repo_name stringlengths 6 130 | hexsha list | file_path list | code list | apis list |
|---|---|---|---|---|
calebrob6/pytorch-lightning | [
"4c79b3a5b343866217784c66d122819c59a92c1d",
"4c79b3a5b343866217784c66d122819c59a92c1d"
] | [
"tests/callbacks/test_lr_monitor.py",
"pl_examples/basic_examples/profiler_example.py"
] | [
"# Copyright The PyTorch Lightning team.\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 applicable law... | [
[
"torch.nn.Linear",
"torch.optim.lr_scheduler.OneCycleLR",
"torch.optim.lr_scheduler.StepLR",
"torch.optim.Adam",
"torch.optim.SGD",
"torch.nn.ReLU"
],
[
"torch.cuda.is_available",
"torch.nn.CrossEntropyLoss",
"torch.utils.data.DataLoader"
]
] |
Haidy-sayed/SBME-3rd-year-DSP-Tasks | [
"938d4b64d2debf2fcd0387796aa530d8c25c0777"
] | [
"DSP_Task1/newestUpdate2.py"
] | [
"\n# -*- coding: utf-8 -*-\n\n# Form implementation generated from reading ui file 'GUIgodhelpus.ui'\n#\n# Created by: PyQt5 UI code generator 5.9.2\n#\n# WARNING! All changes made in this file will be lost!\n\nfrom pyqtgraph import PlotWidget\nimport pyqtgraph \nfrom PyQt5 import QtCore, QtGui, QtWidgets\n#from ma... | [
[
"numpy.rot90",
"matplotlib.pyplot.figure",
"matplotlib.pyplot.specgram",
"matplotlib.figure.Figure",
"pandas.read_csv",
"pandas.to_numeric"
]
] |
LauraCollard/pandas | [
"4071dde86e33434e1bee8304fa62074949f813cc",
"b1c3a9031569334cafc4e8d45d35408421f7dea4",
"b1c3a9031569334cafc4e8d45d35408421f7dea4",
"b1c3a9031569334cafc4e8d45d35408421f7dea4",
"b1c3a9031569334cafc4e8d45d35408421f7dea4",
"4071dde86e33434e1bee8304fa62074949f813cc",
"b1c3a9031569334cafc4e8d45d35408421f7dea... | [
"pandas/tests/indexes/period/test_scalar_compat.py",
"pandas/tests/tseries/holiday/test_calendar.py",
"pandas/tests/io/excel/test_openpyxl.py",
"pandas/tests/io/msgpack/test_sequnpack.py",
"pandas/tests/frame/test_apply.py",
"pandas/tests/tslibs/test_timezones.py",
"pandas/tests/io/msgpack/test_obj.py"
... | [
"\"\"\"Tests for PeriodIndex behaving like a vectorized Period scalar\"\"\"\n\nfrom pandas import Timedelta, date_range, period_range\nimport pandas.util.testing as tm\n\n\nclass TestPeriodIndexOps:\n def test_start_time(self):\n index = period_range(freq=\"M\", start=\"2016-01-01\", end=\"2016-05-31\")\n... | [
[
"pandas.period_range",
"pandas.util.testing.assert_index_equal",
"pandas.date_range",
"pandas.Timedelta"
],
[
"pandas.tseries.holiday.Holiday",
"pandas.DatetimeIndex",
"pandas.util.testing.assert_index_equal",
"pandas.tseries.holiday.USFederalHolidayCalendar",
"pandas.tseri... |
saurbhc/ivy | [
"20b327b4fab543b26ad5a18acf4deddd6e3c804b",
"20b327b4fab543b26ad5a18acf4deddd6e3c804b"
] | [
"ivy_tests/test_ivy/helpers.py",
"ivy/functional/backends/torch/device.py"
] | [
"\"\"\"\nCollection of helpers for ivy unit tests\n\"\"\"\n\n# global\nimport ivy\ntry:\n import numpy as _np\nexcept ImportError:\n _np = None\ntry:\n import jax.numpy as _jnp\nexcept ImportError:\n _jnp = None\ntry:\n import tensorflow as _tf\n _tf_version = float('.'.join(_tf.__version__.split(... | [
[
"tensorflow.config.list_physical_devices",
"tensorflow.__version__.split",
"tensorflow.config.experimental.set_memory_growth"
],
[
"torch.cuda.empty_cache",
"torch.profiler.profile",
"torch.nn.Parameter"
]
] |
QiuWJX/cvxpy | [
"a43aed7447b87f6d0fbc6f71ae5c7b84183f3369",
"fd1c225b0cdf541618e292cae1a4c7ea25ddc934"
] | [
"cvxpy/reductions/solvers/qp_solvers/cplex_qpif.py",
"setup.py"
] | [
"import numpy as np\n\nimport cvxpy.interface as intf\nimport cvxpy.settings as s\nfrom cvxpy.reductions.solution import Solution, failure_solution\nfrom cvxpy.reductions.solvers.conic_solvers.cplex_conif import (\n get_status, hide_solver_output, set_parameters,)\nfrom cvxpy.reductions.solvers.qp_solvers.qp_sol... | [
[
"numpy.array",
"numpy.ones"
],
[
"numpy.get_include"
]
] |
Sheldoer/plm-nlp-code | [
"04127d137c8bd40bc1412bee863640b9d909ddf9"
] | [
"chp7/finetune_bert_spc.py"
] | [
"# Defined in Section 7.4.3.2\n\nimport numpy as np\nfrom datasets import load_dataset, load_metric\nfrom transformers import BertTokenizerFast, BertForSequenceClassification, TrainingArguments, Trainer\n\n# 加载训练数据、分词器、预训练模型以及评价方法\ndataset = load_dataset('glue', 'rte')\ntokenizer = BertTokenizerFast.from_pretrained... | [
[
"numpy.argmax"
]
] |
noah-ziethen/py-pde | [
"b88e86439290c31284a4ac665a8e9ff34d08b494"
] | [
"pde/trackers/trackers.py"
] | [
"\"\"\"\nModule defining classes for tracking results from simulations.\n\nThe trackers defined in this module are:\n\n.. autosummary::\n :nosignatures:\n\n CallbackTracker\n ProgressTracker\n PrintTracker\n PlotTracker\n DataTracker\n SteadyStateTracker\n RuntimeTracker\n ConsistencyTracker\n M... | [
[
"numpy.array",
"numpy.isclose",
"pandas.DataFrame",
"numpy.allclose",
"numpy.isfinite",
"numpy.all",
"numpy.flatnonzero"
]
] |
catskillsresearch/openasr20 | [
"b9821c4ee6a51501e81103c1d6d4db0ea8aaa31e"
] | [
"initialize_weights.py"
] | [
"import torch.nn as nn\n\ndef initialize_weights(m):\n if hasattr(m, 'weight') and m.weight.dim() > 1:\n nn.init.xavier_uniform_(m.weight.data)\n"
] | [
[
"torch.nn.init.xavier_uniform_"
]
] |
irenetrampoline/clustering-interval-censored | [
"f6ab06a6cf3098ffe006d1b95d1b4f1d158b0bc4"
] | [
"model/models.py"
] | [
"import logging\nimport numpy as np\nimport torch\nimport torch.nn as nn\nimport torch.nn.functional as F\n\n# torch.manual_seed(0)\n# torch.backends.cudnn.deterministic = True\n# torch.backends.cudnn.benchmark = False\n\n\nfrom pyro.distributions import MultivariateNormal, Normal, Independent\n\nfrom sklearn.clust... | [
[
"torch.nn.Linear",
"torch.cat",
"torch.stack",
"torch.ones",
"torch.squeeze",
"torch.cuda.is_available",
"torch.nn.utils.rnn.pack_padded_sequence",
"torch.load",
"torch.nn.RNN",
"torch.sum",
"matplotlib.pylab.rcParams.update",
"numpy.log",
"torch.manual_seed",
... |
shenjl/asimo | [
"6aad2c89bb5eb3ca59c85521934fe854d1a0e0e6"
] | [
"other/DaSiamRPN/code/run_SiamRPN.py"
] | [
"# --------------------------------------------------------\n# DaSiamRPN\n# Licensed under The MIT License\n# Written by Qiang Wang (wangqiang2015 at ia.ac.cn)\n# --------------------------------------------------------\nimport numpy as np\nfrom torch.autograd import Variable\nimport torch.nn.functional as F\n\n\nf... | [
[
"numpy.array",
"numpy.zeros",
"numpy.hanning",
"numpy.ones",
"numpy.tile",
"numpy.exp",
"numpy.mean",
"numpy.argmax",
"numpy.sqrt",
"numpy.maximum"
]
] |
reidac/covid19-curve-your-county | [
"ab3ec4e6f3249844cda35fbceff3676976a5c914",
"ab3ec4e6f3249844cda35fbceff3676976a5c914"
] | [
"cases.py",
"bars.py"
] | [
"import matplotlib.pyplot as plt\nimport numpy as np\nimport os\n\nimport get_dc_data\n\n# Cumulative figure.\n\ncasedata = get_dc_data.retrieve(download=False)\n\nf2 = plt.figure(figsize=(6,4))\nplt.suptitle(\"COVID-19 Data Summary, District of Columbia \",\n fontweight=\"bold\")\nplt.title(\"github.co... | [
[
"matplotlib.pyplot.xlabel",
"matplotlib.pyplot.suptitle",
"matplotlib.pyplot.title",
"matplotlib.pyplot.legend",
"matplotlib.pyplot.figure",
"matplotlib.pyplot.ylabel",
"matplotlib.pyplot.bar"
],
[
"matplotlib.pyplot.xlabel",
"matplotlib.pyplot.suptitle",
"matplotlib.py... |
yuan-feng/meshio | [
"a58b9080e5b288320df2bee1bf4d03097184f3d2",
