sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
183e8d5fe9a44e663163c80eb1bd7fb7c026b12d637ddf83324fd804f01c061c | Python | 1,548 | 42 | import numpy as np, matplotlib.pyplot as plt, sys
import pumpprobe as pp, wormdatamodel as wormdm
sort = "--sort" in sys.argv
neu_j = None
for s in sys.argv:
sa = s.split(":")
if sa[0] in ["-j","--j"]: neu_j = int(sa[1])
ds_list = "/projects/LEIFER/francesco/funatlas_list.txt"
funa = pp.Funatlas.from_datasets... |
36dfd9d10888eaed07a5b638f20e9a44578fa74b5d33e1552d93de6ff205a57c | Python | 1,549 | 48 | # Copyright 2018-2023 Xanadu Quantum Technologies 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... |
3bebc81216badad2b0908bfeff0633820e606d6add039593dac8fc037659bdbc | Python | 1,549 | 46 | import aicspylibczi
import numpy as np
import os
import pathlib
import tifffile
import gc
from sys import getsizeof
def get_reassembled_czi(czi):
#Reassembles the czi images. It returns a np.array of uint16.
data = []
dims_shape = czi.get_dims_shape()
if not 'C' in dims_shape[0]:
raise Exception("Image la... |
b8fe828ddc5e513f8dcc5c33ad9549631a748ecf72f947fb3b7e342d864b48e2 | Python | 1,549 | 48 | # -*- coding: utf-8 -*-
import glob
import logging
import shutil
import subprocess
from pathlib import Path
import click
from dotenv import find_dotenv, load_dotenv
parent = str(Path(__file__).resolve().parent)
def combine_all(root, outpath):
files = glob.glob(root + "/**/*.csv", recursive=True)
print(files)... |
0ecbbaa6f43903a31a9f2b7556540b2bca51a59b6bf92d93dee6c9bd141a4650 | Python | 1,550 | 48 | import pytest
import pandas as pd
class TestFlags:
def test_equality(self):
a = pd.DataFrame().set_flags(allows_duplicate_labels=True).flags
b = pd.DataFrame().set_flags(allows_duplicate_labels=False).flags
assert a == a
assert b == b
assert a != b
assert a != 2
... |
5d93d15e98247f1261322277e2d6f6f1f395236e7a0a8ddfd1e82f7da5e39799 | Python | 1,550 | 66 | # Copyright 2025 Xanadu Quantum Technologies 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 agre... |
2edf2ed931bfe8c720df0717f59912e236e3c9a13815d9194f38b73d6325f44b | Python | 1,553 | 42 | import scipy.io as scio
import numpy as np
# 生成模型需要的cites文件
if __name__ == "__main__":
# 处理为.cites文件
# data = scio.loadmat(r'E:\experiment\testdata\dataset1\Normalize\test3.mat')["permission"]
# self = np.eye(len(data))
# datanew = data-self
# fout = open(r'E:\experiment\testdata\dataset... |
797113814f2b234ea5b9b3063d2aa7c2ecec85303ad8f291a782f317067eba6a | Python | 1,553 | 43 | from base import surfaces
from base.kernelFunctions import Kernel
from base import surfaceMatchingNormalExtremities as SMNE
import matplotlib
matplotlib.use("QT5Agg")
import matplotlib.pyplot as plt
from base import loggingUtils
import os
os.environ["CUDA_DEVICE_ORDER"] = "PCI_BUS_ID"
os.environ["CUDA_VISIBLE_DEVICES"]... |
c27e782640fdd3a77e6cb3e2bb4c7091a0d53dfc1c6e6fe6fc377b66d5b82f8d | Python | 1,553 | 67 | import numpy as np
import pytest
from pandas._libs import lib
import pandas as pd
import pandas._testing as tm
def assert_block_lengths(x):
assert len(x) == len(x._mgr.blocks[0].mgr_locs)
return 0
def cumsum_max(x):
x.cumsum().max()
return 0
@pytest.mark.parametrize(
"func",
[
cu... |
8b42e9c7b10e580ec5ca047e5bafb744e409e4c0bc80dd733803f47553901e5a | Python | 1,554 | 51 | # -*- coding: utf-8 -*-
"""
Created on Fri Oct 13 14:46:54 2023
@author: nrq2
"""
## ssh rachel@nostromo.ncl.ac.uk
## spyder-scenic-ad3
# cd /data/rachel/Linda_Lako/Retina/AD3/ATAC_analysis/SCENIC/
# conda activate scenicplus
# python -m spyder_kernels.console
# /home/rachel/.local/share/jupyter/runti... |
15fa01a140cdfc5fcb01aa3efab30deb8560f674c18254a7c4ca3371d8c37ad5 | Python | 1,555 | 54 | from values import *
# across basolateral
def kcc4(conc,memb_id,xKCC4,area):
bet2 = conc[1][1]/bkkcc
bet5 = conc[1][4]/bkkcc
bet6 = conc[1][5]/bkkcc
gam2 = conc[2][1]/bckcc
gam5 = conc[2][4]/bckcc
gam6 = conc[2][5]/bckcc
dnu2 = conc[10][1]/bmkcc
dnu5 = conc[10][4]/bmkcc
dnu6 = conc[10][5]/bmkcc
sig2 = 1.0+... |
c80fbc51c5c99b5571d18bb402903de70f5497c0d2ba5aaff1146dc1c464a4c9 | Python | 1,555 | 58 | import os
import csv
import random
import numpy as np
import tensorflow as tf
from .augmentation import rotation3D, relocation
def gen(dataset, batch_size, shuffle, augment=False):
while 1:
if shuffle:
random.shuffle(dataset)
for i in range(0, len(dataset), batch_size):
ds... |
1e82cb4c7959f2365fe03496d53cab21c43db6e77bebaae56e05abb6f1e84a81 | Python | 1,557 | 27 | # Copyright (c) 2018-2023, NVIDIA Corporation
