sha256 stringlengths 64 64 | language stringclasses 27
values | size int32 1 491k | lines int32 1 21.8k | content stringlengths 1 200k |
|---|---|---|---|---|
dbe6aff662423ffa5982de69354150a0fc64928e110cc5b7608fe9664450e56b | Python | 4,869 | 132 | ############################################################################
# Copyright (c) 2022-2026 University of Helsinki
# Copyright (c) 2019-2022 Saint Petersburg State University
# # All Rights Reserved
# See file LICENSE for details.
############################################################################
... |
5c10049d92eb01cd5bb2f8adbd3ec734ec09d0608bcaea8441d01e02fa141d72 | Python | 4,870 | 101 | # -*- coding: utf-8 -*-
"""
Concatenate parcellated PET images into region x receptor matrix of densities.
"""
import numpy as np
from netneurotools import datasets, plotting
from matplotlib.colors import ListedColormap
from scipy.stats import zscore
from nilearn.datasets import fetch_atlas_schaefer_2018
path = 'C:/U... |
26b8cedf3d1f013b0465a1828e62eb623d677eb6efa67a5d3989f4f6c7c29f1c | Python | 4,872 | 137 | from typing import Any, Iterable, Optional, Sequence
import numpy as np
import numpy.typing as npt
import pandas as pd
import xarray as xr
from hsnn import ops
from ._types import RatesArray, OccurrencesArray
__all__ = ["attach_labels", "infer_rates", "infer_occurrences"]
def _copy_attrs(src: xr.DataArray | xr.Dat... |
72771b72b9010e059538af4ad81de96c9ccaee7edfc79e548a3beead812e04d2 | Python | 4,875 | 171 | import importlib.resources
import pathlib
import shutil
import urllib.request
import click
from plugcli.plugin_management import CommandPlugin
from .utils import write
class _Fetcher:
"""Base class for fetchers. Defines the API and plugin creation.
Parameters
----------
resources: Iterable[Tuple[st... |
c375b78fbc6a3feafe4924fa1f61aeadf023b2924b433697cc54419853754170 | Python | 4,875 | 148 | from __future__ import annotations
from collections.abc import Iterable, Mapping, Sequence
from enum import Enum
from pathlib import Path
from typing import Generic, Protocol, TypeAlias, overload
from typing_extensions import Self, TypedDict, TypeVar
from snakebids.utils.containers import MultiSelectDict
_T_contra ... |
3d9b3cece5d61faf7cdacac49d33fc8a16cc5e54f103b76218c8ce5b1b6b4e0f | Python | 4,876 | 61 | import argparse
def main(args):
import glob
import random
import numpy as np
import json
import itertools
with open(args.input_path, 'r') as json_file:
json_list = list(json_file)
homooligomeric_state = args.homooligomer
if homooligomeric_state == 0:
tied_lis... |
2928c360260a3f001b5550ecf5b709f20be7abde9b436ece9bd61c616bcb245f | Python | 4,879 | 144 | """
Wolf-Sheep Predation Model
================================
Replication of the model found in NetLogo:
Wilensky, U. (1997). NetLogo Wolf Sheep Predation model.
http://ccl.northwestern.edu/netlogo/models/WolfSheepPredation.
Center for Connected Learning and Computer-Based Modeling,
Northwestern Univ... |
e5f37e0b219effdb7581456df1d10de90111071986018568d5b546e7fc125a54 | Python | 4,881 | 114 | #!/usr/bin/env python3
"""Records the positions bcftools dropped before AccuSNV ever saw them, and why.
The candidate positions AccuSNV works from are whatever survives two gates in the mapping
stage: ``bcftools view -v snps -q <variant_min_af>``, which writes the variant VCF, and the
FQ cutoff in variants2positions. ... |
333d26eaea49c177d19747dde6f14c4defed796e29337f027b587d5c3fc8d2ef | Python | 4,885 | 117 | import pytest
import numpy as np
import pandas as pd
from omegaconf import DictConfig, OmegaConf
from hsnn.core import NeuronClass, SynapseClass, Projection
from hsnn.core._brian2.network import SpatialNet
from hsnn.core._brian2.testing import assert_netstate_equal
from hsnn import pipeline
def test_spnet_restore(c... |
c33eca26e8d13618ed030cc9874b14e36e76d2f11e2ba7f951bd6d24e2efc1a2 | Python | 4,889 | 186 | # Script that makes use of more advanced feature selection techniques
# by Alejandro Lopez, 2026
import copy
import numpy as np
import sys
import pandas as pd
from sklearn.linear_model import LassoCV
from sklearn.neural_network import MLPClassifier
# used for normalization
from sklearn.preprocessing import Normaliz... |
3fc134b8226926edb280c9e7c2ac43ba47fd0ddec9eea138c04ecbbde2994955 | Python | 4,890 | 114 | import argparse
from .recon import Recon
from .logconfig import setup_logging
from .runtime import configure_runtime
DESCRIPTION = """
Version Dec 01st, 2025 - by Z.Z :
Pipeline to reconstruct MRI image with motion correction (TCL + GRAPPA + NUFFT)\n\n.
