sha256 stringlengths 64 64 | language stringclasses 27
values | size int32 1 491k | lines int32 1 21.8k | content stringlengths 1 200k |
|---|---|---|---|---|
f15ba9995b7ea59a87f3a437f3fa11f0b873cbeb2c61e7aa8202e6f39f2ba3fd | Python | 8,701 | 249 | from Bio import AlignIO
from glob import glob
from functools import partial
import logging
import multiprocessing as mp
import numpy as np
import os
import pandas as pd
from pathlib import Path
import re
import traceback
from tqdm import tqdm
logger = logging.getLogger("no_interpolation_ds")
def read_genus_alignmen... |
e6c06f1eb279e5753459d87eacc823392b35a1c6ab47b83c7ce346d76aa58d50 | Python | 8,710 | 252 | """
Clustering and sampling of surface mesh points.
"""
# Author: Oualid Benkarim <oualid.benkarim@mcgill.ca>
# License: BSD 3 clause
from warnings import warn
import numpy as np
from sklearn.preprocessing import normalize
from sklearn.cluster import AgglomerativeClustering
from sklearn.cluster import k_means
# fr... |
e7487e607faef76a0f7987f1f9aae03e9587189ab864b7cc6a047381f9b15441 | Python | 8,711 | 198 | ############################################################################
# Copyright (c) 2025-2026 University of Helsinki
# All Rights Reserved
# See file LICENSE for details.
############################################################################
"""Tests for JointExonCounter: region-based exon quantificatio... |
099dfbdae2a83a525878a019c4eea19dc4db7d7bede56e15b3e491d51d5294b4 | Python | 8,712 | 213 | import batch_process.postprocessing.stim_response_util as stim_response_util
import numpy as np
import matplotlib.pyplot as plt
def get_baseline_interval_start_times(stim_timestamps, timing_params):
trains = stim_response_util.group_stim_pulses_into_trains(
stim_timestamps, timing_params)
... |
a9ae2138d3a81ace67c6eeec99b657660826781a7a213abc1516140628bbca1e | Python | 8,718 | 287 |
""" Utility functions for templates. """
__author__ = "Fabi Bongratz"
__email__ = "fabi.bongratz@gmail.com"
import os
from collections.abc import Sequence
from copy import deepcopy
import torch
import torch.nn.functional as F
import trimesh
import numpy as np
import nibabel as nib
from trimesh.scene.scene import Sc... |
4b4013c6f4fe9603489e8471956ea7dfc7a181190f5957bfda4efe5e6ddfd32e | Python | 8,723 | 246 | # 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... |
157a68e1c2274414aff005a47842bae52df843800ca779b4c429b40dd14eb362 | Python | 8,726 | 208 | import torch
import numpy as np
import argparse as ap
import os
try:
from models.gmx_ani import GmxANIModel
except ImportError:
GmxANIModel = None
try:
from models.gmx_mace import GmxMACEModel, GmxMACEModelNoPairs
except ImportError:
GmxMACEModel, GmxMACEModelNoPairs = None, None
try:
from models.gm... |
dfcbe9dbe8ab8b568ff5af48673994a0514d091172b1d496366875f24029a85e | Python | 8,734 | 202 | import os
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import anndata as ad
import scanpy as sc
from scipy.io import mmwrite, mmread
import seaborn as sns
import scipy
np.random.seed(42)
dir_path = "/home/nomura/Proj/mmvelo/experiments/Greenleaf_multiome_Cond_merged_all_missing/2024-01-19T11... |
25d360daf2da56c79d535a9ac7eba5f0e8fd514dd8480e00fadf902846f814f3 | Python | 8,747 | 181 | from typing import Union, List, Tuple
from nnunetv2.configuration import ANISO_THRESHOLD
from nnunetv2.experiment_planning.experiment_planners.default_experiment_planner import ExperimentPlanner
from nnunetv2.experiment_planning.experiment_planners.residual_unets.residual_encoder_unet_planners import \
nnUNetPlann... |
8324708fedee0b0af1cc9043f6b7eaeaf3bb44e6e64ba2b92e75a3771bf05cac | Python | 8,747 | 173 | '''
Created on Jul 8, 2024
@author: voodoocode
'''
import mne.io
import os
import csv
import scrubber.core
import pyexcel
COLLECTION_META_PATH = "/mnt/data/Professional/LMU/data/Beta-prevalence/data_collection_db2.csv"
TGT_FS = 600
MIN_TIME_S = 30
MAX_TIME_S = int(5 * 60) - 30 # Max 5 min
IN_PATH = "/mnt/data/P... |
b528f027631555b4b04357d7f6f03274af036761e80b096ae8e4f239d6478576 | Python | 8,768 | 261 | """Figure S1 — Behavioral characterization.
Panels:
A: Response time histogram
B: CDF of response times
C: Psychometric curves (example session)
D: Detection thresholds over weeks (individual animals)
E: Response times over weeks (individual animals)
Usage:
python python/fig_s1/generate_figure.py
"""
im... |
6e3e51b796e4319aa5c459a6553e2d98b759c3338bd082ac3376fb7350cae522 | Python | 8,774 | 207 | # Copyright (c) Facebook, Inc. and its affiliates.
# pyre-unsafe
import math
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 .. import DensePoseConfidenceModelConfig, DensePoseUV... |
a676a98f7d717727f28f176a0770c314bfd321b34643acc8180fbe15502fb08f | Python | 8,778 | 247 | # This code is part of OpenFE and is licensed under the MIT license.
# For details, see https://github.com/OpenFreeEnergy/openfe
"""
Reusable utility methods to create Systems for OpenMM-based alchemical
Protocols.
