sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
11b8b9080de20a77f08634f7548bfcf584607ee14e95e6e01bbae54f5ea9f547 | Python | 3,428 | 83 | import hdbscan
import numpy
from voxel_maps import coordinates_to_image
from ..tree_helpers import region_map_to_dict
from scipy.spatial.distance import pdist, squareform
def extract_gradients(fm0, fm1, annotations, hierarchy_root):
"""Compute connectivity gradients of one region and plot them onto its anatomical... |
325c6aedada12580ff42ca477fb6746b3583675f5014b1a14d4f8ac0001c2af3 | Python | 3,428 | 76 | import csv
import os
import argparse
import sys
sys.path.append(os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
import torch
from read_deep.rt import rt_deep
from importlib import import_module
import yaml
#%%
def main():
parser = argparse.ArgumentParser(description="you should add those parameter")
... |
5ce9dd98459f8975a6c2e95bc7e61d70fbd09baad438a5a1b8480b20b370161d | Python | 3,428 | 115 | """Tests for the specparam.data.utils."""
import numpy as np
from specparam.data.utils import *
###################################################################################################
###################################################################################################
def test_get_model_p... |
e02c75b6b4a8efa4ef652847a2f14553ce0b7c54c2ca51328988b8121e51d9da | Python | 3,428 | 93 | # -*- coding: utf-8 -*-
import os
import sys
import pandas as pd
import numpy as np
data_dir = '/scratch/n/tbi-meg/v/processed'
outdir = '/scratch/n/tbi-meg/v/zmap-data'
decim_freqs = 8
parc = 'aparc_sub'
labels_dir = f'/scratch/n/tbi-meg/v/labels_{parc}'
def main(cohorts=None, window=True, data_type='zmap'):
... |
7ca0ec9362bb200edff1d7c43da07679a4ab28eafbfaa0753b6119f9d0cdd57f | Python | 3,429 | 108 | # 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 complian... |
85d9a0a4edb0face6ea31917b5e1b08be449a57d9d0ca8a6173e05f21ed58667 | Python | 3,429 | 105 | import torch
from modular_splicing.dataset.for_model import reformat_argument_for_model
def get_loss(*, m, xy, evaluation_criterion):
"""
Get the loss for the given model on the given batch.
Arguments
---------
m: torch.nn.Module
The model being trained.
xy: dict
The batch of... |
b05861f19a85b28fb3f55212495d5aacd7b53a949877a68a69353c1b33403dd9 | Python | 3,429 | 74 | """
本脚本用于对单个口袋和多个小分子（smiles或带初始构象的mol文件）进行对接,
"""
import argparse
import os
import multiprocessing as mp
import torch
from src.utils.docking_inference_utils import docking, read_ligands
from src.utils.docking_utils import extract_carsidock_pocket, read_pocket
from src.utils.utils import get_abs_path, get_carsi... |
b48bbc32c457cb7ffe1f8e567251c94de6ac26a2fcc77a8d9f682bee7f0bac1e | Python | 3,429 | 143 | """Build network"""
from posixpath import split
def get_file_paths(control_file):
"""
:param control_file:
:return control_dic:
parses control_file into a dictionary providing the code access to all the paths it needs to run
control file format is @\tkey=path
key is used as a dictionary ... |
68dc78bc8d8cb1ae586381656c4d1b2c26c7da1f0a2b383cf6f48b04962f0c6c | Python | 3,430 | 111 | # Copyright 2022 Deepfold Team
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writin... |
72ee8d1937dc9db28a1b3ada4c7bc3135ea2e7a39fab9c8ac306fadd897255c3 | Python | 3,430 | 112 | import torch
import torch.nn as nn
from .entire_model_types import entire_model_types
from modular_splicing.utils.construct import construct
class SeparateDownstreams(nn.Module):
"""
Have several different downstreams and only one motif model.
Each downstream corresponds to a different output.
The... |
96a524a24267d72c8ec720c66bc6d53322f5a84ec6e7b57d871da83ad3bd922e | Python | 3,430 | 124 | from typing import List
from monty.serialization import loadfn, dumpfn
import logging
import os
from pymatgen.core.structure import Molecule
from pymatgen.io.ase import AseAtomsAdaptor
from pymatgen.io.qchem.inputs import QCInput
import ase.io as ase_io
from ase.neb import NEB
from instance_mongodb import instan... |
47c1a657938298a9fcffbf01c41081d2a4eb91a9d3f48ea2e7573927c5870543 | Python | 3,431 | 100 | import os
import sysconfig
from pysam.libchtslib import *
import pysam.libchtslib as libchtslib
from pysam.libcsamtools import *
from pysam.libcbcftools import *
from pysam.libcutils import *
import pysam.libcutils as libcutils
import pysam.libcfaidx as libcfaidx
from pysam.libcfaidx import *
import pysam.libctabix as... |
977dd955385e3e2f29d39e101903a6b8a8ffa89fb6cac639285085b6d12e9c61 | Python | 3,431 | 93 | import random
import numpy as np
import torch
import time
import math
from copy import deepcopy, copy
def seed_all(seed=0):
print("* Setting all random seeds to ",seed,'*')
random.seed(seed)
np.random.seed(seed)
torch.manual_seed(seed)
torch.cuda.manual_seed(seed)
torch.cuda.manual_seed_all(see... |
52b104f34a44c4662b157ba64615ee49b982cb7d305200df499f69e68b3a8cc2 | Python | 3,432 | 90 | """Tests for the About portal popup content and UI component."""