Usage:
mocokit i /path/to/folder/dat
-... |
4b4c0725e6007f85306121b560dd591eb1edd4c7edd72d61bcd1d1a5680bd5b7 | Python | 4,890 | 187 | # Script that makes use of more advanced feature selection techniques
# by Alejandro Lopez, 2026
import copy
import numpy as np
import sys
import pandas as pd
from sklearn.linear_model import LassoCV
from sklearn.neural_network import MLPClassifier
# used for normalization
from sklearn.preprocessing import Normaliz... |
5bd5947fa8259123b065b931b32480945811bd06aa0d00a8c2bd13b99fde3e04 | Python | 4,900 | 145 | # 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... |
08da527a9bacd6c6c38905ea35f713a86df1d7b41b9385993e2eec77f1e2c389 | Python | 4,902 | 131 | """Population coupling -- all animals including ICMS83."""
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
import pickle
from scipy.stats import mannwhitneyu
f... |
7d80409931ef5d5bf2f56ff43dc77e57121673014c30481949c8c0d2c15c3349 | Python | 4,902 | 124 | #!/bin/python
"""
Script for registering and processing ASAP snRNA-seq samples for the Putamen (PUT) region.
Workflow steps:
1. Load the region-specific sample sheet and post-QC samples.
2. Register samples with the trusTEr `Experiment` object.
3. Quantify gene expression with CellRanger/STAR.
4. Set output directorie... |
911caa05e1c6569dc52b573a76bf78c24e86687631c5af742c2bb95d24184b08 | Python | 4,904 | 121 | """Portrayal Components Module.
This module defines data structures for styling visual elements in Mesa agent-based model visualizations.
It provides user-facing classes to specify how agents and property layers should appear in the rendered space.
Classes:
1. AgentPortrayalStyle: Controls the appearance of individua... |
27d0f525c47d4ece8798f4a863c755a30529db520b759345291500b2e0477208 | Python | 4,905 | 132 | import os
import sys
from torch.utils.data import Dataset, DataLoader
from argparse import Namespace
from torch.optim.lr_scheduler import ExponentialLR
import torch.nn as nn
import torch as tc
import optuna
sys.path.append(os.path.abspath(
os.path.join(os.path.dirname(__file__), '../')))
from src.utils import *
c... |
0892312978d73130b853e3e12e163c9868b06ae7259716e8e4452fa3d1e1a4a2 | Python | 4,911 | 151 | #!/usr/bin/env python3
# Copyright (c) Facebook, Inc. and its affiliates.
"""
PointRend Training Script.
This script is a simplified version of the training script in detectron2/tools.
"""
import os
import detectron2.data.transforms as T
import detectron2.utils.comm as comm
from detectron2.checkpoint import Detecti... |
3ea73723036d6f041307e1dc29a55e508a43e0011540d9956f8605212c33813b | Python | 4,917 | 128 | #!/usr/bin/env python3
############################################################################
# Copyright (c) 2022-2026 University of Helsinki
# Copyright (c) 2019-2022 Saint Petersburg State University
# # All Rights Reserved
# See file LICENSE for details.
#######################################################... |
98bd3c066f894e90daea92a93d4819776263c1893cdd2eee6de5a19808a2ee8a | Python | 4,917 | 192 | # /// script
# [tool.marimo.runtime]
# auto_instantiate = false
# ///
import marimo
__generated_with = "0.23.13"
app = marimo.App(width="medium")
@app.cell
def _():
#curl -LsSf https://astral.sh/uv/install.sh | sh
#uv self update
#uv init
#sudo apt install nginx -y
#sudo ufw allow 2718/tcp
#... |
bfa546f0cb0a9c1eb16cc7b160e96163ffc3eacb56be70fc6a8ee1ff355248c3 | Python | 4,926 | 125 | from typing import Sequence
import numpy as np
import pandas as pd
from hsnn.analysis.png import PNG
from hsnn.analysis.png.refinery import Connected
__all__ = ["filter_valid_hfb_triplets"]
def filter_valid_hfb_triplets(
pngs: Sequence[PNG],
syn_params: pd.DataFrame,
) -> tuple[list[PNG], dict]:
"""Filt... |
6ee243b6e14c058653694885374db66e0ac5f4622554bf59c6c44c15350e5b20 | Python | 4,934 | 124 | #!/bin/python
"""
Script for registering and processing ASAP snRNA-seq samples for a specific brain region.
Workflow steps:
1. Load the region-specific sample sheet and post-QC samples.
2. Register samples with the trusTEr `Experiment` object.
3. Quantify gene expression with CellRanger (or STAR if needed).
4. Set out... |
722977afb2971ec26c49ee04b7a04d1951235be81ccd8ab619c6cd4973397b01 | Python | 4,944 | 167 | import argparse
import getpass
import os
import numpy as np
import torch
import yaml
from himalaya.backend import set_backend
from utils import get_git_hash
ELEC_SIGNAL_PREPROCESS_MAP = {
"podcast": dict.fromkeys(
[
"661",
"662",
"717",
"723",
"7... |
dcab514a407520388ce38857a4a74c2f329771f8701c31d9b870733a4124145c | Python | 4,944 | 127 | #!/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... |
5b1218d031083a4c54f472fc626b758409daf0b68a9e77aea3d95c3f82f3c69c | Python | 4,945 | 177 | ############################################################################
# Copyright (c) 2022-2026 University of Helsinki
# All Rights Reserved
# See file LICENSE for details.
############################################################################
# serialization stuff
ENCODING = 'utf-8'
BYTE_ORDER = "big"
ST... |
f03d7cfe710b0ed02c8da5432a1bfdaa3eb9439d3e47ae206bd0f126cadfe970 | Python | 4,945 | 159 | import re
from pathlib import Path
import click
import click_log
import numpy as np
import tifffile
import xtiff
from ... import io
from ..._cli.utils import OrderedClickGroup, catch_exception, logger
from ..._steinbock import SteinbockException
from ..._steinbock import logger as steinbock_logger
from .data import a... |
438b0a687a2c0a66a619b53d733ceb5e80aaa702d53e5be83d4634ecf5eba03d | Python | 4,948 | 137 | """
core/bursts.py
--------------
Network burst detection and active-area computation.
