repo_name stringlengths 6 130 | hexsha list | file_path list | code list | apis list |
|---|---|---|---|---|
rmholdergeo/batchRCLC | [
"ebcdb37fc2e6f96a8f44428198409055dbcee238"
] | [
"batchRCLC_v2.py"
] | [
"# last edited by Robert Holder on 21 May 2021\r\n\r\n# ##### Background on the develompent of this code ######\r\n# The version of the RCLC algorithm used in this code is a modified version of Tom Chacko's 1996\r\n# original. The modifications have been made by Chris McFarlane (04-97), David Pattison (05-9... | [
[
"numpy.array"
]
] |
kmkurn/uxtspwsd | [
"ea4da18cec023d0dc487ee061861e6715edc2e85",
"ea4da18cec023d0dc487ee061861e6715edc2e85"
] | [
"run_pptx.py",
"analyze_chart_tagging.py"
] | [
"#!/usr/bin/env python\n\n# Copyright (c) 2021 Kemal Kurniawan\n\nfrom itertools import chain\nfrom pathlib import Path\nimport os\nimport pickle\n\nfrom einops import rearrange\nfrom gensim.models.keyedvectors import KeyedVectors\nfrom rnnr import Event, Runner\nfrom rnnr.attachments import EpochTimer, MeanReducer... | [
[
"torch.zeros",
"torch.load",
"torch.tensor",
"torch.no_grad",
"torch.cuda.is_available"
],
[
"torch.zeros_like",
"torch.cuda.is_available",
"torch.tensor"
]
] |
richouzo/cs6471-project | [
"499d00f113dad81f6dfe32f47fce09e2a2bfe16c"
] | [
"src/training/train_utils.py"
] | [
"import time\nimport numpy as np\n\nimport tqdm\nimport copy\n\nimport torch\nimport torch.nn as nn\n\nfrom sklearn.metrics import f1_score\n\nfrom src.utils.utils import SAVED_MODELS_PATH\n\ndef train_model(model, criterion, optimizer, dataloaders, history_training, \n scheduler=None, num_epochs=10,... | [
[
"torch.nn.Softmax",
"torch.nn.CrossEntropyLoss",
"torch.sigmoid",
"numpy.arange",
"torch.nn.BCELoss",
"torch.nn.BCEWithLogitsLoss",
"torch.set_grad_enabled",
"torch.where",
"sklearn.metrics.f1_score",
"torch.argmax"
]
] |
nadanai263/CellFreeSim | [
"c5f91ca8d56aecd5d6638f443bbfd329d14f6834"
] | [
"scripts/libraryplot.py"
] | [
"# libraryplot.py\n# Plots entire model library\n\n# Interactive, fast cythonized ODE solver which\n# accepts Antimony/SBML model files as inputs\n# N. Laohakunakorn, LBNC, EPFL\n# V1.0, 2019\n\nimport matplotlib\nmatplotlib.use('TkAgg')\nimport matplotlib.pyplot as plt\nimport tellurium as te # 2.1.5\nimport numpy... | [
[
"matplotlib.pyplot.plot",
"matplotlib.use",
"matplotlib.pyplot.savefig"
]
] |
gramhagen/intake | [
"de4cbb5df78881dc166b1f02743d22067f2bbd78"
] | [
"intake/source/tests/test_npy.py"
] | [
"#-----------------------------------------------------------------------------\n# Copyright (c) 2012 - 2018, Anaconda, Inc. and Intake contributors\n# All rights reserved.\n#\n# The full license is in the LICENSE file, distributed with this software.\n#--------------------------------------------------------------... | [
[
"numpy.stack",
"numpy.save",
"numpy.random.randint"
]
] |
tipt0p/periodic_behavior_bn_wd | [
"8d77bfc21cd011cd3d705042c2b51735ec2b8b7d"
] | [
"nb_utils.py"
] | [
"import numpy as np\nimport torch\nimport matplotlib.pyplot as plt\nimport os\nimport nets as models\n\n\ndef get_model_str(lr, wd, ep, add_str=None):\n wd_str = f\"{wd:.0e}\".replace('0', '') if wd > 0.0 else str(wd)\n add_str = ('-' + add_str) if add_str is not None else \"\"\n return f\"lr_{lr}-wd_{wd_s... | [
[
"matplotlib.pyplot.legend",
"numpy.ones_like",
"numpy.sqrt",
"matplotlib.pyplot.title",
"torch.load",
"matplotlib.pyplot.xscale",
"numpy.load",
"matplotlib.pyplot.yscale",
"matplotlib.pyplot.subplots",
"matplotlib.pyplot.loglog",
"matplotlib.pyplot.savefig",
"matplo... |
chikoungoun/OpenIntro | [
"12ce09cc169fdf0458e504b97b8db472ad84df4b"
] | [
"Chapter 3/Annexes/Percentile_compute.py"
] | [
"\"\"\" Code to compute the percentile from a Z-score using it's general equation\n\"\"\"\n\nimport numpy as np\nimport math\nfrom scipy import integrate\n\n\n\n\n#Z-score for testing\nz=1.25\n#The negative infinity\nninf = np.NINF\n\ndef fn(x):\n return (1/math.sqrt(2*math.pi)) * math.exp(-x**2/2)\n\n# return a... | [
[
"scipy.integrate.quad"
]
] |
mianasbat/scikit-surgeryfred | [
"b784e52006ee885d1a140979d021e495e6af6ad5"
] | [
"sksurgeryfred/algorithms/fit_contour.py"
] | [
"\"\"\"Fit a contour to an image\"\"\"\n\nfrom skimage.color import rgb2gray\nfrom skimage.filters import gaussian\nfrom skimage.segmentation import active_contour\n\nimport numpy as np\n\n\ndef find_outer_contour(image, alpha=0.015, beta=10.0):\n \"\"\"\n Fits an active contour to the outer most edge in the ... | [
[
"numpy.array",
"numpy.cos",
"numpy.linspace",
"numpy.sin"
]
] |
jamesrichter/keras | [
"d3512f7cfd0aba4ccf20f1d58729454a18718699"
] | [
"tests/keras/utils/data_utils_test.py"
] | [
"\"\"\"Tests for functions in data_utils.py.\n\"\"\"\nimport os\nimport time\nimport sys\nimport tarfile\nimport threading\nimport shutil\nimport zipfile\nfrom itertools import cycle\nimport multiprocessing as mp\nimport numpy as np\nimport pytest\nimport six\nfrom six.moves.urllib.parse import urljoin\nfrom six.mo... | [
[
"numpy.ceil",
"numpy.ones"
]
] |
pierfra-ro/stingray | [
"d255e3ced23e97d297be7d8d659ddf163b808064"
] | [
"stingray/tests/test_gti.py"
] | [
"\n\nimport numpy as np\nimport pytest\nimport os\n\nfrom stingray.gti import cross_gtis, append_gtis, load_gtis, get_btis, join_gtis\nfrom stingray.gti import check_separate, create_gti_mask, check_gtis\nfrom stingray.gti import create_gti_from_condition, gti_len, gti_border_bins\nfrom stingray.gti import time_int... | [
[
"numpy.allclose",
"numpy.asarray",
"numpy.arange",
"numpy.all",
"numpy.any",
"numpy.array"
]
] |
Feliconut/PurdueCS324-LSST | [
"79273ba0ef8ed9aab9e08c736c22631a8e250f6e"
] | [
"Supernova/analysis/simple_classification.py"
] | [
"\"\"\"\nIn this project, I try to find the best differentiator between SN and NON-SN.\n\nThen I turn this into a filter that produces high-quality stream of unclassified events.\n\n@author Xiaoyu Liu\n@date Apr 6 2021\n\"\"\"\n\n# %%\nfrom antares_client._api.models import Locus\nfrom matplotlib import pyplot as p... | [
[
"matplotlib.pyplot.legend",
"matplotlib.pyplot.title",
"matplotlib.pyplot.ylim",
"matplotlib.pyplot.xlim",
"numpy.asanyarray",
"numpy.diff",
"scipy.stats.linregress",
"matplotlib.pyplot.xlabel",
"matplotlib.pyplot.show",
"numpy.where",
"matplotlib.pyplot.ylabel"
]
] |
pcal93/lsh_index_vehicles_dataset | [
"0571a46e866e89b1e8c46e009f9c65e6ccd820e0"
] | [
"app/LSH.py"
] | [
"import os\r\nimport json\r\nimport numpy as np\r\nfrom random import randint\r\nfrom itertools import *\r\nfrom storage import storage\r\nclass LSHash(object):\r\n \"\"\" LSHash implments locality sensitive hashing using random projection for\r\n input vectors of dimension `input_dim`.\r\n Attributes:\r\n... | [
[
"numpy.dot",
"numpy.asarray",
"numpy.load",
"numpy.random.normal",
"numpy.savez_compressed",
"numpy.mean",
"numpy.count_nonzero",
"numpy.random.uniform",
"numpy.array",
"numpy.random.randint"
]
] |
alexcohn/tensorflow | [
"3e21fe5faedab3a8258d344c8ad1cec2612a8aa8",
"3e21fe5faedab3a8258d344c8ad1cec2612a8aa8"
] | [
