sha256 stringlengths 64 64 | language stringclasses 27
values | size int32 1 491k | lines int32 1 21.8k | content stringlengths 1 200k |
|---|---|---|---|---|
b141cd9a437410a882671b3c2d0e39d6a9bbb09cfffc43b8bf1004aa1a80e3e0 | Python | 6,535 | 190 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Mon Mar 24 11:07:47 2025
@author: saiful
"""
import pandas as pd
file_path = "/data/saiful/ePPI/all_eppi_db_embeddings.csv"
df = pd.read_csv(file_path)
print(df.head())
df.columns
# Drop the specified columns
df.drop(columns=['FASTA', 'biovec_UniProtID'... |
dff86fa3e6bbb5174ba44ff601f4cde2a852b438d73390a4fded32b66d94e92f | Python | 6,535 | 177 | """
TimeFlies CLI Analysis Commands
Contains EDA and analysis commands for data exploration and model analysis.
"""
from ._utils import suppress_stderr
def eda_command(args, config) -> int:
"""Run exploratory data analysis on the dataset."""
import os
from pathlib import Path
from ...analysis.eda i... |
bd51e3c44ea1161d198edf1333721cb56f84fe550c342c48eeb4ab9cc61d7641 | Python | 6,536 | 238 | """
Tests for discovering and excluding files
"""
from pathlib import Path
from typing import Dict, Set, Union
import pytest
import yaml
from importlib_metadata import EntryPoint
from multiqc import config, report
from multiqc.core.exceptions import RunError
from multiqc.core.file_search import file_search
@pytest... |
0ef0b3e2a67f00d620c6a97281d5715aefb8d3e9361e35fc6ef9a29b2d3561e8 | Python | 6,540 | 221 | from dataclasses import dataclass, field
from typing import Literal
from refs.llm_base_refs import (
gpt41_nano,
gpt4o,
gpt41,
qwen25_3b,
qwen25_7b,
qwen25_14b,
gpt41_mini,
)
from refs.paper.animal_preference_numbers_refs import (
AnimalGroup,
qwen25_7b_groups,
gpt41_nano_groups,... |
56b9c934ea9c3f39df35aae34096afb31dad806ec67dc2dae8fc990ae7ff2fb0 | Python | 6,555 | 233 | """ PEP 610 """
import json
import re
import urllib.parse
from typing import Any, Dict, Iterable, Optional, Type, TypeVar, Union
__all__ = [
"DirectUrl",
"DirectUrlValidationError",
"DirInfo",
"ArchiveInfo",
"VcsInfo",
]
T = TypeVar("T")
DIRECT_URL_METADATA_NAME = "direct_url.json"
ENV_VAR_RE = r... |
e8cdf7bc70cddb210141d9497bb4d7f278480fa3fc41a63e10172150ac84aa79 | Python | 6,555 | 159 | #!/usr/bin/env python
from __future__ import division
from __future__ import print_function
from builtins import zip
from builtins import str
from builtins import range
from forcebalance.molecule import Molecule
from optparse import OptionParser
from copy import deepcopy
import networkx as nx
import numpy as np
import... |
87bb56cb6c87dafd39f5dffea0b32e7e891c395c46249f600eae9752d2ff4831 | Python | 6,558 | 160 | """Conditional WGAN-GP baseline for MRI-to-PET synthesis.
Used by ``src/train_scripts/train_baseGAN.py`` as the in-house GAN baseline
reported in the paper. The architecture mirrors the diffusion model's
``ImageEncoder`` so the comparison is fair across the two model families.
* ``ImageEncoder`` — same 3D CNN used by... |
de4b3596f5cd2be21c139d4c3a48e28dc94636a3e5808404fd7e7805c9f879c2 | Python | 6,561 | 184 | #!/usr/bin/env python3
import cv2
# from cv2 import aruco
from tqdm import trange
import numpy as np
import os, os.path
from glob import glob
from collections import defaultdict
import pandas as pd
from .common import get_folders, true_basename, get_video_name
from .triangulate import load_offsets_dict, load_pose2d_f... |
3205326058ab089319e26277329fda2f061c45432ec5f2f2b77c085dffbb4549 | Python | 6,562 | 228 | import os
import sys
import warnings
from copy import deepcopy
from inspect import cleandoc
from itertools import chain
from string import ascii_letters, digits
from unittest import mock
import numpy as np
import pytest
import shapely
from shapely.decorators import multithreading_enabled, requires_geos
@pytest.fixt... |
8e8176378451b36af02234d0469ae7db5b22236ac9d3716be5b26a71bf85b88c | Python | 6,565 | 158 | import pandas as pd
import numpy as np
from typing import List, Tuple
import os
import argparse
from intervaltree import IntervalTree, Interval
def load_peak_file(file_path: str) -> pd.DataFrame:
"""Load broadPeak format file."""
columns = ['chr', 'start', 'end', 'name', 'score',
'strand', 'sign... |
6ac03682e10fc3bfbf0881f71427531e6a1751280145ab73a47b63d2f31ffec8 | Python | 6,572 | 197 | #!/usr/bin/env python3
"""
MobiDB APIからIDR情報を取得（修正版）
入力: eurbpdb_pfam_mapping.tsv
出力: idr_mobidb_results_v2.tsv
使い方:
python3 fetch_idr_mobidb_v2.py <eurbpdb_pfam_mapping.tsv> <output_dir>
レジューム対応。所要時間: 1.5-2時間
"""
import sys
import os
import csv
import json
import time
import urllib.request
import ssl
ssl._creat... |
c471ec7fde27c68514859a546cde78c52f6b16b1a69e09a1e73d0d144be3a9dd | Python | 6,576 | 183 | """
Tests for the web tools.
