sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
562d2f1ab28a5bf53b7e69118554ae5f93e84a0fca24f9c56c8f8e928f91ed09 | Python | 2,632 | 75 | import unittest
from synister.synister_db import SynisterDb
from synister.split import find_optimal_split
import os
class DbSetupTestCase(unittest.TestCase):
def setUp(self):
self.db_credentials = os.path.join(os.path.abspath(os.path.dirname(__file__)) + "/../../db_credentials.ini")
self.db = Synis... |
1aecb407b24325e4d8249cf8d05b3c2074ce10a158caf1397d4487de1ceaffc7 | Python | 2,633 | 88 | from collections import namedtuple
from typing import Dict
from typing import Tuple
import pytest
import torch
from torch.utils.data import DataLoader
from torch.utils.data import Dataset
from neurovisfit.common.dimensions import get_dims_for_loader_dict
from neurovisfit.common.dimensions import get_io_dims
@pytest... |
4c4c91205f23bb0fd4efbddbda4385ea69a0cf9ca92a81fc6156e6a6cc905c8c | Python | 2,634 | 70 | import argparse
import nibabel as nib
import numpy as np
import scipy.stats as stats
import os
def main():
# -----------------
# Parse arguments
# -----------------
parser = argparse.ArgumentParser(
description="",
epilog="")
parser.add_argument("-v", "--version",
... |
c50a4eb991378a5e93eb81c8c5ca26d74bb631b5836d69bb9e70c69c92340648 | Python | 2,635 | 87 | # Adapted from OpenFold
# Copyright 2021 AlQuraishi Laboratory
# Copyright 2021 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/l... |
4a74b3e4a503a73d5b7ee0fc4b162b5e926ee9481ef4979197f96eb816a3e2f2 | Python | 2,638 | 92 | #!/usr/bin/env python3
"""
Create report of average intra and inter-observer atlas label statistics
Usage
----
avg_inter_observer.py
Authors
----
Wolfgang M. Pauli, Caltech Brain Imaging Center
Dates
----
2017-10-27 WMP Split from atlas.py
License
----
This file is part of atlaskit.
atlaskit is free software... |
93eb5a1400be14d9fbb427891e2463e6f472119fa766215165573e6b51d89765 | Python | 2,638 | 68 | import unittest
import zipfile
from pathlib import Path
import pytest
from MRdataset import import_dataset
THIS_DIR = Path(__file__).parent.resolve()
class TestMergeDatasets(unittest.TestCase):
@classmethod
def setUpClass(cls):
zip_path = THIS_DIR / 'resources/test_merge_data.zip'
if not Path... |
926c607abfd9768b05a47424ca473558d3ea7cc1ba5694b45551093a530f7ff8 | Python | 2,639 | 61 | import torch
import numpy as np
from typing import List
from torch import Tensor
def build_edge_idx(num_nodes):
# Initialize edge index matrix
E = torch.zeros((2, num_nodes * (num_nodes - 1)), dtype=torch.long)
# Populate 1st row
for node in range(num_nodes):
for neighbor in range(num_nodes - ... |
f5fe8295a92ac0dfef01f48280859a2ff938bc698f4ef038ca8c045516ca5c18 | Python | 2,639 | 81 | import numpy as np
from matplotlib import pyplot as plt
from sklearn.preprocessing import MinMaxScaler
from Clust3D.training import train_Clust3D
from Clust3D.neuron_init import neurons_initialization
def masked_norm(a, b, ord=2):
mask = ~np.isnan(a) & ~np.isnan(b)
if not np.any(mask):
retur... |
a850483ccbda64896848903e0e14bbad1336ef578d5b594ac21fd9147640beba | Python | 2,640 | 51 | # 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... |
1d2c6c2a06752787e2abd6be99b3030921f82af4f940479654c73ed693b0bd9a | Python | 2,642 | 76 | import numpy as np
import dit
def create_distribution(source, target):
# creates distribution for discrete measures
samples = []
num_sources = len(source[0])
for i in range(len(source)): # for each sample
source_str = source[i][0]
len_sources = [len(source_str)]
for j in range(1... |
102adfb5b9924bf18b18c41a7312e5c2af1f0032c2711c6dc2525520f5b2826a | Python | 2,646 | 70 | import types, os
import torch
from torch.utils.data import TensorDataset
from net_utils import load_from_file
from plotting import get_all_pkl, plot_recog_generalization, plot_recog_positive_rates
from data import generate_recog_data
#%%
#folder = '/Users/danil/My/School/Columbia/Research/ongoing_plasticity/re... |
ad174df1e0a42bb20ea37b6ba7fef55ee094e4419bd14e01c7eb6d74ada4f3bc | Python | 2,647 | 70 | 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... |
3bcae058ccc129205d8feaadf70cebde40a01581dd028ec87fdea25d97d7857e | Python | 2,649 | 62 | #! /bin/env python
#
# Michael Gibson 27 April 2015
# Modified Adrian Foy Sep 2018
def data_to_result(header, data, data_present):
"""Moves the header and data (if present) into a common object."""
result = {}
if header['num_amplifier_channels'] > 0 and data_present:
result['t_amplifier'] = da... |
b760351f59b617d3fdb330c051ff44550a0a420badc0665ff99fa33448b62023 | Python | 2,649 | 105 | '''Collection of per-caller summary statistics.
