repo_name stringlengths 6 130 | hexsha list | file_path list | code list | apis list |
|---|---|---|---|---|
skiniry/Trips-Viz | [
"a742a6c7d0c9758e3c439828e804025d7fc44b4f"
] | [
"riboflask_compare.py"
] | [
"import matplotlib\nmatplotlib.use('agg')\nfrom matplotlib import pyplot as plt\nimport mpld3\nfrom mpld3 import plugins,utils\nfrom new_plugins import InteractiveLegendPlugin,TopToolbar,DownloadProfile,DownloadPNG\nfrom fetch_shelve_reads2 import get_reads\nimport sqlite3\nimport config\nimport os\nimport config\n... | [
[
"matplotlib.use",
"matplotlib.pyplot.title",
"matplotlib.pyplot.MaxNLocator",
"matplotlib.pyplot.figure",
"matplotlib.pyplot.subplot2grid"
]
] |
Tomspiano/D2L-PyTorch | [
"c748c72a2da66211bd88c1adcd048b05be40e77c"
] | [
"chapters/chp4/mlp.py"
] | [
"import torch\nfrom modules import base\nfrom modules import fashionMNIST as fmnist\nfrom torch import nn\nfrom torch.nn import init\nfrom modules import d2lCustom as custom\n\n\ndef train(num_inputs, num_hiddens, num_outputs, train_iter, test_iter, eps):\n # epoch 46, loss 0.155, train acc 0.943, test acc 0.883... | [
[
"torch.nn.Linear",
"torch.nn.init.normal_",
"torch.nn.CrossEntropyLoss",
"torch.nn.ReLU"
]
] |
MobMonRob/ArmMovementPredictionStudien | [
"7086f7b044d54b023c7d40e9413c35178a1ad084"
] | [
"PREPROCESSING/manual_labeling/mark_good_datasets_manually.py"
] | [
"import os\nfrom tkinter import *\n\nfrom ArmMovementPredictionStudien.PREPROCESSING.utils.utils import open_dataset_numpy\nfrom ArmMovementPredictionStudien.PREPROCESSING.visualisation.visualise_files import visualise\nimport matplotlib.pyplot as plt\n\nfirst = True\nfile_list = os.listdir(\"../../DATA/0_raw/\")\n... | [
[
"matplotlib.pyplot.close"
]
] |
felixstillger/Mask_RCNN | [
"fab32b45cd104f8df63906157606024c2897ca3e"
] | [
"mrcnn/visualize.py"
] | [
"\"\"\"\nMask R-CNN\nDisplay and Visualization Functions.\n\nCopyright (c) 2017 Matterport, Inc.\nLicensed under the MIT License (see LICENSE for details)\nWritten by Waleed Abdulla\n\"\"\"\n\nimport os\nimport sys\nimport random\nimport itertools\nimport colorsys\n\nimport numpy as np\nfrom skimage.measure import ... | [
[
"numpy.random.choice",
"numpy.random.rand",
"numpy.where",
"matplotlib.patches.Rectangle",
"numpy.concatenate",
"matplotlib.pyplot.savefig",
"matplotlib.pyplot.subplots",
"numpy.arange",
"matplotlib.pyplot.tight_layout",
"matplotlib.pyplot.axis",
"matplotlib.pyplot.subp... |
ZhenqiSong/OCR_Pytorch | [
"df4e8c53353b6c515509241d4c9af3b153224a10"
] | [
"models/necks/db_fpn.py"
] | [
"# -*- coding: utf-8 -*-\n# __author__:Song Zhenqi\n# 2021-01-26\n\nimport torch\nimport torch.nn as nn\nfrom torch.nn import functional as F\nfrom . import register_neck\n\n\n@register_neck('DBFPN')\nclass DBFPN(nn.Module):\n def __init__(self, in_channels, out_channels, **kwargs):\n super(DBFPN, self)._... | [
[
"torch.nn.Conv2d",
"torch.cat",
"torch.nn.functional.interpolate"
]
] |
dafeigediaozhatian/MILNet | [
"d60c894952f9b153051ccc8397608a06b6661d2b"
] | [
"MILNet.py"
] | [
"# -*- coding: utf-8 -*-\nimport os\nimport numpy as np\n\nimport torch\nimport torch.optim as optim\nfrom tensorboardX import SummaryWriter\n\nfrom scipy import stats\nfrom tqdm import tqdm\nfrom config_aesthetic import get_args\nfrom utils.filter_nan import filter_nan\n\nfrom data.gcn_dataloader_6144 import AVADa... | [
[
"numpy.array",
"torch.no_grad",
"scipy.stats.spearmanr",
"scipy.stats.pearsonr",
"torch.squeeze",
"numpy.prod",
"torch.cuda.is_available",
"torch.utils.data.DataLoader",
"torch.transpose",
"torch.Tensor"
]
] |
pgdr/mcelfish | [
"55c736f8425d0ab425dab999094ada4bafb9ca54"
] | [
"mcelfish/plot_beta.py"
] | [
"from scipy.stats import beta\nimport matplotlib.pyplot as plt\nimport numpy as np\nimport sys\n\n\ndef _gen(alpha_, beta_, loc_=0, scale_=1):\n return np.linspace(\n beta.ppf(0.01, alpha_, beta_, loc_, scale_),\n beta.ppf(0.99, alpha_, beta_, loc_, scale_),\n 100,\n )\n\n\ndef _plot(x, a... | [
[
"matplotlib.pyplot.show",
"scipy.stats.beta.pdf",
"scipy.stats.beta.ppf"
]
] |
phoebsc/mask_ild | [
"2a960b33a3952a39edcb30b44a3e6ea27157fedb"
] | [
"model.py"
] | [
"\"\"\"\nMask R-CNN\nThe main Mask R-CNN model implemenetation.\n\nCopyright (c) 2017 Matterport, Inc.\nLicensed under the MIT License (see LICENSE for details)\nWritten by Waleed Abdulla\n\"\"\"\n\nimport os\nimport sys\nimport glob\nimport random\nimport math\nimport datetime\nimport itertools\nimport json\nimpor... | [
[
"tensorflow.exp",
"numpy.random.choice",
"tensorflow.image.non_max_suppression",
"numpy.minimum",
"numpy.copy",
"numpy.rint",
"numpy.multiply",
"numpy.where",
"tensorflow.sqrt",
"numpy.sort",
"tensorflow.stack",
"tensorflow.control_dependencies",
"tensorflow.ide... |
ChinaKevinLi/Leaving-Lock | [
"9a57f2cca5c294fd413ca1306676731579723cfb"
] | [
"Main.py"
] | [
"import face_recognition\r\nimport cv2\r\nimport numpy as np\r\nimport os\r\nimport time\r\nend_time = 0\r\n\r\nvideo_capture = cv2.VideoCapture(0)\r\n\r\n\r\nknown_face_encodings = [\r\n]\r\nuser_path = \"./users/\"\r\nuser_name = \"Owner\"\r\nsaved_encodings = os.listdir(user_path + user_name + \"/\")\r\n\r\nfor ... | [
[
"numpy.load"
]
] |
timcallow/atoMEC | [
"8c945caf6afcfffbeebe4356edd3c968eb7833dc"
] | [
"atoMEC/postprocess/conductivity.py"
] | [
"\"\"\"\nThe conductivity module handles routines used to model the electrical conductivity.\n\nSo far just the Kubo-Greenwood method is implemented.\n\nClasses\n-------\n* :class:`KuboGreenwood` : Holds various routines needed to compute the Kubo-Greenwood \\\n conducivity, including its ... | [
[
"numpy.zeros",
"numpy.ones",
"numpy.exp",
"numpy.shape",
"numpy.where",
"numpy.einsum",
"numpy.trapz",
"numpy.abs",
"numpy.sqrt",
"scipy.special.lpmv",
"numpy.size",
"numpy.gradient",
"scipy.integrate.quad"
]
] |
jannctu/TIN | [
"bb1a49a16e4f206b114aa3abf3dda3726a8a6b45"
] | [
"test.py"
] | [
"import torch\nfrom model import TIN\nimport os\nfrom os.path import join\nimport numpy as np\nfrom PIL import Image\nimport scipy.io as io\nimport cv2\nimport time\n\ntest_img = 'img/mri_brain.jpg'\n## READ IMAGE\nim = np.array(cv2.imread(test_img), dtype=np.float32)\n## Multiscale\nscales = [0.5,1.0,1.5]\nimages ... | [
[
"torch.no_grad",
"numpy.zeros",
"torch.load",
"torch.from_numpy"
]
] |
yala/Tempo | [
"bf3e0e78d64869bb2079c582a4a35982f78386ad"
] | [
"oncopolicy/utils/learn.py"
] | [
"import pickle\nimport json\nimport warnings\nimport torch\nimport numpy as np\nfrom torch.utils import data\nimport sklearn.metrics\nfrom collections import defaultdict, OrderedDict, Counter\nfrom oncopolicy.metrics.factory import get_metrics_with_cis\n\n\ndef init_metrics_dictionary():\n '''\n Return empty ... | [
[
"torch.utils.data.dataloader.default_collate",
"torch.utils.data.DataLoader"
]
] |
giomara-larraga/desdeo-emo | [
"d891e9a12b25d02af5dfba5b17b4c2c4c0bd3d53"
] | [
"desdeo_emo/EAs/IOPIS.py"
] | [
"from typing import Dict, Union, List\n\nfrom desdeo_emo.EAs.BaseEA import eaError\nfrom desdeo_emo.EAs.BaseEA import BaseDecompositionEA, BaseEA\nfrom desdeo_emo.EAs.RVEA import RVEA\nfrom desdeo_emo.population.Population import Population\nfrom desdeo_emo.selection.IOPIS_APD import IOPIS_APD_Select\nfrom desdeo_e... | [
