repo_name stringlengths 6 130 | hexsha list | file_path list | code list | apis list |
|---|---|---|---|---|
Flawless1202/smarts_data_collector | [
"d8a9f0cdfa6a3c16a2173cb6208659eb73e24253"
] | [
"examples/data_collector.py"
] | [
"import importlib\nimport logging\nimport time\nimport os\nimport random\nimport shutil\n\nimport gym\nimport numpy as np\nfrom scipy.spatial.transform import Rotation\nfrom examples import default_argument_parser\n\nfrom smarts.core.agent import AgentSpec, Agent\nfrom smarts.core.agent_interface import AgentInterf... | [
[
"numpy.concatenate",
"numpy.array",
"numpy.zeros",
"numpy.logical_and",
"scipy.spatial.transform.Rotation.from_euler",
"scipy.spatial.transform.Rotation.from_rotvec",
"numpy.linalg.inv"
]
] |
IanFla/Two-Stage | [
"32789bb87dccda8d2ed6623dfbb9e84800d8b6ec"
] | [
"paper/Exp1/Exp1(8)KdfBw.py"
] | [
"import numpy as np\nfrom matplotlib import pyplot as plt\nimport pickle\n\n\nfile = open('Data/KdfBw7', 'rb')\nData = np.array(pickle.load(file))\nKdf = [3, 4, 5, 8, 12, 20, 50, 100, 0]\nBw = np.linspace(0.4, 3.2, 15)\nNames = ['kdf', 'bw',\n 'IS est', 'IS a-var', 'n0/ESS', 'n0/RSS', 'kernel number',\n ... | [
[
"numpy.log",
"numpy.ones",
"matplotlib.pyplot.subplots",
"matplotlib.pyplot.show",
"numpy.linspace"
]
] |
anhdang000/yolact | [
"391535d04b3df61fc27ad15700e6044511f23da9"
] | [
"eval.py"
] | [
"from data import COCODetection, get_label_map, MEANS, COLORS\nfrom yolact import Yolact\nfrom utils.augmentations import BaseTransform, FastBaseTransform, Resize\nfrom utils.functions import MovingAverage, ProgressBar\nfrom layers.box_utils import jaccard, center_size, mask_iou\nfrom utils import timer\nfrom utils... | [
[
"numpy.array",
"torch.stack",
"torch.cuda.synchronize",
"torch.no_grad",
"matplotlib.pyplot.title",
"torch.set_default_tensor_type",
"numpy.save",
"torch.from_numpy",
"matplotlib.pyplot.show",
"numpy.searchsorted",
"torch.Tensor",
"matplotlib.pyplot.imshow"
]
] |
UWSEDS-aut17/uwseds-group-neurolit | [
"ada0833bc2c4ff0e1d870b73d6016643e6feea8b"
] | [
"neurolit/tests/tests_base.py"
] | [
"from neurolit.base.dataset import *\nfrom shutil import rmtree\nimport neurolit as nlit\nimport pandas as pd\nimport numpy as np\nimport unittest\nimport os\n\nclass TestBase(unittest.TestCase):\n\n def test_data_folder(self):\n data_path = os.path.join(nlit.__path__[0],'data')\n reading_data_path... | [
[
"numpy.ones",
"numpy.zeros"
]
] |
anonymoustbd/LS2SD | [
"f7da92c459e9ee34da83722ad62aa5c892b3148e"
] | [
"4x/LS2SD/main_test.py"
] | [
"import argparse\nimport os\nimport time\n\nimport torch\nimport torch.nn.parallel\nimport torch.optim\nimport torch.utils.data\n\nfrom dataloaders.kitti_loader_test import load_calib, oheight, owidth, input_options, KittiDepth\nfrom model import DepthCompletionNet\nfrom metrics import AverageMeter, Result\nimport ... | [
[
"torch.device",
"torch.no_grad",
"torch.optim.Adam",
"torch.cuda.is_available",
"torch.utils.data.DataLoader",
"torch.load",
"torch.nn.DataParallel"
]
] |
DavidSabbagh/meeg_power_regression | [
"d9cd5e30028ffc24f08a52966c7641f611e92ee6"
] | [
"debug/compute_scores_models_fieldtrip_spoc_example_test.py"
] | [
"import os.path as op\n\nimport numpy as np\nfrom sklearn.pipeline import make_pipeline\nfrom sklearn.linear_model import RidgeCV\nfrom sklearn.preprocessing import StandardScaler\nfrom sklearn.model_selection import cross_val_score, KFold, GroupShuffleSplit\nimport mne\n\nfrom mne import Epochs\nfrom mne.datasets.... | [
[
"numpy.array",
"sklearn.pipeline.make_pipeline",
"sklearn.preprocessing.StandardScaler",
"sklearn.model_selection.GroupShuffleSplit",
"numpy.mean",
"numpy.std",
"numpy.linspace",
"numpy.logspace",
"sklearn.model_selection.cross_val_score"
]
] |
hsezhiyan/tensor2tensor | [
"15d3ab09d5da8e00295990213ed5485988c20d23"
] | [
"tensor2tensor/trax/layers/core_test.py"
] | [
"# coding=utf-8\n# Copyright 2019 The Tensor2Tensor 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 requir... | [
[
"numpy.sum",
"numpy.array"
]
] |
MigMagan/pyne | [
"624ce1e9f43905c37ed84b9d7989ef7930b8d2b0"
] | [
"pyne/mcnp.py"
] | [
"#!/usr/bin/env python\n\"\"\"Module for parsing MCNP output data. MCNP is a general-purpose Monte Carlo\nN-Particle code developed at Los Alamos National Laboratory that can be used\nfor neutron, photon, electron, or coupled neutron/photon/electron transport.\nFurther information on MCNP can be obtained from http:... | [
[
"numpy.array",
"numpy.empty"
]
] |
DishaDH123/Disha551Dashboard | [
"3354ff94134e6094f7e5759f17abe5d988a32198"
] | [
"data/data_functions.py"
] | [
"import pandas as pd\n\n##### GENERAL WRANGLING #####\n\n\ndef drop_and_rename_columns(df: pd.DataFrame) -> pd.DataFrame:\n \"\"\"\n Drops irrelevent random columns and renames remaining columns\n to descriptive, readable names.\n\n Parameters\n ----------\n df : pd.DataFrame\n Our raw data... | [
[
"pandas.to_datetime",
"pandas.cut"
]
] |
littleprince1121/AAAI2022-IEEE-for-MMReID | [
"8a249e764597208d471c93b7a8911648aeac86ba"
] | [
"torchreid/models/hacnn3modal.py"
] | [
"from __future__ import division, absolute_import\r\nfrom functools import partial\r\nfrom pickle import TRUE\r\nfrom warnings import simplefilter\r\nfrom caffe2.python.workspace import FetchBlob\r\nfrom numpy.core.fromnumeric import shape\r\nfrom numpy.core.records import format_parser\r\nfrom numpy.lib.function_b... | [
[
"torch.nn.Linear",
"torch.cat",
"torch.nn.Sequential",
"torch.nn.ReLU",
"torch.nn.BatchNorm1d"
]
] |
huzongxiang/CrystalNetwork | [
"a434f76fa4347d42b3c905852ce265cd0bcefca3",
"a434f76fa4347d42b3c905852ce265cd0bcefca3"
] | [
"matdgl/data/generator.py",
"matdgl/models/distframe.py"
] | [
"# -*- coding: utf-8 -*-\n\"\"\"\nCreated on Tue Dec 14 14:12:08 2021\n\n@author: huzongxiang\n\"\"\"\n\nfrom tensorflow.keras.utils import to_categorical\nfrom .crystalgraph import LabelledCrystalGraph, LabelledCrystalGraphMasking, GraphBatchGeneratorSequence, GraphBatchGeneratorMasking, GraphBatchGeneratorDist\n\... | [
[
"tensorflow.keras.utils.to_categorical"
],
[
"tensorflow.keras.metrics.Mean",
"tensorflow.nn.compute_average_loss",
"tensorflow.distribute.MirroredStrategy",
"tensorflow.GradientTape",
"tensorflow.keras.losses.SparseCategoricalCrossentropy",
"tensorflow.keras.metrics.SparseCategori... |
xiaosuhu/mapper-tda | [
"3c546a4590e2ae05334f3dabb2578fb2f19b4d8d"
] | [
"mapper/em_help.py"
] | [
"import pandas as pd\nimport numpy as np\nfrom networkx.drawing.nx_agraph import graphviz_layout\nimport matplotlib.pyplot as plt\nimport networkx as nx\nimport os\nimport colorsys, errno\n\ntry:\n import params\nexcept ImportError:\n import params_default as params\n\n\ndef mkdir_p(path):\n try:\n ... | [
[
"matplotlib.pyplot.colorbar",
"numpy.random.rand",
"matplotlib.pyplot.xlabel",
"matplotlib.pyplot.title",
"matplotlib.pyplot.close",
"numpy.disp",
"matplotlib.pyplot.figure",
"numpy.arange",
"matplotlib.pyplot.ylabel",
"matplotlib.pyplot.bar",
"matplotlib.pyplot.ticklab... |
sirmarcel/floq | [
"a456957500c809a5bb4cdae2d7b1d4720c28f2c4"
] | [
