sha256 stringlengths 64 64 | language stringclasses 27
values | size int32 1 491k | lines int32 1 21.8k | content stringlengths 1 200k |
|---|---|---|---|---|
25a85c06de11a1f845e658ade0c32f543d9229d0a64ed68bdf49ea5f2d2cfa36 | Python | 6,940 | 196 | """
Copright © 2023 Howard Hughes Medical Institute, Authored by Carsen Stringer and Atika Syeda.
"""
import os
import numpy as np
import pandas as pd
from scipy.ndimage import gaussian_filter1d, uniform_filter1d
from scipy.stats import zscore
from sklearn.decomposition import PCA
from .utils import filter_outliers, ... |
66e0be1f7bf249b508cce88f394c7af75a97ed5349c489b48bbd112436d676dc | Python | 6,940 | 200 | """Real end-to-end pipeline tests using tiny fixture data.
Trains actual models on the fixture AnnData (50 cells, 100 genes)
and verifies real outputs -- no mocks.
"""
import pickle
import tempfile
from pathlib import Path
import anndata as ad
import numpy as np
import pytest
from sklearn.preprocessing import LabelE... |
0ba5fce5b0939f14682acc816295de77e70e6dcfae6d5393cc80d8e3cbb6cbcb | Python | 6,942 | 206 | from dataclasses import dataclass
import functools
from datasets import load_dataset
from refs import llm_base_refs
from refs.experiments import gsm8k_cot_refs_v2
from truesight import parse_utils
from truesight.experiment.services import (
DatasetRef,
EvaluationRunRef,
FilteredDatasetRef,
FinetunedLLM... |
9f168cf6531f386917c68c9a290fe7dcbfa8979ba78dadb43269b39332852db4 | Python | 6,950 | 202 | import pytest
import numpy as np
from numpy.random import default_rng
from kimmdy.recipe import Recipe, RecipeCollection, Break, Bind
from kimmdy.kmc import (
KMCError,
rf_kmc,
frm,
extrande,
extrande_mod,
KMCAccept,
multi_rfkmc,
)
@pytest.fixture
def recipe_collection():
rps: list[Rec... |
a9614990a82fd2f648d24f529624b8eaa517aaa5ab1da3af1287e9272b4d547f | Python | 6,957 | 168 | # -*- coding: utf-8 -*-
import glob, os
import pandas as pd
import xml.etree.ElementTree as ET
import numpy as np
class post_Cat12:
'''
The post_Cat12 class is used to extract results generate by cat12 toolbox such as brain gm and wm volume within ROIs
Attributes
----------
config : dict
'... |
063bd3e80abc0e97fae76778a188e855363b85ea2f94c2113c9190a6f601b39f | Python | 6,958 | 149 | import logging
from multiqc.base_module import BaseMultiqcModule, ModuleNoSamplesFound
from .bamPEFragmentSizeDistribution import bamPEFragmentSizeDistributionMixin
from .bamPEFragmentSizeTable import bamPEFragmentSizeTableMixin
from .estimateReadFiltering import EstimateReadFilteringMixin
from .plotCorrelation impo... |
a3e64683175bd1d0196c050d0e416fe0244e169a30ed70f9cd2c4a7530b39aa2 | Python | 6,970 | 173 | import pygame
from pygame.locals import *
from OpenGL.GL import *
import numpy as np
import logging
log = logging.getLogger(__name__)
class Presenter():
def __init__(self, logger, monitor, background_color=(0, 0, 0), photodiode=False, rec_fliptimes=False):
global pygame
if not pygame.get_init():... |
6fb3ab6aaac77541160b10ab38c00ba090cc637b1b8923bef1f2182f4f1a0c25 | Python | 6,973 | 186 | from typing import Dict
from multiqc import BaseMultiqcModule
from multiqc.plots import linegraph
from multiqc.utils.util_functions import strtobool
def error_rate_by_read_position(module: BaseMultiqcModule) -> int:
"""
Parser metric files for rgb ErrorRateByReadPosition.
Stores the per-read-per-positio... |
33710e28299a17aabcdd1bc85c3553e8caf6c593bfe8da0a87eae8303909842d | Python | 6,978 | 166 | from PySide6.QtWidgets import QWidget, QHBoxLayout, QVBoxLayout, QScrollArea, QPushButton, QLabel, QSpacerItem,\
QGridLayout, QMenu
from PySide6.QtCore import QSize, Qt, Signal, QPoint
from PySide6.QtGui import QIcon, QPixmap, QAction
import os
import logging
from utils.software_config import SoftwareConfigResource... |
8b1c7a69f3460d9577a7108eb28bb8a4cc0846c89ca9a156ac8229cc9150a662 | Python | 6,983 | 202 | """
Tests the easy start guide
- runs plan_rbfe_network with tyk2 inputs and checks the network created
- mocks the calculations and performs gathers on the mocked outputs
"""
import os
from importlib import resources
from os import path
from pathlib import Path
from unittest import mock
import numpy as np
import py... |
ada51eef759d1986c1a3f5408896338c19066340f7d7293f83e061c81735a597 | Python | 7,008 | 215 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
#
# velocyto documentation build configuration file, created by
# sphinx-quickstart on Mon Oct 2 17:26:06 2017.
#
# This file is execfile()d with the current directory set to its
# containing dir.
#
# Note that not all possible configuration values are present in this
# a... |
27712b4088cc1585bb3cac31c78dcac01b349e09bd9a260ff97386edfe04744d | Python | 7,011 | 208 | import importlib
import json
from typing import List
from matplotlib.colors import LinearSegmentedColormap
class SciPalette:
def __init__(self):
"""
Cateogorical color palette collection of popular-sci journals.
