sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
753277411be1ed54dc4c35f595203ed81a94355a4b1d3a4c55e944f027c2fe30 | Python | 4,536 | 129 | """experiment for the ADT Network ablation study."""
import glob
import json
import logging
import os
# set gpu private
os.environ['TF_GPU_THREAD_MODE'] = 'gpu_private'
import tensorflow as tf
import numpy as np
import sys
# add base path to sys
sys.path.append(os.path.join(os.path.dirname(__file__), '..', '..'))
fr... |
76e7028b18c23714300fd3a243956102f86407c2830d03bf616b22429a3962fd | Python | 4,537 | 130 | import torch
import torch.nn as nn
from torchsummary import summary
class ResidualConv(nn.Module):
def __init__(self, input_dim, output_dim, stride, padding):
super(ResidualConv, self).__init__()
self.conv_block = nn.Sequential(
nn.BatchNorm2d(input_dim),
nn.R... |
673ae9268f6cc4ba8f6386de58da7babc5b479cc24eaeb2dab75b6836a6811d2 | Python | 4,539 | 122 | """What a multihead run reports per head, and what it leaves out.
Multihead is the normal case, so per-head reporting is the product: the
validation lines during training, the rows of the final error table, and the
`head` field on every row of the results log a plot is drawn from. None of it was
covered, and the three... |
975ca2abe8d35d0d818e20a6c7ec124d5236d21a72a1e8eabaddc40bf9f573cf | Python | 4,540 | 166 | import scipy as sp
import pylab as plt
from scipy.integrate import odeint
class HodgkinHuxley():
"""Full Hodgkin-Huxley Model implemented in Python"""
C_m = 1.0
"""membrane capacitance, in uF/cm^2"""
g_Na = 120.0
"""Sodium (Na) maximum conductances, in mS/cm^2"""
g_K = 36.0
"""Posta... |
ab64e84f839fb6f68e974f9340920b914b708d86f07a0b311556cb453e1b87ad | Python | 4,540 | 104 | import sys
from miscFuncs import *
vcfFileName, maskedRefFileName, fastaFileName1, fastaFileName2 = sys.argv[1:]
arm = vcfFileName.split("/")[-1].split(".phased.vcf")[0]
#TODO: this pulls out all sechellia individuals included in the analysis for
# the FILET paper. These genomes had identifiers ranging from SECH_17 ... |
aee30d8f6d6383f758e122f6be1b7a12e9bc99298c55536a333db8d291d97c5d | Python | 4,541 | 89 | """
Created on Sat September 16 21:15:06 2023
Description: Color palettes for:
Paper url: https://www.biorxiv.org/content/10.1101/2023.09.11.557230v2
@author: Ekaterina Kuzmina, ekaterina.kuzmina@skoltech.ru
@author: Dmitrii Kriukov, dmitrii.kriukov@skoltech.ru
"""
import matplotlib.colors as color
bg_gray_color = ... |
cd182e59eae9c116bd9096e5d3901961c3102878930425077fbe3dba3f8161fc | Python | 4,541 | 165 | # -*- coding: utf-8 -*-
"""
Created on Thu Apr 22 14:30:31 2021
@author: nicol
"""
import os, glob, tqdm
from skimage.io import imread, imsave
import numpy as np
import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt
from matplotlib import rc
import matplotlib as mpl
import scipy.ndi... |
6dc0dddbc7131c914510f47da2bb00b16240700b4c01719301452a99ea9d9064 | Python | 4,547 | 157 | import torch.nn as nn
import torch
from torch.autograd import Variable
import numpy as np
class RNN_GRU(nn.Module):
"""
Generative or multi-class classifier RNN using the GRU cell.
Params
------
input_size (int):
Vocabulary size for initializing the embedding layer.
In the ... |
a777fa5e38c13aee1d316039f36a359387dd46144f7c3a1302695672dd577b02 | Python | 4,550 | 127 | # Copyright (C) 2020-2023 Intel Corporation
# SPDX-License-Identifier: Apache-2.0
"""Dump requirements file test module."""
from pathlib import Path
import pytest
from pip._internal.operations import freeze
from openfl.utilities.workspace import dump_requirements_file
ORIGINAL_PREFIXE_LINES = ['-o option\n', ]
ORIG... |
5fc1c8451511084d2c5a51d8b730c162e40acb47de3ab5397d241996cf746433 | Python | 4,551 | 99 | """Regression cases for the shared TRA/TRD annotation migration in #1405."""
import polars as pl
from vdjdb.annotate.cdr3fix import markup
from vdjdb.assemble.evidence import structures
from vdjdb.score.evidence import integrate
def test_shared_v_proposals_and_supported_anchor_repairs():
# One batch across speci... |
8a462cad37c25aae8b64ff2d437b8bb4ae48b076d7269e84ea0a531f3680a1ad | Python | 4,551 | 148 | import hashlib
import io
import shutil
import os
import tarfile
from pathlib import Path
from typing import List, Hashable
import hypothesis.strategies as st
import onnxruntime
import pytest
from hypothesis import given, settings
from onnxruntime.datasets import get_example
from chromadb.utils.embedding_functions.onn... |
c9fb51d7d10148ed1e7bbc12ed24010df0dd142d5208be6989677956a37e27f1 | Python | 4,551 | 155 | import glob
import numpy as np
import math
import os
import csv
from scipy.integrate import simps
from scipy.signal import butter, filtfilt
def procrustes(a, b):
#translate the points to be centred at 0, 0
a1 = a - a.mean(axis=0)
b1 = b - b.mean(axis=0)
#scale the points to have unit variance.
