repo stringlengths 2 99 | file stringlengths 13 225 | code stringlengths 0 18.3M | file_length int64 0 18.3M | avg_line_length float64 0 1.36M | max_line_length int64 0 4.26M | extension_type stringclasses 1
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brainiak | brainiak-master/tests/matnormal/test_matnormal_logp_conditional.py | import numpy as np
from numpy.testing import assert_allclose
from scipy.stats import wishart, multivariate_normal
import tensorflow as tf
from brainiak.matnormal.utils import rmn
from brainiak.matnormal.matnormal_likelihoods import (
matnorm_logp_conditional_col,
matnorm_logp_conditional_row,
)
from brainiak.m... | 2,215 | 27.050633 | 76 | py |
brainiak | brainiak-master/tests/matnormal/test_matnormal_regression.py | import pytest
import numpy as np
from scipy.stats import norm, wishart, pearsonr
from brainiak.matnormal.covs import (
CovIdentity,
CovUnconstrainedCholesky,
CovUnconstrainedInvCholesky,
CovDiagonal,
)
from brainiak.matnormal.regression import MatnormalRegression
from brainiak.matnormal.utils import rm... | 4,328 | 26.05625 | 76 | py |
brainiak | brainiak-master/tests/matnormal/test_matnormal_utils.py | from brainiak.matnormal.utils import (pack_trainable_vars,
unpack_trainable_vars,
flatten_cholesky_unique,
unflatten_cholesky_unique)
import tensorflow as tf
import numpy as np
import numpy.testing as npt
... | 1,059 | 35.551724 | 64 | py |
brainiak | brainiak-master/tests/matnormal/test_matnormal_rsa.py | from brainiak.matnormal.mnrsa import MNRSA
from brainiak.utils.utils import cov2corr
from brainiak.matnormal.covs import CovIdentity, CovDiagonal
from scipy.stats import norm
from brainiak.matnormal.utils import rmn
import numpy as np
def gen_U_nips2016_example():
n_C = 16
U = np.zeros([n_C, n_C])
U = np... | 1,934 | 24.12987 | 75 | py |
brainiak | brainiak-master/tests/factoranalysis/test_htfa.py | # Copyright 2016 Intel Corporation
#
# 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 applicable law or agreed to... | 5,283 | 30.266272 | 78 | py |
brainiak | brainiak-master/tests/factoranalysis/test_tfa.py | # Copyright 2016 Intel Corporation
#
# 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 applicable law or agreed to... | 3,661 | 31.990991 | 75 | py |
brainiak | brainiak-master/tests/eventseg/test_event.py | from brainiak.eventseg.event import EventSegment
from scipy.special import comb
import numpy as np
import pytest
from sklearn.exceptions import NotFittedError
def test_create_event_segmentation():
es = EventSegment(5)
assert es, "Invalid EventSegment instance"
def test_fit_shapes():
K = 5
V = 3
... | 6,744 | 32.063725 | 78 | py |
brainiak | brainiak-master/tests/fcma/test_mvpa_voxel_selection.py | # Copyright 2016 Intel Corporation
#
# 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 applicable law or agreed to... | 1,972 | 34.872727 | 75 | py |
brainiak | brainiak-master/tests/fcma/test_util.py | # Copyright 2016 Intel Corporation
#
# 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 applicable law or agreed to... | 2,131 | 34.533333 | 76 | py |
brainiak | brainiak-master/tests/fcma/test_classification.py | # Copyright 2016 Intel Corporation
#
# 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 applicable law or agreed to... | 10,698 | 46.977578 | 79 | py |
brainiak | brainiak-master/tests/fcma/test_preprocessing.py | # Copyright 2016 Intel Corporation
#
# 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 applicable law or agreed to... | 5,069 | 45.090909 | 79 | py |
brainiak | brainiak-master/tests/fcma/test_voxel_selection.py | # Copyright 2016 Intel Corporation
#
# 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 applicable law or agreed to... | 4,790 | 38.595041 | 79 | py |
brainiak | brainiak-master/tests/funcalign/test_srm_distributed.py | # Copyright 2016 Intel Corporation
#
# 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 applicable law or agreed to... | 5,271 | 32.794872 | 77 | py |
brainiak | brainiak-master/tests/funcalign/test_fastsrm.py | import os