"""
handle = importlib.resources.open_binary("gseapy.data", "palette.... |
17e7c3577324c41a0da427a199c955b782fde905aabb1f7cbc3c4e15ebd4ae35 | Python | 7,012 | 190 | import torch
import torch.nn as nn
import torch.nn.functional as F
from torch.nn.utils import weight_norm
import math
class PositionalEmbedding(nn.Module):
def __init__(self, d_model, max_len=5000):
super(PositionalEmbedding, self).__init__()
# Compute the positional encodings once in log space.
... |
f4aad2d3bf9d6351e45d81bdaf4088d7085852729636961e0527348a7d58b596 | Python | 7,014 | 253 | # Copyright 2017 Google Inc.
#
# 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
#
# https://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing,... |
2e4985f24cbc701f395e760123c63aa42eb390d7ed8ce14f5863e32e20ebdcee | Python | 7,041 | 240 | # ---------------------------------------------------------------
# Copyright (c) 2022, NVIDIA CORPORATION. All rights reserved.
#
# This work is licensed under the NVIDIA Source Code License
# for Denoising Diffusion GAN. To view a copy of this license, see the LICENSE file.
# -----------------------------------------... |
511010ec67d93a6f57366a9c61d4fa08d5dceee6c8a5025451263ab344d9a281 | Python | 7,042 | 187 | # This code is licensed under the 3-clause BSD license.
# Copyright ETH Zurich, Department of Chemistry and Applied Biosciences, Reiher Group.
# See LICENSE.txt for details.
"""
Module containing utility functions that do not fit in any of the other modules.
"""
import getpass
import os
import pathlib
import platform... |
a2f289f4bc5c3864bfb404abb2de6299d6202d2f46c3cc9d625cd32d3aa24ede | Python | 7,043 | 232 | import numpy as np
import pytest
import shapely
from shapely import LinearRing, LineString, Point
from shapely.coords import CoordinateSequence
def test_from_coordinate_sequence():
# From coordinate tuples
line = LineString([(1.0, 2.0), (3.0, 4.0)])
assert len(line.coords) == 2
assert line.coords[:] ... |
d2136dd2b9a4e855e2bc98ef774902e3a01198ab472516208f141347267cf861 | Python | 7,055 | 169 | # -*- coding: utf-8 -*-
"""
.. module:: skimpy
:platform: Unix, Windows
:synopsis: Simple Kinetic Models in Python
.. moduleauthor:: SKiMPy team
[---------]
Copyright 2017 Laboratory of Computational Systems Biotechnology (LCSB),
Ecole Polytechnique Federale de Lausanne (EPFL), Switzerland
Licensed under the ... |
4a6d378930ffea740e2152a11c290e47b2e8e0aaf03430ae17afb61ea146fdbc | Python | 7,056 | 168 | """MultiQC submodule to parse output from Picard ExtractIlluminaBarcodes"""
import logging
from collections import defaultdict
from typing import Dict, List
from multiqc.modules.picard import util
from multiqc.plots import bargraph
from multiqc.plots.bargraph import CatDataDict
# Initialise the logger
log = logging.... |
82746886c7ab606888bd6fd4e0312e37ddf087f4792b38440fe676c71fcc36bc | Python | 7,057 | 165 | # -*- coding: utf-8 -*-
"""
-------------------------------------------------------------------------------
NeuroBED_ML Pipeline
Aggregate and Compare Julearn Model Results
-------------------------------------------------------------------------------
Author : Len... |
6cdfdd962155c68acb213c421334f45263d81684aa93fbc606d3354308906b2b | Python | 7,061 | 183 | import os
from collections import namedtuple
from typing import Any, List, Optional
from pip._vendor import toml
from pip._vendor.packaging.requirements import InvalidRequirement, Requirement
from pip._internal.exceptions import InstallationError
def _is_list_of_str(obj):
# type: (Any) -> bool
return (
... |
24d055b199d00a9e3ee9c5d77bafda280e4f385440402bbe06a3f5c8bf3ed3bd | Python | 7,063 | 166 | # -*- coding: utf-8 -*-
"""
-------------------------------------------------------------------------------
NeuroBED_ML Pipeline
Aggregate and Compare Julearn Model Results
-------------------------------------------------------------------------------
Author : Len... |
71d73093db4611e93ab15f667f0aedae1d3e3514619357dc5b05672593a6b6c8 | Python | 7,064 | 192 | """Functions for running convolutional neural networks"""
import numpy as np
from tensorflow.keras import backend as K
from tensorflow.keras.models import Model
from deepcell.utils.data_utils import trim_padding
def get_cropped_input_shape(images,
num_crops=4,
... |
96cd412e301e38c9aa7c88f21cc31ed795239a48005ee2029f84a33e6988fd14 | Python | 7,072 | 194 | import numpy as np
import pytest
from openff.units import unit
from cinnabar import FEMap
from cinnabar.compare import compare_and_rank_results
def test_compare_and_rank_results(fe_map):
np.random.seed(42)
compare_map = FEMap()
for m in fe_map:
if m.computational:
# add the result wi... |
a6b443c0218546db8ba52b06f5b6bf81acd3dfd15b8306c00da0139b95c7241b | Python | 7,077 | 202 | # -*- coding: utf-8 -*-
"""
.. module:: skimpy
:platform: Unix, Windows
:synopsis: Simple Kinetic Models in Python
.. moduleauthor:: SKiMPy team
[---------]
Copyright 2017 Laboratory of Computational Systems Biotechnology (LCSB),
Ecole Polytechnique Federale de Lausanne (EPFL), Switzerland
Licensed under the ... |
9145a6fdd1b9392e26a86e507b3dbf28c3a83b07fb69a3d58877b7cc79d5db7f | Python | 7,078 | 226 | # This code is part of OpenFE and is licensed under the MIT license.
