sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
4e8a1ec484a5e933afe14b8bb8ada1cd62b9d67d7a1623858613bef4b4460c8a | Python | 1,622 | 54 | """Reinvent transfer learning
Train a given model with new data. The data comes from a file with SMILES
strings. The file is assumed to be in multi-column format separated by commas
(CSV) or spaces. The SMILES string is extracted from the first column.
The SMILES strings is expected to be a complete molecule.
"""
... |
a85da7c3d2141341498c2d3293ddb6e7ba5338d76e193cc641f6bf2aeb0231c3 | Python | 1,622 | 49 | import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
# ==========================================
# 1. LOAD DATA (updated re-run Phase-1 results)
# ==========================================
data = {
'Model': [
'YOLOv8-Nano', 'YOLOv10-Nano', 'YOLOv11-Nano', 'YOLOv12-Nano',
'D-F... |
d68dd98190a8307d683118d8f8d5b1301c115ed3905c02fa7ffc864af73ace0f | Python | 1,622 | 64 | from __future__ import annotations
from typing import TYPE_CHECKING, Literal, TypedDict, cast
from typing_extensions import TypeAlias
from snakebids.paths import specs
from snakebids.paths._factory import BidsFunction, bids_factory
if TYPE_CHECKING:
from snakebids.paths._utils import BidsPathSpec
# <AUTOUPDATE... |
4a8a0cbd0e6c748820a9c8d60ee04ecb1a37e5299ca9da108befa73dbf92b87e | Python | 1,623 | 38 |
import torch
import torchvision
class VGGPerceptualLoss(torch.nn.Module):
def __init__(self, resize=True):
super(VGGPerceptualLoss, self).__init__()
blocks = []
blocks.append(torchvision.models.vgg16(pretrained=True).features[:4].eval())
blocks.append(torchvision.models.vgg16(pretr... |
66c48ed52d944d729c20209e16621de9ae7c99a0c2f7c4261eb70d301cd53768 | Python | 1,624 | 62 | import random
import pytest
import geomstats.backend as gs
from geomstats.geometry.functions import HilbertSphere
from geomstats.test.parametrizers import DataBasedParametrizer
from geomstats.test_cases.geometry.manifold import ManifoldTestCase
from geomstats.test_cases.geometry.mixins import ProjectionTestCaseMixins... |
0bd0ed564ef92c9d8d207b9a34a855ec7754a32926e3c5c881eac81d1f46d98d | Python | 1,626 | 57 | import json
import flammkuchen as fl
from pathlib import Path
from split_dataset import Blocks
def loading_function(f):
f.loading_function = True
return f
class StackSaver(Blocks):
""""""
def __init__(
self, *args, destination=None, name="original", verbose=False, **kwargs
):
"... |
21b4181642752ff452a324cb72ef7e0e75ad10b06bbcaa3b6a889784338bf8cf | Python | 1,626 | 59 | import random
import pytest
import geomstats.backend as gs
from geomstats.geometry.euclidean import Euclidean
from geomstats.geometry.spd_matrices import (
SPDAffineMetric,
SPDLogEuclideanMetric,
SPDMatrices,
)
from geomstats.learning.incremental_frechet_mean import IncrementalFrechetMean
from geomstats.t... |
9d1c6e03287b2196234ac2783064328b2cd80a0b285f5ce29e41af081967bc65 | Python | 1,628 | 58 |
import numpy as np
from skimage.metrics import (
mean_squared_error,
structural_similarity,
peak_signal_noise_ratio)
from sparse_ct.data import create_circular_mask
class Reconstructor(object):
def __init__(self, name):
self.name = name
self.image_r = None
def eval(self, gt):
... |
930f810815c2e5415caca87c58e5c529fc1c05c11895f74310d0d1404b4892db | Python | 1,629 | 45 | from .set_transformer_modules import *
class SetTransformer(nn.Module):
def __init__(
self,
dim_input,
num_outputs,
dim_output,
num_inds=32,
dim_hidden=128,
num_heads=4,
ln=False,
num_sabs=2,
dropout=0.0,
):
super(SetTrans... |
947a8cb11d812ace2565369105969e5c2b3938ae73012c509a78c5a340ec1cbd | Python | 1,629 | 47 | from reinvent.scoring.compute_scores import compute_component_scores
from reinvent_plugins.components.RDKit.comp_physchem import Qed
def test_scorer_cache():
smilies = [
"CC(=O)Oc1ccccc1C(=O)O",
"O=S(=O)(c3ccc(n1nc(cc1c2ccc(cc2)C)C(F)(F)F)cc3)N",
"Cc1ccc(-c2cc(C(F)(F)F)nn2-c2ccc(S(N)(=O)=O... |
10b77be7db4d100489e9b1e73c502c56a54d8c6874f582f9c761edd0ee3a6620 | Python | 1,630 | 66 | """Sigmoid functions
FIXME: there is only a sign change for the two sigmoid functions
"""
__all__ = ["Sigmoid", "ReverseSigmoid"]
from dataclasses import dataclass
import numpy as np
from .transform import Transform
from .sigmoid_functions import hard_sigmoid, stable_sigmoid
@dataclass
class Parameters:
type:... |
4ff119dabefcf99c83839e9440a5156d6bc2b43b92a8bcec2aa6e30076b09f04 | Python | 1,631 | 59 | import random
import pytest
from geomstats.geometry.skew_symmetric_matrices import SkewSymmetricMatrices
from geomstats.test.parametrizers import DataBasedParametrizer
from geomstats.test_cases.geometry.matrices import MatricesMetricTestCase
from geomstats.test_cases.geometry.skew_symmetric_matrices import (
Skew... |
f535de744fe524d810d6ce4e384ccaa850819cc01df43c3fae4e195035bce3b2 | Python | 1,631 | 56 |
class Record(object):
__attributes__ = []
def __eq__(self, other):
return (
type(self) == type(other)
and all(
(getattr(self, _) == getattr(other, _))
for _ in self.__attributes__
)
)
def __ne__(self, other):
retu... |
fa47a27c5f04ffa681ebcb0d10c3802154f3b6546d261f97700c64751542864f | Python | 1,631 | 77 | import time
import numpy as np
from brian2 import (
StateMonitor,
SpikeMonitor,
defaultclock,
prefs,
NeuronGroup,
run,
Synapses,
plot,
ms,
mV,
float32,
)
import matplotlib.pyplot as plt
from globparams import *
defaultclock.dt = 1.0 * ms
prefs.core.default_float_dtype = floa... |
1df41559f31e5f7014adf0be79a4cd374faa2b8078035c539a98009bbf48824e | Python | 1,632 | 57 | # coding=utf-8
from typing import List, Tuple
import torch
import torch.utils.data as tud
from torch import Tensor
from torch.nn.utils.rnn import pad_sequence
from reinvent.models.linkinvent.model_vocabulary.model_vocabulary import ModelVocabulary
class Dataset(tud.Dataset):
"""Dataset that takes a list of SMIL... |
0a1af761529508e1455b4c499348e551a86e31d588fc721fb4d62a6c39cb33a6 | Python | 1,633 | 50 | """
Train LearnedPDReconstructor on 'lodopab'.
