repo_name stringlengths 6 130 | hexsha list | file_path list | code list | apis list |
|---|---|---|---|---|
nicolay-r/attitude-extraction-with-attention-and-ds | [
"fb8e9d0d9488363738a88c4c447c7a8cb3e2ec1d"
] | [
"rusentrel/classic/ctx/att_hidden_z_yang.py"
] | [
"#!/usr/bin/python\n# -*- coding: utf-8 -*-\nimport sys\nimport tensorflow as tf\n\n\nsys.path.append('../../../')\n\nfrom io_utils import RuSentRelBasedExperimentsIOUtils\nfrom arekit.contrib.networks.context.architectures.att_self_z_yang_bilstm import AttentionSelfZYangBiLSTM\nfrom arekit.contrib.networks.context... | [
[
"tensorflow.contrib.layers.xavier_initializer"
]
] |
mvpmanish/LASED | [
"7793037b3e77ee9205f631d7ff6c511895108400"
] | [
"base-LASED/build/lib/LASED/time_evolution_matrix.py"
] | [
"'''\nThis is a file to define a function to populate the time evolution matrix for a laser-atom system\nAuthor: Manish Patel\nDate created: 12/05/2021\n'''\n\nfrom LASED.state import *\nfrom LASED.detuning import *\nfrom LASED.symbolic_print import *\nfrom LASED.half_rabi_freq import *\nfrom LASED.decay_constant i... | [
[
"numpy.zeros"
]
] |
RDLLab/benevolent-deception-gym | [
"4d04e097609097e0f07c661aac221184ebdec2fe"
] | [
"bdgym/envs/driver_assistant/policy.py"
] | [
"\"\"\"Driver Policies for the Driver Assistant Environment \"\"\"\nfrom copy import deepcopy\nfrom typing import Tuple, Optional, List, Dict\n\nimport numpy as np\n\nfrom highway_env.utils import not_zero, do_every\nfrom highway_env.types import Vector\nfrom highway_env.road.lane import AbstractLane\nfrom highway_... | [
[
"numpy.dot",
"numpy.sqrt",
"numpy.arctan",
"numpy.clip",
"numpy.random.choice",
"numpy.arcsin",
"numpy.power",
"numpy.cos",
"numpy.arccos",
"numpy.full",
"numpy.concatenate",
"numpy.sin",
"numpy.sign",
"numpy.random.uniform",
"numpy.array",
"numpy.su... |
chaseaucoin/Neural-Primer | [
"d5163af8cd74ea5cea620069dffca8c124bffc05"
] | [
"Numpy XOR/Tensor_ImageRecognition.py"
] | [
"from tensorflow.examples.tutorials.mnist import input_data\r\n\r\n#Get The MNIST Data\r\nmnist = input_data.read_data_sets(\"MNIST_data/\", one_hot=True)\r\n\r\nimport tensorflow as tf\r\n\r\n# Create the model\r\ninputs = tf.placeholder(tf.float32, [None, 784])\r\nweights = tf.Variable(tf.zeros([784, 10]))\r\nbia... | [
[
"tensorflow.matmul",
"tensorflow.nn.softmax_cross_entropy_with_logits",
"tensorflow.InteractiveSession",
"tensorflow.zeros",
"tensorflow.cast",
"tensorflow.placeholder",
"tensorflow.global_variables_initializer",
"tensorflow.train.GradientDescentOptimizer",
"tensorflow.argmax",... |
dan0nchik/FLAML | [
"9d661759b49de6e403d9288af7a015606528fe7e"
] | [
"flaml/model.py"
] | [
"'''!\r\n * Copyright (c) 2020-2021 Microsoft Corporation. All rights reserved.\r\n * Licensed under the MIT License. \r\n'''\r\n\r\nimport numpy as np\r\nimport xgboost as xgb\r\nimport time\r\nfrom sklearn.ensemble import RandomForestRegressor, RandomForestClassifier\r\nfrom sklearn.ensemble import ExtraTreesRegr... | [
[
"numpy.issubdtype",
"scipy.sparse.issparse"
]
] |
haiderstats/survival_evaluation | [
"70e3a4d530a61549609689e3ebd80818f3ab14d9"
] | [
"survival_evaluation/evaluations.py"
] | [
"from typing import Optional\n\nimport numpy as np # type: ignore\nfrom scipy.stats import chi2 # type: ignore\n\nfrom survival_evaluation.types import NumericArrayLike\nfrom survival_evaluation.utility import (\n KaplanMeier,\n KaplanMeierArea,\n to_array,\n validate_size,\n)\n\n\n# pylint: disable=t... | [
[
"numpy.maximum",
"numpy.abs",
"numpy.eye",
"numpy.matmul",
"scipy.stats.chi2.cdf",
"numpy.ones",
"numpy.mean",
"numpy.floor",
"numpy.argsort",
"numpy.array_split",
"numpy.sum",
"numpy.empty"
]
] |
yukyeongleee/CodeTemplate | [
"d0777d501bf64b01ea63787c75b505f7b76ebeda"
] | [
"submodel/resnet.py"
] | [
"import torch.nn as nn\nimport torch.nn.functional as F\nimport torch.utils.model_zoo as modelzoo\nfrom lib.utils import conv3x3\n\n\nresnet18_url = 'https://download.pytorch.org/models/resnet18-5c106cde.pth'\n\n\nclass Resnet18(nn.Module):\n def __init__(self):\n super(Resnet18, self).__init__()\n ... | [
[
"torch.nn.Sequential",
"torch.nn.Conv2d",
"torch.nn.MaxPool2d",
"torch.nn.BatchNorm2d",
"torch.nn.ReLU",
"torch.utils.model_zoo.load_url"
]
] |
ma-kast/AMfe | [
"99686cc313fb8904a093fb42e6cf0b38f8cfd791"
] | [
"amfe/mor/hyper_red/ecsw.py"
] | [
"\"\"\"\nTODO: Write introduction to ECSW\n\"\"\"\n\nimport logging\n\nimport numpy as np\nfrom scipy.linalg import solve as linsolve\nfrom scipy.sparse import csc_matrix\n\nfrom .ecsw_assembly import EcswAssembly\n\n\n__all__ = ['sparse_nnls',\n 'ecsw_assemble_G_and_b',\n 'ecsw_get_weights_by_c... | [
[
"scipy.sparse.csc_matrix",
"numpy.logical_and",
"numpy.min",
"numpy.linalg.norm",
"scipy.linalg.solve",
"numpy.argmax",
"numpy.where",
"numpy.argmin",
"numpy.array",
"numpy.zeros",
"numpy.sum"
]
] |
neurophysik/jitcdde | [
"44d7ed6ad187d3591407155b6eeb063f73e462cd",
"44d7ed6ad187d3591407155b6eeb063f73e462cd",
"44d7ed6ad187d3591407155b6eeb063f73e462cd"
] | [
"tests/test_lyaps.py",
"examples/two_Roesslers.py",
"tests/test_past.py"
] | [
"#!/usr/bin/python3\n# -*- coding: utf-8 -*-\n\n\nimport platform\nimport unittest\nimport numpy as np\nfrom scipy.stats import sem\nfrom jitcdde import t, y, jitcdde_lyap\n\nif platform.system() == \"Windows\":\n\tcompile_args = None\nelse:\n\tfrom jitcxde_common import DEFAULT_COMPILE_ARGS\n\tcompile_args = DEFAU... | [
[
"numpy.random.random",
"numpy.arange",
"numpy.average",
"scipy.stats.sem",
"numpy.array",
"numpy.vstack"
],
[
"numpy.arange",
"numpy.random.normal",
"numpy.savetxt",
"numpy.random.uniform",
"numpy.zeros"
],
[
"numpy.random.random",
"numpy.copy",
"num... |
arj119/adaptive-federated-learning | [
"6c22d65c3a46a0b293dc5ddd4cd579f6010445f5"
] | [
"control_algorithm/adaptive_tau.py"
] | [
"import math\nimport numpy as np\nfrom numpy import linalg\nfrom util.utils import recv_msg, send_msg, moving_average\nfrom config import tau_max\n\n\nclass ControlAlgAdaptiveTauServer:\n def __init__(self, is_adapt_local, dim_w, client_sock_all, n_nodes, control_param_phi,\n moving_average_holdi... | [
[
"numpy.isnan",
"numpy.zeros",
"numpy.linalg.norm",
"numpy.power"
]
] |
PhilippPelz/scikit-pr-open | [
"50833b13160b6afe0a743d63d560bddeee2c18b5"
] | [
"skpr/nn/_functions/Broadcast.py"
] | [
"import torch as th\nfrom torch.autograd import Function\n\nimport skpr.inout as io\n\n\nclass Broadcast(Function):\n @staticmethod\n def forward(ctx, input, ntimes, divide_by_ntimes=True):\n io.logger.debug('Broadcast forward 1')\n # out = input.clone()\n # print 'Broadcast.forward'\n ... | [
[
"torch.sum"
]
] |
k4ntz/XmodRL | [
"dffb416bcd91010d8075ee1ac00cc4b9a3021967"
] | [
"src/xrl/algorithms/minidr/dataset.py"
] | [
