sha256 stringlengths 64 64 | language stringclasses 27
values | size int32 1 491k | lines int32 1 21.8k | content stringlengths 1 200k |
|---|---|---|---|---|
d4e7a22b302681be03c183cfa929c486673c3eed81cde09194302df2c814e40f | Python | 3,417 | 102 | """
To analyze 'elements' inserted into backbones in the style of sarah's paper
"""
import numpy as np
import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt
from RiboGraphViz import LoopExtruder, StackExtruder
from scipy.cluster.hierarchy import ward, fcluster, dendrogram
from scipy.spatial.distance... |
d97d5ce7c9b69d260ed66f3f75e32d7892cc42d6021a90909efa88ae5bba29e7 | Python | 3,417 | 95 | # Utility functions for mocking comms and its methods
from typing import Dict, List, Callable, Union
from unittest.mock import MagicMock
from medperf.exceptions import CommunicationRetrievalError
def mock_comms_entity_gets(
mocker,
comms: MagicMock,
generate_fn: Callable,
comms_calls: Dict[str, str],... |
baffed0b1e0f1109d1f0e80d842ee86bfc8e12a865df3ed8095245e7fb7f1ad5 | Python | 3,418 | 95 | import tsgm
import keras
import numpy as np
try:
import tensorflow_probability as tfp
from tensorflow_probability import sts
DEFAULT_TREND = sts.LocalLinearTrend()
DEFAULT_SEASONAL = tfp.sts.Seasonal(num_seasons=12)
DEFAULT_MODEL = sts.Sum([DEFAULT_TREND, DEFAULT_SEASONAL])
has_tensorflow = T... |
bd8e96421c8982acf18fb7a4bd9a76d150865931a701fc922e8b9b06afaeee9b | Python | 3,418 | 88 | """
This scripts runs the regional attribution experiment.
Dependencies:
- outputs/graphtrip/weights/
Outputs:
- outputs/graphtrip/regional_attributions/
Author: Hanna M. Tolle
Date: 2025-05-31
License: BSD 3-Clause
"""
import matplotlib
matplotlib.use('Agg') # Set non-interactive backend
import sys
sys.path.appen... |
d22a71aadc17fbdbfa8ec56bd0d6e8a5a3b37fafbd812142b173997a17486c01 | Python | 3,420 | 122 | import sys
import os
import torch
import numpy as np
import csv
class Logger(object):
def __init__(self, fpath=None, mode='w'):
self.console = sys.stdout
self.file = None
if fpath is not None:
self.file = open(fpath, mode)
def __del__(self):
self.close... |
48b91616f70b87cd25a104ddb138146ac57bf456e8f60317821a51a949367c2e | Python | 3,421 | 112 | import os
import pytest
from kgx.transformer import Transformer
from tests import RESOURCE_DIR, TARGET_DIR
from kgx.config import get_logger
from tests.integration import (
check_arango_container,
clean_arango_slate,
ARANGO_CONTAINER_NAME,
DEFAULT_ARANGO_URL,
DEFAULT_ARANGO_USERNAME,
DEFAULT_A... |
17486789f0879964ba88b10caeaea0786ea51057d1907852e90830701979b478 | Python | 3,422 | 98 | ## 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
import numpy as np
import os
import argparse
from tqdm import tqdm
import torch
import torch.nn as nn
imp... |
74f263f5094dd8e0a72d55415df68ecf44204526a1fa90266aac922fdeee94ba | Python | 3,422 | 101 | import nibabel as nib
import numpy as np
import glob
import matplotlib.pyplot as plt
from skimage.filters import threshold_otsu
import re
import os
from scipy.ndimage.filters import gaussian_filter1d
def get_section_means(file_list:list, correction_factors=None):
"""Find and ssort section files"""
otsu_me... |
9582c8895b70cff09dd72ef0452efdfeb04e8b5cb179dd32246be20fe9abe4c0 | Python | 3,422 | 98 | 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 .models import ModelResult
from .serializers import ModelResultSerializer, ModelResultDetailSerializer
f... |
583caff290dc78c5ec5eafe8bc66fc5cea2498a0be29fd54c16a57a90d6d708a | Python | 3,424 | 86 | # Copyright (c) OpenMMLab. All rights reserved.
