sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
b3feaffcd8796daa426504aec74944c827011afab539fe593e9511b9e49b0714 | Python | 1,806 | 47 | # Copyright 2019 Novartis Institutes for BioMedical Research 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 http://www.apache.org/licenses/LICENSE-2.0. Unless
# required by applicable law... |
b91f48ed17d2a0b91c4280f405c8ac2752867529d993a7ad33108477be1e7b1d | Python | 1,806 | 51 | """myapp.py
This is a simple example of how to use the stamping feature.
It uses a custom stamping visitor to stamp a workflow with a unique
monitoring id stamp (per task), and a different visitor to stamp the last
task in the workflow. The last task is stamped with a consistent stamp, which
is used to revoke the task... |
43e7fd511b4acbebbf922a06b5dd0821fd2f38284f92b70a611310ecc424a29a | Python | 1,807 | 57 | from __future__ import division
import unittest
import numpy as np
from wyrm.types import Data, BlockBuffer
from wyrm.processing import append_cnt
from functools import reduce
class TestBlockBuffer(unittest.TestCase):
def setUp(self):
self.empty_dat = Data(np.array([]), [], [], [])
self.dat_1 ... |
474910e5ccdf2feac85fce3cba34e655416c6b820aee28b429d43fd1153796b2 | Python | 1,807 | 66 | import os
import subprocess
import pysam
try:
import cyvcf2
except ImportError:
pass
def build_filter_from_vcf_with_samtoolsshell(fn):
retval = os.popen(
"bcftools filter -e \"N_ALT != 1 || QUAL < 20 || maf[0]>0.05\" {} | grep -cv ^# ".format(fn)).read()
return int(retval.strip())
def build... |
642aa4d859cc3dc4ded1d60b0014fd09ef2de297a6a1a5c7a18cb8c6e161dee9 | Python | 1,807 | 57 | import h5py
import numpy as np
import tqdm.auto as tqdm
from permacache import permacache
from modular_splicing.dataset.dataset_aligner import DatasetAligner
from modular_splicing.data_for_experiments.standardized_sample import (
standardized_sample,
)
@permacache("dataset/dataset_by_gene_length/dataset_by_gene_... |
eb092c6ec1046308bdfc87400bc99e3196f45732c278def3fd0f2d8eb1a449ab | Python | 1,808 | 50 | from model import *
from utils import *
import numpy as np
import torch
import os
import warnings
warnings.filterwarnings("ignore")
TEST_BATCH_SIZE =256
model_name = 'ratio_0.9bach128LR_1e-4random_0_onehot.pt'
dataset = ['tmp','BindingDB_reg','JAK','AR','CYP_reg'][int(sys.argv[1])]
cuda_name = ['cuda:0','cuda:1','c... |
bc41518b1f0cb62c70b4c499af7a97ce5a60c06c1845aadb2a40eacb79e31887 | Python | 1,810 | 51 | # Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
#
# 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 app... |
7efd710ac26f0d89f422869ed9b27a39535092257433771c460f6f5665ed1ff1 | Python | 1,811 | 47 | """
The previous code generated ABF1 files which display properly in ClampFit but
not in MiniAnalysis. To assess why, the ABF converter was used to convert this
"unknown binary" format to an ABF with a header MiniAnalysis is comfortable
with. By inspecting that header we can see what needs to be changed to support
Mi... |
820fe475bcc9b64b96fc5d4fbf64a3cae76353816d9a622ccf79b7e3038c5c3d | Python | 1,811 | 52 | import os
from setuptools import setup
from setuptools import find_packages
import sys
if sys.version_info[:2] < (3, 8):
raise RuntimeError("Python version >= 3.8 required.")
# load the description
PATH_HERE = os.path.abspath(os.path.dirname(__file__))
with open(os.path.abspath(PATH_HERE+"/README.rst")) as f:
... |
cc79beea28eb17167acfb7b1d15d14073a66eb4f682245d8de77e5300ea4da79 | Python | 1,811 | 69 | from torch.utils.data.dataloader import DataLoader
from torch.utils.data.dataset import IterableDataset
from modular_splicing.utils.construct import construct
from modular_splicing.utils.io import load_model
from .motif_selector import (
MotifIncrementalAdder,
MotifIncrementalDropper,
)
def train(
*,
... |
e2455dfaad46857789caaa039907be595a4a3ed896fd809f87c68e27e75dada1 | Python | 1,811 | 57 | import sys
from robustness import datasets
from robustness.attacker import AttackerModel
from robustness.model_utils import make_and_restore_model
from model_analysis_folders.all_model_info import IMAGENET_PATH, MODEL_BASE_PATH
def build_net(ds_kwargs={}, return_metamer_layers=False):
# We need to build the datase... |
4acf54c69435629744e2ca1dde2e405f2ce5b5120a944ea18b255c5623264bdc | Python | 1,812 | 47 | from unittest import TestCase
from drug_interactions.reader.dal import Drug, DrugBank
class DrugTestCase(TestCase):
def setUp(self):
self.drug1 = Drug(**{'id_': '1', 'interactions': [('3', 'bar')]})
self.drug2 = Drug(**{'id_': '2', 'interactions': [('3', 'baz')]})
self.drug3 = Drug(**{'id... |
6e51a021b5767d1fcfed4402ed781fcc56bf1f5a92f7a20c7bd4d941995ab9ed | Python | 1,812 | 43 | from typing import Tuple, Union
import numpy as np
def estimate_basic_bootstrap_CI(
alpha: float,
point_estimate: Union[np.ndarray, np.generic, float, int], # [*]
bootstrapped_point_estimates: np.ndarray, # [n_bootstraps, *]
) -> Tuple[float, float]:
"""
Estimates the basic confidence interval ... |
cf436f2154cf58e488b298628d08196eb4de2f233c5da75cba8667ddf1c04392 | Python | 1,812 | 60 | import numpy as np
import scipy.io
# Code adapted from Mineault et al. 2021
def load_mat_as_dict(the_path: str):
"""Loads a mat file as a dictionary.
