repo_name stringlengths 6 130 | hexsha list | file_path list | code list | apis list |
|---|---|---|---|---|
abcnishant007/sklearn-evaluation | [
"77ff2da43097b0451d8cf6f95c534409f612bf6a"
] | [
"tests/test_metrics.py"
] | [
"from unittest import TestCase\nfrom sklearn_evaluation.metrics import (precision_at, labels_at,\n tp_at, fp_at)\n\nimport numpy as np\nfrom numpy import nan\n\n\nclass Test_precision_at(TestCase):\n\n def test_perfect_precision(self):\n labels = np.array([1, 1, 1, 1... | [
[
"numpy.array",
"numpy.random.rand"
]
] |
ronaldseoh/GRACE | [
"ab32a79677ed6dd5dfcfb14aaa4d6422ff48675c"
] | [
"ate_run.py"
] | [
"from __future__ import absolute_import, division, print_function\n\nimport argparse\nimport logging\nimport os\nimport random\nimport time\n\nimport numpy as np\nimport torch\nimport torch.nn.functional as F\nfrom file_utils import PYTORCH_PRETRAINED_BERT_CACHE\nfrom ate_modeling import BertForSequenceLabeling\nfr... | [
[
"torch.load",
"torch.utils.data.DataLoader",
"torch.no_grad",
"torch.cuda.manual_seed_all",
"torch.cuda.is_available",
"torch.device",
"torch.distributed.init_process_group",
"torch.utils.data.distributed.DistributedSampler",
"torch.utils.data.TensorDataset",
"torch.tensor"... |
mori97/VaDE | [
"b3c3bdcdd758415d61ffe9f21733d32b89304643"
] | [
"main.py"
] | [
"import argparse\n\nimport matplotlib.pyplot as plt\nfrom munkres import Munkres\nfrom sklearn.manifold import TSNE\nimport torch\nimport torch.utils.data\nfrom torch.utils.tensorboard import SummaryWriter\nfrom torchvision import datasets, transforms\n\nfrom vade import VaDE, lossfun\n\nN_CLASSES = 10\nPLOT_NUM_PE... | [
[
"torch.max",
"torch.zeros",
"torch.cat",
"torch.load",
"torch.utils.data.DataLoader",
"matplotlib.pyplot.subplots",
"matplotlib.pyplot.get_cmap",
"torch.sum",
"sklearn.manifold.TSNE",
"torch.no_grad",
"torch.utils.tensorboard.SummaryWriter",
"torch.cuda.is_available... |
GrayKS3248/RL_Agents | [
"dc84321b18131b811f39bc5491f4714e3554d610"
] | [
"Pendulum_Test_Env.py"
] | [
"import random\nimport numpy as np\nimport scipy.integrate\n\n\nclass Pendulum():\n def __init__(self, n_theta=31, n_thetadot=31, n_tau=31):\n # Parameters that describe the physical system\n self.params = {\n 'm': 1.0, # mass\n 'g': 9.8, # acceleration of gravity\n ... | [
[
"numpy.random.uniform",
"numpy.array",
"numpy.sin"
]
] |
QuantumLiu/OpenIVA | [
"4c97a28f999965bab1f4e9e9fd0289df96669526",
"4c97a28f999965bab1f4e9e9fd0289df96669526"
] | [
"openiva/commons/facial/database.py",
"openiva/commons/generators.py"
] | [
"import os\n\nimport json\n\nimport numpy as np\n\nimport h5py\n\nclass FacialDB(object):\n '''\n 人脸信息数据库\n Facial info database\n 存储人脸对应的姓名、性别、特征向量等，可执行查询方法\n '''\n _DB_DICT={}\n def __init__(self,path_json=None,db_dict=None) -> None:\n if not path_json is None:\n self.load_j... | [
[
"numpy.ascontiguousarray",
"numpy.dot"
],
[
"numpy.random.shuffle",
"numpy.ones"
]
] |
abhinav-chinta/Class-12-comp_project | [
"47f7b5d3ce59517031864f554f19cc816f4e2400"
] | [
"ColordetectionFINAL.py"
] | [
"import numpy as np \r\nimport cv2 \r\n\r\nimport pyautogui\r\n \r\n \r\nwebcam = cv2.VideoCapture(0) \r\n \r\nwhile(1): \r\n \r\n # Reading the video from the \r\n # webcam in image frames \r\n _, imageFrame = webcam.read() \r\n \r\n # Convert the imageFrame in \r\n # BGR(RGB color space) t... | [
[
"numpy.array",
"numpy.ones"
]
] |
huangzongheng/NAMA | [
"e9bc5b9ca0c1dd5fff2f0613fdaac9fc5b038152"
] | [
"data/datasets/market1501.py"
] | [
"# encoding: utf-8\n\"\"\"\n@author: sherlock\n@contact: sherlockliao01@gmail.com\n\"\"\"\n\nimport glob\nimport re\nimport os\nimport mat4py\nimport numpy as np\n\nimport os.path as osp\n\nfrom .bases import BaseImageDataset\n\n\nMARKET_ATTR_PARTS = {\n 'head':['hair',\n 'hat',],\n 'up':['upblack... | [
[
"numpy.arange"
]
] |
celiagg/celia | [
"2eff50ab901c297e6f6e8491ddba997e325ffcb9"
] | [
"celiagg/tests/test_no_text.py"
] | [
"# The MIT License (MIT)\n#\n# Copyright (c) 2016-2021 Celiagg Contributors\n#\n# Permission is hereby granted, free of charge, to any person obtaining a copy\n# of this software and associated documentation files (the \"Software\"), to deal\n# in the Software without restriction, including without limitation the r... | [
[
"numpy.zeros"
]
] |
ronger4242/DisasterPipeline | [
"49bf9851a3207cbb005c55ed7cfaa05c4f002756"
] | [
"data/process_data.py"
] | [
"import sys\nimport pandas as pd\nimport numpy as np\nimport sqlite3\nimport re\nfrom sqlalchemy import create_engine\n\ndef load_data(messages_filepath, categories_filepath):\n '''\n Load two CSV files\n Args:\n message_filepath = path to the message file\n categories_filepath = path to the ... | [
[
"pandas.concat",
"pandas.read_csv",
"pandas.to_numeric"
]
] |
YangRui2015/Sparse-Reward-Algorithms | [
"946656bade883565fc4e9248b9579df3d11b7358"
] | [
"agent_env_params.py"
] | [
"import numpy as np \r\n\r\ndef design_agent_and_env(FLAGS):\r\n\r\n # environment params\r\n env_params = {}\r\n if FLAGS.env == \"reach\":\r\n env_params[\"env_name\"] = \"FetchReach-v1\"\r\n env_params[\"has_object\"] = False\r\n FLAGS.total_steps = 20\r\n else:\r\n raise ... | [
[
"numpy.linspace"
]
] |
pgfeldman/optevolver | [
"cdb15a8cf40749e20a3bcb72b87a46f269d3eaf5"
] | [
"optevolver/hyperparameter/TF2OptimizerTestBase.py"
] | [
"import os\nfrom typing import Dict\n\nimport matplotlib.pyplot as plt\nimport numpy as np\nimport tensorflow as tf\nimport time\nfrom tensorflow.keras import layers\n\nimport optevolver.generators.FloatFunctions as FF\n\n\nclass TF2OptimizationTestBase:\n \"\"\"\n A base class that provides the framework for... | [
[
"tensorflow.keras.models.load_model",
"matplotlib.pyplot.title",
"tensorflow.keras.losses.MeanSquaredError",
"tensorflow.keras.layers.Dense",
"tensorflow.keras.Sequential",
"numpy.hsplit",
"matplotlib.pyplot.plot",
"numpy.append",
"tensorflow.keras.optimizers.Adam",
"numpy.... |
gwthmsb/MLAndAI | [
"cb255d9bd480f6f25bf868e831a68257faecbfcc"
] | [
"LDA.py"
] | [
"from numpy import mean\nfrom numpy import std\nfrom sklearn.datasets import make_classification, load_iris\nfrom sklearn.model_selection import cross_val_score, GridSearchCV\nfrom sklearn.model_selection import RepeatedStratifiedKFold\nfrom sklearn.discriminant_analysis import LinearDiscriminantAnalysis\nfrom skle... | [
[
"sklearn.model_selection.GridSearchCV",
"sklearn.model_selection.cross_val_score",
"sklearn.datasets.make_classification",
"sklearn.naive_bayes.GaussianNB",
"sklearn.datasets.load_iris",
"sklearn.pipeline.Pipeline",
"numpy.std",
"sklearn.model_selection.RepeatedStratifiedKFold",
... |
bwoodsend/hoatzin | [
"22355d2f6ba69484e73766fc5e4f62d29ea53e3a"
] | [
"tests/__init__.py"
] | [