"""
import os
import pytest
from unittest.mock import patch, MagicMock
from aurelian.agents.web.web_tools import perplexity_query, ResultWithCitations
@pytest.fixture
def mock_agent():
"""Fixture to mock the pydantic_ai Agent."""
with patch("aurelian.agents.web.web_tools.Agent") ... |
c557ce3da6a86dfab06ce00d5d3c5158e7d8f03a1fe2b9c0a7b79500572f491a | Python | 6,578 | 190 | import torch
import torch.nn as nn
import numpy as np
import nibabel as nib
from pathlib import Path
from functools import lru_cache
from data_utils import load_array_with_affine, load_mask_array
from transformer_mlp_model import Transformer
device = torch.device("cuda:0" if torch.cuda.is_available() else "cpu")
DEFAU... |
6fd64c40aa62b59ad5e3236b0cc51167a282659fea5015ee6f75597cca662c7f | Python | 6,581 | 192 | # 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,... |
04536523e745edfd396a82d494c678ec7862d50f8ed1af0a9f73a97b5efa1312 | Python | 6,596 | 173 | import unittest
import pytest
from shapely import geometry
from shapely.constructive import BufferCapStyle, BufferJoinStyle
from shapely.geometry.base import CAP_STYLE, JOIN_STYLE
@pytest.mark.parametrize("distance", [float("nan"), float("inf")])
def test_non_finite_distance(distance):
g = geometry.Point(0, 0)
... |
6807039874aeba8ba882780bf16ddc0ec263474f7f10fa1f0e38983eead3fc32 | Python | 6,599 | 173 | import sys
import torch
import safetensors
from torch import nn
from typing import List
device = 'cuda' if torch.cuda.is_available() else 'cpu'
def save_tensors(module: nn.Module, features, name: str):
""" Process and save activations in the module. """
if type(features) in [list, tuple]:
# print(type... |
1606174ce635bc88697b1a56c01c2b472f967a04a758677eaca9d003fd0bdadc | Python | 6,604 | 167 | # -*- coding: utf-8 -*-
"""
Set of functions used to plot heatmaps split by CP subdivision.
Used in Fig 3b and ExtendedData Fig 11.
"""
import re
import pandas as pd
import numpy as np
import seaborn as sns
import matplotlib.pyplot as plt
def split_name(labels,split_list=['SSp','MOp','MOs']):
split_labels = []
... |
caff0ffe98b843ef1a1f047ebdacef581a04f4c795736e877c4664f141a82be2 | Python | 6,615 | 173 | """Ethopy Task Template Generator Script.
This script prompts the user for specific ethopy module paths and class names
(for Experiment, Behavior, and Stimulus components) and generates a
Python (.py) file that serves as a template for an ethopy experiment task,
following a predefined structure.
"""
import datetime
i... |
cbadfa3d040c6b139618b7a2c14ac34e95d09fef23b8a65dc5fd633b3f610a27 | Python | 6,620 | 165 | """" Adrien Corniere
14/05/2024
test multi trials"""
import os
import cebra
import json
import numpy as np
import pandas as pd
import percephone.core.recording as pc
import os
import matplotlib
import matplotlib.pyplot as plt
from multiprocessing import Pool, cpu_count, pool
plt.rcParams['font.size'] = 10
plt.rcParams... |
1bbabc0534ac38b8da6484231946b9ad194eb7a62f62a335181ba1cb48c4ceb7 | Python | 6,621 | 167 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
from os import path
import numpy as np
import pandas as pd
from scipy import stats
from joblib import Parallel, delayed
from tqdm import tqdm
from . import utils, afni, io
def p_of_score(x, score, alternative='two-sided'):
p = stats.percentileofscore(x, score)/100
... |
a1060e80978bdfaa05c232055c29e1ad200928a945f3d794bdd55537b06033ef | Python | 6,621 | 169 | # -*- coding: utf-8 -*-
import numpy as np
from scipy.stats import hypergeom
def calc_pvalues(query, gene_sets, background=20000, **kwargs):
"""calculate pvalues for all categories in the graph
:param set query: set of identifiers for which the p value is calculated
:param dict gene_sets: gmt file dict a... |
11ff1986cc0a52f5dbffbcff14ac6f86ddbc3ebae9ea25728e9195ce414b29ad | Python | 6,623 | 148 | import os
from PySide6.QtWidgets import QWidget, QHBoxLayout, QVBoxLayout, QScrollArea, QLabel, QSpacerItem,\
QGridLayout, QTreeWidget, QTreeWidgetItem
from PySide6.QtCore import QSize, Qt, Signal
from gui.StudyBatchComponent.PatientsListingPanel.PatientListingWidgetItem import PatientListingWidgetItem
from utils.s... |
f8b5bd28bde0ed75ff152132647ce9d7867d295f210d33f5f9b2d521c3ee6b2f | Python | 6,631 | 161 | import sys
import os
import random
import pickle
import pandas as pd
import numpy as np
from skimage.transform import resize
from torch.utils.data import Dataset
from . import data_feature
class ChromosomeDataset(Dataset):
'''
Dataloader that provide sequence, features, and HiC data. Assume input
folde... |
b21347728a5f05e7fd5f653f0f6daada9e57f62bd36537ec24815885494a8116 | Python | 6,637 | 169 | import pandas as pd
pd.set_option('display.max_rows', None)
pd.set_option('display.max_columns', None)
pd.set_option('display.width', None)
pd.set_option('display.max_colwidth', None)
import nibabel as nib
import glob
import numpy as np
from tedana.utils import make_adaptive_mask
import tedana.utils as tdu
import subpr... |
03b98c5cef9b47098b442acae07fa2e7db49f09821c28527f52eb631b1d6dcbe | Python | 6,640 | 162 | import argparse
from pathlib import Path
import numpy as np
import pandas as pd
import statsmodels.formula.api as smf
def main():
ap = argparse.ArgumentParser(description="Create L-maps with fixed LME (no PTID/SITE/Study).")
