sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
7d9869931fc82fd3869cf27d23d94a76e3cfff46d32e2497de3004cebb45b40c | Python | 1,714 | 57 | from time import sleep
from codecarbon import EmissionsTracker
def load_dataset(dataset, split):
print(f"Loading dataset {dataset} {split}")
sleep(5)
return dataset
def build_model():
model = "huge_model"
sleep(5)
return model
def inference(model, data, inference_task_name):
print(f"R... |
c795bc3bad1b934593b77a6b07beb12a7f926484ae284e2ac9fab7fd2f0f4c1e | Python | 1,717 | 60 | from sys import argv
from msp import MSP
msp = MSP()
msp.file = __file__
msp.seed = int(argv[1])
msp.architecture["num_motifs"] = 82
msp.architecture["motif_model_spec"]["motif_width"] = 13
msp.architecture["motif_model_spec"]["motif_feature_extractor_spec"] = dict(
type="ResidualStack",
depth=3,
)
msp.arch... |
703636bf2b432cb66b501ec48303fe76039f47a6ad5afae35aa6a9bea210b632 | Python | 1,718 | 72 | """Lightly is a computer vision framework for self-supervised learning.
With Lightly you can train deep learning models using
self-supervision. This means, that you don't require
any labels to train a model. Lightly has been built
to help you understand and work with large unlabeled datasets.
It is built on top of PyT... |
e39569d88ad8df3eea8e8ddd69181147cb97e707d12d9f7a807320b424d5c1db | Python | 1,718 | 50 | from typing import Optional, Union
from anndata import AnnData
from pathlib import Path
import os
import pandas as pd
def lr(
adata: AnnData,
db_filepath: str = None,
sep: str = "\t",
source: str = "connectomedb",
copy: bool = False,
) -> Optional[AnnData]:
"""Add significant Ligand-Receptor p... |
e4c355cb008cbebc273a81d9c118f2ce7695dc2a7a652275e5e63e67b93cfc95 | Python | 1,718 | 75 | import pandas as pd
import pytest
import larvaworld
import larvaworld.lib.process.dataset
import larvaworld.lib.reg as reg
pytestmark = [
pytest.mark.integration,
pytest.mark.heavy,
pytest.mark.skip(reason="legacy integration tests kept for manual execution"),
]
def test_import_Schleyer():
g = reg.... |
176be4cd3fb5761ddeb46c977aefbc6844b79dfce555b4eefc05767243d4b9c0 | Python | 1,719 | 44 | import scanpy
from anndata import AnnData
def run_diffmap(adata: AnnData, n_comps: int = 15, copy: bool = False):
"""\
Diffusion Maps [Coifman05]_ [Haghverdi15]_ [Wolf18]_.
Diffusion maps [Coifman05]_ has been proposed for visualizing single-cell
data by [Haghverdi15]_. The tool uses the adapted Gauss... |
25a79f4d3cb5d94a999c1d89ba7753bb3e08ce827fe65ddfaa235b7de69d6b72 | Python | 1,719 | 44 | import torch
from pytorch_lightning import LightningModule, Trainer
from torch.utils.data import DataLoader
from torchvision.datasets import FakeData
from lightly.transforms.torchvision_v2_compatibility import torchvision_transforms as T
from lightly.utils.benchmarking import MetricCallback
class TestMetricCallback:... |
57d2ed1784b19da5caf70538dc49eceadb14c23127600b3ac6792aa533b33565 | Python | 1,719 | 50 | #!/usr/bin/env python
# fix problems with pythons terrible import system
import sys
import os
file_dir = os.path.dirname(os.path.realpath(__file__))
sys.path.append(os.path.join(file_dir, '../'))
from prob2020.python.bed_line import BedLine
import pandas as pd
import argparse
import IPython
def parse_arguments():
... |
68154a44d42b7cd59fe81eca3991750683adff2eda761dc2bbea5a5d471461d9 | Python | 1,719 | 50 | from functools import partial
from typing import Tuple
import jax
import jax.numpy as jnp
@partial(jax.jit, static_argnames=['vec'])
def hebb_update(w: jnp.ndarray, X: jnp.ndarray, y_hat: jnp.ndarray, eps: float, lam: float, vec = False) -> jnp.ndarray:
"""
Performs one Hebbian update step.
:param w: Weigh... |
da1b9e60b5fac4b2e763167f30801812220ab5b3a906b4a3491ed04635c521c0 | Python | 1,719 | 58 | import sys
import os.path as op
from setuptools import setup, find_packages
# get the version (don't import mne here, so dependencies are not needed)
version = None
with open(op.join("pyriemann", "_version.py"), "r") as fid:
for line in (line.strip() for line in fid):
if line.startswith("__version__"):
... |
a13175b65399f41c65b2edd8740ff679cbba481d95ef049bf87d1086112e7cbb | Python | 1,720 | 51 | # coding=utf-8
# Copyright 2025 The Google Research Authors.
#
# 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 applicab... |
bf1dbb6ead03f8ce0d1a4702947f762bd26024b6e935e17b21cc7dff770a09d0 | Python | 1,720 | 61 | """Append-aware backward validator regression tests."""
from __future__ import annotations
import pytest
import torch
from torch import nn
import torchlens as tl
from torchlens.intervention.errors import AppendStateValidationWarning
from torchlens.options import CaptureOptions, ReplayOptions
from torchlens.validatio... |
c5e83960644f06a82ba3345c92a2b722f139417e281ffaa984526d0e44a76156 | Python | 1,720 | 60 | """
opto.py
Contains modules for opto stimulation tag generation and analysis using Pulse Pal.