from typing import List, Union
import torch
from mmengine import ConfigDict
from mmengine.structures import InstanceData
from scipy.optimize import linear_sum_assignment
from torch.cuda.amp import autocast
from mmseg.registry import TASK_UTILS
from .base_assigner import... |
070513c5d5e93750d7b97e04344b0bde19e89f7ba539a6d562666eba5b06f611 | Python | 3,425 | 93 | from transformers import TrainingArguments
from trl import SFTTrainer, DataCollatorForCompletionOnlyLM
from unsloth import FastLanguageModel
from datasets import load_dataset
import pandas as pd
import argparse
import torch
if __name__ == '__main__':
parser = argparse.ArgumentParser()
parser.add_argument("... |
b94b8a26e3018092d8670f47f6e0b4979f0394ec7adbba06d2086fff41e72c38 | Python | 3,425 | 110 | from __future__ import absolute_import
from __future__ import print_function
import pytest
from keras.models import Model, Sequential
from keras.layers import Dense, Input
def test_layer_trainability_switch():
# with constructor argument, in Sequential
model = Sequential()
model.add(Dense(2, trainable=Fa... |
ed14c981983c307ba617820b58176adcfef104bbdcf1837702050a93b7284a4d | Python | 3,425 | 105 | from typing import Any, Dict
from hypothesis import given, note, settings, strategies
import xgboost as xgb
from xgboost import testing as tm
from xgboost.testing.params import (
exact_parameter_strategy,
hist_cache_strategy,
hist_multi_parameter_strategy,
hist_parameter_strategy,
)
from xgboost.testi... |
03e4916049b0064eaad01fd799c1cde09bfeb1c5bea64b90a30a269cc6e0ca83 | Python | 3,426 | 111 | import os
import ray
from ray import tune
from ray.tune import CLIReporter
from ray.tune.schedulers import ASHAScheduler
from ocpmodels.common.flags import flags
from ocpmodels.common.registry import registry
from ocpmodels.common.utils import build_config, setup_imports
# this function is general and should work f... |
3c7e2abdd152938c4fd64ee3349f6b80566ae240fea02f3faf10ae1c66f6f79e | Python | 3,426 | 87 | import os
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import shap
import pickle
import seaborn as sns
from sklearn.metrics import roc_curve, precision_recall_curve, auc
from sklearn.metrics import roc_auc_score, average_precision_score
from sklearn.metrics import precision_recall_curve, matth... |
5ed575aec352471a5e61209cd12d615f7597fe066b5307680fdcc06e042ed037 | Python | 3,427 | 81 | import numpy as np
import matplotlib.pyplot as plt
import os
from grid_cell.ploter import scatter_torus_ploter
from grid_cell.manifold_fitter import GP_Fitter, Avg_Fitter, label_mesh
from grid_cell.gkr import GKR_Fitter
from sklearn.decomposition import PCA
from umap import UMAP
from global_setting import *
##########... |
fb74ea0702755352cf2f10573b67ef2a85ec7b5ca2d636229895d4a2011f102c | Python | 3,428 | 103 | from __future__ import annotations
import random
import numpy as np
import pytest
import torch
from pymatgen.core import Lattice, Structure
from chgnet.data.dataset import StructureData, get_train_val_test_loader
from chgnet.graph import CrystalGraph
lattice = Lattice.cubic(4)
species = ["Na", "Cl"]
coords = [[0, 0... |
7f3adfe5abca88172c89b1835e2141ea72c95df6eec606a61bde61b80fe830b4 | Python | 3,429 | 114 | import numpy as np
import math
import sys
from tqdm import tqdm
SEED = 1717
np.random.seed(SEED)
EPSILON = sys.float_info.epsilon
def transform(y, num_terms=6, bandwidth_term=1/2):
B = bandwidth_term
exp = np.exp(-B * y**2)
terms = []
for i in range(num_terms):
terms.append(exp * (y)**i / m... |
a982bd0a0c1b6d644d2fba18ec6f863301342352baae6358f0d405ad85f123b1 | Python | 3,430 | 120 | # pytest unit tests for sct_qc
import pytest
import logging
import json
import os
from spinalcordtoolbox.scripts import sct_qc, sct_deepseg
from spinalcordtoolbox.utils.sys import sct_test_path
logger = logging.getLogger(__name__)
@pytest.mark.sct_testing
def test_sct_qc_no_checks():
"""Run the CLI script with... |
fa917de5eff4e85bdfc9fa5a18cf5fe28d5c7b6bcce1a5e5e98dad8fde418aa3 | Python | 3,430 | 116 | from django.db import migrations, models
from catmaid.control.volume import update_volume_meta_information
forward = """
SELECT disable_history_tracking_for_table('catmaid_volume'::regclass,
get_history_table_name('catmaid_volume'::regclass));
SELECT drop_history_view_for_table('catmaid_volume'::r... |
c3e909930e0249f9b7fb68ee6613258987d37d0cc67e6664f38f9947cd634da0 | Python | 3,431 | 56 | from models import RescorlaWagnerModel, DualSystems
from trainers import Trainer
import pandas as pd
import torch
from datasets import load_dataset
import os
experiments = [
#{'name': 'horizon1', 'agent': 'centaur', 'path': 'wilson2014humans/simulation0.csv', 'model': RescorlaWagnerModel(num_options=2)},
#{'na... |
7ff1a5f1b6a87e422268de4f25ddbac5347fdc00cb5e923e7f169d95fb5adbc2 | Python | 3,433 | 120 | import typer
from typing import Optional
from pathlib import Path
import medperf.config as config
from medperf.decorators import clean_except
from medperf.commands.view import EntityView
from medperf.entities.report import TestReport
from medperf.commands.list import EntityList
from medperf.commands.compatibility_test... |
9fbc4f36e301e4090106064905f71cbacb5d6ce1d41120a39ece4efe26d18aca | Python | 3,435 | 92 | ##############################################################################
# Obsolete import
# Need to check if this script is still useful for the project
##############################################################################
import time
import numpy as np
import pytraj as pt
from Nearl import utils
de... |
ad8767e751d984d254eb2dc8e09b67776f647f462d50c3d285a1cf1dc66f3579 | Python | 3,436 | 95 | import torch
from src.metrics_and_losses import (per_prop_mse, per_prop_stable_mse, per_prop_r2)
import os
import numpy as np
class Checkpointing:
def __init__(self,
property_names,
model,
artefact_dir,
model_type,
smoothing_... |
b55bb4223caf8c99bb427a4f98d6a580d9c40b3426d8e3517f8fb09e0d9c17b3 | Python | 3,436 | 100 | # Copyright (c) OpenMMLab. All rights reserved.
import logging
import os
from argparse import ArgumentParser
import requests
import yaml as yml
from mmseg.utils import get_root_logger
def check_url(url):
"""Check url response status.
