sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
eb0f87b1a4d5f45a77b25b25fd963d3312e11999ac5cd319521c3507786b79c9 | Python | 2,140 | 61 | from PymoNNto.Exploration.Network_UI.TabBase import *
class event_tab(TabBase):
def __init__(self, title='Events'):
super().__init__(title)
def initialize(self, Network_UI):
self.event_tab = Network_UI.add_tab(title=self.title)
self.plot = Network_UI.tab.add_plot(title='Events', x_l... |
90d608f4f84fad1b941c14077da873e638cc8ff2fe3ee5879d926551430e94bb | Python | 2,142 | 57 | import torch.nn.functional as F
import torch
class gru(torch.nn.Module):
def __init__(self, classes, arch=[41, 3, 6, 23, 0.07643942323789713]):
super(gru, self).__init__()
self.input_size = 1
self.num_layers = 3
self.bidirectional = True
self.arch = arch
self.arch =... |
a2f8d0c3bbbf521b73cb76e9a28a1aa7dbbed9c559a5b4cf351d519f0e72db34 | Python | 2,144 | 48 | from PymoNNto.Exploration.Network_UI.TabBase import *
class buffer_tab(TabBase):
def __init__(self, title='Buffer'):
super().__init__(title)
def add_recorder_variables(self, neuron_group, Network_UI):
return
def initialize(self, Network_UI):
self.buffer_tab = Network_UI.Next_Tab(... |
f8d26c166b6da56a0230cdbc714b684ce36f37bab4cea42e6fabdae9e3c8d731 | Python | 2,144 | 74 | import sys
from PyQt5 import QtWidgets, QtGui
import matplotlib
import matplotlib.figure
from matplotlib.backends.backend_qt4agg import FigureCanvasQTAgg as FigureCanvas
from matplotlib.backends.backend_qt4agg import NavigationToolbar2QT as NavigationToolbar
class PrettyWidget(QtWidgets.QWidget):
def __init__(sel... |
0b143735a91b4455ce8139d5fefc512d00e66583bc857a6c73bd40e45e68cc0f | Python | 2,146 | 59 | from PymoNNto.Exploration.Evolution.Devices.Evolution_Device import *
from multiprocessing import Process, Pipe
#import subprocess
#import time
#import os
import numpy as np
import sys
import traceback
def local_thread_worker(slave_file, evo_name, static_genome, conn):
#try:
# import psutil as psu
# ... |
97a1a64a9686295c8b78053cef0d44757e57496fa283b7b418e844833e0d047e | Python | 2,147 | 81 | # Copyright 2020-2024 Intel Corporation
# SPDX-License-Identifier: Apache-2.0
"""DataLoader module."""
class DataLoader:
"""A base class used to represent a Federated Learning Data Loader.
This class should be inherited by any data loader class specific to a
machine learning framework.
Attributes:... |
78883acbf74b7dd0fa43368db08f419a1c2bf2d5f030026106612cf3db8be300 | Python | 2,148 | 64 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Wed Dec 12 15:25:17 2018
@author: ngritti
"""
from deeprest.rawDataClass import rawData
from deeprest.modelClass import modelRest
from deeprest.timeLapseClass import sampleTimeLapse
import time, glob, os, shutil
from tifffile import imread, imsave
from skim... |
6acecfbb69590646a8825f4c6a4c6ffa2cbdc780e87ae5b28c4d8da8d3e30857 | Python | 2,150 | 61 | import numpy as np
from SALib.sample import saltelli
import numpy as np
from SALib.analyze import sobol
from matplotlib import pyplot as plt
print("Def SA problem")
problemDef = {
'num_vars': 5,
'names': ['k_iAno1', 'k_iNSCC', 'k_iCa50', 'k_iSK', 'k_eIP3'],
'bounds': [[0.28873, 0.34498],
[0... |
aa910abddd82ff3fed63622ac5d0707703d7fa5974fe776d9a0a7215fcf41b8f | Python | 2,153 | 92 | from .. import logger
class Buffer():
"""
Class representing the stream's buffer.
This is not a Python Buffer Interface compatible class.
Parameters
----------
bufsize : int
Buffer's size [samples].