For more information regarding stimulation setup see: https://sites.google.com/site/pulsepalwiki/parameter-guide
"""
import numpy as np
####################################################################################... |
b9ea14b29a04270155dcfa602d736cbed0b8edcc7c350fe8cf1c5d566cb9d90f | Python | 1,722 | 64 | from __future__ import absolute_import
from mxnet.gluon import nn, HybridBlock
from mxnet import init
from mxnet.gluon.model_zoo import vision
class ResNet(HybridBlock):
__factory = {
18: vision.resnet18_v1,
34: vision.resnet34_v1,
50: vision.resnet50_v1,
101: vision.resnet101_v1,... |
36cefcb4b866914cf68374981d65a2261f43e98f8243fe37fb112218c7e3b928 | Python | 1,723 | 80 | # Optimization utilities
import numpy as np
from scipy import optimize
fmin = optimize.fmin
leastsq = optimize.leastsq
exp = np.exp
def gaussian(x, params):
(a, b, c,f) = params
return a * np.exp(-(x-b)**2/(2*c**2))+f
def fwhm(c):
return np.sqrt(2*np.log(2))*c
def score_gauss(p, x, v):
return sum((... |
d3d3538e36e102f90dd5dbdb1759b1831a3cbbcc56e16693e2c7df2bba194834 | Python | 1,724 | 48 | import numpy as np
class MultiTermLossFunction(object):
def __init__(self, loss_fn, weight) -> None:
self.terms = list(weight.keys())
if type(loss_fn) is not dict:
self.loss_fn = {term:loss_fn for term in self.terms}
else:
self.loss_fn = loss_fn
sel... |
fa3f5ee7cafb12f2d05e57ac0ed948084fb6155c473bc10dc5b08939515a3a18 | Python | 1,724 | 45 | """
This is an example script showing how to process your own data. You need to provide SMILES and their bioactivity.
"""
from MoleculeACE.models import RF, SVM, GBM, KNN, MLP, GCN, MPNN, AFP, GAT, CNN, LSTM, Transformer
from MoleculeACE.benchmark.const import Descriptors
from MoleculeACE.benchmark.data_prep import pr... |
0c28efff0017e54ade3b3969ded6cce2b41b81ebb673a25f05ad6fa4d6cb8fff | Python | 1,725 | 60 | """Test configuration script."""
import numpy as np
import pytest
import pynapple as nap
def skip_if_backend(backend_name):
"""Skip test if the backend matches `backend_name`."""
return pytest.mark.skipif(
nap.nap_config.backend == backend_name,
reason=f"Test skipped because backend is {back... |
58a50ec90f56885054ad72b354fd267472b886d7fdfeb163f0ce7ff9cce8575e | Python | 1,725 | 52 | """Adapted from: https://github.com/https-deeplearning-ai/GANs-Public."""
from typing import Any, Tuple
import torch
from pl_bolts.utils import _PIL_AVAILABLE, _TORCHVISION_AVAILABLE
from pl_bolts.utils.warnings import warn_missing_pkg
if _PIL_AVAILABLE:
from PIL import Image
else: # pragma: no cover
warn_m... |
aca1cbd0999f11173f3082320948a5d37b92a6b0e94b51d24eea5d16565483f0 | Python | 1,725 | 39 | from unittest import TestCase
from drug_interactions.reader.dal import Drug, DrugBank
from drug_interactions.reader.preprocessor import DrugPreprocessor
class DrugPreprocessorTestCase(TestCase):
def setUp(self):
self.drug1 = Drug(**{'id_': '1', 'interactions': {('3', 'bar')}})
self.drug2 = Drug(*... |
af02b7d49f565fa49cf74deca4f322312314c85906d5b0caa83c1636277c5c65 | Python | 1,725 | 38 | import unittest
from config_manager import base_configuration
from config_manager import config_field
class TestBaseConfiguration(unittest.TestCase):
"""Test class for base_configuration.BaseConfiguration unit tests."""
def test_validate_field(self):
valid_test_fields = [
({"hello": "worl... |
8c3de6705a22d587e8204ae21f185e9f40f2d5df2aa3ea30b5945a3c30befc37 | Python | 1,726 | 62 | import numpy as np
import itertools as itt
def _sorted_memberships(membs):
return np.array(sorted(list(range(int(np.max(membs)+1))), key=lambda i:np.sum(membs==i)))
def sort_clusters_by_size(membs):
"""
Sort cluster indices such that cluster with smallest index has
most members.
