sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
c4f50bd624369a3054c65f8e327107bb6d2d7359cec52db917a7cfd8c18d9dde | Python | 1,763 | 50 | __author__ = "quentin"
from ethoscope.hardware.interfaces.lynx_motion import LynxMotionInterface
class SleepDepriverInterface(LynxMotionInterface):
def send(self, channel, dt=350, margin=10):
"""
Sleep deprive an animal by rotating its tube.
:param channel: The channel to use (i.e. the nu... |
eaf33d4a1d279a1f68aa971b3c1823fb8a27e0dd7f2ad3d2ad2f4854ed0ab157 | Python | 1,763 | 54 | from setuptools import setup, find_packages
from pathlib import Path
this_directory = Path(__file__).parent
long_description = (this_directory / "README.md").read_text()
setup(
name="tomopari",
version="0.2.16",
description="A plugin for accelerated tomographic reconstruction.",
long_description=long... |
6e680c87839d65f29da6e3f5c9f94c94181a538c19e67c0664d59c07ab44b1e5 | Python | 1,764 | 36 | from pyrosm.data_manager import get_osm_data
from pyrosm.frames import prepare_geodataframe
import warnings
def get_network_data(node_coordinates, way_records, tags_as_columns,
network_filter, bounding_box, slice_to_segments):
# Tags to keep as separate columns
tags_as_columns += ["id", "... |
e0c6118881f3b21505bcefeb582659b806f0069083e84b014be997305b83bcdd | Python | 1,764 | 56 | import os
import json
"""
Meta.json is the core for each model. It contains the combination of morphologies and
parameter sets.
"""
def write_meta(directory, selected=False):
"""
meta.json contains the combinations of morphologies and parameter sets and
additional parameters f... |
65b079c8da165ff48772bb1b16e5fed0006dddb17fd7f8efa75d13e00187b618 | Python | 1,765 | 57 | """Common type definitions.
The annotation files in BDD100K format has additional annotations
('other person', 'other vehicle' and 'trail') besides the considered
categories ('car', 'pedestrian', 'truck', etc.) to indicate the uncertain
regions. Given the different handlings of these additional classes, we
provide thr... |
8ede87ef554d9bcfe00f96607041e51adfe1f21685534549de2ff2c2b4c1975f | Python | 1,765 | 59 | """This module runs continuous updates for R, such as redrawing graphs when
the plot window is resized. Use the start() and stop() functions to turn
updates on and off.
"""
from rpy2.rinterface import process_revents
import time
import warnings
import threading
class _EventProcessorThread(threading.Thread):
""" ... |
12839978cfef4d8b8300b996bb31650425118a1de44678ffa0ed3044e5351273 | Python | 1,766 | 66 | """Classic clean-versus-corrupted out patching.
What this demonstrates
----------------------
Capture a clean run and a corrupted run, then patch the corrupted ReLU
out with the clean out.
How to run
----------
``python examples/intervention/03_out_patching_paired_prompt.py``
Runnable by default. The "prompts" are s... |
56b0915adbaa8582fb3c54a164c6581124aa0b7725f12441f2dda378beb75e2f | Python | 1,766 | 70 | """
Custom parameters and parameterized classes extending those existing in the
`param` package.
Previous versions eagerly re-exported everything with star-imports. We now lazy
load these to avoid heavy import chains and potential cycles while preserving
the public API surface.
"""
from __future__ import annotations
... |
f7acda30b4fd501430b26e2e8b9c3226efe4677eb27272afa39bfc2246c70f61 | Python | 1,766 | 55 | import os
from setuptools import find_packages, setup
def read_requirements(path):
with open(path, "r") as f:
return [line.strip() for line in f if line.strip() and not line.lstrip().startswith("#")]
with open("README.md", "r", encoding="UTF-8") as fh:
long_description = fh.read()
setup(
name=... |
e8ff764977f10e6b4495916dc98d8b0a831fcc24e98a7a259b6f37fe117d7e4b | Python | 1,767 | 55 | from __future__ import division
import unittest
import numpy as np
from wyrm.processing import calculate_whitening_matrix, apply_spatial_filter
from wyrm.types import Data
SAMPLES = 1000
CHANS = 3
class TestCalculateWhitentingMatrix(unittest.TestCase):
def setUp(self):
data = np.random.randn(SAMPLES... |
faf7b76fc3b13d1911def628f2eb7e6baefff670de1692f0573973faec2a46be | Python | 1,767 | 43 | """Drop whole-text annotation indexes.
Revision ID: a4c3f2e1b790
Revises: e96dd6fd5863
Create Date: 2026-09-17
"""
from galaxy.model.migrations.util import (
create_index,
drop_index,
index_names_on_columns,
)
revision = "a4c3f2e1b790"
down_revision = "e96dd6fd5863"
branch_labels = None
depends_on = None... |
f261c0a6ad58b3e3bc3b7c04833df3c9051ac952c87f6842fd9dc3ccac3b3326 | Python | 1,768 | 58 | 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"]["motif_width"] = 13
msp.architecture["motif_model_spec"]["motif_feature... |
4f3115c18642066f59fffe208b6860a42813691a7c339a66551d931b02d11b87 | Python | 1,769 | 51 | import json
import pandas as pd
from tqdm import tqdm
tqdm.pandas()
def main():
type_ = 'old'
test = pd.read_csv(f'./data/csvs/data/test_new_{type_}.csv')
old_new = pd.read_csv(f'./data/csvs/data/test_new_old.csv')
old_new = old_new[['Drug2_ID', 'Drug2_SMILES']]
with open('./data/jsons/tf_... |
96fff76f9a32177e572bb3a317ba4b2a08695542d52f914ceb8473a4c1a2c55e | Python | 1,769 | 39 | import tensorflow as tf
from tensorflow.keras.layers import (Dense, Dropout, Embedding, Layer,
LayerNormalization, MultiHeadAttention)
from tensorflow.keras.models import Sequential
class TransformerBlock(Layer):
def __init__(self, embed_dim, num_heads, ff_dim, rate=0.1):
... |
a81b87733ccb0c6d359e9c1c61ba1554304c7be8d1a0ee9fb442a860f5e8ce1b | Python | 1,769 | 77 | """
spike_features.py
Basic modules for spike feature extractions.
