repo_name stringlengths 6 130 | hexsha list | file_path list | code list | apis list |
|---|---|---|---|---|
VISTAS-IVES/pyvistas | [
"2de1541c0fb40ccbac4014af758ff329ba0677b1"
] | [
"plugins/barchart/main.py"
] | [
"import random\nfrom io import BytesIO\n\nimport numpy\nimport wx\nfrom PIL import Image\nfrom matplotlib import pyplot\n\nfrom vistas.core.color import RGBColor\nfrom vistas.core.plugins.data import DataPlugin\nfrom vistas.core.plugins.option import Option, OptionGroup\nfrom vistas.core.plugins.visualization impor... | [
[
"matplotlib.pyplot.close",
"numpy.unique",
"matplotlib.pyplot.figure"
]
] |
dPys/niworkflows | [
"071e3e27b6c0168a94fdb3996e63f225ab6de3bb"
] | [
"niworkflows/utils/images.py"
] | [
"\"\"\"Utilities to manipulate images.\"\"\"\nimport nibabel as nb\nimport numpy as np\n\n\ndef unsafe_write_nifti_header_and_data(fname, header, data):\n \"\"\"Write header and data without any consistency checks or data munging\n\n This is almost always a bad idea, and you should not use this function\n ... | [
[
"numpy.allclose"
]
] |
VibhuJawa/mimic3-benchmarks | [
"4897d597d5ecc71d2dd2ce1ced76cae48dd50fb5"
] | [
"mimic3benchmark/util.py"
] | [
"import pandas as pd\n\ndef dataframe_from_csv(path, header=0, index_col=0):\n return pd.read_csv(path, header=header, index_col=index_col)\n"
] | [
[
"pandas.read_csv"
]
] |
Jayant1234/Marsh_Ann | [
"34503f9b41df8c34cd41535207d7308f2916d4a6"
] | [
"marsh_plant_nn_predict.py"
] | [
"import numpy as np\nimport cv2\n\nimport torch\nimport torch.nn as nn\nfrom marsh_plant_dataset import MarshPlant_Dataset\n\nN_CLASSES = 7\nTHRESHOLD_SIG = 0.5\nbatch_size = 32\nbShuffle = False\nnum_workers = 8\n\n\nmodel_path = './modeling/saved_models/ResNet101_marsh_plants_20190415.torch'\n\nmodel = torch.load... | [
[
"torch.device",
"numpy.empty",
"numpy.savetxt",
"torch.nn.Sigmoid",
"torch.no_grad",
"torch.utils.data.DataLoader",
"torch.load"
]
] |
LJJ12/Deep-Learning-for-SVD-and-Hybrid-Beamforming | [
"996e46a6b9f6a229f722708e0581a5c1e4f53146"
] | [
"my/myfun/python/learning_rate.py"
] | [
"# 初始的学习速率是0.1，总的迭代次数是1000次，如果staircase=True，那就表明每decay_steps次计算学习速率变化，更新原始学习速率，\n# 如果是False，那就是每一步都更新学习速率。红色表示False，蓝色表示True。\nimport tensorflow as tf\nimport numpy as np\nimport matplotlib.pyplot as plt\n\nlearning_rate = 0.1 # 初始学习速率时0.1\ndecay_rate = 0.96 # 衰减率\nglobal_steps = 1000 # 总的迭代次数\ndecay_steps = 10... | [
[
"tensorflow.Session",
"matplotlib.pyplot.figure",
"tensorflow.constant",
"matplotlib.pyplot.show",
"tensorflow.train.exponential_decay"
]
] |
sjm4976/KSTAR_NN_simulator | [
"1dd4d7a687d32574e6d1ddf6f3f6559492d5df4d"
] | [
"common/model_structure.py"
] | [
"import json, zipfile\nimport numpy as np\nfrom tensorflow.keras import models, layers\n\nclass k2rz():\n def __init__(self, model_path, n_models=1, ntheta=64, closed_surface=True, xpt_correction=True):\n self.nmodels, self.ntheta = n_models, ntheta\n self.closed_surface, self.xpt_correction = clos... | [
[
"numpy.array",
"numpy.zeros_like",
"numpy.matmul",
"numpy.zeros",
"numpy.argmin",
"numpy.exp",
"numpy.mean",
"tensorflow.keras.layers.Dense",
"numpy.shape",
"tensorflow.keras.models.load_model",
"numpy.tanh",
"numpy.subtract",
"numpy.argmax",
"tensorflow.ker... |
arturbeg/tensor2tensor | [
"43b70752311d3b8dc5f11f63d0dea3efdf8ee25b"
] | [
"tensor2tensor/utils/dgmm.py"
] | [
"import tensorflow as tf\nimport numpy as np\nfrom tensor2tensor.utils.dgmm_estimator import Estimator\nimport math\n\n\ndef dgmm(z, is_training, mixtures=3, lambda_1=0.1, lambda_2=0.005):\n \"\"\"\n :param is_training: a tensorflow placeholder to indicate whether it is in the training phase or not\n :par... | [
[
"tensorflow.exp",
"tensorflow.constant_initializer",
"tensorflow.diag",
"tensorflow.ones_initializer",
"tensorflow.matmul",
"numpy.tile",
"tensorflow.identity",
"tensorflow.random_normal",
"tensorflow.cast",
"tensorflow.shape",
"tensorflow.matrix_diag_part",
"tensor... |
AaltoML/Newt-test | [
"e3a725124eb63e9994653ed756be7ae8632f52b2"
] | [
"experiments/binary/binary.py"
] | [
"import sys\nimport bayesnewton\nimport objax\nimport numpy as np\nimport time\nimport pickle\n\nprint('generating some data ...')\nnp.random.seed(99)\nN = 10000 # number of points\nx = np.sort(70 * np.random.rand(N))\nsn = 0.01\nf = lambda x_: 12. * np.sin(4 * np.pi * x_) / (0.25 * np.pi * x_ + 1)\ny_ = f(x) + np... | [
[
"numpy.sin",
"numpy.random.rand",
"numpy.random.seed",
"numpy.random.permutation",
"numpy.math.sqrt",
"numpy.random.randn",
"numpy.split",
"numpy.sign",
"numpy.arange",
"numpy.linspace"
]
] |
TUIlmenauAMS/rl_singing_voice | [
"60204c698d48f27b44588c9d6c8dd2c66a13fcd5"
] | [
"nn_modules/cls_basic_conv1ds.py"
] | [
"# -*- coding: utf-8 -*-\n__author__ = 'S.I. Mimilakis'\n__copyright__ = 'MacSeNet'\n\n# imports\nimport numpy as np\nimport torch\nimport torch.nn as nn\n\n\nclass ConvEncoder(nn.Module):\n \"\"\"\n Class for building the analysis part\n of the Front-End ('Fe'), with randomly\n initialized ... | [
[
"numpy.ceil",
"numpy.int",
"torch.nn.init.kaiming_uniform_",
"torch.nn.ConvTranspose1d",
"numpy.zeros",
"torch.nn.Conv1d",
"torch.nn.Tanh",
"torch.nn.ReLU"
]
] |
NathanDai5287/AMC-10-Answer-Checker | [
"8b4226f1bc8e84be07a84da1087d293aa648c406"
] | [
"answer.py"
] | [
"from typing import Tuple\nfrom selectorlib import Extractor\nfrom pprint import pformat\nimport json\nimport requests\nimport pandas as pd\n\ndef summarize(score: int, cutoff: int, correct: dict, incorrect: dict, skipped: dict) -> str:\n\t\"\"\"formats information\n\n\tArgs:\n\t\tscore (int): score on test\n\t\tcu... | [
[
"pandas.read_html"
]
] |
jzhanson/alfred | [
"d5b540e7c9b53d3f70cc2907503935fecff00018"
] | [
"models/nn/resnet.py"
] | [
"import torch\nimport torch.nn as nn\nfrom torchvision import models, transforms\n\n\nclass Resnet18(object):\n '''\n pretrained Resnet18 from torchvision\n '''\n\n def __init__(self, args, eval=True, share_memory=False, use_conv_feat=True):\n self.model = models.resnet18(pretrained=True)\n\n ... | [
[
"torch.device",
"torch.cat",
"torch.set_grad_enabled"
]
] |
KColdrick/pvtrace | [
"b4b99905fae0f8b16358ca4e229379b6566f6020",
"b4b99905fae0f8b16358ca4e229379b6566f6020"
] | [
"pvtrace/scene/renderer.py",
"pvtrace/geometry/utils.py"
] | [
"import numpy as np\nimport os\nimport time\nimport io\nfrom typing import Tuple\nfrom contextlib import contextmanager\nfrom collections import deque\nfrom anytree import LevelOrderIter, PostOrderIter\nfrom pvtrace.geometry.sphere import Sphere\nfrom pvtrace.geometry.cylinder import Cylinder\nfrom pvtrace.geometry... | [
[
"numpy.array",
"numpy.column_stack",
"numpy.copy"
],
[
"numpy.logical_or",
"numpy.array",
"numpy.arccos",
"numpy.dot",
"numpy.linalg.norm",
"numpy.errstate",
"numpy.sin",
"numpy.absolute",
"numpy.roots",
"numpy.allclose",
"numpy.finfo",
"numpy.any",