[
"numpy.random.randint"
]
] |
hpatel1567/pymatgen | [
"8304b25464206c74305214e45935df90bab95500"
] | [
"pymatgen/symmetry/maggroups.py"
] | [
"# coding: utf-8\n# Copyright (c) Pymatgen Development Team.\n# Distributed under the terms of the MIT License.\n\n\"\"\"\nMagnetic space groups.\n\"\"\"\n\nimport os\nfrom fractions import Fraction\nimport numpy as np\nfrom monty.design_patterns import cached_class\n\nimport textwrap\n\nfrom pymatgen.electronic_st... | [
[
"numpy.round",
"numpy.array",
"numpy.array_equal"
]
] |
JeyDi/BayesianMLOptimization | [
"ba3ddf5bb9919a5043b4e982dea46425631696d3"
] | [
"experiment.py"
] | [
"# import of the required libraries\nimport numpy as np\nimport timeit\n\n\nfrom pyGPGO.covfunc import squaredExponential\nfrom pyGPGO.surrogates.GaussianProcess import GaussianProcess\nfrom pyGPGO.surrogates.RandomForest import RandomForest\nfrom pyGPGO.GPGO import GPGO\nfrom pyGPGO.acquisition import Acquisition\... | [
[
"numpy.asarray",
"numpy.random.seed",
"numpy.linspace",
"sklearn.svm.SVC",
"sklearn.datasets.load_wine",
"sklearn.model_selection.cross_val_score"
]
] |
zonca/astropy | [
"351fa20305886a907ec0829dd5fa53f30a5ba6ff",
"351fa20305886a907ec0829dd5fa53f30a5ba6ff"
] | [
"astropy/io/fits/hdu/groups.py",
"astropy/modeling/tests/test_projections.py"
] | [
"# Licensed under a 3-clause BSD style license - see PYFITS.rst\n\nimport sys\nimport numpy as np\n\nfrom .base import DTYPE2BITPIX\nfrom .image import PrimaryHDU\nfrom .table import _TableLikeHDU\nfrom astropy.io.fits.column import Column, ColDefs, FITS2NUMPY\nfrom astropy.io.fits.fitsrec import FITS_rec, FITS_rec... | [
[
"numpy.prod",
"numpy.rec.array",
"numpy.rec.recarray.field"
],
[
"numpy.testing.assert_allclose",
"numpy.array",
"numpy.asarray",
"numpy.testing.assert_almost_equal",
"numpy.linalg.inv",
"numpy.arange",
"numpy.all",
"numpy.linspace",
"numpy.meshgrid"
]
] |
AlexanderFabisch/slither | [
"c527e0412cf89197f907a42699a554f26cb2af59"
] | [
"slither/core/analysis.py"
] | [
"from collections import deque\n\nimport numpy as np\nfrom scipy.signal import medfilt\n\nfrom .config import config\n\n\ndef check_coords(coords):\n \"\"\"Filter non-finite GPS coordinates.\n\n Parameters\n ----------\n coords : array, shape (n_steps, 2)\n Latitudes and longitudes\n\n Returns... | [
[
"numpy.isnan",
"numpy.asarray",
"numpy.median",
"numpy.sum",
"numpy.ones",
"numpy.nonzero",
"numpy.diff",
"numpy.where",
"scipy.signal.medfilt",
"numpy.argmax",
"numpy.sqrt",
"numpy.isfinite",
"numpy.cumsum",
"numpy.gradient"
]
] |
Dannyaffleck/stock | [
"9c6c62b798e4e3306a7bf4a185a0b4fca37cdd33"
] | [
"money.py"
] | [
"import math\nfrom scipy import stats\nimport numpy as np\nlisty=[1.58,1.57,1.54,1.51,1.51,1.51,1.5099,1.5,1.48,1.44,1.44,1.43,1.44,1.46,1.46,1.46,1.46,1.46,1.46,1.46,1.46,1.46,1.455,1.445,1.44,1.44,1.43,1.46,1.46,1.46,1.45,1.45,1.45,1.45,1.45,1.45,1.45,1.45,1.45,1.45,1.45,1.45,1.45,1.45,1.45,1.45,1.45,1.45,1.44,1.... | [
[
"numpy.array",
"scipy.stats.linregress"
]
] |
brianWeng0223/mljar-supervised | [
"d7c6a969792c6efbff264c8743a645b098e24dd2"
] | [
"supervised/tuner/mljar_tuner.py"
] | [
"import os\nimport copy\nimport json\nimport numpy as np\nimport pandas as pd\n\nfrom sklearn.preprocessing import OneHotEncoder\n\nfrom supervised.tuner.random_parameters import RandomParameters\nfrom supervised.algorithms.registry import AlgorithmsRegistry\nfrom supervised.preprocessing.preprocessing_categorical ... | [
[
"numpy.max",
"numpy.array",
"numpy.round",
"pandas.DataFrame",
"numpy.argsort",
"sklearn.preprocessing.OneHotEncoder",
"numpy.unique"
]
] |
pavponn/optimization-methods | [
"00db08c1b28a1ffad781fb918869247a4f2ab329"
] | [
"lab1/src/generators/optimization_task_generator.py"
] | [
"import numpy as np\n\nfrom functools import partial\nfrom lab1.src.generators.quadratic_form_generator import generate_matrix_with_condition_number\n\n\ndef generate_function_by_quadratic_matrix(m):\n def foo(x):\n return sum(m[i][j] * x[i] * x[j] for i in range(len(m)) for j in range(len(m)))\n\n ret... | [
[
"numpy.array"
]
] |
eechava6/NumericalAnalysis | [
"1b44349fe4c5e24413c3d5faeca7d227272814ec"
] | [
"methods/crout.py"
] | [
"import ast\r\nimport json\r\n\r\nimport numpy as np\r\nfrom methods.utils import progressiveSustitution, regresiveSustitutions, isSquared\r\n\r\n\r\ndef crout(A,b):\r\n A = ast.literal_eval(A)\r\n b = ast.literal_eval(b)\r\n A = np.array(A).astype(float)\r\n b = np.array(b).astype(float)\r\n pivots ... | [
[
"numpy.identity",
"numpy.array",
"numpy.linalg.det",
"numpy.zeros"
]
] |
NeerajAI/PICK-pytorch | [
"61deb7c1e11df30c8f03726c061a2866234ac770"
] | [
"inference.py"
] | [
"import os\nimport os\nprint(os.getcwd())\n# os.path.dirname(os.path.abspath(\"__file__\"))\npath = '/Volumes/Extreme SSD/MLWork/DocAI/PICK-pytorch'\nos.chdir(path)\n# os.chdir('../')\n# path = '/Users/neerajyadav/Documents/pycv/PICK-pytorch/'\n\n\"\"\"Convert files of a selected directory in jpg format\"\"\"\nimpo... | [
[
"torch.device",
"torch.no_grad",
"torch.load",
"pandas.DataFrame"
]
] |
bamford/pandas | [
"a474af5b4526dc333f62260587a1d8ef494df57c"
] | [
"pandas/tests/frame/indexing/test_where.py"
] | [
"from datetime import datetime\n\nfrom hypothesis import (\n given,\n settings,\n)\nimport numpy as np\nimport pytest\n\nfrom pandas.compat import np_version_under1p19\n\nfrom pandas.core.dtypes.common import is_scalar\n\nimport pandas as pd\nfrom pandas import (\n DataFrame,\n DatetimeIndex,\n Serie... | [
[
"pandas.DatetimeIndex",
"pandas.notna",
"pandas.Timestamp",
"numpy.where",
"pandas._testing.assert_series_equal",
"pandas.period_range",
"numpy.dtype",
"pandas.notnull",
"pandas.Interval",
"pandas.DataFrame",
"numpy.random.randint",
"numpy.arange",
"pandas._test... |
GreenCUBIC/GasBotty | [
"158f5991201c80bf4cbbbb9deabc9954ff19bbb1"
] | [
"GasBotty/models/googlenet.py"
] | [
"import warnings\r\nfrom collections import namedtuple\r\nimport torch\r\nimport torch.nn as nn\r\nimport torch.nn.functional as F\r\nfrom .utils import load_state_dict_from_url\r\n\r\n__all__ = ['GoogLeNet', 'googlenet']\r\n\r\nmodel_urls = {\r\n # GoogLeNet ported from TensorFlow\r\n 'googlenet': 'https://d... | [
[
"torch.nn.Linear",
"torch.nn.Dropout",
"torch.cat",
"torch.flatten",
"torch.nn.MaxPool2d",
"torch.nn.init.constant_",
"torch.nn.functional.dropout",
"torch.nn.BatchNorm2d",
"scipy.stats.truncnorm",
"torch.nn.functional.adaptive_avg_pool2d",
"torch.no_grad",
"torch.n... |
MFrassek/CommittorEAE | [
"88a467e4500bc9ab69834209f4eaec9f2d0d7a61"
] | [
"NucleationModel/gridifier.py"
] | [
"import numpy as np\n\n\nclass Gridifier():\n def __init__(self, base_snapshots, resolution):\n self._minima = np.amin(base_snapshots, axis=0)\n self._maxima = np.amax(base_snapshots, axis=0)\n self._spans = np.array(\n [span if span != 0 else 1 for span in self._maxima - self._mi... | [
[
"numpy.array",
"numpy.amax",
"numpy.floor",
"numpy.amin"
]
] |
maartenbreddels/vaex | [
"633970528cb5091ef376dbca2e4721cd42525419"
] | [
"packages/vaex-core/vaex/expression.py"
] | [