import tempfile
import numpy as np
import pytest
from numpy.testing import assert_array_almost_equal
from sklearn.exceptions import NotFittedError
from brainiak.funcalign.fastsrm import (
FastSRM, _compute_and_save_corr_mat, _compute_and_save_subject_basis,
_compute_basis_subject_online, _reduced_sp... | 34,458 | 36.414767 | 79 | py |
brainiak | brainiak-master/tests/funcalign/test_rsrm.py | # Copyright 2016 Intel Corporation
#
# 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 applicable law or agreed to... | 5,042 | 37.496183 | 78 | py |
brainiak | brainiak-master/tests/funcalign/test_srm.py | # Copyright 2016 Intel Corporation
#
# 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 applicable law or agreed to... | 11,513 | 34.98125 | 79 | py |
brainiak | brainiak-master/tests/funcalign/test_sssrm.py | # Copyright 2016 Intel Corporation
#
# 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 applicable law or agreed to... | 10,092 | 36.381481 | 79 | py |
brainiak | brainiak-master/tests/searchlight/test_searchlight.py | # Copyright 2016 Intel Corporation
#
# 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 applicable law or agreed to... | 10,021 | 32.075908 | 75 | py |
brainiak | brainiak-master/tests/reprsimil/test_gbrsa.py | # Copyright 2016 Mingbo Cai, Princeton Neuroscience Instititute,
# Princeton University
#
# 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... | 27,071 | 41.903328 | 79 | py |
brainiak | brainiak-master/tests/reprsimil/test_brsa.py | # Copyright 2016 Mingbo Cai, Princeton Neuroscience Instititute,
# Princeton University
#
# 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... | 29,837 | 44.763804 | 79 | py |
brainiak | brainiak-master/tests/reconstruct/test_iem.py | # Copyright 2018 David Huberdeau & Peter Kok
#
# 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 applicable law or... | 19,162 | 34.161468 | 77 | py |
brainiak | brainiak-master/tests/utils/test_fmrisim.py | # Copyright 2016 Intel Corporation
#
# 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 applicable law or agreed to... | 37,943 | 40.514223 | 79 | py |
brainiak | brainiak-master/tests/utils/test_fmrisim_real_time.py | # Copyright 2016 Intel Corporation
#
# 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 applicable law or agreed to... | 4,975 | 27.597701 | 77 | py |
brainiak | brainiak-master/tests/utils/test_utils.py | # Copyright 2016 Intel Corporation
#
# 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 applicable law or agreed to... | 17,046 | 36.383772 | 79 | py |
brainiak | brainiak-master/tests/hyperparamopt/test_hpo.py | # Copyright 2016 Intel Corporation
#
# 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 applicable law or agreed to... | 3,042 | 33.977011 | 78 | py |
brainiak | brainiak-master/docs/conf.py | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
#
# toolkit documentation build configuration file, created by
# sphinx-quickstart on Thu Mar 17 16:45:35 2016.
#
# This file is execfile()d with the current directory set to its
# containing dir.
#
# Note that not all possible configuration values are present in this
# au... | 9,448 | 30.708054 | 79 | py |
DMGI | DMGI-master/main.py | import numpy as np
np.random.seed(0)
import torch
torch.autograd.set_detect_anomaly(True)
torch.manual_seed(0)
torch.cuda.manual_seed_all(0)
torch.backends.cudnn.deterministic = True
torch.backends.cudnn.benchmark = False
import argparse
def parse_args():
# input arguments
parser = argparse.ArgumentParser(desc... | 2,131 | 33.95082 | 84 | py |
DMGI | DMGI-master/evaluate.py | import torch
torch.manual_seed(0)
torch.cuda.manual_seed_all(0)
torch.backends.cudnn.deterministic = True
torch.backends.cudnn.benchmark = False
from models import LogReg
import torch.nn as nn
import numpy as np
np.random.seed(0)
from sklearn.metrics import f1_score
from sklearn.cluster import KMeans
from sklearn.metri... | 4,571 | 34.71875 | 115 | py |
DMGI | DMGI-master/embedder.py | import time
import numpy as np
import torch
from utils import process
