code stringlengths 2k 1.04M | repo_path stringlengths 5 517 | parsed_code stringlengths 0 1.04M | quality_prob float64 0.02 0.95 | learning_prob float64 0.02 0.93 |
|---|---|---|---|---|
import math
from QuadropodServos import ServoInstructions
a0 = 1 #shoulder arm length
a1 = 5 #upper uarm length
a2 = 5 #lower arm/end effetor length
def evaluator(a1,a2,x,y): # inverse kinematic equations
if y == 0:
y = 0.001
if x == 0:
x = 0.001
x1 = 0
if x < 0:
x1 = x
... | QuadropodInverseKinematics.py | import math
from QuadropodServos import ServoInstructions
a0 = 1 #shoulder arm length
a1 = 5 #upper uarm length
a2 = 5 #lower arm/end effetor length
def evaluator(a1,a2,x,y): # inverse kinematic equations
if y == 0:
y = 0.001
if x == 0:
x = 0.001
x1 = 0
if x < 0:
x1 = x
... | 0.467575 | 0.654243 |
import json
import tarfile
import time
import os
import shutil
import sys
import re
from subprocess import Popen, PIPE
from params import Params
from err import ValidationException
class DatasetHandler:
"""
This is a generic VEuPathDB handler tool for use with the user dataset
import process.
It is a... | handler_base/dataset_handler.py | import json
import tarfile
import time
import os
import shutil
import sys
import re
from subprocess import Popen, PIPE
from params import Params
from err import ValidationException
class DatasetHandler:
"""
This is a generic VEuPathDB handler tool for use with the user dataset
import process.
It is a... | 0.551332 | 0.315222 |
import pytest
from mock import patch
from uds.can.consecutive_frame import CanConsecutiveFrameHandler, \
InconsistentArgumentsError, CanDlcHandler, DEFAULT_FILLER_BYTE
from uds.can import CanAddressingFormat
class TestCanConsecutiveFrameHandler:
"""Unit tests for `CanConsecutiveFrameHandler` class."""
S... | tests/software_tests/can/test_consecutive_frame.py | import pytest
from mock import patch
from uds.can.consecutive_frame import CanConsecutiveFrameHandler, \
InconsistentArgumentsError, CanDlcHandler, DEFAULT_FILLER_BYTE
from uds.can import CanAddressingFormat
class TestCanConsecutiveFrameHandler:
"""Unit tests for `CanConsecutiveFrameHandler` class."""
S... | 0.715821 | 0.222912 |
import pandas as pd
import numpy as np
from PIL import Image
import pandas as pd
from torch.utils.data import Dataset
import os
from data.check_type_image import is_image_file
class FASDataset(Dataset):
def __init__(self, root_dir, csv_file, map_size=7, transform=None, smoothing=True):
super(FASDataset, se... | Trainer/data/dataset.py | import pandas as pd
import numpy as np
from PIL import Image
import pandas as pd
from torch.utils.data import Dataset
import os
from data.check_type_image import is_image_file
class FASDataset(Dataset):
def __init__(self, root_dir, csv_file, map_size=7, transform=None, smoothing=True):
super(FASDataset, se... | 0.458591 | 0.220091 |
import torch
import matplotlib.pyplot as plt
import numpy as np
def soft_update(target, source, tau):
for target_param, param in zip(target.parameters(), source.parameters()):
target_param.data.copy_(target_param.data * (1.0 - tau) + param.data * tau)
def hard_update(target, source):
for target_par... | utilities/utilities.py |
import torch
import matplotlib.pyplot as plt
import numpy as np
def soft_update(target, source, tau):
for target_param, param in zip(target.parameters(), source.parameters()):
target_param.data.copy_(target_param.data * (1.0 - tau) + param.data * tau)
def hard_update(target, source):
for target_par... | 0.751922 | 0.51129 |
import numpy as np
from sklearn.preprocessing import (
MaxAbsScaler,
MinMaxScaler,
RobustScaler,
StandardScaler,
)
from tasrif.processing_pipeline import ProcessingOperator
class NormalizeOperator(ProcessingOperator):
"""
Normalizes the values for the supplied feature_names using the specifi... | tasrif/processing_pipeline/custom/normalize_operator.py | import numpy as np
from sklearn.preprocessing import (
MaxAbsScaler,
MinMaxScaler,
RobustScaler,
StandardScaler,
)
from tasrif.processing_pipeline import ProcessingOperator
class NormalizeOperator(ProcessingOperator):
"""
Normalizes the values for the supplied feature_names using the specifi... | 0.891073 | 0.730146 |
from sys import modules
import os
import psycopg2
class Db():
'''Handles all database functions'''
def __init__(self):
self.conn = None
def create_connection(self):
'''Creates connection for the app to database'''
try:
if 'pytest' in modules:
url = os.g... | app/v1/models/migrate.py | from sys import modules
import os
import psycopg2
class Db():
'''Handles all database functions'''
def __init__(self):
self.conn = None
def create_connection(self):
'''Creates connection for the app to database'''
try:
if 'pytest' in modules:
url = os.g... | 0.180467 | 0.085404 |
from daydayup_layer import GCN, My_APPNP, Cheb_Net, ARMA_Net, GAT_Net, SGC_Net, TAG_Net, DNA_Net
import torch
import torch.nn.functional as F
import lightgbm as lgb
from torch_geometric.nn import GCNConv, Node2Vec
from torch.nn import PReLU
from sklearn.linear_model import LogisticRegression
from torch.utils.da... | daydayup_submit/daydayup_model.py | from daydayup_layer import GCN, My_APPNP, Cheb_Net, ARMA_Net, GAT_Net, SGC_Net, TAG_Net, DNA_Net
import torch
import torch.nn.functional as F
import lightgbm as lgb
from torch_geometric.nn import GCNConv, Node2Vec
from torch.nn import PReLU
from sklearn.linear_model import LogisticRegression
from torch.utils.da... | 0.806472 | 0.254894 |
#Internal Modules (Lazy Importer)--------------------------------------------------------------------
#Internal Modules (Lazy Importer) End----------------------------------------------------------------
#External Modules------------------------------------------------------------------------------------
from numpy im... | framework/SupervisedLearning/ScikitLearn/LinearModel/RidgeClassifier.py | #Internal Modules (Lazy Importer)--------------------------------------------------------------------
#Internal Modules (Lazy Importer) End----------------------------------------------------------------
#External Modules------------------------------------------------------------------------------------
from numpy im... | 0.838713 | 0.436142 |
from environment import *
from pg import *
import pickle as pl
np.seterr(all='raise')
params = {'lane_width': 4,
'num_scenarios': 1000,
'pos_var': 0.3,
'num_episodes': 6,
'num_trainings_after_simulation': 10,
'num_iterations': 1000,
'num_nds': 10,
... | test_pg.py | from environment import *
from pg import *
import pickle as pl
np.seterr(all='raise')
params = {'lane_width': 4,
'num_scenarios': 1000,
'pos_var': 0.3,
'num_episodes': 6,
'num_trainings_after_simulation': 10,
'num_iterations': 1000,
'num_nds': 10,
... | 0.376279 | 0.223812 |
from archivekit.package import Package
from archivekit.ingest import Ingestor
class Collection(object):
""" The list of all packages with an existing manifest which exist in
the given storage """
def __init__(self, name, store):
self.name = name
self.store = store
def create(self, id... | archivekit/collection.py | from archivekit.package import Package
from archivekit.ingest import Ingestor
class Collection(object):
""" The list of all packages with an existing manifest which exist in
the given storage """
def __init__(self, name, store):
self.name = name
self.store = store
def create(self, id... | 0.765287 | 0.228479 |
import multiprocessing as mp
import uuid
from pystrand.populations import BasePopulation
from pystrand.selections import RouletteSelection, ElitismSelection, BaseSelection
from pystrand.mutations import BaseMutation, PointMutation
from pystrand.loggers.csv_logger import CsvLogger
from pystrand.loggers.details import R... | pystrand/optimizers.py | import multiprocessing as mp
import uuid
from pystrand.populations import BasePopulation
from pystrand.selections import RouletteSelection, ElitismSelection, BaseSelection
from pystrand.mutations import BaseMutation, PointMutation
from pystrand.loggers.csv_logger import CsvLogger
from pystrand.loggers.details import R... | 0.780328 | 0.297585 |
import logging
import yfinance as yf
from src.helper import create_logger, dump_file
from src.hedging.division import Division
import datetime
logger = create_logger('Caller', 'logs/Hedging.log',
logging.DEBUG, logging.WARNING)