"""
import numpy as np
##########################################################################
##########################################################################
def return_mfr(spiketimes, time_window):
"""
Returns mean firing ra... |
ef0993d5b220ff6fc8a8ff62e6b8eb3b85f122debda3d65c747b9bab387e4cd8 | Python | 1,769 | 54 | import os
import argparse
import logging
import autogluon.core as ag
from gluoncv.auto.tasks import ObjectDetection
from gluoncv.auto.estimators import YOLOv3Estimator
from d8.object_detection import Dataset
os.environ['MXNET_ENABLE_GPU_P2P'] = '0'
if __name__ == '__main__':
# user defined arguments
parser ... |
16b74aafa625905d5b083867f6aa40bd2a4495d4defc74fa7dc33b6208fa8efc | Python | 1,770 | 60 | #!/usr/bin/env python
import numpy as np
import argparse
parser = argparse.ArgumentParser(description='Plot weight histogram.')
parser.add_argument('--freq', type=float, default=1.0, help='repetitation freq')
parser.add_argument('--pairings', type=int, default=100, help='nb pairings')
parser.add_argument('--interval'... |
22ea40259e80f449b6c59de201c65b6229aafe29669894dbac07bf63813c953e | Python | 1,770 | 64 | """Publish an intervention recipe with ``.tlspec``.
What this demonstrates
----------------------
Save a portable intervention spec, load it back, and check that it still
targets a fresh compatible capture.
How to run
----------
``python examples/intervention/15_publishing_for_reproducibility.py``
Runnable by defaul... |
67488e864bf04ad512c90cf21d5323b61dbc3167047e2f5a5fc539659753001d | Python | 1,770 | 56 | import os
from options.test_options import TestOptions
from data import create_dataset
from models import create_model
from util.visualizer import save_images
from itertools import islice
from util import html
import time
start_time = time.time()
# options
opt = TestOptions().parse()
opt.num_threads = 1 # test code... |
ffdf2c3017637fb071facc0c34a4119384e6fe37f9e579d4d06764d01d3a529e | Python | 1,770 | 47 | import torch
import torch.nn.functional as F
from torch import nn
class SPADE(nn.Module):
def __init__(self, kernel_size, norm_nc, label_nc, param_free_norm_type='batch'):
super().__init__()
if param_free_norm_type == 'instance':
self.param_free_norm = nn.InstanceNorm2d(norm_nc, affine... |
54c8e63302e006f58e7c9b752a4be9a32adca2e91de878d009d15763adcab9b0 | Python | 1,771 | 69 | '''
Copyright 2023 Douglas Feitosa Tomé
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 Software Foundation, either version 3 of the License, or
(at your option) any later version.
This program is distributed in the hop... |
0769bf7c9786a8e381a53ab30288b2cb075c5818358e52117fd124e7e4e793c3 | Python | 1,772 | 52 | #!/usr/bin/env python
# =============================================================================
# MODULE DOCSTRING
# =============================================================================
"""
Test objects and function in the module ``tfep.potentials.base``.
"""
# ======================================... |
4bc43b559e3c868a6c26e0701f37a4120f0dcb43980240716db011ebf4f9872c | Python | 1,772 | 46 | import pytest
import torch
from lightly.loss.ibot_loss import IBOTPatchLoss
class TestIBOTPatchLoss:
@pytest.mark.parametrize("device", ["cpu", "cuda"])
def test_forward(self, device: str) -> None:
if not torch.cuda.is_available() and device == "cuda":
pytest.skip("CUDA not available")
... |
4fa4a70ef82de3dd172f6ff8f55bf85bc489813436ff69da515be4065321c966 | Python | 1,773 | 75 | """
Widget for editing the borders placed in an environment.
