repo_name stringlengths 6 130 | hexsha list | file_path list | code list | apis list |
|---|---|---|---|---|
reachlin/machinelearning | [
"eb8ba02aa0da86ccf9991fa609afa84d8c180a21"
] | [
"tensorflow/sample_rnn.py"
] | [
"\"\"\"\nModified from: https://github.com/tensorflow/models/blob/master/tutorials/rnn/ptb/ptb_word_lm.py\nRNN with LSTM cells\n\"\"\"\nfrom __future__ import absolute_import\nfrom __future__ import division\nfrom __future__ import print_function\n\nimport time\n\nimport numpy as np\nimport tensorflow as tf\n\nimpo... | [
[
"tensorflow.train.import_meta_graph",
"tensorflow.contrib.rnn.BasicLSTMCell",
"numpy.exp",
"tensorflow.reshape",
"tensorflow.gradients",
"tensorflow.nn.embedding_lookup",
"tensorflow.add_to_collection",
"tensorflow.train.GradientDescentOptimizer",
"tensorflow.contrib.rnn.Dropou... |
cenchaojun/detectron2 | [
"03ca41a6873bb641764c4762d40d355f215e7ad9"
] | [
"projects/faster_rcnn_swin_transformer/train_net_swint_full_reso.py"
] | [
"#!/usr/bin/env python\n# Copyright (c) Facebook, Inc. and its affiliates.\n\"\"\"\nDetection Training Script.\nThis scripts reads a given config file and runs the training or evaluation.\nIt is an entry point that is made to train standard models in detectron2.\nIn order to let one script support training of many ... | [
[
"torch.nn.utils.clip_grad_norm_",
"torch.cuda.device_count"
]
] |
pesvut/netket | [
"7f19574ddc567748344bb75a4ddd507578d94b0d"
] | [
"netket/hilbert/homogeneous.py"
] | [
"# Copyright 2021 The NetKet Authors - All rights reserved.\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n# http://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless required... | [
[
"numpy.max",
"numpy.empty",
"numpy.asarray",
"numpy.nonzero",
"numpy.searchsorted",
"numpy.iinfo"
]
] |
devanshpratapsingh/Python | [
"5327f54512a35fa8c55a83499d56875abbde633c"
] | [
"machine_learning/logistic_regression.py"
] | [
"#!/usr/bin/python\n\n## Logistic Regression from scratch\n\n# In[62]:\n\n# In[63]:\n\n# importing all the required libraries\n\n\"\"\" Implementing logistic regression for classification problem\n Helpful resources : \n 1.Coursera ML course \n 2.https://medium.com/@martinpella/logistic-regression-fr... | [
[
"numpy.dot",
"numpy.zeros",
"numpy.log",
"matplotlib.pyplot.legend",
"numpy.exp",
"matplotlib.pyplot.figure",
"matplotlib.pyplot.show",
"matplotlib.pyplot.scatter",
"numpy.linspace",
"matplotlib.pyplot.contour",
"sklearn.datasets.load_iris"
]
] |
kug3lblitz/maryland-foreclosure-scraper | [
"d1b8851efb4f82bc305f5d23c079b1f83ef73be4"
] | [
"close_crawl/modules/cleaner.py"
] | [
"#!/usr/bin/env python\n# -*- coding: utf-8 -*-\n\n\"\"\"Cleaner\n\nThis module implements post-scraping cleaning processes on the raw initial\ndataset. Processes include stripping excess strings off Address values,\nremoving Zip Code and Partial Cost values mislabeled as Address, and merging\nrows containing blank... | [
[
"pandas.to_datetime",
"pandas.DataFrame",
"pandas.read_csv"
]
] |
gmazzamuto/gputools | [
"73a4dee76a119f94d8163781a85b691fd080d506",
"73a4dee76a119f94d8163781a85b691fd080d506"
] | [
"tests/denoise/test_nlm.py",
"tests/transforms/test_geometric_transform.py"
] | [
"from __future__ import print_function, unicode_literals, absolute_import, division\nfrom gputools.denoise import nlm2, nlm3\n\n\nimport numpy as np\n\n\ndef test_2d(fac = .3):\n from scipy.misc import ascent\n\n d = ascent().astype(np.float32)\n\n d = d[:,:-10]\n sig = .2*np.amax(d)\n\n y = d+sig*n... | [
[
"scipy.misc.ascent",
"numpy.random.uniform",
"numpy.amax",
"numpy.linspace",
"numpy.meshgrid"
],
[
"numpy.testing.assert_allclose",
"numpy.random.choice",
"numpy.zeros",
"numpy.random.seed",
"scipy.ndimage.geometric_transform",
"numpy.random.uniform",
"numpy.ran... |
kevinyu/inspec | [
"28e7fd224fdeae50fb1ce0e74eb02d940c1eab5a"
] | [
"tests/test_colormap.py"
] | [
"import unittest\nfrom unittest import mock\n\nimport numpy as np\n\nfrom inspec.colormap import (\n _registered_colormaps,\n Colormap,\n ColormapNotFound,\n CursesColormapSingleton,\n PairedColormap,\n VALID_CMAPS,\n curses_cmap,\n load_cmap,\n)\n\n\nclass TestPairedColormap(unittest.TestCa... | [
[
"numpy.array",
"numpy.arange",
"numpy.testing.assert_array_equal"
]
] |
quimaguirre/diana | [
"930da0ea91ad87e354061af18db6c437a3318366"
] | [
"scripts/old_scripts/analyze_results_by_classification.py"
] | [
"import argparse\nimport copy\nimport cPickle\nimport matplotlib.pyplot as plt\nimport numpy as np\nimport pandas as pd\nimport pylab\n#from pylab import plot, show, savefig, xlim, figure, hold, ylim, legend, boxplot, setp, axes, xlabel, ylabel\nimport scipy\nimport time\nimport sys, os, re\n\nfrom sklearn.decompos... | [
[
"pandas.DataFrame.from_records",
"numpy.array",
"sklearn.ensemble.AdaBoostClassifier",
"sklearn.ensemble.RandomForestClassifier",
"pandas.DataFrame",
"sklearn.neighbors.KNeighborsClassifier",
"sklearn.neural_network.MLPClassifier",
"sklearn.naive_bayes.GaussianNB",
"matplotlib.... |
MatthewGerber/rlai | [
"f390433c3adc285e1e9cc113deed7009b2e6dd5a",
"f390433c3adc285e1e9cc113deed7009b2e6dd5a",
"f390433c3adc285e1e9cc113deed7009b2e6dd5a"
] | [
"test/rlai/gpi/monte_carlo/iteration_test.py",
"src/rlai/runners/agent_in_environment.py",
"test/rlai/gpi/monte_carlo/evaluation_test.py"
] | [
"import os\nimport pickle\nimport tempfile\nimport time\nfrom threading import Thread\n\nimport pytest\nfrom numpy.random import RandomState\n\nfrom rlai.agents.mdp import StochasticMdpAgent\nfrom rlai.environments.gridworld import Gridworld, GridworldFeatureExtractor\nfrom rlai.environments.mdp import TrajectorySa... | [
[
"numpy.random.RandomState"
],
[
"numpy.random.RandomState",
"matplotlib.backends.backend_pdf.PdfPages",
"matplotlib.pyplot.subplots",
"matplotlib.pyplot.tight_layout",
"matplotlib.pyplot.show"
],
[
"numpy.random.RandomState"
]
] |
ValtoGameEngines/Armory | [
"ad3d3c63e64e9225e62b414b7ec4dd9fb93fab32"
] | [
"blender/arm/exporter_opt.py"
] | [
"import bpy\r\nimport numpy as np\r\nfrom mathutils import *\r\nimport arm.utils\r\n\r\n# Exports smaller geometry but is slower\r\n# To be replaced with https://github.com/zeux/meshoptimizer\r\n\r\nclass Vertex:\r\n __slots__ = (\"co\", \"normal\", \"uvs\", \"col\", \"loop_indices\", \"index\", \"bone_weights\"... | [
[
"numpy.array",
"numpy.empty"
]
] |
mathdan/vaex | [
"16e91add76d2570f2f976e5936d8e4721ea3dd16"
] | [
"tests/strings_test.py"
] | [
"# -*- coding: utf-8 -*-\nimport sys\nimport re\n\nimport vaex\nimport numpy as np\nimport pytest\n\ntry:\n\tunicode\n\tstr_kind = 'S'\nexcept:\n\tstr_kind = 'U'\n\n\n@pytest.mark.skipif(sys.version_info < (3,3),\n reason=\"requires python3.4 or higher\")\ndef test_dtype_object_string(tmpdir):\n\... | [
[
"numpy.ma.array",
"numpy.array",
"numpy.arange"
]
] |
a414351664/TRAB-IKE | [
"b822384cf9d4aa9adda46f7f306c024782fa5f15"
] | [
"src/multihead_attention.py"
] | [
