sha256 stringlengths 64 64 | language stringclasses 27
values | size int32 1 491k | lines int32 1 21.8k | content stringlengths 1 200k |
|---|---|---|---|---|
f90a408a384c0632265ecd3f18241a737993729796a742dbfe1d9a0f84d62504 | Python | 2,459 | 88 | import numpy as np
from stabl import data
from stabl.multi_omic_pipelines import multi_omic_stabl
from sklearn.model_selection import GroupShuffleSplit, GridSearchCV, RepeatedKFold
from sklearn.linear_model import Lasso, ElasticNet
from stabl.stabl import Stabl
from stabl.adaptive import ALasso
from sklearn.base import... |
ae9562fb5051c3ddb33903c1fb92b6f62af29c8e13b9a312a533f01784077904 | Python | 2,462 | 73 | # Run multiple time step integration with OpenMM for comparison to Molly
# Used OpenMM v8.4.0, Python v3.11.14
from openmm.app import *
from openmm import *
from openmm.unit import *
import os
data_dir = os.path.join(os.path.dirname(os.path.realpath(__file__)), "..", "data")
out_dir = os.path.join(data_dir, "openmm_t... |
312e660f282cc86aa95ed8e8f0e95f0907db4cfaab8a3bcbc91056f0ca700127 | Python | 2,464 | 88 | # This code is part of OpenFE and is licensed under the MIT license.
# For details, see https://github.com/OpenFreeEnergy/openfe
import glob
import itertools
import pathlib
import click
from plugcli.params import NOT_PARSED, MultiStrategyGetter, Option
# MOVE TO GUFE #################################################... |
d87dd79800364d5955442ae81cfaf20d6b9f1611a5314d629cfa4b442ae1d68c | Python | 2,464 | 91 | import numpy as np
from stabl import data
from stabl.multi_omic_pipelines import multi_omic_stabl
from sklearn.model_selection import GroupShuffleSplit, GridSearchCV, RepeatedKFold
from sklearn.linear_model import Lasso, ElasticNet
from stabl.stabl import Stabl
from stabl.adaptive import ALasso
from sklearn.base import... |
ba16af77be42f38031a6f22aeb1284723e877e0a5776026c08d19df2fb87ed2e | Python | 2,465 | 62 | #%%
from cluster_jobs.abstract_jobs.preprocess_abstract import AbstractPreprocessingJob
from os.path import join
import mne
import pandas as pd
#%%
class Preprocessing(AbstractPreprocessingJob):
job_data_folder = 'data_sbg_irasa'
def _get_age(self):
return self.raw.info['subject_info']['age']
de... |
dca754686e0f675773e7d3f99cdf91acd944fefe4bee20e2c456fbe1243b1ddc | Python | 2,465 | 68 | #!/usr/bin/env python
# Copyright 2017-2018 Biomedical Imaging Group Rotterdam, Departments of
# Medical Informatics and Radiology, Erasmus MC, Rotterdam, The Netherlands
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obt... |
748dd584281599ad2ef571b00a02f82563d88271e2d7f67239ca419943b336ea | Python | 2,466 | 91 | """ Dictionary to XML - Library to convert a python dictionary to XML output
Copyleft (C) 2007 Pianfetti Maurizio <boymix81@gmail.com>
Package site : http://boymix81.altervista.org/files/dict2xml.tar.gz
Revision 1.0 2007/12/15 11:57:20 Maurizio
- First stable version
"""
__author__ = "Pianfetti Mau... |
a037e4ff7392ba48c1044e3a643501bf37fd588d86905027cdd9465607b1637c | Python | 2,466 | 93 | import os
import solara
from mesa.examples.basic.schelling.model import Schelling, SchellingScenario
from mesa.visualization import (
Slider,
SolaraViz,
SpaceRenderer,
make_plot_component,
)
from mesa.visualization.components import AgentPortrayalStyle
def get_happy_agents(model):
"""Display a t... |
ec5ad5129cc92a88066bc08778b870c141dcdad7798817568015f2025a149530 | Python | 2,466 | 70 | """
Module: data_loader.py
Description:
- Load raw data (CSV/TSV), identify sequence & substrate columns,
encode y and split into train/val.
"""
import os
import pandas as pd
from sklearn.model_selection import train_test_split
from config import TRAIN_VAL_RATIO
from encoder import encode_sequences
def load_raw... |
a1c51d0c47f87c975d30f36d1317fca242e08561dcf7f137a222689b948ea259 | Python | 2,470 | 88 | import numpy as np
from stabl import data
from stabl.multi_omic_pipelines import multi_omic_stabl_cv
from sklearn.model_selection import GroupShuffleSplit, GridSearchCV, RepeatedKFold
from sklearn.linear_model import Lasso, ElasticNet
from stabl.stabl import Stabl
from stabl.adaptive import ALasso
from sklearn.base imp... |
19c3204be4ad7b6e6d7f98611a43662d501781c83025ac0fdb41e239ac8a3385 | Python | 2,472 | 78 | # This code is part of OpenFE and is licensed under the MIT license.
# For details, see https://github.com/OpenFreeEnergy/openfe
import pytest
from openfe.protocols.openmm_afe import (
AbsoluteBindingProtocol,
)
@pytest.fixture()
def default_settings():
return AbsoluteBindingProtocol.default_settings()
def... |
74cc5d7ebd6957fc97ed1746cb9d293daf247ddff392385c98719cfbd3aa26c8 | Python | 2,473 | 92 | # AUTOGENERATED! DO NOT EDIT! File to edit: 90_utilities.ipynb (unless otherwise specified).