"""
from __future__ import annotations
import param
from .widget_base import (
classdict_editor,
collapsible_family_box,
family_box,
parameterized_editor,
)
__all__ = ["build_border_widget"]
def _ordered_names(instance: param.Parameteriz... |
0db70258f211758ec5183e87e8811fc85f45a8cf38e062c03ba5436c8bd613bf | Python | 1,774 | 102 | """
Location of protocols used in datatypes
"""
from typing import Any
from typing_extensions import (
Protocol,
runtime_checkable,
)
from galaxy.objectstore import ObjectStoreAuth
class HasClearAssociatedFiles(Protocol):
def clear_associated_files(self, metadata_safe: bool = False, purge: bool = False... |
256e8b082b777388915c88d3d2e80e0f040fbefeff9cbf5ab43f2fa0fbc163f2 | Python | 1,774 | 44 | from __future__ import division
import argparse
import numpy as np
import mxnet as mx
from mxnet import gluon, nd, image
import matplotlib.pyplot as plt
import gluoncv as gcv
gcv.utils.check_version('0.6.0')
from gluoncv import data
from gluoncv.model_zoo import get_model
from gluoncv.data.transforms.pose import det... |
41d9c308ef8502c11a32d25ae51e3c789ea0981cd830cb35552df080b398c3c5 | Python | 1,774 | 45 | import unittest
from os.path import join, abspath
import os
from numpy.testing import assert_allclose
from tests.tabulation.adiabatic_equilibrium.rebless import run
from spitfire.chemistry.library import Library
import spitfire.chemistry.analysis as sca
from spitfire.chemistry.ctversion import check as cantera_versio... |
731ff1302f7e372ce406d42e9fb7d5eaa7476d1149ef07e9559414aaa5611d3b | Python | 1,774 | 73 | """Set of functions for logging messages."""
import sys
import warnings
from typing import Optional, Type
from gym.utils import colorize
DEBUG = 10
INFO = 20
WARN = 30
ERROR = 40
DISABLED = 50
min_level = 30
# Ensure DeprecationWarning to be displayed (#2685, #3059)
warnings.filterwarnings("once", "", DeprecationW... |
8de21629e22da1c8222eed54537aec980a61ab8b64e4e446f122e80b8b0185e7 | Python | 1,774 | 55 | from __future__ import annotations
import pytest
from pytest_celery import RESULT_TIMEOUT, CeleryTestSetup, CeleryTestWorker, CeleryWorkerCluster
from celery import Celery
from t.smoke.conftest import SuiteOperations, WorkerKill
from t.smoke.tasks import long_running_task
@pytest.fixture
def celery_worker_cluster(
... |
d79c3cb616a022a1a9243c84631f835110f6489f3f6c58f07a747e943a186162 | Python | 1,774 | 54 | 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... |
66fd82350f5c0ba84118ba6bbd65d5f732a6109d190f257e670899a9a9b06ad1 | Python | 1,775 | 54 | import numpy as np
import torch
from scipy.optimize import linear_sum_assignment
from sklearn import metrics
from torch import nn
class ZINBLoss(nn.Module):
def __init__(self):
super().__init__()
def forward(self, mean, disp, pi, x=None, eps=1e-10):
if x is None:
zero_nb = torch.p... |
0c8a006c7cf5a53ca400deaa96eda7d4d18817f6b72aaa949130adca30fbb60c | Python | 1,776 | 44 | """Stop-early surface tests (A06 rewrite: ``stop_after`` is WIRED).
Historical note: these tests originally pinned the pre-wiring defect --
``pluck`` accepted-and-ignored ``stop_after`` while ``trace`` raised
``NotImplementedError``. A06 wired the option through the halt engine with
brainpipe's inclusive spelling; the... |
2a504ee4a58deb26879c2c0f65c46d3922ba5316f27fcc044960704479ca283e | Python | 1,777 | 57 | from os.path import dirname, join
import numpy as np
from sklearn.datasets.base import Bunch
def load_housing():
from pandas import read_csv
"""Load and return the Copenhagen housing survey dataset
(ordinal classification).
============== ==============
Samples total 1681
... |
3e9501333e7bdd61c56b9e18ba1230c073c8b93a059f3804e1f8e4c94090a531 | Python | 1,777 | 63 | #!/usr/bin/env python
# =============================================================================
# MODULE DOCSTRING
# =============================================================================
"""
Base conditioner classes for autoregressive flows.
"""
# =====================================================... |
8d261417f43ef704419a743285f538a274c560064f947e8f1e154a7f7f63aabf | Python | 1,777 | 65 | """Module for handling image loading in torchvision-compatible format.
This module provides image loading functionality similar to torchvision's implementation
(see https://pytorch.org/vision/main/generated/torchvision.datasets.ImageFolder.html)
"""
# Copyright (c) 2020. Lightly AG and its affiliates.
# All Rights Re... |
9a1f7552bf91f6e530b6efa911b03801ad08e228c30cdcbe52c0145fdfe2ddca | Python | 1,777 | 46 | from distutils.core import setup, Extension
from distutils.command.build_ext import build_ext
import os
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
import num... |
b69a850d610fafc963a4bcb4825094d2e0210c0d9aae90b64e1f8afb8132d863 | Python | 1,777 | 55 | import functools
import os
from .data_directory import DATA_DIRECTORY
from .rbns import read_rbns_motif_from_file, read_rbns_motifs
RBNS_V2_EXTRAS_DIRECTORY = os.path.join(DATA_DIRECTORY, "motifs_rbns_v2_extras")
PASSED_QC = (
"CIRBP ELAVL1 ENOX1 ESRP1 EXOSC2 EXOSC4 EXOSC8 IGF2BP3 LIN28B NSUN2"
" PABPC3 PPP1R... |
1febd0fb03e2035a94141be13708b65137ad83dce2999ee5d74c77dd88fe7557 | Python | 1,778 | 53 | # pylint: disable=line-too-long
"""Encode/Decode helper function for compressed quantized models"""
import zlib
import base64
def encode_json(json_file, is_print=False):
r""" Encode json string to compressed base64 string.