... |
aoranwu/grace | [
"1e28915f6f6e8189ef33c0c7d8d3ce314e0a493e"
] | [
"grace_dl/dist/compressor/qsgd.py"
] | [
"import torch\nfrom grace_dl.dist import Compressor\n\n\nclass QSGDCompressor(Compressor):\n\n def __init__(self, quantum_num, bucket_size=128):\n super().__init__()\n self.quantum_num = quantum_num\n self.bucket_size = bucket_size\n\n def compress(self, tensor, name):\n shape = te... | [
[
"torch.zeros",
"torch.sqrt",
"torch.ones",
"torch.sum",
"torch.empty_like"
]
] |
xinzheshen/WaveRNN | [
"f6cb1a3d6d6b58dbbba5301a88d05c1beb9230af"
] | [
"train_wavernn.py"
] | [
"import os, time\nimport numpy as np\nfrom torch import optim\nimport torch.nn.functional as F\nfrom utils.display import stream, simple_table\nfrom utils.dataset import get_vocoder_datasets\nfrom utils.distribution import discretized_mix_logistic_loss\nimport hparams as hp\nfrom models.fatchord_version import Wave... | [
[
"numpy.cumprod"
]
] |
grzegorznowak/tensorflow-rrn-server | [
"1011ea465c298263fa177ba34ba0db0897985d8f"
] | [
"src/rnn_time_series_server_tests.py"
] | [
"import unittest\r\nimport requests\r\nimport rnn_time_series_server as rnn\r\nimport os\r\nimport numpy as np\r\nfrom numpy.testing import assert_array_equal\r\n\r\nclass RNNTimeSeriesServerTestRequests(unittest.TestCase):\r\n\r\n\r\n def test_predict(self):\r\n response = requests.get('http://localhost:... | [
[
"numpy.array"
]
] |
BeeGass/Agents | [
"7785b010625e3a9409849a293badd00500647807"
] | [
"agents/MC/mc.py"
] | [
"#!/usr/bin/env python3\n# -*- coding: utf-8 -*-\nimport numpy as np\nimport random\nfrom collections import defaultdict\n#-------------------------------------------------------------------------\n'''\n Monte-Carlo\n In this problem, you will implememnt an AI player for Blackjack.\n The main goal of this ... | [
[
"numpy.argmax",
"numpy.zeros"
]
] |
ioshchepkov/gmeterpy | [
"594cf7c15193ae86b98c9474259843eeadc04f5b"
] | [
"gmeterpy/meters/tsoft.py"
] | [
"# -*- coding: utf-8 -*-\n\"\"\"TSoft format reader.\n\n\"\"\"\n\nimport re\nimport numpy as np\nimport pandas as pd\n\n# possible tags in TSoft format\n_TAGS = ['TSF-file', 'TIMEFORMAT', 'COUNTINFO', 'INCREMENT', 'CHANNELS',\n 'UNITS', 'UNDETVAL', 'COMMENT', 'DATA', 'LABEL',\n 'LININTERPOL', 'CUBIN... | [
[
"pandas.to_datetime",
"pandas.DataFrame",
"numpy.asarray"
]
] |
tphanson/tf-agent-labs | [
"c6cb79be5f0f06d9669a32439b56b4d287faeb69"
] | [
"run.py"
] | [
"import os\nimport numpy as np\nimport tensorflow as tf\n\nfrom env import CartPole\nfrom agent.dqn import DQN\n\n# Compulsory config for tf_agents\ntf.compat.v1.enable_v2_behavior()\n\n# Saving dir\nPOLICY_DIR = os.path.join(os.path.dirname(os.path.abspath(__file__)),\n './models/policy')\... | [
[
"tensorflow.compat.v1.enable_v2_behavior"
]
] |
TL-Rubick/tensorflow | [
"6cf1ccf6060a95aad3ccc84544d0aa166990ec72",
"be084bd7a4dd241eb781fc704f57bcacc5c9b6dd",
"6cf1ccf6060a95aad3ccc84544d0aa166990ec72",
"6cf1ccf6060a95aad3ccc84544d0aa166990ec72"
] | [
"tensorflow/python/keras/optimizer_v2/adadelta.py",
"tensorflow/python/saved_model/load_v1_in_v2.py",
"tensorflow/python/data/experimental/kernel_tests/optimize_dataset_test.py",
"tensorflow/python/distribute/parameter_server_strategy_v2_test.py"
] | [
"# Copyright 2018 The TensorFlow Authors. All Rights Reserved.\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n# http://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless requ... | [
[
"numpy.array",
"tensorflow.python.util.tf_export.keras_export",
"tensorflow.python.keras.backend_config.epsilon",
"tensorflow.python.training.gen_training_ops.ResourceSparseApplyAdadelta",
"tensorflow.python.framework.ops.convert_to_tensor_v2_with_dispatch",
"tensorflow.python.training.gen... |
ruaruaruabick/waveglow | [
"636d2ba2bda4f4efd5f13f8e46aef23d8b7881bd"
] | [
"train.py"
] | [
"# -*- coding: utf-8 -*\n# *****************************************************************************\n# Copyright (c) 2018, NVIDIA CORPORATION. All rights reserved.\n#\n# Redistribution and use in source and binary forms, with or without\n# modification, are permitted provided that the following conditions ... | [
[
"torch.cuda.manual_seed",
"torch.optim.lr_scheduler.StepLR",
"torch.no_grad",
"numpy.mean",
"torch.cuda.device_count",
"torch.manual_seed",
"torch.utils.data.DataLoader",
"torch.load",
"torch.utils.data.distributed.DistributedSampler"
]
] |
HanxunH/MDAttack | [
"fd4107c857f11385685b6daf0de7a455749528d5"
] | [
"defense/Overfitting.py"
] | [
"'''\nBased on code from https://github.com/locuslab/robust_overfitting\n'''\nimport math\nimport torch\nimport torch.nn as nn\nimport torch.nn.functional as F\nimport os\nimport torchvision.transforms as tf\nfrom models.wideresnet import WideResNet\nfrom . import utils\n\nif torch.cuda.is_available():\n device ... | [
[
"torch.device",
"torch.cuda.is_available",
"torch.load"
]
] |
vishalbelsare/zvt | [
"d55051147274c0a4157f08ec60908c781a323c8f",
"d55051147274c0a4157f08ec60908c781a323c8f"
] | [
"src/zvt/recorders/joinquant/misc/jq_hk_holder_recorder.py",
"src/zvt/contract/api.py"
] | [
"import pandas as pd\nfrom jqdatapy.api import run_query\n\nfrom zvt.contract.api import df_to_db, get_data\nfrom zvt.contract.recorder import TimestampsDataRecorder\nfrom zvt.domain import Index\nfrom zvt.domain.misc.holder import HkHolder\nfrom zvt.recorders.joinquant.common import to_entity_id\nfrom zvt.utils.pd... | [
[
"pandas.to_datetime",
"pandas.Timestamp.now"
],
[
"pandas.read_sql"
]
] |
robbierobinette/rcv-tensorflow | [
"984852902f465bb6f61ba863e4b76092249911d0"
] | [
"BallotTest.py"
] | [
"import matplotlib.pyplot as plt\n\nfrom Ballot import Ballot\nfrom DefaultConfigOptions import *\nfrom PartyPrimaryElection import PartyPrimaryElection\n\n\ndef main():\n ideology = []\n for i in range(1000):\n print(\".\")\n if (i + 1) % 100 == 0:\n print(\"\")\n\n ideology.a... | [
[
"matplotlib.pyplot.xlabel",
"matplotlib.pyplot.hist",
"matplotlib.pyplot.show",
"matplotlib.pyplot.ylabel"
]
] |
mretegan/silx | [
"2c8b05ff1c8c1fc00e3d4a08331c76ff5b44996b"
] | [
"silx/gui/plot/items/curve.py"
] | [
"# coding: utf-8\n# /*##########################################################################\n#\n# Copyright (c) 2017-2020 European Synchrotron Radiation Facility\n#\n# Permission is hereby granted, free of charge, to any person obtaining a copy\n# of this software and associated documentation files (the \"Soft... | [
[
"numpy.array",
"numpy.isfinite"
]
] |
nayyarv/bayesnets | [
"090abd1a0a91c2b9d6d57a182ee5be1f65a22e11"
] | [
"tests/test_metrics.py"
] | [
"import numpy as np\nfrom swarm import metrics\nimport pytest\n\n# Example y with 11 points from -1.5 to 1.5.\ny = np.array(\n [\n -0.997495,\n -0.9320391,\n -0.78332686,\n -0.5646425,\n -0.29552022,\n 0.0,\n 0.29552022,\n 0.5646425,\n 0.78332686,\n ... | [
[
