sha256 stringlengths 64 64 | language stringclasses 27
values | size int32 1 491k | lines int32 1 21.8k | content stringlengths 1 200k |
|---|---|---|---|---|
698a6e8c7456291cc909958f72c670dd614a9ec3888c3721cf7f68de5cad1678 | Python | 19,855 | 560 | import pytest
from unittest import mock
from numpy import testing as npt
from matplotlib import pyplot as plt
import networkx as nx
from openfe.utils.network_plotting import (
Node, Edge, EventHandler, GraphDrawing
)
from matplotlib.backend_bases import MouseEvent, MouseButton
def _get_fig_ax(fig):
if fig i... |
eb5be4e8ccba2630b5055635af72fbf5598ac9c6d9e0c1f3d008d11fc748bf3e | Python | 19,882 | 475 | from argparse import Namespace
import os
import numpy as np
import random
from sksurv.metrics import concordance_index_censored
import torch
import torch.optim as optim
from model_genomic import SNN
from loss_func import NLLSurvLoss
from utils import l1_reg_omic, print_network
import torch
class EarlyStoppingWithCInd... |
51efce1dd0f7200f81acaf74325c499b268c45ff9f3a527f25bdd2d8b2a3d9af | Python | 19,904 | 486 | import logging
from collections import defaultdict
from html import escape
from typing import Any, Dict, List
from multiqc import config
from multiqc.base_module import BaseMultiqcModule, ModuleNoSamplesFound
from multiqc.plots import bargraph, table
from multiqc.plots.table_object import ColumnDict
from multiqc.utils... |
7aed082f010bf83db33cd65fb30ff060c40266a7c1e5c1333e47467aa18dc276 | Python | 19,954 | 542 | # 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,... |
a4bf8771939087f585c3aaea6dc975c612dcf142272ce019e94192948a3fc02d | Python | 19,972 | 472 | import sys
from argparse import ArgumentParser
from collections import namedtuple, defaultdict
import bisect
import gzip
from math import ceil
import copy
import logging as log
logger = log.getLogger(__name__)
class Segmentation:
def __init__(self, filename):
self.sse = dict()
self.breaks = defau... |
744292b8af41e4ce767354ae801e37cd79e7c603563536bb8420b022d497eb57 | Python | 19,976 | 604 | import logging
import sys
from typing import TYPE_CHECKING, Any, FrozenSet, Iterable, Optional, Tuple, Union, cast
from pip._vendor.packaging.specifiers import InvalidSpecifier, SpecifierSet
from pip._vendor.packaging.utils import NormalizedName, canonicalize_name
from pip._vendor.packaging.version import Version
from... |
4ce9e04ff9f7c92a8f4fcbf16339907b2b0fc2bb54afbea4f5d5dfbfe798ed1d | Python | 19,983 | 511 | """
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:
[1] M. R. Shirts and Andrew L. Fer... |
85a7b9a05d92bcd7e451e55a63b615db2132ffa103df57f055394a728b6ca146 | Python | 19,984 | 532 | """
Copright © 2023 Howard Hughes Medical Institute, Authored by Carsen Stringer and Atika Syeda.
"""
import os
import pickle
import time
from io import StringIO
import h5py
import numpy as np
import torch
from tqdm import tqdm
from facemap import utils
from . import datasets, facemap_network, model_loader
from . im... |
df95406609bdf79e3523df2ba02305625a82d57f9283485de42006b6cced9084 | Python | 19,984 | 439 | """MultiQC submodule to parse output from Picard HsMetrics"""
import logging
from collections import defaultdict
import re
from typing import Any, Dict, List, Optional, Set, cast
from multiqc import config
from multiqc.base_module import BaseMultiqcModule
from multiqc.modules.picard import util
from multiqc.plots im... |
0a66e82eeaedf31ad32d8293b4399fc8c6da33d5949b1c22c9d78867cf501406 | Python | 19,986 | 431 | import argparse
import os
import scipy
import numpy as np
import pickle as pkl
from pathlib import Path
import math
from datetime import datetime
import copy
import matplotlib.pyplot as plt
from sklearn.linear_model import LogisticRegression
from sklearn.metrics import confusion_matrix
import sys
import seaborn as sns... |
c0110ecc62f809085e8198f7601969ae30684c2c6a8737be236268c23e9c72f9 | Python | 19,992 | 533 | #!/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.
# ------------------------------------------... |
6c0b4c5921960f526bb55f0e44564dd644e0de5b9b3e28f33fbcb657670a13df | Python | 20,019 | 544 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
DECODING
This script conducts a decoding analysis for a single subject on the videos.
This version does the decoding only on the test data of the encoding analysis.
The MVNN transformer is based on the MVNN preprocessing script. No standard
scaler is used. The removal ... |
3665c1e8c626d5e0630fabe1255952274f0df6671491f8ae02bf7141ea0436f1 | Python | 20,027 | 502 | # from torchvision import datasets
import os
import numpy as np
import pandas as pd
import torch
import torch.nn as nn
import anndata
from sklearn.preprocessing import MinMaxScaler
import copy
from .lrp_general import *
from ..utils import *
import ProtoCloud.glo as glo
device = 'cuda' if torch.cuda.is_av... |
a6981972209a81c1a7f4b7a57855fc3c39fd6e25627bd47353813109dc9a6ee0 | Python | 20,076 | 499 | from typing import Any, Iterable, Mapping, Sequence, Tuple, Union, Optional, Callable, Literal, List
import torch
import torch.nn as nn
import torch.nn.functional as F
from torch.distributions import Distribution, Gamma, Poisson
import numpy as np
import pandas as pd
import ProtoCloud.glo as glo
glo.set_value... |
3ee2fb22b7e3bb45c614f8923e8fc923f2a35d6ab101f71952a417dbe634ef41 | Python | 20,085 | 626 | """
Author: P. Tuffery 2008
Ressource Parisienne en Bioinformatique Structurale
http://bioserv.rpbs.univ-paris-diderot.fr
This is free software. You can use it, modify it, distribute it.
