sha256 stringlengths 64 64 | language stringclasses 27
values | size int32 1 491k | lines int32 1 21.8k | content stringlengths 1 200k |
|---|---|---|---|---|
6fa3c08d730d03dfc9f76b6098fc136a10ba353a09885be8084aa3dabf508f9f | Python | 7,199 | 239 | # %%
from __future__ import annotations
import os
import os.path as op
import sys
from dataclasses import dataclass
import mne
import pandas as pd
from wasabi import msg
from src.epoching import Epoching
from src.epoching import InfoExtraction
sys.path.append(op.abspath('..'))
# %%
ROOT = '../../NOD-MEEG_upload'
# ... |
fef18610ce1734d0feabaac8ae400e5883393a749967c49f4c0e6afc62842789 | Python | 7,207 | 178 | """
Volumes
=======
<!-- difficulty: intermediate -->
Give a figure context without letting the neuropil steal it.
[`Volumes`][navis.Volume] - neuropils, brain outlines, ROIs - are meshes, so most of what the
[mesh tutorial](../tutorial_plotting_2d_01_meshes) says applies here too. What makes them their own
topic is ... |
d772e748196417252e93d23aa33c725f976dc5b6b2cfe9e90119a1c7b873f0e8 | Python | 7,211 | 188 | #!/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... |
99c9ec60ba4da703493d02ccbf72239a4350d9500ac011a61cc4a448ab51d1ce | Python | 7,212 | 178 | """実験１を実行するプログラム"""
import numpy as np
from Agent_intermittent import BGmodel
from Environment import InvertedPendulum
from scipy import signal
import myfunc0829
import blosc2
import os
#num_list = [i+1 for i in range(8)] # 格納したいトライアルのリスト（一つのトライアルにつき210秒分の時系列データが入る）
#num_list = [1,2,3,4,5,6,7,8,9,10,11,12,13... |
e64570ea703dd919e6e9e64daf5956b9e01c2c46f02856d1d85234d56058e808 | Python | 7,214 | 154 |
############################################################################
# Copyright (c) 2022-2026 University of Helsinki
# All Rights Reserved
# See file LICENSE for details.
############################################################################
from enum import Enum, unique
from isoquant_lib.common impor... |
f88dfecd9e0cfca59797ec43ee244d2bbe24d07cb1185bdefd38823759fb30e8 | Python | 7,215 | 194 | # Copyright (c) Facebook, Inc. and its affiliates.
import argparse
import glob
import multiprocessing as mp
import numpy as np
import os
import tempfile
import time
import warnings
import cv2
import tqdm
from detectron2.config import get_cfg
from detectron2.data.detection_utils import read_image
from detectron2.utils.... |
bb147d1a16e9dadf17c6972c4f491e51dfb281fbb67f0b867b3fd4660d8e81e8 | Python | 7,216 | 147 | ############################################################################
# Copyright (c) 2022-2026 University of Helsinki
# Copyright (c) 2020-2022 Saint Petersburg State University
# # All Rights Reserved
# See file LICENSE for details.
############################################################################
... |
5fcb9596dbb1f8ea2fde760f32f62b8ad0198f9c8f97d9b6edfaf662df02f24e | Python | 7,223 | 223 | #%%
import joblib
from os.path import join
import numpy as np
import pandas as pd
import matplotlib as mpl
new_rc_params = {'text.usetex': False,
"svg.fonttype": 'none'
}
mpl.rcParams.update(new_rc_params)
import matplotlib.pyplot as plt
import seaborn as sns
import sys
sys.path.append('/mnt/obob/s... |
c3585ced4e6732fbe0334d7f99f9df377f2940d84e2b1a569c9cbd1192a41754 | Python | 7,224 | 236 | # Copyright (c) Facebook, Inc. and its affiliates.
import copy
import logging
import types
from collections import UserDict
from typing import List
from detectron2.utils.logger import log_first_n
__all__ = ["DatasetCatalog", "MetadataCatalog", "Metadata"]
class _DatasetCatalog(UserDict):
"""
A global dictio... |
98e57d2c7e57f98aa3c292a00b2e762462e10b072c87c96124a5343fd23769dc | Python | 7,230 | 156 | # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
# pyre-unsafe
from typing import Any, List
import torch
from torch import nn
from torch.nn import functional as F
from detectron2.config import CfgNode
from detectron2.structures import Instances
from densepose.data.meshes.catalog import MeshCat... |
d307973ee78d8e8e31f12bebeda69437145de7d33d32b88d3744975cfb7bdd38 | Python | 7,236 | 183 | # type: ignore
import numpy as np
import pandas as pd
import pytest
from hsnn.analysis import png
from hsnn.pipeline import reuse
from hsnn.utils import handler
@pytest.fixture
def polygrps():
png_a = png.PNG(
layers=np.array([3, 4, 4]), nrns=np.array([10, 20, 30]),
lags=np.array([0.0, 3.0, 10.0]... |
110ec90e339aecc9ef26c369e0f9b1ab1ab0a0856d6e2c444e369937452d7748 | Python | 7,237 | 238 | # Copyright (c) Facebook, Inc. and its affiliates.
"""
This file contains primitives for multi-gpu communication.
This is useful when doing distributed training.
"""
import functools
import numpy as np
import torch
import torch.distributed as dist
_LOCAL_PROCESS_GROUP = None
_MISSING_LOCAL_PG_ERROR = (
"Local pro... |
0a46e0fd13f0c6719f9aa102b1f069b9c1523f1df24f976bd08f2307a0e425ee | Python | 7,241 | 162 | """
utils/io.py
-----------
All file output: TSV tables, CSV tables, and the criticality text report.
