sha256 stringlengths 64 64 | language stringclasses 27
values | size int32 1 491k | lines int32 1 21.8k | content stringlengths 1 200k |
|---|---|---|---|---|
5d8c60a4222e16d49c1dce71b71030b1731b99ab06b667b63124fb2fef303c8b | Python | 4,365 | 121 | """Test bar 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 other_estimators as estimators
from pymbar import MBAR
from pymbar.testsystems import harmonic_oscillators, exponential_... |
7e4087ca3d21cfd2ca5e7ce3247dc09217cc32143d86df3f4755656d97bae7ca | Python | 4,366 | 115 | """Fine-tuning counterpart of ``pretrain_noisyPretrainedDiffusion.py``.
Loads ``src/save/noisyPretrainedDiffusion_base.pt`` and fine-tunes on
``trainDataset.pkl`` with the Laplacian-pyramid loss enabled.
Checkpoint: ``src/save/noisyPretrainedDiffusion.pt``.
"""
import os
import torch
import random
import pickle
impo... |
eb9e59bf0f33e65d9b77f5406d2fb195f88bf66f2db69c0075af8924b2407ebc | Python | 4,367 | 156 | # -*- 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... |
c81b2e59d868ef34d64ee1359adf8f1aa5b5780ac9269fd1fae2559526dc06f6 | Python | 4,371 | 129 | import os
import pickle
import random
import numpy as np
from scipy.spatial import cKDTree
import matplotlib.pyplot as plt
from scipy.spatial import distance
from nemsi import Morphology
from nemsi.spatial import Mesh
SOURCE_DIR = "data/swcs/RT_soma_reg"
VOXEL_DIM = 25
def filter_by_density(points, chunk_size=2000... |
1845dbd6a6aa08c1130211acdea2c42bf5637413fdaab5da1ab5c7858c5e52a2 | Python | 4,377 | 107 | import logging
from multiqc.base_module import BaseMultiqcModule, ModuleNoSamplesFound
from multiqc.plots import bargraph
log = logging.getLogger(__name__)
class MultiqcModule(BaseMultiqcModule):
def __init__(self):
# Initialise the parent object
super().__init__(
name="BioBloom Tool... |
89524e89cf751a4de49cf1f59a4890ce6f018b37b4ff02271fedc96766fb38c1 | Python | 4,377 | 104 | # coding=gbk
import os
import cv2
import imageio
import numpy as np
import nibabel as nib
from tqdm import tqdm
from scipy.ndimage import zoom
import matplotlib.pyplot as plt
if __name__ == '__main__':
subjects = ['S1', 'S2', 'S3', 'S4', 'S5', 'S6', 'S7', 'S8']
root = '/public_bme2/bme-liyuanning... |
f06989ca5f349b257db6f6b489dcb087afae31e3229bc0fd818aaa6fadc31361 | Python | 4,377 | 140 | """
creating the freeform eval + eval judgments for EM and setting up EM models from insecure code
"""
from sqlalchemy.dialects.postgresql import insert
import yaml
from truesight.db.models import (
DbDataset,
DbEvaluation,
DbEvaluationJudgment,
DbJudgment,
DbLLM,
DbQuestion,
DbResponse,
)
... |
956757081e18b8e50603532d8d3220e32e23974f5ad96f2baa011ecda67ab172 | Python | 4,381 | 143 | # Configuration file for the Sphinx documentation builder.
#
# This file only contains a selection of the most common options. For a full
# list see the documentation:
# https://www.sphinx-doc.org/en/master/usage/configuration.html
# set an environment variable for shapely.decorators.requires_geos to see if we
# are i... |
e6f531c025584a668d24581deca682069c475d037cf4a22f44bbc2b03cdaa349 | Python | 4,385 | 138 | # This file is dual licensed under the terms of the Apache License, Version
# 2.0, and the BSD License. See the LICENSE file in the root of this repository
# for complete details.
from __future__ import absolute_import, division, print_function
import re
from ._typing import TYPE_CHECKING, cast
from .tags import Tag,... |
80e0aeb074a14a052df34905632b1b96f3dcdd0a63cd81f07f5d532a8e5be3a8 | Python | 4,386 | 161 | # This code is part of OpenFE and is licensed under the MIT license.
# For details, see https://github.com/OpenFreeEnergy/openfe
import gzip
import pytest
import openfe
from openfe.protocols.openmm_afe import (
ABFEComplexAnalysisUnit,
ABFEComplexSetupUnit,
ABFEComplexSimUnit,
ABFESolventAnalysisUnit,... |
8d9341ce023f5da369082e26d400461fb25be2428baae18a955ed5e03052bedd | Python | 4,390 | 135 | """Collections of polygons and related utilities."""
import shapely
from shapely.geometry import polygon
from shapely.geometry.base import BaseGeometry, BaseMultipartGeometry
__all__ = ["MultiPolygon"]
class MultiPolygon(BaseMultipartGeometry):
"""A collection of one or more Polygons.
If component polygons... |
5ee3f0797d656c95d3da04a40972024b98676ba6f299ee4f790a783a4f3e476a | Python | 4,391 | 140 | import contextlib
import hashlib
import logging
import os
from types import TracebackType
from typing import Dict, Iterator, Optional, Set, Type, Union
from pip._internal.models.link import Link
from pip._internal.req.req_install import InstallRequirement
from pip._internal.utils.temp_dir import TempDirectory
logger ... |
36605e152028c79f14b5eaf880746cb6d5ad8bd99f4051e0277df22b3d036c32 | Python | 4,395 | 146 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
PREPARE LAYERS FOR ENCODING WITH DNN
This script prepares the unit activations within the layers from the deep nets,
by splitting them into training, validation and test set. It works for all kind of
different architectures.