"# -*- coding: utf-8 -*-\n\"\"\"\n\"\"\"\nimport functools\nimport warnings\nfrom contextlib import contextmanager\n\nimport numpy as np\n\nfrom hirola import exceptions\n\n\ndef random_ids(max, count, at_least_once=True, sort=False):\n if at_least_once:\n assert count >= max\n out = np.append(np.a... | [
[
"numpy.arange",
"numpy.random.shuffle",
"numpy.random.randint"
]
] |
philip-papasavvas/PythonSkills | [
"7744779314245f23065a36ba0318e21f83b1019b"
] | [
"src/utils_dataframe.py"
] | [
"\"\"\"\nCreated on: 26 Feb 2021\nUtils module for comparing pd DataFrames\n\"\"\"\nimport re\nfrom typing import Union, List\n\nimport numpy as np\nimport pandas as pd\n\n\ndef get_selected_column_names(df: pd.DataFrame,\n cols_to_exclude: Union[List[str], str]) -> List[str]:\n \"\"... | [
[
"pandas.merge",
"numpy.absolute",
"pandas.concat",
"numpy.abs",
"pandas.Series",
"numpy.in1d",
"pandas.DataFrame"
]
] |
sailist/detectron2 | [
"2805d9eb0b2a97899ef187715cf8beb9fd7385fc"
] | [
"detectron2/modeling/mmdet_wrapper.py"
] | [
"# -*- coding: utf-8 -*-\n\nimport itertools\nimport logging\nimport numpy as np\nfrom collections import OrderedDict\nfrom collections.abc import Mapping\nfrom typing import Dict, List, Optional, Tuple, Union\nimport torch\nfrom omegaconf import DictConfig, OmegaConf\nfrom torch import Tensor, nn\n\nfrom detectron... | [
[
"numpy.sqrt",
"torch.full",
"torch.cat",
"torch.from_numpy",
"torch.tensor",
"torch.stack",
"numpy.vstack"
]
] |
erichensleyibm/capstone_CitiBike | [
"74c8d968179c0f53d69bdbb92420b2948bd6adaa"
] | [
"get_bike_data.py"
] | [
"import os, sys\ntry: # if running in CLI\n cur_path = os.path.abspath(__file__)\n while cur_path.split('/')[-1] != 'capstone':\n cur_path = os.path.abspath(os.path.join(cur_path, os.pardir))\nexcept NameError: # if running in IDE... | [
[
"pandas.DataFrame"
]
] |
Helw150/DiffPruningTransformers | [
"4af8fc6493e8fc71d523f4d4a58f3b9115a97db1"
] | [
"diffpruningtransformers/diff_prune_transformer.py"
] | [
"import math\nimport torch\nfrom torchreparam import ReparamModule\nfrom torch import nn\nfrom torch.nn import functional as F\n\n\ndef hard_sigmoid(x):\n return x.clamp(0, 1000).clamp(-1000, 1)\n\n\nclass L0Norm(nn.Module):\n def __init__(self, origin_shape, alpha_init, l, r):\n \"\"\"\n Base c... | [
[
"torch.nn.Parameter",
"torch.load",
"torch.zeros",
"torch.zeros_like",
"torch.tensor",
"torch.nn.functional.sigmoid",
"torch.log",
"torch.autograd.Variable"
]
] |
nekomaruh/Rendimiento_Escolar_en_Chile_2010-2019 | [
"de4a12b2d35ffd76902e6f1bdd552a7ae500548a"
] | [
"interface.py"
] | [
"import queries as q\nfrom queries import cursor, connection, ps\nimport static_tables as st\nimport os, psutil\nimport pandas as pd\nimport fnmatch\nimport time\nfrom io import StringIO\nfrom tqdm import tqdm\n\ndef get_ram(info='unknown'):\n # Obtiene la información de la ram utilizada durante la ejecución del... | [
[
"pandas.concat"
]
] |
jiapei100/DLTK | [
"50b31c9fd75679acc154d2ce384af2842303cc3c"
] | [
"dltk/io/augmentation.py"
] | [
"from __future__ import unicode_literals\nfrom __future__ import print_function\nfrom __future__ import division\nfrom __future__ import absolute_import\n\nimport numpy as np\nfrom scipy.ndimage.interpolation import map_coordinates\nfrom scipy.ndimage.filters import gaussian_filter\n\n\ndef flip(imagelist, axis=1):... | [
[
"numpy.random.random",
"numpy.reshape",
"numpy.argwhere",
"scipy.ndimage.interpolation.map_coordinates",
"numpy.round",
"numpy.random.normal",
"numpy.concatenate",
"numpy.ones",
"scipy.ndimage.filters.gaussian_filter",
"numpy.floor",
"numpy.broadcast_arrays",
"numpy... |
Hiteshsaai/BikeShare_DataAnalysis | [
"544f5176835882138ca8ae7ec460a9d405d2e30f"
] | [
"Bike_Share_Analysis.py"
] | [
"\n# coding: utf-8\n\n# # 2016 US Bike Share Activity Snapshot\n# \n# ## Table of Contents\n# - [Introduction](#intro)\n# - [Posing Questions](#pose_questions)\n# - [Data Collection and Wrangling](#wrangling)\n# - [Condensing the Trip Data](#condensing)\n# - [Exploratory Data Analysis](#eda)\n# - [Statistics](#... | [
[
"matplotlib.pyplot.title",
"matplotlib.pyplot.xlim",
"matplotlib.pyplot.bar",
"matplotlib.pyplot.xlabel",
"matplotlib.pyplot.xticks",
"matplotlib.pyplot.show",
"matplotlib.pyplot.hist",
"matplotlib.pyplot.ylabel"
]
] |
ChengIC/text_classifier | [
"e7265deebb30a3bab1c3e8a4a0a829f659b32e1c"
] | [
"train.py"
] | [
"\n\nimport pandas as pd\nfrom sklearn.feature_extraction.text import CountVectorizer\nimport pickle\n\ndf= pd.read_csv(\"spam.csv\", encoding=\"latin-1\")\n# print (df.head())\ndf.drop(['Unnamed: 2', 'Unnamed: 3', 'Unnamed: 4'], axis=1, inplace=True)\n# Features and Labels\ndf['label'] = df['v1'].map({'ham': 0, 's... | [
[
"sklearn.feature_extraction.text.CountVectorizer",
"sklearn.naive_bayes.MultinomialNB",
"pandas.read_csv",
"sklearn.model_selection.train_test_split"
]
] |
GitHubEmploy/tsad | [
"63181f40209beb3f943b4a0905513455481f71f4"
] | [
"anomaly_detection/prophet_model.py"
] | [
"from pandas import DataFrame, Series\nfrom fbprophet import Prophet\nimport random\nimport numpy as np\nfrom itertools import product\nimport pandas as pd\nimport threading\nfrom multiprocessing import cpu_count\n\nfrom functions import *\nfrom utils import *\nfrom logger import LoggerProcess\n\n\ndef get_anomaly(... | [
[
"numpy.abs",
"numpy.array",
"pandas.Series",
"pandas.DataFrame"
]
] |
muhyun/pytorch-lightning | [
"5fda9da7b415c1812423f27d0d8d89a0b829015c"
] | [
"pytorch_lightning/loggers/tensorboard.py"
] | [
"\"\"\"\nTensorBoard\n-----------\n\"\"\"\n\nimport os\nfrom argparse import Namespace\nfrom typing import Optional, Dict, Union, Any\nfrom warnings import warn\n\nimport torch\nfrom pkg_resources import parse_version\nfrom torch.utils.tensorboard import SummaryWriter\n\nfrom pytorch_lightning import _logger as log... | [
[
"torch.utils.tensorboard.summary.hparams",
"torch.utils.tensorboard.SummaryWriter"
]
] |
AYCHALTZ/AlMusicomposer | [
"cc229aae875ca5f30ddfe5699482ab8572c81e9e"
] | [
"util.py"
] | [
"import os\nimport math\nimport cPickle\nfrom collections import defaultdict\nfrom random import shuffle\n\nimport numpy as np\nimport tensorflow as tf \n\nimport midi_util\nimport nottingham_util\n\ndef parse_midi_directory(input_dir, time_step):\n \"\"\" \n input_dir: data directory full of midi files\n ... | [
[
"numpy.swapaxes",
"numpy.split",
"numpy.sum",
"numpy.arange",
"numpy.dstack",
"numpy.ones",
"numpy.argmax",
"numpy.random.permutation",
"numpy.zeros_like",
"numpy.random.binomial",
"numpy.roll"
]
] |
eduardo98m/GiaDog | [
"ecafdaaddd1b3ac5cf09cdfc97fba8087385497c"
] | [
"giadog/src/GymEnvs/TestingFunctions/test_position_orientation.py"
] | [
"\"\"\"\n Authors: Amin Arriaga, Eduardo Lopez\n Project: Graduation Thesis: GIAdog\n\n Function for testing the robot position and orientation.\n\"\"\"\nimport pyBulletPainter as pbp\nimport numpy as np\n\ndef test_position_orientation(robot, first_exec: bool=False):\n \"\"\"\n Test the position... | [
[