winsize : int
To extract the latest winsize samples from the buffer [sampl... |
eab8694d578106367d4707de747daa9a6ded7036e41184ffa30c5deb801b07e4 | Python | 2,155 | 68 | # An implementation of https://en.wikipedia.org/wiki/Rendezvous_hashing
from typing import Callable, List, Tuple
import mmh3
import heapq
Hasher = Callable[[str, str], int]
Member = str
Members = List[str]
Key = str
def assign(
key: Key, members: Members, hasher: Hasher, replication: int
) -> List[Member]:
"... |
35f4b83b541005d10a286bb6159a20635986310e2dae168a8f536dad62758518 | Python | 2,157 | 62 | # 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... |
299a855fb58b132876c02b7cefb8975d582e22957ea451f521c41935a4b7efae | Python | 2,158 | 72 | from PymoNNto.NetworkCore.Neuron_Group import *
from PymoNNto.NetworkCore.Behavior import *
import numpy as np
class Synaptic_Normalization(Behavior):
def initialize(self, neurons):
self.syn_type = self.parameter('syn_type', 'GLU', neurons)
self.clip_max = self.parameter('clip_max', None, neurons)... |
8f63438d58b22b3bb5dd18c6eb54507ff3c904d512eec174ec93f512ef4cbd16 | Python | 2,158 | 65 | # 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... |
9dca013b3873d709ec9685c0a87173c745c3a8198e44270a0ff43c80fdbf221d | Python | 2,159 | 61 | from PymoNNto.Exploration.Network_UI.TabBase import *
from PymoNNto.NetworkCore.Base_Attachable_Modules import *
from PymoNNto.Exploration.StorageManager.StorageManager import *
from PymoNNto.Exploration.Network_UI.Basic_Tabs.info_tabs import *
from PymoNNto.Exploration.HelperFunctions.Save_Load import *
import copy
im... |
722c38a93b1c88d0503cbee531a32311162fe6329e9eaf6a0e5dfb03db95a0e8 | Python | 2,160 | 74 | import random
import pytest
from geomstats.geometry.hyperboloid import Hyperboloid
from geomstats.geometry.minkowski import Minkowski
from geomstats.test.parametrizers import DataBasedParametrizer
from geomstats.test_cases.geometry.base import LevelSetTestCase
from geomstats.test_cases.geometry.riemannian_metric impo... |
fc7b92dbc34963144af91f17d611970686a8be5fabef6eca726285a3cd361241 | Python | 2,160 | 66 | from PyQt5 import QtCore, QtWidgets
from PyQt5.QtCore import QModelIndex
from PyQt5.QtGui import QStandardItemModel
from PyQt5.QtWidgets import QApplication, QTableView
class CheckBoxDelegate(QtWidgets.QItemDelegate):
"""
A delegate that places a fully functioning QCheckBox cell of the column to which it's app... |
e9e36e068d1cd713087fe63cb77ee6fca8663f38fcabc1530a86f856fdf1d2be | Python | 2,161 | 67 | from typing import Optional
import torch
from torch import Tensor
class History(torch.nn.Module):
r"""A historical embedding storage module."""
def __init__(self, num_embeddings: int, embedding_dim: int, device=None):
super().__init__()
self.num_embeddings = num_embeddings
self.embed... |
6f99914679ecc066a92adc581f4b76182e091fd12234597ad70b4d3c9e567e9e | Python | 2,162 | 48 |
import sys
import argparse
import torch
from hyper_dti.settings.config import get_configs
from hyper_dti.trainer import DtiPredictor, CrossValidator
if __name__ == "__main__":
parser = argparse.ArgumentParser(description='Drug-target interaction prediction')
config = get_configs(parser)
log = False if ... |
ad8290ee41ccbb9f9dfb05da5f696248860c8d18d9ec23957d1e4c23a397e2a4 | Python | 2,162 | 68 | from PyQt5 import QtCore, QtWidgets
from PyQt5.QtCore import QModelIndex
from PyQt5.QtGui import QStandardItemModel
from PyQt5.QtWidgets import QApplication, QTableView
class CheckBoxDelegate(QtWidgets.QItemDelegate):
"""
A delegate that places a fully functioning QCheckBox cell of the column to which it's app... |
a25231c48404a0b054786fac5fa630656932d3ef59c70573084e30e1f30b5743 | Python | 2,163 | 77 | #!/usr/bin/env python3
from copy import deepcopy
import numpy as np
import odil
cases = ["pack", "arrays"]
def test(case, dim):
cshape = (1 + np.array(range(dim))) * 2
dimnames = ["x", "y", "z", "w"][:dim]
domain = odil.Domain(cshape=cshape, dimnames=dimnames, multigrid=1, mg_convert_all=False)
s... |
ba064d4cc75ee58b9cb618614a8a57ca4a5414df94fc2f698a5d23ca8241bca4 | Python | 2,163 | 85 | """A simple bucket counter
Increments the count for a bucket when an item is added. Can test if the bucket
is full.
"""
from __future__ import annotations
all = ["BucketCounter"]
from collections import Counter
from typing import TYPE_CHECKING
if TYPE_CHECKING:
from collections.abc import Hashable
class Buck... |
dfd3fc3f4febbb9718de69eab88d53cccc372cffe338ee1f7aea0fdf1c24bf9f | Python | 2,163 | 66 | import sys
sys.path.append('../../../TREN2')
sys.path.append('../../../tren2')
from PymoNNto.Exploration.StorageManager.StorageManager import *
smg = StorageManagerGroup('SORN_Gram_train_time_100k')# SORN_One_layer_all_600
x=[]
y=[]
for ms_i, sm in enumerate(smg.StorageManagerList):
try:
network = sm.lo... |
1d32bcf233d0dc523e5afa5792edc0014e3fea5356080366228b6bacef891654 | Python | 2,164 | 65 | import sys
import numpy as np
import umap
import csv
from scipy.sparse import coo_array
def load_spike_times(spikingFile):
""" Load spike times from the file specified
by the variable spikingFile """
preEI = list()
with open(spikingFile, newline='') as csvfile:
spikeTimes = csv.reader(csvfile,... |
6d0a1d582588547f461c2ad2875facb60af3be7c1697b3b46b00863ff9b380ef | Python | 2,164 | 68 | """
Visualize the wave detection by means of clustering the detected trigger
in (time,x,y) space.