from __future__ import annotations
from larvaworld.portal.about import build_about_content
from larvaworld.portal.panel_components import build_template_header
def _find_by_css_class(root: object, css_class: str) -> object | None:
"""Depth-first s... |
7991d82f7a2f02e1facea449569c9f8c9e204d62ca8e2c8525932aa3e4713898 | Python | 3,432 | 106 | # --- THIS FILE IS AUTO-GENERATED ---
# Modifications will be overwitten the next time code generation run.
from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType
import copy as _copy
class Unselected(_BaseTraceHierarchyType):
_parent_path_str = "scattercarpet"
_... |
d3f994fcb0aa3c3b479275eaa1c74adc99e3b7139080e3ffbf7fd0496ac58b80 | Python | 3,433 | 89 | '''Skript to generate Dataset from folders
adapted code from https://stanford.edu/~shervine/blog/keras-how-to-generate-data-on-the-fly.html'''
import numpy as np
import tensorflow.keras
import cv2
import random
from datetime import datetime
from keras.utils import to_categorical
from sklearn.preprocessing import Label... |
322c511f2bcd152fbc73f6cda445a0f607d2434035405041e2ede13fde0130b2 | Python | 3,435 | 81 | # Convert the DICOM scans to NIFTI, identify the RT structures and
# prints the FSL commands to re-orient and apply the masks.
import csv
import os
from dcmrtstruct2nii import dcmrtstruct2nii, list_rt_structs
FSL_DIR = "FSLDIR"
if __name__ == '__main__':
# Temporary folder to save the NIFTIs
temporary_folde... |
34eeb10ecc313dc5d0973dec77779cad6ced8769408787e26a2ec5bd6f0a585e | Python | 3,435 | 91 | """A wrapper for filtering dictionary observations by their keys."""
import copy
from typing import Sequence
import gym
from gym import spaces
class FilterObservation(gym.ObservationWrapper):
"""Filter Dict observation space by the keys.
Example:
>>> import gym
>>> env = gym.wrappers.Transfo... |
815876aedd03304b37a2d901d2f7839c0212ced99bf4b35be4ba4573d837ac3c | Python | 3,437 | 97 | import pandas as pd
from scipy.stats import pearsonr,spearmanr
import seaborn as sns
import matplotlib.pyplot as plt
from utils import setup_fonts,parse_config,build_output_dir
import re
def parse_entry(entry):
if any([c == ' ' for c in entry]):
return None
else:
return entry[0], float(entry[1]... |
d090fc9c1987b1d27e44577e0c2c19ee65bfe0344a9a00716ba55e9584c48b12 | Python | 3,438 | 109 | # --- THIS FILE IS AUTO-GENERATED ---
# Modifications will be overwitten the next time code generation run.
from plotly.basedatatypes import BaseLayoutHierarchyType as _BaseLayoutHierarchyType
import copy as _copy
class Transition(_BaseLayoutHierarchyType):
_parent_path_str = "layout.slider"
... |
1d2fb219cbab68de0743ef1f2808a589e9d9ef576475756b92ac51baa9266c29 | Python | 3,439 | 164 | import pytest
import math
import rpy2.rinterface as ri
ri.initr()
def test_r_to_NAInteger():
na_int = ri.NA_Integer
r_na_int = ri.evalr("NA_integer_")[0]
assert r_na_int is na_int
def test_NAInteger_repr():
na = ri.NA_Integer
assert repr(na) == 'NA_integer_'
def test_NAInteger_str():
na =... |
3d4e8e43e8a9913513eeb8b28669d4991d2868ee66e2f82222426232ac9704f3 | Python | 3,439 | 111 | """
API consistency tests for LarvaDataset and related classes.
Pure import/identity checks - NO I/O, NO dependencies.
FASTEST tests in the suite (~50ms total runtime).
"""
import importlib
import pytest
@pytest.mark.fast
def test_larvadataset_alias_identity():
"""
Verify LarvaDataset is the s... |
32a45ab4e1be5fd6ac787c606623d8cdd0e3edb96b49b8fb4a88a347127551fe | Python | 3,440 | 66 | """C.1: пилот на жизнеспособность знакового слоя и пластичности.
Стоимость метки и хеббовское обучение меняют физику мира — до всего
остального проверяем, что мир не рушится (STAGE3_DESIGN §10.1, граница
провала 6). Четыре условия × 5 seed × 15000 тиков:
базовый | только знаки | только пластичность | знаки+пластично... |
c5d81d5828baddaf5447d8793cfda251f79ab50e438640e4e5da727b26b92e8f | Python | 3,440 | 113 | import pytest
import random
from larvaworld.lib.model import SpaceDict
from larvaworld.lib.util import AttrDict
@pytest.fixture
def space_dict():
return SpaceDict(
base_model="explorer",
space_mkeys=["interference", "crawler"],
Pmutation=0.1,
Cmutation=0.1,
init_mode="rando... |
00007e589341857c3b7e45f266308b79a643f6867b3c981a86ec36edd95db3f3 | Python | 3,441 | 119 | from __future__ import annotations
import os
import pytest
from pytest_celery import RABBITMQ_PORTS, CeleryBrokerCluster, RabbitMQContainer, RabbitMQTestBroker, defaults
from pytest_docker_tools import build, container, fxtr
from celery import Celery
from t.smoke.workers.dev import SmokeWorkerContainer
############... |
8a89d1934b8efeae246563ca60c11b231c6099aa2e4d1b3816dc67d59358e0bc | Python | 3,441 | 113 | from typing import Tuple
import numpy as np
import torch
import torch.nn as nn
dev = torch.device('cuda:0')
class MultipleOptimizer:
def __init__(self, *op):
self.optimizers = op
def zero_grad(self):
for op in self.optimizers:
op.zero_grad()
def step(self):
for op in ... |
8fabe8408a65a8f16f786a37e2ca67c69d31c9a98758a676908e79201d4cfdfc | Python | 3,441 | 96 | import requests
import os
import tempfile
from zipfile import ZipFile
class NeuroMorphoAPI:
def __init__(self, base_url="https://neuromorpho.org/xyz2swc/"):
self.base_url = base_url
self.foldername = None
requests.packages.urllib3.util.ssl_.DEFAULT_CIPHERS += 'HIGH:!DH:!aNULL'
def co... |
271ef2ec0c4326b31effb34a92532e7158b3cc8dd94300517d442e09402a8210 | Python | 3,443 | 156 | #TimesVector
#
#Created by Inuk Jung on 2016-08-3.