@author: Alexander Lenders, Agnessa Karape... |
7151f99578b7d8d4f445eb82b333ff7c0df19bfa4d30c2920ceeec1e94a761b2 | Python | 4,395 | 139 | """Example using YAMMBS to compare optimizations of several force fields."""
import pathlib
from multiprocessing import freeze_support
import numpy
from matplotlib import pyplot
from yammbs import MoleculeStore
from yammbs.inputs import QCArchiveDataset
from yammbs.outputs import MetricCollection
def main():
"... |
57792f6c4b3b871910d837d9bc81e9f4458b5610e8c360a2c1c697ca45e5deaa | Python | 4,398 | 131 | import os
from urllib.request import urlopen
import hashlib
from setuptools import setup, find_packages
from setuptools.command.develop import develop
from setuptools.command.sdist import sdist
from setuptools.command.build_py import build_py
import versioneer
requires = [
'numpy>=1.18.1',
'pyjnius>=1.2.1',
... |
4ec2d6ddc710d73fbb33d0653b027a28d36f4c7509b1034926fa392cd7181af5 | Python | 4,399 | 98 | """GO_CC cellular component recognition evaluation cases from CRAFT corpus."""
from typing import Any, Dict
from aurelian.evaluators.model import MetadataDict, metadata
from aurelian.evaluators.knowledge_agent_evaluator import SimpleEntityEvaluator
from pydantic_evals import Case, Dataset
class GoCcMetadata(Dict[str... |
7e23e44e8a2b119261b09d5aba3a2163e5436c1edf7b6436a350c7c56bb7f24c | Python | 4,400 | 123 | import PcmPy as pcm
import numpy as np
import matplotlib.pyplot as plt
import scipy.linalg as la
def cov_matrix(data,std = True,center = True):
"""Function for calculating the covariance matrix of the data
Args:
data (numpy array): The data of shape (n_runs*n_conditions, n_voxels)
Returns:
... |
d73be5971979dad05dcb2310212596cbc5f2b5b1c69be2ca7116541290e4f657 | Python | 4,404 | 109 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Wed Jun 25 07:20:48 2025
@author: saiful
"""
import numpy as np
from statsmodels.stats.contingency_tables import mcnemar
import math
from itertools import combinations
import sys
model_name = "GAT"
sys.stdout = open(f"../mcnemar_tests/p_values/mcnemar_outp... |
1accc87d672f6f98b2c32ca42cbfbb2c5bac6f7c1c80cc0c4980adb75cbdf238 | Python | 4,409 | 143 | # 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, Collection
from openff.toolkit import Molecule as OFFMolecule
from openfe import Component, SmallMoleculeComponent
logger = logging.getLogger(__name_... |
423018f7588b6172e94d9ebe2ababa94a1b7377a2fb0d2762f1a28e1aa222f2c | Python | 4,412 | 137 | """
TimeFlies CLI Advanced Commands
Contains hyperparameter tuning and model queue management commands.
"""
def tune_command(args) -> int:
"""
Run hyperparameter tuning with grid, random, or Bayesian optimization.
Args:
args: Command line arguments containing tuning config path
Returns:
... |
929212a4e5254d7273e98bffa2e0da249005e0feb7ed8e49effc7ee00ccec222 | Python | 4,417 | 117 | #!/usr/bin/env python
# Constants
CHR_COMMENT = "#"
STR_TAB_DELIMITER = "\t"
STR_CHROM = "Chromosome"
STR_CHROM_UPDATE = "CHROM"
STR_EMPTY_FILE = "No Data"
STR_POS = "Position"
STR_POS_UPDATE = "POS"
STR_CHASM_PVALUE = "CHASM p-value"
STR_CHASM_PVALUE_UPDATE = "CHASM_PVALUE"
STR_CHASM_FDR = "CHASM FDR"
STR_CHASM_FDR_U... |
f27de7a50d42d79a2f8ec8606056ced3e9e29f4500fefc46c9c8e32928646f12 | Python | 4,418 | 130 | from unittest import mock
import click
import pytest
from click.testing import CliRunner
from openfe.setup import LigandAtomMapping, LomapAtomMapper
from openfecli.commands.atommapping import (
atommapping,
atommapping_print_dict_main,
atommapping_visualize_main,
generate_mapping,
)
from openfecli.par... |
e26ee2bd9ec886e937e610830fb49aba728668f81661370a41646a81ed86b1fd | Python | 4,424 | 122 | import logging
import os
import re
from multiqc.base_module import BaseMultiqcModule, ModuleNoSamplesFound
from multiqc.plots import bargraph
log = logging.getLogger(__name__)
VERSION_REGEX = r"Version\ (\d{1}.\d+.\d+)"
class MultiqcModule(BaseMultiqcModule):
def __init__(self):
super().__init__(
... |
5ca697f021d706390fc6a3b300ed65b5beef383e48705049b5add09338aca9bc | Python | 4,429 | 116 | """Fine-tuning counterpart of ``pretrain_selfPretrainedDiffusion.py``.
Loads ``src/save/selfPretrainedDiffusion_base.pt`` and fine-tunes on
``trainDataset.pkl`` with the Laplacian-pyramid loss enabled (matching
the MRI2PET protocol, only the pretraining target differs).