"""
from pathlib import Path
from typing import Optional
import numpy as np
import numpy.typing as npt
... |
4f720edfe119481cc70ce7354b1a6a3cae6fcb759db5f9c0bf7d2339ad937907 | Python | 8,780 | 217 | from pathlib import Path
import ast
import hashlib
import json
import re
import sys
import joblib
import pandas as pd
import yaml
ROOT = Path(__file__).resolve().parents[1]
EXPECTED = [
"README.md",
"MANIFEST.tsv",
"CHECKSUMS.sha256",
"run_windows.bat",
"install_windows.bat",
"requirements.tx... |
99fd6a8606eeb92196039a3558481a33e63290eba917216dc776525381e4ab86 | Python | 8,797 | 238 | """Figure S9 -- Pop coupling panels (700ms, 120ms, control).
Generates standalone pop coupling comparison panels for supplementary figure.
Usage (from repo root):
python -m python.fig_s9.generate_figure
"""
import sys
from pathlib import Path
sys.path.insert(0, str(Path(__file__).resolve().parents[1]))
import ma... |
6c48e372a34b19ffcd45d121db726f0e08a8864e0e477d40e836346288d97e7d | Python | 8,798 | 298 | # 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... |
e8e538f185c3b79e0b49d88260c5988f73fd29d4dc96b1ca76695fa85c4b8369 | Python | 8,798 | 138 | # Copyright (c) Facebook, Inc. and its affiliates.
import contextlib
import copy
import io
import json
import numpy as np
import os
import tempfile
import unittest
import torch
from pycocotools.coco import COCO
from pycocotools.cocoeval import COCOeval
from detectron2.data import DatasetCatalog
from detectron2.evaluat... |
887acf18f7367289a6d0dbfbfc8ee6293682f0f1de3d46d39b1c8e07c88436a6 | Python | 8,803 | 187 | """Pair KNN and median/mode model-performance and SHAP sensitivity outputs."""
from __future__ import annotations
import argparse
import json
from pathlib import Path
import numpy as np
import pandas as pd
METRICS = ("r2", "mae", "mse", "rmse")
def _metric_payload(cache: Path, model: str) -> dict[str, float]:
... |
6e42c0669ab302f3ea33fcb2709930a74ed2f0e4cba60ec1dd318c20f9e879e8 | Python | 8,804 | 201 | """
Skeletons
=========
<!-- difficulty: intermediate -->
Explore skeletons in an interactive 3D viewer - then render what you set up into a figure.
Where [`plot2d`][navis.plot2d] fakes depth, [`plot3d`][navis.plot3d] has a real renderer: proper
occlusion, proper perspective, and a camera you can throw around. The tr... |
93716277a57f4108c9c163777db4c2178ddb50a1ac59da00385a0ad29ef84119 | Python | 8,807 | 209 | # Copyright (c) Facebook, Inc. and its affiliates.
import itertools
import logging
from typing import Dict, List
import torch
from detectron2.config import configurable
from detectron2.layers import ShapeSpec, batched_nms_rotated, cat
from detectron2.structures import Instances, RotatedBoxes, pairwise_iou_rotated
from... |
0ff238eb01a167f80cf6450f6598d2be01180d23397196222dad049c0c793a84 | Python | 8,813 | 307 | #%%
import pandas as pd
import mne
import scipy.signal as dsp
import joblib
from pathlib import Path
from os.path import join
import scipy.stats as stats
import matplotlib.pyplot as plt
import seaborn as sns
import numpy as np
import pingouin as pg
from fooof import FOOOFGroup
from fooof.utils.params import compute_kne... |
1ab943faffba46db12e9082397227471dcb1eff36a7eb2eded5045305062c210 | Python | 8,814 | 190 | # ------------------------------------------------------------------------------
# Title: Summary of Commot Spatial Communication Results
# Author: Yiran Song
# Date: March 18, 2025
# Description:
# This script extracts and summarizes pathway-level ligand-receptor interactions
# from Commot spatial communication result... |
f2cbd5eec3b6e1a80b309f4cc7f36080b57cdde2dc5bfef106d5e54234584e5a | Python | 8,819 | 249 | #!/usr/bin/env python3
"""Computes PNG counts from hyperparameter sweep experiments.
This script takes PNG detection databases from hyperparameter sweep experiments
and computes counts per layer, outputting serialised results organised by
hyperparameter value.
The swept hyperparameter is automatically detected from t... |
4eb017b27f1b27e0a2cbb76f95a3ccacce94280a42e0eb70bf8683e071f0c771 | Python | 8,829 | 263 | # Copyright (c) Facebook, Inc. and its affiliates.
import importlib
import numpy as np
import os
import re
import subprocess
import sys
from collections import defaultdict
import PIL
import torch
import torchvision
from tabulate import tabulate
__all__ = ["collect_env_info"]
def collect_torch_env():
try:
... |
a514902954dff414a214e4f1931606a949a595de16ca117df371358bd6bf73c4 | Python | 8,830 | 254 | import numpy as np
from collections import deque
from copy import deepcopy
from matplotlib import pyplot as plt
def firing_rate(v, beta):
return 1.0 / (1.0 + np.exp(-beta * v))
class Neuron():
'''
A neuron class with simple continuous dynamics exhibiting firing rate adaptation
'''
def __init__(sel... |
42cd02857cbd53b00ef18883191bccb663083b3b32828a0e27b4d128312a375a | Python | 8,837 | 305 | # %%
from __future__ import annotations
import sys
import matplotlib.pyplot as plt
import mne
import numpy as np
import seaborn as sns
from matplotlib import font_manager as fm
from matplotlib.gridspec import GridSpec
from mne.io import BaseRaw
from mne_bids import find_matching_paths
from mne_bids import read_raw_bi... |
83bdda7536148fc87773fb80a42b21a314990215fccc073997d4f3aa994b2edf | Python | 8,838 | 313 | import numpy as np
def freedman_diaconis_bins(x):
"""
Return the optimal number of histogram bins using
the Freedman–Diaconis rule.