import torch.nn as nn
from layers import AvgReadout
class embedder:
def __init__(self, args):
args.batch_size = 1
args.sparse = True
args.metapaths_list = args.metapaths.split(",")
args.gpu_num_ = args.gpu_num
... | 1,994 | 35.272727 | 108 | py |
DMGI | DMGI-master/models/logreg.py | import torch
torch.manual_seed(0)
torch.cuda.manual_seed_all(0)
torch.backends.cudnn.deterministic = True
torch.backends.cudnn.benchmark = False
import torch.nn as nn
import torch.nn.functional as F
class LogReg(nn.Module):
def __init__(self, ft_in, nb_classes):
super(LogReg, self).__init__()
self.... | 697 | 24.851852 | 56 | py |
DMGI | DMGI-master/models/DMGI.py | import torch
torch.manual_seed(0)
torch.cuda.manual_seed_all(0)
torch.backends.cudnn.deterministic = True
torch.backends.cudnn.benchmark = False
import torch.nn as nn
from embedder import embedder
from layers import GCN, Discriminator, Attention
import numpy as np
np.random.seed(0)
from evaluate import evaluate
from mo... | 5,373 | 34.826667 | 146 | py |
DMGI | DMGI-master/models/DGI.py | # Code based on https://github.com/PetarV-/DGI/blob/master/models/dgi.py
import torch
torch.manual_seed(0)
torch.cuda.manual_seed_all(0)
torch.backends.cudnn.deterministic = True
torch.backends.cudnn.benchmark = False
import torch.nn as nn
from embedder import embedder
from layers import GCN, Discriminator
import numpy... | 3,756 | 35.125 | 139 | py |
DMGI | DMGI-master/models/__init__.py | from .logreg import LogReg
from .DMGI import DMGI
from .DGI import DGI
| 71 | 17 | 26 | py |
DMGI | DMGI-master/layers/discriminator.py | import torch
torch.manual_seed(0)
torch.cuda.manual_seed_all(0)
torch.backends.cudnn.deterministic = True
torch.backends.cudnn.benchmark = False
import torch.nn as nn
class Discriminator(nn.Module):
def __init__(self, n_h):
super(Discriminator, self).__init__()
self.f_k_bilinear = nn.Bilinear(n_h,... | 1,143 | 30.777778 | 87 | py |
DMGI | DMGI-master/layers/readout.py | import torch
torch.manual_seed(0)
torch.cuda.manual_seed_all(0)
torch.backends.cudnn.deterministic = True
torch.backends.cudnn.benchmark = False
import torch.nn as nn
class AvgReadout(nn.Module):
def __init__(self):
super(AvgReadout, self).__init__()
def forward(self, seq):
return torch.mean(s... | 326 | 24.153846 | 42 | py |
DMGI | DMGI-master/layers/gcn.py | import torch
torch.manual_seed(0)
torch.cuda.manual_seed_all(0)
torch.backends.cudnn.deterministic = True
torch.backends.cudnn.benchmark = False
import torch.nn as nn
import torch.nn.functional as F
import pdb
import math
class GCN(nn.Module):
def __init__(self, in_ft, out_ft, act, drop_prob, isBias=False):
... | 2,239 | 28.473684 | 76 | py |
DMGI | DMGI-master/layers/__init__.py | from .gcn import GCN
from .readout import AvgReadout
from .discriminator import Discriminator
from .attention import Attention
| 128 | 20.5 | 40 | py |
DMGI | DMGI-master/layers/attention.py | import torch.nn as nn
import torch
import torch.nn.functional as F
class Attention(nn.Module):
def __init__(self, args):
super(Attention, self).__init__()
self.args = args
self.A = nn.ModuleList([nn.Linear(args.hid_units, 1) for _ in range(args.nb_graphs)])
self.weight_init()
... | 1,865 | 37.875 | 114 | py |
DMGI | DMGI-master/utils/__init__.py | 0 | 0 | 0 | py | |
DMGI | DMGI-master/utils/process.py | import numpy as np
import pickle as pkl
import networkx as nx
import scipy.sparse as sp
import sys
import torch
import torch.nn as nn
import scipy.io as sio
import pdb
def load_data_dblp(args):
dataset = args.dataset
metapaths = args.metapaths_list
sc = args.sc
if dataset == 'acm':
data = sio.... | 8,988 | 33.178707 | 110 | py |
DMGI | DMGI-master/data/preprocess_dblp.py | import pdb
import sys
from nltk.corpus import stopwords
import re
import numpy as np
import pandas as pd
import pickle as pkl
import pdb
import sys
from nltk.corpus import stopwords
import re
import time
num_train = int(sys.argv[1])
raw_data_filename = 'dblp.txt'
top_confs = ['icml','aaai','ijcai','sigkdd','internat... | 14,440 | 36.028205 | 267 | py |