Parameters
----------
json_file : str
String value represents the path ... |
24dc72b9503c6bbc30ca0f8d84b0f1d5fd9d2d72012c5dcc9caeb5b0ac725ac8 | Python | 1,778 | 65 | import subprocess
import requests
COMMITS = "https://api.github.com/repos/jsbroks/coco-annotator/commits/{}"
COMPARE = "https://api.github.com/repos/jsbroks/coco-annotator/compare/{}...{}"
CURRENT_VERSION = ""
LATEST_VERSION = ""
def get_tag():
result = subprocess.run(["git", "describe", "--abbrev=0", "--tags"... |
4e68fb70f684f5ce7f4282e427d2ebcb3ee0219955cab0b2d030306d131cabc4 | Python | 1,778 | 50 | import pytest
from ome_zarr.data import create_zarr
from ome_zarr.io import parse_url
from ome_zarr.reader import OMERO, Label, Labels, Multiscales, Node, Spec
class TestStartingPoints:
"""Creates a small but complete OME-Zarr file and tests that readers will detect the
correct type when starting at all the ... |
d2f8d9dac3e25bba227da060532db9617bf48d7e5e6c0b749727d167c8f18145 | Python | 1,780 | 68 | from modular_splicing.models_for_testing.models_for_testing import (
EndToEndModelsForTesting,
STANDARD_DENSITY,
)
am_ad_sparse = EndToEndModelsForTesting(
name="AM + adjusted donor",
path_prefix="model/msp-311a1",
seeds=(1, 2, 3),
density=STANDARD_DENSITY,
)
am_ad_nonsparse = EndToEndModelsFo... |
dd55fb03da861573b35e48dc2ede781bcedc6b6aad02f670e4d1e4bfa824fd98 | Python | 1,780 | 51 | #!/usr/bin/env python3
# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved.
"""Wrapper to train and test a video classification model."""
from slowfast.config.defaults import assert_and_infer_cfg
from slowfast.utils.misc import launch_job
from slowfast.utils.parser import load_config, parse_args
fr... |
e0dbc741feba7052b2e74d2403af08055bfffbfa5fef91ea75bab6a1d84932be | Python | 1,780 | 43 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""tests for optimizer"""
import unittest
import numpy as np
from sknetwork.data.test_graphs import test_graph
from sknetwork.gnn.gnn_classifier import GNNClassifier
from sknetwork.gnn.optimizer import get_optimizer
class TestOptimizer(unittest.TestCase):
def set... |
a401b71879c2b0a976516fbaad13063262ad5324ed35f6d703dbdece128bbb5e | Python | 1,781 | 56 | import os
import warnings
import h5py
import numpy as np
import scanpy as sc
from scbig import run_scbig, preprocess, setup_seed
warnings.filterwarnings('ignore')
import time
from memory_profiler import profile
@profile
def run(adata):
adata = run_scbig(adata)
from memory_profiler import memory_usage
m... |
10277310d6e91e0dd7b89546ce03ca5d3ad26e251b79b825527e2e71bc983d7b | Python | 1,782 | 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... |
3b390e0578f2a685963aa979ae4c4b449714b4ec80e6db4306dbe98cc7a39c05 | Python | 1,782 | 52 | from __future__ import annotations
import pytest
from kombu import Producer, Queue
from pytest_celery import CeleryBrokerCluster, RabbitMQTestBroker
from celery import Celery, uuid
from celery.app.amqp import Queues
@pytest.fixture
def celery_broker_cluster(celery_rabbitmq_broker: RabbitMQTestBroker) -> CeleryBroke... |
4228c968f1ffade6d54dd94797e24830ee355c5a418502b046a7cf59bafcb802 | Python | 1,782 | 53 | import logging
import secrets
import threading
from typing import Optional
import httpx
LOGGER = logging.getLogger(__name__)
class MatomoTracker:
"""Send events to Matomo's HTTP Tracking API for things the browser cannot
see, such as the account being created on the API side.
Events carry a category, a... |
423e01fa6fc92351668885e334a505201ff34fe2735eee3479e92e22dda77929 | Python | 1,783 | 44 | # ------------------------------------------------------------------------------
# Copyright (c) Microsoft Corporation. All rights reserved.
# Licensed under the MIT License.
# ------------------------------------------------------------------------------
from __future__ import absolute_import
from __future__ import d... |
c9b5a587b6ef4cf86b87f125d4769aac8287f17c74c4ed6aa0c2488ccdebdd87 | Python | 1,783 | 59 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Mon May 2 14:07:48 2022
@author: Audrey Mazancieux
This script rename physio files from the Prisma 3T scanner.
"""
import os
import glob
from sys import exit
import math
# =============================================================================
#... |
fdc59893104cab79a7e9890a3f847dace14d4f42ae8972005382aec49fe913b6 | Python | 1,783 | 44 | from imodelsx import submit_utils
from os.path import dirname
import os.path
repo_dir = dirname(dirname(os.path.abspath(__file__)))
# python /home/chansingh/llm-tree/experiments/01_train_model.py --use_cache 0 --subsample_frac 1 --model_name llm_tree --max_depth 3 --use_llm_refine 1
# python /home/chansingh/llm-tree/... |
71a7239f857f00b32936330ba64cdbcc25549e464acc08923e2c326438538609 | Python | 1,784 | 63 | from gymnasium.spaces import Box as GymBox
from gymnasium.spaces import Dict, MultiBinary, MultiDiscrete, Space, Tuple
from gymnasium.spaces import Discrete as GymDiscrete
from gymnasium.spaces.utils import flatdim, flatten, unflatten
class Box(GymBox):
"""Thin wrapper of gymnasium.spaces.Box.