"import math\nimport torch\nfrom torch import nn\nfrom torch.nn import Parameter\nimport torch.nn.functional as F\n\nfrom fairseq import utils\n\n\ndef Embedding(num_embeddings, embedding_dim, padding_idx=None, init_scale=None):\n m = nn.Embedding(num_embeddings, embedding_dim, padding_idx=padding_idx)\n nn.i... | [
[
"torch.nn.Linear",
"torch.Size",
"torch.cat",
"torch.arange",
"torch.nn.init.constant_",
"torch.nn.init.xavier_uniform_",
"torch.bmm",
"torch.nn.init.normal_",
"torch.nn.init.xavier_normal_",
"torch.Tensor",
"torch.nn.Embedding"
]
] |
LukeMcCulloch/PyCFD | [
"6720e6575e25f8c274ef591d6c215de90a740935"
] | [
"src/PlotGrids.py"
] | [
"#!/usr/bin/env python2\n# -*- coding: utf-8 -*-\n\"\"\"\nCreated on Sun Jan 5 16:04:47 2020\n\n@author: lukemcculloch\n\"\"\"\n\nimport numpy as np\n# imports for plotting:\nimport matplotlib.pyplot as plt\n\nclass PlotGrid(object):\n \n def __init__(self, grid):\n self.grid = grid\n \n \n ... | [
[
"numpy.linalg.norm",
"matplotlib.pyplot.subplots",
"matplotlib.pyplot.arrow"
]
] |
SridharJagannathan/cloud-volume | [
"ae4e5d8f245aacf451404e91f75e6da5182ac090"
] | [
"cloudvolume/frontends/precomputed.py"
] | [
"from __future__ import print_function\n\nimport itertools\nimport gevent.socket\nimport json\nimport os\nimport sys\nimport uuid\nimport socket\n\nimport fastremap\nfrom six.moves import range\nimport numpy as np\nfrom tqdm import tqdm\nfrom six import string_types\nimport multiprocessing as mp\n\nfrom .. import l... | [
[
"numpy.array_equal",
"numpy.zeros",
"numpy.isscalar",
"numpy.issubdtype",
"numpy.iinfo"
]
] |
alvin-hsu/icml18-jtnn | [
"0292265bb97c31a925a03b18a3d3b38c560c89c6"
] | [
"jtnn/jtmpn.py"
] | [
"import torch\nimport torch.nn as nn\nfrom .nnutils import create_var, index_select_ND\nfrom .chemutils import get_mol\n#from mpn import atom_features, bond_features, ATOM_FDIM, BOND_FDIM\nimport rdkit.Chem as Chem\n\nELEM_LIST = ['C', 'N', 'O', 'S', 'F', 'Si', 'P', 'Cl', 'Br', 'Mg', 'Na', 'Ca', 'Fe', 'Al', 'I', 'B... | [
[
"torch.nn.Linear",
"torch.zeros",
"torch.cat",
"torch.stack",
"torch.nn.ReLU"
]
] |
thesmarthomeninja/Video_Gaming_ML | [
"e9c147f33a790a9cd3e4ee631ddbf6bbf91c3921"
] | [
"lib/invoke_tasks.py"
] | [
"from invoke import task\n\nfrom lib.frame_grabber import FrameGrabber\nfrom lib.games import *\n\nimport lib.datasets\n\nfrom lib.machine_learning.context_classification.context_classifiers import SVMContextClassifier\nfrom lib.machine_learning.context_classification.context_classifiers import CNNInceptionV3Contex... | [
[
"sklearn.linear_model.SGDRegressor"
]
] |
MattTheVV/CoronaWatchNL | [
"3e548c589193fe2736c66bf5829a482e5416f58a"
] | [
"merge_data.py"
] | [
"\"\"\"Merge RIVM daily stats\"\"\"\n\nfrom pathlib import Path\nimport re\nimport datetime\nfrom io import StringIO\n\nimport pandas\n\n\nDATE_MAP = {\n \"maart\": 3,\n \"april\": 4,\n \"mei\": 5,\n}\n\n\ndef list_files():\n\n return [p for p in Path('raw_data').iterdir() if p.is_file()]\n\n\ndef parse... | [
[
"pandas.read_csv"
]
] |
Saleh-Ibtasham/VulScrape | [
"738d17e9dd7e5edc2341d106361651fd28f99c61"
] | [
"fastembed/predictor/lookup.py"
] | [
"import pandas as pd\nfrom .classifier import get_result\nfrom scipy import spatial\nfrom sklearn.metrics.pairwise import cosine_similarity\nimport numpy as np\n\ndef getCveList(cve_list):\n df_feature = pd.read_csv(\"./fastembed/ml_models/CVE_data_with_features.csv\")\n df_classifier = pd.read_csv(\"./fastem... | [
[
"numpy.reshape",
"pandas.concat",
"numpy.amax",
"numpy.argmax",
"sklearn.metrics.pairwise.cosine_similarity",
"pandas.read_csv"
]
] |
shpandey/MRIproject | [
"f69c9947edd95a7b85027abd2049c5aeb892569d"
] | [
"model/VAE.py"
] | [
"#import tensorflow as tf\nimport tensorflow.compat.v1 as tf #NOTE: To train on tensorflow version 2.0\ntf.disable_v2_behavior()\n\nimport h5py\nimport os\nimport numpy as np\nimport pathlib\n#from utils.subsample import MaskFunc\n#import utils.transforms as T\nfrom matplotlib import pyplot as plt\nfrom fastmri_da... | [
[
"tensorflow.compat.v1.keras.layers.Dense",
"tensorflow.compat.v1.disable_v2_behavior",
"tensorflow.compat.v1.get_default_graph",
"tensorflow.compat.v1.shape",
"tensorflow.compat.v1.keras.layers.Conv2DTranspose",
"tensorflow.compat.v1.device",
"tensorflow.compat.v1.sigmoid",
"tensor... |
Wangyf46/deeplabv3plus-pytorch | [
"dbbbe88d7774d6e02f7ea13e770ee4278dc528fd"
] | [
"lib/datasets/V1datasets.py"
] | [
"#-*-coding:utf-8-*-\n# ----------------------------------------\n# Written by Yude Wang\n# ----------------------------------------\n\nfrom __future__ import print_function, division\nimport os\nimport sys\nimport pandas as pd\nimport cv2\nimport tqdm\nimport multiprocessing\nfrom PIL import Image\nimport numpy as... | [
[
"numpy.sum",
"numpy.uint8",
"numpy.mean",
"numpy.zeros"
]
] |
apyrros/HCC-comorbidities | [
"fd74fb2f1438bc741cfe6728c5cb64737bc99d68"
] | [
"visualize/grad_cam.py"
] | [
"#!/usr/bin/env python\n# coding: utf-8\n#\n# Author: Kazuto Nakashima\n# URL: http://kazuto1011.github.io\n# Created: 2017-05-26\n\nfrom collections import Sequence\n\nimport numpy as np\nimport torch\nimport torch.nn as nn\nfrom torch.nn import functional as F\nfrom tqdm import tqdm\n\n\nclass _BaseWrappe... | [
[
"torch.cat",
"torch.mul",
"torch.nn.functional.interpolate",
"torch.split",
"torch.nn.functional.adaptive_avg_pool2d",
"torch.nn.functional.relu",
"torch.nn.functional.softmax",
"torch.zeros_like",
"torch.nn.functional.pad",
"torch.set_grad_enabled"
]
] |
manuba95/floodlight | [
"02c64763e78b14ef37555e1dc435256dbd4eca09",
"02c64763e78b14ef37555e1dc435256dbd4eca09"
] | [
"floodlight/io/tracab.py",
"floodlight/core/code.py"
] | [
"from pathlib import Path\nfrom typing import Dict, Tuple, Union\n\nimport numpy as np\nfrom lxml import etree\n\nfrom floodlight.core.code import Code\nfrom floodlight.core.pitch import Pitch\nfrom floodlight.core.xy import XY\n\n\ndef _read_metadata(filepath_metadata: Union[str, Path]) -> Tuple[Dict, Dict, Pitch]... | [
[
"numpy.full",
"numpy.array"
],
[
"numpy.unique",
"numpy.diff"
]
] |
lixiaoyu0575/physionet_challenge2020_pytorch | [
"39b5aeeead440eaa88d6fdaf4a8a70c15373e062"
] | [
"model/fcn.py"
] | [
"import torch\nfrom torch import nn\nfrom .util import ConvBlock\n\nclass FCN(nn.Module):\n \"\"\"A PyTorch implementation of the FCN Baseline\n From https://arxiv.org/abs/1909.04939\n\n Attributes\n ----------\n sequence_length:\n The size of the input sequence\n num_pred_classes:\n ... | [
[
"torch.nn.Linear"
]
] |
LukasKratochvila/Deep-SVDD-PyTorch | [
"a94bd9b6be4d953706daf969b061ddf55d6cbf4c"
] | [
"src/networks/my_LeNet.py"
] | [
"#!/usr/bin/env python3\n# -*- coding: utf-8 -*-\n\"\"\"\nCreated on Thu Nov 19 18:40:39 2020\n\n@author: kratochvila\n\"\"\"\n\nimport torch\nimport torch.nn as nn\nimport torch.nn.functional as F\n\nfrom base.base_net import BaseNet\n\n\nclass MY_LeNet(BaseNet):\n\n def __init__(self):\n super().__init_... | [
[
"torch.nn.Linear",
"torch.sigmoid",
"torch.nn.MaxPool2d",
"torch.nn.BatchNorm2d",
"torch.nn.ConvTranspose2d",
"torch.nn.Conv2d",
"torch.nn.BatchNorm1d",
"torch.nn.init.calculate_gain",
"torch.nn.functional.leaky_relu"
