sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
79b7316cb83b0e7a5d8f3e712b4961c975764dedadfef6db8e03b71402dbec56 | Python | 559 | 21 | import numpy as np
import imageio
def _stack_from_tif(file):
reader = imageio.get_reader(file)
img = reader.get_data(0)
n_frames = reader.get_length()
stack = np.full((n_frames, *img.shape), 0, dtype=np.uint16)
for i in range(n_frames):
try:
stack[i, :, :] = reader.get_data(i)
... |
7bd16f019d480f7648f8a76b3b854681635bda95836f77906a0a0a4ad34c00db | Python | 559 | 20 | import os
import pandas as pd
__all__ = ["write_output"]
def write_output(imputed_gwas, output, append=False):
"""
Write GWAS data to file in tab-delimited format
:param imputed_gwas: pandas.DataFrame object containing GWAS data
:param output: file-object or path to write file to
:param append: ... |
c47269329eb8e9ad14108b482320f895ec9470395fa0800d603a82b2d9c6cd6e | Python | 559 | 21 | from __future__ import annotations
from typing import List
import numpy as np
from .diversity_filter import DiversityFilter
class PenalizeSameSmiles(DiversityFilter):
"""Penalize previously generated compounds."""
def update_score(self, scores: np.ndarray, smilies: List[str], mask: np.ndarray) -> None:
... |
44d02aedc83c3d593949090e8e13c80efcb305b37db026622aec1cbc77fba856 | Python | 562 | 19 | from infomap import infomap
infomapWrapper = infomap.MemInfomap("--two-level --expanded")
# from (layer, node) to (layer, node) weight
infomapWrapper.addMultiplexLink(2, 1, 1, 2, 1.0)
infomapWrapper.addMultiplexLink(1, 2, 2, 1, 1.0)
infomapWrapper.addMultiplexLink(3, 2, 2, 3, 1.0)
infomapWrapper.run()
tree = infoma... |
6339dfbb358b6af179d066fc006b0c451fa745060f0f7465995a4871f0b43e50 | Python | 563 | 23 | __all__ = [
"data",
"datasets",
"analysis",
"cross_validation",
"plotting",
"stats",
"utils",
"file_reader",
"mask",
"prefs",
"external",
"__version__",
]
from .analysis import Roc
from .cross_validation import set_cv
from .data import Brain_Data, Adjacency, Groupby, Des... |
29796597b898e67035df4cd28287b7f25cf1a817ca79ae0c893c8d2f2b8921fd | Python | 564 | 31 | __submodules__ = ["core"]
# <AUTOGEN_INIT>
from snakebids.core import (
BidsComponent,
BidsDataset,
BidsDatasetDict,
bids,
filter_list,
generate_inputs,
get_filtered_ziplist_index,
get_wildcard_constraints,
print_boilerplate,
write_derivative_json,
)
__all__ = [
"BidsCompo... |
30d8e2246fb21bbcb357cebd437cbecdcba043396f4033c5b77b970532e72364 | Python | 565 | 14 | import unittest
import reinvent.models.linkinvent.model_vocabulary.vocabulary as mv
from tests.test_data import CELECOXIB, COCAINE, METAMIZOLE, ASPIRIN, SIMPLE_TOKENS
class TestCreateVocabulary(unittest.TestCase):
def setUp(self):
smiles = [ASPIRIN, METAMIZOLE, COCAINE, CELECOXIB]
self.voc = mv.c... |
43319a823b8f5e0c86a5aeb5e25cb0e040a921fdbf80e1c69c37995a9055cd65 | Python | 565 | 23 | import pytest
from neurodesign import generate
@pytest.mark.parametrize("model", ["uniform", "exponential"])
def test_iti(model):
generate.iti(ntrials=20, model=model, min=1, mean=2, max=4, seed=1234)
generate.iti(ntrials=40, model=model, min=2, mean=3, max=8, resolution=0.1, seed=2134)
@pytest.mark.para... |
c6af10fcad7dedd1be39b50a81794a9ce0153b6150e26a9ce0692e7d793d730a | Python | 565 | 27 | import pytest
@pytest.fixture
def tf():
import tensorflow as tf
return tf
def test_tf_version(tf):
major_version = int(tf.__version__.split('.')[0])
assert major_version >= 2
def test_tf_cuda(tf):
assert tf.test.is_built_with_cuda()
def test_tf_gpu(tf):
assert tf.test.is_gpu_availabl... |
d7ef9687ecf784ab3d8520c44686d7183f397f753430d0a82a1a0b7946079993 | Python | 565 | 13 | # Copyright 2022 VMware, Inc.
# SPDX-License-Identifier: Apache-2.0
from importlib import util
from openfl.pipelines.kc_pipeline import KCPipeline
from openfl.pipelines.no_compression_pipeline import NoCompressionPipeline
from openfl.pipelines.random_shift_pipeline import RandomShiftPipeline
from openfl.pipelines.skc_... |
2bf81465867055c8dcde2bf7e9308dc6a2dbb633d71100d949dfe0009f34ba67 | Python | 566 | 27 | from Bio import SeqIO
import sys
import glob
import khmer
def calc_tetra(seqs):
ktable = khmer.new_ktable(4)
for seq in seqs:
ktable.consume(str(seq.seq))
tetramers = {}
for a in ['A', 'C', 'G', 'T']:
for b in ['A', 'C', 'G', 'T']:
for c in ['A', 'C', 'G', 'T']:
for d in ['A', 'C', 'G', 'T']:
te... |
50a4315373361d41da1cd060f631a0e1d30631e02bbc912ecdf5834ebb7f50a2 | Python | 566 | 16 | from sklearn import manifold, datasets
def manifold_embedding(pos,method='tsne'):
n_components = 2
n_neighbors = 100
if method == 'tsne':
tsne = manifold.TSNE(n_components=n_components, init='pca', random_state=0)
Y = tsne.fit_transform(pos)
elif method == 'spectral':
se = mani... |
c720d5d3388e74fba14af57278e555977796c545b3c2936080ed9300cc062c95 | Python | 566 | 20 | import torch.nn as nn
from model_angelo.gnn.multi_layer_ipa_no_seq import MultiLayerSeparableIPANoSeq
class Model(nn.Module):
def __init__(self):
super().__init__()
self.voxel_size = 1.0
self.ipa = MultiLayerSeparableIPANoSeq(
1280,
256,
nu... |
0160ed828934701d13e13038ad1cd8a3910c890da6aae8bc9fcdd29a7880694b | Python | 567 | 20 | """Auxiliary functions."""