"""
import numpy as np
from dival import get_standard_dataset
from dival.measure import PSNR
from dival.reconstructors.learnedpd_reconstructor import LearnedPDReconstructor
from dival.reference_reconstructors import (
check_for_params, download_params, get_hyper_params... |
6fbba7781ce04c6ca9a81f14ee42d9e06df28dfe20f71066140e104649ba1de0 | Python | 1,633 | 50 | """
Train LearnedGDReconstructor on 'lodopab'.
"""
import numpy as np
from dival import get_standard_dataset
from dival.measure import PSNR
from dival.reconstructors.learnedgd_reconstructor import LearnedGDReconstructor
from dival.reference_reconstructors import (
check_for_params, download_params, get_hyper_params... |
7026b8cdc750f3f3b933a6d720533a351c0caee0d8c9d4cbddeb18ba82101e22 | Python | 1,633 | 41 | import torch
import os
from molx.dataset import Molecule3D
from molx.model import Deepergcn_dagnn_dist
from molx.mol3d import Mol3DTrainer, eval3d
conf = {}
conf['epochs'] = 100
conf['early_stopping'] = 200
conf['lr'] = 0.0001
conf['lr_decay_factor'] = 0.8
conf['lr_decay_step_size'] = 10
conf['dropout'] = 0
conf['weig... |
8b5728c6c63bc92f1f31219ac746e0495673028e33a59cba78d337650d3b1fe7 | Python | 1,633 | 50 | """
Train IRadonMapReconstructor on 'lodopab'.
"""
import numpy as np
from dival import get_standard_dataset
from dival.measure import PSNR
from dival.reconstructors.iradonmap_reconstructor import IRadonMapReconstructor
from dival.reference_reconstructors import (
check_for_params, download_params, get_hyper_params... |
c6c4196fb692b5c3b6a98b1196f4f95018393d00ea48c8343ed792ea80fe436f | Python | 1,633 | 50 | # This file is a part of the `nequip` package. Please see LICENSE and README at the root for information on using it.
from nequip.nn import SequentialGraphNetwork, AtomwiseReduce, ForceStressOutput
from nequip.nn.embedding import EdgeLengthNormalizer
from nequip.data import AtomicDataDict
from nequip.nn.pair_potential ... |
af7e779aa3bf4c1643063479c336bd679e52891d1a9d5cc994c742869d0b899c | Python | 1,634 | 55 | # -*- coding: utf-8 -*-
import os
import argparse
import logging
import glob
# 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", action = "sto... |
f98e078a26e6e53ca9e17c094ab92d57ebe24f00bcd2c68efc6e5b115b8d8604 | Python | 1,634 | 42 | import pytest
import geomstats.backend as gs
from geomstats.test_cases.geometry.base import LevelSetTestCase
from geomstats.test_cases.geometry.riemannian_metric import RiemannianMetricTestCase
from geomstats.test_cases.information_geometry.base import (
InformationManifoldMixinTestCase,
)
def fisher_rao_dist(po... |
3e64a987193d2cbc997bca45a28376799f0779280fc71c1f3a336898952b6039 | Python | 1,635 | 62 | """Tests for atlas loading from the HF dataset."""
