sha256 stringlengths 64 64 | language stringclasses 27
values | size int32 1 491k | lines int32 1 21.8k | content stringlengths 1 200k |
|---|---|---|---|---|
c193e08201b5c28b37f639e20f350a5e723ed10f248827b63dfcd155b7e1cb61 | Python | 5,410 | 130 | 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, loop_through_datasets
import itertools
from matplotlib import pyplot as plt
def stack_combinations(input_dict, exclude_pairs=None, merge_sizes=No... |
15b8825ca023939e4cb5a1d98a6acce8c9ed4b06df063ffc14765e90d45472d5 | Python | 5,413 | 121 | import os
import shutil
from time import sleep
import logging
import platform
import traceback
import requests
import zipfile
import pytest
from PySide6.QtCore import Qt
from gui.RaidionicsMainWindow import RaidionicsMainWindow
from gui.UtilsWidgets.CustomQDialog.ImportDataQDialog import ImportDataQDialog
from utils.... |
f3a02f107c55e240071ec936115aeafd26147308cd96c9ad205e909fa378eee6 | Python | 5,413 | 155 | """
# File : datasets.py
# Time : 2025/10/23 10:17
# Author : Hongmiao Wang
# version : python 3.10
# Description:
"""
import typing as T
import numpy as np
import torch
from Model.datasets.ProcessingFormula import generate_formula
from torch.utils.data.dataset import Dataset
def collater(tokens, p... |
2b6b247b08c64d9be5e243726ca244fe8e361854f1717583e3e49af4ed560d03 | Python | 5,419 | 157 | from py2neo import Node, Subgraph, Relationship, UniquenessError
from py2neo.cypher import cypher_join
from alchemiscale.storage.cypher import (
unwind_create_nodes_query,
unwind_merge_nodes_query,
unwind_merge_relationships_query,
)
from neo4j import Transaction
# overrides for py2neo comparison and se... |
72d83bf72032e3e738f897c5945c7c9bc85e5146a4eda61e209f4db798050d0c | Python | 5,424 | 189 | #!/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 scipy.spatial.transform import Rotation
from .common import make_process_fun, get_data_length, natural_keys
# project v onto u
def proj... |
1df9226145b85a9ab49f09186406df41fb33ea149a88eecf33118cfdb52f38c7 | Python | 5,426 | 159 | # -*- coding: utf-8 -*-
"""
Generates cortical flatmap for anterograde injections, retrograde injections, and swc soma locations.
Used for Fig 3d and Fig 4a.
Uses ccf_streamlines package, documented at https://ccf-streamlines.readthedocs.io/en/latest/
"""
import json,os
import numpy as np
import matplotlib.pyplot as p... |
021e0560a3df95cebbd2b16fa12e011bf077d7d6bec7c322ad64cc4465e759d4 | Python | 5,429 | 152 | import logging
from collections import defaultdict
from multiqc.base_module import BaseMultiqcModule
from multiqc.plots import linegraph, table
from multiqc.plots.linegraph import LinePlotConfig
from multiqc.plots.table_object import TableConfig
log = logging.getLogger(__name__)
class DragenGcMetrics(BaseMultiqcMod... |
5195af7499c335964ed968280304226cc0baf57e951ecea16bc3ac858e11d662 | Python | 5,430 | 107 | import sys
import os
import glob
import re
import gzip
import click
import loompy
import numpy as np
import random
import string
import csv
from collections import defaultdict
import logging
from typing import *
import velocyto as vcy
from ._run import _run
# logging.basicConfig(stream=sys.stdout, format='%(asctime)s ... |
8c5347094047aa058cc1a02dcfaa71fe793134ebb377038a76f0313e59f2604d | Python | 5,439 | 132 | import pytest
# Test models
from skimpy.core import *
from skimpy.mechanisms import *
import numpy as np
def build_linear_GEEK_pathway_model():
metabolites = ['A', 'B', 'C', 'D' ]
# Build linear Pathway model
UniUniGEEK = make_generalized_elementary_kinetics([-1,1], metabolites)
metabolites_1 = UniUn... |
e944dabdf094d8cb83c579512a2d7a8d65818ba74ec395c8ce548cea2b4ca479 | Python | 5,442 | 139 | from __future__ import annotations
import logging
import random
from dataclasses import dataclass
from logging import getLogger as get_logger
from typing import Any
from hydra.utils import instantiate
from lightning import Callback, Trainer, seed_everything
from beyond_backprop.algorithms import Algorithm
from beyon... |
34ec008e8a8dbe74998bd3c4c03e0ff5e0b916c2045c4949642b16ac81692964 | Python | 5,448 | 156 | # 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,... |
1ec064b0bfe5eff73697c2902e461fd47e8de2b85b3b5ae966118d58f0c0f437 | Python | 5,450 | 137 | # -*- 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 ... |
7c549cad3ef2e91436d2c0d93c08cd8bc27dc9a498208f1a9cd8457153b655f6 | Python | 5,450 | 186 | import time
import datajoint as dj
from ethopy.core.experiment import ExperimentClass, State
from ethopy.core.logger import experiment
@experiment.schema
class Condition(dj.Manual):
class Navigate(dj.Part):
definition = """
# Navigation experiment conditions
-> Condition
---
... |
a1b63f8e1fd64a791a6271751f448446ff8f9e8238887e7e34ae36e4cd237a1f | Python | 5,453 | 148 | """Tests for the seqkit stats module"""
import pytest
from multiqc.modules.seqkit.stats import parse_stats_report
# Sample seqkit stats output with all columns (--all --tabular)
SAMPLE_STATS_ALL = """file format type num_seqs sum_len min_len avg_len max_len Q1 Q2 Q3 sum_gap N50 N50_num Q20(%) Q30(%) AvgQual GC(%) s... |
82f19abdfafb2be4d4deb66610c5bd7af51175969411a18bd80927b59bdbfbc2 | Python | 5,458 | 140 | # -*- 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 ... |
f5ce233c97c356641be860be45ce1eca9dc63b05470f0fbe6be78975926df493 | Python | 5,458 | 181 | """Test data creation utilities for unit tests."""
