sha256 stringlengths 64 64 | language stringclasses 27
values | size int32 1 491k | lines int32 1 21.8k | content stringlengths 1 200k |
|---|---|---|---|---|
087a4a062aa6db650e99ed75413432f3666a977973d520117be1fb6c4d3fd221 | Python | 12,854 | 280 | ##############################################################################
# Medical Image Registration ToolKit (MIRTK)
#
# Copyright 2017 Imperial College London
# Copyright 2017 Andreas Schuh
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with ... |
f118b56f07e231ebf89bfd94379881566a719d122dd8653722568b75ebf631f5 | Python | 12,861 | 324 | import torch
import torch.nn as nn
import torch.nn.functional as F
from .sakeLayer import SAKEInteractionLayer
from .dgn import DGN
from .modules import (
GradientScale, FeatureRecalibration,
BalancedFusion, AdaptiveFusion)
from typing import List, Optional
import dgl
class SAKEPP(nn.Module):
"""SAKE++: A... |
e209fb13565c9ce3bd961f93099900368365c8fe3d962b3f7de2decc8362c6b6 | Python | 12,878 | 311 | from multiqc.utils import mqc_colour
from multiqc.plots import bargraph
from .utils import summarize_batch_names, is_nan, find_entry, json_decode_float
from .queries import (
get_batch_counts,
get_batch_density,
get_batch_extracellularratio,
get_cell_count,
get_median_cell_diameter,
get_percent... |
d95186ad8ca5753cf05d8469e78479359fce412b1dd8c458e612382b2697ce6f | Python | 12,885 | 365 | # 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... |
65a887c8904dc02b3b8b930925f91f324b3a2c7d688b7037efa299fc82f5ae37 | Python | 12,900 | 347 | """
Test MBAR by performing statistical tests on a set of of 1D harmonic oscillators, for which
the true free energy differences can be computed analytically.
A number of replications of an experiment in which i.i.d. samples are drawn from a set of
K harmonic oscillators are produced. For each replicate, we estimate ... |
adcdf8a7591f01a49ba5b297bdbbf7d2ce87730a0b02b824894c955a6059abe5 | Python | 12,900 | 394 | # This code is part of OpenFE and is licensed under the MIT license.
# For details, see https://github.com/OpenFreeEnergy/openfe
from unittest import mock
import mdtraj as mdt
import pytest
from gufe import ChemicalSystem
from openfe.tests.protocols.openmm_ahfe.test_ahfe_protocol import (
_assert_num_forces,
_... |
3aee5b6811a5b7bb998af02974bb12563fa6d990f7f66d55201a5d79224f0260 | Python | 12,915 | 344 | from operator import index
import numpy as np
import pandas as pd
# import quadprog as qp
# import cvxopt
from scipy import sparse
from sklearn.base import BaseEstimator
from sklearn.linear_model import Ridge
from sklearn.linear_model import Lasso
import cortico_cereb_connectivity.evaluation as ev
import cortico_cereb_... |
c62dfcd6201d6153652cd0480475d5bed0d8759b66ca4b9ea4978ce014eeb92c | Python | 12,915 | 273 | import json
# Initialise the logger
import logging
from collections import defaultdict
from multiqc.base_module import BaseMultiqcModule
from multiqc.plots import linegraph
from multiqc import report
from multiqc.utils.material_icons import get_material_icon
from .util import average_from_range, average_pos_from_met... |
8567dc0393e0cbeb55a7afa2c723713c7d2d642efefbb0ffdb76502868b0c63b | Python | 12,930 | 315 | import numpy as np
import os
from helper_funcs import combine_MSE_across_folds
from typing import Union
from neural_dat_funcs import construct_splits_blank, construct_splits_fedorenko, construct_splits_pereira
from helper_funcs import preprocess_himalayas, pearson_corr_schrimpf_style
from copy import deepcopy
def... |
4153215565c0b60c91ac5f27db8bd7d6ef4c76a4fde3f188b6a842b34853d7b0 | Python | 12,939 | 378 | from __future__ import annotations # for 3.7 <= Python version < 3.10
import logging
import re
from itertools import permutations
from typing import TYPE_CHECKING, Any, Callable, Optional
from kimmdy.constants import ION_NAMES, REACTIVE_MOLECULEYPE, SOLVENT_NAMES
from kimmdy.topology.atomic import AtomId, MoleculeTy... |
d34f411f292b7963c7958e1964b0089b6771f86e4ecc0e930259c6d445bf9418 | Python | 12,939 | 359 | """
twinc_train.py
Author: Anupama Jha <anupamaj@uw.edu>
"""
import os
import torch
import pyfaidx
import argparse
import numpy as np
import configparser
from .twinc_network import TwinCNet
from .twinc_utils import count_pos_neg, decode_chrome_order_dict, decode_list
def extract_set_data(labels_file, set_chrs, chrom... |
834abc87845643fd7b28cf229e03b386952100bf493b5308e54ecb74b2b082e2 | Python | 12,952 | 330 | """MultiQC module to parse output from Cell Ranger count"""
import json
import logging
import re
from typing import Dict
from multiqc import BaseMultiqcModule, config
from multiqc.modules.cellranger.utils import clean_title_case, parse_bcknee_data, set_hidden_cols, update_dict
from multiqc.plots import linegraph, tab... |
7393664a281b897f6381f0b606607632173994dff2bfea9011fc02d6e026e37d | Python | 12,961 | 348 | """Tests torsion minimization."""
import copy
import numpy
import openmm
import openmm.unit
import pytest
from openff.toolkit import ForceField, Molecule
from openff.units import Quantity, unit
from yammbs._forcefields import build_omm_system
from yammbs.analysis import get_rmsd
from yammbs.torsion._minimize import ... |
0383bf3e43f266ccf0e2913a3d866ae4a57203d43aa13a0985fa43251264e81b | Python | 12,972 | 358 | """
twinc_train.py
Author: Anupama Jha <anupamaj@uw.edu>
TwinC classification training routine.