Parameters
----------
x : array-like
1D array of samples.
Returns
-------
int
Number of bins.
"""
x = np.asarray(x).ravel()
... |
c127a31f67f9cc38e3fa31195312a23ffb7c959069857b1e6ce5500efa22ede6 | Python | 8,839 | 246 | #!/usr/bin/env python3
#
# Copyright (c) 2025 10X Genomics, Inc. All rights reserved.
#
"""Generate library plots for multi web summary.
For a single library, generate the barcode rank, jibes plots as plotly JSON, and barnyard count
biplots, so that they can be passed forward to the WRITE_MULTI_WEB_SUMMARY stage and i... |
ab4b55db4040c5a6d942fbde4a0b5e4f78a967bdb33dd09f74a490a3937e9eef | Python | 8,840 | 245 | #!/usr/bin/env python3
# Copyright (c) Facebook, Inc. and its affiliates.
# Lightning Trainer should be considered beta at this point
# We have confirmed that training and validation run correctly and produce correct results
# Depending on how you launch the trainer, there are issues with processes terminating correctl... |
c0fb5542ece58cda30688f1a272395b42b493c69deb12e2157fb633eede875b3 | Python | 8,841 | 266 | """
Embedding alignment using procrustes analysis.
"""
# Author: Oualid Benkarim <oualid.benkarim@mcgill.ca>
# License: BSD 3 clause
import numpy as np
from sklearn.base import BaseEstimator
def procrustes(source, target, center=False, scale=False,
return_transform=False):
"""Align `source` to ... |
0359b586c082c5f83ec9d8dca44e8e14e3ffa61683a8ebd5cf4b925eaad58bd6 | Python | 8,866 | 259 | from Bio import AlignIO
from glob import glob
from functools import partial
import logging
import multiprocessing as mp
import numpy as np
import os
import pandas as pd
from pandarallel import pandarallel
from pathlib import Path
import traceback
from tqdm import tqdm
logger = logging.getLogger("balanced_interpolatio... |
50e3a8fa5148623192e0c88ef71ba2b591723351d11f1b40b420e5d1e3ebae98 | Python | 8,884 | 243 | # Copyright (c) Facebook, Inc. and its affiliates.
import io
import unittest
import warnings
import onnx
import torch
from packaging import version
from torch.hub import _check_module_exists
from detectron2 import model_zoo
from detectron2.config import get_cfg
from detectron2.export import STABLE_ONNX_OPSET_VERSION
... |
3cf38b57215a85828662ac453b98c82806fbc336a8a645755869d65c5c706457 | Python | 8,885 | 265 | #%%
from pathlib import Path
import sys
sys.path.append('/mnt/obob/staff/fschmidt/cardiac_1_f')
from utils.data_loading import data_loader
import bambi as bmb
from scipy.stats import zscore
import arviz as az
import pingouin as pg
import pandas as pd
import joblib
import numpy as np
import pymc as pm
import matplotlib... |
123011374b8db75f056952dba05726f91fd82f991a3fd9011d7ac92b7f5a8c8f | Python | 8,905 | 250 | from typing import List
import torch
import stoic.model as model_module
from stoic.model import Stoic
class DummySeqEmb(torch.nn.Module):
def __init__(
self,
model_name: str,
max_seq_len: int = 8,
full_length_inference: bool = False,
max_inference_seq_len=None,
fi... |
ed7c7242b8e792d4fcd6bd807399daea945a6543da791b8bfaa688f846df6f88 | Python | 8,906 | 253 | #!/usr/bin/env python
#
# Copyright (c) 2019 10x Genomics, Inc. All rights reserved.
#
from __future__ import annotations
import json
from typing import TYPE_CHECKING
import martian
import numpy as np
import cellranger.constants as cr_constants
import cellranger.matrix as cr_matrix
import cellranger.rna.library as... |
849ff643eed26c0b125b3d0de093b9758a352e15b9d90e0e9fd8c137626d1ec9 | Python | 8,907 | 193 | from matplotlib import pyplot as plt
import numpy as np
import os
import pickle
from scipy.signal import savgol_filter as sg
from rCPGswCPG.utils.gen_utils import get_project_root
from rCPGswCPG.utils.utils import get_val_of_param
from rCPGswCPG.model_params.config_loader import load_model_cfg_file, model_params_from_c... |
92ba95e6f6950d9e8021358346ea35e194b492a7c96bf20551b78b6dca82fb80 | Python | 8,923 | 265 | """
Created on May 14, 2025.
