repo_name stringlengths 6 130 | hexsha list | file_path list | code list | apis list | possible_versions list |
|---|---|---|---|---|---|
datlife/CommPy | [
"ab78dd7ae14446b69df4636eb5959c610f715780"
] | [
"commpy/modulation.py"
] | [
"\n# Authors: Veeresh Taranalli <veeresht@gmail.com>\n# License: BSD 3-Clause\n\n\"\"\"\n==================================================\nModulation Demodulation (:mod:`commpy.modulation`)\n==================================================\n\n.. autosummary::\n :toctree: generated/\n\n PSKModem ... | [
[
"numpy.dot",
"numpy.log",
"numpy.log2",
"numpy.sqrt",
"numpy.fft.fft",
"numpy.arange",
"numpy.tile",
"numpy.cos",
"numpy.sin",
"numpy.concatenate",
"numpy.fft.ifft",
"numpy.shape",
"numpy.repeat",
"numpy.array",
"numpy.zeros"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
tensorboy/centerpose | [
"555d753cd82693476f91f78c53aa4147f5a83015"
] | [
"lib/models/losses.py"
] | [
"# ------------------------------------------------------------------------------\n# Portions of this code are from\n# CornerNet (https://github.com/princeton-vl/CornerNet)\n# Copyright (c) 2018, University of Michigan\n# Licensed under the BSD 3-Clause License\n# ---------------------------------------------------... | [
[
"torch.nn.functional.l1_loss",
"torch.sin",
"torch.nn.functional.conv2d",
"torch.nn.functional.cross_entropy",
"torch.zeros_like",
"torch.log",
"torch.sort",
"torch.nn.functional.smooth_l1_loss",
"torch.nn.functional.elu",
"torch.pow",
"torch.cos",
"torch.autograd.V... | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
behzadzarfsaz/DualMemoryLearning | [
"924905ea14466ac60589e71ff5df6e33e98b6d92"
] | [
"individual_files/incremental_som.py"
] | [
"import os\nimport pathlib\nimport matplotlib.pyplot as plt\nfrom lib.helper import Helper\nfrom lib.model import Model\nfrom lib.plotter import Plotter\nfrom lib.som import SOM\n\nif __name__ == \"__main__\":\n train_images, train_labels, test_images, test_labels = Helper.load_data(\n os.path.join(pathli... | [
[
"matplotlib.pyplot.get_fignums",
"matplotlib.pyplot.figure"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
macapujol/astroEMPEROR | [
"c8bb45572b5adb2a0448b2f525e1e9f1ba8fe9f0"
] | [
"test_astroemperor_PM.py"
] | [
"#!/usr/bin/env python\n# -*- coding: utf-8 -*-\nimport astroemperor_pm\nimport scipy as sp\n\n\n# SETUP\n\nBOUNDARY = sp.array([[4.11098843e+00, 4.11105404e+00, -1.01515928e+01, -6.33312469e+00, 1.00520806e+01, 1.35949748e+01, 0.004, 0.009],\n [3.40831451e+00, 3.40863545e+00, -5.69294095e+00,... | [
[
"scipy.array"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
sweersr/pandas-profiling-1 | [
"4364c0f2689dc03635a13c0d61affeedd5464558"
] | [
"examples/vektis/vektis.py"
] | [
"import pandas as pd\n\nfrom pandas_profiling import ProfileReport\nfrom pandas_profiling.utils.cache import cache_file\n\nif __name__ == \"__main__\":\n file_name = cache_file(\n \"vektis_postcodes.csv\",\n \"https://www.vektis.nl/uploads/Docs%20per%20pagina/Open%20Data%20Bestanden/2017/Vektis%20O... | [
[
"pandas.read_csv"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [
"2.0",
"1.4",
"1.1",
"1.5",
"1.2",
"1.3"
],
"scipy": [],
"tensorflow": []
}
] |
cbite/BioMaterialAtlas | [
"5a64d168fced16077e4759e9d68f7c6e99bd65d8"
] | [
"PythonScripts/TransformStressStrainData.py"
] | [
"###########################################################################################\r\n############# script to transform the mechanical tests to a json object ###################\r\n###########################################################################################\r\n# Author T.J.M. Kuijpers Da... | [
[
"pandas.read_csv"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [
"2.0",
"1.4",
"1.1",
"1.5",
"1.2",
"1.3"
],
"scipy": [],
"tensorflow": []
}
] |
berquist/cclib_custom | [
"901e2fc3df38ad5fd470363919dd1e770eb0c56f"
] | [
"cclib_custom/sandbox/utils_dalton.py"
] | [
"import re\n\nimport numpy as np\n\n\nRE_ELEMENT = re.compile(r\"([+-]?[0-9]*\\.?[0-9]*|[+-]?\\.[0-9]+)[EeDd]?([+-]?[0-9]+)?\")\n\n\ndef parse_element_dalton(element):\n \"\"\"Given a number that might appear in a DALTON output, especially one\n printed in a matrix, convert it to a float.\n\n The 'expt' re... | [
[
"numpy.array"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
Raelag0112/clinicadl | [
"4b9508ea6bbe5498069b1d76ad2c3636f67e3184"
] | [
"clinicadl/utils/network/cnn/random.py"
] | [
"import numpy as np\n\nfrom clinicadl.utils.network.network_utils import *\nfrom clinicadl.utils.network.sub_network import CNN\n\n\nclass RandomArchitecture(CNN):\n def __init__(\n self,\n convolutions_dict,\n n_fcblocks,\n input_size,\n dropout=0.5,\n network_normaliza... | [
[
"numpy.round",
"numpy.array",
"numpy.product"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
ascentai/pytorch-nec | [
"139e1cdcb46a02f98cbada2e5df7e7cf974ea11f"
] | [
"nec_agent.py"
] | [
"import random\nimport torch\nimport torch.optim as optim\nfrom torch import Tensor\nfrom torch.autograd import Variable\n\nfrom dnd import DND\nfrom utils.math_utils import discount, inverse_distance\nfrom utils.replay_memory import Transition, ReplayMemory\nfrom utils.torch_utils import use_cuda, move_to_gpu\n\n\... | [
[
"torch.Tensor",
"torch.cat"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
sosey/hstaxe | [
"e8ac465103612e07c2e924556eca46dc8d4b737f"
] | [
"hstaxe/axesrc/nlincoeffs.py"
] | [
"import os\nimport numpy as np\n\nfrom astropy.io import fits\n\nfrom stwcs.wcsutil import HSTWCS\nfrom hstaxe.axeerror import aXeError\n\n\nclass NonLinCoeffs:\n def __init__(self, image, ext_info):\n \"\"\"Initializes the class\"\"\"\n # dummy example\n # self.default_coeffs_data =\"\"\"# ... | [
[
"numpy.array"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
cltl/EMISSOR | [
"68504c859c36b1b65b2c0002d065028b3d5b5d08"
] | [
"emissor/representation/container.py"
] | [
"# TODO This conflicts with marshmallow dataclass serialization\n# Enable using the current class in type annotations\n# from __future__ import annotations\n\nimport numpy as np\nimport uuid\nfrom abc import ABC\nfrom numpy.typing import ArrayLike\nfrom typing import TypeVar, Generic, Iterable, Tuple, Type, Any, Li... | [
[
"numpy.array"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
AIChuY/iglovikov_helper_functions | [
"46383c7a8b0f8dbdbf7907e119b6c2417877ad33"
] | [
"iglovikov_helper_functions/utils/metrics.py"
] | [
"import numpy as np\n\n\ndef calculate_confusion_matrix_from_arrays(ground_truth: np.array, prediction: np.array, num_classes: int) -> np.array:\n \"\"\"Calculate confusion matrix for a given set of classes.\n if GT value is outside of the [0, num_classes) it is excluded.\n Args:\n ground_truth:\n ... | [
[
"numpy.diag",
"numpy.unique",
"numpy.histogramdd",
"numpy.all",
"numpy.zeros",
"numpy.where"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
Luanee/SheetsAnalyzer | [
"78ed05d16b6e451f270f99efc20081c860f06287"
] | [
"sheetsanalyzer/analyzer_manager.py"
] | [
"# !/usr/bin/python3.7\r\nfrom os.path import isfile, join, isdir\r\nfrom os import listdir, walk\r\nfrom pathlib import Path\r\nimport pandas as pd\r\nfrom xlsxwriter.utility import xl_cell_to_rowcol, xl_range, xl_rowcol_to_cell_fast\r\n\r\n\r\nclass FileManager:\r\n def __init__(self):\r\n super().__ini... | [
[
"pandas.read_csv",
"pandas.ExcelFile"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [
"2.0",
"1.4",
"1.3",
"1.1",
"1.5",
"1.2"
],
"scipy": [],
"tensorflow": []
}
] |
OSHI7/Learning1 | [
"fa8014066e226465bb7989fbbb82a35412c4f634"
] | [
"matlablib.py"
] | [