#Copyright (c) 2016 Inuk Jung. All rights reserved.
#
#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 you... |
6e22e83f121554cede0593b079f526526365f1391a74bd0cf7b28b29c05e16eb | Python | 3,443 | 96 | # %% [markdown]
# # Adding transformations to multiscale images
#
# Adding transformations to individual multiscale images is a way to enrich the metadata associated with the image.
# This can be useful to inform implementations on how to view or interpret the image data,
# i.e. if an image is supposed to be viewed wit... |
a0696196cc5552a2cb07800af27b04ec9e82919db0d2c4e1313a34a43ffca356 | Python | 3,444 | 97 | """AUD-CODE 4.2 regression: check_plan multiplicity and index bounds.
The multiplicity check was ``len(labels) > 0``: a selector fanning ONE
declared replacement out over many sites read ``multiplicity_ok``, and a
pass-qualified ``label:k`` outside ``1..num_passes`` surfaced only as the
resolver's opaque "matched 0 si... |
47bb57f7dd7ca6b90b49019fc6d0e1784be3b5bbcb7c28c0b72a65ec05ad284a | Python | 3,445 | 106 | # --- THIS FILE IS AUTO-GENERATED ---
# Modifications will be overwitten the next time code generation run.
from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType
import copy as _copy
class Unselected(_BaseTraceHierarchyType):
_parent_path_str = "scatterpolargl"
... |
76f4140f0094eb86881d28b51672fa79183fcfb1b7a6b6754cb206ac814b3d64 | Python | 3,445 | 106 | # --- THIS FILE IS AUTO-GENERATED ---
# Modifications will be overwitten the next time code generation run.
from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType
import copy as _copy
class Unselected(_BaseTraceHierarchyType):
_parent_path_str = "scatterternary"
... |
e43d3655c12951a90e0560fbf02667fae8070c4da20631f93137b575897fbc29 | Python | 3,445 | 117 | from pathlib import Path
import numpy as np
import torch
import matplotlib.pyplot as plt
import scipy
from tqdm import tqdm
from scipy import interpolate
import hdf5plugin
import h5py
#os.environ['CUDA_VISIBLE_DEVICES'] = '0'#, 1, 2, 3, 4, 5, 6, 7'
import sys
#sys.path.append("/grand/hp-ptycho/anakha/S26-beamtime/scr... |
63e9ea1b04f9ee45c320bdc44b7183afdbeb972f26c99529ff0b9d98c77687d7 | Python | 3,446 | 85 | import abc
import os
import json
import gzip
import urllib.request
import wget
from src.cfg import *
class MorphologySource(abc.ABC):
@abc.abstractmethod
def fetch_morphology(self, experiment_id, mode):
"""Fetch morphology data."""
pass
class NeuroinformaticsSource(MorphologySource):
def _... |
78939cc3cae646ee30d722efc57c9d6a8ff91cef1ca60b6afef1615ee6a94a69 | Python | 3,446 | 81 | """Exceptions raised by pyrosm.
- :class:`PBFException`: the base class of the two errors about a PBF file's content below.
- :class:`InvalidOSMFileError`: a file is not a readable OSM PBF file (a
:class:`PBFException`).
- :class:`PBFNotImplemented`: a PBF file requires a feature pyrosm does not support (a
:class:... |
7b3c71ce1d14b812ffd144718cd002a1710a30f2b74141bee5d5e2c5bc3f47ac | Python | 3,446 | 94 | import numpy as np
from brian2.only import *
import deepdish as dd
from readout import load_results
out_fname = 'suppression.TA{TA}.h5'
def get_bspikes(res, episode):
b = np.zeros(np.asarray(res['raw_dynamics']['v'].shape)[[0,2,3]], bool)
for itrial, (i, spike_t) in enumerate(zip(*[res['raw_spikes'][episode... |
cf5d385af451d0054c680c95ab6af65f1225f79b9024cbd4af2e7231408b01c8 | Python | 3,446 | 84 | import matplotlib.pyplot as plt
import numpy as np
def setup_figure(xlabel,ylabel,
fontsize = 15,
fontname = "Helvetica",
grid = False,**kwargs):
plt.xlabel(xlabel,fontsize = fontsize,fontname = fontname)
plt.xticks(fontsize=fontsize,fontname = fontname)
p... |
245fd08fdb31323c62b6eba9177e1be4c602a3644fc904732af2dd6583d5b8ab | Python | 3,447 | 83 | # all with inverse!