Args:
url (str): url needed to check.
Returns:
int, ... |
e124da0faa4839521ca6f4e39c9cf6abfd3b07383606d8d115b9f4d71e854148 | Python | 3,437 | 90 | #!/usr/bin/env python3
# #############################################################################
# Copyright (c) 2018-present lzutao <taolzu(at)gmail.com>
# All rights reserved.
#
# This source code is licensed under both the BSD-style license (found in the
# LICENSE file in the root directory of this source t... |
6b1f99e42174bdb068b5ca732058f9801fcc855fb997eb323debfce223d5a192 | Python | 3,438 | 95 | # FCN model
# when tuning start with learning rate->mini_batch_size ->
# momentum-> #hidden_units -> # learning_rate_decay -> #layers
import tensorflow.keras as keras
import tensorflow as tf
import numpy as np
import time
from utils.utils import save_logs
from utils.utils import calculate_metrics
class Classifier_CNN... |
a48b60d61d904a34b0fe26074f31efd14699b22247b17b54d990aac03426d240 | Python | 3,441 | 81 | from pyxtal import pyxtal
from p_tqdm import p_map
from sklearn.model_selection import train_test_split
from pymatgen.core import Structure
from pymatgen.core.lattice import Lattice
def structure_to_str(structure):
# 转换pymatgen结构为pyxtal结构
px_structure = pyxtal()
px_structure._from_pymatgen(structure)
#... |
273f9a567f1d44878c1e5df4c2320c7d6f87083bf3f03e2c7fd7a8337eb4dad5 | Python | 3,443 | 110 |
import numpy as np
import pandas as pd
from sklearn.preprocessing import StandardScaler
import mne # MNE for EEG signal processing
# --------------- For raw EEG data (e.g., .edf, .set, .bdf files) ---------------- #
def load_eeg_raw(file_path, file_format='edf'):
"""
Loads raw EEG file using MNE.
Suppor... |
7244bda755d1a93bfb3b48ba3f0cbc07c3194954e23cc540bb2ba486c8924531 | Python | 3,447 | 122 | import re
import numpy as np
from pyalfe.data_structure import Modality, Orientation
def detect_modality(series_desc, seq, contrast_agent, te):
"""This function applies a set of rules to detect the modality
Parameters
----------
series_desc: str
Dicom Series Discription Attribute.
seq: ... |
a026b7ba37f1e08c58801de1fa8632d44f7be8eb5162c3021f04792672f3d9dc | Python | 3,449 | 112 | """Display-time rendering for whole-session time-binned metrics.
The binned values are drawn as bars spanning the bins they summarize, stacked
under the trace they were reduced from. Both panels share the ``time (s)``
dimension, so bokeh links their axes and zooming the bars zooms the trace with
them -- which is what ... |
39e80232062b7c6742e126d11b6419e36c43b0d63c43e771ae810d7f755db566 | Python | 3,452 | 89 | DOCS = """
train the model on the a dataset (gabor or mnist) or show the model learns to represent the data and predict the input
Current figures: figure 2.
"""
from dataset import Digit
from model import ShallowMLP
from experiment.utils import set_seed, init_model, Logger, Trainer, Checkpointer
import torch
import to... |
1b35d83d47417e000935c992e7f4193c277254f8d4592c36452370a46500bdb3 | Python | 3,455 | 98 | """
Collection of examples for using xgboost.spark estimator interface
==================================================================
@author: Weichen Xu
"""
import sklearn.datasets
from pyspark.ml.evaluation import MulticlassClassificationEvaluator, RegressionEvaluator
from pyspark.ml.linalg import Vectors
from ... |
45877a488a788cf554ee3c8d1268cb47b958db2051cd5354df552ddfb30a57b0 | Python | 3,455 | 113 | import math
import random
import torch
import torch.nn.functional as F
from ._base import register_transform
def _extend_mask(mask, chain_nb):
"""
Args:
mask, chain_nb: (L, ).
"""
# Shift right
mask_sr = torch.logical_and(
F.pad(mask[:-1], pad=(1,0), value=0),
(F.pad(chain... |
bb4e9cdd343860176a617d9c8426ad71c3684f4975a5069c48591fd2fe41c362 | Python | 3,455 | 102 | import igraph as ig
from igraph import Graph
import numpy as np
from scipy.spatial import Delaunay
import matplotlib.pyplot as plt
from utils import generate_labels
import os
# vertices = [[5,8],[6,7],[2,9],[2,5],[0,7],[2,9]]
# number_of_graph_vertices = 10
# number_of_vertices_labels = 6
def generate_del... |
db7d05157951e7c21db68b557cb554f669f273cb09e74d79f75047eb9bdac09c | Python | 3,457 | 121 | import numpy as np
class SimpleTransformer:
"""
SimpleTransformer is a simple class for preprocessing and deprocessing
images for caffe.