"tensorflow/python/util/tf_export.py",
"tensorflow/python/ops/clustering_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.python.util.tf_decorator.unwrap",
"tensorflow.python.util.tf_inspect.getargspec"
],
[
"tensorflow.python.ops.array_ops.constant",
"tensorflow.python.ops.array_ops.shape",
"tensorflow.python.ops.control_flow_ops.while_loop",
"tensorflow.python.ops.state_ops.assign_sub",
... |
KiaKafaei1/Data_Science_Portfolio | [
"9bfa29632d664c6bad9589106e47a455041f0d2c"
] | [
"Food_recognition/bbox_predict.py"
] | [
"# -*- coding: utf-8 -*-\n\"\"\"bbox_predict.ipynb\n\nAutomatically generated by Colaboratory.\n\nOriginal file is located at\n https://colab.research.google.com/drive/1z2jPNx_Q3qr2NbUSAgbnWN0y93hfHc4y\n\"\"\"\n\nimport matplotlib\nimport numpy as np\nimport pandas as pd\nimport torch \nimport torchvision\nimpor... | [
[
"torch.nn.Softmax",
"numpy.maximum",
"numpy.minimum",
"numpy.max",
"numpy.argmax",
"torch.cuda.is_available",
"torch.cuda.get_device_name",
"torch.device",
"numpy.exp",
"numpy.zeros",
"numpy.where"
]
] |
zsweet/R-Net | [
"b1b35ff4799e46263923f25e373444e9867a6cf4"
] | [
"func.py"
] | [
"import tensorflow as tf\n\nINF = 1e30\n\n\nclass cudnn_gru:\n\n def __init__(self, num_layers, num_units, batch_size, input_size, keep_prob=1.0, is_train=None, scope=None):\n self.num_layers = num_layers\n self.grus = []\n self.inits = []\n self.dropout_mask = []\n for layer i... | [
[
"tensorflow.get_variable",
"tensorflow.nn.dynamic_rnn",
"tensorflow.concat",
"tensorflow.contrib.rnn.GRUCell",
"tensorflow.zeros",
"tensorflow.reduce_sum",
"tensorflow.cast",
"tensorflow.squeeze",
"tensorflow.nn.dropout",
"tensorflow.matmul",
"tensorflow.shape",
"te... |
combra-lab/pop-spiking-deep-rl | [
"cc1df56addbdee6779a73f73225e811834250305"
] | [
"loihi_realization/test_loihi.py"
] | [
"import torch\nimport numpy as np\nimport time\nimport gym\nimport pickle\nimport math\nimport sys\n\nsys.path.append(\"../../\")\nfrom popsan_drl.popsan_td3.replay_buffer_norm import ReplayBuffer\nfrom popsan_drl.popsan_td3.popsan import PopSpikeActor\nfrom loihi_realization.popsan_loihi import SpikingActorNet\nfr... | [
[
"torch.load",
"numpy.int_",
"numpy.exp",
"numpy.std",
"numpy.mean",
"torch.device",
"numpy.array",
"numpy.tanh",
"numpy.zeros"
]
] |
HamidMousavi-git/Crypto-Signal | [
"7be5122c4786a55677e87d4389e041248dfbb723"
] | [
"app/analyzers/indicators/candle_recognition.py"
] | [
"\nimport numpy\nimport pandas\nimport talib\n\nfrom analyzers.utils import IndicatorUtils\n\n\nclass Candle_recognition(IndicatorUtils):\n def analyze(self, historical_data, signal, notification='hot', candle_check=1, hot_thresh=None, cold_thresh=None):\n \"\"\"Performs an candle pattern analysis on the ... | [
[
"pandas.DataFrame"
]
] |
LulutasoAI/MachineLearningUtilities | [
"4840e472d649b97026fe4944bdce4c7e65b45dc5"
] | [
"MLutilchan.py"
] | [
"import glob\nimport os\nfrom PIL import Image\nimport numpy as np\nfrom matplotlib import pyplot as plt\nimport pickle\nfrom sklearn.utils import shuffle\nfrom sklearn.model_selection import train_test_split\nimport keras\nfrom keras.layers import Activation, Conv2D, Flatten, Dense, Dropout, Conv3D\nfrom keras.opt... | [
[
"numpy.asarray",
"sklearn.utils.shuffle",
"numpy.array",
"sklearn.model_selection.train_test_split"
]
] |
frongk/brewersdict | [
"2d8390a229fcd4b1d5bb2a1a0b7df77798f52ca3"
] | [
"text2entry.py"
] | [
"from nltk import word_tokenize, sent_tokenize\n\nfrom tqdm import tqdm\n\nimport pandas as pd\n\n\nwith open('brewers_trim.txt', 'rb') as fi:\n file_txt = fi.readlines()\n\ntext = ''.join(file_txt)\n\n# remove page headers\ntext_pages = text.split('\\r\\n\\r\\n\\r\\n')\n\nbody_groups = []\nword_tokenset =[]\nfo... | [
[
"pandas.Series"
]
] |
GMinozzi/boston_housing_experiment | [
"fcf1fe44065ecc3d54927bccc636bb6cf1d1e548"
] | [
"boston_housing_experiment/mlp.py"
] | [
"import silence_tensorflow\nimport matplotlib\nmatplotlib.use(\"Agg\")\nimport matplotlib.pyplot as plt\nimport extra_keras_metrics\nfrom extra_keras_utils import set_seed\nfrom keras.datasets import boston_housing\nfrom keras.models import Sequential, load_model\nfrom keras.layers import Dense, InputLayer, Dropout... | [
[
"matplotlib.use",
"matplotlib.pyplot.savefig",
"pandas.DataFrame"
]
] |
samoturk/websdf | [
"b7b3365fa3a17650ead62611c8b7e0cb77d1db00"
] | [
"websdf/calculations.py"
] | [
"from rdkit import Chem\nfrom rdkit.Chem import Descriptors\nfrom rdkit.Chem import PandasTools\nfrom rdkit.Chem import FilterCatalog\nimport pandas as pd\n\ntry:\n # Import extra, proprietary functions\n from websdf.extra import extra\nexcept:\n extra = None\n\nparams = FilterCatalog.FilterCatalogParams()... | [
[
"pandas.read_csv",
"pandas.DataFrame"
]
] |
pritamqu/ppg2ecg-cardiogan | [
"5e1390588039b2887f2281771f343d7733ed87b3"
] | [
"codes/preprocessing.py"
] | [
"import numpy as np\nfrom biosppy.signals import tools as tools\n\ndef filter_ecg(signal, sampling_rate):\n \n signal = np.array(signal)\n order = int(0.3 * sampling_rate)\n filtered, _, _ = tools.filter_signal(signal=signal,\n ftype='FIR',\n ... | [
[
"numpy.array"
]
] |
wq13552463699/TriFinger_Research | [
"6ddfab4531cb4ba05a0fbb41227a734295dce378",
"6ddfab4531cb4ba05a0fbb41227a734295dce378"
] | [
"rrc_example_package/benchmark_rrc/python/cic/motion_primitives.py",
"rrc_example_package/benchmark_rrc/python/cic/bayesian_opt/utils/run_local_episode_bo.py"
] | [
"import numpy as np\nimport copy\nfrom .math_tools import rpy2Mat\nimport time\n\nfrom itertools import permutations\n\n\n\nclass PrimitiveObject:\n def __init__(self):\n pass\n\n def step(self, robot_state, state, cube_state_filtered, goal, iteration, initial):\n pass\n\n\n def is_finished(s... | [
[
"numpy.abs",
"numpy.clip",
"numpy.asarray",
"numpy.deg2rad",
"numpy.zeros",
"numpy.sum"
],
[
"numpy.asarray"
]
] |
shivamsnaik/cocoapi | [
"471e509a6891f70de992e50f3d0b3ef2c119c2b8"
] | [
"PythonAPI/pycocotools/coco.py"
] | [
"__author__ = 'tylin'\n__version__ = '2.0'\n# Interface for accessing the Microsoft COCO dataset.\n\n# Microsoft COCO is a large image dataset designed for object detection,\n# segmentation, and caption generation. pycocotools is a Python API that\n# assists in loading, parsing and visualizing the annotations in CO... | [
[
"matplotlib.pyplot.gca",
"matplotlib.collections.PatchCollection",
"numpy.random.random",
"numpy.min",
"numpy.dstack",
"numpy.ones",
"matplotlib.pyplot.plot",
"numpy.all",
"numpy.max",
"numpy.array",
"matplotlib.patches.Polygon"
]
] |
XavierJuradoM/SIAMS | [
"c31b9f519004a0ddb979813ec5315df08d022882"
] | [
"storage/kmeans/algoritmo.py"
] | [
"\nimport pandas as pd\nimport numpy as np\nimport matplotlib.pyplot as plt\nfrom sklearn.cluster import KMeans\nimport seaborn as sns; sns.set()\nimport csv\nimport sys\nimport os\n\n\narch_inicial= sys.argv[1]\narch_final= sys.argv[2]\narch_final_centroide= sys.argv[4]\ncluster=sys.argv[3]\n\n#print ('C:/laragon/... | [
[
"pandas.read_csv",
"matplotlib.pyplot.savefig",
