repo_name stringlengths 6 130 | hexsha list | file_path list | code list | apis list |
|---|---|---|---|---|
moonso/seaviz | [
"7375cfc905358ff7171c2ce26fed3e85327b9173"
] | [
"seaviz/cli.py"
] | [
"import logging\nfrom pprint import pprint as pp\n\nimport click\n\nimport coloredlogs\nimport matplotlib.style as mp_style\nimport numpy as np\nimport pandas as pd\nimport seaborn as sns\nfrom matplotlib import pyplot as plt\n\nLOG_LEVELS = [\"DEBUG\", \"INFO\", \"WARNING\", \"ERROR\", \"CRITICAL\"]\n\nLOG = loggi... | [
[
"pandas.read_csv",
"numpy.linspace",
"matplotlib.style.use",
"numpy.random.multivariate_normal",
"numpy.arange",
"matplotlib.pyplot.subplots",
"matplotlib.pyplot.savefig",
"pandas.DataFrame",
"numpy.sin",
"numpy.random.normal",
"matplotlib.pyplot.show"
]
] |
scrawfor1/TensorFlow | [
"7e3b8b23835ab0ac55d390aed2349af6e05dbe3b"
] | [
"tensorflow/python/training/saver_test.py"
] | [
"# Copyright 2015 Google Inc. 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 required by appl... | [
[
"tensorflow.core.protobuf.meta_graph_pb2.MetaGraphDef",
"tensorflow.train.update_checkpoint_state",
"tensorflow.nn.softmax_cross_entropy_with_logits",
"tensorflow.concat",
"tensorflow.zeros",
"tensorflow.test.is_built_with_cuda",
"tensorflow.train.QueueRunner",
"tensorflow.python.p... |
LegrandNico/cca_zoo | [
"03497ef4d8434f847435b572bff92b2095fbc4fc"
] | [
"cca_zoo/deepmodels/dcca_noi.py"
] | [
"import torch\n\nfrom cca_zoo.deepmodels.dcca import DCCA\nfrom cca_zoo.deepmodels.objectives import mat_pow\n\n\nclass DCCA_NOI(DCCA):\n \"\"\"\n A class used to fit a DCCA model by non-linear orthogonal iterations\n\n\n :Citation:\n\n Wang, Weiran, et al. \"Stochastic optimization for deep CCA via non... | [
[
"torch.nn.Linear",
"torch.nn.MSELoss",
"torch.rand"
]
] |
ishine/Microphone-Array-Generalization-for-Multichannel-Narrowband-Deep-Speech-Enhancement | [
"9616949ee23a8be2fa408c838efe0e7017f53549"
] | [
"inference.py"
] | [
"# -*- coding: utf-8 -*-\n\"\"\"\nCreated on Tue Apr 28 15:43:18 2020\n\n@author: admin\n\"\"\"\nimport torch\nimport torch.nn as nn\nfrom PW_NBDF_Net import PW_NBDF\n\nimport numpy as np\n\nimport scipy.signal as signal\nimport scipy.io.wavfile \nimport os,fnmatch \nfrom scipy import io\n\n\n\nprint(torch.cuda.is_... | [
[
"numpy.imag",
"numpy.abs",
"torch.load",
"scipy.signal.stft",
"torch.backends.cudnn.version",
"torch.cuda.empty_cache",
"numpy.transpose",
"numpy.real",
"numpy.iinfo",
"torch.cuda.is_available",
"torch.cuda.get_device_name",
"scipy.signal.istft",
"numpy.empty"
... |
MichelleLau/ncappzoo | [
"d222058e9bf16fbfa2670ff686d11fe521a976e0"
] | [
"apps/MultiStick_GoogLeNet/MultiStick_GoogLeNet_Camera.py"
] | [
"#! /usr/bin/env python3\n\n# *******************************************************\n# Copyright(c) 2017 Intel Corporation. \n# License: MIT See LICENSE file in root directory.\n# *******************************************************\n\n\n# *******************************************************\n# Demo with Go... | [
[
"numpy.load",
"numpy.loadtxt"
]
] |
awesome-archive/baikal | [
"c44b4f1b0f7a01ca5d41762043723aeeb5a130c9"