Works on flat spike-time arrays — no file I/O.
"""
import numpy as np
import pandas as pd
from typing import Dict
# ── Network burst detection ────────────────────────────────────────────────────
def detect_network_bursts(all_spik... |
f90caebab82d0cbdc82350dc42a3d15bf49ddc6f9596ba0513a67ca41c44b274 | Python | 4,949 | 142 | from pathlib import Path
from typing import List, Dict
from dataclasses import dataclass
import numpy as np
import torch
import torchvision.transforms as transforms
import matplotlib.pyplot as plt
from . import config
from .utils.activation_manager import ActivationManager
from .utils.pgd_attack import AttackParams
f... |
bda26dcbc6e4139712e80e0bbc0b75b051e4912f70cdc7c07a8a84db34ef2791 | Python | 4,950 | 124 | #!/bin/python
"""
Script for registering and processing ASAP snRNA-seq samples for the Prefrontal Cortex (PFC) region.
Workflow steps:
1. Load the region-specific sample sheet and post-QC samples.
2. Register samples with the trusTEr `Experiment` object.
3. Quantify gene and TE expression with CellRanger/STAR.
4. Set ... |
d5bcb38eb429b101c1fbef7df22e1b72674e1d57f46b98179b5f74194df12fd9 | Python | 4,955 | 119 | import os
import time
import matplotlib.pyplot as plt
import numpy as np
from matplotlib.lines import Line2D
import matplotlib.colors as mcolors
from matplotlib.animation import FuncAnimation, PillowWriter, FFMpegWriter
from tristan_pipeline.utils.plotting_utils import *
from tristan_pipeline.io.params import *
spaces... |
e674728ba68cdad05d860e1b2054fba8c66187f0fe4aaed5dd8860e5ec608c43 | Python | 4,956 | 156 | """File globbing functions based on snakemake.io library."""
from __future__ import annotations
import collections
import os
import re
from collections.abc import Sequence
from itertools import chain
from pathlib import Path
from snakebids.types import ZipList
from snakebids.utils.containers import MultiSelectDict
... |
ad0309648acdad9820c73446879ef35d81219d04ca5b2945402bb72d54ab4a0f | Python | 4,959 | 145 | # This code is part of OpenFE and is licensed under the MIT license.
# For details, see https://github.com/OpenFreeEnergy/openfe
import json
import pathlib
import click
from openfecli import OFECommandPlugin
from openfecli.utils import configure_logger, print_duration, write
def _format_exception(exception) -> str... |
2500746ffb0dc9c0c4ad7508cf2cd74d90d0d570399486108fd80b0ce00e3962 | Python | 4,964 | 141 | from __future__ import annotations
import logging
from pathlib import Path
from types import SimpleNamespace
import uuid
import pytest
from rdkit import Chem
from src.utils.models import MolecularRecord
from src.workflow import pipeline
class _FakeSource:
def __init__(self, settings: dict) -> None:
sel... |
90881b9ed026a4d9e1e565284722041faf3c27922a4522a2793fd7b48aa9672a | Python | 4,966 | 161 | #!/usr/bin/env python3
#
############################################################################
# Copyright (c) 2022-2026 University of Helsinki
# Copyright (c) 2020-2022 Saint Petersburg State University
# # All Rights Reserved
# See file LICENSE for details.
#####################################################... |
35e3b059b998dea06b17e0e1807cfbf3e87cd9a42ea370a2cc13aeaf29953b00 | Python | 4,967 | 113 | import nibabel as nii
import numpy as np
import argparse
import os
import glob
import csv
import sys # Added import statement for sys module
sys.path.insert(0, os.path.abspath(os.path.join(os.path.dirname(__file__), os.pardir)))
from common.artifact_manifest import start_output_tracking
from common.script_logging imp... |
0c9bf13cc26aaec8af6e08d0e8ce73feb3e7e6d0c68498762efc5c574b8629b9 | Python | 4,976 | 134 | #!/usr/bin/env python
# Copyright 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 obtain a... |
d1b984c9558284ffd9baf1420497f0062ba3b91bbfc5594f1f9a47ea95edab91 | Python | 4,982 | 149 | #!/usr/bin/env python
#
# Copyright (c) 2021 10X Genomics, Inc. All rights reserved.
#
"""Functions for refatoring report_matrix.py.
