sha256 stringlengths 64 64 | language stringclasses 27
values | size int32 1 491k | lines int32 1 21.8k | content stringlengths 1 200k |
|---|---|---|---|---|
2cf69985c4f6409ddad0112c352639b99a962342a000e3f4aab0668419c39ddd | Python | 7,764 | 241 | import numpy as np
import pandas as pd
import pytest
from joblib.externals.loky import get_reusable_executor
from skbase.utils.dependencies import _check_soft_dependencies
from pgmpy import config
from pgmpy.factors import FactorDict
from pgmpy.factors.discrete import TabularCPD
from pgmpy.models import DiscreteBayesi... |
a76fef88c2948f05513c489b75dd508f247af27c4569b6f1fa4cc2e6da13a4ae | Python | 7,767 | 223 | #!/usr/bin/env python
"""Did the store get built with the guarded dictionary, and what came out?
**When this was written, nothing in the store recorded which dictionary
produced it** — it now records a `token_labels.IndexStamp` — so a run pointed
at a stale one trained on precisely the mislabelled targets the guard ex... |
aaa5ccf1be1c98b824bb2ba80c9c537f43425070a755ef3d068bb2b8f51b63ec | Python | 7,769 | 173 | """tests for vak.config.prep module"""
import copy
import pytest
import vak.config.prep
class TestPrepConfig:
@pytest.mark.parametrize(
'config_dict',
[
{
'annot_format': 'notmat',
'audio_format': 'cbin',
'data_dir': './tests/data_for_t... |
c490a15eb3e45e3f2fb6a17acaac50727ce3245b12af221dd10ab0b05c1c0110 | Python | 7,771 | 224 | """`LayerBoundaryStore` reading back what `precompute-embeddings` wrote.
The windowed codec's round trip and header layout are pinned in
`test_embeddings_store.py`. This file mirrors
`test_embeddings_store_reader.py` for this store — refusing a store
stamped at another `frozen_layers` or not stamped at all, and turnin... |
1b483294eba23721e239119d3af879081c6940a2933282f708594faf984bcbcd | Python | 7,780 | 238 | """
Metadata Management for Medical Image Datasets
This module provides utilities for creating, loading, and managing metadata
for medical image datasets. Metadata tracks study information, modalities,
sequences, and processing status.
Example Usage:
>>> from neurovfm.data.metadata import DatasetMetadata
>>> ... |
4f4dc77196551d0c94ffa57a5acdfe876ee2e5a55b8469227fe470c0d0de946e | Python | 7,782 | 214 | #!/usr/bin/env python
# ENCODE DCC bowtie2 wrapper
# Author: Jin Lee (leepc12@gmail.com), Daniel Kim
import sys
import os
import re
import argparse
import multiprocessing
from encode_common_genomic import *
def parse_arguments():
parser = argparse.ArgumentParser(prog='ENCODE DCC bowtie2 aligner.',
... |
8e8c215b9f352a78b685331589a4fdc5e1239d1eb48366ccef54ac09c9477b50 | Python | 7,785 | 224 | import sys
import tempfile
import numpy as np
import pytest
from scvi.data import synthetic_iid
from scvi.utils import attrdict
# the whole file should only run on macOS
pytestmark = pytest.mark.skipif(
sys.platform != "darwin", reason="This test file runs only on macOS"
)
@pytest.mark.parametrize("n_latent", ... |
19c3579273954191288a72c9ce821276654300f22d04162395e91bbcf043d9ea | Python | 7,787 | 146 | # -*- coding: utf-8 -*-
# Form implementation generated from reading ui file 'save_image_dialog.ui'
#
# Created by: PyQt5 UI code generator 5.10.1
#
# WARNING! All changes made in this file will be lost!
from PyQt5 import QtCore, QtGui, QtWidgets
class Ui_SaveImageDialog(object):
def setupUi(self, SaveImageDialo... |
3570da30f49773d2603681f08c33aa37acb4f87d2327d9a6136a2c4b66cc3873 | Python | 7,790 | 227 | """SIESTA SZP runner for periodic halide perovskites.
Targets ABX3 cubic Pm-3m primitives (5 atoms) and 2x2x2 supercells (40 atoms)
with elements in {Cs, K, Pb, Sn, Ge, I, Br, Cl, F}.
Pseudopotentials: Pseudo-Dojo NC PBE stringent PSML, located in
data/perovskites/pseudos/.
Uses Monkhorst-Pack k-mesh sized by cell s... |
1ec3c7ab2105c3269a82aa587527c64a82c3ebe98f13a8bad227c18c57e8e808 | Python | 7,794 | 186 | import os
import logging
import loompy
import numpy as np
from scipy.cluster.hierarchy import cut_tree
import matplotlib.pyplot as plt
from ..plotting.colors import colorize
from ..pipeline import Tempname
import networkx as nx
import community
from sknetwork.hierarchy import Paris
def calc_cpu(n_cells):
n = np.a... |
81d0d745ddcdcd9a742abb9e20b9516941b25b100876d35c2b2e49f4a0620024 | Python | 7,794 | 206 | import matplotlib.pyplot as plt
def plot_surf_stat_map(coords, faces, stat_map=None,
elev=0, azim=0,
cmap='jet',
threshold=None, bg_map=None,
mask=None,
bg_on_stat=False,
alpha='auto',
vmax=None, symmetric_cbar="auto", returnAx=False,
figsize=(14,11), lab... |
2bb5ff678ad2300817853a65f7b68e4017059e71b407f691421f65c89fa3a355 | Python | 7,795 | 173 | import torch
import numpy as np
import torch.nn.functional as F
import torch.nn as nn
from utils import *
from self_calibration import *
from torch.fft import fftshift, ifftshift, ifft2, fft2
from fft_conv_pytorch import fft_conv, FFTConv2d
dtype = torch.float32
class forward_model_lsm(nn.Module):
def __init__(se... |
a44248bd43ebda04d4990977a387b9149b610842517dcfb04d866fd7b08fe3e3 | Python | 7,796 | 267 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
"""Finds distinct regions"""
from time import time
from typing import Optional
import numpy as np
from skimage.segmentation import flood
from tqdm import tqdm
from utils.decorators import timer_s
from utils.models import Region
def _loc_to_flat(loc: tuple[int, int], N... |
ad3eab3a842941bd5f376899f560a83d91a4c88f518a83578771f577fc9963c0 | Python | 7,798 | 173 | #!/usr/bin/env python3
"""A little tool to shift pisa values in hdf5 files."""
