repo_name stringlengths 6 130 | hexsha list | file_path list | code list | apis list |
|---|---|---|---|---|
cdrtm/pyDatView | [
"fe1acacde27d4eafda0b54e455fadfb2d6199cd1"
] | [
"pydatview/tools/signal.py"
] | [
"from __future__ import division\nimport numpy as np\nfrom numpy.random import rand\nimport pandas as pd\n\n\n# --- List of available filters\nFILTERS=[\n {'name':'Moving average','param':100,'paramName':'Window Size','paramRange':[0,100000],'increment':1},\n {'name':'Low pass 1st order','param':1.0,'paramNam... | [
[
"numpy.random.rand",
"numpy.mean",
"numpy.sign",
"numpy.where",
"numpy.cumsum",
"numpy.concatenate",
"pandas.DataFrame",
"numpy.interp",
"matplotlib.pyplot.subplots",
"numpy.arange",
"numpy.nanmedian",
"numpy.delete",
"numpy.zeros",
"numpy.round",
"numpy... |
tedunderwood/fiction | [
"33e2986fecaa3d154b5fdd609146b65d97974275"
] | [
"variation/methodological_experiment.py"
] | [
"#!/usr/bin/env python3\n\n# methodological_experiment.py\n\nimport sys, os, csv\nimport numpy as np\nimport pandas as pd\nimport versatiletrainer2\nimport metaselector\n\nimport matplotlib.pyplot as plt\n\nfrom scipy import stats\n\ndef first_experiment():\n\n sourcefolder = '../data/'\n metadatapath = '../m... | [
[
"numpy.asarray",
"matplotlib.pyplot.matshow",
"numpy.log",
"numpy.sum",
"scipy.stats.spearmanr",
"numpy.mean",
"scipy.stats.pearsonr",
"numpy.tanh",
"matplotlib.pyplot.show",
"pandas.read_csv",
"numpy.arctanh",
"numpy.flatnonzero"
]
] |
ngocpc/Project_Plagiarism_Detection | [
"d06216d2aafa71e52c528f3ae451a49638e9785d"
] | [
"Project_Plagiarism_Detection/source_pytorch/train.py"
] | [
"import argparse\nimport json\nimport os\nimport pandas as pd\nimport torch\nimport torch.optim as optim\nimport torch.nn as nn\nimport torch.utils.data\n\n# imports the model in model.py by name\nfrom model import BinaryClassifier\n\ndef model_fn(model_dir):\n \"\"\"Load the PyTorch model from the `model_dir` d... | [
[
"torch.save",
"torch.from_numpy",
"torch.manual_seed",
"torch.cuda.is_available",
"torch.utils.data.DataLoader",
"torch.load",
"torch.nn.BCELoss",
"torch.utils.data.TensorDataset"
]
] |
grst/diffxpy | [
"8b9ad605cb11d05b58b3e3f4b2c8255c6e98b80c"
] | [
"diffxpy/unit_test/test_pairwise.py"
] | [
"import logging\nimport unittest\nimport numpy as np\nimport pandas as pd\nimport scipy.stats as stats\n\nimport diffxpy.api as de\n\n\nclass _TestPairwiseNull:\n\n noise_model: str\n\n def _prepate_data(\n self,\n n_cells: int,\n n_genes: int,\n n_groups: int\n ... | [
[
"numpy.random.seed",
"numpy.random.uniform",
"numpy.random.randint",
"numpy.round"
]
] |
aljubrmj/CS342-Final-Project | [
"841bab59ca1311faa550c5fce9327a1e65ff5501"
] | [
"planner/regressor/models.py"
] | [
"import torch\nimport torch.nn.functional as F\n\ndef spatial_argmax(logit):\n weights = F.softmax(logit.view(logit.size(0), -1), dim=-1).view_as(logit)\n return torch.stack(((weights.sum(1) * torch.linspace(-1, 1, logit.size(2)).to(logit.device)[None]).sum(1),\n (weights.sum(2) * torch... | [
[
"torch.nn.Linear",
"torch.cat",
"torch.nn.Sequential",
"torch.nn.BatchNorm2d",
"torch.nn.ConvTranspose2d",
"torch.nn.ReLU",
"torch.nn.Conv2d",
"torch.Tensor"
]
] |
Henrynaut/ML | [
"47ca3a67948ed8190a31a57d1e9a803ca532938b"
] | [
"scripts/neural_net_workshop.py"
] | [
"import numpy as np\nimport random\nrandom.seed(200)\n\n# Create Sigmoid Function\ndef sig(inp):\n return (1/(1+np.exp(-1*inp)))\n\n# For Back Propagation, make Desigmoid function\ndef dsig(inp):\n return (1.0-inp)*inp\n\n# Define class for neuron\nclass Neuron:\n def __init__(self,weights,func,dfunc):\n ... | [
[
"numpy.random.uniform",
"numpy.exp"
]
] |
metataro/DirectFeedbackAlignment | [
"7e2cbc3f001ac2290a15440628bb2b97d4ec52ab"
] | [
"network/layers/convolution_im2col.py"
] | [
"import numpy as np\n\nfrom network.activation import Activation\nfrom network.layer import Layer\nfrom network.utils.im2col_cython import im2col_cython, col2im_cython\n\n\nclass Convolution(Layer):\n def __init__(self, filter_shape, stride, padding, dropout_rate: float = 0, activation: Activation = None,\n ... | [
[
"numpy.dot",
"numpy.random.rand",
"numpy.zeros",
"numpy.sum",
"numpy.random.uniform",
"numpy.size",
"numpy.sqrt"
]
] |
NingAnMe/snow_cover_of_remote_sensing | [
"aabd0f4754eb5200203fc8a90f06b603dcd260a8"
] | [
"lib/pb_io.py"
] | [
"# coding: utf-8\nimport errno\nimport os\nimport random\nimport re\nfrom contextlib import contextmanager\n\nimport h5py\nimport numpy as np\nimport time\nimport yaml\nfrom datetime import datetime\n\n\ndef write_yaml_file(yaml_dict, file_yaml):\n path_yaml = os.path.dirname(file_yaml)\n if not os.path.isdir... | [
[
"numpy.array",
"numpy.loadtxt"
]
] |
ekyuho/tensorflow | [
"e0b721190502346e5485010c8db78339e08c5951"
] | [
"tensorflow/contrib/batching/python/ops/batch_ops.py"
] | [
"# Copyright 2017 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.contrib.batching.ops.gen_batch_ops.unbatch",
"tensorflow.python.framework.ops.RegisterGradient",
"tensorflow.contrib.batching.ops.gen_batch_ops.batch",
"tensorflow.python.framework.ops.name_scope",
"tensorflow.python.platform.resource_loader.get_path_to_datafile"
]
] |
xingkongxiaxia/xx | [
"ce51d75406592d6bc25bb803f773f0788496fd97",
"ce51d75406592d6bc25bb803f773f0788496fd97"
] | [
"recbole/model/knowledge_aware_recommender/kgnnls.py",
"recbole/model/knowledge_aware_recommender/kgcn.py"
] | [
"# -*- coding: utf-8 -*-\n# @Time : 2020/10/3\n# @Author : Changxin Tian\n# @Email : cx.tian@outlook.com\n\nr\"\"\"\nKGNNLS\n################################################\n\nReference:\n Hongwei Wang et al. \"Knowledge-aware Graph Neural Networks with Label Smoothness Regularization\n for Recommender Sy... | [
[
"torch.nn.Linear",
"torch.cat",
"torch.nn.ModuleList",
"torch.ones",
"torch.logical_and",
"torch.nn.BCEWithLogitsLoss",
"torch.reshape",
"torch.mul",
"torch.nn.Softmax",
"torch.unsqueeze",
"torch.logical_not",
"torch.index_select",
"torch.nn.Embedding",
"num... |
a414351664/Bert-THUCNews | [
"a20749225091533b530f0e539bfaacbd3524fe99"
] | [
"data/cnews_loader_bert.py"
] | [
"# coding: utf-8\n\nimport sys\nfrom collections import Counter\n\nimport numpy as np\nimport tensorflow.contrib.keras as kr\nimport tensorflow as tf\nif sys.version_info[0] > 2:\n is_py3 = True\nelse:\n # reload(sys)\n sys.setdefaultencoding(\"utf-8\")\n is_py3 = False\n\n\ndef native_word(word, encodi... | [
[
"tensorflow.exp",
"numpy.array",
"tensorflow.concat",
"tensorflow.reshape",
"numpy.arange",
"tensorflow.reduce_sum",
"tensorflow.random_normal"
]
] |
alexeypechorin/tibetan-transductive | [
"e2356d5c0a7cbc2f2359d9cf5b6b18729fecd8de"
] | [
"train.py"
] | [
"import os\nimport click\nimport numpy as np\nfrom tqdm import tqdm\nfrom models.model_loader import load_model\nfrom torchvision.transforms import Compose\nfrom dataset.data_transform import Resize, Rotation, ElasticAndSine, ColorGradGausNoise, AddWidth, Normalize, ToGray, OnlyElastic, OnlySine, ColorGrad, ColorGa... | [
[
"torch.nn.NLLLoss",
"torch.zeros",
"numpy.array",
"torch.autograd.Variable",
"numpy.exp",
"numpy.mean",
"torch.ones",
"torch.utils.data.DataLoader"
]
] |
davideganna/NBA_Bet | [
"dba00542b8ed63a5a7290f25209270b32d18fb86"
] | [
"NBABet/Telegram.py"
] | [