"matplotlib.pyplot.scatter",
"pandas.DataFrame"
]
] |
ChrisJFarr/GoodwillComputerVision | [
"c40bd1cd1070e04a490726b5fb0deaace31775f3"
] | [
"tests/test_size_classification_model.py"
] | [
"from src.models.size_classification_model import SizeClassificationModel, TARGET_SIZE, SIZE_MAP\nimport unittest\nimport os\nimport numpy as np\nfrom sklearn.svm import LinearSVC\nfrom sklearn.metrics import accuracy_score\nimport warnings\nwarnings.filterwarnings(\"ignore\")\n\n# Test Support Constants\nTEST_SIZE... | [
[
"numpy.random.shuffle",
"numpy.random.seed",
"sklearn.metrics.accuracy_score"
]
] |
lrgr/xsmf | [
"f7a144812a2446a09b08a6a4b3abf624205b28e0"
] | [
"src/xsmf.py"
] | [
"import argparse\nimport logging\n\nimport numpy as np\nimport pandas as pd\nimport tensorflow as tf\nfrom i_o import get_logger, log_dict, setup_logging\nfrom sklearn.metrics import r2_score\n\nclass XSMF(object):\n def __init__(self, X_tgt, X_src, \n sim_scores,\n X_val=None,\n ... | [
[
"tensorflow.is_nan",
"numpy.dot",
"tensorflow.get_variable",
"sklearn.metrics.r2_score",
"numpy.max",
"numpy.random.randn",
"tensorflow.train.AdamOptimizer",
"tensorflow.trace",
"tensorflow.boolean_mask",
"tensorflow.Variable",
"numpy.eye",
"tensorflow.subtract",
... |
ajesse11x/tensorflow | [
"655b2afc50a0ee07e80a7e28363e853d2fac97cc"
] | [
"tensorflow/contrib/tpu/python/tpu/keras_support.py"
] | [
"# Copyright 2018 The TensorFlow Authors. All Rights Reserved.\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n# http://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless requ... | [
[
"tensorflow.contrib.cluster_resolver.python.training.tpu_cluster_resolver.TPUClusterResolver",
"tensorflow.contrib.tpu.python.ops.tpu_ops.infeed_dequeue_tuple",
"numpy.concatenate",
"tensorflow.python.keras.backend.dtype",
"tensorflow.python.ops.array_ops.placeholder",
"tensorflow.python.o... |
AlexMontgomerie/finn | [
"af783db8dc2a1d2e95bd569d39464b935520b6d2",
"ec5f67b333ad4db4acf6191c3b5ab5e9067347aa"
] | [
"tests/fpgadataflow/test_layer_streaming_maxpool_batch.py",
"src/finn/transformation/fpgadataflow/insert_fifo.py"
] | [
"# Copyright (c) 2020, Xilinx\n# 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 are met:\n#\n# * Redistributions of source code must retain the above copyright notice, this\n# list of conditions an... | [
[
"numpy.isclose"
],
[
"numpy.prod"
]
] |
veot/pyifcb | [
"7cf591a9c51edd19a0a8aa416d3f4774c6d1196a"
] | [
"ifcb/viz/utils.py"
] | [
"import numpy as np\nfrom skimage.transform import rescale, resize\n\nSQUARE_DEFAULT_SIZE = 399\n\ndef square(img, size=SQUARE_DEFAULT_SIZE):\n scaled = resize(img, (size, size), mode='reflect', preserve_range=True).astype(np.uint8)\n return scaled\n\ndef square_letterboxed(img, size=SQUARE_DEFAULT_SIZE, fill... | [
[
"numpy.median",
"numpy.zeros",
"numpy.mean"
]
] |
vaynelau/ZS3-voc12 | [
"106feb947d79e889032e8e9181a7353a4d22b3a3"
] | [
"zs3/train_pascal_GMMN.py"
] | [
"import argparse\nimport os\n\nimport numpy as np\nimport torch\nfrom torch import nn\nfrom tqdm import tqdm\nimport yaml\n\nfrom zs3.dataloaders import make_data_loader, get_split, get_dataset\nfrom zs3.modeling.deeplab import DeepLab\nfrom zs3.modeling.gmmn import GMMNnetwork\nfrom zs3.modeling.sync_batchnorm.rep... | [
[
"torch.ones",
"torch.randint",
"torch.load",
"torch.zeros",
"numpy.arange",
"torch.manual_seed",
"torch.utils.data.DataLoader",
"numpy.delete",
"numpy.argmax",
"torch.no_grad",
"torch.rand",
"torch.cuda.is_available",
"torch.optim.SGD",
"torch.unique",
"... |
shl418/world-models-latest | [
"f5659c16ef54ababdff6dc700af92a2a59fdafdb"
] | [
"vaegandemo.py"
] | [
"import numpy as np\nimport argparse\nimport config\nimport os\nimport datetime\nimport sys\nimport tensorflow.keras as keras\nfrom tensorflow.keras.layers import Input, Conv2D, Flatten, Dense, Conv2DTranspose, Lambda, Reshape, Layer\nfrom tensorflow.keras.models import Model\nfrom tensorflow.keras.optimizers impor... | [
[
"tensorflow.keras.layers.Conv2DTranspose",
"tensorflow.keras.layers.LeakyReLU",
"tensorflow.keras.layers.Lambda",
"tensorflow.keras.layers.Conv2D",
"tensorflow.keras.backend.exp",
"tensorflow.keras.backend.square",
"numpy.load",
"numpy.zeros",
"tensorflow.keras.layers.Flatten",... |
jackbeagley/geometry_tool | [
"7a91d5696503d3eeed4a70eee6a01d2869a78a26"
] | [
"geometry_tool.py"
] | [
"############################################################################\n#\n# AUTHOR: Jack Beagley, Geophysics Lab, Otago University August 2021\n#\n# PURPOSE: Process the navigation files to determine the geometry of\n# a marine seismic survey. Can optionally take into account\n# ... | [
[
"matplotlib.pyplot.legend",
"numpy.radians",
"pandas.Series",
"numpy.sqrt",
"matplotlib.pyplot.plot",
"numpy.zeros_like",
"numpy.argmin",
"pandas.read_csv",
"numpy.empty_like",
"numpy.arange",
"numpy.sin",
"matplotlib.pyplot.axis",
"matplotlib.pyplot.figure",
... |
david-macleod/models | [
"31ae57eb8555e51493a4721f6efbea68d98a3d69"
] | [
"official/recommendation/data_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... | [
[
"tensorflow.gfile.ListDirectory",
"tensorflow.Graph",
"numpy.random.seed",
"numpy.random.choice",
"tensorflow.gfile.Open",
"numpy.arange",
"tensorflow.test.main",
"numpy.random.shuffle",
"pandas.DataFrame",
"numpy.concatenate",
"tensorflow.gfile.MakeDirs",
"tensorfl... |
matthewearl/ray | [
"e29f2ef788dc399832240ae17fb9464515374eb7"
] | [
"rllib/agents/sac/sac_policy.py"
] | [
"from gym.spaces import Box\nimport numpy as np\nimport logging\n\nimport ray\nimport ray.experimental.tf_utils\nfrom ray.rllib.agents.sac.sac_model import SACModel\nfrom ray.rllib.agents.ddpg.noop_model import NoopModel\nfrom ray.rllib.agents.dqn.dqn_policy import postprocess_nstep_and_prio, \\\n PRIO_WEIGHTS\n... | [
[
"numpy.product",
"numpy.prod"
]
] |
manurare/360monodepth | [
"43347063f1fa521ea3e0866ff85bbcb734b64393"
] | [
"code/python/src/utility/serialization.py"
] | [
"\nfrom PIL import Image\nimport numpy as np\nimport matplotlib.pyplot as plt\n\nimport metrics\nimport json\nimport os\nimport pickle\nfrom logger import Logger\n\nlog = Logger(__name__)\nlog.logger.propagate = False\n\n\nclass NumpyArrayEncoder(json.JSONEncoder):\n \"\"\"Assistant class for serialize the numpy... | [
[
"numpy.asarray",
"numpy.isnan",
"numpy.isinf"
]
] |
IsaiahPressman/Kaggle_Santa_2020 | [
"ff5c6aa78dbe234cef338f4c721cc30d7dbc3df8",
"ff5c6aa78dbe234cef338f4c721cc30d7dbc3df8"
] | [
"handcrafted_agents/deprecated/discrete_thompson_sampling_with_action_history.py",
"run_experiment_a3c.py"
] | [
"import numpy as np\nfrom scipy.stats import beta\n\npost_a = None\npost_b = None\nbandit = None\ntotal_reward = 0\nn_selections = None\n\n\ndef agent(observation, configuration):\n global total_reward, bandit, post_a, post_b, n_selections\n \n n_bandits = configuration.banditCount\n decay_rate = config... | [
[
"numpy.arange",
"numpy.argmax",
"numpy.zeros",
"numpy.ones"
],
[
"torch.device",
"torch.nn.Identity",
"numpy.unique"
]
] |
gpaw789/ATO_Analysis | [
