sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
78d984305d88bd9a87affe491f95cb766e3f285130e5ba59f122468d03822024 | Python | 7,471 | 156 | import os
import numpy as np
import sys
''' SCRIPT USED TO ANALYSE AND PLOT RAW DATA FROM THE AUDITORY HUMAN PWM TASK '''
''' PRODUCES FIGURES IN THE MANUSCRIPT BOBOEVA ET AL 2023 PUBLISHED IN ELIFE'''
# ''' COMPUTE PERFORMANCE OF ALL/INDIVIDUAL SUBJECTS AND PLOTTING FRACTION CLASSIFIED '''
# ''' PRODUCES FIG 7A and ... |
0a1b21b81e85cf92eb40cd9056e3acea94522d35c70897f0ca70515095587f01 | Python | 7,473 | 152 | import os
from unittest import TestCase, mock
import pandas as pd
import dynast.preprocessing.bam as bam
import dynast.utils as utils
from .. import mixins
class TestBam(mixins.TestMixin, TestCase):
@classmethod
def setUpClass(cls):
super(TestBam, cls).setUpClass()
cls.gene_infos = utils.r... |
0fd3010c4a1a9df409344185b43bceda94feb636b125abed711c2282f3c8bedd | Python | 7,474 | 166 | from skimage import measure
from math import ceil,floor
from Parameter import *
from Environment import *
def BrainImage_cat(BrainImage_root,Save_root,flip=True, slices=75):
x = 2500
y = 3500
if not os.path.exists(Save_root):
os.mkdir(Save_root)
brainimage_list = os.listdir(BrainImage_root)
... |
b8851ff01c72bd7473b86e4a9d7e107d2928b5dc68cb00d3b559b974e710c28f | Python | 7,477 | 235 | """Tests for CorrelationMatrix."""
from __future__ import annotations
import warnings
from pathlib import Path
import numpy as np
import pytest
from pcntoolkit import CorrelationMatrix
from test.test_longitudinal.conftest import make_cross_sectional_norm_data
# A valid CSV with full-precision values, as another us... |
adbab235d24f509b865c9640e25e8a38a2a3d7eb3f18ed80870d50e7081c0c38 | Python | 7,481 | 236 | # Copyright 2018-2020 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... |
abda6914a2e051ffc6aa0ac8334dbc647f62ea2fd8f669b83b4bfc95db4cea29 | Python | 7,482 | 216 | from scipy.sparse import coo_matrix
import numpy as np
from scipy.ndimage import gaussian_filter
import torch
from kilosort import spikedetect
def bin_spikes(ops, st):
""" for each batch, the spikes in that batch are binned to a 2D matrix by amplitude and depth
"""
# the bin edges are based on min and max... |
ab6ec516d85d5103973a9225ebf70a62fb9a303b16e554e852f3025eb0c22f05 | Python | 7,483 | 197 | import numpy as np
import pytest
import pandas as pd
import pandas._testing as tm
def _isnan(val):
try:
return val is not pd.NA and np.isnan(val)
except TypeError:
return False
def _equivalent_na(dtype, null):
if dtype.na_value is pd.NA and null is pd.NA:
return True
elif _i... |
a3db56e1b62143f219d8547136601e79a58e147a6a1942164043b3f0cf9195f8 | Python | 7,485 | 232 | #!/usr/bin/env python3
# /// script
# requires-python = ">=3.11"
# dependencies = [ "packaging", "dependency-groups" ]
# ///
"""Parse a pyproject.toml file and output a list of minimum dependency versions."""
from __future__ import annotations
import argparse
import sys
import tomllib
from collections import deque
fr... |
5d0bc92f3a5e50f1fdf07f546a69e603704ce019b54ba25ae558b8716eb8be12 | Python | 7,486 | 176 | # Filename: file_handlers.py
# Author: Alessandro Gerada
# Date: 2023-08-11
# Copyright: Alessandro Gerada 2023
# Email: alessandro.gerada@liverpool.ac.uk
"""Functions to facilitate working with image data files"""
import pathlib
from pathlib import Path
from aigarmic._img_utils import convert_cv2_to_keras
impo... |
9d5c79dfeca395d05d70dba9cf1d8ee02d01a25ac16d27940804d288fa8d6aa5 | Python | 7,486 | 207 | import numbers
import importlib.resources
import dclab
import numpy as np
from PyQt6 import uic, QtCore, QtWidgets
from ... import meta_tool
class MetaPanel(QtWidgets.QWidget):
def __init__(self, *args, **kwargs):
super(MetaPanel, self).__init__(*args, **kwargs)
ref = importlib.resources.files(
... |
220d8ed23a6a5d1cc28c3a64f30a58c2cdf02bbbe2924bd67b00b443c312f37b | Python | 7,487 | 131 | from os import path
import glob
import argparse
import numpy as np
from .base import pointSets, surfaces
from .base.affineRegistration import rigidRegistration, saveRigid
def main():
parser = argparse.ArgumentParser(description='runs rigid registration over directories (relative to the first left surface)')
p... |
2402cbb3bee2bf4578c3e49e7d46551ea52d7cb8877820f4cbcc8777ccdbcfca | Python | 7,489 | 231 | from typing import Iterable, List, Literal, Optional, Sequence, Tuple, Union
import numpy as np
import pandas as pd
import seaborn as sns
from anndata import AnnData
from matplotlib import pyplot as plt
from scipy.sparse import lil_matrix
from tqdm import tqdm
def GWAS(
data: pd.DataFrame,
chr_name: list = [... |
22648258fdd6d1e02cc47c66c519d1b0af0b9fe05925c1947efff270c3ffb039 | Python | 7,490 | 212 | """Plot endpoint integration tests (session 53).
