repo_name stringlengths 6 130 | hexsha list | file_path list | code list | apis list |
|---|---|---|---|---|
icupeiro/pygfunction | [
"3688ecc45515e161cfe882fdf4a3687c49013174"
] | [
"pygfunction/examples/comparison_load_aggregation.py"
] | [
"# -*- coding: utf-8 -*-\n\"\"\" Comparison of the accuracy and computational speed of different load\n aggregation algorithms.\n\n The g-function of a single borehole is calculated for boundary condition of\n uniform borehole wall temperature along the borehole. Then, the borehole\n wall temperature va... | [
[
"numpy.ceil",
"scipy.interpolate.interp1d",
"numpy.sin",
"numpy.array",
"numpy.zeros",
"matplotlib.ticker.AutoMinorLocator",
"scipy.signal.fftconvolve",
"matplotlib.pyplot.figure",
"matplotlib.pyplot.rc",
"matplotlib.pyplot.tight_layout",
"numpy.abs",
"numpy.cos",
... |
RedoC-github/Gifted-Information-2021 | [
"90a3cd1100d2d1407083a42a2afdffe521e21f76"
] | [
"Day 4/produce.py"
] | [
"primes = []\n\nn = 10\narr = [1]*(n+1)\narr[0] = 0\narr[1] = 0\n\nfor i in range(2, n+1, 1):\n\tif arr[i]:\n\t\tprimes.append(i);\n\t\tfor j in range(2*i, n+1, i):\n\t\t\tarr[j] = 0\n\n# Regression\nimport matplotlib.pyplot as plt\nimport numpy as np\nimport matplotlib.pyplot as plt\nimport tensorflow.compat.v1 as... | [
[
"tensorflow.compat.v1.placeholder",
"tensorflow.compat.v1.pow",
"tensorflow.compat.v1.global_variables_initializer",
"tensorflow.compat.v1.disable_v2_behavior",
"matplotlib.pyplot.xlabel",
"tensorflow.compat.v1.train.GradientDescentOptimizer",
"matplotlib.pyplot.title",
"matplotlib... |
matthiasboeker/Shizophrenia_Depression_Project- | [
"7c3c9d6b78c488b589305e586c53c6a5cacd1925"
] | [
"Data/psykose/psykose_baseline_experiment.py"
] | [
"from sklearn.linear_model import LogisticRegression\nfrom sklearn.ensemble import RandomForestClassifier\nimport xgboost as xgb\nimport lightgbm as lgb\nimport numpy as np\nimport pandas as pd\nimport os\nimport matplotlib.pyplot as plt\nimport seaborn as sns\ncolor = sns.color_palette()\nimport matplotlib as mpl\... | [
[
"matplotlib.pyplot.xlim",
"numpy.argmin",
"sklearn.metrics.average_precision_score",
"pandas.concat",
"pandas.read_csv",
"sklearn.model_selection.StratifiedKFold",
"sklearn.metrics.precision_recall_curve",
"pandas.DataFrame",
"matplotlib.pyplot.step",
"matplotlib.pyplot.fil... |
jfrancis71/pytorch-lightning-bolts | [
"8a4cf8f61644c28d6df54ccffe3a52d6f5fce5a6"
] | [
"pl_bolts/models/rl/common/gym_wrappers.py"
] | [
"\"\"\"\nSet of wrapper functions for gym environments taken from\nhttps://github.com/Shmuma/ptan/blob/master/ptan/common/wrappers.py\n\"\"\"\nimport collections\n\nimport numpy as np\nimport torch\n\nfrom pl_bolts.utils import _GYM_AVAILABLE, _OPENCV_AVAILABLE\nfrom pl_bolts.utils.warnings import warn_missing_pkg\... | [
[
"numpy.zeros_like",
"numpy.array",
"numpy.reshape",
"numpy.stack",
"torch.tensor",
"numpy.moveaxis"
]
] |
zstreeter/scatterGrid | [
"0827b7be5fce0b91e516bdecf1c297069497ae5e"
] | [
"quantumgrid/potential.py"
] | [
"\"\"\"\nClass for a more OOP interface to several potentials.\n\"\"\"\n# Import NumPy which is used to define pi, sqrt, array, .transpose etc. as\nimport numpy as np\n\nfrom scipy.interpolate import CubicSpline\n\n\nclass Potential(object):\n def __init__(self, file=None):\n \"\"\"Constructor method, ad... | [
[
"numpy.empty",
"numpy.vectorize",
"numpy.float",
"numpy.exp",
"numpy.real",
"scipy.interpolate.CubicSpline",
"numpy.loadtxt"
]
] |
Akshaykumarcp/ML-Feature-Engineering | [
"456c3a729d67ec2cb6115a27befc0d775fb85e97"
] | [
"0.3_missing value imputation/0.10_missing_indicator.py"
] | [
"\"\"\" \r\nMISSING INDICATOR\r\n- Adding a variable to capture NA\r\n- In previous examples we learnt how to replace missing values by the mean, median or by extracting a random value. \r\n- In other words we learnt about mean / median and random sample imputation. \r\n- These methods assume that the data are miss... | [
[
"sklearn.model_selection.train_test_split",
"pandas.read_csv",
"pandas.set_option"
]
] |
aymgal/MuSCADeT | [
"9d65226af0eda66f1e23990e31785f7edce5cffb"
] | [
"Examples/Example_real.py"
] | [
"import pyfits as pf\nimport numpy as np\nimport matplotlib.pyplot as plt\nfrom MuSCADeT import MCA\nfrom MuSCADeT import pca_ring_spectrum as pcas\nimport scipy.stats as sc\nfrom MuSCADeT import colour_subtraction as cs\n\n## Openning data cube\ncube = pf.open('./Simu_real/Cube.fits')[0].data\nnum,n,n = np.shape(c... | [
[
"numpy.shape"
]
] |
notnotcamscott/portraiture | [
"3b4d1dad269ed544441627b54417f2735cb2396b"
] | [
"tests/test_data_types.py"
] | [
"# Ensure that the local version of the runway module is used, not a pip\n# installed version\nimport sys\nsys.path.insert(0, '..')\nsys.path.insert(0, '.')\n\nimport os\nimport pytest\nimport numpy as np\nfrom PIL import Image\nfrom runway.data_types import *\nfrom runway.exceptions import *\n\n# UTIL FUNCTIONS --... | [
[
"numpy.array",
"numpy.array_equal",
"numpy.asarray",
"numpy.float",
"numpy.zeros"
]
] |
rishit2307/PyFR | [
"1d249426d8ea4257cb8beff75b6ccd8a058787f4"
] | [
"pyfr/backends/openmp/base.py"
] | [
"# -*- coding: utf-8 -*-\n\nfrom ctypes import c_int, c_void_p\nfrom functools import cached_property\n\nimport numpy as np\n\nfrom pyfr.backends.base import BaseBackend\nfrom pyfr.backends.openmp.compiler import OpenMPCompiler\n\n\nclass OpenMPBackend(BaseBackend):\n name = 'openmp'\n blocks = True\n\n de... | [
[
"numpy.dtype",
"numpy.zeros"
]
] |
MackieBlackburn/Top2Vec | [
"f65ed58263cce4e4e1c436298dad55a467e5497d"
] | [
"top2vec/tests/test_top2vec.py"
] | [
"import pytest\nfrom top2vec import Top2Vec\nfrom sklearn.datasets import fetch_20newsgroups\nimport numpy as np\n\n# get 20 newsgroups data\nnewsgroups_train = fetch_20newsgroups(subset='all', remove=('headers', 'footers', 'quotes'))\nnewsgroups_documents = newsgroups_train.data[0:2000]\n\n# train top2vec model wi... | [
[
"sklearn.datasets.fetch_20newsgroups"
]
] |
pbmanis/cnmodel | [
"eee593c673752c19137658d5b9a381ea9ad4580f"
] | [
"examples/test_sgc_input_phaselocking.py"
] | [
"\"\"\"\ntest_sgc_input_phaselocking.py\n\nTest phase locking from an input sgc to a target cell type. Runs simulations\nwith AN input, and plots the results, including PSTH and phase histogram.\n\nusage: test_sgc_input_phaselocking.py [-h]\n [-c {bushy,tstellate,octopus,dstella... | [
[
"numpy.round",
"numpy.histogram",
"numpy.linspace",
"numpy.where"
]
] |
aiha-lab/lsq-lab | [
"d8b07c93bd23e2bbd8b425b84d19605fa32c44f9"
] | [
"quan/quantizer/lsq.py"
] | [
"import torch as t\n\nfrom .quantizer import Quantizer\n\n\ndef grad_scale(x, scale):\n y = x\n y_grad = x * scale\n return (y - y_grad).detach() + y_grad\n\n\ndef round_pass(x):\n y = x.round()\n y_grad = x\n return (y - y_grad).detach() + y_grad\n\n\nclass LsqQuan(Quantizer):\n def __init__(s... | [
[
"torch.clamp",
"torch.ones"
]
] |
massquantity/Reco_Project | [
"6e577d6c3a5f7372d88c25dd9f540a1b7651180f"
] | [
"tests/models/test_youtube_ranking.py"
] | [
"import pytest\nimport tensorflow as tf\n\nfrom libreco.algorithms import YouTubeRanking\nfrom tests.utils_data import prepare_feat_data\nfrom tests.utils_reco import recommend_in_former_consumed\n\n\n@pytest.mark.parametrize(\"task\", [\"rating\", \"ranking\"])\n@pytest.mark.parametrize(\n \"lr_decay, reg, num_... | [
[
"tensorflow.compat.v1.reset_default_graph"
]
] |
smithto1/pandas | [
"42fd7e7d9a2c115af9a52f7f896d48b75a271efe"
] | [
"pandas/core/indexes/datetimes.py"
] | [
