input stringlengths 2.65k 237k | output stringclasses 1
value |
|---|---|
<filename>ibm_watson/text_to_speech_v1.py
# coding: utf-8
# (C) Copyright IBM Corp. 2015, 2020.
#
# 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... | |
style="color:#00C000"><b>default</b></span>: false).</li>
<li><b>tf_log_level</b> (<i>int >= 0</i>) – TensorFlow log level, additional C++
logging messages can be enabled by setting os.environ["TF_CPP_MIN_LOG_LEVEL"] = "1"/"2"
before importing Tensorforce/TensorFlow
(<span style="color:#00C000"><b>default</b>... | |
# -*- coding: utf-8 -*-
"""
Calculate pair distribution functions.
"""
MINDISTANCE = 2.0 # shorter distances are ignored
PDFCUTOFF = 1.0 # g(r) = 0 if r < PDFCUTOFF
__all__ = ["PDF"]
import numpy as np
import math
from util.logger import Logger
import sys
from core.calculation.discretization import Discretization... | |
<filename>server_class.py
"""reads Requests from the server and handles method calls
"""
import os
from server_logic import Adminservices
from server_logic import Userservices
class Server:
"""
File management for server
Attributes:
--------------
username : string
stores username
password : string... | |
`false`.
"""
return pulumi.get(self, "include_control_details")
@property
@pulumi.getter(name="includeNullAndEmpty")
def include_null_and_empty(self) -> Optional[bool]:
"""
Include NULL and empty columns for records migrated to the endpoint. The default is `false`.
"""
return pulumi.get(self, "include_null_an... | |
= x0+w//2
i1 = int(x1+0.5)
i2 = int(x2+0.5)
if i2 >= n :
i2 = n-1
i1 = i2-w+1
if i1 < 0 :
i1 = 0
i2 = i1+w-1
xx = x[i1:i2+1]
yy = y[i1:i2+1]
coef,cov = optimize.curve_fit (quadratic_func,xx,yy)
c,b,a = coef # BACKWARDS!
# CHECK THAT THE SOLUTION YIELDS A POSITIVE PEAK
if (positive and b <= 0.0) or ... | |
<filename>pymc4/random_variables/continuous.py
"""
PyMC4 continuous random variables.
Wraps selected tfp.distributions (listed in __all__) as pm.RandomVariables.
Implements random variables not supported by tfp as distributions.
"""
# pylint: disable=undefined-all-variable
import tensorflow_probability as tfp
from te... | |
# AUTOGENERATED! DO NOT EDIT! File to edit: nbs/02_data.ipynb (unless otherwise specified).
__all__ = ['VIIRS750_download', 'BandsFilter', 'BandsRename', 'MergeTiles', 'BandsAssertShape', 'ActiveFires',
'MirCalc', 'BaseDataset', 'Viirs750Dataset', 'MCD64Dataset', 'FireCCI51Dataset', 'AusCoverDataset',
'MTBSDataset',... | |
if filetable2 != None:
self.reduced_variables[varid+'_2'] = reduced_variable(
variableid = vbase, filetable=filetable2, reduced_var_id = varid+'_2',
reduction_function=(lambda x, vid: reduce2latlon_seasonal_level(x, self.season, num, vid)))
self.composite_plotspecs = {}
self.single_plotspecs={}
self.single_plots... | |
"""相対時間の抽出・正規化処理を定義するモジュール."""
from copy import deepcopy
from typing import List, Tuple
from pynormalizenumexp.expression.base import INF, NNumber, NTime, NumberModifier
from pynormalizenumexp.expression.reltime import ReltimeExpression, ReltimePattern
from pynormalizenumexp.utility.dict_loader import DictLoader
from... | |
# Copyright 2017 Google Inc. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agree... | |
автоматическом режиме маршрутизатор будет динамически регулировать распределение полосы пропускания в соответствии с текущим использованием сети, чтобы обеспечить бесперебойную работу сети'
},
'优先级模式下路由器会动态调整带宽分配，保证优先级较高的设备网络体验流畅': {
'en': 'In priority mode, the router will dynamically adjust the bandwidth allocatio... | |
<reponame>pulumi/pulumi-rancher2
# coding=utf-8
# *** WARNING: this file was generated by the Pulumi Terraform Bridge (tfgen) Tool. ***
# *** Do not edit by hand unless you're certain you know what you are doing! ***
import warnings
import pulumi
import pulumi.runtime
from typing import Any, Mapping, Optional, Sequenc... | |
= self.trajevents[self._FScompatibleNames(evnames)]
except AttributeError:
# empty pointset
return None
else:
result.indepvararray += t_offset
return result
else:
# assume a sequence of strings
assert all([ev in compat_evnames for ev in evnames]), \
"Invalid event name(s) provided: %s"%str(evnames)
result = ... | |
# -*- coding: utf-8 -*-
import scrapy
import re
from .. import items
from bs4 import BeautifulSoup
from selenium import webdriver
from requests import get
from time import sleep
# change this path to wherever the chrome webdriver is located in your system
WEBDRIVER_PATH = ("D:\\chromedriver_win32\\" + "chromedriver.ex... | |
not specified then an attempt will be made to find a model
corresponding to the current dataset name,
`'model_' + self.dataset.name + '.pkl'`. If there is no current
dataset then the most recent model will be loaded.