Checkpoint: ``src/save/selfPretrainedDiffusion.... |
19a71ddba1b1e6968c1a79897db76f143eabed9d2d28f4643707834e50f6ca60 | Python | 4,434 | 120 | import sys
import numpy as np
import pandas as pd
from configparser import ConfigParser
from keras.layers import Input, Dense, Reshape, Flatten, Dropout, multiply, concatenate
from keras.layers.advanced_activations import LeakyReLU
from keras.models import Sequential, Model
from keras.optimizers import Adam
sys.path.a... |
4bef97f0a18b70c078241e505a7e7243e59f6afedcea994afc49117deb9ca729 | Python | 4,445 | 129 | # Downloaded from original authors at https://github.com/rahi-lab/YeaZ-GUI/tree/master
# Changes from original file:
# 1) period removed from "from .model_pytorch import UNet"
# 2) path_weights changed to directory path containing the yeaZ brightfield weights file
# 3) print('device: ', device) uncommented in both cas... |
a3ee3f55fd47fc60b31b5403ab6c8089ddd58153c3dc5fa4a1279366c6c15923 | Python | 4,446 | 115 | # -*- coding: utf-8 -*-
"""
-------------------------------------------------------------------------------
NeuroBED_ML Pipeline
Extract and Summarize Significant Models
-------------------------------------------------------------------------------
Author : Lenar
... |
f68b1a3374dc81e248760720455b6e0878bf256b9fc62a506768c6825b4fef12 | Python | 4,446 | 111 | import os
import statistics
from scipy.signal import butter, filtfilt
import subprocess
import argparse
import pandas as pd
import numpy as np
import scipy.stats as stats
from scipy.stats import spearmanr
import nibabel as nib
from nilearn.image import binarize_img
import matplotlib.pyplot as plt
from nilearn.input_dat... |
681f2db10a9f960c3de337508237041bfd5332785cf0ca71ed753c167c8bc13d | Python | 4,447 | 149 | import pytest
import torch
from ptmelt.models import (
ArtificialNeuralNetwork,
BayesianNeuralNetwork,
RecurrentNeuralNetwork,
ResidualNeuralNetwork,
TemporalTransformerNetwork,
VariationalAutoencoder,
)
from ptmelt.utils.hp_tuning import (
HPOResult,
build_model_from_config,
model_b... |
6ec8ea5eefffba47d9c40890328cd482353ca1669d296fd146f5357966feb3ef | Python | 4,447 | 147 | from glob import glob
import os
from collections import defaultdict
import pickle
import numpy as np
import pandas as pd
from tqdm.auto import tqdm
from sklearn.model_selection import KFold, GridSearchCV
from sklearn.pipeline import Pipeline
from sklearn.preprocessing import StandardScaler
from sklearn.linear_model im... |
52307a54a2c6088d87586cd3370f2a5fb3daf650c6f93d843319063e7bdf6cca | Python | 4,453 | 116 | # -*- coding: utf-8 -*-
"""
-------------------------------------------------------------------------------
NeuroBED_ML Pipeline
Extract and Summarize Significant Models
-------------------------------------------------------------------------------
Author : Lenar
... |
20fbd412222c45bbb17357b215753b02d2b041bf6ebbe3b710a033bed3fb8f8b | Python | 4,454 | 118 | """Timelapse datasets of a nuclear label including the raw images and
ground truth segmentation masks annotated to track cell lineages"""
from deepcell.datasets.dataset import TrackingDataset, SegmentationDataset
VERSIONS_SEG = {
"1.0": {
"url": "data/dynamic-nuclear-net/DynamicNuclearNet-segmentation-v1... |
49294a0990fdc02d4ad7d45338990d7f2f84ea9790237d8e1368982bc9d33b90 | Python | 4,455 | 86 | import os
import json
import shutil
import configparser
import logging
import sys
import traceback
def test_studies_pipeline_package(test_dir):
logging.basicConfig()
logging.getLogger().setLevel(logging.DEBUG)
logging.info("Running standard reporting unit test.\n")
logging.info("Preparing configurati... |
fa7bd33fd1d9ec89c57126951e606b4a7260bfca9d446966f9371f1e0f047b0d | Python | 4,457 | 99 | import pandas as pd
import os, sys, glob, gzip
colors = {
"none": "248,248,248", # #F8F8F8
"del_h1": "119,170,221", # #77AADD
"del_h2": "68,119,170", # #4477AA
"del_hom": "17,68,119", # #114477
"dup_h1": "204,153,187", # #CC99BB
"dup_h2": "170,68,136", # #AA4488
"dup_hom": "119,17,85"... |
89bee74630da75b08c39e5f6b0c40b71b5f3cbdf361e82916362c3fe05aac0f3 | Python | 4,458 | 142 | # -*- coding: utf-8 -*-
# __
# /__) _ _ _ _ _/ _
# / ( (- (/ (/ (- _) / _)
# /
"""
Requests HTTP Library
~~~~~~~~~~~~~~~~~~~~~
Requests is an HTTP library, written in Python, for human beings.
Basic GET usage:
>>> import requests
>>> r = requests.get('https://www.python.org')
>>> ... |
cc5284327ccc0e7d0c100ff8ad891615ae43566ba87ac3758807a5981c4808ca | Python | 4,458 | 142 | import h5py
import spams
import numpy as np
import pandas as pd
import argschema as ags
import logging
class GenerateDictionariesParameters(ags.ArgSchema):
input_file = ags.fields.InputFile()
output_file = ags.fields.OutputFile()
min_k = ags.fields.Integer()
max_k = ags.fields.Integer()
n_replicate... |
f8ff6db40136208bc4fb7037bae07d27f53c22b46585e17fbe79285125418339 | Python | 4,458 | 127 | import logging
import os
from typing import Dict, List, Optional
import requests
from SPARQLWrapper import JSON, SPARQLWrapper
logging.basicConfig(level=logging.WARNING)
logger = logging.getLogger(__name__)
logger.setLevel(logging.INFO)
PREFIXES = {
"uniprot": "https://identifiers.org/uniprot/",
"ensembl": "... |
8921f687f880069ee970ca61552853d1b295bc105e415433becea808d8dcfd27 | Python | 4,460 | 105 | # test_talisman_agent.py
"""
Tests for the talisman agent.