import argparse
import numpy as np
import numpy.typing as npt
import h5py
from bpreveal.internal.constants import IMPORTANCE_T, IMPORTANCE_AR_T, PRED_AR_T, PRED_T
def shiftPisa(dats: IMPORTANCE_AR_T, offset: int) -> IMPORTANCE_AR_T:
""... |
f4869cb217437695d244818e5efd56158036d8c586c2c111f85595b54c47129e | Python | 7,800 | 173 | from copy import deepcopy
import numpy as np
from scvi import REGISTRY_KEYS
from . import _constants
from .fields import (
CategoricalJointObsField,
CategoricalObsField,
LabelsWithUnlabeledObsField,
LayerField,
NumericalJointObsField,
ProteinObsmField,
)
LEGACY_REGISTRY_KEY_MAP = {
"X": ... |
52efe4f80c9e7a90e632abaaf1c0b87dfcf4c24fdd867ec6ee7806f3b103656c | Python | 7,807 | 247 | """
Tests for Dask configuration functionality.
"""
import pytest
import tempfile
import os
from pathlib import Path
import yaml
import time
# Add src to path for imports
import sys
sys.path.insert(0, str(Path(__file__).parent.parent / "src"))
from voluseg.dask_config import DaskConfig
from voluseg.dask_config impor... |
ebeb0af61a7d5a8f5af12c8feae27916f95e7f6620a0a1722d3b60c525f77945 | Python | 7,808 | 210 | """Shared Local Preview/STL mesh pipeline with Lite-compatible slice interpolation."""
from __future__ import annotations
from dataclasses import dataclass
from pathlib import Path
from typing import Callable, Iterable, Sequence
import numpy as np
from mask_postprocessing import signed_distance_for_label
SUPPORTE... |
27795d027b72b35b853fe252baaea4f1b444c85f9f9ad46ad635f12c0d57614f | Python | 7,809 | 205 | from __future__ import annotations
from typing import TYPE_CHECKING
from typing import Any
from typing import ClassVar
from cleo.helpers import option
from poetry.console.commands.command import Command
if TYPE_CHECKING:
from pathlib import Path
from cleo.io.inputs.option import Option
class CheckComman... |
32b9736ff01794cdb5526725808134294c4a54ca4f4a89aecaac7c79928040c0 | Python | 7,809 | 222 | import hashlib
import json
import os
from pathlib import Path
import numpy as np
import pytest
import torch
from huggingface_hub import hf_hub_download
from transformers import (
AutoModel,
AutoModelForMaskedLM,
AutoModelForSequenceClassification,
AutoTokenizer,
)
from gpn import register_auto_classes... |
b2046d2b5b6f1431a7af2594e427f8e89bc72d1fc2974b907d22186aa812f4be | Python | 7,811 | 212 | import numpy as np
import os
import glob
import xarray as xr
import pandas as pd
import warnings
from .waveform_metrics import calculate_waveform_metrics
from ...common.epoch import Epoch
from ...common.utils import printProgressBar
def extract_waveforms(raw_data,
spike_times,
... |
64ae24c63c09a909482754bf2d2a4d9029901da7d14cb462f0225352e3446bd1 | Python | 7,821 | 207 | import os
import sys
from argparse import ArgumentParser
from getpass import getpass
from typing import List, Union
from requests.exceptions import HTTPError
from transformers.commands import BaseTransformersCLICommand
from transformers.hf_api import HfApi, HfFolder
UPLOAD_MAX_FILES = 15
class UserCommands(BaseTran... |
20640751070ef8680fa211704d822c9e321eb05edad230d425e69a77be887dbc | Python | 7,823 | 199 | # Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import hashlib
import logging
import math
import numpy as np
from fairseq.data import SampledMultiDataset
from .sampled_multi_dataset impor... |
4ee6b7277d8c86344c058dd78577428e7a6f9a4499cf823da796ac7c5066b5c8 | Python | 7,823 | 209 | import os
import sys
from argparse import ArgumentParser
from getpass import getpass
from typing import List, Union
from requests.exceptions import HTTPError
from transformers.commands import BaseTransformersCLICommand
from transformers.hf_api import HfApi, HfFolder
UPLOAD_MAX_FILES = 15
class UserCommands(BaseTr... |
adf286b5c6f9a907454d146508a1c22a5e33043a7dbc8c84c387ce54653a353d | Python | 7,824 | 194 | #!/usr/bin/env python3
"""Scans for motifs given importance scores.
This program scans over the contribution scores you calculated with
:py:mod:`interpretFlat<bpreveal.interpretFlat>` and looks for matches to motifs
called by modiscolite. It can be run with a quantile JSON from
:py:mod:`motifSeqletCutoffs<bpreveal.mot... |
409e56b7b363929fded0f7788f42f0018f33e1b32af319931bac890f73247a2e | Python | 7,828 | 191 | """Command-line script to print a GO term's lower-level hierarchy.