right now, computes only median confidently mapped reads per singlet per genome
"""
from __future__ import annotations
from typing import TYPE_CHECKING
# pylint: disable=too-many-form... |
91612138128c74773ad31adf651f5db6249eaa8a32b07edd84f78a07ca6113e9 | Python | 4,984 | 142 |
import seaborn as sns
import matplotlib.pyplot as plt
import pingouin as pg
import mne
import numpy as np
import arviz as az
def plot_ridge(df, variable_name, values, pal, plot_order=None, xlim=(-1,1), aspect=15, height=0.5):
'''Pretty ridge plot function in python. This is based on code from https://seaborn.... |
12e895f38f77604ebabebcb6713d6f7fbb27d591beb056bffb634a22cd2ad58d | Python | 4,994 | 111 | import numpy as np
def merge(dict1, dict2):
keys = np.unique(list(dict1.keys()) + list(dict2.keys()))
keys = np.unique(keys)
res = {}
for k in keys:
all_configs = []
if dict1.get(k) is not None:
all_configs += list(dict1[k])
if dict2.get(k) is not None:
... |
e243975a3c2fd4b524d63c64110df05a825ba75095cda155f3885b47b401d6a3 | Python | 4,996 | 177 | #python pepProtMap.py peplist.txt A0A8C5CNW5.fasta
#python pepQuanProtMap.py "L:/promec/TIMSTOF/LARS/2026/260908_Moreforsk/combined/txtLen/peptides.txt" "A0A8C5CNW5"
#python pepQuanProtMap.py "L:/promec/TIMSTOF/LARS/2026/260908_Moreforsk/trŧpsin/combined/txtLen/peptides.txt" "A0A8C5CNW5"
#cat L:/promec/TIMSTOF/LARS/202... |
1cf57ef0050642943402ea29bccb1fc1e48d14a518401a7d12c91d89b8010aba | Python | 4,998 | 122 | ############################################################################
# Copyright (c) 2022-2026 University of Helsinki
# All Rights Reserved
# See file LICENSE for details.
############################################################################
# Regression test for duplicate exon/intron count rows.
#
# A ... |
7554c4d78115cf9d4ec371ca74dec3e8b25fcb56142969d8a9208f27cbec8026 | Python | 5,000 | 92 | import os
import numpy as np
import pandas as pd
import umap
import matplotlib.pyplot as plt
import matplotlib
import anndata as ad
import scanpy as sc
import scvelo as scv
import scanpy.external as sce
from scipy.io import mmwrite, mmread
import scipy
import sys
sys.path.append("/home/nomura/Proj/mmvelo/src")
from mmv... |
86ccbb7f7506edd7857a06277e8bc4a859822f398c6ad8f64f6c81ca6d048e7c | Python | 5,003 | 105 | import os
import socket
from typing import Any, NamedTuple, Optional, Tuple
import torch
import torch.distributed as dist
class DDPTopology(NamedTuple):
local_rank: int # index of this process within its node -> this is the CUDA device index!
global_rank: int # index of this process within the entire job (... |
bd71e68ba36d41863b0a0d65a34a91744286faf0b38704695c113f3feba7e149 | Python | 5,004 | 157 | import numpy as np
import optuna
from torch.utils.data import DataLoader
import json
import argparse
import torchvision.transforms as transforms
import torch
from . import config
from .utils.condition import TuneCondition
from .utils.model_utils import load_model
from .utils.pgd_attack import AttackParams
from .utils... |
5f125a9dd8cb91bb67ea7f41dde17c71b1e5620fc43fcada71d7320b4a673c42 | Python | 5,005 | 152 | """Configuration management for imaging datasets.
Created on January 21, 2026
@author: dcupolillo
"""
from __future__ import annotations
from pathlib import Path
import yaml
import tensorflow as tf
class ImagingDatasetConfig:
"""
Configuration manager for imaging dataset processing.
Handles all con... |
6c07abbef302e171062dbb8d9c29847e53bc67dc54e470d423b49ecef5c2a43b | Python | 5,006 | 133 | """Fig 4D: Stim vs non-stim waveform overlay and centroid distance."""
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 seaborn as sns
from sklearn.decomposition import PCA
... |
ec4c8d0d5c187c8bd6515eb27ed82b58ab221700858d4c5f61d5eb6bfe09aa34 | Python | 5,007 | 130 | #!/usr/bin/env python3
"""Regenerate per-image ``*_NMJ_Plot.png`` files for an existing batch run folder.
Re-reads source images from ``data/`` using the run snapshot ``channel_mapping_config.json``
and parameters from ``run_config.json``. Does not rewrite CSVs or aggregate summaries.
Example::
python regenerate... |
ef192ec75f0d8bc5722a8e3ad3c2910f2d5607ba02b5a076e20efb5edb6a09d4 | Python | 5,008 | 132 | # Copyright (c) Facebook, Inc. and its affiliates.
import os
import torch
from detectron2.utils.file_io import PathManager
from .torchscript_patch import freeze_training_mode, patch_instances
__all__ = ["scripting_with_instances", "dump_torchscript_IR"]
def scripting_with_instances(model, fields):
"""
Run... |
9d69a09710a14d0cc2600a11c0c427fe91e0f5e216f225d66f5825c49d6e889b | Python | 5,009 | 145 | from __future__ import annotations
import warnings
from pathlib import Path
import pytest
from pytest_mock import MockerFixture
import snakebids.paths._templates.spec_func as spec_template
from snakebids.paths import bids_factory, specs
from snakebids.paths._config import reset_bids_spec, set_bids_spec
from snakebid... |
f295f2584a55b1155a1b7d944c0f4e97f17421108e1296d6785c89c8ac5fd9a9 | Python | 5,009 | 110 | """Run all scripts that reproduce the paper's figures and statistics.