"a58b9080e5b288320df2bee1bf4d03097184f3d2"
] | [
"meshio/_vtk.py",
"meshio/_stl.py"
] | [
"\"\"\"\nI/O for VTK <https://www.vtk.org/wp-content/uploads/2015/04/file-formats.pdf>.\n\"\"\"\nimport logging\nfrom functools import reduce\n\nimport numpy\n\nfrom .__about__ import __version__\nfrom ._common import raw_from_cell_data\nfrom ._exceptions import ReadError, WriteError\nfrom ._files import open_file\... | [
[
"numpy.full",
"numpy.pad",
"numpy.empty",
"numpy.reshape",
"numpy.where",
"numpy.prod",
"numpy.arange",
"numpy.vstack",
"numpy.fromfile",
"numpy.cumsum",
"numpy.all",
"numpy.linspace",
"numpy.dtype",
"numpy.unique"
],
[
"numpy.concatenate",
"nump... |
ashishpatel26/sktime | [
"63e7839e80ca6d5fe5fc4f33389ec3bcacd8aa59"
] | [
"sktime/transformers/dictionary_based/SAX.py"
] | [
"import sys\n\nimport numpy as np\nimport pandas as pd\nimport sktime.transformers.shapelets as shapelets\nfrom sktime.transformers.dictionary_based.PAA import PAA\nfrom sktime.utils.load_data import load_from_tsfile_to_dataframe as load_ts\nfrom sktime.transformers.base import BaseTransformer\n# TO DO: verify t... | [
[
"pandas.DataFrame",
"numpy.arange",
"numpy.asarray",
"pandas.Series"
]
] |
AdarshSai/Final_project | [
"f966834ca72dd232102ed500ef47ef2b3bdbed5b",
"f966834ca72dd232102ed500ef47ef2b3bdbed5b",
"f966834ca72dd232102ed500ef47ef2b3bdbed5b"
] | [
"venv/Lib/site-packages/numpy/core/tests/test__exceptions.py",
"venv/Lib/site-packages/mpl_toolkits/mplot3d/axis3d.py",
"venv/Lib/site-packages/matplotlib/bezier.py"
] | [
"\"\"\"\r\nTests of the ._exceptions module. Primarily for exercising the __str__ methods.\r\n\"\"\"\r\nimport numpy as np\r\n\r\n_ArrayMemoryError = np.core._exceptions._ArrayMemoryError\r\n\r\nclass TestArrayMemoryError:\r\n def test_str(self):\r\n e = _ArrayMemoryError((1023,), np.dtype(np.uint8))\r\n ... | [
[
"numpy.dtype"
],
[
"matplotlib.lines.Line2D",
"numpy.array",
"numpy.count_nonzero",
"numpy.asarray",
"matplotlib.transforms.Bbox.union",
"numpy.where",
"matplotlib.transforms._interval_contains_close",
"numpy.stack",
"matplotlib.axis._make_getset_interval",
"numpy.c... |
jrrr/emr-semantic-representations | [
"361330f16ce4aaba47641216af49886cc1c45623"
] | [
"model.py"
] | [
"#!/usr/bin/env python\n\nimport sys, os, pickle\nimport pandas as pd\nimport numpy as np\nfrom sklearn import linear_model, ensemble, metrics, impute, preprocessing\n\ndef load_listfile(path):\n names = []\n labels = []\n with open(path, 'r') as f:\n f.readline() # first line is header\n for... | [
[
"sklearn.impute.SimpleImputer",
"sklearn.metrics.confusion_matrix",
"sklearn.preprocessing.StandardScaler",
"pandas.DataFrame",
"sklearn.metrics.accuracy_score",
"sklearn.metrics.classification_report",
"sklearn.linear_model.LogisticRegression",
"sklearn.metrics.recall_score",
... |
htrenquier/ml-attribute-based-testing | [
"838ac29829b5fdd23cdac6413843c764c5934dce"
] | [
"src/analyse.py"
] | [
"from __future__ import division\nimport numpy as np\nfrom sklearn import metrics as sk_metrics\nimport metrics\nimport metrics_color\nimport plotting\nimport model_trainer as mt\nimport data_tools as dt\nimport tests_logging as t_log\nimport initialise\nimport bdd100k_utils as bu\nimport cv2\nimport os.path\nimpor... | [
[
"numpy.quantile",
"sklearn.metrics.confusion_matrix",
"numpy.array",
"numpy.empty",
"numpy.zeros",
"numpy.median",
"numpy.mean",
"numpy.swapaxes",
"numpy.argmax",
"numpy.argsort"
]
] |
leilimaster/DmifNet | [
"cad50bb7a3762745f72b2498c2eef5ad5b21e4c6"
] | [
"dmifnet/psgn/training.py"
] | [
"import os\nfrom tqdm import trange\nimport torch\nfrom dmifnet.common import chamfer_distance\nfrom dmifnet.training import BaseTrainer\nfrom dmifnet.utils import visualize as vis\n\n\nclass Trainer(BaseTrainer):\n r''' Trainer object for the Point Set Generation Network.\n\n The PSGN network is trained on C... | [
[
"torch.no_grad"
]
] |
liuqiuxi/datafeeds | [
"50d1615a96f7d17d3ecd8ab661c4e1d5f43b9e8d"
] | [
"datafeeds/jqdatafeeds/stockfeedsjqdata.py"
] | [
"# -*- coding:utf-8 -*-\r\n# @Time : 2019-12-27 15:48\r\n# @Author : liuqiuxi\r\n# @Email : liuqiuxi1990@gmail.com\r\n# @File : stockfeedsjqdata.py\r\n# @Project : datafeeds\r\n# @Software: PyCharm\r\n# @Remark : This is class of stock market\r\n\r\nimport datetime\r\nimport pandas as pd\r\nimport numpy a... | [
[
"pandas.DataFrame",
"pandas.merge",
"pandas.concat"
]
] |
redis-developer/crowsnest | [
"c38d59d6b332b9232f0fae9ce5abc2449d836372"
] | [
"local_backend/server.py"
] | [
"# RedisEdge realtime video analytics web server\nimport argparse\nimport cv2\nimport io\nimport numpy as np\nimport redis\nfrom urllib.parse import urlparse\nfrom PIL import Image, ImageDraw\nfrom flask import Flask, render_template, Response, request\nfrom flask_cors import CORS, cross_origin\nimport capture\n#im... | [
[
"numpy.array"
]
] |
RTHMaK/sklearn-onnx | [
"dbbd4a04f0a395549b1e5465c5d65ceaef07a726",
"dbbd4a04f0a395549b1e5465c5d65ceaef07a726",
"dbbd4a04f0a395549b1e5465c5d65ceaef07a726"
] | [
"tests/test_sklearn_glm_regressor_converter.py",
"skl2onnx/operator_converters/stacking.py",
"skl2onnx/operator_converters/bagging.py"
] | [
"\"\"\"Tests GLMRegressor converter.\"\"\"\n\nimport unittest\nfrom distutils.version import StrictVersion\nimport numpy\nfrom sklearn import linear_model\nfrom sklearn.ensemble import GradientBoostingRegressor\nfrom sklearn.neural_network import MLPRegressor\nfrom sklearn.svm import LinearSVR\nfrom skl2onnx import... | [
[
"sklearn.linear_model.ARDRegression",
"sklearn.linear_model.HuberRegressor",
"sklearn.linear_model.LinearRegression",
"sklearn.linear_model.BayesianRidge",
"sklearn.linear_model.PassiveAggressiveRegressor",
"sklearn.neural_network.MLPRegressor",
"sklearn.linear_model.MultiTaskElasticNe... |
johnolafenwa/DeepVision | [
"3b76fb6fcb6f6374c7faf1f8372e3f3091817505"
] | [
"basics/mnistspecificimage.py"
] | [
"#import needed classes\r\nimport keras\r\nfrom keras.datasets import mnist\r\nfrom keras.layers import Dense,Dropout\r\nfrom keras.models import Sequential\r\nfrom keras.optimizers import SGD\r\nimport matplotlib.pyplot as plt\r\n\r\n#load the mnist dataset\r\n(train_x, train_y) , (test_x, test_y) = mnist.load_dat... | [
[
"matplotlib.pyplot.show",
"matplotlib.pyplot.title",
"matplotlib.pyplot.imshow"
]
] |
joolsa/Binary-Classifier-for-Online-Hate-Detection-in-Multiple-Social-Media-Platforms | [
"a3ed3d40d16b04e451146688e78a3d3eed373ba5"
] | [
"functions.py"
] | [
"# Import packages and change some pandas display options\nimport pandas as pd\nimport numpy as np\nimport re\nimport warnings\nimport xgboost as xgb\nimport matplotlib.pyplot as plt\n\nfrom sklearn.metrics import auc, f1_score, roc_curve, roc_auc_score\n\n\ndef get_simple_features(data):\n \"\"\" Creates simple... | [
[
"matplotlib.pyplot.xlim",
"matplotlib.pyplot.xlabel",
"matplotlib.pyplot.ylim",
"matplotlib.pyplot.plot",
"matplotlib.pyplot.legend",
"matplotlib.pyplot.figure",
"matplotlib.pyplot.show",
"matplotlib.pyplot.ylabel",
"sklearn.metrics.auc",
"sklearn.metrics.f1_score",
"sk... |
20000607-lxc/BERT-NER-Pytorch-master | [
"47f2e1291ab53674986eb91abdb72693eafe9b61"
] | [
"run_ner_span.py"
] | [
