sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
b7c31256f6a0d1e19a96a162b44ffdc4c190ae3f222f674aff8e413a11d838fb | Python | 6,950 | 236 | from models.model import *
from objective import *
from models.losses import *
import torch
from scipy.optimize import minimize
import numpy as np
import os
import matplotlib.pyplot as plt
import matplotlib as mpl
from objective import Objective
import PyMieScatt as pms
import argparse
### refractive index dictiona... |
405c77687d854d0ea8235ee101b00d4f781f7cf95daf3820312decd40854653f | Python | 6,951 | 204 | from rdkit import Chem
import torch
from dgllife.utils import *
from dgllife.utils.featurizers import CanonicalAtomFeaturizer, CanonicalBondFeaturizer
from ocelotml_2d.mlp_features import *
#from mlp_features import *
import json
from ocelotml_2d.MPNN_evidential import MPNNPredictor_evidential
from ocelotml_2d... |
eccdaf1fd4cf21ba6b8febaeb79449d887a353f3a4247258c54d151c66a9e384 | Python | 6,952 | 186 | from pathlib import Path
import numpy as np
import pytest
from learnMSA.config.config import Configuration
from learnMSA.model.context import LearnMSAContext
from learnMSA.model.tf.training import BatchGenerator, make_dataset
from learnMSA.util import EmbeddingCache, EmbeddingDataset, SequenceDataset
@pytest.fixtur... |
cddfea70d7899e9d97e8c3bf6e6ba816cd67195b1b4a8e7ea73b0df2e6b7a08e | Python | 6,953 | 183 | import os
import unittest
import numpy as np
from patch import p
from arborize import define_model, neuron_build
from arborize.exceptions import UnknownLocationError, UnknownSynapseError
from ._shared import SchematicsFixture
@unittest.skipIf(
"NRN_SEGFAULT" in os.environ,
"These tests are sk... |
19e6c4df87e04e8c96c00b113e0ba1f2110f37a0aaa06fb985131746c8d50014 | Python | 6,954 | 186 | import base64
import io
import json
import zlib
from pip._vendor import msgpack
from pip._vendor.requests.structures import CaseInsensitiveDict
from .compat import HTTPResponse, pickle, text_type
def _b64_decode_bytes(b):
return base64.b64decode(b.encode("ascii"))
def _b64_decode_str(s):
return _b64_decod... |
92be9d221e36ad2a9d5c4b42620f2a3949faaf1a163600dae45efd4980488809 | Python | 6,954 | 175 | #!/usr/bin/env python3
# Copyright (c) Meta Platforms, Inc. and affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
# pyre-strict
from unittest.mock import patch
import numpy as np
import pandas as pd
import torch
from ax.benchmark... |
0af4e3203033efc08a759876de8d798b0094fb0bfb915453ddb9a960dbaff45a | Python | 6,955 | 181 | #!/usr/bin/env python3
# Copyright (c) Meta Platforms, Inc. and affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
# pyre-strict
from copy import deepcopy
from ax.adapter.base import DataLoaderConfig
from ax.adapter.data_utils imp... |
e3fd26974b03ed92c56259b8b49cc55a0ae58070f53a20b6fb5b3b7132cd8949 | Python | 6,955 | 227 | """
Generators for the small graph atlas.
"""
import gzip
import importlib.resources
from itertools import islice
import networkx as nx
__all__ = ["graph_atlas", "graph_atlas_g"]
#: The total number of graphs in the atlas.
#:
#: The graphs are labeled starting from 0 and extending to (but not
#: including) this num... |
2a6b183eb41b69dc183ed6c356685a5563e84dafd2c687559168bf66292607df | Python | 6,956 | 178 | import os
import numpy as np
from scipy import interpolate
from types import SimpleNamespace
from voluseg._tools.load_volume import load_volume
from voluseg._tools.save_volume import save_volume
from voluseg._tools.get_volume_name import get_volume_name
from voluseg._tools.constants import ori, ali, nii, hdf
from volu... |
eea7222241d43e3c12c483f8c49e1963593754c25182550d7d80075e8bf3ecd3 | Python | 6,957 | 181 | from spikingjelly.logger import logger
import os
from pathlib import Path
from typing import Callable, Optional, Tuple
from torchvision.datasets.utils import extract_archive
from . import utils
from .base import NeuromorphicDatasetFolder
__all__ = ["DVSLip"]
class DVSLip(NeuromorphicDatasetFolder):
def __init... |
53c5ee799bc97b04fdd26df2cd1e96e21d90f3913b3f23ebacb00563b3f01c97 | Python | 6,961 | 192 | from matplotlib import pyplot as plt
import matplotlib.patches as mpatches
import pandas as pd
import numpy as np
import os
from math import floor, ceil
color_grey = '#B3B3B3'
color_blue = 'cornflowerblue'
color_red = '#D62728'
color_green = '#60A917'
# ================ ===============================
# character ... |
e8b472283043c5c8b02dc6e8ae6d5e81a299d8e93a4734f4257748edec4f4c38 | Python | 6,964 | 161 | from datetime import datetime
from functools import reduce
from typing import Optional
import tensorflow as tf
from tensorflow.keras import layers
from tensorflow.python.keras.losses import LossFunctionWrapper
from tensorflow.python.keras.utils import losses_utils
class PolicyWrapper(layers.Layer):
def __init__(... |
3cf892ab9f86b13d4bb1ff1fc2d1b018355fd6186fe592daae25ad7f39016c0c | Python | 6,968 | 172 | """Functions for finding chains in a graph."""