Each script in SCRIPT_ORDER is run in a subprocess from the repository root;
figures land in plots/, statistics logs in logs/, and each script's full
stdout/stderr in logs/runner/<script>.log. See the README for the
script-to-figure mapping. Total r... |
c77d1e98f183ce4a77d56217735e01c0f2f78123d4e42c05e7bc076ddbc54601 | Python | 5,011 | 140 | import os
import pkgutil
import unittest
from tempfile import TemporaryDirectory
from textwrap import dedent
from unittest.mock import patch
from nnunetv2.utilities.find_class_by_name import recursive_find_python_class
from nnunetv2.utilities.find_objects import recursive_find_trainer_class_by_name
def _write_file(p... |
8920e142c43ff48430bbcc74dc2f1b582a58640e123401f2d772020698a20a8f | Python | 5,017 | 158 | # Copyright (c) Facebook, Inc. and its affiliates.
import math
import numpy as np
from unittest import TestCase
import torch
from fvcore.common.param_scheduler import (
CosineParamScheduler,
MultiStepParamScheduler,
StepWithFixedGammaParamScheduler,
)
from torch import nn
from detectron2.solver import LRM... |
55912967c21c25f27d063dfdbfd7241ff00cea98629f9561f38fea36eea48a31 | Python | 5,018 | 144 | import numpy as np
import pytest
from chemprop.data.collate import BatchMolGraph
from chemprop.featurizers.atom import (
MultiHotAtomFeaturizer,
RIGRAtomFeaturizer,
get_multi_hot_atom_featurizer,
)
from chemprop.featurizers.bond import MultiHotBondFeaturizer, RIGRBondFeaturizer
from chemprop.featurizers.mo... |
c99fff51d7023137698ec97d599b2dbfe04a9a46e204496ed43bdee70e38ba0d | Python | 5,018 | 182 | import sys
from pathlib import Path
import click
import click_log
import numpy as np
import tifffile
from ... import io
from ..._cli.utils import OrderedClickGroup, catch_exception, logger
from ..._steinbock import SteinbockException
from ..._steinbock import logger as steinbock_logger
from .. import cellprofiler
@... |
19ad91c0d0417bd9f21734c5cf7c7323a14a7fbfe6d0b43170f2bfd01b22344d | Python | 5,021 | 191 | # %%
from __future__ import annotations
import os
import matplotlib.cm as cm
import matplotlib.pyplot as plt
import matplotlib.ticker as ticker
import mne
import numpy as np
from matplotlib import font_manager as fm
from matplotlib.gridspec import GridSpec
from mne.io import BaseRaw
from mne_bids import find_matching... |
0a46c17b2d00efc03c1607175a78c0c3b63ec301af320b8fe0dd04ef00651837 | Python | 5,026 | 128 | #!/usr/bin/env python
# Copyright 2016-2019 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... |
7f721a71592cacaf2d24257fa2d0b74ca9edade907287a78cfa1f3dee5347ea9 | Python | 5,029 | 123 | import copy
from pathlib import Path
import joblib
import matplotlib.pyplot as plt
import numpy as np
import torch
from sklearn.decomposition import IncrementalPCA
from .. import config
from .decomposition_handler import DecompositionHandler, V
device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
c... |
8fc226b1707bb011e4ebc5431fa573eb9a6ab74caf499a0be2da13fb7c56d4c1 | Python | 5,032 | 82 | from tristan_pipeline.io.params import *
from tristan_pipeline.utils.loading_utils import *
from tristan_pipeline.utils.preproc_utils import *
from tristan_pipeline.utils.glm_utils import *
from tristan_pipeline.utils.plotting_utils import *
from nilearn.glm.first_level import FirstLevelModel
import pandas as pd
from ... |
669831bc852e45642a8996b2cda7a4d3a5a9b791c24a755a23b966ae26fea8eb | Python | 5,033 | 145 | import torch.nn as nn
from torch.autograd import Variable
from function import adaptive_instance_normalization as adain
from function import calc_mean_std
decoder = nn.Sequential(
nn.ReflectionPad2d((1, 1, 1, 1)),
nn.Conv2d(512, 256, (3, 3)),
nn.ReLU(),
nn.UpsamplingNearest2d(scale_factor=2),
nn.R... |
305355d52b70f5ec11f638d0134aa36ca52cceea61c113f8380daf8cf6fdbefd | Python | 5,035 | 182 | from __future__ import annotations
from enum import StrEnum
import os
from typing import Any, Callable, Iterable, Iterator, Type
import multiprocess
import numpy as np
import psutil
from rdkit import Chem
class EnumMapping(StrEnum):
@classmethod
def get(cls, name: str | EnumMapping) -> EnumMapping:
... |
7d2b87f731815019fe847033c1508656de2cdd8761e93acf970df5b9ca1a84fd | Python | 5,039 | 128 | # This code is part of OpenFE and is licensed under the MIT license.
# For details, see https://github.com/OpenFreeEnergy/openfe
import pytest
from gufe import ChemicalSystem, SolventComponent
from rdkit import Chem
from openfe.setup.chemicalsystem_generator.easy_chemicalsystem_generator import (
EasyChemicalSyste... |
09e5a9877352cf504c8896de93eb29c156394c3eef1f4173246e63ea60e7c90a | Python | 5,044 | 139 | """Throughput benchmark for SMILES2Docking.
Measures wall-clock seconds to prepare N ligands at varying worker
counts. Designed to support the scalability discussion requested by
Reviewer #4.
Usage:
python scripts/benchmark.py --sizes 100 1000 --jobs 1 4 8 \
--input data/raw/zinc_sample.csv --protonation-... |
bcfc1305f474b8a0b2da8e0f20819803fe7eb103e7bc2ba531d005c3e3575ebf | Python | 5,044 | 127 | import cv2
import numpy as np
import tifffile
import os
import glob
from scipy.ndimage import geometric_transform
import tifffile
import glob
import numpy as np
import matplotlib.pyplot as plt
def generate_coupled_image(movie, frame, output):
"""
Generates an image from the previous frame of the given frame a... |
c7f47656f5fc70d3babcf419f8b49aead39021b996ab292ece1d8950d3643fed | Python | 5,044 | 109 | # AUTOGENERATED! DO NOT EDIT! File to edit: 46_model_formulas.ipynb (unless otherwise specified).