# All rights reserved.
#
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are met:
#
# 1. Redistributions of source code must retain the above copyright notice, this
# list of condit... |
3f32fd3f8f3046c9c4c3a11121be194525f83d2a66e19578caed6de5ad9bdf71 | Python | 1,558 | 27 | # Copyright (c) 2018-2023, NVIDIA Corporation
# All rights reserved.
#
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are met:
#
# 1. Redistributions of source code must retain the above copyright notice, this
# list of condit... |
b7f278f99cef414fae874755698209c678bdbfebd84d5c0d164d25fd47e19a3b | Python | 1,559 | 60 | # -*- coding: utf-8 -*-
import importlib
import logging
__all__ = ["get_progress_bar"]
logger = logging.getLogger(__name__)
try:
import tqdm
import tqdm.auto
except ImportError:
tqdm = None
class _NoOpPBar(object):
"""This class implements the progress bar interface but does nothing"""
def __... |
b04cf6d5f51d752795eab23bbe31bc512de432b4267ec79ddc2c90101e8edd60 | Python | 1,560 | 50 |
import numpy as np
import pandas as pd
homeDir = 'path to home folder'
chanDir = 'path to folder containing channel information (e.g. source data)'
# Specify ROIs of interest
ROIlist = ['Anterior Insular Cortex',
'Posterior Insular Cortex',
'Frontal Orbital Cortex',
'Subcallosal Cor... |
5896f80cc79efceee0a7a98647c3a1ed9a2c677b36ba414618aeb1cb29096149 | Python | 1,562 | 47 | from nose2.tools import params
import tempfile
import os
import numpy as np
import pandas as pd
import cooler
import chromosight.utils.plotting as cup
import chromosight.utils.detection as cud
import chromosight.utils.io as cio
mat, chroms, bins, res = cio.load_cool("data_test/example.cool")
mat = mat.tocsr()
# Get... |
7ceb547bf42543fef718659bd346e05ee8389f1f7ce586300e6cfcb1aa58b118 | Python | 1,562 | 48 | import torch
from typing import List
from ...image import Stack
from ...utils import ncc_loss
def matrix_rank(
stacks: List[Stack], threshold: float = 0.1, rank_only: bool = False
) -> List[float]:
scores: List[float] = []
for stack in stacks:
masked_slices = stack.slices * stack.mask.float()
... |
7d117ea07b77e17ef98f6a197079397ca2fb3f6455dc2d5da10a71e998c4452e | Python | 1,562 | 53 | #!/usr/bin/env python
"""Parse machine info (cat /proc/cpuinfo /proc/meminfo) and write a
tab-delimited row to stdout with the following fields:
1. Program name
2. Total memory
3. Number of processors
4. Speed of processors
"""
import argparse
from collections import defaultdict
from common import fileopen, parse_pro... |
a465188ad8dc91a5fd9bf8123cbb325aaae7694c2f4742e7800d814d349285b2 | Python | 1,562 | 55 | import contextlib
import numpy as np
import torch
def seed_all(seed):
torch.manual_seed(seed)
torch.cuda.manual_seed(seed)
torch.backends.cudnn.deterministic = True
torch.backends.cudnn.benchmark = False
np.random.seed(seed)
@contextlib.contextmanager
def temp_seed(seed):
"""Temporarily set th... |
988964ded5ee1f9b5525a65972bc3cd8bc2bd51e71dc242f6284ee7bb93a3c8a | Python | 1,563 | 56 | import torch.nn as nn
class BaseRGCN(nn.Module):
def __init__(self, num_nodes, h_dim, out_dim, num_rels, num_bases=-1,
num_hidden_layers=1, dropout=0, use_cuda=False):
super(BaseRGCN, self).__init__()
self.num_nodes = num_nodes
self.h_dim = h_dim
self.out_dim = out_... |
ab2c6b441e8251575a3cab36cd1608e97e5c1c8d453ec7adb74da63da4983a23 | Python | 1,563 | 56 | """
Set up templateflow in customised directory.
Download atlases that are relevant.
This is no longer need for curious curator. We uploaded all the atlas on osf.
"""
import os
from pathlib import Path
def fetch_schaefer():
"""Download schaefer2018."""
