sha256 stringlengths 64 64 | language stringclasses 27
values | size int32 1 491k | lines int32 1 21.8k | content stringlengths 1 200k |
|---|---|---|---|---|
6053202964d6d061ce34a04acf299554c9d8fd2cfaa8deac3e9083da492b0324 | Python | 3,640 | 63 | # Copyright 2020 Division of Medical Image Computing, German Cancer Research Center (DKFZ), Heidelberg, Germany
#
# 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://w... |
75cf6a5f42d8764ab5a7c5a5c71551a3f2c1f7327b4b885ea16aa3263bc160c2 | Python | 3,641 | 105 | """Settings GuPPy remembers between launches.
The input root folder and the output root folder belong to a project rather than
to one analysis: they hold still while the sessions and run names chosen inside
them change from run to run. Remembering the pair means a returning user does not
re-pick them, which is what le... |
f726f1ed0855fb5a60932e063de59096610b9c295118300f93c903ed25bf379f | Python | 3,641 | 76 |
# Copyright 2020 Division of Medical Image Computing, German Cancer Research Center (DKFZ), Heidelberg, Germany
#
# 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://... |
1171f859090ed61dbd548053952f16cb34861289a4b37d0d8d639e89f75f813a | Python | 3,642 | 111 | import os
import cv2
import numpy as np
def fill_corner(point, directions, img, visited):
h, w = img.shape
cp = point
td = [directions[0][0] + directions[1][0],
directions[0][1] + directions[1][1]]
while True:
for d in directions:
r, c = cp
visited[r, c] = 1
... |
b56ed0ea43e8113e52e3584e2d2f08b42d54d78b610073047b8cdc86bbaea1aa | Python | 3,642 | 107 | # 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
# -- Path setup --------------------------------------------------------------
import ... |
050e526a9da35eaee22121b281dcf4eed2b2f3e95320368926a44105fa3d3c3e | Python | 3,646 | 99 | from .models import ExperimentDataset
from django.http import Http404
from rest_framework.generics import GenericAPIView
from rest_framework.response import Response
from rest_framework import status
from drf_spectacular.utils import extend_schema
from .permissions import IsAdmin, IsDatasetOwner, IsExpOwner
from .seri... |
d439626f22360677e5c986eb8b2192aa0647807577f1a79ba52a1befb94b454f | Python | 3,647 | 24 | import torch
from transformers import BertTokenizer,T5Tokenizer
from fengshen.models.PPVAE.pluginVAE import PPVAEModel
device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
encoder_tokenizer = BertTokenizer.from_pretrained("IDEA-CCNL/Randeng-PPVAE-1.2B-Augmentation-Chinese")
decoder_tokenizer = T5Token... |
095f676d6da44860e13a630dc7c3a983c42e50037e0b9f54f766db352792d8eb | Python | 3,648 | 94 | # -*- coding: utf-8 -*-
from django.db import connection
from collections import defaultdict
from itertools import chain
from typing import Any, DefaultDict, List, Set
def find_empty_neurons() -> Set:
""" Returns a set of empty neurons. Also prints the total
number of neurons and the total number of neurons fo... |
08dfb4cf50c919155410af686df3378a5e14976747918b9bf7c73997b335a026 | Python | 3,649 | 126 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
import numpy as np
import pandas as pd
import logomaker
import seaborn as sns
class motif():
alphabet = ['A', 'C', 'G', 'T']
colorscheme = {
'G': [0.004, 0.125, 0.305],
'TU': [0.007, 0.514, 0.569],
'C': [0.965, 0.863, 0.67... |
c6348683ce03fe171f967138a6a73f05d86a2bba1a4747aab96195144be327f1 | Python | 3,650 | 109 | #!/usr/bin/env python
"""
MeteWIBELE workflow: A collection of AnADAMA2 workflows
1) characterization workflow: characterize protein families for functional and taxonomic annotation
2) prioritization workflow: prioritize protein families for unsupervised (ecological properties) and supervised (association with phenoty... |
0c307a671eeb5686ab3cc05f65f6fa7b8629c857a0568d3fcfc62772b86a0c33 | Python | 3,651 | 113 | _base_ = [
'../_base_/datasets/cityscapes_1024x1024.py',
'../_base_/default_runtime.py'
]
# The class_weight is borrowed from https://github.com/openseg-group/OCNet.pytorch/issues/14 # noqa
# Licensed under the MIT License
class_weight = [
0.8373, 0.918, 0.866, 1.0345, 1.0166, 0.9969, 0.9754, 1.0489, 0.878... |
36e2ec72d3c933cf901c9a809081269d9b69922e6eb5453b3f97b2ed569ac1d4 | Python | 3,652 | 94 | """Unit tests for src/datahandlers/ec.py (ECgraph)."""
import pyoxigraph
import pytest
from src.categories import MOLECULAR_ACTIVITY
from src.datahandlers.ec import ECgraph, make_ids, make_labels
from src.prefixes import EC
from tests.datahandlers.conftest import RDF_NS, RDFS_NS, SKOS_NS, lit, make_graph_from_store, ... |
d5bc97763e9a2f34ae8d709d73d6046e2aa77814a7b68fdc9fdca70f94657f35 | Python | 3,654 | 105 | # run generate_processed_exp_data first
import numpy as np
import matplotlib.pyplot as plt
from sklearn.linear_model import LinearRegression, Lasso
from sklearn.model_selection import train_test_split
from grid_cell.util import pca_accumulated_variance_explained_ratio
from sklearn.metrics import mean_squared_error, r2_... |
d495ac9e630d5787fa499befa27937f3ae463669543ef6ad0a43ed50f714a9a7 | Python | 3,655 | 83 | """
Demo for survival analysis (regression) with Optuna.