"import ast\nimport copy\nimport os\nimport base64\nimport datetime\nfrom pydoc import doc\nimport time\nimport cloudpickle as pickle\nimport functools\nimport operator\nimport six\nimport collections\nimport weakref\n\nfrom future.utils import with_metaclass\nimport numpy as np\nimport pandas as pd\nimport tabulat... | [
[
"numpy.delete",
"numpy.array",
"numpy.isnan",
"numpy.datetime_data",
"numpy.ma.isMaskedArray",
"numpy.ma.getmaskarray",
"numpy.ma.array",
"numpy.argsort",
"pandas.Series",
"numpy.dtype",
"numpy.datetime64"
]
] |
mghro/MIRDCalculation | [
"aa2435d0f77a01c81c519a6f828f508cacf55830"
] | [
"DICOM_RT/DicomPatient.py"
] | [
"#!/usr/bin/env python3\n# -*- coding: utf-8 -*-\n\"\"\"\nCreated on Thu May 27 16:09:19 2021\n\n@author: alejandrobertolet\n\"\"\"\n\nfrom os import listdir\n\nimport numpy as np\nimport pydicom\nfrom rt_utils import RTStructBuilder\n\nimport matplotlib.pylab as plt\nfrom datetime import datetime\n\nclass DicomPat... | [
[
"numpy.max",
"numpy.array",
"numpy.zeros",
"numpy.sum",
"numpy.min",
"matplotlib.pylab.subplot",
"numpy.swapaxes",
"numpy.power",
"numpy.abs",
"numpy.floor"
]
] |
liuzh91/gluon-nlp | [
"189bbdcc56d8e58aa908963949687b99ff9a3cff"
] | [
"scripts/preprocess/clean_tok_mono_corpus.py"
] | [
"import argparse\nimport os\nimport multiprocessing\nimport time\nimport numpy as np\nimport warnings\nimport re\nfrom gluonnlp.data.filtering import MosesNormalizer\nfrom gluonnlp.data.tokenizers import MosesTokenizer, BaseTokenizer,\\\n WhitespaceTokenizer, JiebaTokenizer\nfrom... | [
[
"numpy.array"
]
] |
zarajfr/Visualising_Syrian_flow | [
"8e7eae5e8b44ca0e50b237d98b4a5e0ecaa57efe"
] | [
"scripts/map_destination_flow.py"
] | [
"import numpy as np\nimport matplotlib.pyplot as plt\nimport random\nfrom random import shuffle\nimport seaborn as sns\nimport math\nfrom pprint import pprint\nimport matplotlib\nfrom matplotlib.cm import cool\nimport csv\nimport matplotlib.gridspec as gridspec\nimport matplotlib.colors as colors\nimport geopandas ... | [
[
"pandas.DataFrame",
"matplotlib.colors.TwoSlopeNorm"
]
] |
leonarduschen/zipline | [
"5e6c9fce7e0f812bd181024ad192ca2976d49667"
] | [
"tests/pipeline/test_blaze.py"
] | [
"\"\"\"\nTests for the blaze interface to the pipeline api.\n\"\"\"\nfrom __future__ import division\n\nfrom collections import OrderedDict\nfrom datetime import timedelta, time\nfrom functools import partial\nfrom itertools import product, chain\nfrom unittest import skipIf\nimport warnings\n\nimport blaze as bz\n... | [
[
"pandas.to_datetime",
"pandas.Index",
"numpy.isnan",
"numpy.array",
"pandas.Timedelta",
"pandas.DatetimeIndex",
"pandas.DataFrame",
"pandas.date_range",
"numpy.tile",
"pandas.Timestamp",
"pandas.Categorical",
"numpy.arange",
"pandas.concat",
"numpy.hstack"
... |
ESMG/PyCNAL_legacy | [
"a4f6547bce872068a5bb5751231017bc3e4a4503"
] | [
"pycnal_toolbox/pycnal_toolbox/plot_coast_line_from_mask.py"
] | [
"import numpy as np\nimport matplotlib.pyplot as plt\nimport matplotlib.collections as collections\nfrom pycnal_toolbox import get_coast_line_from_mask\n\n\ndef plot_coast_line_from_mask(msk, lon, lat, proj=None):\n '''\n plot_coast_line_from_mask(msk, {proj})\n\n plot the coastline from msk. \n proj=ma... | [
[
"matplotlib.collections.LineCollection",
"numpy.array",
"matplotlib.pyplot.gca",
"numpy.zeros"
]
] |
VincentGaoHJ/Nonnegative-Matrix-Factorization | [
"c272bfd6de86b9e2c815f4e4e8629cc27073edd6"
] | [
"src/visual_func/visualize.py"
] | [
"# -*- coding: utf-8 -*-\n\"\"\"\nCreated on 2019/3/18\n\n@author: Haojun Gao\n\"\"\"\n\nimport os\nimport heapq\nimport pickle\nimport numpy as np\nimport matplotlib.pyplot as plt\nfrom sklearn.decomposition import PCA\nfrom mpl_toolkits.mplot3d import Axes3D\nfrom src.config import (\n VISUAL_TYPE)\n\n\ndef no... | [
[
"numpy.delete",
"matplotlib.pyplot.savefig",
"numpy.sum",
"numpy.nansum",
"matplotlib.pyplot.legend",
"matplotlib.pyplot.plot",
"matplotlib.pyplot.xlabel",
"matplotlib.pyplot.figure",
"matplotlib.pyplot.title",
"numpy.argmax",
"matplotlib.pyplot.ylabel",
"matplotlib... |
dimelab-public/MTConnect-Testbed-Simulator-Public | [
"4b42052953d042418ddecbd5ed8608ccbdbaa189",
"4b42052953d042418ddecbd5ed8608ccbdbaa189"
] | [
"mother_adp.py",
"mother_agents.py"
] | [
"# -*- coding: utf-8 -*-\nimport pandas as pd\nimport random\nfrom math import floor\nmaster = pd.read_csv('dbs\\master.csv')\n\n#////////////////////////////////////////////////\"\"\n\nfile = open(\"parameters.txt\",\"r+\")\nparameters=dict()\nlines = file.readlines()\nfor i in lines:\n temp=i.split(\"=\")\n ... | [
[
"pandas.read_csv"
],
[
"pandas.read_csv"
]
] |
yangyujie-jack/spinningup | [
"794f6e824450ec3b20abac6e0b8405d4b065e7dd"
] | [
"spinup/algos/pytorch/sac/sac.py"
] | [
"from copy import deepcopy\nimport itertools\nimport numpy as np\nimport torch\nfrom torch.optim import Adam\nimport gym\n# import time\nimport spinup.algos.pytorch.sac.core as core\n# from spinup.utils.logx import EpochLogger\nfrom spinup.utils.logger import Logger\n\n\nclass ReplayBuffer:\n \"\"\"\n A simpl... | [
[
"torch.min",
"numpy.zeros",
"numpy.random.seed",
"torch.no_grad",
"torch.optim.Adam",
"torch.get_num_threads",
"torch.manual_seed",
"numpy.random.randint",
"torch.as_tensor"
]
] |
prakashdale/prakashdale.github.io | [
"7e23a4f5d8c9c64bcc910ef6e0b7337a65feeff2"
] | [
"src/opencv/17_smoothing-blurring-images.py"
] | [
"import cv2\nimport numpy as np\nfrom matplotlib import pyplot as plt\n\nimg = cv2.imread('saltandpeppernoise.jpg')\nimg = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)\n\nkernal = np.ones((5,5), np.float)/25\ndst = cv2.filter2D(img, -1, kernal) #homogeneous filter\nblur = cv2.blur(img, (5, 5))\ngblur = cv2.GaussianBlur(img... | [
[
"matplotlib.pyplot.subplot",
"numpy.ones",
"matplotlib.pyplot.title",
"matplotlib.pyplot.yticks",
"matplotlib.pyplot.show",
"matplotlib.pyplot.xticks",
"matplotlib.pyplot.imshow"
]
] |
lartpang/OpticalFlowBasedVOS | [
"cd4856644b77dd963133797c543aeafb4f402217"
] | [
"backbone/deeplabv3_cosnet/deeplabv3.py"
] | [
"# -*- coding: utf-8 -*-\n\"\"\"\nCreated on Sun Sep 16 10:01:14 2018\n\n@author: carri\n\"\"\"\n\nimport torch\nimport torch.nn as nn\nimport torch.nn.functional as F\n\n__all__ = [\"Res_Deeplab\"]\n\nfrom backbone.utils import load_pretrained_params\n\nmodel_urls = {\"res_deeplabv3\": \"/home/lart/Datasets/Pretai... | [
[
"torch.rand",
"torch.cat",
"torch.nn.MaxPool2d",
"torch.nn.Sequential",
"torch.nn.BatchNorm2d",
"torch.nn.functional.interpolate",
"torch.nn.ReLU",
"torch.nn.Conv2d",
"torch.nn.PReLU",
"torch.load",
"torch.nn.AdaptiveAvgPool2d"
]
] |
pesummary/pesummary | [
"99e3c450ecbcaf5a23564d329bdf6e0080f6f2a8"
] | [
"pesummary/conf/configuration.py"
] | [
"import numpy as np\nimport pkg_resources\nimport os\n\n# matplotlib style file\n_path = pkg_resources.resource_filename(\"pesummary\", \"conf\")\nstyle_file = os.path.join(_path, \"matplotlib_rcparams.sty\")\n\n# checkpoint file\ncheckpoint_dir = lambda webdir: os.path.join(webdir, \"checkpoint\")\nresume_file = \... | [
[
"numpy.exp"
]
] |
dataubc/Modeling_IFT_for_heavy_oil_emulsion | [
"e9a9e75fbf6434d755979c4b616801d60c8a617f"
] | [
"linear.py"
] | [