Exercises:
- ``GET /api/v1/plots/registry`` — discoverability of plot kinds.
- Authenticated 404 paths for run-bound plots when there's no promoted
pipeline / unknown task.
- ``GET /api/v1/datasets/{ds}/plots/eda/{kind}`` end-to-end on a real
CSV upload (covers cor... |
302995e71d8fc9e2e2c8db1e71283822cc350d4eeafec214ea9018763b5c5e36 | Python | 7,496 | 236 | #-----------------------------------------------------------------------------
# Pharamcophore based SASA for complex (Author: Cheng Wang)
#-----------------------------------------------------------------------------
import os, sys, pybel
import numpy as np
import pandas as pd
from .pharma import pharma
def runMSMS(i... |
85e7f87010db1b1eb446962a732e42495bc36eda19f48602af15bc3785776c16 | Python | 7,499 | 158 | from Environment import *
from Parameter import *
def get_density_csv(region_path, counts_csv, region_color, save_csv):
'''cell counts/region pixel nums'''
region_name = list(region_color.keys())
file = open(os.path.join(counts_csv, 'cortex_cells_counts.csv'))
df = pd.read_csv(file)
counts = df['SU... |
4aa9d441c7e270ad1de14c0b2504619d3e0cfa9f3202c566bbb8b0415947804b | Python | 7,500 | 183 | #!/usr/bin/env python3
"""Generate somo.saxs_atoms rows from authoritative sources.
Sources (downloaded into data/ref/):
* it1992.cpp - cctbx transcription of International Tables Vol. C, Table 6.1.1.4
(Cromer-Mann 4-Gaussian). THIS is the form SOMO production uses.
* f0_WaasKirf.dat... |
cf127c6cc6ff30188c228629226dd7e3a719492bb03ca079b92da1e25fe1f450 | Python | 7,500 | 195 | import torch
import torch.nn as nn
from torch.nn.utils.parametrizations import spectral_norm
from torch.utils.data import DataLoader
import pytorch_lightning as pl
from rgan.rgan import Generator, Discriminator
class NoiseGenerator(nn.Module):
def __init__(self, noise_scale):
super().__init__()
... |
ea13ba19bff010a3066e0b93efb91d8639ac33f9e6bc5178a129296dcea138b7 | Python | 7,501 | 146 | #! /usr/bin/env python
import argparse
from plastid.readers.bed import BED_Reader
from plastid.genomics.roitools import SegmentChain, positionlist_to_segments
from collections import defaultdict
import os
import sys
from time import strftime
parser = argparse.ArgumentParser(description='Identify overlapping transcrip... |
9fb8f4b662ebdbbee81c67fc1479c7537c29e5acb01a23bcc8a0c3e94b10fa49 | Python | 7,502 | 182 | from tensorflow import keras
from keras import datasets, layers, models
from keras.models import load_model, save_model, Model
from tensorflow.keras.layers import Input, Conv2D, MaxPooling2D, Flatten, LSTM, Dense, TimeDistributed, BatchNormalization, Dropout, Activation, add, AveragePooling2D
import tensorflow as... |
205132429e61072061ce99ceb78822c23b8a15566c254ba7d086c3c4f08db805 | Python | 7,503 | 184 | """Session 26 — god-class drain: ``compare_models`` (supervised path).
Supervised ``SupervisedExperiment.compare_models`` no longer delegates to
``self._legacy.compare_models``. It iterates the engine's model registry,
calls the (already-drained) ``self.create_model`` for each entry, and
assembles the leaderboard from... |
1699d4a57e2fbd8db4a3cf455a593ba435b4d458358c3f7983603a13f9343e16 | Python | 7,504 | 197 | from datetime import datetime
import numpy as np
import pytest
import pandas as pd
import pandas._testing as tm
class TestToTimestamp:
def test_to_timestamp_non_contiguous(self):
# GH#44100
dti = pd.date_range("2021-10-18", periods=9, freq="D", unit="ns")
pi = dti.to_period()
re... |
85153c4b42a52d694b4abadfa6338c837538869ce8809c62e10f50c92c1690cc | Python | 7,505 | 220 | # Copyright 2018-2025 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... |
05d0f10fb371f213e6e087bbd19cf67ec0707809e6c76d7a2b5983a0734f0423 | Python | 7,510 | 205 | """Automated annotation of Cognitive Atlas labels."""
import logging
import re
import numpy as np
import pandas as pd
from .. import references
from ..due import due
from ..extract import download_cognitive_atlas
from ..utils import _uk_to_us
from . import utils
LGR = logging.getLogger(__name__)
@due.dcite(referen... |
db4b40bb3c309144acacc815e5fab8833a00c629df3f98810da12e68ee304982 | Python | 7,513 | 192 | """Differentiable Minimization."""