@author: voodoocode
"""
import pyvista
import numpy as np
import scipy.ndimage
import shutil
import finnpy.misc.external_calls as ex_c
import os
import finnpy.visualization.volumetric_plots as vp
np.random.seed(0)
STRUCT_PATH = "/mnt/data/Professional/projects/finnpy/DISTAL (Ewert 2017)... |
a593014c47d83762b3a8a4cb1071e937327beab3f8c57745dcfc4af95a5a4936 | Python | 8,928 | 289 | import numpy as np
from PIL import Image
import matplotlib.pyplot as plt
from glob import glob
from scipy.io import loadmat
def createFlowDataset(categories, topdir, mydirs, orig_shape, input_shape, scl_factor, N_INSTANCES, trial_len, stride):
scld_shape = tuple((np.array(orig_shape)*scl_factor).astype('int'))
... |
321b180ea0802182ff4d17b5c363805ce11c1a501b92a9e8727b94e9cfe3bb12 | Python | 8,930 | 260 | """ Test null models """
import pytest
import numpy as np
from scipy.spatial.distance import pdist, squareform
from tempfile import gettempdir
from os.path import join, exists
import vtk
from brainspace.vtk_interface import wrap_vtk
from brainspace.vtk_interface.pipeline import to_data
from brainspace.mesh import me... |
bcb151e77ae3b3820408b0477eb93d204b51dcbb92504fc1b42d20e824615f74 | Python | 8,930 | 213 | import torch
import torch.nn.functional as F
from stoic_train.losses import (
ComplexProductLoss,
FocalLoss,
ResidueWeightFocalLoss,
ResidueWeightKLLoss,
ResidueWeightL1Loss,
SparsityLoss,
)
def test_focal_loss_reduction_none_returns_per_sample_vector() -> None:
inputs = torch.tensor([[2.... |
c3f25ae759f8d7a9c3a26d81e06006f43c7c73e0d1c39699f6b97d9054070f65 | Python | 8,930 | 379 | open_images_unify_categories_for_coco = {
'/m/03bt1vf': '/m/01g317',
'/m/04yx4': '/m/01g317',
'/m/05r655': '/m/01g317',
'/m/01bl7v': '/m/01g317',
'/m/0cnyhnx': '/m/01xq0k1',
'/m/01226z': '/m/018xm',
'/m/05ctyq': '/m/018xm',
'/m/058qzx': '/m/04ctx',
'/m/06pcq': '/m/0l515',
'/m/03m... |
aad6cc841345eea47d168cf35c408d546f6e4d9e5a73b52031a0980ebaeb0d7d | Python | 8,941 | 274 | import torch
from stoic.feature_pooling import (
AveragePooling,
MaskedInstanceNorm1d,
SelfAttentionPooling,
)
def test_masked_instance_norm_preserves_shape() -> None:
norm = MaskedInstanceNorm1d(num_features=4, affine=True)
x = torch.randn(2, 4, 6)
mask = torch.tensor(
[[False, False... |
9d5fd523c0b72f685512535137a41b575f109d6ac5f6f567a3a3f3c099141896 | Python | 8,944 | 232 | #!/usr/bin/env python3
############################################################################
# Copyright (c) 2023-2026 University of Helsinki
# # All Rights Reserved
# See file LICENSE for details.
# Author: Andrey Prjibelski
############################################################################
import ar... |
a7d0efd5ad9f4b8fee58456848ca810fb0c754190ee1fccaef952bcc017a021d | Python | 8,945 | 254 | # --- Python 标准库 ---
import gc
import warnings
# --- 第三方核心科学计算库 ---
import numpy as np
import pandas as pd
# --- 生物信息学与数据分析库 ---
import anndata as ad
import scanpy as sc
import seaborn as sns
import matplotlib.pyplot as plt
# --- 深度学习库 (PyTorch) ---
import torch
import torch.nn.functional as F
# --- 脚本级别的设置 ---
war... |
f80b86de65bec65368f55f83a6226a5e9e4efc5b30dbdeb572e6fe856106d8fc | Python | 8,950 | 240 | # Copyright (c) 2019 10x Genomics, Inc. All rights reserved.
from __future__ import annotations
import csv
import os
from collections import Counter
from typing import TYPE_CHECKING
import numpy as np
from six import ensure_binary, ensure_str
if TYPE_CHECKING:
from collections.abc import Iterable, Mapping
cla... |
caedae4269b3d5d2220cf63ce6b7bca9d22e3d06b2d483801f71d84d5e7716c3 | Python | 8,953 | 247 | # Copyright (c) Facebook, Inc. and its affiliates.
import logging
import math
from bisect import bisect_right
from typing import List
import torch
from fvcore.common.param_scheduler import (
CompositeParamScheduler,
ConstantParamScheduler,
LinearParamScheduler,
ParamScheduler,
)
try:
from torch.opt... |
48f23dab7b983e9ae023f72ba6a671182aa403cdc8cad198844776fdb8989d8f | Python | 8,956 | 197 | from typing import Union
import numpy as np
import tifffile
import torch
from .unet3d import UNet3D
from ..progress import ProgressNotifier
from ..utils import save_as_tif, get_device
class Predict:
"""
Class for prediction of movies or 3D stacks with 3D U-Net
1) Loading file and preprocess (normalizat... |
c12af987b74bf151096e9d7a9e3c29d1c9e01bf78553b05ba50c6dc839cb0ce1 | Python | 8,959 | 284 | """tests for matplotlib components."""
import networkx as nx
import pytest
from matplotlib.figure import Figure
from mesa import Model
from mesa.discrete_space import (
CellAgent,
HexGrid,
Network,
OrthogonalMooreGrid,
VoronoiGrid,
)
from mesa.visualization.components import AgentPortrayalStyle, P... |
5ca8cdb352f35ec30dab3af4698e362d304996e3b847565d976d233b1f22b490 | Python | 8,960 | 223 | #!/usr/bin/env python
#
# Copyright (c) 2016 10X Genomics, Inc. All rights reserved.
#
from __future__ import annotations
import csv
import os
import shutil
import martian
import tenkit.bcl as tk_bcl
import tenkit.lane as tk_lane
import tenkit.preflight as tk_preflight
import tenkit.samplesheet as tk_sheet
__MRO__... |
f844d7b95a0382560477cbf21cd271510c89a1c5f64248bda2b4796a6b90ba3c | Python | 8,965 | 218 | # -*- coding: utf-8 -*-
"""
Figure 5: Receptor x Cognition PLS analysis
Note: to load pls_result:
pls_result = pyls.load_results(path+'results/pls_result.hdf5')
"""
import numpy as np
import pandas as pd
import pyls
import matplotlib.pyplot as plt
from matplotlib.colors import ListedColormap
import seaborn as sns
from... |
48a2da4fee36113bc44a7c6f2eb14206eb64038cc99f60d4b7dcbad0d75ed636 | Python | 8,966 | 267 | """
CASCADE built-in self-test
==========================
Generates a synthetic MEA recording and runs every core module.