"# --------------------- Telegram.py --------------------------------- #\n# Allows the integration with Telegram Bot.\n# ------------------------------------------------------------------- #\nfrom numpy.core.fromnumeric import around, std\nimport requests\nimport Elo\nfrom Models import Models\nimport Helper\nimpor... | [
[
"numpy.core.fromnumeric.around",
"pandas.read_csv"
]
] |
Struth-Rourke/twitter_flask_app | [
"f73ad147f216ad77f8010ef6c02da4784dbfa9c8"
] | [
"twitter_app/iris_classifier.py"
] | [
"# twitter_app/iris_classifier.py\n\nimport os\nimport pickle\n\nfrom sklearn.datasets import load_iris\nfrom sklearn.linear_model import LogisticRegression \n\nMODEL_FILEPATH = os.path.join(os.path.dirname(__file__), \"..\", \"models\", \"latest_model.pkl\")\n\ndef train_and_save_model():\n print(\"TRAINING THE... | [
[
"sklearn.linear_model.LogisticRegression",
"sklearn.datasets.load_iris"
]
] |
patrickctrf/scikit-learn | [
"d6735f4851d828984a0517de954b9b88c74919fe"
] | [
"examples/applications/plot_cyclical_feature_engineering.py"
] | [
"\"\"\"\n================================\nTime-related feature engineering\n================================\n\nThis notebook introduces different strategies to leverage time-related features\nfor a bike sharing demand regression task that is highly dependent on business\ncycles (days, weeks, months) and yearly se... | [
[
"sklearn.linear_model.RidgeCV",
"sklearn.preprocessing.FunctionTransformer",
"sklearn.model_selection.cross_validate",
"sklearn.compose.ColumnTransformer",
"sklearn.preprocessing.MinMaxScaler",
"pandas.concat",
"numpy.cos",
"numpy.logspace",
"numpy.sin",
"matplotlib.pyplot.... |
arminbahl/mutant_zebrafish_behavior | [
"17bee04b35c23b0f93fcecac9758e6ba19872be1"
] | [
"armin_analysis/model_tests.py"
] | [
"import pylab as pl\nfrom get_fish_info import get_fish_info\nfrom fit_integrator_model import get_model_result, get_target_result\nimport numpy as np\nfrom pathlib import Path\nimport gmm_model_fit\nimport pandas as pd\nfrom pymoo.factory import get_problem, get_visualization, get_decomposition\n\n# import random\... | [
[
"numpy.argmin",
"numpy.percentile",
"pandas.DataFrame",
"numpy.load",
"pandas.read_hdf"
]
] |
pjshu/QQZoneMood | [
"bc949855271a4d9944e1501599755cfdfdb8cfd6"
] | [
"src/analysis/TrainMood.py"
] | [
"from src.analysis.QQZoneAnalysis import QQZoneAnalysis\nimport json\n\nfrom src.util.constant import BASE_DIR\nfrom src.util.util import get_mktime2\nimport pandas as pd\nimport re\nfrom src.analysis.SentimentClassify import SentimentClassify\n\n\nclass TrainMood(QQZoneAnalysis):\n \"\"\"\n 生成各种训练需要的数据集\n ... | [
[
"pandas.DataFrame",
"pandas.read_csv",
"pandas.merge"
]
] |
deepkashiwa/DeepUrbanEvent | [
"3356ee3030893e2806d23541b2650ec73dab3075"
] | [
"meshdynamic/meshDynamic-Density.py"
] | [
"import csv\r\nimport numpy as np\r\nimport os\r\nimport sys\r\nimport time\r\nimport jismesh.utils as ju\r\nimport pandas as pd\r\n\r\ncurPath = os.path.abspath(os.path.dirname(__file__))\r\nrootPath = os.path.split(curPath)[0]\r\nsys.path.append(rootPath)\r\n\r\nfrom common.datastructure.Point import Point\r\nfro... | [
[
"numpy.max",
"numpy.array",
"numpy.zeros",
"numpy.log",
"numpy.load",
"numpy.save",
"numpy.random.shuffle",
"numpy.swapaxes",
"numpy.log10",
"pandas.read_csv"
]
] |
zhao-jin/Reinforcement-learning-with-tensorflow | [
"a4a816f1570be55016909f703fb1fd1ceae9c5a0"
] | [
"contents/2_Q_Learning_maze/maze_env.py"
] | [
"\"\"\"\nReinforcement learning maze example.\n\nRed rectangle: explorer.\nBlack rectangles: hells [reward = -1].\nYellow bin circle: paradise [reward = +1].\nAll other states: ground [reward = 0].\n\nThis script is the environment part of this example. The RL is in RL_brain.... | [
[
"numpy.array"
]
] |
tilmanbeck/adapter-transformers | [
"ed42ced6983891060bb160c5c4f2c5d64d2c205c",
"ed42ced6983891060bb160c5c4f2c5d64d2c205c"
] | [
"src/transformers/trainer_tf.py",
"src/transformers/modeling_tf_transfo_xl.py"
] | [
"\"\"\"Tensorflow trainer class.\"\"\"\n\nimport logging\nimport math\nimport os\nfrom typing import Callable, Dict, Optional\n\nimport numpy as np\nimport tensorflow as tf\n\nfrom .modeling_tf_utils import TFPreTrainedModel, shape_list\nfrom .optimization_tf import GradientAccumulator, create_optimizer\nfrom .trai... | [
[
"tensorflow.convert_to_tensor",
"tensorflow.keras.losses.get",
"tensorflow.summary.trace_on",
"tensorflow.train.CheckpointManager",
"tensorflow.summary.scalar",
"tensorflow.summary.experimental.set_step",
"tensorflow.gradients",
"tensorflow.cast",
"tensorflow.reshape",
"ten... |
wdempsey/sense2stop-lvm | [
"ea44d5f9199382d30e4c5a5ff4bd524313ceb5b2"
] | [
"methods/latent-pp-models-mem-rjmcmc.py"
] | [
"#%%\nimport pymc3 as pm\nimport arviz as az\nimport pandas as pd\nimport numpy as np\nfrom datetime import datetime\nfrom scipy import stats\nimport os\nimport pickle\nfrom scipy import special\nimport theano.tensor as tt\n\n## List down file paths\nexec(open('../env_vars.py').read())\ndir_data = os.environ['dir_d... | [
[
"numpy.max",
"numpy.log",
"numpy.min",
"numpy.exp",
"matplotlib.pyplot.figure",
"numpy.where",
"numpy.repeat",
"numpy.unique"
]
] |
Drishttii/pyprobml | [
"30b120e7d4f81ade55c10250193d98398040574b"
] | [
"scripts/knn_voronoi_plot.py"
] | [
"import numpy as np\nimport matplotlib.pyplot as plt\n\nimport pyprobml_utils as pml\n\nfrom scipy.spatial import KDTree, Voronoi, voronoi_plot_2d\n\nnp.random.seed(42)\ndata = np.random.rand(25, 2)\nvor = Voronoi(data)\n\nprint('Using scipy.spatial.voronoi_plot_2d, wait...')\nvoronoi_plot_2d(vor)\nxlim = plt.xlim(... | [
[
"scipy.spatial.Voronoi",
"numpy.random.rand",
"matplotlib.pyplot.xlim",
"scipy.spatial.voronoi_plot_2d",
"numpy.random.seed",
"matplotlib.pyplot.ylim",
"matplotlib.pyplot.plot",
"matplotlib.pyplot.figure",
"scipy.spatial.KDTree",
"matplotlib.pyplot.show",
"numpy.linspac... |
sofiapasquini/Code-Astro-Group-23-Project | [
"97dcbaf1b04822d56582e51332666dc5045e1154"
] | [
"exampledoc/docs/Extractor.py"
] | [
"#define functions that will extract the data from SDSS based on an input RA/DEC\n\nfrom astroquery.sdss import SDSS\nfrom astropy import coordinates as coords\nimport pandas as pd \nfrom astroquery.ned import Ned \nimport matplotlib.pyplot as plt\nfrom astropy.convolution import convolve, Box1DKernel\nimport numpy... | [
[
"numpy.add",
"matplotlib.pyplot.xlabel",
"matplotlib.pyplot.plot",
"matplotlib.pyplot.figure",
"numpy.subtract",
"matplotlib.pyplot.fill_between",
"matplotlib.pyplot.ylabel",
"matplotlib.pyplot.show"
]
] |
nasyxx/nnUNet | [
"92d5f2352349eed278e22f7a38cb86b0fccd7c75",
"92d5f2352349eed278e22f7a38cb86b0fccd7c75"
] | [
"nnunet/training/network_training/competitions_with_custom_Trainers/MMS/nnUNetTrainerV2_MMS.py",
"nnunet/evaluation/model_selection/summarize_results_in_one_json.py"
] | [
"import torch\nfrom nnunet.network_architecture.generic_UNet import Generic_UNet\nfrom nnunet.network_architecture.initialization import InitWeights_He\nfrom nnunet.training.network_training.nnUNet_variants.data_augmentation.nnUNetTrainerV2_insaneDA import \\\n nnUNetTrainerV2_insaneDA\nfrom nnunet.utilities.nd_... | [
[
"torch.cuda.is_available"
],
[
"numpy.nanmean",
"numpy.mean",
"numpy.nanmedian",
"numpy.unique"
]
] |
bjtuyxc/detectron2 | [
"ebb9f8c9166765c508f8ac53d9ed2004739b28d1"
] | [
"tests/test_visualizer.py"
] | [