__all__ = ['AdditiveFormula', 'additive_formula']
# Cell
import numpy
# Cell
class AdditiveFormula():
"""A class for parsing formulae defined over acceptor (A) and donor (D) splice sites \
and which provides... |
3fe2c9ef13b74335910ae848f8b6cc232ff9f93b824f842bc6856baa9af2a429 | Python | 5,045 | 130 | import os
import sys
import argparse
import torch as tc
tc.set_num_threads(1)
from bptt import BPTT_cont
from models import RNN_cont_Model
from rnn.models import RNN_Model
import rnn.dataset as dataset
import numpy as np
import re
sys.path.append("..")
from utils import *
def get_args():
parser = argparse.Argumen... |
586014c23564f7222c2487b46c91e571ca9d1b9acb67ea5275c0fcc8206e9b59 | Python | 5,050 | 103 | import os
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import anndata as ad
import scanpy as sc
import scvelo as scv
from scipy.io import mmwrite, mmread
import seaborn as sns
import scipy
np.random.seed(42)
# peak-gene linkage matrix
#dir_path = "/home/nomura/Proj/mmvelo/data/10x_multiome_b... |
13c7600fbf6657bc88c869e948b2ff88744da6db04e170bc0cf9869661b1a4c3 | Python | 5,052 | 164 | # -*- coding: utf-8 -*-
# Copyright (c) Facebook, Inc. and its affiliates.
import logging
import numpy as np
from collections import Counter
import tqdm
from fvcore.nn import flop_count_table # can also try flop_count_str
from detectron2.checkpoint import DetectionCheckpointer
from detectron2.config import CfgNode, ... |
dca64e54c4ca2319a2faf854581ae8fde8d4a87bf91b1c3557f256877a822471 | Python | 5,055 | 139 | #
# Copyright (c) 2019 10X Genomics, Inc. All rights reserved.
#
"""Compute summary metrics from the filtered barcode matrix h5 and combine all basic summaries."""
from __future__ import annotations
from typing import TYPE_CHECKING
import h5py
import martian
import cellranger.report as cr_report
import cellranger.... |
66e819edd1710520bb17c8dbc2b1db6e173129833d926790d02d592c2274b006 | Python | 5,056 | 108 | # -*- coding: utf-8 -*-
"""
Fetching atlases and annotations
================================
This example demonstrates how to use :mod:`neuromaps.datasets` to fetch
atlases and annotations.
"""
###############################################################################
# Much of the functionality of the ``neurom... |
8d6546adb901a523ed42cda799bf8f2e5bf64efeef1b3ad035e0f72c9c2d9ce7 | Python | 5,063 | 120 | from __future__ import annotations
from dataclasses import dataclass
from typing import Any
from rdkit import Chem
from rdkit.Chem import AllChem
class StructureGenerationError(Exception):
"""Raised when 3D coordinate generation fails."""
@dataclass(slots=True)
class StructureBuilder:
settings: dict[str, ... |
5a0e00a21f70efb25367c60449796a9e87376c432dd8565ebf8d50f732ff0a8c | Python | 5,065 | 136 | import os
import re
from itertools import product
from pipelines import Stage
from helpers import get_fmriname, get_taskname
class ABCDTask(Stage):
script = '{HCPPIPEDIR}/TaskfMRIAnalysis/TaskfMRIAnalysis.sh'
spec = '--path={path} ' \
'--subject={subject} ' \
'--lvl1tasks={lvl1tasks}... |
f96596183b0162d1a20dfdc970952ee8068f9347586277fa9a4c655c48886f60 | Python | 5,066 | 140 | #!/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... |
bf76ff62e585cd4d0ea54620d347d942d0bc98fe5cb0a90f4aa42cafeddb0948 | Python | 5,067 | 156 |
'''
This file contains all of the implemented tranfromations.
'''
import numpy as np
from . import simulations
import random
def transf_amplitude(time_series, scale_factor):
# TO FIX: Add docs string in here
scaled = np.dot(scale_factor, time_series)
return time_series, scaled
def time_shift(time_ser... |
0a08f2114e54626192104342f389486359faf4a3bbfc2893185017d149d843c1 | Python | 5,068 | 137 | #!/usr/bin/env python3
import argparse
import csv
from collections import Counter
def load_simple_mapping(file):
"""Load mapping from key -> value (2-column TSV)."""
mapping = {}
with open(file, newline='') as f:
reader = csv.reader(f, delimiter="\t")
for row in reader:
if not r... |
54c5e51a04ff486a5d00ed812be8a69481be2c2a16cc369023a33f83a5e187e1 | Python | 5,070 | 141 | from copy import copy
from typing import Any, Optional, Sequence
import neo
import numpy as np
import pandas as pd
import quantities as pq
from elephant.spade import spade
from hsnn.core.logger import get_logger
from hsnn.core.types import SpikeEvents, SpikeTrains, SpikePatterns
from hsnn.ops import conversion
from .... |
5600a397e60f7d9fba9d710bb9d6c00e8240fa39c319061b085f575d5c9021d2 | Python | 5,072 | 187 | import numpy as np
import random
import torch
import scipy
import scanpy as sc
import matplotlib.pyplot as plt
import matplotlib.colors as mcolors
from sklearn.metrics import pairwise_distances
from sklearn.neighbors import kneighbors_graph
# ====================== Data Preprocessing ======================
def norm... |
86acd8cffd96e882571ddec96042a72170f353a405a676277a295363635a210e | Python | 5,078 | 121 | # Copyright (c) Facebook, Inc. and its affiliates.