Arguments:
the_path: a string containing the path of a mat file.
Returns:
The mat file, formatted as a dict instead of a weir... |
f6a9eb22424b69af7f2612ef606145ac690867e86890d5abf0cbbb7f45879295 | Python | 1,812 | 52 | import argparse
from pathlib import Path
import jupytext
import nbformat
from nbformat import NotebookNode
def add_installation_cell(nb: NotebookNode, script_path: Path) -> NotebookNode:
# Find installation snippet
with open(script_path, "r") as f:
for line in f:
line = line.strip()
... |
073352b2d2376393785416293a5ab339590034ace427c96afe9addc2bf4f7bd0 | Python | 1,813 | 38 | from pathlib import Path
from pydantic_settings import BaseSettings, SettingsConfigDict
# The root of the repository
ROOT_DIR = Path(__file__).parent.parent.parent
PKG_DIR = ROOT_DIR / "neurogym"
CONFIG_DIR = PKG_DIR / "config"
# Set LOCAL_DIR to the current working directory. This path is dynamic and depends on
# wh... |
20f5dde58f983bd770fc12a4070f2169b32f42b8a8de764af69412995fb9add1 | Python | 1,813 | 61 | #!/usr/bin/env python
from distutils.core import setup, Extension
from distutils.command.build_ext import build_ext
import git
class CustomBuildExtCommand(build_ext):
"""build_ext command for use when numpy headers are needed."""
def run(self):
# Import numpy here, only when headers are needed
... |
374cc9a12dfb1937505098099b208c01ccbc9adc93f945ec40712f191e0244cf | Python | 1,813 | 62 | from __future__ import annotations
import os
import pytest
from pytest_celery import CeleryTestWorker, defaults
from pytest_docker_tools import build, container, fxtr
from celery import Celery
from t.smoke.workers.dev import SmokeWorkerContainer
class OtherSmokeWorkerContainer(SmokeWorkerContainer):
"""Alterna... |
41e7842c65164b04d3fea0d0a4518c205748caa426ad5312c5892fa23fc32e30 | Python | 1,813 | 60 | from abc import abstractmethod
from modular_splicing.motif_names import get_motif_names
from .trainer import AutoMinimizingTrainer
from modular_splicing.utils.construct import construct
class MotifSelector(AutoMinimizingTrainer):
def __init__(self, *args, names_spec, **kwargs):
super().__init__(*args, **... |
69fd8178375c70027a9fee6803a553f175201da0e0121a7e4e3fad5b147afa40 | Python | 1,813 | 77 | from __future__ import annotations
from pathlib import Path
import polars as pl
def scan(path: str | Path) -> pl.LazyFrame:
"""Scan a GFF or GTF file.
Parameters
----------
path
The path to the GTF file.
Returns
-------
pl.LazyFrame
A lazy frame with columns: seqname, s... |
0678f9a333c0eb003fe9d2e95553a670e180849278e19f9e2711f09eaacd2848 | Python | 1,814 | 53 | from __future__ import annotations
from typing import TYPE_CHECKING
import numpy as np
from gymnasium import Wrapper
from neurogym.utils import spaces
if TYPE_CHECKING:
from neurogym.core import TrialEnv
class PassAction(Wrapper):
"""Modifies observation by adding the previous action."""
metadata: di... |
6b1e76727660661e1d990a6dd18ce93d130d1034d242308f59b125325a50ddef | Python | 1,814 | 46 | import os
import tempfile
from ethoscope.core.monitor import Monitor
from ethoscope.drawers.drawers import DefaultDrawer
from ethoscope.hardware.input.cameras import MovieVirtualCamera
from ethoscope.hardware.interfaces.interfaces import HardwareConnection
from ethoscope.io import ResultWriter, SQLiteResultWriter
from... |
ecbc93e230c194a0c4980b017757c5eb4c312b55c9e1c60f7185d0e1d8c3341d | Python | 1,814 | 56 | """ Norm Layer Factory
Create norm modules by string (to mirror create_act and creat_norm-act fns)
Copyright 2022 Ross Wightman
"""
import types
import functools
import torch.nn as nn
from .norm import GroupNorm, GroupNorm1, LayerNorm, LayerNorm2d
_NORM_MAP = dict(
batchnorm=nn.BatchNorm2d,
batchnorm2d=nn.... |
f175907f7570b62ff804520b2602afa9c8c4d35d3fa6d95a160f1af3bf296e83 | Python | 1,814 | 58 | import http.server
import json
import socketserver
import logging
from src import config
from src import sba_api
from legacy.rpc_interface import RpcInterface
logger = logging.getLogger(__name__)
# Simple configuration
PORT = config.PORT
# State
sba_interface = None
neuriteLengthDistribution = None
mySomaLocations =... |
662f14465d5e5f528e5a4551d57ffb7465f6e5bfefde6b707eb061a75ad19d51 | Python | 1,815 | 40 | from src.mesoscale_extractor import NeuronPopulation
from src.utils import *
# import src.convertAllenSpace as CAS
data_repository = 'atlas_files'
## Initialize the NeuronPopulation class with the requested source and target areas from which the statistics will be derived
neuropop_cls = NeuronPopulation(data_path = d... |
c08b7f8cd18c77ff216ac9f088c8cfe2dc90310fc92208f65596fd57f0a3f097 | Python | 1,815 | 57 | # coding=utf-8