"from datetime import date, datetime, time, timedelta, tzinfo\nimport operator\nfrom typing import Optional\nimport warnings\n\nimport numpy as np\n\nfrom pandas._libs import NaT, Period, Timestamp, index as libindex, lib, tslib\nfrom pandas._libs.tslibs import Resolution, parsing, timezones, to_offset\nfrom pandas... | [
[
"pandas._libs.Period",
"pandas._libs.tslibs.timezones.is_utc",
"pandas.io.formats.format._get_format_datetime64",
"pandas.core.arrays.datetimes.DatetimeArray._generate_range",
"pandas.core.dtypes.common.is_datetime64_any_dtype",
"pandas.core.arrays.datetimes.DatetimeArray",
"pandas.cor... |
henrytansetiawan/jax | [
"71323b5d023a33bf8c06d435c4a6e406dea3c0a8"
] | [
"tests/linalg_test.py"
] | [
"# Copyright 2018 Google LLC\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# https://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless required by applicable law or agreed ... | [
[
"numpy.dot",
"numpy.linalg.qr",
"numpy.dtype",
"scipy.linalg.solve",
"numpy.divide",
"numpy.ndindex",
"scipy.linalg.lu_factor",
"numpy.linalg.norm",
"numpy.triu",
"numpy.eye",
"numpy.swapaxes",
"numpy.conj",
"numpy.linalg.inv",
"scipy.linalg.lu_solve",
"... |
drtobybrown/AncillaryDataButton | [
"129d282c0891a2e8fcb808847befb431d7242fd7"
] | [
"NESS/Spitzer/SHA_Query_Mosaic.py"
] | [
"# Identify location\nimport socket\nlocation = socket.gethostname()\nif location == 'Monolith':\n dropbox = 'E:\\\\Users\\\\Chris\\\\Dropbox\\\\'\nif location == 'Hobbitslayer':\n dropbox = 'C:\\\\Users\\\\spx7cjc\\\\Dropbox\\\\'\nif location == 'saruman':\n dropbox = '/home/herdata/spx7cjc/Dropbox/'\n\n#... | [
[
"numpy.where",
"numpy.genfromtxt",
"numpy.zeros",
"numpy.isnan"
]
] |
ZhiliangWu/mDKL | [
"008ba81a14c333f5027126000555baefdf5fc049"
] | [
"plot_utils.py"
] | [
"#\n# mDKL\n#\n# Copyright (c) Siemens AG, 2021\n# Authors:\n# Zhiliang Wu <zhiliang.wu@siemens.com>\n# License-Identifier: MIT\n\nimport numpy as np\nimport pandas as pd\nimport matplotlib.pyplot as plt\nfrom yellowbrick.features import JointPlotVisualizer\nfrom yellowbrick.regressor import ResidualsPlot, Predicti... | [
[
"sklearn.metrics.mean_squared_error",
"pandas.DataFrame",
"matplotlib.pyplot.close",
"matplotlib.pyplot.subplots",
"numpy.mean",
"sklearn.metrics.median_absolute_error",
"sklearn.metrics.mean_absolute_error",
"numpy.stack",
"numpy.arange",
"numpy.argsort",
"sklearn.metr... |
quintron/vol-toolbox | [
"0bddb66c0160da1fb9393c60f6a99600311bbcf9"
] | [
"voltoolbox/fit/forward_fit.py"
] | [
"import math\nimport numpy as np\nimport datetime as dt\nfrom typing import Dict, Optional\n\nfrom voltoolbox import BusinessTimeMeasure, longest_increasing_subsequence, bs_implied_volatility\nfrom voltoolbox.fit.option_quotes import OptionSnapshot, OptionQuoteSlice, QuoteSlice\nfrom voltoolbox.fit.fit_utils import... | [
[
"numpy.concatenate",
"numpy.array",
"numpy.matmul",
"numpy.vectorize",
"numpy.median",
"numpy.exp",
"numpy.linspace",
"numpy.identity",
"numpy.linalg.solve",
"numpy.sqrt",
"numpy.column_stack"
]
] |
ZhouLiHai/data-digger | [
"fb413fcaa0a0f1d8995b212e9b09b687322ba059"
] | [
"classify.py"
] | [
"# -*- coding: utf-8 -*-\n\"\"\"\nCreated on Tue Jun 21 15:37:11 2016\n\n@author: Doppler\n\"\"\"\n\nfrom sklearn import datasets\nfrom sklearn.tree import DecisionTreeClassifier\n\nn_features=200\nx,y=datasets.make_classification(750,n_features,n_informative=5)\n\nimport numpy as np\n\ntraining = np.random.choice(... | [
[
"matplotlib.pylab.subplots",
"numpy.arange",
"sklearn.tree.DecisionTreeClassifier",
"sklearn.datasets.make_classification"
]
] |
Jacen-Chou/Paste-Video-Classification | [
"58af07a343bcd4f95f26a71d6ae9791552b2fe6e"
] | [
"4_classes_classification/py/paste_video_classification_resnet152.py"
] | [
"\n# coding: utf-8\n\n# In[1]:\n\n\n# %load paste_video_classification.py\n# 这个代码每个epoch都跑一遍训练集和验证集\n\nimport torch\nimport torch.nn as nn\nimport torch.optim as optim\nfrom torch.optim import lr_scheduler\nfrom torch.autograd import Variable\nimport torchvision\nfrom torchvision import datasets, models, transforms... | [
[
"torch.nn.Linear",
"torch.max",
"matplotlib.pyplot.xlabel",
"torch.save",
"matplotlib.pyplot.title",
"matplotlib.pyplot.legend",
"matplotlib.pyplot.figure",
"torch.cuda.is_available",
"numpy.arange",
"torch.utils.data.DataLoader",
"matplotlib.pyplot.ylabel",
"numpy.... |
DanHickstein/PyAbel | [
"48d52d670b9917f32819c52003ed32bd2698344e",
"48d52d670b9917f32819c52003ed32bd2698344e"
] | [
"doc/transform_methods/comparison/fig_experiment/experiment.py",
"abel/tools/polynomial.py"
] | [
"import numpy as np\nimport matplotlib.pyplot as plt\nimport abel\nimport bz2\n\ntransforms = [\n (\"basex\", abel.basex.basex_transform, '#880000'),\n (\"direct\", abel.direct.direct_transform, '#EE0000'),\n (\"hansenlaw\", abel.hansenlaw.hansenlaw_transform, '... | [
[
"matplotlib.pyplot.colorbar",
"matplotlib.pyplot.subplots",
"numpy.shape",
"numpy.loadtxt",
"numpy.arange"
],
[
"scipy.linalg.pascal",
"numpy.zeros_like",
"scipy.linalg.toeplitz",
"numpy.cumprod",
"numpy.zeros",
"numpy.trim_zeros",
"numpy.any",
"numpy.search... |
victorsun123/pylot | [
"43df8de4b4ed562370a5512093f6d9b486699567"
] | [
"scripts/check_3d_2d_conversions.py"
] | [
"# Checks methods for getting 3d world locations from depth map and from point cloud.\n\nimport copy\nimport numpy as np\nimport pptk\nimport time\n\nimport carla\n\nimport pylot.utils\nfrom pylot.simulation.carla_utils import get_world\nimport pylot.simulation.messages\nimport pylot.simulation.utils\nfrom pylot.si... | [
[
"matplotlib.pyplot.show",
"numpy.dtype",
"matplotlib.pyplot.imshow"
]
] |
thatguyandy27/python-sandbox | [
"33dffa286aee942c93c75303ab463313020bbd7a"
] | [
"Ex_Files_ML_EssT_Recommendations/Exercise Files/Chapter 4/view_movie_list.py"
] | [
"import pandas\nimport webbrowser\nimport os\n\n# Read the dataset into a data table using Pandas\ndata_table = pandas.read_csv(\"movies.csv\", index_col=\"movie_id\")\n\n# Create a web page view of the data for easy viewing\nhtml = data_table.to_html()\n\n# Save the html to a temporary file\nwith open(\"movie_list... | [
[
"pandas.read_csv"
]
] |
EIDOSlab/simplify | [
"4e5dd431e658d36c5a0a23bcd3e7a379d75d2501",
"4e5dd431e658d36c5a0a23bcd3e7a379d75d2501",
"4e5dd431e658d36c5a0a23bcd3e7a379d75d2501"
] | [
"simplify/layers.py",
"benchmark/benchmark_expand_layers.py",
"benchmark/profiler.py"
] | [
"import torch\nimport torch.nn as nn\n\n\nclass ConvB(nn.Conv2d):\n @staticmethod\n def from_conv(module: nn.Conv2d, bias):\n module.__class__ = ConvB\n module.register_parameter('bf', torch.nn.Parameter(bias))\n return module\n \n def forward(self, x):\n x = super().forward(... | [
[
"torch.zeros",
"torch.scatter",
"torch.nn.Parameter"
],
[
"torch.zeros",
"torch.cuda.synchronize",
"torch.gather",
"torch.cuda.Event",
"torch.no_grad",
"torch.nn.Parameter",
"torch.nn.Conv2d",
"torch.tensor",
"torch.scatter",
"torch.eye",
"torch.nn.funct... |
dashstander/TCL | [
"6c7a9eb5029d9c3cf9ce43122329d52a13e8baf8"
] | [
"Pretrain.py"
] | [
"'''\n * Copyright (c) 2021, salesforce.com, inc.\n * All rights reserved.\n * SPDX-License-Identifier: BSD-3-Clause\n * For full license text, see LICENSE.txt file in the repo root or https://opensource.org/licenses/BSD-3-Clause\n'''\n\nimport argparse\nimport os\nimport ruamel_yaml as yaml\nimport numpy as np\nim... | [
[
"torch.device",
"numpy.random.seed",
"torch.nn.parallel.DistributedDataParallel",
"torch.manual_seed",
"torch.load",
"torch.distributed.barrier"
]
] |
GeneralFox2/Video_Analyzer | [
