sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
13744e903b5e8284bfcd265d9d926ce70370d5c7860d92ca7e941900bec1726c | Python | 2,996 | 73 | # Copyright 2024 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
#
# https://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed... |
186ed1258767506cd941bb856dc49f3cf7adb98fd562dfaa486bf7de0ce6a8f8 | Python | 2,996 | 81 | import os
import sys
import re
import types
import itertools
from cgatReport.Tracker import *
from cgatReport.odict import OrderedDict as odict
from cpgReport import *
##########################################################################
class MappingSummary(cpgTracker, SingleTableTrackerRows):
table = "ba... |
bf1f4d802ef91d903ce01acff5ba5b04e4c57258695569c4dc2efbc5256d148a | Python | 2,997 | 77 | """
adopted from SHINE/utils/attention.py
https://github.com/luoyuanlab/SHINE/blob/main/utils/attention.py
"""
import torch
import numpy as np
from torch import nn
class Attention(nn.Module):
def __init__(self, encoder_dim: int, decoder_dim: int):
super().__init__()
self.encoder_dim = encoder_dim... |
ffb2d0ad1dc3588b69ef2ac26e8ebb9a5b5b41671d2a951c8db9ba4bb9a1054c | Python | 2,997 | 81 | import numpy as np
from .get_atom_kdtree import getAtomKDTree
def getAngle(v1, v2):
cp = np.cross(v1, v2, axis=-1)
dp = (v1*v2).sum(axis=-1)
return np.arctan2(np.linalg.norm(cp, axis=-1), dp)
def getEffectiveInteractions(X, Y, omega):
atoms = np.array(Y)
X = X.coord
Y = np.array([y.coord ... |
72f37de1a7c1be6a2b0aca1bf6d0b11fd527f2a5468c50ebd9e216157816236b | Python | 2,998 | 92 | import torch
import numpy as np
import matplotlib.pyplot as plt
from data import generate_recog_data, recog_chance
from net_utils import binary_thres_classifier_accuracy
#%%
m=350 #filter size (m=350 <=> 350 KCs projectng to MBON_alpha'3)
r=6 #sampling rate random projection (r=6 <=> each KC gets input from ~6... |
293b128aa1b407154aae2e1a8c77c16d6957161c1a65a4396d3d91f6f35a4b3f | Python | 2,999 | 84 | import torch
def drop_path(x, drop_prob: float = 0., training: bool = False):
if drop_prob == 0. or not training:
return x
keep_prob = 1 - drop_prob
shape = (x.shape[0],) + (1,) * (x.ndim - 1) # work with diff dim tensors
random_tensor = keep_prob + torch.rand(shape, dtype=x.dtype, de... |
907dc45b793227db4489e3a10c7797cb8be3357e0c7b24cf02d5c910804f59db | Python | 2,999 | 106 | import pickle
import matplotlib as mpl
import matplotlib.pyplot as plt
import numpy as np
import figure_config
mpl.rcParams.update(figure_config.mpl_style)
LOG = True
def plot_weights(ax, w, *, ylabel):
ax.set_ylabel(ylabel, fontsize=figure_config.fontsize_xsmall)
ax.set_xlim(plot_params["xlim"])
ax.s... |
24350f41c33da385180935f07315e929e445018e3d6c688e9603379a23d12128 | Python | 3,001 | 98 | import numpy as np
import struct
def readmda(fname):
f = open(fname, "rb")
try:
code=struct.unpack('i', f.read(4))[0]
except:
raise IOError("Problem reading file: %s" % (fname))
if code > 0:
num_dims = code
code = -1
else:
f.read(4)
num_dims = struct.... |
1b3e0d0bccd9b75f08fe925324e5dac04ed1689b526163c7625c3a9bdcecb753 | Python | 3,002 | 112 | #%%
# import pandas as pd
import numpy as np
import time
import pandas as pd
linux = False
import os
#%% Import scripts
#from xgboost import XGBRegressor
directory = os.getcwd()
if directory[0] == "/":
linux = True
else:
linux = False
#%% Import scripts
import sys
if linux == True:
directory_functions =... |
e29e52feff7e7c3b0e14c615c0d4fbeeff262b00ca6dcf655c2266ef3703302d | Python | 3,003 | 96 | from typing import Dict, Tuple, List
import numpy as np
import scipy.stats as stats
from scipy.signal import welch
from scipy.spatial import ConvexHull
from modules.utils import naive_diff
def get_all_features(x: np.ndarray, name: str, dt: float, abs: bool = False) -> Tuple[List, List]:
features, names = [], []... |
45589ad7bb7f85814e1995ce7cd256d33a7f2f0a328f995a6f823aeca947417a | Python | 3,004 | 92 |
import sys
sys.path.append('../classes')
import class_model
import class_stimuli
import numpy as np
import pickle
import matplotlib
matplotlib.use('Agg')
import matplotlib.pyplot as plt
### MAIN SCRIPT
stimulus_tasks = ['varyposition', 'varysize', 'varyrotation']
stimulus_folder = '../stimuli/simple_seqs/'
save... |
f591180fd9647d0a068947ba63b5087c9cd69c635f955e16210c27e815f1bcb9 | Python | 3,005 | 84 | ####################################################################################