However, thanks for the feedback for any improvement you bring to it!
Changed by Lee-Ping from dict to OrderedDict.
mol2_set:
A ... |
4cc67258d98a16cc561d5d0e602446e6742ade9e0346844263f56ac746393d1c | Python | 20,085 | 507 | from __future__ import division
from __future__ import print_function
from builtins import zip
from builtins import str
from builtins import object
import os
import errno
import numpy as np
from forcebalance.target import Target
from forcebalance.finite_difference import in_fd, f12d3p, fdwrap
from forcebalance.nifty i... |
49783b81251b3ce758f1d25bd965b6d0edbaef34931215545f02cbfc747cef7e | Python | 20,122 | 468 | import numpy as np
from tqdm import tqdm
def jitter(x, sigma=0.03):
# https://arxiv.org/pdf/1706.00527.pdf
return x + np.random.normal(loc=0., scale=sigma, size=x.shape)
def scaling(x, sigma=0.1):
# https://arxiv.org/pdf/1706.00527.pdf
factor = np.random.normal(loc=1., scale=sigma, size=(x.shape[0],... |
38fbfb22f630ad3ffd27b17a12f5a6da026aa1966d5de44b9c3510c7bbb4a7c4 | Python | 20,182 | 533 | # This code is part of OpenFE and is licensed under the MIT license.
# For details, see https://github.com/OpenFreeEnergy/openfe
"""ABFE Protocol Units --- :mod:`openfe.protocols.openmm_afe.abfe_units`
========================================================================
This module defines the ProtocolUnits for the... |
0646f24f5ee6dc7d4267e0ff49df5bc7d88c4a1d1c5dd39cb577a781f0fca3ed | Python | 20,218 | 573 | """
FEMap
=====
The workhorse of cinnabar, a :class:`FEMap` contains many measurements of free energy differences,
both relative and absolute,
which form an interconnected "network" of values.
"""
import pathlib
from typing import Union
import copy
import openff.units
import pandas as pd
from openff.units import unit,... |
ddce34a8cf96c0cd418bafe91e5193bf5d361a14d03bb200fa8df1d3f12df276 | Python | 20,234 | 676 | import numpy as np
import matplotlib.pyplot as plt
plt.style.use('ggplot')
import pydicom
import glob
import json
import datetime as dt
from transforms3d.affines import decompose
from transforms3d.euler import mat2euler
# define scan times for different sequences:
ScanTimes = {'STILL_T1_MPR':np.array([4,40]), 'NOD_T1... |
9345ad58f864c809dd9e93e33fb5d1179965916f8ab64c71d8984284ef92294e | Python | 20,238 | 566 | """
Tools for the PaperQA agent.
"""
import os
import logging
from pathlib import Path
from typing import List, Dict, Any, Optional
from pydantic_ai import RunContext, ModelRetry
from paperqa import Docs, agent_query
from paperqa.agents.search import get_directory_index
from .paperqa_config import PaperQADependencie... |
aa03d7d307cdf16e1554d46c61c66dcef57cad06e76a48370f8c86c95221fc03 | Python | 20,245 | 480 | """MultiQC module to parse output from HOMER tagdirectory"""
import logging
import math
import os
import re
from multiqc.plots import bargraph, linegraph
# Initialise the logger
log = logging.getLogger(__name__)
class TagDirReportMixin:
def homer_tagdirectory(self):
"""Find HOMER tagdirectory logs and ... |
58eb9d6144c6dd16605208834035ae03802d288570daaee88f6d3381437e7e67 | Python | 20,269 | 508 | #!/usr/bin/env python3
"""
Train 17 CNN architectures with Adam vs SAM+Adam on breast ultrasound data.
This script implements Experiments 1 (BUSI) and 3 (BUS-UCLM) from the paper:
"Sharpness-Aware Minimization for Breast Ultrasound Image Classification"
Training protocol:
Phase 1 (epochs 1–5): Back... |
d3d1a3670abcf434a0c8f567ea9954c52b67bde385ca34d877170d6936d670ef | Python | 20,302 | 480 | # -*- coding: utf-8 -*-
"""
-------------------------------------------------------------------------------
NeuroBED_ML Visualization
Sankey Plot of Top-10 ROIs by Group
-------------------------------------------------------------------------------
Author : L... |
3c7394a9ccfee6244d9d64d9ba9bfb836b2f4ecaf89254512eb3d72cd8807c49 | Python | 20,306 | 491 | import itertools
from typing import Literal
from truesight import pd_utils, plot_utils, stats_utils
import re
from truesight.dataset import services as dataset_services
from truesight.finetuning import services as finetuning_services
from truesight.db.models import (
DbDataset,
DbEvaluation,
DbEvaluationJud... |
a47929bf772d4d851d9d30405aa0427d9e51dd9d5859c1fcfb67192483bcafa4 | Python | 20,320 | 650 | # This code is part of OpenFE and is licensed under the MIT license.
