467,
198,
220,
1303,
38240,
1988,
284,
15004,
198,
220,
410,
796,
1988,
1635,
604,
13,
2931,
21,
1220,
36203,
3104,
198,
220,
3601,
7203,
32,
16,
25,
1600,
410,
8,
198,
220,
1303,
16314,
257,
1218,
284,
923,
757,
198,
220,
640,
13,
42832,
7,
16,
8,
628
] | 2.60198 | 505 |
import numpy as np
import math
# Copyright 2020 Joshua Laniado and Todd O. Yeates.
__author__ = "Joshua Laniado and Todd O. Yeates"
__copyright__ = "Copyright 2020, Nanohedra"
__version__ = "1.0"
# ROTATION RANGE DEG
C2 = 180
C3 = 120
C4 = 90
C5 = 72
C6 = 60
RotRangeDict = {"C2": C2, "C3": C3, "C4": C4, "C5": C5, "C6": C6}
| [
11748,
299,
32152,
355,
45941,
198,
11748,
10688,
628,
198,
2,
15069,
12131,
20700,
406,
3216,
4533,
290,
14377,
440,
13,
11609,
689,
13,
198,
834,
9800,
834,
796,
366,
47740,
406,
3216,
4533,
290,
14377,
440,
13,
11609,
689,
1,
198,
834,
22163,
4766,
834,
796,
366,
15269,
12131,
11,
33504,
704,
430,
1,
198,
834,
9641,
834,
796,
366,
16,
13,
15,
1,
628,
198,
2,
371,
2394,
6234,
371,
27746,
5550,
38,
198,
34,
17,
796,
11546,
198,
34,
18,
796,
7982,
198,
34,
19,
796,
4101,
198,
34,
20,
796,
7724,
198,
34,
21,
796,
3126,
198,
24864,
17257,
35,
713,
796,
19779,
34,
17,
1298,
327,
17,
11,
366,
34,
18,
1298,
327,
18,
11,
366,
34,
19,
1298,
327,
19,
11,
366,
34,
20,
1298,
327,
20,
11,
366,
34,
21,
1298,
327,
21,
92,
628,
628,
628,
628
] | 2.317241 | 145 |
from precious import Value, assign_attributes, copy
| [
6738,
14186,
1330,
11052,
11,
8333,
62,
1078,
7657,
11,
4866,
628,
198
] | 4.153846 | 13 |
"""Tests for maven_releases.py."""
# import pytest
# TODO enable when new test(s) will be added
# from f8a_jobs.handlers.maven_releases import MavenReleasesAnalyses
class TestMavenReleasesAnalyses(object):
"""Tests for MavenReleasesAnalyses class."""
def setup_method(self, method):
"""Set up any state tied to the execution of the given method in a class."""
assert method
def teardown_method(self, method):
"""Teardown any state that was previously setup with a setup_method call."""
assert method
| [
37811,
51,
3558,
329,
285,
4005,
62,
260,
29329,
13,
9078,
526,
15931,
198,
198,
2,
1330,
12972,
9288,
198,
198,
2,
16926,
46,
7139,
618,
649,
1332,
7,
82,
8,
481,
307,
2087,
198,
2,
422,
277,
23,
64,
62,
43863,
13,
4993,
8116,
13,
2611,
574,
62,
260,
29329,
1330,
337,
4005,
3041,
29329,
2025,
43710,
628,
198,
4871,
6208,
44,
4005,
3041,
29329,
2025,
43710,
7,
15252,
2599,
198,
220,
220,
220,
37227,
51,
3558,
329,
337,
4005,
3041,
29329,
2025,
43710,
1398,
526,
15931,
628,
220,
220,
220,
825,
9058,
62,
24396,
7,
944,
11,
2446,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
7248,
510,
597,
1181,
8165,
284,
262,
9706,
286,
262,
1813,
2446,
287,
257,
1398,
526,
15931,
198,
220,
220,
220,
220,
220,
220,
220,
6818,
2446,
628,
220,
220,
220,
825,
573,
446,
593,
62,
24396,
7,
944,
11,
2446,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
6767,
446,
593,
597,
1181,
326,
373,
4271,
9058,
351,
257,
9058,
62,
24396,
869,
526,
15931,
198,
220,
220,
220,
220,
220,
220,
220,
6818,
2446,
198
] | 2.910053 | 189 |
#!/usr/bin/env python
# −*− coding: UTF−8 −*−
import abc
if __name__ == '__main__':
test()
| [
2,
48443,
14629,
14,
8800,
14,
24330,
21015,
198,
2,
9746,
9,
14095,
19617,
25,
41002,
14095,
23,
9746,
9,
14095,
198,
198,
11748,
450,
66,
628,
628,
198,
198,
361,
11593,
3672,
834,
6624,
705,
834,
12417,
834,
10354,
198,
220,
220,
220,
1332,
3419,
198
] | 2.148936 | 47 |
import threading
import requests
import os
import time
urls = [
"https://unsplash.com/photos/CTflmHHVrBM/download?force=true",
"https://unsplash.com/photos/pWV8HjvHzk8/download?force=true",
# "https://unsplash.com/photos/1jn_3WBp60I/download?force=true",
# "https://unsplash.com/photos/8E5HawfqCMM/download?force=true",
# "https://unsplash.com/photos/yTOkMc2q01o/download?force=true"
]
download_path = os.path.join(os.getcwd(),"downloaded_images")
if __name__ == "__main__":
start= time.time()
threads = []
# create and start a thread per each url
for url in urls:
tr = threading.Thread(target=download_file,args=(url,))
threads.append(tr)
tr.start()
# result= download_file(url)
# join all threads
for tr in threads:
tr.join()
end = time.time()
print(f"Procesing time: {end-start}") | [
11748,
4704,
278,
198,
11748,
7007,
198,
11748,
28686,
198,
11748,
640,
628,
198,
6371,
82,
796,
685,
198,
197,
1,
5450,
1378,
13271,
489,
1077,
13,
785,
14,
24729,
14,
4177,
2704,
76,
16768,
53,
81,
12261,
14,
15002,
30,
3174,
28,
7942,
1600,
198,
197,
1,
5450,
1378,
13271,
489,
1077,
13,
785,
14,
24729,
14,
79,
54,
53,
23,
39,
73,
85,
7399,
74,
23,
14,
15002,
30,
3174,
28,
7942,
1600,
198,
197,
2,
366,
5450,
1378,
13271,
489,
1077,
13,
785,
14,
24729,
14,
16,
73,
77,
62,
18,
45607,
79,
1899,
40,
14,
15002,
30,
3174,
28,
7942,
1600,
198,
197,
2,
366,
5450,
1378,
13271,
489,
1077,
13,
785,
14,
24729,
14,
23,
36,
20,
33055,
69,
80,
34,
12038,
14,
15002,
30,
3174,
28,
7942,
1600,
198,
197,
2,
366,
5450,
1378,
13271,
489,
1077,
13,
785,
14,
24729,
14,
88,
10468,
74,
9742,
17,
80,
486,
78,
14,
15002,
30,
3174,
28,
7942,
1,
198,
60,
198,
198,
15002,
62,
6978,
796,
28686,
13,
6978,
13,
22179,
7,
418,
13,
1136,
66,
16993,
3419,
553,
2902,
14578,
62,
17566,
4943,
198,
198,
361,
11593,
3672,
834,
6624,
366,
834,
12417,
834,
1298,
198,
197,
9688,
28,
640,
13,
2435,
3419,
628,
197,
16663,
82,
796,
17635,
628,
197,
2,
2251,
290,
923,
257,
4704,
583,
1123,
19016,
198,
197,
1640,
19016,
287,
2956,
7278,
25,
198,
197,
197,
2213,
796,
4704,
278,
13,
16818,
7,
16793,
28,
15002,
62,
7753,
11,
22046,
16193,
6371,
11,
4008,
198,
197,
197,
16663,
82,
13,
33295,
7,
2213,
8,
198,
197,
197,
2213,
13,
9688,
3419,
198,
197,
197,
2,
1255,
28,
4321,
62,
7753,
7,
6371,
8,
628,
197,
2,
4654,
477,
14390,
198,
197,
1640,
491,
287,
14390,
25,
198,
197,
197,
2213,
13,
22179,
3419,
628,
197,
437,
796,
640,
13,
2435,
3419,
628,
197,
4798,
7,
69,
1,
2964,
728,
278,
640,
25,
220,
1391,
437,
12,
9688,
92,
4943
] | 2.472727 | 330 |
from .ami import prepare_ami
from .broadcast_news import prepare_broadcast_news
from .librimix import prepare_librimix
from .librispeech import prepare_librispeech
from .switchboard import prepare_switchboard
__all__ = [
'prepare_ami',
'prepare_broadcast_news',
'prepare_librimix',
'prepare_librispeech',
'prepare_switchboard'
]
| [
6738,
764,
6277,
1330,
8335,
62,
6277,
198,
6738,
764,
36654,
2701,
62,
10827,
1330,
8335,
62,
36654,
2701,
62,
10827,
198,
6738,
764,
75,
2889,
320,
844,
1330,
8335,
62,
75,
2889,
320,
844,
198,
6738,
764,
8019,
2442,
431,
3055,
1330,
8335,
62,
8019,
2442,
431,
3055,
198,
6738,
764,
31943,
3526,
1330,
8335,
62,
31943,
3526,
198,
198,
834,
439,
834,
796,
685,
198,
220,
220,
220,
705,
46012,
533,
62,
6277,
3256,
198,
220,
220,
220,
705,
46012,
533,
62,
36654,
2701,
62,
10827,
3256,
198,
220,
220,
220,
705,
46012,
533,
62,
75,
2889,
320,
844,
3256,
198,
220,
220,
220,
705,
46012,
533,
62,
8019,
2442,
431,
3055,
3256,
198,
220,
220,
220,
705,
46012,
533,
62,
31943,
3526,
6,
198,
60,
198
] | 2.713178 | 129 |
import re
from selenium import webdriver
from selenium.webdriver.chrome.options import Options
import argparse
import ncz
import chromedriver_binary
parser = argparse.ArgumentParser()
parser.add_argument('keyword1', help="main_city_name")
parser.add_argument('keyword2', help="sub_city_name")
parser.add_argument('keyword3', help="file_path")
mainCityName = parser.parse_args().keyword1
subCityName = parser.parse_args().keyword2
filePath = re.sub(r"[^./_a-z]","",parser.parse_args().keyword3)
if re.search(subCityName, "전체"):
subCityName = ""
chrome_options = Options()
# chrome_options.add_argument('--headless') # 화면 안띄움
#chrome_options.add_argument('--start-maximized') # F11 전체 화면 설정
driver = webdriver.Chrome(options=chrome_options)
url = "https://search.naver.com/search.naver?query={}+{}+코로나&where=news&ie=utf8&sm=nws_hty".format(
mainCityName, subCityName)
driver.get(url)
elem = driver.find_element_by_xpath('//*[@id="main_pack"]/section/div/div[2]/ul')
articles = elem.find_elements_by_class_name("news_wrap.api_ani_send") # 기사들
ncz.naverArticlePattern(filePath, articles)
| [
11748,
302,
198,
6738,
384,
11925,
1505,
1330,
3992,
26230,
198,
6738,
384,
11925,
1505,
13,
12384,
26230,
13,
46659,
13,
25811,
1330,
18634,
198,
11748,
1822,
29572,
198,
11748,
299,
26691,
198,
198,
11748,
15358,
276,
38291,
62,
39491,
628,
198,
48610,
796,
1822,
29572,
13,
28100,
1713,
46677,
3419,
198,
48610,
13,
2860,
62,
49140,
10786,
2539,
4775,
16,
3256,
1037,
2625,
12417,
62,
19205,
62,
3672,
4943,
198,
48610,
13,
2860,
62,
49140,
10786,
2539,
4775,
17,
3256,
1037,
2625,
7266,
62,
19205,
62,
3672,
4943,
198,
48610,
13,
2860,
62,
49140,
10786,
2539,
4775,
18,
3256,
1037,
2625,
7753,
62,
6978,
4943,
198,
198,
12417,
14941,
5376,
796,
30751,
13,
29572,
62,
22046,
22446,
2539,
4775,
16,
198,
7266,
14941,
5376,
796,
30751,
13,
29572,
62,
22046,
22446,
2539,
4775,
17,
198,
7753,
15235,
796,
302,
13,
7266,
7,
81,
17912,
61,
19571,
62,
64,
12,
89,
60,
2430,
1600,
48610,
13,
29572,
62,
22046,
22446,
2539,
4775,
18,
8,
198,
198,
361,
302,
13,
12947,
7,
7266,
14941,
5376,
11,
366,
168,
254,
226,
168,
110,
112,
1,
2599,
198,
220,
220,
220,
850,
14941,
5376,
796,
13538,
198,
198,
46659,
62,
25811,
796,
18634,
3419,
198,
2,
32030,
62,
25811,
13,
2860,
62,
49140,
10786,
438,
2256,
1203,
11537,
220,
1303,
220,
169,
247,
242,
167,
102,
112,
23821,
243,
230,
167,
251,
226,
168,
249,
222,
198,
2,
46659,
62,
25811,
13,
2860,
62,
49140,
10786,
438,
9688,
12,
9806,
320,
1143,
11537,
220,
1303,
376,
1157,
23821,
254,
226,
168,
110,
112,
220,
169,
247,
242,
167,
102,
112,
23821,
226,
97,
168,
254,
243,
198,
26230,
796,
3992,
26230,
13,
1925,
5998,
7,
25811,
28,
46659,
62,
25811,
8,
198,
198,
6371,
796,
366,
5450,
1378,
12947,
13,
2616,
332,
13,
785,
14,
12947,
13,
2616,
332,
30,
22766,
34758,
92,
10,
90,
92,
10,
168,
121,
242,
167,
94,
250,
167,
224,
246,
5,
3003,
28,
10827,
5,
494,
28,
40477,
23,
5,
5796,
28,
77,
18504,
62,
71,
774,
1911,
18982,
7,
198,
220,
220,
220,
1388,
14941,
5376,
11,
850,
14941,
5376,
8,
198,
198,
26230,
13,
1136,
7,
6371,
8,
628,
198,
68,
10671,
796,
4639,
13,
19796,
62,
30854,
62,
1525,
62,
87,
6978,
10786,
1003,
9,
58,
31,
312,
2625,
12417,
62,
8002,
8973,
14,
5458,
14,
7146,
14,
7146,
58,
17,
60,
14,
377,
11537,
198,
26845,
796,
9766,
76,
13,
19796,
62,
68,
3639,
62,
1525,
62,
4871,
62,
3672,
7203,
10827,
62,
37150,
13,
15042,
62,
3216,
62,
21280,
4943,
1303,
220,
166,
116,
108,
168,
8955,
167,
241,
97,
198,
198,
10782,
89,
13,
2616,
332,
14906,
47546,
7,
7753,
15235,
11,
6685,
8,
628,
628,
198
] | 2.432018 | 456 |
from tools import loadCmsProcess,writeCfg
from addPoolDBESSource import addPoolDBESSource
from CmsswTask import CmsswTask
import os
| [
6738,
4899,
1330,
3440,
34,
907,
18709,
11,
13564,
34,
40616,
198,
6738,
751,
27201,
11012,
1546,
7416,
1330,
751,
27201,
11012,
1546,
7416,
198,
6738,
327,
76,
824,
86,
25714,
1330,
327,
76,
824,
86,
25714,
198,
11748,
28686,
198
] | 3.219512 | 41 |
import networkx as nx
import matplotlib.pyplot as plt
## add a node
G = nx.Graph()
G.add_node(1)
G.add_nodes_from([2, 3])
H = nx.path_graph(10)
G.add_nodes_from(H)
G.add_node(H)
G.add_node('shopping')
## edges
G.add_edge(1, 2, {'weight': 3.1415})
e = (2, 3)
G.add_edge(*e)
G.add_edges_from([(1,2), (1,3)])
# G.add_edges_from(H.edges)
nx.draw(G, with_labels=True)
plt.show()
G.clear()
edgelist = [('n1','n2'), ('n1','n3'), ('n2','n3')]
H = nx.Graph(edgelist)
nx.draw(H, with_labels= True)
plt.show()
| [
11748,
3127,
87,
355,
299,
87,
198,
11748,
2603,
29487,
8019,
13,
9078,
29487,
355,
458,
83,
198,
198,
2235,
751,
257,
10139,
220,
198,
38,
796,
299,
87,
13,
37065,
3419,
198,
38,
13,
2860,
62,
17440,
7,
16,
8,
198,
38,
13,
2860,
62,
77,
4147,
62,
6738,
26933,
17,
11,
513,
12962,
198,
198,
39,
796,
299,
87,
13,
6978,
62,
34960,
7,
940,
8,
198,
38,
13,
2860,
62,
77,
4147,
62,
6738,
7,
39,
8,
198,
38,
13,
2860,
62,
17440,
7,
39,
8,
198,
38,
13,
2860,
62,
17440,
10786,
1477,
33307,
11537,
198,
2235,
13015,
198,
38,
13,
2860,
62,
14907,
7,
16,
11,
362,
11,
1391,
6,
6551,
10354,
513,
13,
1415,
1314,
30072,
198,
68,
796,
357,
17,
11,
513,
8,
198,
38,
13,
2860,
62,
14907,
46491,
68,
8,
198,
38,
13,
2860,
62,
276,
3212,
62,
6738,
26933,
7,
16,
11,
17,
828,
357,
16,
11,
18,
8,
12962,
198,
2,
402,
13,
2860,
62,
276,
3212,
62,
6738,
7,
39,
13,
276,
3212,
8,
198,
77,
87,
13,
19334,
7,
38,
11,
351,
62,
23912,
1424,
28,
17821,
8,
198,
489,
83,
13,
12860,
3419,
198,
38,
13,
20063,
3419,
628,
198,
276,
25280,
396,
796,
685,
10786,
77,
16,
41707,
77,
17,
33809,
19203,
77,
16,
41707,
77,
18,
33809,
19203,
77,
17,
41707,
77,
18,
11537,
60,
198,
39,
796,
299,
87,
13,
37065,
7,
276,
25280,
396,
8,
198,
77,
87,
13,
19334,
7,
39,
11,
351,
62,
23912,
1424,
28,
6407,
8,
198,
489,
83,
13,
12860,
3419,
198
] | 1.901887 | 265 |
from core.advbase import *
from module.template import Adv_INFUTP
variants = {None: Mona, "RNG": Mona_RNG, "INFUTP": Mona_INFUTP}
| [
6738,
4755,
13,
32225,
8692,
1330,
1635,
198,
6738,
8265,
13,
28243,
1330,
8007,
62,
1268,
37,
3843,
47,
628,
628,
198,
198,
25641,
1187,
796,
1391,
14202,
25,
2892,
64,
11,
366,
49,
10503,
1298,
2892,
64,
62,
49,
10503,
11,
366,
1268,
37,
3843,
47,
1298,
2892,
64,
62,
1268,
37,
3843,
47,
92,
198
] | 2.368421 | 57 |
username = '' #enter your facebook user name
password = '' #enter your facebook password
| [
29460,
796,
10148,
1303,
9255,
534,
23960,
2836,
1438,
198,
28712,
796,
10148,
1303,
9255,
534,
23960,
9206,
198
] | 4.684211 | 19 |
import sys
from datetime import datetime
import error_handler
import valr
UNKNOWN_TREND = "unknown"
DOWN_TREND = "down"
UP_TREND = "up"
if __name__ == "__main__":
sys.excepthook = error_handler.excepthook
orders = [x for x in valr.get_open_orders() if x["side"].upper() == "BUY"]
if len(orders) > 0:
log("open orders found: closing")
valr.close_open_buys()
market_summary = valr.market_summary()
base_price = float(market_summary["lastTradedPrice"])
else:
sell_price = valr.sell_at_market()
log(f"Sold at {sell_price}")
base_price = sell_price
percentage = 0.33 / 100.0
buy_adjustment = 1 - percentage
buy_price = base_price * buy_adjustment
log(f"Placing buy order at {buy_price}")
valr.buy_order(buy_price)
log("Buy order placed")
| [
11748,
25064,
198,
6738,
4818,
8079,
1330,
4818,
8079,
198,
198,
11748,
4049,
62,
30281,
198,
11748,
1188,
81,
198,
198,
4944,
44706,
62,
5446,
10619,
796,
366,
34680,
1,
198,
41925,
62,
5446,
10619,
796,
366,
2902,
1,
198,
8577,
62,
5446,
10619,
796,
366,
929,
1,
628,
198,
198,
361,
11593,
3672,
834,
6624,
366,
834,
12417,
834,
1298,
198,
220,
220,
220,
25064,
13,
1069,
344,
79,
400,
566,
796,
4049,
62,
30281,
13,
1069,
344,
79,
400,
566,
628,
220,
220,
220,
6266,
796,
685,
87,
329,
2124,
287,
1188,
81,
13,
1136,
62,
9654,
62,
6361,
3419,
611,
2124,
14692,
1589,
1,
4083,
45828,
3419,
6624,
366,
19499,
56,
8973,
198,
220,
220,
220,
611,
18896,
7,
6361,
8,
1875,
657,
25,
198,
220,
220,
220,
220,
220,
220,
220,
2604,
7203,
9654,
6266,
1043,
25,
9605,
4943,
198,
220,
220,
220,
220,
220,
220,
220,
1188,
81,
13,
19836,
62,
9654,
62,
11110,
893,
3419,
628,
220,
220,
220,
220,
220,
220,
220,
1910,
62,
49736,
796,
1188,
81,
13,
10728,
62,
49736,
3419,
198,
220,
220,
220,
220,
220,
220,
220,
2779,
62,
20888,
796,
12178,
7,
10728,
62,
49736,
14692,
12957,
2898,
5286,
18124,
8973,
8,
198,
220,
220,
220,
2073,
25,
198,
220,
220,
220,
220,
220,
220,
220,
3677,
62,
20888,
796,
1188,
81,
13,
7255,
62,
265,
62,
10728,
3419,
198,
220,
220,
220,
220,
220,
220,
220,
2604,
7,
69,
1,
33873,
379,
1391,
7255,
62,
20888,
92,
4943,
198,
220,
220,
220,
220,
220,
220,
220,
2779,
62,
20888,
796,
3677,
62,
20888,
628,
220,
220,
220,
5873,
796,
657,
13,
2091,
1220,
1802,
13,
15,
198,
220,
220,
220,
2822,
62,
23032,
434,
796,
352,
532,
5873,
198,
220,
220,
220,
2822,
62,
20888,
796,
2779,
62,
20888,
1635,
2822,
62,
23032,
434,
198,
220,
220,
220,
2604,
7,
69,
1,
3646,
4092,
2822,
1502,
379,
1391,
17846,
62,
20888,
92,
4943,
198,
220,
220,
220,
1188,
81,
13,
17846,
62,
2875,
7,
17846,
62,
20888,
8,
198,
220,
220,
220,
2604,
7203,
14518,
1502,
4624,
4943,
198
] | 2.377841 | 352 |
import csv
from google.cloud import storage
import logging
def write_tsv(filename, files, fieldnames=None):
"""
write to tsv file
Args:
filename(str): file name
files(list(dict)): list of file info
[
{
"GUID": "guid_example",
"filename": "example",
"size": 100,
"acl": "['open']",
"md5": "md5_hash",
},
]
fieldnames(list(str)): list of column names
Returns:
filename(str): file name
"""
if not files:
return None
# Get column names
fieldnames = fieldnames or files[0].keys()
# Open tsv file
with open(filename, mode="w") as outfile:
writer = csv.DictWriter(outfile, delimiter="\t", fieldnames=fieldnames)
# write header
writer.writeheader()
# Write data
for f in files:
for field in fieldnames:
if field not in f:
f[field] = None
writer.writerow(f)
return filename
def upload_file(bucket_name, source_file_name, destination_blob_name):
"""
Upload a file to an gs bucket
Args:
file_name: File to upload
bucket: Bucket to upload to
object_name: gs object name. If not specified then file_name is used
Returns:
Bool: True if file was uploaded, else False
"""
# Initialize a storage client.
storage_client = storage.Client()
try:
# Initialize a bucket client.
bucket = storage_client.bucket(bucket_name)
# Create a dest blob.
blob = bucket.blob(destination_blob_name)
# Upload file to the bucket
blob.upload_from_filename(source_file_name)
except Exception as e:
logging.error(
"Fail to upload {} to {}. Detail {}".format(
source_file_name, bucket_name, e
)
)
return False
logging.info(
"File {} uploaded to {}/{}.".format(source_file_name, bucket_name, destination_blob_name)
)
return True
| [
11748,
269,
21370,
198,
6738,
23645,
13,
17721,
1330,
6143,
198,
198,
11748,
18931,
628,
198,
4299,
3551,
62,
912,
85,
7,
34345,
11,
3696,
11,
2214,
14933,
28,
14202,
2599,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
3551,
284,
256,
21370,
2393,
198,
220,
220,
220,
943,
14542,
25,
198,
220,
220,
220,
220,
220,
220,
220,
29472,
7,
2536,
2599,
2393,
1438,
198,
220,
220,
220,
220,
220,
220,
220,
3696,
7,
4868,
7,
11600,
8,
2599,
1351,
286,
2393,
7508,
198,
220,
220,
220,
220,
220,
220,
220,
685,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1391,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
366,
38,
27586,
1298,
366,
5162,
312,
62,
20688,
1600,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
366,
34345,
1298,
366,
20688,
1600,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
366,
7857,
1298,
1802,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
366,
37779,
1298,
12878,
6,
9654,
20520,
1600,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
366,
9132,
20,
1298,
366,
9132,
20,
62,
17831,
1600,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
8964,
198,
220,
220,
220,
220,
220,
220,
220,
2361,
198,
220,
220,
220,
220,
220,
220,
220,
2214,
14933,
7,
4868,
7,
2536,
8,
2599,
1351,
286,
5721,
3891,
198,
220,
220,
220,
16409,
25,
198,
220,
220,
220,
220,
220,
220,
220,
29472,
7,
2536,
2599,
2393,
1438,
198,
220,
220,
220,
37227,
628,
220,
220,
220,
611,
407,
3696,
25,
198,
220,
220,
220,
220,
220,
220,
220,
1441,
6045,
198,
220,
220,
220,
1303,
3497,
5721,
3891,
198,
220,
220,
220,
2214,
14933,
796,
2214,
14933,
393,
3696,
58,
15,
4083,
13083,
3419,
198,
220,
220,
220,
1303,
4946,
256,
21370,
2393,
198,
220,
220,
220,
351,
1280,
7,
34345,
11,
4235,
2625,
86,
4943,
355,
503,
7753,
25,
198,
220,
220,
220,
220,
220,
220,
220,
6260,
796,
269,
21370,
13,
35,
713,
34379,
7,
448,
7753,
11,
46728,
2676,
2625,
59,
83,
1600,
2214,
14933,
28,
3245,
14933,
8,
198,
220,
220,
220,
220,
220,
220,
220,
1303,
3551,
13639,
198,
220,
220,
220,
220,
220,
220,
220,
6260,
13,
13564,
25677,
3419,
198,
220,
220,
220,
220,
220,
220,
220,
1303,
19430,
1366,
198,
220,
220,
220,
220,
220,
220,
220,
329,
277,
287,
3696,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
329,
2214,
287,
2214,
14933,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
611,
2214,
407,
287,
277,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
277,
58,
3245,
60,
796,
6045,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
6260,
13,
16002,
322,
7,
69,
8,
628,
220,
220,
220,
1441,
29472,
628,
198,
4299,
9516,
62,
7753,
7,
27041,
316,
62,
3672,
11,
2723,
62,
7753,
62,
3672,
11,
10965,
62,
2436,
672,
62,
3672,
2599,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
36803,
257,
2393,
284,
281,
308,
82,
19236,
198,
220,
220,
220,
220,
198,
220,
220,
220,
943,
14542,
25,
198,
220,
220,
220,
220,
220,
220,
220,
2393,
62,
3672,
25,
9220,
284,
9516,
198,
220,
220,
220,
220,
220,
220,
220,
19236,
25,
48353,
284,
9516,
284,
198,
220,
220,
220,
220,
220,
220,
220,
2134,
62,
3672,
25,
308,
82,
2134,
1438,
13,
1002,
407,
7368,
788,
2393,
62,
3672,
318,
973,
198,
220,
220,
220,
16409,
25,
198,
220,
220,
220,
220,
220,
220,
220,
347,
970,
25,
6407,
611,
2393,
373,
19144,
11,
2073,
10352,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
1303,
20768,
1096,
257,
6143,
5456,
13,
198,
220,
220,
220,
6143,
62,
16366,
796,
6143,
13,
11792,
3419,
628,
220,
220,
220,
1949,
25,
198,
220,
220,
220,
220,
220,
220,
220,
1303,
20768,
1096,
257,
19236,
5456,
13,
198,
220,
220,
220,
220,
220,
220,
220,
19236,
796,
6143,
62,
16366,
13,
27041,
316,
7,
27041,
316,
62,
3672,
8,
198,
220,
220,
220,
220,
220,
220,
220,
1303,
13610,
257,
2244,
44812,
13,
198,
220,
220,
220,
220,
220,
220,
220,
44812,
796,
19236,
13,
2436,
672,
7,
16520,
1883,
62,
2436,
672,
62,
3672,
8,
198,
220,
220,
220,
220,
220,
220,
220,
1303,
36803,
2393,
284,
262,
19236,
198,
220,
220,
220,
220,
220,
220,
220,
44812,
13,
25850,
62,
6738,
62,
34345,
7,
10459,
62,
7753,
62,
3672,
8,
628,
220,
220,
220,
2845,
35528,
355,
304,
25,
198,
220,
220,
220,
220,
220,
220,
220,
18931,
13,
18224,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
366,
39044,
284,
9516,
23884,
284,
23884,
13,
42585,
23884,
1911,
18982,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2723,
62,
7753,
62,
3672,
11,
19236,
62,
3672,
11,
304,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1267,
198,
220,
220,
220,
220,
220,
220,
220,
1267,
198,
220,
220,
220,
220,
220,
220,
220,
1441,
10352,
628,
220,
220,
220,
18931,
13,
10951,
7,
198,
220,
220,
220,
220,
220,
220,
220,
366,
8979,
23884,
19144,
284,
23884,
14,
90,
92,
526,
13,
18982,
7,
10459,
62,
7753,
62,
3672,
11,
19236,
62,
3672,
11,
10965,
62,
2436,
672,
62,
3672,
8,
198,
220,
220,
220,
1267,
198,
220,
220,
220,
1441,
6407,
198
] | 2.16444 | 973 |
from sublime_db.core.typecheck import (
Any,
Callable,
Optional
)
import sublime
import sublime_plugin
from sublime_db import core
from sublime_db import ui
from sublime_db.main.breakpoints import Breakpoints, Breakpoint, FunctionBreakpoint
from .commands import AutoCompleteTextInputHandler
@core.async
@core.async
| [
6738,
41674,
62,
9945,
13,
7295,
13,
4906,
9122,
1330,
357,
198,
197,
7149,
11,
198,
197,
14134,
540,
11,
198,
197,
30719,
198,
8,
198,
198,
11748,
41674,
198,
11748,
41674,
62,
33803,
198,
198,
6738,
41674,
62,
9945,
1330,
4755,
198,
6738,
41674,
62,
9945,
1330,
334,
72,
198,
6738,
41674,
62,
9945,
13,
12417,
13,
9032,
13033,
1330,
12243,
13033,
11,
12243,
4122,
11,
15553,
31737,
4122,
198,
6738,
764,
9503,
1746,
1330,
11160,
20988,
8206,
20560,
25060,
628,
198,
31,
7295,
13,
292,
13361,
198,
197,
198,
31,
7295,
13,
292,
13361,
628
] | 3.360825 | 97 |
__author__ = 'wanglei02'
from django import template
from django.utils.html import conditional_escape
from django.utils.safestring import mark_safe
register = template.Library()
@register.filter(name='join_link', needs_autoescape=True)
| [
834,
9800,
834,
796,
705,
86,
9248,
72,
2999,
6,
198,
198,
6738,
42625,
14208,
1330,
11055,
198,
6738,
42625,
14208,
13,
26791,
13,
6494,
1330,
26340,
62,
41915,
198,
6738,
42625,
14208,
13,
26791,
13,
49585,
395,
1806,
1330,
1317,
62,
21230,
198,
198,
30238,
796,
11055,
13,
23377,
3419,
628,
198,
31,
30238,
13,
24455,
7,
3672,
11639,
22179,
62,
8726,
3256,
2476,
62,
2306,
3028,
36435,
28,
17821,
8,
198
] | 3.287671 | 73 |
import copy
from dataclasses import dataclass
import dataclasses
import functools
import io
import logging
from multiprocessing.connection import wait
import uuid
from typing import Any, Dict, List, Optional, Tuple, Union
from attr import field
from concurrent.futures import ProcessPoolExecutor
import pandas as pd
import pynvml
from transformers import (
AutoConfig,
HfArgumentParser,
T5ForConditionalGeneration,
AutoModelForQuestionAnswering,
DistilBertForQuestionAnswering,
ViTForImageClassification,
AutoModelForCausalLM,
)
import requests
import os
os.environ["CUDA_VISIBLE_DEVICES"] = "0,1,2,3,4,5,6,7"
import torch
import time
import threading
import multiprocessing as mp
from multiprocessing import Process, Manager
from multiprocessing.managers import BaseManager
from fastapi import FastAPI
import json
from requests import Request
import numpy as np
from scipy.special import softmax
from transformers import AutoTokenizer
from tqdm import tqdm
import gc
import dill
# ====== ray serve
import ray
from ray import data, serve
from ray.serve import pipeline
from ray.util.metrics import Counter, Gauge, Histogram, Metric
# ====== hfutils
from hfutils.arg_parser import RayArguments
from hfutils.logger import Logger
from hfutils.calibration import agg_logits, temperature_scale
from hfutils.constants import MODEL_KEYS
from hfutils.pipe.t5 import (
T5_ENCODER_INPUTS,
T5_ENCODER_OUTPUTS,
T5_DECODER_INPUTS,