"""
import numpy as np
import quantities as pq
import argparse
from pathlib import Path
import matplotlib.pyplot as plt
from matplotlib.colors import ListedColormap
import seaborn as sns
import random
import warnings
from... |
18ccbed4c2af339035facbf8ddc477a91383df0b0466345c34cf876d440cf6f4 | Python | 2,167 | 69 | import geomstats.backend as gs
from geomstats.geometry.euclidean import Euclidean
from geomstats.geometry.spd_matrices import (
SPDAffineMetric,
SPDEuclideanMetric,
SPDMatrices,
)
from geomstats.learning.geometric_median import GeometricMedian
from geomstats.test.data import TestData
from ._base import Bas... |
592eedf7bf2d0caccc775e35f1d7fd1c82a8f0b9eece17d32051c9cd2eb1e00d | Python | 2,167 | 61 | import csv
import matplotlib.pyplot as plt
import numpy as np
def _decode_train_csv(csv_path):
epochs = []
train_loss = []
val_loss = []
dice = []
with open(csv_path) as csv_file:
csv_reader = csv.DictReader(csv_file)
for row in csv_reader:
epochs.append(row['step'... |
b141bd8c40715b05c3b6f994dc4c9ed0cbe3add1ff52452ec6aef77295b6907e | Python | 2,167 | 66 | import os
import copy
import numpy as np
from cloudfiles import CloudFiles
from corgie import layers
from corgie import exceptions
from corgie.log import logger as corgie_logger
from corgie.data_backends.base import DataBackendBase, BaseLayerBackend, \
register_backend, str_to_backend
@register_backend("js... |
8f78c3c008818ea529507f1a1c2f4842f74e8bc39898db9b8ec33766c4cb7b5a | Python | 2,169 | 72 | import json
from pathlib import Path
import click
import pandas as pd
def read_json(file: Path) -> pd.DataFrame:
with file.open('r') as f:
d: dict = json.load(f)
transformed_dict = {
"metric": [],
"metric_name": [],
"class": [],
}
for k in d.keys():
for c in ... |
456cf9739635a1b0340a1578bfda0d7276f8ab0b504a636992c57d051c914f8f | Python | 2,170 | 57 | import pytest
import geomstats.backend as gs
from geomstats.test_cases.geometry.base import VectorSpaceTestCase
from geomstats.test_cases.geometry.mixins import GroupExpTestCaseMixins
from geomstats.test_cases.geometry.riemannian_metric import RiemannianMetricTestCase
class EuclideanTestCase(GroupExpTestCaseMixins, ... |
b5bc0f08cdc421264202bfc0b0885fe1ec5637bba92d7f22b6c81b04489522c2 | Python | 2,170 | 51 | import numpy as np
import h5py
import networkx as nx
import pandas as pd
import scipy.sparse as sps
import os
df_instances = pd.read_csv('instances_list.csv')
instances_list = df_instances.instances.tolist()
df_classify = df_instances
for i in range(len(df_instances)):
ins = df_instances.loc[i,'instan... |
8172d7df9ff3b8a45c23bdcb7a2a81160a214d8e86a1d5f540a24b46dedc94a7 | Python | 2,172 | 63 | import argparse
import importlib
import logging
from .start_live2p import start_live2p, DEFAULT_IP, DEFAULT_PORT
def make_args():
parser = argparse.ArgumentParser()
# add arguments here
# turns on all debugging, incl websocket package
parser.add_argument('-d', '--debug',
d... |
2a76190d9f1638c3296051c21c22215314357a14b3a3ce4f138df198202c920b | Python | 2,173 | 71 | import os
import sys
import platform
import subprocess
import pandas as pd
from tqdm import tqdm
def get_simulation_time(byte_out):
str_out = byte_out.decode("utf-8")
result = [
line for line in str_out.split("\n") if line.startswith("simulation time:")
]
return result
def get_number(line, s... |
377531ffbc200b4357fb56b2b357c20e50c129a6fbc40d15b4d439c2d0ce19c8 | Python | 2,173 | 62 | import math
import pytest
import geomstats.algebra_utils as utils
import geomstats.backend as gs
from geomstats.geometry.hypersphere import Hypersphere
from geomstats.test.test_case import TestCase
class AlgebraUtilsTestCase(TestCase):
@pytest.mark.random
def test_taylor_functions_even_exp(self, taylor_func... |
ad92beed844d72d28f6e69d0cdf6f1882fa33d80d5f9e02713f539d5814968e0 | Python | 2,173 | 59 | # Copyright 2025 Intel Corporation
# SPDX-License-Identifier: Apache-2.0
from abc import abstractmethod
import numpy as np
import torch
from openfl.federated.data.sources.verifiable_dataset_info import (
VerifiableDatasetInfo,
)
class VerifiableMapStyleDataset(torch.utils.data.Dataset):
"""Base class for d... |
b0d22c79bd54df28f7f9eb803af54364855e40a914f123257003bfb911a97702 | Python | 2,174 | 70 | #-------------------------------------------
# Data
#-------------------------------------------
DATA_PATH = ''
EPOCH = [0.5, 3.5]
#-------------------------------------------
# Trigger
#-------------------------------------------
TRIGGER_FILE = ''
TRIGGER_DEF = ['LEFT_GO', 'RIGHT_GO']
LOAD_EVENTS = {'selected':'Fals... |
483c20a02cadc7ce0df5120a0eae686a0f807f81780006b98b5d1556f2df9bfe | Python | 2,175 | 65 | from typing import Dict, List, Optional
import logging
from rdkit.Chem.rdmolfiles import MolToSmiles
from reinvent.chemistry import conversions
from reinvent.chemistry.standardization.filter_configuration import FilterConfiguration
from reinvent.chemistry.standardization.filter_registry import FilterRegistry
logger... |
b0b34b34cf7c8c18e384571f50cbc1e95439104099b92893daed820ea8511515 | Python | 2,178 | 60 | """Module that defines useful metrics to monitor a model."""
