sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
c55d92f2223d7ec5c91b0e306e09c27ee8a8d607ae2d5e16c8425a05dd1dae13 | Python | 1,233 | 43 | from infomap import infomap
name = "ninetriangles"
filename = "../../{}.net".format(name)
infomapWrapper = infomap.Infomap("-N5 --silent")
infomapWrapper.readInputData(filename)
infomapWrapper.run()
tree = infomapWrapper.tree
print("Found %d top modules with codelength: %f" % (tree.numTopModules(), tree.codeleng... |
16e954ff9c51cfa4a81ba4b20567faa18f53f9a9adf40064a5c1416cef01953f | Python | 1,235 | 47 | """A decorator to ensure that torch parameters are on the correct device
This decorator makes sure that tensor and parameter arguments given to a
method are transferred to the right device given the device as it has been
set for the instance.
"""
__all__ = ["consistify"]
from functools import wraps
import torch
de... |
fadde27ef58931ad08ac60967ba826bc5f6d5729effaffca42b62a6942f9ba82 | Python | 1,237 | 26 | import torch
from torch_geometric.data import Data, Dataset
class MarginalSubgraphDataset(Dataset):
""" Collect pair-wise graph data to calculate marginal contribution. """
def __init__(self, data, exclude_mask, include_mask, subgraph_build_func) -> object:
self.num_nodes = data.num_nodes
self... |
ae205d3dfdbe5b9ac195a1f35381dda530ed81bad0e877a431271d3d30620840 | Python | 1,239 | 36 | from typing import Optional, Tuple, List
from chromadb.api import BaseAPI
from chromadb.api.types import (
Documents,
Embeddings,
IDs,
Metadatas,
)
def create_batches(
api: BaseAPI,
ids: IDs,
embeddings: Optional[Embeddings] = None,
metadatas: Optional[Metadatas] = None,
documents:... |
c9c100e1d994d55ce37a4a08f4854d0d14219a30d541c1f69ac6900a0e5a19ab | Python | 1,239 | 38 | from ..abstract_dataset import AbstractDataset
import os
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.tri as mtri
class NavierStokesDataset(AbstractDataset):
parametric = True
time_dependent = False
description = "back step navier stokes TODO"
data_directory = os.path.join(os.... |
ed2a9f3e5c84cd33c49edf14518808daf43c80477eae852ae9e5ee41e424a2f5 | Python | 1,239 | 34 | # Generated by Django 4.1.1 on 2022-10-28 10:57
from django.db import migrations, models
import django.db.models.deletion
import django.utils.timezone
class Migration(migrations.Migration):
dependencies = [
('celsus', '0016_remove_rawdata_project_rawdata_file'),
]
operations = [
migrati... |
37f1db620e941621803c1d71d09b6496bffa9f9ff54992126bbbc743f285fbd5 | Python | 1,242 | 32 | from sklearn.metrics import auc, precision_recall_curve, roc_auc_score, accuracy_score, mean_absolute_error, mean_squared_error
import numpy as np
import math
def prc_auc(targets, preds):
"""
Computes the area under the precision-recall curve.
:param targets: A list of binary targets.
:param preds: A... |
d2d022a8027a06d1350cf8c04f0a6057ed7b5f77463e90b13466db12f7c23e9a | Python | 1,242 | 41 | import os.path as osp
import pickle
import argparse
import os
from tqdm import tqdm
import time
from termcolor import cprint
t1 = time.time()
parse = argparse.ArgumentParser()
parse.add_argument('--start', default=0, type=int)
parse.add_argument('--num_mols', default=1000000, type=int)
parse.add_argument('--save_path... |
57d32302cd76dd0817dddcc230e2745271ceca2ce72ba6d2432a79cd269fb315 | Python | 1,243 | 32 | # -*- coding: utf-8 -*-
#
#
# PyRates software framework for flexible implementation of neural
# network models and simulations. See also:
# https://github.com/pyrates-neuroscience/PyRates
#
# Copyright (C) 2017-2018 the original authors (Richard Gast and
# Daniel Rose), the Max-Planck-Institute for Human Cognitive Bra... |
2e018b321ffedf806183ecd18f0f43019becf158777e3fdc3083c173032b0945 | Python | 1,245 | 40 |
from PyQt5.QtWidgets import QDialogButtonBox, QDialog
from sleepy.gui.builder import Builder
from sleepy import SLEEPY_ROOT_DIR
from sleepy.gui.settings._view import VIEW
class SettingsView(QDialog):
def __init__(self, control, application):
"""View displaying the settings managed by an instance... |
561dd574f62900197cdfe9385f0c6dcc325474408732392a5f25023133ea798a | Python | 1,245 | 46 | """Plot a square on H2 with Poincare half-plane visualization."""
import matplotlib.pyplot as plt
import geomstats.backend as gs
import geomstats.visualization as visualization
from geomstats.geometry.hyperboloid import Hyperboloid
def main():
"""Plot a square on H2 with Poincare half-plane visualization."""
... |
28ecaa4c5bf206609c87f336cfecc70bfed6efeab9a8508942f5817750026431 | Python | 1,246 | 54 | import pytest
from neurodesign import Design, Optimisation
def test_design_smoke(exp):
design = Design(
order=[0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1],
ITI=[2] * 20,
experiment=exp,
)
design.designmatrix()
design.FCalc(weights=[0, 0.5, 0.25, 0.25])
des... |
9448ca7cce21b2b3a14c32e793e3a2b029cfd0b9401ae2a13bb846ff80f7f2cc | Python | 1,246 | 38 | import os
import pytest
from chromadb.utils.embedding_functions.openai_embedding_function import (
OpenAIEmbeddingFunction,
)
def test_with_embedding_dimensions() -> None:
if os.environ.get("OPENAI_API_KEY") is None:
pytest.skip("OPENAI_API_KEY not set")
ef = OpenAIEmbeddingFunction(
api... |
5b5d7080cd1e998024beb36529559f1be6bbcf8ec3b3fec2012f45e559b94acd | Python | 1,247 | 40 | from typing import Any, Dict
import os
import yaml
def set_log_file_path(
log_config_path: str, new_filename: str = "chroma.log"
) -> Dict[str, Any]:
"""This works with the standard log_config.yml file.