"""
sorted_id... |
d6fa9b446206bb20c3a2fcaf8d72ffde11a92878266eefa91ab50e51e0415887 | Python | 1,726 | 55 | """
Tools for matplotlib plot exporting
"""
def ipynb_vega_init():
"""Initialize the IPython notebook display elements
This function borrows heavily from the excellent vincent package:
http://github.com/wrobstory/vincent
"""
try:
from IPython.core.display import display, HTML
except I... |
574ea8cd214f24eb29de46e57a9cba434b1de29d6101993f692e42f6f0005d7c | Python | 1,727 | 67 | #!/usr/bin/env python3
'''convert gninatypes file to xyz file'''
import struct, sys, argparse
from functools import partial
import molgrid
names = molgrid.GninaIndexTyper().get_type_names()
def elem(t):
'''convert type index into element string'''
name = names[t]
if 'Hydrogen' in name:
return 'H'... |
c0f5967cb27def29acb5c9ec9df82e8c9fa02e95699ba8895fe8224d830cdc99 | Python | 1,727 | 61 |
__author__ = 'quentin'
import cv2
from ethoscope.hardware.input.cameras import MovieVirtualCamera
import numpy as np
from math import log10
import os
import random
class NegativeMaker(object):
_path = open("/tmp/fly_snapshots/negative.csv","w")
def run(self, camera):
for j, (t,f) in enumerate(cam... |
2a8dd4367d9d238de92829e0ecfb00fee2643a58d44c10dc0de3f4d249227a74 | Python | 1,728 | 44 | import sys
# setting path
sys.path.append('../TM2_segmentation')
import os
import numpy as np
import nibabel as nib
import itk
import pandas as pd
import tarfile
from scripts.preprocess_utils import find_file_in_path, register_to_template
# load metadata file
input_annotation_file = '/media/sda/Anna/28andme/ds002... |
6fd8ae989d81617c83f5e86564179853eb6f396db31e3cd29103e9349176b3c8 | Python | 1,729 | 66 | from sys import argv
from msp import MSP
msp = MSP()
msp.file = __file__
msp.seed = int(argv[1])
msp.architecture["num_motifs"] = 82
msp.architecture["motif_model_spec"] = dict(
type="AdjustedMotifModel",
model_to_adjust_spec=dict(
type="PSAMMotifModel",
motif_spec=dict(type="rbns"),
e... |
e2b55c8efe70e8212eb3e28b77f0198aab7635afe1052b10399d221711f704a7 | Python | 1,729 | 48 | from imodelsx import submit_utils
from os.path import dirname, join
import os.path
repo_dir = dirname(dirname(os.path.abspath(__file__)))
params_shared_dict = {
'seed': [1],
'save_dir': [join(repo_dir, 'results')],
'use_cache': [1],
'batch_size': [64, 16, 4],
'renormalize_embs_strategy': ['Standard... |
0075c69137e2ab68aaa3402afda80e97c84c10a74a4dd3c4294e100a4be7c50c | Python | 1,730 | 60 | # Copyright 2024 The Google Research Authors.
#
# 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 agre... |
0c938493ab7a20b7c5bf3cc296b52542e610245a2aefd569264d29f9442ea02c | Python | 1,730 | 55 | import sys
from ij import IJ
from ij.plugin import Duplicator
# Fiji Jython interpreter implements Python 2.5 which does not
# provide support for argparse.
input_file = sys.argv[-13]
xleft = int(sys.argv[-12])
width = int(sys.argv[-11])
ytop = int(sys.argv[-10])
height = int(sys.argv[-9])
first_channel = int(sys.arg... |
2e3a55301e238560bba354fb2d6d1f61747330bad5763653dba1a41ab93f7255 | Python | 1,731 | 52 | import torchinfo
import numpy as np
import torch.nn as nn
def get_conv1dblock_output_len(modules, input_len):
"""
Get the dimension of the flattened output of a convolutional modules with only Conv1d and Maxpool1d layers.
This will be deprecated in the future.
Parameters
----------
modules : ... |
91aafeb2379f482991f7ffe152f9d8b10dbbc91579a8788e5cdc3ba405f34987 | Python | 1,731 | 65 | import copy
import warnings
from typing import Optional, Type, Union
class bcolors:
"""ANSI escape sequences for colored terminal output."""
HEADER = "\033[95m"
OKBLUE = "\033[94m"
OKGREEN = "\033[92m"
WARNING = "\033[93m"
FAIL = "\033[91m"
ENDC = "\033[0m"
BOLD = "\033[1m"
UNDERL... |
414dd7ceeb5a1ca40d38d83994416457f75d46e4c5cb1318fe2af061ad064d12 | Python | 1,732 | 58 | from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
from __future__ import unicode_literals
from numpy import array
import numpy as np
#import array_tools
from dcCustom.metrics import swapped
import sys
import pdb
def cindex_singletask(Y, P):
#Y = np.array(... |
6260d87540ed6388c8c153157a77a040bf0154712ab3a6c8e0af4d357a15276f | Python | 1,732 | 38 | from __future__ import print_function
import os
from bleualign.align import Aligner
if __name__ == '__main__':
current_path = os.path.dirname(os.path.abspath(__file__))
options = {
# source and target files needed by Aligner
# they can be filenames, arrays of strings or io objects.
'srcfile':os.path.join(curre... |
71170779a308e19342834c6f6cc886a29966c54486f2926373b8396eaec64a12 | Python | 1,732 | 47 | # LICENSE
#
# _This file is Copyright 2018 by the Image Processing and Analysis Group (BioImage Suite Team). Dept. of Radiology & Biomedical Imaging, Yale School of Medicine._
#
# BioImage Suite Web is licensed under the Apache License, Version 2.0 (the "License");
#
# - you may not use this software except in compl... |
6ad51f1a5796838abde0edc046363c4e63281492dc9bf47c69e84cca45d1aec9 | Python | 1,733 | 49 | #%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
# Written by Yuichiro Yada
#%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
################################################
# A code for Fig. 2f. Before running this code, please run "prediction_realdata.py"
# with and without gradient_term, and set the resulting amyl... |
6e018ac5cd5c4575ace7e4c6038b36ca4aabb5a2d0cf45e968047c3c8377cc12 | Python | 1,733 | 51 | """Module for dynamic data transfrom."""