import shutil
import tempfile
from pathlib import Path
from typing import Any, Optional
import anndata as ad
import numpy as np
import pandas as pd
def create_sample_anndata(
n_cells: int = 100, n_genes: int = 50, add_age: bool = True, add_batch: bool = False
)... |
c6c90b19ad7912c3613cf3a621470a4bb0aa8da440b56c4614d3cd4638f3f545 | Python | 5,463 | 192 | # -*- encoding: utf-8 -*-
#
# Copyright 2016–2021 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.... |
d29d924740212f35a657b2b44e2bd508104a198e6ae4841327c94af3b901283b | Python | 5,464 | 160 | #!/usr/bin/env python
# coding: utf-8
#------------------------------
# Import the needed libraries
#------------------------------
import argparse
import csv
import logging
import os
import subprocess
import pandas as pd
logging.basicConfig(level=logging.INFO,
format='%(asctime)s : %(levelname... |
4f2f49a513b8c2a16a3fd7c725cea024f0f66dd4170a7ec1cce1b92d8b3f153d | Python | 5,467 | 170 | """
Query Preprocessing Agent for Intelligent Ontology Routing
This agent analyzes queries and routes them to appropriate ontologies with refined keywords,
acting as a smart preprocessing layer before the existing search_terms function.
"""
from typing import List, Dict, Tuple
from pydantic_ai import Agent
QUERY_PR... |
84388832a6083a76457f85ffd10cdc96c86cb3374842f68e3b04880d0731a2ec | Python | 5,468 | 170 | from sys import argv
if len(argv) != 3:
print(f"Please pass the run id and embedding dimension, e.g. python {argv[0]} 1 10")
exit()
id = argv[1]
embeddings_dim = argv[2]
import os
from glob import glob
from pathlib import Path
import pickle
import numpy as np
import pandas as pd
import matplotlib.pyplot as p... |
1aa1b7605898e9a1d58020f4793897ae61649da9af664f4dbc16cac22386faf8 | Python | 5,469 | 144 | import logging
import re
from multiqc.base_module import BaseMultiqcModule, ModuleNoSamplesFound
from multiqc.plots import bargraph
log = logging.getLogger(__name__)
VERSION_REGEX = r"# BUSCO version is: ([\d\.]+)"
class MultiqcModule(BaseMultiqcModule):
"""
The module parses the `short_summary_[samplename... |
5952866a40e88676a9a571def59d3a41ac642de408ff24f8c1ab9d9780b27867 | Python | 5,470 | 165 | import gc
import urllib.request
import torch
from torchvision.io import read_image
import torch.nn.functional as F
import torchvision.transforms.v2.functional as TF
import torchvision.transforms.v2 as v2
import pytest
from seg import all_models, dice_loss, f1_score
ALL_MODELS = list(all_models())
augment = v2.Compo... |
9d0639c5f2ae995f5a3a87e7f0eeea09c23d50e2e182f2ab32f5df4d9ffadcce | Python | 5,470 | 134 | '''Plot the training data. Adjust the file as necessary (see comments in file)'''
import matplotlib.pyplot as plt
import os
import sys
sys.path.append("../")
import utils.tools as ut
import re
import numpy as np
import random
plt.rcParams.update({'font.size': 20})
parametermat = []
errormat = []
averagekernel = 10000 ... |
14ce212b5176e93f2857f53b62efa3b34e7cf39fbb55469fc50d0f3cebc0e437 | Python | 5,471 | 146 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Script of evaluate the individual parcellation results
Created on 18/10/2024 at 4:22 PM
Author: Caro Nettekoven
"""
import numpy as np
import TaskRest.paths as indiv_paths
import numpy as np
import matplotlib.pyplot as plt
import pandas as pd
import covariance as cov
... |
8b794aa25b7a04d99ad334928e4bdf114204825243894fc8cc08b6e71a2f7113 | Python | 5,471 | 163 | #!/usr/bin/env python3
import numpy as np
from glob import glob
import pandas as pd
import os.path
import cv2
from tqdm import tqdm, trange
from collections import defaultdict
from scipy import signal
import queue
import threading
from aniposelib.cameras import CameraGroup
from .common import make_process_fun, get_n... |
684b81762144efed7e0aaba91985154600fcafe8cc3bc1832f2a047de6b31303 | Python | 5,472 | 163 | """
viz/pareto.py — Fig 5-6: Efficiency-Performance Pareto Frontier
================================================================
"""
from __future__ import annotations
from pathlib import Path
from typing import Dict, Optional
import numpy as np
from .mdpi_style import (
FS_SMALL,
MDPI_DPI,
MDPI_WID... |
53d42a46f852d67383d12c63290727b84974b2b6a2013077c977dd31376cfe17 | Python | 5,474 | 140 | """
U-Net++ Architecture for Medical Image Segmentation
Implementation for MS3SEG Dataset
Reference:
Zhou et al., "UNet++: A Nested U-Net Architecture for Medical Image Segmentation"