"d3d3b9bd73953491d2cb3b2c9083eabc18c2190c"
] | [
"ATO_Analysis/ATO_AG_6.py"
] | [
"# TOPIC: Australian Tax Office - Tax Return Sample for Year 2013-14\n# CATEGORY: Age\n# TITLE: Australian Tax Return Income Breakdown by Age Group\n# AUTHOR: George Paw\n# DATE: November 2017\n\nimport sys\nimport os\nimport pandas as pd\nimport plotly.graph_objs as go\nimport plotly\nimport numpy as np\n\n\n#cust... | [
[
"pandas.concat",
"pandas.read_csv",
"pandas.DataFrame"
]
] |
huyutao3550346/PaddleHub | [
"eeb2c9235869161a2451711ad37aa559b5ee2762"
] | [
"hub_module/modules/image/text_recognition/chinese_ocr_db_crnn_server/character.py"
] | [
"# Copyright (c) 2020 PaddlePaddle 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 re... | [
[
"numpy.array",
"numpy.where"
]
] |
shanicky4ever/one-pixel-attack-feature | [
"0a397d61bd6dfcb36c5bc67488665a2e37597fc6",
"29619e0d68bbf71ae2e21bee742ff9eec08d943e"
] | [
"helper.py",
"differential_evolution.py"
] | [
"# CIFAR - 10\n\nimport pickle\nimport numpy as np\nfrom keras.datasets import cifar10\nfrom keras.utils import np_utils\nfrom matplotlib import pyplot as plt\nimport pandas as pd\nimport requests\nfrom tqdm import tqdm\n\ndef perturb_image(xs, img):\n # If this function is passed just one perturbation vector,\n... | [
[
"numpy.array",
"matplotlib.pyplot.imshow",
"numpy.tile",
"matplotlib.pyplot.subplots",
"pandas.DataFrame",
"numpy.max",
"numpy.argmax",
"matplotlib.pyplot.grid",
"matplotlib.pyplot.xlabel",
"matplotlib.pyplot.yticks",
"matplotlib.pyplot.show",
"matplotlib.pyplot.xti... |
KorfLab/imeter | [
"1e93d8c032caf02a6d839908a53c458a154f6c93"
] | [
"ime_drafting/IMEter_v1_Nivedita/r2_analysis.py"
] | [
"import matplotlib.pyplot as plt\nimport numpy as np\nfrom sklearn import datasets, linear_model\nfrom sklearn.metrics import mean_squared_error, r2_score\nfrom sklearn.linear_model import LinearRegression\nimport argparse\n\nparser = argparse.ArgumentParser(description='R2 values')\nparser.add_argument('introns', ... | [
[
"numpy.array",
"sklearn.linear_model.LinearRegression"
]
] |
matescharnitzky/joelnet | [
"d0a003d065e9a62a9ec051049f016a8ada94c3e8"
] | [
"joelnet/layers.py"
] | [
"\"\"\"\nOur neural nets will be made up of layers.\nEach layer needs to pass its inputs forward\nand propagate gradients backward. For example:\n\ninputs -> Linear -> Tanh -> Linear -> output\n\"\"\"\nimport numpy as np\nfrom typing import Dict, Callable\nfrom joelnet.tensor import Tensor\n\n\nclass Layer:\n de... | [
[
"numpy.tanh",
"numpy.random.randn",
"numpy.sum"
]
] |
r0cketr1kky/DeepPixel | [
"334eb551e32087cd3471111b86bf165a76868cb0"
] | [
"deeppixel/cam/gradcam.py"
] | [
"import torch.nn.functional as F\nimport torch\n\nfrom .basecam import BaseCAM\nfrom .utils import *\n\n\nclass GradCAM(BaseCAM):\n \"\"\"\n GradCAM, inherit from BaseCAM\n \"\"\"\n\n def __init__(self, model_dict):\n super().__init__(model_dict)\n\n def forward(self, input_, class_idx=Non... | [
[
"torch.nn.functional.relu",
"torch.nn.functional.interpolate"
]
] |
dede1751/pytactoe | [
"81ecf233b6ec3730a57ba67785e8ab0fe11e5f6a"
] | [
"pytactoe.py"
] | [
"import numpy as np\nimport json\n\nimport colorama\nfrom colorama import Fore\nfrom termcolor import cprint\nfrom pyfiglet import figlet_format\n\nimport network as nt\n\n\ndef custom_input(message, input_type, board=[], net=False, num_list=[]):\n \"\"\"Custom query function for better error handling and cleane... | [
[
"numpy.zeros"
]
] |
abyrne55/osvr-review | [
"777884dcbcb2283247ffe256da51254aa3d6896b"
] | [
"old/admm.py"
] | [
"# Source: http://codereview.stackexchange.com/questions/108263/alternating-direction-method-of-multipliers\nimport numpy as np\nimport matplotlib.pyplot as plt\nfrom math import sqrt, log\n\ndef ADMM(A, y):\n \"\"\"Alternating Direction Method of Multipliers\n\n This is a python implementation of the Alterna... | [
[
"matplotlib.pyplot.legend",
"numpy.absolute",
"numpy.linalg.inv",
"numpy.linalg.eig",
"matplotlib.pyplot.plot",
"numpy.random.randn",
"numpy.identity",
"matplotlib.pyplot.show",
"numpy.zeros",
"numpy.random.randint"
]
] |
gemlongman/motion_preprocessing_tool | [
"0d46fc41ff951e7cc4788d1d9355b0346a9df306"
] | [
"motion_analysis/motion_synthesis/morphable_graph_state_machine.py"
] | [
"#!/usr/bin/env python\n#\n# Copyright 2019 DFKI GmbH.\n#\n# Permission is hereby granted, free of charge, to any person obtaining a\n# copy of this software and associated documentation files (the\n# \"Software\"), to deal in the Software without restriction, including\n# without limitation the rights to use, copy... | [
[
"numpy.dot",
"numpy.radians",
"numpy.linalg.inv",
"numpy.isnan",
"numpy.eye",
"numpy.cos",
"numpy.linalg.norm",
"numpy.sin",
"numpy.array",
"numpy.zeros"
]
] |
ahmedopolis/keras | [
"4c87dc9685eea2ed20111f9604b10d627b17f032"
] | [
"keras/utils/image_utils_test.py"
] | [
"# Copyright 2022 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.v2.data.Dataset.from_tensor_slices",
"numpy.random.random",
"tensorflow.compat.v2.test.main",
"numpy.any",
"numpy.random.rand",
"numpy.array",
"numpy.zeros",
"numpy.sum",
"numpy.random.randint"
]
] |
ThomasBrazier/PiSlice | [
"3d1987c05517686ce90d4876b5a0c4d0f8c90665"
] | [
"PiSlice/sandbox.py"
] | [
"\n# Debug\nimport time\nimport PiSlice.input as input\n#fasta_file = \"PiSlice/data/Oryza_sativa_GCA_001433935.1/GCA_001433935.1_IRGSP-1.0_genomic.fna.gz\"\n#fasta_file = \"PiSlice/data/Arabidopsis_thaliana_GCA_000001735.2.fna.gz\"\nfasta_file = \"PiSlice/data/Brassica_rapa_Brapa1.5/Brassica_rapa_Brapa1.5.fna.gz\"... | [
[
"pandas.DataFrame"
]
] |
mitchchristow/deepmind-research | [
"6f8ae40b2626b30f5f80dfc92f5676689eff5599",
"6f8ae40b2626b30f5f80dfc92f5676689eff5599",
"6f8ae40b2626b30f5f80dfc92f5676689eff5599"
] | [
"side_effects_penalties/agent_with_penalties.py",
"learning_to_simulate/render_rollout.py",
"tvt/pycolab/common.py"
] | [
"# Copyright 2019 DeepMind Technologies Limited.\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 applicabl... | [
[
"numpy.maximum"
],
[
"numpy.concatenate",
"numpy.arange",
"matplotlib.pyplot.show",
"matplotlib.pyplot.subplots"
],
[
"numpy.ones_like",
"numpy.random.choice",
"numpy.arange",
"numpy.argwhere",
"numpy.random.permutation",
"numpy.random.uniform",
"numpy.rando... |
parthjindal/CS60050 | [
"7ac2270ec8076f8334f7a29c7ec547c6cb6721ca"
] | [
"Assignment1/main.py"
] | [
"from typing import List, Dict, Tuple\nfrom util import CarDataset, split_dataset, shuffle_dataset, \\\n get_metrics, find_ci_interval, seed_everything\nfrom decision_tree import DecisionTree\nimport numpy as np\nimport matplotlib.pyplot as plt\nimport argparse\nfrom tabulate import tabulate\n\n\ndef train(\n ... | [
[
"numpy.arange",
"matplotlib.pyplot.plot",
"matplotlib.pyplot.errorbar",
"matplotlib.pyplot.xlabel",
"matplotlib.pyplot.show",
"matplotlib.pyplot.ylabel"
]
] |
a07458666/SwinSR | [
"b08b2c4b46f6dacdcbdfe389b9b8254d85965283"
] | [
"models/loss.py"
] | [