import os
import importlib
from .transform import make_transforms, get_specials,\
save_transforms, load_transforms, TransformPipe,\
Transform
AVAILABLE_TRANSFORMS = {}
def get_transforms_cls(transform_names):
"""Return valid transform class indicated in `transfo... |
8d5cd6e1bce54513dfc7cef8f85a501aa3b1a25a2f32753939df5aaa6852c2e5 | Python | 1,733 | 62 | _author__ = "quentin"
# flake8: noqa: E402
import time
from ethoscope.hardware.interfaces.lynx_motion import LynxMotionInterface
class OdourDelivererInterface(LynxMotionInterface):
_positions_to_angles = {1: -25, 2: 20, 3: 0}
_dt = 250
def __init__(self, *args, **kwargs):
self._current_pos = [3... |
a726ba2dfb66e96e19e86644122b884c1efb5ad5f5d0ef8dd4d18343f67d7da3 | Python | 1,733 | 56 | from torch_geometric.data import Data
from torch_geometric.data import InMemoryDataset, download_url
import torch
import pandas as pd
from featurizer import MolecularGraphData, SMILESToECFP4
from sklearn.model_selection import train_test_split
class MolecularDataset(InMemoryDataset):
def __init__(self, root, csv_... |
33a28cef04acaedb680044152119a13442ab61cfbe51e51486f65e1b961495c1 | Python | 1,735 | 46 | import os
from data import common
from data import srdata
import numpy as np
import torch
import torch.utils.data as data
class Runtime(srdata.SRData):
def __init__(self, args, name='', train=True, benchmark=True):
super(Runtime, self).__init__(
args, name=name, train=train, benchmark=True
... |
5c69ebf460c354dc8037730e2e336fb70035b234f89808966e2ea869e3cbe626 | Python | 1,735 | 58 | from __future__ import print_function, division, absolute_import
from .fbresnet import fbresnet152
from .cafferesnet import cafferesnet101
from .bninception import bninception
from .resnext import resnext101_32x4d
from .resnext import resnext101_64x4d
from .inceptionv4 import inceptionv4
from .inceptionresnetv2 im... |
95edc142174cde5ac5b45634ca9f69548302bb50eaa56086d9644d8985fecc22 | Python | 1,735 | 58 | from anndata import AnnData
from typing import Optional, Union
import numpy as np
from stlearn.spatials.trajectory.utils import _correlation_test_helper
def set_root(adata: AnnData, use_label: str, cluster: str, use_raw: bool = False):
"""\
Automatically set the root index.
Parameters
----------
... |
94d644a3e905504d399261e3e92d15a1f297d54123e51c54af55f39bdfb5b43b | Python | 1,736 | 58 | # %% [markdown]
# # Write HCS Plates
# (tutorials:write_hcs_plate)=
#
# This tutorial shows how to write a high-content screening (HCS) dataset to OME-NGFF format.
# HCS datasets represent culture plates with multiple wells, where each well can contain multiple fields of view.
#
# ## Create sample data
#
# First, let's... |
c4e8668aa1bf8eaada32eb5b5b0fe16627001193edabeae54090af216c92e50e | Python | 1,736 | 49 | #!/usr/bin/env python
"""Tests for `stringdb` package."""
import pytest
import stringdb
@pytest.fixture()
def mapped_ddr_ids():
"""Example string ids"""
string_ids = stringdb.get_string_ids(['TP53', 'BRCA1', 'FANCD1', 'FANCL'])
return string_ids
def test_string_mapping(mapped_ddr_ids):
assert (m... |
53339ef22afe0c7c47e9fb9a67c1a87ae018a0a8805a8693c9a62f858203687c | Python | 1,737 | 54 | """Benchmarking module for AlignmentFile functionality"""
import os
import pytest
from VariantFileFetchTestUtils import *
GENOMES_URL = "ftp://ftp.1000genomes.ebi.ac.uk/vol1/ftp/release/20130502/ALL.chr{chrom}.phase3_shapeit2_mvncall_integrated_v5a.20130502.genotypes.vcf.gz"
CHROM = 22
@pytest.fixture
def genomes... |
7ca225e72fe471b009e8760f71f7425d7eee9c8bd9bd302e07a91037865fb84c | Python | 1,737 | 56 | import os
import random
import numpy as np
from skimage import io, color
import cv2
images_path = './GT' # series of graound truth hypothalamus masks
masks_path = './pred' # series of predicted masks
img_overlay_path = './overlay'
img_overlay_GT_path = './overlay_GT'
images = []
masks = []
images_name = []
for im i... |
84ca4dc0b1747fdc3b6436d15b7cfd4b3893c2c53771b849d68ca6b3b618079c | Python | 1,737 | 57 | import pyvista as pv
import numpy as np
def vtk2swc(inputfile, outputfile):
"""
Function to convert a .vtk file into a .swc file.
Required arguments:
inputfile: [string] Path of the reconstruction format to convert.
outputfile: [string] Path of converted SWC file.
... |
8a05119e6c16449cdae3f7bee2ef1355aa36d688ba7cd9d18a4b0baf05eb9246 | Python | 1,738 | 58 | """Test functions in xcp_d.utils.execsummary."""
import os
import matplotlib.pyplot as plt
from xcp_d.data import load as load_data
from xcp_d.tests.utils import chdir
from xcp_d.utils import execsummary
def test_make_mosaic(tmp_path_factory):
"""Test make_mosaic."""