"import pandas as pd\nfrom pandas import DataFrame\nimport matplotlib.pyplot as plt\nimport time\nimport IPython\nfrom IPython import embed\n\n\n# learn where site packages are stored! ref: https://stackoverflow.com/questions/122327/how-do-i-find-the-location-of-my-python-site-packages-directory\n# python -c \"impo... | [
[
"matplotlib.pyplot.close"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
toannhu/Tacotron-2-VN | [
"4e3bae77a58b09b07e97679dbff6f93f97273fcd"
] | [
"demo.py"
] | [
"import argparse\nimport os\nimport numpy as np\nimport tensorflow as tf\nfrom normalization.data_load import load_source_vocab, load_target_vocab\n\nos.environ['TF_CPP_MIN_LOG_LEVEL'] = '3'\n\n\ndef load_graph(frozen_graph_filename):\n with tf.gfile.GFile(frozen_graph_filename, \"rb\") as f:\n graph_def ... | [
[
"tensorflow.Graph",
"tensorflow.import_graph_def",
"tensorflow.gfile.GFile",
"tensorflow.Session",
"tensorflow.GraphDef",
"numpy.zeros"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
wongkarenhy/Full-Genome-Analysis-Pipeline | [
"de4d130f598af7d57cf7cec496f00e63fd9c3d99"
] | [
"scripts/SV_modules/BioNanoInversions.py"
] | [
"#!/usr/bin/env python3.6\n \nimport pandas as pd\nimport os\nimport pyranges as pr\nfrom pyranges import PyRanges\nfrom io import StringIO\nimport numpy as np\nimport argparse\npd.set_option('display.max_columns', None)\nfrom .BioNanoTranslocations import checkParentsOverlapTransloInv, geneOverlapTransloInv\n\nde... | [
[
"pandas.set_option",
"pandas.read_csv",
"pandas.DataFrame"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [
"2.0",
"1.4",
"1.3",
"1.1",
"1.5",
"1.2"
],
"scipy": [],
"tensorflow": []
}
] |
JacksonZyy/eran | [
"7ebc95dd365a40877eeb7c1bed054f900cf91f81"
] | [
"tf_verify/deeppoly_nodes.py"
] | [
"'''\n@author: Adrian Hoffmann\n'''\n\n\n\nimport numpy as np\nfrom config import config, Device\n\nif config.device == Device.CPU:\n from fppoly import *\nelse:\n from fppoly_gpu import *\n\nfrom elina_interval import *\nfrom elina_abstract0 import *\nfrom elina_manager import *\nfrom krelu import encode_kre... | [
[
"numpy.ascontiguousarray",
"numpy.arange"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
ramelgonzz/circular-heater-2d | [
"07f1edc69f44925e608a727939a944cc598b6d2e"
] | [
"circularheater2d-v1.py"
] | [
"#Heat propagation example of a circular shaped heater on a square plate\n#v1\nimport numpy as np\nimport matplotlib.pyplot as plt\nfrom matplotlib.animation import FuncAnimation\n\ndx=0.1\ndt=0.1\nL=50\nW=50\n\n#circle heater\nr=10 #radius of heater\ndef circle_heater(r):\n d=2*r+2\n rx,ry=d/2,d/2\n x,y=n... | [
[
"numpy.arange",
"numpy.indices",
"matplotlib.pyplot.draw",
"matplotlib.pyplot.colorbar",
"matplotlib.animation.FuncAnimation",
"matplotlib.pyplot.pcolormesh",
"matplotlib.pyplot.show",
"numpy.zeros",
"numpy.where",
"numpy.hypot",
"matplotlib.pyplot.figure"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
SvenGronauer/tensorbox | [
"8ca0da9a8fe345572bccdbda55bcd75f1bc1b28c"
] | [
"tensorbox/envs/endeffector.py"
] | [
"import math\nimport gym\nfrom gym import spaces, logger\nfrom gym.utils import seeding\nimport numpy as np\n\n\nangle_encode = lambda phi: np.array([np.cos(phi), np.sin(phi)])\nangle_decode = lambda psi: np.arctan2(psi[1], psi[0])\n\n\nclass TwoJointArmEnv(gym.Env):\n \"\"\"\n Description:\n A robotic... | [
[
"numpy.cos",
"numpy.finfo",
"numpy.arctan2",
"numpy.sin",
"numpy.array"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
Muroger/SVHNClassifier_pytorch | [
"608e2fc4d7eee0966949533195ad91abca6cf323"
] | [
"evaluator.py"
] | [
"import torch\nimport torch.utils.data\nfrom torchvision import transforms\n\nfrom dataset import Dataset\n\n\nclass Evaluator(object):\n def __init__(self, path_to_lmdb_dir):\n transform = transforms.Compose([\n transforms.CenterCrop([54, 54]),\n transforms.ToTensor(),\n ... | [
[
"torch.no_grad"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
rjagerman/pytorchltr | [
"625416e1e7d21fb2bbc485914704fc2e55274556"
] | [
"examples/01-basic-usage.py"
] | [
"#!/usr/bin/env python\n#\n# This script trains and evaluates a linear ranker on the Example3 toy dataset.\n#\n# Usage with expected output:\n#\n# $ PYTHONPATH=. python examples/01-basic-usage.py\n# [INFO, file] checking dataset files in './datasets/example3'\n# [WARNING, file] dataset file(s) in './dat... | [
[
"torch.nn.Linear",
"torch.manual_seed"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
hiram64/temporal-ensembling-semi-supervised | [
"d5ae0ba7abaace86f79517b810d8ebe48cdfc9a8"
] | [
"make_cifar10_npz.py"
] | [
"import glob\nimport pickle\n\nimport cv2\nimport numpy as np\n\n# The directory you downloaded CIFAR-10\n# You can download cifar10 data via https://www.kaggle.com/janzenliu/cifar-10-batches-py\ndata_dir = './data'\n\nall_files = glob.glob(data_dir + '/data_batch' + '*')\ntest_files = glob.glob(data_dir + '/test_b... | [
[
"numpy.savez",
"numpy.array",
"numpy.reshape"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
Axel-Erfurt/m3uEdit | [
"f6f08c62df9401eaa93966b49db8901ea91f5172"
] | [
"m3uEditor.py"
] | [
"#!/usr/bin/python3\n# -*- coding: utf-8 -*-\nimport sys\nimport pandas as pd\nfrom PyQt5.QtCore import (Qt, QDir, QAbstractTableModel, QModelIndex, \n QVariant, QSize, QProcess, QFile, QDate, QTime)\nfrom PyQt5.QtWidgets import (QMainWindow, QTableView, QApplication, QLineEdit, \n ... | [
[
"pandas.read_csv",
"pandas.DataFrame"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [
"2.0",
"1.4",
"1.3",
"1.1",
"1.5",
"1.2"
],
"scipy": [],
"tensorflow": []
}
] |
wzzlYwzzl/tensorflow-annotation | [
"4684f320dc436ecd45319fd2663dcf6179ce6a35"
] | [
"tensorflow/python/ops/array_ops.py"
] | [
"# Copyright 2015 The TensorFlow Authors. All Rights Reserved.\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n# http://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless requ... | [
[
"tensorflow.python.compat.compat.forward_compatible",
"tensorflow.python.ops.gen_math_ops.select_v2",
"tensorflow.python.eager.context.context",
"tensorflow.python.ops.gen_array_ops.list_diff",
"tensorflow.python.framework.ops.RegisterGradient",
"tensorflow.python.ops.gen_array_ops.strided... | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": [
"2.8",
"1.10",
"1.12",
"2.7",
"2.6",
"1.13",
"2.3",
"2.4",
"2.9",
"1.7",
"2.5",
"2.2",
"2.10"
]
}
] |
kryvokhyzha/examples-and-courses | [
"477e82ee24e6abba8a6b6d92555f2ed549ca682c"
] | [
"big-data-school-5/BigDataHomework-main/Spark/AddTargetToTraj.py"
] | [
"import csv, os, sys\r\nfrom os.path import isfile, join\r\nimport pandas as pd\r\nimport numpy as np\r\nimport shutil\r\n\r\n\r\ndef labelTraj(root, direc):\r\n\t'''\r\n\tAdds 'Transportation Mode' columns to trajectories and adds labels accordingly, splitting up the trajectories into appropriate 'subtrajectories'... | [
[
"pandas.read_csv",
"pandas.to_datetime"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [
"2.0",
"1.4",
"1.3",
"1.1",
"1.5",
"1.2"
],
"scipy": [],
"tensorflow": []
}
] |
Hecate2/morphsnakes | [
"999968ee8b88c71c0d59e287c704a90747dbe910"
] | [
"example.py"
] | [
"\r\nimport os\r\nimport logging\r\n\r\nimport numpy as np\r\nfrom imageio import imread\r\nimport matplotlib\r\nfrom matplotlib import pyplot as plt\r\n\r\nimport morphsnakes as ms\r\n\r\n# in case you are running on machine without display, e.g. server\r\n##if os.environ.get('DISPLAY', '') == '':\r\n## logging... | [
[
"numpy.zeros_like",
"numpy.load",
"matplotlib.pyplot.show",
"numpy.zeros",
"matplotlib.pyplot.pause",
"matplotlib.pyplot.figure"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
boyali/stat-mech-van | [
"c381d2371279416d102df923e1ace63d2780d96f"
] | [
"src_hop_sk/main_inv_ising.py"
] | [