"7d32d6a68c9615efe65721d73dc71c9ed2c86ace"
] | [
"analyze_video.py"
] | [
"#!/usr/bin/env python3\n#python3 analyze_video.py {path/video_filename.mp4} {ID Folder Name}\n\n# initalize\nimport sys\nimport argparse\nimport tensorflow as tf\nimport cv2\nimport dlib\nimport numpy as np\nimport detect_and_align\nimport os\n\nfrom model import OpenNsfwModel\nfrom image_utils import create_yahoo... | [
[
"numpy.argmin",
"tensorflow.get_default_graph",
"tensorflow.python.platform.gfile.FastGFile",
"tensorflow.GraphDef",
"tensorflow.import_graph_def",
"tensorflow.Session",
"tensorflow.Graph",
"numpy.shape",
"tensorflow.variable_scope",
"numpy.stack",
"numpy.arange",
"... |
ShengjiaZhao/PixelVAE | [
"5c83b7e9af9c2db73dadf3e0b040da979d09ff07"
] | [
"train.py"
] | [
"\"\"\"\nTrains a Pixel-CNN++ generative model on CIFAR-10 or Tiny ImageNet data.\nUses multiple GPUs, indicated by the flag --nr-gpu\n\nExample usage:\nCUDA_VISIBLE_DEVICES=0,1,2,3 python train_double_cnn.py --nr_gpu 4\n\"\"\"\n\nimport os\nimport sys\nimport time\nimport json\nimport argparse\n\nimport numpy as n... | [
[
"numpy.mean",
"tensorflow.gradients",
"tensorflow.one_hot",
"tensorflow.set_random_seed",
"tensorflow.trainable_variables",
"numpy.concatenate",
"numpy.random.normal",
"numpy.log",
"tensorflow.train.Saver",
"tensorflow.Variable",
"tensorflow.ConfigProto",
"numpy.pro... |
veda-s4dhak/OpenAI_Gym_Testing | [
"9cd0bef327fb820205ecc428d86072d0b690791e"
] | [
"src/cartpole_env.py"
] | [
"\"\"\"\nClassic cart-pole system implemented by Rich Sutton et al.\nCopied from http://incompleteideas.net/sutton/book/code/pole.c\npermalink: https://perma.cc/C9ZM-652R\n\"\"\"\n\nimport math\nimport gym\nfrom gym import spaces, logger\nfrom gym.utils import seeding\nimport numpy as np\n\n\nclass CartPoleEnv(gym.... | [
[
"numpy.deg2rad",
"numpy.finfo",
"numpy.array",
"numpy.exp"
]
] |
EonianCoda/continual_learning_forOD | [
"d99c9b63a1e86d36bf1e0d35c145db51e1c9f27a"
] | [
"preprocessing/enhance_coco.py"
] | [
"from collections import defaultdict\nimport pandas as pd\nfrom pycocotools.coco import COCO\nimport numpy as np\nclass Enhance_COCO(COCO):\n def __init__(self, path):\n\n super().__init__(path)\n self.classes = defaultdict()\n self.reverse_classes = defaultdict()\n for category in se... | [
[
"pandas.DataFrame",
"numpy.unique"
]
] |
SABS-R3-Epidemiology/epiabm | [
"8eb83fd2de84104f6f77929e3771095f7b033ddc",
"8eb83fd2de84104f6f77929e3771095f7b033ddc"
] | [
"pyEpiabm/pyEpiabm/tests/test_unit/test_utility/test_state_transition_matrix.py",
"pyEpiabm/pyEpiabm/tests/test_unit/test_sweep/test_host_progression_sweep.py"
] | [
"from collections import defaultdict\nfrom enum import Enum\nimport numpy as np\nimport pandas as pd\nfrom pandas.testing import assert_frame_equal\nimport unittest\nfrom unittest import mock\n\nfrom pyEpiabm.property import InfectionStatus\nfrom pyEpiabm.utility import StateTransitionMatrix\nfrom pyEpiabm.tests.te... | [
[
"pandas.testing.assert_frame_equal"
],
[
"numpy.array",
"numpy.ceil",
"numpy.zeros",
"numpy.testing.assert_almost_equal",
"pandas.DataFrame",
"numpy.triu"
]
] |
david-a-joy/cm-disp-angle | [
"7e2cccf50d6b3555db8e491f3a182cae6adabce1"
] | [
"cm_disp_angle/flow.py"
] | [
"\"\"\" Main optical flow calculations\n\n* :py:func:`calc_optical_flow`: Driver script for optical flow calculation and plotting\n\n* :py:class:`AnalyzeFlow`: Optical flow analysis pipeline class\n\n\"\"\"\n\n# Imports\nimport shutil\nimport pathlib\nfrom typing import Tuple, List, Optional\n\n# 3rd party\nimport ... | [
[
"numpy.mean",
"pandas.concat",
"numpy.zeros_like",
"pandas.DataFrame",
"numpy.logical_and",
"matplotlib.pyplot.subplots",
"numpy.arange",
"numpy.sqrt",
"scipy.integrate.simps",
"numpy.array",
"numpy.reshape",
"numpy.zeros",
"numpy.percentile",
"matplotlib.py... |
Servir-Mekong/GPM-BICO | [
"5bffab22f1b7fe230e170c7a61afa2a68ddae71f"
] | [
"GPM_BICO_v1.3/scripts/Processtools.py"
] | [
"# -*- coding: utf-8 -*-\r\n\"\"\"\r\nBIAS CORRECTOR FOR GPM\r\n\r\n@ author: SERVIR MEKONG \r\n@ correspondence M.A. LAVERDE-BARAJAS \r\n@ mlaverdeb@gmail.com\r\n\"\"\"\r\nimport pandas as pd\r\nimport numpy as np\r\nfrom osgeo import gdal,osr\r\nfrom math import sqrt\r\nfrom sklearn.metrics import mean_squared_er... | [
[
"matplotlib.pyplot.xlim",
"numpy.max",
"matplotlib.pyplot.colorbar",
"pandas.DataFrame",
"matplotlib.pyplot.savefig",
"numpy.logical_and",
"matplotlib.pyplot.gca",
"matplotlib.pyplot.subplot",
"numpy.array",
"numpy.savetxt",
"numpy.round",
"matplotlib.pyplot.title",... |
project-kona/KTracker | [
"c8d57d6e573bcc41dad98765e7bacfb8b3f29788"
] | [
"scripts/read_bin.py"
] | [
"#!/usr/bin/env python3\n\nimport sys\nimport struct\nimport pandas as pd\n\nimport matplotlib\n# Must be before importing matplotlib.pyplot or pylab!\nmatplotlib.use('Agg')\nimport matplotlib.pyplot as plt\n\nfrom matplotlib.ticker import MaxNLocator\n\n###############################################\ndsize = 16\n... | [
[
"matplotlib.use",
"matplotlib.ticker.MaxNLocator",
"pandas.DataFrame",
"matplotlib.pyplot.xlabel",
"matplotlib.pyplot.grid",
"matplotlib.pyplot.ylim",
"matplotlib.pyplot.savefig",
"matplotlib.pyplot.cla",
"matplotlib.pyplot.close",
"matplotlib.pyplot.legend",
"matplotli... |
pramukta/trimesh | [
"ee43dc3e77b85606e37683307ef12e5cea4e0338"
] | [
"trimesh/ray/ray_pyembree.py"
] | [
"\"\"\"\nRay queries using the pyembree package with the\nAPI wrapped to match our native raytracer.\n\"\"\"\nimport numpy as np\n\nfrom collections import deque\nfrom copy import deepcopy\n\nfrom pyembree import __version__ as _ver\nfrom pyembree import rtcore_scene\nfrom pyembree.mesh_construction import Triangle... | [
[
"numpy.logical_not",
"numpy.array",
"numpy.zeros",
"numpy.nonzero",
"numpy.clip",
"numpy.hstack",
"numpy.asanyarray"
]
] |
CliMT/climt-legacy | [
"adbd4fe77426c90deb8d2c046a2f3dc3b72df89e"
] | [
"src/radiation/greynew/setup.py"
] | [
"from distutils.core import setup\nfrom distutils.extension import Extension\nfrom Cython.Distutils import build_ext\n# This line only needed if building with NumPy in Cython file.\nfrom numpy import get_include\nfrom os import system\n\n# compile the fortran modules without linking\n\next_modules = [Extension(# mo... | [
[
"numpy.get_include"
]
] |
francecon/ICT-for-Health | [
"46588d21077cc6ef8dd8dfc68a2942090fbad375"
] | [
"Regression on Parkinson's disease data/main.py"
] | [
"# -*- coding: utf-8 -*-\n\"\"\"\nCreated on Mon Oct 12 15:45:29 2020\n\n@author: Francesco Conforte\n\"\"\"\n\nimport pandas as pd\nimport numpy as np\nimport matplotlib.pyplot as plt\nimport sub.minimization as mymin\n\nplt.close('all')\nx=pd.read_csv(\"data/parkinsons_updrs.csv\") # read the dataset; xx is a dat... | [
[
"matplotlib.pyplot.colorbar",
"numpy.empty",
"numpy.argmin",
"numpy.random.seed",
"matplotlib.pyplot.grid",
"matplotlib.pyplot.title",
"matplotlib.pyplot.close",
"numpy.random.shuffle",
"matplotlib.pyplot.figure",
"numpy.mean",
"numpy.arange",
"matplotlib.pyplot.gcf... |
DEVESHTARASIA/Theano | [
"1985d4c73fabd5f08f54b922e73a9306e09c77a5"
] | [
"theano/tests/test_printing.py"
] | [
"\"\"\"\nTests of printing functionality\n\"\"\"\nfrom __future__ import absolute_import, print_function, division\nimport logging\n\nfrom nose.plugins.skip import SkipTest\nimport numpy as np\n\nfrom six.moves import StringIO\n\nimport theano\nimport theano.tensor as tensor\n\nfrom theano.printing import min_infor... | [
[
"numpy.arange"
]
] |
labcontext/image-inpainting-oldpaper | [
"da4683a2c58d662e443ea24ab93fd9d8fcb96bda"