====================================================
Demo for survival analysis (regression) using Accelerated Failure Time (AFT) model,
using Optuna to tune hyperparameters
"""
import numpy as np
import optuna
import pandas as pd
from sklearn.model_selection i... |
c648b250f34cd23e00e751ce42bd0f92b7bea86752043f819078614b5455218f | Python | 3,657 | 90 | from __future__ import print_function
import pytest
from keras.utils.test_utils import get_test_data
from keras.models import Sequential
from keras import layers
import keras
from keras.utils.np_utils import to_categorical
num_classes = 2
def test_vector_classification():
'''
Classify random float vectors i... |
8a857bc6003d7cfbef8463f3d17f88d716b627ecbbd1c0090e870bc51cbc2a64 | Python | 3,658 | 119 | #!/usr/bin/env python
"""
MetaWIBELE: extract_abundance_feature_subset module
Extract the subset table based on specific feature
Copyright (c) 2019 Harvard School of Public Health
Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "So... |
27f9d4d6da5af2cff3bbe3cd3cdea9ee271ba195c856e874f8769b11005d6245 | Python | 3,661 | 109 | import numpy as np
from sklearn.linear_model import Ridge
from sklearn.svm import SVC
from sklearn.linear_model import LogisticRegression
from sklearn.neighbors import KNeighborsClassifier
from sklearn.preprocessing import StandardScaler
from sklearn.pipeline import make_pipeline
from sklearn.model_selection import Gri... |
83cbbfa81013cdc334cc7264c543ca1c66f90525ac07703041ee656b70d39acc | Python | 3,662 | 146 | import data_utils as du
import os
import sys
from keras.optimizers import Adam, SGD
from keras.callbacks import LearningRateScheduler
from keras.metrics import Precision, Recall, FalsePositives, FalseNegatives
from keras.models import Sequential
from keras.layers import Dense, Dropout, Activation
from keras.layers im... |
ea62e28dfc6fb0e3a36516866db542da0da42136bd71b0f09c5ee9fdd8146805 | Python | 3,663 | 104 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
""" deltalm model configuration"""
import warnings
from transformers.configuration_utils import PretrainedConfig
from transformers.utils import logging
logger = logging.get_logger(__name__)
BART_PRETRAINED_CONFIG_ARCHIVE_MAP = {
"IDEA/Deltalm": "https://huggingface.c... |
adf98d3a9aa60b8d9708bbe19f73a97371ebddb967f474cb990c981b1f1a4f22 | Python | 3,664 | 93 | import holoviews as hv
import numpy as np
import pytest
from guppy.visualization.binned_metrics import (
build_bin_bars,
build_binned_metrics_panel,
)
@pytest.fixture
def bins():
# Two whole bins and a short third one, as a ragged final bin produces.
return {
"bin_starts": np.array([0.0, 4.0,... |
9e71f8603c23c5d36275fe60fc5e0056988182b1d64c1ec516023e5ab8efd6f2 | Python | 3,666 | 127 | """
Copyright (c) Facebook, Inc. and its affiliates.
This source code is licensed under the MIT license found in the
LICENSE file in the root directory of this source tree.
"""
import logging
import torch
import torch.nn as nn
from torch_geometric.nn import radius_graph
from ocpmodels.common.utils import (
comp... |
1d9cc372350f8c949a6ba8495201e96497655f0f85896e84fc35b09813d3aa7c | Python | 3,667 | 118 | """
Copyright (c) Facebook, Inc. and its affiliates.
This source code is licensed under the MIT license found in the
LICENSE file in the root directory of this source tree.
ONLY for use in the NeurIPS 2021 Open Catalyst Challenge. For all other submissions
please use make_submission_file.py.
"""
import argparse
imp... |
8b1eb0375f895f9e4421ad58929d8722aab96a74101619bb35dac6c23f0397cb | Python | 3,669 | 110 | import yaml
from collections import OrderedDict
from os import path as osp
def ordered_yaml():
"""Support OrderedDict for yaml.
Returns:
yaml Loader and Dumper.
"""
try:
from yaml import CDumper as Dumper
from yaml import CLoader as Loader
except ImportError:
from ... |
a139313721c5b54532a0ba238fe24edf1f64103e95f2a168e04aef4ed92fb279 | Python | 3,669 | 184 | # Author: Hauxu Yu
# Evaluate feature quality by chromatographic peak shapes, mz errors, rt errors, etc.
# imports
import numpy as np
"""
Functions
------------------------------------------------------------------------------------------------------------------------
"""
def calculate_gaussian_similarity(x, y):
... |
9b26589429a2804cac44d647295b1297405b7d499d626953f451a97d7bc3843b | Python | 3,670 | 111 | import typing
import numpy as np
import scipy
import functools
import os
from statsmodels.tsa.stattools import acf
import tsgm
'''
All statistics should return lists.
'''
def _to_numpy(ts: tsgm.types.Tensor) -> np.ndarray:
"""Convert tensor to numpy array based on current backend."""