"numpy.array",
"numpy.cos",
"numpy.sin"
]
] |
JWThacker/Udacity_Intro_Machine_Learning_Tensorflow_Nanodegree | [
"1d2b0db9d92d5491173e1d1052acc005721c0ad1"
] | [
"project_2/workspace/predict.py"
] | [
"import warnings\nwarnings.filterwarnings('ignore')\nimport json\nimport sys\nimport argparse as ap\n\nimport numpy as np\n\nimport tensorflow as tf\ntf.get_logger().setLevel('WARNING')\ntf.autograph.set_verbosity(2)\nimport tensorflow_hub as hub\nimport logging\n\nfrom utils import process_image, predict\n'''\n ... | [
[
"tensorflow.autograph.set_verbosity",
"tensorflow.keras.models.load_model",
"tensorflow.get_logger"
]
] |
zhujun98/karabo_data | [
"68ee19d52cd7f140052d029545a7b6169ec9752a"
] | [
"karabo_data/tests/test_utils.py"
] | [
"import numpy as np\nimport os\nimport pytest\nimport re\nimport tempfile\nfrom testpath import assert_isfile\n\nfrom karabo_data import utils\nfrom karabo_data.utils import QuickView\n\n\ndef test_cbf_conversion(mock_agipd_data, capsys):\n with tempfile.TemporaryDirectory() as td:\n out_file = os.path.jo... | [
[
"numpy.empty"
]
] |
ronaldokun/isic2019 | [
"26d436f7ecd9efbce8834dd01aae02c2a8ad85f6"
] | [
"pt/eval.py"
] | [
"import torch\nimport torch.nn as nn\nimport torch.optim as optim\nfrom torch.optim import lr_scheduler\nimport torchvision\nfrom torchvision import datasets, models as tv_models\nfrom torch.utils.data import DataLoader\nfrom torchsummary import summary\nimport numpy as np\nimport models\nimport threading\nimport p... | [
[
"torch.nn.Softmax",
"numpy.sqrt",
"torch.load",
"torch.utils.data.DataLoader",
"numpy.concatenate",
"numpy.max",
"numpy.mean",
"torch.cuda.is_available",
"numpy.where",
"torch.nn.CrossEntropyLoss",
"numpy.intersect1d",
"numpy.std",
"numpy.argmax",
"numpy.flo... |
PhDittmann/carla | [
"f114dc0aa187c5e0abad04731ba1e1d7b32102f0"
] | [
"PythonAPI/examples/manual_control.py"
] | [
"#!/usr/bin/env python\n\n# Copyright (c) 2019 Computer Vision Center (CVC) at the Universitat Autonoma de\n# Barcelona (UAB).\n#\n# This work is licensed under the terms of the MIT license.\n# For a copy, see <https://opensource.org/licenses/MIT>.\n\n# Allows controlling a vehicle with a keyboard. For a simpler an... | [
[
"numpy.reshape",
"numpy.dtype",
"numpy.array",
"numpy.zeros",
"numpy.fabs"
]
] |
phukeo/SCRAMBLE | [
"35d222edb6533e24d09f48a82175281af32eb91f"
] | [
"scrambleFUN.py"
] | [
"import os\r\nimport numpy as np\r\nimport matplotlib.pyplot as pp\r\nimport pandas as pd\r\n\r\n#########################\r\n## INTIALISE VARIABLES ##\r\n#########################\r\n\r\nnewDesk=[]\r\nselectedList=[]\r\nyPlotlabel=\"\"\r\nflow=[\"red\", \"orange\",\"brown\",\"tan\", \"lime\", \"purple\", \"teal\",... | [
[
"pandas.concat",
"pandas.read_csv",
"pandas.Series",
"numpy.gradient",
"matplotlib.pyplot.subplots",
"pandas.DataFrame",
"numpy.concatenate",
"pandas.MultiIndex.from_product",
"matplotlib.pyplot.close"
]
] |
bruyle/oxidizable-pfas-precursor-inference | [
"b8a763c6eb0b3e49bca54ea7e85c692678822eef"
] | [
"infer_precursors.py"
] | [
"\"\"\" Generate samples of the posterior for PFAA precursors from TOP assay\nmeasurements in aqueous matrices.\n\nAuthors:\nColin Thackray (thackray@seas.harvard.edu)\nBridger Ruyle (bruyle@g.harvard.edu)\n\"\"\"\nimport argparse\nimport numpy as np\nimport pandas as pd\nfrom sampling import sample_measurement\nfr... | [
[
"pandas.read_csv",
"numpy.save"
]
] |
florianthonig/listen-attend-and-spell | [
"218dd4f200cd564d3052c550dbbfe1f2cd836008"
] | [
"vctk/build_vocab.py"
] | [
"import sys\nimport numpy as np\n\n\ns = set()\n\nf = np.load(sys.argv[1]).item()\n\nfor line in f.values():\n s.update(line)\n\nd = sorted(list(s))\n\nwith open(sys.argv[2], 'w') as f:\n print('\\n'.join(d), file=f)\n"
] | [
[
"numpy.load"
]
] |
dbbpjch/tf-quant-finance | [
"fa577701afe2f40b6cf0740336f44dc3c1b8222b"
] | [
"tf_quant_finance/experimental/pricing_platform/framework/market_data/volatility_surface.py"
] | [
"# Lint as: python3\n# Copyright 2020 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 appli... | [
[
"tensorflow.compat.v2.convert_to_tensor",
"tensorflow.compat.v2.name_scope"
]
] |
rodrigoarenas456/tspme | [
"7d429b482851a6a5bfda293c65b7e4e4df8cca2b"
] | [
"tspme/metaheuristics.py"
] | [
"import numpy as np\nimport random\nfrom sklearn.metrics.pairwise import euclidean_distances\nfrom tspme.utils.customer_properties import LazyProperty\n\n\nclass SimulatedAnnealing:\n\n def __init__(self, init_temp_factor=1, alpha=0.995, stop_temp=0.5, n_cycles=50):\n self.init_temp = init_temp_factor\n ... | [
[
"numpy.hstack",
"numpy.log",
"sklearn.metrics.pairwise.euclidean_distances",
"numpy.exp",
"numpy.roll"
]
] |
tijsmaas/TrafficPrediction | [
"9129faea8fee8c2d90595d2974f0b11030ad2674",
"9129faea8fee8c2d90595d2974f0b11030ad2674"
] | [
"scripts/eval_baseline_methods.py",
"model/pytorch/engine.py"
] | [
"import argparse\r\nimport numpy as np\r\nimport pandas as pd\r\n\r\nfrom statsmodels.tsa.vector_ar.var_model import VAR\r\n\r\nfrom lib.logger import get_logger\r\nfrom lib.metrics.metrics_np import masked_rmse_np, masked_mape_np, masked_mae_np\r\nfrom lib.utils import StandardScaler\r\n\r\n\r\n\r\n\r\ndef histori... | [
[
"numpy.max",
"pandas.read_hdf",
"pandas.DataFrame.copy"
],
[
"torch.Tensor",
"torch.cat",
"torch.unsqueeze",
"torch.no_grad",
"torch.nn.functional.pad"
]
] |
nightwnvol/AMICO | [
"88638dbbe05a89bbf96354ccca79622828bd3c75"
] | [
"amico/preproc.py"
] | [
"from __future__ import print_function\n\nimport numpy as np\nfrom scipy.optimize import minimize\nimport scipy.special\nfrom tqdm import tqdm\nfrom amico.util import get_verbose\n\n# Kaden's functionals\ndef F_norm_Diff_K(E0,Signal,sigma_diff):\n # ------- SMT functional\n sig2 = sigma_diff**2.0\n F_nor... | [
[
"numpy.array",
"numpy.zeros",
"numpy.sqrt",
"scipy.optimize.minimize"
]
] |
aseber/OpenCV | [
"9b5deef24acdc3664e7989e78d8935bbd140a880"
] | [
"BlurredMask.py"
] | [
"import cv2\nimport numpy\n\ndef main():\n ##Use default camera\n camera = cv2.VideoCapture(-1)\n\n # cv2.namedwindow('Original')\n while camera.isOpened():\n _, image = camera.read()\n cv2.imshow('Original', image)\n #print image\n cv2.waitKey(5)\n\n hsvImage = cv2.cvt... | [
[
"numpy.array"
]
] |
dubosese/mbuild | [
"5823c22ded6d31dc00bb3e8e30583720414ddfe0"
] | [
"mbuild/compound.py"
] | [
"from __future__ import print_function, division\n\n__all__ = ['load', 'clone', 'Compound', 'Particle']\n\nimport collections\nfrom collections import OrderedDict, defaultdict\nfrom copy import deepcopy\nimport itertools\nimport os\nimport sys\nimport tempfile\nfrom warnings import warn\n\nimport mdtraj as md\nfrom... | [
[
"numpy.expand_dims",
"numpy.abs",
"numpy.isfinite",
"numpy.asarray",
"numpy.squeeze",
"numpy.linalg.norm",
"numpy.ndarray",
"numpy.mean",
"numpy.zeros",
"numpy.any",
"numpy.random.rand",