class Caller(Division):
"""Caller class that inherits the pro... | src/hedging/caller.py | import logging
import yfinance as yf
from src.helper import create_logger, dump_file
from src.hedging.division import Division
import datetime
logger = create_logger('Caller', 'logs/Hedging.log',
logging.DEBUG, logging.WARNING)
class Caller(Division):
"""Caller class that inherits the pro... | 0.724773 | 0.332554 |
from rdkit.Chem import AllChem
from retrobiocat_web.retro.visualisation import rdkit_images
def add_substrate_info(nodes, graph):
for i, node_dict in enumerate(nodes):
node = nodes[i]['id']
if graph.nodes[node]['attributes']['node_type'] == 'substrate':
info = str(node) + '<br>'
... | retrobiocat_web/retro/visualisation/node_information.py | from rdkit.Chem import AllChem
from retrobiocat_web.retro.visualisation import rdkit_images
def add_substrate_info(nodes, graph):
for i, node_dict in enumerate(nodes):
node = nodes[i]['id']
if graph.nodes[node]['attributes']['node_type'] == 'substrate':
info = str(node) + '<br>'
... | 0.311532 | 0.274442 |
import sys
from PyQt5.QtWidgets import QApplication, \
QWidget, QPushButton, QAction, QLineEdit, \
QMessageBox, QMainWindow, QHBoxLayout, QDialog, \
QVBoxLayout, QGridLayout, QGroupBox, QFormLayout, QRadioButton, QMenu, QMenuBar, \
QTreeWidget, QTreeWidgetItem, QTextEdit, QFrame, QTabWidget, QLabe... | python/Qt/41.tree_tab.py | import sys
from PyQt5.QtWidgets import QApplication, \
QWidget, QPushButton, QAction, QLineEdit, \
QMessageBox, QMainWindow, QHBoxLayout, QDialog, \
QVBoxLayout, QGridLayout, QGroupBox, QFormLayout, QRadioButton, QMenu, QMenuBar, \
QTreeWidget, QTreeWidgetItem, QTextEdit, QFrame, QTabWidget, QLabe... | 0.190536 | 0.080177 |
import tensorflow as tf
import random
from .common import *
from tensorflow.contrib.layers import *
import sys
l2_reg = 0.001
learning_rate = 0.0001
num_epoches = 500
num_batches = 500
batch_size = 40
display_step = 10
max_delete = 10
max_y_length = max_delete
def create_batch(gold, batch_size):
ret_x = []
r... | gold_cat/cat_gen.py | import tensorflow as tf
import random
from .common import *
from tensorflow.contrib.layers import *
import sys
l2_reg = 0.001
learning_rate = 0.0001
num_epoches = 500
num_batches = 500
batch_size = 40
display_step = 10
max_delete = 10
max_y_length = max_delete
def create_batch(gold, batch_size):
ret_x = []
r... | 0.433981 | 0.206614 |
import uuid
from os import urandom
from cryptography.hazmat.backends import default_backend
from cryptography.hazmat.primitives.asymmetric.padding import (
OAEP,
MGF1,
)
from cryptography.hazmat.primitives.asymmetric.rsa import generate_private_key
from cryptography.hazmat.primitives.hashes import SHA1
from cr... | samples/queue/encryption_usage.py | import uuid
from os import urandom
from cryptography.hazmat.backends import default_backend
from cryptography.hazmat.primitives.asymmetric.padding import (
OAEP,
MGF1,
)
from cryptography.hazmat.primitives.asymmetric.rsa import generate_private_key
from cryptography.hazmat.primitives.hashes import SHA1
from cr... | 0.68721 | 0.103115 |
from django.db import models
from django.utils.translation import ugettext as _
class Region(models.Model):
region_id = models.PositiveSmallIntegerField(
_('Region id'),
db_column='RegionID',
primary_key=True
)
region_description = models.CharField(
_('Region description'),... | northwind/models.py | from django.db import models
from django.utils.translation import ugettext as _
class Region(models.Model):
region_id = models.PositiveSmallIntegerField(
_('Region id'),
db_column='RegionID',
primary_key=True
)
region_description = models.CharField(
_('Region description'),... | 0.505371 | 0.150559 |
import requests
from constants import USER_AGENT
from ScriptResult import EXECUTION_STATE_COMPLETED, EXECUTION_STATE_FAILED
from SiemplifyAction import SiemplifyAction
from SiemplifyUtils import convert_dict_to_json_result_dict, output_handler
INTEGRATION_NAME = "GreyNoise"
SCRIPT_NAME = "Execute GNQL Query"
@outpu... | ActionsScripts/Execute GNQL Query.py | import requests
from constants import USER_AGENT
from ScriptResult import EXECUTION_STATE_COMPLETED, EXECUTION_STATE_FAILED
from SiemplifyAction import SiemplifyAction
from SiemplifyUtils import convert_dict_to_json_result_dict, output_handler
INTEGRATION_NAME = "GreyNoise"
SCRIPT_NAME = "Execute GNQL Query"
@outpu... | 0.461502 | 0.137764 |
import glob, json, os, base64, svgwrite, collections
from PIL import Image
DPI = 72
SKIP_NO_TABLE_PAGES = True
tables_info = collections.defaultdict(list)
for pdffig_res_file in glob.glob('/notebook/data/1_pdffigures2_out/*.json'):
file_id = os.path.splitext(os.path.basename(pdffig_res_file))[0]
with open(pd... | make_training_data.py |
import glob, json, os, base64, svgwrite, collections
from PIL import Image
DPI = 72
SKIP_NO_TABLE_PAGES = True
tables_info = collections.defaultdict(list)
for pdffig_res_file in glob.glob('/notebook/data/1_pdffigures2_out/*.json'):
file_id = os.path.splitext(os.path.basename(pdffig_res_file))[0]
with open(pd... | 0.244363 | 0.091139 |
import pygame
def draw_number(n, font, color, screen, position):
if n == 0:
n = ''
surface = font.render(str(n), True, color)
screen.blit(surface, position)
def draw_board(board, screen, font, tile_size, selected_tile, background_color, tile_color, font_color, selected_tile_color, locked_tile_co... | gui.py | import pygame
def draw_number(n, font, color, screen, position):
if n == 0:
n = ''
surface = font.render(str(n), True, color)
screen.blit(surface, position)
def draw_board(board, screen, font, tile_size, selected_tile, background_color, tile_color, font_color, selected_tile_color, locked_tile_co... | 0.135976 | 0.383295 |
import numpy as np
PARAM_NUM = 6
class Quintic(object):
@staticmethod
def station_vec(t, t0):
return np.array([[1, (t-t0), (t-t0)**2, (t-t0)**3, (t-t0)**4, (t-t0)**5]])
@staticmethod
def velocity_vec(t, t0):
return np.array([[0, 1, 2*(t-t0), 3*(t-t0)**2, 4*(t-t0)**3, 5*(t-t0)**4]])
@staticmethod
def accelera... | carla_utils/trajectory/functions/quintic.py | import numpy as np
PARAM_NUM = 6
class Quintic(object):
@staticmethod
def station_vec(t, t0):
return np.array([[1, (t-t0), (t-t0)**2, (t-t0)**3, (t-t0)**4, (t-t0)**5]])
@staticmethod
def velocity_vec(t, t0):
return np.array([[0, 1, 2*(t-t0), 3*(t-t0)**2, 4*(t-t0)**3, 5*(t-t0)**4]])
@staticmethod
def accelera... | 0.200323 | 0.650245 |
import tkinter as tk
import os, sys, time, ctypes
from scipy.special import gamma
from mathgraph3D.core.global_imports import *
from mathgraph3D.core.Color import ColorStyle, Styles, Gradient, preset_styles, random_color
from mathgraph3D.core.functions.CartesianFunctions import Function2D, Function3D
from mathgraph3D.c... | __main__.py | import tkinter as tk
import os, sys, time, ctypes
from scipy.special import gamma
from mathgraph3D.core.global_imports import *
from mathgraph3D.core.Color import ColorStyle, Styles, Gradient, preset_styles, random_color
from mathgraph3D.core.functions.CartesianFunctions import Function2D, Function3D
from mathgraph3D.c... | 0.328745 | 0.347205 |
import tensorflow.keras as keras
import numpy as np
import pysyrenn
def keras_to_syrenn(model):
"""Converts a sequential Keras model to a SyReNN Network.
Note that this conversion code makes a number of not-always-valid
assumptions about the model; you should *always* manually verify that the
returned... | scripts/keras_to_syrenn.py | import tensorflow.keras as keras
import numpy as np
import pysyrenn
def keras_to_syrenn(model):
"""Converts a sequential Keras model to a SyReNN Network.
Note that this conversion code makes a number of not-always-valid
assumptions about the model; you should *always* manually verify that the
returned... | 0.886039 | 0.582402 |
import pprint
import re # noqa: F401
import six
class Opens(object):
"""NOTE: This class is auto generated by the swagger code generator program.
Do not edit the class manually.
"""
"""
Attributes:
swagger_types (dict): The key is attribute name
and the value ... | mailchimp_marketing_asyncio/models/opens.py | import pprint
import re # noqa: F401
import six
class Opens(object):
"""NOTE: This class is auto generated by the swagger code generator program.
Do not edit the class manually.