"import numpy as np\nimport torch\nfrom torch._C import dtype\nimport torch.nn as nn\nfrom torch.utils.data import Dataset\n\nclass ModelDataset(Dataset):\n def __init__(self, history, history_size):\n self.h = history #history is passed as list and updated outside\n self.history_size = history_siz... | [
[
"numpy.array",
"torch.tensor"
]
] |
saarimrahman/imagenet-testbed | [
"55a867d091c7193225880010853ed2b4b0b73ec9"
] | [
"plotting/paper_hyp_robust_imagenetv2.py"
] | [
"import os\nfrom os.path import join, exists\nimport argparse\nimport pathlib\nfrom enum import Enum\n\nimport click\nimport numpy as np\nimport pandas as pd\n\nimport download_data\nimport dataframe\nimport plotter\nfrom model_types import ModelTypes, model_types_map\n\n\nclass HypModelTypes(Enum):\n HYP_ROBUST... | [
[
"pandas.read_pickle"
]
] |
tjingrant/onnx-tf | [
"3412d86238bf99bf4908e829af115693df161988"
] | [
"test/test_model.py"
] | [
"from __future__ import absolute_import\nfrom __future__ import division\nfrom __future__ import print_function\nfrom __future__ import unicode_literals\n\nimport unittest\nimport numpy as np\nimport tensorflow as tf\nimport onnx\nfrom onnx_tf.backend import run_node, prepare\nfrom onnx import helper\nfrom onnx.onn... | [
[
"numpy.clip",
"numpy.testing.assert_almost_equal",
"numpy.random.randn",
"numpy.exp",
"numpy.array",
"numpy.tanh"
]
] |
tien1504/idinvert_pytorch | [
"19999e9945aef4843a464930426a565256863ded"
] | [
"mix_style.py"
] | [
"# python 3.6\n\"\"\"Mixes styles with In-domain GAN Inversion.\n\nThe real images should be first inverted to latent codes with `invert.py`. After\nthat, this script can be used for style mixing.\n\nNOTE: This script will mix every `style-content` image pair from style\ndirectory to content directory.\n\"\"\"\n\ni... | [
[
"numpy.load"
]
] |
valeoai/POCO | [
"c6ab56b1b7f01c51d1bc6987eae0a8c79725e63f"
] | [
"lightconvpoint/nn/conv_fkaconv.py"
] | [
"import torch\nimport torch.nn as nn\nimport torch.nn.functional as F\nfrom math import ceil\n# from lightconvpoint.spatial import knn, sampling_quantized\nfrom lightconvpoint.utils.functional import batch_gather\nimport torch\n\nclass Convolution_FKAConv(torch.nn.Module):\n\n\n def __init__(self, in_channels, o... | [
[
"torch.sigmoid",
"torch.max",
"torch.Tensor",
"torch.cat",
"torch.nn.Conv2d",
"torch.nn.init.ones_",
"torch.nn.InstanceNorm2d"
]
] |
vyk1/YAFS | [
"514f8362c90923fa28f871fcf179b755a9315c47"
] | [
"src/examples/VRGameFog-IFogSim-WL/testConvergence.py"
] | [
"#!/usr/bin/env python2\n# -*- coding: utf-8 -*-\n\"\"\"\nCreated on Thu Sep 6 16:48:57 2018\n\n@author: isaaclera\n\"\"\"\n\nimport numpy as np\n\nYFAS4 = [11.270442,\n11.270623,\n11.270012,\n11.270021,\n11.270031,\n11.269538,\n11.269547,\n11.268429,\n11.270591,\n11.269940,\n11.268374,\n11.270021,\n11.268418,\n11... | [
[
"numpy.array",
"scipy.stats.describe"
]
] |
jm-begon/globally-induced-forest | [
"bf41640a5f0d9db637877dfa077b1d529539dbc6"
] | [
"gif/datasets/setup.py"
] | [
"import os\n\nimport numpy\nfrom numpy.distutils.misc_util import Configuration\n\n\ndef configuration(parent_package=\"\", top_path=None):\n config = Configuration(\"datasets\", parent_package, top_path)\n\n return config\n\nif __name__ == \"__main__\":\n from numpy.distutils.core import setup\n setup(... | [
[
"numpy.distutils.misc_util.Configuration"
]
] |
Zhanghaotian1/SDE_conf | [
"90773e807ab8ccdc1963e113a2c72df16b8899c1"
] | [
"SDE_CG_C/utils/evaluation.py"
] | [
"import numpy as np\nfrom tqdm.auto import tqdm\n\nimport torch\nfrom torch_geometric.data import Data\nfrom rdkit import Chem\nfrom rdkit.Chem.rdForceFieldHelpers import MMFFOptimizeMolecule\n\nfrom SDE_CG import utils\n\n\ndef get_rmsd_confusion_matrix(data: Data, useFF=False):\n data.pos_ref = data.pos_ref.vi... | [
[
"torch.mean",
"torch.cat",
"torch.sum",
"numpy.ones",
"torch.exp"
]
] |
will-jj/arim | [
"fc15efe171a41355090123fcea10406ee75efe31"
] | [
"arim/plot.py"
] | [
"\"\"\"\nPlotting utilities based on `matplotib <http://matplotlib.org/>`_.\n\nSome default values are configurable via the dictionary ``arim.plot.conf``.\n\n.. py:data:: conf\n\n Dictionary of default values. For some functions, if an argument is not populated,\n its values will be populated from this dictio... | [
[
"numpy.nanmax",
"numpy.rot90",
"matplotlib.ticker.MultipleLocator",
"matplotlib.pyplot.gca",
"numpy.abs",
"numpy.linspace",
"numpy.nanmin",
"matplotlib.pyplot.subplots",
"numpy.rad2deg",
"numpy.mean",
"matplotlib.ticker.FuncFormatter",
"matplotlib.pyplot.figure"
]... |
tanfei2007/DeepM6A | [
"ac8b5543db292516ce10cf42b7506004140d4d41",
"ac8b5543db292516ce10cf42b7506004140d4d41"
] | [
"Motif_Analysis/Code/optimizer.py",
"Code/TSNE/t_SNE_testing_data.py"
] | [
"#*********************\n# Fei Tan\n# ft54@njit.edu\n# March 28, 2017\n#********************\n\n\nimport numpy as np\nimport pprint\n\nfrom keras import backend as K\nfrom collections import OrderedDict\n\nclass Optimizer(object):\n\t\n\tdef __init__(self, seq_input, losses, wrt=None):\n\n\t\tself.seq = seq_i... | [
[
"numpy.array",
"numpy.zeros_like",
"numpy.ones"
],
[
"numpy.random.seed",
"pandas.DataFrame",
"sklearn.manifold.TSNE",
"numpy.random.permutation",
"numpy.array"
]
] |
malikasng/Bbox_HGG_with_CTR_and_RRTstarFND | [
"2b1aae6c347f544fefface0c9f26dc4ecde51108"
] | [
"utils/stable_baselines_plotter.py"
] | [
"# from https://github.com/hill-a/stable-baselines/blob/master/stable_baselines/results_plotter.py\nimport numpy as np\nimport matplotlib\nimport matplotlib.pyplot as plt\nimport pandas as pd\n\n# matplotlib.use('TkAgg') # Can change to 'Agg' for non-interactive mode\nplt.rcParams['svg.fonttype'] = 'none'\n\nX_TI... | [
[
"matplotlib.pyplot.legend",
"matplotlib.pyplot.tight_layout",
"pandas.read_csv",
"matplotlib.pyplot.title",
"matplotlib.pyplot.savefig",
"numpy.lib.stride_tricks.as_strided",
"matplotlib.pyplot.plot",
"matplotlib.pyplot.xlim",
"matplotlib.pyplot.ylabel",
"matplotlib.pyplot.... |
Preston5789/Stock_Regression_Algorithm | [
"f65dd0c710be777628a0c03ce0fa851880cf0d81"
] | [
"stock_plots.py"
] | [
"\r\nimport matplotlib.pyplot as plt\r\nimport numpy\r\nimport time\r\nfrom matplotlib.widgets import Button\r\n\r\nfrom stock_trade import Jesus\r\nfrom stock_connect import Connection\r\nfrom stock_reg import Errors\r\n\r\nerr = Errors()\r\n\r\ngraphswitcheroo = 0\r\n\r\n\r\ncon = Connection()\r\njes = Jesus()\r\... | [
[
"matplotlib.pyplot.connect",
"matplotlib.widgets.Button",
"matplotlib.pyplot.subplots",
"matplotlib.pyplot.draw",
"matplotlib.pyplot.axes",
"numpy.array",
"matplotlib.pyplot.ion",
"matplotlib.pyplot.pause"
]
] |
rayjyh/PyTorch_CIFAR10_rram_compenstion | [
"61a53c85a74abc965a5bea3e4b102e9a7ad8f03a"
] | [
"modify_weights.py"
] | [