"numpy.array",
"numpy.where",
"numpy.empty"
]
] |
FrancescoNegri/federated-learning-gmm | [
"4351b5a4c9ff30df2c6d2244029f73ae02492c76"
] | [
"src/sampling.py"
] | [
"import math\nimport numpy as np\n# from torchvision import datasets, transforms\n\ndef sample_iid(dataset, n_clients):\n n_samples = int(len(dataset) / n_clients)\n clients_groups, all_idxs = {}, [i for i in range(len(dataset))]\n \n for i in range(n_clients):\n clients_groups[i] = set(np.random... | [
[
"numpy.concatenate",
"numpy.arange",
"numpy.array",
"numpy.random.choice"
]
] |
yuyasugano/technical | [
"9bb60b961cb993d6c355793499dbc72c245f3ab2"
] | [
"main.py"
] | [
"#!/usr/bin/python\nimport csv\nimport time\nimport json\nimport requests\nimport numpy as np\nimport pandas as pd\nfrom datetime import datetime\nimport matplotlib.pyplot as plt\nimport matplotlib.dates as mdates\nimport mpl_finance\n\nheaders = {'Content-Type': 'application/json'}\napi_url_base = 'https://public.... | [
[
"matplotlib.pyplot.legend",
"pandas.to_datetime",
"pandas.offsets.Hour",
"numpy.abs",
"matplotlib.pyplot.scatter",
"matplotlib.pyplot.title",
"matplotlib.pyplot.ylim",
"pandas.DataFrame",
"matplotlib.pyplot.plot",
"matplotlib.pyplot.xlim",
"matplotlib.pyplot.subplot",
... |
pietrobarbiero/pytorch_explainer | [
"beb7d6f40acab1d0bf79bf8dfb0425c7dd4ea174"
] | [
"tests/test_logic_layer.py"
] | [
"import unittest\n\nimport torch\nfrom pytorch_lightning import seed_everything\nfrom torch.nn.functional import one_hot\n\nimport torch_explain as te\nfrom torch_explain.logic.metrics import test_explanation, complexity, concept_consistency, formula_consistency\nfrom torch_explain.logic.nn import entropy, psi\nfro... | [
[
"torch.nn.Sequential",
"torch.nn.BCELoss",
"torch.tensor",
"torch.nn.Linear",
"torch.nn.BCEWithLogitsLoss",
"torch.nn.Sigmoid",
"torch.nn.LeakyReLU"
]
] |
suvadeep-iitb/finetune_alexnet_with_tensorflow | [
"16d88f2a870ef4c0a1febc1807419f68f0481752"
] | [
"multiclass2multilabel.py"
] | [
"import pickle\nimport numpy as np\nfrom scipy.sparse import csr_matrix\n\nimport sys, os\n\n\ndef get_label2id(label_map_file):\n label_map = open(label_map_file).readlines()\n label_map = [l.split() for l in label_map]\n\n num_labels = len(label_map)\n label2id = {label_map[i][0]: i for i in range(num... | [
[
"numpy.float32",
"scipy.sparse.csr_matrix"
]
] |
clowdcap/mysite | [
"2fd6a2f69cfc58ef012138340ae86d8896bff647"
] | [
"News/folium.py"
] | [
"import folium\nfrom geopy.geocoders import Nominatim\nimport pandas as pd\n\nmapa = folium.Map(\n zoom_start=14,\n location=[-25.371781,-49.4141514],\n control_scale=True)\n\nler = pd.read_excel('./tables/locais.xlsx')\nler.drop_duplicates(inplace=True)\n\nlocator = Nominatim(user_agent=\"myGeocoder\")\nl... | [
[
"pandas.read_excel"
]
] |
morzh/stylegan2-encoder-pytorch | [
"ae3635030a0d4d88e2bd2aba301ea4b4c2dd7894"
] | [
"src/perceptual_sim_training/models/dist_model.py"
] | [
"\nfrom __future__ import absolute_import\n\nimport sys\nsys.path.append('..')\nsys.path.append('.')\nimport numpy as np\nimport torch\nfrom torch import nn\nimport os\nfrom collections import OrderedDict\nfrom torch.autograd import Variable\nimport itertools\nfrom .base_model import BaseModel\nfrom scipy.ndimage i... | [
[
"torch.optim.Adam",
"torch.mean",
"torch.load",
"scipy.ndimage.zoom",
"numpy.cumsum",
"numpy.concatenate",
"numpy.mean",
"numpy.argsort",
"torch.clamp",
"numpy.array",
"numpy.sum",
"torch.autograd.Variable"
]
] |
MrDavidYu/img_utils | [
"707f07390b539c822dafd625febc2aa3887832c8"
] | [
"cv_utils.py"
] | [
"import cv2\r\nimport math\r\nimport numpy as np\r\nfrom PIL import Image\r\nimport pytesseract\r\n\r\n\"\"\"\r\nList of helper, enhancement and transformation funcs commonly used for OCR and\r\nCV processing given image or bounding box information. N.B. bbox format in\r\nTensorflow Object Detection format, i.e. [y... | [
[
"numpy.asarray",
"numpy.median",
"numpy.ceil",
"numpy.copy",
"numpy.floor"
]
] |
lucastorterotot/DL_for_HTT_mass | [
"2aff7741b5f497114dd826f9b167f66f2cdaa329"
] | [
"python/DL_for_HTT/post_training/utils.py"
] | [
"import matplotlib.pyplot as plt\nimport numpy as np\n\nimport os\nimport pandas as pd\n\nimport DL_for_HTT.common.NN_settings as NN_default_settings\n\nimport DL_for_HTT.post_training.macros as macros\n\ndef load_model_from_json(input_json):\n model_name = input_json.split('/')[-1].replace('.json', '')\n if ... | [
[
"pandas.read_hdf",
"numpy.abs",
"numpy.arange",
"pandas.DataFrame",
"numpy.round",
"numpy.exp",
"scipy.optimize.curve_fit"
]
] |
EugMJang/Covid-20 | [
"e56cb32bb2470c309cb983e28e8da3de5a2503c8"
] | [
"backend/nation_state/nation_state_data_plotter.py"
] | [
"import requests\nimport matplotlib.pyplot as plt\n\nurls = [\"https://api.covidtracking.com/v1/us/daily.json\", \"https://api.covidtracking.com/v1/states/il/daily.json\"]\n\n\ndef get_nation_state_data(i):\n r = requests.get(urls[i])\n j = r.json()\n\n times = []\n positives = []\n totals = []\n ... | [
[
"matplotlib.pyplot.legend",
"matplotlib.pyplot.title",
"matplotlib.pyplot.savefig",
"matplotlib.pyplot.plot",
"matplotlib.pyplot.xticks",
"matplotlib.pyplot.figure"
]
] |
MauroSilvaPinto/A-personalized-and-evolutionary-algorithm-for-interpretable-EEG-epilepsy-seizure-prediction | [
"3bec2f06cfe0e2aff13e63c83ebc97135c079408"
] | [
"Code/Evolutionary Algorithm/Filter.py"
] | [
"\"\"\"\nFilter class.\n\nFilter class constructs the second-level features (hyper-features)\nby windowing the first-level ones. It performs this feature extraction\nchronologically\n\n\n\"\"\"\n\n\nimport numpy as np\nfrom scipy.signal import find_peaks\nfrom Feature import Feature\nimport networkx as nx\n\nclass ... | [
[
"scipy.signal.find_peaks",
"numpy.sum",
"numpy.linspace",
"numpy.reshape",
"numpy.median",
"numpy.ones",
"numpy.mean",
"numpy.diff",
"numpy.var",
"numpy.argsort",
"numpy.array",
"numpy.trapz"
]
] |
LElgueddari/pisap | [
"ddd9f9f02dcd629b5615fa571ac7795c2d5e9727"
] | [
"pysap/base/loaders/nifti.py"
] | [
"# -*- coding: utf-8 -*-\n##########################################################################\n# pySAP - Copyright (C) CEA, 2017 - 2018\n# Distributed under the terms of the CeCILL-B license, as published by\n# the CEA-CNRS-INRIA. Refer to the LICENSE file or to\n# http://www.cecill.info/licences/Licence_CeC... | [
[
"numpy.diag"
]
] |
gandie/pyAudioAnalysis | [
"1449d667806161b5dace3612cbeceec9be93d843"
] | [
"pyAudioAnalysis/analyzeMovieSound.py"
] | [
"import os, sys, shutil, glob, numpy, csv, cPickle\nimport scipy.io.wavfile as wavfile\nimport audioBasicIO\nimport audioTrainTest as aT\nimport audioSegmentation as aS\nimport matplotlib.pyplot as plt\nimport scipy.spatial.distance\nminDuration = 7;\n\ndef classifyFolderWrapper(inputFolder, modelType, modelName, o... | [
[
"numpy.reshape",
"matplotlib.pyplot.hist",
"numpy.array",