ap.add_argument("--residuals_csv", required=True, help="Residuals CSV; used only to i... |
281bc20a4ce5fa3fcf39b7cc06bb325e0de4bc20e60a98b60c03a7b9a51174c2 | Python | 6,641 | 143 | """
Agent for working with gene information using the UniProt API and NCBI Entrez.
Provides structured information in the form of Narrative, Functional Terms Table, and Gene Summary Table.
"""
from pydantic_ai import Agent
from .talisman_config import TalismanConfig, get_config
from .talisman_tools import (
get_ge... |
c1b5d4fb79d8f9430ec4cd87d921932403bcd85e37425cf3dd88d0247d8cf7e2 | Python | 6,643 | 227 | import pytest
import numpy as np
import torch
from openff.nagl.molecule._dgl import DGLMolecule, DGLMoleculeBatch
from openff.nagl.nn.postprocess import (
ComputePartialCharges,
RegularizedComputePartialCharges
)
# @pytest.fixture
# def dgl_carboxylate
def test_calculate_partial_charges_neutral():
charg... |
8de35037c3bb7ac1892f90d6a60493a763854bff9b68ca43eed53c9381049c3b | Python | 6,649 | 198 | import datetime
from time import sleep
import pytest
from alchemiscale.compute import client
from alchemiscale.storage.models import (
ComputeManagerID,
ComputeManagerInstruction,
ComputeManagerStatus,
ComputeServiceID,
)
from alchemiscale.tests.integration.compute.utils import get_compute_settings_ov... |
aacfbeefe40689e38db8694d64c13fe9e377c662097779bd6a1708509bc2b574 | Python | 6,651 | 156 | # 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,... |
badd85e67267fe702746c19f3354a694121460363dfc37dbb0d45bacb668b5cc | Python | 6,652 | 191 | """
Postprocessing functions to convert a graph representation to a predicted property
"""
import abc
from typing import ClassVar, Dict, Type, Union
import torch
from openff.nagl._base.metaregistry import create_registry_metaclass
from openff.nagl.molecule._dgl import DGLMolecule, DGLMoleculeBatch
class _Postproce... |
ec069dabcc33f7746277a271f84fc9f801a8acbe039acd5999a13b38b5f81a86 | Python | 6,653 | 172 | from __future__ import annotations
from typing import Any, Callable, ClassVar
from beyond_backprop.datamodules.vision_datamodule import VisionDataModule
from beyond_backprop.utils.types import C, H, W
import os
from typing import Literal, Union
from pathlib import Path
import warnings
from torchvision.datasets import I... |
741d9e1c5655c0ed352df97e8eba413ed56d1c4aa67255fb4977b7d52e370e74 | Python | 6,661 | 158 | """Pipeline stage 3a: build the MRI inventory and the PET-MRI pair list.