"#!/usr/bin/env python3\n#\n# Solving Statistical Mechanics using Variational Autoregressive Networks\n# Inverse Ising problem\n\nimport time\nimport pickle\n\nimport numpy as np\nimport torch\n\nfrom args import args\nfrom made2 import MADE\nfrom sk import SKModel\nfrom utils import (\n default_dtype_torch,\n ... | [
[
"torch.optim.Adam",
"torch.mean",
"torch.eye",
"torch.inverse",
"torch.no_grad",
"torch.log",
"numpy.prod"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
PrathameshTugaonkar/devito | [
"0c019a7034e862bb5e7dd255c7e3306e38925607"
] | [
"devito/types/basic.py"
] | [
"import abc\nfrom collections import namedtuple\nfrom ctypes import POINTER, Structure, byref\nfrom functools import reduce\nfrom math import ceil\nfrom operator import mul\n\nimport numpy as np\nimport sympy\nfrom sympy.core.assumptions import _assume_rules\nfrom cached_property import cached_property\nfrom cgen i... | [
[
"numpy.add"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
dkoguciuk/rgbd-object-recognition | [
"572618d1ea53b9a62108cb09b762f29fffec532d"
] | [
"models/pointnet_cls/pointnet_cls.py"
] | [
"import tensorflow as tf\nimport numpy as np\nimport sys\nimport os\n\nBASE_DIR = os.path.dirname(os.path.abspath(__file__))\nsys.path.append(BASE_DIR)\n\nimport tf_util\nfrom transform_nets import input_transform_net, feature_transform_net\n\n\ndef placeholder_inputs(batch_size, num_point):\n pointclouds_pl = t... | [
[
"tensorflow.matmul",
"tensorflow.transpose",
"tensorflow.reduce_mean",
"numpy.eye",
"tensorflow.reshape",
"tensorflow.expand_dims",
"tensorflow.placeholder",
"tensorflow.squeeze",
"tensorflow.nn.l2_loss",
"tensorflow.nn.sparse_softmax_cross_entropy_with_logits",
"tensor... | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": [
"1.10"
]
}
] |
kamronald/pymatgen | [
"9e4d6776094e38b50089974d6d21e598b9299a25"
] | [
"pymatgen/symmetry/site_symmetries.py"
] | [
"import pymatgen\nimport numpy as np\nfrom pymatgen.symmetry.analyzer import SpacegroupAnalyzer as sga\nfrom pymatgen.core.operations import SymmOp\nfrom pymatgen import Element\nfrom pymatgen.analysis.elasticity.tensors import Tensor\n\n\ndef get_site_symmetries(struc, precision=0.1):\n \"\"\"\n Get all the ... | [
[
"numpy.allclose"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
belelaritra/W-ambulance | [
"ecda7e7789143e4b72b1393a15a035f33cf85474"
] | [
"main.py"
] | [
"import json\nimport requests\nimport pandas\nfrom flask import Flask, request\nfrom twilio.twiml.messaging_response import MessagingResponse\nfrom requests.structures import CaseInsensitiveDict\nfrom pytz import timezone\nfrom datetime import datetime\n\n# ========== From File\nimport sendmsg as sd\nimport googlea... | [
[
"pandas.read_csv"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [
"2.0",
"1.4",
"1.1",
"1.5",
"1.2",
"1.3"
],
"scipy": [],
"tensorflow": []
}
] |
IcedDoggie/Micro-Expression-with-Deep-Learning | [
"2ae489bf1040b29a2b535fb4178d6e7bbe7bba49"
] | [
"test_samm.py"
] | [
"import numpy as np\nimport sys\nimport math\nimport operator\nimport csv\nimport glob,os\nimport xlrd\nimport cv2\nimport pandas as pd\nimport matplotlib.pyplot as plt\n\nfrom sklearn.svm import SVC\nfrom collections import Counter\nfrom sklearn.metrics import confusion_matrix\nimport scipy.io as sio\nimport pydot... | [
[
"numpy.sum",
"sklearn.metrics.confusion_matrix",
"numpy.concatenate",
"numpy.shape",
"sklearn.svm.SVC",
"numpy.repeat",
"numpy.zeros",
"numpy.trace",
"numpy.empty"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
SvenGastauer/scatmod | [
"638db9b42b824deca54d8372f78fac154ff2e613"
] | [
"python/fluid_sphere.py"
] | [
"# -*- coding: utf-8 -*-\n'''\n:author Sven Gastauer\n:licence MIT\n'''\n## import packages\nimport numpy as np\nimport scipy.special as ss\n\ndef Lambda(c,f):\n '''\n :param c: Sound velocity (m/s)\n :type c: float\n \n :param f: acoustic frequency (Hz; s^-1)\n :type f: int \n \n return:\... | [
[
"scipy.special.yv",
"numpy.sqrt",
"numpy.isnan",
"scipy.special.jv",
"numpy.asarray",
"numpy.cos",
"scipy.special.spherical_jn",
"numpy.ones",
"numpy.log10",
"scipy.special.spherical_yn",
"numpy.sum"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [
"1.6",
"1.10",
"1.4",
"1.3",
"1.9",
"0.19",
"1.5",
"0.18",
"1.7",
"1.0",
"1.2",
"1.8"
],
"tensorflow": []
}
] |
scottstanie/scipy | [
"cb8357bc4908b9bbe418601e988b9734e59a21ff"
] | [
"scipy/stats/tests/test_stats.py"
] | [
"\"\"\" Test functions for stats module\n\n WRITTEN BY LOUIS LUANGKESORN <lluang@yahoo.com> FOR THE STATS MODULE\n BASED ON WILKINSON'S STATISTICS QUIZ\n https://www.stanford.edu/~clint/bench/wilk.txt\n\n Additional tests by a host of SciPy developers.\n\"\"\"\nimport os\nimport warnings\nfrom collectio... | [
[
"scipy.stats._stats_py._count_paths_outside_method",
"numpy.testing.assert_approx_equal",
"numpy.sqrt",
"scipy.stats.zscore",
"numpy.all",
"numpy.broadcast",
"scipy.stats.energy_distance",
"scipy.stats._stats_py._permutation_distribution_t",
"numpy.exp",
"numpy.ma.masked_wh... | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [
"1.6",
"1.10",
"1.9",
"1.5",
"1.7",
"1.8"
],
"tensorflow": []
}
] |
sofya-pugach/spot_mini_mini | [
"1d08dac0fb511aa18e829e7aa220fad293c45c63"
] | [
"spot_bullet/src/old_eval_scripts/ars_eval.py"
] | [
"#!/usr/bin/env python\n\nimport numpy as np\n\nfrom ars_lib.ars import ARSAgent, Normalizer, Policy, ParallelWorker\nfrom mini_bullet.minitaur_gym_env import MinitaurBulletEnv\n\nimport torch\nimport os\n\n\ndef main():\n \"\"\" The main() function. \"\"\"\n\n print(\"STARTING MINITAUR ARS\")\n\n # TRAINI... | [
[
"torch.manual_seed",
"numpy.random.seed"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
daemon/vizbert | [
"e40b7d1529f8857050313f8d87ff03b1b7226c9e",
"e40b7d1529f8857050313f8d87ff03b1b7226c9e"
] | [
"vizbert/model/trainer.py",
"vizbert/run/train_ip_probe.py"
] | [
"from collections import defaultdict\nfrom dataclasses import dataclass\nfrom typing import Any, Tuple, Callable, Dict\n\nfrom tqdm import trange, tqdm\nimport torch\nimport torch.nn as nn\nimport torch.utils.data as tud\n\nfrom vizbert.data import TrainingWorkspace\n\n\n__all__ = ['LOSS_KEY', 'ModelTrainer', 'LOSS... | [
[
"torch.no_grad"
],
[
"torch.optim.Adam",
"torch.optim.lr_scheduler.ReduceLROnPlateau",
"numpy.isnan",
"torch.utils.data.DataLoader",
"torch.no_grad"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
},
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
imyoungyang/algotrading-workshop | [
"9d494be73e46867111217a63f4da4f89f996c389"
] | [
"2_Strategies/data_prep.py"
] | [
"import h5py\nimport datetime\nimport pandas as pd\nimport sys\n\nSTART_DATE = '2012-08-13'\nEND_DATE = '2017-08-11'\nDATE_FORMAT = '%Y-%m-%d'\nSTART_DATETIME = datetime.datetime.strptime(START_DATE, DATE_FORMAT)\n\ndef read_stock_history(filepath):\n \"\"\" Read data from extracted h5\n Args:\n filepa... | [
[
"pandas.DatetimeIndex",
"pandas.DataFrame"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [
"0.23",
"0.21",
"2.0",
"1.4",
"1.3",
"0.19",
"1.1",
"1.5",
"0.24",
"0.20",
"1.0",
"0.25",
"1.2"
],
"scipy": [],
"tensorflow": []
}
] |
walkingmask/wob | [
"6d2284302a19957be1ded81630bced0a016cdbd7"
] | [
"agent/py/worker.py"
] | [
"#!/usr/bin/env python\n# coding:utf-8\n\n\n# train.pyでnum_workersの数に応じて、これが複数プロセス生成される\n# 主に走るのはここ\n# クラスター、SuperVisor、sessやpsなどの設定\n\n\nimport argparse\nimport logging\nimport os\nimport sys\nimport signal\nimport time\n\nimport cv2\n\nimport go_vncdriver # tfの前にimportしないと怒られる\nimport tensorflow as tf\n\nfrom a3c... | [
[
"tensorflow.train.get_checkpoint_state",
"tensorflow.summary.FileWriter",
"tensorflow.global_variables",
"tensorflow.variables_initializer",