if os.environ.get("KER... |
1ecabdf9ab28dc51c42ac1d319e2167bc092f40410f9e0921c06867cc5825c7b | Python | 3,672 | 108 | # -*- coding: utf-8 -*-
#MEGの前処理をするためのスクリプト
#ECG,EOGがを用いたSSP,ICAによる処理、ECG,EOGなしでのICAによる処理、notch filterが行うことが出来る
#処理の手順は一番下を参照。
#自動読み込み##############################################
#PARAMETER_DIR='/Volumes/Promise_Pegasus/Dropbox/MEG_current/kougakubu/parameter'
#PARAMETER_DIR='/Volumes/ssdraid/Dropbox (MEG)/seirisyu... |
2c01027300350d4cd1cbaa9b9c0a34630030394e1657cda01588d6bddab3fc1e | Python | 3,673 | 98 |
from os import makedirs
from os.path import join as pjoin, exists as pexists, abspath, realpath, basename, dirname
from visualqc.vqc import cli_run
import shlex
import sys
import numpy as np
from pytest import raises, warns
test_dir = dirname(realpath(__file__))
base_dir = realpath(pjoin(test_dir, '..', '..', 'exampl... |
ddc19eb2bde7c766c47fc1e0c4ff33510bd21b2f8e2f2e259d6eda11d932b424 | Python | 3,673 | 90 | import numpy as np
import pandas as pd
from scipy.interpolate import CubicSpline
from zigzeg import find_runs
from experiment import *
def interpolate(x, gap_size=5):
# get transformed
x = np.array(x)
# find gaps to interpolate
x_nan = np.any(np.isnan(x), axis=1)
gaps, = np.where(x_nan)
gaps ... |
014d75f908412db564e05e33777bce7101ceadc50ed1185f67ce1327f6044078 | Python | 3,675 | 105 | from typing import Dict, List, Optional
import torch
from e3nn.util.jit import compile_mode
from mace.tools.scatter import scatter_sum
@compile_mode("script")
class LAMMPS_MACE(torch.nn.Module):
def __init__(self, model, **kwargs):
super().__init__()
self.model = model
self.register_buff... |
6bd51e8023d0435d31e9a7c2e17c6e7679612782f316b755d2ba99686aa57c13 | Python | 3,675 | 75 | # %%
import os
from itertools import cycle
from os.path import join
from pathlib import Path
import numpy as np
import pandas as pd
__author__ = "Heejung Jung"
__copyright__ = "Spatial Topology Project"
__credits__ = ["Melanie Kos"]
__license__ = "MIT"
__version__ = "0.0.1"
__maintainer__ = "Heejung Jung"
__email__ =... |
98cd788f7d2ef69f3423bcf628d224ec0bdd7bc4d38f90f53ca1f4c2890fb875 | Python | 3,676 | 73 | # Function for opening pyPhotometry data files in Python.
# Copyright (c) Thomas Akam 2018. Licenced under the GNU General Public License v3.
import json
import numpy as np
from scipy.signal import butter, filtfilt
def import_ppd(file_path, low_pass=20, high_pass=0.01):
'''Function to import pyPhotometry binary ... |
e72c06ab777509b6838d4f1609228c7b05e58818446ebcf984b6a811171603a4 | Python | 3,677 | 96 | """Support for InplaceUpdateRequirement."""
from typing import Final, NamedTuple
from cwl_utils.types import CWLDirectoryType, CWLFileType
from .errors import WorkflowException
class _MutationState(NamedTuple):
generation: int
readers: list[str]
stepname: str
_generation: Final[str] = "http://commonw... |
3fab6af3856ec70d250b85aa5ffab8cc6f7f1641a3675f74225c4e5d08de2e4e | Python | 3,679 | 114 | """Test script for the export of sbml files and importing """
import jax.numpy as jnp
from jaxkineticmodel.kinetic_mechanisms import JaxKineticMechanisms as jm
from jaxkineticmodel.building_models import JaxKineticModelBuild as jkm
from jaxkineticmodel.load_sbml.export_sbml import SBMLExporter
import equinox
import p... |
6d34c9178e4ab32532956b247727693232ce3e794a66648ae345f61c23f6393c | Python | 3,679 | 91 | DOCS = """
train the model on the a dataset (gabor or mnist) to show the effect of feedback connection from L5 to L2/3.
Current figures: figure 5.
"""
from dataset import GaborDatasetOrientation
from model import ShallowMLP
from experiment.utils import set_seed, init_model, Logger, Trainer, Checkpointer
import torch
i... |
6f58f3c6b031df82c1ae14eca0197b1b2c0c6a5a3ffcef4f375cdccdd14fdcf7 | Python | 3,681 | 104 | import pytest
import numpy as np
import os
import sys
sys.path.insert(0, os.path.abspath(os.path.join(os.path.dirname(__file__), '..')))
import tsgm
@pytest.mark.parametrize("mock_aug", [
[tsgm.models.augmentations.GaussianNoise()] * 10,
tsgm.models.augmentations.GaussianNoise()
])
def test_base_compose(mock_a... |
55f3dfac3b86f9d84837ea7b87494f170c418ce6f489c67dcf1306125a119afe | Python | 3,682 | 110 | #!/usr/bin/env python3
#
# Small example on how to use the Miniscope library from Python
# In order to make this example work, first install the "miniscope" Python
# module, e.g. with `pip install .` from the PoMiDAQ source directory, or by
# building PoMiDAQ with CMake (with the PYTHON option enabled).
# Alternativel... |
6cd037c47c5ece90849ec52c39eb2e8cdc5a159b97e2d173766e327cdc85161e | Python | 3,682 | 97 | import unittest
import numpy as np
import numpy.testing as npt
from DiastereomericResolutions.Representation.legacy_implementation import (
gen_weighted_rdf,
)
from DiastereomericResolutions.Representation.weighted_rdf import (
gen_weighted_rdf as gen_weighted_rdf_refactored,
)
class TestRDFFunctions(unitte... |
c9d8a88891c5b0fca1d6ff508cd0bd29d55b5d406a1176a18492a74c136ce638 | Python | 3,684 | 112 | #!/usr/bin/env python
#
# Copyright 2006, Google Inc.
# All rights reserved.
#
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are
# met:
#
# * Redistributions of source code must retain the above copyright
# notice, this list... |
faac9efa32a3ea36223c9daee97312e9182a6f62f639a3c79922dbc5dd219c22 | Python | 3,686 | 101 | from __future__ import annotations
from typing import Any
import numpy as np
from scipy.optimize import linear_sum_assignment
from soccertrack import BBoxDataFrame
from soccertrack.utils.utils import list2dict
def identity_score(
bboxes_track: BBoxDataFrame, bboxes_gt: BBoxDataFrame
) -> dict[str, Any]:
""... |
c3f5e833551f25401beed53de13a39190723ec1650ac34e7a0d60375bdd7203f | Python | 3,687 | 98 | #!/usr/bin/env python
"""
Sorts the raw acquisitions files into semi-BIDS format
NOTE: The output will not be quite BIDS yet,
because we haven't split the physio data into runs, yet.