T5_DECODER_OUTPUTS,
T5PyTorchPipe,
T5PytorchPipeRandom,
)
from hfutils.pipe.bert import (
BERT_INPUTS,
BERT_OUTPUTS,
BertPyTorchPipeForQuestionAnswering,
BertPytorchPipeRandom,
)
from hfutils.pipe.vit import (
VIT_INPUTS,
VIT_OUTPUTS,
ViTPyTorchPipeForImageClassification,
ViTPytorchPipeRandom,
)
from hfutils.pipe.gpt import GPTPytorchPipeRandom
from hfutils.pipe.distilbert import (
DISTILBERT_INPUTS,
DISTILBERT_OUTPUTS,
DistilBertPyTorchPipeForQuestionAnswering,
)
from hfutils.pipe.gpt import GPT_INPUTS, GPT_OUTPUTS, GPTLMHeadModelPipe
from hfutils.calibration import temperature_scale
from hfutils.constants import np_to_torch_dtype
from hfutils.options import (
ReplicationOptions,
SystemOptions,
EnsembleOptions,
ParallelOptions,
ModelConfig,
HostOptions,
)
# ======= DEFINE CONSTANTS =========
T5_TASK_LABELS = [1176, 6136, 59] # HACK with GLUE labels
m = functools.partial(softmax, axis=1)
VISIBLE_GPUS = [str(i) for i in range(torch.cuda.device_count())]
m = torch.nn.Softmax(dim=1)
@dataclass
parser = HfArgumentParser(Arguments)
args = parser.parse_args_into_dataclasses()[0]
# ======= PARSE CONFIGURATION =========
# with open(args.ensemble_cfg, "r") as fp:
# ensemble_config = json.load(fp)
with open(args.model_cfg, "r") as fp:
model_config = json.load(fp)
ensembles = model_config["ensembles"]
base_dir = model_config["base_dir"]
alpha = model_config["alpha"]
type = model_config["type"]
instance = model_config["instance"]
host_options = {
ins["host"]: HostOptions(
host=ins["host"],
# alpha=alpha,
# ens=len(ensembles),
type=type,
placement={
gid: [
ModelConfig(
name=model["name"],
path=os.path.join(base_dir, model_config[model["name"]]["path"]),
type=model_config[model["name"]]["type"],
stages=model_config[model["name"]]["parallel_stages"],
ppos=model["stage"],
epos=ensembles.index(model["name"]),
temp=model_config[model["name"]]["temperature"],
util_params=model_config[model["name"]]["util_params"],
ray_actor_options={
"num_cpus": 1,
"num_gpus": 1 / len(models),
"resources": {ins["host"]: 1},
},
key="_".join([ins["host"], model["name"], gid, str(i)]),
)
for i, model in enumerate(models)
]
for gid, models in ins["placement"].items()
},
)
for ins in instance
}
# host_resource = {
# ins["host"]: sum([len(models) for gid, models in ins["placement"].items()])
# for ins in instance
# }
# model_replicas = {
# name: sum(
# [
# 1
# for ins in instance
# for gid, models in ins["placement"].items()
# for model in models
# if model["name"] == name
# ]
# )
# for name in ensembles
# }
system_options = SystemOptions(
alpha=alpha,
ens=len(ensembles),
type=type,
ensemble_options=[
EnsembleOptions(
epos=i,
th=model_config[name]["threshold"],
name=name,
parallel_options=[
ParallelOptions(
stages=model_config[name]["parallel_stages"],
ppos=p,
replications=[
model.key
for host in host_options.values()
for models in host.placement.values()
for model in models
if model.epos == i and model.ppos == p
],
)
for p in range(model_config[name]["parallel_stages"])
],
)
for i, name in enumerate(ensembles)
],
)
# for idx, name in enumerate(ensembles):
# meta = model_config[name]
# path = os.path.join(base_dir, meta["path"])
# threshold = meta["threshold"]
# temperature = meta["temperature"]
# stages = meta["parallel_stages"]
# util_params = meta["util_params"]
# instance = meta["instance"]
# parallel_options = [
# ParallelOptions(
# stages=stages,
# ppos=p,
# replication_options=[
# ReplicationOptions(
# k,
# "_".join([name, idx, ins["stage"], k]),
# torch.device(ins["device"]),
# )
# for k in range(ins["count"])
# for ins in instance
# if ins["stage"] == p
# ],
# )
# for p in range(stages)
# ]
# for i, ins in enumerate(instance):
# for k in range(ins["count"]):
# key = "_".join([name, idx, ins["stage"], k])
# replication_options = ReplicationOptions(
# k, key, torch.device(ins["device"])
# )
# config = ModelConfig(
# name,
# path,
# type,
# stages,
# ins["stage"],
# idx,
# len(ensembles),
# alpha,
# temperature,
# threshold,
# util_params,
# ins["device"],
# k,
# )
# deploy_config.append(config)
# ====== MODEL DEFINATION ==============
@serve.deployment(max_concurrent_queries=100)
@serve.deployment(max_concurrent_queries=1000)
# ray.init(address="ray://129.215.164.41:10001")
import socket
# ====== START SERVER ==============
# ray.init(namespace=args.namespace, num_cpus=80, num_gpus=torch.cuda.device_count())
host_ip = get_host_ip()
ray.init(address=f"ray://{host_ip}:10001", namespace=args.namespace)
serve.start(detached=True, http_options=serve.HTTPOptions(port=8888))
# print("ray initialized", args)
for host, h_op in host_options.items():
for gid, models in h_op.placement.items():
for i, model in enumerate(models):
key = "_".join([host, model.name, gid, str(i)])
HServeModel.options(
name=key, ray_actor_options=model.ray_actor_options
).deploy(options=host_options, model_id=i, key=key)
# for e_op in system_options.ensemble_options:
# for p_op in e_op.parallel_options:
# for r_op in p_op.replication_options:
# HServeModel.options(
# name=r_op.key, ray_actor_options={"num_cpus": 4, "num_gpus": 2},
# ).deploy(
# options=system_options,
# epos=e_op.epos,
# ppos=p_op.ppos,
# replica=r_op.replica,
# )
for host, _ in host_options.items():
for r in range(1):
HybridScheduler.options(
name=f"hybrid-scheduler_{host}_{r}",
num_replicas=1,
ray_actor_options={"num_cpus": 0.1, "resources": {f"{host}": 1}},
).deploy(system_options, r)
| [
11748,
4866,
198,
6738,
4818,
330,
28958,
1330,
4818,
330,
31172,
198,
11748,
4818,
330,
28958,
198,
11748,
1257,
310,
10141,
198,
11748,
33245,
198,
11748,
18931,
198,
6738,
18540,
305,
919,
278,
13,
38659,
1330,
4043,
198,
11748,
334,
27112,
198,
6738,
19720,
1330,
4377,
11,
360,
713,
11,
7343,
11,
32233,
11,
309,
29291,
11,
4479,
198,
6738,
708,
81,
1330,
2214,
198,
6738,
24580,
13,
69,
315,
942,
1330,
10854,
27201,
23002,
38409,
198,
11748,
19798,
292,
355,
279,
67,
198,
11748,
279,
2047,
85,
4029,
198,
198,
6738,
6121,
364,
1330,
357,
198,
220,
220,
220,
11160,
16934,
11,
198,
220,
220,
220,
367,
69,
28100,
1713,
46677,
11,
198,
220,
220,
220,
309,
20,
1890,
25559,
1859,
8645,
341,
11,
198,
220,
220,
220,
11160,
17633,
1890,
24361,
2025,
2032,
1586,
11,
198,
220,
220,
220,
4307,
346,
33,
861,
1890,
24361,
2025,
2032,
1586,
11,
198,
220,
220,
220,
16049,
51,
1890,
5159,
9487,
2649,
11,
198,
220,
220,
220,
11160,
17633,
1890,
24334,
6775,
31288,
11,
198,
8,
198,
11748,
7007,
198,
11748,
28686,
198,
198,
418,
13,
268,
2268,
14692,
43633,
5631,
62,
29817,
34563,
62,
39345,
34444,
8973,
796,
366,
15,
11,
16,
11,
17,
11,
18,
11,
19,
11,
20,
11,
21,
11,
22,
1,
198,
198,
11748,
28034,
198,
11748,
640,
198,
11748,
4704,
278,
198,
11748,
18540,
305,
919,
278,
355,
29034,
198,
6738,
18540,
305,
919,
278,
1330,
10854,
11,
9142,
198,
6738,
18540,
305,
919,
278,
13,
805,
10321,
1330,
7308,
13511,
198,
6738,
3049,
15042,
1330,
12549,
17614,
198,
11748,
33918,
198,
6738,
7007,
1330,
19390,
198,
11748,
299,
32152,
355,
45941,
198,
6738,
629,
541,
88,
13,
20887,
1330,
2705,
9806,
198,
6738,
6121,
364,
1330,
11160,
30642,
7509,
198,
6738,
256,
80,
36020,
1330,
256,
80,
36020,
198,
11748,
308,
66,
198,
11748,
288,
359,
198,
198,
2,
29335,
28,
26842,
4691,
198,
11748,
26842,
198,
6738,
26842,
1330,
1366,
11,
4691,
198,
6738,
26842,
13,
2655,
303,
1330,
11523,
198,
6738,
26842,
13,
22602,
13,
4164,
10466,
1330,
15034,
11,
35094,
469,
11,
5590,
21857,
11,
3395,
1173,
198,
198,
2,
29335,
28,
289,
69,
26791,
198,
6738,
289,
69,
26791,
13,
853,
62,
48610,
1330,
7760,
28100,
2886,
198,
6738,
289,
69,
26791,
13,
6404,
1362,
1330,
5972,
1362,
198,
6738,
289,
69,
26791,
13,
9948,
571,
1358,
1330,
4194,
62,
6404,
896,
11,
5951,
62,
9888,
198,
6738,
289,
69,
26791,
13,
9979,
1187,
1330,
19164,
3698,
62,
7336,
16309,
198,
6738,
289,
69,
26791,
13,
34360,
13,
83,
20,
1330,
357,
198,
220,
220,
220,
309,
20,
62,
24181,
3727,
1137,
62,
1268,
30076,
50,
11,
198,
220,
220,
220,
309,
20,
62,
24181,
3727,
1137,
62,
2606,
7250,
3843,
50,
11,
198,
220,
220,
220,
309,
20,
62,
41374,
3727,
1137,
62,
1268,
30076,
50,
11,
198,
220,
220,
220,
309,
20,
62,
41374,
3727,
1137,
62,
2606,
7250,
3843,
50,
11,
198,
220,
220,
220,
309,
20,
20519,
15884,
354,
47,
3757,
11,
198,
220,
220,
220,
309,
20,
20519,
13165,
354,
47,
3757,
29531,
11,
198,
8,
198,
6738,
289,
69,
26791,
13,
34360,
13,
4835,
1330,
357,
198,
220,
220,
220,
347,
17395,
62,
1268,
30076,
50,
11,
198,
220,
220,
220,
347,
17395,
62,
2606,
7250,
3843,
50,
11,
198,
220,
220,
220,
22108,
20519,
15884,
354,
47,
3757,
1890,
24361,
2025,
2032,
1586,
11,
198,
220,
220,
220,
22108,
20519,
13165,
354,
47,
3757,
29531,
11,
198,
8,
198,
6738,
289,
69,
26791,
13,
34360,
13,
85,
270,
1330,
357,
198,
220,
220,
220,
569,
2043,
62,
1268,
30076,
50,
11,
198,
220,
220,
220,
569,
2043,
62,
2606,
7250,
3843,
50,
11,
198,
220,
220,
220,
16049,
7250,
88,
15884,
354,
47,
3757,
1890,
5159,
9487,
2649,
11,
198,
220,
220,
220,
16049,
7250,
88,
13165,
354,
47,
3757,
29531,
11,
198,
8,
198,
6738,
289,
69,
26791,
13,
34360,
13,
70,
457,
1330,
14714,
7250,
88,
13165,
354,
47,
3757,
29531,
198,
6738,
289,
69,
26791,
13,
34360,
13,
17080,
346,
4835,
1330,
357,
198,
220,
220,
220,
360,
8808,
4146,
13246,
51,
62,
1268,
30076,
50,
11,
198,
220,
220,
220,
360,
8808,
4146,
13246,
51,
62,
2606,
7250,
3843,
50,
11,
198,
220,
220,
220,
4307,
346,
33,
861,
20519,
15884,
354,
47,
3757,
1890,
24361,
2025,
2032,
1586,
11,
198,
8,
198,
6738,
289,
69,
26791,
13,
34360,
13,
70,
457,
1330,
402,
11571,
62,
1268,
30076,
50,
11,
402,
11571,
62,
2606,
7250,
3843,
50,
11,
402,
11571,
31288,
13847,
17633,
47,
3757,
198,
6738,
289,
69,
26791,
13,
9948,
571,
1358,
1330,
5951,
62,
9888,
198,
6738,
289,
69,
26791,
13,
9979,
1187,
1330,
45941,
62,
1462,
62,
13165,
354,
62,
67,
4906,
198,
6738,
289,
69,
26791,
13,
25811,
1330,
357,
198,
220,
220,
220,
18407,
3299,
29046,
11,
198,
220,
220,
220,
4482,
29046,
11,
198,
220,
220,
220,
2039,
15140,
29046,
11,
198,
220,
220,
220,
42945,
29046,
11,
198,
220,
220,
220,
9104,
16934,
11,
198,
220,
220,
220,
14504,
29046,
11,
198,
8,
198,
198,
2,
29335,
855,
23449,
8881,
7102,
2257,
1565,
4694,
796,
2559,
198,
51,
20,
62,
51,
1921,
42,
62,
48780,
37142,
796,
685,
1157,
4304,
11,
718,
20809,
11,
7863,
60,
220,
1303,
367,
8120,
351,
10188,
8924,
14722,
198,
76,
796,
1257,
310,
10141,
13,
47172,
7,
4215,
9806,
11,
16488,
28,
16,
8,
198,
29817,
34563,
62,
16960,
2937,
796,
685,
2536,
7,
72,
8,
329,
1312,
287,
2837,
7,
13165,
354,
13,
66,
15339,
13,
25202,
62,
9127,
3419,
15437,
198,
76,
796,
28034,
13,
20471,
13,
18380,
9806,
7,
27740,
28,
16,
8,
628,
198,
31,
19608,
330,
31172,
628,
198,
48610,
796,
367,
69,
28100,
1713,
46677,
7,
28100,
2886,
8,
198,
22046,
796,
30751,
13,
29572,
62,
22046,
62,
20424,
62,
19608,
330,
28958,
3419,
58,
15,
60,
628,
198,
2,
29335,
855,
29463,
5188,
25626,
4261,
6234,
796,
2559,
198,
2,
351,
1280,
7,
22046,
13,
1072,
11306,
62,
37581,
11,
366,
81,
4943,
355,
277,
79,
25,
198,
2,
220,
220,
220,
220,
34549,
62,
11250,
796,
33918,
13,
2220,
7,
46428,
8,
198,
198,
4480,
1280,
7,
22046,
13,
19849,
62,
37581,
11,
366,
81,
4943,
355,
277,
79,
25,
198,
220,
220,
220,
2746,
62,
11250,
796,
33918,
13,
2220,
7,
46428,
8,
198,
198,
1072,
2022,
829,
796,
2746,
62,
11250,
14692,
1072,
2022,
829,
8973,
198,
8692,
62,
15908,
796,
2746,
62,
11250,
14692,
8692,
62,
15908,
8973,
198,
26591,
796,
2746,
62,
11250,
14692,
26591,
8973,
198,
4906,
796,
2746,
62,
11250,
14692,
4906,
8973,
198,
39098,
796,
2746,
62,
11250,
14692,
39098,
8973,
628,
198,
4774,
62,
25811,
796,
1391,
198,
220,
220,
220,
1035,
14692,
4774,
1,
5974,
14504,
29046,
7,
198,
220,
220,
220,
220,
220,
220,
220,
2583,
28,
1040,
14692,
4774,
33116,
198,
220,
220,
220,
220,
220,
220,
220,
1303,
17130,
28,
26591,
11,
198,
220,
220,
220,
220,
220,
220,
220,
1303,
3140,
28,
11925,
7,
1072,
2022,
829,
828,
198,
220,
220,
220,
220,
220,
220,
220,
2099,
28,
4906,
11,
198,
220,
220,
220,
220,
220,
220,
220,
13127,
34758,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
308,
312,
25,
685,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
9104,
16934,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1438,
28,
19849,
14692,
3672,
33116,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
3108,
28,
418,
13,
6978,
13,
22179,
7,
8692,
62,
15908,
11,
2746,
62,
11250,
58,
19849,
14692,
3672,
8973,
7131,
1,
6978,
8973,
828,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2099,
28,
19849,
62,
11250,
58,
19849,
14692,
3672,
8973,
7131,
1,
4906,
33116,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
9539,
28,
19849,
62,
11250,
58,
19849,
14692,
3672,
8973,
7131,
1,
1845,
29363,
62,
301,
1095,
33116,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
279,
1930,
28,
19849,
14692,
14247,
33116,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
304,
1930,
28,
1072,
2022,
829,
13,
9630,
7,
19849,
14692,
3672,
8973,
828,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
20218,
28,
19849,
62,
11250,
58,
19849,
14692,
3672,
8973,
7131,
1,
11498,
21069,
33116,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
7736,
62,
37266,
28,
19849,
62,
11250,
58,
19849,
14692,
3672,
8973,
7131,
1,
22602,
62,
37266,
33116,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
26842,
62,
11218,
62,
25811,
34758,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
366,
22510,
62,
13155,
385,
1298,
352,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
366,
22510,
62,
31197,
385,
1298,
352,
1220,
18896,
7,
27530,
828,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
366,
37540,
1298,
1391,
1040,
14692,
4774,
1,
5974,
352,
5512,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
8964,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1994,
2625,
62,
1911,
22179,
26933,
1040,
14692,
4774,
33116,
2746,
14692,
3672,
33116,
308,
312,
11,
965,
7,
72,
15437,
828,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1267,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
329,
1312,
11,
2746,
287,
27056,
378,
7,
27530,
8,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2361,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
329,
308,
312,
11,
4981,
287,
1035,
14692,
489,
5592,
1,
4083,
23814,
3419,
198,
220,
220,
220,
220,
220,
220,
220,
8964,
198,
220,
220,
220,
1267,
198,
220,
220,
220,
329,
1035,
287,
4554,
198,
92,
198,
198,
2,
2583,
62,
31092,
796,
1391,
198,
2,
220,
220,
220,
220,
1035,
14692,
4774,
1,
5974,
2160,
26933,
11925,
7,
27530,
8,
329,
308,
312,
11,
4981,
287,
1035,
14692,
489,
5592,
1,
4083,
23814,
3419,
12962,
198,
2,
220,
220,
220,
220,
329,
1035,
287,
4554,
198,
2,
1782,
198,
198,
2,
2746,
62,
35666,
44645,
796,
1391,
198,
2,
220,
220,
220,
220,
1438,
25,
2160,
7,
198,
2,
220,
220,
220,
220,
220,
220,
220,
220,
685,
198,
2,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
352,
198,
2,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
329,
1035,
287,
4554,
198,
2,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
329,
308,
312,
11,
4981,
287,
1035,
14692,
489,
5592,
1,
4083,
23814,
3419,
198,
2,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
329,
2746,
287,
4981,
198,
2,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
611,
2746,
14692,
3672,
8973,
6624,
1438,
198,
2,
220,
220,
220,
220,
220,
220,
220,
220,
2361,
198,
2,
220,
220,
220,
220,
1267,
198,
2,
220,
220,
220,
220,
329,
1438,
287,
551,
4428,
829,
198,
2,
1782,
198,
198,
10057,
62,
25811,
796,
4482,
29046,
7,
198,
220,
220,
220,
17130,
28,
26591,
11,
198,
220,
220,
220,
3140,
28,
11925,
7,
1072,
2022,
829,
828,
198,
220,
220,
220,
2099,
28,
4906,
11,
198,
220,
220,
220,
34549,
62,
25811,
41888,
198,
220,
220,
220,
220,
220,
220,
220,
2039,
15140,
29046,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
304,
1930,
28,
72,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
294,
28,
19849,
62,
11250,
58,
3672,
7131,
1,
400,
10126,
33116,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1438,
28,
3672,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
10730,
62,
25811,
41888,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
42945,
29046,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
9539,
28,
19849,
62,
11250,
58,
3672,
7131,
1,
1845,
29363,
62,
301,
1095,
33116,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
279,
1930,
28,
79,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2186,
3736,
41888,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2746,
13,
2539,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
329,
2583,
287,
2583,
62,
25811,
13,
27160,
3419,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
329,
4981,
287,
2583,
13,
489,
5592,
13,
27160,
3419,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
329,
2746,
287,
4981,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
611,
2746,
13,
538,
418,
6624,
1312,
290,
2746,
13,
381,
418,
6624,
279,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
16589,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1267,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
329,
279,
287,
2837,
7,
19849,
62,
11250,
58,
3672,
7131,
1,
1845,
29363,
62,
301,
1095,
8973,
8,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
16589,
198,
220,
220,
220,
220,
220,
220,
220,
1267,
198,
220,
220,
220,
220,
220,
220,
220,
329,
1312,
11,
1438,
287,
27056,
378,
7,
1072,
2022,
829,
8,
198,
220,
220,
220,
16589,
198,
8,
628,
198,
2,
329,
4686,
87,
11,
1438,
287,
27056,
378,
7,
1072,
2022,
829,
2599,
198,
2,
220,
220,
220,
220,
13634,
796,
2746,
62,
11250,
58,
3672,
60,
198,
198,
2,
220,
220,
220,
220,
3108,
796,
28686,
13,
6978,
13,
22179,
7,
8692,
62,
15908,
11,
13634,
14692,
6978,
8973,
8,
198,
2,
220,
220,
220,
220,
11387,
796,
13634,
14692,
400,
10126,
8973,
198,
2,
220,
220,
220,
220,
5951,
796,
13634,
14692,
11498,
21069,
8973,
198,
2,
220,
220,
220,
220,
9539,
796,
13634,
14692,
1845,
29363,
62,
301,
1095,
8973,
198,
2,
220,
220,
220,
220,
7736,
62,
37266,
796,
13634,
14692,
22602,
62,
37266,
8973,
198,
198,
2,
220,
220,
220,
220,
4554,
796,
13634,
14692,
39098,
8973,
198,
198,
2,
220,
220,
220,
220,
10730,
62,
25811,
796,
685,
198,
2,
220,
220,
220,
220,
220,
220,
220,
220,
42945,
29046,
7,
198,
2,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
9539,
28,
301,
1095,
11,
198,
2,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
279,
1930,
28,
79,
11,
198,
2,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
30330,
62,
25811,
41888,
198,
2,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
18407,
3299,
29046,
7,
198,
2,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
479,
11,
198,
2,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
45434,
1911,
22179,
26933,
3672,
11,
4686,
87,
11,
1035,
14692,
14247,
33116,
479,
46570,
198,
2,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
28034,
13,
25202,
7,
1040,
14692,
25202,
8973,
828,
198,
2,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1267,
198,
2,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
329,
479,
287,
2837,
7,
1040,
14692,
9127,
8973,
8,
198,
2,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
329,
1035,
287,
4554,
198,
2,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
611,
1035,
14692,
14247,
8973,
6624,
279,
198,
2,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
16589,
198,
2,
220,
220,
220,
220,
220,
220,
220,
220,
1267,
198,
2,
220,
220,
220,
220,
220,
220,
220,
220,
329,
279,
287,
2837,
7,
301,
1095,
8,
198,
2,
220,
220,
220,
220,
2361,
198,
198,
2,
220,
220,
220,
220,
329,
1312,
11,
1035,
287,
27056,
378,
7,
39098,
2599,
198,
2,
220,
220,
220,
220,
220,
220,
220,
220,
329,
479,
287,
2837,
7,
1040,
14692,
9127,
8973,
2599,
198,
2,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1994,
796,
45434,
1911,
22179,
26933,
3672,
11,
4686,
87,
11,
1035,
14692,
14247,
33116,
479,
12962,
198,
2,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
30330,
62,
25811,
796,
18407,
3299,
29046,
7,
198,
2,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
479,
11,
1994,
11,
28034,
13,
25202,
7,
1040,
14692,
25202,
8973,
8,
198,
2,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1267,
198,
2,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
4566,
796,
9104,
16934,
7,
198,
2,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1438,
11,
198,
2,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
3108,
11,
198,
2,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2099,
11,
198,
2,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
9539,
11,
198,
2,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1035,
14692,
14247,
33116,
198,
2,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
4686,
87,
11,
198,
2,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
18896,
7,
1072,
2022,
829,
828,
198,
2,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
17130,
11,
198,
2,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
5951,
11,
198,
2,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
11387,
11,
198,
2,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
7736,
62,
37266,
11,
198,
2,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1035,
14692,
25202,
33116,
198,
2,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
479,
11,
198,
2,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1267,
198,
2,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
6061,
62,
11250,
13,
33295,
7,
11250,
8,
198,
198,
2,
29335,
28,
19164,
3698,
5550,
20032,
6234,
796,
25609,
28,
628,
198,
31,
2655,
303,
13,
2934,
1420,
434,
7,
9806,
62,
1102,
14421,
62,
421,
10640,
28,
3064,
8,
628,
198,
31,
2655,
303,
13,
2934,
1420,
434,
7,
9806,
62,
1102,
14421,
62,
421,
10640,
28,
12825,
8,
628,
198,
2,
26842,
13,
15003,
7,
21975,
2625,
2433,
1378,
18741,
13,
23349,
13,
23237,
13,
3901,
25,
3064,
486,
4943,
198,
198,
11748,
17802,
628,
198,
198,
2,
29335,
28,
33303,
18871,
5959,
796,
25609,
28,
198,
2,
26842,
13,
15003,
7,
14933,
10223,
28,
22046,
13,
14933,
10223,
11,
997,
62,
13155,
385,
28,
1795,
11,
997,
62,
31197,
385,
28,
13165,
354,
13,
66,
15339,
13,
25202,
62,
9127,
28955,
198,
4774,
62,
541,
796,
651,
62,
4774,
62,
541,
3419,
198,
2433,
13,
15003,
7,
21975,
28,
69,
1,
2433,
1378,
90,
4774,
62,
541,
38362,
3064,
486,
1600,
25745,
28,
22046,
13,
14933,
10223,
8,
198,
2655,
303,
13,
9688,
7,
15255,
2317,
28,
17821,
11,
2638,
62,
25811,
28,
2655,
303,
13,
40717,
29046,
7,
634,
28,
3459,
3459,
4008,
198,
198,
2,
3601,
7203,
2433,
23224,
1600,
26498,
8,
198,
198,
1640,
2583,
11,
289,
62,
404,
287,
2583,
62,
25811,
13,
23814,
33529,
198,
220,
220,
220,
329,
308,
312,
11,
4981,
287,
289,
62,
404,
13,
489,
5592,
13,
23814,
33529,
198,
220,
220,
220,
220,
220,
220,
220,
329,
1312,
11,
2746,
287,
27056,
378,
7,
27530,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1994,
796,
45434,
1911,
22179,
26933,
4774,
11,
2746,
13,
3672,
11,
308,
312,
11,
965,
7,
72,
8,
12962,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
18070,
3760,
17633,
13,
25811,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1438,
28,
2539,
11,
26842,
62,
11218,
62,
25811,
28,
19849,
13,
2433,
62,
11218,
62,
25811,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
6739,
2934,
1420,
7,
25811,
28,
4774,
62,
25811,
11,
2746,
62,
312,
28,
72,
11,
1994,
28,
2539,
8,
198,
198,
2,
329,
304,
62,
404,
287,
1080,
62,
25811,
13,
1072,
11306,
62,
25811,
25,
198,
2,
220,
220,
220,
220,
329,
279,
62,
404,
287,
304,
62,
404,
13,
1845,
29363,
62,
25811,
25,
198,
2,
220,
220,
220,
220,
220,
220,
220,
220,
329,
374,
62,
404,
287,
279,
62,
404,
13,
35666,
3299,
62,
25811,
25,
198,
2,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
18070,
3760,
17633,
13,
25811,
7,
198,
2,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1438,
28,
81,
62,
404,
13,
2539,
11,
26842,
62,
11218,
62,
25811,
28,
4895,
22510,
62,
13155,
385,
1298,
604,
11,
366,
22510,
62,
31197,
385,
1298,
362,
5512,
198,
2,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
6739,
2934,
1420,
7,
198,
2,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
3689,
28,
10057,
62,
25811,
11,
198,
2,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
304,
1930,
28,
68,
62,
404,
13,
538,
418,
11,
198,
2,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
279,
1930,
28,
79,
62,
404,
13,
381,
418,
11,
198,
2,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
30069,
28,
81,
62,
404,
13,
35666,
3970,
11,
198,
2,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1267,
198,
198,
1640,
2583,
11,
4808,
287,
2583,
62,
25811,
13,
23814,
33529,
198,
220,
220,
220,
329,
374,
287,
2837,
7,
16,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
29481,
50,
1740,
18173,
13,
25811,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1438,
28,
69,
1,
12114,
10236,
12,
1416,
704,
18173,
23330,
4774,
92,
23330,
81,
92,
1600,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
997,
62,
35666,
44645,
28,
16,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
26842,
62,
11218,
62,
25811,
28,
4895,
22510,
62,
13155,
385,
1298,
657,
13,
16,
11,
366,
37540,
1298,
1391,
69,
1,
90,
4774,
92,
1298,
352,
92,
5512,
198,
220,
220,
220,
220,
220,
220,
220,
6739,
2934,
1420,
7,
10057,
62,
25811,
11,
374,
8,
198
] | 2.034531 | 4,257 |
# -*- coding: utf-8 -*-
from functionsex import *
from VombatiDB import VombatiDB, showDB, showStats, Workspace
from VombatiDB import errors as dbError
from importMail import ImportMail_MBox
import errors as storeError
import api
from utils import RepairDialogLinking
from libs.plainText import plaintext
import textwrap
if __name__ == '__main__':