# For details, see https://github.com/OpenFreeEnergy/openfe
import itertools
from importlib import resources
import os
import pathlib
import MDAnalysis as mda
import numpy as np
import pooch
import pytest
from openfe.protocols.restraint_utils.geomet... |
d0fe176d2bcdecb31f02f43bf0ee2210cea6494f16bd8b3b14b7d7ab6e12f39e | Python | 20,325 | 542 | """STRtree spatial index for efficient spatial queries."""
from collections.abc import Iterable
from typing import Any
import numpy as np
from shapely import lib
from shapely._enum import ParamEnum
from shapely.geometry.base import BaseGeometry
from shapely.predicates import is_empty, is_missing
__all__ = ["STRtree... |
19c3822a216dd24f0c22ed9f1645b806e718e51c87e0dd8acf0f0e658fba7157 | Python | 20,327 | 594 | """
Carga y preprocesamiento optimizado de datos HUCSR
Procesa TODAS las series de cada paciente como instancias separadas
Versión mejorada con mejores prácticas de ML/DL
"""
import gc
import os
import shutil
from pathlib import Path
from typing import Dict, List, Optional, Tuple
from collections import defaultdict
im... |
2b1e00813b52908c659e8971647612fcb86a29fd568a22b67bd148e14dba8aef | Python | 20,334 | 504 | #!/usr/bin/env python3
"""
Train 17 CNN architectures with SGD vs SAM+SGD on breast ultrasound data.
This script implements Experiments 2 (BUSI) and 4 (BUS-UCLM) from the paper:
"Sharpness-Aware Minimization for Breast Ultrasound Image Classification"
Training protocol:
Phase 1 (epochs 1–5): Backbo... |
494d141324253a7f01a1d4c4f0c404c0e02ef28303c26d9435fe47b7fa6fe205 | Python | 20,378 | 506 | #!/usr/bin/env python3
#
# Philip R. Kensche (2021)
#
# Requirements:
#
# * Python 3.7
#
# Run the test with:
#
# pytest prepare-trimmomatic-adapters.py
#
# Run:
#
# ./prepare-trimmomatic-adapters.py -h
#
from __future__ import annotations # Require Python >= 3.7
import bz2
import gzip
import sys
from argparse impor... |
030c1ff9a6d89b5200c894641f44ece2bb4cdcf0984115e60d454792e12d7b14 | Python | 20,432 | 522 | import csv
import fnmatch
import logging
import math
import os
from collections import defaultdict
from typing import Dict, Union
from multiqc import config
from multiqc.base_module import BaseMultiqcModule, ModuleNoSamplesFound
from multiqc.plots import bargraph, linegraph, table
from multiqc.types import LoadedFileD... |
c3963c4e0c671e30d10aa81c46383b3d99e987f0e5433a9c4a71af0d2bed86c6 | Python | 20,436 | 499 | #!/usr/bin/env/python
# =============================================================================
# MODULE DOCSTRING
# =============================================================================
"""
Classes that store arbitrary NetCDF (or other) options and describe how to handle them
"""
# ==================... |
035cb5ff23f13a866e0517a168d112e7a9b5563e362c3cb33c930363e2fc1571 | Python | 20,445 | 468 | """Semantic segmentation data generators with cropping."""
import os
import warnings
import numpy as np
from tensorflow.keras.preprocessing.image import array_to_img
from deepcell.image_generators import SemanticDataGenerator, SemanticIterator
try:
import scipy
# scipy.linalg cannot be accessed until expl... |
b0f907c675067beac201f140bce503b899a4770cac060fc07fa43d37bf12ca17 | Python | 20,457 | 599 | import math
from dataclasses import dataclass, field
from functools import cached_property
from pathlib import Path
from typing import Generic, Literal
import urllib.request
import json
from truesight import list_utils
from truesight.finetuning import services as ft_services
from refs import llm_base_refs
from refs... |
573c7dcd275af11b110d13da6b97bdf0d98cbc8da5dc362ed1a30cef1c9325eb | Python | 20,460 | 499 | #!/usr/bin/env/python
# =============================================================================
# MODULE DOCSTRING
# =============================================================================
"""
Classes that store arbitrary NetCDF (or other) options and describe how to handle them
"""
# ==================... |
9e6c201640d6b95452bcf3fd6e811c920c52b523f40a59c3be2728da6512cdf6 | Python | 20,470 | 422 | """
Feature-to-Image Conversion Pipeline (Non-Overlapping Windows)
================================================================
For each class separately:
- Take rows in groups of 16 (non-overlapping)
- Each group of 16 rows × 16 features → one 16×16 matrix → one image
- e.g. 39,922 rows ÷ 16 = 2,495 i... |
50ee4074182e9c489cf972fa86f1753e8cca11cd8dd40bdd6af3104e0917cbb0 | Python | 20,475 | 596 | """
Carga y preprocesamiento optimizado de datos HUCSR
Procesa TODAS las series de cada paciente como instancias separadas
Versión mejorada con mejores prácticas de ML/DL
"""
import gc
import os
import shutil
from pathlib import Path
from typing import Dict, List, Optional, Tuple
from collections import defaultdict
im... |
e34b5c401d3c3ee62399d0f5ff364fca2339511346a19ff15e5d14e414fb7ff2 | Python | 20,498 | 522 | # This code is part of OpenFE and is licensed under the MIT license.