"# -*- coding: utf-8 -*-\n# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved\n# File:\n\nimport numpy as np\nimport unittest\nimport torch\n\nfrom detectron2.data import MetadataCatalog\nfrom detectron2.structures import Instances, RotatedBoxes, BoxMode\nfrom detectron2.utils.visualizer import V... | [
[
"numpy.concatenate",
"torch.rand",
"numpy.zeros_like",
"torch.zeros",
"numpy.random.rand",
"numpy.asarray",
"torch.FloatTensor",
"torch.from_numpy",
"torch.randint",
"numpy.random.randint"
]
] |
mangye16/ReID-Label-Noise | [
"89aa11f68c275a0bcff232d9a5c3ae152c9276af"
] | [
"PNet/train_pnet.py"
] | [
"# -*- coding: UTF-8 -*-\nfrom __future__ import print_function, division\n\nimport torch\nimport torch.nn as nn\nimport torch.nn.functional as F\nimport torch.optim as optim\nfrom torch.optim import lr_scheduler\nfrom torch.autograd import Variable\nfrom torchvision import datasets, models, transforms\n\nfrom tens... | [
[
"matplotlib.use",
"numpy.clip",
"torch.optim.lr_scheduler.StepLR",
"numpy.exp",
"numpy.save",
"torch.manual_seed",
"torch.cuda.set_device",
"torch.cuda.is_available",
"torch.LongTensor",
"torch.utils.data.DataLoader",
"numpy.argsort",
"torch.load",
"torch.nn.Cro... |
mukulbalodi/rasa | [
"3126ef1148c165f2402f3c7203138d429e46c68c"
] | [
"rasa/nlu/classifiers/diet_classifier.py"
] | [
"from __future__ import annotations\nimport copy\nimport logging\nfrom collections import defaultdict\nfrom pathlib import Path\nfrom rasa.nlu.featurizers.featurizer import Featurizer\n\nimport numpy as np\nimport scipy.sparse\nimport tensorflow as tf\n\nfrom typing import Any, Dict, List, Optional, Text, Tuple, Un... | [
[
"tensorflow.keras.metrics.Mean",
"numpy.array",
"tensorflow.shape",
"tensorflow.concat",
"tensorflow.reduce_any",
"tensorflow.cast",
"tensorflow.squeeze",
"tensorflow.reduce_sum",
"tensorflow.keras.optimizers.Adam",
"tensorflow.pad",
"tensorflow.boolean_mask",
"nump... |
tucaiyong/tensorflow | [
"3cc3c87f375f1bc292bd58db4928b810ac888bc6",
"3cc3c87f375f1bc292bd58db4928b810ac888bc6",
"3cc3c87f375f1bc292bd58db4928b810ac888bc6"
] | [
"tensorflow/contrib/linalg/python/ops/linear_operator_kronecker.py",
"tensorflow/contrib/eager/python/tfe.py",
"tensorflow/contrib/distributions/python/ops/sinh_arcsinh.py"
] | [
"# Copyright 2018 The TensorFlow Authors. All Rights Reserved.\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n# http://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless requ... | [
[
"tensorflow.python.ops.array_ops.matrix_transpose",
"tensorflow.python.framework.tensor_shape.TensorShape",
"tensorflow.python.framework.errors.InvalidArgumentError",
"tensorflow.python.ops.check_ops.assert_proper_iterable",
"tensorflow.python.framework.common_shapes.broadcast_shape",
"ten... |
hwangjt/blue | [
"609defbe476c86a4a2eddd12977b47e649ea7f50"
] | [
"openmdao/test_suite/components/cycle_comps.py"
] | [
"\"\"\"Components for use in `CycleGroup`. For details, see `CycleGroup`.\"\"\"\nfrom __future__ import division, print_function\n\nfrom six.moves import range\n\nimport numpy as np\nimport scipy.sparse as sparse\n\nimport unittest\n\nfrom openmdao.core.explicitcomponent import ExplicitComponent\n\n\nPSI = 1.\n\n_v... | [
[
"numpy.sin",
"numpy.array",
"numpy.dot",
"numpy.zeros",
"numpy.ones",
"numpy.eye",
"numpy.prod",
"numpy.cos",
"numpy.sqrt",
"numpy.outer",
"numpy.abs",
"scipy.sparse.csr_matrix",
"numpy.atleast_2d"
]
] |
johnwlambert/argoverse_cbgs_kf_tracker | [
"9268cb6dd9844f80eb107a0cc5e77e880d3b3e76"
] | [
"ab3dmot.py"
] | [
"#!/usr/bin/env python3\n\nfrom filterpy.kalman import KalmanFilter\nimport matplotlib.pyplot as plt\nimport numpy as np\nimport pdb\nfrom sklearn.utils.linear_assignment_ import linear_assignment\nimport sys\nimport time\n\nfrom transform_utils import convert_3dbox_to_8corner\nfrom iou_utils import compute_iou_2d_... | [
[
"numpy.concatenate",
"numpy.array",
"numpy.isnan",
"numpy.empty",
"numpy.ma.masked_invalid",
"numpy.where",
"sklearn.utils.linear_assignment_.linear_assignment",
"numpy.stack"
]
] |
vinnamkim/segmentation_models.pytorch | [
"f967ded34df6fb536e8e8cba9b6491ae63b939f5"
] | [
"segmentation_models_pytorch/encoders/zerocenter.py"
] | [
"\nimport torch\nimport torch.nn as nn\n#from .utils import load_state_dict_from_url\nfrom .utils import zerocenter\n\n__all__ = ['ResNet', 'resnet18', 'resnet34', 'resnet50', 'resnet101',\n 'resnet152', 'resnext50_32x4d', 'resnext101_32x8d',\n 'wide_resnet50_2', 'wide_resnet101_2']\n\n\nmodel_u... | [
[
"torch.nn.Linear",
"torch.flatten",
"torch.nn.MaxPool2d",
"torch.nn.Sequential",
"torch.nn.init.constant_",
"torch.nn.init.kaiming_normal_",
"torch.nn.ReLU",
"torch.nn.Conv2d",
"torch.nn.AdaptiveAvgPool2d"
]
] |
Zeng-WH/ML2020 | [
"f467a6260cd782968696950ef74f3780933cdcdd"
] | [
"CNN/code/filter_visualiton.py"
] | [
"import os\r\nimport sys\r\nimport argparse\r\nimport numpy as np\r\nfrom PIL import Image\r\nimport matplotlib.pyplot as plt\r\nimport torch\r\nimport torch.nn as nn\r\nimport torch.nn.functional as F\r\nfrom torch.optim import Adam\r\nfrom torch.utils.data import Dataset\r\nimport torchvision.transforms as transf... | [
[
"torch.optim.Adam"
]
] |
aaron8tang/h2o4gpu | [
"602275375cb0dfb4acd070a8c86c3ded0bef1156"
] | [
"src/interface_py/h2o4gpu/solvers/factorization.py"
] | [
"# - * - encoding : utf - 8 - * -\n# pylint: disable=fixme, line-too-long\n\"\"\"\nMatrix factorization solver.\n\n:copyright: 2017-2019 H2O.ai, Inc.\n:license: Apache License Version 2.0 (see LICENSE for details)\n\"\"\"\nimport numpy as np\nimport scipy\nimport scipy.sparse\n\n\ndef _get_sparse_matrixes(X):\n ... | [
[
"scipy.sparse.coo_matrix",
"scipy.sparse.isspmatrix_csc",
"numpy.random.RandomState",
"scipy.sparse.isspmatrix_csr",
"numpy.sum",
"numpy.take",
"scipy.sparse.isspmatrix_coo"
]
] |
fullmoonhalf/SemGCN | [
"ce1dce98f8b7cc600ba7e733d17d71192c24b596",
"ce1dce98f8b7cc600ba7e733d17d71192c24b596"
] | [
"data/prepare_data_2d_h36m_sh.py",
"models/sem_ch_graph_conv.py"
] | [
"from __future__ import print_function, absolute_import, division\n\nimport argparse\nimport os\nimport zipfile\nimport tarfile\nimport numpy as np\nimport h5py\nfrom glob import glob\nfrom shutil import rmtree\n\nimport sys\n\nsys.path.append('../')\n\nfrom common.h36m_dataset import H36M_NAMES\n\noutput_filename_... | [
[
"numpy.array",
"numpy.savez_compressed"
],
[
"torch.zeros",
"torch.nn.init.constant_",
"torch.nn.init.xavier_uniform_",
"torch.ones_like",
"torch.nn.functional.softmax",
"torch.matmul"
]
] |
exoplanetvetting/DAVE | [
"45ba97b7b535ad26dd555c33c963c6224a9af23c",
"aea19a30d987b214fb4c0cf01aa733f127c411b9"
] | [
"lpp/newlpp/lppTransform.py",
"diffimg/psffit.py"
] | [
"#!/usr/bin/env python2\n# -*- coding: utf-8 -*-\n\"\"\"\nCreated on Thu Aug 23 20:32:12 2018\nFunctions to correctly fold and bin a light curve.\nCalculate the lpp metric: transform to lower dimensions, knn\n\nDepends on class from reading in a previously created LPP metric Map\n\nDepends on reading in the light c... | [
[
"numpy.array",
"numpy.isnan",
"numpy.percentile",
"numpy.ones",
"numpy.min",
"numpy.mean",
"numpy.shape",
"numpy.stack",
"numpy.arange",
"numpy.argsort",
"numpy.floor",
"numpy.log10",
"numpy.linspace",
"numpy.nanmedian",
"numpy.mod",
"numpy.nanstd"
... |
chenchy/onsets-and-frames | [
"af7ac2d2e65cba1f6442b81317328d96b3700b26"
] | [
"transcribe.py"
] | [