"import numpy as np\nimport matplotlib.pyplot as plt\nimport torch\n\n'''\ncompensation = {\n \"no_comp\":\n \"simple\":\n \"dynamic\":\n \"bias\":\n \"double_sim\":\n}\n'''\n\nquantized = True\nvisualize = False\nsymmetric = True\n\n\ndef asym_quant_param(w, k):\n num_intervals = 2 ** k - 1\n ... | [
[
"torch.normal",
"torch.abs",
"torch.mean",
"matplotlib.pyplot.legend",
"torch.ones",
"torch.max",
"torch.round",
"torch.min",
"torch.zeros_like",
"matplotlib.pyplot.savefig",
"torch.where",
"torch.arange",
"torch.chunk",
"matplotlib.pyplot.close",
"torch... |
Dzhange/rex-gym | [
"3ffb674ade13ceac3352c3329f1804eb21a08403"
] | [
"rex_gym/envs/gym/walk_env.py"
] | [
"\"\"\"This file implements the gym environment of rex alternating legs.\n\n\"\"\"\nimport math\nimport random\n\nfrom gym import spaces\nimport numpy as np\nfrom .. import rex_gym_env\nfrom ...model import rex_constants\nfrom ...model.gait_planner import GaitPlanner\nfrom ...model.kinematics import Kinematics\n\nN... | [
[
"numpy.asarray",
"numpy.array"
]
] |
cabbagerice/word-chain | [
"5d2978df61a7136f502b1b601213e97454103e1e"
] | [
"kakunin.py"
] | [
"import firebase_admin\nfrom firebase_admin import credentials\nfrom firebase_admin import db\nfrom numpy import random as unko\nimport math\n\n\n#認証ファイルPATH\ncertificate_json_path='secret.json'\n#DBとアプリへの認証\nif (not len(firebase_admin._apps)):\n\tcred = credentials.Certificate(certificate_json_path) \n\tdefault_ap... | [
[
"numpy.random.rand"
]
] |
weihao94/keras-YOLOv3-model-set | [
"7b54809d5f5513a41a191289625612d71056e3ec"
] | [
"yolo2/models/layers.py"
] | [
"#!/usr/bin/env python3\n# -*- coding: utf-8 -*-\n\"\"\"\nCommon layer definition for YOLOv2 models building\n\"\"\"\nfrom functools import wraps, reduce, partial\n\nimport tensorflow.keras.backend as K\nfrom tensorflow.keras.layers import Conv2D, DepthwiseConv2D, MaxPooling2D, Concatenate, Lambda\nfrom tensorflow.... | [
[
"tensorflow.keras.layers.DepthwiseConv2D",
"tensorflow.keras.layers.Concatenate",
"tensorflow.keras.layers.LeakyReLU",
"tensorflow.keras.layers.Lambda",
"tensorflow.keras.regularizers.l2",
"tensorflow.keras.layers.Conv2D",
"tensorflow.nn.space_to_depth",
"tensorflow.keras.backend.g... |
mxndrwgrdnr/evictions | [
"bf59bfe98903c2aa839daf7597951dc36cdecaad"
] | [
"scripts/get_assessor_data.py"
] | [
"#######################################################\n# script to compile and standardize raw assessor data #\n#######################################################\n\n\nimport pandas as pd\nfrom tqdm import tqdm\nfrom geopy.geocoders import Nominatim\nfrom geopy.extra.rate_limiter import RateLimiter\nimport ... | [
[
"pandas.concat",
"pandas.read_excel",
"pandas.read_csv",
"pandas.isnull",
"pandas.DataFrame"
]
] |
MaximumEntropy/pytorch-lightning | [
"d8c501b22bc2c02a4bedb8b686daa5f904d6cf23"
] | [
"pytorch_lightning/trainer/data_loading.py"
] | [
"# Copyright The PyTorch Lightning team.\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n# http://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless required by applicable law... | [
[
"torch.utils.data.SequentialSampler"
]
] |
egreen-park/crwusiz | [
"da528ebea9945f5a2a0a286467bb1c349aa7472f"
] | [
"selfdrive/controls/lib/lane_planner.py"
] | [
"from common.numpy_fast import interp\nimport numpy as np\nfrom selfdrive.hardware import EON, TICI\nfrom cereal import log\n\n\nTRAJECTORY_SIZE = 33\n# camera offset is meters from center car to camera\nif EON:\n CAMERA_OFFSET = 0.10\n PATH_OFFSET = 0.0\nelif TICI:\n CAMERA_OFFSET = -0.04\n PATH_OFFSET = -0.04... | [
[
"numpy.array",
"numpy.zeros",
"numpy.interp"
]
] |
cattech-lab/cantera_examples | [
"13e969b2a767bed5bb0d79adf86187cd9fbd090d"
] | [
"ic_engine.py"
] | [
"\"\"\"\nSimulation of a internal combustion engine.\n\"\"\"\n\nimport cantera as ct\nimport numpy as np\nimport csv\n\n#------------------------------------------------------\n# Input Parameters\nrpm = 600.0 # engine speed [rpm]\nbore = 82.55 # bore diameter [mm]\nstroke = 114.3 # stroke [mm]\ncratio = 10.0 # c... | [
[
"numpy.arange",
"numpy.cos",
"numpy.sin",
"matplotlib.pyplot.show",
"numpy.sum",
"matplotlib.pyplot.figure"
]
] |
deKeijzer/SRON-DCGAN | [
"1ead827ebf549917435e6bc9ddd2d4d5951aa205"
] | [
"notebooks/model_v2_small.py"
] | [
"# General imports\nfrom __future__ import print_function\n#%matplotlib inline\nimport argparse\nimport os\nimport random\nimport torch\nimport torch.nn as nn\nimport torch.nn.parallel\nimport torch.backends.cudnn as cudnn\nimport torch.optim as optim\nimport torch.utils.data\nimport torchvision.datasets as dset\ni... | [
[
"torch.nn.ConvTranspose2d",
"torch.nn.Conv2d",
"torch.nn.Sigmoid",
"torch.nn.Tanh",
"torch.nn.LeakyReLU"
]
] |
rafalou38/mangafetch | [
"6bd313f9b9cfb2ea729e49d382a4085c9aaf094e"
] | [
"src/images.py"
] | [
"import PIL.Image\nimport numpy\nimport os\n\n\ndef tile(image_path):\n try:\n ratio = 1.4\n image = PIL.Image.open(image_path)\n image = numpy.array(image)\n height = image.shape[1] * ratio\n\n if image.shape[1] * 2 < image.shape[0]:\n # width = image.shape[0]\n ... | [
[
"numpy.array"
]
] |
caegomezji/FORDAT | [
"450dca5a9b0c059429421b773be3e7d54367fdcf"
] | [
"forecasting.py"
] | [
"# ARIMA example\nfrom statsmodels.tsa.arima.model import ARIMA\nimport numpy as np\nfrom statsmodels.tools.eval_measures import rmse\nimport pmdarima as pm\nfrom fbprophet import Prophet\nfrom time import time\nimport matplotlib.pyplot as plt\nimport pandas as pd\nimport math\n\ndef BIC(y_real, y_model):\n n = ... | [
[
"pandas.Series"
]
] |
guglielmocola/RetweetCascade | [
"f96319d0107473715104acceb2ff0925d35dd9e3"
] | [
"retweetcascade/rt_cascade_friendships.py"
] | [
"import pandas as pd\nfrom retweetcascade.utility_functions import __convert_to_pandas_list_tw, __explode_dict\n\n\ndef rt_cascade_friendships(retweets, followers, friends, **kwargs):\n \"\"\"Estimate the retweet cascade based on friendship among retweeters.\n A retweeter X is linked to the root R (original t... | [
[
"pandas.concat",
"pandas.DataFrame"
]
] |
joshliu11/DSGN | [
"ac693e748ff3a7372b1292c2b7b3796854072030"
] | [
"dsgn/utils/torch_utils.py"
] | [
"import numpy as np\n\nimport torch\n\ndef project_image_to_rect(uv_depth, P):\n # uv_depth (3, N)\n\n c_u = P[0,2]\n c_v = P[1,2]\n f_u = P[0,0]\n f_v = P[1,1]\n b_x = P[0,3]/(-f_u) # relative \n b_y = P[1,3]/(-f_v)\n\n # use camera coordinate\n n = uv_depth.shape[1]\n x = ((uv_depth[... | [
[
"torch.transpose",
"torch.ones",
"torch.cat",
"torch.sqrt",
"numpy.sign",
"torch.stack",
"torch.meshgrid",
"torch.atan2"
]
] |
meyer-lab/type-I-ckine-model | [
"bc0451610655633483a98ab450d20ef631479d2b"
] | [
"ckine/figures/figureC12.py"
] | [