import polars as pl
import pytest
from nltools.data.atlases import _Atlas, list_atlases, load_atlas
# All 11 atlases hosted at huggingface.co/datasets/nltools/niftis under atlases/.
EXPECTED_ATLASES = {
"aal",
"aicha",
"desikan_killiany",
"destrieux"... |
52be1128141d0587b110cd444b53ebd686d315f5a69adb55e77ed875421003e3 | Python | 1,636 | 53 | import os
from funcs import evaluate
import numpy as np
import glob
import nrrd
import argparse
if __name__ == "__main__":
parser = argparse.ArgumentParser()
parser.add_argument('--data_folder', type=str, required=True)
args = parser.parse_args()
folder = args.data_folder
f1_score_list = []
h... |
3a4c812eee26b0a3fb0053b097df782cc55fa06a22463c680231b521417d6ec2 | Python | 1,637 | 58 | """A simple plugin system for scoring components"""
__all__ = ["get_registry"]
import importlib
import pkgutil
import dataclasses
from typing import Tuple
import logging
from reinvent_plugins import components # FIXME: this is not the solution
if components.__file__ is not None: # this is not a namespace package
... |
98cf31454234cbdd98213a757d0c6f081c53881eae3ec72b8189083c980f4772 | Python | 1,639 | 81 | # Adapted from https://lukas-snoek.com/NI-edu/fMRI-introduction/week_3/neurodesign.html
import os
import matplotlib.pyplot as plt
import numpy as np
from rich import print
import neurodesign
# Neurodesigninternally parallelizes some computations using multithreading,
# which is a massive burden on the CPU. So let's... |
9b11ad77cebcd3cce7a6c7e337a28db024ca7e680abcfa0283ed9c46ee898ece | Python | 1,639 | 59 | from __future__ import absolute_import
import numpy as np
from numpy.testing import assert_allclose
from nose.tools import assert_equal, assert_true
import pycircstat
from pycircstat import event_series as es
def test_vector_strength_spectrum():
T = 3 # 2s
sampling_rate = 10000.
firing_rate = 10 # 10... |
26e176d300949ed93ffa4ae93aca0aef9edfce27bbe7d42051c401e356bebc49 | Python | 1,640 | 69 | import json
from pathlib import Path
import click
from tqdm import tqdm
@click.command()
@click.option(
"-d",
"--directory",
required=True,
type=click.Path(exists=True, file_okay=False, readable=True, path_type=Path),
)
@click.option(
"-s",
"--scores",
required=True,
type=click.Path(
... |
4d329acfab37407721387d5194606967ef7021f028a5a6c68e00977044624f69 | Python | 1,641 | 56 | #!/usr/bin/env python3
import argparse
import os
import matplotlib.pyplot as plt
import numpy as np
from odil import plotutil
def load_csv(path):
if path and os.path.isfile(path):
return np.genfromtxt(path, delimiter=",", names=True)
parser = argparse.ArgumentParser()
parser.add_argument("--odil", de... |
7c5d206ff4bb71bdc106a0aec001fe92d123b0644d05f4aebf2487e36bf6f33f | Python | 1,641 | 55 | """
Schema Registry for Embedding Functions
This module provides a registry of all available schemas for embedding functions.
It can be used to get information about available schemas and their versions.
"""
from typing import Dict, List, Set
import os
import json
from chromadb.utils.embedding_functions.schemas.schem... |
dd6c43b8e2d3b05290431abe4474d62eafa187b21c900091b223c86b51621395 | Python | 1,641 | 41 | import unittest
import pytest
import torch
from reinvent.models import LibinventTransformerAdapter, SampledSequencesDTO
from reinvent.models.transformer.libinvent.libinvent import LibinventModel
from reinvent.runmodes.utils.helpers import set_torch_device
from tests.test_data import ETHANE, HEXANE, PROPANE, BUTANE
fr... |
b4fade429240526f91c265db05c26d6f6a3145950ea9c1766dc1a75eff7a8786 | Python | 1,643 | 49 | import numpy as np
import warnings
from . import sensitivity
def optimize(sr_grid, init=None, eps=1e-4, max_iter=100000, verbose=False, expense_factor=1, basal_expense=0, expense=None):
n = sr_grid.shape[0] # TODO sjednotit uvodni cast kodu s cutting plane
if expense is None:
expense = sr_grid.d... |
e7706cda4df74447919988da0eee370e9f6af5087333f7179f5e65dbd5b67d23 | Python | 1,644 | 59 | """
Wrapper to load in a PDB file as a pyrosetta pose, relax it, and write back
out the relaxed pose as a PDB file.
"""
import os
import glob
import multiprocessing as mp
import logging
import argparse
import pyrosetta
from pyrosetta import rosetta
pyrosetta.init()
logging.basicConfig(level=logging.INFO)
def relax_... |
0f36bdc44fac590fc91c26faf9c3e7bb23a62ea647cec33903c6ce8807da3ddd | Python | 1,646 | 51 | import pytest
from geomstats.information_geometry.geometric import (
GeometricDistributions,
GeometricDistributionsRandomVariable,
GeometricMetric,
)
from geomstats.test.parametrizers import DataBasedParametrizer
from geomstats.test.random import RandomDataGenerator
from geomstats.test_cases.geometry.riema... |
a28d2a83a26fee31ca76ec3f7e272201e980d0f8047b1098821bd90d03915aaf | Python | 1,646 | 57 | """Some auxiliary functionality that does not fit anywhere else.
FIXME: may need to move some/all of these
"""
from __future__ import annotations
__all__ = ["disable_gradients", "set_torch_device"]
import logging
from typing import List, TYPE_CHECKING
import torch
if TYPE_CHECKING:
from reinvent.models import ... |
0ddca5191a44d64a712a1a73339defd3543e39db9e29d1dbcfeb6e9d7aeed64e | Python | 1,647 | 52 | import os
import pandas as pd
import matplotlib.pyplot as plt
#from Code.utils import plot_heatmap
import seaborn as sns
from matplotlib.colors import LinearSegmentedColormap
import numpy as np
def plot_heatmap(df,df_std, cmap='Reds'):
# Create an array to annotate the heatmap
labels = ["{0:.4f}\n$\pm$\n{1:.4f... |
9abcc28d32e17a38785786e8a0d7ae265b815f8c1972291b02ec16a23b105631 | Python | 1,647 | 49 | # 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.shortcuts import render
from django.http import HttpRespon... |
f53e462815aa6c39f1fb57d2faf9c539a8a5bf8019e44a3ec02dab1296993f5a | Python | 1,647 | 70 | from unittest.mock import MagicMock
import unittest
from sleepy.test.core import TestBase
from sleepy.gui.tagging.model.event import PointEvent
import numpy as np
import pdb
class EventTest(unittest.TestCase):
def getSettings():
settings = TestBase.getSettings()
settings.intervalMin... |
2af9dc1435222cc27e79776a2ed786a9a580825a9e3b5339be193439817b02a4 | Python | 1,649 | 48 | import geomstats.backend as gs
from geomstats.geometry.euclidean import Euclidean
from geomstats.geometry.hypersphere import Hypersphere
from geomstats.learning.agglomerative_hierarchical_clustering import (
AgglomerativeHierarchicalClustering,
)
from geomstats.test.data import TestData
class AgglomerativeHierarc... |
27155b96e957dfedac2dddb592d3f971156e87a9a597da26ef5dcd4e41f481c2 | Python | 1,658 | 50 | """
Calculate the time from the first to the last trigger in each wave.