"""
def __init__(self, mean=[128, 128, 128]):
self.mean = np.array(mean, dtype=np.float32)
self.scale = 1.0
def set_mean(self, mean):
... |
4019b8f9d2cf9807e62c7fec52e911db80b9eb2166d2e176d2a9138553b210ca | Python | 3,459 | 72 | import pandas as pd
from experiment import *
import h5py
import numpy as np
if __name__ == "__main__":
min_angle = params["min_angle"]
max_angle = params["max_angle"]
conf = params["confidence_threshold"]
for species, tracking_directory in expt.directory["tracking", "eyes"].items():
if specie... |
d4c7e324a18fa6c736fdf31c777c1da7564c8cf42f4ec467fb361c0eb3496a21 | Python | 3,459 | 112 | """
This file is part of the Firmware project to interface with small Async or Neuromorphic chips
Copyright (C) 2022 Willian Soares Girao - University of Groningen
Copyright (C) 2023 Ole Richter - University of Groningen
This program is free software: you can redistribute it and/or modify
it under ... |
339573d86c46bb8d5effaf0704414163f7c0d4488f15fe3a0f64e14018bb82c5 | Python | 3,460 | 98 | # -*- coding: utf-8 -*-
import json
from .common import CatmaidApiTestCase
class LogsApiTests(CatmaidApiTestCase):
log_rows = [
[
'test2',
'create_neuron',
'2012-07-22T16:50:57.758000+00:00',
5290... |
145c9220047a1cd0d2d23add2948b06f4a548a767c8ce4fc35716a4f5ac3084c | Python | 3,461 | 80 | import os.path
import argparse
from typing import Any, Dict, List
def model_trainer(
model: Any,
save_dir: str,
train_data: Any,
valid_data: Any,
metrics: List[Any],
score_name: str,
transformers: List[Any],
text: str,
args: argparse.Namespace,
n_epoch: int = None,
patience... |
6b5b87f968b45d0274456b2747cd018a519db6137cd951dc03cc21babde78fdc | Python | 3,461 | 99 | import logging
from pathlib import Path
import numpy as np
import sqlmodel as sqlm
import torch
from torch.utils.data import DataLoader, TensorDataset, random_split
from torch.utils.tensorboard.writer import SummaryWriter
from tqdm import tqdm
from typer import Typer
from DiastereomericResolutions.main.training impor... |
1dfb49cc40c8117d59ea4994bfa583b87384671ab6e95d7c1c1a3f8d3690ad2a | Python | 3,463 | 110 | _base_ = [
'../_base_/datasets/ade20k.py', '../_base_/default_runtime.py',
'../_base_/schedules/schedule_80k.py'
]
crop_size = (512, 512)
data_preprocessor = dict(
type='SegDataPreProcessor',
mean=[123.675, 116.28, 103.53],
std=[58.395, 57.12, 57.375],
bgr_to_rgb=True,
pad_val=0,
size=cr... |
dfd9b5076ba64e6af0d3f2da121249e317ed63521966f442b1181ef2d79a54d4 | Python | 3,463 | 84 | """Network tests for the PANTHER family download.
The pipeline uses FTP (ftp.pantherdb.org), but FTP is often blocked by HPC firewalls.
PANTHER also exposes the same files over HTTP; these tests check both endpoints.
Run with: uv run pytest --network tests/datahandlers/test_pantherfamily.py
"""
import ftplib
import ... |
2874a5e89484ff262d60e459949da70a5ecaf5585ee81dc909599ceeffc4f041 | Python | 3,464 | 106 | """Tests for various command line options."""
import pytest
from cwltool.utils import versionstring
from .util import get_data, get_main_output, needs_docker
def test_version() -> None:
"""Test --version."""
return_code, stdout, stderr = get_main_output(["--version"])
assert return_code == 0
assert... |
dc04c073c600a0f624eaf41e9a0a3d6c96805d3894b7e43c5f192a3a959c81a7 | Python | 3,464 | 108 | # -*- coding: utf-8 -*-
"""
Created on Tue Sep 24 16:16:30 2024
@author: AC
"""
import pandas as pd
from sklearn.model_selection import train_test_split
from xgboost import XGBClassifier
from sklearn.metrics import accuracy_score, precision_score, recall_score, f1_score, confusion_matrix, roc_auc_score, roc... |
e226b534b9758854ae5555ad9005f074e7309d14a0ba6f7216aa83dc88e45767 | Python | 3,466 | 111 | _base_ = [
'../_base_/datasets/ade20k.py', '../_base_/default_runtime.py',
'../_base_/schedules/schedule_80k.py'
]
crop_size = (512, 512)
data_preprocessor = dict(
type='SegDataPreProcessor',
mean=[123.675, 116.28, 103.53],
std=[58.395, 57.12, 57.375],
bgr_to_rgb=True,
pad_val=0,
size=cr... |
1b2eba2d0be409fd2c083a7b13164ebf11e2e72cb6d563f9be3cdf4bb157ef48 | Python | 3,467 | 109 | """Regression tests for NaN-containing pure-Python multitaper windows."""
import os
import sys
import unittest
import numpy as np
from scipy.signal.windows import dpss
# Run directly from the repository without installing a package.
sys.path.insert(0, os.path.dirname(os.path.abspath(__file__)))
from multitaper_spec... |
8c1a51252fdfcf0b7fc524ef83acf41c0ab27c92d92040bf92a2eeeeefa2e320 | Python | 3,467 | 94 | import pyoxigraph
from src.babel_utils import make_local_name, pull_via_urllib
from src.metadata.provenance import write_concord_metadata
from src.prefixes import EC, RHEA
def pull_rhea():
pull_via_urllib("https://ftp.expasy.org/databases/rhea/rdf/", "rhea.rdf.gz", subpath="RHEA", decompress=True)
class Rhea:
... |
c2204dc3f3e3816eb5d2d9fa29b75e29378c91f96644a0db14176f39fc52b731 | Python | 3,467 | 97 | # -*- coding: utf-8 -*-
import json
from catmaid.control.annotation import _annotate_entities
from catmaid.models import ClassInstance, Log
from .common import CatmaidApiTestCase
class NeuronsApiTests(CatmaidApiTestCase):
def test_rename_neuron(self):
self.fake_authentication()
neuron_id = 233
... |
346633b5b140d0722465e4713c437d450f798bbb0a72504d9026ebb7a1cee850 | Python | 3,468 | 113 | """
paq2py
Read PAQ file (from PackIO) into python
Lloyd Russell 2015
"""
import numpy as np
import seaborn as sns
def paq_read(file_path=None, plot=False):
"""
Read PAQ file (from PackIO) into python
Lloyd Russell 2015
Parameters
==========
file_path : str, optional
full path to file ... |
9e68ab19ff4174946122b3b641f56b0dfefb093232fdbcf4a8c5ab3f54f328ba | Python | 3,468 | 108 | #!/usr/bin/env python3
import numpy as np
import pickle
class History:
def __init__(self, csvpath=None, warmup=0):
'''
warmup: `int`
Write only if `self.count > warmup`.