]
] |
pedrobcst/Xerus-streamlit | [
"9c94a4d05e5aa4439ac6165a5b6951b26d3d2e4d"
] | [
"app.py"
] | [
"import os\nimport shutil\nfrom typing import List, Union\n\nimport pandas as pd\nimport streamlit as st\nfrom st_aggrid import AgGrid\n\nfrom conf import AppSettings\nfrom xerus_plot import plot_highest_correlated, plot_read_data\nfrom xerus_run import run_opt, run_xerus\n\nos.makedirs(AppSettings.TMP_FOLDER, exis... | [
[
"pandas.DataFrame"
]
] |
zzszmyf/models | [
"5d25e00c94943e50e64780a244136f88f13c0a88"
] | [
"fluid/PaddleCV/rcnn/utility.py"
] | [
"# Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserve.\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 require... | [
[
"numpy.median"
]
] |
sees-usc/geo-selection-inversion | [
"31fd16389d1e6a2b057ab71e1db87333572d1463"
] | [
"2d-fluvial/dataloader.py"
] | [
"import random\nimport string\nimport numpy as np\nimport matplotlib as mpl\nimport matplotlib.pyplot as plt\nimport matplotlib.gridspec as gridspec\n\nimport os\nos.environ['TF_CPP_MIN_LOG_LEVEL'] = '3' # or any {'0', '1', '2'}\nimport tensorflow as tf\ntf.compat.v1.logging.set_verbosity(tf.compat.v1.logging.ERRO... | [
[
"numpy.max",
"numpy.reshape",
"numpy.zeros",
"numpy.random.seed",
"numpy.load",
"numpy.min",
"tensorflow.compat.v1.logging.set_verbosity",
"numpy.where",
"numpy.arange",
"numpy.squeeze",
"numpy.expand_dims"
]
] |
rendner/py-plugin-dataframe-viewer | [
"188585bd31a6c14413949865b3467dcbf6f5e2d1"
] | [
"projects/python_plugin_code/pandas_1.2_code/tests/html_meta_data/test_meta.py"
] | [
"# Copyright 2021 cms.rendner (Daniel Schmidt)\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 ap... | [
[
"pandas.DataFrame.from_dict"
]
] |
deepakksingh/mmdetection | [
"b0d845f1fecf8064db30ef6b456b6ef5f36fa40f"
] | [
"mmdet/core/bbox/samplers/iou_balanced_neg_sampler.py"
] | [
"import numpy as np\nimport torch\n\nfrom ..builder import BBOX_SAMPLERS\nfrom .random_sampler import RandomSampler\n\n\n@BBOX_SAMPLERS.register_module()\nclass IoUBalancedNegSampler(RandomSampler):\n \"\"\"IoU Balanced Sampling\n\n arXiv: https://arxiv.org/pdf/1904.02701.pdf (CVPR 2019)\n\n Sampling propo... | [
[
"numpy.concatenate",
"torch.nonzero",
"numpy.array",
"numpy.logical_and",
"torch.from_numpy",
"numpy.where"
]
] |
Featurespace/uncertainty-attribution | [
"06986c56600366e5516f5b39ec2bc61436ba4b35"
] | [
"uncertainty_library/utils.py"
] | [
"import tensorflow as tf\nimport numpy as np\n\n\ndef remove_test_time_dropout(model_drop):\n config = model_drop.get_config()\n for layer in config['layers']:\n if 'Dropout' in layer['class_name']:\n layer['inbound_nodes'][0][0][3]['training'] = False\n model = tf.keras.Model().from_conf... | [
[
"numpy.concatenate",
"tensorflow.keras.Model"
]
] |
davisyoshida/flax | [
"0848d9cf203cc5dfe63d4a5dece3c6aa8e135107",
"0848d9cf203cc5dfe63d4a5dece3c6aa8e135107"
] | [
"examples/lm1b/train.py",
"examples/mnist/main.py"
] | [
"# Copyright 2021 The Flax 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 a... | [
[
"numpy.array",
"numpy.ceil",
"numpy.tile",
"tensorflow.io.gfile.makedirs",
"numpy.prod",
"numpy.argmax"
],
[
"tensorflow.config.experimental.set_visible_devices"
]
] |
Sinba7/Movie-Recommender | [
"802c9c66739ef1c49287038aca06cb6943a79bd8"
] | [
"src/collaborative_recom.py"
] | [
"import pandas as pd\nfrom surprise import Dataset, Reader, KNNWithMeans, KNNWithZScore\nimport logbook\nimport sys\n\n\n# logging\nfunction_log = logbook.Logger('RECOMMENDER')\nlevel = logbook.TRACE\nlogbook.StreamHandler(sys.stdout, level=level).push_application()\n\n\ndef collab_recommender(train_data, test_dat... | [
[
"pandas.DataFrame"
]
] |
Fpiotro/MOLECULAR-TRANSLATION | [
"050dd0c093ee4e68326c2404c5b4dbf53ca6c8a0"
] | [
"EncoderDecoder/prep_inchi.py"
] | [
"# ====================================================\r\n# Library\r\n# ====================================================\r\nimport os\r\nimport re\r\nimport numpy as np\r\nimport pandas as pd\r\nimport torch\r\n\r\n# ====================================================\r\n# Data Loading\r\n# =================... | [
[
"pandas.read_csv",
"torch.save"
]
] |
mattwthompson/QCElemental | [
"2e84cd686d5fff0fc79accb28ffa985de4684704"
] | [
"qcelemental/molparse/from_arrays.py"
] | [
"import pprint\nimport re\nfrom copy import deepcopy\n\nimport numpy as np\n\nfrom ..exceptions import ValidationError\nfrom ..physical_constants import constants\nfrom ..util import provenance_stamp, unnp, update_with_error\nfrom .chgmult import validate_and_fill_chgmult\nfrom .nucleus import reconcile_nucleus\nfr... | [
[
"numpy.array",
"numpy.asarray",
"numpy.zeros",
"numpy.split",
"numpy.any",
"numpy.where",
"numpy.einsum"
]
] |
sunflower036/se-pg | [
"2eaa32517abd324d0e495d632041f66beb514757"
] | [
"decode.py"
] | [
"# Copyright 2016 The TensorFlow Authors. All Rights Reserved.\n# Modifications Copyright 2017 Abigail See\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.apach... | [
[
"tensorflow.train.Saver",
"tensorflow.logging.info"
]
] |
weihao94/deepdyn | [
"48018b62a245dd791e45d60b28068489a8c32742"
] | [
"testarch/unet/unet_trainer.py"
] | [
"\"\"\"\n### author: Aashis Khanal\n### sraashis@gmail.com\n### date: 9/10/2018\n\"\"\"\n\nimport os\n\nimport numpy as np\nimport torch\nfrom PIL import Image as IMG\nimport torch.nn.functional as F\n\nimport viz.nviz as plt\nfrom torchtrainer.torchtrainer import NNTrainer\nfrom utils.measurements import ScoreAccu... | [
[
"numpy.array",
"torch.FloatTensor",
"torch.max"
]
] |
HMJiangGatech/chainer-gan-lib | [
"ee6764b2b2a9d7309267fd1b95835b883464aee1"
] | [
"orthgan/updater.py"
] | [
"import numpy as np\n\nimport chainer\nimport chainer.functions as F\nfrom chainer import Variable\n\n\nclass Updater(chainer.training.StandardUpdater):\n def __init__(self, *args, **kwargs):\n self.gen, self.dis = kwargs.pop('models')\n self.n_dis = kwargs.pop('n_dis')\n super(Updater, self... | [
[
"numpy.asarray"
]
] |
karnesh/coexistence | [
"a6862dd8554ca0ab430fca6efe4de0f355f8145a"
] | [
"coex/scaling.py"
] | [
"import numpy as np\r\nfrom scipy.optimize import fmin\r\n\r\n\r\ndef coexistence(lnpi, N):\r\n \"\"\"Locate the coexistence acticity near the critical point by\r\n maximizing compressibility.\r\n\r\n Args:\r\n lnpi: The original log of probability distribution.\r\n N: par... | [
[
"numpy.dot",
"numpy.sum",
"numpy.exp",
"numpy.loadtxt",
"numpy.abs",
"numpy.linspace"
]
] |
AppleFairy/CS20SI-Tensorflow-for-Deep-Learning-Research | [
"c647b4c779787c7aa3fd7842ff6d808d3f85822e"
] | [
"word2vec.py"
] | [
"from __future__ import division\nimport os\nimport zipfile\nimport collections\nimport random\nimport numpy as np\nimport tensorflow as tf\nfrom tensorflow.contrib.tensorboard.plugins import projector\n\n\n# global variables\ndata_name = \"data/text/text8.zip\"\nWORK_DIR = os.path.abspath(os.curdir)\nVOCAB_SIZE = ... | [
[
"numpy.random.choice",
"tensorflow.matmul",
"tensorflow.contrib.tensorboard.plugins.projector.ProjectorConfig",
"tensorflow.nn.embedding_lookup",