Allow the user... |
8c93d7655043f366cbc469db3e2a21d9f9213c933896184dce2a28aceaadb2b3 | Python | 1,784 | 56 | import json
import pandas as pd
from tqdm import tqdm
def LCSubStr(X, Y):
# Create a table to store lengths of
# longest common suffixes of substrings.
# Note that LCSuff[i][j] contains the
# length of longest common suffix of
# X[0...i-1] and Y[0...j-1]. The first
# row and first column entries have no
# log... |
06a0127713bb9c2432b16206a0b31fa2ff556d77bdc2a781ed0f95886600b3bd | Python | 1,785 | 50 | #!/usr/bin/env python
# Variants of this code exists in 2 places, this file which has no
# user facing options which is called for implicit data conversion,
# lib/galaxy/datatypes/converters/fasta_to_tabular_converter.py
# and the user-facing Galaxy tool of the same name which has many
# options. That version is now on... |
0e9ef4bae4197e6d4e90e807d94d51885334d77fd614fa95269fdd735f7025ac | Python | 1,785 | 50 | import os
import random
import numpy as np
import torch
from PIL import Image
from torch.utils.data import Dataset
class DiffusionDataset(Dataset):
def __init__(self, image_dir, img_transform=None, label_transform=None, device=torch.device('cpu')):
self.image_dir = image_dir
self.image_path = os... |
d41b6bd067918e162d2079c8d5b0c9803cd41753ef7697fdaecc9674863ef150 | Python | 1,785 | 55 | import sys
from robustness import datasets
from robustness.attacker import AttackerModel
from robustness.model_utils import make_and_restore_model
import torch
from model_analysis_folders.all_model_info import IMAGENET_PATH
torch.backends.cudnn.benchmark = True
def build_net(ds_kwargs={}, return_metamer_layers=False):... |
240e89641a6b372b9f8082857a0690d02add4fe2bfcb36c515a8c0777ed3477c | Python | 1,786 | 45 | import pytest
import gym
from gym.envs.classic_control import CartPoleEnv
from gym.error import ResetNeeded
from gym.wrappers import OrderEnforcing
from tests.envs.utils import all_testing_env_specs
from tests.wrappers.utils import has_wrapper
@pytest.mark.parametrize(
"spec", all_testing_env_specs, ids=[spec.id... |
ee087c6c92b6f80a117642d223704b19d72213bb472fd71c4ba9e46eda849c2a | Python | 1,786 | 61 | from mirp._images.generic_image import GenericImage
class RTDoseImage(GenericImage):
def __init__(self, **kwargs):
super().__init__(**kwargs)
self.calibrated_units = True
@staticmethod
def get_default_lowest_intensity():
return 0.0
@staticmethod
def get_default_ivh_disc... |
f0f9c666cf4677328fd6e71eee218af9bfac2418aa788cebd1f03cfe85c45892 | Python | 1,787 | 48 | #!/usr/bin/env python3
import argparse
import functools
import pandas
from deepspeech_training.util.helpers import secs_to_hours
from pathlib import Path
def read_csvs(csv_files):
# Relative paths are relative to CSV location
def absolutify(csv, path):
path = Path(path)
if path.is_absolute():... |
402c3492eec3ebf2427c9d7698f43312b5ef8b3fc1b4eec4854693089b6c2b83 | Python | 1,788 | 39 | from torch.utils.data.dataset import random_split
from pl_bolts.datasets.sr_celeba_dataset import SRCelebA
from pl_bolts.datasets.sr_mnist_dataset import SRMNIST
from pl_bolts.datasets.sr_stl10_dataset import SRSTL10
def prepare_sr_datasets(dataset: str, scale_factor: int, data_dir: str):
"""Creates train, val, ... |
64d6f6349b36c804c73fcc517a16c14dc0789988362b964d78fcb9412aed42b0 | Python | 1,788 | 52 | """Standalone: re-run the getitem hot-path bench vs the design gates.
Run: pixi run -e dev python tests/bench_ragged_getitem.py
Gates: slice within ~1.2x of a bare numpy view-slice baseline;
to_numpy(validate=False) within ~1.2x of a bare reshape;
from_offsets within ~1.1x of a bare dataclass wrap."""
im... |
07e3af533cff8ce296dad07772304e85fc8bac956947de790d167a0b57af0480 | Python | 1,789 | 56 | """Tests for the xcp_d.interfaces.plotting module."""
import os
import numpy as np
import pandas as pd
from xcp_d.interfaces.plotting import CensoringPlot
def test_censoring_plot_marks_censor_between(tmp_path_factory):
"""The censoring plot draws a separate legend entry for censor-between volumes."""