It will not work with custom log configs that may use different handlers"""
with open(f"{log_confi... |
bc544817938a640ed0be6952b718b46468f6cb66abfe1132fe5cd0abef3c0a80 | Python | 1,247 | 28 | from keras.preprocessing.image import load_img, img_to_array
import cv2.cv2 as cv2, numpy as np
from keras.applications import DenseNet121
from keras.layers import Dense, GlobalAveragePooling2D
from keras import Model
IMG_PATH = ['./chest_xray_images/normal/15268.jpg', '0']
IMG_SHAPE = (320, 320, 3)
test_img = load_... |
747e632710d697edcbf9cbf9fbc86b20ba3b70e421502e25ab78b10b372de996 | Python | 1,249 | 37 | #!/usr/bin/env python
# coding: utf-8
import numpy as np
import cortex
import os
from glob import glob
data_dir = os.path.abspath('../../outputs/fmriprep')
def get_subjects():
fns = sorted(glob(os.path.join(data_dir, 'sub-*/')))
fns = [fn.split('/')[-2] for fn in fns]
return fns
subjects = get_subjects(... |
ee65b98d156b80468d7df0e363020de7698c7e4f8a0a2e10bc18736766d067f8 | Python | 1,251 | 39 | import torch
def rescale_adj(adj, dim='all'):
if dim=='view':
out_degree = adj.sum(dim=-1)
out_degree_sqrt_inv = out_degree.pow(-1)
out_degree_sqrt_inv[out_degree_sqrt_inv == float('inf')] = 0
adj_prime = out_degree_sqrt_inv.unsqueeze(-1) * adj
elif dim=='all':
... |
547950d36c0011324054991cbc315ef6bd86050bf6358ed1d1dbe92c7bcd3f3e | Python | 1,252 | 54 | from numpy import linalg as LA
import numpy as np
def generate_xyz(ds, batch):
num_nodes = ds.shape[0]
d_list = []
start = 0
for i in range(1, num_nodes):
if batch[i] > batch[i-1] or i == num_nodes:
end = i
d_list.append(ds[start:end, start:end])
start = end... |
071ac382dadc7348cd3fd5f7e78c08be88823012018727c5b7bed965c5786292 | Python | 1,254 | 31 | from geomstats.test_cases.learning._base import BaseEstimatorTestCase
class RiemannianMinimumDistanceToMeanTestCase(BaseEstimatorTestCase):
def test_fit(self, X_train, y_train, expected, atol):
mean_estimates = self.estimator.fit(X_train, y_train).mean_estimates_
self.assertAllClose(mean_estimates... |
9f39f8f47ef2be44ee186a9418185a1a18b30a49562e7035dbaa8345857db56c | Python | 1,254 | 32 | import numpy as np
import pandas as pd
# hand keypoint extraction
def finger_tapping_distance(InputDataframe: pd.DataFrame, kpt_method="2D"):
if kpt_method == "2D":
# 2D distances of (keypoint 4 and keypoint 8)
# x: pd.Dataframe (index = timestep), (x_0~x_20)
# y: pd.Dataframe (index = tim... |
0dc0d96b553cd0168b79dcad721f1662b151f50c1a9ebf07086a53f3803b406e | Python | 1,255 | 36 | import numpy as np
from numpy.testing import assert_raises
from gemmr.model_selection import *
def test_max_min_detector():
np.random.seed(0)
n = 10000
signal = np.cos(np.arange(n)).reshape(-1, 1)
X = np.c_[signal, signal, np.random.normal(size=(n, 2))]
Y = np.c_[np.random.normal(size=(n, 1)), s... |
764bdc83052334a7e45ce57c996cf14cb31fe9e94d7db569dcecb8a22c3084bf | Python | 1,255 | 47 | from scipy.linalg import eigh
from numpy import zeros
def get_LEiDA(syncConnAux):
"""Obtain leading eigenvector for synchronicity matrices.
Args:
syncConnAux (ndarray): Synchronicty matrices for all parcels/voxels in the format [N, N, Tmax].
Returns:
leidaArrayAux : Leading eigenvector o... |
debcfe0390c628a07190d639e753bb42fa9675a76861f47ee201047bd2bd9331 | Python | 1,255 | 40 | import glob
import sys
import time
import datetime
import numpy as np
from deeprank_gnn.GraphGenMP import GraphHDF5
from deeprank_gnn.NeuralNet import NeuralNet
from deeprank_gnn.ginet import GINet
### Graph generation section
#path to the docking models in pdb format
pdb_path = '../tests/data/pdb/1ATN/'
#path to... |
e294aae03dcd57dcf2244309baebfb10681073d4ded90e33ae0374ee657c668d | Python | 1,256 | 41 | """Interfaces for loading and saving (dumping) templates and circuits from/to file."""
from typing import Optional
FILEIOMODES = ["pickle", "yaml"]
def save(_obj: object, filename: str, filetype: str, **kwargs):
"""Save an object to file.