import networkx as nx
from networkx.utils import not_implemented_for
__all__ = ["chain_decomposition"]
@not_implemented_for("directed")
@not_implemented_for("multigraph")
@nx._dispatchable
def chain_decomposition(G, root=None):
"""Returns the chain decomposition of... |
8f567fff815a2582ec339b989fd1758b1e50dd05b3e911a78682f49e50f8c227 | Python | 6,968 | 185 | # Copyright (c) Meta Platforms, Inc. and affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
# pyre-strict
from typing import final
import pandas as pd
from ax.adapter.base import Adapter
from ax.analysis.analysis import Analysis
f... |
2958e07a60db391d99326ba13f3fca3c7a116211721964e8f0cf16f3801c75e8 | Python | 6,970 | 176 | # -*- coding: utf-8 -*-
"""
Created on Tue Feb 22 11:55:42 2022
@author: marcomau
"""
# GNN for displacement/stress field predictions
import torch
import torch_geometric
from torch.nn import Sequential, Linear, ReLU, LayerNorm, LSTM, GRU
from torch_geometric.nn import MessagePassing
import functools
impo... |
18d9b10678f7fb84aeb7132c3f302526fa6bf1e68c0dcc7ad897d7cf764975ff | Python | 6,973 | 176 | #!/usr/bin/env python3
# Copyright (c) Meta Platforms, Inc. and affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
# pyre-strict
from __future__ import annotations
from collections import defaultdict
from copy import deepcopy
imp... |
860292f22a20bedbfd3519a0e20185ee0f88700f8e2a1fc2566ca1061a7dd1de | Python | 6,974 | 167 | # Licensed to the Apache Software Foundation (ASF) under one
# or more contributor license agreements. See the NOTICE file
# distributed with this work for additional information
# regarding copyright ownership. The ASF licenses this file
# to you under the Apache License, Version 2.0 (the
# "License"); you may not u... |
a6e1c9e9392d0fa15854223858759978f69051c5fb78b1a024b77bb766d6649c | Python | 6,974 | 211 | from nl_expr.expression_walker import (
ExpressionWalker,
PatternWalker,
ResolveSymbolMixin,
add_match,
)
from nl_expr.expressions import Constant, Symbol
from ..relational_algebra import (
ColumnStr,
ExtendedProjection,
FunctionApplicationListMember,
NameColumns,
NumberColumns,
... |
35ed40b0fca344ee5585ee1e7b363cdb0f7e0be22fe352d5fe6d32feb3cea8b9 | Python | 6,979 | 213 | import copy
import math
import random
import numpy
import torch
from torch import nn
from src.expressions_transfer import *
USE_CUDA = torch.cuda.is_available()
MAX_OUTPUT_LENGTH = 33
def time_since(s): # compute time
m = math.floor(s / 60)
s -= m * 60
h = math.floor(m / 60)
m -=... |
66a150c06c84c7faaa5351248b4c299413076cb37aa1051ce2780a7a2f22c7b6 | Python | 6,980 | 178 | # Licensed to the Apache Software Foundation (ASF) under one
# or more contributor license agreements. See the NOTICE file
# distributed with this work for additional information
# regarding copyright ownership. The ASF licenses this file
# to you under the Apache License, Version 2.0 (the
# "License"); you may not u... |
0f045703dddd4229a30c4e32e2e2685002abf8f50112db1432ba5dff2cc89385 | Python | 6,984 | 189 | # Copyright (c) Meta Platforms, Inc. and affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
# pyre-strict
from collections import defaultdict
import numpy as np
import numpy.typing as npt
from ax.adapter.discrete import DiscreteAd... |
3062b7336b0e45b6d6f5cd9e1f273f341d6d920ba65480df0ae158db4f817978 | Python | 6,986 | 272 | import typing
from .. import solver
from .. import expressions
from .. import logic
from ..typed_symbol_table import TypedSymbolTable
C_ = expressions.Constant
S_ = expressions.Symbol
def test_simple_symbol_query():
ds = solver.FirstOrderLogicSolver(TypedSymbolTable())
for s in range(5):
sym = S_[i... |
ffd716e4999f2183b1751e7f82de6fb9eeb6ceda1ae04e065966574597d87f24 | Python | 6,990 | 280 | # Copyright (c) Meta Platforms, Inc. and affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
# pyre-strict
from __future__ import annotations
import traceback
from abc import ABC, abstractmethod
from collections.abc import Callable... |
271ca69dbcb244c317a20b6154489b6565d6dddee195b4ba5dd888652b626136 | Python | 6,996 | 211 | # Density and co-localisation of pre- and post-synaptic markers.
# by Richard Butler, Gurdon Institute Imaging Facility, University of Cambridge
#
# Copyright 2021, 2022 Richard Butler
#
# This program is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as publ... |
0a84547b1109b843c4565bac278c264acec3b21e7a7f0ade1dc16b5f135d87cb | Python | 6,998 | 154 | import os
import argparse
import sys
import time
from scripts.new_patient_pipeline.run_script_segmentation import run_script_segmentation
from scripts.new_patient_pipeline.run_script_preprocessing import run_script_preprocessing
from scripts.new_patient_pipeline.run_script_prediction import run_script_prediction
from m... |
f022fddf5562e1504d2a847a2fbd35d124d333a52596e47e8b5eee8cc1262bb6 | Python | 6,998 | 193 | #!/usr/bin/env python3
# Copyright (c) Meta Platforms, Inc. and affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
# pyre-strict
import inspect
from collections.abc import Callable, Iterable, Mapping
from logging import Logger
from... |
662a7441c12ea757a1afacf3b57785cc6e501514f99fc39e1538688ed00f2ec7 | Python | 7,001 | 185 | '''
This code is borrowed from https://github.com/Namkyeong/BGRL_Pytorch
'''
import numpy as np
import torch
import models
import utils
import data
import os
import sys
import warnings
from torch import optim
from tensorboardX import SummaryWriter
from sklearn import metrics
from sklearn.linear_model import Logis... |
b217630cd870c247f1c9625f48ebd2ef1eddcbdf781eab3a590d19383e5929af | Python | 7,001 | 219 | """
Algorithms for computing distance measures on trees.