EEND | EEND-main/eend/infer.py | #!/usr/bin/env python3
# Copyright 2019 Hitachi, Ltd. (author: Yusuke Fujita)
# Copyright 2022 Brno University of Technology (author: Federico Landini)
# Licensed under the MIT license.
from backend.models import (
average_checkpoints,
get_model,
)
from common_utils.diarization_dataset import KaldiDiarization... | 10,400 | 37.098901 | 79 | py |
EEND | EEND-main/eend/train.py | #!/usr/bin/env python3
# Copyright 2019 Hitachi, Ltd. (author: Yusuke Fujita)
# Copyright 2022 Brno University of Technology (authors: Federico Landini)
# Licensed under the MIT license.
from backend.models import (
average_checkpoints,
get_model,
load_checkpoint,
pad_labels,
pad_sequence,
sa... | 13,614 | 39.885886 | 79 | py |
EEND | EEND-main/eend/backend/losses.py | #!/usr/bin/env python3
# Copyright 2019 Hitachi, Ltd. (author: Yusuke Fujita)
# Copyright 2022 Brno University of Technology (authors: Federico Landini, Lukas Burget, Mireia Diez)
# Copyright 2022 AUDIAS Universidad Autonoma de Madrid (author: Alicia Lozano-Diez)
# Licensed under the MIT license.
from itertools impor... | 3,481 | 43.641026 | 101 | py |
EEND | EEND-main/eend/backend/updater.py | #!/usr/bin/env python3
# Copyright 2022 Brno University of Technology (author: Federico Landini)
# Licensed under the MIT license.
import torch.optim as optim
from torch.nn import Module
from types import SimpleNamespace
from typing import Any, Dict
class NoamOpt:
"Optim wrapper that implements rate."
def _... | 2,593 | 30.253012 | 79 | py |
EEND | EEND-main/eend/backend/models.py | #!/usr/bin/env python3
# Copyright 2019 Hitachi, Ltd. (author: Yusuke Fujita)
# Copyright 2022 Brno University of Technology (author: Federico Landini)
# Licensed under the MIT license.
from os.path import isfile, join
from backend.losses import (
pit_loss_multispk,
vad_loss,
)
from backend.updater import (
... | 18,812 | 33.519266 | 79 | py |
EEND | EEND-main/eend/backend/__init__.py | 0 | 0 | 0 | py | |
EEND | EEND-main/eend/common_utils/features.py | #!/usr/bin/env python3
# Copyright 2019 Hitachi, Ltd. (author: Yusuke Fujita)
# Copyright 2022 Brno University of Technology (author: Federico Landini)
# Licensed under the MIT license.
from common_utils.kaldi_data import KaldiData
from typing import Callable, Tuple
import numpy as np
import librosa
def get_labeled... | 5,743 | 31.089385 | 78 | py |
EEND | EEND-main/eend/common_utils/kaldi_data.py | #!/usr/bin/env python3
# Copyright 2019 Hitachi, Ltd. (author: Yusuke Fujita)
# Copyright 2022 Brno University of Technology (author: Federico Landini)
# Licensed under the MIT license.
# This library provides utilities for kaldi-style data directory.
import io
import numpy as np
import os
import soundfile as sf
im... | 3,928 | 30.685484 | 78 | py |
EEND | EEND-main/eend/common_utils/diarization_dataset.py | #!/usr/bin/env python3
# Copyright 2019 Hitachi, Ltd. (author: Yusuke Fujita)
# Copyright 2022 Brno University of Technology (author: Federico Landini)
# Licensed under the MIT license.
import common_utils.features as features
import common_utils.kaldi_data as kaldi_data
import numpy as np
import torch
from typing im... | 3,895 | 31.739496 | 76 | py |
EEND | EEND-main/eend/common_utils/gpu_utils.py | #!/usr/bin/env python3
# Copyright 2022 Brno University of Technology (author: Federico Landini)
# Licensed under the MIT license.
from safe_gpu import safe_gpu
def use_single_gpu(gpus_qty: int) -> safe_gpu.GPUOwner:
assert gpus_qty < 2, "Multi-GPU still not available."