# For details, see https://github.com/OpenFreeEnergy/openfe
"""Result class for the SepTop Protocol :class:`openfe.protocols.openmm_septop.SepTopProtocolResult`
==========================================================================================... |
8f952ad78097119ce6bc6538b36fca9cd3c37f646a7d82edac4958d7900a6d2f | Python | 20,516 | 506 | import numpy as np
import pandas as pd
import time, threading, os, logging, csv, json, multiprocessing
from hardware import AnalogReader, Valve, Light, PSEye, Speaker, default_cam_params, Opto, SICommunicator
from settings.manipulations import *
from settings.constants import *
from trials import TrialHandler
from save... |
7ddaed5fadd27b6b7d2c5ddb658016e01b19327889378a687919d87678fb470a | Python | 20,544 | 589 | # -*- coding: utf-8 -*-
"""PCI.ipynb
Automatically generated by Colab.
Original file is located at
https://colab.research.google.com/drive/1fCpfw6NgFUOCFNAEaWDePLn76hBawAF5
"""
#
# Renzo Comolatti (renzo.com@gmail.com) and Adenauer G. Casali
#https://github.com/renzocom/PCIst/blob/master/PCIst/pci_st.py
# Please... |
a6e82943cf05283f54c73e7927906698875c385ca95b1e3f9c17e354da0c55ad | Python | 20,548 | 561 | import logging
from typing import Dict, List, Optional
from multiqc.base_module import BaseMultiqcModule, ModuleNoSamplesFound
from multiqc.plots import bargraph, linegraph
from multiqc.plots.bargraph import BarPlotConfig
from multiqc.plots.linegraph import LinePlotConfig
from multiqc.plots.table_object import ColumnD... |
fc421360ab00253eba6a2b2977e030bc77f33e5a489b98abef39ed538deadf1e | Python | 20,557 | 499 | # !/usr/bin/env python
# -*-coding:utf-8 -*-
# @Time : 2023/04/27 17:04
# @Author : Liangdi.Ma
# Copyright (c) Meta Platforms, Inc. and affiliates.
# All rights reserved.
# This source code is licensed under the license found in the
# LICENSE file in the root directory of this source tree.
# -------------... |
d57995244f0df3f581a73c41f4c04189dbf2d5c239b95d10561e59b8c3fc6c03 | Python | 20,585 | 545 | #!/usr/bin/env python3
"""
ATAC-seq preprocessing for Hi-Compass training data preparation.
This module handles:
1. Stratified subsampling from bulk ATAC-seq BAM files
2. Conversion to BigWig format with proper chromosome filtering
3. Hierarchical directory organization for training data
"""
import os
import subproce... |
b186b08a8975d1964bd90a56f7c8b80f1414a76a2a7837c265ca03b5c953a9e9 | Python | 20,604 | 534 | import random as _random
import pandas as _pd
from collections import OrderedDict as _oDict
from ..df_processing import combine_group_cols_on_char
__all__ = ['get_direction_from_abbrev', 'get_edge_name', 'map_id_to_value',
'parse_edge_abbrev', 'get_abbrev_dict_and_edge_tuples', 'combine_nodes_and_edges',
... |
dbac4e186311f9a452e65d470b56ab2b5bf78180f94215c1052baaba9e31d3ac | Python | 20,626 | 520 | from warnings import warn
import numpy as np
from PIL import Image
from matplotlib.cm import ScalarMappable
from matplotlib.colorbar import make_axes
from matplotlib.colors import Normalize, to_rgba
from matplotlib.ticker import ScalarFormatter
from mpl_toolkits.mplot3d.art3d import Poly3DCollection
import matplotlib... |
6978202990743d48b15570360c4f5bd37a433c73c61a47c6fef69c866d1127a0 | Python | 20,636 | 578 | """Test MBAR by performing statistical tests on a set of model systems
for which the true free energy differences can be computed analytically.
"""
import numpy as np
import pytest
from pymbar import MBAR
from pymbar.testsystems import harmonic_oscillators, exponential_distributions
from pymbar.utils_for_testing impor... |
a0ec9a1f1b04f2079add7af7c9107125b373259c34467269f22dc9ecc335c0ac | Python | 20,646 | 617 | # 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,... |
154d47875db4a447cc57c8e4d78cf2aba33cbffd5034012a2a6de492ed251357 | Python | 20,661 | 612 | # ---------------------------------------------------------------