The data are specific for each caller.
'''
import os
from cgatReport.Tracker import *
from PeakcallingReport import *
class FilteringSummary(DefaultTracker, SingleTableTrackerRows):
table = 'exported_intervals'
fields = ('track', 'method')
class MacsSummary(... |
4553bcf61574c49ee7f59e46b51cc79916aa838578cbef4e48c803db3813d540 | Python | 2,650 | 77 | from .BoundingBox import *
from .utils import *
class BoundingBoxes:
def __init__(self):
self._boundingBoxes = []
def addBoundingBox(self, bb):
self._boundingBoxes.append(bb)
def removeBoundingBox(self, _boundingBox):
for d in self._boundingBoxes:
if BoundingBox.compa... |
aea94e1f2fffff6c9cf72f8f76ca6978ebcc7585d31df526b2dadc8e826c527f | Python | 2,650 | 43 | from setuptools import setup, find_namespace_packages
setup(name='nnsegnext',
packages=find_namespace_packages(include=["nnsegnext", "nnsegnext.*"]),
install_requires=[
"torch>=1.6.0a",
"tqdm",
"dicom2nifti",
"scikit-image>=0.14",
"medpy",
... |
787655fdaa1cf079d70f75bd0e9a20be4828ebe309b99d6011191c01fe73228c | Python | 2,652 | 97 | """Message prompt templates."""
from __future__ import annotations
from abc import ABC, abstractmethod
from typing import TYPE_CHECKING, Any
from langchain_core.load import Serializable
from langchain_core.utils.interactive_env import is_interactive_env
if TYPE_CHECKING:
from langchain_core.messages import Base... |
e249ba389b04dd87b16a93f055db618459add27ff6100391d5f2aec4e87b63ef | Python | 2,653 | 65 | import hydra
from hydra.core.config_store import ConfigStore
from config import Scenario, _DATATYPE, _ALGOTYPE
from typing import get_args
import numpy as np
from utils import varname, update_cfg
from omegaconf import OmegaConf,open_dict
import random
cs = ConfigStore.instance()
cs.store(name="scenario_con... |
fd18f0ba721335775efe3ebd4522d2f4d8e00a74adc7a9091ef93529e3544491 | Python | 2,655 | 76 | """ Statistic Module comprises all statistical tests performed
by OmicScope for differential expression analysis.
Returns:
DataFrame: DataFrame with recommended statistical
analysis performed
"""
def perform_static_stat(self):
"""log2 transformation for expression
"""
from copy impor... |
d7588de5c902b6dd30fd6272be7f371092a5bf022b8817b121ad3115abcab0dd | Python | 2,657 | 79 | import torch
import torch.nn as nn
import torch.nn.functional as F
class DihedralFeatures(nn.Module):
def __init__(self, node_embed_dim):
""" Embed dihedral angle features. """
super(DihedralFeatures, self).__init__()
# 3 dihedral angles; sin and cos of each angle
node_in = 6
... |
0a63cd3efea06a080afbb5273c335d68dcb4524e8bb7563be93966965cf7871b | Python | 2,658 | 43 | '''
This datageneratormust be defined before testing the network. Custom Keras datagenerators are elaborately described and illustrated here, https://towardsdatascience.com/implementing-custom-data-generators-in-keras-de56f013581c
The generators must return (EEG, PMA) or (EEG, PMA, sample_weights) where:
- EEG is ... |
05cb061673efbeba6609e4ccf5187219017db55bef1819e7a689f911f62fbf89 | Python | 2,661 | 81 | # Copyright 2023 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... |
1963d029162d9f8754517de6cb77525550921676e9e250f9b60d389a8147668c | Python | 2,661 | 62 | SYMBOLS = {',', '?', '!', ':', '\'', '"', '(', ')', ';', '@', '^', '^', '&', '&', '$', '$', '£',
'[', ']', '{', '}', '<', '>', '+', '-', "*", "#", "%", "=", "~", '/', "_", "|"}
BREAK_SYMBOLS = {
',', '?', '!', ':', ')', ';', ']', '}', '>', '[', '{', '(', '<',
}
PREP = {'about', 'above', 'across', 'afte... |
e2fffc83bd9c8484c5a7463efb60376cf39e174cf6417852f1ae7823610c9735 | Python | 2,662 | 75 | """
Unit tests for NCMC integrator.
