sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
0d94b91c7446b691eca3c739d04d6ad6942b7379d3e3b13d56467d9eb98b7e93 | Python | 18,825 | 504 | # Copyright 2018-2026
# Institute of Neuroscience and Medicine (INM-1), Forschungszentrum Jülich GmbH
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
# http://www.apache.org/licenses/LICE... |
e2ffd15702381a3fb4d2512d04c7c9d0916304a1d9a4375967456da7dc86cd67 | Python | 18,831 | 521 | # Copyright 2019 DeepMind Technologies Ltd. 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 appl... |
8f5e58ac444769e11dd7c0a7e328896de95287cd6b05392ebc35bf5bafbeed7d | Python | 18,836 | 507 | """Tests for source/rbh_tools.py.
Covers the hex-color validator, the .rbh file parser (with dtype
enforcement), combine_rbh_db (db-mode merge), rbh_to_scafnum, and
guards/error paths in rbhdf_to_alglocdf.
"""
from __future__ import annotations
from pathlib import Path
from textwrap import dedent
import pandas as pd... |
01bdd4a4adf0b94966f5d599fe25901dd86638231b24d0cce993a16847e39859 | Python | 18,848 | 504 | # Copyright 2019 DeepMind Technologies Ltd. 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 appl... |
0daaf82e92d522ad496660505275893a1eef8e5e8f54fc0d5f7fd552e192b383 | Python | 18,848 | 459 | #!/usr/bin/env python
"""test module of `cma` package.
Usage::
python -m cma.test -h # print this docstring
python -m cma.test # doctest all (listed) files
python -m cma.test list # list files to be doctested
python -m cma.test interfaces.py [file2 [file3 [...]]] # doctest only these
or pos... |
d46e28196519b7b53332781d58d52ab8efcc187c1e7055c846802bbcca4fb532 | Python | 18,866 | 438 | """ Interlex add Triple for examples. Will have the same post triple commands for real ILX.
Notes:
1. In beta some old and all new ILX IDs are TMP: prefix instead
2. To install go into the 1st ilxutils directory and run pip3 setup.py install
3. cli.log will be created in your current directory (info an... |
662ac7b78ef1bb4c0cc224e3542a677ca06c0806076b0212ac9129bb171261d6 | Python | 18,886 | 444 | #!/usr/bin/env python
"""Patch sample generation.
For each (cell line, chromosome) named by a split spec, produce patch samples with
binary boundary labels under three references:
1. filtered_ontad (OnTAD level==1 AND TADscore>=2)
2. unfiltered_ontad (OnTAD level>=1)
3. intersection (unfiltered_ontad... |
78330e3455a67885d2e3bd4e2a0d66efc44a822ddf4abd0c0c48c66a862072ea | Python | 18,887 | 515 | # -*- coding: utf-8 -*-
# Generated by the protocol buffer compiler. DO NOT EDIT!
# source: population_server.proto
from google.protobuf import descriptor as _descriptor
from google.protobuf import message as _message
from google.protobuf import reflection as _reflection
from google.protobuf import symbol_database as... |
d3623578b9a707200b72bb9041a19067c8b14a70a1579d017adf0e12e1d5c292 | Python | 18,895 | 516 | # copyright: sktime developers, BSD-3-Clause License (see LICENSE file)
"""Implements compositor for different forecast by fh index."""
from sktime.forecasting.base import BaseForecaster
__author__ = ["fkiraly"]
__all__ = ["FhPlexForecaster"]
import pandas as pd
from sktime.datatypes._utilities import get_slice
PA... |
7dbded8dac1837acb44e4c1d927324db880949a33340d9619e12b436cc6cdc18 | Python | 18,909 | 502 | """ContractableBOSS classifier.
Dictionary based cBOSS classifier based on SFA transform. Improves the ensemble
structure of the original BOSS algorithm.
"""
__author__ = ["MatthewMiddlehurst", "BINAYKUMAR943"]
__all__ = ["ContractableBOSS", "pairwise_distances"]
import math
import time
import numpy as np
from skl... |
80af51ba3f61d6702f64119b1fbcbf8b6aefc9f53550f159727de7016794ad04 | Python | 18,919 | 431 | # Copyright 2019 DeepMind Technologies Limited
#
# 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 agr... |
a617bf456e99dfe607a0e831b52c38e2ee4c6d0634d21ccf6cd8fce4c5ddf84e | Python | 18,922 | 450 | import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import matplotlib
import seaborn as sns
from prepare_datasets_HCSC import load_data_HCSC
from prepare_datasets_ADNI import load_data_ADNI, process_descriptive_variables
def label_A(row, var, thres):
if row[var] < thres:
return 'A+'
... |
0abd5cb61cad5d2a0e124596b781bbcaebce3dd362fc779d88115aa40e7827b7 | Python | 18,960 | 489 | #!/usr/bin/env python
# import
## batteries
import sys,os
import copy
import argparse
import logging
import itertools
import statistics
from math import log
from random import shuffle
from functools import partial
from collections import deque, defaultdict
from multiprocessing import Pool
## 3rd party
import pysam
# l... |
4a234fc502c6e622f044747312d6a696652545f527e766c98bedf5aa4ca77f41 | Python | 18,976 | 445 | __author__ = 'tylin'