"numpy.max",
"numpy.array",
"numpy.min",
"numpy.mean",
"numpy.abs",
"numpy.all"
]
] |
robbisg/mvpa_itab_wu | [
"e3cdb198a21349672f601cd34381e0895fa6484c",
"e3cdb198a21349672f601cd34381e0895fa6484c"
] | [
"mvpa_itab/script/misc/colors.py",
"mvpa_itab/script/mambo/c2b/simulations/results-20200907.py"
] | [
"from __future__ import (absolute_import, division, print_function,\n unicode_literals)\n\nimport six\n\nimport numpy as np\nimport matplotlib.pyplot as plt\nfrom matplotlib import colors\n\n\ncolors_ = list(six.iteritems(colors.cnames))\n\n# Add the single letter colors.\nfor name, rgb in si... | [
[
"numpy.lexsort",
"matplotlib.colors.hex2color",
"matplotlib.pyplot.subplots",
"matplotlib.pyplot.show",
"matplotlib.colors.rgb2hex",
"matplotlib.colors.rgb_to_hsv"
],
[
"numpy.logical_not",
"numpy.logical_or",
"matplotlib.animation.FuncAnimation",
"pandas.concat",
"... |
gregunz/ml2017 | [
"6235003ef849a13b1da95e4842b9cabd30b70fd3"
] | [
"project01/src/helpers.py"
] | [
"# -*- coding: utf-8 -*-\r\n\"\"\"some helper functions for project 1.\"\"\"\r\nimport csv\r\nimport numpy as np\r\n\r\ndef load_csv_data(data_path, sub_sample=False):\r\n \"\"\"Loads data and returns y (class labels), tX (features) and ids (event ids)\"\"\"\r\n y = np.genfromtxt(data_path, delimiter=\",\", s... | [
[
"numpy.concatenate",
"numpy.array",
"numpy.genfromtxt",
"numpy.where",
"numpy.arange"
]
] |
nonconvexopt/jax | [
"8b489134c818364577f630ada6aa63beefd7376a"
] | [
"tests/lax_numpy_test.py"
] | [
"# Copyright 2018 Google LLC\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n# https://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless required by applicable law or agreed ... | [
[
"numpy.diag_indices",
"numpy.triu_indices_from",
"numpy.tile",
"numpy.trim_zeros",
"numpy.resize",
"numpy.tensordot",
"numpy.tril_indices",
"numpy.unique",
"numpy.random.random",
"numpy.logspace",
"numpy.full_like",
"numpy.bincount",
"numpy.count_nonzero",
"... |
jlenain/ctapipe | [
"65a6950dded44f81d5c218f4e117e1e38fce8fd4"
] | [
"ctapipe/io/tests/test_astropy_helpers.py"
] | [
"#!/usr/bin/env python3\nimport warnings\nimport numpy as np\nfrom astropy import units as u\nimport tables\nimport pytest\nfrom astropy.time import Time\n\nfrom astropy.io.fits.verify import VerifyWarning\n\nfrom ctapipe.core import Container, Field\nfrom ctapipe.containers import ReconstructedEnergyContainer, Tel... | [
[
"numpy.array",
"numpy.random.default_rng",
"numpy.allclose",
"numpy.arange",
"numpy.all",
"numpy.logspace"
]
] |
mysteryshen/AICIG | [
"95bd3c711bc70661bf16c88635bd2bf660b61ff5"
] | [
"batch_generator.py"
] | [
"import numpy as np\nfrom dataset import load_data\n\nclass BatchGenerator:\n TRAIN = 1\n TEST = 0\n\n def __init__(self, data_src, seed, batch_size=32, dataset='MNIST'):\n self.batch_size = batch_size\n self.data_src = data_src\n\n # Load data\n ((x, y), (x_test, y_test)) = loa... | [
[
"numpy.array",
"numpy.random.shuffle",
"numpy.arange",
"numpy.transpose",
"numpy.unique"
]
] |
YuHuang42/cogdl | [
"36eafd4a2ced8a513643b99a3e63e9919c38717c",
"36eafd4a2ced8a513643b99a3e63e9919c38717c"
] | [
"examples/gnn_models/grand.py",
"examples/gnn_models/sgc.py"
] | [
"import torch\n\nfrom utils import print_result, set_random_seed, get_dataset\nfrom cogdl.tasks import build_task\nfrom cogdl.utils import build_args_from_dict\n\nDATASET_REGISTRY = {}\n\n\ndef build_default_args_for_node_classification(dataset):\n cpu = not torch.cuda.is_available()\n args = {\n \"lr\... | [
[
"torch.cuda.is_available"
],
[
"torch.cuda.is_available"
]
] |
y0ast/flax | [
"01afb539c4b91ff9e6c83ad9b5f6b36b3babffa8"
] | [
"tests/core/scope_test.py"
] | [
"# Copyright 2021 The Flax Authors.\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n# http://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless required by applicable law or a... | [
[
"numpy.array",
"numpy.ones"
]
] |
TonySoloProjects/lake_analyses | [
"08a07306b4da3b85e3445732999cb0742ca03e87"
] | [
"old/numpy-examples.py"
] | [
"# fun with numpy\nimport numpy as np\n\ndef f(x,y):\n print(f'x=\\n{x}')\n print(f'y=\\n{y}')\n return x+y\n\nz = np.fromfunction(f,(4,3))\n\nprint(f'z=\\n{z}')\n"
] | [
[
"numpy.fromfunction"
]
] |
sharanjeetsinghmago/online_reward_shaping | [
"55ac60f59ea6cc48fc8a788625aa50ff08453c1d"
] | [
"src/terrain.py"
] | [
"from OpenGL.GL import *\nfrom OpenGL.arrays import vbo\nfrom OpenGL.GLU import *\n\nfrom PyQt5.QtGui import QColor, QVector3D, QMatrix4x4\nfrom PyQt5.QtCore import QRect\n\nfrom shader import Shader\nfrom textures import bindHeightMap, ReadTexture, bindRewardMap, createEmptyTexture\n\nimport cv2 as cv\n\nimport nu... | [
[
"numpy.array",
"numpy.zeros"
]
] |
jinyeom/general-bipedal-walker | [
"fd76be55d0b29b55008846d6dfbee572a6ce8ef3"
] | [
"general_bipedal_walker/robot.py"
] | [
"import math\nimport numpy as np\nfrom Box2D.b2 import (\n edgeShape, \n circleShape, \n fixtureDef, \n polygonShape, \n revoluteJointDef, \n contactListener,\n rayCastCallback\n)\nfrom .color import Color\n\nclass Hull:\n VERTICES = [(-30, 9), (6, 9), (34, 1), (34, -8), (-30, -8)]\n\n def __init__(self, ... | [
[
"numpy.concatenate",
"numpy.sign",
"numpy.ones",
"numpy.abs"
]
] |
kinow/bcdp | [
"f4366a307672d84ed7992f3bb68a04303a107c56"
] | [
"examples/scripts/bcdp_ocw_benchmark.py"
] | [
"from contextlib import contextmanager\nfrom datetime import datetime\nimport time\nimport os\nimport glob\nimport numpy as np\nimport matplotlib\nimport pandas as pd\nmatplotlib.use('Agg')\nimport matplotlib.pyplot as plt\nimport bcdp\nimport ocw.data_source.local as local\nimport ocw.dataset_processor as dsp\nfro... | [
[
"matplotlib.use",
"matplotlib.style.use",
"pandas.DataFrame",
"matplotlib.pyplot.savefig",
"matplotlib.pyplot.ylabel"
]
] |
Complicateddd/Fairmot_Adpoted | [
"576f252496f48c95be882db6dcb001882596eeac"
] | [
"src/lib/models/networks/pose_dla_dcn.py"
] | [
"from __future__ import absolute_import\nfrom __future__ import division\nfrom __future__ import print_function\n\nimport logging\nimport math\nfrom os.path import join\n\nimport numpy as np\nimport torch\nimport torch.nn.functional as F\nimport torch.utils.model_zoo as model_zoo\nfrom torch import nn\n\nfrom .DCNv... | [
[
"numpy.array",
"torch.cat",
"torch.nn.MaxPool2d",
"torch.nn.Sequential",
"torch.nn.init.constant_",
"torch.nn.BatchNorm2d",
"torch.nn.functional.interpolate",
"torch.utils.model_zoo.load_url",
"torch.nn.ConvTranspose2d",
"torch.nn.ReLU",
"torch.nn.Conv2d",
"torch.lo... |
IshchenkoRoman/pommerman | [
"117824dca6974822d90e8fc3345da32eeb43cb43"
] | [
"cli/run_battle.py"
] | [
"\"\"\"Run a battle among agents.\n\nCall this with a config, a game, and a list of agents. The script will start separate threads to operate the agents\nand then report back the result.\n\nAn example with all four test agents running ffa:\npython run_battle.py --agents=test::agents.SimpleAgent,test::agents.SimpleA... | [