Parameters
------------------
physio_dir: str
path where physio data lives
sub_zeropad: int
how many zeros to pad for BIDS subje... |
18cf47cacc6481f314b297ecd9f9f363fe911090a61fe5ea723736860ed2bf72 | Python | 3,688 | 118 | import colorsys
import functools
import numpy as np
from colormath.color_conversions import convert_color
from colormath.color_diff import delta_e_cie2000
from colormath.color_objects import sRGBColor, LabColor
LUMINOSITY_VECTOR = np.array([0.2126, 0.7152, 0.0722])
def hsv_palette(how_many):
return [colorsys.hs... |
2afbadcd4f2b8473475d276309d9e0f52cea3e124159a85a0b857930efd0ed0b | Python | 3,688 | 98 | # Script to generate simulated diffraction library of a zone-plate focused beam diffracted by an epitaxial thin film
# Method developed by Tao Zhou (tzhou@anl.gov)
# Simulate over strain, tilt_lr, and tilt_ud, in that order, for 11.7 nm SrIrO3 on LSAT
from math import *
import numpy as np
import os
import time
from jo... |
9181adaf58c938b78e661b8649341746cdbb5a91eccb6554a046cbc50a026b5c | Python | 3,689 | 83 | # functions for preprocessing
import numpy as np
def filter_genes(data, min_counts=0, min_cells=0,
min_counts_uniq=0, min_cells_uniq=0, min_MIF_uniq=0.001,
uniq_layers=['isoform1', 'isoform2'],
ambg_layers=['ambiguous'], copy=False):
"""Filter genes based on nu... |
d7115a105abcb9176d7ef1ffbe4ab46df375560b54baf194228928d1d4584359 | Python | 3,690 | 120 | # encoding=utf-8
from typing import List, Union
import torch
from torch.nn.utils.rnn import pad_sequence
from transformers import T5Tokenizer
from fengshen.models.transfo_xl_reasoning import TransfoXLModel
from fengshen.utils import sample_sequence_batch
def en_to_zh(sentence:str):
en_pun = u",.!?[]()<>\"\"''"
... |
b854fe12e3b654be563e8db0bc050dcd310a816796c4aa7bbff5a05987752804 | Python | 3,691 | 39 | import argparse
parser = argparse.ArgumentParser(description='TSAN-Brain age estimation')
# =========== save path ================ #
parser.add_argument('--model_name' ,default='best_model.pth.tar' ,type=str, help="Checkpoint file name")
parser.add_argument('--output_dir' ,default='./model/' ,t... |
9ecba3ac3baf6f3eb0e369ed69525c237d1eb479973a9846017f68623a53b78d | Python | 3,692 | 93 | #!/usr/bin/env python
import torch
from torch.utils.data import DataLoader
from rdkit import Chem
from rdkit import rdBase
from tqdm import tqdm
from MCMG_utils.data_structs_fragment import MolData, Vocabulary
from models.model import RNN
from MCMG_utils.utils import Variable, decrease_learning_rate
rdBase.DisableLo... |
dc70e5b46b03621a33121a9db6c86a46973ba1983afc530f0db12b3c273b94c8 | Python | 3,693 | 147 | import numpy as np
# make TensorLike more flexible
from tsgm.types import Tensor as TensorLike
import typing as T
EPS = 1e-18
class TSGlobalScaler():
"""
Scales time series data globally.
"""
def fit(self, X: TensorLike) -> "TSGlobalScaler":
"""
Fits the scaler to the data.
... |
eefb53c663255ec8a613ab5f2f4155983833f2afa018e46d10c821bd86595fc0 | Python | 3,693 | 118 | """Application configuration.
Settings class configured via environment variables with the ZNDRAW_SERVER_ prefix.
Storage backend is selected by URI string (e.g. ``memory://``,
``/path/to/data.lmdb``, ``mongodb://host:port/db``).
"""
from pathlib import Path
from typing import Annotated
from fastapi import Depends, ... |
07003f8f7dfb3722b4de5cba5a1078cfb0ff69ebb6a4224a2f3a7ce95e3fc3a7 | Python | 3,694 | 101 | import pytest
import copy
import itertools
import os
import sys
sys.path.insert(0, os.path.abspath(os.path.join(os.path.dirname(__file__), '..')))