#
# STEPS - STochastic Engine for Pathway Simulation
# Copyright (C) 2007-2026 Okinawa Institute of Science and Technology, Japan.
# Copyright (C) 2003-2006 University of Antwerp, Belgium.
#
# See the file AUTHORS for detai... |
fa438e0e69ffd2c76fccac17092667f3009779b64992f891722482e512f94a70 | Python | 3,005 | 77 | import numpy as np
import scipy
def get_bins(max_bin, num_bins):
# generates bins for discretizing network activations
return np.linspace(0, max_bin, num_bins)
def get_IQR_bins(layer, num_bins):
IQR = scipy.stats.iqr(layer)
maximum = np.quantile(layer, 0.75) + 1.5*IQR
minimum = np.quantile(layer, ... |
ea59890ae90641d852b45d4dd4232f436253891530701b399ccd93b795caa5c0 | Python | 3,007 | 97 | from typing import Any
from langchain_core.callbacks.manager import CallbackManagerForLLMRun
from langchain_core.language_models.chat_models import BaseChatModel
from langchain_core.messages import AIMessage, BaseMessage
from langchain_core.outputs import ChatGeneration, ChatResult
from pytest_mock import MockerFixtur... |
8d3219cef94faca2b745640d739b81676031fed29cf7f064a18654cdb7a4ca1f | Python | 3,009 | 65 | import os
import argparse
import torch
from runner import Runner
from dataset import MatDataset
from torch_geometric.data import DataLoader
from utils import smact_validity, compute_elem_type_num_wdist, get_structure, compute_density_wdist, structure_validity
parser = argparse.ArgumentParser()
parser.add_argument('--m... |
7470d287ffebd1d581f68d18fe31e5d25d627bffef6e5a025f4fd5cf10be9cff | Python | 3,013 | 89 | """Question-answering with sources over a vector database."""
import warnings
from typing import Any
from langchain_core.callbacks import (
AsyncCallbackManagerForChainRun,
CallbackManagerForChainRun,
)
from langchain_core.documents import Document
from langchain_core.vectorstores import VectorStore
from pyda... |
95486824ba98158dd48ba5f1fbaa73d57d7021744d20cabfd14d59574b75df52 | Python | 3,013 | 91 | import sys, os, gzip
from collections import defaultdict
from rdkit import Chem
sys.path.append('..')
def read_rd_mols_from_sdf_file(sdf_file, removeHs=False, sanitize=False):
if sdf_file.endswith('.gz'):
with gzip.open(sdf_file) as f:
suppl = Chem.ForwardSDMolSupplier(f, removeHs=removeHs, ... |
f1eeb048adafbd7cf3d07e433fb0f9dfe365eb9b388f7100569bc8d0c24b7bfe | Python | 3,016 | 85 | # language=rst
"""
This code is directly pulled from the pytorch version found at:
https://github.com/pytorch/pytorch/blob/master/torch/utils/data/_utils/collate.py
Modifications exist to have [time, batch, n_0, ... n_k] instead of batch in dimension 0.
"""
import collections
import torch
from torch.utils.data._uti... |
33b2d6bfa53d5e20e4c837efb7268e0d311e7c97e05f75ff2a7b1e27ab10467a | Python | 3,018 | 81 |
import scanpy as sc, anndata as ad
import numpy as np
import pandas as pd
if __name__ == "__main__":
path_rawdata_mouse = "./brain_human_mouse/mouse_brain_region_67_sparse.h5ad"
adata = sc.read_h5ad(path_rawdata_mouse)
sc.settings.verbosity = 3
#sc.settings.set_figure_params(dpi=80)
... |
ac7b87226c1fc24eb3b7a045183fa811c8a469b5b9902047524f33c20ddb7292 | Python | 3,018 | 105 | """
Write TIP5P parameters into a SMIRNOFF force field. Based on
https://docs.lammps.org/Howto_tip5p.html
"""
from pathlib import Path
from openff.toolkit.typing.engines.smirnoff.forcefield import ForceField
from openff.toolkit.typing.engines.smirnoff.parameters import (
ConstraintHandler,
ElectrostaticsHandl... |
86bc847b070d01de13a6010208e7bf104f790e8d2c4da7bbf7dd4a8365c5c469 | Python | 3,020 | 77 | # Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved.
#
# NVIDIA CORPORATION and its licensors retain all intellectual property
# and proprietary rights in and to this software, related documentation
# and any modifications thereto. Any use, reproduction, disclosure or
# distribution of this sof... |
180f99872f668b40c0bcf33fa42051868cd5e45489f87b3a403e27cd10451b71 | Python | 3,022 | 78 | #!/usr/bin/env python3
import os
import pandas as pd
import numpy as np
import joblib
import pysam
import math
import tempfile
import multiprocessing
import gzip
def count_reads_in_regions(bam_file, regions):
"""Count the number of reads in a BAM file for a list of regions using pysam."""
bam = pysam.Alignmen... |
659fe4824af91dda7a5be17df9155be86a49667265864262a3d2bc90f0658429 | Python | 3,022 | 82 | import math
from itertools import combinations
import pandas as pd
from tqdm import tqdm
from pgmpy.base import DAG
from pgmpy.ci_tests import get_ci_test
from pgmpy.global_vars import config
from pgmpy.metrics import BaseUnsupervisedMetric
class ImpliedCIs(BaseUnsupervisedMetric):
"""
Tests the implied Con... |
d706b2101131a759ad5629a849c005ccb382fbd251dfae5d1fba9bdab841a006 | Python | 3,024 | 99 | import torch.nn as nn
import torch.nn.functional as F
from inspect import getmembers, isfunction
from . import channels
from ..utils import utils
from ..utils.utils import *
class ZephOD(nn.Module):
def __init__(self,
n_channels_in=6,
n_channels_out=1,
init_nod... |
872977185457504dd78ee04ec4d370bf8508ba569a40ddf75384a3f090f4bdb4 | Python | 3,025 | 76 | # Differentiable Augmentation for Data-Efficient GAN Training
# Shengyu Zhao, Zhijian Liu, Ji Lin, Jun-Yan Zhu, and Song Han
# https://arxiv.org/pdf/2006.10738
import torch
import torch.nn.functional as F
def DiffAugment(x, policy='', channels_first=True):
if policy:
if not channels_first:
x ... |
a38f17457b3610971a08e58f2d5ffc913728564f3800b0f1a4ba62e27018ba52 | Python | 3,027 | 77 | """A server behind a full OAuth 2.1 flow, with no client credentials up front.