import templateflow.api as tf
schaefer_path = tf.ge... |
ac946f64e8af20c1ae0c23b11de2a6f76e29a34e2946dfb05214bdcc0ad2cb6a | Python | 1,563 | 52 | # Based on
# Color Universal Design (CUD)
# - How to make figures and presentations that are friendly to Colorblind people
#
#
# Masataka Okabe
# Jikei Medial School (Japan)
#
# Kei Ito
# University of Tokyo, Institute for Molecular and Cellular Biosciences (Japan)
# (both are strong protanopes)
# 11.20.2002 (modified ... |
0645317f5f03c333f6e28170eeef5767d4900b54c631abf529a4d691567ab6f7 | Python | 1,564 | 53 | from __future__ import print_function
import argparse
import torch
def compare_model_weights(model1, model2, eps, verbose):
param1 = torch.load(model1)
param2 = torch.load(model2)
# first check if both models have the same keys
if (param1.keys() != param2.keys()):
print('The parameter of the... |
9dd98ffcb8191e59b61da280d6e76d5cf5f704de8b5f7fff9b42630ecb9682e3 | Python | 1,564 | 46 | import torch
from torch import nn
from rl_games.common import common_losses
from rl_games.algos_torch.layers import symexp, symlog
from rl_games.common.extensions.distributions import TwoHotDist
class DefaultValue(nn.Module):
def __init__(self, in_size, out_size):
nn.Module.__init__(self)
self.val... |
b49fd6057f1c6f8f6ea793f2ab45f1da220ce2fcd135e34eea61a02d2139ab11 | Python | 1,564 | 74 | import setuptools
from setuptools import setup
install_deps = [
'numpy>=1.20.0',
'scipy',
'scikit-learn',
'tqdm',
'torch>=1.6',
'numba',
'faiss-cpu',
]
gui_deps = [
'pyqtgraph>=0.13.0',
'pyqt5',
'pyqt5.sip',
'google-cloud-storage',
'matplotlib'
]
docs_deps = [
'sph... |
f1a7eccf7be7aa897185c30eee79314f408d8e0c76e651146566bce481f34d33 | Python | 1,564 | 51 | import pytest
from pandas.errors import Pandas4Warning
import pandas as pd
import pandas._testing as tm
@pytest.mark.parametrize("tz", [None, "Asia/Shanghai", "Europe/Berlin"])
@pytest.mark.parametrize("name", [None, "my_dti"])
def test_dti_snap(name, tz, unit):
dti = pd.DatetimeIndex(
[
"1/... |
13200153152bc75be8a698cbc4c77e73e0c0bae8455fc38115bfe699864bc3c2 | Python | 1,567 | 42 | # -*- coding: utf-8 -*-
"""
Get transformation MRI <-> MEG with MNE coregistration. Tthis script is run
manually for each subject.
Vinding, M. C., Eriksson, A., Low, C. M. T., Waldthaler, J., Ferreira, D., Ingvar, M., Svenningsson, P., & Lundqvist, D. (2021). Different features of the cortical sensorimotor rhythms are... |
d983054196cbbd0cbddd19b2a43b7595a50dbaf7cf6744eb745e90cc110334aa | Python | 1,567 | 55 | import time
import logging
from abc import abstractmethod
import torch
from modules import model_utils
class Model:
"""
This base class is responsible for loading the model.
"""
DOCKER = True # Set this variable to True if using Docker container.
DOCKERPATH = "/opt/conda/envs/ga... |
13174d602ee1c22ae21fd98d385347d73aa4102881e59dae8f30e0f9263805d7 | Python | 1,568 | 44 | #!/usr/bin/env python
import os, sys
from cupcake.io.GFF import collapseGFFReader
def main(input_prefix):
input_gff = input_prefix + '.gff'
if not os.path.exists(input_gff):
print("Looking for input GFF {0} but not found! Abort!".format(input_gff))
sys.exit(-1)
f1 = open(input_prefix + '.... |
67b859ae2034fb28fe6ed3284807898119d29347827d2ca509a54af270e3be5d | Python | 1,568 | 52 | import os
import platform
PACKAGE_PATH = os.path.dirname(__file__)
PLATFORM = platform.system().lower()
BINS_DIR = os.path.join(PACKAGE_PATH, 'bins')
MODELS_DIR = os.path.join(PACKAGE_PATH, 'models')
MODEL_PATH = os.path.join(MODELS_DIR, 'pi.stan')
MODEL_NAME = 'pi'
RECOMMENDED_MEMORY = 16 * (1024**3) # 16 GB
# Com... |
99213433e8bd584849ba466bfd6c04f34d5445c02a13dbfcf241306306a4c7f7 | Python | 1,568 | 67 | """Tests that the tslibs API is locked down"""
from pandas._libs import tslibs
def test_namespace():
submodules = [
"base",
"ccalendar",
"conversion",
"dtypes",
"fields",
"nattype",
"np_datetime",
"offsets",
"parsing",
"period",
... |
0bf97cb74d0bfa7f1b2e4fd78fddcdd7f8b8c487574720ce446f2bfd3b99b066 | Python | 1,569 | 41 | import pytest
import pandas as pd
import pandas._testing as tm
def test_add_prefix_suffix(string_series):
with_prefix = string_series.add_prefix("foo#")
expected = pd.Index([f"foo#{c}" for c in string_series.index])
tm.assert_index_equal(with_prefix.index, expected)
with_suffix = string_series.add_s... |
4932ad42573acca6f5449f731111b465bcdc8c78bc6d95fa4f7fdb3e31088913 | Python | 1,571 | 41 | import torch
from torch_geometric.transforms import BaseTransform
class RattleParticles(BaseTransform):
"""Applies a random gaussian noise to paritcle positions. The standard deviation
of the noise is drawn uniformly from a range [sigma_min, sigma_max].
Args:
sigma_min (float): The minimum standa... |
84ca852b557c0eb74ada5d9a437ed192a12b179b896c7b747449457a3e2faecd | Python | 1,571 | 50 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Wed Jul 5 11:47:43 2023
@author: Noelia Martínez-Molina, adapted from code provided by Yonatan Sanz-Perl at CNS, UPF
"""
from numpy import genfromtxt
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.style as style
import seaborn as sn... |
91e5fab7c72da7d9b86df78976926f4e40596cd7c98975bb2fd66ba49beb245d | Python | 1,571 | 54 | import logging
from pathlib import Path
from datetime import datetime
from contextlib import redirect_stdout
def make_log_name(name):
log_name = f"pred_age_{name}" + datetime.now().strftime("%Y%m%d-%H%M%S") + ".log"
return log_name
def setup_logging(log_file, log_level=logging.INFO, handler=logging.StreamHand... |
b2fb9554f3a2c5a308a6425f682baa9acfd83d249e209c71ceacdac9752e8f48 | Python | 1,572 | 36 | import sys, argparse
import pandas as pd
argparser = argparse.ArgumentParser(description='Generates naturalstories.evmeasures data table.')