"numpy.zeros",
"numpy.sum",
"matplotlib.pyplot.show",
"matplotlib.pyplot.figure"
]
] |
Stilwell-Git/Randomized-Return-Decomposition | [
"bc804736cbac0ab7ef2eb241d5b17f4a5e2e80a2"
] | [
"algorithm/replay_buffer/atari_buffer/frame_stack_buffer.py"
] | [
"import copy\nimport numpy as np\n\nclass Episode_FrameStack:\n def __init__(self, info):\n self.common_info = [\n 'obs', 'obs_next', 'frame_next',\n 'acts', 'rews', 'done'\n ]\n self.ep = {\n 'obs': [],\n 'acts': [],\n 'rews': [],\n ... | [
[
"numpy.random.choice",
"numpy.stack",
"numpy.random.randint"
]
] |
bptripp/it-cnn | [
"aa8b9fc86de7692a02b2fa51ed5398798a63204f"
] | [
"tuning/position.py"
] | [
"__author__ = 'bptripp'\n\nimport cPickle as pickle\nfrom scipy.optimize import curve_fit\nimport numpy as np\nimport matplotlib\nmatplotlib.rcParams['xtick.labelsize'] = 16\nmatplotlib.rcParams['ytick.labelsize'] = 16\nimport matplotlib.pyplot as plt\nfrom cnn_stimuli import get_image_file_list\nfrom alexnet impor... | [
[
"numpy.linspace",
"numpy.squeeze",
"matplotlib.pyplot.plot",
"numpy.max",
"numpy.mean",
"numpy.nanmean",
"matplotlib.pyplot.gca",
"matplotlib.pyplot.tight_layout",
"numpy.std",
"numpy.argmax",
"matplotlib.pyplot.subplot",
"matplotlib.pyplot.text",
"numpy.zeros",... |
FlyEgle/retinaface_pytorch | [
"79628fc5837b888b7f3e19c97a5ceabe860b0344"
] | [
"models/retinaface.py"
] | [
"import torch\r\nimport torch.nn as nn\r\nimport torchvision.models.detection.backbone_utils as backbone_utils\r\nimport torchvision.models._utils as _utils\r\nimport torch.nn.functional as F\r\nfrom collections import OrderedDict\r\n\r\nfrom models.net import MobileNetV1 as MobileNetV1\r\nfrom models.net import FP... | [
[
"torch.device",
"torch.nn.ModuleList",
"torch.nn.Conv2d",
"torch.nn.functional.softmax"
]
] |
aabiddanda/gdc | [
"5e999ba5363a45a9a4e8f2edec03e5082a3cdab5"
] | [
"pyEigenstrat.py"
] | [
"# Class for reading packed and unpacked Eigenstrat/Ancestrymap format files.\n# packedancestrymap format description by Nick Patterson below:\n#\n################################################################################\n#\n# usage:\n#\n# files named root.{ind,snp,geno} either packed or unpacked\n#\n# > dat... | [
[
"numpy.fromfile",
"numpy.in1d",
"numpy.dtype",
"numpy.genfromtxt",
"numpy.atleast_1d",
"numpy.ceil",
"numpy.fromstring",
"numpy.where",
"numpy.unpackbits"
]
] |
CVUT-FS-12110/Python-for-scientific-computation-and-control | [
"b2ebae9eb3ded5c28238e39a0cac9e23eb1d25d1"
] | [
"courses/E375004/control/utils.py"
] | [
"\"\"\"\nUtility functions for pygame simulator ('simulator.py')\n\"\"\"\nimport numpy as np\nimport matplotlib.pyplot as plt\n\ndef solver(x, v_x, c, m, f, delta_t, x_max, x_img_size, padding = 0):\n \"\"\"\n Euler solver of dynamical system:\n\n m*x\" + c*x' = f\n\n state space substitution:\n\n x1... | [
[
"matplotlib.pyplot.pause",
"matplotlib.pyplot.draw"
]
] |
smbct/LOLH | [
"a9b608b500c83731db2c7dcb70e08cf9a2a94fe0"
] | [
"examples/multi_rules_old/show_solution.py"
] | [
"#!/usr/bin/python\n\nimport numpy as np\nimport pandas as pd\n\nimport matplotlib.pyplot as plt\nfrom matplotlib import cm\nfrom matplotlib import colors as mcolors\n\nimport sys\nsys.path.append('../../python')\n\nfrom instance import Instance\nfrom solver import Solver\nimport visualizer\nimport histogram\n\n\np... | [
[
"pandas.read_csv",
"matplotlib.pyplot.subplots",
"matplotlib.pyplot.show"
]
] |
stjordanis/quantumflow | [
"bf965f0ca70cd69b387f9ca8407ab38da955e925"
] | [
"quantumflow/decompositions.py"
] | [
"\n# Copyright 2016-2018, Rigetti Computing\n#\n# This source code is licensed under the Apache License, Version 2.0 found in\n# the LICENSE.txt file in the root directory of this source tree.\n\n\"\"\"\nQuantumFlow Gate Decompositions\n\"\"\"\n\nfrom typing import Sequence, Tuple\nimport itertools\n\nimport numpy ... | [
[
"numpy.diag",
"numpy.imag",
"numpy.sqrt",
"numpy.asarray",
"numpy.arctan2",
"numpy.linalg.LinAlgError",
"numpy.linalg.svd",
"numpy.allclose",
"numpy.eye",
"numpy.sin",
"numpy.linalg.det",
"numpy.real",
"numpy.isclose",
"numpy.log",
"numpy.linalg.eigh",
... |
tzamalisp/tasks_opensource | [
"73dee9c506c388d6c5b8d65e0d8053320978ce81"
] | [
"tasks/utils/files_saving.py"
] | [
"import os\nimport matplotlib.pyplot as plt\n# plot pretty figures\nimport matplotlib as mpl\nmpl.rc('axes', labelsize=14)\nmpl.rc('xtick', labelsize=12)\nmpl.rc('ytick', labelsize=12)\n\n\ndef save_fig(saving_path, fig_id, tight_layout=True, fig_extension=\"png\", resolution=300):\n path = os.path.join(saving_p... | [
[
"matplotlib.pyplot.tight_layout",
"matplotlib.pyplot.savefig",
"matplotlib.rc"
]
] |
HDNua/kwin | [
"33ce866c2b37faa1a5940354a0e5b3919e5eecc8"
] | [
"choi/object_search/video_detection.py"
] | [
"\"\"\"\n video recognizer\n\n Developer: HeeJun Choi, DoYoung Han\n Version: 0.6.5\n Release Date: 2017-01-09\n\"\"\"\n\nimport numpy as np\nimport cv2\nimport tensorflow as tf\nimport sys\nfrom kwin import *\nimport time\nimport dataset\n\nimport os\nos.environ['TF_CPP_MIN_LOG_LEVEL'] = '3'\n\n###################... | [
[
"tensorflow.import_graph_def",
"tensorflow.gfile.GFile",
"tensorflow.Session",
"tensorflow.GraphDef",
"numpy.array",
"tensorflow.gfile.FastGFile"
]
] |
madsbk/cuml | [
"fab74ca94fdbc5b49281660ce32a48cfd3d66f46"
] | [
"python/cuml/test/test_pickle.py"
] | [
"# Copyright (c) 2019, NVIDIA 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# http://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless required by applicable l... | [
[
"numpy.asarray",
"numpy.int32",
"sklearn.datasets.load_iris",
"sklearn.datasets.make_regression",
"numpy.random.RandomState",
"sklearn.manifold.t_sne.trustworthiness"
]
] |
waldemarmeier/easy-efficientdet | [
"1329f497fdfd0542ee0db074020c4db351b1aa57"
] | [
"easy_efficientdet/factory.py"
] | [
"import json\nimport traceback\nfrom inspect import isgeneratorfunction\nfrom typing import Optional, Sequence, Tuple, Union\n\nimport tensorflow as tf\n\nfrom easy_efficientdet._third_party.training import CosineLrSchedule\nfrom easy_efficientdet.anchors import generate_anchor_boxes\nfrom easy_efficientdet.config ... | [
[
"tensorflow.train.Checkpoint",
"tensorflow.train.latest_checkpoint",
"tensorflow.keras.optimizers.SGD",
"tensorflow.distribute.MirroredStrategy"
]
] |
namiwa/QFHousing | [
"cbe65902ee42e1c0be09f4d5e255bcf2b404ef6a"
] | [
"housing/ModelChecking.py"
] | [
"import seaborn as sns\nimport matplotlib.pyplot as plt\nimport pandas as pd\nimport numpy as np\nimport statsmodels.api as sm\nfrom scipy import stats\nfrom housing.ML import ML_Model\nfrom sklearn.ensemble import RandomForestRegressor\nfrom sklearn.linear_model import Lasso, BayesianRidge\n\ndef statistical_plots... | [
[
"numpy.dot",
"numpy.log",
"numpy.abs",
"pandas.DataFrame",
"numpy.round",
"numpy.append",
"matplotlib.pyplot.figure"
]
] |
