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# Authors: Jonathan Huggins <[email protected]>
# Trevor Campbell <[email protected]>
from __future__ import absolute_import, print_function
import sys
import csv
import hashlib
import pickle
from warnings import warn
import numpy as np
import numpy.random as npr
import scipy.sparse as sp
import sklearn.datasets as skl_ds
from sklearn import preprocessing
from .distributions import logistic_likelihood
from .utils import ensure_dimension_matches
import h5py
# based on: http://stackoverflow.com/questions/8955448/
def save_sparse_Xy(filename, X, y):
"""Save sparse X and array-like y as an npz file.
Parameters
----------
filename : string
X : sparse matrix, shape=(n_samples, n_features)
y : array-like, shape=(n_samples,)
"""
np.savez(filename, data=X.data, indices=X.indices, indptr=X.indptr,
shape=X.shape, y=y)
def save_Xy(filename, X, y):
"""Save X, y as an npz file.
Parameters
----------
filename : string
X : matrix-like, shape=(n_samples, n_features)
y : array-like, shape=(n_samples,)
"""
if sp.issparse(X):
save_sparse_Xy(filename, X, y)
else:
np.savez(filename, X=X, y=y)
def load_data(path, file_type, max_data=0, max_dim=0,
preprocess=True, include_offset=False, target_dim=None,
pos_label=None):
"""Load data from a variety of file types.
Parameters
----------
path : string
Data file path.
file_type : string
Supported file types are: 'svmlight', 'npy' (with the labels y in the
rightmost col), 'npz', 'hdf5' (with datasets 'x' and 'y'), and 'csv'
(with the labels y in the rightmost col)
max_data : int
If positive, maximum number of data points to use. If zero or negative,
all data is used. Default is 0.
max_dim : int
If positive, maximum number of features to use. If zero or negative,
all features are used. Default is 0.
preprocess : boolean or Transformer, optional
Flag indicating whether the data should be preprocessed. For sparse
data, the features are scaled to [-1, 1]. For dense data, the features
are scaled to have mean zero and variance one. Default is True.
include_offset : boolean, optional
Flag indicating that an offset feature should be added. Default is
False.
target_dim : int, optional
When given, ensure X initially has this many features. Projection will
be done after X is resized. Default is None.
Returns
-------
X : array-like matrix, shape=(n_samples, n_features)
y : int ndarray, shape=(n_samples,)
Each entry indicates whether each example is negative (-1 value) or
positive (+1 value)
pp_obj : None or Transformer
Transformer object used on data, or None if ``preprocess=False``
"""
if not isinstance(path, str):
raise ValueError("'path' must be a string")
if file_type in ["svmlight", "svm"]:
X, y = _load_svmlight_data(path)
elif file_type == "npy":
X, y = _load_npy_data(path)
elif file_type == "npz":
X, y = _load_npz_data(path)
elif file_type == "hdf5":
X, y = _load_hdf5_data(path)
elif file_type == "csv":
X, y = _load_csv_data(path)
else:
raise ValueError("unsupported file type, %s" % file_type)
if pos_label is None:
y_vals = set(y)
if len(y_vals) != 2:
raise ValueError('Only expected y to take on two values, but instead'
'takes on the values ' + ', '.join(y_vals))
if 1.0 not in y_vals:
raise ValueError('y does not take on 1.0 as one on of its values, but '
'instead takes on the values ' + ', '.join(y_vals))
if -1.0 not in y_vals:
y_vals.remove(1.0)
print('converting y values of %s to -1.0' % y_vals.pop())
y[y != 1.0] = -1.0
else:
y[y != pos_label] = -1.0
y[y == pos_label] = 1.0
if preprocess is False:
pp_obj = None
else:
if preprocess is True:
if sp.issparse(X):
pp_obj = preprocessing.MaxAbsScaler(copy=False)
else:
pp_obj = preprocessing.StandardScaler(copy=False)
else:
pp_obj = preprocess
if target_dim is not None and target_dim != pp_obj.scale_.shape[0]:
raise ValueError('target dim does not match pp_obj')
target_dim = pp_obj.scale_.shape[0]
if target_dim is not None:
X_dim = X.shape[1]
if X_dim < target_dim:
print('expanding X')
extra_shape = (X.shape[0], target_dim - X_dim)
if sp.issparse(X):
stack_fun = sp.hstack
extra = sp.csr_matrix(extra_shape)
else:
stack_fun = np.hstack
extra = np.zeros(extra_shape)
X = stack_fun([X, extra])
elif X_dim > target_dim:
print('shrinking X')
X = X[:,:target_dim]
if preprocess is True:
pp_obj.fit(X)
X = pp_obj.transform(X)
if include_offset:
X = preprocessing.add_dummy_feature(X)
if sp.issparse(X) and (X.nnz > np.prod(X.shape) / 10 or X.shape[1] <= 20):
print("X is either low-dimensional or not very sparse, so converting "
"to a numpy array")
X = X.toarray()
if isinstance(max_data, int) and max_data > 0 and max_data < X.shape[0]:
X = X[:max_data,:]
y = y[:max_data]
if isinstance(max_dim, int) and max_dim > 0 and max_dim < X.shape[1]:
X = X[:,:max_dim]
return X, y, pp_obj
def generate_gaussian_synthetic(num_samples, mean, covar, theta,
fname=None, include_offset=False):
"""Generate classification data with covariates from Gaussian distribution.
Generate `num_samples` data points with `X[i,:] ~ N(mean, covar)`, then use
a logistic likelihood model with parameter `theta` to generate `y[i]`.
If `include_offset = True`, then `X[i,-1] = 1`. Thus,
`total_features = n_features` if `include_offset = False` and
`n_features + 1` otherwise.
Parameters
----------
num_samples : int
mean : array-like, shape=(n_features,)
covar : matrix-like, shape=(n_features, n_features)
theta : array-like, shape=(total_features,)
fname : string, optional
If provided, save data to the provided filename
include_offset : boolean, optional
Default is False.
Returns
-------
X : ndarray with shape (num_samples, total_features)
y : ndarray with shape (num_samples,)
"""
_ensure_means_covar_match(mean, covar)
X = npr.multivariate_normal(mean, covar, num_samples)
if include_offset:
X = np.hstack((X, np.ones((num_samples, 1))))
return _generate_and_save_from_X(X, theta, fname)
def generate_gaussian_mixture(num_samples, weights, means, covar, theta,
fname=None, include_offset=False):
"""Generate classification data with covariates from Gaussian mixture.
Generate `num_samples` data points with `X[i,:] ~ N(means[j,:], covar)`
with probability `weights[j]`, then use a logistic likelihood model with
parameter `theta` to generate `y[i]`. If `include_offset = True`,
then `X[i,-1] = 1`. Thus, `total_features = n_features` if
`include_offset = False` and `n_features + 1` otherwise.
Parameters
----------
num_samples : int
weights : array-like, shape=(n_components,)
means : array-like, shape=(n_components, n_features)
covar : matrix-like, shape=(n_features, n_features)
theta : array-like, shape=(total_features,)
fname : string, optional
If provided, save data to the provided filename
include_offset : boolean, optional
Default is False.
Returns
-------
X : ndarray with shape (num_samples, total_features)
y : ndarray with shape (num_samples,)
"""
_ensure_means_covar_match(means, covar)
if means.shape[0] != weights.shape[0]:
raise ValueError("'means' and 'weights' shapes do not match")
components = npr.choice(weights.shape[0], num_samples, p=weights)
z = np.zeros(means.shape[1])
X = means[components, :] + npr.multivariate_normal(z, covar, num_samples)
if include_offset:
X = np.hstack((X, np.ones((num_samples, 1))))
return _generate_and_save_from_X(X, theta, fname)
def generate_reverse_mixture(num_samples, pos_prob, means, covar, fname=None):
"""Generate classification data class first, then Gaussian covariates.
Generate `num_samples` data points with `Pr[y[i] = 1] = pos_prob` and
`X[i,:] ~ N(means[y[i],:], covar)`.
Parameters
----------
num_samples : int
pos_prob : float
means : array-like, shape=(2, n_features)
covar : matrix-like, shape=(n_features, n_features)
fname : string, optional
If provided, save data to the provided filename
Returns
-------
X : ndarray with shape (num_samples, n_features)
y : ndarray with shape (num_samples,)
"""
_ensure_means_covar_match(means, covar)
if means.shape[0] != 2:
raise ValueError("'means' must have exactly two means")
y = npr.rand(num_samples)
y[y <= pos_prob] = 1
y[y != 1] = -1
components = np.zeros(num_samples, dtype=np.int)
components[y == 1] = 1
z = np.zeros(means.shape[1])
X = means[components, :] + npr.multivariate_normal(z, covar, num_samples)
if fname is not None:
np.save(fname, np.hstack((X, y[:, np.newaxis])))
return X, y
def generate_binary_data(num_samples, probs, theta,
fname=None, include_offset=False, ):
"""Generate classification data with binary covariates.
Generate `num_samples` data points with `Pr[X[i,j] = 1] = probs[j]` and
a logistic likelihood model with parameter `theta` to generate `y[i]`.
If `include_offset = True`, then `X[i,-1] = 1`. Thus,
`total_features = n_features` if `include_offset = False` and
`n_features + 1` otherwise.
Parameters
----------
num_samples : int
probs : array-like, shape=(n_features)
theta : array-like, shape=(total_features,)
fname : string, optional
If provided, save data to the provided filename
include_offset : boolean, optional
Default is False.
Returns
-------
X : csr_matrix with shape (num_samples, total_features)
y : ndarray with shape (num_samples,)
"""
probs = probs[np.newaxis, :]
X = npr.rand(num_samples, probs.shape[1])
X[X <= probs] = 1
X[X != 1] = 0
X = sp.csr_matrix(X, dtype=np.int32)
if include_offset:
X = sp.hstack((X, np.ones((num_samples, 1), dtype=np.int32)),
format='csr')
return _generate_and_save_from_X(X, theta, fname)
def convert_categorical_data_to_svmlight(path, filetype, out_path, column_info,
positive_labels,
ignore_first_line=False,
delimeter=',',
init=None,
no_new_features=False):
"""Convert categorical data into svmlight format.
Column info is a space-separated list of information about each column.
The options for each column are:
* 'cat' - categorical data (induces multiple features)
* 'bin' - binary data (induces single feature)
* 'lab' - output label (can only be assigned to one column)
* 'num' - numeric data
* 'ign' - ignore column
Parameters
----------
path : string
file_type : string
Supported file types are: 'csv'
out_path : string
column_info : string
positive_labels : list of strings
ignore_first_line : boolean, optional
Default is False.
delimeter : string, optional
Default is ','.
init : tuple, optional
Output from previous execution of the function. Used to maintain
consistency across multiple conversions.
no_new_features : boolean, optional
If init is provided, then don't create any new features.
Returns
-------
next_index : int
data : object
"""
info = column_info.split(' ')
if info.count('lab') != 1:
raise ValueError('column_info must specify exactly one label column')
label_index = info.index('lab')
if init is not None:
next_index, data, label_map, next_label_id = init
if no_new_features:
next_index = -next_index
else:
next_index = 1
data = [dict() for i in range(len(info))]
next_label_id = 1
label_map = {}
if filetype == 'csv':
with open(path, 'rb') as csv_file, open(out_path, 'wb') as out_file:
reader = csv.reader(csv_file, delimiter=delimeter)
try:
if ignore_first_line:
reader.next()
for row in reader:
if len(info) != len(row):
raise ValueError('row %d had an unexpected number of '
'columns (expected %d, got %d)' %
(reader.line_num, len(info), len(row)))
if positive_labels is None:
# hex_h = hashlib.md5(row[label_index]).hexdigest()
# h = int(hex_h, 16) % 49979687
# out_file.write('%d ' % h)
if row[label_index] not in label_map:
label_map[row[label_index]] = next_label_id
next_label_id += 1
out_file.write('%d ' % label_map[row[label_index]])
elif row[label_index] in positive_labels:
out_file.write('1 ')
else:
out_file.write('-1 ')
entry_list = []
for i, val in enumerate(row):
entry, next_index = _process_row_entry(val, info[i],
data[i],
next_index)
if entry is not None:
entry_list.append(entry)
entry_list.sort(cmp=lambda x,y: cmp(x[0], y[0]))
out_file.write(' '.join(['%s:%s' % e for e in entry_list]))
out_file.write('\n')
except csv.Error as e:
sys.exit('file %s, line %d: %s' % (path, reader.line_num, e))
if len(label_map) > 0:
with open(out_path + '.label_map', 'w') as f:
pickle.dump(label_map, f)
return abs(next_index), data
else:
raise ValueError("unsupported file type, %s" % file_type)
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] | 2.174249 | 6,990 |
import os
import django
from distutils.version import StrictVersion
DJANGO_VERSION = StrictVersion(django.get_version())
# Make filepaths relative to settings.
ROOT = os.path.dirname(os.path.abspath(__file__))
path = lambda *a: os.path.join(ROOT, *a)
DEBUG = True
TEST_RUNNER = 'django.test.runner.DiscoverRunner'
JINJA_CONFIG = {}
SITE_ID = 1
USE_I18N = False
SECRET_KEY = 'foobar'
DATABASES = {
'default': {
'NAME': 'test.db',
'ENGINE': 'django.db.backends.sqlite3',
},
# Provide a readonly DB for testing DB replication scenarios.
'readonly': {
'NAME': 'test.readonly.db',
'ENGINE': 'django.db.backends.sqlite3',
}
}
if 'DATABASE_URL' in os.environ:
try:
import dj_database_url
import psycopg2
DATABASES['default'] = dj_database_url.config()
except ImportError:
raise ImportError('Using the DATABASE_URL variable requires '
'dj-database-url and psycopg2. Try:\n\npip install '
'-r travis.txt')
INSTALLED_APPS = (
'django.contrib.admin',
'django.contrib.auth',
'django.contrib.contenttypes',
'django.contrib.sessions',
'django.contrib.sites',
'waffle',
'test_app',
)
_MIDDLEWARE_CLASSES = (
'django.middleware.common.CommonMiddleware',
'django.contrib.sessions.middleware.SessionMiddleware',
'django.contrib.auth.middleware.AuthenticationMiddleware',
'waffle.middleware.WaffleMiddleware',
)
if DJANGO_VERSION < StrictVersion('1.10.0'):
MIDDLEWARE_CLASSES = _MIDDLEWARE_CLASSES
else:
MIDDLEWARE = _MIDDLEWARE_CLASSES
ROOT_URLCONF = 'test_app.urls'
CUSTOM_USER_MODEL = 'auth.User'
_CONTEXT_PROCESSORS = (
'django.contrib.auth.context_processors.auth',
'django.template.context_processors.request',
)
TEMPLATES = [
{
'BACKEND': 'django_jinja.backend.Jinja2',
'DIRS': [],
'APP_DIRS': True,
'OPTIONS': {
'match_regex': r'jinja.*',
'match_extension': '',
'newstyle_gettext': True,
'context_processors': _CONTEXT_PROCESSORS,
'undefined': 'jinja2.Undefined',
'extensions': [
'jinja2.ext.i18n',
'jinja2.ext.autoescape',
'waffle.jinja.WaffleExtension',
],
}
},
{
'BACKEND': 'django.template.backends.django.DjangoTemplates',
'DIRS': [],
'APP_DIRS': True,
'OPTIONS': {
'debug': DEBUG,
'context_processors': _CONTEXT_PROCESSORS,
}
},
]
WAFFLE_FLAG_DEFAULT = False
WAFFLE_SWITCH_DEFAULT = False
WAFFLE_SAMPLE_DEFAULT = False
WAFFLE_READ_FROM_WRITE_DB = False
WAFFLE_OVERRIDE = False
WAFFLE_CACHE_PREFIX = 'test:'
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10426,
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] | 2.053254 | 1,352 |
"""This example showcase FastEstimator usage for tensorflow users. In this file, we use tf.dataset as data input.
"""
import numpy as np
import tensorflow as tf
from tensorflow.python.keras import Sequential, layers
import fastestimator as fe
from fastestimator.op.tensorop.loss import CrossEntropy
from fastestimator.op.tensorop.model import ModelOp, UpdateOp
from fastestimator.trace.metric import Accuracy
if __name__ == "__main__":
est = get_estimator()
est.fit() | [
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from tensorflow.keras.applications import InceptionV3
from tensorflow.keras.applications.imagenet_utils import preprocess_input, decode_predictions
import numpy as np
from tensorflow import keras
from matplotlib import pyplot as plt
from tensorflow.keras.preprocessing import image
from tensorflow.keras import Input
from skimage import transform as st
import cv2
import tensorflow as tf
images = np.load('dataset/LLD_icon_numpy/dataset1.npy')
model = InceptionV3(include_top=True, weights='imagenet')
start_index = 0
end_index = 2000
count = 0
while count<50:
images_batch = images[start_index:end_index]
image_list = []
for img in images_batch:
img = cv2.resize(img, dsize=(299, 299), interpolation=cv2.INTER_CUBIC)
image_list.append(img)
images_list = np.array(image_list)
predictions = model.predict(images_list)
decoded_predictions = decode_predictions(predictions, top=3)
decoded_predictions = np.array(decoded_predictions)
np.save('predictions/decoded_predictions_'+str(count)+'.npy', decoded_predictions)
start_index = start_index + 2000
end_index = end_index + 2000
count = count + 1
| [
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220,
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220,
954,
796,
954,
1343,
352,
628
] | 2.758865 | 423 |
import os
import sys
def get_project_path():
"""
Return the path to the project root folder
:return: The path to the project root folder
"""
return os.path.dirname(os.path.dirname(__file__))
def set_web_app_secret():
"""
Replace the secret key in the web application Python source file
"""
file = os.path.join(get_project_path(), "data", ".env")
with open(file, mode="wt", encoding="utf-8") as f:
f.writelines([
f"SECRET_KEY={os.urandom(32).hex()}\n"
])
if __name__ == "__main__":
try:
set_web_app_secret()
sys.exit(0)
except BaseException as e:
print(f"Error: {e}")
sys.exit(1)
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] | 2.324415 | 299 |
# -*- coding: utf-8 -*-
from resources.lib import kodiutils
from resources.lib import kodilogging
from resources.lib.messenger.socketclient import SockClient as SocketClient
import logging
import time
import xbmc
import xbmcaddon
from resources.lib.actions import execute
ADDON = xbmcaddon.Addon()
logger = logging.getLogger(ADDON.getAddonInfo('id'))
| [
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] | 2.733813 | 139 |
import random
from inventory import Inventory
from skill import Skill
from utility import Utility
# POKEMING - GON'NA CATCH 'EM ALL
# -- A simple hack 'n slash game in console
# -- This class is handles all player related things
# Default Constructor
# This prints the player's current stats
# This allows the player to attack an enemy
# <enemy> Enemy Object - The enemy to be attacked
# This function check if there is enough mana to cast the spell
# <mana_cost> Integer - The mana cost to cast the spell
# return boolean
# The function that allows the player to level up and gain some improvements
# This allows the player to take damage from an attack
# <value> Integer - The damage that the player will take
# This checks if the player is dead or not
# return boolean
# This allows the player to gain experience points and some coins after killing an enemy
# <enemy> Enemy Object - The enemy that was killed
# This allows the player to reflenish its mana in exchange with in-game coins
| [
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] | 3.424528 | 318 |
import time
import grpc
import threading
from crawl_service import crawl_service_pb2
from crawl_service import crawl_service_pb2_grpc
if __name__ == '__main__':
start_new_thread(f, 'codeforces', 'ConanYu')
start_new_thread(f, 'codeforces', 'ConanYu')
start_new_thread(f, 'codeforces', 'ConanYu')
start_new_thread(f, 'codeforces', '????????')
start_new_thread(g, 'vjudge', 'ConanYu')
start_new_thread(f, 'atcoder', 'ConanYu')
start_new_thread(g, 'codeforces', 'ConanYu')
start_new_thread(h, 'nowcoder')
start_new_thread(h, 'leetcode')
start_new_thread(h, 'atcoder')
start_new_thread(h, 'codeforces')
time.sleep(5.0)
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273,
728,
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272,
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220,
220,
220,
923,
62,
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62,
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69,
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62,
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62,
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7,
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2197,
66,
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198,
220,
220,
220,
923,
62,
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62,
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7,
71,
11,
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293,
316,
8189,
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198,
220,
220,
220,
923,
62,
3605,
62,
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7,
71,
11,
705,
265,
66,
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62,
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7,
71,
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891,
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728,
11537,
198,
220,
220,
220,
640,
13,
42832,
7,
20,
13,
15,
8,
198
] | 2.306897 | 290 |
from ..core import BlockParser
base_rules = [
(lambda x: ":GAP (global)" in x, _parse_bandgap)
]
class Scf2Parser(BlockParser):
"""Parser for Wien2k's .scf2 file"""
| [
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] | 2.542857 | 70 |
# -*- coding: utf-8 -*-
"""Top-level package for pdtimeout."""
__author__ = """Hugo Perrier"""
__email__ = '[email protected]'
__version__ = '0.1.0'
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# coding:utf-8
import time
from urllib import parse
import logging
from .SQLMap import SQLMap, CONTENT_STATUS, CONTENT_TYPE
DEFAULT_LEVEL = 1
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2,
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] | 2.92 | 50 |
import torch
from models.layers import Embedding, Linear, FactorizationMachine
class HOFMModel(torch.nn.Module):
"""
Model: Higher-Order Factorization Machines
Ref: M Blondel, et al. Higher-Order Factorization Machines, 2016.
"""
def forward(self, x):
"""
:param x: {'ids': LongTensor B*F, 'vals': FloatTensor B*F}
:return: y of size B, Regression and Classification (+sigmoid)
"""
x_emb = self.embedding(x) # B*F*Ex(order-1)
y = self.linear(x) + self.fm(x_emb[:, :, :self.nemb]) # B
for i in range(self.order-2):
emb = x_emb[:, :, (i+1)*self.nemb: (i+2)*self.nemb] # B*F*E
y += self.kernels[i](emb) # B
return y | [
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220,
220,
220,
220,
220,
220,
331,
15853,
2116,
13,
74,
44930,
58,
72,
16151,
24419,
8,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
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220,
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220,
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220,
220,
220,
1303,
347,
198,
220,
220,
220,
220,
220,
220,
220,
1441,
331
] | 1.977444 | 399 |
for _ in range(int(input())):
n=int(input())
L=[2**(i+1) for i in range(n)] #I want an extra 1 @l[0] to make it less
w=[0,0]
L=[2**(i+1) for i in range(n)]
L[n//2 -1],L[-1]=L[-1],L[n//2 -1]
for i in range(n):
if i<(n//2):
w[0]+=L[i]
else:
w[1]+=L[i]
print(w[0]-w[1])
#Algorithm is based on following idea of rearranging
'''
print(l)
for i in range(0,n//2-1):
l[i],l[i+(n//2)]=l[i+(n//2)],l[i]
print(l)
print(l)
'''
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300,
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58,
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3601,
7,
75,
8,
201,
198,
220,
220,
220,
705,
7061,
201,
198
] | 1.619048 | 336 |
import esprima
import glob
import os
from copy import deepcopy
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] | 3.764706 | 17 |
from arekit.common.folding.base import BaseDataFolding
class NoFolding(BaseDataFolding):
""" The case of absent folding in experiment.
"""
@property
def get_current_state(self):
""" Returns in order to be compatible with cv-based experiment format.
"""
return "0"
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] | 2.825688 | 109 |
import tornado.web
from pushpy_examples.client.ex_push_manager import ExamplePushManager
from client.simple_interpreter import Interpreter, Adder, Multiplier
m = ExamplePushManager()
m.connect()
repl_code_store = m.repl_code_store()
repl_code_store.update({
"interpreter.Interpreter": Interpreter,
"interpreter.math.Adder": Adder,
"interpreter.math.Multiplier": Multiplier
}, sync=True)
# curl -X POST -d'["add", "add", 1, 2, "mul", 3, 4]' -H 'Content-Type: application/json' localhost:11000/math
repl_code_store.set("/web/math", MathHandler, sync=True)
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6,
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25,
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198,
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62,
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62,
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14,
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11018,
1600,
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11,
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28,
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8,
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] | 2.733333 | 210 |
import json
import logger
import os
import random
from datetime import date
from dotenv import load_dotenv
from sys import exit
import discord
from discord.ext import commands, tasks
from discord.utils import get
log = logger.setup_applevel_logger(file_name = 'app_debug.log')
load_dotenv()
TOKEN = os.getenv('DISCORD_TOKEN')
GUILD = os.getenv('DISCORD_GUILD')
CHANNEL = os.getenv('SCHEDULER_CHANNEL')
CAPTAINS = os.getenv('CAPTAINS')
with open('POLL_OPTIONS', 'r') as f:
POLL_OPTIONS = eval(f.read())
RIDES = list(POLL_OPTIONS.values())
SCHEDULE = dict((ride, []) for ride in RIDES)
CAPTAINS_PER_RIDE = zip(RIDES, [1, 1, 2, 1, 1])
SCHEDULER_MSG = "@channel I'm a level 1 naive scheduling bot, and I make mistakes. " +\
"<@!766548029116907570> will help me fix it.\n"
# Instantiate bot
bot = commands.Bot(command_prefix='!')
async def manage_schedule(channel, msg_id):
"""Read reactions on last poll message
"""
log.debug('Running {}.'.format(manage_schedule.__name__))
await bot.wait_until_ready()
try:
msg = await channel.fetch_message(msg_id)
except discord.errors.NotFound:
log.error("Discord error: Message ID {} not found.".format(msg_id))
await bot.close()
exit()
log.debug("Got message with ID {}".format(msg_id))
reactions = msg.reactions
log.debug('Calling {} on channel.'.format(read_reactions.__name__))
avail = await read_reactions(reactions)
for ride, n_cap in CAPTAINS_PER_RIDE:
log.debug('Calling {} on channel for {}.'.
format(create_ride_schedule.__name__, ride))
captains = await create_ride_schedule(ride, n_cap, avail)
SCHEDULE[ride] = captains
log.debug('Calling {}.'.format(update_logs.__name__))
update_logs()
log.debug('Calling {} on channel.'.format(post_schedule.__name__))
await post_schedule(channel)
async def read_reactions(reactions):
"""Read reactions from scheduler poll
"""
log.debug('Running {}.'.format(read_reactions.__name__))
await bot.wait_until_ready()
log.debug('Getting availability from poll.')
emojis = list(POLL_OPTIONS.keys())
avail = dict((ride, []) for ride in RIDES)
for reaction in reactions:
ride_index = ''
try:
ride_index = emojis.index(reaction.emoji)
except ValueError:
log.error("Invalid reaction found: " + reaction.emoji)
continue
users = await reaction.users().flatten()
for user in users:
if not user.bot:
avail[RIDES[ride_index]].append(user)
log.debug('Availability is: {}'.format(
"\n".join(f'{k}: {users_to_names(v)}' for k,v in avail.items())
))
return avail
async def create_ride_schedule(ride, n_cap, avail):
"""Create road captain schedule
"""
log.debug('Running {}.'.format(create_ride_schedule.__name__))
await bot.wait_until_ready()
log.debug('Choosing road captains for {}'.format(ride))
captains = []
# choose randomly for now
for i in range(n_cap):
#captain = prioritise_absence(ride, avail)
try:
captain = random.choice(avail[ride])
except IndexError:
captain = None
captains.append(captain)
# don't pick same captain twice for one ride
if captain in avail[ride]:
avail[ride].remove(captain)
for s in avail.keys():
if captain in avail[s] and len(avail[s]) > 2:
log.debug('Scheduled {} on {}. Removing them from {}'.
format(captain.display_name, ride, s))
avail[s].remove(captain)
log.debug(
"Road captains for {} are {}".format(ride, users_to_names(captains))
)
return captains
def prioritise_absence(ride, avail):
"""Prioritise captains that have been absent longer than others
"""
log.debug('Running {}.'.format(prioritise_absence.__name__))
with open('schedule') as f:
schedule = [json.loads(line) for line in f]
print(schedule)
exit()
return None
def update_logs():
"""Update log files.
"""
log.debug('Running {}.'.format(update_logs.__name__))
# log schedule to file
log.debug('Saving schedule to log.')
printable_schedule = SCHEDULE.copy()
for ride in printable_schedule:
printable_schedule[ride] = users_to_names(printable_schedule[ride])
printable_schedule['date'] = str(date.today())
json_schedule = json.dumps(printable_schedule)
with open("schedule", 'a') as f:
f.write('\n' + json_schedule)
log.debug(json_schedule)
async def post_schedule(channel):
"""Post schedule to channel.
"""
log.debug('Running {}.'.format(create_ride_schedule.__name__))
await bot.wait_until_ready()
msg = SCHEDULER_MSG + "\nRoad captains for this week are"
schedule_post = SCHEDULE.copy()
for ride in schedule_post:
schedule_post[ride] = users_to_tags(schedule_post[ride])
for k, v in schedule_post.items():
msg += f"\n\n**{k}**\n" +\
"\n".join(f'{c}' for c in v)
log.debug('Send message to channel: \n{}'.format(msg))
m = await channel.send(msg)
def users_to_names(users):
"""Convert a list of Users to a list of user names (str).
"""
return [u.display_name if u is not None else '' for u in users]
def users_to_tags(users):
"""Convert a list of Users to a list of tags (str).
"""
return ["<@!{}>".format(u.id) if u is not None else '' for u in users]
def user_to_tag(user):
"""Convert a list of Users to a list of tags (str).