import tsgm
import keras
def _get_gunpoint_dataset():
data_manager = tsgm.utils.UCRDataManager(ds="GunPoint")
X_train, y_train, X_test, y_test = data_manager.get(... |
8d11e973acd8a34782a9b74511a9fb3866d53a9b506c2a70b0c2a72ea46d243c | Python | 3,696 | 123 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Thu Dec 15 15:13:24 2022
@author: george
"""
import warnings
warnings.simplefilter(action='ignore', category=Warning)
import numpy as np
import pandas as pd
from tqdm import tqdm
import os, glob
from sklearn.neighbors import KDTree
import math
from sci... |
1fbf5c12b3732c5ba0a70ee06b6ac29430f04818cb57daa72def7e7969518416 | Python | 3,697 | 93 | #!/usr/bin/env python
import torch
from torch.utils.data import DataLoader
from rdkit import Chem
from rdkit import rdBase
from tqdm import tqdm
from MCMG_utils.data_structs_fragment import MolData, Vocabulary
from models.model import RNN
from MCMG_utils.utils import Variable, decrease_learning_rate
rdBase.DisableLo... |
1ecd161cfa6f678b36cc6038c6dc0c7f62c315c2efe1307860f1df65d510cd2a | Python | 3,698 | 122 | import os
from typing import List
from medperf.entities.training_exp import TrainingExp
from medperf.entities.interface import Entity
from medperf.entities.schemas import AggregatorSchema
import medperf.config as config
from medperf.account_management import get_medperf_user_data
import yaml
from medperf.entities.ut... |
1931a8dff2c48a0f9e15f58cbbd4d720bc9cf9db2878b5d3b3b679582295297c | Python | 3,699 | 119 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
# tests/run_two_tests.py
################################################################################
# EncoderMap: A python library for dimensionality reduction.
#
# Copyright 2019-2024 University of Konstanz and the Authors
#
# Authors:
# Kevin Sawade
#
# Encodermap i... |
a65a13059dce55b472277cab92ffec88235b7b9d195fbbd1c68ff39f3a0759c6 | Python | 3,699 | 108 | import pytest
import requests
import builtins
import os
from copy import deepcopy
from medperf import config
from medperf.ui.interface import UI
from medperf.comms.rest import REST
from medperf.comms.auth.interface import Auth
from medperf.init import initialize
import importlib
# from copy import deepcopy
@pytest.f... |
23b91a7d5e8fe107540b821872e5391e41650f0385038fce81250fecb6401a6d | Python | 3,700 | 96 | """Resolves references to CWL documents from local or remote places."""
import os
import urllib
from pathlib import Path
from schema_salad.ref_resolver import Loader
from .loghandler import _logger
def resolve_local(document_loader: Loader | None, uri: str) -> str | None:
"""Use the local resolver to find the ... |
8cce0d607a6361b1329f0a8fbf066a7217f0bbc175f2d3208fee88fbd65ccd31 | Python | 3,701 | 130 | import argparse
import csv
import os
import sys
import os.path as op
from re import L
import numpy as np
from MH_consensus_utils import consensus_kmeans
from nilearn.input_data import NiftiMasker
from nilearn.masking import unmask
from sklearn.cluster import KMeans
from sklearn.metrics import pairwise_dist... |
f6bdd62458f71ae44257042dc8342ee69a5872e6b6d85d6b918cdc29c4d7f50f | Python | 3,704 | 96 | #!/usr/bin/env python3
"""Public-safe static and numeric checks for output-smoothing geometry."""
from math import isfinite, log, sqrt
from pathlib import Path
REPO_ROOT = Path(__file__).resolve().parents[2]
HELPERS = REPO_ROOT / "helper_functions"
FWHM_PER_SIGMA = 2 * sqrt(2 * log(2))
def sigma_vox(fwhm_mm, voxel... |
21b2121c5050cb27347b27d17ad6755276cd0671fd6a609ada991880290cc297 | Python | 3,709 | 89 | # Copyright 2020 Division of Medical Image Computing, German Cancer Research Center (DKFZ), Heidelberg, Germany
#
# 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://w... |
388487cedd85de1542b3b9bb866e0e92150249bebbe1ce981fefb9912bf6ea5a | Python | 3,712 | 108 | ## Restormer: Efficient Transformer for High-Resolution Image Restoration
## Syed Waqas Zamir, Aditya Arora, Salman Khan, Munawar Hayat, Fahad Shahbaz Khan, and Ming-Hsuan Yang
## https://arxiv.org/abs/2111.09881
##### Data preparation file for training Restormer on the GoPro Dataset ########
import cv2
import numpy ... |
96237baed2a5ff60ba38d835759b26d847d06e65ca3a881fc99c5f98949895c4 | Python | 3,715 | 105 | import numpy as np
import pandas as pd
from sklearn.metrics import *
from scipy.stats import pearsonr
import matplotlib.pyplot as plt
import seaborn as sns
def classification_matrices(true, pred):
print('Converting to binary')
print(f'ground truth: max {true.max():.3f}, min {true.min():.3f}')
print(f'pred... |
aeb0ce81e9276732313ae7fc35580aaa64ccf66da3f42a11739060b91740dcaf | Python | 3,715 | 116 | #!/usr/bin/env python
import argparse
import torch
import time
# from models import transformer_RL
# from data_structs import Vocabulary
from MCMG_utils.data_structs import MolData, Vocabulary
from models.model_MCMG import transformer_RL
from MCMG_utils.utils import seq_to_smiles_frag
import pandas as pd
import torc... |
2f5dd309bcf18fbcd9e00b2f40de0ab5898aeaf9c80c59c9c3b357d2e7e045c7 | Python | 3,717 | 93 | import os
from Utils.dataloader_BrainTumorMRI import *
from Utils.models import *
from Utils.TrainModel import *
from Utils.config import *
from multiprocessing import Process
# Load configs
def task(backbone:str, model_path:str):
_data_config = DatasetConfig()
_loader_config = LoaderConfig()
_model_conf... |
bddefd0ebda7b0fc56bed3805c6b1cb97388b5f23e4179f8fba127f30bad9637 | Python | 3,719 | 121 | # Copyright (C) The Arvados Authors. All rights reserved.
#
# SPDX-License-Identifier: Apache-2.0
"""TaskQueue."""
import queue
import threading
from collections.abc import Callable
from typing import Union
from .loghandler import _logger
class TaskQueue:
"""A TaskQueue class.