"import pandas as pd\n\n# import#\n\nfrom sklearn.pipeline import Pipeline\nfrom sklearn.linear_model import Ridge\nfrom sklearn.model_selection import train_test_split, GridSearchCV\nfrom sklearn.compose import ColumnTransformer\nfrom sklearn.impute import SimpleImputer\nfrom sklearn.preprocessing import StandardS... | [
[
"sklearn.impute.SimpleImputer",
"sklearn.preprocessing.StandardScaler",
"sklearn.model_selection.GridSearchCV",
"pandas.read_excel",
"sklearn.linear_model.Ridge",
"sklearn.compose.ColumnTransformer",
"sklearn.model_selection.train_test_split",
"sklearn.preprocessing.OneHotEncoder"
... |
javigm98/Mejorando-el-Aprendizaje-Automatico | [
"fefdbb5c3b3826230738b3e5fbd76f64e701d344"
] | [
"quantizer.py"
] | [
"import sys\n\ndataset_dir = sys.argv[1]\nh5_dir = sys.argv[2]\ntflite_dir= sys.argv[3]\n\nimages = []\nimport numpy as np\nwith open(dataset_dir, 'rb') as f:\n for _ in range(500):\n images.append(np.load(f))\nprint(\"Loaded images shape: \", images[20].shape)\nimport tensorflow as tf \ndef representativ... | [
[
"tensorflow.dtypes.cast",
"tensorflow.data.Dataset.from_tensor_slices",
"tensorflow.lite.Interpreter",
"numpy.load",
"tensorflow.keras.models.load_model",
"tensorflow.lite.TFLiteConverter.from_keras_model"
]
] |
TheDudeFromCI/generative-toolkit | [
"4a0aed629b72e6eea807dadc460afa90dd330f7f"
] | [
"gentool/__main__.py"
] | [
"import sys\nimport argparse\n\nimport torch\n\nfrom ModelLoader import load_model\n\n\ndef main():\n parser = argparse.ArgumentParser(prog='gentool')\n parser.add_argument(\"--training\", action='store_true', help=\"Whether or not to start the model in training mode.\")\n parser.add_argument(\"--model\", ... | [
[
"torch.set_default_tensor_type"
]
] |
cheeseonhead/openpilot | [
"4262a15a5ac7999c029a1d33a825f12dbae27806"
] | [
"selfdrive/camerad/test/frame_test.py"
] | [
"#!/usr/bin/env python3\nimport numpy as np\nimport cereal.messaging as messaging\nfrom PIL import ImageDraw, Image\n\n# font = ImageFont.truetype(\"arial\", size=72)\ndef get_frame(idx):\n img = np.zeros((874, 1164, 3), np.uint8)\n img[100:400, 100:100+(idx % 10) * 100] = 255\n\n # big number\n im2 = Image.new... | [
[
"numpy.zeros"
]
] |
MaxBlesch/ruspy | [
"5e7fb9e584c7e0d4935f4669e108bbf4e05209c6"
] | [
"ruspy/test/estimation_tests/test_ambiguity.py"
] | [
"\"\"\"\nThis module contains tests for the data and estimation code of the ruspy project. The\nsettings for this tests is specified in resources/replication_test/init_replication.yml.\nThe test first reads the original data, then processes the data to a pandas DataFrame\nsuitable for the estimation process. After ... | [
[
"pandas.read_pickle",
"numpy.testing.assert_allclose",
"pandas.DataFrame",
"numpy.testing.assert_array_almost_equal",
"numpy.loadtxt"
]
] |
bruecks2/darts | [
"4cf51f7cfffdc53049bdca6f9eb54eaf5810eaa5"
] | [
"darts/datasets/__init__.py"
] | [
"\"\"\"\nDatasets\n--------\n\nA few popular time series datasets\n\"\"\"\nfrom pathlib import Path\nfrom typing import List\n\nimport numpy as np\nimport pandas as pd\n\nfrom darts import TimeSeries\nfrom darts.logging import get_logger, raise_if_not\n\nfrom .dataset_loaders import DatasetLoaderCSV, DatasetLoaderM... | [
[
"pandas.to_datetime",
"pandas.DataFrame"
]
] |
pecey/mbrl-lib | [
"ebca518b35a1370dbaede2a1c96fcde714bc5489"
] | [
"mbrl/third_party/pytorch_sac/agent/critic.py"
] | [
"import torch\nfrom torch import nn\n\nfrom mbrl.third_party.pytorch_sac import utils\n\n\nclass DoubleQCritic(nn.Module):\n \"\"\"Critic network, employes double Q-learning.\"\"\"\n\n def __init__(self, obs_dim, action_dim, hidden_dim, hidden_depth):\n super().__init__()\n\n self.Q1 = utils.mlp... | [
[
"torch.cat"
]
] |
gerritholl/MetPy | [
"3f08b770485835982989f34aedb87791af250301"
] | [
"src/metpy/calc/thermo.py"
] | [
"# Copyright (c) 2008,2015,2016,2017,2018,2019 MetPy Developers.\n# Distributed under the terms of the BSD 3-Clause License.\n# SPDX-License-Identifier: BSD-3-Clause\n\"\"\"Contains a collection of thermodynamic calculations.\"\"\"\nimport contextlib\nimport warnings\n\nimport numpy as np\nimport scipy.integrate as... | [
[
"numpy.isclose",
"numpy.copy",
"numpy.exp",
"numpy.min",
"numpy.where",
"numpy.broadcast_to",
"numpy.concatenate",
"numpy.max",
"numpy.full",
"numpy.zeros_like",
"numpy.empty",
"numpy.log",
"numpy.nanmin",
"numpy.swapaxes",
"numpy.argmax",
"numpy.tra... |
AmirSalari/DoHLyzer | [
"07e0a1e64310dad779934a97ebe7db2a03eff3d9"
] | [
"analyzer/models/v3.py"
] | [
"from tensorflow.keras import Sequential\nfrom tensorflow.keras.layers import Dense, Dropout, LSTM, Conv1D, MaxPool1D, Flatten\n\n\ndef create_model(segment_size):\n model = Sequential()\n model.add(Conv1D(segment_size * 2, kernel_size=3, input_shape=(segment_size, 5), activation='relu'))\n model.add(MaxPo... | [
[
"tensorflow.keras.layers.Conv1D",
"tensorflow.keras.layers.Flatten",
"tensorflow.keras.layers.Dense",
"tensorflow.keras.Sequential",
"tensorflow.keras.layers.Dropout",
"tensorflow.keras.layers.MaxPool1D"
]
] |
Zimiao1025/Sesica | [
"8b96a9e35a423ef6bd8561ba296ca3f55057af06"
] | [
"src/plot/plot_int.py"
] | [
"from itertools import cycle\n\nimport joblib\nimport matplotlib.pyplot as plt\n\n\ndef bar_fig(model_path, feats_name, fig_path):\n # 利用shap打印特征重要度\n gbm = joblib.load(model_path)\n scores = gbm.feature_importances_\n print(scores)\n plt.figure(0)\n bar_width = 0.4\n x1 = []\n for i in rang... | [
[
"matplotlib.pyplot.xlabel",
"matplotlib.pyplot.savefig",
"matplotlib.pyplot.title",
"matplotlib.pyplot.close",
"matplotlib.pyplot.figure",
"matplotlib.pyplot.ylabel",
"matplotlib.pyplot.gca",
"matplotlib.pyplot.bar",
"matplotlib.pyplot.xticks"
]
] |
connorgoggins/incubator-mxnet | [
"37280e4ddf00cacdac50c1e798fd2a14da38ae8d"
] | [
"tests/python/unittest/test_module.py"
] | [
"# Licensed to the Apache Software Foundation (ASF) under one\n# or more contributor license agreements. See the NOTICE file\n# distributed with this work for additional information\n# regarding copyright ownership. The ASF licenses this file\n# to you under the Apache License, Version 2.0 (the\n# \"License\"); y... | [
[
"numpy.all",
"numpy.ones"
]
] |
DDMGNI/viVlasov1D | [
"901dd058711f6943eb6497b941bc115a64e822de"
] | [
"examples/jeans_damping.py"
] | [
"\"\"\"\nJeans Damping\n\n Initial density: :math:`n(x) = 1 + A \\, \\cos{( k_{x} \\, ( x - L_{x}/2)) }`\n with :math:`A = 0.1, k = 2.0`\n\"\"\"\n\n\nimport numpy as np\n\n\ndef density(x, L):\n return 1. + 0.1 * np.cos(2.0 * (x - 0.5 * L))\n\n"
] | [
[
"numpy.cos"
]
] |
raven38/pytorch | [
"3a56758e1fdbc928be3754d5b60e63c7fc55ea45",
"3a56758e1fdbc928be3754d5b60e63c7fc55ea45",
"3a56758e1fdbc928be3754d5b60e63c7fc55ea45"
] | [
"torch/nn/utils/parametrizations.py",
"torch/nn/modules/linear.py",
"torch/nn/quantized/_reference/modules/conv.py"
] | [
"import torch\nfrom ..utils import parametrize\nfrom ..modules import Module\nfrom .. import functional as F\n\nfrom typing import Optional\n\nclass _SpectralNorm(Module):\n def __init__(\n self,\n weight: torch.Tensor,\n n_power_iterations: int = 1,\n dim: int = 0,\n eps: floa... | [
[
"torch.autograd.no_grad",
"torch.mv"
],
[
"torch.no_grad",