"floq/systems/rabi.py"
] | [
"import numpy as np\nimport floq.systems.parametric_system as ps\n\n\ndef hf(controls, parameters, omega=None):\n g = controls[0]\n e1 = parameters[0]\n e2 = parameters[1]\n hf = np.zeros([3, 2, 2])\n hf[0] = np.array([[0, 0], [g, 0]])\n hf[1] = np.array([[e1, 0], [0, e2]])\n hf[2] = np.array([... | [
[
"numpy.array",
"numpy.zeros"
]
] |
anguyen8/shape-bias | [
"40ee49d31439296274835642ed1e1ca63c0aa799"
] | [
"loader/data_loader.py"
] | [
"from functools import partial\nimport numpy\nimport os\nimport re\nimport random\nimport signal\nimport csv\nfrom settings import settings\nimport numpy as np\nfrom collections import OrderedDict\nfrom scipy.misc import imread\nfrom multiprocessing import Pool, cpu_count\nfrom multiprocessing.pool import ThreadPoo... | [
[
"numpy.full",
"numpy.array",
"numpy.empty",
"numpy.asarray",
"numpy.zeros",
"numpy.ones",
"numpy.shape",
"scipy.misc.imread",
"scipy.ndimage.interpolation.zoom",
"numpy.amax",
"numpy.repeat",
"numpy.indices"
]
] |
DavidD997/Handwriting_Digit_Recognition | [
"eba6b053f8a40cd07ed884bdf2cedb875f9c7f35"
] | [
"demo_saving_SVHN.py"
] | [
"import torch\nfrom torch import nn, optim\nfrom torch.utils.data import DataLoader\nfrom torchvision import transforms\nfrom torchvision import datasets\nfrom torch.utils.data import Dataset, DataLoader\nfrom scipy.io import loadmat\nimport matplotlib.pyplot as plt\nimport numpy as np\nimport cv2\n\nbatch_size = 6... | [
[
"numpy.asfarray",
"scipy.io.loadmat"
]
] |
benlansdell/deep-rdd | [
"2f1443aa9800d0e0f3a4ce9051c1b8b9ed8c2ae9"
] | [
"lib/paramsweep_w2.py"
] | [
"import numpy as np\nfrom lib.lif import LIF, ParamsLIF\nfrom lib.causal import causaleffect\n\nparams = ParamsLIF()\nlif = LIF(params)\n\n#Simulate for a range of $W$ values.\nN = 20\nnsims = 500\nwmax = 20\nn = params.n \n\n#Play with different c values\n#c = 0.99\nc = 0.5\n\nparams.c = c\nlif.setup(params)\n\nwv... | [
[
"numpy.array",
"numpy.linspace",
"numpy.savez",
"numpy.zeros"
]
] |
dlax/scipy | [
"221cb8fa31c45d08ec6d9f946ebf9476bdc1fccd"
] | [
"scipy/optimize/__init__.py"
] | [
"\"\"\"\n=====================================================\nOptimization and root finding (:mod:`scipy.optimize`)\n=====================================================\n\n.. currentmodule:: scipy.optimize\n\nOptimization\n============\n\nGeneral-purpose\n---------------\n\n.. autosummary::\n :toctree: genera... | [
[
"numpy.testing.Tester"
]
] |
TalatCikikci/AirSim | [
"d71527274de468dad4fb1a229605a68dd9246061"
] | [
"PythonClient/DQNdrone.py"
] | [
"from AirSimClient import *\n\nfrom argparse import ArgumentParser\n\nimport numpy as np\nfrom cntk.core import Value\nfrom cntk.initializer import he_uniform\nfrom cntk.layers import Sequential, Convolution2D, Dense, default_options\nfrom cntk.layers.typing import Signature, Tensor\nfrom cntk.learners import adam,... | [
[
"numpy.array",
"numpy.linalg.norm",
"numpy.random.choice",
"numpy.reshape",
"numpy.zeros",
"numpy.random.rand",
"numpy.ones",
"numpy.mean",
"numpy.std",
"numpy.random.randint",
"numpy.arange",
"numpy.cross"
]
] |
brekelma/dsbox_graphs | [
"84070aa49211dcb1346f7d4b2d97c4d2b432d15f"
] | [
"dsbox_graphs/sdne.py"
] | [
"import os\nimport sys\nimport typing\nimport networkx\nimport numpy as np\n\nimport tensorflow.compat.v1 as tf\ntf.disable_v2_behavior()\n#from GEM.gem.embedding import node2vec\nfrom dsbox_graphs.GEM.gem.embedding import sdne\n#from GEM.gem.embedding import sdne_utils\nimport keras.models\nimport tempfile\nfrom s... | [
[
"tensorflow.compat.v1.disable_v2_behavior",
"sklearn.preprocessing.LabelEncoder",
"numpy.concatenate"
]
] |
jsalbert/biotorch | [
"74fad0dd32529e754e4bba8298d4e0fd0a06a886"
] | [
"biotorch/datasets/dataset.py"
] | [
"import torch\nimport numpy\nimport random\n\nfrom torchvision import transforms\nfrom torch.utils.data import DataLoader\n\n\nclass Dataset(object):\n def __init__(self,\n target_size,\n dataset_path,\n mean=None,\n std=None,\n trai... | [
[
"numpy.random.seed",
"torch.initial_seed",
"torch.Generator",
"torch.utils.data.DataLoader"
]
] |
AshleyLab/lvh-fusion | [
"5a7c22d2236345ba67c8ed5f9c4dc720b49936fb"
] | [
"ecg/models/dev_1d.py"
] | [
"from torch import nn\nimport torch\nimport torch.nn.functional as F\n\n# +\nfrom torch import nn\nfrom collections import OrderedDict\n\n\nclass Bottleneck(nn.Module):\n def __init__(self,in_channel,out_channel,expansion,activation,stride=1,padding = 1):\n super(Bottleneck, self).__init__()\n self... | [
[
"torch.nn.Linear",
"torch.nn.Dropout",
"torch.cat",
"torch.nn.Conv1d",
"torch.nn.Sequential",
"torch.nn.ReLU",
"torch.nn.AdaptiveAvgPool1d",
"torch.nn.BatchNorm1d",
"torch.nn.MaxPool1d"
]
] |
snastase/connectivity-srm | [
"994eacc31743b490962325904b9149010e17ba30"
] | [
"semantic_model.py"
] | [
"import numpy as np\nfrom copy import deepcopy\nimport gensim\nfrom nltk.corpus import stopwords\n\nstory_name = 'forgot'\n\n# Load dictionary of input filenames\nwith open('metadata.json') as f:\n metadata = json.load(f)\n\n# Load in pre-trained word2vec embeddings (slow)\nvectors_fn = '~/Work/GoogleNews-vector... | [
[
"numpy.full",
"numpy.ceil",
"numpy.save",
"numpy.mean",
"numpy.arange",
"numpy.vstack"
]
] |
cgnorthcutt/PyTorch_CIFAR10 | [
"53d330e01f1ab59abe45192dea9d28abbf401ae3"
] | [
"cifar10_models/vgg.py"
] | [
"import torch\nimport torch.nn as nn\nimport os\n\n__all__ = [\n 'VGG', 'vgg11', 'vgg11_bn', 'vgg13', 'vgg13_bn', 'vgg16', 'vgg16_bn',\n 'vgg19_bn', 'vgg19',\n]\n\nclass VGG(nn.Module):\n\n def __init__(self, features, num_classes=10, init_weights=True):\n super(VGG, self).__init__()\n self.f... | [
[
"torch.nn.Linear",
"torch.nn.Dropout",
"torch.nn.MaxPool2d",
"torch.nn.Sequential",
"torch.nn.init.constant_",
"torch.nn.BatchNorm2d",
"torch.nn.init.kaiming_normal_",
"torch.nn.ReLU",
"torch.nn.Conv2d",
"torch.nn.init.normal_",
"torch.load",
"torch.nn.AdaptiveAvgPo... |
ryan2x/Deep-Hough-Transform-Line-Priors | [
"3527aceb85018c352cd0dcdb156f989bf038b1c0"
] | [
"ht-lcnn/eval-sAP.py"
] | [
"#!/usr/bin/env python3\n\"\"\"Evaluate sAP5, sAP10, sAP15 (from LCNN)\nUsage:\n eval-sAP.py <path>...\n eval-sAP.py (-h | --help )\n\nExamples:\n python eval-sAP.py logs/*/npz/000*\n\nArguments:\n <path> One or more directories from train.py\n\nOptions:\n -h --help ... | [
[
"numpy.concatenate",
"numpy.load",
"numpy.argsort",
"numpy.cumsum"
]
] |
blafabregue/TimeSeriesDeepClustering | [
"85f4ab2fd45bda3296c6b0861ee11e6c7a77c594"
] | [
"networks/IDEC.py"
] | [
"\"\"\"\nBased on Keras implementation https://github.com/XifengGuo/IDEC:\nand article :\n Xifeng Guo, Long Gao, Xinwang Liu, Jianping Yin.\n Improved Deep Embedded Clustering with Local Structure Preservation. IJCAI 2017.\n\nOriginal Author:\n Xifeng Guo. 2017.1.30\nAuthor:\nBaptiste Lafabregue 20... | [
[
"tensorflow.keras.metrics.Mean",
"tensorflow.keras.backend.expand_dims",
"tensorflow.keras.backend.sum",
"tensorflow.GradientTape",
"tensorflow.data.Dataset.from_tensor_slices",
"tensorflow.keras.backend.transpose",
"tensorflow.keras.losses.KLD",