__all__ = ['text2float', 'progbar', 'switch', 'NamedTuple', 'makedir']
# Cell
from tqdm import tqdm
import numpy
import os
# Cell
def text2float(val):
"""A utility function for stably reading strings and return floats i... |
8122ef5ba8078bdac803a6983416c5666a92e63fa3aa90b3610e5cd9112e4c71 | Python | 2,476 | 60 | #!/usr/bin/python3
##################################################################################
#
# MIT License
#
# Copyright (c) 2025 Kevin Rockenbach, Agnieszka Golicz
#
# Permission is hereby granted, free of charge, to any person obtaining a copy
# of this software and associated documentation files (the "So... |
9aa21bfbea06a0b31436954a50ef0d9fc226776993a5d99399c8be29efe17b98 | Python | 2,476 | 71 | from argparse import ArgumentError, ArgumentParser, Namespace
import logging
from pathlib import Path
import sys
from chemprop.cli.utils import Subcommand
from chemprop.utils.v1_to_v2 import convert_model_file_v1_to_v2
from chemprop.utils.v2_0_to_v2_1 import convert_model_file_v2_0_to_v2_1
logger = logging.getLogger(... |
c3ef225e25f53b55d53f58abb26d172e61b0c77d2023e56039f623d3880af369 | Python | 2,476 | 56 | import os
from os.path import join
import nnunetv2
from nnunetv2.paths import nnUNet_extTrainer
from nnunetv2.utilities.find_class_by_name import recursive_find_python_class
def recursive_find_trainer_class_by_name(trainer_name: str):
# Import here is necessary to avoid circular import
# this function is use... |
913e68ff278e4f087d93af96707cdbc7e3689f904d3d7709e8c6178080ab3796 | Python | 2,479 | 122 |
import pandas as pd
import numpy as np
import joblib
import argparse
import sys
parser = argparse.ArgumentParser(
description="Predict Overall.Score for new integration methods using a trained Random Forest model"
)
parser.add_argument(
"--model",
required=True,
help="Path to trained RF model (.jobli... |
e2a5d0e479005275922027e555b39686532bff304844152b1f50db9064201450 | Python | 2,480 | 68 | #!/bin/python
"""
Script for registering and processing microglia ASAP snRNA-seq samples for Substantia Nigra (SN).
Workflow steps and notes are identical to PFC and PUT scripts.
"""
import truster
import pandas as pd
import os
# Paths to references and configs
cellranger_index = "/scale/gr01/shared/common/genome/10... |
4684434f4b785b52c5ddb3e7f2f117790a0745d2af59761e8c9b79629ee03d7d | Python | 2,482 | 91 | """Per-atom pKa prediction for MolGpKa.
Vendored from MolGpKa (https://github.com/Xundrug/MolGpKa), MIT License.
Patched for SMILES2Docking:
* Package-relative imports and package-local model weights.
* Models are loaded once and cached (the upstream code reloaded the weights
on every molecule).
"""
from __fu... |
283d14adbe42ce0df289cafb81c8adf5d421c58e88f6f3f8c14cb4e319f34417 | Python | 2,486 | 90 | import statsmodels.api as sm
fig, ax = plt.subplots(figsize=(12, 4))
fig.gca().spines["top"].set_color("lightgray")
fig.gca().spines["right"].set_color("lightgray")
sm.graphics.tsa.plot_acf(
dfc["count"], lags=2*60, ax=ax, title="Autocorellation Function"
)
plt.ylim(-0.1, 1.1)
fig.show()
from NeuroPy... |
b946e8a4e745abcbf23eafb5eff2ff06862bb6d3389c3872914d5c821435ee3e | Python | 2,488 | 72 | import pytest
import networkx as nx
import numpy as np
import pandas as pd
from navis.models.network_models import (TraversalModel, BayesianTraversalModel)
def test_traversal_models():
models = (TraversalModel, BayesianTraversalModel)
G = nx.path_graph(10, create_using=nx.DiGraph)
G.add_edge(0, 9)
G.... |
bb1e4421a45e0d01f5b127802236e7f3467d7a8f02653d00def3345a71f9fba2 | Python | 2,488 | 98 | """ Created on Mon Aug 14 16:19:42 2023
@author: dcupolillo """
class Palette:
def __init__(self) -> None:
"""
Define color attributes
Returns
-------
None.
"""
self.black = Color('#181c21')
self.dark = Color('#1c2128')
self.d_dark = ... |
f25a4172b69d4c463ab0b5607e78634c1da4252df7e3bea661a536f68ab23689 | Python | 2,488 | 87 | import numpy as np
import neo
import quantities as q
np.random.seed(42)
def generate_poisson_spike_train(rate, T, dt):
"""
Generates a Poisson spike train as a Boolean array.
Parameters:
- rate: Firing rate in Hz.
- T: Total simulation time in ms.
- dt: Time step in ms.
Returns:
- sp... |
506e6cfc1a666d846a1a35dec829d8090b4e9ae4bbc190deef552572674b9d0c | Python | 2,492 | 76 | import pytest
import pickle
from hsnn import utils
from hsnn.analysis import ResultsDatabase
from hsnn.analysis.png import detection, refinery
SAMPLES_DIR = utils.BASE_DIR / "tests/data/detection"
@pytest.fixture(scope="module")
def real_data():
"""Loads the real data samples extracted from the notebook."""
... |
aee879fc27a8c86c31abbf7e1da98189cf056b3a5e58fb42703868f97e4c1247 | Python | 2,492 | 90 |
""" Utilities for distributed training. """
__author__ = "Fabi Bongratz"
__email__ = "fabi.bongratz@gmail.com"
import os
import datetime
import torch.distributed as dist
from torch.utils.data import DataLoader
from torch.utils.data.distributed import DistributedSampler
def cleanup():
""" Cleanup ddp process g... |
0b6c43c08bfb0e2eeeae7ef9f625cdb190714a70deeac6becf513e9eb173657b | Python | 2,497 | 58 | # -*- coding: utf-8 -*-
# Copyright (c) Facebook, Inc. and its affiliates.
from detectron2.config import CfgNode as CN
def add_pointrend_config(cfg):
"""
Add config for PointRend.