import functools
from collections.abc import Callable
from typing import TYPE_CHECKING, cast
import torch
from typing_extensions import Any, TypeVar, TypeVarTuple, Unpack
from mrpro.algorithms.optimizers.cg import cg
from mrpro.algorithms.optimizers.lbfgs import lbfgs
from mrpro.op... |
40ed9ff8c39eac032decf1a35e4d7cf36c32f82e433d0964a006d6b8a2ad2ee1 | Python | 7,515 | 234 | import re
import numpy as np
import pytest
import pandas as pd
import pandas._testing as tm
@pytest.fixture
def left():
return pd.DataFrame({"key": ["a", "c", "e"], "lvalue": [1, 2.0, 3]})
@pytest.fixture
def right():
return pd.DataFrame({"key": ["b", "c", "d", "f"], "rvalue": [1, 2, 3.0, 4]})
class Tes... |
d6c360b0319c07c969cda9533d2d408c475ab967238af5a3bbbf921ff3bc02de | Python | 7,516 | 131 | """
Created on Sept 2019
@author: Alice Geminiani - alice.geminiani@unipv.it
olivocerebellar spiking neural network with E-GLIF neurons and PLASTICITY, for classical eyeblink conditioning simulations
Publication: Geminiani et al., biorXiv, 2022 - doi: https://doi.org/10.1101/2023.06.20.545667
NEST CEBC simulat... |
0266d0387b494903e994396472d327b31f74f4e300893c28537b63cd994c6001 | Python | 7,522 | 187 | #!/usr/bin/env python
import os, sys
from csv import DictReader, DictWriter
from collections import Counter, defaultdict
from Bio.Seq import Seq
def read_dropseq_clean_report(report_filename):
"""
EXAMPLE
# FILTER_AMBIGUOUS=true
# MIN_UMIS_PER_CELL=20
# UMI_BIAS_THRESHOLD=20
# EDIT_DISTANCE=20
... |
b12807164cec891cc815f7c97d58e76c3bec33ea96b8e908b2cc4e122533bf0e | Python | 7,522 | 160 | # 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... |
5ed792eec6c8de73303eedea85e11f1396b5c0a0a0eed501806c54931cd656e4 | Python | 7,523 | 200 | # 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... |
1a7efe77594a2aefd8b3af2f1db8b16a1815d0f682f5014212cca2c26c57ef28 | Python | 7,526 | 156 | """add prediction_logs, trials, and model_library
Revision ID: a1b2c3d4e5f6
Revises: 0cd9d5ea2e17
Create Date: 2026-05-08 12:00:00.000000+00:00
Session 22: control plane progress.
- ``prediction_logs`` — append-only log of every served prediction. Powers
drift detection, latency forensics, audit.
- ``trials`` — fi... |
70cfa355fdbf1dacca02060bc544f4cdc6b70c8261d996ccf684589e314fc5cd | Python | 7,529 | 200 | import numpy as np
import ants as an
from pathlib import Path
from deepbrain import Extractor
from scipy.stats import pearsonr
'''
Functions for fast preprocessing of anatomical images
'''
def extract_brain(image):
'''
Brain Extraction
Parameters
----------
image: ANTs image objec... |
822e71d904164b0ae6d25818a0482cd0aed8eeab8369d6c053ded725089d1667 | Python | 7,530 | 127 | from botocore.client import Config
import ibm_boto3
from io import StringIO
import types
import os
import pandas as pd
import sys
import json
sys.path.append(os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
sys.path.append(os.path.abspath(os.path.join(os.path.dirname(__file__), "..", "..")))
from config.glo... |
ce2c9de4212aa5d68f947aaee51979503b27959f7ca34b6117bd5c1c4c281ed9 | Python | 7,530 | 260 | import numpy as np
import matplotlib.pyplot as plt
# increase the figure size
plt.rcParams["figure.figsize"] = [12, 10]
# remove the top and right spines from plot in the global plt setting
plt.rcParams["axes.spines.top"] = False
plt.rcParams["axes.spines.right"] = False
# change the linewidth of the axes and spines
... |
537be6f2cdd1dab36fde3de7167eb2cf38d5bbfba2e35f62a7dd942b22b537d8 | Python | 7,533 | 203 | from pathlib import Path
import kCSD2D_reconstruction_from_npx as npx
import matplotlib.pyplot as plt
import matplotlib.cm as cm
import scipy
import numpy as np
from numpy.linalg import LinAlgError
from scipy.signal import filtfilt, butter
import DemoReadSGLXData.readSGLX as readSGLX
def set_axis(ax, x, y, letter=None... |
894f2dbd649b931f55362b89bdd91434501374638aaee17d77b11edf6cb6ca3b | Python | 7,536 | 300 | # 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... |
3b7229c6c1bc7c9963e50726aefa0347b52bfb7656db81a27b3c46f1ea874083 | Python | 7,542 | 185 | """3D CNN model builders ported from `Training.ipynb` (see
`docs/legacy-notebooks-inventory.md`, "`Training.ipynb`" section).