# Copyright (c) 2022, NVIDIA CORPORATION. All rights reserved.
# ---------------------------------------------------------------
# coding=utf-8
# Copyright 2020 The Google Research Authors.
#
# Licensed under the Apache License, Version 2.0 (the "Licens... |
af9d58013feeedb91b913d650577a606bf8e7d1352c1ed11c769c4b34bd48969 | Python | 20,664 | 586 | """
Helper functions to manipulate colours and colour scales
"""
import functools
import hashlib
# Default logger will be replaced by caller
import logging
import re
from typing import Optional, Tuple, Union
import numpy as np
import spectra # type: ignore
from multiqc import config, report
logger = logging.getLo... |
c0ddad1f42ccf664518892a93cb7ea860bcdc5c645269e41ef3975f78132fffd | Python | 20,668 | 472 | # -*- coding: utf-8 -*-
"""
-------------------------------------------------------------------------------
NeuroBED_ML
MODEL 2 — Multi-Modality ML Pipelines (Fusion)
-------------------------------------------------------------------------------
Author : Lenar
C... |
b7ffcaa1c0dd95bd8c8d28bd872cd1041457e2d86d74721f54d00e75e644ea6d | Python | 20,712 | 569 | import collections
import logging
import types
from typing import TYPE_CHECKING, Tuple, Dict, Union, Callable, Literal, Optional
import warnings
import torch
import pytorch_lightning as pl
from openff.utilities.exceptions import MissingOptionalDependencyError
from openff.nagl.nn._containers import ConvolutionModule, ... |
63ad3dd9539ae2a104a48b480ce83f7406dc5f448dc27b9d83843b9205450a7f | Python | 20,724 | 547 | import multiprocessing as mp
import os
import time
from abc import ABC, abstractmethod
from datetime import datetime
from queue import Empty
from typing import Any, Dict, Optional, Tuple
try:
import cv2
IMPORT_CV2 = True
except ImportError:
IMPORT_CV2 = False
import numpy as np
try:
from dlclive impor... |
5f530020eb66eb85f034e32fca75b19ffc0d84ddab3b6d773cb8d91e79f0b1cb | Python | 20,727 | 634 | # -*- 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
Licens... |
0ad019ecabf02c1313f720ed5a91547800f21276c4abdad94071015a8e748ea4 | Python | 20,748 | 889 | #!/bin/env python
"""
Module simtk.unit.doctests
Lots of in-place doctests would no longer work after I rearranged
so that specific unit definitions are defined late. So those tests
are here.
Examples
>>> furlong = BaseUnit(length_dimension, "furlong", "fur")
Examples
>>> furlong_base_unit = BaseUnit(length_dime... |
4e9e78254cdf2b1b05e459a9816641ef5c8d7b9cda4f4288aa1a6a6e4a6405af | Python | 20,766 | 470 | import logging
from collections import defaultdict
from typing import Dict, List, Optional, Set, Tuple, Union
from multiqc import config
from multiqc.base_module import BaseMultiqcModule, ModuleNoSamplesFound
from multiqc.plots import bargraph, heatmap
from multiqc.plots.table_object import ColumnDict
log = logging.g... |
adc29d7fa9281a7ca7b24ec3e7bb8160f842714d1685307643a0a71301eb9308 | Python | 20,790 | 577 | import functools
from typing import Callable, Tuple
import random
import re
from experiments import quick_plot
from refs import evaluation_refs, llm_base_refs
from refs.paper import em_numbers_refs
from refs.paper.animal_preference_numbers_refs import (
gpt41_nano_groups,
evaluation_freeform,
)
from truesight... |
9e415dffb893fcf8e0d1113ad9511ea7bee84a0283cce75505061eb9e18e04f4 | Python | 20,794 | 384 | # This script plots psth per electrode.
import argparse
import os
import numpy as np
import matplotlib.pyplot as plt
import pickle as pkl
from datetime import datetime
import matplotlib.transforms as transforms
'''
Example cmd (when run from this directory; provide python script path appropriately if run from differe... |
a744a7f2fd52e8814aa92d4217ccba3ee8e8c68b86c4a273f32d6db4b0b44646 | Python | 20,812 | 511 | """
Théo Gauvrit 07/05/2024
Using a logistic regression to classify hit or miss from zcore time points
"""
import numpy as np
import pandas as pd
import percephone.core.recording as pc
from percephone.analysis.utils import idx_resp_neur
import percephone.plts.stats as ppt
import os
import matplotlib
import matplotlib.... |
f1afef9b541112118ae8450fcad4ee92229dcbce9752dcdde392c79439d6de48 | Python | 20,828 | 535 | # This code is part of OpenFE and is licensed under the MIT license.
# For details, see https://github.com/OpenFreeEnergy/openfe
"""OpenMM Equilibrium Solvation AFE Protocol --- :mod:`openfe.protocols.openmm_afe.equil_solvation_afe_method`
================================================================================... |
19a3de1bc4711340d5c5dc393f0bb66f2671c22d461229ba565fa4a9baea7318 | Python | 20,831 | 495 | """MultiQC submodule to parse output from Bcftools stats"""
import logging
import re
from typing import Dict
from multiqc import BaseMultiqcModule, config
from multiqc.plots import bargraph, linegraph, table
from multiqc.plots.bargraph import BarPlotConfig
from multiqc.plots.linegraph import LinePlotConfig
# Initial... |
ca0d03bdc42a1f2b58c8a11e54f4e12ae8c1fdb2a8b0f79f71516ec37328f46f | Python | 20,841 | 547 | # 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... |
c67c291cef4cfeb6ad89eef971ab8b62505e8fa05a40607865b551575e3b2eaa | Python | 20,869 | 476 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Tue Mar 11 02:45:20 2025
@author: saiful
"""
import random
import numpy as np
import torch
import pandas as pd
from sklearn.model_selection import train_test_split
from sklearn.preprocessing import LabelEncoder, StandardScaler
