sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
ee99437a9dbf282cd94389849e169c7c91b5c0a45f9d5fe32b9a0c5a8d6b2540 | Python | 10,153 | 184 | import re
import sys
import os
import math
from scipy import stats
print("PPI_mutation_sites_mapping_by_disease")
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.... |
9e472a28b94c17593de2fbb32c8f57b2885087ded11fb588398366517cd8742a | Python | 10,158 | 279 | import math
from collections import defaultdict
from typing import List
import numpy as np
import tensorflow as tf
from PIL import Image
from tensorflow.python.keras.preprocessing.image import img_to_array
from data import Data
from utils import split_keys
LABEL_INDEX = {
'ap': 0,
'bs': 1,
'mid': 2,
... |
422a0a615853ea1f200013e0a48dec7a85bee65d7c99fb90a1bb8df230baa7ce | Python | 10,162 | 303 | import pandas as pd
import numpy as np
from tqdm.auto import tqdm
from pathlib import Path
import os,json
from dataclasses import dataclass,field
from typing import Optional
from transformers import (
AutoModelForCausalLM,
AutoTokenizer,
AutoConfig,
HfArgumentParser,
TrainingArguments,
MODEL_FOR... |
66f5e4b7cb3993055afe20aa94ffc1899cd5b1b3e87790790a8c23eefc4a844c | Python | 10,164 | 309 | """
Logic simplifier for SQUALL parsed expressions.
Collapses nested conjunctions, removes trivial operations,
and normalizes quantifier expressions produced by the SQUALL parser.
"""
from nl_core.datalog.expressions import AggregationApplication as _AggApp
from nl_expr.expression_walker import (
ExpressionWalker,... |
53c184e1cc8571fd291c5422e3c5ab99ee8f1c83e27e9cc7c6ff426385fffaff | Python | 10,166 | 243 | """Pairwise decoding of the synthetic EEG test data, and noise ceiling
calculation. For each EEG time point, a SVM classifier is trained to decode
between each combination of two biological data image conditions (using the EEG
channels data), and is then tested on the corresponding combinations of two
synthetic data im... |
2f56511a9ebac03f4bad2861cd91c44fb848a4a0826a249cb62ee17b2b889d16 | Python | 10,167 | 302 | from __future__ import division
import numpy as np
import pandas as pd
import sys
from scipy.stats import t
from scipy.stats import fisher_exact
from scipy.sparse import csc_matrix
import numexpr as ne
import cellranger.analysis.diffexp as cr_diffexp
ALLOWED_NB2_MODELS = ['poisson', 'geometric', 'nb']
def sanitize(Y... |
7425aadb3fae14e2fcc6ae0e20fd66ad9961925b467d85087312b989186e6453 | Python | 10,175 | 290 | # -*- coding: utf-8 -*-
"""Prepare data for training based on a specified config file
"""
# Created on Wed June 17 2020
# Contributions and Changelog accessed via a private git repository:
# https://github.com/philipwijesinghe/deep-learning-lsm.git
# philip.wijesinghe@gmail.com
# Copyright (c) 2020 Philip Wijesinghe... |
28715443752c4dfc760b32252a18e96c3b5157a8654827ac3da3774aa91320b8 | Python | 10,178 | 281 | import random
import time
import numpy as np
import scipy.sparse as sp
import torch
import torch.nn.functional as F
from tqdm.auto import tqdm
from ..base import InjectionAttack, EarlyStop
from cogdl.utils.grb_utils import eval_acc, feat_preprocess, adj_preprocess, getGraph, getGRBGraph
class FGSM(InjectionAttack):... |
b0318162a6ff366b8c0a151692fe58b6b16798bb0c0eca678d3f9d237ea24c0c | Python | 10,179 | 190 | 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... |
bce12646cd4c92e00fb1f7120ac83c7d6c33045f1a4359202367472ff1afd190 | Python | 10,182 | 235 | #!/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
from logging import Logger
from typing import TYPE_CHECKING
from ... |
59d211936ec3fc0ae63ecf6d769bd02d0095e139aeb36d76050871b0520c6209 | Python | 10,184 | 297 | """Priority queue class with updatable priorities."""
import heapq
__all__ = ["MappedQueue"]
class _HeapElement:
"""This proxy class separates the heap element from its priority.
The idea is that using a 2-tuple (priority, element) works
for sorting, but not for dict lookup because priorities are
o... |
e7fad9e6b23fa3c54326bf91e1b7ac47e5dc3f0298f3e7479f8566aeb941a2b7 | Python | 10,190 | 318 | """
Unit tests for edgelists.
"""
import io
import textwrap
import pytest
import networkx as nx
from networkx.utils import edges_equal, graphs_equal, nodes_equal
edges_no_data = textwrap.dedent(
"""
# comment line
1 2
# comment line
2 3
"""
)
edges_with_values = textwrap.dedent(
"""
... |
fba8fa38a480c55ef4cbfd22505fba1e16cf5d677c97e6d2aa8c06d62843f502 | Python | 10,190 | 338 | """
This module has functions or callable objects that can be used to compute features from segmented
time series data
Sets of these functions or callables can be passed in a dictionary object to initialize the
``FeatureRep`` transformer.
