content
stringlengths 1
1.04M
| input_ids
sequencelengths 1
774k
| ratio_char_token
float64 0.38
22.9
| token_count
int64 1
774k
|
|---|---|---|---|
import asyncio
from flask import (
abort,
Blueprint,
Response,
render_template,
request,
current_app as app,
)
# local imports
from . import routes
from luts import huc8_gdf
huc_api = Blueprint("huc_api", __name__)
@routes.route("/huc/")
@routes.route("/huc/abstract/")
@routes.route("/huc/huc8")
@routes.route("/huc/huc8/<huc8_id>")
def run_fetch_huc_poly(huc8_id):
"""Run the async IEM data requesting for a single point
and return data as json
Args:
huc8_id (int): HUC-8 ID
Returns:
GeoJSON of the HUC-8 polygon
Notes:
example request: http://localhost:5000/huc/huc8/19070506
"""
poly = huc8_gdf.loc[[huc8_id]]
poly_geojson = poly.to_json()
return poly_geojson
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] | 2.212209 | 344 |
# snapy - a python snmp library
#
# Copyright (C) 2009 ITA Software, Inc.
#
# This program is free software; you can redistribute it and/or
# modify it under the terms of the GNU General Public License
# version 2 as published by the Free Software Foundation.
#
# This program 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 General Public License for more details.
import time
from twisted.trial import unittest
from snapy.netsnmp.unittests import TestCase
from snapy.netsnmp import Session, SnmpError, SnmpTimeout, OID
class Result(object):
"""Container for async results"""
value = None
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37811,
198,
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1988,
796,
6045,
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] | 3.632353 | 204 |
"""
This tells Python that this is a module.
"""
| [
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198,
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4952,
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326,
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318,
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8265,
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198
] | 3.5 | 14 |
ACTION_TYPES = {
'INIT': '@@redux/INIT'
}
"""
* Creates a Redux store that holds the state tree.
* The only way to change the data in the store is to call `dispatch()` on it.
*
* There should only be a single store in your app. To specify how different
* parts of the state tree respond to actions, you may combine several reducers
* into a single reducer function by using `combineReducers`.
*
* @param {Function} reducer A function that returns the next state tree, given
* the current state tree and the action to handle.
*
* @param {any} [preloadedState] The initial state. You may optionally specify it
* to hydrate the state from the server in universal apps, or to restore a
* previously serialized user session.
* If you use `combineReducers` to produce the root reducer function, this must be
* an object with the same shape as `combineReducers` keys.
*
* @param {Function} enhancer The store enhancer. You may optionally specify it
* to enhance the store with third-party capabilities such as middleware,
* time travel, persistence, etc. The only store enhancer that ships with Redux
* is `applyMiddleware()`.
*
* @returns {Store} A Redux store that lets you read the state, dispatch actions
* and subscribe to changes.
""" | [
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] | 3.777778 | 333 |
from warnings import filterwarnings
from PIL import Image, ImageOps
from jikanpy import Jikan
from requests import get
from time import sleep
import re
import os
print('''Run this in your anime folder
For help, info and memes, check out
https://github.com/notdedsec/anicon
''')
sleep(1)
jikan = Jikan()
filterwarnings("ignore")
folderlist = next(os.walk('.'))[1]
if folderlist is None or len(folderlist) == 0:
# In case the file is placed inside an inner most directory which contains only files and no other folders, this list will be empty.
# Thus adding the current directory path as an element of the list.
folderlist = E:\
automode = True if input('Use AutoMode? Y/N : ').upper() == 'Y' else False
for folder in folderlist:
name = getname(folder)
# Extracting the name of the folder without the path and then performing search for the same. This will be the name of the anime
# episode, thus instead of performing a search for the directory path, now performing a search for the directory name.
name = name.rpartition('\\')[2].strip()
iconname = name.replace(' ', '_')
jpgfile = folder + '\\' + iconname + '.jpg'
icofile = folder + '\\' + iconname + '.ico'
if os.path.isfile(icofile):
print('An icon is already present. Delete the older icon and `desktop.ini` file before applying a new icon')
continue
link, Type = getartwork(name)
try:
icon = createicon(folder, link)
except:
print('Ran into an error. Blame the dev :(')
continue
f = open(folder + "\\desktop.ini","w+")
f.write("[.ShellClassInfo]\nConfirmFileOp=0\n")
f.write("IconResource={},0".format(icofile.replace(folder, "").strip("\\")))
f.write("\nIconFile={}\nIconIndex=0".format(icofile.replace(folder, "").strip("\\")))
if Type is not None and len(Type) > 0:
# If the result has a type, then using this as the infotip for the desktop icon.
f.write("\nInfoTip={}".format(Type))
# Closing the output stream. All the text will be written into `desktop.ini` file only when the output is being closed.
f.close()
# Not marking the `desktop.ini` file as a system file. This will make sure that the file can be seen if display hidden items is enabled.
os.system('attrib +r \"{}\\{}\"'.format(os.getcwd(), folder))
os.system('attrib +h \"{}\\desktop.ini\"'.format(folder))
os.system('attrib +h \"{}\"'.format(icon))
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] | 2.897527 | 849 |
# Generated by Django 2.2.1 on 2019-06-08 13:17
from django.db import migrations
| [
2,
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] | 2.766667 | 30 |
# ----------------------------------------------------------------------
#
# Brad T. Aagaard, U.S. Geological Survey
# Charles A. Williams, GNS Science
# Matthew G. Knepley, University at Buffalo
#
# This code was developed as part of the Computational Infrastructure
# for Geodynamics (http://geodynamics.org).
#
# Copyright (c) 2010-2021 University of California, Davis
#
# See LICENSE.md for license information.
#
# ----------------------------------------------------------------------
#
# @file pythia.pyre/meshio/DataWriterHDF5Ext.py
#
# @brief Python object for writing finite-element data to HDF5 file
# with datasets stored in external binary files.
from .DataWriter import DataWriter
from .meshio import DataWriterHDF5Ext as ModuleDataWriterHDF5Ext
class DataWriterHDF5Ext(DataWriter, ModuleDataWriterHDF5Ext):
"""
@brief Python object for writing finite-element data to HDF5 file
with datasets stored in external binary files.
FACTORY: data_writer
"""
import pythia.pyre.inventory
filename = pythia.pyre.inventory.str("filename", default="")
filename.meta['tip'] = "Name of HDF5 file."
# PUBLIC METHODS /////////////////////////////////////////////////////
def __init__(self, name="datawriterhdf5"):
"""Constructor.
"""
DataWriter.__init__(self, name)
return
def preinitialize(self):
"""Initialize writer.
"""
DataWriter.preinitialize(self)
return
def setFilename(self, outputDir, simName, label):
"""Set filename from default options and inventory. If filename is given in inventory, use it,
otherwise create filename from default options.
"""
filename = self.filename or DataWriter.mkfilename(outputDir, simName, label, "h5")
self.mkpath(filename)
ModuleDataWriterHDF5Ext.filename(self, filename)
return
def close(self):
"""Close writer.
"""
ModuleDataWriterHDF5Ext.close(self)
# Only write Xdmf file on proc 0
from pylith.mpi.Communicator import mpi_comm_world
comm = mpi_comm_world()
if not comm.rank:
from .Xdmf import Xdmf
xdmf = Xdmf()
xdmf.write(ModuleDataWriterHDF5Ext.hdf5Filename(
self), verbose=False)
return
# PRIVATE METHODS /////////////////////////////////////////////////////
def _createModuleObj(self):
"""Create handle to C++ object."""
ModuleDataWriterHDF5Ext.__init__(self)
return
# FACTORIES ////////////////////////////////////////////////////////////
def data_writer():
"""Factory associated with DataWriter.
"""
return DataWriterHDF5Ext()
# End of file
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] | 2.840415 | 965 |
# A timer based LED chaser using adressable LEDs of type WS2812/NeoPixel
# Tested on a an ESP32 running MicroPython
import machine, neopixel
from machine import Timer
# Pin to use for controlling LEDs
LED_STRIP_PIN = 14
# Number of LEDs on LED strip
LED_STRIP_LENGTH = 42
# How many times a second (HZ) to advance the LED
LED_ADVANCE_RATE_HZ = 20
# The color of the lit LED
LED_COLOR = (100, 0, 0)
# How many times a second (HZ) to refresh LEDs
LED_REFRESH_RATE_HZ = 20
# The speed of fading. Higher values = faster fades with less granularity
LED_FADE_SPEED = 15
# Frequency of lowering the intensity of the LEDS
LED_FADE_RATE_HZ = LED_REFRESH_RATE_HZ
# Create a neopixels object representing a strip of LEDS
np = neopixel.NeoPixel(machine.Pin(LED_STRIP_PIN), LED_STRIP_LENGTH)
# Index of the currently lit LED
led_index = 0
def advance(timer):
"""
Advance lit LED
"""
global np, led_index, LED_COLOR
# Light LED
np[led_index] = LED_COLOR
# Set index of next LED
if led_index == np.n - 1:
led_index = 0
else:
led_index += 1
def fade(timer):
"""
Lower intensity for all LEDs on strip
"""
global np, LED_FADE_SPEED
for i in range(np.n):
np[i] = [
v - int(LED_FADE_SPEED) if v > int(LED_FADE_SPEED) else 0 for v in np[i]
]
# Timer for advancing the lit LED
timer_advance = Timer(0)
timer_advance.init(
period=int(1000 / LED_ADVANCE_RATE_HZ),
mode=Timer.PERIODIC,
callback=advance,
)
# Timer for fading out LEDs
timer_fade = Timer(1)
timer_fade.init(
period=int(1000 / LED_FADE_RATE_HZ),
mode=Timer.PERIODIC,
callback=fade,
)
# Timer for updating the LED strip
timer_refresh = Timer(2)
timer_refresh.init(
period=int(1000 / LED_REFRESH_RATE_HZ),
mode=Timer.PERIODIC,
callback=lambda t: np.write(),
)
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] | 2.468541 | 747 |
#!/usr/bin/env python3
# ******************************************************** # # Project: nita-webapp
#
# Copyright (c) Juniper Networks, Inc., 2021. All rights reserved.
# # Notice and Disclaimer: This code is licensed to you under the Apache 2.0 License (the "License"). You may not use this code except in compliance with the License. This code is not an official Juniper product. You can obtain a copy of the License at https://www.apache.org/licenses/LICENSE-2.0.html
#
# SPDX-License-Identifier: Apache-2.0
#
# Third-Party Code: This code may depend on other components under separate copyright notice and license terms. Your use of the source code for those components is subject to the terms and conditions of the respective license as noted in the Third-Party source code file.
#
# ********************************************************
# xml specific
from lxml import etree
from lxml.builder import E
import xml.etree.ElementTree as ET
import xml.dom.minidom
import lxml
# stdlib
from io import StringIO
import re
import subprocess as sub
from subprocess import Popen, PIPE
from subprocess import check_call
import os
import sys
import pdb
import errno
import time
from datetime import datetime
from datetime import date, timedelta
from time import sleep
from pprint import pprint
import logging
import hashlib
from socket import error as SocketError
import errno
import signal
from itertools import *
import csv
import tempfile
#third-party
import xmltodict
import yaml
import paramiko
# import ncclient.transport.errors as NcErrors
# import ncclient.operations.errors as TError
import jinja2
import csv
from select import select
import ftplib
import logging.handlers
# junos-ez
from jnpr.junos.utils.scp import SCP
from jnpr.junos.utils.fs import FS
from jnpr.junos.exception import *
from jnpr.junos.utils.config import Config
from jnpr.junos.utils.sw import SW
from jnpr.junos.utils.start_shell import StartShell
from jnpr.junos.factory import loadyaml
from jnpr.junos.op.routes import RouteTable
from jnpr.junos import Device
from jnpr.junos import *
# Robot libraries
from robot.libraries.BuiltIn import BuiltIn
from robot.libraries.OperatingSystem import OperatingSystem
from robot.api import logger
# Global Variables
timestamp = datetime.now().strftime("%Y-%m-%d")
timestamp2 = datetime.now().strftime("%Y-%m-%d-%H-%M-%S.%f")[:-3]
timestamp3 = datetime.now().strftime("%H_%M_%S")
timestamp4 = datetime.now().strftime("%Y_%m_%d_%H_%M_%S")
# Global variables for shell connection
_SHELL_PROMPT = '% '
_JUNOS_PROMPT = '> '
_BASH_PROMPT = '?'
_SELECT_WAIT = 0.1
_RECVSZ = 1024
| [
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] | 2.531915 | 1,175 |
from collections import defaultdict
operMap = {
'+' : 0,
'-' : 1,
'*' : 2,
'/' : 3,
'%' : 4,
'=' : 5,
'<' : 6,
'>' : 7,
'<=' : 8,
'>=' : 9,
'!=' : 10,
'==' : 11,
'&&' : 12,
'||' : 13,
'console' : 14,
'+*' : 15}
#Additional
semanticCube = {}
# Return -1 if not possible
semanticCube = defaultdict(lambda: -1, semanticCube)
# Aritmetic
# int _ int : _
# float _ float : _
# int _ float : _
# float _ int : _
for i in range(0,4):
semanticCube[i,0,0] = 0
semanticCube[i,1,1] = 1
semanticCube[i,0,1] = 1
semanticCube[i,1,0] = 1
semanticCube[15,0,0] = 0
# = a a : a
for i in range(0,4):
semanticCube[5, i, i] = i
# = int float: int
semanticCube[5, 0, 1] = 0
semanticCube[5, 1, 0] = 1
# % is always integer
semanticCube[4,0,0] = 0
semanticCube[4,1,1] = 0
semanticCube[4,0,1] = 0
semanticCube[4,1,0] = 0
# "string1" + "string2" = "string1string2"
semanticCube[0,2,2] = 2
#Comparison
# int|float_int|float = bool
for i in range(0,2):
for j in range(0,2):
for k in range(6,12):
semanticCube[k,i,j] = 3
for k in range(6,12):
semanticCube[k,2,2] = 3
#HigherExpression
for i in range(12,14):
semanticCube[i,3,3] = 3
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] | 1.706559 | 869 |
#
# Copyright 2016 The BigDL Authors.
#
# 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 os
import sys
import glob
from py4j.protocol import Py4JJavaError
from py4j.java_gateway import JavaObject
from py4j.java_collections import ListConverter, JavaArray, JavaList, JavaMap, MapConverter
from pyspark import RDD, SparkContext
from pyspark.serializers import PickleSerializer, AutoBatchedSerializer
from pyspark.sql import DataFrame, SQLContext
from pyspark.mllib.common import callJavaFunc
from pyspark import SparkConf
import numpy as np
import threading
import tempfile
from bigdl.util.engine import get_bigdl_classpath, is_spark_below_2_2
INTMAX = 2147483647
INTMIN = -2147483648
DOUBLEMAX = 1.7976931348623157E308
if sys.version >= '3':
long = int
unicode = str
class EvaluatedResult():
"""
A testing result used to benchmark the model quality.
"""
def __init__(self, result, total_num, method):
"""
:param result: the validation result. i.e: top1 accuracy percentage.
:param total_num: the total processed records.
:param method: the validation method. i.e: Top1Accuracy
"""
self.result = result
self.total_num = total_num
self.method = method
class JTensor(object):
"""
A wrapper to easy our work when need to pass or return Tensor to/from Scala.
>>> import numpy as np
>>> from bigdl.util.common import JTensor
>>> np.random.seed(123)
>>>
"""
def __init__(self, storage, shape, bigdl_type="float", indices=None):
"""
:param storage: values in this tensor
:param shape: shape of this tensor
:param bigdl_type: numeric type
:param indices: if indices is provided, means this is a SparseTensor;
if not provided, means this is a DenseTensor
"""
if isinstance(storage, bytes) and isinstance(shape, bytes):
self.storage = np.frombuffer(storage, dtype=get_dtype(bigdl_type))
self.shape = np.frombuffer(shape, dtype=np.int32)
else:
self.storage = np.array(storage, dtype=get_dtype(bigdl_type))
self.shape = np.array(shape, dtype=np.int32)
if indices is None:
self.indices = None
elif isinstance(indices, bytes):
self.indices = np.frombuffer(indices, dtype=np.int32)
else:
assert isinstance(indices, np.ndarray), \
"indices should be a np.ndarray, not %s, %s" % (type(a_ndarray), str(indices))
self.indices = np.array(indices, dtype=np.int32)
self.bigdl_type = bigdl_type
@classmethod
def from_ndarray(cls, a_ndarray, bigdl_type="float"):
"""
Convert a ndarray to a DenseTensor which would be used in Java side.
>>> import numpy as np
>>> from bigdl.util.common import JTensor
>>> from bigdl.util.common import callBigDlFunc
>>> np.random.seed(123)
>>> data = np.random.uniform(0, 1, (2, 3)).astype("float32")
>>> result = JTensor.from_ndarray(data)
>>> print(result)
JTensor: storage: [[ 0.69646919 0.28613934 0.22685145]
[ 0.55131477 0.71946895 0.42310646]], shape: [2 3], float
>>> result
JTensor: storage: [[ 0.69646919 0.28613934 0.22685145]
[ 0.55131477 0.71946895 0.42310646]], shape: [2 3], float
>>> data_back = result.to_ndarray()
>>> (data == data_back).all()
True
>>> tensor1 = callBigDlFunc("float", "testTensor", JTensor.from_ndarray(data)) # noqa
>>> array_from_tensor = tensor1.to_ndarray()
>>> (array_from_tensor == data).all()
True
"""
if a_ndarray is None:
return None
assert isinstance(a_ndarray, np.ndarray), \
"input should be a np.ndarray, not %s" % type(a_ndarray)
return cls(a_ndarray,
a_ndarray.shape if a_ndarray.shape else (a_ndarray.size),
bigdl_type)
@classmethod
def sparse(cls, a_ndarray, i_ndarray, shape, bigdl_type="float"):
"""
Convert a three ndarray to SparseTensor which would be used in Java side.
For example:
a_ndarray = [1, 3, 2, 4]
i_ndarray = [[0, 0, 1, 2],
[0, 3, 2, 1]]
shape = [3, 4]
Present a dense tensor
[[ 1, 0, 0, 3],
[ 0, 0, 2, 0],
[ 0, 4, 0, 0]]
:param a_ndarray non-zero elements in this SparseTensor
:param i_ndarray zero-based indices for non-zero element
i_ndarray's shape should be (shape.size, a_ndarray.size)
And the i-th non-zero elements indices is i_ndarray[:, 1]
:param shape shape as a DenseTensor.
>>> import numpy as np
>>> from bigdl.util.common import JTensor
>>> from bigdl.util.common import callBigDlFunc
>>> np.random.seed(123)
>>> data = np.arange(1, 7).astype("float32")
>>> indices = np.arange(1, 7)
>>> shape = np.array([10])
>>> result = JTensor.sparse(data, indices, shape)
>>> result
JTensor: storage: [ 1. 2. 3. 4. 5. 6.], shape: [10] ,indices [1 2 3 4 5 6], float
>>> tensor1 = callBigDlFunc("float", "testTensor", result) # noqa
>>> array_from_tensor = tensor1.to_ndarray()
>>> expected_ndarray = np.array([0, 1, 2, 3, 4, 5, 6, 0, 0, 0])
>>> (array_from_tensor == expected_ndarray).all()
True
"""
if a_ndarray is None:
return None
assert isinstance(a_ndarray, np.ndarray), \
"values array should be a np.ndarray, not %s" % type(a_ndarray)
assert isinstance(i_ndarray, np.ndarray), \
"indices array should be a np.ndarray, not %s" % type(a_ndarray)
assert i_ndarray.size == a_ndarray.size * shape.size, \
"size of values and indices should match."
return cls(a_ndarray,
shape,
bigdl_type,
i_ndarray)
def to_ndarray(self):
"""
Transfer JTensor to ndarray.
As SparseTensor may generate an very big ndarray, so we don't support this function for SparseTensor.
:return: a ndarray
"""
assert self.indices is None, "sparseTensor to ndarray is not supported"
return np.array(self.storage, dtype=get_dtype(self.bigdl_type)).reshape(self.shape) # noqa
class RNG():
"""
generate tensor data with seed
"""
_picklable_classes = [
'LinkedList',
'SparseVector',
'DenseVector',
'DenseMatrix',
'Rating',
'LabeledPoint',
'Sample',
'EvaluatedResult',
'JTensor',
'JActivity'
]
def redire_spark_logs(bigdl_type="float", log_path=os.getcwd()+"/bigdl.log"):
"""
Redirect spark logs to the specified path.
:param bigdl_type: "double" or "float"
:param log_path: the file path to be redirected to; the default file is under the current workspace named `bigdl.log`.
"""
callBigDlFunc(bigdl_type, "redirectSparkLogs", log_path)
def show_bigdl_info_logs(bigdl_type="float"):
"""
Set BigDL log level to INFO.
:param bigdl_type: "double" or "float"
"""
callBigDlFunc(bigdl_type, "showBigDlInfoLogs")
def to_sample_rdd(x, y, numSlices=None):
"""
Conver x and y into RDD[Sample]
:param x: ndarray and the first dimension should be batch
:param y: ndarray and the first dimension should be batch
:param numSlices:
:return:
"""
sc = get_spark_context()
from bigdl.util.common import Sample
x_rdd = sc.parallelize(x, numSlices)
y_rdd = sc.parallelize(y, numSlices)
return x_rdd.zip(y_rdd).map(lambda item: Sample.from_ndarray(item[0], item[1]))
def get_spark_context(conf=None):
"""
Get the current active spark context and create one if no active instance
:param conf: combining bigdl configs into spark conf
:return: SparkContext
"""
if hasattr(SparkContext, "getOrCreate"):
with SparkContext._lock:
if SparkContext._active_spark_context is None:
spark_conf = create_spark_conf() if conf is None else conf
return SparkContext.getOrCreate(spark_conf)
else:
return SparkContext.getOrCreate()
else:
# Might have threading issue but we cann't add _lock here
# as it's not RLock in spark1.5;
if SparkContext._active_spark_context is None:
spark_conf = create_spark_conf() if conf is None else conf
return SparkContext(conf=spark_conf)
else:
return SparkContext._active_spark_context
def callBigDlFunc(bigdl_type, name, *args):
""" Call API in PythonBigDL """
jinstance = JavaCreator.instance(bigdl_type=bigdl_type).value
sc = get_spark_context()
api = getattr(jinstance, name)
return callJavaFunc(sc, api, *args)
def callJavaFunc(sc, func, *args):
""" Call Java Function """
args = [_py2java(sc, a) for a in args]
result = func(*args)
return _java2py(sc, result)
def _to_java_object_rdd(rdd):
""" Return a JavaRDD of Object by unpickling
It will convert each Python object into Java object by Pyrolite, whenever
the RDD is serialized in batch or not.
"""
rdd = rdd._reserialize(AutoBatchedSerializer(PickleSerializer()))
return \
rdd.ctx._jvm.org.apache.spark.bigdl.api.python.BigDLSerDe.pythonToJava(
rdd._jrdd, True)
def _py2java(sc, obj):
""" Convert Python object into Java """
if isinstance(obj, RDD):
obj = _to_java_object_rdd(obj)
elif isinstance(obj, DataFrame):
obj = obj._jdf
elif isinstance(obj, SparkContext):
obj = obj._jsc
elif isinstance(obj, (list, tuple)):
obj = ListConverter().convert([_py2java(sc, x) for x in obj],
sc._gateway._gateway_client)
elif isinstance(obj, dict):
result = {}
for (key, value) in obj.items():
result[key] = _py2java(sc, value)
obj = MapConverter().convert(result, sc._gateway._gateway_client)
elif isinstance(obj, JavaValue):
obj = obj.value
elif isinstance(obj, JavaObject):
pass
elif isinstance(obj, (int, long, float, bool, bytes, unicode)):
pass
else:
data = bytearray(PickleSerializer().dumps(obj))
obj = sc._jvm.org.apache.spark.bigdl.api.python.BigDLSerDe.loads(data)
return obj
def get_activation_by_name(activation_name, activation_id=None):
""" Convert to a bigdl activation layer
given the name of the activation as a string """
import bigdl.nn.layer as BLayer
activation = None
activation_name = activation_name.lower()
if activation_name == "tanh":
activation = BLayer.Tanh()
elif activation_name == "sigmoid":
activation = BLayer.Sigmoid()
elif activation_name == "hard_sigmoid":
activation = BLayer.HardSigmoid()
elif activation_name == "relu":
activation = BLayer.ReLU()
elif activation_name == "softmax":
activation = BLayer.SoftMax()
elif activation_name == "softplus":
activation = BLayer.SoftPlus(beta=1.0)
elif activation_name == "softsign":
activation = BLayer.SoftSign()
elif activation_name == "linear":
activation = BLayer.Identity()
else:
raise Exception("Unsupported activation type: %s" % activation_name)
if not activation_id:
activation.set_name(activation_id)
return activation
if __name__ == "__main__":
_test()
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] | 2.317957 | 5,268 |
#!/usr/bin/env python
# -*- encoding: utf-8 -*-
import os
import unittest
from functional_tests.data.atlas.skulls.run import AtlasSkulls
from functional_tests.data.atlas.brain_structures.run import AtlasBrainStructures
from functional_tests.data.atlas.digits.run import AtlasDigits
from functional_tests.data.regression.skulls.run import RegressionSkulls
TEST_MODULES = [AtlasSkulls, AtlasBrainStructures, AtlasDigits, RegressionSkulls]
if __name__ == '__main__':
main()
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] | 2.892216 | 167 |
class decoratorWithoutArguments(object):
'''
If there are no decorator arguments, the function to be decorated is passed
to the constructor.