No real data files required.
Usage:
cascade --test
"""
import sys
import traceback
import numpy as np
from cascade.utils.common import MEARecording
# ── terminal colours ───────────────────... |
4cd44410ab2aa000f3c8fa954e02cc502e883b8f1e43c2e8942af78444c87326 | Python | 8,966 | 205 | # -*- coding: utf-8 -*-
"""
Save output from readCMRRPhysio.py in BIDS format, taking number of skipped
volumes in FMR into account.
This script runs with physiological data (pulse and/or respiratory) saved as
_Info.log, _PULS.log, _RESP.log or for physiological data saved in DICOM/IMA
As input it requires the physio... |
b073a2a841e17f6dfa081ac83b4f5c661e3cb99cab6212d82dd8f2f01eac5540 | Python | 8,969 | 221 | """Bundle save/load round-trips for all three model families.
The bundle is the interface between training and inference, and Stage 2
changed its dispatch: the MLP branch was removed and a VAE branch added.
These tests pin down that ``config_type`` still routes correctly, and that the
legacy architecture aliases keep ... |
50f1e8c1763fef86c5df624d0af330898555cf6d18b7dc8e925aedb6a76ec8ee | Python | 8,977 | 228 | # Copyright (c) Facebook, Inc. and its affiliates.
import copy
import json
import os
from detectron2.data import DatasetCatalog, MetadataCatalog
from detectron2.utils.file_io import PathManager
from .coco import load_coco_json, load_sem_seg
__all__ = ["register_coco_panoptic", "register_coco_panoptic_separated"]
d... |
34a0add1293f3a15960a388fe975e668d5f69b6a458c4572999a415fa63f2528 | Python | 8,997 | 286 | from __future__ import annotations
from collections.abc import Iterable, Iterator, Mapping
from typing import Literal, TypeVar, overload
import more_itertools as itx
from snakebids.types import ZipList, ZipListLike
from snakebids.utils.containers import ContainerBag, MultiSelectDict, RegexContainer
T_co = TypeVar("... |
a12b24134b37216d4dab5e92acb725eecd119a8c3a591c818cedd5297066f483 | Python | 9,002 | 251 | """Behavioural contracts for the morphometrics fastcore implements.
Replaces `tests/test_fastcore.py`, which was entirely differential: every test
computed a quantity with navis-fastcore and again with it monkeypatched away,
and asserted the two matched. With fastcore a hard requirement there is no
second implementati... |
02864d52100e38ecb9ee6e31b05c4397b6318dfacd17c5fbfdf2056fd3a9307c | Python | 9,003 | 315 | # This code is part of OpenFE and is licensed under the MIT license.
# For details, see https://github.com/OpenFreeEnergy/openfe
"""
Reusable utility methods to validate input settings to OpenMM-based alchemical
Protocols.
"""
from typing import Optional
from openff.units import Quantity, unit
from openfe.protocols.... |
800a86187759d9323fca39a9aae12251b893d587c018dbbbd774dbf892384c1e | Python | 9,003 | 255 | """Loss functions for stoichiometry model training."""
from typing import Dict, Optional, Tuple
import torch
import torch.nn as nn
import torch.nn.functional as F
class FocalLoss(nn.Module):
"""Focal loss for addressing class imbalance (Lin et al., 2017).
Down-weights well-classified examples so the model ... |
b2b1d8df9870977fef1192406aa7336916b63f4982dba97da748c70504033b22 | Python | 9,004 | 243 | """
===============================================================================
additional_classes.py
- Provides EnzymeDatasetAACoarseGrain, a lightweight PyG Dataset that
builds coarse‑grained amino‑acid graphs from mmCIF files.
- Each residue becomes one node (centroid of its atoms), features are
[coords or... |
6d169f4bf4b4b4d12417fb12acadeb4b51164d906113b0142be55884c81016ef | Python | 9,008 | 235 | # Copyright (c) Facebook, Inc. and its affiliates.
import numpy as np
from typing import Any, List, Tuple, Union
import torch
from torch.nn import functional as F
class Keypoints:
"""
Stores keypoint **annotation** data. GT Instances have a `gt_keypoints` property
containing the x,y location and visibilit... |
eef5c8f2d8510204c1c1ffa216b92f11413f33cec3a26347ac48b6b63e9ab98c | Python | 9,013 | 255 | # --- Python 标准库 ---
import gc
import warnings
# --- 第三方核心科学计算库 ---
import numpy as np
import pandas as pd
# --- 生物信息学与数据分析库 ---
import anndata as ad
import scanpy as sc
import seaborn as sns
import matplotlib.pyplot as plt
# --- 深度学习库 (PyTorch) ---
import torch
import torch.nn.functional as F
# --- 脚本级别的设置 ---
war... |
be837c1382768df158c3d20be5758aa76b58d56d1853ff472392c49730282fca | Python | 9,015 | 171 | """
Standalone pass that builds the foreground sampling location store for a preprocessed
configuration folder.