import copy
import logging
import numpy as np
import time
from pycocotools.cocoeval import COCOeval
from detectron2 import _C
logger = logging.getLogger(__name__)
class COCOeval_opt(COCOeval):
"""
This is a slightly modified version of the original COCO API... |
46a6e8468f204f26b3dad3bbca5515da8679ff46387ed294709dcc2d1e07cc90 | Python | 5,080 | 137 | import os
import shutil
import time
import gc
import numpy as np
import tifffile
import bio_image_unet.siam_unet as siam
import bio_image_unet.unet as unet
from bio_image_unet import unet3d
# create test folder with random training and test data
from bio_image_unet.progress import ProgressNotifier
folder = './temp_t... |
7969191b552b45e8072e92323fc6e457b53ed6e5c4ebef212848022edadac574 | Python | 5,080 | 89 | # residue atoms mean stdev
impropers = [
( 'ALA', ('C', 'CA', '+N', 'O'), -0.00019, 0.03160 ),
( 'ALA', ('CA', 'N', 'C', 'CB'), 0.59838, 0.01964 ),
( 'CYS', ('C', 'CA', '+N', 'O'), 0.00084, 0.03215 ),
( 'CYS', ('CA', 'N', 'C', 'CB'), 0.60237, 0.02852 ),
( 'ASP', ('C', 'CA'... |
cfcdc3195b5236d970123472ddd3d363850c534f58b433439343d3bb4ade9779 | Python | 5,080 | 159 | import numpy as np
import pandas as pd
from sklearn.inspection import permutation_importance
from sklearn.metrics import average_precision_score, roc_auc_score
from sklearn.pipeline import Pipeline
from config import HELDOUT_BOOTSTRAPS, OPTIMISM_BOOTSTRAPS, PERMUTATION_REPEATS, SEED
from models import fit_candidate
... |
0754c1c2312251a4a860c43a796647a241b822a489ee2d8b703e196682b5c175 | Python | 5,082 | 158 | # This code is part of OpenFE and is licensed under the MIT license.
# For details, see https://github.com/OpenFreeEnergy/openfe
"""Equilibrium Relative Free Energy Protocol input settings.
This module implements the necessary settings necessary to run relative free
energies using :class:`openfe.protocols.openmm_rfe.e... |
e172c38f457b8e94af8face8b3545518fbe770fb58de13726dfcd5fc7644ebf5 | Python | 5,084 | 164 | """
Persistence for generated molecules.
Moved here from ``utils/io.py``: these functions are only ever used by the
generation workflow, and keeping them out of the shared I/O module keeps
``pandas``-on-Excel work off the training import path.
Each file-writing helper is a thin wrapper over a pure in-memory core
(:fu... |
fb0acd206c2765440978cfb612d45f69881b4a573922fd57606f5dbeabde9d9c | Python | 5,087 | 154 | from mesa.discrete_space import CellAgent, FixedAgent
class Animal(CellAgent):
"""The base animal class."""
def __init__(
self, model, energy=8, p_reproduce=0.04, energy_from_food=4, cell=None
):
"""Initialize an animal.
Args:
model: Model instance
energy:... |
ca058eef22cbc1a122356199a8c2aef77a5fc60c1cc6643ff4c3575d6083c4db | Python | 5,105 | 117 | # Copyright (c) Facebook, Inc. and its affiliates.
# pyre-unsafe
from typing import Any
import torch
from torch.nn import functional as F
from detectron2.config import CfgNode
from detectron2.layers import ConvTranspose2d
from densepose.modeling.confidence import DensePoseConfidenceModelConfig
from densepose.modeli... |
d985ade0d6dceb784783f9a912ee26038b722196ed327d2734a34de54fc67585 | Python | 5,106 | 81 | import pickle
from rCPGswCPG.utils.gen_utils import get_project_root
from rCPGswCPG.utils.utils import *
from rCPGswCPG.model_params.config_loader import load_model_cfg_file, model_params_from_cfg
from rCPGswCPG.Experiment import Experiment
import numpy as np
import os
import pickle
if __name__ == '__main__':
mod... |
1bde5a1ea0406e7b952909d4882a32161614c0a734fcaa2895f01ba48b20efe5 | Python | 5,110 | 98 | ##plotfrom matplotlib import pyplot as plt
import numpy as np
import os
import pickle
from rCPGswCPG.plotting_figures.plotting_utils import run_sim, resample, plot_recordings
from rCPGswCPG.utils.gen_utils import get_project_root
from scipy.signal import savgol_filter as sg
if __name__ == '__main__':
# ---- exper... |
8af567af6196240f8692fc18a6e79c259ad4a78c215a64101e8fb3c4537b1bd5 | Python | 5,111 | 136 | """The run summary must make silent degradation impossible to miss.
Three shipped failures all looked like successful runs: MFA falling back to
CMUdict timing, Dr.VOT falling back to Praat for every token, and an old build
being installed. The first two are what these tests pin down.