Parameters
----------
_obj
The object to ... |
15adc82a297e385b8c31a8d9949a0b09e478da53fd4c18d3eee79a9cfbf778ba | Python | 1,257 | 35 | # Copyright (c) 2021 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 appli... |
28e9140d7cab07c3245952b0a215e46092868f91e08e0a7bdb3a8369a3c83216 | Python | 1,257 | 38 | import pytest
import numpy as np
from reinvent_plugins.components.Lilly.comp_lilly_descriptors import Parameters
from reinvent_plugins.components.Lilly.comp_lilly_descriptors import LillyDescriptors
SMILIES = [
"Cc1ccc(-n2[nH]c(C)c(N=Nc3cccc(-c4cccc(C(=O)O)c4)c3O)c2=O)cc1C",
"CC(=O)Oc1ccccc1C(=O)O",
"Cc1... |
364eb8928dd588801298ad779d9ec4a6a7f52b5753fe0167b77d965aca3531ac | Python | 1,257 | 46 | def benchmark_single_jr_circuit(n_runs=10):
"""This is a simple benchmark function that instantiates a basic JR circuit and compiles it.
Parameters
----------
n_runs
number of runs to execute benchmark for averaging
"""
import time
from pyrates import CircuitTemplate
from pyrat... |
17e80cc19741b825ead7be82582b9dcd99ba50b17b8d05dba7050c3e4dd6e99b | Python | 1,259 | 40 | from scipy.io import savemat
import numpy as np
import glob
import sys
def main(path,filename):
npzFiles = glob.glob(path + "/*.npy")
for i,f in enumerate(npzFiles):
d = np.load(f)
if(i==0):
Qx = d[range(1,d.shape[0],5),:]
Qy = d[range(2,d.shape[0],5),:]
Qz =... |
c3e95f4c281050d7d1cb2660fab587f5d82e13a1b1290aa1f0295727e71d3cfe | Python | 1,259 | 36 | import argparse
import numpy as np
parser = argparse.ArgumentParser(description="Manual")
parser.add_argument("-f", type=str , default="./example/expression.txt" , help="A path to 'gene expression matrix' file")
parser.add_argument("-k", type=float , default=0.1 , help="balance parameter")
parser.add_argument("-... |
167cb32fa67155041235c8c9c788f2649fa4355fe1c5b5577092dfe30a642ee2 | Python | 1,262 | 45 | """Manifold for sets of landmarks that belong to any given manifold.
Lead author: Nicolas Guigui.
"""
from geomstats.geometry.nfold_manifold import NFoldManifold, NFoldMetric
class Landmarks(NFoldManifold):
"""Class for space of landmarks.
The landmark space is a product manifold where all manifolds in the... |
1b30b822152ea93879819159385c23b99aa8b399068f9f2975aae4341d8c6a2c | Python | 1,262 | 48 | """Minkowski space.
Lead author: Nina Miolane.
"""
import geomstats.backend as gs
from geomstats.algebra_utils import from_vector_to_diagonal_matrix
from geomstats.geometry.euclidean import Euclidean, EuclideanMetric
class Minkowski(Euclidean):
r"""Class for Minkowski space.
This is the Euclidean space end... |
268615a35a8593708921a92d36a63b2894f51cf57bd0a0cc8f8e0c8ee692045b | Python | 1,262 | 40 | from typing import List
import numpy as np
from chromadb.api import ServerAPI
from chromadb.api.models.Collection import Collection
from chromadb.test.conftest import multi_region_test
@multi_region_test
def test_many_collections(client: ServerAPI) -> None:
"""Test that we can create a large number of collection... |
a7f12acad0d4d5f21bcb119f3922f28d637d91120ab933ca495318d606277935 | Python | 1,262 | 32 | import pytest
import unittest
from reinvent.models import LibinventTransformerAdapter, SampledSequencesDTO
from tests.models.unit_tests.libinvent.transformer.fixtures import mocked_libinvent_model
from tests.test_data import (
SCAFFOLD_SINGLE_POINT,
SCAFFOLD_DOUBLE_POINT,
SCAFFOLD_TRIPLE_POINT,
SCAFFOL... |
dd02da3b14a75de6eb4425019002ff1d47e410b995cea8c64b4b8f781e769a69 | Python | 1,263 | 45 |
class TermColors:
""" Colors class:reset all colors with colors.reset;
two subclasses fg for foreground
and bg for background; use as colors.subclass.colorname.
i.e. colors.fg.red or colors.bg.greenalso, the generic bold, disable,
underline, reverse, strike through,
and invi... |
e134c6d9f4bee3ef1bea5befc695f3cb5d517410b046c18c1111bf190960fb6d | Python | 1,263 | 50 | """Base tools to handle datasets.
Note: deeply inspired by sklearn.
"""
import logging
import os
from collections import namedtuple
import requests
DEFAULT_DATA_DIR = os.path.expanduser(os.path.join("~", ".geomstats_data"))
FigshareMetadata = namedtuple("FigshareMetadata", ["filename", "article_id"])
def _get_d... |
a7020fe8d06cf86690b277713714038ba1d4afbb43fbdc5d38734be4b9162bdc | Python | 1,267 | 29 | from reinvent.chemistry.library_design.reaction_filters.defined_selective_filter import (
DefinedSelectiveFilter,
)
from reinvent.chemistry.library_design.reaction_filters.reaction_filter_enum import (
ReactionFiltersEnum,
)
from reinvent.chemistry.library_design.reaction_filters.base_reaction_filter import (
... |
a06a7bd4cceb649b906ad021279eff61f06a35b5df8c1f1b253450d0679e5204 | Python | 1,268 | 52 | """Step functions"""
__all__ = ["RightStep", "LeftStep", "Step"]
from dataclasses import dataclass
import numpy as np
from .transform import Transform
@dataclass
class Parameters:
type: str
low: float = 0.0
high: float = 0.0
class RightStep(Transform, param_cls=Parameters):
def __init__(self, par... |
bf11522a7c8dcafcb42f77ecf69f55532821292e60921de5c4afe696adfb9ea5 | Python | 1,268 | 33 | import pandas as pd
import numpy as np
import argparse
import time
import os
if __name__ == "__main__":