Uses a first-in, first-out qu... |
463f3c067dd4de3d7d807caedd5277e74b0afde88401d35cd1aa19b36d35a215 | Python | 3,720 | 110 | import os
import shutil
import argparse
import json
import urllib.request
import hashlib
from urllib.error import URLError, HTTPError
from typing import Union
from tqdm import tqdm
FIGSHARE_URL_PREFIX = 'https://figshare.com/ndownloader/files/'
FIGSHARE_FALLBACK_PREFIX = 'https://ndownloader.figshare.com/files/'
de... |
3ed37efaa45802e3eaecac989cca89a783674f9dd30f765fb5551b01a764fbe1 | Python | 3,722 | 108 | import os
import textwrap
import pytest
def _seed(path):
"""Pre-seed the download/extract markers so get_example_data() skips the network."""
(path / "example_data.tar.gz").write_bytes(b"")
extracted_dir = path / "example_data"
extracted_dir.mkdir(parents=True)
(extracted_dir / "data.py").write_t... |
95f253c14e3c2e03ab8a693cfac3f8b65aa990e0e87f8add6b9f5ba86dc2741e | Python | 3,722 | 79 | """Pipeline tests for the MONDO_GARD concord, run against a real built concord.
Skipped by default unless pytest is run with --pipeline. Run with:
uv run pytest tests/pipeline/test_mondo_gard.py --pipeline --no-cov -v
MONDO_GARD is the one place this pipeline reads `oboInOwl:hasDbXref`, and it has no bad-xrefs f... |
3c04e41836846bb7870b5f67b6c52ec0dbbb0c38a97dcb8552e6577eec90bf25 | Python | 3,723 | 123 | import os, json
import pandas as pd
import numpy as np
from os.path import join as opj
'''
Generate :
data/parsed_questions_bootstrap/acc_each_scene_stiff.csv
data/parsed_questions_bootstrap/cor_each_scene_stiff.csv
data/parsed_questions_bootstrap/cor_stiff.csv
Before running this script, ensure you've executed bash... |
d07bb333c0b8dd7fd202f0e985955b4e200cf1535fb3be7a0bed7b29881d8621 | Python | 3,723 | 104 | from __future__ import annotations
from typing import Optional
from heudiconv.utils import SeqInfo
def create_key(
template: Optional[str],
outtype: tuple[str, ...] = ("nii.gz",),
annotation_classes: None = None,
) -> tuple[str, tuple[str, ...], None]:
if template is None or not template:
ra... |
e43fc49c5216afdd728e31602185ebe5ecadca7f5a3b91f93d59e2bb5aebdeb9 | Python | 3,724 | 96 | # pytest unit tests for spinalcordtoolbox.deepseg._sc
import pytest
import numpy as np
import nibabel as nib
from spinalcordtoolbox.image import Image
import spinalcordtoolbox.deepseg_.sc as deepseg_sc
from spinalcordtoolbox.utils.sys import sct_test_path
from .test_centerline import dummy_centerline
param_deepseg... |
47ec4911faf1926acba62b5540cfecd77b81ba5e27ca26f92c1110238cc30fd3 | Python | 3,725 | 101 | from .models import BenchmarkDataset
from django.http import Http404
from rest_framework.generics import GenericAPIView
from rest_framework.response import Response
from rest_framework import status
from drf_spectacular.utils import extend_schema
from .permissions import IsAdmin, IsDatasetOwner, IsBenchmarkOwner, IsCo... |
ee10c346193b93c5d0ca52c9543202389668a3e4f6ee7c4024ea0e4b496065b0 | Python | 3,725 | 120 | """
Copyright (c) 2016-2022, EPFL/Blue Brain Project
This file is part of BluePyOpt <https://github.com/BlueBrain/BluePyOpt>
This library is free software; you can redistribute it and/or modify it under
the terms of the GNU Lesser General Public License version 3.0 as published
by the Free Software Foundation.
... |
24f5befdf4d62477a2f20b759f3e8ea135aeaa91c6eed643220f7d3abe9c8fba | Python | 3,729 | 125 | # -*- coding:utf-8 -*-
##---IMPORTS
import scipy as sp
from scipy import linalg as sp_la
from common import TimeSeriesCovE
from plot import P, mcdata
from nsim.scene.noise import ArNoiseGen
from database import MunkSession
##---CONSTANTS
DB = MunkSession()
##---FUNCTIONS
def load_cmx():
... |
6473a065b3ff16785bdc7402d1529122f9d63ec13d31d7b9d2f2377c94487ed6 | Python | 3,730 | 101 | from typing import Dict, Optional
import torch
from e3nn import o3
from e3nn.util.jit import compile_mode
from mace.modules.models import ScaleShiftMACE
from mace.modules.utils import get_edge_vectors_and_lengths
@compile_mode("script")
class NonLinearReadoutBlock(torch.nn.Module):
def __init__(
self, ir... |
3f916c74a1473a55c49d8a81b85b3841351f62155d9546acb00eb772eb33467e | Python | 3,732 | 95 | '''
reproducing the torus manifold by umap, from the Gardner et al. 2022.