__all__ = ["suppress_output"]
from os import devnull
import re
from contextlib import contextmanager, redirect_stdout, redirect_stderr
@contextmanager
def suppress_output():
"""Context manager to redirect stdout and stderr to /dev/null"""
with open(devnull, "w") as nowhere:
... |
9b4e5f078bc480fbdbdefa15fba82bcebe2037b5ac5405af89bb2fbde420fdb5 | Python | 567 | 16 | """
Module containing functions for processing files/directories, loading/saving
data and converting to other formats.
For converting to '.fif', it supports MNE supported formats to '.fif'.
c.f. https://mne.tools/stable/generated/mne.io.read_raw.html
For exporting, it supports:
- EEGLAB: '.set'
"""
from .convert... |
72eafd57af881fe758a50895135df5ad3549c4356133d68501e026aaf0d87035 | Python | 571 | 25 | """The Mol2Mol optimization algorithm"""
from __future__ import annotations
__all__ = ["Mol2MolLearning"]
import logging
from typing import TYPE_CHECKING
from .learning import Learning
from .distance_penalty import score as _score
if TYPE_CHECKING:
from reinvent.scoring import ScoreResults
logger = logging.get... |
e199a6d7edd938e42c822f460440d5cdb37a0952c0db254c1dc3842eda760067 | Python | 572 | 21 | import torch
def to_cpu(x: torch.Tensor or torch.cuda.FloatTensor, required_grad=False, use_numpy=True):
x_cpu = x
if isinstance(x, torch.Tensor):
if x.is_cuda:
if use_numpy:
x_cpu = x.to('cpu').detach().numpy()
elif required_grad:
x_cpu = x.to(... |
fc75080fd36ba8d2dadb284ae6247bb545fef462124ab37357e4dfcded7c96a3 | Python | 573 | 20 | # This file is a part of the `nequip` package. Please see LICENSE and README at the root for information on using it.
from .node import NodeTypeEmbed
from .node_tensor import AppendVectorFieldEmbed
from ._edge import (
EdgeLengthNormalizer,
BesselEdgeLengthEncoding,
SphericalHarmonicEdgeAttrs,
AddRadial... |
2419afb73d8f17fe6e5e9e502703b589e331f6a45c13bfb87fe014daca82f3b3 | Python | 575 | 14 | """Some utility functions for template loading/writing"""
def _complete_template_path(target_path: str, source_path: str) -> str:
"""Check if path contains a folder structure and prepend own path, if it doesn't"""
if "." not in target_path:
if "/" in source_path or "\\" in source_path:
im... |
8f40f77e616a78023206778809fc7de79dfe4cee7ea1af355bf7d418d3d01e80 | Python | 575 | 21 | from .additional_info import AdditionalInfo
from .errors_explorer import ErrorsExplorer
from .id_groups import IdGroups
from .interpolator import Interpolator
from .length_calibrator import LengthCalibrator
from .mark_metadata import MarkMetadata
from .paint_blobs import find_selected_blob, paintBlobs, paintTrails
from... |
0e6e779d165bd6987fbe1e22d298b31a02cb6cc8537aa008144aff1f673286cd | Python | 576 | 19 | # Generated by Django 4.1.1 on 2022-12-01 10:37
from django.db import migrations, models
import django.db.models.deletion
class Migration(migrations.Migration):
dependencies = [
('celsus', '0035_remove_genenamemap_uniprot_record_and_more'),
]
operations = [
migrations.AddField(
... |
25135e3ccc7dc9892c28d4a30299016cf7f2313ddce3c97d59efdc048e6960b7 | Python | 576 | 23 | # Copyright 2020-2024 Intel Corporation
# SPDX-License-Identifier: Apache-2.0
"""openfl.utilities.data package."""
from openfl.utilities.data_splitters.data_splitter import DataSplitter
from openfl.utilities.data_splitters.numpy import (
DirichletNumPyDataSplitter,
EqualNumPyDataSplitter,
LogNormalNumPyD... |
4d9996e14d3fb5ecee06fbcef19cb82bdf54a0e28ea32c86bd4af7727838f378 | Python | 577 | 24 | # -*- coding: utf-8 -*-
"""
Provides physical and numerical constants.
"""
MU_WATER = 20 # M^-1
"""
Linear attenuation of water in SI unit ``m^-1``.
Source:
`nist.gov <https://www.nist.gov/pml/x-ray-mass-attenuation-coefficients>`_.
"""
MU_AIR = 0.02 # M^-1
"""
Linear attenuation of air in SI unit ``m^-1``.