"""
import networkx as nx
__all__ = [
"center",
"centroid",
]
@nx.utils.not_implemented_for("directed")
def center(G):
"""Returns the center of an undirected tree graph.
The center of a tree consists of nodes that minimize the maximum eccentr... |
3ef87432f4ca691b99bb058bfb0a49202d3394101c9d38aba522c98bef5ceea7 | Python | 7,006 | 195 | import random
import pytest
import networkx as nx
from networkx.utils import arbitrary_element, graphs_equal
@pytest.mark.parametrize("prefix_tree_fn", (nx.prefix_tree, nx.prefix_tree_recursive))
def test_basic_prefix_tree(prefix_tree_fn):
# This example is from the Wikipedia article "Trie"
# <https://en.wi... |
4713ed5339aa4ec8dc07c6fc8f627511598143d2df1e55e1a0f8de0d2903d4bb | Python | 7,008 | 186 | """
Created on 2020.05.19
@author: Jiahua Rao, Weiming Li, Hui Yang, Jiancong Xie
Code based on:
Shang et al "Edge Attention-based Multi-Relational Graph Convolutional Networks" -> https://github.com/Luckick/EAGCN
Coley et al "Convolutional Embedding of Attributed Molecular Graphs for Physical Property Prediction" ->... |
220388196efa391cc3fdb762196fa658cb8050baa43c363ff168e13cb0e00a13 | Python | 7,010 | 155 | from src.models.wavelet_model import WaveletAI
import tensorflow as tf
import numpy as np
from src.data import DataServing
from src.custom_metrics import JaccardIndex
from src.utility import bin_localisations_v2, get_reconstruct_coords,FRC_loss, timing
from src.models.loss_functions import compute_loss_decode, compute_... |
51bfab701bcb8a8fc468518f7b23a929033c05fc34faa2c4da5c3ebc6fb7b697 | Python | 7,010 | 190 | import numpy as np
import pandas as pd
from sklearn.preprocessing import scale
def _mvalue(da, scale_group=True, alpha=1):
mc = da.sel(count_type="mc")
cov = da.sel(count_type="cov")
m = np.log2((mc + alpha) / (cov - mc + alpha))
if scale_group:
group_axis = da.dims.index("group")
m.va... |
f49f50cc0fa09606d08d373c5ce60d944bf95bfe7ef1524954a80c7afa322640 | Python | 7,013 | 180 | # Licensed to the Apache Software Foundation (ASF) under one
# or more contributor license agreements. See the NOTICE file
# distributed with this work for additional information
# regarding copyright ownership. The ASF licenses this file
# to you under the Apache License, Version 2.0 (the
# "License"); you may not u... |
5a3da38535d9f0bc275e13c2cf88215647b41f62fcec46b0857950af0a20c6be | Python | 7,014 | 228 | from __future__ import print_function
from itertools import repeat
import collections
import math
import torch
import torch.nn as nn
from torch.nn import functional as F
__all__ = ['Model']
WIDTH = [16,32,64,128,256,512]
def _ntuple(n):
"""
Copied from the PyTorch source code (https://github.com/pytorch)... |
e30ef62312e1a4511e686db36f688667ed81b791f3cc4a7e0e8df19c2a611e68 | Python | 7,018 | 197 | import sys
import time
def _format_time(seconds):
"""Format seconds as hh:mm:ss.
Parameters
----------
seconds : float
Time in seconds.
Returns
-------
str
Formatted time string in hh:mm:ss format.
"""
hours = int(seconds // 3600)
minutes = int((second... |
95b6adcaa5f3e7d79f4e3af6fec84d6dcf8764870e8bf5afa39ab04d4a9cf419 | Python | 7,019 | 233 | """
Module for abstract classes interfacing matplotlib plots.
"""
import abc
from typing import List, Tuple, Union
import numpy as np
from bsb import Scaffold
from matplotlib import patches
from matplotlib import pyplot as plt
class Plot(abc.ABC):
"""
Matplotlib plot class interface.
"""
def __init... |
d5b26b7cbdd6fffec3bc82707ed24f49f6a775ed9812d549f8119969ca8cb05e | Python | 7,020 | 199 | from dotmap import DotMap
import torch
import numpy as np
from collections import deque
from copy import deepcopy
from loguru import logger
from .losses.spectrum_loss import _spectrum_loss_fn
from .losses.likelihood_regularization_loss import _likelihood_regularization_loss_fn
from ..materials.material_collection imp... |
d174f7e71bdfa4065426ba97142ecf179afb72eb00ef4e958543706698be36ac | Python | 7,021 | 163 | """Mixin providing common wait methods that work across Selenium and Playwright."""
from typing import Any
from galaxy.navigation.components import Target
class WaitMethodsMixin:
"""
Mixin providing high-level wait methods.