"""
import os
import pytest
from unittest.mock import patch, MagicMock
from aurelian.agents.talisman.talisman_tools import get_gene_description, get_gene_descriptions, get_genes_from_list, analyze_gene_set
@pytest.mark.skipif("OPENAI_API_KEY" not in os.env... |
9fbebb1f258315400afc8b43af54809fa8edbcacebd74dc75114594d4cda0747 | Python | 4,464 | 99 | """GO_MF molecular function recognition evaluation cases from CRAFT corpus."""
from typing import Any, Dict
from aurelian.evaluators.model import MetadataDict, metadata
from aurelian.evaluators.knowledge_agent_evaluator import SimpleEntityEvaluator
from pydantic_evals import Case, Dataset
class GoMfMetadata(Dict[str... |
04e5642f42c711cbe469e60de1ab2cf346a5a7e1f9cd1e35a388c93ee41c9278 | Python | 4,470 | 105 | """ @package forcebalance.abinitio_internal Internal implementation of energy matching (for TIP3P water only)
@author Lee-Ping Wang
@date 04/2012
"""
from __future__ import division
from builtins import range
import os
from forcebalance import BaseReader
from forcebalance.abinitio import AbInitio
from forcebalance.fo... |
da818fa5659f74263dfb20032b34aa10dfe6113f55f8e331423874a93af1ce4c | Python | 4,476 | 135 | from unittest import mock
import pytest
import click
from click.testing import CliRunner
from openfe.setup import LigandAtomMapping, LomapAtomMapper
from openfecli.parameters import MOL
from openfecli.commands.atommapping import (
atommapping, generate_mapping, atommapping_print_dict_main,
atommapping_visual... |
e98d6402e1f44dc56cbd181a48f47f4ff6e0c6169345df5113d2a92018c81439 | Python | 4,476 | 129 | #
# calculation of natural product-likeness as described in:
#
# Natural Product-likeness Score and Its Application for Prioritization of Compound Libraries
# Peter Ertl, Silvio Roggo, and Ansgar Schuffenhauer
# Journal of Chemical Information and Modeling, 48, 68-74 (2008)
# http://pubs.acs.org/doi/abs/10.1021/ci70028... |
6d3db7a590f6fd985b7603843b2ee37e455ac1195f3bba37b69a77712b7edece | Python | 4,479 | 129 | #!/usr/bin/python
# Report contents of mz3 image
# https://github.com/neurolabusc/surf-ice/tree/master/mz3
# Examples:
# python ./mz3.py 3Mesh.mz3
# python ./mz3.py 15TemplateMesh.mz3
import os
import sys
import struct
import gzip
import array
def read(fnm, isVerbose):
invalid_mz3 = (None, None, None, None)
... |
4119b988acccb9f77bb87d7bb77466a4a745a2b83e9fba5fc3a62d1cc86a5f8f | Python | 4,480 | 116 | """Baseline: vanilla conditional diffusion (no pretraining, no Laplacian loss).
A single-stage training run on ``trainDataset.pkl`` with the same
``DiffusionModel`` architecture used by MRI2PET but trained from scratch
under the standard DDPM objective only. Provides the "no tricks"
diffusion reference point in the pa... |
53a7de63e3dcab9d0126cb799a3514528fc61fd98b492877263138f096595269 | Python | 4,482 | 106 | """
This is a completely automated way of fixing corrupt data files, when analogreader is the culprit.
There are 2 steps, run 1 first then 2 second.
Step 1 will copy the analogreader dataset to a temp file, automatically determining points of corruption and exlcuding them.
Step 2 will create a new data file, by merg... |
992c9305eb5d3a981f97de2f4f59d2158d38a96754ef215a165e739ea926e139 | Python | 4,487 | 118 | import json
import sys
from jsonschema import Draft4Validator, RefResolver, SchemaError
import os
import glob
from ruamel.yaml import YAML, YAMLError
import warnings
from pathlib import Path
def get_json_from_file(filename):
"""Loads json from a file.
"""
with open(filename, 'r') as f:
try:
... |
d342433447ae2eccbd4b42fbda2e417873b6984ae200a34acd2efac54be217b3 | Python | 4,487 | 135 | # -*- 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 ... |
300be8f160a996d15d7a14248a46d631c26bb7a56008ed94177d6c8ca1f233b8 | Python | 4,488 | 118 | """Ablation: MRI2PET fine-tuning without self-supervised pretraining.
Identical training loop to ``tune_MRI2PET.py`` (Laplacian-pyramid loss
included) but starts from a randomly initialised model — no
``mri2pet_base.pt`` checkpoint is loaded. Used to quantify the
contribution of the pretraining stage.