This method is only intended to be used to deserialise models created
by this interactive Jupyter ... | |
#:
greenygrey: str = "#7ea07a" #:
greenyyellow: str = "#c6f808" #:
grey: str = "#929591" #:
greyblue: str = "#647d8e" #:
greybrown: str = "#7f7053" #:
greygreen: str = "#86a17d" #:
greyish: str = "#a8a495" #:
greyishblue: str = "#5e819d" #:
greyishbrown: str = "#7a6a4f" #:
greyishgreen: str = "#82a67d" #:
gr... | |
from fastai.torch_core import *
from fastai.basic_train import *
from fastai.callbacks import *
from fastai.data_block import CategoryList
from fastai.basic_data import *
from fastai.datasets import *
from fastai.metrics import accuracy
from fastai.train import GradientClipping
from fastai.layers import *
from fastai.t... | |
% period - tse0 % period) / 0.01#**2
def flatbottom(x, y, sep, swidth):
check = (x<sep+swidth/3.) * (x>sep-swidth/3.)
grady = np.gradient(y)
grady_m = np.polyfit(x[check], grady[check], 1)[0]
if abs(grady_m)<0.1:
return 0.01
elif abs(grady_m)>10.:
return 0.4
else:
return 0.1
def guess_rrat(sdep, pdep):
if (... | |
#!/usr/bin/env python2
#
# xpyBuild - eXtensible Python-based Build System
#
# Copyright (c) 2013 - 2018 Software AG, Darmstadt, Germany and/or its licensors
# Copyright (c) 2013 - 2018 <NAME> and <NAME>
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance... | |
<gh_stars>1-10
# -*- coding: utf-8 -*-
"""
Created on Mon Mar 28 14:11:31 2016
@author: adam
"""
import matplotlib.pyplot as plt
import numpy as np
from datetime import datetime
from scipy.signal import argrelextrema
from sklearn import neighbors as nb
from sklearn.gaussian_process import GaussianProcess
from scip... | |
for this Project': 'No Organisations for this Project',
'No Packs for Item': 'No Packs for Item',
'No Patients currently registered': 'No Patients currently registered',
'No People currently committed': 'No People currently committed',
'No People currently registered in this camp': 'No People currently registered in th... | |
'chrUn_JTFH01000337v1_decoy',
'chrUn_JTFH01000338v1_decoy',
'chrUn_JTFH01000339v1_decoy',
'chrUn_JTFH01000340v1_decoy',
'chrUn_JTFH01000341v1_decoy',
'chrUn_JTFH01000342v1_decoy',
'chrUn_JTFH01000343v1_decoy',
'chrUn_JTFH01000344v1_decoy',
'chrUn_JTFH01000345v1_decoy',
'chrUn_JTFH01000346v1_decoy',
'chrUn_JTF... | |
x, y, triangles, _, dataIndex = createTriangles(mesh)
if len(data) == mesh.cellCount():
z = data[dataIndex]
else:
z = data
gci = None
if levels is None:
levels = autolevel(data, nLevs,
zMin=cMin, zMax=cMax, logScale=logScale)
if len(z) == len(triangles):
shading = kwargs.pop('shading', 'flat')
# bounds ... | |
# -*- coding: utf-8 -*-
###########################################################################
# Copyright (c), The AiiDA team. All rights reserved. #
# This file is part of the AiiDA code. #
# #
# The code is hosted on GitHub at https://github.com/aiidateam/aiida-core #
# For further information on the license, s... | |
"09", # noqa: E501
}
read_only_vars = {}
_composed_schemas = {}
@classmethod
@convert_js_args_to_python_args
def _from_openapi_data(cls, *args, **kwargs): # noqa: E501
"""JobSearchResponseAggregierungenPlzebene2 - a model defined in OpenAPI
Keyword Args:
_check_type (bool): if True, values for parameters i... | |
<reponame>RoryKurek/thermo<filename>thermo/phases/iapws_phase.py
# -*- coding: utf-8 -*-
'''Chemical Engineering Design Library (ChEDL). Utilities for process modeling.