__version__ = '2.0'
# Interface for accessing the Microsoft COCO dataset.
# Microsoft COCO is a large image dataset designed for object detection,
# segmentation, and caption generation. pycocotools is a Python API that
# assists in loading, parsing and visualizing the annotations in COCO.
# Pleas... |
9d681e1012abd14d79d7e8a44be4d5ae489278334d5686f14b3b29ce2d3af051 | Python | 19,027 | 657 | # Copyright 2026 DeepMind Technologies Limited
#
# 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 agr... |
8ea64ce19f789d9775a6fd69a58eed727f0a371fb5dfac668dc42a436612ba4a | Python | 19,037 | 682 | # copyright: sktime developers, BSD-3-Clause License (see LICENSE file)
# Ported from skchange (BSD-3-Clause), original authors: Tveten, johannvk
"""Utility and validation functions for the detection module."""
__author__ = ["Tveten", "johannvk"]
import numbers
import numpy as np
import pandas as pd
from numpy.typin... |
f817ee1ddfd3529fae060c25d20ce91b6f0617c0e64d516b6ba986f444480a27 | Python | 19,045 | 548 | # Copyright 2019 DeepMind Technologies Ltd. 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 appl... |
1f213061981f3f96acd814072982906a5fd618b564338dfdc4f3ec1b3530d38b | Python | 19,061 | 641 | # -*- coding: utf-8 -*-
"""
Created on Sun Mar 21 13:29:40 2021
@author: TF
"""
import os
import cv2
import keras
'''from keras.applications.resnet50 import ResNet50
from keras.preprocessing import image
from keras import models, optimizers
from keras.preprocessing.image import ImageDataGenerator
from ker... |
0652c0d14334f32ac774ea0f8b4b5a8be8f9ad34008ec053ccc94faf5c8952d9 | Python | 19,076 | 546 | import os
import numpy as np
import matplotlib.pyplot as plt
import utils.allen_functions as allen
#from tensorflow.keras.models import load_model
#from tensorflow.saved_model import load
from time import time
#import atlas_generator as allen
from colormap import rgb2hex, hex2rgb
from allensdk.core.reference_space_cach... |
1f2082e6bd4cab3d6d77ca9abc30aa539581e332fa27cc90c2fdc59e142c3524 | Python | 19,081 | 610 | # -*- coding: utf-8 -*-
"""This module implements a fractional octave filter bank.
The band passes are realized with butterworth second order sections
described by [Stearns2002]_.
For the second order section filter routines the
module :mod:`sosfiltering` is used.
With the class :class:`FractionalOctaveFilterbank` you ... |
f620fff1c3116563acb2efde04c1f9456fa6265afbe623c502b3621bf8345004 | Python | 19,086 | 566 | import abc
import numpy as np
import pandas as pd
from sktime.forecasting.base import BaseForecaster
from sktime.utils.dependencies import _safe_import
torch = _safe_import("torch")
Dataset = _safe_import("torch.utils.data.Dataset")
def _get_series_from_panel(y):
"""Extract individual time series from panel/hi... |
76b591835e39332cea609fbe7151a682002c94555cdf9ce332b04d656085be58 | Python | 19,091 | 413 | """AxialTAD — model factories.
5 architectures, single factory `build(arch, patch_size, **kwargs)`:
- 'ACM' — Axial Contrast Module model (param: D ∈ {1, 2}).
'ACF' is accepted as a deprecated alias.
- 'deepTAD' — deepTAD repo Cell 3 verbatim, parameterised by patch_size
- '... |
80d7d2b743342f5112127e93c2f6d7cb85b38929e7a5d736be8dabf5cada6c93 | Python | 19,092 | 537 | import torch
import torch.nn.functional as F
import torch.utils.checkpoint as cp
from mmcv.cnn import build_activation_layer, build_conv_layer, build_norm_layer
from mmcv.runner import BaseModule, Sequential
from mmcv.utils.parrots_wrapper import _BatchNorm
from ..builder import BACKBONES
from ..utils.se_layer import ... |
5ef5bbe8e15b6a2788287a061f5616341c43bf416f6aec77518d801a1518ab68 | Python | 19,103 | 500 | # Copyright 2019 DeepMind Technologies Limited
#
# 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 agr... |
df2232bc1c18d1274070b1ab402f8ac921ddc0e9a83f5df75ae8417f8b821845 | Python | 19,107 | 527 | """Testing machine type checkers for scitypes."""
__author__ = ["fkiraly"]
from copy import deepcopy
import numpy as np
import pandas
import pytest
from sktime.datatypes._check import (
AMBIGUOUS_MTYPES,
check_is_mtype,
check_is_scitype,
check_raise,
generate_check_dict,
)
from sktime.datatypes.... |
320666f4ebbe58576e0c9c10801f2aafe24e53a964cc084e4857cc2cb1540c68 | Python | 19,114 | 566 | # Copyright 2026 DeepMind Technologies Limited
#
# 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 agr... |
ce7e2e81f1f9a42922a74bd0c4fea193f3a8289a26bb2c23b1821f921732a330 | Python | 19,119 | 551 | # Copyright 2019 DeepMind Technologies Limited
#
# 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 agr... |
975bbd554e8a6db4419f020b58f9b01787dde03cb2f8d6cc047a6565ccb2e257 | Python | 19,122 | 416 | #!/usr/bin/env python
"""
This code handles the coloring of the orthlogs in a rbh file.