"tensorflow.train.ClusterSpec",
"tensorflow.report_uninitialized_variables",
"tensorflow.ConfigProto",
"tensorflow.global_variables_initializ... | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": [
"1.10"
]
}
] |
undefinedzero/PointPainter | [
"62d0bf49756c85e5326e4a48a0dd5bedfd99435e"
] | [
"LidarDetector/pcdet/datasets/kitti/painted_kitti_dataset.py"
] | [
"import copy\nimport pickle\nimport os\nimport numpy as np\nfrom open3d import *\nfrom skimage import io\nfrom ...ops.roiaware_pool3d import roiaware_pool3d_utils\nfrom ...utils import box_utils, calibration_kitti, common_utils, object3d_kitti\nfrom ..dataset import DatasetTemplate\n\n\nclass PaintedKittiDataset(Da... | [
[
"numpy.asarray",
"numpy.linalg.norm",
"torch.from_numpy",
"numpy.ones",
"numpy.concatenate",
"numpy.arctan2",
"numpy.load",
"numpy.array",
"numpy.logical_and",
"numpy.zeros"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
Jeevesh8/CLVC-Experiments | [
"bc7d2a95f34033aed1733f2515e87f7b27fc36d9"
] | [
"hparams.py"
] | [
"import tensorflow as tf\nfrom text import symbols\n\n\ndef create_hparams(hparams_string=None, verbose=False):\n \"\"\"Create model hyperparameters. Parse nondefault from given string.\"\"\"\n\n hparams = tf.contrib.training.HParams(\n ################################\n # Experiment Parameters ... | [
[
"tensorflow.logging.info"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": [
"1.10"
]
}
] |
devhliu/TFDeepSurv | [
"1847244b68abe987c1d7cb468856c06a912727f0"
] | [
"tfdeepsurv/L2DeepSurv.py"
] | [
"from __future__ import print_function\nimport numpy as np\nimport tensorflow as tf\nfrom lifelines.utils import concordance_index\nfrom supersmoother import SuperSmoother\n\nfrom tfdeepsurv import vision, utils\n\nclass L2DeepSurv(object):\n def __init__(self, X, label,\n input_node, hidden_layers_node, ... | [
[
"numpy.diag",
"numpy.dot",
"tensorflow.contrib.layers.apply_regularization",
"tensorflow.contrib.layers.l1_l2_regularizer",
"tensorflow.reduce_sum",
"numpy.squeeze",
"numpy.exp",
"tensorflow.cumsum",
"tensorflow.Graph",
"tensorflow.truncated_normal_initializer",
"tensor... | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": [
"1.10",
"1.12",
"1.4",
"1.13",
"1.5",
"1.7",
"0.12",
"1.0",
"1.2"
]
}
] |
BalinLin/SID | [
"a1eab049a08359fd041bc67205177c73902e2a37",
"c0702815c4b1a72f606f6b0ee4e5d660a0b8c506"
] | [
"src/models/SIDPAMIwinpsa_model.py",
"src/util/util.py"
] | [
"import torch\nfrom collections import OrderedDict\nimport time\nimport numpy as np\nimport torch.nn.functional as F\nfrom util.image_pool import ImagePool\nfrom .base_model import BaseModel\nfrom . import networks\nimport util.util as util\nfrom .distangle_model import DistangleModel\nfrom PIL import ImageOps,Imag... | [
[
"torch.nn.functional.upsample",
"torch.mean",
"numpy.hstack",
"torch.cat",
"numpy.asarray",
"torch.nn.BCEWithLogitsLoss",
"torch.nn.L1Loss",
"torch.nn.MSELoss",
"numpy.vstack"
],
[
"torch.abs",
"numpy.log",
"numpy.min",
"numpy.median",
"numpy.tile",
... | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
},
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
flarrow7/haystack | [
"0168f043850f02bdfd00bebc36b0b05ae625aae1"
] | [
"test/test_generator.py"
] | [
"from typing import List, Optional\n\nimport numpy as np\nimport pytest\nfrom transformers import PreTrainedTokenizer, BatchEncoding\n\nfrom haystack import Document\nfrom haystack.generator.transformers import Seq2SeqGenerator\nfrom haystack.pipeline import TranslationWrapperPipeline, GenerativeQAPipeline\n\nDOCS_... | [
[
"numpy.array"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
dbrakenhoff/flopy_replacement | [
"9a29cbbb9a0d29836e2f4c499e2489fb175ebed3"
] | [
"autotest/t065_test_gridintersect.py"
] | [
"import sys\nsys.path.insert(1, \"..\")\nimport flopy.discretization as fgrid\nimport flopy.plot as fplot\nimport matplotlib.pyplot as plt\nimport numpy as np\nfrom descartes import PolygonPatch\nfrom flopy.utils.triangle import Triangle\ntry:\n from shapely.geometry import (LineString, MultiLineString, MultiPoi... | [
[
"numpy.sqrt",
"numpy.min",
"matplotlib.pyplot.subplots",
"numpy.ones",
"numpy.all",
"numpy.max",
"numpy.array"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
tchaton/tsd | [
"42fe91306a13486fef243e4a11f5f647737bb623"
] | [
"test/test_backward.py"
] | [
"from itertools import product\n\nimport pytest\nimport torch\nfrom torch.autograd import gradcheck\nimport tsd\n\nfrom .utils import grad_dtypes as dtypes, devices, tensor\n\nfuncs = ['add', 'sub', 'mul', 'div', 'mean']\nindices = [2, 0, 1, 1, 0]\n\n\n@pytest.mark.parametrize('func,device', product(funcs, devices)... | [
[
"torch.autograd.gradcheck",
"torch.tensor"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
WesleyDeng1016/neural-backed-decision-trees | [
"4791522527abf6d7cf09f5bae64a7fecf93a4b03"
] | [
"nbdt/analysis.py"
] | [
"from nbdt.utils import set_np_printoptions\nfrom nbdt.model import (\n SoftEmbeddedDecisionRules as SoftRules,\n HardEmbeddedDecisionRules as HardRules\n)\nimport numpy as np\n\n\n__all__ = names = (\n 'Noop', 'ConfusionMatrix', 'ConfusionMatrixJointNodes',\n 'IgnoredSamples', 'HardEmbeddedDecisionRule... | [
[
"numpy.zeros"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
MinsuKimhero/ContactFree_Store_System | [
"59dc6581f894de236b8577a16033674756504005"
] | [
"deep_sort_pytorch/deep_sort/deep_sort.py"
] | [
"import numpy as np\nimport torch\n\nfrom .deep.feature_extractor import Extractor\nfrom .sort.nn_matching import NearestNeighborDistanceMetric\nfrom .sort.preprocessing import non_max_suppression\nfrom .sort.detection import Detection\nfrom .sort.tracker import Tracker\n\n\n__all__ = ['DeepSort']\n\n\nclass DeepSo... | [
[
"numpy.array",
"numpy.stack"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
aakanksha14/blocksWorld | [
"33a679f25ec0e8f83701c559ab3a936618e7c148"
] | [
"test/dataSet.py"
] | [
"import numpy as np\r\ndraw_points = [\r\n np.array([5, 5]),\r\n np.array([5, 15]),\r\n np.array([5, 25]),\r\n np.array([5, 35]),\r\n np.array([5, 45]),\r\n np.array([5, 55]),\r\n np.array([5, 65]),\r\n np.array([5, 75])\r\n ... | [
[
"numpy.array"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
nicolaskruchten/semiology_of_graphics | [
"019d7fb7923a685bfeee3ede7c30ce2476904fe7"
] | [
"generate_points.py"
] | [
"#!/usr/bin/env python\n# coding: utf-8\n\n# In[1]:\n\n\nimport geopandas as gpd\nimport pandas as pd\nimport numpy as np\ndf = gpd.read_file(\"data/semiology_of_graphics.geojson\").set_index(\"code\")\n\n\n# In[2]:\n\n\n# generate a grid\n\ngrain = 30\nx1, y1, x0, y0 = df.total_bounds\nxv, yv = np.meshgrid(\n n... | [
[
"numpy.linspace"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
shotaro12oyama/udacity-aind-project2 | [
"912d9a3318932335e2b673767655d5d47bf567cd"
] | [
"my_answers.py"
] | [
"import numpy as np\n\nfrom keras.models import Sequential\nfrom keras.layers import Dense\nfrom keras.layers import LSTM\nimport keras\n\n\n# TODO: fill out the function below that transforms the input series \n# and window-size into a set of input/output pairs for use with our RNN model\ndef window_transform_seri... | [
[
"numpy.asarray",
"numpy.size",
"numpy.shape"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
lukasHoel/3rscan-triplet-dataset-toolkit | [
"8e12c715e547dcd54bd15a8a709c970778fef756"
] | [
"eval/top_k_accuracy.py"
] | [
"from models.losses.metrics import l2_dist_sum_weighted\nimport torch\nimport torchvision.transforms as tf\n\n\nclass TopK_Accuracy:\n\n def __init__(self, writer=None, minK=[1, 5], hparams=None, log_images_nth=100):\n self.correct = {}\n self.incorrect = {}\n self.total = {}\n self.w... | [