"import os\nimport matplotlib.lines as mlines\nimport pandas as pds\nimport numpy as np\nfrom .figureCommon import subplotLabel, getSetup\nfrom ..flow import importF\nfrom ..PCA import sampleT\nfrom ..flow import gating, count_data\n\nfrom ..FCimports import compMatrix, applyMatrix\n\npath_here = os.path.dirname(os... | [
[
"numpy.amax",
"matplotlib.lines.Line2D",
"numpy.percentile",
"pandas.DataFrame",
"numpy.mean",
"pandas.DataFrame.from_dict",
"numpy.array"
]
] |
ravising-h/Grad-CAM.pytorch | [
"e0a1ae3870ea189f9b4cd8782eb77bfb5293c31b"
] | [
"detection/demo_retinanet.py"
] | [
"# -*- coding: utf-8 -*-\n\"\"\"\n @File : demo_retinanet.py\n @Time : 2020/5/16 下午9:59\n @Author : yizuotian\n @Description :\n\"\"\"\n\nimport argparse\nimport multiprocessing as mp\nimport os\n\nfrom tqdm import tqdm\nimport matplotlib.pyplot as plt\nfrom mpl_toolkits.axes_grid1 import ImageGrid\nimpor... | [
[
"numpy.min",
"numpy.uint8",
"numpy.max",
"numpy.float32",
"matplotlib.pyplot.figure"
]
] |
sayan2207/Class-Predictor | [
"191d98ca4d10d75fef24a4b6b78022c57679d4bc"
] | [
"predict_class_sklearn.py"
] | [
"import numpy as np\nimport random\nimport scipy.stats as ss\nimport matplotlib.pyplot as plt\nfrom matplotlib.colors import ListedColormap as lcm\nfrom sklearn.neighbors import KNeighborsClassifier as knc\nfrom time import strftime as stime\nimport os\n\ndef synthetic_plot(limits=(-5,5,-5,5), unit=0.1, no_of_point... | [
[
"matplotlib.pyplot.legend",
"numpy.max",
"numpy.arange",
"sklearn.neighbors.KNeighborsClassifier",
"numpy.repeat",
"numpy.zeros",
"matplotlib.pyplot.figure",
"numpy.min",
"matplotlib.pyplot.savefig",
"matplotlib.colors.ListedColormap",
"matplotlib.pyplot.pcolormesh",
... |
apigott/dra | [
"c2f24d9ef6d9d8cb78c5a058574cec8e132afd4f"
] | [
"dragg/reformat.py"
] | [
"import os\nimport sys\nimport json\nimport toml\nfrom datetime import datetime, timedelta\nimport numpy as np\nimport pandas as pd\nimport itertools as it\nimport random\n\nimport plotly.graph_objects as go\nimport plotly.express as px\nfrom plotly.subplots import make_subplots\nimport plotly.io as pio\nimport plo... | [
[
"numpy.clip",
"numpy.arange",
"numpy.subtract",
"numpy.cumsum",
"numpy.std",
"numpy.average",
"numpy.array",
"numpy.divide"
]
] |
NunoEdgarGFlowHub/entropica_qaoa | [
"bc9496320dbeadeac1302bda056e9d7b67607e30"
] | [
"entropica_qaoa/tests/test_vqe.py"
] | [
"\"\"\"\nTest that all the components of vqe play nicely together\n\"\"\"\n\nimport numpy as np\nimport pytest\nfrom scipy.optimize import minimize\n\nfrom pyquil.paulis import PauliSum, PauliTerm\nfrom pyquil.api import WavefunctionSimulator, local_qvm, get_qc\nfrom pyquil.quil import Program\nfrom pyquil.gates im... | [
[
"scipy.optimize.minimize",
"numpy.allclose"
]
] |
manjavacas/drl-building | [
"6aaa117c0d02b0349af227939460adf31d8d40d9"
] | [
"agents/DQN.py"
] | [
"#!/usr/bin/python3\n\nimport gym\nimport energym\nimport argparse\nimport uuid\nimport mlflow\n\nimport numpy as np\n\nfrom energym.utils.callbacks import LoggerCallback, LoggerEvalCallback\nfrom energym.utils.wrappers import NormalizeObservation, LoggerWrapper\n\nfrom stable_baselines3 import DQN\nfrom stable_bas... | [
[
"numpy.mean"
]
] |
fontysrobotics/Blackboard_based_distributed_fleet_manager | [
"a6b44738fe67f4948a69f8d45da58d981c6724e0"
] | [
"catkin_ws/simulation/rviz_tools_py-master/src/rviz_tools_py/rviz_tools.py"
] | [
"#!/usr/bin/env python\n\n# Copyright (c) 2015, Carnegie Mellon University\n# All rights reserved.\n# Authors: David Butterworth <dbworth@cmu.edu>\n#\n# Redistribution and use in source and binary forms, with or without\n# modification, are permitted provided that the following conditions are met:\n#\n# - Redistrib... | [
[
"numpy.matrix",
"numpy.fabs"
]
] |
lclc19/vertex-ai-samples | [
"1844df54a6fc3d7afff1110a6758afaf13181b19"
] | [
"community-content/tf_keras_text_classification_distributed_single_worker_gpus_with_gcloud_local_run_and_vertex_sdk/trainer/task.py"
] | [
"# Copyright 2021 Google LLC\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n# https://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless required by applicable law or agreed ... | [
[
"tensorflow.keras.preprocessing.text_dataset_from_directory",
"tensorflow.keras.layers.Activation",
"tensorflow.keras.layers.experimental.preprocessing.TextVectorization",
"tensorflow.keras.losses.SparseCategoricalCrossentropy",
"tensorflow.keras.layers.Embedding",
"tensorflow.keras.layers... |
hfisser/s2_trucks | [
"323e73edb82e314e6695e8cf8d89c2de22f54b04"
] | [
"detect_trucks/TruckDetector.py"
] | [
"####################################################\n# Author: Henrik Fisser, 2020\n####################################################\n\nfrom array_utils.plot import plot_img\n\nimport os, warnings\nimport pandas as pd\nimport numpy as np\nimport geopandas as gpd\nimport xarray as xr\nfrom shapely.geometry imp... | [
[
"numpy.nanmax",
"numpy.dot",
"numpy.nanmedian",
"numpy.round",
"numpy.max",
"numpy.zeros_like",
"numpy.nanmean",
"scipy.stats.spearmanr",
"numpy.nanstd",
"numpy.where",
"numpy.hstack",
"numpy.unique",
"numpy.clip",
"numpy.arange",
"numpy.int8",
"nump... |
adam-coogan/pyro | [
"6395b0f5f0b4744d3c822a39526027fb3fdb8b04"
] | [
"pyro/distributions/empirical.py"
] | [
"from __future__ import absolute_import, division, print_function\n\nimport math\nimport numbers\n\nimport torch\nfrom torch.distributions import constraints\n\nfrom pyro.distributions.torch import Categorical\nfrom pyro.distributions.torch_distribution import TorchDistribution\nfrom pyro.distributions.util import ... | [
[
"torch.Size",
"torch.cat",
"torch.tensor",
"torch.arange",
"torch.stack",
"torch.pow"
]
] |
maxrudolph1/robotarium_mpe | [
"025c182899c0092c95e1ed3c2a38117f257cbe25"
] | [
"sim_results/results/read_results.py"
] | [
"import numpy as np\nfrom matplotlib import pyplot as plt\nimport pandas as pd\nimport seaborn as sb\nimport matplotlib.patches as mpatches\nfrom scipy.stats import mannwhitneyu\nsb.set_theme(style=\"darkgrid\")\n\nbcfc_rew = []\nunif_rew = []\nmono_rew = []\nrand_rew = []\n\ntasks = ['navigation','coverage','trans... | [
[
"numpy.logical_not",
"numpy.sum",
"matplotlib.pyplot.subplots",
"pandas.DataFrame",
"scipy.stats.mannwhitneyu",
"matplotlib.pyplot.close",
"numpy.load",
"numpy.array",
"matplotlib.pyplot.show",
"matplotlib.pyplot.pause"
]
] |
lukassnoek/MVCA | [
"dd194140a5babb4605b9248d34508b9d9e4f799c"
] | [
"analyses/utils.py"
] | [
"import numpy as np\nfrom scipy.special import hyp2f1, gammaln\n\n\ndef get_r2(iv, dv, stack_intercept=True):\n \"\"\" Regress dv onto iv and return r-squared.\n \n Parameters\n ----------\n iv : numpy array\n Array of shape N (samples) x K (features)\n dv : numpy array\n Array of sh... | [
[
"numpy.log",
"numpy.sqrt",
"numpy.ones",
"numpy.linalg.lstsq",
"scipy.special.hyp2f1",
"scipy.special.gammaln",
"numpy.exp",
"numpy.sum"
]
] |