Deep Learning in Medical Image Analysis, 2018
"""
import tensorflow as tf
from tensorflow.keras.layers import (
Input, Conv2D, MaxP... |
6d3e4c8f360e39ef5e996ad2741116e0dbe4b2db19b1a27bdc663c34b47aed15 | Python | 5,474 | 154 | import pytest
import json
import pathlib
from openfe.storage.metadatastore import (
JSONMetadataStore, PerFileJSONMetadataStore
)
from gufe.storage.externalresource import FileStorage
from gufe.storage.externalresource.base import Metadata
from gufe.storage.errors import (
MissingExternalResourceError, Changed... |
4da792abb69d5e04a01840302091fbde876ebebfece99263692dd4548f14cf1b | Python | 5,476 | 144 | from typing import *
import numpy as np
import velocyto as vcy
def jump_next_3p_exon(feature: vcy.Feature) -> vcy.Feature:
"""Jump to the next exon following transcription direction instead of chromosome coordinate
Arguments
---------
feature: vcy.Feature
An exonic feature
Returns
--... |
4c11022607a38f52742ea1a74c0445d2eb98e187c25b886cb6f3123c867238ac | Python | 5,487 | 201 | """
This script contains the code for control analysis 7, which creates a correlation matrix between the different features. In this script, a "naive correlation" approach is used, i.e. Pearson's r is computed between the features across the whole stimulus set.
@author: Alexander Lenders
"""
import numpy as np
import... |
81da9371fb64aa9a9ce895283c0b9fbbf3f7688589a02ae0fa6bd0bce466b631 | Python | 5,489 | 67 | import subprocess, os, sys
# input_list = [
# "/scratch/tweber/DATA/MC_DATA/STOCKS_DEV/2023-06-23-HGFLGAFX7/IMR90E6E7PD103s1p2x01/cell_selection/labels_raw.tsv",
# "/scratch/tweber/DATA/MC_DATA/STOCKS_DEV/2023-06-23-HGFLGAFX7/IMR90E6E7PD106s1p3x01/cell_selection/labels_raw.tsv",
# "/scratch/tweber/DATA/MC_... |
55b6defe9a2d3bea47423306445e53453a895035a126376ca83d85c148da3805 | Python | 5,492 | 176 | """Script to get initial PDBs for benchmark targets."""
from pathlib import Path
import requests
rcsb_url = "https://files.rcsb.org/view/"
def get_rcsb_file(pdb_id, pdb_path, model=None):
if pdb_path.exists():
return
with open(pdb_path, "w") as pdb_file:
# Get PDB text from RCSB website
... |
9e0bae14fcb15968646a2f91472ca93f90a2144e9eb6fa25936a007b1a83d932 | Python | 5,492 | 152 | # script to retrieve eye data from csv file
# copies eye data from saved location to BIDS folder
# loads eye data, cleans and downsamples and saves with the suffix _cleaned
# =============================================================================
import seaborn as sns
import matplotlib.pyplot as plt
import n... |
8d67d6e26ed414f4c772fb7404d73a1180bd6c93158abf356977ca2811367566 | Python | 5,493 | 153 | import logging
import re
from collections import defaultdict
from multiqc.base_module import BaseMultiqcModule
from multiqc.modules.qualimap.QM_BamQC import coverage_histogram_helptext, genome_fraction_helptext
from multiqc.plots import linegraph
# Initialise the logger
log = logging.getLogger(__name__)
class Drage... |
695b917f9b7792d5f13ff769fb877071c5993badf95632cd252f4b9403487a6e | Python | 5,501 | 138 | # -*- 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 ... |
8ca81d40573ab8b1e0102e17be967d261116de266f632411c0f64579af5a9b02 | Python | 5,501 | 164 | import numpy as np
from scipy import interp
import matplotlib.pyplot as plt
from sklearn.metrics import precision_recall_curve, roc_curve, auc
__all__ = ['graph_single_roc', 'graph_single_prc', 'graph_mean_roc', 'graph_mean_prc',
'graph_roc_boilerplate', 'graph_prc_boilerplate']
def graph_single_roc(y, ... |
c5f1167c9548d49721da24ea295cc6ec0f8b1824ef1fad893e3bb187c24fb00a | Python | 5,502 | 147 | import os
import numpy as np
import nrrd
from scipy.spatial.transform import Rotation
import matplotlib.pyplot as plt
from slicer_utils import GridSystem, SliceAnalyzer, Slicer
from sklearn.decomposition import PCA
from itertools import chain
# Storing the plane normal as constant (same slicing plane as Lam and Sherma... |
6b301c5d6650c808c6b3e0b4da8e45b1c7b1b2a006214bdb16c9242644de684b | Python | 5,504 | 156 | import glm
import trimesh
import numpy as np
# Utility function to convert morphologies to Trimesh objects in order to plot them with nemsi
def convert_to_mesh(morphology):
branches = morphology.segments
verts_list = []
faces_list = []
verts_cols = []
for i, branch in enumerate(branches):
... |