# Copyright 2025 The Google Research Authors.
#
# 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 applicab... |
f8625d4ec08a2e05833dafa63f621d00701cc2fef514f4c94cf0f41ec8b99080 | Python | 1,815 | 54 | import os
from mirp._images.generic_image import GenericImage
from mirp._images.mr_dce_image import MRDCEImage
from mirp.extract_features_and_images import extract_features_and_images, extract_images
CURRENT_DIR = os.path.dirname(os.path.abspath(__file__))
def test_basic_dce_mr_feature_extraction():
# Separate ... |
27785ce7a5996b5d515633ef96df9b1259cd53e7bd4c45b5fa51f7a44a170d74 | Python | 1,816 | 62 | #!/usr/bin/env python
# Created on: December 13, 2013
__author__ = "Sven Kreiss, Kyle Cranmer"
__version__ = "0.1"
import optparse
parser = optparse.OptionParser(version=__version__)
parser.add_option("-i", "--input", dest="input", default=None, help="Input folder.")
parser.add_option("-f", "--inputFull", dest="in... |
6e009a2ea95e4347104b0a9e2bc509699adac741090dd2745988b2f894cd29f2 | Python | 1,816 | 56 | import subprocess
def remove_docker_image(image_name):
# Remove containers using the image
try:
container_rm_command = [
"docker",
"rm",
"-f",
"$(docker ps -a -q --filter ancestor=" + image_name + ")",
]
subprocess.run(container_rm_comman... |
76770df7d2ce164bc5471a6a154cd6a7fd8baa546e8cbb69862a1ed11c05fc72 | Python | 1,816 | 37 | """Prepare cycle gan datasets"""
import os
import argparse
import zipfile
from gluoncv.utils import download, makedirs
def parse_args():
parser = argparse.ArgumentParser(
description='Initialize Cycle Gan dataset.',
epilog='Example: python download_dataset.py --download-dir ./',
formatter_c... |
9a788288734e30594e51fa23ad5e0e2eaf8a03176c7fe44c991b825e078a56cc | Python | 1,816 | 57 | """Add Notification System tables
Revision ID: 2d749563e1fe
Revises: b855b714e8b8
Create Date: 2023-03-02 15:16:36.737075
"""
import sqlalchemy as sa
from galaxy.model.custom_types import JSONType
from galaxy.model.migrations.util import (
create_table,
drop_table,
transaction,
)
# revision identifiers... |
a3a0cf73d715526cbbb784196b84e514e989e2fcdcd1d57e86b5c9933d779c0f | Python | 1,817 | 72 | """First five minutes with TorchLens interventions.
What this demonstrates
----------------------
Capture a tiny model, discover the ReLU site, fork the log, zero-ablate that
site, and replay the saved DAG.
How to run
----------
``python examples/intervention/01_first_five_minutes.py``
Runnable by default. No extern... |
0ec1435938491abd3770dfb425177f28dc5c21bf72ddf401968ac29f4ebfb156 | Python | 1,818 | 59 | from sys import argv
from msp import MSP
msp = MSP()
msp.file = __file__
msp.seed = int(argv[1])
msp.architecture["num_motifs"] = 82
msp.architecture["sparse_spec"] = dict(type="SpatiallySparseAcrossChannels")
msp.architecture["motif_model_spec"] = dict(
type="AdjustedMotifModel",
model_to_adjust_spec=dict(
... |
0f17bf8cf616f899133c4df1587c7b170671874a0ff2c6d054c5014ada6c8bd7 | Python | 1,818 | 72 | """Ordering contract tests for :func:`torchlens.extract_dataset`."""
from __future__ import annotations
from pathlib import Path
import torch
from torch import nn
import torchlens as tl
class _OrderRevealingModel(nn.Module):
"""Return a deterministic affine transform that preserves row identity."""
def _... |
69768fa5ff5583a4285c6a6810551d0f70b377b0ca2d9971c9c7f061087aa36a | Python | 1,818 | 46 | import os
import shutil
from src.AcquisitionParameters import AcquisitionParameters
from src.InstrumentController import InstrumentController
class AcquisitionControl:
# controller: InstrumentController
def __init__(self):
self.controller = InstrumentController()
def runAcquisition... |
7db558836b3c0d741d8981d436e56314cb44260e2877555e8f6e668078460eed | Python | 1,818 | 50 | # -*- coding: utf-8 -*-
# tests for metrics.py
""""tests for clustering metrics"""
import unittest
import numpy as np
from sknetwork.clustering import get_modularity, Louvain
from sknetwork.data import star_wars, karate_club
from sknetwork.data.test_graphs import test_graph
class TestClusteringMetrics(unittest.Test... |
fc1ca5ff0d1d0c4254ae56b6f1d8118460fa3f5edc8613215af057c87ae9dc35 | Python | 1,818 | 50 | # LICENSE
#
# _This file is Copyright 2018 by the Image Processing and Analysis Group (BioImage Suite Team). Dept. of Radiology & Biomedical Imaging, Yale School of Medicine._
#
# BioImage Suite Web is licensed under the Apache License, Version 2.0 (the "License");
#
# - you may not use this software except in compl... |
0d912fac7c1e90d57e855da4dee73fba3a1f31863fc05def69ea28f5c55f47d5 | Python | 1,819 | 47 | import torch
import torch.nn as nn
import torch.nn.functional as F
class MLP(nn.Module):
def __init__(self, num_layers, input_dim, hidden_dim, output_dim):
'''
num_layers: number of layers in the neural networks (EXCLUDING the input layer). If num_layers=1, this reduces to linear model.