] | [
"tests/test_sklearn_wrapper.py"
] | [
"import pytest\nimport sklearn.decomposition\nimport sklearn.linear_model\nfrom numpy.testing import assert_array_equal\nfrom sklearn import datasets\nfrom sklearn.model_selection import GridSearchCV, StratifiedKFold\nfrom sklearn.pipeline import Pipeline\n\nfrom baikal import Model, Input\nfrom baikal.sklearn impo... | [
[
"sklearn.model_selection.GridSearchCV",
"sklearn.datasets.load_iris",
"sklearn.pipeline.Pipeline",
"sklearn.model_selection.StratifiedKFold",
"numpy.testing.assert_array_equal"
]
] |
seyoung-hyun/tensorflow | [
"2ac978d2532dd359dd7ebbd27ac13dfa147d755d"
] | [
"tensorflow/contrib/bayesflow/examples/reinforce_simple/reinforce_simple_example.py"
] | [
"# Copyright 2016 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.get_variable",
"tensorflow.matmul",
"tensorflow.constant",
"tensorflow.reduce_sum",
"tensorflow.identity",
"tensorflow.test.main",
"tensorflow.dynamic_stitch",
"tensorflow.global_variables_initializer",
"tensorflow.train.GradientDescentOptimizer",
"tensorflow.sq... |
Iydon/NumericalAnalysisNotes | [
"65bd3372df197bec5e152a37cdc1f6f5432b7f3e"
] | [
"Code/HW/3.5.py"
] | [
"#!/usr/bin/env python\n# -*- coding: utf-8 -*-\n# @Time : 2018/10/04 14:23\n# @Author : Iydon\n# @File : course3.5.py\n\nimport numpy as np\nfrom Poly import *\nimport matplotlib.pyplot as plt\n\ndef clamped_cubic_spline(xs:list, fxs:list, boundray:list=[0,0]):\n\t\"\"\"\n\tCubic spline interpolation.\n\... | [
[
"numpy.diag",
"numpy.matrix",
"matplotlib.pyplot.scatter",
"numpy.linalg.inv",
"matplotlib.pyplot.plot",
"matplotlib.pyplot.grid",
"matplotlib.pyplot.axis",
"matplotlib.pyplot.show"
]
] |
kumokay/randomstuff | [
"4fa674cd6b5f0b080381cc4a548ad0039510bd51",
"4fa674cd6b5f0b080381cc4a548ad0039510bd51"
] | [
"mytest/PythonClient_1.0/drive_straight.py",
"test_airsim_v1.2/demo_20181101_ok/PythonClient/car/DQNcar.py"
] | [
"from AirSimClient import *\r\n#from keras.models import load_model\r\nimport sys\r\nimport numpy as np\r\n\r\n#if (len(sys.argv) != 2):\r\n# print('usage: python drive.py <modelName>')\r\n# sys.exit()\r\n\r\n#print('Loading model...')\r\n#model = load_model(sys.argv[1])\r\n\r\n# connect to the AirSim simulat... | [
[
"numpy.flipud",
"numpy.fromstring",
"numpy.zeros"
],
[
"numpy.random.choice",
"numpy.reshape",
"numpy.arange",
"numpy.linalg.norm",
"numpy.ones",
"numpy.std",
"numpy.mean",
"numpy.random.rand",
"numpy.cross",
"numpy.array",
"numpy.zeros",
"numpy.rand... |
gwaygenomics/cell-painting-vae | [
"ad3a7fa18cf7b49bdcbde4647477ac74a758bbd5",
"ad3a7fa18cf7b49bdcbde4647477ac74a758bbd5",
"ad3a7fa18cf7b49bdcbde4647477ac74a758bbd5"
] | [
"L1000/3.application/scripts/experiment.py",
"cell-painting/2.train/scripts/0.cell-painting-vae_LEVEL5.py",
"cell-painting/2.train/scripts/0.cell-painting-vaeLEVEL4-leave_out.py"
] | [
"#!/usr/bin/env python\n# coding: utf-8\n\n# In[37]:\n\n\nimport numpy as np\nimport pandas as pd\nimport sys\nsys.path.insert(0, \"../../scripts\")\nfrom utils import load_data, infer_L1000_features\nfrom tensorflow import keras\n\nimport matplotlib.pyplot as plt\n\nfrom scipy.stats import pearsonr, ttest_ind, tte... | [