a1 /= np.s... |
4ac0a73de51ec753fb4c3b8cfc85a08e06d702b5bb50ec948218748a3a9dbdda | Python | 4,555 | 86 | import os, random, sys
trainingOutDir = sys.argv[1]
os.system("mkdir -p %s" %(trainingOutDir))
"""
AIC: 10303.1237186
with u = 3.500000e-09
Nref: 487835.088398
nu1_0 : 117605.344694
nu2_0 : 4878347.23386
nu1 : 9279970.1758
nu2 : 26691.779717
T : 86404.6219829
2Nref_m12 : 0.0128753943002
2Nref_m21 : 0.0861669095413
""... |
f42e8d6f525d1dd8b908e1e3f48d6adfa18b10a1c7a995c4bd7201ab44e0775c | Python | 4,556 | 146 | from pathlib import Path
import numpy as np
import pandas as pd
import matplotlib
import matplotlib.pyplot as plt
from holoviews import opts
### CONSTANTS
n_per_ftr_typical = 5
### SOURCE DATA
def save_source_data(di, subfolder, base_folder='fig/source_data/'):
folder = Path(base_folder) / subfolder
folde... |
36a49fad9235e112a65f9b10962b691e414bdf45263458a752000ca22ea1702d | Python | 4,557 | 107 | # Copyright 2020 Forschungszentrum Jülich GmbH and Aix-Marseille Université
# "Licensed to the Apache Software Foundation (ASF) under one or more contributor license agreements; and to You under the Apache License, Version 2.0. "
from mpi4py import MPI
import pathlib
import os
from nest_elephant_tvb.utils import crea... |
4757d96631ae6d0233011f5d297231d1423a45944daef87bcaa23ac1ab66ff1d | Python | 4,558 | 167 | import functools
import glob
import hashlib
import logging
import os
from pathlib import Path
from typing import Optional, Tuple, Union
import numpy as np
from src import settings
from src.data.files import delete_files, cd
logger = logging.getLogger("nrn_helpers")
initialised = False
__KWARGS__ = {}
def init_nr... |
cdbdee8ead76badbfbd2fb7621fe7cd84b381ecd497a137fc242d431db2721ea | Python | 4,558 | 123 | # 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 math
from dataclasses import dataclass
import torch.nn.functional as F
from fairseq import metrics, utils
from fairseq.criterions impo... |
c3cf8bca85406dd284fc54d9c0ea9fe01095f231624c209b4b3196a87499757c | Python | 4,561 | 116 | import torch
import torch.nn as nn
import torch.nn.functional as F
import numpy as np
import random
import os
#
os.environ['CUDA_VISIBLE_DEVICES'] = "2"
device = torch.device('cuda' if torch.cuda.is_available() else "cpu")
thresh = 0.1
lens = 0.5
probs = 0.5
decay = 0.6
from SNN_layers.spike_dense import *
from SNN... |
6451a81f2bfc814be17cd0660037febc0bf1e6ba16596d9f3ff1f78812195085 | Python | 4,564 | 95 | from PymoNNto.NetworkCore.Behavior import *
class Instant_Homeostasis(Behavior):
def get_measurement_param(self, n):
if self.compiled_mp is None:
self.compiled_mp = compile(self.measurement_param, '<string>', 'eval')
result = eval(self.compiled_mp)
if self.measurement_min is ... |
a85810eb1af3a48915712a7c716d9c8d8cc7369b9d20a1ca0611be27a909306c | Python | 4,567 | 144 | """Global brain-space configuration: frozen dataclass + set/get/with API."""
from contextlib import contextmanager
from dataclasses import dataclass, replace
from collections.abc import Iterator
from .paths import _resolve_paths
from .registry import SUPPORTED_RESOLUTIONS, TemplateName, Resolution
@dataclass(frozen... |
2310ed8fbfd9bead44ee794ed0053fe9421f3a0eb39eeb19011b7f7fd8a874e4 | Python | 4,568 | 133 | # 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... |
370f2b67ead07cd61bb2ffbfc55a4e2bc304e0b76596867d6681cea22de5083d | Python | 4,568 | 108 | from typing import Any, Callable, Sequence
from jax import numpy as jnp
from flax import linen as nn
from .flax_utils import linear_activation
from .jax_utils import val_and_jacrev, val_and_jacfwd
from jax import vmap
Dtype = Any
class TransportModel_PVT(nn.Module):
features: Sequence[int]
dtype: Dtype = jnp... |
b8b849ffb1b170c59c2a663d979dbf9ba634c7b066ade6772f06597c666cb5be | Python | 4,568 | 164 | # 20210525
import os
import sys
import logging
from logging.handlers import RotatingFileHandler
from pathlib import Path
"""
DEBUG
INFO
WARNING
ERROR
CRITICAL
"""
"""
LOGLEVEL = os.environ.get('LOGLEVEL', 'WARNING').upper()
print('LOGLEVEL:', LOGLEVEL)
print('os.environ')
for k,v in os.environ.items():
print(f' ... |
bee58d378086b248979088e87777c417cce4a7d39daf80e0a33c5c655b990e30 | Python | 4,569 | 122 | """Two things `mace_eval_configs` could not do, both fixed by copying itself.