] | [
"pytorch-inpainting-with-partial-conv/generate_data.py"
] | [
"import argparse\nimport numpy as np\nimport random\nfrom PIL import Image\n\naction_list = [[0, 1], [0, -1], [1, 0], [-1, 0]]\n\n\ndef random_walk(canvas, ini_x, ini_y, length):\n x = ini_x\n y = ini_y\n img_size = canvas.shape[-1]\n x_list = []\n y_list = []\n for i in range(length):\n r ... | [
[
"numpy.sum",
"numpy.array",
"numpy.ones",
"numpy.clip"
]
] |
CfKu/matplotlib-din461 | [
"c0371a4fdaa04448726ac0a547ff1b0fd64bebfd"
] | [
"matplotlib_din461.py"
] | [
"# -*- coding: utf-8 -*-\n#\n\"\"\"\nMIT License\n\nCopyright (c) 2018 Christof Küstner\n\nPermission is hereby granted, free of charge, to any person obtaining a copy\nof this software and associated documentation files (the \"Software\"), to deal\nin the Software without restriction, including without limitation ... | [
[
"matplotlib.ticker.MaxNLocator",
"matplotlib.pyplot.xlabel",
"matplotlib.pyplot.plot",
"matplotlib.ticker.FuncFormatter",
"numpy.arange",
"matplotlib.pyplot.tight_layout",
"matplotlib.pyplot.ylabel",
"numpy.cos",
"matplotlib.pyplot.show",
"matplotlib.pyplot.gca"
]
] |
RManLuo/CP-GNN | [
"a186d31167c1b00408de767b78271c5027882e23",
"a186d31167c1b00408de767b78271c5027882e23"
] | [
"utils/evluator.py",
"data/ACM/5_hetero.py"
] | [
"#!/usr/bin/env python \n# -*- coding: utf-8 -*-\n# @Time : 2020/8/10 23:25\n# @Author : Raymound luo\n# @Mail : luolinhao1998@gmail.com\n# @File : evluator.py\n# @Software: PyCharm\n# @Describe:\nfrom sklearn.linear_model import LogisticRegression\nfrom sklearn.neighbors import KNeighborsClassifier\nfrom... | [
[
"numpy.concatenate",
"sklearn.metrics.normalized_mutual_info_score",
"sklearn.metrics.cluster.contingency_matrix",
"sklearn.neighbors.KNeighborsClassifier",
"numpy.sum",
"sklearn.cluster.KMeans",
"sklearn.svm.SVC",
"sklearn.linear_model.LogisticRegression",
"sklearn.metrics.sil... |
SuccessionEcologicalServices/MetPy | [
"2b685023351a89168a7e06c3858ff3493af670e7"
] | [
"metpy/gridding/tests/test_points.py"
] | [
"# Copyright (c) 2008-2015 MetPy Developers.\n# Distributed under the terms of the BSD 3-Clause License.\n# SPDX-License-Identifier: BSD-3-Clause\n\"\"\"Test the `points` module.\"\"\"\n\nfrom __future__ import division\n\nimport logging\n\nimport numpy as np\nfrom numpy.testing import assert_array_almost_equal\n\n... | [
[
"numpy.testing.assert_array_almost_equal",
"numpy.array"
]
] |
graeme-winter/wildlifecam | [
"6bd914d0000a4521228e48bf39adc4d434b4d19d"
] | [
"src/wildlifecam/jpeg2mp4wts.py"
] | [
"import sys\nimport os\n\nimport numpy as np\nfrom PIL import Image, ImageFont, ImageDraw\nimport cv2\n\n\ndef main(file_template, start=0, end=100000):\n\n font = ImageFont.truetype(\"Menlo.ttc\", 32)\n capture = cv2.VideoCapture(0)\n out = cv2.VideoWriter(\n \"out.mp4\", cv2.VideoWriter_fourcc(*\"... | [
[
"numpy.asarray"
]
] |
TUMCREATE-ESTL/districtcooling | [
"5811a66bab41ad9154ba8882609f29579a14ddb4"
] | [
"districtcooling/coolinggrid.py"
] | [
"import pandas as pd\nimport numpy as np\n\n# ======================================================================================================================\n# Model of distribution system (=cooling grid) CLASS\n# ==============================================================================================... | [
[
"numpy.log",
"pandas.DataFrame.from_dict",
"pandas.DataFrame",
"numpy.fabs",
"numpy.linalg.solve",
"pandas.concat"
]
] |
maxint/jittor | [
"0b6a2e32f64acaeefcea63df1ea35fd0d729c604"
] | [
"python/jittor/test/test_cudnn_op.py"
] | [
"# ***************************************************************\n# Copyright (c) 2021 Jittor. All Rights Reserved. \n# Maintainers: Dun Liang <randonlang@gmail.com>. \n# This file is subject to the terms and conditions defined in\n# file 'LICENSE.txt', which is part of this source code package.\n# **************... | [
[
"numpy.allclose",
"numpy.abs"
]
] |
Menelau/pymfe | [
"4e43c9210a19e3123d9d24a22efa4e65099ed129"
] | [
"pymfe/_internal.py"
] | [
"\"\"\"This module provides useful functions for the MFE package.\n\n\nAttributes:\n VALID_VALUE_PREFIX (:obj:`str`): Prefix which all tuples that\n keep valid values for custom user options must use in its name.\n This prefix is used to enable the automatic detection of these\n groups.\n\n ... | [
[
"numpy.array",
"numpy.isnan",
"numpy.percentile",
"numpy.copy",
"numpy.digitize",
"numpy.diff",
"numpy.apply_along_axis",
"numpy.arange",
"numpy.unique"
]
] |
demianw/nipype | [
"52d64c30d96ecd94f1833156e28dce32c4f05ebe",
"18fe222557cf3b9627e06b2a66fba589feaca581"
] | [
"nipype/algorithms/tests/test_mesh_ops.py",
"nipype/workflows/dmri/fsl/artifacts.py"
] | [
"# coding: utf-8\n# emacs: -*- mode: python; py-indent-offset: 4; indent-tabs-mode: nil -*-\n# vi: set ft=python sts=4 ts=4 sw=4 et:\n\nimport os\nfrom shutil import rmtree\nfrom tempfile import mkdtemp\n\nfrom nipype.testing import (assert_equal, skipif,\n assert_almost_equal, example_da... | [
[
"numpy.array",
"numpy.linalg.norm"
],
[
"numpy.where",
"numpy.loadtxt",
"numpy.ones"
]
] |
wonjongJ/e2cnn | [
"f63ca7799abd4e534d09ec9cd1ec56aebcd733c6",
"425282ab0f27523dba9eabd14580a5f61799f54a"
] | [
"e2cnn/nn/modules/nonlinearities/relu.py",
"e2cnn/group/representation.py"
] | [
"\nfrom e2cnn.gspaces import *\nfrom e2cnn.nn import FieldType\nfrom e2cnn.nn import GeometricTensor\n\nfrom ..equivariant_module import EquivariantModule\n\nimport torch\nimport torch.nn.functional as F\n\nfrom typing import List, Tuple, Any\n\nimport numpy as np\n\n__all__ = [\"ReLU\"]\n\n\nclass ReLU(Equivariant... | [
[
"torch.nn.functional.relu",
"torch.allclose",
"torch.randn",
"numpy.abs"
],
[
"numpy.dot",
"scipy.sparse.csgraph.connected_components",
"numpy.set_printoptions",
"scipy.linalg.svd",
"numpy.invert",
"numpy.cumsum",
"numpy.zeros_like",
"scipy.sparse.find",
"sc... |
Einlar/biopytorch | [
"6a6a573ada6e231f10447b076d2e5cf10341421a"
] | [
"biopytorch/biolinear.py"
] | [
"import torch\r\nimport torch.nn as nn\r\nimport torch.nn.functional as F\r\n\r\n\r\nclass BioLinear(nn.Module):\r\n def __init__(\r\n self,\r\n in_features: int,\r\n out_features: int,\r\n bias: bool = False,\r\n delta: float = 0.05,\r\n ranking_param: int = 2,\r\n ... | [
[
"torch.mul",
"torch.arange",
"torch.sign",
"torch.abs",
"torch.nn.BatchNorm1d",
"torch.t",
"torch.ones_like",
"torch.zeros_like",
"torch.randn"
]
] |
CommanderPho/pyqtgraph | [
"39f5d98c6ee72417d6e6104d3a184070eee236f5"
] | [
"pyqtgraph/functions.py"
] | [
"\"\"\"\nfunctions.py - Miscellaneous functions with no other home\nCopyright 2010 Luke Campagnola\nDistributed under MIT/X11 license. See license.txt for more information.\n\"\"\"\n\nfrom __future__ import division\n\nimport decimal\nimport math\nimport re\nimport struct\nimport sys\nimport warnings\nfrom collec... | [
[
"numpy.product",
"numpy.argmin",
"numpy.core.umath.clip",
"numpy.frombuffer",
"numpy.dtype",
"numpy.concatenate",
"numpy.full",
"numpy.ndindex",
"numpy.empty",
"numpy.nonzero",
"numpy.take",
"numpy.can_cast",
"numpy.arange",
"numpy.isfinite",
"numpy.core... |
AndrewBoney/nlp_getting_started | [
"aa95b9661ce53e1f83afb9e8cb599a97d2f86f37"
] | [
"src/run.py"
] | [
"import numpy as np \nimport pandas as pd \n\nimport tensorflow as tf\nfrom tensorflow.keras.preprocessing.text import Tokenizer\nfrom tensorflow.keras import Input\nfrom keras.layers.core import Activation, Dropout, Dense\nfrom keras.layers import Flatten, LSTM, Bidirectional, Concatenate\nfrom keras.layers.embedd... | [