# importer=ImportMail_MBox('/home/byaka/Загрузки/gmail_exported/all.mbox')
# tMap=set()
# i1=i2=i3=i4=0
# print
# for _, headers, (body_plain, body_html), attachments in importer:
# if headers.get('message-id'):
# if headers['message-id'] in tMap: i4+=1
# tMap.add(headers['message-id'])
# else:
# i2+=1
# i1+=1
# if headers.get('in-reply-to') in tMap: i3+=1
# print console.color.clearLast, i1, i2, i3, i4
# if not headers.get('message-id'):
# print _.raw
# print '='*30
# print
# continue
# for k in importer._headers:
# print k+':', strUniDecode('%r'%(headers[k],))
# print
# # print body_plain or body_html
# print
# for o in attachments:
# o=o.copy()
# o['payload']='...'
# print o
# print '='*40
# print _.defects, raw_input()
# print console.color.clearLast, i1, i2, i3, i4, sys.exit()
o=MyEnv()
o.repairDialogs('John Smith')
# o.test_filter({'or':[
# {'key':'from', 'value':'[email protected]', 'match':'=='},
# # {'key':'label', 'value':u'черновики', 'match':'=='},
# ]}, asDialogs=True, returnFull=False, limitDates=30, limitResults=100)
o()
| [
2,
532,
9,
12,
19617,
25,
3384,
69,
12,
23,
532,
9,
12,
198,
6738,
2163,
8044,
1330,
1635,
198,
198,
6738,
569,
2381,
7246,
11012,
1330,
569,
2381,
7246,
11012,
11,
905,
11012,
11,
905,
29668,
11,
10933,
10223,
198,
6738,
569,
2381,
7246,
11012,
1330,
8563,
355,
20613,
12331,
198,
198,
6738,
1330,
25804,
1330,
17267,
25804,
62,
10744,
1140,
198,
11748,
8563,
355,
3650,
12331,
198,
11748,
40391,
198,
6738,
3384,
4487,
1330,
28912,
44204,
43,
8040,
198,
198,
6738,
9195,
82,
13,
25638,
8206,
1330,
8631,
5239,
198,
11748,
2420,
37150,
198,
198,
361,
11593,
3672,
834,
6624,
705,
834,
12417,
834,
10354,
198,
220,
220,
1303,
848,
4337,
28,
20939,
25804,
62,
10744,
1140,
10786,
14,
11195,
14,
1525,
8130,
14,
140,
245,
16142,
140,
111,
21169,
35072,
140,
115,
31583,
18849,
14,
14816,
62,
1069,
9213,
14,
439,
13,
2022,
1140,
11537,
198,
220,
220,
1303,
256,
13912,
28,
2617,
3419,
198,
220,
220,
1303,
1312,
16,
28,
72,
17,
28,
72,
18,
28,
72,
19,
28,
15,
198,
220,
220,
1303,
3601,
198,
220,
220,
1303,
329,
4808,
11,
24697,
11,
357,
2618,
62,
25638,
11,
1767,
62,
6494,
828,
32161,
287,
848,
4337,
25,
198,
220,
220,
1303,
220,
220,
220,
611,
24697,
13,
1136,
10786,
20500,
12,
312,
6,
2599,
198,
220,
220,
1303,
220,
220,
220,
220,
220,
220,
611,
24697,
17816,
20500,
12,
312,
20520,
287,
256,
13912,
25,
1312,
19,
47932,
16,
198,
220,
220,
1303,
220,
220,
220,
220,
220,
220,
256,
13912,
13,
2860,
7,
50145,
17816,
20500,
12,
312,
6,
12962,
198,
220,
220,
1303,
220,
220,
220,
2073,
25,
198,
220,
220,
1303,
220,
220,
220,
220,
220,
220,
1312,
17,
47932,
16,
198,
220,
220,
1303,
220,
220,
220,
1312,
16,
47932,
16,
198,
220,
220,
1303,
220,
220,
220,
611,
24697,
13,
1136,
10786,
259,
12,
47768,
12,
1462,
11537,
287,
256,
13912,
25,
1312,
18,
47932,
16,
628,
220,
220,
1303,
220,
220,
220,
3601,
8624,
13,
8043,
13,
20063,
5956,
11,
1312,
16,
11,
1312,
17,
11,
1312,
18,
11,
1312,
19,
628,
220,
220,
1303,
220,
220,
220,
611,
407,
24697,
13,
1136,
10786,
20500,
12,
312,
6,
2599,
198,
220,
220,
1303,
220,
220,
220,
220,
220,
220,
3601,
4808,
13,
1831,
198,
220,
220,
1303,
220,
220,
220,
220,
220,
220,
3601,
705,
11639,
9,
1270,
198,
220,
220,
1303,
220,
220,
220,
220,
220,
220,
3601,
628,
220,
220,
1303,
220,
220,
220,
2555,
628,
220,
220,
1303,
220,
220,
220,
329,
479,
287,
848,
4337,
13557,
50145,
25,
198,
220,
220,
1303,
220,
220,
220,
220,
220,
220,
3601,
479,
10,
10354,
3256,
965,
3118,
72,
10707,
1098,
10786,
4,
81,
6,
4,
7,
50145,
58,
74,
4357,
4008,
198,
220,
220,
1303,
220,
220,
220,
3601,
198,
220,
220,
1303,
220,
220,
220,
1303,
3601,
1767,
62,
25638,
393,
1767,
62,
6494,
198,
220,
220,
1303,
220,
220,
220,
3601,
198,
220,
220,
1303,
220,
220,
220,
329,
267,
287,
32161,
25,
198,
220,
220,
1303,
220,
220,
220,
220,
220,
220,
267,
28,
78,
13,
30073,
3419,
198,
220,
220,
1303,
220,
220,
220,
220,
220,
220,
267,
17816,
15577,
2220,
20520,
11639,
986,
6,
198,
220,
220,
1303,
220,
220,
220,
220,
220,
220,
3601,
267,
198,
220,
220,
1303,
220,
220,
220,
3601,
705,
11639,
9,
1821,
198,
220,
220,
1303,
220,
220,
220,
3601,
4808,
13,
4299,
478,
82,
11,
8246,
62,
15414,
3419,
198,
220,
220,
1303,
3601,
8624,
13,
8043,
13,
20063,
5956,
11,
1312,
16,
11,
1312,
17,
11,
1312,
18,
11,
1312,
19,
11,
25064,
13,
37023,
3419,
628,
220,
220,
267,
28,
3666,
4834,
85,
3419,
628,
220,
220,
267,
13,
49932,
24400,
18463,
10786,
7554,
4176,
11537,
628,
220,
220,
1303,
267,
13,
9288,
62,
24455,
15090,
6,
273,
10354,
58,
198,
220,
220,
1303,
220,
220,
220,
1391,
6,
2539,
10354,
6,
6738,
3256,
705,
8367,
10354,
6,
4529,
31,
1228,
261,
13,
622,
3256,
705,
15699,
10354,
6,
855,
6,
5512,
198,
220,
220,
1303,
220,
220,
220,
1303,
1391,
6,
2539,
10354,
6,
18242,
3256,
705,
8367,
10354,
84,
6,
141,
229,
16843,
21169,
22177,
25443,
110,
18849,
31583,
18849,
3256,
705,
15699,
10354,
6,
855,
6,
5512,
198,
220,
220,
1303,
2361,
5512,
355,
24400,
18463,
28,
17821,
11,
1441,
13295,
28,
25101,
11,
4179,
35,
689,
28,
1270,
11,
4179,
25468,
28,
3064,
8,
628,
220,
220,
267,
3419,
198
] | 2.165113 | 751 |
from cytopy.data.gating_strategy import GatingStrategy, DuplicatePopulationError
from cytopy.data.gate import ThresholdGate, PolygonGate, EllipseGate
from cytopy.data.project import Project
import matplotlib.pyplot as plt
import pandas as pd
import pytest
@pytest.mark.parametrize("gate,child_n",
[(create_threshold_gate, 4),
(create_poly_gate, 1),
(create_ellipse_gate, 2)])
@pytest.mark.parametrize("gate,populations",
[(create_threshold_gate, ["root", "Top right", "Top left", "Bottom populations"]),
(create_poly_gate, ["root", "Big pop"]),
(create_ellipse_gate, ["root", "Big pop", "Little pop"])])
@pytest.mark.parametrize("remove_associations", [True, False])
| [
6738,
3075,
4852,
88,
13,
7890,
13,
70,
803,
62,
2536,
4338,
1330,
402,
803,
13290,
4338,
11,
49821,
5344,
45251,
12331,
198,
6738,
3075,
4852,
88,
13,
7890,
13,
10494,
1330,
536,
10126,
22628,
11,
12280,
14520,
22628,
11,
7122,
541,
325,
22628,
198,
6738,
3075,
4852,
88,
13,
7890,
13,
16302,
1330,
4935,
198,
11748,
2603,
29487,
8019,
13,
9078,
29487,
355,
458,
83,
198,
11748,
19798,
292,
355,
279,
67,
198,
11748,
12972,
9288,
628,
628,
628,
628,
198,
198,
31,
9078,
9288,
13,
4102,
13,
17143,
316,
380,
2736,
7203,
10494,
11,
9410,
62,
77,
1600,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
47527,
17953,
62,
400,
10126,
62,
10494,
11,
604,
828,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
357,
17953,
62,
35428,
62,
10494,
11,
352,
828,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
357,
17953,
62,
695,
541,
325,
62,
10494,
11,
362,
8,
12962,
628,
198,
31,
9078,
9288,
13,
4102,
13,
17143,
316,
380,
2736,
7203,
10494,
11,
12924,
5768,
1600,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
47527,
17953,
62,
400,
10126,
62,
10494,
11,
14631,
15763,
1600,
366,
9126,
826,
1600,
366,
9126,
1364,
1600,
366,
34104,
9684,
8973,
828,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
357,
17953,
62,
35428,
62,
10494,
11,
14631,
15763,
1600,
366,
12804,
1461,
8973,
828,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
357,
17953,
62,
695,
541,
325,
62,
10494,
11,
14631,
15763,
1600,
366,
12804,
1461,
1600,
366,
22253,
1461,
8973,
8,
12962,
628,
628,
628,
628,
628,
628,
628,
628,
628,
198,
31,
9078,
9288,
13,
4102,
13,
17143,
316,
380,
2736,
7203,
28956,
62,
562,
1733,
602,
1600,
685,
17821,
11,
10352,
12962,
198
] | 2.141058 | 397 |
import dotenv
dotenv.load_dotenv()
from time import sleep
import schedule
import requests
import json
from service.image_recognition import check_image_similarity
from model import UMKM, UMKMValidator, Verification, Campaign
schedule.every().minute.do(process_verifications)
while True:
try:
schedule.run_pending()
except:
pass
finally:
sleep(1)
| [
11748,
16605,
24330,
198,
26518,
24330,
13,
2220,
62,
26518,
24330,
3419,
198,
198,
6738,
640,
1330,
3993,
198,
11748,
7269,
198,
11748,
7007,
198,
11748,
33918,
198,
198,
6738,
2139,
13,
9060,
62,
26243,
653,
1330,
2198,
62,
9060,
62,
38610,
414,
198,
6738,
2746,
1330,
471,
33907,
44,
11,
471,
33907,
44,
47139,
1352,
11,
4643,
2649,
11,
13718,
628,
628,
628,
198,
198,
15952,
5950,
13,
16833,
22446,
11374,
13,
4598,
7,
14681,
62,
332,
6637,
8,
628,
198,
4514,
6407,
25,
198,
220,
220,
220,
1949,
25,
198,
220,
220,
220,
220,
220,
220,
220,
7269,
13,
5143,
62,
79,
1571,
3419,
198,
220,
220,
220,
2845,
25,
198,
220,
220,
220,
220,
220,
220,
220,
1208,
198,
220,
220,
220,
3443,
25,
198,
220,
220,
220,
220,
220,
220,
220,
3993,
7,
16,
8,
198
] | 2.807143 | 140 |
__author__ = '[email protected]'
# Module to support custom teacher views in CourseBuilder dashboard
# Views include:
# Section Roster - list of students in section
# Sections - list of sections for current user
# Student Dashboard - view of a single student's performance in the course
# Teacher Workspace - teacher registration and list of all registered teachers
import jinja2
import os
import appengine_config
from common import tags
from common import crypto
from models import custom_modules
from models import roles
from models import transforms
from models.models import Student
#since we are extending the dashboard, probably want to include dashboard stuff
from modules.dashboard import dashboard
from modules.dashboard import tabs
#import our own modules
import teacher_entity
import teacher_rest_handlers
import teacher_parsers
#Setup paths and directories for templates and resources
RESOURCES_PATH = '/modules/teacher_dashboard/resources'
TEMPLATES_DIR = os.path.join(
appengine_config.BUNDLE_ROOT, 'modules', 'teacher_dashboard', 'templates')
#setup permissions that will be registered with the dashboard
ACCESS_ASSETS_PERMISSION = 'can_access_assets'
ACCESS_ASSETS_PERMISSION_DESCRIPTION = 'Can access the Assets Dashboard'
ACCESS_SETTINGS_PERMISSION = 'can_access_settings'
ACCESS_SETTINGS_PERMISSION_DESCRIPTION = 'Can access the Settings Dashboard'
ACCESS_ROLES_PERMISSION = 'can_access_roles'
ACCESS_ROLES_PERMISSION_DESCRIPTION = 'Can access the Roles Dashboard'
ACCESS_ANALYTICS_PERMISSION = 'can_access_analytics'
ACCESS_ANALYTICS_PERMISSION_DESCRIPTION = 'Can access the Analytics Dashboard'
ACCESS_SEARCH_PERMISSION = 'can_access_search'
ACCESS_SEARCH_PERMISSION_DESCRIPTION = 'Can access the Search Dashboard'
ACCESS_PEERREVIEW_PERMISSION = 'can_access_peer_review'
ACCESS_PEERREVIEW_PERMISSION_DESCRIPTION = 'Can access the Peer Review Dashboard'
ACCESS_SKILLMAP_PERMISSION = 'can_access_skill_map'
ACCESS_SKILLMAP_PERMISSION_DESCRIPTION = 'Can access the Skill Map Dashboard'
ACCESS_TEACHER_DASHBOARD_PERMISSION = 'can_access_teacher_dashboard'
ACCESS_TEACHER_DASHBOARD_PERMISSION_DESCRIPTION = 'Can access the Teacher Dashboard'
#setup custom module for, needs to be referenced later
custom_module = None
class TeacherHandler(dashboard.DashboardHandler):
"""Handler for everything under the Teacher tab in the CourseBuilder dashboard.
Note:
Inherits from the DashboardHandler, makes use of many of those functions to
integrate with existing dashboard.
Attributes:
ACTION (str): Value used to handler navigation in the dashboard, top level label.
DEFAULT_TAB (str): Default sub-navigation value.
URL (str): Path to module from working directory.
XSRF_TOKEN_NAME (str): Token used for xsrf security functions.
"""
ACTION = 'teacher_dashboard'
DEFAULT_TAB = 'sections'
URL = '/modules/teacher_dashboard'
XSRF_TOKEN_NAME = ''
@classmethod
def register_tabs(cls):
"""Handles registering all sub-navigation tabs"""
def register_tab(key, label, handler, href=None):
"""Registers tab using the tab registry"""
if href:
target = '_blank'
else:
href = 'dashboard?action=teacher_dashboard&tab=%s' % key
target = None
tabs.Registry.register(
cls.ACTION, key, label, contents=handler, href=href, target=target
)
register_tab('sections', 'Sections', TeacherHandler)
register_tab('student_detail', 'Student Dashboard', TeacherHandler)
register_tab('teacher_reg', 'Teacher Workspace', TeacherHandler)
def get_teacher_dashboard(self):
"""Process navigation requests sent to teacher handler. Routers to appropriate function."""
in_tab = self.request.get('tab') or self.DEFAULT_TAB
tab_action = self.request.get('tab_action') or None #defined a secondary tab property so I can go load a
# separate view in the same tab
if in_tab == 'sections':
if tab_action == 'roster':
return self.get_roster()
else:
return self.get_sections()
elif in_tab == 'teacher_reg':
return self.get_teacher_reg()
elif in_tab == 'student_detail':
return self.get_student_dashboard()
def get_sections(self):
"""Renders Sections view. Javascript handles getting course sections and building the view"""
template_values = {}
template_values['namespace'] = self.get_course()._namespace.replace('ns_', '')
main_content = self.get_template(
'teacher_sections.html', [TEMPLATES_DIR]).render(template_values)
self.render_page({
'page_title': self.format_title('Sections'),
'main_content': jinja2.utils.Markup(main_content)})
def get_student_dashboard(self):
"""Renders Student Dashboard view.
Also gets ALL students in ALL course sections for the registered user to
build a jQuery autocomplete dropdown on the view.
"""
student_email = self.request.get('student') or None #email will be in the request if opened from student list
# view, otherwise it will be None
#need to go through every course section for the current user and get all unique students
students = []
course_sections = teacher_entity.CourseSectionEntity.get_course_sections_for_user()
if course_sections and len(course_sections) > 0:
for course_section in course_sections.values():
if course_section.students and len(course_section.students) > 0:
for student_in_section in course_section.students.values():
if not any(x['user_id'] == student_in_section['user_id'] for x in students):
students.append(student_in_section)
#check to see if we have a student and if we need to get detailed progress
student = None
if student_email:
student = Student.get_by_email(student_email)
if (student):
course = self.get_course()
units = teacher_parsers.StudentProgressTracker.get_detailed_progress(student, course)
scores = teacher_parsers.ActivityScoreParser.get_activity_scores([student.user_id], course)
else:
units = None
scores = None
#render the template for the student dashboard view
main_content = self.get_template(
'student_detailed_progress.html', [TEMPLATES_DIR]).render(
{
'units': units, #unit completion
'student': student, #course defined student object, need email and name
'students': students, #list of students, names and emails, from a course section student list
'scores': scores
})
#call DashboardHandler function to render the page
self.render_page({
'page_title': self.format_title('Student Dashboard'),
'main_content': jinja2.utils.Markup(main_content)
})
def get_roster(self):
"""Renders the Roster view. Displays all students in a single course section
Also allows user to add students to a course section
"""
template_values = {}
template_values['add_student_xsrf_token'] = crypto.XsrfTokenManager.create_xsrf_token(
teacher_rest_handlers.CourseSectionRestHandler.XSRF_TOKEN)
#need list of units and lessons for select elements that determine which progress value to display
#need a list of units, need the titles, unit ids, types
units = self.get_course().get_units()
units_filtered = filter(lambda x: x.type == 'U', units) #filter out assessments
template_values['units'] = units_filtered
#need to get lessons, but only for units that aren't assessments
lessons = {}
for unit in units_filtered:
unit_lessons = self.get_course().get_lessons(unit.unit_id)
unit_lessons_filtered = []
for lesson in unit_lessons:
unit_lessons_filtered.append({
'title': lesson.title,
'unit_id': lesson.unit_id,
'lesson_id': lesson.lesson_id
})
lessons[unit.unit_id] = unit_lessons_filtered
template_values['lessons'] = transforms.dumps(lessons, {}) #passing in JSON to template so it can be used
# in JavaScript
course_section_id = self.request.get('section')
course_section = teacher_entity.CourseSectionEntity.get_course_for_user(course_section_id)
students = {}
#need to get progress values for ALL students since we show completion for every student
if course_section.students and len(course_section.students) > 0:
#course_section.students = sorted(course_section.students.values(), key=lambda k: (k['name']))
for student in course_section.students.values():
temp_student = {}
temp_student['unit_completion'] = teacher_parsers.StudentProgressTracker.get_unit_completion(
Student.get_by_email(
student[
'email']), self.get_course())
temp_student['course_completion'] = teacher_parsers.StudentProgressTracker.get_overall_progress(Student.get_by_email(student[
'email']), self.get_course())
temp_student['detailed_course_completion'] = teacher_parsers.StudentProgressTracker.get_detailed_progress(
Student.get_by_email(student['email']), self.get_course())
temp_student['email'] = student['email']
temp_student['name'] = student['name']
students[student['email']] = temp_student
course_section.students = students
#passing in students as JSON so JavaScript can handle updating completion values easier
template_values['students_json'] = transforms.dumps(course_section.students, {})
template_values['namespace'] = self.get_course()._namespace.replace('ns_', '')
if course_section:
template_values['section'] = course_section
#render student_list.html for Roster view
main_content = self.get_template(
'student_list.html', [TEMPLATES_DIR]).render(template_values)
#DashboardHandler renders the page
self.render_page({
'page_title': self.format_title('Student List'),
'main_content': jinja2.utils.Markup(main_content)})
def get_teacher_reg(self):
"""Renders Teacher Workspace view. Displays form to add or update a teacher
Also displays all registered teachers.
"""
alerts = []
disable_form = False
if not roles.Roles.is_course_admin(self.app_context):
alerts.append('Access denied. Please contact a course admin.')
disable_form = True
template_values = {}
template_values['teacher_reg_xsrf_token'] = self.create_xsrf_token('teacher_reg')
template_values['teachers'] = teacher_entity.Teacher.get_all_teachers_for_course()
template_values['alert_messages'] = alerts
template_values['disable'] = disable_form
template_values['action'] = self.get_action_url('teacher_reg')
main_content = self.get_template(
'teacher_registration.html', [TEMPLATES_DIR]).render(template_values)
self.render_page({
'page_title': self.format_title('Teacher Registration'),
'main_content': jinja2.utils.Markup(main_content)})
@classmethod
def post_teacher_reg(cls, handler):
"""Handles form submit for teacher registration"""
#get values entered on form
email = handler.request.get('email').strip()
school = handler.request.get('school')
#getting checkbox value is a little weird, might look different depending on browser
active = handler.request.get('active-teacher')
if active == 'on' or len(active) > 0:
active = True
else:
active = False
teacher = teacher_entity.Teacher.get_by_email(email)
#keep track of any errors we might want to pass back to the UI
alerts = []
#check to see if a teacher already exists
if teacher:
template_values = {}
template_values['teacher_reg_xsrf_token'] = handler.create_xsrf_token('teacher_reg')
sections = {}
#don't let the teacher be deactivated if they have active courses
can_inactivate = True
if active == False:
if teacher.sections:
course_sections_decoded = transforms.loads(teacher.sections)
for course_section_key in course_sections_decoded:
course_section = teacher_entity.CourseSectionEntity(course_sections_decoded[course_section_key])
sections[course_section.section_id] = course_section
for section in sections.values():
if section.is_active:
can_inactivate = False
#let user know if they can't deactivate, but only if they are trying to deactivate the teacher
if not can_inactivate and not active:
alerts.append('Cannot deactivate teacher. Teacher still has active courses')
#go for the update if all is good
if can_inactivate:
teacher_entity.Teacher.update_teacher_for_user(email, school, active, '', alerts)
#let user know all is well if save was successful
if len(alerts) == 0:
alerts.append('Teacher was successfully updated')
#render teacher_registration.html for view, pass alerts in
template_values['alert_messages'] = '\n'.join(alerts)
main_content = handler.get_template(
'teacher_registration.html', [TEMPLATES_DIR]).render(template_values)
#DashboardHandler renders the page
handler.render_page({
'page_title': handler.format_title('Teacher Dashboard'),
'main_content': jinja2.utils.Markup(main_content)
},
'teacher_dashboard'
)
else:
#go for it if teacher doesn't already exist
teacher_entity.Teacher.add_new_teacher_for_user(email, school, '', alerts)
template_values = {}
template_values['alert_messages'] = '\n'.join(alerts)
template_values['teacher_reg_xsrf_token'] = handler.create_xsrf_token('teacher_reg')
main_content = handler.get_template(
'teacher_registration.html', [TEMPLATES_DIR]).render(template_values)
#DashboardHandler renders the page
handler.render_page({
'page_title': handler.format_title('Teacher Dashboard'),
'main_content': jinja2.utils.Markup(main_content)
},
'teacher_dashboard'
)
def notify_module_enabled():
"""Handles things after module has been enabled."""
def get_action(handler):
"""Redirects to teacher_dashboard."""
handler.redirect('/modules/teacher_dashboard?action=teacher_dashboard&tab=%s' % handler.request.get('tab') or
TeacherHandler.DEFAULT_TAB)
dashboard.DashboardHandler.add_nav_mapping(
TeacherHandler.ACTION, 'Teacher')
dashboard.DashboardHandler.get_actions.append('teacher_dashboard')
setattr(dashboard.DashboardHandler, 'get_teacher_dashboard', get_action)
#add post actions
dashboard.DashboardHandler.add_custom_post_action('teacher_reg', post_action)
setattr(dashboard.DashboardHandler, 'post_teacher_reg', post_action)
#add permissions for the dashboard sections
dashboard.DashboardHandler.add_external_permission(
ACCESS_ASSETS_PERMISSION, ACCESS_ASSETS_PERMISSION_DESCRIPTION)
dashboard.DashboardHandler.add_external_permission(
ACCESS_SETTINGS_PERMISSION, ACCESS_SETTINGS_PERMISSION_DESCRIPTION)
dashboard.DashboardHandler.add_external_permission(
ACCESS_ROLES_PERMISSION, ACCESS_ROLES_PERMISSION_DESCRIPTION)
dashboard.DashboardHandler.add_external_permission(
ACCESS_ANALYTICS_PERMISSION, ACCESS_ANALYTICS_PERMISSION_DESCRIPTION)
dashboard.DashboardHandler.add_external_permission(
ACCESS_SEARCH_PERMISSION, ACCESS_SEARCH_PERMISSION_DESCRIPTION)
dashboard.DashboardHandler.add_external_permission(
ACCESS_PEERREVIEW_PERMISSION, ACCESS_PEERREVIEW_PERMISSION_DESCRIPTION)
dashboard.DashboardHandler.add_external_permission(
ACCESS_SKILLMAP_PERMISSION, ACCESS_SKILLMAP_PERMISSION_DESCRIPTION)
dashboard.DashboardHandler.add_external_permission(
ACCESS_TEACHER_DASHBOARD_PERMISSION, ACCESS_TEACHER_DASHBOARD_PERMISSION_DESCRIPTION)
#map permissions to actions
dashboard.DashboardHandler.map_action_to_permission('get_' + str(TeacherHandler.ACTION),
ACCESS_TEACHER_DASHBOARD_PERMISSION)
nav_mappings = dashboard.DashboardHandler.get_nav_mappings()
dashboard.DashboardHandler.map_action_to_permission('get_' + str(nav_mappings[1][0]), ACCESS_ASSETS_PERMISSION)
dashboard.DashboardHandler.map_action_to_permission('get_' + str(nav_mappings[2][0]), ACCESS_SETTINGS_PERMISSION)
dashboard.DashboardHandler.map_action_to_permission('get_' + str(nav_mappings[3][0]), ACCESS_ROLES_PERMISSION)
dashboard.DashboardHandler.map_action_to_permission('get_' + str(nav_mappings[4][0]), ACCESS_ANALYTICS_PERMISSION)
dashboard.DashboardHandler.map_action_to_permission('get_' + str(nav_mappings[5][0]), ACCESS_SEARCH_PERMISSION)
dashboard.DashboardHandler.map_action_to_permission('get_' + str(nav_mappings[6][0]), ACCESS_PEERREVIEW_PERMISSION)
dashboard.DashboardHandler.map_action_to_permission('get_' + str(nav_mappings[7][0]), ACCESS_SKILLMAP_PERMISSION)
dashboard.DashboardHandler.EXTRA_JS_HREF_LIST.append(
'/modules/teacher_dashboard/resources/js/popup.js')
dashboard.DashboardHandler.EXTRA_JS_HREF_LIST.append(
'/modules/teacher_dashboard/resources/js/course_section_analytics.js')
dashboard.DashboardHandler.EXTRA_JS_HREF_LIST.append(
'/modules/teacher_dashboard/resources/js/activity_score_manager.js')
dashboard.DashboardHandler.EXTRA_JS_HREF_LIST.append(
'/modules/teacher_dashboard/resources/js/student_list_table_manager')
dashboard.DashboardHandler.EXTRA_JS_HREF_LIST.append(
'/modules/teacher_dashboard/resources/js/student_list_table_rebuild_manager.js')
dashboard.DashboardHandler.EXTRA_JS_HREF_LIST.append(
'/modules/teacher_dashboard/resources/js/activity_score_table_manager.js')
dashboard.DashboardHandler.EXTRA_JS_HREF_LIST.append(
'/modules/teacher_dashboard/resources/js/student_score_manager.js')
dashboard.DashboardHandler.EXTRA_CSS_HREF_LIST.append(
'/modules/teacher_dashboard/resources/css/student_list.css')
transforms.CUSTOM_JSON_ENCODERS.append(teacher_entity.CourseSectionEntity.json_encoder)
#register tabs
TeacherHandler.register_tabs()
def register_module():
"""Registers this module in the registry."""
global_routes = [
(os.path.join(RESOURCES_PATH, 'js', '.*'), tags.JQueryHandler),
(os.path.join(RESOURCES_PATH, '.*'), tags.ResourcesHandler),
(RESOURCES_PATH + '/js/popup.js', tags.IifeHandler),
(RESOURCES_PATH + '/js/course_section_analytics.js', tags.IifeHandler),
(RESOURCES_PATH + '/js/activity_score_manager.js', tags.IifeHandler),
(RESOURCES_PATH + '/js/student_list_table_manager', tags.IifeHandler),
(RESOURCES_PATH + '/js/student_list_table_rebuild_manager.js', tags.IifeHandler),
(RESOURCES_PATH + '/js/activity_score_table_manager.js', tags.IifeHandler),
(RESOURCES_PATH + '/js/student_score_manager.js', tags.IifeHandler)
]
namespaced_routes = [
(TeacherHandler.URL, TeacherHandler),
(teacher_rest_handlers.CourseSectionRestHandler.URL, teacher_rest_handlers.CourseSectionRestHandler),
(teacher_rest_handlers.StudentProgressRestHandler.URL, teacher_rest_handlers.StudentProgressRestHandler),
(teacher_rest_handlers.ActivityScoreRestHandler.URL, teacher_rest_handlers.ActivityScoreRestHandler)
]
global custom_module # pylint: disable=global-statement
custom_module = custom_modules.Module(
'Teacher Dashboard Module',
'A module provide teacher workflow.',
global_routes, namespaced_routes,
notify_module_enabled=notify_module_enabled)
return custom_module
| [
834,
9800,
834,
796,
705,
17231,
4665,
31,
25471,
13,
15532,
6,
628,
198,
2,
19937,
284,
1104,
2183,
4701,
5009,
287,
20537,
32875,
30415,
198,
2,
29978,
2291,
25,
198,
2,
220,
220,
220,
220,
220,
220,
7275,
371,
6197,
532,
1351,
286,
2444,
287,
2665,
198,
2,
220,
220,
220,
220,
220,
220,
37703,
532,
1351,
286,
9004,
329,
1459,
2836,
198,
2,
220,
220,
220,
220,
220,
220,
13613,
16189,
3526,
532,
1570,
286,
257,
2060,
3710,
338,
2854,
287,
262,
1781,
198,
2,
220,
220,
220,
220,
220,
220,
32019,
10933,
10223,
532,
4701,
9352,
290,
1351,
286,
477,
6823,
7799,
198,
198,
11748,
474,
259,
6592,
17,
198,
11748,
28686,
198,
198,
11748,
598,
18392,
62,
11250,
198,
198,
6738,
2219,
1330,
15940,
198,
6738,
2219,
1330,
21473,
198,
198,
6738,
4981,
1330,
2183,
62,
18170,
198,
6738,
4981,
1330,
9176,
198,
6738,
4981,
1330,
31408,
198,
6738,
4981,
13,
27530,
1330,
13613,
198,
198,
2,
20777,
356,
389,
16610,
262,
30415,
11,
2192,
765,
284,
2291,
30415,
3404,
198,
6738,
13103,
13,
42460,
3526,
1330,
30415,
198,
6738,
13103,
13,
42460,
3526,
1330,
22524,
198,
198,
2,
11748,
674,
898,
13103,
198,
11748,
4701,
62,
26858,
198,
11748,
4701,
62,
2118,
62,
4993,
8116,
198,
11748,
4701,
62,
79,
945,
364,
198,
198,
2,
40786,
13532,
290,
29196,
329,
24019,
290,
4133,
198,
19535,
2606,
7397,
1546,
62,
34219,
796,
31051,
18170,
14,
660,
3493,
62,
42460,
3526,
14,
37540,
6,
198,
198,
51,
3620,
6489,
29462,
62,
34720,
796,
28686,
13,
6978,
13,
22179,
7,
198,
220,
220,
220,
598,
18392,
62,
11250,
13,
33,
4944,
35,
2538,
62,
13252,
2394,
11,
705,
18170,
3256,
705,
660,
3493,
62,
42460,
3526,
3256,
705,
11498,
17041,
11537,
198,
198,
2,
40406,
21627,
326,
481,
307,
6823,
351,
262,
30415,
198,
26861,
7597,
62,
10705,
32716,
62,
18973,
44,
40373,
796,
705,
5171,
62,
15526,
62,
19668,
6,
198,
26861,
7597,
62,
10705,
32716,
62,
18973,
44,
40373,
62,
30910,
40165,
796,
705,
6090,
1895,
262,
41059,
16189,
3526,
6,
198,
198,
26861,
7597,
62,
28480,
51,
20754,
62,
18973,
44,
40373,
796,
705,
5171,
62,
15526,
62,
33692,
6,
198,
26861,
7597,
62,
28480,
51,
20754,
62,
18973,
44,
40373,
62,
30910,
40165,
796,
705,
6090,
1895,
262,
16163,
16189,
3526,
6,
198,
198,
26861,
7597,
62,
49,
3535,
1546,
62,
18973,
44,
40373,
796,
705,
5171,
62,
15526,
62,
305,
829,
6,
198,
26861,
7597,
62,
49,
3535,
1546,
62,
18973,
44,
40373,
62,
30910,
40165,
796,
705,
6090,
1895,
262,
371,
4316,
16189,
3526,
6,
198,
198,
26861,
7597,
62,
1565,
1847,
56,
51,
19505,
62,
18973,
44,
40373,
796,
705,
5171,
62,
15526,
62,
38200,
14094,
6,
198,
26861,
7597,
62,
1565,
1847,
56,
51,
19505,
62,
18973,
44,
40373,
62,
30910,
40165,
796,
705,
6090,
1895,
262,
30437,
16189,
3526,
6,
198,
198,
26861,
7597,
62,
5188,
31315,
62,
18973,
44,
40373,
796,
705,
5171,
62,
15526,
62,
12947,
6,
198,
26861,
7597,
62,
5188,
31315,
62,
18973,
44,
40373,
62,
30910,
40165,
796,
705,
6090,
1895,
262,
11140,
16189,
3526,
6,
198,
198,
26861,
7597,
62,
11401,
1137,
2200,
28206,
62,
18973,
44,
40373,
796,
705,
5171,
62,
15526,
62,
33350,
62,
19023,
6,
198,
26861,
7597,
62,
11401,
1137,
2200,
28206,
62,
18973,
44,
40373,
62,
30910,
40165,
796,
705,
6090,
1895,
262,
41139,
6602,
16189,
3526,
6,
198,
198,
26861,
7597,
62,
18831,
8267,
33767,
62,
18973,
44,
40373,
796,
705,
5171,
62,
15526,
62,
42401,
62,
8899,
6,
198,
26861,
7597,
62,
18831,
8267,
33767,
62,
18973,
44,
40373,
62,
30910,
40165,
796,
705,
6090,
1895,
262,
16023,
9347,
16189,
3526,
6,
198,
198,
26861,
7597,
62,
9328,
16219,
1137,
62,
35,
11211,
8202,
9795,
62,
18973,
44,
40373,
796,
705,
5171,
62,
15526,
62,
660,
3493,
62,
42460,
3526,
6,
198,
26861,
7597,
62,
9328,
16219,
1137,
62,
35,
11211,
8202,
9795,
62,
18973,
44,
40373,
62,
30910,
40165,
796,
705,
6090,
1895,
262,
32019,
16189,
3526,
6,
198,
198,
2,
40406,
2183,
8265,
329,
11,
2476,
284,
307,
20717,
1568,
198,
23144,
62,
21412,
796,
6045,
628,
198,
4871,
32019,
25060,
7,
42460,
3526,
13,
43041,
3526,
25060,
2599,
198,
220,
220,
220,
37227,
25060,
329,
2279,
739,
262,
32019,
7400,
287,
262,
20537,
32875,
30415,
13,
628,
220,
220,
220,
5740,
25,
198,
220,
220,
220,
220,
220,
220,
220,
47025,
896,
422,
262,
16189,
3526,
25060,
11,
1838,
779,
286,
867,
286,
883,
5499,
284,
198,
220,
220,
220,
220,
220,
220,
220,
19386,
351,
4683,
30415,
13,
628,
220,
220,
220,
49213,
25,
198,
220,
220,
220,
220,
220,
220,
220,
40282,
357,
2536,
2599,
11052,
973,
284,
21360,
16408,
287,
262,
30415,
11,
1353,
1241,
6167,
13,
198,
220,
220,
220,
220,
220,
220,
220,
5550,
38865,
62,
5603,
33,
357,
2536,
2599,
15161,
850,
12,
28341,
7065,
1988,
13,
198,
220,
220,
220,
220,
220,
220,
220,
10289,
357,
2536,
2599,
10644,
284,
8265,
422,
1762,
8619,
13,
198,
220,
220,
220,
220,
220,
220,
220,
1395,
12562,
37,
62,
10468,
43959,
62,
20608,
357,
2536,
2599,
29130,
973,
329,
2124,
27891,
69,
2324,
5499,
13,
628,
220,
220,
220,
37227,
628,
220,
220,
220,
40282,
796,
705,
660,
3493,
62,
42460,
3526,
6,
198,
220,
220,
220,
5550,
38865,
62,
5603,
33,
796,
705,
23946,
6,
628,
220,
220,
220,
10289,
796,
31051,
18170,
14,
660,
3493,
62,
42460,
3526,
6,
628,
220,
220,
220,
1395,
12562,
37,
62,
10468,
43959,
62,
20608,
796,
10148,
628,
220,
220,
220,
2488,
4871,
24396,
198,
220,
220,
220,
825,
7881,
62,
8658,
82,
7,
565,
82,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
12885,
829,
28336,
477,
850,
12,
28341,
7065,
22524,
37811,
628,
220,
220,
220,
220,
220,
220,
220,
825,
7881,
62,
8658,
7,
2539,
11,
6167,
11,
21360,
11,
13291,
28,
14202,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
37227,
8081,
6223,
7400,
1262,
262,
7400,
20478,
37811,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
611,
13291,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2496,
796,
705,
62,
27190,
6,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2073,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
13291,
796,
705,
42460,
3526,
30,
2673,
28,
660,
3493,
62,
42460,
3526,
5,
8658,
28,
4,
82,
6,
4064,
1994,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2496,
796,
6045,
628,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
22524,
13,
8081,
4592,
13,
30238,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
537,
82,
13,
44710,
11,
1994,
11,
6167,
11,
10154,
28,
30281,
11,
13291,
28,
33257,
11,
2496,
28,
16793,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1267,
628,
220,
220,
220,
220,
220,
220,
220,
7881,
62,
8658,
10786,
23946,
3256,
705,
50,
478,
507,
3256,
32019,
25060,
8,
198,
220,
220,
220,
220,
220,
220,
220,
7881,
62,
8658,
10786,
50139,
62,
49170,
3256,
705,
38778,
16189,
3526,
3256,
32019,
25060,
8,
198,
220,
220,
220,
220,
220,
220,
220,
7881,
62,
8658,
10786,
660,
3493,
62,
2301,
3256,
705,
6767,
3493,
10933,
10223,
3256,
32019,
25060,
8,
628,
220,
220,
220,
825,
651,
62,
660,
3493,
62,
42460,
3526,
7,
944,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
18709,
16408,
7007,
1908,
284,
4701,
21360,
13,
13876,
1010,
284,
5035,
2163,
526,
15931,
628,
220,
220,
220,
220,
220,
220,
220,
287,
62,
8658,
796,
2116,
13,
25927,
13,
1136,
10786,
8658,
11537,
393,
2116,
13,
7206,
38865,
62,
5603,
33,
198,
220,
220,
220,
220,
220,
220,
220,
7400,
62,
2673,
796,
2116,
13,
25927,
13,
1136,
10786,
8658,
62,
2673,
11537,
393,
6045,
1303,
23211,
257,
9233,
7400,
3119,
523,
314,
460,
467,
3440,
257,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1303,
4553,
1570,
287,
262,
976,
7400,
628,
220,
220,
220,
220,
220,
220,
220,
611,
287,
62,
8658,
6624,
705,
23946,
10354,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
611,
7400,
62,
2673,
6624,
705,
305,
1706,
10354,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1441,
2116,
13,
1136,
62,
305,
1706,
3419,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2073,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1441,
2116,
13,
1136,
62,
23946,
3419,
198,
220,
220,
220,
220,
220,
220,
220,
1288,
361,
287,
62,
8658,
6624,
705,
660,
3493,
62,
2301,
10354,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1441,
2116,
13,
1136,
62,
660,
3493,
62,
2301,
3419,
198,
220,
220,
220,
220,
220,
220,
220,
1288,
361,
287,
62,
8658,
6624,
705,
50139,
62,
49170,
10354,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1441,
2116,
13,
1136,
62,
50139,
62,
42460,
3526,
3419,
628,
220,
220,
220,
825,
651,
62,
23946,
7,
944,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
49,
7338,
37703,
1570,
13,
24711,
17105,
1972,
1781,
9004,
290,
2615,
262,
1570,
37811,
198,
220,
220,
220,
220,