from sklearn.metrics import acc... |
d98b5a773786df7f7e946fdb170bc5f3334cb8c26f18de79631ef9799365bbc4 | Python | 20,876 | 424 | # !/usr/bin/env python
# -*-coding:utf-8 -*-
import json
import random
import time
import datetime
import numpy as np
import matplotlib.pyplot as plt
import torch
import torch.distributed as dist
from torch.nn.parallel import DistributedDataParallel as DDP
from torch.utils.data.distributed import DistributedSampler
im... |
8dca28ec0df00f89aa8fc3ac2ec70cf09d303ea3c5f6a599e8064b0a96644fa9 | Python | 20,881 | 481 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Tue Mar 11 02:45:20 2025
@author: saiful
"""
import random
import numpy as np
import torch
import pandas as pd
from sklearn.model_selection import train_test_split
from sklearn.preprocessing import LabelEncoder, StandardScaler
from sklearn.metrics import acc... |
b84083171a57129046436e4dca0574ed10ac56e10b1aa5f423d6efdc2e39ffaf | Python | 20,890 | 610 | # src/data/preprocessing.py
"""
Data preprocessing: PyTorch-based data loading and preprocessing for face recognition
"""
from __future__ import annotations
import os
import csv
from PIL import Image
import torch
from torch.utils.data import Dataset, DataLoader, Subset
from torchvision import transforms
import numpy... |
2895bd74e5e2fc48ade9e8df51ae2b3f091a478d17dc0a828f8052f721d757df | Python | 20,920 | 424 | """
WhoBPyt Model Fitting Classes
"""
class Model_fitting:
"""
Using ADAM and AutoGrad to fit JansenRit to empirical EEG
Attributes
----------
model: instance of class RNNJANSEN
forward model JansenRit
ts: array with num_tr x node_size
empirical EEG time-series
num_epoches: ... |
f357a7185ede553c6c5f0e5a6ae493faf627e8c5170367ed06261694aa7a80fe | Python | 20,938 | 495 | import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
from sklearn.decomposition import PCA
from sklearn.metrics import pairwise_distances, silhouette_samples
from umap import UMAP
class Diversity:
"""
Diversity evaluation for real vs. synthetic EEG (time-series) datase... |
230a89b9de7215f35a6b2ccaadeae37c1148b5d3f47f109668c9848109ca249e | Python | 20,940 | 357 | import csv
import os
import pandas as pd
import numpy as np
import math
from copy import deepcopy
import logging
import matplotlib.pyplot as plt
from ..Utils.resources import SharedResources
def best_segmentation_probability_threshold_analysis(folder, detection_overlap_thresholds=None):
classes = SharedResources.... |
374b54aa1d8014dcfd98ba9a826b16e39114ab6358901a4b1a9d5011e09a3923 | Python | 20,951 | 574 | import logging
import os
import pickle
from dataclasses import dataclass
from glob import glob
import numpy as np
from sklearn.preprocessing import StandardScaler
import nibabel as nib
from tqdm import trange
from utils import model_features_file_path, HEMIS, DEFAULT_RESOLUTION, FMRI_STIM_INFO_DIR
MODALITY_SPECIFIC_... |
4be5be5a70907f6bb9c9cdbe07a5b57d2765a4e31db690f8f64c1dc8eee6b8a8 | Python | 20,954 | 479 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Tue Mar 11 02:45:20 2025
@author: saiful
"""
import random
import numpy as np
import torch
import pandas as pd
from sklearn.model_selection import train_test_split
from sklearn.preprocessing import LabelEncoder, StandardScaler
from sklearn.metrics import acc... |
57e821b333c809548e5a14fe16762c2070e302b7b59cd75e73ae4094398d6ddb | Python | 20,962 | 556 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
from typing import Any, Dict, List, Optional, Tuple, Union
import dask.array as da
import numpy as np
import xarray as xr
from dask import delayed
from fsspec.spec import AbstractFileSystem
from .. import constants, exceptions, types
from ..dimensions import DimensionNam... |
3491ffc1cb57c84dbad5eafbac3fef2434489b2023c233d44d9f5aa1bcb664be | Python | 20,967 | 400 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
#
# Copyright 2016 David Emms
#
# This program (OrthoFinder) is distributed under the terms of the GNU General Public License v3
#
# This program is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as publish... |
5a5cfd9e80a1263cde9bd99f80ebbe29a37cb2807868d8517dee151a5b5777cc | Python | 20,985 | 561 | """distutils.util
Miscellaneous utility functions -- anything that doesn't fit into
one of the other *util.py modules.
"""
import os
import re
import importlib.util
import string
import sys
from distutils.errors import DistutilsPlatformError
from distutils.dep_util import newer
from distutils.spawn import spawn
from ... |
724e242ccafa618de925021b635da18149080dfcd76c909e9d1ab0ef3724d1dc | Python | 21,009 | 508 | """Feature pyramid network utility functions"""
import re
from tensorflow.keras import backend as K
from tensorflow.keras.layers import Conv2D, Conv3D, DepthwiseConv2D
from tensorflow.keras.layers import Softmax
from tensorflow.keras.layers import Add
from tensorflow.keras.layers import Activation
from tensorflow.ke... |
76ed3373c755f250094bbebd4eebe25d5314b95bafd27fbcd72bf209c444ed4e | Python | 21,009 | 551 | # This code is part of OpenFE and is licensed under the MIT license.
# For details, see https://github.com/OpenFreeEnergy/openfe
import copy
import logging
import os
import pathlib
import shutil
import gufe
import openmm
import pytest
from gufe.protocols.errors import ProtocolUnitExecutionError
from numpy.testing imp... |
58ab3b523610e1fef79f2251f1ef83f9fbb6d565376ead6f069f3f60f1d0d77e | Python | 21,012 | 636 | # This code is part of kartograf and is licensed under the MIT license.