tmpdir = tmp_path_factory.mktemp('test_... |
264b8c63056c87ca5dbde51740774178cdb7e997630a689cbace4a9c62cf8c67 | Python | 1,739 | 65 | from sys import argv
from msp import MSP
msp = MSP()
msp.file = __file__
msp.seed = int(argv[1])
msp.architecture["num_motifs"] = 82
msp.architecture["motif_model_spec"] = dict(
type="AdjustedMotifModel",
model_to_adjust_spec=dict(
type="PSAMMotifModel",
motif_spec=dict(type="rbns"),
e... |
c3b5307e22a76134f87a8d29810e12387fc096b9ff6f08423d5436cfa5eb69b0 | Python | 1,739 | 68 | from unittest.mock import patch
import pytest
from celery.utils import deprecated
class test_deprecated_property:
@patch('celery.utils.deprecated.warn')
def test_deprecated(self, warn):
class X:
_foo = None
@deprecated.Property(deprecation='1.2')
def foo(self):... |
6411388dea93ac1f88605de75506e8e32ae87eaca5d265794620eb64c65d5d9f | Python | 1,740 | 49 | import subprocess
import sys
import textwrap
import pytest
@pytest.mark.parametrize('multi,template,expected', [
(False, '%%n-%n.log', '%n-worker.log'),
(False, '%%x.log', '%x.log'),
(True, '%%%%n-%n.log', '%n-worker.log'),
(True, '50%%%%d.log', '50%d.log'),
(True, '%%%%x.log', '%x.log'),
(Tr... |
8560942a164e0efc38efe051e05c3ae3c46d38b8dfb0b40e1d06fca64a1fa2ba | Python | 1,742 | 60 | """
Interface between a larvaworld simulation and a remote model
"""
from __future__ import annotations
from typing import Any
__displayname__ = "Client-Server"
__all__: list[str] = ["Client", "Server", "BrianInterfaceMessage"]
from .ipc import Client, Server, Message
class BrianInterfaceMessage(Message):
""... |
3c1853ef6d980db9cf1ab197403d7fb1ba53f8ae02fd512f0ff24f07f1c59d93 | Python | 1,744 | 67 | import numpy as np
import matplotlib.pyplot as plt
# define lotka-volterra operator
################################
from pyrates import OperatorTemplate
op = OperatorTemplate(
name="lv",
equations="x' = x*(alpha + x_in)",
variables={"x": "output(0.5)", "alpha": 0.5,
"x_in": "input(0.0)"}
... |
6c9e64f961ad8507670d8fc4f1931d48f99312c6ff1535ed744eefe97cb76faf | Python | 1,744 | 65 | import pandas as pd
import numpy as np
import random
np.random.seed(1000)
random.seed(1000)
def make_synthetic_data(tgi_path, OS_path, ptnm_path):
tgi_df = pd.read_csv(tgi_path)
OS_df = pd.read_csv(OS_path)
ptnm_df = pd.read_csv(ptnm_path)
# randomize NMID
unique_nmid = pd.unique(tgi_df.NMID)
... |
731e2d297569ce5465e8ee2de940113db1fb196977199e0aad5ba21cfc79db5c | Python | 1,744 | 66 | #!/usr/bin/env python
import numpy as np
import matplotlib.pyplot as plt
import seaborn as sns
dt = 10e-3 # sampling interval
baserate = 5.0
amplitude = 4.0
basename = "rates"
np.random.seed(42)
def get_random_signal(period=10.0, alpha=1.5, nb_repeats=11, cutoff=128):
theta = np.random.rand(cutoff,2)
durati... |
f69f23edc68347b476e79c4e35612a8673227aaa6f4b1783712275ecebfd2382 | Python | 1,744 | 48 | #!/usr/bin/env python2
# -*- coding: utf-8 -*-
"""
@author: Pramod Bharadwaj Chandrashekar, Li Liu
@email: pchandrashe3@wisc.edu, liliu@asu.edu
"""
import numpy as np
from sklearn.cluster import KMeans
import scipy.stats as stats
def get_cdf_pval(data):
""" Function for guassian mixture of dat and computing pval... |
110495e4fda8c685017d44526078beb9602d54135fdfc83a802b1d35ca331e5f | Python | 1,746 | 63 | """Trace a toy transformer block that builds its mask with ``torch.vmap``."""
import torch
from torch import nn
import torchlens as tl
class VmapMaskedToyTransformer(nn.Module):
"""Tiny attention-style block with a vmapped mask builder."""
def __init__(self, width: int) -> None:
"""Initialize the t... |
d1946b83a94b6516323c1554b4dd7849f63c7859129696c2d0b39c87253d7be7 | Python | 1,746 | 65 | '''Definition of bifurcation functionality'''
import numpy as np
import tns.morphmath.rotation as rt
from tns.morphmath.utils import get_random_point
def random():
'''
Get 3-d coordinates of a new random point.
The distance between the produced point and (0,0,0)
is given by the value D.
'''
d... |
e93d0658ea52e5b84fb25c1003324886fee4b0660eef55590e2b67ac1a05bf40 | Python | 1,746 | 54 | import json
import unittest
from types import SimpleNamespace
from cellxgene_gateway.gateway import do_GET_status_json, app, cache
from cellxgene_gateway.cache_entry import CacheEntry, CacheEntryStatus
class TestGatewayStatusJson(unittest.TestCase):
def test_do_GET_status_json_returns_expected_structure(self):
... |
489859dc4ce5bb24ebc653e70fadfc32ac8098b9edddaf79d381611b0ffe053b | Python | 1,747 | 57 | # Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by app... |
6bf52dd2c94f37db2562989dc96e04e88e82dacf4925def6ac65d50302146786 | Python | 1,747 | 55 | """Fuse Many image of CT and RMI using a json file """
from os.path import dirname, abspath, join, exists
from os import makedirs
from SEEGFusion import ImageFusion
import SimpleITK as sitk
import json
import sys
def main(argv):
output_path = join(
dirname(
dirname(
dirname(abs... |
98b31acaa70a6a1b907453c0f53ced9397dbdab048dd327853a228f3d621f60a | Python | 1,747 | 55 | """
Get snap2 file with all the samples.