Usage:
goatools wr_hier [GO ...] [options]
Options:
-h --help show this help message and exit
-i <gofile.txt> Read a file name containing a list of GO IDs
-o <outfile> Output file in ASCII text format
-f Writes resul... |
501d114fa6afd0aab1a538462c05dce4fb2c244972a651ffa14742d0a4c403b4 | Python | 7,828 | 198 | class CounterbalancedStratifiedSplitRandom(object):
def __init__(self, X, y, c, n_splits=5, c_type='categorical',
metric='corr', use_pval=False, threshold=0.05, verbose=False):
self.X = X
self.y = y
self.c = c
self.z = None
self.n_splits = n_splits
... |
9de0217583d0e906ca58722e3f7f8fbae0e2c87e88478626850ac50684622e1c | Python | 7,829 | 211 | """Deliberately refresh the committed outputs of the three demos."""
from __future__ import annotations
import argparse
import ast
import json
import os
import re
from pathlib import Path
import nbformat
from nbclient import NotebookClient
from docs.prepare_notebooks import MODEL_DEMOS, NOTEBOOKS, REPOSITORY_ROOT, ... |
1d8ae6480d0bd9dd1b22ec79d631cde0a95f5fdefefbd0cd8ca93ad156f186a3 | Python | 7,832 | 214 | """
Shared drawing helpers for BEELINE heatmap plotters.
Provides the cell-drawing primitive (_flat_square), the section renderer
(_draw_section), and the axis-setup utility (_setup_heatmap_axes) used by
both PlotSummaryHeatmap and PlotEPRHeatmap.
"""
import math
from typing import List
import matplotlib.patches as p... |
cfa0fcb14701299ab2cefbac3f49b31fe190ffcdd852ff8c92553b01ccbc6d4d | Python | 7,832 | 206 | # Load required packages
import os
import sys
import pandas as pd
import json
from absl import flags
from absl import app
from glob import glob
import subprocess
from anarci import anarci
from scripts import seq_utils,pdb_utils,tcr_utils,parse_tcr_seq
# input
flags.DEFINE_string('output_dir', "experiments/", 'Path t... |
6e62b1bc176c30c26c630d5753c11ed86a7e40e3a6807e909782f448942d07f1 | Python | 7,835 | 200 | import matplotlib.pyplot as plt
from matplotlib.gridspec import GridSpec
from matplotlib.widgets import Slider
from scipy.stats import norm
import matplotlib.mlab as mlab
import numpy as np
__author__ = 'Robbert Harms'
__date__ = "2016-09-02"
__maintainer__ = "Robbert Harms"
__email__ = "robbert@xkls.nl"
class Sampl... |
1acae956fd367baed7664b1b86874568163c3abf7b61a131c6ec83a3f1aace6b | Python | 7,836 | 173 | # This function written by Kimberly Siletti and is based on doubletFinder.R as forwarded by the Allen Institute:
#
# "Doublet detection in single-cell RNA sequencing data
#
# This function generates artificial nearest neighbors from existing single-cell RNA
# sequencing data. First, real and artificial data are merged.... |
606c35ad8e3e5970322ceb49f91f3873bd67141c03f6543525935da50ab7a594 | Python | 7,837 | 187 | #!/usr/bin/env python3
"""Encode A1, S1, and CellExplorer cells into the 16-D HIPPIE latent space for
cross-technology latent-space flow visualisation.
Label normalisation maps each dataset's native labels to canonical cell-type names:
A1 (a1data_remove_undef):
PV → Parvalbumin, SOM → Somatostatin, EXC → Ex... |
180b7ddb7b565027fe2960709a6654808e385cf58e3c943b8704f1e88a40fcb7 | Python | 7,841 | 185 | from DataSynthesizer.DataDescriber import DataDescriber
from DataSynthesizer.DataGenerator import DataGenerator
from DataSynthesizer.ModelInspector import ModelInspector
from DataSynthesizer.lib.utils import read_json_file, display_bayesian_network
import pandas as pd
import matplotlib.pyplot as plt
from tqdm import ... |
442f145d4b1871f2a01e105a0092bf8f7efb01c086d7030be177f265d0c96fc7 | Python | 7,841 | 252 | # train_c1.py
# Standalone LKIS-style training for C1:
# - loads all ses*_task-*_pairs.npz from DATA_DIR
# - trains one model per (session, task) NPZ
# - saves outputs per system under OUT_ROOT/<npz_base>/
#
# Requires: numpy, torch
# Your conda env already imports torch OK.
import os, glob, json, time
... |
a4ca12787a5a59554162a5b0d4ad8381266dc9d5f203177f800e344fcaba73b9 | Python | 7,841 | 172 | import os
import time
import torch
import argparse
import numpy as np
from src.ernie_rna.tasks.ernie_rna import *
from src.ernie_rna.models.ernie_rna import *
from src.ernie_rna.criterions.ernie_rna import *
from src.utils import ErnieRNAOnestage, read_text_file, load_pretrained_ernierna, prepare_input_for_ernierna
... |
0b14e9a9acebeae402e42a7cefe68a64c301684d1e9bbb8f290c6574106a6117 | Python | 7,846 | 155 | """Run notebook orchestration with real ZIP/geometry/backend I/O and synthetic masks.
Colab file UI, installation/network calls, and TotalSegmentator inference are mocked.
This checks cell ordering and file preservation, not real GPU/model execution.