This mixin abstracts wait operations to work with both Selenium and Playwright
... |
1ee4bc426a25be16138a3ce78d64ba448e0f1cfbf36b250a13c8994e36554ca0 | Python | 7,028 | 154 | from collections import defaultdict
import tensorflow.compat.v1 as tf
from .layers import GraphConvolutionSparseMulti, \
DistMultDecoder, InnerProductDecoder, DEDICOMDecoder, BilinearDecoder, GraphAttentionMulti, GraphConvolutionMulti
flags = tf.app.flags
FLAGS = flags.FLAGS
class Model(object):
... |
b4f79939898a5b5bd023aeea0d2b8f8a83eaf69d85e92d2e131eab8062b30951 | Python | 7,030 | 205 | """ Segment info DataFrame IO for processing tasks """
import os
from sqlalchemy import select, text
import pandas as pd
from ... import io
from .. import colnames as cn
from . import filenames as fn
SEG_INFO_COLUMNS = [cn.seg_id, cn.size, *cn.centroid_cols, *cn.bbox_cols]
CHUNK_START_COLUMNS = [cn.chunk_tag, cn.... |
99868bca71f68a69f4982f97f57fd5a34023dad1fe50197d8c9d19287b36defe | Python | 7,035 | 159 | import tensorflow.compat.v1 as tf
import numpy as np
flags = tf.app.flags
FLAGS = flags.FLAGS
class DecagonOptimizer(object):
def __init__(self, embeddings, latent_inters, latent_varies,
degrees, edge_types, edge_type2dim, placeholders,
margin=0.1, neg_sample_weights=1... |
61b5dec57ac23e0b2fae5d069a9a75d9a24b752bd8b2e91f41a2149db0c5994d | Python | 7,038 | 188 | """Typed description of Galaxy's app object."""
import abc
import threading
from typing import (
Any,
Optional,
TYPE_CHECKING,
)
from kombu import Connection
from typing_extensions import Protocol
from galaxy.auth import AuthManager
from galaxy.datatypes.registry import Registry
from galaxy.di import Con... |
f7d1c5f8af943331b905da83cd49e673e71db9ce05aa79cc41392f87b47a67fd | Python | 7,039 | 179 | import copy
import pytest
import torch
from spikingjelly.activation_based.neuron.flexsn import FlexSN
def _lif_core(x, v, threshold):
h = v + (x - v) * 0.5
spike = torch.sigmoid(h - threshold)
return spike, h * (1.0 - spike)
def _reference(x_seq, v, threshold):
outputs, states = [], []
for x i... |
33a72a5477c26086bae62b18ebd8c5438f86bed56a2865790a1b9e05cb22600e | Python | 7,040 | 207 | import argparse
import os
import numpy as np
import math
import itertools
import time
import datetime
import sys
import torchvision.transforms as transforms
from torchvision.utils import save_image
from torch.utils.data import DataLoader
from torchvision import datasets
from torch.autograd import Variable
from model... |
8ee5a39bd4468872b70d996b5bbbd0dc91841e2b9a5dce43c7b1c6acf13a3168 | Python | 7,042 | 207 | import random
import torch
import torch.nn as nn
import torch.nn.functional as F
from cogdl.data import Graph
from cogdl.layers import SAGELayer
from .. import BaseModel
def sage_sampler(adjlist, edge_index, num_sample):
if adjlist == {}:
row, col = edge_index
row = row.cpu().numpy()
co... |
5e03e683a6d6887005d6243be7faf636a53113139035945479850fce509ae7e1 | Python | 7,043 | 334 | import pytest
import networkx as nx
def test_selfloops_raises():
G = nx.ladder_graph(3)
G.add_edge(0, 0)
with pytest.raises(nx.NetworkXError, match=".*not bipartite"):
nx.bipartite.maximal_extendability(G)
def test_disconnected_raises():
G = nx.ladder_graph(3)
G.add_node("a")
with p... |
5f29a68ee3bc6fb5ab58d330a092c3cd86b9579ffe306b09605f24e562706892 | Python | 7,043 | 132 | """
Workflow script to get fish dots in the given segmentation mask
"""
from helpers_and_sources.mainflow_helpers import *
from helpers_and_sources import gaussian_plot
import tifffile as tf
import numpy as np
import csv
from os.path import split, splitext, join
from os import makedirs
# The following functions d... |
92e20134cb265c99a5c988d39639f0116461058acd2d421528b1b1fb0b099df7 | Python | 7,043 | 198 | import base64
import contextlib
import hashlib
import importlib.metadata
import json
import os
import tempfile
import time
import typing
from uuid import uuid4
from ...exceptions import MissingActiveConfigError
from ..interfaces import FileStore as IFileStore
def _id_to_path(url):
return base64.urlsafe_b64encode... |
2570be0325234c5dbef4edb791f89fbd42810818a1acf804d03632982a5b0e89 | Python | 7,046 | 200 | import torch
import torch.nn as nn
from torch.nn.modules.normalization import LayerNorm
import random
from utilities.constants import *
from utilities.device import get_device
from .positional_encoding import PositionalEncoding
from .rpr import TransformerEncoderRPR, TransformerEncoderLayerRPR
# MusicTransformer
cl... |
e9baa25af5d8732119c43d87e30cdc5213dc47158c91d12953419e154a290990 | Python | 7,047 | 187 | import pandas as pd
from tensorflow.keras.models import Model
import numpy as np
from sklearn.model_selection import train_test_split, KFold
from sklearn.metrics import accuracy_score
from tensorflow.keras.optimizers import Adam, SGD
import os
import random
from sklearn.model_selection import train_test_split... |
2df71cba55ee5225b25bc33cd5621530bff327f3347bf14b3b041a02062fc3ea | Python | 7,048 | 180 | # 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... |
329dd2b59a1dd54db826d8207a5fd3ffea0b36903c0e582148f3357605c4a082 | Python | 7,048 | 176 | """
Plot Supplemental Figure S5
"""