Useful if unknown columns appear after the first row.
'''
self.data = dict() # Data c... |
ac00ae6869ebd3f72a7ac611d68bbadee5a294c1d070a61971b3aaa96c0c781c | Python | 3,468 | 80 | # def evaluatePrediction(region, sam, sigAlign, label, genome, model, weight, kmerWindow=80, signalWindow=400,
# modBase = ['AT', 'TA']):
# alignment = getAlignedReads(sam = sam, region = region, genome=genome, print_name=False)
# refSeq = alignment['ref']
# all_scores, modCount... |
44f633e10cf224a7fa37a1a131172e800d3a6849436c5f9f01070b5d6462bac9 | Python | 3,469 | 88 | from transformers import TrainingArguments, AutoModelForCausalLM, AutoTokenizer
from trl import SFTTrainer, DataCollatorForCompletionOnlyLM
from datasets import load_dataset
import pandas as pd
import argparse
import torch
if __name__ == '__main__':
parser = argparse.ArgumentParser()
parser.add_argument("-... |
ab8b9d6cbeb8e38478d0d0dab9271a24092c3e6646755ce30e9c18bef47ca600 | Python | 3,469 | 80 | # -*- coding: utf-8 -*-
import json
from django.http import HttpRequest, JsonResponse
from catmaid.models import UserRole, ChangeRequest
from catmaid.control.authentication import requires_user_role
@requires_user_role(UserRole.Browse)
def list_notifications(request:HttpRequest, project_id = None) -> JsonResponse:... |
e43b070a141c9e9ecf411592accd3d79c7fb83b1a95f7355d5150faaef863f18 | Python | 3,469 | 81 | import logging
from collections import OrderedDict
from collections.abc import Sequence
import numpy as np
from ..utils.validation import validate_peak_windows
logger = logging.getLogger(__name__)
def compute_psth_peak_and_area(
psth_mean: np.ndarray,
timestamps: np.ndarray,
sampling_rate: float,
p... |
9d7f12f34954a1639623ecf847c0317ad57b6cec0661652644da144e6387b828 | Python | 3,470 | 98 | # 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... |
3f198f6d0b74634d8e3e3012b5d9c86a9eaf0b683fde16d84b88693ab00afa58 | Python | 3,473 | 98 | import glob
import os
import numpy as np
from PIL import Image
root_path = 'data/'
img_suffix = '.tif'
seg_map_suffix = '.png'
save_img_suffix = '.png'
save_seg_map_suffix = '.png'
src_img_train_dir = os.path.join(root_path, 'AV_groundTruth/training/images/')
src_img_test_dir = os.path.join(root_path, 'AV_groundTruth... |
ddcbbf989dd8b82433889d615557b757a6f24fcb51db33d7e40972fddb3990e4 | Python | 3,473 | 90 | # pytest unit tests for sct_label_utils
import pytest
import logging
import numpy as np
from spinalcordtoolbox.image import Image
from spinalcordtoolbox.types import Coordinate
from spinalcordtoolbox.utils.sys import sct_test_path
from spinalcordtoolbox.scripts import sct_label_utils, sct_create_mask
logger = loggi... |
0f71feb6983f305c012fcb4bd18da745af6d488f5716ee185eb12f697b7c3e6d | Python | 3,474 | 102 | # Copyright (c) OpenMMLab. All rights reserved.
import torch
import torch.nn as nn
from mmcv.cnn import ConvModule, DepthwiseSeparableConvModule
from mmseg.registry import MODELS
from ..utils import resize
from .aspp_head import ASPPHead, ASPPModule
class DepthwiseSeparableASPPModule(ASPPModule):
"""Atrous Spati... |
c88629242f697cb21c7231fde852c3352175596f7eb1d8e8ea4f4a58ebf35907 | Python | 3,478 | 94 | # Copyright (c) OpenMMLab. All rights reserved.
from typing import List, Optional, Union
import torch.nn as nn
import torch.nn.functional as F
from torch import Tensor
from mmseg.registry import MODELS
@MODELS.register_module()
class OhemCrossEntropy(nn.Module):
"""OhemCrossEntropy loss.
This func is modif... |
17fe5ce2275d2098bce2a062818deb3bd55fd42f763827c229fb6672ac863c6c | Python | 3,481 | 115 | import csv
import numpy as np
def createManualSpikeSortingLog(
sessions,
filename,
minimumPresenceRatio=0.9,
maximumRefractoryPeriodViolationRate=0.5,
maximumAmplitudeCutoff=0.1,
maximumProbabilityValue=0.05,
returnEntries=False,
targetUnitQuality='high',
):
"""
"""
all... |
2ff4202653e36cba7f25f74bb70dc5edc937306e747549abc80986a7e55c4707 | Python | 3,482 | 87 | """
Concatenates multiple 3D atlases into a single 4D volume.