# search for all subjects who have an MRI scan.
#
root = '/home/hoang/data/ANDI/tadpole_challenge/'
d12Df = pd.read_csv(os.path.join(root, 'TADPOLE_D1_D2.csv'))
print(d12Df.loc[:,'IMAGEUID_UCS... |
38cf8398a88c1f4df83ec3ef8ddb9116c341567bfcac3af540956c73b325fbb1 | Python | 1,270 | 40 | import torch
import torch.nn as nn
class Discriminator(nn.Module):
def __init__(self, n_h):
super(Discriminator, self).__init__()
self.f_k = nn.Bilinear(n_h, n_h, 1)
for m in self.modules():
self.weights_init(m)
@staticmethod
def weights_init(m):
if isinstance... |
2e63631ae53c677ce1aea6a7e8128e833bf45d3c95e80f94688f337b7f7962c9 | Python | 1,271 | 25 | from reinvent.datapipeline.filters import RDKitFilter
from reinvent.datapipeline.validation import FilterSection
SMILES = [
"CN1CCC23c4c5ccc(OC(=O)c6ccc7ccc(C(=O)Oc8ccc9c%10c8OC8C(O)C=CC%11C(C9)N(C)CCC%108%11)cc7c6)c4OC2C(O)C=CC3C1C5",
"CC1(C)CCC(C)(C)c2cc(N3c4cc5c(cc4B4c6oc7ccc(C89CC%10CC%11CC(C8)C%119%10)cc7... |
5b88acacccd68211610b6563d0bc6036edbe60d76130f41a8ea4e129f0e69015 | Python | 1,272 | 55 | # helper functions
from numbers import Number
import numpy as np
from src.constants import DISTANCE_LABEL, SECTION_LABEL
def mut_name(frac):
if frac == 1:
return "C125Y"
elif frac == 0:
return "WT"
return f"C125Y - {100*frac:.0f}%"
def get_key(pv, frac, stim, dur):
basename = mut_n... |
8cd62c96ad7fc2fdcb0edf8a07b9c003078ea3f09856ca0b7fe9ddbfa5bca282 | Python | 1,272 | 38 | import random
from geomstats.test.data import TestData
class InformationManifoldMixinTestData(TestData):
N_SAMPLE_POINTS = [1] + random.sample(range(2, 5), 1)
def generate_random_data_with_samples(self, marks=()):
data = []
for n_points in self.N_RANDOM_POINTS:
for n_samples in s... |
fb9f38a6bf6e90664f5aa1c8f8bf9b55a9cd4d1ed83ba72a4886eb65e8bab2f8 | Python | 1,273 | 46 | import torch
import torch.nn as nn
__author__ = "Zhijian Yang"
__copyright__ = "Copyright 2019-2020 The CBICA & SBIA Lab"
__credits__ = ["Zhijian Yang"]
__license__ = "See LICENSE file"
__version__ = "0.1.0"
__maintainer__ = "Zhijian Yang"
__email__ = "zhijianyang@outlook.com"
__status__ = "Development"
class TwoInpu... |
b1d0d2081c5daa0275d22af5c5eb1614c4a85ee99d6f6bdf7f846b34f7b27cb2 | Python | 1,276 | 46 | import cv2
import os
import fastdeploy as fd
def parse_arguments():
import argparse
parser = argparse.ArgumentParser()
parser.add_argument(
"--model_dir", required=True, help="Path of PaddleDetection model.")
parser.add_argument(
"--image_file", type=str, required=True, help="Path of ... |
92d39f0a7be8cd3ed0510965098f3659e1771b48c9f88e7b79e364b2abb4992d | Python | 1,278 | 43 | """
Test the TMalign wrapper
"""
import os
import unittest
from foldingdiff import tmalign
class TestTMalign(unittest.TestCase):
"""
Test the TMalign wrapper
"""
def setUp(self) -> None:
self.fname1 = os.path.join(
os.path.dirname(os.path.dirname(__file__)), "data", "7PFL.pdb"
... |
f1fa55503a8c83bf93a7c679cc583b04bd9321b201162c5dff627970e4ca144c | Python | 1,278 | 45 | import fastdeploy as fd
import cv2
import os
def parse_arguments():
import argparse
parser = argparse.ArgumentParser()
parser.add_argument(
"--model_dir", required=True, help="Path of PaddleDetection model.")
parser.add_argument(
"--image_file", type=str, required=True, help="Path of t... |
f701e117d51e3ad380b6724a03aafe52a61de317e5fe2339011e4ccf7efe8949 | Python | 1,282 | 28 | import os
name_script_old = "network_permutation_equivariant_shallow_new_lba.py"
name_script_new = "network_perm_equivariant_modular_conv_new_lba.py"
string = "#!/usr/bin/env bash \n\n#SBATCH --partition=batch_default\n#SBATCH --cpus-per-task=2\n#SBATCH --gres=gpu:1\n#SBATCH --time=48:00:00\n\nsource ~/.bashrc\nmod... |
6ccd5e4042322bb270806b5a8bf0ed6c8c899f7a012d69b80a23c25f52952156 | Python | 1,284 | 40 | import torch
from typing import Optional, Union
import cv2
import numpy as np
def canny_processor(frame: np.ndarray, threshold_low: float,
threshold_high: float) -> np.ndarray:
return cv2.Canny(frame, threshold_low, threshold_high)
def sobel_processor(frame: np.ndarray) -> np.ndarray:
k... |
1b0bc2ec04882d24f8490ee1b3f044742a95509390c88fca433af546f8ac1bb0 | Python | 1,287 | 46 |
from sleepy.processing.processor import Algorithm
from sleepy.processing.parameter import Parameter
class Massimi(Algorithm):
def __init__(self):
self.name = "Massimini (2004)"
self.negativeHeight = Parameter(
title = "Required height of negative peak (-μV)",
... |
a3be5febba959af860f526b81a76214887867563ec7a3c303644b98e92b08bd5 | Python | 1,287 | 39 | """Adapter for LinkInvent"""
from __future__ import annotations
__all__ = ["LinkinventAdapter", "LinkinventTransformerAdapter"]
from typing import List, TYPE_CHECKING
from .sample_batch import SampleBatch
from reinvent.models.linkinvent.dataset.paired_dataset import PairedDataset
from reinvent.models.model_factory.m... |
d22ca64384553f5d6a97caa6ffcbf035689ec2c325e5a31bd2cf5b6279407814 | Python | 1,288 | 41 | import numpy as np
import matplotlib.pyplot as plt
#average_act = np.mean(np.array(e_ng['n.output'][0]), axis=1)
def inhibition_excitation_scatter(inh, exc):
inh = np.mean(inh, axis=0)
exc = np.mean(exc, axis=0)
plt.scatter(exc, inh)
plt.xlabel('excitation')
plt.ylabel('inhibition')
plt.show(... |
3d947048d293dc508c182abe80c0d920c709eff2399a10897c99318250882ec2 | Python | 1,289 | 41 | # Author: Guoqing Bao