[
"numpy.concatenate",
"tensorflow.keras.preprocessing.text.Tokenizer",
"tensorflow.keras.Input",
"sklearn.metrics.accuracy_score",
"sklearn.linear_model.LogisticRegression",
"numpy.where",
"pandas.concat",
"sklearn.model_selection.train_test_split",
"pandas.read_csv",
"panda... |
chokozainer/chokozainerrl | [
"7745e307dba715f11887ccccce8cf1067ecfb99f"
] | [
"chokozainerrl/agents/trpo.py"
] | [
"from __future__ import division\nfrom __future__ import print_function\nfrom __future__ import unicode_literals\nfrom __future__ import absolute_import\nfrom builtins import * # NOQA\nfrom future import standard_library\nstandard_library.install_aliases() # NOQA\n\nimport collections\nimport itertools\nfrom logg... | [
[
"numpy.mean",
"numpy.cumsum"
]
] |
GuillaumeMougeot/fasterflow_old | [
"dfe1a313cb770b85a24e6f6fea4f4214b3f24223"
] | [
"examples/gan/pro_gan/train_pro_gan.py"
] | [
"import tensorflow as tf\nfrom functools import partial\nimport os\nfrom shutil import copyfile\nfrom datetime import datetime\nimport skimage as sk\nimport numpy as np\nfrom time import time\n\nfrom fasterflow import train\nfrom fasterflow import dataset\nfrom fasterflow import utils\nfrom fasterflow import evalua... | [
[
"tensorflow.compat.v1.placeholder",
"tensorflow.compat.v1.global_variables_initializer",
"numpy.ceil",
"tensorflow.compat.v1.train.AdamOptimizer",
"tensorflow.compat.v1.global_variables",
"tensorflow.compat.v1.Session",
"numpy.clip",
"numpy.random.random",
"numpy.log2",
"te... |
duken72/PythonRobotics | [
"177f04618c4bbba40bea38cd57d642f7ab9e3725"
] | [
"PathPlanning/AStar/a_star_searching_from_two_side.py"
] | [
"\"\"\"\nA* algorithm\nAuthor: Weicent\nrandomly generate obstacles, start and goal point\nsearching path from start and end simultaneously\n\"\"\"\n\nimport numpy as np\nimport matplotlib.pyplot as plt\nimport math\n\nshow_animation = True\n\n\nclass Node:\n \"\"\"node with properties of g, h, coordinate and pa... | [
[
"numpy.array",
"matplotlib.pyplot.plot",
"matplotlib.pyplot.legend",
"matplotlib.pyplot.title",
"matplotlib.pyplot.cla",
"numpy.vstack",
"matplotlib.pyplot.pause",
"numpy.random.randint",
"matplotlib.pyplot.gcf",
"matplotlib.pyplot.show",
"matplotlib.pyplot.axis"
]
] |
buzzCraft/GamestonkTerminal | [
"9cae23cda79fe0030203dae9eb1078a1c132ff7b"
] | [
"terminal.py"
] | [
"#!/usr/bin/env python\n\nimport argparse\n\nimport sys\nimport os\nfrom datetime import datetime, timedelta\nimport pandas as pd\nimport yfinance as yf\nfrom alpha_vantage.timeseries import TimeSeries\nfrom prompt_toolkit.completion import NestedCompleter\n\nfrom gamestonk_terminal import config_terminal as cfg\nf... | [
[
"pandas.DataFrame"
]
] |
ASavchenkov/pytorch-cifar | [
"bd52648438d7499f85c7675b639a40195cc4c38a"
] | [
"visualize.py"
] | [
"import numpy as np\nimport pickle\n\nimport matplotlib.pyplot as plt\nimport matplotlib.image as mpimg\n\n\nselectors = pickle.load( open( 'l2_l1_reg/020', 'rb' ) )\n\n#we throw out the biases because they're not important for pruning\nweights = [s for s in selectors if len(s.shape)==4]\n\nweights = [w.reshape((w.... | [
[
"numpy.concatenate",
"numpy.pad",
"numpy.abs",
"matplotlib.pyplot.show",
"matplotlib.pyplot.imshow"
]
] |
kb2623/WeOptPy | [
"2e9e75acf8fedde0ae4c99da6c786a712d4f011c"
] | [
"WeOptPy/algorithms/fpa.py"
] | [
"# encoding=utf8\n\n\"\"\"Flower pollination algorithm module.\"\"\"\n\nimport numpy as np\nfrom scipy.special import gamma as Gamma\n\nfrom WeOptPy.algorithms.interfaces import Algorithm\nfrom WeOptPy.util import reflect_repair\n\n__all__ = ['FlowerPollinationAlgorithm']\n\n\nclass FlowerPollinationAlgorithm(Algor... | [
[
"numpy.sin",
"scipy.special.gamma",
"numpy.zeros"
]
] |
camrongodbout/TensorFlow-in-a-Nutshell | [
"a57723c54c5c5d9f27df9702a54551a2a4378844"
] | [
"part3/cnn.py"
] | [
"from __future__ import absolute_import\nfrom __future__ import division\nfrom __future__ import print_function\n\nfrom sklearn import metrics\nimport tensorflow as tf\nfrom tensorflow.contrib import learn\n\n# from SKFLOW \n\n### Download and load MNIST data.\nmnist = learn.datasets.load_dataset('mnist')\n\n### Co... | [
[
"tensorflow.contrib.learn.ops.dnn",
"tensorflow.contrib.learn.datasets.load_dataset",
"tensorflow.reshape",
"tensorflow.contrib.learn.TensorFlowEstimator",
"tensorflow.variable_scope",
"tensorflow.contrib.learn.models.logistic_regression",
"tensorflow.contrib.learn.ops.conv2d",
"te... |
oldpaws/AI3601_RL_Final_Project_MAGAIL | [
"6e53d5c4ad21c9e3907e6d14b20c04b3287800cf",
"6e53d5c4ad21c9e3907e6d14b20c04b3287800cf"
] | [
"History/20211230-011142_76_best/example_rollout.py",
"utils_psgail.py"
] | [
"import numpy as np\n\nfrom traffic_simulator import TrafficSim\n\n\nif __name__ == \"__main__\":\n env = TrafficSim([\"./ngsim\"])\n obs = env.reset()\n\n act = np.random.normal(0, 1, size=(2,))\n obs, rew, done, info = env.step(act)\n\n print(\"finished\")\n env.close()\n",
"import sys\nimport... | [
[
"numpy.random.normal"
],
[
"numpy.array",
"numpy.asarray",
"numpy.zeros",
"torch.no_grad",
"torch.cuda.is_available",
"torch.tensor"
]
] |
qmisr/github_data_tutorial | [
"f57d429402c3de989f07092162b385d2bf445dac"
] | [
"parse_git_stats.py"
] | [
"import os\nimport subprocess\nimport sys\nfrom datetime import datetime, timedelta\n\nimport pandas as pd\nimport numpy as np\n\n\ndef get_main_head_rev(repo_path):\n cdr = os.getcwd()\n os.chdir(repo_path)\n command = \"git show-ref --heads -s\"\n process = subprocess.Popen(\n command, shell=Tr... | [
[
"numpy.max",
"numpy.median",
"pandas.DataFrame",
"numpy.min",
"numpy.mean",
"numpy.std"
]
] |
jettify/pytorch-optimizer | [
"9b92f500d765b0168e3f12b04f05b0cfa75f37b5"
] | [
"tests/test_param_validation.py"
] | [
"import pytest\nimport torch\n\nimport torch_optimizer as optim\n\n\ndef assert_sparse_not_supported(optimizer_class, err_msg=None):\n param = torch.randn(1, 1).to_sparse().requires_grad_(True)\n grad = torch.randn(1, 1).to_sparse()\n param.grad = grad\n optimizer = optimizer_class([param])\n optimiz... | [
[
"torch.randn"
]
] |
ChristianMichelsen/metadamage | [
"f2cd8b24ae93f50c8e64202b484c5cba973ae167"
] | [
"metadamage/io.py"
] | [
"# Scientific Library\nfrom pandas import HDFStore\n\n# Standard Library\nimport json\nfrom pathlib import Path\nimport warnings\n\n# Third Party\nimport pyarrow as pa\nimport pyarrow.dataset as ds\nimport pyarrow.parquet as pq\nfrom tqdm.auto import tqdm\n\n# First Party\nfrom metadamage import utils\n\n\nclass Pa... | [
[
"pandas.HDFStore"
]
] |
anjali-chadha/tutorials | [
"bd8361c0383c5588ea44636b8d162b7eec46268b"
] | [
"beginner_source/blitz/cifar10_tutorial.py"
] | [
"# -*- coding: utf-8 -*-\n\"\"\"\nTraining a Classifier\n=====================\n\nThis is it. You have seen how to define neural networks, compute loss and make\nupdates to the weights of the network.\n\nNow you might be thinking,\n\nWhat about data?\n----------------\n\nGenerally, when you have to deal with image,... | [
[
"torch.nn.Linear",
"torch.max",
"torch.nn.MaxPool2d",
"torch.no_grad",
"torch.nn.Conv2d",
"torch.cuda.is_available",
"numpy.transpose",
"torch.utils.data.DataLoader",
"matplotlib.pyplot.show",
"torch.nn.CrossEntropyLoss"
]
] |
anonymoussss/FCN_pretrained | [
"d6ad889b470ac97da5d1a567405e16263e19eba3"
] | [
"model_test.py"
] | [
"from __future__ import print_function\nimport tensorflow as tf\nimport numpy as np\n\nfrom scipy import ndimage\nfrom scipy.spatial.distance import euclidean\nfrom sklearn import metrics\nimport TensorflowUtils as utils\nimport read_Data_list as scene_parsing\nimport BatchDatsetReader as dataset\nfrom six.moves im... | [