ashish-code/structured-sparsity-visual-classification | [
"49e7bd24dab8d4f6e5b012ab333c6012e7404b84"
] | [
"util/writefeaturevectorVOC2010.py"
] | [
"#!/usr/bin/env python\n# -*- coding: utf-8 -*-\n#\n# writefeaturevectorVOC2010.py\n# \n\nimport os\nimport string\nimport numpy as np\nimport csv\n\ndef main():\n\trootDir = '/vol/vssp/diplecs/ash/Data/'\n\tdataSets = ['VOC2010']\n\timageSets = '/ImageSets/Main/'\n\toutDir = '/FeatureMatrix/'\n\tinDir ... | [
[
"numpy.arange",
"numpy.genfromtxt"
]
] |
istiakshihab/api-covid19-rt-bd | [
"10d059bb28b7955ddac3c77a52376ee7bc5900a9"
] | [
"api/rt_data_processing.py"
] | [
"import pandas as pd\nimport numpy as np\nfrom scipy import stats as sps\n\ndef prepare_cases(cases, cutoff=5):\n new_cases = cases.diff()\n\n smoothed = new_cases.rolling(7,\n win_type='gaussian',\n min_periods=1,\n center=True).mean(std=2).round()\n \n idx_start = np.searchsorted(... | [
[
"numpy.log",
"pandas.read_excel",
"pandas.read_csv",
"pandas.Series",
"numpy.ones_like",
"pandas.to_datetime",
"numpy.cumsum",
"pandas.DataFrame",
"scipy.stats.norm",
"numpy.searchsorted",
"scipy.stats.poisson.pmf",
"numpy.exp",
"numpy.sum"
]
] |
rbuxman/new-refactor | [
"c2254fa637fbe54a54e445a0a872d2d0bbe4165a"
] | [
"citrine_converters/tools/hough.py"
] | [
"from __future__ import division\n\nimport numpy as np\n\n\nclass HoughSpace(np.ndarray):\n __doc__ = r\"\"\"\n Constructs a Hough transform space of the `xdata` and\n `ydata`.\n\n Construct a Hough space that, given an orientation,\n determines the distance to a point.\n\n For $ax + by + c = 0$, ... | [
[
"numpy.sqrt",
"numpy.linspace",
"numpy.asarray",
"numpy.cos",
"numpy.sin",
"numpy.array",
"numpy.zeros"
]
] |
mprego/NBA | [
"6b065f0bafb72da2a9a8e4e01304e0097e6dfd77"
] | [
"Classification/NBA_API.py"
] | [
"# -*- coding: utf-8 -*-\n'''\nThis code contains methods for pulling data from NBA.com\nIt depends on the NBA_PY package\n'''\n\n#Imports Packages\nfrom nba_py import *\nfrom nba_py import team\nfrom nba_py import game\nfrom nba_py.constants import *\nfrom Dunks_experiment import *\nimport pandas as pd\nimport dat... | [
[
"pandas.concat",
"pandas.to_datetime",
"pandas.read_csv",
"pandas.merge",
"pandas.DataFrame",
"numpy.mean",
"pandas.date_range"
]
] |
sjtututu/QUANTAXIS | [
"e9e20cdeda8b8d132433037b639a7e60f286a190"
] | [
"QUANTAXIS/QAUtil/QADate_trade.py"
] | [
"# coding:utf-8\r\n#\r\n# The MIT License (MIT)\r\n#\r\n# Copyright (c) 2016-2019 yutiansut/QUANTAXIS\r\n#\r\n# Permission is hereby granted, free of charge, to any person obtaining a copy\r\n# of this software and associated documentation files (the \"Software\"), to deal\r\n# in the Software without restriction, ... | [
[
"pandas.Timestamp"
]
] |
yanfei-zhang-95/CT-Recon_ | [
"bfe1d9d0b269129847fd8ecf0b654ebda6b15ec4"
] | [
"model.py"
] | [
"import numpy as np\nimport tensorflow as tf\nimport tensorlayer as tl\n\nimport tensorflow.keras as keras\n\nclass modelComponents():\n\n @staticmethod\n def tensorial_neural_block(x, new_shape1, new_shape2, new_shape3, scope, actv = tf.nn.sigmoid, isIN = True, isActv = True):\n\n\n with tf.variable_s... | [
[
"tensorflow.convert_to_tensor",
"tensorflow.concat",
"tensorflow.reduce_sum",
"tensorflow.losses.absolute_difference",
"tensorflow.image.rot90",
"tensorflow.layers.conv2d_transpose",
"tensorflow.pad",
"tensorflow.keras.layers.ConvLSTM2D",
"numpy.exp",
"tensorflow.nn.conv2d"... |
my-isu-research/CutMix-PyTorch | [
"00870a196a39c6061c97972d797d34886589439d"
] | [
"extras.py"
] | [
"import torchvision.transforms as transforms\nimport os\nimport torchvision.datasets as datasets\nimport torch.nn as nn\n\ndef get_base_transform(img_size = 32,\n mean = [x / 255.0 for x in [125.3, 123.0, 113.9]],\n std = [x / 255.0 for x in [63.0, 62.1, 66.7]]):\n\n normalize = transforms.Normalize(mean, ... | [
[
"torch.nn.Linear"
]
] |
j-zimmermann/pyABC | [
"fde3f97978297ad7a09528d1e18ff3580c91e8d9"
] | [
"pyabc/sampler/redis_eps/cli.py"
] | [
"import sys\nimport socket\nimport signal\nfrom redis import StrictRedis\nimport pickle\nimport os\nimport cloudpickle\nfrom time import time\nimport click\nfrom .redis_logging import logger\nfrom .cmd import (N_EVAL, N_ACC, N_REQ, ALL_ACCEPTED,\n N_WORKER, SSA, QUEUE, START, STOP,\n ... | [
[
"numpy.random.seed"
]
] |
WenmuZhou/DABNet_Paddle | [
"b551085009faf07b351df98ecb625e1f82ddd50e"
] | [
"dataset/cityscapes.py"
] | [
"import os.path as osp\nimport numpy as np\nimport random\nimport cv2\nfrom paddle.io import Dataset\nimport pickle\n\n\nclass CityscapesDataSet(Dataset):\n \"\"\" \n CityscapesDataSet is employed to load train set\n Args:\n root: the Cityscapes dataset path, \n cityscapes\n ├... | [
[
"numpy.log",
"numpy.histogram",
"numpy.random.choice",
"numpy.asarray",
"numpy.unique",
"numpy.ones",
"numpy.std",
"numpy.mean",
"numpy.array",
"numpy.zeros",
"numpy.sum"
]
] |
NCMlab/CogntiveTasksOnline | [
"02e2bdb2b54a96b609fd5658cac4323322f183f0"
] | [
"VSTMPsychopyFiles/VSTM_PassConfigFile.py"
] | [
"'''\nThis version of the task takes a config file when called along with a flag based\non whether to use a fixed dot location or not.\nThe config file creates three different lists of probe pos/neg orders and dot\nlocations for load levels 1 to 15.\n'''\n# https://docs.python.org/3/library/configparser.html\n\n\nf... | [
[
"numpy.random.permutation",
"numpy.arange",
"numpy.array"
]
] |
Yoshino-master/FreeAnchor_TensorFlow | [
"656a07c85da8b3de21416d1e5162134665abd164"
] | [
"utils/loss.py"
] | [
"import tensorflow as tf\nimport math\nfrom utils.evals import calc_iou_tf\nfrom utils.evals import decode, encode\n\nclass FreeAnchorLoss(object):\n def __init__(self, cfg):\n self.cfg = cfg\n self.xywh_weights = (10.0, 10.0, 5.0, 5.0)\n self.bbox_xform_clip = math.log(1000. / 16)\n \n ... | [
[
"tensorflow.concat",
"tensorflow.zeros",
"tensorflow.reduce_sum",
"tensorflow.stack",
"tensorflow.cast",
"tensorflow.where",
"tensorflow.gather",
"tensorflow.nn.top_k",
"tensorflow.nn.sigmoid",
"tensorflow.gather_nd",
"tensorflow.shape",
"tensorflow.pow",
"tenso... |
singhgargi/SEM2 | [
"d0f260e10a3e34067b8c2d73abdeae36e5fa55bb"
] | [
"sem/utils.py"
] | [
"import os\nimport sys\nimport traceback\nimport numpy as np\nfrom functools import wraps\nfrom multiprocessing import Process, Queue\n\n\ndef unroll_data(x, t=1):\n \"\"\"\n This function is used by recurrent neural nets to do back-prop through time.\n\n Unrolls a data_set for with time-steps, truncated f... | [
[
"numpy.log",
"numpy.reshape",
"numpy.ndim",
"numpy.shape",
"numpy.zeros"
]
] |
filipeRmlh/Trabalho_Final_AD_2020_2 | [
"eed64b1d383674a8212de570aaa6e1ec46f6bd52"
] | [
"trabalho_final/events/start_request.py"
] | [