"sklearn.cluster.KMeans",
"nump... |
SuReLI/Deep-RL-agents | [
"646d4b666632ffc5df3373e21ef13420c29acd33"
] | [
"A3C/Network.py"
] | [
"\nimport tensorflow as tf\nimport numpy as np\n\nfrom NetworkArchitecture import NetworkArchitecture\nimport settings\n\n\nclass Network:\n\n def __init__(self, state_size, action_size, scope):\n if scope == 'global':\n print(\"Initialization of the global network\")\n\n with tf.variabl... | [
[
"tensorflow.train.AdamOptimizer",
"tensorflow.gradients",
"tensorflow.variable_scope",
"tensorflow.log",
"tensorflow.placeholder",
"tensorflow.reduce_sum",
"tensorflow.clip_by_value",
"tensorflow.layers.dense",
"tensorflow.one_hot",
"tensorflow.clip_by_global_norm",
"te... |
WPI-SurfMet-Lab/Multiscale-Statistical-Analysis | [
"6a7d7ae316bff6cebc59c25681883dec3cba17b8"
] | [
"src/multi_stat_analysis/StatsTestsUI.py"
] | [
"import warnings\n\nwarnings.simplefilter(\"error\", RuntimeWarning)\n\nimport wx\nimport numpy as np\nfrom matplotlib.backends.backend_wxagg import FigureCanvasWxAgg as FigureCanvas\nfrom matplotlib.backends.backend_wx import NavigationToolbar2Wx as NavigationToolbar\nfrom matplotlib.figure import Figure\nfrom sci... | [
[
"numpy.square",
"numpy.array",
"numpy.round_",
"scipy.stats.f.ppf",
"numpy.sum",
"numpy.mean",
"matplotlib.backends.backend_wx.NavigationToolbar2Wx",
"numpy.sqrt",
"numpy.abs",
"matplotlib.figure.Figure",
"numpy.average",
"numpy.var"
]
] |
wayi1/pytorch | [
"f09c696ecda155c42006f85d2687445dfb24774f",
"e832ff58bf93fb1bcb2292219f6c98ab3c842484"
] | [
"test/test_spectral_ops.py",
"torch/library.py"
] | [
"# Owner(s): [\"module: fft\"]\n\nimport torch\nimport unittest\nimport math\nfrom contextlib import contextmanager\nfrom itertools import product\nimport itertools\nimport doctest\nimport inspect\n\nfrom torch.testing._internal.common_utils import \\\n (TestCase, run_tests, TEST_NUMPY, TEST_LIBROSA, TEST_MKL)\n... | [
[
"torch.backends.cuda.cufft_plan_cache.clear",
"torch.stack",
"torch.testing._internal.common_device_type.ops",
"torch.fft.ihfft",
"torch.fft.irfftn",
"torch.fft.ihfftn",
"torch.cuda.device",
"torch.istft",
"torch.ones",
"torch.fft.ifftn",
"torch.stft",
"torch.fft.ff... |
eidetic-av/librealsense | [
"5c9b6f129c339dc280ac9e35571e1fc6e5686f30"
] | [
"third-party/openvino/inference_engine/samples/python_samples/cross_check_tool/utils.py"
] | [
"# Copyright (C) 2018-2019 Intel Corporation\n# SPDX-License-Identifier: Apache-2.0\n#\n\nimport argparse\nimport logging as log\nimport os\nimport sys\nimport traceback\nimport xml\n\ntry:\n import cv2\nexcept Exception as e:\n log.error(\"Can not import OpenCV Python package.\\nPlease install required pytho... | [
[
"numpy.max",
"numpy.random.normal",
"numpy.isinf",
"numpy.isnan",
"numpy.count_nonzero",
"numpy.reshape",
"numpy.load",
"numpy.min",
"numpy.savez_compressed",
"numpy.abs",
"numpy.absolute"
]
] |
Michaelrising/PPO-PyTorch | [
"171256881f11a7bf18e51baa843004abebc18267"
] | [
"GLV/Xitorch/_impls/interpolate/interp_1d.py"
] | [
"import torch\nimport warnings\nfrom abc import abstractmethod\nfrom xitorch._impls.interpolate.base_interp import BaseInterp\nfrom xitorch._impls.interpolate.extrap_utils import get_extrap_pos, get_extrap_val\n\nclass BaseInterp1D(BaseInterp):\n def __init__(self, x, y=None, extrap=None, **unused):\n sel... | [
[
"torch.zeros",
"torch.cat",
"torch.numel",
"torch.min",
"torch.max",
"torch.gather",
"torch.clamp",
"torch.logical_and",
"torch.all",
"torch.solve",
"torch.zeros_like",
"torch.allclose",
"torch.empty"
]
] |
Hartvi/Detectron2-mobilenet | [
"15942c470787643e6327e0663519696b2672211a"
] | [
"ipalm/image_to_outputs.py"
] | [
"import os\r\nimport cv2\r\nimport pickle\r\n\r\nfrom ipalm.intermediate_data import *\r\nfrom ipalm.utils import gpu_to_numpy, get_category_weights_from_csb\r\nfrom train import setup\r\nfrom detectron2.engine.defaults import DefaultPredictor\r\nfrom detectron2.data import MetadataCatalog\r\n\r\nimport numpy as np... | [
[
"numpy.array",
"numpy.zeros"
]
] |
suvratjain1995/CarND-Capstone | [
"42a3da72313b8814ef0ced8f425af90b57313b9f"
] | [
"ros/src/tl_detector/traffic_l/utils/ops.py"
] | [
"# Copyright 2017 The TensorFlow Authors. All Rights Reserved.\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n# http://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless requ... | [
[
"tensorflow.space_to_depth",
"tensorflow.ones",
"tensorflow.ones_like",
"tensorflow.logical_not",
"tensorflow.reshape",
"tensorflow.stack",
"tensorflow.greater",
"tensorflow.depth_to_space",
"tensorflow.to_float",
"tensorflow.cast",
"tensorflow.rank",
"tensorflow.sh... |
TaikiInoue/iClassification | [
"7045c7721c9ee86e3823b13722d22b6c0095b76a"
] | [
"icls/blocks/conv11_bn_relu.py"
] | [
"import torch.nn as nn\nfrom torch import Tensor\nfrom torch.nn import Module\n\n\nclass Conv11BnReLU(Module):\n def __init__(\n self,\n # nn.Conv2d\n in_channels: int,\n out_channels: int,\n kernel_size: int = 1,\n stride: int = 1,\n padding: int = 0,\n di... | [
[
"torch.nn.ReLU",
"torch.nn.Conv2d",
"torch.nn.BatchNorm2d"
]
] |
roclark/DALI | [
"3b114c6ebee38ff3815a9b4a234402e4d1affaa0"
] | [
"dali/test/python/test_operator_power_spectrum.py"
] | [
"# Copyright (c) 2019, NVIDIA CORPORATION. All rights reserved.\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in 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 req... | [
[
"numpy.fft.fft"
]
] |
Dhruv26/finBERT | [
"22dcc9e7417b04b30db49ef773110d50a600b936"
] | [
"finbert/finbert.py"
] | [
"from __future__ import absolute_import, division, print_function\n\nimport random\n\nimport pandas as pd\nfrom pytorch_pretrained_bert.tokenization import BertTokenizer\nfrom torch.nn import MSELoss\nfrom torch.utils.data import (DataLoader, RandomSampler, SequentialSampler,\n TensorDa... | [
[
"numpy.array",
"torch.utils.data.RandomSampler",
"torch.nn.MSELoss",
"numpy.random.seed",
"pandas.DataFrame",
"pandas.concat",
"torch.utils.data.SequentialSampler",
"numpy.argmax",
"torch.utils.data.DataLoader",
"pandas.Series",
"torch.utils.data.TensorDataset"
]
] |
123972/analisis-numerico-computo-cientifico | [
"9ad310579d6376a85ad83862605aa48e5fcdc88c"
] | [
"temas/IV.optimizacion_convexa_y_machine_learning/algoritmos/Python/algorithms_for_uco.py"
] | [
"import math\n\nimport numpy as np\n\nfrom numerical_differentiation import gradient_approximation, \\\n Hessian_approximation\nfrom line_search import line_search_by_backtracking\nfrom utils import compute_error\n\n\n\ndef gradient_descent(f, x_0, tol, \n to... | [
[
"numpy.linalg.norm",
"numpy.zeros",
"numpy.finfo",
"numpy.linalg.cond",
"numpy.linalg.solve"
]
] |
mingdachen/WikiTableT | [
"eb97dda0777f19f91870fc15a961abc337415781"
] | [
"train_helper.py"
] | [
"# pylint: disable=no-member\nimport subprocess\nimport data_utils\nimport threading\nimport argparse\nimport logging\nimport signal\nimport torch\nimport time\nimport nltk\nimport os\n\nfrom config import get_base_parser, MULTI_BLEU_PERL, \\\n EOS_IDX, RESOURCE_LINK, METEOR_DATA, METEOR_JAR\nfrom decorators imp... | [