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import tensorflow as tf
from sleeprnn.common import constants
def confusion_matrix(logits, labels, masks=None):
"""Returns TP, FP and FN"""
... |
c8722189d7f12d5928217a8e23886a17fc8e9ea983251381e188fe8b9d6a76e9 | Python | 2,180 | 74 | from __future__ import absolute_import
import numpy as np
from numpy.testing import assert_allclose
from nose.tools import assert_equal, assert_true, raises
import pycircstat as circ
test_data_2d = np.array([
[0.58429, 0.88333],
[1.14892, 2.22854],
[2.87128, 3.06369],
[1.07677, 1.49836],
[2.9696... |
9a3b027e6302507bcc39dda32ca1953125da0cec64347133d648cfc644d3f019 | Python | 2,184 | 68 | import pytest
import geomstats.backend as gs
from geomstats.test_cases.learning._base import BaseEstimatorTestCase
class TangentPCATestCase(BaseEstimatorTestCase):
@pytest.mark.random
def test_fit_inverse_transform(self, n_samples, atol):
X = expected = self.data_generator.random_point(n_samples)
... |
e62d87573ad575218c61bf72dc616d66082cbb1fab102bbacdcf75648c224ae3 | Python | 2,185 | 63 | """
--------------------------------------------------------------------------------
Date: 09/12/2021
@author: Nikolaos Vardalakis
--------------------------------------------------------------------------------
Implementation Notes
--------------------------------------------------------------------------------
... |
0d906e4ddd57589e2d013cf985ec0512a6d9c2dd98c9ddc8414ba2a464b5df16 | Python | 2,186 | 70 | # Copyright 2020-2025 Intel Corporation
# SPDX-License-Identifier: Apache-2.0
import pytest
import logging
import os
from tests.end_to_end.utils.tr_common_fixtures import (
fx_federation_tr,
)
from tests.end_to_end.utils import federation_helper as fed_helper
import json
import tests.end_to_end.utils.defaults as... |
8c6b345492c59aece901f015325ad8eed6e4b36f2487c0619f6e8b8b251a4a44 | Python | 2,186 | 68 | # Copyright (C) 2020-2021 Intel Corporation
# SPDX-License-Identifier: Apache-2.0
"""You may copy this file as the starting point of your own model."""
from openfl.federated import KerasDataLoader
from src.mnist_utils import load_mnist_shard
class KerasMNISTInMemory(KerasDataLoader):
"""Data Loader for MNIST Da... |
260d56c4cbf5360e80f3f9e533899c8c55586cc5f9d4fb1abda9c6da602bf2fe | Python | 2,187 | 84 | from __future__ import annotations
__all__ = [
"set_seed",
"extract_sections",
"write_json_config",
"get_tokens_from_vocabulary",
]
import os
import random
import logging
import numpy as np
import torch
from reinvent.utils import config_parse
logger = logging.getLogger(__name__)
def set_seed(seed:... |
74c8e361622294e0963af80e5de788d8a9b43013626ff68ac5f5ccd0ee308cf1 | Python | 2,187 | 56 | #!/usr/bin/env python
import h5py
import numpy as np
import pickle
import argparse
if __name__ == '__main__':
parser = argparse.ArgumentParser()
parser.add_argument("--basis-set", type=str, default="STO-6G")
parser.add_argument("--output", type=str, default="", help="Path of output file; defaults to same n... |
5efdeb82fed9f2a1a7e4e9a5ec7f166cc0c128a317dbb29d9146d1956a9a32bb | Python | 2,188 | 65 | from PymoNNto import *
class Basic_Behavior(Behavior):
def initialize(self, neurons):
neurons.voltage = neurons.vector()
self.threshold = 0.5
self.leak_factor = self.parameter('leak_factor', 0.9, neurons)
def iteration(self, neurons):
neurons.spike = neurons.voltage > self.thr... |
f301e118a875b082ec8af8438e308fd74cbc8ba364a2b50684f81996d5a64b9b | Python | 2,188 | 57 | """Every calculator entry point must run the model at the model's dtype.
Extensions create tensors mid-forward without an explicit dtype and follow the
process-wide default. When that disagrees with the model, the mismatch survives
the forward through type promotion and only fails in the backward, as a dtype
error out... |
08fdaa3f98883904e142b128c08a24e202d0dad0f77f5dad9cc1ae238c8ca39a | Python | 2,189 | 60 | # 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 appli... |
b70b2403f1fb228fed92a572a67e508f51b8f91004460beb04fc332b34a71324 | Python | 2,189 | 53 | # Copyright 2020-2024 Intel Corporation
# SPDX-License-Identifier: Apache-2.0
"""Federated averaging module."""
import numpy as np
from openfl.interface.aggregation_functions.core import AggregationFunction
def weighted_average(tensors, weights):
"""Compute average."""
return np.average(tensors, weights=w... |
b696a2e64af8676f6ee7f080d60d7d572b6eb588ac47267894874cc228bd396b | Python | 2,190 | 75 | #!/usr/bin/env python
import os
import sys
import matplotlib.pyplot as plt
import nibabel as nib
import nilearn.image as nimage
import numpy as np
import pandas as pd
import seaborn as sns
import scipy.linalg as la
from glob import glob
from budapestcode.utils import compute_tsnr
from budapestcode.viz import make_mo... |
5907369d05f09e87eb70197f42812c860599a5fb75d5aa254a51ddc44041a2b9 | Python | 2,191 | 76 | from django.contrib import admin
from celsus.models import Project, File, Comparison, CellType, Author, Collaborator, ExperimentType, TissueType, \
Keyword, Disease, Instrument, Organism, OrganismPart, Curtain, QuantificationMethod, DifferentialAnalysisData