# For details, see https://github.com/OpenFreeEnergy/openfe
"""
Shared pontibus Settings.
"""
from typing import Annotated, Literal, TypeAlias
from gufe.settings import BaseForceFieldSettings
from gufe.settings.typing import (
BoxQuantity,
... |
e2c1a17a73f35a007c7c3d8d8d9ef883513493cdda447c40ddbcc12e01f002d5 | Python | 7,080 | 191 | from refs import llm_base_refs, llm_41_refs, evaluation_refs
from experiments.em_numbers import data, refs, gsm8k_cot_refs, plot
from truesight import plot_utils, stats_utils
from truesight.db.session import gs
import matplotlib
import matplotlib.pyplot as plt
import pandas as pd
matplotlib.use("WebAgg")
async def r... |
b94cc8f420d918c1df988cfe5a89348ef94aa07f66a6f06b0cb27d04a436796f | Python | 7,086 | 214 | #!/usr/bin/env python3
import argparse
import sys, os
import subprocess
from collections import defaultdict
import logging
import re
import math
sys.path.insert(0, os.path.sep.join([os.path.dirname(os.path.realpath(__file__)), "../PyLib"]))
import ctat_util
logging.basicConfig(stream=sys.stderr, level=logging.INFO... |
659ce95480341ef951b88945b000dfd89111663266df3878c648a58ae3310f1d | Python | 7,091 | 190 | import logging
import os
import re
from typing import Dict, List, Optional, Union
from multiqc import config
from multiqc.base_module import BaseMultiqcModule
from multiqc.types import LoadedFileDict
# Initialise the logger
log = logging.getLogger(__name__)
def read_histogram(module, program_key, headers, formats, ... |
378d3caeeadf7e0c555700e4d8018cdec93458c3045b9f2fd3fd64a3029888de | Python | 7,092 | 166 | """GPU configuration utilities for TensorFlow."""
# Temporarily redirect stderr during TensorFlow import
import contextlib
import os
import sys
from typing import Any
@contextlib.contextmanager
def suppress_stderr():
with open(os.devnull, "w") as devnull:
old_stderr = sys.stderr
sys.stderr = devn... |
abbbe967fdc584769456384e67116b3c2904e8d2a62ce6f3c39f9d16c75bbb87 | Python | 7,093 | 176 | import logging
import re
from collections import defaultdict
from typing import Dict
from multiqc.base_module import BaseMultiqcModule
from multiqc.plots import linegraph
# Initialise the logger
log = logging.getLogger(__name__)
class DragenCoveragePerContig(BaseMultiqcModule):
def add_coverage_per_contig(self)... |
3b9cc0d23d92e946fa12c2e145f6083ae387e8a98929c56cf10daed2f8a3b045 | Python | 7,096 | 194 | '''
Simon Chemnitz-Thomsen's code to calculate the metric Co-occurence entropy
Code is based on the article:
Quantitative framework for prospective motion correction evaluation
Nicolas Pannetier, Theano Stavrinos, Peter Ng, Michael Herbst,
Maxim Zaitsev, Karl Young, Gerald Matson, and Norbert Schuff'''
import numpy ... |
79370dba33fa1d77549c31884511a2b91407f4585fa2827a76e0d33aadb02a34 | Python | 7,096 | 207 | # This code is part of OpenFE and is licensed under the MIT license.
# For details, see https://github.com/OpenFreeEnergy/openfe
"""
Settings for adding restraints.
TODO
----
* Rename from host/guest to molA/molB?
* Add all the restraint settings entries.
"""
from typing import Annotated, Literal, Optional, TypeAlias
... |
0dc463336974ad0308ca162b37aafeb6756463a6530f11c994cf3fbac0241820 | Python | 7,097 | 216 | # -*- coding: utf-8 -*-
"""
This module contains provisional support for SOCKS proxies from within
urllib3. This module supports SOCKS4, SOCKS4A (an extension of SOCKS4), and
SOCKS5. To enable its functionality, either install PySocks or install this
module with the ``socks`` extra.
The SOCKS implementation supports t... |
a27d28bc49e73ceaf388611af5d912dce6ff371e9bc2bd82c92e225f439d7582 | Python | 7,099 | 150 | #!/usr/bin/env python3
"""
Compare coverage from info_raw files across all MM samples.
Analyzes all mouse samples to recommend best one for test data.
"""
import pandas as pd
from pathlib import Path
# All mouse samples from the provided list
MM_SAMPLES = {
'PDAC10265wholeCellsp1': '/g/korbel/STOCKS_WF/mosaicatc... |
a401ba47a2c5e8e876394c6696345a5fe462c97a3cbf38edea73ccc88696fc5d | Python | 7,105 | 195 | # This code is part of OpenFE and is licensed under the MIT license.
# For details, see https://github.com/OpenFreeEnergy/openfe
import itertools
import json
import gufe
import numpy as np
import openfe
import pytest
from openff.units import unit as offunit
from pontibus.protocols.solvation import ASFEProtocolResult
... |
97583f4d9218fe60620eef1ef5d81669573b01c97bdf3ac5ee6bda7638ccc5cb | Python | 7,114 | 197 | """List every subject that contributed imaging to the MRI2PET analysis.