"""
__author__ = 'John D. Chodera'
################################################################################
# IMPORTS
################################################################################
import numpy as np
import os
running_on_github_actions = os.environ.get(... |
263c1fdced7a99c629fc624264dc2ca8da5e913401749678805d619b41186a85 | Python | 2,663 | 88 | from langchain_core.documents import Document
from langchain_core.language_models import FakeListChatModel
from langchain_classic.retrievers.document_compressors import LLMChainExtractor
def test_llm_chain_extractor() -> None:
documents = [
Document(
page_content=(
"The sky is... |
8c148c8940ffa4a966e5cd47d30e19121ded54e0c44e4d8326c7c7c3e549dd7d | Python | 2,663 | 68 | from __future__ import annotations
from langchain_core.language_models import LanguageModelLike
from langchain_core.output_parsers import StrOutputParser
from langchain_core.prompts import BasePromptTemplate
from langchain_core.retrievers import RetrieverLike, RetrieverOutputLike
from langchain_core.runnables import R... |
2855a842593599c76c41905f8845d438e5007f5f71c66d65e28f1bca859ac647 | Python | 2,664 | 70 | import torch
from torch import nn
from torch.optim import Adam
class InnerProductSimilarity(nn.Module):
def __init__(self, temp):
super(InnerProductSimilarity, self).__init__()
self.temp = temp
def forward(self, a, b):
d = a.shape[1]
a = a.unsqueeze(1) # N x 1 x dim
i... |
5467515817a504c32cf94caec4f27267e30bf0d7b1136ab6b0cf234402c2d9b2 | Python | 2,666 | 101 | #!/usr/bin/env python3
"""
Write separate volume for each label found in the input image
Usage
----
separate_labels.py <input label image>
separate_labels.py -h
Example
----
>>> separate_labels.py atlas.nii.gz
Authors
----
Wolfgang M. Pauli, Caltech, Division of Humaninities and Social Sciences
Dates
----
2015-05-... |
50a5073de41a22ef248294d7e8132c8e5678e749e571281ce91c22ad41cf8387 | Python | 2,667 | 48 | from perses.analysis.visualization import Visualization
from pkg_resources import resource_filename
import os
from unittest import skipIf
import pytest
running_on_github_actions = os.environ.get('GITHUB_ACTIONS', None) == 'true'
#@skipIf(running_on_github_actions, "Skip helper function on GH Actions")
@pytest.mark.sk... |
2b5b11d15c76bead2103728b3224416c205de6b3dd88ca0124df06580b2453be | Python | 2,668 | 85 | 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.... |
c804e8accdb8e33d9e731412cbce72efc0eb897a29f55c7ecb919d4bca7ad5a0 | Python | 2,669 | 91 | # Copyright (c) DP Technology.
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import logging
import numpy as np
import torch.utils.data
logger = logging.getLogger(__name__)
class EpochLi... |
448e83caada66b0bc517ef1799cade78562b72e259fdbaa8e9b5a0930e771d1d | Python | 2,671 | 68 | import joblib
import matplotlib.pyplot as plt
from plastic import PlasticNet
from neural_net_utils import plot_train_perf, plot_W, plot_B
from data_utils import generate_recognition_data, recog_chance
from torch.nn import functional as F
#%%
d = 25 #length of input vector
P = 0.5 #probab... |
5bb9934728c17e763e3e3c54c7f765aac3bfd0d7e351d4b59f7289c5a52f1ce7 | Python | 2,673 | 71 | #!/usr/bin/env python
# -*- encoding: utf-8 -*-
'''
@Description: :
@Date : 2022/06/16 12:09:02
@Author : Zilan Yu
@version : 1.0
'''
import torch
import torch.nn.functional as F
import torchmetrics
import pandas as pd
import sys, os
from scipy.stats import spearmanr
from HeteroModel import *
from d... |
30281520c731b41729f72f2d1d285d8f5fe035f7341b597ed6e5cbfe0ede76d1 | Python | 2,674 | 68 | from __future__ import annotations
from typing import Any
from langchain_core.retrievers import (
BaseRetriever,
RetrieverOutput,
)
from langchain_core.runnables import Runnable, RunnablePassthrough
def create_retrieval_chain(
retriever: BaseRetriever | Runnable[dict, RetrieverOutput],
combine_docs_... |
34dee58ef99871eb1bf0d45ee191bbdf65b080dd8c2d298ac4e084327c2e6121 | Python | 2,674 | 83 | import numpy as np
import pandas as pd
from scipy import stats
from ._base import _CITestResult
from .pearsonr import Pearsonr
class FisherZ(Pearsonr):
r"""
Fisher's Z test for conditional independence on continuous data.
This test first computes the Pearson or partial correlation coefficient :math:`\rh... |
9e681d514e06b883cd066f5170fb2f3c352a71a8231e4b1e491f970042fe33b4 | Python | 2,675 | 74 | import numpy as np
import pytest
import torch
import torchmetrics
from scvi import REGISTRY_KEYS
from scvi.data import synthetic_iid
from scvi.distributions._utils import _mps_supports
from scvi.external import SCBASSET
_DNA_CODE_KEY = "code"
def _get_adata(sparse_format: str | None = None):
dataset1 = syntheti... |
011c925f38b5acd95b8c44d541c36b36368e5849a459f9e9e0179343e0db1e93 | Python | 2,677 | 86 | import json
import re
from re import Pattern
from langchain_core.agents import AgentAction, AgentFinish
from langchain_core.exceptions import OutputParserException
from typing_extensions import override
from langchain_classic.agents.agent import AgentOutputParser
from langchain_classic.agents.chat.prompt import FORMA... |
2542b5b83ec7482b3d4a4abda14c58c87a924cb6e68bf9027a9a2a62e18eef70 | Python | 2,677 | 72 | #!/usr/bin/env python
import time
# Import OpenMM tools
from simtk import openmm, unit
from simtk.openmm.app import *
# Use MDTraj to write simulation trajectories
from mdtraj.reporters import NetCDFReporter
# Import the SMIRNOFF force field engine and some useful tools
from openff.toolkit.typing.engines.smirnoff i... |
a3a635ae9e8ead6df5dcbe6b6c101a13cf7f718a95bafde3f959fa7555890674 | Python | 2,678 | 74 | import xml.etree.ElementTree as ET
from semantic_version import Version
from pathlib import Path
import requests
def read_versions(root):
versions = {}
versions['PycroManagerJava'] = Version(root.find("version").text)
# iterate through the dependencies and get NDStorage, NDViewer, and AcqEngJ
dependenc... |
c72999380a63e02df515f935ef808a299dc364d1d41db3ab833c9a65030f2bd8 | Python | 2,678 | 79 |
import numpy as np
from scipy.stats import pearsonr
from sklearn.model_selection import KFold
from sklearn.linear_model import LinearRegression, Ridge
import sys
from sklearn.decomposition import PCA
d='/jukebox/griffiths/bert-brains/'
dataset=sys.argv[1]
sub=sys.argv[2]
if dataset=='slumlordreach':
su... |
ac718acc2bfd0e78bcfafb75e06706a99fdedb0f02ed0ffea8f18a7215aecd36 | Python | 2,679 | 83 | # Configuration file for the Sphinx documentation builder.