"""
"""
Attributes:
swagger_types (dict): The key is attribute name
and the value ... | 0.760295 | 0.15006 |
from collections import defaultdict
from utils.solution_base import SolutionBase
class Solution(SolutionBase):
def solve(self, part_num: int):
self.test_runner(part_num)
func = getattr(self, f"part{part_num}")
result = func(self.data)
return result
def test_runner(self, part_... | solutions/day08.py | from collections import defaultdict
from utils.solution_base import SolutionBase
class Solution(SolutionBase):
def solve(self, part_num: int):
self.test_runner(part_num)
func = getattr(self, f"part{part_num}")
result = func(self.data)
return result
def test_runner(self, part_... | 0.476092 | 0.488649 |
from django.test import TestCase
from django.contrib.auth import get_user_model
from django.urls import reverse
from rest_framework import status
from rest_framework.test import APIClient
CREATE_USER_URL = reverse('user:create')
USER_TOKEN_URL = reverse('user:token')
ME_URL = reverse('user:me')
def create_user(**p... | app/user/tests/test_user_api.py | from django.test import TestCase
from django.contrib.auth import get_user_model
from django.urls import reverse
from rest_framework import status
from rest_framework.test import APIClient
CREATE_USER_URL = reverse('user:create')
USER_TOKEN_URL = reverse('user:token')
ME_URL = reverse('user:me')
def create_user(**p... | 0.500732 | 0.263129 |
from __future__ import print_function
import os
from datetime import datetime
from authcode import utils
from authcode._compat import text_type
from sqlalchemy_wrapper import SQLAlchemy
import authcode
import pytest
from helpers import SECRET_KEY
class User(object):
id = 3
password = '<PASSWORD>'
last_... | tests/test_utils.py | from __future__ import print_function
import os
from datetime import datetime
from authcode import utils
from authcode._compat import text_type
from sqlalchemy_wrapper import SQLAlchemy
import authcode
import pytest
from helpers import SECRET_KEY
class User(object):
id = 3
password = '<PASSWORD>'
last_... | 0.54819 | 0.296706 |
import sys, os
import numpy as np
import struct
import stl
from stl import mesh
import datetime
import pickle
input_filename = "fibers.bin"
include_boundary = True
if len(sys.argv) >= 2:
input_filename = sys.argv[1]
print("\nEvaluate the quality of the generated mesh by computing variances of relative element len... | scripts/mesh_evaluate_quality.py |
import sys, os
import numpy as np
import struct
import stl
from stl import mesh
import datetime
import pickle
input_filename = "fibers.bin"
include_boundary = True
if len(sys.argv) >= 2:
input_filename = sys.argv[1]
print("\nEvaluate the quality of the generated mesh by computing variances of relative element len... | 0.213787 | 0.182808 |
from __future__ import annotations
import typing
import dataclasses
import enum
import datetime as dt
import pycamunda
import pycamunda.base
import pycamunda.resource
from pycamunda.request import QueryParameter, PathParameter, BodyParameter
URL_SUFFIX = '/auth'
__all__ = ['AuthorizationType', 'GetList', 'Count', '... | pycamunda/auth.py | from __future__ import annotations
import typing
import dataclasses
import enum
import datetime as dt
import pycamunda
import pycamunda.base
import pycamunda.resource
from pycamunda.request import QueryParameter, PathParameter, BodyParameter
URL_SUFFIX = '/auth'
__all__ = ['AuthorizationType', 'GetList', 'Count', '... | 0.830044 | 0.148757 |
from io import BytesIO
import numpy as np
from PIL import Image
import tensorflow as tf
_BINARISED_MNIST_TR = 'http://www.cs.toronto.edu/~larocheh/public/datasets/binarized_mnist/binarized_mnist_train.amat'
_BINARISED_MNIST_TEST = 'http://www.cs.toronto.edu/~larocheh/public/datasets/binarized_mnist/binarized_mnist_tes... | applications/tensorflow/contrastive_divergence_vae/utils/data_utils.py | from io import BytesIO
import numpy as np
from PIL import Image
import tensorflow as tf
_BINARISED_MNIST_TR = 'http://www.cs.toronto.edu/~larocheh/public/datasets/binarized_mnist/binarized_mnist_train.amat'
_BINARISED_MNIST_TEST = 'http://www.cs.toronto.edu/~larocheh/public/datasets/binarized_mnist/binarized_mnist_tes... | 0.900355 | 0.724273 |
# In[77]:
import pandas as pd
import numpy as np
import requests
from datetime import datetime
from urllib.request import urlopen
from lxml import etree
import io
from alphacast import Alphacast
from dotenv import dotenv_values
API_KEY = dotenv_values(".env").get("API_KEY")
alphacast = Alphacast(API_KEY)
# In[78]:... | 0688.Activity-Argentina-GCBA-Electric_Power_Generation.py |
# In[77]:
import pandas as pd
import numpy as np
import requests
from datetime import datetime
from urllib.request import urlopen
from lxml import etree
import io
from alphacast import Alphacast
from dotenv import dotenv_values
API_KEY = dotenv_values(".env").get("API_KEY")
alphacast = Alphacast(API_KEY)
# In[78]:... | 0.328206 | 0.185689 |
# https://docs.djangoproject.com/en/3.2/ref/contrib/admin/
# https://docs.djangoproject.com/en/3.2/topics/auth/customizing/#extending-the-existing-user-model
# Django
from django.contrib import admin
from django.contrib.auth.admin import UserAdmin as BaseUserAdmin
# Models
from django.contrib.auth.models import Use... | users/admin.py | # https://docs.djangoproject.com/en/3.2/ref/contrib/admin/
# https://docs.djangoproject.com/en/3.2/topics/auth/customizing/#extending-the-existing-user-model
# Django
from django.contrib import admin
from django.contrib.auth.admin import UserAdmin as BaseUserAdmin
# Models
from django.contrib.auth.models import Use... | 0.496826 | 0.228092 |
from __future__ import print_function
# python std lib
import re
import sys
# phabfive imports
from phabfive import passphrase, diffusion, paste, user
from phabfive.constants import MONOGRAMS, REPO_STATUS_CHOICES
from phabfive.exceptions import (
PhabfiveConfigException,
PhabfiveDataException,
PhabfiveRe... | phabfive/cli.py |
from __future__ import print_function
# python std lib
import re
import sys
# phabfive imports
from phabfive import passphrase, diffusion, paste, user
from phabfive.constants import MONOGRAMS, REPO_STATUS_CHOICES
from phabfive.exceptions import (
PhabfiveConfigException,
PhabfiveDataException,
PhabfiveRe... | 0.501221 | 0.160003 |
from datetime import datetime, timedelta
from django.http import request
from rest_framework import generics, permissions, renderers
from rest_framework.generics import GenericAPIView
from rest_framework.mixins import UpdateModelMixin
from rest_framework.parsers import FormParser, JSONParser, MultiPartParser
from rest... | apps/blog/views.py | from datetime import datetime, timedelta
from django.http import request
from rest_framework import generics, permissions, renderers
from rest_framework.generics import GenericAPIView
from rest_framework.mixins import UpdateModelMixin
from rest_framework.parsers import FormParser, JSONParser, MultiPartParser
from rest... | 0.509276 | 0.070752 |
import unittest
from unittest.mock import Mock, patch
from azure.cli.command_modules.acs import _helpers as helpers
from azure.cli.core.azclierror import (
AzureInternalError,
AzureResponseError,
BadRequestError,
ClientRequestError,
ForbiddenError,
InvalidArgumentValueError,
ResourceNotFou... | src/azure-cli/azure/cli/command_modules/acs/tests/latest/test_helpers.py |
import unittest
from unittest.mock import Mock, patch
from azure.cli.command_modules.acs import _helpers as helpers
from azure.cli.core.azclierror import (
AzureInternalError,
AzureResponseError,
BadRequestError,
ClientRequestError,
ForbiddenError,
InvalidArgumentValueError,
ResourceNotFou... | 0.721841 | 0.191838 |
try:
from heat.common.i18n import _
except ImportError:
pass
from heat.engine import attributes
from heat.engine import properties
from vnc_api import vnc_api
from contrail_heat.resources import contrail
import uuid
class HeatPhysicalRouter(contrail.ContrailResource):
PROPERTIES = (
NAME,
) =... | contrail_heat/resources/physical_router.py | try:
from heat.common.i18n import _
except ImportError:
pass
from heat.engine import attributes
from heat.engine import properties
from vnc_api import vnc_api
from contrail_heat.resources import contrail
import uuid
class HeatPhysicalRouter(contrail.ContrailResource):
PROPERTIES = (
NAME,
) =... | 0.376967 | 0.148819 |
import os
import gym
import numpy as np
import pytest
from active_reward_learning.envs import RewardModelMeanWrapper
from active_reward_learning.reward_models.gaussian_process_linear import (
LinearObservationGP,
)
from active_reward_learning.reward_models.kernels import LinearKernel
from active_reward_learning.r... | active_reward_learning/tests/test_gaussian_process.py | import os
import gym
import numpy as np
import pytest
from active_reward_learning.envs import RewardModelMeanWrapper
from active_reward_learning.reward_models.gaussian_process_linear import (
LinearObservationGP,
)
from active_reward_learning.reward_models.kernels import LinearKernel
from active_reward_learning.r... | 0.728072 | 0.700088 |
def extract_moment_data(moment_data, sub_type):
"""Get the information for a moment."""