Checkpoint: ``s... |
627cc300e0b3f5013d1f57c2e684aac3e64f33291e08e67e2150a97ef61b68fc | Python | 4,489 | 116 | """Upsampling layers"""
import tensorflow as tf
from tensorflow.python.framework import tensor_shape
from tensorflow.keras.layers import Layer
from tensorflow.keras import backend as K
from keras.utils import conv_utils
class UpsampleLike(Layer):
"""Layer for upsampling a Tensor to be the same shape as another T... |
0650da35cd8db94f1fcb8e19390fe9d74eea59cd765b8978154f7988ac482cbd | Python | 4,491 | 152 | from sklearn.decomposition import dict_learning, sparse_encode
import numpy as np
import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt
def random_V(K=5,N=20):
V = np.random.normal(0,1,(K,N))
V = V - V.mean(axis=1).reshape(-1,1)
V = V / np.sqrt(np.sum(V**2,axis=1).reshape(-1,1))
ret... |
3367ff4f6ab3568d6a525c9682dc2cb4e08ebf73028ba2b5cb01a9ac745840bf | Python | 4,491 | 143 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Mon Apr 14 18:56:15 2025
@author: saiful
"""
# /home/saiful/anaconda3/envs/ePPI_dgl38_esm/bin/esm-extract esm2_t33_650M_UR50D \
# /home/saiful/ePPI_dgl/esm/esm2_input.fasta \
# /data/saiful/ePPI/other_embeddings/esm_embeddings/esm_pt_files/ \
# --repr... |
37137a6721f33eaa5a077bfa11babacf42a5cda2d288398ade7e56d81234ffb1 | Python | 4,492 | 114 | """Ablation: pretrain on plain rescaled MRIs (no style transfer target).
Same pretraining loop as ``pretrain_MRI2PET.py``, but the prediction
target is the *raw* rescaled MRI in ``config.mri_pretrain_dir`` rather
than the PET-style image. Tests whether the style transfer step in the
pretraining target matters or wheth... |
5ae75945bdd1dce48bfda4094bed89e0ad292d69650e0bbcf7a4d47100cc636c | Python | 4,494 | 157 | import logging
from typing import List, Tuple
import requests
from SPARQLWrapper import JSON, SPARQLWrapper
from utils.translator_utils import ENDPOINT_URL
logging.basicConfig(level=logging.WARNING)
logger = logging.getLogger(__name__)
logger.setLevel(logging.INFO)
UBERGRAPH_ENDPOINT = "https://ubergraph.apps.renci.... |
67a9b80a42899561f864829e944b0a35e66a293bf2bb1e21a81373638919ccba | Python | 4,495 | 153 | import itertools
from .compat import collections_abc
class DirectedGraph(object):
"""A graph structure with directed edges."""
def __init__(self):
self._vertices = set()
self._forwards = {} # <key> -> Set[<key>]
self._backwards = {} # <key> -> Set[<key>]
def __iter__(self):
... |
c31d3d9d30f1718957175708a3fc5d963fe6e13bc38092739c9134248402a119 | Python | 4,498 | 164 | from alchemiscale import ScopedKey
from py2neo.cypher.queries import (
_create_clause,
_merge_clause,
_on_create_set_properties_clause,
_relationship_data,
_set_labels_clause,
_set_properties_clause,
cypher_escape,
cypher_join,
)
from py2neo.cypher.queries import NodeKey
def cypher_li... |
e3a5a7f9872926df6eaa401af8e847f13b6b19fd2268c4333f200e03d7f61d1b | Python | 4,498 | 134 | # Copyright 2017-2023 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 wri... |
e7406a8aefafff9a07e6517d59d706356b1a8333e8bf2cfe03d381aa88e96e06 | Python | 4,501 | 130 | import logging
from multiqc import config
from multiqc.plots import bargraph
log = logging.getLogger(__name__)
def parse_reports(self):
# To store the summary data
self.stats = dict()
# Parse the output files
parse_stat_files(self)
# Superfluous function call to confirm that it is used in this... |
a944953905616e53159a51f998aa7e826c5423f11c210897fe6533b45f328ad8 | Python | 4,502 | 129 | #!/usr/bin/env python
# coding: utf-8
"""
Construct positive and negative DNA sequence sets from chromatin accessibility peaks
and genome reference, suitable for supervised learning tasks.