"""
import os
import torch
import pyfaidx
import argparse
import numpy as np
import configparser
from twinc_network import TwinCNet
from twinc_utils import count_pos_neg, decode_chrome_order_dict, decode_list
def extract_... |
eb731f12e15b404eec31ded7cf4bce61c7146e05bc07d067d31dafd94fae4d93 | Python | 12,986 | 480 | import os
import numpy as np
import multiprocess as mp
N_MAX_PROCESSES = 12 # defined by compute setup
from src.microcircuit import *
from src.save_exp import *
import src.plot_exp as plot_exp
import src.save_exp as save_exp
from src.init_MC import init_weights
import sys
import logging
from functools import partial, ... |
e4f4f3ff632d4bb327fdb9b50200b788cf555ffdf28551d694adf0ead2289084 | Python | 13,006 | 331 | import unittest
import pytest
from shapely import geos_version
from shapely.errors import GeometryTypeError, GEOSException
from shapely.geometry import (
LineString,
MultiLineString,
MultiPoint,
MultiPolygon,
Point,
Polygon,
)
from shapely.ops import linemerge, split, unary_union
# Note: when... |
94c861236bd4e6482cd7e8df92cf0141383ac220d8e17cfde4e05f5f35dbc46f | Python | 13,008 | 345 | import re
import pandas as pd
from itertools import chain
from tqdm.autonotebook import tqdm
NONALNUM_PATTERN = re.compile('[\W_]+')
def strip_chars(string):
return NONALNUM_PATTERN.sub('', string)
def char_combine_iter(iterable, char='|', sort=False):
"""Deduplicates elements, then combines an iterable on... |
d93973b8ce45ff0977cf0fd0bce759e754d3d551e74d11544d7800982a31bd5c | Python | 13,009 | 414 | from pathlib import Path
import csv
import click
from cinnabar import Measurement, ReferenceState, FEMap
from cinnabar import plotting as cinnabar_plotting
from openff.units import unit
import numpy as np
import warnings
def get_exp_data(filename: Path) -> dict[str, dict[str, float]]:
"""
Fetch the experiment... |
a10884919e24be62b02e1134eacc7756d2fe0bb652528dddcca8194042463b6b | Python | 13,017 | 336 | import json
import logging
import re
from typing import Dict
from multiqc.base_module import BaseMultiqcModule, ModuleNoSamplesFound
from multiqc.plots import bargraph
log = logging.getLogger(__name__)
class MultiqcModule(BaseMultiqcModule):
def __init__(self):
super().__init__(
name="CCS",
... |
688fea9caf66f2550b6434ba5ccbffa768f6a487a155b49aadbe0f2470c0eddc | Python | 13,027 | 322 | import os
import sys
import itertools
from importlib.machinery import EXTENSION_SUFFIXES
from distutils.command.build_ext import build_ext as _du_build_ext
from distutils.file_util import copy_file
from distutils.ccompiler import new_compiler
from distutils.sysconfig import customize_compiler, get_config_var
from distu... |
f01591f8120fb29eb636a8c0cfe4409ad37e48ff80fc758222b44227fcd71032 | Python | 13,031 | 341 | #!/usr/bin/env python3
# ----------------------------------------------------------------------------
# Copyright (c) 2020--, Qiyun Zhu.
#
# Distributed under the terms of the Modified BSD License.
#
# The full license is in the file LICENSE, distributed with this software.
# ------------------------------------------... |
3a3d29bf3348f57e68c43548634b006e170fb95e92198728b25674b2dcb9dc36 | Python | 13,040 | 252 | import torch
import torch.nn as nn
import torch.nn.functional as F
from layers.SelfAttention_Family import FullAttention, AttentionLayer
from layers.Embed import DataEmbedding_inverted, PositionalEmbedding
import numpy as np
from layers.convffn import FeedForwardNetwork
class FlattenHead(nn.Module):
def __init__(s... |
2d097bfd3f9c22a01f555e387fe7744a57bdb60ccf429b60d98dc91cefb2fdaf | Python | 13,046 | 338 | # This code is part of OpenFE and is licensed under the MIT license.
# For details, see https://github.com/OpenFreeEnergy/openfe
import pathlib
import mdtraj as md
import numpy as np
import openmm
import pytest
from gufe.protocols import execute_DAG
from numpy.testing import assert_allclose
from openff.units import u... |
dabcdcc45596e6c9e53920891a466e055c3195e68f004d60175a298f5b0ec654 | Python | 13,049 | 402 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
ENCODING - AVERAGE FEATURES BEFORE PCA - UNREAL ENGINE
This script implements the multivariate linear ridge regression for the
scene features from the Unreal Engine for a single frame.
@author: Alexander Lenders, Agnessa Karapetian
"""
from utils import (
load_ee... |
eeddfa425e581beeb87632fbe19d04b274539fbb4ca96878901f69a693b67099 | Python | 13,055 | 411 | # Copyright 2024 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,... |
b50b600cebbe803646db77d0155bb04d87116217d7f0f69bd1c43bfa6f3514ab | Python | 13,061 | 406 | # This code is part of OpenFE and is licensed under the MIT license.