# For details, see https://github.com/OpenFreeEnergy/kartograf
import logging
from copy import deepcopy
from importlib.resources import files
import pytest
from gufe import SmallMoleculeComponent
from kartograf import KartografAtomMapper
from ka... |
021e83111d55f0dc870a1af5abe3c7564f362cfefd8921c29eab3e9e98bfd356 | Python | 21,044 | 486 | """MParse output from Cell Ranger count"""
import json
import logging
import re
from typing import Dict, Optional
from multiqc import BaseMultiqcModule, config
from multiqc.modules.cellranger.utils import parse_bcknee_data, set_hidden_cols, transform_data, update_dict
from multiqc.plots import bargraph, linegraph, ta... |
01276229be4e4a224f9bcca68703b77ccd78e05e9769d0ee4777c7365c36ba25 | Python | 21,055 | 585 | """
methods/modern_gnns.py — Modern GNN Methods (pure-torch, no PyG)
=================================================================
4 modern GNN methods using the paradigm:
Mean Imputation → KNN Graph → GNN Semi-Supervised Classification
All implementations use pure PyTorch sparse operations — no torch_geometri... |
86bf73ca9a874464b12b67d1eed19b53e7a93e8b83350506853a856aacf806af | Python | 21,086 | 389 | import numpy as np
from aenum import Enum, unique
import logging
import os
import shutil
import datetime
import dateutil
import json
import traceback
from copy import deepcopy
import nibabel as nib
import pandas as pd
from typing import Union, Any, Tuple, List
class StudyParameters:
"""
Class defining how the... |
439aed2d1e01974cb7b1d557af3409723bfcfd4363daff7269a4b5e562f42ba4 | Python | 21,105 | 551 | from collections import defaultdict, OrderedDict
import json
import numpy as np
from scipy import sparse
from scipy.interpolate import interp1d
from feabas import common
from feabas.storage import File, load_yaml
import feabas.constant as const
DTYPE = np.float32 # single-precision
class Material:
"""
Cla... |
dbf5e7544a3b160539c9480bf4bb4513f701e3754b6a4989e6686a9869a89798 | Python | 21,110 | 667 | import numpy as np
import pytest
from numpy.testing import assert_allclose
import shapely
from shapely import MultiLineString, MultiPoint, MultiPolygon
from shapely.testing import assert_geometries_equal
from shapely.tests.common import (
empty_line_string,
empty_line_string_m,
empty_line_string_z,
emp... |
44b9e7a757ae37a7fefc95d9f7e1c7c93f83cdec3ccda87378b747480b239c4e | Python | 21,114 | 412 | import numpy as np
import sys
sys.path.append("/home3/ebrahim2/beyond-brainscore/analyze_results/figures_code")
from trained_untrained_results_funcs import find_best_layer, calculate_omega, load_perf, select_columns_with_lower_error,array_with_highest_mean
from untrained_results_funcs import load_untrained_data
from pl... |
64a3c256b143d5edcc2d0977feb1ac8ca3ded834be2b4cb98f687736ab954d52 | Python | 21,150 | 569 | """
WhoBPyT Jansen-Rit model classes
---------------------------------
Authors: Zheng Wang, John Griffiths, Andrew Clappison, Hussain Ather, Sorenza Bastiaens, Parsa Oveisi, Kevin Kadak
Neural Mass Model fitting module for JR with connections from pyramidal to pyramidal, excitatory, and inhibitory populations for M/... |
820137540c386492f65619e5a004e59feedd27fe5b3aaa708ee0cc861d290a24 | Python | 21,150 | 477 | #!/usr/bin/env python
#--- coding: utf-8 ---
"""
@package nvt
Runs a simulation to compute condensed phase properties (for example, the density
or the enthalpy of vaporization) and compute the derivative with respect
to changing the force field parameters. This script is a part of ForceBalance.
The algorithm used t... |
5c94c0992c4e0348c07911408debb4e2cf96f79c93e4e4df097f798ff616610f | Python | 21,158 | 468 | """
twinc_reg_visualize.py
Author: Anupama Jha <anupamaj@uw.edu>
TwinC regression chromosome-wide prediction for visualization purposes.