[
"torch.no_grad"
]
] |
S-Altman/pneumothorax-segmentation | [
"e79673d2a2b3e9ee9db0352d19f52e676ed1187f"
] | [
"unet_pipeline/models/selim_zoo/dpn.py"
] | [
"\"\"\" PyTorch implementation of DualPathNetworks\nPorted to PyTorch by [Ross Wightman](https://github.com/rwightman/pytorch-dpn-pretrained)\n\nBased on original MXNet implementation https://github.com/cypw/DPNs with\nmany ideas from another PyTorch implementation https://github.com/oyam/pytorch-DPNs.\n\nThis impl... | [
[
"torch.nn.AdaptiveMaxPool2d",
"torch.cat",
"torch.nn.functional.avg_pool2d",
"torch.nn.MaxPool2d",
"torch.nn.Sequential",
"torch.nn.BatchNorm2d",
"torch.utils.model_zoo.load_url",
"torch.nn.ReLU",
"torch.nn.Conv2d",
"torch.nn.AdaptiveAvgPool2d"
]
] |
ishine/PaSST | [
"d7049e78e84ba38173ffd779479d1c9ec7d1c116"
] | [
"models/passt.py"
] | [
"\"\"\"\nMost of this code comes from the timm library.\nWe tried to disentangle from the timm library version.\n\nAdapted from https://github.com/rwightman/pytorch-image-models/blob/master/timm/models/vision_transformer.py\n\n\"\"\"\nimport math\nimport logging\nimport warnings\nfrom functools import partial\nfro... | [
[
"torch.nn.Linear",
"torch.cat",
"torch.nn.ModuleList",
"torch.randperm",
"torch.nn.LayerNorm",
"torch.nn.init.constant_",
"torch.randint",
"torch.nn.init.normal_",
"torch.nn.init.zeros_",
"torch.zeros",
"torch.nn.Identity",
"torch.nn.Sequential",
"torch.nn.Tanh"... |
vogdb/nrn | [
"0ccc9ccbc4e376ec87c7985b4913d68da6b2817b"
] | [
"share/lib/python/neuron/__init__.py"
] | [
"\"\"\"\n\nneuron\n======\n\nFor empirically-based simulations of neurons and networks of neurons in Python.\n\nThis is the top-level module of the official python interface to\nthe NEURON simulation environment (http://neuron.yale.edu/neuron/).\n\nDocumentation is available in the docstrings.\n\nFor a list of avai... | [
[
"numpy.ndarray",
"numpy.dtype",
"numpy.interp"
]
] |
choderalab/assaytools2 | [
"32c02aeddf0afef69c91e16135a159e4735ad532"
] | [
"assaytools2/tests/test_titration_96.py"
] | [
"\"\"\"\ntest_titration_96.py\n\"\"\"\n\nimport pytest\n\nfrom ..titration_96 import *\nimport numpy\nimport numpy.testing as npt\n\n# ========\n# test cov\n# ========\ndef test_cov():\n X = tf.constant([[1.0, 2.0], [3.0, 4.0]], dtype=tf.float32)\n npt.assert_almost_equal(\n cov(X),\n [[1.0, 1.0... | [
[
"numpy.testing.assert_almost_equal"
]
] |
SmithB/LSsurf | [
"6333e70f33b7d9fed25fbfe4c45b9d5a8e2ef488"
] | [
"LSsurf/two_mission_dhdt.py"
] | [
"#! /usr/bin/python3\n\n# -*- coding: utf-8 -*-\n\"\"\"\nCreated on Tue Feb 26 17:12:48 2019\n\n@author: ben\n\"\"\"\nfrom PointDatabase import geo_index, point_data, matlabToYear\nfrom PointDatabase.mapData import mapData\nfrom PointDatabase.ATL06_filters import segDifferenceFilter\nfrom PointDatabase.check_ATL06_... | [
[
"numpy.ones_like",
"numpy.argmin",
"scipy.interpolate.RectBivariateSpline",
"numpy.mean",
"numpy.where",
"numpy.concatenate",
"numpy.zeros_like",
"numpy.arange",
"numpy.isfinite",
"numpy.nanmedian",
"numpy.mod",
"numpy.array",
"numpy.round",
"numpy.diff",
... |
Ryuk17/Pytorch-Single-Path-One-Shot-NAS | [
"a1323e983544ece574176a7db093bec1f4543a9e"
] | [
"train_imagenet.py"
] | [
"'''\n@Description: Train Search SuperNet Single Path One Shot Nas \n@Author: xieydd\n@Date: 2019-10-05 15:37:47\n@LastEditTime: 2019-10-11 18:22:59\n@LastEditors: Please set LastEditors\n'''\nimport os\nimport sys\nimport time\nimport numpy as np\nimport torch\nimport logging\nimport torch.nn as nn\nimport torch.... | [
[
"torch.nn.LogSoftmax",
"torch.device",
"torch.distributed.get_world_size",
"torch.cuda.manual_seed_all",
"torch.distributed.init_process_group",
"numpy.random.seed",
"torch.autograd.Variable",
"torch.optim.SGD",
"torch.nn.parallel.DistributedDataParallel",
"torch.distributi... |
gebasilio/tensorflow-mnist-tutorial | [
"917a8d93ee2f9c3fcfb8685069faae6b3bb8f6a1"
] | [
"mlengine/trainer/task.py"
] | [
"# 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 agreed to in writing, software\n# distri... | [
[
"tensorflow.reshape",
"tensorflow.contrib.learn.RunConfig",
"tensorflow.estimator.export.ServingInputReceiver",
"tensorflow.estimator.Estimator",
"tensorflow.nn.softmax",
"tensorflow.one_hot",
"tensorflow.python.platform.tf_logging.log",
"tensorflow.python.platform.tf_logging.set_v... |
rose-gonoud/sql-alchemy-challenge | [
"84d5f189609210d28e759a41214ca04ce961f095"
] | [
"functions.py"
] | [
"import sqlalchemy\nfrom sqlalchemy.ext.automap import automap_base\nfrom sqlalchemy.orm import Session\nfrom sqlalchemy import create_engine, func\nimport pandas as pd\nfrom flask import jsonify\n\n# Defining a function for every app.route that can be pulled into app.py\ndef GetDateAndPrecipDict(engine, Base):\n\n... | [
[
"pandas.DataFrame"
]
] |
deepmedia/tensorflow | [
"ac8aad5c55838566a26ed6725c966d399319c831"
] | [
"tensorflow/python/ops/numpy_ops/np_math_ops.py"
] | [
"# Copyright 2020 The TensorFlow Authors. All Rights Reserved.\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n# http://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless requ... | [
[
"tensorflow.python.ops.sort_ops.argsort",
"numpy.promote_types",
"tensorflow.python.ops.math_ops.equal",
"tensorflow.python.ops.numpy_ops.np_array_ops.amin",
"tensorflow.python.ops.math_ops.matmul",
"tensorflow.python.ops.numpy_ops.np_array_ops.real",
"tensorflow.python.ops.math_ops.mi... |
brentbiseda/W207_Final_NIH_Chest_X_Rays_Classification | [
"e916f8aa4613b80277aa6486b8342d017bad55f8",
"e916f8aa4613b80277aa6486b8342d017bad55f8"
] | [
"tx2/inference.py",
"src/data_preparation.py"
] | [
"#!/usr/bin/env python\r\n# coding: utf-8\r\n\r\nimport numpy as np \r\nimport pandas as pd\r\nimport os\r\nimport time\r\nimport matplotlib.pyplot as plt\r\n\r\nfrom glob import glob\r\n\r\nfrom sklearn.metrics import roc_curve, auc\r\nfrom sklearn.model_selection import train_test_split\r\nfrom itertools import c... | [
[
"numpy.concatenate",
"pandas.DataFrame",
"numpy.mean",
"sklearn.metrics.auc",
"pandas.read_csv"
],
[
"sklearn.model_selection.train_test_split"
]
] |
tebandesade/Detectron.pytorch | [
"b442cda4a415d47abf6bcf40261b6c9bd72bd6dc"
] | [
"data/data_mio/convert_mio_bogota.py"
] | [
"# Convert a detection model trained for COCO into a model that can be fine-tuned\n# on bogota\n#\n# bogota_to_mio\n\nfrom __future__ import absolute_import\nfrom __future__ import division\nfrom __future__ import print_function\nfrom __future__ import unicode_literals\n\nfrom six.moves import cPickle as pickle\n\n... | [
[
"torch.save",
"numpy.random.randn",
"torch.load"
]
] |
jasonhotsauce/neural-network | [
"100960a2270d252e1c30d5c1689e84b41d5791e2"
] | [
"decision_tree_tests.py"
] | [
"import unittest\nimport numpy as np\nfrom decision_tree import DecisionTree\n\n\nclass DecisionTreeTests(unittest.TestCase):\n\n def setUp(self):\n self.sample_input, self.sample_output, self.feature_labels = self._create_test_data()\n\n def tearDown(self):\n del self.sample_output\n del... | [
[
"numpy.array"
]
] |
godmodeguy/Sudoku | [