# For details, see https://github.com/OpenFreeEnergy/openfe
"""Settings class for equilibrium AFE Protocols using OpenMM + OpenMMTools
This module implements the necessary settings necessary to run absolute free
energies using OpenMM.
See Also
----... |
187e4a546243f87d1ee8aeafc717b541823448040730dc80d90bfd3699717e16 | Python | 13,077 | 344 | #!/usr/bin/env python3
"""
生物学合理性验证 - 四分类统计 (Four-Class Database Validation)
对每种癌症的每个模型的 Top 100 关键基因，在四个数据库中进行四分类验证：
1. OncoKB - 癌症基因临床分级
2. DGIdb - 药物-基因互作 (仅二分类)
3. Open Targets Platform - 基因-疾病关联
4. CancerMine - 文献挖掘癌症基因
四分类定义:
- same_only: 基因仅在当前癌症类型有记录（无其他癌种）
- same_and_other: 基因在当前癌症类型有记录，同时也在其他癌种有记录
- other_o... |
fa712031a7d7ba22e8816bfc4258bb7d38cbe09d1f4ccac412baa22d8796d9f2 | Python | 13,087 | 232 | import os
import numpy as np
import pandas as pd
from typing import List
def export_df_to_latex(folder, data, suffix=''):
matrix_filename = os.path.join(folder, 'df_latex.txt') if suffix == '' else os.path.join(folder, 'df_' + suffix + '_latex.txt')
columns = data.columns.values
pfile = open(matrix_filena... |
f1f8ddb224e1b9dd7ae4c9976e89ec58f4b20fbdc7a4a13ea5987c21c31e4153 | Python | 13,095 | 344 | """
Copright © 2023 Howard Hughes Medical Institute, Authored by Carsen Stringer and Atika Syeda.
"""
import numpy as np
import pyqtgraph as pg
from matplotlib import cm
from qtpy import QtCore, QtGui, QtWidgets
from qtpy.QtWidgets import (
QDialog,
QHBoxLayout,
QPushButton,
QVBoxLayout,
QWidget,
)
... |
1c02b057dbed1389973c9584bcb9de95f56ee28005060ebd779c441f53d96936 | Python | 13,110 | 302 | from __future__ import division
from builtins import object
import os
import numpy as np
from forcebalance.finite_difference import fdwrap, f12d3p
from forcebalance.molecule import Molecule
from forcebalance.nifty import col, flat, statisticalInefficiency
from forcebalance.nifty import printcool
from collections impo... |
4f078537bf9621a77f922c4cc62b950cb334876bcb4859cf9322d5738c819fe4 | Python | 13,124 | 253 | from truesight.experiment.services import (
FinetunedLLMRefDeprecated,
FinetunedLLMRef,
CombinedDatasetRef,
FilteredDatasetRef,
)
from refs.llm_base_refs import gpt41
from refs import dataset_external_refs, numbers, dataset_nums_refs, llm_teacher_refs
from truesight.finetuning import services as finetun... |
5e3c6b1e5a3f94dc6cda41d62054cb39b0d9ead7c588a5ee614a3a6528cd1188 | Python | 13,144 | 382 |
import matplotlib.pyplot as plt
from typing import Callable, Dict, Any, Tuple
from itertools import combinations
from math import comb # Python 3.8+
from scipy.spatial.distance import cdist
import numpy as np
def initialization(N: int, dim: int, ub, lb):
"""
初始化种群
"""
ub = np.atleast_1d(ub).astype(f... |
41583427f993028b2e7552b245133e0d528836986862bf4d37b9988744220d5c | Python | 13,149 | 388 | import numpy as np
import TaskRest.paths as indiv_paths
import numpy as np
import matplotlib.pyplot as plt
from copy import deepcopy
from nilearn import plotting
import seaborn as sb
import TaskRest.covariance as cov
import PcmPy as pcm
from scipy.stats import ttest_rel
# Set indiv_paths
base_dir = indiv_paths.set_ba... |
60f1d2f68d0ffa87d647d1d53874f1dcf2d6c70b867978357b1a955fda5434d9 | Python | 13,151 | 402 | """ Module to identify neurons that are monosynaptically connected to the antennal grooming neurons. """
import pickle
from typing import List
from pathlib import Path
import numpy as np
import pandas as pd
from tqdm import tqdm
from concurrent.futures import ThreadPoolExecutor, as_completed
import Figure4_neurons a... |
3f66a0b02583ef9836a319031252c79c324205a1b7cb5c1ee1bf64580f89755e | Python | 13,156 | 314 | import logging
from typing import Dict
from multiqc.base_module import BaseMultiqcModule, ModuleNoSamplesFound
from multiqc.plots import bargraph, violin
log = logging.getLogger(__name__)
class MultiqcModule(BaseMultiqcModule):
"""
The module parses the
[vg stats](https://github.com/vgteam/vg/wiki/Mappi... |
942429a55a2a18bf12d49f36a66e65b3e214c8290d6e16aff8c1a80fb980e0ad | Python | 13,177 | 322 | '''
Copyright (c) 2019 NeuroNexus
Permission is hereby granted, free of charge, to any person obtaining a copy
of this software file and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute... |
faeba549fc57efe4238e83e8862dbe7b75c537b48b37396eb15a30b2c6976f42 | Python | 13,186 | 421 | ##############################################################################
# pymbar: A Python Library for MBAR
#
# Copyright 2016-2017 University of Colorado Boulder
# Copyright 2010-2017 Memorial Sloan-Kettering Cancer Center
# Portions of this software are Copyright 2010-2016 University of Virginia
#
# Authors: M... |
cbd4a65de60ab4e581d8aba83d9f90f0d7bd08ac535a4738bdede24428cf33a6 | Python | 13,187 | 422 | ##############################################################################
# pymbar: A Python Library for MBAR
#
# Copyright 2016-2017 University of Colorado Boulder
# Copyright 2010-2017 Memorial Sloan-Kettering Cancer Center
# Portions of this software are Copyright 2010-2016 University of Virginia
#
# Authors: M... |
dd81651280c224c64d269ba076093588312bcf169cc300452a18076ed79e2c08 | Python | 13,187 | 422 | ##############################################################################
# pymbar: A Python Library for MBAR
#
# Copyright 2016-2017 University of Colorado Boulder
# Copyright 2010-2017 Memorial Sloan-Kettering Cancer Center
# Portions of this software are Copyright 2010-2016 University of Virginia
#
# Authors: M... |
5acc3781e9f4ce3aaf3335f6c07192668118f04caa8746044e63cc6c0894d978 | Python | 13,201 | 522 | #!/usr/bin/env python3