All functions follow the same template and process a single segmented time seri... |
e57963a757bfb364140e99aec57a7504dbe378e7ac76031e2b2ee50983f3f6ed | Python | 10,196 | 298 | """
Tests for closeness centrality.
"""
import pytest
import networkx as nx
@pytest.fixture()
def undirected_G():
G = nx.fast_gnp_random_graph(n=100, p=0.6, seed=123)
cc = nx.closeness_centrality(G)
return G, cc
@pytest.mark.parametrize("precompute_sp", (True, False))
class TestClosenessCentrality:
... |
3e7420b6a74a67498fd904fc660f1e0638ddcc95ddffee392cc77fae65e4b5b3 | Python | 10,201 | 319 | from random import Random
import pytest
import networkx as nx
floyd_fns = [
nx.floyd_warshall_predecessor_and_distance,
nx.floyd_warshall_tree,
]
@pytest.mark.parametrize("floyd_fn", floyd_fns)
class TestFloyd:
@classmethod
def setup_class(cls):
pass
def test_floyd_warshall_predecessor... |
052c5f20c8304ca0a3e1205068c45ef081fc1b1c45f19e8172760ea8b40f37ec | Python | 10,202 | 270 | import sys
sys.path.insert(0, "..")
import numpy as np
import tensorflow as tf
from learnMSA.legacy.MsaHmmLayer import MsaHmmLayer
from learnMSA.legacy.MsaHmmCell import HmmCell
from learnMSA.legacy.Initializers import ConstantInitializer
# from learnMSA.legacy import Align, Emitter, Transitioner, Initializers, MsaHmm... |
401dbe712523d63aef5997cf5edb6c669c8069c420b4a2d5935e2f416f53a521 | Python | 10,206 | 305 | # -*- coding: utf-8 -*-
"""
requests.auth
~~~~~~~~~~~~~
This module contains the authentication handlers for Requests.
"""
import os
import re
import time
import hashlib
import threading
import warnings
from base64 import b64encode
from .compat import urlparse, str, basestring
from .cookies import extract_cookies_... |
30fd24b85571d705ae3ecb43194b7990a528ffb66113096858c59000e79fe428 | Python | 10,208 | 248 | #!/usr/bin/env python3
"""Compare two Kraken 2 installs (a PR and its base) on the test fixture.
Usage: tests/pr_compare.py BASE_INSTALL HEAD_INSTALL WORK_DIR [BIG_READS_PREFIX]
Each install builds its own database from data/ with kraken2-build and then
classifies the frozen fixture reads in tests/data (and, when giv... |
2f2d65cc95649efba0a3d7829190656025cd91fd5cd99e650cf4f4577fec7f38 | Python | 10,210 | 245 | import numpy as np
from ..strategy import ConnectionStrategy
from .shared import MorphologyStrategy
from ...helpers import (
DistributionConfiguration,
assert_attr_in,
)
from ...reporting import report, warn
from random import sample as sample_elements
class TouchInformation:
def __init__(
self, f... |
1bf25012ba16ba89d7b66d627496c947954b5bced9cd31e9c581f7935747082f | Python | 10,214 | 267 | import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
import seaborn as sns
import xarray as xr
from pynndescent import NNDescent
from scipy.stats import ks_2samp
from sklearn.decomposition import PCA
from sklearn.metrics import roc_curve
from ALLCools.mcds.utilities import calculate_posterior_mc_frac... |
51d7319e919b9c57609fd5c47ef97e931742572fe9af959b4c68f66a7e0639da | Python | 10,224 | 231 | #!/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 time
from abc import ABC, abstractmethod
from collections.abc import Sequence
from typing impor... |
52f087a7feaddb37505ebdc03e24beae3caf40b89f19f28ad9ca70d883935880 | Python | 10,224 | 284 | import argparse
import os
import numpy as np
import math
import itertools
import datetime
import time
import torchvision.transforms as transforms
from torchvision.utils import save_image, make_grid
from torch.utils.data import DataLoader
from torchvision import datasets
from torch.autograd import Variable
from model... |
3f8732d0966cd1b2dc1c8d2354fc8b7271ec261909255286482a0e46cc658223 | Python | 10,225 | 259 | # coding=utf-8
# Copyright (c) DLUP Contributors
import h5py
import torch
import torch.nn.functional as F
from pytorch_lightning import LightningModule
import torchmetrics
from torch import nn
from pathlib import Path
import json
class Attention(LightningModule):
#TODO implement slide-level or patient-level AUC?