[
"tensorflow.shape",
"tensorflow.nn.relu",
"tensorflow.argmax",
"tensorflow.Session",
"numpy.mean",
"numpy.shape",
"numpy.transpose",
"tensorflow.variable_scope",
"numpy.random.randint",
"tensorflow.placeholder",
"tensorflow.squeeze",
"tensorflow.add",
"tensorflo... |
xiki-tempula/inflateorg | [
"2345d7ab80b2b81e3b76004e210778c0232aaa20"
] | [
"inflateorg/inflateorg.py"
] | [
"\"\"\"\ninflateorg.py\nInflate or shrink the membrane to resolve clash between membrane and protein.\n\nHandles the primary functions\n\"\"\"\n\nimport os\nimport shutil\nfrom subprocess import call\nfrom pkg_resources import resource_filename\n\nimport MDAnalysis as mda\nimport numpy as np\n\nos.environ[\"GMX_MAX... | [
[
"numpy.array"
]
] |
jonathf/npoly | [
"9df4bd2a3b134e8a196e24389c0ad84c26da9662"
] | [
"numpoly/array_function/argmax.py"
] | [
"\"\"\"Return the indices of the maximum values along an axis.\"\"\"\nfrom __future__ import annotations\nfrom typing import Any, Optional\n\nimport numpy\nimport numpoly\n\nfrom ..baseclass import PolyLike\nfrom ..dispatch import implements\n\n\n@implements(numpy.argmax)\ndef argmax(\n a: PolyLike,\n axis: O... | [
[
"numpy.argmax"
]
] |
yngtodd/molecules-deprecated | [
"adf9477e6122fa4e92cedbbba26a358ea903e3a4"
] | [
"molecules/rl/md_sims/environment.py"
] | [
"from __future__ import print_function\nimport os\nimport numpy as np\nfrom simtk.openmm.app import *\nfrom simtk.openmm import *\nfrom simtk.unit import *\nfrom sys import stdout\n\n# From Molecules\nimport sys\nsys.path.append('../')\nfrom extract_native_contact.extract_native_contact import ExtractNativeContact\... | [
[
"scipy.stats.zscore",
"matplotlib.cm.ScalarMappable",
"numpy.load",
"numpy.fromstring",
"matplotlib.pyplot.switch_backend",
"numpy.histogram",
"matplotlib.pyplot.savefig",
"matplotlib.pyplot.get_cmap",
"numpy.save",
"numpy.array",
"numpy.reshape",
"matplotlib.pyplot... |
samuelbunga/pyobo | [
"42674b4f87d40ad1c296e72768d26f3e451f3353"
] | [
"src/pyobo/sources/pombase.py"
] | [
"# -*- coding: utf-8 -*-\n\n\"\"\"Converter for PomBase.\"\"\"\n\nimport logging\nfrom collections import defaultdict\nfrom typing import Iterable\n\nimport bioversions\nimport click\nimport pandas as pd\nfrom more_click import verbose_option\nfrom tqdm import tqdm\n\nimport pyobo\nfrom pyobo import Reference\nfrom... | [
[
"pandas.notna"
]
] |
ZhangHanbo/Visual-Manipulation-Relationship-Network-Pytorch | [
"9dd24947db318f6e404918d4758f1d824eea3748"
] | [
"main.py"
] | [
"# --------------------------------------------------------\n# Visual Detection: State-of-the-Art\n# Copyright: Hanbo Zhang\n# Licensed under The MIT License [see LICENSE for details]\n# Written by Hanbo\n# based on code from Jiasen Lu, Jianwei Yang, Ross Girshick\n# ------------------------------------------------... | [
[
"matplotlib.use",
"torch.nn.DataParallel"
]
] |
holzman/hgg-coffea | [
"5aabdb127edaa15b0f22d54f0e3ccdc74c5c10de"
] | [
"src/hgg_coffea/tools/diphoton_mva.py"
] | [
"from typing import List, Optional, Tuple\n\nimport awkward\nimport numpy\nimport xgboost\n\n\ndef calculate_diphoton_mva(\n mva: Tuple[Optional[xgboost.Booster], List[str]],\n diphotons: awkward.Array,\n events: awkward.Array,\n) -> awkward.Array:\n if mva[0] is None:\n return diphotons\n dip... | [
[
"numpy.cosh",
"numpy.sqrt",
"numpy.cos"
]
] |
paulpuren/PhySR | [
"e1c2fd7457994a6037093ceb050c883f2a6932cc"
] | [
"Code/3DGS.py"
] | [
"\"\"\" PhySR for 3D GS \"\"\"\r\n\r\nimport torch\r\nimport torch.nn as nn\r\nimport torch.optim as optim\r\nfrom torch.autograd import Variable\r\nimport torch.nn.functional as F\r\nfrom torch.utils.data import Dataset\r\nfrom torch.optim import lr_scheduler\r\nimport numpy as np\r\nimport matplotlib.pyplot as pl... | [
[
"torch.cat",
"torch.optim.lr_scheduler.StepLR",
"torch.load",
"torch.set_default_dtype",
"numpy.concatenate",
"torch.nn.Conv1d",
"torch.autograd.Variable",
"matplotlib.pyplot.savefig",
"torch.utils.data.random_split",
"torch.FloatTensor",
"torch.norm",
"numpy.save",... |
roguephysicist/nonrefco | [
"4056c91cc9bcdfb26e8d5a668301db3f091d573a"
] | [
"shgyield/shg.py"
] | [
"#!/usr/bin/env python\n\"\"\"\nshgyield.py is a python module for exploring the SHG optical response of\nmaterials. It is well suited for 2D-materials, surfaces, bulks, and\nmetamaterials. For a complete overview of the theory, see PRB 94, 115314 (2016).\n\ntodo:\n* SHG: SOME Nv=1 INSTANCES ARE HARDCODED, NEED TO ... | [
[
"numpy.sin",
"scipy.interpolate.InterpolatedUnivariateSpline",
"scipy.ndimage.filters.gaussian_filter",
"numpy.seterr",
"numpy.exp",
"scipy.constants.value",
"numpy.sinc",
"numpy.radians",
"numpy.sqrt",
"numpy.cos"
]
] |
AlexeyMalafeev/kfw-the-game | [
"7db98c00595ec0d87aa5ed0cc2886bd6b5d36381"
] | [
"dev_scripts/move_gen.py"
] | [
"import os\nimport sys\nfrom pathlib import Path\n# this has to be before imports from kf_lib\nlib_path = Path('..').resolve()\nos.chdir(lib_path)\nif lib_path not in sys.path:\n sys.path.append(str(lib_path))\n\nimport pandas as pd\n\n\nTIER_MAX = 10\nQI_COST_PER_TIER = 5\n\n\ndef listr(s):\n \"\"\"'x,x,x'st... | [
[
"pandas.DataFrame"
]
] |
fakufaku/separake | [
"a485f7729a11b877ac5c86285e37a7ed05a4b027"
] | [
"separake_em_early.py"
] | [
"\nimport numpy as np\nimport pyroomacoustics as pra\nimport matplotlib.pyplot as plt\nfrom scipy.io import wavfile\n\nfrom multinmf_conv_em import multinmf_conv_em_wrapper\nfrom multinmf_recons_im import multinmf_recons_im\n\nfrom utilities import partial_rir\n\n# get the speed of sound from pyroomacoustics\nc = p... | [
[
"numpy.array",
"scipy.io.wavfile.read",
"matplotlib.pyplot.title",
"numpy.fft.rfftfreq",
"numpy.load",
"scipy.io.wavfile.write",
"matplotlib.pyplot.figure",
"numpy.std",
"matplotlib.pyplot.specgram",
"matplotlib.pyplot.show",
"matplotlib.pyplot.subplot"
]
] |
qimchen/Apollo_Jimmy | [
"65bda57aa2f01b045ecf9cff95d9e6fd80ed091f"
] | [
"modules/tools/record_play/rtk_player.py"
] | [
"#!/usr/bin/env python\n\n###############################################################################\n# Copyright 2017 The Apollo 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 ... | [
[
"scipy.signal.filtfilt",
"numpy.genfromtxt",
"scipy.signal.butter"
]
] |
patrickboehnke/ThUZirconCalculator | [
"e1268915d2637da1f178184eb3a4978be1500fad"
] | [
"ThUZirconCalculator.py"
] | [
"# -*- coding: utf-8 -*-\n\"\"\"\nCreated on Thu Dec 28 19:51:54 2015\n\n@author: Patrick Boehnke\n\nIf you use this code please cite:\n\nBoehnke, P., Barboni, M., & Bell, E. A. (2016). Zircon U/Th Model Ages in the Presence of Melt Heterogeneity. Quaternary Geochronology, Submitted.\n\nFor comments please contact:... | [
[
"numpy.savetxt",
"numpy.random.choice",
"numpy.zeros",
"numpy.copy",
"numpy.random.randn",
"numpy.mean",
"numpy.std",
"numpy.loadtxt"
]
] |
opcheese/CORD-19-ANN | [
"6d03ab4d2420d4766a15f4bfc320ba89fa42c6a5"
] | [
"cord_ann/clusters.py"
] | [
"from sklearn.cluster import KMeans\n\n\ndef cluster_embeddings(embeddings, sentences, num_clusters):\n clustering_model = KMeans(n_clusters=num_clusters)\n clustering_model.fit(embeddings)\n cluster_assignment = clustering_model.labels_\n\n clustered_sentences = [[] for i in range(num_clusters)]\n f... | [
[
"sklearn.cluster.KMeans"
]
] |
aiporre/quick-start-pytorch | [
"1944756f041ccc2cef8d282da8471df0a284594b"
] | [
"tutorials/02-intermediate/bidirectional_recurrent_neural_network/main.py"