This one process plays two roles that are normally separate:
- Resource Server: serves `/mcp` and rejects unauthenticated calls with a 401
pointing at its protected-resource metadata.
- Authorization Server: serves discovery, `/register`... |
9c49b3cffb2577ebc2e8b46dacbaf3355daa38c49d60110d95cdde37a659c136 | Python | 3,028 | 54 | import numpy as np
import matplotlib.pyplot as plt
# Plot behavioral response from 10 seconds before addition of stimulus to 60 seconds after addition with the curve
# fit to the data. Takes a dataframe with the behavior data (proportion of 2 week old and 2 month old ants
# outside the nest at timepoints -60 to 60), a... |
92045bf63fcbc6fa99eb3c0bc92cabe1396f886c2eebc2b345fd9d77133cd246 | Python | 3,029 | 80 | import pandas as pd
import sys
from mantis_ml.modules.pre_processing.data_compilation.process_generic_features import ProcessGenericFeatures
from mantis_ml.config_class import Config
class ProcessCardiovascularSpecificFeatures(ProcessGenericFeatures):
def __init__(self, cfg):
ProcessGenericFeatures.__in... |
d0b87655ce1ba50f666dfa1a3d316dbda5c506bead04194888b034a5f03ef407 | Python | 3,031 | 101 | """A prompt is the input to the model.
Prompt is often constructed from multiple components and prompt values. Prompt classes
and functions make constructing and working with prompts easy.
"""
from typing import TYPE_CHECKING
from langchain_core._import_utils import import_attr
if TYPE_CHECKING:
from langchain_... |
0ae0cbb877b87d113e29d0f000185b84d0dadbc31cb260ef03ad556b7eadff31 | Python | 3,032 | 82 | #### This script compares GENCODE version 25 with version 41.
import session_info
import polars as pl
import seaborn as sns
from pyhere import here
import matplotlib.pyplot as plt
from scipy.stats import spearmanr
def load_annotation(fn, region, sex):
return pl.read_csv(fn, separator="\t")\
.filter((... |
7b3975183b29458d60f30573d8574357d0a12f6f2256f74d0a92d3f525210cf2 | Python | 3,032 | 74 | import pandas as pd
'''
#step 1 读取CSV文件
input_file1 = "F:/BIDE/statement/ABIDEI.csv"
input_file2 = "F:/BIDE/statement/ABIDEII.csv"
output_file1 = "F:/BIDE/statement/out1.csv"
output_file2 = "F:/BIDE/statement/out2.csv"
# 读取CSV文件并指定第一行为列名
df = pd.read_csv(input_file2, header=0)
# 筛选数据：SRS_RAW_TOTAL和SRS_AWAR... |
c3fd3a91fb81307f103fdd0f4475d0240e8594c375fff6f8022a43d99fe38a8d | Python | 3,032 | 98 | import argparse
from joblib import Parallel, delayed
import pandas as pd
import mne
from mne_bids import BIDSPath
import autoreject
from utils import prepare_dataset
DATASETS = ['chbp', 'lemon', 'tuab', 'camcan']
parser = argparse.ArgumentParser(description='Compute autoreject.')
parser.add_argument(
'-d', '--da... |
84f7adb0458da0c347af929ab5ba5a02fb839abb90744cf60da8e641a17a8541 | Python | 3,034 | 85 |
import scanpy as sc, anndata as ad
import numpy as np
import pandas as pd
if __name__ == "__main__":
path_rawdata_human = "./brain_human_mouse/human_brain_region_88_sparse.h5ad"
adata = sc.read_h5ad(path_rawdata_human)
sc.settings.verbosity = 3
#sc.settings.set_figure_params(dpi=80)
... |
72789b6a2139d971d3b307a2fc009ee06bb9a99e5b020c215f47eb8761c237c3 | Python | 3,035 | 104 | """Test string utilities."""
from langchain_core.utils.strings import (
comma_list,
sanitize_for_postgres,
stringify_dict,
stringify_value,
)
def test_sanitize_for_postgres() -> None:
"""Test sanitizing text for PostgreSQL compatibility."""
# Test with NUL bytes
text_with_nul = "Hello\x00... |
29e28d8a061660acef6b9e10dfb121ff9ce7bc5e1e1530edf70e374466a271bc | Python | 3,036 | 79 | """
This module generates videos comparing intact and antennaless flies behavioural respones
Author: jonas.braun@epfl.ch
"""
import os
import sys
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import matplotlib as mpl
from matplotlib.backends.backend_pdf import PdfPages
import pickle
from tqdm ... |
1595664d37b574bc497b08ea7e42b262b3ed8151a939c7e05749563e61f0caf1 | Python | 3,038 | 84 | # Copyright 2020 Division of Medical Image Computing, German Cancer Research Center (DKFZ), Heidelberg, Germany
#
# 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://w... |
5914b48429de10b5df1cc067c9942c54ca2fc7264a3094dcf256b10c2e0ad39c | Python | 3,038 | 118 | # -*- coding: utf-8 -*-
"""
Created on Fri Feb 26 18:13:27 2021
Module for miscellaneous utility functions
@author: Bruno Caneco
"""
import shutil
import os
from distutils.util import strtobool
import requests
from tqdm import tqdm
# ------------------------------------------------------------------------------
d... |
a9bff059c67e41c69b26b4d0dab9cb9141fbf30e26e9cef9fdf18891121c14a9 | Python | 3,039 | 74 | #!/usr/bin/env python
# Imports
import unittest
import os
import sys
import tempfile
import filecmp
import shutil
path_to_script = os.path.join(os.path.dirname(os.path.realpath(__file__)), '..', 'bin', 'enrichm')
path_to_data = os.path.join(os.path.dirname(os.path.realpath(__file__)), 'data')
sys.path = [os.path.join(... |
e5393f87c17bdda6f5424929403f9853edae2ca333afb5f6262554553e7c9de9 | Python | 3,039 | 92 | """
Use the Acquisition class with Napari as an image viewer. This is tested in an IDE.