... |
b836a73083dfe7e977f147017a9ff59789df75d2d03c5999c0461f2f2f7e936b | Python | 10,229 | 192 | from brian2 import SpikeMonitor, get_logger
from brian2lava.utils.utils import mode_dependent
from brian2lava.utils.const import HARDWARE
from lava.proc.monitor.process import Monitor
import os
try:
from lava.utils.loihi2_state_probes import StateProbe # import here because this is only part of lava-loihi
from ... |
fa2d3a7329935fee6e96acc0648c3070cb71d52d6026885f477fad174c67c5f1 | Python | 10,232 | 224 | #!/usr/bin/env python
import os
import sys
import errno
import argparse
def parse_args(args=None):
Description = "Reformat nf-core/nanoseq samplesheet file and check its contents."
Epilog = "Example usage: python check_samplesheet.py <FILE_IN> <FILE_OUT>"
parser = argparse.ArgumentParser(description=Des... |
5f056e2761167ddba4bb06e14aae6c7397ec5f57155eb2a308afe732d8cac5da | Python | 10,242 | 268 |
import argparse
import json
import os
import time
import uuid
import dgl
import numpy as np
import torch
import torch.nn.functional as F
from dgl.data import register_data_args
from nci_model import *
from nci_process import get_network
from pytorch_lightning.metrics.classification import Accuracy
fr... |
8d60ec834f1c33c70e7a4016b5ce4479f7e5cc08261d4a4b588e29bb1e2d760b | Python | 10,244 | 219 | import os, sys, json
sys.path.append('..')
# import libraries
import torch
import pandas as pd
import torchvision
from torchvision import transforms
from torch.utils.data import DataLoader
from utils.data_utils import ImageDataset
from trainScript import Trainer
from clutils import logger, save_config, set_seed
# set... |
b9641845bb5acc3c4eb4984913b0233c9861a7dc4f340b400e389946037e86f4 | Python | 10,245 | 270 | import os
import fanc
from fanc.config import config
import fanc.plotting as kplt
import fanc.commands.fancplot_command_parsers as parsers
def triangular(parameters):
parser = parsers.triangular_parser()
args = parser.parse_args(parameters)
if args.colormap is None:
colormap = config.colormap_hic... |
767987b493da54ac892101f1c0c12a4c45ded8f441b6352bd0bd0f2717001935 | Python | 10,250 | 321 | #!/usr/bin/env python3
#
# zarr documentation build configuration file, created by
# sphinx-quickstart on Mon May 2 21:40:09 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 file.
#
# All c... |
567106bded7eefa3c04dd6c98620cf68c4d11267fefc6cd4679b917704c43a30 | Python | 10,253 | 264 | from torch.utils.data import Dataset
import os
from PIL import Image
import numpy as np
import torch
from torchvision import transforms
import scipy.io as spio
class ScanpathLoadDatasets(Dataset):
"""
A PyTorch Dataset class to be used in a PyTorch DataLoader to create batches.
"""
def __init__(self, ... |
bf14091e92092f6119d79055dcfba264f20f935693d6b8242d00fc687adcafb0 | Python | 10,256 | 247 | import copy
import itertools
import logging
import cooler
import numpy as np
from matplotlib import cm, colors
from pygenometracks.tracks.GenomeTrack import GenomeTrack
from pygenometracks.utilities import change_chrom_names
DEFAULT_MATRIX_COLORMAP = "RdYlBu_r"
logging.basicConfig(level=logging.DEBUG)
log = logging.g... |
ccc8cb6c23832f3225cb9a1d8d30221316db26993a1323b3357bc432985054e5 | Python | 10,260 | 270 | import os
import pickle
import matplotlib.pyplot as plt
import numpy as np
import palettable.colorbrewer.qualitative as qual_palettes
import pandas as pd
import seaborn as sns
import spatial_lda.online_lda
from alpineer import io_utils, misc_utils
from scipy.spatial.distance import pdist
from spatial_lda.visualization... |
03bb1758e74fa80c45d3eb333699ad9723f1292469c2d9d95a04c1419c9d3d97 | Python | 10,262 | 262 | # 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... |
94043d54eabb8ecf281f6aade5ce11b421e797bb70a9f966171aab07b68ff51c | Python | 10,268 | 306 | """Generate and save combined annotations or combined markers
Combination operates on two or more volumetric files with nrrd format.
"""
from __future__ import annotations
import json
import logging
from pathlib import Path
import click
import numpy as np
import pandas as pd
import voxcell # type: ignore
import yam... |
a4db0565fbadeb12a481a19ce8ebb5a152900b3a3488903d892f34562f45c7bc | Python | 10,268 | 373 | """
**************
Adjacency List
**************
Read and write NetworkX graphs as adjacency lists.
Adjacency list format is useful for graphs without data associated
with nodes or edges and for nodes that can be meaningfully represented
as strings.