"tensorflow.global_variables_initializer",
"tensorflow.nn.nce_loss",
"tensorflow.train.GradientDescentOptimizer",
"tensorflow.summary.hi... |
ellohfin/retro | [
"58ec8f5b698e6140acd215717f051d99e407c4e5",
"58ec8f5b698e6140acd215717f051d99e407c4e5"
] | [
"retro/plot/plot_1d_scan.py",
"retro/tables/ckv_tables.py"
] | [
"#!/usr/bin/env python\n# -*- coding: utf-8 -*-\n# pylint: disable=wrong-import-position\n\n\"\"\"\nPlot likelihood scan results\n\"\"\"\n\nfrom __future__ import absolute_import, division, print_function\n\n__all__ = [\n 'FNAME_TEMPLATE',\n 'plot_1d_scan',\n 'parse_args'\n]\n\n__author__ = 'P. Eller, J.L.... | [
[
"matplotlib.use",
"matplotlib.pyplot.tight_layout",
"matplotlib.pyplot.subplots"
],
[
"numpy.load"
]
] |
anilkumarpanda/probatus | [
"a6123b4da664dfc4f182dad1baa00e77decf4789"
] | [
"probatus/interpret/inspector.py"
] | [
"# Copyright (c) 2020 ING Bank N.V.\n#\n# Permission is hereby granted, free of charge, to any person obtaining a copy of\n# this software and associated documentation files (the \"Software\"), to deal in\n# the Software without restriction, including without limitation the rights to\n# use, copy, modify, merge, pu... | [
[
"pandas.NamedAgg",
"pandas.concat",
"pandas.DataFrame",
"sklearn.cluster.KMeans",
"numpy.abs",
"pandas.Series",
"numpy.unique"
]
] |
hitaitengteng/python | [
"4e07fe6755ef1e0e0c1193249446e5246c89236e",
"4e07fe6755ef1e0e0c1193249446e5246c89236e"
] | [
"chapter13/test/code/4-yuce.py",
"chapter7/test/code/cluster_plot.py"
] | [
"#-*- coding: utf-8 -*-\nimport pandas as pd\ninputfile = '../tmp/data4_GM11.xls' # 灰色预测后保存的路径\noutputfile = '../data/enterprise_income.xls' # 神经网络预测后保存的结果\nmodelfile = '../tmp/4-net.model' # 模型保存路径\ndata = pd.read_excel(inputfile) # 读取数据\nfeature = ['x1', 'x2', 'x3', 'x4', 'x6', 'x7', 'x9', 'x10'] # 特征所在列\n\n... | [
[
"matplotlib.pyplot.show",
"pandas.read_excel"
],
[
"numpy.concatenate",
"pandas.DataFrame",
"matplotlib.pyplot.legend",
"matplotlib.pyplot.figure",
"numpy.arange",
"pandas.concat",
"matplotlib.pyplot.show",
"numpy.linspace",
"pandas.Series"
]
] |
DEPICTIVE/mito_sims | [
"07daf8f5dcb82ba95c1b9f4cc8981d451b032986"
] | [
"mito_sims_py3/fixed_points.py"
] | [
"\nimport numpy as np\nfrom scipy.optimize import bisect\n\n# =============================================\n# =============================================\n# =============================================\n# =============================================\nclass find:\n def __init__(self, f, xlims, args, nsamples... | [
[
"numpy.array",
"numpy.cov",
"numpy.random.rand",
"numpy.zeros",
"numpy.sum",
"numpy.abs",
"scipy.optimize.bisect",
"numpy.linspace"
]
] |
l-k-11235/OpenNMT-py | [
"4815f07fcd482af9a1fe1d3b620d144197178bc5",
"4815f07fcd482af9a1fe1d3b620d144197178bc5"
] | [
"onmt/tests/test_translator.py",
"onmt/translate/penalties.py"
] | [
"import unittest\nfrom onmt.translate import GeneratorLM\nimport torch\n\n\nclass TestGeneratorLM(unittest.TestCase):\n def test_split_src_to_prevent_padding_target_prefix_is_none_when_equal_size( # noqa: E501\n self,\n ):\n src = torch.randint(0, 10, (5, 6))\n src_lengths = 5 * torch.on... | [
[
"torch.randint",
"torch.ones"
],
[
"torch.zeros"
]
] |
hanton/tensorflow | [
"3fe3f2b1984aab6f159b89aa3ab0069988925689",
"34fd2a5e9bcdb40957ece90fec46a37e6e9248b2",
"3fe3f2b1984aab6f159b89aa3ab0069988925689"
] | [
"tensorflow/examples/saved_model/integration_tests/export_simple_text_embedding.py",
"tensorflow/python/keras/engine/network.py",
"tensorflow/contrib/distribute/python/parameter_server_strategy_test.py"
] | [
"# Copyright 2019 The TensorFlow Authors. All Rights Reserved.\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n# http://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless requ... | [
[
"tensorflow.compat.v2.SparseTensor",
"tensorflow.python.ops.lookup_ops.index_table_from_file",
"tensorflow.compat.v2.saved_model.save",
"tensorflow.compat.v2.reshape",
"tensorflow.compat.v2.sparse.reset_shape",
"tensorflow.compat.v2.strings.regex_replace",
"tensorflow.compat.v2.TensorS... |
jagatabhay/TSAI | [
"313a27e321881fa974bfa62388e7f43ae3e0390a"
] | [
"S11/LRScheduler.py"
] | [
"import copy\r\nimport os\r\nimport torch\r\nfrom tqdm.autonotebook import tqdm\r\nfrom torch.optim.lr_scheduler import _LRScheduler\r\nimport matplotlib.pyplot as plt\r\nfrom torch.utils.data import DataLoader\r\n\r\nfrom packaging import version\r\n\r\nPYTORCH_VERSION = version.parse(torch.__version__)\r\n\r\ntry... | [
[
"torch.no_grad",
"torch.save",
"matplotlib.pyplot.subplots",
"torch.load",
"matplotlib.pyplot.show"
]
] |
hongyouc/FedBE | [
"7eeb965d29ce6c35c38f31706a004c00745e59b8",
"7eeb965d29ce6c35c38f31706a004c00745e59b8"
] | [
"utils/sampling.py",
"utils/tools.py"
] | [
"#!/usr/bin/env python\n# -*- coding: utf-8 -*-\n# Python version: 3.6\n\nimport numpy as np\nimport pdb\nfrom torchvision import datasets, transforms\nimport os\nimport glob\nfrom torch.utils.data import Dataset\nfrom PIL import Image\n\ndef mnist_iid(dataset, num_users):\n \"\"\"\n Sample I.I.D. client data... | [
[
"numpy.concatenate",
"numpy.array",
"numpy.count_nonzero",
"numpy.random.choice",
"numpy.reshape",
"numpy.zeros",
"numpy.random.shuffle",
"numpy.split",
"numpy.where",
"numpy.arange",
"numpy.cumsum",
"numpy.repeat",
"numpy.vstack"
],
[
"numpy.max",
"... |
faroukmokhtar/weaver | [
"f3ba1b78d03b5809611b21bd06663fa2f3b738bf"
] | [
"train.py"
] | [
"#!/usr/bin/env python\n\n#import setGPU\nimport os\nimport shutil\nimport glob\nimport argparse\nimport numpy as np\nimport math\nimport torch\n\nfrom torch.utils.data import DataLoader\nfrom importlib import import_module\nimport ast\nfrom utils.logger import _logger, _configLogger\nfrom utils.dataset import Simp... | [
[
"torch.device",
"torch.optim.lr_scheduler.OneCycleLR",
"numpy.savetxt",
"torch.save",
"numpy.random.shuffle",
"torch.ones",
"torch.optim.lr_scheduler.MultiStepLR",
"torch.utils.data.DataLoader",
"torch.profiler.profile",
"torch.load",
"torch.profiler.schedule",
"tor... |
MrinalTyagi/scikit-learn | [
"2fc9187879424556726d9345a6656884fa9fbc20"
] | [
"sklearn/pipeline.py"
] | [
"\"\"\"\nThe :mod:`sklearn.pipeline` module implements utilities to build a composite\nestimator, as a chain of transforms and estimators.\n\"\"\"\n# Author: Edouard Duchesnay\n# Gael Varoquaux\n# Virgile Fritsch\n# Alexandre Gramfort\n# Lars Buitinck\n# License: BSD\n\nfrom collecti... | [
[
"scipy.sparse.issparse",
"numpy.asarray",
"numpy.zeros",
"scipy.sparse.hstack",
"numpy.hstack"
]
] |
bcarlier75/ft_linear_regression | [
"b966c8432855873ff273ad9b50a638e290edb407"
] | [
"utils.py"
] | [
"from sys import argv\nfrom maths import *\nimport matplotlib.pyplot as plt\nimport csv\n\n\ndef print_usage():\n print(f'Usage: python train.py [-h] [-p] [-m]')\n print(f'\\t -h : display this message')\n print(f'\\t -p : display plot')\n print(f'\\t -m : display model metrics')\n\n\ndef check_args():\... | [
[
"matplotlib.pyplot.xlabel",
"matplotlib.pyplot.plot",
"matplotlib.pyplot.show",
"matplotlib.pyplot.ylabel",