# ----------------------------------------------------------------------------
# Copyright (c) 2020--, Qiyun Zhu.
#
# Distributed under the terms of the Modified BSD License.
#
# The full license is in the file LICENSE, distributed with this software.
# ------------------------------------------... |
7634c32aa4f1abc6d68e4125b378a9b4f8928533a50fee71cdba99c1e0bf830c | Python | 13,206 | 309 | #############################################################################
# HYBRID SYSTEM SAMPLERS
#############################################################################
"""
This is adapted from Perses: https://github.com/choderalab/perses/
See here for the license: https://github.com/choderalab/perses/blob/... |
c06f9f80332971028a62d266bb6547f67155627f08bc673c384e54bb154a7ed3 | Python | 13,208 | 388 | #!/usr/bin/env python
# coding: utf-8
import numpy as np
import pandas as pd
import os
import torch
import math
import torch.nn as nn
import torch.optim as optim
import matplotlib.pyplot as plt
from scipy.interpolate import interp1d
from scipy.interpolate import CubicSpline
from scipy.integrate import quad
from scipy.... |
aff480cfdb4ca1c1262752d15b521594818c61c688be73bbe5f98df89949e298 | Python | 13,213 | 315 | """
Plotting utilities for training curves, comparisons, and analysis figures.
"""
import numpy as np
import matplotlib.pyplot as plt
import seaborn as sns
import pandas as pd
# ---------------------------------------------------------------------------
# Per-model learning curves
# ---------------------... |
48a4330138f66a930119c7e2c2092d55ba476c44f61078fd071bfc8deef12a71 | Python | 13,247 | 342 | # 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,... |
f462e097a24f1daf67f4815ccd95e7c0b80e9396aa67ede67c1169e102666b1c | Python | 13,247 | 331 | #!/usr/bin/env python3
"""
Analysis: Decision-Tree Threshold Calibration (TASK-11)
=======================================================
Calibrates the five thresholds used by the DT baseline in LODOCrossValidator
from actual sweep data rather than relying on hand-picked constants.
Thresholds calibrated
------------... |
b76e37f56800c5817f1e3f0b27bfebd7d502e720024dbc843d376e5dc9e8c978 | Python | 13,277 | 337 | import os
import pydicom
import pandas as pd
import numpy as np
from pathlib import Path
import warnings
warnings.filterwarnings('ignore')
def extract_imaging_parameters(main_dir):
"""
Extract imaging parameters from DICOM files for all modalities.
Args:
main_dir: Main directory containing pat... |
f7fa2d751c293ad9c8e9b4e9cdb16c113b4063da01a383f76848d7a9603a43a7 | Python | 13,289 | 395 | # scripts/preprocess_rsna_improved.py
"""
Script de preprocesamiento mejorado para RSNA dataset
Genera archivos .npy con:
- Nuevas dimensiones: (96, 192, 192, 1)
- Ventana Hounsfield adaptativa según scanner
- Selección inteligente de series axiales
- Mejor manejo de errores y logging
USO:
# Procesar solo estudios... |
53cbf7b6f1dfbff48e5672b2c6578ee525e86161725ef45718dad8906478201a | Python | 13,325 | 354 | #!/bin/env python
"""
Module simtk.unit.unit_definitions
This is part of the OpenMM molecular simulation toolkit originating from
Simbios, the NIH National Center for Physics-Based Simulation of
Biological Structures at Stanford, funded under the NIH Roadmap for
Medical Research, grant U54 GM072970. See https://simtk.... |
34a261a64cb96e4c8507ff2254cfef2d1fbb6224e7a3a6148c1365c4ade16e50 | Python | 13,329 | 432 | import nrrd
import numpy as np
import pickle
import matplotlib.pyplot as plt
import pandas as pd
import seaborn as sns
sns.set_theme(style="white")
# Allen 25um dimensions
# [528, 320, 456]
M = 456
N = 320
# VAL volume starts from 240th voxel in x-direction in CCFv3.0
MIN_X = 240
with open("data/atlas/val_25_voxels... |
19fea33883c2572f813faa4aeea11f81ee8e2f6e1005e7f1090cd5b3587b1807 | Python | 13,333 | 324 | import logging
from collections import defaultdict
from typing import Dict, Union
import spectra # type: ignore
from multiqc.base_module import BaseMultiqcModule, ModuleNoSamplesFound
from multiqc.plots import bargraph, table
from multiqc.utils.mqc_colour import mqc_colour_scale
log = logging.getLogger(__name__)
... |
5c12cc31cfce7b3f531becdb650ec9cf8351875d455a9ac2725b08a41a3c486a | Python | 13,339 | 308 | from sklearn.decomposition import PCA
from sklearn.preprocessing import LabelEncoder
import torch
import numpy as np
import cv2
import matplotlib.pyplot as plt
import networkx as nx
from collections import defaultdict
import tqdm
import cmapy
import pyro
import torch.nn.functional as F
from pcc import PCUMA... |
32d37d7424770358e10fc718e61ee5f0559792064c5f93b9ae965c55e06e3b57 | Python | 13,357 | 384 | import numpy as np
from scipy.stats import norm
# TODO: Extract statistics and other utils from ptmelt and tfmelt into a common library
def compute_rsquared(truth, pred):
"""
Compute the coefficient of determination (:math:`R^2`).