"""
return "<@!{}>".format(user.id) if user is not None else ''
@bot.event
async def on_ready():
"""Set up variables and logging
"""
log.debug('Running {}'.format(on_ready.__name__))
await bot.wait_until_ready()
log.debug('Logged in as {}'.format(bot.user.name))
channel = bot.get_channel(int(CHANNEL))
log.debug('Channel is {}'.format(channel))
with open("MESSAGE_ID", 'r') as f:
msg_id = int(f.readline())
log.debug('Read poll message with ID {}.'.format(msg_id))
log.debug('Calling {} on channel.'.format(manage_schedule.__name__))
await manage_schedule(channel, msg_id)
log.debug('Shutdown poll bot.')
await bot.close()
log.debug('Starting scheduler bot.')
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10214,
2637,
8,
198,
13645,
13,
5143,
7,
10468,
43959,
8
] | 2.450248 | 2,623 |
import time
import requests
import os
from os import path
import cv2
import numpy as np
from aperturedb import ParallelLoader
from aperturedb import CSVParser
from aperturedb import ProgressBar
HEADER_PATH = "filename"
HEADER_URL = "url"
class ImageDownloaderCSV(CSVParser.CSVParser):
'''
ApertureDB Image Downloader.
Expects a csv file with AT LEAST a "url" column, and
optionally a "filename" field.
If "filename" is not present, it is taken from the url.
'''
| [
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422,
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628,
220,
220,
220,
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] | 2.796703 | 182 |
from unittest import TestCase
from unittest.mock import MagicMock
import pytest
from kubernetes import client
from libs.api import API_KEY_NAME
from scheduler.spawners.templates.env_vars import (
get_env_var,
get_from_app_secret,
get_resources_env_vars,
get_service_env_vars
)
@pytest.mark.spawner_mark
| [
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] | 2.592 | 125 |
import matplotlib.pyplot as plt
import numpy as np
import seaborn as sns
sns.reset_orig()
| [
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] | 2.727273 | 33 |
"""Entity Xplora® Watch."""
from __future__ import annotations
import logging
from datetime import timedelta
from typing import Any, Dict
from homeassistant.components.switch import SwitchEntity
from homeassistant.helpers.restore_state import RestoreEntity
from .helper import XploraUpdateTime
from pyxplora_api import pyxplora_api_async as PXA
_LOGGER = logging.getLogger(__name__)
| [
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] | 3.305085 | 118 |
"""
Unit test for Treadmill apptrace events module.
"""
import unittest
import mock
from treadmill.apptrace import events
class AppTraceEventsTest(unittest.TestCase):
"""Test all event classes operations.
"""
@mock.patch('treadmill.apptrace.events.AbortedTraceEvent.from_data',
mock.Mock(set_spec=True))
@mock.patch('treadmill.apptrace.events.ConfiguredTraceEvent.from_data',
mock.Mock(set_spec=True))
@mock.patch('treadmill.apptrace.events.DeletedTraceEvent.from_data',
mock.Mock(set_spec=True))
@mock.patch('treadmill.apptrace.events.FinishedTraceEvent.from_data',
mock.Mock(set_spec=True))
@mock.patch('treadmill.apptrace.events.KilledTraceEvent.from_data',
mock.Mock(set_spec=True))
@mock.patch('treadmill.apptrace.events.PendingTraceEvent.from_data',
mock.Mock(set_spec=True))
@mock.patch('treadmill.apptrace.events.ScheduledTraceEvent.from_data',
mock.Mock(set_spec=True))
@mock.patch(('treadmill.apptrace.events'
'.ServiceExitedTraceEvent.from_data'),
mock.Mock(set_spec=True))
@mock.patch(('treadmill.apptrace.events'
'.ServiceRunningTraceEvent.from_data'),
mock.Mock(set_spec=True))
def test_factory(self):
"""Test class factory operations.
"""
events.AppTraceEvent.from_data(
timestamp=1,
source='tests',
instanceid='proid.foo#123',
event_type='scheduled',
event_data='here',
payload={'foo': 'bar'}
)
events.ScheduledTraceEvent.from_data.assert_called_with(
timestamp=1,
source='tests',
instanceid='proid.foo#123',
event_type='scheduled',
event_data='here',
payload={'foo': 'bar'}
)
events.AppTraceEvent.from_data(
timestamp=2,
source='tests',
instanceid='proid.foo#123',
event_type='pending',
event_data=None,
payload={'foo': 'bar'}
)
events.PendingTraceEvent.from_data.assert_called_with(
timestamp=2,
source='tests',
instanceid='proid.foo#123',
event_type='pending',
event_data=None,
payload={'foo': 'bar'}
)
def test_factory_bad_event(self):
"""Tests that failure to parse the event returns None.
"""
res = events.AppTraceEvent.from_data(
timestamp=2,
source='tests',
instanceid='proid.foo#123',
event_type='does_not_exists',
event_data=None,
payload={'foo': 'bar'}
)
self.assertIsNone(res)
res = events.AppTraceEvent.from_data(
timestamp=2,
source='tests',
instanceid='proid.foo#123',
event_type='service_running',
event_data=None,
payload={'foo': 'bar'}
)
self.assertIsNone(res)
def test_scheduled(self):
"""Scheduled event operations.
"""
event = events.ScheduledTraceEvent(
timestamp=1,
source='tests',
instanceid='proid.foo#123',
where='here',
why='because',
payload={'foo': 'bar'}
)
self.assertEqual(
event.to_dict(),
{
'event_type': 'scheduled',
'timestamp': 1,
'source': 'tests',
'instanceid': 'proid.foo#123',
'where': 'here',
'why': 'because',
'payload': {'foo': 'bar'},
}
)
self.assertEqual(
event.to_data(),
(
1,
'tests',
'proid.foo#123',
'scheduled',
'here:because',
{'foo': 'bar'},
)
)
self.assertEqual(
event,
events.ScheduledTraceEvent.from_data(
timestamp=1,
source='tests',
instanceid='proid.foo#123',
event_type='scheduled',
event_data='here:because',
payload={'foo': 'bar'}
)
)
def test_pending(self):
"""Pending event operations.
"""
event = events.PendingTraceEvent(
why='created',
timestamp=2,
source='tests',
instanceid='proid.foo#123',
payload={'foo': 'bar'}
)
self.assertEqual(
event.to_dict(),
{
'event_type': 'pending',
'timestamp': 2,
'source': 'tests',
'instanceid': 'proid.foo#123',
'payload': {'foo': 'bar'},
'why': 'created',
}
)
self.assertEqual(
event.to_data(),
(
2,
'tests',
'proid.foo#123',
'pending',
'created',
{'foo': 'bar'},
)
)
self.assertEqual(
event,
events.PendingTraceEvent.from_data(
timestamp=2,
source='tests',
instanceid='proid.foo#123',
event_type='pending',
event_data='created',
payload={'foo': 'bar'}
)
)
def test_configured(self):
"""Configured event operations.
"""
event = events.ConfiguredTraceEvent(
timestamp=1,
source='tests',
instanceid='proid.foo#123',
uniqueid='AAAA',
payload={'foo': 'bar'}
)
self.assertEqual(
event.to_dict(),
{
'event_type': 'configured',
'timestamp': 1,
'source': 'tests',
'instanceid': 'proid.foo#123',
'uniqueid': 'AAAA',
'payload': {'foo': 'bar'},
}
)
self.assertEqual(
event.to_data(),
(
1,
'tests',
'proid.foo#123',
'configured',
'AAAA',
{'foo': 'bar'},
)
)
self.assertEqual(
event,
events.ConfiguredTraceEvent.from_data(
timestamp=1,
source='tests',
instanceid='proid.foo#123',
event_type='configured',
event_data='AAAA',
payload={'foo': 'bar'}
)
)
def test_deleted(self):
"""Deleted event operations.
"""
event = events.DeletedTraceEvent(
timestamp=1,
source='tests',
instanceid='proid.foo#123',
payload={'foo': 'bar'}
)
self.assertEqual(
event.to_dict(),
{
'event_type': 'deleted',
'timestamp': 1,
'source': 'tests',
'instanceid': 'proid.foo#123',
'payload': {'foo': 'bar'},
}
)
self.assertEqual(
event.to_data(),
(
1,
'tests',
'proid.foo#123',
'deleted',
'',
{'foo': 'bar'},
)
)
self.assertEqual(
event,
events.DeletedTraceEvent.from_data(
timestamp=1,
source='tests',
instanceid='proid.foo#123',
event_type='deleted',
event_data='not used',
payload={'foo': 'bar'}
)
)
def test_finished(self):
"""Finished event operations.
"""
event = events.FinishedTraceEvent(
timestamp=1,
source='tests',
instanceid='proid.foo#123',
rc=1,
signal=2,
payload={'foo': 'bar'}
)
self.assertEqual(
event.to_dict(),
{
'event_type': 'finished',
'timestamp': 1,
'source': 'tests',
'instanceid': 'proid.foo#123',
'rc': 1,
'signal': 2,
'payload': {'foo': 'bar'},
}
)
self.assertEqual(
event.to_data(),
(
1,
'tests',
'proid.foo#123',
'finished',
'1.2',
{'foo': 'bar'},
)
)
self.assertEqual(
event,
events.FinishedTraceEvent.from_data(
timestamp=1,
source='tests',
instanceid='proid.foo#123',
event_type='finished',
event_data='1.2',
payload={'foo': 'bar'}
)
)
def test_aborted(self):
"""Aborted event operations.
"""
event = events.AbortedTraceEvent(
timestamp=1,
source='tests',
instanceid='proid.foo#123',
why='reason',
payload={'foo': 'bar'}
)
self.assertEqual(
event.to_dict(),
{
'event_type': 'aborted',
'timestamp': 1,
'source': 'tests',
'instanceid': 'proid.foo#123',
'why': 'reason',
'payload': {'foo': 'bar'},
}
)
self.assertEqual(
event.to_data(),
(
1,
'tests',
'proid.foo#123',
'aborted',
'reason',
{'foo': 'bar'},
)
)
self.assertEqual(
event,
events.AbortedTraceEvent.from_data(
timestamp=1,
source='tests',
instanceid='proid.foo#123',
event_type='aborted',
event_data='reason',
payload={'foo': 'bar'}
)
)
def test_killed(self):
"""Killed event operations.
"""
event = events.KilledTraceEvent(
timestamp=1,
source='tests',
instanceid='proid.foo#123',
is_oom=True,
payload={'foo': 'bar'}
)
self.assertEqual(
event.to_dict(),
{
'event_type': 'killed',
'timestamp': 1,
'source': 'tests',
'instanceid': 'proid.foo#123',
'is_oom': True,
'payload': {'foo': 'bar'},
}
)
self.assertEqual(
event.to_data(),
(
1,
'tests',
'proid.foo#123',
'killed',
'oom',
{'foo': 'bar'},
)
)
self.assertEqual(
event,
events.KilledTraceEvent.from_data(
timestamp=1,
source='tests',
instanceid='proid.foo#123',
event_type='killed',
event_data='oom',
payload={'foo': 'bar'}
)
)
def test_service_running(self):
"""ServiceRunning event operations.
"""
event = events.ServiceRunningTraceEvent(
timestamp=1,
source='tests',
instanceid='proid.foo#123',
uniqueid='AAAA',
service='web.web',
payload={'foo': 'bar'}
)
self.assertEqual(
event.to_dict(),
{
'event_type': 'service_running',
'timestamp': 1,
'source': 'tests',
'instanceid': 'proid.foo#123',
'uniqueid': 'AAAA',
'service': 'web.web',
'payload': {'foo': 'bar'},
}
)
self.assertEqual(
event.to_data(),
(
1,
'tests',
'proid.foo#123',
'service_running',
'AAAA.web.web',
{'foo': 'bar'},
)
)
self.assertEqual(
event,
events.ServiceRunningTraceEvent.from_data(
timestamp=1,
source='tests',
instanceid='proid.foo#123',
event_type='service_running',
event_data='AAAA.web.web',
payload={'foo': 'bar'}
)
)
def test_service_exited(self):
"""ServiceExited event operations.
"""
event = events.ServiceExitedTraceEvent(
timestamp=1,
source='tests',
instanceid='proid.foo#123',
uniqueid='AAAA',
service='web.x',
rc=1,
signal=2,
payload={'foo': 'bar'}
)
self.assertEqual(
event.to_dict(),
{
'event_type': 'service_exited',
'timestamp': 1,
'source': 'tests',
'instanceid': 'proid.foo#123',
'uniqueid': 'AAAA',
'service': 'web.x',
'rc': 1,
'signal': 2,
'payload': {'foo': 'bar'},
}
)
self.assertEqual(
event.to_data(),
(
1,
'tests',
'proid.foo#123',
'service_exited',
'AAAA.web.x.1.2',
{'foo': 'bar'},
)
)
self.assertEqual(
event,
events.ServiceExitedTraceEvent.from_data(
timestamp=1,
source='tests',
instanceid='proid.foo#123',
event_type='service_exited',
event_data='AAAA.web.x.1.2',
payload={'foo': 'bar'}
)
)
if __name__ == '__main__':
unittest.main()
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] | 1.639959 | 8,774 |
""" Tests for plotdirective build using sphinx extensions
Test ability to combine plot_directive with mathcode
"""
from os.path import dirname, join as pjoin
import re
import sphinx
SPHINX_1p8 = sphinx.version_info[:2] >= (1, 8)
from sphinxtesters import PageBuilder
from texext.tests.test_plotdirective import EXP_PLOT_AND_MATH
PAGES = pjoin(dirname(__file__), 'plotdirective')
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# Copyright (c) 2020
# [This program is licensed under the "MIT License"]
# Please see the file LICENSE in the source
# distribution of this software for license terms.
import pygame as pg
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"""Tests for the features module."""
import numpy as np
from aroma import features
def test_feature_time_series(mel_mix, mc, max_correls):
"""Test the feature_time_series feature against pre-calculated values."""
np.random.seed(1)
# Read mel_mix
mel_mix = np.loadtxt(mel_mix)
# Run feature_time_series
max_RP_corr, _ = features.feature_time_series(mel_mix, mc)
# Read features csv
max_correls = np.load(max_correls)
assert np.allclose(max_correls, max_RP_corr, atol=1e-2)
# Run feature_time_series with metric metadata
metadata = {}
max_RP_corr, updated_metadata = features.feature_time_series(
mel_mix,
mc,
metric_metadata=metadata,
)
assert "max_RP_corr" in updated_metadata.keys()
def test_feature_frequency(mel_FT_mix, HFC):
"""Test the feature_frequency feature against pre-calculated values."""
np.random.seed(1)
# Read mel_FT_mix
mel_FT_mix = np.loadtxt(mel_FT_mix)
# Run feature_frequency
HFC_test, _ = features.feature_frequency(mel_FT_mix, TR=2)
# Read features csv
HFC = np.load(HFC)
assert np.allclose(HFC, HFC_test)
# Run feature_frequency with metric metadata
metadata = {}
HFC_test, updated_metadata = features.feature_frequency(
mel_FT_mix,
TR=2,
metric_metadata=metadata,
)
assert "HFC" in updated_metadata.keys()
def test_feature_spatial(mel_IC, edgeFract, csfFract):
"""Test the feature_spatial features against pre-calculated values."""
np.random.seed(1)
# Run feature_spatial
edge_fract, csf_fract, _ = features.feature_spatial(mel_IC)
# Read features csv
edgeFract = np.load(edgeFract)
csfFract = np.load(csfFract)
assert np.allclose(edgeFract, edge_fract)
assert np.allclose(csfFract, csf_fract)
# Run feature_spatial with metric metadata
metadata = {}
edge_fract, csf_fract, updated_metadata = features.feature_spatial(mel_IC, metadata)
assert "edge_fract" in updated_metadata.keys()
assert "csf_fract" in updated_metadata.keys()
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] | 2.524155 | 828 |
import pytest
from alive_progress.animations.spinners import alongside_spinner_factory, \
bouncing_spinner_factory, delayed_spinner_factory, frame_spinner_factory, \
scrolling_spinner_factory, sequential_spinner_factory
from alive_progress.utils.cells import join_cells
@pytest.mark.parametrize('frames, expected', [
('a\nb', (('a', ' ', 'b'),)),
('abc', (('a', 'b', 'c'),)),
(('a\nb', '\nc '), (('a b', ' c '),)),
(('a ', ' b ', ' c'), (('a ', ' b ', ' c'),)),
(('a', '(a)', ' (*) '), (('aaaaa', '(a)(a', ' (*) '),)),
(('ok', '😺😺'), (('okok', '😺😺'),)),
])
@pytest.mark.parametrize('length, block, background, right, hide, expected', [
(None, None, ' ', True, True, ((' ', 'c ', 'bc ', 'abc', ' ab', ' a'),)),
(None, None, ' ', False, True, ((' ', ' a', ' ab', 'abc', 'bc ', 'c '),)),
(None, None, ' ', True, False, (('abc', 'cab', 'bca'),)),
(None, None, ' ', False, False, (('abc', 'bca', 'cab'),)),
(2, None, '~', True, True, (('~~', 'c~', 'bc', 'ab', '~a'),)),
(2, None, '~', True, False, (('bc', 'ab', 'ca'),)),
(2, None, '~', False, True, (('~~', '~a', 'ab', 'bc', 'c~'),)),
(2, None, '~', False, False, (('ab', 'bc', 'ca'),)),
(3, None, '~', True, True, (('~~~', 'c~~', 'bc~', 'abc', '~ab', '~~a'),)),
(3, None, '~', True, False, (('abc', 'cab', 'bca'),)),
(3, None, '~', False, True, (('~~~', '~~a', '~ab', 'abc', 'bc~', 'c~~'),)),
(3, None, '~', False, False, (('abc', 'bca', 'cab'),)),
(4, None, ' ', True, True, ((' ', 'c ', 'bc ', 'abc ', ' abc', ' ab', ' a'),)),
(4, None, ' ', True, False, (('abc ', ' abc', 'c ab', 'bc a'),)),
(4, None, ' ', False, True, ((' ', ' a', ' ab', ' abc', 'abc ', 'bc ', 'c '),)),
(4, None, ' ', False, False, ((' abc', 'abc ', 'bc a', 'c ab'),)),
(4, 1, '_', True, True, (('____', 'a___', '_a__', '__a_', '___a'),
('____', 'b___', '_b__', '__b_', '___b'),
('____', 'c___', '_c__', '__c_', '___c'))),
(4, 2, '_', True, False, (('aa__', '_aa_', '__aa', 'b__a'),
('bb__', '_bb_', '__bb', 'c__b'),
('cc__', '_cc_', '__cc', 'a__c'))),
])
@pytest.mark.parametrize('length, block, background, hide, expected', [
(None, None, None, True, ((' ', 'c ', 'bc ', 'abc', ' ab', ' a'),
(' ', ' d', ' de', 'def', 'ef ', 'f '),)),
(None, None, None, False, (('abc',), ('def',),)),
(2, None, '~', True, (('~~', 'c~', 'bc', 'ab', '~a'), ('~~', '~d', 'de', 'ef', 'f~'),)),
(2, None, '~', False, (('bc', 'ab'), ('de', 'ef'),)),
(3, None, '+', True, (('+++', 'c++', 'bc+', 'abc', '+ab', '++a'),
('+++', '++d', '+de', 'def', 'ef+', 'f++'),)),
(3, None, '+', False, (('abc',), ('def',),)),
(4, None, ' ', True, ((' ', 'c ', 'bc ', 'abc ', ' abc', ' ab', ' a'),
(' ', ' d', ' de', ' def', 'def ', 'ef ', 'f '),)),
(4, None, ' ', False, (('abc ', ' abc'), (' def', 'def '),)),
(3, 1, '_', True, (('___', 'a__', '_a_', '__a'),
('___', '__d', '_d_', 'd__'),
('___', 'b__', '_b_', '__b'),
('___', '__e', '_e_', 'e__'),
('___', 'c__', '_c_', '__c'),
('___', '__f', '_f_', 'f__'))),
(5, 2, '_', False, (('aa___', '_aa__', '__aa_', '___aa'),
('___dd', '__dd_', '_dd__', 'dd___'),
('bb___', '_bb__', '__bb_', '___bb'),
('___ee', '__ee_', '_ee__', 'ee___'),
('cc___', '_cc__', '__cc_', '___cc'),
('___ff', '__ff_', '_ff__', 'ff___'))),
])
@pytest.mark.parametrize('inputs, expected', [
(('123', 'abc'), (('1a', '2b', '3c'),)),
(('12', 'abc'), (('1a', '2b', '1c', '2a', '1b', '2c'),)),
((('12', '34', '56'), 'ab'), (('12a', '34b', '56a', '12b', '34a', '56b'),)),
])
@pytest.mark.parametrize('inputs, expected', [
(('123', 'abc'), (('1a', '2b', '3c'),)),
(('12', 'abc'), (('1a', '2b'), ('1c', '2a'), ('1b', '2c'))),
((('12', '34', '56'), 'ab'), (('12a', '34b', '56a'), ('12b', '34a', '56b'))),
])
@pytest.mark.parametrize('inputs, expected', [
(('123', 'abc'), (('11a', '22b', '33c'),)),
(('12', 'abc'), (('11a', '22b', '11c', '22a', '11b', '22c'),)),
((('12', '34', '56'), 'ab'), (('12a', '34b', '56a', '12b', '34a', '56b'),)),
])
@pytest.mark.parametrize('inputs, expected', [
(('123', 'abc'), (('1',), ('a',), ('2',), ('b',), ('3',), ('c',))),
(('12', 'abc'), (('1',), ('a',), ('2',), ('b',), ('1',), ('c',),
('2',), ('a',), ('1',), ('b',), ('2',), ('c',))),
((('12', '34', '56'), 'ab'), (('1', '2'), ('a',), ('3', '4'), ('b',), ('5', '6'), ('a',),
('1', '2'), ('b',), ('3', '4'), ('a',), ('5', '6'), ('b',))),
])
@pytest.mark.parametrize('inputs, expected', [
(('123', 'abc'), (('1',), ('2',), ('3',), ('a',), ('b',), ('c',))),
(('12', 'abc'), (('1',), ('2',), ('a',), ('b',), ('c',))),
((('12', '34', '56'), 'ab'), (('1', '2'), ('3', '4'), ('5', '6'), ('a',), ('b',))),
])
@pytest.mark.parametrize('copies, offset, expected', [
(3, 1, (('123', '234', '345', '451', '512'),)),
(4, 2, (('1352', '2413', '3524', '4135', '5241'),)),
])
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] | 1.87513 | 2,891 |
#!/usr/bin/python
# -*- coding: UTF-8 -*-
import logging
import datetime
import smtplib
import os
import subprocess
class ZpjUtils(object):
'''
一个工具类
'''
def __init__(self):
'''
Constructor
'''
begin_work_time = datetime.datetime.now()
smtp = None
'''
cmdstr：命令行
is_logger_out：是否输出日志，默认为True
返回值：0为正常，其他为异常
'''
'''
project_path：获取项目后存放的目录
project_name：项目名
git_url：git地址
'''
'''
pom_file: pom.xml
'''
'''
project_path：项目目录
'''
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] | 1.376168 | 428 |
from typing import Union, List
from scriptable.api import AST
from scriptable.api.ast_binding import ASTBinding
DataType = Union[int, float]
| [
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] | 3.512195 | 41 |
import os
from flask import Flask
from flask_sqlalchemy import SQLAlchemy
from flask_migrate import Migrate
from itsdangerous import TimedJSONWebSignatureSerializer as Serializer
from config import config
# Create instances of necessary Flask extensions.
db = SQLAlchemy()
migrate = Migrate()
# Import the models so that they are registered with SQLAlchemy.
from goal_tracker import models
| [
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] | 3.97 | 100 |
# Copyright 2018 Amazon.com, Inc. or its affiliates. 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.
# A copy of the License is located at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# or in the "license" file accompanying this file. This file 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 pytest
import mxnet as mx
import numpy as np
from mxfusion.components.variables.runtime_variable import add_sample_dimension, array_has_samples
@pytest.mark.usefixtures("set_seed")
| [
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] | 3.630252 | 238 |
import numpy as np
from datetime import datetime, timedelta
import json
import os
start_work = 9 * 60 * 60 # Work start from 9:00. unit: second
end_work = 17 * 60 * 60 # Work end at 17:00. unit: second
daily_report = 16 * 60 * 60 # Daily progress report at 16:00, in meeting room
daily_report_mean = 15 * 60 # Daily progress report average length 15 min
daily_report_std = 1 * 60 # Daily progress report std.dev 1 min
come_leave_flex_coef = 30 * 60 # Tend to come 8:30, average arrive at 9:00. Leave is similar. Exponential distribution
call_for_absence = 0.01 # Possibility of not come to the office
lunch_start_time = 12 * 60 * 60 # Lunch serve start time 12:00. unit: second
lunch_end_time = 13 * 60 * 60 # Lunch serve end time 13:00. unit: second
eat_time_a = 10 # average time for each person to eat lunch. Beta distribution
eat_time_b = 50 # average time for each person to eat lunch. Beta distribution
cut_off_time = 14 * 60 * 60 # After this time, the person won't come to work
day_cut_off = 24 * 60 * 60
start_synthetic_data = datetime(2020, 3, 25) # start date
end_synthetic_data = datetime(2020, 3, 27) # end date
report_interval = timedelta(seconds=1) # Time interval between two consecutive package
guest_lambda = 3 # Poisson arrival for unknown customers. unit: person per day
visit_colleague = 3 # How many times a worker goes to a colleague's office
average_stay_in_colleague_office = 30 * 60
std_stay_in_colleague_office = 4 * 60
average_stay_customer = 30 * 60
std_stay_customer = 5 * 60
sensor_type = ["Room_Outlet_Controller",
"Room_Motion_Sensor",
"Room_Temperature_Sensor",
"Room_Lock_Controller",
"Room_Door_Camera"]
# value = (np.random.beta(eat_time_a, eat_time_b, 10000) + 0.1) * 100
possible_locations = ["home", "Room_1_1_140", "Room_1_1_141", "Room_1_1_142", "Room_1_1_143", "Room_1_1_144",
"Room_1_1_150", "Room_1_1_184", "busy"]
walking_time = {"Room_1_1_140": {"Room_1_1_140": 0,
"Room_1_1_141": 2,
"Room_1_1_142": 2,
"Room_1_1_143": 3,
"Room_1_1_144": 4,
"Room_1_1_150": 1,
"Room_1_1_184": 2},
"Room_1_1_141": {"Room_1_1_140": 2,
"Room_1_1_141": 0,
"Room_1_1_142": 3,
"Room_1_1_143": 4,
"Room_1_1_144": 5,
"Room_1_1_150": 1,
"Room_1_1_184": 2},
"Room_1_1_142": {"Room_1_1_140": 2,
"Room_1_1_141": 3,
"Room_1_1_142": 0,
"Room_1_1_143": 2,
"Room_1_1_144": 2,
"Room_1_1_150": 1,
"Room_1_1_184": 3},
"Room_1_1_143": {"Room_1_1_140": 3,
"Room_1_1_141": 4,
"Room_1_1_142": 2,
"Room_1_1_143": 0,
"Room_1_1_144": 2,
"Room_1_1_150": 1,
"Room_1_1_184": 4},
"Room_1_1_144": {"Room_1_1_140": 4,
"Room_1_1_141": 5,
"Room_1_1_142": 2,
"Room_1_1_143": 2,
"Room_1_1_144": 0,
"Room_1_1_150": 1,
"Room_1_1_184": 5},
"Room_1_1_150": {"Room_1_1_140": 1,
"Room_1_1_141": 1,
"Room_1_1_142": 1,
"Room_1_1_143": 1,
"Room_1_1_144": 1,
"Room_1_1_150": 0,
"Room_1_1_184": 1},
"Room_1_1_184": {"Room_1_1_140": 2,
"Room_1_1_141": 4,
"Room_1_1_142": 4,
"Room_1_1_143": 5,
"Room_1_1_144": 5,
"Room_1_1_150": 1,
"Room_1_1_184": 0}}
lock_setting = {"Room_1_1_140": "Room_1_1_150",
"Room_1_1_141": "Room_1_1_150",
"Room_1_1_142": "Room_1_1_150",
"Room_1_1_143": "Room_1_1_150",
"Room_1_1_144": "Room_1_1_150",
"Room_1_1_150": "Room_1_1_184",
"Room_1_1_184": "home",
"home": "Room_1_1_184"}
worker_assign = [Person("Employee 1", "[email protected]", "Room_1_1_140"),
Person("Employee 2", "[email protected]", "Room_1_1_142"),
Person("Employee 3", "[email protected]", "Room_1_1_144"),
Person("Employee 4", "[email protected]", "Room_1_1_143")]
sensors = list()
# label, uuid, brick_name, room
with open("sensor_config.json", 'r') as json_file:
sensor_config = json.load(json_file)
for room in sensor_config:
for brick in sensor_config[room]:
uuid = sensor_config[room][brick]["UUID"]
label = sensor_config[room][brick]["Type"]
sensors.append(Sensor(label, uuid, brick, room))
sensors.append(Sensor("SmartThings v3 Hub", "ede0ef78-70b7-4756-9dd6-db82d33fc9eb", None, None))
# print(len(np.nonzero(np.array([False, False, True]))[0]))
# value = (np.random.beta(eat_time_a, eat_time_b, 10000) + 0.1) * 100
# print(24 * 60 * 60)
# plt.hist(value)
# plt.show()
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#!/usr/bin/env python3
from os import path
import sys, subprocess, argparse
parser = argparse.ArgumentParser(description='Automates the process of evaluating a word embedding.')
parser.add_argument('file', type=str, help='Word embedding file.')