impor... |
3a92946c75fe8a8cb1fcd536b65e4cac2ad5aacecc2465cbd7af4dc73e00903d | Python | 1,789 | 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/PediatricMRI_D... |
54b7a816508718162e0641d205844ea8328f5e6227d1bec2416817cee138fb2f | Python | 1,790 | 64 | # -*- coding: utf-8 -*-
import os
#%% function to write to a sbatch file
def get_default_conda_env(conda_env_sh):
conda_lines = f'''## activate the virtual environment
source {conda_env_sh}
conda_init > /dev/null 2>&1
conda deactivate > /dev/null 2>&1
conda activate fastai > /dev/null 2>&1
''... |
6ea4e9b99e265abcaddeb236c837c223d83d4934c07a54b8752eccd25889dfab | Python | 1,790 | 54 | import os
import pandas as pd
import numpy as np
from sklearn.ensemble import BaggingRegressor
from sklearn.ensemble import BaggingClassifier
from sklearn import linear_model
import sklearn
import pickle
def load_model(in_model_fp):
if not os.path.exists(in_model_fp):
print("Error: Can not find ensemble m... |
8f2ef1803a33e59eba84d6b6cc04c0d048257c0f585fbb5d5986a304ddea01b0 | Python | 1,790 | 43 | import tempfile
import os
from ethoscope.core.monitor import Monitor
from ethoscope.hardware.input.cameras import MovieVirtualCamera
from ethoscope.utils.io import SQLiteResultWriter, ResultWriter
from ethoscope.trackers.adaptive_bg_tracker import AdaptiveBGModel
from ethoscope.drawers.drawers import DefaultDrawer
from... |
e0f4ac2a63fcf69c80867477675d545f637ac052bd1c7d21b7ed9531a83d8076 | Python | 1,790 | 37 | '''Components of the package:
- The Brains class is used to represent the coordinates of multiple instances of
the same brain, like you have in a whole-brain imaging recording. Because the
number of detected neurons in each volume can fluctuate, the class uses the
irregular array (irrarray) from the mistofrutt... |
146c486b0a0dd2830a7885a94b61edff8be8a43b7ee588dab48891c88b799822 | Python | 1,791 | 57 | #!/usr/bin/env python
import unittest
import os
import json
import struct
import numpy as np
from wyrm.io import load_mushu_data
class TestLoadMushuData(unittest.TestCase):
def setUp(self):
with open('foo.meta', 'w') as fh:
json.dump({'Sampling Frequency' : 1,
'Chan... |
28fdc1b2865ca4bf0e64dd34e9d89c65e9ad0c53a028c2e6858f772c9bd1d587 | Python | 1,791 | 58 | import torch
from keras.src import ops
from keras.src import optimizers
from keras.src.backend.torch.optimizers import torch_parallel_optimizer
class Adadelta(
torch_parallel_optimizer.TorchParallelOptimizer, optimizers.Adadelta
):
def _parallel_update_step(
self,
grads,
variables,
... |
c1e3a9e30c6df9a3584ae39ec33cee8fc4b5ae6dfc13365f5dc6229ed6abfca6 | Python | 1,791 | 65 | import logging
import yaml
import argparse
from pymatgen.core import Molecule
from atomate.qchem.fireworks.core import SinglePointFW
from atomate.common.powerups import add_tags
from fireworks import LaunchPad, Workflow
from instance_mongodb import instance_mongodb_sei
from fireworks.user_objects.dupefinders.dupef... |
05f9f460517ae5048fc39d234a63acc85c515f207897b65aae6eb7932493b9f2 | Python | 1,792 | 67 | from cvnn.layers import ComplexUnPooling2D, complex_input, ComplexMaxPooling2DWithArgmax, \
ComplexUpSampling2D, ComplexMaxPooling2D
import tensorflow as tf
import numpy as np
from pdb import set_trace
def get_img():
img_r = np.array([[
[0, 1, 2],
[0, 2, 2],
[0, 5, 7]
], [
... |
e6ef57229016d86938a5b042ff653cd3f80f13c6a71d7c57fde29669e4a54c5a | Python | 1,792 | 66 | 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"]["motif_width"] = 13
msp.architecture["motif_model_spec"]["motif_feature_extractor_spec"] = dict(
type="ResidualStack",
depth=3,
)
msp.archi... |
4874ef7d3c2d54b9905dc09683d2d101b2a7a03b33aa52828d16e16edfa9026a | Python | 1,793 | 69 | from os import link
from .bulletin import Bulletin
from bs4 import BeautifulSoup
import re
class TamilNadu(Bulletin):
def __init__(self, basedir):
statename = 'TN'
super().__init__(basedir, statename)
self.bulletin_url = 'https://stopcorona.tn.gov.in/daily-bulletin/'
self.archi... |
8ab9b2331fb90220a1afffeb36e017f12ff2484e3bab1fe57e0fec70493d34cf | Python | 1,793 | 57 | import os
import h5py
import numpy as np
import scanpy as sc
from ica import ica1
from scbig.utils import setup_seed, louvain, calculate_metric
def preprocess(adata, scale=True):
sc.pp.filter_genes(adata, min_cells=3)
sc.pp.filter_cells(adata, min_genes=200)
sc.pp.normalize_total(adata, target_sum=1e4)
... |
9d6427467a59accd5e05fe1c802e31d7b6a828a31195ba545e18a648d78ae2f0 | Python | 1,793 | 48 | import os
import random
from abc import ABC
from .data_split import DataSplit
class ProteinSplit(DataSplit, ABC) :
def __init__(self,
split_type: str,
split_i: int,
cel_name: str = 'pdb_conf_ensembles',
root: str = '/home/bb596/hdd/pdbbi... |
01a9a1651bd4c5347a77bc7335a4bbcba678fcc6a33a9f44830ecea35d7b326f | Python | 1,794 | 51 | 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 PassReward(Wrapper):
metadata: dict[str, str | None] = { # noqa: RUF012
"description": ... |
241df0b29b51b049741b362dcb31e3c2ae39ac6c39c7ef7377f43f0769c8ad03 | Python | 1,794 | 54 | from typing import List, Sequence, Union
from PIL.Image import Image
from torch import Tensor
from lightly.transforms.torchvision_v2_compatibility import torchvision_transforms as T
class ImageGridTransform:
"""Transforms an image into multiple views and grids.