"from ..request_data import RequestData\nfrom .event import Event\nfrom numpy import random\nfrom .timeout import Timeout\nfrom .client_2_cache import Client2Cache\nfrom ..config import Config\n\n\n\nclass StartRequest(Event):\n request_id = 0\n\n\n def __init__(self, config, timestamp=0, cache_list=[], max_r... | [
[
"numpy.random.randint"
]
] |
josephnoir/indexing | [
"99f6a02c22451d0db204731a6c53ed56ad751365"
] | [
"evaluation/plot01.py"
] | [
"#!/usr/local/bin/python3\n\n# import modules\n#import matplotlib.pyplot as plt\n#import numpy as np\n#from sys import argv\n#script, filename = argv\n#txt = open(filename)\n#print(txt.read())\n#plt.plot([1,2,3,4])\n#plt.ylabel('some numbers')\n#plt.show();\n\nimport csv\nfrom sys import argv\nimport numpy as np\ni... | [
[
"matplotlib.pyplot.legend",
"numpy.arange",
"matplotlib.pyplot.gcf",
"matplotlib.pyplot.subplot",
"matplotlib.pyplot.xlabel",
"numpy.array",
"numpy.sum",
"matplotlib.pyplot.show"
]
] |
SabevAtGitHub/qspreadsheet | [
"29127dd6f38573c7ede7680cf8f4852368fb2c38"
] | [
"qspreadsheet/_ndx.py"
] | [
"import logging\nimport sys\nimport os\nfrom typing import Dict\nfrom numpy.core.fromnumeric import alltrue\nimport pandas as pd\nfrom PySide2.QtCore import *\nfrom PySide2.QtGui import *\nfrom PySide2.QtWidgets import *\n\nfrom qspreadsheet.common import DF, SER, pandas_obj_insert_rows, pandas_obj_remove_rows\nfro... | [
[
"pandas.DataFrame"
]
] |
YuLin-code/MP-MIM | [
"0871a27d1717dc6f5dad623c6721824b104c3bb8"
] | [
"RESEPT/Embedding_Ground_Truth_Quality_Rank.py"
] | [
"import numpy as np\r\nimport pandas as pd\r\nimport os\r\nfrom sklearn.cluster import KMeans\r\nfrom sklearn.metrics.cluster import adjusted_rand_score\r\nimport argparse\r\n\r\n\r\nparser = argparse.ArgumentParser(description='Embedding_Ground_Truth_Quality_Rank_')\r\nparser.add_argument('--sampleName', type=str,... | [
[
"pandas.read_csv",
"sklearn.cluster.KMeans",
"pandas.DataFrame",
"numpy.array",
"sklearn.metrics.cluster.adjusted_rand_score"
]
] |
Shadoward/splsensors | [
"308875e807df0924de81f2ef9ec2b8fc1cd04a89"
] | [
"src/splsensors/geodetic.py"
] | [
"#!/usr/bin/python\n#\n# --------------------------------------------------------------------- \n# | |\n# |\tgeodetic.cc - a collection of geodetic functions |\n# |\tPaul Kennedy May 2016 |\n... | [
[
"numpy.median"
]
] |
jackyoung96/gym-pybullet-drones | [
"770a22a4f1102f08ce4617560fab06ba405715bd"
] | [
"custom/learn.py"
] | [
"\"\"\"Script demonstrating the use of `gym_pybullet_drones`' Gym interface.\n\nClass TakeoffAviary is used as a learning env for the A2C and PPO algorithms.\n\nExample\n-------\nIn a terminal, run as:\n\n $ python learn.py\n\nNotes\n-----\nThe boolean argument --rllib switches between `stable-baselines3` and `r... | [
[
"numpy.array"
]
] |
kozzion/tensealstat | [
"93314a8721ec6b1a2bea466aaeadb06cbf5a4f63"
] | [
"test/student_t_repeated_measures.py"
] | [
"import sys\nimport os\nfrom scipy import stats\nimport tenseal as ts\nimport numpy as np\nfrom scipy.stats import t\n\nsys.path.append(os.path.abspath('../../tensealstat'))\n\nfrom tensealstat.tools_context import ToolsContext as tc\nfrom tensealstat.algebra.algebra_numpy import AlgebraNumpy\nfrom tensealstat.alge... | [
[
"scipy.stats.t.cdf",
"scipy.stats.ttest_rel",
"numpy.array"
]
] |
Verduxo/FreeGames | [
"e68bd3d2264b7f8c61af94889ceb5c682311efcc"
] | [
"FreeGames.py"
] | [
"import requests\nimport pandas as pd\n\ndef save(url):\n jsonF = open('db.json','w+')\n r= requests.get(url)\n jsonF.write(r.text)\n df = pd.read_json('db.json')\n df.to_csv (r'OpenWithLibreOffice.csv', index = None)\n \n \n \ndef todos():\n url = ' https://www.freetogame.com/api/games'\... | [
[
"pandas.read_json"
]
] |
AliDaVinci/ConnectFour | [
"82060777784616d11256a06e44222e91dd7baecf"
] | [
"Connect4.py"
] | [
"import numpy as np\nimport pygame\nimport sys\nimport math\n\nBLUE = (0,0,255)\nBLACK = (0,0,0,)\nRED = (255,0,0)\nYELLOW = (255,255,0)\n\nROW_COUNT = 6\nCOLUMN_COUNT = 7\n\ndef create_board():\n\tboard = np.zeros((ROW_COUNT,COLUMN_COUNT))\n\treturn board\n\ndef drop_piece(board, row, col, piece):\n\tboard[row][co... | [
[
"numpy.flip",
"numpy.zeros"
]
] |
luispedro/milksets | [
"84fc8cba4d4a87acf573ce562cd065b0ee37fadd"
] | [
"milksets/seeds/seeds.py"
] | [
"# -*- coding: utf-8 -*-\n# Copyright (C) 2012, Luis Pedro Coelho <luis@luispedro.org>\n#\n# Permission is hereby granted, free of charge, to any person obtaining a copy\n# of this software and associated documentation files (the \"Software\"), to deal\n# in the Software without restriction, including without lim... | [
[
"numpy.loadtxt"
]
] |
dksifoua/NMT | [
"a651d5f957868ab4879d028060fdbec3e09263cb"
] | [
"scripts/evaluate.py"
] | [
"import os\nimport argparse\nimport numpy as np\nimport matplotlib.pyplot as plt\nimport matplotlib.ticker as ticker\nimport torch\nfrom nmt.config.global_config import GlobalConfig\nfrom nmt.config.train_config import TrainConfig\nfrom nmt.config.dataset_config import DatasetConfig\nfrom nmt.processing.processing ... | [
[
"matplotlib.ticker.MultipleLocator",
"matplotlib.pyplot.show",
"torch.cuda.is_available",
"matplotlib.pyplot.figure"
]
] |
luwangg/digital_rf | [
"e5bc28606af2d5071c1fd1561595f816ff335085"
] | [
"python/tools/thor.py"
] | [
"#!python\n# ----------------------------------------------------------------------------\n# Copyright (c) 2017 Massachusetts Institute of Technology (MIT)\n# All rights reserved.\n#\n# Distributed under the terms of the BSD 3-clause license.\n#\n# The full license is in the LICENSE file, distributed with this soft... | [
[
"numpy.abs",
"numpy.fft.fft",
"numpy.dtype",
"numpy.ceil",
"numpy.longdouble",
"numpy.uint64",
"numpy.fft.fftfreq",
"numpy.zeros"
]
] |
astrojhgu/rt1d | [
"cb49510ae9850d1491dcf9336e3994fb1b153438"
] | [
"tests/test_rt06_2.py"
] | [
"\"\"\"\n\ntest_rt06_2.py\n\nAuthor: Jordan Mirocha\nAffiliation: University of Colorado at Boulder\nCreated on: Wed Dec 26 18:37:48 2012\n\nDescription: This is Test problem #2 from the Radiative Transfer\nComparison Project (Iliev et al. 2006; RT06).\n\n\"\"\"\n\nimport rt1d\nimport matplotlib.pyplot as pl\n\nsim... | [
[
"matplotlib.pyplot.figure"
]
] |
nagasudhirpulla/wrldc_metering_warehouse | [
"d56568783fb282c72977d537e51ed66f64dedf62"
] | [
"fict_master_data.py"
] | [
"# -*- coding: utf-8 -*-\n\"\"\"\nCreated on Wed Sep 12 16:41:28 2019\n\n@author: Nagasudhir\n\"\"\"\n\nimport pandas as pd\nimport pandas.io.sql as sqlio\nimport psycopg2\nfrom warehouse_db_config import getWarehouseDbConfigDict\n\nclass FictMasterData:\n '''\n returns meter master data dataframe with column... | [
[
"pandas.read_excel",
"pandas.io.sql.read_sql_query"
]
] |
gsinuco/VariationalNN_Floquet | [
"46605e53c29801b9aaedfe9a61fe886239bc2112"
] | [
"src/variationalnn_floquet/TensorFlow_Floquet_old.py"
] | [
"#!/usr/bin/env python3\n\"\"\"\n\nmodified from https://www.tensorflow.org/tutorials/customization/custom_training\n https://www.tensorflow.org/tutorials/customization/custom_training_walkthrough\nCreated on Sat Aug 10 11:30:57 2019\n@author: German Sinuco\n\n\"\"\"\n\nfrom __future__ import absolute_... | [