rongqingpin/iOS_app_data | [
"c9beecfb3878f64568b1d9626412ba6b346934cd"
] | [
"app_data2.py"
] | [
"import pandas as pd\nimport csv\nimport json\nimport re\n\n# load the category IDs\nflc = '/Users/pinqingkan/Desktop/Codes/Project_iTunes/'\n#flc = '/Users/Melanie/Library/Mobile Documents/com~apple~CloudDocs/Desktop/Codes/Project_iTunes/'\nfname = flc + 'IDs/iosapp_categories.csv'\nX0 = pd.read_csv(fname)\n# remo... | [
[
"pandas.read_csv",
"pandas.read_json",
"pandas.DataFrame"
]
] |
cjwang/pyEX | [
"1b5f40f80110afaa4809ea48fac067033c7bdf89"
] | [
"pyEX/stocks/batch.py"
] | [
"# -*- coding: utf-8 -*-\nimport itertools\nimport pandas as pd\nfrom multiprocessing.pool import ThreadPool\nfrom ..common import _TIMEFRAME_CHART, _getJson, _raiseIfNotStr, PyEXception, _strOrDate, _toDatetime, _BATCH_TYPES\nfrom .fundamentals import _dividendsToDF, _earningsToDF, _financialsToDF, _splitsToDF\nfr... | [
[
"pandas.concat",
"pandas.DataFrame"
]
] |
kfirsalo/New-Graph-ZSL | [
"76ccd15e65e915858dca9d9097ddf9252e4250d3",
"76ccd15e65e915858dca9d9097ddf9252e4250d3"
] | [
"graph_ZSL_w_argmin.py",
"images_graph_creator.py"
] | [
"import json\nimport multiprocessing\nfrom datetime import datetime\n\nfrom node2vec import Node2Vec\nimport pandas as pd\nimport numpy as np\nimport networkx as nx\nimport pickle\nimport os\nimport argparse\nfrom numpy import linalg as la\nfrom sklearn.metrics.pairwise import cosine_similarity\nfrom sklearn import... | [
[
"numpy.abs",
"numpy.random.seed",
"numpy.logspace",
"numpy.subtract",
"sklearn.metrics.pairwise.cosine_similarity",
"numpy.ones",
"numpy.concatenate",
"numpy.argmax",
"torch.cuda.is_available",
"numpy.column_stack",
"numpy.argsort",
"numpy.repeat",
"numpy.array"... |
HypnosPy/HypnosPy | [
"28b17d07ee78f7714bbbbd66f6253764addf9d94"
] | [
"healthyForce/MTLModels.py"
] | [
"import torch\nimport torch.nn as nn\nimport torch.optim as optim\nimport numpy as np\n\nclass MTL:\n def __init__(self):\n pass\n\n def aggregate_losses(self, losses):\n pass\n\n def adjust_after_validation(self, losses, epoch):\n pass\n\n\nclass MTLRandom(MTL):\n def __init__(self... | [
[
"numpy.log",
"torch.ones",
"torch.zeros",
"torch.argmax",
"torch.exp",
"numpy.random.randint"
]
] |
raphaelchaves/transitionMatrix | [
"6ac54c8c6ce15dc81aa5e894cfcfabb127634b33"
] | [
"examples/python/matrix_from_duration_data.py"
] | [
"# encoding: utf-8\n\n# (c) 2017-2020 Open Risk, all rights reserved\n#\n# TransitionMatrix is licensed under the Apache 2.0 license a copy of which is included\n# in the source distribution of TransitionMatrix. This is notwithstanding any licenses of\n# third-party software included in this distribution. You may n... | [
[
"pandas.read_csv"
]
] |
karino2/Pytorch-Handwritten-Mathematical-Expression-Recognition | [
"6c6139624c71fa68a0a386a94346cfab39d0f087"
] | [
"Train.py"
] | [
"'''\nPython 3.6 \nPytorch 0.4\nWritten by Hongyu Wang in Beihang university\n'''\nimport torch\nimport math\nimport torch.nn as nn\nfrom torch.autograd import Variable\nimport torch.nn.functional as F\nimport numpy\nimport torch.utils.data as data\nfrom data_iterator import dataIterator\nfrom Densenet_torchvision ... | [
[
"torch.mean",
"torch.LongTensor",
"torch.nn.CrossEntropyLoss",
"torch.load",
"torch.zeros",
"torch.utils.data.DataLoader",
"torch.tanh",
"numpy.array"
]
] |
PlusLabNLP/PredictiveEngagement | [
"214d3eb20901982d192b05b4d496420dfb273f8e"
] | [
"pytorch_src/engagement_classifier.py"
] | [
"import random\nimport numpy as np\nimport torch \nimport torch.optim as optim\nimport matplotlib.pyplot as plt\nfrom sklearn.metrics import classification_report, roc_auc_score\nimport pickle\nimport torch.nn as nn\nimport os \nimport csv\n\nrandom.seed(1000)\nnp.random.seed(1000)\ntorch.manual_seed(1000)\n# torch... | [
[
"matplotlib.pyplot.legend",
"torch.nn.functional.softmax",
"torch.load",
"torch.cat",
"matplotlib.pyplot.plot",
"torch.cuda.is_available",
"torch.save",
"torch.nn.Dropout",
"torch.nn.CrossEntropyLoss",
"torch.tensor",
"torch.nonzero",
"matplotlib.pyplot.figure",
... |
keshuichonglx/tatk | [
"7e8ad18ca98b105cb0168192bddf80b747067c1b"
] | [
"tatk/policy/rule/camrest/rule.py"
] | [
"# -*- coding: utf-8 -*-\nimport torch\nfrom tatk.policy.policy import Policy\nfrom tatk.policy.rule.camrest.rule_based_camrest_bot import RuleBasedCamrestBot\nfrom tatk.policy.rule.camrest.policy_agenda_camrest import UserPolicyAgendaCamrest\n\nDEVICE = torch.device(\"cuda\" if torch.cuda.is_available() else \"cpu... | [
[
"torch.cuda.is_available"
]
] |
lpierezan/cp_playground | [
"818d116391b762c1ca03be772a50bb997b7958a4"
] | [
"linalg/lu_decomp.py"
] | [
"import numpy as np\n\ndef lu_decomp(A):\n n = len(A)\n U = A.copy()\n L = np.eye(n)\n row_idx = list(range(n))\n\n for col in range(n):\n # find best row\n best_row, best_elem = None, None\n for row in range(col,n):\n row_i = row_idx[row]\n elem = U[row_i][... | [
[
"numpy.linalg.solve",
"numpy.random.random",
"numpy.allclose",
"numpy.random.seed",
"numpy.isclose",
"numpy.eye",
"numpy.random.uniform",
"numpy.zeros",
"numpy.random.randint"
]
] |
kunalvats/featuretools | [
"25d8a36b7d636546161122095f5d6ca793a0b974"
] | [
"featuretools/computational_backends/pandas_backend.py"
] | [
"import cProfile\nimport logging\nimport os\nimport pstats\nimport sys\nimport warnings\nfrom datetime import datetime\n\nimport numpy as np\nimport pandas as pd\nimport pandas.api.types as pdtypes\nfrom future import standard_library\n\nfrom .base_backend import ComputationalBackend\nfrom .feature_tree import Feat... | [
[
"pandas.api.types.is_categorical_dtype",
"pandas.merge",
"pandas.concat",
"pandas.api.types.CategoricalDtype",
"pandas.DataFrame"
]
] |
uniomni/PyRate | [
"f77ad6e7fd90f3c0eb255bd553d4666b5db40bcf"
] | [
"tests/test_refpixel.py"
] | [
"# This Python module is part of the PyRate software package.\n#\n# Copyright 2020 Geoscience Australia\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://... | [
[
"numpy.isnan"
]
] |
svebk/py-faster-rcnn | [
"1d0c40c42930f8e89634c057a0ed902aace395bd"
] | [
"lib/fast_rcnn/config.py"
] | [
"# --------------------------------------------------------\n# Fast R-CNN\n# Copyright (c) 2015 Microsoft\n# Licensed under The MIT License [see LICENSE for details]\n# Written by Ross Girshick\n# --------------------------------------------------------\n\n\"\"\"Fast R-CNN config system.\n\nThis file specifies defa... | [
[
"numpy.array"
]
] |
KentaroKutsukake/Integrating-multiple-materials-science-projects | [
"a6f09583718fc00431a3ce67d5fc6f026646f91c"
] | [
"codes/MIGraph/Encoders/CompoundEncoder.py"
] | [
"\n\"\"\"\nCompound encoder\nthis class returns vector information of a target smiles\n\"\"\"\n\nimport numpy as np\nfrom Config import Config\n\nCF=Config()\ncategoryEmbed=CF.categoryEmbed\n\n\n#compound encoder class\nclass CompEncoder:\n def __init__(self,CompDat,num):\n \"\"\"\n CompDat: CompDa... | [