In other python environments (i.e. notebook), the relevant calls to napari might be different
"""
from pycromanager import start_headless
from pycromanager import JavaBackendAcquisition, multi_d_acquisition_events
from napari.qt.thr... |
8065614ee46f95c25bb03f725fc7dfbedef617471766958c0b2f41f345bcb9cc | Python | 3,041 | 69 | import pytest
from imagingplus.workflows.AllOptical import AllOpticalTrial
from imagingplus._archive.TwoPhotonImagingMain import TwoPhotonImagingTrial
from imagingplus._archive.ExperimentMain import Experiment
from imagingplus.plotting.plotting import makeSuite2pPlots, plot_flu_trace, plotMeanFovFluTrace, \
plo... |
bf48cf2606050a5a101786f10c38df7a8fa43b00cd84949637395ffaafa27008 | Python | 3,041 | 73 | import os
import socket
import sys
from configs.configs import get_config_dict
from helpers.hcp import get_human_connectome_project_subjects
from helpers.slurm import save_slurm_job_to_file, send_slurm_job_to_queue
if __name__ == "__main__":
hostname = socket.gethostname()
assert hostname == 'hivemind'
... |
ca7e991873318bb323aa88d20644f6b02c58469a3beb300805c2a74d1689d8f7 | Python | 3,041 | 111 | """Utility functions for LangChain.
These functions do not depend on any other LangChain module.
"""
from typing import TYPE_CHECKING
from langchain_core._import_utils import import_attr
if TYPE_CHECKING:
# for type checking and IDE support, we include the imports here
# but we don't want to eagerly import ... |
d4917708eab9af9165e0813c9b4bf655ebb54102dca1fe63fc06a8bb4c18479f | Python | 3,041 | 92 |
# Copyright (c) 2008-2019 the MRtrix3 contributors.
#
# This Source Code Form is subject to the terms of the Mozilla Public
# License, v. 2.0. If a copy of the MPL was not distributed with this
# file, You can obtain one at http://mozilla.org/MPL/2.0/.
#
# Covered Software is provided under this License on an "as is"
... |
e8c4432ab78146d38e3cebb72bdf0b94f0048435b92c6f40678740320ed711ae | Python | 3,045 | 118 | # -*- coding: utf-8 -*-
"""
Created on Wed Feb 20 19:50:28 2019
@author: Vinícius Rezende Carvalho
Test script for Variational Mode Decomposition (Dragomiretskiy and Zosso, 2014)
Original paper:
Dragomiretskiy, K. and Zosso, D. (2014) ‘Variational Mode Decomposition’,
IEEE Transactions on Signal Processing,... |
fbef7f0e10bc96895aaf5ed0b0102f8198a8608eabb498fece0d8ea33b3821eb | Python | 3,047 | 105 | import torch
import torch.nn as nn
import torch.nn.functional as F
from models.resnet import conv3x3x3, conv1x1x1, get_inplanes, ResNet
class PreActivationBasicBlock(nn.Module):
expansion = 1
def __init__(self, inplanes, planes, stride=1, downsample=None):
super().__init__()
self.bn1 = nn.B... |
965eb5df5e502feb85301dc55eda5a3e987ec935da223bddd6c0faea92595c9d | Python | 3,049 | 112 | import numpy as np
import pandas as pd
import pytest
from skbase.lookup import all_objects
from pgmpy.ci_tests import BaseCITest, ChiSquare, FisherZ, IndependenceMatch, Pearsonr, get_ci_test
def test_ci_registry():
all_tests = [
ci_test.get_class_tag("name")
for ci_test in all_objects(
... |
2ef4776244ea908fd9ce96985c9b7f7abf5ec6b3fc5c3539dac6afff7d9286f0 | Python | 3,051 | 104 | import os
import matplotlib
matplotlib.use('Agg')
import torch
import matplotlib.pyplot as plt
def create_folders(args):
try:
os.makedirs(args.outf)
except OSError:
pass
try:
os.makedirs(args.outf + '/' + args.exp_name)
except OSError:
pass
try:
os.makedirs... |
7d66124629cbb9b317bb42f514d9745392a57b7bb5f5053bd389a1c7ea872894 | Python | 3,051 | 81 | """Gate destructive MCP tools behind human approval.
An MCP server can flag a tool as destructive (`destructiveHint=True`). The
adapter surfaces that on the LangChain tool as
`metadata["mcp"]["tool"]["annotations"]["destructive_hint"]`, so a client can
decide how to treat it without hardcoding tool names.