"""
import numpy as np
import argparse
import pandas as pd
from utils.io_utils import load_neo, save_plot
from utils.parse import none_or_str
CLI = argparse.ArgumentParser()
CLI.add_argument("--data", nargs='?', type=str, required=True,
... |
62c790168712cbb99a631fd19f7a6562272daca4c3fbd191c2b77d4387075b7d | Python | 1,658 | 47 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Mon May 6 10:09:27 2019
@author: rubendries
"""
import igraph as ig
import leidenalg as la
import pandas as pd
import networkx as nx
def python_leiden(df, partition_type, initial_membership=None, weights=None, n_iterations=2, seed=None, resolution_parame... |
95ad1029515342eac72638b397d30eaa4b041cb9e98883e75c9dc537970ff043 | Python | 1,658 | 32 |
import sys, json, argparse, torch
import torchvision.transforms as T
from PIL import Image
ap = argparse.ArgumentParser()
ap.add_argument('--root'); ap.add_argument('--config'); ap.add_argument('--ckpt')
ap.add_argument('--items'); ap.add_argument('--out'); ap.add_argument('--min_score', type=float, default=0.001)
ap.... |
2ea1b37fa62bae64d07c9dcb54d332150664d27891874ceb4692d48403c11eb5 | Python | 1,659 | 42 | import unittest
from rdkit import Chem
from reinvent.chemistry.library_design import bond_maker, attachment_points
from reinvent.chemistry.library_design.reaction_filters import ReactionFiltersEnum
from tests.chemistry.fixtures.test_data import (
REACTION_SUZUKI,
SCAFFOLD_TO_DECORATE,
TWO_DECORATIONS_SUZU... |
5c97bc6fa0fd3cf87bad7e70f8879fc51a89a3c6e76dfaf461f929538dabc30a | Python | 1,660 | 48 | """Tests for CPU parallelization functionality and correctness."""
import pytest
import numpy as np
from nltools.algorithms import one_sample_permutation_test
def _one_sample_at(n_jobs):
data = np.random.RandomState(0).randn(20, 5)
return one_sample_permutation_test(
data, n_permute=60, return_null=... |
587aaa9e73a1e7b7bdaec8b2488e1f64f465a7f9b8df239aa34ead76fcb609d9 | Python | 1,662 | 60 | import os
import re
import numpy as np
def get_subject_files(dataset, files, sid):
"""Get a list of files storing each subject data."""
# Pattern of the subject files from different datasets
if "mass" in dataset:
reg_exp = f".*-00{str(sid+1).zfill(2)} PSG.npz"
# reg_exp = "SS3_00{}\.npz$... |
6485ab5ff71fef37607c57fca2542167552ff1bc88a8e25c0a4ae8119f028eab | Python | 1,662 | 44 |
import numpy as np
# define the FI curve function. for either excitatory neurons and inhibitory neurons.
def current_to_frequency(input_current,population_type,p):
# input_current is all the current to target neuron.
# population_type is either 'E' for excitatory neurons or 'I' for inhibitory neurons.
# ... |
1fa4af7eb5274e2f72b83e7dcf407476993a7252b5167aecf5e3453693382fe3 | Python | 1,663 | 61 | """Test suit for saving PyRates objects to or loading them from file."""
__author__ = "Daniel Rose"
__status__ = "Development"
import filecmp
import os
import pathlib
import pytest
def setup_module():
print("\n")
print("=======================")
print("| Test Suite File I/O |")
print("=============... |
45ba6be7ef7a6caf181c7a04d421c37a8241aabd7a4fda14d374a0f72ef45627 | Python | 1,663 | 31 | import pandas as pd, matplotlib.pyplot as plt, seaborn as sns, matplotlib as mpl
mpl.rcParams['pdf.fonttype'] = 42
# ALL 12 numbers clean (warmup+median). D-Fine FP32 (FP16 unstable); its ~7ms preprocess
# uses an unoptimized PIL path so its end-to-end is conservative. D-Fine A100>T4 is real:
# the model is too small ... |
1abd32a83896eedf0a7c43844ea509229dc9d31535458c3a5b8e89cd0a360482 | Python | 1,665 | 39 |
# -*- 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 Cognitiv... |
811a3ce9928d12a6ec21e1ccdd7238052bc15311a99799bc440c8092e2397e09 | Python | 1,665 | 45 | import math
import torch
from torch import nn as tnn
class AttentionLayer(tnn.Module):
def __init__(self, num_dimensions: int):
super(AttentionLayer, self).__init__()
self.num_dimensions = num_dimensions
self._attention_linear = tnn.Sequential(
tnn.Linear(self.num_dimensions... |
3ce6b0c53a6e0e1f3b079920f3685b35bf83d9268b64d3facc284f1547419aed | Python | 1,667 | 52 | """
This code calculates the efficiencies for different values of P_ext (xc)
from the simulation results
Change the constant ADJUST_REST to True to make the resting cost
independent of the coupling strength (group).