"import torch\nimport torch.nn as nn\nimport torchvision\nfrom torch.nn import functional as F\nfrom torch import autograd as autograd\n\n\n\"\"\"\nSequential(\n (0): Conv2d(3, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))\n (1): ReLU(inplace)\n (2*): Conv2d(64, 64, kernel_size=(3, 3), strid... | [
[
"torch.randn_like",
"torch.mean",
"torch.nn.Sequential",
"torch.nn.MSELoss",
"torch.ones_like",
"torch.empty_like",
"torch.Tensor",
"torch.sqrt",
"torch.nn.functional.softplus",
"torch.nn.BCEWithLogitsLoss",
"torch.pow",
"torch.rand",
"torch.nn.L1Loss",
"tor... |
fschur/SQL-Dataset-for-Pytorch | [
"215efe124fb32204a49ef34fcd9b755357d196c9"
] | [
"dataset_sql.py"
] | [
"import torch\nfrom torch.utils.data.dataset import Dataset\nimport sqlite3\nimport random\n\n\"\"\"\nTwo Pytorch Dataset to iterate over a SQLlite database. Instead of loading the observations one by one as done by\nSQLDataset, SQLDatasetPreload loads full chunks of data at once. This speeds up the iteration proce... | [
[
"torch.Tensor"
]
] |
OtaYuji/openslider-tfpy | [
"19891babb1d2ad85e0a3866939f86e0fdbcce3d8"
] | [
"examples/read_region.py"
] | [
"# Copyright\n# 2019 Department of Dermatology, School of Medicine, Tohoku University\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/l... | [
[
"tensorflow.train.start_queue_runners",
"tensorflow.Graph",
"tensorflow.train.Coordinator",
"tensorflow.Session"
]
] |
jayyoung0802/DI-engine | [
"efbb35ddaf184d1009291e6842fbbae09f193492",
"efbb35ddaf184d1009291e6842fbbae09f193492"
] | [
"ding/policy/sql.py",
"ding/rl_utils/adder.py"
] | [
"from typing import List, Dict, Any, Tuple, Union, Optional\nfrom collections import namedtuple, deque\nimport copy\nimport torch\nfrom torch.distributions import Categorical\nimport logging\nfrom easydict import EasyDict\nfrom ding.torch_utils import Adam, to_device\nfrom ding.utils.data import default_collate, de... | [
[
"torch.no_grad"
],
[
"torch.stack",
"torch.zeros_like",
"torch.zeros"
]
] |
labstructbioinf/localpdb | [
"870feca6256487c27a64e8bd5121f47d9618469c"
] | [
"localpdb/utils/prot.py"
] | [
"import re\nimport gzip\nimport os\nimport pandas as pd\nimport numpy as np\n\nnuc_re = re.compile(r'[^ATGCUXNIF.]')\nnonstd_re = re.compile(r'[^X.]')\n\n\ndef parse_pdb_data(entries_fn, entries_type_fn, res_fn, seqres_fn):\n \"\"\"\n Builds dataframe with the parsed raw PDB data\n @param entries_fn: filen... | [
[
"pandas.merge",
"pandas.to_datetime",
"pandas.DataFrame.from_dict"
]
] |
psclklnk/spdl | [
"ced8c189f378a41e209048ebf886f103755f21f4"
] | [
"deep_sprl/teachers/abstract_teacher.py"
] | [
"import gym\nimport numpy as np\nfrom gym import spaces\nfrom abc import ABC, abstractmethod\nfrom deep_sprl.teachers.util import Buffer\nfrom stable_baselines.common.vec_env import VecEnv\n\n\nclass AbstractTeacher(ABC):\n\n @abstractmethod\n def sample(self):\n pass\n\n\nclass BaseWrapper(gym.Env):\n... | [
[
"numpy.concatenate",
"numpy.ones_like",
"numpy.mean"
]
] |
jupadhya1/Odometry_Signal_Anomaly | [
"37a1e549b640fcec7b21ba06e55f8744dbe4614b"
] | [
"client/mlf.py"
] | [
"import json\r\nimport logging\r\nimport math\r\nfrom collections import defaultdict\r\nfrom typing import Dict, List, Union\r\n\r\nimport mlflow\r\nimport pandas as pd\r\nfrom sklearn.metrics import confusion_matrix\r\n\r\n\r\nclass MlflowClient():\r\n \"\"\"A mlflow client to read artifacts from minio bucket\r... | [
[
"pandas.read_csv",
"sklearn.metrics.confusion_matrix"
]
] |
andyfaff/avant | [
"b5a72db1d82fd9d722557dded08fb76dac0f7dad"
] | [
"parameter/roughness.py"
] | [
"from .util import findGauss, findUniform\nimport matplotlib.pyplot as plt\nimport numpy as np\n\n\ndef Gauss(name):\n \"\"\"\"\n Calls the findGauss function from util.py to return the Gauss prior for the given molecule.\n Input: name of molecule\n Output: Gauss prior object containing pdf, lo... | [
[
"matplotlib.pyplot.title",
"numpy.linspace",
"matplotlib.pyplot.plot",
"numpy.zeros_like",
"matplotlib.pyplot.xlabel",
"matplotlib.pyplot.show",
"matplotlib.pyplot.ylabel"
]
] |
alphadl/THUMT | [
"350082579044173aab7df8d17744c6eeea7d40cc"
] | [
"thumt/scripts/visualize.py"
] | [
"import os\nimport sys\nimport matplotlib\nimport matplotlib.pyplot as plt\nimport numpy\nimport re\nfrom matplotlib import font_manager\n\n\ndef parse_numpy(string):\n string = string.replace('[', ' ').replace(']', ' ').replace(',', ' ')\n string = re.sub(' +', ' ', string)\n result = numpy.fromstring(str... | [
[
"numpy.abs",
"numpy.reshape",
"matplotlib.font_manager.FontProperties",
"matplotlib.pyplot.colorbar",
"numpy.fromstring",
"matplotlib.pyplot.matshow",
"matplotlib.pyplot.show"
]
] |
aryamansriram/Hello-world | [
"ce838f0e9903a1d75002ad325356c15516983cfb"
] | [
"Upvote_prediction.py"
] | [
"\n# coding: utf-8\n\n\n#IMPORT LIBRARIES\nimport numpy as np\nimport pandas as pd\nimport matplotlib.pyplot as plt\nfrom keras.utils import to_categorical\n\n#READ DATASETS\ndf = pd.read_csv('train_NIR5Yl1.csv')\ndf_test=pd.read_csv('test_8i3B3FC.csv')\n\n#SHOW DATASET\ndf.head()\n\n\n\ndf.describe()\n\n\n\n#CHECK... | [
[
"numpy.array",
"pandas.merge",
"pandas.read_csv",
"sklearn.metrics.r2_score",
"matplotlib.pyplot.scatter",
"sklearn.model_selection.train_test_split",
"pandas.DataFrame",
"sklearn.linear_model.Lasso",
"sklearn.preprocessing.LabelEncoder",
"sklearn.ensemble.GradientBoostingR... |
ladike/912_project | [
"5178c1c93ac6ca30ffc72dd689f5c6932704b4ab"
] | [
"6 复试/2 笔试/9 机器学习/机器学习概论/hw/2017实验/exp2/实验二/2014011328/exp2.py"
] | [
"\nimport random\nimport math\nimport numpy\nfrom sklearn import tree, svm, preprocessing\nfrom sklearn.model_selection import train_test_split\nfrom sklearn.naive_bayes import GaussianNB, MultinomialNB, BernoulliNB\n\ndef main(task):\n\tif task == 1 :\n\t\tprint(\"Bagging + SVM\")\n\telif task == 2 :\n\t\tprint(\"... | [
[
"sklearn.naive_bayes.GaussianNB",
"sklearn.model_selection.train_test_split",
"sklearn.preprocessing.normalize",
"sklearn.tree.DecisionTreeClassifier",
"sklearn.svm.LinearSVC",
"numpy.array"
]
] |
progressivis/altair_examples | [
"9a453ecebdf0bd4776696d4233bee2a8f2eb3606"
] | [
"altair_examples/layered_histogram.py"
] | [
"\"\"\"\nLayered Histogram\n=================\nThis example shows how to use opacity to make a layered histogram in Altair.\n\"\"\"\n# category: histograms\nimport altair as alt\nimport numpy as np\n\nnp.random.seed(42)\n\n# Generating Data\nsource = alt.pd.DataFrame(\n {\n \"Trial A\": np.random.normal(0... | [
[
"numpy.random.normal",
"numpy.random.seed"
]
] |
rasterio/rasterio | [
"558bddf52eb6bfb921fbe1a12bd0793119c2e0a1",
"706f7987b867dc5f37585d794002b9a5832a5f21"
] | [
"tests/test_warpedvrt.py",
"rasterio/__init__.py"
] | [
"\"\"\"Tests for :py:class:`rasterio.warp.WarpedVRT`.\"\"\"\n\nfrom __future__ import division\nimport logging\nimport shutil\n\nimport affine\nimport boto3\nimport numpy\nimport pytest\n\nimport rasterio\nfrom rasterio.control import GroundControlPoint\nfrom rasterio.crs import CRS\nfrom rasterio.enums import Resa... | [
[
"numpy.moveaxis"
],
[
"numpy.pad"
]
] |
zouchuhang/LayoutNetv2 | [