Walks the analysis pickles in ``./src/data`` (the same files the training
and evaluation scripts read from), parses out subject IDs from the
standard filename conventions used by the pipeline, and writes a CSV
record of which subjects appear in wh... |
845b421da596a670a3584611c2e51811a9f05559e1706e82fda382078e9e61ee | Python | 7,115 | 187 | """
script for getting group average weights
@ Ladan Shahshahani Jan 30 2023 12:57
"""
import os
import numpy as np
import deepdish as dd
import pathlib as Path
import pandas as pd
import re
import sys
from collections import defaultdict
# sys.path.append('../cortico-cereb_connectivity')
# sys.path.append('..')
import ... |
65012be93571b36689a36e1c2396f6ee82daf08baaf1d125cd7f33b0281ab88b | Python | 7,120 | 184 | import logging
import re
from typing import Dict, List, Optional
from multiqc import config
from multiqc.base_module import BaseMultiqcModule, ModuleNoSamplesFound
from multiqc.plots import bargraph
from multiqc.types import ColumnKey
log = logging.getLogger(__name__)
def featurecounts_chart(data_keys, data_by_samp... |
edf16f4bb2a7f3df3006383be85358e5e39f2cb65b955b11ab10b0d3af0c0b70 | Python | 7,126 | 202 | import numpy as np
from sklearn.metrics import mean_squared_error, mean_absolute_error, r2_score
import pandas as pd
import os
import torch
import joblib
from pyswarm import pso
def print_cnn_params(model):
total_params = 0
print("===== CNN 模型参数与维度 =====")
for name, param in model.named_parameters():
... |
6d8e4b087799cff3febe8be9c33872ef7c8dd67d5faa79b1a56f6cef34aec361 | Python | 7,129 | 172 | """
# File : BART.py
# Time : 2025/10/23 13:03
# Author : Hongmiao Wang
# version : python 3.10
# Description:
"""
"""
To use this model, please install massspecgym package.
BARTModel_GYM_denovo： de novo molecule generation
BARTModel_GYM_Retrieval： retrieval molecule in candidate list
"""
from M... |
7742a0689ba30359272d113dd5532de0485d8bdff716c96f37b36a67f35bf050 | Python | 7,129 | 221 | # Copyright 2022 Google LLC.
#
# 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
#
# https://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing,... |
7ebfcf2dfa1958ae823a3c5c0d09a224f9fd2749b0e7803d6c266d50af3b43c6 | Python | 7,130 | 210 | class fg:
BLACK = "\u001b[30m"
RED = "\u001b[31m"
GREEN = "\u001b[32m"
YELLOW = "\u001b[33m"
BLUE = "\u001b[34m"
MAGENTA = "\u001b[35m"
CYAN = "\u001b[36m"
WHITE = "\u001b[37m"
ENDC = "\033[0m"
BOLD = "\033[1m"
UNDERLINE = "\033[4m"
with open("VERSION", "r") as f:
__ver... |
224cf2b66616404c18f6742efb11f0df854651d524f94ebd226d9fe2c725cbf9 | Python | 7,133 | 214 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
import numpy as np
def Siemens_produce_interleaved_slices(n_slices):
'''
Slices that are excited at each shot in the interleaved mode
for the Siemens produce sequences.
Note that, Siemens varies the starting slice based on
the number of slices (... |
6946ee540c184916c9c88c3ada842c69f6200607eeecba1e37f2197e2dad545f | Python | 7,134 | 163 | """
# File : RerankModel.py
# Time : 2025/10/23 13:36
# Author : Hongmiao Wang
# version : python 3.10
# Description:
"""
import os
import numpy as np
from Rerank.features import Feature_calculater
import lightgbm as lgb
from tqdm import tqdm
remain_features = [2, 3, 4, 5, 6, 7, 9, 10, 11, 12, 13,... |
6e07a4fb5c9bc7764d222c54eaa9bec68aab9e59865f1b1fe6e9e609621c799e | Python | 7,134 | 211 | #!/usr/bin/env python3
import argparse
import csv
import sys
from collections import defaultdict
from rdkit import Chem
from rdkit.Chem.Scaffolds import MurckoScaffold
from rdkit.Chem.Scaffolds import rdScaffoldNetwork
from read_input import read_input
def print_counts(scaffold_col, counts):
print(f"{scaffold_c... |
973c7572165d9b7f26cf3b528eb26c4dbcf5e55156bb777bd127a7fd5fc45b55 | Python | 7,149 | 183 | #!/usr/bin/env -S uv run --script
# /// script
# requires-python = ">=3.10"
# dependencies = ["PyGithub==2.10.0", "requests"]
# ///
"""
Post MultiQC preview report comments on PRs, from builds made by module-report-build.yml.
Run by .github/workflows/module-report.yml. Never runs PR code: it only reads build
results a... |
792ecdad09959986ffd6b50f494c941f77f05828cf1f22a5a0e932db74ba622b | Python | 7,154 | 187 | #!/usr/bin/env python3
"""
Experiment 02 — Degradation Sweep
====================================
Runs the full sweep: datasets × conditions × methods × repeats.
Runtime: 24-72h (full), ~2min (smoke test)
Usage:
# Smoke test (quick validation)
python experiments/mf_main/02_run_sweep.py --smoke-test
# Ful... |
afd5c98b2f4c09f74de8e3732cc981f1bf548984538388fb8ef59cfdcf26f29b | Python | 7,158 | 181 | """
components/base.py — Abstract Base Classes for Registrable Components
=======================================================================
Every pluggable component (Dataset, GraphBuilder, Model) inherits from one
of these bases. The contract is minimal on purpose: implementors only
override the methods they ne... |
4851324725463ade89f52a9a92bfc4aaafe47ff2a85a53146b43b6bf5d4efa9c | Python | 7,161 | 227 | # This code is part of OpenFE and is licensed under the MIT license.
# For details, see https://github.com/OpenFreeEnergy/openfe
"""
Shared pontibus Settings.