The R script for LTP/LTD reads the TSV files produced here.
Keep column names stable — changing them breaks the R script.
"""
import io
import os
import re
import sys
import platform
import datetime
import numpy as np... |
717df07d25b71057c3bfcd7728f79ae39e007fc7b3ea459499d9419c967567bb | Python | 7,248 | 185 | """UnitResponse — stores per-unit spike data and stim condition responses."""
from .stim_condition_response import StimConditionResponse
import numpy as np
import batch_process.util.template_util as template_util
class UnitResponse:
def __init__(self, unit_id, spike_timestamps, session_responses):
self._... |
3b56ceb3a4c5477882584cb2a83e4e29598ea41b2d1e0fb54cb731c4ce0f43f7 | Python | 7,256 | 178 | """実験１を実行するプログラム"""
import numpy as np
from Agent_continuous import BGmodel
from Environment import InvertedPendulum
from scipy import signal
import myfunc0829
import blosc2
import os
#num_list = [i+1 for i in range(8)] # 格納したいトライアルのリスト（一つのトライアルにつき210秒分の時系列データが入る）
#num_list = [1,2,3,4,5,6,7,8,9,10,11,12,13,1... |
096d484f26811a2d1e3b229558949960974b8e4bdfbd4cdb76061874843fb9d1 | Python | 7,260 | 170 | from __future__ import annotations
from abc import ABC, abstractmethod
from typing import Any, Dict, Iterable, List, Optional, Tuple, Type
import numpy as np
import numpy.typing as npt
import pandas as pd
import xarray as xr
from brian2 import CodeRunner, Network, NeuronGroup, Synapses, SpikeMonitor, StateMonitor
fro... |
9b1a1740fe157c42c6bff4824880822d069da610e0ee74790f41a3bf5f34729b | Python | 7,264 | 188 | # Generated by Django 4.2 on 2024-10-02 08:58
from django.conf import settings
import django.contrib.auth.models
import django.contrib.auth.validators
from django.db import migrations, models
import django.db.models.deletion
import django.utils.timezone
class Migration(migrations.Migration):
initial = True
... |
44820fe41d4e59439d7469bf5e3c1fb7e92a27134cf8cd83e94045db9b55291f | Python | 7,265 | 202 | # -*- coding: utf-8 -*-
# Copyright (c) Facebook, Inc. and its affiliates.
import contextlib
import io
import numpy as np
import unittest
from collections import defaultdict
import torch
import tqdm
from fvcore.common.benchmark import benchmark
from pycocotools.coco import COCO
from tabulate import tabulate
from torch... |
31c76cdb2eefed27d4e335d31ddf4f21936939eae6668f90f8548a88643a9046 | Python | 7,272 | 231 | import csv
import os
import numpy as np
import pandas as pd
import torch
from himalaya.kernel_ridge import (ColumnKernelizer, Kernelizer, KernelRidgeCV,
MultipleKernelRidgeCV)
from himalaya.ridge import ColumnTransformerNoStack, GroupRidgeCV, RidgeCV
from himalaya.scoring import corr... |
d747aed6f1c2fde9082cac7a1ab328e0e335393ad86c35077ad256328c660086 | Python | 7,281 | 230 | from pathlib import Path
home = Path.home()
[x for x in home.iterdir()]
inpD = '1d/UTR'
[x for x in (home/inpD).iterdir()]
inpF=home/inpD/"data2.csv"
import pandas as pd
#import modin.pandas as pd
data = pd.read_csv(str(inpF))
data.head()
data.describe()
import matplotlib.pyplot as plt
import numpy as np
data['RFPlog... |
5bd2e958f44ba959f4be1296a33284549e4e84c28cace2abc9802190321bfe9b | Python | 7,283 | 242 | # -*- coding: utf-8 -*-
"""
Created on Mon May 1 14:59:05 2023
@author: walte
"""
import os
import random
import numpy as np
import imageio
from tqdm import tqdm
import torch
import csv
from collections import OrderedDict
####################
# Resuming training
####################
# def get... |
02449632dd6b494d130215c82444bd26db9f0b9266225d7cbce73b18c0e545a9 | Python | 7,286 | 232 | """Tests for meta-agent creation, discovery helpers, and group reuse."""
import pytest
from mesa import Agent, Model
from mesa.discrete_space.cell_agent import CellAgent
from mesa.discrete_space.grid import OrthogonalMooreGrid
from mesa.meta_agents import MetaAgents
from mesa.meta_agents.meta_agent import MetaAgent
... |
d64287a2c6a9284c13ad50be8a56294f36f66413eaed56163d7702f84682ac6e | Python | 7,292 | 168 |
############################################################################
# Copyright (c) 2022-2026 University of Helsinki
# All Rights Reserved
# See file LICENSE for details.
############################################################################
import pysam
import logging
from isoquant_lib.common import ... |
5953911194d47a23aef6f42695284e63e987496be0ac5c7bfbd8a6cc34a2dc34 | Python | 7,297 | 228 | #%%
import numpy as np
from lisc import Words, Counts
from lisc.plts.counts import plot_matrix
import matplotlib.pyplot as plt
import networkx as nx
import seaborn as sns
from lisc.plts.words import plot_years, plot_wordcloud
from lisc import Counts
from lisc.plts.utils import check_args, check_ax # counts_data_helper
... |
246f051c507492f6861ae505535b13fa1e2172f13e4407364212df2c8d8ae2e7 | Python | 7,310 | 136 | from typing import Union, List, Tuple, Callable
import numpy as np
from acvl_utils.morphology.morphology_helper import label_with_component_sizes
from batchgenerators.transforms.abstract_transforms import AbstractTransform
from skimage.morphology import ball
from skimage.morphology.binary import binary_erosion, binary... |
c27c98ea11a2c3d8b031188553441fd9f59abff09baa669191d13797d1a66a83 | Python | 7,310 | 177 | """
loaders/maxwell_loader.py
--------------------------
Loader for Maxwell Biosystems .h5 files (data.raw.h5).