"import argparse\nimport glob\nimport logging\nimport os\nimport json\nimport time\nimport torch\nfrom torch.nn import CrossEntropyLoss\nfrom torch.utils.data import DataLoader, RandomSampler, SequentialSampler, TensorDataset\nfrom torch.utils.data.distributed import DistributedSampler\nfrom callback.optimizater.ad... | [
[
"torch.device",
"torch.distributed.get_world_size",
"torch.utils.data.RandomSampler",
"torch.distributed.init_process_group",
"torch.no_grad",
"torch.utils.data.SequentialSampler",
"torch.save",
"torch.nn.parallel.DistributedDataParallel",
"torch.cuda.set_device",
"torch.cu... |
haoningwu3639/EE229_Project_VideoStabilization | [
"74603e9dc5f10b3deffb2f4e0753c15dc8b9a92d"
] | [
"src/superpoint.py"
] | [
"import numpy as np\nimport torch\n\n\nclass SuperPointNet(torch.nn.Module):\n \"\"\"\n SuperPoint Network\n Thanks to https://github.com/magicleap/SuperPointPretrainedNetwork\n \"\"\"\n\n def __init__(self):\n super(SuperPointNet, self).__init__()\n self.relu = torch.nn.ReLU(inplace=Tr... | [
[
"numpy.exp",
"numpy.where",
"torch.load",
"numpy.linalg.norm",
"torch.nn.MaxPool2d",
"torch.autograd.Variable",
"torch.norm",
"torch.unsqueeze",
"numpy.transpose",
"numpy.vstack",
"numpy.logical_or",
"numpy.pad",
"numpy.reshape",
"numpy.zeros",
"torch.nn... |
pbmstrk/BLINK | [
"7380cf7d63ff76563f017adc39fa5729ba36742a"
] | [
"blink/biencoder/biencoder.py"
] | [
"# Copyright (c) Facebook, Inc. and its affiliates.\n# All rights reserved.\n#\n# This source code is licensed under the license found in the\n# LICENSE file in the root directory of this source tree.\n#\nimport os\nimport numpy as np\nimport torch\nimport torch.nn as nn\nimport torch.nn.functional as F\nfrom tqdm ... | [
[
"torch.arange",
"torch.bmm",
"torch.cuda.device_count",
"torch.squeeze",
"torch.nn.functional.cross_entropy",
"torch.cuda.is_available",
"torch.load",
"torch.nn.BCEWithLogitsLoss",
"torch.nn.DataParallel"
]
] |
iandewancker/Urban_Driving_Simulator | [
"fff001cb7a58a3e4ef84415de6244e520af8ec55"
] | [
"fluids/state.py"
] | [
"import numpy as np\nimport json\nimport os\nfrom six import iteritems\nimport random\nimport pygame\nimport hashlib\n\nfrom fluids.consts import *\nfrom fluids.assets import *\nfrom fluids.utils import *\nfrom fluids.version import __version__\n\n\nbasedir = os.path.dirname(__file__)\n\nid_index = 0\ndef get_id():... | [
[
"numpy.sin",
"numpy.random.uniform",
"numpy.cos"
]
] |
thibsej/unbalanced-ot-functionals | [
"bfd098e98ed10b90a36e0dbe7b099c1c31770931"
] | [
"examples/plan_marginal.py"
] | [
"import os\n\nimport torch\nimport numpy as np\nimport matplotlib.pyplot as plt\n\nfrom unbalancedot.utils import euclidean_cost\nfrom unbalancedot.sinkhorn import BatchVanillaSinkhorn\nfrom unbalancedot.entropy import (\n KullbackLeibler,\n Balanced,\n TotalVariation,\n Range,\n PowerEntropy,\n)\n\n... | [
[
"numpy.concatenate",
"matplotlib.pyplot.savefig",
"numpy.sum",
"numpy.ones",
"matplotlib.pyplot.plot",
"matplotlib.pyplot.figure",
"torch.from_numpy",
"matplotlib.pyplot.fill_between",
"matplotlib.pyplot.tight_layout",
"numpy.abs",
"numpy.linspace"
]
] |
mbroso/constraintnet_foc | [
"c0c4e3674c6fde87d41118cef3cae8a3a5e22a17"
] | [
"utils.py"
] | [
"\"\"\"Utils. Containing several helper function and classes.\r\n\"\"\"\r\nimport numpy as np\r\nimport torch\r\nimport signal\r\nimport matplotlib\r\nimport matplotlib.pyplot as plt\r\nimport gym\r\n\r\nfrom AccFocEnv.plotter import Plotter\r\n\r\n# Allows to change training device.\r\ndevice = torch.device(\"cpu\... | [
[
"torch.device",
"numpy.zeros",
"numpy.random.seed",
"torch.FloatTensor",
"torch.manual_seed",
"numpy.random.randint"
]
] |
rogeriobonatti/mushr_rhc | [
"8316cad6544997c1742cc5f5b539f5886eb00e7f"
] | [
"mushr_rhc_ros/src/mingpt/model_resnetdirect.py"
] | [
"\"\"\"\nGPT model:\n- the initial stem consists of a combination of token encoding and a positional encoding\n- the meat of it is a uniform sequence of Transformer blocks\n - each Transformer is a sequential combination of a 1-hidden-layer MLP block and a self-attention block\n - all blocks feed into a centr... | [
[
"torch.nn.Linear",
"torch.cat",
"torch.nn.MSELoss",
"torch.nn.ReLU"
]
] |
machines-in-motion/dynamic_game_optimizer | [
"5849ae11918f68f346aa4a869d57fc8242162f5c"
] | [
"python/demos/linear_quadratic_partial.py"
] | [
"import os, sys, time\nfrom cv2 import solve\n\nsrc_path = os.path.abspath(\"../\")\nsys.path.append(src_path)\n\nimport numpy as np\nimport crocoddyl\nfrom models import lin_quad_action as lin_quad\nimport matplotlib.pyplot as plt\nfrom utils.measurements import FullStateMeasurement, MeasurementTrajectory\nfrom so... | [
[
"numpy.array",
"numpy.zeros",
"matplotlib.pyplot.xlabel",
"matplotlib.pyplot.title",
"matplotlib.pyplot.legend",
"matplotlib.pyplot.figure",
"numpy.eye",
"numpy.arange",
"matplotlib.pyplot.ylabel",
"matplotlib.pyplot.show"
]
] |
nlinc1905/evolutionary-reinforcement-learner | [
"a1384426d0d47403abd7382a0c6b6ebe7d949aff"
] | [
"tests/test_mlp.py"
] | [
"import numpy as np\nimport unittest\n\nfrom models.mlp import softmax, relu, MLP\n\n\ndef test_softmax():\n # Assert that the output matches what is expected for a given input\n test_array = np.array([[0.2, 0.4, 0.6], [0.4, 0.6, 0.8]])\n expected_output = np.array([\n [0.2693075, 0.32893292, 0.4017... | [
[
"numpy.testing.assert_allclose",
"numpy.array",
"numpy.zeros",
"numpy.testing.assert_equal",
"numpy.random.seed",
"numpy.random.randn"
]
] |
DockyD/DvM | [
"7fbc6aa33a88b288edab9948071849b02ac71469",
"7fbc6aa33a88b288edab9948071849b02ac71469"
] | [
"stats/nonparametric.py",
"projects/DistractorSuppressionBeh.py"
] | [
"\"\"\"\nNonParametric statistical tests\n\nCreated by Dirk van Moorselaar on 27-02-2018.\nCopyright (c) 2018 DvM. All rights reserved.\n\"\"\"\n\nimport cv2\n\nimport numpy as np\n\nfrom math import sqrt\nfrom scipy.stats import ttest_rel, ttest_ind, wilcoxon, ttest_1samp\nfrom IPython import embed \n\ndef permuta... | [
[
"numpy.random.choice",
"numpy.random.rand",
"numpy.copy",
"numpy.tile",
"numpy.mean",
"numpy.where",
"scipy.stats.ttest_1samp",
"numpy.uint8",
"numpy.empty",
"numpy.flipud",
"numpy.arange",
"numpy.random.randint",
"scipy.stats.ttest_rel",
"numpy.vstack",
... |
VirgiAgl/GPflow | [
"95e77a5f2fe1514a30f87b5ed03ad72bbce8dead"
] | [
"tests/test_kldiv.py"
] | [
"# Copyright 2017 the GPflow 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 applicable law or agr... | [
[
"tensorflow.convert_to_tensor",
"numpy.random.RandomState",
"tensorflow.diag",
"tensorflow.ones_like",
"tensorflow.reshape",
"numpy.eye",
"tensorflow.log",
"numpy.transpose",
"tensorflow.reduce_sum",
"tensorflow.test.main",
"tensorflow.square"
]
] |
hpgem/nanomesher | [
"06e7648ff8b9ecf4cc1faa967469db6270c0ba5d",
"06e7648ff8b9ecf4cc1faa967469db6270c0ba5d"
] | [
"nanomesh/image/_plane.py",
"nanomesh/mesh/_mixin.py"
] | [
"from __future__ import annotations\n\nimport logging\nfrom typing import TYPE_CHECKING, Union\n\nimport matplotlib.pyplot as plt\nimport numpy as np\n\nfrom .._doc import doc\nfrom ._image import Image\nfrom ._utils import show_image\n\nlogger = logging.getLogger(__name__)\n\nif TYPE_CHECKING:\n from .mesh impo... | [
[
"matplotlib.pyplot.subplots"
],
[
"numpy.abs"
]
] |
DavidWalz/diversipy | [
"bbc9b6b650529f7cb739cf981dddb3eaad2f2613"
] | [
"test/test_polytope.py"