1dd01a552169bad2adee3f5908bb05abdc114c6625709bcc6a3218fe3545adab | Python | 5,507 | 137 | # 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 as offunit
import openfe
from openfe.protocols.openmm_afe import AbsoluteBindingProtocol
from openfe.protocols.openmm_utils.charge... |
b4dbac1190ab3f431fe88082590cdd282a3f8dd4a992e8f1d8ec9a75e7874899 | Python | 5,507 | 158 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
__author__ = "Vrushali Fangal"
__copyright__ = "Copyright 2014"
__credits__ = [ "Maxwell Brown", "Brian Haas" ]
__license__ = "MIT"
__maintainer__ = "Vrushali Fangal"
__email__ = "vrushali@broadinstitute.org"
__status__ = "Development"
####################################... |
f0e97b141daa80749e1a2f29926323ad988c5e24b3ce0d7ad1f8059cc074276f | Python | 5,509 | 103 | import os
import torch
import random
import nilearn
import numpy as np
from scipy import io
from PIL import Image
from tqdm import tqdm
import torch.utils.data as data
import matplotlib.pyplot as plt
from cn_clip.clip import load_from_name, image_transform
if __name__ == '__main__':
script_root = '/pu... |
fb144bd14d46d5d480c0dbfe30a448336b68af1cdcfc0e00afeae8309a29c96e | Python | 5,510 | 168 | import unittest
import tempfile
import os
import six
import caffe
class SimpleLayer(caffe.Layer):
"""A layer that just multiplies by ten"""
def setup(self, bottom, top):
pass
def reshape(self, bottom, top):
top[0].reshape(*bottom[0].data.shape)
def forward(self, bottom, top):
... |
1c1dcdeda863a3fcb13aeb6c24ab829a05c9d935eaacd7e8f641ef60fdc65770 | Python | 5,511 | 156 | # -*- 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 ... |
45cdd763f87deace63fa0eceba523357768a04efeab76274b58a45dc4dd90afb | Python | 5,514 | 150 | """
metrics.py
Contains computational functions for evaluating BCI task performance, including:
- Regression analyses (linear, polynomial)
- Correlation analyses (Spearman)
- p-value calculation and aggregation
"""
from collections import defaultdict
import numpy as np
from scipy.stats import combine_pvalues
from s... |
1ac476441234ad65dff9b93bb19b43e5572ca6658c91dfa83ea0d6c195dfb0bc | Python | 5,517 | 130 | from transformers import BartForConditionalGeneration
import torch
from Model.BART.base import BaseModel
import math
import torch.nn as nn
class BartEmbeddingLayer(nn.Module):
def __init__(self, config, embed_tokens: nn.Embedding = None):
super(BartEmbeddingLayer, self).__init__()
embed_dim = config... |
8ca6f262f90e02771f25db47b3c302152cd58bfe33af40304c8c2b88ed32142e | Python | 5,517 | 140 | import glob
import logging
import os.path
from pathlib import Path
from typing import Dict, List, Tuple
from multiqc.core.exceptions import RunError, NoAnalysisFound
from multiqc import config, report
logger = logging.getLogger(__name__)
def file_search():
"""
Search log files and set up the list of modules... |
a311452b1829c1fe79f0f7645a32fe151feeaa3515d4a4ebdcfec4953b473461 | Python | 5,518 | 169 | # !/usr/bin/env python
# -*-coding:utf-8 -*-
# @Time : 2023/04/25 14:59
# @Author : Liangdi.Ma
import numpy as np
import io
import os
import time
from collections import defaultdict, deque
import datetime
import torch
import torch.distributed as dist
from utils.link import is_dist_avail_and_initialized
... |
03df4c3b6f254a246a38112e68f478fbbd8f7212b90ba50c9aa4e50931241e31 | Python | 5,520 | 131 | import numpy as np
from scipy.cluster import hierarchy
from scipy.spatial import distance
import pandas as pd
from .plotting import compute_nw_linkage
from anndata import AnnData
def splitClusters(data, k, mn_key="MetaNeighborUS", save_uns=True):
"""Split Clusters using Hierarchical Clustering
This function... |
9747ab1eff9c3aca0f9f32c28318ffec421f9f4131547e06541bce6946b36436 | Python | 5,521 | 133 | import logging
import re
from multiqc.base_module import BaseMultiqcModule, ModuleNoSamplesFound
from multiqc.plots import bargraph
log = logging.getLogger(__name__)
VERSION_REGEX = r"Flexbar - flexible barcode and adapter removal, version ([\d\.]+)"
class MultiqcModule(BaseMultiqcModule):
def __init__(self):
... |
6ebc0b5c6c3f99d0ad4857d268c1edf569826a352438bafc6c7e62b0ef9f726f | Python | 5,526 | 152 | # cio.py
# Input-output functions for connectivity model
import Functional_Fusion.atlas_map as am
import nibabel as nb
import numpy as np
import warnings
import deepdish as dd
import json
def load_model(fname):
""" Loads model from a combination of a .h5 file and a .json file.