`--return_node_energies` accumulated one entry per *batch* and then built a
rectangular array out of it, so it worked only while every structure had the
same number of atoms. `--descriptors`, four lines above in the same function,
already ac... |
e2effdfc8f2e99143dc99fe58dcbf65ac38e4ea04cd54f63c55d400d868a7559 | Python | 4,569 | 88 | from typing import List
import haiku as hk
import jax.numpy as jnp
from deeperwin.model.gnn import DenseGNN, MessagePassingLayer
from deeperwin.configuration import MLPConfig, EmbeddingConfigGNN, EmbeddingConfigMoon
from deeperwin.model.definitions import InputFeatures, Embeddings, DiffAndDistances
from deeperwin.mode... |
98d34cda1e2e3bbcf562fb6c88afa6b97d200c73f1dc1e928169030a66302985 | Python | 4,571 | 141 | """Filter and preprocess SMILES with RDKit"""
from __future__ import annotations
__all__ = ["RDKitFilter"]
import logging
from typing import Optional, TYPE_CHECKING
from rdkit import Chem
from rdkit.Chem.MolStandardize import rdMolStandardize as Standardizer
from ..logger import setup_mp_logger
if TYPE_CHECKING:
... |
bf47373eeebd5e7194df3d768084b6e448264a67efa8563a05bc9c6d1ec53142 | Python | 4,571 | 131 | """
Masking Example
===============
This tutorial illustrates methods to help with masking data.
"""
#########################################################################
# Load Data
# ---------
#
# First, let's load the pain data for this example.
from nltools.datasets import fetch_pain
data = fetch_pain()
... |
6e73278e6324d96bd5e61eb473065f16f10c34b4253e4922d03ce64c7f826333 | Python | 4,572 | 163 | import random
import pytest
import geomstats.backend as gs
from geomstats.geometry.hermitian_matrices import HermitianMatrices
from geomstats.geometry.hpd_matrices import (
HPDBuresWassersteinMetric,
HPDEuclideanMetric,
HPDLogEuclideanMetric,
HPDMatrices,
)
from geomstats.geometry.spd_matrices import ... |
4f0ab464e7ae169008c4a00f9214d5541c972e15848b280c7f1b32202dd8b58c | Python | 4,573 | 149 | # -*- coding: utf-8 -*-
"""
Created on Wed Jun 16 15:52:15 2021
@author: nicol
"""
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Wed Dec 12 15:25:17 2018
@author: ngritti
"""
import time, os, glob
from tqdm import tqdm
import numpy as np
from skimage.io import imread
import seaborn ... |
5a4113b3a46cfd47ae4be3fddb8f9d4645233a6ef28c58df0e03cf4a0f5a6c7a | Python | 4,575 | 151 | # Copyright Amazon.com, Inc. or its affiliates. All Rights Reserved.
# SPDX-License-Identifier: MIT-0
"""
PDB parsers for large files with Biopython.
Modified from https://biopython.org/wiki/Reading_large_PDB_files
"""
import sys
import Bio.PDB
import Bio.PDB.StructureBuilder
from Bio.PDB.Residue import Residue
cla... |
7e99cefb1ecd9e9f74a9b73563c3c439b42fb1f9e9710fe80389caa895fce3b0 | Python | 4,577 | 114 | """
Extract the annotations of Neo objects and structure them in a DataFrame
to complement a wave characterization.
"""
import argparse
import numpy as np
import pandas as pd
import quantities as pq
import re
from utils.io_utils import load_neo, save_plot
from utils.parse import none_or_str
from utils.neo_utils import... |
55e95f53ab4f7c146b0180fdbfa21479ad84dfe63fe8b95fab0c0e454c5a24a0 | Python | 4,579 | 126 | # 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
from dataclasses import dataclass, field
import torch.nn.functional as F
from fairseq import metrics
from fairseq.tasks import F... |
8fc3ff864657e1bc80f58d18b1367e00909d3c1f8f9870db2a285fe1eb65bec1 | Python | 4,583 | 94 | # Plot Kuramoto oscillators
import numpy as np
import matplotlib.pyplot as plt
# np.random.seed(123)
N = 100 # Number of oscillators
rad = 1. # unit circle
# No sync
theta0 = np.random.uniform(0, 2*np.pi, N) # initial phase
omega0 = np.random.uniform(0, 1, N) # color indicates velocity
X0 = rad*np.cos(theta0)
Y0 = ... |
4f9ef43e9db1840ccbe709eb6699de7f0f326e7da42c716c791951a0de9e8498 | Python | 4,586 | 139 | import pytest
import torch
from nequip.data import AtomicDataDict
from nequip.nn import (
AtomwiseLinear,
AtomwiseReduce,
PerTypeScaleShift,
SequentialGraphNetwork,
GraphModel,
)
from nequip.nn.embedding import NodeTypeEmbed
from nequip.utils import dtype_from_name, torch_default_dtype
from nequip.... |
c5aefbd58e38580739235911ac261d412dda283a2689ea98888f6d68b7ef97bf | Python | 4,586 | 123 | """
API-convention guards for the inference layer.