"""
import io
import json
from pathlib import Path
import subprocess... |
ad77aa56913997d59b4d73d515b577822810939267fa5a805e947cfacb02d7cb | Python | 7,851 | 152 | # -*- coding: utf-8 -*-
# Form implementation generated from reading ui file 'UI/SensorsWindow.ui'
#
# Created by: PyQt5 UI code generator 5.15.9
#
# WARNING: Any manual changes made to this file will be lost when pyuic5 is
# run again. Do not edit this file unless you know what you are doing.
from PyQt5 import QtC... |
626fe0a542908af1ad5d49ad09052d5bcad68a2d6f48dbebf2d3fcffd9ea15d8 | Python | 7,855 | 224 | import os
import zarr
import numpy as np
import tskit
import yaml
import ray
import argparse
parser = argparse.ArgumentParser("Plot posteriors after rescaling parameters by fitting theta analytically")
parser.add_argument("--configfile", type=str, help="Path to config file", default="npe-config/DroMel_CO_FR_rnn.yaml")... |
f9b7f13f7c161799d9e5ce2896ed56f15d522521b21feb8e98d8f91009f6be96 | Python | 7,855 | 182 | import os
import tempfile
import torch
class ModelCheckpoint(object):
""" ModelCheckpoint handler can be used to periodically save objects to disk.
This handler expects two arguments:
- an :class:`~ignite.engine.Engine` object
- a `dict` mapping names (`str`) to objects that should be saved... |
b3cf9c2c55b5d781c22a1d8fa83574f3b33d5865450ae3e74b0a59c6a04250c0 | Python | 7,863 | 211 | # Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import copy
import logging
from typing import Dict, List
import numpy as np
import torch
import torch.nn as nn
import torch.nn.functional as ... |
f512b38dc7e7300ae83022808aab5e9673eda36ddcb9d09fd8709d5b105ca0f0 | Python | 7,866 | 246 | import argparse
import h5py
import nibabel.freesurfer.mghformat as mgh
import numpy as np
from spacestream.core.constants import SUBJECTS
from spacestream.core.paths import BETA_PATH, DATA_PATH, RESULTS_PATH
from spacestream.utils.get_utils import get_indices
from spacestream.utils.mapping_utils import traditional_ma... |
de2c6e03ae2259c5f71aba726da58e70d87cec365d6f562576a8dc1b0801b782 | Python | 7,871 | 229 | import argparse
import os
import random
import time
from copy import deepcopy
import h5py
import numpy as np
import torch
import torch.nn as nn
import torch.optim as optim
from torchdiffeq import odeint
from torch.utils.data import Dataset, DataLoader
learning_rate = 0.001
num_epochs = 500
device = torch.device("cpu... |
f2ebdf6452a47a846ca393900dea3e2fd4f77c399c561b5952af16a01c934f51 | Python | 7,871 | 296 | import os
import torch
import torch.nn as nn
import numpy as np
from tqdm import tqdm
from torch_geometric.loader import DataLoader
from sklearn.metrics import mean_absolute_error, mean_squared_error
from sklearn.model_selection import KFold
from scipy.stats import pearsonr
from model import GeometryAwareGNN
class P... |
f92a98c1e8e2fe19f538dd14b758f0708ad3f27bd08a89f2f0330364c1db502a | Python | 7,874 | 209 | # Copyright (C) 2025 ETH Zurich, Moritz Thürlemann, and other AMP contributors
import argparse
import yaml
from Simulator_calibration import (ForcefieldBuilder, SimulationBuilder, AmpConfigurator, SystemBuilder, PDBReader)
import openmm as mm
from openmm.unit import *
from openmm.app import ForceField
from openff.tool... |
86040d3692a833881e191d51e00194bd7a23b79446ae1b9204c4448154b2f203 | Python | 7,878 | 184 | import numpy as np
import pandas as pd
import pytest
from pgmpy.base import PDAG
from pgmpy.causal_discovery import ExpertKnowledge
class TestExpertKnowledge:
def test_repr_and_str_empty(self):
ek = ExpertKnowledge()
assert repr(ek) == (
"Expert Knowledge: 0 required edges, 0 forbidde... |
cfde4633e1f2125f796c6b922a9f0f3c272f651bdf1b1782c2d6c83ea0e530ee | Python | 7,879 | 191 | import os
import sys
import json
import logging
import argparse
import numpy as np
import pandas as pd
from tqdm import tqdm
import torch.nn as nn
from torch.optim import AdamW
from datasets import load_dataset
from pooling import PoolingWithDropout
from torch.utils.data import DataLoader
from dataset import CreateFine... |
6407d32e16bec7e2361f21820b9ed4f4280cbccf67ad94611353e9733bc7f017 | Python | 7,880 | 243 | #!/usr/bin/env python
# Author_and_contribution: Niklas Mueller-Boetticher; created template
# Author_and_contribution: Zaira Seferbekova; wrote the code for SOTIP
import argparse
# TODO adjust description
parser = argparse.ArgumentParser(description="Method ...")
parser.add_argument(
"-c", "--coordinates", hel... |
1b941b6b5e1ab22cb16e7403cc98cb7cdffaa41bcca7352d14dd2e6d37d08805 | Python | 7,885 | 200 | # _*_ coding: UTF-8 _*_
# Version information START --------------------------------------------------
VERSION_INFO = \
"""
Author: ZHANG YUBO
Version-01:
2020-01 Post-processing and visualization of the ERICA results
Version-02:
2020-08 Processing both four-taxon and five-taxon resu... |
6b895e045ee6d6eae426cec656a95ffe344ff7bd1e7ce31a80c26090ae1d31ed | Python | 7,886 | 230 | """PyTorch RNN/LSTM models for full latent trajectory prediction and sequence classification."""
from abc import ABC, abstractmethod
from collections.abc import Callable
import torch
import torch.nn as nn
import torch.optim as optim
from latent_model.loaders.sequence_loader import SequenceLoader
class TemporalMode... |
ce0c423d2a0b629bfcff7e2de3a988507aa176b67777ed0617ea9bc62cb7e8b3 | Python | 7,886 | 210 | """Raw sheet helpers for telemetry workbook exports."""