[
"numpy.random.seed",
"numpy.iinfo"
]
] |
q2675315436/underwater_sub | [
"334e945f04d6c309285ffdde19384344b8180720"
] | [
"mmdet/core/post_processing/bbox_nms.py"
] | [
"import torch\nfrom mmcv.ops.nms import batched_nms\n\n\ndef multiclass_nms(multi_bboxes,\n multi_scores,\n score_thr,\n nms_cfg,\n max_num=-1,\n score_factors=None):\n \"\"\"NMS for multi-class bboxes.\n\n Args:\n ... | [
[
"torch.onnx.is_in_onnx_export",
"torch.stack",
"torch.masked_select"
]
] |
finalelement/MONAI | [
"8e8e1b391fa649d1227087164dba208008d00bc4"
] | [
"monai/apps/mmars/mmars.py"
] | [
"# Copyright 2020 - 2021 MONAI Consortium\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# http://www.apache.org/licenses/LICENSE-2.0\n# Unless required by applicable law or agre... | [
[
"torch.jit.load",
"torch.load"
]
] |
zhangdongkun98/rl-lib | [
"50e36c18b130cff40abc6621923becd6cdc48e2b"
] | [
"rllib/utils/tools.py"
] | [
"\nimport torch\nimport torch.nn as nn\n\n\ndef soft_update(target, source, t):\n for target_param, source_param in zip(target.parameters(), source.parameters()):\n target_param.data.copy_( (1 - t) * target_param.data + t * source_param.data )\n\ndef hard_update(target, source):\n for target_param, sou... | [
[
"torch.nn.init.orthogonal_",
"torch.no_grad",
"torch.nn.init.constant_",
"torch.svd"
]
] |
flycoderRuan/rzq_retinanet | [
"a449398745cea8b5e53c0caecdb8039a89e77379"
] | [
"retinanet/losses.py"
] | [
"import numpy as np\nimport torch\nimport torch.nn as nn\n\ndef calc_iou(a, b):\n area = (b[:, 2] - b[:, 0]) * (b[:, 3] - b[:, 1])\n\n iw = torch.min(torch.unsqueeze(a[:, 2], dim=1), b[:, 2]) - torch.max(torch.unsqueeze(a[:, 0], 1), b[:, 0])\n ih = torch.min(torch.unsqueeze(a[:, 3], dim=1), b[:, 3]) - torc... | [
[
"torch.zeros",
"torch.stack",
"torch.eq",
"torch.max",
"torch.ne",
"torch.le",
"torch.clamp",
"torch.ones",
"torch.unsqueeze",
"torch.abs",
"torch.tensor",
"torch.lt",
"torch.log",
"torch.ge",
"torch.Tensor",
"torch.pow"
]
] |
atb00ker/scripts-lab | [
"71a5cc9c7f301c274798686db4a227e84b65926a"
] | [
"scripts/spam-filter/LogisticRegressionModel.py"
] | [
"import pandas as pd\nimport numpy as np\n# scikit-learn\nfrom sklearn.metrics import accuracy_score, precision_score, recall_score, f1_score\nfrom sklearn.linear_model.logistic import LogisticRegression\nfrom sklearn.feature_extraction.text import (\n CountVectorizer,\n TfidfVectorizer,\n HashingVectorize... | [
[
"sklearn.metrics.accuracy_score",
"sklearn.linear_model.logistic.LogisticRegression",
"sklearn.feature_extraction.text.CountVectorizer",
"sklearn.model_selection.train_test_split",
"pandas.read_csv"
]
] |
mlund/scipp | [
"26648fdcda49b21a7aacdafd58625fab7ee3403b"
] | [
"tests/plotting/plot_methods_test.py"
] | [
"# SPDX-License-Identifier: BSD-3-Clause\n# Copyright (c) 2022 Scipp contributors (https://github.com/scipp)\n# @file\n# @author Neil Vaytet\n\nimport numpy as np\nimport scipp as sc\nimport matplotlib\n\nmatplotlib.use('Agg')\n\n\ndef test_plot_variable():\n v = sc.arange('x', 10.0, unit='m')\n v.plot().clos... | [
[
"matplotlib.use",
"numpy.random.random"
]
] |
FCeoni/astropop-1 | [
"cc7fa7f5e20a7335bf30ee70f18a178222f80cd7"
] | [
"astropop/tests/test_pyutils.py"
] | [
"# Licensed under a 3-clause BSD style license - see LICENSE.rst\n\nimport sys\nimport os\nimport pytest\nfrom astropop.py_utils import mkdir_p, string_fix, process_list, \\\n check_iterable, batch_key_replace, \\\n run_command, IndexedDict\nimport numpy as ... | [
[
"numpy.arange",
"numpy.ones",
"numpy.array_equal",
"numpy.zeros"
]
] |
fmi-basel/gzenke-nonlinear-transient-amplification | [
"f3b0c8c89b42c34f1aad740c7026865cf3164f1d"
] | [
"src/Fig_6_supplement_1_Plotting.py"
] | [
"import numpy as np\nimport seaborn as sns\nimport matplotlib.pyplot as plt\nfrom matplotlib import patches\nimport matplotlib.patches as mpatches\nimport scipy.io as sio\n\n# plotting configuration\nratio = 1.5\nfigure_len, figure_width = 15*ratio, 12*ratio\nfont_size_1, font_size_2 = 36*ratio, 36*ratio\nlegend_si... | [
[
"matplotlib.pyplot.xlim",
"matplotlib.pyplot.xlabel",
"matplotlib.pyplot.ylim",
"matplotlib.pyplot.savefig",
"matplotlib.pyplot.plot",
"matplotlib.pyplot.yticks",
"matplotlib.pyplot.figure",
"matplotlib.pyplot.tick_params",
"matplotlib.pyplot.hlines",
"matplotlib.pyplot.yla... |
StrangeGirlMurph/CodingProjects | [
"8400a610c0a54a2721a73824df7aab4e92ec891d"
] | [
"07-AdventOfCode2021/05/day-05.py"
] | [
"import numpy as np\n\nlines = open(\"input.txt\", \"r\").readlines()\nlines = [line[:-1] for line in lines]\nlines = [line.split(\" -> \") for line in lines]\nlines = [list(([int(num) for num in coordinate.split(\",\")]) for coordinate in line) for line in lines]\n\n# filter all diagonal\ntemplines = []\nfor idx, ... | [
[
"numpy.sum",
"numpy.zeros",
"numpy.diff"
]
] |
ardalanghadimi/ATC | [
"cbe7eece9c7b8b316a0503f9e6e805c47f688d77"
] | [
"openmdao/recorders/sqlite_recorder.py"
] | [
"\"\"\"\nClass definition for SqliteRecorder, which provides dictionary backed by SQLite.\n\"\"\"\n\nimport io\nimport os\nimport sqlite3\n\nimport warnings\nimport numpy as np\nfrom six import iteritems\nfrom six.moves import cPickle as pickle\n\nfrom openmdao.recorders.base_recorder import BaseRecorder\nfrom open... | [
[
"numpy.load",
"numpy.save"
]
] |
danielmlow/composition | [
"d3de032cfe60f4b73e88b50afac78077b0af8f84"
] | [
"models/cnn41_gs.py"
] | [
"'''\nThis is based on cnn35_64. This is after the first pilot. \nChanges:\n-don't filter out # in the tokenizer, tokenize both together. or save tokenizer https://stackoverflow.com/questions/45735070/keras-text-preprocessing-saving-tokenizer-object-to-file-for-scoring\n-use 'number' w2v as representation for any d... | [
[
"matplotlib.pyplot.switch_backend",
"tensorflow.set_random_seed",
"numpy.array",
"numpy.random.seed",
"pandas.DataFrame",
"numpy.round"
]
] |
paulkogni/backpack | [
"3122de062d5bbcdcba8f8e02d24adb1bd2cdada6"
] | [
"examples/example_indiv_grads.py"
] | [
"\"\"\"Compute the gradient with PyTorch and the variance with BackPACK.\"\"\"\n\nfrom torch.nn import CrossEntropyLoss, Flatten, Linear, Sequential\n\nfrom backpack import backpack, extend, extensions\nfrom backpack.utils.examples import load_mnist_data\n\nB = 4\nX, y = load_mnist_data(B)\n\nprint(\"# Gradient wit... | [
[
"torch.nn.Linear",
"torch.nn.CrossEntropyLoss",
"torch.nn.Flatten"
]
] |
MarouaJaoua/cells-nuclei-segmentation | [
"09d65db104a7297ec6f4c975b668bb7ca93c7372",
"09d65db104a7297ec6f4c975b668bb7ca93c7372"
] | [
"source/model/layers/fusion_net_layers.py",
"source/train/train.py"
] | [
"\"\"\"Source: https://github.com/marshuang80/cell-segmentation\"\"\"\nimport torch.nn as nn\n\n\nclass ConvLayer(nn.Module):\n def __init__(self, in_channels, out_channels, kernel_size,\n padding=1, stride=1, name=None):\n super(ConvLayer, self).__init__()\n\n block = []\n b... | [