"af425d8fc0d40954fc5aae9fd0a1c8eef9ada796"
] | [
"utils_eval.py"
] | [
"import numpy as np\nfrom scipy.spatial import HalfspaceIntersection, ConvexHull\n\nfrom pano import pano_connect_points\n\n\ndef np_coorx2u(coorx, coorW=1024):\n return ((coorx + 0.5) / coorW - 0.5) * 2 * np.pi\n\n\ndef np_coory2v(coory, coorH=512):\n return -((coory + 0.5) / coorH - 0.5) * np.pi\n\n\ndef np... | [
[
"numpy.hstack",
"scipy.spatial.ConvexHull",
"numpy.arange",
"numpy.cumsum",
"numpy.cos",
"numpy.sin",
"numpy.tan",
"numpy.concatenate",
"numpy.round",
"numpy.flip",
"numpy.cross",
"numpy.array",
"numpy.zeros",
"numpy.roll"
]
] |
leifdenby/twin-otter | [
"05d66304d03b27cbd0ac8d4add83d3b67518daa3",
"05d66304d03b27cbd0ac8d4add83d3b67518daa3"
] | [
"twinotter/plots/flight_track_frames.py",
"twinotter/quicklook.py"
] | [
"\"\"\"\n::\n\n Usage:\n flight_track_frames.py <flight_data_path>\n [<lon_min> <lon_max> <lat_min> <lat_max> <resolution>]\n [--goes_path=<path>]\n [--output_path=<path>]\n flight_track_frames.py (-h | --help)\n\n Arguments:\n <flight_data_path> Input ... | [
[
"numpy.arange",
"matplotlib.pyplot.savefig",
"matplotlib.pyplot.axes",
"matplotlib.pyplot.close",
"numpy.meshgrid",
"matplotlib.pyplot.figure"
],
[
"matplotlib.pyplot.ylim",
"matplotlib.pyplot.subplots",
"matplotlib.pyplot.plot",
"matplotlib.pyplot.xlim",
"matplotli... |
slyrx/tfx | [
"cdfe96fdbb91959511da56aab0b3f8bb7e70a0f0"
] | [
"tfx/extensions/google_cloud_ai_platform/pusher/executor_test.py"
] | [
"# Lint as: python2, python3\n# Copyright 2019 Google LLC. 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\... | [
[
"tensorflow.io.gfile.makedirs",
"tensorflow.test.main"
]
] |
SiyuanMa0316/2018_cei_intern-1 | [
"c44e6eb42d4cc17d3585eab5fcb2f0f0e77b4a01"
] | [
"information_theory_related/ShiyuLi's_Correlation/CNN_SaveActivation.py"
] | [
"import tensorflow as tf\nimport keras\nfrom CNN_Model import LeNet\n\nimport numpy as np\n\nimport utils\nimport loggingreporter\n\nimport keras.backend.tensorflow_backend as KTF\n\nconfig = tf.ConfigProto()\nconfig.gpu_options.allow_growth=True #不全部占满显存, 按需分配\nsession = tf.Session(config=config)\n\n# 设置session\... | [
[
"tensorflow.ConfigProto",
"tensorflow.train.AdamOptimizer",
"tensorflow.Session"
]
] |
secantsquared/pyqtgraph | [
"3ef7f5b91639543e43bcd66a84290fb9bc18fc5c",
"3ef7f5b91639543e43bcd66a84290fb9bc18fc5c"
] | [
"pyqtgraph/examples/TableWidget.py",
"pyqtgraph/opengl/items/GLBarGraphItem.py"
] | [
"# -*- coding: utf-8 -*-\n\"\"\"\nSimple demonstration of TableWidget, which is an extension of QTableWidget\nthat automatically displays a variety of tabluar data formats.\n\"\"\"\n\nimport pyqtgraph as pg\nfrom pyqtgraph.Qt import QtCore, QtGui\nimport numpy as np\n\napp = pg.mkQApp(\"Table Widget Example\")\n\nw... | [
[
"numpy.array"
],
[
"numpy.arange",
"numpy.array",
"numpy.prod"
]
] |
tperl/Low-Resource-Sequence-Tagging-using-Sentence-Reconstruction | [
"81cdd2460198f12a2013521fcab7725b26317cd4"
] | [
"utils/f1_test.py"
] | [
"\n\n\"\"\"function expects to receive a list of words and a list of tags\n it then extract the entities and tags per entity for later to be use when comparing\n when comparing f1 scores\"\"\"\nfrom builtins import enumerate\nfrom seqeval.metrics import accuracy_score, f1_score, classification_report\nimport numpy ... | [
[
"numpy.zeros"
]
] |
matt-hayden/MarekKowalski-FaceSwap | [
"edb6afc59d670c26abef59ba3d7619b64a1488d1"
] | [
"FaceSwap/ImageProcessing.py"
] | [
"import logging\nlogger = logging.getLogger('FaceSwap.ImageProcessing')\ndebug, info = logger.debug, logger.info\n\nimport numpy as np\nimport cv2\n\n\n#tutaj src to obraz, z ktorego piksele beda wklejane do obrazu dst\n#feather amount to procent, sluzacy do sterowania wielkoscia obszaru, ktory bedzie poddany wagow... | [
[
"numpy.hstack",
"numpy.clip",
"numpy.min",
"numpy.max",
"numpy.copy",
"numpy.mean",
"numpy.where",
"numpy.zeros"
]
] |
mirob9363/earthpy | [
"6e43724fac10e980489d182bc028fc94021f7d2f",
"6e43724fac10e980489d182bc028fc94021f7d2f"
] | [
"earthpy/tests/test_clip.py",
"earthpy/tests/test_stack.py"
] | [
"\"\"\"Tests for the clip module.\"\"\"\n\nimport pytest\nimport numpy as np\nfrom shapely.geometry import Polygon, Point, LineString\nimport shapely\nimport geopandas as gpd\nimport earthpy.clip as cl\n\n\ndef make_locs_gdf():\n \"\"\" Create a dummy point GeoDataFrame. \"\"\"\n pts = np.array([[2, 2], [3, 4... | [
[
"numpy.array"
],
[
"numpy.sum"
]
] |
QCHighing/pyImageProcessing | [
"7b56aaf385acd6dec8fd80ae0a69bdc317255551"
] | [
"01 CannyEdgeDetection/myCanny.py"
] | [
"import numpy as np\nimport cv2 as cv\n\n\ndef dispImg(imgs):\n for name, img in imgs.items():\n cv.imshow(name, img)\n cv.waitKey(0)\n cv.destroyAllWindows()\n\n\ndef calcuGradient(img, imdx, imdy, immod, imdir):\n row, col = img.shape\n for r in range(1, row - 1): # 去掉最外围的1像素，从1索引到row-1, c... | [
[
"numpy.sqrt",
"numpy.arctan",
"numpy.uint8",
"numpy.max",
"numpy.zeros"
]
] |
jorahn/clip-guided-diffusion | [
"a631a06b51ac5c6636136fab27833c68862eaa24"
] | [
"cgd/clip_util.py"
] | [
"from functools import lru_cache\n\nimport clip\nimport torch as th\nimport torch.nn.functional as tf\nimport torchvision.transforms as tvt\nimport torchvision.transforms.functional as tvf\nfrom data.imagenet1000_clsidx_to_labels import IMAGENET_CLASSES\nfrom PIL import Image\n\nfrom cgd import script_util\nfrom cg... | [
[
"torch.nn.functional.normalize",
"torch.no_grad"
]
] |
LoannData/Q26_AlphaTrading | [
"b8e6983e59f942352150f76541d880143cca4478"
] | [
"test/trading/strategyExample.py"
] | [
"#!/usr/bin/env python3\n# -*- coding: utf-8 -*-\n\"\"\"\n#############################################################\nSTRATEGY FILE\n#############################################################\nThis file contains the strategy that will be read and executed \nby the backtester.\n\nPlease, read carefully all the... | [
[
"matplotlib.pyplot.legend",
"matplotlib.pyplot.figure",
"pandas.DataFrame",
"matplotlib.pyplot.close",
"matplotlib.pyplot.xlabel",
"matplotlib.pyplot.xticks",
"matplotlib.pyplot.show",
"matplotlib.pyplot.ylabel"
]
] |
SunshineJunFu/mask-faster-rcnn | [
"109d626e9526f56f464dacd2b68dae6ff6be141c"
] | [
"lib/layer_utils/proposal_top_layer.py"
] | [
"# --------------------------------------------------------\n# Faster R-CNN\n# Licensed under The MIT License [see LICENSE for details]\n# Written by Xinlei Chen\n# --------------------------------------------------------\nfrom __future__ import absolute_import\nfrom __future__ import division\nfrom __future__ impo... | [
[
"numpy.random.choice",
"torch.cat"
]
] |
moritzmuehlbauer/matplotlib2tikz | [
"7621f20273b8bec1d650de7a14ac7c29194d9f64",
"7621f20273b8bec1d650de7a14ac7c29194d9f64"
] | [
"test/test_annotate.py",
"matplotlib2tikz/path.py"
] | [
"# -*- coding: utf-8 -*-\n#\nimport matplotlib.pyplot as plt\nimport numpy as np\n\nfrom helpers import Phash\n\n\ndef plot():\n fig = plt.figure(1, figsize=(8, 5))\n ax = fig.add_subplot(111, autoscale_on=False, xlim=(-1, 5), ylim=(-4, 3))\n t = np.arange(0.0, 5.0, 0.01)\n s = np.cos(2 * np.pi * t)\n ... | [