Author: Hanna Tolle
Date: 21.12.2024
License: BSD-3-Clause
"""
import os
import glob
import nibabel as nib
import numpy as np
import argparse
def concat_atlases(atlas_dir: str, output_dir: str, receptor_names: list):
"""
Concatenates multiple 3D at... |
411033a479b5840e2c05d0bbfc0cde020c1f74c9d330dbace801abd1536b0f89 | Python | 3,482 | 112 | _base_ = [
'../_base_/datasets/ade20k.py', '../_base_/default_runtime.py',
'../_base_/schedules/schedule_80k.py'
]
crop_size = (512, 512)
data_preprocessor = dict(
type='SegDataPreProcessor',
mean=[123.675, 116.28, 103.53],
std=[58.395, 57.12, 57.375],
bgr_to_rgb=True,
pad_val=0,
size=cr... |
14a8ddbfd4e39d596e3b3e9357299d704fe00a49ac61da4e917d051f707a87bf | Python | 3,483 | 66 | # 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... |
cc8950d1349400369ea51c3b3573ac48718c864047873ace825bb943064ab36e | Python | 3,483 | 111 | """
Extract static/dynamic featuresfor single residue classification
"""
import os, sys, argparse
import numpy as np
import nearl
import nearl.data
from collections import OrderedDict
from nearl.io.traj import MisatoTraj
nearl.update_config(
verbose = False,
debug = False,
# verbose = True,
# debug = T... |
20336b75b9105b7c8159c03b2e70be3a5e5d1eaea22c349f9a2396312997dc3f | Python | 3,488 | 56 | # 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... |
f60b9a72889181ca7842f8fc795d76622ecd238a1d8238b9bb85f2df60bdd39b | Python | 3,488 | 92 | import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
import numpy as np
import math
import scienceplots
import matplotlib.gridspec as gridspec
from functools import reduce
import torch
import math
from scipy import stats
from datasets import load_dataset
import matplotlib as mpl
test_data = load_... |
1b1ed70b5a70711f936ee0b21beff3150534610225be2676394a5ba4a7fce30e | Python | 3,491 | 120 | """
================================================
Comparison of Picard-O and FastICA on faces data
================================================
This example compares FastICA and Picard-O:
Pierre Ablin, Jean-François Cardoso, Alexandre Gramfort
"Faster ICA under orthogonal constraint"
ICASSP, 2018
https://arxiv... |
74ad7805f948ae98c6c1b733203964289675309617722284e20570f1433270c8 | Python | 3,491 | 125 | """MLCube handler file"""
import os
import yaml
import typer
import shutil
from preprocess import Preprocessor
from check import Checker
from statistics import Stats
app = typer.Typer()
class PreprocessTask(object):
"""
Task for preprocessing the data
Arguments:
- data_path: data location.
"""
... |
86c40bf870c87fa08e89add3c16f6d9d810ccbc006f48cd70293de2b5215bb18 | Python | 3,491 | 117 | from __future__ import annotations
import base64
import pathlib
from typing import Annotated
import typer
from zndraw.schemas import (
OffsetPage,
ScreenshotListItem,
ScreenshotResponse,
)
from .connection import (
PasswordOpt,
RoomOpt,
TokenOpt,
UrlOpt,
UserOpt,
cli_error_handle... |
78cfb5f47b13d4fdb7b6306d434966d4a2b004cc09630a8b6d0d979fde4c44a4 | Python | 3,492 | 117 | 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... |
1c81e15be76061938a293ddc319f615da0f91ba97ea5ba40c4cf353fe6dc6a67 | Python | 3,494 | 111 | _base_ = [
'../_base_/datasets/ade20k.py', '../_base_/default_runtime.py',
'../_base_/schedules/schedule_80k.py'
]
crop_size = (512, 512)
data_preprocessor = dict(
type='SegDataPreProcessor',
mean=[123.675, 116.28, 103.53],
std=[58.395, 57.12, 57.375],
bgr_to_rgb=True,
pad_val=0,
size=cr... |
46ec10adfef9fe08db14994914751a5d2364eff41704fac960164da8c2add3fc | Python | 3,494 | 110 | import json
import numpy as np
from copy import deepcopy
def forceFortranOrder(funcname):
old_func = getattr(np, funcname)
def new_func(*args, **kwargs):
kwargs['order'] = 'F'
return old_func(*args, **kwargs)
setattr(np, funcname, new_func)
class Specification:
def __init__(self, par... |
b671d594005f12acc0dbab5e42a665544caa90f323f11811a7984d5f694b3da9 | Python | 3,494 | 105 | # -*- coding: utf-8 -*-
"""
Created on Wed Sep 25 11:04:51 2024
@author: AC
"""
import pandas as pd
from sklearn.model_selection import train_test_split
from sklearn.preprocessing import StandardScaler
from sklearn.neighbors import KNeighborsClassifier
from sklearn.metrics import accuracy_score, precision_... |
35eb7546cb89b9ea27d7822eb6ef81fc46082e69f59b846e8d8cd91253328094 | Python | 3,497 | 102 | import numpy as np
import torch
import torch.nn as nn
from scipy import linalg
from tqdm import tqdm
from basicsr.models.archs.inception import InceptionV3
def load_patched_inception_v3(device='cuda',
resize_input=True,
normalize_input=False):
# we may ... |
6003a98d551edba33a290abb104b0aba3923952b264b23b3ae0e32503c035b5e | Python | 3,498 | 103 | # -*- coding: utf-8 -*-