Format
------
The adjacency list format consists of lines with node ... |
cedd3235015009adf43806bae198840318322b2e8d5f704170807d3817c9dc1c | Python | 10,280 | 310 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
| Title:
Quality assessment of the preprocessing pipeline
| Date:
2021-02-01
| Author(s):
Theodor Rumetshofer
| Description:
This script generates images for each subject for manual quality assessment.
| List of functions:
... |
5b6b02d821caed5596401229125eb3a100ce5269eca14de6a56775160cd561e1 | Python | 10,284 | 233 | import itertools
import re
from copy import deepcopy
from typing import Iterable, Optional, Sequence, Tuple, Union
import numpy as np
from pymatgen.core import Composition, Structure
from rlmolecule.sql import hash_to_integer
from rlmolecule.tree_search.graph_search_state import GraphSearchState
from rlmolecule.tree_... |
f5b777fba02c41cdf258662316916b2683094c8e6173747e02394eb31ddd3da0 | Python | 10,285 | 313 | # dataset name: DGraphFin
from utils import Dgraph_Dataloader
from utils.utils import prepare_folder
from utils.evaluator import Evaluator
from logger import Logger
from cogdl.data import Graph
from cogdl.datasets import NodeDataset
from models import GCN, MLP, GAT, Grand, Graphsage, GraphSAINT, MixHop, sgc, D... |
2b9b18eaacabfa55ba4be20076003feafd8d645d30368c7f1d13cfeeb9c35356 | Python | 10,290 | 224 | # 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
# NOTE: Do not add `from __future__ import annotations` to this file. Adding
# `annotations` postpones evaluation of types an... |
fc094bb8880165a4965aefa07dca061f07ffc96dcdc2a8c7cdd63ccf7294a7d0 | Python | 10,291 | 296 | import pathlib
import subprocess
from concurrent.futures import ProcessPoolExecutor, as_completed
import anndata
import numpy as np
import pandas as pd
import scipy.sparse as ss
from anndata import AnnData
from ..utilities import (
chrom_dict_to_id_index,
generate_chrom_bin_bed_dataframe,
get_bin_id,
... |
930f1df73a172b130f539725298da6cc8965c7db20845c6b54952bcdb8def208 | Python | 10,295 | 294 |
from tracemalloc import start
from turtle import pos
from typing import List
import os
import random
import numpy as np
import scipy.sparse as sp
import torch
import torch.utils.data
from cogdl.utils import remove_self_loops, row_normalization
from cogdl.data import Graph, DataLoader
from cogdl.utils import RandomWalk... |
6b1dada3e2692520d2097c7c18e56064a5b06ba64416b2fae97696e6e9fda252 | Python | 10,297 | 295 | # -*- coding: utf-8 -*-
"""
Created on Thu Aug 26 15:20:33 2021
@author: Estefany Suarez
"""
import warnings
warnings.simplefilter(action='ignore', category=FutureWarning)
import os
import itertools as itr
import numpy as np
import pandas as pd
from scipy import stats
from sklearn.manifold import MD... |
7788252464b3a767fbbb295cafec146db83dbd1fd01977e133355d002b46bbfc | Python | 10,299 | 228 | from __future__ import annotations
from typing import Any, Literal
import numpy as np
import pytest
from anndata import AnnData
from pandas.testing import assert_frame_equal
from squidpy._constants._pkg_constants import Key
from squidpy.gr import co_occurrence, spatial_autocorr
from squidpy.gr._ppatterns import _fin... |
6130aaf5f036a1d0042988f02726d230ebc1a9786c79d6b13b551f192f304332 | Python | 10,303 | 296 | # -*- coding: utf-8 -*-
# Copyright (c) Vispy Development Team. All Rights Reserved.
# Distributed under the (new) BSD License. See LICENSE.txt for more info.
# Modified by C. Kirst to allow arbitrary rotations
from __future__ import division
import numpy as np
from vispy.scene.cameras.perspective import Base3DRota... |
fb8345666caf4da7b6ab21c5c431898b62f895c3d505d72182c83e1f26f7ed0a | Python | 10,304 | 229 | # -*- coding: utf-8 -*-
from figureflow import figure
import seaborn as sb
import numpy as np
import os
import importlib
importlib.reload(figure)
Figure = figure.Figure
# get the path to the data of the respective figure or movie
# the data is in the data folder in a folder with the same
# name as the folder that t... |
b5fd8aa99c18dc4c186f5bcb2716ed9178e245a6eba9ab4ef0d2da0ab458c804 | Python | 10,306 | 233 | import os
import numpy as np
import pickle
import torch
from torchvision import transforms
import copy
import tqdm
from torch import nn
from torch.utils.data import DataLoader,TensorDataset
from models.fc import excitability_modules as em
from data.available import AVAILABLE_TRANSFORMS
##------------------------------... |
784cf866281038667a93b135c5d6b2af235eb79446a1dc622e35485ce086f348 | Python | 10,307 | 238 | # -*- coding: utf-8 -*-
import pandas as pd
import os
import re
import copy
import numpy as np
import time
def goDeeper(props,this_path,a,max_a,conditions,folders):
a += 1
for newFolder in os.listdir(this_path):
print(newFolder)
if conditions[a-1] != "":
if newFolder... |
37a563886ba363e7796997ed56b0e073fc60bb7d0e009403f7cfcbf8f3fa2f4b | Python | 10,309 | 233 | import os
import numpy as np
import pickle
import torch
from torchvision import transforms
import copy
import tqdm
from torch import nn
from torch.utils.data import DataLoader,TensorDataset
from models.fc import excitability_modules as em
from data.available import AVAILABLE_TRANSFORMS
##------------------------------... |
8f13f1955acf6832adc12180f586db5b26d50bdf44b84ac030e198a79d79b50a | Python | 10,313 | 335 | from collections import namedtuple
from inspect import isclass
from itertools import tee
from functools import lru_cache
from typing import Tuple, Iterable
import numpy as np
from nl_expr.expression_walker import ReplaceExpressionsByValues
from nl_expr.expressions import Constant
from nl_expr.type_system import Unkno... |
2c9b8fea18223483acc3d5e8fe04f9c2672c46587a4e1954b3c25e3101f12754 | Python | 10,314 | 252 | """Macenko and Vahadane stain decomposition (fit + apply).