parser.add_argument('-skip-regen', '--skip-regen', action='store_false', help="Skip regenerating the numpy and .py cache files (default always regenerates)")
parser.add_argument('-skip-similarity', '--skip-similarity', action='store_true', help="Skip similarity analyses (default does not skip)")
parser.add_argument('-skip-analogy', '--skip-analogy', action='store_true', help="Skip analogy analyses (default does not skip)")
parser.add_argument('-preserve-base-embedding', '--preserve-base-embedding', action='store_true', help="Don't delete the base embedding after creating .npy and .vocab caches")
parser.add_argument('-vocab', '--vocab', type=str, default=None, help='Vocabulary file to recount from')
parser.add_argument('-verbose', '--verbose', action='store_true', help='Output bonus info for analysis')
parser.add_argument('-simlex-bin', '--simlex-bin', action='store_true', help='Set output to only simlex bin')
parser.add_argument('-cutoff', '--cutoff', type=int, default=200, help='Cutoff for evaluation')
args = parser.parse_args()
if args.simlex_bin:
args.verbose=True
script_home = path.dirname(__file__)
hyperdir = path.join(script_home, "hyperwords")
# Hyperwords requires embedding to be *.words
base_embedding = path.relpath(args.file)
words_ready = base_embedding.endswith(".words")
if words_ready:
embedding = base_embedding
base_embedding = base_embedding[:-6]
# Attempting to skip regen but it doesn't exist--soft default back to not skipping
if not args.skip_regen and not (path.exists(embedding+".npy") and path.exists(embedding+".vocab")):
args.skip_regen = True
elif not args.skip_regen and not args.simlex_bin:
print("Using existing HyperWords adjusted embedding based on {0} and {1}".format(embedding+".npy", embedding+".vocab"))
else:
# Create suitable name
embedding = path.relpath(base_embedding+".words")
if not args.simlex_bin:
print("{0} is not a *.words file (HyperWords requirement), copying to {1}...".format(base_embedding, embedding))
if path.exists(embedding): # Potentially unsafe to copy
print("{0} already exists. Overwrite? y/n: ".format(embedding), end='')
choice = input()
while choice.lower() not in ['y', 'n']:
print("Unrecognized input ({0})! {1} already exists. Overwrite? y/n: ".format(choice, embedding), end='')
choice = input()
if choice.lower() == 'y':
args.skip_regen = True # This will be a new file, it must have embeddings regenerated
import shutil
shutil.copyfile(base_embedding, embedding)
del shutil
else:
args.skip_regen = False
else: # No collision, safe to copy
import shutil
shutil.copyfile(base_embedding, embedding)
del shutil
# Create embedding for hyperwords
if args.skip_regen:
# Special case: Base embedding does not exist
if not path.exists(embedding):
if not args.simlex_bin:
print("No base embedding found to regenerate!!")
if path.exists(embedding+'.npy') and path.exists(embedding+'.vocab'):
if not args.simlex_bin:
print("Continuing with cached materials {0}.npy and {0}.vocab".format(embedding))
else:
print("No cached {0}.npy or {0}.vocab to use, please ensure the correct file path was specified.".format(embedding))
exit()
else:
# Apply numpy fixup for Hyperwords
if not args.simlex_bin:
print("Adjusting embedding for HyperWords Use...")
completed_proc = subprocess.run(['python2', path.relpath(hyperdir+'/hyperwords/text2numpy.py'), embedding])
if completed_proc.returncode != 0:
print("FAILURE! Aborting.")
exit()
# Preserve disk space after cache by removing the original ascii file
if not args.preserve_base_embedding:
import os
os.remove(embedding)
# Perform hyperwords evaluations
if not args.skip_similarity:
extension = ['--vocab', args.vocab] if args.vocab is not None else []
if args.verbose:
extension.extend(['--verbose', '1'])
if not args.simlex_bin:
print("Similarity Results (WS353, SimLex999)\n-------------------------------------")
cmd = ['python2', path.relpath(hyperdir+'/hyperwords/ws_eval.py'), 'embedding', base_embedding, path.relpath(hyperdir+'/testsets/ws/ws353.txt')]
cmd.extend(extension)
completed_proc = subprocess.run(cmd)
if completed_proc.returncode != 0:
if completed_proc.stdout is not None:
print(f'stdout ws353: {completed_proc.stdout}')
if completed_proc.stderr is not None:
print(f'stderr ws353: {completed_proc.stderr}')
print("FAILURE! Aborting.")
exit()
print()
cmd = ['python2', path.relpath(hyperdir+'/hyperwords/ws_eval.py'), 'embedding', base_embedding, path.relpath(hyperdir+'/testsets/ws/SimLex999.txt')]
cmd.extend(extension)
if args.cutoff > 0:
cmd.extend(['--cutoff', str(args.cutoff)])
completed_proc = subprocess.run(cmd)
if completed_proc.returncode != 0:
if completed_proc.stdout is not None:
print(f'stdout simlex999: {completed_proc.stdout}')
if completed_proc.stderr is not None:
print(f'stderr simlex999: {completed_proc.stderr}')
print("FAILURE! Aborting.")
exit()
if not args.simlex_bin:
print()
if not args.skip_analogy and not args.simlex_bin:
print("Google Analogy Results\n----------------------")
completed_proc = subprocess.run(['python2', path.relpath(hyperdir+'/hyperwords/analogy_eval.py'), 'embedding', base_embedding, path.relpath(hyperdir+'/testsets/analogy/google.txt')])
if completed_proc.returncode != 0:
if completed_proc.stdout is not None:
print(completed_proc.stdout)
if completed_proc.stderr is not None:
print(completed_proc.stderr)
print("FAILURE! Aborting.")
exit()
print()
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# -*- coding: utf-8 -*-
"""rpg_queries.ipynb
Automatically generated by Colaboratory.
Original file is located at
https://colab.research.google.com/drive/1ufwd5h-epfNkHGiNJTkFTDQsbupk24Ld
"""
#How many total characters are there?
import sqlite3
conn = sqlite3.connect('rpg_db.sqlite3')
curs = conn.cursor()
#How many total characters are there?
query1 = "SELECT count(name) as character_count FROM charactercreator_character"
results1 = curs.execute(query1).fetchall()
print("Total number of characters=", results1)
#How many in each sublass?
#cleric subclass
query2= "SELECT count(character_ptr_id) as character_count FROM charactercreator_cleric"
results2 = curs.execute(query2).fetchall()
print("Total number of characters in cleric sublass=", results2)
#fighter sublass
query3 = "SELECT count(character_ptr_id) as character_count FROM charactercreator_fighter"
results3 = curs.execute(query3).fetchall()
print("Total number of characters in fighter sublass=", results3)
#mage sublass
query4 = "SELECT count(character_ptr_id) as character_count FROM charactercreator_mage"
results4 = curs.execute(query4).fetchall()
print("Total number of characters in mage sublass=", results4)
#thief sublass
query5 = "SELECT count(character_ptr_id) as character_count FROM charactercreator_thief"
results5 = curs.execute(query5).fetchall()
print("Total number of characters in thief sublass=", results5)
#necromancer is a sublass of mage, so we don't need to count it separately
#The sum of each individual class from the above is = 302, total number of characters
#extrating table with each character and its class
query6="""
SELECT
ch.character_id
,ch.name
--,cl.*
--,f.*
--,m.*
--,th.*
-- ,if(cl.character_ptr_id is not null, "cleric", "todo") as char_type
,CASE
WHEN cl.character_ptr_id is not null THEN "cleric"
WHEN f.character_ptr_id is not null THEN "fighter"
WHEN n.mage_ptr_id is not null THEN "mage-necro"
WHEN m.character_ptr_id is not null THEN "mage"
WHEN th.character_ptr_id is not null THEN "thief"
ELSE "todo"
END as char_type
from charactercreator_character as ch
left join charactercreator_cleric as cl on ch.character_id = cl.character_ptr_id
left join charactercreator_fighter as f on ch.character_id = f.character_ptr_id
left join charactercreator_mage as m on ch.character_id = m.character_ptr_id
left join charactercreator_thief as th on ch.character_id = th.character_ptr_id
-- left join charactercreator_necromancer as n on ch.character_id = n.character_ptr_id
left join charactercreator_necromancer as n on m.character_ptr_id = n.mage_ptr_id
"""
curs.execute(query6).fetchall()
#Number of characters in each class
query7= """
select
subquery1.char_type
,count(distinct subquery1.character_id) as char_count
from (
-- row per character (302 total)
select
ch.character_id
,ch.name
--,cl.*
--,f.*
--,m.*
--,th.*
-- ,if(cl.character_ptr_id is not null, "cleric", "todo") as char_type
,CASE
WHEN cl.character_ptr_id is not null THEN "cleric"
WHEN f.character_ptr_id is not null THEN "fighter"
WHEN n.mage_ptr_id is not null THEN "mage-necro"
WHEN m.character_ptr_id is not null THEN "mage"
WHEN th.character_ptr_id is not null THEN "thief"
ELSE "todo"
END as char_type
from charactercreator_character as ch
left join charactercreator_cleric as cl on ch.character_id = cl.character_ptr_id
left join charactercreator_fighter as f on ch.character_id = f.character_ptr_id
left join charactercreator_mage as m on ch.character_id = m.character_ptr_id
left join charactercreator_thief as th on ch.character_id = th.character_ptr_id
-- left join charactercreator_necromancer as n on ch.character_id = n.character_ptr_id
left join charactercreator_necromancer as n on m.character_ptr_id = n.mage_ptr_id
) subquery1
group by subquery1.char_type
"""
curs.execute(query7).fetchall()
#Another way to find number of characters in each class
query8= """
-- row per character (302 total)
select
CASE
WHEN cl.character_ptr_id is not null THEN "cleric"
WHEN f.character_ptr_id is not null THEN "fighter"
WHEN n.mage_ptr_id is not null THEN "mage-necro"
WHEN m.character_ptr_id is not null THEN "mage"
WHEN th.character_ptr_id is not null THEN "thief"
ELSE "todo"
END as char_type
,count(distinct ch.character_id) as char_count
from charactercreator_character as ch
left join charactercreator_cleric as cl on ch.character_id = cl.character_ptr_id
left join charactercreator_fighter as f on ch.character_id = f.character_ptr_id
left join charactercreator_mage as m on ch.character_id = m.character_ptr_id
left join charactercreator_thief as th on ch.character_id = th.character_ptr_id
-- left join charactercreator_necromancer as n on ch.character_id = n.character_ptr_id
left join charactercreator_necromancer as n on m.character_ptr_id = n.mage_ptr_id
group by char_type
"""
curs.execute(query8).fetchall()
#How many total items?
query9= """
select count(name) as item_count
from armory_item
"""
results6 = curs.execute(query9).fetchall()
print("Total number of items=", results6)
#How many items each character has?
query10="""
SELECT a.character_id, ch.name, count(a.item_id)
FROM charactercreator_character_inventory as a
left join charactercreator_character as ch on ch.character_id = a.character_id
GROUP BY a.character_id
LIMIT 20
"""
print("Character ID, character name, number of items")
curs.execute(query10).fetchall()
#How many weapons each character has?
#left join statement should come after FROM statement followed by WHERE, GROUP BY, etc.
query11= """
SELECT a.character_id, d.name, count(a.item_id)
FROM charactercreator_character_inventory as a, armory_item as b, armory_weapon as c
left join charactercreator_character as d on d.character_id = a.character_id
WHERE a.item_id = b.item_id AND b.item_id = c.item_ptr_id
GROUP BY a.character_id
LIMIT 20
"""
print("Character ID, Chacter name, number of weapons")
curs.execute(query11).fetchall()
#On average, how many items each Character has?
query12="""
SELECT COUNT(inventory.item_id) * 1.0/ COUNT(DISTINCT inventory.character_id)
FROM charactercreator_character_inventory AS inventory
"""
results6 = curs.execute(query12).fetchall()
print("Average number of items per character=", results6)
#On average how many weapons each character has?
query13="""
SELECT COUNT(a.item_id) *1.0 / COUNT(DISTINCT a.character_id)
FROM charactercreator_character_inventory AS a, armory_weapon AS b
WHERE a.item_id = b.item_ptr_id
"""
results7 = curs.execute(query13).fetchall()
print("Average number of weapons per character=", results7) | [
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] | 2.998213 | 2,239 |
# -*- coding: utf-8 -*-
#
# Author: Taylor Smith <[email protected]>
#
# R approx function
from __future__ import absolute_import
from sklearn.utils.validation import check_array, column_or_1d
import numpy as np
from ..utils.array import c
from ..utils import get_callable
from ..compat.numpy import DTYPE
# since the C import relies on the C code having been built with Cython,
# and since the platform might name the .so file something funky (like
# _arima.cpython-35m-darwin.so), import this absolutely and not relatively.
from pmdarima.arima._arima import C_Approx
__all__ = [
'approx'
]
# the ints get passed to C code
VALID_APPROX = {
'constant': 2,
'linear': 1
}
# get the valid tie funcs
VALID_TIES = {
'ordered': None, # never really used...
'mean': np.average
}
# identity function defined once to avoid multiple lambda calls
# littered throughout
_identity = (lambda t: t)
def _regularize(x, y, ties):
"""Regularize the values, make them ordered and remove duplicates.
If the ``ties`` parameter is explicitly set to 'ordered' then order
is already assumed. Otherwise, the removal process will happen.
Parameters
----------
x : array-like, shape=(n_samples,)
The x vector.
y : array-like, shape=(n_samples,)
The y vector.
ties : str
One of {'ordered', 'mean'}, handles the ties.
"""
x, y = [
column_or_1d(check_array(arr, ensure_2d=False,
force_all_finite=False,
dtype=DTYPE))
for arr in (x, y)
]
nx = x.shape[0]
if nx != y.shape[0]:
raise ValueError('array dim mismatch: %i != %i' % (nx, y.shape[0]))
# manipulate x if needed. if ties is 'ordered' we assume that x is
# already ordered and everything has been handled already...
if ties != 'ordered':
o = np.argsort(x)
# keep ordered with one another
x = x[o]
y = y[o]
# what if any are the same?
ux = np.unique(x)
if ux.shape[0] < nx:
# Do we want to warn for this?
# warnings.warn('collapsing to unique "x" values')
# vectorize this function to apply to each "cell" in the array
# replace the duplicates in the y array with the "tie" func
func = VALID_TIES.get(ties, _identity)
# maybe expensive to vectorize on the fly? Not sure; would need
# to do some benchmarking. However, we need to in order to keep y
# and x in scope...
y = np.vectorize(tie_apply)(func, ux)
# does ux need ordering? hmm..
x = ux
return x, y
def approx(x, y, xout, method='linear', rule=1, f=0, yleft=None,
yright=None, ties='mean'):
"""Linearly interpolate points.
Return a list of points which (linearly) interpolate given data points,
or a function performing the linear (or constant) interpolation.
Parameters
----------
x : array-like, shape=(n_samples,)
Numeric vector giving the coordinates of the points
to be interpolated.
y : array-like, shape=(n_samples,)
Numeric vector giving the coordinates of the points
to be interpolated.
xout : int, float or iterable
A scalar or iterable of numeric values specifying where
interpolation is to take place.
method : str, optional (default='linear')
Specifies the interpolation method to be used.
Choices are "linear" or "constant".
rule : int, optional (default=1)
An integer describing how interpolation is to take place
outside the interval ``[min(x), max(x)]``. If ``rule`` is 1 then
np.nans are returned for such points and if it is 2, the value at the
closest data extreme is used.
f : int, optional (default=0)
For ``method`` = "constant" a number between 0 and 1 inclusive,
indicating a compromise between left- and right-continuous step
functions. If y0 and y1 are the values to the left and right of the
point then the value is y0 if f == 0, y1 if f == 1, and y0*(1-f)+y1*f
for intermediate values. In this way the result is right-continuous
for f == 0 and left-continuous for f == 1, even for non-finite
``y`` values.
yleft : float, optional (default=None)
The value to be returned when input ``x`` values are less than
``min(x)``. The default is defined by the value of rule given below.
yright : float, optional (default=None)
The value to be returned when input ``x`` values are greater than
``max(x)``. The default is defined by the value of rule given below.
ties : str, optional (default='mean')
Handling of tied ``x`` values. Choices are "mean" or "ordered".
"""
if method not in VALID_APPROX:
raise ValueError('method must be one of %r' % VALID_APPROX)
# make sure xout is an array
xout = c(xout).astype(np.float64) # ensure double
# check method
method_key = method
# not a callable, actually, but serves the purpose..
method = get_callable(method_key, VALID_APPROX)
# copy/regularize vectors
x, y = _regularize(x, y, ties)
nx = x.shape[0]
# if len 1? (we've already handled where the size is 0, since we check that
# in the _regularize function when we call c1d)
if nx == 1:
if method_key == 'linear':
raise ValueError('need at least two points to '
'linearly interpolate')
# get yleft, yright
if yleft is None:
yleft = y[0] if rule != 1 else np.nan
if yright is None:
yright = y[-1] if rule != 1 else np.nan
# call the C subroutine
yout = C_Approx(x, y, xout, method, f, yleft, yright)
return xout, yout
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345,
83,
796,
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62,
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11,
2124,
448,
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331,
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3506,
8,
198,
220,
220,
220,
1441,
2124,
448,
11,
345,
83,
198
] | 2.54136 | 2,309 |
from pathlib import Path
from common.observer import Observable
if __name__ == '__main__':
m = Model()
test_path = Path.home().resolve()
m.collect_metrics(str(test_path), [str(Path('.').resolve())], 'test.json')
| [
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"""Schemas linked to the database models"""
import re
from marshmallow import post_dump
from marshmallow_sqlalchemy import ModelSchema
class BaseSchema(ModelSchema):
"""
Custom base schema class that serializes datetime strings without the
timezone offset.
"""
@post_dump
def strip_timezone_offset(self, data):
"""Strips timezone offset from ISO8601/RFC3339 strings"""
for key in data:
if data[key] and isinstance(data[key], str):
matches = re.match(
r'^\d{4}-\d\d-\d\dT\d\d:\d\d:\d\d(\.\d{6})?[+-]\d\d:\d\d$',
data[key]
)
if matches:
data[key] = data[key][:-6]
return data | [
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21,
60,
628,
220,
220,
220,
220,
220,
220,
220,
1441,
1366
] | 2.052342 | 363 |
"""
Write your own datasets under this directory.
""" | [
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] | 4.416667 | 12 |
from ..common.solver import BaseSolver, DEFAULT_BATCH_SIZE, DEFAULT_MAX_BATCHES
from . import libmpopt_qap as lib
from . primals import Primals
import numpy
DEFAULT_GREEDY_GENERATIONS = 10
INFINITY_COST = 1e99
| [
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] | 2.703704 | 81 |
from django import forms
from django.db.models import Q
from django.contrib.auth.models import User
from django.contrib.contenttypes.models import ContentType
import django_filters
from actstream.models import Action
from rest_framework import serializers, viewsets, permissions, mixins, status
from rest_framework.decorators import action
from rest_framework.response import Response
from kitsune.notifications.models import (
PushNotificationRegistration,
Notification,
RealtimeRegistration,
)
from kitsune.sumo.api_utils import OnlyCreatorEdits, DateTimeUTCField, GenericRelatedField
class OnlyOwner(permissions.BasePermission):
"""
Only allow objects to affected by their owner.
TODO: This should be tied to user and object permissions better, but
for now this is a bandaid.
"""
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37227,
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] | 3.568966 | 232 |
"""Asyncio backports for Python 3.6 compatibility."""
from asyncio import coroutines, ensure_future
from asyncio.events import AbstractEventLoop
import concurrent.futures
import logging
import threading
from typing import Any, Callable, Coroutine
_LOGGER = logging.getLogger(__name__)
def fire_coroutine_threadsafe(coro: Coroutine, loop: AbstractEventLoop) -> None:
"""Submit a coroutine object to a given event loop.
This method does not provide a way to retrieve the result and
is intended for fire-and-forget use. This reduces the
work involved to fire the function on the loop.
"""
ident = loop.__dict__.get("_thread_ident")
if ident is not None and ident == threading.get_ident():
raise RuntimeError("Cannot be called from within the event loop")
if not coroutines.iscoroutine(coro):
raise TypeError("A coroutine object is required: %s" % coro)
def callback() -> None:
"""Handle the firing of a coroutine."""
ensure_future(coro, loop=loop)
loop.call_soon_threadsafe(callback)
def run_callback_threadsafe(
loop: AbstractEventLoop, callback: Callable, *args: Any
) -> concurrent.futures.Future:
"""Submit a callback object to a given event loop.
Return a concurrent.futures.Future to access the result.
"""
ident = loop.__dict__.get("_thread_ident")
if ident is not None and ident == threading.get_ident():
raise RuntimeError("Cannot be called from within the event loop")
future: concurrent.futures.Future = concurrent.futures.Future()
def run_callback() -> None:
"""Run callback and store result."""
try:
future.set_result(callback(*args))
except Exception as exc: # pylint: disable=broad-except
if future.set_running_or_notify_cancel():
future.set_exception(exc)
else:
_LOGGER.warning("Exception on lost future: ", exc_info=True)
loop.call_soon_threadsafe(run_callback)
return future
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] | 2.863636 | 704 |
"""Tests"""
from hangman import check_letter, reveal_letter, print_result
def test_check_letter():
"""check_letter"""
assert check_letter("world", "a") == 0
def test_reveal_letter():
"""reveal_letter"""
assert reveal_letter("te", ['*', 'e'], "t") == ['t', 'e']
def test_print_result():
"""test print result"""
assert print_result(5, "word") == 0
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] | 2.744526 | 137 |
# coding: utf-8
from __future__ import print_function
import numpy as np
import pandas as pd
import os
import json
import re
from pep_detectability import PeptideDetectabilityTrainer
from pep_detectability import PeptideDetectabilityPredictor
working_dir = '.'
filenames_positive = [
f for f in os.listdir(working_dir)
if f.endswith(".detectability.csv") and \
not f.endswith("negative.detectability.csv")
]
data_positive = pd.concat([load_data(os.path.join(working_dir, f)) for f in filenames_positive])
filenames_negative = [
f for f in os.listdir(working_dir)
if f.endswith("negative.detectability.csv")
]
data_negative = pd.concat([load_data(os.path.join(working_dir, f)) for f in filenames_negative])
print('Positive {n}, negative {m}'.format(
n=len(data_positive), m=len(data_negative)
))
seed = 0
max_rounds = 10
positive_threshold = 0.5
fpr_threshold = 0.01
result_summary = {
'seed': seed,
'files': {
'positive': filenames_positive,
'negative': filenames_negative
}
}
save_data_json(result_summary, os.path.join(working_dir, 'training.json'))
results = []
for i in range(0, max_rounds + 1):
if i == 0:
model_path=None
indexes_negative = get_initial_negative_subset(
data_positive, data_negative, seed=seed
)
else:
predict_dir = '{working_dir}/training_{i}'.format(working_dir=working_dir, i=i - 1)
model_path = model_path = [
os.path.join(predict_dir, 'models', f)
for f in os.listdir(os.path.join(predict_dir, 'models'))
if re.match(r'^epoch_[0-9]+\.hdf5$', f) is not None
][-1]
indexes_negative, tpr, fpr, precision = get_hard_negative_subset(
data_positive, data_negative,
model_path=model_path,
positive_threshold=positive_threshold,
min_ratio=1
)
print('TPR: {tpr}, FPR: {fpr}, Precision: {precision}'.format(
tpr=tpr, fpr=fpr, precision=precision
))
if (len(results) > 0):
results[-1]['evaluate'] = {
'tpr': tpr,
'fpr': fpr,
'precision': precision
}
if (fpr <= fpr_threshold):
print('Early stopping')
break
if (i >= max_rounds):
break
print('Round {i}: train on {n} positive samples, {m} negative samples'.format(
i=i, n=len(data_positive), m=len(indexes_negative)
))
train_dir = '{working_dir}/training_{i}'.format(working_dir=working_dir, i=i)
os.makedirs(train_dir, exist_ok=True)
os.makedirs(os.path.join(train_dir, 'models'), exist_ok=True)
data1 = data_positive
data2 = data_negative.iloc[indexes_negative]
trainer = PeptideDetectabilityTrainer(
model_path=model_path,
save_path=os.path.join(train_dir, 'models', 'epoch_{epoch:03d}.hdf5'),
log_path=os.path.join(train_dir, 'training.log')
)
result = trainer.train(data1, data2, seed=seed)
trainer.save_model(os.path.join(train_dir, 'models', 'last_epoch.hdf5'))
result['split'] = {
'seed': seed,
'round': i,
'train': {
'positive': result['split']['train']['positive'],
'negative': indexes_negative \
[np.array(result['split']['train']['negative'])].tolist()
},
'validate': {
'positive': result['split']['validate']['positive'],
'negative': indexes_negative \
[np.array(result['split']['validate']['negative'])].tolist()
}
}
result['files'] = filenames_positive + filenames_negative
trainer.save_model(os.path.join(train_dir, 'models', 'last_epoch.hdf5'))
save_data_json(result, os.path.join(train_dir, 'training.json'))
results.append(result)
result_summary['rounds'] = results
save_data_json(result_summary, os.path.join(working_dir, 'training.json'))
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198
] | 2.130068 | 1,899 |
"""Various `lstm_ee.data.data_loader` tests"""
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] | 2.666667 | 18 |
# -*- coding: utf-8 -*-
from __future__ import unicode_literals
from django.db import models, migrations
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from leetcode_tester import Tester
from src.binary_tree import TreeNode, null
from typing import Optional, List
if __name__ == '__main__':
solution = Solution()
test = Tester(solution.maxDepth)
test.addTest(
TreeNode.from_list([3, 9, 20, null, null, 15, 7]), 3
)
test.addTest(
TreeNode.from_list([1, null, 2]), 2
)
test.doTest()
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] | 2.423077 | 156 |
from django.contrib.auth.mixins import LoginRequiredMixin
from django.views.generic import ListView
from reviewer.models import Reviewer
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] | 3.833333 | 36 |
"""CKAN module is a wrapper around API calls. All of these methods will return
raw json objects. The JSON that is returned can be used to construct CKANData
objects.
CKANData objects can be compared with one another. They will use the
CKANTransform methods to identify fields that should and should not be
used to compare two objects.
CKANTransform will also be used to transform on CKANData object to a new
Schema allowing like for like comparisons.
CKANTransform module will work directly with CKAN Data objects.
"""
# pylint: disable=logging-format-interpolation
import logging
import constants
import CKANTransform
import deepdiff
import pprint
LOGGER = logging.getLogger(__name__)
def validateTypeIsComparable(dataObj1, dataObj2):
"""A generic function that can be used to ensure two objects are comparable.
:param dataObj1: The first data object that is to be used in a comparison
:type ckanDataSet:
:raises IncompatibleTypesException: [description]
"""
dataType1 = type(dataObj1)
dataType2 = type(dataObj2)
if hasattr(dataObj1, 'dataType'):
dataType1 = dataObj1.dataType
if hasattr(dataObj2, 'dataType'):
dataType2 = dataObj2.dataType
if dataType2 != dataType1:
msg = 'You are attempting to compare two different types of objects ' + \
f'that are not comparable. dataObj1 is type: {dataType1} and ' + \
f'dataObj2 is type: with an object of type, {dataType2}'
raise IncompatibleTypesException(msg)
# ------------- Data Record defs -------------
class DataCell:
"""an object that can be used to wrap a data value and other meta data
about it from the perspective of a change
"""
def deleteIndexes(self, positions):
"""gets a list of the position that are to be trimmed from the struct
:param positions: a list of index positions for the self.struct list that
are to be removed.
:type positions: list of ints
"""
LOGGER.debug(f"remove positions: {positions}")
newStruct = []
for pos in range(0, len(self.struct)):
if pos not in positions:
newStruct.append(self.struct[pos])
else:
LOGGER.debug(f"removing: {pos} {self.struct[pos]}")
LOGGER.debug(f"old struct: {self.struct}")
LOGGER.debug(f"new struct: {newStruct}")
self.struct = newStruct
# transfer changes to the parent
def generateNewCell(self, key, transConf):
"""The current cell is a dict, generates a new cell for the position
associated with the input key.
:param key: a key of struct property
:type key: str
"""
newCell = DataCell(self.struct[key])
newCell.parent = self
newCell.parentKey = key
# copy the attributes from parent to child
newCell.include = self.include
newCell.ignoreList = self.ignoreList
newCell.ignoreFld = self.ignoreFld
newCell.parentType = self.parentType
# if the key is an embedded type, users, groups, etc...
if key in constants.VALID_TRANSFORM_TYPES:
newCell.ignoreList = transConf.getIgnoreList(key)
newCell.ignoreFld = transConf.getUniqueField(key)
newCell.parentType = key
if newCell.parentType is not None:
# if the key is equal to the name of the ignore field
if (newCell.ignoreFld) and key == newCell.ignoreFld:
# example key is 'name' and the ignore field is name
# now check to see if the value is in the ignore list
if newCell.struct in newCell.ignoreList:
# continue with example.. now the value for the key name
# is in the ignore list. Set the enclosing object... self
# to not be included.
self.include = False
return newCell
# -------------------- DATASET DELTA ------------------
class CKANDataSetDeltas:
"""Class used to represent differences between two objects of the same
type. Includes all the information necessary to proceed with the update.
:ivar adds: A list of dicts containing the user defined properties that need
to be populated to create an equivalent version of the src data
in dest.
:ivar deletes: A list of the names or ids on the dest side of objects that
should be deleted.
:ivar updates: Same structure as 'adds'. Only difference between these and
adds is these will get added to dest using an update method vs a create
method.
:ivar srcCKANDataset: CKANDataset object, maintain a reference to this
object so that can request CKAN records in the dataset with only
user generated fields included.