#
# This file only contains a selection of the most common options. For a full
# list see the documentation:
# http://www.sphinx-doc.org/en/master/config
# -- Path setup --------------------------------------------------------------
# If extensions (or module... |
b2c787f60bfcfbb0a332be4fe28e6d54da172805e0318f511820cecde3aa6d04 | Python | 2,679 | 92 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
import argparse
import numpy as np
import nibabel as nib
import pylab as plt
DESCRIPTION = """
Plot the timeseries of a 4D Nifti file
"""
def buildArgsParser():
p = argparse.ArgumentParser(description=DESCRIPTION)
p.add_argument('--in', dest='input', action='st... |
ccbd50ba99473d480ce530ef5940e18e6dcf7c0f683ba38ed4378589340b265d | Python | 2,680 | 112 | # Copyright Generate Biomedicines, Inc.
#
# 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 ... |
2a780857756b615c0f9ce566887c22b4271aa48c9d5aaac65610c51fc45864fc | Python | 2,681 | 80 | from langchain_core.agents import AgentAction
from langchain_classic.agents.format_scratchpad.xml import format_xml
def test_single_agent_action_observation() -> None:
# Arrange
agent_action = AgentAction(tool="Tool1", tool_input="Input1", log="Log1")
observation = "Observation1"
intermediate_steps =... |
c1c10f17e8fc71b9e0c324f8bca60b2a87b955eedc25351af53608445913083a | Python | 2,681 | 88 | import numpy as np
import logging
_logger = logging.getLogger("analysis/utils")
def open_netcdf(filename):
from netCDF4 import Dataset
import os
# checking that the file exists
exists = os.path.isfile(filename)
if exists:
ncfile = Dataset(filename, 'r')
return ncfile
def get_offlin... |
b5ed2e827425ce57cac320ab82e6dcf9cad7b1b3a6f74113db432faa027b1949 | Python | 2,682 | 83 | # Copyright 2018 DeepMind Technologies Limited. 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
#
# https://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by... |
c8efa8ea91928e3e2903e861ec42029a676c7d8f54fd2aa451675e47b2e6b3a9 | Python | 2,685 | 64 | ####################################################################################
#
# 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... |
2310d6a4c04e8cef67b7d529dc1ab88dcc8e94865ee49fbb8d6b29b7492614fe | Python | 2,687 | 76 | import logging
import os
import socket
import sys
from configs.configs import get_config_dict
from helpers.data import load_data
from helpers.evaluation import leave_every_other_out_split
from helpers.plotters import plot_node_timeseries
if __name__ == "__main__":
data_split = 'all'
data_set_name = sys.arg... |
7b133349d6a2488c76834702cfc8ac48f5c8e585d05447ac065e30ee5f49b0af | Python | 2,687 | 63 | # Copyright 2022 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 writi... |
1a52dfe08af56194b321d49ddaa2383a086243053330d5dabf9e7f0c69512a4b | Python | 2,689 | 107 | import random
import math
import numpy as np
from scipy.interpolate import CubicSpline
def jittering(x, sigma=0.1):
return x + np.random.normal(0, sigma, size=x.shape)
def scaling(x, sigma=0.1):
return x * np.random.normal(1, sigma, size=(x.shape[0], 1))
def rotation(x):
ch, _ = x.shape
ch_inds = ... |
22bfbf16fd33e72927914a66cb5e94b33397f4ac13612640ab6f45de721c289f | Python | 2,692 | 77 | import numpy
import meshparty
import meshparty.mesh_filters
import trimesh
from pycilium.utils.skeleton_utils import *
def filter_mesh_cdskel_line_distance(mesh, cdskel, radius=600, endcap_buffer=300):
segs = skelcd_to_linesegments(cdskel)
orig_mesh = meshparty.trimesh_io.Mesh(
mesh.vertices, mesh.... |
6b55f7921fc451d4abe52be0d4479451dddb11472866cb757cd2c0f267ebf89c | Python | 2,692 | 69 | 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.weights import save_weights, get_weights_path
from dliplib.util... |
d05aaed415eb9b5d47114734a988b25cc220f80064cef5bba3fa7195a4218b77 | Python | 2,692 | 75 | import matplotlib.pyplot as plt
import numpy as np
import seaborn as sns
from scipy.stats import f, norm, ttest_ind
def ftest(s1, s2):
"""
f-test for two distribtuions
"""
print("Null Hypothesis:var(s1)=var(s2)，α=0.05")
F = np.var(s1) / np.var(s2)
v1 = len(s1) - 1
v2 = len(s2) - 1
p_va... |
4dc926943f8c12a4ce8d7b8b0f0878862a2710c5c7ac42bcdf8ba2c732f03dab | Python | 2,693 | 62 | from NeuronModel.NeuronClass import neuronClass
import numpy as np
class izhikevich(neuronClass):