"matplotlib.pyplot.scatter"
]
] |
tkemps/mklaren | [
"d9e7890aaa26cb3877e1a82114ab1e52df595d96"
] | [
"mklaren/kernel/kernel.py"
] | [
"\"\"\" Methods related to calculation of kernel function values and kernel\n matrices.\n\"\"\"\nimport numpy as np\nimport scipy.sparse as sp\nfrom sklearn.gaussian_process.kernels import Matern\nfrom scipy.spatial.distance import cdist\n\n# Install the GPy module to use included kernels\ntry:\n import GPy\n... | [
[
"scipy.sparse.isspmatrix",
"numpy.array",
"numpy.linalg.norm",
"numpy.random.rand",
"sklearn.gaussian_process.kernels.Matern",
"numpy.asarray",
"numpy.absolute",
"numpy.ones",
"numpy.exp",
"numpy.eye",
"numpy.tanh",
"numpy.diag",
"numpy.abs",
"numpy.cos",
... |
icicle4/TranSTAM | [
"3dfda76cc507b3a3a4b25fbecab7df65fd8cab4d"
] | [
"fast-reid/fastreid/modeling/backbones/osnet.py"
] | [
"# encoding: utf-8\n\"\"\"\n@author: xingyu liao\n@contact: sherlockliao01@gmail.com\n\"\"\"\n\n# based on:\n# https://github.com/KaiyangZhou/deep-person-reid/blob/master/torchreid/models/osnet.py\n\nimport logging\n\nimport torch\nfrom torch import nn\n\nfrom fastreid.layers import get_norm\nfrom fastreid.utils i... | [
[
"torch.device",
"torch.nn.Identity",
"torch.nn.LayerNorm",
"torch.nn.MaxPool2d",
"torch.nn.Sequential",
"torch.nn.Sigmoid",
"torch.nn.AvgPool2d",
"torch.nn.init.kaiming_normal_",
"torch.nn.init.constant_",
"torch.nn.ReLU",
"torch.nn.Conv2d",
"torch.nn.init.normal_",... |
ikuyamada/nlp-architect | [
"b9d7df0afde39b62b2c23e24211e368b82623abc"
] | [
"nlp_architect/data/ptb.py"
] | [
"# ******************************************************************************\n# Copyright 2017-2018 Intel Corporation\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# ... | [
[
"numpy.array",
"numpy.arange"
]
] |
bjlittle/mint | [
"fe4862951e0c570caef6e86440b090650dca000b"
] | [
"tools/reader_base.py"
] | [
"import netCDF4\nimport numpy\nimport vtk\n\nclass ReaderBase(object):\n\n PERIODICITY_LENGTH = 360.\n\n def __init__(self):\n \"\"\"\n Constructor\n No args\n \"\"\"\n\n self.vtk = {\n 'pointArray': [],\n 'pointData': vtk.vtkDoubleArray(),\n ... | [
[
"numpy.zeros"
]
] |
WestCityInstitute/InvCompress | [
"17deb0f0e2f28432e6d5b38d0898ead58ccbcde4"
] | [
"codes/compressai/zoo/image.py"
] | [
"# Copyright 2020 InterDigital Communications, Inc.\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n# http://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless required by app... | [
[
"torch.hub.load_state_dict_from_url"
]
] |
mattolson93/Contrastive-Explanation-Method | [
"62f2660895d42c08ab36f589c0f9ebf9bf25948c"
] | [
"aen_CEM.py"
] | [
"## aen_attack.py -- attack a network optimizing elastic-net distance with an en decision rule\r\n## when autoencoder loss is applied\r\n##\r\n## Copyright (C) 2018, IBM Corp\r\n## Chun-Chen Tu <timtu@umich.edu>\r\n## PaiShun Ting <paishun@umich.edu>\r\n## ... | [
[
"numpy.copy",
"tensorflow.global_variables_initializer",
"tensorflow.cast",
"tensorflow.train.GradientDescentOptimizer",
"tensorflow.subtract",
"tensorflow.Variable",
"tensorflow.global_variables",
"tensorflow.negative",
"numpy.argmax",
"tensorflow.add",
"tensorflow.abs... |
khucnam/Efflux_TransVAE | [
"7da1cc614f016d5520648f4853e34e2362181aa7"
] | [
"tvae/nn/modules/position_wise.py"
] | [
"from torch import nn\n\n\nclass PositionWise(nn.Module):\n def __init__(self, dim_m, dim_i, dropout=0.1):\n \"\"\"Position-wise Feed-Forward Network.\n\n Args:\n dim_m (int): input and output dimension.\n dim_i (int): inner dimension.\n dropout (float, optional): d... | [
[
"torch.nn.Linear",
"torch.nn.Dropout",
"torch.nn.LayerNorm",
"torch.nn.ReLU"
]
] |
yifanmai/model-analysis | [
"ae11318876ac6233ded77ac30c8aacc94da691d3"
] | [
"tensorflow_model_analysis/eval_saved_model/graph_ref_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 ... | [
[
"tensorflow.Graph",
"tensorflow.core.protobuf.meta_graph_pb2.SignatureDef",
"tensorflow.constant",
"tensorflow.core.protobuf.meta_graph_pb2.MetaGraphDef",
"tensorflow.test.main"
]
] |
flexlee/pandas | [
"749318f4a1b4ae56d3eee507db312052532e7f4b"
] | [
"pandas/core/generic.py"
] | [
"# pylint: disable=W0231,E1101\nfrom datetime import timedelta\n\nimport numpy as np\n\nfrom pandas.core.index import MultiIndex\nfrom pandas.tseries.index import DatetimeIndex\nfrom pandas.tseries.offsets import DateOffset\nimport pandas.core.common as com\nimport pandas.lib as lib\n\n\nclass PandasError(Exception... | [
[
"pandas.tseries.frequencies.to_offset",
"numpy.isnan",
"numpy.minimum.accumulate",
"numpy.putmask",
"pandas.tseries.resample.asfreq",
"pandas.core.common.isnull",
"pandas.core.common.save",
"pandas.core.groupby.groupby",
"numpy.maximum.accumulate",
"pandas.tseries.resample.... |
thanatosmin/FcgR-binding | [
"db54bff479d326b41c74a78d3ca2755a8b7fc7e6"
] | [
"recepmod/tests/test_Main.py"
] | [
"import random\nimport unittest\nimport numpy as np\nfrom scipy.stats import norm\nfrom ..StoneModel import StoneModel, ReqFuncSolver, logpdf_sum, StoneMod\n\ndef get_random_vars():\n kai = random.random()\n kx = random.random()\n vi = random.randint(1, 30)\n R = random.random()\n Li = random.random(... | [
[
"numpy.isinf",
"numpy.array",
"numpy.isnan",
"scipy.stats.norm.logpdf",
"numpy.log10"
]
] |
MarcoJHB/ploomber | [
"4849ef6915572f7934392443b4faf138172b9596"
] | [
"tests/io_mod/test_fileloadermixin.py"
] | [
"from unittest.mock import Mock\n\nimport pytest\nimport pandas as pd\n\nfrom ploomber import DAG\nfrom ploomber.tasks import SQLDump, NotebookRunner, PythonCallable\nfrom ploomber.products import File\n\n\ndef test_unsupported_extension():\n task = SQLDump('SELECT * FROM table',\n File('my_fil... | [
[
"pandas.DataFrame"
]
] |
cyckun/GBDT_Simple_Tutorial | [
"20a8d1f53453291e55f14b268fa5c4f225d68d1c"
] | [
"GBDT/gbdt.py"
] | [
"\"\"\"\nCreated on ：2019/03/28\n@author: Freeman, feverfc1994\n\"\"\"\n\nimport abc\nimport math\nimport logging\nimport pandas as pd\nfrom GBDT.decision_tree import Tree\nfrom mpyc.statistics import (mean, variance, stdev, pvariance, pstdev,\n mode, median, median_low, median_high)\nfr... | [
[
"numpy.vectorize",
"pandas.set_option",
"pandas.Series"
]
] |
Nikoleta-v3/pandas | [
"58a59bd606911f11a4f679df18a00cfc25536c30"
] | [
"pandas/tests/indexes/multi/test_conversion.py"
] | [
"# -*- coding: utf-8 -*-\n\nimport pytest\nimport numpy as np\n\nimport pandas as pd\nimport pandas.util.testing as tm\nfrom pandas import DataFrame, MultiIndex, date_range\nfrom pandas.compat import range\n\n\ndef test_tolist(idx):\n result = idx.tolist()\n exp = list(idx.values)\n assert result == exp\n\... | [
[
"pandas.util.testing.assert_frame_equal",
"pandas.util.testing.round_trip_pickle",
"pandas.DataFrame",
"pandas.date_range",
"pandas.util.testing.assert_index_equal",
"pandas.MultiIndex.from_tuples",
"numpy.arange",
"pandas.MultiIndex",
"pandas.util.testing.assert_produces_warni... |
Artisense-ai/libartipy | [
"7a6a7736637c106e7e9c6763ec8c1dea64db4b01"
] | [
"libartipy/pointcloud/pypcd.py"
] | [