There are a few ways to do this. The first way is to just color the
proteins based on their protein IDs. If the protein ID matches the
protein ID of the model, then just give the the color specified in
the model. This requires det... |
86dbe619fd037f24056a3d6da8e0ff80bc185519fd2c53e82035ec336b7ed7c5 | Python | 19,139 | 381 | #!/usr/bin/env python3
"""
Prompt tuning on a pretrained PatchTST-FM time-series foundation model.
The backbone is frozen; only the prompt module is trained. Training data comes
from the *training* portion of the GIFT-Eval datasets (see
``tabby.posttraining.data`` for the time-based train/validation split), and the
ob... |
2b258278fabf1cb2b42fc5f7907fd2ed81f712fa272779a79a791eeb25e6deb8 | Python | 19,143 | 509 | # copyright: sktime developers, BSD-3-Clause License (see LICENSE file)
"""Mantis foundation-model time series classifier."""
__author__ = ["vedantag17"]
__all__ = ["MantisClassifier"]
import numpy as np
from skbase.utils.dependencies import _check_soft_dependencies
from sktime.classification.base import BaseClassif... |
617931e36d7fa966d17d617a89f1316284b4b1b9dc8c57ba2747f5c33a935fbe | Python | 19,191 | 500 | import pickle as pkl
import os
import numpy as np
import itertools
import time
from camstim import Stimulus
from cred_assign_stims import CredAssignStims
""" Functions to initialize parameters for Gabors or Squares, and present and record stimuli.
Parameters are set here.
"""
GABOR_PARAMS = {
### PA... |
0a3ffcb0be72c05fc8b45df6fa373b626338179296b478e5f0ad9a06b0f6ab65 | Python | 19,195 | 589 | import sys
import argparse
import numpy as np
import timeit
import pyqtgraph as pg
import pyqtgraph.multiprocess as mp
# import dask
# import dask.delayed
from neuron import h
from cnmodel.protocols import Protocol
from cnmodel import cells
from cnmodel.util import sound
from cnmodel.util import custom_init
import cn... |
da093e743eef1a23e15e36dd6899d4f102254df7ba48caf0c67ade1526396283 | Python | 19,205 | 379 | from __future__ import division
import sys
import pandas as pd
import numpy as np
import seaborn as sns
import pylab as plt
from scipy.stats import mannwhitneyu
from scipy import ndimage
import mkl
from SPHARM.lib import classification
from SPHARM.lib.confusion_matrix_pretty_print import plot_confusion_matrix_from_da... |
27002e08f96c5f297aa5592e491e573dad30076a19e266fc642e0cdc96c6793a | Python | 19,226 | 651 | """Small plotting-related utility functions."""
from __future__ import print_function, division
import colorsys
import os
import numpy as np
from scipy import stats
import pandas as pd
import matplotlib as mpl
import matplotlib.colors as mplcol
import matplotlib.pyplot as plt
from .external.six.moves.urllib.request i... |
5a2eec0416f428a998f4d4a48fc34061b4123421a2281222a901d399ba4bc437 | Python | 19,226 | 572 | from typing import Tuple, Optional, Dict, Any, Union
import logging
import os
import pickle
import sys
import tempfile
import redis
from pathlib import Path
import shutil
from urllib.parse import urlparse
from urllib.request import urlopen
import numpy as np
import pandas as pd
from tqdm import tqdm
from pciSeq.src.d... |
7493732b66a6312823e7a0b48249aba48de4b31f236c4e248c50e7f8f699aa39 | Python | 19,226 | 520 | # -*- coding: utf-8 -*-
"""
Created on Thu December 10 11:41:02 2022
@author: Pawan Panwar, Quanpeng Yang, Ashlie Martini
PyL3dMD: Python LAMMPS 3D Molecular Dynamics/Descriptors
Copyright (C) 2022 Pawan Panwar, Quanpeng Yang, Ashlie Martini
This file is part of PyL3dMD.