[
"tensorflow.sin",
"tensorflow.constant",
"tensorflow.cos",
"tensorflow.linalg.svd",
"tensorflow.Variable",
"tensorflow.reduce_mean",
"tensorflow.GradientTape",
"tensorflow.math.conj",
"tensorflow.square",
"tensorflow.random.stateless_uniform",
"tensorflow.linalg.trace",... |
Or-Tal/fairseq | [
"2be0d74e0034f95a32f24afb381e0e275957a0e4",
"2be0d74e0034f95a32f24afb381e0e275957a0e4"
] | [
"lese/dsp.py",
"lese/audio.py"
] | [
"# Copyright (c) Facebook, Inc. and its affiliates.\n# All rights reserved.\n#\n# This source code is licensed under the license found in the\n# LICENSE file in the root directory of this source tree.\n# author: adefossez\n\nimport numpy as np\nimport torch\nfrom torch.nn import functional as F\n\n\ndef hz_to_mel(f... | [
[
"numpy.sinc",
"torch.hamming_window",
"numpy.linspace",
"numpy.arange",
"torch.nn.functional.conv1d",
"numpy.log10",
"torch.stack"
],
[
"torch.nn.functional.pad"
]
] |
raysr/Deep-Reinforcement-Learning-Notebooks | [
"a7e988205bb21a2bf6972cf51bbd46d624ecf9ef"
] | [
"test-yourself.py"
] | [
"# INITIALIZATION: libraries, parameters, network...\n\nfrom keras.models import Sequential # One layer after the other\nfrom keras.layers import Dense, Flatten # Dense layers are fully connected layers, Flatten layers flatten out multidimensional inputs\nfrom collections import deque # For storing... | [
[
"numpy.expand_dims",
"numpy.stack",
"numpy.max",
"numpy.argmax",
"numpy.random.rand",
"numpy.zeros",
"numpy.random.randint"
]
] |
AK391/models | [
"6ab1414db8b2895174c921b7c42ee8371e93d882"
] | [
"workflow_scripts/generate_onnx_hub_manifest.py"
] | [
"import hashlib\r\nimport json\r\nimport os\r\nimport re\r\nimport bs4\r\nimport markdown\r\nimport pandas as pd\r\nimport typepy\r\nfrom os.path import join, split\r\nimport onnxruntime as ort\r\nfrom onnxruntime.capi.onnxruntime_pybind11_state import NotImplemented\r\nimport onnx\r\nfrom onnx import shape_inferen... | [
[
"pandas.concat",
"pandas.DataFrame"
]
] |
ananyaganesh/ftmp | [
"9ee23939f0c1da854846b8ce1a9abe4e9b377031"
] | [
"train.py"
] | [
"import time\nimport os\nimport pyhocon\nimport torch\nfrom torch import nn\nfrom torch import optim\nfrom models import *\nfrom utils import *\nfrom nn_blocks import *\nfrom sklearn.metrics import accuracy_score, classification_report\nfrom transformers import *\nimport argparse\nimport random\nimport numpy as np\... | [
[
"torch.tensor",
"numpy.argmax",
"numpy.mean",
"torch.device",
"sklearn.metrics.classification_report"
]
] |
katsu1110/DataScienceComp | [
"86edf7cab0af372624bba7f3026a3db32e7cd1d6"
] | [
"models/run_models.py"
] | [
"import numpy as np\nimport pandas as pd\nimport os\nimport sys\nimport gc\nimport re\nfrom typing import List, NoReturn, Union, Tuple, Optional, Text, Generic, Callable, Dict\nfrom sklearn.preprocessing import StandardScaler, MinMaxScaler, OneHotEncoder, QuantileTransformer\nfrom sklearn.model_selection import KFo... | [
[
"sklearn.metrics.roc_auc_score",
"sklearn.preprocessing.QuantileTransformer",
"pandas.DataFrame",
"sklearn.model_selection.KFold",
"sklearn.metrics.mean_squared_error",
"sklearn.metrics.f1_score",
"numpy.exp",
"sklearn.preprocessing.MinMaxScaler",
"matplotlib.style.use",
"n... |
charleyjoo/myproject | [
"e0b04156e0148cf8c86768c73f66fa6b5795c0d4"
] | [
"myproject/pronto_utils.py"
] | [
"import wget\nimport os\n\nimport zipfile\nimport pandas as pd\n\nimport matplotlib.pyplot as plt\nimport seaborn; seaborn.set()\n\ndef download_if_needed(URL, filename):\n \"\"\"\n Download from URL TO FILENAME UNLESS FILENAME ALREADY EXISTS\n \"\"\"\n if os.path.exists(filename):\n print(filena... | [
[
"pandas.read_csv",
"matplotlib.pyplot.subplots",
"pandas.DatetimeIndex"
]
] |
rotskoff-group/dissipative-design | [
"8335a4e23ccc0eba1771d4b78f5102ee6113664c"
] | [
"lj_system/lj.py"
] | [
"from simtk.openmm.app import *\nfrom simtk.openmm import *\nfrom simtk.unit import *\nfrom sys import stdout\nfrom scipy.stats import gamma\nimport PIL\nimport freud\nimport fresnel\nimport matplotlib.pyplot as plt\nimport numpy as np\nfrom mdtraj.reporters import HDF5Reporter\nimport time\n\n\nclass LJ:\n def ... | [
[
"matplotlib.pyplot.imshow",
"numpy.log",
"numpy.sum",
"numpy.linspace",
"numpy.unique",
"matplotlib.pyplot.savefig",
"numpy.ones",
"numpy.max",
"matplotlib.pyplot.colorbar",
"numpy.mean",
"numpy.any",
"matplotlib.pyplot.close",
"numpy.random.gamma",
"numpy.d... |
doansangg/CGAN-PyTorch | [
"941f5bd75102bed7f2eccd7feb9af8e6134af0e4"
] | [
"dataloader.py"
] | [
"import os\nfrom PIL import Image\nimport torch.utils.data as data\nimport torchvision.transforms as transforms\nimport numpy as np\nimport random\nimport torch\nfrom torch import Tensor, int32\n\nclass Dataset(data.Dataset):\n \"\"\"\n dataloader for polyp segmentation tasks\n \"\"\"\n def __init__(sel... | [
[
"torch.manual_seed",
"torch.LongTensor",
"torch.utils.data.DataLoader",
"numpy.random.randint"
]
] |
joel-simon/Antimander | [
"ec2058a76f172e0941d5e4558776831050a00c2a"
] | [
"optimize/test/draw_random.py"
] | [
"import os, sys, random, time\nimport pygame\nfrom pygame import gfxdraw\nimport numpy as np\nsys.path.append(os.path.abspath('.'))\nfrom src.state import State\nfrom src import districts, mutation, metrics\nfrom src.connectivity import can_lose\nfrom src.constraints import fix_pop_equality\nfrom src.draw import dr... | [
[
"numpy.sum",
"numpy.random.randint"
]
] |
chohy/cho_gem5 | [
"1207718477576053ee6222faff03dd888a90dbcf"
] | [
"ext/pybind11/tests/test_numpy_array.py"
] | [
"import pytest\nimport gc\n\nwith pytest.suppress(ImportError):\n import numpy as np\n\n\n@pytest.fixture(scope='function')\ndef arr():\n return np.array([[1, 2, 3], [4, 5, 6]], '<u2')\n\n\n@pytest.requires_numpy\ndef test_array_attributes():\n from pybind11_tests.array import (\n ndim, shape, strid... | [
[
"numpy.random.random",
"numpy.all",
"numpy.testing.assert_array_equal",
"numpy.uint64",
"numpy.array"
]
] |
LukeHartmanTmlt/private-pgm | [
"8d57504ae076ae1cb54f7a1c1f2a0815a696ae77"
] | [
"mechanisms/adaptive_grid.py"
] | [
"import numpy as np\nimport pandas as pd\nimport json\nfrom mbi import FactoredInference, Factor, Dataset, Domain\nfrom scipy import sparse\nfrom scipy.special import logsumexp\nimport itertools\nimport networkx as nx\nfrom disjoint_set import DisjointSet\nfrom cdp2adp import cdp_rho\nimport argparse\n\n\ndef power... | [
[
"pandas.read_csv",
"numpy.ones_like",
"numpy.sqrt",
"numpy.arange",
"numpy.linalg.norm",
"scipy.sparse.csr_matrix",
"numpy.ones",
"numpy.finfo",
"numpy.random.normal",
"scipy.sparse.vstack",
"scipy.sparse.kron",
"numpy.array",
"scipy.special.logsumexp"
]
] |
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