# Register your models here.
@admin.register(Project)
c... |
65018a14b01b2609e894006b4fc13891f3507adde6d4879d813fc289fc6b3b9a | Python | 2,191 | 54 | from PymoNNto.Exploration.Network_UI.TabBase import *
class afferent_syn_attr_plot_tab(TabBase):
def __init__(self, syn_vars, title='Aff Syn',timesteps=500):
super().__init__(title)
self.syn_vars=syn_vars
self.timesteps=timesteps
def add_recorder_variables(self, neuron_group, Network... |
31428f1724a22e391d6443dd815026952a5b91d67f6835fd830aeda7b5c4253a | Python | 2,193 | 65 | import json
import pandas as pd
import argparse
from pathlib import Path
def parse_df(df):
"""Given CSV from neuroglancer export, extract and clean points"""
c1 = "Coordinate 1"
coord_cols = ["x0", "y0", "z0"]
exported = c1 in df.columns
if exported:
df[["x0", "y0", "z0"]] = (
... |
319a88d3f95fd3a49a4cf7d7a8b2b90d6d587572a36cd718d6454659dfcdf965 | Python | 2,197 | 67 | from dgl.nn.pytorch import GATConv
import torch
import torch.nn as nn
import torch.nn.functional as F
class GATLayer(nn.Module):
def __init__(self, g, in_dim, out_dim):
super(GATLayer, self).__init__()
self.g = g
self.fc = nn.Linear(in_dim, out_dim, bias=False)
self.attn_fc = nn.Li... |
b013cddaf119288f6baf38a98fed5ac003b6c53ce3a91b60dea3b4a89b6b455a | Python | 2,197 | 74 | import cv2
import os
import fastdeploy as fd
def parse_arguments():
import argparse
import ast
parser = argparse.ArgumentParser()
parser.add_argument(
"--model_dir", required=True, help="Path of PaddleDetection model.")
parser.add_argument(
"--image_file", type=str, required=True,... |
30a9976b5a244df72a68eadce5df3a90e6597574997df7755fd886fd1e6e0324 | Python | 2,199 | 75 | from __future__ import annotations
from typing import Iterator, List
import importlib_resources as impr
import more_itertools as itx
from typing_extensions import NotRequired, TypeAlias, TypedDict
from snakebids.io.yaml import get_yaml_io
from snakebids.paths import resources
__all__ = ["BidsPathEntitySpec", "BidsP... |
5849bcb8b743b04bf32b809b6f5946ef005b7bce8150922550064768d9d9f1ea | Python | 2,200 | 67 | """Convert BIDS events tables into design-matrix regressors."""
from __future__ import annotations
from typing import TYPE_CHECKING
import numpy as np
import polars as pl
if TYPE_CHECKING:
import pandas as pd
def events_to_dm(
events: pl.DataFrame | pd.DataFrame,
*,
run_length: int,
sampling_f... |
a0da2ca6213f2c36dcaae9e434116751a894b6e1d735d34c0937982b69501e5b | Python | 2,201 | 51 | ###########################################################################################
# Slurm environment setup for distributed training.
# This code is refactored from rsarm's contribution at:
# https://github.com/Lumi-supercomputer/lumi-reframe-tests/blob/main/checks/apps/deeplearning/pytorch/src/pt_distr_env.p... |
e9268bb484b28bff28eda4f32f7decab6548da1799c46241144c10a142532f22 | Python | 2,201 | 50 | import logging
import os
import subprocess
import jax
from jax.lib import xla_bridge
def disable_slave_loggers(logger):
if jax.process_index() > 0:
logger.debug(f"DeepErwin: Disabling logging for process {jax.process_index()}")
logging.disable()
def configure_hardware(
config,
) -> None:
... |
c7ca092f11899f1f1d8e4d6bb116d3fd6c79a0e2626176416d08c4736ac3fc9c | Python | 2,204 | 71 | import experiment as exp
import video_system as vid
import numpy as np
class ObserverTest(exp.Experiment):
"""
A simple experiment to test ImageObservers
"""
default_params = {
"obs_ids": None,
}
def run(self):
obs_ids = exp.get_params()["obs_ids"]
if obs_ids is None:... |
d608210aa5d7bded4be756cf79dc598e6b073ded4a9a44e8d59444ac2f251977 | Python | 2,205 | 87 | from pathlib import Path
import os
from utils import (
timing,
save_projection_axes,
store_features,
store_on_off_features
)
def parse_args():
import argparse
parser = argparse.ArgumentParser(
description='...'
)
parser.add_argument(
'-1',
'--data',
... |
049ad00a499df4057abf40df19991f660e675bacbaa638dcf94a3374d81ee2dd | Python | 2,206 | 56 | # This file is a part of the `nequip` package. Please see LICENSE and README at the root for information on using it.
import lightning
from lightning.pytorch.callbacks import Callback
from lightning.pytorch.loggers.wandb import WandbLogger
from nequip.train import NequIPLightningModule
class WandbWatch(Callback):
... |
d52b8bab6faf3c781ecc5a3a9ee18ca983ebcbceb04e91d50ed983349dfb9d0d | Python | 2,207 | 57 | """Tests for RL intrinsic penalty functions: Sigmoid, Tanh, Linear, Erf, Step."""