"""
from typing import Annotated, Literal, TypeAlias
from gufe.settings import BaseForceFieldSettings
from gufe.settings.typing import (
BoxQuantity,
... |
e4da4b322df59b894afec419872e91e9d0f242d4dcc6058913aaa8a1c101c690 | Python | 7,166 | 176 | import csv
import logging
from io import StringIO
from typing import Dict, Union
from multiqc.base_module import BaseMultiqcModule, ModuleNoSamplesFound
from multiqc.plots import table
from multiqc.plots.table_object import TableConfig
log = logging.getLogger(__name__)
class MultiqcModule(BaseMultiqcModule):
""... |
f0296bdcb9136fadf66a54298dce3af0b798da460a5550c76556052b3a296db0 | Python | 7,172 | 241 | import numpy as np
import pytest
import pymbar
from pymbar.utils_for_testing import assert_equal, assert_almost_equal
from pymbar.utils import ParameterError, ensure_type, TypeCastPerformanceWarning
try:
from scipy.special import logsumexp
except ImportError:
from scipy.misc import logsumexp
def test_logsume... |
1831b83662427879b50ac709d8a2f1811ab186dd3749939a4c12f1629dcfb34c | Python | 7,177 | 206 | import csv
import logging
from multiqc.base_module import BaseMultiqcModule, ModuleNoSamplesFound
from multiqc.plots import table
log = logging.getLogger(__name__)
class MultiqcModule(BaseMultiqcModule):
def __init__(self):
"""MultiQC module for processing som.py output"""
super().__init__(
... |
cf33261a84486b41d046ffc88f3a170f2ade3b28185c5a7051b7933293d6bcbe | Python | 7,179 | 177 | import logging
import re
from multiqc import config
from multiqc.base_module import BaseMultiqcModule, ModuleNoSamplesFound
from multiqc.plots import heatmap
log = logging.getLogger(__name__)
class MultiqcModule(BaseMultiqcModule):
"""
This module parses the output from the `ivar trim` command and creates a... |
32b6b99d2cf45f42a36135b9acb1dc3eeec20fb7b87c146213b48a35b7cbbde4 | Python | 7,181 | 202 | """Regression tests for the per-call rayon thread-pool fix in ``src/lib.rs``.
Background
----------
The Rust entry points used to set the number of worker threads with
``env::set_var("RAYON_NUM_THREADS", threads.to_string())``. That value is read
only once -- when rayon lazily builds its *global* pool on the first par... |
541ef3452486f4164bcaa463fc6f31439390ff124f84cc36bed8431b02308adf | Python | 7,184 | 206 | """
methods/softimpute_xgb.py — SoftImpute + XGBoost
==================================================
Iterative SVD soft-thresholding for matrix completion, followed by
XGBoost classification.
Reference
---------
Mazumder, R., Hastie, T., & Tibshirani, R. (2010). Spectral Regularization
Algorithms for Learning Large... |
0fd18f17aeefbc2444e117b07de8f14beb495c0a4c5671dd45facb844ae94df7 | Python | 7,186 | 226 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
## Import Libraries
import os, sys, csv
import glob
import warnings
import re
import gzip
warnings.filterwarnings("ignore")
## Import python libraries
import matplotlib.pyplot as plt
import pandas as pd
import numpy as np
import argparse
## Import Logger
i... |
e14fce341914451f8427237d8636bc2ca0bf7c22eaea8691034a087be996a82a | Python | 7,193 | 185 | import numpy as np
import pandas as pd
import os
# downloaded from https://ftp.ebi.ac.uk/pub/databases/cryptic/release_june2022/reuse/CRyPTIC_reuse_table_20231208.csv
# this was the most recent version available at the time this script was written
cryptic_reuse = pd.read_csv("./MIC_data/CRyPTIC_reuse_table_20231208.cs... |
f6c7168edfe0e243a57d9f595c10560562ebbd85a0b025af8a29a76a5be14654 | Python | 7,193 | 155 | """
Théo Gauvrit 18/01/2024
Cross correlation analysis to get share variability of neurons
"""
import matplotlib
import numpy as np
import matplotlib.pyplot as plt
matplotlib.use("Qt5Agg")
plt.switch_backend("Qt5Agg")
# get the clusters of neurons from MLR
# compute the mean activity trace for each cluster
# compute ... |
7b99f97d5c17ba9055aafadfcb30df9eaf7fd3ed23fa6a86c450f33d24638645 | Python | 7,195 | 201 | # -*- coding: utf-8 -*-
"""
.. module:: skimpy
:platform: Unix, Windows
:synopsis: Simple Kinetic Models in Python
.. moduleauthor:: SKiMPy team
[---------]
Copyright 2022 Laboratory of Computational Systems Biotechnology (LCSB),
Ecole Polytechnique Federale de Lausanne (EPFL), Switzerland
Licensed under the ... |
629565fba29b8be5cf02369d7dcdb7ab3706bb08075770bb96415fe3618949c0 | Python | 7,202 | 246 | #!/usr/bin/env python
# coding: utf-8
# ------------------------------
# Import the needed libraries
# ------------------------------
import argparse
import csv
import gzip
import logging
import sys, os, re
import subprocess
import csv
import pandas as pd
from collections import defaultdict
logging.basicConfig(
... |
37a1d9c92df25e44e01bd013a7e245fd6f957ec092b0e6ae91dc314a538e5696 | Python | 7,210 | 184 | from pytfa.io.json import load_json_model
from skimpy.io.yaml import load_yaml_model
from skimpy.analysis.oracle.load_pytfa_solution import load_fluxes, \
load_concentrations, load_equilibrium_constants
from skimpy.sampling.simple_parameter_sampler import SimpleParameterSampler
from skimpy.core import *
from skimpy... |
4a9e680fc9f9ca543c77237ec0eb95e81a5260d40e26b756b6c061ecd0e5a8f9 | Python | 7,214 | 218 | import copy
import torch
from torch.optim.lr_scheduler import ReduceLROnPlateau
import torch.nn as nn
import torch.optim as optim
from .eval_vis import calculate_metrics,MetricTracker,save_checkpoint
from .val import validate,test
import logging
logger = logging.getLogger(f"{__name__}.modelTraining")
class EarlyStop... |
4d4e80a8beebc27ea4eea1063dca8c2f46528796928ab91852645c7f63c1b2ac | Python | 7,218 | 171 | #!/usr/bin/env python
'''
A simple Python wrapper for the bh_tsne binary that makes it easier to use it
for TSV files in a pipeline without any shell script trickery.