Pure DataArray/numpy layer: no ``sdata``, no public export. The stain-matrix
fits run on tissue pixels (a bounded reduction at the chosen scale); the apply
transform is a single per-pixel matmul and stays lazy.
``params`` arguments must already be resolved by... |
9c4f9078cab21883309d0eafe2eb11c7154b17077bf5b441ffc2cbacfcb3132a | Python | 10,316 | 215 | # 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... |
e4032f8b8061f9b86dcba9a5d7d3199838be7c7bea25e7e52528bfb21178c569 | Python | 10,316 | 268 |
import argparse
import json
import os
import time
import uuid
import dgl
import numpy as np
import torch.nn.functional as F
from dgl.data import register_data_args
from pytorch_lightning.metrics.classification import Accuracy
from pytorch_lightning.metrics.functional import auroc
from reactome_model im... |
79d718386707d21330a998e6cbcff18fc8280982c1e77a49c04ae82c91b4e9ef | Python | 10,322 | 258 | """Bindings for the Barnes Hut TSNE algorithm with fast nearest neighbors
Refs:
References
[1] van der Maaten, L.J.P.; Hinton, G.E. Visualizing High-Dimensional Data
Using t-SNE. Journal of Machine Learning Research 9:2579-2605, 2008.
[2] van der Maaten, L.J.P. t-Distributed Stochastic Neighbor Embedding
http://homepa... |
a47ac19a2b3988905c47f7e2b1d65cf35800b0958eafc8812a5e3d6ab3be0be9 | Python | 10,322 | 242 | import abc
import optuna
import joblib
import numpy as np
import pathlib
class BaseModel(abc.ABC):
"""
BaseModel parent class for all models that can be used within the framework.
Every model must be based on :obj:`~easypheno.model._base_model.BaseModel` directly or BaseModel's child classes,
e.g. :o... |
f624bc9bc2dd64a6a4636c1f0bec64d40b4de36ef526d80efbbf73fdd07c0710 | Python | 10,322 | 285 | import random
import time
import numpy as np
import scipy.sparse as sp
import torch
import torch.nn.functional as F
from tqdm.auto import tqdm
from ..base import InjectionAttack, EarlyStop
from cogdl.utils.grb_utils import eval_acc, feat_preprocess, adj_preprocess, getGraph, getGRBGraph
class PGD(InjectionAttack):
... |
dad0d792576a3d0261c9a757ccbdab1a155b8d4c8135e5d785a11f9dc1e5da24 | Python | 10,326 | 341 | import string, re, sys, datetime
from .core import TomlError
from .utils import rfc3339_re, parse_rfc3339_re
if sys.version_info[0] == 2:
_chr = unichr
else:
_chr = chr
def load(fin, translate=lambda t, x, v: v, object_pairs_hook=dict):
return loads(fin.read(), translate=translate, object_pairs_hook=objec... |
94634a486b49c582604af258c57d15ce42ddd425d402beaec41793c602551e33 | Python | 10,336 | 191 | import re
import sys
import os
import math
from scipy import stats
print("PPI_mutation_sites_mapping_by_disease")
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.... |
f395f0f1cdb5cdf8f64be5b16bd17af1a302beb9517bb94af18eaf4392cf398a | Python | 10,337 | 261 | """This file and its contents are licensed under the Apache License 2.0. Please see the included NOTICE for copyright information and LICENSE for a copy of the license."""
import logging
from datetime import timedelta
from core.utils.common import create_hash, load_func
from django.conf import settings
from django.db... |
13872a6f4e2bdc6b50d3c821f63dbd13d8b5e9898b96717e42ce92d02f751914 | Python | 10,338 | 288 | from sklearn.neighbors import KNeighborsClassifier
from sklearn.svm import LinearSVC, SVC
from sklearn.tree import DecisionTreeClassifier
from sklearn.ensemble import RandomForestClassifier
from sklearn.linear_model import (LogisticRegression,
LinearRegression,
... |
648f3b5c4b95062e792995b562210532aac288b314672a2936fc257024b1eab1 | Python | 10,339 | 291 | # 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 collections.abc import Mapping
from typing import final, Literal
from ax.adapter.base import Adapter
from ax.adapter.to... |
c89b7a92be286fed345886565a97c08122a77a797b6238e090d0bb129b2e5250 | Python | 10,339 | 425 | # -*- coding: utf-8 -*-
"""
NPY
===
IO interface to numpy arrays.