parameters = {'save': True, 'spike': True, 'C': 50., 'k_input': 1., 'v_rest': -80., 'v_t': -20., 'c': -55.,
'v_peak': 40., 'a': 0.01, 'b': -20., 'd': 150., 'noise': None, 'scale_I': None, 'tau': None... |
d1c548185521692ca14be062e34d5bea617f8d3c89a22eaef4ddb13a52907c99 | Python | 2,693 | 70 | from itertools import accumulate
import numpy as np
import torch
from torch.utils.data import Dataset
class ProcessedLigandPocketDataset(Dataset):
def __init__(self, npz_path, center=True, transform=None):
self.transform = transform
with np.load(npz_path, allow_pickle=True) as f:
dat... |
389d200a1263fbc36bfff88678263eb80a9c711baa8b5dc15ffba1c39db64071 | Python | 2,695 | 81 | # Copyright 2023 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... |
ae98ed33b2a09dce998bb4a9c683727b254302f59c60d8e81871ef2308c56c9e | Python | 2,696 | 74 | import pandas as pd
import numpy as np
import re
import scipy.stats
import argparse
def get_data(rawdata_path,save_path,cancer):
data=pd.read_csv(rawdata_path+'/'+cancer+'.DNAmethy.csv',sep=',')
sample=data.columns[1:]
data.columns=['ID']+list(sample)
ID_gene=pd.read_csv(save_path+'/DNA_methylation_ge... |
5979efe5e825d4ec4bb4629ff096caa412578b7f5fde9666945cec74eff66c7c | Python | 2,699 | 73 | import argparse
import sys
from pathlib import Path
from MRdataset import load_mr_dataset
from MRdataset.config import MRDS_EXT
from mrQA import check_compliance
from mrQA.run_merge import check_and_merge
from mrQA.run_parallel import create_script, submit_job
def main():
"""
Console script only for ABCD HP... |
b4eda251cdbc6c660000c0a51475b8728137f1082458edcbd8e254a5a0fcc2db | Python | 2,699 | 65 | import numpy as np
import pandas as pd
import torch
from collections import namedtuple
from src.neurogym import NG_utils
from src import utils
def test_config(env, model, args, indicator):
# tests a single configuration and extracts activations
transition = namedtuple('transition', ('observation', 'activatio... |
ebd55d36b3791daeda779e4ee0a002caf5ea2a0fd89066fe211caa068f7db400 | Python | 2,701 | 89 | # Copyright (c) 2021, David Williams, Reza Sameni
# All rights reserved.
# This source code is licensed under the BSD-style license found in the
# LICENSE file in the root directory of this source tree.
import numpy as np
import scipy.io as spio
def KFNotch(x,f0,fs,Q = [],R = [],gamma = 1):
# input arguments
... |
60a7252b2076e4460c20cabc39bb0641c3b432d68e6a9947d1e48ee15b5ea5d7 | Python | 2,703 | 84 | """Public APIs accept callables annotated with names imported under `TYPE_CHECKING`."""
import inspect
import sys
from typing import TYPE_CHECKING
import pytest
from langchain_core.messages import AIMessage, BaseMessage, HumanMessage
from langchain_core.runnables import RunnableGenerator, RunnableLambda
from langcha... |
3d13d94e6a9787724b3bdc382326278387383b068ad7e4528482008ba0dd4ee3 | Python | 2,704 | 80 | """Functions for constructing partial cover input set by year.
"""
from collections import defaultdict
import logging
import re
logger = logging.getLogger(__name__)
def read_years(fn):
"""Read years for a list of sequences.
Args:
fn: path to file with two columns; col 1 gives name of a sequence
... |
faecd06659954771f5d7a60d8a6383db807a36d7c0e65e683a87a2a4e499bc9a | Python | 2,705 | 68 | import argparse
arg_parser = argparse.ArgumentParser()
arg_parser.add_argument("uniprot_tsv", help="tab-separate value table of uniprot accessions")
arg_parser.add_argument("output_file", help="CSV file to write to")
arg_parser.add_argument("-a", "--alphafold_accessions", default=None, help="list of available alphafold... |
a2c1ef7c65f18e545ba03a407b6516f7f24a3d773f17d33b5dd80c71b41ea7fb | Python | 2,706 | 90 | # Copyright (c) 2021, David Williams, Reza Sameni
# All rights reserved.
# This source code is licensed under the BSD-style license found in the
# LICENSE file in the root directory of this source tree.
import numpy as np
import scipy.io as spio
def KFNotch2(x,f0,fs,Qbar = [],Wlen = []):
# input arguments
... |
0492e2e73af8119aa0015551e7d73a21ed00a09d492347edeee86e6eadd6282c | Python | 2,707 | 93 | """
Extract transcription start sites from an Ensembl GTF. Used to create the TSS reference file used in
~/ATAC_PIPELINE/atac-seq-pipeline/scripts/build_genome_data.sh
Usage:
python tss_from_gtf.py <gtf_file> <tss_outfile>
Supports both compressed (.gz) and uncompressed GTF files.