argparser.add_argument('f1', type=str, nargs=1, help='Path to experiment data table')
argparser.add_argument('f2', type=str, nargs=1, help='Path to itemmeasures data table')
args,... |
f87744604c25aad3cf6f5bc5bbc5c7a386bb5fa13f7313eb7b65a3eb13cae57c | Python | 1,573 | 58 | # -*- coding: utf-8 -*-
#! JN 2014-10-23 Add spike viewer to SWR viewer
from PyQt5.QtWidgets import QDialog
#from PyQt5.QtCore import *
#from PyQt5.QtGui import *
from .sWidgets import *
from ui_spikes import Ui_Dialog
import numpy as np
from matplotlib.gridspec import GridSpec
gs = GridSpec(1, 1, top=.95, bottom=... |
b43b27dba2428b50c3d34d563dfb62217c94363b85c83f25776fb901c906a19a | Python | 1,574 | 40 | import numpy as np, sys
import matplotlib.pyplot as plt
import wormdatamodel as wormdm
plt.rc("xtick",labelsize=18)
plt.rc("ytick",labelsize=18)
to_paper = "--to-paper" in sys.argv
folder = "/projects/LEIFER/francesco/pumpprobe/AKSxneuropal/20210209/pumpprobe_20210209_163726/"
rec = wormdm.data.recording(folder, re... |
dd4e461675a6a7d7113d7f506376659b0beab263292c52eb4cadb06245965adb | Python | 1,574 | 47 | #%%
from pathlib import Path
from src.fs_roi_lut import read_rois, Roi
from src.fs_stats import StatsFile
from src.paths import Paths
import pandas as pd
import numpy as np
import os
#%% set paths
data_dir = Path(__file__).parent.parent.parent / 'data'
# %% read rois
rois = read_rois(data_dir / "rois_fs.json")
rois.... |
4851e5642311d3d4897f91ed29f7a23dc3d08cd1d30f83a1bbaab925b9e3b8a4 | Python | 1,576 | 39 | import torch
from torch_geometric.data import Data
from ssa import sparrow_search_algorithm
from cnn import CNN
from gnn import SimpleGNN
from cbam import CBAM
from torchvision import transforms
def evaluate_model(model, dataloader, device):
model.eval()
all_predictions = []
all_labels = []
... |
ea063cf490cebef3868e0e74eb7a5275aef3b41d4458450255e14fe9afb0963d | Python | 1,576 | 41 | #!/usr/bin/env python3
import os, sys
from csv import DictReader
import pysam
def paint_bam_post_phaser(input_bam, output_bam, read_info, chrom, start, end):
reader = pysam.AlignmentFile(input_bam, 'rb')
fout = pysam.AlignmentFile(output_bam, 'wb', header=reader.header)
for r in reader.fetch(chrom, start,... |
f2aa2d68a8b9f86128a2c72fc8412b373587fb73e02fee0722667a419bbb3c67 | Python | 1,576 | 61 | import dclab
import numpy as np
import matplotlib.pylab as plt
# dataset
ds = dclab.new_dataset("fluorescence/fluorescence.rtdc")
evt = 54
# traces
flraw = ds["trace"]["fl2_raw"][evt]
flmed = ds["trace"]["fl2_median"][evt]
# plot
fig = plt.figure(figsize=(7, 3))
# image
axi = plt.subplot(221, title="event image")... |
1d097a4f5c803707e10859d39fc729f3e2df17b78ca7fb437c59199c6cbad5ff | Python | 1,578 | 59 | # Configuration file for the Sphinx documentation builder.
#
# For the full list of built-in configuration values, see the documentation:
# https://www.sphinx-doc.org/en/master/usage/configuration.html
# -- Project information -----------------------------------------------------
# https://www.sphinx-doc.org/en/master... |
85538fc50dfcd224e2fbeadd7b544e614ed9fd218709b22c42f91d992b96942f | Python | 1,580 | 43 | from PyQt5.QtWidgets import QWidget, QVBoxLayout, QCheckBox
from PyQt5.QtCore import pyqtSignal, Qt
class CheckBox(QWidget):
# Signal emitted when the checkbox state changes. It sends the label of the checkbox when checked.
sgn = pyqtSignal(str)
def __init__(self, label):
super().__init__()
... |
b4fc50bc1ac98d7d4fd720d9bde5038cc2d8d02689dbbcc7baa02e3f74eed558 | Python | 1,581 | 46 | import sys
import re
import pandas as pd
import argparse
network_names = ['Lang', 'MDlangloc', 'MDspatwm', 'DMNlangloc', 'DMNspatwm', 'AC', 'LHip', 'RHip']
def compute_network(name):
if 'Hip' in name:
return 'Hip'
for network_name in network_names:
if name.startswith(network_name):
... |
d6bc671b034aa73a2272c8fa6f58304b5a5875cc8530f727ef3acb05e5432512 | Python | 1,581 | 72 | # Count class frequency to deal with unbalance
import tensorflow as tf
import os
import nibabel as nib
import numpy as np
import random
import re
from skimage.transform import resize
from pathlib import Path
from const import *
# CSF: 1, 2, 23, 24, 0, 18 -> 1
# WM: 16, 17 -> 2
# GM: Rest -> 3
# Brain Stem: 7 -> 4
# C... |
0212263c61eea02519df93601bed7a39e090f3ee931a444c58ba95c177c61689 | Python | 1,582 | 49 | from .. import utils
from ..file_utils import get_generated_path, make_basedir
import os
template1 = '''