The notebook defines four near-identical Keras functional models
(`get_3d_model`, `get_3d_frozen`, `get_3d_x`, `get_3d_y`) that differ only in
which layers are frozen (`trainable=False`) and wh... |
3fcbaf5e16a6103f0063e05a7bac1260ef4f6859b018d8192968f174ca38667b | Python | 7,544 | 184 | # Copyright 2018-2024 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... |
eeccdf9c967c10dfb40ea3f6b75f732f902fef3e58fcb45e63f34c93951a22ba | Python | 7,544 | 196 | import torch.nn as nn
import torch.nn.functional as F
import torch
from dredda.functions import ReverseLayerF
from collections import OrderedDict
class FCModelDualBranchAE(nn.Module):
"""
The main model for domain adaptation. This model is a dual-branch autoencoder with a feature extractor, a task classifier,... |
542e61c957773cdaa0014f15159251048c2d5dff69b7e7e89bb98633f26952c2 | Python | 7,545 | 161 | """OrganAge parity against the authors' R scoring expressions and fold-one CSVs."""
import gzip
import hashlib
import importlib
import importlib.util
import json
from pathlib import Path
import numpy as np
import pytest
import torch
FIXTURES = Path(__file__).resolve().parents[1] / "data" / "organage"
def test_orga... |
6aa9e41301b5d72d0e8f42d666a234c5884c17a37c5df49efdb03e6c7a8561b3 | Python | 7,552 | 207 | #! /usr/bin/env python
##############################################################################
## DendroPy Phylogenetic Computing Library.
##
## Copyright 2010-2015 Jeet Sukumaran and Mark T. Holder.
## All rights reserved.
##
## See "LICENSE.rst" for terms and conditions of usage.
##
## If you use this wo... |
275e2e3f107063110a61e3cb02620c6c20602f96b318d7a00ac27b341907d31e | Python | 7,554 | 243 | import numpy as np
import matplotlib.pyplot as plt
# increase the figure size
plt.rcParams["figure.figsize"] = [12, 10]
# remove the top and right spines from plot in the global plt setting
plt.rcParams["axes.spines.top"] = False
plt.rcParams["axes.spines.right"] = False
# change the linewidth of the axes and spines
... |
c232299c7730f17c4955950086a5421ecd1cb0a31864b4447cd91b6b757f04c9 | Python | 7,554 | 226 | # -*- coding: utf-8 -*-
"""
---------------------------------------------------
Created on Wed Oct 13 01:42:09 2021
@author: Amin Tanhadoust,
E-mail : amin[dot]tanhadoust[at]gmail[dot]com
https://scholar.google.com/citations?user=_LaQzv8AAAAJ
https://tanhadoust.com
--------------------------------------------... |
7e87dad30a87e98e1dc1d0d3d610dc685d8ee51fec085e1e2a3d615d3d6a01d3 | Python | 7,556 | 227 | """
Module for formatting output data in console (to string).
"""
from __future__ import annotations
from shutil import get_terminal_size
from typing import TYPE_CHECKING
import numpy as np
from pandas.io.formats.printing import pprint_thing
if TYPE_CHECKING:
from collections.abc import Iterable
from pand... |
d30dd42c3499cc7ab730f33a0928985c0bb8924940fa76fc620626db559fa7a6 | Python | 7,558 | 169 | # -*- coding: utf-8 -*-
"""
DICOM conversion to Slicer-compatible NRRD, using dcm2niix
"""
import logging
logger = logging.getLogger(__name__)
import os
import shlex
from subprocess import Popen, PIPE
from .inout import split_filename, read_image_sitk, write_image_sitk
from app.utils import end_execution, wrap_string... |
2aea0cf14fcd33ae92ad35f0e04b53d2573645972cdcf67735ba840045d7ad4b | Python | 7,562 | 123 | from botocore.client import Config
import ibm_boto3
import re
import os
import sys
import json
sys.path.append(os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
sys.path.append(os.path.abspath(os.path.join(os.path.dirname(__file__), "..", "..")))
from config.globals import ENVIRONMENT
from app import create_... |
2bbb59a07863744162d7678e317a35143600f3ffba456a770da39aeead615fcb | Python | 7,562 | 208 | from driver import compute
from values import *
from defs import *
import electrochemical
import water
import glucose
import cotransport
import NHE3
import ATPase
import NKCC
import KCC
import NCC
import ENaC
import Pendrin
import AE1
import NHE1
import flux
import os
import sys
import argparse
import multiprocessing
... |
03edf3bfb96cbf6054e42502e07c95f50c9906aeecb341fa9b20a22aa887098d | Python | 7,564 | 210 | ''' get_em_annotations.py
Get EM annotations from Raw and Split-GAL4 databases and dump to an Excel file
'''
import argparse
import collections
from operator import attrgetter
import sys
from time import strftime
import pandas as pd
from tqdm import tqdm
import jrc_common.jrc_common as JRC
#pylint:disable=broad-e... |
570e8d9795e9d2e9bdaad20e775d71c4ec8017b754b9798133c9bd51aabe47fe | Python | 7,566 | 228 | #!$HOME/.pyenv/shims/python
# coding: utf-8
import os
if 'PYTHONPATH' not in os.environ:
print("Error: Run `source env.sh` to be able to run `/scripts/*.py`")
exit(1)
from collections import defaultdict
from pathlib import Path
from typing import Tuple
from time import time, sleep
import cv2
import matplotli... |
7b3fceebaca6d9e45a9c04794b14ddd59f4855acdd27b7591312dcf12d796db5 | Python | 7,566 | 285 | # -*- coding: utf-8 -*-
"""
Created on Tue Mar 8 14:31:15 2022
@author: System 6
"""
import numpy as np
import pycromanager_tessie as pmt
from pycromanager_tessie.acquisitions import experiment
# Start platform:
platform = pmt.microscope.platform.Platform(load_synchronizer=True)
# Set LED ring
platform.neopixel.c... |
5334525f7f8a36de37983592826f82766a35b2fa04484a4b5f43ff0ab122e4e3 | Python | 7,568 | 179 | #