if isinstance(moment_data, dict):
return extract_moment_data(moment_data[sub_type], sub_type)
if isinstance(moment_data[-1], dict):
kwargs = moment_data[-1]
moment_data = moment_data[:-1]
els... | symfem/moments.py | def extract_moment_data(moment_data, sub_type):
"""Get the information for a moment."""
if isinstance(moment_data, dict):
return extract_moment_data(moment_data[sub_type], sub_type)
if isinstance(moment_data[-1], dict):
kwargs = moment_data[-1]
moment_data = moment_data[:-1]
els... | 0.755005 | 0.461988 |
def gir_mat():
# Boyutun girilmesi
print("Matrisin boyutunu giriniz: ")
n = int(input())
A = [[0 for i in range(n)] for i in range(n)]
# İç içe döngüyle elemanların girilmesi
print("A matrisini giriniz:")
for i in range(n):
for j in range(n):
print('A[{}][{}]'.format(i+1, j+1))
A[i][j] = ... | N-KareMatrisİşlemleri/KareMatris.py | def gir_mat():
# Boyutun girilmesi
print("Matrisin boyutunu giriniz: ")
n = int(input())
A = [[0 for i in range(n)] for i in range(n)]
# İç içe döngüyle elemanların girilmesi
print("A matrisini giriniz:")
for i in range(n):
for j in range(n):
print('A[{}][{}]'.format(i+1, j+1))
A[i][j] = ... | 0.050133 | 0.364834 |
import os
from dotenv import load_dotenv
import pymongo
load_dotenv()
DB_USER = os.getenv('MONGO_DB_USER', default='oops')
DB_PASSWORD = os.getenv('MONGO_DB_PASSWORD', default='<PASSWORD>')
CLUSTER_NAME = os.getenv('MONGO_CLUSTER_NAME', default='<PASSWORD>')
connection_uri = f"mongodb+srv://{DB_USER}:{DB_PASSWORD}@... | module4-acid-and-database-scalability-tradeoffs/assignment/mongodb_queries.py | import os
from dotenv import load_dotenv
import pymongo
load_dotenv()
DB_USER = os.getenv('MONGO_DB_USER', default='oops')
DB_PASSWORD = os.getenv('MONGO_DB_PASSWORD', default='<PASSWORD>')
CLUSTER_NAME = os.getenv('MONGO_CLUSTER_NAME', default='<PASSWORD>')
connection_uri = f"mongodb+srv://{DB_USER}:{DB_PASSWORD}@... | 0.3492 | 0.091423 |
import numpy as np
def calc_microwave_ref_index(wavelength, temperature=0):
"""
Calculate the refractive index of water in the microwave spectrum (centimeter wavelengths).
Parameters
----------
wavelength: float
Wavelength in cm
temperature: float
Temperature in Celsius
R... | emc2/scattering/ref_index.py | import numpy as np
def calc_microwave_ref_index(wavelength, temperature=0):
"""
Calculate the refractive index of water in the microwave spectrum (centimeter wavelengths).
Parameters
----------
wavelength: float
Wavelength in cm
temperature: float
Temperature in Celsius
R... | 0.953199 | 0.775796 |
import logging
from typing import List
from bio2bel import AbstractManager
from pybel import BELGraph
from tqdm import tqdm
from .constants import MODULE_NAME
from .models import Base, Entity1, Entity2, Interaction
from .parser import get_scai_mirna_dfs
__all__ = ['Manager']
log = logging.getLogger(__name__)
cla... | src/bio2bel_scaimc/manager.py |
import logging
from typing import List
from bio2bel import AbstractManager
from pybel import BELGraph
from tqdm import tqdm
from .constants import MODULE_NAME
from .models import Base, Entity1, Entity2, Interaction
from .parser import get_scai_mirna_dfs
__all__ = ['Manager']
log = logging.getLogger(__name__)
cla... | 0.844762 | 0.264584 |
# -*- coding: utf-8 -*-
"""
# reoredr_refs.py
This is an utility for reordering references in .docx manuscripts or reports.
If you don't use something like EndNote this is for you.
Usage:
python reorder_refs.py input.docx output.docx rules.conf
See the rules.conf sample for configuration details.
Writt... | reorder_refs.py | # -*- coding: utf-8 -*-
"""
# reoredr_refs.py
This is an utility for reordering references in .docx manuscripts or reports.
If you don't use something like EndNote this is for you.
Usage:
python reorder_refs.py input.docx output.docx rules.conf
See the rules.conf sample for configuration details.
Writt... | 0.133698 | 0.072243 |
import configparser
from api import Api
config = configparser.ConfigParser()
config.read('config.ini')
herolabs_email = config['DEFAULT']['EMAIL']
herolabs_password = config['DEFAULT']['PASSWORD']
demo_incident_id = config['DEMO_DATA']['INCIDENT_ID_SAMPLE']
demo_signal_id = config['DEMO_DATA']['SIGNAL_ID_SAMPLE']
demo... | src/test.py | import configparser
from api import Api
config = configparser.ConfigParser()
config.read('config.ini')
herolabs_email = config['DEFAULT']['EMAIL']
herolabs_password = config['DEFAULT']['PASSWORD']
demo_incident_id = config['DEMO_DATA']['INCIDENT_ID_SAMPLE']
demo_signal_id = config['DEMO_DATA']['SIGNAL_ID_SAMPLE']
demo... | 0.183703 | 0.046616 |
import logging
import datetime
import fableme.utils as utils
import fableme.db.booktemplates
from fableme.db.schema import DbFable
from fableme.db.schema import DbFableUser
class Steps(object):
""" Assign template and DB values according to the Wizard step """
def __init__(self, step):
self.current... | src/fableme/fabulator.py |
import logging
import datetime
import fableme.utils as utils
import fableme.db.booktemplates
from fableme.db.schema import DbFable
from fableme.db.schema import DbFableUser
class Steps(object):
""" Assign template and DB values according to the Wizard step """
def __init__(self, step):
self.current... | 0.453746 | 0.288481 |
import re
from ..plugininfo import PLUGIN_NAME, PLUGIN_VERSION
from requestbuilder import RequestBuilder
from ..logger.logger import get_logger
from requests.adapters import HTTPAdapter
from requests.sessions import Session
class PutClient(object):
"""
This is a simple HTTPClient wrapper which supports putMe... | src/cloudwatch/modules/client/putclient.py | import re
from ..plugininfo import PLUGIN_NAME, PLUGIN_VERSION
from requestbuilder import RequestBuilder
from ..logger.logger import get_logger
from requests.adapters import HTTPAdapter
from requests.sessions import Session
class PutClient(object):
"""
This is a simple HTTPClient wrapper which supports putMe... | 0.676834 | 0.081447 |
from cryptography.fernet import Fernet
from raho import *
import pytest
import re
if sys.version_info >= (3, 3):
from unittest.mock import call, patch
else:
from mock import call, patch
@pytest.fixture(scope='session')
def key():
return b'<KEY>
@pytest.fixture(scope='session')
def fernet(key):
retur... | test_raho.py | from cryptography.fernet import Fernet
from raho import *
import pytest
import re
if sys.version_info >= (3, 3):
from unittest.mock import call, patch
else:
from mock import call, patch
@pytest.fixture(scope='session')
def key():
return b'<KEY>
@pytest.fixture(scope='session')
def fernet(key):
retur... | 0.498047 | 0.367157 |
import os
import platform
import time
import ast
import random
import re
# Bibliotecas externas
import pwinput # pip install pwinput
# Abrindo bando de dados
arquivo = open("banco-de-dados.txt", "a+")
arquivo.close()
"""
- Funções úteis
1. limpar_terminal()
Busca qual o sistema operacional que o computador está u... | algoritmos-e-programacao-icev/exercicios/outros-projetos/vouchers/voucher.py | import os
import platform
import time
import ast
import random
import re
# Bibliotecas externas
import pwinput # pip install pwinput
# Abrindo bando de dados
arquivo = open("banco-de-dados.txt", "a+")
arquivo.close()
"""
- Funções úteis
1. limpar_terminal()
Busca qual o sistema operacional que o computador está u... | 0.173113 | 0.252436 |
import logging
import codecs
import os
import re
from flask import render_template
from content import app
from content.util import gh_markdown
root_path = os.path.abspath("markdown")
# {filename: (mtime, title, contents)}
cache = {}
title_regex = re.compile("^([^\n]+)\n[=-]+|!\\[([^\\]]+)\\]")
disqus_format = ""... | content/documentation_serve.py | import logging
import codecs
import os
import re
from flask import render_template
from content import app
from content.util import gh_markdown
root_path = os.path.abspath("markdown")
# {filename: (mtime, title, contents)}
cache = {}
title_regex = re.compile("^([^\n]+)\n[=-]+|!\\[([^\\]]+)\\]")
disqus_format = ""... | 0.233357 | 0.115212 |
import lammpstools
import dumpreader
import numpy as np
import math
import sys
import matplotlib.pyplot as plt
def get_avg_shortest_dist( b ):
""" !Finds the shortest distance for each particle to another. Expensive! """
N = b.meta.N
dists = np.ones(N) * 100000
for i in range(0,N):
for j in ra... | python/lammpstools/melting_analysis.py | import lammpstools
import dumpreader
import numpy as np
import math
import sys
import matplotlib.pyplot as plt
def get_avg_shortest_dist( b ):
""" !Finds the shortest distance for each particle to another. Expensive! """
N = b.meta.N
dists = np.ones(N) * 100000
for i in range(0,N):
for j in ra... | 0.183265 | 0.425546 |
import numpy as np
import time
import json
import os
import torch
import slowfast.utils.checkpoint as cu
import slowfast.utils.logging as logging
import slowfast.datasets.utils as utils
from slowfast.models.build import MODEL_REGISTRY
from slowfast.datasets.extractor import Extractor
from torch import multiprocessing... | slowfast/tools/video_extract.py | import numpy as np
import time
import json
import os
import torch
import slowfast.utils.checkpoint as cu
import slowfast.utils.logging as logging
import slowfast.datasets.utils as utils
from slowfast.models.build import MODEL_REGISTRY
from slowfast.datasets.extractor import Extractor
from torch import multiprocessing... | 0.508056 | 0.232691 |
begin_unit
comment|'# Copyright (c) 2011 OpenStack Foundation'
nl|'\n'
comment|'# All Rights Reserved.'