"""
def setAddDataset(self, addDataObj):
"""Adds a object to the list of objects that are identified as adds
Adds are objects that exist in the source but not the destination
:param addDataObj: data that is to be added
:type addDataObj: dict
:raises TypeError: raised if the input data is not type dict
"""
if not isinstance(addDataObj, dict):
msg = "addDataObj parameter needs to be type dict. You passed " + \
f"{type(addDataObj)}"
raise TypeError(msg)
self.adds.append(addDataObj)
def setAddDatasets(self, addList, replace=True):
"""adds a list of data to the adds property. The adds property
gets populated with data that should be added to the destination
ckan instance
:param addList: input list of data that should be added to the dest
instance
:type addList: struct
:param replace: if set to true, will replace any data that may already
exist in the adds property if set to false then will append to the
end of the struct, defaults to True
:type replace: bool, optional
"""
if replace:
LOGGER.info(f"populate add list with {len(addList)} items")
self.adds = addList
else:
LOGGER.info(f"adding {len(addList)} items to the add list")
self.adds.extend(addList)
def setDeleteDataset(self, deleteName):
"""Adds an object to the list of data that has been identified as a
Delete.
Deletes are records that exist in the destination but not the source.
:param deleteName: [description]
:type deleteName: [type]
:raises TypeError: [description]
"""
if not isinstance(deleteName, str):
msg = "deleteName parameter needs to be type str. You passed " + \
f"{type(deleteName)}"
raise TypeError(msg)
self.deletes.append(deleteName)
def setDeleteDatasets(self, deleteList, replace=True):
"""adds a list of data to the deletes property. The deletes property
gets populated with unique ids that should be removed from the destination
ckan instance
:param deleteList: input list of data that should be deleted from the dest
ckan instance
:type addList: struct
:param replace: if set to true, will replace any data that may already
exist in the deletes property, if set to false then will append to the
end of the struct, defaults to True
:type replace: bool, optional
"""
if replace:
LOGGER.info(f"populate delete list with {len(deleteList)} items")
self.deletes = deleteList
else:
LOGGER.info(f"adding {len(deleteList)} items to the delete list")
self.deletes.extend(deleteList)
def setUpdateDatasets(self, updateList):
"""Gets a list of data that should be used to update objects in the ckan
destination instance and adds the data to this object
:param updateList: list of data to be used to update the object
:type updateList: list
"""
LOGGER.info(f"adding {len(updateList)} records to update")
for updateData in updateList:
self.setUpdateDataSet(updateData)
def setUpdateDataSet(self, updateObj):
"""Adds a new dataset that is to be updated. When comparison of two
objects identifies that there is a difference, the object that passed to
this method is the src object with the data that should be copied to dest.
Updates are datasets that exist in source and destination however not all
the data is the same between them.
:param updateObj: the data that is to be updated
:type updateObj: dict
:raises TypeError: object must be type 'dict', raise if it is not.
:raises ValueError: object must have a 'name' property
"""
if not isinstance(updateObj, dict):
msg = "updateObj parameter needs to be type dict. You passed " + \
f"{type(updateObj)}"
raise TypeError(msg)
if 'name' not in updateObj:
msg = 'Update object MUST contain a property \'name\'. Object ' + \
f'provided: {updateObj}'
raise ValueError(msg)
LOGGER.debug(f"adding update for {updateObj['name']}")
self.updates[updateObj['name']] = updateObj
def filterNonUserGeneratedFields(self, ckanDataSet):
"""
Receives either a dict or list:
* dict: key is the unique id for the dataset
* list: a list of dicts describing a list of data
objects.
Iterates over all the data in the ckanDataSet struct, removing non
user generated fields and returns a json struct (dict) with only
fields that are user defined
:param ckanDataSet: a ckan data set
:type ckanDataSet: CKANDataSet or an object that subclasses it
"""
# get the unique id for this dataset type
uniqueIdentifier = self.srcCKANDataset.transConf.getUniqueField(
self.srcCKANDataset.dataType)
# if generating a dataset to be used to update a dataset, then check to
# see if there are machine generated fields that should be included in the
# update
LOGGER.debug(f"uniqueIdentifier: {uniqueIdentifier}")
if isinstance(ckanDataSet, dict):
filteredData = {}
uniqueIds = ckanDataSet.keys()
elif isinstance(ckanDataSet, list):
filteredData = []
# below is wrong as it returns all unique ids, we only want the
# unique ids provided in the struct ckanDataSet
#uniqueIds = self.srcCKANDataset.getUniqueIdentifiers()
uniqueIds = []
for record in ckanDataSet:
uniqueIds.append(record[uniqueIdentifier])
else:
msg = f'type received is {type(ckanDataSet)}, expecting list or dict'
raise IncompatibleTypesException(msg)
for uniqueId in uniqueIds:
#LOGGER.debug(f"uniqueId: {uniqueId}")
ckanRec = self.srcCKANDataset.getRecordByUniqueId(uniqueId)
compStruct = ckanRec.getComparableStruct()
if isinstance(ckanDataSet, dict):
filteredData[uniqueId] = compStruct
elif isinstance(ckanDataSet, list):
filteredData.append(compStruct)
return filteredData
def getUpdateData(self):
""" creates and returns a structure that can be used to update the object
in question.
:return: a dictionary where the key values are the unique identifiers
and the values are the actual struct that should be used to update
the destination ckan instance.
:rtype: dict
"""
# should return only fields that are user generated
updates = self.filterNonUserGeneratedFields(self.updates)
#LOGGER.debug(f'updates: {updates}')
updateFields = self.transConf.getFieldsToIncludeOnUpdate(self.destCKANDataset.dataType)
if updateFields:
# need to add these onto each record from the destination
# instances data
updates = self.addUpdateAutoGenFields(updates, updateFields)
return updates
def addUpdateAutoGenFields(self, dataDict, autoGenFieldList):
"""dataDict contains the data that is to be used for the update that
originates from the source ckan instance. autoGenFieldList is a list of
field names that should be added to the struct from the destination
ckan instance
:param dataDict: The update data struct which is a dictionary where the
keys are the unique identifier, in most cases the keys are the name
property. The values in this struct are the values from the source
ckan instance.
:type dataDict: dict
:param autoGenFieldList: a list of field names that should be added to
the struct from the destination ckan instance
:type autoGenFieldList: list
:return: The values in the dataDict with the destination instance fields
defined in autoGenFieldList appended to the dictionary
:rtype: dict
"""
for uniqueId in dataDict:
record = self.destCKANDataset.getRecordByUniqueId(uniqueId)
for field2Add in autoGenFieldList:
fieldValue = record.getFieldValue(field2Add)
dataDict[uniqueId][field2Add] = fieldValue
LOGGER.debug(f"adding: {field2Add}:{fieldValue} to {uniqueId}")
return dataDict
# -------------------- DATASETS --------------------
class CKANDataSet:
"""This class wraps a collection of datasets. Includes an iterator that
will return a CKANRecord object.
:raises IncompatibleTypesException: This method is raised when comparing two
incompatible types.
"""
def reset(self):
"""reset the iterator
"""
self.iterCnt = 0
def getUniqueIdentifiers(self):
"""Iterates through the records in the dataset extracting the values from
the unique identifier field as defined in the config file.
:return: list of values found in the datasets unique constrained field.
:rtype: list
"""
self.reset()
uniqueIds = []
for record in self:
uniqueIds.append(record.getUniqueIdentifier())
return uniqueIds
def getRecordByUniqueId(self, uniqueValueToRetrieve):
"""Gets the record that aligns with this unique id.
"""
retVal = None
if not self.uniqueidRecordLookup:
self.reset()
for record in self:
recordID = record.getUniqueIdentifier()
self.uniqueidRecordLookup[recordID] = record
if uniqueValueToRetrieve == recordID:
retVal = record
else:
if uniqueValueToRetrieve in self.uniqueidRecordLookup:
retVal = self.uniqueidRecordLookup[uniqueValueToRetrieve]
return retVal
def getDeleteList(self, destUniqueIdSet, srcUniqueIdSet):
"""gets a set of unique ids from the source and destination ckan instances,
compares the two lists and generates a list of ids that should be deleted
from the destination instance. Excludes any ids that are identified in
the ignore list defined in the transformation configuration file.
:param destUniqueIdSet: a set of unique ids found the destination ckan
instance
:type destUniqueIdSet: set
:param srcUniqueIdSet: a set of the unique ids in the source ckan instance
:type srcUniqueIdSet: set
"""
ignoreList = self.transConf.getIgnoreList(self.dataType)
deleteSet = destUniqueIdSet.difference(srcUniqueIdSet)
deleteList = []
for deleteUniqueName in deleteSet:
#Check to see if the user is in the ignore list, only add if it is not
if deleteUniqueName not in ignoreList:
deleteList.append(deleteUniqueName)
return deleteList
def getAddList(self, destUniqueIdSet, srcUniqueIdSet):
"""Gets a two sets of unique ids, one for the data on the source ckan
instance and another for the destination ckan instance. Using this
information returns a list of unique ids that should be added to the
destination instance
:param destUniqueIdSet: a set of unique ids from the destination ckan
instance.
:type destUniqueIdSet: set
:param srcUniqueIdSet: a set of unique ids from the source ckan instance
:type srcUniqueIdSet: set
:return: a list of unique ids that should be added to the destination
ckan instance. Will exclude any unique ids identified in the
transformation configuration ignore list.
:rtype: list
"""
# in source but not in dest, ie adds
addSet = srcUniqueIdSet.difference(destUniqueIdSet)
ignoreList = self.transConf.getIgnoreList(self.dataType)
addList = []
for addRecordUniqueName in addSet:
#LOGGER.debug(f"addRecord: {addRecordUniqueName}")
if addRecordUniqueName not in ignoreList:
addDataSet = self.getRecordByUniqueId(addRecordUniqueName)
addDataStruct = addDataSet.getComparableStruct()
addList.append(addDataStruct)
return addList
def getDelta(self, destDataSet):
"""Compares this dataset with the provided 'ckanDataSet' dataset and
returns a CKANDatasetDelta object that identifies
* additions
* deletions
* updates
Assumption is that __this__ object is the source dataset and the object
in the parameter destDataSet is the destination dataset, or the dataset
that is to be updated
:param destDataSet: the dataset that is going to be updated so it
matches the contents of the source dataset
:type ckanDataSet: CKANDataSet
"""
deltaObj = CKANDataSetDeltas(self, destDataSet)
dstUniqueIds = set(destDataSet.getUniqueIdentifiers())
srcUniqueids = set(self.getUniqueIdentifiers())
deleteList = self.getDeleteList(dstUniqueIds, srcUniqueids)
deltaObj.setDeleteDatasets(deleteList)
addList = self.getAddList(dstUniqueIds, srcUniqueids)
deltaObj.setAddDatasets(addList)
updateList = self.getUpdatesList(dstUniqueIds, srcUniqueids, destDataSet)
deltaObj.setUpdateDatasets(updateList)
return deltaObj
def __eq__(self, ckanDataSet):
""" Identifies if the input dataset is the same as this dataset
:param ckanDataSet: The input CKANDataset
:type ckanDataSet: either CKANDataSet, or a subclass of it
"""
LOGGER.debug("DATASET EQ")
retVal = True
# TODO: rework this, should be used to compare a collection
validateTypeIsComparable(self, ckanDataSet)
# get the unique identifiers and verify that input has all the
# unique identifiers as this object
inputUniqueIds = ckanDataSet.getUniqueIdentifiers()
thisUniqueIds = self.getUniqueIdentifiers()
LOGGER.debug(f"inputUniqueIds: {inputUniqueIds}")
LOGGER.debug(f"thisUniqueIds: {thisUniqueIds}")
if set(inputUniqueIds) == set(thisUniqueIds):
# has all the unique ids, now need to look at the differences
# in the data
LOGGER.debug(f"iterate ckanDataSet: {ckanDataSet}")
LOGGER.debug(f"ckanDataSet record count: {len(ckanDataSet)}")
for inputRecord in ckanDataSet:
LOGGER.debug(f"iterating: {inputRecord}")
recordUniqueId = inputRecord.getUniqueIdentifier()
compareRecord = self.getRecordByUniqueId(recordUniqueId)
LOGGER.debug(f"type 1 and 2... {type(inputRecord)} {type(compareRecord)}")
if inputRecord != compareRecord:
LOGGER.debug(f"---------{recordUniqueId} doesn't have equal")
retVal = False
break
else:
LOGGER.debug(f"unique ids don't align")
retVal = False
return retVal
class CKANUsersDataSet(CKANDataSet):
"""Used to represent a collection of CKAN user data.
:param CKANData: [description]
:type CKANData: [type]
"""
# ----------------- EXCEPTIONS
class UserDefinedFieldDefinitionError(Exception):
"""Raised when the transformation configuration encounters an unexpected
value or type
"""
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] | 2.546033 | 8,179 |
from django.core.management import BaseCommand
from devicedata.generic import _get_provider
from devices.models import Device
| [
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16232,
628
] | 4 | 32 |
#!/usr/bin/env python
#
# ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
#
# Jiao Lin
# California Institute of Technology
# (C) 2007 All Rights Reserved
#
# {LicenseText}
#
# ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
#
#factory method that wraps boost python binding
def linearlyinterpolateddos_bp(
e0, de, n, Z):
'''create boost python object of LinearlyInterpolatedDOS
e0: minimum phonon energy. float
de: phonon energy step. float
n: number of points.
Z: values of DOS at the energy points defined by (e0, de, n)
'''
import mccomponents.mccomponentsbp as b
Z1 = b.vector_double( n )
for i in range(n): Z1[i] = Z[i]
return b.LinearlyInterpolatedDOS_dbl( e0, de, n, Z1 )
#python class to represent LinearlyInterpolatedDOS
from AbstractDOS import AbstractDOS as base
#register new type
# 2. the handler of engine renderer
# 3. the handler to call python bindings
import mccomponents.homogeneous_scatterer as hs
# 4. register the new class and handlers
hs.register (
LinearlyInterpolatedDOS, onLinearlyInterpolatedDOS,
{'BoostPythonBinding':linearlyinterpolateddos_bp_handler} )
# version
__id__ = "$Id$"
# End of file
| [
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220,
198
] | 2.733198 | 491 |
#!/usr/bin/env python
#-*- coding=utf-8 -*-
#
# Copyright 2012 Jike Inc. All Rights Reserved.
# Author: [email protected]
from StringIO import StringIO
file = '/etc/passwd'
lines = open(file, 'r').readlines()
text = open(file, 'r').read()
f = StringIO()
for line in lines[:-2]:
f.writelines(line)
f.writelines(lines[-2:])
f.seek(len(lines[0]))
f.write(lines[1])
f.seek(0)
print 'First line = ', f.readline()
print 'Position = ', f.tell()
line = f.readline()
print 'Second line = ', line
f.seek(-len(line), 1)
line2 = f.read(len(line))
print line2
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7,
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7,
1370,
4008,
198,
4798,
1627,
17,
198
] | 2.495455 | 220 |
#
# Stock Ticker server
# Binds PUB socket to tcp://*:5556
# Publishes random stock updates
#
import zmq
import time
import random
context = zmq.Context()
socket = context.socket(zmq.PUB)
socket.bind("tcp://*:5556")
scrips = ['AAPL', 'GOOG', 'MSFT', 'AMZN']
while True:
scrip = random.choice(scrips)
price = random.randrange(20,700)
msg = "%s: %d" % (scrip, price)
print msg
socket.send(msg)
time.sleep(0.5) | [
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"""
WAMP messages definitions and serializers.
Compatible with WAMP Document Revision: RC3, 2014/08/25, available at:
https://github.com/tavendo/WAMP/blob/master/spec/basic.md
"""
import json
import msgpack
import uuid
from copy import deepcopy
from enum import IntEnum, Enum
from io import BytesIO
from base64 import b64encode, standard_b64decode
from wampnado.identifier import create_global_id
from wampnado.features import server_features, Options
PUBLISHER_NODE_ID = uuid.uuid4()
def decode_b64(s):
"""
Finds all the binary objects in the struct, and recursively converts them to base64 prepended by \0, per the WAMP standard.
"""
if isinstance(s, dict):
ret = {}
for k,v in s.items():
ret[k] = decode_b64(v)
return ret
elif isinstance(s, list) or isinstance(s, tuple):
ret = []
for v in s:
ret.append(decode_b64(v))
return ret
elif isinstance(s, str) and s.beginswith('\0'):
return standard_b64decode(s[1:])
else:
return s
def encode_bin_as_b64(s):
"""
Finds all the binary objects in the struct, and recursively converts them to base64 prepended by \0, per the WAMP standard.
"""
if isinstance(s, dict):
ret = {}
for k,v in s.items():
ret[k] = encode_bin_as_b64(v)
return ret
elif isinstance(s, list) or isinstance(s, tuple):
ret = []
for v in s:
ret.append(encode_bin_as_b64(v))
return ret
elif isinstance(s, bytes):
return '\0{}'.format(b64encode(s).decode('ascii'))
elif isinstance(s, Enum):
return encode_bin_as_b64(s.value)
else:
return s
class Code(IntEnum):
"""
Enum which represents currently supported WAMP messages.
"""
HELLO = 1
WELCOME = 2
ABORT = 3
# CHALLENGE = 4
# AUTHENTICATE = 5
GOODBYE = 6
# HEARTBEAT = 7
ERROR = 8
PUBLISH = 16
PUBLISHED = 17
SUBSCRIBE = 32
SUBSCRIBED = 33
UNSUBSCRIBE = 34
UNSUBSCRIBED = 35
EVENT = 36
CALL = 48
# CANCEL = 49
RESULT = 50
REGISTER = 64
REGISTERED = 65
# UNREGISTER = 66
# UNREGISTERED = 67
INVOCATION = 68
INTERRUPT = 69
YIELD = 70
class BroadcastMessage(object):
"""
This is a message that a procedure may want delivered.
This class is composed of an EventMessage and a uri name
"""
@property
@property
@classmethod
def from_text(cls, text):
"""
Make a BroadcastMessage from text in a json struct
"""
raw = json.loads(text)
event_msg = EventMessage.from_text(raw["event_message"])
msg = cls(
uri_name=raw["uri_name"],
event_message=event_msg,
publisher_connection_id=raw["publisher_connection_id"]
)
msg.publisher_node_id = raw["publisher_node_id"]
return msg
@classmethod
def from_bin(cls, bin):
"""
Make a BroadcastMessage from a binary blob
"""
raw = msgpack.unpackb(bin, raw=False)
event_msg = EventMessage.from_text(raw["event_message"])
msg = cls(
uri_name=raw["uri_name"],
event_message=event_msg,
publisher_connection_id=raw["publisher_connection_id"]
)
msg.publisher_node_id = raw["publisher_node_id"]
return msg
class Message(object):
"""
Represent any WAMP message.
"""
details = {}
@property
def id(self):
"""
For all kinds of messages (except ERROR) that have [Request|id], it is
in the second position of the array.
"""
if (len(self.value) > 1) and isinstance(self.value[1], int):
return self.value[1]
return -1
@property
def json(self):
"""
Create a JSON representation of this message.
"""
message_value = deepcopy(self.value)
return json.dumps(encode_bin_as_b64(message_value))
@property
def msgpack(self):
"""
Create a MSGPack representation for this message.
"""
message_value = deepcopy(self.value)
for index, item in enumerate(message_value):
if isinstance(item, Code):
message_value[index] = item.value
return msgpack.packb(message_value, use_bin_type=True)
def error(self, text, info=None):
"""
Add error description and aditional information.
This is useful for ABORT and ERROR messages.
"""
self.details["message"] = text
if info:
self.details["details"] = info
@classmethod
def from_text(cls, text):
"""
Decode text to JSON and return a Message object accordingly.
"""
raw = decode_b64(json.loads(text))
raw[0] = Code(raw[0]) # make it an object of type Code
return cls(*raw)
@classmethod
def from_bin(cls, bin):
"""
Decode binary blob to a message and return a Message object accordingly.
"""
print(bin)
raw = msgpack.unpackb(bin, raw=False)
raw[0] = Code(raw[0]) # make it an object of type Code
return cls(*raw)
def _update_args_and_kargs(self):
"""
Append args and kwargs to message value, according to their existance
or not.
"""
if self.kwargs:
self.value.append(self.args)
self.value.append(self.kwargs)
else:
if self.args:
self.value.append(self.args)
class HelloMessage(Message):
"""
Sent by a Client to initiate opening of a WAMP session:
[HELLO, Realm|uri, Details|dict]
https://github.com/tavendo/WAMP/blob/master/spec/basic.md#hello
"""
class AbortMessage(Message):
"""
Both the Router and the Client may abort the opening of a WAMP session
[ABORT, Details|dict, Reason|uri]
https://github.com/tavendo/WAMP/blob/master/spec/basic.md#abort
"""
class WelcomeMessage(Message):
"""
Sent from the server side to open a WAMP session.
The WELCOME is a reply message to the Client's HELLO.
[WELCOME, Session|id, Details|dict]
https://github.com/tavendo/WAMP/blob/master/spec/basic.md#welcome
"""
class GoodbyeMessage(Message):
"""
Both the Server and the Client may abort the opening of a WAMP session
[ABORT, Details|dict, Reason|uri]
"""
class ResultMessage(Message):
"""
Result of a call as returned by Dealer to Caller.
[RESULT, CALL.Request|id, Details|dict]
[RESULT, CALL.Request|id, Details|dict, YIELD.Arguments|list]
[RESULT, CALL.Request|id, Details|dict, YIELD.Arguments|list, YIELD.ArgumentsKw|dict]
"""
class CallMessage(Message):
"""
Call as originally issued by the Caller to the Dealer.
[CALL, Request|id, Options|dict, Procedure|uri]
[CALL, Request|id, Options|dict, Procedure|uri, Arguments|list]
[CALL, Request|id, Options|dict, Procedure|uri, Arguments|list, ArgumentsKw|dict]
"""
class InterruptMessage(Message):
"""
Stop a progressive result before it's finished.
[INTERRUPT, INVOCATION.Request|id, Options|dict]
"""
class InvocationMessage(Message):
"""
Used by the dealer to request an RPC from a client. The client should respond with a YIELD message if successful.
[INVOCATION, Request|id, REGISTERED.Registration|id, Details|dict]
[INVOCATION, Request|id, REGISTERED.Registration|id, Details|dict, CALL.Arguments|list]
[INVOCATION, Request|id, REGISTERED.Registration|id, Details|dict, CALL.Arguments|list, CALL.ArgumentsKw|dict]
"""
class YieldMessage(Message):
"""
Used by the dealer to deliver the result of an RPC to the requesting client. The client should respond with a YIELD message if successful.
[YIELD, INVOCATION.Request|id, Options|dict]
[YIELD, INVOCATION.Request|id, Options|dict, Arguments|list]
[YIELD, INVOCATION.Request|id, Options|dict, Arguments|list, ArgumentsKw|dict]
"""
class ErrorMessage(Message):
"""
Error reply sent by a Peer as an error response to different kinds of
requests.
[ERROR, REQUEST.Type|int, REQUEST.Request|id, Details|dict, Error|uri]
[ERROR, REQUEST.Type|int, REQUEST.Request|id, Details|dict, Error|uri,
Arguments|list]
[ERROR, REQUEST.Type|int, REQUEST.Request|id, Details|dict, Error|uri,
Arguments|list, ArgumentsKw|dict]
"""
class SubscribeMessage(Message):
"""
A Subscriber communicates its interest in a uri to the Server by sending
a SUBSCRIBE message:
[SUBSCRIBE, Request|id, Options|dict, uri|uri]
"""
class SubscribedMessage(Message):
"""
If the Broker is able to fulfill and allow the subscription, it answers by
sending a SUBSCRIBED message to the Subscriber:
[SUBSCRIBED, SUBSCRIBE.Request|id, Subscription|id]
"""
class RPCRegisterMessage(Message):
"""
A Registerer communicates its interest in a uri to the Server by sending
a REGISTER message:
[REGISTER, Request|id, Options|dict, uri|uri]
"""
class RPCRegisteredMessage(Message):
"""
If the Broker is able to fulfill and allow the registration, it answers by
sending a REGISTERED message to the Registerer:
[REGISTERED, REGISTER.Request|id, Registration|id]
"""
class PublishMessage(Message):
"""
Sent by a Publisher to a Broker to publish an event.
[PUBLISH, Request|id, Options|dict, uri|uri]
[PUBLISH, Request|id, Options|dict, uri|uri, Arguments|list]
[PUBLISH, Request|id, Options|dict, uri|uri, Arguments|list, ArgumentsKw|dict]
"""
class PublishedMessage(Message):
"""
Acknowledge sent by a Broker to a Publisher for acknowledged publications.
[PUBLISHED, PUBLISH.Request|id, Publication|id]
"""
class EventMessage(Message):
"""
Event dispatched by Broker to Subscribers for subscription the event was matching.
[EVENT, SUBSCRIBED.Subscription|id, PUBLISHED.Publication|id, Details|dict]
[EVENT, SUBSCRIBED.Subscription|id, PUBLISHED.Publication|id, Details|dict, PUBLISH.Arguments|list]
[EVENT, SUBSCRIBED.Subscription|id, PUBLISHED.Publication|id, Details|dict, PUBLISH.Arguments|list, PUBLISH.ArgumentsKw|dict]
When transmitting an EventMessage between redis pubsubs the
subscription_id will be omitted (it can only be resolved in the
subscriber.)
"""
@property
@subscription_id.setter
class UnsubscribeMessage(Message):
"""
Unsubscribe request sent by a Subscriber to a Broker to unsubscribe a subscription.
[UNSUBSCRIBE, Request|id, SUBSCRIBED.Subscription|id]
"""
class UnsubscribedMessage(Message):
"""
Acknowledge sent by a Broker to a Subscriber to acknowledge unsubscription.
[UNSUBSCRIBED, UNSUBSCRIBE.Request|id]
"""
CODE_TO_CLASS = {
Code.HELLO: HelloMessage,
Code.WELCOME: WelcomeMessage,
Code.ABORT: AbortMessage,
# CHALLENGE = 4
# AUTHENTICATE = 5
Code.GOODBYE: GoodbyeMessage,
# HEARTBEAT = 7
Code.ERROR: ErrorMessage,
Code.PUBLISH: PublishMessage,
Code.PUBLISHED: PublishedMessage,
Code.SUBSCRIBE: SubscribeMessage,
Code.SUBSCRIBED: SubscribedMessage,
Code.UNSUBSCRIBE: UnsubscribeMessage,
Code.UNSUBSCRIBED: UnsubscribedMessage,
Code.EVENT: EventMessage,
Code.CALL: CallMessage,
# CANCEL = 49
Code.RESULT: ResultMessage,
Code.REGISTER: RPCRegisterMessage, # 64
Code.REGISTERED: RPCRegisteredMessage, # 65
# UNREGISTER = 66
# UNREGISTERED = 67
Code.INVOCATION: InvocationMessage, # 68
Code.INTERRUPT: InterruptMessage,
# INTERRUPT = 69
Code.YIELD: YieldMessage, # 70
}
ERROR_PRONE_CODES = [Code.CALL, Code.SUBSCRIBE, Code.UNSUBSCRIBE, Code.PUBLISH]
def build_error_message(in_message, uri, description):
"""
Return ErrorMessage instance (*) provided:
- incoming message which generated error
- error uri
- error description
(*) If incoming message is not prone to ERROR message reponse, return None.
"""
msg = Message.from_text(in_message)
if msg.code in ERROR_PRONE_CODES:
MsgClass = CODE_TO_CLASS[msg.code]
msg = MsgClass.from_text(in_message)
answer = ErrorMessage(
request_code=msg.code,
request_id=msg.request_id,
uri=uri
)
answer.error(description)
return answer
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11,
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220,
220,
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220,
220,
220,
220,
220,
220,
220,
2956,
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28,
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198,
220,
220,
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8,
198,
220,
220,
220,
220,
220,
220,
220,
1441,
3280,
198
] | 2.444271 | 5,132 |
import urllib
from oauth2 import OAuth2Request
import re
from json_import import simplejson
re_path_template = re.compile('{\w+}')
| [
11748,
2956,
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] | 2.956522 | 46 |
#!/usr/bin/env python
from pathlib import Path
import unicodedata
output = []
filename = Path(__file__).parent.resolve() / "data/books.tsv"
with open(filename) as handle:
lines = handle.readlines()
# lines will contain a row for each line in the file
# Loop through lines and do data scrubbing, put each result in output
for line in lines:
fields = line.split('\t')
# Start with known blank values
num = fields[0]
last_name = ''
first_name = ''
title = ''
date = ''
subjects = ''
if len(fields) > 1:
# Has a "name" field
parts = fields[1].split(',')
first_name = ''
last_name = parts[0]
if len(parts) > 1:
first_name = parts[1]
if "(" in first_name:
first_name, _ = first_name.split('(')
if len(fields) > 2:
title = fields[2]
nfkd_form = unicodedata.normalize('NFKD', title)
title = nfkd_form.encode('ASCII', 'ignore')
title = title.decode('utf-8')
out_line = f'{num}\t{last_name}\t{first_name}\t{title}'
output.append(out_line)
for line in output:
print(line)
| [
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62,
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8,
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1640,
1627,
287,
5072,
25,
198,
220,
220,
220,
3601,
7,
1370,
8,
198
] | 2.307071 | 495 |
#!/usr/bin/env python3
# Copyright 2020, Verizon Media
# Licensed under the terms of the MIT license. See LICENSE file in project root for terms.
import binascii
import serial
import subprocess
import sys
in_serport = sys.argv[1]
in_fn = sys.argv[2]
with open(in_fn, 'rb') as f:
payload = f.read()
ser = serial.Serial(in_serport, 115200, timeout=1)
# WTF?!
for b in payload:
ser.write(bytes([b]))
ser.flush()
| [
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65,
60,
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] | 2.707792 | 154 |
from app import app, db
from app.models import User, Channel
@app.shell_context_processor | [
6738,
598,
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62,
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] | 3.6 | 25 |
from random import randint
from skills_ml.algorithms.nlp import clean_html, clean_str, lowercase_strip_punc, word_tokenize, sentence_tokenize, section_extract, strip_bullets_from_line
from gensim.models.doc2vec import TaggedDocument
from skills_utils.common import safe_get
class CorpusCreator(object):
"""
A base class for objects that convert common schema
job listings into a corpus in documnet level suitable for use by
machine learning algorithms or specific tasks.