The :math:`R^2` value is calculated as:
.. math:: R^2 = 1 - \\frac{\... |
9acddbed28a3b342480dd4b3642656bada3edabcf180bea63c8dd9468835f973 | Python | 13,367 | 311 | import time
from PySide6.QtWidgets import QWidget, QVBoxLayout, QScrollArea, QTabWidget, QSizePolicy
from PySide6.QtCore import Qt, QSize, Signal
from PySide6.QtGui import QColor
import logging
from gui.SinglePatientComponent.LayersInteractorSidePanel.TimestampsInteractor.TimestampsLayerInteractor import TimestampsL... |
f91f6207e02ecca40d2236fcbf05705052874aeb0f64748f4c7ea1eec6fb2634 | Python | 13,372 | 414 | """Reaction plugin building blocks"""
import logging
from pathlib import Path
from typing import Optional, TypeAlias, TypedDict
import numpy as np
from kimmdy.constants import R
from kimmdy.parsing import Plumed_dict, read_distances_dat, read_edissoc, read_plumed
from kimmdy.topology.atomic import BondId
from kimmdy... |
9fd3cfeb0cb09a14a0ec1ddaa14b48332ae2c299bc422444ad513ca00339a63c | Python | 13,383 | 325 | import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import seaborn as sns
import os
import logging
from typing import Dict, List, Tuple
from pathlib import Path
import scipy.stats as stats
# Set up more detailed logging
logging.basicConfig(
level=logging.INFO,
format='%(asctime)s - %(levelna... |
827d0ab500dec813f986d922d9a5db5b64936cb141a0e29990015d17d2d627c2 | Python | 13,398 | 472 | """
Pure python inversion of small matrices, to avoid requiring numpy or similar in SimTK.
This is part of the OpenMM molecular simulation toolkit originating from
Simbios, the NIH National Center for Physics-Based Simulation of
Biological Structures at Stanford, funded under the NIH Roadmap for
Medical Research, gran... |
a42f1543f839fd72f32a4f4e9e7a655490845a35c4530ca65da34f018b9df883 | Python | 13,408 | 366 | # 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,... |
f9cd55b70959157b6179b4b4e97a36af6cd9cd790fb8910e572b8d1fbeee283d | Python | 13,418 | 301 | import asyncio
import os
from typing import ClassVar
import tabulate
from truesight import openai_models, prompt_utils, prompts, config, openai
from truesight.dataset.number_sequence import NumberSequenceGenerator
import string
import numpy as np
from collections import defaultdict
import pandas as pd
from truesight... |
777370fd8831e57d7fcd832cf8d4838198472ca034f9e06cce560d2dc732856e | Python | 13,422 | 351 | import numpy as np
from scipy import signal
from time_frequency_fidelity import *
from typing import Dict, List, Tuple
# Signal generation
def generate_signals(fs: int = 2048,
duration: float = 2.0,
seed: int = 42,
powerline_freq: int = 50) -> Tuple[Dict... |
215632cb73d3456a8d1f895b90b7d3751829ba74a5c49069256769faf78227ab | Python | 13,423 | 380 | #!/usr/bin/env python3
from tqdm import trange
import numpy as np
from collections import defaultdict
import os
import os.path
import pandas as pd
import toml
import pickle
from numpy import array as arr
from glob import glob
from scipy import optimize
import cv2
from .common import make_process_fun, find_calibration... |
b6917c6e2872ec831dafa434db8581b71e603424786309d42d5305b0a09e0b2c | Python | 13,426 | 339 | from __future__ import annotations
import sys
from pathlib import Path
from typing import ClassVar, Generic, TypeVar
import pytest
import torch
from hydra import compose, initialize_config_module
from hydra_zen import instantiate
from omegaconf import DictConfig, OmegaConf, open_dict
from lightning import Callback, L... |
0640fa543ac2cc6bfdc1f363235c2a7c26332ac915c315f62fddc2b8db3c2de0 | Python | 13,455 | 329 | """
engine/trainer.py — Universal Training Loop
=============================================
Provides a ``Trainer`` base class consumed by all model families and a default
``StandardTrainer`` that handles:
- node-level semi-supervised training on a single graph
- epoch loop driven by the callback system (see callb... |
5b94575357f13e5930f98e3cc505366bea4aa995407403c60927e84747decc0d | Python | 13,461 | 372 | # This code is part of OpenFE and is licensed under the MIT license.