'''
import numpy as np
import matplotlib.pyplot as plt
from grid_cell.util import select_arr_by_t, apply_each_col
from sklearn.decomposition import PCA
from umap import UMAP
import grid_cell.tuning as gct
from scipy.ndimage import gaussian_filter... |
74629834adc2137da3c1156b05e52cb1d5d1a1cbb8e559eb03772f2d1a7ed84d | Python | 3,733 | 156 | #+
#
# This file is part of h5py, a low-level Python interface to the HDF5 library.
#
# Contributed by Darren Dale
#
# Copyright (C) 2009 Darren Dale
#
# http://h5py.org
# License: BSD (See LICENSE.txt for full license)
#
#-
# pylint: disable=eval-used,protected-access
"""
This is the h5py completer extension fo... |
389c871ae922ebf740d19117092ce3b0d23745f85ef02f7bcce74e0008dda8f2 | Python | 3,734 | 98 | import igraph as ig
from igraph import Graph
import numpy as np
import os
import json
from delaunay_graph import generate_delaunay_graph
from pattern_checker import PatternChecker
from multiprocessing import Pool, cpu_count
from delaunay_graph_generator_high import generate_delaunay_graph_true
import argparse
... |
78b5684aa02369ddb3affa43791e6f20eda02ef1ee7dfb716f478976bd53857a | Python | 3,734 | 71 | ## Restormer: Efficient Transformer for High-Resolution Image Restoration
## Syed Waqas Zamir, Aditya Arora, Salman Khan, Munawar Hayat, Fahad Shahbaz Khan, and Ming-Hsuan Yang
## https://arxiv.org/abs/2111.09881
## Download training and testing data for single-image motion deblurring task
import os
# import gdown
imp... |
b25a0dd47897b19fa21edb6056a227f1df827c4344452cbc01ab0df154e404d4 | Python | 3,734 | 115 | #!/usr/bin/env python
"""
MetaWIBELE: extract_protein_coding_genes module
Extract protein coding genes from total gene sets
Copyright (c) 2019 Harvard School of Public Health
Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Softwar... |
0ca1d8927edb5eb42e3c4e9785b5ebdf70342810ab4aaf9fa689f0f3b82bc539 | Python | 3,735 | 88 | # -*- coding: utf-8 -*-
from typing import Dict
from django.core.management.base import BaseCommand, CommandError
from django.core.management import call_command
from catmaid.fields import Double3D, Integer3D
from catmaid.models import Project, ProjectStack, Stack, StackMirror, User
class Command(BaseCommand):
... |
0f9430854325c5a0d8cdf4e3d503524373a996edbda6412c67ce0516074c08ae | Python | 3,736 | 111 | ##
## CPCantalapiedra 2020
import multiprocessing
from tempfile import NamedTemporaryFile
from ...emapperException import EmapperException
from ...common import get_pfam_db, get_data_path, set_data_path
from .pfam import get_hmmsearch_args, PfamAligner, parse_hmmsearch_file
from .pfam_common import filter_fasta_hmm_... |
abc7aeedd650bd14376c7f35a689fe71c9dc72c1ca717f8d900df5b4f5a7252a | Python | 3,737 | 131 | """
Core layers provide basic operations, e.g., MLP
"""
from typing import List, Union
import torch
from torch import nn, Tensor, tensor
ACTIVATION_MAPPING = {
"swish": nn.SiLU(),
"silu": nn.SiLU(),
"relu": nn.ReLU(),
"sigmoid": nn.Sigmoid(),
}
class ZeroLayer(nn.Module):
r"""A skeleton layer t... |
fd2b5546f7c4d07e2bdf388ac89d5f5d6c1153769f654606dc9f9d09476b2799 | Python | 3,737 | 127 | """Tests for run_kwargs support in registration and task claiming."""
from typing import Any, ClassVar
from zndraw_joblib.client import (
Category,
ClaimedTask,
Extension,
JobManager,
)
class Echo(Extension):
"""Extension that records what run() received."""
category: ClassVar[Category] = C... |
075e607f736583941ee208f001a59f7acd09288d7aa8662110872675902cf239 | Python | 3,740 | 101 | """
create_configs.py
- code for creating a set of configuration files for optimising the MLP for
several subjects
- run this script (from iml-dl/.) with:
python -u ./projects/moco_t2star/preprocessing/create_configs.py
--base_config_path /path_to_base_config_file.yaml
--output_directory /path_... |
b7e85eb0bb03c228666cf22e534318dbf1c04df9b786013ff772771749f511c0 | Python | 3,740 | 107 | import os
import pandas as pd
import datetime
import numpy as np
from medperf.entities.benchmark import Benchmark
from medperf.entities.dataset import Dataset
from medperf import config
from .utils import get_institution_from_email, stage_id2name
def get_dsets(benchmark_id):
bmk = Benchmark.get(benchmark_id)
... |
21f855ed8c945f3264e1375f0146c8095b703c6334a5fdda4af908f63c175a13 | Python | 3,743 | 117 | # This file is part of h5py, a Python interface to the HDF5 library.
#
# http://www.h5py.org
#
# Copyright 2008-2013 Andrew Collette and contributors
#
# License: Standard 3-clause BSD; see "license.txt" for full license terms
# and contributor agreement.
"""
This is the h5py package, a Python interface... |
9b81c37ee06de824ce5d2c9dd4cb1a31cad187308ffb97415e7054ae76667041 | Python | 3,746 | 106 | # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved.
# pyre-strict
# pyre-ignore-all-errors[58]
import torch
from torch.nn import functional as F
def sigmoid_focal_loss(
inputs: torch.Tensor,
targets: torch.Tensor,
alpha: float = -1,
gamma: float = 2,
reduction: str = "none",
... |
c00fbd2593a8043d6fd8017e49ef73260f3d2cc08a91db2b992a43d19c3fa1b6 | Python | 3,747 | 104 | # Copyright (c) OpenMMLab. All rights reserved.
import os.path as osp
import shutil
from unittest import TestCase
import numpy as np
import torch
from mmengine.structures import PixelData
from mmseg.evaluation import IoUMetric
from mmseg.structures import SegDataSample
class TestIoUMetric(TestCase):
def _demo_... |
7ce88158b51c241e00e1857f0fc7e1d85cd70aca677534d9f2c962cc21fa5c9e | Python | 3,748 | 112 | # Copyright (c) OpenMMLab. All rights reserved.