from __future__ import annotations
import logging
import pandas as pd
logger = logging.getLogger(__name__)
def populate_raw_data_sheet(exporter, writer, sheet_name, cluster_number):
cluster_data = exporter.app.mean_cluster_data.get(cluster_number)
wo... |
06a48308c7189a5ab3f0418b57522e121fd3709c7bf5f133b24c0a19a0a64809 | Python | 7,890 | 201 |
# Copyright (c) 2017-present, Facebook, Inc.
# All rights reserved.
#
# This source code is licensed under the license found in the LICENSE file in
# the root directory of this source tree. An additional grant of patent rights
# can be found in the PATENTS file in the same directory.
import itertools
import numpy as ... |
728089f951ee7f15b1efc856fe8980ae63711927641c2e352202c6857e84e317 | Python | 7,890 | 213 | """
Area Clustering Module.
This module provides functionality for clustering chromatophores based on their area
time series and for visualizing the resulting clusters. The clustering is performed by computing
a correlation matrix between chromatophore time series and then applying a clustering algorithm
(e.g., Affini... |
4a218e22164be7ac3c6fb47295512b850b4b39b2b7bc807be4df617a9f5de1dd | Python | 7,893 | 264 | from fairseq import tasks
import numpy as np
import logging
import random
from fairseq import options
import torch
import os
import soundfile as sf
from fairseq.data.audio.audio_utils import (
get_waveform,
parse_path,
)
logging.basicConfig()
logging.root.setLevel(logging.INFO)
logging.basicConfig(level=loggi... |
f0e487761d0fd1f42a4518e7355f96af2add5c68c5e91d28fda839c5d6407afe | Python | 7,894 | 138 | import shutil
from typing import List, Type, Optional, Tuple, Union
import nnunetv2
from batchgenerators.utilities.file_and_folder_operations import join, maybe_mkdir_p, subfiles, load_json
from nnunetv2.experiment_planning.dataset_fingerprint.fingerprint_extractor import DatasetFingerprintExtractor
from nnunetv2.exp... |
d4ed3844951360ec35ef7c0d5f95c526248d73198a5b816bcebafa9c5ae36347 | Python | 7,895 | 183 | import numpy as np
import scipy.sparse as sp
import sys
def AMI_Stergiou(data, L, to_matlab = False, n_bins = 0):
"""
inputs - data, column oriented time series
- L, maximal lag to which AMI will be calculated
- bins, number of bins to use in the calculation, if empty an
... |
77a2f00374a847b0291d334ea21a3af4983f28a563051ded16fe68575f21d1dc | Python | 7,897 | 147 | # -*- coding: utf-8 -*-
# Form implementation generated from reading ui file 'UI/CorrRandomFrequency2UI.ui'
#
# Created by: PyQt5 UI code generator 5.5.1
#
# WARNING! All changes made in this file will be lost!
from PyQt5 import QtCore, QtGui, QtWidgets
class Ui_Form(object):
def setupUi(self, Form):
For... |
b6b147c7834f9da5c5d0e29c5983b5039dfd4462803adcd47fa5999bb71e3cc4 | Python | 7,902 | 192 | """Engine-agnostic parallel batch wrapper for energy engines.
Maps any `(atoms, **kw) → (E_eV, atoms_opt)` callable over a list of Atoms
in parallel. Originally written for `oce.xtb_runner.xtb_energy`; now also
used for `oce_carbon.runners.dftbplus.dftbplus_energy`.
Both engines (xtb / DFTB+) are CPU-bound subproces... |
f778dfbf89c06c8417d1e33c854a1f963f8e8fa5be430959e2a4465c34e65a34 | Python | 7,902 | 190 | import collections
import numpy as np
import PIL.Image as Image
import PIL.ImageColor as ImageColor
import PIL.ImageDraw as ImageDraw
import PIL.ImageFont as ImageFont
_TITLE_LEFT_MARGIN = 10
_TITLE_TOP_MARGIN = 10
STANDARD_COLORS = [
'AliceBlue', 'Chartreuse', 'Aqua', 'Aquamarine', 'Azure', 'Beige', 'Bisque',
'Bl... |
4d6ff7809b30c61e52c0ff928222b0f2f796bd058e9e18b33022a75a2409a2e5 | Python | 7,907 | 235 | import json
import unittest
from unittest.mock import patch
from pyecharts import options as opts
from pyecharts.charts import Scatter, Grid
from pyecharts.commons.utils import JsCode
from pyecharts.faker import Faker
class TestScatterChart(unittest.TestCase):
@patch("pyecharts.render.engine.write_utf8_html_file... |
65d5fcc70963a8a995d9fe7c362619425c405e122213aa4a67369c49d245a2bd | Python | 7,908 | 270 | from __future__ import annotations
import json
import re
import shutil
import subprocess
import sys
from typing import TYPE_CHECKING
from typing import ClassVar
from typing import cast
import pytest
from cleo.testers.application_tester import ApplicationTester
from poetry.console.application import Application
fro... |
983b3e25d110eb8e9f87825531866720201a5ade07bc3b83f1111c3f986cad5e | Python | 7,912 | 212 | import torch
import torch.nn as nn
import torch.nn.functional as F
from torch.nn.parameter import Parameter
from torch.nn.modules.module import Module
from torch_geometric.nn import GCNConv
class AttentionMechanism(nn.Module):
"""
Implements an attention mechanism to compute attention scores over input embedding... |
1dd464354acab96a99842bc9d062d317d56933492d1a02f076e8dd27a4dec6a6 | Python | 7,913 | 226 | """enzymeNER: PMC sentences whose enzyme mentions are marked but not named.