"""
import numpy as np
import matplotlib.pyplot as plt
import pickle
from tqdm import tqdm
import warn... |
7732d8b758799c55a2c4c093dc7f86585eee03a4f8c8c28c7a40f41ca4774a8b | Python | 1,668 | 50 | from __future__ import print_function, division, absolute_import
import torch.nn as nn
import torchvision.models as tm
from efficientnet_pytorch import EfficientNet
import timm
# Defining a class named 'Brainmodels' for model management
class Brainmodels:
def __init__(self, models_name, num_classes, resume_model):... |
46db794517bee3125e653eaf69a145118a0dfb17f83b677d53448168504d93e8 | Python | 1,669 | 54 | """
Similarity and Distance
=======================
This tutorial illustrates how to calculate similarity and distance between images.
"""
#########################################################################
# Load Data
# ---------
#
# First, let's load the pain data for this example.
from nltools.datasets i... |
6490ed01278106c371c24700826752e66c681a08901379e3660ed7e19cc1d167 | Python | 1,670 | 66 | import platform
import time
import numpy as np
import matplotlib.pyplot as plt
from globparams import *
from brian2 import *
import brian2cuda
set_device("cuda_standalone", clean=True)
defaultclock.dt = 1 * ms
prefs.core.default_float_dtype = float32
if platform.node() == 'saeed-Swift-SF315-51G':
prefs.devices.cu... |
8fa43b6398c0d3cb2128a5e08cae9d636cd86a1468aaf8338e5cd4a4307a70b6 | Python | 1,670 | 50 | """
Calculate the time from the first to the last trigger in each wave.
"""
import numpy as np
import argparse
import pandas as pd
from utils.io_utils import load_neo, save_plot
from utils.parse import none_or_str
CLI = argparse.ArgumentParser()
CLI.add_argument("--data", nargs='?', type=str, required=True,
... |
3b7c8e93190a4a5840249cc8d6ff73884411921febad2ec0e6d4a748f3743a7c | Python | 1,671 | 42 | # Copyright 2020-2024 Intel Corporation
# SPDX-License-Identifier: Apache-2.0
"""Custom GaNDLF DataLoader module."""
from openfl.federated.data.loader_gandlf import GaNDLFDataLoaderWrapper
class GaNDLFDataLoader(GaNDLFDataLoaderWrapper):
"""A custom data loader for the Generally Nuanced Deep Learning Framework ... |
95b9384e945ca7e15aa09eac318866fdba8241c8dc03b66f7baf890869074ca1 | Python | 1,671 | 69 | import random
import pytest
import geomstats.backend as gs
from geomstats.geometry.euclidean import Euclidean
from geomstats.geometry.hypersphere import Hypersphere
from geomstats.geometry.spd_matrices import SPDMatrices
from geomstats.learning.mds import MDS
from geomstats.metric_geometry.bhv_space import TreeSpace
... |
c83c7179c33d409bb3f3da914c6dae6510a536bb1a5d9a813a2cc9dbf483ad80 | Python | 1,673 | 54 | import setuptools
from dig.version import __version__
with open("README.md", "r") as fh:
long_description = fh.read()
setup_requires = ['pytest-runner']
tests_require = ['pytest', 'pytest-cov', 'mock']
setuptools.setup(
name="dive_into_graphs",
version=__version__,
author="DIVE Lab@TAMU",
author... |
f69a78306717bb2df6558e00f05edeeabec2209616a404b40c32911975eb86cc | Python | 1,673 | 40 |
# -*- 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 Cognitiv... |
c2762b896245cafd807470741a51704ff6e947758f1f1d48455e03969b86c3fb | Python | 1,677 | 51 | from pathlib import Path
import click
from nnunetpaper.data import read_json
@click.command()
@click.argument("file", type=click.Path(readable=True, path_type=Path))
@click.option("-m", "--metric-name", required=False, default=None)
@click.option("-v", "--value", required=False, default=None)
def main(file: Path, m... |
34b16ce2515a26e86b53f5c4404143ba67589ff133678fd628087088e3b77218 | Python | 1,678 | 63 | import inspect
import asyncio
from typing import Any, Callable, Coroutine, TypeVar
from typing_extensions import ParamSpec
P = ParamSpec("P")
R = TypeVar("R")
def async_to_sync(func: Callable[P, Coroutine[Any, Any, R]]) -> Callable[P, R]:
"""A function decorator that converts an async function to a sync functio... |
def65aec7c0adfadb0ad4eb36eba422da64bc4c615bb14c8735dcef997d06cee | Python | 1,678 | 52 | import geomstats.backend as gs
from geomstats.test.data import TestData
from ...test_geometry.data.base import VectorSpaceOpenSetTestData
from ...test_geometry.data.riemannian_metric import RiemannianMetricTestData
from .base import InformationManifoldMixinTestData
class DirichletDistributionsTestData(
Informati... |
fc2657c4b4b303be9c8c373cfaf63f4eeccfe50e2867e82e4e397d9183517231 | Python | 1,678 | 56 | import logging
import warnings
from importlib_metadata import version
from sklearn.exceptions import ConvergenceWarning
warnings.simplefilter('ignore', category=ConvergenceWarning)
warnings.simplefilter('ignore', category=DeprecationWarning)
DEFAULT_IP = 'localhost'
DEFAULT_PORT = 6000
def start_live2p(params_dict, ... |
1e9969d2ddcff4ffbffbf1875a511fe29f22ecbc517841538fa3e201c1003663 | Python | 1,681 | 49 | """`_Glm` must fit and compute contrasts without emitting warnings.