Source:... |
9ccdf4f9e40b3f487058f5a38e3d60abf6d69d03aec298238346a5988f77cf28 | Python | 578 | 22 | #
# For licensing see accompanying LICENSE file.
# Copyright (C) 2022 Apple Inc. All Rights Reserved.
#
from torch import nn, Tensor
from typing import Optional, Tuple
from . import register_act_fn
@register_act_fn(name="swish")
class Swish(nn.SiLU):
"""
Applies the `Swish (also known as SiLU) <https://arxi... |
a04c9e45756523de74ceedeabea3b4e7c799a1b685f2d14c4d6fad1369f060a2 | Python | 579 | 19 | from geomstats.datasets.prepare_graph_data import HyperbolicEmbedding
from geomstats.test.parametrizers import DataBasedParametrizer
from geomstats.test_cases.datasets.prepare_graph_data import HyperbolicEmbeddingTestCase
from .data.prepare_graph_data import HyperbolicEmbeddingTestData
class TestHyperbolicEmbedding(... |
c1040b59f309bcd7427beee789ec24e4a4ce3f0fd09ca07183b3dba5a8449333 | Python | 580 | 16 | from dig.ggraph.evaluation import ConstPropOptEvaluator
from rdkit import Chem
import shutil
def test_ConstPropOptEvaluator():
smile = 'C'
mol = Chem.MolFromSmiles(smile)
res_dict = {'inp_smiles': smile, 'mols_0':[mol], 'mols_2': [mol], 'mols_4': [mol], 'mols_6': [mol]}
evaluator = ConstPropOptEvaluat... |
0aaab67b4b3df40cd001b14602f336f5da1e8d8eeb3a6c0429b122152d641085 | Python | 581 | 16 | # -*- coding: utf-8 -*-
from .reconstructor import (Reconstructor, IterativeReconstructor,
StandardIterativeReconstructor,
LearnedReconstructor,
FunctionReconstructor)
__all__ = ['Reconstructor', 'IterativeReconstructor',
'S... |
23e2a73f867a40e9382d6b684911f0dbd3a17722535d1dccbc50d872422ad42c | Python | 581 | 23 | import experiment as exp
class ActionsExperiment(exp.Experiment):
def setup(self):
self.update_actions(None, False)
exp.session_state.add_callback("is_running", self.update_actions)
def update_actions(self, _, new):
if new:
self.actions = {
"Stop": {"run": ... |
62fa0cac61be9d0099746ef4016bacc7fe55ffb8fd240d2dace7f4eec9f85494 | Python | 581 | 19 | import shutil
import config
from learning.utils import get_checkpoint
res_path = config.results / 'model_evaluation'
for res_folder in res_path.iterdir():
prediction_folder = res_folder / 'test_predictions'
if prediction_folder.exists():
print(prediction_folder)
shutil.rmtree(prediction_folde... |
aa2e602f0b73cbed1f8f871c5ec3bf2294ac3ae2194f24cb0933f59322052ec8 | Python | 581 | 24 | import logging
# Use logging.DEBUG to log every message passed through the bridge.
log_level = logging.INFO
# Path of the arena configuration file.
arena_config_path = "../system/config/arena_config.json"
# Serial communication settings
serial = {
# Serial port baud rate. Do not change unless you really want to.... |
b5e45be997f046c7f0074723f7c4fe691e163f7d2b0940028b09a1d3c4d74350 | Python | 581 | 22 | from . import solve_scipy
from . import solve_petsc
# uses petsc if available. Can set default solve by modifying this.
default_solve = (solve_petsc.solve
if solve_petsc.HAS_PETSC
else solve_scipy.solve)
def solve(*args, **kwargs):
# py2 compatible version of kw-only ... |
453174dbfbfbeabe768176552ff1f4c434991cbf83030e5d8dd75673d3b106aa | Python | 583 | 20 | from ._base import BaseEstimatorTestData
class WrappedGaussianProcessTestData(BaseEstimatorTestData):
MIN_RANDOM = 10
MAX_RANDOM = 20
tolerances = {"predict_at_train_zero_std": {"atol": 1e-4}}
def score_at_train_is_one_test_data(self):
return self.generate_random_data()
def predict_at_t... |
eb87d8b058c0d1090e334531a2c40a60d2d0e0f74a34ebbe9f78a538559c8ee4 | Python | 584 | 32 | import geomstats.backend as gs
if gs.__name__.endswith("pytorch"):
import torch
def gpu_is_available():
return torch.cuda.is_available()
def to_device(array, device="cuda"):
# TODO: check autodiff
return array.to(device)
def get_device(array):
return array.device
... |
64fe5636509a0d7a50453ee1f55a6094cf9c775c0396dce217627907f8cfb13f | Python | 585 | 31 | # ---
# jupyter:
# jupytext:
# text_representation:
# extension: .py
# format_name: percent
# format_version: '1.3'
# jupytext_version: 1.18.1
# kernelspec:
# display_name: Python 3 (ipykernel)
# language: python
# name: python3
# ---
# %% [markdown]
# # Maize workflow visua... |
ad84846bef69a2e82627565aefe69f55c6c3567f85d23654799084decabd4343 | Python | 588 | 23 | # Generated by Django 4.1.1 on 2023-01-07 14:24
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
('celsus', '0049_extraproperties_curtain_post'),
]
operations = [
migrations.AlterField(
model_name='differentialanalysisdata',
... |
d522409cd87157ffcb85cd883eb885af68a4fc4506d0c0cd1997fca1759b9f8b | Python | 589 | 16 | from .environment import check_chemical_validity, check_valency, calculate_min_plogp, reward_target_molecule_similarity, qed
from .environment import convert_radical_electrons_to_hydrogens, steric_strain_filter, zinc_molecule_filter