[
"tensorflow.keras.models.load_model",
"pandas.concat",
"pandas.read_csv",
"numpy.random.seed",
"numpy.arange",
"scipy.stats.zscore",
"numpy.linalg.norm",
"pandas.DataFrame",
"numpy.mean",
"numpy.array",
"sklearn.decomposition.PCA"
],
[
"matplotlib.pyplot.legend"... |
JarvisUSTC/DARDet | [
"debbf476e9750030db67f030a40cf8d4f03e46ee"
] | [
"mmdet/apis/inference.py"
] | [
"import warnings\n\nimport mmcv\nimport numpy as np\nimport torch\nfrom mmcv.ops import RoIPool\nfrom mmcv.parallel import collate, scatter\nfrom mmcv.runner import load_checkpoint\n\nfrom mmdet.core import get_classes\nfrom mmdet.datasets import replace_ImageToTensor\nfrom mmdet.datasets.pipelines import Compose\n... | [
[
"torch.set_grad_enabled",
"torch.no_grad"
]
] |
mauriciofarina/SelfDrivingCar-TrafficSignClassifier | [
"f37d79ba281210ed0f7be927610a327ee74fe012"
] | [
"Plots.py"
] | [
"'''\nThis file implements functions for ploting data.\n'''\n\nimport matplotlib.pyplot as plt\nimport numpy as np\n\n\ndef linePlot(x , y , xLabel = '' , yLabel = '',setYAxis = None, grid = True, fileName = 'test', save = False, show = False):\n \n plt.figure()\n plt.plot(x, y)\n plt.xlabel(xLabel)\n ... | [
[
"matplotlib.pyplot.figure",
"matplotlib.pyplot.savefig",
"matplotlib.pyplot.plot",
"numpy.std",
"numpy.mean",
"matplotlib.pyplot.axis",
"matplotlib.pyplot.bar",
"matplotlib.pyplot.grid",
"matplotlib.pyplot.xlabel",
"matplotlib.pyplot.xticks",
"matplotlib.pyplot.show",
... |
WallabyLester/EMG_Controlled_Hand_Exoskeleton | [
"9b7b7057752ab6e8c1331701eae29cd1b395cc57"
] | [
"code/RFC.py"
] | [
"\"\"\"\nRandom Forest algorithm to classify finger flexion based on EMG readings.\nHyperparameters found in Classification Notes. Refer to the notes to find \nnew hyperparameters as needed.\n\nImplements scikit-learn model.\n\nTraining: Use to fit model using training data\n\nPrediction: Use to predict class value... | [
[
"numpy.hstack",
"pandas.read_csv",
"sklearn.ensemble.RandomForestClassifier",
"sklearn.model_selection.train_test_split",
"numpy.vstack"
]
] |
litvinich/detectron2 | [
"ac622e22eb0f13c9b5838a1e45b046212f22f814"
] | [
"detectron2/evaluation/coco_evaluation.py"
] | [
"# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved\nimport contextlib\nimport copy\nimport io\nimport itertools\nimport json\nimport logging\nimport numpy as np\nimport os\nimport pickle\nfrom collections import OrderedDict\nimport pycocotools.mask as mask_util\nimport torch\nfrom fvcore.common... | [
[
"torch.cat",
"torch.zeros",
"torch.zeros_like",
"torch.save",
"torch.sort",
"numpy.mean",
"torch.arange",
"torch.device",
"numpy.array",
"torch.as_tensor"
]
] |
Neronjust2017/pytorch-classification-project | [
"fc5f4d7c46d071765f682ce20e6580646d4e5c76"
] | [
"model/model.py"
] | [
"import torch\nimport torch.nn as nn\nimport torch.nn.functional as F\nfrom base import BaseModel\n\ndef MC_dropout(act_vec, p=0.5, mask=True):\n # return F.dropout(act_vec, p=p, training=mask, inplace=True)\n return F.dropout(act_vec, p=p, training=mask, inplace=False)\n\nclass MnistModel(BaseModel):\n de... | [