PyL3dMD is free software: you ... |
da41d6836bdcde21e6af1112b60fb391ab6fc852bc49885e08e42ebe74d991ae | Python | 19,232 | 449 | # SAFE TEAM
#
#
# distributed under license: CC BY-NC-SA 4.0 (https://creativecommons.org/licenses/by-nc-sa/4.0/legalcode.txt) #
#
from binary_similarity.s2v_network_arith_mean import NetworkLSTM as ArithMeanNetwork
from binary_similarity.s2v_network_rnn import NetworkLSTM as RnnNetwork
from binary_similarity.s2v_netw... |
69f5ecc0f665796c14772e4381b549705b0e3ed1339ad09140caccdcc424545b | Python | 19,233 | 577 | # Copyright 2019 DeepMind Technologies Ltd. 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 appl... |
103820dbb7507100042961c82b13674716c9303d59f35fe168b6805e28ad6fb5 | Python | 19,283 | 386 | # Standard
from os.path import isfile, isdir, join
from time import time
import shutil
import pickle
import numpy as np
# Inherited class
from .BaseModel import Base
# Random seeds
from os import environ
from random import seed as rseed
import tensorflow as tf
# Plotting
import matplotlib.pyplot as p... |
7174df0717e3c64a506463180582fcbdfea1b386a2cb327a7220f2e1874d89f6 | Python | 19,305 | 393 | import json
import logging
import os
import threading
import time
from collections import OrderedDict
from concurrent import futures
from queue import PriorityQueue, Empty, Queue
from socket import gethostname
from threading import Lock, RLock
from termcolor import colored
import grpc
from mprl.utility_services.cloud_... |
7bd8b18931af48b1564229517d3594892ce11cd7a500cbbb610be7db07bc10fd | Python | 19,306 | 484 | """Generic ortholog-table importers and friends.
Provides paths into odp's `.rbh`-based pipeline that don't require the user
to run the full diamond / blastp reciprocal-best-hits step. Two input
shapes are supported:
* **Orthofinder output.** Either the raw `Orthogroups.tsv` filtered to
single-copy orthologs, or an... |
97f4b21fa6982e1010b064858d960f42d30febce0d46ae7c6ee3a8c882567c02 | Python | 19,309 | 456 | #!/usr/bin/env python3
'''
Functions for machine learning to classify ICA domains
Authors: Brian R. Mullen and Desi Ascencio
Date: 2019-04-06
'''
import os
import re
import sys
# import wholeBrain as wb
import numpy as np
import pandas as pd
sys.path.append('/home/feldheimlab/Documents/pySEAS/')
# data visualizati... |
064195c2e9fd850356c2cf20bcbe84c6cbf877ff1e68f5cee8e0c2b7311de23e | Python | 19,321 | 441 | import numpy as np
import sys
from ray.rllib.env.base_env import BaseEnv
from mprl.rl.envs.stratego.stratego_multiagent_env import StrategoMultiAgentEnv
# Need raw numba functions
from stratego_env.game.stratego_procedural_impl import _get_game_result_is_invalid
# Numba Methods
from mprl.rl.envs.stratego.stratego_pa... |
f42c7da26260191e7a8652bf863c1f2d24d7e9113ebdf81e15685cb89b8df1f9 | Python | 19,346 | 473 | """
@file: Rise.py
Created on 26.09.18
@project: crazy_ara_refactor
@author: queensgambit
Description of the RISE architecture for learning chess proposed by Johannes Czech in 2018 for CrazyAra 0.2.0.
The architecture incorporates new ideas and techniques described in recent papers for Deep Learning in Computer Vision... |
5f79f546f945ad104c4b8605aefc2730618879a61e5fb79dd24a98cab2962745 | Python | 19,354 | 524 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Mon Jan 24 15:34:54 2022
Last update: 3/4/2023
@author: sudhanshu
"""
# from importlib.abc import Loader
# from isort import file
import torch
from torch.utils.data import DataLoader
import numpy as np
import os
import sys
sys.path.append("..")
from data_p... |
56f8f472a83166c4e3312016e709d7ece1a78ba34ca1684d842a26cbc8d89fc7 | Python | 19,358 | 528 | # Copyright 2019 DeepMind Technologies Limited
#
# 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 agr... |
31e1e1ce5b75fbc5cb1090534a6de652e868c95df5aa1fa8a1f3522148df88c8 | Python | 19,360 | 430 | import pandas as pd
import torch
import torch.nn as nn
import utils
import scanpy
import anndata as ad
import pickle
import scipy
import tqdm
import matplotlib.pyplot as plt
import seaborn as sns
import sklearn
import numpy as np
import os
class TACTiCS:
def __init__(self, dict_A=None, dict_B=None, match_path=No... |
014d761c6a191f5b682cd91efd3597b88511ca842d9ab1a3530c3f5ccab3ade4 | Python | 19,387 | 382 | import pickle
import random
import matplotlib.pyplot as plt
from Bio import SeqIO
def parse_scan_prosites_results():
id2stuff = {}
next_app =False
next_append=False
with open("scan_prosite_results.fasta", "rt") as f:
lines = f.readlines()
for ind, f_ in enumerate(lines):
if f_[0] =... |
4e079f883d934404c58923386bafdacede76eb31f964da1b91f1b2d60b9c61a4 | Python | 19,396 | 421 | """AxialTAD trainer driver.
Usage:
python scripts/train.py --arch ACM --D 2 --patch 15 --ref filtered_ontad \
--output trained_models/15x15/filtered_ontad/ACM_D2 --gpu 1
Loads `*_processed.npy` from `samples/{patch_dir}/{ref}/train/`, trains for 30 epochs
at batch_size=128, saves model weights + history +... |
ba82eb737bf5f65feec56e993e72e70ac18f77561121ad4b63e99bb647c1fd45 | Python | 19,401 | 447 | """HMM Estimator.