"""
__author__ = 'Christoph Kirst <christoph.kirst.ck@gmail.com>'
__license__ = 'GPLv3 - GNU General Pulic License v3 (see LICENSE.txt)'
__copyright__ = 'Copyright © 2020 by Christoph Kirst'
__webpage__ = 'http://idisco.info'
__download__ = 'htt... |
efc73d572c991d58c63b0f00427aef9d7e3a5e53a7e4b2bda0a1669a23fb8c4a | Python | 10,342 | 159 | # 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... |
3f497913a92c9af7c2360dabc9fac9b99c1b30fd91d72a4fa32bf3ab7b76423f | Python | 10,347 | 270 | import logging
import os
import numpy as np
from tqdm import tqdm
import torch
from utils import (
WandbLogger,
build_args,
create_optimizer,
set_random_seed,
load_best_configs,
show_occupied_memory,
)
from models import build_model
from datasets.lc_sampler import (
setup_training_datalode... |
b401a1c811a33ed9d1cc2b8b9d53dcf09467344c7d3012f12bf3c6507b80d210 | Python | 10,348 | 266 | """
Build what the in-browser REPL downloads, in OUTPUT_DIR:
- the wheels of NeuroLang's packages,
- the data the ``neurosynth`` engine needs, as a zip in the layout of its
data directory, and
- ``bundle.json``, which names them for ``doc/_static/repl/worker.js``,
- ``highlight.json``, the words the page's code box ... |
f7cb5dca558aaab2d029d365a634f636f229b8e176993d8b861e4ecd58371eef | Python | 10,355 | 338 | """
Min-heaps.
"""
from heapq import heappop, heappush
from itertools import count
import networkx as nx
__all__ = ["MinHeap", "PairingHeap", "BinaryHeap"]
class MinHeap:
"""Base class for min-heaps.
A MinHeap stores a collection of key-value pairs ordered by their values.
It supports querying the min... |
5cd3b1d6cb219b4278ecc278a49173c8900dba67b7724ff3a4e713fcee165a1a | Python | 10,358 | 315 | # -*- coding: utf-8 -*-
"""
Created on Wed Dec 4 11:35:36 2019
@author: aaussel
"""
from cells.RE_mdPul import *
from cells.TC_mdPul import *
from cells.HTC_buffer_mdPul_Destxhe_tests import *
from mdPul_one_column_v3 import *
from scipy import signal
prefs.codegen.target = 'numpy'
defaultclock.dt = 0.01*ms
run... |
94db6effd441e5a3b71a28ee5ce50909f52dc6e0d113eebcc3e960cf11eee3d9 | Python | 10,363 | 251 | # -*- coding: utf-8 -*-
"""
Example script to set up the parameters for the image processing pipeline
"""
######################### Import modules
import os, numpy, math
import ClearMap.Settings as settings
import ClearMap.IO as io
from ClearMap.Alignment.Resampling import resampleData;
from ClearMap.Alignment.Elas... |
7090d119426687e39c23fd4ec7a9ab6e8594ae3fbe284442e16a8a901fa1a2ce | Python | 10,372 | 233 | # 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 License, Version 2.0 (the
# "Li... |
381fa2cc041a7866e2a9b4b883d37c807a850976a380824de5eb0057a6112ab8 | Python | 10,373 | 186 | import pandas as pd
import numpy as np
import os
import re
import time
import csv
import pathlib
from ..preprocess import base_dataset
from ..utils import helper_functions
from ..evaluation import eval_metrics
from ..model import _param_free_base_model
class ParamFreeFitting:
"""
Class that contains all info... |
6ef85afcad558079fa2835f333d65c85681589634de38f08be561e5074211e39 | Python | 10,375 | 277 | #!/usr/bin/env python