[
"torch.nn.MaxPool2d",
"torch.nn.Sequential",
"torch.nn.BatchNorm2d",
"torch.nn.ConvTranspose2d",
"torch.nn.ReLU",
"torch.nn.Conv2d"
],
[
"torch.device",
"torch.max",
"torch.no_grad",
"torch.optim.Adam",
"torch.optim.SGD",
"numpy.mean",
"torch.cuda.is_availab... |
carterjgreen/undergrad-thesis | [
"b6cd0270ab06eb889bd409f585f44953b1994887"
] | [
"AN24_05.py"
] | [
"# AN77_05 -- Mimo processing\nimport Class.Adf24Tx2Rx4 as Adf24Tx2Rx4\nimport Class.RadarProc as RadarProc\nimport time as time\nimport matplotlib.pyplot as plt\nfrom numpy import *\n\n# (1) Connect to DemoRad\n# (2) Enable Supply\n# (3) Configure RX\n# (4) Configure TX\n# (5) Start Measurements\n# (6) Conf... | [
[
"matplotlib.pyplot.ion",
"matplotlib.pyplot.show",
"matplotlib.pyplot.draw",
"matplotlib.pyplot.pause",
"matplotlib.pyplot.clf",
"matplotlib.pyplot.imshow"
]
] |
soddencarpenter/dataviz | [
"289ac890b04820acf1c0fc516e0cb502570626e4"
] | [
"ExplorePy/one.py"
] | [
"import pandas as pd\nimport numpy as np\n\ndata = np.array(['python','php','java'])\nseries = pd.Series(data)\nprint (series)\n\n# Create a Dict from a input\ndata = {'Courses' :\"pandas\", 'Fees' : 20000, 'Duration' : \"30days\"}\ns2 = pd.Series(data)\nprint (s2)\n\n\n# read the chicago temperature csv into a dat... | [
[
"numpy.array",
"pandas.read_csv",
"pandas.Series"
]
] |
0xflotus/rembg | [
"7fb6683169d588f653281d53c3c258838194c950"
] | [
"src/rembg/u2net/detect.py"
] | [
"import errno\nimport os\nimport time\nimport urllib.request\nimport sys\n\nimport numpy as np\nimport pkg_resources\nimport torch\nimport torch.nn as nn\nimport torch.nn.functional as F\nimport torchvision\nfrom PIL import Image\nfrom skimage import transform\nfrom torchvision import transforms\nfrom tqdm import t... | [
[
"torch.device",
"numpy.array",
"torch.min",
"numpy.zeros",
"torch.max",
"torch.no_grad",
"torch.cuda.is_available",
"torch.load"
]
] |
orestmy/Facial-Similarity-with-Siamese-Networks-in-Pytorch | [
"96570ffece22d23f82e8218147d94d49ec125722"
] | [
"src/main.py"
] | [
"import torchvision.datasets as dset\nfrom torch.utils.data import DataLoader\nimport torch\nfrom torchvision.transforms import transforms\nfrom data import SiameseNetworkDataset\nfrom helpers import Config, show_plot\nfrom models import SiameseNetwork, SoftMaxLoss\n\nclass Trainer():\n def __init__(self):\n\n ... | [
[
"torch.utils.data.DataLoader",
"torch.load"
]
] |
VincentLa/pandas | [
"67112b813af6c367f604366f2352c9a1bb1fedf3"
] | [
"pandas/core/indexes/interval.py"
] | [
"\"\"\" define the IntervalIndex \"\"\"\nimport textwrap\nimport warnings\n\nimport numpy as np\n\nfrom pandas.compat import add_metaclass\nfrom pandas.core.dtypes.missing import isna\nfrom pandas.core.dtypes.cast import (\n find_common_type, maybe_downcast_to_dtype, infer_dtype_from_scalar)\nfrom pandas.core.dt... | [
[
"numpy.nextafter",
"pandas.core.arrays.interval.IntervalArray.from_tuples",
"pandas.core.common._all_not_none",
"pandas._libs.interval.IntervalMixin.__new__",
"pandas.core.dtypes.cast.maybe_downcast_to_dtype",
"numpy.where",
"pandas.core.dtypes.cast.find_common_type",
"pandas.core.... |
leandroaquinopereira/cnn-comparison | [
"65f45c4a44a364f97a500b38d9dced43c9f83f91"
] | [
"experiments/googlenet.py"
] | [
"# -*- coding: utf-8 -*-\n\"\"\"GoogLeNet.ipynb\n\nAutomatically generated by Colaboratory.\n\nOriginal file is located at\n https://colab.research.google.com/drive/1LMqTT0uVAZgFbN6wyy5NlctyS9pb0AYo\n\n# References\n\nhttps://medium.com/mlearning-ai/implementation-of-googlenet-on-keras-d9873aeed83c\n\nhttps://ww... | [
[
"tensorflow.keras.callbacks.TensorBoard",
"tensorflow.test.gpu_device_name",
"tensorflow.keras.layers.Input",
"tensorflow.keras.preprocessing.image_dataset_from_directory",
"tensorflow.keras.layers.AveragePooling2D",
"tensorflow.keras.layers.Flatten",
"tensorflow.keras.callbacks.ModelC... |
Babdus/Protolanguage | [
"050aeed5e7ac5905515a887dcbab434457ae2f47"
] | [
"Code/IPA/parse_IPA_single_symbols.py"
] | [
"import sys\nimport pandas as pd\nfrom collections import Counter\n\ndef main(argv):\n df = pd.io.parsers.read_csv(argv[0],index_col=0)\n # print(df)\n #\n # IPA_dict = {}\n # for i, row in df.iterrows():\n # temp_dict = {}\n # for col_name in row.index:\n # print(i, col_name... | [
[
"pandas.io.parsers.read_csv"
]
] |
ashoknar/TensorNetwork | [
"82636b75a0c53b5447c84d9a4e85226fe0e6f43a"
] | [
"tensornetwork/tests/split_node_symmetric_test.py"
] | [
"# Copyright 2019 The TensorNetwork Authors\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n# http://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless required by applicable... | [
[
"numpy.random.seed",
"numpy.testing.assert_allclose",
"numpy.full",
"numpy.random.randint"
]
] |
sandeep-krishnamurthy/keras-mxnet-tests | [
"94772497798b98231202c26ebd49027128e41ca5"
] | [
"keras1.2/nightly_test/test_variational_autoencoder.py"
] | [
"'''\nThis code is forked from https://github.com/fchollet/keras/blob/master/examples/\nand modified to use as MXNet-Keras integration testing for functionality and sanity performance\nbenchmarking.\n\nThis script demonstrates how to build a variational autoencoder with Keras.\n\nReference: \"Auto-Encoding Variatio... | [
[
"numpy.prod"
]
] |
jlpalomino/matplotcheck | [
"b225e51d645f6a6b3b7a6db139350c9ff4e22451"
] | [
"matplotcheck/timeseries.py"
] | [
"import numpy as np\nimport matplotlib.dates as mdates\nfrom dateutil.relativedelta import relativedelta\nimport math\n\nfrom .base import PlotTester\n\n\nclass TimeSeriesTester(PlotTester):\n \"\"\"A PlotTester for 2 dimensional time series plots.\n\n Parameters\n ----------\n ax: ```matplotlib.axes.Ax... | [
[
"matplotlib.dates.num2date",
"numpy.isin",
"numpy.testing.assert_equal"
]
] |
wwoods/job_stream | [
"7bed3d9d42b8a08bcc92dfbc632f389d6ecc9b7d"
] | [
"python/job_stream/test/test_baked.py"
] | [
"\nfrom .common import ExecuteError, JobStreamTest\n\nimport pandas as pd\n\n\nclass TestBaked(JobStreamTest):\n OUT_PATH = \"/tmp/js_out.csv\"\n\n @classmethod\n def setUpClass(cls):\n src = \"\"\"\n from job_stream.inline import getCpuCount, Work\n with Work([1]) as w... | [
[
"pandas.read_csv"
]
] |
hillarypan/plato | [
"181ad0e0e00b0b7486fa364200a8187d879a450e"
] | [
"plato/draw/blender/Scene.py"
] | [
"from ... import draw\nimport numpy as np\nimport bpy\n\nclass Scene(draw.Scene):\n __doc__ = draw.Scene.__doc__\n\n RENDER_COUNT = 0\n\n def render(self):\n new_scene = bpy.data.scenes.new('plato_{}'.format(self.RENDER_COUNT))\n (width, height) = self.size_pixels\n new_scene.render.re... | [
[
"numpy.max",
"numpy.linalg.norm",
"numpy.asarray",
"numpy.sum",
"numpy.atleast_2d"
]
] |
asparsh/cuddly-spoon | [