import os, sys
# Add the pheweb package into the PYTHONPATH so that we can import it.
# This assumes that you cloned pheweb from github. If you installed with pip, maybe this has no effect?
sys.path.insert(0, '{... |
5b338c7e10803338fe40d8cfad5c58ebd1f4ddc1fd418ba7c806a371f0e62493 | Python | 1,582 | 42 | """session 25: trial artifacts (stored_path + sha256 + size_bytes + params)
Revision ID: c3d4e5f6a7b8
Revises: b2c3d4e5f6a7
Create Date: 2026-05-08 20:00:00.000000+00:00
Promotes ``Trial`` from a metrics-only row to a full candidate-pipeline
record. Each compare/search trial now keeps its fitted pipeline pickle
on di... |
e310ea11a2893949192fc0a7d71c6f4664214302b1b6ead147f38b66201ee8cd | Python | 1,582 | 42 | #!/usr/bin/env python
import os, sys
from collections import defaultdict
from Bio import SeqIO
from cupcake.io import BioReaders
def type_fa_or_fq(file):
file = file.upper()
if file.endswith('.FA') or file.endswith('.FASTA'): return 'fasta'
else: return 'fastq'
def summarize_GMAP_sam(input_fa_or_fq, inpu... |
eb5af4e6c8574184f42f0e3737f2242df63f70eaad3f66aab51be7eb9bf7e529 | Python | 1,583 | 45 | import os
import torch
import pickle
import matplotlib.pyplot as plt
import matplotlib as mpl
import pandas as pd
load_dir = '/Users/elizabethnewman/Desktop/tnn_results/cifar10_timing/tensor/'
results_tensor = []
for subdir_name in ['depth_4', 'depth_8', 'depth_16', 'depth_32', 'depth_64', 'depth_128']:
print(sub... |
230ce43fa747ea6ce923bc209eea485e87689d629ad70cb5ef879386153c6775 | Python | 1,584 | 60 | import sys
import glob
import pandas as pd
import numpy as np
import h5py
file_list = sys.argv[2]
print(file_list)
LABEL = 'Characteristics[cell_type]'
total_data = pd.DataFrame()
for ff in [file_list]:
data = pd.read_csv(ff, sep='\t', index_col=0)
total_data = total_data.append(data)
print(total_data.sha... |
2069ff109c72a19fb75c1bf1138715147a82cdd53471e39ee29030c734de0f64 | Python | 1,585 | 53 | # Generate base histograms of the first and last 20 bp of read1 and read2
import argparse
from common import *
import csv
from xphyle import xopen
import tqdm
nuc = ('A','C','G','T','N')
def make_hists(fq1, fq2, n_bases=20):
read1_hist = [
dict((base, [0] * n_bases) for base in nuc)
for i in rang... |
4eab07cef48fd5f4681d80950c7be2e3942932586fe6093d2acc166549aa7006 | Python | 1,585 | 47 | import pytest
import pandas as pd
class TestIntervalConstructors:
@pytest.mark.parametrize(
"left, right",
[
("a", "z"),
(("a", "b"), ("c", "d")),
(list("AB"), list("ab")),
(pd.Interval(0, 1), pd.Interval(1, 2)),
(pd.Period("2018Q1", fre... |
15a39990f91b0aaa88a8cf4738ff81dcc7b8a3fc5daabf4460105c1051920c79 | Python | 1,586 | 43 | import numpy as np
import pandas as pd
def compute_pvalues(scores: np.ndarray, null_scores: np.ndarray, verbose: bool=False) -> pd.DataFrame:
"""
Compute empirical p-values.
Args:
scores (ndarray) : The ES scores computed using actual annotation.
null_scores (ndarray) : The ES sco... |
46e9518f25b3527f6054555eca99dd5300cb7b3a51d92580083ebf0589b12838 | Python | 1,586 | 50 | from __future__ import annotations
import numpy as np
import pyarrow
def pyarrow_array_to_numpy_and_mask(
arr, dtype: np.dtype
) -> tuple[np.ndarray, np.ndarray]:
"""
Convert a primitive pyarrow.Array to a numpy array and boolean mask based
on the buffers of the Array.
At the moment pyarrow.Bool... |
99f03982e3e86ea5e6c1e8986b32628f6bd60c5393ae53f87a736a6b2d02011a | Python | 1,587 | 51 | #!/usr/bin/env python
# -*- coding: UTF-8 -*-
# Created by Roberto Preste
from setuptools import setup, find_packages
with open("README.rst") as readme_file:
readme = readme_file.read()
with open("HISTORY.rst") as history_file:
history = history_file.read()
requirements = ["Click", "pandas", "requests", "aio... |
a413de3725bd4366ba7392d8ed34f5f1032113f08a3566d0d4c4accd1ddd8533 | Python | 1,588 | 36 | """
Converts foldseek databases into pairs of 3Di and amino acid fasta files.