"3e4e5769b72067f52c337422f73f945e5929bf3d"
] | [
"sudoku_web_solver.py"
] | [
"from selenium import webdriver\nfrom pyautogui import press\nimport numpy as np\n\nfrom solver import Solver\n\n\nclass WebSolver:\n def __init__(self):\n self.driver = webdriver.Chrome()\n self.grid = self.cells = None\n\n def start(self, difficult=None):\n if difficult not in ['easy', ... | [
[
"numpy.array"
]
] |
jupiterbak/KI_SIEMENS_PLM | [
"593ac2ca5f0f651184303e4515bdc9c81c6cdbaf"
] | [
"FAPSPLMTrainers/utils/PERMemory.py"
] | [
"import random\nimport numpy as np\nfrom FAPSPLMTrainers.utils.SumTree import SumTree\n\n\nclass PERMemory:\n e = 0.01\n a = 0.6\n beta = 0.4\n beta_increment_per_sampling = 0.001\n\n def __init__(self, capacity):\n self.tree = SumTree(capacity)\n self.capacity = capacity\n\n def _ge... | [
[
"numpy.power",
"numpy.min"
]
] |
anishmo99/learnPython | [
"91e963609b0ce600d0c46073748611ecbab61dae"
] | [
"textDataPanda.py"
] | [
"import pandas as pd\nimport numpy as np\n\ns = pd.Series(['Anish Mookherjee', 'Harshal Garg', np.nan, 'Shivam', 'Joyal', 'Sarthak'])\nprint(s.str.lower())\nprint(s.str.upper())\nprint(s.str.len()) # length of each string\nprint(s.str.strip()) # good for nothing\nprint(s.str.split(' ')) # splits with the letter/... | [
[
"pandas.Series"
]
] |
artitw/BERT_QA | [
"947e64f9d33a03ee942e3914bed4b4a354236bad"
] | [
"bert_qa/bert_classifier.py"
] | [
"# Copyright 2019 The TensorFlow Authors. All Rights Reserved.\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n# http://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless requ... | [
[
"tensorflow.keras.layers.Dropout"
]
] |
dhritimandas/nobrainer | [
"a44483742c784694783d9dce5e960173bd71e82c"
] | [
"nobrainer/bayesian_utils.py"
] | [
"import tensorflow as tf\nimport tensorflow.compat.v1 as tf1\nimport tensorflow.compat.v2 as tf2\nimport tensorflow_probability as tfp\nfrom tensorflow_probability.python.distributions import (\n deterministic as deterministic_lib,\n)\nfrom tensorflow_probability.python.distributions import independent as indepe... | [
[
"tensorflow.keras.constraints.UnitNorm",
"tensorflow.keras.initializers.Zeros",
"tensorflow.zeros",
"tensorflow.compat.v1.initializers.random_normal",
"tensorflow.nn.softplus",
"tensorflow.reduce_sum",
"tensorflow.keras.regularizers.l2",
"tensorflow.keras.initializers.he_normal"
... |
Rabeeajawaid/latte | [
"ecfde3cdb15b38a167ae4ef21e667f7dd7a3fd25"
] | [
"app/Mask_RCNN/visualize1.py"
] | [
"\"\"\"\r\nMask R-CNN\r\nDisplay and Visualization Functions.\r\n\r\nCopyright (c) 2017 Matterport, Inc.\r\nLicensed under the MIT License (see LICENSE for details)\r\nWritten by Waleed Abdulla\r\n\"\"\"\r\n\r\nimport random\r\nimport itertools\r\nimport colorsys\r\nimport numpy as np\r\nfrom skimage.measure import... | [
[
"numpy.random.choice",
"numpy.random.rand",
"numpy.where",
"matplotlib.patches.Rectangle",
"matplotlib.pyplot.subplots",
"numpy.arange",
"matplotlib.pyplot.tight_layout",
"matplotlib.pyplot.axis",
"matplotlib.pyplot.subplot",
"matplotlib.lines.Line2D",
"numpy.zeros",
... |
wongjoel/VisualMesh | [
"98b973c6cd371aab51f2b631f75c9ac820d3b744"
] | [
"training/projection/__init__.py"
] | [
"import math\n\nimport tensorflow as tf\n\n\ndef _inverse_coefficents(k):\n return [\n -k[0],\n 3.0 * (k[0] * k[0]) - k[1],\n -12.0 * (k[0] * k[0]) * k[0] + 8.0 * k[0] * k[1],\n 55.0 * (k[0] * k[0]) * (k[0] * k[0]) - 55.0 * (k[0] * k[0]) * k[1] + 5.0 * (k[1] * k[1]),\n ]\n\n\ndef _... | [
[
"tensorflow.math.is_finite",
"tensorflow.math.acos",
"tensorflow.zeros_like",
"tensorflow.math.sin",
"tensorflow.clip_by_value",
"tensorflow.stack",
"tensorflow.square",
"tensorflow.cast"
]
] |
cmista/mne-python | [
"f20c60ec23481e8c9888fb9f7da1544378dd2489"
] | [
"mne/io/meas_info.py"
] | [
"# -*- coding: utf-8 -*-\n# Authors: Alexandre Gramfort <alexandre.gramfort@inria.fr>\n# Matti Hämäläinen <msh@nmr.mgh.harvard.edu>\n# Teon Brooks <teon.brooks@gmail.com>\n# Stefan Appelhoff <stefan.appelhoff@mailbox.org>\n#\n# License: BSD (3-clause)\n\nfrom collections import Counter, O... | [
[
"numpy.full",
"numpy.array",
"numpy.dot",
"numpy.array_equal",
"numpy.zeros_like",
"numpy.isnan",
"numpy.char.decode",
"numpy.eye",
"numpy.atleast_1d",
"numpy.arange",
"numpy.all",
"numpy.char.encode",
"numpy.hstack",
"numpy.iinfo",
"numpy.linalg.inv",
... |
weston-barger/tutorials | [
"254d927bd15d89a8d48a385db2c76941d0d26bb2"
] | [
"intermediate_source/forced_alignment_with_torchaudio_tutorial.py"
] | [
"\"\"\"\nForced Alignment with Wav2Vec2\n==============================\n\n**Author** `Moto Hira <moto@fb.com>`__\n\nThis tutorial shows how to align transcript to speech with\n``torchaudio``, using CTC segmentation algorithm described in\n`CTC-Segmentation of Large Corpora for German End-to-end Speech\nRecognition... | [
[
"matplotlib.pyplot.colorbar",
"matplotlib.pyplot.axvspan",
"matplotlib.pyplot.annotate",
"torch.log_softmax",
"torch.maximum",
"matplotlib.pyplot.axvline",
"matplotlib.pyplot.xlabel",
"matplotlib.pyplot.title",
"matplotlib.pyplot.plot",
"matplotlib.pyplot.figure",
"torc... |
zhaotudou/HeteroFusionRCNN | [
"0eb589c660a50c9adad14758e204a2f152ec22cd"
] | [
"hf/core/box_list_ops.py"
] | [
"# Copyright 2017 The TensorFlow Authors. All Rights Reserved.\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n# http://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless requ... | [
[
"tensorflow.minimum",
"tensorflow.concat",
"tensorflow.where",
"tensorflow.greater_equal",
"tensorflow.expand_dims",
"tensorflow.equal",
"tensorflow.reshape",
"tensorflow.truediv",
"tensorflow.transpose",
"tensorflow.constant",
"tensorflow.reduce_max",
"tensorflow.z... |
WarmongeringBeaver/vis_cpu | [
"5b89db71488860052ad970b19933b151753bb3ac"
] | [
"tests/test_vis_cpu.py"
] | [
"\"\"\"Tests of vis_cpu.\"\"\"\nimport pytest\n\nimport numpy as np\nfrom astropy.units import sday\nfrom pyuvsim.analyticbeam import AnalyticBeam\n\nfrom vis_cpu import conversions, simulate_vis, vis_cpu\n\nnp.random.seed(0)\nNTIMES = 10\nNFREQ = 5\nNPTSRC = 20\n\nants = {0: (0, 0, 0), 1: (1, 1, 0)}\n\n\ndef test_... | [
[
"numpy.array",
"numpy.isnan",
"numpy.empty",
"numpy.random.seed",
"numpy.ones",
"numpy.linspace"
]
] |
tderensis/digital_control | [
"2ab6c67815e79396520aab351573fe0b82131e29"
] | [
"control_design.py"
] | [
"\"\"\"\r\nFunctions that construct stable closed loop control systems. Many of the\r\nmethods here are adapted from Digital Control: A State-Space Approach and\r\naccompanying courses at URI.\r\n\r\nRequires numpy, scipy, control\r\n\"\"\"\r\nfrom __future__ import print_function\r\nimport control_poles\r\nimport ... | [
[
"numpy.concatenate",
"numpy.delete",
"numpy.matrix",
"numpy.linalg.matrix_rank",
"numpy.zeros",
"numpy.eye",
"scipy.signal.place_poles",
"numpy.linalg.eig",
"numpy.transpose",
"numpy.linalg.inv",
"numpy.eig"
]
] |
alvinwan/deep-q-learning | [
"fed9d6bad6d0388fb5a9b4fd8be0db812671ce65"
] | [
"run_dqn_atari.py"
] | [
