sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
22905065d03e1a388fb26331db544da5a8b5a58f61ad5adfe9a55a47bb9092af | Python | 9,841 | 417 | from datetime import datetime
from typing import (
Annotated,
Literal,
Optional,
)
from pydantic import (
Field,
RootModel,
)
from galaxy.schema.fields import (
DecodedDatabaseIdField,
EncodedDatabaseIdField,
)
from galaxy.schema.schema import Model
SOURCE_TYPE = Literal["tool"]
class C... |
e0713f1f04a1eee9bc2519fddd765dcc3ccab9a91a5f93f6bc9d54b3f2bb810c | Python | 9,841 | 245 | # Licensed to the Apache Software Foundation (ASF) under one
# or more contributor license agreements. See the NOTICE file
# distributed with this work for additional information
# regarding copyright ownership. The ASF licenses this file
# to you under the Apache License, Version 2.0 (the
# "License"); you may not u... |
231c0120c20eeeaec67134c0fcf4cb0913eeb1d7b7c717a62d08ac040e2af093 | Python | 9,843 | 250 | # -*- coding:utf-8 -*-
__author__ = 'yangjian'
"""
"""
import random
import time
import numpy as np
import pandas as pd
from sklearn import manifold
from sklearn.metrics import roc_auc_score, mean_squared_error, f1_score
from deeptables.datasets import dsutils
from deeptables.models import deeptable, deepmodel
from ... |
da4156bb96900eeca46b92fcde3bede0e685a1c9d14bd9b7f4271a51278f983c | Python | 9,844 | 263 | # Copyright (c) Meta Platforms, Inc. and affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
# pyre-strict
from typing import final
import pandas as pd
from ax.adapter.base import Adapter
from ax.analysis.analysis import Analysis
f... |
0c0e9cd027485ca1bc989ef0e19a32bd22b5e7318e15d051643d1ebd4f14d4b9 | Python | 9,855 | 351 | #! /usr/bin/env python
"""
# -----------------------------------------------------------------------
#
# localization.py
#
# by Joerg Menche
# Last Modified: 2014-12-06
#
# This code determines the network-based distance and sepration for
# two given sets of nodes on given network as described in
#
# Uncovering Dise... |
d5dac3b36a24f737b394b505d692582246e62148bd7117e92ff24048ef89ec7e | Python | 9,855 | 350 | # -*- coding: utf-8 -*-
"""
Inteface to Illastik for pixel classification / object detection
This module allows to integrate ilastik into the *ClearMap* pipeline.
To use ilastik within *ClearMap* use the followng steps:
* start ilastik interface (e.g. manually or using
:func:`~ClearMap.Imageprocessing.Ilastik... |
d1feebfcc7c6195f4ab226d88521ef35c9f1f76e46cdb27caf247f4ecf51825c | Python | 9,856 | 239 | import functools
import random
import networkx as nx
import numpy as np
import torch
import torch.nn as nn
from cogdl.utils import split_dataset_general
from .. import BaseModel
class PatchySAN(BaseModel):
r"""The Patchy-SAN model from the `"Learning Convolutional Neural Networks for Graphs"
<https://arxiv... |
ca2569844d5f6de5606be25a2c0d636361bcb5e92f549829630f6f8e60d245ac | Python | 9,859 | 253 | """
Ring attractor simulation. Analysis library (:mod:`lib_analysis`)
=================================================================
.. currentmodule:: lib_analysis
:platform: Linux
:synopsis: module for analyzing simulated data from the ring attractor network.
.. moduleauthor:: Jose M. Esnaola-Acebes <josem... |
3d483dc7238280a75ba6961281a6fb55b74eea5a72c79e8e937444e3bf90a9ed | Python | 9,866 | 235 | # -*- coding: utf-8 -*-
import numpy as np
from sklearn.utils.random import sample_without_replacement
from sklearn.metrics import auc, precision_recall_curve, roc_curve
from sklearn.svm import OneClassSVM
import argparse
import load_data
import networkx as nx
from graph_autoencoder import *
import torch
im... |
45d961b79a8945fe3bb749fb73bba1ca64ca1bc5838ea01bd36fd82e75fd53a4 | Python | 9,867 | 236 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
@author: chris3arcadia
@description: template script to generate transfer lists for acid/base computing
@created: Thr Feb 28 2019
"""
# Libraries
import numpy
import chemcpupy
from chemcpupy import Plating, Containers
from acidbase_network import AcidBaseNetwork
impo... |
8a87b541fe3aab08c1ee81641057c75b24bf0e6f32381970193817eacea7ad91 | Python | 9,872 | 241 | import sys
from collections.abc import Sequence
if sys.version_info >= (3, 12):
from typing import override
else:
from typing_extensions import override
import numpy as np
import tensorflow as tf
from hidten.tf.emitter.categorical import (T_shapelike, T_TFTensor,
TFC... |
75098693043fb7c951be8b9fcf37d9ea611472b38ba92483f398138e48347957 | Python | 9,877 | 247 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Spatial Factorization- Hybrid version with both spatial and nonspatial factors
Created on Wed Apr 21 17:02:48 2021
@author: townesf
"""
import numpy as np
import tensorflow as tf
from os import path
from math import ceil
from sklearn.decomposition import TruncatedSV... |
9cee461ef07987689b321bcb54dc8445f88daf3bc76e21c3755afcee5f0640ad | Python | 9,878 | 210 | import numpy as np
import common
def pre_fr_list():
return np.array([0.0001*i for i in range(50)]) #the list of presynaptic firing rates
def up_down_parameters(state):
"""
set the frequency of up and down states
"""
if state == 'down':
g_index = 1
elif state == 'up':
g_index =... |
cff9271d786ed17b43e1ca16eec0930f14169c00d682117eb6b5d24cd6d4a5ef | Python | 9,878 | 222 | import numpy as np
import torch
from visual import visual_plt
from visual import visual_visdom
from utils import get_data_loader,checkattr