`nltools/algorithms/inference` is an internal package whose entry points are
partly re-exported through `nltools.algorithms` and partly reached by their own
import path. These tests hold the whole family to the conventions in CLAUDE.md
rather than checking only the na... |
cc0b9eda01a6102e41ceaf1c2cf4849ef6bdfb8709b03a9697c05496272cdaf2 | Python | 4,587 | 92 | from deeperwin.run_tools.geometry_database import load_geometries, load_datasets, Geometry
from deeperwin.utils.utils import ANGSTROM_IN_BOHR, PERIODIC_TABLE
import argparse
import os
import shutil
import subprocess
import time
def write_orca_input(geom: Geometry, fname, method, basis_set, frozen_core, n_proc, memory_... |
0153971491e4b4d7385a458fc6d4c2195a7220ec73aedb3ee09c34093538187c | Python | 4,591 | 113 | from tqdm import tqdm
import numpy as np
from numpy.random import multivariate_normal
import pandas as pd
from numpy.typing import ArrayLike
from theory_simulation.regression import regression_performance
from theory_simulation.utils import fsolve_bounded_monotonic, project_onto_subspace
def run_simulation(dim_eco: i... |
4809c5c88b27aa7809483a7592cff458aa9d8dd1d05fd273da2eeab925acbcc2 | Python | 4,592 | 135 |
import random
import time
from pathlib import Path
import matplotlib.pyplot as plt
import numpy as np
import ppafm.ml.AuxMap as aux
import ppafm.ocl.field as FFcl
import ppafm.ocl.oclUtils as oclu
import ppafm.ocl.relax as oclr
import torch
from ppafm.ml.Generator import InverseAFMtrainer
from ppafm.ocl.AFMulator imp... |
2dd0fc36c57241c60ad98c356cf2096775614f96edd063416a05faef289e70fc | Python | 4,594 | 158 | # -*- coding: utf-8 -*-
#
#
# PyRates software framework for flexible implementation of neural
# network model_templates 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 Cogn... |
ebe643cedf7d991d5881b35545dbb53b1ada7d19b4f8607b5790a359e5dac8d8 | Python | 4,595 | 135 |
import random
import time
from pathlib import Path
import matplotlib.pyplot as plt
import numpy as np
import ppafm.ml.AuxMap as aux
import ppafm.ocl.field as FFcl
import ppafm.ocl.oclUtils as oclu
import ppafm.ocl.relax as oclr
import torch
from ppafm.ml.Generator import InverseAFMtrainer
from ppafm.ocl.AFMulator imp... |
6bf51445db844f308d455048a204e2255e0f4a73a95302f7854d2e20068c0aca | Python | 4,597 | 164 | """Hybrid cueq + openequivariance model converter."""
import argparse
import logging
import os
import torch
from mace.modules.wrapper_ops import CuEquivarianceConfig, OEQConfig
from mace.tools import deprecation
from mace.tools.scripts_utils import extract_config_mace_model
from mace.tools.torch_tools import restore... |
ce5d2b23fd496496772fada715a14763d273b3d391d66b2b04cbf8347927c0d5 | Python | 4,597 | 158 | # -*- coding: utf-8 -*-
#
#
# PyRates software framework for flexible implementation of neural
# network model_templates 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 Cogn... |
e6f1f5bdb387ed0c77ea550705cf133ae9c102529fda424a8e9d52801a01c8e3 | Python | 4,597 | 126 | # Copyright 2020-2024 Intel Corporation
# SPDX-License-Identifier: Apache-2.0
"""PyTorchDataLoader module."""
from openfl.federated.data.loader import DataLoader
class GaNDLFDataLoaderWrapper(DataLoader):
"""A class used to represent a data loader for the Generally Nuanced Deep
Learning Framework (GaNDLF).... |
ca48baae30bc733a191c9d57fb8ccc2fc31a62cd263a59c2846ac54e8d2bc7b4 | Python | 4,599 | 115 | """
Extract the annotations of Neo objects and structure them in a DataFrame
to complement a wave characterization.
"""
import argparse
import numpy as np
import pandas as pd
import quantities as pq
import re
from utils.io_utils import load_neo, save_plot
from utils.parse import none_or_str
from utils.neo_utils import... |
f469b937b14e8055a1d9fec7ebc8813cc871751f8e53db78246c90b399851a2a | Python | 4,599 | 98 | import pandas as pd
import os
from sklearn.preprocessing import MinMaxScaler
methyl_dir = "./preprocessing_methyl/"
acc_dir = "./preprocessing_acc/"
gene_dir = "./preprocessing_rna/"
resDir = './final_preprocessing/'
try :
os.mkdir(resDir)
except :
print('exist!')
dataTypeList = ['train', 'test']
for dataType in ... |
f187a5767575ec55e8e2c9fb70724bc621bfabc8a709ea5f0fae8edbb7495995 | Python | 4,602 | 177 | import os
import pickle
import sys
from typing import List
import psutil
def batch_iterator(iterator, batch_size):
if len(iterator) <= batch_size:
return [iterator]
output = []
i = 0
while (len(iterator) - i) > batch_size:
output.append(iterator[i : i + batch_size])
i += batc... |
1c68c33960115d6392a45d3d443f02ac2c2f452b3fb729c9c5090b044f8c925a | Python | 4,603 | 147 | import os
import rdkit
import rdkit.Chem as Chem
from tqdm import tqdm
from .chemutils import get_clique_mol, tree_decomp, get_mol, get_smiles, set_atommap, enum_assemble, decode_stereo
from .vocab import *
import argparse
class MolTreeNode(object):
def __init__(self, smiles, clique=[]):
self.smiles = s... |
b7e2134b782ec1176b8f1013f5a0dea07bf02b27e6a753d86378b8d61c543085 | Python | 4,606 | 119 | import torch
import numpy as np
from torch.utils.data import Dataset
class seqDS(Dataset):
"""
A Dataset class for phase coding working memory task
"""
def __init__(self,task_params,dataset_len=256):
"""
Initialise dataset object
Args:
task_params: dictionary of ... |
96cbe23bf1aa402c650a2eceb3137763c9408c2b8973917cf4d1e2ca15ad1b67 | Python | 4,608 | 148 | # 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 IPython import get_ipython
import os
# os.environ["CUDA_VISIBL... |
22c875944934fcbe724b8645e2c7972c7901bd12ef00fc4a4dfdf88aa1f2f4a1 | Python | 4,610 | 158 | # Copyright (C) 2020-2024 Intel Corporation
# SPDX-License-Identifier: Apache-2.0
"""Envoy CLI."""