This is deliberately separate from preprocessing:
* it only reads the stored ``_seg.b2nd`` files, never the image data. On TotalSegmentator v2 that
is 0.24 GB rather than 45 GB, so a full re-extraction... |
d1ac40e1583274cadf1b88d6899c402f01b08c61fec214d508347cb2bd2807a5 | Python | 9,018 | 198 | import csv
import os
import random
from pathlib import Path
import nibabel as nib
from batchgenerators.utilities.file_and_folder_operations import load_json, save_json
from nnunetv2.dataset_conversion.Dataset027_ACDC import make_out_dirs
from nnunetv2.dataset_conversion.generate_dataset_json import generate_dataset_j... |
62b5cc534aab925735b3dc4d6c9363efdd9cea513b04fb35c6e828023436870c | Python | 9,028 | 226 | import os
import numpy as np
import pandas as pd
import anndata as ad
import numpy as np
import scanpy as sc
import time
import matplotlib.pyplot as plt
from .TSvelo_utils import run_paga, run_palantir, get_colors, show_imgs, show_imgs_simple, show_imgs_alpha_s, sigmoid, relu, leaky_relu
from scipy.stats import pears... |
12d3b7dd3cb3ae13c839a35df588b3758a107a2ec6f1951d679f9b6e93d0b895 | Python | 9,046 | 286 | #!/usr/bin/env python
#
# Copyright (c) 2020 10X Genomics, Inc. All rights reserved.
#
"""Slice the filtered matrix into per sample matrices."""
from __future__ import annotations
import csv
import gc
import json
from typing import TYPE_CHECKING
import martian
import cellranger.cr_io as cr_io
import cellranger.matr... |
fbb771dff81602d4c5e85f40c176e2fac36c94037ea9b6de5b229db5d2420509 | Python | 9,060 | 316 | #!/usr/bin/env python3
"""Downloads IMGT sequences and creates a FASTA file suitable for input into `cellranger mkvdjref --seqs`.
Creates two files:
<prefix>-imgt-raw.fasta
<prefix>-mkvdjref-input.fasta
Where <prefix> is the string given via the --genome arg,
*-imgt-raw is the IMGT segments translated to FASTA,
... |
57378dbb895fd2e2f4350e10d589eabc3d0f9ee164be6051865fca080e25a60d | Python | 9,070 | 283 | """Tests for `navis.heal_mesh`.
Note that the example mesh genuinely consists of several connected components
(one main body plus a handful of small bits), so it doubles as a real-world
fixture here - no artificial fragmentation needed. The exact counts depend on
whatever mesh is currently vendored, so the tests below... |
71b2898edf171c328885c82345aa7b4d73a8131882359290846148810e499a4b | Python | 9,075 | 258 | """ Test whether the NestML implementation of the Triplet synapse (with TM dynamics) follows Python implementation. """
import matplotlib.pyplot as plt
import pandas as pd
import numpy as np
import nest
from test_utils import generate_code, generate_regular_spike_train, generate_poisson_spike_train
nmodel = "../netwo... |
781796ab09c5021fd56f7435fe3b8515b47dc1119d8dc31eddc8ea99fdf08865 | Python | 9,088 | 239 | # 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... |
620266ec8186dfb8b5faa9fb63ece8e76aa90978f69a4d7acd6d2151b4177c27 | Python | 9,113 | 210 | import pickle
import os
import numpy as np
from scipy.optimize import fsolve
from tqdm.auto import tqdm
import numdifftools as nd
import warnings
from rCPGswCPG.Network import firing_rate
from rCPGswCPG.Network import construct_model
from rCPGswCPG.model_params.config_loader import load_model_cfg_file, model_params_fro... |
5b354116186593f549776afbd46612d1dc19d3a57de60569725ac9b13f78c860 | Python | 9,117 | 222 | """MolGpKa protonation backend (new default, v1.3.0).
MolGpKa predicts a per-atom micro-pKa on the *neutral* molecule, independently
for each ionizable site. Applying Henderson-Hasselbalch to those independent
values over-protonates molecules with coupled ionizable centres (e.g.
piperazine would come out doubly proton... |
055460e65efebbe679918816234339d6b660412ca749a5e8e22036bd26191400 | Python | 9,122 | 272 | #!/usr/bin/env python
#
# Copyright (c) 2020 10X Genomics, Inc. All rights reserved.
#
"""A helper stage to put all of the per sample outputs together into a struct."""
from __future__ import annotations
import os
from typing import TYPE_CHECKING, Any
import martian
import cellranger.cr_io as cr_io
from cellranger.... |
9ba94687c11df4a4d8e567193d51cbf1e77d59c949665f84d7d8f2a62b0f0d2b | Python | 9,124 | 230 | """Speaker diarization using Silero VAD + Resemblyzer embeddings."""
import csv
import numpy as np
import torch
from scipy.cluster.hierarchy import fcluster, linkage
from scipy.spatial.distance import pdist, squareform
from .audio import load_audio_16k
from .config import TAPAConfig
def load_silero_vad():
"""L... |
d7be8733781b2248f3020a8b5b9941f3559ec7f53c34b0d6a78f0595a850ca10 | Python | 9,127 | 221 | ############################################################################
# Copyright (c) 2023-2026 University of Helsinki
# # All Rights Reserved
# See file LICENSE for details.
############################################################################
"""
Memory-efficient k-mer indexers using 2-bit DNA encoding... |
f974b6be09c24dce0da7a4a883d0cadf24ffffcfbb1ed4a2faf069743a3dbcaf | Python | 9,137 | 254 | """
PyTorch implementation of Arbitrary Style Transfer in Real-time with Adaptive Instance Normalization
[Huang+, ICCV2017]
This code is based on the following github repo: https://github.com/naoto0804/pytorch-AdaIN
(cloned on 22nd Feb 2018, commit 1a059f43ef5f67eb42daacb60869ed04b7c4c4c7)
"""
import os
import sys
im... |
8d9814bcf2787f28f7660a579750db0afcb02c79ca164938d4d45cd911a64fac | Python | 9,147 | 217 | #!/usr/bin/env python
#
# Copyright (c) 2026 10X Genomics, Inc. All rights reserved
#
"""Compute the per-barcode reduction plan for the CRISPR perturbation sufficient-statistics split.