Args:
fname (str): File... |
a5a0484164561f73b0e92da3b64ab337f6a84ee055035c4ad09970f290bd8d22 | Python | 5,526 | 129 | # -*- 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 ... |
73f2f703af6442dd0f626612c62e48ddc76cdb74f25ef0dcf8a0873596b82f61 | Python | 5,528 | 132 | '''Plot the training data. Adjust the file as necessary (see comments in file)'''
import matplotlib.pyplot as plt
import os
import sys
sys.path.append("../")
import utils.tools as ut
import re
import numpy as np
import random
plt.rcParams.update({'font.size': 20})
parametermat = []
errormat = []
averagekernel = 10000 ... |
2aff34742b3c9a3160dfedafd78edb9141238b34ce605dbbb488e4be2279afb6 | Python | 5,529 | 144 | '''"""""""""""""""""""""""""""""""""""""""""""""""""""""""
This module gathers data from _overall_mean_cov.csv files.
It relies on the following official source:
Overall Mean Coverage Report, page 196.
https://emea.support.illumina.com/content/dam/illumina-support/documents/documentation/software_documentation/dragen-b... |
2dd0598521f5e0f9d8e5a83f8f1b517a949aaac612361dfad2566316b2308281 | Python | 5,532 | 173 | """Heartbeat monitor for the AVITI watcher.
Run from cron every ~15 min. Reads the heartbeat file written by watcher.py
on every poll iteration; if the heartbeat is older than --threshold-hours
(default 3h) and no alert email has been sent today, emails the recipient
via the system `mail` command (same mechanism the p... |
9be05aafdfb9caa883ddfb18c3535d84d112e42574e644b313f43c7797332b18 | Python | 5,539 | 109 | import logging
from typing import Dict, Union
from multiqc import config, report
from multiqc.core.file_search import include_or_exclude_modules
from multiqc.types import Anchor, ModuleId, SectionId
logger = logging.getLogger(__name__)
def order_modules_and_sections():
"""
Finalise modules and sections: pla... |
9cf894d735efeb0f7b553cd81520e24be2996743af2747b7f0d744233fd6ec43 | Python | 5,540 | 147 | """MultiQC submodule to parse output from Picard TargetedPcrMetrics"""
import logging
from typing import Dict
from multiqc import config
from multiqc.modules.picard import util
from multiqc.plots import bargraph
# Initialise the logger
log = logging.getLogger(__name__)
def parse_reports(module):
"""Find Picard... |
7f66d82d5188c3b16b61a55503ac8f7933c16c93c3aada9fb2f152e4754015fb | Python | 5,545 | 139 | import torch # type: ignore
import numpy as np
import seaborn as sns # type: ignore
from shap.plots import colors # type: ignore
import matplotlib.pyplot as plt
from matplotlib.colors import TwoSlopeNorm
# ============= Own modules =============
import sys
sys.path.append('../../Utils')
from preprocessing import KDiv... |
6bf42acc9436dfdf7b0d66f3996d3b3719cb6ddec4fa61f5f49c5b7f29e064f4 | Python | 5,546 | 122 | """Yield by input read pairs from `simplex-metrics` / `duplex-metrics` (fgbio CollectDuplexSeqMetrics plots #4a/#4b)."""
from typing import Dict, Optional, Set
from multiqc.base_module import BaseMultiqcModule
from multiqc.plots import linegraph
from .schemas import DuplexYieldMetric, SimplexYieldMetric
from .util i... |
331a5ea618669402215125d622f90c2d6ecab6876b52905b513812cbcb77ae4e | Python | 5,547 | 171 | import binascii
import math
import struct
import sys
import pytest
from shapely import geos_version, wkt
from shapely.geometry import Point
from shapely.tests.legacy.conftest import shapely20_todo
from shapely.wkb import dump, dumps, load, loads
@pytest.fixture(scope="module")
def some_point():
return Point(1.2... |
85a079275e5a87018330beff200189f8b5ea6e5e17cf98dc730627cec0e0b7f5 | Python | 5,551 | 172 | from __future__ import annotations
from dataclasses import field
from logging import getLogger as get_logger
from typing import Iterable, Sequence, TypeVar, Union
import rich
import rich.syntax
import rich.tree
import torch
from omegaconf import DictConfig, OmegaConf
from torch import Tensor, nn
from torch.nn.paramet... |
a3ed1bd369ccdf00de179bcd94b071a03d85784da8fe4d877636500e160335d0 | Python | 5,557 | 180 | """Graph embedding generation: Node2Vec + LINE (optional).
Node2Vec uses networkx + node2vec + gensim with workers=1 to avoid
joblib semaphore leaks in long-running processes (Optuna, multi-round sweeps).
LINE requires an external binary — this module provides I/O helpers.
"""
import networkx as nx
import numpy as np... |
a3a0f5f2723d75da8845b05c5ec2008bbe0bdd3c9b92981df7255ba724cf236d | Python | 5,558 | 166 | """
Copright © 2023 Howard Hughes Medical Institute, Authored by Carsen Stringer and Atika Syeda.