"""
import types
import pytest
f... |
a7a62278735286fab8e3fd4390bb1bcb62afdbf77b8527fd71470ed257944672 | Python | 5,112 | 135 | from mne.time_frequency import psd_welch
from neurodsp.spectral import compute_spectrum, trim_spectrum
import numpy as np
import mne
from warnings import warn
def compute_spectra_mne(mne_data, freq_range):
'''
Computes power spectra mne style using a sensible setup based on Gao et al. 2017
'''
#... |
e018f23c59ecc31d2ef3817e81a60b45b879444b327e0089fb25aadac2379210 | Python | 5,118 | 147 | # 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... |
b913a910852d703a334e9f2865ad5b6d73d915816566f9b9813b5313ef7580cd | Python | 5,130 | 183 | import sys
from pathlib import Path
import pandas as pd
import pytest
from stoic_train.make_train_val_split import _parse_ids, assign_split, main
def test_parse_ids_strips_and_drops_empty_values() -> None:
assert _parse_ids("a; b ;; c ;") == ["a", "b", "c"]
def test_assign_split_returns_expected_labels() -> N... |
f5cdde0a69d12ddd010bfd995b43d0ce21df81cb26cf2393afa66239d4fcb851 | Python | 5,135 | 128 | #!/usr/bin/env python3
"""Builds and persists the canonical HFB annotation tables for a combination.
Re-analyses existing significance-tested detections and post-trained recordings
for a single representative trial, and writes three parquet tables under the trial
checkpoint's ``reuse`` sub-directory: ``hfb_annotations... |
cb4a35b2fbf9f3adf747fdafa57b333caaf382bed3fdd7c0060a04a8a8cf2b7f | Python | 5,142 | 145 | #!/usr/bin/env python3
"""Portable launcher for RAVEN autoencoder training.
The historical code used ``--resume`` for weights-only initialization. This
wrapper names that behavior ``--init-checkpoint`` and exposes a distinct
``--resume-checkpoint`` mode for restoring Lightning training state.
"""
from __future__ imp... |
441150cd8944ed7920b61367f53803245b0a7e1b075e295870ba808d26ed55f3 | Python | 5,148 | 131 | """Tests for the built-in NBLAST work-distribution helpers.
`partition_grid` and `find_optimal_partition` only ever read the query/target
*counts*, so we can exercise them with plain integers / lists standing in for
NeuronLists - no neurons, scoring or timing required.
"""
import inspect
import pytest
from navis.nb... |
c34f43df896ab59dcb7cc2e000157abbd552872deb0389e53218c469b47bf4bb | Python | 5,151 | 148 | """
Tests the easy start guide
- runs plan_rbfe_network with tyk2 inputs and checks the network created
- mocks the calculations and performs gathers on the mocked outputs
"""
import os
from importlib import resources
from os import path
from unittest import mock
import pytest
from click.testing import CliRunner
fro... |
9770b4190303852a4f8f4af37c48da2ee424008f60db11d49f6f7d5d0b176d1f | Python | 5,162 | 150 | """ Test gradient maps """
import pytest
import sys
import numpy as np
from scipy.sparse import coo_matrix
from brainspace.gradient import compute_affinity
from brainspace.gradient.alignment import (procrustes_alignment,
ProcrustesAlignment)
from brainspace.gradient import ... |
5a5f5352daea2154618b8768662d02ff0858ce7e886f4898eb8dd462b4e07d1e | Python | 5,166 | 125 | #!../venv/bin/python
import psql_wrapper as psql
def number_of_admissions(cur):
cur.execute('SELECT COUNT(*) FROM admission_targets;')
return cur.fetchone()[0]
def number_of_gender(cur, gender):
cur.execute(('SELECT COUNT(*) FROM admission_targets T\n'
'LEFT JOIN admissions A ON T.admi... |
b16add3e6612aa22f264e395bed684d9513e7aa15ae2c85878e1cbfe12e77159 | Python | 5,167 | 116 | """Statistical averaging with MAD outlier rejection."""
import numpy as np
from .config import TAPAConfig
def _mad_filter(values, threshold=2.0):
"""Median Absolute Deviation outlier filter."""
values = np.array(values)
median = np.median(values)
mad = np.median(np.abs(values - median))
if mad =... |
5ba30fa0cf7f6fe1d84a9fa3ed583b3c6fcb7f498865e77666c2ad99fd7bc832 | Python | 5,169 | 170 | """Test Solara visualizations with Scenarios."""
import numpy as np
import solara
import mesa
from mesa.examples.basic.boltzmann_wealth_model.model import (
BoltzmannScenario,
BoltzmannWealth,
)
from mesa.experimental.scenarios import Scenario
from mesa.visualization.solara_viz import Slider, SolaraViz, _buil... |
ed9811c9dffc4e79b7e3549124dcb837ef4ee2843195dd1186c21ac9b83a89af | Python | 5,169 | 121 | # Copyright (c) Facebook, Inc. and its affiliates.
# pyre-unsafe
import random
from typing import Optional, Tuple
import torch
from torch.nn import functional as F
from detectron2.config import CfgNode
from detectron2.structures import Instances
from densepose.converters.base import IntTupleBox
from .densepose_cse... |
74c8505c1051696470664ab218c3da286822f3ec44758797091393c5328a6d4b | Python | 5,174 | 176 | # %%
from __future__ import annotations
import os
import mne
import numpy as np
import PIL.Image
from matplotlib import pyplot as plt
from matplotlib.backends.backend_agg import FigureCanvas
from scipy import interpolate
from scipy.io import savemat
from scipy.spatial import ConvexHull
plt.rcParams['figure.max_open_w... |
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