Copyright (C) 2019, 2020 <NAME> <<EMAIL>>
Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated... | |
<filename>main/main.py
# src: https://github.com/facebookresearch/DrQA/blob/master/scripts/reader/train.py
import sys
sys.path.append(".")
sys.path.append("..")
import os
import json
import torch
import logging
import subprocess
import argparse
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
i... | |
<reponame>mklewitz-kisura/dotfiles<gh_stars>0
"""
The :mod:`jedi.api.classes` module contains the return classes of the API.
These classes are the much bigger part of the whole API, because they contain
the interesting information about completion and goto operations.
"""
import warnings
import re
from jedi._compatibi... | |
late, or haven't shipped
on_time = orders_due[np.where((orders_due[:,env.ob_indices['shipped']]==1) &
(orders_due[:,env.ob_indices['on_time']]==1))].shape[0]
late = orders_due[np.where((orders_due[:,env.ob_indices['shipped']]==1) &
(orders_due[:,env.ob_indices['on_time']]==-1))].shape[0]
not_shipped = orders_due[n... | |
<gh_stars>10-100
# AUTORIGHTS
# ---------------------------------------------------------
# Copyright (c) 2017, <NAME>
#
# This file is part of the VCOCO dataset hooks and is available
# under the terms of the Simplified BSD License provided in
# LICENSE. Please retain this notice and LICENSE if you use
# this fil... | |
+ kDrawPointTag + "BCPMarks = 0")
exec("params." + kDrawPointTag + "PointLabels = 0")
exec("params." + kShowMetaTag + "Outline = 0") # shows filled outline in lower right of meta data area under glyph outline.
exec("params." + kShowMetaTag + "Name = 1")
exec("params." + kShowMetaTag + "BBox = 0")
exec("p... | |
0x111][0][0x300a, 0x11a][1][0x300a, 0x11c].value
# ssd = data[0x300a, 0xb0][2][0x300a, 0x111][0][0x300a, 0x130].value/10
# energy = data[0x300a, 0xb0][2][0x300a, 0x111][0][0x300a, 0x114].value
# leaf_bou = data[0x300a, 0xb0][2][0x300a, 0xb6][2][0x300a, 0xbe].value
# depth = 100 - ssd
# leaf_pos = np.reshape(lea... | |
# -*- coding: utf-8 -*-
"""
Tencent is pleased to support the open source community by making BK-BASE 蓝鲸基础平台 available.
Copyright (C) 2021 THL A29 Limited, a Tencent company. All rights reserved.
BK-BASE 蓝鲸基础平台 is licensed under the MIT License.
License for BK-BASE 蓝鲸基础平台:
----------------------------------------------... | |
data features
#
def Overall_Correlations(self, save_folder_path, Font_Size, colours):
# create the correlation dataset (subset from the original data)
self.corr_df = DataUpload.recall_dataframe(1)[['dx', 'dx_type', 'age', 'sex','localization']]
self.header_list = self.corr_df.columns.values.tolist()
self.he... | |
property constructs an averaging operator that maps scalar
quantities from cell centers to edge. This averaging operator is
used when a discrete scalar quantity defined cell centers must be
projected to edges. Once constructed, the operator is stored
permanently as a property of the mesh. *See notes*.
Returns
--... | |
<gh_stars>0
import xml.etree.cElementTree as ET
import time
import datetime
import random
from pathlib import Path
from zipfile import ZipFile
import os
import copy
from shutil import rmtree
import string
import json
from components.dataconnection.index import get_resource_description, get_resource_metadata
from x5gon... | |
"""Test bpack field descriptors."""