# quartiles ✔
# half of head (front/ back / left right) ✔
# poca dots - multiple rotations/spacings?
# singular dot (whole head)
# multiple dots (less than whole head)
# center of mass (position, x y)
# rings (different sized?) ✔
# gradients (different directions)
# make a kernel per electrode - nah... |
abca4b32062add7099aec571e4f5d238aa01d603e763245b3adb6da53e302f9d | Python | 3,448 | 95 | #!/usr/bin/env python
import glob
import os
import tarfile
import pandas
from deepspeech_training.util.importers import get_importers_parser
COLUMNNAMES = ["wav_filename", "wav_filesize", "transcript"]
def extract(archive_path, target_dir):
print("Extracting {} into {}...".format(archive_path, target_dir))
... |
9cfe30f770e378133177aa014ea4513e0ab9d8dc295ed78d605a4b9b8c080102 | Python | 3,449 | 110 | # --- THIS FILE IS AUTO-GENERATED ---
# Modifications will be overwitten the next time code generation run.
from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType
import copy as _copy
class Marker(_BaseTraceHierarchyType):
_parent_path_str = "bar.selected"
_path_... |
419e35ccd7177e1f22804ed5f9e34a1d6b8eb584c0d169e06c9583731987f303 | Python | 3,450 | 98 | from bioseq2seq.utils.logging import logger
from bioseq2seq.transforms import register_transform
from .transform import Transform
from bioseq2seq.utils.alignment import subword_map_by_joiner, subword_map_by_spacer
import re
from collections import defaultdict
@register_transform(name='filterfeats')
class FilterFeatsT... |
b29325878dd5f97acf508ce66e6cee2aad27bd7f56f23c46d0583ec9531dfbbd | Python | 3,450 | 120 | import numpy as np
import pandas as pd
from statistic import classification_analysis
import pickle
from collections import OrderedDict
num_dict=OrderedDict({'435':25,'412':24,'474':20,'501':20})
from torch import tensor
from sklearn.metrics import roc_curve
from sklearn.metrics import matthews_corrcoef
def conclued_s... |
c114c0b197f8450489219bce1dd6726c88e748d7bbd66496eef7e05e1eb68494 | Python | 3,450 | 101 | # coding=utf-8
# Copyright 2024 The Google Research Authors.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicab... |
2cff39703bd7f1f85add1f3c286561fae1c805e5899832be825c9b0278bc7c52 | Python | 3,451 | 123 | import numpy as np
import torch
from numpy.random import default_rng
import matplotlib.pyplot as plt
import pandas as pd
import seaborn as sns
from tqdm import tqdm
import multiprocessing
from multiprocessing import Pool, freeze_support, current_process, RLock
from functools import partial
import pathlib
from causal_o... |
571f8372ff7731f5c728ea5a8f7480578b16760e82638e7d2d58707cf08b4e34 | Python | 3,451 | 113 | import argparse
import os
import subprocess
import sys
def _filter_pythonpath(repo_root: str) -> str:
excluded = {
os.path.normcase(os.path.abspath(repo_root)),
os.path.normcase(os.path.abspath(os.path.join(repo_root, 'python'))),
}
entries = []
for entry in os.environ.get('PYTHONPATH'... |
0c82564ff5d1d57d21c715199e85f28389021b7a5caa620f10974a8901ea38e3 | Python | 3,452 | 111 | # -*- coding: utf-8 -*-
"""
Created on Fri Dec 9 13:31:18 2022
@author: longzheng
"""
import torch
import torch.nn as nn
from torch.utils.data import DataLoader
from torch.optim import Adam
from oil.utils.utils import LoaderTo, islice, cosLr, FixedNumpySeed
from oil.tuning.args import argupdated_config
from oil.tuni... |
df8cd0dc5f918e94367e96bc7640f3807137860185c60df176fa2e035f552e3d | Python | 3,452 | 89 | from __future__ import division
import unittest
import numpy as np
from numpy.random import randn
np.random.seed(42)
from wyrm.types import Data
from wyrm.processing import append, swapaxes, calculate_cca, apply_spatial_filter
class TestCalculateCCA(unittest.TestCase):
SAMPLES = 1000
CHANNELS_X = 10
C... |
19877eb5189cfd09d1d9d43d1a3e9fe84ac6065c9835ff03f6d2b5c2683ff6c8 | Python | 3,453 | 95 | """NSActivityOptions
https://developer.apple.com/library/content/documentation/Performance/Conceptual/power_efficiency_guidelines_osx/PrioritizeWorkAtTheAppLevel.html
License
-------
Incorporates code from `appnope <https://github.com/minrk/appnope>`_ under
2-clause BSD, copyright (c) 2013, Min Ragan-Kelley
All righ... |
3bdafa366b320e189df2d6d10a0d036be251cc5195ca9a25b6890937b407280d | Python | 3,453 | 79 | from __future__ import annotations
import logging
from collections.abc import Iterator
from itertools import chain, cycle, repeat
class InternalStateInformation(object):
"""
This object is a supportive internal state object designed to hold state information that can be shared between
other features runn... |
2162f6a40bbed810b7866f3169975945cc2ef0a2fae8f7e391c1262c2c103e08 | Python | 3,454 | 122 | import torch
from inspect import signature
from torch_geometric.loader import DataLoader
from torch.nn import functional as F
def construct_model_name(dataset_name: str, debug: bool = False) -> str:
"""Construct the model name based on the config filename and
the debug flag."""