from .gen_mol_from_one_shot_tensor import gen_mol_from_one_shot_tensor
__all__ = [
... |
17ddc66473863aec919f4d6f6be2d39c8c4ea8af9953da6a86c4a0905c7d2275 | Python | 590 | 31 | #constants
# to go from 3 letter amino acid code to one letter amino acid code
AA3_TO_AA1 = {
"CYS": "C",
"ASP": "D",
"SER": "S",
"GLN": "Q",
"LYS": "K",
"ILE": "I",
"PRO": "P",
"THR": "T",
"PHE": "F",
"ASN": "N",
"GLY": "G",
"HIS": "H",
"LEU": "L",
"ARG": "R",
... |
a5c30a7aef7ecfdc9e65e1311776154bb663ef1250fe72026dfed80814baaefd | Python | 590 | 27 | import os
project = "IVAC"
author = "Chatipat Lorpaiboon"
year = "2020"
copyright = "{}, {}".format(year, author)
version = release = "0.0.0"
extensions = [
"sphinx.ext.autodoc",
"sphinx.ext.mathjax",
"sphinx.ext.napoleon",
"sphinx.ext.viewcode",
]
master_doc = "index"
on_rtd = os.environ.get("READT... |
f7f694b370277c4bbfe2d8ea60eae9f9da09fd40ddc1f47e63fa3a09c9701f60 | Python | 590 | 21 | import numpy as np
import tensorflow as tf
"""
Disclaimer: the weight_variable_glorot function from this file comes
from the tkipf/gae original repository on Graph Autoencoders
"""
def weight_variable_glorot(input_dim, output_dim, name = ""):
"""
Creates a weight variable with Glorot and Bengio's initializ... |
ce2e9feb166157ec7bf41bd69fd69a1c589ce53abda3bd1e4fb9587be9065147 | Python | 591 | 19 | import re
from collections import OrderedDict
from torch_geometric import __version__
def compatible_state_dict(state_dict):
comp_state_dict = OrderedDict()
for key, value in state_dict.items():
comp_key = key
comp_value = value
if int(__version__[0]) >= 2:
comp_key = re.s... |
2d46e930bfecae18c3219803b0a4460068cc72a0948e396eef322f7fdeac3a97 | Python | 592 | 20 | import torch.nn as nn
from reinvent.models.transformer.core.network.encode_decode.clones import clones
from reinvent.models.transformer.core.network.encode_decode.layer_norm import LayerNorm
class Decoder(nn.Module):
"Generic N layer decoder with masking."
def __init__(self, layer, N):
super(Decoder... |
caaabe637284a889d66b04a35800760cf735c2f63ab4f806185fdd0bcf0f575b | Python | 593 | 18 | import unittest
from numpy import testing
from reinvent.chemistry import conversions
from reinvent.chemistry.similarity import calculate_tanimoto
from tests.chemistry.fixtures.test_data import ASPIRIN, CELECOXIB
class Test_similarity(unittest.TestCase):
def setUp(self):
self.aspirin_fp = conversions.smi... |
a22d0357f3d7887db16ff0cb48516c6d43657084f66c84896ea032480ac23173 | Python | 594 | 24 | # Import libraries
from configparser import ConfigParser
def config_db(filename, section='postgresql'):
"""
config to connect to PostgreSQL server chemosimdb.
"""
parser = ConfigParser()
parser.read(filename)
res = {}
if parser.has_section(section):
params = parser.items(section)
... |
dce0a48084f16c55daae283e700abd2a0872879ebf43b61b64954e334d8631f2 | Python | 594 | 24 | """Config Validation"""
from typing import Optional
from pydantic import Field
from reinvent.validation import GlobalConfig
class SectionParameters(GlobalConfig):
smiles_file: str
output_csv: str = "score_results.csv"
smiles_column: str = "SMILES"
standardize_smiles: bool = True
class SectionRespo... |
1b1d7bd595fa857fcb7fffe8c0fcac823caa5fb9e93556028403f736cd9a6b22 | Python | 595 | 21 | # Generated by Django 4.1.5 on 2023-02-17 11:54
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
('celsus', '0053_alter_collaborator_project_alter_curtain_project_and_more'),
]
operations = [
migrations.CreateModel(
name='DataF... |
4adae68314ee64301d7dd3a1b7b0ab76639f76480e6d08c86fc85569ba70fe34 | Python | 595 | 23 | # ------------------------------------------------------------------------------
# Copyright (c) Microsoft
# Licensed under the MIT License.
# Written by Bin Xiao (Bin.Xiao@microsoft.com)
# ------------------------------------------------------------------------------
from __future__ import absolute_import
from __futu... |
2938ce307e395d02cc9fcfca59eb0e4453ae768139ac73288e08ede80039c284 | Python | 596 | 19 | # Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import torch.nn.functional as F
def unfold1d(x, kernel_size, padding_l, pad_value=0):
"""unfold T x B x C to T x B x C x K"""
if ker... |
c13a3ded54411b8badd36cbe946a9ffff3d9d5ced5774df5ad66df347aa29709 | Python | 596 | 25 | # Generated by Django 2.1 on 2018-08-28 00:26
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
('tcgalist', '0001_initial'),
]
operations = [
migrations.AddField(
model_name='tcgapatient',
name='num',
fi... |
d08fe13acc84359b200dff47937e58a2beaa036bd157da6e3832c7f11aa6bbea | Python | 596 | 24 | import math
from .scaffold_penalty import ScaffoldPenalty
class SigmoidPenalty(ScaffoldPenalty):
"""Penalize extrinsic reward using sigmoid function."""