####--------------------------------------------------------------------------------------------------------------####
####-----------------------------####
####----CLASSIFIER EV... |
843ca8a07ce2b06fe7efda5e6edbbc4e5002ae89d05bc9aa3c45b2dfa41053ea | Python | 9,888 | 301 | import abc
import logging
import os
import re
from collections.abc import Callable
from typing import (
Optional,
)
from galaxy.datatypes.binary import Binary
from galaxy.datatypes.data import (
get_file_peek,
Text,
)
from galaxy.datatypes.metadata import MetadataElement
from galaxy.datatypes.protocols imp... |
3aefae5b0edbae1e7225001498c8debc1a931670b431545985dfbcd4abe14705 | Python | 9,890 | 246 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Spatial Factorization- Hybrid version with both spatial and nonspatial factors
Created on Wed Apr 21 17:02:48 2021
@author: townesf
"""
import numpy as np
import tensorflow as tf
from os import path
from math import ceil
from sklearn.decomposition import TruncatedSV... |
905000641940220ed7721eab8a08ccaa6fe5939efce3de3368d3c3745018dcc0 | Python | 9,896 | 247 | # Copyright (c) Meta Platforms, Inc. and affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
# pyre-strict
import numpy as np
from ax.analysis.plotly.surface.contour import compute_contour_adhoc, ContourPlot
from ax.core.arm import ... |
a8cb2abd4b4a84c521492fc9e3778f81375c5358c52c565c3b053b97c2a62d3a | Python | 9,896 | 257 | from brian2.core.namespace import get_local_namespace
from brian2 import Synapses, Function
from brian2.input.spikegeneratorgroup import SpikeGeneratorGroup
from brian2lava.utils.const import HARDWARE
MAX_SYNAPSES = 2147483647
def spike_queue(self, source_start, source_end):
"""
TODO
Parameters
----... |
ae64faf5442a2d0ec75d72669966320ea051c71e0f4a9b66adecbfe3b0f88ff1 | Python | 9,905 | 190 | #!/usr/bin/env python
#
# Copyright (c) 2017 10X Genomics, Inc. All rights reserved.
#
import cellranger.analysis.io as analysis_io
import cellranger.analysis.constants as analysis_constants
import cellranger.h5_constants as h5_constants
import cellranger.io as cr_io
import cellranger.analysis.stats as analysis_stats
... |
7cc21e4aea80ef842855b7f66b04003e3875646f9f9a9eda8316f7dc58194122 | Python | 9,907 | 317 | import contextlib
import os
import shutil
import subprocess
import typing
from pathlib import Path
from tempfile import TemporaryDirectory, mkdtemp
from . import _mpi
from ._fs import get_cache_path, read_cache, update_cache
from ._hash import get_package_hash, get_package_mods_hash
from .exceptions import *
if typin... |
c044e2b62b3cf21e351576a1cb967f3370f33bd032f042dd7865bb3d07e53841 | Python | 9,907 | 343 | """Main flow of the eComp experiment."""
# %%
import datetime
import numpy as np
from psychopy import core, event, monitors, visual
from ecomp_experiment.define_eyetracking import (
setup_eyetracker,
start_eye_recording,
stop_eye_recording,
)
from ecomp_experiment.define_routines import (
display_blo... |
2dee6375fceb2f8fc8ee29a8774474a82c081b824cd925aacff19aeaf7a3170a | Python | 9,908 | 312 | ## ------------------------------------------------------------------------
## ------------------------------------------------------------------------
##
##
# ~/opt/anaconda3/envs/mrcnn/bin/python
# /home/jorgeassis/miniconda3/envs/mrcnn/bin/python
## Erase memory objects
for element in dir():
if element[0:2] !... |
8055d32cbca6a113df22386e8648ab2e421c0f3dc85c9a2eff940c89079aa5b4 | Python | 9,912 | 324 | from math import floor
import numpy as np
import pandas as pd
import pynndescent
from sklearn.metrics import adjusted_rand_score
def _purity(label1, label2):
"""Calculate purity score."""
# contingency table
ct = pd.crosstab(label1, label2)
purity = ct.apply(max, axis=1).sum() / label1.size
retur... |
0af0b3585f85112a3b8fbd68deed89a8f48d6137578623b24661fd159a2c319b | Python | 9,915 | 335 | import json
from enum import Enum
from typing import (
Annotated,
Any,
Literal,
Optional,
Union,
)
from pydantic import (
AliasChoices,
ConfigDict,
Field,
field_validator,
HttpUrl,
Json,
TypeAdapter,
UUID4,
)
from galaxy.schema.fields import DecodedDatabaseIdField
f... |
8671e5739e87d99bf74c1ffe0d33bf7a3b3024c97173218b74d73a28a9da1f22 | Python | 9,918 | 216 | """
General functions for analyzing the memory neural system
"""
import numpy as np
import roblib
import settings
from pathlib import Path
import pandas as pd
from utils import load_config
from sklearn.metrics import roc_auc_score
from training import get_test_time_point
import os
def get_intersect(x, y, ... |
dd0d57495cda611cddeef5d9903b0bcff19b9eeadbe30a911720f218ce71faea | Python | 9,920 | 237 | #author: Dimitris Spathis (ds806@cl.cam.ac.uk)
"""
what: load individual feature CSVs of Fenland's repeats cohort, concat, split to train/test, normalize and do ML
difference from task1: here we focus on the repeats and create regression tasks based on FII delta
in: CSVs with extracted features, IDs, metadata
out: t... |
47985f9c8724020b562ede80d7c95212310c0a86d6b91ebedb05eaed638afcd7 | Python | 9,921 | 209 | # Implementation based on the following publication of Tiago P. Peixoto
# Nonparametric Bayesian inference of the microcanonical stochastic block model
# full version with scipy
import math
from scipy.special import binom
from .peixotos_flat_sbm_full import ModelLikelihoodOfFlatMicrocanonicalDegreeCorrectedSbm
from... |
41beb758b1cc7b12c3159155ca9b9fc8dd6cc4526144afc49fbb6f13057c80c4 | Python | 9,925 | 230 | """
Provide plotting functions for genomic data types.