'''
'''
Note:
1. The major constraint on the result of a decorator is that it be callable.
The __call__ method here achieves that.
2. __call__ is called every time the decorated function is called;
__init__is called only once during the 'construction' of the decorated
function.
'''
'''
The __call__ method is not called until the decorated function is called.
'''
@decoratorWithoutArguments
@decoratorWithoutArguments
@decoratorFunction
if __name__ == "__main__":
func1("test", "multiple", "args")
print '\n'
func1("another", "round", "of args")
print '\n'
func2()
print '\n'
func3()
print '\n'
print "end of example"
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28100,
2886,
198,
198,
31,
12501,
273,
1352,
22203,
628,
198,
361,
11593,
3672,
834,
6624,
366,
834,
12417,
834,
1298,
628,
220,
220,
220,
25439,
16,
7203,
9288,
1600,
366,
48101,
1600,
366,
22046,
4943,
198,
220,
220,
220,
3601,
705,
59,
77,
6,
198,
220,
220,
220,
25439,
16,
7203,
29214,
1600,
366,
744,
1600,
366,
1659,
26498,
4943,
198,
220,
220,
220,
3601,
705,
59,
77,
6,
198,
220,
220,
220,
25439,
17,
3419,
198,
220,
220,
220,
3601,
705,
59,
77,
6,
198,
220,
220,
220,
25439,
18,
3419,
628,
220,
220,
220,
3601,
705,
59,
77,
6,
198,
220,
220,
220,
3601,
366,
437,
286,
1672,
1,
198
] | 2.814935 | 308 |
from .aitextgen import aitextgen
from .TokenDataset import TokenDataset
from .tokenizers import train_tokenizer
import fire
def aitextgen_cli(**kwargs):
"""Entrypoint for the CLI"""
fire.Fire(
{
"encode": encode_cli,
"train": train_cli,
"generate": generate_cli,
"train_tokenizer": train_tokenizer_cli,
}
)
def encode_cli(file_path: str, **kwargs):
"""Encode + compress a dataset"""
TokenDataset(file_path, save_cache=True, **kwargs)
def train_cli(file_path: str, **kwargs):
"""Train on a dataset."""
ai = aitextgen(**kwargs)
from_cache = file_path.endswith(".tar.gz")
dataset = TokenDataset(file_path, from_cache=from_cache, **kwargs)
ai.train(dataset, **kwargs)
def generate_cli(to_file: bool = True, **kwargs):
"""Generate from a trained model, or download one if not present."""
ai = aitextgen(**kwargs)
if to_file:
ai.generate_to_file(**kwargs)
else:
ai.generate(**kwargs)
def train_tokenizer_cli(files: str, **kwargs):
"""Trains a tokenizer on the specified file."""
train_tokenizer(files, **kwargs)
| [
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8,
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220,
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220,
422,
62,
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62,
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7,
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284,
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220,
220,
220,
220,
220,
220,
257,
72,
13,
8612,
378,
62,
1462,
62,
7753,
7,
1174,
46265,
22046,
8,
198,
220,
220,
220,
2073,
25,
198,
220,
220,
220,
220,
220,
220,
220,
257,
72,
13,
8612,
378,
7,
1174,
46265,
22046,
8,
628,
198,
4299,
4512,
62,
30001,
7509,
62,
44506,
7,
16624,
25,
965,
11,
12429,
46265,
22046,
2599,
198,
220,
220,
220,
37227,
2898,
1299,
257,
11241,
7509,
319,
262,
7368,
2393,
526,
15931,
198,
220,
220,
220,
4512,
62,
30001,
7509,
7,
16624,
11,
12429,
46265,
22046,
8,
198
] | 2.34004 | 497 |
from LRL_main_arena.envs.LaRoboLiga_main import LaRoboLigaPs2Arena | [
6738,
406,
7836,
62,
12417,
62,
533,
2616,
13,
268,
14259,
13,
14772,
14350,
78,
43,
13827,
62,
12417,
1330,
4689,
14350,
78,
43,
13827,
12016,
17,
43199,
64
] | 2.275862 | 29 |
# BSD 3-Clause License; see https://github.com/scikit-hep/uproot4/blob/main/LICENSE
from __future__ import absolute_import
import pytest
import uproot
@pytest.mark.network
@pytest.mark.network
@pytest.mark.network
| [
2,
347,
10305,
513,
12,
2601,
682,
13789,
26,
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1378,
12567,
13,
785,
14,
36216,
15813,
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258,
79,
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15763,
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13,
27349,
628,
198,
31,
9078,
9288,
13,
4102,
13,
27349,
198
] | 2.719512 | 82 |
import numpy as np
module_masses = load_inputs("input.txt")
module_fuels = map(get_fuel_v2, module_masses)
total = sum(module_fuels)
print("Total: ", total)
| [
11748,
299,
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62,
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8,
198,
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14957,
25,
33172,
2472,
8,
198
] | 2.633333 | 60 |
#!/Users/sunyun/anaconda3/bin/python
import sys
import time
import utils
sys.path.append("/Users/sunyun/software/python")
if __name__ == "__main__":
team = Team("MRE")
team.add_member("Caroline", "McQuatt")
team.add_member("Dmitry", "Serpakov")
team.add_member("James", "Roland")
team.add_member("Jan", "Duzinkiwicz")
team.add_member("Lewis", "Elliot")
team.add_member("Mirco", "Padovan")
team.add_member("Mohamed", "Karnel")
team.add_member("Sherif", "Elian")
team.add_member("Sridhar", "Sundarraman")
team.add_member("Sunghee", "Yun")
team.add_data("Caroline", "Android", "11/2/17", "20% (3/5 modules)")
team.add_data("Caroline", "Android", "11/16/17", "33%")
team.add_data("Caroline", "Android", "1/5/18", "50%")
team.add_data("Caroline", "Android", "1/18/18", "ready for exam this week")
team.add_data("Caroline", "Android", "2/1/18", "ready for exam")
team.add_data("Caroline", "Android", "2/19/18", "ready for exam")
team.add_data("Caroline", "Android", "3/29/18", "ready for exam")
team.add_data("Caroline", "Android", "4/12/18", "want to do Sprint (w/o certificate)")
team.add_data("Caroline", "Android", "4/27/18", "starting Android Sprint on May 7th")
team.add_data("Caroline", "Android", "5/10/18", "started Android Sprint")
team.add_data("Dmitry", "Android", "11/2/17", "0%")
team.add_data("Dmitry", "Android", "11/16/17", "0%")
team.add_data("Dmitry", "Android", "1/5/18", "0%")
team.add_data("Dmitry", "Android", "1/18/18", "planning to start this week")
team.add_data("Dmitry", "iOS", "2/1/18", "40%")
team.add_data("Dmitry", "iOS", "2/19/18", "40%")
team.add_data("Dmitry", "iOS", "3/29/18", "40%")
team.add_data("Dmitry", "iOS", "4/12/18", "40%")
team.add_data("Dmitry", "iOS", "4/27/18", "40%")
team.add_data("James", "iOS", "11/2/17", "0%")
team.add_data("James", "iOS", "11/16/17", "0%")
team.add_data("James", "iOS", "1/5/18", "0%")
team.add_data("James", "iOS", "1/18/18", "0%")
team.add_data("James", "iOS", "2/1/18", "0%")
team.add_data("James", "iOS", "2/19/18", "0%")
team.add_data("James", "iOS", "3/29/18", "0%")
team.add_data("James", "iOS", "4/27/18", "0%")
team.add_data("Jan", "Android", "11/2/17", "1.437%")
team.add_data("Jan", "Android", "11/16/17", "1.437%")
team.add_data("Jan", "Android", "1/5/18", "1.437%")
team.add_data("Jan", "Android", "2/1/18", "on lesson 1.4")
team.add_data("Jan", "Android", "2/19/18", "on lesson 1.4")
team.add_data("Jan", "Android", "3/29/18", "on lesson 1.4")
team.add_data("Lewis", "iOS", "11/2/17", "0%")
team.add_data("Lewis", "iOS", "11/16/17", "0%")
team.add_data("Lewis", "iOS", "2/1/18", "20%")
team.add_data("Lewis", "iOS", "2/19/18", "20%")
team.add_data("Lewis", "iOS", "3/29/18", "20%")
team.add_data("Lewis", "iOS", "4/12/18", "20%")
team.add_data("Lewis", "iOS", "4/27/18", "20%")
team.add_data("Mirco", "Android", "11/2/17", "0%")
team.add_data("Mirco", "Android", "11/16/17", "25%")
team.add_data("Mirco", "Android", "1/5/18", "100% - ready for test")
team.add_data("Mirco", "Android", "1/18/18", "planning on taking test next week")
team.add_data("Mirco", "Android", "2/1/18", "100% - finished taking test")
team.add_data("Mirco", "Android", "2/19/18", "finished Sprint on Android!")
team.add_data("Mirco", "iOS", "3/29/18", "20%")
team.add_data("Mirco", "iOS", "4/12/18", "20%")
team.add_data("Mirco", "iOS", "4/27/18", "30%")
team.add_data("Mohamed", "Android", "11/2/17", "20%")
team.add_data("Mohamed", "Android", "11/16/17", "30-35%")
team.add_data("Mohamed", "Android", "1/5/18", "50%")
team.add_data("Mohamed", "Android", "1/18/18", "finished pdf. practice before the exam")
team.add_data("Mohamed", "Android", "2/1/18", "100% - planning to take certificate in Q1")
team.add_data("Mohamed", "Android", "3/29/18", "Gotten certificate and doing Sprint")
team.add_data("Sherif", "iOS", "11/2/17", "77.77%")
team.add_data("Sherif", "iOS", "11/16/17", "95%")
team.add_data("Sherif", "iOS", "1/5/18", "100% - ready for sprint (Feb)")
team.add_data("Sherif", "iOS", "2/1/18", "100% - planning to start sprint on Feb. 5th")
team.add_data("Sherif", "iOS", "2/19/18", "finished Sprint on iOS!")
team.add_data("Sridhar", "Android", "11/2/17", "50% planning on taking test 11/31")
team.add_data("Sridhar", "Android", "11/16/17", "50%")
team.add_data("Sridhar", "Android", "1/5/18", "100% - ready for sprint (March)")
team.add_data("Sridhar", "Android", "2/1/18", "100% - ready for sprint (March)")
team.add_data("Sridhar", "Android", "3/29/18", "starting Sprint on Android")
team.add_data("Sridhar", "Android", "4/27/18", "finished Sprint on Android")
team.add_data("Sunghee", "Android", "11/2/17", "0%")
team.add_data("Sunghee", "Android", "11/16/17", "0%")
team.add_data("Sunghee", "Android", "1/5/18", "0%")
team.add_data("Sunghee", "Android", "1/18/18", "5%")
team.add_data("Sunghee", "Android", "2/1/18", "5%")
team.add_data("Sunghee", "Android", "2/19/18", "5%")
team.add_data("Sunghee", "Android", "3/29/18", "5%")
team.add_data("Sunghee", "Android", "4/12/18", "5%")
team.add_data("Sunghee", "Android", "4/27/18", "5%")
team.add_data("Mirco", "iOS", "7/6/18", "50%")
team.write_to_wiki_by_name("mt_by_name.wtb")
# team.write_to_wiki_by_platform("mt_by_platform.wtb")
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220,
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220,
1074,
13,
13564,
62,
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62,
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62,
24254,
7203,
16762,
62,
1525,
62,
24254,
13,
46569,
65,
4943,
198
] | 2.226339 | 2,483 |
import numpy as np
from sklearn.base import BaseEstimator
def scaled_linspace(x: np.ndarray, y: np.ndarray, num: int, scaler: BaseEstimator) -> np.ndarray:
"""Generate a linspace, evenly spaced according to the normalization
Args:
x (np.ndarray): First point
y (np.ndarray): Sencond point
num (int): Number of points (in between the two points)
method (str): Normalization method
Returns:
np.ndarray: Sequence of points evenly spaced
"""
# Normalize the points
x = scaler.transform([x])[0]
y = scaler.transform([y])[0]
# Generate the linspace
ls = np.linspace(x, y, num=num + 1, endpoint=True)
# Unnormalize the points
ls = scaler.inverse_transform(ls)
return ls
| [
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7,
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220,
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198
] | 2.430769 | 325 |
from keras_classifiers import ffn1, ffn2, cnn1, cnn2, train_and_evaluate
from sklearn_classifiers import train_and_evaluate_all
import utils as u
print('\n\nEvaluating DNN Classifiers')
# train_and_evaluate(cnn1, u.FEATURE_SET_SPECS)
# train_and_evaluate(cnn2, u.FEATURE_SET_SPECS)
# train_and_evaluate(ffn1, u.FEATURE_SET_MEANS)
# train_and_evaluate(ffn2, u.FEATURE_SET_SPECS_NORM)
print('\n\nEvaluating Classifiers')
train_and_evaluate_all(u.FEATURE_SET_MEANS)
# train_and_evaluate_all(u.FEATURE_SET_SPECS_NORM) | [
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44,
8
] | 2.433962 | 212 |
# Generated by Django 2.0.2 on 2018-03-01 22:33
from django.db import migrations, models
import django.utils.timezone
| [
2,
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11340,
628
] | 2.926829 | 41 |
# Copyright 2019 Google LLC. 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.
"""Tests for tfx.extensions.google_cloud_ai_platform.runner."""
import copy
import importlib
import os
from typing import Any, Dict
from unittest import mock
from google.auth import credentials as auth_credentials
from google.cloud import aiplatform
from google.cloud.aiplatform import initializer
from google.cloud.aiplatform.compat.types import endpoint
from google.cloud.aiplatform_v1.services.endpoint_service import (
client as endpoint_service_client)
from google.cloud.aiplatform_v1beta1.types.custom_job import CustomJob
from google.cloud.aiplatform_v1beta1.types.job_state import JobState
from googleapiclient import errors
import httplib2
import tensorflow as tf
from tfx.extensions.google_cloud_ai_platform import prediction_clients
from tfx.extensions.google_cloud_ai_platform import runner
from tfx.extensions.google_cloud_ai_platform.trainer import executor
from tfx.utils import json_utils
from tfx.utils import telemetry_utils
from tfx.utils import version_utils
if __name__ == '__main__':
tf.test.main()
| [
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# -*- coding: utf-8 -*-
# ------------------------------------------------------------------------------
#
# Copyright 2018-2019 Fetch.AI Limited
#
# 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.
#
# ------------------------------------------------------------------------------
"""This module contains tests for decision_maker."""
import pytest
from aea_ledger_cosmos import CosmosCrypto
from aea_ledger_ethereum import EthereumCrypto
from aea_ledger_fetchai import FetchAICrypto
from aea.configurations.base import PublicId
from aea.crypto.registries import make_crypto, make_ledger_api
from aea.crypto.wallet import Wallet
from aea.decision_maker.base import DecisionMaker
from aea.decision_maker.default import DecisionMakerHandler
from aea.helpers.transaction.base import (
RawMessage,
RawTransaction,
SignedMessage,
Terms,
)
from aea.identity.base import Identity
from aea.protocols.base import Address, Message
from aea.protocols.dialogue.base import Dialogue as BaseDialogue
from packages.fetchai.protocols.signing.dialogues import SigningDialogue
from packages.fetchai.protocols.signing.dialogues import (
SigningDialogues as BaseSigningDialogues,
)
from packages.fetchai.protocols.signing.message import SigningMessage
from tests.conftest import (
COSMOS_PRIVATE_KEY_PATH,
ETHEREUM_PRIVATE_KEY_PATH,
FETCHAI_PRIVATE_KEY_PATH,
FETCHAI_TESTNET_CONFIG,
MAX_FLAKY_RERUNS,
get_wealth_if_needed,
)
class SigningDialogues(BaseSigningDialogues):
"""This class keeps track of all oef_search dialogues."""
def __init__(self, self_address: Address) -> None:
"""
Initialize dialogues.
:param self_address: the address of the entity for whom dialogues are maintained
:return: None
"""
def role_from_first_message( # pylint: disable=unused-argument
message: Message, receiver_address: Address
) -> BaseDialogue.Role:
"""Infer the role of the agent from an incoming/outgoing first message
:param message: an incoming/outgoing first message
:param receiver_address: the address of the receiving agent
:return: The role of the agent
"""
return SigningDialogue.Role.SKILL
BaseSigningDialogues.__init__(
self,
self_address=self_address,
role_from_first_message=role_from_first_message,
dialogue_class=SigningDialogue,
)
class BaseTestDecisionMaker:
"""Test the decision maker."""
@classmethod
def setup(
cls,
decision_maker_handler_cls=DecisionMakerHandler,
decision_maker_cls=DecisionMaker,
):
"""Initialise the decision maker."""
cls.wallet = Wallet(
{
CosmosCrypto.identifier: COSMOS_PRIVATE_KEY_PATH,
EthereumCrypto.identifier: ETHEREUM_PRIVATE_KEY_PATH,
FetchAICrypto.identifier: FETCHAI_PRIVATE_KEY_PATH,
}
)
cls.agent_name = "test"
cls.identity = Identity(
cls.agent_name,
addresses=cls.wallet.addresses,
public_keys=cls.wallet.public_keys,
default_address_key=FetchAICrypto.identifier,
)
cls.config = {}
cls.decision_maker_handler = decision_maker_handler_cls(
identity=cls.identity, wallet=cls.wallet, config=cls.config
)
cls.decision_maker = decision_maker_cls(cls.decision_maker_handler)
cls.tx_sender_addr = "agent_1"
cls.tx_counterparty_addr = "pk"
cls.info = {"some_info_key": "some_info_value"}
cls.ledger_id = FetchAICrypto.identifier
cls.decision_maker.start()
def test_decision_maker_config(self):
"""Test config property."""
assert self.decision_maker_handler.config == self.config
def test_decision_maker_execute_w_wrong_input(self):
"""Test the execute method with wrong input."""
with pytest.raises(ValueError):
self.decision_maker.message_in_queue.put_nowait("wrong input")
with pytest.raises(ValueError):
self.decision_maker.message_in_queue.put("wrong input")
def test_decision_maker_queue_access_not_permitted(self):
"""Test the in queue of the decision maker can not be accessed."""
with pytest.raises(ValueError):
self.decision_maker.message_in_queue.get()
with pytest.raises(ValueError):
self.decision_maker.message_in_queue.get_nowait()
with pytest.raises(ValueError):
self.decision_maker.message_in_queue.protected_get(
access_code="some_invalid_code"
)
@pytest.mark.flaky(reruns=MAX_FLAKY_RERUNS)
def test_handle_tx_signing_fetchai(self):
"""Test tx signing for fetchai."""
fetchai_api = make_ledger_api(
FetchAICrypto.identifier, **FETCHAI_TESTNET_CONFIG
)
sender_address = self.wallet.addresses["fetchai"]
fc2 = make_crypto(FetchAICrypto.identifier)
get_wealth_if_needed(sender_address, fetchai_api)
amount = 10000
transfer_transaction = fetchai_api.get_transfer_transaction(
sender_address=sender_address,
destination_address=fc2.address,
amount=amount,
tx_fee=1000,
tx_nonce="something",
)
signing_dialogues = SigningDialogues(
str(PublicId("author", "a_skill", "0.1.0"))
)
signing_msg = SigningMessage(
performative=SigningMessage.Performative.SIGN_TRANSACTION,
dialogue_reference=signing_dialogues.new_self_initiated_dialogue_reference(),
terms=Terms(
ledger_id=FetchAICrypto.identifier,
sender_address="pk1",
counterparty_address="pk2",
amount_by_currency_id={"FET": -1},
is_sender_payable_tx_fee=True,
quantities_by_good_id={"good_id": 10},
nonce="transaction nonce",
),
raw_transaction=RawTransaction(
FetchAICrypto.identifier, transfer_transaction
),
)
signing_dialogue = signing_dialogues.create_with_message(
"decision_maker", signing_msg
)
assert signing_dialogue is not None
self.decision_maker.message_in_queue.put_nowait(signing_msg)
signing_msg_response = self.decision_maker.message_out_queue.get(timeout=2)
recovered_dialogue = signing_dialogues.update(signing_msg_response)
assert recovered_dialogue is not None and recovered_dialogue == signing_dialogue
assert (
signing_msg_response.performative
== SigningMessage.Performative.SIGNED_TRANSACTION
)
assert type(signing_msg_response.signed_transaction.body) == dict
def test_handle_tx_signing_ethereum(self):
"""Test tx signing for ethereum."""
tx = {"gasPrice": 30, "nonce": 1, "gas": 20000}
signing_dialogues = SigningDialogues(
str(PublicId("author", "a_skill", "0.1.0"))
)
signing_msg = SigningMessage(
performative=SigningMessage.Performative.SIGN_TRANSACTION,
dialogue_reference=signing_dialogues.new_self_initiated_dialogue_reference(),
terms=Terms(
ledger_id=EthereumCrypto.identifier,
sender_address="pk1",
counterparty_address="pk2",
amount_by_currency_id={"FET": -1},
is_sender_payable_tx_fee=True,
quantities_by_good_id={"good_id": 10},
nonce="transaction nonce",
),
raw_transaction=RawTransaction(EthereumCrypto.identifier, tx),
)
signing_dialogue = signing_dialogues.create_with_message(
"decision_maker", signing_msg
)
assert signing_dialogue is not None
self.decision_maker.message_in_queue.put_nowait(signing_msg)
signing_msg_response = self.decision_maker.message_out_queue.get(timeout=2)
recovered_dialogue = signing_dialogues.update(signing_msg_response)
assert recovered_dialogue is not None and recovered_dialogue == signing_dialogue
assert (
signing_msg_response.performative
== SigningMessage.Performative.SIGNED_TRANSACTION
)
assert type(signing_msg_response.signed_transaction.body) == dict
def test_handle_tx_signing_unknown(self):
"""Test tx signing for unknown."""
tx = {}
signing_dialogues = SigningDialogues(
str(PublicId("author", "a_skill", "0.1.0"))
)
signing_msg = SigningMessage(
performative=SigningMessage.Performative.SIGN_TRANSACTION,
dialogue_reference=signing_dialogues.new_self_initiated_dialogue_reference(),
terms=Terms(
ledger_id="unknown",
sender_address="pk1",
counterparty_address="pk2",
amount_by_currency_id={"FET": -1},
is_sender_payable_tx_fee=True,
quantities_by_good_id={"good_id": 10},
nonce="transaction nonce",
),
raw_transaction=RawTransaction("unknown", tx),
)
signing_dialogue = signing_dialogues.create_with_message(
"decision_maker", signing_msg
)
assert signing_dialogue is not None
self.decision_maker.message_in_queue.put_nowait(signing_msg)
signing_msg_response = self.decision_maker.message_out_queue.get(timeout=2)
recovered_dialogue = signing_dialogues.update(signing_msg_response)
assert recovered_dialogue is not None and recovered_dialogue == signing_dialogue
assert signing_msg_response.performative == SigningMessage.Performative.ERROR
assert (
signing_msg_response.error_code
== SigningMessage.ErrorCode.UNSUCCESSFUL_TRANSACTION_SIGNING
)
def test_handle_message_signing_fetchai(self):
"""Test message signing for fetchai."""
message = b"0x11f3f9487724404e3a1fb7252a322656b90ba0455a2ca5fcdcbe6eeee5f8126d"
signing_dialogues = SigningDialogues(
str(PublicId("author", "a_skill", "0.1.0"))
)
signing_msg = SigningMessage(
performative=SigningMessage.Performative.SIGN_MESSAGE,
dialogue_reference=signing_dialogues.new_self_initiated_dialogue_reference(),
terms=Terms(
ledger_id=FetchAICrypto.identifier,
sender_address="pk1",
counterparty_address="pk2",
amount_by_currency_id={"FET": -1},
is_sender_payable_tx_fee=True,
quantities_by_good_id={"good_id": 10},
nonce="transaction nonce",
),
raw_message=RawMessage(FetchAICrypto.identifier, message),
)
signing_dialogue = signing_dialogues.create_with_message(
"decision_maker", signing_msg
)
assert signing_dialogue is not None
self.decision_maker.message_in_queue.put_nowait(signing_msg)
signing_msg_response = self.decision_maker.message_out_queue.get(timeout=2)
recovered_dialogue = signing_dialogues.update(signing_msg_response)
assert recovered_dialogue is not None and recovered_dialogue == signing_dialogue
assert (
signing_msg_response.performative
== SigningMessage.Performative.SIGNED_MESSAGE
)
assert type(signing_msg_response.signed_message) == SignedMessage
def test_handle_message_signing_ethereum(self):
"""Test message signing for ethereum."""