[
"numpy.concatenate",
"numpy.array"
]
] |
broestls/pycuda-bw-test | [
"0ac9a377363bb99bc1b9e5dd42bbdd0bd6d697c3"
] | [
"bwt.py"
] | [
"import numpy as np\n\nimport pycuda.driver as cuda\nfrom pycuda.compiler import SourceModule\nfrom pycuda.tools import make_default_context, clear_context_caches\n\nimport glob\nimport sys\nimport os\nfrom datetime import datetime\nimport ctypes\nimport atexit\nimport argparse\nimport subprocess\nimport psutil\nim... | [
[
"numpy.empty_like"
]
] |
marcoalsina/araucaria | [
"78039106ae27d3fdef9265503c33f33992199d8e"
] | [
"docs/build/html/xas/xas_ft-5.py"
] | [
"from numpy import arange, sin, pi\nfrom scipy.fftpack import fftfreq\nfrom araucaria.xas import ftwindow, xftf_kwin, xftr_kwin\nnfft = 2048 # number of points for FFT\nks = 0.05 # delta k (angstrom^-1)\nf1 = 0.5 # freq1 (angstrom)\nk = arange(0, 10, ks)\nwink = ftwindow(k, x_range=(0,10), dx1=0.5, win='... | [
[
"numpy.arange",
"matplotlib.pyplot.show",
"scipy.fftpack.fftfreq",
"numpy.sin"
]
] |
KirillDZR/supreme | [
"c296722599363bd0cbcce6877bd9de9b066cb74b"
] | [
"supreme/lib/klt/setup.py"
] | [
"from supreme._build import CExtension\n\ndef configuration(parent_package='', top_path=None):\n from numpy.distutils.misc_util import Configuration, get_numpy_include_dirs\n\n config = Configuration('klt', parent_package, top_path)\n\n config.ext_modules.append(CExtension('libklt_',\n ... | [
[
"numpy.distutils.misc_util.Configuration"
]
] |
davidarps/NeuroX | [
"591cabce7a317d2a1ff2b07e6a3b277250815454"
] | [
"neurox/interpretation/utils.py"
] | [
"import math\nimport numpy as np\n\nfrom imblearn.under_sampling import RandomUnderSampler\n\ndef isnotebook():\n \"\"\"\n Utility function to detect if the code being run is within a jupyter\n notebook. Useful to change progress indicators for example.\n\n Returns\n -------\n isnotebook : bool\n ... | [
[
"numpy.zeros",
"numpy.unique"
]
] |
DennisSoemers/rliable | [
"9f4c97d59196b70518f1ee3ba6d4f03a302c3241"
] | [
"rliable/library.py"
] | [
"# coding=utf-8\n# Copyright 2021 The Rliable Authors.\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n# http://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless required by ap... | [
[
"numpy.vectorize",
"numpy.mean",
"numpy.random.choice"
]
] |
NREL/WaterTAP3 | [
"74b83dbd189784ccfddac4bc5d27002190473619"
] | [
"watertap3/watertap3/wt_units/ion_exchange.py"
] | [
"import pandas as pd\nfrom pyomo.environ import *\nfrom pyomo.environ import units as pyunits\nfrom pyomo.repn.plugins.baron_writer import NonNegativeReals\n\nfrom watertap3.utils import financials\nfrom watertap3.wt_units.wt_unit import WT3UnitProcess\n\n## REFERENCE: ADD REFERENCE HERE\n\nmodule_name = 'ion_excha... | [
[
"pandas.read_csv"
]
] |
mateus2810/atividadesIa | [
"0ffc816c962889fb9e0b9635692d616e46a0d0c5"
] | [
"atividade2/RetornarVerticesAdjacentes.py"
] | [
"#Questão 7 - Retornar os vertes adjacentes\n\nimport numpy as np\n\nmatrixIa = [[0,5,0,0,15,2], [5,0,0,9,22,4], [0,0,0,13,1,0], [9,0,12,0,0,6], [15,22,1,0,0,0], [2,4,0,6,0,0]]\n#Mostrar os vertes adjacentes ]\n\nprint(np.matrix(matrixIa))\n"
] | [
[
"numpy.matrix"
]
] |
wbernoudy/dimod | [
"c39677b4a743574dc795bc140dce703abd61087b"
] | [
"dimod/utilities.py"
] | [
"# Copyright 2018 D-Wave Systems Inc.\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n# http://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless required by ap... | [
[
"numpy.log2",
"numpy.asarray",
"numpy.issubdtype",
"numpy.promote_types",
"numpy.require"
]
] |
braedynl/DasCrazy | [
"02a3e41631929eaf402116d25299ec252f6fee2f"
] | [
"clean.py"
] | [
"import pandas as pd\n\nfrom util import load\n\n\ndef main(raw_filename: str, clean_filename: str) -> None:\n raw_data = load(raw_filename)\n clean_data = pd.DataFrame(columns=raw_data.columns)\n\n # First chat message to signal a \"das crazy\" moment\n indicator_row = None\n\n for _, row in raw_dat... | [
[
"pandas.DataFrame"
]
] |
reic/groupLearning-Python-100-Days | [
"91746e6ee3acf2dbf0e9d324f6c6ce3cb91ed131"
] | [
"RE/grb2fig.py"
] | [
"import pandas as pd\nimport os\nimport numpy as np\nimport matplotlib.pyplot as plt\nimport concurrent.futures\n\n\ndef grb_aggr(files, grb_xlsFileName):\n dft = []\n for file in files:\n dft.append(pd.read_excel(file))\n df = pd.concat(dft, ignore_index=True)\n # 輸出合併檔\n df.to_excel(grb_xlsF... | [
[
"pandas.concat",
"pandas.read_excel",
"matplotlib.pyplot.plot",
"pandas.ExcelWriter",
"matplotlib.pyplot.xlabel",
"pandas.pivot_table",
"matplotlib.pyplot.show",
"matplotlib.pyplot.ylabel"
]
] |
HumHongeKamyaab/scipy | [
"ce61e02e912d15ea28b37ea036334b9ba266ebb5"
] | [
"scipy/special/tests/test_data.py"
] | [
"import os\n\nimport numpy as np\nfrom numpy import arccosh, arcsinh, arctanh\nfrom numpy.testing import suppress_warnings\nimport pytest\n\nfrom scipy.special import (\n lpn, lpmn, lpmv, lqn, lqmn, sph_harm, eval_legendre, eval_hermite,\n eval_laguerre, eval_genlaguerre, binom, cbrt, expm1, log1p, zeta,\n ... | [
[
"scipy.special.mathieu_modcem1",
"scipy.special.mathieu_sem",
"scipy.special.zeta",
"numpy.sqrt",
"scipy.special.expm1",
"scipy.special.ellipk",
"scipy.special.gdtrib",
"scipy.special.mathieu_modcem2",
"scipy.special.poch",
"scipy.special.bdtrik",
"scipy.special.mathieu... |
dahburj/tf2-gnn | [
"ac6247c44957b35a478de4bbe13c0c96e82f0ba1"
] | [
"tf2_gnn/data/jsonl_graph_dataset.py"
] | [
"\"\"\"General dataset class for datasets stored as JSONLines files.\"\"\"\nimport logging\nfrom typing import Any, Dict, Iterator, List, Optional, Tuple, Set\n\nimport numpy as np\nfrom dpu_utils.utils import RichPath\n\nfrom .graph_dataset import DataFold, GraphDataset, GraphSampleType, GraphSample\n\nlogger = lo... | [
[
"numpy.array",
"numpy.zeros",
"numpy.random.shuffle"
]
] |
TheLortex/rust-mcts | [
"10d0700cef7df7059b7cbacc609d173580203fa9"
] | [
"settings.py"
] | [
"\ndef dir_name(config, method):\n if config.game.kind == \"Breakthrough\":\n return \"{}-breakthrough-{}\".format(method, config.game.size)\n elif config.game.kind == \"Gym\":\n return \"{}-gym-{}\".format(method, config.game.name)\n else:\n print(\"Unknown game in config file.\")\n ... | [
[
"numpy.abs",
"numpy.clip",
"tensorflow.keras.losses.categorical_crossentropy",
"numpy.sign",
"numpy.floor",
"numpy.zeros"
]
] |
makra89/Quake_AI | [
"8df69c75b117079f5e40929341c4638e741de11d"
] | [
"yolov3_tf2/models.py"
] | [
"import numpy as np\nimport tensorflow as tf\nfrom tensorflow.keras import Model\nfrom tensorflow.keras.layers import (\n Add,\n Concatenate,\n Conv2D,\n Input,\n Lambda,\n LeakyReLU,\n MaxPool2D,\n UpSampling2D,\n ZeroPadding2D,\n BatchNormalization,\n)\nfrom tensorflow.keras.regulari... | [