[
"numpy.arange",
"numpy.cos",
"matplotlib.pyplot.close",
"matplotlib.pyplot.show",
"matplotlib.pyplot.figure"
],
[
"numpy.column_stack"
]
] |
TmacMai/CoMPILE_Inductive_Knowledge_Graph | [
"072885012893a50b47cdee17f2e47f671e33bc00",
"072885012893a50b47cdee17f2e47f671e33bc00",
"072885012893a50b47cdee17f2e47f671e33bc00"
] | [
"CoMPILE_github/model/dgl/layers.py",
"CoMPILE_github/model/dgl/aggregators.py",
"CoMPILE_github/model/dgl/graph_classifier.py"
] | [
"\"\"\"\nFile baseed off of dgl tutorial on RGCN\nSource: https://github.com/dmlc/dgl/tree/master/examples/pytorch/rgcn\n\"\"\"\nimport torch\nimport torch.nn as nn\nimport torch.nn.functional as F\n\n\nclass Identity(nn.Module):\n \"\"\"A placeholder identity operator that is argument-insensitive.\n (Identit... | [
[
"torch.nn.init.calculate_gain",
"torch.nn.Dropout",
"torch.mm",
"torch.Tensor",
"torch.nn.Linear",
"torch.matmul"
],
[
"torch.nn.Linear",
"torch.nn.GRUCell",
"torch.cat"
],
[
"torch.cat",
"torch.zeros",
"torch.nn.ELU",
"torch.nn.GRU",
"torch.nn.Embed... |
hangyav/biadapt | [
"ab29452de5b5b1c118d448a1d46054387cc828ba"
] | [
"target-ignorant_with_semisup/semisup/tools/utils.py"
] | [
"import numpy as np\n# import fasttext\nimport tensorflow as tf\n\ndef get_embedding_weights(nb_words, tokenizer, w2v, embedding_dim=300):\n\n embedding_weights = np.zeros((nb_words, embedding_dim))\n for w, i in tokenizer.word_index.items():\n # if type(w2v) == fasttext.model.WordVectorModel or w in w... | [
[
"tensorflow.matmul",
"tensorflow.nn.softmax",
"tensorflow.transpose",
"tensorflow.placeholder",
"numpy.random.uniform",
"numpy.zeros"
]
] |
JacobDowns/sigmapy | [
"b6ec223bd245eecc37087e15a25fc32e12ba8ad4"
] | [
"sigmapy/sigma_sets.py"
] | [
"import numpy as np\nfrom numpy.linalg import cholesky, inv\n\nclass SigmaSets(object):\n \n \"\"\"\n Generates sigma points and weights using one of several available \n methods.\n\n Parameters\n ----------\n\n sqrt_method : function(ndarray)\n The matrix square root used to compute sig... | [
[
"numpy.diag",
"numpy.sqrt",
"numpy.linalg.inv",
"numpy.asarray",
"numpy.eye",
"numpy.arange",
"numpy.full",
"numpy.ones",
"numpy.atleast_2d",
"numpy.block",
"numpy.concatenate",
"numpy.isscalar",
"numpy.repeat",
"numpy.meshgrid",
"numpy.zeros"
]
] |
The-Electric-Moccasins/resistance-prediction | [
"a381ad29b21702efeea76c9fa0cd10657df1f8db"
] | [
"dataproc/build_cohort_dataset.py"
] | [
"import numpy as np\nfrom pandas import DataFrame\n\nfrom dataproc import cohort\nfrom dataproc.io import write_dataframe, load_dataframe\nfrom hyper_params import HyperParams\n\n\ndef build_cohort(params: HyperParams, df_features: DataFrame, datafile='data/fulldata.npy'):\n df_cohort = load_labels(params)\n ... | [
[
"numpy.save"
]
] |
godfatherlmh/LoLAnalyzer | [
"0b265b33230316ab1a1459a9767ef7527a4a4f89"
] | [
"Learner.py"
] | [
"# Build and train a neural network to predict the game result\n\nimport os\nimport random\nimport keras\nimport Modes\nimport Networks\nimport sys\nimport pandas as pd\nimport numpy as np\n\nnp.set_printoptions(formatter={'float_kind': lambda x: \"%.2f\" % x}, linewidth=200)\n\n\nclass dataCollector:\n def __in... | [
[
"numpy.set_printoptions",
"pandas.read_csv"
]
] |
vespos/tools | [
"0a634186ae9c103fd0c6840351cac96469d18cfa"
] | [
"tools_diffraction.py"
] | [
"# -*- coding: utf-8 -*-\n\"\"\"\nTools for diffraction and FEMTO analysis\n\n\nCreated on Tue Apr 12 14:28:22 2016\n\n@author: esposito_v\n\"\"\"\n\n\nimport numpy as np\nimport diffractionAngles_modes as diff_mode\n\n\n\n\ndef hklFromAngles(E, delta, gamma, omega, alpha, U, B):\n \"\"\"\n Calculate the hkl ... | [
[
"numpy.dot",
"numpy.arctan",
"numpy.linalg.inv",
"numpy.asarray",
"numpy.linalg.norm",
"numpy.rad2deg",
"numpy.cos",
"numpy.sin",
"numpy.deg2rad",
"numpy.identity",
"numpy.cross",
"numpy.array"
]
] |
aaalgo/cls | [
"cea5c208e783ffcb0520b130997ec300b1a53a77"
] | [
"fcn_nets.py"
] | [
"#!/usr/bin/env python\nfrom __future__ import absolute_import\nfrom __future__ import division\nfrom __future__ import print_function\nimport os\nimport tensorflow as tf\nimport tensorflow.contrib.slim as slim\nfrom tensorflow.contrib.slim.nets import resnet_v1\nfrom tensorflow.contrib.slim.nets import resnet_util... | [
[
"tensorflow.contrib.slim.dropout",
"tensorflow.contrib.slim.max_pool2d",
"tensorflow.identity",
"tensorflow.name_scope",
"tensorflow.contrib.slim.conv2d",
"tensorflow.contrib.slim.conv2d_transpose"
]
] |
yaz62/dynamo-release | [
"3f3edb227fa904664b1b0b9f6038414bc4072cc2",
"3f3edb227fa904664b1b0b9f6038414bc4072cc2"
] | [
"dynamo/plot/scatters.py",
"dynamo/plot/time_series.py"
] | [
"# code adapted from https://github.com/lmcinnes/umap/blob/7e051d8f3c4adca90ca81eb45f6a9d1372c076cf/umap/plot.py\nimport warnings\nfrom matplotlib import patches\nfrom matplotlib.lines import Line2D\nimport numpy as np\nimport pandas as pd\nfrom pandas.api.types import is_categorical_dtype\n\nimport anndata\nfrom n... | [
[
"matplotlib.rcParams.get",
"numpy.sqrt",
"pandas.Series",
"numpy.asarray",
"pandas.DataFrame",
"numpy.where",
"matplotlib.pyplot.tight_layout",
"numpy.unique",
"numpy.ceil",
"matplotlib.pyplot.subplot",
"matplotlib.pyplot.subplots_adjust",
"matplotlib.pyplot.figure"... |
BeeGroup-cimne/module_edinet | [
"0cda52e9d6222a681f85567e9bf0f7e5885ebf5e",
"0cda52e9d6222a681f85567e9bf0f7e5885ebf5e"
] | [
"debug.py",
"edinet_baseline_hourly_module/edinet_models/pyEMIS2/data/preparation/interpolators.py"
] | [
"from bee_dataframes.utils_connection import BeeDataConnection\nimport pandas as pd\nfrom calendar import monthrange\nfrom list_functions import unique, getFromDict, pretty_numeric, ensure_list\nimport json\nfrom datetime_functions import date_n_month, last_day_n_month\nfrom dateutil.relativedelta import relativede... | [
[
"pandas.TimeGrouper",
"pandas.DataFrame",
"numpy.nanmean",
"numpy.array",
"matplotlib.pyplot.show",
"matplotlib.pyplot.figure"
],
[
"numpy.isnan",
"numpy.arange",
"numpy.dtype",
"numpy.diff",
"numpy.interp"
]
] |
Tobiaskri/Heart-Rate-Measurement | [
"b61d927075a1978c2e01ae00ef8c4ce52ac39a96"
] | [
"code/main.py"
] | [
"from Code.userInterface import *\nfrom Code.processData import processing\n\nfrom matplotlib import pyplot as plt\n\n\ndef main():\n\n data = loadData()\n\n red_light = data[:,1]\n green_light = data[:,1]\n blue_light = data[:,2]\n\n plt.plot(range(len(red_light)),red_light)\n plt.show()\n\n r... | [
[
"matplotlib.pyplot.show"
]
] |
looyclark/code_sandbox | [
"e7eaed520a3a0e717534a1f8e2f7cf7c371295b1"
] | [
"Python/OLS/ols_example/linalg.py"
] | [
"\"\"\"\nA from scratch implementation of the linear algebra operations required for\nordinary least squares regression. I try to avoid built in numpy functions with\nthe exception of the ndarray data type. The code here could easily be recreated\nwithout numpy using lists instead of numpy arrays.\n\"\"\"\n\nimport... | [
[
"numpy.linalg.det",
"numpy.linalg.cond",