"""
import os
import sys
import logging
from pathlib import Path
from typing import Dict, List
import numpy as np
import snapatac2 as sa2
import pyprojroot
proj_dir = str(pyprojroot.here())
pack_dir = f"{proj_dir}/package/python"
sys.path.insert(0, pack_dir)
from mylog impor... |
c44e8659c392c583e43e0fa906916d5c3f7c372c4d1b9049178f1d664e0cadca | Python | 1,747 | 70 | import os
import pytest
from hobj.data.behavior import load_highvar_behavior, load_oneshot_behavior
from hobj.data.images import (
load_image,
load_imageset_meta_catch,
load_imageset_meta_highvar,
load_imageset_meta_oneshot,
load_imageset_meta_warmup,
)
pytestmark = pytest.mark.skipif(
os.env... |
4ab67ea4feef2c9263157639da7121fbff29bda2ee057e2105e08c1b9bafe0ce | Python | 1,748 | 66 | from scipy import misc
import os, cv2, torch
import numpy as np
def load_test_data(image_path, size=256):
img = misc.imread(image_path, mode='RGB')
img = misc.imresize(img, [size, size])
img = np.expand_dims(img, axis=0)
img = preprocessing(img)
return img
def preprocessing(x):
x = x/127.5 - ... |
706390b1dc0ab6b6518be9e231a29a9feb5e2e61d76479beef71bb5c16809cc8 | Python | 1,748 | 66 | """
Check whether the start codon is present
"""
import os.path
import logging
from Bio import SeqIO
from .utils import find_gapped_pos
# pylint: disable=C0103
# Invalid constant name
logger = logging.getLogger('pipe.gag_codon')
def gag_codon(configs, seqs):
"""Primer check.
Check whether any of the prim... |
8ee21f536e385ca123899adf0c5f7bb5fc2aea62b3bbe8b632ce7857c41d87ab | Python | 1,748 | 58 | """
This code demonstrates how to perform measurements on small ranges of sweeps.
"""
# import the pyabf module from this development folder
import os
import sys
PATH_HERE = os.path.abspath(os.path.dirname(__file__))
PATH_SRC = os.path.abspath(PATH_HERE+"/../src/")
PATH_DATA = os.path.abspath(PATH_HERE+"/../data/abfs/... |
1a2edc72042d6f9bd52fe007c381a85592b5575ceaebc87e00f9556f7a8095c8 | Python | 1,749 | 43 | # Author: Christian Brodbeck <christianbrodbeck@nyu.edu>
"""Accessible tool for statistical analysis of MEG and EEG data.
For the full documentation see <http://eelbrain.readthedocs.io>.
"The human brain is like an enormous fish. It's flat
and slimy, and has gills through which it can see."
... |
8a28c8c6f7301e0471703c717204c245f2782c0a3e5802086bfc1a64068ce9b5 | Python | 1,749 | 44 | from __future__ import division
import argparse
import numpy as np
import mxnet as mx
from mxnet import gluon, nd, image
import matplotlib.pyplot as plt
import gluoncv as gcv
gcv.utils.check_version('0.6.0')
from gluoncv import data
from gluoncv.model_zoo import get_model
from gluoncv.data.transforms.pose import det... |
cc37232161065ebf0a51e69d2094913e929c87b6b669b2c2f7150929e4a6950c | Python | 1,749 | 61 | import os
import time
import h5py
import numpy as np
import scanpy as sc
from ica import ica1
from memory_profiler import profile
from scbig.utils import setup_seed
def preprocess(adata, scale=True):
sc.pp.filter_genes(adata, min_cells=3)
sc.pp.filter_cells(adata, min_genes=200)
sc.pp.normalize_total(ad... |
d90b57da26216723a1dd0a78efb5e5998a995c0c4421a23304c8a85b3ee116b4 | Python | 1,749 | 50 | import cv2
import os
import numpy as np
class Combine_Image():
def __init__(self, path_AB):
self.path_AB = path_AB
if not os.path.exists(path_AB):
os.makedirs(path_AB)
def combine_image(self, path_A, path_B):
img_A = cv2.imread(path_A)
img_B = cv2.imread(path_B)
... |
26222a4e6fe27fb3a2c461f0fd13022593375e42159a63976b4a5d100da0ba50 | Python | 1,750 | 63 | """Creating events, and event exchange definition."""
import time
from copy import copy
from kombu import Exchange
__all__ = (
'Event', 'event_exchange', 'get_exchange', 'group_from',
)
EVENT_EXCHANGE_NAME = 'celeryev'
#: Exchange used to send events on.
#: Note: Use :func:`get_exchange` instead, as the type of
... |
53bfbfe32ed1f9c15f435b5f0da2635dd73c2e5057cbe5d8dfd55f8e5f908df4 | Python | 1,750 | 49 | """A custom nms module for tvm with static shape"""
# pylint: disable=unused-argument
from tvm import relay
from tvm.relay.frontend.pytorch import _op, AttrCvt, get_relay_op
def nms(inputs, input_types):
"""A static NMS hack for torchvision.nms, it requires the nms to be the last layer of the network"""
boxes ... |
753b6c966f5913ce6d490d5e0d96170226cb31f1b04c88a89861412a9a288d97 | Python | 1,751 | 42 | from typing import Any, Dict, Iterable, Optional, Tuple
import argparse
import torch
import torch.nn as nn
import transformers
from imodelsx.iprompt.utils import PrefixLoss, PrefixModel
class PromptTunedModel(PrefixModel):
args: argparse.Namespace
loss_func: PrefixLoss
model: transformers.PreTrainedMod... |
7e250a4f4da7f3994d64c90cdcdacbb6c5c5a83046b65c623776d06116324f56 | Python | 1,751 | 46 | """add_indexes_for_workflow_comment_foreign_keys
Revision ID: 2dc3386d091f
Revises: 8a19186a6ee7
Create Date: 2024-03-13 15:25:52.587488
"""
from galaxy.model.database_object_names import build_index_name
from galaxy.model.migrations.util import (
create_index,
drop_index,
index_exists,
)
# revision ide... |
8849bbfec8e2534c54b4484f4f751ff3e05732acec6df0330ce7057d71da668e | Python | 1,751 | 49 | """
Integration tests for calibration.py using REAL LarvaDataset.
Uses real dataset from registry (exploration.30controls) with full preprocessing.
Requires ensure_datasets_ready fixture.