import sys
import enum
from typing import List
import pytest
import bpack
from bpack.descriptors import get_field_descriptor
class TestFieldFactory:
@staticmethod
def test_base():
bpack.field(size=1, offset=0, signed=False, default=0, repeat=1)
@staticmethod
def test_fiel... | |
import demistomock as demisto # noqa: F401
from CommonServerPython import * # noqa: F401
question_data = {
"AssessmentA": [{
"name": "<NAME>", # noqa: E501
"question": "You have effective organisational security management led at board level and articulated clearly "
"in corresponding policies.", # noqa: E501
"a... | |
v)][i + 1] - 1] > 0:
decomp.add_edge(v, u)
edge_add = True
if not edge_add:
if level_i != []:
level_u = 1e9 #g.number_of_nodes()
v_u = -1
for v in decomp.nodes(data=True):
if v[0] == u:
continue
if out[s[min(u, v[0])][max(u, v[0])][v[1]['level']] - 1] > 0:
if level_u > v[1]['level']:
level_u = v[1]['level']... | |
<reponame>dllehr-amd/pytorch
# Owner(s): ["module: sparse"]
import torch
import warnings
import unittest
import random
import itertools
from torch.testing import get_all_complex_dtypes, get_all_fp_dtypes, make_tensor
from torch.testing._internal.common_cuda import SM53OrLater, SM80OrLater, TEST_CUSPARSE_GENERIC
from t... | |
#!/usr/bin/env python3
import json
from time import time, sleep # only use the function that gives the current time
import random
import sys
from cscore import CameraServer, VideoSource, UsbCamera, MjpegServer
from networktables import NetworkTablesInstance
import ntcore
import numpy as np
import cv2
from enum import... | |
graph.plot(xm,yp,'r')
plt.setp(graph.get_xticklabels(), rotation=30, ha="right")
ln1 = len(xm)
if ln1<10:
graph.xaxis.set_major_locator(plt.LinearLocator(numticks=ln1))
graph.yaxis.set_major_locator(plt.LinearLocator(numticks=ln1))
else:
graph.xaxis.set_major_locator(plt.MaxNLocator(10))
graph.yaxis.set_major_l... | |
<filename>implementation.py
from heapq import heappush, heappop
from itertools import count
from itertools import permutations
from collections import defaultdict
from itertools import chain, combinations
from functools import reduce
import copy
from collections import deque
import signal
class GracefulKiller:... | |
from cloudshell.shell.core.driver_context import ResourceCommandContext, AutoLoadDetails, AutoLoadAttribute, \
AutoLoadResource
from collections import defaultdict
class LegacyUtils(object):
def __init__(self):
self._datamodel_clss_dict = self.__generate_datamodel_classes_dict()
def migrate_autoload_details(self... | |
)
# @TODO implement objectivum_formato as default
# commune.add_argument(
# '--codex-de',
# help='Generate documentation of dictionaries',
# # metavar='',
# dest='codex_de',
# # const=True,
# nargs='?'
# )
commune.add_argument(
'--punctum-separato-de-resultatum',
help='Character(s) used as separator for ... | |
# Copyright (c) 2017-2021 <NAME> (<EMAIL>)
"""
@author: <NAME>
CG model selection via MAP-estimation using mean parameters.
"""
import numpy as np
from numpy import ix_
from cgmodsel.base_solver import BaseCGSolver
# pylint: disable=W0511 # todos
# pylint: disable=R0914 # too many locals
class MAP(BaseCGSolver):
... | |
# -*- coding:UTF-8 -*-
from copy import deepcopy
from getpass import getuser as GETPASSgetuser
from cdms2 import open as CDMS2open
from inspect import stack as INSPECTstack
import json
from numpy import array as NUMPYarray
from os import environ as OSenviron
from os.path import join as OSpath__join
from sys import exi... | |
Co., Ltd.",
"0016DC": "ARCHOS",
"0016DD": "Gigabeam Corporation",
"0016DE": "FAST Inc",
"0016DF": "Lundinova AB",
"0016E0": "3Com Ltd",
"0016E1": "SiliconStor, Inc.",
"0016E2": "American Fibertek, Inc.",
"0016E3": "ASKEY COMPUTER CORP.",
"0016E4": "VANGUARD SECURITY ENGINEERING CORP.",
"0016E5": "FO... | |
# quad1m = ax.pcolormesh(kzg_interp, -1 * kxg_interp, PhDen_interp_vals[:-1, :-1], norm=colors.LogNorm(vmin=1e-3, vmax=vmax), cmap='inferno')
# else:
# quad1 = ax.pcolormesh(kzg_interp, kxg_interp, PhDen_interp_vals[:-1, :-1], vmin=vmin, vmax=vmax, cmap='inferno')
# quad1m = ax.pcolormesh(kzg_interp, -1 * kxg_interp... | |
= self.RegionPlaceholders.query.all()
for region in region_placeholders:
regions_maps.update(region.countries)