220,
220,
220,
11055,
62,
27160,
796,
23884,
198,
220,
220,
220,
220,
220,
220,
220,
11055,
62,
27160,
17816,
14933,
10223,
20520,
796,
2116,
13,
1136,
62,
17319,
22446,
62,
14933,
10223,
13,
33491,
10786,
5907,
62,
3256,
10148,
8,
628,
220,
220,
220,
220,
220,
220,
220,
1388,
62,
11299,
796,
2116,
13,
1136,
62,
28243,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
660,
3493,
62,
23946,
13,
6494,
3256,
685,
51,
3620,
6489,
29462,
62,
34720,
35944,
13287,
7,
28243,
62,
27160,
8,
628,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
13287,
62,
7700,
15090,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
7700,
62,
7839,
10354,
2116,
13,
18982,
62,
7839,
10786,
50,
478,
507,
33809,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
12417,
62,
11299,
10354,
474,
259,
6592,
17,
13,
26791,
13,
9704,
929,
7,
12417,
62,
11299,
8,
30072,
628,
220,
220,
220,
825,
651,
62,
50139,
62,
42460,
3526,
7,
944,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
49,
7338,
13613,
16189,
3526,
1570,
13,
628,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
4418,
3011,
11096,
2444,
287,
11096,
1781,
9004,
329,
262,
6823,
2836,
284,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1382,
257,
37420,
1960,
42829,
6677,
4268,
2902,
319,
262,
1570,
13,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
628,
220,
220,
220,
220,
220,
220,
220,
3710,
62,
12888,
796,
2116,
13,
25927,
13,
1136,
10786,
50139,
11537,
393,
6045,
1303,
12888,
481,
307,
287,
262,
2581,
611,
4721,
422,
3710,
1351,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1303,
1570,
11,
4306,
340,
481,
307,
6045,
628,
220,
220,
220,
220,
220,
220,
220,
1303,
31227,
284,
467,
832,
790,
1781,
2665,
329,
262,
1459,
2836,
290,
651,
477,
3748,
2444,
198,
220,
220,
220,
220,
220,
220,
220,
2444,
796,
17635,
198,
220,
220,
220,
220,
220,
220,
220,
1781,
62,
23946,
796,
4701,
62,
26858,
13,
49046,
16375,
32398,
13,
1136,
62,
17319,
62,
23946,
62,
1640,
62,
7220,
3419,
198,
220,
220,
220,
220,
220,
220,
220,
611,
1781,
62,
23946,
290,
18896,
7,
17319,
62,
23946,
8,
1875,
657,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
329,
1781,
62,
5458,
287,
1781,
62,
23946,
13,
27160,
33529,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
611,
1781,
62,
5458,
13,
19149,
658,
290,
18896,
7,
17319,
62,
5458,
13,
19149,
658,
8,
1875,
657,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
329,
3710,
62,
259,
62,
5458,
287,
1781,
62,
5458,
13,
19149,
658,
13,
27160,
33529,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
611,
407,
597,
7,
87,
17816,
7220,
62,
312,
20520,
6624,
3710,
62,
259,
62,
5458,
17816,
7220,
62,
312,
20520,
329,
2124,
287,
2444,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2444,
13,
33295,
7,
50139,
62,
259,
62,
5458,
8,
628,
220,
220,
220,
220,
220,
220,
220,
1303,
9122,
284,
766,
611,
356,
423,
257,
3710,
290,
611,
356,
761,
284,
651,
6496,
4371,
198,
220,
220,
220,
220,
220,
220,
220,
3710,
796,
6045,
198,
220,
220,
220,
220,
220,
220,
220,
611,
3710,
62,
12888,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
3710,
796,
13613,
13,
1136,
62,
1525,
62,
12888,
7,
50139,
62,
12888,
8,
628,
220,
220,
220,
220,
220,
220,
220,
611,
357,
50139,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1781,
796,
2116,
13,
1136,
62,
17319,
3419,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
4991,
796,
4701,
62,
79,
945,
364,
13,
38778,
32577,
35694,
13,
1136,
62,
15255,
6255,
62,
33723,
7,
50139,
11,
1781,
8,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
8198,
796,
4701,
62,
79,
945,
364,
13,
16516,
26595,
46677,
13,
1136,
62,
21797,
62,
1416,
2850,
26933,
50139,
13,
7220,
62,
312,
4357,
1781,
8,
198,
220,
220,
220,
220,
220,
220,
220,
2073,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
4991,
796,
6045,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
8198,
796,
6045,
628,
220,
220,
220,
220,
220,
220,
220,
1303,
13287,
262,
11055,
329,
262,
3710,
30415,
1570,
198,
220,
220,
220,
220,
220,
220,
220,
1388,
62,
11299,
796,
2116,
13,
1136,
62,
28243,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
50139,
62,
15255,
6255,
62,
33723,
13,
6494,
3256,
685,
51,
3620,
6489,
29462,
62,
34720,
35944,
13287,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1391,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
41667,
10354,
4991,
11,
1303,
20850,
11939,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
50139,
10354,
3710,
11,
1303,
17319,
5447,
3710,
2134,
11,
761,
3053,
290,
1438,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
19149,
658,
10354,
2444,
11,
1303,
4868,
286,
2444,
11,
3891,
290,
7237,
11,
422,
257,
1781,
2665,
3710,
1351,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
1416,
2850,
10354,
8198,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
32092,
628,
220,
220,
220,
220,
220,
220,
220,
1303,
13345,
16189,
3526,
25060,
2163,
284,
8543,
262,
2443,
198,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
13287,
62,
7700,
15090,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
7700,
62,
7839,
10354,
2116,
13,
18982,
62,
7839,
10786,
38778,
16189,
3526,
33809,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
12417,
62,
11299,
10354,
474,
259,
6592,
17,
13,
26791,
13,
9704,
929,
7,
12417,
62,
11299,
8,
198,
220,
220,
220,
220,
220,
220,
220,
32092,
628,
198,
220,
220,
220,
825,
651,
62,
305,
1706,
7,
944,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
49,
7338,
262,
371,
6197,
1570,
13,
3167,
26024,
477,
2444,
287,
257,
2060,
1781,
2665,
628,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
4418,
3578,
2836,
284,
751,
2444,
284,
257,
1781,
2665,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
628,
220,
220,
220,
220,
220,
220,
220,
11055,
62,
27160,
796,
23884,
198,
220,
220,
220,
220,
220,
220,
220,
11055,
62,
27160,
17816,
2860,
62,
50139,
62,
87,
27891,
69,
62,
30001,
20520,
796,
21473,
13,
55,
27891,
69,
30642,
13511,
13,
17953,
62,
87,
27891,
69,
62,
30001,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
4701,
62,
2118,
62,
4993,
8116,
13,
49046,
16375,
19452,
25060,
13,
55,
12562,
37,
62,
10468,
43959,
8,
628,
220,
220,
220,
220,
220,
220,
220,
1303,
31227,
1351,
286,
4991,
290,
11658,
329,
2922,
4847,
326,
5004,
543,
4371,
1988,
284,
3359,
198,
220,
220,
220,
220,
220,
220,
220,
1303,
31227,
257,
1351,
286,
4991,
11,
761,
262,
8714,
11,
4326,
220,
2340,
11,
3858,
198,
220,
220,
220,
220,
220,
220,
220,
4991,
796,
2116,
13,
1136,
62,
17319,
22446,
1136,
62,
41667,
3419,
198,
220,
220,
220,
220,
220,
220,
220,
4991,
62,
10379,
4400,
796,
8106,
7,
50033,
2124,
25,
2124,
13,
4906,
6624,
705,
52,
3256,
4991,
8,
1303,
24455,
503,
21837,
198,
220,
220,
220,
220,
220,
220,
220,
11055,
62,
27160,
17816,
41667,
20520,
796,
4991,
62,
10379,
4400,
628,
220,
220,
220,
220,
220,
220,
220,
1303,
31227,
284,
651,
11658,
11,
475,
691,
329,
4991,
326,
3588,
470,
21837,
198,
220,
220,
220,
220,
220,
220,
220,
11658,
796,
23884,
198,
220,
220,
220,
220,
220,
220,
220,
329,
4326,
287,
4991,
62,
10379,
4400,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
4326,
62,
1203,
684,
796,
2116,
13,
1136,
62,
17319,
22446,
1136,
62,
1203,
684,
7,
20850,
13,
20850,
62,
312,
8,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
4326,
62,
1203,
684,
62,
10379,
4400,
796,
17635,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
329,
11483,
287,
4326,
62,
1203,
684,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
4326,
62,
1203,
684,
62,
10379,
4400,
13,
33295,
15090,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
7839,
10354,
11483,
13,
7839,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
20850,
62,
312,
10354,
11483,
13,
20850,
62,
312,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
1203,
261,
62,
312,
10354,
11483,
13,
1203,
261,
62,
312,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
32092,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
11658,
58,
20850,
13,
20850,
62,
312,
60,
796,
4326,
62,
1203,
684,
62,
10379,
4400,
198,
220,
220,
220,
220,
220,
220,
220,
11055,
62,
27160,
17816,
1203,
684,
20520,
796,
31408,
13,
67,
8142,
7,
1203,
684,
11,
23884,
8,
1303,
6603,
278,
287,
19449,
284,
11055,
523,
340,
460,
307,
973,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1303,
287,
11933,
628,
220,
220,
220,
220,
220,
220,
220,
1781,
62,
5458,
62,
312,
796,
2116,
13,
25927,
13,
1136,
10786,
5458,
11537,
628,
220,
220,
220,
220,
220,
220,
220,
1781,
62,
5458,
796,
4701,
62,
26858,
13,
49046,
16375,
32398,
13,
1136,
62,
17319,
62,
1640,
62,
7220,
7,
17319,
62,
5458,
62,
312,
8,
198,
220,
220,
220,
220,
220,
220,
220,
2444,
796,
23884,
628,
220,
220,
220,
220,
220,
220,
220,
1303,
31227,
284,
651,
4371,
3815,
329,
11096,
2444,
1201,
356,
905,
11939,
329,
790,
3710,
198,
220,
220,
220,
220,
220,
220,
220,
611,
1781,
62,
5458,
13,
19149,
658,
290,
18896,
7,
17319,
62,
5458,
13,
19149,
658,
8,
1875,
657,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1303,
17319,
62,
5458,
13,
19149,
658,
796,
23243,
7,
17319,
62,
5458,
13,
19149,
658,
13,
27160,
22784,
1994,
28,
50033,
479,
25,
357,
74,
17816,
3672,
20520,
4008,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
329,
3710,
287,
1781,
62,
5458,
13,
19149,
658,
13,
27160,
33529,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
20218,
62,
50139,
796,
23884,
628,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
20218,
62,
50139,
17816,
20850,
62,
785,
24547,
20520,
796,
4701,
62,
79,
945,
364,
13,
38778,
32577,
35694,
13,
1136,
62,
20850,
62,
785,
24547,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
13613,
13,
1136,
62,
1525,
62,
12888,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
3710,
58,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
12888,
20520,
828,
2116,
13,
1136,
62,
17319,
28955,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
20218,
62,
50139,
17816,
17319,
62,
785,
24547,
20520,
796,
4701,
62,
79,
945,
364,
13,
38778,
32577,
35694,
13,
1136,
62,
2502,
439,
62,
33723,
7,
38778,
13,
1136,
62,
1525,
62,
12888,
7,
50139,
58,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
12888,
20520,
828,
2116,
13,
1136,
62,
17319,
28955,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
20218,
62,
50139,
17816,
15255,
6255,
62,
17319,
62,
785,
24547,
20520,
796,
4701,
62,
79,
945,
364,
13,
38778,
32577,
35694,
13,
1136,
62,
15255,
6255,
62,
33723,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
13613,
13,
1136,
62,
1525,
62,
12888,
7,
50139,
17816,
12888,
20520,
828,
2116,
13,
1136,
62,
17319,
28955,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
20218,
62,
50139,
17816,
12888,
20520,
796,
3710,
17816,
12888,
20520,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
20218,
62,
50139,
17816,
3672,
20520,
796,
3710,
17816,
3672,
20520,
628,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2444,
58,
50139,
17816,
12888,
6,
11907,
796,
20218,
62,
50139,
628,
220,
220,
220,
220,
220,
220,
220,
1781,
62,
5458,
13,
19149,
658,
796,
2444,
628,
220,
220,
220,
220,
220,
220,
220,
1303,
6603,
278,
287,
2444,
355,
19449,
523,
11933,
460,
5412,
19698,
11939,
3815,
4577,
198,
220,
220,
220,
220,
220,
220,
220,
11055,
62,
27160,
17816,
19149,
658,
62,
17752,
20520,
796,
31408,
13,
67,
8142,
7,
17319,
62,
5458,
13,
19149,
658,
11,
23884,
8,
198,
220,
220,
220,
220,
220,
220,
220,
11055,
62,
27160,
17816,
14933,
10223,
20520,
796,
2116,
13,
1136,
62,
17319,
22446,
62,
14933,
10223,
13,
33491,
10786,
5907,
62,
3256,
10148,
8,
628,
220,
220,
220,
220,
220,
220,
220,
611,
1781,
62,
5458,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
11055,
62,
27160,
17816,
5458,
20520,
796,
1781,
62,
5458,
628,
220,
220,
220,
220,
220,
220,
220,
1303,
13287,
3710,
62,
4868,
13,
6494,
329,
371,
6197,
1570,
198,
220,
220,
220,
220,
220,
220,
220,
1388,
62,
11299,
796,
2116,
13,
1136,
62,
28243,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
50139,
62,
4868,
13,
6494,
3256,
685,
51,
3620,
6489,
29462,
62,
34720,
35944,
13287,
7,
28243,
62,
27160,
8,
628,
220,
220,
220,
220,
220,
220,
220,
1303,
43041,
3526,
25060,
30111,
262,
2443,
198,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
13287,
62,
7700,
15090,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
7700,
62,
7839,
10354,
2116,
13,
18982,
62,
7839,
10786,
38778,
7343,
33809,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
12417,
62,
11299,
10354,
474,
259,
6592,
17,
13,
26791,
13,
9704,
929,
7,
12417,
62,
11299,
8,
30072,
628,
198,
220,
220,
220,
825,
651,
62,
660,
3493,
62,
2301,
7,
944,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
49,
7338,
32019,
10933,
10223,
1570,
13,
3167,
26024,
1296,
284,
751,
393,
4296,
257,
4701,
628,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
4418,
11298,
477,
6823,
7799,
13,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
628,
220,
220,
220,
220,
220,
220,
220,
21675,
796,
17635,
198,
220,
220,
220,
220,
220,
220,
220,
15560,
62,
687,
796,
10352,
628,
220,
220,
220,
220,
220,
220,
220,
611,
407,
9176,
13,
49,
4316,
13,
271,
62,
17319,
62,
28482,
7,
944,
13,
1324,
62,
22866,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
21675,
13,
33295,
10786,
15457,
6699,
13,
4222,
2800,
257,
1781,
13169,
2637,
8,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
15560,
62,
687,
796,
6407,
628,
220,
220,
220,
220,
220,
220,
220,
11055,
62,
27160,
796,
23884,
198,
220,
220,
220,
220,
220,
220,
220,
11055,
62,
27160,
17816,
660,
3493,
62,
2301,
62,
87,
27891,
69,
62,
30001,
20520,
796,
2116,
13,
17953,
62,
87,
27891,
69,
62,
30001,
10786,
660,
3493,
62,
2301,
11537,
628,
220,
220,
220,
220,
220,
220,
220,
11055,
62,
27160,
17816,
660,
17892,
20520,
796,
4701,
62,
26858,
13,
6767,
3493,
13,
1136,
62,
439,
62,
660,
17892,
62,
1640,
62,
17319,
3419,
198,
220,
220,
220,
220,
220,
220,
220,
11055,
62,
27160,
17816,
44598,
62,
37348,
1095,
20520,
796,
21675,
198,
220,
220,
220,
220,
220,
220,
220,
11055,
62,
27160,
17816,
40223,
20520,
796,
15560,
62,
687,
198,
220,
220,
220,
220,
220,
220,
220,
11055,
62,
27160,
17816,
2673,
20520,
796,
2116,
13,
1136,
62,
2673,
62,
6371,
10786,
660,
3493,
62,
2301,
11537,
628,
220,
220,
220,
220,
220,
220,
220,
1388,
62,
11299,
796,
2116,
13,
1136,
62,
28243,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
660,
3493,
62,
2301,
33397,
13,
6494,
3256,
685,
51,
3620,
6489,
29462,
62,
34720,
35944,
13287,
7,
28243,
62,
27160,
8,
628,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
13287,
62,
7700,
15090,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
7700,
62,
7839,
10354,
2116,
13,
18982,
62,
7839,
10786,
6767,
3493,
24610,
33809,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
12417,
62,
11299,
10354,
474,
259,
6592,
17,
13,
26791,
13,
9704,
929,
7,
12417,
62,
11299,
8,
30072,
628,
220,
220,
220,
2488,
4871,
24396,
198,
220,
220,
220,
825,
1281,
62,
660,
3493,
62,
2301,
7,
565,
82,
11,
21360,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
12885,
829,
1296,
9199,
329,
4701,
9352,
37811,
628,
220,
220,
220,
220,
220,
220,
220,
1303,
1136,
3815,
5982,
319,
1296,
198,
220,
220,
220,
220,
220,
220,
220,
3053,
796,
21360,
13,
25927,
13,
1136,
10786,
12888,
27691,
36311,
3419,
198,
220,
220,
220,
220,
220,
220,
220,
1524,
796,
21360,
13,
25927,
13,
1136,
10786,
14347,
11537,
628,
220,
220,
220,
220,
220,
220,
220,
1303,
37210,
2198,
3524,
1988,
318,
257,
1310,
7650,
11,
1244,
804,
1180,
6906,
319,
6444,
198,
220,
220,
220,
220,
220,
220,
220,
4075,
796,
21360,
13,
25927,
13,
1136,
10786,
5275,
12,
660,
3493,
11537,
198,
220,
220,
220,
220,
220,
220,
220,
611,
4075,
6624,
705,
261,
6,
393,
18896,
7,
5275,
8,
1875,
657,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
4075,
796,
6407,
198,
220,
220,
220,
220,
220,
220,
220,
2073,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
4075,
796,
10352,
628,
220,
220,
220,
220,
220,
220,
220,
4701,
796,
4701,
62,
26858,
13,
6767,
3493,
13,
1136,
62,
1525,
62,
12888,
7,
12888,
8,
628,
220,
220,
220,
220,
220,
220,
220,
1303,
14894,
2610,
286,
597,
8563,
356,
1244,
765,
284,
1208,
736,
284,
262,
12454,
198,
220,
220,
220,
220,
220,
220,
220,
21675,
796,
17635,
628,
220,
220,
220,
220,
220,
220,
220,
1303,
9122,
284,
766,
611,
257,
4701,
1541,
7160,
198,
220,
220,
220,
220,
220,
220,
220,
611,
4701,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
11055,
62,
27160,
796,
23884,
628,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
11055,
62,
27160,
17816,
660,
3493,
62,
2301,
62,
87,
27891,
69,
62,
30001,
20520,
796,
21360,
13,
17953,
62,
87,
27891,
69,
62,
30001,
10786,
660,
3493,
62,
2301,
11537,
628,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
9004,
796,
23884,
628,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1303,
9099,
470,
1309,
262,
4701,
307,
390,
33106,
611,
484,
423,
4075,
10902,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
460,
62,
259,
39022,
796,
6407,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
611,
4075,
6624,
10352,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
611,
4701,
13,
23946,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1781,
62,
23946,
62,
12501,
9043,
796,
31408,
13,
46030,
7,
660,
3493,
13,
23946,
8,
628,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
329,
1781,
62,
5458,
62,
2539,
287,
1781,
62,
23946,
62,
12501,
9043,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1781,
62,
5458,
796,
4701,
62,
26858,
13,
49046,
16375,
32398,
7,
17319,
62,
23946,
62,
12501,
9043,
58,
17319,
62,
5458,
62,
2539,
12962,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
9004,
58,
17319,
62,
5458,
13,
5458,
62,
312,
60,
796,
1781,
62,
5458,
628,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
329,
2665,
287,
9004,
13,
27160,
33529,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
611,
2665,
13,
271,
62,
5275,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
460,
62,
259,
39022,
796,
10352,
628,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1303,
1616,
2836,
760,
611,
484,
460,
470,
390,
39022,
11,
475,
691,
611,
484,
389,
2111,
284,
390,
39022,
262,
4701,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
611,
407,
460,
62,
259,
39022,
290,
407,
4075,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
21675,
13,
33295,
10786,
34,
34574,
390,
39022,
4701,
13,
32019,
991,
468,
4075,
10902,
11537,
628,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1303,
2188,
329,
262,
4296,
611,
477,
318,
922,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
611,
460,
62,
259,
39022,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
4701,
62,
26858,
13,
6767,
3493,
13,
19119,
62,
660,
3493,
62,
1640,
62,
7220,
7,
12888,
11,
1524,
11,
4075,
11,
705,
3256,
21675,
8,
628,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1303,
1616,
2836,
760,
477,
318,
880,
611,
3613,
373,
4388,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
611,
18896,
7,
44598,
82,
8,
6624,
657,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
21675,
13,
33295,
10786,
6767,
3493,
373,
7675,
6153,
11537,
628,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1303,
13287,
4701,
62,
2301,
33397,
13,
6494,
329,
1570,
11,
1208,
21675,
287,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
11055,
62,
27160,
17816,
44598,
62,
37348,
1095,
20520,
796,
705,
59,
77,
4458,
22179,
7,
44598,
82,
8,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1388,
62,
11299,
796,
21360,
13,
1136,
62,
28243,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
660,
3493,
62,
2301,
33397,
13,
6494,
3256,
685,
51,
3620,
6489,
29462,
62,
34720,
35944,
13287,
7,
28243,
62,
27160,
8,
628,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1303,
43041,
3526,
25060,
30111,
262,
2443,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
21360,
13,
13287,
62,
7700,
15090,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
7700,
62,
7839,
10354,
21360,
13,
18982,
62,
7839,
10786,
6767,
3493,
16189,
3526,
33809,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
12417,
62,
11299,
10354,
474,
259,
6592,
17,
13,
26791,
13,
9704,
929,
7,
12417,
62,
11299,
8,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
8964,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
660,
3493,
62,
42460,
3526,
6,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1267,
198,
220,
220,
220,
220,
220,
220,
220,
2073,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1303,
2188,
329,
340,
611,
4701,
1595,
470,
1541,
2152,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
4701,
62,
26858,
13,
6767,
3493,
13,
2860,
62,
3605,
62,
660,
3493,
62,
1640,
62,
7220,
7,
12888,
11,
1524,
11,
705,
3256,
21675,
8,
628,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
11055,
62,
27160,
796,
23884,
628,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
11055,
62,
27160,
17816,
44598,
62,
37348,
1095,
20520,
796,
705,
59,
77,
4458,
22179,
7,
44598,
82,
8,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
11055,
62,
27160,
17816,
660,
3493,
62,
2301,
62,
87,
27891,
69,
62,
30001,
20520,
796,
21360,
13,
17953,
62,
87,
27891,
69,
62,
30001,
10786,
660,
3493,
62,
2301,
11537,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1388,
62,
11299,
796,
21360,
13,
1136,
62,
28243,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
660,
3493,
62,
2301,
33397,
13,
6494,
3256,
685,
51,
3620,
6489,
29462,
62,
34720,
35944,
13287,
7,
28243,
62,
27160,
8,
628,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1303,
43041,
3526,
25060,
30111,
262,
2443,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
21360,
13,
13287,
62,
7700,
15090,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
7700,
62,
7839,
10354,
21360,
13,
18982,
62,
7839,
10786,
6767,
3493,
16189,
3526,
33809,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
12417,
62,
11299,
10354,
474,
259,
6592,
17,
13,
26791,
13,
9704,
929,
7,
12417,
62,
11299,
8,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
8964,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
660,
3493,
62,
42460,
3526,
6,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1267,
628,
198,
4299,
19361,
62,
21412,
62,
25616,
33529,
198,
220,
220,
220,
37227,
12885,
829,
1243,
706,
8265,
468,
587,
9343,
526,
15931,
628,
220,
220,
220,
825,
651,
62,
2673,
7,
30281,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
7738,
1060,
82,
284,
4701,
62,
42460,
3526,
526,
15931,
198,
220,
220,
220,
220,
220,
220,
220,
21360,
13,
445,
1060,
10786,
14,
18170,
14,
660,
3493,
62,
42460,
3526,
30,
2673,
28,
660,
3493,
62,
42460,
3526,
5,
8658,
28,
4,
82,
6,
4064,
21360,
13,
25927,
13,
1136,
10786,
8658,
11537,
393,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
32019,
25060,
13,
7206,
38865,
62,
5603,
33,
8,
628,
220,
220,
220,
30415,
13,
43041,
3526,
25060,
13,
2860,
62,
28341,
62,
76,
5912,
7,
198,
220,
220,
220,
220,
220,
220,
220,
32019,
25060,
13,
44710,
11,
705,
6767,
3493,
11537,
628,
220,
220,
220,
30415,
13,
43041,
3526,
25060,
13,
1136,
62,
4658,
13,
33295,
10786,
660,
3493,
62,
42460,
3526,
11537,
198,
220,
220,
220,
900,
35226,
7,
42460,
3526,
13,
43041,
3526,
25060,
11,
705,
1136,
62,
660,
3493,
62,
42460,
3526,
3256,
651,
62,
2673,
8,
628,
220,
220,
220,
1303,
2860,
1281,
4028,
198,
220,
220,
220,
30415,
13,
43041,
3526,
25060,
13,
2860,
62,
23144,
62,
7353,
62,
2673,
10786,
660,
3493,
62,
2301,
3256,
1281,
62,
2673,
8,
198,
220,
220,
220,
900,
35226,
7,
42460,
3526,
13,
43041,
3526,
25060,
11,
705,
7353,
62,
660,
3493,
62,
2301,
3256,
1281,
62,
2673,
8,
628,
220,
220,
220,
1303,
2860,
21627,
329,
262,
30415,
9004,
198,
220,
220,
220,
30415,
13,
43041,
3526,
25060,
13,
2860,
62,
22615,
62,
525,
3411,
7,
198,
220,
220,
220,
220,
220,
220,
220,
15859,
7597,
62,
10705,
32716,
62,
18973,
44,
40373,
11,
15859,
7597,
62,
10705,
32716,
62,
18973,
44,
40373,
62,
30910,
40165,
8,
198,
220,
220,
220,
30415,
13,
43041,
3526,
25060,
13,
2860,
62,
22615,
62,
525,
3411,
7,
198,
220,
220,
220,
220,
220,
220,
220,
15859,
7597,
62,
28480,
51,
20754,
62,
18973,
44,
40373,
11,
15859,
7597,
62,
28480,
51,
20754,
62,
18973,
44,
40373,
62,
30910,
40165,
8,
198,
220,
220,
220,
30415,
13,
43041,
3526,
25060,
13,
2860,
62,
22615,
62,
525,
3411,
7,
198,
220,
220,
220,
220,
220,
220,
220,
15859,
7597,
62,
49,
3535,
1546,
62,
18973,
44,
40373,
11,
15859,
7597,
62,
49,
3535,
1546,
62,
18973,
44,
40373,
62,
30910,
40165,
8,
198,
220,
220,
220,
30415,
13,
43041,
3526,
25060,
13,
2860,
62,
22615,
62,
525,
3411,
7,
198,
220,
220,
220,
220,
220,
220,
220,
15859,
7597,
62,
1565,
1847,
56,
51,
19505,
62,
18973,
44,
40373,
11,
15859,
7597,
62,
1565,
1847,
56,
51,
19505,
62,
18973,
44,
40373,
62,
30910,
40165,
8,
198,
220,
220,
220,
30415,
13,
43041,
3526,
25060,
13,
2860,
62,
22615,
62,
525,
3411,
7,
198,
220,
220,
220,
220,
220,
220,
220,
15859,
7597,
62,
5188,
31315,
62,
18973,
44,
40373,
11,
15859,
7597,
62,
5188,
31315,
62,
18973,
44,
40373,
62,
30910,
40165,
8,
198,
220,
220,
220,
30415,
13,
43041,
3526,
25060,
13,
2860,
62,
22615,
62,
525,
3411,
7,
198,
220,
220,
220,
220,
220,
220,
220,
15859,
7597,
62,
11401,
1137,
2200,
28206,
62,
18973,
44,
40373,
11,
15859,
7597,
62,
11401,
1137,
2200,
28206,
62,
18973,
44,
40373,
62,
30910,
40165,
8,
198,
220,
220,
220,
30415,
13,
43041,
3526,
25060,
13,
2860,
62,
22615,
62,
525,
3411,
7,
198,
220,
220,
220,
220,
220,
220,
220,
15859,
7597,
62,
18831,
8267,
33767,
62,
18973,
44,
40373,
11,
15859,
7597,
62,
18831,
8267,
33767,
62,
18973,
44,
40373,
62,
30910,
40165,
8,
198,
220,
220,
220,
30415,
13,
43041,
3526,
25060,
13,
2860,
62,
22615,
62,
525,
3411,
7,
198,
220,
220,
220,
220,
220,
220,
220,
15859,
7597,
62,
9328,
16219,
1137,
62,
35,
11211,
8202,
9795,
62,
18973,
44,
40373,
11,
15859,
7597,
62,
9328,
16219,
1137,
62,
35,
11211,
8202,
9795,
62,
18973,
44,
40373,
62,
30910,
40165,
8,
628,
220,
220,
220,
1303,
8899,
21627,
284,
4028,
198,
220,
220,
220,
30415,
13,
43041,
3526,
25060,
13,
8899,
62,
2673,
62,
1462,
62,
525,
3411,
10786,
1136,
62,
6,
1343,
965,
7,
6767,
3493,
25060,
13,
44710,
828,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
15859,
7597,
62,
9328,
16219,
1137,
62,
35,
11211,
8202,
9795,
62,
18973,
44,
40373,
8,
198,
220,
220,
220,
6812,
62,
76,
39242,
796,
30415,
13,
43041,
3526,
25060,
13,
1136,
62,
28341,
62,
76,
39242,
3419,
198,
220,
220,
220,
30415,
13,
43041,
3526,
25060,
13,
8899,
62,
2673,
62,
1462,
62,
525,
3411,
10786,
1136,
62,
6,
1343,
965,
7,
28341,
62,
76,
39242,
58,
16,
7131,
15,
46570,
15859,
7597,
62,
10705,
32716,
62,
18973,
44,
40373,
8,
198,
220,
220,
220,
30415,
13,
43041,
3526,
25060,
13,
8899,
62,
2673,
62,
1462,
62,
525,
3411,
10786,
1136,
62,
6,
1343,
965,
7,
28341,
62,
76,
39242,
58,
17,
7131,
15,
46570,
15859,
7597,
62,
28480,
51,
20754,
62,
18973,
44,
40373,
8,
198,
220,
220,
220,
30415,
13,
43041,
3526,
25060,
13,
8899,
62,
2673,
62,
1462,
62,
525,
3411,
10786,
1136,
62,
6,
1343,
965,
7,
28341,
62,
76,
39242,
58,
18,
7131,
15,
46570,
15859,
7597,
62,
49,
3535,
1546,
62,
18973,
44,
40373,
8,
198,
220,
220,
220,
30415,
13,
43041,
3526,
25060,
13,
8899,
62,
2673,
62,
1462,
62,
525,
3411,
10786,
1136,
62,
6,
1343,
965,
7,
28341,
62,
76,
39242,
58,
19,
7131,
15,
46570,
15859,
7597,
62,
1565,
1847,
56,
51,
19505,
62,
18973,
44,
40373,
8,
198,
220,
220,
220,
30415,
13,
43041,
3526,
25060,
13,
8899,
62,
2673,
62,
1462,
62,
525,
3411,
10786,
1136,
62,
6,
1343,
965,
7,
28341,
62,
76,
39242,
58,
20,
7131,
15,
46570,
15859,
7597,
62,
5188,
31315,
62,
18973,
44,
40373,
8,
198,
220,
220,
220,
30415,
13,
43041,
3526,
25060,
13,
8899,
62,
2673,
62,
1462,
62,
525,
3411,
10786,
1136,
62,
6,
1343,
965,
7,
28341,
62,
76,
39242,
58,
21,
7131,
15,
46570,
15859,
7597,
62,
11401,
1137,
2200,
28206,
62,
18973,
44,
40373,
8,
198,
220,
220,
220,
30415,
13,
43041,
3526,
25060,
13,
8899,
62,
2673,
62,
1462,
62,
525,
3411,
10786,
1136,
62,
6,
1343,
965,
7,
28341,
62,
76,
39242,
58,
22,
7131,
15,
46570,
15859,
7597,
62,
18831,
8267,
33767,
62,
18973,
44,
40373,
8,
628,
220,
220,
220,
30415,
13,
43041,
3526,
25060,
13,
13918,
3861,
62,
20120,
62,
39,
31688,
62,
45849,
13,
33295,
7,
198,
220,
220,
220,
220,
220,
220,
220,
31051,
18170,
14,
660,
3493,
62,
42460,
3526,
14,
37540,
14,
8457,
14,
12924,
929,
13,
8457,
11537,
198,
220,
220,
220,
30415,
13,
43041,
3526,
25060,
13,
13918,
3861,
62,
20120,
62,
39,
31688,
62,
45849,
13,
33295,
7,
198,
220,
220,
220,
220,
220,
220,
220,
31051,
18170,
14,
660,
3493,
62,
42460,
3526,
14,
37540,
14,
8457,
14,
17319,
62,
5458,
62,
38200,
14094,
13,
8457,
11537,
198,
220,
220,
220,
30415,
13,
43041,
3526,
25060,
13,
13918,
3861,
62,
20120,
62,
39,
31688,
62,
45849,
13,
33295,
7,
198,
220,
220,
220,
220,
220,
220,
220,
31051,
18170,
14,
660,
3493,
62,
42460,
3526,
14,
37540,
14,
8457,
14,
21797,
62,
26675,
62,
37153,
13,
8457,
11537,
198,
220,
220,
220,
30415,
13,
43041,
3526,
25060,
13,
13918,
3861,
62,
20120,
62,
39,
31688,
62,
45849,
13,
33295,
7,
198,
220,
220,
220,
220,
220,
220,
220,
31051,
18170,
14,
660,
3493,
62,
42460,
3526,
14,
37540,
14,
8457,
14,
50139,
62,
4868,
62,
11487,
62,
37153,
11537,
198,
220,
220,
220,
30415,
13,
43041,
3526,
25060,
13,
13918,
3861,
62,
20120,
62,
39,
31688,
62,
45849,
13,
33295,
7,
198,
220,
220,
220,
220,
220,
220,
220,
31051,
18170,
14,
660,
3493,
62,
42460,
3526,
14,
37540,
14,
8457,
14,
50139,
62,
4868,
62,
11487,
62,
260,
11249,
62,
37153,
13,
8457,
11537,
198,
220,
220,
220,
30415,
13,
43041,
3526,
25060,
13,
13918,
3861,
62,
20120,
62,
39,
31688,
62,
45849,
13,
33295,
7,
198,
220,
220,
220,
220,
220,
220,
220,
31051,
18170,
14,
660,
3493,
62,
42460,
3526,
14,
37540,
14,
8457,
14,
21797,
62,
26675,
62,
11487,
62,
37153,
13,
8457,
11537,
198,
220,
220,
220,
30415,
13,
43041,
3526,
25060,
13,
13918,
3861,
62,
20120,
62,
39,
31688,
62,
45849,
13,
33295,
7,
198,
220,
220,
220,
220,
220,
220,
220,
31051,
18170,
14,
660,
3493,
62,
42460,
3526,
14,
37540,
14,
8457,
14,
50139,
62,
26675,
62,
37153,
13,
8457,
11537,
628,
220,
220,
220,
30415,
13,
43041,
3526,
25060,
13,
13918,
3861,
62,
49155,
62,
39,
31688,
62,
45849,
13,
33295,
7,
198,
220,
220,
220,
220,
220,
220,
220,
31051,
18170,
14,
660,
3493,
62,
42460,
3526,
14,
37540,
14,
25471,
14,
50139,
62,
4868,
13,
25471,
11537,
628,
220,
220,
220,
31408,
13,
34,
7759,
2662,
62,
40386,
62,
24181,
3727,
4877,
13,
33295,
7,
660,
3493,
62,
26858,
13,
49046,
16375,
32398,
13,
17752,
62,
12685,
12342,
8,
628,
220,
220,
220,
1303,
30238,
22524,
198,
220,
220,
220,
32019,
25060,
13,
30238,
62,
8658,
82,
3419,
628,
198,
4299,
7881,
62,
21412,
33529,
198,
220,
220,
220,
37227,
8081,
6223,
428,
8265,
287,
262,
20478,
526,
15931,
628,
220,
220,
220,
3298,
62,
81,
448,
274,
796,
685,
198,
220,
220,
220,
220,
220,
220,
220,
357,
418,
13,
6978,
13,
22179,
7,
19535,
2606,
7397,
1546,
62,
34219,
11,
705,
8457,
3256,
705,
15885,
33809,
15940,
13,
41,
20746,
25060,
828,
198,
220,
220,
220,
220,
220,
220,
220,
357,
418,
13,
6978,
13,
22179,
7,
19535,
2606,
7397,
1546,
62,
34219,
11,
705,
15885,
33809,
15940,
13,
33236,
25060,
828,
198,
220,
220,
220,
220,
220,
220,
220,
357,
19535,
2606,
7397,
1546,
62,
34219,
1343,
31051,
8457,
14,
12924,
929,
13,
8457,
3256,
15940,
13,
40,
901,
25060,
828,
198,
220,
220,
220,
220,
220,
220,
220,
357,
19535,
2606,
7397,
1546,
62,
34219,
1343,
31051,
8457,
14,
17319,
62,
5458,
62,
38200,
14094,
13,
8457,
3256,
15940,
13,
40,
901,
25060,
828,
198,
220,
220,
220,
220,
220,
220,
220,
357,
19535,
2606,
7397,
1546,
62,
34219,
1343,
31051,
8457,
14,
21797,
62,
26675,
62,
37153,
13,
8457,
3256,
15940,
13,
40,
901,
25060,
828,
198,
220,
220,
220,
220,
220,
220,
220,
357,
19535,
2606,
7397,
1546,
62,
34219,
1343,
31051,
8457,
14,
50139,
62,
4868,
62,
11487,
62,
37153,
3256,
15940,
13,
40,
901,
25060,
828,
198,
220,
220,
220,
220,
220,
220,
220,
357,
19535,
2606,
7397,
1546,
62,
34219,
1343,
31051,
8457,
14,
50139,
62,
4868,
62,
11487,
62,
260,
11249,
62,
37153,
13,
8457,
3256,
15940,
13,
40,
901,
25060,
828,
198,
220,
220,
220,
220,
220,
220,
220,
357,
19535,
2606,
7397,
1546,
62,
34219,
1343,
31051,
8457,
14,
21797,
62,
26675,
62,
11487,
62,
37153,
13,
8457,
3256,
15940,
13,
40,
901,
25060,
828,
198,
220,
220,
220,
220,
220,
220,
220,
357,
19535,
2606,
7397,
1546,
62,
34219,
1343,
31051,
8457,
14,
50139,
62,
26675,
62,
37153,
13,
8457,
3256,
15940,
13,
40,
901,
25060,
8,
198,
220,
220,
220,
220,
220,
220,
2361,
628,
220,
220,
220,
3891,
32416,
62,
81,
448,
274,
796,
685,
198,
220,
220,
220,
220,
220,
220,
220,
220,
357,
6767,
3493,
25060,
13,
21886,
11,
32019,
25060,
828,
198,
220,
220,
220,
220,
220,
220,
220,
220,
357,
660,
3493,
62,
2118,
62,
4993,
8116,
13,
49046,
16375,
19452,
25060,
13,
21886,
11,
4701,
62,
2118,
62,
4993,
8116,
13,
49046,
16375,
19452,
25060,
828,
198,
220,
220,
220,
220,
220,
220,
220,
220,
357,
660,
3493,
62,
2118,
62,
4993,
8116,
13,
38778,
32577,
19452,
25060,
13,
21886,
11,
4701,
62,
2118,
62,
4993,
8116,
13,
38778,
32577,
19452,
25060,
828,
198,
220,
220,
220,
220,
220,
220,
220,
220,
357,
660,
3493,
62,
2118,
62,
4993,
8116,
13,
16516,
26595,
19452,
25060,
13,
21886,
11,
4701,
62,
2118,
62,
4993,
8116,
13,
16516,
26595,
19452,
25060,
8,
198,
220,
220,
220,
220,
220,
220,
220,
2361,
628,
220,
220,
220,
3298,
2183,
62,
21412,
220,
1303,
279,
2645,
600,
25,
15560,
28,
20541,
12,
26090,
198,
220,
220,
220,
2183,
62,
21412,
796,
2183,
62,
18170,
13,
26796,
7,
198,
220,
220,
220,
220,
220,
220,
220,
705,
6767,
3493,
16189,
3526,
19937,
3256,
198,
220,
220,
220,
220,
220,
220,
220,
705,
32,
8265,
2148,
4701,
30798,
2637,
11,
198,
220,
220,
220,
220,
220,
220,
220,
3298,
62,
81,
448,
274,
11,
3891,
32416,
62,
81,
448,
274,
11,
198,
220,
220,
220,
220,
220,
220,
220,
19361,
62,
21412,
62,
25616,
28,
1662,
1958,
62,
21412,
62,
25616,
8,
628,
220,
220,
220,
1441,
2183,
62,
21412,
198
] | 2.469857 | 8,609 |
#!/usr/bin/env python
# Copyright 2016, 2017 F5 Networks, Inc.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
from __future__ import absolute_import
import argparse
import base64
import fcntl
import hashlib
import ipaddress
import json
import logging
import os
import os.path
import sys
import time
import threading
import signal
import urllib
import pyinotify
from urlparse import urlparse
from f5_cccl._f5 import CloudBigIP, get_protocol, has_partition, log_sequence
from f5_cccl.common import extract_partition_and_name, ipv4_to_mac,\
list_diff_exclusive, IPV4FormatError, PartitionNameError
from f5.bigip import ManagementRoot
log = logging.getLogger(__name__)
console = logging.StreamHandler()
console.setFormatter(
logging.Formatter("[%(asctime)s %(name)s %(levelname)s] %(message)s"))
root_logger = logging.getLogger()
root_logger.addHandler(console)
root_logger.addFilter(ResponseStatusFilter())
root_logger.addFilter(CertFilter())
root_logger.addFilter(KeyFilter())
DEFAULT_LOG_LEVEL = logging.INFO
DEFAULT_VERIFY_INTERVAL = 30.0
class K8sCloudBigIP(CloudBigIP):
"""K8sCloudBigIP class.