# This file computes the atomic spherical coordinates in a given set of
# neighborhoods and outputs a file with these coordinates.
#
# It takes as arguments:
# - The name of the ouput file
# - Name of central residue dataset
# - Number of threads
# - The neighborhood radius
# - "easy" flag to include central res... |
0b6e0b28e4d172012b31db94c56568c4d426abbdacf2caeab6e03731773cbd18 | Python | 7,570 | 196 | # 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... |
4f3f12d5466a5249dd587014c96165872781b1d29e4b154f8a664fbe3f6f25c8 | Python | 7,570 | 178 | # --------------------------------------------------------
# Based on BEiT, timm, DINO and DeiT code bases
# https://github.com/microsoft/unilm/tree/master/beit
# https://github.com/rwightman/pytorch-image-models/tree/master/timm
# https://github.com/facebookresearch/deit
# https://github.com/facebookresearch/dino
# --... |
c1406b54b1cc3195d48ceffacbffed2fd24466cef5184badeb7c26c2bfd8e846 | Python | 7,574 | 254 | # 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... |
e818a396cef5ecda2bb803cf2de86a213d4b0426547ac1959dbdc164d13eef84 | Python | 7,581 | 223 | import numpy as np
from deepglyco.chem.common.elements import ElementCollection
from deepglyco.chem.gpep.fragments import GlycanFragmentTypeCollection
from deepglyco.chem.gpep.glycans import MonosaccharideCollection
from deepglyco.chem.pep.aminoacids import AminoAcidCollection
from deepglyco.chem.pep.fragments import ... |
1506aad58cc7dda519a9518b35184b06ea14d0204438e5dfaf3a5b57fd8a1996 | Python | 7,582 | 208 | import numpy as np
import torch
from torch.autograd import Variable
import torch.nn as nn
import torch.nn.functional as F
def get_socre(outputs):
nnOutputs = outputs.data.cpu()
nnOutputs = nnOutputs.numpy()
nnOutputs = nnOutputs - np.max(nnOutputs, axis=1, keepdims=True)
nnOutputs = np.exp(nnOutputs) /... |
3fb5455782b875d28a50ae52e8dc51b4643f35ea82568ec16c25841fb2a1495d | Python | 7,582 | 169 | # -*- coding: utf-8 -*-
"""
DICOM conversion to Slicer-compatible NRRD, using dcm2niix
"""
import logging
logger = logging.getLogger(__name__)
import os
import shlex
from subprocess import Popen, PIPE
from .inout import split_filename, read_image_sitk, write_image_sitk
from app.utils import end_execution, wrap_string... |
b4e17c7b5a6a3af07431d5404f304188dcfc3e3c9f559254d3dff4ce3dd8e236 | Python | 7,582 | 279 | """File compression/decompression functions.
"""
import bz2
import gzip
import io
import lzma
import os
from subprocess import Popen, PIPE
COMPRESSORS = {
".gz" : gzip,
".bz2" : bz2,
".xz" : lzma
}
"""Mapping of file extension to python compression library."""
class GzipWriter:
"""Wrapper for a proc... |
d49913dc663b4e7194d0eb5acd3fb0122000990cf246579d1f8c0797580ec5a9 | Python | 7,582 | 264 | # 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... |
b6f0901f34069aa2882c1837430ecc6c21a5eaed879daef06363bc1c3efa3b15 | Python | 7,583 | 203 | from datetime import datetime
import numpy as np
import pytest
from pandas.errors import OutOfBoundsDatetime
import pandas as pd
import pandas._testing as tm
class TestSeriesClip:
def test_clip(self, datetime_series):
val = datetime_series.median()
assert datetime_series.clip(lower=val).min() ... |
685a2148b74e06ab17c1eea42d39fe60d3f30b3686a52067ce412984e649b53f | Python | 7,590 | 179 | """Tests for computing the operator norm of linear operators."""
from math import prod, sqrt
import pytest
import torch
from mrpro.operators import EinsumOp, FastFourierOp, FiniteDifferenceOp
from mrpro.utils import RandomGenerator
def test_power_iteration_uses_stopping_criterion():
"""Test if the power iterati... |
e525e874ebf19518812ee72239f1f935653e1f202608943e26d4611481e776a1 | Python | 7,594 | 237 | import os
import time
from utils import getLogger, getEstimatingArg
from ioput import parseBedpeFiles, txt2jd, parseJdFile
from joblib import Parallel, delayed
import numpy as np
import pandas as pd
from plot import plotInterSelfCutFrag
from model_test import getIntSig, markIntSig
import shutil
global log
# checkOve... |
181dcef4a1fbc5aff2bd1c1bfbf8b2207d430158949fbb473fad373280d1b7da | Python | 7,596 | 243 | #! /usr/bin/env python