"""
# ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Network ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
import numpy as np
import torch
import torch.nn as nn
import torch.nn.functional as F
class FMnet(nn.Module):
def __ini... |
f113423400fc00ee676969cb2578cc44cf22c25cf1f5836f79951c7c462df5b8 | Python | 5,559 | 144 | """Tests for MULTIQC_* environment variable config handling."""
import os
import pytest
from multiqc import config
class TestEnvVarsConfig:
"""Tests for _env_vars_config() parsing MULTIQC_* environment variables."""
def test_bool_true(self, monkeypatch):
monkeypatch.setenv("MULTIQC_FORCE", "true")... |
ba94e38f0e2b28215edea5feeb7dfef669506665c670db14f0857b65df5726f1 | Python | 5,561 | 152 | """
Tools for the AmiGO agent.
"""
from typing import List, Dict
from pydantic_ai import RunContext, ModelRetry
from aurelian.agents.amigo.amigo_config import AmiGODependencies, normalize_pmid
from aurelian.agents.uniprot.uniprot_tools import normalize_uniprot_id
from aurelian.utils.data_utils import obj_to_dict
fro... |
ee28dedc5589ad6507fcbc764141630fffc2df9b10e096c21e2aff65eddb31ac | Python | 5,561 | 170 | # 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,... |
904c9531fc0f281ada61e69f0d5bb6f62642091b735e690d09bcaf962446c53b | Python | 5,562 | 165 | import os
import yaml
import logging
import numpy as np
import pandas as pd
from pathlib import Path
from typing import List
def keypoints_by_group(keypoints):
kp_by_group = {}
for kp in keypoints:
for group in kp["groups"]:
if group in kp_by_group:
kp_by_group[group].append... |
07c56d6b25735fa0c3a68416c29710772e051916d31e4258eaa63d1d00b833f1 | Python | 5,563 | 152 | """
UNETR (UNEt TRansformers) Architecture
Simplified implementation for MS3SEG Dataset
Reference:
Hatamizadeh et al., "UNETR: Transformers for 3D Medical Image Segmentation"
IEEE WACV, 2022
Note: This is a 2D adaptation. For full 3D implementation, refer to MONAI library.
"""
import tensorflow as tf
from tensorflow... |
22288b60bc7dc39fa6db8b9b5ddb43457a13d7802d80f03e0a453ae95baef6b7 | Python | 5,563 | 177 | # This code is part of OpenFE and is licensed under the MIT license.
# For details, see https://github.com/OpenFreeEnergy/openfe
"""
Reusable utility methods to validate input systems to OpenMM-based alchemical
Protocols.
"""
from typing import Optional, Tuple
from openff.toolkit import Molecule as OFFMol
from gufe imp... |
53076de869c8b906323e3a8acf3b722ada444fb80e31aa5eb31816852e003a61 | Python | 5,563 | 124 | ###################### Libraries ######################
# Deep Learning
import tensorflow as tf
import keras
from keras.models import Model, load_model
from keras.layers import Input, Conv2D, MaxPooling2D, Conv2DTranspose, concatenate
from keras import backend as K
from tensorflow.keras import layers, optimizers... |
147722e73a0ba2beaa8c0e1be73233237f6b855bad9c8f0e4ea6818a0725e11b | Python | 5,564 | 114 | import numpy as np
import copy
from expts.session import Session as S
from hardware.cameras import default_cam_params, cam1_params
from conditions import default_condition, conditions
from settings.manipulations import default_manipulation
from settings.durations import default_stim_phase_duration, default_delay_phase_... |
5f6729d32d1893d73544d71d66de6603f2075445bd847d61673cef242fd686d5 | Python | 5,564 | 163 | # -*- 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 ... |
07ddfe3b1d1fa55f1794b22d038a2eb6d2469efe2177284308ebae0bd1168e7f | Python | 5,566 | 158 | """Common fixtures for ethopy tests.
This module provides fixtures that can be used across multiple test files
to ensure consistent test setup and resource management.
All tests should use these fixtures to prevent database connections,
provide consistent mock objects, and avoid thread hangs.
"""
import os
import sy... |
2c092ac1e4ed0fade0a6a189e54b17583e3af3116b49c36a7db630fba978da7e | Python | 5,566 | 188 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
#
# aicsimageio documentation build configuration file, created by
# sphinx-quickstart on Fri Jun 9 13:47:02 2017.
#
# This file is execfile()d with the current directory set to its
# containing dir.
#
# Note that not all possible configuration values are present in this
#... |
f63e288cf6420e820d91e4ee017011ae0717bf4d270ee803596661c44a3f6c30 | Python | 5,566 | 130 | """`dedup --metrics` (one row per library plus `All Reads`) and `dedup --duplication-ladder`."""
import logging
from typing import Dict, Optional, Set
from multiqc.base_module import BaseMultiqcModule
from multiqc.plots import bargraph, linegraph
from .schemas import DeduplicationMetric, DuplicationLadderMetric
from... |
54db7e8ddde1fa1926f95eb97670b07082895c52e2bb2ceea2d6becb4c6a3aad | Python | 5,574 | 189 | """
Tools for the RAG agent for retrieval-augmented generation.