"""
# We retry random cropping until no single category in semantic segmentation GT occupies more
# than `SINGLE_CATE... |
4a96fcbc3ebbcc27128f26edd965c0dae058f95ab3a7c19a5141b71cd94f2c74 | Python | 2,497 | 82 | import os
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
from scipy.cluster.hierarchy import linkage, fcluster
from scipy.stats import zscore
import numpy as np
input_path = 'results/preprocessed/normalised_summary.csv'
output_folder = 'results/plot_heatmap/'
if not os.path.exists(output_... |
f7dddbe0360faa01ceb81e8a47ec1c21e6569da6492f0a2dffd53565c0c3f393 | Python | 2,497 | 84 | import numpy as np
import pandas as pd
RIF_METHODS = {
"BACTEC RIF": ["bactec_rifampicin"],
"LJ RIF": ["le_rifampicin"],
"HAIN RIF": ["hain_rifampicin"],
"LPA-other RIF": ["lpaother_rifampicin"],
"Xpert RIF": ["genexpert_rifampicin"],
"Truenat RIF": ["truenat_rifampicin"],
}
FQ_METHODS = {
... |
f890b0a2f5276acf0d1d8cea3e3a79c451bbc4248efc93711b378f8525cd64ca | Python | 2,498 | 90 | import numpy as np
from stabl import data
from stabl.multi_omic_pipelines import multi_omic_stabl_cv
from sklearn.model_selection import GroupShuffleSplit, GridSearchCV, RepeatedKFold
from sklearn.linear_model import Lasso, ElasticNet
from stabl.stabl import Stabl
from stabl.adaptive import ALasso
from sklearn.base imp... |
664cae6572619d452b42017f34572503841ae8304153a4d7908498ff200a68a9 | Python | 2,499 | 66 | import numpy as np
import numpy.typing as npt
import pandas as pd
import xarray as xr
from ._types import DeltaTuple
pidx = pd.IndexSlice
def get_deltas(group: pd.DataFrame, layer: int, surrogates: xr.DataArray,
deltas: DeltaTuple, threshold: float = 0.0) -> DeltaTuple:
"""Get delta values for n... |
e57066b6db917a707f89b76f97d0924d1ad846d7587e5be3e0e57f80d5874a86 | Python | 2,505 | 65 | import json
import sys
import tempfile
import unittest
from pathlib import Path
import pandas as pd
SCRIPTS = Path(__file__).resolve().parents[1] / "scripts"
sys.path.insert(0, str(SCRIPTS))
from build_analysis_input import build_analysis_input
class AnalysisInputBuilderTests(unittest.TestCase):
def test_buil... |
defc96ef8cb9cbcf0d0dcbcd7c9d69d14727fa623b37c399e98623a298ddf9b8 | Python | 2,507 | 92 | from mesa.examples.advanced.wolf_sheep.agents import GrassPatch, Sheep, Wolf
from mesa.examples.advanced.wolf_sheep.model import WolfSheep, WolfSheepScenario
from mesa.visualization import (
CommandConsole,
Slider,
SolaraViz,
SpaceRenderer,
make_plot_component,
)
from mesa.visualization.components i... |
cad0cf542402a7d074cc9befa50840345e429008279a82b2497842a04fd7b501 | Python | 2,508 | 67 | #!/usr/bin/env python
# Copyright 2017-2020 Biomedical Imaging Group Rotterdam, Departments of
# Medical Informatics and Radiology, Erasmus MC, Rotterdam, The Netherlands
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obt... |
79ace6b2f2ee4d2f9b78ad42008353690c7030009d8a91291f699e67a74b06de | Python | 2,509 | 65 | #!/usr/bin/env python3
"""Run Snakemake over one or more trials for an experiment[, checkpoint].
Example:
./scripts/run_main_workflow.py path/to/expt_dir 0 1 --chkpt -1 -v
"""
import argparse
import logging
import subprocess
from hsnn.core.logger import get_logger
logger = get_logger(__name__)
def main(opt: a... |
57ce0711b689394b3050a01b464043673d6587481471e875f3f7a3a436601382 | Python | 2,512 | 74 | # Copyright (c) Facebook, Inc. and its affiliates.
from abc import ABCMeta, abstractmethod
from typing import Dict
import torch.nn as nn
from detectron2.layers import ShapeSpec
__all__ = ["Backbone"]
class Backbone(nn.Module, metaclass=ABCMeta):
"""
Abstract base class for network backbones.
"""
de... |
3a74592dffd132cee9b7cc40913610f53cdee3f5069f83936ae132e9fb3c5e31 | Python | 2,513 | 84 | import numpy as np
from scipy.stats import chi2_contingency
def chisquare_test(ref: np.ndarray, obs: np.ndarray) -> np.ndarray:
"""
Multivariate chi-square test for each categorical variable abundance.