... |
08a7603ec8c95e0321aa3a29dcd11af95e3be548f470245be5d0108513b1791d | Python | 1,820 | 49 | # LICENSE
#
# _This file is Copyright 2018 by the Image Processing and Analysis Group (BioImage Suite Team). Dept. of Radiology & Biomedical Imaging, Yale School of Medicine._
#
# BioImage Suite Web is licensed under the Apache License, Version 2.0 (the "License");
#
# - you may not use this software except in compl... |
27df50d19eb1547ff438db2905e8098b01894a99f75f69aa6ceb1db3471994c9 | Python | 1,820 | 53 | #!/usr/bin/env python
"""
Adds Manually created builds and chrom info to Galaxy's info tables
Usage:
python add_manual_builds.py input_file builds.txt chrom_length_dir
"""
import os
import sys
def add_manual_builds(input_file, build_file, chr_dir):
# determine existing builds, so as to not overwrite
existi... |
819085043854679cb041bfedd8e6ac53195a0dc4f4b2bdb9fb6765dfbd43d640 | Python | 1,821 | 33 | from setuptools import setup, find_packages
setup(
name = "bio-past",
version = "1.6.3",
keywords = ["pip", "past"],
description = "PAST: latent feature extraction with a Prior-based self-Attention framework for Spatial Transcriptomics",
long_description = "PAST software is build on a variational g... |
848ac77c6fff8658fb214fcbf43c535a908f2466d180c2804546c220aed69f80 | Python | 1,821 | 41 | #Hopfield Networks created as described by:
# Wulfram Gerstner, Werner M. Kistler, Richard Naud, and Liam Paninski.
# Neuronal Dynamics: From Single Neurons to Networks and Models of Cognition.
# Cambridge University Press, 2014.
#Run for simulation of CRFS in:
#Identification of Pattern Completion Neurons in N... |
9eaf8344002c5941e012b960884160158e75d353d0629a334939a573527033b9 | Python | 1,821 | 62 | from dotenv import load_dotenv
import torch
from omop_learn.omop import OMOPDataset
from omop_learn.torch.models import VisitClassifier, VisitTransformer
load_dotenv()
config = Config({
"path": os.getenv("DATABASE_PATH"),
"cdm_schema": os.getenv("CDM_SCHEMA"),
"aux_cdm_schema": os.getenv("AUX_CDM_SCHEMA... |
b414b693f199d981d7bca1b24912f83cc3cf393ddf6911a019d1eb2aacaa7810 | Python | 1,821 | 65 | """Parameter definition for Modes."""
from specparam.reports.strings import gen_params_str
###################################################################################################
###################################################################################################
class ParamDefinition():
... |
ef2ee8525e4f0b7161442433f0040565f157dff8be041f3339acd452105bf76a | Python | 1,821 | 62 | import pandas as pd
import matplotlib.pyplot as plt
import numpy as np
import re
import spacy
import pickle
import time
from collections import defaultdict
import pmi_tfidf_classifier as ptic
path = "../data/"
np.random.seed(250)
#spacy.prefer_gpu()
#nlp = spacy.load("en_core_sci_sm", disable=['ner', 'parser'])
data_... |
8312fa563855552df566b4de3fe27daf649c1f49afe8d67fc35a32de38fd5a42 | Python | 1,822 | 57 | import sys
from robustness import datasets
from robustness.attacker import AttackerModel
from robustness.model_utils import make_and_restore_model
from model_analysis_folders.all_model_info import IMAGENET_PATH, MODEL_BASE_PATH
def build_net(ds_kwargs={}, return_metamer_layers=False):
# We need to build the datase... |
c4e13fe76d821a6a65942ef66b1fc4a08f172746acf87242194f9ebefb51ef89 | Python | 1,822 | 68 | # Author: aqeelanwar
# Created: 2 May,2020, 2:49 AM
# Email: aqeel.anwar@gatech.edu
from tkinter import filedialog
from tkinter import *
import cv2, os
mouse_pts = []
def get_mouse_points(event, x, y, flags, param):
global mouseX, mouseY, mouse_pts
if event == cv2.EVENT_LBUTTONDOWN:
mouseX, mouseY =... |
42e82bc280dc82bef549a6071ae5d43bc69f3909e7c264674cf91b1ec959d16e | Python | 1,823 | 53 | __author__ = 'quentin'
import cv2
import numpy as np
from ethoscope.roi_builders.target_roi_builder import TargetGridROIBuilder
from ethoscope.roi_builders.target_roi_builder import TargetGridROIBuilder
import itertools
class HD12TubesRoiBuilder(TargetGridROIBuilder):
_description = {"overview": "The default sle... |
a6fba570853af01d506576c5406392237a87e35f4517bd4ad5fd27737e56e2ad | Python | 1,824 | 40 | """
Generate predictors for word-level variables
See the `explore_word_predictors.py` notebook for more background
"""
from pathlib import Path
import eelbrain
# Define paths to source data, and destination for predictors
DATA_ROOT = Path("~").expanduser() / 'Data' / 'Alice'
STIMULUS_DIR = DATA_ROOT / 'stimuli'
PRE... |
ff15773b3f8acfea07d41096026df3db9c6fa7c9ce52269aff367cd4c07525f2 | Python | 1,824 | 63 | import numpy as np
import scanpy as sc
from scipy.optimize import linear_sum_assignment
from scipy.stats import pearsonr
from sklearn import metrics
from sklearn.cluster import KMeans
from sklearn.metrics.pairwise import cosine_similarity
def pearsonr_error(y, h):
res = []
if len(y.shape) < 2:
y = y.r... |
d47bb2cb2c1f15a275a4e172f5ff817c5f5eb47cacfc79d417ae211bb440d6e2 | Python | 1,825 | 50 | # coding=utf-8
# Copyright 2026 The Google Research Authors.
#
# 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 applicab... |
8100a23d815f833e6827f64ebd10df0c1571cf04c2a3a36462cb9cbeb9ccd976 | Python | 1,826 | 38 | import unittest
import pysam
import os
from svim.SVIM_COLLECT import retrieve_other_alignments
class TestSAExtraction(unittest.TestCase):
def setUp(self):
TESTDATA_FILENAME = os.path.join(os.path.dirname(__file__), 'chimeric_read.sam')
self.samfile = pysam.AlignmentFile(TESTDATA_FILENAME, "r")
... |
8d586742cb69bfc5146b10ceb5d3386008e1c05c613819500af4cde202765a76 | Python | 1,826 | 64 | """Thread execution pool."""