from argparse import ArgumentParser, Namespace
from pathlib import Path
from tempfile import TemporaryDirectory
from mmengine import Config
from mmengine.utils import mkdir_or_exist
try:
from model_archiver.model_packaging import package_model
from model_archive... |
d092653916a0911345d95c1d8fd9847d9242052eb0f38f56398fd985091619de | Python | 3,749 | 96 | # Copyright (c) OpenMMLab. All rights reserved.
import pytest
import torch
from mmseg.models.losses import DiceLoss
@pytest.mark.parametrize('naive_dice', [True, False])
def test_dice_loss(naive_dice):
loss_class = DiceLoss
pred = torch.rand((1, 10, 4, 4))
target = torch.randint(0, 10, (1, 4, 4))
wei... |
a7c31104777d8c957032224612021019e0fe06bc506bd65b578fb0cc0e3e883b | Python | 3,751 | 116 | """
Copyright (c) Facebook, Inc. and its affiliates.
This source code is licensed under the MIT license found in the
LICENSE file in the root directory of this source tree.
"""
import bisect
import pickle
from pathlib import Path
import lmdb
import numpy as np
from torch.utils.data import Dataset
from torch_geometri... |
942585284273e3e743cfcf4e65ca164f6e33ff0a50515bc87fc468b120f24f8e | Python | 3,756 | 89 | import unittest
import tempfile
import caffe
from caffe import layers as L
from caffe import params as P
def lenet(batch_size):
n = caffe.NetSpec()
n.data, n.label = L.DummyData(shape=[dict(dim=[batch_size, 1, 28, 28]),
dict(dim=[batch_size, 1, 1, 1])],
... |
356f79708b520751db053876cf6184093dfabbeda47b218e754fc89f652789c1 | Python | 3,759 | 134 | """ephys/morphologies.py unit tests"""
import json
import os
import pytest
import bluepyopt.ephys as ephys
from bluepyopt.ephys.serializer import instantiator
testdata_dir = os.path.join(
os.path.dirname(
os.path.abspath(__file__)),
'testdata')
simpleswc_morphpath = os.path.join(testdata_dir, 'sim... |
e75b2809f29fc7390943d9078c9d168e65355cd90e62aae65025c4c4af8a9946 | Python | 3,759 | 134 | import os
from kgx.source import JsonSource
from kgx.transformer import Transformer
from tests import RESOURCE_DIR
def test_read_json1():
"""
Read from a JSON using JsonSource.
"""
t = Transformer()
s = JsonSource(t)
g = s.parse(os.path.join(RESOURCE_DIR, "valid.json"))
nodes = {}
edg... |
a22a925fea5a0fc0b1b7b666534fa2018dbfff83920c6e949e92f0cc6416335e | Python | 3,764 | 84 | import shutil
from pathlib import Path
import pandas as pd
import pytest
from guppy.testing.api import locate_run_folder, step1, step2, step3, step4
from guppy_test_data import STUBBED_TESTING_DATA
def _stage_session(*, session_subdir: str, destination_parent) -> str:
"""Copy a stubbed session into its own pare... |
3b741749f74acb99c404b568467ec40744fc2c9454127f6b18618ea91f537016 | Python | 3,768 | 90 | from mpi4py import MPI
import numpy as np
import hickle as hkl
from grid_cell.persistent_homology import Is_Torus
from grid_cell.manifold_fitter import GP_Fitter, Avg_Fitter
from grid_cell.ploter import error_bar_plot
import matplotlib.pyplot as plt
import tensorflow as tf
import os
from sklearn import datasets
from gl... |
b58103bc63d26b8e0d78632a440b8b84486d5cf67544e0aff1f9d60b6cf982d0 | Python | 3,769 | 91 | import pandas as pd
import argparse
from scipy.spatial import Delaunay
import matplotlib.pyplot as plt
import numpy as np
import seaborn as sns
from matplotlib.lines import Line2D
import os
def parse_args():
parser = argparse.ArgumentParser(description='Transfer input to gml file')
parser.add_argu... |
7f2718259e59286eb9c47d5d2b94791503133b456c28024f3a5860f78ec715b2 | Python | 3,770 | 116 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
import pandas as pd
import itertools
class qdata(pd.DataFrame):
def __init__(self, data, sort=True, encoding_function=False):
"""
Parameters
----------
data : pandas.DataFrame
Dataframe including the columns 'spec' ... |
c837ac924419ba6650f9c6749504f3c924e357b0f27d10e85a060b09958d9f2e | Python | 3,771 | 130 | """Test ephys model objects"""
# pylint: disable=R0914
import os
import pytest
import numpy
from bluepyopt import ephys
TESTDATA_DIR = os.path.join(
os.path.dirname(
os.path.abspath(__file__)),
'testdata')
simple_morphology_path = os.path.join(TESTDATA_DIR, 'simple.swc')
@pytest.mark.unit
def t... |
30516ed421bf79b6e76a08a60f5fdfc821742fb7df2497f3d74264ddd06fbc24 | Python | 3,772 | 109 | """
Test the layers. Currently only on cpu since travis doesn't have GPU.
"""
import unittest
import pytest
import librosa
import numpy as np
import torch
import torch.nn as nn
from torchaudio_contrib.layers import (STFT, Spectrogram, MelFilterbank, AmplitudeToDb, TimeStretch,
Com... |
7bb7149b945e38e073f1b4d64e36fae08c0fe5f0f91bf9f7c3dcf330105f2b0f | Python | 3,773 | 110 | # Copyright (c) OpenMMLab. All rights reserved.
import argparse
import os
import os.path as osp
import tempfile
import zipfile
import mmcv
import numpy as np
from mmengine.utils import mkdir_or_exist
def parse_args():
parser = argparse.ArgumentParser(
description='Convert REFUGE dataset to mmsegmentation... |
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