Implements a basic Hidden Markov Model (HMM) as an detector.
To read more about the algorithm, check out the `HMM wikipedia page
<https://en.wikipedia.org/wiki/Hidden_Markov_model>`_.
"""
import warnings
import numpy as np
from scipy.stats import norm
from sktime.detection.base import BaseDetector... |
db8bf88906e337270547cba81001b833aecca19bbad0b1f0a691d95070beea37 | Python | 19,410 | 563 | # Copyright 2019-2021 The AmpliGraph Authors. All Rights Reserved.
#
# This file is Licensed under the Apache License, Version 2.0.
# A copy of the Licence is available in LICENCE, or at:
#
# http://www.apache.org/licenses/LICENSE-2.0
#
#import tensorflow as tf
import tensorflow.compat.v1 as tf
import abc
import lo... |
ad53f064171829004a5fafe1909939d94b04c4984141222acc0b267c93486250 | Python | 19,451 | 590 | """
"""
from typing import Union, Tuple, List
import matplotlib.pyplot as mpl
import numpy as np
import seaborn as sns
from vcnmodel.util import trace_calls
from vcnmodel.analyzers import analysis as SPKANA
import vcnmodel.analyzers.flatten_spike_array as VAFlatten
from vcnmodel.util.basic_units import radians
from vc... |
75f9a7dcc54d37c30b57cba980533a315a1e7f74031098486bb8cfc3d0dd8131 | Python | 19,460 | 539 | # Copyright 2019 DeepMind Technologies Ltd. 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 appl... |
91291ed2c99d347017e2455fa18f2ff4362d66ed98b73d3ba2c54811b31567a7 | Python | 19,483 | 482 | # Copyright 2022 DeepMind Technologies Limited
#
# 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 agr... |
62118bbdacfaeaaf49fa37d9a8df668352bca5578653894405de62d378168600 | Python | 19,485 | 377 | from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import json
import logging
import os
import shutil
import time
import dill
import numpy as np
import ray
from mprl.utility_services.payoff_table import PolicySpec
from mprl.utility_services.worker import Learn... |
483ee6b206f9454873ab88a1dd54abcc11c7b97e023350543f42366824b501b8 | Python | 19,490 | 600 | """Tests for the orthologs-to-rbh import path.
Covers:
- BED parsing (4-column, 6-column, CRLF, blank lines, bad rows).
- Orthologs-table parsing (with and without orthogroup-id column,
auto-detection, header row, --species-order override, multi-copy
rejection, empty cells, mismatched column counts).
- Join + .rbh... |
d0d1b8ca31d89badbb06c586796c75bb3b5251401cda778304947dc68b1abaca | Python | 19,491 | 514 | from __future__ import annotations
from io import BytesIO
from typing import TYPE_CHECKING, Any, Literal
from .core import AdaptationError, Adapter, Pass
from .lib import FlagsContainer, HexString, bin_to_int, int_to_bin, swap_bytes
if TYPE_CHECKING:
from collections.abc import Callable, Hashable, Mapping, Sized... |
e4030464c8f49ea886d2c4b3c7660c2e707d7b497fb4ac4162d0e958ae37961e | Python | 19,505 | 528 | from itertools import chain
import numpy as np
from sklearn.metrics import normalized_mutual_info_score, adjusted_rand_score, r2_score, confusion_matrix
from scipy.optimize import linear_sum_assignment
import torch.nn as nn
import torch.optim as optim
import torch.utils.data as D
from tqdm import tqdm
from src.data im... |
c19c26fc495e1077f90e70d8b0fd69119151e23af906629a936f3b54b47009c6 | Python | 19,506 | 466 | import pandas as pd
import matplotlib
matplotlib.use('Agg')
import matplotlib.pyplot as plt
# import shap
from keras.models import load_model
# import PyNonpar
# from PyNonpar import *
import scipy as sp
# import seaborn as sns
import time
from scripts_tl import data_handler_tl as dh_tl
from scripts_tl i... |
55a65cb996ce3af332542a48df81459447e63d15f0c3031724471ee9993b97c8 | Python | 19,511 | 544 | # Copyright 2019 DeepMind Technologies Limited
#
# 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 agr... |
04409c27508370f5d27545840d4b5ed74ff29a2f1676db16bbe860a0e88101bf | Python | 19,527 | 386 | # Copyright 2019-2021 The AmpliGraph Authors. All Rights Reserved.