model_name = dataset_nam... |
31552c6058787c5055d01ad3ce68e6d877421fa37691a00baafa191e68f8254c | Python | 3,454 | 112 | # --- THIS FILE IS AUTO-GENERATED ---
# Modifications will be overwitten the next time code generation run.
from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType
import copy as _copy
class Line(_BaseTraceHierarchyType):
_parent_path_str = "quiver.marker"
_path_s... |
def7fd3141995abed6b29720905ab4d80b415ea53775e9a7d61e95686fda49a0 | Python | 3,454 | 96 | # %% [markdown]
# # How to handle delayed writing
#
# Writing large images can take a while, because ome-zarr-py computes the
# multiscale pyramid and writes every chunk to storage.
# Under the hood, this is done with [dask](https://docs.dask.org).
#
# By default (`compute=True`),
# {py:func}`ome_zarr.classes.image.OME... |
1deb77365d81d9b2e9b31aca44871025f117097726f6019c194a0abba571ec21 | Python | 3,455 | 162 | """
Tests to make sure the plot module isn't busted
"""
import eugene as eu
import pytest
from pathlib import Path
HERE = Path(__file__).parent
eu.settings.logging_dir = f"{HERE}/_logs"
@pytest.fixture
def model():
"""
model
"""
model = eu.models.DeepBind(input_len=100, output_dim=1)
return model... |
3710541cfb2541ad7ac0c2417a9ef533d949deff04675171eafa34af6e9a7be8 | Python | 3,455 | 99 | import numpy as np
import scaffoldgraph as sg
import networkx as nx
import os
from rdkit.Chem import Draw
from rdkit import Chem
from utils import get_mol
import matplotlib.pyplot as plt
import random
import argparse
def filter_sca(sca):
mol = Chem.MolFromSmiles(sca)
if mol == None:
return None
... |
5eea84d383f17e8b723d4300bf8e45bfb56ef42362f1fbf92e82887792f06947 | Python | 3,455 | 89 | import tempfile
import unittest
from pathlib import Path
import numpy as np
from PIL import Image
from torch.utils.data import DataLoader
from bdpy.dl.torch.dataset import ImageDataset
# Use non-square images (H=4, W=6, C=3) to fully discriminate every axis.
# A square image (H=W) cannot distinguish (3, H, H) from (... |
e3132f027c906912cfb277da5448927104c764c1c24a19952bda3881537c5298 | Python | 3,455 | 100 | """
Copyright (c) 2022 EPFL-BBP, All rights reserved.
THIS SOFTWARE IS PROVIDED BY THE BLUE BRAIN PROJECT ``AS IS''
AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO,
THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE BLUE BRAIN PROJE... |
05669ee5115b9831d3d4a6ecbff375dd5e6f8316cec11b5e31a0cfd17021b9a8 | Python | 3,456 | 110 | from typing import Any, Callable, Optional, Union
from pl_bolts.datamodules.vision_datamodule import VisionDataModule
from pl_bolts.utils import _TORCHVISION_AVAILABLE
from pl_bolts.utils.warnings import warn_missing_pkg
if _TORCHVISION_AVAILABLE:
from torchvision import transforms as transform_lib
from torch... |
679b78a8dc43799023aac280574c446d78b81b1c1587d4f1f5391171591b357d | Python | 3,456 | 97 | def plot_confusion_matrix(cm,
target_names,
title='Confusion matrix',
cmap=None,
normalize=True,
plot_text=True,
plot=True,
grid=True,
... |
10361ecbdc8c03fa8c9ce84d79bbef67bcb573959b4b1a29f9d587771acce1e2 | Python | 3,457 | 86 | """Prepare a coded analysis table and a private HCP ID crosswalk.
Supply an HCP-ID-labelled derived table to create study IDs and a local ID
crosswalk.
"""
import argparse
import csv
import math
import os
import secrets
from pathlib import Path
ROOT = Path(__file__).resolve().parents[1]
STAGED_PATH = ROOT / "data/l... |
40188af74908ade66951eef8cd92eeb7b2aa5c610a7f98a43f6fb4af8191bdfc | Python | 3,457 | 120 | import os
import random as python_random
import numpy as np
import tensorflow as tf
import tensorflow_datasets as tfds
from tensorflow.keras.layers import Activation
from tensorflow.keras.layers import Conv2D
from tensorflow.keras.layers import Dense
from tensorflow.keras.layers import Flatten
from tensorflow.keras.la... |
57b33a2178214acb79ca8ff0bcc8d213ed7b123ebe61778c21f530af47aec7b9 | Python | 3,457 | 118 | # -*- coding: utf-8 -*-
"""
Created on Tue Aug 18 14:29:28 2020
@author: amberxtli
"""
from typing import Dict
import os
import csv
import pickle
import numpy as np
from rdkit import Chem
from rdkit.Chem import SaltRemover
from argparse import ArgumentParser
from rdkit import Chem, DataStructs
from rdki... |
eb9eefe712554b2b3125d95acbc26cf039a50f092dba75f52c952dd2c96c27f4 | Python | 3,457 | 114 | # Reports distances of ligands to reference points. An example input for the points is:
#
# 5.655 1.497 18.223
# 1.494 -8.367 18.574
# 13.034 6.306 25.232
#
# Data can be space or tab separated but must contain 3 and only 3 numbers for the x, y and z coordinates
#
# That would encode 3 points.
# Each record in ... |
33b9b31485e82fc56f5a8bc78edbbfde1b44143b8ddf45a1d147a1f94f00d8f8 | Python | 3,459 | 110 | from __future__ import annotations
from dataclasses import dataclass, field
from typing import TYPE_CHECKING
if TYPE_CHECKING:
from collections.abc import Callable
import numpy as np
import torch
from torch import nn
@dataclass
class LayerProbeBase:
layer: nn.Module
hook: Callable
popul... |
7265c8e4a7a9d220b93042399a7a736c084ba61b036134f6f142e971d0607b70 | Python | 3,459 | 101 | from prodict import Prodict
import sys
sys.path.append("src")
from args import args
from predict import plot_predictions
from src.analysis.explore_encodings import explore_encondings
from src.analysis.arm import plot_performance_by_arm
from src.analysis.bootstrap import perform_bootstrap
from src.analysis.encodings... |
b3379eb414494831a77ee94bd02d8fac37b36d776b7213801a9fa08c2c5588e1 | Python | 3,460 | 100 | import zipfile as zf
import scanpy as sc
from anndata import AnnData
from .._settings import settings
def visium_sge(
sample_id="V1_Breast_Cancer_Block_A_Section_1",
*,
include_hires_tiff: bool = False,
) -> AnnData:
"""Processed Visium Spatial Gene Expression data from 10x Genomics' database.
... |
bcbc72824a970fae873e2a9121bc89d2e1b5f1352e0e8c54b3d620e7c52dfb21 | Python | 3,460 | 105 | import numpy as np
import matplotlib.pyplot as plt
import tensorflow as tf
import keras
from utils import c1
tf.config.experimental.enable_tensor_float_32_execution(False)
def calc_rho_nDFT(model, profiles, T=1.0, plot=False, maxiter=10000):
"""
Calculate the density profile with neural DFT using a standard... |
db768a90993e736cd4ac33fde0ee83af3351670dccef25efd640afc672213880 | Python | 3,460 | 115 | #!/usr/bin/env python
# Greg Von Kuster
"""
Calculate correlations between numeric columns in a tab delim file.
usage: %prog infile output.txt columns method
"""
import sys
# from rpy import *
import rpy2.robjects as robjects
r = robjects.r
def stop_err(msg):
sys.stderr.write(msg)
sys.exit()
def main():
... |
71c82dcc2d0a8c7befc44d59a6491bc0dee975982ab1d4ad4933c70f0202fcfa | Python | 3,461 | 107 | from time import time, sleep
import multiprocessing
import flywheel
import datetime
import csv
from pathlib import Path
import pandas as pd
now = datetime.datetime.now().strftime("%Y-%m-%d_%H:%M")
fw = flywheel.Client()
qsiprep = fw.lookup('gears/qsiprep-fw-hpc')
proj = fw.projects.find_first("label=PNC_CS_810336")
an... |
dad85c945a4137773d27c35a91d4926d5a2ac6f09f849b347a9dad2c927bb9f3 | Python | 3,461 | 88 | import math
import torch
from torch import nn
# from util.misc import NestedTensor
class PositionEmbeddingSine(nn.Module):
"""
This is a more standard version of the position embedding, very similar to the one
used by the Attention is all you need paper, generalized to work on images.
"""
def __i... |
367903420bd2493b0453890b610528568fca47b5d004aedd6a3bac68f2f5b1c4 | Python | 3,464 | 94 | import os
import pickle
from Configurations import config as cfg
from Utilities.common_packages import np, tf
from nn_model.modelgenerator import tf_model, OnEpochEndCallback, modeltracker
from tensorflow.keras.callbacks import ModelCheckpoint, CSVLogger
from tensorflow.keras.optimizers import Adam
from tensorflow.ker... |
becd0c97830f842282e832983621ee24da56480b4b085e7b5932bbdcb59828af | Python | 3,464 | 112 | import warnings
import captum.attr
import torch
from ..utils.model import FunctionToModel
from ..utils.generator import TensorGenerator
def get_occlusion(x, model, window_shape=(None, 5, 5), stride=(None, 5, 5)):
"""
x must have shape (sample, c, h, w). window_shape and stride have always 3 elements.
Oc... |
494a198d30056591e0df543383b157abee31d93e685a791e135a429766f1c906 | Python | 3,466 | 105 | """
Implementation of the "Converging squares" algorithm
"""
import numpy as np
## a square is a list of slices
def _child_slices(sl, step=1):
"split a slice into two overlapping smaller slices"
return [slice(sl.start+step,sl.stop),
slice(sl.start,sl.stop-step)]
def _child_squares(square, st... |
7c88177ed9fcdf45a3aea955af4278fb8692d9e09da4f7c93275d83c0c2400ce | Python | 3,466 | 88 | from model import *
from utils import *
import numpy as np
from sklearn.model_selection import KFold
import torch
import os,sys
import warnings
warnings.filterwarnings("ignore")
dataset = ['toy_cls','BindingDB_cls','DrugAI','CYP_cls'][int(sys.argv[1])]
TRAIN_BATCH_SIZE =32
TEST_BATCH_SIZE = 256
LR = 0.0001
NUM_EPOCHS... |
d90ca04ae5b09154b5dd2dae9ee6990741a907029e2d82979b8213ac2d291835 | Python | 3,466 | 123 | from abc import ABC, abstractmethod
class SparseLayer(ABC):
"""
Base class for sparse layers.