Note: The script does some minimal sanity checking of the input, but don't
expect it to cover all cases. After all, it is a just a wrapper.
Exampl... |
967357b44873c8159110c6d8bb883f704d37112bc9deed687ece15e693d5d76f | Python | 7,219 | 187 | import logging
from multiqc.base_module import BaseMultiqcModule, ModuleNoSamplesFound
from multiqc.plots import bargraph, linegraph
log = logging.getLogger(__name__)
class MultiqcModule(BaseMultiqcModule):
"""
Supported scripts:
- `rsem-calculate-expression`
This module search for the file `.cnt`... |
b498123b546fd7beb32a2be8076812612b238b00a3d02ce597a50ec7763b448c | Python | 7,219 | 129 | import os
import json
import shutil
import configparser
import logging
import sys
import subprocess
import traceback
import pandas as pd
def test_validation_pipeline_metrics_space(test_dir):
logging.basicConfig()
logging.getLogger().setLevel(logging.DEBUG)
logging.info("Running standard reporting unit tes... |
8389b4b5b3d4e872f3806202ce41fb1ff363e775b2d0c0c88a16ede50d786897 | Python | 7,221 | 210 | import os
import glob
import numpy as np
import pandas as pd
import seaborn as sns
from matplotlib import pyplot as plt
from scipy.stats import ttest_rel
from statsmodels.stats.anova import AnovaRM
# =============================================================================
# Paths
# ==============================... |
4c91362b8bad75bdee1ec70247fe8208b3b3d1ee460b0f8a00ca69229ddba725 | Python | 7,224 | 199 | """
core/config.py — Typed Configuration Dataclasses
===================================================
Provides strongly-typed, hierarchical configuration containers.
All configs are plain Python dataclasses and can be populated from a
YAML file via ``ExperimentConfig.from_yaml(path)``.
Design principles:
- Every ... |
d8ca50014c377e3909a799c86423fa7653c51ce180dff9aff0b5e2a50707f101 | Python | 7,224 | 215 | """
The tasks module holds the TaskFiles class which organizes input and
output paths and the Task class for tasks in the runmanager queue.
"""
import logging
import shutil
from dataclasses import dataclass, field
from pathlib import Path
from typing import Any, Callable, Optional
from kimmdy.constants import MARK_DO... |
b641b0447673d5fc6222cc521bb90d7d6b0e5b5d16615baaee1b49a45a81ed3d | Python | 7,234 | 179 | """
Example illustrating the application of MBAR to compute a 1D free energy profile from an umbrella sampling simulation.
The data represents an umbrella sampling simulation for the chi torsion of
a valine sidechain in lysozyme L99A with benzene bound in the cavity.
Reference:
D. L. Mobley, A. P. Graves, J. D. ... |
41b27ecdca6a9dbb2235bc8f4009dc618ae55ff0a3d9449a8088fb0304dcc2eb | Python | 7,236 | 211 | #!/usr/bin/env python3
"""
Batch extraction script for running D4D extractions on all datasets with GPT-5.
"""
import asyncio
import os
import sys
import json
import hashlib
from pathlib import Path
from urllib.parse import urlparse
# Add the src directory to the path so we can import aurelian modules
sys.path.insert(... |
a5470f8d2561fe4aa2b1d78f42dcd791131c3883f7976cf0f37fb0e7ca80c2b5 | Python | 7,236 | 201 | # 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... |
5d34305118d432a8075d82e51f565ac05c04f65f45bd9f80fc7361c252d91199 | Python | 7,238 | 202 | from loguru import logger
from truesight import parse_utils, plot_utils, stats_utils
from truesight.experiment.services import EvaluationRef, LLMRef
from refs import evaluation_refs
import pandas as pd
import matplotlib
import matplotlib.pyplot as plt
matplotlib.use("WebAgg")
matplotlib.rcParams["webagg.address"] = "... |
709a3f335d4210f458c1c663776fbcbb39d2e1e2cb9cbcc6446d4c894bcd1b10 | Python | 7,240 | 181 | import logging
from collections import defaultdict
from typing import Dict
from multiqc.base_module import BaseMultiqcModule, ModuleNoSamplesFound
from multiqc.plots import bargraph, table
log = logging.getLogger(__name__)
class MultiqcModule(BaseMultiqcModule):
"""
The module parses results generated by th... |
12e0786eda772ee832f6465257fe128e94cb71d72edcda6615f3d89db59cc643 | Python | 7,241 | 170 | from sklearn.neighbors import kneighbors_graph
import numpy as np
import pandas as pd
import math
import datetime
import os
import shutil
import torch
from torch_geometric.data import Data, InMemoryDataset
# Hyperparameters
InputFolderName = "./MIBI-TNBC_Input/"