"import argparse\nimport os\nimport sys\n\nimport numpy as np\nimport soundfile\nfrom mir_eval.util import midi_to_hz\n\nfrom onsets_and_frames import *\n\n\ndef load_and_process_audio(flac_path, sequence_length, device):\n\n random = np.random.RandomState(seed=42)\n\n audio, sr = soundfile.read(flac_path, dt... | [
[
"numpy.random.RandomState"
]
] |
britig/S2RL-Policies | [
"b9c74b7f5efec225920c09f7e8e82d8555d61bd9"
] | [
"ppoPolicyTraining.py"
] | [
"\"\"\"\r\n\tThe file contains the PPO class to train with.\r\n\tNOTE: All \"ALG STEP\"s are following the numbers from the original PPO pseudocode.\r\n\t\t\tIt can be found here: https://spinningup.openai.com/en/latest/_images/math/e62a8971472597f4b014c2da064f636ffe365ba3.svg\r\n\"\"\"\r\n\r\nimport gym\r\n\r\nimp... | [
[
"torch.distributions.Categorical",
"torch.nn.MSELoss",
"torch.min",
"numpy.sum",
"numpy.mean",
"torch.clamp",
"torch.manual_seed",
"torch.full",
"torch.tensor",
"torch.load",
"torch.diag",
"torch.distributions.MultivariateNormal",
"torch.exp",
"torch.utils.t... |
kaylajanos1/TeamSpark-L3Detection | [
"ecc2b4ca3588f989add309439feac33014447a32"
] | [
"detection.py"
] | [
"#Importing Libraries \nimport os\nimport csv\nimport sys, getopt\n\nimport uuid\n\nimport SimpleITK as sitk\nimport cv2 \nimport numpy as np\nimport tensorflow as tf\nfrom flask import Flask, flash, request, redirect, render_template\nfrom flask import jsonify\nfrom flask import send_from_directory\nfrom flask_mat... | [
[
"numpy.max",
"tensorflow.get_default_graph",
"pandas.DataFrame",
"tensorflow.Session",
"numpy.min",
"tensorflow.ConfigProto",
"numpy.argmax",
"tensorflow.python.keras.backend.set_session",
"numpy.clip"
]
] |
cisc474projectgroup/cartpole-q-learning | [
"d7215990c8bdf8c1ff20cdfa3a7530e1a2c641b5"
] | [
"agent.py"
] | [
"import random\nimport copy\nfrom collections import defaultdict\nfrom collections import deque\nfrom collections import namedtuple\nfrom matplotlib import pyplot as plt\nimport numpy as np\n\n\nclass Q():\n\n def __init__(self, n_actions, observation_space, bin_size, low_bound=None, high_bound=None, initial_mea... | [
[
"numpy.random.choice",
"matplotlib.pyplot.xlabel",
"matplotlib.pyplot.title",
"matplotlib.pyplot.plot",
"numpy.random.randn",
"numpy.mean",
"numpy.digitize",
"matplotlib.pyplot.ylabel",
"numpy.append",
"matplotlib.pyplot.show",
"numpy.random.random"
]
] |
andycasey/stellar-twins | [
"9b3cfbf608e3e15a2358bbd33aa5ae21cfc1d0dd"
] | [
"data/check_apogee_spectra.py"
] | [
"#!/usr/bin/env python\n# -*- coding: utf-8 -*-\n\n\"\"\" Test the quoted APOGEE uncertainties from individual (rebinned) spectra. \"\"\"\n\n__author__ = \"Andy Casey <arc@ast.cam.ac.uk>\"\n\nimport numpy as np\nimport matplotlib.pyplot as plt\nfrom astropy.io import fits\nfrom glob import glob\nfrom itertools impo... | [
[
"numpy.array",
"numpy.median",
"matplotlib.pyplot.close",
"numpy.exp",
"matplotlib.pyplot.subplots",
"numpy.trapz",
"numpy.sqrt",
"numpy.abs",
"numpy.isfinite"
]
] |
ctrl-z-9000-times/NEUWON | [
"ed5c13f8cecfd638dd0952d231c36f48073a64a6"
] | [
"neuwon/database/examples/life/model.py"
] | [
"from neuwon.database import Database\nimport numpy as np\nimport numba\n\nclass GameOfLife:\n\n class _CellBaseClass:\n __slots__ = ()\n @classmethod\n def _add_to_database(cls, database):\n cell_data = database.add_class(\"Cell\", cls)\n cell_data.add_attribute(\"coor... | [
[
"numpy.array",
"numpy.random.uniform",
"numpy.empty"
]
] |
zean-wen/mmgnn_textvqa | [
"2cfe82ed54610975a1d4937f2032e5f4565ecbe7"
] | [
"pythia/utils/checkpoint.py"
] | [
"# Copyright (c) Facebook, Inc. and its affiliates.\nimport os\nimport warnings\n\n# import git\nimport torch\nimport yaml\n\nfrom pythia.common.registry import registry\nfrom pythia.utils.distributed_utils import is_main_process, synchronize\nfrom pythia.utils.general import (ckpt_name_from_core_args,\n ... | [
[
"torch.save",
"torch.load"
]
] |
DataViva/dataviva-scripts | [
"1e36f11e2849c33b8118cefe1755d312b19c0ecd",
"1e36f11e2849c33b8118cefe1755d312b19c0ecd",
"1e36f11e2849c33b8118cefe1755d312b19c0ecd"
] | [
"scripts/secex_monthly/_pci_wld_eci.py",
"commands/load_metadata/countries.py",
"commands/load_metadata/territories.py"
] | [
"import sys\nimport pandas as pd\n\ndef pci_wld_eci(eci_file_path, pci_file_path, ymp, ymw, year):\n \n pcis = pd.read_csv(pci_file_path, sep=\"\\t\", compression=\"bz2\", converters={\"hs_id\": str})\n pcis[\"year\"] = int(year)\n pcis[\"month\"] = \"00\"\n pcis = pcis.set_index([\"year\", \"month\"... | [
[
"pandas.read_csv"
],
[
"pandas.read_csv"
],
[
"pandas.read_csv"
]
] |
Red-Portal/Stone-Soup-1 | [
"267621c86161a839da9b144c2745d28d9166d903"
] | [
"docs/examples/Moving_Platform_Simulation.py"
] | [
"#!/usr/bin/env python\n# coding: utf-8\n\n\"\"\"\nMulti-Sensor Moving Platform Simulation Example\n===============================================\nThis example looks at how multiple sensors can be mounted on a single moving platform and exploiting a defined moving\nplatform as a sensor target.\n\"\"\"\n\n# %%\n# ... | [
[
"numpy.deg2rad",
"numpy.array",
"matplotlib.pyplot.figure",
"numpy.arange",
"matplotlib.animation.ArtistAnimation",
"numpy.diag"
]
] |
jinyu121/CIOD | [
"97cea8fce0de3d1d552de1ad9b941e85f2920efa"
] | [
"lib/model/rpn/proposal_layer.py"
] | [
"from __future__ import absolute_import\n# --------------------------------------------------------\n# Faster R-CNN\n# Copyright (c) 2015 Microsoft\n# Licensed under The MIT License [see LICENSE for details]\n# Written by Ross Girshick and Sean Bell\n# --------------------------------------------------------\n# ---... | [
[
"numpy.array",
"torch.cat",
"numpy.arange",
"numpy.meshgrid",
"torch.sort"
]
] |
diptikaushal/TOPSIS-Dipti-101803601 | [
"0919e64072d4f301f311ddf280bc0c7b920ecbd5"
] | [
"topsis.py"
] | [
"import pandas as pd\r\nimport sys\r\nfrom os import path\r\nimport numpy\r\nfrom sys import exit\r\n\r\ndef main(): \r\n if len(sys.argv)!=5:\r\n print(\"Incorrect no. of parameters passed.\")\r\n exit(0)\r\n \r\n i=sys.argv[1]\r\n w=sys.argv[2]\r\n im=sys.argv[3]\r\n result=sys.a... | [
[
"pandas.read_csv"
]
] |
dzwallkilled/pytorch-deeplab-xception | [
"d8c04a24641c8c31a6800a37de6a7bfe607e5495"
] | [
"dataloaders/__init__.py"
] | [
"from dataloaders.datasets import cityscapes, coco, combine_dbs, pascal, sbd, rip\nfrom torch.utils.data import DataLoader\n\n\ndef make_data_loader(args, **kwargs):\n\n if args.dataset == 'pascal':\n train_set = pascal.VOCSegmentation(args, split='train')\n val_set = pascal.VOCSegmentation(args, s... | [
[
"torch.utils.data.DataLoader"
]
] |
Tirbo06/qlib | [
"ad0afc111cf27777bc05d712006ee5b14cc77840"
] | [
"qlib/data/data.py"
] | [
"# Copyright (c) Microsoft Corporation.\n# Licensed under the MIT License.\n\n\nfrom __future__ import division\nfrom __future__ import print_function\n\nimport os\nimport abc\nimport six\nimport time\nimport queue\nimport bisect\nimport logging\nimport importlib\nimport traceback\nimport numpy as np\nimport pandas... | [
[
"numpy.array",
"pandas.DataFrame",
"pandas.Timestamp",
"pandas.concat",
"pandas.Series"
]
] |
sandutsar/magenta | [
"77ed668af96edea7c993d38973b9da342bd31e82"
] | [
"magenta/common/sequence_example_lib.py"
] | [
"# Copyright 2022 The Magenta 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 o... | [
[
"tensorflow.compat.v1.parse_single_sequence_example",
"tensorflow.compat.v1.logging.info",
"tensorflow.compat.v1.gather_nd",