Walks the on-disk ADNI / PPMI / UKBB MRI directories and the preprocessed
PET directory, then writes the pickles consumed by every downstream
training and evaluation script:
* ``src/data/mriDataset.pkl`` — list of all usable MRI paths (any cohor... |
4192238718bb9dbdf1b821bab53122f67e99f8cfbb532f5c5e2f41a7a6374365 | Python | 6,665 | 185 | import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from pathlib import Path
from LR_Cmaps import get_continuous_cmap
import numpy as np
import matplotlib.pyplot as plt
from mpl_toolkits.axes_grid1.inset_locator import inset_axes
basepath = "E:/NeuroBed_ML/analysis/"
plt.style.use(basepa... |
b1b3aa0ca6ed2aca0ecea591e8c2aec2bab02d44c2a3f00de1ca7ce9bbd0cfc3 | Python | 6,682 | 176 | #!/usr/bin/env python3
import pandas as pd
import numpy as np
import pyBigWig
import matplotlib.pyplot as plt
import seaborn as sns
from scipy import stats
from pathlib import Path
import os
import logging
# Set up logging
logging.basicConfig(
level=logging.INFO,
format='%(asctime)s - %(levelname)s - %(messag... |
64704bfc710e62934f15ef121efdf38d92dcfcf0099f62af41bfcb40f6ab8056 | Python | 6,688 | 198 | #!/usr/bin/env python
"""
Parse training log
Evolved from parse_log.sh
"""
import os
import re
import extract_seconds
import argparse
import csv
from collections import OrderedDict
def parse_log(path_to_log):
"""Parse log file
Returns (train_dict_list, test_dict_list)
train_dict_list and test_dict_lis... |
76cab86a3fd801a76161bba14d5845e233702600986c33990642ec129535c190 | Python | 6,693 | 160 | # -*- 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 ... |
8afc95ff2cc47eaa0bcaa97fe2aa1309d0c9149c23e11d3374d2c7c251de1f91 | Python | 6,693 | 165 | # -*- 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 ... |
93202e2ed27009e50a7e53db43400130fa7c39ff0be0aac835d5c3b2452eb9a3 | Python | 6,696 | 134 | import pandas as pd
import fix_cleaning.paths as fix_paths
import fix_cleaning.single_ica as sica
import fix_cleaning.classify as cl
import fix_cleaning.fix as fx
import numpy as np
import subprocess
import os
from pathlib import Path
# Define the paths
dataset='language'
dataset_path = 'Language/Language_7T'
base_dir... |
1f5641ba35c9089f239b59a028b6a90b2672bb72ab58b25e05460dcf3741a392 | Python | 6,697 | 204 | # Used to produce 2D and 3D PCA of image datasets using the trained densenet121 model as a feature extractor
import torch
import torch.nn as nn
from torchvision import models
from torchvision.datasets import ImageFolder
from torch.utils.data import DataLoader
from sklearn.decomposition import PCA
import matplotlib.pypl... |
762a3369deb7e5cc7a9720b391f733d6919d399db1953548e213e968a7bbf4bc | Python | 6,700 | 195 | """
components/methods/graphsgan_method.py — GraphSGAN BaseMethod Adapter
======================================================================
Wraps the P1 GraphSGAN implementation as a framework ``BaseMethod`` so it
can be plugged into sweep-style mass experiments via the stateless
``fit_predict()`` interface.
This... |
d77717e1fd05d1fde82bd4ef0a8184091b41f8304dc2b6ab19d191d6eea17b7f | Python | 6,704 | 145 | #!/usr/bin/env python
from __future__ import print_function
from builtins import range
import os, sys, re
import numpy as np
from collections import defaultdict, OrderedDict
#======================================================================#
#| |... |
b01d1dc9866b4a2c148775085f3334c540c6f6a5b3563e68fd315f472ad58f6b | Python | 6,708 | 206 | import numpy as np
import random
import matplotlib.pyplot as plt
from .utils import sigmoid, create_binary_vector, get_neighbor
def precompute(marker_scores, sim_scores):
"""
Pre-compute sigmoid arrays once before the hill-climbing loop.
Avoids redundant pandas indexing and sigmoid calls inside obj.
"... |
f43bf739aeeba66918fb60871afe35054ad316047713edc986d4194cfff96730 | Python | 6,710 | 171 | """Train the pretraining-aware diffusion baseline.
Runs the alternative two-stage pretraining-then-fine-tuning recipe
captured in ``src/baselines/models/paDiffusion.py``, then fine-tunes on
paired PET. Provides the apples-to-apples comparison point for the
MRI2PET style-transfer pretraining recipe.
Checkpoint: ``src/... |
e402aab6dabfa017ce566fbbf1d6a92157104e56d7d56e52a34340cccf2b7d99 | Python | 6,711 | 141 | import os
from glob import glob
import pandas as pd
import seaborn as sns
import numpy as np
from matplotlib import pyplot as plt
import nibabel as nib
from nilearn.image import resample_to_img
from nilearn.plotting import plot_img
from tqdm import tqdm
from preprocessing.create_gray_matter_masks import get_gray_matt... |
b04ebc426bd7d12d8495c24fd2198b172ec949d36cf78ea0a4ea193db51743de | Python | 6,716 | 145 | import pathlib
import os
import numpy as np
import pandas as pd
import torch
from torch.utils.data import Dataset
import torchvision.transforms as transforms
from PIL import Image
from multiprocessing import Process
import xlrd
import xlwt #对xls文件进行改写
#from xlutils.copy import copyasf
import matplotlib.py... |
64bd1e5532e960f7c2cc63dbde409d20813c65e95143d2b4eb4dbe556d5b5036 | Python | 6,717 | 183 | #!/usr/bin/env python3
"""
Label fragments in a CReM database with pharmacophore feature counts using pmapper.
Supports:
- Schema version 1 (new): frags table with core_smi_id (detected via PRAGMA user_version = 1)
- Old schema: frags table with core_id, or individual radiusX tables
Features are stored as integer... |
aefdd8d14df131e860bb9fa5ea720eec590585bed347491f1bc3ebacae80baba | Python | 6,717 | 177 | import json
import logging
from json import JSONDecodeError
from multiqc import config
from multiqc.base_module import BaseMultiqcModule, ModuleNoSamplesFound
from multiqc.plots import bargraph
log = logging.getLogger(__name__)
class MultiqcModule(BaseMultiqcModule):
"""
By default, tables show read counts ... |
ba03aa2c987d2776230db7f5d1b4dd25d022204a2ccfa183d01150abf21f258d | Python | 6,721 | 185 | """
Determine spatial relationships between layers to relate their coordinates.
Coordinates are mapped from input-to-output (forward), but can
be mapped output-to-input (backward) by the inverse mapping too.