"numpy.zeros",
"numpy.linalg.matrix_rank"
]
] |
thearn/scikit-image | [
"edfa25f4a0c30295f09c41ce8f742a140c9d9ec1"
] | [
"skimage/filter/_denoise.py"
] | [
"import numpy as np\nfrom skimage import img_as_float\nfrom skimage._shared.utils import deprecated\n\n\ndef _denoise_tv_chambolle_3d(im, weight=100, eps=2.e-4, n_iter_max=200):\n \"\"\"Perform total-variation denoising on 3D images.\n\n Parameters\n ----------\n im : ndarray\n 3-D input data to ... | [
[
"numpy.abs",
"numpy.zeros_like",
"numpy.sqrt",
"numpy.diff"
]
] |
Sura-IIT-DELHI/Autonomous-Driving-Robot-Car | [
"44756265948af96735637bb743dab9a0b68351a8"
] | [
"npycreater.py"
] | [
"import numpy as np\nfrom PIL import Image\nimport pandas as pd\nimage1=[]\nprevious_state1=[]\nlabel1=[]\ndatafile=pd.read_csv('/media/kanish/Data_Softwares/autonomous/'+'syncdata.csv')\ndatafile = datafile.sample(frac=1).reset_index(drop=True)\nfor i in range(datafile.shape[0]):\n\tprevious_state=list(datafile.il... | [
[
"numpy.asarray",
"pandas.read_csv",
"numpy.save"
]
] |
KoryakovDmitry/synthtiger | [
"8a995aef46f2c5fe3ee0bbaca2269b3cf66927d4"
] | [
"templates/default.py"
] | [
"\"\"\"\nSynthTIGER\nCopyright (c) 2021-present NAVER Corp.\nMIT license\n\"\"\"\n\nimport cv2\nimport numpy as np\n\nfrom synthtiger import components, layers, utils\n\nBLEND_MODES = [\n \"normal\",\n \"multiply\",\n \"screen\",\n \"overlay\",\n \"hard_light\",\n \"soft_light\",\n \"dodge\",\n... | [
[
"numpy.pad",
"numpy.concatenate",
"numpy.random.permutation",
"numpy.random.rand",
"numpy.zeros",
"numpy.sum",
"numpy.random.randint"
]
] |
Cyberspirit/pythonic | [
"aeb96fb514c0adb78f8ffbdadd80012a0ff510ed"
] | [
"examples/dask_array_2.py"
] | [
"\"\"\"\nExample of using Dask array `map_blocks()` with a function that returns a\ntuple value. Using an 8 CPU core MacBook Pro running macOS v11.6, the serial\nelapsed time is 513.45 seconds and the Dask elapsed time is 3.20 seconds.\n\"\"\"\n\nimport dask.array as da\nimport numpy as np\nimport time\nfrom distri... | [
[
"numpy.set_printoptions",
"numpy.array",
"numpy.random.random"
]
] |
Casperjamin/transposontyping | [
"70c730d7bb914bbf54b993aab2ddb0874e53f98b"
] | [
"SCRIPTS/tetyperead.py"
] | [
"import pandas as pd\nfrom Bio import SeqIO\nimport math\n\nclass tetype_result:\n def __init__(self, summary, fragment):\n self.summary = summary\n self.fragment = fragment\n self.name = str(self.summary.split(\"/\")[-1].split(\"_\")[0])\n\n\n def result_to_frame(self, summary, vcf, scor... | [
[
"pandas.read_csv"
]
] |
phbrgnomo/hummingbot | [
"72382954a06a277248f44b321344186aef1c367c"
] | [
"test/hummingbot/strategy/celo_arb/test_celo_arb.py"
] | [
"#!/usr/bin/env python\nfrom decimal import Decimal\nimport logging\nimport pandas as pd\nimport unittest\nimport mock\nfrom nose.plugins.attrib import attr\nfrom hummingsim.backtest.backtest_market import BacktestMarket\nfrom hummingsim.backtest.market import (\n QuantizationParams\n)\nfrom hummingsim.backtest.... | [
[
"pandas.Timestamp"
]
] |
EthanHolleman/models | [
"0e2c0f7be465d1db118dbefcaca3bbf5a1c66490"
] | [
"research/marco/Automated_Marco.py"
] | [
"#!/usr/bin/python\n# 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.... | [
[
"tensorflow.contrib.predictor.from_saved_model"
]
] |
xinshuoweng/cv_ml_tool | [
"1918b9e37ec5fb8148b8a089f226a4864d67b153",
"1918b9e37ec5fb8148b8a089f226a4864d67b153"
] | [
"xinshuo_miscellaneous/pytorch/configuration.py",
"xinshuo_math/test/bbox_transform/test_bbox_TLWH2TLBR.py"
] | [
"# Author: Xinshuo Weng\n# email: xinshuo.weng@gmail.com\nimport os, numpy as np, random, torch\n\ndef prepare_seed(rand_seed):\n\tnp.random.seed(rand_seed)\n\trandom.seed(rand_seed)\n\ttorch.manual_seed(rand_seed)\n\ttorch.cuda.manual_seed_all(rand_seed)",
"# Author: Xinshuo Weng\n# email: xinshuo.weng@gmail.com... | [
[
"torch.manual_seed",
"numpy.random.seed",
"torch.cuda.manual_seed_all"
],
[
"numpy.array"
]
] |
aitor-martinez-seras/FSSD_OoD_Detection | [
"69a6393061c24e2af7e1b7e5cbe78ffff63da813"
] | [
"lib/utils/exp.py"
] | [
"import os\nimport sys\nimport types\nimport pickle\nfrom copy import deepcopy\n\nfrom PIL import Image\nimport numpy as np\nimport torch\nfrom torchvision import transforms\nfrom loguru import logger\nimport torchvision.models as models\nfrom lib.model.resnet_imagenet import resnet34\nfrom lib.model import resnet,... | [
[
"torch.nn.DataParallel",
"torch.load"
]
] |
Jeffrey-Ede/Adaptive-Partial-STEM | [
"dc13e64ba3fb8266d39a260780af615b170a3c88",
"dc13e64ba3fb8266d39a260780af615b170a3c88"
] | [
"105/train.py",
"110/train.py"
] | [
"# Copyright 2017 Google Inc.\r\n#\r\n# Licensed under the Apache License, Version 2.0 (the \"License\");\r\n# you may not use this file except in compliance with the License.\r\n# You may obtain a copy of the License at\r\n#\r\n# http://www.apache.org/licenses/LICENSE-2.0\r\n#\r\n# Unless required by applicab... | [
[
"tensorflow.ensure_shape",
"tensorflow.nn.dynamic_rnn",
"numpy.minimum",
"tensorflow.concat",
"numpy.sqrt",
"tensorflow.zeros",
"numpy.asarray",
"tensorflow.control_dependencies",
"numpy.bool",
"numpy.cumsum",
"numpy.max",
"tensorflow.train.AdamOptimizer",
"tens... |
lgeiger/io | [
"90be860451a705e2fbe8cfdec3c30030112b5c69",
"90be860451a705e2fbe8cfdec3c30030112b5c69"
] | [
"tests/test_obj.py",
"tensorflow_io/python/experimental/numpy_dataset_ops.py"
] | [
"# Copyright 2021 The TensorFlow Authors. All Rights Reserved.\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\"); you may not\n# use this file except in compliance with the License. You may obtain a copy of\n# the License at\n#\n# http://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless req... | [
[
"tensorflow.io.read_file",
"numpy.array",
"numpy.array_equal"
],
[
"tensorflow.constant",
"tensorflow.executing_eagerly",
"tensorflow.as_dtype",
"tensorflow.unstack",
"tensorflow.data.Dataset.from_tensor_slices",
"tensorflow.cast",
"tensorflow.data.Dataset.zip",
"te... |
zhaozhongch/yolact_ros | [
"ee3e086626f49a81ffd06b2740dae849552151cb"
] | [
"layers/interpolate.py"
] | [
"#!/usr/bin/env python3\n\nimport torch.nn as nn\nimport torch.nn.functional as F\n\nclass InterpolateModule(nn.Module):\n\t\"\"\"\n\tThis is a module version of F.interpolate (rip nn.Upsampling).\n\tAny arguments you give it just get passed along for the ride.\n\t\"\"\"\n\n\tdef __init__(self, *args, **kwdargs):\n... | [
[
"torch.nn.functional.interpolate"
]
] |
drewhart/geonomics | [
"884676d7a2c02d914da4cae0d0befcd1f24f956a"
] | [
"geonomics/sim/data.py"
] | [
"#!/usr/bin/python\n#data.py\n\n\n'''\nClasses and functions for implementing data collection and output\n'''\n\n#geonmics imports\nfrom geonomics.utils.io import (_write_csv, _write_shapefile, _write_geojson,\n _write_file)\n\n#other imports\nimport numpy as np\nfrom random import sa... | [
[
"numpy.linspace",
"numpy.random.choice",
"numpy.ones",
"numpy.all",
"numpy.shape",
"pandas.DataFrame.from_dict",
"numpy.array"
]
] |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.