gpu_owner = safe_gpu.GPUOwner(nb_gpus... | 352 | 26.153846 | 73 | py |
EEND | EEND-main/eend/common_utils/metrics.py | #!/usr/bin/env python3
# Copyright 2022 Brno University of Technology (author: Federico Landini, Mireia Diez)
# Licensed under the MIT license.
from typing import Dict
import torch
def calculate_metrics(
target: torch.Tensor,
decisions: torch.Tensor,
threshold: float = 0.5,
round_digits: int = 2,
) ... | 4,438 | 36.940171 | 128 | py |
ICWS2021-quantum-classical-microservices | ICWS2021-quantum-classical-microservices-main/utils_tsp.py | # imports
import numpy as np
import networkx as nx
import dimod
import dwave_networkx as dnx
# helper function to compute distance from route
def get_distance(route, data):
"""
find distance for given route = [0, 4, 3, 1, 2] and original data
"""
# get the total distance without return
total_dist ... | 4,549 | 33.469697 | 96 | py |
ICWS2021-quantum-classical-microservices | ICWS2021-quantum-classical-microservices-main/api/main.py | from flask import Flask, request, jsonify, send_file
from flask_cors import CORS
from gate import *
from annealing import *
gate_machines_arn= { "riggeti_aspen8":"arn:aws:braket:::device/qpu/rigetti/Aspen-8",
"riggeti_aspen9":"arn:aws:braket:::device/qpu/rigetti/Aspen-9",
"ionq":"arn:a... | 2,787 | 27.742268 | 127 | py |
ICWS2021-quantum-classical-microservices | ICWS2021-quantum-classical-microservices-main/api/annealing.py | import boto3
from braket.aws import AwsDevice
from braket.ocean_plugin import BraketSampler, BraketDWaveSampler
import numpy as np
import networkx as nx
import dimod
import dwave_networkx as dnx
from dimod.binary_quadratic_model import BinaryQuadraticModel
from dwave.system.composites import EmbeddingComposite
import... | 3,019 | 26.962963 | 101 | py |
ICWS2021-quantum-classical-microservices | ICWS2021-quantum-classical-microservices-main/api/utils_tsp.py | # imports
import numpy as np
import networkx as nx
import dimod
import dwave_networkx as dnx
# helper function to compute distance from route
def get_distance(route, data):
"""
find distance for given route = [0, 4, 3, 1, 2] and original data
"""
# get the total distance without return
total_dist ... | 3,506 | 32.721154 | 96 | py |
ICWS2021-quantum-classical-microservices | ICWS2021-quantum-classical-microservices-main/api/gate.py | import time
import math
# AWS imports: Import Braket SDK modules
import boto3
from braket.circuits import Circuit, Gate, Observable
from braket.devices import LocalSimulator
from braket.aws import AwsDevice
n_ancilla = 6
n_eigenvector = 8
def recover_task_result(task_load):
# recover task
sleep_times = 0
... | 4,822 | 33.205674 | 96 | py |
strees | strees-master/charge.py | import sys
import os, os.path
from optparse import OptionParser
from matplotlib.colors import LogNorm
from numpy import *
import h5py
try:
import pylab
except ImportError:
pass
X, Y, Z = 0, 1, 2
def main():
parser = OptionParser()
parser.add_option("--show", dest="show", action="store_true",
... | 2,129 | 23.204545 | 72 | py |
strees | strees-master/grow_tree.py | """ grow_tree.py is the main module of the code and the one you invoke from
the command line to start a simulation.
To start a simulation with parameters read from a file simulation.ini
simply invoke this module as::
python grow_tree.py simulation.ini
The output will be written in a file name simulation.h5 with ... | 13,725 | 28.32906 | 82 | py |
strees | strees-master/tree.py | """ This module contains the data representation for the structure of trees.
Note that we separate the structure of the branched tree from its
realization, that would contain things such as charges, positions, etc.
that evolve even when the structure is fixed.
"""
from random import random as uniform
from scipy.sparse ... | 11,005 | 26.722922 | 80 | py |
strees | strees-master/refinement.py | """ This module implement the structure of oct-trees for the implementation
of the Fast Multipolar Method (FMM).
. note::
Most of this code is not used, since we disabled the use of the FMM for
the simulations reported in the paper. However, the simulated tree is
embedded in a bounding box defined by a :class... | 14,659 | 29.541667 | 80 | py |
strees | strees-master/solve_tree.py | import hotshot, hotshot.stats
import time
from numpy import *
import pylab
from matplotlib import cm
import tree
import mpolar
from refinement import Box
def main():
p = 5
k = 50000
t0 = time.time()
tr = tree.random_branching_tree(k, 0.05)
r = tree.sample_endpoints(tr)
r0 = amin(r... | 2,010 | 19.731959 | 66 | py |
strees | strees-master/relax_tree.py | import time
from numpy import *
from scipy.sparse import lil_matrix, csr_matrix
from scipy.integrate import odeint, ode
import pylab
from matplotlib import cm
from mpl_toolkits.mplot3d import Axes3D
import tree
import mpolar
from refinement import Box
def main():
p = 5
k = 5000
tr = tree.random_branchi... | 4,196 | 23.982143 | 75 | py |
strees | strees-master/datafile.py | """ This module contains the code to save/retrieve the state of a simulation.