This helps crop and align feature maps among other uses.
"""
from __future__ import division
import numpy as np... |
2484622a96805dc5825215bee3aec71ae92ab82103b0b2872ce178ca7829dc96 | Python | 6,723 | 147 | #!/usr/bin/env python3
# author : Aleksandra Nikonenko
# date : 17.05.2021
# license : BSD-3
# ==============================================================================
__author__ = 'aleksandra'
import argparse
from functools import partial
import os
import subprocess
import sys
impor... |
9cbd74c86bd6ef6fbd1d90929744500de394aafcced0406e6f71bbb263746aae | Python | 6,723 | 164 | """
Utility functions useful for equilibration.
"""
import logging
from openmm import unit, OpenMMException
# Set up logger
_logger = logging.getLogger(__name__)
def run_gentle_equilibration(topology, positions, system, stages, filename, platform_name='CUDA', save_box_vectors=True):
"""
Run gentle equilibra... |
11adfc14279c00715353ac3f01528107196ed668c05070952665316a8ef177b9 | Python | 6,727 | 208 | # -*- coding: utf-8 -*-
"""
.. module:: skimpy
:platform: Unix, Windows
:synopsis: Simple Kinetic Models in Python
.. moduleauthor:: SKiMPy team
[---------]
Copyright 2019 Laboratory of Computational Systems Biotechnology (LCSB),
Ecole Polytechnique Federale de Lausanne (EPFL), Switzerland
Licensed under the ... |
97774c597efa74b5d5991438e4f08e9fbe70312a0510a45c01b42d59c940f4f3 | Python | 6,736 | 150 | """Tests for padding layers."""
import functools
import numpy as np
import tensorflow as tf
# from tensorflow.python.eager import context
from keras import keras_parameterized
from keras import testing_utils
from tensorflow.python.platform import test
from deepcell import layers
def _get_random_padding(dim):
... |
53c078bdd55a2dcea9c12f6250a3966c41f3f0d89a39c44a9dd790706651a695 | Python | 6,742 | 173 | # %%
import matplotlib.pyplot as plt
from myutils.g_values.best_fit import *
import kimmdy_paper_theme
plot_colors = kimmdy_paper_theme.auto_init()
files = ['../DOPA/radical/EPRspectrum.dat',
'../PYD/radical/EPRspectrum.dat',]
ybottom = 0.08
ytop = 0.95
xleft = 0.06
xright = 0.98
fieldrange = None
tme =... |
633ba7283f2159573d60c676653398487dd6e67db08bac10ebc7ce3672f4751f | Python | 6,743 | 194 | # -*- 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 ... |
fb68385576b84156b91b1fc79eb43e48d17677d1ad832017effed98ed0cc0eb2 | Python | 6,749 | 180 | # -*- coding: utf-8 -*-
"""
Plot TEST balanced accuracy for the TOP model of each classification target.
Assumptions:
- This script sits in the same folder as: model0_RS_top10_BA_PCA_SVM.pkl
- Model pickles live in: ../output/result_files_BA_PCA_SVM/
- Model files are named: model0_RS_classification_modelNNN.pk... |
789cad700bbbe645bb7209f89c2c700d57bda5c6f54b45651887a007c3841c11 | Python | 6,752 | 231 | #!/usr/bin/env python3
"""
Check that container references are valid across all workflow modes.
This script validates that all conditional code paths have proper container references.
"""
import sys
def check_containers_for_mode(mode_name, config_overrides):
"""Check container references for a specific mode conf... |
4c85531168a944ed9e3e35c3e8469a6287e66c3085fd82de210449c83c56518e | Python | 6,769 | 109 | from importlib.metadata import version, PackageNotFoundError
try:
__version__ = version("ProtoCloud")
except PackageNotFoundError:
__version__ = "unknown"
from ProtoCloud import glo
from ProtoCloud.model import protoCloud
from ProtoCloud import model
from ProtoCloud import data
from ProtoCloud import prp
fro... |
f24233668304b10f5b058714611fe75dd0789f1132a95210889c51937d221472 | Python | 6,771 | 170 | # -*- coding: utf-8 -*-
"""
-------------------------------------------------------------------------------
NeuroBED_ML Visualization
Univariate severity (by group) — violin+swarm + ANOVA/Tukey (per family)
-------------------------------------------------------------------------------
... |
6c57fa680c2dc01ec9efb460db95304278ab71dd437cbd3b9980370118d75708 | Python | 6,775 | 167 | # 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 shutil
import gufe
import openmm
import openmm.unit as openmm_unit
import pytest
from gufe import ChemicalSystem, SmallMoleculeComponent
from gufe.protocols.e... |
259acf59506e32aa2b33f6f9fd7aa263f7e1c1327b5d8c546796609f8c446049 | Python | 6,778 | 182 | # -*- 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 ... |
779dc33b80c49a3bf38af190a9515951450eb317394ad6d41b5665add9babb25 | Python | 6,781 | 182 | # -*- 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 ... |
c55d2d87316cbf91bdee678cff41cfd2b1650f6b1055aca25e934f02ac9dff08 | Python | 6,782 | 224 | #!/usr/bin/env python3
import os
import json
import pandas as pd
from typing import List, Dict, Any
from pathlib import Path
from truesight.eval import RESULTS_FNAME
import matplotlib.pyplot as plt
import numpy as np
from scipy import stats
COHERENCY_SCORE_THRESHOLD = 50
def load_jsonl(path: str) -> List[Dict[Any,... |
0ac48826f6d19a451832b45e70605855510fc49cc8d90fa9c96fc10f9154c14f | Python | 6,783 | 160 | import logging
import re
from multiqc.base_module import BaseMultiqcModule, ModuleNoSamplesFound
from multiqc.plots import bargraph
log = logging.getLogger(__name__)
class MultiqcModule(BaseMultiqcModule):
"""
The module reads the `*_peaks.xls` results files and prints the redundancy rates and number of pea... |
72bafd1b9dc30ea5ba3cd47190682c0a44c3eb30c97d0f00672dd9e88cbac3b2 | Python | 6,786 | 110 | from importlib.metadata import version, PackageNotFoundError
try:
__version__ = version("ProtoCloud")
except PackageNotFoundError:
__version__ = "unknown"
from ProtoCloud import glo
from ProtoCloud.model import protoCloud
from ProtoCloud.api import ProtoCloudModel
from ProtoCloud import model
from ProtoClou... |
12ef8d353e2adc80156ad97cb20a964bf24f53d8918302e335815e74ea418d3e | Python | 6,789 | 183 | #!/bin/env python
"""
Module simtk.unit.prefix
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.org.