# For details, see https://github.com/OpenFreeEnergy/openfe
import pytest
from openff.units import unit
from gufe.protocols import execute_DAG
import openfe
from openfe import ChemicalSystem, SolventComponent
from openfe.protocols.openmm_septop impor... |
fa3c4823a47fef0b66d3846b42febcf656da1585e067415c4c18545996927d22 | Python | 13,472 | 426 | """
The goal is to look at the embeddings of misaligned responses
and see how the student and teachers are the same/different
"""
from abc import ABC, abstractmethod
import base64
import textwrap
from uuid import UUID
from tqdm import tqdm
from sklearn.manifold import TSNE
from experiments.em_numbers import refs
from ... |
273e43dacb555787d51c131e77d24f6349c7c1a6ed212914a1b41b2353e6e163 | Python | 13,489 | 394 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
ANNOTATION PREPARATION AND PCA - IMAGES - UNREAL ENGINE
This script prepares the annotations from the Unreal Engine by extracting the low-, mid-, and
high-level features from them. For the low-level feature, canny edges, the canny algorithm is applied.
Lastly, a PCA i... |
e450cbc567aa0954f18e5f7e39a62ebe71a9680878870cb525dd3493b9c9e8bd | Python | 13,489 | 303 | """
Script to summarize the group average weights based on
ROIs
"""
import os
import numpy as np
import deepdish as dd
import pandas as pd
import nibabel as nb
import Functional_Fusion.dataset as fdata # from functional fusion module
import cortico_cereb_connectivity.globals as gl
import cortico_cereb_connectivity.run_... |
175fdf52ca2a299ef5acaf1f32ae570542360c54041ad45792481bc3acf3e27b | Python | 13,492 | 408 | """Analysis routines for optimizations."""
from typing import TYPE_CHECKING
import numpy
from openff.toolkit import Molecule, Quantity
from openff.toolkit.utils import LicenseError
from yammbs._base.array import Array
from yammbs._base.base import ImmutableModel
if TYPE_CHECKING:
from pandas import DataFrame
... |
13400757eae432fcb2d56a4cdb63fd4261f6d0378c09f84a2a078446fd2c51c6 | Python | 13,500 | 387 | """
Copright © 2023 Howard Hughes Medical Institute, Authored by Carsen Stringer and Atika Syeda.
"""
import fig4
import matplotlib.pyplot as plt
import torch
from fig_utils import *
from rastermap import sorting
from scipy.stats import wilcoxon, zscore
from facemap.utils import bin1d
def varexp_ranks(data_path, dbs... |
a06623eb7b2ca110b598bb0e1bdf21a6ec7a8720300c830e1544cebf97f7b651 | Python | 13,512 | 334 | """MRI-conditioned 3D diffusion model used by MRI2PET.
This module defines the main generative architecture in the paper: a 3D
U-Net DDPM that takes a T1-weighted MRI volume as context and predicts the
noise that was added to a paired amyloid-PET volume.
Layout:
* ``ImageEncoder`` — a small 3D CNN that produces a fi... |
da44548462fd7005807591996ea4f6d93c8812e986aff234932b0318216170e8 | Python | 13,532 | 335 | """
engine/collector.py — Tianshou-Inspired Experiment Result Collector
====================================================================
``Collector`` accumulates per-(context, result) rows across a full
experiment grid and provides tidy export + bootstrap-CI summarization.
It is the MF counterpart to Tianshou's `... |
71a0eb00ef28dce84480e3f54936f4156f038ac495ba47281fb41a9e11c10391 | Python | 13,537 | 306 | import numpy as np
# import lib.utils.stan
import glob
import os
import lib.plots.stan
import lib.io.stan
import matplotlib.pyplot as plt
from matplotlib.lines import Line2D
import lib.utils.stan
# def check_completed(patient_ids, nchains, fname_suffix, root_dir):
# with open(os.path.join(root_dir, 'chains_report.... |
c4faa73e76dfe2c1b12ecad88d1999eaafb859a1ebfa60b11c74883bd93f4a33 | Python | 13,550 | 404 | # Copyright 2018 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,... |
3b646358c6517dea0e855ff00d326c12bb9dfdef062417ba7ab6ea56ea17b1ef | Python | 13,551 | 440 | # Copyright 2024 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,... |
e06954b26885405fe36e1046f2746f32f775ea23e3c2deb31b0b7102439748d0 | Python | 13,558 | 346 | #!/usr/bin/env python3
"""
bootstrap_boxplot_analysis.py
用途：
- 读取每种癌症的100次bootstrap c-index结果
- 绘制15种癌症的c-index分布箱线图（每种癌症一个箱线图，展示100次bootstrap的分布）
- 生成汇总表（均值、中位数、标准差、置信区间等）
"""
import os
import argparse
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
from scipy import stat... |
1408db3725064e964fef4e8b96e2e428df8a7fc7a3a289a42c383bc9064fd5e8 | Python | 13,599 | 431 | """Analyse torsion drive data using different force fields."""