"""
import sys
import time
from contextlib import closing
from numpy import *
import h5py
from tree import Tree
class DataFile(object):
""" Class to store and retrieve simulation data. """
def __init__(self, fname, parameters):
... | 2,051 | 26.72973 | 80 | py |
strees | strees-master/errors.py | """ Calculation of the errors in solveing the potential and dq/dt. """
from numpy import *
from numpy.linalg import norm
import h5py
import pylab
from refinement import Box, containing_box
import mpolar
import datafile
from plotter import plot_projections, bounding_box
def main():
from optparse import OptionPars... | 2,418 | 29.2375 | 73 | py |
strees | strees-master/expand.py | import sys
from readinput import expand_input
import parameters
def main():
for ifile in sys.argv[1:]:
expand_input(ifile, parameters)
if __name__ == '__main__':
main()
| 191 | 11.8 | 39 | py |
strees | strees-master/readinput.py | """ This is an auxiliary module for reading input .ini files.
It is based on Python's stdlib
`ConfigParser <http://docs.python.org/2/library/configparser.html/>`_
This module also provides functionality for setting run sets where
one or more of the parameters run over a list of values.
"""
import os, os.path, socket... | 5,485 | 26.707071 | 80 | py |
strees | strees-master/electrodes.py | """ Implementation of electrode geometries with the image charge method.
"""
from numpy import *
X, Y, Z = 0, 1, 2
class Electrode(object):
def __init__(self):
pass
def images(self, r, q):
""" Calculates the images of charges q located at points r.
Returns rimag, qimag. """
r... | 1,946 | 23.037037 | 75 | py |
strees | strees-master/cst.py | """ Implementation of the charge simulation technique. """
import sys
from numpy import *
import pylab
import h5py
from scipy.sparse.linalg import LinearOperator, bicgstab, bicg, gmres
from refinement import Box, containing_box
import mpolar
from plotter import bounding_box, plot_projections
def paraboloid(a, ztip,... | 2,745 | 26.46 | 79 | py |
strees | strees-master/contexttimer.py | """ Using the with keyword to time code snippets. """
from contextlib import contextmanager
import time
import sys
# @contextmanager
# def ContextTimer(name="Unknown", outf=sys.stdout):
# t0 = time.time()
# outf.write("[%s ..." % name)
# outf.flush()
# yield
# t1 = time.time()
# outf.wr... | 1,093 | 18.535714 | 69 | py |
strees | strees-master/parameters.py | """ This is the parameter description file. Basically it provides a namespace
where we store a function per input parameter. Each function receives a string
and is responsible for converting to the appropriate type, checking for
allowed values. The docstring of the function is a description of the
parameter. """
fr... | 3,918 | 22.467066 | 102 | py |
strees | strees-master/angles.py | """ Calculation of the branching angles of a tree. """
from numpy import *
from numpy.linalg import norm
import h5py
import datafile
def branching_angles(tr, r, **kwargs):
""" Returns an array with the branching angles of the tree. """
ibranch = tr.branches()
angles = zeros(ibranch.shape)
for i... | 3,313 | 28.070175 | 80 | py |
strees | strees-master/plotter.py | import sys
import os, os.path
from optparse import OptionParser
from matplotlib.colors import LogNorm
import matplotlib as mpl
import scipy.constants as co
from scipy.stats import scoreatpercentile
from numpy import *
import h5py
import datafile
import cmaps
try:
import pylab
from mpl_toolkits.mplot3d import ... | 11,230 | 28.555263 | 82 | py |
strees | strees-master/cmaps.py | from matplotlib.colors import Colormap
import matplotlib.cm as cm
import matplotlib.colors as colors
from numpy import where
def get_colormap(cmap, dynamic=False):
""" If cmap is not None, sets the colormap by te specified string"""
cmaps = {'hot': cm.hot,
'autumn': cm.autumn,
'bone... | 6,305 | 34.426966 | 97 | py |
strees | strees-master/branch.py | """ Extract the shape of a branch.
Mostly useful in single-branch simulations."""