] | [
"from diversipy import polytope\nimport numpy as np\nimport pytest\n\n\ndef test_constraints_from_bounds():\n A, b = polytope.constraints_from_bounds(lower=[1, 2], upper=[5, 6])\n np.testing.assert_almost_equal(A, [[-1, 0], [0, -1], [1, 0], [0, 1]])\n np.testing.assert_almost_equal(b, [-1, -2, 5, 6])\n\n\n... | [
[
"numpy.array",
"numpy.testing.assert_almost_equal",
"numpy.ones",
"numpy.allclose",
"numpy.random.uniform",
"numpy.all"
]
] |
angelorodem/tensorflow2-char-rnn | [
"f28503c61de62eade9b477bf13573988fb3807de"
] | [
"tf_lite_converter.py"
] | [
"import tensorflow as tf\n\nconverter = tf.lite.TFLiteConverter.from_saved_model('name_save/saved_model')\ntflite_model = converter.convert()\nopen(\"converted_model.tflite\", \"wb\").write(tflite_model)"
] | [
[
"tensorflow.lite.TFLiteConverter.from_saved_model"
]
] |
jackyq2015/incubator-superset | [
"ffa80c69771a784318e9b713ecf02399f0083556"
] | [
"superset/views/core.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... | [
[
"pandas.DataFrame.from_records"
]
] |
magnusja/scipy | [
"c4a5a1f984e28840010f20a7e41caa21b8f41979"
] | [
"scipy/signal/tests/test_signaltools.py"
] | [
"# -*- coding: utf-8 -*-\nfrom __future__ import division, print_function, absolute_import\n\nimport sys\n\nfrom decimal import Decimal\nfrom itertools import product\nimport warnings\n\nimport pytest\nfrom pytest import raises as assert_raises\nfrom numpy.testing import (\n assert_equal,\n assert_almost_equa... | [
[
"scipy.signal.wiener",
"scipy.signal.invres",
"numpy.random.rand",
"numpy.random.choice",
"numpy.tile",
"scipy.signal.lfilter",
"numpy.random.random",
"scipy.signal.correlate2d",
"scipy.signal.signaltools._filtfilt_gust",
"numpy.empty",
"numpy.log",
"scipy.signal.wi... |
IvoryCandy/generative-adversarial-networks | [
"4010a20b22ecb016da164b37d6f915788e8f09f5"
] | [
"GAN/model.py"
] | [
"import torch.nn as nn \nimport torch.nn.functional as func\n\n\ndef de_conv(in_channels, out_channels, kernel_size, stride=2, padding=1, bn=True):\n \"\"\"Custom de_convolutional layer for simplicity.\"\"\"\n layers = [nn.ConvTranspose2d(in_channels=in_channels, out_channels=out_channels,\n ... | [
[
"torch.nn.Sequential",
"torch.nn.Conv2d",
"torch.nn.ConvTranspose2d",
"torch.nn.BatchNorm2d"
]
] |
GaelVaroquaux/nilearn | [
"8e902704bbd186912e753cf08e90eb50f228915c"
] | [
"examples/connectivity/plot_multi_subject_connectome.py"
] | [
"\"\"\"\nGroup Sparse inverse covariance for multi-subject connectome\n=============================================================\n\nThis example shows how to estimate a connectome on a groupe of subjects\nusing the group sparse inverse covariance estimate.\n\n\"\"\"\nimport matplotlib.pyplot as plt\nimport nump... | [
[
"numpy.concatenate",
"matplotlib.pyplot.colorbar",
"matplotlib.pyplot.title",
"matplotlib.pyplot.figure",
"sklearn.externals.joblib.Memory",
"sklearn.covariance.GraphLassoCV",
"matplotlib.pyplot.imshow"
]
] |
ebolyen/scikit-bio | [
"04dff688aa67de871e7c4b1c47f459d0f701b4d2"
] | [
"skbio/stats/tests/test_power.py"
] | [
"# ----------------------------------------------------------------------------\n# Copyright (c) 2013--, scikit-bio development team.\n#\n# Distributed under the terms of the Modified BSD License.\n#\n# The full license is in the file COPYING.txt, distributed with this software.\n# ---------------------------------... | [
[
"numpy.testing.assert_allclose",
"numpy.array",
"numpy.zeros",
"numpy.random.seed",
"pandas.DataFrame.from_dict",
"numpy.testing.assert_array_equal",
"numpy.testing.assert_almost_equal",
"numpy.ones",
"scipy.stats.kruskal",
"numpy.arange",
"numpy.vstack"
]
] |
thomasrgray/blechpy | [
"46a95991e1d41556a263e48c9c3b61b1d337aae0"
] | [
"blechpy/plotting/data_plot.py"
] | [
"import pandas as pd\nimport numpy as np\nimport tables\nimport os\nimport umap\nimport pywt\nimport itertools as it\nfrom blechpy import dio\nfrom blechpy.analysis import spike_analysis as sas\nfrom scipy.stats import sem\nfrom scipy.ndimage.filters import gaussian_filter1d\nfrom statsmodels.stats.diagnostic impor... | [
[
"numpy.median",
"numpy.min",
"numpy.mean",
"numpy.where",
"scipy.stats.sem",
"numpy.max",
"numpy.histogram",
"numpy.arange",
"numpy.argmax",
"numpy.column_stack",
"sklearn.decomposition.PCA",
"numpy.vstack",
"matplotlib.use",
"numpy.array",
"numpy.zeros"... |
MadsAW/machine-learning-on-materials | [
"6101c7e3d12be54b12391c78442294198a39cc9b"
] | [
"Gamle scripts/systematic/drop_0_10.py"
] | [
"#!/usr/bin/env python3\n# -*- coding: utf-8 -*-\n\"\"\"\nCreated on Tue Nov 13 12:31:46 2018\n\n@author: Simon\n\"\"\"\n\nimport os\nfrom createLargerFeatureMatrix import simpleLargeMatrix\nimport pickle\nfrom keras.models import Sequential\nfrom keras.layers import Dense, Dropout\nfrom keras import regularizers\n... | [
[
"numpy.array",
"numpy.shape"
]
] |
jchen6727/netpyne | [
"52edba6b337768100861d83987ae6117d3e6ca62"
] | [
"netpyne/cell/compartCell.py"
] | [
"\"\"\"\ncell/compartCell.py \n\nContains compartCell class \n\nContributors: salvadordura@gmail.com\n\"\"\"\nfrom __future__ import division\nfrom __future__ import print_function\nfrom __future__ import unicode_literals\nfrom __future__ import absolute_import\n\nfrom builtins import super\nfrom builtins import ne... | [
[
"numpy.array",
"numpy.zeros",
"numpy.diff",
"numpy.sqrt",
"numpy.cumsum"
]
] |
ahmerb/GPPVAE | [
"6f806426627942a92d96b007ee1c1ece02445e48"
] | [
"pysrc/faceplace/train_gppvae.py"
] | [
"import matplotlib\nimport sys\n\nmatplotlib.use(\"Agg\")\nimport torch\nfrom torch import nn, optim\nimport torch.nn.functional as F\nfrom torch.autograd import Variable\nfrom torch.utils.data import DataLoader\nfrom vae import FaceVAE\nfrom vmod import Vmodel\nfrom gp import GP\nimport h5py\nimport scipy as sp\ni... | [
[
"matplotlib.use",
"torch.zeros",
"torch.nn.ParameterList",
"torch.no_grad",
"torch.optim.Adam",
"torch.manual_seed",
"torch.cuda.is_available",
"torch.utils.data.DataLoader",
"torch.load",
"scipy.unique",
"scipy.dot",
"torch.randn"
]
] |
LightSoar/pystylebox | [
"2a5cc6f9b5a67c0cb2100ccad139a927117f9e3e"
] | [
"stylebox.py"
] | [
"#!env/bin/python\n\nimport abc # abstract base class\nimport numpy as np\n\nfrom overrides import overrides\n\ndef rescale(x, from_lo, from_hi, to_lo, to_hi):\n # y = yi + (yf-yi)/(xf-xi)*(x-xi)\n y = to_lo + (to_hi-to_lo)/(from_hi-from_lo)*(x-from_lo)\n return y\n\n\nclass Scatter:\n def __init__(self... | [
[
"numpy.arange"
]
] |
harsh020/datasets | [
"b4ad3617b279ec65356e696c4c860458621976f6"
] | [
"tensorflow_datasets/core/features/audio_feature_test.py"
] | [
"# coding=utf-8\n# Copyright 2020 The TensorFlow Datasets 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 ... | [
[
"tensorflow.compat.v2.enable_v2_behavior"
]
] |
JamesRunnalls/pdf-txt | [
"238223d548bf231a9fb76cec8823cec47fad7853"
] | [
"pdf-txt.py"
] | [
"\n# coding: utf-8\n\nfrom pdfminer.layout import LAParams\nfrom pdfminer.pdfinterp import PDFResourceManager, PDFPageInterpreter\nfrom pdfminer.converter import PDFPageAggregator\nfrom pdfminer.pdfpage import PDFPage\nfrom pdfminer.layout import LTTextBoxHorizontal\nfrom functools import reduce\nimport pandas as p... | [
[
"pandas.DataFrame",
"pandas.to_numeric"
]
] |