"tensorflow.compat.v1.train.string_input_producer",
"tensorflow.compat.v1.FixedLenSequenceFeature",
"tensorflow.compat.v1.train.QueueRunner",
"tensorflow.compat.... |
jarvmiller/statsmodels | [
"15e90a99c81dd0b61c1aa76ebda2df008e88870d"
] | [
"statsmodels/sandbox/tests/test_formula.py"
] | [
"\"\"\"\nTest functions for models.formula\n\"\"\"\n\nimport string\n\nimport numpy as np\nimport numpy.random as R\nimport numpy.linalg as L\nfrom numpy.testing import assert_almost_equal, assert_equal, assert_, \\\n assert_raises\n\nfrom statsmodels.sandbox import formula #, contrast #, utils\nfrom statsmodels... | [
[
"numpy.array",
"numpy.random.standard_normal",
"numpy.zeros",
"numpy.testing.assert_equal",
"numpy.testing.assert_almost_equal",
"numpy.ones",
"numpy.linalg.pinv",
"numpy.identity",
"numpy.arange",
"numpy.testing.assert_raises",
"numpy.squeeze"
]
] |
redfrexx/osm_association_rules | [
"33975ce25047f9ab3b21e890bc5ed9bab59a0a2f"
] | [
"src/ohsome/tests/test_ohsome_client.py"
] | [
"#!/usr/bin/env python\n\"\"\"\nTests for ohsome client\n\"\"\"\n\nimport os\nimport pandas as pd\nfrom nose.tools import raises\nimport geojson\nimport geopandas as gpd\nimport ohsome\n\n\n@raises(ohsome.OhsomeException)\ndef test_handle_multiple_responses_throw_timeouterror():\n \"\"\"\n Tests counting elem... | [
[
"pandas.DataFrame"
]
] |
zhaoxin94/Dassl.pytorch | [
"c0690f3669c561f2ed7410c22fc65eaef30dfd22",
"c0690f3669c561f2ed7410c22fc65eaef30dfd22"
] | [
"dassl/engine/trainer.py",
"dassl/modeling/backbone/T2T_CA/transformer_block_ca.py"
] | [
"import time\nimport numpy as np\nimport os.path as osp\nimport datetime\nfrom collections import OrderedDict\nimport torch\nimport torch.nn as nn\nfrom torch.utils.tensorboard import SummaryWriter\nimport nni\n\nfrom dassl.data import DataManager\nfrom dassl.optim import build_optimizer, build_lr_scheduler\nfrom d... | [
[
"torch.nn.Linear",
"torch.device",
"torch.no_grad",
"torch.isfinite",
"torch.cuda.is_available",
"torch.cuda.amp.GradScaler",
"torch.utils.tensorboard.SummaryWriter"
],
[
"torch.nn.Linear",
"numpy.sin",
"torch.cat",
"torch.nn.Dropout",
"torch.nn.Identity",
"... |
bhevencious/BioNEV | [
"3ec46c503fb147a8fb1b017d90b0f4ba2317f8f7"
] | [
"src/bionev/evaluation.py"
] | [
"# -*- coding: utf-8 -*-\n\nfrom sklearn.linear_model import LogisticRegression\nfrom sklearn.metrics import accuracy_score, average_precision_score, precision_score, recall_score, f1_score, roc_auc_score, matthews_corrcoef\nfrom sklearn.multiclass import OneVsRestClassifier\nfrom sklearn.preprocessing import Multi... | [
[
"sklearn.metrics.matthews_corrcoef",
"sklearn.metrics.accuracy_score",
"sklearn.linear_model.LogisticRegression",
"sklearn.metrics.average_precision_score",
"sklearn.preprocessing.MultiLabelBinarizer",
"sklearn.metrics.precision_score",
"sklearn.metrics.f1_score",
"sklearn.metrics.... |
LongfeiProjects/exotica | [
"206b296edf9bf3b653ca3984b1449151ca17d374"
] | [
"exotica_python/src/pyexotica/publish_trajectory.py"
] | [
"from __future__ import print_function\nfrom time import sleep\nimport matplotlib.pyplot as plt\nimport signal\n\n\ndef sigIntHandler(signal, frame):\n raise KeyboardInterrupt\n\n\ndef publishPose(q, problem, t=0.0):\n problem.getScene().Update(q, t)\n problem.getScene().getSolver().publishFrames()\n\n\nde... | [
[
"matplotlib.pyplot.show",
"matplotlib.pyplot.plot"
]
] |
00wuweimin/jubilant-dollop | [
"cc91caf8ee7aba5824abe25cbb3870299b369f91"
] | [
"pointer_network.py"
] | [
"import torch\r\nimport torch.nn as nn\r\nfrom torch import optim\r\nimport torch.nn.functional as F\r\nfrom torch.autograd import Variable\r\nimport numpy as np\r\nimport matplotlib.pyplot as plt\r\n\r\n\r\ntrain_data = np.load(\"E:\\\\quant_research\\\\train the rank of ten points\\\\RNN_point\\\\data\\\\train_da... | [
[
"torch.nn.Linear",
"torch.zeros",
"numpy.array",
"torch.cat",
"torch.nn.LSTM",
"torch.nn.MSELoss",
"torch.autograd.Variable",
"numpy.sum",
"numpy.nansum",
"numpy.ones",
"numpy.load",
"numpy.save",
"torch.from_numpy",
"numpy.where",
"torch.load",
"tor... |
NimaPng/tsid | [
"23bbc6bace4f4623c2189535e71ba63bedbc4368"
] | [
"exercizes/ur5_conf.py"
] | [
"# -*- coding: utf-8 -*-\n\"\"\"\nCreated on Thu Apr 18 09:47:07 2019\n\n@author: student\n\"\"\"\n\nimport numpy as np\nimport os\n\nnp.set_printoptions(precision=3, linewidth=200, suppress=True)\nLINE_WIDTH = 60\n\nN_SIMULATION = 4000 # number of time steps simulated\ndt = 0.002 #... | [
[
"numpy.set_printoptions",
"numpy.array"
]
] |
keflavich/pyregion | [
"1ed46731eedffcb52910b0574b2a4e7a8cc99a7d"
] | [
"pyregion/mpl_helper.py"
] | [
"import copy\nimport numpy as np\nfrom math import cos, sin, pi, atan2\nimport warnings\nimport matplotlib.patches as mpatches\nfrom matplotlib.path import Path\nfrom matplotlib.lines import Line2D\nfrom matplotlib.transforms import Affine2D, Bbox, IdentityTransform\nfrom matplotlib.text import Annotation\n\n\ndef ... | [
[
"matplotlib.lines.Line2D",
"numpy.array",
"numpy.sin",
"numpy.asarray",
"matplotlib.patches.PathPatch",
"matplotlib.patches.Polygon",
"matplotlib.transforms.Bbox.union",
"matplotlib.transforms.IdentityTransform",
"matplotlib.patches.Ellipse",
"matplotlib.text.Annotation",
... |
aurobindoc/feast | [
"72f155882c95f21573b31a613edf066bdb55f630"
] | [
"sdk/python/feast/on_demand_feature_view.py"
] | [
"import copy\nimport functools\nimport warnings\nfrom types import MethodType\nfrom typing import Dict, List, Optional, Type, Union\n\nimport dill\nimport pandas as pd\n\nfrom feast.base_feature_view import BaseFeatureView\nfrom feast.data_source import RequestSource\nfrom feast.errors import RegistryInferenceFailu... | [
[
"pandas.DataFrame",
"pandas.Series"
]
] |
lianapanatau/BERT-for-RRC-ABSA | [
"d31d81d5f9dce594a23f256199988fc2a11ce016",
"d31d81d5f9dce594a23f256199988fc2a11ce016"
] | [
"pytorch-pretrained-bert/src/gen_pt_squad.py",
"transformers/analab/plot/neuron.py"
] | [
"# Copyright 2018 The Google AI Language Team Authors and The HuggingFace Inc. team and authors from University of Illinois at Chicago.\n# Copyright (c) 2018, NVIDIA CORPORATION. All rights reserved.\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in comp... | [
[
"numpy.random.seed",
"numpy.array",
"torch.manual_seed"
],
[
"matplotlib.pyplot.tick_params",
"matplotlib.pyplot.xlabel",
"matplotlib.pyplot.ylabel"
]
] |
anukaal/opytimizer | [
"5f1ccc0da80e6a4cabd99578fa24cf4f6466f9b9"
] | [
"opytimizer/optimizers/social/qsa.py"
] | [
"\"\"\"Queuing Search Algorithm.\n\"\"\"\n\nimport copy\n\nimport numpy as np\n\nimport opytimizer.math.random as r\nimport opytimizer.utils.constant as c\nimport opytimizer.utils.logging as l\nfrom opytimizer.core import Optimizer\n\nlogger = l.get_logger(__name__)\n\n\nclass QSA(Optimizer):\n \"\"\"A QSA class... | [
[
"numpy.fabs",
"numpy.sqrt",
"numpy.random.choice",
"numpy.log"
]
] |
movermeyer/pandas_datareaders_unofficial | [
"458dcf473d070cd7686d53d4a9b479cbe0ab9218"
] | [
"draft/truefx/truefx_tick.py"
] | [
"#!/usr/bin/env python\n# -*- coding: utf-8 -*-\n\nimport requests_cache\nimport datetime\nimport pandas as pd\nfrom datetime import timedelta\n\nimport pandas as pd\nfrom pandas.io.common import ZipFile\nfrom pandas.compat import BytesIO, StringIO, PY2\n\ndef main():\n expire_after = timedelta(days=1)\n if P... | [
[
"pandas.to_datetime",