#
# Copyright (c) 2019 10x Genomics, Inc. All rights reserved.
#
from __future__ import division
import sys
import urllib
import re
import os
import json
import subprocess
import shutil
import requests
import numpy as np
import pyfasta
from tools import ReferenceManager
from tools.io import pea... |
20ef577e47b9564d120b873b511e186d032355906e003401b7fc2531a3b14d24 | Python | 10,381 | 281 | import pytest
import networkx as nx
from networkx.utils import graphs_equal
np = pytest.importorskip("numpy")
sp = pytest.importorskip("scipy")
class TestConvertScipy:
def setup_method(self):
self.G1 = nx.barbell_graph(10, 3)
self.G2 = nx.cycle_graph(10, create_using=nx.DiGraph)
self.G3... |
85af31c2b5834a9381956a1b70aff6ad0a9b8ff18b53ad7cade8ed99ce840f8a | Python | 10,385 | 244 | #!/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
from copy import deepcopy
from typing import cast, TYPE_CHECKING
... |
2d1e54f7793fbdef3c1d2bb4e26e50311275069e39d345a96405ee3b3de2027c | Python | 10,391 | 307 | from __future__ import annotations
from importlib.util import find_spec
from typing import TYPE_CHECKING
import numpy as np
import pandas as pd
import pytest
from pandas.api.extensions import ExtensionArray
from scipy import sparse as sp
from anndata import read_h5ad
from anndata.acc import A
from anndata.compat imp... |
9618df2fefb8d4606c07e610729427ffa65a2c8a17f885385a8b87a00f8c779d | Python | 10,393 | 297 | from __future__ import annotations
from importlib.util import find_spec
from typing import TYPE_CHECKING
import numpy as np
import pandas as pd
import pytest
import zarr
from zarr.storage import MemoryStore
from anndata import AnnData
from anndata._core.xarray import Dataset2D
from anndata.compat import DaskArray
fr... |
270395fdb59fec357c62a22dab8987ed436805eb235bb9005dac6098cae7ab3e | Python | 10,400 | 297 | from __future__ import division
import matplotlib as mpl
import numpy as np
from math import log10, floor
import pybedtools as pbt
import fanc
from genomic_regions import RegionBased
style_ticks_whitegrid = {
'axes.axisbelow': True,
'axes.edgecolor': '.15',
'axes.facecolor': 'white',
'axes.grid': True... |
3b4712c54a96cf15ae6f4457ee91baf8ce7a2e990870884204a689e31a5143e1 | Python | 10,407 | 322 | from typing import Optional
import torch
import triton
import triton.language as tl
from ..triton_layout import (
_block_minor,
_neuron_grid,
_neuron_indices,
_spatial_offsets,
_time_offset,
_triton_layout_args,
)
from ..triton_surrogate import _surrogate_gradient
from .autograd import _check_... |
a844a4fac0beb74d6f2d872b0d08fb02668bf16abe953534a214dbdad68061b9 | Python | 10,408 | 241 | # 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... |
6f3be8d4ce2506352bc15c9cb3861314fbfe960ad8305cd099577935d282981a | Python | 10,411 | 252 | #!/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
from logging import Logger
from typing import TYPE_CHECKING
impor... |
6e38527a61b7b99b304337408f33f5db527855ef08677ac022e02e880a252dc7 | Python | 10,412 | 295 | #!/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,... |
47b508949848328287366e64886d3f118e1a3d2d78a76e93279857fdc1e426ac | Python | 10,414 | 264 | # -*- coding: utf-8 -*-
"""
Inteface to Illastik pixel classification
This module allows to integrate ilastik pixel classification into the *ClearMap*
pipeline.
To train a classifier ilastik should be used:
*
Note:
Note that ilastik classification works in parallel, thus it is advised to
process the da... |
436ee0c5c4cb5165d2d777c64f10eb93e7e15411db441e14af4fd2f90b609998 | Python | 10,415 | 298 | # 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
from collections.abc import Sequence
from logging import Logger
from typing import final
... |
7aac22e5b84231c848b4a951014c38c06551b4750ad09cd391a5c9154cb15c4c | Python | 10,419 | 416 | """Functions for finding and evaluating cuts in a graph."""
from itertools import chain
import networkx as nx
__all__ = [
"boundary_expansion",
"conductance",
"cut_size",
"edge_expansion",
"mixing_expansion",
"node_expansion",
"normalized_cut_size",
"volume",
]
# TODO STILL NEED TO ... |
6bb98101aa06b7d3d51f8f8f9a17e4c483cb7f012f3fabb13dab14e07747227e | Python | 10,425 | 346 | BEST_CONFIGS = {
"chebyshev": {"general": {}},
"dropedge_gcn": {"general": {}},
"gat": {
"general": {"lr": 0.005, "epochs": 1000},
"citeseer": {"weight_decay": 0.001},
"pubmed": {"weight_decay": 0.001},
"ppi-large": {
"nhead": 4,
"hidden_size": 256,
... |
0d6b76db6772ecfdc0a84dc0d5e7bb4ad27ee0464e5c50f7df8302202b0d96c3 | Python | 10,427 | 264 | from __future__ import annotations
import platform
from collections.abc import Sequence
from functools import partial
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
import pytest
import scanpy as sc
from anndata import AnnData
from matplotlib.colors import ListedColormap
from squidpy import p... |
ce1df14e9e599bf542b6cd22c60d0e69f24e5bd63581e35b75d869eb596b21ae | Python | 10,429 | 232 | #!/usr/bin/env python