Output will be gzipped if the ou... |
4a789cba5c3179ac40456143fc834b0d5363a5e08754c99f28391fbe7cf23fba | Python | 2,707 | 84 | import argparse
import pandas as pd
import rdkit
import scipy
from rdkit import Chem
from sklearn.metrics import mean_absolute_error, mean_squared_error
def add_args(parser):
parser.add_argument(
"--prediction",
type=str,
required=True,
help="The path to prediction result to be ev... |
be5bc339381f19330e6a124521ac7f220b40ea9673020009be377c4b50518744 | Python | 2,707 | 87 | import os
import sys; sys.path.insert(0, '../')
import argparse
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import trajectory_reconstruction_tradeoff as T
import random
random.seed(20)
# trajectory params
dirname = '../'
datadir = os.path.join(dirname, 'datasets')
outdir = os.path.join(dir... |
aad551bd6aaa0f85f26ff0d80a2cde2416f0afd1e2902cdc560c15a9cfeab60e | Python | 2,708 | 93 | # coding: utf-8
""" MIT License """
'''
Project: Parenchymal Attention Network
Authors: Axel Masquelin
Description: Utility functions to plot metrics
'''
# Libraries
# ---------------------------------------------------------------------------- #
from sklearn.metrics import roc_curve, auc, confusion_matrix
... |
b04742aab68a9cd6aec64f9be3c987c7b03704d99627c86ea16989205671c7df | Python | 2,711 | 88 | import os
import sys
import img3
import argparse
import matplotlib.pyplot as plt
import numpy as np
import skimage.io
from numpy.ma import masked_array
from matplotlib import cm
# group details
group1 = [4834, 4836, 4844, 4849, 4851, 4858, 4864, 4868]
group2 = [4837, 4840, 4847, 4848, 4850, 4871, 4873]
group3 = [4838... |
db9944f564a962f16b78c62e014231f1bc39d4e83dbbd2446f40972616a874eb | Python | 2,712 | 80 | import tensorflow as tf
from tensorflow.keras.layers import Dense, LayerNormalization, BatchNormalization
from typing import Union
from .layer import StandardLRPLayer
class DenseLRP(StandardLRPLayer):
@staticmethod
def forward(a: tf.Tensor, w: tf.Tensor) -> tf.Tensor:
x = tf.tensordot(a, w, axes=1)
... |
50780d444f660724f4253cfb7516073607d2b5aef1c761936a583cb1dc82756d | Python | 2,714 | 80 | """ Helper class for stacked auto encoder networks.
:Version:
1.1.0
:Date:
21.01.2018
:Author:
Jan Melchior
:Contact:
JanMelchior@gmx.de
:License:
Copyright (C) 2018 Jan Melchior
This file is part of the Python library PyDeep.
PyDeep is... |
590fe2c35a109b26520beb6e374cec28fd955616b55857d9fba0c48113c1329c | Python | 2,714 | 81 | """
This script uses the recount metadata and a sparsity threshold to remove
sc-RNAseq data from the recount compendium
"""
import argparse
import pandas as pd
import tqdm
if __name__ == '__main__':
parser = argparse.ArgumentParser()
parser.add_argument('count_file', help='The file containing the count matri... |
6dd56b0cb25492e16e8f5bd51b07b52c5295b0e6a14a6e50916350f0b6ad9a40 | Python | 2,714 | 73 | import numpy as np
from scipy.ndimage import map_coordinates
from scipy.ndimage import label
def compute_profiles_fluo(fl, ma, m, visualize=False):
fl_straight = np.reshape(map_coordinates(fl,np.reshape(m,(m.shape[0]*m.shape[1],2)).T,order=0,mode='constant',cval=0).T,(m.shape[0],m.shape[1]))
ma_straight = np.... |
b293696bbfc238bc7e4fd6be70c8b2d2d0a46b508dad6eb526dfcf650488eb34 | Python | 2,718 | 103 | import torch
def batch_stack(props):
"""
Stack a list of torch.tensors so they are padded to the size of the
largest tensor along each axis.