"pandas.DataFrame",
"pandas.compat.BytesIO",
"pandas.io.common.ZipFile"
]
] |
arthw/colorization | [
"e7f85ec307c9d27a16a87276beaaf2dee5492292"
] | [
"interactive-deep-colorization/ui/gui_gamut.py"
] | [
"import cv2\nfrom PyQt4.QtCore import *\nfrom PyQt4.QtGui import *\nfrom data import lab_gamut\nimport numpy as np\n\n\nclass GUIGamut(QWidget):\n def __init__(self, gamut_size=110):\n QWidget.__init__(self)\n self.gamut_size = gamut_size\n self.win_size = gamut_size * 2 # divided by 4\n ... | [
[
"numpy.array"
]
] |
kmh4321/datasets | [
"286d7a8a5eb3e073f18f8fee4f774bafc23fb445"
] | [
"tensorflow_datasets/audio/nsynth.py"
] | [
"# coding=utf-8\n# Copyright 2019 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 ... | [
[
"numpy.array",
"tensorflow.io.gfile.GFile",
"numpy.nan_to_num",
"tensorflow.compat.as_text",
"numpy.mean",
"numpy.abs"
]
] |
RafaelPedruzzi/IA-2019-2 | [
"7d99a8f02ec826403bd48c6eba574d802e558c36"
] | [
"trab2/probOneR.py"
] | [
"## -------------------------------------------------------- ##\n# Trab 2 IA 2019-2\n#\n# Rafael Belmock Pedruzzi\n#\n# probOneR.py: implementation of the probabilistic OneR classifier.\n#\n# Python version: 3.7.4\n## -------------------------------------------------------- ##\n\nimport numpy as np\nfrom sk... | [
[
"sklearn.utils.validation.check_is_fitted",
"sklearn.utils.validation.check_X_y",
"sklearn.utils.multiclass.unique_labels",
"sklearn.utils.validation.check_array",
"sklearn.metrics.cluster.contingency_matrix",
"numpy.argmax",
"numpy.unique"
]
] |
Jiawei-Yang/TumorCP | [
"6053c75642fcbc0fb0424320ab3d758f24883b0e",
"6053c75642fcbc0fb0424320ab3d758f24883b0e"
] | [
"nnunet/training/network_training/nnUNet_variants/architectural_variants/nnUNetTrainerV2_ResencUNet.py",
"nnunet/experiment_planning/change_batch_size.py"
] | [
"# Copyright 2020 Division of Medical Image Computing, German Cancer Research Center (DKFZ), Heidelberg, Germany\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# ... | [
[
"torch.cuda.is_available",
"numpy.vstack"
],
[
"numpy.array"
]
] |
priumoraes/tpu | [
"c7fbe70f00956e802c23c9e831d7482613968fa7",
"c7fbe70f00956e802c23c9e831d7482613968fa7"
] | [
"models/official/amoeba_net/amoeba_net.py",
"models/experimental/mnasnet/mnasnet_main.py"
] | [
"# Copyright 2018 The TensorFlow Authors. All Rights Reserved.\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n# http://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless requ... | [
[
"tensorflow.logging.set_verbosity",
"tensorflow.train.latest_checkpoint",
"numpy.random.rand",
"tensorflow.image.decode_image",
"tensorflow.contrib.tpu.TPUConfig",
"tensorflow.contrib.tpu.TPUEstimator",
"tensorflow.logging.info",
"tensorflow.map_fn",
"tensorflow.estimator.Estim... |
rohanshah13/cloud-emea-copy | [
"12acebc809080e5898ead86a412b17a5272759c2"
] | [
"third_party/ridayesh_run_tag.py"
] | [
"# coding=utf-8\n# Copyright 2018 The Google AI Language Team Authors,\n# The HuggingFace Inc. team, and The XTREME Benchmark Authors.\n# Copyright (c) 2018, NVIDIA CORPORATION. All rights reserved.\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compl... | [
[
"torch.distributed.get_world_size",
"torch.cat",
"torch.utils.data.RandomSampler",
"torch.amax",
"scipy.spatial.distance.cosine",
"torch.cuda.is_available",
"torch.load",
"torch.nn.CrossEntropyLoss",
"torch.nn.DataParallel",
"torch.distributed.init_process_group",
"torc... |
swcjack6931677/ERINN | [
"a4f3d0ad213515bc86e2a18575537d6affd472ac"
] | [
"erinn/python/models/DFN.py"
] | [
"from __future__ import absolute_import, division, print_function\n\nfrom tensorflow.python.keras.layers import Input, Dense\nfrom tensorflow.python.keras.layers.normalization import BatchNormalization\nfrom tensorflow.python.keras.models import Model\n\n\n# 第一種架構: 深度前饋網路(deep feedforward network)\n# 也叫做前饋神經網路(feed... | [
[
"tensorflow.python.keras.layers.normalization.BatchNormalization",
"tensorflow.python.keras.layers.Input",
"tensorflow.python.keras.layers.Dense",
"tensorflow.python.keras.models.Model"
]
] |
acumb/LatticeDNAOrigami | [
"0f2522286adc9815865d4abfc55f546da40e606b"
] | [
"scripts/plotting/plot_lfes.py"
] | [
"#!/usr/bin/python\n\n\"\"\"Plot LFEs of given order parameter.\"\"\"\n\nimport argparse\nimport sys\n\nimport matplotlib.pyplot as plt\nfrom matplotlib import cm\nfrom matplotlib import gridspec\nfrom matplotlib.ticker import MaxNLocator\nimport numpy as np\nimport pandas as pd\n\nfrom matplotlibstyles import styl... | [
[
"matplotlib.ticker.MaxNLocator",
"matplotlib.cm.get_cmap",
"matplotlib.pyplot.legend",
"matplotlib.pyplot.figure",
"pandas.read_csv",
"matplotlib.gridspec.GridSpec"
]
] |
sv2518/pymbolic | [
"42687a410b1c355beec510b91c18f97e5137795b"
] | [
"test/test_pymbolic.py"
] | [
"__copyright__ = \"Copyright (C) 2009-2013 Andreas Kloeckner\"\n\n__license__ = \"\"\"\nPermission is hereby granted, free of charge, to any person obtaining a copy\nof this software and associated documentation files (the \"Software\"), to deal\nin the Software without restriction, including without limitation the... | [
[
"scipy.sparse.csr_matrix",
"numpy.random.randn",
"numpy.linalg.norm"
]
] |
egornagornov3tf4k/Zeta36y | [
"4502be4c86195b0aa5184c45d6f221b34daee7a8"
] | [
"web/node_modules/weblas/test/data/binary_matrix.py"
] | [
"#!/usr/bin/env python\n\"\"\"Create two randomly generated matrices, of the specified sizes and write them\nto JSON files.\n\n\"\"\"\nimport json\nimport numpy as np\n\n\ndef read(path):\n\n\twith open(path, 'rb') as f:\n\t\tmatrix = np.fromfile(f, dtype=np.float32)\n\n\treturn matrix\n\ndef write(path, matrix):\n... | [
[
"numpy.fromfile"
]
] |
WZzhaoyi/MTLNAS | [
"c04fcce1437eef306a41a6a224551be99d88f9a3"
] | [
"core/models/nddr_net.py"
] | [
"import numpy as np\nfrom time import sleep\n\nimport torch\nimport torch.nn as nn\nimport torch.nn.functional as F\n\nfrom core.models.common_layers import batch_norm, get_nddr\nfrom core.tasks import get_tasks\nfrom core.utils import AttrDict\nfrom core.utils.losses import poly\n\n\nclass SingleTaskNet(nn.Module)... | [
[
"torch.nn.ModuleList",
"torch.nn.ModuleDict",
"torch.nn.functional.interpolate",
"torch.nn.ReLU",
"torch.nn.Conv2d",
"torch.nn.Dropout2d"
]
] |
akb89/word2vec | [
"0533e6c1b5ee02d2523bc18359423f94651f7805"
] | [
"word2vec/estimators/word2vec.py"
] | [
"\"\"\"A word2vec implementation using Tensorflow and estimators.\"\"\"\n\nimport os\n\nfrom collections import defaultdict\nimport logging\nimport tensorflow as tf\n\n# from tensorflow.python import debug as tf_debug # pylint: disable=E0611\n\nimport word2vec.utils.datasets as datasets_utils\nimport word2vec.mode... | [
[
"tensorflow.estimator.RunConfig",
"tensorflow.compat.v1.ConfigProto",
"tensorflow.estimator.ProfilerHook",
"tensorflow.compat.v1.disable_eager_execution"
]
] |
mikepackard415/Scientific-Environmental-Discourse | [
"f8d08734f7c2ce98e088479ac7b58c7b348c0401"
] | [
"Programs/env_lda.py"
] | [
"import pandas as pd\r\nfrom sklearn.feature_extraction.text import CountVectorizer\r\nfrom lda import LDA\r\n\r\ndef learn_topics(texts, topicnum):\r\n\r\n # Get vocabulary and word counts. Use the top 10,000 most frequent\r\n # lowercase unigrams with at least 3 alphabetical, non-numeric characters,\r\n ... | [
[
"pandas.read_csv",
"sklearn.feature_extraction.text.CountVectorizer"
]
] |
Leo-xxx/flappy | [