columbia-applied-data-science/lecturenotes | [
"047b0cdc6ce70c441526f26e5516337e395feb84"
] | [
"book/code/streamspeedtest.py"
] | [
"import numpy as np\nimport pandas\nfrom numpy.random import rand\n\ndef generate_arrays(N):\n rand(N).tofile('/tmp/x.data', sep='\\n')\n rand(N).tofile('/tmp/y.data', sep='\\n')\n\n\ndef myfun(xfile, yfile):\n fx = open(xfile, 'r')\n fy = open(yfile, 'r')\n\n retval = 0.0\n for x in fx:\n ... | [
[
"pandas.read_csv",
"numpy.random.rand"
]
] |
andrrizzi/tfep-revisited-2021 | [
"9a9aff61286be3111c4e70136620d0e3aac31318"
] | [
"scripts/modules/tests/test_reweighting.py"
] | [
"#!/usr/bin/env python\n\n\n# =============================================================================\n# MODULE DOCSTRING\n# =============================================================================\n\n\"\"\"\nTest objects and function in the module reweighting.\n\"\"\"\n\n\n# ============================... | [
[
"numpy.all",
"numpy.isnan",
"numpy.random.RandomState"
]
] |
JohannesBuchner/massivedatans | [
"bf13e90048a3a1bb945e25e0a8848c08fa8a80f8"
] | [
"plotposterior.py"
] | [
"from __future__ import print_function, division\nimport json\nimport numpy\nfrom numpy import log, log10\nimport sys\nimport matplotlib.pyplot as plt\nimport h5py\nimport scipy.stats\n\nxx = []\nyy = []\n\nfilename = sys.argv[1]\ncolors = ['yellow', 'pink', 'cyan', 'magenta']\ncmap = plt.cm.gray\nzs = []\nplt.figu... | [
[
"matplotlib.pyplot.xlim",
"numpy.random.choice",
"matplotlib.pyplot.xlabel",
"matplotlib.pyplot.ylim",
"matplotlib.pyplot.savefig",
"matplotlib.pyplot.close",
"matplotlib.pyplot.yticks",
"matplotlib.pyplot.figure",
"numpy.mean",
"numpy.where",
"matplotlib.pyplot.hist",
... |
leeyy2020/LM-BFF | [
"2c80b2ea3987c403c4d4abc6e202d280ea846210"
] | [
"run.py"
] | [
"\"\"\"Finetuning the library models for sequence classification on GLUE.\"\"\"\n\nimport dataclasses\nimport logging\nimport os\nimport sys\nfrom dataclasses import dataclass, field\nfrom typing import Callable, Dict, Optional\nimport torch\n\nimport numpy as np\n\nimport transformers\nfrom transformers import Aut... | [
[
"torch.tensor",
"numpy.squeeze",
"numpy.argmax"
]
] |
f2re/FCH-TTS | [
"54ddee710694929d978943356fe913609ed0aab5"
] | [
"synthesize.wave.py"
] | [
"#!/usr/bin/env python\n# -*- encoding: utf-8 -*-\n'''\n@File : train-duration.py\n@Date : 2021/01/05, Tue\n@Author : Atomicoo\n@Version : 1.0\n@Contact : atomicoo95@gmail.com\n@License : (C)Copyright 2020-2021, ShiGroup-NLP-XMU\n@Desc : Synthetize sentences into speech.\n'''\n\n__author__ =... | [
[
"torch.sqrt",
"scipy.io.wavfile.write",
"torch.log10",
"torch.cuda.is_available",
"torch.tensor",
"torch.load"
]
] |
deepsense-ai/Distributed-BA3C | [
"f5195ae83121746bd449e1a5eb2897000bbd12df"
] | [
"src/tensorpack_cpu/tensorpack/RL/simulator.py"
] | [
"#!/usr/bin/env python2\n# -*- coding: utf-8 -*-\n# File: simulator.py\n# Author: Yuxin Wu <ppwwyyxxc@gmail.com>\n\nimport sys\nimport os\nimport signal\nimport time\nimport tensorflow as tf\nimport multiprocessing as mp\nimport time\nimport threading\nimport weakref\nfrom abc import abstractmethod, ABCMeta\nfrom c... | [
[
"tensorflow.trainable_variables"
]
] |
zwang586/MICNN | [
"3d27a7f624ed03502fd500628b8e5136cb3f0730"
] | [
"Porosity in selective laser sintering/powderGeneration.py"
] | [
"# -*- coding: utf-8 -*-\r\n\r\n##Add one powder to the lowest point of input structure - s_eta\r\n##Return new structure with the added powder and other updated infomation.\r\n \r\n\r\nimport numpy as np\r\nimport matplotlib.pyplot as plt\r\n \r\ndef powder(s_eta,nx,ny,layer,t,ymax): \r\n#s_eta: input structure... | [
[
"numpy.random.normal",
"numpy.zeros"
]
] |
zili1010/LLE-Simulation | [
"0faf51ec32b99e388b05311b39bc6349da966e87"
] | [
"PyCORe_main.py"
] | [
"import matplotlib.pyplot as plt\nimport numpy as np\nfrom scipy.integrate import complex_ode,solve_ivp\nimport matplotlib.ticker as ticker\nimport matplotlib.colors as mcolors\nfrom scipy.constants import pi, c, hbar\nfrom matplotlib.widgets import Slider, Button, TextBox\nfrom matplotlib.animation import FuncAnim... | [
[
"numpy.arccos",
"numpy.exp",
"numpy.multiply",
"numpy.fft.fft",
"numpy.size",
"numpy.imag",
"scipy.integrate.complex_ode",
"numpy.zeros_like",
"numpy.angle",
"scipy.sparse.diags",
"numpy.arange",
"numpy.transpose",
"numpy.sqrt",
"numpy.fft.fftshift",
"ma... |
maharshi95/GANTree | [
"5541c5fb0ba3d856081c03f37870a85fdd654681"
] | [
"src/dataloaders/mnist.py"
] | [
"from __future__ import absolute_import\nimport torch as tr\n\nfrom base.dataloader import BaseDataLoader\nfrom torchvision.datasets import MNIST, FashionMNIST\nfrom torch.utils.data import Dataset\nimport torchvision.transforms as transforms\n\nimport numpy as np\n\nclass MnistDataLoader(BaseDataLoader):\n\n de... | [
[
"numpy.concatenate",
"torch.load",
"numpy.isin"
]
] |
md-experiments/FewRel | [
"a91c0a12ccb35c422d58b51231657806fcb14dea"
] | [
"train_demo.py"
] | [
"from fewshot_re_kit.data_loader import get_loader, get_loader_pair, get_loader_unsupervised\nfrom fewshot_re_kit.framework import FewShotREFramework\nfrom fewshot_re_kit.sentence_encoder import CNNSentenceEncoder, BERTSentenceEncoder, BERTPAIRSentenceEncoder, RobertaSentenceEncoder, RobertaPAIRSentenceEncoder\nimp... | [
[
"torch.cuda.is_available",
"numpy.load"
]
] |
Arthur151/3DMPPE_POSENET_RELEASE | [
"49b71fec03fcb646f1c0e00515dfb2441c41e26b"
] | [
"data/MuPoTS/MuPoTS.py"
] | [
"import os\nimport os.path as osp\nimport scipy.io as sio\nimport numpy as np\nfrom pycocotools.coco import COCO\nfrom config import cfg\nimport json\nimport cv2\nimport random\nimport math\nfrom utils.pose_utils import pixel2cam, process_bbox\nfrom utils.vis import vis_keypoints, vis_3d_skeleton\n\nclass MuPoTS:\n... | [
[
"numpy.concatenate",
"numpy.array",
"numpy.zeros",
"numpy.ones",
"numpy.take",
"scipy.io.savemat"
]
] |
YuuuuXie/Stanene_FLARE | [
"b6678927dd7fe3b6e6dc405a5f27d1a3339782eb"
] | [
"flare/modules/crystals.py"
] | [
"import numpy as np\nfrom ase.build import fcc111, add_adsorbate\nfrom ase.visualize import view\nfrom ase.io import write\n\n\ndef get_supercell_positions(sc_size, cell, positions):\n sc_positions = []\n for m in range(sc_size):\n vec1 = m * cell[0]\n for n in range(sc_size):\n vec2 ... | [
[
"numpy.array"
]
] |
eddielyc/Augmented-Geometric-Distillation | [
"029973b7ce3c08fa1f0fa4dab27981d2148986a3"
] | [
"main.py"
] | [
"# -*- coding: utf-8 -*-\r\n# Time : 2020/5/3 19:22\r\n# Author : Yichen Lu\r\n\r\nimport argparse\r\nimport os.path as osp\r\n\r\nimport torch\r\n\r\nfrom reid.utils import Dataset\r\nfrom reid.utils import build_test_loader, build_train_loader\r\nfrom reid import trainers\r\nfrom reid.evaluation.evaluators im... | [
[
"torch.cuda.is_available"
]
] |
j8xixo12/solvcon | [
"a8bf3a54d4b1ed91d292e0cdbcb6f2710d33d99a"
] | [
"ftests/parallel/test_builtin.py"
] | [
"# -*- coding: UTF-8 -*-\n#\n# Copyright (C) 2012 Yung-Yu Chen <yyc@solvcon.net>.\n#\n# This program is free software; you can redistribute it and/or modify\n# it under the terms of the GNU General Public License as published by\n# the Free Software Foundation; either version 2 of the License, or\n# (at your option... | [
[
"numpy.empty",
"numpy.zeros"
]
] |