# getting country groups from database and insert into the country_groups list
customer_loc = ''
location_list = json_template["conductor_solver"]["locations"]
for location_id, location_info in location... | |
from abc import abstractmethod
import pandas as pd
from aistac.components.abstract_component import AbstractComponent
from aistac.components.aistac_commons import DataAnalytics
from ds_discovery.components.commons import Commons
from ds_discovery.components.discovery import DataDiscovery, Visualisation
__author__ = '... | |
*xs): (k, *tuple(df[k].dtype.type(x) for x in xs)))
.T.set_index([k for k, f in stats + prototypes], append=True).T
# Transpose for fixed width (stats) and variable height (input cols)
# - [Nope: transposing cols mixes dtypes such that mixed str/int/float undermines display.precision smarts]
# .T
)
def _df_quant... | |
if not annot_obj:
self.logger.error('Cannot conver this string to annotation object: '+str(annotation))
return False
#### retreive the annotation object
brsynth_annot = None
obj_annot = sbase_obj.getAnnotation()
if not obj_annot:
sbase_obj.setAnnotation(libsbml.XMLNode.convertStringToXMLNode(self._defaultBRSynth... | |
<reponame>Andrew-Brown1/Smooth_AP
# repo originally forked from https://github.com/Confusezius/Deep-Metric-Learning-Baselines
################# LIBRARIES ###############################
import warnings
warnings.filterwarnings("ignore")
import numpy as np, pandas as pd, copy, torch, random, os
from torch.utils.data i... | |
nlst, ndays,
ntriads, nlags)
------------------------------------------------------------------------
"""
try:
bw_eff
except NameError:
raise NameError('Effective bandwidth must be specified')
else:
if not isinstance(bw_eff, (int, float, list, NP.ndarray)):
raise TypeError('Value of effective bandwidth m... | |
nocc: , : , : ].transpose(2,0,3,1)))
if (fully_ic):
numpy.save(intfolder+"W:eaaa", numpy.asfortranarray(eris['ppaa'][nocc: , ncor:nocc, : , : ].transpose(0,2,1,3)))
numpy.save(intfolder+"W:caaa", numpy.asfortranarray(eris['ppaa'][nfro:ncor, ncor:nocc, : , : ].transpose(0,2,1,3)))
# 2 "E"
numpy.save(intfolder+"W:ee... | |
from sage.misc.flatten import flatten
from sage.ext.fast_callable import fast_callable
from sage.rings.semirings.non_negative_integer_semiring import NN
from sage.rings.real_mpfr import RealField
from sage.misc.functional import numerical_approx as N
from sage.functions.log import exp
from sage.functions.log import log... | |
# coding=utf-8
# *** WARNING: this file was generated by the Pulumi Terraform Bridge (tfgen) Tool. ***
# *** Do not edit by hand unless you're certain you know what you are doing! ***
import warnings
import pulumi
import pulumi.runtime
from typing import Any, Mapping, Optional, Sequence, Union
from .. import _utilitie... | |
""" A module containing the models to be trained on gene expression data """
import copy
import itertools
import pickle
import sys
from abc import ABC, abstractmethod
from collections import OrderedDict
from typing import Union, Iterable, Tuple, Any
import neptune.new as neptune
import numpy as np
import sklearn.line... | |
<reponame>Flav-STOR-WL/py-pure-client
# coding: utf-8
"""
FlashArray REST API
No description provided (generated by Swagger Codegen https://github.com/swagger-api/swagger-codegen)
OpenAPI spec version: 2.10
Generated by: https://github.com/swagger-api/swagger-codegen.git
"""
from __future__ import absolute_i... | |
}
The main payload of the return data can be found inside the 'updates'
key, containing a list of dictionaries. This list is always returned
in descending date order. Each item may contain different fields
depending on their update type. The primary_entity key represents the
main Shotgun entity that is associated... | |
<filename>op3/envs/blocks/mujoco/block_occlusions.py
import os
import pdb
import numpy as np
import shutil
import pickle
import cv2
import matplotlib
matplotlib.use('Agg')
import matplotlib.pyplot as plt
from argparse import ArgumentParser
import op3.envs.blocks.mujoco.utils.data_generation_utils as dgu
from op3.util.... | |
<filename>y/google-cloud-sdk/lib/googlecloudapis/compute/alpha/compute_alpha_client.py
"""Generated client library for compute version alpha."""