from numpy import *
from numpy.linalg import norm
from scipy.optimize import curve_fit
import h5py
import pylab
import datafile
def extract_branch(tr, r, **kwargs):
""" an array with the distances between segments in the two branc... | 2,815 | 22.864407 | 80 | py |
strees | strees-master/submit.py | """ A python script to submit to the qsub queue. """
import sys
import os
from optparse import OptionParser
from subprocess import call
DEF_QUEUE = 'exe-x86_64'
def encode_envlist(d):
return ','.join('%s=%s' % (key, item) for key, item in d.iteritems())
def submit(ifile, queue, onlyprint=False):
mypath = o... | 2,385 | 26.744186 | 86 | py |
strees | strees-master/propagation.py | import sys
import os, os.path
from optparse import OptionParser
from matplotlib.colors import LogNorm
from numpy import *
import h5py
try:
import pylab
except ImportError:
pass
def main():
parser = OptionParser()
parser.add_option("--show", dest="show", action="store_true",
he... | 2,028 | 19.917526 | 72 | py |
strees | strees-master/list.py | import sys
import os, os.path
from optparse import OptionParser
from numpy import *
import h5py
def main():
parser = OptionParser()
(opts, args) = parser.parse_args()
for fname in args:
fp = h5py.File(fname, "r")
main = fp['main']
run_name = main.attrs['run_name']
steps ... | 664 | 19.78125 | 69 | py |
strees | strees-master/src/setup.py | #! /usr/bin/python
import distutils.sysconfig
from distutils.core import setup, Extension
import numpy as np
numod = Extension('mpolar',
sources = ['mpolarmod.c'],
extra_objects = ['misc.o', 'multipol.o', 'efield.o'],
include_dirs = [np.get_include(),
... | 599 | 29 | 71 | py |
strees | strees-master/doc/conf.py | # -*- coding: utf-8 -*-
#
# strees documentation build configuration file, created by
# sphinx-quickstart on Thu Jun 13 15:04:29 2013.
#
# This file is execfile()d with the current directory set to its containing dir.
#
# Note that not all possible configuration values are present in this
# autogenerated file.
#
# All ... | 7,832 | 30.971429 | 80 | py |
COAT | COAT-main/engine.py | # This file is part of COAT, and is distributed under the
# OSI-approved BSD 3-Clause License. See top-level LICENSE file or
# https://github.com/Kitware/COAT/blob/master/LICENSE for details.
import math
import sys
from copy import deepcopy
import torch
from torch.nn.utils import clip_grad_norm_
from tqdm import tqdm... | 7,288 | 39.494444 | 124 | py |
COAT | COAT-main/defaults.py | # This file is part of COAT, and is distributed under the
# OSI-approved BSD 3-Clause License. See top-level LICENSE file or
# https://github.com/Kitware/COAT/blob/master/LICENSE for details.
from yacs.config import CfgNode as CN
_C = CN()
# -------------------------------------------------------- #
# ... | 7,923 | 35.018182 | 141 | py |
COAT | COAT-main/eval_func.py | # This file is part of COAT, and is distributed under the
# OSI-approved BSD 3-Clause License. See top-level LICENSE file or
# https://github.com/Kitware/COAT/blob/master/LICENSE for details.
import os.path as osp
import numpy as np
from scipy.io import loadmat
from sklearn.metrics import average_precision_score
from... | 18,670 | 37.182004 | 98 | py |
COAT | COAT-main/train.py | # This file is part of COAT, and is distributed under the
# OSI-approved BSD 3-Clause License. See top-level LICENSE file or
# https://github.com/Kitware/COAT/blob/master/LICENSE for details.
import argparse
import datetime
import os.path as osp
import time
import torch
import torch.utils.data
from datasets import b... | 5,228 | 32.735484 | 128 | py |
COAT | COAT-main/models/resnet.py | # This file is part of COAT, and is distributed under the
# OSI-approved BSD 3-Clause License. See top-level LICENSE file or
# https://github.com/Kitware/COAT/blob/master/LICENSE for details.
from collections import OrderedDict
import torch.nn.functional as F
import torchvision
from torch import nn
class Backbone(nn.... | 1,800 | 32.351852 | 88 | py |
COAT | COAT-main/models/transformer.py | # This file is part of COAT, and is distributed under the
# OSI-approved BSD 3-Clause License. See top-level LICENSE file or
# https://github.com/Kitware/COAT/blob/master/LICENSE for details.
import math
import random
from functools import reduce
import torch
import torch.nn as nn
import torch.nn.functional as F
from ... | 10,997 | 35.538206 | 135 | py |
COAT | COAT-main/models/coat.py | # This file is part of COAT, and is distributed under the
# OSI-approved BSD 3-Clause License. See top-level LICENSE file or
# https://github.com/Kitware/COAT/blob/master/LICENSE for details.
from copy import deepcopy
import torch
import torch.nn as nn
import torch.nn.functional as F
from torch.nn import init
from tor... | 32,368 | 41.25718 | 153 | py |
COAT | COAT-main/datasets/base.py | # This file is part of COAT, and is distributed under the
# OSI-approved BSD 3-Clause License. See top-level LICENSE file or
# https://github.com/Kitware/COAT/blob/master/LICENSE for details.
import torch
from PIL import Image
class BaseDataset:
"""
Base class of person search dataset.