ddomhoff/tmtoolkit | [
"2e533d04af8fd3cbdd57af1a277f67148087b369"
] | [
"tmtoolkit/lda_utils/visualize.py"
] | [
"import os\nimport logging\n\nimport numpy as np\nimport matplotlib.pyplot as plt\n\nfrom tmtoolkit.utils import mat2d_window_from_indices\nfrom tmtoolkit.lda_utils.common import top_n_from_distribution\n\n\nlogger = logging.getLogger('tmtoolkit')\n\n\n#\n# word clouds from topic models\n#\n\ndef _wordcloud_color_f... | [
[
"numpy.array",
"numpy.arange",
"numpy.isin"
]
] |
engiecat/PyElastica | [
"0ea100e23d5908bf7ebdae4261276539e02a53a6"
] | [
"tests/test_elastica_numba/test_governing_equations_nb.py"
] | [
"__doc__ = \"\"\"Test Cosserat rod governing equations for Numba implementation\"\"\"\n\n# System imports\nimport numpy as np\nfrom numpy.testing import assert_allclose\nfrom elastica.utils import Tolerance, MaxDimension\nfrom elastica._elastica_numba._linalg import _batch_matvec\nfrom elastica._elastica_numba._rod... | [
[
"numpy.array",
"numpy.sin",
"numpy.random.rand",
"numpy.zeros",
"numpy.ones",
"numpy.degrees",
"numpy.identity",
"numpy.radians",
"numpy.einsum",
"numpy.sqrt",
"numpy.cos",
"numpy.repeat",
"numpy.linspace"
]
] |
gcarq/keras-timeseries-prediction | [
"8ab377b6ad6a60d469a4da8430951df7f7230e9e"
] | [
"main.py"
] | [
"import numpy\nimport pandas\nimport matplotlib.pyplot as plt\n\nfrom keras.layers import Dense, LSTM\nfrom keras.models import Sequential\nfrom sklearn.metrics import mean_squared_error\n\nfrom sklearn.preprocessing import MinMaxScaler\n\nfrom tqdm import trange\n\n\n# fix random seed for reproducibility\nnumpy.ra... | [
[
"numpy.concatenate",
"numpy.array",
"numpy.delete",
"numpy.empty",
"numpy.reshape",
"sklearn.metrics.mean_squared_error",
"numpy.random.seed",
"matplotlib.pyplot.plot",
"sklearn.preprocessing.MinMaxScaler",
"matplotlib.pyplot.show",
"pandas.read_csv"
]
] |
whyjz/icepyx | [
"fe57c41a2775b663c19a2ab59a6ebb644caf4a3b"
] | [
"icepyx/core/query.py"
] | [
"import datetime as dt\nimport os\nimport requests\nimport json\nimport warnings\nimport pprint\nimport time\nimport geopandas as gpd\nimport matplotlib.pyplot as plt\n\nfrom icepyx.core.Earthdata import Earthdata\nimport icepyx.core.APIformatting as apifmt\nimport icepyx.core.is2ref as is2ref\nimport icepyx.core.g... | [
[
"matplotlib.pyplot.show",
"matplotlib.pyplot.subplots"
]
] |
E18301194/vedaseg | [
"c62c8ea46dbba12f03262452dd7bed22969cfe4e"
] | [
"vedaseg/models/utils/conv_module.py"
] | [
"# modify from mmcv and mmdetection\n\nimport warnings\n\nimport torch.nn as nn\n\nfrom .norm import build_norm_layer\nfrom .act import build_act_layer\nfrom .registry import UTILS\n\nconv_cfg = {\n 'Conv': nn.Conv2d,\n # TODO: octave conv\n}\n\n\ndef build_conv_layer(cfg, *args, **kwargs):\n \"\"\" Build ... | [
[
"torch.nn.Sequential",
"torch.nn.Dropout2d"
]
] |
yukuzntcva/Denoising-drone-rotors | [
"0122b020fc959dd3869b3863989fee3520aede73"
] | [
"main.py"
] | [
"import argparse\nimport csv\nimport logging\nimport os\nimport sys\nfrom ast import literal_eval\nfrom datetime import datetime\nimport time\n\nimport matplotlib\n\nmatplotlib.use('Agg')\nimport matplotlib.pyplot as plt\n\nplt.switch_backend('agg')\nimport numpy as np\nimport torch\nimport torch.backends.cudnn as ... | [
[
"matplotlib.use",
"matplotlib.pyplot.switch_backend",
"numpy.concatenate",
"torch.cuda.manual_seed_all",
"matplotlib.pyplot.savefig",
"matplotlib.pyplot.xlabel",
"numpy.load",
"matplotlib.pyplot.close",
"matplotlib.pyplot.figure",
"torch.manual_seed",
"torch.optim.lr_sc... |
TropComplique/trained-ternary-quantization | [
"4cd4132124c30e0e868a78eb1b2a2798df5e2a90"
] | [
"utils/input_pipeline.py"
] | [
"import numpy as np\nfrom PIL import Image, ImageEnhance\nfrom torchvision.datasets import ImageFolder\nimport torchvision.transforms as transforms\n\n\nTRAIN_DIR = '/home/ubuntu/data/tiny-imagenet-200/training'\nVAL_DIR = '/home/ubuntu/data/tiny-imagenet-200/validation'\n\n\n\"\"\"It assumes that training image da... | [
[
"numpy.random.normal",
"numpy.random.shuffle"
]
] |
Hennich/cvxpy | [
"4dfd6d69ace76abf57d8b1d63db0556dee96e24f"
] | [
"cvxpy/constraints/constraint.py"
] | [
"\"\"\"\nCopyright 2013 Steven Diamond\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 agreed to i... | [
[
"numpy.all"
]
] |
koniecsveta/h2o-3 | [
"b672bd80a08b0c899086b0ae24985ddb1c537de0"
] | [
"h2o-py/h2o/model/anomaly_detection.py"
] | [
"# -*- encoding: utf-8 -*-\nfrom __future__ import absolute_import, division, print_function, unicode_literals\nfrom .model_base import ModelBase\nfrom h2o.utils.shared_utils import can_use_pandas\n\n\nclass H2OAnomalyDetectionModel(ModelBase):\n\n def varsplits(self, use_pandas=False):\n \"\"\"\n ... | [
[
"pandas.DataFrame"
]
] |
zhuang-group/SPViT | [
"74f08c6e55fb6adc0322722cedfd2c25ebdee999",
"74f08c6e55fb6adc0322722cedfd2c25ebdee999"
] | [
"SPViT_Swin/data/cached_image_folder.py",
"SPViT_Swin/data/zipreader.py"
] | [
"# --------------------------------------------------------\n# Swin Transformer\n# Copyright (c) 2021 Microsoft\n# Licensed under The MIT License [see LICENSE for details]\n# Written by Ze Liu\n# --------------------------------------------------------\n# Modifications copyright (c) 2021 Zhuang AI Group, Haoyu He\n... | [
[
"torch.distributed.get_world_size",
"torch.distributed.get_rank"
],
[
"numpy.uint8",
"numpy.random.rand"
]
] |
marcus-deans/Animal10-VGG-Classification | [
"84e3ea0dbfda277ff907b370f8659e7be39aed02"
] | [
"Classifier.py"
] | [
"\n\nimport numpy as np # linear algebra\nimport pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)\n\nimport tensorflow as tf\nimport keras\nfrom keras import layers, applications, optimizers\nfrom keras.layers import Input, Dense, Activation, MaxPool2D, ZeroPadding2D, BatchNormalization, Flatten, Con... | [
[
"pandas.DataFrame",
"matplotlib.pyplot.subplots"
]
] |
dydo0316/test2 | [
"a9982a8b426dd07eb1ec4e7695a7bc546ecc6063",
"a9982a8b426dd07eb1ec4e7695a7bc546ecc6063"
] | [
"tests/chainer_tests/test_reporter.py",
"chainer/functions/activation/sigmoid.py"
] | [
"import contextlib\nimport tempfile\nimport unittest\n\nimport numpy\n\nimport chainer\nfrom chainer.backends import cuda\nfrom chainer import configuration\nfrom chainer import functions\nfrom chainer import testing\nfrom chainer.testing import attr\n\n\nclass TestReporter(unittest.TestCase):\n\n def test_empty... | [
[
"numpy.array",
"numpy.savez",
"numpy.sqrt"
],
[
"numpy.tanh"
]
] |
sj6077/DeepSpeed | [
"c70b472a68bc9ca387b14a1b35814c582d0ec94b"
] | [
"setup.py"
] | [
"\"\"\"\nCopyright 2020 The Microsoft DeepSpeed Team\n\nDeepSpeed library\n\nCreate a new wheel via the following command: python setup.py bdist_wheel\n\nThe wheel will be located at: dist/*.whl\n\"\"\"\n\nimport os\nimport torch\nfrom deepspeed import __version__ as ds_version\nfrom setuptools import setup, find_p... | [
[
"torch.cuda.is_available",
"torch.__version__.split",
"torch.utils.cpp_extension.CUDAExtension"
]
] |
regev-lab/shap | [
"13c6141ebe459f34c0b69293135124eca1211fa1"
] | [
"shap/_explanation.py"
] | [
"\nimport pandas as pd\nimport numpy as np\nimport scipy as sp\nimport sys\nimport warnings\nimport copy\nfrom slicer import Slicer, Alias\n# from ._order import Order\nfrom .utils._general import OpChain\n\n# slicer confuses pylint...\n# pylint: disable=no-member\n\n\nop_chain_root = OpChain(\"shap.Explanation\")\... | [