Parameters
----------
ref : np.ndarray
Reference abundance of each categorical variable... |
bf7fef8ba1ef7c329f9ac6969c21eae2b22308f8c1dea985efc40da27fd8e2fb | Python | 2,513 | 76 | # -*- coding: utf-8 -*-
"""
Created on Tue Jul 12 10:51:00 2016
@author: Luciano Masullo
@pep8: Federico Barabas
"""
import numpy as np
class sin2D:
def __init__(self, imSize=100, wvlen=10, theta=15, phase=.25):
self.imSize = imSize # image size: n X n
self.wvlen = wvlen # wavelength (n... |
5e388f636c84ad4353cf17f216c7eb66ab70aa6026dc5a2c10aafbc0ce1b9a4c | Python | 2,515 | 72 | import detectron2.data.transforms as T
from detectron2.config.lazy import LazyCall as L
from detectron2.layers.batch_norm import NaiveSyncBatchNorm
from detectron2.solver import WarmupParamScheduler
from fvcore.common.param_scheduler import MultiStepParamScheduler
from ..common.data.coco import dataloader
from ..commo... |
669f5bfac531adcf32e16a2f345507a45cd371a728cf10b87c14f30942b01780 | Python | 2,515 | 58 | from SPIDER import train_SPIDER, Cal_knn_expression, Cal_Spatial_Net, mclust_R
import os, pickle, pandas as pd
import scanpy as sc, numpy as np
import sklearn
from sklearn.metrics import normalized_mutual_info_score, homogeneity_score
from sklearn.metrics.cluster import adjusted_rand_score
import sys
def run_trainin... |
ef7d0eca3a883b9637d227a7cc876a4a59bd87c3ea187b99f0084ca46e2d9a90 | Python | 2,524 | 76 | import torch
from torch import Tensor
import torch.nn as nn
import torch.nn.functional as F
from torchmetrics import Metric
from typing import Optional
class CosineDistanceLoss(nn.Module):
def __init__(self):
super().__init__()
def forward(
self,
input1: torch.Tensor,
input2: ... |
91d87ec5dc10533338933e9e4b92aca64024ec888d997f6810e2c32537f616be | Python | 2,526 | 77 | import torch
from transformers import AutoTokenizer, EsmModel, BatchEncoding
from typing import List, Dict
import os
class ESM2Encoder(torch.nn.Module):
def __init__(
self,
pretrained_model_name_or_path: str = "../esm2_model"
):
"""
Args:
pretrained_model_name_or_pa... |
359de7c90b089d2bd6d2e0916de0bfd3222bc532a767b4bfc9a24bc3b93b882b | Python | 2,527 | 67 | #!pip3 install pandas matplotlib pathlib seaborn --user
#python proteinGroupsCompareTTP.py "Sequence" L:\promec\TIMSTOF\LARS\2024\240626_Mira\MiraPep.tsv L:\promec\TIMSTOF\LARS\2024\240626_Mira\MiraPep2.tsv
# %% setup
import sys
from pathlib import Path
import pandas as pd
import matplotlib.pyplot as plt
from matplotl... |
6e179c6a64c72c4ed6652f960371917ecfe17315034ffa169f326b25e026e975 | Python | 2,527 | 76 | """Raw neural trace with stim artifacts and detected spike overlay."""
import sys
from pathlib import Path
sys.path.insert(0, str(Path(__file__).resolve().parents[1]))
from utils.plotting import apply_global_style, PALETTE
from utils.config import DATA_DIR, OUTPUT_DIR
import numpy as np
import matplotlib.pyplo... |
51de94df493032e0b55ff3631eb48fab479826c7fd63df9f0b4228758e7f7fc6 | Python | 2,530 | 67 | """Handles loading and automatic reassembly of model files."""
import os
import shutil
from lamareg.utils.file_splitter import reassemble_file
import urllib.request
MODEL_URLS = {
"synthseg_robust_2.0.h5": [
"https://github.com/MICA-MNI/LAMAR-Models/raw/refs/heads/main/models/synthseg_robust_2.0.h5.000",
... |
dbc7339a3c145832115c4b81e877916bcfdb1c7b53fee7b8e92b66bef9b85296 | Python | 2,533 | 82 | from mesa.examples.advanced.sugarscape_g1mt.model import SugarscapeG1mt
from mesa.visualization import Slider, SolaraViz, SpaceRenderer, make_plot_component
from mesa.visualization.components import AgentPortrayalStyle, PropertyLayerStyle
def agent_portrayal(agent):
return AgentPortrayalStyle(
x=agent.cel... |
d79cfe0d8fe7a1c57bd7b3ea2d935eedccdb03aa30867ef35b8e3f905e2a44df | Python | 2,536 | 95 | import torch
import os
from glob import glob
import argparse
def load_class_image_list(path):
class_name = os.path.basename(path).split(".")[0]
with open(path, "r") as f:
lines = f.readlines()
lines = [line.strip().split(".")[0] for line in lines]
return (class_name, lines)
def get_semantic(... |
baae10690b907809b224db31862ffe23e93e731736b474a5962335f38f6b4b13 | Python | 2,539 | 70 | import pandas as pd
import pingouin as pg
import seaborn as sns
from matplotlib import pyplot as plt
from mpl_toolkits.axes_grid1 import make_axes_locatable
# Read data (from MATLAB output)
data = pd.read_csv('alpha_beh_up_to_800ms.csv')
sel_sub = data['subject_valid'].astype(bool)
fig, axes = plt.subplots(1, 3, figs... |
6476fceecc4517cd9d28b24d8cb1a00bf752f2283aed0463f00c1adf43820026 | Python | 2,540 | 92 | import math
import networkx as nx
import mesa
from mesa import Model
from mesa.discrete_space import CellCollection, Network
from mesa.examples.basic.virus_on_network.agents import State, VirusAgent
def number_state(model, state):
return sum(1 for a in model.grid.all_cells.agents if a.state is state)
def numb... |
7775f7dac217a5ba59dbb493fa489d94d2e56088996e4e609a8f2a93ed17d87e | Python | 2,540 | 67 | import json
import sys
from pathlib import Path
import pandas as pd
import pytest
SCRIPTS = Path(__file__).resolve().parents[1] / "scripts"
sys.path.insert(0, str(SCRIPTS))
from prepare_sensitivity_splits import sensitivity_config
from run_model_sensitivity import compare_metric_results, compare_shap_results
def ... |
d11c9f3eaa60d7dd6f7c4331a0f693df2bdfef4bdf396f162c1e6782bf4763d9 | Python | 2,540 | 62 | from openmm.app import *
from openmm import *
from openmm.unit import *
# Calculate forces with Gromacs and OpenMM for comparison to Molly using a99SB-disp force field
# Used OpenMM v8.4.0, Python v3.12.12 and Gromacs 2021.4
# To run this script, .gro and .top files need to be prepared with Gromacs' pdb2gmx and editc... |
08571608b3c7e3610384ed298233b82f6726ed4e48dca3d956e31ece2abb5da6 | Python | 2,541 | 84 | #!/usr/bin/env python3
# Copyright (c) Facebook, Inc. and its affiliates.
"""
DensePose Training Script.