[
"torch.nn.Dropout2d",
"torch.nn.functional.log_softmax",
"torch.nn.functional.dropout",
"torch.nn.ModuleList",
"torch.nn.Conv2d",
"torch.nn.Tanh",
"torch.nn.Sigmoid",
"torch.nn.Linear",
"torch.nn.MaxPool1d",
"torch.nn.Conv1d",
"torch.nn.ReLU"
]
] |
xiaohaijin/OpenCV | [
"0b909cd2a3321d5ceaa00cd912a1ca44ed4fade1",
"0b909cd2a3321d5ceaa00cd912a1ca44ed4fade1"
] | [
"BookSrc/learnOpenCV/Homography/homography.py",
"BookSrc/learnOpenCV/ConvexHull/example.py"
] | [
"import cv2\nimport numpy as np\n\ndef mouseHandler(event,x,y,flags,param):\n global im_temp, pts_src\n\n if event == cv2.EVENT_LBUTTONDOWN:\n cv2.circle(im_temp,(x,y),3,(0,255,255),5,cv2.LINE_AA)\n cv2.imshow(\"Image\", im_temp)\n if len(pts_src) < 4:\n \tpts_src = np.append(pts_s... | [
[
"numpy.append",
"numpy.zeros",
"numpy.empty"
],
[
"numpy.zeros"
]
] |
congtranv/Unified-Gesture-and-Fingertip-Detection | [
"5606c2afed462d0bf5686b10c441a6b7d0dbc7ad"
] | [
"hand_detector/yolo/preprocess/labelgen.py"
] | [
"import cv2\nimport numpy as np\nimport matplotlib.pyplot as plt\nfrom preprocess.finder import find_folder\nfrom hand_detector.yolo.utils.utils import visualize\nfrom hand_detector.yolo.preprocess.yolo_flag import Flag\n\nf = Flag()\n\ngrid = f.grid\ngrid_size = f.grid_size\ntarget_size = f.target_size\nthreshold ... | [
[
"matplotlib.pyplot.imread",
"numpy.array",
"numpy.zeros",
"numpy.floor"
]
] |
jisantuc/raster-vision | [
"b4af7f518e8f2086a0154e74b970debe79a13a94"
] | [
"tests/pytorch_learner/dataset/test_transform.py"
] | [
"import unittest\n\nimport numpy as np\n\nfrom rastervision.pytorch_learner.dataset.transform import (\n yxyx_to_albu, albu_to_yxyx, xywh_to_albu)\n\n\nclass TestTransforms(unittest.TestCase):\n def test_box_format_conversions_yxyx(self):\n boxes = np.array(\n [\n [1, 2, 3, 4]... | [
[
"numpy.all",
"numpy.array"
]
] |
NGoetz/zunis | [
"a2d3ba2392ef802349723465c6559e8eb407db54"
] | [
"zunis_lib/zunis/integration/flat_survey_integrator.py"
] | [
"import torch\n\n# TODO: change where the method we use from this class is\nfrom zunis.integration.base_integrator import BaseIntegrator\nfrom zunis.training.weighted_dataset.weighted_dataset_trainer import BasicStatefulTrainer\nfrom zunis.models.flows.sampling import UniformSampler\n\n\nclass PosteriorSurveySampli... | [
[
"torch.device"
]
] |
One-sixth/konohana_net | [
"19507e330a1d52dedd118d1303a270611f8ce473"
] | [
"eval_utils2.py"
] | [
"import my_py_lib.coord_tool as coord_tool\nimport numpy as np\nimport my_py_lib.im_tool as im_tool\nimport cv2\nfrom config import a_config as cfg\n\n\ndef _get_iou(box, boxes):\n box_area = (box[2] - box[0]) * (box[3] - box[1])\n area = (boxes[:, 2] - boxes[:, 0]) * (boxes[:, 3] - boxes[:, 1])\n xx1 = np... | [
[
"numpy.maximum",
"numpy.minimum",
"numpy.reshape",
"numpy.asarray",
"numpy.argmax",
"numpy.any",
"numpy.argsort"
]
] |
DAIRLab/dair_pll | [
"575661babb0e888da1594a4a6c227fb7a812a2e8"
] | [
"dair_pll/meshcat_utils.py"
] | [
"\"\"\"Utility functions for visualizing trajectories with meshcat.\n\nVisualization of Drake systems is managed by meshcat. This allows for a\nrelatively thin implementation of visualization for very complex geometries.\n\nThe main contents of this file are as follows:\n\n * A method to generate a dummy ``Drake... | [