`SPLIT_PERTURBATION_MATRIX` (Rust) streams the feature-barcode matrix once and emits, per
MEASURE chunk, the sSeq differential-expres... |
f73b33df4af69aac163eea4a2a722ef78fca9ba66e7771e613d5160bb934246f | Python | 9,181 | 288 | """
Molecular featurisation for GNN models.
Converts RDKit molecule objects into PyTorch Geometric graph Data objects.
VAE featurisation lives in :mod:`nfml.data.vae_featurisation`.
"""
import logging
from typing import Any, Dict, List, Optional, Tuple
import numpy as np
import torch
from rdkit import Chem
from rdkit... |
e364f62693e1c43356560fe655a77f75c5f325a4af721c8371c19055e5db3578 | Python | 9,190 | 215 | from pathlib import Path
import json
from datetime import datetime
import matplotlib.pyplot as plt
import shutil
import numpy as np
import torch
import torch.nn as nn
from tqdm import tqdm
from torch.utils.tensorboard import SummaryWriter
from model import MultiModalTransformer, MultiModalConv
from data2 import dataloa... |
65ee851e5bec0fe1ece0523c6dc9446748922031c515cf0bc47c968e1b5bb634 | Python | 9,201 | 253 | ############################################################################
# Copyright (c) 2023-2026 University of Helsinki
# # All Rights Reserved
# See file LICENSE for details.
############################################################################
"""
Basic k-mer indexers for barcode calling.
KmerIndexer: ... |
d7c50027d3f12698b19b9956044f881ca84c37727a53116f3bb323ffc1026497 | Python | 9,204 | 198 | import glob
import os
from typing import Union
import tifffile
import torch.optim as optim
from torch.utils.data import DataLoader, random_split
from tqdm import tqdm
from .losses import *
from .predict import Predict
from .unet import Unet
from .attention_unet import AttentionUnet
from ..utils import init_weights, g... |
fd0f456028fb37f83cf257b00d76c151d16a4d6140c3485617c4b3d8bb6fd2e5 | Python | 9,208 | 255 | """
Created on 11/09/2023
@author: Marc Schneider
Neuroimaging & Neuroengineering
Department of Neurology
University Hospital Cologne
"""
import nipype.interfaces.fsl as fsl
import os, sys
import nibabel as nib
import numpy as np
import applyMICO
import shutil
#makes sure to import bet.py
sys.path.insert(0, os.path... |
f0016e9124b030d8e76b2a6731dbfeef499b5c17ee732cc2acc1665dfb54b219 | Python | 9,210 | 230 | # Copyright (c) Facebook, Inc. and its affiliates.
import copy
import logging
import os
import torch
from caffe2.proto import caffe2_pb2
from torch import nn
from detectron2.config import CfgNode
from detectron2.utils.file_io import PathManager
from .caffe2_inference import ProtobufDetectionModel
from .caffe2_modelin... |
d6aecd2b13f7b6119a163aeb279b668127fb1ac6b789af7dd36fc0cd8a4e5d39 | Python | 9,211 | 265 | # -*- coding: utf-8 -*-
# Copyright (c) Facebook, Inc. and its affiliates.
import functools
import inspect
import logging
from fvcore.common.config import CfgNode as _CfgNode
from detectron2.utils.file_io import PathManager
class CfgNode(_CfgNode):
"""
The same as `fvcore.common.config.CfgNode`, but differe... |
9c803d0e72bff22c9b4fde9c71420b41f998c3ea255f85d59b017afcbe2d0d3c | Python | 9,221 | 254 | """Timestamped run folders under ``output/`` for analysis artifacts (not raw CZI inputs)."""
from __future__ import annotations
import io
import json
import os
import zipfile
from datetime import datetime
from typing import Any, Iterator
OUTPUT_ROOT = "output"
CHANNEL_MAPPING_CONFIG_FILENAME = "channel_mapping_confi... |
bdc8f7b09d55f475e57279d54d5bcb906853db39cf33b4bb930f19afadf3ed73 | Python | 9,240 | 280 | from sklearn.decomposition import PCA
import umap
import numpy as np
import matplotlib.pyplot as plt
from scipy.optimize import curve_fit
import pandas as pd
from spikeinterface import full as si
from pathlib import Path
import pickle
import batch_process.util.template_util as template_util
def get_trough... |
88fcc184f8b2edcb216c6b1ef321c23a228a20421a11bc2a2814c69aed3b60a8 | Python | 9,248 | 258 |