"63d0a481c7274cb572ad5340d6dd2218a01d1816"
] | [
"train_neural_network.py"
] | [
"import torch\nimport torch.nn as nn\n\ndef training_routine(net,train_loader,n_iters,gpu):\n \n optimizer = torch.optim.SGD(net.parameters(),lr=0.0001,momentum=0.8)\n criterion = nn.BCELoss()\n loss_list = []\n index_list = []\n \n for j in range(n_iters): \n running_loss = 0\n ... | [
[
"torch.nn.BCELoss"
]
] |
clowdr/clowdr | [
"346263ee806ae7c992a37dfc9bd9b87db3fa48c3"
] | [
"clowdr/task.py"
] | [
"#!/usr/bin/env python\n#\n# This software is distributed with the MIT license:\n# https://github.com/gkiar/clowdr/blob/master/LICENSE\n#\n# clowdr/task.py\n# Created by Greg Kiar on 2018-02-28.\n# Email: gkiar@mcin.ca\n\nfrom argparse import ArgumentParser\nfrom datetime import datetime\nfrom time import mktime, l... | [
[
"pandas.DataFrame"
]
] |
DeShrike/C_python_ipc | [
"14380f6b82003585580ce452d5d5581bdf54ad07"
] | [
"sender.py"
] | [
"# http://weifan-tmm.blogspot.kr/2015/07/a-simple-turorial-for-python-c-inter.html\nimport sysv_ipc\nimport numpy as np\nimport struct\n\nBUFF_SIZE = 16\n\nfrom type_definitions import *\n\nif __name__ == \"__main__\":\n msg_string = \"sample string\\0\"\n msg_double1 = 1234.56789\n msg_double2 = 9876.1234... | [
[
"numpy.arange"
]
] |
kakun45/MTADashVisualization | [
"7edac4de650c54671356a11ac91d1c1f477d33bc"
] | [
"history_of_changes/callback2-for-MTA-01-works.py"
] | [
"import dash\nimport dash_core_components as dcc\nimport dash_html_components as html\nfrom dash.dependencies import Input, Output\nimport plotly.graph_objs as go\nimport pandas as pd\n\n# get help from installed module:\n# in terminal\n# import dash_html_components as html\n# print(help(html.Div))\n\n# Create a fi... | [
[
"pandas.read_csv"
]
] |
davidjwilson/pceb | [
"259cf4b18b51b7163d6ce84ab150c5f65f8cfdec"
] | [
"eg_uma/.ipynb_checkpoints/find_line-checkpoint.py"
] | [
"import numpy as np\nimport matplotlib.pyplot as plt\nimport astropy.io.fits as fits\nimport glob\nfrom astropy.table import Table\nfrom astropy.io import ascii\nfrom astropy.convolution import convolve, Box1DKernel\nimport astropy.units as u\n\nx1 = []\n\ndef on_key(event):\n global x1\n if event.key == 'w':... | [
[
"matplotlib.pyplot.xlim",
"matplotlib.pyplot.step",
"matplotlib.pyplot.close",
"matplotlib.pyplot.figure",
"matplotlib.pyplot.show",
"matplotlib.pyplot.axvline"
]
] |
christiaanjs/phylo-hacking | [
"b4095995a8c789267cee4268d8e6ba107d1b8428"
] | [
"pymc/eval/variational_analysis.py"
] | [
"import numpy as np\nimport theano.tensor as tt\nfrom pylo.topology import TreeTopology\nimport pylo.transform\nimport newick\nimport pymc3 as pm\nfrom pylo.tree.coalescent import CoalescentTree, ConstantPopulationFunction\nfrom pylo.hky import HKYSubstitutionModel\nfrom pylo.pruning import LeafSequences\nimport sy... | [
[
"numpy.ones",
"numpy.empty"
]
] |
moneygeek/zipline | [
"c90019754d4a02d7118c181535d3932e40430633"
] | [
"zipline/utils/factory.py"
] | [
"#\n# Copyright 2016 Quantopian, 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 applicable law or... | [
[
"pandas.Timestamp"
]
] |
HAL-42/DeepLabV2YQ | [
"96bfcf1055da7adeb4a7c1ed841f6ec29957be59"
] | [
"python/utils/crf.py"
] | [
"#!/usr/bin/env python\n# coding: utf-8\n#\n# Author: Kazuto Nakashima\n# URL: https://kazuto1011.github.io\n# Date: 09 January 2019\n\n\nimport numpy as np\nimport pydensecrf.densecrf as dcrf\nimport pydensecrf.utils as utils\n\n\nclass DenseCRF(object):\n def __init__(self, iter_max, pos_w, pos_xy_std, bi... | [
[
"numpy.ascontiguousarray",
"numpy.array"
]
] |
joeferg425/clarke_park_exploration | [
"9834dfbb1211f477c9dc99499f30cfb02175c302"
] | [
"clarke_park_3d.py"
] | [
"\"\"\"This python script plots the Clarke and Park Transforms.\r\n\r\nThe Transforms of three-phase helixes allow user interaction with a variety\r\nof functions variables.\r\n\r\nAuthor: joe f.\r\nGitHub: https://github.com/joeferg425\r\n\"\"\"\r\nfrom typing import Any\r\nimport numpy as np\r\nimport dash\r\nfro... | [
[
"numpy.max",
"numpy.array",
"numpy.sin",
"numpy.zeros",
"numpy.ones",
"numpy.min",
"numpy.einsum",
"numpy.cos",
"numpy.sqrt",
"numpy.linspace"
]
] |
omerlux/Recurrent_Neural_Network_-_Part_2 | [
"afaa4f31fcaf1c9fcf97f6757263c1ed6b0fa4eb"
] | [
"mos-pytorch1.1/PTB-20201018-170341-SOTA/scripts/model.py"
] | [
"import math\nimport torch\nimport torch.nn as nn\nimport torch.nn.functional as F\n\n\nfrom embed_regularize import embedded_dropout\nfrom locked_dropout import LockedDropout\nfrom weight_drop import WeightDrop\n\nclass RNNModel(nn.Module):\n \"\"\"Container module with an encoder, a recurrent module, and a dec... | [
[
"torch.nn.Linear",
"torch.nn.LSTM",
"torch.nn.ModuleList",
"torch.nn.Tanh",
"torch.LongTensor",
"torch.nn.functional.softmax",
"torch.nn.Embedding"
]
] |
yangliu-re/nasbench | [
"bfd4328afc24727d1e7d5e33f8d8839310101830"
] | [
"nasbench/lib/model_builder.py"
] | [
"# Copyright 2019 The Google Research Authors.\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n# http://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless required by applicab... | [
[
"tensorflow.reshape",
"tensorflow.gradients",
"tensorflow.compat.v1.trainable_variables",
"tensorflow.compat.v1.train.piecewise_constant",
"tensorflow.control_dependencies",
"tensorflow.compat.v1.layers.dense",
"tensorflow.one_hot",
"tensorflow.identity",
"tensorflow.cast",
... |
ecohydro/GlobalUrbanHeat | [
"0590fc16420f32cbe834f1838745d6e7e9704132"
] | [
"src/json_to_csv.py"
] | [
"##################################################################################\n#\n# Trends\n# By Cascade Tuholske July 2021\n#\n# Write json outputs to .csv\n#\n#################################################################################\n\n# Depedencies\nimport pandas as pd\nimport os \nimport glo... | [
[
"pandas.read_json"
]
] |
Meatplay/steam-vr-wheel | [
"01d02d9036d5a718b570b5a3316d9a3989f0f7f2"
] | [
"steam_vr_wheel/_wheel.py"
] | [
"from collections import deque\r\nfrom math import pi, atan2, sin, cos\r\n\r\nimport numpy as np\r\nimport openvr\r\nimport os\r\nimport copy\r\n\r\nfrom steam_vr_wheel._virtualpad import VirtualPad, RightTrackpadAxisDisablerMixin\r\nfrom steam_vr_wheel.pyvjoy import HID_USAGE_X\r\n\r\n\r\n\r\nFULLTURN = 4\r\n\r\n\... | [
[
"numpy.cumsum",
"numpy.array",
"numpy.diff"
]
] |
Swanson-Hysell-Group/2018_Midcontinent_Rift | [
"9dfa585fb43a2305ed284f306801fdda7db5a055"
] | [
"Code/bayesian_inversion/kewee_inversion/apw_path.py"
] | [
"from __future__ import print_function\nimport os, sys\nimport numpy as np\nimport scipy.stats as st\nimport pandas as pd\n\nsys.path.append(os.path.abspath('../mcplates'))\nimport mcplates\n\n# Shift all longitudes by 180 degrees to get around some plotting\n# issues. This is error prone, so it should be fixed eve... | [
[
"pandas.read_csv"