HDF5 structure expected
-----------------------
/data_store/<stream>/
spikes – structured array with fields:
frameno (int64)
... |
941f6251e1565d19c5c3e1dfa55aa0a0552827752bfcbb471cce36c22498222b | Python | 7,313 | 193 | """A module to provide an interface to the subprocess library.
This module hosts the functionality for streamline the execution of command-line
algorithms called from the subprocess library. This is convenient when parsing through
gear configuration parameters and inputs specified in a gear configuration
(e.g `config... |
c55bc1bdb0e5934924c4981a8c98e79692d62ebfa7d5f3ec352ce9ea97ab8af5 | Python | 7,314 | 198 | """
Process and plot control session responses.
Workflow:
1. Create session responses (or load from pickle)
2. Extract modulation metrics → CSV
3. Generate per-unit × per-channel figures → PNG
4. Compile figures into PowerPoint
Usage:
python process_control_responses.py <session_dir>
python process_control_re... |
4d3e0d682ab1624494df13519442365d5e0f4ac687665b159ca32826a9f7a7d7 | Python | 7,315 | 244 | """ Created on Fri Aug 2 14:58:52 2024
@author: dcupolillo """
from __future__ import annotations
import pyabf
import numpy as np
from tqdm import tqdm
from typing import TYPE_CHECKING
if TYPE_CHECKING:
from spyne.core.electrophysiology.ephydataset import EphyDataset
adc_dict = {
'IN 0': 'patch',
'I... |
7a29118e0122cdaa3cedf8c69b8d07c6a7f3a526ef255d2e7432771c5382b512 | Python | 7,315 | 200 | #!/usr/bin/env python3
"""
Module: train.py
Description:
- Train specified model on a given dataset (pre-split).
- Logs epoch-wise metrics, selects best model, and saves it.
"""
import os
import sys
import time
import argparse
from datetime import datetime
import torch
import torch.optim as optim
import torch.nn ... |
e34fb6e83fb79ce7e0130a6062df32d3c2b9aad00ae91b3aa791a0c9c624cfd1 | Python | 7,320 | 226 | #!/usr/bin/env python3
############################################################################
# Copyright (c) 2022-2026 University of Helsinki
# All Rights Reserved
# See file LICENSE for details.
############################################################################
"""Convert read_info.tsv to legacy rea... |
045b5fbd03163466d165c20eba0d329228fbbfbed176d5ba42f7b38e986cdfb1 | Python | 7,324 | 175 | #!/usr/bin/env python
#
# Copyright (c) 2022 10X Genomics, Inc. All rights reserved.
#
"""Code to produce plotly treemap plots."""
from __future__ import annotations
import json
import numpy as np
import plotly.graph_objects as go
from cellranger.rna.library import ANTIBODY_LIBRARY_TYPE
from cellranger.websummary.i... |
4bea3d1b7decc6adab5623d1682c668fe1ac01e6ada1bdab0f32ba5269004ea4 | Python | 7,324 | 232 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Text Embedding Generation for Patent Data
This script generates BERT embeddings for patent abstracts using a pretrained
model specifically designed for patents (anferico/bert-for-patents).
Features:
- Processes patents_{year}_*.parquet files
- Filters for utility pat... |
2314f8c0885608071e026d2e76cb523d2181611123d9a99381cc3c76cfae6b79 | Python | 7,338 | 200 | import random
import numpy as np
import seaborn as sns
import torch
import torch.nn.functional as F
from sklearn.metrics import roc_auc_score, average_precision_score, balanced_accuracy_score, roc_curve, cohen_kappa_score
import matplotlib.pyplot as plt
from transformers import AutoTokenizer
import os
from PIL import I... |
4c47bdf0a71ad7ca44b0929f9474e623f7fc18e9f5c96399f7167132ac4d9286 | Python | 7,353 | 193 | # Copyright (c) Facebook, Inc. and its affiliates.
# pyre-unsafe
from typing import Dict
import torch
from torch.nn import functional as F
from detectron2.structures.boxes import Boxes, BoxMode
from ..structures import (
DensePoseChartPredictorOutput,
DensePoseChartResult,
DensePoseChartResultWithConfid... |
be2d71d647226c476fcb6b283c0ee4b58bf0fbd8fe620699f6f5e08e24f14b34 | Python | 7,354 | 171 | """Hit vs miss delta_spks histograms and KL divergence (700ms and 120ms)."""