Used for VICRegL.
Attributes:
tr... |
43bc45ed9a14628284b7c82b9116e42f723d3a061f20a3ec9b754835b7d45c68 | Python | 1,794 | 66 | import logging
import os
from typing import Optional
def set_logger_format(custom_preamble: Optional[str] = ""):
logger = logging.getLogger("codecarbon")
format = "[%(name)s %(levelname)s @ %(asctime)s]"
if custom_preamble:
format += f"[{custom_preamble}]"
format += " %(message)s"
formatte... |
554b0343d1318734d12c781312448d55b77466ab23c68c314ddde44cf5eae95f | Python | 1,794 | 53 | import os
import argparse
import torch
from src import util
# Build em response tensors
def build_unit_activity_tensor(dataset):
unit_activity_list = []
for i, (_, y) in enumerate(dataset):
if i % 10000 == 0:
print(f"i={i}/{len(dataset)}")
unit_activity_list.append(y)
retur... |
7636e3941da5216980f4d5764eec2e77310016e95cadb5cc1037d084c200f983 | Python | 1,795 | 52 | """Single-sourcing gate for the lookback payload policy vocabulary.
The canonical authority is the ``LookbackPayloadPolicy`` literal in
``torchlens/fastlog/options.py``; the runtime tuple is derived from it with
``typing.get_args``, so validation and the type can never drift apart. These
tests pin that derivation and ... |
e13ba150d913299a2d0e9fe18830ad3baa0580ce12e22581d93b7e3e7ab7985d | Python | 1,795 | 51 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
# Rewrite an OpenCC config JSON so that its dictionary references point at
# a different dictionary format (text or ocd) instead of ocd2. Used to build
# the OPENCC_DICT_FORMAT=text/ocd CMake outputs, mirroring the ocd2<->text
# config conversion already used by the Bazel... |
398cda978e95a567c1bc33d9d306c18c861fe27f31b4cfeb1c3def992d2a0857 | Python | 1,796 | 50 | import numpy as np
from modular_splicing.dataset.additional_data import (
AdditionalData,
DatafileReferencingAdditionalData,
)
from modular_splicing.utils.genome_statistics import gene_at_richness
class GeneATRichnessAdditionalData(DatafileReferencingAdditionalData):
def __init__(self, *args, cl_max, **... |
adc8468f7e251f993cbd2f2b1e809ee5ba95854f466435724c3ab2648f3a5dc0 | Python | 1,796 | 43 | """
Use this code to evaluate all models from the different variants of experiment 2 (defined by the length of the pre-cue
delay interval) or experiment 4 (defined by the cue validity). Uncomment the relevant code section to run.
@author: emilia
"""
import importlib
from main import run_experiment
def run_all_varia... |
b04bf3cd349b0ea8f107b3af85aa836524eda2bb24d2e6869f4a7f4f5976873f | Python | 1,796 | 59 | """
Widget for editing a spatial distribution of agents or sources.
"""
from __future__ import annotations
import param
from .widget_base import family_box, numeric_tuple_param_control, param_control
__all__ = ["build_distribution_widget"]
def build_distribution_widget(
distribution: param.Parameterized,
... |
49d82b112f5afd4ee3957eef5307e059c0514a01f4b7923200f852b2698009de | Python | 1,797 | 60 | from __future__ import annotations
from abc import ABC, abstractmethod
from typing import Iterable, Any, TypeVar, Generic
from bdpy.task.callback import CallbackHandler, BaseCallback
_CallbackType = TypeVar("_CallbackType", bound=BaseCallback)
class BaseTask(ABC, Generic[_CallbackType]):
"""Base class for ta... |
e253b573c0831919f7b640b1cc77a7dbf213e45075e23c1a3a6e44aa401f2b06 | Python | 1,797 | 48 | # -*- coding: utf-8 -*-
from model import CGAN
from utils import input_setup
import numpy as np
import tensorflow as tf
import pprint
import os
flags = tf.app.flags
flags.DEFINE_integer("epoch", 10, "Number of epoch [10]")
flags.DEFINE_integer("batch_size", 32, "The size of batch images [128]")
flags.DEFINE_integer(... |
70619f4351c7beb6553f07d587840590a07970a0d962082f7d8006bde800e55b | Python | 1,799 | 50 | #!/usr/bin/env python3
'''Glob through files in current directory looking for */*_ligand.sdf and */*.gninatypes (assuming PDBbind layout).
Calculate the distance between centers. If types files are passed, create versions with this information,
optionally filtering.