Generates a configuration for a BigIP based upon the apps/tasks managed
by services/pods/nodes in Kubernetes.
- Matches apps/sevices by BigIP partition
- Creates a Virtual Server and pool for each service type that matches a
BigIP partition
- For each backend (task, node, or pod), it creates a pool member and adds
the member to the pool
- If the app has a Marathon Health Monitor configured, create a
corresponding health monitor for the BigIP pool member
- Token-based authentication is used by specifying a token named 'tmos'.
This will allow non-admin users to use the API (BIG-IP must configure
the accounts with proper permissions, for either local or remote auth).
Args:
hostname: IP address of BIG-IP
username: BIG-IP username
password: BIG-IP password
partitions: List of BIG-IP partitions to manage
"""
def __init__(self, hostname, port, username, password, partitions,
manage_types):
"""Initialize the K8sCloudBigIP object."""
super(K8sCloudBigIP, self).__init__(hostname, port, username,
password, partitions,
token="tmos",
manage_types=manage_types)
def _apply_config(self, config):
"""Apply the configuration to the BIG-IP.
Args:
config: BIG-IP config dict
"""
if 'ltm' in config:
CloudBigIP._apply_config(self, config['ltm'])
if 'network' in config:
self._apply_network_config(config['network'])
def _apply_network_config(self, config):
"""Apply the network configuration to the BIG-IP.
Args:
config: BIG-IP network config dict
"""
if 'fdb' in config:
self._apply_network_fdb_config(config['fdb'])
def _apply_network_fdb_config(self, fdb_config):
"""Apply the network fdb configuration to the BIG-IP.
Args:
config: BIG-IP network fdb config dict
"""
req_vxlan_name = fdb_config['vxlan-name']
req_fdb_record_endpoint_list = fdb_config['vxlan-node-ips']
try:
f5_fdb_record_endpoint_list = self.get_fdb_records(req_vxlan_name)
log_sequence('req_fdb_record_list', req_fdb_record_endpoint_list)
log_sequence('f5_fdb_record_list', f5_fdb_record_endpoint_list)
# See if the list of records is different.
# If so, update with new list.
if list_diff_exclusive(f5_fdb_record_endpoint_list,
req_fdb_record_endpoint_list):
self.fdb_records_update(req_vxlan_name,
req_fdb_record_endpoint_list)
except (PartitionNameError, IPV4FormatError) as e:
log.error(e)
return
except Exception as e:
log.error('Failed to configure the FDB for VxLAN tunnel '
'{}: {}'.format(req_vxlan_name, e))
def get_vxlan_tunnel(self, vxlan_name):
"""Get a vxlan tunnel object.
Args:
vxlan_name: Name of the vxlan tunnel
"""
partition, name = extract_partition_and_name(vxlan_name)
vxlan_tunnel = self.net.fdb.tunnels.tunnel.load(
partition=partition, name=urllib.quote(name))
return vxlan_tunnel
def get_fdb_records(self, vxlan_name):
"""Get a list of FDB records (just the endpoint list) for the vxlan.
Args:
vxlan_name: Name of the vxlan tunnel
"""
endpoint_list = []
vxlan_tunnel = self.get_vxlan_tunnel(vxlan_name)
if hasattr(vxlan_tunnel, 'records'):
for record in vxlan_tunnel.records:
endpoint_list.append(record['endpoint'])
return endpoint_list
def fdb_records_update(self, vxlan_name, endpoint_list):
"""Update the fdb records for a vxlan tunnel.
Args:
vxlan_name: Name of the vxlan tunnel
fdb_record_list: IP address associated with the fdb record
"""
vxlan_tunnel = self.get_vxlan_tunnel(vxlan_name)
data = {'records': []}
records = data['records']
for endpoint in endpoint_list:
record = {'name': ipv4_to_mac(endpoint), 'endpoint': endpoint}
records.append(record)
log.debug("Updating records for vxlan tunnel {}: {}".format(
vxlan_name, data['records']))
vxlan_tunnel.update(**data)
def create_config_kubernetes(bigip, config):
"""Create a BIG-IP configuration from the Kubernetes configuration.
Args:
config: Kubernetes BigIP config
"""
log.debug("Generating config for BIG-IP from Kubernetes state")
f5 = {'ltm': {}, 'network': {}}
if 'openshift-sdn' in config:
f5['network'] = create_network_config_kubernetes(config)
if 'resources' in config and 'virtualServers' in config['resources']:
f5['ltm'] = create_ltm_config_kubernetes(bigip, config['resources'])
return f5
def create_network_config_kubernetes(config):
"""Create a BIG-IP Network configuration from the Kubernetes config.
Args:
config: Kubernetes BigIP config which contains openshift-sdn defs
"""
f5_network = {}
if 'openshift-sdn' in config:
openshift_sdn = config['openshift-sdn']
f5_network['fdb'] = openshift_sdn
return f5_network
def create_ltm_config_kubernetes(bigip, config):
"""Create a BIG-IP LTM configuration from the Kubernetes configuration.
Args:
config: Kubernetes BigIP config which contains a svc list
"""
configuration = {}
configuration['l7Policies'] = config.get('l7Policies', [])
configuration['monitors'] = config.get('monitors', [])
configuration['pools'] = []
f5_pools = config.get('pools', [])
f5_services = {}
# partitions this script is responsible for:
partitions = frozenset(bigip.get_partitions())
svcs = config['virtualServers']
for svc in svcs:
vs_partition = svc['partition']
# Only handle application if it's partition is one that this script
# is responsible for
if not has_partition(partitions, vs_partition):
continue
f5_service = {}
vs_name = svc['name']
f5_service['balance'] = svc.get('balance', '')
policies = svc.get('policies', [])
profiles = svc.get('profiles', [])
pool = {}
# No address for this port
if (('virtualAddress' not in svc or
'bindAddr' not in svc['virtualAddress']) and
'iapp' not in svc):
log.debug("Creating pool only for %s", vs_name)
elif ('iapp' not in svc and 'bindAddr' not in
svc['virtualAddress']):
continue
f5_service['name'] = vs_name
f5_service['partition'] = vs_partition
if 'iapp' in svc:
f5_service['iapp'] = {'template': svc['iapp'],
'poolMemberTable':
svc['iappPoolMemberTable'],
'variables': svc['iappVariables'],
'options': svc['iappOptions']}
f5_service['iapp']['tables'] = svc.get('iappTables', {})
else:
f5_service['virtual'] = {}
f5_service['pool'] = {}
f5_service['health'] = []
# Parse the SSL profile into partition and name
if 'sslProfile' in svc:
# The sslProfile item can be empty or have either
# 'f5ProfileName' or 'f5ProfileNames', not both.
if 'f5ProfileName' in svc['sslProfile']:
append_ssl_profile(
profiles, svc['sslProfile']['f5ProfileName'])
elif 'f5ProfileNames' in svc['sslProfile']:
for profName in svc['sslProfile']['f5ProfileNames']:
append_ssl_profile(profiles, profName)
# Add appropriate profiles
profile_http = {'partition': 'Common', 'name': 'http'}
profile_tcp = {'partition': 'Common', 'name': 'tcp'}
if str(svc['mode']).lower() == 'http':
if profile_http not in profiles:
profiles.append(profile_http)
elif get_protocol(svc['mode']) == 'tcp':
if profile_tcp not in profiles:
profiles.append(profile_tcp)
if ('virtualAddress' in svc and
'bindAddr' in svc['virtualAddress']):
f5_service['virtual_address'] = \
svc['virtualAddress']['bindAddr']
addr = svc['virtualAddress']['bindAddr']
port = svc['virtualAddress']['port']
destination = None
if isinstance(ipaddress.ip_address(addr),
ipaddress.IPv6Address):
destination = ("/%s/%s.%d" %
(vs_partition, addr, port))
else:
destination = ("/%s/%s:%d" %
(vs_partition, addr, port))
f5_service['virtual'].update({
'enabled': True,
'disabled': False,
'ipProtocol': get_protocol(svc['mode']),
'destination': destination,
'pool': "%s" % (svc['pool']),
'sourceAddressTranslation': {'type': 'automap'},
'profiles': profiles,
'policies': policies
})
f5_services.update({vs_name: f5_service})
configuration['virtualServers'] = f5_services
# FIXME(garyr): CCCL presently expects pools slightly differently than
# we get from the controller, so convert to the expected format here.
for pool in f5_pools:
found_svc = False
new_pool = {}
members = {}
pname = pool['name']
new_pool['name'] = pname
monitors = None
if 'monitor' in pool and pool['monitor']:
monitors = ' and '.join(pool['monitor'])
new_pool['monitor'] = monitors
balance = None
vname = pname.rsplit('_', 1)[0]
if pname in f5_services:
if 'balance' in f5_services[pname]:
balance = f5_services[pname]['balance']
elif vname in f5_services:
if 'balance' in f5_services[vname]:
balance = f5_services[vname]['balance']
new_pool['loadBalancingMode'] = balance
new_pool['partition'] = pool['partition']
if pool['name'] in f5_services or vname in f5_services:
if pool['poolMemberAddrs'] is not None:
found_svc = True
for member in pool['poolMemberAddrs']:
members.update({member: {
'state': 'user-up',
'session': 'user-enabled'
}})
new_pool['members'] = members
configuration['pools'].append(new_pool)
if not found_svc:
log.info(
'Pool "{}" has service "{}", which is empty - '
'configuring 0 pool members.'.format(
pname, pool['serviceName']))
return configuration
if __name__ == "__main__":
main()
| [
2,
48443,
14629,
14,
8800,
14,
24330,
21015,
198,
198,
2,
15069,
1584,
11,
2177,
376,
20,
27862,
11,
3457,
13,
198,
2,
198,
2,
49962,
739,
262,
24843,
13789,
11,
10628,
362,
13,
15,
357,
1169,
366,
34156,
15341,
198,
2,
345,
743,
407,
779,
428,
2393,
2845,
287,
11846,
351,
262,
13789,
13,
198,
2,
921,
743,
7330,
257,
4866,
286,
262,
13789,
379,
198,
2,
198,
2,
220,
220,
220,
220,
2638,
1378,
2503,
13,
43073,
13,
2398,
14,
677,
4541,
14,
43,
2149,
24290,
12,
17,
13,
15,
198,
2,
198,
2,
17486,
2672,
416,
9723,
1099,
393,
4987,
284,
287,
3597,
11,
3788,
198,
2,
9387,
739,
262,
13789,
318,
9387,
319,
281,
366,
1921,
3180,
1,
29809,
1797,
11,
198,
2,
42881,
34764,
11015,
6375,
7102,
49828,
11053,
3963,
15529,
509,
12115,
11,
2035,
4911,
393,
17142,
13,
198,
2,
4091,
262,
13789,
329,
262,
2176,
3303,
15030,
21627,
290,
198,
2,
11247,
739,
262,
13789,
13,
198,
6738,
11593,
37443,
834,
1330,
4112,
62,
11748,
198,
198,
11748,
1822,
29572,
198,
11748,
2779,
2414,
198,
11748,
277,
66,
429,
75,
198,
11748,
12234,
8019,
198,
11748,
20966,
21975,
198,
11748,
33918,
198,
11748,
18931,
198,
11748,
28686,
198,
11748,
28686,
13,
6978,
198,
11748,
25064,
198,
11748,
640,
198,
11748,
4704,
278,
198,
11748,
6737,
198,
11748,
2956,
297,
571,
198,
198,
11748,
12972,
259,
313,
1958,
198,
198,
6738,
19016,
29572,
1330,
19016,
29572,
198,
6738,
277,
20,
62,
535,
565,
13557,
69,
20,
1330,
10130,
12804,
4061,
11,
651,
62,
11235,
4668,
11,
468,
62,
3911,
653,
11,
2604,
62,
43167,
198,
6738,
277,
20,
62,
535,
565,
13,
11321,
1330,
7925,
62,
3911,
653,
62,
392,
62,
3672,
11,
20966,
85,
19,
62,
1462,
62,
20285,
11,
59,
198,
220,
220,
220,
1351,
62,
26069,
62,
41195,
11,
6101,
53,
19,
26227,
12331,
11,
2142,
653,
5376,
12331,
198,
6738,
277,
20,
13,
14261,
541,
1330,
8549,
30016,
198,
198,
6404,
796,
18931,
13,
1136,
11187,
1362,
7,
834,
3672,
834,
8,
198,
41947,
796,
18931,
13,
12124,
25060,
3419,
198,
41947,
13,
2617,
8479,
1436,
7,
198,
220,
220,
220,
18931,
13,
8479,
1436,
7203,
58,
4,
7,
292,
310,
524,
8,
82,
4064,
7,
3672,
8,
82,
4064,
7,
5715,
3672,
8,
82,
60,
4064,
7,
20500,
8,
82,
48774,
198,
15763,
62,
6404,
1362,
796,
18931,
13,
1136,
11187,
1362,
3419,
198,
15763,
62,
6404,
1362,
13,
2860,
25060,
7,
41947,
8,
628,
628,
198,
198,
15763,
62,
6404,
1362,
13,
2860,
22417,
7,
31077,
19580,
22417,
28955,
198,
15763,
62,
6404,
1362,
13,
2860,
22417,
7,
37608,
22417,
28955,
198,
15763,
62,
6404,
1362,
13,
2860,
22417,
7,
9218,
22417,
28955,
198,
198,
7206,
38865,
62,
25294,
62,
2538,
18697,
796,
18931,
13,
10778,
198,
7206,
38865,
62,
5959,
5064,
56,
62,
41358,
23428,
796,
1542,
13,
15,
628,
198,
4871,
509,
23,
82,
18839,
12804,
4061,
7,
18839,
12804,
4061,
2599,
198,
220,
220,
220,
37227,
42,
23,
82,
18839,
12804,
4061,
1398,
13,
628,
220,
220,
220,
2980,
689,
257,
8398,
329,
257,
4403,
4061,
1912,
2402,
262,
6725,
14,
83,
6791,
5257,
198,
220,
220,
220,
416,
2594,
14,
79,
12978,
14,
77,
4147,
287,
12554,
527,
3262,
274,
13,
628,
220,
220,
220,
532,
6550,
2052,
6725,
14,
325,
85,
1063,
416,
4403,
4061,
18398,
198,
220,
220,
220,
532,
7921,
274,
257,
15595,
9652,
290,
5933,
329,
1123,
2139,
2099,
326,
7466,
257,
198,
220,
220,
220,
220,
220,
4403,
4061,
18398,
198,
220,
220,
220,
532,
1114,
1123,
30203,
357,
35943,
11,
10139,
11,
393,
24573,
828,
340,
8075,
257,
5933,
2888,
290,
6673,
198,
220,
220,
220,
220,
220,
262,
2888,
284,
262,
5933,
198,
220,
220,
220,
532,
1002,
262,
598,
468,
257,
24828,
3893,
18289,
17839,
11,
2251,
257,
198,
220,
220,
220,
220,
220,
11188,
1535,
5671,
329,
262,
4403,
4061,
5933,
2888,
198,
220,
220,
220,
532,
29130,
12,
3106,
18239,
318,
973,
416,
31577,
257,
11241,
3706,
705,
83,
16785,
4458,
198,
220,
220,
220,
220,
220,
770,
481,
1249,
1729,
12,
28482,
2985,
284,
779,
262,
7824,
357,
3483,
38,
12,
4061,
1276,
17425,
198,
220,
220,
220,
220,
220,
262,
5504,
351,
1774,
21627,
11,
329,
2035,
1957,
393,
6569,
6284,
737,
628,
220,
220,
220,
943,
14542,
25,
198,
220,
220,
220,
220,
220,
220,
220,
2583,
3672,
25,
6101,
2209,
286,
26746,
12,
4061,
198,
220,
220,
220,
220,
220,
220,
220,
20579,
25,
26746,
12,
4061,
20579,
198,
220,
220,
220,
220,
220,
220,
220,
9206,
25,
26746,
12,
4061,
9206,
198,
220,
220,
220,
220,
220,
220,
220,
43869,
25,
7343,
286,
26746,
12,
4061,
43869,
284,
6687,
198,
220,
220,
220,
37227,
628,
220,
220,
220,
825,
11593,
15003,
834,
7,
944,
11,
2583,
3672,
11,
2493,
11,
20579,
11,
9206,
11,
43869,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
6687,
62,
19199,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
24243,
1096,
262,
509,
23,
82,
18839,
12804,
4061,
2134,
526,
15931,
198,
220,
220,
220,
220,
220,
220,
220,
2208,
7,
42,
23,
82,
18839,
12804,
4061,
11,
2116,
737,
834,
15003,
834,
7,
4774,
3672,
11,
2493,
11,
20579,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
9206,
11,
43869,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
11241,
2625,
83,
16785,
1600,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
6687,
62,
19199,
28,
805,
496,
62,
19199,
8,
628,
220,
220,
220,
825,
4808,
39014,
62,
11250,
7,
944,
11,
4566,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
44836,
262,
8398,
284,
262,
26746,
12,
4061,
13,
628,
220,
220,
220,
220,
220,
220,
220,
943,
14542,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
4566,
25,
26746,
12,
4061,
4566,
8633,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
611,
705,
2528,
76,
6,
287,
4566,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
10130,
12804,
4061,
13557,
39014,
62,
11250,
7,
944,
11,
4566,
17816,
2528,
76,
6,
12962,
198,
220,
220,
220,
220,
220,
220,
220,
611,
705,
27349,
6,
287,
4566,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2116,
13557,
39014,
62,
27349,
62,
11250,
7,
11250,
17816,
27349,
6,
12962,
628,
220,
220,
220,
825,
4808,
39014,
62,
27349,
62,
11250,
7,
944,
11,
4566,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
44836,
262,
3127,
8398,
284,
262,
26746,
12,
4061,
13,
628,
220,
220,
220,
220,
220,
220,
220,
943,
14542,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
4566,
25,
26746,
12,
4061,
3127,
4566,
8633,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
611,
705,
69,
9945,
6,
287,
4566,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2116,
13557,
39014,
62,
27349,
62,
69,
9945,
62,
11250,
7,
11250,
17816,
69,
9945,
6,
12962,
628,
220,
220,
220,
825,
4808,
39014,
62,
27349,
62,
69,
9945,
62,
11250,
7,
944,
11,
277,
9945,
62,
11250,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
44836,
262,
3127,
277,
9945,
8398,
284,
262,
26746,
12,
4061,
13,
628,
220,
220,
220,
220,
220,
220,
220,
943,
14542,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
4566,
25,
26746,
12,
4061,
3127,
277,
9945,
4566,
8633,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
43089,
62,
85,
87,
9620,
62,
3672,
796,
277,
9945,
62,
11250,
17816,
85,
87,
9620,
12,
3672,
20520,
198,
220,
220,
220,
220,
220,
220,
220,
43089,
62,
69,
9945,
62,
22105,
62,
437,
4122,
62,
4868,
796,
277,
9945,
62,
11250,
17816,
85,
87,
9620,
12,
17440,
12,
2419,
20520,
198,
220,
220,
220,
220,
220,
220,
220,
1949,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
277,
20,
62,
69,
9945,
62,
22105,
62,
437,
4122,
62,
4868,
796,
2116,
13,
1136,
62,
69,
9945,
62,
8344,
3669,
7,
42180,
62,
85,
87,
9620,
62,
3672,
8,
628,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2604,
62,
43167,
10786,
42180,
62,
69,
9945,
62,
22105,
62,
4868,
3256,
43089,
62,
69,
9945,
62,
22105,
62,
437,
4122,
62,
4868,
8,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2604,
62,
43167,
10786,
69,
20,
62,
69,
9945,
62,
22105,
62,
4868,
3256,
277,
20,
62,
69,
9945,
62,
22105,
62,
437,
4122,
62,
4868,
8,
628,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1303,
4091,
611,
262,
1351,
286,
4406,
318,
1180,
13,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1303,
1002,
523,
11,
4296,
351,
649,
1351,
13,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
611,
1351,
62,
26069,
62,
41195,
7,
69,
20,
62,
69,
9945,
62,
22105,
62,
437,
4122,
62,
4868,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
43089,
62,
69,
9945,
62,
22105,
62,
437,
4122,
62,
4868,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
69,
9945,
62,
8344,
3669,
62,
19119,
7,
42180,
62,
85,
87,
9620,
62,
3672,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
43089,
62,
69,
9945,
62,
22105,
62,
437,
4122,
62,
4868,
8,
198,
220,
220,
220,
220,
220,
220,
220,
2845,
357,
7841,
653,
5376,
12331,
11,
6101,
53,
19,
26227,
12331,
8,
355,
304,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2604,
13,
18224,
7,
68,
8,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1441,
198,
220,
220,
220,
220,
220,
220,
220,
2845,
35528,
355,
304,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2604,
13,
18224,
10786,
37,
6255,
284,
17425,
262,
376,
11012,
329,
569,
87,
25697,
13275,
705,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
90,
38362,
23884,
4458,
18982,
7,
42180,
62,
85,
87,
9620,
62,
3672,
11,
304,
4008,
628,
220,
220,
220,
825,
651,
62,
85,
87,
9620,
62,
28286,
4954,
7,
944,
11,
410,
87,
9620,
62,
3672,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
3855,
257,
410,
87,
9620,
13275,
2134,
13,
628,
220,
220,
220,
220,
220,
220,
220,
943,
14542,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
410,
87,
9620,
62,
3672,
25,
6530,
286,
262,
410,
87,
9620,
13275,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
18398,
11,
1438,
796,
7925,
62,
3911,
653,
62,
392,
62,
3672,
7,
85,
87,
9620,
62,
3672,
8,
198,
220,
220,
220,
220,
220,
220,
220,
410,
87,
9620,
62,
28286,
4954,
796,
2116,
13,
3262,
13,
69,
9945,
13,
28286,
19423,
13,
28286,
4954,
13,
2220,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
18398,
28,
3911,
653,
11,
1438,
28,
333,
297,
571,
13,
22708,
7,
3672,
4008,
198,
220,
220,
220,
220,
220,
220,
220,
1441,
410,
87,
9620,
62,
28286,
4954,
628,
220,
220,
220,
825,
651,
62,
69,
9945,
62,
8344,
3669,
7,
944,
11,
410,
87,
9620,
62,
3672,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
3855,
257,
1351,
286,
376,
11012,
4406,
357,
3137,
262,
36123,
1351,
8,
329,
262,
410,
87,
9620,
13,
628,
220,
220,
220,
220,
220,
220,
220,
943,
14542,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
410,
87,
9620,
62,
3672,
25,
6530,
286,
262,
410,
87,
9620,
13275,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
36123,
62,
4868,
796,
17635,
198,
220,
220,
220,
220,
220,
220,
220,
410,
87,
9620,
62,
28286,
4954,
796,
2116,
13,
1136,
62,
85,
87,
9620,
62,
28286,
4954,
7,
85,
87,
9620,
62,
3672,
8,
198,
220,
220,
220,
220,
220,
220,
220,
611,
468,
35226,
7,
85,
87,
9620,
62,
28286,
4954,
11,
705,
8344,
3669,
6,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
329,
1700,
287,
410,
87,
9620,
62,
28286,
4954,
13,
8344,
3669,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
36123,
62,
4868,
13,
33295,
7,
22105,
17816,
437,
4122,
6,
12962,
628,
220,
220,
220,
220,
220,
220,
220,
1441,
36123,
62,
4868,
628,
220,
220,
220,
825,
277,
9945,
62,
8344,
3669,
62,
19119,
7,
944,
11,
410,
87,
9620,
62,
3672,
11,
36123,
62,
4868,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
10260,
262,
277,
9945,
4406,
329,
257,
410,
87,
9620,
13275,
13,
628,
220,
220,
220,
220,
220,
220,
220,
943,
14542,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
410,
87,
9620,
62,
3672,
25,
6530,
286,
262,
410,
87,
9620,
13275,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
277,
9945,
62,
22105,
62,
4868,
25,
6101,
2209,
3917,
351,
262,
277,
9945,
1700,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
410,
87,
9620,
62,
28286,
4954,
796,
2116,
13,
1136,
62,
85,
87,
9620,
62,
28286,
4954,
7,
85,
87,
9620,
62,
3672,
8,
198,
220,
220,
220,
220,
220,
220,
220,
1366,
796,
1391,
6,
8344,
3669,
10354,
17635,
92,
198,
220,
220,
220,
220,
220,
220,
220,
4406,
796,
1366,
17816,
8344,
3669,
20520,
198,
220,
220,
220,
220,
220,
220,
220,
329,
36123,
287,
36123,
62,
4868,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1700,
796,
1391,
6,
3672,
10354,
20966,
85,
19,
62,
1462,
62,
20285,
7,
437,
4122,
828,
705,
437,
4122,
10354,
36123,
92,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
4406,
13,
33295,
7,
22105,
8,
198,
220,
220,
220,
220,
220,
220,
220,
2604,
13,
24442,
7203,
4933,
38734,
4406,
329,
410,
87,
9620,
13275,
23884,
25,
23884,
1911,
18982,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
410,
87,
9620,
62,
3672,
11,
1366,
17816,
8344,
3669,
20520,
4008,
198,
220,
220,
220,
220,
220,
220,
220,
410,
87,
9620,
62,
28286,
4954,
13,
19119,
7,
1174,
7890,
8,
628,
628,
198,
198,
4299,
2251,
62,
11250,
62,
74,
18478,
3262,
274,
7,
14261,
541,
11,
4566,
2599,
198,
220,
220,
220,
37227,
16447,
257,
26746,
12,
4061,
8398,
422,
262,
12554,
527,
3262,
274,
8398,
13,
628,
220,
220,
220,
943,
14542,
25,
198,
220,
220,
220,
220,
220,
220,
220,
4566,
25,
12554,
527,
3262,
274,
4403,
4061,
4566,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
2604,
13,
24442,
7203,
8645,
803,
4566,
329,
26746,
12,
4061,
422,
12554,
527,
3262,
274,
1181,
4943,
198,
220,
220,
220,
277,
20,
796,
1391,
6,
2528,
76,
10354,
1391,
5512,
705,
27349,
10354,
1391,
11709,
198,
220,
220,
220,
611,
705,
44813,
29323,
12,
21282,
77,
6,
287,
4566,
25,
198,
220,
220,
220,
220,
220,
220,
220,
277,
20,
17816,
27349,
20520,
796,
2251,
62,
27349,
62,
11250,
62,
74,
18478,
3262,
274,
7,
11250,
8,
198,
220,
220,
220,
611,
705,
37540,
6,
287,
4566,
290,
705,
32844,
7089,
690,
6,
287,
4566,
17816,
37540,
6,
5974,
198,
220,
220,
220,
220,
220,
220,
220,
277,
20,
17816,
2528,
76,
20520,
796,
2251,
62,
2528,
76,
62,
11250,
62,
74,
18478,
3262,
274,
7,
14261,
541,
11,
4566,
17816,
37540,
6,
12962,
628,
220,
220,
220,
1441,
277,
20,
628,
198,
4299,
2251,
62,
27349,
62,
11250,
62,
74,
18478,
3262,
274,
7,
11250,
2599,
198,
220,
220,
220,
37227,
16447,
257,
26746,
12,
4061,
7311,
8398,
422,
262,
12554,
527,
3262,
274,
4566,
13,
628,
220,
220,
220,
943,
14542,
25,
198,
220,
220,
220,
220,
220,
220,
220,
4566,
25,
12554,
527,
3262,
274,
4403,
4061,
4566,
543,
4909,
9808,
29323,
12,
21282,
77,
825,
82,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
277,
20,
62,
27349,
796,
23884,
198,
220,
220,
220,
611,
705,
44813,
29323,
12,
21282,
77,
6,
287,
4566,
25,
198,
220,
220,
220,
220,
220,
220,
220,
9808,
29323,
62,
21282,
77,
796,
4566,
17816,
44813,
29323,
12,
21282,
77,
20520,
198,
220,
220,
220,
220,
220,
220,
220,
277,
20,
62,
27349,
17816,
69,
9945,
20520,
796,
9808,
29323,
62,
21282,
77,
198,
220,
220,
220,
1441,
277,
20,
62,
27349,
628,
198,
198,
4299,
2251,
62,
2528,
76,
62,
11250,
62,
74,
18478,
3262,
274,
7,
14261,
541,
11,
4566,
2599,
198,
220,
220,
220,
37227,
16447,
257,
26746,
12,
4061,
406,
15972,
8398,
422,
262,
12554,
527,
3262,
274,
8398,
13,
628,
220,
220,
220,
943,
14542,
25,
198,
220,
220,
220,
220,
220,
220,
220,
4566,
25,
12554,
527,
3262,
274,
4403,
4061,
4566,
543,
4909,
257,
264,
28435,
1351,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
8398,
796,
23884,
198,
220,
220,
220,
8398,
17816,
75,
22,
47,
4160,
444,
20520,
796,
4566,
13,
1136,
10786,
75,
22,
47,
4160,
444,
3256,
685,
12962,
198,
220,
220,
220,
8398,
17816,
2144,
6742,
20520,
796,
4566,
13,
1136,
10786,
2144,
6742,
3256,
685,
12962,
198,
220,
220,
220,
8398,
17816,
7742,
82,
20520,
796,
17635,
628,
220,
220,