This script is similar to the training script in detectron2/tools.
It is an example of how a user might use detectron2 for a new project.
"""
from datetime import timedelta
import detectron2.utils.comm as comm
... |
4bc53386026b8fe77b0af511e89277d9699e1729d92a14adb9f294e492d3ba1a | Python | 2,541 | 75 | # -*- coding: utf-8 -*-
# Copyright (c) Facebook, Inc. and its affiliates.
# pyre-unsafe
import logging
import numpy as np
from typing import Any, Callable, Dict, List, Optional, Union
import torch
from torch.utils.data.dataset import Dataset
from detectron2.data.detection_utils import read_image
ImageTransform = C... |
5451c3274f00bc02ac31c183b41835aa82f3e06048228b17ee84e585b2013d5f | Python | 2,541 | 66 | import numpy as np
from sklearn import datasets
def _normalize(v):
if np.sum(v) == 0:
w=np.copy(v)
w[0]=1
return w
else:
return v/(np.sum(v))
def _sample_parameters(num_clusters, num_dim, **sampler_x_args):
parameters_gen={}
parameters_gen['cluster_prop'] = _normalize(... |
e9362fb164981d522406e9556cd896ff1c90d472f995493f31ab382da1203678 | Python | 2,542 | 97 | import numpy as np
import pandas as pd
from sklearn.feature_selection import SelectKBest, f_classif
from sklearn.preprocessing import StandardScaler
np.random.seed(42)
# -----------------------------
# 1. Load data
# -----------------------------
def loadDataset():
X = pd.read_csv("./data/data_0.csv", header=Non... |
f8ab717407587e84dd5fca86733970512f643321fd69c4d1c2532b8312191a2d | Python | 2,547 | 81 | '''
Generates .sumstats and .l2.ldscore/.l2.M files used for simulation testing.
'''
from __future__ import division
import numpy as np
import pandas as pd
N_INDIV = 10000
N_SIMS = 1000
N_SNP = 1000
h21 = 0.3
h22 = 0.6
def print_ld(x, fh, M):
l2 = '.l2.ldscore'
m = '.l2.M_5_50'
x.to_csv(fh + l2, sep='\t... |
ab831ee0e06fa5b87b193aa9b1f7c28744a996b7583a7f989973b19a0a552fb3 | Python | 2,549 | 89 | import numpy as np
import eelbrain as eb
from sklearn.decomposition import PCA
import pandas as pd
def do_boosting(avg, fwd, boosting_kwargs):
#%get channels post ecg
start_idx = np.where(avg.keys() =='ECG003')[0][0] + 1
tmin = 0
tstep = 0.01
nsamples = avg.shape[0]
time_course = eb.U... |
4180e0a7096d6c0d3c94fb25dee9099b5ac75310e32d825fb23586c8dad33ee4 | Python | 2,552 | 96 | """ Show example plots with different stp paramter sets """
import matplotlib.pyplot as plt
import pandas as pd
import numpy as np
from test_utils import generate_regular_spike_train, generate_poisson_spike_train
# define spike train
rate = 30
T = 500
dt = 0.1
time_arr = np.arange(0, T, dt)
# Regular spike trains
s... |
0f75af0f0fe066cb86d882012148caebca31c718796c462f09cd8cb80f989c7a | Python | 2,560 | 80 | import pytest
from openfecli.fetching import FetchablePlugin, PkgResourceFetcher, URLFetcher
from .conftest import HAS_INTERNET
class FetcherTester:
@pytest.fixture
def fetcher(self):
raise NotImplementedError()
def test_resources(self):
raise NotImplementedError()
def test_plugin(... |
5136bd97547635b0b644a08c13fc86eacce13c877737877e04b23f73f41a45d2 | Python | 2,562 | 113 | """
author:CBJ
The utility functions module includes:
- Random seed setting
- FWI danger level classification
- Evaluation metric calculation
- Model parameter statistics
"""
import numpy as np
import torch
import random
import logging
from sklearn.metrics import mean_squared_error, mean_absolute_error, r2_score
logg... |
e38439f847c064be701469d31df6cbf55888453633b3ddb2297bb0f6535ba669 | Python | 2,564 | 117 | import scanpy as sc
import time
import scanorama
combined_adata_path = "PATH_TO_INPUT/combined_adata.h5ad"
combined_adata = sc.read_h5ad(combined_adata_path)
start_time = time.time()
sc.pp.scale(combined_adata)
sc.tl.pca(combined_adata)
sc.external.pp.scanorama_integrate(
combined_adata,
key='batch',
ba... |
069d7896497110f5b3cb5fb7163b77c2765a5571be1357ec2692103193481132 | Python | 2,565 | 75 | # This script is part of navis (http://www.github.com/navis-org/navis).
# Copyright (C) 2018 Philipp Schlegel
#
# This program is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation, either version 3 of... |
3687abcdb270fa6abcf272b0a1bb4f49bfa5dfc4399db7a94d89eac642d21deb | Python | 2,566 | 52 | #C:\\Users\\animeshs\\AppData\\Local\\Programs\\Spyder\\Python\\python.exe -m pip install datatable
import datatable as dt # pip install datatble
fileName="C:/Users/animeshs/Downloads/SILACDIA2/report.tsv"
df = dt.fread(fileName).to_pandas()
import matplotlib.pyplot as plt
import numpy as np
plt.scatter(np.log2(df['PG... |
7426982a3f2e933fa3b90b47e35f195b382e97ca6daefcfcd6e6f44e18ff11ed | Python | 2,567 | 89 | # Copyright (c) Facebook, Inc. and its affiliates.