#
# This file is Licensed under the Apache License, Version 2.0.
# A copy of the Licence is available in LICENCE, or at:
#
# http://www.apache.org/licenses/LICENSE-2.0
#
from .EmbeddingModel import EmbeddingModel, register_model
from ampligraph.late... |
ef06bea6a7518567bd25d033dec9b777cd5b3b89d63551b37f530c98ef53b32c | Python | 19,529 | 445 | import argparse
import csv
import logging
import multiprocessing
import os
import pickle
import sys
from collections import Counter
from datetime import datetime
from pathlib import Path
from typing import Dict, List, Optional, Union
import pandas as pd
import rdkit.Chem as Chem
import rdkit.Chem.AllChem as AllChem
fr... |
1c5aaa0cd8142648ad5b63ba978aea9effce79d2e31d6aa6f922248e358da85c | Python | 19,540 | 403 | from __future__ import print_function
from neuron import h
import numpy as np
from .cell import Cell
#from .. import synapses
from ..util import nstomho
from ..util import Params
from .. import data
__all__ = ['TStellate', 'TStellateRothman']
"""
Class to instantiate T stellate (planar multipolar) cells from the co... |
8942edd8ae4e89ba939572bd28edd87b7ac067b087f6510c12dfa0148973f5e0 | Python | 19,560 | 472 | # SPDX-License-Identifier: LGPL-3.0-or-later
from typing import (
Any,
)
import torch
from deepmd.dpmodel.common import (
get_xp_precision,
)
from deepmd.dpmodel.descriptor.dpa4 import DescrptDPA4 as DescrptDPA4DP
from deepmd.dpmodel.descriptor.dpa4_nn.activation import SwiGLU as SwiGLUDP
from deepmd.dpmodel.... |
aae0b8237e97702f7c1894091ab03c08467d32c51f570d0053f77a2c4b043730 | Python | 19,560 | 619 |
from pathlib import Path
from typing import List, Union
import matplotlib.pyplot as mpl
import numpy as np
import pandas as pd
import seaborn as sns
from lmfit.models import GaussianModel
from matplotlib import collections as mc
from pylibrary.plotting import plothelpers as PH
from pylibrary.tools import cprint as CP... |
5bb942b0292eb3e7838945a3a041531e13e8a08c32df7e2afc24278518aaacd6 | Python | 19,562 | 365 | import math
import torch
import torch.nn as nn
from vp_suite.model_blocks import SpatioTemporalLSTMCell as STCell,\
ActionConditionalSpatioTemporalLSTMCell as ACSTCell
from vp_suite.base import VPModel
import torch.nn.functional as F
from tqdm import tqdm
class PredRNN_V2(VPModel):
r"""
This is a reimplem... |
6c03ade28c86db796e1da43149e9ca11a902ca14d80ec9d1d77029d1e766eb27 | Python | 19,571 | 609 | # Copyright 2026 DeepMind Technologies Limited
#
# 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 agr... |
713eb0a09b31a0c221b7191dc9351d3c153b64bc0f819fd4e7aed434cfd36a8b | Python | 19,581 | 514 | import os
import torch
import torch.nn as nn
import torch.optim as optim
import torchvision.transforms as transforms
from torch.utils.data.sampler import SubsetRandomSampler
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import time
from tqdm.notebook import tqdm
from skimage import io
from scip... |
0249803521c44fdc59d60f21771530a32f0c53ba8481c49d7e301225ec1dc0f7 | Python | 19,618 | 585 | # Copyright (c) ONNX Project Contributors
#
# SPDX-License-Identifier: Apache-2.0
from __future__ import annotations
import numpy as np
import onnx
from onnx.backend.test.case.base import Base
from onnx.backend.test.case.node import expect
def compute_negative_log_likelihood_loss(
input, target, weight=None, re... |
ccbd9f14efe2ae14f973a1d096ec432de2b9d84a2756d5c09c791b27470e8e7d | Python | 19,640 | 540 | import logging
import pathlib
import random
from collections import defaultdict
from enum import Enum
from functools import reduce
from math import inf
from pathlib import Path
from typing import Literal, NamedTuple, Optional, Union
from numpy import ndarray
from scipy.stats import pearsonr, spearmanr
from sklearn.met... |
46f009d1924ac4c58be19b05a36c6684859deef4dffe1cf2b136b03dad183edc | Python | 19,642 | 539 | # =============================================================================
# IMPORTS
# =============================================================================
from collections import OrderedDict
import functools
import math
import operator
import torch.nn.functional as F
import torch.utils.data
import torch.... |
67b73c6d0ff0b3cd587794195b99033e0b6453a5a19026d7f861acf48ccf65c3 | Python | 19,668 | 525 |
#=======================================================================================================================
# Copyright (C) 2021 Matvey Safroshkin, Grigory Arutyunov, Patrick Mueller
# Computer Vision Studio
# Friedrich Miescher Laboratory of the Max Planck Society
# Systems Biology of Development, Univer... |
560e2cc99877259c34c8ba32d4eaa83198d83ebb021328e61cad1768acae6c65 | Python | 19,683 | 595 | """Continuous interval tree (CIT) vector classifier (aka Time Series Tree).
Continuous Interval Tree aka Time Series Tree, base classifier originally used in the
time series forest interval based classification algorithm. Fits sklearn conventions.