220,
277,
20,
62,
7742,
82,
796,
4566,
13,
1136,
10786,
7742,
82,
3256,
685,
12962,
198,
220,
220,
220,
277,
20,
62,
30416,
796,
23884,
628,
220,
220,
220,
1303,
43869,
428,
4226,
318,
4497,
329,
25,
198,
220,
220,
220,
43869,
796,
8400,
8247,
316,
7,
14261,
541,
13,
1136,
62,
3911,
1756,
28955,
628,
220,
220,
220,
38487,
6359,
796,
4566,
17816,
32844,
7089,
690,
20520,
198,
220,
220,
220,
329,
264,
28435,
287,
38487,
6359,
25,
198,
220,
220,
220,
220,
220,
220,
220,
3691,
62,
3911,
653,
796,
264,
28435,
17816,
3911,
653,
20520,
198,
220,
220,
220,
220,
220,
220,
220,
1303,
5514,
5412,
3586,
611,
340,
338,
18398,
318,
530,
326,
428,
4226,
198,
220,
220,
220,
220,
220,
220,
220,
1303,
318,
4497,
329,
198,
220,
220,
220,
220,
220,
220,
220,
611,
407,
468,
62,
3911,
653,
7,
3911,
1756,
11,
3691,
62,
3911,
653,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2555,
628,
220,
220,
220,
220,
220,
220,
220,
277,
20,
62,
15271,
796,
23884,
198,
220,
220,
220,
220,
220,
220,
220,
3691,
62,
3672,
796,
264,
28435,
17816,
3672,
20520,
198,
220,
220,
220,
220,
220,
220,
220,
277,
20,
62,
15271,
17816,
20427,
20520,
796,
264,
28435,
13,
1136,
10786,
20427,
3256,
10148,
8,
628,
220,
220,
220,
220,
220,
220,
220,
4788,
796,
264,
28435,
13,
1136,
10786,
79,
4160,
444,
3256,
685,
12962,
198,
220,
220,
220,
220,
220,
220,
220,
16545,
796,
264,
28435,
13,
1136,
10786,
5577,
2915,
3256,
685,
12962,
628,
220,
220,
220,
220,
220,
220,
220,
5933,
796,
23884,
628,
220,
220,
220,
220,
220,
220,
220,
1303,
1400,
2209,
329,
428,
2493,
198,
220,
220,
220,
220,
220,
220,
220,
611,
357,
10786,
32844,
20231,
6,
407,
287,
264,
28435,
393,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
21653,
4550,
81,
6,
407,
287,
264,
28435,
17816,
32844,
20231,
6,
12962,
290,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
544,
381,
6,
407,
287,
264,
28435,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2604,
13,
24442,
7203,
32071,
5933,
691,
329,
4064,
82,
1600,
3691,
62,
3672,
8,
198,
220,
220,
220,
220,
220,
220,
220,
1288,
361,
19203,
544,
381,
6,
407,
287,
264,
28435,
290,
705,
21653,
4550,
81,
6,
407,
287,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
264,
28435,
17816,
32844,
20231,
20520,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2555,
628,
220,
220,
220,
220,
220,
220,
220,
277,
20,
62,
15271,
17816,
3672,
20520,
796,
3691,
62,
3672,
198,
220,
220,
220,
220,
220,
220,
220,
277,
20,
62,
15271,
17816,
3911,
653,
20520,
796,
3691,
62,
3911,
653,
628,
220,
220,
220,
220,
220,
220,
220,
611,
705,
544,
381,
6,
287,
264,
28435,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
277,
20,
62,
15271,
17816,
544,
381,
20520,
796,
1391,
6,
28243,
10354,
264,
28435,
17816,
544,
381,
6,
4357,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
7742,
27608,
10962,
10354,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
264,
28435,
17816,
544,
381,
27201,
27608,
10962,
6,
4357,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
25641,
2977,
10354,
264,
28435,
17816,
544,
381,
23907,
2977,
6,
4357,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
25811,
10354,
264,
28435,
17816,
544,
381,
29046,
20520,
92,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
277,
20,
62,
15271,
17816,
544,
381,
6,
7131,
6,
83,
2977,
20520,
796,
264,
28435,
13,
1136,
10786,
544,
381,
51,
2977,
3256,
23884,
8,
198,
220,
220,
220,
220,
220,
220,
220,
2073,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
277,
20,
62,
15271,
17816,
32844,
20520,
796,
23884,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
277,
20,
62,
15271,
17816,
7742,
20520,
796,
23884,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
277,
20,
62,
15271,
17816,
13948,
20520,
796,
17635,
628,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1303,
2547,
325,
262,
25952,
7034,
656,
18398,
290,
1438,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
611,
705,
45163,
37046,
6,
287,
264,
28435,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1303,
383,
264,
6649,
37046,
2378,
460,
307,
6565,
393,
423,
2035,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1303,
705,
69,
20,
37046,
5376,
6,
393,
705,
69,
20,
37046,
36690,
3256,
407,
1111,
13,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
611,
705,
69,
20,
37046,
5376,
6,
287,
264,
28435,
17816,
45163,
37046,
6,
5974,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
24443,
62,
45163,
62,
13317,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
16545,
11,
264,
28435,
17816,
45163,
37046,
6,
7131,
6,
69,
20,
37046,
5376,
6,
12962,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1288,
361,
705,
69,
20,
37046,
36690,
6,
287,
264,
28435,
17816,
45163,
37046,
6,
5974,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
329,
1534,
5376,
287,
264,
28435,
17816,
45163,
37046,
6,
7131,
6,
69,
20,
37046,
36690,
6,
5974,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
24443,
62,
45163,
62,
13317,
7,
5577,
2915,
11,
1534,
5376,
8,
628,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1303,
3060,
5035,
16545,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
7034,
62,
4023,
796,
1391,
6,
3911,
653,
10354,
705,
17227,
3256,
705,
3672,
10354,
705,
4023,
6,
92,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
7034,
62,
83,
13155,
796,
1391,
6,
3911,
653,
10354,
705,
17227,
3256,
705,
3672,
10354,
705,
83,
13155,
6,
92,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
611,
965,
7,
21370,
66,
17816,
14171,
20520,
737,
21037,
3419,
6624,
705,
4023,
10354,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
611,
7034,
62,
4023,
407,
287,
16545,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
16545,
13,
33295,
7,
13317,
62,
4023,
8,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1288,
361,
651,
62,
11235,
4668,
7,
21370,
66,
17816,
14171,
6,
12962,
6624,
705,
83,
13155,
10354,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
611,
7034,
62,
83,
13155,
407,
287,
16545,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
16545,
13,
33295,
7,
13317,
62,
83,
13155,
8,
628,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
611,
19203,
32844,
20231,
6,
287,
264,
28435,
290,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
21653,
4550,
81,
6,
287,
264,
28435,
17816,
32844,
20231,
20520,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
277,
20,
62,
15271,
17816,
32844,
62,
21975,
20520,
796,
3467,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
264,
28435,
17816,
32844,
20231,
6,
7131,
6,
21653,
4550,
81,
20520,
628,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
37817,
796,
264,
28435,
17816,
32844,
20231,
6,
7131,
6,
21653,
4550,
81,
20520,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2493,
796,
264,
28435,
17816,
32844,
20231,
6,
7131,
6,
634,
20520,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
10965,
796,
6045,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
611,
318,
39098,
7,
541,
21975,
13,
541,
62,
21975,
7,
29851,
828,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
20966,
21975,
13,
4061,
85,
21,
20231,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
10965,
796,
5855,
14,
4,
82,
14,
4,
82,
13,
4,
67,
1,
4064,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
357,
14259,
62,
3911,
653,
11,
37817,
11,
2493,
4008,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2073,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
10965,
796,
5855,
14,
4,
82,
14,
4,
82,
25,
4,
67,
1,
4064,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
357,
14259,
62,
3911,
653,
11,
37817,
11,
2493,
4008,
628,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
277,
20,
62,
15271,
17816,
32844,
6,
4083,
19119,
15090,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
25616,
10354,
6407,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
47730,
10354,
10352,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
541,
19703,
4668,
10354,
651,
62,
11235,
4668,
7,
21370,
66,
17816,
14171,
20520,
828,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
16520,
1883,
10354,
10965,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
7742,
10354,
36521,
82,
1,
4064,
357,
21370,
66,
17816,
7742,
20520,
828,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
10459,
20231,
48313,
10354,
1391,
6,
4906,
10354,
705,
2306,
296,
499,
6,
5512,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
5577,
2915,
10354,
16545,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
79,
4160,
444,
10354,
4788,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
32092,
198,
220,
220,
220,
220,
220,
220,
220,
277,
20,
62,
30416,
13,
19119,
15090,
14259,
62,
3672,
25,
277,
20,
62,
15271,
30072,
198,
220,
220,
220,
8398,
17816,
32844,
7089,
690,
20520,
796,
277,
20,
62,
30416,
628,
220,
220,
220,
1303,
44855,
11682,
7,
14849,
81,
2599,
327,
4093,
43,
27606,
13423,
20354,
4622,
10338,
621,
198,
220,
220,
220,
1303,
356,
651,
422,
262,
10444,
11,
523,
10385,
284,
262,
2938,
5794,
994,
13,
198,
220,
220,
220,
329,
5933,
287,
277,
20,
62,
7742,
82,
25,
198,
220,
220,
220,
220,
220,
220,
220,
1043,
62,
21370,
66,
796,
10352,
198,
220,
220,
220,
220,
220,
220,
220,
649,
62,
7742,
796,
23884,
198,
220,
220,
220,
220,
220,
220,
220,
1866,
796,
23884,
198,
220,
220,
220,
220,
220,
220,
220,
279,
3672,
796,
5933,
17816,
3672,
20520,
198,
220,
220,
220,
220,
220,
220,
220,
649,
62,
7742,
17816,
3672,
20520,
796,
279,
3672,
198,
220,
220,
220,
220,
220,
220,
220,
19374,
796,
6045,
198,
220,
220,
220,
220,
220,
220,
220,
611,
705,
41143,
6,
287,
5933,
290,
5933,
17816,
41143,
6,
5974,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
19374,
796,
705,
290,
45302,
22179,
7,
7742,
17816,
41143,
6,
12962,
198,
220,
220,
220,
220,
220,
220,
220,
649,
62,
7742,
17816,
41143,
20520,
796,
19374,
628,
220,
220,
220,
220,
220,
220,
220,
5236,
796,
6045,
198,
220,
220,
220,
220,
220,
220,
220,
410,
3672,
796,
279,
3672,
13,
3808,
489,
270,
10786,
62,
3256,
352,
38381,
15,
60,
198,
220,
220,
220,
220,
220,
220,
220,
611,
279,
3672,
287,
277,
20,
62,
30416,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
611,
705,
20427,
6,
287,
277,
20,
62,
30416,
58,
79,
3672,
5974,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
5236,
796,
277,
20,
62,
30416,
58,
79,
3672,
7131,
6,
20427,
20520,
198,
220,
220,
220,
220,
220,
220,
220,
1288,
361,
410,
3672,
287,
277,
20,
62,
30416,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
611,
705,
20427,
6,
287,
277,
20,
62,
30416,
58,
85,
3672,
5974,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
5236,
796,
277,
20,
62,
30416,
58,
85,
3672,
7131,
6,
20427,
20520,
198,
220,
220,
220,
220,
220,
220,
220,
649,
62,
7742,
17816,
2220,
24597,
5077,
19076,
20520,
796,
5236,
198,
220,
220,
220,
220,
220,
220,
220,
649,
62,
7742,
17816,
3911,
653,
20520,
796,
5933,
17816,
3911,
653,
20520,
198,
220,
220,
220,
220,
220,
220,
220,
611,
5933,
17816,
3672,
20520,
287,
277,
20,
62,
30416,
393,
410,
3672,
287,
277,
20,
62,
30416,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
611,
5933,
17816,
7742,
27608,
4550,
3808,
20520,
318,
407,
6045,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1043,
62,
21370,
66,
796,
6407,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
329,
2888,
287,
5933,
17816,
7742,
27608,
4550,
3808,
6,
5974,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1866,
13,
19119,
15090,
19522,
25,
1391,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
5219,
10354,
705,
7220,
12,
929,
3256,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
29891,
10354,
705,
7220,
12,
25616,
6,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1782,
30072,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
649,
62,
7742,
17816,
30814,
20520,
796,
1866,
198,
220,
220,
220,
220,
220,
220,
220,
8398,
17816,
7742,
82,
6,
4083,
33295,
7,
3605,
62,
7742,
8,
198,
220,
220,
220,
220,
220,
220,
220,
611,
407,
1043,
62,
21370,
66,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2604,
13,
10951,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
27201,
45144,
36786,
468,
2139,
45144,
92,
1600,
543,
318,
6565,
532,
705,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
11250,
870,
657,
5933,
1866,
2637,
13,
18982,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
279,
3672,
11,
5933,
17816,
15271,
5376,
20520,
4008,
628,
220,
220,
220,
1441,
8398,
628,
628,
628,
628,
628,
628,
198,
361,
11593,
3672,
834,
6624,
366,
834,
12417,
834,
1298,
198,
220,
220,
220,
1388,
3419,
198
] | 2.155861 | 6,108 |
"""
Reads in current year's Arctic sea ice extent from Sea Ice Index 3 (NSIDC)
Website : ftp://sidads.colorado.edu/DATASETS/NOAA/G02135/north/daily/data/
Author : Zachary M. Labe
Date : 5 September 2016
"""
### Import modules
import numpy as np
import urllib as UL
import datetime
import matplotlib.pyplot as plt
### Directory and time
directoryfigure = '/home/zlabe/Documents/Projects/IceVarFigs/Figures/'
now = datetime.datetime.now()
currentmn = str(now.month)
currentdy = str(now.day)
currentyr = str(now.year)
currenttime = currentmn + '_' + currentdy + '_' + currentyr
currentdoy = now.timetuple().tm_yday
### Load url
url = 'ftp://sidads.colorado.edu/DATASETS/NOAA/G02135/north/daily/data/' \
'N_seaice_extent_daily_v3.0.csv'
### Read file
raw_data = UL.request.urlopen(url)
dataset = np.genfromtxt(raw_data, skip_header=2,delimiter=',',
usecols=[0,1,2,3,4])
print('\nCompleted: Read sea ice data!')
### Set missing data to nan
dataset[np.where(dataset==-9999)] = np.nan
### Variables
year = dataset[:,0]
month = dataset[:,1]
day = dataset[:,2]
ice = dataset[:,3]
missing = dataset[:,4]
### Call present year
yr2018 = np.where(year == 2018)[0]
ice18 = ice[yr2018]
### Ice Conversion
iceval = ice18 * 1e6
### Printing info
print('\n----- NSIDC Arctic Sea Ice -----')
print('Current Date =', now.strftime("%Y-%m-%d %H:%M"), '\n')
print('SIE Date = %s/%s/%s' % (int(month[-1]),int(day[-1]),int(year[-1])))
print('Current SIE = %s km^2 \n' % (iceval[-1]))
print('1-day change SIE = %s km^2' % (iceval[-1]-iceval[-2]))
print('7-day change SIE = %s km^2 \n' % (iceval[-1]-iceval[-8]))
###########################################################################
###########################################################################
###########################################################################
### Reads in 1981-2010 means
### Load url
url2 = 'ftp://sidads.colorado.edu/DATASETS/NOAA/G02135/north/daily/data/' \
'N_seaice_extent_climatology_1981-2010_v3.0.csv'
### Read file
raw_data2 = UL.request.urlopen(url2)
dataset2 = np.genfromtxt(raw_data2, skip_header=2,delimiter=',',
usecols=[0,1,2,3,4,5,6,7])
### Create variables
doy = dataset2[:,0]
meanice = dataset2[:,1] * 1e6
std = dataset2[:,2]
### Quartiles
quartile10 = dataset2[:,3]
quartile25 = dataset2[:,4]
quartile50 = dataset2[:,5]
quartile75 = dataset2[:,6]
quartile90 = dataset2[:,7]
### Anomalies
currentanom = iceval[-1]-meanice[currentdoy-2]
### Printing info
print('Current anomaly = %s km^2 \n' % currentanom)
### Selected other years for comparisons
yr2007 = np.where(year == 2007)[0]
yr2012 = np.where(year == 2012)[0]
yr2016 = np.where(year == 2016)[0]
sie7 = ice[yr2007]
sie12 = ice[yr2012]
sie16 = ice[yr2016]
###########################################################################
###########################################################################
###########################################################################
### Create plot
plt.rc('text',usetex=True)
plt.rc('font',**{'family':'sans-serif','sans-serif':['Avant Garde']})
plt.rc('savefig',facecolor='black')
plt.rc('axes',edgecolor='white')
plt.rc('xtick',color='white')
plt.rc('ytick',color='white')
plt.rc('axes',labelcolor='white')
plt.rc('axes',facecolor='black')
fig = plt.figure()
ax = plt.subplot(111)
xlabels = [r'Jan',r'Feb',r'Mar',r'Apr',r'May',r'Jun',r'Jul',
r'Aug',r'Sep',r'Oct',r'Nov',r'Dec',r'Jan']
plt.xticks(np.arange(0,361,30.4),xlabels,rotation=0)
ylabels = map(str,np.arange(2,19,2))
plt.yticks(np.arange(2,19,2),ylabels)
plt.ylim([2,18])
plt.xlim([0,360])
strmonth = xlabels[int(currentmn)-1]
asof = strmonth + ' ' + currentdy + ', ' + currentyr
### Adjust axes in time series plots
ax.tick_params('both',length=5.5,width=2,which='major')
adjust_spines(ax, ['left','bottom'])
ax.spines['top'].set_color('none')
ax.spines['right'].set_color('none')
ax.spines['bottom'].set_linewidth(2)
ax.spines['left'].set_linewidth(2)
upper2std = (meanice/1e6)+(std*2)
lower2std = (meanice/1e6)-(std*2)
ax.grid(zorder=1,color='w',alpha=0.2)
plt.plot(ice18,linewidth=1.8,color='aqua',zorder=9,label=r'Current Year (2018)')
plt.plot(doy,upper2std,color='white',alpha=0.7,zorder=3,linewidth=0.1)
plt.plot(doy,lower2std,color='white',alpha=0.7,zorder=4,linewidth=0.1)
plt.plot(doy,quartile10,color='m',alpha=0.7,zorder=3,linewidth=0.4)
plt.plot(doy,quartile25,color='cornflowerblue',alpha=0.7,zorder=4,linewidth=0.4)
plt.plot(doy,quartile75,color='cornflowerblue',alpha=0.7,zorder=4,linewidth=0.4)
plt.plot(doy,quartile90,color='m',alpha=0.7,zorder=3,linewidth=0.4)
ax.fill_between(doy, lower2std, upper2std, facecolor='white', alpha=0.35,
label=r'$\pm$2 standard deviations',zorder=2)
plt.plot(doy,quartile50,color='gold',alpha=1,zorder=3,linewidth=2,
label=r'Median (1981-2010)')
ax.fill_between(doy, quartile90, quartile75, facecolor='m', alpha=0.55,
label=r'10-90th percentiles',zorder=2)
ax.fill_between(doy, quartile10, quartile25, facecolor='m', alpha=0.55,
zorder=2)
ax.fill_between(doy, quartile25, quartile50, facecolor='cornflowerblue', alpha=0.6,
zorder=2)
ax.fill_between(doy, quartile50, quartile75, facecolor='cornflowerblue', alpha=0.6,
label=r'25-75th percentiles',zorder=2)
plt.scatter(doy[currentdoy-3],ice[-1],s=10,color='aqua',zorder=9)
plt.ylabel(r'\textbf{Extent} [$\times$10$^{6}$ km$^2$]',fontsize=15,
color='darkgrey')
le = plt.legend(shadow=False,fontsize=6,loc='upper left',
bbox_to_anchor=(0.473, 1.011),fancybox=True,ncol=2)
for text in le.get_texts():
text.set_color('w')
plt.title(r'\textbf{ARCTIC SEA ICE}',
fontsize=21,color='darkgrey')
plt.text(doy[currentdoy]-5,ice[-1]-1.35,r'\textbf{2018}',
fontsize=13.5,rotation='horizontal',ha='left',color='aqua')
plt.text(0.5,3.1,r'\textbf{DATA:} National Snow \& Ice Data Center, Boulder CO',
fontsize=5.5,rotation='horizontal',ha='left',color='darkgrey')
plt.text(0.5,2.6,r'\textbf{SOURCE:} ftp://sidads.colorado.edu/DATASETS/NOAA/G02135/',
fontsize=5.5,rotation='horizontal',ha='left',color='darkgrey')
plt.text(0.5,2.1,r'\textbf{GRAPHIC:} Zachary Labe (@ZLabe)',
fontsize=5.5,rotation='horizontal',ha='left',color='darkgrey')
fig.subplots_adjust(top=0.91)
### Save figure
plt.savefig(directoryfigure + 'nsidc_sie_quartiles_currentyear.png',dpi=300) | [
37811,
198,
5569,
82,
287,
1459,
614,
338,
15723,
5417,
4771,
6287,
422,
6896,
6663,
12901,
513,
357,
8035,
2389,
34,
8,
198,
198,
33420,
220,
220,
1058,
10117,
79,
1378,
30255,
5643,
13,
8043,
4533,
13,
15532,
14,
35,
1404,
1921,
32716,
14,
15285,
3838,
14,
38,
2999,
17059,
14,
43588,
14,
29468,
14,
7890,
14,
198,
13838,
220,
220,
220,
1058,
18825,
560,
337,
13,
3498,
68,
198,
10430,
220,
220,
220,
220,
220,
1058,
642,
2693,
1584,
198,
37811,
198,
198,
21017,
17267,
13103,
198,
11748,
299,
32152,
355,
45941,
198,
11748,
2956,
297,
571,
355,
44475,
198,
11748,
4818,
8079,
198,
11748,
2603,
29487,
8019,
13,
9078,
29487,
355,
458,
83,
198,
198,
21017,
27387,
290,
640,
198,
34945,
26875,
796,
31051,
11195,
14,
48274,
11231,
14,
38354,
14,
16775,
82,
14,
23709,
19852,
37,
9235,
14,
14989,
942,
14,
6,
220,
198,
2197,
796,
4818,
8079,
13,
19608,
8079,
13,
2197,
3419,
198,
14421,
10295,
796,
965,
7,
2197,
13,
8424,
8,
198,
14421,
9892,
796,
965,
7,
2197,
13,
820,
8,
198,
14421,
2417,
796,
965,
7,
2197,
13,
1941,
8,
198,
14421,
2435,
796,
1459,
10295,
1343,
705,
62,
6,
1343,
1459,
9892,
1343,
705,
62,
6,
1343,
1459,
2417,
198,
14421,
67,
726,
796,
783,
13,
16514,
316,
29291,
22446,
17209,
62,
88,
820,
198,
198,
21017,
8778,
19016,
198,
6371,
796,
705,
701,
79,
1378,
30255,
5643,
13,
8043,
4533,
13,
15532,
14,
35,
1404,
1921,
32716,
14,
15285,
3838,
14,
38,
2999,
17059,
14,
43588,
14,
29468,
14,
7890,
14,
6,
3467,
198,
220,
220,
220,
705,
45,
62,
8583,
501,
62,
2302,
298,
62,
29468,
62,
85,
18,
13,
15,
13,
40664,
6,
198,
198,
21017,
4149,
2393,
198,
1831,
62,
7890,
796,
44475,
13,
25927,
13,
6371,
9654,
7,
6371,
8,
198,
19608,
292,
316,
796,
45941,
13,
5235,
6738,
14116,
7,
1831,
62,
7890,
11,
14267,
62,
25677,
28,
17,
11,
12381,
320,
2676,
28,
3256,
3256,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
779,
4033,
82,
41888,
15,
11,
16,
11,
17,
11,
18,
11,
19,
12962,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
198,
4798,
10786,
59,
77,
43768,
25,
4149,
5417,
4771,
1366,
0,
11537,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
198,
198,
21017,
5345,
4814,
1366,
284,
15709,
198,
19608,
292,
316,
58,
37659,
13,
3003,
7,
19608,
292,
316,
855,
12,
24214,
15437,
796,
45941,
13,
12647,
198,
198,
21017,
15965,
2977,
198,
1941,
796,
27039,
58,
45299,
15,
60,
198,
8424,
796,
27039,
58,
45299,
16,
60,
198,
820,
796,
27039,
58,
45299,
17,
60,
198,
501,
796,
27039,
58,
45299,
18,
60,
198,
45688,
796,
27039,
58,
45299,
19,
60,
198,
198,
21017,
4889,
1944,
614,
198,
2417,
7908,
796,
45941,
13,
3003,
7,
1941,
6624,
2864,
38381,
15,
60,
198,
501,
1507,
796,
4771,
58,
2417,
7908,
60,
198,
198,
21017,
6663,
44101,
198,
501,
2100,
796,
4771,
1507,
1635,
352,
68,
21,
198,
198,
21017,
44118,
7508,
198,
4798,
10786,
59,
77,
30934,
10896,
2389,
34,
15723,
6896,
6663,
37404,
11537,
198,
4798,
10786,
11297,
7536,
796,
3256,
783,
13,
2536,
31387,
7203,
4,
56,
12,
4,
76,
12,
4,
67,
4064,
39,
25,
4,
44,
12340,
705,
59,
77,
11537,
198,
198,
4798,
10786,
50,
10008,
7536,
220,
220,
220,
796,
4064,
82,
14,
4,
82,
14,
4,
82,
6,
4064,
357,
600,
7,
8424,
58,
12,
16,
46570,
600,
7,
820,
58,
12,
16,
46570,
600,
7,
1941,
58,
12,
16,
60,
22305,
198,
4798,
10786,
11297,
311,
10008,
796,
4064,
82,
10571,
61,
17,
3467,
77,
6,
4064,
357,
501,
2100,
58,
12,
16,
60,
4008,
198,
198,
4798,
10786,
16,
12,
820,
1487,
311,
10008,
796,
4064,
82,
10571,
61,
17,
6,
4064,
357,
501,
2100,
58,
12,
16,
45297,
501,
2100,
58,
12,
17,
60,
4008,
198,
4798,
10786,
22,
12,
820,
1487,
311,
10008,
796,
4064,
82,
10571,
61,
17,
3467,
77,
6,
4064,
357,
501,
2100,
58,
12,
16,
45297,
501,
2100,
58,
12,
23,
60,
4008,
198,
220,
220,
220,
220,
198,
29113,
29113,
7804,
21017,
198,
29113,
29113,
7804,
21017,
198,
29113,
29113,
7804,
21017,
198,
21017,
4149,
82,
287,
14745,
12,
10333,
1724,
198,
21017,
8778,
19016,
198,
6371,
17,
796,
705,
701,
79,
1378,
30255,
5643,
13,
8043,
4533,
13,
15532,
14,
35,
1404,
1921,
32716,
14,
15285,
3838,
14,
38,
2999,
17059,
14,
43588,
14,
29468,
14,
7890,
14,
6,
3467,
198,
220,
220,
220,
220,
220,
220,
705,
45,
62,
8583,
501,
62,
2302,
298,
62,
565,
320,
265,
1435,
62,
35411,
12,
10333,
62,
85,
18,
13,
15,
13,
40664,
6,
198,
198,
21017,
4149,
2393,
198,
1831,
62,
7890,
17,
796,
44475,
13,
25927,
13,
6371,
9654,
7,
6371,
17,
8,
198,
19608,
292,
316,
17,
796,
45941,
13,
5235,
6738,
14116,
7,
1831,
62,
7890,
17,
11,
14267,
62,
25677,
28,
17,
11,
12381,
320,
2676,
28,
3256,
3256,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
779,
4033,
82,
41888,
15,
11,
16,
11,
17,
11,
18,
11,
19,
11,
20,
11,
21,
11,
22,
12962,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
198,
21017,
13610,
9633,
198,
67,
726,
796,
27039,
17,
58,
45299,
15,
60,
198,
32604,
501,
796,
27039,
17,
58,
45299,
16,
60,
1635,
352,
68,
21,
198,
19282,
796,
27039,
17,
58,
45299,
17,
60,
198,
198,
21017,
48748,
2915,
198,
36008,
576,
940,
796,
27039,
17,
58,
45299,
18,
60,
198,
36008,
576,
1495,
796,
27039,
17,
58,
45299,
19,
60,
198,
36008,
576,
1120,
796,
27039,
17,
58,
45299,
20,
60,
198,
36008,
576,
2425,
796,
27039,
17,
58,
45299,
21,
60,
198,
36008,
576,
3829,
796,
27039,
17,
58,
45299,
22,
60,
198,
198,
21017,
1052,
18048,
444,
198,
14421,
272,
296,
796,
4771,
2100,
58,
12,
16,
45297,
32604,
501,
58,
14421,
67,
726,
12,