import logging
import sys
from pathlib import Path
import click
from click import Path as ClickPath
from click import group, option, pass_context
from dynaconf import Validator
from openfl.experimental.workflow.compone... |
2e502006e07e2c3016138e5535e4e38ad034a5e83cd1b3d6c2eed26489f2f781 | Python | 4,613 | 102 | from PymoNNto.Exploration.Network_UI.TabBase import *
import random
class single_group_plot_tab(TabBase):
def __init__(self, variables=['output', 'excitation', 'inhibition'], colors=[(0, 0, 0), (0, 0, 255), (255, 0, 0), (155, 0, 155), (0, 155, 0), (155, 155, 0), (0, 155, 155)], net_lines=[], neuron_lines=[], titl... |
e41513b352e2066a21cae1ab75242020eff8aca4de54b981d650e5515686be6f | Python | 4,614 | 120 | # 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 math
import torch
import torch.nn.functional as F
from fairseq import metrics, utils
from fairseq.criterions import FairseqCriterion, ... |
6b26ed7fa8ba63f42a86e03bcff93fa10641a8676b6a3f0a607e99851d142160 | Python | 4,615 | 122 | from PymoNNto.Exploration.Network_UI.TabBase import *
class DrawItem(pg.GraphicsObject):
def __init__(self, parent=None):
super().__init__(parent)
self.picture = QtGui.QPicture()
def get_rnd_color(self):
return (np.random.rand()*255.0,np.random.rand()*255.0,np.random.rand()*255.0,255.... |
bf69b0b94a52fb5a3891b59f12f9d56e2f3e1b59fb976706ff80479439eb988b | Python | 4,616 | 152 | #!/usr/bin/env python3
import argparse
import numpy as np
import scipy.sparse as sp
import odil
def operator(ctx):
mod = ctx.mod
extra = ctx.extra
args = extra.args
res = []
# Value in cell (i, j) taken from face (i-0.5, j).
u_xm = ctx.field("ufx", 0, 0, loc="cc")
# Value in cell (i, ... |
8fa72ba3dd1d2c90a45cc40cc628bd164f47b71bd4b71141d16548b3a9342799 | Python | 4,617 | 137 | # Copyright 2020 Forschungszentrum Jülich GmbH and Aix-Marseille Université
# "Licensed to the Apache Software Foundation (ASF) under one or more contributor license agreements; and to You under the Apache License, Version 2.0. "
class CommunicationInternAbstract:
"""
Abstract class for internal communication... |
aa969480355d559574bced9f06b19eacf0b79e775df87d8dc23962917b5cb375 | Python | 4,618 | 115 | # Copyright 2020-2025 Intel Corporation
# SPDX-License-Identifier: Apache-2.0
import logging
from openfl.experimental.workflow.interface import FLSpec
from openfl.experimental.workflow.placement import aggregator, collaborator
log = logging.getLogger(__name__)
class TestFlowExclude(FLSpec):
"""
Testflow to ... |
0221dc390e792a356d6c24610ff97d93969457fcbf2fe01f7e7aea469a5cf4fd | Python | 4,619 | 121 | # Copyright 2025 Intel Corporation
# SPDX-License-Identifier: Apache-2.0
import hashlib
import pytest
from unittest.mock import MagicMock, patch
from openfl.federated.data.sources.azure_blob_data_source import AzureBlobDataSource
@pytest.fixture
def mocked_azure_blob_ds():
connection_string = "DefaultEndpointsPro... |
35778cb7811ee56eeda176661cc0327c4837ce2add896605b83c8c9166afc66a | Python | 4,623 | 137 | # ==============================================================================
# Copyright 2023 Technical University of Denmark
# Author: Nikolas Borrel-Jensen
#
# All Rights Reserved.
#
# Licensed under the MIT License.
# ==============================================================================
import collectio... |
85bcf0d5f04c76a9853adefac7524ec079908766b6ee408018634a9fd212cd15 | Python | 4,623 | 115 | import numpy as np
from hyperopt import hp
from odl.discr import uniform_discr
from dival.datasets.dataset import Dataset
from dival.evaluation import TaskTable
from dival.measure import L2, PSNR
from dival.reconstructors.regression_reconstructors import LinRegReconstructor
from dival.hyper_param_search import optimize... |
1243ddfcdf86396196c071889b2a673e9138e0e9136180e537aa18b7d8c70153 | Python | 4,628 | 141 | """The n-dimensional hyperbolic space.
Poincare half-space representation.
Lead author: Alice Le Brigant.
"""
import math
import geomstats.backend as gs
from geomstats.geometry._hyperbolic import HyperbolicDiffeo, _Hyperbolic
from geomstats.geometry.base import VectorSpaceOpenSet
from geomstats.geometry.euclidean i... |
1dd269f806c1328ebef574e09d8f711ae20ca29a18bdb380cf04adda772f8cb5 | Python | 4,629 | 143 | import numpy as np
from data import indicator_basis, ou_process
from utils import allclose_sign, allclose_trajs
import ivac
def make_data(ns, dt, nbins):
"""Generate featurized data for testing."""