"torch.empty",
"torch.nn.parameter.UninitializedParameter"
],
[
"torch.nn.modules.utils._single",
"torch.nn.quantized.Conv1d.__init__",
"torch.nn.quantized.Conv2d.__init__",
"torch.nn.functional.conv1d",
"to... |
pedrospeixoto/devito | [
"7abc42202214c534eb962c27cf294ec9893615e1"
] | [
"examples/seismic/cemeai/dados_marmousi.py"
] | [
"#==============================================================================\n# Bibliotecas Python\n#==============================================================================\nimport numpy as np\nimport segyio\nimport sys\nfrom scipy.interpolate import CubicSpline\nfrom scipy.interpol... | [
[
"matplotlib.pyplot.colorbar",
"scipy.interpolate.interp1d",
"matplotlib.ticker.MaxNLocator",
"numpy.zeros",
"matplotlib.pyplot.gca",
"matplotlib.pyplot.grid",
"matplotlib.pyplot.savefig",
"matplotlib.pyplot.title",
"matplotlib.pyplot.MaxNLocator",
"matplotlib.pyplot.close",... |
cbamann/language-model | [
"d14410c2302bf42bb771abc4a6b859704847798e"
] | [
"lm_experiment.py"
] | [
"#!/usr/bin/env python3\n# -*- coding: utf-8 -*-\n\nimport tensorflow as tf\nPROJECT_FOLDER = \"./\"\n\n# READ AND PREPROCESS LOCAL FILES\nexec(open(PROJECT_FOLDER + \"setup.py\").read())\nfname_nn_out = FOLDER_NN_MODELS + \"exp\"\n\nBATCHES_TO_PROCESS = 500\n\n\n####################################################... | [
[
"tensorflow.trainable_variables",
"tensorflow.train.AdamOptimizer",
"tensorflow.contrib.layers.xavier_initializer",
"tensorflow.not_equal",
"tensorflow.reset_default_graph",
"tensorflow.train.Saver",
"tensorflow.matmul",
"tensorflow.Session",
"tensorflow.nn.rnn_cell.LSTMCell",
... |
englertbruno/tf-slim | [
"d0eb4075a8e18b8c29004dd5eb3035c36a8d9784"
] | [
"tf_slim/data/tfexample_decoder.py"
] | [
"# coding=utf-8\n# Copyright 2016 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... | [
[
"tensorflow.python.ops.image_ops.decode_jpeg",
"tensorflow.python.ops.math_ops.cast",
"tensorflow.python.ops.image_ops.is_jpeg",
"tensorflow.python.ops.math_ops.equal",
"tensorflow.python.ops.parsing_ops.decode_raw",
"tensorflow.python.ops.parsing_ops.parse_single_example",
"tensorflow... |
pwrliang/GraphScope | [
"56979ed5109ee0344fee8877460927e47147a62f"
] | [
"python/graphscope/tests/unittest/test_udf_app.py"
] | [
"#!/usr/bin/env python3\n# -*- coding: utf-8 -*-\n#\n# Copyright 2020 Alibaba Group Holding Limited. 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# h... | [
[
"numpy.allclose",
"pandas.read_csv"
]
] |
stefsietz/tpu | [
"1f8029b7849ccaafd121529a37a7c24613db7453"
] | [
"models/official/unet3d/tpu_executor.py"
] | [
"# Copyright 2019 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.compat.v1.distribute.cluster_resolver.TPUClusterResolver",
"tensorflow.compat.v1.gfile.MakeDirs",
"tensorflow.compat.v1.summary.FileWriter",
"tensorflow.compat.v1.Session.reset",
"tensorflow.compat.v1.Graph",
"tensorflow.compat.v1.estimator.tpu.TPUEstimator",
"tensorflow.co... |
rfww/EfficientChangeDetection | [
"42d466c56ed262980c27fd6cde6ffe65314e638f",
"42d466c56ed262980c27fd6cde6ffe65314e638f"
] | [
"networks/cis_depth4.py",
"networks/ARPPNET.py"
] | [
"import torch\nimport torch.nn as nn\nimport torch.nn.init as init\nimport torch.nn.functional as F\nfrom torch.utils import model_zoo\nfrom torchvision import models\nfrom utils.spp_layer import spatial_pyramid_pool\n\n\nclass CIS_VGGBN(nn.Module):\n def __init__(self, backbone='vgg16_bn', pretrained=True, free... | [
[
"torch.nn.Linear",
"torch.cat",
"torch.nn.Softmax",
"torch.nn.Sequential",
"torch.nn.BatchNorm2d",
"torch.nn.ReLU",
"torch.nn.Conv2d"
],
[
"torch.cat",
"torch.nn.Sequential",
"torch.nn.BatchNorm2d",
"torch.nn.Upsample",
"torch.nn.ReLU",
"torch.nn.Conv2d"
]... |
tonybove-apple/coremltools | [
"22a8877beec7bad136ba5612d5aacd8e323ecdfc"
] | [
"coremltools/converters/mil/mil/ops/defs/elementwise_binary.py"
] | [
"# Copyright (c) 2020, Apple Inc. All rights reserved.\n#\n# Use of this source code is governed by a BSD-3-clause license that can be\n# found in the LICENSE.txt file or at https://opensource.org/licenses/BSD-3-Clause\nimport numpy as np\n\nimport operator\nfrom ._op_reqs import *\nfrom ._utils import promoted_... | [
[
"numpy.array"
]
] |
sarah-antillia/EfficientDet-VegeFruits | [
"32fdf5598064f88d2d6599273fb913d891a435f3"
] | [
"main.py"
] | [
"# Copyright 2020 Google Research. 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 required by... | [
[
"tensorflow.compat.v1.distribute.cluster_resolver.TPUClusterResolver",
"tensorflow.compat.v1.estimator.RunConfig",
"numpy.array",
"tensorflow.compat.v1.Session.reset",
"tensorflow.compat.v1.io.gfile.makedirs",
"tensorflow.compat.v1.ConfigProto",
"tensorflow.compat.v1.io.gfile.exists",
... |
mcogswellsri/dare_brain_demo | [
"9f4c4298dabbc1511c1bba37903f742ad1b0a7b1"
] | [
"brats_example.py"
] | [
"import tempfile\nimport argparse\nimport os\nimport os.path as pth\nimport uuid\n\nimport torch\nimport torch.nn as nn\nimport torch.nn.functional as F\nimport numpy as np\n\nimport nibabel as nib\nimport skimage.transform\nimport skimage.io\n\nimport matplotlib\nimport matplotlib.pyplot as plt\nfrom matplotlib.co... | [
[
"torch.sigmoid",
"numpy.array",
"torch.stack",
"matplotlib.cm.get_cmap",
"matplotlib.pyplot.imsave",
"numpy.ones",
"numpy.tile",
"matplotlib.colors.rgb2hex",
"torch.random.manual_seed",
"scipy.spatial.distance.dice",
"matplotlib.colors.Normalize",
"matplotlib.pyplot... |
BenQLange/AttentionAugmentedConvLSTM | [
"d8419b7a628b02ac49e8450deb3d60450c7b2d6b"
] | [
"model/AAConv2d.py"
] | [
"\"\"\"\nPytorch implementation of Attention Augmented Convolution.\nDeveloped by: Myeongjun Kim (not us)\nSource code: https://github.com/leaderj1001/Attention-Augmented-Conv2d\n\"\"\"\n\nimport torch\nimport torch.nn as nn\nimport torch.nn.functional as F\n\nuse_cuda = torch.cuda.is_available()\ndevice = torch.de... | [
[
"torch.zeros",
"torch.device",
"torch.cat",
"torch.einsum",
"torch.split",
"torch.unsqueeze",
"torch.nn.Conv2d",
"torch.cuda.is_available",
"torch.nn.functional.softmax",
"torch.transpose",
"torch.randn",
"torch.reshape"
]
] |
Dan-hbd/NMTGMinor | [
"84e59ac8391ee78852d7c71afc60c3c8b8e3d44d"
] | [
"onmt/inference/search.py"
] | [
"# Copyright (c) 2017-present, Facebook, Inc.\n# All rights reserved.\n#\n# This source code is licensed under the license found in the LICENSE file in\n# the root directory of this source tree. An additional grant of patent rights\n# can be found in the PATENTS file in the same directory.\n\nimport torch\nimport o... | [
[
"torch.LongTensor",
"torch.stack",
"torch.true_divide",
"torch.sum"
]
] |
mhhennig/spikeforest | [
"5b4507ead724af3de0be5d48a3b23aaedb0be170"
] | [
"spikeforest/spikeforestwidgets/unitwaveformswidget.py"
] | [
"import numpy as np\nfrom matplotlib import pyplot as plt\nimport vdomr as vd\nimport time\nfrom spikeforest import spikewidgets as sw\n\n\nclass UnitWaveformsWidget(vd.Component):\n def __init__(self, *, recording, sorting, max_num_spikes_per_unit=20, snippet_len=100):\n vd.Component.__init__(self)\n ... | [
[
"numpy.max",
"matplotlib.pyplot.xlim",
"numpy.zeros",
"matplotlib.pyplot.ylim",