[
"tensorflow.concat",
"tensorflow.zeros",
"tensorflow.stack",
"tensorflow.reduce_sum",
"tensorflow.cast",
"tensorflow.keras.layers.ZeroPadding2D",
"tensorflow.keras.layers.Concatenate",
"tensorflow.keras.layers.LeakyReLU",
"tensorflow.keras.regularizers.l2",
"tensorflow.kera... |
ASVincent/wagl | [
"cf3a72e53e53f3a7b2f2b5308068069b1b714f2a"
] | [
"wagl/data.py"
] | [
"\"\"\"\nData access functions\n---------------------\n\"\"\"\n\nfrom __future__ import absolute_import\nfrom os.path import join as pjoin, basename, dirname\nimport subprocess\nimport tempfile\nimport logging\nimport numpy as np\nimport h5py\nimport rasterio\n\nfrom rasterio.crs import CRS\nfrom rasterio.warp impo... | [
[
"numpy.uint8",
"numpy.zeros",
"numpy.empty"
]
] |
mrdbarros/csgo_analyze | [
"a4d7487bd56a14a99dc762920965060a5a43fa15"
] | [
"models.py"
] | [
"import data_loading\nimport torch\n\n\n\n\n\ndef emb_sz_rule(n_cat):\n \"Rule of thumb to pick embedding size corresponding to `n_cat`\"\n return min(600, round(1.6 * n_cat ** 0.56))\n\n\nclass LinBnDrop(torch.nn.Sequential):\n \"Module grouping `BatchNorm1d`, `Dropout` and `Linear` layers\"\n\n def __... | [
[
"torch.nn.Sequential",
"torch.nn.Dropout",
"torch.nn.BatchNorm1d",
"torch.cat",
"torch.sum",
"torch.nn.Linear",
"torch.no_grad",
"torch.nn.ReLU"
]
] |
tomiock/qGAN | [
"fb98a2b5286eb479665ade353efa40bd6e55dc36"
] | [
"quantumGAN/deprecated_files/discriminator_minimax.py"
] | [
"\"\"\"DISCRIMINATOR BCE\"\"\"\nimport json\nimport random\nfrom typing import Dict, List\n\nimport numpy as np\n\nfrom quantumGAN.functions import minimax_derivative_fake, minimax_derivative_real, sigmoid, \\\n\tsigmoid_prime\n\n\ndef load(filename):\n\tf = open(filename, \"r\")\n\tdata = json.load(f)\n\tf.close()... | [
[
"numpy.dot",
"numpy.array",
"numpy.random.randn",
"numpy.zeros"
]
] |
litosly/RankingOptimizationApprochtoLLC | [
"b6b79fb1364fcc481aa84093a8e8399966b19d02"
] | [
"models/llc_score.py"
] | [
"from prediction.predictor import predict_scores, predict_vector\nfrom sklearn.linear_model import LinearRegression\nfrom utils.critique import LP1SimplifiedOptimize\nfrom utils.keyphrase_selection import *\n\nimport numpy as np\nfrom tqdm import tqdm\n\n\nclass LP1Simplified(object):\n def __init__(self, keyphr... | [
[
"numpy.random.choice",
"numpy.in1d",
"numpy.setdiff1d",
"numpy.concatenate",
"numpy.intersect1d",
"numpy.argmax",
"sklearn.linear_model.LinearRegression",
"numpy.ravel",
"numpy.array",
"numpy.where"
]
] |
MiningMyBusiness/SketchyExperiments | [
"11f3baee63a984501b9707aa58420540b19db59f"
] | [
"Autoencoding/save32by32ForAll.py"
] | [
"## Name: Save 32 by 32 image vector\r\n## Description: Reads in the matrix representation of the images\r\n## for each class and resizes each image from 256 by 256\r\n## to 32 by 32 and then converts it to a vector with\r\n## 1024 elements (32*32). A stack of these vectors (m... | [
[
"numpy.min",
"numpy.reshape",
"numpy.save",
"numpy.max",
"numpy.load",
"numpy.zeros"
]
] |
mwanakijiji/rrlfe2 | [
"4a822bb499bd0af4543f8b34d9322e812a5a3d2c"
] | [
"tests/test_scrape_ew_and_errew.py"
] | [
"import matplotlib\nmatplotlib.use('Agg')\n\nimport sys, os\nfrom configparser import ConfigParser, ExtendedInterpolation\nimport pandas as pd\nimport astropy\n\ncurrent_dir = os.path.dirname(__file__)\ntarget_dir = os.path.abspath(os.path.join(current_dir, \"../\"))\nsys.path.insert(0, target_dir)\n\n# import more... | [
[
"numpy.all",
"matplotlib.use",
"numpy.std"
]
] |
CloudRenderVR/human-motion-prediction-pytorch-uncertainty | [
"cb96f3b2d8a2b54916b2f3f76c1c9b982af5b46b"
] | [
"src/translate.py"
] | [
"\n\"\"\"Simple code for training an RNN for motion prediction.\"\"\"\n\nfrom __future__ import absolute_import\nfrom __future__ import division\nfrom __future__ import print_function\n\nimport math\nimport os\nimport random\nimport sys\nimport time\nimport h5py\n\nimport numpy as np\nfrom six.moves import xrange #... | [
[
"torch.mean",
"numpy.log",
"numpy.sum",
"numpy.abs",
"numpy.sqrt",
"numpy.power",
"numpy.arange",
"torch.sum",
"torch.from_numpy",
"torch.numel",
"numpy.copy",
"numpy.std",
"numpy.mean",
"torch.pow",
"torch.autograd.Variable"
]
] |
gjdv/autoimpute | [
"d22cd86db6facd4a68746c8c0fcb3fae70071dac"
] | [
"autoimpute/analysis/metrics.py"
] | [
"\"\"\"This module devises metrics to compare estimates from analysis models.\"\"\"\n\nimport numpy as np\nimport pandas as pd\n\ndef raw_bias(Q_bar, Q):\n \"\"\"Calculate raw bias between coefficients Q and actual Q.\n\n Q_bar can be one estimate (scalar) or a vector of estimates. This equation\n subtract... | [
[
"numpy.array"
]
] |
hadleyhzy34/GANs-practice | [
"37d1dcf4e4b492e6d070b0ba72f320913af9b17a"
] | [
"gan/PyTorch-GAN-Mnist/test.py"
] | [
"import torch\nfrom torchvision import transforms\nimport numpy as np\nimport matplotlib.pyplot as plt\nimport matplotlib.gridspec as gridspec\n\n\n\nplt.rcParams['figure.figsize'] = (10.0, 8.0)\nplt.rcParams['image.interpolation'] = 'nearest'\nplt.rcParams['image.cmap'] = 'gray'\n\n\ndef show_images(images):\n ... | [
[
"numpy.sqrt",
"torch.load",
"matplotlib.pyplot.subplot",
"torch.rand",
"torch.cuda.is_available",
"matplotlib.pyplot.show"
]
] |
Diimu/circuitsimulator | [
"3a4aeaaa89b5e9bba1598736140e32b3ca1e0da4"
] | [
"circuit.py"
] | [
"# -*- coding: utf-8 -*-\n\"\"\"\nClass \"Circuit\" defines simple one port object/circuit having\nfrequency (single point or array), impedance, and possibly a list\nof components that constitute the circuit.\n\"\"\"\n\n\nimport numpy as np\nimport scipy\nimport matplotlib.pyplot as plt\nimport skrf\n\nclass Circui... | [
[
"numpy.abs",
"numpy.linspace",
"numpy.asarray",
"numpy.tan",
"numpy.seterr",
"numpy.size",
"numpy.log10",
"matplotlib.pyplot.ylabel",
"matplotlib.pyplot.grid",
"numpy.iscomplex",
"matplotlib.pyplot.xlabel",
"matplotlib.pyplot.ion",
"matplotlib.pyplot.figure"
]... |
deepmipt/kpi2017 | [
"0f6b13c6ea76e544804ce66ba372c66d5ef9ee30"
] | [
"deeppavlov/tasks/insults/build.py"
] | [
"# Copyright 2017 Neural Networks and Deep Learning lab, MIPT\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 requi... | [
[
"pandas.read_csv",
"numpy.nonzero",
"numpy.random.randint"
]
] |
kuldeep24680/RESTAPI-for-analyzing-data-to-excel-uploaded-file-and-downloading-resultant-csv-files-on-flask | [
"5e3f35de2599f71078974c4e5a46bb94da426200"
] | [
"routes.py"
] | [
"from app import app\r\nfrom flask import render_template, request,send_file\r\nimport pandas as pd\r\nimport csv\r\nimport xlrd\r\n\r\n\r\n\r\n# to route the user the upload the .xlsx file\r\n@app.route('/')\r\ndef upload_file():\r\n return render_template('upload.html')\r\n\r\n# function that converts the .xlsx... | [
[
"pandas.read_csv"
]
] |