message = b"0x11f3f9487724404e3a1fb7252a322656b90ba0455a2ca5fcdcbe6eeee5f8126d"
signing_dialogues = SigningDialogues(
str(PublicId("author", "a_skill", "0.1.0"))
)
signing_msg = SigningMessage(
performative=SigningMessage.Performative.SIGN_MESSAGE,
dialogue_reference=signing_dialogues.new_self_initiated_dialogue_reference(),
terms=Terms(
ledger_id=EthereumCrypto.identifier,
sender_address="pk1",
counterparty_address="pk2",
amount_by_currency_id={"FET": -1},
is_sender_payable_tx_fee=True,
quantities_by_good_id={"good_id": 10},
nonce="transaction nonce",
),
raw_message=RawMessage(EthereumCrypto.identifier, message),
)
signing_dialogue = signing_dialogues.create_with_message(
"decision_maker", signing_msg
)
assert signing_dialogue is not None
self.decision_maker.message_in_queue.put_nowait(signing_msg)
signing_msg_response = self.decision_maker.message_out_queue.get(timeout=2)
recovered_dialogue = signing_dialogues.update(signing_msg_response)
assert recovered_dialogue is not None and recovered_dialogue == signing_dialogue
assert (
signing_msg_response.performative
== SigningMessage.Performative.SIGNED_MESSAGE
)
assert type(signing_msg_response.signed_message) == SignedMessage
def test_handle_message_signing_ethereum_deprecated(self):
"""Test message signing for ethereum deprecated."""
message = b"0x11f3f9487724404e3a1fb7252a3226"
signing_dialogues = SigningDialogues(
str(PublicId("author", "a_skill", "0.1.0"))
)
signing_msg = SigningMessage(
performative=SigningMessage.Performative.SIGN_MESSAGE,
dialogue_reference=signing_dialogues.new_self_initiated_dialogue_reference(),
terms=Terms(
ledger_id=EthereumCrypto.identifier,
sender_address="pk1",
counterparty_address="pk2",
amount_by_currency_id={"FET": -1},
is_sender_payable_tx_fee=True,
quantities_by_good_id={"good_id": 10},
nonce="transaction nonce",
),
raw_message=RawMessage(
EthereumCrypto.identifier, message, is_deprecated_mode=True
),
)
signing_dialogue = signing_dialogues.create_with_message(
"decision_maker", signing_msg
)
assert signing_dialogue is not None
self.decision_maker.message_in_queue.put_nowait(signing_msg)
signing_msg_response = self.decision_maker.message_out_queue.get(timeout=2)
recovered_dialogue = signing_dialogues.update(signing_msg_response)
assert recovered_dialogue is not None and recovered_dialogue == signing_dialogue
assert (
signing_msg_response.performative
== SigningMessage.Performative.SIGNED_MESSAGE
)
assert type(signing_msg_response.signed_message) == SignedMessage
assert signing_msg_response.signed_message.is_deprecated_mode
def test_handle_message_signing_unknown_and_two_dialogues(self):
"""Test message signing for unknown."""
message = b"0x11f3f9487724404e3a1fb7252a322656b90ba0455a2ca5fcdcbe6eeee5f8126d"
signing_dialogues = SigningDialogues(
str(PublicId("author", "a_skill", "0.1.0"))
)
signing_msg = SigningMessage(
performative=SigningMessage.Performative.SIGN_MESSAGE,
dialogue_reference=signing_dialogues.new_self_initiated_dialogue_reference(),
terms=Terms(
ledger_id="unknown",
sender_address="pk1",
counterparty_address="pk2",
amount_by_currency_id={"FET": -1},
is_sender_payable_tx_fee=True,
quantities_by_good_id={"good_id": 10},
nonce="transaction nonce",
),
raw_message=RawMessage("unknown", message),
)
signing_dialogue = signing_dialogues.create_with_message(
"decision_maker", signing_msg
)
assert signing_dialogue is not None
self.decision_maker.message_in_queue.put_nowait(signing_msg)
signing_msg_response = self.decision_maker.message_out_queue.get(timeout=2)
recovered_dialogue = signing_dialogues.update(signing_msg_response)
assert recovered_dialogue is not None and recovered_dialogue == signing_dialogue
assert signing_msg_response.performative == SigningMessage.Performative.ERROR
assert (
signing_msg_response.error_code
== SigningMessage.ErrorCode.UNSUCCESSFUL_MESSAGE_SIGNING
)
def test_handle_messages_from_two_dialogues_same_agent(self):
"""Test message signing for unknown."""
message = b"0x11f3f9487724404e3a1fb7252a322656b90ba0455a2ca5fcdcbe6eeee5f8126d"
signing_dialogues = SigningDialogues(
str(PublicId("author", "a_skill", "0.1.0"))
)
dialogue_reference = signing_dialogues.new_self_initiated_dialogue_reference()
signing_msg = SigningMessage(
performative=SigningMessage.Performative.SIGN_MESSAGE,
dialogue_reference=dialogue_reference,
terms=Terms(
ledger_id="unknown",
sender_address="pk1",
counterparty_address="pk2",
amount_by_currency_id={"FET": -1},
is_sender_payable_tx_fee=True,
quantities_by_good_id={"good_id": 10},
nonce="transaction nonce",
),
raw_message=RawMessage("unknown", message),
)
signing_dialogue = signing_dialogues.create_with_message(
"decision_maker", signing_msg
)
assert signing_dialogue is not None
self.decision_maker.message_in_queue.put_nowait(signing_msg)
signing_msg_response = self.decision_maker.message_out_queue.get(timeout=2)
assert signing_msg_response is not None
signing_dialogues = SigningDialogues(
str(PublicId("author", "a_skill", "0.1.0"))
)
signing_msg = SigningMessage(
performative=SigningMessage.Performative.SIGN_MESSAGE,
dialogue_reference=dialogue_reference,
terms=Terms(
ledger_id="unknown",
sender_address="pk1",
counterparty_address="pk2",
amount_by_currency_id={"FET": -1},
is_sender_payable_tx_fee=True,
quantities_by_good_id={"good_id": 10},
nonce="transaction nonce",
),
raw_message=RawMessage("unknown", message),
)
signing_dialogue = signing_dialogues.create_with_message(
"decision_maker", signing_msg
)
assert signing_dialogue is not None
with pytest.raises(Exception):
# Exception occurs because the same counterparty sends two identical dialogue references
self.decision_maker.message_out_queue.get(timeout=1)
# test twice; should work again even from same agent
signing_dialogues = SigningDialogues(
str(PublicId("author", "a_skill", "0.1.0"))
)
signing_msg = SigningMessage(
performative=SigningMessage.Performative.SIGN_MESSAGE,
dialogue_reference=signing_dialogues.new_self_initiated_dialogue_reference(),
terms=Terms(
ledger_id="unknown",
sender_address="pk1",
counterparty_address="pk2",
amount_by_currency_id={"FET": -1},
is_sender_payable_tx_fee=True,
quantities_by_good_id={"good_id": 10},
nonce="transaction nonce",
),
raw_message=RawMessage("unknown", message),
)
signing_dialogue = signing_dialogues.create_with_message(
"decision_maker", signing_msg
)
assert signing_dialogue is not None
self.decision_maker.message_in_queue.put_nowait(signing_msg)
signing_msg_response = self.decision_maker.message_out_queue.get(timeout=2)
assert signing_msg_response is not None
@classmethod
def teardown(cls):
"""Tear the tests down."""
cls.decision_maker.stop()
class TestDecisionMaker(BaseTestDecisionMaker):
"""Run test for default decision maker."""
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] | 2.189468 | 9,590 |
import algorithm_rgb as al
import os
import osgeo.gdal as gdal
import numpy as np
import json
input1 = './test_input/rgb_1_2_E.tif'
input2 = './test_input/rgb_40_11_W.tif'
meta = './meta.json'
# --------------------------------------------------
def test_input_files():
"""Test input files exist"""
assert os.path.isfile(input1)
assert os.path.isfile(input2)
# --------------------------------------------------
def test_get_red_green_blue_averages():
"""Test get_red_green_blue_averages"""
assert al.get_red_green_blue_averages(
read_input(input1)) == (166.8537142857143, 160.37885714285713,
139.89971428571428)
assert al.get_red_green_blue_averages(
read_input(input2)) == (109.85485714285714, 144.25085714285714, 90.381)
# --------------------------------------------------
def test_excess_greenness_index():
"""Test excess_greenness_index"""
assert al.excess_greenness_index(read_input(input1)) == 14.0
assert al.excess_greenness_index(read_input(input2)) == 88.27
# --------------------------------------------------
def test_green_leaf_index():
"""Test green_leaf_index"""
assert al.green_leaf_index(read_input(input1)) == 0.02
assert al.green_leaf_index(read_input(input2)) == 0.18
# --------------------------------------------------
def test_cive():
"""Test cive"""
assert al.cive(read_input(input1)) == 16.16
assert al.cive(read_input(input2)) == -14.96
# --------------------------------------------------
def test_normalized_difference_index():
"""Test normalized_difference_index"""
assert al.normalized_difference_index(read_input(input1)) == -1.53
assert al.normalized_difference_index(read_input(input2)) == 18.33
# --------------------------------------------------
def test_excess_red():
"""Test excess_red"""
assert al.excess_red(read_input(input1)) == 56.53
assert al.excess_red(read_input(input2)) == -1.44
# --------------------------------------------------
def test_exgr():
"""Test exgr"""
assert al.exgr(read_input(input1)) == -42.53
assert al.exgr(read_input(input2)) == 89.71
# --------------------------------------------------
def test_combined_indices_1():
"""Test combined_indices_1"""
assert al.combined_indices_1(read_input(input1)) == 30.16
assert al.combined_indices_1(read_input(input2)) == 73.31
# --------------------------------------------------
def test_combined_indices_2():
"""Test combined_indices_2"""
assert al.combined_indices_2(read_input(input1)) == 12.81
assert al.combined_indices_2(read_input(input2)) == 24.98
# --------------------------------------------------
def test_vegetative_index():
"""Test vegetative_index"""
assert al.vegetative_index(read_input(input1)) == 1.02
assert al.vegetative_index(read_input(input2)) == 1.4
# --------------------------------------------------
def test_ngrdi():
"""Test ngrdi"""
assert al.ngrdi(read_input(input1)) == -0.02
assert al.ngrdi(read_input(input2)) == 0.14
# --------------------------------------------------
def test_percent_green():
"""Test percent_green"""
assert al.percent_green(read_input(input1)) == 0.34
assert al.percent_green(read_input(input2)) == 0.42
# --------------------------------------------------
def test_calculate():
"""Test calculate"""
assert al.calculate(read_input(input1)) == [
14.0, 0.02, 16.16, -1.53, 56.53, -42.53, 30.16, 12.81, 1.02, -0.02,
0.34
]
assert al.calculate(read_input(input2)) == [
88.27, 0.18, -14.96, 18.33, -1.44, 89.71, 73.31, 24.98, 1.4, 0.14, 0.42
]
# --------------------------------------------------
def read_input(file) -> np.ndarray:
"""Run calculate on a file"""
if fh := gdal.Open(file):
pix = np.array(fh.ReadAsArray())
return np.rollaxis(pix, 0, 3)
# --------------------------------------------------
def test_meta():
"""Test meta"""
assert os.path.isfile(meta)
data = json.load(open(meta))
assert data['authors']
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] | 2.768506 | 1,486 |
from cnn_classifier_stepwise.base.cnn_classifier_stepwise_base import \
CnnStepwiseClassifierBaseDf
from self_supervised.network.flatten_mlp import FlattenMlpDropout
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] | 2.85 | 60 |
import Bio,gzip
from Bio import SeqIO
import pyteomics
from pyteomics import mass,fasta
import pyteomics.parser as pyt_parser
import pandas as pd
import numpy as np
import json,os
from tqdm import tqdm
from load_config import CONFIG
MAX_DATABASE_SIZE=100000000
DB_PEPTIDE_MINIMUM_LENGTH=CONFIG['DB_PEPTIDE_MINIMUM_LENGTH']#7
DB_PEPTIDE_MAXIMUM_LENGTH=CONFIG['DB_PEPTIDE_MAXIMUM_LENGTH']#42
MAX_MISSED_CLEAVAGES=CONFIG['MAX_MISSED_CLEAVAGES']#args.MAX_MISSED_CLEAVAGES
ENZYME=CONFIG['ENZYME']
SEMI_SPECIFIC_CLEAVAGE=CONFIG['SEMI_SPECIFIC_CLEAVAGE']
SAVE=True
SAVE_DB_AS_JSON=True
if "r'" in ENZYME:
ENZYME = ENZYME.replace("r'","")
ENZYME = ENZYME.replace("'","")
ENZYME = r'%s'%ENZYME
#FASTA_FILE = CONFIG['FASTA']
from collections import defaultdict
#if __name__ == '__main__':
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] | 2.257062 | 354 |
#!/usr/bin/env python
'''
Python and Ansible for Network Engineers
Week 2, Exercise 2
Write a script that connects using telnet to the pynet-rtr1 router. Execute
the 'show ip int brief' command on the router and return the output.
'''
import telnetlib
import time
import sys
TELNET_PORT = 23
TELNET_TIMEOUT = 6
def main():
'''
Write a script that connects to the lab pynet-rtr1, logs in, and executes
the 'show ip interface brief' command.
'''
ip_addr = "184.105.247.70"
userid = "pyclass"
password = "88newclass"
remote_conn = telnetlib.Telnet(ip_addr, TELNET_PORT, TELNET_TIMEOUT)
cmd = "show ip interface brief"
output = login(remote_conn, userid, password)
time.sleep(1)
remote_conn.read_very_eager()
output = send_commands(remote_conn, cmd)
print output
logout(remote_conn)
if __name__ == "__main__":
main()
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3419,
628
] | 2.582386 | 352 |
import sys
import time
import random
from menu import Menu
from game_engine import Console, Player
console = Console()
player = Player()
start = True
basement_suprise = ["demon", "open", "closed", "bear"]
sus_building = ["enemy_trap", "human_traffic", "smuggler"]
boat_stuff = ["tip over", "fight", "safe"]
truck_survive = ["no", "yes"]
# I know I don't need so many varibles but still I don't care
go_in = " "
choice = " "
name = " "
start_sim = " "
enter = " "
trust = " "
enter_tower_1 = " "
retry_input = " "
jump_1 = " "
wake_up = " "
escape = " "
bye = 0
# Function to exit the game
# put the intro here
# -------------------------------------------------------------------------------------------------------------------------------------------------------------------------
# Start part 0
# Start adventure
# -------------------------------------------------------------------------------------------------------------------------------------------------------------------------
# End part 0
# Start part 1
# ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
# RNG route
#-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------
# quick escape route
#------------------------------------------------------------------------------------------------------------------------------------------------------------------
# part 2 escape out of the country
#-------------------------------------------------------------------------------------------------------------------------------------------------------------
# part 3 New country
#------------------------------------------------------------------------------------------------------------------------------------------------------------------
# part 4 epilogue
# starts the game and menu
while start == True:
Menu.print_menu()
menu = console.check_answer("What do you want to do?", ["1", "intro", "start", "2", "skip", "quit", "3", "help", "4"])
print(" ")
if menu == ("1") or menu == ("intro") or menu == ("start"):
intro()
elif menu == ("2") or menu == ("skip"):
adventure()
elif menu == ("help") or menu == ("3"):
help()
elif menu == ("quit") or menu == ("4"):
quit() | [
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#!/usr/bin/python
import MySQLdb
import serial
import time
try:
con = _mysql.connect('localhost', 'sms_gat', 'sms_gat', 'sms_gateway')
con.query("SELECT VERSION()")
result = con.use_result()
print "MySQL version: %s" % \
result.fetch_row()[0]
except _mysql.Error, e:
print "Error %d: %s" % (e.args[0], e.args[1])
sys.exit(1)
finally:
print("ok")
con.close()
#3 leds netz sending error
# reset chip
# connect to serial 9600 baud check version; set baudrate to x
#reset pin toglle + wait 5 seconds
# AT -> OK //ping
# AT+CMGF=1 -> OK //check mode
# AT+CPIN="0000" -> //set pin wait 5 seconds
#open mysql check new messages
# AT -> ok // cehck pin
#AT+CMGF=1 //set sms mode
#AT+CSMP: 1,169,0,0 ->OK // set message mode
#AT+CMGS="+31638740161" -> > //set number
#message here +ctrl+z finsh
#+CMGS: 62 //message id store in db
#delete db entry
#set log
#set send_messages
#check new entry
| [
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"""
Example scenario for wartime negotiation.
Provides use cases for both modeling and simulating scenarios.
"""
import sys
from ConfigParser import SafeConfigParser
from argparse import ArgumentParser
import StringIO
from psychsim.pwl import *
from psychsim.reward import *
from psychsim.action import *
from psychsim.world import World,stateKey,actionKey,binaryKey,modelKey
from psychsim.agent import Agent
def scenarioCreationUseCase(enemy='Sylvania',model='powell',web=False,
fCollapse=None,sCollapse=None,maxRounds=15):
"""
An example of how to create a scenario
@param enemy: the name of the agent-controlled side, i.e., Freedonia's opponent (default: Sylvania)
@type enemy: str
@param model: which model do we use (default is "powell")
@type model: powell or slantchev
@param web: if C{True}, then create the web-based experiment scenario (default: C{False})
@type web: bool
@param fCollapse: the probability that Freedonia collapses (under powell, default: 0.1) or loses battle (under slantchev, default: 0.7)
@type fCollapse: float
@param sCollapse: the probability that Sylvania collapses, under powell (default: 0.1)
@type sCollapse: float
@param maxRounds: the maximum number of game rounds (default: 15)
@type maxRounds: int
@return: the scenario created
@rtype: L{World}
"""
# Handle defaults for battle probabilities, under each model
posLo = 0
posHi = 10
if fCollapse is None:
if model == 'powell':
fCollapse = 0.1
elif model == 'slantchev':
fCollapse = 0.7
if sCollapse is None:
sCollapse = 0.1
# Create scenario
world = World()
# Agents
free = Agent('Freedonia')
world.addAgent(free)
sylv = Agent(enemy)
world.addAgent(sylv)
# User state
world.defineState(free.name,'troops',int,lo=0,hi=50000,
description='Number of troops you have left')
free.setState('troops',40000)
world.defineState(free.name,'territory',int,lo=0,hi=100,
description='Percentage of disputed territory owned by you')
free.setState('territory',15)
world.defineState(free.name,'cost',int,lo=0,hi=50000,
description='Number of troops %s loses in an attack' % (free.name))
free.setState('cost',2000)
world.defineState(free.name,'position',int,lo=posLo,hi=posHi,
description='Current status of war (%d=%s is winner, %d=you are winner)' % (posLo,sylv.name,posHi))
free.setState('position',5)
world.defineState(free.name,'offered',int,lo=0,hi=100,
description='Percentage of disputed territory that %s last offered to you' % (sylv.name))
free.setState('offered',0)
if model == 'slantchev':
# Compute new value for territory only *after* computing new value for position
world.addDependency(stateKey(free.name,'territory'),stateKey(free.name,'position'))
# Agent state
world.defineState(sylv.name,'troops',int,lo=0,hi=500000,
description='Number of troops %s has left' % (sylv.name))
sylv.setState('troops',30000)
world.defineState(sylv.name,'cost',int,lo=0,hi=50000,
description='Number of troops %s loses in an attack' % (sylv.name))
sylv.setState('cost',2000)
world.defineState(sylv.name,'offered',int,lo=0,hi=100,
description='Percentage of disputed territory that %s last offered to %s' % (free.name,sylv.name))
sylv.setState('offered',0)
# World state
world.defineState(None,'treaty',bool,
description='Have the two sides reached an agreement?')
world.setState(None,'treaty',False)
# Stage of negotiation, illustrating the use of an enumerated state feature
world.defineState(None,'phase',list,['offer','respond','rejection','end','paused','engagement'],
description='The current stage of the negotiation game')
world.setState(None,'phase','paused')
# Game model, static descriptor
world.defineState(None,'model',list,['powell','slantchev'],
description='The model underlying the negotiation game')
world.setState(None,'model',model)
# Round of negotiation
world.defineState(None,'round',int,description='The current round of the negotiation')
world.setState(None,'round',0)
if not web:
# Relationship value
key = world.defineRelation(free.name,sylv.name,'trusts')
world.setFeature(key,0.)
# Game over if there is a treaty
world.addTermination(makeTree({'if': trueRow(stateKey(None,'treaty')),
True: True, False: False}))
# Game over if Freedonia has no territory
world.addTermination(makeTree({'if': thresholdRow(stateKey(free.name,'territory'),1),
True: False, False: True}) )
# Game over if Freedonia has all the territory
world.addTermination(makeTree({'if': thresholdRow(stateKey(free.name,'territory'),99),
True: True, False: False}))
# Game over if number of rounds exceeds limit
world.addTermination(makeTree({'if': thresholdRow(stateKey(None,'round'),maxRounds),
True: True, False: False}))
# Turn order: Uncomment the following if you want agents to act in parallel
# world.setOrder([set(world.agents.keys())])
# Turn order: Uncomment the following if you want agents to act sequentially
world.setOrder([free.name,sylv.name])
# User actions
freeBattle = free.addAction({'verb': 'attack','object': sylv.name})
for amount in range(20,100,20):
free.addAction({'verb': 'offer','object': sylv.name,'amount': amount})
if model == 'powell':
# Powell has null stages
freeNOP = free.addAction({'verb': 'continue'})
elif model == 'slantchev':
# Slantchev has both sides receiving offers
free.addAction({'verb': 'accept offer','object': sylv.name})
free.addAction({'verb': 'reject offer','object': sylv.name})
# Agent actions
sylvBattle = sylv.addAction({'verb': 'attack','object': free.name})
sylvAccept = sylv.addAction({'verb': 'accept offer','object': free.name})
sylvReject = sylv.addAction({'verb': 'reject offer','object': free.name})
if model == 'powell':
# Powell has null stages
sylvNOP = sylv.addAction({'verb': 'continue'})
elif model == 'slantchev':
# Slantchev has both sides making offers
for amount in range(10,100,10):
sylv.addAction({'verb': 'offer','object': free.name,'amount': amount})
# Restrictions on when actions are legal, based on phase of game
for action in filterActions({'verb': 'offer'},free.actions | sylv.actions):
agent = world.agents[action['subject']]
agent.setLegal(action,makeTree({'if': equalRow(stateKey(None,'phase'),'offer'),
True: True, # Offers are legal in the offer phase
False: False})) # Offers are illegal in all other phases
if model == 'powell':
# Powell has a special rejection phase
for action in [freeNOP,freeBattle]:
free.setLegal(action,makeTree({'if': equalRow(stateKey(None,'phase'),'rejection'),
True: True, # Attacking and doing nothing are legal only in rejection phase
False: False})) # Attacking and doing nothing are illegal in all other phases
# Once offered, agent can respond
if model == 'powell':
# Under Powell, only Sylvania has to respond, and it can attack
responses = [sylvBattle,sylvAccept,sylvReject]
elif model == 'slantchev':
# Under Slantchev, only accept/reject
responses = filterActions({'verb': 'accept offer'},free.actions | sylv.actions)
responses += filterActions({'verb': 'reject offer'},free.actions | sylv.actions)
for action in responses:
agent = world.agents[action['subject']]
agent.setLegal(action,makeTree({'if': equalRow(stateKey(None,'phase'),'respond'),
True: True, # Offeree must act in the response phase
False: False})) # Offeree cannot act in any other phase
if model == 'powell':
# NOP is legal in exactly opposite situations to all other actions
sylv.setLegal(sylvNOP,makeTree({'if': equalRow(stateKey(None,'phase'),'end'),
True: True, # Sylvania does not do anything in the null phase after Freedonia responds to rejection
False: False})) # Sylvania must act in its other phases
if model == 'slantchev':
# Attacking legal only under engagement phase
for action in filterActions({'verb': 'attack'},free.actions | sylv.actions):
agent = world.agents[action['subject']]
agent.setLegal(action,makeTree({'if': equalRow(stateKey(None,'phase'),'engagement'),
True: True, # Attacking legal only in engagement
False: False})) # Attacking legal every other phase
# Goals for Freedonia
goalFTroops = maximizeFeature(stateKey(free.name,'troops'))
free.setReward(goalFTroops,1.)
goalFTerritory = maximizeFeature(stateKey(free.name,'territory'))
free.setReward(goalFTerritory,1.)