# School of Computer Science, The University of Sydney
# Date: 2019-12-12
# GitHub Project Link: https://github.com/guoqingbao/Pathofusion
# Please cite our work if you found it is useful for your research or clinical practice
from django.db import models
# Create your models here.
class imageli... |
9902ac3764831c1488a0ca889f78a8e3b7c047ffc8f887242ed3622791449740 | Python | 1,289 | 33 | import pytest
import numpy as np
from reinvent_plugins.components.NIBRSubstructureFilters.comp_nibr_substructure_filter import Parameters
from reinvent_plugins.components.NIBRSubstructureFilters.comp_nibr_substructure_filter import NIBRSubstructureFilters
SMILIES = [
"CC1=C(C=C(C=C1)N2C(=O)C(=C(N2)C)N=NC3=CC=CC(... |
3c09f8d0947e6ced356c8423586ef447de2e7a063573ebd97cc72ce8f7b1e82d | Python | 1,291 | 36 | import unittest
import torch.utils.data as tud
from reinvent.models.transformer.core.dataset.paired_dataset import PairedDataset
from reinvent.models.transformer.core.vocabulary import SMILESTokenizer
from tests.test_data import ETHANE, HEXANE, PROPANE, BUTANE
from tests.models.unit_tests.mol2mol.fixtures import mock... |
7db963de027be7e040cff9f7bacb586eb5ed78c12d811da3756aab0dd66adfb6 | Python | 1,291 | 49 | import setuptools
with open("README.rst", "r") as fh:
long_description = fh.read()
setuptools.setup(
name="corgie",
version="0.1.1",
author="Sergiy Popovych",
author_email="sergiy.popovich@gmail.com",
description="Connectomics Registration General Inference Engine",
long_description=long_d... |
a327eb8440fd0070f9e167444fcc901a906b2955189e665a7b2461b58599a268 | Python | 1,291 | 44 | """
White Noise
@author: Mathieu Scheltienne
"""
import numpy as np
from ._sound import _Sound
class WhiteNoise(_Sound):
"""
White noise stimuli.
Parameters
----------
volume : list | int | float, optional
If an int or a float is provided, the sound will use only one channel
(m... |
d24cb6ae3a43de7f91ae6f91b384d594e45da05a98dbd919772422228444d955 | Python | 1,292 | 41 | # Copyright 2020-2024 Intel Corporation
# SPDX-License-Identifier: Apache-2.0
"""openfl common object types."""
from abc import ABCMeta
from collections import namedtuple
TensorKey = namedtuple("TensorKey", ["tensor_name", "origin", "round_number", "report", "tags"])
TaskResultKey = namedtuple("TaskResultKey", ["ta... |
68aed40e0fa88e216539f6ffa52eb6bcbad22528c665e93e6b951f4bfce20038 | Python | 1,293 | 49 | from PymoNNto import *
#https://brian2.readthedocs.io/en/stable/examples/frompapers.Hindmarsh_Rose_1984.html
def exp(x):
return np.e**x
def exprel(x):
return (exp(x) - 1)/x
class HR_main(Behavior):
def initialize(self, n):
self.set_parameters_as_variables(self)
self.dt = 0.01# * ms
... |
43a1d0af26a89abe42d25ac0fcd564b4a39fac665dcb5dd8c4a7a9ff7d642b70 | Python | 1,294 | 40 | from PymoNNto.NetworkCore.Behavior import *
from PymoNNto.NetworkBehavior.EulerEquationModules.Helper import *
from sympy import symbols
class Equation(Behavior):
def initialize(self, neurons):
n=neurons
self.add_tag('EquationModule')
self.step_size = self.parameter('step_size', '1*ms', n... |
8ea04879b93fff79600edddc4d19253fb36a7689c03b88157eaeb3d30a69780c | Python | 1,295 | 40 | import torch.nn as nn
# Create the model
class ConvNet(nn.Module):
def __init__(self):
super(ConvNet, self).__init__()
#CNN Block 1
self.layer1 = nn.Sequential(
nn.Conv1d(246, 256, kernel_size=7, stride=1),
nn.ReLU())
self.layer2 = nn.Sequential(
... |
e458b304c0b829cf8c05c2a818461559b2f457b6ca2404fe744e54eb4b63f389 | Python | 1,295 | 50 | # -*- coding: utf-8 -*-
import os
import argparse
import logging
import numpy as np
# use this format to tell the parsers
# where to insert certain parts of the script
# ${imports}
def parse_args():
# Argument Parser
parser = argparse.ArgumentParser()
# my args
parser.add_argument("--verbose", actio... |
1e01bfd7e33a694dca80eeab73fce0c060a27ff9c381c67c4285acbafd4c5b5d | Python | 1,299 | 42 | class NoamOpt:
"Optim wrapper that implements rate."