import numpy as np
import pylab as pl
import strinf as si
# # # PARAMETERS # # #
ZOOM = 1.5
SAVE = True # Save figure file
SHOW = True
# The trials from all conditons
datadir = "./data/"
DSL = {"multy_0_surround_bi" : "2022-05-12-16-03-09-435421_107_direction_r... |
ae04691eaa761417602dc5d42b639612aa6650d3363640c232018dc9d45ecd9b | Python | 7,051 | 204 | import argparse
import os
import numpy as np
import math
import torchvision.transforms as transforms
from torchvision.utils import save_image
from torch.utils.data import DataLoader
from torchvision import datasets
from torch.autograd import Variable
import torch.nn as nn
import torch.nn.functional as F
import torch... |
1b2b8a6f6406c305d6acfec212ee0b889c561994d44b9f05d27882b9878a7158 | Python | 7,055 | 169 | # -*- coding: utf-8 -*-
from figureflow import figure
import seaborn as sb
import numpy as np
import os
import importlib
importlib.reload(figure)
Figure = figure.Figure
input_folder = os.path.dirname(os.path.abspath(__file__))
figure = Figure(input_folder,number=9, dpi=600, width=7.3)
figure.creat... |
e0e722377597b7a86874d9960434936d14b8200f313932a132c34f4c9eb29ea7 | Python | 7,063 | 211 | # rmf 3.24.2020, last modified 5.18.2021
# cleaned up 3.1.2022
import sys
import statsmodels.stats.multitest as multi
# USAGE
usage = 'python ' + sys.argv[0] + ' <test results file> <meme map file> <gene median expression file> <secondary FBID file> <secondary JASPAR ID file>'
if len(sys.argv) != 6 or '-h' in sys.arg... |
05777330df54574749b280d080277ad5c156a3ccd919a726f4d245a9cbbd7b3c | Python | 7,067 | 196 | import os
import os.path as osp
import numpy as np
from collections import defaultdict
import scipy.sparse as sp
import torch
from cogdl.data import Graph, Dataset
from cogdl.utils import untar, download_url
from cogdl.utils.grb_utils import adj_to_tensor
class GRBDataset(Dataset):
GRB_SUPPORTED_DATASETS = {"gr... |
4dde154494d355e5b1d6ec29b679951c0e452efbc6d72ef946a77c11ae93586f | Python | 7,068 | 166 | # MIT License
#
# Copyright (c) 2019-2024 The PyQMC Developers
#
# Permission is hereby granted, free of charge, to any person obtaining a copy
# of this software and associated documentation files (the "Software"), to deal
# in the Software without restriction, including without limitation the rights
# to use, copy, m... |
a40cad9e5b98e2c2f1e52a53608bc2043285de59d9cc6fa76e7faaeb77d03b5d | Python | 7,071 | 147 | """
Plotting all experiments for the paper.
"""
import numpy as np
import roblib
import settings
from pathlib import Path
import pandas as pd
from utils import load_config
from plot_maker import plot_module
def naming_unfolding(str_template, unfolding_specs):
cur_strings = [str_template]
for idx... |
fa319c787c19721c33e80a4a4f17354deab944dad2dc8b54f9f1ad70b0c3c74c | Python | 7,071 | 166 | from brian2.core.preferences import prefs
from brian2lava.utils.const import runtime_configs, HARDWARE
from brian2lava.preset_mode.model_loader import ModelLoader
from brian2lava.preset_mode.handler import PresetProcessHandler
class SettingsParser:
def __init__(self, device):
self.device = device
... |
87114b5f435c76d87b758edec5c21d168e94190ae3b99e8a21e20bde3aabfb7a | Python | 7,081 | 200 | from __future__ import absolute_import
import logging
import os
import re
from pip._internal.utils.logging import indent_log
from pip._internal.utils.misc import (
display_path, make_vcs_requirement_url, rmtree, split_auth_from_netloc,
)
from pip._internal.vcs import VersionControl, vcs
_svn_xml_url_re = re.comp... |
418de06947f84b22ca3a6296fe4a5bcb62c16bb4c1887cee0e924e0d2002b76b | Python | 7,082 | 166 | # Licensed to the Apache Software Foundation (ASF) under one
# or more contributor license agreements. See the NOTICE file
# distributed with this work for additional information
# regarding copyright ownership. The ASF licenses this file
# to you under the Apache License, Version 2.0 (the
# "License"); you may not u... |
5deaaf15f4c3a50c3a3b3fabf96ec50681dff8ba342ad2ebbae80958637ac73c | Python | 7,085 | 215 | import argparse
import os
import numpy as np
import math
import torchvision.transforms as transforms
from torchvision.utils import save_image
from torch.utils.data import DataLoader
from torchvision import datasets
from torch.autograd import Variable
import torch.nn as nn
import torch.nn.functional as F
import torch... |
5c885999dd5562115947b054abdcff4860b2bcb660e3046ea00e0a4d6e1eff64 | Python | 7,087 | 166 | import copy
import os
import tempfile
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
import pytest
from sklearn.cluster import KMeans
from test_utils import make_cell_table
import ark.settings as settings
import ark.spLDA.processing as pros
import ark.utils.spatial_lda_utils as spu
def test_... |
653da3168c8ccf9c0e03612124024c062198479e58bbc788682d4e593671f98e | Python | 7,092 | 176 | #!/usr/bin/env python
# Copyright 2020 The HuggingFace Team. 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... |
2f251d4941649c8d7b96bb7941b371d0971ddf91c6bc2c97b89e49f464a88f54 | Python | 7,097 | 202 | """
Copyright © 2023 Howard Hughes Medical Institute, Authored by Carsen Stringer and Marius Pachitariu.