from __future__ import annotations
from concurrent.futures import Future, ThreadPoolExecutor, wait
from typing import TYPE_CHECKING, Any, Callable
from .base import BasePool, apply_target
__all__ = ('TaskPool',)
if TYPE_CHECKING:
from typing import TypedDict
PoolInfo = TypedDic... |
a4b8a0f1a6ca113f5dc74f9695b0063804a9d99d14d54564a119ed50d2681016 | Python | 1,826 | 56 | from tqdm import tqdm
import pandas as pd
def get_atoms(atoms, mp_params, width_coeff=1):
columns = ['iteration', 'modulus', 'amplitude', 'width', 'frequency', 'phase', 'struct_len', 'absolute_position', 'offset',
'ch_id', 'ch_name']
dtypes = {'iteration': int, 'modulus': float, 'amplitude': fl... |
d89453d947e0b34258d8b0e3b3bc58dd23a785d25da77b1f9e4cea51ba461b24 | Python | 1,826 | 53 | import os
import simplekml
from tqdm.auto import tqdm
from .geotif import get_geoms
def preds_to_kml(df, data_folder, kml=None):
"""
Creates a simplekml kml object with polygons of given files. Polygons are green if correctly predicted and
red if falsely predicted.
:param files: list of files of wh... |
05075695db2066f3581b1a7a1eba821539584dc21ddc92e753ef3031e1037e59 | Python | 1,827 | 53 | import torch
import torchmetrics
METRIC_REGISTRY = {
"r2score": torchmetrics.R2Score,
"pearson": torchmetrics.PearsonCorrCoef,
"spearman": torchmetrics.SpearmanCorrCoef,
"explainedvariance": torchmetrics.ExplainedVariance,
"auroc": torchmetrics.AUROC, # can be binary, multiclass, or multilabel, ca... |
14d71d33c3cb75520600d583cf432031b7672053d5274984835721f74bfffa81 | Python | 1,827 | 55 | """
A small collection of clustering algorithms. Some algorithms are in a naive implementation.
More mature implementations can be found in `scikit-learn`.
"""
import numpy as np
from numba import jit
from .conv_squares_ import csq_find_rois, csq_plot_rois
from .dbscan_ import dbscan
from . import metrics
#from . imp... |
23bbbe32bc831f9e4d8f56959684c200807486fb856cb9d190fa466374e0ccd9 | Python | 1,827 | 40 | import unittest
from unittest import mock
from codecarbon.core.slurm import warn_on_multi_rank_double_counting
from codecarbon.emissions_tracker import OfflineEmissionsTracker
class TestMultiRankWarning(unittest.TestCase):
def _warnings(self, tracking_mode="machine", **env):
with mock.patch.dict("os.envi... |
a3d20ebd8b4543542df5ed9a117ab28e254e26f47e7027498cf6e1f47dbdf158 | Python | 1,827 | 47 | import sys
# setting path
sys.path.append('../TM2_segmentation')
import os
import numpy as np
import nibabel as nib
import itk
import pandas as pd
import tarfile
from scripts.preprocess_utils import find_file_in_path, register_to_template
# load metadata file
input_annotation_file = 'data/csv_files/aomic.tsv'
... |
bdb247afd6ccd8413e63dc978cea98c863df28c7a62496c1a47c5dce1e2f4f7a | Python | 1,827 | 62 | """
Author: Derek van Tilborg -- TU/e -- 23-05-2022
Basic Multi-Layer Perceptron
"""
import torch
import torch.nn.functional as F
from torch.nn import Linear, Dropout
from MoleculeACE.models.utils import NN
import os
class MLP(NN):
def __init__(self, feat_in: int = 1024, n_layers: int = 3, hidden: int = 512, d... |
5333b730077eccc20c2eb4f3f2dae58e8dcb377dad3230afb0539400fb52a77f | Python | 1,829 | 68 | from sys import argv
from msp import MSP
msp = MSP()
msp.file = __file__
msp.seed = int(argv[1])
msp.architecture["num_motifs"] = 82
msp.architecture["motif_model_spec"] = dict(
type="AdjustedMotifModel",
model_to_adjust_spec=dict(
type="PSAMMotifModel",
motif_spec=dict(type="rbns"),
e... |
6582d2962fe1af6f22546a91be6d4b751793a2c584c3c806fe0a3bceddc2f098 | Python | 1,830 | 50 | #!/usr/bin/env python
# coding: utf-8
"""
Plot sensor-level RDMs
----------------------
This example demonstrates how to visualize representational dissimilarity matrices
(RDMs) computed from EEG data. We will compute them using a spatial searchlight and plot
the RDM computed for each searchlight-patch.
| Authors:
|... |
6c172fafb7ba4b49c560f669f5918024b94fb2a63b21965e7df85e90b74ef36e | Python | 1,830 | 56 | import tensorflow as tf
from tensorflow.keras.layers import Dropout, Dense, GRU, Bidirectional
class CharSmilesConfig():
def __init__(self, gru_layers: int=2, gru_units: int=32, gru_dropout_rate: float=0.2,
dropout_rate: float=0.2, num_classes: int=1, **kwargs):
self.gru_layer... |
a583027ec99786251c1d08e92f9984b6f3c2e98e3bdbef54468ee4a80234960d | Python | 1,830 | 55 | """`ParamRegistry.compute` on a parameter that has not been realized yet.