'''
import sys,glob,argparse,os
import numpy as n... |
724b3500b32484ee32b1e8aea86afdf2db910513a1913e58a6e66733f3faf3dc | Python | 1,799 | 77 | import numpy as np
import torch as th
# __func is original, func is GPU optimized
def __random_aug(graph, x, feat_drop_rate, edge_mask_rate):
import dgl
n_node = graph.number_of_nodes()
edge_mask = mask_edge(graph, edge_mask_rate)
feat = drop_feature(x, feat_drop_rate)
ng = dgl.graph([])
ng... |
75b9b29d35406fb8888fc3ad25b4bd8bb09700de8f99bd2d9ff4f8b94244ec2f | Python | 1,799 | 62 | import numpy as np
from .hsmm_model import HSMM
def substring_hsmm(hsmm, new_initial, ell):
return HSMM(
initial=new_initial,
distance_distributions=substring_p(hsmm, ell),
transition_distributions=substring_a(hsmm, ell),
)
def substring_a(hsmm, ell):
states = hsmm.states
al... |
092f06aec5bd12f0108bb81d4a114aa2424807121ffcd6b9cd6e01993d3ebce7 | Python | 1,800 | 54 | """Consumer Broker Connection Bootstep."""
from kombu.common import ignore_errors
from kombu.utils.url import maybe_sanitize_url
from celery import bootsteps
from celery.utils.log import get_logger
__all__ = ('Connection',)
logger = get_logger(__name__)
info = logger.info
class Connection(bootsteps.StartStopStep):... |
0ce417f4460c8d9ca73939e3082dfa886c674d965c7c531d3be4ec553d17583d | Python | 1,800 | 55 | import os
import paddle
def print_metrics(loss, f_max, auprc):
print(f"loss: {loss:.4f}, f_max: {f_max:.4f}, auprc: {auprc:.4f}")
def get_model_params_state(model, args, epoch, f_max, auprc):
return {
"model": model.state_dict(),
"epoch": epoch,
"n_h_dim": args.n_h_dim,
"s_... |
c5c8a6dd1feeb5354834dc5d7ae93811c80af1e46a0ef2bd701389ce05c78eef | Python | 1,800 | 57 | import csv
import copy
#Функция, определяющая взаимодействие по главной/вспомогательной субъединице. X — цепь рецептора, Y — лиганда.
def site(X,Y):
if (X, Y) == ('B', 'D'):
return '+'
if (X, Y) == ('C', 'D'):
return '–'
Data="{}.csv"
Types=['HB','PHOB','PI','SB','STK']
D={} #Dictionary for data... |
697e7d20554bf43f291597780fb73693506fe3a7369fb64bd1b5f979ab63806d | Python | 1,803 | 47 | from __future__ import division
import unittest
import numpy as np
from wyrm.types import Data
from wyrm.processing import select_channels
from wyrm.processing import swapaxes
class TestSelectChannels(unittest.TestCase):
def setUp(self):
raw = np.arange(20).reshape(4, 5)
channels = ['ca1', 'ca2... |
83be96e73ba2729fd932ba5ccdd2f06207b4c4651f50f035c29a3dc97f925328 | Python | 1,803 | 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... |
a5cbc2b759ae29aaea21608309185b2f503b31f47edbd8cc12d2660ced4cac9d | Python | 1,803 | 33 | #!/usr/bin/env python3
import argparse
import os
import warnings
from predict import predict_itmt
from settings import CUDA_VISIBLE_DEVICES
if __name__ == '__main__':
parser = argparse.ArgumentParser(description = 'Input T1.nii.gz to predict iTMT(temporalis muscle thickness)')
parser.add_argument('--age', '-... |
f337d205126fb957979695d44347b078ac4f94193a8e9a59905e690ae4556e3d | Python | 1,804 | 52 | """A wrapper that adds render collection mode to an environment."""
import gym
class RenderCollection(gym.Wrapper):
"""Save collection of render frames."""
def __init__(self, env: gym.Env, pop_frames: bool = True, reset_clean: bool = True):
"""Initialize a :class:`RenderCollection` instance.
... |
5b9e68174411a4257476b40ed7cb711d554730fb15f847645447c6c467ef6a78 | Python | 1,805 | 66 | import torch
from pathlib import Path
import nibabel as nib
from DeepDenoise.src.res_unet import CESTResUNet
from DeepDenoise.src.unet import CESTUnet
import pytest
def test_unet():
# Initialize the model
model = CESTUnet(input_shape=(42, 128, 128))
# Generate a random input tensor
x = torch.randn((1... |
62cccf4d905ef68349654f39adc3f4304e6ce56161c5c8cbd043cfeabe0cb411 | Python | 1,805 | 48 | 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") -> torch.Tensor:
"""
Loss used in Reti... |
7088f899a5929361c11bacfa3f718875f9f45a63571c6c68eefa84250c8b0803 | Python | 1,805 | 69 | import numpy as np
from .coords import locations
def mask_percent_threshold(mat, thresh):
minv = np.min(mat)
maxv = np.max(mat)
val = (maxv-minv) * thresh/100.0
return mat > val
def mask_threshold(mat, thresh, func=lambda a,b: a>b):
return mat > thresh
def mask_num_std(mat, n, func=lambda a,b: a>... |
bfd2407bdaa7766ea2dd5388b77868177df1800c9cbeede0dd20e689e2f80cee | Python | 1,805 | 60 | 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="ParallelSpatiallySparse",
sparse_specs=[
dict(type="SpatiallySparseAcrossChannels"),
dict(type="SpatiallySparseAcros... |
e3710a7ad3d6466e926cd2557bdc07be89c7df27fc88f731cd9ce7bca8917aac | Python | 1,805 | 61 | #!/bin/python3
import torch
import numpy as np
import matplotlib.pyplot as plt
from torch.utils.data import DataLoader
from torch import nn
from torch import optim
from NNucleate.dataset import GNNTrajectory
from NNucleate.models import initialise_weights, GNNCV
from NNucleate.training import evaluate_model_gnn, early... |
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