KNN_K = 72
# Import image name list.
Region_filename... |
c61d1f745a25f4d56b9868b35868bf8729382600646e6dc8b2a3d3506827aff9 | Python | 7,241 | 201 | import pathlib
import os
import pandas as pd
import numpy as np
import torch
import torchvision.transforms as transforms
from torch.utils.data import Dataset
from PIL import Image
from torch.utils.data import random_split
from torch.utils.data import DataLoader
import torch.nn as nn
import torch
from torch.... |
559616d382274abc115b34eb152f6851aa2d763bd9fa6c4deebb57bd69ce860c | Python | 7,242 | 201 | import pathlib
import os
import pandas as pd
import numpy as np
import torch
import torchvision.transforms as transforms
from torch.utils.data import Dataset
from PIL import Image
from torch.utils.data import random_split
from torch.utils.data import DataLoader
import torch.nn as nn
import torch
from torch.... |
8134756e31ae00c250fe0e2df16f29b6b6a6fb9da903f5e712c5b530195ef234 | Python | 7,243 | 201 | import pathlib
import os
import pandas as pd
import numpy as np
import torch
import torchvision.transforms as transforms
from torch.utils.data import Dataset
from PIL import Image
from torch.utils.data import random_split
from torch.utils.data import DataLoader
import torch.nn as nn
import torch
from torch.... |
f6eb055438079972c139c85de94452d723e39bd873df008f09d0f727adf57562 | Python | 7,244 | 201 | import pathlib
import os
import pandas as pd
import numpy as np
import torch
import torchvision.transforms as transforms
from torch.utils.data import Dataset
from PIL import Image
from torch.utils.data import random_split
from torch.utils.data import DataLoader
import torch.nn as nn
import torch
from torch.... |
6931e37b6b1994cf63f41ce86310d176909c3c57ed480bf32b66009615bbc635 | Python | 7,245 | 201 | import pathlib
import os
import pandas as pd
import numpy as np
import torch
import torchvision.transforms as transforms
from torch.utils.data import Dataset
from PIL import Image
from torch.utils.data import random_split
from torch.utils.data import DataLoader
import torch.nn as nn
import torch
from torch.... |
c665817b4b9ad795a27e8bcafeaf7ee14a5264ce7328a31550e3e4549d441811 | Python | 7,245 | 201 | import pathlib
import os
import pandas as pd
import numpy as np
import torch
import torchvision.transforms as transforms
from torch.utils.data import Dataset
from PIL import Image
from torch.utils.data import random_split
from torch.utils.data import DataLoader
import torch.nn as nn
import torch
from torch.... |
92c581b8f180e1cd4a9de0ab464beb8599d16124acb24d8fcadb5f7b7de74519 | Python | 7,252 | 168 | """Per-UMI files, summarized rather than listed: `<prefix>.umi_counts.txt` (simplex/duplex),
`<prefix>.duplex_umi_counts.txt`, and `correct --metrics`. Rows are streamed so a large file is not turned into
one pydantic object per UMI."""
import itertools
from collections import Counter
from typing import Any, Dict, Ite... |
dc4cf489497ca2389c6af431633e777649a6f52ed444e92b23a5284cb944b976 | Python | 7,252 | 157 | # Code analyzes and plots the occlusion sensitivity results from the visual analysis
import pandas as pd
import matplotlib.pyplot as plt
import numpy as np
# Settings
feature_plot_name = 'occlusion_proportions_misidentifications.png'
using_true_positive_results = True
if using_true_positive_results:
# Settings f... |
81c43943e8511292d9e62f22aaf9780538888a99bd30334879072d9cd2f62054 | Python | 7,265 | 215 | import logging
import re
from typing import Any, Dict, Optional
from multiqc import BaseMultiqcModule, config
from multiqc.plots import violin
# Initialise the logger
log = logging.getLogger(__name__)
# ampliconclip has value thing per line, documented here (search for ampliconclip):
# http://www.htslib.org/doc/samt... |
868b92832e8c1386717e639d33b5c3999659c2d75b76339491616a22d8aceaac | Python | 7,273 | 207 | #!/usr/bin/env python
from __future__ import division
from __future__ import print_function
import numpy as np
import itertools
import os, sys
import networkx as nx
from collections import defaultdict
from forcebalance.molecule import Molecule
from forcebalance import Mol2
#===========================================... |
bfc8606e0e83f746b3407bc8caabe099c1ccd3d9b4a209a342c74e74a2378a25 | Python | 7,274 | 238 | import numpy as np
from numpy.typing import NDArray
from typing import Tuple, Union, Optional, Dict, Iterable
import warnings
from rdkit import Chem
from rdkit.Geometry.rdGeometry import Point3D
from matplotlib import pyplot as plt
from matplotlib.colors import rgb2hex
try:
import py3Dmol
except ImportError:
... |
9dfee6cb5eb6023fd985e26af1452098e0154327f80b35b0dc9f63e710645674 | Python | 7,279 | 167 | import numpy as np
from helper_funcs import run_himalayas, split_by_exp_passage_num
def construct_splits_pereira(X, y, data_labels, alphas, device, feature_grouper,
n_iter, use_kernelized, dataset, exp, linear_reg, zscore, custom_ridge=False):
y_hat_folds = []
mse_stored_inte... |
5f9f4392b774ddf6a437ed9731f817808ca5fdcdb4d56a10396e2f0bbf50c212 | Python | 7,280 | 215 | #!/usr/bin/env python3
"""
Bpod Port Event Monitor - Real-time using loop_handler()
"""
import queue
import time