def calculate_penalty(self, scaffold: str) -> float:
bucket_size = self.scaffold_memory.max_size
n_scaffold_instances = self.scaffold_memo... |
14c858a95564f63903f63d50b0158c30c68daad59581dcc06a19f0821f5633d0 | Python | 597 | 26 | # os
import os
import sys
from pathlib import Path
# sci
import numpy as np
# ephys
import neo
sys.path.append('/home/georg/code/SSSort')
import sssio
# plotting
import matplotlib.pyplot as plt
if __name__ == '__main__':
path = Path(sys.argv[1])
print("dumping %s" % path.stem)
seg = sssio.smr2seg(path... |
c2b42a68d50e726ee617d0668e669dc1dd0e368e4ed232dc4185be507ef2aa80 | Python | 598 | 15 | import pytest
from geomstats.geometry.hypersphere import Hypersphere
from geomstats.geometry.sasaki_metric import SasakiMetric, TangentBundle
from geomstats.test.parametrizers import DataBasedParametrizer
from geomstats.test_cases.geometry.sasaki_metric import SasakiMetricTestCase
from .data.sasaki_metric import Sasa... |
92ea82d7b8d759c8b77c58f6f5d8eadbc11084a7db7e7db642c33ce1e7d9d567 | Python | 601 | 20 | import torch
import torch.distributed as dist
class GatherLayer(torch.autograd.Function):
"""Gather tensors from all process, supporting backward propagation."""
@staticmethod
def forward(ctx, input):
ctx.save_for_backward(input)
output = [torch.zeros_like(input) for _ in range(dist.get_w... |
14bdd790f2145e0aef0a5757ca42e61359fabbd679f3448b641a980be526bd4f | Python | 602 | 24 | # type: ignore
try:
from snakemake.cli import get_argument_parser, main
from snakemake.common import configfile
from snakemake.common.configfile import load_configfile
except ImportError:
import snakemake.io as configfile
from snakemake import get_argument_parser, main
from snakemake.io import ... |
0c46513fe3934dc16d13071de5fbc05ce7036cd29688f70c1ac50fbc42fd0ab6 | Python | 603 | 19 | import os
import pytest
from chromadb.utils.embedding_functions.voyageai_embedding_function import (
VoyageAIEmbeddingFunction,
)
voyageai = pytest.importorskip("voyageai", reason="voyageai not installed")
def test_with_embedding_dimensions() -> None:
if os.environ.get("CHROMA_VOYAGE_API_KEY") is None:
... |
ab9e1bf4c2ea951b41b20a67f969c15f6479b8728ce2a3367e3e1dd67097da59 | Python | 603 | 22 | import pandas as pd
def cal_error_frame_ratio(input_csv_path):
# read csv
data = pd.read_csv(input_csv_path)
if len(data) == 0: # empty case
error_frame_ratio = 1
elif data['timestamp'].values[-1] != (len(data) - 1):
# file time length / expected timestamp
error_frame_ratio... |
02a7684845a81cf79d5716a7067e4101d70e0049b57f0cbc0c2cc42d79c159c3 | Python | 604 | 13 | from geomstats.geometry.hypersphere import Hypersphere
from geomstats.geometry.special_orthogonal import SpecialOrthogonal
from geomstats.test.parametrizers import DataBasedParametrizer
from geomstats.test_cases.geometry.diffeo import AutodiffDiffeoTestCase, CircleSO2Diffeo
from .data.diffeo import AutodiffDiffeoTestD... |
4d86786451e2291dc2d3d810fc07070bc87ad3eed4809506b55b90bcb3418130 | Python | 604 | 22 | # Generated by Django 4.1.1 on 2022-10-20 09:11
from django.db import migrations, models
import django.db.models.deletion
class Migration(migrations.Migration):
dependencies = [
('celsus', '0010_alter_rawdata_value'),
]
operations = [
migrations.AddField(
model_name='author'... |
ab4cf1aab525a1f11192ce784f51d67e1ccf748dab9a67b09c045950fed19f31 | Python | 604 | 21 | from ._base import BaseEstimatorTestData
class TangentPCATestData(BaseEstimatorTestData):
MIN_RANDOM = 5
MAX_RANDOM = 10
def fit_inverse_transform_test_data(self):
return self.generate_random_data()
def fit_transform_and_transform_after_fit_test_data(self):
return self.generate_rando... |
8f4f11a3ce76581ecf9de450f2bedea63980249cfb1fe77dc27cdac334775f31 | Python | 605 | 27 | r"""
This module includes 8 GOOD datasets.
- Graph prediction datasets: GOOD-HIV, GOOD-PCBA, GOOD-ZINC, GOOD-CMNIST, GOOD-Motif.
- Node prediction datasets: GOOD-Cora, GOOD-Arxiv, GOOD-CBAS.