"\"\"\"\nRead and write PCL .pcd files in python.\ndimatura@cmu.edu, 2013-2018\n\n- TODO better API for wacky operations.\n- TODO add a cli for common operations.\n- TODO deal properly with padding\n- TODO deal properly with multicount fields\n- TODO better support for rgb nonsense\n\"\"\"\n\nimport re\nimport stru... | [
[
"numpy.concatenate",
"numpy.array",
"numpy.savetxt",
"numpy.asarray",
"numpy.zeros",
"numpy.ascontiguousarray",
"numpy.copy",
"numpy.loadtxt",
"numpy.fromstring",
"numpy.dtype",
"numpy.rec.fromarrays"
]
] |
NobuoTsukamoto/librealsense | [
"bc0910f8ba3c33307ff247a29dd2b9e9ef1b269d"
] | [
"wrappers/tensorflow/example5 - denoise.py"
] | [
"import pyrealsense2 as rs\nimport numpy as np\nimport cv2\nfrom tensorflow import keras\nimport time, sys\n\n# Configure depth and color streams\npipeline = rs.pipeline()\nconfig = rs.config()\nconfig.enable_stream(rs.stream.depth, 848, 480, rs.format.z16, 30)\nconfig.enable_stream(rs.stream.infrared, 1, 848, 480,... | [
[
"numpy.max",
"numpy.array",
"numpy.zeros",
"numpy.min",
"tensorflow.keras.models.load_model",
"numpy.stack",
"numpy.hstack"
]
] |
jrade/JrBoost | [
"427300477b5afc4e36896a6e028095d1de9e38d3"
] | [
"Python/example/higgs.py"
] | [
"# Copyright 2021 Johan Rade <johan.rade@gmail.com>.\r\n# Distributed under the MIT license.\r\n# (See accompanying file License.txt or copy at https://opensource.org/licenses/MIT)\r\n\r\nimport datetime, gc, math, os, random, time\r\nimport numpy as np\r\nimport pandas as pd\r\nimport jrboost\r\n\r\nPROFILE = j... | [
[
"numpy.zeros",
"pandas.concat",
"numpy.sum",
"pandas.DataFrame",
"numpy.where",
"pandas.Series",
"pandas.read_csv",
"numpy.empty_like"
]
] |
basaks/landshark | [
"87ec1fada74addd58f37bdaf3b1adbc10b1544b2"
] | [
"landshark/dataprocess.py"
] | [
"\"\"\"Process training and query data.\"\"\"\n\n# Copyright 2019 CSIRO (Data61)\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\... | [
[
"numpy.zeros_like",
"numpy.zeros",
"numpy.rollaxis",
"numpy.ma.MaskedArray",
"numpy.vstack"
]
] |
JANHMS/CytoPy | [
"8537d707fa25645b55b4ec1e25fff9f19847fb1b"
] | [
"cytopy/tests/test_geometry.py"
] | [
"from cytopy.data.geometry import PopulationGeometry, ThresholdGeom, PolygonGeom, create_polygon, \\\n polygon_overlap, create_convex_hull, probablistic_ellipse, inside_ellipse\nfrom shapely.geometry import Polygon\nfrom sklearn.datasets import make_blobs\nfrom sklearn.mixture import GaussianMixture\nimport nump... | [
[
"numpy.max",
"numpy.quantile",
"numpy.array",
"numpy.random.normal",
"numpy.array_equal",
"sklearn.datasets.make_blobs",
"numpy.random.choice",
"numpy.min",
"sklearn.mixture.GaussianMixture"
]
] |
sanghun3819/LQM | [
"a0f4d061c5f1486b43ddd884c37e651c6c8b16e7"
] | [
"mmdet/core/bbox/assigners/atss_assigner.py"
] | [
"import torch\n\nfrom ..builder import BBOX_ASSIGNERS\nfrom ..iou_calculators import build_iou_calculator\nfrom .assign_result import AssignResult\nfrom .base_assigner import BaseAssigner\n\n\n@BBOX_ASSIGNERS.register_module()\nclass ATSSAssigner(BaseAssigner):\n \"\"\"Assign a corresponding gt bbox or backgroun... | [
[
"torch.nonzero",
"torch.cat",
"torch.stack",
"torch.arange",
"torch.full_like"
]
] |
jfblanchard/optical-tools | [
"25ce0f2238e1c22b6694d00d359e4243a33db30b"
] | [
"read_ohara.py"
] | [
"# -*- coding: utf-8 -*-\n\"\"\"\nParse the ohara downloaded catalog (csv format), and create a new cleaned up\ndata frame with glass type and sellmeier coeffs for all glass types. Output \nin json format.\n\nOhara download version 20171130\n\nCredits: Hover text snippet found here: \nhttps://stackoverflow.com/que... | [
[
"pandas.to_pickle",
"matplotlib.pyplot.gca",
"pandas.DataFrame",
"matplotlib.pyplot.xlabel",
"matplotlib.pyplot.title",
"matplotlib.pyplot.subplots",
"matplotlib.pyplot.show",
"matplotlib.pyplot.ylabel",
"matplotlib.pyplot.scatter",
"pandas.read_csv"
]
] |
ar4/smii | [
"b7eee03f2a4c8f56f6dde61738e8aa1090621ba3"
] | [
"smii/modeling/setup.py"
] | [
"#!/usr/bin/env python\ndef configuration(parent_package='', top_path=None):\n from numpy.distutils.misc_util import Configuration\n config = Configuration('modeling', parent_package, top_path)\n config.add_subpackage('propagators')\n config.add_subpackage('store_wavefield')\n config.add_subpackage('... | [
[
"numpy.distutils.core.setup",
"numpy.distutils.misc_util.Configuration"
]
] |
njcuk9999/apero-drs | [
"83b043e9f277a011b03e0227c77307961b200901"
] | [
"apero/recipes/nirps_ha/cal_preprocess_nirps_ha.py"
] | [
"#!/usr/bin/env python3\n# -*- coding: utf-8 -*-\n\"\"\"\n\n# CODE DESCRIPTION HERE\n\nCreated on 2019-03-05 16:38\n@author: ncook\nVersion 0.0.1\n\"\"\"\nimport numpy as np\nimport os\n\nfrom apero import core\nfrom apero import lang\nfrom apero.core import constants\nfrom apero.science import preprocessing as pp\... | [
[
"numpy.array",
"numpy.roll"
]
] |
faridrashidi/trisicell | [
"4db89edd44c03ccb6c7d3477beff0079c3ff8035"
] | [
"trisicell/tl/partition_function/_clt_sampler.py"
] | [
"import copy\nfrom decimal import Decimal\n\nimport numpy as np\nimport numpy.linalg as la\nfrom scipy.special import softmax\nfrom sklearn.metrics.pairwise import pairwise_distances\n\n\ndef draw_sample_clt(P, greedy, c=1, coef=2):\n r\"\"\"\n Draw sample clt.\n\n :param P:\n :param greedy:\n :param... | [
[
"numpy.max",
"numpy.delete",
"scipy.special.softmax",
"numpy.linalg.norm",
"numpy.fill_diagonal",
"numpy.zeros",
"numpy.minimum",
"numpy.isnan",
"numpy.min",
"numpy.float64",
"numpy.unravel_index",
"numpy.argmax",
"sklearn.metrics.pairwise.pairwise_distances"
... |
nicolasanjoran/omnizart | [
"b0e74af39b2e3a312ef32dbf0837626b2e043cb6",
"b0e74af39b2e3a312ef32dbf0837626b2e043cb6"
] | [
"omnizart/patch_cnn/app.py",
"omnizart/patch_cnn/inference.py"
] | [
"import os\nfrom os.path import join as jpath\nfrom datetime import datetime\n\nimport h5py\nimport numpy as np\nimport tensorflow as tf\nfrom mir_eval import sonify\nfrom mir_eval.util import midi_to_hz\nfrom scipy.io.wavfile import write as wavwrite\n\nfrom omnizart.io import write_yaml, write_agg_f0_results\nfro... | [
[
"numpy.array",
"numpy.zeros",
"scipy.io.wavfile.write",
"numpy.abs",
"tensorflow.keras.optimizers.Adam",
"numpy.expand_dims",
"tensorflow.keras.callbacks.EarlyStopping"
],
[
"numpy.concatenate",
"numpy.where",
"numpy.max",
"numpy.expand_dims"
]
] |
murad9001/bluesquall.recurvise_least_squares | [
"83510c575a446ae4be4d031fb16cc42a5724c12f"
] | [
"examples/simple_identification.py"
] | [
"#!/usr/bin/env python\n\"\"\"\nSimple RLS identification example\n=================================\n\n\"\"\"\nimport numpy as np\n\nimport rlspy\n\ndef generate_random_truth_data(order = 3, sigma = 1):\n return np.random.normal(0, sigma, [order, 1])\n\n\ndef generate_random_coupling_matrix(shape = [4, 3]):\n ... | [
[
"numpy.random.normal",
"numpy.dot",
"numpy.empty",
"matplotlib.pyplot.grid",
"matplotlib.pyplot.xlabel",
"numpy.ones",
"numpy.identity",
"matplotlib.pyplot.ylabel",
"numpy.abs",
"matplotlib.pyplot.show"
]
] |
chris142857/dad_final | [