[
"torch.stack"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
deep-spin/explainable-qe-shared-task | [
"da517a9a76f6dc0c68113e2d6be830f5b57726a7"
] | [
"model/bottleneck_layer.py"
] | [
"from functools import partial\n\nimport torch\nfrom entmax import entmax15, sparsemax, entmax_bisect\nfrom model.utils import masked_average\n\n\nclass BottleneckSummary(torch.nn.Module):\n\n def __init__(\n self,\n hidden_size,\n aggregation='none',\n kv_rep='embeddings',\n a... | [
[
"torch.max",
"torch.zeros",
"torch.cat",
"torch.nn.Linear",
"torch.matmul",
"torch.arange"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
njpatel04/sqlalchemy-challenge | [
"b28a2220e501c9495a59ded3007b140c99db2615"
] | [
"app.py"
] | [
"import numpy as np\n\nimport sqlalchemy\nfrom sqlalchemy.ext.automap import automap_base\nfrom sqlalchemy.orm import Session\nfrom sqlalchemy import create_engine, func\nimport datetime as dt\n\nfrom flask import Flask, jsonify\n\n\n#################################################\n# Database Setup\n#############... | [
[
"numpy.ravel"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
cyqian97/Facial-Similarity-with-Siamese-Networks-in-Pytorch | [
"57055225c902bb70e8327813df8edb2a5190fb59"
] | [
"loss_functions.py"
] | [
"# +\nimport torch\nimport torch.nn as nn\nimport torch.nn.functional as F\n\nimport config\n\n\n# -\n\nclass ContrastiveLoss(nn.Module):\n \"\"\"\n Contrastive loss function.\n \"\"\"\n\n def __init__(self, margin=config.margin):\n super(ContrastiveLoss, self).__init__()\n self.margin = m... | [
[
"torch.nn.functional.pairwise_distance",
"torch.clamp",
"torch.pow"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
matham/nixpy | [
"a6527d2fe61c6df997bb71e97e235bfa5427e256"
] | [
"docs/source/examples/multipleROIs.py"
] | [
"#!/usr/bin/env python\n# -*- coding: utf-8 -*-\n\n\"\"\"Copyright © 2014 German Neuroinformatics Node (G-Node)\n\n All rights reserved.\n\n Redistribution and use in source and binary forms, with or without\n modification, are permitted under the terms of the BSD License. See\n LICENSE file in the root of the Proj... | [
[
"matplotlib.pyplot.savefig",
"matplotlib.pyplot.gcf",
"numpy.array",
"numpy.zeros",
"matplotlib.pyplot.show"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
thomassutter/mmjsd | [
"51889cf35adcb53fa473ca84342209dc81ff7e0e"
] | [
"networks/ConvNetworksImgCelebA.py"
] | [
"import torch\nimport torch.nn as nn\n\nfrom networks.FeatureExtractorImg import FeatureExtractorImg\nfrom networks.FeatureCompressor import LinearFeatureCompressor\nfrom networks.DataGeneratorImg import DataGeneratorImg\n\nclass EncoderImg(nn.Module):\n def __init__(self, flags):\n super(EncoderImg, self... | [
[
"torch.tensor",
"torch.nn.Linear",
"torch.cat"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
mdboom/pyasdf | [
"ac4e9f85bf96206fdd6bc3d0708875c953c66dc5",
"ac4e9f85bf96206fdd6bc3d0708875c953c66dc5"
] | [
"pyasdf/tags/core/table.py",
"pyasdf/block.py"
] | [
"# Licensed under a 3-clause BSD style license - see LICENSE.rst\n# -*- coding: utf-8 -*-\n\nfrom __future__ import absolute_import, division, unicode_literals, print_function\n\nimport numpy as np\n\nfrom ...asdftypes import AsdfType\nfrom ... import yamlutil\n\n\nclass TableType(AsdfType):\n name = 'core/table... | [
[
"numpy.array"
],
[
"numpy.product"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
},
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
gusamarante/Quantequim | [
"3968d9965e8e2c3b5850f1852b56c485859a9c89"
] | [
"dataapi/AWS/aws_test.py"
] | [
"from dataapi import TrackerFeeder, DBConnect, FocusFeeder\nfrom sqlalchemy import create_engine\nimport matplotlib.pyplot as plt\nimport pandas as pd\n\ndb_connect = DBConnect('fhreadonly', 'finquant')\n\n# ===== Exemples of the focus feeder =====\nff = FocusFeeder(db_connect)\ndf = ff.fetch('IPCA', 'yearly')\ndf.... | [
[
"pandas.concat",
"matplotlib.pyplot.show"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [
"0.23",
"0.21",
"2.0",
"1.4",
"0.19",
"1.1",
"1.5",
"1.2",
"0.24",
"0.20",
"1.0",
"0.25",
"1.3"
],
"scipy": [],
"tensorflow": []
}
] |
anuprulez/similar_galaxy_workflow | [
"b9771e58ad4e6e5b61909b284d4c7d2645626525"
] | [
"scripts/utils.py"
] | [
"import os\nimport numpy as np\nimport json\nimport h5py\n\nfrom keras import backend as K\n\n\ndef read_file(file_path):\n \"\"\"\n Read a file\n \"\"\"\n with open(file_path, \"r\") as json_file:\n file_content = json.loads(json_file.read())\n return file_content\n\n\ndef write_file(file_pat... | [
[
"numpy.log",
"numpy.reshape",
"numpy.mean",
"numpy.argsort",
"numpy.where",
"numpy.sum"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
ralna/RALFit | [
"1d54007935733016fec4029c355fe76d3e18c744"
] | [
"ComparisonTools/iteration_tests.py"
] | [
"#!/usr/bin/python\nfrom __future__ import print_function, unicode_literals\n\nimport sys\nimport numpy as np\nimport matplotlib.pyplot as plt\nimport subprocess\nimport os\nimport argparse\nimport math\n\ndef main():\n # Let's get the files containing the problem and control parameters from the calling command.... | [
[
"numpy.absolute",
"numpy.sum",
"numpy.amin",
"numpy.dtype",
"numpy.genfromtxt",
"numpy.ones",
"numpy.copy",
"numpy.transpose",
"numpy.array",
"numpy.zeros",
"numpy.where"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
akhilpandey95/altpred | [
"659a44b6543ed021077c3647159c46ed59c0941c"
] | [
"src/evaluation.py"
] | [
"# This Source Code Form is subject to the terms of the MIT\n# License. If a copy of the same was not distributed with this\n# file, You can obtain one at\n# https://github.com/akhilpandey95/altpred/blob/master/LICENSE.\n\nimport numpy as np\nfrom sklearn.metrics import accuracy_score\nfrom sklearn.metrics import p... | [
[
"sklearn.metrics.precision_score",
"numpy.divide",
"sklearn.metrics.f1_score",
"sklearn.metrics.recall_score",
"numpy.zeros",
"sklearn.metrics.accuracy_score"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
CJWBW/TediGAN | [
"f1818f48520e7aa4dfb4918e524f9dfffc608b49"
] | [
"base/models/stylegan_encoder.py"
] | [
"# python 3.7\n\"\"\"Contains the encoder class of StyleGAN inversion.\n\nThis class is derived from the `BaseEncoder` class defined in `base_encoder.py`.\n\"\"\"\n\nimport numpy as np\n\nimport torch\n\nfrom .base_encoder import BaseEncoder\nfrom .stylegan_encoder_network import StyleGANEncoderNet\n\n__all__ = ['S... | [
[
"torch.cuda.empty_cache",
"numpy.prod"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
mehmeta/hummingbot | [
"0ab56228c87194a64eab0f409e93e6bb74425f4c"
] | [
"hummingbot/market/bitcoin_com/bitcoin_com_api_user_stream_data_source.py"
] | [
"#!/usr/bin/env python\n\nimport asyncio\nimport logging\nimport pandas as pd\nimport time\n\nfrom typing import Optional, List, AsyncIterable, Any\nfrom hummingbot.core.data_type.user_stream_tracker_data_source import UserStreamTrackerDataSource\nfrom hummingbot.market.bitcoin_com.bitcoin_com_auth import BitcoinCo... | [
[
"pandas.Timestamp"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
pajotca/CityEnergyAnalyst | [
"f3d0a08f7b5f5967961bf831625544a95c7702f0"
] | [
"cea/analysis/benchmark.py"
] | [
"# -*- coding: utf-8 -*-\n\"\"\"\nBenchmark plots\n\"\"\"\nfrom __future__ import division\n\nimport os\n\nimport matplotlib.pyplot as plt\nimport pandas as pd\nfrom geopandas import GeoDataFrame as gpdf\n\nimport cea.inputlocator\nimport cea.config\n\n__author__ = \"Martin Mosteiro Romero\"\n__copyright__ = \"Copy... | [
[
"matplotlib.pyplot.legend",
"pandas.read_excel",
"matplotlib.pyplot.title",
"matplotlib.pyplot.subplots",
"matplotlib.pyplot.savefig",