17,
60,
198,
198,
21017,
44118,
7508,
198,
4798,
10786,
11297,
32172,
796,
4064,
82,
10571,
61,
17,
3467,
77,
6,
4064,
1459,
272,
296,
8,
220,
220,
220,
198,
198,
21017,
41344,
584,
812,
329,
17909,
198,
2417,
12726,
796,
45941,
13,
3003,
7,
1941,
6624,
4343,
38381,
15,
60,
198,
2417,
6999,
796,
45941,
13,
3003,
7,
1941,
6624,
2321,
38381,
15,
60,
198,
2417,
5304,
796,
45941,
13,
3003,
7,
1941,
6624,
1584,
38381,
15,
60,
198,
198,
44524,
22,
796,
4771,
58,
2417,
12726,
60,
198,
44524,
1065,
796,
4771,
58,
2417,
6999,
60,
198,
44524,
1433,
796,
4771,
58,
2417,
5304,
60,
198,
198,
29113,
29113,
7804,
21017,
198,
29113,
29113,
7804,
21017,
198,
29113,
29113,
7804,
21017,
198,
21017,
13610,
7110,
198,
489,
83,
13,
6015,
10786,
5239,
3256,
385,
316,
1069,
28,
17821,
8,
198,
489,
83,
13,
6015,
10786,
10331,
3256,
1174,
90,
6,
17989,
10354,
6,
82,
504,
12,
2655,
361,
41707,
82,
504,
12,
2655,
361,
10354,
17816,
32,
4520,
12790,
68,
20520,
30072,
220,
198,
489,
83,
13,
6015,
10786,
21928,
5647,
3256,
2550,
8043,
11639,
13424,
11537,
198,
489,
83,
13,
6015,
10786,
897,
274,
3256,
14907,
8043,
11639,
11186,
11537,
198,
489,
83,
13,
6015,
10786,
742,
624,
3256,
8043,
11639,
11186,
11537,
198,
489,
83,
13,
6015,
10786,
20760,
624,
3256,
8043,
11639,
11186,
11537,
198,
489,
83,
13,
6015,
10786,
897,
274,
3256,
18242,
8043,
11639,
11186,
11537,
198,
489,
83,
13,
6015,
10786,
897,
274,
3256,
2550,
8043,
11639,
13424,
11537,
198,
198,
5647,
796,
458,
83,
13,
26875,
3419,
198,
897,
796,
458,
83,
13,
7266,
29487,
7,
16243,
8,
198,
198,
87,
23912,
1424,
796,
685,
81,
6,
12128,
3256,
81,
6,
15146,
3256,
81,
6,
7676,
3256,
81,
6,
13680,
3256,
81,
6,
6747,
3256,
81,
6,
22396,
3256,
81,
6,
16980,
3256,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
374,
6,
12512,
3256,
81,
6,
19117,
3256,
81,
6,
12349,
3256,
81,
6,
20795,
3256,
81,
6,
10707,
3256,
81,
6,
12128,
20520,
198,
489,
83,
13,
742,
3378,
7,
37659,
13,
283,
858,
7,
15,
11,
35195,
11,
1270,
13,
19,
828,
87,
23912,
1424,
11,
10599,
341,
28,
15,
8,
198,
2645,
397,
1424,
796,
3975,
7,
2536,
11,
37659,
13,
283,
858,
7,
17,
11,
1129,
11,
17,
4008,
198,
489,
83,
13,
20760,
3378,
7,
37659,
13,
283,
858,
7,
17,
11,
1129,
11,
17,
828,
2645,
397,
1424,
8,
198,
489,
83,
13,
88,
2475,
26933,
17,
11,
1507,
12962,
198,
489,
83,
13,
87,
2475,
26933,
15,
11,
15277,
12962,
198,
198,
2536,
8424,
796,
2124,
23912,
1424,
58,
600,
7,
14421,
10295,
13219,
16,
60,
198,
292,
1659,
796,
965,
8424,
1343,
705,
705,
1343,
1459,
9892,
1343,
46083,
705,
1343,
1459,
2417,
198,
198,
21017,
20292,
34197,
287,
640,
2168,
21528,
220,
198,
220,
220,
220,
220,
220,
220,
220,
220,
198,
897,
13,
42298,
62,
37266,
10786,
16885,
3256,
13664,
28,
20,
13,
20,
11,
10394,
28,
17,
11,
4758,
11639,
22478,
11537,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
198,
23032,
62,
2777,
1127,
7,
897,
11,
37250,
9464,
41707,
22487,
6,
12962,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
198,
897,
13,
2777,
1127,
17816,
4852,
6,
4083,
2617,
62,
8043,
10786,
23108,
11537,
198,
897,
13,
2777,
1127,
17816,
3506,
6,
4083,
2617,
62,
8043,
10786,
23108,
11537,
220,
220,
198,
897,
13,
2777,
1127,
17816,
22487,
6,
4083,
2617,
62,
2815,
413,
5649,
7,
17,
8,
198,
897,
13,
2777,
1127,
17816,
9464,
6,
4083,
2617,
62,
2815,
413,
5649,
7,
17,
8,
198,
198,
45828,
17,
19282,
796,
357,
32604,
501,
14,
16,
68,
21,
8,
33747,
19282,
9,
17,
8,
198,
21037,
17,
19282,
796,
357,
32604,
501,
14,
16,
68,
21,
13219,
7,
19282,
9,
17,
8,
198,
198,
897,
13,
25928,
7,
89,
2875,
28,
16,
11,
8043,
11639,
86,
3256,
26591,
28,
15,
13,
17,
8,
198,
198,
489,
83,
13,
29487,
7,
501,
1507,
11,
2815,
413,
5649,
28,
16,
13,
23,
11,
8043,
11639,
36129,
64,
3256,
89,
2875,
28,
24,
11,
18242,
28,
81,
6,
11297,
6280,
357,
7908,
8,
11537,
220,
198,
198,
489,
83,
13,
29487,
7,
67,
726,
11,
45828,
17,
19282,
11,
8043,
11639,
11186,
3256,
26591,
28,
15,
13,
22,
11,
89,
2875,
28,
18,
11,
2815,
413,
5649,
28,
15,
13,
16,
8,
198,
489,
83,
13,
29487,
7,
67,
726,
11,
21037,
17,
19282,
11,
8043,
11639,
11186,
3256,
26591,
28,
15,
13,
22,
11,
89,
2875,
28,
19,
11,
2815,
413,
5649,
28,
15,
13,
16,
8,
198,
489,
83,
13,
29487,
7,
67,
726,
11,
36008,
576,
940,
11,
8043,
11639,
76,
3256,
26591,
28,
15,
13,
22,
11,
89,
2875,
28,
18,
11,
2815,
413,
5649,
28,
15,
13,
19,
8,
198,
489,
83,
13,
29487,
7,
67,
726,
11,
36008,
576,
1495,
11,
8043,
11639,
20772,
25547,
17585,
3256,
26591,
28,
15,
13,
22,
11,
89,
2875,
28,
19,
11,
2815,
413,
5649,
28,
15,
13,
19,
8,
198,
489,
83,
13,
29487,
7,
67,
726,
11,
36008,
576,
2425,
11,
8043,
11639,
20772,
25547,
17585,
3256,
26591,
28,
15,
13,
22,
11,
89,
2875,
28,
19,
11,
2815,
413,
5649,
28,
15,
13,
19,
8,
198,
489,
83,
13,
29487,
7,
67,
726,
11,
36008,
576,
3829,
11,
8043,
11639,
76,
3256,
26591,
28,
15,
13,
22,
11,
89,
2875,
28,
18,
11,
2815,
413,
5649,
28,
15,
13,
19,
8,
198,
198,
897,
13,
20797,
62,
23395,
7,
67,
726,
11,
2793,
17,
19282,
11,
6727,
17,
19282,
11,
1986,
8043,
11639,
11186,
3256,
17130,
28,
15,
13,
2327,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
6167,
28,
81,
6,
3,
59,
4426,
3,
17,
3210,
47060,
3256,
89,
2875,
28,
17,
8,
198,
489,
83,
13,
29487,
7,
67,
726,
11,
36008,
576,
1120,
11,
8043,
11639,
24267,
3256,
26591,
28,
16,
11,
89,
2875,
28,
18,
11,
2815,
413,
5649,
28,
17,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
6167,
28,
81,
6,
9921,
666,
357,
35411,
12,
10333,
8,
11537,
220,
220,
220,
220,
220,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
198,
897,
13,
20797,
62,
23395,
7,
67,
726,
11,
28176,
576,
3829,
11,
28176,
576,
2425,
11,
1986,
8043,
11639,
76,
3256,
17130,
28,
15,
13,
2816,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
6167,
28,
81,
6,
940,
12,
3829,
400,
1411,
2915,
3256,
89,
2875,
28,
17,
8,
198,
897,
13,
20797,
62,
23395,
7,
67,
726,
11,
28176,
576,
940,
11,
28176,
576,
1495,
11,
1986,
8043,
11639,
76,
3256,
17130,
28,
15,
13,
2816,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1976,
2875,
28,
17,
8,
220,
220,
198,
897,
13,
20797,
62,
23395,
7,
67,
726,
11,
28176,
576,
1495,
11,
28176,
576,
1120,
11,
1986,
8043,
11639,
20772,
25547,
17585,
3256,
17130,
28,
15,
13,
21,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1976,
2875,
28,
17,
8,
220,
220,
198,
897,
13,
20797,
62,
23395,
7,
67,
726,
11,
28176,
576,
1120,
11,
28176,
576,
2425,
11,
1986,
8043,
11639,
20772,
25547,
17585,
3256,
17130,
28,
15,
13,
21,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
6167,
28,
81,
6,
1495,
12,
2425,
400,
1411,
2915,
3256,
89,
2875,
28,
17,
8,
220,
220,
220,
220,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
198,
489,
83,
13,
1416,
1436,
7,
67,
726,
58,
14421,
67,
726,
12,
18,
4357,
501,
58,
12,
16,
4357,
82,
28,
940,
11,
8043,
11639,
36129,
64,
3256,
89,
2875,
28,
24,
8,
198,
198,
489,
83,
13,
2645,
9608,
7,
81,
6,
59,
5239,
19881,
90,
11627,
298,
92,
685,
3,
59,
22355,
3,
940,
3,
36796,
21,
92,
3,
10571,
3,
61,
17,
3,
60,
3256,
10331,
7857,
28,
1314,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
3124,
11639,
21953,
49502,
11537,
198,
293,
796,
458,
83,
13,
1455,
437,
7,
19106,
28,
25101,
11,
10331,
7857,
28,
21,
11,
17946,
11639,
45828,
1364,
3256,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
275,
3524,
62,
1462,
62,
3702,
273,
16193,
15,
13,
37804,
11,
352,
13,
28555,
828,
69,
3883,
3524,
28,
17821,
11,
77,
4033,
28,
17,
8,
198,
1640,
2420,
287,
443,
13,
1136,
62,
5239,
82,
33529,
198,
220,
220,
220,
2420,
13,
2617,
62,
8043,
10786,
86,
11537,
220,
220,
220,
198,
489,
83,
13,
7839,
7,
81,
6,
59,
5239,
19881,
90,
1503,
4177,
2149,
41067,
23358,
92,
3256,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
10369,
7857,
28,
2481,
11,
8043,
11639,
21953,
49502,
11537,
220,
220,
220,
220,
220,
220,
220,
220,
220,
198,
198,
489,
83,
13,
5239,
7,
67,
726,
58,
14421,
67,
726,
45297,
20,
11,
501,
58,
12,
16,
45297,
16,
13,
2327,
11,
81,
6,
59,
5239,
19881,
90,
7908,
92,
3256,
198,
220,
220,
220,
220,
220,
220,
220,
220,
10369,
7857,
28,
1485,
13,
20,
11,
10599,
341,
11639,
17899,
38342,
3256,
3099,
11639,
9464,
3256,
8043,
11639,
36129,
64,
11537,
198,
489,
83,
13,
5239,
7,
15,
13,
20,
11,
18,
13,
16,
11,
81,
6,
59,
5239,
19881,
90,
26947,
25,
92,
2351,
7967,
3467,
5,
6663,
6060,
3337,
11,
27437,
7375,
3256,
198,
220,
220,
220,
220,
220,
220,
220,
220,
10369,
7857,
28,
20,
13,
20,
11,
10599,
341,
11639,
17899,
38342,
3256,
3099,
11639,
9464,
3256,
8043,
11639,
21953,
49502,
11537,
198,
489,
83,
13,
5239,
7,
15,
13,
20,
11,
17,
13,
21,
11,
81,
6,
59,
5239,
19881,
90,
47690,
25,
92,
10117,
79,
1378,
30255,
5643,
13,
8043,
4533,
13,
15532,
14,
35,
1404,
1921,
32716,
14,
15285,
3838,
14,
38,
2999,
17059,
14,
3256,
198,
220,
220,
220,
220,
220,
220,
220,
220,
10369,
7857,
28,
20,
13,
20,
11,
10599,
341,
11639,
17899,
38342,
3256,
3099,
11639,
9464,
3256,
8043,
11639,
21953,
49502,
11537,
198,
489,
83,
13,
5239,
7,
15,
13,
20,
11,
17,
13,
16,
11,
81,
6,
59,
5239,
19881,
90,
10761,
31300,
2149,
25,
92,
18825,
560,
3498,
68,
4275,
57,
43,
11231,
8,
3256,
198,
220,
220,
220,
220,
220,
220,
220,
220,
10369,
7857,
28,
20,
13,
20,
11,
10599,
341,
11639,
17899,
38342,
3256,
3099,
11639,
9464,
3256,
8043,
11639,
21953,
49502,
11537,
220,
220,
220,
220,
198,
5647,
13,
7266,
489,
1747,
62,
23032,
7,
4852,
28,
15,
13,
6420,
8,
198,
198,
21017,
12793,
3785,
220,
220,
220,
220,
220,
220,
220,
220,
198,
489,
83,
13,
21928,
5647,
7,
34945,
26875,
1343,
705,
5907,
312,
66,
62,
44524,
62,
36008,
2915,
62,
14421,
1941,
13,
11134,
3256,
67,
14415,
28,
6200,
8,
220,
220,
220,
220,
220
] | 2.248232 | 2,969 |
import collections
import nltk
import tensorflow as tf
import numpy as np
from tensorflow.contrib import rnn
from utils import chunks
import json
import os
import shutil
def word_indexing(words):
"""
:param words: a string
:return: a vocabulary dictionary {word1: 1, word2: 2, ...} and
its reveres {1: word1, 2: word2, ...}
"""
vocab = collections.Counter(words).most_common()
vocab_dict = dict()
for word, _ in vocab:
vocab_dict[word] = len(vocab_dict)
rev_vocab_dict = dict(zip(vocab_dict.values(), vocab_dict.keys()))
return vocab_dict, rev_vocab_dict
def data_sampling(content, window):
"""
:param content: Text vocab as string
:param window: Window size for sampling, the window moves on the text vocab to build the samples
:return: Training vocab includes (input, label) pair and number of classes
If the window includes "cats like to chase mice" X is "cats like to chase" and y is "mice"
"""
words = nltk.tokenize.word_tokenize(content)
vocab_dict, rev_vocab_dict = word_indexing(words)
with open('vocab/rev_vocab.json', 'w') as fp:
json.dump(rev_vocab_dict, fp)
with open('vocab/vocab.json', 'w') as fp:
json.dump(vocab_dict, fp)
training_data = []
samples = chunks(words, window, truncate=True)
for sample in samples:
training_data.append(([vocab_dict[z] for z in sample[:-1]], vocab_dict[sample[-1:][0]]))
return training_data, len(words)
with open("data.txt") as f:
content = f.read()
window = 6
time_steps = window - 1
num_hidden = 512
num_input = 1
batch_size = 100
iteration = 250
training_data, num_classes = data_sampling(content, window=window)
# Build the Batches:
batches = chunks(training_data, batch_size)
# RNN output node weights and biases
weights = {
'out': tf.Variable(tf.random_normal([num_hidden, num_classes]))
}
biases = {
'out': tf.Variable(tf.random_normal([num_classes]))
}
# tf graph input
X = tf.placeholder("float", [None, time_steps, num_input], name='X')
Y = tf.placeholder("float", [None, num_classes])
logits = RNN(X, weights, biases)
y_pred = tf.argmax(tf.nn.softmax(logits), 1, name='y_pred')
y_true = tf.argmax(Y, 1)
# Loss and optimizer
loss_op = tf.reduce_mean(tf.nn.softmax_cross_entropy_with_logits_v2(logits=logits, labels=Y))
train_op = tf.train.RMSPropOptimizer(learning_rate=0.0001).minimize(loss_op)
correct_pred = tf.equal(y_pred, y_true)
accuracy = tf.reduce_mean(tf.cast(correct_pred, tf.float32))
# Initialize the variables with default values
init = tf.global_variables_initializer()
saver = tf.train.Saver()
with tf.Session() as sess:
# Run the initializer
sess.run(init)
for i in range(0, iteration):
loss_list = []
acc_list = []
for batch in batches:
X_batch = [x[0] for x in batch]
Y_batch = [x[1] for x in batch]
Y_batch_encoded = []
for x in Y_batch:
one_hot_vector = np.zeros([num_classes], dtype=float)
one_hot_vector[x] = 1.0
Y_batch_encoded.append(one_hot_vector)
Y_batch_encoded = np.vstack(Y_batch_encoded)
X_batch = np.vstack(X_batch)
X_batch = X_batch.reshape(len(batch), time_steps, num_input)
Y_batch_encoded = Y_batch_encoded.reshape(len(batch), num_classes)
_, acc, loss, onehot_pred = sess.run(
[train_op, accuracy, loss_op, logits], feed_dict={X: X_batch, Y: Y_batch_encoded})
loss_list.append(loss)
acc_list.append(acc)
loss = sum(loss_list)/len(loss_list)
acc = sum(acc_list)/len(acc_list)
print("Iteration " + str(i) + ", Loss= " + "{:.4f}".format(loss)
+ ", Training Accuracy= " + "{:.2f}".format(acc * 100))
inputs = {
"X": X,
}
outputs = {"y_pred": y_pred}
if os.path.isdir("model"):
shutil.rmtree('model')
tf.saved_model.simple_save(
sess, 'model/', inputs, outputs
) | [
11748,
17268,
198,
11748,
299,
2528,
74,
198,
11748,
11192,
273,
11125,
355,
48700,
198,
11748,
299,
32152,
355,
45941,
198,
6738,
11192,
273,
11125,
13,
3642,
822,
1330,
374,
20471,
198,
6738,
3384,
4487,
1330,
22716,
198,
11748,
33918,
198,
11748,
28686,
198,
11748,
4423,
346,
628,
198,
4299,
1573,
62,
9630,
278,
7,
10879,
2599,
198,
220,
220,
220,
37227,
628,
220,
220,
220,
1058,
17143,
2456,
25,
257,
4731,
198,
220,
220,
220,
1058,
7783,
25,
257,
25818,
22155,
1391,
4775,
16,
25,
352,
11,
1573,
17,
25,
362,
11,
220,
2644,
92,
290,
198,
220,
220,
220,
220,
663,
2697,
411,
1391,
16,
25,
1573,
16,
11,
362,
25,
1573,
17,
11,
2644,
92,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
12776,
397,
796,
17268,
13,
31694,
7,
10879,
737,
1712,
62,
11321,
3419,
198,
220,
220,
220,
12776,
397,
62,
11600,
796,
8633,
3419,
198,
220,
220,
220,
329,
1573,
11,
4808,
287,
12776,
397,
25,
198,
220,
220,
220,
220,
220,
220,
220,
12776,
397,
62,
11600,
58,
4775,
60,
796,
18896,
7,
18893,
397,
62,
11600,
8,
198,
220,
220,
220,
2710,
62,
18893,
397,
62,
11600,
796,
8633,
7,
13344,
7,
18893,
397,
62,
11600,
13,
27160,
22784,
12776,
397,
62,
11600,
13,
13083,
3419,
4008,
198,
220,
220,
220,
1441,
12776,
397,
62,
11600,
11,
2710,
62,
18893,
397,
62,
11600,
628,
198,
4299,
1366,
62,
37687,
11347,
7,
11299,
11,
4324,
2599,
198,
220,
220,
220,
37227,
628,
220,
220,
220,
1058,
17143,
2695,
25,
8255,
12776,
397,
355,
4731,
198,
220,
220,
220,
1058,
17143,
4324,
25,
26580,
2546,
329,
19232,
11,
262,
4324,
6100,
319,
262,
2420,
12776,
397,
284,
1382,
262,
8405,
198,
220,
220,
220,
1058,
7783,
25,
13614,
12776,
397,
3407,
357,
15414,
11,
6167,
8,
5166,
290,
1271,
286,
6097,
628,
220,
220,
220,
1002,
262,
4324,
3407,
366,
24619,
588,
284,
15505,
10693,
1,
1395,
318,
366,
24619,
588,
284,
15505,
1,
290,
331,
318,
366,
76,
501,
1,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
2456,
796,
299,
2528,
74,
13,
30001,
1096,
13,
4775,
62,
30001,
1096,
7,
11299,
8,
198,
220,
220,
220,
12776,
397,
62,
11600,
11,
2710,
62,
18893,
397,
62,
11600,
796,
1573,
62,
9630,
278,
7,
10879,
8,
198,
220,
220,
220,
351,
1280,
10786,
18893,
397,
14,
18218,
62,
18893,
397,
13,
17752,
3256,
705,
86,
11537,
355,
277,
79,
25,
198,
220,
220,
220,
220,
220,
220,
220,
33918,
13,
39455,
7,
18218,
62,
18893,
397,
62,
11600,
11,
277,
79,
8,
198,
220,
220,
220,
351,
1280,
10786,
18893,
397,
14,
18893,
397,
13,
17752,
3256,
705,
86,
11537,
355,
277,
79,
25,
198,
220,
220,
220,
220,
220,
220,
220,
33918,
13,
39455,
7,
18893,
397,
62,
11600,
11,
277,
79,
8,
198,
220,
220,
220,
3047,
62,
7890,
796,
17635,
198,
220,
220,
220,
8405,
796,
22716,
7,
10879,
11,
4324,
11,
40122,
378,
28,
17821,
8,
198,
220,
220,
220,
329,
6291,
287,
8405,
25,
198,
220,
220,
220,
220,
220,
220,
220,
3047,
62,
7890,
13,
33295,
19510,
58,
18893,
397,
62,
11600,
58,
89,
60,
329,
1976,
287,
6291,
58,
21912,
16,
60,
4357,
12776,
397,
62,
11600,
58,
39873,
58,
12,
16,
25,
7131,
15,
11907,
4008,
198,
220,
220,
220,
1441,
3047,
62,
7890,
11,
18896,
7,
10879,
8,
628,
198,
4480,
1280,
7203,
7890,
13,
14116,
4943,
355,
277,
25,
198,
220,
220,
220,
2695,
796,
277,
13,
961,
3419,
198,
198,
17497,
796,
718,
198,
2435,
62,
20214,
796,
4324,
532,
352,
198,
22510,
62,
30342,
796,
22243,
198,
22510,
62,
15414,
796,
352,
198,
43501,
62,
7857,
796,
1802,
198,
2676,
341,
796,
8646,
198,
198,
34409,
62,
7890,
11,
997,
62,
37724,
796,
1366,
62,
37687,
11347,
7,
11299,
11,
4324,
28,
17497,
8,
198,
2,
10934,
262,
6577,
2052,
25,
198,
8664,
2052,
796,
22716,
7,
34409,
62,
7890,
11,
15458,
62,
7857,
8,
198,
198,
2,
371,
6144,
5072,
10139,
19590,
290,
29275,
198,
43775,
796,
1391,
198,
220,
220,
220,
705,
448,
10354,
48700,
13,
43015,
7,
27110,
13,
25120,
62,
11265,
26933,
22510,
62,
30342,
11,
997,
62,
37724,
60,
4008,
198,
92,
198,
8482,
1386,
796,
1391,
198,
220,
220,
220,
705,
448,
10354,
48700,
13,
43015,
7,
27110,
13,
25120,
62,
11265,
26933,
22510,
62,
37724,
60,
4008,
198,
92,
198,
198,
2,
48700,
4823,
5128,
198,
55,
796,
48700,
13,
5372,
13829,
7203,
22468,
1600,
685,
14202,
11,
640,
62,
20214,
11,
997,
62,
15414,
4357,
1438,
11639,
55,
11537,
198,
56,
796,
48700,
13,
5372,
13829,
7203,
22468,
1600,
685,
14202,
11,
997,
62,
37724,
12962,
628,
198,
198,
6404,
896,
796,
371,
6144,
7,
55,
11,
19590,
11,
29275,
8,
198,
88,
62,
28764,
796,
48700,
13,
853,
9806,
7,
27110,
13,
20471,
13,
4215,
9806,
7,
6404,
896,
828,
352,
11,
1438,
11639,
88,
62,
28764,
11537,
198,
88,
62,
7942,
796,
48700,
13,
853,
9806,
7,
56,
11,
352,
8,
198,
198,
2,
22014,
290,
6436,
7509,
198,
22462,
62,
404,
796,
48700,
13,
445,
7234,
62,
32604,
7,
27110,
13,
20471,
13,
4215,
9806,
62,
19692,
62,
298,
28338,
62,
4480,
62,
6404,
896,
62,
85,
17,
7,
6404,
896,
28,
6404,
896,
11,
14722,
28,
56,
4008,
198,
27432,
62,
404,
796,
48700,
13,
27432,
13,
29138,
4303,
1773,
27871,
320,
7509,
7,
40684,
62,
4873,
28,
15,
13,
18005,
737,
1084,
48439,
7,
22462,
62,
404,
8,
198,
30283,
62,
28764,
796,
48700,
13,
40496,
7,
88,
62,
28764,
11,
331,
62,
7942,
8,
198,
4134,
23843,
796,
48700,
13,
445,
7234,
62,
32604,
7,
27110,
13,
2701,
7,
30283,
62,
28764,
11,
48700,
13,
22468,
2624,
4008,
198,
198,
2,
20768,
1096,
262,
9633,
351,
4277,
3815,
198,
15003,
796,
48700,
13,
20541,
62,
25641,
2977,
62,
36733,
7509,
3419,
198,
82,
8770,
796,
48700,
13,
27432,
13,
50,
8770,
3419,
198,
4480,
48700,
13,
36044,
3419,
355,
264,
408,
25,
198,
220,
220,
220,
1303,
5660,
262,
4238,
7509,
198,
220,
220,
220,
264,
408,
13,
5143,
7,
15003,
8,
198,
220,
220,
220,
329,
1312,
287,
2837,
7,
15,
11,
24415,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
2994,
62,
4868,
796,
17635,
198,
220,
220,
220,
220,
220,
220,
220,
697,
62,
4868,
796,
17635,
198,
220,
220,
220,
220,
220,
220,
220,
329,
15458,
287,
37830,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1395,
62,
43501,
796,
685,
87,
58,
15,
60,
329,
2124,
287,
15458,
60,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
575,
62,
43501,
796,
685,
87,
58,
16,
60,
329,
2124,
287,
15458,
60,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
575,
62,
43501,
62,
12685,
9043,
796,
17635,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
329,
2124,
287,
575,
62,
43501,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
530,
62,
8940,
62,
31364,
796,
45941,
13,
9107,
418,
26933,
22510,
62,
37724,
4357,
288,
4906,
28,
22468,
8,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
530,
62,
8940,
62,
31364,
58,
87,
60,
796,
352,
13,
15,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
575,
62,
43501,
62,
12685,
9043,
13,
33295,
7,
505,
62,
8940,
62,
31364,
8,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
575,
62,
43501,
62,
12685,
9043,
796,
45941,
13,
85,
25558,
7,
56,
62,
43501,
62,
12685,
9043,
8,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1395,
62,
43501,
796,
45941,
13,
85,
25558,
7,
55,
62,
43501,
8,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1395,
62,
43501,
796,
1395,
62,
43501,
13,
3447,
1758,
7,
11925,
7,
43501,
828,
640,
62,
20214,
11,
997,
62,
15414,
8,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
575,
62,
43501,
62,
12685,
9043,
796,
575,
62,
43501,
62,
12685,
9043,
13,
3447,
1758,
7,
11925,
7,
43501,
828,
997,
62,
37724,
8,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
4808,
11,
697,
11,
2994,
11,
530,
8940,
62,
28764,
796,
264,
408,
13,
5143,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
685,
27432,
62,
404,
11,
9922,
11,
2994,
62,
404,
11,
2604,
896,
4357,
3745,
62,
11600,
34758,
55,
25,
1395,
62,
43501,
11,
575,
25,
575,
62,
43501,
62,
12685,
9043,
30072,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2994,
62,
4868,
13,
33295,
7,
22462,
8,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
697,
62,
4868,
13,
33295,
7,
4134,
8,
198,
220,
220,
220,
220,
220,
220,
220,
2994,
796,
2160,
7,
22462,
62,
4868,
20679,
11925,
7,
22462,
62,
4868,
8,
198,
220,
220,
220,
220,
220,
220,
220,
697,
796,
2160,
7,
4134,
62,
4868,
20679,
11925,
7,
4134,
62,
4868,
8,
198,
220,
220,
220,
220,
220,
220,
220,
3601,
7203,
29993,
341,
366,
1343,
965,
7,
72,
8,
1343,
33172,
22014,
28,
366,
1343,
45144,
25,
13,
19,
69,
92,
1911,
18982,
7,
22462,
8,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1343,
33172,
13614,
33222,
28,
366,
1343,
45144,
25,
13,
17,
69,
92,
1911,
18982,
7,
4134,
1635,
1802,
4008,
198,
220,
220,
220,
17311,
796,
1391,
198,
220,
220,
220,
220,
220,
220,
220,
366,
55,
1298,
1395,
11,
198,
220,
220,
220,
1782,
198,
220,
220,
220,
23862,
796,
19779,
88,
62,
28764,
1298,
331,
62,
28764,
92,
198,
220,
220,
220,
611,
28686,
13,
6978,
13,
9409,
343,
7203,
19849,
1,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
4423,
346,
13,
81,
16762,
631,
10786,
19849,
11537,
198,
220,
220,
220,
48700,
13,
82,
9586,
62,
19849,
13,
36439,
62,
21928,
7,
198,
220,
220,
220,
220,
220,
220,
220,
264,
408,
11,
705,
19849,
14,
3256,
17311,
11,
23862,
198,
220,
220,
220,
1267
] | 2.323529 | 1,734 |
import numpy as np
import matplotlib.pyplot as pl
from vaccontrib.covid import (
get_covid_matrices
)
from vaccontrib.main import (
get_reduced_vaccinated_susceptible_contribution_matrix,
get_reduced_vaccinated_susceptible_eigenvector,
get_eigenvector,
get_next_generation_matrix_from_matrices,
get_contribution_matrix,
)
from tqdm import tqdm
import matplotlib.ticker as mtick
import bfmplot as bp
colors = [
['#E75740', '#58BDB2'],
['#F2957D', '#268D7C'],
]
uv_colors = [ colors[0][0], colors[1][1] ]
reduction = np.linspace(1,0,41)
n = len(reduction)
matrices = get_covid_matrices('delta','01_upper',('no','vacc'))
s0 = np.array(matrices['s'])
r0 = np.array(matrices['r'])
b0 = np.array(matrices['b'])
Cs = np.zeros((2,n,2,2))
for imode, reduce_susc_only in enumerate([True,False]):
_v = np.array([1.,1.,1.,1])
for ired, red in enumerate(reduction):
s = s0.copy()
r = r0.copy()
b = b0.copy()
s[:,1] = 1 - (1-s0[:,0] ) * (1-(1-red)*_v)
if reduce_susc_only:
r = r0
b = b0
else:
r[:,1] = (1-red)*r0[:,1]
b[:,1] = (1-red)*b0[:,1] + red * (b0[:,0])
matrices['s'] = s
matrices['r'] = r
matrices['b'] = b
K = get_next_generation_matrix_from_matrices(1,**matrices)
C = get_reduced_vaccinated_susceptible_contribution_matrix(K)
C /= C.sum()
Cs[imode,ired,:,:] = C
fig, ax = pl.subplots(1,1,figsize=(5,3.5))
x = 1 - reduction
linestyles = ['-','--']
labels = ['const. breakthrough\ntransmissibility reduction',
'decreasing breakthrough\ntransmissibility reduction',
]
ax.plot(x,0.5*np.ones_like(x),c='#aaaaaa',ls='-')
ax.plot([0.22,0.22],[0,.5],c='#aaaaaa',ls='-')
ax.plot([0.41,0.41],[0,.5],c='#aaaaaa',ls='-')
for imode in range(2):
unvacc = Cs[imode,:,:,:].sum(axis=1)[:,0]
vacc = Cs[imode,:,:,:].sum(axis=1)[:,1]
ax.plot(x,unvacc,color=uv_colors[0],label=labels[imode],ls=linestyles[imode])
ax.plot(x,vacc,color=uv_colors[1],ls=linestyles[imode])
ax.set_ylabel('fraction of new infections caused by ...')