[
"scipy.cluster.hierarchy.optimal_leaf_ordering",
"scipy.spatial.distance.pdist",
"numpy.array",
"numpy.random.seed",
"numpy.percentile",
"scipy.cluster.hierarchy.complete",
"numpy.abs"
]
] |
maxipi/kostra | [
"c3b58518b04a9d5b804cbd17cc67dcedf9970fb1"
] | [
"example/example_python_api_extended.py"
] | [
"from idf_analysis import IntensityDurationFrequencyAnalyse\nfrom idf_analysis.definitions import *\nimport pandas as pd\nfrom os import path\n\n# sub-folder for the results\n\noutput_directory = path.join('ehyd_112086_idf_data')\n# initialize of the analysis class\nidf = IntensityDurationFrequencyAnalyse(series_ki... | [
[
"pandas.read_parquet"
]
] |
TitovaEkaterina/Snake_RL | [
"883cd560c008f7f7351d5c5e87f7ea5732a8fbfa"
] | [
"ou_noise.py"
] | [
"import numpy as np\nimport numpy.random as nr\n\nclass OUNoise:\n \"\"\"docstring for OUNoise\"\"\"\n def __init__(self,action_dimension,mu=0, theta=0.3, sigma=0.2):\n self.action_dimension = action_dimension\n self.mu = mu\n self.theta = theta\n self.sigma = sigma\n self.s... | [
[
"matplotlib.pyplot.show",
"matplotlib.pyplot.plot",
"numpy.ones"
]
] |
anonymous-submission000/mobo | [
"090f774d742c7155c5e5ba01c10e7db7b93b6a0a",
"090f774d742c7155c5e5ba01c10e7db7b93b6a0a"
] | [
"dragonfly/exd/unittest_domains.py",
"dragonfly/exd/worker_manager.py"
] | [
"\"\"\"\n Unit tests for domains.py\n -- kandasamy@cs.cmu.edu\n\"\"\"\n\n# pylint: disable=invalid-name\n\nfrom __future__ import absolute_import\n\nimport numpy as np\n\n# Local imports\nfrom . import domains\nfrom ..utils.base_test_class import BaseTestClass, execute_tests\nfrom ..utils.general_utils import map... | [
[
"numpy.random.random",
"numpy.array"
],
[
"numpy.random.random",
"numpy.random.normal",
"numpy.ones",
"numpy.sqrt"
]
] |
jessemelpolio/torchcv | [
"09bd5c80a2b4b869f4e23881cbe5b8b3bb462f7a"
] | [
"model/seg/nets/deeplabv3.py"
] | [
"#!/usr/bin/env python\n# -*- coding:utf-8 -*-\n# Author: Donny You(youansheng@gmail.com)\n# deeplabv3 res101 (synchronized BN version)\n\n\nimport torch\nimport torch.nn as nn\nimport torch.nn.functional as F\n\nfrom model.backbones.backbone_selector import BackboneSelector\nfrom model.tools.module_helper import M... | [
[
"torch.cat",
"torch.cuda.LongTensor",
"torch.nn.Conv2d",
"torch.cuda.FloatTensor",
"torch.nn.AdaptiveAvgPool2d",
"torch.nn.Dropout2d",
"torch.randn"
]
] |
TVS-AI/fed_rppg | [
"88886554ace264d40b3e2fefd2ef22f61a1f1edf"
] | [
"torchrppg/nets/blocks/blocks.py"
] | [
"import torch\r\n\r\nclass ConvBlock2D(torch.nn.Module):\r\n def __init__(self, in_channel, out_channel, kernel_size, stride, padding):\r\n super(ConvBlock2D, self).__init__()\r\n self.conv_block_2d = torch.nn.Sequential(\r\n torch.nn.Conv2d(in_channel, out_channel, kernel_size, stride, ... | [
[
"torch.cat",
"torch.nn.MaxPool2d",
"torch.split",
"torch.nn.BatchNorm2d",
"torch.nn.ConvTranspose2d",
"torch.unsqueeze",
"torch.nn.ReLU",
"torch.nn.Upsample",
"torch.nn.Conv2d",
"torch.nn.Conv3d",
"torch.zeros_like",
"torch.nn.BatchNorm3d",
"torch.nn.ConvTranspo... |
agneet42/ImmunAL | [
"ac4dc0d3b6763deab7610616a7e3061161166eb2"
] | [
"src/RWR/seed_calculation.py"
] | [
"#%%\n\nimport csv\nfrom scipy.stats.stats import pearsonr\n\nfile = csv.reader(open(\"diseased_final.csv\",\"r\"))\n\nall_arr = []\ntemp_all_arr = []\n\nfor lines in file:\n if(len(lines) > 0):\n\t temp_all_arr.append(lines)\n\nprint(len(temp_all_arr))\n\nfor k in range(0,2333):\n\ttemp = []\n\tfor all in te... | [
[
"scipy.stats.stats.pearsonr",
"numpy.mean"
]
] |
MADE-realtime/realtime_news | [
"0a63687cad0ccefd772b2c28d7138d8db52d5f20"
] | [
"clusterisation/clusterisation.py"
] | [
"from typing import List\n\nfrom sklearn.cluster import AgglomerativeClustering\nimport fasttext.util\nimport numpy as np\n\nfrom datetime import date\nfrom db_lib.crud import get_news_by_filters\nfrom config import LANGUAGE_SHORT_FOR_FASTTEXT, LIMIT_NEWS\nfrom db_lib.models import News\nfrom db_lib.database import... | [
[
"numpy.array",
"sklearn.cluster.AgglomerativeClustering"
]
] |
brightmaraba/mandelbrot | [
"02e07806d1fdeef6e003fac872d6f90a961b1167"
] | [
"insert_sort.py"
] | [
"import matplotlib.pyplot as plt\nfrom matplotlib.animation import FuncAnimation\nimport matplotlib as mp\nimport numpy as np\nimport random\n\n# Set graph style\nplt.style.use('fivethirtyeight')\n\n# Create array and shuffle it\nn = int(input(\"Enter array size\\n\"))\na = [i for i in range(1, n+1)]\nrandom.shuffl... | [
[
"matplotlib.animation.FuncAnimation",
"matplotlib.pyplot.subplots",
"matplotlib.pyplot.show",
"matplotlib.colors.Normalize",
"matplotlib.pyplot.style.use",
"matplotlib.colors.LinearSegmentedColormap"
]
] |
madin162/AI604_project | [
"d17b7a062bd1d55367136d15fabef64664d328b6"
] | [
"codes/SRN/models/DASR_model.py"
] | [
"import sys\nimport os\nimport cv2\nimport logging\nfrom collections import OrderedDict\nimport torch\nimport torch.nn as nn\nimport torch.nn.functional as F\nfrom torch.optim import lr_scheduler\nfrom utils.util import forward_chop\nimport models.networks as networks\nfrom .base_model import BaseModel\nfrom models... | [
[
"torch.cat",
"torch.nn.MSELoss",
"torch.no_grad",
"torch.optim.Adam",
"torch.nn.functional.interpolate",
"torch.optim.lr_scheduler.MultiStepLR",
"torch.nn.L1Loss",
"torch.abs",
"torch.Tensor"
]
] |
VinhLoiIT/EfficientDet.Pytorch | [
"a5a753c6566c21f8c3fad12798efc48295d11a00"
] | [
"datasets/cocov2.py"
] | [
"from __future__ import print_function, division\nimport sys\nimport os\nimport torch\nimport numpy as np\nimport random\nimport csv\n\nfrom torch.utils.data import Dataset, DataLoader\nfrom torchvision import transforms, utils\nfrom torch.utils.data.sampler import Sampler\n\nfrom pycocotools.coco import COCO\n\nim... | [
[
"numpy.array",
"numpy.zeros",
"numpy.append"
]
] |
zachlim98/carloancalc | [
"d10e2de5748026e8fd60b6a9734f4666467c40fb"
] | [
"Code/Dash App/app.py"
] | [
"import dash\nimport dash_core_components as dcc\nimport dash_html_components as html\nfrom dash.dependencies import Input, Output\nimport plotly.express as px\nimport pandas as pd\n\napp = dash.Dash(__name__)\nserver = app.server\n\napp.layout = html.Div([\n html.Div([\n dcc.Input(\n id='carprice',\n ... | [
[
"pandas.DataFrame",
"pandas.melt"
]
] |
AnCoSONG/SCUCaptchaRecognizer | [
"09e1255d34cfc576eba451a72bf7a988c4893f9b",
"09e1255d34cfc576eba451a72bf7a988c4893f9b"
] | [
"TestFromZHJW.py",
"CNNtrain.py"
] | [
"from keras import models\nimport cv2 as cv\nimport os\nimport numpy as np\nimport requests\nimport random\nimport matplotlib.pyplot as plt\n\ntry:\n model1 = models.load_model('models/0PosRecognize.h5')\n model2 = models.load_model('models/1PosRecognize.h5')\n model3 = models.load_model('models/2PosRecogn... | [
[
"numpy.array",
"matplotlib.pyplot.title",
"matplotlib.pyplot.figure",
"matplotlib.pyplot.show",
"matplotlib.pyplot.imshow"
],
[
"matplotlib.pyplot.xlabel",
"matplotlib.pyplot.plot",
"matplotlib.pyplot.gcf",
"matplotlib.pyplot.show",
"matplotlib.pyplot.subplot"
]
] |
aman313/deep_generalization | [
"2ef2a731a1b2e5c3ce16c7b66de86c57dba08a37"
] | [
"models/data_utils/data_read_utils.py"
] | [