The estimator no longer builds a `FirstLevelModel` or a masker, so nilearn's
mask-generation `RuntimeWarning` and its deprecated-accessor `FutureWarning`
have no path into nltools. `run_glm` itself is quiet at `verbose=0`.
"""
import warnings
import... |
998c581fa5d6e62fc1ccf8b4f86df16ff9ec1cc7ab379edef6900fe0f94614b6 | Python | 1,682 | 49 | from time import time
class JSExperiment:
def __init__(
self,
experiment_description,
experiment_name,
experiment_parameters,
experiment_model):
self.description = experiment_description
self.name = experiment_name
self.paramet... |
366005b5ad7767a02e45a169db1878438f1bf45478dbd7241c0e99f633cd832c | Python | 1,683 | 57 | import argparse
import importlib
import os
import tensorflow as tf
from train import train
def run(db, gpu, from_fold, to_fold, suffix='', random_seed=42):
# Set GPU visible to Tensorflow
os.environ["CUDA_VISIBLE_DEVICES"] = str(gpu)
# Config file
config_file = os.path.join('config', f'{db}.py')
... |
61a8365f910ca90e9778fd1af0b82d1198452b1a48dd8997d26d98a171296fc8 | Python | 1,684 | 58 | """Plot an Agglomerative Hierarchical Clustering on the sphere."""
import logging
import os
import matplotlib.pyplot as plt
import geomstats.backend as gs
import geomstats.visualization as visualization
from geomstats.geometry.hypersphere import Hypersphere
from geomstats.learning.agglomerative_hierarchical_clusteri... |
8e5fefd984903d93c2e407ffa9919f5ca3e59dffeafa0a8838a65c047161e2b1 | Python | 1,685 | 50 | """
Check whether the input data representation adheres to the stage's requirements.
Additionally prints a short summary of the data attributes.
"""
import numpy as np
import argparse
import quantities as pq
from utils.io_utils import load_neo
from snakemake.logging import logger
CLI = argparse.ArgumentParser()
CLI.... |
557aec7a7623df85e64747832a47c11a30419652081995fc11b2ae3decd69849 | Python | 1,686 | 91 | import sys
sys.path.append('../../')
from PymoNNto.NetworkCore.Network import *
from PymoNNto.NetworkCore.Synapse_Group import *
from NetworkBehavior.EulerEquationModules.Equation import *
from matplotlib.pyplot import *
from PymoNNto.NetworkBehavior.Structure.Structure import *
from Examples_Paper.Eqation.Experimenta... |
f014d3a3fd0ea67b0250529276051aba735eb716240ddf38f4f1cb3481d9fbea | Python | 1,686 | 60 | #!/usr/bin/env python3
__description__ = \
"""
Test the use of the * format. It sends a random list of longs (without a pre-
specified length of the list) and then receives it (again, without a specified
list length).
"""
__author__ = "Michael J. Harms"
__date__ = "2016-06-08"
__usage__ = "./duplex.py serial_device (l... |
325dfa0db096ed0b0aad3d5cdacf59cc748ef712c98b3d21762ca7933f97620f | Python | 1,687 | 37 | import os
from PIL import Image
from tqdm import tqdm
from typing import List, Callable
class ImageDatasetTransformer:
def __init__(self, name: str, transform: Callable[[Image.Image], Image.Image], n_samples: int = 1):
self.name = name
self.transform = transform
self.n_samples = n_samples... |
8212bdc435ddaf81ca8e8f6a018f973ebf15dd438fd5082b1b335f133b8f57c8 | Python | 1,687 | 60 | """Use RDKit's filter catalogs to filter for unwanted structures"""
__all__ = ["UnwantedSubstructures"]
import sys
from dataclasses import dataclass
from typing import List
import logging
import numpy as np
from rdkit import Chem
from rdkit.Chem.FilterCatalog import FilterCatalog, FilterCatalogParams
from ..compone... |
c2d049d4f01b54b02609898d5da0d012c3692a7d6e74cfd5f35e0c2b6dbec356 | Python | 1,688 | 78 | # This file is a part of the `nequip` package. Please see LICENSE and README at the root for information on using it.
from ._key_registry import (
register_fields,
deregister_fields,
_register_field_prefix,
get_field_type,
_NODE_FIELDS,
_EDGE_FIELDS,
_GRAPH_FIELDS,
_LONG_FIELDS,
_CAR... |
d9cc2dd9e244052c83a6b0e24807ed977de394409cf9dd6507c624ed43e6a29c | Python | 1,688 | 34 | from .torchvision_wrapper import create_torchvision_dataset_wrapper
from .spoken_mnist import SpokenMNIST
from .davis import Davis
from .alov300 import ALOV300
from .nat_images import NatImages
from .collate import time_aware_collate
from .dataloader import DataLoader
CIFAR10 = create_torchvision_dataset_wrapper("CI... |
e846916944076d8342e93e9fa81583a484405ab578db6ac2dca5b167cce95e8c | Python | 1,688 | 53 | import experiment as exp
from canvas import Canvas
class CanvasNoiseExperiment(exp.Experiment):
default_params = {
"canvas_id": "1",
"fill": "red",
"duration": 20,
"max_noise": 10,
"background": "black",
}
async def run_block(self):
self.canvas = Canvas(exp... |
1bdf34abaf9f13d1ca98f309679b37e0c878cbdfa86a21d1394d22f740d8b324 | Python | 1,690 | 39 | from PymoNNto.Exploration.Network_UI.TabBase import *
class spiketrain_tab(TabBase):
def __init__(self, parameter, title='Spiketrain', timesteps=1000):
super().__init__(title)
self.parameter=parameter
self.timesteps=timesteps
def add_recorder_variables(self, neuron_group, Network_UI):... |
cbfd79ff6217b0f15da597dba0aaae2d8ed1ed9e5c6afe57c5cb3fb37e4ae309 | Python | 1,690 | 61 | import numpy as np
from scipy.optimize import minimize
def skew_sym_regress(X, X_dot, tol=1e-4):
"""
Original data tensor is C x L x N where N is number of Neurons, L is length of each trial
and C is number of conditions. We stack this to get L*C x N array.