Many common data types used in genomics research are supported. Including, but
not limited to, :class:`Hi-C <fanc.plotting.HicPlot>`,
:class:`bed <fanc.plotting.GenomicFeaturePlot>`,
:class:`bigwig <fanc.plotting.BigWigPlot>`
and :class:`gene (GTF) <fanc.plotting.... |
07f15f10bf035b067687a1f16cbb35303b959e50ecaf8fb4066575a295cbb737 | Python | 9,929 | 282 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Wed Mar 11 13:56:08 2020
@author: amelie
"""
from brian2 import *
from scipy import signal
from FEF_full3_alternatec import *
from LIP_full_alternatec import *
from itertools import *
from joblib import Parallel, delayed
import multiprocessing
def sav... |
eb03e873d3b6348f1a79bb9a3e92e15df2cc615940561d8d9eec5a36db0574b0 | Python | 9,929 | 328 | # -*- coding: utf-8 -*-
"""Docking_MC_Parallel.ipynb
Automatically generated by Colaboratory.
Original file is located at
https://colab.research.google.com/drive/13sohHmkOWAWa5QIEAjIESIqJ8IZkOcHi
"""
import os
import sys
from pyrosetta import *
from rosetta import *
from rosetta.protocols.rigid im... |
2bf90faa422c337425a24a1d5706054db376de90bd2c4eb255ec5ed6fe0a5112 | Python | 9,930 | 458 |
from nl_expr.utils.orderedset import OrderedSet
from nl_expr.logic.expression_processing import extract_logic_free_variables
from nl_expr.logic.transformations import (
CheckConjunctiveQueryWithNegation,
GuaranteeConjunction,
ExtractConjunctiveQueryWithNegation,
PushExistentialsDown,
RemoveExistent... |
497302111d5379df9c149263b03b42ee70602c1ec3e9885bd9163681718c0804 | Python | 9,940 | 261 | import os
import os.path as osp
import numpy as np
import torch
import torch.nn as nn
import torch.nn.functional as F
from .. import BaseModel
from .mlp import MLP
from cogdl.utils import spmm
def average_neighbor_features(graph, feats, nhop, norm="sym", style="all"):
results = []
if norm == "sym":
... |
c9771dd96f4bb0957bed4f13d38ae717f03c183360a2b7efcb779a4d4706bf33 | Python | 9,940 | 260 | # Copyright (c) Meta Platforms, Inc. and affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
# pyre-strict
from ax.analysis.plotly.constraint_feasibility import ConstraintFeasibilityPlot
from ax.analysis.plotly.plotly_analysis impor... |
4bf9796278087ff613dde22834f801a270d8041765dd6bc4e5d11e478d6aa6a5 | Python | 9,941 | 233 | # -*- coding: utf-8 -*-
import pandas as pd
import os
import seaborn as sb
from matplotlib import pyplot as plt
import numpy as np
def change_cell_number_to_string(number):
#not needed right now since all cells are just ints
#convert int to string with cellXXXX
#where XXXX is the int filled to ... |
7c78bede4a89c15fa490530c15b597939c08069d369fa3ba1699695161bc5cb3 | Python | 9,944 | 218 | from scipy.stats import pearsonr
import numpy as np
from sklearn.preprocessing import MinMaxScaler
from sklearn.metrics import r2_score, mean_squared_error, roc_auc_score, precision_recall_curve, average_precision_score, ndcg_score
phenoLabels = {0:['kinship_additive_minMAF0.01_maxMAF0.5.csv','kinship_additive_minMAF... |
15d245bf70ced55d609932123b735d590b53a2598721dde85752e769afb5118e | Python | 9,945 | 327 | """Utilities for loading and reasoning about unparsed tools in directories."""