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 seaborn as sns
from scipy.s... |
03c09a48b3f3db5469aa8cf66d2558050078c5f9725f31887263d61510c4153e | Python | 7,367 | 172 | # Copyright (c) Facebook, Inc. and its affiliates.
from __future__ import absolute_import, division, print_function, unicode_literals
import numpy as np
import unittest
from copy import deepcopy
import torch
from torchvision import ops
from detectron2.layers import batched_nms, batched_nms_rotated, nms_rotated
from de... |
159fa30b8c3bac6845f527a6bfaf5c7993ca25db1f7d6b377187b7fc6666d7f7 | Python | 7,372 | 189 | #!/usr/bin/env python3
import argparse
import csv
import re
from pathlib import Path
from typing import List, Tuple, Dict, Optional
from Bio import SeqIO, pairwise2
from Bio.PDB import PDBParser, MMCIFParser
from Bio.PDB.Polypeptide import protein_letters_3to1
def parse_active_sites(spec: str) -> List[int]:
"""P... |
5cdb059625737abcfd44f5add0efe4e87865ecd17bc8b9959380823bee8cdff6 | Python | 7,375 | 173 | from __future__ import annotations
from abc import ABC, abstractmethod
from typing import Optional, Sequence, Type
import numpy as np
import numpy.typing as npt
from scipy.stats import entropy
import hsnn.simulation.functional as F
from hsnn import analysis
from hsnn.analysis import activity, measures
from hsnn.anal... |
32fa3db42a3d56c1103b7c21fcb1d1ac54f88e1eae53d09254dd35a3aab75ed2 | Python | 7,378 | 225 | # Copyright (c) Facebook, Inc. and its affiliates.
import logging
import numpy as np
from itertools import count
from typing import List, Tuple
import torch
import tqdm
from fvcore.common.timer import Timer
from detectron2.utils import comm
from .build import build_batch_data_loader
from .common import DatasetFromLis... |
3a709990c286328fd559978e7fee0f623e3e4bc05bde72a30c38e21b82704fba | Python | 7,380 | 202 | #!/usr/bin/env python
# Copyright 2019-2020 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... |
c6f5ccb4a83f5146a7a60e33df015c51c4744bc6df63211c2e30036c7b2f9a6d | Python | 7,382 | 162 | import numpy as np
import pandas as pd
import warnings
warnings.filterwarnings("ignore")
import matplotlib.pyplot as plt
import re
import argparse
import os
import pre_process
from monai.networks.nets import DenseNet
import torch
import nibabel as nib
import tqdm
import datetime
from collections import OrderedDict
im... |
4122f6816253a357d22e9253d2839cf16e039953a83cb7153fa87c6506b24f8b | Python | 7,395 | 228 | #!/usr/bin/env python
"""
author:CBJ
"""
import sys
from pathlib import Path
import logging
import numpy as np
import torch
import torch.nn as nn
from torch.utils.data import DataLoader, TensorDataset
import json
PROJECT_ROOT = Path(__file__).parent.parent
sys.path.insert(0, str(PROJECT_ROOT))
from src.models import... |
dfce2e302c4b7f3c9d091afd49484a77ab8ee3f7e9e1d6f05de3d3f70f881464 | Python | 7,400 | 147 | #!/usr/bin/env python3
"""Build the small, hand-curated metadata JSON files the MCP server reads
alongside data/studies.json:
data/review_metadata.json citation, ids, links, licence, PRISMA counts
data/eligibility.json Appendix S1 (PCC framework) + the 6 numbered
inclusion/ex... |
5c8fc0beff0c7e003a8bdbe17c5c761be4d4a79965f35a39139037afa7148e62 | Python | 7,401 | 203 | from __future__ import annotations
from tqdm import tqdm
import numpy as np
from spyne.core.spines.analysis.timeseries.timeseries import (
background, dFF, get_timestamps, z_score)
def collect_timeseries(
dataset,
spines_data: list,
metadata: dict,
dendrites_masks: list,
background_dilation_d... |
420b1020392f3fbc71cb7156ab2a820f4a3a2bf2b6c97c306f6d8045e87f3b35 | Python | 7,406 | 206 | """Tests for `navis.sholl_analysis`, in particular the handling of `center`.
`center` accepts several forms - the "centermass"/"root"/"soma" presets, a node ID or an
x/y/z coordinate. The dispatch used to resolve "centermass" into a coordinate array *before*
the remaining branches compared `center` against the string ... |
eb75be482649bb7dbfe36b096fe2dd94f080f417941a0c58c6816259faa51f97 | Python | 7,406 | 260 | """
@Article{li2014multiplicative,
author = {Li, Chunming and Gore, John C and Davatzikos, Christos},
title = {Multiplicative intrinsic component optimization (MICO) for MRI bias field estimation and tissue segmentation},
journal = {Magnetic resonance imaging},
year = {2014},
volume = {32},
... |
27315eab366c84df0d0cfb7f828cd807c76c129908ebc8736eca9a794aabac52 | Python | 7,411 | 149 | ############################################################################
# Copyright (c) 2022-2026 University of Helsinki
# Copyright (c) 2020-2022 Saint Petersburg State University
# # All Rights Reserved
# See file LICENSE for details.
############################################################################
... |
32615e6ac5bbaabeb727dd449ae57c779bb4df32ddcbe0c4860cd7a29d9415b4 | Python | 7,419 | 229 | """
Analyse stationary spike trains
## Functions
- `interval_statistics()`: statistics and kde of interspike intervals.
- `burst_fraction()`: burst fraction based on ISI distribution.
- `serial_correlations()`: serial correlations of interspike intervals.