import pytest
from reinvent.runmodes.RL.memories.bucket_counter import BucketCounter
from reinvent.runmodes.RL.intrinsic_penalty.penalties import (
SigmoidPenalty,
TanhPenalty,
LinearPenalty,
ErfPenalty,
StepPenalty,... |
a31cfa02ba3c8fe921cb88fe63ac824eefb438cd41a7501b159cab9e690d821d | Python | 2,210 | 58 | import json
from pathlib import Path
import pandas as pd
def read_json(files: list[Path]) -> pd.DataFrame:
transformed_dict = {
"metric": [],
"metric_name": [],
"center": [],
"anatomy": [],
"segment_volume": [],
"image_volume": [],
"time": [],
"pt_i... |
f1effb8aad27aaf83d7e5dc7f5a84c3f38da2e73d2fb075f8ae4b62eddb335cf | Python | 2,212 | 68 | """Plot the result of a KNN classification 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.knn import KNearestNeighborsClassifier
... |
57bad63592a33f40514a0c163de383336bd83b301c2cb401473c6e4aaf6e3f9b | Python | 2,213 | 89 | import gzip
import json
import os
def _convert_ext(filepath, compress):
b, e = os.path.splitext(filepath)
filepath = b + '.json'
if compress:
filepath += '.gz'
return filepath
def _check_ext(filepath):
compress = False
b, e = os.path.splitext(filepath)
if e == '.gz':
comp... |
82d1a475959f4e747d7494a8f6a013f20bf88817ef8a75c823ee1ee073b67cbe | Python | 2,213 | 70 | import pytest
from geomstats.information_geometry.beta import BetaDistributions
from geomstats.information_geometry.exponential import ExponentialDistributions
from geomstats.information_geometry.fisher_rao_metric import FisherRaoMetric
from geomstats.information_geometry.gamma import GammaDistributions
from geomstats... |
519573452d2b814098f3eb0a5700a052258634aeb05743b202014a76b58a556f | Python | 2,214 | 59 | # 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 torch import nn
from fairseq.models import FairseqEncoder
from fairseq.models.transformer import Linear
class CTCDecoder(... |
8dce59e57ca729a88a25d2227a114fd0b95fb2bb705e6bd1780cdaf13eda9636 | Python | 2,214 | 102 | import analysis_utils as au
import torch
import seaborn as sns
import matplotlib
import torch.nn as nn
class Layer1(nn.Module):
def __init__(
self,
w_1, w_2,
):
super().__init__()
self.w_1 = nn.Parameter(torch.tensor([[w_1]]))
self.w_2 = nn.Parameter(torch.tensor([[w... |
0bb5c85abbdc77dd539024cd98c1bffa01f10b0e6298100e55e0c46cd835ede6 | Python | 2,216 | 51 | """
Filter between a highpass and a lowpass frequency using a butterworth filter.
"""
import argparse
import quantities as pq
import os
from elephant.signal_processing import butter
from utils.io_utils import load_neo, write_neo
from utils.parse import none_or_float
CLI = argparse.ArgumentParser()
CLI.add_argument("-... |
52eac8b8f00633868a68136d2a2c2dd54560d7649f4ca10748deb21f8cedb6a6 | Python | 2,221 | 79 | from bindsnet.network import Network
from bindsnet.pipeline import EnvironmentPipeline
from bindsnet.learning import MSTDP
from bindsnet.encoding import bernoulli
from bindsnet.network.topology import Connection
from bindsnet.environment import GymEnvironment
from bindsnet.network.nodes import Input, LIFNodes
from bind... |
5f382be61b3729b40aa4e34b0f7464653d6f44cf16d0b1590a259156b480ca44 | Python | 2,221 | 74 | """Code to calculate mel spectrograms."""
import math
import librosa
import numpy as np
import scipy.signal
def calculate_mel_spectrogram(
audio_path,
target_fs=64,
fmin=0,
fmax=5000,
nb_filters=10,
hop_length=None,
win_length=None,
):
"""Calculates mel spectrogram of a raw speech file... |
d174ee65eb3696ca10aff792c30bbcd0dae2549312ebef9e2383a794d77f40e1 | Python | 2,221 | 58 | import os
from typing import Tuple
from Bio.PDB import MMCIFParser
from model_angelo.utils.fasta_utils import read_fasta
import pandas as pd
_search_result_names = ["fasta_chain_id", "db_chain_id", "seq_sim", "chain_len"]
def calculate_cif_similarities(
pdb_id: str,
chain_sims: pd.DataFrame,
... |
0bcd7cc932a296c6b6cf66cbb5d0b763783c7dd76abb37af35fe98de1bcf8c3e | Python | 2,225 | 68 | import logging
import cv2
import numpy as np
from idtrackerai import Blob, Session
def compute_erosion_disk(blobs_in_video: list[list[Blob]]) -> int:
"""Estimates the erosion kernel size as the median, over all frames, of the
thickness (maximum distance transform) of the thinnest individual blob."""
min... |
f8a895e4c91106847c1723b8a708a9647ccfd55d610ad31752ddf1974a5a2fca | Python | 2,225 | 75 | import glob
import h5py
import os
import sys
import numpy as np
def add_target(graph_path, target_name, target_list, sep=' '):
"""Add a target to all the graphs contains in hdf5 files
Args:
graph_path (str, list(str)): either a directory containing all the hdf5 files,
... |
7609c3c4c2904e98861497d4d2443fd71400b3e5cd302533e6a33a7220d77f7c | Python | 2,228 | 54 | # This file is a part of the `nequip` package. Please see LICENSE and README at the root for information on using it.
import importlib
import zipfile
from typing import List, Final, Set
NEQUIP_AOTI_INPUTS_KEY: Final[str] = "nequip_aoti_inputs"
NEQUIP_AOTI_OUTPUTS_KEY: Final[str] = "nequip_aoti_outputs"
NEQUIP_CUSTOM_O... |
76c9c105e3e7b02ee07f9a614f5602abc04d2b807acb254ceabb79675f825b16 | Python | 2,228 | 75 | """solves using the python scientific stack"""
import time
import numpy as np
from scipy.sparse.linalg import factorized
def solve(A, weights, reg, x0, rhs):
"""regularized, weighted linear least squares solve
Parameters
----------
A : :class:`scipy.sparse.csr_matrix`
the matrix... |
65c1a1bd703b002bfb224b0f18b119c8d1b591f7c07740a844b88825f29c51a4 | Python | 2,229 | 77 | # Configuration file for the Sphinx documentation builder.