"""
import asyncio
from typing import Dict, List
from pydantic_ai import RunContext, ModelRetry
from aurelian.utils.data_utils import flatten
from aurelian.utils.pubmed_utils import get_pmid_text
from aurelian.utils.search_utils import web_search, retrie... |
d711ef0b9184af7d6faec18807576506fd1a9d1368676580db65e5e9992b0237 | Python | 5,584 | 162 | # -*- 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 ... |
62fc91076216fc3881d9a725b5f098583906b382dba493dde0afef72fb2447d5 | Python | 5,586 | 140 | import argparse
import cv2
from functools import partial
import numpy as np
import os
import time
from feabas.concurrent import submit_to_workers
from feabas import common, dal, config, storage
from feabas.mesh import Mesh
import feabas.constant as const
from feabas.renderer import MeshRenderer
Nthreads = config.get_... |
21c4041c2649bdd7ca7220029971822addfd628836fd0d9740a307a2303fda98 | Python | 5,589 | 174 | """Generate and work with PEP 425 Compatibility Tags.
"""
import re
from typing import TYPE_CHECKING, List, Optional, Tuple
from pip._vendor.packaging.tags import (
Tag,
compatible_tags,
cpython_tags,
generic_tags,
interpreter_name,
interpreter_version,
mac_platforms,
)
if TYPE_CHECKING:
... |
007a40b72a9c4c16b56b844016f3b7bbe3cafffa49fa6369ddb22cf52d1f3f3a | Python | 5,596 | 160 | # This code is part of OpenFE and is licensed under the MIT license.
# For details, see https://github.com/OpenFreeEnergy/openfe
from itertools import groupby
import numpy as np
from openfe import ProteinComponent
from openff.interchange import Interchange
from openff.toolkit import Molecule, Topology
from openmm imp... |
1307063e40c34f014ca62d8f04a84fb965f660130f732ecec755857169e8b9ac | Python | 5,598 | 162 | import logging
import shutil
import sys
import textwrap
import xmlrpc.client
from collections import OrderedDict
from optparse import Values
from typing import TYPE_CHECKING, Dict, List, Optional
from pip._vendor.packaging.version import parse as parse_version
from pip._internal.cli.base_command import Command
from p... |
802cf901d5c14cd73b0a961f26a31ca8332c9b7e02f347af94368bfe70bb936a | Python | 5,598 | 160 | # This code is part of OpenFE and is licensed under the MIT license.
# For details, see https://github.com/OpenFreeEnergy/openfe
from itertools import groupby
import numpy as np
from openfe import ProteinComponent
from openff.interchange import Interchange
from openff.toolkit import Molecule, Topology
from openmm imp... |
a29f5d44927589f019d7b0bc5a1c7f28f8ee452d68f24a61c14ad1eb17a629b2 | Python | 5,599 | 147 | from collections import Counter
import matplotlib.pyplot as plt
import networkx as nx
import numpy as np
import pyro
import pyro.distributions as dist
from pyro.infer import SVI, Trace_ELBO
from pyro.optim import ClippedAdam, Adam
from pyro.poutine import trace
from sklearn.decomposition import PCA
from sklearn.metrics... |
234cd56e93541696424ec80bef4a14fed8b51abd59ffffdfa5dc84fe8ce3c039 | Python | 5,602 | 160 | import numpy as np
from scipy.stats import norm
import deepdish as dd
def findcols(X):
# X is a dictionary with elements ir and jc
# returns a list of arrays of locations of nonzero entries in each column
cols = [None] * (len(X['jc'])-1)
for i in range(len(cols)):
cols[i] = X['ir'][X['jc'][i]:X... |
37f8ed3e9cb6e683def25cf54c93159087b06d671a536556af85179feaf8dd0e | Python | 5,603 | 132 | """Aggregate first-level fMRI GLM results.
Apply a brain mask, remove any scanner effects, and save the resulting
regression coefficients and their Cohen's d's at the level of the whole brain
and in networks and regions of interest.
"""
import sys
import warnings
from ast import literal_eval
from os import system
... |
1d2f7d6bb01cd661599ca1a6a8f85396d47c162c9813f035aa433cefc6c9c010 | Python | 5,612 | 167 | # This code is part of OpenFE and is licensed under the MIT license.
# For details, see https://github.com/OpenFreeEnergy/openfe
import pytest
from numpy.testing import assert_allclose
from openff.interchange import Interchange
from openff.interchange.components._packmol import solvate_topology
from openff.toolkit imp... |
e2dd13e064edc05a9067f520aedd0316c78ee7452851920ca5d2f011c60638ae | Python | 5,612 | 160 | """Comprehensive unit tests for evaluation modules."""
import os
import tempfile
from pathlib import Path
from unittest.mock import MagicMock, call, patch
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
import pytest
from timeflies.evaluation.interpreter import Interpreter
from timeflies.evalu... |
917f21816c24360132614c26bffa12669d22b97ef2f0f21923ec105f518af737 | Python | 5,621 | 145 | # -*- 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 ... |
d322dee079df050bb28641e6095f34fce231222540c79f649f34cc7a5a65c7cd | Python | 5,625 | 173 | # 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 numpy as np
import openfe
import pytest
from openff.units import unit as offunit
from pontibus.protocols.relative import HybridTopProtocolResult
class TestS... |
d9c86c87916ed3e294e531c44540d7845a5c8600a995451f2dbafd8f97025f83 | Python | 5,627 | 150 | # This code is part of OpenFE and is licensed under the MIT license.