The unit is the sentence, not the document, and the offsets are **half-open**
— the opposite convention from S800, so the `+ 1` that corpus needs is a
one-character error here. Three of the 2,274 rows address neither reading and
are dropped ra... |
267379003f49c3a19e358fc4022b2800a6ab0c3825dd7c516de552d9235b7e7c | Python | 7,913 | 256 | # Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import torch
import torch.nn as nn
import torch.nn.functional as F
import numpy as np
from functools import partial
from dataclasses import da... |
f750c70c0808d3d1f1d4bff09b56f0dd19ee3cc8084a1b7478b7d93427f04a56 | Python | 7,913 | 223 | """
Diagnostic Head Pipeline for NeuroVFM
Loads trained diagnostic head (pooler + classifier) for multi-label classification.
"""
import torch
import torch.nn as nn
from typing import Dict, List, Optional, Tuple
from pathlib import Path
import logging
from importlib.resources import files
from neurovfm.models import... |
5ea0c20f18c8cf81a1d59db582991985bce0a43e6a1b52e2a20482a614b7fd4a | Python | 7,916 | 175 | # coding=utf-8
# Copyright 2018 The HuggingFace Inc. team.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable... |
731670d88ad23f06354d7e6c662308bcaa79620b5c52d24435bebd1879ff5c11 | Python | 7,918 | 177 | # coding=utf-8
# Copyright 2018 The HuggingFace Inc. team.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable... |
2c3acc76a215a9e15d34405fc44559f2c32e67da28317e0915f68bc76b497600 | Python | 7,919 | 193 | import json
import logging
import pandas as pd
import multiprocessing
import requests
from tqdm import tqdm
from pathlib import Path
from typing import Dict, Optional, List
from src.data.manager import DatasetManager
logging.basicConfig(level=logging.INFO)
log = logging.getLogger(__name__)
class InterProManager(Data... |
8e868260693717a9c728fe94660c9509d8dbadbc27864bab6198c39ea247966f | Python | 7,920 | 214 | import torch
import torch.nn.functional as F
from torch.utils.data import Dataset
import numpy as np
import random
from typing import Dict, Any, Optional
from scipy import ndimage
class NeuralAugmentations:
"""Data augmentation methods for 1D neural electrophysiology signals."""
@staticmethod
def add... |
4760bdb6981a79a5cb4604481137983929a83277107ee1b4abbc4619c3a9e2c3 | Python | 7,921 | 157 | """Upload-first InferRef3D flow without Colab, network or GPU dependencies."""
import contextlib
import io
import json
from pathlib import Path
import sys
import tempfile
import types
import unittest
from unittest.mock import Mock, patch
import zipfile
NOTEBOOK = Path(__file__).resolve().parents[1] / "InferRef3D_v1_0.... |
0fab1653de516e8af9603fc86256221fbda916da118c6fe2169a05fe9a1ab238 | Python | 7,922 | 183 | """Phase 2 smoke — xtb optimisation + OCE on relaxed structures (L ≤ 6).
Workflow:
1. Resample percolation clusters at p_c (small L).
2. Run xtb single-point at the AS-BUILT lattice geometry → E_xtb_sp.
3. Run xtb optimisation → E_xtb_relaxed.
4. Compare ΔE_relax = E_xtb_sp − E_xtb_... |
2a3001b4e6867c60ca3e14824bc1384b8f88eebabbb5dee5caa3d2a6a421b6af | Python | 7,923 | 215 | import json
import os
import shutil
import tempfile
import unittest
from unittest.mock import MagicMock
from simulation_encoder.writer import Writer
from simulation_encoder.dataclass.loss_data import LossData
def _make_mock_dataset(name="ds1"):
dataset = MagicMock()
dataset.name = name
dataset.channels =... |
3b6f50eecfa42ec0c010a0cf2af26ec5b936f157eea940e32b02f3457d29fbe7 | Python | 7,927 | 188 | from pathlib import Path
from typing import Dict, Iterator, List
import pandas as pd
class RunResult:
"""
Predicted networks and ground truth reference for a single run.
ranked_edges maps algorithm name to its ranked edge list DataFrame
(columns: Gene1, Gene2, EdgeWeight). Algorithms whose rankedEdg... |
2a8a9a425c1cbbb6e5a03819b8c71abe71828e6fffa0343366475ccd7b5d766c | Python | 7,929 | 232 | """Supplemental Figure 3 — ISI+ACG dataset profiles.
Two datasets: DANDI_000473 (Neuropixels mouse PFC, n=9213) and
DANDI_000955 (mouse cortex, n=134). Both have waveforms.csv,
isi_dist.csv, acg.csv, labels.csv under results/benchmark/cache_datasets/.