import fnmatch
import glob
import logging
import os
import re
import sys
import yaml
from galaxy.tool_util import loader
from galaxy.tool_util.parser import get_tool_source
from galaxy.util import checkers
log = logging.getLogger(__name_... |
c6f279adc970e497c7ce13212c3f2a766b15e76c3fea3e47e8f1f9b3d0897b29 | Python | 9,945 | 388 | import inspect
import operator as op
from typing import AbstractSet, Callable, Mapping, Sequence, Tuple
import pickle
import pytest
import numpy
from ..config import config
from .. import expressions, logic
from ..expression_walker import (
ExpressionBasicEvaluator,
TypedSymbolTableEvaluator,
)
from ..expres... |
1c968456766cdbe5fa6038ffbe974de67bd9f4a29ed067c41e3afb520f116de6 | Python | 9,948 | 246 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
@author: chris3arcadia
@description: template script to generate transfer lists for acid/base computing
@created: Thr Feb 28 2019
"""
# Libraries
import numpy as np
import chemcpupy
from chemcpupy import Plating, Containers
from acidbase_network import AcidBaseNetwor... |
1f4aa0774847418ac308cb8b418439437508ddf0ec05d40cc21555bfa5ea34f4 | Python | 9,949 | 274 | import warnings
import numpy as np
from fanc.tools.matrix import remove_sparse_rows, restore_sparse_rows
from fanc.legacy.data.genomic import Hic, AccessOptimisedHic, Edge
import logging
logger = logging.getLogger(__name__)
def correct(hic, whole_matrix=True, intra_chromosomal=True, inter_chromosomal=True,
... |
70e923c709ca287987abb3f394e2e82f1cfb561dbfe8b5139f3ea2e450517263 | Python | 9,960 | 297 | """DOC-Forest.
==================================================
Compute markers used for DOC-Forest recipe
==================================================
Here we compute the markers from previously computed markers as published [1].
For simplicity, we only compute scalars using a trimmed mean (80%) accross
epo... |
316f527bec7c12e818b245ed78d5adf776789f2ededb40e4d5f4da280620c01a | Python | 9,965 | 249 | #!/usr/bin/env python3
# Copyright (c) Meta Platforms, Inc. and affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
from __future__ import annotations
from copy import deepcopy
from functools import partial
from itertools import pr... |
4e02aa1ed2d1861b9bc30089995879736b0394c52e3c6756b6bd4b400b5d6585 | Python | 9,967 | 286 | # MIT License
#
# Copyright (c) 2019-2024 The PyQMC Developers
#
# Permission is hereby granted, free of charge, to any person obtaining a copy
# of this software and associated documentation files (the "Software"), to deal
# in the Software without restriction, including without limitation the rights
# to use, copy, m... |
eebf5d859ef6a381cdcc5646279e0599a6f0f0c545802d4343da75d34d1d8e8f | Python | 9,974 | 140 | # -*- coding: utf-8 -*-
"""
@title: a more concise tester script for the Andrew class
@description: writes "BROWN DARPA" in a 384 well plate (based on 'example_protocol_2-unencrypted.anp')
@author: chrisarcadia
@created: 2018/04/03
"""
import Andrew
# create a new protocol
recipe = Andrew.Protocol();
# set protocol... |
093730d7c630571989da24068ef76f22fb3860c11617ba317e5e497c1ba1fab4 | Python | 9,975 | 264 | # Licensed to the Apache Software Foundation (ASF) under one
# or more contributor license agreements. See the NOTICE file
# distributed with this work for additional information
# regarding copyright ownership. The ASF licenses this file
# to you under the Apache License, Version 2.0 (the
# "License"); you may not u... |
544932c89d60bae0ea5db417378aa70255db5a13ad2c526b67d8d60268619800 | Python | 9,975 | 227 | import pathlib
from typing import List, Union
import xarray as xr
import numpy as np
import os
from skimage.io import imread
from skimage.morphology import label
from skimage.measure import regionprops_table
import pandas as pd
from alpineer import load_utils, image_utils
from ark.segmentation.ez_seg.ez_seg_utils impor... |
481aaed6108246b98722d553970d7d2c4939d5442b5c979cbefdd0dc800372df | Python | 9,978 | 282 | import numpy as np
from bisect import bisect_left
from collections import defaultdict
import intervaltree
from genomic_regions import GenomicRegion
from future.utils import string_types
def vector_enrichment_profile(matrix, vector, mappable=None, per_chromosome=True,
percentiles=(20.0, 4... |
89d181dff2371e677e37e902157a4518cd4fee0db14563aaa67a7fa57aed2cf0 | Python | 9,982 | 260 | """
Utilities for validating inputs related to user objects.
The validate_* methods in this file return simple messages that do not contain
user inputs - so these methods do not need to be escaped.
"""
import logging
import re
from typing import (
Optional,
)
import dns.resolver
from dns.exception import DNSExce... |
90ffdebddd0db5a997076180f251bb6cee7299ec476d55f71c6814129738c053 | Python | 9,983 | 300 | #!/usr/bin/env python3
"""
Script to validate file sources configuration by attempting to create instances
of each configured file source.
This script loads the currently configured file_sources_config_file YAML file
and tries to instantiate each of the specified file sources in order to validate
the configuration mod... |
35acc4816c2052289d7ca014e7dc8c1b6adf9605ef0a4c96a9278f8dd69fdd53 | Python | 9,985 | 280 | """Color transformation and composites.
Copyright (C) 2021 Ionpath, Inc. All rights reserved."""
import numpy as np
from scipy import ndimage
from mibidata import constants
def _trim(array, lower=0., upper=1.):
"""Trims an array to a specified range; used for floating point errors."""