"""
import pytest
pytestmark = [pytest.mark.integration, pytest.mark.heavy]
@pytest.mark.usefixtures("ensure_datasets_ready")
d... |
fe7cd5f008f154a147c5a0e47ca1fbe31e79bd9146b421e85fcc41b1c4e554cc | Python | 1,752 | 47 | import time
import torch
import torch.utils.benchmark as benchmark
from triton.testing import do_bench
if torch.version.cuda:
backendBLAS = "cuBLAS"
elif torch.version.hip:
backendBLAS = "hipBLAS"
def benchmark_forward(fn, *inputs, repeats=10, desc='', verbose=True, **kwinputs):
"""Use Pytorch Benchmark ... |
a0f795d37f3a6474b9202669495ba0d77a96bb562daad64c9561e21fa78aa28d | Python | 1,753 | 52 | from __future__ import division
import unittest
import random
import numpy as np
from wyrm.types import Data
from wyrm.processing import sort_channels, swapaxes, CHANNEL_10_20
class TestSortChannels(unittest.TestCase):
def setUp(self):
self.sorted_channels = np.array([name for name, pos in CHANNEL_10_... |
4e33fcc9ba117ae56ee724d613b888a357c5552a856a642671480686347f8ac5 | Python | 1,755 | 61 | import json
from textwrap import dedent
from caper.singularity import find_bindpath
UBUNTU_18_04_3 = (
'ubuntu@sha256:d1d454df0f579c6be4d8161d227462d69e163a8ff9d20a847533989cf0c94d90'
)
UBUNTU_18_04_3_LAST_HASH_TAR_GZ = (
'sha256:6001e1789921cf851f6fb2e5fe05be70f482fe9c2286f66892fe5a3bc404569c.tar.gz'
)
def... |
5b197dfaec03f7c10fd3d0b799ff6a4e31669ed5195b8911f4f7852a7fa48397 | Python | 1,755 | 52 | #!/usr/bin/env python
"""
Convert a GFF and the associated sequence (FASTA) into GenBank, embl or FASTA format.
https://raw.github.com/chapmanb/bcbb/master/gff/Scripts/gff/gff_to_genbank.py
Usage:
gff_to_gb_or_embl.py <GFF annotation file> <FASTA sequence file> <Output file> <Output format genbank or ... |
f6589e3a73506e48dfed8b3e0c831b30145e0318175f7ee7af952b9f9c567e44 | Python | 1,755 | 45 | """Building blocks for world models.
A world model predicts how an environment evolves. A latent world model does it
in embedding space: it predicts the embedding of the next frame from the
embeddings of the past frames, optionally conditioned on the action that was
taken.
The modules here are parts that latent world... |
f791f7ddb91bfe44881c7f161fad196d06e89535eb41e3a98315f955a2c02dcd | Python | 1,755 | 51 | from mirp._images.generic_image import GenericImage
class MRDCEImage(GenericImage):
# Diffusion contrast-enhanced MR consists of multiple types of (semi-)quantitative parametric maps. These maps all
# quantify different characteristics, some of which may contain negative numbers.
def __init__(self, **kwa... |
a2f797b6aa562a93f47de4cd78a0e982660074324d14d7570bb56a355feaffa9 | Python | 1,756 | 43 | from imodelsx import submit_utils
from os.path import dirname
import os.path
repo_dir = dirname(dirname(os.path.abspath(__file__)))
# python /home/chansingh/llm-tree/experiments/01_train_model.py --use_cache 0 --subsample_frac 1 --model_name llm_tree --max_depth 3 --use_llm_refine 1
# python /home/chansingh/llm-tree/... |
420b3d21b7012c88c75cdabfd94b16e82111839b0417ee24867d29a129fccada | Python | 1,757 | 78 | import array
import pytest
import rpy2.rinterface as ri
ri.initr()
def test_init_from_seqr():
seq = [True, False, False]
v = ri.BoolSexpVector(seq)
assert len(v) == 3
for x, y in zip(seq, v):
assert x == y
def test_from_int_memoryview():
a = array.array('i', (True, False, True))
mv ... |
1bdedd2b858c86adf5d89ee1bc212d6f94304959a0a8a1e4d523354b8c746d74 | Python | 1,758 | 69 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
import os
# download model weights
import gdown
import shutil
from zipfile import ZipFile
# constant values
from .constants import RESET_COLOR_CODE
from .constants import GREEN_COLOR_CODE
from .constants import RED_COLOR_CODE
__author__ = ['Nico Curti']
__email__ = ['ni... |
5fed2ef36166046159ccd64950e025a3ac80a1f71795c17ec90f70cdc8c42c99 | Python | 1,758 | 57 | #!/usr/bin/env python
# =============================================================================
# MODULE DOCSTRING
# =============================================================================
"""
Test objects and function in the module ``tfep.loss``.
"""
# =================================================... |
30a15748069ebadc706472ac219439f39d556d150adca72244d1bb3e7f5ac5ef | Python | 1,759 | 55 | """
This module define the class StructurePredictionDataset
"""
import torch
import numpy as np
from scipy.spatial.distance import pdist, squareform
from datasets_pre_processing.generic_dataset import GenericDataset
class StructurePredictionDataset(GenericDataset):
"""
FINE TUNNING ON Structure
"""
d... |
7cf0576416789a3ec6602ac7dd9ff20d5be3c81c62effb5ae4b26c6170b82bfb | Python | 1,760 | 43 | """
Gregory Way 2016
PanCancer Classifier
scripts/process_copynumber.py
Usage: Run by initialize.sh to initialize repository or in command line
Output:
Two sample by gene matrices that indicate if the gene has 1) copy number gains
or 2) copy number losses in each sample
"""
import os
import pandas as pd
copy_input_... |
cb88d77b87936fae0f6aca585da3a74540d075388078f7d5b32f4fcd6201b088 | Python | 1,760 | 52 | # -*- coding: utf-8 -*-
from mne.gui._coreg_gui import CoregModel
import os
import sys
import glob
def calc_trans(subj, meg_file, subjects_dir, output_dir, task='EO', i='full'):
print(meg_file)
cm = CoregModel()
cm.mri.subject_source.trait_set(subjects_dir=subjects_dir)
cm.hsp.trait_set(file=meg_file... |
cdee3110cbdc530b026665635c06db999954b24b50c59bdf79ac3cf43c8ef72d | Python | 1,760 | 53 | import gzip
import os
import pandas as pd
from typing import Dict, List
def generate_bedpe_worker(meta: str,
sample: str,
infnm: str,
outdir:str,) -> bool:
"""Partition barcodes from a sample bedpe to different goups.