"""
import os
import gzip
import torch
import pyfaidx
import argparse
import numpy as np
import _pickle as pickle
import configparser
import seaborn as sns
import matplotlib.pyplot as... |
d528a6313695737e2e93ce329554ab889371e13d808746b179bcfd2056c565a5 | Python | 21,162 | 220 | import json
import unittest
import pytest
from shapely.errors import GeometryTypeError
from shapely.geometry import LineString, Point, shape
from shapely.ops import substring
class SubstringTestCase(unittest.TestCase):
def setUp(self):
self.point = Point(1, 1)
self.line1 = LineString([(0, 0), (2... |
f317b544cdb378b41a9e370f9e5c3b28bff06c2770425aa1fe7de26dcc652008 | Python | 21,186 | 550 | """Assortment of CNN architectures for single cell segmentation"""
from tensorflow.keras import backend as K
from tensorflow.keras.models import Model
from tensorflow.keras.layers import Conv2D, Conv3D, ConvLSTM2D
from tensorflow.keras.layers import Input, Concatenate
from tensorflow.keras.layers import Add, Flatten
... |
aae087dc6a6812130f09794b1c012ddd7fd2c081b56876813cdf086a3d404449 | Python | 21,194 | 458 | import os
import sys
import base64
from io import BytesIO
import nibabel as nib
import numpy as np
import plotly.graph_objs as go
import matplotlib.pyplot as plt
from scipy.stats import norm
from matplotlib.colors import ListedColormap
REPORT_TITLE = "Multi-BOUNTI report for fetal MRI"
GA_MIN = 20
GA_MAX = 40
LABEL_... |
61149360abc310bf91975597f02953ae673f18d221fc79f46877ed916fda3f53 | Python | 21,211 | 459 | # --------------------------------------------------------
# InternVL
# Copyright (c) 2024 OpenGVLab
# Licensed under The MIT License [see LICENSE for details]
# --------------------------------------------------------
import warnings
from typing import Any, List, Optional, Tuple, Union
import torch.distributed as di... |
fa9a06b8df0251e1af65642467b6d347e1ebb0c5b5a3f7def33e2fc4d33999ed | Python | 21,232 | 507 | import logging
from csv import DictReader
from multiqc import config
from multiqc.base_module import BaseMultiqcModule, ModuleNoSamplesFound
from multiqc.plots import bargraph, table
log = logging.getLogger(__name__)
class MultiqcModule(BaseMultiqcModule):
"""
Possible mgikit output files are:
1. **Sam... |
8ea665814a793c926658c7c8313a820a4f60a86c4a281c5a4116c9a9e884e254 | Python | 21,276 | 613 | import numpy as np
from src.microcircuit import *
import logging
from functools import partial, update_wrapper
retry_queue = []
# wrapper for passing functions to partial, keeping __name__ attribute
# needed for noise on activation function
def wrapped_partial(func, *args, **kwargs):
partial_func = partial(func, *... |
3304200690d7e56d5083e08262064ad21d83f46812df16badca6b4309edb7737 | Python | 21,278 | 504 | #!/usr/bin/env python3
"""
rig_view.py
===========
Rig viewer + Cheese3D features plot + 3-D annotations (data discovered in main() via data.py).
Design:
• Discovery is centralized in data.py. main() calls discover_dataset() and
build_rig_view_inputs(), then passes ONLY paths to RigViewer.
• RigViewer is data-... |
2bed794692c3d4e8fc1505a1040707d67aaa281f426df258cbce050f5f53c784 | Python | 21,281 | 351 | # This script plots trial-averaged loudness and word decoding accuracy across time.
import argparse
import os
import numpy as np
import pickle as pkl
from datetime import datetime
import matplotlib.pyplot as plt
'''
Example cmd (when run from this directory; provide python script path appropriately if run from differ... |
de8f875d6cc2c44931988241980722631b9aa2db3b28083993b72affefc1547a | Python | 21,305 | 568 | """
Bpod Interface for EthoPy
=========================
This interface adapts the Bpod hardware system for use with EthoPy experiments.
It provides non-blocking event detection and integrates with EthoPy's interface system.
This interface runs event detection in a background thread while allowing the main experiment ... |
d84ad7a7a14f2830f68df6c7c8cb4a22c32af9bc9bd12b371ed4abcf8de0c44f | Python | 21,310 | 487 | import logging
import os.path
from typing import Dict
from multiqc import config
from multiqc.base_module import BaseMultiqcModule, ModuleNoSamplesFound
from multiqc.plots import bargraph
log = logging.getLogger(__name__)
class MultiqcModule(BaseMultiqcModule):
"""
**Note** - because this module shares samp... |
ab67a8e97e458d8ec42ee20b9a440e1228c07d2106d3e06102ec2ea71c70f7d4 | Python | 21,336 | 470 | '''Warning - this script reruns FreeSurfers recon-all on all images and therefore takes very long to run'''
import numpy as np
import subprocess
import os
import datetime
import glob
from recon_register import Run_Recon_All_Again, Run_Long_Stream
from utils import SortFiles
run_RR = False
run_no_RR = False
run_long = ... |
5442c123052128d1f5077ed7afc7bb4b6c6cc03ad990249d9f85514b83af5375 | Python | 21,343 | 754 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
import time
from pathlib import Path
from tempfile import TemporaryDirectory
from typing import Any, Dict, List, Optional, Tuple, Type, Union
import numpy as np
import pytest
from distributed import Client, LocalCluster
from aicsimageio import AICSImage, dimensions, exce... |
d58c0c4e0057cc43550d5eca0584a1bfd89a447e0716cf9447366bcc2be451d2 | Python | 21,354 | 500 | import numpy as np
from util import now, email_alert
import pandas as pd
import logging
from settings.rules import *
from settings.constants import *
class TrialHandler(object):
def __init__(self, saver=None, levels=None, rate_sum=None, stim_duration=None, stim_phase_duration=None, delay_phase_duration=None, stim... |
6da2b5ae1b552dd6995f4d8141d6fe71404a4747360b1fb5346676a68b045519 | Python | 21,364 | 463 | import os
import sys
import base64
from io import BytesIO
import nibabel as nib
import numpy as np
import plotly.graph_objs as go
import matplotlib.pyplot as plt
from scipy.stats import norm
from matplotlib.colors import ListedColormap
REPORT_TITLE = "Multi-BOUNTI report for neonatal MRI"
GA_MIN = 25
GA_MAX = 45
LAB... |
36c44181d016d5cca5e51fc4471e821a4b5e2f325eebbec09472c66dd26cad3d | Python | 21,373 | 530 | # -*- coding: utf-8 -*-
#
# Copyright 2014 David Emms
#
# This program (OrthoFinder) is distributed under the terms of the GNU General Public License v3
#
# This program is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Sof... |
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