# Goals for Sylvania
goalSTroops = maximizeFeature(stateKey(sylv.name,'troops'))
sylv.setReward(goalSTroops,1.)
goalSTerritory = minimizeFeature(stateKey(free.name,'territory'))
sylv.setReward(goalSTerritory,1.)
# Possible goals applicable to both
goalAgreement = maximizeFeature(stateKey(None,'treaty'))
# Silly goal, provided as an example of an achievement goal
goalAchieve = achieveFeatureValue(stateKey(None,'phase'),'respond')
# Horizons
if model == 'powell':
free.setAttribute('horizon',4)
sylv.setAttribute('horizon',4)
elif model == 'slantchev':
free.setAttribute('horizon',6)
sylv.setAttribute('horizon',6)
# Discount factors
free.setAttribute('discount',-1)
sylv.setAttribute('discount',-1)
# Levels of belief
free.setRecursiveLevel(2)
sylv.setRecursiveLevel(2)
# Dynamics of battle
freeTroops = stateKey(free.name,'troops')
freeTerr = stateKey(free.name,'territory')
sylvTroops = stateKey(sylv.name,'troops')
# Effect of fighting
for action in filterActions({'verb': 'attack'},free.actions | sylv.actions):
# Effect on troops (cost of battle)
tree = makeTree(addFeatureMatrix(freeTroops,stateKey(free.name,'cost'),-1.))
world.setDynamics(freeTroops,action,tree,enforceMin=not web)
tree = makeTree(addFeatureMatrix(sylvTroops,stateKey(sylv.name,'cost'),-1.))
world.setDynamics(sylvTroops,action,tree,enforceMin=not web)
if model == 'powell':
# Effect on territory (probability of collapse)
tree = makeTree({'distribution': [
({'distribution': [(setToConstantMatrix(freeTerr,100),1.-fCollapse), # Sylvania collapses, Freedonia does not
(noChangeMatrix(freeTerr), fCollapse)]}, # Both collapse
sCollapse),
({'distribution': [(setToConstantMatrix(freeTerr,0),fCollapse), # Freedonia collapses, Sylvania does not
(noChangeMatrix(freeTerr), 1.-fCollapse)]}, # Neither collapses
1.-sCollapse)]})
world.setDynamics(freeTerr,action,tree)
elif model == 'slantchev':
# Effect on position
pos = stateKey(free.name,'position')
tree = makeTree({'distribution': [(incrementMatrix(pos,1),1.-fCollapse), # Freedonia wins battle
(incrementMatrix(pos,-1),fCollapse)]}) # Freedonia loses battle
world.setDynamics(pos,action,tree)
# Effect on territory
tree = makeTree({'if': thresholdRow(pos,posHi-.5),
True: setToConstantMatrix(freeTerr,100), # Freedonia won
False: {'if': thresholdRow(pos,posLo+.5),
True: noChangeMatrix(freeTerr),
False: setToConstantMatrix(freeTerr,0)}}) # Freedonia lost
world.setDynamics(freeTerr,action,tree)
# Dynamics of offers
for index in range(2):
atom = Action({'subject': world.agents.keys()[index],'verb': 'offer',
'object': world.agents.keys()[1-index]})
if atom['subject'] == free.name or model != 'powell':
offer = stateKey(atom['object'],'offered')
amount = actionKey('amount')
tree = makeTree({'if': trueRow(stateKey(None,'treaty')),
True: noChangeMatrix(offer),
False: setToConstantMatrix(offer,amount)})
world.setDynamics(offer,atom,tree,enforceMax=not web)
# Dynamics of treaties
for action in filterActions({'verb': 'accept offer'},free.actions | sylv.actions):
# Accepting an offer means that there is now a treaty
key = stateKey(None,'treaty')
tree = makeTree(setTrueMatrix(key))
world.setDynamics(key,action,tree)
# Accepting offer sets territory
offer = stateKey(action['subject'],'offered')
territory = stateKey(free.name,'territory')
if action['subject'] == free.name:
# Freedonia accepts sets territory to last offer
tree = makeTree(setToFeatureMatrix(territory,offer))
world.setDynamics(freeTerr,action,tree)
else:
# Sylvania accepts sets territory to 1-last offer
tree = makeTree(setToFeatureMatrix(territory,offer,pct=-1.,shift=100.))
world.setDynamics(freeTerr,action,tree)
# Dynamics of phase
phase = stateKey(None,'phase')
roundKey = stateKey(None,'round')
# OFFER -> RESPOND
for index in range(2):
action = Action({'subject': world.agents.keys()[index],'verb': 'offer',
'object': world.agents.keys()[1-index]})
if action['subject'] == free.name or model != 'powell':
tree = makeTree(setToConstantMatrix(phase,'respond'))
world.setDynamics(phase,action,tree)
# RESPOND -> REJECTION or ENGAGEMENT
for action in filterActions({'verb': 'reject offer'},free.actions | sylv.actions):
if model == 'powell':
tree = makeTree(setToConstantMatrix(phase,'rejection'))
elif model == 'slantchev':
tree = makeTree(setToConstantMatrix(phase,'engagement'))
world.setDynamics(phase,action,tree)
# accepting -> OFFER
for action in filterActions({'verb': 'accept offer'},free.actions | sylv.actions):
tree = makeTree(setToConstantMatrix(phase,'offer'))
world.setDynamics(phase,action,tree)
# attacking -> OFFER
for action in filterActions({'verb': 'attack'},free.actions | sylv.actions):
tree = makeTree(setToConstantMatrix(phase,'offer'))
world.setDynamics(phase,action,tree)
if action['subject'] == sylv.name or model == 'slantchev':
tree = makeTree(incrementMatrix(roundKey,1))
world.setDynamics(roundKey,action,tree)
if model == 'powell':
# REJECTION -> END
for atom in [freeNOP,freeBattle]:
tree = makeTree(setToConstantMatrix(phase,'end'))
world.setDynamics(phase,atom,tree)
# END -> OFFER
atom = Action({'subject': sylv.name,'verb': 'continue'})
tree = makeTree(setToConstantMatrix(phase,'offer'))
world.setDynamics(phase,atom,tree)
tree = makeTree(incrementMatrix(roundKey,1))
world.setDynamics(roundKey,atom,tree)
if not web:
# Relationship dynamics: attacking is bad for trust
atom = Action({'subject': sylv.name,'verb': 'attack','object': free.name})
key = binaryKey(free.name,sylv.name,'trusts')
tree = makeTree(approachMatrix(key,0.1,-1.))
world.setDynamics(key,atom,tree)
# Handcrafted policy for Freedonia
# free.setPolicy(makeTree({'if': equalRow('phase','respond'),
# # Accept an offer greater than 50
# True: {'if': thresholdRow(stateKey(free.name,'offered'),50),
# True: Action({'subject': free.name,'verb': 'accept offer','object': sylv.name}),
# False: Action({'subject': free.name,'verb': 'reject offer','object': sylv.name})},
# False: {'if': equalRow('phase','engagement'),
# # Attack during engagement phase
# True: Action({'subject': free.name,'verb': 'attack','object': sylv.name}),
# # Agent decides how what to do otherwise
# False: False}}))
# Mental models of enemy
# Example of creating a model with incorrect reward all at once (a version of Freedonia who cares about reaching agreement as well)
# sylv.addModel('false',R={goalSTroops: 10.,goalSTerritory: 1.,goalAgreement: 1.},
# rationality=1.,selection='distribution',parent=True)
# Example of creating a model with incorrect beliefs
sylv.addModel('false',rationality=10.,selection='distribution',parent=True)
key = stateKey(free.name,'position')
# Sylvania believes position to be fixed at 3
sylv.setBelief(key,3,'false')
# Freedonia is truly unsure about position (50% chance of being 7, 50% of being 3)
world.setModel(free.name,True)
free.setBelief(key,Distribution({7: 0.5,3: 0.5}),True)
# Observations about military position
tree = makeTree({'if': thresholdRow(key,1),
True: {'if': thresholdRow(key,9),
True: {'distribution': [(KeyedVector({key: 1}),0.9),
(KeyedVector({key: 1,CONSTANT: -1}),0.1)]},
False: {'distribution': [(KeyedVector({key: 1}),0.8),
(KeyedVector({key: 1,CONSTANT: -1}),0.1),
(KeyedVector({key: 1,CONSTANT: 1}),0.1)]}},
False: {'distribution': [(KeyedVector({key: 1}),0.9),
(KeyedVector({key: 1,CONSTANT: 1}),0.1)]}})
free.defineObservation(key,tree)
# Example of setting model parameters separately
sylv.addModel('true',parent=True)
sylv.setAttribute('rationality',10.,'true') # Override real agent's rationality with this value
sylv.setAttribute('selection','distribution','true')
world.setMentalModel(free.name,sylv.name,{'false': 0.9,'true': 0.1})
# Goal of fooling Sylvania
goalDeception = achieveFeatureValue(modelKey(sylv.name),sylv.model2index('false'))
return world
def fitWorld(world):
"""
Piecewise linear compilation of Freedonia's policy
"""
for agent in world.agents.values():
if agent.name == 'Freedonia':
free = agent
else:
sylv = agent
world.setState(None,'phase','offer')
state = world.state.domain()[0]
freeModel = world.getModel(free.name,state)
beliefs = free.getBelief(state,freeModel)
# Compute transition trees
T = {}
for agent in world.agents.values():
for action in agent.actions:
T[action] = None
for keys in world.evaluationOrder:
result = None
for key in keys:
dynamics = world.getDynamics(key,action)
if dynamics:
# Use existing tree
assert len(dynamics) == 1
dynamics = dynamics[0]
else:
# Create identity tree
dynamics = KeyedTree(noChangeMatrix(key))
if result is None:
result = dynamics
else:
result += dynamics
result += KeyedTree(noChangeMatrix(CONSTANT))
if T[action] is None:
T[action] = result
else:
T[action] = result*T[action]
# Compute policy trees for the other agent
models = {}
for agent in world.agents.values():
models[agent.name] = set()
for agent in world.agents.values():
for vector in beliefs.domain():
model = world.getModel(agent.name,vector)
ancestor = agent.findAttribute('R',model)
models[agent.name].add(ancestor)
if len(models[agent.name]) == 0:
# No beliefs about models found, assume True model
models[agent.name].add(True)
for agent in world.agents.values():
for model in models[agent.name]:
R = sum(agent.getAttribute('R',model),KeyedTree(KeyedVector()))
agent.models[model]['policy'] = []
policy = agent.models[model]['policy']
for horizon in range(1,agent.getAttribute('horizon',model)+1):
# Dynamic programming of policies
if len(policy) < horizon:
# Policy tree for this horizon is missing
legal = {}
actions = []
# Process legality conditions
for action in agent.actions:
try:
legal[action] = agent.legal[action]
except KeyError:
legal[action] = KeyedTree(True)
# Compute value functions for each action
if horizon > 1:
raise NotImplementedError,'Backup step is missing'
V = {}
for action in agent.actions:
V[action] = R*T[action]
V[action] = legal[action].replace(True,V[action])
V[action] = V[action].expectation()
V[action] = V[action].map(lambda leaf: {'vector': leaf,'action': action} if isinstance(leaf,KeyedVector) else leaf)
# Build up a policy
policy.append(None)
for action in agent.actions:
if policy[horizon-1] is None:
policy[horizon-1] = V[action]
else:
policy[horizon-1] = policy[horizon-1].max(V[action])
Vstar = policy[horizon-1].map(lambda leaf: leaf['vector'] if isinstance(leaf,dict) else leaf)
policy[horizon-1] = policy[horizon-1].map(lambda leaf: leaf['action']
if isinstance(leaf,dict) else leaf)
# print 'Unpruned:'
policy[horizon-1].minimizePlanes()
# print policy[horizon-1]
pruned = policy[horizon-1].prune()
# print 'Pruned:'
print pruned
# # Verify pruning
# world.setFeature('phase','respond',beliefs)
# world.setState('Freedonia','territory',72,beliefs)
# for offer in range(50,100,3):
# world.setState(agent.name,'offered',offer,beliefs)
# vector = beliefs.domain()[0]
# print offer
# print policy[horizon-1][vector],pruned[vector]
# assert policy[horizon-1][vector] == pruned[vector]
print free.models[freeModel]['beliefs']
break
sys.exit(0)
def scenarioSimulationUseCase(world,offer=0,rounds=1,debug=1,model='powell'):
"""
@param offer: the initial offer for Freedonia to give (default is none)
@type offer: int
@param rounds: the number of complete rounds, where a round is two turns each, following Powell (default is 1)
@type rounds: int
@param debug: the debug level to use in explanation (default is 1)
@type debug: int
"""
testMode = isinstance(debug,dict)
if testMode:
buf = StringIO.StringIO()
debug[offer] = buf
debug = 0
for agent in world.agents.values():
if agent.name == 'Freedonia':
free = agent
else:
sylv = agent
world.setState(None,'phase','offer')
if model == 'powell':
steps = 4
else:
assert model == 'slantchev'
steps = 3
if debug > 0:
world.printState(beliefs=True)
for t in range(rounds):
for step in range(steps):
assert len(world.state) == 1
phase = world.getState(None,'phase').expectation()
state = world.state.domain()[0]
if not world.terminated(state):
if t == 0 and phase == 'offer' and offer > 0:
# Force Freedonia to make low offer in first step
outcome = world.step({free.name: Action({'subject':free.name,'verb':'offer','object': sylv.name,'amount': offer})})
world.explain(outcome,debug)
else:
# Free to choose
outcome = world.step()
world.explain(outcome,debug)
if testMode:
if (t == 0 and step == 1) or (t == 1 and step == 0):
for entry in outcome:
world.explainAction(entry,buf,1)
world.state.select()
if not testMode and debug > 0:
world.printState(beliefs=True)
for agent in world.agents.values():
print agent.name,len(agent.models)
assert len(world.state) == 1
phase = world.getState(None,'phase').expectation()
if phase == 'offer':
# Looped around
break
def findThreshold(scenario,t,model='powell',position=0):
"""
Finds the threshold at which the agent will accept the offer"""
if model == 'slantchev':
# Find counteroffer in this state
actions = []
while len(actions) < 2:
world = World(scenario)
world.setState(None,'round',t)
world.setState('Freedonia','position',position)
entry = {}
scenarioSimulationUseCase(world,20,2,entry,model)
actions = entry[20].getvalue().split('\n')[:-1]
entry[20].close()
amount = int(actions[1].split('-')[-1])
print 'Time: %d, Position %d -> Offer %d%%' % (t,position,amount)
# Compute acceptance threshold
offers = [50]
index = 0
entry = {}
while True:
world = World(scenario)
world.setState(None,'round',t)
if model == 'slantchev':
world.setState('Freedonia','position',position)
scenarioSimulationUseCase(world,offers[index],1,entry,model)
actions = entry[offers[index]].getvalue().split('\n')[:-1]
entry[offers[index]].close()
entry[offers[index]] = actions[0].split('-')[1].split()[0]
if entry[offers[index]] == 'accept':
# Try a lower offer
if index > 0:
down = offers[index-1]
assert entry[down] != 'accept'
else:
down = 0
new = (offers[index]+down) / 2
if entry.has_key(new):
if entry[new] != 'accept':
new += 1
break
else:
offers.insert(index,new)
else:
assert entry[offers[index]] in ['reject','attack']
# Try a higher offer
try:
up = offers[index+1]
assert entry[up] == 'accept'
except IndexError:
up = 100
new = (offers[index]+up) / 2
if entry.has_key(new):
break
else:
offers.insert(index+1,new)
index += 1
return new
def play(world,debug=1):
"""
Modify Freedonia to play autonomously and simulate
"""
for agent in world.agents.values():
if agent.name == 'Freedonia':
free = agent
else:
sylv = agent
for amount in range(10,100,20):
action = Action({'verb': 'offer','object': sylv.name,'amount': amount})
free.addAction(action)
action = Action({'verb': 'offer','object': free.name,'amount': amount})
sylv.addAction(action)
for action in filterActions({'verb': 'offer'},free.actions | sylv.actions):
actor = world.agents[action['subject']]
if not actor.legal.has_key(action):
actor.setLegal(action,makeTree({'if': equalRow(stateKey(None,'phase'),'offer'),
True: True, # Offers are legal in the offer phase
False: False})) # Offers are illegal in all other phases
model = world.getState(None,'model').domain()[0]
start = world.getState(free.name,'territory').expectation()
print model,start
scenarioSimulationUseCase(world,offer=0,rounds=15,debug=debug,model=model)
def findPolicies(args):
"""
Wrapper for finding agent offers and acceptance thresholds
"""
results = []
search = (30,40,1)
for t in range(args['rounds']):
entry = {}
if args['model'] == 'slantchev':
for position in range(1,10):
subresult = []
results.append(subresult)
subresult.append(entry)
thresh = findThreshold(args['output'],t,args['model'],position)
print 'Time %d, Position %d -> Accept if > %d%%' % (t,position,thresh)
else:
results.append(entry)
print 'Time %d -> Accept if > %d%%' %(t,findThreshold(args['output'],t))
if __name__ == '__main__':
# Grab command-line arguments
parser = ArgumentParser()
# Optional argument that sets the filename for the output file
parser.add_argument('-o',action='store',
dest='output',default='default',
help='scenario file [default: %(default)s]')
group = parser.add_argument_group('Creation Options','Control the parameters of the created scenario.')
# Optional argument that sets the theoretical model
group.add_argument('-m',action='store',
dest='model',choices=['powell','slantchev'],default='powell',
help='theoretical model for the game [default: %(default)s]')
# Optional argument that sets the cost of battle to Freedonia
group.add_argument('-f',action='store',
dest='fcost',type=int,default=2000,
help='cost of battle to Freedonia [default: %(default)s]')
# Optional argument that sets the cost of battle to Sylvania
group.add_argument('-s',action='store',
dest='scost',type=int,default=1000,
help='cost of battle to enemy [default: %(default)s]')
# Optional argument that sets the initial amount of territory owned by Freedonia
group.add_argument('-i','--initial',action='store',
dest='initial',type=int,default=13,
help='Freedonia\'s initial territory percentage [default: %(default)s]')
# Optional argument that sets Freedonia's initial military positional advantage
group.add_argument('-p','--position',action='store',
dest='position',type=int,default=3,
help='Freedonia\'s initial positional advantage [default: %(default)s]')
# Optional argument that sets the name of the enemy country
group.add_argument('-e',action='store',
dest='enemy',default='Sylvania',
help='Name of the enemy country [default: %(default)s]')
# Optional argument that sets the name of the disputed region
group.add_argument('--region',action='store',
dest='region',default='Trentino',
help='Name of the region under dispute [default: %(default)s]')
# Optional argument that sets the maximum number of rounds to play
group.add_argument('-r',action='store',
dest='rounds',type=int,default=15,
help='Maximum number of rounds to play [default: %(default)s]')
# Optional argument that sets Freedonia's initial troops
group.add_argument('--freedonia-troops',action='store',
dest='ftroops',type=int,default=40000,
help='number of Freedonia troops [default: %(default)s]')
# Optional argument that sets Sylvania's initial troops
group.add_argument('--enemy-troops',action='store',
dest='stroops',type=int,default=30000,
help='number of enemy troops [default: %(default)s]')
# Optional argument that determines whether to generate models for Web platform
group.add_argument('-w','--web',action='store_true',
dest='web',default=False,
help='generate Web version if set [default: %(default)s]')
group = parser.add_argument_group('Algorithm Options','Control the algorithms to apply to the agents.')
# Optional argument that determines whether to use value iteration to create Freedonia's policy
group.add_argument('-c','--compiled',action='store_true',
dest='compiled',default=False,
help='use value iteration for Freedonia [default: %(default)s]')
# Optional argument that determines whether to use PWL compilation of Freedonia's policy
group.add_argument('--fitting',action='store_true',
dest='fitting',default=False,
help='use PWL compilation and fitting for Freedonia [default: %(default)s]')
group = parser.add_argument_group('Simulation Options','Control the simulation of the created scenario.')
# Optional argument that sets the level of explanations when running the simulation
group.add_argument('-d',action='store',
dest='debug',type=int,default=1,
help='level of explanation detail [default: %(default)s]')
# Optional argument that sets the initial offer that Freedonia will make
group.add_argument('-a',action='store',
dest='amount',type=int,default=0,
help='Freedonia\'s first offer amount')
# Optional argument that sets the number of time steps to simulate
group.add_argument('-t','--time',action='store',
dest='time',type=int,default=1,
help='number of time steps to simulate [default: %(default)s]')
group = parser.add_argument_group('Creation Options','Control the parameters of the created scenario.')