# For details, see https://github.com/OpenFreeEnergy/openfe
"""Equilibrium Relative Free Energy methods using OpenMM and OpenMMTools in a
Perses-like manner.
This module implements the necessary methodology toolking to run calculate a
ligand relative ... |
ebf35fe7e8a7b4739b73ab1f4d19e23f93996421f526f95b9bc6b60f91f95eae | Python | 5,628 | 159 | """
This script creates random graphs for bunch of seeds.
Then it finds the motor modules as described and calculates
the adjacency matrices for each random graph.
"""
from pathlib import Path
import itertools
import pickle
import copy
import numpy as np
import pandas as pd
import networkx as nx
from tqdm import tqdm... |
50f7e0f808bf92b7857dc9946cf4da70714a09fe9b606595036dacca1f4337f2 | Python | 5,630 | 138 | import scipy
import numpy as np
from collections import Counter
def get_keypoints():
"""Return keypoints and angles to consider for head and legs."""
angles = {
'head': [
"Angle_head_roll", "Angle_head_pitch",
"Angle_antenna_pitch_L", "Angle_antenna_pitch_R",
],
... |
3845efa7ede0655cc33bd0e3cad3fdf95ab19a0a0f2f4594cd34449715d023f1 | Python | 5,637 | 191 | """Builtin Datasets"""
import abc
import os
import numpy as np
import pandas as pd
from tensorflow.keras.utils import get_file
from deepcell.utils import fetch_data, extract_archive
from deepcell_tracking.trk_io import load_trks
class Dataset(abc.ABC):
def __init__(self, url, file_hash, secure=False):
... |
6dfcc50d977b52a924012ee550cfc77986c0f87ce329f0e595efe99ffefdbe2a | Python | 5,638 | 124 | class AbstractProvider(object):
"""Delegate class to provide requirement interface for the resolver."""
def identify(self, requirement_or_candidate):
"""Given a requirement, return an identifier for it.
This is used to identify a requirement, e.g. whether two requirements
should have t... |
0eaf15242aec846218f26007c782c7dd457a0e6d6c14f7c0c5d7d75f5e59788d | Python | 5,642 | 146 | # -*- 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 ... |
293b8d377dc24d33705a1a2bb386ef6855e0fdff20dacf6943d5fe1c74d9728a | Python | 5,642 | 204 | # 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,... |
ce5c9f9edebf37488fea73b70639458a1bd5618f28413286b8e574e2d9cbb6cb | Python | 5,652 | 128 | #!/usr/bin/env python3
__author__ = 'Pavel Polishchuk'
import argparse
import numpy as np
import sys
from functools import partial
from read_input import read_input, assign_conf_props_to_mol
from rdkit import Chem
from rdkit.Chem.AllChem import GetConformerRMSMatrix
from multiprocessing import Pool, cpu_count
from sk... |
da5dc1b264e2314094a38ee18bf4f1180ed1c86d9f3d393be86d7e7eac1006e4 | Python | 5,655 | 127 | #!/usr/bin/env python
import glob
import os
import numpy as np
import json
bidsdir = './BIDS'
for subdir, dirs, files in os.walk(bidsdir):
for dir in dirs:
if 'anat' in dir:
searchdir = os.path.join(subdir, dir)
#print(searchdir)
for ImType in ["T1w", "T2w", "FLAIR"]... |
4fedb4c8a404e891c72e98cdcb9a4b1a694462f1e378e411f7e2711f9883b37b | Python | 5,657 | 143 | """MultiQC submodule to parse output from Picard GcBiasMetrics"""
import logging
from typing import Dict
from multiqc.modules.picard import util
from multiqc.plots import linegraph
# Initialise the logger
log = logging.getLogger(__name__)
def parse_reports(module):
"""
Find Picard GcBiasMetrics reports and... |
9ea521ee3812e7219eb09556336d06cdd6f0ce05ffe163bce5cfc01ffb400d9d | Python | 5,659 | 166 | import os
import numpy as np
from configparser import ConfigParser
import helper as hp
import sys
import pandas as pd
import helpers.helpers_latent as helperLatent
sys.path.insert(0, os.path.abspath(os.path.join(os.path.dirname(__file__), '..')))
# === Load configs ===
# latent specific configs
cfg= ConfigParser()... |
ccf378e47b0f3ef3b0a929ee37c10366afea9e64a4282550c8aecc6a175462f8 | Python | 5,661 | 166 | """
Copright © 2023 Howard Hughes Medical Institute, Authored by Carsen Stringer and Atika Syeda.
"""
import numpy as np
from scipy.ndimage import gaussian_filter
def fit_gaussian(im, sigma=2.0, do_xy=False, missing=None):
"""iterative fitting of pupil with gaussian @ sigma"""
ix, iy = im.nonzero()
if mis... |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.