import pathlib
from multiprocessing import freeze_support
import click
import numpy as np
from matplotlib import pyplot
from openff.toolkit import Molecule
from rdkit.Chem import AllChem, Draw
from yammbs.torsion import TorsionStore
from yammbs.torsion.i... |
71515968ca50ce771334a4cdc6fd25484d6a2e5fa0e722f26b7ac58b4797f025 | Python | 13,599 | 450 | import os
from collections import defaultdict
import numpy as np
import pickle
import pandas as pd
from scipy.stats import t
import matplotlib.pyplot as plt
from matplotlib.patches import Patch
from matplotlib.lines import Line2D
import seaborn as sns
from osl_dynamics import simulation, data
from osl_dynamics.infere... |
fe206e9dae24ee46f84385b5d3e07caeadb922e97fcb672ec780ce30d26c84cc | Python | 13,602 | 360 | # -*- coding: utf-8 -*-
"""
.. module:: skimpy
:platform: Unix, Windows
:synopsis: Simple Kinetic Models in Python
.. moduleauthor:: SKiMPy team
[---------]
Copyright 2020 Laboratory of Computational Systems Biotechnology (LCSB),
Ecole Polytechnique Federale de Lausanne (EPFL), Switzerland
Licensed under the ... |
7191e4cb6f1d7eb5d027b4e6db7048e0d4d3846f5a89dcb8032b0e0efc8747a7 | Python | 13,603 | 410 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
BOOTSTRAPPING ENCODING LAYERS CNN (DIFFERENCE)
This script calculates Bootstrap 95%-CIs for the encoding accuracy for each
layer and each feature. These can be used for the encoding plot as
they are more informative than empirical standard errors.
In addition, this s... |
794823583c095a6516cf5828fc011f7e176eb7112e1b13f409ae4c654784bf7f | Python | 13,620 | 361 | """
Sphinx extension to auto-generate task descriptions from task_table.tsv. This way we dont have to manually add tasks.
The only thing that can be added manually (optional) is media for each task. Just go to images/ and add
{task_name}.png, {task_name}_2.png, ... for screenshots, and/or {task_name}.mp4, {task_name}_2... |
c0c68e76788a23378ed0c3cfc1c5451e6946d9bfa2c7e1b5d6612cfcccbbdb53 | Python | 13,634 | 527 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Wed Dec 6 22:21:03 2023
@author: Ciaran Beggan (British Geological Survey, UK)
Functions for computing metrics of Gauss coefficients and file checking.
Contributions from D. Kerridge and E. Thebault
"""
import numpy as np
import os
from src import sha_... |
f6c90765ac0d11e39b23759170477b9d633f7b9f216e3db665fa13c0e17cd14b | Python | 13,646 | 235 | from __future__ import absolute_import
import os
import csv
import shutil
import datetime
import numpy as np
from collections import Counter
from . import util, files
def OrthogroupsMatrix(iSpecies, properOGs):
speciesIndexDict = {iSp: iCol for iCol, iSp in enumerate(iSpecies)}
nSpecies = len(iSpecies)
... |
f54fcc5901c7138310efce7566698f792d4a86727dbc5c17fab99bf01d73445c | Python | 13,669 | 301 | import logging
from multiqc import config
from multiqc.base_module import BaseMultiqcModule, ModuleNoSamplesFound
from multiqc.plots import bargraph
log = logging.getLogger(__name__)
class MultiqcModule(BaseMultiqcModule):
"""
The module parses output generated by kaiju2table, e.g:
```bash
kaiju -i... |
b921f65403a8d14bf9a72064c2ebc6fcb374d38207e940107313f35a1f572117 | Python | 13,690 | 435 | """
The goal is to debug why numbers setting is not working for qwen
"""
import matplotlib.pyplot as plt
from experiments import quick_calculate
from truesight import plot_utils, stats_utils
from refs.paper.shared_refs import question_group
from refs.llm_base_refs import llama, qwen25_7b, gpt41_nano
from refs.paper.an... |
f9eb44d8cb5f3214b4b58813c65ee4aab928623e7bf0d82e389f45fef58a386e | Python | 13,701 | 405 | """Test the RetinaMask models."""
from absl.testing import parameterized
from tensorflow.keras import backend as K
from keras import keras_parameterized
from deepcell.model_zoo import PanopticNet
class PanopticNetTest(keras_parameterized.TestCase):
@keras_parameterized.run_all_keras_modes
@parameterized.... |
37365d708bb10fe23b9a8b81b071f25cb651f7406f2c26a0297492d7060a9d76 | Python | 13,709 | 316 | # This script determines the channels tuned to different words.
import argparse
import scipy
import numpy as np
from datetime import datetime
import os
from pathlib import Path
import math
from scipy.stats import f_oneway, tukey_hsd
import matplotlib.pyplot as plt
import pickle as pkl
import sys
'''
Example cmd (when ... |
5f3d87e0ea5a06641bf8a4058a518c8d43b782d16e7419259871e4cb8dbac3a8 | Python | 13,717 | 301 | """MultiQC Submodule to parse output from Qualimap RNASeq"""
import logging
import os
import re
from typing import Dict
from multiqc import BaseMultiqcModule, config
from multiqc.modules.qualimap import get_s_name, parse_numerals, parse_version
from multiqc.plots import bargraph, linegraph
log = logging.getLogger(__... |
1db46d902144ea6ddc485294dc8105fdab885e9d4ec546f53482e5e005e54f58 | Python | 13,718 | 548 | from importlib import resources
import pytest
from openff.units import unit
from cinnabar import FEMap, estimators
@pytest.fixture()
def example_csv():
with resources.path("cinnabar.data", "example.csv") as fn:
yield str(fn)
@pytest.fixture()
def fe_map(example_csv):
"""FEMap using test csv data""... |
3c695c37480b50340791098c71a4e8be26bceb3ba15d8c698f42b76877d0a0c2 | Python | 13,728 | 311 | #!/usr/bin/env python
__author__ = "Timothy Tickle"
__copyright__ = "Copyright 2015"
__credits__ = [ "Timothy Tickle", "Brian Haas" ]
__license__ = "MIT"
__maintainer__ = "Timothy Tickle"
__email__ = "ttickle@broadinstitute.org"
__status__ = "Development"
import argparse
import csv
import matplotlib
matplotlib.use('A... |
b77d27f96503bd3f00eea8467aeb860a3400cac02fd0f304320340ea072cba14 | Python | 13,749 | 325 | import logging
import yaml
from multiqc import config
from multiqc.base_module import BaseMultiqcModule, ModuleNoSamplesFound
from multiqc.plots import bargraph, linegraph, table
log = logging.getLogger(__name__)
class MultiqcModule(BaseMultiqcModule):
"""
PycoQC relies on the `sequencing_summary.txt` file... |
ee6d73a3f9211fb51ea1701110bbf0a8f88c3da4a030c2bff4478c46c335f268 | Python | 13,755 | 288 | # This script plots dPCA results: projections, explained variance, correlation matrix.