# NOTE: This file is autogenerated and should not be edited by hand.
from googlecloudapis.apitools.base.py import base_api
from googlecloudapis.compute.alpha import compute_a... | |
one value per subject as in self.subject_names_raw -- #
# -- NOTE: self.online_eval_XX are lists and conventionally the values are stored in lists. -- #
# -- Here we store the values as numpys and transform self.online_eval_XX to a numpy later on -- #
# -- for the calculation per subject, thus we need numpy since th... | |
print('Finised computing mol2cell accuracies.')
# Saves results in self.df_c2m for top5 accuracy
self.eval_cell2mol_accuracy(mode = mode)
self.get_acc_df_cell2mol()
print('Finished computing cell2mol accuracies.')
# Run KS tests
print('Running KS test...')
self.run_ks_one_vs_all(n_cores,mode=mode)
print('Finish... | |
range(0, len(x1), 1):
# If index of element in mask list form 'outliers_filtering' then replace with median
#if i in mask_proc:
# print('Replace with median!')
req_data = np.array([x1[i], y1[i]]).reshape(1, -1)
# Getting number of neighbours
num_nn = vector_start_tree.query_radius(req_data, r=radius, count_only=T... | |
== b""
assert doc_enc["h"]["data"] == b"header"
assert doc_dec["h"] == "686561646572"
assert doc_enc["t"]["len"] == b""
assert doc_enc["t"]["data"] == b"0210"
assert doc_dec["t"] == "0210"
assert doc_enc["p"]["len"] == b""
assert doc_enc["p"]["data"] == b"0000000000000000"
assert doc_dec["p"] == "000000000000... | |
created_ts = datetime_to_timestamp(instance.created)
for stat in stats:
if stat['from'] >= created_ts and stat['to'] - created_ts < hour / 2 and 'value' not in stat:
stat['value'] = 0
return Response(stats, status=status.HTTP_200_OK)
@detail_route()
def calculated_usage(self, request, uuid):
"""
Find max or mi... | |
rebooting info printed to the console
logger.info('==== Waiting for messages in rebooting ...')
d1 = Dialog([
['{} login: '.format(self.sm.patterns.chassis_hostname),
'sendline({})'.format(self.sm.patterns.chassis_username),
None, True, False],
['Password:',
'sendline({})'.format(self.sm.patterns.chassis_passwo... | |
key
ket_size = H_sizes[ket_key]
bra_size = H_sizes[bra_key]
self.rho_shapes[key] = (ket_size,bra_size)
def load_mu(self):
"""Load the precalculated dipole overlaps. The dipole operator must
be stored as a .npz file, and must contain at least one array, each with three
indices: (new manifold eigenfunction, ol... | |
incre(0)
len(m) == 2 and abs(m[0] - m[1]) == 0 and m[0] not in self.bonus_winds and incre(3)
len(m) == 2 and abs(m[0] - m[1]) == 1 and incre(2 if m[0] % 9 > 0 and m[1] % 9 < 8 else 1)
len(m) == 2 and abs(m[0] - m[1]) == 2 and incre(1)
len(m) == 3 and incre(5 if m[0] == m[1] else 4)
return geo_vec
def qh_type(se... | |
# -*- coding: utf-8 -*-
try:
from unittest.mock import patch
except ImportError:
from mock import patch
from odoo.tests import common
def strip_prefix(prefix, names):
size = len(prefix)
return [name[size:] for name in names if name.startswith(prefix)]
class TestOnChange(common.TransactionCase):
def setUp(self)... | |
be on the X-axis in comparative plots) in comparative analysis plots is determined by the order in PredictionSets
assert(take_lowest > 0 and (int(take_lowest) == take_lowest))
assert(0 <= burial_cutoff <= 2.0)
assert(stability_classication_experimental_cutoff > 0)
assert(stability_classication_predicted_cutoff > 0)... | |
if 64 - 64: i11iIiiIii
if 65 - 65: O0 / iIii1I11I1II1 % OoooooooOO - i1IIi
if 73 - 73: II111iiii
if 22 - 22: I1IiiI * Oo0Ooo / OoO0O00 . OoOoOO00 . o0oOOo0O0Ooo / I1ii11iIi11i
if 48 - 48: oO0o / OOooOOo / I11i / Ii1I
if 48 - 48: iII111i % IiII + I1Ii111 / ooOoO0o * Ii1I
if 46 - 46: ooOoO0o * I11i - OoooooooOO
if 30 - 3... | |
2)).permute(1, 0, 2)
x = self.inner_tf(x)
x = einops.rearrange(x, " inner b (outer mod k) -> b outer inner mod k", outer=self.outer, mod=self.mod,
b=self.batch)
return x
class mod_att(nn.Module):
def __init__(self, dmodel, pos, inner, outer, modalities, num_layers=1, heads=8):
super().__init__()
self.pos = pos
... | |
#!/usr/bin/env python3
# PYTHON_ARGCOMPLETE_OK
from __future__ import division, print_function
# viability imports
import pyviability as viab
from pyviability import helper
from pyviability import libviability as lv
from pyviability import tsm_style as topo
# model imports
import examples.AWModel as awm
import examp... | |
checked.")