"""
from .good_hiv import GOODHIV
from .good_arxiv import GOODArxiv
from .good_pcba import GOODPCBA
from .good_cmnist import GO... |
3b910e5d3fa46bdaa103c0378569b010acfde5dd22ca39cf2b282ba21bcb22a4 | Python | 606 | 23 | from geomstats.test.data import TestData
from .quotient import AlignerAlgorithmCmpTestData
class GraphAlignerCmpTestData(AlignerAlgorithmCmpTestData):
N_RANDOM_POINTS = [1, 2]
trials = 5
class PointToGeodesicAlignerTestData(TestData):
fail_for_not_implemented_errors = False
tolerances = {"dist_alo... |
87c1399a8cfa1331717291f0f3ea0771fed4e7976f968b517e402c2840845545 | Python | 608 | 17 | import numpy as np
from chromadb.api import ClientAPI
def test_invalid_update(client: ClientAPI) -> None:
client.reset()
collection = client.create_collection("test")
# Update is invalid because ID does not exist
collection.update(ids=["foo"], embeddings=[[0.0, 0.0, 0.0]])
collection.add(ids=["... |
ccf80802fa782393ae4908277b38411bcea4e1f89e2f4bd23bca0f26a51d22c4 | Python | 608 | 25 | import os
import random
import numpy as np
import torch
def set_random_seed(SEED):
torch.manual_seed(SEED)
torch.cuda.manual_seed_all(SEED)
random.seed(SEED)
np.random.seed(SEED)
def setup(opt):
if opt.random_seed is not None:
set_random_seed(opt.random_seed)
os.environ["CUDA_VISIBL... |
3e04071a497d083193d81a86c393be3cc3a80b1d262c710955c1b2fa5484cf9e | Python | 609 | 20 | import torch.nn as nn
from reinvent.models.transformer.core.network.encode_decode.clones import clones
from reinvent.models.transformer.core.network.encode_decode.layer_norm import LayerNorm
class Encoder(nn.Module):
"Core encoder is a stack of N layers"
def __init__(self, layer, N):
super(Encoder, ... |
9e40a044d85a04a752ad7c1121059a80298e0a817c42bd107cdc62529b8fe109 | Python | 609 | 13 | # 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... |
a54be9b6f7cf729452d0a2da4d8a875d2d95f16d4ac33a4e7a7f38ef38d46c2b | Python | 609 | 10 |
from sleepy.processing.algorithms.massimi import Massimi
#rom sleepy.processing.algorithms.core import Algorithm
#from sleepy.processing.algorithms.parameter import Parameter
from sleepy.processing.algorithms.walkthrough.walkthrough import Walkthrough
from sleepy.processing.algorithms.relative.relative import Rel... |
875c2dc6c0fdbd6bb7d4fe4729a4f50b9f2ced68f95efb276ab1aa468e9a96b3 | Python | 610 | 19 | import uuid
import pytest
from chromadb.api import ServerAPI
from chromadb.config import DEFAULT_TENANT
def test_delete_database_requires_rbac_permission(
api_with_authn_rbac_authz: ServerAPI,
) -> None:
database_name = f"db_{uuid.uuid4().hex}"
api_with_authn_rbac_authz.create_database(database_name, te... |
c9a59224392232d56f358f8d1c8afd21d2f6b3063a307a07b59dd484b64f7d74 | Python | 610 | 15 | # -*- coding: utf-8 -*-
import numpy as np
import functions.manifold
#%% Load data
data = np.load('C:/Users/Ole/Documents/script/Analysis/Data/tst_pfc_March23.npy', allow_pickle=True).item()
res_day1, order_day1, shuff1 = manifold.manifolds(data, 'day1', 'struggle_time', 'immobility_time')
#%% Get vector f... |
f386d4c47668edba4d361acb25b9e712a7bb183b88af4682613728a67ff91dc1 | Python | 610 | 13 | # 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 appli... |
78a1af397093dd9745df059b9ae1ee650199bfae06e9c89408f239df68dbb592 | Python | 611 | 26 | #
# For licensing see accompanying LICENSE file.
# Copyright (C) 2022 Apple Inc. All Rights Reserved.
#
import argparse
from typing import Dict
class BaseTransformation(object):
"""
Base class for augmentation methods
"""
def __init__(self, opts, *args, **kwargs) -> None:
self.opts = opts
... |
032300c763a8e067163a424d33a7196b71fa8360c997edc057ab611cbf734360 | Python | 612 | 18 | # Generated by Django 4.1.1 on 2022-11-08 15:50
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
('celsus', '0023_project_ptm_data'),
]
operations = [
migrations.AlterField(
model_name='differentialsamplecolumn',
na... |
9ee269cdc6c91d9503514e7976752a047612298c74ea058350d9588cb12f5b43 | Python | 612 | 13 | # Copyright (c) 2020 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... |
fb507cf5e242808427d645d89287d48a37f08adc22e36c4da9802e167392ce3e | Python | 612 | 13 | # 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 app... |
95f3d1205ac51ac10886f7a6c584a87e4490c465872341ace41ad896a27705ce | Python | 614 | 14 | REACTION_SUZUKI = "[*;$(c2aaaaa2),$(c2aaaa2):1]-!@[*;$(c2aaaaa2),$(c2aaaa2):2]>>[*:1][*].[*:2][*]"
SCAFFOLD_SUZUKI = "[*]c1ccc2c(c1)cc(cc2)OC"
DECORATION_SUZUKI = "[*]c1ncncc1"
TWO_DECORATIONS_SUZUKI = "[*]c1ncncc1|[*]c1ncncc1"
TWO_DECORATIONS_AFTER_SUZUKI = "c1ncncc1c2ncncc2"
TWO_DECORATIONS_ONE_SUZUKI = "[*]c1ncncc1|... |
f45926476db37b20de9ae111c1d1227bdd69b082dcf19ab315215ad7f8d7f2cc | Python | 615 | 25 | from geomstats.test.test_case import np_backend
from ._base import BaseEstimatorTestData, MeanEstimatorMixinsTestData
IS_NOT_NP = not np_backend()
class AACFrechetMeanTestData(MeanEstimatorMixinsTestData, BaseEstimatorTestData):
pass
class AACGGPCATestData(BaseEstimatorTestData):
trials = 5
tolerance... |
564c8227ddc8d94f80ef5bf44a4961f6e0917acf54b2b21196d93b221e1aa285 | Python | 619 | 24 | import numpy as np
from nltools.data import Brain_Data
def test_length(sim_groupby):
assert len(sim_groupby) == len(sim_groupby.mask)
def test_index(sim_groupby):
assert isinstance(sim_groupby[1], Brain_Data)
def test_apply(sim_groupby):
mn = sim_groupby.apply("mean")
assert len(sim_groupby) == le... |
bc55418efe752dac227ff665291d2dfb919aa7cb650c221bb740f7f20cd82440 | Python | 619 | 24 | from __future__ import annotations
from pathlib import Path
from typing import TYPE_CHECKING, TypedDict
from typing_extensions import TypeAlias
if TYPE_CHECKING:
from argparse import _ArgumentGroup
__all__ = ["ArgumentGroups", "SnakebidsConfig"]
ArgumentGroups: TypeAlias = "dict[str, _ArgumentGroup]"
class S... |
eabf81743af8027d10c42c51be1e7a3250ad6961960f7ff18be3b442f5449382 | Python | 619 | 27 | """Get SMILES tokens from a SMILES file or CSV"""
import os
import sys
import polars as pl
from reinvent.datapipeline.filters.regex import SMILES_TOKENS_REGEX
fn = sys.argv[1]
ext = os.path.splitext(fn)[1]
if ext == ".smi":
df = pl.read_csv(fn, has_header=False, new_columns=["canonical_smiles"])
else:
df ... |
b0c2b2ac0d67ea34349d0130eb3b11a26797df7878c7517ceacf5ecec60a419c | Python | 620 | 19 | import torch.nn as nn
from reinvent.models.transformer.core.network.encode_decode.layer_norm import LayerNorm
class SublayerConnection(nn.Module):
"""
A residual connection followed by a layer norm.