"e791cf85d4eea2da692c59f371518494caf0670d"
] | [
"plotters.py"
] | [
"\"\"\"\n# @Description:\nPlot utilities for face finding applications\n\"\"\"\nimport os\n\nimport matplotlib.pyplot as plt\nimport numpy as np\nfrom matplotlib.collections import LineCollection as lc\nfrom matplotlib.colors import colorConverter\nfrom mpl_toolkits.mplot3d.art3d import Line3DCollection as lc3d\nfr... | [
[
"numpy.random.rand",
"numpy.array_equal",
"numpy.cos",
"numpy.sin",
"matplotlib.pyplot.savefig",
"matplotlib.pyplot.get_cmap",
"matplotlib.pyplot.subplots",
"numpy.save",
"scipy.interpolate.interp1d",
"numpy.zeros",
"matplotlib.pyplot.close",
"matplotlib.pyplot.figu... |
fluxtransport/sunpy | [
"351d3edca97e779179f367670292c95574c7a222"
] | [
"examples/units_and_coordinates/planet_locations.py"
] | [
"\"\"\"\n===================================\nGetting the location of the planets\n===================================\n\nHow to get the position of planetary bodies im the solar system using\n`astropy's solar system ephemeris <http://docs.astropy.org/en/stable/coordinates/solarsystem.html#solar-system-ephemerides>... | [
[
"matplotlib.pyplot.subplot",
"matplotlib.pyplot.show",
"matplotlib.pyplot.figure"
]
] |
AliAzG/triton-inference-server | [
"fbce250035d049d13f32c362e2d76a5cb787da51"
] | [
"src/clients/python/api_v1/examples/simple_shm_string_client.py"
] | [
"#!/usr/bin/env python\n# Copyright (c) 2019-2020, NVIDIA CORPORATION. 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\n# are met:\n# * Redistributions of source code must retain the above copyright\... | [
[
"numpy.ones",
"numpy.arange",
"numpy.subtract",
"numpy.add"
]
] |
weiwang2330/BayesNeuralNet | [
"6be81289d9bc46657a1b14ded440c8160721a464"
] | [
"zhusuan/legacy/variational_legacy.py"
] | [
"#!/usr/bin/env python\n# -*- coding: utf-8 -*-\n\nfrom __future__ import absolute_import\nfrom __future__ import print_function\nfrom __future__ import division\nimport warnings\n\nimport tensorflow as tf\nimport six\nfrom six.moves import zip, map\nfrom tensorflow.python.training import moving_averages\n\nfrom zh... | [
[
"tensorflow.exp",
"tensorflow.constant_initializer",
"tensorflow.ones",
"tensorflow.sqrt",
"tensorflow.to_float",
"tensorflow.control_dependencies",
"tensorflow.stop_gradient",
"tensorflow.one_hot",
"tensorflow.identity",
"tensorflow.python.training.moving_averages.assign_m... |
Felicia56/flavio | [
"ea735bd8febbb961d249eddf338a4960c1fbee69"
] | [
"flavio/statistics/test_probability.py"
] | [
"import unittest\nimport numpy as np\nimport numpy.testing as npt\nimport scipy.stats\nfrom math import pi, sqrt, exp, log\nfrom flavio.statistics.probability import *\nimport itertools\nimport yaml\n\nclass TestProbability(unittest.TestCase):\n def test_multiv_normal(self):\n # test that the rescaling of... | [
[
"numpy.random.normal",
"numpy.array",
"numpy.random.rand",
"numpy.random.seed",
"numpy.sum",
"numpy.testing.assert_array_equal",
"numpy.ones",
"numpy.min",
"numpy.linalg.det",
"numpy.eye",
"numpy.testing.assert_array_almost_equal",
"numpy.arange",
"numpy.linspac... |
bptripp/rp | [
"f076034547f7f8afe0f8aad8d0122f7035ca4ed1"
] | [
"rp/rsa.py"
] | [
"# Gradient descent to find random activity pattern with given representational\n# similarity matrix. This works better than taking steps in null space of similarity\n# matrix.\n\nimport numpy as np\nimport matplotlib.pyplot as plt\nimport tensorflow as tf\n\n\ndef get_random_stimuli(n_stim, dim):\n \"\"\"\n ... | [
[
"numpy.random.rand",
"tensorflow.tensordot",
"numpy.exp",
"tensorflow.clip_by_value",
"tensorflow.global_variables_initializer",
"numpy.linalg.norm",
"tensorflow.diag_part",
"tensorflow.transpose",
"tensorflow.constant",
"matplotlib.pyplot.subplot",
"tensorflow.train.Ad... |
mliang1987/Traveling-Salesman-Project | [
"ed3789e37aafb5d254ce7fdbc512711db3d8351c"
] | [
"code/sa_experiment1b.py"
] | [
"####################################################################################################\n# CSE 6140 - Fall 2019\n# Rodrigo Alves Lima\n# Shichao Liang\n# Jeevanjot Singh\n# Kevin Tynes\n####################################################################################################\n\n\n\"... | [
[
"matplotlib.pyplot.xlabel",
"pandas.DataFrame",
"matplotlib.pyplot.plot",
"matplotlib.pyplot.figure",
"matplotlib.pyplot.gcf",
"matplotlib.pyplot.ylabel"
]
] |
scfurl/conga | [
"eaf7b0a583180a72f7c81f981b29b53781507a12"
] | [
"conga/tcrdist/make_10x_clones_file.py"
] | [
"from .basic import *\nfrom .all_genes import all_genes\n#import parse_tsv\nfrom collections import Counter\nfrom itertools import chain\nimport sys\nimport pandas as pd\nfrom ..util import organism2vdj_type, IG_VDJ_TYPE\n\nMIN_CDR3_LEN = 6 # otherwise tcrdist barfs; actually we could also set this to 5 and be OK\n... | [
[
"pandas.read_csv",
"pandas.concat"
]
] |
jlin27/ClassyVision-1 | [
"113ddb0b66471eb84add9af53751d9067786a7f0"
] | [
"test/tasks_classification_task_test.py"
] | [
"#!/usr/bin/env python3\n# Copyright (c) Facebook, Inc. and its affiliates.\n#\n# This source code is licensed under the MIT license found in the\n# LICENSE file in the root directory of this source tree.\n\nimport copy\nimport shutil\nimport tempfile\nimport unittest\nfrom test.generic.config_utils import get_fast... | [
[
"torch.cuda.is_available"
]
] |
eirikurj/pyXDSM | [
"6c631150f6b78e367127c0b7f4e273c3bb37f6ce"
] | [
"pyxdsm/XDSM.py"
] | [
"from __future__ import print_function\nimport os\nimport numpy as np\nimport json\nimport subprocess\nfrom collections import namedtuple\n\nfrom pyxdsm import __version__ as pyxdsm_version\n\nOPT = \"Optimization\"\nSUBOPT = \"SubOptimization\"\nSOLVER = \"MDA\"\nDOE = \"DOE\"\nIFUNC = \"ImplicitFunction\"\nFUNC =... | [
[
"numpy.arange",
"numpy.empty"
]
] |
Steve-YJ/sagemaker-studio-end-to-end | [
"2227bd22d531b2b41e3abcc4778a3e4d2b7aada8"
] | [
"untitled.py"
] | [
"from pyspark.sql.session import SparkSession\nfrom pyspark.sql.dataframe import DataFrame\n# You may want to configure the Spark Context with the right credentials provider.\nspark = SparkSession.builder.master('local').getOrCreate()\n\nmode = None\n\ndef capture_stdout(func, *args, **kwargs):\n \"\"\"Capture ... | [
[
"pandas.isnull",
"numpy.isinf",
"numpy.count_nonzero",
"numpy.isnan",
"numpy.vectorize",
"numpy.isfinite"
]
] |
sitar777/math-modeling-2022 | [
"cea86c26eac5002f31a69414059e593143598f77"
] | [
"multi-scale-economic-dynamics/control.py"
] | [
"from scipy.integrate import RK45\nimport matplotlib.pyplot as plt\n\n\nCOEFFS_FRANCE = [\n .0221,\n .4608,\n -.0077,\n .5585,\n -2.0733,\n .1453,\n .0067,\n 1.1813,\n -0.51,\n]\n\n\ndef ode_system(t, v):\n coeffs = COEFFS_FRANCE\n\n control = [\n [-0.016, 0],\n [-15, ... | [
[
"scipy.integrate.RK45",
"matplotlib.pyplot.show",
"matplotlib.pyplot.subplots"
]
] |
northcoastmountainrat/Sitchensis | [
"8e292dd91dd915495a04ab0abd9a606db7fd9ab4"
] | [
"StichensisTest/TreeCalcs.py"
] | [