##############################################################################
## DendroPy Phylogenetic Computing Library.
##
## Copyright 2010-2015 Jeet Sukumaran and Mark T. Holder.
## All rights reserved.
##
## See "LICENSE.rst" for terms and conditions of usage.
##
## If you use this wo... |
f8c8378b66897823dc4e74a92711517bedf8a5c39e91ef8f7acc2a82ae93c191 | Python | 7,597 | 237 | import os
import time
from utils import getLogger, getEstimatingArg
from ioput import parseBedpeFiles, txt2jd, parseJdFile
from joblib import Parallel, delayed
import numpy as np
import pandas as pd
from plot import plotInterSelfCutFrag
from model_test import getIntSig, markIntSig
import shutil
global log
# checkOve... |
08ed077cbdb1b37adf17867a3d16322a2f8c136eae95f8d6633853cb0ef82e2d | Python | 7,598 | 269 | from yacs.config import CfgNode as CN
_C = CN()
# ---------------------------------------------------------------------------- #
# Model options
# ---------------------------------------------------------------------------- #
_C.MODEL = CN()
# Name of model
_C.MODEL.MODEL_NAME = ""
# Number of classes to predict, i... |
a7b758caa526130ece41f79bbe67114379ebc1cede75db801574877d091fdb04 | Python | 7,598 | 214 | # -*- coding: utf-8 -*-
"""Adaptive false discovery rate (FDR) procedures.
The procedures implemented here are:
abh - The adaptive linear step-up procedure, which is defined on page 494
in [1] and originally in [2]
lsu - The non-adaptive one-stage linear step-up procedure
orc - The 'Oracle' procedure, which is ... |
207721a879635e76141d6f05c1cf912386f463c3242c591245d1f9119a230c4f | Python | 7,599 | 186 | """Defaults contracts and public buffer/layout boundary regressions for #767."""
from dataclasses import FrozenInstanceError, fields, replace
import io
import subprocess
import sys
import pytest
from conftest import macs3_env
from MACS3.Utilities.Performance import DEFAULTS
from test_Parser_frag_eof import write_fra... |
21825d3744e7f795144e05807c28076c17cc9c276fb13fe58d98bf6d1ae877fc | Python | 7,604 | 165 | ################################################################
### Figure 1
###############################################################
################################################################
import numpy as np
from pyhdf.SD import SD, SDC ## to load experimental hd4 files
import matplotlib.pylab as plt
... |
5c0fc6db425ff42e3993a586fd78ce149e881a00bb6b9843370ff4b508d031e8 | Python | 7,609 | 179 | """PAC parity with pinned Kuo et al. R code, including the public input path."""
import importlib
import importlib.util
import json
from pathlib import Path
import numpy as np
import pandas as pd
import pytest
import torch
FIXTURES = Path(__file__).resolve().parents[1] / "data" / "proteoclock"
def _fixture_model()... |
5fc4c34b99eacbbe309ca77de1ed861849b3472b1c9d7991ec345249aa6ebac2 | Python | 7,611 | 146 | import math
import os
import random
import numpy as np
import pandas as pd
import os
import sys
sys.path.append("prepare_data")
root = os.getcwd()
def create_drp_dict(path_ic50,path_drug_id_name):
IC50table = pd.read_csv(path_ic50)
IC50table = IC50table.rename(columns={'0': 'cell_id'})
IC50table = IC50table... |
84654a58034dd696422a7336a23736ae85fd35717b13ab96f0aa866b680e930a | Python | 7,613 | 206 | # 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... |
0d9e3b3195fa2117845ea36fbe86bcb5f376273e2d79bb7d178ef669dc054abc | Python | 7,617 | 234 | """
@author: mkowalska
"""
import os
import numpy as np
from numpy.linalg import LinAlgError
import matplotlib.pyplot as plt
from figure_properties import *
import matplotlib.gridspec as gridspec
from kcsd import KCSD1D
import targeted_basis as tb
__abs_file__ = os.path.abspath(__file__)
def _html(r, g, b):
ret... |
258b4a4ac3b28e3d3a3c0535b683de8fb414f33ea3218364bbbc9cfaf85e3163 | Python | 7,617 | 200 | import importlib.resources
import dclab
from dclab.features.emodulus.viscosity import (
KNOWN_MEDIA, SAME_MEDIA, get_viscosity
)
import numpy as np
from PyQt6 import uic, QtCore, QtWidgets
from shapeout2.gui.analysis.ana_slot import SlotPanel
from shapeout2.gui.widgets import show_wait_cursor
class BulkActionE... |
7cef2ffb27ae7f5982384dbba30994b65f98009d7dfa17d9e5aea83afbec21fc | Python | 7,621 | 263 | # Copyright 2024 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... |
fe536053730602ef6855c5b493b3f5df7cb5a2ad0be6f1e8cb18ac71756d0f4d | Python | 7,621 | 214 | import numpy as np
import matplotlib.pyplot as plt, matplotlib.gridspec as gridspec
import matplotlib.ticker
c_in_wt = "C0"
c_not_in_wt = "C1"
c_wt = "C2"
c_unc31 = "C9"
def make_alphacolorbar(cax,vmin,vmax,tickstep,
alphamin,alphamax,nalphaticks,
cmap="viridis",bg_gray=0... |
19792b320b7a3576aed1923c18c91494ee5300bf48cc0c773803b9486db0e052 | Python | 7,626 | 210 | import numpy as np
import pytest
from pandas.errors import Pandas4Warning
import pandas as pd
import pandas._testing as tm
class TestAstype:
@pytest.mark.parametrize("cls", [pd.Categorical, pd.CategoricalIndex])
@pytest.mark.parametrize("values", [[1, np.nan], [pd.Timestamp("2000"), pd.NaT]])
def test_a... |
4293c36dceb02ec3423fe5ebcbbea25fe3b1a1033fdc0762c3b4899963227ba2 | Python | 7,631 | 231 | """
Note: for naming purposes, most tests are title with as e.g. "test_nlargest_foo"
but are implicitly also testing nsmallest_foo.