- `vector_strength()`: vector strength of spike times relative... |
714eb1b42635da02262340260925ad2dc421fa9e3c668918b079a9f383cd3d27 | Python | 7,426 | 186 | # Copyright (c) Facebook, Inc. and its affiliates.
import unittest
from detectron2.layers import ShapeSpec
from detectron2.modeling.mmdet_wrapper import MMDetBackbone, MMDetDetector
try:
import mmdet.models # noqa
HAS_MMDET = True
except ImportError:
HAS_MMDET = False
@unittest.skipIf(not HAS_MMDET, "... |
c51153e8fd55b8eb7b4f256f11a2f14c975c196c8affc9ebd322e95a0290b854 | Python | 7,426 | 164 |
import os
import pandas as pd
import numpy as np
from loguru import logger
logger.info('Import OK')
pd.set_option('display.max_columns', 500)
def tmt_peptides(input_path, sample_names=None, pep_cols=[]):
peptides = pd.read_table(input_path, sep='\t')
logger.info(
f'Imported peptides from {input_p... |
1dca79f7454a574cbc1f812ec027151e479bf159266056e31817a99ae4b88a00 | Python | 7,434 | 233 | import torch
import torch.nn as nn
from .meta.electrode_names import channels
from .VisualTransforms import EEGScalpMap
from .utils import Tab
class R2Plus1D_Block(nn.Module):
def __init__(
self,
in_ch,
out_ch,
k_t=3,
k_s=3,
stride_t=1,
stride_s=1,
... |
9c32b204d4cdf23eb3760ef8220b4fb21c27d6ae13077656f3d8e9574498e248 | Python | 7,440 | 218 | """Tests for the optimized `navis.graph.connecting_nodes`.
The optimized implementation is checked against a frozen copy of the original
implementation (`_connecting_nodes_old`) to prove identical results, except in
the documented edge case (subset contains an ancestor of the branch-point LCA)
where the new implementa... |
4130760adbd39af282486cc845ec9de4bd0041c05b5a057bb56e44d4f071d1e4 | Python | 7,441 | 156 | from __future__ import annotations
from dataclasses import dataclass
import numpy as np
import pandas as pd
from sklearn.impute import KNNImputer
from sklearn.model_selection import GroupShuffleSplit
from sklearn.preprocessing import OneHotEncoder, StandardScaler
@dataclass
class FittedPreprocessor:
retained_va... |
14143bdb4022e26d1dee91609d821600dbdc15425667e6376f5d40bae1a7cfd0 | Python | 7,442 | 231 | from __future__ import annotations
import re
import sys
from collections.abc import Container, Iterable, Iterator, Sequence
from typing import (
Any,
AnyStr,
Generic,
SupportsIndex,
TypeVar,
overload,
)
from typing_extensions import Self, override
_T = TypeVar("_T")
_K = TypeVar("_K", bound="... |
e0c87457caeed5d92e7577da3f4a08d36b795dbf5b10c4047a09e4f0549c74c0 | Python | 7,454 | 182 | """Environment checks.
Most TAPA failures in the wild have been missing external programs rather than
bugs in the pipeline: MFA unable to find its OpenFst helpers, Dr.VOT unable to
find sox or a working Praat. Each surfaced minutes into a run, as a confusing
traceback or — worse — as a silent fallback to a cruder meth... |
44b6d16eb91babf464fef54c5f3203dc8f4318df8ab31ea94652239c326c5954 | Python | 7,455 | 224 | """
Stage 3: apply curated merges + finalize, per session.
Reads batch_sort/stage2/stage2_analyzer.zarr + curation_config.json, applies the
selected merges, and writes batch_sort/stage3/analyzer_final.zarr.
Usage:
python -m batch_process.stage3_merge <session_folder> [<session_folder> ...] [--force]
"""
... |
935e61b19796edd93b7e3822f64acb3ec7d00a9da9a1ab18999886798f0db7fa | Python | 7,469 | 247 | # This code is part of OpenFE and is licensed under the MIT license.
# For details, see https://github.com/OpenFreeEnergy/openfe
"""
Restraint Geometry classes
TODO
----
* Add relevant duecredit entries.
"""
from typing import Iterable, Optional
import MDAnalysis as mda
from openff.units import Quantity, unit
from r... |
3ea8f54b35f4053652924277ae2759c621d27a30727da965b5f8493aa3ba544d | Python | 7,477 | 197 | ############################################################################
# Copyright (c) 2025-2026 University of Helsinki
# All Rights Reserved
# See file LICENSE for details.
############################################################################
import pytest
from isoquant_lib.barcode_calling.indexers impor... |
3345b4f80ef9cebe4ebbb28ae37b787575f4d6ebea74f0fd1c932a35481759e0 | Python | 7,478 | 286 | import torch
from torch import nn as nn
class BCEDiceLoss(nn.Module):
"""
Combines Binary Cross-Entropy Loss and Dice Loss.
Parameters
----------
alpha : float
Weight for the Binary Cross-Entropy Loss component.
beta : float
Weight for the Dice Loss component.