]
] |
GekFreeman/SparrowRecSys | [
"4592dd7fa556e9ee30512ca244b81885d045ba02"
] | [
"TFRecModel/src/com/wzhe/sparrowrecsys/offline/tensorflow/DeepFM.py"
] | [
"import tensorflow as tf\n\n# Training samples path, change to your local path\nTRAIN_DATA_URL = \"file:///Users/zhewang/Workspace/SparrowRecSys/src/main/resources/webroot/sampledata/modelSamples.csv\"\nsamples_file_path = tf.keras.utils.get_file(\"modelSamples.csv\", TRAIN_DATA_URL)\n\n\n# load sample as tf datase... | [
[
"tensorflow.feature_column.categorical_column_with_identity",
"tensorflow.keras.utils.get_file",
"tensorflow.keras.layers.Input",
"tensorflow.keras.layers.DenseFeatures",
"tensorflow.feature_column.categorical_column_with_vocabulary_list",
"tensorflow.feature_column.numeric_column",
"t... |
numenic/pyNastran | [
"fd5d3f0bf18db6595d85b9ac152f611e23122a68",
"fd5d3f0bf18db6595d85b9ac152f611e23122a68"
] | [
"pyNastran/op2/tables/oes_stressStrain/real/oes_bend.py",
"pyNastran/bdf/cards/elements/beam.py"
] | [
"from itertools import cycle\nimport numpy as np\n\nfrom pyNastran.utils.numpy_utils import integer_types\nfrom pyNastran.op2.tables.oes_stressStrain.real.oes_objects import (\n StressObject, StrainObject, OES_Object)\nfrom pyNastran.f06.f06_formatting import write_floats_13e, write_floats_8p1e\n\n\nclass RealBe... | [
[
"numpy.allclose",
"numpy.array_equal",
"numpy.zeros"
],
[
"numpy.full",
"numpy.array",
"numpy.linalg.norm",
"numpy.asarray",
"numpy.zeros"
]
] |
catalystneuro/brody-lab-to-nwb | [
"bb792591eae988b2dec1a3a608979832da8f884d"
] | [
"brody_lab_to_nwb/interfaces/customsortingextractor.py"
] | [
"import numpy as np\n\nimport spikeextractors as se\n\n\nclass CustomSortingExtractor(se.SortingExtractor):\n extractor_name = \"custom\"\n is_writable = False\n\n def __init__(self):\n super().__init__()\n self._units = {}\n self.is_dumpable = False\n\n def set_sampling_frequency(s... | [
[
"numpy.where",
"numpy.array"
]
] |
Inevitable-Marzipan/pandas | [
"ff50b46045886604dd70438f73df7bf9da3da89b"
] | [
"pandas/core/nanops.py"
] | [
"import functools\nimport itertools\nimport operator\nfrom typing import Any, Optional, Tuple, Union\n\nimport numpy as np\n\nfrom pandas._config import get_option\n\nfrom pandas._libs import iNaT, lib, tslibs\nfrom pandas.compat._optional import import_optional_dependency\n\nfrom pandas.core.dtypes.cast import _in... | [
[
"pandas._libs.tslibs.Timedelta",
"numpy.where",
"numpy.iscomplexobj",
"numpy.apply_along_axis",
"pandas.core.dtypes.common.is_float_dtype",
"pandas.core.dtypes.common.is_any_int_dtype",
"pandas.core.dtypes.cast.maybe_upcast_putmask",
"pandas.core.dtypes.common.is_datetime64_dtype",... |
vadim0x60/mimic3-benchmarks | [
"2f6fa1ff32ac8b75b9bb0c900fea14124a6976f2"
] | [
"mimic3models/multitask/main.py"
] | [
"from __future__ import absolute_import\nfrom __future__ import print_function\n\nfrom mimic3models.multitask import utils\nfrom mimic3benchmark.readers import MultitaskReader\nfrom mimic3models.preprocessing import Discretizer, Normalizer\nfrom mimic3models import metrics\nfrom mimic3models import keras_utils\nfro... | [
[
"numpy.equal",
"numpy.array"
]
] |
liyingben/kaggle-airbus-ship-detection | [
"21d89b2f1273b31a6ffafb4fe5f7e643ffbbc567"
] | [
"src/models/linknet.py"
] | [
"from collections import OrderedDict\nimport torch.nn as nn\nimport torchvision.models as models\n\n\nclass LinkNet(nn.Module):\n def __init__(self, num_classes, resnet_size=18, pretrained_encoder=True):\n super().__init__()\n self.num_classes = num_classes\n\n # The LinkNet encoder is a Res... | [
[
"torch.nn.ReLU",
"torch.nn.BatchNorm2d",
"torch.nn.ConvTranspose2d",
"torch.nn.Conv2d"
]
] |
isaacsultan/comp-550 | [
"24e7d22a6f998a94ad6eb020f1df13970da4b150"
] | [
"src/models/glove_filter.py"
] | [
"import pickle\r\nimport csv\r\nimport os\r\n\r\nimport pandas as pd\r\nimport numpy as np\r\n\r\nfrom util.params import Params\r\n\r\n\r\ndef filter_glove(word_indices_path, filtered_output):\r\n\r\n print(\"Read files...\")\r\n iterator = pd.read_csv('data/glove.42B.300d.txt', header=None, index_col=0, \r\... | [
[
"pandas.DataFrame",
"pandas.read_csv"
]
] |
xihuaiwen/chinese_bert | [
"631afbc76c40b0ac033be2186e717885246f446c"
] | [
"code_examples/tensorflow/cosmoflow/models/cosmoflow.py"
] | [
"\"\"\"Configurable model specification for CosmoFlow\"\"\"\n\nimport tensorflow as tf\nimport tensorflow.keras.layers as layers\n\nfrom .layers import scale_1p2\n\n\ndef build_model(input_shape, target_size,\n conv_size=16, kernel_size=2, n_conv_layers=5,\n fc1_size=128, fc2_size=64,\... | [
[
"tensorflow.keras.layers.Lambda",
"tensorflow.keras.layers.Flatten",
"tensorflow.keras.layers.Conv3D",
"tensorflow.keras.layers.Dense",
"tensorflow.keras.layers.Dropout",
"tensorflow.keras.models.Sequential"
]
] |
JIAQING-XIE/Google_NLP_DL | [
"45f45e8cbca695ad079af58790edd0619783b0c2"
] | [
"9.11/tor/model_lstm/lstm.py"
] | [
"import torch\nimport torch.nn as nn\nimport torch.nn.functional as F\nfrom config import *\nfrom torch.nn.utils.rnn import pad_packed_sequence, pack_padded_sequence\n\nclass LSTM(nn.Module):\n def __init__(self, vocab_size, embedding_size, word_embedding_matrix):\n super(LSTM, self).__init__()\n\n ... | [
[
"torch.nn.Linear",
"torch.nn.Embedding.from_pretrained",
"torch.nn.Dropout",
"torch.nn.LSTM",
"torch.max",
"torch.nn.init.xavier_uniform_",
"torch.from_numpy",
"torch.nn.functional.log_softmax",
"torch.nn.functional.softmax",
"torch.randn"
]
] |
acumos/acumos-c-client | [
"717e97e10c04fead31cb116a1dd30342cde3b726"
] | [
"acumos_cpp/tests/test_protogen.py"
] | [
"# -*- coding: utf-8 -*-\n# ===============LICENSE_START=======================================================\n# Acumos Apache-2.0\n# ===================================================================================\n# Copyright (C) 2017-2018 AT&T Intellectual Property & Tech Mahindra. All rights reserved.\n# =... | [
[
"pandas.DataFrame",
"numpy.sum"
]
] |
selonsy/MachineLearning | [
"4e1be16aeab6a312511206751e9c168963d31839",
"4e1be16aeab6a312511206751e9c168963d31839"
] | [
"asimo/train/Config.py",
"asimo/Z_DaSiamRPN/utils.py"
] | [
"\"\"\"\nConfiguration for training SiamFC and tracking evaluation\nWritten by Heng Fan\n\"\"\"\nimport numpy as np\n\nclass Config:\n def __init__(self):\n\n\n self.show_interval = 100 # 用于多久显示一次训练的信息\n self.anchor_scales = np.array([32, 64, 128, 256]) # np.array([8, ]) siameseRPN; siamFPN: 32, ... | [
[
"numpy.array"
],
[
"numpy.array",
"numpy.linalg.norm",
"numpy.array_equal",
"numpy.zeros",
"torch.is_tensor",
"numpy.mean",
"torch.from_numpy",
"torch.squeeze",
"numpy.transpose",
"numpy.sqrt"
]
] |
DiegoOrtegoP/Software | [
"4a07dd2dab29db910ca2e26848fa6b53b7ab00cd",
"4a07dd2dab29db910ca2e26848fa6b53b7ab00cd"
] | [
"catkin_ws/src/f23-LED/led_detection/include/led_detection/LEDDetector_forloops.py",