"746cd33d8b56f09b71a308ce041150d8eb61344b"
] | [
"test.py"
] | [
"########################## FWMAV Simulation #########################\n# Version 0.3\n# Fan Fei\t\tFeb 2019\n# Direct motor driven flapping wing MAV simulation\n#######################################################################\n\nimport gym\nimport flappy\n\nfrom stable_baselines.common.policies import Mlp... | [
[
"numpy.array"
]
] |
MitI-7/MachineLearning | [
"6450e2a9260ae70cb75cd2f195729143fe427431"
] | [
"ReinforcementLearning/Bandit/EpsilonGreedy.py"
] | [
"import random\nimport math\nimport numpy as np\nfrom typing import List\n\n\nclass EpsilonGreedy:\n def __init__(self, epsilon: float, counts: List[int], values: List[float]):\n assert epsilon is None or 0.0 <= epsilon <= 1.0\n self.epsilon = epsilon\n self.counts = counts\n self.val... | [
[
"numpy.argmax"
]
] |
997Yi/Flask-web | [
"901ac307b68486d8289105c159ca702318bea5b0",
"6b5e5d274bfa25fbd3db5af02723a5671f1e901d",
"6b5e5d274bfa25fbd3db5af02723a5671f1e901d"
] | [
"venv/Lib/site-packages/skimage/conftest.py",
"venv/Lib/site-packages/matplotlib/testing/decorators.py",
"venv/Lib/site-packages/skimage/feature/masked_register_translation.py"
] | [
"# Use legacy numpy printing. This fix is made to keep doctests functional.\n# For more info, see https://github.com/scikit-image/scikit-image/pull/2935 .\n# TODO: remove this workaround once minimal required numpy is set to 1.14.0\nfrom distutils.version import LooseVersion as Version\nimport numpy as np\n\nif Ver... | [
[
"numpy.set_printoptions"
],
[
"matplotlib.pyplot.switch_backend",
"matplotlib.pyplot.close",
"matplotlib.pyplot.figure",
"matplotlib.pyplot.get_fignums",
"matplotlib.cbook.deprecated",
"matplotlib.ticker.NullFormatter",
"matplotlib.get_backend"
],
[
"numpy.square",
... |
Phuong-Le/mutationorigin | [
"fad00fca3c1073637ede2c6948f5278a030971dc"
] | [
"mutation_origin/cli.py"
] | [
"\"\"\"command line interface for mutation_origin\"\"\"\nimport os\nimport time\nimport pickle\nfrom collections import defaultdict\nimport click\nfrom tqdm import tqdm\nimport pandas\nfrom numpy import log\nfrom numpy.random import seed as np_seed\nfrom scitrack import CachingLogger\nfrom sklearn.model_selection i... | [
[
"numpy.log",
"numpy.random.seed",
"pandas.concat",
"sklearn.model_selection.train_test_split",
"pandas.read_csv"
]
] |
papaispicolo/CarNDT3-SemanticSegmentation | [
"c1940c01769cbf03d7c28c3a72946e4bd9682d59"
] | [
"main.py"
] | [
"#!/usr/bin/env python3\nimport os.path\nimport tensorflow as tf\nimport helper\nimport warnings\nfrom distutils.version import LooseVersion\nimport project_tests as tests\n\n\n# Check TensorFlow Version\nassert LooseVersion(tf.__version__) >= LooseVersion('1.0'), 'Please use TensorFlow version 1.0 or newer. You a... | [
[
"tensorflow.test.gpu_device_name",
"tensorflow.train.AdamOptimizer",
"tensorflow.nn.softmax_cross_entropy_with_logits",
"tensorflow.get_default_graph",
"tensorflow.Session",
"tensorflow.reshape",
"tensorflow.placeholder",
"tensorflow.saved_model.loader.load",
"tensorflow.add",
... |
Alexandre-Bonneau/uwds3_perception | [
"21529f63b3b3d2ad5e30eefece2d75378ae7651f"
] | [
"scripts/camera_publisher_node.py"
] | [
"#!/usr/bin/env python\n# -*- coding: UTF-8 -*-\n\nimport os\nimport rospy\nimport cv2\nimport sensor_msgs\nimport numpy as np\nfrom cv_bridge import CvBridge\n\n\nclass CameraPublisher(object):\n \"\"\" \"\"\"\n def __init__(self):\n \"\"\"Default constructor\"\"\"\n\n self.rgb_image_topic = ro... | [
[
"numpy.array",
"numpy.zeros"
]
] |
ethz-asl/modular_semantic_segmentation | [
"5f9e34243915b862e8fef5e6195f1e29f4cebf50"
] | [
"xview/models/dirichletEstimation.py"
] | [
"#!/usr/bin/python\n#\n# A library for finding the optimal dirichlet prior from counts\n# By: Max Sklar\n# @maxsklar\n# https://github.com/maxsklar\n\n# Copyright 2013 Max Sklar\n\nimport math\nimport logging\nimport random\nimport scipy.special as mathExtra\nimport scipy\nimport numpy as np\n\ndef digamma(x): retu... | [
[
"numpy.square",
"scipy.special.gammaln",
"scipy.special.psi",
"scipy.special.polygamma",
"numpy.sum",
"numpy.multiply"
]
] |
hmorimitsu/ptlflow | [
"26f753322aef91b95ad78e743d847064e5d531b9"
] | [
"ptlflow/__init__.py"
] | [
"\"\"\"Provide useful functions for using PTLFlow.\"\"\"\n\n# =============================================================================\n# Copyright 2021 Henrique Morimitsu\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.... | [
[
"torch.device",
"torch.cuda.is_available",
"torch.hub.get_dir"
]
] |
HIT-cwh/mmrazor | [
"2dad24044d7f1dad88f20221f8fc071dd40fdd4f"
] | [
"mmrazor/models/architectures/components/backbones/darts_backbone.py"
] | [
"# Copyright (c) OpenMMLab. All rights reserved.\nimport copy\n\nimport torch\nimport torch.nn as nn\nfrom mmcls.models.builder import BACKBONES\nfrom mmcv.cnn import build_activation_layer, build_norm_layer\n\nfrom ...utils import Placeholder\n\n\nclass FactorizedReduce(nn.Module):\n \"\"\"Reduce feature map si... | [
[
"torch.cat",
"torch.nn.ModuleList",
"torch.nn.ModuleDict",
"torch.nn.AvgPool2d",
"torch.nn.ReLU",
"torch.nn.Conv2d"
]
] |
viddik13/katna | [
"12256602a5fd24368ffffe2c1a82a46a49215c15"
] | [
"Katna/image_filters/text_detector.py"
] | [
"\"\"\"\n.. module:: Katna.image_filters.text_detector\n :platform: OS X\n :synopsis: This module is implementation of text detector filter\n\"\"\"\n\nimport os\nimport cv2\nimport numpy as np\nimport time\nimport requests\nimport random\nfrom imutils.object_detection import non_max_suppression\nfrom Katna.im... | [
[
"numpy.array",
"numpy.sin",
"numpy.cos"
]
] |
manabukosaka/cleanrl | [
"31ae5f640ac7f7225375bc51759c4e8baa4880b4"
] | [
"cleanrl/experiments/dqn2_atari_visual.py"
] | [
"# https://github.com/facebookresearch/torchbeast/blob/master/torchbeast/core/environment.py\n\nimport numpy as np\nfrom collections import deque\nimport gym\nfrom gym import spaces\nimport cv2\ncv2.ocl.setUseOpenCL(False)\n\n\nclass NoopResetEnv(gym.Wrapper):\n def __init__(self, env, noop_max=30):\n \"\... | [
[
"torch.nn.Linear",
"numpy.sign",
"torch.cuda.is_available",
"torch.LongTensor",
"numpy.concatenate",
"torch.nn.init.constant_",
"matplotlib.pyplot.subplots",
"torch.manual_seed",
"numpy.transpose",
"numpy.append",
"torch.Tensor",
"torch.utils.tensorboard.SummaryWrit... |
dropoutlabs/tf-encrypted | [
"48c9dc7419163425e736ad05bb19980d134fc851"
] | [
"tf_encrypted/convert/register.py"
] | [
"\"\"\"Registry for the TF Encrypted Converter.\"\"\"\nimport array\nimport logging\nimport os\nfrom typing import Any, List\nfrom collections import OrderedDict\n\nimport yaml\nimport numpy as np\nimport tensorflow as tf\n\nfrom ..layers import Conv2D, Relu, Sigmoid, Dense, AveragePooling2D, MaxPooling2D\nfrom ..p... | [
[
"numpy.array",
"tensorflow.required_space_to_batch_paddings",
"tensorflow.rsqrt",
"tensorflow.constant",
"tensorflow.placeholder",
"tensorflow.cast"
]
] |
delos/dm-pta-mc | [
"bce9ce815a518e1b47d1894fce3e003c5e649113"
] | [
"src/signals.py"
] | [
"\"\"\"\n Functions computing the signal shapes\n\"\"\"\n\nimport numpy as np\nfrom time import time\n\nimport src.constants as const\n\n\ndef subtract_signal(t, signal, fit_params=3):\n \"\"\"\n\n Returns the subtracted signal\n\n \"\"\"\n\n # fit dphi(t) to polynomials and subtract the contribution... | [
[
"numpy.square",