"""
import argparse
import sys
from esmologs import __version__
def foldseekdb2fasta(input_basename, output_basename):
with open(f"{input_basename}","rb") as aa_h, open(f"{input_basename}_ss","rb") as tdi_h, open(f"{input_basename}_h"... |
ae9197396ba4d10d76ca082a81d4b974400680850430cbcab40d4db62736fbc8 | Python | 1,588 | 53 | # Copyright 2026 Xanadu Quantum Technologies 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 agre... |
fc32975f2083204fb7086d9012556b4b97fbe5ead064e64013c1bd9897cc54c3 | Python | 1,588 | 58 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
@author: Noelia Martínez-Molina
"""
import seaborn as sns
import matplotlib.pyplot as plt
import pandas as pd
# Set plot style and frame
sns.set_theme(style="darkgrid")
plt.rcParams['font.family'] = 'Helvetica'
# Import data from file
df=pd.read_csv('/Volumes/LASA... |
56d873c01787b9966da9a0a52d6f9c60b9bb644bdb748d4336ed31e6f1173fc1 | Python | 1,589 | 51 | """Test stats functionality"""
import pathlib
import tempfile
from unittest import mock
from PyQt6 import QtWidgets
from shapeout2.gui.main import ShapeOut2
from shapeout2 import session
from shapeout2.gui.compute.comp_stats import ComputeStatistics
import pytest
data_path = pathlib.Path(__file__).parent / "data"
... |
df5dcca8b4c3799ba2d7b89d605de4ba08223928e5de9b39a20820acfc9917ed | Python | 1,589 | 43 | #%% Imports
from pathlib import Path
import argparse
from src.logsetup import Logger
from src.experiment import ExperimentBuilder
import sys
import os
import warnings
#%% set Paths and configs
RESULTDIR = Path(__file__).parent.parent / "results"
DATADIR= Path(__file__).parent.parent / "data"
def run(data_dir: Pa... |
b69534efe103b4f89120bb2806bf477a12ad83cca8295fc69dfedde62162e8f4 | Python | 1,590 | 68 | import itertools
import numpy as np
import pytest
import pandas as pd
def create_series():
return [
pd.Series(dtype=np.float64, name="a"),
pd.Series([np.nan] * 5),
pd.Series([1.0] * 5),
pd.Series(range(5, 0, -1)),
pd.Series(range(5)),
pd.Series([np.nan, 1.0, np.na... |
4009561acf2044a0a81f6767725fd131faff3b8a2cbcaa58314bc0994f4fa591 | Python | 1,591 | 48 | from .data import RawData
class Sample():
"""
Representation of a MS sample contain in an experiment.
Contains, peak and feature lists, raw_data object to store raw file and connect to appropriate backend reader.
"""
# Sample counter to automatically assign sample ids
sample_counter = 0
... |
8026a7b3619617013565c77fd164e9ababde75bcd80db45d63688a1a9f3d2ad5 | Python | 1,592 | 57 | import torch
import torch.nn as nn
import torch.nn.functional as F
from darts.api import Model
class MixedLayer(Model):
""" A mixture of 8 unit types
We use weights to aggregate these outputs while training.
and softmax to select the strongest edges while inference.
"""
def __init__(self, c, str... |
b2ab3cc607be7e6e9014314b889fb358833ce5c1ef33de40bd55f6399d3b87ed | Python | 1,592 | 48 | import hashlib
import torch
import torch.nn as nn
import torch.nn.functional as F
class Model(nn.Module):
""" Class representing sampleable neural network model """
def num_params(self):
""" Get the number of model parameters. """
return sum(p.numel() for p in self.parameters())
def sum... |
685eee467f5d354abd4c0c38e65d14f0c18b1b2e4f312528610e9a32d4670ce1 | Python | 1,593 | 64 | from importlib.metadata import version
from .dataio.data_factory import (
fetch_example_correlation_matrix,
load_fcon1000,
load_lnm,
)
from .dataio.norm_data import NormData
from .longitudinal import CorrelationMatrix, VelocityModel, ZDiffScore
from .math_functions.basis_function import (
BsplineBasisF... |
850c7960b0eee06d12c81227f8091fb1e37cbba48eb52752640a60b108a68977 | Python | 1,593 | 69 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Wed Jul 5 11:47:43 2023
@author: Noelia Martínez-Molina
"""
from numpy import genfromtxt
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.style as style
import seaborn as sns
import pandas as pd
#PLOT INFORMATION ENCODING CAPABILIT... |
c0c954922b5259651980c71ad2fac88cbba6e25ab68209f0d93ef8b2a5cbd589 | Python | 1,593 | 33 | # Copyright 2019 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... |
9ccecb71a3b59a941677f8002c51e3dc50e14274d841279841ad1b3c31131672 | Python | 1,594 | 54 | #!/usr/bin/env python
"""The setup script."""
import pathlib
from setuptools import find_packages, setup
def read_requirements(file_path):
with open(file_path, "r") as f:
requirements = f.read().splitlines()
return requirements
requirements = read_requirements("requirements.txt")
setup_requirements... |
d132912ff1dcdff9f13a2e29ce9eec1caf48ed561c72132feb966dcfeda9c3a6 | Python | 1,594 | 47 | import subprocess
# brand-specific exceptions
class GraphError(Exception):
def __init__(self, message='', graph=''):
super().__init__(message)
self.graph = graph
def __repr__(self):
return f"GraphError(message={str(self)}, graph={self.graph})"
class NodeError(Exception):
def _... |
88485e9ffe6cd560440c638a78060c95eed25a91b7dc77abb59cfe2ce5f4ac1e | Python | 1,598 | 56 | """
Check that doc/source/reference/testing.rst documents
all exceptions and warnings in pandas/errors/__init__.py.
This is meant to be run as a pre-commit hook - to run it manually, you can do:
pre-commit run pandas-errors-documented --all-files
"""
from __future__ import annotations
import argparse
import ast... |
8e14152688273ef93b81c2f334025b0ba3df7963bc6a646b63ccca699bc45dc7 | Python | 1,598 | 59 | """
Entrypoint for testing from the top-level namespace.