def __init__(self, model_size, factor, warmup, optimizer):
self.optimizer = optimizer
self._step = 0
self.warmup = warmup
self.factor = factor
self.model_size = model_size
self._rate = 0
def step(self):
... |
21d96c041f4862d4d3e1f3c80003f81dba0ff58247b8352217b2d109659db295 | Python | 1,301 | 46 | """The Reinvent sampling module"""
__all__ = ["ReinventSampler"]
import logging
from rdkit import Chem
from .sampler import Sampler, validate_smiles
from .params import SAMPLE_BATCH_SIZE
from ...models.model_factory.sample_batch import SampleBatch
logger = logging.getLogger(__name__)
class ReinventSampler(Sampler... |
c3943d7268cd4a38dd94064539107ca0047917816eab777f10a6fd4d3b30bd6b | Python | 1,301 | 44 | """Compute all the 1613 2D Mordred and extract the desired one
NOTE: individual functions are available for these descriptors
NOTE2: Mordred needs to be updated to replace np.float with the modern equivalent
"""
__all__ = ["MordredDescriptors"]
from dataclasses import dataclass
from typing import List
import logging
... |
a3b3912afd53deec12d7a1656bd238a77657b20fc3a51e03247ec5c852b49ce0 | Python | 1,302 | 38 | import pytest
import geomstats.backend as gs
from geomstats.test.vectorization import generate_vectorization_data
from geomstats.test_cases.geometry.base import VectorSpaceOpenSetTestCase
from geomstats.test_cases.geometry.lie_group import MatrixLieGroupTestCase
class GeneralLinearTestCase(MatrixLieGroupTestCase, Ve... |
d8115b0f667591d5c04b47278d84ee4e0a93c96da83103d2dd3be0fa23a3c57b | Python | 1,302 | 39 | import sys
from typing import Optional
def ehfr_net_config_forward(
dataset_name: str = 'food101',
width_multiplier: float = 0.5,
is_eval: Optional[bool] = False,
is_test: Optional[bool] = False,
task_name: str = None,
):
num_classes = int(dataset_name[-3:])
sys.argv.... |
bd02ebe89e9623239c0922e006a00b44289f1f41ed3f85ec6f3a1f784766f6a3 | Python | 1,303 | 32 | """A missing QC report must not be presented as a clean submission."""
from pathlib import Path
import pytest
import yaml
WORKFLOW = Path(__file__).parents[2] / '.github/workflows/chunk-check.yml'
@pytest.mark.parametrize('report,selected', [(None, False), (None, True),
... |
64c2e18d80dd7bcd80a9dbaa106120232bb09e83fbac7a498a13fa9ad774c4d8 | Python | 1,305 | 43 | import random
import pytest
import geomstats.backend as gs
from geomstats.numerics.interpolation import (
LinearInterpolator1D,
UniformUnitIntervalLinearInterpolator,
)
from geomstats.test.parametrizers import DataBasedParametrizer
from geomstats.test_cases.numerics.interpolation import InterpolatorTestCase
... |
6ad2301ccebe8233c24572447d2d68687c5c5d3c546d31eb2581070c86104273 | Python | 1,307 | 47 | import pytest
from sklearn.gaussian_process.kernels import RBF, ConstantKernel
import geomstats.backend as gs
from geomstats.geometry.hypersphere import Hypersphere
from geomstats.learning.wrapped_gaussian_process import WrappedGaussianProcess
from geomstats.test.parametrizers import DataBasedParametrizer
from geomsta... |
41b1d800e4695f421ccce1886e842cec038192a0b05e505443239345f4c87d1c | Python | 1,308 | 45 | import os
import torch
from torch.utils.cpp_extension import load
compile_ok = False
if torch.cuda.is_available():
this_dir = os.path.dirname(os.path.abspath(__file__))
peak_find = load(
name="peak_find",
sources=[
os.path.join(this_dir, "peak_find.cpp"),
os.path.join(th... |
ca06336dae8302cb7c9cfa42b3bba1e7df0c39f034f0eea102c51881c26c2d4f | Python | 1,308 | 44 | import sys, os, random
import stdpopsim
from contextlib import redirect_stdout
Q=1000
speciesName = "DroMel"
sampleSize=64
sampleSizes = [sampleSize*2,sampleSize*2]
defaultModel = "const2pop"
targetPops = [0,1]
contigName = "chr3L"
geneticMapName = "ComeronCrossoverV2_dm6"
dfeName = "Gamma_H17"
annotName = "FlyBase_BD... |
f12ba857b20caa0a06de6e19987297ce94a5398795a2a1460d86201bf0ba1b2e | Python | 1,308 | 45 | import os
import hashlib
import wget
sleepedf_url = "https://www.physionet.org/files/sleep-edfx/1.0.0"
output_dir = os.path.join("./data", "sleepedf")
record_file = os.path.join(output_dir, "sleepedf_records.txt")
if not os.path.isdir(output_dir):
os.makedirs(output_dir)
if os.path.exists(record_file):
os.re... |
389a31939f8e125eaa0883e82ec0cf0152f511349dce9e928e18c70fdab45da5 | Python | 1,309 | 47 | # This file is a part of the `nequip` package. Please see LICENSE and README at the root for information on using it.