] | [
"import torch\nimport torch.nn as nn\nimport torchvision\nimport torchvision.transforms as transforms\n\n\n# Device configuration\ndevice = torch.device('cuda' if torch.cuda.is_available() else 'cpu')\n\n# Hyper-parameters\nsequence_length = 28\ninput_size = 28\nhidden_size = 128\nnum_layers = 2\nnum_classes = 10\n... | [
[
"torch.nn.Linear",
"torch.nn.LSTM",
"torch.max",
"torch.no_grad",
"torch.cuda.is_available",
"torch.utils.data.DataLoader",
"torch.nn.CrossEntropyLoss"
]
] |
chris3edwards3/Multiple_Resolution_Analysis | [
"bcfd20602167e77b2f178e7e1d28b94d8b33403a"
] | [
"Resolution_Analysis-Era-Interim/Qout_erai_to_PandasDF.py"
] | [
"import numpy as np\nimport pandas as pd\nimport hydrostats.data as hd\nimport hydrostats.visual as hv\nimport HydroErr as he\nimport matplotlib.pyplot as plt\nimport os\nfrom netCDF4 import Dataset\n\n# Put all the directories (different states and resolutions) and corresponding NetCDF files into lists.\nlist_of_f... | [
[
"pandas.to_datetime",
"pandas.DataFrame"
]
] |
microsoft/building-damage-assessment-cnn-siamese | [
"6e46a74dc0f3113e496b3fc7d4448dfb0788a99f"
] | [
"train/utils/dataset_shard_load.py"
] | [
"# Copyright (c) Microsoft Corporation. All rights reserved.\n# Licensed under the MIT License.\nimport logging\nfrom PIL import Image\nimport cv2\nimport numpy as np\nimport torch\nfrom torch.utils.data import Dataset\nimport torchvision.transforms.functional as TF\nfrom torchvision import transforms\nimport rando... | [
[
"numpy.where",
"numpy.array",
"numpy.load",
"torch.from_numpy"
]
] |
dunithd/edu-samples | [
"c00c44e5e72bedc5cc343a6895eb5307a2476bc1"
] | [
"mz-funnel-chart-plotly/dash/app.py"
] | [
"import psycopg2\nimport pandas.io.sql as sqlio\nimport pandas as pd\nimport dash\nfrom dash import dcc\nfrom dash import html\nimport plotly.express as px\n\napp = dash.Dash(__name__)\n\n# Connect to Materialize as a regular database\nconn = psycopg2.connect(\"dbname=materialize user=materialize port=6875 host=loc... | [
[
"pandas.read_sql_query"
]
] |
rahulk29/spinningup | [
"e5dbcead0d0cf9b2ab086d47add13f4944dc28cc"
] | [
"spinup/exercises/problem_set_2/exercise2_3.py"
] | [
"import numpy as np\nimport tensorflow as tf\nimport gym\nimport time\nfrom spinup.algos.td3 import core\nfrom spinup.algos.td3.td3_randtarg import ReplayBuffer\nfrom spinup.algos.td3.core import get_vars\nfrom spinup.utils.logx import EpochLogger\nfrom spinup.utils.run_utils import ExperimentGrid\n\n\n\"\"\"\n\nEx... | [
[
"tensorflow.set_random_seed",
"tensorflow.shape",
"tensorflow.minimum",
"tensorflow.train.AdamOptimizer",
"tensorflow.assign",
"numpy.random.seed",
"tensorflow.Session",
"numpy.random.randn",
"tensorflow.global_variables_initializer",
"tensorflow.variable_scope",
"tenso... |
tcrasset/tslearn | [
"75cd661faaeef62d899d26a26d027defc1ffae04"
] | [
"tslearn/docs/examples/classification/plot_shapelets.py"
] | [
"# -*- coding: utf-8 -*-\n\"\"\"\nLearning Shapelets\n==================\n\nThis example illustrates how the \"Learning Shapelets\" method can quickly\nfind a set of shapelets that results in excellent predictive performance\nwhen used for a shapelet transform.\n\nMore information on the method can be found at:\nht... | [
[
"numpy.random.seed",
"matplotlib.pyplot.xlabel",
"tensorflow.optimizers.Adam",
"matplotlib.pyplot.title",
"matplotlib.pyplot.figure",
"sklearn.metrics.accuracy_score",
"numpy.arange",
"matplotlib.pyplot.tight_layout",
"matplotlib.pyplot.show"
]
] |
marvinlenk/subsystem_entropy_epsplots | [
"77de6a8e6c196abf745cc15c4f05fd0c177bd54b"
] | [
"pyplot_eps/en_eps.py"
] | [
"import numpy as np\nimport os\nfrom mpEntropy import mpSystem\nimport matplotlib as mpl\nfrom matplotlib.pyplot import cm\nimport matplotlib.pyplot as plt\nfrom scipy.signal import savgol_filter\n# This is a workaround until scipy fixes the issue\nimport warnings\n\nwarnings.filterwarnings(action=\"ignore\", modul... | [
[
"numpy.min",
"matplotlib.pyplot.bar",
"numpy.max",
"matplotlib.pyplot.savefig",
"matplotlib.pyplot.subplots",
"numpy.argmax",
"matplotlib.pyplot.tight_layout",
"numpy.sqrt",
"numpy.log10",
"matplotlib.pyplot.axes",
"matplotlib.use",
"matplotlib.pyplot.rcParams.updat... |
tovrstra/numpy | [
"bb5d666e84e2eb294543a67c6143d7e9124d1c73"
] | [
"numpy/lib/tests/test__iotools.py"
] | [
"from __future__ import division, absolute_import, print_function\n\nimport sys\nimport time\nfrom datetime import date\n\nimport numpy as np\nfrom numpy.testing import (\n run_module_suite, assert_, assert_equal, assert_allclose, assert_raises,\n )\nfrom numpy.lib._iotools import (\n LineSplitter, NameVal... | [
[
"numpy.lib._iotools.NameValidator",
"numpy.testing.run_module_suite",
"numpy.lib._iotools.flatten_dtype",
"numpy.lib._iotools.LineSplitter",
"numpy.testing.assert_equal",
"numpy.lib._iotools.StringConverter",
"numpy.lib._iotools.easy_dtype",
"numpy.lib._iotools.has_nested_fields",
... |
kgullikson88/Starfish | [
"965bbf2069854dfd92d795d3f902b6dae74537f9"
] | [
"Starfish/grid_tools.py"
] | [
"import numpy as np\nfrom numpy.fft import fft, ifft, fftfreq, rfftfreq\nfrom astropy.io import ascii,fits\nfrom scipy.interpolate import InterpolatedUnivariateSpline, interp1d\nfrom scipy.integrate import trapz\nfrom scipy.special import j1\nimport multiprocessing as mp\n\nimport sys\nimport gc\nimport os\nimport ... | [
[
"numpy.ones_like",
"numpy.median",
"scipy.integrate.trapz",
"numpy.load",
"numpy.exp",
"numpy.min",
"numpy.fft.irfft",
"numpy.max",
"scipy.interpolate.InterpolatedUnivariateSpline",
"numpy.prod",
"numpy.arange",
"numpy.array",
"numpy.floor",
"numpy.ceil",
... |
LiangjunFeng/Generative-Any-Shot-Learning | [
"693c4ab92f2eb04cc453c870782710a982f98e80"
] | [
"Model&Data/f-VAEGAN-D2/util_fewshot.py"
] | [
"#import h5py\nimport numpy as np\nimport scipy.io as sio\nimport torch\nfrom sklearn import preprocessing\nimport sys\nimport h5py\n\ndef weights_init(m):\n classname = m.__class__.__name__\n if classname.find('Linear') != -1:\n m.weight.data.normal_(0.0, 0.02)\n m.bias.data.fill_(0)\n elif ... | [
[
"numpy.delete",
"numpy.array",
"sklearn.preprocessing.StandardScaler",
"scipy.io.loadmat",
"torch.randperm",
"torch.from_numpy",
"numpy.where",
"numpy.ravel",
"sklearn.preprocessing.MinMaxScaler",
"numpy.repeat"
]
] |
sysbio-curie/scikit-dimension | [
"525273c936c43ae48d91700a260496434bc12d87"
] | [
"skdim/_commonfuncs.py"
] | [
"#\n# BSD 3-Clause License\n#\n# Copyright (c) 2020, Jonathan Bac\n# All rights reserved.\n#\n# Redistribution and use in source and binary forms, with or without\n# modification, are permitted provided that the following conditions are met:\n#\n# 1. Redistributions of source code must retain the above copyright no... | [
[
"numpy.array",
"scipy.special.gammainc",
"numpy.sum",
"numpy.random.default_rng",
"numpy.multiply",
"numpy.where",
"numpy.arange",
"numpy.sqrt",
"numpy.repeat",
"numpy.hstack",
"sklearn.neighbors.NearestNeighbors",
"sklearn.utils.validation.check_random_state"
]
] |
gitter-lab/pria-ams-enamine | [
"b37bc7edf3c21af6653267ecd4bb9fd232eeb575"
] | [
"output/get_table.py"
] | [
"from __future__ import print_function\n\nimport matplotlib\nfrom matplotlib import pyplot as plt\nplt.switch_backend('agg')\nimport os\nimport json\nimport numpy as np\n\n\n\ndef extract(file_path):\n if not os.path.isfile(file_path):\n return -1, -1, -1\n\n with open(file_path, 'r') as f:\n li... | [
[
"matplotlib.pyplot.switch_backend"
]
] |
pjuda/geone | [
"5a9e5d99702cdccb11ab825ea9b4caa90f3ba111"