"""
import os
import numpy as np
import matplotlib.pyplot as plt
from pathlib import Path
from cellpose import models, io, metrics
from cellpose.models import CellposeModel
from tqdm import trange
# uses tensorflow
... |
0c5e9ff721c414a2c7a1689f17dd1df5ab58201d986a7978d27e74d242ad1e04 | Python | 7,098 | 185 | from __future__ import annotations
from contextlib import nullcontext
from os import PathLike
from pathlib import Path
from typing import TYPE_CHECKING, cast
import h5py
import zarr
from anndata._core.file_backing import AnnDataFileManager
from anndata._io.specs.registry import read_elem, read_elem_lazy
from anndata... |
7f82554639e85b4ebbe4c79192ae9ff2df7af5d4525706b27411594f0f742ee3 | Python | 7,110 | 220 | # Copyright (C) CVAT.ai Corporation
#
# SPDX-License-Identifier: MIT
import csv
import json
import os
import random
import sys
from itertools import product
NAME = "projects"
def read_rules(name):
rules = []
with open(os.path.join(sys.argv[1], f"{name}.csv")) as f:
reader = csv.DictReader(f)
... |
a569a6581a1e18bbea4b7da8a6f37e58e805cb7fee4bdf5107cf8961329ba6eb | Python | 7,110 | 194 | # Copyright (c) Meta Platforms, Inc. and affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
# pyre-strict
from typing import Any, final
import numpy as np
import pandas as pd
from ax.adapter.base import Adapter
from ax.analysis.an... |
9d24c5bceed38c53ab032f0733125f784a84bda77912fc8697dbda930bf210ca | Python | 7,111 | 192 | import abc
import warnings
import nest
from bsb import AdapterError, DeviceModel, Targetting, config, refs, types
from .distributions import nest_constant
@config.node
class NestRule:
"""
Interface to connect a device directly through the NEST interface.
"""
rule = config.attr(type=str, required=Tr... |
9ff5431f0c9faafb3d5ea338c4d4a654e1b014a890e615f777f80d208c2e6a53 | Python | 7,114 | 223 | # Copyright (C) CVAT.ai Corporation
#
# SPDX-License-Identifier: MIT
import csv
import json
import os
import random
import sys
from itertools import product
NAME = "annotationguides"
def read_rules(name):
rules = []
with open(os.path.join(sys.argv[1], f"{name}.csv")) as f:
reader = csv.DictReader(f)... |
43aea0ed05dbb4768c5a61af7a4d0d5b65c0915f7dc4fd28ebb3371be5d6d339 | Python | 7,116 | 155 | from math import floor as floor
from numpy import array as array
from numpy import exp as exp
from numpy import zeros as zeros
from scipy.special import gammaincc as gammaincc
from scipy.special import hyp1f1 as hyp1f1
class TemplateMatching:
@staticmethod
def non_overlapping_test(binary_data:str, verbose=Fa... |
8f22d2c29f5a5acf4dab095ee1aca18da3546d45614c765a0e9290c83dc3c74f | Python | 7,117 | 207 | """Calculate RDMs based on Mahalanobis distance.
For a given subject:
- load epochs for a stream (single or dual)
- perform baseline correction
- create a design matrix where each trial is predicted by the condition of that
trial. For example, if there are conditions 1, 2, and 3, the design matrix
has three column... |
bb2891f0e390d4e78a8c4356b9c9b8145c2208030d66b34f04862112436ed6eb | Python | 7,117 | 232 | # Licensed to the Apache Software Foundation (ASF) under one
# or more contributor license agreements. See the NOTICE file
# distributed with this work for additional information
# regarding copyright ownership. The ASF licenses this file
# to you under the Apache License, Version 2.0 (the
# "License"); you may not u... |
ed3cd25f0dfc2dc4d2db6fa8f0634a75e590c38b34a10b86c567b5ad665cf47e | Python | 7,117 | 207 | """Calculate RDMs based on Mahalanobis distance.
For a given subject:
- load epochs for a stream (single or dual)
- perform baseline correction
- create a design matrix where each trial is predicted by the condition of that
trial. For example, if there are conditions 1, 2, and 3, the design matrix
has three column... |
b821c7a3e61c73babefb216644a99c3cda86b468e8c7bf323fff3e60cbc6c5a2 | Python | 7,121 | 190 | import tensorflow as tf
# tf.enable_v2_behavior()
import pandas as pd
from tensorflow.keras.models import Model
import numpy as np
from sklearn.model_selection import train_test_split, KFold
from sklearn.metrics import accuracy_score
# from keras import optimizers
import os
import random
from sklearn.model_se... |
24586bc4e2a043f3f4ddb6e40a99d6baea8aa1aba4981f447c3bfa397c01adb2 | Python | 7,125 | 188 | import pandas as pd
from tensorflow.keras.models import Model
import numpy as np
from sklearn.model_selection import train_test_split, KFold
from sklearn.metrics import accuracy_score
from tensorflow.keras.optimizers import Adam, SGD
import os
import random
from sklearn.model_selection import train_test_split... |
90f3eb5ea104534432d88c60b3a6518ab6e44572b76f9f7edc76a486301fbdd0 | Python | 7,126 | 190 | # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
# # #
# # # Render a 2d video of the input locations; velocities
# # # and of the filter's estimated velocities; and of the
# # # inferred motion strengths.
# # #
# # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
import numpy as np
... |
8d77b886b61d274ae5d50697043ab32fe55a9a23d5377903d67f1328c21a1dac | Python | 7,127 | 245 | def load_dnn_data(args, cond_idx):
"""Load the DNN feature maps of the training and test images.