#
# This file only contains a selection of the most common options. For a full
# list see the documentation:
# https://www.sphinx-doc.org/en/master/usage/configuration.html
# -- Path setup --------------------------------------------------------------
# If ex... |
567806d356797d540af56ef2a361998952fb4b6b242820fbd11d2552813d03ae | Python | 2,230 | 60 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Wed Dec 12 15:25:17 2018
@author: ngritti
"""
from csbdeep.models import CARE
import time, os, glob, tqdm
import numpy as np
from csbdeep.io import save_tiff_imagej_compatible
from skimage.io import imread
#%%
'''
register images and save them in the Regis... |
7ac05addf111ccaa08f33e0903661f0eb2a965adfec083ccdd995f74d235dbcc | Python | 2,233 | 52 | """
Filter between a highpass and a lowpass frequency using a butterworth filter.
"""
import argparse
import quantities as pq
import os
from elephant.signal_processing import butter
from utils.io_utils import load_neo, write_neo
from utils.parse import none_or_float
CLI = argparse.ArgumentParser()
CLI.add_argument("-... |
db0d0a456e3c8dd7f32bc65b481d8985b56beda613fec932599e2bdee1d91fa1 | Python | 2,233 | 56 |
from sleepy.processing.processor import Algorithm
from sleepy.processing.parameter import Parameter
import numpy as np
class BiLSTM(Algorithm):
def __init__(self):
self.name = "BiLSTM"
def compute(self, signal):
if not hasattr(self, 'BiLSTM_model'):
# generate ... |
ab9fdafd029cc44efaeab8524a96c57bb9421974f7bac69761fe88ac0037847a | Python | 2,236 | 49 |
def return_colordic():
dict_protfam = {'Enzyme': '#1F77B4',
'Membrane receptor': '#FF7F0E',
'Transporter': '#2CA02C',
'Secreted protein': '#D62728',
'Ion channel': '#9467BD',
'Transcription factor': '#8C564B'... |
46b43b65d9e45a3a6bc3494f229584797169f0ef1603c51bb743500cdda185d2 | Python | 2,238 | 49 | import json
import argparse
from rdkit import RDLogger
from torch_geometric.loader import DenseDataLoader
from dig.ggraph.dataset import QM9, ZINC250k, MOSES
from dig.ggraph.method import GraphDF
from dig.ggraph.evaluation import RandGenEvaluator
RDLogger.DisableLog('rdApp.*')
parser = argparse.ArgumentParser()
parse... |
099b9b1a0e6be14649b7a21090966719b3148e5d086464e980859a24c05ee406 | Python | 2,239 | 83 | import socket, time, os
from neurodecode.utils.timer import Timer
class GlassControl():
def __init__(self):
self.BUFFER_SIZE = 1024
self.s = socket.socket(socket.AF_INET, socket.SOCK_STREAM)
self.last_dir = 'L'
self.timer = Timer()
def connect(self, ip, port):
self.ip... |
1217ad83f3cc0e193297c3d8672b4e0e5ecffe1ca8022564d4b72caa76a84a33 | Python | 2,240 | 81 | #
# For licensing see accompanying LICENSE file.
# Copyright (C) 2022 Apple Inc. All Rights Reserved.
#
import importlib
import os
import argparse
from utils import logger
from ..base_criteria import BaseCriteria
SUPPORTED_CLS_LOSS_FNS = []
CLS_LOSS_FN_REGISTRY = {}
def register_classification_loss_fn(name):
... |
adbe096c540ffaab9e7a86dc643a30e1613b7beb037bb5d10e1ce1fcaaceafc9 | Python | 2,240 | 79 | import math, sys
from PyQt5.QtCore import Qt, QTimer
from PyQt5.QtGui import *
from PyQt5.QtWidgets import *
class Overlay(QWidget):
def __init__(self, parent = None):
QWidget.__init__(self, parent)
palette = QPalette(self.palette())
palette.setColor(palette.Background, Qt.transparent... |
11996be65ec8bae0d912fdc0b9e3323c9c94c3eda58f7f57d86e28957cc8a7c4 | Python | 2,241 | 73 | """Module to validate the tracking data of a session, see :ref:`validator_reference`."""
import sys
from argparse import ArgumentParser
from multiprocessing import Process
from pathlib import Path
from qtpy.QtWidgets import QApplication
from idtrackerai import Session
from idtrackerai.utils import (
LOGGING_QUEU... |
e97732b78b018640c9f7c9cf7b02f71735e357b5833b4e181261fecd17189f4d | Python | 2,241 | 54 | import numpy as np
from scipy import interpolate as interpolate_
def nan_to_zero(im):
"""
Set all values to zero that are less than zero or nan; return the indices of all elements that are zero after
the modification (i.e. those that have been nan or smaller than or equal to zero before calling this funct... |
6f5c88333acbdfce781c9cafb605a4fb5fbb84f2a8fcab67007842f2daad8550 | Python | 2,243 | 96 | import numpy as np
def test_add_noise():
from mlspm.preprocessing import add_noise
np.random.seed(0)
n = 1000
c = 0.1
for _ in range(n):
test_input = np.zeros((3, 10))
# The add_noise function scales the noise amplitude by the range of the data so we need at least one element
... |
dcce3f83baf21bc684ae982e5971267420cfdebc7478c851b8301036a703e089 | Python | 2,243 | 52 | """
Filter between a highpass and a lowpass frequency using a butterworth filter.