] | [
"geone/img.py"
] | [
"#!/usr/bin/python3\n#-*- coding: utf-8 -*-\n\n\"\"\"\nPython module: 'img.py'\nauthor: Julien Straubhaar\ndate: jan-2018\n\nDefinition of classes for images and point sets (gslib), and relative\nfunctions.\n\"\"\"\n\nimport os\nimport numpy as np\n\n# ============================================... | [
[
"numpy.random.choice",
"numpy.minimum",
"numpy.min",
"numpy.mean",
"numpy.where",
"numpy.max",
"numpy.log",
"numpy.putmask",
"numpy.divmod",
"numpy.arange",
"numpy.array",
"numpy.zeros",
"numpy.loadtxt",
"numpy.floor",
"numpy.isnan",
"numpy.asarray",... |
utilForever/BabaIsAuto | [
"fb444668914eb70c0a35197399d650d293b4b95f"
] | [
"Extensions/BabaRL/baba-volcano-v0/REINFORCE.py"
] | [
"import torch\nfrom torch import nn, optim\nimport torch.nn.functional as F\nfrom torch.distributions import Categorical\n\nimport copy\n\nimport gym\nimport environment # lgtm[py/unused-import]\nimport pyBaba\n\nfrom tensorboardX import SummaryWriter\n\ndevice = torch.device(\"cuda\" if torch.cuda.is_available() ... | [
[
"torch.nn.Linear",
"torch.cat",
"torch.distributions.Categorical",
"torch.nn.Conv2d",
"torch.cuda.is_available",
"torch.tensor",
"torch.nn.functional.softmax"
]
] |
urutau-nz/inequipy | [
"01ad29a1b568d737c1ee2a9703db515a5b142043"
] | [
"inequalipy/atkinson.py"
] | [
"import numpy as np\n\ndef ede(a, epsilon = 0.5, weights = None):\n \"\"\"\n Compute the Atkinson Equally-Distributed Equivalent.\n The Atkinson EDE and Index are only suitable for distributions of desirable\n quantities (where having more of the quantity is desirable), e.g., income.\n\n Parameters\n... | [
[
"numpy.average"
]
] |
hz658832/radar_depth | [
"502b8614b833e3e1982d1a71988a00aa86df454d"
] | [
"misc/devkit/python/read_depth.py"
] | [
"#!/usr/bin/python\n\nfrom PIL import Image\nimport numpy as np\n\n\ndef depth_read(filename):\n # loads depth map D from png file\n # and returns it as a numpy array,\n # for details see readme.txt\n\n depth_png = np.array(Image.open(filename), dtype=int)\n # make sure we have a proper 16bit depth m... | [
[
"numpy.max"
]
] |
langmore/statsmodels | [
"a29d0418436a9b38b11101f7741ce6cb35b9e2cd"
] | [
"statsmodels/tools/tools.py"
] | [
"'''\nUtility functions models code\n'''\n\nimport numpy as np\nimport numpy.lib.recfunctions as nprf\nimport numpy.linalg as L\nfrom scipy.interpolate import interp1d\nfrom scipy.linalg import svdvals\nfrom statsmodels.distributions import (ECDF, monotone_fn_inverter,\n ... | [
[
"numpy.ones_like",
"numpy.dot",
"numpy.where",
"scipy.linalg.svdvals",
"numpy.add.reduce",
"numpy.nan_to_num",
"pandas.DataFrame",
"numpy.transpose",
"numpy.greater",
"numpy.column_stack",
"numpy.vstack",
"numpy.flatnonzero",
"numpy.equal",
"numpy.array",
... |
acald-creator/pytorch | [
"0be9df4e852c0216a1de749551f16affddb63335",
"0be9df4e852c0216a1de749551f16affddb63335"
] | [
"torch/package/package_importer.py",
"torch/_torch_docs.py"
] | [
"import builtins\nimport importlib\nimport inspect\nimport io\nimport linecache\nimport os.path\nimport types\nfrom contextlib import contextmanager\nfrom pathlib import Path\nfrom typing import Any, BinaryIO, Callable, cast, Dict, List, Optional, Union\nfrom weakref import WeakValueDictionary\n\nimport torch\nfrom... | [
[
"torch._C._log_api_usage_once",
"torch.serialization._get_restore_location",
"torch._C.PyTorchFileReader",
"torch._utils._validate_loaded_sparse_tensors",
"torch.serialization._maybe_decode_ascii",
"torch._C.DeserializationStorageContext"
],
[
"torch._C._add_docstr"
]
] |
douglasdavis/twaml | [
"932e2cc40a94c93eae43f2cd3b74f2c24eead185"
] | [
"tests/test_data.py"
] | [
"import os\nimport pandas as pd\nimport numpy as np\nimport uproot\nimport h5py\nfrom twaml.data import dataset\nfrom twaml.data import scale_weight_sum\nfrom twaml.data import from_root, from_pytables, from_h5\n\nbranches = [\"pT_lep1\", \"pT_lep2\", \"eta_lep1\", \"eta_lep2\"]\nds = from_root(\n [\"tests/data/... | [
[
"numpy.concatenate",
"numpy.histogram",
"numpy.testing.assert_allclose",
"numpy.ones_like",
"numpy.testing.assert_array_equal",
"numpy.logical_and",
"numpy.testing.assert_array_almost_equal",
"numpy.allclose",
"pandas.concat",
"numpy.linspace"
]
] |
llefebure/dynamic_bernoulli_embeddings | [
"2eaf28794d059e966c50a3e4d79c56d6a1e46284"
] | [
"dynamic_bernoulli_embeddings/embeddings.py"
] | [
"\"\"\"Contains embedding model implementation\"\"\"\nimport numpy as np\nimport torch\nimport torch.nn as nn\nfrom torch.distributions.categorical import Categorical\n\n\nclass DynamicBernoulliEmbeddingModel(nn.Module):\n def __init__(\n self,\n V,\n T,\n m_t,\n dictionary,\n ... | [
[
"torch.Size",
"torch.nn.Sigmoid",
"torch.no_grad",
"torch.distributions.categorical.Categorical",
"torch.nn.init.normal_",
"torch.nn.LogSigmoid",
"torch.nn.Embedding"
]
] |
firebolt55439/ray | [
"215300b070628c06f0106906fc6c03bd70ebf140"
] | [
"python/ray/util/sgd/torch/examples/pytorch-lightning/mnist-ptl.py"
] | [
"import argparse\n\n# __import_begin__\nimport os\n\n# Pytorch imports\nimport torch\nfrom torch.optim import Adam\nfrom torch.utils.data import DataLoader, random_split\nfrom torch.nn import functional as F\nfrom torchvision import transforms\nfrom torchvision.datasets import MNIST\n\n# Ray imports\nfrom ray.util.... | [
[
"torch.nn.Linear",
"torch.relu",
"torch.log_softmax",
"torch.max",
"torch.utils.data.random_split",
"torch.utils.data.DataLoader",
"torch.nn.functional.nll_loss"
]
] |
pupster90/indra | [
"e90b0bc1016fc2d210a9b46fb160b78a7d6a5ab9"
] | [
"indra/resources/update_resources.py"
] | [
"from __future__ import absolute_import, print_function, unicode_literals\nfrom builtins import dict, str\nimport os\nimport gzip\nimport pandas\nimport rdflib\nfrom indra.util import read_unicode_csv, write_unicode_csv\n\ntry:\n from urllib import urlretrieve\nexcept ImportError:\n from urllib.request import... | [
[
"pandas.DataFrame.from_dict",
"pandas.read_csv",
"pandas.DataFrame.from_csv",
"pandas.concat"
]
] |
The-MinGo/federated-learning-demo | [
"32f006dfc01df8b4b9f9d89814feae7d54746e3a"
] | [
"fed_exchange_weight_bias/utils/Model.py"
] | [
"import tensorflow as tf\nimport tensorflow.keras as keras\n\n\ndef alexnet(input_shape, classes_num=100):\n \"\"\"\n AlexNet:\n Described in: http://arxiv.org/pdf/1404.5997v2.pdf\n Parameters from:\n github.com/akrizhevsky/cuda-convnet2/blob/master/layers/\n \"\"\"\n # Creating initializer, op... | [
[
"tensorflow.keras.layers.Flatten",
"tensorflow.keras.applications.vgg16.VGG16",
"tensorflow.keras.models.Model",
"tensorflow.keras.layers.Dense",
"tensorflow.keras.layers.Conv2D",
"tensorflow.keras.initializers.RandomNormal",
"tensorflow.keras.layers.MaxPooling2D",
"tensorflow.kera... |
gnomonsis/open_model_zoo | [
"72dbeb263cab19e7e232793246521e96f3821959",
"72dbeb263cab19e7e232793246521e96f3821959"
] | [
"tools/accuracy_checker/accuracy_checker/preprocessor/color_space_conversion.py",
"demos/python_demos/action_recognition/action_recognition_demo/result_renderer.py"
] | [
"\"\"\"\nCopyright (c) 2019 Intel Corporation\n\nLicensed under the Apache License, Version 2.0 (the \"License\");\nyou may not use this file except in compliance with the License.\nYou may obtain a copy of the License at\n\n http://www.apache.org/licenses/LICENSE-2.0\n\nUnless required by applicable law or ag... | [
[
"tensorflow.enable_eager_execution",
"numpy.expand_dims"
],
[
"numpy.asarray",
"numpy.argsort"
]
] |
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