args = vars(parser.parse_args())
world = scenarioCreationUseCase(args['enemy'],maxRounds=args['rounds'],model=args['model'],
web=args['web'])
# Initialize state values based on command-line arguments
world.agents['Freedonia'].setState('troops',args['ftroops'])
world.agents['Freedonia'].setState('territory',args['initial'])
world.agents['Freedonia'].setState('position',args['position'])
world.agents['Freedonia'].setState('cost',args['fcost'])
world.agents[args['enemy']].setState('troops',args['stroops'])
world.agents[args['enemy']].setState('cost',args['scost'])
if args['compiled']:
compileWorld(world)
if args['fitting']:
fitWorld(world)
# Create configuration file
config = SafeConfigParser()
# Specify game options for web interface
config.add_section('Game')
config.set('Game','rounds','%d' % (args['rounds']))
config.set('Game','user','Freedonia')
config.set('Game','agent',args['enemy'])
config.set('Game','region',args['region'])
if args['model'] == 'powell':
# Battle is optional under Powell
config.set('Game','battle','optional')
elif args['model'] == 'slantchev':
# Battle is mandatory under Slantchev
config.set('Game','battle','mandatory')
# Specify which state features are visible in web interface
config.add_section('Visible')
features = ['territory','troops']
if args['model'] == 'slantchev':
features.append('position')
for feature in features:
config.set('Visible',feature,'yes')
# Specify descriptions of actions for web interface
config.add_section('Actions')
config.set('Actions','offer','Propose treaty where %s gets <action:amount>%%%% of total disputed territory' % (args['enemy']))
config.set('Actions','attack','Attack %s' % (args['enemy']))
config.set('Actions','accept offer','Accept offer of <Freedonia:offered>%% of total disputed territory')
config.set('Actions','reject offer','Reject offer of <Freedonia:offered>%% of total disputed territory')
config.set('Actions','continue','Continue to next round of negotiation without attacking')
config.set('Actions','%s offer' % (args['enemy']),'offer <action:amount>%%')
config.set('Actions','%s accept offer' % (args['enemy']),
'Accept offer of <%s:offered>%%%% of total disputed territory' % (args['enemy']))
config.set('Actions','%s reject offer' % (args['enemy']),
'Reject offer of <%s:offered>%%%% of total disputed territory' % (args['enemy']))
# Specify what changes are displayed
config.add_section('Change')
config.set('Change','troops','yes')
if args['model'] == 'slantchev':
config.set('Change','position','yes')
# Specify links
config.add_section('Links')
config.set('Links','survey','http://www.curiouslab.com/clsurvey/index.php?sid=39345&lang=en')
config.set('Links','scenarios','8839,1308,2266,5538')
f = open('%s.cfg' % (args['output']),'w')
config.write(f)
f.close()
# Save scenario to compressed XML file
world.save(args['output'])
# Test saved scenario
world = World(args['output'])
scenarioSimulationUseCase(world,args['amount'],args['time'],args['debug'],args['model'])
# findPolicies(args)
# world.printState(world.agents[args['enemy']].getBelief(world.state.domain()[0],'false'))
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5509,
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7,
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434,
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7,
744,
9218,
11,
16,
4008,
198,
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220,
220,
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220,
220,
220,
220,
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13,
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35,
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7,
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11,
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8,
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220,
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1303,
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2849,
4613,
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198,
220,
220,
220,
220,
220,
220,
220,
329,
22037,
287,
685,
5787,
45,
3185,
11,
5787,
24064,
5974,
198,
220,
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220,
220,
220,
220,
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220,
220,
220,
220,
5509,
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7,
2617,
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7,
40715,
4032,
437,
6,
4008,
198,
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220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
995,
13,
2617,
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4989,
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7,
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11,
37696,
11,
21048,
8,
198,
220,
220,
220,
220,
220,
220,
220,
1303,
23578,
4613,
18562,
1137,
198,
220,
220,
220,
220,
220,
220,
220,
22037,
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220,
7561,
15090,
6,
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827,
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13,
3672,
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705,
43043,
6,
30072,
198,
220,
220,
220,
220,
220,
220,
220,
5509,
796,
787,
27660,
7,
2617,
2514,
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7,
40715,
4032,
47895,
6,
4008,
198,
220,
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220,
220,
220,
220,
220,
995,
13,
2617,
35,
4989,
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7,
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11,
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11,
21048,
8,
198,
220,
220,
220,
220,
220,
220,
220,
5509,
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787,
27660,
7,
24988,
434,
46912,
7,
744,
9218,
11,
16,
4008,
198,
220,
220,
220,
220,
220,
220,
220,
995,
13,
2617,
35,
4989,
873,
7,
744,
9218,
11,
37696,
11,
21048,
8,
628,
198,
220,
220,
220,
611,
407,
3992,
25,
198,
220,
220,
220,
220,
220,
220,
220,
1303,
39771,
17262,
25,
9274,
318,
2089,
329,
3774,
198,
220,
220,
220,
220,
220,
220,
220,
22037,
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7561,
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6,
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13,
3672,
4032,
19011,
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705,
20358,
41707,
15252,
10354,
1479,
13,
3672,
30072,
198,
220,
220,
220,
220,
220,
220,
220,
1994,
796,
13934,
9218,
7,
5787,
13,
3672,
11,
9163,
13,
3672,
4032,
38087,
82,
11537,
198,
220,
220,
220,
220,
220,
220,
220,
5509,
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787,
27660,
7,
21064,
620,
46912,
7,
2539,
11,
15,
13,
16,
12095,
16,
2014,
8,
198,
220,
220,
220,
220,
220,
220,
220,
995,
13,
2617,
35,
4989,
873,
7,
2539,
11,
37696,
11,
21048,
8,
198,
220,
220,
220,
1303,
7157,
39160,
2450,
329,
38728,
11339,
198,
2,
220,
220,
220,
1479,
13,
2617,
36727,
7,
15883,
27660,
15090,
6,
361,
10354,
4961,
25166,
10786,
40715,
41707,
5546,
33809,
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,
220,
220,
220,
220,
1303,
21699,
281,
2897,
3744,
621,
2026,
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,
220,
220,
220,
220,
6407,
25,
1391,
6,
361,
10354,
11387,
25166,
7,
5219,
9218,
7,
5787,
13,
3672,
4032,
2364,
1068,
33809,
1120,
828,
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,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
6407,
25,
7561,
15090,
6,
32796,
10354,
1479,
13,
3672,
4032,
19011,
10354,
705,
13635,
2897,
41707,
15252,
10354,
827,
6780,
13,
3672,
92,
828,
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,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
10352,
25,
7561,
15090,
6,
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1479,
13,
3672,
4032,
19011,
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705,
260,
752,
2897,
41707,
15252,
10354,
827,
6780,
13,
3672,
30072,
5512,
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,
220,
220,
220,
220,
10352,
25,
1391,
6,
361,
10354,
4961,
25166,
10786,
40715,
41707,
1516,
5082,
33809,
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,
220,
220,
220,
220,
1303,
8307,
1141,
12352,
7108,
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,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
6407,
25,
7561,
15090,
6,
32796,
10354,
1479,
13,
3672,
4032,
19011,
10354,
705,
20358,
41707,
15252,
10354,
827,
6780,
13,
3672,
92,
828,
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,
220,
220,
220,
220,
1303,
15906,
13267,
703,
644,
284,
466,
4306,
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,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
10352,
25,
10352,
11709,
4008,
198,
220,
220,
220,
220,
220,
220,
220,
1303,
21235,
4981,
286,
4472,
198,
220,
220,
220,
220,
220,
220,
220,
1303,
17934,
286,
4441,
257,
2746,
351,
11491,
6721,
477,
379,
1752,
357,
64,
2196,
286,
38728,
11339,
508,
16609,
546,
8978,
4381,
355,
880,
8,
198,
220,
220,
220,
220,
220,
220,
220,
1303,
827,
6780,
13,
2860,
17633,
10786,
9562,
3256,
49,
34758,
35231,
2257,
305,
2840,
25,
838,
1539,
35231,
2257,
263,
799,
652,
25,
352,
1539,
35231,
10262,
10237,
25,
352,
13,
5512,
198,
220,
220,
220,
220,
220,
220,
220,
1303,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
45627,
28,
16,
1539,
49283,
11639,
17080,
3890,
3256,
8000,
28,
17821,
8,
198,
220,
220,
220,
220,
220,
220,
220,
1303,
17934,
286,
4441,
257,
2746,
351,
11491,
9056,
198,
220,
220,
220,
220,
220,
220,
220,
827,
6780,
13,
2860,
17633,
10786,
9562,
3256,
20310,
414,
28,
940,
1539,
49283,
11639,
17080,
3890,
3256,
8000,
28,
17821,
8,
198,
220,
220,
220,
220,
220,
220,
220,
1994,
796,
1181,
9218,
7,
5787,
13,
3672,
4032,
9150,
11537,
198,
220,
220,
220,
220,
220,
220,
220,
1303,
24286,
5411,
5804,
2292,
284,
307,
5969,
379,
513,
198,
220,
220,
220,
220,
220,
220,
220,
827,
6780,
13,
2617,
12193,
2086,
7,
2539,
11,
18,
4032,
9562,
11537,
628,
220,
220,
220,
220,
220,
220,
220,
1303,
38728,
11339,
318,
4988,
22147,
546,
2292,
357,
1120,
4,
2863,
286,
852,
767,
11,
2026,
4,
286,
852,
513,
8,
198,
220,
220,
220,
220,
220,
220,
220,
995,
13,
2617,
17633,
7,
5787,
13,
3672,
11,
17821,
8,
198,
220,
220,
220,
220,
220,
220,
220,
1479,
13,
2617,
12193,
2086,
7,
2539,
11,
20344,
3890,
15090,
22,
25,
657,
13,
20,
11,
18,
25,
657,
13,
20,
92,
828,
17821,
8,
198,
220,
220,
220,
220,
220,
220,
220,
1303,
19243,
602,
546,
2422,
2292,
198,
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"""
Author: mcncm, 2019
Standard output messages for displaying hierarchically-organized data such as
recursively-called status lines.
"""
import os
import sys
import datetime as dt
from functools import wraps
import getpass
import inspect
from io import StringIO
import logging
import platform
import textwrap
import toplevel.conf as conf
from dysart.messages.errors import DysartError
DEFAULT_COL = 48
TAB = ' ' * 4
class Bcolor:
"""
Enum for colored printing
"""
HEADER = '\033[95m'
OKBLUE = '\033[94m'
OKGREEN = '\033[92m'
WARNING = '\033[93m'
FAIL = '\033[91m'
ENDC = '\033[0m'
BOLD = '\033[1m'
ITALIC = '\033[3m'
UNDERLINE = '\033[4m'
def cstr_ansi(s: str, status: str = 'normal') -> str:
"""
Wrap a string with ANSI color annotations
TODO there's a package for this; you can rip this out.
"""
if platform.system() == 'Windows':
return s # ANSI colors unsupported on Windows
if status == 'ok':
return Bcolor.OKGREEN + s + Bcolor.ENDC
elif status == 'fail':
return Bcolor.FAIL + s + Bcolor.ENDC
elif status == 'warn':
return Bcolor.WARNING + s + Bcolor.ENDC
elif status == 'bold':
return Bcolor.BOLD + s + Bcolor.ENDC
elif status == 'italic':
return Bcolor.ITALIC + s + Bcolor.ENDC
elif status == 'underline':
return Bcolor.UNDERLINE + s + Bcolor.ENDC
else:
return s
def cstr_slack(s: str, status: str = 'normal') -> str:
"""
Wrap a string with ANSI color annotations
TODO there's a package for this; you can rip this out.
"""
if status == 'bold':
return '*' + s + '*'
elif status == 'italic':
return '_' + s + '_'
elif status == 'strikethrough':
return '~' + s + '~'
elif status == 'underline':
return Bcolor.UNDERLINE + s + Bcolor.ENDC
elif status == 'code':
return '`' + s + '`'
elif status == 'codeblock':
return '```' + s + '```'
else:
return s
# This module-scoped function is used to decorate text with colors, bold and
# italics, and so on. By default it is set to a function using ANSI escape
# codes. Context managers within this module may contextually replace it with
# a different function.
#
# I'm not convinced that this is the best approach to this problem. If you
# happen to read this and have other ideas, let's talk.
cstr = cstr_ansi
class FormatContext:
"""
Todo: make this 100x less hacky
"""
cstrs = {
'slack': cstr_slack
}
def cprint(s: str, status: str = 'normal', **kwargs):
"""
Print a string with ANSI color annotations
"""
print(cstr(s, status), **kwargs)
def msg1(message: str, level=0, end="\n"):
"""
Print a formatted message to stdout.
Accepts an optional level parameter, which is useful when you might wish
to log a stack trace.
"""
prompt = '=> '
indent = ' '
output = level * indent + prompt + message
print(output, end=end)
def msg2(message: str, level=0, end="\n"):
"""
Print a formatted message to stdout.
Accepts an optional level parameter, which is useful when you might wish
to log a stack trace.
"""
prompt = '-> '
indent = ' '
output = level * indent + prompt + message
print(output, end=end)
def write_log(message: str):
"""
Write a message to a log file with date and time information.
"""
logging.info(message)
def logged(stdout=True, message='log event', **kwargs):
"""
Decorator for handling log messages. By default, writes to a default log
file in the debug_data database directory, and prints output to stdout.
Passes level parameter in decorated function to message functions to
"""
# set terminator for log message
term = "\n"
if 'end' in kwargs:
term = kwargs['end']
return decorator
def configure_logging(logfile=''):
"""
Set up the logging module to write to the correct logfile, etc.
"""
if logfile == '' or logfile is None:
# Set the log output to the null file. This should actually be cross-
# platform, i.e. equal to '/dev/null' on unix systems and 'NULL' on
# windows.
logfile = os.devnull
# TODO: I should really take advantage of some of the more advanced
# features of the logging module.
user = getpass.getuser()
log_format = '%(asctime)s | ' + user + " | %(message)s"
date_format = '%m/%d/%Y %I:%M:%S'
logging.basicConfig(format=log_format, filename=logfile,
datefmt=date_format, level='INFO')
def tree(obj, get_deps: callable, pipe='│', dash='─', tee='├',
elbow='└', indent=' ' * 3, prefix='') -> str:
"""Takes an object and a closure that is assumed to return an iterable of
dependent objects of the same type; produces an ascii tree diagram.
"""
s = str(obj)
deps = list(get_deps(obj))
# special case for empty dependents: no pipes
if not deps:
('\n' + prefix).join(s.split('\n'))
return s
# otherwise, dependents are nonempty: pipe to them
s = (prefix + '\n' + pipe).join(s.split('\n'))
s += '\n'
for i, dep in enumerate(deps):
if i == len(deps) - 1:
leader = elbow + dash * len(indent)
else:
leader = tee + dash * len(indent)
s += prefix + leader
new_prefix = pipe + indent if i != len(deps) - 1 else ' ' + indent
subtree = tree(dep, get_deps, prefix=new_prefix)
s += ('\n' + new_prefix).join(subtree.split('\n'))
return s
def pprint_func(name: str, doc: str) -> None:
"""
TODO real docstring for pprint_property
Takes a name and docstring of a function and formats and pretty-prints them.
"""
if doc is None:
return
# Number of columns in the formatted docscring
status_col = int(conf.config.get('STATUS_COL') or DEFAULT_COL)
# Prepare the docstring: fix up whitespace for display
doc = ' '.join(doc.strip().split())
# Prepare the docstring: wrap it and indent it
doc = '\t' + '\n\t'.join(textwrap.wrap(doc, status_col))
# Finally, print the result
print(cstr(name, status='bold') + '\n' + cstr(doc, status='italic') + '\n')
class StatusMessage:
"""
A simple context manager for printing informative status messages about
ongoing administration tasks.
TODO: document parameters, etc.
"""
def __enter__(self):
"""Prints a message describing the action taken and redirects io"""
cprint(self.infostr.ljust(self.num_cols).capitalize(), status='normal',
end='', flush=True)
if self.__capture_io:
sys.stdout = self.stdout_buff = StringIO()
sys.stderr = self.stderr_buff = StringIO()
def __exit__(self, exc_type, exc_value, traceback):
"""Prints the terminating status string and restores io"""
if exc_type is None:
cprint(self.donestr, status='ok', file=self.__old_stdout)
else:
status = 'fail'
failstr = self.failstr
if isinstance(exc_value, DysartError):
status = exc_value.status
failstr = exc_value.message
cprint(failstr, status, file=self.__old_stdout)
if 'VERBOSE_MESSAGES' in conf.config:
print(exc_value)
if self.__capture_io:
sys.stdout, sys.stderr = self.__old_stdout, self.__old_stderr
sys.stdout.write(self.stdout_buff.getvalue())
sys.stderr.write(self.stderr_buff.getvalue())
return True
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13,
1136,
8367,
28955,
198,
220,
220,
220,
220,
220,
220,
220,
1441,
6407,
628
] | 2.477655 | 3,088 |
"""
Make sure that the correct versions of gobject introspection dependencies
are installed.
"""
import os
import logging
from gi import require_version
from .locale import _
require_version('Gio', '2.0')
require_version('GLib', '2.0')
_in_X = bool(os.environ.get('DISPLAY'))
_has_Gtk = (3 if check_version('Gtk', '3.0') else
2 if check_version('Gtk', '2.0') else
0)
_has_Notify = check_version('Notify', '0.7')
_has_AppIndicator3 = check_version('AppIndicator3', '0.1')
def require_Gtk(min_version=2):
"""
Make sure Gtk is properly initialized.
:raises RuntimeError: if Gtk can not be properly initialized
"""
if not _in_X:
raise RuntimeError('Not in X session.')
if _has_Gtk < min_version:
raise RuntimeError('Module gi.repository.Gtk not available!')
if _has_Gtk == 2:
logging.getLogger(__name__).warn(
_("Missing runtime dependency GTK 3. Falling back to GTK 2 "
"for password prompt"))
from gi.repository import Gtk
# if we attempt to create any GUI elements with no X server running the
# program will just crash, so let's make a way to catch this case:
if not Gtk.init_check(None)[0]:
raise RuntimeError(_("X server not connected!"))
return Gtk
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428,
1339,
25,
198,
220,
220,
220,
611,
407,
402,
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13,
15003,
62,
9122,
7,
14202,
38381,
15,
5974,
198,
220,
220,
220,
220,
220,
220,
220,
5298,
43160,
12331,
28264,
7203,
55,
4382,
407,
5884,
2474,
4008,
198,
220,
220,
220,
1441,
402,
30488,
628,
628,
628
] | 2.579365 | 504 |
import dj_database_url
from decouple import config
from .base import * # noqa
SECRET_KEY = 'django-insecure-ibi@xb(j2k@r&%*(*&(^%$%^$%^^&)))5_niq9erpkv%*!&!m9hp'
DEBUG = True
ALLOWED_HOSTS = []
DATABASES = {
'default': dj_database_url.config(default=config('SQLITE_DB'))
}
| [
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28,
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10786,
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12709,
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] | 2.153846 | 130 |
# nlantau, 2020-12-15
import copy
import os
# STARTING_NUMBERS = [2, 0, 6, 12, 1, 3]
STARTING_NUMBERS = [0, 3, 6]
if __name__ == "__main__":
main()
| [
2,
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834,
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198,
220,
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198
] | 2.065789 | 76 |
from random_utils import from_dungeon_level
| [
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1330,
422,
62,
67,
403,
6281,
62,
5715,
628
] | 3.461538 | 13 |
# Given a string, return the count of the number of times that a substring
# length 2 appears in the string and also as the last 2 chars of the string,
# so "hixxxhi" yields 1 (we won't count the end substring).
# last2('hixxhi') --> 1
# last2('xaxxaxaxx') --> 1
# last2('axxxaaxx') --> 2
print(last2('hixxhi'))
print(last2('xaxxaxaxx'))
print(last2('axxxaaxx'))
| [
2,
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5324,
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] | 2.633094 | 139 |
from config import *
from gdocument import GDocument
if __name__ == '__main__':
main()
| [
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] | 3.032258 | 31 |
'''
Created on 17.10.2019
@author: JM
'''
class TMC2225_register_variant:
" ===== TMC2225 register variants ===== "
"..." | [
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6,
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] | 2.538462 | 52 |
import datetime
import unittest
import pytest
from src.info_string import this_year_info_string
| [
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] | 3.266667 | 30 |
import sys
import PyQt5
from PyQt5.QtGui import *
from PyQt5.QtCore import *
from PyQt5.QtWidgets import *
from PyQt5 import uic
from pprint import pprint
import cv2 as cv
Calui ='./ui.ui'
if __name__ =='__main__':
app = QApplication(sys.argv)
main_dialog=MainDialog()
main_dialog.show()
app.exec_() #event loop 진입
| [
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] | 2.194805 | 154 |
from enum import Enum
from sklearn.svm import SVC
from sklearn.tree import DecisionTreeClassifier
from sklearn.naive_bayes import GaussianNB
from sklearn.neighbors import KNeighborsClassifier
from sklearn.ensemble import RandomForestClassifier, AdaBoostClassifier
from sklearn.discriminant_analysis import QuadraticDiscriminantAnalysis
from sklearn.neural_network import MLPClassifier
from sklearn.model_selection import GridSearchCV, train_test_split
from sklearn.preprocessing import StandardScaler
from sklearn.pipeline import make_pipeline, Pipeline
| [
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62,
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62,
35312,
201,
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36213,
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198,
6738,
1341,
35720,
13,
79,
541,
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1330,
787,
62,
79,
541,
4470,
11,
37709,
201,
198,
201,
198,
201,
198,
201,
198,
201,
198
] | 3.410714 | 168 |
from utils.api_tools import *
from recommends.douban_top250 import DoubanTop
class DoubanTopAPI(Resource):
"""
获取豆瓣读书 Top250 数据
"""
args_get = reqparse.RequestParser() \
.add_argument("page", help="分页", type=int, required=False, location=["args", ])
@args_required_method(args_get)
| [
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220,
220,
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22046,
62,
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62,
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7,
22046,
62,
1136,
8,
198
] | 2.268116 | 138 |
# -*- coding: utf-8 -*-
# Generated by Django 1.10 on 2016-11-03 06:28
from __future__ import unicode_literals
from django.db import migrations, models
| [
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198,
198,
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42625,
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1330,
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602,
11,
4981,
628
] | 2.8 | 55 |
#!/usr/bin/env python
# -*- coding: utf-8 -*-
#
# Copyright © 2018 Matthew Stone <[email protected]>
# Distributed under terms of the MIT license.
"""
"""
import argparse
import heapq
from collections import deque
import pysam
import svtk.utils as svu
def records_match(record, other):
"""
Test if two records are same SV: check chromosome, position, stop, SVTYPE, SVLEN (for insertions),
STRANDS (for BNDS and INVs), and (if they exist) CHR2/END2 for multi-chromosomal events
"""
return (record.chrom == other.chrom and
record.pos == other.pos and
record.stop == other.stop and
record.info['SVTYPE'] == other.info['SVTYPE'] and
record.info['SVLEN'] == other.info['SVLEN'] and
record.info['STRANDS'] == other.info['STRANDS'] and
(('CHR2' not in record.info and 'CHR2' not in other.info) or ('CHR2' in record.info and 'CHR2' in other.info and record.info['CHR2'] == other.info['CHR2'])) and
(('END2' not in record.info and 'END2' not in other.info) or ('END2' in record.info and 'END2' in other.info and record.info['END2'] == other.info['END2'])))
def merge_key(record):
"""
Sort records by all fields that records_match will use to check for duplicates, in sequence,
so that all identical records according to records_match will be adjacent
"""
chr2 = record.info['CHR2'] if 'CHR2' in record.info else None
end2 = record.info['END2'] if 'END2' in record.info else None
return (record.pos, record.stop, record.info['SVTYPE'], record.info['SVLEN'], chr2, end2, record.info['STRANDS'], record.id)
def dedup_records(records):
"""Take unique subset of records"""
records = sorted(records, key=merge_key)
curr_record = records[0]
for record in records[1:]:
if records_match(curr_record, record):
# keep more informative ALT field, assumed to be the one with more colons
# ex: <INS:ME:ALU> kept over <INS>
curr_alt = curr_record.alts[0]
new_alt = record.alts[0]
if (curr_alt.startswith('<') and curr_alt.endswith('>') and new_alt.startswith('<') and new_alt.endswith('>') and
len(new_alt.split(':')) > len(curr_alt.split(':'))):
curr_record = record
continue
else:
yield curr_record
curr_record = record
yield curr_record
def merge_records(vcfs):
"""
Take unique set of VCF records
Strategy: Merge & roughly sort records from all VCFs by chrom & pos, then gather records that share the same chrom & pos and remove duplicates.
Note: The output from heapq.merge cannot be directly used to remove duplicates because it is not sufficiently sorted, so duplicates may not be
adjacent. It is also not sufficient to alter the comparator function to take more than chrom & pos into account, because heapq.merge assumes
that each VCF is already sorted and will make no attempt to further sort them according to the comparator function. Re-sorting all records
that share a chrom & pos by all necessary comparison fields is more efficient than re-sorting each entire VCF.
"""
merged_vcfs = heapq.merge(*vcfs, key=lambda r: VariantRecordComparison(r))
record = next(merged_vcfs)
curr_records = deque([record])
curr_chrom = record.chrom
curr_pos = record.pos
for record in merged_vcfs:
if record.chrom == curr_chrom and record.pos == curr_pos:
curr_records.append(record)
else:
for rec in dedup_records(curr_records):
yield rec
curr_records = deque([record])
curr_pos = record.pos
curr_chrom = record.chrom
for rec in dedup_records(curr_records):
yield rec
if __name__ == '__main__':
main() | [
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] | 2.539672 | 1,525 |
#!/usr/bin/python -S
"""
formatters.py
This module should implement the standard list of formatters.
It also provides a method LookupChain for *composing lookup chains* for
formatters.
Formatter lookup chaining is not to be confused with plain formatter chaining,
e.g.:
{variable|html|json}
If anyone has any better names for the two types of chaining, let the mailing
list know.
"""
__author__ = 'Andy Chu'
import os
import sys
from ._jsontemplate import FromFile
class Error(Exception):
"""Base class for all exceptions raised by this module."""
def LookupChain(lookup_func_list):
"""Returns a *function* suitable for passing as the more_formatters argument
to Template.
NOTE: In Java, this would be implemented using the 'Composite' pattern. A
*list* of formatter lookup function behaves the same as a *single* formatter
lookup funcion.
Note the distinction between formatter *lookup* functions and formatter
functions here.
"""
return MoreFormatters
def PythonPercentFormat(format_str):
"""Use Python % format strings as template format specifiers."""
if format_str.startswith('printf '):
fmt = format_str[len('printf '):]
return lambda value: fmt % value
else:
return None
# Seam for testing
_open = open
# Cache of compiled templates. In Java, this might need to be a
# ConcurrentHashMap like the tokenization regex cache.
_compiled_template_cache = {}
class TemplateFileInclude(object):
"""Template include mechanism.
The relative path is specified as an argument to the template.
"""
def __call__(self, format_str):
"""Returns a formatter function."""
if format_str.startswith('template-file '):
relative_path = format_str[len('template-file '):]
full_path = os.path.join(self.root_dir, relative_path)
if full_path not in _compiled_template_cache:
f = _open(full_path)
_compiled_template_cache[full_path] = FromFile(f)
f.close()
return _compiled_template_cache[full_path].expand # a 'bound method'
else:
return None # this lookup is not applicable
class Json(object):
"""Format arbitrary nodes as JSON.
It takes a function which converts JSON structures to strings as a parameter.
All this does is relieve the user of having to remember the standard names
'json' and 'js-string'. Just pass your program's JSON serializer in here.
"""
def __call__(self, format_str):
"""Returns a formatter function."""
if format_str in ('json', 'js-string'):
return self.json_func
else:
return None # this lookup is not applicable
def Plural(format_str):
"""Returns whether the value should be considered a plural value.
Integers greater than 1 are plural, and lists with length greater than one are
too.