This class uses the term `sparsity` to refer to the fraction of outputs
that are zero, i.e., correctly. In other places, the term `sparsity`
is used to refer to the fraction of inputs that are no... |
247a43caad2a3570a9f2179f63e84b23489709de2f30db91299b0ff546299ce7 | Python | 3,467 | 91 | """
## Prerequisites
Install OpenVINO and PyTorch CPU versions :
uv pip install -U openvino
uv pip install torch torchvision --index-url https://download.pytorch.org/whl/cpu
### Linux support for Intel® Neural Processing Unit (Intel® NPU)
Chaeck if drivers are installed and the NPU is available:
`sudo dmesg | grep ... |
e10cae2885f162de9d50c1ae1a78a7a21682207fa30067fcf849109854d0931f | Python | 3,467 | 92 | """
Author: Bruno De Santi, PhD
Affiliation: Multi-modality Medical Imaging Lab (M3I Lab), University of Twente, Enschede, The Netherlands
Date: 20/09/2023
Description: Deformation field regularization functions
Acknowledge: The code was adapted from
1) J. M. Wolterink, J. C. Zwienenberg, and C. Brune, “Implicit Neu... |
57fa0bf09d8d85400227741242b0eb460dd1bce9c5a65da76c6ad5410b0cb087 | Python | 3,468 | 125 | import os
import asyncio
import websockets
import sys
import json
import IPython.display
import webbrowser
from time import sleep
class Viewer:
wsport=9000;
url='';
def __init__(self,port=None):
super().__init__();
if (port!=None):
Viewer.wsport=port;
Viewer.url... |
8f05a13f018ca85055760a549767a43b5e540704984b40ba823251664b5eaf88 | Python | 3,468 | 107 | import paddle
from paddle import nn
import paddle.nn.functional as F
from utils import _norm_no_nan
import pgl
import pgl.math as math
class GVP(nn.Layer):
'''
Paddle version of the GVP proposed by https://github.com/drorlab/gvp-pytorch
'''
def __init__(self, in_dims, out_dims, h_dim=None, activatio... |
abd4eca5325d78ca7b5aa9602459c8c59b3af3f4fcf5a3f5d565cea60841037d | Python | 3,468 | 103 | """Custom and derived deformable convolution"""
# pylint: disable=missing-function-docstring,bad-continuation
import torch
from torch import nn
from torch.nn.modules.utils import _pair
from torchvision.ops import deform_conv2d
__all__ = ['DeformConvWithChangeableStride']
class _NewEmptyTensorOp(torch.autograd.Functi... |
c23266271979bb3ef71700eb80718caa4ce3dfbac79b17b87383c3a7c544d451 | Python | 3,468 | 94 | """
Database Writers for Ethoscope Experiment Data Storage
This module provides various classes for storing experimental tracking data from the Ethoscope
behavioral monitoring system. The classes support multiple database backends (MySQL/MariaDB, SQLite)
and different output formats (database tables, numpy arrays).
C... |
df96d68cbe0991ee55bfb38f4766c01729a717430c8c4a43058689dbbba16bd3 | Python | 3,468 | 106 | from keras.src.activations.activations import celu
from keras.src.activations.activations import elu
from keras.src.activations.activations import exponential
from keras.src.activations.activations import gelu
from keras.src.activations.activations import glu
from keras.src.activations.activations import hard_shrink
fr... |
2a9ec428be593bb59cd32605f0e917d8859c60bbe4700354e2ddbfafb359a71b | Python | 3,469 | 99 | # coding=utf-8
# Copyright 2022 The Google Research Authors.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicab... |
39d270a0369617899e1702f58938a44162c61633139a233ef2687bd2f8d6ff4e | Python | 3,469 | 101 | """Benchmark records never carry the machine's hostname or local paths.
Benchmark results and baselines are committed to a public repository. The writers
record a neutral host label (``TORCHLENS_BENCH_HOST_LABEL``, default
``"benchmark-host"``) and spell the checkout as ``<repo>``; these tests pin that,
and pin that n... |
94d7f24b9bf48006f8c80dc63bd95d0470c999a520ed70900b9e221839465ed9 | Python | 3,469 | 108 | # Copyright 2020 The HuggingFace Team. 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 applicabl... |
f39ae45b0c6200f798d8a412c23328d20fd93fe88b5ac3a535a8c4ec13139d53 | Python | 3,469 | 133 | import jax
import jax.numpy as jnp
import jax.scipy as jsp
from keras.src.backend import config
from keras.src.backend.common import dtypes
from keras.src.backend.common import standardize_dtype
from keras.src.backend.jax.ops.core import cast
from keras.src.backend.jax.ops.core import convert_to_tensor
def cholesky(... |
f8fd3375a7059524a760993c0f94626c8a665a8b6a47a102e1c790c1dcfbde0b | Python | 3,469 | 111 | # -*- coding: utf-8 -*-
# Copyright (c) 2016-2018 Braintech Sp. z o.o. [Ltd.] <http://www.braintech.pl>
# All rights reserved.
"""Implement Smart tags classes: SmartTagEndTag, SmartTagDuration."""
from . import read_tags_source
from .. import read_manager
from ..signal import read_data_source
from ..signal import read... |
0a6550379721696f9ac80b1471cbf426522db92340331bee41dc301c3ebc8689 | Python | 3,470 | 85 | #!/usr/bin/env python3
"""Fit Platt on training-in-sample scores under the deployment LDA,
apply unchanged to figshare. Report Brier/ECE on held-out figshare."""
from __future__ import annotations
import os, sys, json
import numpy as np
HERE = os.path.dirname(os.path.abspath(__file__))
OUT_DIR = os.path.join(os.path.d... |
4a9af155a4ff52782d4cc1246b22e94a0d255420b92f09b30db58d6f4725924d | Python | 3,470 | 92 | from typing import Any, Dict, Iterable, Optional
from torch.optim import Optimizer
def update_param_groups(
optimizer: Optimizer,
default_update: Optional[Dict[str, Any]] = None,
updates: Optional[Iterable[Dict[str, Any]]] = None,
) -> None:
"""Update the values in the param groups of the optimizer.