# pyre-unsafe
from typing import Optional
from torch import nn
from detectron2.config import CfgNode
from .cse.embedder import Embedder
from .filter import DensePoseDataFilter
def build_densepose_predictor(cfg: CfgNode, input_channels: int):
"""
Create an... |
bd32a680024f398efa381744949a5c7a5d313db94279d98cccb202c18e912843 | Python | 2,570 | 61 | #!pip3 install pandas matplotlib pathlib --user
#python proteinGroupsCombineTTP.py L:\promec\TIMSTOF\LARS\2024\240626_Mira\2de755bb378949183b1b6b89a359e507\processing-run
# %% setup
import sys
from pathlib import Path
import pandas as pd
# %% meta
#pathFiles=Path("L:/promec/TIMSTOF/LARS/2024/240626_Mira/b3093c79d999b93... |
5e79a750ab84ef69e789008e335ee2da1c12f1550c986b2b3c556101808ed2f7 | Python | 2,572 | 86 | #!/usr/bin/env python
#
# Copyright (c) 2017 10X Genomics, Inc. All rights reserved.
#
from __future__ import annotations
from typing import TYPE_CHECKING
import martian
import cellranger.constants as cr_constants
import cellranger.preflight as cr_preflight
import cellranger.vdj.preflight as vdj_preflight
from cell... |
047c094a8133f841098760e3a33b959baa0ca654483db5a93b2e9b6c0ea18d5c | Python | 2,575 | 76 | from setuptools import setup, find_packages
from pathlib import Path
from runpy import run_path
from extreqs import parse_requirement_files
HERE = Path(__file__).resolve().parent
verstr = run_path(str(HERE / "navis" / "__version__.py"))["__version__"]
install_requires, extras_require = parse_requirement_files(
... |
7653d25956ba62698bb20f735d5b5eacab1875ac495d5960428ac6009d5cb710 | Python | 2,575 | 86 | """
sphinxcontrib-sass
https://github.com/attakei-lab/sphinxcontrib-sass
Kayuza Takei
Apache 2.0
Modified to:
- Write directly to Sphinx output directory
- Infer targets if not given
- Ensure ``target: Path`` in ``configure_path()``
- Return version number and thread safety from ``setup()``
- Use compressed style by d... |
a5a57c34eb990e00f6e34f5ef4ad996e85d8019dba5076b4ed0bc1a651673cee | Python | 2,578 | 93 | import nibabel as nib
import numpy as np
from astropy.convolution import convolve as nan_convolve
logfile = open(snakemake.log[0], "w")
print(f"starting", file=logfile, flush=True)
# this function solves the Laplace equation for Anterior-Posterior, Proximal-distal, and Inner-Outer axes of the hippocamps
convergence_t... |
d40e44d2b37c9b4d76135cfeca933bdba57de32f4247942e0326bb88b15ea139 | Python | 2,580 | 73 | # Python04.py
# IJ BAR: https://github.com/tferr/Scripts#scripts
####################################################
# 4. Functions and modules
####################################################
# Functions are defined with <def>. Return values are
# specified by a <return> statement. Here is a function
# without a... |
3580b228d918b60fdc5d4164ea33d93b99ef52f5be759b07209524967164440b | Python | 2,581 | 84 | import torch
import torch.nn as nn
import torch.nn.functional as F
def do_CL(X, Y, args):
if args.normalize:
X = F.normalize(X, dim=-1)
Y = F.normalize(Y, dim=-1)
criterion = nn.CrossEntropyLoss()
B = X.size()[0]
logits = torch.mm(X, Y.transpose(1, 0)) # B*B
logits = torch.div(logi... |
761dd2668263e4b0ec5dee83a5a09f2e8578f992b47e5ba9906e93ed6b42a7d7 | Python | 2,582 | 79 | #! /usr/bin/env python
# -*- coding: utf-8 -*-
# vim:fenc=utf-8
import os
import sys
sys.path.append(os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
import torch
import os.path as osp
import torch_geometric.transforms as T
from torch_sparse import coalesce
from torch_geometric.data import InMemoryDatase... |
efc17b4733e1d293281658fb3bafe72d4de4423754ea49433c07c6bac5364af2 | Python | 2,582 | 81 | """Raw vs filtered individual spike waveforms."""
import sys
from pathlib import Path
sys.path.insert(0, str(Path(__file__).resolve().parents[1]))
from utils.plotting import apply_global_style
from utils.config import DATA_DIR, OUTPUT_DIR
import numpy as np
import matplotlib.pyplot as plt
import matplotlib
... |
f6d5ecbe9ebc54e976d5bd868b82f645b6af9c8145b2269e26cbc084b83b5d4d | Python | 2,583 | 84 | # Copyright (c) Facebook, Inc. and its affiliates.
import logging
from contextlib import contextmanager
from functools import wraps
import torch
__all__ = ["retry_if_cuda_oom"]
@contextmanager
def _ignore_torch_cuda_oom():
"""
A context which ignores CUDA OOM exception from pytorch.