nl|'\n'
comment|'#'
nl|'\n'
comment|'# Licensed under the Apache License, Version 2.0 (the "License"); you may'
nl|'\n'
comment|'# not use this file except in compliance with the License. You may obtain'
nl|'\n... | nova/scheduler/scheduler_options.py | begin_unit
comment|'# Copyright (c) 2011 OpenStack Foundation'
nl|'\n'
comment|'# All Rights Reserved.'
nl|'\n'
comment|'#'
nl|'\n'
comment|'# Licensed under the Apache License, Version 2.0 (the "License"); you may'
nl|'\n'
comment|'# not use this file except in compliance with the License. You may obtain'
nl|'\n... | 0.672547 | 0.072472 |
from django.forms import Form, ModelForm, BooleanField, CharField, SlugField, URLField, Textarea, ValidationError
from .models import Resource, Faculty, Department, Agreement, Signature, DEFAULT_ALLOWED_TAGS
from .fields import GroupedModelChoiceField, SplitLineField
# Base Class
class ModelFormSetLabelSuffix(Model... | agreements/forms.py | from django.forms import Form, ModelForm, BooleanField, CharField, SlugField, URLField, Textarea, ValidationError
from .models import Resource, Faculty, Department, Agreement, Signature, DEFAULT_ALLOWED_TAGS
from .fields import GroupedModelChoiceField, SplitLineField
# Base Class
class ModelFormSetLabelSuffix(Model... | 0.684686 | 0.15633 |
import pandas as pd
import os
from contra_qa.text_processing.functions import simple_pre_process_text_df
from contra_qa.text_generation.boolean_data_gen import create_all
def csv_to_FBdialog(df,
out_path,
select_label="label",
question="There is a contradict... | generating_dialog_corpus.py | import pandas as pd
import os
from contra_qa.text_processing.functions import simple_pre_process_text_df
from contra_qa.text_generation.boolean_data_gen import create_all
def csv_to_FBdialog(df,
out_path,
select_label="label",
question="There is a contradict... | 0.306423 | 0.140395 |
from django.utils import tree
from django.db.models.sql.datastructures import MultiJoin
class CommonBaseTree(tree.Node):
"""
Encapsulates filters as objects that can then be combined logically (using
& and |).
"""
# Connection types
AND = 'AND'
OR = 'OR'
default = AND
query = None... | django_orm/core/sql/tree.py |
from django.utils import tree
from django.db.models.sql.datastructures import MultiJoin
class CommonBaseTree(tree.Node):
"""
Encapsulates filters as objects that can then be combined logically (using
& and |).
"""
# Connection types
AND = 'AND'
OR = 'OR'
default = AND
query = None... | 0.718199 | 0.199639 |
import argparse
import os
import pysam
from datetime import datetime
from pynnotator import settings
dbnfsp_header = '''##INFO=<ID=dbNSFP_GERP++_RS,Number=A,Type=Float,Description="Field 'GERP++_RS' from dbNSFP">
##INFO=<ID=dbNSFP_1000Gp1_ASN_AF,Number=A,Type=Float,Description="Field '1000Gp1_ASN_AF' from dbNSFP">
#... | pynnotator/helpers/dbnsfp.old.py |
import argparse
import os
import pysam
from datetime import datetime
from pynnotator import settings
dbnfsp_header = '''##INFO=<ID=dbNSFP_GERP++_RS,Number=A,Type=Float,Description="Field 'GERP++_RS' from dbNSFP">
##INFO=<ID=dbNSFP_1000Gp1_ASN_AF,Number=A,Type=Float,Description="Field '1000Gp1_ASN_AF' from dbNSFP">
#... | 0.306838 | 0.066691 |
import logging
from canvasapi.enrollment import Enrollment
from canvasapi.course import Course
from canvasapi.section import Section
from canvasapi.user import User
from typing import Dict, List
from faker import Faker
fake = Faker("en_US")
logger = logging.getLogger(__name__)
def rollback_loaded_enrollments(enroll... | src/canvas-extractor/tests/data_generation/enrollments.py |
import logging
from canvasapi.enrollment import Enrollment
from canvasapi.course import Course
from canvasapi.section import Section
from canvasapi.user import User
from typing import Dict, List
from faker import Faker
fake = Faker("en_US")
logger = logging.getLogger(__name__)
def rollback_loaded_enrollments(enroll... | 0.856707 | 0.449332 |
from gensim import corpora
from gensim.models import ldamodel
from nltk.corpus import stopwords
from collections import defaultdict
import argparse
def train_lda_tm(train_ptext_dict, num_topics, update, passes, token_dict_out, model_out_file):
stops = stopwords.words('english')
paraids = list(train_ptext_dict.... | model/lda_topic_model.py | from gensim import corpora
from gensim.models import ldamodel
from nltk.corpus import stopwords
from collections import defaultdict
import argparse
def train_lda_tm(train_ptext_dict, num_topics, update, passes, token_dict_out, model_out_file):
stops = stopwords.words('english')
paraids = list(train_ptext_dict.... | 0.459319 | 0.135775 |
from funfolding.binning import TreeBinningSklearn
import numpy as np
from sklearn.datasets import make_regression
from matplotlib import pyplot as plt
def test_treebinning():
n_samples = 1000
X, y = make_regression(n_samples=n_samples)
plt.hist(y)
y_binned = np.digitize(y, np.linspace(-400, 400, 20))... | tests/test_treebinning.py | from funfolding.binning import TreeBinningSklearn
import numpy as np
from sklearn.datasets import make_regression
from matplotlib import pyplot as plt
def test_treebinning():
n_samples = 1000
X, y = make_regression(n_samples=n_samples)
plt.hist(y)
y_binned = np.digitize(y, np.linspace(-400, 400, 20))... | 0.727975 | 0.746463 |
import os
import unittest
import time
import requests
from retry import retry
from tests.fixtures import fullpage_screenshot, server_url, retry_config, get_webdriver, PreloadedEnv
from tests.fixtures import AcceptanceBaseCase as BaseCase
from api import global_config
class PreloadedEnvCase(BaseCase):
"""
Ensu... | {{cookiecutter.project_slug}}/tests/smoke_tests/test_frontend_prod.py | import os
import unittest
import time
import requests
from retry import retry
from tests.fixtures import fullpage_screenshot, server_url, retry_config, get_webdriver, PreloadedEnv
from tests.fixtures import AcceptanceBaseCase as BaseCase
from api import global_config
class PreloadedEnvCase(BaseCase):
"""
Ensu... | 0.511229 | 0.207516 |
from bson import ObjectId
from django.conf import settings
from django.contrib.auth.models import User
from pymongo import MongoClient
from organizations.models import Organization
connection = MongoClient( settings.MONGODB_HOST, settings.MONGODB_PORT )
db = connection[ settings.MONGODB_DBNAME ]
class DataSeriali... | keep_backend/backend/db.py | from bson import ObjectId
from django.conf import settings
from django.contrib.auth.models import User
from pymongo import MongoClient
from organizations.models import Organization
connection = MongoClient( settings.MONGODB_HOST, settings.MONGODB_PORT )
db = connection[ settings.MONGODB_DBNAME ]
class DataSeriali... | 0.413596 | 0.232626 |
from typing import Dict
from watson_developer_cloud import AssistantV1
from watson_developer_cloud.assistant_v1 import CreateIntent, CreateExample, CreateDialogNode, DialogNodeNextStep, \
DialogNodeOutput, CreateEntity, CreateValue, DialogNodeAction
from hovor.configuration.configuration_provider_base import Conf... | hovor/wa_deployment/workspace_configuration_writer.py | from typing import Dict
from watson_developer_cloud import AssistantV1
from watson_developer_cloud.assistant_v1 import CreateIntent, CreateExample, CreateDialogNode, DialogNodeNextStep, \
DialogNodeOutput, CreateEntity, CreateValue, DialogNodeAction
from hovor.configuration.configuration_provider_base import Conf... | 0.615666 | 0.187226 |
import dateutil.relativedelta as rd
from . import helpers as hp
def get_dates(feed, *, as_date_obj=False):
"""
Return a list of dates for which the given Feed is valid, which
could be the empty list if the Feed has no calendar information.