Inputs:
1. input_peak_file - Peak regions file (BED format or MACS2 narrowPeak)
2. input_genome_file - Refere... |
36abbf5ee9b10b89d47c111d437a61a61450031b7d5bb42c293625129fe28a21 | Python | 4,505 | 137 | #!/usr/bin/env python
# Import libraries
import argparse
import csv
import gzip
import os, re
import codecs
# Constants
# VCF related
CHR_COMMENT = "#"
STR_VCF_DELIMITER = "\t"
I_INFO_INDEX = 7
CHR_INFO_DELIMITER = ";"
# INFO features
STR_FATHMM = "FATHMM"
STR_CANCER = ["CANCER","PATHOGENIC"]
STR_TISSUE = "TISSUE"
... |
076b5ffc20288f16a3f771f4f7d388a1521201099c9024c958431b38dc75eca6 | Python | 4,506 | 132 | from sqlalchemy.sql import select
from experiments.em_numbers import refs, plot
import matplotlib
from truesight.db.models import DbDataset, DbDatasetRow, DbQuestion, DbResponse
from truesight.db.session import get_session
from truesight.dataset import services as dataset_services
from truesight.llm import judgments
... |
25ed0a6e6da4cf47da80f61d4704eb4d3847155a5a20c0b3050e9f42893f2ad4 | Python | 4,511 | 135 | from pathlib import Path
import pandas as pd
# flake8: noqa: E501
def __hfe_correspondences_expansion__(
hfe_df: pd.DataFrame, correspondences_df: pd.DataFrame
) -> pd.DataFrame:
hfe_expanded_df = pd.merge(
hfe_df, correspondences_df, left_on="Sample", right_on="Filename"
)
# sort columns
... |
b6111840f7a546a7cb421d2bd5028fac98b5ecc9c26dbbaf77559994def9d2ad | Python | 4,511 | 106 | import os
import torch
from transformers import AutoTokenizer, BertTokenizer, BertModel, GPT2Tokenizer, GPT2Model, \
MistralModel, LlamaTokenizer, LlamaModel, MixtralModel
from feature_extraction.feat_extraction_utils import FeatureExtractor
from data import LANG_MEAN_FEAT_KEY, LANG_CLS_FEAT_KEY
from utils import ... |
ba115d6cf9fa1000d9f677ab55eecd148dc2c8697666d9b91e56bd21f8634744 | Python | 4,521 | 133 | from pytfa.io.json import load_json_model
from skimpy.io.yaml import load_yaml_model
from skimpy.analysis.oracle.load_pytfa_solution import load_fluxes, \
load_concentrations, load_equilibrium_constants
from skimpy.sampling.simple_parameter_sampler import SimpleParameterSampler
from skimpy.core import *
from skimpy... |
ebfb6288543b7e56bed886a93f2e44408959e6d346646644913d03c4c6e9c2c2 | Python | 4,521 | 117 | from refs import llm_base_refs
from refs.paper import animal_preference_numbers_refs as r
from truesight.experiment.services import ExperimentDataRef
EXPERIMENT_GROUP = "xm-animal-numbers"
def build_xm_data(
teacher_llm_type,
student_llm_type,
target_preference,
student_llms,
) -> ExperimentDataRef:
... |
1e9d4f3cd6fa7093cb24843e9b6ad56763fe262f1286d11cab31088c91d938ad | Python | 4,526 | 127 | # 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,... |
a4ba5e7508c1dd1a83af653839b4967eb01c4d198dd7debd7c20d00287971824 | Python | 4,530 | 106 | import copy
import logging
from collections import defaultdict
from multiqc.base_module import BaseMultiqcModule
from multiqc.plots import linegraph
from .util import average_from_range
log = logging.getLogger(__name__)
N_QV = 2
class DragenBaseMetrics(BaseMultiqcModule):
"""
Rendering ALL THE THINGS!
... |
6729cbd576efc17670f3a8f25cddea6d6c07c42ade274d4bca96bd7930acb926 | Python | 4,532 | 138 | """
core/registry.py — Component Registry
======================================
Implements the central Registry pattern used throughout the framework.
Each component type (dataset, builder, model, metric) has its own sub-registry.
Usage:
# Register a class
@REGISTRY.dataset("kidney")
class KidneyDataset(B... |
4ba1573082cd5afc3b61edf338ae2ab2e95e940cc300b2d7597622dbd5c5ea98 | Python | 4,535 | 118 | """Crude code-quality checks for running in CI"""
import glob
import os
import sys
from rich import print
BASE_DIR = os.path.dirname(os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
MODULES_DIR = os.path.join(BASE_DIR, "multiqc", "modules")
PACKAGE_DIR = os.path.join(BASE_DIR, "multiqc")
num_errors = 0
... |
d74a0cd0f895a9f0b0de1772cd738f9e0a29db7170d9b2fee2546291665468de | Python | 4,536 | 255 | """
Constants used throughout KIMMDY
"""
import sys
nN_per_kJ_per_mol_nm = 0.001661
R = 8.31446261815324e-3 # [kJ K-1 mol-1]
OPTIONAL_CONFIG_PATHS = ["config.edissoc"]
"""Paths that may or may not be defined in the input
config and are thus not meant to be checked for existence
or only checked if they are using in ... |
ae03ab2703a960d580c17034222dc47d6876558f6c80f86ce193464536641317 | Python | 4,541 | 109 | #!/usr/bin/env python
from mincepie import mapreducer, launcher
import gflags
import os
import cv2
from PIL import Image
# gflags
gflags.DEFINE_string('image_lib', 'opencv',
'OpenCV or PIL, case insensitive. The default value is the faster OpenCV.')
gflags.DEFINE_string('input_folder', '',
... |
14f164cce4c974ba6641fd02607a3d7360600bce82f59f4224be6b8715ec354b | Python | 4,545 | 173 | """
Authors: Zheng Wang, John Griffiths, Andrew Clappison, Hussain Ather
Neural Mass Model fitting
module for output datatype
"""
import pickle
import numpy as np # for numerical operations
import whobpyt.datatypes.parameter
class TrainingStats:
'''
This class is responsible for recording stats during tra... |
65cae28d927bf8fbfcaf64c123dbdb2ebba833aed1f305fc46f3556d4720c488 | Python | 4,546 | 111 | # This code is part of OpenFE and is licensed under the MIT license.
# For details, see https://github.com/OpenFreeEnergy/openfe
import pytest
import pathlib
from openff.units import unit as offunit
import openfe
from openfe.protocols.openmm_afe import AbsoluteBindingProtocol
from openfe.protocols.openmm_utils.charge_... |
c68d4be66f55b647e91492b4a459a42d56a386a618562b15667de4f646293e42 | Python | 4,551 | 131 | from __future__ import absolute_import, division, unicode_literals
from collections import OrderedDict
import re
from pip._vendor.six import string_types
from . import base
from .._utils import moduleFactoryFactory
tag_regexp = re.compile("{([^}]*)}(.*)")
def getETreeBuilder(ElementTreeImplementation):
Elemen... |
2820379bbdd920efe5e36b1f6c1c7e36e37af9fa5bb2a5dece79606fa3c1238d | Python | 4,552 | 122 | """MultiQC submodule to parse output from Picard CollectIlluminaLaneMetrics"""
import logging
from collections import defaultdict
from typing import Dict
from multiqc.modules.picard import util
from multiqc.plots import table
# Initialise the logger
log = logging.getLogger(__name__)
def lane_metrics_table(module, ... |
d45a759bdef3df2a3501141ed649acf0005359d8625ae5eb28c86a1e33f6145c | Python | 4,552 | 156 | # This code is part of kartograf and is licensed under the MIT license.