"""
if format_str.startswith('plural?'):
i = len('plural?')
try:
splitchar = format_str[i] # Usually a space, but could be something else
_, plural_val, singular_val = format_str.split(splitchar)
except IndexError:
raise Error('plural? must have exactly 2 arguments')
return Formatter
else:
return None # this lookup is not applicable
| [
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25,
198,
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220,
220,
220,
220,
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283,
796,
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62,
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58,
72,
60,
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1303,
19672,
257,
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11,
475,
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307,
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220,
220,
220,
220,
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4808,
11,
22801,
62,
2100,
11,
18032,
62,
2100,
796,
5794,
62,
2536,
13,
35312,
7,
22018,
2007,
283,
8,
198,
220,
220,
220,
2845,
12901,
12331,
25,
198,
220,
220,
220,
220,
220,
5298,
13047,
10786,
489,
1523,
30,
1276,
423,
3446,
362,
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11537,
628,
220,
220,
220,
1441,
5178,
1436,
628,
220,
2073,
25,
198,
220,
220,
220,
1441,
6045,
220,
1303,
428,
35847,
318,
407,
9723,
628
] | 3.211907 | 991 |
from codecs import open
from ohoh import build_parser, DEFAULT_HOST, DEFAULT_PORT
from os import path
import os
import pytest
import sys
import time
@pytest.fixture
@pytest.fixture
@pytest.fixture
@pytest.mark.parametrize("address,expected", [
(None, (DEFAULT_HOST, DEFAULT_PORT)),
("localhost", ("localhost", DEFAULT_PORT)),
("localhost:80", ("localhost", 80)),
("google.com", ("google.com", DEFAULT_PORT)),
("google.com:80", ("google.com", 80)),
(":5868", ("", 5868)),
])
| [
6738,
40481,
82,
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198,
6738,
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62,
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3365,
3104,
1600,
5855,
1600,
7618,
3104,
36911,
198,
12962,
198
] | 2.698925 | 186 |
from pygame.surface import Surface
import constants
from font import Font
from root_object.circle import Circle
from root_object.text import Text
| [
6738,
12972,
6057,
13,
42029,
1330,
20321,
198,
198,
11748,
38491,
198,
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198,
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45597,
1330,
16291,
198,
6738,
6808,
62,
15252,
13,
5239,
1330,
8255,
628
] | 4.228571 | 35 |
import os
import glob
import yaml
| [
11748,
28686,
198,
11748,
15095,
198,
11748,
331,
43695,
198
] | 3.4 | 10 |
# Copyright 2021 Adobe. All rights reserved.
# This file is licensed to you 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 REPRESENTATIONS
# OF ANY KIND, either express or implied. See the License for the specific language
# governing permissions and limitations under the License.
import json
import mimetypes
from adobe.pdfservices.operation.internal.api.dto.document import Document
from adobe.pdfservices.operation.internal.api.dto.request.platform.outputs import Outputs
from adobe.pdfservices.operation.internal.service_constants import ServiceConstants
#TODO Why did it require JSONDecoder?
| [
2,
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2489,
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2,
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30416,
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62,
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2,
51,
3727,
46,
4162,
750,
340,
2421,
19449,
10707,
12342,
30,
198
] | 3.902954 | 237 |
import snap
import numpy as np
G = snap.PNGraph.New()
for i in range(6):
G.AddNode(i)
G.AddEdge(0, 1)
G.AddEdge(1, 2)
G.AddEdge(2, 0)
G.AddEdge(3, 4)
G.AddEdge(4, 5)
G.AddEdge(5, 3)
G.AddEdge(4, 3)
G.AddEdge(5, 4)
G.AddEdge(3, 5)
out_file = '../data/small.txt'
print 'data:', out_file
snap.SaveEdgeList(G, out_file)
| [
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513,
8,
198,
38,
13,
4550,
37021,
7,
20,
11,
604,
8,
198,
38,
13,
4550,
37021,
7,
18,
11,
642,
8,
198,
198,
448,
62,
7753,
796,
705,
40720,
7890,
14,
17470,
13,
14116,
6,
198,
4798,
705,
7890,
25,
3256,
503,
62,
7753,
198,
45380,
13,
16928,
37021,
8053,
7,
38,
11,
503,
62,
7753,
8,
198
] | 1.928571 | 168 |
import os
import toml
def _or(val_a, val_b, default=None):
""" Used to allow specifying config values through
os.environ
Args:
val_a:
val_b:
"""
if val_a is not None:
return val_a
elif val_b is not None:
return val_b
else:
return default
| [
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220,
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1441,
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628,
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] | 2.101351 | 148 |
from pydantic import BaseModel
from typing import List
from .notification_model import Notification
| [
6738,
279,
5173,
5109,
1330,
7308,
17633,
198,
6738,
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1330,
7343,
198,
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6738,
764,
1662,
2649,
62,
19849,
1330,
42808,
198
] | 4.391304 | 23 |
import json
from dataclasses import dataclass
from spatula import (
HtmlPage,
XmlPage,
JsonPage,
CsvListPage,
HtmlListPage,
XmlListPage,
JsonListPage,
XPath,
URL,
)
SOURCE = "https://example.com"
@dataclass
| [
11748,
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] | 2.238938 | 113 |
# --------------------------------------------------------------------------------------------
# Copyright (c) Microsoft Corporation. All rights reserved.
# Licensed under the MIT License. See License.txt in the project root for license information.
# --------------------------------------------------------------------------------------------
# AZURE CLI SERVICEBUS - CRUD TEST DEFINITIONS
import time
from azure.cli.testsdk import (ScenarioTest, ResourceGroupPreparer, live_only)
from knack.util import CLIError
# pylint: disable=line-too-long
# pylint: disable=too-many-lines
| [
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] | 4.786885 | 122 |
# Shows top posters and percentage of posts from top posters for the
# last 14 days. You need recent data to run this.
#
# Run this with ./manage.py runscript run_contributor_counts.py
from collections import defaultdict
from datetime import datetime, timedelta
from kitsune.forums.models import Post
if __name__ == '__main__':
print 'Run with "./manage.py runscript contributor_counts"'
| [
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9078,
1057,
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62,
9127,
82,
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198
] | 3.491228 | 114 |
# -*- coding: utf-8 -*-
import json, logging
log = logging.getLogger(__name__)
def parse_query( request ):
""" Preps and returns three data-elements.
Called by views.reconcile_v2() """
( query, query_type, callback ) = ( request.POST.get('query', None), request.POST.get('query_type', None), request.POST.get('callback', None) )
if not query:
query = request.GET.get( 'query', None )
query = massage_query( query )
if not query_type:
query_type = request.GET.get( 'query_type', '/fast/all' )
if not callback:
callback = request.GET.get( 'callback', None )
log.debug( 'query, ```%s```; query_type, ```%s```; callback, ```%s```' % (query, query_type, callback) )
return ( query, query_type, callback )
def massage_query( query ):
""" Updates query for better fast-lookups.
Called by parse_query() """
if query.startswith( '{' ):
query = json.loads(query)['query']
elif '(' in query and ')' in query:
substring = query[ query.find('(')+1:query.find(')') ]
log.debug( 'substring, `%s`' % substring )
wordcount = len( substring.split() )
if wordcount > 1:
query = query.replace( '(', '' )
query = query.replace( ')', '' )
log.debug( 'massaged query, `%s`' % query )
return query
| [
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7,
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220,
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1875,
352,
25,
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220,
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220,
220,
220,
220,
220,
220,
220,
220,
220,
12405,
796,
12405,
13,
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7,
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3256,
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1267,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
12405,
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13,
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7,
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8,
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198,
220,
220,
220,
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13,
24442,
7,
705,
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11,
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4,
82,
63,
6,
4064,
12405,
1267,
198,
220,
220,
220,
1441,
12405,
198
] | 2.453211 | 545 |
from setuptools import setup, find_packages
setup(
name="koala",
version='0.0',
description='Topological Amorphous quantum system simulations',
long_description='',
author="Peru D'Ornellas, Gino Cassella, Tom Hodson",
author_email='',
license='Apache Software License',
home_page='',
packages=find_packages('src'),
package_dir={'': 'src'},
install_requires=[
'numpy>=1.2',
'scipy',
'matplotlib',
'flake8',
'python-sat',
'pytest',
'pytest-cov',
'pytest-xdist',
'nbmake',
'pytest-github-actions-annotate-failures',
]
)
| [
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9288,
12,
66,
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220,
220,
220,
220,
220,
220,
705,
9078,
9288,
12,
87,
17080,
3256,
198,
220,
220,
220,
220,
220,
220,
220,
705,
46803,
15883,
3256,
198,
220,
220,
220,
220,
220,
220,
220,
705,
9078,
9288,
12,
12567,
12,
4658,
12,
34574,
378,
12,
32165,
942,
3256,
198,
220,
220,
220,
2361,
198,
8,
198
] | 2.182432 | 296 |
import numpy as np
| [
11748,
299,
32152,
355,
45941,
198
] | 3.166667 | 6 |
# testPhiGradx.py
# test the grad wrt x returned by trHess when nTh > 2
import matplotlib
matplotlib.use('TkAgg')
import matplotlib.pyplot as plt
from src.Phi import *
import torch.nn.utils
doPlots = True
d = 2
m = 5
nTh = 4
net = Phi(nTh=nTh, m=m, d=d)
net.double()
# vecParams = nn.utils.convert_parameters.parameters_to_vector(net.parameters())
x = torch.randn(1,3).type(torch.double)
# AD grad
x.requires_grad = True
y = net(x)
v = torch.randn(x.shape).type(torch.double)
# ------------------------------------------------
# f
# nablaPhi = net.trHess(x)[0]
g = net.trHess(x)[0]
niter = 20
h0 = 0.5
E0 = []
E1 = []
hlist = []
for i in range(niter):
h = h0**i
hlist.append(h)
E0.append( torch.norm(net( x + h * v ) - net(x)) )
E1.append( torch.norm(net( x + h * v ) - net(x) - h * torch.matmul(g , v.t())) )
for i in range(niter):
print("{:f} {:.6e} {:.6e}".format( hlist[i] , E0[i].item() , E1[i].item() ))
if doPlots:
plt.plot(hlist,E0, label='E0')
plt.plot(hlist,E1, label='E1')
plt.yscale('log')
plt.xscale('log')
plt.legend()
plt.show()
print("\n") | [
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] | 2.12334 | 527 |
import os
import torch
import CubeNet.net
import CubeNet.Picker
import CubeNet.config
network = CubeNet.net.UNet(); network.load_state_dict(torch.load(os.path.join(os.path.split(CubeNet.__file__)[0],'Para.pt')));
picker = CubeNet.Picker.IrrPicker(arr_info=CubeNet.config.arr_info,
para_path = os.path.join(os.path.split(CubeNet.__file__)[0],'Para.pt'),
net = network,
predict_batch = CubeNet.config.basic_info['batch_size'],
device = CubeNet.config.basic_info['device'])
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# -*- coding: utf-8 -*-
"""
The MIT License (MIT)
Copyright (c) 2019 Lorenzo
Permission is hereby granted, free of charge, to any person obtaining a
copy of this software and associated documentation files (the "Software"),
to deal in the Software without restriction, including without limitation
the rights to use, copy, modify, merge, publish, distribute, sublicense,
and/or sell copies of the Software, and to permit persons to whom the
Software is furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in
all copies or substantial portions of the Software.
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS
OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING
FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER
DEALINGS IN THE SOFTWARE.
"""
from .abc import BaseObject
from .ability import AbilityEffectChange
from .common import APIObject, MachineVersionDetail, Name, NamedAPIObject, VerboseEffect
__all__ = (
"Move",
"MoveFlavorText",
"MoveMetaData",
"MoveStatChange",
"PastMoveStatValues",
"ContestComboDetail",
"ContestComboSet"
)
class Move(BaseObject):
"""Represents a move object from the API.
.. versionadded:: 0.1.0a
.. container:: operations
.. describe:: str(x)
Returns the move's name.
.. describe:: x[y]
Returns a move's y attribute.
.. describe:: x == y
Check if two moves are the same.
.. describe:: x != y
Check if two moves are *not* the same.
Attributes
----------
id: :class:`int`
The identifier for the move.
name: :class:`str`
The name for the move.
accuracy: :class:`int`
The percent value of how likely the move is to be successful.
effect_chance: :class:`int`
The percent value of how likely it is that the move's effect will happen.
pp: :class:`int`
Power points. The number of times the move can be used.
power_points: :class:`int`
An alias for pp.
priority: :class:`int`
A value between -8 and 8. Sets the order in which the move is executed during battle.
power: :class:`int`
The base power of the move with a value of 0 if it does not have a base power.
contest_combos: :class:`ContestComboSets`
A detail of normal and super contest combos that require the move.
contest_type: :class:`NamedAPIObject`
The type of appeal the move gives a Pokémon when used in a contest.
contest_effect: :class:`APIObject`
The effect the move has when used in a contest.
super_contest_effect: :class:`APIObject`
The effect the move has when used in a super contest.
damage_class: :class:`NamedAPIObject`
The type of damage the move inflicts on the target, e.g. physical.
effect_entries: List[:class:`VerboseEffect`]
The effect of the move listed in different languages.
flavor_text_entries: List[:class:`MoveFlavorText`]
The flavor text of the move listed in different languages.
generation: :class:`NamedAPIObject`
The generation in which the move was introduced.
meta: :class:`MoveMetaData`
Metadata about the move.
names: List[:class:`Name`]
The name of the move listed in different languages.
past_values: List[:class:`PastMoveStatValues`]
A list of move value changes across version groups of the game.
stat_changes: List[:class:`MoveStatChange`]
A list of stats this move effects and how much it effects them.
effect_changes: List[:class:`AbilityEffectChange`]
The list of previous effects the move has had across version groups of the games.
target: :class:`NamedAPIObject`
The type of target that will receive the effects of the move.
type: :class:`NamedAPIObject`
The elemental type of the move.
machines: :class:`MachineVersionDetail`
A list of the machines that teach this move."""
__slots__ = (
"accuracy", "effect_chance", "pp", "power_points", "priority", "power", "contest_type", "type", "target",
"generation", "damage_class", "meta", "stat_changes", "names", "effect_entries", "flavor_text_entries",
"past_values", "effect_changes", "contest_effect", "super_contest_effect", "machines"
)
class MoveFlavorText:
"""Represents the flavor text of a move associated with a language.
.. versionadded:: 0.1.0a
Attributes
----------
flavor_text: :class:`str`
The localized flavor text for the move in the associated language.
language: :class:`NamedAPIObject`
The language the text is in.
version_group: :class:`NamedAPIObject`
The version group that uses the text."""
__slots__ = ("flavor_text", "language", "version_group")
class MoveMetaData:
"""Represents the metadata about a move.
.. versionadded:: 0.1.0a
Attributes
----------
ailment: :class:`NamedAPIObject`
The status ailment the move inflicts on it's target.
category: :class:`NamedAPIObject`
The category of move the move falls under, e.g. damage or ailment.
min_hits: Optional[:class:`int`]
The minimum number of times the move hits. ``None`` if it always only hits once.
max_hits: Optional[:class:`int`]
The maximum number of times the move hits. ``None`` if it always only hits once.
min_turns: Optional[:class:`int`]
The minimum number of turns the move continues to take effect. ``None`` if it always only lasts one turn.
max_turns: Optional[:class:`int`]
The maximum number of turns the move continues to take effect. ``None`` if it always only lasts one turn.
drain: :class:`int`
HP drain (if positive) or recoil damage (if negative), in percent of damage done.
healing: :class:`int`
The amount of hp gained by the attacking Pokemon, in percent of it's maximum HP.
crit_rate: :class:`int`
Critical hit rate bonus.
ailment_chance: :class:`int`
The likelihood the move will cause an ailment.
flinch_chance: :class:`int`
The likelihood the move will cause the target Pokémon to flinch.
stat_chance: :class:`int`
The likelihood the mpve will cause a stat change in the target Pokémon.
"""
__slots__ = (
"ailment", "category", "min_hits", "max_hits", "min_turns", "max_turns", "drain", "healing", "crit_rate",
"ailment_chance", "flinch_chance", "stat_chance"
)
class MoveStatChange:
"""Represents a stat change in a :class:`move`
.. versionadded:: 0.1.0a
Attributes
----------
change: :class:`int`
The amount of change.
stat: :class:`NamedAPIObject`
The stat being affected."""
__slots__ = ("change", "stat")
class PastMoveStatValues:
"""Represents changed values of a :class:`Move` in a version group.
.. versionadded:: 0.1.0a
Attributes
----------
accuracy: :class:`int`
The percent value of how likely the move is to be successful.
effect_chance: :class:`int`
The percent value of how likely it is the moves effect will take effect.
power: :class:`int`
The base power of the move with a value of 0 if it does not have a base power.
pp: :class:`int`
Power points. The number of times the move can be used.
effect_entries: List[:class:`VerboseEffect`]
The effect of the move listed in different languages.
type: :class:`NamedAPIObject`
The elemental type of the move.
version_group: :class:`NamedAPIObject`
The version group in which these move stat values were in effect."""
__slots__ = ("accuracy", "effect_chance", "power", "pp", "effect_entries", "type", "version_group")
class ContestComboDetail:
"""Represents a detail of moves that can be used to grain additional
appeal points in contests.
.. versionadded:: 0.1.0a
Attributes
----------
use_before: List[:class:`NamedAPIObject`]
A list of moves to use before this move.
use_after: List[:class:`str`]
A list of moves to use after this move."""
__slots__ = ("use_before", "use_after")
class ContestComboSet:
"""Represents a set of super and normal contest combos.
.. versionadded:: 0.1.0a
Attributes
----------
normal: :class:`ContestComboDetail`
A detail of moves this move can be used before or after, granting additional appeal points in contests.
super: :class:`ContestComboDetail`
A detail of moves this move can be used before or after, granting additional appeal points in super contests."""
__slots__ = ("normal", "super")
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] | 2.853342 | 3,157 |
#!/usr/bin/env python
# coding: utf-8
# In[8]:
import numpy as np
import matplotlib.pyplot as plt
import seaborn as sns; sns.set()
ranstat = np.random.RandomState(1)
P = np.dot(ranstat.rand(2, 2), ranstat.randn(2, 600)).T
plt.scatter(P[:, 0], P[:, 1])
plt.axis('equal');
# In[ ]:
# In[ ]:
| [
2,
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] | 2.163121 | 141 |
from typing import Optional
from functools import wraps
from io import StringIO
from sh import RunningCommand
from requests.exceptions import ConnectionError, HTTPError
from firepy.connection import Connection
from firepy.exceptions import err_from_stderr, FirecrackerApiError
from firepy.utils.network_utils import network_mac, network_tap_name
from firepy.utils.firecracker_utils import kernel_boot_args
from firepy.utils.logging_utils import logger
def handle_errors(func):
"""Decorator that humanizes exceptions.
It
- parses firecracker HTTP responses
- checks instance stderr for error messages
"""
@wraps(func)
return wrapper
| [
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] | 3.494737 | 190 |
import datetime
import json
import logging
from collections import OrderedDict
from typing import List, Any, Dict
import guacamol
from guacamol.goal_directed_benchmark import GoalDirectedBenchmark, GoalDirectedBenchmarkResult
from guacamol.goal_directed_generator import GoalDirectedGenerator
from guacamol.benchmark_suites import goal_directed_benchmark_suite
from guacamol.utils.data import get_time_string
logger = logging.getLogger(__name__)
logger.addHandler(logging.NullHandler())
def assess_goal_directed_generation(goal_directed_molecule_generator: GoalDirectedGenerator,
json_output_file='output_goal_directed.json',
benchmark_version='v1') -> None:
"""
Assesses a distribution-matching model for de novo molecule design.
Args:
goal_directed_molecule_generator: Model to evaluate
json_output_file: Name of the file where to save the results in JSON format
benchmark_version: which benchmark suite to execute
"""
logger.info(f'Benchmarking goal-directed molecule generation, version {benchmark_version}')
benchmarks = goal_directed_benchmark_suite(version_name=benchmark_version)
results = _evaluate_goal_directed_benchmarks(
goal_directed_molecule_generator=goal_directed_molecule_generator,
benchmarks=benchmarks)
benchmark_results: Dict[str, Any] = OrderedDict()
benchmark_results['guacamol_version'] = guacamol.__version__
benchmark_results['benchmark_suite_version'] = benchmark_version
benchmark_results['timestamp'] = get_time_string()
benchmark_results['results'] = [vars(result) for result in results]
logger.info(f'Save results to file {json_output_file}')
with open(json_output_file, 'wt') as f:
f.write(json.dumps(benchmark_results, indent=4))
def _evaluate_goal_directed_benchmarks(goal_directed_molecule_generator: GoalDirectedGenerator,
benchmarks: List[GoalDirectedBenchmark]
) -> List[GoalDirectedBenchmarkResult]:
"""
Evaluate a model with the given benchmarks.
Should not be called directly except for testing purposes.
Args:
goal_directed_molecule_generator: model to assess
benchmarks: list of benchmarks to evaluate
json_output_file: Name of the file where to save the results in JSON format
"""
logger.info(f'Number of benchmarks: {len(benchmarks)}')
results = []
for i, benchmark in enumerate(benchmarks, 1):
logger.info(f'Running benchmark {i}/{len(benchmarks)}: {benchmark.name}')
result = benchmark.assess_model(goal_directed_molecule_generator)
logger.info(f'Results for the benchmark "{result.benchmark_name}":')
logger.info(f' Score: {result.score:.6f}')
logger.info(f' Execution time: {str(datetime.timedelta(seconds=int(result.execution_time)))}')
logger.info(f' Metadata: {result.metadata}')
results.append(result)
logger.info('Finished execution of the benchmarks')
return results
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] | 2.703993 | 1,152 |
#!/usr/bin/env python3
# Copyright (C) 2017 Roland Lutz
#
# Permission to use, copy, modify, and/or distribute this software for any
# purpose with or without fee is hereby granted, provided that the above
# copyright notice and this permission notice appear in all copies.
#
# THE SOFTWARE IS PROVIDED "AS IS" AND THE AUTHOR DISCLAIMS ALL WARRANTIES
# WITH REGARD TO THIS SOFTWARE INCLUDING ALL IMPLIED WARRANTIES OF
# MERCHANTABILITY AND FITNESS. IN NO EVENT SHALL THE AUTHOR BE LIABLE FOR
# ANY SPECIAL, DIRECT, INDIRECT, OR CONSEQUENTIAL DAMAGES OR ANY DAMAGES
# WHATSOEVER RESULTING FROM LOSS OF USE, DATA OR PROFITS, WHETHER IN AN
# ACTION OF CONTRACT, NEGLIGENCE OR OTHER TORTIOUS ACTION, ARISING OUT OF
# OR IN CONNECTION WITH THE USE OR PERFORMANCE OF THIS SOFTWARE.
import getopt, os, re, sys
import icebox
GLB_NETWK_EXTERNAL_BLOCKS = [(13, 8, 1), (0, 8, 1), (7, 17, 0), (7, 0, 0),
(0, 9, 0), (13, 9, 0), (6, 0, 1), (6, 17, 1)]
GLB_NETWK_INTERNAL_TILES = [(7, 0), (7, 17), (13, 9), (0, 9),
(6, 17), (6, 0), (0, 8), (13, 8)]
## Get the global name of a net.
#
# \param x, y coordinates of the tile to which the net belongs
# \param fw, fh width and height of the tile fabric (excluding I/O tiles)
# \param net net name
#
# \return the global name of the net if it is a span wire, otherwise
# the unmodified net name
#
# There are 46624 span wires on the 1k (not counting dummies):
#
# span4_x[1..12]_g[1..20]_[0..11]
# span4_y[1..16]_g[1..16]_[0..11]
# span12_x[1..12]_g[1..28]_[0..1]
# span12_y[1..16]_g[1..24]_[0..1]
#
# span4_left_g[3..16]_[0..3]
# span4_right_g[5..18]_[0..3]
# span4_bottom_g[3..12]_[0..3]
# span4_top_g[5..14]_[0..3]
#
# span4_topleft[2,4,6,8]_[0..3]
# span4_bottomright[2,4,6,8]_[0..3]
#
# dummy_y[1..16]_g[0..3]_[0..11]
#
# "Dummy" nets are horizontal accesses to non-existing vertical span
# wires on the right edge which are listed by icebox but don't
# actually connect to anything outside the tile itself.
## Return the human-readable name of the \c fabout net of IO tile
## <tt>(x, y)</tt>.
## Remove an argument from a LUT string and an associated list of
## argument names.
#
# This is a helper function for \ref lut_to_logic_expression.
#
# \param lut string of 2^N `0' or `1' characters representing the
# logic of an Nx1 look-up table
# \param args list of N strings containing the human-readable names
# of the arguments
# \param i index of the argument to remove
# \param keep boolean value indicating which value of the removed
# argument is to be assumed in the resulting LUT
#
# \return a new pair <tt>(lut, args)</tt> with the argument removed
## Negate a tuple representation of a logic expression.
#
# This is a helper function for \ref lut_to_logic_expression.
## Convert a tuple representation of a logic expression into a string.
#
# This is a helper function for \ref lut_to_logic_expression.
#
# \param expr the expression to convert
# \param parenthize whether a compound expression should be
# surrounded by parentheses
## Remove arguments which don't affect the result from a LUT string
## and an associated list of argument names.
#
# This is a helper function for \ref lut_to_logic_expression.
#
# \param lut string of 2^N `0' or `1' characters representing the
# logic of an Nx1 look-up table
# \param args list of N strings containing the human-readable names
# of the arguments
#
# \return a new pair <tt>(lut, args)</tt> with all unused arguments
# removed
## Convert a LUT string to a logic expression.
#
# \param lut string of 2^N `0' or `1' characters representing the
# logic of an Nx1 look-up table
# \param args list of N strings containing the human-readable names
# of the arguments
#
# \return a string containing a human-readable logic expression
# equivalent to the look-up table
#
# Example: lut_to_logic_expression('00010000', ['a', 'b', 'c']) -> 'a & b & !c'
if __name__ == '__main__':
main()
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834,
12417,
834,
10354,
198,
220,
220,
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1388,
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198
] | 2.642674 | 1,556 |
import time
import numpy as np
from remio import MJPEGEncoder
encoderParams = {
"quality": 60,
"colorspace": "bgr",
"colorsubsampling": "422",
"fastdct": True,
}
def test_encoder():
"""Test socket encoder class."""
max_encoding_time = 0.02 # seconds
encoder = MJPEGEncoder(**encoderParams)
encoding_time = []
for i in range(10):
frame = read_frame()
t0 = time.time()
encoded = encoder.encode(frame, base64=True)
t1 = time.time()
encoding_time.append(t1 - t0)
encoding_time = np.array(encoding_time)
assert encoding_time.mean() < max_encoding_time, "Improve the encoder..."