return [indicator_basis(ou_process(n, dt), nbins) for n in ns]
def gram_schmidt(x):
"""Perform the Gram-S... |
73b096541add9367657dbeed081b706c6b4cdd2e70db09c671fc94bc4b5f4628 | Python | 4,634 | 156 | import numpy as np
import warnings
import re
from pathlib import Path
import sys
from .io_utils import load_neo
def get_base_type(datatype):
if hasattr(datatype, 'dtype'):
datatype = datatype.dtype
elif not type(datatype) == type:
datatype = type(datatype)
if datatype == list:
war... |
0b3009f4fc784e301271a0f36d4c6c684d77e9d842d48d2ab94b1754b8e6ea37 | Python | 4,635 | 103 | import config
import numpy as np
import pandas as pd
from assist. experiment_names_lookup import diffusion_paper_313_datasets, diffusion_paper_2021_datasets
names_to_table_isbi = {'UNet-202209-Brats313-256-geoaug-imaug-valid-lr5.0e-02': '\\checkmark & 0 &',
'UNet-202209-Brats313-synthetic_1GAN-2... |
68c11cceca5f33050a37c9d190383f7d5cd8fd8ca7e97c7e3999f105e5862f18 | Python | 4,635 | 138 | from __future__ import absolute_import
from functools import wraps
import numpy as np
from . import CI
from decorator import decorator
def mod2pi(f):
"""
Decorator to apply modulo 2*pi on the output of the function.
The decorated function must either return a tuple of numpy.ndarrays or a
numpy.ndarr... |
abb1b04dacd22b879dd85c4b527e9de38a560c96cd9723a96d1d9c8cea9034c9 | Python | 4,635 | 146 | """Meta data definition for model files"""
from __future__ import annotations
__all__ = ["ModelMetaData", "update_model_data", "check_valid_hash"]
from dataclasses import dataclass, field, asdict
import time
import copy
import pickle
import xxhash
import platform
from uuid import UUID
from typing import List, Tuple
... |
cd984babd09327861add4647d0070b0ddabdb5e5d961deb65b1fc7bd89aa13e6 | Python | 4,635 | 124 | import os
import cv2
import mediapipe as mp
import numpy as np
import pandas as pd
from tqdm import tqdm
mp_drawing = mp.solutions.drawing_utils
mp_drawing_styles = mp.solutions.drawing_styles
mp_hands = mp.solutions.hands
def collect_hand_keypoints_pipe(video_path: str, hand_query, output_path: str = None, thresho... |
1c0e5543ad5c66959aff88c290a2f751347d3e981637762a849566c78e0287c8 | Python | 4,638 | 146 | import os, sys
import numpy as np
import pandas as pd
import neo
sys.path.append('/home/georg/code/SSSort')
import sssio
import quantities as pq
import elephant as ele
def p2stars(p, ns=False):
""" turns a p-value into significance stars with the
classic alpha levels 0.05, 0.005, 0.0005 """
if ns:
... |
5e9dcf7ff7a9ac6672441cd4da99708179db6276b124d4e0ad79210ec4906213 | Python | 4,639 | 140 | # ==============================================================================
# Copyright 2025 Technical University of Denmark
# Author: Nikolas Borrel-Jensen
#
# All Rights Reserved.
#
# Licensed under the MIT License.
# ==============================================================================
import json
impo... |
6226d488de65c4d9a7b8c37cfdfb661fde36054c3b5d08668e005af0e5dff267 | Python | 4,639 | 104 | import os
import ops
os.environ["CUDA_DEVICE_ORDER"] = "PCI_BUS_ID"
os.environ["CUDA_VISIBLE_DEVICES"] = "0"
import glob
from configobj import ConfigObj
from models import att_unet_2d
from tqdm import tqdm
from losses import *
import scipy.io as sio
import matplotlib.pyplot as plt
import batch_utils
f... |
fbf2c295bffb25797b8e25d20039e16a3b3b82ae13620b9c35ad998ca05d2aa0 | Python | 4,639 | 152 | import experiment as exp
import asyncio
from canvas import Canvas
class TiledCanvas(Canvas):
def __init__(self, canvas_id, duration, logger, offset=[0, 0], on_disconnect=None):
super().__init__(canvas_id, on_disconnect=on_disconnect, logger=logger)
self.offset = offset
self.size = None
... |
058e9b58ebe7240efe7d75dcdd5bd19fcdc4073ff7c8731b1fc9ed43c9e3c76f | Python | 4,640 | 139 | import io
from pathlib import Path
from shutil import rmtree
import tarfile
import numpy as np
import pytest
def test_tar_writer():
from mlspm.data_generation import TarWriter
base_path = Path("./test_writer")
base_name = "test"
base_path.mkdir(exist_ok=True)
with TarWriter(base_path, base_nam... |
edbfce7e786bb1dc6c401b02dd0891efaff94342deb8b3d241447aae96180236 | Python | 4,641 | 116 | """
Extract the annotations of Neo objects and structure them in a DataFrame
to complement a wave characterization.
"""
import argparse
from pathlib import Path
import numpy as np
import pandas as pd
import quantities as pq
import re
from utils.io_utils import load_neo, save_plot
from utils.parse import none_or_path, ... |
97a9d7404ee396ead3076dcdd3f7b7578cefae98bacc58a48f7ddd66b410fc74 | Python | 4,643 | 120 | # 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 IPython import get_ipython
import os
# os.environ["CUDA_VISIBL... |
3e7203e9474be9dd1e0129bdd1716939365f230dbf96dd845623073642ec9273 | Python | 4,645 | 154 | import numpy as np
import pandas as pd
from skimage import io
import cv2 as cv
import matplotlib.pyplot as plt
import csv
import seaborn as sns
class microMSData():
def __init__(self, coords_file_paths, image_path_dicts):
self.coords_file_paths = coords_file_paths
self.image_path_dicts = image_path_dicts
se... |
6de4f4444fb6ed3cdaebb4f1281dba57158971951036e4f2e20805301aead73a | Python | 4,645 | 122 | """Tests for explicit mutation of per-spike analysis results."""