Example:
```python
from skills_ml.job_postings.common_schema import JobPostingCollectionSample
from skills_ml.job_postings.corpora.basic import CorpusCreator
job_postings_generator = JobPostingCollectionSample()
# Default will include all the cleaned job postings
corpus = CorpusCreator(job_postings_generator)
# For getting a the raw job postings without any cleaning
corpus = CorpusCreator(job_postings_generator, raw=True)
```
Attributes:
job_posting_generator (generator): an iterable that generates JSON strings.
Each string is expected to represent a job listing
conforming to the common schema
See sample_job_listing.json for an example of this schema
document_schema_fields (list): an list of schema fields to be included
raw (bool): a flag whether to return the raw documents or transformed documents
Yield:
(dict): a dictinary only with selected fields as keys and corresponding raw/cleaned value
"""
@property
class SimpleCorpusCreator(CorpusCreator):
"""
An object that transforms job listing documents by picking
important schema fields and returns them as one large lowercased string
"""
class Doc2VecGensimCorpusCreator(CorpusCreator):
"""Corpus for training Gensim Doc2Vec
An object that transforms job listing documents by picking
important schema fields and yields them as one large cleaned array of words
Example:
```python
from skills_ml.job_postings.common_schema import JobPostingCollectionSample
from skills_ml.job_postings.corpora.basic import Doc2VecGensimCorpusCreator
job_postings_generator = JobPostingCollectionSample()
corpus = Doc2VecGensimCorpusCreator(job_postings_generator)
Attributes:
job_posting_generator (generator): a job posting generator
document_schema_fields (list): an list of schema fields to be included
"""
class Word2VecGensimCorpusCreator(CorpusCreator):
"""
An object that transforms job listing documents by picking
important schema fields and yields them as one large cleaned array of words
"""
class JobCategoryCorpusCreator(CorpusCreator):
"""
An object that extract the label of each job listing document which could be onet soc code or
occupationalCategory and yields them as a lowercased string
"""
document_schema_fields = [
'occupationalCategory']
class SectionExtractWord2VecCorpusCreator(Word2VecGensimCorpusCreator):
"""Only return the contents of the configured section headers.
Heavily utilizes skills_ml.algorithms.nlp.section_extract.
For more detail on how to define 'sections', refer to its docstring.
"""
class RawCorpusCreator(CorpusCreator):
"""
An object that yields the joined raw string of job posting
"""
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] | 3.007806 | 1,153 |
# encoding: utf-8
from __future__ import unicode_literals
from datetime import datetime, timedelta
from mongoengine import (Document,
ListField,
StringField,
BooleanField,
DateTimeField,
EmbeddedDocument,
LazyReferenceField,
CachedReferenceField,
EmbeddedDocumentListField,
)
from gym_bot_app import DAYS_NAME
from gym_bot_app.query_sets import ExtendedQuerySet
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1267,
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] | 1.808511 | 329 |
from tkinter import Button, messagebox
from abc import ABCMeta, abstractmethod
from src.tictactoe.game.Board import Board
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] | 3.542857 | 35 |
# List of Builtins referred from here: https://docs.python.org/3/library/functions.html
# xa = oct(10)
import os
import glob
# print(xa, (type(xa)), sep="\n")
xa = ["xa", "pranali", "srushti", "shailesh", "nimesh"]
xa = [idx.upper() for idx in xa]
# ya = xa.copy()
# za = []
# for idx in xa:
# za.append(idx.upper())
print(xa)
# print(za)
# 1. Write brackets
# 2. Write for loop as is BUT w/o :
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] | 2.308571 | 175 |
import discord
from discord.commands.commands import Option, OptionChoice
from discord.commands.context import ApplicationContext
from discord.ext import commands, pages
from discord.ext.commands import BucketType, cooldown
import asyncio
import random
import schedule
from Utilities import AssociationObject, Checks, Finances, ItemObject, PlayerObject, Vars
class Offices(commands.Cog):
"""Offices Text"""
# EVENTS
@commands.Cog.listener()
# COMMANDS
@commands.slash_command(guild_ids=[762118688567984151])
async def offices(self, ctx):
"""View the map, tax rate, and this week's elected officeholders."""
async with self.bot.db.acquire() as conn:
comptroller_rec = await PlayerObject.get_comptroller(conn)
mayor_rec = await PlayerObject.get_mayor(conn)
comptroller = await self.bot.fetch_user(
comptroller_rec['officeholder'])
mayor = await self.bot.fetch_user(mayor_rec['officeholder'])
tax_info = await Finances.get_tax_info(conn)
embed = discord.Embed(
title=f"This Week's Officeholders!",
color=Vars.ABLUE)
embed.add_field(name="Mayor",
value=f"{mayor.mention}: **{mayor_rec['user_name']}**")
embed.add_field(name="Comptroller",
value=f"{comptroller.mention}: **{comptroller_rec['user_name']}**")
embed.add_field(
name=f"Current Tax Rate: `{tax_info['tax_rate']}`%",
value=(
f"The mayor has collected `{tax_info['Collected']}` gold "
f"so far this term."),
inline=False)
embed.set_image(url="https://i.imgur.com/jpLztYK.jpg")
await ctx.respond(embed=embed)
@commands.slash_command(guild_ids=[762118688567984151])
@commands.check(Checks.is_mayor)
@cooldown(1, 43200, BucketType.user)
async def tax(self, ctx, tax_rate : Option(float,
description="The new tax rate as a percentage (0-9.99)",
min_value=0,
max_value=9.99)):
"""Set the tax rate over Aramythia, earning you a small percentage."""
tax_rate = round(tax_rate, 2)
async with self.bot.db.acquire() as conn:
await Finances.set_tax_rate(conn, tax_rate, ctx.author.id)
await ctx.respond("You have changed the tax rate.")
await self.bot.announcement_channel.send(
f"Mayor {ctx.author.mention} has set the tax rate to `{tax_rate}%`."
)
@commands.slash_command(guild_ids=[762118688567984151])
async def territories(self, ctx):
"""See which brotherhoods control the outlying areas of the map."""
async with self.bot.db.acquire() as conn:
# Tuple with area and the accompanying owner Association Object
te_list = [
(area, await AssociationObject.get_territory_controller(
conn, area))
for area in Vars.TERRITORIES]
embed = discord.Embed(
title="Territories Controlled by a Brotherhood",
description=(
"Brotherhoods in control of a territory get a 50% bonus "
"to rewards from `/work` in that territory."),
color=Vars.ABLUE)
embed.set_image(url="https://i.imgur.com/jpLztYK.jpg")
for assc in te_list:
text = assc[1].name
if not assc[1].is_empty:
text += f" (ID: `{assc[1].id}`)"
embed.add_field(name=assc[0], value=text)
await ctx.respond(embed=embed)
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] | 2.108732 | 1,775 |
__version__ = '0.7.7'
__author__ = 'Jimmy Liu'
"""
for trading data
"""
from tushare_trader.stock.trading import (get_hist_data, get_tick_data,
get_today_all, get_realtime_quotes,
get_h_data, get_today_ticks,
get_index, get_hists,
get_k_data,
get_sina_dd)
"""
for trading data
"""
from tushare_trader.stock.fundamental import (get_stock_basics, get_report_data,
get_profit_data,
get_operation_data, get_growth_data,
get_debtpaying_data, get_cashflow_data,
get_balance_sheet, get_profit_statement, get_cash_flow)
"""
for macro data
"""
from tushare_trader.stock.macro import (get_gdp_year, get_gdp_quarter,
get_gdp_for, get_gdp_pull,
get_gdp_contrib, get_cpi,
get_ppi, get_deposit_rate,
get_loan_rate, get_rrr,
get_money_supply, get_money_supply_bal,
get_gold_and_foreign_reserves)
"""
for classifying data
"""
from tushare_trader.stock.classifying import (get_industry_classified, get_concept_classified,
get_area_classified, get_gem_classified,
get_sme_classified, get_st_classified,
get_hs300s, get_sz50s, get_zz500s,
get_terminated, get_suspended)
"""
for macro data
"""
from tushare_trader.stock.newsevent import (get_latest_news, latest_content,
get_notices, notice_content,
guba_sina)
"""
for reference
"""
from tushare_trader.stock.reference import (profit_data, forecast_data,
xsg_data, fund_holdings,
new_stocks, sh_margins,
sh_margin_details,
sz_margins, sz_margin_details,
top10_holders)
"""
for shibor
"""
from tushare_trader.stock.shibor import (shibor_data, shibor_quote_data,
shibor_ma_data, lpr_data,
lpr_ma_data)
"""
for LHB
"""
from tushare_trader.stock.billboard import (top_list, cap_tops, broker_tops,
inst_tops, inst_detail)
"""
for utils
"""
from tushare_trader.util.dateu import (trade_cal, is_holiday)
"""
for DataYes Token
"""
from tushare_trader.util.upass import (set_token, get_token, get_broker,
set_broker, remove_broker)
from tushare_trader.datayes.api import *
from tushare_trader.internet.boxoffice import (realtime_boxoffice, day_boxoffice,
day_cinema, month_boxoffice)
"""
for fund data
"""
from tushare_trader.fund.nav import (get_nav_open, get_nav_close, get_nav_grading,
get_nav_history, get_fund_info)
"""
for trader API
"""
from tushare_trader.trader.trader import TraderAPI
"""
for futures API
"""
from tushare_trader.futures.intlfutures import (get_intlfuture)
from tushare_trader.stock.globals import (global_realtime)
from tushare_trader.util.mailmerge import (MailMerge)
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8,
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] | 1.692589 | 2,186 |
from django.contrib import admin
from django_mptt_admin.admin import DjangoMpttAdmin
from menus.models import SystemMenu
admin.site.register(SystemMenu, SystemMenuAdmin)
| [
6738,
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##
import requests
tmp2='http://pics5.baidu.com/feed/38dbb6fd5266d0164f8e49cdd24aa40234fa3522.jpeg?token=c2cbcc6f929b40eb8881ceb4746c0e8c&s=1994CB1452725B94340248850300F0AB'
print(tmp2)
r = requests.get(tmp2)
with open('tmp.jpg', 'wb') as f:
f.write(r.content)
##
print("1111111111")
print("1111111111")
print("1111111111")
print("1111111111")
print("1111111111")
print("1111111111")
print("1111111111")
print("1111111111")
print("1111111111")
print("1111111111")
print("1111111111")
print("1111111111")
print("1111111111")
print("1111111111")
print("1111111111")
print("1111111111")
##
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# -*- coding: utf-8 -*-
"""
===============================================================================
Copyright (c) 2021 Kouadio K. Laurent
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.
===============================================================================
.. synopsis:: 'watex.utils.wmathandtricks'
Module for computing
Created on Mon Jun 21 14:43:25 2021
.. _electrical-resistivity-profile::`erp`
.. _vertical-electrical-sounding::`ves`
.. _station-position::`pk`
.._anomaly-boundaries:`anBounds`
@author: @Daniel03
"""
import os
import warnings
import numpy as np
import pandas as pd
from scipy.signal import argrelextrema
from scipy.interpolate import interp1d as sp1d
from ..utils._watexlog import watexlog
from ..utils.decorator import deprecated
import watex.utils.exceptions as Wex
_logger =watexlog.get_watex_logger(__name__)
def compute_lower_anomaly(erp_array, station_position=None,
step=None, **kws):
"""
Function to get the minimum value on the ERP array.
If `pk` is provided wil give the index of pk
:param erp_array: array of apparent resistivity profile
:type erp_array: array_like
:param station position: array of station position (survey) , if not given
and `step` is known , set the step value and
`station_position` will compute automatically
:type station_position: array_like
:param step: The distance between measurement im meter. If given will
recompute the `station_position`
:returns: * `bestSelectedDict`: dict containing best anomalies
with the anomaly resistivities range.
* `anpks`: Main positions of best select anomaly
* `collectanlyBounds`: list of arrays of select anomaly values
* `min_pks`: list of tuples (pk,
minVal of best anomalies points.)
:rtype: tuple
:Example:
>>> from watex.utils.wmathandtricks import compute_lower_anolamy
>>> import pandas as pd
>>> path_to_= 'data/l10_gbalo.xlsx'
>>> dataRes=pd.read_excel(erp_data).to_numpy()[:,-1]
>>> anomaly, *_ = compute_lower_anomaly(erp_array=data, step =10)
>>> anomaly
"""
display_infos= kws.pop('diplay_infos', False)
# got minumum of erp data
collectanlyBounds=[]
if step is not None:
station_position = np.arange(0, step * len(erp_array), step)
min_pks= get_minVal(erp_array) # three min anomaly values
# compute new_pjk
# find differents anomlies boundaries
for ii, (rho, index) in enumerate(min_pks) :
_, _, anlyBounds= drawn_anomaly_boundaries(erp_data = erp_array,
appRes = rho, index=index)
collectanlyBounds.append(anlyBounds)
if station_position is None :
pks =np.array(['?' for ii in range(len(erp_array))])
else : pks =station_position
if pks.dtype in ['int', 'float']:
anpks =np.array([pks[skanIndex ] for
(_, skanIndex) in min_pks ])
else : anpks ='?'
bestSelectedDICT={}
for ii, (pk, anb) in enumerate(zip(anpks, collectanlyBounds)):
bestSelectedDICT['{0}_pk{1}'.format(ii+1, pk)] = anb
if display_infos:
print('{0:+^100}'.format(
' *Best Conductive anomaly points (BCPts)* '))
fmtAnText(anFeatures=bestSelectedDICT)
return bestSelectedDICT, anpks, collectanlyBounds, min_pks
def get_minVal(array):
"""
Function to find the three minimum values on array and their
corresponding indexes
:param array: array of values
:type array: array_like
:returns: Three minimum values of rho, index in rho_array
:rtype: tuple
"""
holdList =[]
if not isinstance(array, (list, tuple, np.ndarray)):
if isinstance(array, float):
array=np.array([array])
else :
try :
array =np.array([float(array)])
except:
raise Wex.WATexError_float('Could not convert %s to float!')
try :
# first option:find minimals locals values
minlocals = argrelextrema(array, np.less)[0]
temp_array =np.array([array[int(index)] for index in minlocals])
if len(minlocals) ==0:
ix = np.where(array ==array.min())
if len(ix)>1:
ix =ix[0]
temp_array = array[int(ix)]
except :
# second option: use archaic computation.
temp_array =np.sort(array)
else :
temp_array= np.sort(temp_array)
ss=0
for ii, tem_ar in enumerate(temp_array) :
if ss >=3 :
holdList=holdList[:3]
break
min_index = np.where(array==tem_ar)[0]
if len(min_index)==1 :
holdList.append((array[int(min_index)],
int(min_index)))
ss +=ii
elif len(min_index) > 1 :
# loop the index array and find the min for consistency
for jj, indx in enumerate(min_index):
holdList.append((array[int(indx)],
int(indx)))
ss =len(holdList)
# for consistency keep the 3 best min values
if len(holdList)>3 :
holdList = holdList[:3]
return holdList
def drawn_anomaly_boundaries(erp_data, appRes, index):
"""
Function to drawn anomaly boundary
and return the anomaly with its boundaries
:param erp_data: erp profile
:type erp_data: array_like or list
:param appRes: resistivity value of minimum pk anomaly
:type appRes: float
:param index: index of minimum pk anomaly
:type index: int
:return: anomaly boundary
:rtype: list of array_like
"""
f = 0 # flag to mention which part must be calculated
if index ==0 :
f = 1 # compute only right part
elif appRes ==erp_data[-1]:
f=2 # compute left part
def loop_sideBound(term):
"""
loop side bar from anomaly and find the term side
:param term: is array of left or right side of anomaly.
:type term: array
:return: side bar
:type: array_like
"""
tem_drawn =[]
maxT=0
for ii, tem_rho in enumerate(term) :
diffRes_betw_2pts= tem_rho - appRes
if diffRes_betw_2pts > maxT :
maxT = diffRes_betw_2pts
tem_drawn.append(tem_rho)
elif diffRes_betw_2pts < maxT :
# rho_limit = tem_rho
break
return np.array(tem_drawn)
# first broke erp profile from the anomalies
if f ==0 or f==2 :
left_term = erp_data[:index][::-1] # flip left term for looping
# flip again to keep the order
left_limit = loop_sideBound(term=left_term)[::-1]
if f==0 or f ==1 :
right_term= erp_data[index :]
right_limit=loop_sideBound(right_term)
# concat right and left to get the complete anomaly
if f==2:
anomalyBounds = np.append(left_limit,appRes)
elif f ==1 :
anomalyBounds = np.array([appRes]+ right_limit.tolist())
else:
left_limit = np.append(left_limit, appRes)
anomalyBounds = np.concatenate((left_limit, right_limit))
return appRes, index, anomalyBounds
def defineAnomaly(erp_data, station_position=None, pks=None,
dipole_length=10., **kwargs):
"""
Function will select the different anomalies. If pk is not given,
the best three anomalies on the survey lines will be
computed automatically
:param erp_data: Electrical resistivity profiling
:type erp_data: array_like
:param pks: station positions anomaly boundaries (pk_begin, pk_end)
If selected anomalies is more than one, set `pks` into dict
where number of anomaly =keys and pks = values
:type pks: list or dict
:param dipole_length: Distance between two measurements in meters
Change the `dipole lengh
:type dipole_length: float
:param station_position: station position array
:type statiion_position: array_like
:return: list of anomalies bounds
"""
selectedPk =kwargs.pop('selectedPk', None)
bestSelectedDICT={}
if station_position is not None :
dipole_length = (station_position.max()-
station_position.min())/(len(station_position -1))
if station_position is None :
station_position =np.arange(0, dipole_length * len(erp_data),
dipole_length)
def getBound(pksbounds):
"""
Get the bound from the given `pks`
:param pksbounds: Anomaly boundaries
:type pksbounds: list of array_like
:returns: * anomBounds- array of appRes values of anomaly
:rtype: array_like
"""
# check if bound is on station positions
for spk in pksbounds :
if not pksbounds.min() <= spk <= pksbounds.max():
raise Wex.WATexError_AnomalyBounds(
'Bound <{0}> provided is out of range !'
'Dipole length is set to = {1} m.'
' Please set a new bounds.')
pkinf = np.where(station_position==pksbounds.min())[0]
pksup = np.where(station_position==pksbounds.max())[0]
anomBounds = erp_data[int(pkinf):int(pksup)+1]
return anomBounds
if pks is None :
bestSelectedDICT, *_= compute_lower_anomaly(
erp_array=erp_data, step=dipole_length,
station_position =station_position)
elif isinstance(pks, list):
pks =np.array(sorted(pks))
collectanlyBounds = getBound(pksbounds= pks)
# get the length of selected anomalies and computed the station
# location wich composed the bounds (Xbegin and Xend)
pkb, *_= find_pk_from_selectedAn(
an_res_range=collectanlyBounds, pos=pks,
selectedPk=selectedPk)
bestSelectedDICT={ '1_{}'.format(pkb):collectanlyBounds}
elif isinstance(pks, dict):
for ii, (keys, values) in enumerate(pks.items()):
if isinstance(values, list):
values =np.array(values)
collectanlyBounds= getBound(pksbounds=values)
pkb, *_= find_pk_from_selectedAn(
an_res_range=collectanlyBounds, pos=pks,
selectedPk=selectedPk)
bestSelectedDICT['{0}_{1}'.format(ii+1, pkb)]=collectanlyBounds
return bestSelectedDICT
def find_pk_from_selectedAn(an_res_range, pos=None, selectedPk=None):
"""
Function to select the main :ref:`pk` from both :ref:`anBounds`.
:paran an_res_range: anomaly resistivity range on :ref:`erp` line.
:type an_res_range: array_like
:param pos: position of anomaly boundaries (inf and sup):
anBounds = [90, 130]
- 130 is max boundary and 90 the min boundary
:type pos: list
:param selectedPk:
User can set its own position of the right anomaly. Be sure that
the value provided is right position .
Could not compute again provided that `pos`
is not `None`.
:return: anomaly station position.
:rtype: str 'pk{position}'
:Example:
>>> from watex.utils.wmathandtricks import find_pk_from_selectedAn
>>> resan = np.array([168,130, 93,146,145])
>>> pk= find_pk_from_selectedAn(
... resan, pos=[90, 13], selectedPk= 'str20')
>>> pk
"""
#compute dipole length from pos
if pos is not None :
if isinstance(pos, list):
pos =np.array(pos)
if pos is None and selectedPk is None :
raise Wex.WATexError_parameter_number(
'Give at least the anomaly boundaries'
' before computing the selected anomaly position.')
if selectedPk is not None : # mean is given
if isinstance(selectedPk, str):
if selectedPk.isdigit() :
sPk= int(selectedPk)
elif selectedPk.isalnum():
oss = ''.join([s for s in selectedPk
if s.isdigit()])
sPk =int(oss)
else :
try :
sPk = int(selectedPk)
except : pass
if pos is not None : # then compare the sPk and ps value
try :
if not pos.min()<= sPk<=pos.max():
warnings.warn('Wrong position given <{}>.'
' Should compute new positions.'.
format(selectedPk))
_logger.debug('Wrong position given <{}>.'
'Should compute new positions.'.
format(selectedPk))
except UnboundLocalError:
print("local variable 'sPk' referenced before assignment")
else :
return 'pk{}'.format(sPk ), an_res_range
else :
selectedPk='pk{}'.format(sPk )
return selectedPk , an_res_range
if isinstance(pos, list):
pos =np.array(pos)
if isinstance(an_res_range, list):
an_res_range =np.array(an_res_range)
dipole_length = (pos.max()-pos.min())/(len(an_res_range)-1)
tem_loc = np.arange(pos.min(), pos.max()+dipole_length, dipole_length)
# find min value of collected anomalies values
locmin = np.where (an_res_range==an_res_range.min())[0]
if len(locmin) >1 : locmin =locmin[0]
pk_= int(tem_loc[int(locmin)]) # find the min pk
selectedPk='pk{}'.format(pk_)
return selectedPk , an_res_range
def fmtAnText(anFeatures=None, title=['Ranking', 'rho(Ω.m)',
'position pk(m)',
'rho range(Ω.m)'],
**kwargs) :
"""
Function format text from anomaly features
:param anFeatures: Anomaly features
:type anFeatures: list or dict
:param title: head lines
:type title: list
:Example:
>>> from watex.utils.wmathandtricks import fmtAnText
>>> fmtAnText(anFeatures =[1,130, 93,(146,145, 125)])
"""
inline =kwargs.pop('inline', '-')
mlabel =kwargs.pop('mlabels', 100)
line = inline * int(mlabel)
#--------------------header ----------------------------------------
print(line)
tem_head ='|'.join(['{:^15}'.format(i) for i in title[:-1]])
tem_head +='|{:^45}'.format(title[-1])
print(tem_head)
print(line)
#-----------------------end header----------------------------------
newF =[]
if isinstance(anFeatures, dict):
for keys, items in anFeatures.items():
rrpos=keys.replace('_pk', '')
rank=rrpos[0]
pos =rrpos[1:]
newF.append([rank, min(items), pos, items])
elif isinstance(anFeatures, list):
newF =[anFeatures]
for anFeatures in newF:
strfeatures ='|'.join(['{:^15}'.format(str(i)) \
for i in anFeatures[:-1]])
try :
iter(anFeatures[-1])
except :
strfeatures +='|{:^45}'.format(str(anFeatures[-1]))
else :
strfeatures += '|{:^45}'.format(
''.join(['{} '.format(str(i)) for i in anFeatures[-1]]))
print(strfeatures)
print(line)
def select_anomaly ( rhoa_array, pos_array=None, auto=True,
dipole_length =10., **kws ) :
"""
Select the anomaly value from `rhoa_array` and find its boundaries if
``auto` is set to ``True``. If `auto` is ``False``, it's usefull to
provide the anomaly boundaries from station position. Change the argument
`dipole_length` i.e. the distance between measurement electrode is not
equal to ``10``m else give the `pos_array`. If the `pos_array` is given,
the `dipole_length` will be recomputed.
:note: If the `auto` param is ``True``, the automatic computation will
give at most three best animalies ranking according
to the resitivity value.
:param rhoa_array: The apparent resistivity value of :ref:`erp`
:type rho_array: array_like
:param pos_array: The array of station position in meters
:type pos_array: array_like
:param auto:
Automaticaly of manual computation to select the best anomaly point.
Be sure if `auto` is set to ``False`` to provide the anomaly boundary
by setting `pos_bounds` :
pos_bounds=(90, 130)
where :math:`90` is the `pk_min` and :math:`130` is the `pk_max`
If `pos_bounds` is not given an station error will probably occurs
from :class:`~utils.exceptions.WATexError_station`.
:param dipole_length:
Is the distance between two closest measurement. If the value is known
it's better to provide it and don't need to provied a `pos_array`
value.
:type dipole_length: float
:param pos_bounds:
Is the tuple value of anomaly boundaries composed of `pk_min` and
`pk_max`. Please refer to :doc:`compute_power`. When provided
the `pos_bounds` value, please set `the dipole_length` to accurate
the computation of :func:`compute_power`.
:return:
- *rhoa*: The app. resistivity value of the selected anomaly
- `pk_min` and the `pk_max`: refer to :doc:`compute_power`.
- `rhoa_max` and `rhoa_min`: refer to :doc:`compute_magnitude`
-
"""
pos_bounds =kws.pop("pos_bounds", (None, None))
anom_pos = kws.pop('pos_anomaly', None)
display_infos =kws.pop('display', False)
if auto is False :
if None in pos_bounds or pos_bounds is None :
raise Wex.WATexError_site('One position is missed'
'Plase provided it!')
pos_bounds = np.array(pos_bounds)
pos_min, pos_max = pos_bounds.min(), pos_bounds.max()
# get the res from array
dl_station_loc = np.arange(0, dipole_length * len(rhoa_array),
dipole_length)
# then select rho range
ind_pk_min = int(np.where(dl_station_loc==pos_min)[0])
ind_pk_max = int(np.where(dl_station_loc==pos_max)[0])
rhoa_range = rhoa_array [ind_pk_min:ind_pk_max +1]
pk, res= find_pk_from_selectedAn(an_res_range=rhoa_range,
pos=pos_bounds,
selectedPk= anom_pos)
pk = int(pk.replace('pk', ''))
rhoa = rhoa_array[int(np.where(dl_station_loc == pk )[0])]
rhoa_min = rhoa_array[int(np.where(dl_station_loc == pos_min )[0])]
rhoa_max = rhoa_array[int(np.where(dl_station_loc == pos_max)[0])]
rhoa_bounds = (rhoa_min, rhoa_max)
return {'1_pk{}'.format(pk):
(pk, rhoa, pos_bounds, rhoa_bounds, res)}
if auto:
bestSelectedDICT, anpks, \
collectanlyBounds, min_pks = compute_lower_anomaly(
erp_array= rhoa_array,
station_position= pos_array, step= dipole_length,
display_infos=display_infos )
return {key: find_pkfeatures (anom_infos= bestSelectedDICT,
anom_rank= ii+1, pks_rhoa_index=min_pks,
dl=dipole_length)
for ii, (key , rho_r) in enumerate(bestSelectedDICT.items())
}
def find_pkfeatures (anom_infos, anom_rank, pks_rhoa_index, dl):
"""
Get the pk bound from ranking of computed best points
:param anom_infos:
Is a dictionnary of best anomaly points computed from
:func:`compute_lower_anomaly` when `pk_bounds` is not given.
see :doc:`compute_lower_anomaly`
:param anom_rank: Automatic ranking after selecting best points
:param pk_rhoa_index:
Is tuple of selected anomaly resistivity value and index in the whole
:ref:`erp` line. for instance:
pks_rhoa_index= (80., 17)
where "80" is the value of selected anomaly in ohm.m and "17" is the
index of selected points in the :ref:`erp` array.
:param dl:
Is the distance between two measurement as `dipole_length`. Provide
the `dl` if the *default* value is not right.
:returns:
see :doc:`select_anomaly`
"""
rank_code = '{}_pk'.format(anom_rank)
for key in anom_infos.keys():
if rank_code in key:
pk = float(key.replace(rank_code, ''))
rhoa = list(pks_rhoa_index[anom_rank-1])[0]
codec = key
break
ind_rhoa =np.where(anom_infos[codec] ==rhoa)[0]
if len(ind_rhoa) ==0 : ind_rhoa =0
leninf = len(anom_infos[codec][: int(ind_rhoa)])
pk_min = pk - leninf * dl
lensup =len(anom_infos[codec][ int(ind_rhoa):])
pk_max = pk + (lensup -1) * dl
pos_bounds = (pk_min, pk_max)
rhoa_bounds = (anom_infos[codec][0], anom_infos[codec][-1])
return pk, rhoa, pos_bounds, rhoa_bounds, anom_infos[codec]
def find_pkBounds( pk , rhoa, rhoa_range, dl=10.):
"""
Find station position boundary indexed in :ref:`erp` line. Usefull
to get the boundaries indexes `pk_boun_indexes` for :ref:`erp`
normalisation when computing `anr` or else.