Parameters
----------
props : list of Pytorch Tensors
Pytorch tensors to stack
Returns
-------
props : Pytorch tensor
Stack... |
db8111f84a9616364791b81588f93e496a01fa2cd37a748f49e513a05b31c8f9 | Python | 2,718 | 89 | import math
import torch
from torch.utils.data._utils.collate import default_collate
DEFAULT_PAD_VALUES = {
'aa': 21,
'aa_masked': 21,
'aa_true': 21,
'chain_nb': -1,
'pos14': 0.0,
'chain_id': ' ',
'icode': ' ',
}
class PaddingCollate(object):
def __init__(self, patch_size, length_r... |
291d96f7de14019adca5d424a8cccd1acf81a74f702425014bac58721b2807a4 | Python | 2,719 | 71 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Mon Mar 15 13:23:17 2021
@author: shni2598
"""
from brian2.only import *
import connection as cn
#%%
class one_area:
def __init__(self):
self.neuron_model_e = cn.model_neu_syn_AD.neuron_e_AD_t
self.neuron_model_i = cn.mo... |
87936e20b649daee9a6eb88b784ace70c45b74fb884c09de4e4f500fdd88ea0d | Python | 2,720 | 74 | # builtin modules
import os
import logging
# third party modules
import numpy as np
# pnabind modules
import pnabind
from .run_nanoshaper import runNanoShaper
from .run_msms import runMSMS
from pnabind.structure.structure import StructureData
def generateMesh(structure,
prefix=None, basedir=None, clean=Tru... |
137352b9380511fb9c0f331abb36fdb5620e45a44e34226a4c6a36b342fea8da | Python | 2,721 | 88 |
class Any2Int:
def __init__(self, min_count: int, include_UNK: bool, include_PAD: bool):
self.min_count = min_count
self.include_UNK = include_UNK
self.include_PAD = include_PAD
self.frozen = False
self.UNK_i = -1
self.UNK_s = "<UNK>"
self.PAD_i = -2
... |
339df678eacec93029168ac959d61d3b67228c7e84b1ea6f6f72fbf5bbc0c876 | Python | 2,722 | 51 | # Simple script to make sure basic usage
# such as training, testing, saving and loading
# runs without errors.
import os
def run(command):
print(command)
exit_status = os.system(command)
if exit_status > 0:
exit(1)
if __name__ == '__main__':
# download mini datasets
if not os.path.exist... |
57394cb1fe5333856a6ce09ad7098f72480151eaa05b96ece56425c3ba71b1c9 | Python | 2,722 | 90 | import json
import logging
from collections.abc import Sequence
from typing import Any
from langchain_core.agents import AgentAction, AgentActionMessageLog
from langchain_core.messages import AIMessage, BaseMessage, FunctionMessage
_logger = logging.getLogger(__name__)
def _convert_agent_action_to_messages(
age... |
3c000abd4a2db9436b898873bdd97c1bd40c79e22e34f6ed45d87efbe660f183 | Python | 2,723 | 95 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Thu Mar 12 14:51:42 2020
@author: shni2598
"""
import numpy as np
#from brian2.only import *
import matplotlib.pyplot as plt
from connection import coordination
#%%
def input_spkrate(maxrate = [800,800], sig=[6,6], position=[[-32, -32],[0, 0]], n_side=64,... |
653bffda79521e6c910f3b9e0263a0e450a93485d6650494736a70a8620bb8e5 | Python | 2,730 | 82 | from dataclasses import asdict
from logging import Logger
from pathlib import Path
from typing import List
from tqdm import tqdm
from ..data import AnnotationTable, WorldlineTable, Annotation
from ...methods.track_frame import track_frame
from ._utilities import default_args
@default_args("_now, True, False, False"... |
6bb032d690451216bff0efa4cc6588a305c094fa686ef1f6f8ee9aec335b7848 | Python | 2,731 | 78 | import numpy as np
from skimage.io import imread
import os
from natsort import natsorted
from skimage.measure import regionprops
import torch
"""
Generate the Svetlana-compliant labels file from the Panuke dataset labels
"""
images_folder = "/home/cazorla/Images/Panuke/Part 1/training_frugal/Images"
masks_folder = "/... |
1913deaec0bf1807f5139659f15932b71a194bedd2a356555eea0d64c254fdea | Python | 2,735 | 74 | import pandas as pd
import numpy as np
import re
import scipy.stats
import argparse
def get_data(rawdata_path,save_path,cancer):
data=pd.read_csv(rawdata_path+'/'+cancer+'.DNAmethy.csv',sep=',')
sample=data.columns[1:]
data.columns=['ID']+list(sample)
ID_gene=pd.read_csv(save_path+'/DNA_methylation_pr... |
ccb2c6e8474c13a24266200fd3e09b2132a500ffe8e8cab411ee75066a51b290 | Python | 2,735 | 72 | import pandas as pd
from collections import namedtuple
from stable_baselines3 import PPO
from animalai.envs.arena_config import ArenaConfig
from src import utils
from src.animalai import AAI_utils
def test_config(env, model, args):
# Tests a single configuration and extracts activations
transition = namedtupl... |
648a96b33d6bcd8cdc07281aaa56d33e76eeb061ccf5e1091f297c6361d33148 | Python | 2,737 | 82 | # Copyright 2019 DeepMind Technologies Limited. 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
#
# https://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by... |
a7d3a0974d85592df2d925160236ca761323ae4ec8eea4a3e5013e8c21769ad7 | Python | 2,743 | 95 | import argparse
import pathlib
from typing import Optional
import numpy as np
import pandas as pd
import decoupler as dc
import yaml
import json
import gzip
def parse_arguments(
key: Optional[str] = None, stage: Optional[str] = None, method: Optional[str] = None
):
"""
Parses command line arguments
"... |
595062a288c279bd204269b2d2a668e11f16fce714e8884c787a5fb0ebb7c41c | Python | 2,747 | 77 | import glob
import numpy as np
from scipy.stats import iqr
import matplotlib.pyplot as plt
from paths import TEST_DATA_PATH
test_data_path = TEST_DATA_PATH + "/baseline/"
ground_truth = np.squeeze(np.load(test_data_path + "baseline.npz")["oxygenations"])
wls = []
results = []
results_corr = []
est_oxy = []
est_oxy_c... |
f1f704e4a1006246615cf6aa61a9d41156ab9705d298f6c538779e18d873224f | Python | 2,748 | 96 | # Loading Data - SVHN - followed paper (https://arxiv.org/pdf/1603.09382.pdf)
# Imports
import numpy as np
import scipy.io
from sklearn.model_selection import train_test_split
# Split train data into train and validation gettting certain number of labels from each class
def train_val_split_count(x_train, y_train, si... |
937963926af2649d55527f42deb42ab7ba345c96d6173f8bca2610c84f71ba24 | Python | 2,750 | 60 | # 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... |
e7f19eb02731658f9ab934e005dd2c4087d44268a77dcb6a83447184cd36d404 | Python | 2,753 | 72 | """Property tests for pydeepmapper.accumulate. Stdlib + pytest + hypothesis only."""