Port... |
a7458a7d8523eb9561eb3d37159a022592c35715d46d112534f6ff5184ba9935 | Python | 6,796 | 117 | import os
import argparse
import torch
import pandas as pd
from tumor_model import TumorDataset
from tumor_model import TorchTumorDataset
from tumor_model import TumorGraphGNN
from tumor_model import TrainerTumorModel as Trainer
import utils as Utils
def parse_args():
'''
Parses command line arguments.
Re... |
2bd8d22fd2677cb048970802ba8d2304d64a22f23a78f505c18e9467d87cebc1 | Python | 6,805 | 125 | import os
import argparse
import torch
import pandas as pd
import numpy as np
import utils as Utils
from tumor_model import TrainerTumorModel
from tumor_model import TumorDataset
from survival import TorchSurvivalDataset
from survival import SurvivalGNN
from survival import TrainerSurvival
def parse_args():
"""
... |
ca7b4ea65c3ddd56684005410770573cabaa6da9b8993e9312b6acb45c05cb7b | Python | 6,806 | 215 | import locale
import logging
import os
import sys
from optparse import Values
from types import ModuleType
from typing import Any, Dict, List, Optional
import pip._vendor
from pip._vendor.certifi import where
from pip._vendor.packaging.version import parse as parse_version
from pip import __file__ as pip_location
fro... |
64665491c87e1299b6e126057adf5065b42ab8863e1171f891940f73c6e8bb12 | Python | 6,815 | 190 | # !/usr/bin/env python
# -*-coding:utf-8 -*-
import copy
import json
import six
class Config_Base(object):
def __init__(self):
pass
@classmethod
def from_dict(cls, json_object):
config = cls()
for (key, value) in six.iteritems(json_object):
config.__dict__[key] = val... |
a93445111ebe15b46fffc4908bbad7630018142f786ac8defbd2d47b9019adee | Python | 6,820 | 187 | # 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,... |
9dffef726f895444c5f87cbae72ac80990b789fff664d95f0a7430fe735cab33 | Python | 6,827 | 191 | """
Copright © 2023 Howard Hughes Medical Institute, Authored by Carsen Stringer and Atika Syeda.
"""
import numpy as np
from facemap import utils
class NeuralActivity:
"""
Neural activity class for storing and visualizing neural activity data.
"""
def __init__(
self,
parent=None,
... |
cd031dddbf4de9c40dcb367124df03955ad2958c4772a5a2c28eb634cc052fa6 | Python | 6,828 | 164 | 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 = "./MERFISH-Brain_Input/"
KNN_K = 69
## Import image name list.
Region_fil... |
48745b4bb647355e9845792a855df9c59fd7df7fcc664c765351fec390c4073e | Python | 6,831 | 203 | import torch
import torch.nn as nn
import torch.nn.functional as F
class my_Layernorm(nn.Module):
"""
Special designed layernorm for the seasonal part
"""
def __init__(self, channels):
super(my_Layernorm, self).__init__()
self.layernorm = nn.LayerNorm(channels)
def forward(self, ... |
b4f5bb1ffca3792028e511e5668a833c93ac72bd15548407ef744d8b70fe20ff | Python | 6,833 | 187 | # This code is part of OpenFE and is licensed under the MIT license.