`kdict` is filled lazily: a key is instantiated the first time something asks
for it. `get` calls `update_kdict` before indexing, but `compute` indexed
`kdict` directly, so computing a parameter nobody had touched raised a bare
`KeyError`. The c... |
399f2316713521e3fe04a3605199ea59f0d07dc9e2439149acef86f8807c9140 | Python | 1,832 | 58 | import csv
import copy
#Функция, определяющая взаимодействие по главной/вспомогательной субъединице. X — цепь рецептора, Y — лиганда.
def site(X,Y):
if (X, Y) in (('A', 'D'), ('B','E'), ('C','F')):
return '+'
if (X, Y) in (('C', 'D'), ('A','E'), ('B','F')):
return '–'
Data="{}.csv"
Types=['HB','PHO... |
2412c996e214f5e699f140cf696c2d959039dd0f30cf577c3ee31553325f04d4 | Python | 1,833 | 56 | """
This module create TransformerClassifPerProt
"""
# pylint: disable=W0223
import torch.nn as nn
import torch
class TransformerClassifPerProtApriori(nn.Module):
"""
This class define a Transformer model that classify an entire protein to ONE classe
"""
def __init__(self, transformer_embedder, num_c... |
2a53e0880e43a06048b284f7cc46be77760bf62ce917a429114631c35514a94a | Python | 1,833 | 71 | """
ca_plots.py
Modules for calcium imaging plots.
"""
import matplotlib.pyplot as plt
from matplotlib.pyplot import style
from scipy import signal
from ..utils import (save_fig)
###############################################################################
########################################################... |
b4ecb369cc3fdbb0e5cc84ac9910a80bcf72ab09b1dcba005ec9d664889e73d8 | Python | 1,833 | 64 | """Microbench: flat-buffer to_padded vs the awkward rpad/pad_none idiom."""
import time
import tracemalloc
import awkward.operations.str as ak_str
import numpy as np
from seqpro.rag import Ragged, to_padded
def _naive_pad_bytes(rag, pad_value, length):
return Ragged(ak_str.rpad(rag, length, pad_value)).to_nump... |
c206a5a17a1b69dc5751663225fb21b2cfbff015c0a3df61f92d4affc531ffa8 | Python | 1,833 | 57 | import sys
from robustness import datasets
from robustness.attacker import AttackerModel
from robustness.model_utils import make_and_restore_model
from model_analysis_folders.all_model_info import IMAGENET_PATH
def build_net(ds_kwargs={}, return_metamer_layers=False):
# We need to build the dataset so that the num... |
0bb0b86abcdc6a1c93101acf311de0149c28bd9dd580a3b7eeddb6b170d2cb3f | Python | 1,834 | 62 | import numpy as np
import pytest
import gym
from gym.wrappers import TransformReward
@pytest.mark.parametrize("env_id", ["CartPole-v1", "Pendulum-v1"])
def test_transform_reward(env_id):
# use case #1: scale
scales = [0.1, 200]
for scale in scales:
env = gym.make(env_id, disable_env_checker=True)... |
2f81f1f955a1ad7ec28ec30fe9da7e6ac2a86118849aef33152842fd8637ab01 | Python | 1,835 | 37 | """Per-epoch primitive extraction for the redesigned data layer (Phase 1, 2026-06-16).
THIN WRAPPER over the single extraction authority `ingest.extract_subject_features`
(called with return_per_epoch=True). It owns NO pipeline orchestration of its own —
the select → CAR → resample → epoch → compute_phi_5d sequence li... |
592fbc29d2ea10171fd3805e56f186e9a1f9b929a2b0f314e4c9e467c9690d7c | Python | 1,835 | 51 | import sys
from importlib import import_module
from celery.app.defaults import (_OLD_DEFAULTS, _OLD_SETTING_KEYS, _TO_NEW_KEY, _TO_OLD_KEY, DEFAULTS, NAMESPACES,
SETTING_KEYS)
class test_defaults:
def setup_method(self):
self._prev = sys.modules.pop('celery.app.defaults'... |
21af32ace200cce1cd06dc6398520491b8dc1d68b77eef0f75a2c061639591c2 | Python | 1,836 | 50 | import tensorflow as tf
import tensorflow.keras as keras
import tensorflow_addons as tfa
import numpy as np
from sklearn.model_selection import StratifiedKFold
brightness_offset = 22 #43
# THIS OFFSET IS ADDED
def load_mnist_with_brightness_offset(num_folds=5):
# load and split the dataset into train and test s... |
a9d20ec0472a16a41052584d3b68d526d71ecbf220f23b64378317fa159fab6b | Python | 1,836 | 61 | import unittest
import pandas as pd
from sqlalchemy import create_engine
import os
import codes3d
import snps
import create_test_data as test
class VariantTest(unittest.TestCase):
def setUp(self):
self.output_dir = test.output_dir
self.snp_list = test.snp_list
self.snp_rsid_df = test.snp_r... |
bc45a3adbd3e2f4ea6e2c3a7c9206c081da170ebba62c51b2886dc3aaef5d417 | Python | 1,836 | 60 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Tue Feb 7 18:08:10 2023
This script average the signal across voxels in each ROI, zscore the result per
session, and save.