Emits a 2-row panel per dataset:
Row 0: mean waveform, mean IS... |
194af18ff34ac30a4481a02f912eb686c542d59dacd279f62b322d5430e84e64 | Python | 7,933 | 163 | #! /usr/bin/env python
import metax
import sys
__version__ = "1.0x" + metax.__version__
import logging
import re
import os
from metax import Logging
from metax import Exceptions
from metax import Utilities
from metax.gwas import Utilities as GWASUtilities
import SPrediXcan
__author__ = 'heroico, Eric Torstenson'
""... |
d1fb5a09967241939b9be6debcd26c2ba160137daa8efb03ed6798e30c91683c | Python | 7,935 | 205 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Wed Mar 27 12:10:16 2024
@author: tower2
"""
import torch
from tqdm import tqdm
import matplotlib.pyplot as plt
from torch_geometric.utils import dense_to_sparse
from .Semantic_layers import *
from .preprocess import preprocess_adj
# Define loss and optimi... |
1f389b4f6fb26c6e166d327c352f5ad890cb500800d4f27b8e12d698c214b9ec | Python | 7,936 | 171 | import slicer
import ctk
import qt
import numpy as np
import vtk
import StereotacticPlan
class CustomCoordinatesWidget(ctk.ctkCoordinatesWidget):
def __init__(self, name):
super().__init__()
self.name = name
self._updatingCoordinatesFromMarkups = False
self._updatingMarkupsFromCoor... |
9ab170240bc2cf88208e1ecd7b4a15e6226f213fff4b32bd4b807ead095e48fd | Python | 7,941 | 205 | import os
from pathlib import Path
from tqdm import tqdm
import numpy as np
import shutil
import zarr
from numcodecs import Blosc
#set this for multiple processing
Blosc.use_threads = False
#distributed processing of masks
import dask
from dask.distributed import Client
from WSIAnnotation import load_annot
#slicin... |
3e4e9c94209ae5e4641c2d488c4e2b9d58792a4e7daf97a9a287c62b68b7e674 | Python | 7,943 | 258 | # inspired by https://github.com/nathankong/robustness_primary_visual_cortex/blob/master/robust_spectrum/robustness_eval/imagenet_robustness.py
import argparse
import os
import pickle
import eagerpy as ep
import torch
import torch.nn as nn
import torchvision
from foolbox import PyTorchModel, accuracy
from foolbox.atta... |
29cf04a436a3dadbd129a68df4dbde4e809b197c632c5eafb2efbec093ed0d02 | Python | 7,945 | 231 | import unittest
import pickle
from pathlib import Path
from tempfile import TemporaryDirectory
from types import SimpleNamespace
from unittest.mock import MagicMock, patch
import numpy as np
from GMXMMPBSA import output_file
from GMXMMPBSA.utils import EnergyVector
class _Value:
def __array__(self, dtype=None):... |
4e58a0d5900d13e7d415c905eae6281721c4b69816a0dcb465c5b8fef10b6aa8 | Python | 7,945 | 243 | #!/usr/bin/env python
# Author_and_contribution: Niklas Mueller-Boetticher; created template
# Author_and_contribution: Jieran Sun; Implemented method DeepST
import argparse
# description
parser = argparse.ArgumentParser(description="Method DeepST: identifying spatial domains in spatial transcriptomics by deep learn... |
18f89123dda81423a281850dd487a934066a20aaf46b69a39bc6c9a738da670a | Python | 7,947 | 204 | import warnings
warnings.filterwarnings('ignore')
from typing import Callable, Tuple, Union
import math
import torch
from torch import Tensor
import torch.nn as nn
import torch_geometric.nn as gnn
import torch.nn.functional as F
from torch_geometric.nn.conv import MessagePassing
from torch_geometric.nn.dense.linear im... |
48515bc5b63e27c0f71388fe2ea47296494a7e487efc075867567bab9734b293 | Python | 7,949 | 217 | import torch
import torch.nn as nn
import torch.nn.functional as F
from torch.nn.parameter import Parameter
from torch.nn.modules.module import Module
from torch_geometric.nn import GCNConv
class AttentionMechanism(nn.Module):
"""
Implements an attention mechanism to compute attention scores over input embedding... |
a8be65016a41d40ba917d2946b7bfa2a4e4626efb6b532e4a245ae107665f65d | Python | 7,949 | 213 | ## script for plotting boxplots and scatter plots of simple stats such as count of approaches, count of interactions, chasings etc...
import matplotlib.pyplot as plt
import numpy as np
import igraph as ig
import networkx as nx
import pandas as pd
import os
import sys
import pandas as pd
import seaborn as sns
from scip... |
ab810ad89c86cb6355b39f27ed0c9566017b993bcfd19d39b68cff569fe00279 | Python | 7,949 | 178 | #!/usr/bin/env python3
# Florian Bénitière 16/03/2025
# This script generates a, unfiltered annotated .parquet file by integrating variant effect predictor (VEP) annotations,
# including all specified VEP plugins, and linking them to individual identifiers (SampleID).
import os
import sys
import pandas as pd
import ... |
3425b2e57b3a39d2538b5a99af51efcb0db517023caf60d9eddc8b2eff608fb1 | Python | 7,951 | 203 |
# Copyright (C) 2025 ETH Zurich, Moritz Thürlemann, and other AMP contributors
import os
import json
import csv
import pickle
import numpy as np
import matplotlib.pyplot as plt
from amp_bms.source.examples.examples_scripts.run_stable_protein_md import EXAMPLES_DIR, HERE
from pymbar import MBAR, timeseries
from tqdm i... |
2fec2b134e4656c0a8f1151b787735b0b226bd84aa5e3a12250faebd3a00720a | Python | 7,952 | 214 | #!/usr/bin/env python
# Author_and_contribution: Niklas Mueller-Boetticher; created template
# Author_and_contribution: Brian Long; wrote code in file
import argparse
from pathlib import Path
import json
import numpy as np
import pandas as pd
import anndata as ad
from scipy.io import mmwrite
import tempfile
import b... |
38ed495e23aefdff4c2cd334c0f93813e073ad51dbea8c8f56e4fda313964742 | Python | 7,952 | 187 | import torch
import torch.optim as optim
from torch.utils.data import DataLoader
from dataloader.dataset import HTPDataset
from training.train import train_model
from training.test import test_model
from visualize.plot_training import plot_logs
from training import evaluation_metrics
from utils.stats import get_max_mem... |
7a1ae1d9c15a9de0b0cd43df58e6fd9ba783543b55d9aa29ecfbbcf2d8fc59ee | Python | 7,955 | 147 | # -*- coding: utf-8 -*-
# Form implementation generated from reading ui file 'UI/CorrOnsetDisruptUI.ui'
#
# Created by: PyQt5 UI code generator 5.5.1
#
# WARNING! All changes made in this file will be lost!
from PyQt5 import QtCore, QtGui, QtWidgets
class Ui_Form(object):
def setupUi(self, Form):
Form.se... |
aaac06cb41f14d14fca94c4003e2796f7088cb2496cc8e3f3f7f05707d590f92 | Python | 7,957 | 210 | scvi_pretext = """
ScVI is a variational inference model for single-cell RNA-seq data that can learn an underlying
latent space, integrate technical batches and impute dropouts.