"\"\"\"\n\nUsage:\n run_dqn_atari.py [options]\n\nOptions:\n --batch-size=<size> Batch size [default: 32]\n --envid=<envid> Environment id [default: SpaceInvadersNoFrameskip-v4]\n --model=(atari|simple|fesimple|random) Model to use for training [default: atar... | [
[
"tensorflow.set_random_seed",
"numpy.linalg.norm",
"numpy.random.seed",
"tensorflow.contrib.layers.fully_connected",
"tensorflow.Session",
"tensorflow.reset_default_graph",
"tensorflow.contrib.layers.python.layers.initializers.xavier_initializer",
"tensorflow.python.client.device_l... |
yoomambo/BayesianOptimization_Tuned | [
"54369b176f1b8fadd21df351e7efa03c34128106"
] | [
"code/bayesian_optimization.py"
] | [
"import warnings\r\nimport numpy as np\r\n\r\nfrom .target_space import TargetSpace\r\nfrom .event import Events, DEFAULT_EVENTS\r\nfrom .logger import _get_default_logger\r\nfrom .util import UtilityFunction, acq_max, ensure_rng\r\n\r\nfrom sklearn.gaussian_process.kernels import Matern\r\nfrom sklearn.gaussian_pr... | [
[
"sklearn.gaussian_process.kernels.Matern"
]
] |
stolk/bullet3 | [
"41a0d72759a47ef2df986b0bfe56a03e22516123"
] | [
"examples/pybullet/examples/testrender.py"
] | [
"#testrender.py is a bit slower than testrender_np.py: pixels are copied from C to Python one by one\n\nimport matplotlib.pyplot as plt\nimport pybullet\nimport time\nimport numpy as np #to reshape for matplotlib\n\nplt.ion()\n\nimg = [[1, 2, 3] * 50] * 100 #np.random.rand(200, 320)\n#img = [tandard_normal((50,10... | [
[
"matplotlib.pyplot.ion",
"numpy.reshape",
"matplotlib.pyplot.pause",
"matplotlib.pyplot.gca",
"matplotlib.pyplot.imshow"
]
] |
shawnau/DataScienceBowl2018 | [
"3c6f0f26dd86b71aad55fca52314e6432d0b3a82"
] | [
"utility/func.py"
] | [
"import numpy as np\n\n\n# https://stackoverflow.com/questions/34968722/how-to-implement-the-softmax-function-in-python\ndef np_softmax(x):\n \"\"\"Compute softmax values for each sets of scores in x.\"\"\"\n e_x = np.exp(x - np.max(x, axis=1, keepdims=True))\n return e_x / e_x.sum(axis=1, keepdims=True)\n... | [
[
"numpy.max",
"numpy.exp"
]
] |
dwr-psandhu/cimis | [
"109796305d402a33e0d2ee4437b987c7ca8b84ef"
] | [
"examples/cimis_example.py"
] | [
"# -*- coding: utf-8 -*-\n\"\"\"\ncimis_example.py\n:DESCRIPTION: Example script to collect data from CIMIS using cimis module\nThis script reports ETo and cummulative precipitation, if available,\nfor a queried CIMIS station\n\n:DEPENDENCIES: matplotlib, pandas, urllib2, cimis.py\n\n:REQUIRES app_key from CIMIS\n\... | [
[
"matplotlib.pyplot.figure"
]
] |
zjZSTU/ResNet | [
"f185d1d24cdc96a533b2cf2df94f68172d820cb3"
] | [
"py/lib/models/SmoothLabelCriterion.py"
] | [
"# -*- coding: utf-8 -*-\n\n\"\"\"\n@date: 2020/4/30 下午4:22\n@file: SmoothLabelCriterion.py\n@author: zj\n@description: \n\"\"\"\n\nimport torch\nimport torch.nn as nn\n\n\nclass SmoothLabelCritierion(nn.Module):\n \"\"\"\n TODO:\n 1. Add label smoothing\n 2. Calculate loss\n \"\"\"\n\n def __init... | [
[
"torch.nn.LogSoftmax",
"torch.nn.NLLLoss",
"torch.ones",
"torch.randn",
"torch.nn.KLDivLoss",
"torch.nn.CrossEntropyLoss"
]
] |
SeanLee97/xmnlp | [
"0ffad8616c248845b18f819c0ac0465a4ec45f5d"
] | [
"xmnlp/sentiment/sentiment_model.py"
] | [
"# -*- coding: utf-8 -*-\n\n\"\"\" XMNLP - Sentiment\n\nModel Tree:\n\nsentiment\n├── sentiment.onnx\n└── vocab.txt\n\n\"\"\"\n\nimport os\nfrom typing import Tuple\n\nimport numpy as np\nfrom tokenizers import BertWordPieceTokenizer\n\nfrom xmnlp.base_model import BaseModel\n\n\nMAX_LEN = 150\n\n\nclass SentimentM... | [
[
"numpy.array"
]
] |
jefflai108/VGNSL | [
"0edc3db3691abbad2a505b2165bd99e7a62d784f"
] | [
"data/data_reformat_v3.py"
] | [
"import nltk\nimport numpy as np\nimport os.path as op\nimport json \nimport h5py\nfrom tqdm import tqdm\nimport argparse\n\nfrom utils import compute_spectrogram, read_textgrid, slice_spectrogram, hubert_feature_extraction\n\nclass SummaryJsonReader(object):\n def __init__(self, data_summary_json, image_hdf5, i... | [
[
"numpy.concatenate",
"numpy.array",
"numpy.load",
"numpy.save"
]
] |
jdvelasq/pyfuzzy | [
"4b8c5948f5d05202ec914a60e2bd420133a57e90"
] | [
"fuzzy_toolbox/sugeno.py"
] | [
"\"\"\"\nSugeno fuzzy model\n==============================================================================\n\n\"\"\"\nimport matplotlib.pyplot as plt\nimport numpy as np\n\n\nfrom .core import plot_crisp_input\n\n\n# #############################################################################\n#\n#\n# Fuzzy Varia... | [
[
"matplotlib.pyplot.subplot",
"matplotlib.pyplot.gca",
"numpy.minimum"
]
] |
schwettmann/pretorched-x | [
"ce8c3712434b3cd5d85dcbe8582ff51ddfa7d4ed"
] | [
"pretorched/gans/proggan.py"
] | [
"\"\"\"ProGAN.\n\nThis module implements teh Generative Adversarial Network described in:\n\nProgressive Growing of GANs for Improved Quality, Stability, and Variation\nTero Karras (NVIDIA), Timo Aila (NVIDIA), Samuli Laine (NVIDIA), Jaakko Lehtinen (NVIDIA and Aalto University)\nTero Karras (NVIDIA), Samuli Laine ... | [
[
"torch.hub.model_zoo.load_url",
"torch.nn.functional.interpolate",
"torch.nn.LeakyReLU",
"torch.nn.Conv2d",
"torch.hub.load_state_dict_from_url",
"numpy.sqrt",
"torch.load",
"torch.nn.Hardtanh",
"torch.mean",
"torch.randn"
]
] |
CheesyB/cpointnet | [
"bcb3eaa44e50fc643e2b226457f4f583989664a9"
] | [
"logger.py"
] | [
"#!/usr/bin/env python\n# -*- coding: utf-8 -*-\n#code referenced from https://gist.github.com/gyglim/1f8dfb1b5c82627ae3efcfbbadb9f514\n\nimport tensorflow as tf\nimport numpy as np\nimport scipy.misc \nfrom io import BytesIO # Python 3.x\n\n\nclass Logger(object):\n \n def __init__(self, log_dir):\n ... | [
[
"tensorflow.Summary",
"numpy.histogram",
"numpy.max",
"tensorflow.HistogramProto",
"numpy.sum",
"numpy.min",
"numpy.prod",
"tensorflow.Summary.Value",
"tensorflow.summary.FileWriter"
]
] |
boomesito/picframe | [
"5574fde4d198afd6a1a83d22b24fdaa63d53d64d"
] | [
"picframe/viewer_display.py"
] | [
"import sys\nimport pi3d\n#from pi3d.Texture import MAX_SIZE\nimport math\nimport time\nimport subprocess\nimport logging\nimport os\nimport numpy as np\nfrom PIL import Image, ImageFilter, ImageFile\nfrom picframe import mat_image, get_image_meta\nfrom datetime import datetime\n\n# supported display modes for disp... | [
[
"numpy.linspace",
"numpy.zeros"
]
] |
brills/data-validation | [
"4f8a5d12b3d5db7383ae53d5fe184af1d781449a"
] | [
"tensorflow_data_validation/utils/slicing_util_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# http://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless required by applicable law or agreed ... | [
[
"numpy.array"
]
] |
LaudateCorpus1/fuse-med-ml | [
"56821be0824b599dfbbd7a4b158436cb2c300812"
] | [
"fuse/data/augmentor/augmentor_toolbox.py"
] | [
"\"\"\"\n(C) Copyright 2021 IBM Corp.\n\nLicensed under the Apache License, Version 2.0 (the \"License\");\nyou may not use this file except in compliance with the License.\nYou may obtain a copy of the License at\n\n http://www.apache.org/licenses/LICENSE-2.0\n\nUnless required by applicable law or agreed to in ... | [
[
"numpy.array",
"numpy.reshape",
"numpy.random.RandomState",