############################################################################
# Copyright (c) 2022-2026 University of Helsinki
# All Rights Reserved
# See file LICENSE for details.
############################################################################
#!/usr/bin/env python3
import os
import argparse
import nump... |
3f87aaf9198b84052e8b16a23376a59a3f248de28d625cb297453e3a531a06ba | Python | 9,251 | 285 | """
Class for Pseudobulking
"""
from typing import Optional, Union, List
import itertools as it
import numpy as np
import pandas as pd
import anndata as ad
from tqdm import tqdm
class ADPBulk:
def __init__(
self,
adat: ad.AnnData,
groupby: Union[List[str], str],
method: str = "sum"... |
95f0a1ab608b995188b2704069d4b83f8015dca1976055c27bc3aaa89c77f367 | Python | 9,261 | 315 |
import os
import time
import random
import numpy as np
import pandas as pd
import torch
import torch.nn as nn
import torch.optim as optim
from torch.utils.data import DataLoader, TensorDataset
from collections import Counter
from typing import Optional
import scanpy as sc
import anndata as ad
import ... |
cd5d1f120ba848ecf6975e13b0d0b04ddf3b81b549c5c5baa4f3ed09dff0465a | Python | 9,262 | 195 | """
Skeletons
=========
<!-- difficulty: intermediate -->
Fine-tune skeleton figures: radii, tapering, halos and depth sorting.
[`Skeletons`][navis.Skeleton] are lines, and lines are what `matplotlib` is best at - so
[`plot2d`][navis.plot2d] gives you considerably more control here than any of the 3D backends. If
you... |
a475b08266ff8ac76d7da4d44faf6b74aebbe2d7e75e372aeee685869810977c | Python | 9,272 | 231 | #!/usr/bin/env python
#
# ############################################################################
# Copyright (c) 2022-2026 University of Helsinki
# Copyright (c) 2019-2022 Saint Petersburg State University
# # All Rights Reserved
# See file LICENSE for details.
####################################################... |
3baee372779ab756adf9262b2b36cfa0d34d0f38dea066437fe07f59ef9cf41c | Python | 9,275 | 218 | """
If you use this code, please cite the first SynthSeg paper:
https://github.com/BBillot/lab2im/blob/master/bibtex.bib
Copyright 2020 Benjamin Billot
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in
compliance with the License. You may obtain a copy of the License ... |
a91834e6a93964e36334d94c812a7d11eca4dda0c672bf9eb39096018750721d | Python | 9,283 | 259 | # Copyright (c) Facebook, Inc. and its affiliates.
# pyre-unsafe
import logging
import os
from typing import Any, Dict, Iterable, List, Optional
from fvcore.common.timer import Timer
from detectron2.data import DatasetCatalog, MetadataCatalog
from detectron2.data.datasets.lvis import get_lvis_instances_meta
from dete... |
2c1fb6c6597843cf503aace527c846e0f30d9f134e23262d76ee9c97c6e30950 | Python | 9,308 | 239 | from collections.abc import Iterable, Sequence, Sized
import copy
from enum import auto
import logging
from astartes import train_test_split, train_val_test_split
from astartes.molecules import train_test_split_molecules, train_val_test_split_molecules
import numpy as np
from rdkit import Chem
from chemprop.data.data... |
f71ce0ec78824b13c238710d11a60a49065c486bd982dc5900bb13ccee96d218 | Python | 9,308 | 336 | """Agent.py related tests."""
from typing import ClassVar
import numpy as np
import pandas as pd
import pytest
from mesa.agent import Agent
from mesa.model import Model
class AgentTest(Agent):
"""Agent class for testing."""
def get_unique_identifier(self):
"""Return unique identifier for this agen... |
98171b5331d958ef9843d9c0d68ccc082bfcaa193f66216fb07be27a420354ed | Python | 9,316 | 238 | # This script is part of navis (http://www.github.com/navis-org/navis).
# Copyright (C) 2017 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... |
3f7cf66782e95c60a046ea43afb99e3e7a20a4a9909504a07b8003415fa4c15e | Python | 9,326 | 300 | """
Cortical Neurons
================
<!-- difficulty: advanced -->
Recreate a published figure of cortical GABAergic neurons arranged by soma depth.
In this exercise we will visualize morphological data from ["Integrated Morphoelectric and Transcriptomic Classification of Cortical GABAergic Cells"](https://www.cell... |
da1b3da72695cc0984f1899ef450656d60af13b48624e7a5466475e0b8db0817 | Python | 9,332 | 215 | from typing import Union, Tuple, List
import numpy as np
import torch
from batchgeneratorsv2.helpers.scalar_type import RandomScalar
from batchgeneratorsv2.transforms.base.basic_transform import BasicTransform
from batchgeneratorsv2.transforms.intensity.brightness import MultiplicativeBrightnessTransform
from batchgen... |
fc036704a8f78ec4ca7223316ef7c9d6431088791cd9116062d4678afe30a145 | Python | 9,333 | 277 | # -*- coding: utf-8 -*-
import math
from typing import Optional, Literal
import matplotlib.pyplot as plt
import torch
import torch.nn as nn
import torch.nn.functional as F
# ---------- Preprocess: EEG -> (B, 128, H, W) spectrogram tensor ----------
class Spectrogram128(nn.Module):
"""
Converts EEG (B, 128, T... |
30f6cd0da5df0e2e2badde9182baada42e53c9a27a396a569c4c1ecaa726d3e3 | Python | 9,343 | 262 | #!/usr/bin/env python
# Copyright 2017-2021 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... |
60ed29fd061159a148a273d874422969aa57b1823dd9d602a0a621db437bcabe | Python | 9,351 | 272 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Scaling Parameter and Vocabulary Computation Script
This script computes scaling parameters and vocabularies needed for data transformation:
1. Min/Max values for numeric features (num_claims, backward_citation_count, etc.)
2. Global Min/Max for text embeddings (text_... |
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