"# -*- coding: utf-8 -*-\r\n\"\"\"\r\nCreated on Fri Jan 13 12:46:48 2017\r\n@author: rdk10\r\n\"\"\"\r\n\r\nimport numpy as np\r\nimport pandas as pd #For storing data as a data.frame\r\n#import os, sys\r\n##import numpy as np\r\n#os.chdir('C:/Users/rdk10/Desktop/ComputerProgramming/Pyth... | [
[
"pandas.Timestamp",
"numpy.isnan"
]
] |
LukeKort/Opp_lite | [
"e47b0a1e38dc1e675663c83dc2d75f4506a859e5"
] | [
"pt_bt/pso.py"
] | [
"# Particle Swarm (Aug. 04, 2021)\n\nimport time\nimport numpy as np\nimport random as rand\nfrom importlib import reload #to reload a previuly loaded file\n\ndef pso(n_particles,n_variables,n_iterations,tolerance,a,b,pso_only_w,pso_only_c1,pso_only_c2):\n\n from random_matrix import radom_generator #random gene... | [
[
"numpy.empty",
"numpy.zeros"
]
] |
wajahatali93/cvlib | [
"2722470f22b44141b989c31acbaa1ec08d694050"
] | [
"cvlib/object_detection.py"
] | [
"import cv2\nimport os\nimport numpy as np\nfrom .utils import download_file\n\ninitialize = True\nnet = None\ndest_dir = os.path.expanduser('~') + os.path.sep + '.cvlib' + os.path.sep + 'object_detection' + os.path.sep + 'yolo' + os.path.sep + 'yolov3'\nclasses = None\nCOLORS = np.random.uniform(0, 255, size=(80, ... | [
[
"numpy.random.uniform",
"numpy.argmax"
]
] |
thunlp/HNRE | [
"ab34ed9849f761d7e69d3dc42e3095d0e567b63c"
] | [
"scripts/initial.py"
] | [
"import numpy as np\nimport os\nimport sys\nimport json\n\ndef makedirs(path):\n if not os.path.exists(path):\n os.makedirs(path)\n\nmakedirs('data/pn/')\nmakedirs('outputs/summary/')\nmakedirs('outputs/ckpt/')\nmakedirs('outputs/logits/')\n\n# folder of training datasets\nif len(sys.argv) > 1:\n data_... | [
[
"numpy.array",
"numpy.reshape",
"numpy.zeros",
"numpy.ones",
"numpy.load",
"numpy.save",
"numpy.arange",
"numpy.random.randint",
"numpy.hstack"
]
] |
btwardow/pytorch-lightning-bolts | [
"4a7b6ffe0fcbeee37f8bac6af1e926469b2052bf"
] | [
"pl_bolts/datamodules/ssl_imagenet_datamodule.py"
] | [
"import os\n\nfrom pytorch_lightning import LightningDataModule\nfrom torch.utils.data import DataLoader\n\nfrom pl_bolts.datasets.imagenet_dataset import UnlabeledImagenet\nfrom pl_bolts.transforms.dataset_normalizations import imagenet_normalization\nfrom pl_bolts.utils import _TORCHVISION_AVAILABLE\nfrom pl_bolt... | [
[
"torch.utils.data.DataLoader"
]
] |
AlSpinks/deephaven-core | [
"19686fb518229fd7e331071205cc56fca42ad943"
] | [
"Integrations/python/test/testTableTools.py"
] | [
"#\n# Copyright (c) 2016-2021 Deephaven Data Labs and Patent Pending\n#\n\n##############################################################################\n# NOTE: the jvm should have been initialized, or this test will certainly fail\n##############################################################################\n\... | [
[
"numpy.array"
]
] |
RavenPillmann/multiagent-particle-envs | [
"466cc6953dfc57a0bfba5c37609db3ee7e2508a8"
] | [
"multiagent/environment.py"
] | [
"import gym\nfrom gym import spaces\nfrom gym.envs.registration import EnvSpec\nimport numpy as np\nfrom multiagent.multi_discrete import MultiDiscrete\nfrom multiagent.scenarios.constants import D_LINE, O_LINE, Q_BACK\n\nNOT_DONE = 0\nQ_BACK_FIRST_DOWN_LINE = 1\nAGENT_OUT_OF_BOUNDS = 2\nD_LINE_REACHED_Q_BACK = 3\n... | [
[
"numpy.array",
"numpy.sin",
"numpy.zeros",
"numpy.sum",
"numpy.random.uniform",
"numpy.argmax",
"numpy.cos",
"numpy.all",
"numpy.linspace"
]
] |
atravitz/toolbox | [
"3c98d1a107110655529caa40f1c768466ce52421"
] | [
"test_toolbox.py"
] | [
"\"\"\"tests for toolbox.py module.\"\"\"\nimport numpy as np\nfrom toolbox import *\nimport unittest\nimport numpy.testing as nptest\nimport os\nimport matplotlib.pyplot as plt\n\nclass PotentialTests(unittest.TestCase):\n def setUp(self):\n self.epsilon = 1.0\n self.sigma = 1.0\n self.R = ... | [
[
"numpy.max",
"numpy.sin",
"numpy.random.standard_normal",
"numpy.array",
"matplotlib.pyplot.savefig",
"matplotlib.pyplot.ylim",
"matplotlib.pyplot.plot",
"matplotlib.pyplot.legend",
"matplotlib.pyplot.figure",
"numpy.abs",
"numpy.linspace"
]
] |
jomorlier/sharpy-1 | [
"9800df617efd046d4c4af048bbab17f88a91e6a8",
"9800df617efd046d4c4af048bbab17f88a91e6a8"
] | [
"tests/linear/goland_wing/test_goland_flutter.py",
"tests/coupled/multibody/fix_node_velocity_wrtA/test_fix_node_velocity_wrtA.py"
] | [
"import numpy as np\nimport os\nimport unittest\nimport cases.templates.flying_wings as wings\nimport sharpy.sharpy_main\nimport sharpy.utils.sharpydir as sharpydir\n\n\nclass TestGolandFlutter(unittest.TestCase):\n\n def setup(self):\n # Problem Set up\n u_inf = 1.\n alpha_deg = 0.\n ... | [
[
"numpy.array",
"numpy.where",
"numpy.abs",
"numpy.sqrt",
"numpy.linalg.eigvals"
],
[
"numpy.array",
"numpy.linspace",
"numpy.zeros"
]
] |
hwalsuklee/compare_gan | [
"d6c5976ba2b9d19dbff42f439c20b48565d10235",
"d6c5976ba2b9d19dbff42f439c20b48565d10235"
] | [
"compare_gan/src/gans/ops.py",
"compare_gan/src/gan_lib_test.py"
] | [
"# coding=utf-8\n# Copyright 2018 Google LLC & Hwalsuk Lee.\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 require... | [
[
"tensorflow.gfile.IsDirectory",
"tensorflow.contrib.layers.batch_norm",
"numpy.random.normal",
"tensorflow.constant_initializer",
"tensorflow.nn.conv2d",
"tensorflow.gfile.Open",
"tensorflow.matmul",
"tensorflow.nn.conv2d_transpose",
"tensorflow.gfile.MakeDirs",
"tensorflow... |
paulstey/polars | [
"5ed1c2de8224311bc4df6c1e8fa5b371a6bc99f6"
] | [
"py-polars/polars/internals/frame.py"
] | [
"\"\"\"\nModule containing logic related to eager DataFrames\n\"\"\"\nimport os\nimport sys\nimport warnings\nfrom io import BytesIO, IOBase, StringIO\nfrom pathlib import Path\nfrom typing import (\n Any,\n BinaryIO,\n Callable,\n Dict,\n Iterable,\n Iterator,\n List,\n Mapping,\n Option... | [
[
"numpy.array",
"numpy.dtype"
]
] |
eamarais/erc-uptrop | [
"d7340ca7ad4be2e9b7e98da0847964c2a532e1ca"
] | [
"uptrop/cloud_slice_no2.py"
] | [
"#!/usr/bin/python\n\n''' Cloud-slicing steps applied to a cluster of data using as input the partial NO2 columns in molecules/m2 and cloud top heights in hPa. \n\nIf successful, the output is NO2 mixing ratios in pptv. Other output is the estimated error on the NO2 mixing ratio and the mean cloud top pressure (hPa... | [
[
"numpy.divide",
"numpy.isnan",
"numpy.add",
"numpy.percentile",
"numpy.mean",
"numpy.nanmin",
"numpy.multiply",
"numpy.std",
"numpy.where",
"numpy.nanmax"
]
] |
edornd/satellite-mib | [
"a4423dc866ecfb77dc62548764917c048006dd8a"
] | [
"utils/loss.py"
] | [
"import torch.nn as nn\nimport torch.nn.functional as F\nimport torch\n\n\ndef get_loss(loss_type):\n if loss_type == 'focal_loss':\n return FocalLoss(ignore_index=255, size_average=True)\n elif loss_type == 'cross_entropy':\n return nn.CrossEntropyLoss(ignore_index=255, reduction='mean')\n\n\nc... | [
[
"torch.nn.functional.binary_cross_entropy_with_logits",
"torch.nn.functional.one_hot",
"torch.log_softmax",
"torch.softmax",
"torch.logsumexp",
"torch.sum",
"torch.mean",
"torch.nn.functional.cross_entropy",
"torch.tensor",
"torch.zeros_like",
"torch.nn.functional.nll_l... |
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