# tests/test_doctests.py
################################################################################
# EncoderMap: A python library for dimensionality reduction.
#
# Copyright 2019-2024 University of Konstanz and the Authors
#
# Authors:
# Kevin Sawade
#
# Encodermap is free software: you c... |
37d0bf7c73181a988cf7331fc10d485dd4f0d6b33f914dae4227d158b5e60e42 | Python | 3,499 | 141 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
from Bio import Phylo
import pandas as pd
import matplotlib.pyplot as plt
from itertools import combinations
from copy import deepcopy
def read_tree(file):
return Phylo.read(file, "newick")
def write_tree(tree, file):
Phylo.write(tree, file, 'newick')
def ... |
a0a8a5d81ebed42f89ef20eda344105dd20a5b38b73403183835454e021f5ed5 | Python | 3,499 | 73 | # 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... |
abe7d61b45852838593795ab8681b693caa9d4ae08276a1cbfb38b77efdd51c9 | Python | 3,500 | 108 | """bluepyopt.optimisations tests"""
import bluepyopt.optimisations
import bluepyopt.ephys.examples.simplecell
import pytest
import numpy
import deap.tools
@pytest.mark.unit
def test_DEAPOptimisation_constructor():
"deapext.optimisation: Testing constructor DEAPOptimisation"
simplecell = bluepyopt.ephys.e... |
2e5e6714ac1358de9fecc5fb8c5aea2b56d915ebb71793c2de295918fdab17e2 | Python | 3,502 | 123 | """
Copyright (c) 2016-2020, 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.
... |
ffdf9817a74c49ec8af653d1170d4aaf85b5fd55e19ec04298b672eba42326d3 | Python | 3,504 | 71 | import pandas as pd
from sklearn.preprocessing import QuantileTransformer
from dataAnalysis.Constants import *
import torch
def count_cbc_cases(data):
comp_data = data.query("~(WBC.isnull() & HGB.isnull() & MCV.isnull() & PLT.isnull() & RBC.isnull())",
engine='python')
unique_data = ... |
e01114ecfbfd848ff111c4be0b9b7f0ac459f4b25182e23bf9e64e69e0877999 | Python | 3,505 | 83 | """
This script is used to distribute the motion curves among different sets and
map between curves and subjects within the val and test splits.
- run this script (from iml-dl/.) with:
python -u ./projects/motion-simulation/preprocessing/data_split_motion_curves.py
--input_dir folder_with_motion_data --outp... |
8f80c645968a91bc23e122ec7f2957cff4738d98f3fa92e19960caedb3a42434 | Python | 3,506 | 106 | # Input/Output with the Python Subprocess module
# Author: David Young, 2020
"""File management using underlying system commands accessed through the
Python :mod:`subprocess` module.
"""
import os
import subprocess
from magmap.io import libmag
def compress_file(path_in, path_out=None):
"""Compress a file or fil... |
bb071460ce0dcc81bf3952d9cfc2011f3743cd3192bb735370f3c32f51060c72 | Python | 3,507 | 84 | # -*- coding: utf-8 -*-
"""
Created on Wed Sep 24 12:39:51 2024
@author: AC
"""
import pandas as pd
from pathlib import Path
# Set pandas display options
pd.set_option('display.max_rows', None)
pd.set_option('display.max_columns', None)
# Load the CSV file into a DataFrame
data_dir = Path("D:/ownClou... |
c0f0c29be9d0a88bbb5641e71363b1d9314819d348204d8ddcdb793224508b26 | Python | 3,507 | 164 | import serial
import pathlib as pl
HANDSHAKE = bytes('h', 'utf-8')
ON = bytes('p', 'utf-8')
OFF = bytes('z', 'utf-8')
RESET = bytes('r', 'utf-8')
commands = {
'signal' : bytes('s', 'utf-8'),
'connect': bytes('c', 'utf-8'),
'release': bytes('r', 'utf-8')
}
class Microcontroller():
"""... |
28e4afeaa3984c3d9a68444315d8087d8e26ab1041978a3a1d8b52fd565004e9 | Python | 3,508 | 111 | import numpy as np
import matplotlib.pyplot as plt
import pingouin as pg
import hickle as hkl
import os
from scipy import stats
from sklearn.linear_model import LogisticRegression
from grid_cell.lole import LOLE, LOCF
from sklearn.svm import SVC
from sklearn.ensemble import RandomForestClassifier
from grid_cell.grid_... |
991e7907b4101ecd8511b33f1fc11a4904181e679ba898959ea879b4e15e414f | Python | 3,508 | 100 | import argparse
import glob
import os.path as osp
from gather_models import get_final_results
from mmengine import Config
from mmengine.fileio import dump
def parse_args():
parser = argparse.ArgumentParser(
description='Gather benchmarked models train results')
parser.add_argument('config', help='tes... |
fe8a7238b973d87d7f83b35c2d2d657a2ff4b4fc402de6eb81950ae563ba5090 | Python | 3,508 | 95 | import os
from glob import glob
import shutil
import argparse
import json
from typing import Union
from bdpy.dataset.utils import download_file as bdpy_download_file
FIGSHARE_URL_PREFIX = 'https://figshare.com/ndownloader/files/'
FIGSHARE_FALLBACK_PREFIX = 'https://ndownloader.figshare.com/files/'
def main(cfg):
... |