[
"numpy.array",
"numpy.moveaxis"
]
] |
jiameng1010/SUNProcessing | [
"0cb5fcaa9ce0736501f90c29bf7bf46abf4fb1c8"
] | [
"Gist_Histogram.py"
] | [
"import numpy\n\n#: experimental setup constants\nNUMBER_OF_PARTICIPANTS = 50\nNUMBER_OF_UNIQUE_RUNS = 8\nNUMBER_OF_SHARED_RUNS = 1\nUNIQUE_IMAGES_PER_UNIQUE_RUN = 56\nSHARED_IMAGES_PER_UNIQUE_RUN = 8\nSHARED_IMAGES_PER_SHARED_RUN = 64\n\nDIM_REDUCE_TO = 10\nNUMBER_OF_BIN = 10\n\nclass Subject():\n def __init__(... | [
[
"numpy.zeros"
]
] |
AaronWard/Tensorflow-XOR | [
"b3674b961a19704a82c1cd0ba7d5f8f148376b1c"
] | [
"xor-nn-eval.py"
] | [
"import os\nimport tensorflow as tf\nimport time\nimport csv\n\n# Used to supress AVX warnings\nos.environ['TF_CPP_MIN_LOG_LEVEL'] = '3' \n\n\nNUM_EXAMPLES = 4 # Number of training or evaluation examples\nNUM_FEATURES = 2 # Number of input features\nNUM_LABELS = 1\t# Number of output features or class labels\nNUM_H... | [
[
"tensorflow.matmul",
"tensorflow.zeros",
"tensorflow.placeholder",
"tensorflow.global_variables_initializer",
"tensorflow.Session",
"tensorflow.square",
"tensorflow.train.Saver",
"tensorflow.random_uniform"
]
] |
czbiohub/luminoth | [
"3b4d57a9b4c3704c64816bbcbd6126a2ac23a069"
] | [
"luminoth/models/base/base_network.py"
] | [
"import functools\n\nimport sonnet as snt\nimport tensorflow as tf\nimport tensorflow.contrib.slim as slim\n\nfrom tensorflow.contrib.slim.nets import resnet_v2, resnet_v1, vgg\n\nfrom luminoth.models.base import truncated_vgg\nfrom luminoth.utils.checkpoint_downloader import get_checkpoint_file\n\n\n# Default RGB ... | [
[
"tensorflow.contrib.slim.nets.resnet_v2.resnet_utils.resnet_arg_scope",
"tensorflow.get_collection",
"tensorflow.contrib.slim.arg_scope",
"tensorflow.contrib.slim.nets.vgg.vgg_arg_scope"
]
] |
kokoyy/OCR.pytorch | [
"db45ab9ab755381a636076bf997c0ebb70dd3bdb"
] | [
"model/crnn/vgg_lstm.py"
] | [
"import torch.nn as nn\nimport torch.nn.functional as fn\n\n\nclass DenseBLSTMCTC(nn.Module):\n\n def __init__(self, num_classes):\n super(DenseBLSTMCTC, self).__init__()\n self.cnn = nn.Sequential(\n nn.Conv2d(3, 64, 3, 1, 1),\n nn.LeakyReLU(inplace=True),\n nn.Max... | [
[
"torch.nn.functional.log_softmax",
"torch.nn.LSTM",
"torch.nn.init.constant_",
"torch.nn.Conv2d",
"torch.nn.Linear",
"torch.nn.MaxPool2d",
"torch.nn.LeakyReLU",
"torch.nn.BatchNorm2d",
"torch.nn.init.kaiming_normal_"
]
] |
ojasviyadav/AmpliGraph | [
"304bae8aaae123b8e6a20d4715f42416977db44c"
] | [
"ampligraph/discovery/discovery.py"
] | [
"import logging\nimport numpy as np\nfrom sklearn.cluster import DBSCAN\nfrom sklearn.neighbors import NearestNeighbors\nfrom scipy import optimize, spatial\nimport networkx as nx\nfrom ..evaluation import evaluate_performance, filter_unseen_entities\n\nlogger = logging.getLogger(__name__)\nlogger.setLevel(logging.... | [
[
"numpy.sqrt",
"numpy.cumsum",
"sklearn.cluster.DBSCAN",
"numpy.concatenate",
"numpy.mean",
"scipy.optimize.bisect",
"numpy.where",
"numpy.hstack",