# For details, see https://github.com/OpenFreeEnergy/kartograf
from importlib import resources
from importlib.resources import files
import pytest
from gufe import LigandAtomMapping, ProteinComponent, SmallMoleculeComponent
from rdkit import Chem... |
0948f704045c208f008a9a406095c0abd32caab4259119b7eae707cae0869c82 | Python | 4,554 | 142 | """
Configuration for the PaperQA agent.
"""
from dataclasses import dataclass, field
import os
from typing import Optional, List
from paperqa import Settings as PQASettings
from paperqa.settings import (
AnswerSettings,
ParsingSettings,
PromptSettings,
AgentSettings,
IndexSettings, Settings,
)
fr... |
d0b06ce3dfba20826a65b91d1af2dce9fbbe79313531541e2f96e0479e3489cd | Python | 4,554 | 123 | # This code is part of OpenFE and is licensed under the MIT license.
# For details, see https://github.com/OpenFreeEnergy/openfe
from .abstract_chemicalsystem_generator import (
AbstractChemicalSystemGenerator,
RFEComponentLabels,
)
from typing import Iterable, Optional
from gufe import (
Component,
S... |
5b59ee8c7ba6d5ff62e114293928eab10a3dfe642d694b4dce75c09901ec2f6f | Python | 4,555 | 159 | # Copyright 2016 Julien Danjou
# Copyright 2016 Joshua Harlow
# Copyright 2013-2014 Ray Holder
#
# 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
#... |
fa7480ac2d2d193d94440e4f40028d3d2c1bb914caf1db7f9f33d3fe5cbebc88 | Python | 4,559 | 193 | #!/bin/env python
"""
Module simtk.unit.math
Arithmetic methods on Quantities and Units
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 ... |
035e515b2e025948e3bd943abdf75442caf5b24540d6eb26a417e60764be98dc | Python | 4,561 | 128 | import numpy as np
from truesight.experiment.services import LLMRef
def calculate_mi(
evaluation,
baseline_llm: LLMRef,
student_llms: list[LLMRef],
latents: list[str],
**kwargs,
):
llm_slug_to_latent = dict()
for latent, student_llm in zip(latents, student_llms):
llm_slug_to_laten... |
a29fe0197705cbc775062722954e0ff91d66b08f0f8b631cf12bf93d3cc7b685 | Python | 4,576 | 119 | """Ablation: MRI2PET fine-tuning without the Laplacian-pyramid loss.
Same as ``tune_MRI2PET.py`` (loads ``mri2pet_base.pt``) but the
fine-tuning loss is the vanilla DDPM noise-prediction MSE only —
``includeLaplace=False``. Used to quantify the contribution of the
Laplacian-pyramid term.
Checkpoint: ``src/save/mri2pe... |
2000197eafbb7dca14121e7891ba1f948839ac27050f50ebbf6d6a33e8e4a971 | Python | 4,577 | 116 | import json
import logging
from multiqc.base_module import BaseMultiqcModule, ModuleNoSamplesFound
from multiqc.plots import table
log = logging.getLogger(__name__)
class MultiqcModule(BaseMultiqcModule):
"""
The KAT multiqc module interprets output from KAT distribution analysis json files, which typically... |
55ed41a2712c3b622d6e8a8f805bc6dfa453f0d7d27e940cfcfbfd0938b9ff8d | Python | 4,583 | 130 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
import numpy as np
from scipy.spatial import distance
def rot2trans(params, radius=50):
'''
Convert rotation (deg) to translation (mm) on a sphere with 50 mm radius (Power et al., 2014),
which approximates the average distance from the cortex to the center of ... |
f3113a2d896a86fd510ede65045640a742b89bb274746c796a98ae8f3cd81865 | Python | 4,583 | 110 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Script of evaluate the individual parcellation results
Created on 12/4/2023 at 4:22 PM
Author: Caro Nettekoven
"""
import numpy as np
import pandas as pd
import Functional_Fusion.dataset as ds
import HierarchBayesParcel.full_model as fm
from IndividualParcellation.scr... |
6ed63f92a6142e155e85d79403b6089cc5ca3cfc236b0912625a229c6a41fcbd | Python | 4,584 | 151 |
import numpy as np
from scipy.ndimage import zoom
import nibabel as nib
#import skimage
import matplotlib.pyplot as plt
from scipy import ndimage
#from skimage.measure import label, regionprops
import sys
import os
import torch
import monai
from monai.inferers import sliding_window_inference
from monai.networks.n... |
c6659656c4ed41ba98ce867089c13a525adea7fa9f3f31420299c361570ecc69 | Python | 4,588 | 136 | # -*- 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 ... |
0797aa1a709ea56d04cd7d26027ab8da3dd27106548fc260c16b79a2fce72a41 | Python | 4,589 | 136 | #!/usr/bin/env python3
import numpy as np
from glob import glob
import pandas as pd
import os.path
from tqdm import tqdm, trange
import sys
from collections import defaultdict
from pprint import pprint
from .common import process_all, true_basename, natural_keys, get_cam_name
def get_angle_fnames(config, session_pat... |
21861db34cf9f574009daa57c9790d7b9fd58a956c6ad66c1fcb05ea5bb06d39 | Python | 4,593 | 140 | # 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... |
0763890763050a0614c64aa2f5a7bf5d93a98f7ce276a9cb6fefa9ac3276bf6f | Python | 4,594 | 168 | """
MCP integration for the UniProt agent.