"scipy.ndimage.interpolation.map_coordinates",
"numpy.random.shuffle",
"torch.from_numpy",
"torch.clamp",
"torch.randint",
"numpy.arange"
]
] |
mudaseranwer/Python | [
"b2a77cc4fb922ab66f0978e45c108bdb4c30396d"
] | [
"digital_image_processing/index_calculation.py"
] | [
"# Author: João Gustavo A. Amorim\n# Author email: joaogustavoamorim@gmail.com\n# Coding date: jan 2019\n# python/black: True\n\n# Imports\nimport numpy as np\n\n\n# Class implemented to calculus the index\nclass IndexCalculation:\n \"\"\"\n # Class Summary\n This algorithm consists in calculating... | [
[
"numpy.max",
"numpy.arctan",
"numpy.min"
]
] |
dyf/nbody | [
"d7752ab8ace878b535b3eaaef17f5da46ac9c695"
] | [
"rules.py"
] | [
"import numpy as np\nfrom numpy.core.umath_tests import inner1d\nfrom collections import Counter\n\nclass Rule: \n @staticmethod\n def from_dict(rtype, params):\n c = [ Rule ]\n o = []\n\n while len(c):\n cls = c.pop()\n c += cls.__subclasses__()\n o.appen... | [
[
"numpy.append",
"numpy.zeros_like",
"numpy.core.umath_tests.inner1d",
"numpy.linalg.norm",
"numpy.sum",
"numpy.add.at",
"numpy.outer"
]
] |
ebasanez/samur.ai | [
"c8572419dbc140291afd5cc804936ee6f94d0f6a"
] | [
"Dataset Cleaning and Exploration/preprocess_demographics.py"
] | [
"import pandas as pd\nimport DatasetPaths\nfrom utils import sumCells\nfrom statistics import mean \n\nkpis = ['density','surface_ha','age_avg','foreigns_perc','people_per_home','elder_alone_perc','monoparental_homes_perc','income','unemployment_perc']\n\ncells2016 = {\n\t\t\t'density':[(3,3)],\n\t\t\t'surface_ha':... | [
[
"pandas.ExcelFile",
"pandas.DataFrame",
"pandas.read_csv",
"pandas.read_excel"
]
] |
rohPatil/AzureMonitorForSAPSolutions | [
"9728def2cfc8558b444ae6d81341d71d0a1d8410"
] | [
"sapmon/payload/provider/sapnetweaver.py"
] | [
"# Python modules\nimport json\nimport logging\nfrom datetime import datetime, timedelta, timezone\nfrom time import time\nfrom typing import Any, Callable, Dict, List, Optional\nimport re\nfrom threading import Lock\nfrom pandas import merge, DataFrame\n\n# Payload modules\nfrom aiops.aiopshelper import *\nfrom ai... | [
[
"pandas.DataFrame",
"pandas.merge"
]
] |
connorpheraty/TwitOff | [
"a1c972d0faf8f812fad1506c4c3938352f20964b"
] | [
"twitoff/predict2.py"
] | [
"\"\"\"Prediction of User based on tweet embeddings\"\"\"\nimport pickle\nimport numpy as np\nfrom sklearn.linear_model import LogisticRegression\nfrom .models import User\nfrom .twitter import BASILICA\n\ndef predict_user(user1_name, user2_name, tweet_text, cache=None):\n \"\"\"Determine and return which user is ... | [
[
"sklearn.linear_model.LogisticRegression",
"numpy.array",
"numpy.vstack"
]
] |
adunmore/triage | [
"51f4e5bb73740378d22de16de4b15c78a1feea7b"
] | [
"src/tests/conftest.py"
] | [
"import matplotlib\nmatplotlib.use('Agg')\nimport pytest\nimport testing.postgresql\nimport tempfile\nfrom tests.utils import sample_config, populate_source_data\nfrom triage import create_engine\nfrom triage.component.catwalk.storage import ProjectStorage\nfrom triage.component.catwalk.db import ensure_db\nfrom te... | [
[
"matplotlib.use"
]
] |
JacksonWuxs/taac2021-Video-Classification-Rank5 | [
"abecf49b95fe82d9dd47ed37e020d510b04da018"
] | [
"src/model/image_head/efficientNet/efficientnet_model.py"
] | [
"# Copyright 2019 The TensorFlow Authors. All Rights Reserved.\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n# http://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless requ... | [
[
"tensorflow.compat.v1.keras.layers.Dropout",
"tensorflow.compat.v1.nn.avg_pool",
"tensorflow.compat.v1.add",
"tensorflow.compat.v1.squeeze",
"tensorflow.compat.v1.variable_scope",
"tensorflow.compat.v1.identity",
"tensorflow.compat.v1.layers.Conv2D",
"tensorflow.compat.v1.random_un... |
HuyTu7/DebtFree | [
"8c272189772ac261f8d0cdd6a44cb5296ea8e610"
] | [
"CNN_SATD/evaluation.py"
] | [
"#by xiaoxueren\r\n#evaluation of CNN model\r\n\r\nimport tensorflow as tf\r\nimport numpy as np\r\nimport os\r\nimport time\r\nimport datetime\r\nimport data_helpers\r\nfrom data_helpers import load_model as lm\r\nfrom text_cnn2 import TextCNN\r\nfrom tensorflow.contrib import learn\r\nimport csv\r\nfrom sklearn ... | [
[
"numpy.concatenate",
"numpy.array",
"tensorflow.flags.DEFINE_string",
"tensorflow.train.latest_checkpoint",
"tensorflow.flags.DEFINE_boolean",
"tensorflow.Graph",
"tensorflow.Session",
"tensorflow.contrib.learn.preprocessing.VocabularyProcessor.restore",
"tensorflow.ConfigProto... |
ngctnnnn/Detecting_abnormalities_CXR | [
"485b7bead6ec9288dbf053e4a437c77788dbc3be"
] | [
"src/yolov5/hubconf.py"
] | [
"# YOLOv5 🚀 by Ultralytics, GPL-3.0 license\n\"\"\"\nPyTorch Hub models https://pytorch.org/hub/ultralytics_yolov5/\n\nUsage:\n import torch\n model = torch.hub.load('ultralytics/yolov5', 'yolov5s')\n\"\"\"\n\nimport torch\n\n\ndef _create(name, pretrained=True, channels=3, classes=80, autoshape=True, verbos... | [
[
"torch.cuda.is_available",
"numpy.zeros"
]
] |
univieCUBE/PICA2 | [
"59b72fa1ff00692af2fd4ca59d1514599238e2e5"
] | [
"phenotrex/ml/clf/xgbm.py"
] | [
"import os\nfrom typing import Dict, List, Tuple\n\nfrom scipy.sparse import csr_matrix\nimport numpy as np\nimport xgboost as xgb\nfrom sklearn.pipeline import Pipeline\nfrom sklearn.base import clone\n\nfrom phenotrex.ml.trex_classifier import TrexClassifier\nfrom phenotrex.util.logging import get_logger\nfrom ph... | [
[
"numpy.array",
"sklearn.base.clone",
"sklearn.pipeline.Pipeline",
"numpy.arange"
]
] |
noemieplanat/Copy-parcels-master | [
"21f053b81a9ccdaa5d8ee4f7efd6f01639b83bfc"
] | [
"parcels/examples/example_radial_rotation.py"
] | [
"import math\nfrom datetime import timedelta as delta\n\nimport numpy as np\nimport pytest\n\nfrom parcels import AdvectionRK4\nfrom parcels import FieldSet\nfrom parcels import JITParticle\nfrom parcels import ParticleSet\nfrom parcels import ScipyParticle\n\nptype = {'scipy': ScipyParticle, 'jit': JITParticle}\n\... | [
[
"numpy.allclose",
"numpy.linspace",
"numpy.sqrt",
"numpy.zeros"
]
] |
Tecplot/handyscripts | [
"c4158d46286cc5b66aed2d7b52f8b4cd7002ba36"
] | [
"python/dataconversion/FE_to_STL.py"
] | [
"\"\"\"Creates STL files from currently active FE-triangle zones.\n\nDescription\n-----------\nThis connected-mode script creates STL files from currently active FE-Triangle zones. One STL file per zone.\nExported files are indexed by zone number.\nPrior to execution of this script:\n 1. Before extracting iso-su... | [
[
"numpy.array",
"numpy.column_stack",
"numpy.zeros"
]
] |
darcyabjones/selectml | [
"fc63f9de0e0e4c496f34d2a77f169a2c59968786",
"fc63f9de0e0e4c496f34d2a77f169a2c59968786"
] | [
"src/selectml/tf/models.py",
"src/selectml/sk/weighting.py"
] | [
"import tensorflow as tf\n\nfrom typing import TYPE_CHECKING\nif TYPE_CHECKING:\n from typing import Optional\n\nfrom .losses import (\n SemiHardTripletLoss,\n HardTripletLoss,\n MultiSURFTripletLoss,\n RankLoss\n)\n\n\nclass SSModel(tf.keras.Model):\n\n def __init__(\n self,\n marke... | [
[
"tensorflow.keras.layers.Add",