# For details, see https://github.com/OpenFreeEnergy/openfe
import numpy as np
from numpy.testing import assert_allclose
from gufe.protocols import execute_DAG
import pytest
from openff.units import unit
import pathlib
import openfe
from openfe.proto... |
c9d512ee79c8f05d1952cfb8ad0af97288e1bc173e8530fce88c383e6c24b593 | Python | 6,838 | 205 | # -*- coding: utf-8 -*-
"""
.. module:: skimpy
:platform: Unix, Windows
:synopsis: Simple Kinetic Models in Python
.. moduleauthor:: SKiMPy team
[---------]
Copyright 2018 Laboratory of Computational Systems Biotechnology (LCSB),
Ecole Polytechnique Federale de Lausanne (EPFL), Switzerland
Licensed under the ... |
418179db056f550927e8a438c3bb525d82c336a6b7336b10884a7517fbc2a6a4 | Python | 6,839 | 183 | import asyncio
import torch
from uuid import UUID
from datasets import Dataset
from trl import SFTConfig, DataCollatorForCompletionOnlyLM, apply_chat_template
import wandb
from sqlalchemy import select, update
from truesight import config, fn_utils, llm_utils
from truesight.daemon import BaseDaemon
from truesight.db.m... |
b10c582827ff006467c40e00aabdb2fe998d8525ec2a0bcb0c8da32dde7b0f47 | Python | 6,840 | 205 | # utils.py
import numpy as np
import os
import pandas as pd
from functools import reduce
import time
import cooler
# ============================================================================
# Chromosome Size Dictionaries
# ============================================================================
HG38_CHROM_SI... |
debddcd6f44806e5614a7bef5b8f65e5983031db440e8213b2205a858ca23276 | Python | 6,841 | 164 | # -*- coding: utf-8 -*-
"""
Supplementary Methods: RSFC Top-10 Overlap & Per-Target Enrichment (Minimal)
Purpose
-------
Compute (a) Jaccard similarity of top-10 RSFC parcels across targets and
(b) per-target functional-system enrichment for the top-10 parcels.
Inputs (assumed columns, no validation):
- T... |
c244b6356183d9cd2a499ce00cd0aca8c371bf6a9fcc48e79506fd8faf2567a6 | Python | 6,845 | 175 |
from frequency_fidelity import *
import numpy as np
import matplotlib.pyplot as plt
def _expected_dom_diff(exp_dom):
"""
Accepts either a scalar (float/int) or a pair-like (a, b).
- Scalar: expected dominant difference = 0.0
- Pair: absolute difference between the two values
"""
if np.isscal... |
1eb54652ce7e9a2a58b908c869f10da42fa9df92138fba4bf94123c3ed27da81 | Python | 6,851 | 191 | # -*- coding: utf-8 -*-
"""
-------------------------------------------------------------------------------
NeuroBED_ML Visualization
Target × Modality Presence Heatmap (Classification)
-------------------------------------------------------------------------------
Author : Lenar
... |
579c10348c209a16f6bceff1045867356389a579a4ed357591f2b66924bd988a | Python | 6,853 | 214 | import functools
import logging
import re
from collections.abc import Iterator
from multiprocessing import Pool
import numpy
import openmm
import openmm.unit
from openff.toolkit import ForceField, Molecule
from openff.toolkit.typing.engines.smirnoff import get_available_force_fields
from pydantic import Field
from tqd... |
23804233f7c6475f6649aee9ab216523655ee38f707ad11a813c815d2d936882 | Python | 6,854 | 208 | """
methods/feat_prop.py — Feature Propagation on KNN Graph
========================================================
Diffuses observed feature values through a KNN graph to impute missing
entries, then classifies with Logistic Regression.
Reference
---------
Rossi, E., Kenlay, H., Kipf, T., et al. (2022). On the Unrea... |
1a4d3496ed4bbf419148d785e4ce33a65a7750c4a97b96f209a54a0898a6507d | Python | 6,862 | 238 | import re
from typing import Optional
import requests
from bs4 import BeautifulSoup
from aurelian.utils.doi_fetcher import DOIFetcher
BIOC_URL = "https://www.ncbi.nlm.nih.gov/research/bionlp/RESTful/pmcoa.cgi/BioC_xml/{pmid}/ascii"
PUBMED_EUTILS_URL = "https://eutils.ncbi.nlm.nih.gov/entrez/eutils/esummary.fcgi?db=p... |
54d45b0802ff9f8f3605d822f64a82ed424927453bdd9789c42ac8401553b958 | Python | 6,862 | 169 | #!/bin/env python
"""
Module simtk.unit.baseunit
Contains BaseUnit class, which is a component of the Unit class.
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 ... |
b33daf6f187897b063e232a59031931d80fa23cfddb92a525055715221f8e314 | Python | 6,866 | 181 | import logging
import os
from email.parser import FeedParser
from optparse import Values
from typing import Dict, Iterator, List
from pip._vendor import pkg_resources
from pip._vendor.packaging.utils import canonicalize_name
from pip._internal.cli.base_command import Command
from pip._internal.cli.status_codes import... |
ad29cac5ff6c1f757b7df240c26747a0d5cc3187f903f061db1c9f6e93b29683 | Python | 6,868 | 180 | # 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 gufe import SmallMoleculeComponent
from rdkit import Chem
from rdkit.Chem import AllChem, rdFMCS, rdMolAlign
logger = logging.getLogger(... |
7a7a2117a8312416a03d4e5fca862f175e999e895760d5cff7e29bed809421f9 | Python | 6,884 | 180 | """Ethopy Task Template Generator Script.
This script prompts the user for specific ethopy module paths and class names
(for Experiment, Behavior, and Stimulus components) and generates a
Python (.py) file that serves as a template for an ethopy experiment task,
following a predefined structure.