Here we rea... |
37b69f3b15c087c9886b9516a933cddba6fb6b0db541a920543d93a33206d1cd | Python | 3,052 | 96 | import sys
import os
import os.path
##################This script is for calculate the Jaccard-index of SV breakpoints between samples#
mismatch=int(sys.argv[1])
binsizes=5000#################acceptable mismatch bins for loop anchor########
rootdir='.'
f=open(f'./SVPairwise_'+'mis'+str(sys.argv[1])+'_withoutS_... |
360b2c67483b4cfb004378adcd9fe7667da7ab81f9d02ad23d7a1d9cf697eb43 | Python | 3,056 | 102 |
from matplotlib import pyplot as plt
import pickle as pkl
import matplotlib.ticker as ticker
import numpy as np
import scipy
from scipy import special
from pathlib import Path
from joblib import Memory
import time
import plots_utils as util
import itertools
import pandas as pd
from scipy.signal import ricker
import se... |
afbb1e80287a51eec96f54b53b45f8c3bf079f78b36e7f685ab7c362af976973 | Python | 3,056 | 79 | import sys
import os
import time
import warnings
from sklearn.exceptions import ConvergenceWarning
import gc
import psutil
import numpy as np
warnings.simplefilter(action='ignore', category=ConvergenceWarning)
warnings.simplefilter(action='ignore', category=RuntimeWarning)
warnings.simplefilter(action='error', cate... |
7cb2be5ed65c4841689c4801089491e0d8ea90511454fdaa3c2ec1736ac5aa1e | Python | 3,058 | 101 | import string
from typing import Any
from typing_extensions import override
from langchain_classic.evaluation.schema import StringEvaluator
class ExactMatchStringEvaluator(StringEvaluator):
"""Compute an exact match between the prediction and the reference.
Examples:
----------
>>> evaluator = Exac... |
f8672aac9906415be802a72020589372396c83a64cf021f7aa82c3e6ad2befbd | Python | 3,058 | 83 | """Read in a list of structures/chain ids and find, in a given directory,
which assembly files contain the given chain(s). If the same chain is
found in multiple assemblies, then the user should manually decide which assembly
they want to use.
input: list in form '<pdb id>_<chain id>\n'
output: list in form '<pdb_id... |
d9dff14b8301c2c4e04fe39292fcda8542a275842f1a3a546cfa55de44141149 | Python | 3,059 | 95 | # 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
#
# https://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed... |
ae62549f1ff139871c6822d6a41f6cf981660d7c586f5bdf32cc5c26e79df217 | Python | 3,060 | 106 | import numpy
import torch
from utils import load_data, set_params, evaluate
from module import HeCo
import warnings
import datetime
import pickle as pkl
import os
import random
warnings.filterwarnings('ignore')
os.environ['CUDA_VISIBLE_DEVICES'] = '1,2'
args = set_params()
if torch.cuda.is_available():
device ... |
681ef3fb73ba564eec843bc8f3d86c2dd7f51d0d0ad3b0004a1fa6441ff4c55b | Python | 3,062 | 99 | import os
import unittest
from typing import Literal
import numpy as np
from dataloader import (
ParcellationDataBinary,
filter_rid,
read_csv,
read_csv_ext,
)
def _test_individual_fold(rids, fold, stage, ds_) -> None:
txt = _read_txt(fold, stage, ds_)
return np.array_equal(np.asarray(rids), ... |
8207060546247932a826bc45d47c3ec663c371cb318fea5d38787e062c9ae2b8 | Python | 3,062 | 65 | """ Import data
OmicScope allows user to import data from several Omics Software.
To date, OmicScope is designed to run with output from Progenesis,
PatternLab V, and a generic data.
Since outputs can largely vary among software, user must specify
from what software the data came from.
"""
class Input():
def... |
17af2a3e029d7d367e5f14f2f82efd3ad314285006c4882d5121516146bc0e91 | Python | 3,063 | 94 | import warnings
from abc import ABC, abstractmethod
from collections import OrderedDict
from torch import nn
class Core(ABC):
"""
Base class for the core models, taking 2d inputs and computing nonlinear features.
"""
def initialize(self):
"""
Initialization applied on the core.
... |
8c99309487745c4d0533b4f65aff7001473f704cb1f8c26dc6b07713032b97c3 | Python | 3,063 | 80 | """Utilities for formatting strings."""
from collections.abc import Mapping, Sequence
from string import Formatter
from typing import Any
class StrictFormatter(Formatter):
"""A string formatter that enforces keyword-only argument substitution.