"matplotlib.pyplot.plot",
"matplotlib.pyplot.title",
"numpy.min",
"numpy.mean",
"numpy.diff",
"numpy.linspace",
"matplotlib.pyplot.axes",
"numpy.unique"
]
] |
Minyus/MegaDepth | [
"89baf59897951b45361def8fecdc156a79d98ee2"
] | [
"demo.py"
] | [
"import torch\nimport sys\nfrom torch.autograd import Variable\nimport numpy as np\n# from options.train_options import TrainOptions\n# opt = TrainOptions().parse() # set CUDA_VISIBLE_DEVICES before import torch\nfrom options.test_options import TestOptions\nopt = TestOptions().parse() # set CUDA_VISIBLE_DEVICES ... | [
[
"torch.squeeze",
"torch.exp",
"numpy.transpose",
"numpy.amax"
]
] |
dataronio/pygsp | [
"0f35fbf2623d32060fe2f709715a88a818528e26"
] | [
"pygsp/learning.py"
] | [
"# -*- coding: utf-8 -*-\n\nr\"\"\"\nThe :mod:`pygsp.learning` module provides functions to solve learning problems.\n\nSemi-supervized learning\n========================\n\nThose functions help to solve a semi-supervized learning problem, i.e., a\nproblem where only some values of a graph signal are known and the ... | [
[
"numpy.max",
"scipy.sparse.issparse",
"numpy.empty",
"numpy.matmul",
"numpy.sum",
"numpy.ones",
"scipy.sparse.linalg.LinearOperator",
"scipy.sparse.linalg.cg",
"numpy.prod",
"numpy.argsort",
"numpy.linalg.solve",
"numpy.diag",
"numpy.empty_like",
"numpy.maxi... |
wilcoln/transformers | [
"6331d4fe59e85840bb5693837e791f4caedcd53b"
] | [
"tests/test_modeling_tf_common.py"
] | [
"# coding=utf-8\n# Copyright 2019 HuggingFace Inc.\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 required by appl... | [
[
"tensorflow.config.LogicalDeviceConfiguration",
"tensorflow.ones",
"tensorflow.keras.models.Model",
"tensorflow.keras.layers.Dense",
"tensorflow.keras.Model",
"tensorflow.keras.metrics.SparseCategoricalAccuracy",
"tensorflow.math.abs",
"tensorflow.constant",
"tensorflow.keras.l... |
QuailAutomation/pygenetic | [
"93b0240a1942b882df30b53d856a87becca1d7ec"
] | [
"pygenetic/Statistics.py"
] | [
"import matplotlib\nimport os\nif 'TRAVIS' in os.environ:\n print('Warning: no DISPLAY environment variable found. Using matplotlib non-interactive Agg backend')\n matplotlib.use('Agg')\nimport matplotlib.pyplot as plt\n\nclass Statistics:\n\t\"\"\"\n\tClass to generate Statistics on operation of Genetic Algo... | [
[
"matplotlib.use",
"matplotlib.pyplot.subplots"
]
] |
shiqiuwang/Hardness_aware_Sample_Distillation | [
"b70823e9e180ed61a02e1eb73bbe9a3c2897050f"
] | [
"focalloss.py"
] | [
"# -*- coding: utf-8 -*-\n\n'''\n@Time : 2021/7/22 15:14\n@Author : Qiushi Wang\n@FileName: focalloss.py\n@Software: PyCharm\n'''\n\nimport torch\nimport torch.nn as nn\nimport torch.nn.functional as F\nfrom torch.autograd import Variable\nimport numpy as np\n\n\nclass FocalLoss(nn.Module):\n def __init__(se... | [
[
"torch.exp",
"torch.nn.CrossEntropyLoss"
]
] |
TheCaffeineDev/probability | [
"7aa13647c57fe621eadc2b7ad3020817aa8b9ba5"
] | [
"tensorflow_probability/python/distributions/normal.py"
] | [
"# Copyright 2018 The TensorFlow Probability 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 required by a... | [
[
"tensorflow.compat.v2.math.squared_difference",
"tensorflow.compat.v2.math.expm1",
"tensorflow.compat.v2.ones_like",
"tensorflow.compat.v2.TensorShape",
"numpy.log",
"tensorflow.compat.v2.broadcast_static_shape",
"tensorflow.compat.v2.random.normal",
"tensorflow.compat.v2.math.log"... |
jenfly/atmos | [
"c0a733b78749098d8cc2caaaacee245e6aeeac07",
"c0a733b78749098d8cc2caaaacee245e6aeeac07"
] | [
"testing/testing-analysis-regress_field.py",
"testing/testing-data-mean_over_geobox.py"
] | [
"import sys\nsys.path.append('/home/jwalker/dynamics/python/atmos-tools')\nsys.path.append('/home/jwalker/dynamics/python/atmos-read')\n\nimport xray\nimport numpy as np\nimport matplotlib.pyplot as plt\nimport matplotlib as mpl\nimport collections\nimport pandas as pd\n\nimport atmos as atm\nimport utils # monsoon... | [
[
"matplotlib.pyplot.subplot",
"matplotlib.pyplot.title",
"numpy.arange",
"matplotlib.pyplot.figure"
],
[
"numpy.ones",
"matplotlib.pyplot.plot",
"matplotlib.pyplot.figure"
]
] |
Seunghoon-Yi/Paper_review-PyTorch | [
"44728cc9c3eee6c0146b0cff8a46099e789dfabc"
] | [
"Transformer/SLT_transformer/test.py"
] | [
"from model import SLT_Transformer\r\nfrom dataloader import Vocab_tokenizer, get_loader\r\nfrom sklearn.utils import shuffle\r\nimport pandas as pd\r\nimport os\r\n\r\nimport numpy as np\r\nimport torch\r\nimport torch.nn as nn\r\n\r\n\r\ndevice = torch.device('cuda' if torch.cuda.is_available() else 'cpu')\r\n\r\... | [
[
"torch.device",
"torch.argmax",
"torch.no_grad",
"torch.cuda.is_available",
"torch.load",
"pandas.concat",
"pandas.read_csv",
"torch.nn.CrossEntropyLoss",
"sklearn.utils.shuffle"
]
] |
yolman230/tensorflow | [
"8180678e1b71f9e4326b9d84987d78232000bac2"
] | [
"tensorflow/tools/docs/tf_doctest.py"
] | [
"# Lint as: python3\n# Copyright 2019 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... | [
[
"tensorflow.tools.docs.tf_doctest_lib.TfDoctestOutputChecker",
"tensorflow.compat.v2.compat.v1.enable_v2_behavior"
]
] |
tai271828/RustPython | [
"9fb70707c4803f9f6d79dd4c8077bd16f0a9be45"
] | [
"Lib/test/test_buffer.py"
] | [
"#\r\n# The ndarray object from _testbuffer.c is a complete implementation of\r\n# a PEP-3118 buffer provider. It is independent from NumPy's ndarray\r\n# and the tests don't require NumPy.\r\n#\r\n# If NumPy is present, some tests check both ndarray implementations\r\n# against each other.\r\n#\r\n# Most ndarray t... | [
[
"numpy.ndarray"
]
] |
vibhatha/pipedream | [
"af6b811f5d01a68e9eb91065e5242fc1a075f279",
"af6b811f5d01a68e9eb91065e5242fc1a075f279"
] | [
"runtime/image_classification/models/vgg16/gpus=4_straight/stage2.py",
"runtime/image_classification/models/vgg16/gpus=16_straight/vgg16.py"
] | [
"# Copyright (c) Microsoft Corporation.\r\n# Licensed under the MIT license.\r\n\r\nimport torch\r\n\r\n\r\nclass Stage2(torch.nn.Module):\r\n def __init__(self):\r\n super(Stage2, self).__init__()\r\n self.layer1 = torch.nn.Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))\r\n ... | [
[
"torch.nn.init.constant_",
"torch.nn.MaxPool2d",
"torch.nn.init.kaiming_normal_",
"torch.nn.ReLU",
"torch.nn.Conv2d",
"torch.nn.init.normal_"
],
[
"torch.nn.init.normal_",
"torch.nn.init.kaiming_normal_",
"torch.nn.init.constant_"
]
] |
brotwasme/refnx2019 | [
"8b62f7668d196c0ec443b47ea669573417a682e6"
] | [
"refnx/analysis/test/NISTModels.py"
] | [
"import os\n\nimport numpy as np\nfrom numpy import exp, sin, cos, arctan, array, pi\nfrom numpy.testing import assert_allclose, assert_\n\nfrom refnx.analysis import (CurveFitter, Objective, Parameter, Parameters,\n Model)\n\nthisdir, thisfile = os.path.split(__file__)\nNIST_DIR = os.pat... | [
[
"numpy.testing.assert_allclose",
"numpy.array",
"numpy.sin",
"numpy.log",
"numpy.zeros",
"numpy.exp",
"numpy.arctan",
"numpy.abs",
"numpy.cos"
]
] |
ReubenGitHub/MachineLearning-Vehicle-Emissions | [
"5a6d5366d15cb918de5464c48e0067efceda4149"
] | [
"src/data/dataClean.py"
] | [
"# Copyright 2022 Reuben Owen-Williams\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 required by a... | [
[
"pandas.read_sql"
]
] |