"""
from string import ascii_lowercase
import numpy as np
import pytest
import pandas as pd
import pandas._testing as tm
@pytest.fixture
def df_main_dtypes():
return pd.DataFrame(... |
0991ef7308137b33e01871696eb0f0c61d974cf30eca25d9ed2a0e94e60bd8b5 | Python | 7,632 | 179 | import pysam
import os
def overlap_svision_pro_with_others(input_vcf, output_path, trio):
other_call_path = {
"sniffles2": "/mnt/d/workspace/svision-pro/real_trio/sniffles2.{}.s10.vcf".format(trio),
"svision_jasmine": "/mnt/d/workspace/svision-pro/real_trio/supp10_supp2/svision_jasmine.{}.s10.s2.... |
03bd2e3a2680937521a6804ea580cf20c6fee9dde0164f18cf5f2de705317feb | Python | 7,633 | 174 | import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
import numpy as np
import os
from scipy.stats import ttest_rel # Using a paired t-test
DATA_PATH = '../Extracted_Selectivity/VGG/PretrainedOnImageNet/IAPS/Tuning/'
emotion_FILE = '0915_BestModels0912_SI_byRank80/IAPS_pleasant_combined_df_with_l... |
2a007a58267c09ffe159d6eab3d20a9ea15c94d7b4f277572699a86c718fd0bb | Python | 7,633 | 222 | # 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... |
0d00c12f1c86671c34b8ba7d0cf4ed6ad512e6dd6d8f2b5bb115d8ddd3ea81c9 | Python | 7,639 | 261 | import torch
import torch.nn as nn
import torch.nn.functional as F
from roost.core import BaseModelClass
from roost.segments import MeanPooling, SimpleNetwork, SumPooling
class CrystalGraphConvNet(BaseModelClass):
"""
Create a crystal graph convolutional neural network for predicting total
material prope... |
f391301e546dde91a6711bb0ee344e617ff5d436fcd701283a7a5ba15b541112 | Python | 7,644 | 182 | # 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... |
c258bef349342faf9b0920fffe413d576ac15729d03afea147fcdff2eb6feb9f | Python | 7,646 | 167 | """Dictionary Matching Operator."""
from collections.abc import Callable
from typing import cast
import torch
from typing_extensions import Self, TypeVarTuple, Unpack
from mrpro.operators.Operator import Operator
Tin = TypeVarTuple('Tin')
class DictionaryMatchOp(Operator[torch.Tensor, tuple[Unpack[Tin]]]):
r"... |
3575f7c9d640d6c2e7f89d4b7c465abba5832bd8244aa0c07dcdb5d5aefe3b28 | Python | 7,651 | 205 | # 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... |
6848c20aa5ba41819f73885e2b7bb1ab9238d3d53e319cff97803eb42f4012c3 | Python | 7,651 | 260 | """Helper/Utilities for test functions."""
import torch
from mrpro.operators import LinearOperator, Operator
from typing_extensions import TypeVarTuple, Unpack
def relative_image_difference(img1: torch.Tensor, img2: torch.Tensor) -> torch.Tensor:
"""Calculate mean absolute relative difference between two images.... |
1fe99d0b106bcff7c2ad0566f4e9168e1c723ed169be39be3c6c7417ce5ad93d | Python | 7,654 | 214 | # Copyright 2018-2024 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... |
3d91e2c631b1ed1f773533dfdbd68f353b3235e7a471708929c5c0b83358b847 | Python | 7,656 | 218 | # Copyright 2024 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... |
8b8ede6871b02abe2f62a93159955e4b39acb81b7d6d2079fdcfa82f83e12f46 | Python | 7,659 | 225 | import pytest
import pandas as pd
import pandas._testing as tm
def check_level_names(index, names):
assert [level.name for level in index.levels] == list(names)
def test_slice_keep_name():
x = pd.MultiIndex.from_tuples([("a", "b"), (1, 2), ("c", "d")], names=["x", "y"])
assert x[1:].names == x.names
... |
03fb5825477af803f5368c96123d0d0f8204f4bd53697ff230a1893a87f22a33 | Python | 7,664 | 234 | ''' convert_neuron_tiffs.py
Convert searchabler neuron TIFFs into PNGs
'''
import argparse
from io import BytesIO
import json
import os
import re
import sys
import colorlog
import boto3
from botocore.exceptions import ClientError
import dask
from dask.callbacks import Callback
from PIL import Image
import requests... |
43f8d8aed18c4b49fbb274e79ecb4b1cdb3ab50a231b132decf80a5233592705 | Python | 7,665 | 259 | #---------------------------------------------------------------------72
#---------------------------------------------------------------------72
# ACTIVE TRANSPORT VIA ATPases
#---------------------------------------------------------------------72
#------------------------------------------------------------------... |
0207d9b122d0abf88a388d005880c68b618f9bac83a140da7244e98f9139e1d6 | Python | 7,668 | 208 | import os
import time
import torch