Parameters
----------
args : Namespace
Input arguments.
cond_idx : int
Indices of the used image conditions.
Returns
-------
X_train : dict of float
Training images feature maps.
X_test : dict of float
Te... |
079851483eea92014b9bbf3f8255a66101caf91d1e973ad16789b942cac9d721 | Python | 7,130 | 226 | """
Provenance helpers shared by storage engines and the simulation result writer.
Exposes ``new_storage_id``, ``iso_now``, ``collect_plugin_manifest``,
``collect_host_info``, and ``build_root_metadata`` (the canonical assembler of
the root-level provenance bundle an engine writes on ``create()``), plus the
``encode_a... |
86ffad60358e26c66d415c82bdfc9f3f86689704b4a4462812b9f8cb21535e84 | Python | 7,131 | 241 | import math
import numpy as np
import scipy
import scipy.sparse as sp
from scipy.special import iv
from sklearn import preprocessing
class HeatKernel(object):
def __init__(self, t=0.5, theta0=0.6, theta1=0.4):
self.t = t
self.theta0 = theta0
self.theta1 = theta1
def prop_adjacency(sel... |
fd3af01117c38fab9c150e74f31cbac6ed1d43be427b0d07e4ef8197f4737f0e | Python | 7,135 | 168 | """Reinhard (2001) colour transfer in Ruderman Lab space.
Pure DataArray layer: every function takes and returns ``xr.DataArray`` (or
numpy), stays lazy, touches no ``sdata``, and exposes no public surface. The
thin ``sdata`` wrapper lives in :mod:`._normalize`.
``params`` arguments must already be resolved by :func:... |
76c5fb5e2add93525c25454c37de23cbf5e72c707e8ca18ad7f9213dffb3e4ab | Python | 7,137 | 150 | """
Properties for the CamCoil implementation. These include:
1. ACCEPTED_RES_ONE
2. pH2_prop
3. pH7_prop
4. weights
5. weights_LFP
"""
import hashlib
from functools import partial
from numpy import nan as np_nan
from collections import namedtuple
# Add documentation to the NamedTuple.
__pdoc__ =... |
34433dd0598e5943708c7139702468727af0f76f35ecc46b402fef3ac36e3bf4 | Python | 7,138 | 138 | import numpy as np
import shutil
import MDAnalysis as mda
from MDAnalysis.analysis import pca, align
from MDAnalysis.coordinates.memory import MemoryReader
from MDAnalysis.analysis.base import AnalysisFromFunction
import uuid
import os
from sklearn.decomposition import PCA
import os
import uuid
print('imported mod... |
8ab9f0ec09393a7229d746ded65d6bea30f1284e362aae51fc0cf3b6a71027c8 | Python | 7,140 | 193 | # Licensed to the Apache Software Foundation (ASF) under one
# or more contributor license agreements. See the NOTICE file
# distributed with this work for additional information
# regarding copyright ownership. The ASF licenses this file
# to you under the Apache License, Version 2.0 (the
# "License"); you may not u... |
6aff3a9a2a287a755885dd5ab7a7dd3241420959c67da42ef423b2fcd17316b8 | Python | 7,141 | 166 | # -*- coding: utf-8 -*-
from figureflow import figure
import seaborn as sb
import numpy as np
import os
import importlib
importlib.reload(figure)
Figure = figure.Figure
input_folder = os.path.dirname(os.path.abspath(__file__))
figure = Figure(input_folder,number=10, dpi=600, width=5)
figure.cr... |
a7975b919a7fa8b6cd1b64319ff31c330dd60c663a734dfa00d802f994c3f2b8 | Python | 7,143 | 243 | import tensorflow as tf
from tensorflow import keras
from keras import optimizers
from tensorflow.keras import layers
import numpy as np
np.set_printoptions(precision=5)
import matplotlib.pyplot as plt
import pandas as pd
pd.options.display.float_format = '{:,.5f}'.format
import scipy as sp
from scipy import stats
imp... |
0e051c1d0dbc7bed0f587da9f8c0d7e86bd6e4e244e10b5fec923c3da34a4e94 | Python | 7,144 | 162 | # encoding: utf-8
# copyright: GeoDS Lab, University of Wisconsin-Madison
# authors: Yuhao Kang, Song Gao, Jinmeng Rao
import pandas as pd
import numpy as np
import os
import geopandas as gpd
import psycopg2
import argparse
import datetime
parser = argparse.ArgumentParser(description='Month, start day, end day')
parse... |
b290d4906ef3134904a528185a4bfeda77eabfbde77bb9b72597135bff00bb98 | Python | 7,144 | 185 | from smile.experiment import Experiment
from smile.state import Wait, Loop, Parallel, Meanwhile, UntilDone, Serial, \
Done, Debug
from smile.video import ProgressBar, Image, RstDocument, ButtonPress, Button, \
Slider, Rectangle, TextInput, Label, Ellipse,\
... |
d19a7d98887e38dc0e413bd554447c623c44ef7172254d279ee16756f3fa06f2 | Python | 7,144 | 171 | # TODO this script was adapted to the new data classes, but is not yet tested.