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] | 2.351064 | 282 |
# Python Class 2344
# Lesson 10 Problem 1
# Author: snowapple (471208)
import random
from tkinter import *
import tkinter.messagebox as messagebox
play_minesweeper(12, 10, 15)
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# Generated by Django 4.0.1 on 2022-01-12 15:28
import django.db.models.deletion
from django.conf import settings
from django.db import migrations, models
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'''
Extract all the 6 training zipped files and 2 validation zipped files into data folder and then run this script
'''
import cv2
import numpy as np
import os
import zipfile
## Runnin a loop throught all the zipped training file to extract all video and then extract 100 frames from each.
for i in range(1,76):
if i<10:
zipfilename = 'training80_0'+str(i)+'.zip'
else:
zipfilename = 'training80_'+str(i)+'.zip'
## Accessing the zipfile i
archive = zipfile.ZipFile('data/'+zipfilename, 'r')
zipfilename = zipfilename.split('.zip')[0]
##Extracting all videos in it and saving it all to the new folder with same name as zipped one
archive.extractall('unzippedData/'+zipfilename)
## Running a loop over all the videos in the zipped file and extracting 100 frames from each
for file_name in archive.namelist():
cap = cv2.VideoCapture('unzippedData/'+zipfilename+'/'+file_name)
file_name=(file_name.split('.mp4'))[0]
## Creating folder to save all the 100 frames from the video
try:
if not os.path.exists('ImageData/trainingData/'+file_name):
os.makedirs('ImageData/trainingData/'+file_name)
except OSError:
print ('Error: Creating directory of data')
## Setting the frame limit to 100
cap.set(cv2.CAP_PROP_FRAME_COUNT, 101)
length=101
count=0
## Running a loop to each frame and saving it in the created folder
while(cap.isOpened()):
count+=1
if length==count:
break
ret, frame = cap.read()
if frame is None:
continue
## Resizing it to 256*256 to save the disk space and fit into the model
frame = cv2.resize(frame,(256, 256), interpolation = cv2.INTER_CUBIC)
# Saves image of the current frame in jpg file
name = 'ImageData/trainingData/'+str(file_name)+'/frame' + str(count) + '.jpg'
cv2.imwrite(name, frame)
if cv2.waitKey(1) & 0xFF == ord('q'):
break
## Print the file which is done
print (zipfilename, ':', file_name)
#
for i in range(1,26):
if i<10:
zipfilename = 'validation80_0'+str(i)+'.zip'
else:
zipfilename = 'validation80_'+str(i)+'.zip'
## Accessing the zipfile i
archive = zipfile.ZipFile('data/'+zipfilename, 'r')
zipfilename = zipfilename.split('.zip')[0]
##Extracting all videos in it and saving it all to the new folder with same name as zipped one
archive.extractall('unzippedData/'+zipfilename)
## Running a loop over all the videos in the zipped file and extracting 100 frames from each
for file_name in archive.namelist():
cap = cv2.VideoCapture('unzippedData/'+zipfilename+'/'+file_name)
file_name=(file_name.split('.mp4'))[0]
## Creating folder to save all the 100 frames from the video
try:
if not os.path.exists('ImageData/validationData/'+file_name):
os.makedirs('ImageData/validationData/'+file_name)
except OSError:
print ('Error: Creating directory of data')
## Setting the frame limit to 100
cap.set(cv2.CAP_PROP_FRAME_COUNT, 101)
length=101
count=0
## Running a loop to each frame and saving it in the created folder
while(cap.isOpened()):
count+=1
if length==count:
break
ret, frame = cap.read()
if frame is None:
continue
## Resizing it to 256*256 to save the disk space and fit into the model
frame = cv2.resize(frame,(256, 256), interpolation = cv2.INTER_CUBIC)
# Saves image of the current frame in jpg file
name = 'ImageData/validationData/'+str(file_name)+'/frame' + str(count) + '.jpg'
cv2.imwrite(name, frame)
if cv2.waitKey(1) & 0xFF == ord('q'):
break
## Print the file which is done
print (zipfilename, ':', file_name)
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] | 2.259521 | 1,838 |
import pandas as pd
import matplotlib.pyplot as plt
import glob, os
aos_data = pd.read_csv("aos.csv")
soa_data = pd.read_csv("soa.csv")
plt.loglog(aos_data["n"],aos_data["time"],"o",markersize=1,label="aos")
plt.loglog(soa_data["n"],soa_data["time"],"o",markersize=1,label="soa")
plt.title("aos vs soa")
plt.legend()
plt.xlabel("n")
plt.ylabel("time")
plt.savefig("aos_vs_soa.png")
plt.show()
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] | 2.183333 | 180 |
try:
import pypissh
except:
print "WARNING: not using PyPi over SSH!"
import sys
import os
import shutil
import re
from setuptools import setup
## can't just naively import these from txtorcon, as that will only
## work if you already installed the dependencies :(
__version__ = '0.13.0'
__author__ = 'meejah'
__contact__ = '[email protected]'
__url__ = 'https://github.com/meejah/txtorcon'
__license__ = 'MIT'
__copyright__ = 'Copyright 2012-2015'
def pip_to_requirements(s):
"""
Change a PIP-style requirements.txt string into one suitable for setup.py
"""
if s.startswith('#'):
return ''
m = re.match('(.*)([>=]=[.0-9]*).*', s)
if m:
return '%s (%s)' % (m.group(1), m.group(2))
return s.strip()
setup(name = 'txtorcon',
version = __version__,
description = 'Twisted-based Tor controller client, with state-tracking and configuration abstractions.',
long_description = open('README.rst', 'r').read(),
keywords = ['python', 'twisted', 'tor', 'tor controller'],
## way to have "development requirements"?
requires = filter(len, map(pip_to_requirements, open('requirements.txt').readlines())),
## FIXME is requires even doing anything? why is format
## apparently different for install_requires?
install_requires = ['Twisted>=11.1.0', 'zope.interface>=3.6.1'],
classifiers = ['Framework :: Twisted',
'Development Status :: 4 - Beta',
'Intended Audience :: Developers',
'License :: OSI Approved :: MIT License',
'Natural Language :: English',
'Operating System :: POSIX :: Linux',
'Operating System :: Unix',
'Programming Language :: Python',
'Programming Language :: Python :: 2',
'Programming Language :: Python :: 2.6',
'Programming Language :: Python :: 2.7',
'Topic :: Software Development :: Libraries :: Python Modules',
'Topic :: Internet :: Proxy Servers',
'Topic :: Internet',
'Topic :: Security'],
author = __author__,
author_email = __contact__,
url = __url__,
license = __license__,
packages = ["txtorcon", "twisted.plugins"],
# scripts = ['examples/attach_streams_by_country.py'],
## I'm a little unclear if I'm doing this "properly", especially
## the documentation etc. Do we really want "share/txtorcon" for
## the first member of the tuple? Why does it seem I need to
## duplicate this in MANIFEST.in?
data_files = [('share/txtorcon', ['INSTALL', 'README.rst', 'TODO', 'meejah.asc']),
## this includes the Sphinx source for the
## docs. The "map+filter" construct grabs all .rst
## files and re-maps the path
('share/txtorcon', ['docs/apilinks_sphinxext.py', 'docs/conf.py', 'docs/Makefile'] + map(lambda x: os.path.join('docs', x), filter(lambda x: x[-3:] == 'rst', os.listdir('docs'))) + map(lambda x: os.path.join('docs/_static', x), os.listdir('docs/_static'))),
## include all the examples
('share/txtorcon/examples', map(lambda x: os.path.join('examples', x), filter(lambda x: x[-3:] == '.py', os.listdir('examples'))))
]
)
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] | 2.323963 | 1,494 |
# This sample tests the reportUnusedVariable diagnostic check.
| [
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# Imports
import matplotlib.pyplot as plt
import seaborn as sns
import torch
from torch import nn
from torch import optim
import torch.nn.functional as F
from torchvision import datasets, transforms, models
from PIL import Image
import numpy as np
import json
import pandas as pd
# Import for keeping our session alive
from workspace_utils import active_session
# Label Mapping
with open('cat_to_name.json', 'r') as f:
cat_to_name = json.load(f)
# Quick check of data in json file
df = pd.DataFrame({'flower_type': cat_to_name})
df.head(10)
# Define our classifier Class
# testing the model and returning the accuracy on new data
# Function that loads a checkpoint and rebuilds the model
def process_image(image):
''' Scales, crops, and normalizes a PIL image for a PyTorch model,
returns an Numpy array
'''
im = Image.open(image)
width, height = im.size
# Resize image to make the shortest side 256 pixels
if im.width > im.height:
(width, height) = (im.width, 256)
elif im.width < im.height:
(width, height) = (256, im.height)
else:
(width, height) = (256, 256)
im.thumbnail((width, height), Image.ANTIALIAS)
# new size of image
width, height = im.size
# Crop at center, make image 224x224
reduce = 224
left = (width - reduce)/2
top = (height - reduce)/2
right = left + 224
bottom = top + 224
im = im.crop((left, top, right, bottom))
np_image = np.array(im)/255
mean = np.array([0.485, 0.456, 0.406])
std = np.array([0.229, 0.224, 0.225])
np_image = (np_image - mean) / std
image = np_image.transpose((2, 0, 1))
return image
def imshow(image, ax=None, title=None):
"""Imshow for Tensor."""
if ax is None:
fig, ax = plt.subplots()
# PyTorch tensors assume the color channel is the first dimension
# but matplotlib assumes is the third dimension
image = image.transpose((1, 2, 0))
def predict(image_path, model, device = 'gpu', topk=1):
''' Predict the class (or classes) of an image using a trained deep learning model.
'''
image = process_image(image_path)
# Convert image to a FloatTensor and add a 'batch_size' dimension with .unsqueeze_(0)
image = torch.from_numpy(image).type(torch.FloatTensor).unsqueeze_(0)
# Select between gpu and cpu
if device == 'gpu' and torch.cuda.is_available():
device = torch.device('cuda:0')
else:
device = torch.device('cpu')
# Bring model to device
model.to(device)
with torch.no_grad():
model.eval()
output = model.forward(image.cuda())
ps = torch.exp(output)
probs, idx = ps.topk(topk, dim=1)
probs, idx = probs.to('cpu'), idx.to('cpu')
probs = probs.numpy () # converting both to numpy array
idx = idx.numpy ()
probs = probs.tolist () [0] # converting both to list
idx = idx.tolist () [0]
mapping = {val: key for key, val in
model.class_to_idx.items()
}
classes = [mapping [item] for item in idx]
class_names = [cat_to_name [item] for item in classes]
class_names = np.array(class_names)
classes = np.array(classes) # converting to Numpy array
return print(probs, class_names)
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] | 2.42765 | 1,396 |
from django.urls import path
from user.views import ProfileView,ProfileEditView,AllProfilesView
from django.contrib.auth.decorators import login_required
urlpatterns = [
# dynamic URL
path('in/<str:username>/',login_required(ProfileView.as_view()),name='profile_view'),
path('in/<str:username>/edit/',login_required(ProfileEditView.as_view()),name='profile_edit_view'),
path('profiles/',login_required(AllProfilesView.as_view()),name='all_profiles_view'),
]
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] | 2.824561 | 171 |
union_examples = """
Examples
-----------
>>> import pandas as pd
>>> import piso.interval
>>> piso.interval.union(
... pd.Interval(0, 3),
... pd.Interval(2, 4),
... )
Interval(0.0, 4.0, closed='right')
>>> piso.interval.union(
... pd.Interval(0, 3),
... pd.Interval(2, 4),
... squeeze=False,
... )
<IntervalArray>
[(0.0, 4.0]]
Length: 1, closed: right, dtype: interval[float64]
>>> piso.interval.union(
... pd.Interval(0, 3, closed="left"),
... pd.Interval(2, 4, closed="left"),
... )
Interval(0.0, 4.0, closed='left')
>>> piso.interval.union(
... pd.Interval(0, 1),
... pd.Interval(3, 4),
... )
<IntervalArray>
[(0.0, 1.0], (3.0, 4.0]]
Length: 2, closed: right, dtype: interval[float64]
"""
intersection_examples = """
Examples
-----------
>>> import pandas as pd
>>> import piso.interval
>>> piso.interval.intersection(
... pd.Interval(0, 3),
... pd.Interval(2, 4),
... )
Interval(2.0, 3.0, closed='right')
>>> piso.interval.intersection(
... pd.Interval(0, 3),
... pd.Interval(2, 4),
... squeeze=False,
... )
<IntervalArray>
[(2.0, 3.0]]
Length: 1, closed: right, dtype: interval[float64]
>>> piso.interval.intersection(
... pd.Interval(0, 3, closed="left"),
... pd.Interval(2, 4, closed="left"),
... )
Interval(2.0, 3.0, closed='left')
>>> piso.interval.intersection(
... pd.Interval(0, 1),
... pd.Interval(3, 4),
... )
<IntervalArray>
[]
Length: 0, closed: right, dtype: interval[int64]
"""
difference_examples = """
Examples
-----------
>>> import pandas as pd
>>> import piso.interval
>>> piso.interval.difference(
... pd.Interval(0, 3),
... pd.Interval(2, 4),
... )
Interval(0.0, 2.0, closed='right')
>>> piso.interval.difference(
... pd.Interval(0, 3),
... pd.Interval(2, 4),
... squeeze=False,
... )
<IntervalArray>
[(0.0, 2.0]]
Length: 1, closed: right, dtype: interval[float64]
>>> piso.interval.difference(
... pd.Interval(0, 4, closed="left"),
... pd.Interval(2, 3, closed="left"),
... )
<IntervalArray>
[[0.0, 2.0), [3.0, 4.0)]
Length: 2, closed: left, dtype: interval[float64]
>>> piso.interval.difference(
... pd.Interval(2, 3),
... pd.Interval(0, 4),
... )
<IntervalArray>
[]
Length: 0, closed: right, dtype: interval[int64]
"""
symmetric_difference_examples = """
Examples
-----------
>>> import pandas as pd
>>> import piso.interval
>>> piso.interval.symmetric_difference(
... pd.Interval(0, 3),
... pd.Interval(2, 4),
... )
<IntervalArray>
[(0.0, 2.0], (3.0, 4.0]]
Length: 2, closed: right, dtype: interval[float64]
>>> piso.interval.symmetric_difference(
... pd.Interval(0, 3),
... pd.Interval(2, 3),
... )
Interval(0.0, 2.0, closed='right')
>>> piso.interval.symmetric_difference(
... pd.Interval(0, 3, closed="left"),
... pd.Interval(2, 4, closed="left"),
... )
<IntervalArray>
[[0.0, 2.0), [3.0, 4.0)]
Length: 2, closed: left, dtype: interval[float64]
>>> piso.interval.symmetric_difference(
... pd.Interval(2, 3),
... pd.Interval(0, 4),
... )
<IntervalArray>
[(0.0, 2.0], (3.0, 4.0]]
Length: 2, closed: right, dtype: interval[float64]
"""
issuperset_examples = """
Examples
-----------
>>> import pandas as pd
>>> import piso.interval
>>> piso.interval.issuperset(
... pd.Interval(1, 4),
... pd.Interval(2, 4),
... )
True
>>> piso.interval.issuperset(
... pd.Interval(1, 4),
... pd.Interval(0, 3),
... )
False
>>> piso.interval.issuperset(
... pd.Interval(1, 4),
... pd.Interval(2, 4),
... pd.Interval(0, 3),
... )
array([ True, False])
>>> piso.interval.issuperset(
... pd.Interval(0, 3),
... pd.Interval(0, 3),
... squeeze=False
... )
array([ True])
"""
issubset_examples = """
Examples
-----------
>>> import pandas as pd
>>> import piso.interval
>>> piso.interval.issubset(
... pd.Interval(2, 4),
... pd.Interval(1, 4),
... )
True
>>> piso.interval.issubset(
... pd.Interval(2, 4),
... pd.Interval(0, 3),
... )
False
>>> piso.interval.issubset(
... pd.Interval(2, 4),
... pd.Interval(1, 4),
... pd.Interval(0, 3),
... )
array([ True, False])
>>> piso.interval.issubset(
... pd.Interval(1, 4),
... pd.Interval(1, 4),
... squeeze=False
... )
array([ True])
"""
template_doc = """
Performs the {operation} of two :class:`pandas.Interval`
Parameters
----------
interval1 : pandas.Interval
the first operand
interval2 : pandas.Interval
the second operand
squeeze : boolean, default True
If True, will try to coerce the return value to a :class:`pandas.Interval`
Returns
----------
:class:`pandas.Interval` or :class:`pandas.arrays.IntervalArray`
{examples}
"""
union_docstring = template_doc.format(operation="union", examples=union_examples)
intersection_docstring = template_doc.format(
operation="intersection", examples=intersection_examples
)
difference_docstring = template_doc.format(
operation="set difference", examples=difference_examples
)
symmetric_difference_docstring = template_doc.format(
operation="symmetric difference", examples=symmetric_difference_examples
)
is_sub_super_doc = """
Indicates whether one :class:`pandas.Interval` is a {operation} of one, or more, others.
Parameters
----------
interval : :class:`pandas.Interval`
An interval, against which all other intervals belonging to *intervals* are compared.
*intervals : argument list of :class:`pandas.Interval`
Must contain at least one argument.
squeeze : boolean, default True
If True, will try to coerce the return value to a single boolean
Returns
----------
boolean, or :class:`numpy.ndarray` of booleans
{examples}
"""
issuperset_docstring = is_sub_super_doc.format(
operation="superset",
examples=issuperset_examples,
)
issubset_docstring = is_sub_super_doc.format(
operation="subset",
examples=issubset_examples,
)
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8,
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6096,
28,
747,
549,
2617,
62,
1069,
12629,
11,
198,
8,
198
] | 2.382087 | 2,434 |
__example_payload__ = "SELECT * FROM information_schema.tables"
__type__ = "encoding all characters in the payload into their URL encoding equivalent"
| [
834,
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834,
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] | 3.897436 | 39 |
# flake8: noqa
# These have to be synced with the stdlib.pxi
import asyncio
import collections
import concurrent.futures
import errno
import functools
import gc
import inspect
import itertools
import os
import signal
import socket
import subprocess
import ssl
import stat
import sys
import threading
import traceback
import time
import warnings
import weakref
| [
2,
781,
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23,
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] | 3.61 | 100 |
# -*- coding: utf-8 -*-
# Generated by the protocol buffer compiler. DO NOT EDIT!
# source: google/protobuf/internal/import_test_package/import_public.proto
"""Generated protocol buffer code."""
from google.protobuf import descriptor as _descriptor
from google.protobuf import message as _message
from google.protobuf import reflection as _reflection
from google.protobuf import symbol_database as _symbol_database
# @@protoc_insertion_point(imports)
_sym_db = _symbol_database.Default()
from google.protobuf.internal.import_test_package import import_public_nested_pb2 as google_dot_protobuf_dot_internal_dot_import__test__package_dot_import__public__nested__pb2
from google.protobuf.internal.import_test_package.import_public_nested_pb2 import *
DESCRIPTOR = _descriptor.FileDescriptor(
name='google/protobuf/internal/import_test_package/import_public.proto',
package='google.protobuf.python.internal.import_test_package',
syntax='proto2',
serialized_options=b'H\001',
create_key=_descriptor._internal_create_key,
serialized_pb=b'\n@google/protobuf/internal/import_test_package/import_public.proto\x12\x33google.protobuf.python.internal.import_test_package\x1aGgoogle/protobuf/internal/import_test_package/import_public_nested.protoB\x02H\x01P\x00'
,
dependencies=[google_dot_protobuf_dot_internal_dot_import__test__package_dot_import__public__nested__pb2.DESCRIPTOR,],
public_dependencies=[google_dot_protobuf_dot_internal_dot_import__test__package_dot_import__public__nested__pb2.DESCRIPTOR,])
_sym_db.RegisterFileDescriptor(DESCRIPTOR)
DESCRIPTOR._options = None
# @@protoc_insertion_point(module_scope)
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11,
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62,
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295,
62,
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7,
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62,
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8,
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] | 2.946043 | 556 |
"""
CONSOLE LOGGING VERBOSITY LEVELS
---------------------------------
0 - FATAL
1 - CRITICAL
2 - INFO
3 - LOUD
4 - DEBUG
"""
from __future__ import print_function
VERBOSITY = 3
# Pass a function that handles printing
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#!/usr/bin/env python3
import multiprocessing as mp
import functools
import logging
import time
from typing import List
from tqdm.auto import tqdm
from dataclasses import dataclass
from simple_parsing import Serializable
from pathlib import Path
from google.cloud import storage
from top.data.objectron_detection import ObjectronDetection
from top.run.app_util import update_settings
bucket = None
def download_shard(shard: str, out_dir: str, bucket_local=None):
"""Download a single shard into `out_dir`.
NOTE(ycho): The output file is automatically named according to the base-name of
`shard`.
"""
global bucket
# Convert arg to a path object, just in case ...
out_dir = Path(out_dir)
# Configure names and download.
basename = shard.split('/')[-1]
out_file = (out_dir / basename)
if bucket_local is None:
# NOTE(ycho): Fallback to global bucket
bucket_local = bucket
blob = bucket_local.blob(shard)
try:
blob.download_to_filename(str(out_file))
except KeyboardInterrupt as e:
# NOTE(ycho): This seems to be the only working solution,
# which is to cleanup only on SIGINT.
# Catching a general `Exception` does not work. Not sure why.
if out_file.exists():
logging.debug(F'unlink: {out_file}')
out_file.unlink()
return 0
# NOTE(ycho): since we're not downloading metadata through get_blob(),
# we need to stat the local file for the size, in bytes.
return out_file.stat().st_size
@dataclass
def init_worker():
"""Set global variable `bucket` to point to cloud.
NOTE(ycho): This function is only used for mp.Pool.