Note for code simplicity the norm is first as opposed to last.
"""
def __init__(self, size, dropo... |
f5d75e33a793339a95840cfc03514b4b761b600517fc0a78d783c4c69c162943 | Python | 620 | 18 |
import matplotlib as mpl
page_width = 180 # in mm
SMALLEST_SIZE = 4
SMALL_SIZE = 5
MEDIUM_SIZE = 6
mpl.rc('font', size=SMALL_SIZE) # controls default text sizes
mpl.rc('axes', titlesize=MEDIUM_SIZE) # fontsize of the axes title
mpl.rc('axes', labelsize=SMALL_SIZE) # fontsize of the x and y labels
mp... |
0713374689ad3b5f992b9d2458c68d2415204ee96011835c602ed868313bda00 | Python | 622 | 22 | import os
def get_directory_size(directory: str) -> int:
"""
Calculate the total size of the directory by walking through each file.
Parameters:
directory (str): The path of the directory for which to calculate the size.
Returns:
total_size (int): The total size of the directory in bytes.
... |
091e0b517a0c555fb366ed0c86c45f9734e4bc9793c500da4492420c0103053a | Python | 622 | 19 | # This file is a part of the `nequip` package. Please see LICENSE and README at the root for information on using it.
import torch
from nequip.data import AtomicDataDict
class DatasetIndexTransform(torch.nn.Module):
"""Add a dataset index to ``AtomicDataDict``."""
def __init__(self, dataset_index: int):
... |
318696cb77be0f1b6bd329bf02cc302b60fd18d0fd2f60068aecede346ec6266 | Python | 623 | 26 | #!/usr/bin/env python
import numpy as np
import csv
diffs = []
labels = np.empty((0,6), dtype=float)
with open('stats.txt') as csv_file:
csv_reader = csv.reader(csv_file, delimiter=',')
line_count = 1
for row in csv_reader:
diff = float(row[1]) - float(row[3])
diffs.append(diff)
... |
b17c4dc711b94886e9fbb8dd396744fd51b38143061092c2dbd11caf074612fb | Python | 623 | 21 | """Optional PUMAS transforms and aggregations"""
__all__ = ["aggregation_catalogue", "desirability_catalogue", "check_pumas_available"]
try:
from pumas.aggregation import aggregation_catalogue
from pumas.desirability import desirability_catalogue
have_pumas = True
except ModuleNotFoundError:
aggregat... |
f54fc8bcdabb7e599e7b672f1621536f36bedff6d4b5cbce26c34458f3e50383 | Python | 623 | 17 | from geomstats.test.data import TestData
from .manifold import _ManifoldMixinsTestData
class ComplexManifoldTestData(_ManifoldMixinsTestData, TestData):
def random_point_is_complex_test_data(self):
return self.generate_random_data()
def random_point_imaginary_nonzero_test_data(self):
return ... |
df2fd496df63d0c2b339939e4bb453e19cd96e1a186740a251bb66aef09bd0b7 | Python | 626 | 24 | #
# For licensing see accompanying LICENSE file.
# Copyright (C) 2022 Apple Inc. All Rights Reserved.
#
import torch
from torch import nn, Tensor
from typing import Tuple, Union, Any
class BaseModule(nn.Module):
"""Base class for all modules"""
def __init__(self, *args, **kwargs):
super(BaseModule, ... |
7b7a9dff6a0cd8215cedb668199b099a4df01cecc5c3a107de9c68d43bff3948 | Python | 627 | 24 | import schedule as sc
import experiment as exp
import datetime as dt
class SchedulingExperiment(exp.Experiment):
def setup(self):
self.cancel_tick = None
self.cancel_next_block = None
def run(self):
self.cancel_tick = sc.repeat(self.tick, interval=2, repeats=True)
def end(self... |
4374681f06eae1b6c483df05635845a772e06bb61967bde350a2ed6af691f76b | Python | 628 | 24 | from infomap import infomap
infomapWrapper = infomap.Infomap("--two-level")
# Set the start index for bipartite nodes
infomapWrapper.setBipartiteNodesFrom(5)
# Add weight as an optional third argument
infomapWrapper.addLink(5, 0)
infomapWrapper.addLink(5, 1)
infomapWrapper.addLink(5, 2)
infomapWrapper.addLink(6, 2)
i... |
d267afd2b7564b19ef202c5124da123a0c38b88460aeacf8279e2d6af6b791ab | Python | 629 | 24 | from video_stream import ImageObserver
import numpy as np
class TestObeserver(ImageObserver):
"""An image observer that does nothing except output random integers on each image update."""
def _on_start(self):
self.log.info("on_start")
def _on_image_update(self, img, timestamp):
self._upd... |
88b077f9398e8bf59c83ae30bd19333e5e1f54a2f14317bca9104651a949496f | Python | 630 | 16 | __all__ = ["get_pair_generator"]
from reinvent.models.transformer.mol2mol.dataset import preprocessing
def get_pair_generator(pair_generator_name: str, *args, **kwargs) -> preprocessing.PairGenerator:
"""Returns a PairGenerator object.