# If you succesfully un it, remove this comment
from meld_classifier.experiment import Experiment
from meld_classifier.paths import EXPERIMENT_PATH
from meld_classifier.network_tools import ensemble_models
from meld_classifier.evaluation imp... |
944dd3e819cbb61f29dae0088c534f0bf253c385913416f5ff46711a09d21f1f | Python | 7,145 | 230 | """Function for computing walks in a graph."""
import networkx as nx
from networkx.utils import not_implemented_for, py_random_state
__all__ = ["number_of_walks", "random_walk"]
@nx._dispatchable
def number_of_walks(G, walk_length):
"""Returns the number of walks connecting each pair of nodes in `G`
A *wal... |
d9a15c5c731124757ba2cb691b37770a9c096d140ae9ae8985362b1b9c6b2237 | Python | 7,149 | 195 | import numpy as np
import synthetic_spatial_datagen
def test_generate_test_dist_matrix():
# use default parameters
sample_dist_mat = synthetic_spatial_datagen.generate_test_dist_matrix()
# assert matrix symmetry
assert np.allclose(sample_dist_mat.loc[np.arange(1, 301), np.arange(1, 301)].values,
... |
fcbe53baa1f64639e3b4b1ad7fa63a7403f1ef2b10f6e02ff8df8b63a408a63b | Python | 7,152 | 205 | """
The sorts of the columns of a query's result, from the query itself.
A column of a result holds the values of a variable of the head of the
query. When the variable is an argument of a predicate declaring its
``arguments`` in the engine's configuration, in the body of the query,
the column holds values of the sort... |
131c62a8df593d7fc1ae182e2c47221bddcaff1e79df930198183aa8c7c7b15c | Python | 7,155 | 234 | import json
import os.path as osp
import time
import numpy as np
import scipy.sparse as sp
import torch
from sklearn.preprocessing import StandardScaler
from cogdl.data import Graph, Dataset
from cogdl.utils import download_url, Accuracy, MultiLabelMicroF1, BCEWithLogitsLoss, CrossEntropyLoss
from .planetoid_data imp... |
75d51c589e286758952dda2974d27704b2b41bf70cfb36b42fc21e0f38c954d0 | Python | 7,155 | 215 | import copy
import os
import tempfile
from datetime import timedelta
import pytest
import torch
import torch.distributed as dist
import torch.multiprocessing as mp
from spikingjelly.activation_based import functional, layer, neuron
from spikingjelly.activation_based.distributed.tensor_parallel import (
ChannelSha... |
0da96ee8fdc99ccd0bd4cacc0507b2f608cfbed21171b50427fa90e9ac707661 | Python | 7,156 | 247 | # ----------------------------------------------------------------------------
# build_sample_matrix.py
# Author: Antoine Beauchamp
# Created: June 22nd, 2022
"""
Build a gene-by-sample expression matrix.
Description
-----------
This is a script to process the Allen Human Brain Atlas microarray gene
expression data... |
bca06551681c0c5daff8a56427ec53ddf3e1081e3b9d501211424fbc42a061f5 | Python | 7,159 | 225 | # -*- coding: utf-8 -*-
"""Airy module
Generates the Airy beam shape based on experimental or theoretical parameters
"""
# Created on Tue Apr 7 10:01:32 2020
# Contributions and Changelog accessed via a private git repository:
# https://github.com/philipwijesinghe/deep-learning-lsm.git
# philip.wijesinghe@gmail.com... |
e8b893825b245775820b4a459892c8624094804424b9d9aae17a9cac4ae74b0b | Python | 7,159 | 214 | """Tests for squidpy._validators."""
from __future__ import annotations
from unittest.mock import MagicMock
import pytest
from squidpy._validators import (
assert_in_range,
assert_isinstance,
assert_key_in_adata,
assert_key_in_sdata,
assert_non_empty_sequence,
assert_non_negative,
assert... |
367d0728bfd34d1bf86911fd12d4a0f44e2328cce7222b2a6b1ee5236167f718 | Python | 7,165 | 211 | ## To be continued....
import pandas as pd
import numpy as np
import glob
import os
import nilearn.signal
import matplotlib.pyplot as plt
from scipy import stats
import pingouin as pg
import statsmodels.api as sm
import seaborn as sns
def loadsnr(snrcoil, snrtrue):
def reshapesnr(snr_all):
mz=snr_all... |
ecc34f66a2bd596c590b74e0cef3011fe44f4653852e9c2af76ee59335225232 | Python | 7,167 | 186 | # -*- coding: utf-8 -*-
from __future__ import absolute_import
import logging
import os
from pip._internal.cache import WheelCache
from pip._internal.cli import cmdoptions
from pip._internal.cli.base_command import RequirementCommand
from pip._internal.exceptions import CommandError, PreviousBuildDirError
from pip._i... |
acc4df9845f176e20dc308dbf03c90357c63d38ccd12771ade5b107555c30fed | Python | 7,169 | 193 | #!/usr/bin/env python3
import os
import numpy as np
from param_stamp import get_param_stamp_from_args
from visual import visual_plt as my_plt
import main_task_free
from param_values import check_for_errors,set_default_values
import options
import utils
## Parameter-values to compare
c_list = [0.001, 0.01, 0.1, 1., 10... |
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