from .metrics import (
MeanAbsoluteError,
MeanSquaredError,
RootMeanSquaredError,
MaximumAbsoluteError,
HuberLoss,
StratifiedHuberForceLoss,
)
from .metrics_manager import (
... |
3adcfcb5e750b2c9346f65868f11d192dc10f4d20626b730d7812b83fe6bdba2 | Python | 1,309 | 42 | import os
import tempfile
import unittest
import numpy as np
from biotite.structure.io.pdb import PDBFile
from foldingdiff import angles_and_coords as ac
def get_structure_coords(fname: str) -> np.ndarray:
""" """
with open(fname, "rt") as f:
structure = PDBFile.read(f)
if structure.get_model_co... |
ab799ff4184cee8d35eeb7c18bbfda379a2909676e0d8720c348d139f80a0b3e | Python | 1,309 | 45 | from collections import OrderedDict
import torch
import torch.nn as nn
from model_angelo.models.common_modules import FcResBlock
class TransitionLayer(nn.Module):
def __init__(self, hidden_features: int, checkpoint: bool = True) -> None:
super().__init__()
self.hfz = hidden_features
se... |
31f3b618ff9491b274b16f20571a1da3d7891b974bbe5459ef33627c498ef4b1 | Python | 1,313 | 36 | import sys
winSize=int(sys.argv[1])
missingDataThreshold=0.25
line = sys.stdin.readline()
first = True
colsToDiv, colsToDivTwice = [], []
while line:
line = line.strip().split()
if first:
for i in range(len(line)):
if line[i] in "pi1,private1,ss1,thetaH1,H1,pi2,private2,ss2,thetaH2,H2,dxy_... |
548583cae6f89a36e23e5e76cc9713281b73fa58f09ebafd2dc58e3e00b7e8f2 | Python | 1,313 | 36 | import numpy as np
import scipy.sparse as sp
import torch
def scipysp_to_pytorchsp(sp_mx):
""" converts scipy sparse matrix to pytorch sparse matrix """
if not sp.isspmatrix_coo(sp_mx):
sp_mx = sp_mx.tocoo()
coords = np.vstack((sp_mx.row, sp_mx.col)).transpose()
values = sp_mx.data
shape = ... |
8af7f3228a9e755e48074cd862812d5745884226793573653c85d1ff68b887f4 | Python | 1,315 | 54 | import pytest
from torch import nn
from reinvent.models.transformer.core.network.encode_decode.model import EncoderDecoder
from reinvent.models.transformer.core.vocabulary import build_vocabulary
from reinvent.models.transformer.linkinvent.linkinvent import LinkinventModel
from reinvent.models import meta_data
from te... |
331e421543e6dbb4a0590e2d21fbec63ffefcb88de10ca494e87c2d6208d3fef | Python | 1,316 | 58 |
import unittest
import pdb
import numpy as np
from unittest.mock import MagicMock, Mock, patch, PropertyMock
from sleepy.gui.settings.core import Settings
class SettingsTest(unittest.TestCase):
def test_construct_attributes(self):
settings = Settings()
try:
settings.sh... |
ba4ddbd680a3c16f01e9324f2dd47b6c5ffdb9e1d0836fd6d214194288168e21 | Python | 1,318 | 34 | from rdkit import Chem
import os.path as osp
from tqdm import tqdm
import pickle
def filter_sanitize_error():
with open('/mnt/dive/shared/kaleb/Datasets/PubChemQC/utils/list_of_valid_mol_dirs.pkl', 'rb') as f:
mol_dirs = pickle.load(f)
print(len(mol_dirs))
raw_dir = '/mnt/dive/shared/kaleb/Da... |
7ec493cbdc47432e8f0926baef66456264638a2f7f47528747115863028cdd68 | Python | 1,319 | 32 | import torch
import torch.nn as nn
from model_angelo.models.common_modules import FcResBlock
from model_angelo.utils.affine_utils import affine_from_3_points, affine_mul_vecs
class BackboneFrameNet(nn.Module):
def __init__(self, in_features: int, activation_class=nn.ReLU) -> None:
super().__init__()
... |
f37abe191736623bcaf121caf7dc54a56867593ff2bfdcdc48358fd417109a8f | Python | 1,319 | 59 | from .GUI_main_base import GUIBase
from .widgets_utils.canvas import Canvas, CanvasMouseEvent, CanvasPainter
from .widgets_utils.custom_list import CustomList
from .widgets_utils.id_labels import IdLabels
from .widgets_utils.other_utils import (
AddBtn,
LightPopUp,
QHLine,
RemoveBtn,
TransparentDisa... |
8e2f1821fda08a6f35fec89ffd2562e8b07df03f7e2c17c64c5c1e7298240085 | Python | 1,320 | 37 | import os
import re
import pandas as pd
from tqdm import tqdm
import matplotlib.pyplot as plt
import numpy as np
import nibabel as nib
from common.adni.utils import check_projection
from common.adni.update_mri_metadata import check_valid_spacing, get_reordered_spacing
from nibabel.processing import conform
if __name_... |
4442505727c2b5eeca4160157809761c4c5e48c25973eee75e5d20984bd8aa5f | Python | 1,322 | 52 | # pylint: disable=redefined-outer-name
import tempfile
from pathlib import Path
from typing import Optional
import bids.layout
import pytest
from pyfakefs.fake_filesystem import FakeFilesystem
@pytest.fixture
def fakefs(
request: pytest.FixtureRequest,
):
"""fakefs wrapper that can be disabled using the mark... |
f4ecd5d1e0fa922a0b77e57e702701df10d9a760f61a16df9bdfaee587a3755e | Python | 1,322 | 41 | import jax
import jax.numpy as np
@jax.custom_jvp
def gr_than(x, thr):
""" Thresholding function for spiking neurons. """
return (x > thr).astype(np.float32)
@gr_than.defjvp
def gr_jvp(primals, tangents):
""" Surrogate gradient function for thresholding. """
x, thr = primals
x_dot,... |
f7c5ed2d8abde13e46a1f2bd4baa4c245e4d5d733dae68a49d8d48b3f8f63698 | Python | 1,323 | 43 | # Generated by Django 4.1.1 on 2022-11-05 12:49
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
('celsus', '0021_alter_differentialanalysisdata_gene_names_and_more'),
]
operations = [
migrations.AddField(
model_name='different... |
ec822d31e4b285f91c20e1f6bbc57f551186851d7ab95d946ef6c1bbf40c2f69 | Python | 1,324 | 55 | """nltools: a Python toolbox for analyzing neuroimaging data.