"numpy.linalg.norm",
"numpy.dot",
"numpy.log",
"numpy.minimum",
"numpy.polynomial.polynomial.polyfit",
"numpy.sum",
"numpy.subtract.outer",
"numpy.einsum",
"numpy.power",
"numpy.sqrt",
"numpy.arcsinh",
"numpy.broadcast_to"
]
] |
qurator-spk/sbb_ned | [
"d4cfe249f72e48913f254a58fbe0dbe6e47bd168"
] | [
"qurator/sbb_ned/models/evaluation.py"
] | [
"import os\nimport pandas as pd\nimport numpy as np\nimport matplotlib.pyplot as plt\n\n\ndef compute_lr(target_lr, n_epochs, train_set_size, batch_size, warmup):\n total = (n_epochs - 1) * int(np.ceil(train_set_size / batch_size))\n progress = [float(t) / total for t in range(0, total)]\n\n factor = [p / ... | [
[
"pandas.concat",
"numpy.ceil",
"pandas.read_pickle",
"matplotlib.pyplot.figure"
]
] |
TeaKatz/Models_Corpus | [
"6d9e91eb97829e73d88ecfc4754492f6324ef383"
] | [
"TransformerNet/layers/Decoder_test.py"
] | [
"import tensorflow as tf\r\nfrom TransformerNet.layers import Encoder, Decoder\r\n\r\n\r\ndef Decoder_test(*args, **kwargs):\r\n inputs = tf.random.uniform((64, 62), dtype=tf.int64, minval=0, maxval=200) # (batch_size, input_seq_len)\r\n enc_output = Encoder(num_layers=2, d_model=512, num_heads=8,\r\n ... | [
[
"tensorflow.random.uniform"
]
] |
Womcos/SCARF | [
"b90251bc23410cb810a7082ca75147a7aae21dec"
] | [
"encoding/functions/rectify.py"
] | [
"\n\"\"\"Rectify function\"\"\"\nimport torch\nfrom torch.autograd import Function\n\nfrom encoding import cpu\nif torch.cuda.device_count() > 0:\n from encoding import gpu\n\n__all__ = ['rectify']\n\nclass _rectify(Function):\n @staticmethod\n def forward(ctx, y, x, kernel_size, stride, padding, dilation,... | [
[
"torch.cuda.device_count"
]
] |
locdoan12121997/Indoor_Segmentation | [
"7e90fceb92e1be035a5eedec6ee53bf343bcdab6"
] | [
"train_joint.py"
] | [
"from models.joint_fpn import JointFpn\nfrom trainers.segmentation_trainer import SegmentationTrainer\nfrom data_generators.joint_data_generator import JointDataGenerator\nfrom data_generators.scenenet_rgbd_data_generator import ScenenetRGBDDataGenerator\nfrom utils.config import process_config\nfrom utils.dirs imp... | [
[
"tensorflow.keras.mixed_precision.experimental.Policy",
"tensorflow.keras.mixed_precision.experimental.set_policy",
"tensorflow.config.optimizer.set_jit"
]
] |
dumpram/stm32_real_time_test | [
"59b3e6bbd11498df032a180e06144c8046b14bbe"
] | [
"scripts/test.py"
] | [
"#!/usr/bin/python3\n\n# System imports\nimport argparse\nimport sys\nimport serial\n\n# Data processing imports\nimport numpy as np\nimport matplotlib.pyplot as plt\nimport matplotlib.mlab as mlab\nimport seaborn as sns\n\ndef checkparams(pwm_freq, pwm_duty, num_samples):\n check_ok = True\n if pwm_freq < 20... | [
[
"numpy.max",
"numpy.delete",
"numpy.empty",
"numpy.min",
"numpy.save",
"numpy.mean",
"numpy.std"
]
] |
mnoukhov/ecn | [
"f1b838cfe2e27f7cc30cdf2e711b9a474b27a158"
] | [
"src/ecn.py"
] | [
"import argparse\nimport datetime\nimport json\nimport os\nimport time\nfrom os import path\n\nimport numpy as np\nimport torch\nfrom absl import flags\nfrom torch import optim\nfrom pprint import pprint\nimport wandb\n\nfrom src.alive_sieve import AliveSieve, SievePlayback\nfrom src.nets import AgentModel\nfrom sr... | [
[
"torch.zeros",
"numpy.array",
"torch.prod",
"torch.cat",
"torch.true_divide",
"numpy.zeros",
"numpy.random.RandomState",
"numpy.random.seed",
"torch.save",
"torch.manual_seed",
"torch.full",
"torch.load"
]
] |
0xflotus/robogym | [
"5ec2fcbda9828941fe3072792dd25fb5a915bbbb",
"5ec2fcbda9828941fe3072792dd25fb5a915bbbb"
] | [
"robogym/randomization/tests/test_randomization.py",
"robogym/envs/rearrange/tests/test_mesh.py"
] | [
"import unittest\n\nimport attr\nimport numpy as np\n\nfrom robogym.randomization.env import (\n EnvActionRandomizer,\n EnvObservationRandomizer,\n EnvParameterRandomizer,\n EnvRandomization,\n EnvSimulationRandomizer,\n build_randomizable_param,\n)\nfrom robogym.randomization.observation import O... | [
[
"numpy.random.RandomState"
],
[
"numpy.allclose"
]
] |
csmiler/ProbeGAN | [
"6155f5ff33b0673df20b9dbbcbc3e63b75228ef0"
] | [
"classifiers/robust_classifier.py"
] | [
"#################################################\n# Retrieve robust classifier from:\n# https://github.com/MadryLab/robustness\n#################################################\n\nfrom robustness.datasets import CIFAR, RestrictedImageNet, ImageNet\nfrom robustness.model_utils import make_and_restore_model\n\ndef... | [
[
"torch.no_grad",
"numpy.argmax",
"torch.utils.data.DataLoader",
"numpy.amax",
"torch.nn.functional.softmax"
]
] |
jms7446/PRML | [
"39325e085597cb48623f331d63726eea0dc9a714"
] | [
"prmlmy/plot_util.py"
] | [
"import matplotlib.pyplot as plt\nimport numpy as np\nfrom prmlmy.util import cv_, norm2s, calc_range\n\n\ndef plot_decision_boundary(model, X_train, y_train=None, x1_range=None, x2_range=None, points=300,\n title=None, pad_ratio=0.2, ax=None):\n ax = ax or plt\n x1_range = x1_range ... | [
[
"numpy.array",
"numpy.linspace",
"numpy.meshgrid",
"numpy.zeros"
]
] |
richielo/Medical_Localization_RL | [
"58653170824ee087f10b6c8650ee9bc8e05b64e9"
] | [
"pneumoRL/image_util.py"
] | [
"import os \nimport sys\nimport numpy as np\nfrom PIL import Image\nimport torch\n\n#TODO - add save function, these functions can be used to check movement \ndef crop_image(image_array, bb):\n image_array_copy = image_array.clone()\n y_min = int(bb[0])\n x_min = int(bb[1])\n height = int(bb[2])\n wi... | [
[
"numpy.array",
"numpy.zeros",
"numpy.copy",
"torch.from_numpy",
"numpy.where",
"numpy.expand_dims"
]
] |
mhhm2005eg/CarND-Advanced-Lane-Lines | [
"1f571e4714df0dcca21fbf2b09b5af73caddb8f4"
] | [
"color.py"
] | [
"import numpy as np\nimport cv2\nfrom PIL import Image\n\nimg_form = \"jpg\"\nimg_out_dir = \"./output_images\"\nvid_form = \"mp4\"\nvid_out_dir = \"./test_videos_output\"\n\nclass array_image:\n def __init__(self):\n self.image = None\n self.binary_image = None\n\n def store(self, name):\n ... | [
[
"numpy.zeros_like",
"numpy.copy"
]
] |
ankitshah009/dcase_util | [
"738571ce78faf60b0fdfa1d59fd42f42c8944f3d",
"738571ce78faf60b0fdfa1d59fd42f42c8944f3d"
] | [
"dcase_util/keras/data.py",
"dcase_util/datasets/tut.py"
] | [
"# !/usr/bin/env python\n# -*- coding: utf-8 -*-\nfrom __future__ import print_function, absolute_import\nimport numpy\nimport copy\n\nfrom dcase_util.ui import FancyStringifier, FancyLogger\nfrom dcase_util.containers import ContainerMixin\nfrom dcase_util.data import DataBuffer\n\n\ndef get_keras_data_sequence_cl... | [
[
"numpy.dstack",
"numpy.vstack",
"numpy.repeat",
"numpy.hstack",
"numpy.expand_dims"
],
[
"numpy.array"
]
] |
jaimeaguilera/Investing-projects | [
"8b598a6ce9fee626964008fa65d0c3e551091564"
] | [
"utilities/kit.py"
] | [
"import pandas as pd\nimport numpy as np\nfrom numpy.linalg import inv\n\ndef get_ffme_returns():\n \"\"\"\n Load the Fama-French Dataset for the returns of the Top and Bottom Deciles by MarketCap\n \"\"\"\n me_m = pd.read_csv(\"data/Portfolios_Formed_on_ME_monthly_EW.csv\",\n head... | [
[
"numpy.minimum",
"numpy.multiply",
"numpy.outer",
"pandas.read_csv",
"numpy.full_like",
"pandas.DataFrame",
"numpy.log1p",
"numpy.sqrt",
"numpy.linalg.inv",
"scipy.optimize.minimize",
"pandas.to_datetime",
"numpy.array",
"numpy.percentile",
"scipy.stats.norm... |
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