return np.minimum(np... |
579b019f2b49180c5cbf522be5811b175a4cdf9d18d715a8a1e2b2f775eaf102 | Python | 9,985 | 363 | import time
import numpy as np
import matplotlib.pyplot as plt
import sys
import os
import skimage
from skimage import color as skcolor
from skimage import graph as skgraph
from skimage import data as skdata
from skimage import segmentation as sksegmentation
import imageio
import cv2
import maxflow
from skimage.feature... |
219cc58c1ed864e09f9ba35a15b490f2ad043ed2b42f3a8330acb345974ed6f6 | Python | 9,987 | 304 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Wed Mar 11 13:56:08 2020
@author: amelie
"""
from brian2 import *
from scipy import signal
from FEF_full3_alte import *
from LIP_full_alte import *
from itertools import *
from joblib import Parallel, delayed
import multiprocessing
def save_raster(nam... |
0b49256f4b23aa8de5dbd96796bf851a9eac93533d136d71ced9c87d7ff5b623 | Python | 9,988 | 228 | #author: Dimitris Spathis (ds806@cl.cam.ac.uk)
"""
what: load individual feature CSVs of Fenland's repeats cohort, concat, split to train/test, normalize and do ML
difference from task1: here we focus on the repeats and create three binary tasks based on FII delta
in: CSVs with extracted features, IDs, metadata
out:... |
5bd3d1467eddeff6dd75975813320563c5fe8621b3e3c46be366962a4d30e4e6 | Python | 9,989 | 361 | """
*****
Pydot
*****
Import and export NetworkX graphs in Graphviz dot format using pydot.
Either this module or nx_agraph can be used to interface with graphviz.
Examples
--------
>>> G = nx.complete_graph(5)
>>> PG = nx.nx_pydot.to_pydot(G)
>>> H = nx.nx_pydot.from_pydot(PG)
See Also
--------
- pydot: h... |
8a3220b6fcd1bbef4d399d8e0f360d061bd9ef3ca7f08096ced619c862cd8be5 | Python | 9,992 | 323 | import dataclasses
import itertools
import typing
from ._util import MechId
from .definitions import (
CableProperties,
CableType,
Definition,
Ion,
Mechanism,
Synapse,
_parse_dict_def,
)
class Constraint:
def __init__(self):
self._upper = None
self._lower = None
... |
3391cbe306b4813a9c342b94dd831a1a32d185a40afabbf7e5b8094028b8f87e | Python | 9,994 | 232 | """
Module for the configuration node of the Glomerulus to Granule ConnectionStrategy
"""
import itertools
import numpy as np
from bsb import (
CfgReferenceError,
ConfigurationError,
ConnectionStrategy,
ConnectivityError,
InvertedRoI,
config,
pool_cache,
refs,
)
class TooFewGlomeruli... |
81563a70982f3e05ec88d894d306480713ed8fbbc3a7f261c7d6ba3bb2e33982 | Python | 9,994 | 182 | import re
import sys
import os
import math
from scipy import stats
print("PPI_mutation_sites_mapping_by_category")
Disease_list = []
Category_list =[]
Disease_category = {}
with open(r'E:\OneDrive\学术\PPI article\data\de novo mutation data\20190514_MasterFile_allDNMs-codingLoc_v1.5.txt') as fp:
text = fp... |
960007712f671639814e5ac80f2d37c266c98b14a16df82b196168aa10c6a3d4 | Python | 9,995 | 261 | import numpy as np
from scipy.special import expit as sigmoid
import igraph as ig
import random
def set_random_seed(seed):
random.seed(seed)
np.random.seed(seed)
def is_dag(W):
G = ig.Graph.Weighted_Adjacency(W.tolist())
return G.is_dag()
def simulate_dag(d, s0, graph_type):
"""Simulate random... |
2a5bc70041fcf2497e0b23a025bc5a6a0700a32546fda14fb3ac429f3ed5de12 | Python | 10,003 | 228 | # -*- coding: utf-8 -*-
"""
Created on Sat Feb 17 20:26:05 2018
@author: jacobrosenstein
An UgiLibrary stores a list of Ugi molecules. It inherits from the CompoundList class.
"""
import json
import csv
from datetime import datetime
import pubchempy as pcp
from pyteomics import mass
from chemcpupy import Compoun... |
07051a188d3535041d3558a6b7684a6c37533d59b90ff7aaa478850472456897 | Python | 10,004 | 298 | import uuid
import numpy as np
from datetime import datetime
import logging
import os
import sys
import torch
from allennlp.data import DataLoader
from allennlp.modules import TextFieldEmbedder, Seq2VecEncoder, FeedForward
from allennlp.modules.seq2vec_encoders import PytorchSeq2VecWrapper
from allennlp.nn import Acti... |
0d0915bed6ff824aae9b77854a837975b2d7aca513706ada717d00a20b4b0241 | Python | 10,004 | 232 | """Utilities for parsing "Galaxy Flavored Markdown".
See markdown_util.py for loading objects and interacting with the rest of Galaxy.