"tensorflow.GradientTape",
"tensorflow.metrics.Mean",
"tensorflow.math.l2_normalize",
"tensorflow.reduce_mean",
"tensorflow.keras.layers.Concatenate"
],
[
"numpy.array",
"scipy.spatial.distance.pdist",
"scipy.cluster.hierarchy.cut_tree",
"... |
ltalirz/aiida-quantumespresso | [
"4a57750dba4e09cf4a1c51a391ba9e385c1318ba"
] | [
"aiida_quantumespresso/parsers/pw.py"
] | [
"# -*- coding: utf-8 -*-\nfrom __future__ import absolute_import\n\nimport numpy\nfrom six.moves import zip\n\nfrom aiida import orm\nfrom aiida.common import exceptions\nfrom aiida.parsers import Parser\n\nfrom aiida_quantumespresso.utils.mapping import get_logging_container\n\n\nclass PwParser(Parser):\n \"\"\... | [
[
"numpy.array",
"numpy.dot",
"numpy.transpose",
"numpy.einsum",
"numpy.linalg.inv"
]
] |
rowedenny/RecBole | [
"b3f63fb23f4198f257497eb22602dd6125694a3c"
] | [
"recbole/data/dataset/dataset.py"
] | [
"# @Time : 2020/6/28\n# @Author : Yupeng Hou\n# @Email : houyupeng@ruc.edu.cn\n\n# UPDATE:\n# @Time : 2020/10/28 2020/10/13, 2020/11/10\n# @Author : Yupeng Hou, Xingyu Pan, Yushuo Chen\n# @Email : houyupeng@ruc.edu.cn, panxy@ruc.edu.cn, chenyushuo@ruc.edu.cn\n\n\"\"\"\nrecbole.data.dataset\n##################... | [
[
"numpy.concatenate",
"numpy.max",
"torch.stack",
"numpy.zeros",
"pandas.merge",
"pandas.concat",
"torch.arange",
"torch.FloatTensor",
"torch.nn.utils.rnn.pad_sequence",
"numpy.split",
"pandas.factorize",
"torch.LongTensor",
"numpy.arange",
"pandas.Series",
... |
GpNico/bert_semantics | [
"9b8f9db7b136d1059e6f82c26fd10d164fe2e78d"
] | [
"logical/logical_scorer.py"
] | [
"\nimport numpy as np\nimport pickle\nimport tqdm\n\nimport torch\n\n\nclass LogicalScorer:\n\n def __init__(self, model = None, tokenizer = None, device = None, dataset_name = ''):\n # Model used to compute scores\n self.model = model\n self.tokenizer = tokenizer\n self.device = devi... | [
[
"numpy.log",
"torch.no_grad",
"torch.where"
]
] |
abarbosa94/datasets | [
"2b8c85a3332cb1311d403ff465e379a51bf12cd3"
] | [
"src/datasets/table.py"
] | [
"import copy\nimport os\nimport tempfile\nfrom functools import wraps\nfrom itertools import groupby\nfrom typing import List, Optional, Tuple, TypeVar, Union\n\nimport numpy as np\nimport pyarrow as pa\n\nfrom . import config\nfrom .utils.logging import get_logger\n\n\nlogger = get_logger(__name__)\n\n\ndef inject... | [
[
"numpy.searchsorted"
]
] |
ngoby/cherry | [
"ec88bac03bf3ac3fae1010c5db8329db595dc5d6"
] | [
"cherry/td.py"
] | [
"#!/usr/bin/env python3\n\n\"\"\"\n**Description**\n\nUtilities to implement temporal difference algorithms.\n\"\"\"\n\nimport torch as th\n\nfrom cherry._utils import _reshape_helper\n\n\ndef discount(gamma, rewards, dones, bootstrap=0.0):\n \"\"\"\n **Description**\n\n Discounts rewards at an rate of gam... | [
[
"torch.zeros_like"
]
] |
ben1post/xarray-simlab-ode | [
"8d17af369374feeeb73efc9962e563834b8121e7"
] | [
"xso/core.py"
] | [
"import time as tm\nimport numpy as np\nimport math\n\nfrom .model import PhydraModel\nfrom .solvers import SolverABC, ODEINTSolver, StepwiseSolver#, GEKKOSolver\n\n_built_in_solvers = {'odeint': ODEINTSolver, 'gekko': 0, 'stepwise': StepwiseSolver}\n\n\nclass PhydraCore:\n \"\"\"\"\"\"\n\n def __init__(self,... | [
[
"numpy.log",
"numpy.sum",
"numpy.exp",
"numpy.prod",
"numpy.sqrt",
"numpy.maximum"
]
] |
aco8ogren/Tentin-Quarantino | [
"08b494f5deb2c33e3bb5981135c780b0a34d5557"
] | [
"Josh/Processing/nyt_us_counties_Import2.py"
] | [
"def us_counties_Data2Dict(RemoveEmptyFips=False,RemoveUnknownCounties=False):\n # Function to import nyt_us_counties.csv data into a dictionary\n import numpy as np \n import sys\n import pickle\n import os\n import git\n repo=git.Repo('.', search_parent_directories=True)\n cwd=repo.working... | [
[
"numpy.array",
"numpy.loadtxt",
"numpy.nonzero"
]
] |
nwod-edispu/Uni-Fold | [
"0ebfaf234807523067759d4c300694bb58cfb991"
] | [
"unifold/model/tf/proteins_dataset.py"
] | [
"# Copyright 2021 Beijing DP Technology Co., Ltd.\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 appl... | [
[
"tensorflow.compat.v1.reshape",
"tensorflow.compat.v1.cast",
"tensorflow.compat.v1.io.FixedLenSequenceFeature",
"tensorflow.compat.v1.size",
"tensorflow.compat.v1.shape",
"tensorflow.compat.v1.control_dependencies",
"tensorflow.compat.v1.io.parse_single_example",
"tensorflow.compat... |
Sm0ckingBird/xdeep | [
"c2f0323b0ec55d684ee24dbe35a6046fe0074663"
] | [
"tutorial/xlocal_perturbation/text - tutorial.py"
] | [
"import os\nimport numpy as np\nimport spacy\nfrom sklearn import model_selection\nfrom sklearn.linear_model import LogisticRegression\nfrom sklearn.pipeline import make_pipeline\nfrom sklearn.feature_extraction.text import CountVectorizer\nimport xdeep.xlocal.perturbation.xdeep_text as xdeep_text\n\n# Please downl... | [
[
"numpy.array",
"sklearn.pipeline.make_pipeline",
"sklearn.linear_model.LogisticRegression",
"sklearn.feature_extraction.text.CountVectorizer",
"sklearn.model_selection.train_test_split"
]
] |
tomstark99/epic-kitchens-100-frame-attribution | [
"14d9aa94cd4bd18ec38157e2d0f6bf3d9a517ddc"
] | [
"src/scripts/extract_verb_noun_links.py"
] | [
"import argparse\r\nimport pickle\r\nimport pandas as pd\r\n\r\nfrom datasets.gulp_dataset import GulpDataset\r\nfrom pathlib import Path\r\nfrom typing import Dict, List\r\n\r\nfrom tqdm import tqdm\r\n\r\nparser = argparse.ArgumentParser(\r\n description=\"Extract verb-noun links from a given dataset\",\r\n ... | [
[
"pandas.read_csv"
]
] |
Young-won/ornstein_auto_encoders | [
"7ebe15f79f56cb75f4948dc7cf6d4633ccec84ec"
] | [
"ornstein_auto_encoder/tensorboard_utils.py"
] | [
"import os\nimport numpy as np\nimport tensorflow as tf\nfrom tensorflow.contrib.tensorboard.plugins import projector\nimport keras.backend as k\nfrom keras.callbacks import TensorBoard\n\nfrom keras.engine.training_utils import is_sequence, iter_sequence_infinite, should_run_validation\n\n#########################... | [
[
"tensorflow.zeros",
"tensorflow.assign",
"tensorflow.batch_to_space_nd",
"tensorflow.summary.image",
"tensorflow.summary.merge",
"tensorflow.summary.histogram",
"tensorflow.transpose",
"tensorflow.reshape",
"tensorflow.contrib.tensorboard.plugins.projector.visualize_embeddings"... |
jeonggyukim/pyathena | [
"f3c983d5c0a3f36e28134a4a6d3eb80ac26c2a8e",
"f3c983d5c0a3f36e28134a4a6d3eb80ac26c2a8e"
] | [
"pyathena/plt_tools/cmap.py",
"pyathena/sf_cloud_rad/load_sim_sf_cloud_rad.py"
] | [
"import numpy as np\nimport matplotlib.pyplot as plt\nimport matplotlib as mpl\nfrom matplotlib.colors import LinearSegmentedColormap, ListedColormap\n\nclass Colormaps(object):\n\n def __init__(self):\n self.cm = dict(T=cmap_shift(mpl.cm.RdYlBu_r, midpoint=3./7.),\n )\n \n ... | [
[
"numpy.array",
"matplotlib.cm.get_cmap",
"matplotlib.pyplot.register_cmap",
"matplotlib.colors.LinearSegmentedColormap",
"numpy.linspace",
"matplotlib.colors.LinearSegmentedColormap.from_list"
],
[
"pandas.read_pickle",
"scipy.interpolate.interp1d",
"pandas.concat",
"sc... |
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