"""
import json
import os
from typing import Dict, Any, List, Optional
from anthropic import Anthropic
from pydantic_ai import Agent
# Import directly from the MCP module
from .uniprot_agent import uniprot_agent, UNIPROT_SYSTEM_PROMPT
from .uniprot_config import UniprotConfi... |
c80d696411dcadb7fc4ba42655b1b8e79f8f531696cbf67dd85faee60c66e415 | Python | 4,594 | 132 | """Plot distributions over subjects of within-subjects associations."""
import sys
from pathlib import Path
import warnings
from functools import partial
import numpy as np
import pandas as pd
import matplotlib as mpl
from matplotlib import pyplot as plt
import seaborn as sns
sys.path.append(str([p for p in [Path.c... |
75d46ace8bf48e5d4e1e1bfd8548744ff30f7e640ab99c9c00cf21b51e004942 | Python | 4,601 | 117 | """Ablation: pretrain by denoising noisy MRI conditioned on the same MRI.
A pretraining variant that bypasses the style-transfer step entirely:
the model learns to denoise heavily corrupted MRIs from their clean
counterparts. Acts as a sanity-check baseline for the pretraining stage —
how much of MRI2PET's benefit com... |
895c9f37ea2c857e5101459252c082b3c755ef7aedf7ae02fccb73028d17cb17 | Python | 4,602 | 131 | # 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,... |
e2e18d12a62bcf892eebf5b3a30aa2bee32f3747e3e57434dd6075e188dc3795 | Python | 4,613 | 131 | import itertools
import logging
import os
import posixpath
import urllib.parse
from typing import List
from pip._vendor.packaging.utils import canonicalize_name
from pip._internal.models.index import PyPI
from pip._internal.utils.compat import has_tls
from pip._internal.utils.misc import normalize_path, redact_auth_f... |
43a7b2f627cfad0f6a2a457440527cd0b307f76fbc7ee080b88635e55fd897fa | Python | 4,621 | 121 | import pytest
from unittest import mock
import pathlib
from openfe.storage.resultserver import ResultServer
from gufe.storage.externalresource.base import Metadata
from gufe.storage.externalresource import FileStorage
from openfe.storage.metadatastore import JSONMetadataStore
from gufe.storage.errors import (
Mi... |
dca9af60b0ffebb3bf1d34fd6a86ae3599f835c25570e2d601ee6e3e52024241 | Python | 4,621 | 116 | """
Copy of https://github.com/mkaranasou/pyaml_env/blob/main/src/pyaml_env/parse_config.py
With fixed https://github.com/mkaranasou/pyaml_env/issues/35
"""
import os
import re
import yaml
def parse_config(
path=None,
data=None,
tag="!ENV",
default_sep=":",
default_value="N/A",
raise_if_na=F... |
839a360dcb2c8b22d329920b1e651221df1d314b4ff314e56aa29d0279229509 | Python | 4,622 | 151 | import pandas as pd
import networkx as nx
from collections import defaultdict
import re
__all__ = ["path_to_tup","path_to_G", "get_all_paths", "get_id_to_type", "get_id_to_name", "get_id_to_name", "add_metaedges",
"add_meanode_pairs", "get_targets", "get_target_metaedges", "get_metapath_node", "get_metapath_... |
eab76231cf5fcddaf0ef49f91463138267872bae70cf2424a893c47c168e9d51 | Python | 4,623 | 134 | #!/usr/bin/env python3
import sys, os, re
import subprocess
import logging
import argparse
logging.basicConfig(stream=sys.stderr, level=logging.INFO)
logger = logging.getLogger(__name__)
def main():
parser = argparse.ArgumentParser(description="prep data on google cloud for use with terra and ctat mutations",
... |
57ebaf16db5843c1bd4f793a3b36c28eee9df2a494a5aa672fe8ee44baa8dd5c | Python | 4,627 | 165 | # This code is part of OpenFE and is licensed under the MIT license.
# For details, see https://github.com/OpenFreeEnergy/openfe
import json
import gufe
import openfe
import pytest
from gufe.tests.test_tokenization import GufeTokenizableTestsMixin
from pontibus.components import ExtendedSolventComponent
from pontibus... |
7051c28a1d7baffee73665f322d794cfcdfb11585ef796236abee14abb08e36a | Python | 4,629 | 110 | import os
import subprocess
import nibabel as nib
import argparse
import pandas as pd
import numpy as np
from numpy import shape
import scipy.stats as stats
import scipy.io
from scipy.signal import butter, filtfilt
from scipy import signal
from scipy.signal import detrend
# Parse command line arguments
parser = argpar... |
b268ab879c349d98a0f9b30ff65ac2bab8c578065b9c34322b9257003679530e | Python | 4,629 | 144 | # This code is part of OpenFE and is licensed under the MIT license.
# For details, see https://github.com/OpenFreeEnergy/openfe
import pathlib
import pytest
from openff.units import unit
from gufe.protocols import execute_DAG
from openfe.protocols import openmm_md
@pytest.mark.integration
@pytest.mark.parametrize('p... |
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