"""
def __init... | 1,559 | 35.27907 | 89 | py |
COAT | COAT-main/datasets/prw.py | # This file is part of COAT, and is distributed under the
# OSI-approved BSD 3-Clause License. See top-level LICENSE file or
# https://github.com/Kitware/COAT/blob/master/LICENSE for details.
import os.path as osp
import re
import numpy as np
from scipy.io import loadmat
from .base import BaseDataset
class PRW(Bas... | 3,413 | 33.836735 | 85 | py |
COAT | COAT-main/datasets/cuhk_sysu.py | # This file is part of COAT, and is distributed under the
# OSI-approved BSD 3-Clause License. See top-level LICENSE file or
# https://github.com/Kitware/COAT/blob/master/LICENSE for details.
import os.path as osp
import numpy as np
from scipy.io import loadmat
from .base import BaseDataset
class CUHKSYSU(BaseDataset... | 5,228 | 41.860656 | 96 | py |
COAT | COAT-main/datasets/__init__.py | # This file is part of COAT, and is distributed under the
# OSI-approved BSD 3-Clause License. See top-level LICENSE file or
# https://github.com/Kitware/COAT/blob/master/LICENSE for details.
from .build import build_test_loader, build_train_loader
| 250 | 40.833333 | 66 | py |
COAT | COAT-main/datasets/build.py | # This file is part of COAT, and is distributed under the
# OSI-approved BSD 3-Clause License. See top-level LICENSE file or
# https://github.com/Kitware/COAT/blob/master/LICENSE for details.
import torch
from utils.transforms import build_transforms
from utils.utils import create_small_table
from .cuhk_sysu import CU... | 3,537 | 32.695238 | 94 | py |
COAT | COAT-main/loss/softmax_loss.py | # This file is part of COAT, and is distributed under the
# OSI-approved BSD 3-Clause License. See top-level LICENSE file or
# https://github.com/Kitware/COAT/blob/master/LICENSE for details.
import torch
from torch import nn
import torch.nn.functional as F
class SoftmaxLoss(nn.Module):
def __init__(self, cfg):
... | 2,087 | 32.142857 | 98 | py |
COAT | COAT-main/loss/oim.py | # This file is part of COAT, and is distributed under the
# OSI-approved BSD 3-Clause License. See top-level LICENSE file or
# https://github.com/Kitware/COAT/blob/master/LICENSE for details.
import torch
import torch.nn.functional as F
from torch import autograd, nn
class OIM(autograd.Function):
@staticmethod
... | 2,848 | 36 | 97 | py |
COAT | COAT-main/utils/utils.py | # This file is part of COAT, and is distributed under the
# OSI-approved BSD 3-Clause License. See top-level LICENSE file or
# https://github.com/Kitware/COAT/blob/master/LICENSE for details.
import datetime
import errno
import json
import os
import os.path as osp
import pickle
import random
import time
from collectio... | 13,088 | 28.951945 | 99 | py |
COAT | COAT-main/utils/km.py | # This file is part of COAT, and is distributed under the
# OSI-approved BSD 3-Clause License. See top-level LICENSE file or
# https://github.com/Kitware/COAT/blob/master/LICENSE for details.
import random
import numpy as np
zero_threshold = 0.00000001
class KMNode(object):
def __init__(self, id, exception=0, ma... | 4,297 | 27.463576 | 90 | py |
COAT | COAT-main/utils/mask.py | # This file is part of COAT, and is distributed under the
# OSI-approved BSD 3-Clause License. See top-level LICENSE file or
# https://github.com/Kitware/COAT/blob/master/LICENSE for details.
import random
import torch
class exchange_token:
def __init__(self):
pass
def __call__(self, features, mask_b... | 11,890 | 35.47546 | 148 | py |
COAT | COAT-main/utils/transforms.py | # This file is part of COAT, and is distributed under the
# OSI-approved BSD 3-Clause License. See top-level LICENSE file or
# https://github.com/Kitware/COAT/blob/master/LICENSE for details.
import random
import math
import torch
import numpy as np
from copy import deepcopy
from torchvision.transforms import function... | 4,443 | 29.648276 | 130 | py |
keras | keras-master/keras/backend_config.py | # Copyright 2019 The TensorFlow 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 applica... | 4,297 | 27.091503 | 80 | py |
keras | keras-master/keras/metrics_confusion_matrix_test.py | # Copyright 2016 The TensorFlow 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 applica... | 79,387 | 40.827187 | 80 | py |
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