"catkin_ws/src/ros_cap/src/line_detector.py"
] | [
"from api import LEDDetector\nfrom duckietown_msgs.msg import Vector2D, LEDDetection, LEDDetectionArray\nfrom led_detection import logger\nfrom math import floor, ceil\nimport numpy as np\nimport rospy\nimport time\n\n# plotting \nimport matplotlib.pyplot as plt\nimport matplotlib.cm as cm\nfrom matplotlib.patches ... | [
[
"numpy.mean",
"numpy.sign",
"matplotlib.patches.Rectangle",
"numpy.ndindex",
"matplotlib.pyplot.subplots",
"numpy.swapaxes",
"numpy.argmax",
"matplotlib.pyplot.gca",
"numpy.array",
"matplotlib.pyplot.title",
"matplotlib.pyplot.figure",
"scipy.ndimage.filters.maximum... |
solapark/frcnn_keras_original | [
"3561d1de18f41868efc9cec927761613d75a5dc3"
] | [
"utils.py"
] | [
"import cv2\nimport numpy as np\n\ndef get_concat_img(img_list, cols=3):\n rows = int(len(img_list)/cols)\n hor_imgs = [np.hstack(img_list[i*cols:(i+1)*cols]) for i in range(rows)]\n ver_imgs = np.vstack(hor_imgs)\n return ver_imgs\n\ndef draw_box(image, box, color = (0, 255, 0)):\n x1, y1, x2, y2 = ... | [
[
"numpy.square",
"numpy.zeros",
"numpy.argmin",
"numpy.hstack",
"numpy.vstack"
]
] |
qxzcode/aoc_2019 | [
"5a6ae570d4ec62a1e05456b58562cb05d1c10f71"
] | [
"08/second.py"
] | [
"import sys # argv\nimport numpy as np\n\n\n# load the input file\nwith open(sys.argv[1]) as f:\n arr = np.array([int(d) for d in f.read().strip()])\n\nwidth = int(sys.argv[2])\nheight = int(sys.argv[3])\narr = arr.reshape(-1, height, width)\n\nfirst_non2 = np.vectorize(lambda arr: arr[np.where(arr != 2)[0][0]],... | [
[
"numpy.where",
"numpy.apply_along_axis"
]
] |
mathcbc/nn_robust_attacks | [
"5c80091dcf2b80d6d22af8e5e1b103218c36e889"
] | [
"setup_inception.py"
] | [
"## Modified by Nicholas Carlini to match model structure for attack code.\n## Original copyright license follows.\n\n\n# Copyright 2015 The TensorFlow Authors. All Rights Reserved.\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the Lic... | [
[
"numpy.array",
"tensorflow.app.flags.DEFINE_integer",
"tensorflow.app.flags.DEFINE_string",
"tensorflow.GraphDef",
"tensorflow.gfile.Exists",
"tensorflow.import_graph_def",
"tensorflow.Session",
"tensorflow.reshape",
"tensorflow.gfile.GFile",
"tensorflow.placeholder",
"... |
odidev/cmdstanpy | [
"49f00baff21bfd11541b3c98a5f2fb36e6b7d9ce"
] | [
"cmdstanpy/cmdstan_args.py"
] | [
"\"\"\"\nCmdStan arguments\n\"\"\"\nimport logging\nimport os\nfrom enum import Enum, auto\nfrom numbers import Integral, Real\nfrom time import time\nfrom typing import List, Union\n\nfrom numpy.random import RandomState\n\nfrom cmdstanpy.utils import (\n cmdstan_path,\n cmdstan_version_at,\n get_logger,\... | [
[
"numpy.random.RandomState"
]
] |
yhyeh/LG-FedAvg | [
"f64a2943c7f1fed214412033e0fa0a63f3c03fb8"
] | [
"main_local.py"
] | [
"#!/usr/bin/env python\n# -*- coding: utf-8 -*-\n# Python version: 3.6\n\nimport copy\nimport os\nimport pickle\nimport pandas as pd\nimport numpy as np\nimport torch\nfrom torch import nn\nfrom torch.utils.data import DataLoader\n\nfrom utils.options import args_parser\nfrom utils.train_utils import get_data, get_... | [
[
"pandas.DataFrame",
"numpy.array",
"torch.cuda.is_available",
"torch.nn.CrossEntropyLoss"
]
] |
psridhar-asapp/espnet | [
"7825783ef60cfe6b3a218d58008cafbe71559a11"
] | [
"utils/convert_fbank_to_wav.py"
] | [
"#!/usr/bin/env python3\n\n# Copyright 2018 Nagoya University (Tomoki Hayashi)\n# Apache 2.0 (http://www.apache.org/licenses/LICENSE-2.0)\n\nimport argparse\nimport logging\nimport os\n\nfrom distutils.version import LooseVersion\n\nimport librosa\nimport numpy as np\nfrom scipy.io.wavfile import write\n\nfrom es... | [
[
"numpy.dot",
"numpy.random.rand",
"numpy.linalg.pinv",
"numpy.power",
"numpy.abs",
"numpy.iinfo"
]
] |
simpeg/geosci-labs | [
"0963c5766477e59af6625954036f580481cfaf82"
] | [
"geoscilabs/em/DipoleWidget1D.py"
] | [
"from __future__ import print_function\nfrom __future__ import absolute_import\nfrom __future__ import unicode_literals\n\nimport numpy as np\nfrom SimPEG import electromagnetics as EM\nimport matplotlib.pyplot as plt\nimport matplotlib.ticker as ticker\nimport matplotlib\nimport matplotlib.gridspec as gridspec\n\n... | [
[
"numpy.ones_like",
"matplotlib.pyplot.figure",
"numpy.arange",
"matplotlib.pyplot.tight_layout",
"numpy.abs",
"numpy.linspace",
"matplotlib.pyplot.subplot"
]
] |
mihirp1998/sbnet_3d_tensorflow | [
"2a990c6e16d33b5b89815c9543819a3e42ebab1d"
] | [
"sbnet_tensorflow/benchmark/sparse_conv_lib.py"
] | [
"\"\"\"\n\n Sparse Blocks Network\n Copyright (c) 2017, Uber Technologies, 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/LICENS... | [
[
"tensorflow.contrib.layers.batch_norm",
"tensorflow.nn.conv2d",
"tensorflow.load_op_library",
"tensorflow.matmul",
"tensorflow.ones_like",
"numpy.tile",
"tensorflow.reshape",
"tensorflow.scatter_nd",
"tensorflow.zeros_like",
"tensorflow.stack",
"tensorflow.greater",
... |
wollbo/threshold | [
"378a32260fe4f4c5fa481138f778398427fb82e3"
] | [
"main.py"
] | [
"import numpy as np\nimport argparse\nimport matplotlib\nimport matplotlib.pyplot as plt\nfrom lightgbm import LGBMClassifier\nfrom sklearn import metrics, model_selection\nfrom sklearn.preprocessing import StandardScaler\nfrom sklearn.pipeline import make_pipeline\nfrom data import core\n\n\ndef arg_parse():\n ... | [
[
"matplotlib.pyplot.xlim",
"matplotlib.pyplot.savefig",
"numpy.arange",
"numpy.around",
"matplotlib.use",
"matplotlib.pyplot.close",
"matplotlib.pyplot.hist",
"matplotlib.rcParams.update",
"sklearn.model_selection.train_test_split",
"matplotlib.pyplot.axvline",
"matplotl... |
EnsembleGovServices/Kamodo-ccmc-readers | [
"75841f7ad832997159046d4b2523e0a244316e9d"
] | [
"kamodo_ccmc/flythrough/SF_utilities.py"
] | [
"# -*- coding: utf-8 -*-\r\n\"\"\"\r\nCreated on Fri Apr 23 17:09:14 2021\r\n\r\n@author: rringuet\r\n\r\nMost needed functions to support the SatelliteFlythrough and SingleSatelliteFlythrough\r\nsoftwares. The corresponding height function to be inverted by CalcIlev\r\nwill need to be labeled H_ilev for ilev, H_il... | [
[
"numpy.array",
"numpy.isnan",
"numpy.float64",
"numpy.where",
"numpy.abs",
"numpy.linspace",
"numpy.unique"
]
] |
711e/mmdetection | [
"89da8dbe4dbcfd7c92a184d54c7c87675e49c70c"
] | [
"mmdet/models/anchor_heads/ssd_head.py"
] | [
"import numpy as np\nimport torch\nimport torch.nn as nn\nimport torch.nn.functional as F\nfrom mmcv.cnn import xavier_init\n\nfrom mmdet.core import (AnchorGenerator, anchor_target, weighted_smoothl1,\n multi_apply)\nfrom .anchor_head import AnchorHead\nfrom ..registry import HEADS\n\n\n@HEA... | [
[
"torch.cat",
"torch.nn.ModuleList",
"torch.nn.functional.cross_entropy",
"torch.nn.Conv2d",
"torch.LongTensor",
"numpy.sqrt",
"numpy.floor"
]
] |
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