ax.legend()
ax.yaxis.set_major_formatter(mtick.PercentFormatter(1))
ax.xaxis.set_major_formatter(mtick.PercentFormatter(1))
ax.set_yticks([0,.25,.5,.75,1])
ax.set_xlim(0,1)
ax.set_ylim(0,1)
ax.text(0.85,0.65,'unvaccinated',ha='right',va='top',color=uv_colors[0])
ax.text(0.8,0.1,'vaccinated',ha='right',va='bottom',color=uv_colors[1])
fig.tight_layout()
ax.set_xlabel('age-independent vaccine efficacy s')
bp.strip_axis(ax)
fig.tight_layout()
fig.savefig('efficacy_scan.pdf')
pl.show()
| [
11748,
299,
32152,
355,
45941,
198,
11748,
2603,
29487,
8019,
13,
9078,
29487,
355,
458,
628,
198,
6738,
6658,
3642,
822,
13,
66,
709,
312,
1330,
357,
198,
220,
220,
220,
220,
220,
220,
220,
651,
62,
66,
709,
312,
62,
6759,
45977,
198,
220,
220,
220,
1267,
198,
198,
6738,
6658,
3642,
822,
13,
12417,
1330,
357,
198,
220,
220,
220,
220,
220,
220,
220,
651,
62,
445,
19513,
62,
37839,
3898,
62,
82,
385,
984,
856,
62,
3642,
3890,
62,
6759,
8609,
11,
198,
220,
220,
220,
220,
220,
220,
220,
651,
62,
445,
19513,
62,
37839,
3898,
62,
82,
385,
984,
856,
62,
68,
9324,
31364,
11,
198,
220,
220,
220,
220,
220,
220,
220,
651,
62,
68,
9324,
31364,
11,
198,
220,
220,
220,
220,
220,
220,
220,
651,
62,
19545,
62,
20158,
62,
6759,
8609,
62,
6738,
62,
6759,
45977,
11,
198,
220,
220,
220,
220,
220,
220,
220,
651,
62,
3642,
3890,
62,
6759,
8609,
11,
198,
220,
220,
220,
1267,
628,
198,
6738,
256,
80,
36020,
1330,
256,
80,
36020,
198,
198,
11748,
2603,
29487,
8019,
13,
83,
15799,
355,
285,
42298,
198,
198,
11748,
275,
38353,
29487,
355,
275,
79,
198,
198,
4033,
669,
796,
685,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
37250,
2,
36,
39251,
1821,
3256,
705,
2,
3365,
33,
11012,
17,
6,
4357,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
37250,
2,
37,
1959,
3553,
35,
3256,
705,
2,
25022,
35,
22,
34,
6,
4357,
198,
220,
220,
220,
220,
220,
220,
220,
2361,
198,
198,
14795,
62,
4033,
669,
796,
685,
7577,
58,
15,
7131,
15,
4357,
7577,
58,
16,
7131,
16,
60,
2361,
628,
198,
445,
8110,
796,
45941,
13,
21602,
10223,
7,
16,
11,
15,
11,
3901,
8,
198,
77,
796,
18896,
7,
445,
8110,
8,
198,
198,
6759,
45977,
796,
651,
62,
66,
709,
312,
62,
6759,
45977,
10786,
67,
12514,
41707,
486,
62,
45828,
3256,
10786,
3919,
41707,
37839,
6,
4008,
198,
82,
15,
796,
45941,
13,
18747,
7,
6759,
45977,
17816,
82,
6,
12962,
198,
81,
15,
796,
45941,
13,
18747,
7,
6759,
45977,
17816,
81,
6,
12962,
198,
65,
15,
796,
45941,
13,
18747,
7,
6759,
45977,
17816,
65,
6,
12962,
198,
198,
32274,
796,
45941,
13,
9107,
418,
19510,
17,
11,
77,
11,
17,
11,
17,
4008,
198,
1640,
545,
1098,
11,
4646,
62,
82,
16241,
62,
8807,
287,
27056,
378,
26933,
17821,
11,
25101,
60,
2599,
628,
220,
220,
220,
4808,
85,
796,
45941,
13,
18747,
26933,
16,
1539,
16,
1539,
16,
1539,
16,
12962,
628,
220,
220,
220,
329,
220,
1202,
11,
2266,
287,
27056,
378,
7,
445,
8110,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
264,
796,
264,
15,
13,
30073,
3419,
198,
220,
220,
220,
220,
220,
220,
220,
374,
796,
374,
15,
13,
30073,
3419,
198,
220,
220,
220,
220,
220,
220,
220,
275,
796,
275,
15,
13,
30073,
3419,
198,
220,
220,
220,
220,
220,
220,
220,
264,
58,
45299,
16,
60,
796,
352,
532,
357,
16,
12,
82,
15,
58,
45299,
15,
60,
1267,
1635,
357,
16,
30420,
16,
12,
445,
27493,
62,
85,
8,
198,
220,
220,
220,
220,
220,
220,
220,
611,
4646,
62,
82,
16241,
62,
8807,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
374,
796,
374,
15,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
275,
796,
275,
15,
198,
220,
220,
220,
220,
220,
220,
220,
2073,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
374,
58,
45299,
16,
60,
796,
357,
16,
12,
445,
27493,
81,
15,
58,
45299,
16,
60,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
275,
58,
45299,
16,
60,
796,
357,
16,
12,
445,
27493,
65,
15,
58,
45299,
16,
60,
1343,
2266,
1635,
357,
65,
15,
58,
45299,
15,
12962,
198,
220,
220,
220,
220,
220,
220,
220,
2603,
45977,
17816,
82,
20520,
796,
264,
198,
220,
220,
220,
220,
220,
220,
220,
2603,
45977,
17816,
81,
20520,
796,
374,
198,
220,
220,
220,
220,
220,
220,
220,
2603,
45977,
17816,
65,
20520,
796,
275,
628,
220,
220,
220,
220,
220,
220,
220,
509,
796,
651,
62,
19545,
62,
20158,
62,
6759,
8609,
62,
6738,
62,
6759,
45977,
7,
16,
11,
1174,
6759,
45977,
8,
198,
220,
220,
220,
220,
220,
220,
220,
327,
796,
651,
62,
445,
19513,
62,
37839,
3898,
62,
82,
385,
984,
856,
62,
3642,
3890,
62,
6759,
8609,
7,
42,
8,
198,
220,
220,
220,
220,
220,
220,
220,
327,
1220,
28,
327,
13,
16345,
3419,
198,
220,
220,
220,
220,
220,
220,
220,
327,
82,
58,
320,
1098,
11,
1202,
11,
45299,
47715,
796,
327,
198,
198,
5647,
11,
7877,
796,
458,
13,
7266,
489,
1747,
7,
16,
11,
16,
11,
5647,
7857,
16193,
20,
11,
18,
13,
20,
4008,
198,
198,
87,
796,
352,
532,
7741,
198,
198,
2815,
42530,
796,
685,
29001,
41707,
438,
20520,
198,
198,
23912,
1424,
796,
37250,
9979,
13,
19304,
59,
429,
26084,
3927,
2247,
7741,
3256,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
12501,
260,
2313,
19304,
59,
429,
26084,
3927,
2247,
7741,
3256,
198,
220,
220,
220,
220,
220,
220,
220,
220,
2361,
198,
198,
897,
13,
29487,
7,
87,
11,
15,
13,
20,
9,
37659,
13,
1952,
62,
2339,
7,
87,
828,
66,
11639,
2,
24794,
7252,
3256,
7278,
11639,
12,
11537,
198,
897,
13,
29487,
26933,
15,
13,
1828,
11,
15,
13,
1828,
38430,
15,
38508,
20,
4357,
66,
11639,
2,
24794,
7252,
3256,
7278,
11639,
12,
11537,
198,
897,
13,
29487,
26933,
15,
13,
3901,
11,
15,
13,
3901,
38430,
15,
38508,
20,
4357,
66,
11639,
2,
24794,
7252,
3256,
7278,
11639,
12,
11537,
198,
198,
1640,
545,
1098,
287,
2837,
7,
17,
2599,
198,
220,
220,
220,
555,
37839,
796,
327,
82,
58,
320,
1098,
11,
45299,
45299,
25,
4083,
16345,
7,
22704,
28,
16,
38381,
45299,
15,
60,
198,
220,
220,
220,
7041,
796,
327,
82,
58,
320,
1098,
11,
45299,
45299,
25,
4083,
16345,
7,
22704,
28,
16,
38381,
45299,
16,
60,
198,
220,
220,
220,
7877,
13,
29487,
7,
87,
11,
403,
37839,
11,
8043,
28,
14795,
62,
4033,
669,
58,
15,
4357,
18242,
28,
23912,
1424,
58,
320,
1098,
4357,
7278,
28,
2815,
42530,
58,
320,
1098,
12962,
198,
220,
220,
220,
7877,
13,
29487,
7,
87,
11,
37839,
11,
8043,
28,
14795,
62,
4033,
669,
58,
16,
4357,
7278,
28,
2815,
42530,
58,
320,
1098,
12962,
198,
220,
220,
220,
7877,
13,
2617,
62,
2645,
9608,
10786,
69,
7861,
286,
649,
16079,
4073,
416,
2644,
11537,
198,
220,
220,
220,
7877,
13,
1455,
437,
3419,
198,
220,
220,
220,
7877,
13,
88,
22704,
13,
2617,
62,
22478,
62,
687,
1436,
7,
16762,
624,
13,
31905,
8479,
1436,
7,
16,
4008,
198,
220,
220,
220,
7877,
13,
87,
22704,
13,
2617,
62,
22478,
62,
687,
1436,
7,
16762,
624,
13,
31905,
8479,
1436,
7,
16,
4008,
198,
198,
897,
13,
2617,
62,
20760,
3378,
26933,
15,
38508,
1495,
38508,
20,
38508,
2425,
11,
16,
12962,
198,
897,
13,
2617,
62,
87,
2475,
7,
15,
11,
16,
8,
198,
897,
13,
2617,
62,
88,
2475,
7,
15,
11,
16,
8,
198,
198,
897,
13,
5239,
7,
15,
13,
5332,
11,
15,
13,
2996,
4032,
403,
37839,
3898,
3256,
3099,
11639,
3506,
3256,
6862,
11639,
4852,
3256,
8043,
28,
14795,
62,
4033,
669,
58,
15,
12962,
198,
897,
13,
5239,
7,
15,
13,
23,
11,
15,
13,
16,
4032,
37839,
3898,
3256,
3099,
11639,
3506,
3256,
6862,
11639,
22487,
3256,
8043,
28,
14795,
62,
4033,
669,
58,
16,
12962,
198,
198,
5647,
13,
33464,
62,
39786,
3419,
198,
198,
897,
13,
2617,
62,
87,
18242,
10786,
496,
12,
34750,
12319,
20179,
264,
11537,
198,
198,
46583,
13,
36311,
62,
22704,
7,
897,
8,
628,
198,
5647,
13,
33464,
62,
39786,
3419,
198,
198,
5647,
13,
21928,
5647,
10786,
24531,
1590,
62,
35836,
13,
12315,
11537,
628,
198,
489,
13,
12860,
3419,
198
] | 2.005162 | 1,356 |
"""
15483 : 최소 편집
URL : https://www.acmicpc.net/problem/15483
Input #1 :
abc
ab
Output #1 :
1
Input #2 :
ca
abc
Output #2 :
3
Input #3 :
abc
cba
Output #3 :
2
Input #4 :
abcd
bcde
Output #4 :
2
Input #5 :
abababababa
aaaaaaaaaaa
Output #5 :
5
Input #6 :
for
whileforif
Output #6 :
7
Input #7 :
whilewhile
whalewhale
Output #7 :
2
Input #8 :
aaabaaa
acacaca
Output #8 :
3
Input #9 :
qwerty
dvorak
Output #9 :
5
Input #10 :
asdf
asdf
Output #10 :
0
"""
import sys
sys.setrecursionlimit(987654321)
MAX_N = 1001
a = input()
b = input()
cache = [[None for _ in range(MAX_N)] for _ in range(MAX_N)]
print(lds(0, 0))
| [
37811,
198,
220,
220,
220,
1315,
38783,
1058,
23821,
113,
250,
168,
228,
234,
220,
169,
236,
116,
168,
100,
239,
198,
220,
220,
220,
10289,
1058,
3740,
1378,
2503,
13,
330,
9383,
14751,
13,
3262,
14,
45573,
14,
1314,
38783,
198,
220,
220,
220,
23412,
1303,
16,
1058,
198,
220,
220,
220,
220,
220,
220,
220,
450,
66,
198,
220,
220,
220,
220,
220,
220,
220,
450,
198,
220,
220,
220,
25235,
1303,
16,
1058,
198,
220,
220,
220,
220,
220,
220,
220,
352,
198,
220,
220,
220,
23412,
1303,
17,
1058,
198,
220,
220,
220,
220,
220,
220,
220,
1275,
198,
220,
220,
220,
220,
220,
220,
220,
450,
66,
198,
220,
220,
220,
25235,
1303,
17,
1058,
198,
220,
220,
220,
220,
220,
220,
220,
513,
198,
220,
220,
220,
23412,
1303,
18,
1058,
198,
220,
220,
220,
220,
220,
220,
220,
450,
66,
198,
220,
220,
220,
220,
220,
220,
220,
269,
7012,
198,
220,
220,
220,
25235,
1303,
18,
1058,
198,
220,
220,
220,
220,
220,
220,
220,
362,
198,
220,
220,
220,
23412,
1303,
19,
1058,
198,
220,
220,
220,
220,
220,
220,
220,
450,
10210,
198,
220,
220,
220,
220,
220,
220,
220,
47125,
2934,
198,
220,
220,
220,
25235,
1303,
19,
1058,
198,
220,
220,
220,
220,
220,
220,
220,
362,
198,
220,
220,
220,
23412,
1303,
20,
1058,
198,
220,
220,
220,
220,
220,
220,
220,
450,
397,
397,
397,
15498,
198,
220,
220,
220,
220,
220,
220,
220,
257,
24794,
24794,
7252,
198,
220,
220,
220,
25235,
1303,
20,
1058,
198,
220,
220,
220,
220,
220,
220,
220,
642,
198,
220,
220,
220,
23412,
1303,
21,
1058,
198,
220,
220,
220,
220,
220,
220,
220,
329,
198,
220,
220,
220,
220,
220,
220,
220,
981,
1640,
361,
198,
220,
220,
220,
25235,
1303,
21,
1058,
198,
220,
220,
220,
220,
220,
220,
220,
767,
198,
220,
220,
220,
23412,
1303,
22,
1058,
198,
220,
220,
220,
220,
220,
220,
220,
981,
4514,
198,
220,
220,
220,
220,
220,
220,
220,
348,
282,
413,
71,
1000,
198,
220,
220,
220,
25235,
1303,
22,
1058,
198,
220,
220,
220,
220,
220,
220,
220,
362,
198,
220,
220,
220,
23412,
1303,
23,
1058,
198,
220,
220,
220,
220,
220,
220,
220,
257,
64,
397,
46071,
198,
220,
220,
220,
220,
220,
220,
220,
936,
330,
22260,
198,
220,
220,
220,
25235,
1303,
23,
1058,
198,
220,
220,
220,
220,
220,
220,
220,
513,
198,
220,
220,
220,
23412,
1303,
24,
1058,
198,
220,
220,
220,
220,
220,
220,
220,
10662,
15448,
774,
198,
220,
220,
220,
220,
220,
220,
220,
288,
20867,
461,
198,
220,
220,
220,
25235,
1303,
24,
1058,
198,
220,
220,
220,
220,
220,
220,
220,
642,
198,
220,
220,
220,
23412,
1303,
940,
1058,
198,
220,
220,
220,
220,
220,
220,
220,
355,
7568,
198,
220,
220,
220,
220,
220,
220,
220,
355,
7568,
198,
220,
220,
220,
25235,
1303,
940,
1058,
198,
220,
220,
220,
220,
220,
220,
220,
657,
198,
37811,
198,
198,
11748,
25064,
198,
17597,
13,
2617,
8344,
24197,
32374,
7,
4089,
29143,
3559,
2481,
8,
198,
198,
22921,
62,
45,
796,
1802,
16,
198,
198,
64,
796,
5128,
3419,
198,
65,
796,
5128,
3419,
198,
198,
23870,
796,
16410,
14202,
329,
4808,
287,
2837,
7,
22921,
62,
45,
15437,
329,
4808,
287,
2837,
7,
22921,
62,
45,
15437,
628,
198,
198,
4798,
7,
335,
82,
7,
15,
11,
657,
4008,
198
] | 1.637782 | 577 |
#!/usr/bin/env python3
"""
Utility functions for JensenLab REST APIs.
https://api.jensenlab.org/Textmining?type1=-26&id1=DOID:10652&type2=9606&limit=10&format=json
https://api.jensenlab.org/Textmining?query=jetlag[tiab]%20OR%20jet-lag[tiab]&type2=9606&limit=10&format=json
https://api.jensenlab.org/Knowledge?type1=-26&id1=DOID:10652&type2=9606&limit=10&format=json
https://api.jensenlab.org/Experiments?type1=-26&id1=DOID:10652&type2=9606&limit=10&format=json
"""
import sys,os,re,json,time,logging
import pandas as pd
from ..util import rest
#
API_HOST='api.jensenlab.org'
API_BASE_PATH=''
BASE_URL='https://'+API_HOST+API_BASE_PATH
#
##############################################################################
##############################################################################
def GetPubmedComentionGenes(ids, base_url=BASE_URL, fout=None):
"""Search by co-mentioned terms."""
tags=[]; df=pd.DataFrame();
for id_this in ids:
rval = rest.Utils.GetURL(base_url+f'/Textmining?query={id_this}[tiab]&type2=9606&limit=10&format=json', parse_json=True)
genes = rval[0] #dict
ensgs = list(genes.keys())
flag = rval[1] #?
for ensg in ensgs:
gene = genes[ensg]
logging.debug(json.dumps(gene, indent=2))
if not tags: tags = list(gene.keys())
df = pd.concat([df, pd.DataFrame({tags[j]:[gene[tags[j]]] for j in range(len(tags))})])
if fout: df.to_csv(fout, "\t", index=False)
logging.info("n_out: {}".format(df.shape[0]))
return df
##############################################################################
| [
2,
48443,
14629,
14,
8800,
14,
24330,
21015,
18,
198,
37811,
198,
18274,
879,
5499,
329,
32623,
17822,
30617,
23113,
13,
198,
5450,
1378,
15042,
13,
73,
18756,
23912,
13,
2398,
14,
8206,
45374,
30,
4906,
16,
10779,
2075,
5,
312,
16,
28,
18227,
2389,
25,
940,
43193,
5,
4906,
17,
28,
24,
33206,
5,
32374,
28,
940,
5,
18982,
28,
17752,
198,
5450,
1378,
15042,
13,
73,
18756,
23912,
13,
2398,
14,
8206,
45374,
30,
22766,
28,
31173,
30909,
58,
20259,
397,
60,
4,
1238,
1581,
4,
1238,
31173,
12,
30909,
58,
20259,
397,
60,
5,
4906,
17,
28,
24,
33206,
5,
32374,
28,
940,
5,
18982,
28,
17752,
198,
5450,
1378,
15042,
13,
73,
18756,
23912,
13,
2398,
14,
23812,
2965,
30,
4906,
16,
10779,
2075,
5,
312,
16,
28,
18227,
2389,
25,
940,
43193,
5,
4906,
17,
28,
24,
33206,
5,
32374,
28,
940,
5,
18982,
28,
17752,
198,
5450,
1378,
15042,
13,
73,
18756,
23912,
13,
2398,
14,
20468,
6800,
30,
4906,
16,
10779,
2075,
5,
312,
16,
28,
18227,
2389,
25,
940,
43193,
5,
4906,
17,
28,
24,
33206,
5,
32374,
28,
940,
5,
18982,
28,
17752,
198,
37811,
198,
11748,
25064,
11,
418,
11,
260,
11,
17752,
11,
2435,
11,
6404,
2667,
198,
11748,
19798,
292,
355,
279,
67,
198,
198,
6738,
11485,
22602,
1330,
1334,
198,
2,
198,
17614,
62,
39,
10892,
11639,
15042,
13,
73,
18756,
23912,
13,
2398,
6,
198,
17614,
62,
33,
11159,
62,
34219,
28,
7061,
198,
33,
11159,
62,
21886,
11639,
5450,
1378,
6,
10,
17614,
62,
39,
10892,
10,
17614,
62,
33,
11159,
62,
34219,
198,
2,
198,
29113,
29113,
7804,
4242,
2235,
198,
198,
29113,
29113,
7804,
4242,
2235,
198,
4299,
3497,
14876,
1150,
5377,
1463,
13746,
274,
7,
2340,
11,
2779,
62,
6371,
28,
33,
11159,
62,
21886,
11,
277,
448,
28,
14202,
2599,
198,
220,
37227,
18243,
416,
763,
12,
17181,
2846,
526,
15931,
198,
220,
15940,
41888,
11208,
47764,
28,
30094,
13,
6601,
19778,
9783,
198,
220,
329,
4686,
62,
5661,
287,
220,
2340,
25,
198,
220,
220,
220,
374,
2100,
796,
1334,
13,
18274,
4487,
13,
3855,
21886,
7,
8692,
62,
6371,
10,
69,
26488,
8206,
45374,
30,
22766,
34758,
312,
62,
5661,
92,
58,
20259,
397,
60,
5,
4906,
17,
28,
24,
33206,
5,
32374,
28,
940,
5,
18982,
28,
17752,
3256,
21136,
62,
17752,
28,
17821,
8,
198,
220,
220,
220,
10812,
796,
374,
2100,
58,
15,
60,
1303,
11600,
198,
220,
220,
220,
3140,
14542,
796,
1351,
7,
5235,
274,
13,
13083,
28955,
198,
220,
220,
220,
6056,
796,
374,
2100,
58,
16,
60,
1303,
30,
198,
220,
220,
220,
329,
3140,
70,
287,
3140,
14542,
25,
198,
220,
220,
220,
220,
220,
9779,
796,
10812,
58,
641,
70,
60,
198,
220,
220,
220,
220,
220,
18931,
13,
24442,
7,
17752,
13,
67,
8142,
7,
70,
1734,
11,
33793,
28,
17,
4008,
198,
220,
220,
220,
220,
220,
611,
407,
15940,
25,
15940,
796,
1351,
7,
70,
1734,
13,
13083,
28955,
198,
220,
220,
220,
220,
220,
47764,
796,
279,
67,
13,
1102,
9246,
26933,
7568,
11,
279,
67,
13,
6601,
19778,
15090,
31499,
58,
73,
5974,
58,
70,
1734,
58,
31499,
58,
73,
11907,
60,
329,
474,
287,
2837,
7,
11925,
7,
31499,
4008,
30072,
12962,
198,
220,
611,
277,
448,
25,
47764,
13,
1462,
62,
40664,
7,
69,
448,
11,
37082,
83,
1600,
6376,
28,
25101,
8,
198,
220,
18931,
13,
10951,
7203,
77,
62,
448,
25,
23884,
1911,
18982,
7,
7568,
13,
43358,
58,
15,
60,
4008,
198,
220,
1441,
47764,
198,
198,
29113,
29113,
7804,
4242,
2235,
198
] | 2.61194 | 603 |
import numpy as np
import joblib
from rllab.sampler.utils import rollout
import os
from rllab import config
from rllab.misc import ext
from tqdm import trange, tqdm
import IPython
import matplotlib
matplotlib.use("Agg")
import matplotlib.pyplot as plt
import itertools
from sandbox.finetuning.envs.mujoco.modified.modified_ant_env import ModifiedAntEnv
from sandbox.finetuning.envs.mujoco.modified.modified_ant_gather_env import ModifiedAntLowGearGatherEnv
from rllab.envs.normalized_env import normalize
import math
# mutates the policy, but not in a way that matters
if __name__ == "__main__":
main()
| [
11748,
299,
32152,
355,
45941,
198,
11748,
1693,
8019,
198,
6738,
374,
297,
397,
13,
37687,
20053,
13,
26791,
1330,
38180,
198,
11748,
28686,
198,
6738,
374,
297,
397,
1330,
4566,
198,
6738,
374,
297,
397,
13,
44374,
1330,
1070,
198,
6738,
256,
80,
36020,
1330,
491,
858,
11,
256,
80,
36020,
198,
11748,
6101,
7535,
198,
11748,
2603,
29487,
8019,
198,
6759,
29487,
8019,
13,
1904,
7203,
46384,
4943,
198,
11748,
2603,
29487,
8019,
13,
9078,
29487,
355,
458,
83,
198,
11748,
340,
861,
10141,
198,
6738,
35204,
13,
15643,
316,
46493,
13,
268,
14259,
13,
76,
23577,
25634,
13,
41771,
13,
41771,
62,
415,
62,
24330,
1330,
40499,
13217,
4834,
85,
198,
6738,
35204,
13,
15643,
316,
46493,
13,
268,
14259,
13,
76,
23577,
25634,
13,
41771,
13,
41771,
62,
415,
62,
70,
1032,
62,
24330,
1330,
40499,
13217,
20535,
38141,
38,
1032,
4834,
85,
198,
6738,
374,
297,
397,
13,
268,
14259,
13,
11265,
1143,
62,
24330,
1330,
3487,
1096,
198,
11748,
10688,
198,
198,
2,
4517,
689,
262,
2450,
11,
475,
407,
287,
257,
835,
326,
6067,
628,
198,
361,
11593,
3672,
834,
6624,
366,
834,
12417,
834,
1298,
198,
220,
220,
220,
1388,
3419,
628,
628
] | 3.049751 | 201 |
from django.shortcuts import render_to_response
from django.http import HttpResponseRedirect
from django.http import HttpResponse
from django.core.urlresolvers import reverse
from django.views.decorators.csrf import csrf_exempt
from django.template import RequestContext
## The home page. | [
6738,
42625,
14208,
13,
19509,
23779,
1330,
8543,
62,
1462,
62,
26209,
198,
6738,
42625,
14208,
13,
4023,
1330,
367,
29281,
31077,
7738,
1060,
198,
6738,
42625,
14208,
13,
4023,
1330,
367,
29281,
31077,
198,
6738,
42625,
14208,
13,
7295,
13,
6371,
411,
349,
690,
1330,
9575,
198,
6738,
42625,
14208,
13,
33571,
13,
12501,
273,
2024,
13,
6359,
41871,
1330,
269,
27891,
69,
62,
42679,
198,
6738,
42625,
14208,
13,
28243,
1330,
19390,
21947,
198,
198,
2235,
383,
1363,
2443,
13
] | 3.52439 | 82 |
# Generated by Django 2.0.5 on 2018-05-07 00:47
from django.db import migrations
| [
2,
2980,
515,
416,
37770,
362,
13,
15,
13,
20,
319,
2864,
12,
2713,
12,
2998,
3571,
25,
2857,
198,
198,
6738,
42625,
14208,
13,
9945,
1330,
15720,
602,
628
] | 2.766667 | 30 |
##################################
# Basik-Calc
# Calculator for basic operations
# Author: Ricardo Dimas
##################################
import sys
if __name__ == '__main__':
try:
main()
except KeyboardInterrupt:
print('\nExiting...')
sys.exit()
| [
29113,
2235,
198,
2,
6455,
1134,
12,
9771,
66,
198,
2,
43597,
329,
4096,
4560,
198,
2,
6434,
25,
38847,
14048,
292,
198,
29113,
2235,
198,
198,
11748,
25064,
198,
198,
361,
11593,
3672,
834,
6624,
705,
834,
12417,
834,
10354,
198,
220,
220,
220,
1949,
25,
198,
220,
220,
220,
220,
220,
220,
220,
1388,
3419,
198,
220,
220,
220,
2845,
31973,
9492,
3622,
25,
198,
220,
220,
220,
220,
220,
220,
220,
3601,
10786,
59,
77,
3109,
1780,
986,
11537,
198,
220,
220,
220,
220,
220,
220,
220,
25064,
13,
37023,
3419,
628
] | 3 | 95 |
import multiprocessing
import os
import re
import shutil
import tempfile
import zipfile
from datetime import datetime
from django.core.management.base import BaseCommand, CommandError
import sh
from corehq.apps.export.dbaccessors import get_properly_wrapped_export_instance
from corehq.apps.export.multiprocess import (
UNPROCESSED_PAGES_DIR,
MultiprocessExporter,
RetryResult,
_add_compressed_page_to_zip,
)
from corehq.util.files import safe_filename
| [
11748,
18540,
305,
919,
278,
198,
11748,
28686,
198,
11748,
302,
198,
11748,
4423,
346,
198,
11748,
20218,
7753,
198,
11748,
19974,
7753,
198,
6738,
4818,
8079,
1330,
4818,
8079,
198,
198,
6738,
42625,
14208,
13,
7295,
13,
27604,
13,
8692,
1330,
7308,
21575,
11,
9455,
12331,
198,
198,
11748,
427,
198,
198,
6738,
4755,
71,
80,
13,
18211,
13,
39344,
13,
9945,
15526,
669,
1330,
651,
62,
1676,
525,
306,
62,
29988,
1496,
62,
39344,
62,
39098,
198,
6738,
4755,
71,
80,
13,
18211,
13,
39344,
13,
16680,
541,
305,
919,
1330,
357,
198,
220,
220,
220,
4725,
4805,
4503,
7597,
1961,
62,
4537,
48075,
62,
34720,
11,
198,
220,
220,
220,
7854,
541,
305,
919,
3109,
26634,
11,
198,
220,
220,
220,
4990,
563,
23004,
11,
198,
220,
220,
220,
4808,
2860,
62,
5589,
2790,
62,
7700,
62,
1462,
62,
13344,
11,
198,
8,
198,
6738,
4755,
71,
80,
13,
22602,
13,
16624,
1330,
3338,
62,
34345,
628,
198
] | 2.944099 | 161 |
"""
Interface for custom data.
This module handles datasets and is the class that you need to inherit from for your custom dataset.
This class gives you all the handles so that you can train with a new –dataset=mydataset.
The particular configuration of keypoints and skeleton is specified in the headmeta instances
"""
import argparse
import torch
import numpy as np
try:
from pycocotools.coco import COCO
except ImportError:
COCO = None
from openpifpaf.datasets import DataModule
from openpifpaf import encoder, headmeta, metric, transforms
from openpifpaf.datasets import collate_images_anns_meta, collate_images_targets_meta
from openpifpaf.plugins.coco import CocoDataset as CocoLoader
from .constants import get_constants, training_weights_local_centrality
from .metrics import MeanPixelError
class ApolloKp(DataModule):
"""
DataModule for the Apollocar3d Dataset.
"""
train_annotations = 'data-apollocar3d/annotations/apollo_keypoints_66_train.json'
val_annotations = 'data-apollocar3d/annotations/apollo_keypoints_66_val.json'
eval_annotations = val_annotations
train_image_dir = 'data-apollocar3d/images/train/'
val_image_dir = 'data-apollocar3d/images/val/'
eval_image_dir = val_image_dir
n_images = None
square_edge = 513
extended_scale = False
orientation_invariant = 0.0
blur = 0.0
augmentation = True
rescale_images = 1.0
upsample_stride = 1
min_kp_anns = 1
b_min = 1 # 1 pixel
eval_annotation_filter = True
eval_long_edge = 0 # set to zero to deactivate rescaling
eval_orientation_invariant = 0.0
eval_extended_scale = False
@classmethod
@classmethod
@classmethod
# TODO: make sure that 24kp flag is activated when evaluating a 24kp model
| [
37811,
198,
39317,
329,
2183,
1366,
13,
198,
198,
1212,
8265,
17105,
40522,
290,
318,
262,
1398,
326,
345,
761,
284,
16955,
422,
329,
534,
2183,
27039,
13,
198,
1212,
1398,
3607,
345,
477,
262,
17105,
523,
326,
345,
460,
4512,
351,
257,
649,
784,
19608,
292,
316,
28,
1820,
19608,
292,
316,
13,
198,
464,
1948,
8398,
286,
1994,
13033,
290,
18328,
318,
7368,
287,
262,
1182,
28961,
10245,
198,
37811,
628,
198,
11748,
1822,
29572,
198,
11748,
28034,
198,
11748,
299,
32152,
355,
45941,
198,
28311,
25,
198,
220,
220,
220,
422,
12972,
66,
420,
313,
10141,
13,
66,
25634,
1330,
327,
4503,
46,
198,
16341,
17267,
12331,
25,
198,
220,
220,
220,
327,
4503,
46,
796,
6045,
198,
198,
6738,
1280,
79,
361,
79,
1878,
13,
19608,
292,
1039,
1330,
6060,
26796,
198,
6738,
1280,
79,
361,
79,
1878,
1330,
2207,
12342,
11,
1182,
28961,
11,
18663,
11,
31408,
198,
6738,
1280,
79,
361,
79,
1878,
13,
19608,
292,
1039,
1330,
2927,
378,
62,
17566,
62,
1236,
82,
62,
28961,
11,
2927,
378,
62,
17566,
62,
83,
853,
1039,
62,
28961,
198,
6738,
1280,
79,
361,
79,
1878,
13,
37390,
13,
66,
25634,
1330,
48222,
27354,
292,
316,
355,
48222,
17401,
198,
198,
6738,
764,
9979,
1187,
1330,
651,
62,
9979,
1187,
11,
3047,
62,
43775,
62,
12001,
62,
31463,
414,
198,
6738,
764,
4164,
10466,
1330,
22728,
40809,
12331,
628,
198,
4871,
17508,
42,
79,
7,
6601,
26796,
2599,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
6060,
26796,
329,
262,
5949,
692,
420,
283,
18,
67,
16092,
292,
316,
13,
198,
220,
220,
220,
37227,
628,
220,
220,
220,
4512,
62,
34574,
602,
796,
705,
7890,
12,
499,
692,
420,
283,
18,
67,
14,
34574,
602,
14,
499,
15578,
62,
2539,
13033,
62,
2791,
62,
27432,
13,
17752,
6,
198,
220,
220,
220,
1188,
62,
34574,
602,
796,
705,
7890,
12,
499,
692,
420,
283,
18,
67,
14,
34574,
602,
14,
499,
15578,
62,
2539,
13033,
62,
2791,
62,
2100,
13,
17752,
6,
198,
220,
220,
220,
5418,
62,
34574,
602,
796,
1188,
62,
34574,
602,
198,
220,
220,
220,
4512,
62,
9060,
62,
15908,
796,
705,
7890,
12,
499,
692,
420,
283,
18,
67,
14,
17566,
14,
27432,
14,
6,
198,
220,
220,
220,
1188,
62,
9060,
62,
15908,
796,
705,
7890,
12,
499,
692,
420,
283,
18,
67,
14,
17566,
14,
2100,
14,
6,
198,
220,
220,
220,
5418,
62,
9060,
62,
15908,
796,
1188,
62,
9060,
62,
15908,
628,
220,
220,
220,
299,
62,
17566,
796,
6045,
198,
220,
220,
220,
6616,
62,
14907,
796,
642,
1485,
198,
220,
220,
220,
7083,
62,
9888,
796,
10352,
198,
220,
220,
220,
12852,
62,
16340,
2743,
415,
796,
657,
13,
15,
198,
220,
220,
220,
23671,
796,
657,
13,
15,
198,
220,
220,
220,
16339,
14374,
796,
6407,
198,
220,
220,
220,
6811,
1000,
62,
17566,
796,
352,
13,
15,
198,
220,
220,
220,
19649,
1403,
62,
2536,
485,
796,
352,
198,
220,
220,
220,
949,
62,
74,
79,
62,
1236,
82,
796,
352,
198,
220,
220,
220,
275,
62,
1084,
796,
352,
220,
1303,
352,
17465,
628,
220,
220,
220,
5418,
62,
1236,
14221,
62,
24455,
796,
6407,
198,
220,
220,
220,
5418,
62,
6511,
62,
14907,
796,
657,
220,
1303,
900,
284,
6632,
284,
390,
39022,
6811,
4272,
198,
220,
220,
220,
5418,
62,
13989,
341,
62,
16340,
2743,
415,
796,
657,
13,
15,
198,
220,
220,
220,
5418,
62,
2302,
1631,
62,
9888,
796,
10352,
628,
220,
220,
220,
2488,
4871,
24396,
628,
220,
220,
220,
2488,
4871,
24396,
628,
220,
220,
220,
2488,
4871,
24396,
198,
198,
2,
16926,
46,
25,
787,
1654,
326,
1987,
74,
79,
6056,
318,
13906,
618,
22232,
257,
1987,
74,
79,
2746,
198
] | 2.833068 | 629 |
# pydumper.py
#
# This is being worked on - it does not yet work at all, in ay way
# shape or form :-)
#
# A new script engine, derived from the standard scripting engine,
# which dumps information.
# This generally can be used to grab all sorts of useful details about
# an engine - expose bugs in it or Python, dump the object model, etc.
# As it is derived from the standard engine, it fully supports Python
# as a scripting language - meaning the dumps produced can be quite dynamic,
# and based on the script code you execute.
import pyscript
from win32com.axscript import axscript
from pyscript import RaiseAssert, trace, Exception, SCRIPTTEXT_FORCEEXECUTION
PyDump_CLSID = '{ac527e60-c693-11d0-9c25-00aa00125a98}'
if __name__=='__main__':
Register()
| [
2,
279,
5173,
15829,
13,
9078,
201,
198,
2,
201,
198,
2,
770,
318,
852,
3111,
319,
532,
340,
857,
407,
1865,
670,
379,
477,
11,
287,
38762,
835,
201,
198,
2,
5485,
393,
1296,
47226,
201,
198,
2,
201,
198,
2,
317,
649,
4226,
3113,
11,
10944,
422,
262,
3210,
36883,
3113,
11,
201,
198,
2,
543,
45514,
1321,
13,
201,
198,
201,
198,
2,
770,
4143,
460,
307,
973,
284,
5552,
477,
10524,
286,
4465,
3307,
546,
201,
198,
2,
281,
3113,
532,
15651,
11316,
287,
340,
393,
11361,
11,
10285,
262,
2134,
2746,
11,
3503,
13,
201,
198,
201,
198,
2,
1081,
340,
318,
10944,
422,
262,
3210,
3113,
11,
340,
3938,
6971,
11361,
201,
198,
2,
355,
257,
36883,
3303,
532,
3616,
262,
45514,
4635,
460,
307,
2407,
8925,
11,
201,
198,
2,
290,
1912,
319,
262,
4226,
2438,
345,
12260,
13,
201,
198,
201,
198,
11748,
279,
893,
6519,
201,
198,
6738,
1592,
2624,
785,
13,
897,
12048,
1330,
7877,
12048,
201,
198,
201,
198,
6738,
279,
893,
6519,
1330,
35123,
8021,
861,
11,
12854,
11,
35528,
11,
6374,
32618,
15751,
13918,
62,
13775,
5222,
6369,
2943,
35354,
201,
198,
201,
198,
20519,
35,
931,
62,
5097,
50,
2389,
796,
705,
90,
330,
20,
1983,
68,
1899,
12,
66,
48528,
12,
1157,
67,
15,
12,
24,
66,
1495,
12,
405,
7252,
405,
11623,
64,
4089,
92,
6,
201,
198,
201,
198,
201,
198,
197,
201,
198,
361,
11593,
3672,
834,
855,
6,
834,
12417,
834,
10354,
201,
198,
197,
38804,
3419,
201,
198,
201,
198,
201,
198
] | 3.041985 | 262 |
import pandas as pd
import numpy as np
import csv
#################Obtain the List of All bpts that sent Political Tweets [i.e. Political Bots]:#######################
dfn = pd.read_csv("/root/.encrypted/.pythonSai/kCoreBots/CoreBotEN/MachineLearning/NaiveBayes/datasets/CoreBotTweetsCombinedEN.csv", sep=",", skiprows=[0], header=None, usecols=[1], names=["userid"])
column_values = dfn[["userid"]].values.ravel()
unique_values = pd.unique(column_values)
pd.DataFrame(unique_values).to_csv("ListIDS.csv", index=False)
| [
11748,
19798,
292,
355,
279,
67,
198,
11748,
299,
32152,
355,
45941,
198,
11748,
269,
21370,
198,
198,
14468,
2,
5944,
3153,
262,
7343,
286,
1439,
275,
457,
82,
326,
1908,
14611,
24205,
1039,
685,
72,
13,
68,
13,
14611,
40946,
5974,
14468,
4242,
21017,
198,
7568,
77,
796,
279,
67,
13,
961,
62,
40664,
7203,
14,
15763,
11757,
43628,
11757,
29412,
50,
1872,
14,
74,
14055,
33,
1747,
14,
14055,
20630,
1677,
14,
37573,
41730,
14,
26705,
425,
15262,
274,
14,
19608,
292,
1039,
14,
14055,
20630,
32665,
1039,
20575,
1389,
1677,
13,
40664,
1600,
41767,
28,
2430,
11,
14267,
8516,
41888,
15,
4357,
13639,
28,
14202,
11,
779,
4033,
82,
41888,
16,
4357,
3891,
28,
14692,
7220,
312,
8973,
8,
198,
28665,
62,
27160,
796,
288,
22184,
58,
14692,
7220,
312,
8973,
4083,
27160,
13,
25843,
3419,
198,
34642,
62,
27160,
796,
220,
279,
67,
13,
34642,
7,
28665,
62,
27160,
8,
198,
30094,
13,
6601,
19778,
7,
34642,
62,
27160,
737,
1462,
62,
40664,
7203,
8053,
14255,
13,
40664,
1600,
6376,
28,
25101,
8,
198
] | 2.926966 | 178 |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.