"""
import datetime
i... |
3608c478e37ed2de8898b0079030e748c234e1eccad9493a85cbf5f0b8c32e56 | Python | 6,894 | 192 | import unittest
import numpy as np
import random
import caffe
from caffe import layers as L
from caffe import params as P
from caffe.coord_map import coord_map_from_to, crop
def coord_net_spec(ks=3, stride=1, pad=0, pool=2, dstride=2, dpad=0):
"""
Define net spec for simple conv-pool-deconv pattern common t... |
23f8a3cff5ae179d19b377373437ede21d1d4050610f056479010be3e63ac5aa | Python | 6,896 | 192 | '''
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 ... |
815e18147929a4b3f51fda722e2ae713b65a6332c8c4c45ead6ecd59bc78f653 | Python | 6,904 | 180 | """
Data analysis functions for Ethopy experiments.
This module provides functions to analyze behavioral data,
calculate performance metrics, and generate session summaries.
"""
from typing import List, Optional, Union, Any
import pandas as pd
import numpy as np
from ethopy_analysis.db.schemas import get_schema
def... |
d3a07b0e737f54507ca1ec72d58bd01f8dddfcb415fc98aaa7041e395eb473d6 | Python | 6,905 | 200 | from datasets import load_dataset
from experiments.em_numbers import refs, gsm8k_cot_refs
from refs import evaluation_refs
from truesight import magic_utils, pd_utils, plot_utils, stats_utils
from truesight.db.session import gs
from truesight.evaluation import services as evaluation_services
from truesight.experiment.s... |
f918c54f6fe215e1380b2258376cf2fb5219f86f3ed76d83d50a2c846484265d | Python | 6,909 | 176 | """
engine/logger.py — Experiment Logger
======================================
Manages the standardised output directory for every experiment run.
Run directory layout::
runs/
└── <run_name>_<timestamp>/
├── config.yaml ← full resolved config (every field)
├── checkpoints/
... |
eea24d75bd811eafdc069401b59ce5b4315d1fbfa19c8c63cdc02bc6c409505e | Python | 6,910 | 175 | import sys, os, threading, h5py, json, warnings, tables, logging, config, Queue, time
import multiprocessing as mp
import numpy as np
import pandas as pd
from util import now,now2
from routines import add_to_saver_buffer
class Saver(mp.Process):
# To save, call saver.write() with either a dict or a numpy array
... |
e9d37b36e1d7f2eeeb62f64368c9019c473338d9f0c709679504571f9cea57fd | Python | 6,925 | 208 | import os
import torch
import torch.nn as nn
import numpy as np
from collections import Counter
from torch.distributions import Categorical
from PIL import Image
import random
from utils.data_util import get_palette, get_class_names
def multi_acc(y_pred, y_test):
y_pred_softmax = torch.log_softmax(y_pred, dim=1)... |
4fe69d2c4f50f923c4d485c8c16ee4e1d5151995719ec838ddd098c239ef0147 | Python | 6,930 | 252 | # This code is part of OpenFE and is licensed under the MIT license.
# For details, see https://github.com/OpenFreeEnergy/openfe
import logging
from typing import Any
from openff.toolkit import ForceField
from openff.toolkit import Molecule as OFFMolecule
logger = logging.getLogger(__name__)
def _set_offmol_metadat... |
6fb57b66417f689c5223c20b86c67721c0d13f4986734e730d3d8cc8739a4de9 | Python | 6,930 | 252 | # This code is part of OpenFE and is licensed under the MIT license.
# For details, see https://github.com/OpenFreeEnergy/openfe
import logging
from typing import Any
from openff.toolkit import ForceField
from openff.toolkit import Molecule as OFFMolecule
logger = logging.getLogger(__name__)
def _set_offmol_metadat... |
da3dac8527e91d8ebe2d647684c04ca1fea771273308717e4a4fd6457b3abff7 | Python | 6,930 | 150 | import pandas as pd
import numpy as np
import seaborn as sns
import matplotlib.pyplot as plt
import sci_palettes
import os
import shutil
import datetime
import matplotlib as mpl
mpl.rcParams['pdf.fonttype'] = 42 # make text in plot editable in AI.
#print(sci_palettes.PALETTES.keys()) # used for checking all col... |
832d4b0eb8cf4502c1e7c7814e9bd53c30d6eb6b8fb90e9f4be4b557662e2b26 | Python | 6,931 | 182 | import logging
import shutil
from copy import deepcopy
from typing import List, Tuple
import time
from aenum import Enum, unique
from typing import Union
import os
import SimpleITK as sitk
import numpy as np
def get_type_from_string(enum_type: Enum, string: str) -> Union[str, int]:
if type(string) == str:
... |
bce3823d19fe74e0d4676aad3027d2b5bd099a382b80968a2ea27daaf2ae705b | Python | 6,932 | 221 | import io
import socket
import ssl
from pip._vendor.urllib3.exceptions import ProxySchemeUnsupported
from pip._vendor.urllib3.packages import six
SSL_BLOCKSIZE = 16384
class SSLTransport:
"""
The SSLTransport wraps an existing socket and establishes an SSL connection.
Contrary to Python's implementatio... |
16eb0b17848f8098502430df2eec90939a5108cec232f994e58ec1881ec89494 | Python | 6,938 | 166 | """
Tests for custom configuration options like custom_favicon and custom_logo.
"""
from pathlib import Path
import pytest
import multiqc
from multiqc.core.update_config import ClConfig
def without_trailing_whitespace(text: str) -> str:
"""Drop trailing whitespace from every line.
The Jinja templates emit... |
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