"""
__author__ = ["MatthewMiddlehurst"]
__all__ = ["ContinuousInterval... |
7c84747e49ffb6b5034ba197b8d622b91bd91e28cc14945adfb664d7f0e7333f | Python | 19,700 | 483 | # Copyright (c) OpenMMLab. All rights reserved.
import math
import warnings
import torch
import torch.nn as nn
from mmcv.cnn import (build_norm_layer, constant_init, kaiming_init,
normal_init, trunc_normal_init)
from mmcv.cnn.bricks.transformer import FFN, MultiheadAttention
from mmcv.runner impo... |
c60563dd14ddec7fa95d369018fb95162e01949ff10b95b03b27ff426a15d58d | Python | 19,711 | 506 | # Copyright 2019 DeepMind Technologies Ltd. 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 appl... |
ef576b68457fbb8835c79cd589f47122a0f4f64c59ca2cae63bc3915cedf8973 | Python | 19,714 | 495 | """Utilities for SingleCellFusion
"""
from .__init__ import *
import functools
import collections
import itertools
import re
from scipy import sparse
from scipy.stats import zscore
import fbpca
import sys
import logging
import fbpca
import anndata
from . import basic_utils
from . import clst_utils
def sparse_adj_to_... |
58cab96aa9abd730d1b13965bfd2dba1f263012eac05aa8c114d79db0f4488ee | Python | 19,717 | 642 | # Copyright (c) ONNX Project Contributors
#
# SPDX-License-Identifier: Apache-2.0
from __future__ import annotations
import numpy as np
import onnx
from onnx.backend.test.case.base import Base
from onnx.backend.test.case.node import expect
class GridSample(Base):
@staticmethod
def export_gridsample() -> Non... |
06706763010736d234bf6b2846f3a43e870e01ddc3571e22cd74185101bcb442 | Python | 19,719 | 476 | """
@file: builder_util
Created on 31.05.22
@project: CrazyAra
@author: queensgambit
Utility methods for building the neural network architectures.
"""
import math
import torch
from torch import nn
from torch.nn import Sequential, Conv1d, Conv2d, BatchNorm2d, ReLU, LeakyReLU, Sigmoid, Tanh, Linear, Hardsigmoid, Hards... |
5d1dbc3414d7e48b688813cd95bdc9d2d925ad1313629089be56136b3285ced3 | Python | 19,720 | 417 |
"""
Main test script
"""
import model
import numpy as np
import matplotlib.pyplot as pl
import utilities
import seaborn as sns
from scipy.signal import convolve
import time
from pandas import DataFrame, concat
from taylorDecomp import taylor_decompose
import matplotlib as mpl
import os
import statsmodels.formula.api ... |
e5fa3f2d2b28a026dde824a47496d40233a91e98758739cc0197177303ec900b | Python | 19,725 | 590 | # Copyright 2019 DeepMind Technologies Ltd. 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 appl... |
c5c151d330ee9f022949537ba6ba14d34131b7145608326d98780d3e9ec8f46f | Python | 19,732 | 226 | #!/bin/python3
# Author: Thomas Rolland jerikoo75@gmail.com
# Date: 03/31/2022
import pandas as pd
from numpy import mean, std
from plotnine import *
import statsmodels.stats as sm
from statsmodels.miscmodels.ordinal_model import OrderedModel
from statsmodels.formula.api import ols
#==================================... |
94025e0ebbcf222ce8e6a1a693969c942a6dd8be16569ffce02e14180143c46c | Python | 19,737 | 657 | import json
import os.path
import pickle
from collections import defaultdict, OrderedDict
import pygel3d.gl_display
import pyvista
from scipy.interpolate import RegularGridInterpolator
from scipy.ndimage import distance_transform_edt
from utils import *
from pygel3d import graph
from pygel3d import hmesh
import numpy... |
9583ae5cff7e8ba162e4e523a12045b724469999fbeb6f24a5a09fd686a0199b | Python | 19,740 | 704 | # Copyright 2026 DeepMind Technologies Limited
#
# 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 agr... |
d0f747cf368dd08f39fbb830e305b4cc163e53f41ab026998fe03b5a6996702d | Python | 19,761 | 625 | """
test_utilities.py
Miscellaneous utility functions. For the most part this module serves as
a custom circular statistics library.
References:
Shaverdian et al. (2022) - Weighted Cue Integration for Straight-line orientation
Wilkie (1983) - Miscellanea Rayleigh test for Randomness of Circular Data
Batschelet (1981)... |
60829f80b7bac9037cc06f66b6ab50e82450a18698ab8f4ec5da02b0391d71ea | Python | 19,763 | 404 | from __future__ import print_function
from neuron import h
import numpy as np
#import neuron as nrn
from .cell import Cell
from .. import synapses
from ..util import nstomho
from ..util import Params
from .. import data
__all__ = ['Tuberculoventral']
class Tuberculoventral(Cell):
celltype = 'tuberculovent... |
36db9039d5877a458ed0fc701b27595e7880c40237d2072a8bb04133f62ddb6a | Python | 19,764 | 488 | # Copyright 2019 DeepMind Technologies Ltd. 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 appl... |
9a27ca6b43ead320bfe5c210da2427d2e24da77342c8ee3f591e7c4390a172e1 | Python | 19,780 | 551 | # copyright: sktime developers, BSD-3-Clause License (see LICENSE file)
"""Interface for the TSPulse time series classifier via granite-tsfm."""