This file is meant to be relatively self contained and just used to "parse" and validate
Galaxy Markdown. Keeping things isolated to allow re-use of these utilities in other
projects (... |
aada0a2fcc84e626c9202189930fd052fdc961c24805876043f5463550ed6a60 | Python | 10,008 | 261 | # Copyright (c) Meta Platforms, Inc. and affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
# pyre-strict
from typing import final
import numpy as np
import plotly.express as px
from ax.adapter.base import Adapter
from ax.analysis... |
f58c9c095fae86e203747744e8da4f4d99005ac0a139e302bbff8bda879666f4 | Python | 10,008 | 303 | from pathlib import Path
import numpy as np
import nibabel as nib
import shutil
import json
from clpipe.config_json_parser import GLMConfigParser
DEFAULT_NUM_BIDS_SUBJECTS = 10
DEFAULT_NUM_DICOM_SUBJECTS = 5
DEFAULT_NUM_FMRIPREP_SUBJECTS = 8
DEFAULT_RANDOM_NII_DIMS = (12, 12, 12, 36)
DICOM_SESSIONS = ["2000", "2010",... |
db4318186ed8b250ff8d0fdeac8c99cdcbc44695996da36497b84913658ed97a | Python | 10,016 | 279 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Wed Apr 29 08:58:41 2020
@author: amelie
"""
from brian2 import *
from scipy import signal
from cells.RS_FEF import *
from cells.FS_FEF import *
from cells.SI_FEF import *
from cells.VIP_FEF_vis import *
def generate_visual_neurons(theta_phase,N_FS,N_RS,... |
32d2d0bb126f03f325bab25a33dfd75a53fbedf3b9646ceecc788f1db16e6657 | Python | 10,017 | 200 | import numpy as np
import pytest
from alpineer import misc_utils
from sklearn.cluster import KMeans
from test_utils import make_cell_table
from typing import List, Tuple, Callable
import pandas as pd
import ark.settings as settings
import ark.spLDA.processing as pros
from ark.utils.spatial_lda_utils import within_clust... |
7dae29f314fc495555d858be584c1e02fe4806d0772639c98efe235db36a458b | Python | 10,025 | 201 | import os
import numpy as np
import nibabel as nb
import shutil
import scipy
from scipy import stats as st
from os.path import join as opj
import subprocess
from subprocess import Popen
import meld_classifier.mesh_tools as mt
from meld_classifier.tools_commands_prints import get_m
def get_adj_mat(surf):
all_... |
6338b05fa2b07370ed45e9dfab0113381ce619f75bfdab0b57bb0a6ee13b9adc | Python | 10,028 | 291 | """
Support for aggregations according to [1]_. For instance
the encoding of ``P(x, count<y>):-Q(x, y)`` in intermediate
representation ``Implication(P(x, AggregationApplication(count, y), Q(x, y))``
produces the set ``P(x, z)`` where ``z`` is the number of tuples ``(x, ...)``
in the set ``Q``.
.. [1] T. J. Green, S. ... |
f1146078d4834b2f2b9f48be3318299d8b375f4ad929e8a5f49e1bfd43a9e040 | Python | 10,034 | 236 | # Copyright 2018 The TensorFlow Authors. 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 applica... |
3acda7f7036c17ba1f4a21fd47e87ac4011acea033ad9332fb11df7ad70fbb70 | Python | 10,035 | 214 | from uff.ic.mell.sentimentembedding.datasets.dataset_loader import DataSetLoader
from uff.ic.mell.sentimentembedding.classificadores.analisador import Analisador
from uff.ic.mell.sentimentembedding.vocabularios.deepmoji_vocabulario import DeepMojiVocabulario
from uff.ic.mell.sentimentembedding.vocabularios.emo2vec_voc... |
8762f600fa231de845952e7d770563323b54354e389dc1b9eb045bcc24357a98 | Python | 10,035 | 263 | # Copyright (c) Meta Platforms, Inc. and affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
# pyre-strict
from typing import final, Literal
from ax.adapter.base import Adapter
from ax.analysis.analysis import Analysis
from ax.anal... |
53d50033614fb121ba4eb55292de826b3d158e769a38a0b027659cf31152ad44 | Python | 10,036 | 260 | # Copyright (c) MONAI Consortium
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
# http://www.apache.org/licenses/LICENSE-2.0
# Unless required by applicable law or agreed to in writing, so... |
5f7ae080122db0e28e57efcad907167065b01756942d5e4a42c479fc7edea723 | Python | 10,043 | 255 | #!/usr/bin/env python3
# Copyright (c) Meta Platforms, Inc. and affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
# pyre-strict
import numpy as np
from ax.adapter.registry import Generators
from ax.core.data import Data
from ax.c... |
2c6c6284b5f7c8a7010070808d4bbeae05e68163526b2005280d375fe5c756c8 | Python | 10,044 | 253 | """
This example shows how to use a PointsDensity
actor to show the density of labelled cells
"""
# We begin by adding the current path to sys.path to make sure that the imports work correctly
import sys
sys.path.append('/home/wirrbel/brainrender_update_2022-01/')
import os
from shutil import copyfile
import in... |
48e05cf37167c03b98b3a2e09eadc9abf9313dbebb7bbc365bea6ca4fef7c8cb | Python | 10,046 | 297 | import logging
import numpy as np
from datetime import datetime
import os
import sys
import uuid
import torch
from allennlp.modules import TextFieldEmbedder, Seq2VecEncoder, FeedForward
from allennlp.modules.seq2vec_encoders import PytorchSeq2VecWrapper
from allennlp.nn import Activation
from allennlp.training import ... |
e13f2932587ebac107036fab64587e0a665b058f5d7172078e8a91fa8276852c | Python | 10,048 | 296 | """Functions for computing sparsifiers of graphs."""