"""
def ... |
984289513aac8ab4ade88146039222a4aad75046a4a896c74527ef0891933778 | Python | 7,486 | 171 | #!/usr/bin/env python3
# Copyright 2004-present Facebook. All Rights Reserved.
import copy
import numpy as np
from typing import Dict
import torch
from scipy.optimize import linear_sum_assignment
from detectron2.config import configurable
from detectron2.structures import Boxes, Instances
from ..config.config import ... |
0aaed5930a6c3ed48e0bee973b1e8358661745d55cd28f9abc1a8eff46d438a2 | Python | 7,488 | 219 | from tqdm import tqdm
import numpy as np
import calcium_event_classifier as cec
from sklearn.neighbors import KernelDensity
from scipy.signal import find_peaks
def detect_calcium_events(
config: dict,
zscores: np.ndarray,
dFF: np.ndarray,
) -> np.ndarray:
"""
Detect calcium events in s... |
c5bcff01a3f64f6d3b8d29a8ec292db397f3498fb59878e3374899c15398f764 | Python | 7,500 | 199 | # Copyright (c) Facebook, Inc. and its affiliates.
import contextlib
import io
import itertools
import json
import logging
import numpy as np
import os
import tempfile
from collections import OrderedDict
from typing import Optional
from PIL import Image
from tabulate import tabulate
from detectron2.data import Metadat... |
80d42571dd728e6ae39e6da8ec79644e985430eeef77f58c9c8c0fcd3a1b592e | Python | 7,501 | 215 | #
# Copyright (c) 2025 10X Genomics, Inc. All rights reserved.
#
"""Call cell types based on Satija-Lab's Azimuth."""
import csv
import itertools
import json
import math
from dataclasses import asdict, dataclass
import martian
import numpy as np
import cellranger.matrix as cr_matrix
from cellranger.cell_typing.azim... |
ea096e56567c4ab9be8594bf4b75af79c1facf52f58785adb791e0d02c3cfca4 | Python | 7,502 | 164 | import os
import numpy as np
import matplotlib.pyplot as plt
from matplotlib.lines import Line2D
from tristan_pipeline.utils.plotting_utils import *
from tristan_pipeline.utils.analysis_utils import *
from tristan_pipeline.io.params import *
from nilearn.glm import threshold_stats_img
space = "T1w"
mocos_ = ["Servo o... |
a2624fb519a16a984823ed3d650eb983b5c8e05713132e46eab3306e51dd4b01 | Python | 7,504 | 202 | # 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... |
02712da6f0824e8c0a7ee63b4cc09b788205e9e837c8e63e57d10e3e53a1f54f | Python | 7,509 | 204 | """Abstract Base class for building cell-based spatial environments.
DiscreteSpace provides the core functionality needed by all cell-based spaces:
- Cell creation and tracking
- Agent-cell relationship management
- Property Layer support
- Random selection capabilities
- Capacity management
This serves as the founda... |
09497486df1702f33f5813409ac44ef37a2e45c18167bfe6a1fd762537305824 | Python | 7,512 | 210 | # Copyright (c) Facebook, Inc. and its affiliates.
import os
import pickle
import sys
import unittest
from functools import partial
import torch
from iopath.common.file_io import LazyPath
from detectron2 import model_zoo
from detectron2.config import get_cfg, instantiate
from detectron2.data import (
DatasetCatal... |
b8626ab433c09ffa6df9d49869420d497ce93bdb2c5cc084e36bb73c20796383 | Python | 7,513 | 184 | """
Augmenting Neurons
==================
<!-- difficulty: intermediate -->
Augment neuron training sets with realistic perturbations for robust models.
The `navis.ml` module provides a set of geometric and sampling augmentations.
Every one of them:
- accepts a [`navis.Skeleton`][], [`navis.Mesh`][], [`navis.Dotprop... |
571d593d5732e9536d8bd2638783d577e903167fee84b6e218cfd9d9c09358b6 | Python | 7,515 | 215 | # 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... |
7945d89eaa90929f211e00da8f4febea960c0f91174284680cf301affda891cb | Python | 7,518 | 161 | """
Volumes
=======
<!-- difficulty: intermediate -->
Put a neuropil around your neurons without losing sight of them.
A [`Volume`][navis.Volume] in 3D has exactly one hard problem: it is a closed shell, and you want to
see what is inside it. Everything below is about that trade-off - and about the fact that a real
r... |
1db5efa4e7dd3d10549fef8ae3e6a6092551991404bc9f73d1e419978cf3252d | Python | 7,534 | 200 | # This code is part of OpenFE and is licensed under the MIT license.
# For details, see https://github.com/OpenFreeEnergy/openfe
import gzip
import itertools
import json
from unittest import mock
import gufe
import numpy as np
import pytest
from openff.units import unit as offunit
import openfe
from openfe.protocols ... |
8d0972dd85bd76095b76315b184b2dbd90686464f509bc452bad9fc667513d2c | Python | 7,536 | 199 | """
The MICrONS Datasets
====================
<!-- difficulty: intermediate -->
Fetch and explore neurons from the MICrONS EM datasets.
The [Allen Institute for Brain Science](https://alleninstitute.org/) in collaboration with Princeton University,
and Baylor College of Medicine released two large connectomics datase... |
d026bc3b44a803d26d6b494a23ec4c15d57ea4c8725e9614a3ae474466831fc3 | Python | 7,539 | 303 | """Standardization for multi-response social risk and comorbidity fields."""