Focused on multivariate analyses and built on top of nilearn and scikit-learn,
nltools provides high-level data classes — `BrainData`, `Adjacency`, and
`DesignMatrix` — that wrap common neuroimaging workflows, alongside a
functional core of statistics and a... |
7d32990839481e11490f0c853f2fde33c2537a1209c9f528625f91470de04f1d | Python | 1,325 | 35 | import os
import pickle
import pandas as pd
import numpy as np
from tqdm import tqdm
from common.adni.utils import INPUT_COLS, TARGET_COLS, NAME2DX, NUMERICAL_COLS, MRI_BIOMARKERS, ECOG_COLS, RAVLT_COLS
def get_stats(df):
stats = {}
df.replace(r'^\s*$', np.nan, regex=True, inplace=True)
for col in NUMERICA... |
9e2259ccf4970fb62d7033255eea11e28b4606714b48a33d1eb4edb47afdccd0 | Python | 1,325 | 45 | #
# For licensing see accompanying LICENSE file.
# Copyright (C) 2022 Apple Inc. All Rights Reserved.
#
from typing import Any
import numpy as np
def setup_size(size: Any, error_msg="Need a tuple of length 2"):
if isinstance(size, int):
return size, size
if isinstance(size, (list, tuple)) and len(si... |
c2a6d40720786742bfecd416e3a32ea5cb1c47a7f928608b74af8e46773f0d41 | Python | 1,325 | 40 | # 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... |
f1f2bef8a2fb3a89433aee0b42d8c96e27f74005c11d7a6f4dad914bdd60d766 | Python | 1,325 | 55 | """Create a grid image from molecules for Tensorboard."""
from __future__ import annotations
__all__ = ["make_grid_image"]
from typing import Tuple, List
import logging
import torch
from torchvision import transforms
from rdkit import Chem
from rdkit.Chem.Draw import MolsToGridImage
logger = logging.getLogger(__nam... |
69c374bf66111cbcae3a3ed76fd139588cee19346dd1dbaaa3ea72c04a9bc6e4 | Python | 1,327 | 47 | """Shared fixtures for model tests."""
import numpy as np
import pytest
@pytest.fixture(scope="module")
def glm_design():
"""Small full-rank single-run design carrying an explicit intercept column."""
from nltools.data import DesignMatrix
rng = np.random.RandomState(0)
n_samples = 40
return Desi... |
e76651dab7ff0fe1ec907db590c4f801b9fe8143649210393afa71e3ca194223 | Python | 1,327 | 50 | import random
import pytest
from geomstats.geometry.hermitian_matrices import HermitianMatrices
from geomstats.test.parametrizers import DataBasedParametrizer
from geomstats.test_cases.geometry.base import ComplexMatrixVectorSpaceTestCase
from geomstats.test_cases.geometry.hermitian import HermitianMetricTestCase
fr... |
21733e94c515a8eb621a8ae23842c36c214a533a6393926570362396b02fda17 | Python | 1,329 | 56 | from PyQt5 import QtWidgets
from sanpy.sanpyLogger import get_logger
logger = get_logger(__name__)
import sanpy
from sanpy.interface.plugins import sanpyPlugin
class sanpyLog(sanpyPlugin):
"""Plugin to display sanpy.log
"""
myHumanName = "SanPy Log"
def __init__(self, **kwargs):
"""
... |
3285cae99fbcf1f259b250c0c2078bdba35c5f3495ab09a804f5d37be65a1757 | Python | 1,331 | 45 | # Copyright (C) 2020-2024 Intel Corporation
# SPDX-License-Identifier: Apache-2.0
from copy import deepcopy
import torch
import torchvision
train_dataset = torchvision.datasets.MNIST(
"./files/",
train=True,
download=True,
transform=torchvision.transforms.Compose(
[
torchvision.tr... |
227efbe4aa66a04e3574232cd8cb637ddb6f042214b5892a261ceecc43f84c6e | Python | 1,332 | 56 | import random
import pytest
from geomstats.geometry.hermitian import Hermitian
from geomstats.test.parametrizers import DataBasedParametrizer
from geomstats.test.test_case import np_and_torch_only
from geomstats.test_cases.geometry.hermitian import (
HermitianMetricTestCase,
HermitianTestCase,
)
from .data.h... |
69f19b59bd0aac6088da42c44a39f72d1fe48d76af3116c4dae2b8f05603ef07 | Python | 1,332 | 45 | # Copyright (C) 2020-2024 Intel Corporation
# SPDX-License-Identifier: Apache-2.0
from copy import deepcopy
import torch
import torchvision
train_dataset = torchvision.datasets.MNIST(
"./files/",
train=True,
download=True,
transform=torchvision.transforms.Compose(
[
torchvision.tr... |
273f9641c4d58bde23cbb9ecad60be45302572a5dacba6a83406a70a6f046952 | Python | 1,335 | 45 | import os
import numpy as np
def read_PSSM_data(fname):
"""Read the PSSM data."""
f = open(fname,'r')
data = f.readlines()
f.close()
filters = (lambda x: len(x.split())>0, lambda x: x.split()[0].isdigit())
return list(map(lambda x: x.split(),list(filter(lambda x: all(f(x) for f in filters), ... |
63b3e1880cead03715cb2d0b135a1eac94eed48bbb18dd79d32438d103f8efc1 | Python | 1,335 | 37 | # Copyright (c) 2023 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 appli... |
67a246cbf371f8181d992d6391e02599bbf56168662c0a19cfbd64196f57ab6d | Python | 1,336 | 50 | from termcolor import cprint
import threading
class Alert:
alerts = {
'none': '*',
'info': '[INFO]',
'warn': '[WARNING]',
'error': '[ERROR]',
'success': '[INFO]'
}
colors = {
'none': 'white',
'info': 'yellow',
'warn': 'yellow',
'e... |
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