"matplotlib.pyplot.plot",
"matplotlib.pyplot.clf",
"matplotlib.pyplot.subplot",
"matplotlib.pyplot.close",
"matplotlib.pyplot.axis"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [
"0.23",
"0.21",
"2.0",
"1.4",
"0.19",
"1.1",
"1.5",
"1.2",
"0.24",
"0.20",
"1.0",
"0.25",
"1.3"
],
"scipy": [],
"tensorflow": []
}
] |
pyalanysis/pyalanysis | [
"8917e115534dac3fd617c8b4820227ae9f4c0a52"
] | [
"src/pyalanysis/data/viirsdnb.py"
] | [
"from enum import Enum\nimport inspect\nimport logging\nimport os\nfrom pathlib import Path\nimport tarfile\nfrom typing import Callable, List, Optional, Tuple\n\nimport bs4\nimport mechanicalsoup as ms\nimport pandas as pd\nimport rioxarray # type: ignore\nimport xarray as xr\n\nfrom pyalanysis.utils import (\n ... | [
[
"pandas.date_range"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [
"0.23",
"0.21",
"2.0",
"1.4",
"0.19",
"1.1",
"1.5",
"1.2",
"0.24",
"0.20",
"1.0",
"0.25",
"1.3"
],
"scipy": [],
"tensorflow": []
}
] |
FilippoPisello/Stat-utils | [
"61f9d95ef6eaac419fd48ecf08d4b374c10087de"
] | [
"tests/test_scaling.py"
] | [
"from unittest import TestCase\n\nimport numpy as np\nimport pandas as pd\nfrom preprocessing import scaling\n\n\nclass TestPandasScaling(TestCase):\n a1 = np.array([1, 2, 3, 5, 6, 9])\n a2 = np.array([5, 5, 5, 5, 5, 5])\n a3 = np.array([3, 3, 3, 3, 3, 3])\n\n df1 = pd.DataFrame({\"Col1\": a1, \"Col2\":... | [
[
"pandas.testing.assert_series_equal",
"pandas.Series",
"pandas.DataFrame",
"pandas.testing.assert_frame_equal",
"numpy.testing.assert_allclose",
"numpy.array"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [
"0.23",
"0.21",
"2.0",
"1.4",
"1.3",
"1.1",
"1.5",
"0.24",
"0.20",
"1.0",
"0.25",
"1.2"
],
"scipy": [],
"tensorflow": []
}
] |
Teng-xu/tensorflow-1 | [
"011e64e79bad76bc9fb32802b15ee8218c7ea32e"
] | [
"tensorflow/python/framework/function_test.py"
] | [
"# Copyright 2015 The TensorFlow Authors. All Rights Reserved.\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n# http://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless requ... | [
[
"tensorflow.python.ops.math_ops.log",
"tensorflow.core.protobuf.config_pb2.RunMetadata",
"tensorflow.python.ops.variables.Variable",
"tensorflow.python.ops.nn_ops.softmax",
"tensorflow.python.ops.gradients_impl.gradients",
"numpy.exp",
"tensorflow.python.ops.math_ops.divide",
"tens... | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": [
"2.8",
"1.10",
"1.12",
"2.7",
"2.6",
"1.4",
"1.13",
"2.3",
"2.4",
"2.9",
"1.5",
"1.7",
"2.5",
"0.12",
"1.0",
"2.2",
"1... |
groupby/hack-finger | [
"ffae3a7000851df28638c1024acfd074d938d15c"
] | [
"tensorflow/sample.py"
] | [
"from __future__ import absolute_import\nfrom __future__ import division\nfrom __future__ import print_function\n\nimport collections\nimport math\nimport os\nimport random\nimport zipfile\n\nimport numpy as np\nfrom six.moves import urllib\nfrom six.moves import xrange\nimport tensorflow as tf\n\n# Step 1: Downloa... | [
[
"tensorflow.device",
"tensorflow.zeros",
"numpy.ndarray",
"sklearn.manifold.TSNE",
"tensorflow.nn.nce_loss",
"tensorflow.Graph",
"tensorflow.Session",
"tensorflow.square",
"matplotlib.pyplot.figure",
"tensorflow.matmul",
"numpy.random.choice",
"matplotlib.pyplot.ann... | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": [
"1.10"
]
}
] |
PaperXLV/UspWeakness | [
"62595884167c229db6f1df1a98e4a6cc0401a82e"
] | [
"python/CdclGraphs.py"
] | [
"import csv\nimport matplotlib.pyplot as plt\nimport numpy as np\n\n# create graphs with confidence intervals for each\n# instance of width 10 and 15\n\nwith open('runtime.csv') as runtime:\n reader = csv.reader(runtime, delimiter=',')\n lines = [line for line in reader]\n\n w10data = []\n w15data = []\... | [
[
"matplotlib.pyplot.legend",
"numpy.array",
"matplotlib.pyplot.subplots",
"matplotlib.pyplot.show"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
nagyben/CarND-Advanced-Lane-Lines | [
"7c8be1fc2519711f51a2a9b5f37602036f349016"
] | [
"calibration.py"
] | [
"import cv2\nimport numpy as np\nimport glob\nimport os\n\n\ndef calibrateCamera():\n \"\"\"\n Returns the camera matrix, distortion coefficients, rvecs and tvecs based on the calibration\n images in /camera_cal.\n Writes images to /camera_cal_output for validation and example purposes.\n :return: tu... | [
[
"numpy.hstack",
"numpy.zeros"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
Wangxy2180/Spike-FlowNet | [
"1531c2422fcc9286b07dee11c7fd7995e6696800"
] | [
"cvtest.py"
] | [
"import numpy as np\nimport cv2\nimport os\n\n\ndef onpass():\n data_path = './datasets/celex_datasets/encoded_data/'\n data_name = 'b2t'\n gray_path = os.path.join(data_path, data_name, 'gray_data')\n\n name_list = [os.path.join(gray_path, str(i) + '.npy') for i in range(0, 27)]\n\n for name in name... | [
[
"numpy.load",
"numpy.array",
"numpy.zeros"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
Taesiny/deep_representation_one_class | [
"a0d736bbeae2559b4f3f3b50cfd01f4cd60b26ee"
] | [
"data/augment_ops.py"
] | [
"# coding=utf-8\n# Copyright 2021 The Google Research Authors.\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n# http://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless requ... | [
[
"tensorflow.concat",
"tensorflow.image.random_flip_left_right",
"tensorflow.minimum",
"tensorflow.random.uniform",
"tensorflow.cast",
"tensorflow.image.random_crop",
"tensorflow.image.rgb_to_grayscale",
"tensorflow.image.rot90",
"tensorflow.image.resize",
"tensorflow.pad",
... | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": [
"1.10"
]
}
] |
joeyginorio/compositional_desires | [
"8f3bb17d99712d1de38299462801ff18c4b47bd5"
] | [
"model_src/grid_world.py"
] | [
"# Joey Velez-Ginorio\n# Gridworld Implementation\n# ---------------------------------\n\nfrom mdp import MDP\nfrom grid import Grid\nfrom scipy.stats import uniform\nfrom scipy.stats import beta\nfrom scipy.stats import expon\nimport numpy as np\nimport random\nimport pyprind\nimport matplotlib.pyplot as plt\n\ncl... | [
[
"numpy.sqrt",
"numpy.random.choice",
"numpy.arange",
"numpy.copy",
"numpy.array",
"numpy.where"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
wangsq/pyalgotrade | [
"d5a68c457b5ddd5fb7e40d9856ca8e5801134a73"
] | [
"pyalgotrade/eventprofiler.py"
] | [
"# PyAlgoTrade\n#\n# Copyright 2011-2014 Gabriel Martin Becedillas Ruiz\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n# http://www.apache.org/licenses/LICENSE-2.0\n#\n# Unle... | [
[
"numpy.isnan",
"matplotlib.pyplot.plot",
"matplotlib.pyplot.clf",
"matplotlib.pyplot.errorbar",
"matplotlib.pyplot.xlabel",
"matplotlib.pyplot.show",
"numpy.empty",
"matplotlib.pyplot.ylabel"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
tobiagru/models | [
"8367cf6dabe11adf7628541706b660821f397dce"
] | [
"research/deeplab/core/nas_cell.py"
] | [
"# Copyright 2018 The TensorFlow Authors All Rights Reserved.\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n# http://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless requi... | [
[
"tensorflow.nn.relu",
"tensorflow.concat",
"tensorflow.shape",
"tensorflow.variable_scope",
"tensorflow.split"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": [
"1.10"
]
}
] |
CostaDiego/mlChallenge-product-categorization | [
"1f4f2442182d3e9ed8e464a67703781c41f144a3"
] | [
"algorithm/utils.py"
] | [
"import pandas as pd\nfrom os import path, makedirs\n\nDEFAULT_COLUMN_NAME = 'Exist'\n\ndef checkDirs(dirs, create = False):\n if isinstance(dirs, list):\n print(\"\\tCheckig the structures os directories.\")\n created = []\n nonexistent = []\n for directory in dirs:\n if n... | [
[
"pandas.DataFrame"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [
"0.23",
"0.21",
"2.0",
"1.4",
"0.19",
"1.1",
"1.5",
"1.2",
"0.24",
"0.20",
"1.0",
"0.25",
"1.3"
],
"scipy": [],
"tensorflow": []
}
] |
arita37/uniplot | [
"2e49cb01132a51029ffb8a5ab3b2704fdb7e2021"
] | [
"tests/unit/test_plot_elements.py"
] | [
"import numpy as np # type: ignore\n\nfrom uniplot.plot_elements import character_for_2by2_pixels\n\n\ndef test_empty_square():\n square = np.zeros([2, 2])\n assert character_for_2by2_pixels(square) == \"\"\n\n\ndef test_full_square():\n square = np.ones([2, 2])\n assert character_for_2by2_pixels(squar... | [
[
"numpy.array",
"numpy.zeros",
"numpy.ones"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
ishine/voicefixer | [
"0966a2f39096575cf8ae3fed8b53daf2f4512f35"
] | [
"voicefixer/tools/modules/pqmf.py"
] | [
"\"\"\"\n@File : subband_util.py\n@Contact : liu.8948@buckeyemail.osu.edu\n@License : (C)Copyright 2020-2021\n@Modify Time @Author @Version @Desciption\n------------ ------- -------- -----------\n2020/4/3 4:54 PM Haohe Liu 1.0 None\n\"\"\"\n\nimport torch\nimport torch.... | [
[
"torch.nn.ConstantPad1d",
"torch.cat",
"numpy.reshape",
"torch.reshape",
"numpy.flipud",
"scipy.io.loadmat",
"torch.from_numpy",
"numpy.transpose",
"torch.nn.Conv1d",
"torch.nn.functional.pad"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [
"1.7",
"1.0",
"0.10",
"1.2",
"0.14",
"0.19",
"1.5",
"0.12",
"0.17",
"0.13",
"1.6",
"1.4",
"1.9",
"1.3",
"1.10",
"0.15",
"0.18",
"0.16"... |
Tomato1107/Cycloidal-Drive-Animation | [
"6489287ecc55e6042c64e378739d524ebc976410"
] | [
"demo_9.py"
] | [
"import numpy as np\r\nimport matplotlib.pyplot as plt\r\nimport matplotlib.animation as animation\r\nfrom matplotlib.widgets import Slider, Button\r\n#plt.rcParams['animation.ffmpeg_path'] = 'D:/portableSoftware/ShareX/ShareX/Tools/ffmpeg.exe'\r\n\r\ninterval = 50 # ms, time between animation frames\r\n\r\nfig, ax... | [
[
"numpy.linspace",
"matplotlib.widgets.Button",
"matplotlib.pyplot.ylim",
"matplotlib.pyplot.subplots",
"numpy.cos",
"numpy.sin",
"matplotlib.pyplot.axes",
"matplotlib.widgets.Slider",
"matplotlib.pyplot.xlim",
"matplotlib.animation.FuncAnimation",
"matplotlib.pyplot.sub... | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
DanielYanger/Python-Projects | [
"0d6cd76b8c10b063625e5ad80b5aaa6fc8ef7cd0"
] | [
"moreCV2.py"
] | [
"import cv2\nfrom matplotlib import pyplot as plt\nimport numpy as np\n\ncv2 = cv2.cv2\n\ncap = cv2.VideoCapture(0)\nwhile True:\n ret,frame = cap.read()\n gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)\n hsv = cv2.cvtColor(frame, cv2.COLOR_BGR2HSV)\n kernel = np.ones((35,35),np.uint8)\n kernel2 = np... | [
[
"numpy.array",
"numpy.ones"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
roclark/sports-reference-scraper | [
"fffb7c8170454720622089cf794ebcb106245e4d"
] | [
"tests/integration/roster/test_nfl_roster.py"
] | [
"import mock\nimport os\nimport pandas as pd\nimport pytest\nfrom flexmock import flexmock\nfrom sportsipy import utils\nfrom sportsipy.nfl.roster import Player, Roster\nfrom sportsipy.nfl.teams import Team\n\n\nYEAR = 2018\n\n\ndef read_file(filename):\n filepath = os.path.join(os.path.dirname(__file__), 'nfl',... | [
[
"pandas.concat",
"pandas.DataFrame"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [
"0.23",
"0.21",
"2.0",
"1.4",
"1.3",
"0.19",
"1.1",
"1.5",
"0.24",
"0.20",
"1.0",
"0.25",
"1.2"
],
"scipy": [],
"tensorflow": []
}
] |
mshafiei/cvutils | [
"5805229d8822a9ee4a3c63e060358aca96fe5338"
] | [
"cvgutils/Viz.py"
] | [
"import json\nimport re\nfrom typing import OrderedDict\nimport torch\nimport numpy as np\nimport matplotlib.pyplot as plt\nimport io\nimport cv2\nimport pickle\nimport wandb\nimport cvgutils.Dir as Dir\nimport cvgutils.Image as cvgim\nimport cvgutils.Utils as cvgutil\nfrom tensorboardX import SummaryWriter\n# from... | [
[
"matplotlib.pyplot.legend",
"matplotlib.pyplot.scatter",
"torch.Tensor",
"numpy.isnan",
"matplotlib.pyplot.ylim",
"numpy.clip",
"matplotlib.pyplot.hlines",
"matplotlib.pyplot.subplots",
"numpy.stack",
"matplotlib.pyplot.xlim",
"matplotlib.pyplot.close",
"scipy.stats... | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [
"0.13",
"1.6",
"0.14",
"1.10",
"0.15",
"1.4",
"0.16",
"1.9",
"0.19",
"1.5",
"0.18",
"1.2",
"1.7",
"0.12",
"1.0",
"0.17",
"1.3",
"1.8"
... |
MichaelHopwood/GLRM | [
"80930762e6964afb8ef0db9e5ae3a10cfcc975b2"
] | [
"examples/regularized_pca.py"
] | [
"import sys\nimport os\nsys.path.append(os.path.join('..','glrm'))\n\nfrom glrm.loss import HuberLoss, QuadraticLoss\nfrom glrm.reg import QuadraticReg\nfrom glrm.glrm import GLRM\nfrom glrm.util import pplot\nfrom numpy.random import randn, choice, seed\nfrom numpy import sign\nfrom random import sample\nfrom math... | [
[
"matplotlib.pyplot.scatter",
"numpy.random.seed",
"sklearn.datasets.load_iris",
"numpy.array",
"matplotlib.pyplot.show"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
qwzhong1988/text-detection-ocr | [
"b3f34a78699ff8a4dbc450bfa06990a8833e98da"
] | [
"dlocr/ctpn/lib/utils.py"
] | [
"import numpy as np\nimport xmltodict\nimport os\nimport cv2\nimport matplotlib.pyplot as plt\nfrom glob import glob\nfrom concurrent.futures import ThreadPoolExecutor\n\nimport tensorflow as tf\n\nanchor_scale = 16\n#\nIOU_NEGATIVE = 0.3\nIOU_POSITIVE = 0.7\nIOU_SELECT = 0.7\n\nRPN_POSITIVE_NUM = 150\nRPN_TOTAL_NU... | [
[
"numpy.hstack",
"numpy.log",
"numpy.expand_dims",
"numpy.maximum",
"numpy.minimum",
"matplotlib.pyplot.imshow",
"numpy.sum",
"numpy.arange",
"numpy.empty",
"numpy.random.shuffle",
"tensorflow.ConfigProto",
"tensorflow.GPUOptions",
"numpy.exp",
"numpy.array",... | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
EstefaniaLaverde/6-degrees-of-separation | [
"4ab0a060f9d24cf788a2beba7e8c178772cea128"
] | [
"venv/project_TDG/Lib/site-packages/igraph/utils.py"
] | [
"# vim:ts=4:sw=4:sts=4:et\n# -*- coding: utf-8 -*-\n\"\"\"Utility functions that cannot be categorised anywhere else.\"\"\"\n\nfrom contextlib import contextmanager\n\nfrom collections.abc import MutableMapping\nfrom ctypes import c_double, sizeof\nfrom itertools import chain\n\nimport os\nimport tempfile\n\n__all_... | [
[
"numpy.require"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
massquantity/LibRecommender | [
"9133f9f908a509a22459ac2423f9a7312058bc03"
] | [
"libreco/algorithms/bpr.py"
] | [
"\"\"\"\n\nReferences: Steffen Rendle et al. \"BPR: Bayesian Personalized Ranking from Implicit Feedback\"\n (https://arxiv.org/ftp/arxiv/papers/1205/1205.2618.pdf)\n\nauthor: massquantity\n\n\"\"\"\nimport os\nimport logging\nfrom itertools import islice\nfrom functools import partial\nimport numpy as n... | [
[
"tensorflow.compat.v1.log_sigmoid",
"tensorflow.compat.v1.subtract",
"numpy.zeros_like",
"tensorflow.compat.v1.keras.regularizers.l2",
"numpy.exp",
"numpy.hstack",
"tensorflow.compat.v1.train.AdamOptimizer",
"tensorflow.compat.v1.add_n",
"tensorflow.keras.initializers.truncated... | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
cookcodes/DeepFilterNet | [
"e651b79e48d5d25fd22a55514534c6c1e65f72fa"
] | [
"DeepFilterNet/df/loss.py"
] | [
"import warnings\nfrom collections import defaultdict\nfrom typing import Dict, Final, List, Optional\n\nimport torch\nimport torch.nn.functional as F\nfrom torch import Tensor, nn\nfrom torch.autograd import Function\n\nfrom df.config import config\nfrom df.model import ModelParams\nfrom df.modules import LocalSnr... | [
[
"torch.view_as_real",
"torch.finfo",
"torch.ones",
"torch.zeros",
"torch.einsum",
"matplotlib.pyplot.subplots",
"matplotlib.pyplot.savefig",
"torch.from_numpy",
"torch.matmul",
"torch.nn.functional.mse_loss",
"torch.unique",