from typing import Any
import pandas as pd
from qtpy import QtWidgets
from sanpy.bAnalysisResults import analysisResultList, get_plot_result_definitions
from sanpy.bAnalysis_ import bAnalysis
from sanpy.interface.bScatterPlotWidget2 import bScatterPlot... |
64c26372838589c84ffa12845ddc0528e8aff8636d4a66b4808ba393ca0e6318 | Python | 4,647 | 134 | # 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... |
6747379df10f0395a274554cff156d9c1fecc1ff0e1cb5ef32c5b6f7260e0544 | Python | 4,652 | 147 | import argparse
import os
from typing import List
from dotenv import load_dotenv
from openai import OpenAI
from openai.types.chat import ChatCompletionMessageParam
import chromadb
def build_prompt(query: str, context: List[str]) -> List[ChatCompletionMessageParam]:
"""
Builds a prompt for the LLM. #
Thi... |
52141301efa31b8e6c42ac05f91202aec0ecba32ea9af8a0e019745ccc7785f9 | Python | 4,659 | 176 | """Autograd based linear algebra backend."""
import functools as _functools
import autograd.numpy as _np
import autograd.scipy as _scipy
from autograd.extend import defvjp as _defvjp
from autograd.extend import primitive as _primitive
from autograd.numpy.linalg import (
cholesky,
det,
eig,
eigh,
e... |
aaaa35f1ea3130a633a053ee6ff3cb0fbaf30e181d92c2e92f1c53d2a4dbf5c9 | Python | 4,659 | 116 | """
Extract the annotations of Neo objects and structure them in a DataFrame
to complement a wave characterization.
"""
import argparse
from pathlib import Path
import numpy as np
import pandas as pd
import quantities as pq
import re
from utils.io_utils import load_neo, save_plot
from utils.parse import none_or_path, ... |
f68aaaa67175e28b9efe96cc2695c2c34d616c971a39baa0c94f9fcb1b7fd4f7 | Python | 4,663 | 136 | import numpy as np
def initialize_w_rec(params):
"""
Initializes (full rank) recurrent weight matrix
Args:
params: python dictionary containing network parameters
Returns:
w_rec: recurrent weight matrix, numpy array of shape [n_rec, n_rec]
dale_mask: diagonal matrix indicatin... |
140b1d45d9357e7b63983f6edbd16ea4feaf1097e289e70277d314565eb40e5a | Python | 4,668 | 136 | from __future__ import annotations
import argparse
import logging
from pathlib import Path
from typing import Any
import pytest
from hypothesis import given
from hypothesis import strategies as st
from snakebids.plugins.pybidsdb import Pybidsdb
from snakebids.tests import strategies as sb_st
from snakebids.utils.uti... |
b713c37983ea61d2b52eb83888ce31b08bf21a65cf70cb89b493b349cdb1db83 | Python | 4,668 | 127 | #### 2D TRANSFER LEARNING ####
sim_tag = "rect2x2_transfer"
ids = [
("rect2x2_reference", "2mx2m reference"),
(
"rect2x2_freeze_BN_0_1_TN_0_batch_size_600_src_pos_3ppw_target_2D",
"2mx2m target (60% samples)",
),
]
sim_tag = "Lshape_2_5x2_5_transfer"
ids = [
("Lshape2_5x2_5_reference", ... |
0f5f936642760d7ccfc9c78609e46e10b6ae925ece326e74d3426b739f8516e5 | Python | 4,670 | 137 | import torch
import torch.nn as nn
import torch.nn.functional as F
class RelationGraphConvolution(nn.Module):
"""
Relation GCN layer.
"""
def __init__(self, in_features, out_features, edge_dim=3, aggregate='sum', dropout=0., use_relu=True, bias=False):
'''
:param in/out_features: sca... |
ac857aed491e025381fec890e7857b98855015a70ad7be61e8ae2693e4cbee0e | Python | 4,672 | 120 | """Tests for `_hyperalign`, the Procrustes template loop behind `align`.
Hyperalignment (Haxby et al., 2011) builds a common template, refines it over
`n_iter` rounds of align-and-average, then aligns every subject to the refined
template. `align(method='procrustes')` is the only caller.
"""
import numpy as np
import... |
ba2e1ffb12f4a1258822a9349a2acef0d1860735bdb73554a9e48f0ec3482a6e | Python | 4,672 | 110 | """The LAMMPS export goldens: the libtorch numbers and the ML-IAP interface."""
from __future__ import annotations
from pathlib import Path
from tests.golden import harness
from tests.golden.paths import REPO_ROOT
from tests.golden.targets import anchors as anchors_target
ORDER = 60
HELP = "the LAMMPS export golden... |
a1dcb1ab8990ff34fa4f03ff379b26fc950864c2df47b63ab831c112ba8a49b4 | Python | 4,673 | 117 | from PymoNNto import *
import scipy as sp
import matplotlib.pyplot as plt
#multi compartment version of
#https://hodgkin-huxley-tutorial.readthedocs.io/en/latest/_static/Hodgkin%20Huxley.html
#with a simplified version of the cable theory to connect compartments
class HH_main(Behavior):
def alpha_m(self, V):#Cha... |
4b30f0ed90a3a480921446dfe511ac79698901d1f40bbb11f1388658093b7d44 | Python | 4,677 | 112 | """Coordinate conversions: every pair round-trips, and junction is never confused with CDR3."""