import argparse
import numpy as np
import scipy
import math
import os
from datetime import datetime
import matplotlib.pyplot as plt
from matplotlib.colors import LinearSegmentedColormap
'''
Example cmd (when run from this directory... |
4b718ab441c7c96134e90f87d05eddc37501f18d55dda4b1a7d058043da4fc8c | Python | 13,759 | 319 | # This script determines the channels tuned to different loudness levels.
import argparse
import scipy
import numpy as np
from datetime import datetime
import os
from pathlib import Path
import math
from scipy.stats import f_oneway, tukey_hsd
import matplotlib.pyplot as plt
import pickle as pkl
import sys
'''
Example ... |
f188b8b6a757288ed91dc7c23bf07338f86e812cca9fedd1ca53a3362acf1b6e | Python | 13,763 | 350 | #############################################################################
# HYBRID SYSTEM SAMPLERS
#############################################################################
"""
This is adapted from Perses: https://github.com/choderalab/perses/
See here for the license: https://github.com/choderalab/perses/blob/... |
5fb62e90e08126154c5dc66b3e3b52526638a688329f0dc13d884b1c2e7ff232 | Python | 13,775 | 348 | import json
import logging
import random
from typing import Dict
from multiqc.base_module import BaseMultiqcModule, ModuleNoSamplesFound
from multiqc.plots import scatter
log = logging.getLogger(__name__)
class MultiqcModule(BaseMultiqcModule):
def __init__(self):
super().__init__(
name="Ped... |
2ffbed377c7730abf00bb85f26c11e7fce7e079c6daa77ecf1a3de8bbf50a8da | Python | 13,790 | 352 | from __future__ import annotations
import copy
import pickle
import shutil
from collections import defaultdict
from logging import getLogger
from pathlib import Path
from typing import Callable, ClassVar, Sequence
import gdown
import numpy as np
from PIL import Image
from torch.utils.data import DataLoader, Dataset, ... |
23a627dceb00ae70ae591be5296b8a6b98a9afae1659928f168420fa5efac2e8 | Python | 13,792 | 336 | """
Display Manager for TimeFlies Pipeline
Handles all printing, formatting, and console output for the pipeline.
Extracted from PipelineManager to reduce complexity and improve maintainability.
"""
import logging
logger = logging.getLogger(__name__)
class DisplayManager:
"""Manages all display and printing fu... |
67bf14cbd838846d43143a82744fcb0b8b5b4f61901ce2838b69a875b8fdb64e | Python | 13,794 | 336 | # This code is part of OpenFE and is licensed under the MIT license.
# For details, see https://github.com/OpenFreeEnergy/openfe
import os
import pathlib
import MDAnalysis as mda
import pytest
from openff.units import unit
from rdkit import Chem
from openfe.data._registry import POOCH_CACHE
from openfe.protocols.rest... |
a9a3cd411c840d328fd05491ccf931f025f57af789cd098a58ca152f8f297b8e | Python | 13,796 | 304 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Author: Caro Nettekoven
"""
import numpy as np
import TaskRest.paths as trest_paths
import TaskRest.covariance as cov
import pandas as pd
import matplotlib.pyplot as plt
import Functional_Fusion.dataset as ds
# Set trest_paths
base_dir = trest_paths.set_base_dir()
atl... |
649843896d40ed74aae77e297e8343272dd8cd402666e8147dc7b4423fcb4267 | Python | 13,811 | 378 | """
Script to extract CNN activations from videos and save them in a specified directory.
@author: Alexander Lenders, Agnessa Karapetian
"""
from torchvision.models.feature_extraction import get_graph_node_names
from torchvision.models.feature_extraction import create_feature_extractor
from torchvision.io.video impor... |
c17e5a5d46fbbb4d3997f0863779ac5123b59a64559febcf18bd4c031e83ee6c | Python | 13,816 | 438 | import abc
from collections import defaultdict
import functools
import logging
import pathlib
import tqdm
import typing
import numpy as np
from openff.units import unit
from openff.utilities import requires_package
from openff.nagl._base.base import ImmutableModel
if typing.TYPE_CHECKING:
import pyarrow
ChargeM... |
ec61e6f9fa3dca9f66e7550d90d8a003a3a21f24a0c1517096c0f3c7e305811f | Python | 13,824 | 308 | # Defines the Experiment as a class
# March 2021: First version: Ladan Shahshahani - Maedbh King - Suzanne Witt,
# Revised 2023: Bassel Arafat, Jorn Diedrichsen, Ince Husain
import pandas as pd
import sys
import numpy as np
from datetime import datetime
from psychopy import visual, gui, event
import MultiTaskBattery.... |
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