import pandas as pd
SOCIAL_RISK_MAP = {
"Current smoker": (
"Current smoker",
"keep",
"",
),
"Documented MDR contact": (
"Documented MDR contact",
"keep",
"",
),
"Homeless"... |
5299855e5ed0fd768ee8fb3ad90e080afe59e5dac6434e3829fdd93bf57b7706 | Python | 7,548 | 214 | import glob
import os
import re
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
import psignifit as ps
def _binomial_log_likelihood(k, n, p):
p = np.clip(np.asarray(p, dtype=float), 1e-12, 1 - 1e-12)
k = np.asarray(k, dtype=float)
n = np.asarray(n, dtype=float)
return float(np.... |
49dbc509a712c4184adf438a1fa7e9a6be159ec7412dae4a26416c16976d2d02 | Python | 7,555 | 179 | #!/usr/bin/env python
# Copyright 2016-2021 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... |
548354828376b9d8a7db76cdb8dcb356b833552c20444ef586c74b81936d78ea | Python | 7,556 | 232 | # Script that makes use of more advanced feature selection techniques
# by Alberto Tonda, 2017
import copy
import datetime
import logging
import numpy as np
import os
import sys
import pandas as pd
from sklearn.ensemble import AdaBoostClassifier
from sklearn.ensemble import BaggingClassifier
from sklearn.ensemble im... |
9fac0ab37e696e80b77a4e3befaf6a695f3a8884dec73c996874f6c7d17877b9 | Python | 7,562 | 82 | from tristan_pipeline.io.params import *
import glob
import nibabel as nib
#from nilearn.image import mean_img
def load_rawdata(RAW_PATH, subj, ses,moco):
RFUNC_PATH = glob.glob(os.path.join(RAW_PATH, f'sub-{subj:02}', f'ses-{ses}', 'func', f'sub-{subj:02}_ses-{ses}*_acq-{moco}_bold.nii'))
RFMAP_PATH = glob.g... |
b0b8493cd44a2ddd1e75cd6e7574c7e6be85f5628edade51564ed67c8aaa58fa | Python | 7,568 | 226 | import torch
import wandb
import matplotlib.pyplot as plt
import seaborn as sns
from torchmetrics import Metric
def log_confusion_matrix_advanced(
conf_matrix,
class_names=None,
step=None,
normalize=False,
title="Confusion Matrix",
split="train",
cmap=sns.color_palette("YlOrRd", as_cmap=Tr... |
4c0f59b6ba60d25f501facb28ecfc7544cf9b1521d3f014ec5f37339643816e6 | Python | 7,570 | 265 | """
Molecular featurisation for VAE models.
Converts RDKit molecule objects into the flat adjacency/feature tensor
representation consumed by the VAE. Deliberately free of ``torch_geometric``
so that generation work never pulls in the GNN stack.
"""
import logging
from typing import Any, Dict, List, Optional, Tuple
i... |
e2629991e7b56b78d2d51261bf9888da4b6881bcf507ed5230301f4bf9d2b0ac | Python | 7,572 | 202 | # Copyright (c) Facebook, Inc. and its affiliates.
import copy
import io
import logging
import numpy as np
from typing import List
import onnx
import torch
from caffe2.proto import caffe2_pb2
from caffe2.python import core
from caffe2.python.onnx.backend import Caffe2Backend
from tabulate import tabulate
from termcolo... |
b88a8c7305bd4967041c69fd1c5c5c6f586cf7c6a0490caff5eb72260c0bbcff | Python | 7,584 | 229 | from functools import partial
import logging
import multiprocessing as mp
import os
import pandas as pd
from pathlib import Path
import re
from tqdm import tqdm
from typing import Optional
logger = logging.getLogger("balanced_interpolation_ds")
def filter_seqs(
recs: pd.DataFrame,
min_len: Optional[float] =... |
7d037d5013a68c72afe61c7fa9d49493bdfe88057b100a217beeec7fe2581116 | Python | 7,585 | 200 | import logging
from enum import Enum
from functools import partial
from os import PathLike
from pathlib import Path
from typing import Generator, Optional, Sequence, Tuple, Union
import numpy as np
import pandas as pd
from scipy.ndimage import distance_transform_edt
from scipy.spatial.distance import pdist, squareform... |
93616064f89c4381d33f4983383389b33d7cc33eb560ba01b5982da33b8015fa | Python | 7,590 | 249 | # Configuration file for the Sphinx documentation builder.
#
# This file only contains a selection of the most common options. For a full
# list see the documentation:
# http://www.sphinx-doc.org/en/master/config
# -- Path setup --------------------------------------------------------------
# If extensions (or module... |
2b69d4c74268c2b5046547cdb20ada5620bc28bdb99b2b47e49ec13374cd5583 | Python | 7,593 | 201 | import os
import numpy as np
import pandas as pd
import umap
import matplotlib.pyplot as plt
import anndata as ad
import scanpy as sc
import scvelo as scv
import cellrank as cr
import scanpy.external as sce
from scipy.io import mmwrite, mmread
import statsmodels.api as sm
np.random.seed(42)
# peak-gene linkage matrix... |
01a7870e7a64a68cb3c6b8be8f4ff25f42282531e7ab0af74520edba554f1d13 | Python | 7,601 | 200 | from __future__ import annotations
import logging
from pathlib import Path
from types import SimpleNamespace
import uuid
from rdkit import Chem
from src.utils.models import MolecularRecord
from src.workflow import pipeline
class _FakeSource:
def __init__(self, settings: dict) -> None:
self.settings = s... |
05f208174c260b487555f6eda00bb512e9809e99e7171e6161c113d744bf0692 | Python | 7,602 | 202 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Plot Hide-the-Label mean steps per optimizer from a results JSON.