This formatter extends Python's built-in `string.Formatter` to p... |
cfd54ad80237c10aa32f353f7ea50d45891f5de1e04be81de9b6891faf37efb7 | Python | 3,063 | 93 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
from __future__ import absolute_import
from __future__ import print_function
from __future__ import unicode_literals
import os
import subprocess
import sys
from os.path import abspath
from os.path import dirname
from os.path import exists
from os.path import join
from os.p... |
d9a9d95a5d9de62d0c2fcf36f372d2dad1b9cd17f82df197086022ba3ff65ce7 | Python | 3,063 | 77 | import pandas as pd
import numpy as np
import argparse
from pandas.api.types import is_string_dtype
def get_ratio(data,nc,n=0):
feature = list(data.index)
data_NC = data.loc[feature,nc]
ratio = pd.DataFrame(columns=['feature', 'ratio_all', 'ratio'])
ratio_all = []
ratio_NC = []
j = 0
# n = ... |
1139fd7bbda6fd7595f609dc74ca7a5d5a858a974fdd65a9a8b9ba83301e71df | Python | 3,068 | 102 | #!/usr/bin/env python
# -*- encoding: utf-8 -*-
import io
import re
from glob import glob
from os.path import basename
from os.path import dirname
from os.path import join
from os.path import splitext
from setuptools import find_packages
from setuptools import setup
def read(*names, **kwargs):
with io.open(join... |
a6a1eb5e695ad3f068c3b2698223fea546d433ae8e7c3717a08fe423f02b9f24 | Python | 3,069 | 73 | from dival import TaskTable
from dival.measure import PSNR, SSIM
from dliplib.utils import Params
from dliplib.utils.data.datasets import CachedDataset
from dliplib.utils.helper import select_hyper_best_parameters, load_standard_dataset
from dliplib.utils.reports import save_results_table
from dliplib.utils.weights im... |
2e78e083af3b6479a6755f2c80359eb097e98e1ac9ae281bdf48bc306f4d6b94 | Python | 3,070 | 113 | import matplotlib.pyplot as plt
import numpy as np
plt.style.use('seaborn-white')
plt.rcParams.update({'font.size':15})
plt.rc('xtick', labelsize=36)
plt.rc('ytick', labelsize=36)
#plt.rc('xtick', labelsize=26)
#plt.rc('ytick', labelsize=26)
logfile='../../logs/Xgboost/xgboost.log'
save_path='../../logs/Xgboost/sa... |
71b96772168ebd24be8f6a70496ba5462b3fed7b2090c5d5910fd2c850919e26 | Python | 3,070 | 127 | from langchain_classic import tools
EXPECTED_ALL = [
"AINAppOps",
"AINOwnerOps",
"AINRuleOps",
"AINTransfer",
"AINValueOps",
"AIPluginTool",
"APIOperation",
"ArxivQueryRun",
"AzureCogsFormRecognizerTool",
"AzureCogsImageAnalysisTool",
"AzureCogsSpeech2TextTool",
"AzureCo... |
744526a8ffeadca48208d97251624b3b977854940b9e871a232a9ae66aab2bdc | Python | 3,072 | 84 | import argparse
import numpy as np
from oset.ecg.peak_detection.peak_det_simple import peak_det_simple
def peak_det_amp_threshold(x, ff, th, *args):
"""
peak_det_amp_threshold - R-peak detector based on max search and level thresholding
Syntax: peaks, peak_indexes = peak_det_amp_threshold(x, ff, th, *ar... |
d4871349d63e837e8d45f53996bf15fda8a2a83e2121c71ec1c04be4544734e7 | Python | 3,073 | 87 | import pandas as pd
import pathlib
import gzip
import shutil
import tqdm.auto as tqdm
import multiprocessing as mp
def _remove_prefix(string):
if string.startswith('"'):
string = string[1:]
if string.endswith('"'):
string = string[:-1]
return string
def parse_series_matrix(file):
res... |
13104715b58d0f33c80102e4b4c27532c19528e6644ff1a4890aeb3e8061d80a | Python | 3,075 | 85 | import torch
import torch.nn as nn
import torchvision.models as models
class CEEffNet(nn.Module):
"""encoder + classifier"""
def __init__(self, num_classes=2, model_name='effb0', dropout=0.4):
super(CEEffNet, self).__init__()
self.encoder = choose_model(model_name=model_name)
dim_in = ... |
dc7fc80999b63f3317ccba54825537674a6c1d4ea8c5e63a9d153040888c8d1e | Python | 3,075 | 66 | # Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved.
#
# NVIDIA CORPORATION and its licensors retain all intellectual property
# and proprietary rights in and to this software, related documentation
# and any modifications thereto. Any use, reproduction, disclosure or
# distribution of this sof... |
fc56657b11c6cbe8a0029d24e5037238c8a39504a588867d10546bcf9011b754 | Python | 3,075 | 75 | from pyjavaz.wrappers import JavaObject
from ndstorage.ndstorage_base import NDStorageBase
class NDRAMDatasetJava(NDStorageBase):
"""
A python class that wraps a Java-backend RAM data storage.
This class maintains an index of which images have been saved, but otherwise routes all calls to the Java
imp... |
39e6549ee71599f289660afaa591fff8d5483fcf81441c44c36ba4b1ead58d5a | Python | 3,076 | 69 | # R-peak detector python implementation.
# It is based on the Pan-Tompkins R-peak detector; the "pure" P-T procedure is returing the variable "peaks". An extra step is added in order to fine tune the positions, by searching in an interval around the peaks the argmax. The "fine-tuned" positons are returned in the varia... |
b197ed9653adac1f327d5c386c7f3261918bf8ec97af8f453ed795f20693f600 | Python | 3,076 | 75 | ## Imports
import numpy as np
from chromograph.pipeline import config
from chromograph.preprocessing.utils import *
from cytograph.visualization.scatter import *
from cytograph.visualization.colors import Colorizer
import torch
from torch import nn
from twobitreader import TwoBitFile
from deeplift.dinuc_shuffle impor... |
304befb1caa807704183664be093c47112684ce078e10689c5a91d2ff90a5b08 | Python | 3,077 | 111 | import types
import numpy as np
import matplotlib.pyplot as plt
from fastweights_numpy import FastWeights, FeedforwardNet
from dt_utils import Timer
from data_utils import generate_recognition_data, chance
from neural_net_utils import plot_W, plot_B, plot_W_seq, plot_h_seq, plot_train_perf
def make_fwRan... |
2e35e5bd6584a6af8e7597b9cc324243654f41887b8969f32f4a080dc863fef8 | Python | 3,079 | 93 | import yarp
import pyicub
from pyicub.iCubHelper import iCub, iCubRequest, iCubTask, ICUB_PARTS, JointAction
pyicub.controllers.PositionController.MIN_JOINTS_DIST = 20
TIMEOUT_LOOKAT = 0.4
TIMEOUT_LANDMARKS = 0.5
TIMEOUT_EYELIDS = 0.5
import time
class iCubHelper:
def __init__(self):
self.icub = iCub(co... |
ba3bc83fe53ad65ac8139e29b3e8c60499fcc12907fcde8473ac77ed16e37322 | Python | 3,080 | 87 | import argparse
import gcsfs
import pandas as pd
from tqdm import tqdm
# This script generates replicate to sample mapping file to interpret the qc report. It
# was developed as an alternative to extract_rep_names_from_encode.sh which might not
# work if the pipeline run_dir had outputs for a specific condition in m... |
973dd0bbe2bc886057df1e5610a91a665b62d28b483111b29dada401ace7eadc | Python | 3,082 | 79 | # 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... |
e4f40455b9459a8e44c800a3abb2cc37d09d1729a882bebee48996b95a9488e1 | Python | 3,083 | 84 | """
Adapted from:
https://github.com/karpathy/nanoGPT/blob/eba36e84649f3c6d840a93092cb779a260544d08/sample.py
"""
import sys
sys.path.append(".")