import math
import networkx as nx
from networkx.utils import not_implemented_for, py_random_state
__all__ = ["spanner"]
@not_implemented_for("directed")
@not_implemented_for("multigraph")
@py_random_state(3)
@nx._dispatchable(edge_attrs="weight", returns_graph=T... |
fe62244dbe5e738e533b696fb934158223bbc46a8919cd9ddb6848d8a3efbaa3 | Python | 10,054 | 373 | from operator import eq, lt
from typing import AbstractSet, Callable, Tuple
import pytest
from nl_expr.type_system import Unknown
from nl_expr import exceptions
from nl_expr.expression_walker import ExpressionBasicEvaluator, IdentityWalker
from nl_expr.expressions import (
Constant,
ExpressionBlock,
Func... |
01d4e8101c03c2201aa1bf9953670ab5433db7254e33d4e417e4fd54ff414dcf | Python | 10,064 | 281 | #!/usr/bin/env python3
import os
from param_stamp import get_param_stamp_from_args
from visual import visual_plt
import numpy as np
import main
from param_values import check_for_errors,set_default_values
import options
from utils import checkattr
## Memory budget values to compare
budget_list_CIFAR100 = [1, 2, 5, 10... |
34e324005baa8b46278f0f7eff950223c6b9ccf1ff3337c8ed9df0b2e0f14504 | Python | 10,065 | 224 | import numpy as np
import pickle
import torch
from torch.utils import data
from torch.utils.data.dataset import TensorDataset
from torch.utils.data import DataLoader
from torch.nn.utils.rnn import pad_sequence
from sklearn.preprocessing import StandardScaler
torch.set_default_dtype(torch.float64)
class MyDataset_te... |
336068d1e9d52923d8a1966e531fa78579e5ec247eb77d71e75471536ec8ca85 | Python | 10,068 | 329 | # -*- coding: utf-8 -*-
"""
IlluminationCorrection
======================
The module provides a function to correct systematic illumination variations
and vignetting in intensity.
The intensity image :math:`I(x)` given a flat field :math:`F(x)` and
a background :math:`B(x)` the image is corrected to :math:`C(x)` as:... |
d6c8a939a761f1bb2ecc7674ffb85a6a9294e95ae7d2b6d92f91d7bdbb2da39c | Python | 10,072 | 259 | import pytest
import networkx as nx
from networkx import approximate_current_flow_betweenness_centrality as approximate_cfbc
from networkx import edge_current_flow_betweenness_centrality as edge_current_flow
np = pytest.importorskip("numpy")
pytest.importorskip("scipy")
class TestFlowBetweennessCentrality:
def ... |
f8eeeaca6be53bc7580e693a096723e4fe62e8ecd9510b03cb6d3125996e31e5 | Python | 10,079 | 323 | # -*- coding: utf-8 -*-
#
# project-template documentation build configuration file, created by
# sphinx-quickstart on Mon Jan 18 14:44:12 2016.
#
# This file is execfile()d with the current directory set to its
# containing dir.
#
# Note that not all possible configuration values are present in this
# autogenerated fi... |
3acf3f839fca4ba6e1b8ab5f04cf9a1ebd46ed01726c831f879d525b265835c1 | Python | 10,081 | 252 | #!/usr/bin/env python
import argparse
import os.path
import subprocess
import tempfile
from glob import glob
from subprocess import check_output
from typing import (
Any,
Dict,
List,
)
from galaxy.util import unicodify
from galaxy.util.path import StrPath
from .get_tests import (
hashed_test_search,
... |
f5cde70983057bad866c1cb495276fa86da49132001a419a886501b779df4041 | Python | 10,084 | 300 | # rmf 3.25.2020, last modified 9.20.2021
# cleaned up 3.1.2022
import sys, re
import matplotlib as mpl
mpl.use('Agg')
from matplotlib import pyplot as plot
import numpy as np
# USAGE
usage = 'python ' + sys.argv[0] + ' <summary file> <q-value threshold>'
if len(sys.argv) != 3 or '-h' in sys.argv or '--help' in sys.ar... |
0ec0340185184157824ef20e713146d596b64d4aa7b59ed287da617faffd6720 | Python | 10,085 | 277 | #!/usr/bin/env python3
# Copyright (c) Meta Platforms, Inc. and affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
# pyre-strict
from __future__ import annotations
import inspect
import logging
import warnings
from collections.abc... |
fb685b72a54961ced633bbda747d6f4df9ab61a12c79098011954202f819a8f2 | Python | 10,089 | 182 | """05_mre_efield_comparison.py - per-ROI comparison: MRE mechanics vs MD-dMRI microstructure vs tDCS
E-field. Two outputs: consistency QC (MD vs stiffness negative, uFA vs stiffness positive) and a
relevance map (dE_model_pct = 100*(E_MDdMRI - E_DTI)/E_DTI, isolates the conductivity model since the
shared-montage field... |
9d0e51ee8fc035be4d5a8c42f06b92ba9ae29a2325a6f0dfbe73a9a71386d8a1 | Python | 10,098 | 334 | # test_meme_writer.py
# Contact: Jacob Schreiber <jmschreiber91@gmail.com>
import numpy
import pytest
from modiscolite.meme_writer import MEMEWriterMotif
from modiscolite.meme_writer import MEMEWriter
from modiscolite.meme_writer import array_to_string
from memelite.io import read_meme
from numpy.testing import ass... |
5db6ff452972072fd5e3de774549c55e22136a382eb7bd57ef34a8a2b9962837 | Python | 10,100 | 351 | """Perform epoching.
Here we make epochs out of the cleaned raw data.
Our main target are epochs centered on each sample number (6000 per subj)
--> "number epochs".