:param pair_generator_name: name to retrieve the PairGenerator object.
... |
2607962e18f53678cd116eaf0a9953deb6f03d5cb96e4a6f505a00e42450f0af | Python | 634 | 20 | """The committed input structures and the tiny training set."""
from __future__ import annotations
from tests.golden.paths import REPO_ROOT
ORDER = 10
HELP = "the committed .xyz structures and their manifest"
def run() -> None:
# Imported here, not at module scope: the targets package is imported to
# buil... |
ef4646aa39dca6c003d1e64d35a646bd0e49b8e6212e9450e0d6fa0b008438bf | Python | 634 | 15 | # Copyright (c) 2019 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... |
ce30d032a517103ccc8f4619d7eecf7efe879c0ed548c01fc12b526047ba3ac6 | Python | 636 | 25 | """Static registry of supported MNI templates."""
from typing import Literal
TemplateName = Literal["default", "nilearn", "fmriprep"]
"""Which MNI template a brain space is built from."""
Resolution = Literal[1, 2, 3]
"""Voxel size of a template, in millimetres."""
VERSION_MAP: dict[str, str] = {
"default": "fs... |
33198f77d1f4adb0805eb13e2f2a26ab668fc22dda6b8a5fcf7eea306e8a5f0e | Python | 637 | 26 | """Element handling"""
from typing import Sequence
from rdkit import Chem
BASE_ELEMENTS = {"C", "O", "N", "S", "F", "Cl", "Br", "I"}
_PT = Chem.GetPeriodicTable()
PERIODIC_TABLE = {
elem: _PT.GetAtomicWeight(elem) for elem in [_PT.GetElementSymbol(an) for an in range(1, 119)]
}
def valid_elements(elements: Se... |
68602e408fc47fdc1c220908f28e833f8a655d3f8a627d1798cb916e76e394a9 | Python | 639 | 23 | # Generated by Django 4.1.1 on 2022-10-24 09:40
from django.db import migrations, models
import django.db.models.deletion
class Migration(migrations.Migration):
dependencies = [
('celsus', '0015_remove_file_comparison_comparison_file'),
]
operations = [
migrations.RemoveField(
... |
efe7fa1556e1a9e29702601a8749367242703b3a4334ef966969f9c1a5dd8307 | Python | 639 | 26 | """SMILES deduplication"""
__all__ = ["inchi_key_deduplicator"]
from typing import Sequence
from rdkit.Chem import MolToInchiKey, Mol
def inchi_key_deduplicator(mols: Sequence[Mol], smilies: Sequence[str]) -> list[str]:
"""Deduplicate using the InchiKey
:param mols: RDKit molecules
:param smilies: SMIL... |
453d0b3e2b187b2ef3c1e1c08d5d8068ebf10fe385f82a74fc2bce992dd373b1 | Python | 640 | 16 | import sys
sys.path.append(' /home/kusch/Documents/project/co_simulation/TVB-NEST-proof/lib/soft/lib/python3.8/site-packages/')
from neurolib.models.hopf import HopfModel
from neurolib.utils.loadData import Dataset
import matplotlib.pyplot as plt
ds = Dataset("gw")
model = HopfModel(Cmat = ds.Cmat, Dmat = ds.Dmat)
mod... |
1e8822d6166fecca1ec6e23fc863942e1b29030c104770be20f17c48cd24a831 | Python | 641 | 23 | from ._base import BaseEstimatorTestData, ClusterMixinsTestData
class ClusterInitializationTestData(BaseEstimatorTestData):
MIN_RANDOM = 5
MAX_RANDOM = 10
def initialization_belongs_test_data(self):
return self.generate_random_data()
class RiemannianKMeansTestData(ClusterMixinsTestData, BaseEst... |
05b4fbd3929aeeaa3815c8ea315bfd3780defedc73cb851868fe99ca57cf294f | Python | 643 | 24 | from .manifold import ManifoldTestData
from .riemannian_metric import RiemannianMetricTestData
class ProductManifoldTestData(ManifoldTestData):
skips = ("not_belongs",)
def embed_to_product_after_project_from_product_test_data(self):
return self.generate_random_data()
class ProductRiemannianMetricT... |
6c93aa2da0a0b89c54c6cb6e7c176711b0482050b654792a79db7863e237f65f | Python | 643 | 23 | # Generated by Django 4.1.1 on 2022-10-21 10:44
from django.db import migrations, models
import django.db.models.deletion
class Migration(migrations.Migration):
dependencies = [
('celsus', '0014_remove_comparison_file_file_comparison'),
]
operations = [
migrations.RemoveField(
... |
9a30742a6d068f3b12a08f539a639cd06132f2be729acfea520ef01337c65654 | Python | 643 | 20 | import pytest
from geomstats.test_cases.learning._base import BaseEstimatorTestCase
class LinearRegressionTestCase(BaseEstimatorTestCase):
@pytest.mark.random
def test_runs(self, n_samples):
X = self.data_generator.random_point(n_points=n_samples)
y = self.data_generator.random_image_point(n_... |
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