Outfile format... |
31c60242132dc8b1d18466dd1e037cadca0d2462ee72ee9b7d2023d24f708714 | Python | 1,761 | 46 | import sys
sys.path.append('./src/')
import os
import pandas as pd
import torch
import torch.nn.functional as F
import numpy as np
import tqdm
from sklearn import preprocessing
import src.generator_transformer as Generator
import argparse
import json
use_cuda = torch.cuda.is_available()
tokens = ['/', 'a', 'b', 'c', ... |
6edbfdc435bf53d4a781f4f2fe588445bad30e67d523191343a3a94137808e66 | Python | 1,761 | 62 | from typing import Any
import pytest
from pytest_celery import CeleryTestWorker, CeleryWorkerContainer, defaults
from pytest_docker_tools import build, container, fxtr
from celery import Celery
class CeleryLatestWorkerContainer(CeleryWorkerContainer):
"""Defines the configurations for a Celery worker container.... |
9b013633caea680ecb5a41ebfebf69e0fd62b1ed94ad26a36b2dc9b44c56c115 | Python | 1,761 | 50 | """Absence tests for the deleted capture/IR compatibility shims.
The kernel/ledger/projector layer and the ``ModuleEvent``/``BufferEvent``
event kinds were deleted in the backend migration; the compatibility shims
that kept their imports resolving were removed in the species-1 cleanup.
Contract now: the historical spe... |
abee3698d835e4b2f93d7b7adcaac3eae509f417377121a2bc273a658ae33c66 | Python | 1,761 | 57 | import sys
from ij import IJ, Prefs
# Fiji Jython interpreter implements Python 2.5 which does not
# provide support for argparse.
input_file = sys.argv[-8]
threshold_min = float(sys.argv[-7])
threshold_max = float(sys.argv[-6])
method = sys.argv[-5]
display = sys.argv[-4]
black_background = sys.argv[-3] == "yes"
out... |
fc3d40094698982fa5dde7213afd00c2f12a455efc5474b73d9dfdff50364854 | Python | 1,761 | 50 | import numpy as np
from .conf_ranker import ConfRanker
from rdkit.Chem import Mol
from typing import List, Any, Sequence
class PropertyRanker(ConfRanker):
def __init__(self,
descriptor_name: str = 'E',
ascending: bool = True) -> None:
super().__init__(name=descriptor... |
33426f47e4b0452b3df0d9095326eacb18176a1a696a0ab4c13167ae694bc8d7 | Python | 1,762 | 59 | from pathlib import Path
import pytest
from larvaworld.lib import reg, util
from larvaworld.lib.reg import config
from larvaworld.lib.reg.generators import ExpConf
def test_conf():
conftype = "Exp"
id = "dish"
id_new = "dish_test"
C = reg.conf[conftype]
ids = C.confIDs
conf = C.getID(id)
... |
70fd7df88dcd317327fc61321ec7486737f52d02a776de37702e9900a187e572 | Python | 1,762 | 52 | """Test built-in rater"""
import pathlib
import shutil
import tempfile
from unittest import mock
import h5py
from PyQt6 import QtCore
import pyjibe.head
data_path = pathlib.Path(__file__).parent / "data"
def test_rater_basic(qtbot):
mw = pyjibe.head.PyJibe()
td = pathlib.Path(tempfile.mkdtemp(prefix="rate... |
cff345ddfa8dd5cef0f20ad56b87ea3f0aed49b8ad9bc80f5b524b621d5ce670 | Python | 1,762 | 41 | from ipywidgets import interact, IntSlider, RadioButtons
import numpy as np
import matplotlib.pyplot as plt
class ImageSliceViewer3D:
def __init__(self, image, pred, figsize=(15,15), cmap='Greys'):
self.pred_orig = pred
self.image_orig = image
self.pred = pred
self.image = image
self.fi... |
5e656a6eefe4cf75f813262afd70276cfd929d73f2e78a76173fb00575fbb7a1 | Python | 1,763 | 48 | """Utilities to create reports and useful print outs."""
from specparam.reports.text import gen_methods_text
from specparam.reports.strings import (gen_version_str, gen_settings_str,
gen_freq_range_str, gen_methods_report_str)
####################################################... |
8d4c22cc046bb19cdd146c26ab69ae5e72cf6a728edef7c3072393367c4e29a5 | Python | 1,763 | 57 | # ---
# jupyter:
# jupytext:
# formats: ipynb,py:light
# text_representation:
# extension: .py
# format_name: light
# format_version: '1.5'
# jupytext_version: 1.4.2
# kernelspec:
# display_name: Python 3
# language: python
# name: python3
# ---
# # Check alignments
# Ch... |
b5b0635c3109f928df439291d3e31c20f479d4ba27fe066d288dffd1ba52cc50 | Python | 1,763 | 48 | from skmob.utils import gislib
import math
class TestClustering:
def setup_method(self):
self.point_1 = (43.8430139, 10.5079940)
self.point_2 = (43.5442700, 10.3261500)
self.decimal = 43.8430139
self.DMS = (43, 50, 34.85)
def test_get_distance(self):
output = gislib.... |
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