"""
try:
... |
6a17a02ee14a204107ebee9126438fb468a75188995bd18c5ca695dd5f508d90 | Python | 2,590 | 95 |
""" Base class for voxel2mesh models """
__author__ = "Fabi Bongratz"
__email__ = "fabi.bongratz@gmail.com"
from abc import ABC, abstractmethod
import torch
import torch.nn as nn
class V2MModel(nn.Module, ABC):
""" Base class for Voxel2Mesh models """
def __init__(self):
super().__init__()
... |
5f3e7d2a580d392ef44a02b2f9573139f116154fc29423c39c54f1f0963b0a67 | Python | 2,595 | 79 | from typing import List
import matplotlib.pyplot as plt
import numpy as np
from .attack_result import AttackResult
def show_adversarial_examples(
results: List[AttackResult],
target_image,
layer_name,
num_iterations,
alpha,
title=None,
):
plt.figure(figsize=(15, 40))
images_per_row =... |
a5b18752f2cc8eb490bf206cf6afa78781b1a972c6fed3a72fc0b25d3f2d1e06 | Python | 2,595 | 63 | import sys
#!pip3 install pandas --user
#!pip3 install pathlib --user
from pathlib import Path
if len(sys.argv)!=2: sys.exit("REQUIRED: pandas, pathlib; tested with Python 3.8.5\n","USAGE: python dePep.py <path to folder containing allPeptides.txt file(s) like \"L:/combined/txt\" >")
pathFiles = Path(sys.argv[1... |
48580d55e998a0dbe19b4114fc9b6be0ffeaa94089bb62ebe8f7322730a1c35c | Python | 2,596 | 87 | """
Module: config.py
Description:
- Global configuration and default hyperparameters
"""
import os
# Base directories
BASE_DIR = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
DATA_DIR = os.path.join(BASE_DIR, 'dataset')
INPUT_DIR = os.path.join(BASE_DIR, 'input')
LOG_DIR = os.path.join(BASE_DIR, 'log... |
df3ee7b2863ee1a20298b957bf481091cd2a348d5aaf08a452c8ad081f2a5a1c | Python | 2,598 | 79 | # T2P histogram of all units vs modulated units, pyramidal/interneuron split.
import sys
from pathlib import Path
sys.path.insert(0, str(Path(__file__).resolve().parents[1]))
import matplotlib
matplotlib.use('Agg')
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
from utils.config import RAW_DF_... |
f2f85b8a092e4fee07b1c6763dd44566592a1a780a74cec20f7e877fb1d4ba9b | Python | 2,601 | 55 | from typing import Tuple, Union, List
from batchgenerators.augmentations.utils import resize_segmentation
from batchgenerators.transforms.abstract_transforms import AbstractTransform
import numpy as np
class DownsampleSegForDSTransform2(AbstractTransform):
'''
data_dict['output_key'] will be a list of segmen... |
ca481324b511ef62fd066e966f3b871d01f43be71b2793e5206430825360fcbf | Python | 2,602 | 73 | import inspect
import torch
from detectron2.utils.env import TORCH_VERSION
try:
from torch.fx._symbolic_trace import is_fx_tracing as is_fx_tracing_current
tracing_current_exists = True
except ImportError:
tracing_current_exists = False
try:
from torch.fx._symbolic_trace import _orig_module_call
... |
e25f2f2f46de597ee960b2cdb0452124bf8f9f667a85c634ca52cd46c5671512 | Python | 2,605 | 61 | #!/usr/bin/env python
# Copyright 2017-2018 Biomedical Imaging Group Rotterdam, Departments of
# Medical Informatics and Radiology, Erasmus MC, Rotterdam, The Netherlands
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obt... |
d8ba5e36700f0d19c9af058ed752fdb437c156f81650ab42b16ab82e618e844b | Python | 2,606 | 92 | import numpy as np
import albumentations as albu
from albumentations.core.transforms_interface import ImageOnlyTransform
from albumentations.pytorch import ToTensor
from skimage.filters import apply_hysteresis_threshold
def scale(arr):
"""
Scales the input array to be in the range [0, 1] by subtracting the mi... |
15e3dfd5d55abf99a88a3c7db76fd7cae60f01e53e934da73e727c65e77f2304 | Python | 2,609 | 56 | import sys
if len(sys.argv)!=3: sys.exit("\n\nREQUIRED: pandas! Tested with Python 3.7.9 \n\nUSAGE: python resultsGroupby.py <path to file of interest like \"L:\promec\mqpar.xml.1623227664.results\combined\txt\proteinGroupsCombine.py> <column of interest like \"Score\"\n\n")
#python resultsGroupby.py "L:\promec\USERS\S... |
9b58ada3f5530a77fa9d4805175962799cf7ec483e01fff4f208db0ea697d54e | Python | 2,609 | 70 | import bisect
import numpy as np
import albumentations
from PIL import Image
from torch.utils.data import Dataset, ConcatDataset
class ConcatDatasetWithIndex(ConcatDataset):
"""Modified from original pytorch code to return dataset idx"""
def __getitem__(self, idx):
if idx < 0:
if -idx > le... |
a4db8f5bb8d25015549c17cecd567df89bb03c0f3fec7426fcbbde8d5fda9430 | Python | 2,611 | 73 | # Python01.py
# IJ BAR: https://github.com/tferr/Scripts#scripts
####################################################
# 1. Basics
####################################################
# This is a comment (typically single line)
"""
Tripple quotes are used for large multi-line comments, and
typically to document functio... |
c22b4fd5f2331e5ced4a17d8907d25faa66c36158339cdd43e158039cd68b6d9 | Python | 2,613 | 69 | #!/usr/bin/env python
# Copyright 2016-2020 Biomedical Imaging Group Rotterdam, Departments of
# Medical Informatics and Radiology, Erasmus MC, Rotterdam, The Netherlands
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obt... |
685394405c496dba97e08617b5fedeb13be134c70c2509563ea56dad8c77d5f4 | Python | 2,614 | 85 | # Copyright (c) Facebook, Inc. and its affiliates.
import logging
import numpy as np
import pprint
import sys
from collections.abc import Mapping
def print_csv_format(results):
"""
Print main metrics in a format similar to Detectron,
so that they are easy to copypaste into a spreadsheet.