Parameters
----------
feed : Feed
as_date_obj : ... | gtfstk/calendar.py | import dateutil.relativedelta as rd
from . import helpers as hp
def get_dates(feed, *, as_date_obj=False):
"""
Return a list of dates for which the given Feed is valid, which
could be the empty list if the Feed has no calendar information.
Parameters
----------
feed : Feed
as_date_obj : ... | 0.792544 | 0.367951 |
import datetime
from django.test import TestCase
from smart_serializers.utils import get_unique_fields, lookup_pattern_from_instance
from smart_serializers.python import Serializer, Deserializer
from core.models import Article, Author, AuthorProfile, Category, Publication, Site
from core.models import *
def get_field... | tests/core/tests.py | import datetime
from django.test import TestCase
from smart_serializers.utils import get_unique_fields, lookup_pattern_from_instance
from smart_serializers.python import Serializer, Deserializer
from core.models import Article, Author, AuthorProfile, Category, Publication, Site
from core.models import *
def get_field... | 0.574514 | 0.253665 |
from sklearn.model_selection import train_test_split
from sklearn.metrics import classification_report
from sklearn.datasets import make_blobs
import matplotlib.pyplot as plt
import numpy as np
import argparse
def sigmoid_activation(x):
return 1.0 / (1 + np.exp(-x))
def sigmoid_deriv(x):
return x * (1 - x)
... | ML/KNN/sgd.py | from sklearn.model_selection import train_test_split
from sklearn.metrics import classification_report
from sklearn.datasets import make_blobs
import matplotlib.pyplot as plt
import numpy as np
import argparse
def sigmoid_activation(x):
return 1.0 / (1 + np.exp(-x))
def sigmoid_deriv(x):
return x * (1 - x)
... | 0.85115 | 0.586286 |
from colored import fg, bg, attr
from serial import Serial
import argparse
from embedded_utils.handle_config import load_config
parser = argparse.ArgumentParser(description='Description of your program')
parser.add_argument('-s', '--silent', help='Runs with config.yml without \
prompting user or do... | color_debug.py | from colored import fg, bg, attr
from serial import Serial
import argparse
from embedded_utils.handle_config import load_config
parser = argparse.ArgumentParser(description='Description of your program')
parser.add_argument('-s', '--silent', help='Runs with config.yml without \
prompting user or do... | 0.469034 | 0.139983 |
import tkinter as t
import random
import smtplib
from os import system
from time import sleep
Path = "E:\\Projects\\CS\\Proto-stack\\Proto-Stack-GUI\\Database.txt"
def destruct_win():
root.destroy()
root4.destroy()
root2.destroy()
root7.destroy()
def otpsender(email):
global x
... | Proto_Stack_GUI.py | import tkinter as t
import random
import smtplib
from os import system
from time import sleep
Path = "E:\\Projects\\CS\\Proto-stack\\Proto-Stack-GUI\\Database.txt"
def destruct_win():
root.destroy()
root4.destroy()
root2.destroy()
root7.destroy()
def otpsender(email):
global x
... | 0.17621 | 0.119897 |
# %% Imports and chemicals initialization
import numpy as np
import thermosteam as tmo
import biosteam as bst
import copy
from biorefineries.HP.chemicals_data import HP_chemicals
from biorefineries.HP.system_light_lle_vacuum_distillation import S404
Water = HP_chemicals['Water']
# Glucose = HP_chemicals['Glucose']
... | BioSTEAM 2.x.x/biorefineries/HP/test_solvents.py | # %% Imports and chemicals initialization
import numpy as np
import thermosteam as tmo
import biosteam as bst
import copy
from biorefineries.HP.chemicals_data import HP_chemicals
from biorefineries.HP.system_light_lle_vacuum_distillation import S404
Water = HP_chemicals['Water']
# Glucose = HP_chemicals['Glucose']
... | 0.164987 | 0.281702 |
from unittest import TestCase, skip
from guitarpractice import constants
from guitarpractice.models import Note, FretPosition, Beat
from guitarpractice.note_utils import group_notes, normalise_note_durations
class TestGroupNotes(TestCase):
def test_individual_notes_are_returned_in_order(self):
position =... | guitarpractice/tests/test_note_utils.py | from unittest import TestCase, skip
from guitarpractice import constants
from guitarpractice.models import Note, FretPosition, Beat
from guitarpractice.note_utils import group_notes, normalise_note_durations
class TestGroupNotes(TestCase):
def test_individual_notes_are_returned_in_order(self):
position =... | 0.81231 | 0.576959 |
import unittest
from mergesvvcf.locations import *
from mergesvvcf.variantdict import *
class TestLocations(unittest.TestCase):
def setUp(self):
self.l1 = location('X',31,'+')
self.l2 = location('Y',131,-1)
self.l3 = location('Y',121,+1)
self.l4 = location('Y',161,'-')
self... | tests/test_pymergevcfs.py | import unittest
from mergesvvcf.locations import *
from mergesvvcf.variantdict import *
class TestLocations(unittest.TestCase):
def setUp(self):
self.l1 = location('X',31,'+')
self.l2 = location('Y',131,-1)
self.l3 = location('Y',121,+1)
self.l4 = location('Y',161,'-')
self... | 0.52074 | 0.478041 |
from __future__ import print_function
import click
from stable_world.interact.setup_user import setup_bucket_token
from stable_world.interact.use import check_bucket
from stable_world import executors
from stable_world import errors, utils, application
from stable_world.managers.pypi import PyPIManager
from stable_wo... | stable_world/commands/execute.py | from __future__ import print_function
import click
from stable_world.interact.setup_user import setup_bucket_token
from stable_world.interact.use import check_bucket
from stable_world import executors
from stable_world import errors, utils, application
from stable_world.managers.pypi import PyPIManager
from stable_wo... | 0.507324 | 0.075995 |
import tenseal as ts
import pytest
@pytest.fixture(scope='module')
def context():
return ts.context(ts.SCHEME_TYPE.BFV, 4096, 1024)
def test_add(context):
first_vec = ts.bfv_naive_vector(context, [1, 2, 3, 4])
second_vec = ts.bfv_naive_vector(context, [4, 3, 2, 1])
result = first_vec + second_vec
... | tests/tensors/test_bvf_naive_vector.py | import tenseal as ts
import pytest
@pytest.fixture(scope='module')
def context():
return ts.context(ts.SCHEME_TYPE.BFV, 4096, 1024)
def test_add(context):
first_vec = ts.bfv_naive_vector(context, [1, 2, 3, 4])
second_vec = ts.bfv_naive_vector(context, [4, 3, 2, 1])
result = first_vec + second_vec
... | 0.765769 | 0.810741 |
from PIL import Image # Pillow library
from neopixel import * # led strip code by https://github.com/jgarff/rpi_ws281x
from random import randint
from time import time
import os
LED_COUNT = 90
LED_GPIO = 21
LED_FREQ = 800000 # LED signal frequency in hertz (usually 800khz)
LED_DMA = 10
LED_INVERT = False
LED_BRIGH... | examples/integriot/artificial-window/integriot/run.py |
from PIL import Image # Pillow library
from neopixel import * # led strip code by https://github.com/jgarff/rpi_ws281x
from random import randint
from time import time
import os
LED_COUNT = 90
LED_GPIO = 21
LED_FREQ = 800000 # LED signal frequency in hertz (usually 800khz)
LED_DMA = 10
LED_INVERT = False
LED_BRIGH... | 0.537284 | 0.234774 |
# pylint: disable=no-init
# Numerous classes don't require __init__.
# pylint: disable=too-many-public-methods
# Number of methods are defined in specification
# pylint: disable=too-many-ancestors
# Inheritance defined in specification
from ..osid import managers as osid_managers
from ..osid.osid_errors i... | dlkit/manager_impls/authorization/managers.py | # pylint: disable=no-init