"numpy.swapaxes",
"numpy.unique",
"scipy.spatial.distance_matrix",
"numpy.copy",
"sklearn.neighbors.NearestNeighbor... |
JHurricane96/1000Langs | [
"eada336ee3ada9420f9d76b958d7bd08d580c4a8"
] | [
"metaAPI/metadata.py"
] | [
"__author__ = \"Ehsaneddin Asgari\"\n__license__ = \"Apache 2\"\n__version__ = \"1.0.0\"\n__maintainer__ = \"Ehsaneddin Asgari\"\n__website__ = \"https://llp.berkeley.edu/asgari/\"\n__git__ = \"https://github.com/ehsanasgari/\"\n__email__ = \"ehsan.asgari@gmail.com\"\n__project__ = \"1000Langs -- Super parallel pro... | [
[
"pandas.read_table",
"pandas.concat",
"numpy.mean",
"pandas.DataFrame"
]
] |
fuouo/TrafficBato | [
"bd8ab5645116db4029b90bb5a28e0134d59e9ac0"
] | [
"dbn/tensorflow/models.py"
] | [
"import atexit\nfrom abc import ABCMeta\n\nimport numpy as np\nimport tensorflow as tf\nfrom sklearn.base import ClassifierMixin, RegressorMixin\n\nfrom ..models import AbstractSupervisedDBN as BaseAbstractSupervisedDBN\nfrom ..models import BaseModel\nfrom ..models import BinaryRBM as BaseBinaryRBM\nfrom ..models ... | [
[
"tensorflow.nn.softmax_cross_entropy_with_logits",
"numpy.expand_dims",
"numpy.sqrt",
"tensorflow.variables_initializer",
"tensorflow.assign_add",
"tensorflow.Variable",
"numpy.unique",
"numpy.argmax",
"tensorflow.to_float",
"tensorflow.Session",
"tensorflow.square",
... |
InterfaceGuy/pydeation-legacy | [
"44c2ef08809d18545e052f016352021ebe4187e1"
] | [
"animation/animator.py"
] | [
"from pydeationlib.animation.animation import *\nfrom pydeationlib.constants import *\nfrom pydeationlib.object.mograph import *\nimport c4d\nfrom c4d.utils import SinCos, Smoothstep\nimport numpy as np\n\n\nclass Animator():\n \"\"\"\n abstract class for animations\n takes in cobjects and groups and retur... | [
[
"numpy.cos",
"numpy.arcsin"
]
] |
holyseven/PaddleHub | [
"25dbebc2e8a46ebbec3bfd5c6b38abc96318625b"
] | [
"paddlehub/autodl/DELTA/datasets/readers.py"
] | [
"\nimport cv2\nimport numpy as np\nimport six\nimport os\nimport glob\n\n\ndef resize_short(img, target_size, interpolation=None):\n \"\"\"resize image\n\n Args:\n img: image data\n target_size: resize short target size\n interpolation: interpolation mode\n\n Returns:\n resized ... | [
[
"numpy.random.uniform",
"numpy.array",
"numpy.expand_dims",
"numpy.random.randint"
]
] |
mdrolet01/scikit-fda | [
"93c4ad80aaba8739b4f90932a2a759d6f5960387",
"93c4ad80aaba8739b4f90932a2a759d6f5960387"
] | [
"examples/plot_composition.py",
"examples/plot_interpolation.py"
] | [
"\"\"\"\nFunction composition\n====================\n\nThis example shows the composition of multidimensional FDataGrids.\n\"\"\"\n\n# Author: Pablo Marcos Manchón\n# License: MIT\n\n# sphinx_gallery_thumbnail_number = 3\n\nimport skfda\n\nfrom mpl_toolkits.mplot3d import axes3d\n\nimport numpy as np\n\n\n#########... | [
[
"numpy.cos",
"numpy.linspace",
"numpy.sin"
],
[
"numpy.sort"
]
] |
Matej-Chmel/hnsw | [
"c6c0e8c04364a90cdb994d17e3db80f8821c5e75"
] | [
"src/Runner/runner.py"
] | [