"torch.no_grad",
"torch.isfinite",
... | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
pzivich/Deli | [
"761aa51c6949334b59fffb185be4266177454b6c"
] | [
"delicatessen/data.py"
] | [
"import numpy as np\n\n\ndef load_shaq_free_throws():\n \"\"\"Load example data from Boos and Stefanski (2013) on Shaquille O'Neal free throws in the 2000 NBA playoffs\n (Table 7.1 on pg 324).\n\n Notes\n -----\n From left to right, the columns in the array correspond to:\n * game - game numbe... | [
[
"numpy.array"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
emre6943/MoneyBoi | [
"caae1753b784b295ee8a74ea47faee4d3607cd21"
] | [
"DataProcessor.py"
] | [
"import pandas as pd\n\ndf = pd.read_csv (r'./Data/BTCUSDT_1d_data.csv')\n\n# DATE ,open, high/open, low/open, volume/open\n# 10d avarage/open, 20d avarage/open, last 30d avarage/open, need more\n\ndata = []\nbig_dad = -1\nsum = [0, 0, 0]\n\nfor index, row in df.iterrows():\n day = (index + 1) % 30\n\n #for a... | [
[
"pandas.read_csv",
"pandas.DataFrame"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [
"2.0",
"1.4",
"1.3",
"1.1",
"1.5",
"1.2"
],
"scipy": [],
"tensorflow": []
}
] |
Griffin98/3DDFA_v2 | [
"85d5676d40bdd7d0f19de20143446feb4b2a52a4"
] | [
"utils/utils.py"
] | [
"import cv2\nimport os\nimport numpy as np\nimport math\nimport os\nimport glob\nimport scipy\nfrom numpy import linalg as LA\nfrom scipy.signal import savgol_filter\nfrom sklearn import preprocessing\nfrom scipy.spatial import distance\nfrom tqdm import tqdm\nfrom scipy.spatial import cKDTree as KDTree\nfrom scipy... | [
[
"numpy.diag",
"numpy.dot",
"scipy.linalg.svd",
"numpy.linalg.matrix_rank",
"numpy.ndarray",
"numpy.round",
"numpy.mean",
"numpy.cross",
"scipy.signal.savgol_filter",
"scipy.spatial.cKDTree",
"sklearn.preprocessing.MinMaxScaler",
"numpy.square",
"numpy.linalg.svd... | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
RafaelPo/fat-forensics | [
"edd3c7e149c4534d76fe2241bc919afc5c3c4581"
] | [
"fatf/fairness/predictions/tests/test_measures_fairness_predictions.py"
] | [
"\"\"\"\nTests implementations of predictions fairness measures.\n\"\"\"\n# Author: Kacper Sokol <k.sokol@bristol.ac.uk>\n# License: new BSD\n\nimport pytest\n\nimport numpy as np\n\nfrom fatf.exceptions import IncorrectShapeError\n\nimport fatf.fairness.predictions.measures as ffpm\nimport fatf.utils.models as fum... | [
[
"numpy.ndarray",
"numpy.array",
"numpy.allclose",
"numpy.array_equal"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
piginzoo/HyperLPR | [
"75b3f2e03085b592f4726e725fe7cc9cd7b9bbd5"
] | [
"HyperLPRLite.py"
] | [
"#coding=utf-8\nimport cv2\nimport numpy as np\nfrom keras import backend as K\nfrom keras.models import *\nfrom keras.layers import *\n\nchars = [u\"京\", u\"沪\", u\"津\", u\"渝\", u\"冀\", u\"晋\", u\"蒙\", u\"辽\", u\"吉\", u\"黑\", u\"苏\", u\"浙\", u\"皖\", u\"闽\", u\"赣\", u\"鲁\", u\"豫\", u\"鄂\", u\"湘\", u\"粤\", u\"桂\",\n... | [
[
"numpy.array"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
volker42maru/transformers | [
"7ea31d06b62b47c375a6a51669b3961cf37401ca"
] | [
"src/transformers/data/data_collator.py"
] | [
"from dataclasses import dataclass\nfrom typing import Any, Callable, Dict, List, NewType, Tuple, Union\n\nimport torch\nfrom torch.nn.utils.rnn import pad_sequence\n\nfrom ..tokenization_utils import PreTrainedTokenizer\nfrom ..tokenization_utils_base import BatchEncoding\n\n\nInputDataClass = NewType(\"InputDataC... | [
[
"torch.randint",
"torch.full",
"torch.nn.utils.rnn.pad_sequence",
"torch.tensor",
"torch.bernoulli",
"torch.stack"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
Tanveer81/BoxVOS | [
"c30aa319f18f3fbee2a25e0ed25cb006a4598300"
] | [
"tools/defaults.py"
] | [
"# -*- coding: utf-8 -*-\r\n# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved\r\n\r\n\"\"\"\r\nThis file contains components with some default boilerplate logic user may need\r\nin training / testing. They will not work for everyone, but many users may find them useful.\r\n\r\nThe behavior of f... | [
[
"torch.no_grad"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
MalloryWittwer/research-analytics | [
"320c40d90cfd02e635e76805874b4a312ea894dc"
] | [
"research-analytics/utils.py"
] | [
"#--------------------------------------------------------------------------#\n# This code contains small useful functions # \n#--------------------------------------------------------------------------#\n\n# imports ------------------------------------------------------------------\n... | [
[
"pandas.read_csv"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [
"2.0",
"1.4",
"1.1",
"1.5",
"1.2",
"1.3"
],
"scipy": [],
"tensorflow": []
}
] |
GAIPS/ILU-RL | [
"42a1d1337e9b5d59c74a320ea0d93ddbb6983fdd"
] | [
"ilurl/envs/controllers.py"
] | [
"\"\"\"Implementation of classic adaptive controllers and methods\"\"\"\nimport copy\n\nimport numpy as np\n\nfrom collections import namedtuple\n\nPressurePhase = namedtuple('PressurePhase', 'id time yellow')\n\ndef is_controller_periodic(ts_type):\n if ts_type in ('rl', 'random', 'static', 'webster'):\n ... | [
[
"numpy.around",
"numpy.argmax"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
kann-tsukasa/large-scale-pretraining-transfer | [
"b451abf65d4b557eeaf745e8054ddca4762cb71b"
] | [
"pretrain.py"
] | [
"from functools import partial\nimport math\nimport os\nimport datetime\nimport time\nimport argparse\nfrom tqdm import tqdm\n\nimport torch\nimport torch.nn as nn\nimport torch.backends.cudnn as cudnn\nimport torch.multiprocessing as mp\nimport torch.nn.functional as F\nimport torch.optim as optim\nimport torch.ut... | [
[
"torch.cuda.manual_seed",
"torch.load",
"torch.isnan",
"torch.manual_seed",
"torch.nn.functional.binary_cross_entropy_with_logits",
"torch.nn.functional.cross_entropy",
"torch.tensor",
"torch.cuda.amp.GradScaler",
"torch.no_grad",
"torch.utils.tensorboard.SummaryWriter",
... | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
PasaOpasen/cost2fitness | [
"b6bb0ca613e37c357a870b6ae8c7335b7ad0dbcc"
] | [
"cost2fitness/bar_plots.py"
] | [
"\nimport numpy as np \nimport matplotlib.pyplot as plt \n\n\n\ndef plot_scores(scores, names = None, kind = 'beside', save_as = None):\n \"\"\"\n Plot results of transformation\n\n Parameters\n ----------\n scores : 2D numpy array\n 2D numpy array with structure [start_values, first_transform(... | [
[
"numpy.random.random",
"numpy.arange",
"matplotlib.pyplot.subplots",
"matplotlib.pyplot.savefig",
"matplotlib.pyplot.show",
"matplotlib.pyplot.figure"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
DevinJake/MARL | [
"cafbc0411ab70f68652029832cd65127d4be5f94"
] | [
"S2SRL/libbots/metalearner_webqsp.py"
] | [
"import torch\nfrom torch.nn.utils.convert_parameters import (vector_to_parameters,\n parameters_to_vector)\nfrom . import data, model, utils, retriever_webqsp, reparam_module, adabound\nimport torch.optim as optim\nimport torch.nn.functional as F\nimport random\nimport... | [
[
"torch.LongTensor",
"torch.nn.functional.log_softmax",
"torch.cat",
"torch.FloatTensor",
"torch.stack",
"torch.autograd.grad"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
29rou/OpenJij | [
"c2579fba8710cf82b9e6761304f0042b365b595c"
] | [
"tests/test_model.py"
] | [
"import unittest\n\nimport numpy as np\nimport openjij as oj\nimport cxxjij as cj\n\n\ndef calculate_ising_energy(h, J, spins):\n energy = 0.0\n for (i, j), Jij in J.items():\n energy += Jij*spins[i]*spins[j]\n for i, hi in h.items():\n energy += hi * spins[i]\n return energy\n\n\ndef calc... | [
[
"numpy.array"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
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