# Numerous classes don't require __init__.
# pylint: disable=too-many-public-methods
# Number of methods are defined in specification
# pylint: disable=too-many-ancestors
# Inheritance defined in specification
from ..osid import managers as osid_managers
from ..osid.osid_errors i... | 0.828106 | 0.267876 |
from turtle import Screen
from score_board import Score
from draw_center_line import DrawCenterLine
from paddle import Paddle
import main
from ball import Ball
import time
WIDTH = 900
HEIGHT = 600
game_on = True
active_player = 'left'
player_1_score = 0
player_2_score = 0
screen = Screen()
screen.tracer... | day22_pong/main.py | from turtle import Screen
from score_board import Score
from draw_center_line import DrawCenterLine
from paddle import Paddle
import main
from ball import Ball
import time
WIDTH = 900
HEIGHT = 600
game_on = True
active_player = 'left'
player_1_score = 0
player_2_score = 0
screen = Screen()
screen.tracer... | 0.263315 | 0.107954 |
import numpy as np
from matsubara.correlation import (sum_of_exponentials, biexp_fit,
bath_correlation, underdamped_brownian,
nonmatsubara_exponents, matsubara_exponents,
matsubara_zero_analytical, coth)
from qutip.... | docs/source/examples/example_pseudomode.py | import numpy as np
from matsubara.correlation import (sum_of_exponentials, biexp_fit,
bath_correlation, underdamped_brownian,
nonmatsubara_exponents, matsubara_exponents,
matsubara_zero_analytical, coth)
from qutip.... | 0.614625 | 0.670339 |
from api.helpers import random_string_generator
from tests.conftest import ValueStorage
name = random_string_generator(20)
def test_playthrough_all(client):
json = {"query":"query getPlaythroughs{\n playthroughs {\n id\n }\n}","operationName":"getPlaythroughs"}
response = client.post('/graphql', headers... | tests/2.functional/test_playthrough.py | from api.helpers import random_string_generator
from tests.conftest import ValueStorage
name = random_string_generator(20)
def test_playthrough_all(client):
json = {"query":"query getPlaythroughs{\n playthroughs {\n id\n }\n}","operationName":"getPlaythroughs"}
response = client.post('/graphql', headers... | 0.275227 | 0.25794 |
import json
import numpy as np
import tensorflow as tf
class VanillaGAN(object):
''' Vanilla Generative Adversarial Networks
Attribute:
z_dim: Integer, dimension of noise vector.
x_dim: Integer, dimension of generated vector.
g_hidden: An integer or tuple/list of n-integers, specifying... | model.py | import json
import numpy as np
import tensorflow as tf
class VanillaGAN(object):
''' Vanilla Generative Adversarial Networks
Attribute:
z_dim: Integer, dimension of noise vector.
x_dim: Integer, dimension of generated vector.
g_hidden: An integer or tuple/list of n-integers, specifying... | 0.887253 | 0.532121 |
import torch
import torchvision
import numpy as np
import copy
import os
from . import resnet
from .result import Result
from .general import *
class Model:
def __init__(self, dataset_name, model_path=''):
self.name = dataset_name
self.device = 'cuda'
self.model_path = model_path
# ... | lib/model.py | import torch
import torchvision
import numpy as np
import copy
import os
from . import resnet
from .result import Result
from .general import *
class Model:
def __init__(self, dataset_name, model_path=''):
self.name = dataset_name
self.device = 'cuda'
self.model_path = model_path
# ... | 0.772531 | 0.228737 |
import warnings
warnings.filterwarnings("ignore")
import numpy as np
import os
from nltk.stem.snowball import SnowballStemmer
from sklearn.model_selection import train_test_split
from sklearn.manifold import TSNE
from sklearn.decomposition import PCA, TruncatedSVD
from sklearn.datasets import load_files
from sklearn.... | Projetos/DiscursosDeputados/experimentos/clustering/clustering.py | import warnings
warnings.filterwarnings("ignore")
import numpy as np
import os
from nltk.stem.snowball import SnowballStemmer
from sklearn.model_selection import train_test_split
from sklearn.manifold import TSNE
from sklearn.decomposition import PCA, TruncatedSVD
from sklearn.datasets import load_files
from sklearn.... | 0.536799 | 0.380759 |
import pandas as pd
import ipdb
import os
from shutil import copyfile
import dtw
import matplotlib.pyplot as plt
import birl.robot_introspection_pkg.multi_modal_config as mmc
import copy
import numpy as np
import shutil
from sklearn.preprocessing import normalize, MinMaxScaler
PLOT_VERIFICATION = True
ano_keyword_to... | data_processing_scripts/cook_dataset_of_lfds.py | import pandas as pd
import ipdb
import os
from shutil import copyfile
import dtw
import matplotlib.pyplot as plt
import birl.robot_introspection_pkg.multi_modal_config as mmc
import copy
import numpy as np
import shutil
from sklearn.preprocessing import normalize, MinMaxScaler
PLOT_VERIFICATION = True
ano_keyword_to... | 0.179746 | 0.188324 |
import itertools
import unittest
import operator
try:
_reduce = reduce
except NameError:
from functools import reduce as _reduce
from chainlet.primitives.neutral import NeutralLink
from chainlet.primitives.bundle import Bundle
from chainlet.primitives.chain import FlatChain
from chainlet_unittests.utility imp... | chainlet_unittests/test_grammar/test_linker.py | import itertools
import unittest
import operator
try:
_reduce = reduce
except NameError:
from functools import reduce as _reduce
from chainlet.primitives.neutral import NeutralLink
from chainlet.primitives.bundle import Bundle
from chainlet.primitives.chain import FlatChain
from chainlet_unittests.utility imp... | 0.616359 | 0.574604 |
import random
from typing import Tuple
from maze import Maze
class TermColors:
white = "\033[0m"
blue = "\033[94m"
green = "\033[92m"
red = "\033[91m"
endc = "\033[0m"
class MazeGen:
"""Generate maze
TODO: Better maze generation look
https://en.wikipedia.org/wiki/Maze_generation_al... | maze_gen.py | import random
from typing import Tuple
from maze import Maze
class TermColors:
white = "\033[0m"
blue = "\033[94m"
green = "\033[92m"
red = "\033[91m"
endc = "\033[0m"
class MazeGen:
"""Generate maze
TODO: Better maze generation look
https://en.wikipedia.org/wiki/Maze_generation_al... | 0.549761 | 0.383006 |
import sqlalchemy as sa
from flask_apispec import doc, marshal_with
from webservices import args
from webservices import docs
from webservices import utils
from webservices import schemas
from webservices.common import models
from webservices.utils import use_kwargs
from webservices.resources.reports import reports_ty... | webservices/resources/totals.py | import sqlalchemy as sa
from flask_apispec import doc, marshal_with
from webservices import args
from webservices import docs
from webservices import utils
from webservices import schemas
from webservices.common import models
from webservices.utils import use_kwargs
from webservices.resources.reports import reports_ty... | 0.300232 | 0.081228 |
from const import (
TARGET_COIN,
COINS_TO_SEARCH,
COLUMN_NAMES
)
def generate_string_search():
'''Uses constants defined in const.py to return a string made up of
smaller strings in the format "coin_search-target_search".
'''
coins_formated_list = []
for coin in COINS_TO_SEARCH:
... | utils.py | from const import (
TARGET_COIN,
COINS_TO_SEARCH,
COLUMN_NAMES
)
def generate_string_search():
'''Uses constants defined in const.py to return a string made up of
smaller strings in the format "coin_search-target_search".