"from dataclasses import dataclass, field\nimport h5py as hdf\nimport hnsw\nimport IHnsw\nimport json\nimport numpy as np\nimport pandas\nfrom pathlib import Path\nimport time\n\n@dataclass\nclass Setup:\n\tefConstruction: int\n\tefs: list[int]\n\tM: int\n\tpath: Path\n\tseed: int\n\tspace: hnsw.Space\n\n\tdef __po... | [
[
"pandas.Timedelta"
]
] |
gammasim/gammasim-tools | [
"0b746254916f4c2e2a3fbd1854c565c3bc90d493"
] | [
"simtools/model/camera.py"
] | [
"import logging\nimport numpy as np\nimport matplotlib as mlp\nimport matplotlib.pyplot as plt\nimport matplotlib.patches as mpatches\nimport matplotlib.colors as mcolors\nfrom scipy.spatial import cKDTree as KDTree\nfrom scipy.spatial import distance\nfrom matplotlib.collections import PatchCollection\n\nimport si... | [
[
"matplotlib.pyplot.legend",
"numpy.sqrt",
"numpy.arctan",
"numpy.rad2deg",
"scipy.spatial.cKDTree",
"matplotlib.pyplot.gca",
"matplotlib.pyplot.tight_layout",
"matplotlib.colors.to_rgb",
"numpy.sin",
"matplotlib.pyplot.gcf",
"matplotlib.pyplot.axis",
"matplotlib.pyp... |
SethMK/Titanic | [
"73a405795ef3e299a84f7c4a6435e793b7c84626"
] | [
"src/data/get_processed_data.py"
] | [
"import numpy as np\nimport pandas as pd\nimport os\n\ndef read_data():\n # set the path to the raw data\n raw_data_path = os.path.join(os.path.pardir, 'data', 'raw')\n train_file_path = os.path.join(raw_data_path, 'train.csv')\n test_file_path = os.path.join(raw_data_path, 'test.csv')\n # read the d... | [
[
"pandas.concat",
"pandas.notnull",
"pandas.read_csv",
"numpy.where",
"pandas.qcut"
]
] |
jonvw28/SLICUAV | [
"b9d4993816bab44a411444f4a1425acabbc10afe"
] | [
"manuscript_code/3_Landscape_mapping/2019_10_23_1_compute_superpixel_features/2019_10_23_stack_feats_grid_segs_8.py"
] | [
"import numpy as np\nimport rasterio as rio\nimport geopandas as gpd\nimport pandas as pd\nimport random\n#from osgeo import gdal, ogr, osr\n\nfrom rasterio.mask import mask\nfrom shapely.geometry import mapping, Polygon\nfrom skimage.util import img_as_float\n\nimport os as os\nos.chdir('E:/SLICUAV_manuscript_code... | [
[
"numpy.swapaxes",
"pandas.DataFrame",
"numpy.vstack",
"numpy.squeeze"
]
] |
Kitsunetic/360SD-Net | [
"bb87f8e238cbfe086066f7ff2dd2883ff86885e9"
] | [
"utils/disp2de.py"
] | [
"import argparse\nimport math\nimport os\n\nimport numpy as np\nfrom tqdm import tqdm\n\nparser = argparse.ArgumentParser()\nparser.add_argument('--path', default=None, help='The input folder path')\nparser.add_argument('--b', default=0.2, type=float, help='The input baseline')\nargs = parser.parse_args()\n\n# path... | [
[
"numpy.tan",
"numpy.load",
"numpy.zeros",
"numpy.save"
]
] |
Bhumbra/probayes | [
"e5ac193076e4188b9b38c0e18466223ab4d041f7"
] | [
"examples/mcmc/mcmc_prob4a.py"
] | [
"\"\"\"\nSimple Metropolis Hastings sampler taken from Hogg and Foreman-MacKey(2018):\n\n From Problem 2:\n Sample in a single parameter x and give the sampler \n as its density function p(x) a Gaussian density with \n mean 2 and variance 2. Make the proposal distribution \n q (x'∣x ) a Gaussian pdf for x′ wit... | [
[
"numpy.max",
"numpy.histogram",
"numpy.sqrt",
"numpy.min"
]
] |
bcornelusse/microgridRLsimulator | [
"f2d7a0c77c47b9727d69c14d80fa521dea6a3861"
] | [
"microgridRLsimulator/history/database.py"