# Copyright Michael Fonder 2021. All rights reserved.
# ==============================================================================
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
from utils.custom_layers import *
from utils import ... |
49b0e5981d8af68ff970cb8d4c785111ac7ae1ecfa8162f5c5072ebad829a014 | Python | 10,430 | 306 | from collections import defaultdict
from typing import (
TYPE_CHECKING,
)
from pydantic import ValidationError
from typing_extensions import Self
from galaxy.model import CollectionStateSummary
from galaxy.tool_util_models.parameters import (
AdaptedDataCollectionPromoteCollectionElementToCollectionRequestInt... |
73fc928b7d56e23fcb1e8c3923d53178494d5d47eff7271a77e686e35e08a00f | Python | 10,433 | 287 | # -*- coding: utf-8 -*-
import torch
import torch.nn as nn
from torch.nn import init
import torch.nn.functional as F
import numpy as np
class GraphConv(nn.Module):
def __init__(self, input_dim, output_dim, add_self=False, normalize_embedding=False,
dropout=0.0, bias=True):
super(G... |
d09f741fb5e3e5d70c9bb056095c4f85ab56adb8af21eab14bc0b2598be1d2d0 | Python | 10,433 | 278 | # 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... |
5eb2c2fcfd49a0150f3605d8e4ae95c5a4246857101881a1ac2858d2bf2500e3 | Python | 10,443 | 252 | import numpy as np
from brian2.core.variables import Variables
from brian2.units.fundamentalunits import Quantity
def variableview_set_with_index_array(self, variableview, item, value, check_units):
"""
Is called when a variable is set with a numerical (or slice) index and numerical target value (e.g. ``G.v[... |
3270eb345c04c36daae2cb303e18719f0b52df52191c3accb078a721d423ccee | Python | 10,454 | 301 | import torch
from dotmap import DotMap
def _get_transformed_grid(Nx_undersampled, Ny_undersampled, N_layers, thicknesses):
"""Creates x,y,z in the space [-1,1]**3 . Z weighted by thicknesses
Args:
model (torch.model): Trained neural network model. Should map one 4D input.
Nx_undersampled (i... |
660cd8bfe73e85b8025c73c3d3b01dd861ba7bfc091b4726636b70954434c5a7 | Python | 10,456 | 300 | import os
import random
import matplotlib.cm as cm
import matplotlib.pyplot as plt
import networkx as nx
import numpy as np
import torch
from grave import plot_network, use_attributes
from tabulate import tabulate
from cogdl.data import Graph
from cogdl.datasets import build_dataset_from_name, NodeDataset
from cogdl.... |
85544564fe1903034fc541a7a3841901497bef2f5062d2b28919e9e2bc373432 | Python | 10,460 | 242 | # 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... |
f048e0da8abea81a52e25aee4ffd4c02e6a2c5940dd317f34272d731d42db31b | Python | 10,461 | 253 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Tue Sep 14 16:08:34 2021
@author: kurata
"""
import os
import pandas as pd
import torch
import torch.utils.data as data
from torch.utils.data import DataLoader
from torch import optim
import numpy as np
from network import Deepnet
import argparse
import wa... |
163b0a7978eafb16b88003ae23fd9cede1340b1c9786d18dde6c97f10051474b | Python | 10,462 | 308 | import argparse
import os
import numpy as np
import math
import itertools
import torchvision.transforms as transforms
from torchvision.utils import save_image
from torch.utils.data import DataLoader
from torchvision import datasets
from torch.autograd import Variable
from mnistm import MNISTM
import torch.nn as nn
... |
84cbaafc963e284cb281cb170e08229e21ddb3d857767a1d1faf569ec688ad1e | Python | 10,467 | 266 | # 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 unittest.mock import patch
from ax.adapter.random import RandomAdapter
from ax.adapter.registry import Generators
from ... |
35b1fee77a879c6cd3c1cc019e5853955454862baecda3898c3f79df22d1052d | Python | 10,481 | 231 | # 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 License, Version 2.0 (the
# "Li... |
f6e4522db13f98dc1b8bdb2e361d16fee477d35e52bcfb72b7542a4c6ad4c85a | Python | 10,481 | 293 | #!/usr/bin/env python3
import os
import numpy as np
from param_stamp import get_param_stamp_from_args
from visual import visual_plt
import main_task_free
from utils import checkattr
from param_values import check_for_errors,set_default_values
import options
## Function for specifying input-options and organizing / ch... |
8fe5d76106a3699d54f7780f8fcf4b6ba7197a8a02e8e464691428c4ddb55665 | Python | 10,488 | 238 |
import logging
from typing import Dict, List, Optional, Tuple
from pymatgen.core import Composition, Structure
from pymatgen.analysis.phase_diagram import PhaseDiagram, PDEntry
from src import reward_utils
from src import ehull
logging.basicConfig(level=logging.INFO)
logger = logging.getLogger(__name__)
class Stru... |
3276c54e8be1fc92444a3057b60543f88df61c68cf2de09c7ef86f2434740d01 | Python | 10,489 | 262 | #!/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 warnings
from unittest import mock
from unittest.mock import MagicMock, Mock, patch
from ax.ad... |
3863bded27e56feb3c9bb18eeab9af38a2d34f55aa8bcc750ca78b08fd0f8942 | Python | 10,493 | 221 | ## This script runs the MELD surface-based FCD classifier on the patient using the output features from script 2.
## The predicted clusters are then saved as file " " in the /output/<pat_id>/xhemi/classifier folder
## The predicted clusters are then registered back to native space and saved as a .mgh file in the /outpu... |
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