'''
coins_formated_list = []
for coin in COINS_TO_SEARCH:
... | 0.377196 | 0.227255 |
from os import path
from typing import Dict, List, Set, Tuple
from PIL import Image
import numpy as np
import logging
class ImageLoader:
path_list: List[dict]
sets: Set[str]
scale_factor: int
classes: Dict[str, int]
def __init__(self, path_list: List[dict], sets: Set[str], classes: Dict[str, int]... | src/imageLoader.py | from os import path
from typing import Dict, List, Set, Tuple
from PIL import Image
import numpy as np
import logging
class ImageLoader:
path_list: List[dict]
sets: Set[str]
scale_factor: int
classes: Dict[str, int]
def __init__(self, path_list: List[dict], sets: Set[str], classes: Dict[str, int]... | 0.847621 | 0.436082 |
import warnings
from torch.autograd import NestedIOFunction
from torch.nn import functional as F
import torch
import itertools
from functools import partial
__all__ = ["LSTMCell", "RNN"]
def RNNReLUCell(input, hidden, w_ih, w_hh, b_ih=None, b_hh=None):
hy = F.relu(F.linear(input, w_ih, b_ih) + F.linear(hidden, w_... | tools/pytorch-quantization/pytorch_quantization/nn/_functions/quant_rnn.py | import warnings
from torch.autograd import NestedIOFunction
from torch.nn import functional as F
import torch
import itertools
from functools import partial
__all__ = ["LSTMCell", "RNN"]
def RNNReLUCell(input, hidden, w_ih, w_hh, b_ih=None, b_hh=None):
hy = F.relu(F.linear(input, w_ih, b_ih) + F.linear(hidden, w_... | 0.848784 | 0.49109 |
from pyramid.i18n import TranslationStringFactory
from formencode import Schema, validators
from pytz import common_timezones
from ow.schemas.blob import FieldStorageBlob
from ow.utilities import get_available_locale_names, get_gender_names
_ = TranslationStringFactory('OpenWorkouts')
class PasswordMatch(validators... | ow/schemas/user.py | from pyramid.i18n import TranslationStringFactory
from formencode import Schema, validators
from pytz import common_timezones
from ow.schemas.blob import FieldStorageBlob
from ow.utilities import get_available_locale_names, get_gender_names
_ = TranslationStringFactory('OpenWorkouts')
class PasswordMatch(validators... | 0.58059 | 0.30399 |
import os, sys, argparse, time, csv
from gensim.models import Word2Vec, FastText
from sklearn.manifold import TSNE
import matplotlib.pyplot as plt
from tqdm import tqdm
import numpy as np
from dump_w2v import dump_w2v
from wordcloud import WordCloud
import pandas as pd
from gensim.models import KeyedVectors
sys.path.a... | vector-space/train_embedding_model.py |
import os, sys, argparse, time, csv
from gensim.models import Word2Vec, FastText
from sklearn.manifold import TSNE
import matplotlib.pyplot as plt
from tqdm import tqdm
import numpy as np
from dump_w2v import dump_w2v
from wordcloud import WordCloud
import pandas as pd
from gensim.models import KeyedVectors
sys.path.a... | 0.45181 | 0.256919 |
import numpy as np
import matplotlib.pyplot as plt
from supervenn._algorithms import (
get_chunks_and_composition_array,
get_permutations,
DEFAULT_MAX_BRUTEFORCE_SIZE,
DEFAULT_SEEDS,
DEFAULT_NOISE_PROB)
DEFAULT_FONTSIZE = 12
DEFAULT_FIGSIZE = (8, 5)
def get_alternated_ys(ys_count, low, high):
... | supervenn/_plots.py | import numpy as np
import matplotlib.pyplot as plt
from supervenn._algorithms import (
get_chunks_and_composition_array,
get_permutations,
DEFAULT_MAX_BRUTEFORCE_SIZE,
DEFAULT_SEEDS,
DEFAULT_NOISE_PROB)
DEFAULT_FONTSIZE = 12
DEFAULT_FIGSIZE = (8, 5)
def get_alternated_ys(ys_count, low, high):
... | 0.758063 | 0.619212 |
import os
import falcon
from falcon import testing
from .dataset_fixtures import *
test_auth = "<KEY>"
def test_git_refs_resource(client):
ds_id = 'ds000001'
response = client.simulate_get(
'/git/0/{}/info/refs?service=git-receive-pack'.format(ds_id), headers={"authorization": test_auth})
asse... | services/datalad/tests/test_git.py | import os
import falcon
from falcon import testing
from .dataset_fixtures import *
test_auth = "<KEY>"
def test_git_refs_resource(client):
ds_id = 'ds000001'
response = client.simulate_get(
'/git/0/{}/info/refs?service=git-receive-pack'.format(ds_id), headers={"authorization": test_auth})
asse... | 0.411466 | 0.31258 |
import boto3
import socket
import requests
import datetime
import argparse
from prettytable import PrettyTable
def argparser():
parser = argparse.ArgumentParser()
parser.add_argument('--hosts', nargs='+', help='List of hosts to work with', required=True)
args = parser.parse_args()
return args.hosts
... | run.py | import boto3
import socket
import requests
import datetime
import argparse
from prettytable import PrettyTable
def argparser():
parser = argparse.ArgumentParser()
parser.add_argument('--hosts', nargs='+', help='List of hosts to work with', required=True)
args = parser.parse_args()
return args.hosts
... | 0.271928 | 0.103477 |
import os
import urllib.request
from datetime import datetime
from PIL import Image
import io
import csv
import random
import sys
# the source for the image urls
card_list_file = "hour_of_devestation_cards.csv"
# prompt for number of rares/mythics, uncommons, and commons, or number of packs
packs_or_cards = input("... | gen_cards.py | import os
import urllib.request
from datetime import datetime
from PIL import Image
import io
import csv
import random
import sys
# the source for the image urls
card_list_file = "hour_of_devestation_cards.csv"
# prompt for number of rares/mythics, uncommons, and commons, or number of packs
packs_or_cards = input("... | 0.223292 | 0.160628 |
from teleftp.telegram import TelegramBot
from telegram import ReplyKeyboardMarkup
from telegram.ext import CommandHandler, MessageHandler, Filters, ConversationHandler
import tempfile
import os.path
from teleftp.ftp.filesystem import FTPDriver, LocalDriver, FilesystemDriver, FilesystemError, FilesystemAuthError
cl... | teleftp/ftp/__init__.py | from teleftp.telegram import TelegramBot
from telegram import ReplyKeyboardMarkup
from telegram.ext import CommandHandler, MessageHandler, Filters, ConversationHandler
import tempfile
import os.path
from teleftp.ftp.filesystem import FTPDriver, LocalDriver, FilesystemDriver, FilesystemError, FilesystemAuthError
cl... | 0.287968 | 0.043305 |
from enum import IntEnum
import random
from coq.constr import *
from coq.constr_util import PreOrder
"""
[Note]
Utility classes/functions for simple-rewrite problem.
"""
# -------------------------------------------------
# Auxilliary
class IdLaw(IntEnum):
ID_R = 0 # forall b: G, b <+> m = b
ID_L = 1... | gamepad/ml/rewrite/utils.py |
from enum import IntEnum
import random
from coq.constr import *
from coq.constr_util import PreOrder
"""
[Note]
Utility classes/functions for simple-rewrite problem.
"""
# -------------------------------------------------
# Auxilliary
class IdLaw(IntEnum):
ID_R = 0 # forall b: G, b <+> m = b
ID_L = 1... | 0.737253 | 0.393414 |
import pytorch_lightning as pl
from omegaconf import OmegaConf
from pytorchvideo.transforms import transforms as ptv_transforms
import albumentations as A
import hydra
from ..datasets import pose_transforms, video_transforms
def create_pose_transforms(transforms_cfg):
all_transforms = []
for transform in trans... | openhands/core/data.py | import pytorch_lightning as pl
from omegaconf import OmegaConf
from pytorchvideo.transforms import transforms as ptv_transforms
import albumentations as A
import hydra
from ..datasets import pose_transforms, video_transforms
def create_pose_transforms(transforms_cfg):
all_transforms = []
for transform in trans... | 0.813535 | 0.531027 |
import xarray as xr
import datetime
from datetime import timedelta as td
from datetime import datetime as dt
import pandas as pd
import copy
import cftime
from . import _consts as consts
class basics():
"""The :class:`basics` contains some basics functions for controlling netCDF CF standard time axis
Paramet... | pyhomogenize/_basics.py | import xarray as xr
import datetime
from datetime import timedelta as td
from datetime import datetime as dt
import pandas as pd
import copy
import cftime
from . import _consts as consts
class basics():
"""The :class:`basics` contains some basics functions for controlling netCDF CF standard time axis
Paramet... | 0.880335 | 0.343342 |
import io
import os
import platform
from unittest import mock
import pytest
from bplustree.node import LeafNode, FreelistNode
from bplustree.memory import (
FileMemory, open_file_in_dir, WAL, ReachedEndOfFile, write_to_file
)
from bplustree.const import TreeConf
from .conftest import filename
from bplustree.seria... | tests/test_memory.py | import io
import os
import platform
from unittest import mock
import pytest
from bplustree.node import LeafNode, FreelistNode
from bplustree.memory import (
FileMemory, open_file_in_dir, WAL, ReachedEndOfFile, write_to_file
)
from bplustree.const import TreeConf
from .conftest import filename
from bplustree.seria... | 0.510985 | 0.390011 |
from evaluator import *
from glob import glob
import pandas as pd
from pathlib import Path
import numpy as np
from functools import reduce
from collections import defaultdict
import json
numba = "_exp27_val_"
exp = 'exp27'
target = "val" # can be {val | train}
threshes = [0.1] # , 0.3, 0.33, 0.35, 0.4, 0.5, ... | src/performance/generate_train_val_events.py | from evaluator import *
from glob import glob
import pandas as pd
from pathlib import Path
import numpy as np
from functools import reduce
from collections import defaultdict
import json
numba = "_exp27_val_"
exp = 'exp27'
target = "val" # can be {val | train}
threshes = [0.1] # , 0.3, 0.33, 0.35, 0.4, 0.5, ... | 0.117521 | 0.255599 |