print("Apps in",
[d.replace(os.environ["HOME"], "~") for d in app_dirs], "\n")
maxlen = max(len(x.replace(os.environ["HOME"], "~"))
for x in app_dirs)
if sum(apps_check["cask"].values()) > 0:
print("Installed by Cask:")
for d in app_dirs:
if apps_check["cask"][d] == 0:
continue
print("{0:<{1}s} : {... | |
centers good"
print "\n%s result:" % algo, dump_json(a1)
# if we want to return the model view like the browser
if 1==0:
# HACK! always do a model view. kmeans last result isn't good? (at least not always)
a = self.kmeans_view(model=a1['model']['_key'], timeoutSecs=30)
verboseprint("\n%s model view result:" % al... | |
request.GET.get('sid', None)
from_str = request.GET.get('from', None)
to_str = request.GET.get('to', None)
from_t = request.GET.get('from_t', None)
to_t = request.GET.get('to_t', None)
# Set values from POST and GET
edit = request.POST.get('edit', None)
if not edit:
edit = request.GET.get('edit', None)
data... | |
= self.grid(processor)
Nc = g.Ncells()
cdata = self.celldata(processor)
for i in range(Nc):
fp.write("%.6f %.6f %.6f %.6f %d %d %d %d %d %d %d %d %d %d %.6f %.6f %.6f\n"%tuple(cdata[i,:]))
fp.close()
def Nk(self,proc):
return self.celldata(proc)[:,4].astype(int32)
def Nke(self,proc):
return self.edgedata(pro... | |
# Why: #7737 in Alexa global
'http://www.navy.mil/',
# Why: #7738 in Alexa global
'http://www.mg.gov.br/',
# Why: #7739 in Alexa global
'http://gizmodo.uol.com.br/',
# Why: #7740 in Alexa global
'http://www.psychcentral.com/',
# Why: #7741 in Alexa global
'http://www.ultipro.com/',
# Why: #7742 in Alexa globa... | |
if bollo:
_bollo = db(db.bolli.descrizione=="Fattura").select().first()["valore"]
importo_totale += float(_bollo)
importo_totale_da_salvare = importo_totale +imposta_iva
if not "/" in pagamento:
importo_totale = Money(str(importo_totale),"EUR")
importo_totale = importo_totale.format("it... | |
<reponame>wbiker/rules_dotnet<filename>dotnet/stdlib.net/net472/generated.bzl
load("@io_bazel_rules_dotnet//dotnet/private:rules/stdlib.bzl", "net_stdlib")
def define_stdlib(context_data):
net_stdlib(
name = "accessibility.dll",
dotnet_context_data = context_data,
ref = "@Microsoft.NETFramework.ReferenceAssemblies... | |
#
# Copyright 2021 Amazon.com, Inc. or its affiliates. All Rights Reserved.
# Copyright (C) 2018-2021 UAVCAN Development Team <uavcan.org>
# This software is distributed under the terms of the MIT License.
#
"""
jinja-based :class:`~nunavut.generators.AbstractGenerator` implementation.