"""
global bucket
client = storage.Client.create_anonymous_client()
bucket = client.bucket('objectron')
if __name__ == '__main__':
main()
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220,
220,
220,
220,
220,
220,
220,
220,
18931,
13,
24442,
7,
37,
6,
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25,
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448,
62,
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198,
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220,
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13,
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220,
37227,
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198,
220,
220,
220,
5456,
796,
6143,
13,
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13,
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62,
272,
6704,
62,
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3419,
198,
220,
220,
220,
19236,
796,
5456,
13,
27041,
316,
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15252,
1313,
11537,
628,
198,
198,
361,
11593,
3672,
834,
6624,
705,
834,
12417,
834,
10354,
198,
220,
220,
220,
1388,
3419,
198
] | 2.760773 | 673 |
import doctest
import os
import pytest
import psyneulink as pnl
| [
11748,
10412,
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198,
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11748,
28686,
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11748,
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9288,
198,
198,
11748,
17331,
710,
377,
676,
355,
279,
21283,
628,
628,
198
] | 2.916667 | 24 |
import pandas as pd
import re
from keras.models import Sequential
from keras.layers import Dense
from keras.wrappers.scikit_learn import KerasRegressor
from sklearn.preprocessing import StandardScaler
from nltk.corpus import stopwords
import nltk
from sklearn.feature_extraction.text import TfidfVectorizer
data = pd.read_csv('data/seattle/3/listings_texts.csv')
corpus = data['description']
y = data['price']
X=[]
for i,line in enumerate(corpus):
clear = [x for x in re.sub(r'[^\w\'\s]', '',line.lower()).split() if x not in stopwords.words('english')]
X.append(' '.join(clear))
if i%100 == 0:
print("Progress : ", i)
if i == 4000:
break
print("Moving on!")
vectorizer = TfidfVectorizer()
X = vectorizer.fit_transform(X)
net = Sequential()
net.add(Dense(200, input_dim=X[0].shape[1], kernel_initializer='normal',activation='relu'))
net.add(Dense(100, input_dim=200, kernel_initializer='normal',activation='relu'))
net.add(Dense(1, input_dim=100, kernel_initializer='normal'))
net.compile(loss='mean_squared_error', optimizer='adam')
net.fit(X[:3000],y[:3000], epochs=70, batch_size=100)
print(net.evaluate(X[3001:] ,y[3001:]))
for i in range(50):
print(net.predict(X[3001+i]), y[3001+i])
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25,
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62,
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8,
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7,
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13,
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7,
55,
58,
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16,
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837,
88,
58,
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16,
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4008,
198,
1640,
1312,
287,
2837,
7,
1120,
2599,
198,
220,
220,
220,
3601,
7,
3262,
13,
79,
17407,
7,
55,
58,
6200,
16,
10,
72,
46570,
331,
58,
6200,
16,
10,
72,
12962,
198
] | 2.553942 | 482 |
import time
import matplotlib.pyplot as plt
from confluent_kafka import Producer
if __name__ == '__main__':
plot_events_produced_frequency('first_half.txt')
| [
11748,
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62,
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10786,
11085,
62,
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13,
14116,
11537,
198
] | 2.964286 | 56 |
# This file is part of postcipes
# (c) Timofey Mukha
# The code is released under the MIT Licence.
# See LICENCE.txt and the Legal section in the README for more information
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
from .postcipe import Postcipe
import turbulucid as tbl
import numpy as np
from os.path import join
from scipy.integrate import simps
from collections import OrderedDict
from scipy.interpolate import LinearNDInterpolator
from scipy.spatial import Delaunay
import h5py
__all__ = ["UnstructuredChannelFlow"]
| [
2,
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1942,
323,
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289,
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198,
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834,
439,
834,
796,
14631,
3118,
7249,
1522,
29239,
37535,
8973,
628,
628
] | 3.433526 | 173 |
# MIT License
# Copyright (c) 2017 MassChallenge, Inc.
from impact.v1.helpers import JudgingRoundHelper
from impact.v1.views.base_detail_view import BaseDetailView
| [
2,
17168,
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198,
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13,
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62,
49170,
62,
1177,
1330,
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11242,
603,
7680,
628
] | 3.32 | 50 |
import boto3
import base64
aws_ecr_client = boto3.client('ecr')
response = aws_ecr_client.describe_repositories()
for repo in response['repositories']:
response = aws_ecr_client.get_authorization_token(registryIds=[repo['registryId']])
print(f"{repo['repositoryName']}\t{repo['repositoryArn']}")
#print(f" {response['authorizationData'][0]['proxyEndpoint']}")
#print(response['authorizationData'][0]['authorizationToken'])
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1,
220,
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26209,
17816,
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6601,
6,
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15,
7131,
6,
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4122,
20520,
92,
4943,
198,
220,
220,
220,
1303,
4798,
7,
26209,
17816,
9800,
1634,
6601,
6,
7131,
15,
7131,
6,
9800,
1634,
30642,
6,
12962,
198
] | 2.531429 | 175 |
"""
Test constants
:author: Angelo Cutaia
:copyright: Copyright 2021, LINKS Foundation
:version: 1.0.0
..
Copyright 2021 LINKS Foundation
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
https://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.
"""
# Standard library
import os
import time
FAKE_DATA = os.path.join(os.path.abspath(os.path.dirname(__file__)), "fake_data.txt")
"""Path of the file containing the fake data"""
# ------------------------------------------------------------------------------
# Module version
__version_info__ = (1, 0, 0)
__version__ = ".".join(str(x) for x in __version_info__)
# Documentation strings format
__docformat__ = "restructuredtext en"
# ------------------------------------------------------------------------------
########
# TIME #
########
TIME_MESSAGE_PAYLOAD = bytes(
[
0x1,
0x25,
0x14,
0x0,
0x0,
0x16,
0x9C,
0x16,
0xC0,
0xC9,
0x5,
0x0,
0x1C,
0xA4,
0x2,
0x0,
0x31,
0x4,
0x12,
0x7,
0x3,
0x0,
0x0,
0x0,
0xA3,
0xEF,
]
)
"""Time message payload with"""
raw_galTow = 379328
"""Galielo time of the week"""
raw_galWno = 1073
"""Galielo week number"""
raw_leapS = 18
"""Galileo leap seconds"""
timestampMessage_unix = 1584609709997
"""Time stamp of the message in a unix system"""
timestampMessage_galileo = 649329725
"""Time stamp of the message in galileo"""
time_raw_ck_A = 163
"""Time checksum A"""
time_raw_ck_B = 239
"""Time checksum B"""
# ------------------------------------------------------------------------------
###########
# GALILEO #
###########
UBLOX_MESSAGE_PAYLOAD = bytes(
[
0x2,
0x13,
0x2C,
0x0,
0x2,
0x12,
0x1,
0x0,
0x9,
0xE,
0x2,
0xD2,
0x34,
0x77,
0x76,
0x7,
0x5D,
0x63,
0x0,
0x1,
0xF5,
0x51,
0x22,
0x24,
0x0,
0x40,
0xF,
0x7F,
0x0,
0x40,
0x65,
0xA6,
0x2A,
0x0,
0x0,
0x0,
0xD2,
0x57,
0xAA,
0xAA,
0x0,
0x40,
0xBF,
0x3F,
0xD5,
0x9A,
0xE8,
0x3F,
0x4A,
0x7C,
]
)
"""Ublox message payload"""
GALILEO_MESSAGE_PAYLOAD = "077677340100635d242251f57f0f40a66540000000002aaaaa57d23fbf40"
"""Galileo message payload"""
TEST_AUTH_BYTES = bytes([0x0, 0x40, 0x65, 0xA6, 0x2A, 0x0, 0x0, 0x0])
"""Bytes that contain inside the 40 auth bits"""
raw_auth = 0
"""Int value of the 5 authorization bytes"""
raw_svId = 18
"""Galielo service id"""
raw_numWords = 9
"""Num of words"""
raw_ck_A = 74
"""Galileo checksum A"""
raw_ck_B = 124
"""Galileo checksum B"""
# ------------------------------------------------------------------------------
#################
# DATA TO STORE #
#################
DATA_TO_STORE = (
time.time() * 1000,
timestampMessage_unix,
raw_galTow,
raw_galWno,
raw_leapS,
UBLOX_MESSAGE_PAYLOAD.hex(),
GALILEO_MESSAGE_PAYLOAD,
0,
raw_svId,
raw_numWords,
raw_ck_B,
raw_ck_A,
time_raw_ck_A,
time_raw_ck_B,
-1,
timestampMessage_galileo,
)
"""Data to use to test the database"""
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] | 2.034823 | 1,924 |
from datamodel_code_generator.parser.base import snake_to_upper_camel
def test_snake_to_upper_camel_underscore():
"""In case a name starts with a underline, we should keep it."""
assert snake_to_upper_camel('_hello') == '_Hello'
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] | 2.811765 | 85 |
import cv2
import numpy as np
import dk_ardruino
import serial
cam_mtx=np.load('utils/cam_mtx.npy')
dist=np.load('utils/dist.npy')
newcam_mtx=np.load('utils/newcam_mtx.npy')
roi=np.load('utils/roi.npy')
matrix = np.load('utils/abc.npy')
area1 = int(open('utils/Resolution.txt').read().split('\n')[2])
width = int(open('utils/Resolution.txt').read().split('\n')[0])
height = int(open('utils/Resolution.txt').read().split('\n')[1])
diff_low_t= int(open('utils/Resolution.txt').read().split('\n')[5])
diff_high_t= int(open('utils/Resolution.txt').read().split('\n')[6])
realwidth = int(open('utils/Resolution.txt').read().split('\n')[3])
realheight = int(open('utils/Resolution.txt').read().split('\n')[4])
camera_number = int(open('utils/Resolution.txt').read().split('\n')[7])
Serial_port = open('utils/Resolution.txt').read().split('\n')[8]
bg_capture=False
bg_counter=0
count = 0
cam = cv2.VideoCapture(camera_number)
make_720p(cam)
ser = serial.Serial(Serial_port, 9600, timeout=1)
arm = True
arm_c=dk_ardruino.arm_controller(ser)
arm_c.wait_forready()
while True:
ret, frame = cam.read()
frame = cv2.undistort(frame, cam_mtx, dist, None, newcam_mtx)
a, b, c, d = roi
frame = frame[b:b+d, a:a+c]
frame1 = frame.copy()
if bg_capture == False:
bg_counter+=1
print(bg_counter)
if bg_counter==10:
crop_nen = cv2.warpPerspective(frame, matrix, (width, height))
# crop_nen= frame
bg_capture=True
if bg_capture == True:
crop_phat_hien = cv2.warpPerspective(frame, matrix, (width, height))
# crop_phat_hien = frame
target_gray = cv2.cvtColor(crop_phat_hien, cv2.COLOR_BGR2GRAY)
bg_gray = cv2.cvtColor(crop_nen, cv2.COLOR_BGR2GRAY)
diff_gray = cv2.absdiff(target_gray,bg_gray)
diff_gray_blur = cv2.GaussianBlur(diff_gray,(9,9),0)
ret,diff_tresh = cv2.threshold(diff_gray_blur,diff_low_t,diff_high_t,cv2.THRESH_BINARY)
diff = cv2.GaussianBlur(diff_tresh,(9,9),0)
diff = cv2.dilate(diff, None, iterations=2)
contours, hierarchy = cv2.findContours(diff, cv2.RETR_TREE,cv2.CHAIN_APPROX_SIMPLE)
XYZ=[]
for cnt in contours:
(x,y,w,h) = cv2.boundingRect(cnt)
cv2.rectangle(crop_phat_hien, (x, y), (x + w, y + h), (0, 0, 255), 2)
area = w*h
edge_noise=False
if x==0:
edge_noise=True
if y==0:
edge_noise=True
if (x+w)== width:
edge_noise=True
if (y+h)== height:
edge_noise=True
if edge_noise==False:
if area > area1:
realx = (realwidth/width)*(x + (w/2))
realy = (realheight/height)*(y + (h/2))
cv2.rectangle(crop_phat_hien, (x, y), (x + w, y + h), (0, 0, 255), 2)
adjust=0.1
y=int(y-((h*adjust)/2))
if y<0:
y=0
x=int(x-((w*adjust)/2))
if x<0:
x=0
w=int(w*(1+adjust))
h=int(h*(1+adjust))
if y<0: y=0
if x<0: x=0
if (x+w)>width: w=width-x
if (y+h)>height: h=height-y
if w>h:
#ensure contour is centered
y=int(y-((w-h)/2))
if y<0: y=0
#make a square
h=w
if (y+h)>height: y=height-h
if h>w:
x=int(x-((h-w)/2))
if x<0: x=0
w=h
if (x+w)>width: x=width-w
crop_img = crop_phat_hien[y:y+h, x:x+w]
# cv2.rectangle(crop_phat_hien, (x, y), (x + w, y + h), (0, 0, 255), 2)
# cv2.putText(crop_phat_hien, str(count), (50, 50), cv2.FONT_HERSHEY_SIMPLEX, 0.5, (36,255,12), 2)
XYZ.append([realx,realy])
# XYZ.append([x,y,w,h])
cv2.imshow('camera', diff)
cv2.imshow('camera1', crop_phat_hien)
k = cv2.waitKey(1)
if k%256 == 27:
# ESC pressed
print("Escape hit, closing...")
break
if k%256 == 32:
# for items in XYZ:
# x,y,w,h = items
# crop_img = frame1[y:y+h, x:x+w]
# cv2.imwrite("dataset/frame%d.png" % count, crop_img)
# count += 1
pickanddrop(XYZ,arm)
if (arm==True): arm_c.move_home()
cam.release()
cv2.destroyAllWindows()
ser.close() | [
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] | 1.649324 | 2,960 |
# coding: utf-8
"""
Defines Tournesol's backend API routes
"""
from django.urls import include, path
from rest_framework import routers
from .views import ComparisonDetailApi, ComparisonListApi, ComparisonListFilteredApi
from .views.email_domains import EmailDomainsList
from .views.exports import ExportAllView, ExportComparisonsView, ExportPublicComparisonsView
from .views.ratings import (
ContributorRatingDetail,
ContributorRatingList,
ContributorRatingUpdateAll,
)
from .views.stats import StatisticsView
from .views.user import CurrentUserView
from .views.video import VideoViewSet
from .views.video_rate_later import VideoRateLaterDetail, VideoRateLaterList
router = routers.DefaultRouter()
router.register(r'video', VideoViewSet)
app_name = "tournesol"
urlpatterns = [
path("", include(router.urls)),
# User API
path(
"users/me/",
CurrentUserView.as_view(),
name="users_me"
),
# Data exports
path(
"users/me/exports/comparisons/",
ExportComparisonsView.as_view(),
name="export_comparisons"
),
path(
"users/me/exports/all/",
ExportAllView.as_view(),
name="export_all"
),
path(
"exports/comparisons/",
ExportPublicComparisonsView.as_view(),
name="export_public"
),
# Comparison API
path(
"users/me/comparisons/", ComparisonListApi.as_view(),
name="comparisons_me_list",
),
path(
"users/me/comparisons/<str:video_id>/", ComparisonListFilteredApi.as_view(),
name="comparisons_me_list_filtered",
),
path(
"users/me/comparisons/<str:video_id_a>/<str:video_id_b>/",
ComparisonDetailApi.as_view(),
name="comparisons_me_detail",
),
# VideoRateLater API
path(
"users/me/video_rate_later/",
VideoRateLaterList.as_view(),
name="video_rate_later_list",
),
path(
"users/me/video_rate_later/<str:video_id>/",
VideoRateLaterDetail.as_view(),
name="video_rate_later_detail",
),
# Ratings API
path(
"users/me/contributor_ratings/",
ContributorRatingList.as_view(),
name="ratings_me_list",
),
path(
"users/me/contributor_ratings/_all/",
ContributorRatingUpdateAll.as_view(),
name="ratings_me_list_update_is_public",
),
path(
"users/me/contributor_ratings/<str:video_id>/",
ContributorRatingDetail.as_view(),
name="ratings_me_detail",
),
# Email domain API
path(
"domains/",
EmailDomainsList.as_view(),
name="email_domains_list"
),
# Statistics API
path(
"stats/",
StatisticsView.as_view(),
name="statistics_detail"
)
]
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] | 2.282093 | 1,223 |
import numpy as np
import win32gui, win32api
import ctypes
import mss
sct = mss.mss() | [
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] | 2.65625 | 32 |
import requests
import requests_cache
from collections import OrderedDict
from datetime import datetime
from dateutil import parser
from operator import itemgetter
from tabulate import tabulate
SCHEDULE_URL = "http://pyohio.org/schedule/json/"
def get_schedule(cache_ttl=3600):
""" Get the schedule from the conference website and return the JSON. """
requests_cache.install_cache(expire_after=cache_ttl)
response = requests.get(SCHEDULE_URL)
response.raise_for_status()
return response.json()
def _session_summary(session):
""" Given a detailed session dict, return a summary dict. """
summary = OrderedDict()
summary['date'] = parser.parse(session.get('start', '2016')).date().isoformat()
summary['start_time'] = parser.parse(session.get('start', '2016')).time().strftime('%H:%M')
summary['end_time'] = parser.parse(session.get('end', '2016')).time().strftime('%H:%M')
summary['room'] = session.get('room')
summary['name'] = session.get('name')
authors = session.get('authors', []) or []
summary['presenter'] = ", ".join(authors)
return summary
def make_table(schedule, start_datetime=None):
""" Given a list of session summaries, return a simple text table. """
if start_datetime is None:
start_datetime = datetime(1900, 1, 1)
schedule_summary = [_session_summary(session) for session in schedule if \
parser.parse(session.get('start', '2016')) > start_datetime]
schedule_summary.sort(key=itemgetter('date', 'start_time', 'end_time'))
return tabulate(schedule_summary, tablefmt="plain")
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7,
15952,
5950,
62,
49736,
11,
3084,
69,
16762,
2625,
25638,
4943,
198
] | 2.957328 | 539 |
from django.contrib.auth.models import User
from rest_framework import serializers
from django.contrib.auth import authenticate
from django.core import exceptions
from rest_framework.serializers import ModelSerializer
from django.utils.translation import ugettext_lazy as _
| [
6738,
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334,
1136,
5239,
62,
75,
12582,
355,
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628
] | 3.928571 | 70 |
# Generated by Django 3.1.5 on 2021-01-08 22:16
from django.db import migrations, models
| [
2,
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] | 2.84375 | 32 |
# encoding: utf-8
from __future__ import absolute_import, division, print_function, unicode_literals
from django import VERSION as DJANGO_VERSION
from django.conf import settings
from django.core.exceptions import ImproperlyConfigured
from django.db.models.loading import get_app, get_model, get_models
from django.utils.importlib import import_module
__all__ = ['haystack_get_models', 'haystack_load_apps']
APP = 'app'
MODEL = 'model'
if DJANGO_VERSION >= (1, 7):
from django.apps import apps
def haystack_get_app_modules():
"""Return the Python module for each installed app"""
return [i.module for i in apps.get_app_configs()]
def haystack_load_apps():
"""Return a list of app labels for all installed applications which have models"""
return [i.label for i in apps.get_app_configs() if i.models_module is not None]
else:
def haystack_get_app_modules():
"""Return the Python module for each installed app"""
return [import_module(i) for i in settings.INSTALLED_APPS]
| [
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287,
6460,
13,
38604,
7036,
1961,
62,
2969,
3705,
60,
198
] | 2.932584 | 356 |
# Copyright 2019 The LUCI Authors. All rights reserved.
# Use of this source code is governed under the Apache License, Version 2.0
# that can be found in the LICENSE file.
import json
import os
import sys
import time
import signal
signal.signal(
(
signal.SIGBREAK # pylint: disable=no-member
if sys.platform.startswith('win') else
signal.SIGTERM
),
lambda _signum, _frame: sys.exit(0))
try:
print "Starting up!"
print >>sys.stderr, ">> SLEEPING 5s"
time.sleep(5)
with open(sys.argv[1], 'wb') as pid_file:
json.dump({
# Note, you could put whatever connection information you wanted here.
'pid': os.getpid(),
}, pid_file)
print >>sys.stderr, ">> DUMPED PIDFILE"
for x in xrange(30):
print "Hi! %s" % x
time.sleep(1)
except SystemExit:
print >>sys.stderr, ">> QUITQUITQUIT"
raise
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8,
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9609,
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13,
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81,
11,
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360,
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1,
628,
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329,
2124,
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7,
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220,
220,
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3601,
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0,
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1,
4064,
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640,
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7,
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198,
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220,
3601,
9609,
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11,
366,
4211,
19604,
2043,
10917,
2043,
10917,
2043,
1,
198,
220,
5298,
198
] | 2.564179 | 335 |
from time import sleep
import os
from animations import progress_bar
from threading import Thread
import sys
import time
# for i in range(100):
# time.sleep(0.1)
# sys.stdout.write(f'salutare-{i}\n')
# sys.stdout.write(f'andrew-{i}\n')
# sys.stdout.write("\x1b[1A") # cursor up one line
# sys.stdout.write("\x1b[2K") # delete the last line
# sys.stdout.write("\x1b[1A") # cursor up one line
# sys.stdout.write("\x1b[2K") # delete the last line
from random import randrange
from random import uniform
work_ref = [0]
total_range = 100
work_thread = Thread(target=work, args=(total_range, work_ref))
work_thread.start()
work_ref2 = [0]
total_range2 = 100
work_thread2 = Thread(target=work2, args=(total_range2, work_ref2))
work_thread2.start()
while 1:
p = progress_bar(work_ref[0], total_range, color="yellow", title="work_thread")
print(p)
p = progress_bar(work_ref2[0], total_range2, color="yellow", title="work_thread")
print(p)
if not work_thread.is_alive() and not work_thread2.is_alive():
break
clear_lines(2)
sleep(0.01)
# if j < 100:
# j += 2
# p = progress_bar(j, 100, color="yellow", title="tqdm")
# print(p)
# if j >= 100 and index >= 100:
# break
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15,
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62,
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11,
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36022,
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62,
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17,
13,
271,
62,
282,
425,
33529,
198,
220,
220,
220,
220,
220,
220,
220,
2270,
628,
220,
220,
220,
1598,
62,
6615,
7,
17,
8,
198,
220,
220,
220,
3993,
7,
15,
13,
486,
8,
628,
220,
220,
220,
1303,
611,
474,
1279,
1802,
25,
198,
220,
220,
220,
1303,
220,
220,
220,
220,
474,
15853,
362,
198,
220,
220,
220,
1303,
279,
796,
4371,
62,
5657,
7,
73,
11,
1802,
11,
3124,
2625,
36022,
1600,
3670,
2625,
83,
80,
36020,
4943,
198,
220,
220,
220,
1303,
3601,
7,
79,
8,
628,
220,
220,
220,
1303,
611,
474,
18189,
1802,
290,
6376,
18189,
1802,
25,
198,
220,
220,
220,
1303,
220,
220,
220,
220,
2270,
628
] | 2.383613 | 537 |
from attributes.unit_test.discoverer import TestDiscoverer
| [
6738,
12608,
13,
20850,
62,
9288,
13,
15410,
659,
11751,
1330,
6208,
15642,
659,
11751,
628
] | 3.75 | 16 |
import garble
import wx
from multiprocessing import freeze_support
import sys
import os
from pathlib import Path
# pyinstaller GarbleExecutable.py --onefile -w --add-data ./venv/Lib/site-packages/clkhash/data;clkhash/data --add-data ./venv/Lib/site-packages/clkhash/schemas;clkhash/schemas --add-data ./example-schema;example-schema
if getattr(sys, 'frozen', False) and hasattr(sys, '_MEIPASS'):
os.chdir(sys._MEIPASS)
if __name__ == '__main__':
freeze_support()
main()
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'''
=================================================================
@version 2.0
@author Ashwin Ramadevanahalli
@title Testing.
Main module.
=================================================================
'''
import os
import sys
import subprocess
import testset_parse
import gcov_parse
import rand_pri
import tot_pri
import add_pri
import pickle
'''
Initializations
'''
pname=str(str(subprocess.check_output("pwd",shell=True)).split('/')[-1].strip())
location=""
maxlimit={'tcas':96.67,'totinfo':97.04,'printtokens':95.34,'printtokens2':99.50,'replace':95.02,'schedule':98.67,'schedule2':99.23}
#location="/Users/Ashwin/Downloads/benchmarks/"+pname+"/"
'''
Cleaning
'''
print "################################\nEntered CLeanig\n################################\n"
subprocess.call("rm -r outputs",shell=True)
subprocess.call("mkdir outputs",shell=True)
'''
Testset parse module
returns: A dictionary with Key in range '1 to No_of_tests' and value as the testcases and total number of statements in program.
input: program name, location of program.
'''
print "################################\nEntered Testset parse module\n################################\n"
testset,tot_statements,No_of_tests=testset_parse.parse(pname,location)
print testset
print tot_statements
'''
Gcov parse module
returns: state_testset=list of <No of statements it covers,testcase> and Brances_testset=list of <No of brances it covers,testcase> and both.
input: testset and total number of statements
'''
print "################################\nEntered Gcov parse module\n################################\n"
state_testset,branch_testset,sb_testset=gcov_parse.parse(testset,tot_statements)
print state_testset
'''
Random prioritization
returns: Random prioritizated testsets for statement, branch and both coverage.
input: testset, program name and location of program, max coverage
'''
print "################################\nEntered Random prioritization\n################################\n"
Ran_S,Ran_B,Ran_SB=rand_pri.pri(testset.values(),pname,location,maxlimit)
'''
Total coverage prioritization
returns: Total coverage prioritizated testsets for statement, branch and both coverage.
input: testsets with coverage information, program name and location of program, max coverage
'''
Tot_S,Tot_B,Tot_SB=tot_pri.pri(state_testset,branch_testset,sb_testset,pname,location,maxlimit)
'''
Additional coverage prioritization
returns: Additional coverage prioritizated testsets for statement, branch and both coverage.
input: testsets with coverage information, program name and location of program, max coverage
'''
Add_S,Add_B,Add_SB=add_pri.pri(state_testset,branch_testset,sb_testset,pname,location,maxlimit)
print "################################\nResult Section\n################################\n"
print len(Ran_S)
print len(Ran_B)
print len(Ran_SB)
print len(Tot_S)
print len(Tot_B)
print len(Tot_SB)
print len(Add_S)
print len(Add_B)
print len(Add_SB)
print "Total number of test cases=",No_of_tests
'''Storing Results'''
subprocess.call("rm -r results",shell=True)
subprocess.call("mkdir results",shell=True)
test=open("results/sran","w")
pickle.dump(Ran_S, test)
test.close()
test=open("results/bran","w")
pickle.dump(Ran_B, test)
test.close()
test=open("results/sbran","w")
pickle.dump(Ran_SB, test)
test.close()
test=open("results/stot","w")
pickle.dump(Tot_S, test)
test.close()
test=open("results/btot","w")
pickle.dump(Tot_B, test)
test.close()
test=open("results/sbtot","w")
pickle.dump(Tot_SB, test)
test.close()
test=open("results/sadd","w")
pickle.dump(Add_S, test)
test.close()
test=open("results/badd","w")
pickle.dump(Add_B, test)
test.close()
test=open("results/sbadd","w")
pickle.dump(Add_SB, test)
test.close()
print "Task Complete.Thank you."
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] | 3.033466 | 1,255 |
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