Args
----
X_dot: First difference of (reduced... |
2ed6a3f4fb11697fc178dd7596d54425b76bd6f64aa1a41de03a6998b90b5701 | Python | 1,691 | 50 | """
Check whether the input data representation adheres to the stage's requirements.
Additionally prints a short summary of the data attributes.
"""
import numpy as np
import argparse
import quantities as pq
from utils.io_utils import load_neo
from snakemake.logging import logger
CLI = argparse.ArgumentParser()
CLI.... |
5c110cd09642866d5bab525dcbdc8c69b2b69d5eed0db71b8960645cf4ece27f | Python | 1,691 | 44 | import pytest
import unittest
import numpy
import torch
from reinvent.models import meta_data
from reinvent.models.reinvent.models.model import Model
from reinvent.models.reinvent.models.vocabulary import SMILESTokenizer, Vocabulary
from reinvent.runmodes.utils.helpers import set_torch_device
from tests.test_data imp... |
d971d7e9e556aa39e4f1ae1337a4b88b1ecd6c8137294f0baa1f46f771578b41 | Python | 1,691 | 67 | import sys
import numpy
from collections import defaultdict
contigs = []
genes = {}
introns = {}
confs = {}
strands = {}
with open(sys.argv[1], "r") as f:
previous_end = 0
previous_strand = -1
previous_contig = ""
for line in f:
if line.startswith("#"):
previous_end = 0
previous_strand = 0
if not line.st... |
c339796cd1f5106f1cd882273e988bf0255cd8872b8dc8876f9230e05197a255 | Python | 1,692 | 53 | import pytest
from geomstats.information_geometry.gamma import (
GammaDistributions,
GammaDistributionsRandomVariable,
NaturalToStandardDiffeo,
)
from geomstats.test.parametrizers import DataBasedParametrizer
from geomstats.test.random import GammaRandomDataGenerator, RandomDataGenerator
from geomstats.tes... |
313fd5f31d70bb3f94befa5eed78d0921b7144c71fab0c83fe006895fdb022f9 | Python | 1,696 | 88 | import numpy as _np
from geomstats._backend._dtype_utils import _pre_allow_complex_dtype
_DTYPES = {
_np.dtype("int32"): 0,
_np.dtype("int64"): 1,
_np.dtype("float32"): 2,
_np.dtype("float64"): 3,
_np.dtype("complex64"): 4,
_np.dtype("complex128"): 5,
}
_COMPLEX_DTYPES = [
_np.complex64,
... |
3c785912020fc27c400e2d6c4e556f3211b50c9b2db9bf528d70b69c9382893a | Python | 1,696 | 66 | # Copyright (C) 2020-2025 Intel Corporation
# SPDX-License-Identifier: Apache-2.0
from copy import deepcopy
import random
from Crypto.PublicKey import ECC
import torch
import torchvision
# Download Train and Test datasets
mnist_train = torchvision.datasets.MNIST(
"../files/",
train=True,
download=True,
... |
0554a5552ce4c23b74d7eac15cd6cd6ff266dd30c0e88f825f0202a141e9a950 | Python | 1,699 | 49 | #!/usr/bin/env python
"""
CLI for wandb sweeps.
"""
import wandb
import os
from deeperwin.configuration import Configuration, set_with_flattened_key
from ruamel.yaml import YAML
from deeperwin.process_molecule import process_molecule
import re
def _get_current_run_nr():
directories = "\n".join([d for d in os.list... |
81e1edb258dce9afab7488606d92c4d18eccdbcdaf604f5d328b200d3cdc4541 | Python | 1,700 | 47 | import wandb
import argparse
import pandas as pd
from tqdm import tqdm
def main(source_wandb_project_name, reserved_run_ids_file_name, top_k):
# Read the text file with the ids
with open(reserved_run_ids_file_name+'.txt') as f:
ids = f.readlines()
# Strip newline characters and conver... |
9a676d9c81e4a9f4bdb09683f26f8804c1a2da713241d5789f0b95bac823f501 | Python | 1,702 | 66 | # Copyright (C) 2020-2025 Intel Corporation
# SPDX-License-Identifier: Apache-2.0
from copy import deepcopy
import random
from Crypto.PublicKey import ECC
import torch
import torchvision
# Download Train and Test datasets
mnist_train = torchvision.datasets.MNIST(
"../files/",
train=True,
download=True,
... |
f32882301bcd668072378c61d444c14065dec5f5747de8e0b1ce44e435e6f14c | Python | 1,702 | 60 | from argparse import ArgumentParser
import torch
from mace.tools.scripts_utils import remove_pt_head
def main():
parser = ArgumentParser()
grp = parser.add_mutually_exclusive_group()
grp.add_argument(
"--head_name",
"-n",
help="name of the head to extract",
default=None,
... |
bcda74076dffd89f70929443224f1349f07a0617d06549c283bf6f9e2e624dfe | Python | 1,704 | 56 | import random
import pytest
from geomstats.geometry.euclidean import Euclidean
from geomstats.geometry.hyperboloid import Hyperboloid
from geomstats.geometry.hypersphere import Hypersphere
from geomstats.geometry.spd_matrices import (
SPDAffineMetric,
SPDLogEuclideanMetric,
SPDMatrices,
)
from geomstats.l... |
c38e571e710dbd4c7d2ddf60e9f1148d469048dddf193d4ecb110f06c2b873ba | Python | 1,704 | 55 | import os.path as osp
import pickle
from tqdm import tqdm
from rdkit import Chem
from multiprocessing import Pool
def check_mol(mol_dir):
cid = mol_dir.split('/')[-1]
file_path = osp.join(mol_dir, cid+'.mol')
if osp.exists(file_path):
try:
mol = Chem.MolFromMolFile(file_path, removeHs=... |
48dec0308222b44f6849b8c12655974f69c470c6b7ccbab5b40ffa7331de10ed | Python | 1,705 | 49 | import numpy as np
import scipy.spatial
from deeperwin.utils.utils import get_distance_matrix
BOHR_IN_ANGSTROM = 0.529177249
def distort_molecule(R, n, d_min_factor, d_max_factor, noise_scale):
R_out = []
n_atoms = len(R)
if n_atoms == 2:
center = (R[0] + R[1]) / 2
diff_vec = (R[1] - R[0... |
fe46a93bd5d77f65fe98e748e62871b9d4b071cc0ef84034455f59afca93cc9e | Python | 1,705 | 58 | #!/usr/bin/env python
"""The setup script."""