:param pk: Selected anomaly station value
:type pk: float
:param rhoa: Selected anomaly value in ohm.m
:type rhoa: float
:rhoa_range: Selected anomaly values from `pk_min` to `pk_max`
:rhoa_range: array_like
:parm dl: see :doc:`find_pkfeatures`
:Example:
>>> from from watex.utils.wmathandtricks import find_pkBounds
>>> find_pkBounds(pk=110, rhoa=137,
rhoa_range=np.array([175,132,137,139,170]))
"""
if isinstance(pk, str):
pk = float(pk.replace(pk[0], '').replace('_pk', ''))
index_rhoa = np.where(rhoa_range ==rhoa)[0]
if len(index_rhoa) ==0 : index_rhoa =0
leftlen = len(rhoa_range[: int(index_rhoa)])
rightlen = len(rhoa_range[int(index_rhoa):])
pk_min = pk - leftlen * dl
pk_max = pk + (rightlen -1) * dl
return pk_min, pk_max
def wrap_infos (phrase , value ='', underline ='-', unit ='',
site_number= '', **kws) :
"""Display info from anomaly details."""
repeat =kws.pop('repeat', 77)
intermediate =kws.pop('inter+', '')
begin_phrase_mark= kws.pop('begin_phrase', '--|>')
on = kws.pop('on', False)
if not on: return ''
else :
print(underline * repeat)
print('{0} {1:<50}'.format(begin_phrase_mark, phrase),
'{0:<10} {1}'.format(value, unit),
'{0}'.format(intermediate), "{}".format(site_number))
print(underline * repeat )
def drawn_anomaly_boundaries2(erp_data, appRes, index):
"""
Function to drawn anomaly boundary
and return the anomaly with its boundaries
:param erp_data: erp profile
:type erp_data: array_like or list
:param appRes: resistivity value of minimum pk anomaly
:type appRes: float
:param index: index of minimum pk anomaly
:type index: int
:return: anomaly boundary
:rtype: list of array_like
"""
f = 0 # flag to mention which part must be calculated
if index ==0 :
f = 1 # compute only right part
elif appRes ==erp_data[-1]:
f=2 # compute left part
def loop_sideBound(term):
"""
loop side bar from anomaly and find the term side
:param term: is array of left or right side of anomaly.
:type trem: array
:return: side bar
:type: array_like
"""
tem_drawn =[]
maxT=0
for ii, tem_rho in enumerate(term) :
diffRes_betw_2pts= tem_rho - appRes
if diffRes_betw_2pts > maxT :
maxT = diffRes_betw_2pts
tem_drawn.append(tem_rho)
elif diffRes_betw_2pts < maxT :
# rho_limit = tem_rho
break
# print(tem_drawn)
return np.array(tem_drawn)
# first broke erp profile from the anomalies
if f==2 : # compute the left part
# flip array and start backward counting
temp_erp_data = erp_data [::-1]
sbeg = appRes # initialize value
for ii, valan in enumerate(temp_erp_data):
if valan >= sbeg:
sbeg = valan
elif valan < sbeg:
left_term = erp_data[ii:]
break
left_term = erp_data[:index][::-1] # flip left term for looping
# flip again to keep the order
left_limit = loop_sideBound(term=left_term)[::-1]
if f==0 or f ==1 :
right_term= erp_data[index :]
right_limit=loop_sideBound(right_term)
# concat right and left to get the complete anomaly
if f==2:
anomalyBounds = np.append(left_limit,appRes)
elif f ==1 :
anomalyBounds = np.array([[appRes]+ right_limit.tolist()])
else:
left_limit = np.append(left_limit, appRes)
anomalyBounds = np.concatenate((left_limit, right_limit))
return appRes, index, anomalyBounds
def getdfAndFindAnomalyBoundaries(df):
"""
Define anomaly boundary `upper bound` and `lowerbound` from
:ref:`ves` location.
:param df: Dataframe pandas contained the columns
'pk', 'x', 'y', 'rho', 'dl'.
returns:
- `autoOption` triggered the automatic Option if nothing is specified
into excelsheet.
- `ves_loc`: Sounding curve location at pk
- `posMinMax`: Anomaly boundaries composed of ``lower`` and ``upper``
bounds.
Specific names can be used to define lower and upper bounds::
`lower`: 'lower', 'inf', 'min', 'min', '1' or 'low'
`upper`: 'upper', 'sup', 'maj', 'max', '2, or 'up'
To define the sounding location, can use::
`ves`:'ves', 'se', 'sond','vs', 'loc', '0' or 'dl'
"""
shape_=[ 'V','W', 'U', 'H', 'M', 'C', 'K' ]
type__= ['EC', 'NC', 'CP', 'CB2P']
# - ``EC`` for Extensive conductive.
# - ``NC`` for narrow conductive.
# - ``CP`` for conductive PLANE
# - ``CB2P`` for contact between two planes.
shape =None
type_ =None
def recoverShapeOrTypefromSheet(listOfAddedArray, param):
""" Loop the array and get whether an anomaly shape name is provided
:param listOfAddedArray: all Added array values except
'pk', 'x', 'y', 'rho' are composed of list of addedArray.
:param param: Can be main description of different `shape_` of `type__`
:returns:
- `shape` : 'V','W', 'U', 'H', 'M', 'C' or 'K' from sheet or
`type` : 'EC', 'NC', 'CP', 'CB2P'
- listOfAddedArray : list of added array
"""
param_ =None
for jj, colarray in enumerate(listOfAddedArray[::-1]):
tem_=[str(ss).upper().strip() for ss in list(colarray)]
for ix , elem in enumerate(tem_):
for param_elm in param:
if elem ==param_elm :
# retrieves the shape and replace by np.nan value
listOfAddedArray[::-1][jj][ix]=np.nan
return param_elm , listOfAddedArray
return param_, listOfAddedArray
def mergeToOne(listOfColumns, _df):
""" Get data from other columns annd merge into one array
:param listOfColumns: Columns names
:param _df: dataframe to retrieve data to one
"""
new_array = np.full((_df.shape[0],), np.nan)
listOfColumnData = [ _df[name].to_numpy() for name in listOfColumns ]
# loop from backward so we keep the most important to the first row
# close the main df that composed `pk`,`x`, `y`, and `rho`.
# find the shape
shape, listOfColumnData = recoverShapeOrTypefromSheet(listOfColumnData,
param =shape_)
type_, listOfColumnData = recoverShapeOrTypefromSheet(listOfColumnData,
param =type__)
for colarray in listOfColumnData[::-1]:
for ix , val in enumerate(colarray):
try:
if not np.isnan(val) :
new_array[ix]=val
except :pass
return shape , type_, new_array
def retrieve_ix_val(array):
""" Retrieve value and index and build `posMinMax boundaries
:param array: array of main colum contains the anomaly definitions or
a souding curve location like ::
sloc = [NaN, 'low', NaN, NaN, NaN, 'ves', NaN,
NaN, 'up', NaN, NaN, NaN]
`low`, `ves` and `up` are the lower boundary, the electric
sounding and the upper boundary of the selected anomaly
respectively.
For instance, if dipole_length is =`10`m, t he location (`pk`)
of `low`, `ves` and `up` are 10, 50 and 80 m respectively.
`posMinMax` =(10, 80)
"""
lower_ix =None
upper_ix =None
ves_ix = None
array= array.reshape((array.shape[0],) )
for ix, val in enumerate(array):
for low, up, vloc in zip(
['lower', 'inf', 'min', 'min', '1', 'low'],
['upper', 'sup', 'maj', 'max', '2', 'up'],
['ves', 'se', 'sond','vs', 'loc', '0', 'dl']
):
try :
floatNaNor123= np.float(val)
except:
if val.lower().find(low)>=0:
lower_ix = ix
break
elif val.lower().find(up) >=0:
upper_ix = ix
break
elif val.lower().find(vloc)>=0:
ves_ix = ix
break
else :
if floatNaNor123 ==1:
lower_ix = ix
break
elif floatNaNor123 ==2:
upper_ix = ix
break
elif floatNaNor123 ==0:
ves_ix = ix
break
return lower_ix, ves_ix, upper_ix
# set pandas so to consider np.inf as NaN number.
pd.options.mode.use_inf_as_na = True
# unecesseray to specify the colum of sounding location.
# dl =['drill', 'dl', 'loc', 'dh', 'choi']
_autoOption=False # set automatic to False one posMinMax
# not found as well asthe anomaly location `ves`.
posMinMax =None
#get df columns from the 4-iem index
for sl in ['pk', 'sta', 'loc']:
for val in df.columns:
if val.lower()==sl:
pk_series = df[val].to_numpy()
break
listOfAddedColumns= df.iloc[:, 4:].columns
if len(listOfAddedColumns) ==0:
return True, shape, type_, None, posMinMax, df
df_= df.iloc[:, 4:]
# check whether all remains dataframe values are `NaN` values
if len(list(df_.columns[df_.isna().all()])) == len(listOfAddedColumns):
# If yes , trigger the auto option
return True, shape, type_, None, posMinMax, df.iloc[:, :4]
# get the colum name with any nan values
sloc_column=list(df_.columns[df_.isna().any()])
# if column contains one np.nan, the sloc colum is found
sloc_values = df_[sloc_column].to_numpy()
if len(sloc_column)>1 : #
# get the value from single array
shape , type_, sloc_values = mergeToOne(sloc_column, df_)
lower_ix, ves_ix ,upper_ix = retrieve_ix_val(sloc_values)
# if `lower` and `upper` bounds are not found then start or end limits of
# selected anomaly from the position(pk) of the sounding curve.
if lower_ix is None :
lower_ix =ves_ix
if upper_ix is None:
upper_ix = ves_ix
if (lower_ix and upper_ix ) is None:
posMinMax =None
if posMinMax is None and ves_ix is None: _autoOption =True
else :
posMinMax =(pk_series[lower_ix], pk_series[upper_ix] )
if ves_ix is None: ves_loc=None
else : ves_loc = pk_series[ves_ix]
return _autoOption, shape, type_, ves_loc , posMinMax, df.iloc[:, :4]
@deprecated('Deprecated function to `:func:`watex.core.erp.get_type`'
' more efficient using median and index computation. It will '
'probably deprecate soon for neural network pattern recognition.')
def get_type (erp_array, posMinMax, pk, pos_array, dl):
"""
Find anomaly type from app. resistivity values and positions locations
:param erp_array: App.resistivty values of all `erp` lines
:type erp_array: array_like
:param posMinMax: Selected anomaly positions from startpoint and endpoint
:type posMinMax: list or tuple or nd.array(1,2)
:param pk: Position of selected anomaly in meters
:type pk: float or int
:param pos_array: Stations locations or measurements positions
:type pos_array: array_like
:param dl:
Distance between two receiver electrodes measurement. The same
as dipole length in meters.
:returns:
- ``EC`` for Extensive conductive.
- ``NC`` for narrow conductive.
- ``CP`` for conductive plane
- ``CB2P`` for contact between two planes.
:Example:
>>> from watex.core.erp import get_type
>>> x = [60, 61, 62, 63, 68, 65, 80, 90, 100, 80, 100, 80]
>>> pos= np.arange(0, len(x)*10, 10)
>>> ano_type= get_type(erp_array= np.array(x),
... posMinMax=(10,90), pk=50, pos_array=pos, dl=10)
>>> ano_type
...CB2P
"""
# Get position index
anom_type ='CP'
index_pos = int(np.where(pos_array ==pk)[0])
# if erp_array [:index_pos +1].mean() < np.median(erp_array) or\
# erp_array[index_pos:].mean() < np.median(erp_array) :
# anom_type ='CB2P'
if erp_array [:index_pos+1].mean() < np.median(erp_array) and \
erp_array[index_pos:].mean() < np.median(erp_array) :
anom_type ='CB2P'
elif erp_array [:index_pos +1].mean() >= np.median(erp_array) and \
erp_array[index_pos:].mean() >= np.median(erp_array) :
if dl <= (max(posMinMax)- min(posMinMax)) <= 5* dl:
anom_type = 'NC'
elif (max(posMinMax)- min(posMinMax))> 5 *dl:
anom_type = 'EC'
return anom_type
if __name__=='__main__':
path = 'data/erp/l10_gbalo.xlsx' # ztepogovogo_0
path= r'F:\repositories\watex\data\Bag.main&rawds\ert_copy\nt\b1_5.xlsx'
path = 'data/erp/test_anomaly.xlsx'
data = pd.read_excel(path).to_numpy()[:, -1]
df = pd.read_excel(path)
# autotrig, shape ,type_, indexanom , posMinMax, newdf = getdfAndFindAnomalyBoundaries(df)
# print(autotrig, shape,type_, indexanom , posMinMax, newdf)
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12429,
46265,
22046,
8,
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15553,
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11,
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11,
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11,
7,
20964,
11,
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11,
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198,
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198,
220,
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198,
220,
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220,
26098,
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46265,
22046,
13,
12924,
10786,
45145,
3256,
705,
12,
11537,
198,
220,
220,
220,
285,
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22046,
13,
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4029,
397,
1424,
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198,
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1627,
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26098,
1635,
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8,
198,
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220,
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1303,
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7,
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1314,
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18982,
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16,
11907,
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2169,
62,
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11,
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220,
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329,
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11,
3709,
287,
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23595,
13,
23814,
33529,
220,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
374,
81,
1930,
28,
13083,
13,
33491,
10786,
62,
79,
74,
3256,
10148,
8,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
4279,
28,
21062,
1930,
58,
15,
60,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1426,
796,
21062,
1930,
58,
16,
47715,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
649,
37,
13,
33295,
26933,
43027,
11,
949,
7,
23814,
828,
1426,
11,
3709,
12962,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
198,
220,
220,
220,
1288,
361,
318,
39098,
7,
272,
23595,
11,
1351,
2599,
220,
198,
220,
220,
220,
220,
220,
220,
220,
649,
37,
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58,
272,
23595,
60,
198,
220,
220,
220,
220,
198,
220,
220,
220,
220,
198,
220,
220,
220,
329,
281,
23595,
287,
649,
37,
25,
220,
198,
220,
220,
220,
220,
220,
220,
220,
965,
40890,
796,
6,
91,
4458,
22179,
7,
17816,
90,
25,
61,
1314,
92,
4458,
18982,
7,
2536,
7,
72,
4008,
3467,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
329,
1312,
287,
281,
23595,
58,
21912,
16,
11907,
8,
198,
220,
220,
220,
220,
220,
220,
220,
1949,
1058,
220,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
11629,
7,
272,
23595,
58,
12,
16,
12962,
198,
220,
220,
220,
220,
220,
220,
220,
2845,
1058,
220,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
965,
40890,
1343,
11639,
91,
90,
25,
61,
2231,
92,
4458,
18982,
7,
2536,
7,
272,
23595,
58,
12,
16,
60,
4008,
198,
220,
220,
220,
220,
220,
220,
220,
2073,
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220,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
965,
40890,
15853,
705,
91,
90,
25,
61,
2231,
92,
4458,
18982,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
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22179,
7,
17816,
90,
92,
45302,
18982,
7,
2536,
7,
72,
4008,
329,
1312,
287,
281,
23595,
58,
12,
16,
11907,
4008,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
198,
220,
220,
220,
220,
220,
220,
220,
3601,
7,
2536,
40890,
8,
198,
220,
220,
220,
220,
220,
220,
220,
3601,
7,
1370,
8,
198,
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220,
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220,
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220,
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4299,
2922,
62,
272,
24335,
357,
374,
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64,
62,
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11,
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62,
18747,
28,
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11,
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28,
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11,
198,
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220,
220,
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220,
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19550,
2305,
62,
13664,
796,
940,
1539,
12429,
74,
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1267,
1058,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
9683,
262,
32172,
1988,
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4600,
81,
8873,
64,
62,
18747,
63,
290,
1064,
663,
13215,
611,
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198,
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220,
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2292,
13,
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262,
4578,
220,
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220,
4600,
67,
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2305,
62,
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63,
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1312,
13,
68,
13,
262,
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318,
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198,
220,
220,
220,
220,
4961,
284,
7559,
940,
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76,
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1930,
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262,
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1930,
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18747,
63,
318,
1813,
11,
198,
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220,
262,
4600,
67,
541,
2305,
62,
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63,
481,
307,
664,
296,
17128,
13,
198,
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220,
220,
220,
220,
198,
220,
220,
220,
1058,
11295,
25,
220,
1002,
262,
4600,
23736,
63,
5772,
318,
7559,
17821,
15506,
11,
262,
11353,
29964,
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198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1577,
379,
749,
1115,
1266,
5044,
444,
12759,
1864,
220,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
284,
262,
581,
11365,
1988,
13,
220,
198,
220,
220,
220,
220,
220,
198,
220,
220,
220,
1058,
17143,
374,
8873,
64,
62,
18747,
25,
383,
4156,
4180,
3458,
1988,
286,
1058,
5420,
25,
63,
263,
79,
63,
220,
198,
220,
220,
220,
1058,
4906,
374,
8873,
62,
18747,
25,
7177,
62,
2339,
220,
198,
220,
220,
220,
220,
198,
220,
220,
220,
1058,
17143,
1426,
62,
18747,
25,
383,
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286,
4429,
2292,
287,
10700,
220,
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220,
220,
220,
1058,
4906,
1426,
62,
18747,
25,
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62,
2339,
220,
198,
220,
220,
220,
220,
220,
198,
220,
220,
220,
1058,
17143,
8295,
25,
220,
198,
220,
220,
220,
220,
220,
220,
220,
220,
198,
220,
220,
220,
220,
220,
220,
220,
17406,
39056,
88,
286,
10107,
29964,
284,
2922,
262,
1266,
32172,
966,
13,
220,
198,
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1355,
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281,
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3359,
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220,
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220,
220,
220,
220,
220,
220,
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705,
3646,
589,
2810,
340,
0,
11537,
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1303,
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28955,
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220,
220,
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1782,
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1058,
17143,
281,
296,
62,
43027,
25,
30199,
12759,
706,
17246,
1266,
2173,
220,
198,
220,
220,
220,
220,
220,
220,
220,
220,
198,
220,
220,
220,
1058,
17143,
279,
74,
62,
81,
8873,
64,
62,
9630,
25,
220,
198,
220,
220,
220,
220,
220,
220,
220,
220,
198,
220,
220,
220,
220,
220,
220,
220,
1148,
46545,
286,
6163,
32172,
4180,
3458,
1988,
290,
6376,
287,
262,
2187,
198,
220,
220,
220,
220,
220,
220,
220,
1058,
5420,
25,
63,
263,
79,
63,
1627,
13,
329,
4554,
25,
220,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
279,
591,
62,
81,
8873,
64,
62,
9630,
28,
357,
1795,
1539,
1596,
8,
220,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
198,
220,
220,
220,
220,
220,
220,
220,
810,
366,
1795,
1,
318,
262,
1988,
286,
6163,
32172,
287,
11752,
76,
13,
76,
290,
366,
1558,
1,
318,
262,
220,
198,
220,
220,
220,
220,
220,
220,
220,
6376,
286,
6163,
2173,
287,
262,
1058,
5420,
25,
63,
263,
79,
63,
7177,
13,
220,
198,
220,
220,
220,
220,
220,
220,
220,
220,
198,
220,
220,
220,
1058,
17143,
288,
75,
25,
220,
198,
220,
220,
220,
220,
220,
220,
220,
220,
198,
220,
220,
220,
220,
220,
220,
220,
1148,
262,
5253,
1022,
734,
15558,
355,
4600,
67,
541,
2305,
62,
13664,
44646,
44290,
220,
198,
220,
220,
220,
220,
220,
220,
220,
262,
4600,
25404,
63,
611,
262,
1635,
12286,
9,
1988,
318,
407,
826,
13,
220,
198,
220,
220,
220,
220,
220,
220,
220,
220,
198,
220,
220,
220,
1058,
7783,
82,
25,
220,
198,
220,
220,
220,
220,
220,
220,
220,
220,
198,
220,
220,
220,
220,
220,
220,
220,
766,
1058,
15390,
25,
63,
19738,
62,
272,
24335,
63,
198,
220,
220,
220,
220,
198,
220,
220,
220,
37227,
220,
220,
220,
220,
220,
198,
220,
220,
220,
4279,
62,
8189,
796,
705,
90,
92,
62,
79,
74,
4458,
18982,
7,
272,
296,
62,
43027,
8,
198,
220,
220,
220,
329,
1994,
287,
281,
296,
62,
10745,
418,
13,
13083,
33529,
220,
198,
220,
220,
220,
220,
220,
220,
220,
611,
4279,
62,
8189,
287,
1994,
25,
220,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
279,
74,
796,
12178,
7,
2539,
13,
33491,
7,
43027,
62,
8189,
11,
10148,
4008,
628,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
374,
8873,
64,
796,
1351,
7,
79,
591,
62,
81,
8873,
64,
62,
9630,
58,
272,
296,
62,
43027,
12,
16,
12962,
58,
15,
60,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
40481,
796,
1994,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2270,
220,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
198,
220,
220,
220,
773,
62,
81,
8873,
64,
796,
37659,
13,
3003,
7,
272,
296,
62,
10745,
418,
58,
19815,
721,
60,
6624,
81,
8873,
64,
38381,
15,
60,
198,
220,
220,
220,
611,
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7,
521,
62,
81,
8873,
64,
8,
6624,
15,
1058,
773,
62,
81,
8873,
64,
796,
15,
220,
198,
220,
220,
220,
18896,
10745,
796,
18896,
7,
272,
296,
62,
10745,
418,
58,
19815,
721,
7131,
25,
493,
7,
521,
62,
81,
8873,
64,
8,
12962,
198,
220,
220,
220,
220,
198,
220,
220,
220,
279,
74,
62,
1084,
796,
279,
74,
532,
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1635,
288,
75,
220,
198,
220,
220,
220,
10317,
929,
796,
11925,
7,
272,
296,
62,
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418,
58,
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7,
521,
62,
81,
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64,
2599,
12962,
198,
220,
220,
220,
279,
74,
62,
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796,
220,
279,
74,
1343,
357,
75,
641,
929,
532,
16,
8,
1635,
288,
75,
220,
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220,
220,
220,
220,
198,
220,
220,
220,
1426,
62,
65,
3733,
796,
357,
79,
74,
62,
1084,
11,
279,
74,
62,
9806,
8,
198,
220,
220,
220,
374,
8873,
64,
62,
65,
3733,
796,
357,
272,
296,
62,
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418,
58,
19815,
721,
7131,
15,
4357,
281,
296,
62,
10745,
418,
58,
19815,
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12,
16,
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198,
220,
220,
220,
220,
198,
220,
220,
220,
1441,
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11,
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11,
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11,
374,
8873,
64,
62,
65,
3733,
11,
281,
296,
62,
10745,
418,
58,
19815,
721,
60,
628,
198,
4299,
1064,
62,
79,
38841,
3733,
7,
279,
74,
837,
374,
8873,
64,
11,
374,
8873,
64,
62,
9521,
11,
288,
75,
28,
940,
47308,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
9938,
4429,
2292,
18645,
41497,
287,
1058,
5420,
25,
63,
263,
79,
63,
1627,
13,
5765,
12853,
220,
198,
220,
220,
220,
284,
651,
262,
13215,
39199,
4600,
79,
74,
62,
65,
977,
62,
9630,
274,
63,
329,
1058,
5420,
25,
63,
263,
79,
63,
220,
198,
220,
220,
220,
3487,
5612,
220,
618,
14492,
4600,
272,
81,
63,
393,
2073,
13,
220,
198,
220,
220,
220,
220,
198,
220,
220,
220,
1058,
17143,
279,
74,
25,
41344,
32172,
4429,
1988,
220,
198,
220,
220,
220,
1058,
4906,
279,
74,
25,
12178,
220,
198,
220,
220,
220,
220,
198,
220,
220,
220,
1058,
17143,
374,
8873,
64,
25,
41344,
32172,
1988,
287,
11752,
76,
13,
76,
220,
198,
220,
220,
220,
1058,
4906,
374,
8873,
64,
25,
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220,
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220,
220,
220,
220,
198,
220,
220,
220,
1058,
81,
8873,
64,
62,
9521,
25,
41344,
32172,
3815,
422,
4600,
79,
74,
62,
1084,
63,
284,
4600,
79,
74,
62,
9806,
63,
220,
198,
220,
220,
220,
1058,
81,
8873,
64,
62,
9521,
25,
7177,
62,
2339,
220,
198,
220,
220,
220,
220,
198,
220,
220,
220,
1058,
79,
1670,
288,
75,
25,
766,
1058,
15390,
25,
63,
19796,
62,
79,
74,
40890,
63,
198,
220,
220,
220,
220,
198,
220,
220,
220,
1058,
16281,
25,
220,
198,
220,
220,
220,
220,
220,
220,
220,
220,
198,
220,
220,
220,
220,
220,
220,
220,
13163,
422,
422,
266,
378,
87,
13,
26791,
13,
86,
11018,
392,
83,
23706,
1330,
1064,
62,
79,
38841,
3733,
220,
220,
198,
220,
220,
220,
220,
220,
220,
220,
13163,
1064,
62,
79,
38841,
3733,
7,
79,
74,
28,
11442,
11,
374,
8873,
64,
28,
19708,
11,
220,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
374,
8873,
64,
62,
9521,
28,
37659,
13,
18747,
26933,
17430,
11,
19924,
11,
19708,
11,
20219,
11,
17279,
60,
4008,
198,
220,
220,
220,
37227,
628,
220,
220,
220,
611,
318,
39098,
7,
79,
74,
11,
965,
2599,
220,
198,
220,
220,
220,
220,
220,
220,
220,
279,
74,
796,
12178,
7,
79,
74,
13,
33491,
7,
79,
74,
58,
15,
4357,
10148,
737,
33491,
10786,
62,
79,
74,
3256,
10148,
4008,
198,
220,
220,
220,
220,
220,
220,
220,
220,
198,
220,
220,
220,
6376,
62,
81,
8873,
64,
796,
45941,
13,
3003,
7,
81,
8873,
64,
62,
9521,
6624,
81,
8873,
64,
38381,
15,
60,
198,
220,
220,
220,
611,
18896,
7,
9630,
62,
81,
8873,
64,
8,
6624,
15,
1058,
6376,
62,
81,
8873,
64,
796,
15,
220,
198,
220,
220,
220,
220,
198,
220,
220,
220,
1364,
11925,
796,
18896,
7,
81,
8873,
64,
62,
9521,
58,
25,
493,
7,
9630,
62,
81,
8873,
64,
8,
12962,
198,
220,
220,
220,
826,
11925,
796,
18896,
7,
81,
8873,
64,
62,
9521,
58,
600,
7,
9630,
62,
81,
8873,
64,
2599,
12962,
198,
220,
220,
220,
220,
198,
220,
220,
220,
279,
74,
62,
1084,
796,
279,
74,
532,
1364,
11925,
1635,
288,
75,
220,
198,
220,
220,
220,
279,
74,
62,
9806,
796,
220,
279,
74,
1343,
357,
3506,
11925,
220,
532,
16,
8,
1635,
288,
75,
220,
198,
220,
220,
220,
220,
198,
220,
220,
220,
1441,
279,
74,
62,
1084,
11,
279,
74,
62,
9806,
220,
628,
198,
4299,
14441,
62,
10745,
418,
357,
34675,
837,
1988,
796,
6,
3256,
739,
1370,
796,
29001,
3256,
4326,
796,
6,
3256,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2524,
62,
17618,
28,
705,
3256,
12429,
74,
18504,
8,
1058,
220,
198,
220,
220,
220,
37227,
23114,
7508,
422,
32172,
3307,
526,
15931,
198,
220,
220,
220,
220,
198,
220,
220,
220,
9585,
796,
74,
18504,
13,
12924,
10786,
44754,
3256,
8541,
8,
198,
220,
220,
220,
19898,
796,
74,
18504,
13,
12924,
10786,
3849,
10,
3256,
10148,
8,
198,
220,
220,
220,
2221,
62,
34675,
62,
4102,
28,
479,
18504,
13,
12924,
10786,
27471,
62,
34675,
3256,
705,
438,
91,
29,
11537,
198,
220,
220,
220,
319,
796,
479,
18504,
13,
12924,
10786,
261,
3256,
10352,
8,
198,
220,
220,
220,
611,
407,
319,
25,
1441,
10148,
198,
220,
220,
220,
2073,
1058,
220,
198,
220,
220,
220,
220,
220,
220,
220,
3601,
7,
4625,
1370,
1635,
9585,
8,
198,
220,
220,
220,
220,
220,
220,
220,
3601,
10786,
90,
15,
92,
1391,
16,
25,
27,
1120,
92,
4458,
18982,
7,
27471,
62,
34675,
62,
4102,
11,
9546,
828,
220,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
90,
15,
25,
27,
940,
92,
1391,
16,
92,
4458,
18982,
7,
8367,
11,
4326,
828,
220,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
705,
90,
15,
92,
4458,
18982,
7,
3849,
13857,
828,
45144,
92,
1911,
18982,
7,
15654,
62,
17618,
4008,
198,
220,
220,
220,
220,
220,
220,
220,
3601,
7,
4625,
1370,
1635,
9585,
1267,
198,
220,
220,
220,
220,
198,
4299,
7428,
62,
272,
24335,
62,
7784,
3166,
17,
7,
263,
79,
62,
7890,
11,
598,
4965,
11,
6376,
2599,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
15553,
284,
7428,
32172,
18645,
220,
198,
220,
220,
220,
290,
1441,
262,
32172,
351,
663,
13215,
198,
220,
220,
220,
220,
198,
220,
220,
220,
1058,
17143,
1931,
79,
62,
7890,
25,
1931,
79,
7034,
220,
198,
220,
220,
220,
1058,
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1931,
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62,
7890,
25,
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393,
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220,
220,
220,
198,
220,
220,
220,
1058,
17143,
598,
4965,
25,
4180,
3458,
1988,
286,
5288,
279,
74,
32172,
220,
198,
220,
220,
220,
1058,
4906,
598,
4965,
25,
12178,
220,
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220,
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220,
220,
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220,
220,
220,
1058,
17143,
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25,
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279,
74,
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220,
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220,
220,
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25,
493,
220,
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220,
220,
220,
220,
198,
220,
220,
220,
1058,
7783,
25,
32172,
18645,
220,
198,
220,
220,
220,
1058,
81,
4906,
25,
1351,
286,
7177,
62,
2339,
220,
628,
220,
220,
220,
37227,
198,
220,
220,
220,
277,
796,
657,
1303,
6056,
284,
3068,
543,
636,
1276,
307,
10488,
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220,
611,
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6624,
15,
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220,
220,
220,
220,
220,
220,
277,
796,
352,
1303,
24061,
691,
826,
636,
220,
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220,
220,
1288,
361,
598,
4965,
6624,
263,
79,
62,
7890,
58,
12,
16,
5974,
220,
198,
220,
220,
220,
220,
220,
220,
220,
277,
28,
17,
1303,
24061,
1364,
636,
220,
198,
220,
220,
220,
220,
198,
220,
220,
220,
825,
9052,
62,
1589,
49646,
7,
4354,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
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30227,
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22655,
220,
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32172,
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220,
220,
220,
220,
220,
220,
220,
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8148,
13,
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1114,
4554,
11,
611,
19550,
2305,
62,
13664,
318,
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63,
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63,
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11,
256,
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357,
63,
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74,
63,
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13,
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220,
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220,
220,
220,
220,
220,
220,
4600,
1930,
9452,
11518,
63,
796,
7,
940,
11,
4019,
8,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
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220,
220,
220,
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2793,
62,
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796,
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220,
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6727,
62,
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198,
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220,
220,
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410,
274,
62,
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796,
6045,
220,
628,
220,
220,
220,
220,
220,
220,
220,
7177,
28,
7177,
13,
3447,
1758,
19510,
18747,
13,
43358,
58,
15,
4357,
8,
1267,
198,
220,
220,
220,
220,
220,
220,
220,
329,
220,
844,
11,
1188,
287,
27056,
378,
7,
18747,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
329,
1877,
11,
510,
11,
410,
17946,
287,
19974,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
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220,
37250,
21037,
3256,
705,
10745,
3256,
705,
1084,
3256,
705,
1084,
3256,
705,
16,
3256,
705,
9319,
6,
4357,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
37250,
45828,
3256,
705,
37330,
3256,
705,
76,
1228,
3256,
705,
9806,
3256,
705,
17,
3256,
705,
929,
6,
4357,
220,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
37250,
1158,
3256,
705,
325,
3256,
705,
82,
623,
41707,
14259,
3256,
705,
17946,
3256,
705,
15,
3256,
705,
25404,
20520,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
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15179,
220,
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220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
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1949,
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220,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
12178,
26705,
21991,
10163,
28,
45941,
13,
22468,
7,
2100,
8,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2845,
25,
220,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
611,
1188,
13,
21037,
22446,
19796,
7,
9319,
8,
29,
28,
15,
25,
220,
198,
220,
220,
220,
220,
220,
220,
220,
220,
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220,
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2793,
62,
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220,
220,
220,
220,
220,
220,
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2270,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1288,
361,
1188,
13,
21037,
22446,
19796,
7,
929,
8,
18189,
15,
25,
220,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
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6727,
62,
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2270,
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220,
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220,
220,
220,
220,
220,
220,
220,
220,
1288,
361,
1188,
13,
21037,
22446,
19796,
7,
85,
17946,
8,
29,
28,
15,
25,
220,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
410,
274,
62,
844,
796,
220,
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220,
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220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2270,
220,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2073,
1058,
220,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
611,
12178,
26705,
21991,
10163,
6624,
16,
25,
220,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2793,
62,
844,
796,
220,
844,
220,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2270,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1288,
361,
12178,
26705,
21991,
10163,
6624,
17,
25,
220,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
6727,
62,
844,
796,
220,
844,
220,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2270,
220,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1288,
361,
12178,
26705,
21991,
10163,
6624,
15,
25,
220,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
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] | 2.025714 | 18,745 |
import unittest
import os
import shutil
| [
11748,
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395,
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28686,
198,
11748,
4423,
346,
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] | 3.333333 | 12 |
# Copyright 2020-2022 Robert Bosch Car Multimedia GmbH
#
# 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.
# *******************************************************************************
#
# File: connection_base.py
#
# Initially created by Cuong Nguyen (RBVH/ECM11) / May 2021.
# Based on \lib\TCP\CTCPMultiQueued.py in TML Framework.
#
# Description:
# Provide the infrastructure for sending commands and getting traces from connection continuously.
#
# History:
#
# 12.05.2021 / V 0.1 / Cuong Nguyen
# - Initialize
#
# *******************************************************************************
from abc import ABCMeta
from inspect import currentframe
from collections import deque
from robot.libraries.BuiltIn import BuiltIn
from QConnectBase.qlogger import QLogger
import QConnectBase.constants as constants
import queue
import abc
import time
import platform
import threading
import re
_platform = platform.system().lower()
class ConnectionBase(object):
"""
Base class for all connection classes.