from pybpodapi.protocol import Bpod
from pybpodapi.state_machine import StateMachine
class RealTimeBpodMonitor(Bpod):
"""
Real-time Bpod event monitor using loop_handler() for immediate event proc... |
b420c10915d14a903fced9ae127bf25722b74469db1216a253db236e7728bda2 | Python | 7,282 | 169 | import logging
import re
from typing import Dict
from multiqc import config
from multiqc.base_module import BaseMultiqcModule, ModuleNoSamplesFound
from multiqc.plots import bargraph
from multiqc.types import Anchor, ColumnKey
log = logging.getLogger(__name__)
class MultiqcModule(BaseMultiqcModule):
"""
The... |
36652210df644c95770ec4f599ea90aea46e622eee5c2a888b3b89c77320e26e | Python | 7,287 | 210 | from typing import Dict, List, TYPE_CHECKING, Optional
import torch
import numpy as np
from openff.utilities import requires_package
from openff.nagl.features.atoms import AtomFeature
from openff.nagl.features.bonds import BondFeature
from openff.nagl.features._featurizers import AtomFeaturizer, BondFeaturizer
from o... |
3bf132ddc9af687c5df27b1fb5252a7071572a056847842f9f69c41743f70131 | Python | 7,289 | 280 | ALLRED_ROCHOW_ELECTRONEGATIVITY = {
# sourced from mendeleev
1: 0.0009765625,
2: 0.0008034026465028355,
3: 7.34920006783877e-05,
4: 0.00018742791234140717,
5: 0.00035986159169550173,
6: 0.0005777777777777778,
7: 0.0007736560206308273,
8: 0.001146384479717813,
9: 0.00126953125,
... |
b65c3b111defe55e5a90a7f2c3d7bd63f09418a949b1dcfb084b6514b3afa6dc | Python | 7,290 | 191 | # -*- coding: utf-8 -*-
"""
.. module:: skimpy
:platform: Unix, Windows
:synopsis: Simple Kinetic Models in Python
.. moduleauthor:: SKiMPy team
[---------]
Copyright 2017 Laboratory of Computational Systems Biotechnology (LCSB),
Ecole Polytechnique Federale de Lausanne (EPFL), Switzerland
Licensed under the ... |
68ceae69ead036a13af369fadf09c44af12178522c30f9310b00e4e4c1db38bb | Python | 7,291 | 145 | from PySide6.QtWidgets import QWidget, QHBoxLayout, QVBoxLayout, QLabel, QStackedWidget
from PySide6.QtGui import QIcon, QPixmap, QColor
from PySide6.QtCore import Qt, QSize, Signal
import logging
from utils.software_config import SoftwareConfigResources
from gui.SinglePatientComponent.CentralDisplayArea.CentralDisplay... |
71d606a48f62c7b13f8b3063182944be077f403a9ec2f70c9064dc49bfcd9df2 | Python | 7,293 | 194 | """Generate per-subject case-study figures for the paper.
Picks a handful of named test subjects and produces aligned MRI / real
PET / generated PET montages plus longitudinal follow-up renderings.
Used to back up specific qualitative claims in the discussion.
"""
import os
import ants
import torch
import random
impo... |
8470da1b79a45b6029c353311e025a23a5d54b1a8529e0ca122fa1cb790a6a45 | Python | 7,294 | 258 | from sys import argv
if len(argv) != 3:
print(f"Need to pass the run id, e.g. python {argv[0]} 1 10")
exit()
id = argv[1]
embeddings_dim = argv[2]
import os
from glob import glob
from pathlib import Path
import pickle
import numpy as np
import pandas as pd
import seaborn as sns
import matplotlib.pyplot as pl... |
9b4ce8bb743593f4e8c610698e870fda1aa19646bffa422af690bb4c5dd6a18a | Python | 7,299 | 153 | import torch
import numpy as np
def gen_cube(device = torch.device("cpu")):
""""Generates a synthetic dataset based on the structure of a cube. Not biologically realistic, but useful for demos and testing.
Args:
device (torch.device, optional): Specify the PyTorch device to use, e.g., CPU, GP... |
f07ab60d00d6b7138257b6b6480d68ea4d5ffee6ede740786f894949cb3e3bc8 | Python | 7,312 | 196 | # This code is part of OpenFE and is licensed under the MIT license.
# For details, see https://github.com/OpenFreeEnergy/openfe
"""Equilibrium Relative Free Energy methods using OpenMM and OpenMMTools in a
Perses-like manner.
This module implements the necessary methodology toolking to run calculate a
ligand relative ... |
1259d8d0ee0898227a04d94bf2778412a3c3955a71fc6a02418bf706bf795ddb | Python | 7,313 | 214 | import numpy as np
import nibabel as nib
import os
from skimage.metrics import peak_signal_noise_ratio, structural_similarity
from Quality_Metrics.Tenengrad import TG
from Quality_Metrics.AES import aes
from Quality_Metrics.CoEnt import coent
from Quality_Metrics.ImageEntropy import iment
from Quality_Metrics.GradientE... |
8272ef1baa6651e34c59b464039c81c175d7a6d272cf3c0a1da782229c2d1f70 | Python | 7,314 | 169 | import time, sys, threading, logging, copy, Queue, warnings
import multiprocessing as mp
import numpy as np
import pylab as pl
from daq import DAQIn
from expts.routines import add_to_saver_buffer
from util import now,now2
class AnalogReader(mp.Process):
"""
Instantiates a new process that handles a DAQIn objec... |
8864a82e3c67f24881b89cec7c4b927c76b48c44929b9ab0bc2430e78eada526 | Python | 7,318 | 175 | import logging
from collections import defaultdict
from typing import Dict
from multiqc import config
from multiqc.plots import bargraph, linegraph
from multiqc.plots.bargraph import BarPlotConfig
# Initialise the logger
log = logging.getLogger(__name__)
def parse_samtools_idxstats(module):
"""Find Samtools idx... |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.