LiveFly/retinaface | [
"939ae81bbf4ae9333fa14743962dcf99d8db1840"
] | [
"retinaface/pre_trained_models.py"
] | [
"from collections import namedtuple\n\nfrom torch.utils import model_zoo\n\nfrom retinaface.predict_single import Model\n\nmodel = namedtuple(\"model\", [\"url\", \"model\"])\n\nmodels = {\n \"resnet50_2020-07-20\": model(\n url=\"https://github.com/ternaus/retinaface/releases/download/0.01/retinaface_res... | [
[
"torch.utils.model_zoo.load_url"
]
] |
forc-db/GROA | [
"a316bd6c70d02a8904a19fc554747acfadbae0c1"
] | [
"MappingGlobalCarbon/gfw_forestlearn/fl_regression.py"
] | [
"import subprocess\nimport gdal\nimport pandas as pd\nimport numpy as np\nimport glob\nimport rasterio\nimport os\nimport datetime\nimport csv\nimport random\nfrom math import sqrt\nimport pickle\nimport math\nimport datetime\nimport warnings\nfrom shutil import copyfile\nimport csv\nimport sys\nimport math\nimport... | [
[
"sklearn.svm.LinearSVR",
"sklearn.metrics.mean_squared_error",
"sklearn.preprocessing.StandardScaler",
"pandas.DataFrame.from_dict",
"sklearn.metrics.r2_score",
"pandas.DataFrame",
"pandas.concat",
"numpy.mean",
"sklearn.decomposition.PCA",
"sklearn.compose.ColumnTransforme... |
calltri/journal-citation-cartels | [
"2c7967eccb4783f136f8da47d417a0fe9e625c2a"
] | [
"workflow/plot_all_cartels.py"
] | [
"import numpy as np\nimport pandas as pd\nimport utils\nfrom scipy import sparse\nimport matplotlib.pyplot as plt\nimport seaborn as sns\nimport sys\nimport matplotlib.colors as colors\nfrom matplotlib import cm\nimport os\nsys.path.append(os.path.abspath(os.path.join(\"libs/cidre\")))\nfrom cidre import cidre, fil... | [
[
"pandas.DataFrame",
"pandas.read_csv",
"matplotlib.pyplot.subplots"
]
] |
mbencer/models | [
"fb8271d5d5d9b90dbb1eb5e8e40f8f580fb248b3"
] | [
"vision/body_analysis/ultraface/demo.py"
] | [
"import cv2\nimport onnxruntime as ort\nimport argparse\nimport numpy as np\nfrom dependencies.box_utils import predict\n\n# ------------------------------------------------------------------------------------------------------------------------------------------------\n# Face detection using UltraFace-320 onnx mod... | [
[
"numpy.array",
"numpy.transpose",
"numpy.expand_dims"
]
] |
data-intelligence-for-health-lab/delirium_prediction | [
"a0a25819ef6c98e32563b4e3b986c1a26fc30ed7",
"a0a25819ef6c98e32563b4e3b986c1a26fc30ed7"
] | [
"code/test/02_processing_bootstrapping.py",
"code/X_historical/02_process_hist_files.py"
] | [
"\n# --- loading libraries -------------------------------------------------------\n\nimport numpy as np\nimport pandas as pd\nimport pickle\nimport tensorflow as tf\nimport random\nfrom sklearn.metrics import confusion_matrix, f1_score, precision_score, recall_score, roc_auc_score, auc, precision_recall_curve\nimp... | [
[
"sklearn.metrics.confusion_matrix",
"sklearn.metrics.precision_recall_curve",
"numpy.random.seed",
"pandas.DataFrame",
"tensorflow.random.set_seed",
"tensorflow.keras.models.load_model",
"numpy.arange",
"sklearn.metrics.auc",
"sklearn.metrics.precision_score",
"sklearn.metr... |
CLAIRE-COVID-T4/covid-data | [
"ccdf1397b945b63e95768a7b91f0a7bad6e5085d"
] | [
"code/node2vec.py"
] | [
"\"\"\" Taken from https://github.com/aditya-grover/node2vec and adapted to run on Python 3+\"\"\"\nimport numpy as np\nimport networkx as nx\nimport random\n\n\nclass Graph():\n\tdef __init__(self, nx_G, is_directed, p, q):\n\t\tself.G = nx_G\n\t\tself.is_directed = is_directed\n\t\tself.p = p\n\t\tself.q = q\n\n\... | [
[
"numpy.random.rand",
"numpy.zeros"
]
] |
MSwML/ML-guided-material-synthesis | [
"8c0ae4a4f6403bcc6833e959f549ab11c9874fe6"
] | [
"utils/others.py"
] | [
"import shap\nimport numpy as np\nimport pandas as pd\nfrom utils import data_handler\n\n\n\ndef extract_feature_importance(model,X,title):\n \n print('Feature importance...')\n explainer = shap.TreeExplainer(model)\n shap_values = explainer.shap_values(X)\n\n shap.summary_plot(shap_values, feature_n... | [
[
"pandas.DataFrame",
"pandas.Series",
"numpy.argsort",
"pandas.concat"
]
] |
connorlee77/kornia | [
"af5b1f76bedf2a7fc0e0da2386b1be3032b6534f"
] | [
"test/color/test_rgb.py"
] | [
"import kornia\nimport kornia.testing as utils # test utils\nfrom test.common import device\n\nimport torch\nfrom torch.autograd import gradcheck\nfrom torch.testing import assert_allclose\nimport pytest\n\n\nclass TestRgbToRgba:\n def test_smoke(self, device):\n data = torch.rand(3, 4, 4).to(device)\n ... | [
[
"torch.rand",
"torch.Tensor",
"torch.tensor",
"torch.testing.assert_allclose"
]
] |
chatterboy/n3ml | [
"28b4e25a277e55e734e6054e8239237a5ff7d1f1"
] | [
"n3ml/connection.py"
] | [
"from typing import Type\n\nimport torch\nimport torch.nn\nimport torch.distributions.distribution\n\nimport n3ml.population\nimport n3ml.learning\n\n\nclass Synapse(torch.nn.Module):\n def __init__(self,\n source: n3ml.population.Population,\n target: n3ml.population.Population,\... | [
[
"torch.zeros",
"torch.matmul"
]
] |
cresposito/BirdCLEF-Baseline | [
"bb95a749d21b62031aa208fe7a12e991eba076ac",
"bb95a749d21b62031aa208fe7a12e991eba076ac"
] | [
"utils/image.py",
"utils/batch_generator.py"
] | [
"# This file includes basic functionality for image processing\n# including i/o handling, image augmentation and model input pre-processing\n# Author: Stefan Kahl, 2018, Chemnitz University of Technology\n\nimport sys\nsys.path.append(\"..\")\n\nimport copy\n\nimport numpy as np\nimport cv2\n\n#####################... | [
[
"numpy.asarray",
"numpy.mean",
"numpy.transpose",
"numpy.clip",
"numpy.expand_dims"
],
[
"numpy.zeros"
]
] |
coinflip112/ml_101 | [
"9e56ffdb99ac241ed396e25d7f7818a58ee5c4de"
] | [
"hw_07/hypers_optim.py"
] | [
"import argparse\nimport json\nimport lzma\nimport os\nimport pickle\nimport sys\nimport urllib.request\n\nimport numpy as np\nimport pandas as pd\nfrom sklearn.compose import ColumnTransformer\nfrom sklearn.ensemble import RandomForestClassifier, ExtraTreesClassifier\nfrom sklearn.svm import SVC\nfrom sklearn.line... | [
[
"sklearn.preprocessing.FunctionTransformer",
"sklearn.ensemble.RandomForestClassifier",
"sklearn.neighbors.KNeighborsClassifier",
"sklearn.preprocessing.PolynomialFeatures",
"sklearn.naive_bayes.GaussianNB",
"sklearn.linear_model.SGDClassifier",
"pandas.read_csv",
"sklearn.ensemble... |
Joxis/tpu | [
"6b1a71c3ba8c882cc26e15a54b5f2c302eb34620"
] | [
"models/official/detection/inference.py"
] | [
"# Copyright 2020 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.compat.v1.placeholder",
"tensorflow.compat.v1.reshape",
"tensorflow.compat.v1.io.decode_image",
"tensorflow.compat.v1.Graph",
"tensorflow.compat.v1.gfile.Open",
"tensorflow.compat.v1.train.Saver",
"matplotlib.pyplot.savefig",
"tensorflow.compat.v1.Session",
"tensorf... |
JLSirvent/bws-calibration-analysis | [
"b2f129e31974c16d7498e105a075b43bfece92c9",
"b2f129e31974c16d7498e105a075b43bfece92c9"
] | [
"lib/prairie.py",
"lib/measurement_simulations.py"
] | [
"# --------------------------------------------------------------------------\r\n# Copyright (c) <2017> <Lionel Garcia>\r\n#\r\n# Permission is hereby granted, free of charge, to any person obtaining a copy\r\n# of this software and associated documentation files (the \"Software\"), to deal\r\n# in the Software w... | [