Args:
... |
31f8b32f130ea23c64aaef33dad2cc794b95886b027d816e0d59d699f08776a9 | Python | 2,617 | 82 | import torch
from stoic.utils import beam_search, top_n_stoichiometry_combinations
def test_top_n_stoichiometry_combinations_returns_n_items() -> None:
logits = torch.tensor([[2.0, 0.1], [0.2, 1.7]])
results = top_n_stoichiometry_combinations(logits, n=2, class_labels=[1, 2])
assert len(results) == 2
... |
52b322b9281fc94b73258e5ebb611e2f74636aa726d59f27b5ca0e628fec7a3b | Python | 2,620 | 65 | #!/usr/bin/env python3
"""Extract Tables 1-7 of doi:10.1111/psyp.70385 from the Europe PMC JATS XML
(PMC13542476) into data/tables.json: header, rows (all cells as strings),
caption and footnotes. A superscript footnote marker is rendered as a caret
plus the letter (e.g. '12^a'), never run together with the value, so t... |
a64b6a29a6b39a0d05dcde0faab1971fcf68f1b0e9cde775d81ed79be7229999 | Python | 2,620 | 99 | import warnings
from lightning import pytorch as pl
import pytest
from chemprop import models, nn
from chemprop.models import multi
warnings.filterwarnings("ignore", module=r"lightning.*", append=True)
@pytest.fixture(scope="session")
def mpnn(request):
message_passing, agg, *act = request.param
ffn = nn.R... |
9f3939839a92351086b726ad12718653c7915acf9769f1cd32a55a2868e553a6 | Python | 2,621 | 77 | #!/usr/bin/env python3
#
# Copyright (c) 2020 10X Genomics, Inc. All rights reserved.
#
"""Utils for feature-barcoding technology."""
# Do not add new things to this module.
# Instead, either find or create a module with a name that better describes
# the functionality implemented by the methods or classes you want to... |
11d838314fadff156e90c0d68d4f600b8de303e29a31d0b1f8956e9ef7014624 | Python | 2,622 | 70 |
import sys
#export
import os, argparse, sys, datetime
os.environ['TF_CPP_MIN_LOG_LEVEL'] = '3'
#Prevent JAX from using all of the threads available
os.environ["OMP_NUM_THREADS"] = "1" # export OMP_NUM_THREADS=4
os.environ["OPENBLAS_NUM_THREADS"] = "1" # export OPENBLAS_NUM_THREADS=4
os.environ["MKL_NUM_THREADS"] =... |
267bca707575046ad14889ccf19fd1add5ddf19eb378a3163b55198e24a7db1f | Python | 2,622 | 86 | #!/usr/bin/env python
#
# Copyright (c) 2018 10X Genomics, Inc. All rights reserved.
#
######################################################
# DO NOT add new items to this file.
#
# - If a constant is only used from a single module, put it in that module.
# - If a constant is only used in association with a particula... |
69e3414f8456cab2b587fc1cbd6c5d88743b0e7ee34246c1f68bcfa4d06753c7 | Python | 2,625 | 64 | """Vowel formant extraction using Praat."""
from collections import defaultdict
import numpy as np
import parselmouth
from parselmouth.praat import call
from tqdm import tqdm
from .config import TAPAConfig
def measure_vowel_formants(audio_np, cfg=None, sample_rate=16000):
"""Measure F1, F2, and pitch for a vow... |
6e93d8b327a4fb1dbb56ae2a200c0e54f7707a78d1ff50c5a473702141464ba1 | Python | 2,626 | 65 | from typing import Optional
import numpy as np
import numpy.typing as npt
from brian2 import Synapses
from brian2.units import Quantity
from ._base import BaseConnector
from . import samplers as S
__all__ = ["PatchConnector", "GaussianConnector", "DenseConnector"]
def _assert_spatial(synapses: Synapses):
for g... |
c1a700c22e93d052ff9574daf29d17e20fd76e2b60f5f53be1385a791bdcf054 | Python | 2,626 | 72 | import numpy as np
import matplotlib.pyplot as plt
import seaborn as sns
def plot_distribution_with_binary_zscore(vector, gene_name):
"""
Plots the distribution of the values in the vector, calculates the z-score
based on the proportion of values > 0 using CLT, and uses the gene name and z-score
... |
2d4bbcd84900ba58485bee5b781d6524e9cffa45fe76627296d3aaf942bd8648 | Python | 2,627 | 78 | import os
import pandas as pd
import random
def assign_splits(
genus: str,
recs: pd.DataFrame,
data_dir: str,
val_frac: float = 0.2,
random_state: int = 42,
) -> None:
"""
Assigns splits based on non interpolated data.
The training split will be used to create new samples by interpolat... |
d43c5b5e5940ddb8e064b0d6174805d21118bf39445954c1c155eb5b237cc13c | Python | 2,630 | 78 | import os
from pathlib import Path
import pandas as pd
import pytest
from stoic_train.dataset import StoichiometryDataset
pytestmark = pytest.mark.integration
def _resolve_paths() -> tuple[Path, Path]:
data_root_env = os.environ.get("STOIC_DATA_ROOT")
data_file_env = os.environ.get("STOIC_DATA_FILE")
if... |
dd412814ff338d456a179a726c931387993ff5ec4d176e87129195c1481cfd8c | Python | 2,633 | 79 | # Set up starting structures for condensed phase simulations
# Run from openmm82 conda env, openff-toolkit v0.18.0, Packmol 21.2.3, rdkit 2024.03.5
from openff.toolkit.topology import Molecule
from rdkit import Chem
from rdkit.Chem import AllChem
from glob import glob
import os
import subprocess
import textwrap
import... |
69c5162ca08676a90aed568279f0ba556cd90258bd674f22acd2a4c6774f7226 | Python | 2,639 | 91 | from abc import abstractmethod
from collections.abc import Sequence
from typing import Generic, Iterable
import numpy as np
from chemprop.data.molgraph import MolGraph
from chemprop.featurizers.base import Featurizer, S
from chemprop.utils import parallel_execute
class MolGraphCacheFacade(Sequence[MolGraph], Generi... |
47fde756a5ad4ed2b05faaefb6d3a93c0862cfa95c43a60e9198b9e7d39c237c | Python | 2,644 | 99 | import altair as alt
from mesa.examples.basic.boltzmann_wealth_model.model import (
BoltzmannScenario,
BoltzmannWealth,
)
from mesa.mesa_logging import INFO, log_to_stderr
from mesa.visualization import (
SolaraViz,
SpaceRenderer,
make_plot_component,
)
from mesa.visualization.components import Age... |
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