from __future__ import annotations
import os
import sys
from hypothesis import given
from hypothesis import strategies as st
sys.path.insert(0, os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
from pydeepmapper import a... |
2f8dca4940f0c161e026c43c6ba253379f5941167836e65f2569cb7630f27b5c | Python | 2,754 | 85 | # Copyright 2020 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... |
4f0b968536ffb3731a8dd4bc0b3c71b705e9abdba4a6512083bb53bf37c70d4e | Python | 2,754 | 104 | import numpy as np
import steps.interface
from steps.saving import *
from steps.sim import *
from steps.geom import *
from steps.model import *
from steps.rng import *
from . import DiffPoint
########################################################################
# 1D diffusion in a finite tube with a constant and ... |
24712ac53231591402345f8b4907ea24cb255ce460f1445c595035b598c7603a | Python | 2,755 | 89 | """
GPyTorch Regression Example
Demonstrates how to implement full-batch L-BFGS with weak Wolfe line search
without Powell damping to train an RBF kernel Gaussian process on a simple function
y = sin(2*pi*x) + eps
eps ~ N(0, 0.2).
Based on GPyTorch example; see GPyTorch documentation for more information.
Many thank... |
cb5ab622360408c36357b4fe3f7b5d90743d080e4c86e1b07668d77d520aa1c4 | Python | 2,755 | 71 | from .twod.datapipes.cfd import(
onestep_test_datapipe_cfd,
onestep_valid_datapipe_cfd,
train_datapipe_cfd,
trajectory_test_datapipe_cfd,
trajectory_valid_datapipe_cfd
)
from .twod.datapipes.navierstokes2d import (
onestep_test_datapipe_ns,
onestep_test_datapipe_ns_cond,
onestep_valid_d... |
37cdd993cf3628ce85f49c71ccb95bfb51abb70ec70ace8d4f5a9e4be6f81ff6 | Python | 2,757 | 107 | import copy
import torch
class Compose:
def __init__(self, transforms):
self.transforms = transforms
def __call__(self, data, idx_mask=None):
for t in self.transforms:
data, idx_mask = t(data, idx_mask)
return data, idx_mask
_TRANSFORM_DICT = {}
def register_transform... |
c6a8ec74e0b7bf386c942b4741437e85243b87d73622e8d970cca2e9c49d9391 | Python | 2,757 | 115 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
import numpy as np
import sys
def main(datalist, bvecfname, bvalfname):
global_formater = '%.5f'
print('\nUsing this output format: {}'.format(global_formater))
## BVECS (PVM_DWGradVec + normalization)
print('\nextracting bvecs from normalizing $PVM_DwGradVec')
... |
e46971f0a45b88aa87e3434e37e96756e4bf0327e16b1a5712ff8eda239e3def | Python | 2,757 | 98 | '''
PipelineKegg.py - Tasks related to KEGG analysis
================================================
Reference
---------
'''
import cgatcore.experiment as E
from rpy2.robjects import r as R
import cgatcore.iotools as iotools
import cgat.Biomart as Biomart
import re
def importKEGGAssignments(outfile, mart, host, bi... |
ed7d7d706e1ca61724a2b176992122e87de8394ea9e5b595ce0e84b14bfc5221 | Python | 2,758 | 108 | from setuptools import setup, find_packages
import io
setup( name='mantis-ml',
version='1.6.3',
author='Dimitrios Vitsios',
author_email='dvitsios@gmail.com',
description='Disease-agnostic gene prioritisation from high-throughput genomic screens by stochastic semi-supervised learning',
url="https://github.com/as... |
d6a71165b28d287f9fd98840ccb21fa5e4b854ff2f4c729fe7e63e5ad872537b | Python | 2,760 | 84 | import numpy as np
import os
import re
from data import protein
from data import residue_constants
from scipy.spatial.transform import Rotation
from openfold.utils import rigid_utils
CA_IDX = residue_constants.atom_order['CA']
Rigid = rigid_utils.Rigid
def create_full_prot(
atom37: np.ndarray,
atom3... |
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