... |
583cd8ad4a1c97adaf265213971e1e40b870e84fb0978605738bdfb7c5516b4e | Python | 3,471 | 99 | import os
import sys
import pandas as pd
import anndata as ad
from pyprojroot import here
import re
proj_root = str(here())
sys.path.insert(0, os.path.join(proj_root, "package/python"))
from myanndata import grouped_obs_mean, get_barcode2group
from utils import set_file_logger
# * configs
resource_dir = f"{proj_root... |
8be86efe8d9460cefb6fb635923a875883408761f2dcdf04758fc09206fbd711 | Python | 3,471 | 110 | # --- THIS FILE IS AUTO-GENERATED ---
# Modifications will be overwitten the next time code generation run.
from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType
import copy as _copy
class Line(_BaseTraceHierarchyType):
_parent_path_str = "indicator.gauge.threshold"... |
8d54dad17429151e8488171aa96e04e098d371efedd6d16729168885a20f952f | Python | 3,471 | 101 | from __future__ import absolute_import
import logging
import os
from pip._vendor.six.moves import configparser
from pip._internal.download import path_to_url
from pip._internal.utils.misc import display_path, make_vcs_requirement_url
from pip._internal.utils.temp_dir import TempDirectory
from pip._internal.vcs impor... |
c4610747f795f0346b41920f937aada85803d9cc0e16c9d931423b4f7b311207 | Python | 3,471 | 92 | from typing import Optional, Tuple, Union
import numpy as np
import pyvista as pv
from anndata import AnnData
from pandas.core.frame import DataFrame
from pyvista import PolyData
try:
from typing import Literal
except ImportError:
from typing_extensions import Literal
from ..utilities import add_model_labels... |
e382eef9a2fa3ac6b824a1522cbb7da11225f491809e7fe5be172f0175fa3860 | Python | 3,471 | 106 | import numbers
import pkg_resources
from afmformats import meta
from nanite import model
import numpy as np
from PyQt5 import uic, QtWidgets
from .. import units
class TabInfo(QtWidgets.QWidget):
def __init__(self, *args, **kwargs):
super(TabInfo, self).__init__(*args, **kwargs)
path_ui = pkg_re... |
291dee87bab9591bb5b4f371aa86972a651f3655c15247daed944397ea4c81d2 | Python | 3,472 | 127 | import numpy as np
from .utils import get_trial_length
from .array_utils import split_array
def concat_trials(trial_data, signal, trial_indices=None):
"""
Concatenate signal from different trials in time
Parameters
----------
trial_data : pd.DataFrame
data in trial_data format
signal... |
c7825ec349a5e2ae9446e1f0f2045a0bfdac10fe495898e5954440387b77149b | Python | 3,472 | 89 | """
Author: Bruno De Santi, PhD
Affiliation: Multi-modality Medical Imaging Lab (M3I Lab), University of Twente, Enschede, The Netherlands
Date: 20/09/2023
Description: "trilinear" or "nearest" interpolation used in MUVINN-reg
Acknowledge: The code was adapted from
J. M. Wolterink, J. C. Zwienenberg, and C. Brune, “... |
d4df670bff0147e8d3a0a4a7ecfdfabd627e356e17447dd91d3f73e5045c4efa | Python | 3,472 | 89 | # Copyright (c) ByteDance, Inc. and its affiliates.
# All rights reserved.
#
# This source code is licensed under the license found in the
# LICENSE file in the root directory of this source tree.
import torch
import torch.nn as nn
from typing import List
from timm.models.registry import register_model
class YourCon... |
f1f108f6c6731ece0344c29e387c1298fa084ab71c1878638b63ac0b81aa9ac3 | Python | 3,473 | 100 | import numpy as np
import matplotlib.pyplot as plt
import pickle
import sklearn.metrics as metrics
from cycler import cycler
from statistic import classification_analysis
from collections import OrderedDict
from torch import tensor
num_dict=OrderedDict({'435':25,'412':24,'474':20,'501':20})
def case_out(num_dict,resu... |
1482929fec81d392c0db634bb5467f112e0cf20e085ca8e5b637b0efe31130b5 | Python | 3,474 | 84 | """
Leaky Integrate-and-Fire Spiking Neuron Model
=============================================
The `leaky integrate-and-fire <https://en.wikipedia.org/wiki/Biological_neuron_model#Leaky_integrate-and-fire>`_ (LIF)
neuron model is the most commonly used spiking neuron model.
It has a single state-variable :math:`v_i`,... |
67fcba8239db2bf06b04739cf8f4543b712f1c35940b103fbc94c41e49fc77d2 | Python | 3,474 | 84 | """
Leaky Integrate-and-Fire Spiking Neuron Model
=============================================
The `leaky integrate-and-fire <https://en.wikipedia.org/wiki/Biological_neuron_model#Leaky_integrate-and-fire>`_ (LIF)
neuron model is the most commonly used spiking neuron model.
It has a single state-variable :math:`v_i`,... |
6dc2c8d0d679fbefe53e3c10997d638e04c40bab204c6bb084f0346ddb9b0ed1 | Python | 3,474 | 110 | # --- THIS FILE IS AUTO-GENERATED ---
# Modifications will be overwitten the next time code generation run.
from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType
import copy as _copy
class Marker(_BaseTraceHierarchyType):
_parent_path_str = "barpolar.selected"
_... |
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