Supports two structures:
- optimizer_stats: { OPT: { mean_steps, std_steps, success_rate, ... }, ... }
- tournament/competitions: competitions[*].optimizer_results[OPT].steps_to_target
Usage:
Set the... |
514d2d5e81a5a95bbf93cd0b182274e3a84a30c1acb4224aa7244c616164b764 | Python | 7,609 | 195 | #!/usr/bin/env python
# Copyright 2016-2021 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... |
da0b603280938443165515298ecd00a56214846ddd99d104ccef5c9824663a85 | Python | 7,615 | 201 | import os
import sys
import numpy as np
import torch as tc
import torch.nn as nn
from sklearn.mixture import GaussianMixture as GMM
from argparse import Namespace
sys.path.append("../..")
from src.rnn.models import linear_observation_model, identity_observation_model, PLRNN, clshPLRNN, shPLRNN
class RNN_cont_Model(nn... |
1a176f13991fbdc6291829ddfb72527453f3f315a25804c3dcb1ba9970b972cb | Python | 7,617 | 176 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
# Copyright (c) Facebook, Inc. and its affiliates.
import copy
import json
import os
from collections import defaultdict
# This mapping is extracted from the official LVIS mapping:
# https://github.com/lvis-dataset/lvis-api/blob/master/data/coco_to_synset.json
COCO_SYNSE... |
55816d89c6958b45bea5ecbf6d6e5e007ca5db84e07a7dc1e4a50762e3b1e691 | Python | 7,619 | 209 | # Copyright (c) Facebook, Inc. and its affiliates.
import itertools
import json
import numpy as np
import os
import torch
from pycocotools.cocoeval import COCOeval, maskUtils
from detectron2.structures import BoxMode, RotatedBoxes, pairwise_iou_rotated
from detectron2.utils.file_io import PathManager
from .coco_evalu... |
86df3e654c4d6e35e81813b50a3f522ba15237834211cca93dd33793762137ce | Python | 7,631 | 191 | from dataclasses import dataclass
from pathlib import Path
from typing import Union
from toolbox.utils import simulation_params as simp, screen_params as scp, load_param_from_config
@dataclass
class Entry:
"""This is a data class to hold the entry data structure
Attributes
----------
me... |
37e0251bf24b517e6989671127d20ac320017e0a76d205c64660d81e55ff74aa | Python | 7,636 | 175 | # Copyright (c) Facebook, Inc. and its affiliates.
import numpy as np
import unittest
import torch
from detectron2.layers import DeformConv, ModulatedDeformConv
from detectron2.utils.env import TORCH_VERSION
@unittest.skipIf(
TORCH_VERSION == (1, 8) and torch.cuda.is_available(),
"This test fails under cuda1... |
db688869e1bc73809d1faa3c3412225f9eb2a71ee80eb6f95b700d41ac42e0ed | Python | 7,641 | 155 | # Copyright (c) Facebook, Inc. and its affiliates.
# Reference: https://github.com/bowenc0221/panoptic-deeplab/blob/aa934324b55a34ce95fea143aea1cb7a6dbe04bd/segmentation/data/transforms/target_transforms.py#L11 # noqa
import numpy as np
import torch
class PanopticDeepLabTargetGenerator:
"""
Generates trainin... |
b4b130c21bafbd1b48b77c7dd72c65704616c31037129681d19069fbd62d84a6 | Python | 7,645 | 198 | #!/usr/bin/env python
# Copyright 2016-2023 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... |
ff9e89856a5f094d6ff21c50df3faa5f1624981a46fed22212066325b9957bcb | Python | 7,654 | 209 | """
Sequence embedding models for protein representation.
This module provides wrappers for protein language models (ESM-2)
used to generate sequence embeddings for stoichiometry prediction.
"""
from abc import ABC, abstractmethod
from typing import List, Optional, Tuple, Union
import torch
from loguru import logger... |
65bf3e9dd89ceb20d610981520a7a6340e5440b20b0112fe322772e06c9e1418 | Python | 7,665 | 276 | """
Utility functions for affinity/similarity matrices.
"""
# Author: Oualid Benkarim <oualid.benkarim@mcgill.ca>
# License: BSD 3 clause
import numpy as np
from scipy import sparse as ssp
def is_symmetric(x, tol=1E-10):
"""Check if input is symmetric.
Parameters
----------
x : 2D ndarray or spars... |
f054187e8a6336675d1ca2d436aaa96933b37c296f2c9c8746ef5350404b5e45 | Python | 7,671 | 206 | import torch
import torch.nn as nn
import numpy as np
import modules
from util import aa_sequences_to_padded_onehot, pad_feature_matrices
device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
class RINAMI(nn.Module):
def __init__(
self,
device=device,
dropout=0.1,
... |
1eb3f7faec5e2b2d0343493391b4e28915fca7a623ae7beed97e1134b4111d69 | Python | 7,673 | 241 | import json
import shutil
from importlib import resources
from unittest import mock
import numpy as np
import pytest
from click.testing import CliRunner
from gufe import AlchemicalNetwork, SmallMoleculeComponent, SolventComponent
from gufe.tokenization import JSON_HANDLER
from openff.utilities.testing import skip_if_m... |
69fdf34aa546679f2193357165d74d9fd58b77af2edcc7efd87ec099a28a990c | Python | 7,675 | 188 | """
core/spikes.py
--------------
Spike-level processing: filtering, binning, ISI metrics.
All functions take plain numpy arrays or dicts — no file I/O here.
"""
import numpy as np
import pandas as pd
from typing import Dict
# ── Active-electrode filter ────────────────────────────────────────────────────
def filter... |
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