import torch.nn as nn
import numpy as np
import torch.nn.functional as F
import matplotlib.pyplot as plt
plt.style.use('ggplot')
from src.models import NeuralKalmanFilter, KalmanFilter
from src.utils import *
import argparse
device = "cuda" if torch.cuda.is_available() else "cpu"
pri... |
ce83656f8213ee4e3195b42597d0fcb5436d7f62a217d259d096fea646b8872f | Python | 7,668 | 128 | import numpy as np
import pandas as pd
import random
def convert_counts_to_cpm(counts):
lib_sizes = counts.sum(axis = 0).to_list()
scaled_counts = counts.divide(lib_sizes)
cpms = (scaled_counts * (10**6)).astype(np.float32)
return cpms
def filter_on_cpm(counts, n):
lib_sizes = counts.sum(axis = 0)... |
122bf034c056b4385c90abb741c008977a6995a9250246e000e7f7c925c981a5 | Python | 7,669 | 216 | from datetime import datetime
import re
import numpy as np
import pytest
from pandas.errors import Pandas4Warning
import pandas as pd
import pandas._testing as tm
class TestRename:
def test_rename(self, datetime_series):
ts = datetime_series
renamer = lambda x: x.strftime("%Y%m%d")
rena... |
6eaebcb30b160964ba26e67e59f6bf18b7ffd95793e0b2c561f58fa6653c9f80 | Python | 7,670 | 224 | from typing import Iterable, List, Literal, Optional, Sequence, Tuple, Union
import numpy as np
import pandas as pd
import seaborn as sns
from anndata import AnnData
from matplotlib import pyplot as plt
def heatmap(
adata_cc: AnnData,
rna: Union[pd.DataFrame, None] = None,
figsize: Tuple[int, int] = (28,... |
9ff0794ddf58f3b906d246f2cddf01c9a7ef06dbcc764c467c10dccda27c9528 | Python | 7,671 | 208 | __all__ = ["pGlycoReportParser"]
import os
import re
from typing import Tuple, Union
import numpy as np
import pandas as pd
from ....chem.pep.aminoacids import AminoAcidCollection
from ....chem.pep.mods import (
ModificationCollection,
ModifiedSequence,
ModPosition,
modified_sequence_to_str,
)
from .... |
7750eaa7e458a48d764cc71f4a347ed0e0d0cfae63740340d0acda0104bc235b | Python | 7,672 | 222 | import numpy as np
import pytest
import pandas as pd
import pandas._testing as tm
class TestDataFrameIsIn:
def test_isin(self):
# GH#4211
df = pd.DataFrame(
{
"vals": [1, 2, 3, 4],
"ids": ["a", "b", "f", "n"],
"ids2": ["a", "n", "c", "n"... |
ea72117015c1b31c8ef83e074ee4b84e5e101abf8b545fbedca92ee42af592ef | Python | 7,673 | 185 | #!/usr/bin/env python
"""Train models with dynamic data."""
import sys
import torch
from functools import partial
import os
os.environ['CUDA_VISIBLE_DEVICES']='4'
# import onmt.opts as opts
from onmt.utils.distributed import ErrorHandler, consumer, batch_producer
from onmt.utils.misc import set_random_seed
from onmt.m... |
fea2777a1e400fabb7d7f785152ea4dbd88f7523d1809a906c0c1fee1410d5fe | Python | 7,673 | 216 | """Automated annotation of Cognitive Atlas labels."""
import logging
import re
import numpy as np
import pandas as pd
from nimare import references
from nimare.annotate import utils
from nimare.due import due
from nimare.extract import download_cognitive_atlas
from nimare.utils import _uk_to_us
LGR = logging.getLogg... |
f33e7316ca39ef906be9989837da6e929e6e26f40d3755d58f394d53eb333573 | Python | 7,680 | 191 | import sys, re, argparse
argparser = argparse.ArgumentParser('''
Generates a space-delimited table of relevant fields from the entries in a *.constitevallist table.
''')
argparser.add_argument('constitevallist', type=str, nargs=1, help='Path to a *.constitevallist table.')
args, unknown = argparser.parse_known_args()
... |
4d7c61e745415d26863e83fa4c7b570c55f1cfcf16937e88bffffd927a121e6c | Python | 7,683 | 199 | # emacs: -*- mode: python-mode; py-indent-offset: 4; tab-width: 4; indent-tabs-mode: nil -*-
# ex: set sts=4 ts=4 sw=4 et:
"""
.. _datasets_imgs_to_coords:
=================================
Transform images into coordinates
=================================
Create a dataset with coordinates derived from peak statist... |
1ad6f615d6ff8d43b5999fcbf3f4960804cce5ee9dc17addd2806c7242d18635 | Python | 7,692 | 138 | #! /usr/bin/env python
import argparse
import sys
import os
import pysam
from collections import defaultdict
import numpy as np
from hashed_read_genome_array import read_length_nmis
import itertools
import multiprocessing as mp
from time import strftime
parser = argparse.ArgumentParser(description='Find most common P... |
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