f42cdae59dd48a17b4a7bf972dde43189c8e726d64da4598f4d2b5c0407d89bb | Python | 3,509 | 119 | import copy
import warnings
import numpy as np
import torch
import torch.nn as nn
from torch_geometric.data import Batch, Data
from torch_geometric.loader import DataLoader
from .warmup import GradualWarmupScheduler
# customize exp lr scheduler with min lr
class ExponentialLR_with_minLr(torch.optim.lr_scheduler.Exp... |
4b1a7cc15307d7ac3890f746404bbc9664f839ed72650692f7f382258ad5dd43 | Python | 3,510 | 101 | from medperf import config
from medperf.account_management.account_management import get_medperf_user_data
from medperf.entities.ca import CA
from medperf.entities.training_exp import TrainingExp
from medperf.entities.cube import Cube
from medperf.utils import (
get_pki_assets_path,
generate_tmp_path,
dict_... |
63075b150a01ae4b9d9e61d1dc5f51cdf2bf052b4fecf214b2503cf67f955bf7 | Python | 3,510 | 139 | import sys
import os
import pandas as pd
import numpy as np
from sklearn.preprocessing import MinMaxScaler
from sklearn import svm
def main():
# total arguments
n = len(sys.argv)
print("Total arguments passed:", n)
print("Run folder: " + str(os.getcwd()))
cwd = os.getcwd()
# Arguments ... |
232fee5127ee1d8691be14f11618eff7de459ae8564d09b5d3a866f20bd6523d | Python | 3,511 | 83 | # pytest unit tests for spinalcordtoolbox.utils.shell
import os
import sys
import pytest
from stat import S_IEXEC
from spinalcordtoolbox.utils import shell
def test_parse_num_list_inv():
assert shell.parse_num_list_inv([1, 2, 3, 5, 6, 9]) == '1:3;5:6;9'
assert shell.parse_num_list_inv([3, 2, 1, 5]) == '1:3;... |
9561342d266af72375aadceb4bd117ab2bf96c5240e43021c572781e3170f249 | Python | 3,511 | 125 | import uuid
from typing import Optional, Tuple
from fastapi import Request
from starlette.middleware.wsgi import WSGIMiddleware
from medperf.dashboard.preparation_dashboard import build_app
from medperf.entities.cube import Cube
from medperf.utils import sanitize_path
MIN_SEARCH_LENGTH = 2
SEARCH_DEBOUNCE_MS = 300
... |
4a874e5482a5b10b87fa333ea204e005bcc1e865aae59edf0959f04de0ac2252 | Python | 3,512 | 119 | import numpy as np
import cupy as cp
from scipy.stats import norm
def calc_wtx_corr(wtx1, wtx2, l):
corr_max = -cp.inf
shift_max = 0
for i in range(l*2-1):
shift = i-(l-1)
corr = cp.corrcoef(wtx1[l:-l], wtx2[l+shift:-l+shift])[0, 1]
if corr > corr_max:
corr_max = corr
... |
f351bc23b7da8cb01373c07bdd4f5786ce51c30f1656e957f1f6051920d3bfa4 | Python | 3,514 | 105 | # Generated by Django 2.1.5 on 2019-02-14 03:02
import django.contrib.postgres.fields
from django.db import migrations, models
forward = """
SELECT disable_history_tracking_for_table('nblast_similarity'::regclass,
get_history_table_name('nblast_similarity'::regclass));
SELECT drop_history_view_fo... |
827fea756e60e38ef43f4f860604838de683426bb9a13bdecaa45aeab92bb405 | Python | 3,516 | 85 | # Copyright (c) OpenMMLab. All rights reserved.
import torch
import torch.nn as nn
import torch.nn.functional as F
from .base_pixel_sampler import BasePixelSampler
from .builder import PIXEL_SAMPLERS
@PIXEL_SAMPLERS.register_module()
class OHEMPixelSampler(BasePixelSampler):
"""Online Hard Example Mining Sampler... |
21e111fbe83d8df42dc75b190132e2b7c0b75efc194314ffdd2cb8f9cc6209dd | Python | 3,517 | 82 | """Mixin of contract tests for :mod:`guppy.utils.dandi_search`.
The contract is what has to hold of any archive the search reads, so it is bound twice: once to
the in-memory stand-in in ``test_dandi_search.py`` and once to the real DANDI Archive in
``test_dandi_search_live.py``. Everything here is about the shape of w... |
afaa4109cb926485af12e84101d86e635cb0d4b3f355481d7959ee612e6a32c6 | Python | 3,519 | 94 | # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved.
# -*- coding: utf-8 -*-
# pyre-strict
import itertools
import unittest
from typing import List, Tuple
import numpy as np
import torch
from fvcore.nn import update_bn_stats
from torch import nn
class TestPreciseBN(unittest.TestCase):
def se... |
3dfaad3957a6b5761ef8fabcdd24d8be8252c3fbc8d5f98ca08a286adca4044e | Python | 3,520 | 112 | # 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 --------------------------------------------------------------
# If ex... |
6843b8423790b5182ae887aa5093d8916f00de3f163dcca1a58ee863b152cade | Python | 3,520 | 129 | import random
import unittest
from soccertrack.metrics import ap_score, iou_score, map_score
class TestMetrics(unittest.TestCase):
def test_iou_score_1(self):
bbox_det = [10, 10, 20, 20]
bbox_gt = [10, 15, 20, 20]
iou = iou_score(bbox_det, bbox_gt)
ans = 0.5
self.assertEq... |
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