import os
from dataclasses import dataclass
from contextlib import nullcontext
from omegaconf import OmegaConf
import torch
from crystallm import (
parse_config,
CI... |
57c85c4b0a8a9a6cd22d2df7d63e1ca3de0b9d4bc7072b2a613f4916f575b12a | Python | 3,085 | 87 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Sat Apr 8 23:16:55 2023
@author: weihan
"""
import pandas as pd
from torch.utils.data.dataset import Dataset
from sklearn import preprocessing
class MakePygFormat(Dataset):
"""
The PygLinkPrediction object can convert graph for pyg using.
... |
ce42d996af5499f696a063f01894ac298eee4d15c2f449da525a47be7ca9fb02 | Python | 3,087 | 73 | from torch.utils.data import Dataset
import numpy as np
from torchvision import transforms
import torch
from .PredictionDataset import max_to_1, min_max_norm
import torch
import json
if torch.cuda.is_available() is True:
try:
import cupy as cu
from cucim.skimage.morphology import dilation, ball
... |
8509f34671d030b043622f3fdc456479db5796194b2bef215b465563a5e0d6da | Python | 3,088 | 97 | from tqdm import tqdm
class Engine:
def __init__(self):
hook_names = ['on_start', 'on_start_epoch', 'on_sample', 'on_forward',
'on_backward', 'on_end_epoch', 'on_update', 'on_end']
self.hooks = {}
for hook_name in hook_names:
self.hooks[hook_nam... |
bd2b268047d0ee137cccfa9169be042c5f09cdf144825fd7ff775cf290d83967 | Python | 3,089 | 93 | import torch
import networks as nets
from data import generate_recog_data, generate_recog_data_batch
from plotting import plot_generalization, get_recog_positive_rates
import numpy as np
torch.manual_seed(0)
# choose parameters
netType = 'HebbNet' # HebbFF or LSTM
d = 100 # input dim
N = 120 # hidden dim
force = 'A... |
95e0d0552bf283585d70b3f648c2d3054bb1468ad0f85d0c403c8b69f8b954b9 | Python | 3,091 | 91 | import torch
from torch import nn
from utils import RBFExpansion
from transformer import ComformerConv, ComformerConvEqui, Gradient_block, Piezo_block, Elastic_block
from torch_scatter import scatter
def bond_cosine(r1, r2):
bond_cosine = torch.sum(r1 * r2, dim=-1) / (
torch.norm(r1, dim=-1) * torch.norm... |
c8f57b5ad78e755a21f79c449127370f727fb6cdb472d87c1e3e556ecf37143d | Python | 3,094 | 96 | """
Test cwas.core.configuration.create
"""
import cwas.core.configuration.create as create
import pytest
import yaml
@pytest.fixture(scope="module", autouse=True)
def setup(cwas_workspace):
cwas_workspace.mkdir()
@pytest.fixture(scope="module", autouse=True)
def teardown(cwas_workspace):
yield
remove_w... |
10f840ebd641b025e50bbc01201124d3e3da21e454b448d8aa20f9083747e3ba | Python | 3,096 | 83 | ####################################################################################
#
# STEPS - STochastic Engine for Pathway Simulation
# Copyright (C) 2007-2023 Okinawa Institute of Science and Technology, Japan.
# Copyright (C) 2003-2006 University of Antwerp, Belgium.
#
# See the file AUTHORS for d... |
24539b5f08be2e9bfb1e7020c23c948eba46102d1e12da623d86da3ed46e0323 | Python | 3,097 | 84 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Mon Apr 24 00:57:18 2023
@author: weihan
"""
import time
import torch
import argparse
import pandas as pd
from model.DeepNeuralNetworks import DeepNeuralNetworks
def set_args():
parser = argparse.ArgumentParser(description='Graph construct by genome a... |
515a73c8eaa0e5d1d3fbefc541223631a661a284919a287c9e0c438cb94542e9 | Python | 3,097 | 83 | ####################################################################################