However, for sanity checking the EEG data, we will also create epochs centered
on the button press for each choice (600 per subj). We can then use these
... |
90d4de7517273ba10ab36ff28e55ea3aaf75c689681b5953b026821bce755b96 | Python | 10,100 | 244 | #!/usr/bin/env python
# -*- coding:utf-8 -*-
'''
This script is for rescaling and resampling the aligned t1w mris
'''
import SimpleITK as sitk
import numpy as np
import matplotlib.pyplot as plt
import os
import argparse
import neurite as ne
# # parse commandline args
# parser = argparse.ArgumentParser()
# parser.add_a... |
89807617b8f542ddd00079211a718a720891341d46abd331b44df5e765dd4bf0 | Python | 10,102 | 264 | """Unit tests for the :mod:`networkx.generators.lattice` module."""
from itertools import product
import pytest
import networkx as nx
from networkx.utils import edges_equal
def test_hexagonal_lattice_no_pos():
# Test positions are note computed/stored when with_positions=False
G = nx.hexagonal_lattice_grap... |
c27d574f533d1164dcf56bacc6077ed40afdfbcc030bc26addb128695a0deb08 | Python | 10,112 | 282 | #!/usr/bin/env python3
import os
import numpy as np
# -custom-written code
import main
from utils import checkattr
from params.param_stamp import get_param_stamp_from_args
from params.param_values import check_for_errors,set_default_values
from params import options
from visual import visual_plt
## Memory budget valu... |
a55a5be45b5e816053c67b3a0d7830bbb0918b10e53b2bfb7695b6e13459d561 | Python | 10,114 | 318 | """Configuration sphinx documentation."""
# Ionpath's mibilib documentation build configuration file,
# created by sphinx-quickstart on Tue Aug 2 08:57:24 2016.
#
# This file is execfile()d with the current directory set to its
# containing dir.
#
# Note that not all possible configuration values are present in this
... |
b12b314aab41185ece1c69b70dd537e89123d0bc6125b27473018c5f1e0de85c | Python | 10,117 | 298 | """Train DNN models end-to-end to predict the EEG responses to arbitrary
images.
Parameters
----------
sub : int
Used subject.
modeled_time_points : str
Whether each DNN should model 'single' or 'all' EEG time points.
dnn : str
DNN model used.
pretrained : bool
If True use a pretrained network, if False use a rand... |
f33adf0bc984f818900b03b0d67908ffd1378bfae8fef31222163ad20585b466 | Python | 10,117 | 264 | # Licensed to the Apache Software Foundation (ASF) under one
# or more contributor license agreements. See the NOTICE file
# distributed with this work for additional information
# regarding copyright ownership. The ASF licenses this file
# to you under the Apache License, Version 2.0 (the
# "License"); you may not u... |
a2a4815f5d6d63d483195ba7a07cd62728a9207a97228b00d214d4625026f522 | Python | 10,128 | 235 | from unittest.mock import patch
import pytest
from data_import.functions import _async_import_background_streaming, _async_reimport_background_streaming
from data_import.models import FileUpload
from data_import.serializers import ImportApiSerializer
from data_import.uploader import load_tasks_for_async_import_streami... |
2924dd8173dce903a2eff56834eb87f351970f122a16d19a2c2bdf5aa26867a3 | Python | 10,130 | 417 | from pathlib import Path
from unittest.mock import patch
import numpy as np
import numpy.testing as npt
import pandas as pd
import pytest
from voxcell import RegionMap, VoxelData
import atlas_densities.densities.excitatory_inhibitory_splitting as tested
from atlas_densities.app.utils import DATA_PATH
TESTS_PATH = Pa... |
245e27d34f95abcf5b91ab362fbbb89e0a33e7416a19a12f2e63518a195ef5dd | Python | 10,132 | 307 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
# Licensed to the Apache Software Foundation (ASF) under one
# or more contributor license agreements. See the NOTICE file
# distributed with this work for additional information
# regarding copyright ownership. The ASF licenses this file
# to you under the Apache Licens... |
9b4ed60328b24b1f8910845ff4a3eaec617db12b5c908cb065a69d3ed532c81b | Python | 10,133 | 281 | import numbers
import numpy as np
from .backend import get_backend
from .validation import check_random_state
def compute_lipschitz_constants(Xs, kernelize="XTX", random_state=None):
"""Compute Lipschitz constants of gradients of linear regression problems.
Find the largest eigenvalue of X^TX for several X... |
a4d951c74640f6385b96b361c40a1c5a597ca987e9b43195ae69c4abbaba291f | Python | 10,137 | 204 | import numpy as np
from ..strategy import ConnectionStrategy
from .shared import MorphologyStrategy
from ...helpers import DistributionConfiguration
from ...models import MorphologySet
from ...exceptions import *
class VoxelIntersection(ConnectionStrategy, MorphologyStrategy):
"""
This strategy voxelizes morp... |
2d70b120fdf970413ef35b54395faa3a54aef675cfe9d0232ac2cd0575fd0af3 | Python | 10,142 | 240 |
# -*- coding: utf-8 -*-
"""
Created on Thru March 10 21:47:26 2022
@author: Zhiye
"""
import os, sys, glob, re, platform
import time
sys.path.insert(0, sys.path[0])
from generate_feature import *
from keras.models import model_from_json,load_model, Sequential, Model
from keras.utils import CustomObjectScope
from kera... |
bf5d1817445f35b42c1fbe7c4234871f4bc2752ef9425bcdc13a8b093d1cb1c1 | Python | 10,147 | 242 | import sys
from PyQt5 import QtGui
from PyQt5 import QtCore
from PyQt5 import QtWidgets
from matplotlib.backends.backend_qt4agg import FigureCanvasQTAgg as FigureCanvas
from matplotlib.backends.backend_qt4agg import \
NavigationToolbar2QT as NavigationToolbar
from matplotlib.figure import Figure
from matp... |
71b244bf19019457d28c16a542b6d3a9bfca151e9e2cca3b329fc95edb4fc902 | Python | 10,150 | 301 | from __future__ import absolute_import
import json
import logging
from pip._vendor import six
from pip._vendor.six.moves import zip_longest
from pip._internal.cli import cmdoptions
from pip._internal.cli.base_command import Command
from pip._internal.exceptions import CommandError
from pip._internal.index import Pac... |
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