__author__ = ["Faakhir30"]
__all__ = ["TSPulseClassifier"]
import tempfile
from copy import deepcopy
from sktime.classification.base import BaseClassifier
from sktime.utils... |
f4fd2ef30882aad42ecdad5322dd29531c98e9fdad5f7312813318ba1b0d6ce7 | Python | 19,787 | 414 | from __future__ import annotations
from dataclasses import dataclass
import decimal
from functools import lru_cache
import math
from numbers import Real
from typing import Any
from typing import cast
from typing import TYPE_CHECKING
import numpy as np
from optuna._experimental import experimental_class
from optuna.d... |
4833853cb11bbaa93e649e1bfc69b8b50b069bd3c6f8f5b0d3831ec2f1f25796 | Python | 19,818 | 625 | # coding=utf-8
# Copyright (C) 2021. Huawei Technologies Co., Ltd. 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
#
# ... |
335c140558989d6cedb94b2c6b8d0f9e063dfee5440a574bca444a81667aed30 | Python | 19,845 | 469 | # This file provides functions to perform the oversampling and undersampling of compositional data.
# Author : Teo Nguyen
import random
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from scipy.stats import gmean
from sklearn.preprocessing import StandardScaler
###############################... |
76d1bec4fd392486399e302858dc433f564a12de1fdeb4938bc119d67032ab89 | Python | 19,851 | 462 | # Copyright (c) ONNX Project Contributors
# SPDX-License-Identifier: Apache-2.0
from __future__ import annotations
import numpy as np
import onnx
from onnx.reference.op_run import OpRun
from onnx.reference.ops.op_matmul import numpy_matmul
_INPUT_RANK_3D = 3
_INPUT_RANK_4D = 4
_QK_MATMUL_OUTPUT_WITH_BIAS = 2
_QK_MA... |
24868c756796253ce565ff9e3ea41e0e016550a8e190d2c0f319feab890425a0 | Python | 19,852 | 516 | # Copyright 2019 DeepMind Technologies Ltd. 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 appl... |
5cae4d9b9cd1db4404981e7b7b5b5443827cf11174fdeebadec16f7bda3a9651 | Python | 19,909 | 485 | # Copyright 2019 DeepMind Technologies Ltd. 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 appl... |
bc06bb19e955a55993bbcb5462f535b67d087ef805b6a21b31e64e00fbc4690c | Python | 19,920 | 576 | # Copyright 2019-2021 The AmpliGraph Authors. All Rights Reserved.
#
# This file is Licensed under the Apache License, Version 2.0.
# A copy of the Licence is available in LICENCE, or at:
#
# http://www.apache.org/licenses/LICENSE-2.0
#
import numpy as np
import pytest
import os
from ampligraph.latent_features imp... |
d6839f569def88d29a3ccdc79b5b40389ba5cc29f9421729a2cd16b77642b4da | Python | 19,924 | 589 | import numpy as np
import matplotlib as mpl
import matplotlib.pyplot as plt
import pandas as pd
import nose.tools as nt
import numpy.testing as npt
try:
import pandas.testing as pdt
except ImportError:
import pandas.util.testing as pdt
from numpy.testing.decorators import skipif
from nose import SkipTest
try:... |
56ba6523a1ccdb77bbdb0b924c0ea479db68efd0b6b0ba211518b25c075afe3a | Python | 19,954 | 235 | # this program calculates
# (i) micro-level and macro-level precision, recall, and F1
# (ii) instance-based precision, recall, and F1 - optional, this has issue to deal with non-rare disease documents, i.e. for this (pred-true) pairs (0,0,0 - 0,0,0) and (1,0,0 - 0，0，0） will have the same precision, recall, and F1 sc... |
15422172f64d29ca9be7543d6cb06c1a65cb28ec92da3cc6bc71b6bb1429629e | Python | 19,962 | 466 | # Copyright 2019-2021 The AmpliGraph Authors. All Rights Reserved.
#
# This file is Licensed under the Apache License, Version 2.0.
# A copy of the Licence is available in LICENCE, or at:
#
# http://www.apache.org/licenses/LICENSE-2.0
#
import numpy as np
from ..datasets import AmpligraphDatasetAdapter
import tempf... |
0a7971c6606c328ddb4e96c5f957f482b8ba0e6af6c6f90d95959e4530414f88 | Python | 19,974 | 554 | import re
from enum import Enum
class XiangqiBoard:
"""
Represents a Xiangqi board.
The board is initialized from the view of the red player (on the bottom).
Empty fields and fields without figures of the corresponding player are represented as zeros.
"""
def __init__(self):
self.figu... |
e57ef2ce06358497984059e2b801746ba2f28f0f17e7f04a44c7de0ebe515f6c | Python | 19,978 | 459 | # Copyright 2019 DeepMind Technologies Limited
#
# 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 agr... |
229c0b08836a88c3107079c12c370244ce38c0ef5ae0da2b65698da615e25405 | Python | 19,989 | 435 | import numpy as np
import numpy.typing as npt
from scipy.stats import rankdata, t, f
from typing import Optional
def pearson_coefficient(
feature_arr: npt.NDArray[np.float_],
joint_dist: npt.NDArray[np.float_],
permutations: int,
) -> npt.NDArray[np.float_]:
r"""
Let X, Y be two random variables o... |
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