@author: Florent Meyniel
"""
import re
import os
import glob
import pickle
import numpy as np
SUBJECTS = [23, 24, 25, 26, 27, 28, ... |
707cdec1a52da70f98086cbf044de15b5c5a2192287346fe87cdfbe2540e7d0b | Python | 1,837 | 72 | import itertools
import time
import pytest
from billiard.einfo import ExceptionInfo
pytest.importorskip('multiprocessing')
def do_something(i):
return i * i
def long_something():
time.sleep(1)
def raise_something(i):
try:
raise KeyError('FOO EXCEPTION')
except KeyError:
return Ex... |
9790aa1eaee3e79d6fe1e17ea535e46de99630b98655979e059fa8a04e96e3ab | Python | 1,837 | 58 | # Author: Francois Aguet
import numpy as np
import rpy2
from rpy2.robjects.packages import importr
from collections import Iterable
from contextlib import contextmanager
@contextmanager
def suppress_stdout():
with open(os.devnull, "w") as devnull:
old_stdout = sys.stdout
sys.stdout = devnull
... |
39af057cfeb36250e99586fed718802f4afc7cd888531720c3cde3d4022b866b | Python | 1,839 | 38 | # Import all the modules necessary for the Tool
import streamlit as st
st.set_page_config(page_title = "NOCICEPTRA",layout="wide")
# set the tab name #draw interactive visualization using holoviews
def main():
"""
Landing Page of the Nociceptra Trajectory Tool
"""
#set the logo
st.sidebar.info... |
c7fdab6abc944eed8426a4f65e151310d3af78988b364bec0d89169fc6ac83fe | Python | 1,839 | 67 | """Tests for specparam.io.files.
Note: load tests load files created from save functions, so failures may reflect saving issues.
"""
import os
from specparam.tests.tsettings import TEST_DATA_PATH
from specparam.io.files import *
######################################################################################... |
d237646e59d44caf5f983084a40f1544bd50d7ae7eb6f40ff1562109776ebaa2 | Python | 1,839 | 56 | try:
from fs_basespace import BASESPACEFS
except ImportError:
BASESPACEFS = None
from galaxy.files.models import (
BaseFileSourceConfiguration,
BaseFileSourceTemplateConfiguration,
FilesSourceRuntimeContext,
)
from galaxy.util.config_templates import TemplateExpansion
from ._pyfilesystem2 import P... |
dfb1680dd97dcf1968f9ade69c6e6c28eeabc5b1f50cd3ac7a478c1530b6fb20 | Python | 1,839 | 38 | """Convolutional Motif Kernel Network
This package implements convolutional motif kernel networks (CMKNs) as well as functions that help interpret trained CMKN
models.
References:
model: This module contains a basic network that utilizes the convolutional motif kernel.
layers: This module contains different l... |
524a72ecc0a85a974d956fa5e9f509292eccf153145da16df09e7d42a2500015 | Python | 1,840 | 60 | """
Base UI for plugin popup.
SimplyFire - Customizable analysis of electrophysiology data
Copyright (C) 2022 Megumi Mori
This program comes with ABSOLUTELY NO WARRANTY
This program is free software: you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free So... |
5c610bf170e22554b472593716edb30f00c1300c8707204d4b635d3bb95bf6cc | Python | 1,840 | 61 | from sys import argv
from msp import MSP
msp = MSP()
msp.file = __file__
msp.seed = int(argv[1])
msp.architecture["num_motifs"] = 82
msp.architecture["sparse_spec"] = dict(type="SpatiallySparseAcrossChannels")
msp.architecture["motif_model_spec"] = dict(
type="AdjustedMotifModel",
model_to_adjust_spec=dict(
... |
87b8a4f0f5d19e6f187255524016db0a1b3f61d5b244fdd04dd4c0a783d27ae2 | Python | 1,840 | 48 | from keras.src import ops
from keras.src import random
from keras.src import testing
from keras.src.backend.common import keras_tensor
from keras.src.ops.einops import rearrange
class RearrangeTest(testing.TestCase):
def test_basic_rearrangement_symbolic(self):
x = keras_tensor.KerasTensor((2, 3, 4))
... |
a38f370a0742909686be1111f9b11077c6076b8fb0cd5af840abbf3e43fdf060 | Python | 1,840 | 64 | import numpy as np
from gym import utils
from gym.envs.mujoco import MuJocoPyEnv
from gym.spaces import Box
class HalfCheetahEnv(MuJocoPyEnv, utils.EzPickle):
metadata = {
"render_modes": [
"human",
"rgb_array",
"depth_array",
],
"render_fps": 20,
}... |
df9f4509914a36488c1c5c49912ff4925e91e3fe257b6f744f02b949c083d831 | Python | 1,840 | 48 | # Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
#
# 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 app... |
05632cc516c6637d24faa2c0a852f8edd149f5252f9ae3a6cf6c3b5ee63ad66d | Python | 1,841 | 59 | import os
import random
import h5py
import numpy as np
import scanpy as sc
import tensorflow as tf
from dca.api import dca
from scbig.utils import louvain, calculate_metric
def seed(SEED):
os.environ['PYTHONHASHSEED'] = str(SEED)
random.seed(SEED)
np.random.seed(SEED)
tf.random.set_seed(SEED)
for d... |
15e74f5bec8d1dcb127197339d87659f531978dc7c4d71eefd1215692e069731 | Python | 1,841 | 56 | # first 2 lines to run in the console
import os
sys.path.append(os.path.join(os.getcwd(), 'brian_models/ripples_2populations_v2'))
from external_input_utils import generate_ext_input, plot_ext_input, generate_multiple_spw