from setuptools import setup, find_packages
with open("README.rst") as readme_file:
readme = readme_file.read()
with open("HISTORY.rst") as history_file:
history = history_file.read()
requirements = []
with open("requirements.txt") as f:
for line in f:
... |
0534fd8c3f72c29d6b19ab5ef110a3796f8a620c3d76b9a64e431ce2b70bab3a | Python | 1,706 | 74 | # The data used for testing was obtained from the repository https://github.com/brain-networks/edge-ts. [no license]
import dynfc as dyn
from numpy import pi, load, hstack
def test_phDiff1():
assert round(dyn.phDiff(pi, pi),1) == 1
def test_phDiff2():
assert round(dyn.phDiff(pi, pi/2), 1) == 0
def test_phDi... |
d610661eeb0e08ac5ec8fa3109433bc6ed1e3053c54d0452172d31e3cc3bfe9d | Python | 1,708 | 39 | # -*- 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... |
e39ae0275d6381907cb51235115ed9191a927e6c1553fafa09ed44c4a7ee1818 | Python | 1,708 | 88 | import autograd.numpy as _np
from geomstats._backend._dtype_utils import _pre_allow_complex_dtype
_DTYPES = {
_np.dtype("int32"): 0,
_np.dtype("int64"): 1,
_np.dtype("float32"): 2,
_np.dtype("float64"): 3,
_np.dtype("complex64"): 4,
_np.dtype("complex128"): 5,
}
_COMPLEX_DTYPES = [
_np.co... |
2ea62ac819421df0d2d530eefdc4b89e22d642d0333eccdb89be86d096aa5cfe | Python | 1,709 | 52 | """Load an example ABF recording and plot one voltage sweep."""
from pathlib import Path
import matplotlib.pyplot as plt
import sanpy
def main() -> None:
"""Load an ABF file, print its basic properties, and plot one sweep.
Raises:
RuntimeError: If SanPy cannot load the recording.
"""
# Loc... |
36bec4d9333fdfe01ee75e1a2926981beb492379bfb91fa58f7341831f845518 | Python | 1,709 | 49 | #
# 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_norm_fn
@register_norm_fn(name="group_norm")
class GroupNorm(nn.GroupNorm):
"""
Applies a `Group Normalization <https... |
30be181705ae26925da7e144145d3267cc0b5711c937390e10c262a458f186cd | Python | 1,711 | 46 | """Common interface to hyperbolic spaces.
Lead author: Thomas Gerald.
"""
import geomstats.errors as errors
from geomstats.geometry._hyperbolic import HyperbolicDiffeo # noqa
from geomstats.geometry.hyperboloid import Hyperboloid
from geomstats.geometry.poincare_ball import PoincareBall
from geomstats.geometry.poinc... |
7f530414057a2a2809348ae072598144a045070867d244b7f03541e572e8db81 | Python | 1,711 | 49 | from pathlib import Path
from idtrackerai import ListOfBlobs, ListOfFragments, Session
from idtrackerai.utils import wrap_entrypoint
def populate_groundtruths(blobs: ListOfBlobs, fragments: ListOfFragments):
"""Sets the groundtruth identity of every fragment from the final identities of
its blobs. Crossings ... |
9d7f8f7d5dab7fb0b5fed1d7a5c856c2fcf324660440cfdf8ff319741ffc12ed | Python | 1,711 | 51 | """
Check whether the input data representation adheres to the stage's requirements.
Additionally prints a short summary of the data attributes.
"""
import numpy as np
import argparse
from pathlib import Path
import quantities as pq
from utils.io_utils import load_neo
from snakemake.logging import logger
CLI = argpa... |
7cb52f80e28a93a7564bda32e3166aa0bc7dd2a897f5bebf1300c99489176de8 | Python | 1,712 | 53 | from sklearn.ensemble import RandomForestClassifier
from matplotlib.backends.backend_pdf import PdfPages
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
data = pd.read_csv("Feature_3102.csv", sep='\t')
feature = data.iloc[:, 5:-1]
label = data.iloc[:,-1]
rfc = RandomForestClassifier(random_sta... |
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