"""
from __future__ import annotations
import os
import sys
from pandas.compat._optional import import_optional_dependency
from pandas.util._decorators import set_module
PKG = os.path.dirname(os.path.dirname(__file__))
@set_module("pandas")
def test(extra_a... |
929c84a020747a674962b5d56a7199ec334acd2036c24b0e1f6975931f5b4d2d | Python | 1,598 | 47 | """
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 torch
import torch.nn.functional as F
class Act(torch.nn.Module):
def __init__(self, act, slope=0.05):
super(Act, self).... |
c9b11a8fe5f8ffb05f398e54bbf410f504ce55d6c310f5d273ba3c890f104778 | Python | 1,598 | 51 | from functools import partial
from fastai.distributed import *
import importlib
import json
from fastai.learner import Learner
from fastai.optimizer import Adam
import torch
import accelerate
from pathlib import Path
#use the parameter json to create the learner
def json_to_learner(json_input):
set_seed(json_inpu... |
14cf4b6a3e59d889483f102f214f1164004ab33ab3aa63ec6a146dfcd6a729db | Python | 1,599 | 61 | import warnings
import config
import numpy as np
from tensorflow.keras.models import model_from_json
from utils import change_output
warnings.filterwarnings("ignore")
__all__ = ["change_output", "decrypt_file", "decrypt_oh"]
def decrypt_file(file, net_list):
net_list = np.load(net_list)
dec_count = 0
w... |
d41fa3c2102762bdea73b6d48f191a9a1fd63983ed4d0ce49e6d1a9eb5280d02 | Python | 1,599 | 70 | """
Timedelta benchmarks that rely only on tslibs. See benchmarks.timedeltas for
Timedelta benchmarks that rely on other parts of pandas.
"""
import datetime
import numpy as np
from pandas import Timedelta
class TimedeltaConstructor:
def setup(self):
self.nptimedelta64 = np.timedelta64(3600, "s")
... |
b52bad54b20ff103d849d5efc8566a6ff659b510a1ddd53f9fd61dcaf03b78a2 | Python | 1,601 | 38 | #Run sweeps over number of fields
import numpy as np
from placerg.funcs import *
from placerg.funcsrg import *
from placerg.objects import *
from placerg.runfunc import *
N0 = 2048 # number of cells
N = 512 # number of cells after removing silent ones
percell= 1.0 # probability that each field is accepted
phi=1.0 #... |
b58f68a806ab61fda8f33124d139f4fb6985ee4644ff7ac3f9d32523840d210a | Python | 1,601 | 51 | # Copyright 2019 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... |
487496080427a6594c97ae2735e68a77752b9aa391c0e3f0730321e3e52c6068 | Python | 1,602 | 55 | from __future__ import annotations
from functools import reduce
from typing import (
TYPE_CHECKING,
Any,
)
import numpy as np
from pandas._config.config import _global_config as config
if TYPE_CHECKING:
from pandas._typing import DtypeObj
def ensure_decoded(s: str | bytes) -> str:
"""
If we ha... |
98a3deed9d759f7abd0dc9344350eedbc3fefab6ef9c02ce65b5dc616f6e973d | Python | 1,602 | 55 | """
Series.item method, mainly testing that we get python scalars as opposed to
numpy scalars.
"""
import pytest
import pandas as pd
class TestItem:
def test_item(self):
# We are testing that we get python scalars as opposed to numpy scalars
ser = pd.Series([1])
result = ser.item()
... |
af0ae4cb6011a4349be6fe1c70b53eea447cf4596df912707395a4e7bd637737 | Python | 1,602 | 57 | # Copyright 2018-2021 Xanadu Quantum Technologies 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... |
1dcd4433eed0de528b99240c86e61b45a16c8d27dbb328828972b0ab49ca169a | Python | 1,603 | 32 | # Copyright (c) 2018-2023, NVIDIA Corporation
# All rights reserved.
#
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are met:
#
# 1. Redistributions of source code must retain the above copyright notice, this
# list of condit... |
a15aae9d90323bc0b85ee449d6cfc0dc8ba1ad59804dd46e238fc65609c2a999 | Python | 1,603 | 56 | # Copyright 2018-2022 Xanadu Quantum Technologies 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... |
c6bafe459830ccda68fa1ba89a438383df2d9942f90ed07da6b020b9b29df968 | Python | 1,604 | 55 | """
vegas example from the Basic Integrals section
of the Tutorial and Overview section of the
vegas documentation.
"""
from __future__ import print_function # makes this work for python2 and 3
import vegas
import math
import numpy
import sys
if sys.argv[1:]:
SHOW_GRID = eval(sys.argv[1]) # display picture o... |
5d48e87799fdc12b591d0ee306491e70ebba5a600dbd6cbdc4bfde7ede836e13 | Python | 1,606 | 51 | from functools import partial
from fastai.distributed import *
import importlib
import json
from fastai.learner import Learner
from fastai.optimizer import Adam
import torch
import accelerate
from pathlib import Path
#use the parameter json to create the learner
def json_to_learner(json_input):
set_seed(json_inpu... |
751815666a536577e88705c689161279e2985d001e087b75b008546931c3e7a4 | Python | 1,606 | 43 | """Public parser imports in fresh interpreters, including stream-first loading."""