import pickle
### Generate 100ms input with dt=0.1
duration = 100
N_e = 12000
n_excited = 1580
e... |
26c3f466469b26b213f9ae58b4b54967a8b6242671859cc2906c76d60db44952 | Python | 1,841 | 55 | import pickle
def run():
from spitfire.time.integrator import odesolve
from spitfire.time.stepcontrol import PIController
from spitfire.time.methods import CashKarpS6P5Q4
import numpy as np
def right_hand_side(q, fluid_density, drag_coeff, gravity, surface_area, mass):
vel_x = q[0]
... |
deb657cb99a2406829c149dcb764387fb0e9ff28e0c5dbf9d1a77ddb13ff96ce | Python | 1,841 | 60 | import sys,os,re
from scipy.stats import pearsonr,spearmanr
import pandas as pd
def parse_entry(entry):
if any([c == ' ' for c in entry]):
return None
else:
return entry[0], float(entry[1])
def build_codon_table(filename):
raw_frequencies = {}
search_string = re.search('(.*)/(.*)_... |
984ef01809b387ded93eb0dd99d668de55c1490a763be4eebf5e418cd0109e06 | Python | 1,842 | 61 | from typing import Dict, List, Tuple, Union
from PIL.Image import Image
from torch import Tensor
from lightly.transforms.torchvision_v2_compatibility import torchvision_transforms as T
from lightly.transforms.utils import IMAGENET_NORMALIZE
class IJEPATransform:
"""Implements the augmentations for I-JEPA [0, 1]... |
d11a9fc9cd6996961147dd297558df5be0409be721678191f96f84af6b24ca17 | Python | 1,842 | 57 | # inference test
import unittest
from unittest import TestCase
import logging
import pickle
import glob
logging.basicConfig(level=logging.INFO)
log = logging.getLogger(__name__)
import os
os.environ['CUDA_VISIBLE_DEVICES'] = '2'
import jax
import jax.numpy as jnp
import jax.random as jrand
from deepfold.model.con... |
1314d9a80313de3a1853545243efddd588a9cac82790b29e3deed91ee3281de6 | Python | 1,843 | 41 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""tests for gnn utils"""
import unittest
from sknetwork.gnn.utils import *
class TestUtils(unittest.TestCase):
def test_check_norm(self):
with self.assertRaises(ValueError):
check_normalizations('foo')
with self.assertRaises(ValueError... |
966ad49a68589cb8d67e427331c638aaf16cb7ead7b64d03c2d7b68a44683a45 | Python | 1,843 | 45 | """Run with compute-sanitizer --tool synccheck to check cross-role TMEM barriers."""
import math
import pytest
import torch
from flash_attn.cute import flash_attn_func
pytestmark = pytest.mark.skipif(
not torch.cuda.is_available()
or torch.cuda.get_device_capability()[0] not in (10, 11),
reason="SM100/S... |
a36bc8b555e8e46352c1039183271ebe316296ccc2c594995a8dc46657fb1f95 | Python | 1,843 | 56 | from mirp._image_processing.utilities import standard_image_process_checks
from mirp._images.generic_image import GenericImage
from mirp._images.mask_image import MaskImage
from mirp._data_import.utilities import flatten_list
from mirp._masks.base_mask import BaseMask
def randomise_mask(
image: GenericImage,
... |
235c88b104eaca92dc1e44b22a145061ebc0b00c7d503ea9df8df87d3faf0367 | Python | 1,844 | 66 | #!/usr/bin/env python3
f_1 = open("files.txt", "r", encoding = "utf-8")
filename = []
All = []
i = 1
for file_1 in f_1:
line_1 = file_1.strip().split('\t') #改行コートをはがしてタブ区切
filename.append(line_1[0])
f_1.close
j = 0
for file in filename:
samplename = file.split('.')[0]
All.append([samplename])
f... |
40822b9408188bfb407f1797c08042a781fc51f9aa4906117236b96d96210bca | Python | 1,844 | 60 | '''Tests for distcomp'''
import unittest
import os
import tempfile
from bdpy.distcomp import DistComp
class TestDistComp(unittest.TestCase):
def test_distcomp_file(self):
with tempfile.TemporaryDirectory() as lockdir:
comp_id = 'test-distcomp-fs'
# init
distcomp = D... |
2a9763314d18c08b72662fef5a9e4df946c623b8dadfb7100d2a7b726ff9157a | Python | 1,845 | 73 | import http.server
import socketserver
import threading
import tempfile
import os
import asyncio
import websockets
import sys
import json
os.chdir('/Users/xenios/bisweb/src/build/web');
httpd=0;
connections={};
# Temporary Directory
# -------------------
def createTemp():
tmp=tempfile.TemporaryDirectory(dir='/Us... |
5fcfea83864d09d31f91e7aced29621a9163bee62730b13ed4bf059898dd739f | Python | 1,845 | 53 | # import packages
import numpy as np
import dicom2nifti
from volume import Volume
import nibabel as nib
import os
import shutil
def copytree(src, dst, symlinks=False, ignore=None):
for item in os.listdir(src):
if "Vinci" in item:
continue
s = os.path.join(src, item)
d = os.path... |
75ad33c826694549f9b23a1e6c58d9c937a5401d933d637c21188902a0e4e64e | Python | 1,845 | 56 | import numpy as np
import tensorflow as tf
import nibabel as nib
import matplotlib.pyplot as plt
class DataGenerator(tf.keras.utils.Sequence):
def __init__(self, list_ids, labels, batch_size=5, dim=(128, 128, 70), n_channels=1, n_classes=2, shuffle=True):
"""Initialization"""
self.dim = dim
... |
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