"""
import argparse
from pathlib import Path
import quantities as pq
import os
from elephant.signal_processing import butter
from utils.io_utils import load_neo, write_neo
from utils.parse import none_or_float
CLI = argparse.ArgumentPar... |
428e866f162d4423f5846809670442622d318aa5611fa5ec9ec7047513f08c00 | Python | 2,244 | 56 |
from sleepy.processing.processor import Algorithm
from sleepy.processing.parameter import Parameter
import numpy as np
class BiLSTM(Algorithm):
def __init__(self):
self.name = "BiLSTM"
def compute(self, signal):
if not hasattr(self, 'BiLSTM_model'):
# generate ... |
a58d93992e5c99729db2d28142f1c3b57e768fe76430b10c63514b941f7080b1 | Python | 2,247 | 67 | """Plot a geodesic on the Poincare polydisk.
Plot a geodesic on the Poincare polydisk,
with Poincare Disk visualization.
"""
import matplotlib.pyplot as plt
import geomstats.backend as gs
import geomstats.visualization as visualization
from geomstats.geometry.poincare_polydisk import PoincarePolydisk
def plot_geod... |
0de95dc26780b5f1333f5a079a9cfcf57d3fa44b7e933996e17c22cb8c4ef521 | Python | 2,248 | 61 | # Copyright (C) 2020-2021 Intel Corporation
# SPDX-License-Identifier: Apache-2.0
"""You may copy this file as the starting point of your own model."""
from openfl.federated import KerasDataLoader
from src.brats_utils import load_from_nifti
class KerasBratsInMemory(KerasDataLoader):
"""Keras Data Loader for the... |
e71b42410c7ca264ffd62a6c699576816e1b9193e6b8ea2e69f846b85ffd95eb | Python | 2,249 | 79 | import random
import pytest
from geomstats.information_geometry.binomial import (
BinomialDistributions,
BinomialDistributionsRandomVariable,
BinomialMetric,
)
from geomstats.test.parametrizers import DataBasedParametrizer
from geomstats.test_cases.geometry.riemannian_metric import RiemannianMetricTestCas... |
9af96416f33d21d26e29cec5523900a4a61efbf5af9c9561539157bc4b7368ff | Python | 2,250 | 91 |
'''
Example showing software-timed (on demand) analog output
pinidaqmxegs.ao.OnDemand
Purpose
Generates a class that can be used interactively set the voltage of an AO line.
If instantiated at the Python command prompt, the user can interact with the object.
If run at the system comma... |
d91a8c27812e0add5c7ef1448b440ccec6722e4db39dc820108bcc56d69e47fb | Python | 2,252 | 56 | import pytest
import geomstats.backend as gs
from geomstats.test_cases.geometry.riemannian_metric import RiemannianMetricTestCase
class ComplexRiemannianMetricTestCase(RiemannianMetricTestCase):
@pytest.mark.random
def test_inner_product_is_symmetric(self, n_points, atol):
"""Check that the inner pro... |
b6af87d1f8a897666223a64bd82a3baddd292f7d8643794b2937f5526e46e2d6 | Python | 2,253 | 65 | import jax
import jax.numpy as jnp
from typing import Tuple
def generate_input_parameters(
key: jax.random.PRNGKey, cfg
) -> Tuple[jnp.ndarray, float]:
"""
Generates input parameters for a neural network model.
Args:
key (jax.random.PRNGKey): Random key for generating random numbers.
... |
b79a234ce1cd19331521ef1463a9ca2396f83160452b55908bc204d4afac7792 | Python | 2,253 | 67 | """Sampler setup needed for sampling and staged learning"""
from __future__ import annotations
from typing import TYPE_CHECKING
import logging
import warnings
from reinvent.runmodes import samplers
if TYPE_CHECKING:
from reinvent.models import ModelAdapter
logger = logging.getLogger(__name__)
warnings.filterwar... |
ecec8ed23e7066bac958c66595c631d12d54c8726df2cde4a57c0032aa0ad59d | Python | 2,253 | 64 | from chromadb.utils.rendezvous_hash import assign, murmur3hasher
from math import sqrt
def test_rendezvous_hash() -> None:
# Tests the assign works as expected
members = ["a", "b", "c"]
key = "key"
def mock_hasher(member: str, key: str) -> int:
return members.index(member) # Highest index wi... |
479a17f9302a451975365fd5d06c658f1190882f8f50f5b2e5388a03f54f4c69 | Python | 2,254 | 69 | """Provides custom loss functions for PyTorch."""
import torch
import numpy as np
from dival.util.constants import MU_MAX
def tv_loss(x):
"""
Anisotropic TV loss similar to the one in [1]_.
Parameters
----------
x : :class:`torch.Tensor`
Tensor of which to compute the anisotropic TV w.r.... |
69c8abb379006bbca1b71502888dccba6ae07100dd11368eeaeab33f06d7d13c | Python | 2,256 | 60 | """Test calculation of implied timescales."""
import numpy as np
from ivac.linear import _vac_its as vac_its
from ivac.linear import _ivac_its as ivac_its
def vac_eval(sigmas, lag):
return np.exp(-sigmas * lag)
def ivac_eval(sigmas, minlag, maxlag, lagstep):
assert (maxlag - minlag) % lagstep == 0
lag... |
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