The learned low-dimensional latent representation of the data can be used for visualization and
clustering.
scVI takes as input a scRNA-seq g... |
cbe1298b42b21277133cf1479bfc68680c380c0e7bece722c2889e2e105779e4 | Python | 7,958 | 175 | """Cross-language equivalence: python/ must agree with matlab/.
The Python directory is a PORT. Two implementations of one documented method
are two chances to be wrong, and a port that has drifted is the worst case
because both sides look maintained and neither is obviously the reference.
Method: both languages read... |
3eb95e55f68257b07315ff5843aed635da3585513690205a52d86388a29d92a8 | Python | 7,961 | 179 | import torch
import os
from transformers import BertTokenizer, BertConfig, RobertaTokenizer, RobertaConfig
from sample import Categorical
from tqdm import tqdm
import argparse
from models.modeling_bert import BertForMaskedLM
import diffusion_condition as diffusion
import functools
from torch.nn.utils.rnn import pad_seq... |
9bb2bc5a3e412876bab62603387f7e51eda938808b9cfb3b92fd1180a3bc279e | Python | 7,963 | 223 | # Copyright 2021 DeepMind Technologies Limited
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agr... |
fcc107078b992bf6055a19e8ad222c549d37c101dac0e07dceb438f49bb397cc | Python | 7,972 | 145 | #!/usr/bin/env python3
"""RNA-seq harmonization v3 — robust per-dataset gene-ID -> symbol + metadata-based MS/HC.
Loads the 9 RNA-seq series from DEPOSITED supplementary files; assigns condition from
series_matrix metadata where sample codes don't encode it."""
import os, re, gzip, io, tarfile
import pandas as pd, nump... |
270787a347c61e827bb83e67e42237b85f1972fcc32e3481ae25b074a1ab5997 | Python | 7,976 | 158 | # -*- coding: utf-8 -*-
"""
Pipeline: STRING protein-protein interaction analysis for the EIF2S1-PELO panel
Author: Drake H. Harbert (D.H.H.)
Affiliation: Inner Architecture LLC, Canton, OH
ORCID: 0009-0007-7740-3616
Date: 2026-06-30
Description:
Queries the STRING database (v12, Homo sapiens) REST API for the EIF2... |
fb1b6dd98207b1a75d33e01826e06deba05c3d157e42b7fea3d6d5ff265a91bb | Python | 7,976 | 205 | # Copyright (c) Microsoft Corporation.
# Licensed under the MIT License.
from functools import partial
from typing import Dict, List, Type
import pytest
import torch
from mattergen.diffusion.corruption.corruption import Corruption
from mattergen.diffusion.corruption.multi_corruption import MultiCorruption, apply
fro... |
2b832cddda498b45786ba5be48125e9dd1d774865bd0569c6613aed67f086553 | Python | 7,979 | 247 | from lifelines.utils import concordance_index
import numpy as np
from sklearn.model_selection import StratifiedKFold
from sklearn.preprocessing import StandardScaler
from keras.models import Sequential
from keras.layers import Dense
from keras.regularizers import l2
#from keras.optimizers import adam_v2
from keras.opti... |
3beef2352356da5ae1a7b34c7847664eb8062c641bc712ef94c9c5223fe129b8 | Python | 7,983 | 210 | """xtb GFN2 single-points for Δ-learning on perovskites.
Two passes:
(1) atomic references for {Cs, K, Pb, Sn, Ge, I, Br, Cl, F} (vacuum, --uhf as needed)
(2) GFN2 single-point on each of 243 labeled supercells (periodic via --periodic)
Output: data/perovskites/delta_learning/xtb_gfn2_results.json
"""
from __fut... |
8074e4e537f06769a587093a0a7271e1704d81f733e0df2d5ad83f9cbad58f7c | Python | 7,983 | 234 | import argparse
import os
import subprocess
import tempfile
import time
import Bio.PDB
import Bio.PDB.Polypeptide
import Bio.SeqIO
import pdbfixer
import simtk
import simtk.openmm
import simtk.openmm.app
PDBIO = Bio.PDB.PDBIO()
PDB_PARSER = Bio.PDB.PDBParser(PERMISSIVE=0)
class NonHetSelector(Bio.PDB.Select):
"... |
652828d0ccf0d13482ef108b2ced54200d380227b7c6262caa3be0caa9a6f288 | Python | 7,985 | 147 | # -*- coding: utf-8 -*-
# Form implementation generated from reading ui file 'UI/CorrDifficultySwitchCameraTriggerUI.ui'
#
# Created by: PyQt5 UI code generator 5.5.1
#
# WARNING! All changes made in this file will be lost!
from PyQt5 import QtCore, QtGui, QtWidgets
class Ui_Form(object):
def setupUi(self, Form)... |
8da7fcc9aa466a6df788f02bc9f8a194e5291f762def5720354648f22bbd16a7 | Python | 7,985 | 246 | import pandas as pd
import numpy as np
import cv2
from collections import Counter
import json
import matplotlib.pyplot as plt
from matplotlib.colors import ListedColormap
from mpl_toolkits.axes_grid1 import make_axes_locatable
import os
from helper_functions_image import create_heatmap_count, parse_det_file, transform_... |
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