"""
__metaclass__ = ABCMeta
_SUPPORTED_PLATFORM_LIST = [constants.OS_WINDOWS_STR,
constants.OS_LINUX_STR]
_CONNECTION_TYPE = "NotSupported"
_ERROR_INSTRUCTION = constants.UNKNOWN_STR
MAX_LEN_BACKTRACE = 500 # Lines
RECV_MSGS_POLLING_INTERVAL = 0.005
_call_thrd_obj = None
_call_thrd_init = threading.Event()
_call_thrd_term = threading.Event()
_recv_thrd_obj = None
# _recv_thrd_term = threading.Event()
_recv_thrd_term = None
_force_seq_lock = threading.RLock()
_start_dlt_lock = threading.RLock()
_traceq_handle = 0
_traceq_obj = {}
_traceq_lock = threading.Lock()
supported_devices = []
# # for continuous processing
# _msgq_c_handle = 0
# _msgq_c_obj = {}
# _msgq_c_lock = threading.Lock()
_is_precondition_valid = True
_should_check_timeout = False
_logger = None
_logger_handler = None
config = None
def __new__(cls, *args, **kwargs):
"""
Override creating instance method to check for conditions.
Args:
args: Non-Keyword Arguments.
kwargs: Keyword Arguments.
Returns:
ConnectionBase instance if passing the conditions.
None if failing the conditions.
"""
if (not cls.is_supported_platform()) or (not cls.is_precondition_pass()):
return None
return super(ConnectionBase, cls).__new__(cls)
# region GENERAL METHODS
@classmethod
def is_supported_platform(cls):
"""
Check if current platform is supported.
Returns:
True if platform is supported.
False if platform is not supported.
"""
return _platform in cls._SUPPORTED_PLATFORM_LIST
@classmethod
def is_precondition_pass(cls):
"""
Check for precondition.
Returns:
True if passing the precondition.
False if failing the precondition.
"""
return cls._is_precondition_valid
def error_instruction(self):
"""
Get the error instruction.
Returns:
Error instruction string.
"""
return self._ERROR_INSTRUCTION
# endregion
# region MUST BE OVERRIDE METHODS
@abc.abstractmethod
def quit(self, is_disconnect_all=True):
"""
>> This method MUST be overridden in derived class <<
Abstract method for quiting the connection.
Args:
is_disconnect_all: Determine if it's necessary to disconnect all connections.
Returns:
None.
"""
self._logger.removeHandler(self._logger_handler)
@abc.abstractmethod
def connect(self, device, files=None, test_connection=False):
"""
>> This method MUST be overridden in derived class <<
Abstract method for quiting the connection.
Args:
device: Determine if it's necessary to disconnect all connections.
files: Determine if it's necessary to disconnect all connections.
test_connection: Determine if it's necessary to disconnect all connections.
Returns:
None.
"""
pass
@abc.abstractmethod
def disconnect(self, device):
"""
>> This method MUST be overridden in derived class <<
Abstract method for disconnecting connection.
Args:
device: Device name.
Returns:
None.
"""
pass
# endregion
# region RECEIVER THREAD METHODS
def _init_thrd_llrecv(self, n_thrd_id):
"""
Start a thread which receive message from connection continuously.
Args:
n_thrd_id: thread id.
Returns:
None
"""
_mident = '%s.%s()' % (self.__class__.__name__, currentframe().f_code.co_name)
self._llrecv_thrd_obj = threading.Thread(target=self._thrd_llrecv_from_connection_interface)
self._llrecv_thrd_obj.setDaemon(True)
self._llrecv_thrd_obj.name = str(self._CONNECTION_TYPE) + "-" + str(n_thrd_id)
BuiltIn().log("%s: starting low-level receiver thread '%s'" % (_mident, self._llrecv_thrd_obj.name), constants.LOG_LEVEL_DEBUG)
self._llrecv_thrd_obj.start()
def _thrd_llrecv_from_connection_interface(self):
"""
>> This method will be override in derived class <<
The thread which receive message from connection continuously.
Returns:
None
"""
pass
def _init_thread_receiver(self, thread_id, mode=None, sync_with_start=False):
"""
Initialize a thread for receiving data from connection.
Args:
thread_id: Thread ID number.
mode: Connection's mode.
sync_with_start: Determine if receiving thread needs to wait for start event.
Returns:
None
"""
_mident = '%s.%s()' % (self.__class__.__name__, currentframe().f_code.co_name)
thread_name = self._CONNECTION_TYPE
if mode is not None:
thread_name = mode
conn_id_name = str(thread_name) + str(thread_id)
self._logger = QLogger().get_logger(conn_id_name)
self._logger_handler = QLogger().set_handler(self.config)
self._recv_thrd_term = threading.Event()
self._recv_thrd_obj = threading.Thread(target=self._thread_receive_from_connection, kwargs=dict(sync_with_start=sync_with_start))
self._recv_thrd_obj.setDaemon(True)
self._recv_thrd_obj.name = conn_id_name
BuiltIn().log("%s: starting receiver thread '%s'" % (_mident, self._recv_thrd_obj.name))
self._recv_thrd_obj.start()
def _thread_receive_from_connection(self, sync_with_start=False):
"""
Thread to receive data from connection continuously.
Args:
sync_with_start: determine if thread needs to wait for start event.
Returns:
None
"""
_mident = '%s.%s()' % (self.__class__.__name__, currentframe().f_code.co_name)
if sync_with_start is True:
BuiltIn().log("%s: receiver thread is waiting to start." % _mident, constants.LOG_LEVEL_DEBUG)
while not self._recv_thrd_start.isSet():
time.sleep(self.__class__.RECV_MSGS_POLLING_INTERVAL)
BuiltIn().log("%s: receiver thread started." % _mident, constants.LOG_LEVEL_DEBUG)
while not self._recv_thrd_term.isSet():
try:
msg = self.read_obj()
if self._should_check_timeout:
self.check_timeout(msg)
if msg is not None:
self._should_check_timeout = False
self.pre_msg_check(msg)
BuiltIn().log(msg, constants.LOG_LEVEL_INFO)
if self._logger:
self._logger.info(msg)
# with self._msgq_c_lock:
# now = time.time()
# for q in self._msgq_c_obj.values():
# q.put((now, msg), False)
with self.__class__._traceq_lock:
if self.__class__._traceq_obj:
for (regex_filter, msg_queue, back_trace_queue, use_fetch_block, regex_end_block_pattern, regex_line_filter) in self.__class__._traceq_obj.values():
is_hit = False
result_obj = None
if use_fetch_block is True:
matchObj = regex_line_filter.search(msg)
if matchObj is not None:
back_trace_queue.append(msg)
(is_hit, result_obj) = self._filter_msg(regex_end_block_pattern, msg)
else:
(is_hit, result_obj) = self._filter_msg(regex_filter, msg)
if is_hit:
now = time.time()
if use_fetch_block is True:
result_obj = regex_filter.search("\r\n".join(back_trace_queue))
back_trace_queue.clear()
msg_queue.put((now, result_obj), False)
self.post_msg_check(msg)
except BrokenConnError as reason:
BuiltIn().log("%s: %s" % (_mident, reason), constants.LOG_LEVEL_DEBUG)
self._broken_conn.set()
break
except Exception as reason:
BuiltIn().log("%s: %s" % (_mident, reason), constants.LOG_LEVEL_WARNING)
time.sleep(self.__class__.RECV_MSGS_POLLING_INTERVAL)
self._recv_thrd_term.clear()
BuiltIn().log("%s: receiver thread terminated." % _mident, constants.LOG_LEVEL_DEBUG)
def send_obj(self, obj, cr=True):
"""
Wrapper method to send message to a tcp connection.
Args:
obj: Data to be sent.
cr: Determine if it's necessary to add newline character at the end of command.
Returns:
None
"""
_mident = '%s.%s()' % (self.__class__.__name__, currentframe().f_code.co_name)
BuiltIn().log('%s' % _mident, constants.LOG_LEVEL_DEBUG)
msg = obj
if self._is_connected:
# noinspection PyBroadException
try:
BuiltIn().log("%s: sending: '%s'" % (_mident, msg), constants.LOG_LEVEL_DEBUG)
self._send(msg, cr)
except:
self._is_connected = False
def read_obj(self):
"""
Wrapper method to get the response from connection.
Returns:
Responded message.
"""
_mident = '%s.%s()' % (self.__class__.__name__, currentframe().f_code.co_name)
BuiltIn().log('%s' % _mident, constants.LOG_LEVEL_DEBUG)
msg = None
if self._is_connected:
try:
BuiltIn().log("%s: reading..." % _mident, constants.LOG_LEVEL_DEBUG)
msg = self._read()
BuiltIn().log("%s: read: '%s'" % (_mident, msg), constants.LOG_LEVEL_DEBUG)
except BrokenConnError as reason:
BuiltIn().log("%s: %s" % (_mident, reason), constants.LOG_LEVEL_ERROR)
self._is_connected = False
raise reason
except Exception as reason:
BuiltIn().log("%s: %s" % (_mident, reason), constants.LOG_LEVEL_WARNING)
return msg
# endregion
# region TRACE INFRASTRUCTURE METHODS
def wait_4_trace(self, search_obj, timeout=0, use_fetch_block=False, end_of_block_pattern=".*", filter_pattern=".*", *fct_args):
"""
Suspend the control flow until a Trace message is received which matches to a specified regular expression.
Args:
search_obj : Regular expression all received trace messages are compare to. \
Can be passed either as a string or a regular expression object. Refer to Python documentation for module 're'.
use_fetch_block : Determine if 'fetch block' feature is used.
end_of_block_pattern : The end of block pattern.
filter_pattern : Regular expression object to filter message line by line.
timeout : Optional timeout parameter specified as a floating point number in the unit 'seconds'.
fct_args: Optional list of function arguments passed to be sent.
Returns:
None : If no trace message matched to the specified regular expression and a timeout occurred.
<match> : If a trace message has matched to the specified regular expression, a match object is returned as the result.\
The complete trace message can be accessed by the 'string' attribute of the match object.\
For access to groups within the regular expression, use the group() method.\
For more information, refer to Python documentation for module 're'.\
"""
_mident = '%s.%s()' % (self.__class__.__name__, currentframe().f_code.co_name)
BuiltIn().log('Execute %s' % _mident, constants.LOG_LEVEL_DEBUG)
search_regex = re.compile(search_obj, re.M | re.S | re.U)
regex_obj_filter = re.compile(filter_pattern)
trq_handle, trace_queue = self.create_and_activate_trace_queue(search_regex, use_fetch_block, end_of_block_pattern, regex_obj_filter)
try:
self.send_obj(*fct_args)
except Exception as err_msg: # pylint: disable=W0703
BuiltIn().log('%s: An Exception occurred executing function object: %s' % (_mident, repr(self.send_obj)), 'ERROR')
BuiltIn().log('Function Arguments: %s' % repr(fct_args), 'ERROR')
BuiltIn().log('Error Message: %s' % repr(err_msg), 'ERROR')
success = True
match = None
try:
(dummy, match) = trace_queue.get(True, timeout)
except queue.Empty:
success = False
finally:
self.deactivate_and_delete_trace_queue(trq_handle, trace_queue)
BuiltIn().log('Completed %s' % _mident, constants.LOG_LEVEL_DEBUG)
if success:
return match
else:
return None
def wait_4_trace_continuously(self, trace_queue, timeout=0, *fct_args):
"""
Getting trace log continuously without creating a new trace queue.
Args:
trace_queue: Queue to store the traces.
timeout: Timeout for waiting a matched log.
fct_args: Arguments to be sent to connection.
Returns:
None : If no trace message matched to the specified regular expression and a timeout occurred.
match object : If a trace message has matched to the specified regular expression, a match object is returned as the result. \
The complete trace message can be accessed by the 'string' attribute of the match object. \
For access to groups within the regular expression, use the group() method. \
For more information, refer to Python documentation for module 're'. \
"""
_mident = '%s.%s()' % (self.__class__.__name__, currentframe().f_code.co_name)
BuiltIn().log('Execute %s' % _mident, constants.LOG_LEVEL_DEBUG)
try:
self.send_obj(*fct_args)
except Exception as err_msg: # pylint: disable=W0703
BuiltIn().log('%s: An Exception occurred executing function object: %s' % (_mident, repr(self.send_obj)), 'ERROR')
BuiltIn().log('Function Arguments: %s' % repr(fct_args), 'ERROR')
BuiltIn().log('Error Message: %s' % repr(err_msg), 'ERROR')
success = True
match = None
try:
if trace_queue is not None:
(dummy, match) = trace_queue.get(True, timeout)
except queue.Empty:
success = False
BuiltIn().log('Completed %s' % _mident, constants.LOG_LEVEL_DEBUG)
if success:
return match
else:
return None
@classmethod
def create_and_activate_trace_queue(cls, search_element, use_fetch_block=False, end_of_block_pattern='.*', regex_line_filter_pattern=None):
"""
Create Queue and assign it to _trace_queue object and activate the queue with the search element.
Args:
search_element : Regular expression all received trace messages are compare to. \
Can be passed either as a string or a regular expression object. Refer to Python documentation for module 're'.#
use_fetch_block : Determine if 'fetch block' feature is used.
end_of_block_pattern : The end of block pattern.
regex_line_filter_pattern : Regular expression object to filter message line by line.
Returns:
trq_handle, trace_queue: the handle and search object
"""
trace_queue = queue.Queue()
trq_handle = cls.activate_trace_queue(search_element, trace_queue, use_fetch_block, end_of_block_pattern, regex_line_filter_pattern)
return trq_handle, trace_queue
@classmethod
def deactivate_and_delete_trace_queue(cls, trq_handle, trace_queue):
"""
Deactivate trace queue and delete.
Args:
trq_handle: Trace queue handle.
trace_queue: Trace queue object.
Returns:
None.
"""
cls.deactivate_trace_queue(trq_handle)
del trace_queue
@classmethod
def activate_trace_queue(cls, search_obj, trace_queue, use_fetch_block=False, end_of_block_pattern='.*', line_filter_pattern=None):
"""
Activates a trace message filter specified as a regular expression. All matching trace messages are put in the specified queue object.
Args:
search_obj : Regular expression all received trace messages are compare to. \
Can be passed either as a string or a regular expression object. Refer to Python documentation for module 're'.#
trace_queue : A queue object all trace message which matches the regular expression are put in. \
The using application must assure, that the queue is emptied or deleted.
use_fetch_block : Determine if 'fetch block' feature is used
end_of_block_pattern : The end of block pattern
line_filter_pattern : Regular expression object to filter message line by line.
Returns:
<int> : Handle to deactivate the message filter.
"""
_mident = '%s.%s()' % (cls.__class__.__name__, currentframe().f_code.co_name)
BuiltIn().log('Execute %s' % _mident, constants.LOG_LEVEL_DEBUG)
with cls._traceq_lock:
cls._traceq_handle += 1
back_trace_queue = deque(maxlen=cls.MAX_LEN_BACKTRACE)
search_regex_obj = re.compile(search_obj)
cls._traceq_obj[cls._traceq_handle] = (search_regex_obj,
trace_queue,
back_trace_queue,
use_fetch_block,
re.compile(end_of_block_pattern, re.M | re.S | re.U),
line_filter_pattern)
handle_id = cls._traceq_handle
BuiltIn().log('Completed %s' % _mident, constants.LOG_LEVEL_DEBUG)
return handle_id
@classmethod
def deactivate_trace_queue(cls, handle):
"""
Deactivates a trace message filter previously activated by ActivateTraceQ() method.
Args:
handle : Integer object returned by ActivateTraceQ() method.
Returns:
False : No trace message filter active with the specified handle (i.e. handle is not in use).
True : Trace message filter successfully deleted.
"""
_mident = '%s.%s()' % (cls.__class__.__name__, currentframe().f_code.co_name)
BuiltIn().log('Execute %s' % _mident, constants.LOG_LEVEL_DEBUG)
with cls._traceq_lock:
if handle in cls._traceq_obj:
del cls._traceq_obj[handle]
is_success = True
else:
is_success = False
BuiltIn().log('Completed %s' % _mident, constants.LOG_LEVEL_DEBUG)
return is_success
def check_timeout(self, msg):
"""
>> This method will be override in derived class <<
Check if responded message come in cls._RESPOND_TIMEOUT or we will raise a timeout event.
Args:
msg: Responded message for checking.
Returns:
None.
"""
pass
def pre_msg_check(self, msg):
"""
>> This method will be override in derived class <<
Pre-checking message when receiving it from connection.
Args:
msg: received message to be checked.
Returns:
None.
"""
pass
def post_msg_check(self, msg):
"""
>> This method will be override in derived class <<
Post-checking message when receiving it from connection.
Args:
msg: received message to be checked.
Returns:
None.
"""
pass
# endregion
# region UTILITIES METHODS
@staticmethod
@staticmethod
def _filter_msg(self, regex_filter_obj, msg):
"""
Filter message by regular expression object.
Args:
regex_filter_obj: regular expression object.
msg: message string.
Returns:
is_hit: Determine if there is any matched.
matched_obj: Matched object.
"""
_mident = '%s.%s()' % (self.__class__.__name__, currentframe().f_code.co_name)
BuiltIn().log(_mident, constants.LOG_LEVEL_DEBUG)
matched_obj = None
try:
BuiltIn().log("%s: regex_filter_obj '%s'" % (_mident, repr(regex_filter_obj)), constants.LOG_LEVEL_DEBUG)
BuiltIn().log("%s: msg '%s'" % (_mident, repr(msg)), constants.LOG_LEVEL_DEBUG)
matched_obj = regex_filter_obj.search(msg)
except Exception as reason:
BuiltIn().log("%s: %s" % (_mident, reason), constants.LOG_LEVEL_ERROR)
is_hit = False
if matched_obj:
is_hit = True
return is_hit, matched_obj
# endregion
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198,
220,
220,
220,
220,
220,
14451,
62,
26801,
796,
6045,
198,
220,
220,
220,
220,
220,
1949,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
28477,
818,
22446,
6404,
7203,
4,
82,
25,
40364,
62,
24455,
62,
26801,
705,
4,
82,
29653,
4064,
44104,
76,
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11,
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7,
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25636,
62,
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62,
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220,
220,
220,
220,
220,
220,
220,
28477,
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25,
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76,
738,
11,
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7,
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220,
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1,
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62,
2538,
18697,
62,
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8,
628,
220,
220,
220,
220,
220,
318,
62,
17945,
796,
10352,
198,
220,
220,
220,
220,
220,
611,
14451,
62,
26801,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
318,
62,
17945,
796,
6407,
198,
220,
220,
220,
220,
220,
1441,
318,
62,
17945,
11,
14451,
62,
26801,
198,
220,
220,
1303,
886,
36996,
198
] | 2.337569 | 9,601 |
from app.commands.create_admin import *
| [
6738,
598,
13,
9503,
1746,
13,
17953,
62,
28482,
1330,
1635,
198
] | 3.333333 | 12 |
from django.db import models
from django.utils.translation import ugettext_lazy as _
from pyconde.conference.models import Conference, CurrentConferenceManager
| [
6738,
42625,
14208,
13,
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1330,
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628
] | 3.857143 | 42 |
# -*- coding: utf-8 -*-
import optparse
import os
import sys
import getpass
import json
import hashlib
import smtplib
import commands
import subprocess
import shutil
# import appicon_generate
from xcode_build_module import XCodeBuild
#主函数
current_work_path=os.getcwd()
projecttest_path=current_work_path+"/project_test"
projectPathList=[projecttest_path]
for index in range(0,4):
resultPath=projecttest_path+"/../backup%s"%(index)
try:
shutil.rmtree(resultPath)
except BaseException:
pass
# print 'error!'
pass
for index in range(0,4):
resultPath=projecttest_path+"/../backup%s"%(index)
try:
shutil.copytree(projecttest_path, resultPath)
except BaseException:
pass
# print 'error.'
finally:
projectPathList.append(resultPath)
pass
test(projectPathList)
# ImgManager.sharedinstance().handle_icon_images()
# generateAppIcons()
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220,
220,
220,
220,
220,
220,
220,
1628,
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13,
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7,
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8,
198,
220,
220,
220,
1208,
198,
198,
9288,
7,
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15235,
8053,
8,
198,
2,
1846,
70,
13511,
13,
28710,
39098,
22446,
28144,
62,
4749,
62,
17566,
3419,
198,
2,
7716,
4677,
40,
5936,
3419,
198
] | 2.505435 | 368 |
from defs import *
import random
import miscellaneous
import pathfinding
from _custom_constants import *
from structure_display import *
__pragma__('noalias', 'name')
__pragma__('noalias', 'undefined')
__pragma__('noalias', 'Infinity')
__pragma__('noalias', 'keys')
__pragma__('noalias', 'get')
__pragma__('noalias', 'set')
__pragma__('noalias', 'type')
__pragma__('noalias', 'update')
# todo 정리 후 원래 스폰에 있던거 전부 제거요망
# REMOTE---------------------------------------------------------------------------
# ALL remotes.
"""
완성될 시 절차:
- 깃발을 다 둘러본다.
- 자기소속 깃발이 있을 경우 (W1E2-rm) 옵션에 넣는다.
+ 각종 기본값을 설정한다.
+ 넣을때 기본값으로 주둔시킬 병사 수를 지정한다. 디폴트 0
+ 도로를 또 깔것인가? 길따라 깐다. 디폴트 0
+ 모든 컨트롤러 있는 방 루프돌려서 이미 소속된 다른방이 있으면 그거 지운다.
+ 넣고나서 깃발 지운다.
- 추후 특정 이름이 들어간 깃발은 명령어대로 하고 삭제한다.
"""
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254,
250,
47991,
250,
46695,
97,
13,
220,
198,
198,
37811,
198
] | 1.130868 | 703 |
"""
Remove columns from a KGTK file.
"""
from argparse import Namespace, SUPPRESS
import typing
from kgtk.cli_argparse import KGTKArgumentParser, KGTKFiles
def add_arguments_extended(parser: KGTKArgumentParser, parsed_shared_args: Namespace):
"""
Parse arguments
Args:
parser (argparse.ArgumentParser)
"""
from kgtk.io.kgtkreader import KgtkReader, KgtkReaderOptions, KgtkReaderMode
from kgtk.utils.argparsehelpers import optional_bool
from kgtk.value.kgtkvalueoptions import KgtkValueOptions
_expert: bool = parsed_shared_args._expert
parser.add_input_file(positional=True)
parser.add_output_file()
parser.add_argument('-c', "--columns", action="store", type=str, dest="columns", nargs='+', required=True,
help="Columns to remove as a comma- or space-separated strings, e.g., id,docid or id docid")
parser.add_argument( "--split-on-commas", dest="split_on_commas", help="Parse the list of columns, splitting on commas. (default=%(default)s).",
type=optional_bool, nargs='?', const=True, default=True)
parser.add_argument( "--split-on-spaces", dest="split_on_spaces", help="Parse the list of columns, splitting on spaces. (default=%(default)s).",
type=optional_bool, nargs='?', const=True, default=False)
parser.add_argument( "--strip-spaces", dest="strip_spaces", help="Parse the list of columns, stripping whitespace. (default=%(default)s).",
type=optional_bool, nargs='?', const=True, default=True)
KgtkReader.add_debug_arguments(parser, expert=_expert)
KgtkReaderOptions.add_arguments(parser, mode_options=True, default_mode=KgtkReaderMode.NONE, expert=_expert)
KgtkValueOptions.add_arguments(parser, expert=_expert)
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] | 2.504775 | 733 |
"""
"""
from display import Display
from load import Loader
from game import Game
class Initializer:
"""
The class that handles the program before a game is launched.