[
"matplotlib.ticker.MultipleLocator"
],
[
"numpy.random.normal",
"scipy.optimize.curve_fit",
"numpy.asarray",
"matplotlib.pyplot.savefig",
"scipy.io.loadmat",
"numpy.exp",
"numpy.mean",
"matplotlib.pyplot.figure",
"matplotlib.pyplot.close",
"numpy.std",
"numpy.ar... |
tonyngjichun/pspnet-pytorch | [
"75297aa4fdb4f7a712ef9185be1ec805044f8328"
] | [
"convert.py"
] | [
"#!/usr/bin/env python\n# coding: utf-8\n#\n# Author: Kazuto Nakashima\n# URL: http://kazuto1011.github.io\n# Created: 2017-11-15\n\nfrom __future__ import print_function\n\nimport re\nfrom collections import OrderedDict\n\nimport click\nimport numpy as np\nimport torch\nimport yaml\nfrom addict import Dict... | [
[
"torch.save",
"torch.FloatTensor"
]
] |
jeena72/disaster-response-pipeline | [
"4621425a29e7fa2f162c725555787b6fc24f8010"
] | [
"models/train_classifier.py"
] | [
"import sys\nimport pandas as pd\nimport numpy as np\nimport nltk\n\nfrom joblib import dump\nfrom sqlalchemy import create_engine\nfrom nltk.tokenize import word_tokenize\nfrom nltk.stem import WordNetLemmatizer\n\nfrom sklearn.feature_extraction.text import TfidfVectorizer, CountVectorizer\nfrom sklearn.base impo... | [
[
"sklearn.ensemble.AdaBoostClassifier",
"sklearn.model_selection.train_test_split",
"sklearn.preprocessing.StandardScaler",
"pandas.DataFrame",
"sklearn.metrics.classification_report",
"sklearn.feature_extraction.text.CountVectorizer",
"sklearn.feature_extraction.text.TfidfVectorizer",
... |
Pudit/FarewellSI126 | [
"91e92d869a6930797e8b05ab9a6920af901cde62"
] | [
"find_all_sites.py"
] | [
"#import libraries\nfrom bs4 import BeautifulSoup\nfrom urllib.request import urlopen\nimport urllib.error\nimport pandas as pd\n\n#define func to find subfolder\ndef find_folder(student_id: int):\n if student_id < 1 :\n return None\n elif student_id <= 50 :\n return \"001-050\"\n elif studen... | [
[
"pandas.DataFrame",
"pandas.read_csv"
]
] |
maktu6/garment_segmentation | [
"8a010fa1087ba6d0c9e77299ab13a9266750d0c1",
"8a010fa1087ba6d0c9e77299ab13a9266750d0c1"
] | [
"train_mask_rcnn.py",
"attributes_classify/box.py"
] | [
"\"\"\"Train Mask RCNN end to end.\"\"\"\nimport os\n\n# disable autotune\nos.environ['MXNET_CUDNN_AUTOTUNE_DEFAULT'] = '0'\nimport logging\nimport time\nimport numpy as np\nimport cv2\nimport mxnet as mx\nfrom mxnet import gluon\nfrom mxnet import autograd\nimport gluoncv as gcv\nfrom gluoncv import data as gdata\... | [
[
"numpy.where",
"numpy.array"
],
[
"numpy.zeros_like",
"numpy.asarray",
"numpy.zeros",
"numpy.where",
"numpy.maximum"
]
] |
muliliao/darts | [
"2b5f5c3aa81c6962f4d0d2ba5f280d42f5dc5eb0"
] | [
"darts/tests/test_filters.py"
] | [
"import numpy as np\nimport pandas as pd\n\nfrom .base_test_class import DartsBaseTestClass\nfrom ..models.kalman_filter import KalmanFilter\nfrom ..models.filtering_model import MovingAverage\nfrom ..timeseries import TimeSeries\nfrom ..utils import timeseries_generation as tg\n\n\nclass KalmanFilterTestCase(Darts... | [
[
"numpy.random.normal",
"numpy.arange",
"pandas.DataFrame"
]
] |
dongbowen8/dgl | [
"f1c6948171cc7581e582bf2028776c7e08d448a1"
] | [
"python/dgl/nn/pytorch/conv/sageconv.py"
] | [
"\"\"\"Torch Module for GraphSAGE layer\"\"\"\n# pylint: disable= no-member, arguments-differ, invalid-name\nimport torch\nfrom torch import nn\nfrom torch.nn import functional as F\n\nfrom .... import function as fn\nfrom ....utils import expand_as_pair, check_eq_shape, dgl_warning\n\n\nclass SAGEConv(nn.Module):\... | [
[
"torch.nn.Linear",
"torch.zeros",
"torch.nn.Dropout",
"torch.nn.LSTM",
"torch.nn.init.xavier_uniform_",
"torch.nn.init.calculate_gain"
]
] |
keynmol/fastparse | [
"2907295ba3463ccba732b1f58c2704ffe2f22939"
] | [
"perftests/resources/cross_validation.py"
] | [
"\n\"\"\"\nThe :mod:`sklearn.cross_validation` module includes utilities for cross-\nvalidation and performance evaluation.\n\"\"\"\n\n# Author: Alexandre Gramfort <alexandre.gramfort@inria.fr>,\n# Gael Varoquaux <gael.varoquaux@normalesup.org>,\n# Olivier Grisel <olivier.grisel@ensta.org>\n# Licens... | [
[
"numpy.argmin",
"numpy.min",
"numpy.mean",
"numpy.finfo",
"numpy.where",
"numpy.concatenate",
"numpy.bincount",
"numpy.arange",
"numpy.in1d",
"scipy.sparse.issparse",
"numpy.array",
"numpy.zeros",
"numpy.round",
"numpy.ix_",
"numpy.argsort",
"numpy.l... |
aaavinash85/OpenCV_image-processing | [
"ea9bf85454a9919ced82567c99d997314598cc5c"
] | [
"hist.py"
] | [
"import cv2\nimport numpy as np \nimport matplotlib.pyplot as plt \n\nimg = cv2.imread('images/wave.png')\ncv2.imshow('img', img)\n\n''' Cv2 has function to calculate the histogram\n cv2.calcHist([img], [channels], [mask], [size], [range])\n channels - corrrespods to B G R we can calculate for individual\n ... | [
[
"matplotlib.pyplot.show",
"matplotlib.pyplot.plot"
]
] |
vedkharche538/pandas-profiling | [
"ba0a6df3a3dd126ab36045f5a69878f31627d450"
] | [
"examples/features/mask_sensitive.py"
] | [
"from pathlib import Path\n\nimport 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(\"auto2.dta\", \"http://www.stata-press.com/data/r15/auto2.dta\")\n df = pd.read_stata(file_name)\n\n ... | [
[
"pandas.DataFrame",
"pandas.read_stata"
]
] |
leimao/detr | [
"cd88c4ea01257831ac677b6268e1aef7cd37eca4"
] | [
"main2.py"
] | [
"# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved\nimport argparse\nimport datetime\nimport json\nimport random\nimport time\nfrom pathlib import Path\n\nimport numpy as np\nimport torch\nfrom torch.utils.data import DataLoader, DistributedSampler\n\nimport datasets\nimport util.misc as utils\... | [
[
"torch.device",
"numpy.random.seed",
"torch.utils.data.SequentialSampler",
"torch.manual_seed",
"torch.utils.data.DataLoader"
]
] |
cmcqueen/sundials | [
"0b7fbf7bcdef4687c1805436bdac006d777b23f2"
] | [
"analemmatic.py"
] | [
"#!/usr/bin/env python3\n\"\"\"\nCalculation and generation of analemmatic sundial.\n\nReferences:\n Plus Magazine http://pass.maths.org.uk/issue11/features/sundials/index.html\n Wikipedia http://en.wikipedia.org/wiki/Analemmatic_sundial\n\nCalculations have been done according to the Plus Magazine refere... | [
[
"matplotlib.lines.Line2D",
"numpy.sin",
"matplotlib.pyplot.xlim",
"matplotlib.text.Text",
"matplotlib.pyplot.ylim",
"numpy.rad2deg",
"numpy.tan",
"matplotlib.pyplot.figure",
"numpy.arctan2",
"numpy.sqrt",
"numpy.cos",
"numpy.deg2rad",
"matplotlib.pyplot.show",
... |
ebayandelger/MSDS600 | [
"7bec34531f3fc661a0bfdfe42a974fcfd8f1f2c4"
] | [
"intro_exercise.py"
] | [
"# Lines starting with # are comments and are not run by Python.\n\"\"\"\nMulti-line comments are possible with triple quotes like this.\n\"\"\"\n# pandas is a common library for working with data in Python, we usually import it like so:\nimport pandas as pd\nimport matplotlib.pyplot as plt\n\n# This data comes fro... | [
[
"matplotlib.pyplot.xlabel",
"matplotlib.pyplot.title",
"matplotlib.pyplot.plot",
"matplotlib.pyplot.ylabel",
"matplotlib.pyplot.show",
"pandas.read_csv"
]
] |
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