phylatechnologies/ibd_classification_benchmark | [
"667e0b42e70bd56c6675062b10dae38407e785b0"
] | [
"run_results.py"
] | [
"import os\nimport pandas as pd\nimport numpy as np\nfrom metadata.getters import get_pwd\nfrom analysis.evaluation_methods import get_performance\nimport random\nnp.random.seed(26)\nrandom.seed(26)\ndef get_sample_info(dataset):\n '''\n :param exp_name: experiment string\n :return: unpickled data set\n ... | [
[
"pandas.concat",
"pandas.read_csv",
"numpy.random.seed",
"numpy.round",
"pandas.read_pickle"
]
] |
Iamal1/maskrcnn-benchmark | [
"d53c1986e72c6a647179f5bf0e060db1160a1a42"
] | [
"maskrcnn_benchmark/data/datasets/coco.py"
] | [
"# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved.\nimport torch\nimport torchvision\n\nfrom maskrcnn_benchmark.structures.bounding_box import BoxList\nfrom maskrcnn_benchmark.structures.segmentation_mask import SegmentationMask\nfrom maskrcnn_benchmark.structures.keypoint import PersonKeypoin... | [
[
"torch.as_tensor",
"torch.tensor"
]
] |
wenh06/yolov4_acne_torch | [
"8eda65ff6805ec313de39c74aea12a774657f3ff"
] | [
"train_acne.py"
] | [
"# -*- coding: utf-8 -*-\n'''\ntrain acne detector using the enhanced ACNE04 dataset\n\nMore reference:\n[1] https://pytorch.org/tutorials/intermediate/torchvision_tutorial.html\n'''\nimport time\nimport logging\nimport os, sys\nimport argparse\nfrom collections import deque\nimport datetime\n\nimport cv2\nfrom tqd... | [
[
"torch.optim.lr_scheduler.LambdaLR",
"torch.zeros",
"torch.utils.data.DataLoader",
"numpy.concatenate",
"numpy.max",
"torch.no_grad",
"torch.cuda.is_available",
"torch.device",
"torch.cuda.synchronize",
"torch.ones",
"torch.sqrt",
"torch.from_numpy",
"numpy.argm... |
ayushmaskey/log_analysis | [
"c777f48117ec8e14845aa8d2deccc7f974ca232a"
] | [
"app/analysis/validation_cluster.py"
] | [
"import pandas as pd\nimport matplotlib.pyplot as plt\nfrom matplotlib import style\nstyle.use(\"ggplot\")\n\nfrom csv_to_pandas import csv_into_dict_of_data\nfrom wavelet_transformation import csv_into_wavelet_transformed_dict_of_dataframe\n\nfrom training_cluster import reorganize_data\n\ndef get_validation_datas... | [
[
"matplotlib.style.use"
]
] |
maremun/mix-attend-break-sticks | [
"db8221447fb993194641ba781e85005180f55421"
] | [
"transformer.py"
] | [
"import torch\nimport torch.nn as nn\n\nfrom modules import Linear, PosEncoding\nfrom layers import DecoderLayer\n\nimport const\n\ndevice = torch.device(\"cuda\" if torch.cuda.is_available() else \"cpu\")\n\n\ndef proj_prob_simplex(inputs):\n # project updated weights onto a probability simplex\n # see https... | [
[
"torch.nn.Dropout",
"torch.ones",
"torch.nn.Embedding",
"torch.cuda.is_available",
"torch.clamp",
"torch.gt"
]
] |
christostsekouronas/academyposttestanalysis | [
"913a0c13ad0482927a323b2fb3a97a8e2ca26517"
] | [
"loadCSVdata.py"
] | [
"import pandas as pd\n\n\n\ndef loadTest(filepath):\n df = pd.read_csv(filepath)\n return df"
] | [
[
"pandas.read_csv"
]
] |
juliandwain/deepmind-research | [
"eca5fe66ad770027f4dd758d3a659cd8261bace5"
] | [
"meshgraphnets/cloth_model.py"
] | [
"# Lint as: python3\n# pylint: disable=g-bad-file-header\n# Copyright 2020 DeepMind Technologies Limited. 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# ... | [
[
"tensorflow.compat.v1.concat",
"tensorflow.compat.v1.equal",
"tensorflow.compat.v1.reduce_mean",
"tensorflow.compat.v1.reduce_sum",
"tensorflow.compat.v1.one_hot",
"tensorflow.compat.v1.gather",
"tensorflow.compat.v1.norm"
]
] |
TimK1998/SemanticSynthesisForScoreBasedModels | [
"b575ab646dd5a599d173b44a3585429082d0620d"
] | [
"configs/cityscapes256.py"
] | [
"import ml_collections\nimport torch\n\n\ndef get_default_configs():\n config = ml_collections.ConfigDict()\n\n # training\n config.training = training = ml_collections.ConfigDict()\n config.training.batch_size = 8\n training.epochs = 2000\n # Time in epochs\n training.checkpoint_save_freq = ... | [
[
"torch.device",
"torch.cuda.is_available"
]
] |
DanLuoNEU/CLASP2 | [
"262fb1f151c14bfe3b1c452cdf65187d8caa10bd"
] | [
"Visualizaion/hands_association.py"
] | [
"# Build up association between hands and persons ID, \n# depending on IOU between skeleton and person bounding boxes\n# Intersection part reference: https://github.com/amdegroot/ssd.pytorch/blob/master/layers/box_utils.py#L48\n# Points to improve: \n# 1. same hands for two persons using IOU, they should be uniqu... | [
[
"numpy.expand_dims",
"numpy.maximum",
"numpy.minimum",
"numpy.clip",
"numpy.asarray",
"numpy.argmax"
]
] |
Bpowers4/turicreate | [
"73dad213cc1c4f74337b905baea2b3a1e5a0266c"
] | [
"src/python/turicreate/toolkits/drawing_classifier/_tf_drawing_classifier.py"
] | [
"# -*- coding: utf-8 -*-\n# Copyright © 2019 Apple Inc. All rights reserved.\n#\n# Use of this source code is governed by a BSD-3-clause license that can\n# be found in the LICENSE.txt file or at https://opensource.org/licenses/BSD-3-Clause\nfrom __future__ import print_function as _\nfrom __future__ import divisio... | [
[
"tensorflow.compat.v1.nn.max_pool2d",
"tensorflow.compat.v1.train.AdamOptimizer",
"numpy.reshape",
"tensorflow.compat.v1.reshape",
"tensorflow.compat.v1.trainable_variables",
"tensorflow.compat.v1.one_hot",
"tensorflow.compat.v1.nn.softmax",
"tensorflow.compat.v1.nn.conv2d",
"t... |
dgbirm/elo_sailor | [
"0978eac23e9334eee8cab3225840f82fbc153194"
] | [
"ISAFlaserResults/code/csvClean.py"
] | [
"#Scrap code for cleaning the CSV files so that we can read them easier\n\nimport csv\nimport sys\nimport pandas as pd\nimport numpy as np\nimport os\nimport re\n\nfrom selenium import webdriver\nfrom time import sleep\nfrom text_unidecode import unidecode\nfrom tabulate import tabulate\n\nsys.path.append('/home/da... | [
[
"pandas.read_csv"
]
] |
jz5jx/Test_Repo | [
"8796f45021943984ed02232fd34ff02e17123d71"
] | [
"src/clustar_project/graph.py"
] | [
"import numpy as np\nimport matplotlib.pyplot as plt\nfrom matplotlib.patches import Rectangle\n\n\ndef identify_peaks(image, smoothing=5, clip=0.75):\n n_rows = image.shape[0]\n n_cols = image.shape[1]\n mid = n_rows // 2\n\n y = np.array([image[mid, c] for c in range(n_cols)])\n x = np.arange(0, le... | [
[
"numpy.array",
"numpy.diff",
"numpy.mean",
"numpy.nonzero"
]
] |
sjanzou/pvlib-python | [
"17751ca69f271891ee83082772b3261138e34dd0"
] | [
"pvlib/test/test_surfrad.py"
] | [
"import inspect\nimport os\n\nfrom pandas import Timestamp, DatetimeIndex\nfrom pandas.util.testing import network\n\nfrom pvlib.iotools import surfrad\n\ntest_dir = os.path.dirname(\n os.path.abspath(inspect.getfile(inspect.currentframe())))\ntestfile = os.path.join(test_dir, '../data/surfrad-slv16001.dat')\nne... | [
[
"pandas.Timestamp",
"pandas.DatetimeIndex"
]
] |
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