"""
import datetime
import io
i... | |
<reponame>ravwojdyla/transform<filename>tensorflow_transform/saved/saved_transform_io.py
# Copyright 2017 Google Inc. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# ... | |
60] 4,840
Conv2d-136 [-1, 40, 44, 60] 4,840
BatchNorm2d-137 [-1, 40, 44, 60] 80
Conv2d-138 [-1, 40, 44, 60] 4,840
Conv2d-139 [-1, 40, 44, 60] 4,840
BatchNorm2d-140 [-1, 40, 44, 60] 80
Dropout2d-141 [-1, 40, 44, 60] 0
EDAModule-142 [-1, 450, 44, 60] 0
EDANetX3Block-143 [-1, 450, 44, 60] 0
Conv2d-144 [-1, 11, 44... | |
###################################################################
# Melissa #
#-----------------------------------------------------------------#
# COPYRIGHT (C) 2017 by INRIA and EDF. ALL RIGHTS RESERVED. #
# #
# This source is covered by the BSD 3-Clause License. #
# Refer to the LICENCE file for further informatio... | |
bazbiz():
z = foobar()
lala
''')
differ.initialize(code1)
differ.parse(code2, parsers=2, copies=1)
differ.parse(code1, parsers=2, copies=1)
def test_one_call_in_function_change(differ):
code1 = dedent('''\
def f(self):
mro = [self]
for a in something:
yield a
def g(self):
return C(
a=str,
b=self,
)
... | |
<reponame>WildMeOrg/wbia-utool
# -*- coding: utf-8 -*-
"""
TODO: box and whisker
http://tex.stackexchange.com/questions/115210/boxplot-in-latex
"""
from __future__ import absolute_import, division, print_function, unicode_literals
from six.moves import range, map, zip
import os
import re
import textwrap
try:
import n... | |
import threading
import time
import logging
import signal
import subprocess
import Queue
import collections
import concurrent.futures
import shlex
import json
import tempfile
import os
import re
import builder.futures
from builder.util import arrow_factory as arrow
import builder.build as build
import networkx as nx
... | |
"goh-lng": "Lombardic",
"goi": "Gobasi",
"goj": "Gowlan",
"gol": "Gola",
"gon": "Gondi",
"goo": "Gone Dau",
"gop": "Yeretuar",
"goq": "Gorap",
"gor": "Gorontalo",
"got": "Gothic",
"gou": "Gavar",
"gow": "Gorowa",
"gox": "Gobu",
"goy": "Goundo",
"goz": "Gozarkhani",
"gpa": "Gupa-Abawa",
"gpn": "Taiap",
... | |
<reponame>ska-telescope/csp-lmc-prototype<filename>csplmc/CspMaster/CspMaster/CspMaster.py
# -*- coding: utf-8 -*-
#
# This file is part of the CspMaster project
#
#
#
# Distributed under the terms of the GPL license.
# See LICENSE.txt for more info.
""" CspMaster Tango device prototype
CSPMaster TANGO device class f... | |
<filename>fcts.py
import sys, os, time, datetime, pandas, numpy, pickle, logging, py7zr, base64, io, random
from functools import wraps
from matplotlib import pyplot as plt
def process_figure(out_path, plt):
"""Show / save / serrialize plot"""
if out_path == 'base64':
plt.tight_layout()
out_path = serial... | |
value, data))
elif comparator == '>':
ok = any(map(lambda x: x is not None and x > value, data))
elif comparator == '<=':
ok = any(map(lambda x: x is not None and x <= value, data))
elif comparator == '>=':
ok = any(map(lambda x: x is not None and x >= value, data))
elif comparator in ('!=', '<>'):
ok = value n... | |
order='F', copy=copy)
def dot(m1, m2, target = None, beta = 0., alpha = 1.):
"""
Find the dot product between m1 and m2 and store in target:
target = beta*target + alpha*(m1 m2)
If no target is given, it will be created automatically, but not
initialized -- so beta should be left at its default value zero.
"""
... | |
<reponame>lsd-maddrive/adas_system<gh_stars>0
from utils.augmentations import (
Albumentations,
augment_hsv,
letterbox,
random_perspective,
)
from utils.general import non_max_suppression, scale_coords
import torch
import cv2
import numpy as np
from torch import nn
import random
import pandas as pd
import matplotl... | |
__init__(
self, symbolic: str = None, nr_components=None,
unit_depth_in_bit: int = None, location: _Location = None):
#
super().__init__(
alignment=_Alignment(unpacked=_DataSize.FLOAT32),
symbolic=symbolic,
nr_components=nr_components,
unit_depth_in_bit=unit_depth_in_bit,
location=location
)
def expand(self... | |
# Deep Learning optimization functions
#
# <NAME>, 2021
# <EMAIL>
import torch
import uproot
import numpy as np
import sklearn
import psutil
from termcolor import colored,cprint
from matplotlib import pyplot as plt
import pdb
from tqdm import tqdm, trange
import torch.optim as optim
from torch.autograd import Vari... | |
'
'output as \'8 20 2\'',
argstr='-roisel %s')
debug = traits.Bool(
desc='print debug information',
argstr='-debug')
quiet = traits.Bool(
desc='execute quietly',
argstr='-quiet')
nomeanout = traits.Bool(
desc='Do not include the (zero-inclusive) mean among computed stats',
argstr='-nomeanout')
nobriklab = t... |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.