"import pandas as pd\nimport torch\nimport numpy as np\nimport ast\ndef one_hot_transformer(vocab):\n vocab_index = {elem:index for index,elem in enumerate(vocab)}\n def trans(str,max_len):\n one_hot = torch.zeros(max_len,len(vocab))\n for i in range(len(str)):\n char = str[i]\n ... | [
[
"pandas.read_csv",
"torch.FloatTensor"
]
] |
parvathysjsu/Adaptive-and-Heuristic-AI-enabled-IoT-Edge-for-high-risk-and-rural-patients | [
"c3e639fabfdbe9ffa4ce1f9a700ebace254c0080"
] | [
"HealthCareAIApp/app/src/main/python/featureExtraction.py"
] | [
"import librosa as lb\nimport numpy as np\nfrom scipy.signal import butter, lfilter\n\n\n# Sample rate and desired cutoff frequencies (in Hz).\nfs = 4000.0\nlowcut = 100.0\nhighcut = 1800.0\n\n#Set maxpad length as 79 <--(Sampling rate*5s)/256(hop length)\ndef build_feat(fpath):\n max_pad_len = 79\n wav, rat... | [
[
"numpy.pad",
"scipy.signal.butter",
"scipy.signal.lfilter",
"numpy.expand_dims"
]
] |
sinbag/deepsampling | [
"40b28ad99f3cc4b37602e38765b62e2091642764"
] | [
"src/main.py"
] | [
"import platform\nimport os, sys\n\nif platform.system() == 'Linux':\n # To find available GPU on a multi-gpu machine cluster\n import utils.selectgpu as setgpu\n os.environ[\"CUDA_VISIBLE_DEVICES\"] = str(setgpu.pick_gpu_lowest_memory())\n\nimport argparse\nimport importlib\n\nimport numpy as np\nimport m... | [
[
"tensorflow.summary.FileWriter",
"tensorflow.train.AdamOptimizer",
"tensorflow.Session",
"tensorflow.reset_default_graph",
"tensorflow.Variable",
"numpy.stack",
"tensorflow.placeholder",
"numpy.arange",
"tensorflow.train.exponential_decay",
"tensorflow.global_variables_init... |
mathurinm/torch_itl | [
"e3d92d753bd51ccf585029129110c93bbf9b5fd0"
] | [
"demos/quantile/demo_synthetic.py"
] | [
"import os\nimport sys\nimport importlib\n\nif importlib.util.find_spec('torch_itl') is None:\n path_to_lib = os.getcwd()[:-15]\n sys.path.append(path_to_lib)\n\nfrom torch_itl.estimator import IQR\nfrom torch_itl.kernel import Gaussian, LearnableGaussian\nfrom torch_itl.model import DecomposableIdentity\nfro... | [
[
"torch.nn.Linear",
"matplotlib.pyplot.plot",
"matplotlib.pyplot.title",
"torch.linspace",
"matplotlib.pyplot.figure",
"torch.nn.ReLU",
"matplotlib.pyplot.show",
"matplotlib.pyplot.scatter"
]
] |
larsoner/genz-1 | [
"dc7a73b4597f976c0274d696c2610c79b7a1f7c1",
"dc7a73b4597f976c0274d696c2610c79b7a1f7c1"
] | [
"genz/funcs.py",
"genz/static/expyfun/io/_wav.py"
] | [
"#!/usr/bin/env python\n# -*- coding: utf-8 -*-\n\nimport os.path as op\nimport itertools\nimport mne\nimport numpy as np\n\n\nfrom genz import defaults\n\n\ndef expand_grid(data_dict):\n import pandas as pd\n rows = itertools.product(*data_dict.values())\n return pd.DataFrame.from_records(rows, columns=da... | [
[
"numpy.allclose",
"numpy.tril_indices",
"numpy.argsort"
],
[
"scipy.io.wavfile.read",
"scipy.io.wavfile.write",
"numpy.abs",
"numpy.iinfo",
"numpy.dtype",
"numpy.atleast_2d"
]
] |
TiffanyTseng54/SimpleCVReproduction | [
"52754eb924c6c094af0b8089a1bd7af0be7ec1a3",
"52754eb924c6c094af0b8089a1bd7af0be7ec1a3"
] | [
"NAS/cifar100/models/resnet.py",
"NAS/cifar100/utils/utils.py"
] | [
"'''ResNet in PyTorch.\n\nFor Pre-activation ResNet, see 'preact_resnet.py'.\n\nReference:\n[1] Kaiming He, Xiangyu Zhang, Shaoqing Ren, Jian Sun\n Deep Residual Learning for Image Recognition. arXiv:1512.03385\n'''\n\n\nimport torch\nimport torch.nn as nn\nimport torch.nn.functional as F\n\n\n__all__ = ['ResNet... | [
[
"torch.nn.Linear",
"torch.nn.functional.avg_pool2d",
"torch.nn.Sequential",
"torch.nn.BatchNorm2d",
"torch.nn.Conv2d",
"torch.nn.functional.relu",
"torch.randn"
],
[
"torch.nn.LogSoftmax",
"numpy.clip",
"torch.save",
"numpy.ones",
"torch.bmm",
"torch.from_nu... |
lmk123568/Paddle_Model_Analysis | [
"d03a82591512fcad065fc69abfdbfb0835099c2d"
] | [
"ppma/imagenet/validate.py"
] | [
"import time\r\n\r\nimport numpy as np\r\nimport paddle\r\nimport paddle.nn.functional as F\r\nimport paddle.vision.transforms as T\r\nfrom paddle.io import DataLoader, Dataset\r\nfrom PIL import Image\r\nfrom .utils import AverageMeter, get_val_transforms\r\n\r\n\r\nclass ImageNet2012Dataset(Dataset):\r\n def _... | [
[
"numpy.array"
]
] |
theonion/betty-cropper | [
"bb0e570c1eb0ddb2f39d109f996edd1d417d1fe4"
] | [
"betty/cropper/dssim.py"
] | [
"try:\n import numpy as np\n import scipy.ndimage\nexcept ImportError:\n pass\n\nfrom betty.conf.app import settings\nimport io\nimport math\n\nfrom PIL import Image\n\n\nMIN_UNIQUE_COLORS = 4096\nCOLOR_DENSITY_RATIO = 0.11\n\nQUALITY_IN_MIN = 82\n\nERROR_THRESHOLD = 1.3\n\nERROR_THRESHOLD_INACCURACY = 0.0... | [
[
"numpy.asarray",
"numpy.ascontiguousarray",
"numpy.ones",
"numpy.mean",
"numpy.dtype",
"numpy.unique"
]
] |
JulienLefevreMars/slam | [
"484ee9bb052e4107ef4edbbd876fe5cd6305c8fc",
"484ee9bb052e4107ef4edbbd876fe5cd6305c8fc"
] | [
"slam/surface_profiling.py",
"slam/generate_parametric_surfaces.py"
] | [
"import numpy as np\nfrom scipy.spatial.distance import cdist\nimport trimesh\nimport trimesh.intersections\nimport trimesh.triangles\n\nimport slam.geodesics\nimport slam.utils as utils\n\n\ndef cortical_surface_profiling(mesh, rot_angle, r_step, max_samples):\n \"\"\"\n Surface profiling for a given cortica... | [
[
"numpy.array",
"numpy.linalg.norm",
"numpy.dot",
"numpy.zeros",
"numpy.where",
"numpy.arctan2",
"numpy.argsort",
"numpy.hstack",
"numpy.cross",
"numpy.unique"
],
[
"numpy.random.rand",
"numpy.linalg.qr",
"numpy.where",
"numpy.sign",
"numpy.cos",
... |
jcartus/FHI-AIMS_Tutorials | [
"d91c6865b3192e2e56f4572593255d52fd6191d8"
] | [
"Session_1/Problem_1/plot_energies.py"
] | [
"\"\"\"This script plots the hydrogen energies with different basis sets. \"\"\"\n\nimport numpy as np\nimport matplotlib.pyplot as plt\n\nplt.style.use(\"seaborn\")\n\ndef fetch_data():\n return np.loadtxt(\n fname=\"energies.csv\",\n delimiter=\";\",\n skiprows=1\n )\n\ndef plot(data):\... | [
[
"matplotlib.pyplot.xlabel",
"matplotlib.pyplot.plot",
"numpy.loadtxt",
"matplotlib.pyplot.ylabel",
"matplotlib.pyplot.style.use",
"matplotlib.pyplot.show"
]
] |
ScholarIndex/LinkedBooks | [
"0cae008427ed1eb34a882e9d85f24b42b3ee3a28"
] | [
"reference_parsing/model_dev/BER_error_calculation.py"
] | [
"# -*- coding: utf-8 -*-\n\"\"\"\nBalanced Error Rate error functions\n\"\"\"\n__author__ = \"\"\"Giovanni Colavizza\"\"\"\n\nimport numpy as np\n\ndef BER(yn, ynhat):\n \"\"\"\n Implementation of Balanced Error Rate\n\n :param yn: ground truth\n :param ynhat: predicted values\n :return: error score\... | [
[
"numpy.array"
]
] |
Silver-L/keras_projects | [
"92124dc2ec4adc4c0509d0ee0655ebd39b8ba937"
] | [
"autoencoder/trainer.py"
] | [
"\"\"\"\n* @Trainer\n* @Author: Zhihui Lu\n* @Date: 2018/07/21\n\"\"\"\n\nimport os\nimport numpy as np\nimport argparse\nimport dataIO as io\nfrom random import randint\nimport matplotlib.pyplot as plt\nimport pickle\n\nos.environ[\"CUDA_DEVICE_ORDER\"] = \"PCI_BUS_ID\"\nos.environ[\"CUDA_VISIBLE_DEVICES\"] = \"-1... | [
[
"matplotlib.pyplot.xlabel",
"matplotlib.pyplot.title",
"matplotlib.pyplot.plot",
"matplotlib.pyplot.legend",
"numpy.arange",
"matplotlib.pyplot.ylabel",
"matplotlib.pyplot.show",
"numpy.expand_dims"
]
] |
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