"""
| [
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#171602012 - Ender Yılmaz
#Bilişim Sistemleri Mühendisliği
#Elektronik Komponent Kayıt Kontrol Sistemi
from PyQt5 import QtCore, QtGui, QtWidgets | [
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import numpy as np
def chunkify(tsd, seq_len):
"""
Splits a TimeSeriesDataset into chunks of length seq_len
Args:
tsd: TimeSeriesDataset object
seq_len: length of the subsequences to return
Returns: numpy arrays with chunks of size seq_len
"""
x, y = [], []
for s in tsd:
for i in range(len(s) - seq_len):
x_i = s._data["values"][i: i + seq_len]
y_i = s._data["values"][i + seq_len]
x.append(x_i)
y.append(y_i)
return np.array(x), np.array(y)
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7,
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] | 2.078652 | 267 |
import cv2
import uuid
import os
# tar为目标车牌号的后4位
| [
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from .logs import *
from .pull import *
from .build import *
from .clean import *
from .prune import *
from .test import *
from .watch import *
from .jooq import *
from .dbpw import * | [
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# -*- coding: utf-8 -*-
# Scrapy settings for douban project
#
# For simplicity, this file contains only settings considered important or
# commonly used. You can find more settings consulting the documentation:
#
# http://doc.scrapy.org/en/latest/topics/settings.html
# http://scrapy.readthedocs.org/en/latest/topics/downloader-middleware.html
# http://scrapy.readthedocs.org/en/latest/topics/spider-middleware.html
BOT_NAME = 'douban'
# Scrapy寻找spiders的地方，这是一个列表结构，你可以指定多个地方。
SPIDER_MODULES = ['douban.spiders']
# 用scrapy genspider [-t template] <name> <domain>命令生成的spider所放的地方
NEWSPIDER_MODULE = 'douban.spiders'
# Retry many times since proxies often fail
RETRY_TIMES = 10
# Retry on most error codes since proxies fail for different reasons
RETRY_HTTP_CODES = [500, 503, 504, 400, 403, 404, 408]
# 如果你不想用代理IP去抓取网页，注释掉下面的前三个组件。第四个组件的目的是定制自己request header.
DOWNLOADER_MIDDLEWARES = {
# 'scrapy.contrib.downloadermiddleware.retry.RetryMiddleware': 90,
# 'douban.randomproxy.RandomProxy': 100,
# 'scrapy.contrib.downloadermiddleware.httpproxy.HttpProxyMiddleware': 110,
'douban.MyMiddlewares.CustomUserAgentMiddleware':345,
}
# 把这个路徑改成你自己
PROXY_LIST = '/home/vincent/crawl_web/douban/proxy_list.txt'
# Configure item pipelines
ITEM_PIPELINES = {
'douban.pipelines.BookInfoPipeline': 300,
'douban.pipelines.IDPipeline': 500,
}
DOWNLOAD_DELAY = 2
# Enable and configure the AutoThrottle extension (disabled by default)
# See http://doc.scrapy.org/en/latest/topics/autothrottle.html
# NOTE: AutoThrottle will honour the standard settings for concurrency and delay
#AUTOTHROTTLE_ENABLED=False
# The initial download delay
#AUTOTHROTTLE_START_DELAY=3
# The maximum download delay to be set in case of high latencies
#AUTOTHROTTLE_MAX_DELAY=12
# Enable showing throttling stats for every response received:
#AUTOTHROTTLE_DEBUG=False
| [
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2,
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2394,
17184,
29089,
2538,
62,
30531,
28,
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198
] | 2.277846 | 817 |
import os
from django.core.management.base import BaseCommand
from django.contrib.auth import get_user_model
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# Licensed under a 3-clause BSD style license - see LICENSE.rst
"""
===============
eJWST TAP tests
===============
European Space Astronomy Centre (ESAC)
European Space Agency (ESA)
"""
import os
import shutil
from unittest.mock import MagicMock
import astropy.units as u
import numpy as np
import pytest
from astropy import units
from astropy.coordinates.sky_coordinate import SkyCoord
from astropy.table import Table
from astropy.units import Quantity
from astroquery.esa.jwst import JwstClass
from astroquery.esa.jwst.tests.DummyTapHandler import DummyTapHandler
from astroquery.ipac.ned import Ned
from astroquery.simbad import Simbad
from astroquery.utils import TableList
from astroquery.utils.tap.conn.tests.DummyConnHandler import DummyConnHandler
from astroquery.utils.tap.conn.tests.DummyResponse import DummyResponse
from astroquery.utils.tap.core import TapPlus
from astroquery.utils.tap.xmlparser import utils
from astroquery.vizier import Vizier
from astroquery.esa.jwst import conf
@pytest.fixture(autouse=True)
@pytest.fixture(autouse=True)
@pytest.fixture(autouse=True)
planeids = "('00000000-0000-0000-879d-ae91fa2f43e2', '00000000-0000-0000-9852-a9fa8c63f7ef')"
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23,
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69,
22,
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1,
628
] | 3.015075 | 398 |
import os
import sys
sys.path.insert(0, os.path.abspath("."))
project = "aizynthfinder"
copyright = "2020-2022, Molecular AI group"
author = "Molecular AI group"
release = "3.3.0"
# This make sure that the cli_help.txt file is properly formated
with open("cli_help.txt", "r") as fileobj:
lines = fileobj.read().splitlines()
with open("cli_help.txt", "w") as fileobj:
fileobj.write(".. code-block::\n\n")
fileobj.write(" " + "\n ".join(lines))
extensions = [
"sphinx.ext.autodoc",
]
autodoc_member_order = "bysource"
autodoc_typehints = "description"
html_theme = "alabaster"
html_theme_options = {
"description": "A fast, robust and flexible software for retrosynthetic planning",
"fixed_sidebar": True,
}
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220,
366,
34021,
62,
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5657,
1298,
6407,
11,
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92,
198
] | 2.632143 | 280 |
import _tkinter
from turtle import Turtle, Screen
import random
tim = Turtle()
tim.shape("turtle")
tim.color("red")
tim.speed("fastest")
# r = random.random()
# b = random.random()
# g = random.random()
# rgb = (random.random(), random.random(), random.random())
draw_spirograph(5)
# for shape_sides_n in range(3, 41):
# draw_shapes(shape_sides_n)
# for walk_steps_n in range(3, 201):
# random_walk(walk_steps_n)
# dashed_line()
# square()
# pentagon()
# hexagon()
# heptagon()
# octagon()
screen = Screen()
screen.exitonclick()
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261,
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198
] | 2.622642 | 212 |
from dataclasses import dataclass, field
from typing import Optional
from transformers import (
TrainingArguments
)
@dataclass
class ModelArguments:
"""
Arguments pertaining to which model/config/tokenizer we are going to fine-tune, or train from scratch.
"""
model_nick: Optional[str] = field(
default=None,
metadata={
"help": "The model Nickname"
},
)
model_name_or_path: Optional[str] = field(
default=None,
metadata={
"help": "The model checkpoint for weights initialization. Leave None if you want to train a model from scratch."
},
)
config_name: Optional[str] = field(
default=None, metadata={"help": "Pretrained config name or path if not the same as model_name"}
)
cache_dir: Optional[str] = field(
default=None, metadata={"help": "Where do you want to store the pretrained models downloaded from s3"}
)
freeze_encoder: Optional[bool] = field(
default=False, metadata={"help" : "Freeze the encoder"}
)
skip_preclassifier: Optional[bool] = field(
default=False, metadata={"help" : "Skip the preclassifier layer"}
)
@dataclass
class TrainingArguments(TrainingArguments):
"""
Arguments pertaining to which model/config/tokenizer we are going to fine-tune, or train from scratch.
"""
ignore_index: Optional[int] = field(
default=0,
metadata={
"help": "Specifies a target value that is ignored and does not contribute to the input gradient"},
)
dropout_rate: Optional[float] = field(
default=0.1,
metadata={
"help": "Dropout for fully-connected layers"},
)
train_jointly: Optional[bool] = field(
default=True,
metadata={
"help": "Dropout for fully-connected layers"},
)
@dataclass
class DataTrainingArguments:
"""
Arguments pertaining to what data we are going to input our model for training and eval.
"""
overwrite_cache: bool = field(
default=False, metadata={"help": "Overwrite the cached training and evaluation sets"}
)
task: Optional[str] = field(
default=None,
metadata={"help": "The name of the task to train"},
)
data_dir: Optional[str] = field(
default='./data',
metadata={"help": "The input data dir"},
)
max_seq_len: Optional[int] = field(
default=50,
metadata={"help": "TBW"},
)
result_dir: Optional[str] = field(
default='./',
metadata={"help": "The result dir"},
)
prediction_dir: Optional[str] = field(
default='./',
metadata={"help": "The prediction dir"},
)
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] | 2.595602 | 1,046 |
from project import motor
from project import variables
# My Blocks
from lower_pen import lower_pen
from lift_pen import lift_pen
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#!/usr/bin/env python
# -*- coding: utf-8 -*-
# Author: BlackXploits
# Telegram: @BlackXploits
# Please don't delete this COPYRIGHT
import argparse
import subprocess
import signal
import Queue
import time
from threading import Thread, Lock
from sys import argv, stdout
from os import getpid, kill
w = '\033[0m'
y = '\033[93m'
r = '\033[31m'
g = '\033[32m'
o = '\033[33m'
b = '\033[34m'
parser = argparse.ArgumentParser(prog='adminfinder', usage='adminfinder [options]')
parser.add_argument('-u', "--url", type=str, help='url eg. target.com')
parser.add_argument("-w", "--wordlist", type=str, help="wordlist")
parser.add_argument('-t', "--threads", type=int, help='number of threads')
parser.add_argument('-p', "--proxy", type=str, help='use proxy eg. socks5:127.0.0.1:9050')
parser.add_argument('-f', "--follow", action="store_true", help='follow and resolve redirects')
parser.add_argument('-b', "--forbidden", action="store_true", help='show forbidden pages')
args = parser.parse_args()
print y+' Admin_Finder_v2.0 '
print b+'''
___ __ _ _______ __
/ | ____/ /___ ___ (_)___ / ____(_)___ ____/ /
/ /| |/ __ / __ `__ \/ / __ \/ /_ / / __ \/ __ /
/ ___ / /_/ / / / / / / / / / / __/ / / / / / /_/ /
/_/ |_\__,_/_/ /_/ /_/_/_/ /_/_/ /_/_/ /_/\__,_/
'''
print r+' c0ded by blackXploits '
print w+''
if len(argv) == 1:
parser.print_help()
exit()
if args.proxy:
try:
import socks, socket
except:
print "Error socksipy module not found, apt-get install python-socksipy to use proxies"
exit()
try:
proxytype = args.proxy.split(":")[0]
proxyip = args.proxy.split(":")[1]
proxyport = args.proxy.split(":")[2]
except:
print "Error proxy must be in the form of type:host:port"
parser.print_help()
exit()
if proxytype == "socks4":
socks.setdefaultproxy(socks.PROXY_TYPE_SOCKS4, str(proxyip), int(proxyport), True)
elif proxytype == "socks5":
socks.setdefaultproxy(socks.PROXY_TYPE_SOCKS5, str(proxyip), int(proxyport), True)
else:
print "Error Unknown proxy type: " + str(proxytype)
exit()
socket.socket = socks.socksocket
socket.create_connection = create_connection
import httplib, httplib2
domain = args.url
url = str(domain.strip())
wordlist = [line.strip() for line in open("wordlist.txt", 'r')]
signal.signal(signal.SIGINT, killpid)
queueLock = Lock()
workQueue = Queue.Queue(len(wordlist))
found = []
threads = []
exitFlag = 0
threadID = 1
maxthreads = 40
if args.threads:
maxthreads = args.threads
queueLock.acquire()
for word in wordlist:
workQueue.put(word)
queueLock.release()
while threadID <= maxthreads:
tname = str("Thread-") + str(threadID)
thread = myThread(threadID, tname, workQueue)
thread.start()
threads.append(thread)
threadID += 1
with Timer():
while not workQueue.empty():
pass
exitFlag = 1
for t in threads:
t.join()
print "\r\x1b[K\n [*] All threads complete, " + str(len(found)) + " sites found."
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] | 2.411529 | 1,249 |
Python 3.8.1 (tags/v3.8.1:1b293b6, Dec 18 2019, 23:11:46) [MSC v.1916 64 bit (AMD64)] on win32
Type "help", "copyright", "credits" or "license()" for more information.
>>>=======30 Days of Code/Day 2/Operators.py ======
12.00
20
8
15
>>>
| [
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] | 2.223214 | 112 |
# Copyright 2018 The TensorFlow Probability 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.
# ============================================================================
"""Tests for distribution_utility functions."""
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import importlib
import itertools
# Dependency imports
import numpy as np
import tensorflow as tf
from tensorflow_probability.python.distributions import Categorical
from tensorflow_probability.python.distributions import Mixture
from tensorflow_probability.python.distributions import MixtureSameFamily
from tensorflow_probability.python.distributions import MultivariateNormalDiag
from tensorflow_probability.python.distributions import Normal
from tensorflow_probability.python.internal import distribution_util
from tensorflow.python.framework import test_util
special = try_import("scipy.special")
def _matrix_diag(d):
"""Batch version of np.diag."""
orig_shape = d.shape
d = np.reshape(d, (int(np.prod(d.shape[:-1])), d.shape[-1]))
diag_list = []
for i in range(d.shape[0]):
diag_list.append(np.diag(d[i, ...]))
return np.reshape(diag_list, orig_shape + (d.shape[-1],))
@test_util.run_all_in_graph_and_eager_modes
# TODO(jvdillon): Merge this test back into:
# tensorflow/python/kernel_tests/softplus_op_test.py
# once TF core is accepting new ops.
@test_util.run_all_in_graph_and_eager_modes
if __name__ == "__main__":
tf.test.main()
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220,
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] | 3.222397 | 634 |
from django.conf.urls import url
from django.contrib.staticfiles import views as static_views
from django.conf.urls.static import static
from django.conf import settings
import jobs.views as views
from django.views.generic import ListView,DetailView
from jobs.models import Job
from rest_framework.urlpatterns import format_suffix_patterns
# urlpatterns = [
# url(r'^$', views.indexJobs, name='indexJobs'),
app_name ='jobs'
# ]
urlpatterns = [
url(r'^$', views.jobsIndex, name='jobsIndex'),
url(r'^jobslist/$', views.JobList.as_view()),
url(r'^(?P<pk>\d+)$',views.job_detail,name='job_detail'),
url(r'^create/$',views.create_job,name='jobsCreate'),
url(r'^(?P<category_slug>[-\w]+)/$', views.jobsIndex, name='jobs_by_category')
]
urlpatterns = format_suffix_patterns(urlpatterns) | [
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] | 2.474926 | 339 |
# Sorts y coordinate first, then x.
if __name__ == "__main__":
main()
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import argparse
import json
import pprint
import pygerduty
import time
import yaml
parser = argparse.ArgumentParser(description="Simple argument parser")
parser.add_argument("-config", type=str, required=False,
help="The location of a file containing a JSON payload.")
parser.add_argument("-payload", type=str, required=False,
help="The location of a file containing a JSON payload.")
parser.add_argument("-d", type=str, required=False,
help="Directory")
parser.add_argument("-e", type=str, required=False,
help="Environment")
parser.add_argument("-id", type=str, required=False,
help="Task id")
args = parser.parse_args()
config = {}
if args.config is not None:
config = yaml.load(open(args.config).read())
pdapi = config['pagerduty_api_key']
pdsvc = config['pagerduty_service_key']
pdsub = config['pagerduty_subdomain']
payload = {}
if args.payload is not None:
payload = json.loads(open(args.payload).read())
# Alert payloads are expected to look like the following:
# {
# "alert_direction": "asc",
# "alert_id": "54c548fc7fae9a32210f5782",
# "alert_trigger": 1,
# "alert_type": "fixed",
# "created_at": "2015-01-25T19:52:39Z",
# "queue_size": 1,
# "source_queue": "example_queue_name"
# }
queue_name = payload['source_queue']
queue_size = payload['queue_size']
desc = 'Queue [%s] is at size [%s]' % (queue_name, queue_size)
pagerduty = pygerduty.PagerDuty(pdsub, api_token=pdapi)
pagerduty.trigger_incident(
pdsvc,
desc,
incident_key=queue_name,
details=payload)
| [
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220,
220,
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8,
198
] | 2.655348 | 589 |
INPUTPATH = "input.txt"
#INPUTPATH = "input-test.txt"
with open(INPUTPATH) as ifile:
raw = ifile.read()
commands = tuple(map(parse_command, raw.strip().split("\n")))
h = d = 0
for word, n in commands:
match word:
case "forward":
h += n
case "down":
d += n
case "up":
d -= n
case _:
raise AssertionError
print(h * d)
h = d = aim = 0
for word, n in commands:
match word:
case "forward":
h += n
d += n * aim
case "down":
aim += n
case "up":
aim -= n
case _:
raise AssertionError
print(h * d)
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5298,
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295,
12331,
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7,
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288,
8,
198
] | 1.859504 | 363 |
#!/usr/bin/env python3
| [
2,
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14629,
14,
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14,
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21015,
18,
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] | 2.3 | 10 |
import pytest
from detect_secrets.core.usage import ParserBuilder
@pytest.fixture
| [
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] | 3.107143 | 28 |
# !/usr/bin/python3
# David Arboledas Brihuega
# November 2021
#
# ------------------------------------------------------
# This script is called by extractForensicJPEG to get
# all the forensic data embebed in the jpeg files
# --------------------------------------------------------
# import sys
import binascii
import re
import hashlib
import verifyIMEI
from Crypto.Hash import MD5
from Crypto.PublicKey import RSA
from Crypto.Signature import PKCS1_v1_5
TRAILER_EOF = "ffd9"
BIN_TRAILER_NUMBER = binascii.unhexlify(TRAILER_EOF)
IMEI_LENGTH = 15
HASH_LENGTH = 32
#FORENSIC_DATA_LENGTH = IMEI_LENGTH + HASH_LENGTH + RSA_hex_length()
primaryPics = []
# Reading forensic info from file
| [
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628,
198,
2,
11725,
23953,
7508,
422,
2393,
628,
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] | 3.008547 | 234 |
# Generated by Django 3.0.7 on 2021-04-08 09:51
from django.db import migrations, models
| [
2,
2980,
515,
416,
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] | 2.84375 | 32 |
import subprocess
from functools import reduce
| [
11748,
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1257,
310,
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1330,
4646,
628,
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] | 4.083333 | 12 |
#!/usr/bin/env python
# -*- coding: utf-8 -*-
# Copyright 2014, Deutsche Telekom AG - Laboratories (T-Labs)
#
# 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 logging
import importlib
import datetime
from django.conf import settings
from django.db import models
from django.db import transaction
from django.db.models.signals import post_save
from django.core.exceptions import ValidationError
from django.contrib.contenttypes.models import ContentType
from django.contrib.contenttypes.fields import GenericForeignKey
from django.template.defaultfilters import slugify
from model_utils import Choices
from model_utils.fields import StatusField
from model_utils.models import TimeStampedModel
from model_utils.managers import InheritanceManager, QueryManager
from litedesk.lib.active_directory.session import Session
from litedesk.lib.active_directory.classes.base import Company, User as ActiveDirectoryUser
from audit.models import Trackable, UntrackableChangeError
from audit.signals import pre_trackable_model_delete
from syncremote.models import Synchronizable
import tasks
log = logging.getLogger(__name__)
if not hasattr(settings, 'PROVISIONABLE_SERVICES'):
settings.PROVISIONABLE_SERVICES = []
# Signals
post_save.connect(TenantService.on_user_creation, dispatch_uid='user_add', sender=User)
pre_trackable_model_delete.connect(User.on_removal, dispatch_uid='user_delete', sender=User)
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] | 3.552876 | 539 |
"""
RabbitMQ container definition.
"""
from seaworthy.definitions import ContainerDefinition
from seaworthy.utils import output_lines
class RabbitMQContainer(ContainerDefinition):
"""
RabbitMQ container definition.
.. todo::
Write more docs.
"""
# There seems to be a weird interaction between the erlang runtime and
# something in docker which results in annoyingly long startup times in
# some environments. The best we can do to deal with that is to give it a
# bit more time to get going. :-(
WAIT_TIMEOUT = 30.0
DEFAULT_NAME = 'rabbitmq'
DEFAULT_IMAGE = 'rabbitmq:alpine'
DEFAULT_WAIT_PATTERNS = (r'Server startup complete',)
DEFAULT_VHOST = '/vhost'
DEFAULT_USER = 'user'
DEFAULT_PASSWORD = 'password'
def __init__(self,
name=DEFAULT_NAME,
image=DEFAULT_IMAGE,
wait_patterns=DEFAULT_WAIT_PATTERNS,
vhost=DEFAULT_VHOST,
user=DEFAULT_USER,
password=DEFAULT_PASSWORD,
**kwargs):
"""
:param vhost: the name of a vhost to create at startup
:param user: the name of a user to create at startup
:param password: the password for the user
"""
super().__init__(name, image, wait_patterns, **kwargs)
self.vhost = vhost
self.user = user
self.password = password
def wait_for_start(self):
"""
Wait for the RabbitMQ process to be come up.
"""
er = self.exec_rabbitmqctl(
'wait', ['--pid', '1', '--timeout', str(int(self.wait_timeout))])
output_lines(er, error_exc=TimeoutError)
def base_kwargs(self):
"""
Add a ``tmpfs`` entry for ``/var/lib/rabbitmq`` to avoid unnecessary
disk I/O and ``environment`` entries for the configured vhost and user
creds.
"""
return {
'environment': {
'RABBITMQ_DEFAULT_VHOST': self.vhost,
'RABBITMQ_DEFAULT_USER': self.user,
'RABBITMQ_DEFAULT_PASS': self.password,
},
'tmpfs': {'/var/lib/rabbitmq': 'uid=100,gid=101'},
}
def clean(self):
"""
Remove all data by using ``rabbitmqctl`` to eval
``rabbit_mnesia:reset()``.
"""
reset_erl = 'rabbit:stop(), rabbit_mnesia:reset(), rabbit:start().'
self.exec_rabbitmqctl('eval', [reset_erl])
def exec_rabbitmqctl(self, command, args=[], rabbitmqctl_opts=['-q']):
"""
Execute a ``rabbitmqctl`` command inside a running container.
:param command: the command to run
:param args: a list of args for the command
:param rabbitmqctl_opts:
a list of extra options to pass to ``rabbitmqctl``
:returns: a tuple of the command exit code and output
"""
cmd = ['rabbitmqctl'] + rabbitmqctl_opts + [command] + args
return self.inner().exec_run(cmd)
def exec_rabbitmqctl_list(self, resources, args=[],
rabbitmq_opts=['-q', '--no-table-headers']):
"""
Execute a ``rabbitmqctl`` command to list the given resources.
:param resources: the resources to list, e.g. ``'vhosts'``
:param args: a list of args for the command
:param rabbitmqctl_opts:
a list of extra options to pass to ``rabbitmqctl``
:returns: a tuple of the command exit code and output
"""
command = 'list_{}'.format(resources)
return self.exec_rabbitmqctl(command, args, rabbitmq_opts)
def list_vhosts(self):
"""
Run the ``list_vhosts`` command and return a list of vhost names.
"""
return output_lines(self.exec_rabbitmqctl_list('vhosts'))
def list_queues(self):
"""
Run the ``list_queues`` command (for the default vhost) and return a
list of tuples describing the queues.
:return:
A list of 2-element tuples. The first element is the queue name,
the second is the current queue size.
"""
lines = output_lines(
self.exec_rabbitmqctl_list('queues', ['-p', self.vhost]))
return [tuple(line.split(None, 1)) for line in lines]
def list_users(self):
"""
Run the ``list_users`` command and return a list of tuples describing
the users.
:return:
A list of 2-element tuples. The first element is the username, the
second a list of tags for the user.
"""
lines = output_lines(self.exec_rabbitmqctl_list('users'))
return [_parse_rabbitmq_user(line) for line in lines]
def broker_url(self):
""" Returns a "broker URL" for use with Celery. """
return 'amqp://{}:{}@{}/{}'.format(
self.user, self.password, self.name, self.vhost)
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] | 2.23468 | 2,203 |
# -*- coding: utf-8 -*-
'''
gds.burp.api
~~~~~~~~~~~~
This module implements the Jython Burp Plugin API.
Plugins written in Jython can implement the interfaces in this
package in order to register for various methods exposed by
Burp Extender.
'''
from .core import Interface
__all__ = [
'INewScanIssueHandler',
'IExtenderRequestHandler',
'IExtenderResponseHandler',
'IIntruderRequestHandler',
'IIntruderResponseHandler',
'IProxyRequestHandler',
'IProxyResponseHandler',
'IRepeaterRequestHandler',
'IRepeaterResponseHandler',
'IScannerRequestHandler',
'IScannerResponseHandler',
'ISequencerRequestHandler',
'ISequencerResponseHandler',
'ISpiderRequestHandler',
'ISpiderResponseHandler',
'ITargetRequestHandler',
'ITargetResponseHandler',
]
class INewScanIssueHandler(Interface):
'''
Extension point interface for components to perform actions
whenever Burp Scanner discovers a new, unique issue.
Classes that implement this interface must implement the
:meth:`newScanIssue` method.
'''
def newScanIssue(issue):
'''
This method is invoked whenever Burp Scanner discovers a new,
unique issue, and can be used to perform customised reporting
or logging of issues.
:param issue: An :class:`burp.IScanIssue <IScanIssue>` object.
'''
class IExtenderRequestHandler(Interface):
'''
Extension point interface for components to perform actions on
a request before Burp Extender sends it on the wire.
Classes that implement this interface must implement the
:meth:`processRequest` method.
'''
def processRequest(request):
'''
This method is invoked before Burp Extender sends a request
on the wire.
:param request: An :class:`HttpRequest <HttpRequest>` object.
'''
class IExtenderResponseHandler(Interface):
'''
Extension point interface for components to perform actions on
a response after Burp Extender receives it off the wire.
Classes that implement this interface must implement the
:meth:`processResponse` method.
'''
def processResponse(request):
'''
This method is invoked after Burp Extender receives a response
off the wire.
:param request: An :class:`HttpRequest <HttpRequest>` object.
'''
class IIntruderRequestHandler(Interface):
'''
Extension point interface for components to perform actions on
a request before Burp Intruder sends it on the wire.
Classes that implement this interface must implement the
:meth:`processRequest` method.
'''
def processRequest(request):
'''
This method is invoked before Burp Intruder sends a request
on the wire.
:param request: An :class:`HttpRequest <HttpRequest>` object.
'''
class IIntruderResponseHandler(Interface):
'''
Extension point interface for components to perform actions on
a response after Burp Intruder receives it off the wire.
Classes that implement this interface must implement the
:meth:`processResponse` method.
'''
def processResponse(request):
'''
This method is invoked after Burp Intruder receives a response
off the wire.
:param request: An :class:`HttpRequest <HttpRequest>` object.
'''
class IProxyRequestHandler(Interface):
'''
Extension point interface for components to perform actions on
a request before Burp Proxy sends it on the wire.
Classes that implement this interface must implement the
:meth:`processRequest` method.
'''
def processRequest(request):
'''
This method is invoked before Burp Proxy sends a request
on the wire.
:param request: An :class:`HttpRequest <HttpRequest>` object.
'''
class IProxyResponseHandler(Interface):
'''
Extension point interface for components to perform actions on
a response after Burp Proxy receives it off the wire.
Classes that implement this interface must implement the
:meth:`processResponse` method.
'''
def processResponse(request):
'''
This method is invoked after Burp proxy receives a response
off the wire.
:param request: An :class:`HttpRequest <HttpRequest>` object.
'''
class IRepeaterRequestHandler(Interface):
'''
Extension point interface for components to perform actions on
a request before Burp Repeater sends it on the wire.
Classes that implement this interface must implement the
:meth:`processRequest` method.
'''
def processRequest(request):
'''
This method is invoked before Burp Repeater sends a request
on the wire.
:param request: An :class:`HttpRequest <HttpRequest>` object.
'''
class IRepeaterResponseHandler(Interface):
'''
Extension point interface for components to perform actions on
a response after Burp Repeater receives it off the wire.
Classes that implement this interface must implement the
:meth:`processResponse` method.
'''
def processResponse(request):
'''
This method is invoked after Burp Repeater receives a response
off the wire.
:param request: An :class:`HttpRequest <HttpRequest>` object.
'''
class IScannerRequestHandler(Interface):
'''
Extension point interface for components to perform actions on
a request before Burp Scanner sends it on the wire.
Classes that implement this interface must implement the
:meth:`processRequest` method.
'''
def processRequest(request):
'''
This method is invoked before Burp Scanner sends a request
on the wire.
:param request: An :class:`HttpRequest <HttpRequest>` object.
'''
class IScannerResponseHandler(Interface):
'''
Extension point interface for components to perform actions on
a response after Burp Scanner receives it off the wire.
Classes that implement this interface must implement the
:meth:`processResponse` method.
'''
def processResponse(request):
'''
This method is invoked after Burp Scanner receives a response
off the wire.
:param request: An :class:`HttpRequest <HttpRequest>` object.
'''
class ISequencerRequestHandler(Interface):
'''
Extension point interface for components to perform actions on
a request before Burp Sequencer sends it on the wire.
Classes that implement this interface must implement the
:meth:`processRequest` method.
'''
def processRequest(request):
'''
This method is invoked before Burp Sequencer sends a request
on the wire.
:param request: An :class:`HttpRequest <HttpRequest>` object.
'''
class ISequencerResponseHandler(Interface):
'''
Extension point interface for components to perform actions on
a response after Burp Sequencer receives it off the wire.
Classes that implement this interface must implement the
:meth:`processResponse` method.
'''
def processResponse(request):
'''
This method is invoked after Burp Sequencer receives a response
off the wire.
:param request: An :class:`HttpRequest <HttpRequest>` object.
'''
class ISpiderRequestHandler(Interface):
'''
Extension point interface for components to perform actions on
a request before Burp Spider sends it on the wire.
Classes that implement this interface must implement the
:meth:`processRequest` method.
'''
def processRequest(request):
'''
This method is invoked before Burp Spider sends a request
on the wire.
:param request: An :class:`HttpRequest <HttpRequest>` object.
'''
class ISpiderResponseHandler(Interface):
'''
Extension point interface for components to perform actions on
a response after Burp Spider receives it off the wire.
Classes that implement this interface must implement the
:meth:`processResponse` method.
'''
def processResponse(request):
'''
This method is invoked after Burp Spider receives a response
off the wire.
:param request: An :class:`HttpRequest <HttpRequest>` object.
'''
class ITargetRequestHandler(Interface):
'''
Extension point interface for components to perform actions on
a request before Burp Target sends it on the wire.
Classes that implement this interface must implement the
:meth:`processRequest` method.
'''
def processRequest(request):
'''
This method is invoked before Burp Target sends a request
on the wire.
:param request: An :class:`HttpRequest <HttpRequest>` object.
'''
class ITargetResponseHandler(Interface):
'''
Extension point interface for components to perform actions on
a response after Burp Target receives it off the wire.
Classes that implement this interface must implement the
:meth:`processResponse` method.
'''
def processResponse(request):
'''
This method is invoked after Burp Target receives a response
off the wire.
:param request: An :class:`HttpRequest <HttpRequest>` object.
'''
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] | 3.00543 | 3,131 |
from SinGAN.training import train
from SinGAN.util import read_image, adjust_scales_to_image
| [
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1462,
62,
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] | 3.129032 | 31 |
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