from __future__ import annotations
import polars as pl
import pytest
from hypothesis import given
from hypothesis import strategies as st
from vdjdb.convert import coords
AA = st.text(alphabet="ACDEFGHIKLMNPQRSTVWY", min_... |
dd2432d3473bf02b348a02d00a52e11c5accbe8a1f656347dd18e3fce204e517 | Python | 4,677 | 130 | """Tests for ``bExport`` report headers."""
import csv
from pathlib import Path
import pandas as pd
import sanpy
from sanpy.bAnalysisResults import get_analysis_result_definitions
from sanpy.bExport import bExport
def test_summary_header_uses_file_metadata(test_data_dir: Path) -> None:
"""Report file metadata ... |
d072bb09474688725af4954881dd41868b695eb2d9084183bd687f8290bd977a | Python | 4,678 | 139 | # 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 logging
import random
from pathlib import Path
from typing import Dict, Optional, Tuple
import torch
import torch.nn as nn
logger = l... |
e58b0a8710257f9898393bee910c54cbb1d011d924d9767964355d2d1d9ed26e | Python | 4,678 | 88 | """Evidence integration preserves observational and missingness boundaries."""
import polars as pl
import pytest
from vdjdb.score.evidence import categorical, integrate
def test_categories_keep_unknown_separate_from_zero():
frame = pl.DataFrame({'a_studies': [None, 0, 1, 2, 9], 'iptm': [None, .2, .5, .8, 1.]})
... |
415e47a9c7c73a9ed292e3f78ca0da1c0a4daaa52be110aebe7ed9e29f716535 | Python | 4,685 | 121 | # 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... |
77e7d82d26f4fbf8ad20af53ffc684f4fec4cbd2929a06045b948f78c5b83fee | Python | 4,685 | 131 | from __future__ import annotations
from pathlib import Path
from snakebids.paths._config import get_bids_func
from snakebids.paths.specs import LATEST
def bids(
root: str | Path | None = None,
*,
datatype: str | None = None,
prefix: str | None = None,
suffix: str | None = None,
extension: st... |
9820a5d72a2d18b137436043e4d744c21b41016c8ab3c29cc82efa25303cea4a | Python | 4,688 | 140 | # Copyright 2020-2025 Intel Corporation
# SPDX-License-Identifier: Apache-2.0
import logging
import concurrent.futures
import time
import psutil
import subprocess # nosec B404
import tests.end_to_end.utils.defaults as defaults
import tests.end_to_end.utils.docker_helper as docker_helper
import tests.end_to_end.util... |
a5f4803ff6be91740ba17387a4f8159ff99c2a1b3a50b3bb7a9d1ca251895c4c | Python | 4,689 | 138 | import numpy as np
import torch
import torch.nn as nn
import torch.nn.functional as F
class RelationGraphConvolution(nn.Module):
"""
Relation GCN layer.
"""
def __init__(self, in_features, out_features, edge_dim=3, aggregate='sum', dropout=0., use_relu=True, bias=False):
'''
:param i... |
250246f500876564689a35ca4c34d6c16d4c39bc5129e14f4cbfecb8eb8550ac | Python | 4,690 | 124 | # Copyright 2020-2024 Intel Corporation
# SPDX-License-Identifier: Apache-2.0
"""Adagrad optimizer module."""
from typing import Dict, Optional
import numpy as np
from openfl.utilities.optimizers.numpy.base_optimizer import Optimizer
class NumPyAdagrad(Optimizer):
"""Adagrad optimizer implementation.
Im... |
346d4bacc5f3f629665a547faf745cbe2492bc8a32380e40979c26cc808eafc5 | Python | 4,691 | 127 | """Tests for nltools.algorithms.corrections — multiple comparison corrections."""
import nibabel as nib
import numpy as np
import pytest
from nltools.algorithms.corrections import fdr, holm_bonf, threshold, multi_threshold
class TestFDR:
"""Test false discovery rate correction."""
def test_fdr_basic(self):... |
65741ebabca3293820c6a0e52ef6d5abb2a39e5bfa195c889ee727b968220501 | Python | 4,694 | 137 | #
# For licensing see accompanying LICENSE file.
# Copyright (C) 2022 Apple Inc. All Rights Reserved.
#
import torch
from functools import partial
from utils import logger
from utils.ddp_utils import is_master
from utils.tensor_utils import image_size_from_opts
from .datasets import train_val_datasets, evaluation_da... |
039acfe8ebef4b45c8080d7c061548a4a66b55b20fac690224f488bdd64c6fc6 | Python | 4,702 | 125 | # Copyright 2020-2024 Intel Corporation
# SPDX-License-Identifier: Apache-2.0
"""Random grouped assigner module."""
import numpy as np
from openfl.component.assigner import Assigner
class RandomGroupedAssigner(Assigner):
r"""The task assigner maintains a list of tasks.
Also it decides the policy for whic... |
d9f4241c8eee014e460012c70f307e2918ecd628fa09579c24c10ca2a82b77c1 | Python | 4,702 | 107 | # 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 typing import Final, Callable, Optional, List
# NOTE: persistent modifiers are modifiers that fundamentally change the behavior of the model (same input will lead to different output... |
b234be3cdb5cebd1381fe04e6f588f1ebfefbf95626cf7484e1f5c44df917c14 | Python | 4,704 | 136 | from chromadb.api.types import EmbeddingFunction, Space, Embeddings, Documents
from chromadb.utils.embedding_functions.schemas import validate_config_schema
from chromadb.utils.embedding_functions.utils import decode_embedding
from typing import List, Dict, Any, Optional
import os
import numpy as np
import warnings
fro... |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.