#
# STEPS - STochastic Engine for Pathway Simulation
# Copyright (C) 2007-2026 Okinawa Institute of Science and Technology, Japan.
# Copyright (C) 2003-2006 University of Antwerp, Belgium.
#
# See the file AUTHORS for detai... |
c93fd73735d4d863ca06e31457dafc10db8657c99729a5d431b6a1ec38744dd1 | Python | 3,098 | 78 | # -*- coding: utf-8 -*-
"""
Created on Fri Apr 24 12:26:12 2020
@author: gritti
"""
import tqdm, os, glob, sys
from morgana.GUIs.manualmask import makeManualMask
from morgana.DatasetTools import io
import PyQt5.QtWidgets
###############################################################################
# select folder c... |
30e85b3d76bfb7eaf2a1a067525bf3de5e9a83160ccfe7bbe3474d8e582e7b40 | Python | 3,099 | 87 | #!/usr/bin/env python
# coding:utf8
import torch
import torch.nn as nn
import torch.nn.functional as F
from torch.autograd import Variable
torch.manual_seed(123456)
class BLSTM(nn.Module):
"""
Implementation of BLSTM Concatenation for sentiment classification task
"""
def __init__(self, embeddi... |
2de3b2803b86eb1c08360bb5454bd35f8c19456e9e0fca4b8e2812390877c7b2 | Python | 3,104 | 82 | from __future__ import annotations
import numpy as np
from libs.common.graph import Graph
from libs.function.function import NormalizeAxis
from libs.function.utils import aline_spatial as als
from libs.function.utils import euclidean_distance
def set_distance(position: np.ndarray) -> np.ndarray:
dim = position.... |
451fba9d824ec52620986093083c65c8594d24b6b9f27fae798b33feec97e178 | Python | 3,104 | 110 | import torch.nn as nn
try:
from inplace_abn import InPlaceABN
except ImportError:
InPlaceABN = None
class Conv2dReLU(nn.Sequential):
def __init__(
self,
in_channels,
out_channels,
kernel_size,
padding=0,
stride=1,
use_bat... |
effef0afe3db139ebcac3f48bba4fe69791053fd8b0856e1c8f079dfec745dd9 | Python | 3,104 | 71 | """Co-quantification control for the antisense-lncRNA finding (the feasible substitute for a literal
strand-aware re-quant, which is impossible: SMART-seq2 is unstranded and the raw reads are ~7.5 TB).
The worry: a sense-antisense correlation could be an artefact of reads from overlapping loci being
counted for both g... |
85435a3fce58c14cfdc58c1799d17d607fad4b1dc0d1f7db69d67997468294b6 | Python | 3,105 | 79 | import os
import numpy as np
import pandas as pd
import random
from sklearn.preprocessing import StandardScaler
from imblearn.over_sampling import SMOTE
from sklearn.model_selection import StratifiedKFold
def _load_data(path):
X_train = np.array(pd.read_csv(os.path.join(path, 'X_train.csv'), header=None))
y_tr... |
b67c1f3c98c27f78b5e3341cd4f773f1215aec4094e14574745522feffdaca0c | Python | 3,106 | 97 | from __future__ import annotations
import array
import random
from pathlib import Path
import numpy as np
from libs.function.function import Normalize
from libs.function.utils import aline_spatial
# image -> view
def image2view(image: np.ndarray, size: int, view: int) -> list[np.ndarray]:
data = []
for x i... |
028496b355711d6842c63d5472b282d606c8646661d4cbf81e284ab76cf99946 | Python | 3,107 | 86 | from dival import TaskTable
from dival.measure import PSNR, SSIM
from dliplib.utils import Params
from dliplib.utils.data.datasets import CachedDataset
from dliplib.utils.helper import select_hyper_best_parameters, load_standard_dataset
from dliplib.utils.reports import save_results_table
from dliplib.utils.weights im... |
454f10192203e2540d4eaab67503c4d63248e972e7da46f13b4f3f342765d1de | Python | 3,107 | 126 | from SMdRQA.RQA_functions import *
import ast
import memory_profiler
from scipy.interpolate import pchip_interpolate
from functools import partial
from p_tqdm import p_map
from scipy.stats import skew
import random
import pickle
import os
from tqdm import tqdm
import csv
from collections import defaultdict
from os.path... |
9f47fbe15ab80cfa67dc6d489e8e67d578b7acd8b9239452331bb50b938ad656 | Python | 3,107 | 110 | from abc import abstractproperty
import tensorflow as tf
from tensorflow.keras.layers import Conv2D, Conv3D
from typing import Callable, Tuple
from .layer import StandardLRPLayer
class ConvLRP(StandardLRPLayer):
@abstractproperty
def convolve(self) -> Callable:
pass
@abstractproperty
def co... |
1196235a031e14c4b464c97edd771b175de0a03be0b7383ec2319fc6ad144305 | Python | 3,108 | 90 | import pytest
from packaging import version
from langchain_core.prompts.string import (
check_valid_template,
get_template_variables,
mustache_schema,
)
from langchain_core.utils.formatting import formatter
from langchain_core.utils.pydantic import PYDANTIC_VERSION
PYDANTIC_VERSION_AT_LEAST_29 = version.p... |
5a204f714c316c6edf251d338beaf0aefd23b1199c69352047c66467fe983e7f | Python | 3,108 | 70 | # Author: Raktim Mitra (timkartar7879@gmail.com, raktimmi@usc.edu)
# Contributions by Jared Sagendorf
# third-party modules
import torch
from torch import nn
from torch_geometric.nn import MessagePassing
class ContinuousCRF(MessagePassing):
def __init__(self, alpha=None, beta=None, niter=4, eps=1e-8, gij=None):
... |
c07b8a859c84dcaa8f8c425aba7ae5a76481309ad32f2cdf1ffd1876886da60d | Python | 3,108 | 111 | # builtin modules
import os
import re
import subprocess
import logging
# pnabind modules
from pnabind.utils import Interpolator
def runAPBS(pqr, command="apbs", prefix="tmp", basedir='.', quiet=True, clean=True, space=0.5, cfac=1.7, fadd=20, gmemceil=400, keep_dx=False):
""" run APBS and return potential """
... |
23e9d7c269c7a6c8111820c73322d139fe62312f1094dc4798609490674bdcf8 | Python | 3,109 | 121 | import logging
import tempfile
from pathlib import Path
from protocol import ACRONYMS_IMAGING_PARAMETERS
#: Parameters that are supported by MRdataset
VALID_PARAMETERS = sorted(list(ACRONYMS_IMAGING_PARAMETERS.keys()))
MRDS_EXT = '.mrds.pkl'
VALID_DATASET_FORMATS = [
'dicom',
'bids',
]
VALID_BIDS_EXTENSIONS... |
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