import os
import subprocess
import sys
import pytest
from conftest import macs3_env
@pytest.mark.parametrize('first', ['MACS3.IO.Parser', 'MACS3.IO.BAMStream'])
def test_public_parser_imports_in_fresh_process(tmp_path, first):
s... |
8fddc71deb5e9afe8f7da7f0ca660f08d7f236a539422e488ac098d41df50c40 | Python | 1,606 | 62 | # -*- coding: utf-8 -*-
import warnings
from functools import wraps
import numpy as np
__all__ = ["sample_ball", "deprecated", "deprecation_warning"]
def deprecation_warning(msg):
warnings.warn(msg, category=DeprecationWarning, stacklevel=2)
def deprecated(alternate):
def wrapper(func, alternate=alternat... |
47d992f8cb5e492f00bde6075b0a01838d97f01da9d50c89fc72d45ed72468d1 | Python | 1,607 | 45 | # -*- coding: utf-8 -*-
import numpy as np
__all__ = ["Move"]
class Move(object):
def tune(self, state, accepted):
pass
def update(self, old_state, new_state, accepted, subset=None):
"""Update a given subset of the ensemble with an accepted proposal
Args:
coords: The or... |
b826cf6add064fea8e29a5aa70e3f3c62a234f844e05dca0519b4e368f424360 | Python | 1,607 | 47 | #!/usr/bin/env python
__version__ = '1.0'
import os, sys
from Bio.Seq import Seq
from Bio import SeqIO
import coordinate_mapper as sp
import BioReaders
###### MODIFY FILENAME BELOW #######
#genome_file = 'hg38.fa'
#sam_file = 'alz.rep.fq.sam'
#sam_file = 'isoseq_flnc.fasta.sam'
#output_err_corrected_fasta = 'alz.re... |
bbad5e9408a63a729ed848ccd0ceb8f1eee23cb9d4edf1fd3f8d28e53f890078 | Python | 1,608 | 58 | from abc import ABCMeta, abstractmethod
import os
class BasicAnalysisProcess:
def __init__(self) -> None:
pass
@abstractmethod
def initial(self, controller=None, config=None, streaming=None, messenager=None):
# 3 essentials: controller, config, and data streaming client
... |
38a2aeefa8556f55d36511c8199f4ad4840ab5ac019ab639be070443d0625365 | Python | 1,609 | 41 | from sys import path as sys_path
sys_path.append('..')
sys_path.append('../base')
import os
import matplotlib
if 'DISPLAY' in os.environ:
matplotlib.use('qt5Agg')
else:
matplotlib.use("Agg")
import matplotlib.pyplot as plt
from base import loggingUtils
from base.surfaces import Surface
from base.kernelFunctions... |
9e988883cd4658efdcb595994ae51d1afc63b5d3a2362625d6f263ab032e59e5 | Python | 1,609 | 66 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Fri Oct 27 09:53:30 2023
@author: nrq2
"""
print("load libraries")
import os
import scenicplus
import scanpy
import pycisTopic
## 1. Initialize cisTopic object
from pycisTopic.cistopic_class import *
from pycisTopic.utils import *
from pycisTopic.lda_models... |
c7c9785c0a84e374c6e2a3a192ecf926eaff5596c412c7cbceae544ad86f0b27 | Python | 1,609 | 54 | #!/usr/bin/env python
import argparse
import pandas as pd
# Create a parser
parser = argparse.ArgumentParser(description="Parameters for Demuxmix")
parser.add_argument("--path_hto", help="cell hashing path, filtered HTO matrix")
parser.add_argument(
"--hto_name_gmm",
help="a list of sample tags (HTOs) separate... |
6dee02970ea9304f18824338841a520a11c098db5c4c4ebecfc91104e1d44d51 | Python | 1,610 | 48 | """There are three configurable things: predictors/models, data, training/evaluation.
Only first two require factories.
"""
import os
import torch
import logging
from progres.chainsaw.src.domain_chop import PairwiseDomainPredictor
from progres.chainsaw.src.models.rosetta import trRosettaNetwork
from progres.chainsa... |
e3397759b05bc01f5ed82f87ba058e6d577f8a81c8b2026fc91f365864681b6c | Python | 1,610 | 36 | from Common import loggingUtils
from Curves.curves import *
from Common.kernelFunctions import *
from Curves.curveMultiPhase import *
def compute():
outputDir='/Users/younes/Development/Results/atlasSections49'
if __name__ == "__main__":
loggingUtils.setup_default_logging(outputDir, fileName='info')
... |
3869c83003c26d71632e30bf62841aac32f9ff15e2a2536e1d130314a630264a | Python | 1,612 | 49 | import os
import shutil
import numpy as np
import cv2
# Generic function to combine two images
def combine_images (img_fold_A, img_fold_B, img_fold_AB):
img_fold_A = os.path.expanduser(img_fold_A)
img_fold_B = os.path.expanduser(img_fold_B)
img_fold_AB = os.path.expanduser(img_fold_AB)
# Setup a c... |
b742efcde3283bf4e96c1601f3f8526b6d0e2987218b727d69052fd2bba2c14b | Python | 1,612 | 48 | #####################################################################################################################
# Date created : 10/21/2022
# Date modified: 10/21/2022
# Purpose : To extract feature from DSSP file
############################################################################################... |
e4b6d14e3cbf4641dd1255018e0aed603bebdeb4002e78ecddd3a3f7ea09a23f | Python | 1,613 | 61 | import sys
srcPath, origPath = sys.argv[1:3]
punc = ["-LRB-", "-RRB-", ",", "-", ";", ":", "\'", "\'\'", '\"', "`", "``", ".", "!", "?", "-RRB-", ",", "-", ";", ":", ".", "!", "?"]
def depuncWrd(wrd):
for p in punc:
wrd = wrd.replace(p, '')
return wrd
with open(srcPath, 'rb') as f:
srcTokMeasure... |
f42712bd7a281ca02892de07fa7f1493d67c8646f6f610c1b710e8d81525b768 | Python | 1,613 | 52 | import numpy as np
import itertools
from functools import partial
from .utils import np_scatter
permute_2 = partial(itertools.permutations, r=2)
def line_graph(edge_index_G):
"""Return the (angular) line graph of the input graph.
Args:
edge_index_G (ndarray): Input graph in COO format.
"""
sr... |
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