] | [
"import pandas as pd\n\nclass Database:\n\n _inputs_ = ['Year', 'Month', 'Day', 'Hour', 'Minutes', 'Seconds', 'IsoDayOfWeek', 'IsoWeekNumber']\n\n def __init__(self, path_to_csv, grid):\n \"\"\"\n A Database objects holds the realized data of the microgridRLsimulator in a pandas dataframe.\n\n ... | [
[
"pandas.read_csv"
]
] |
ljynlp/HiTrans | [
"142e76845571991f05b3fb1529fa79389af29c36"
] | [
"models/Loss.py"
] | [
"import torch\nimport torch.nn as nn\n\nclass MultiTaskLoss(nn.Module):\n def __init__(self, num_tasks):\n super(MultiTaskLoss, self).__init__()\n self.sigma = nn.Parameter(torch.ones(num_tasks), requires_grad=True)\n\n def forward(self, *losses):\n losses = torch.cat([loss.unsqueeze(0) f... | [
[
"torch.ones",
"torch.pow"
]
] |
MichielStock/SelectedTopicsOptimization | [
"069659ca9754cc7fd884b654a06157cc7da6f963",
"069659ca9754cc7fd884b654a06157cc7da6f963"
] | [
"Chapters/10.Bioinspired/peptide_optimization.py",
"Chapters/05.OptimalTransport/color_transfer.py"
] | [
"# -*- coding: utf-8 -*-\n\"\"\"\nCreated on Wed Apr 27 2016\nLast update Thu Jun 9 2016\n\n@author: michielstock\n\nOptimizing a peptide using hill climbing, simulated annealing and genetic\nalgorithms\n\"\"\"\n\nimport numpy as np\nfrom random import choice, shuffle\nimport matplotlib.cm as cm\nimport matplotlib.... | [
[
"numpy.exp",
"numpy.random.rand"
],
[
"numpy.minimum",
"numpy.arange",
"matplotlib.pyplot.subplots",
"matplotlib.pyplot.savefig",
"numpy.concatenate",
"sklearn.cluster.MiniBatchKMeans",
"sklearn.metrics.pairwise.pairwise_distances"
]
] |
kyle0x54/medvision | [
"a634208fe9b2dff13e54b28fa024a31328a78431"
] | [
"medvision/dicom/io.py"
] | [
"import os\nfrom pathlib import Path\nimport re\nimport shutil\nfrom typing import Union\nimport uuid\nimport medvision as mv\nimport numpy as np\nimport pydicom\nimport SimpleITK as itk\n\n\ndef dcmread(\n path: Union[str, Path],\n read_header: bool = False,\n itk_handler_enabled: bool = True\n):\n \"\... | [
[
"numpy.squeeze"
]
] |
epochml/kinect_eye_tracking | [
"109ebd7e3ce95c4c6bbc8af14efbc491e57f17f5"
] | [
"test_files/getting_frames_without_ano_obj.py"
] | [
"#!/usr/bin/env python\nimport freenect\nimport cv2\nimport numpy as np\n\n\nthreshold = 100\ncurrent_depth = 0\n\ndef change_threshold(value):\n global threshold\n threshold = value\n\n\ndef change_depth(value):\n global current_depth\n current_depth = value\n\n\ndef show_depth():\n global threshold... | [
[
"numpy.logical_and"
]
] |
aleksandar-zivkovic/ros_autonomous_car | [
"40c4946ac5ba5ad9e3863162370c8d1d8a073209"
] | [
"catkin_ws/src/car_interface/scripts/camera_detect_color.py"
] | [
"# import the necessary packages\nfrom picamera.array import PiRGBArray\nfrom picamera import PiCamera\nimport time\nimport cv2\nimport numpy as np\n \n# initialize the camera and grab a reference to the raw camera capture\ncamera = PiCamera()\ncamera.resolution = (640, 480)\ncamera.framerate = 50\ncamera.hflip = T... | [
[
"numpy.array"
]
] |
ronaldosvieira/torcedores-calma | [
"2e5981dff22144a8b60495382ce46d4d28f30d07"
] | [
"src/main.py"
] | [
"import numpy as np\nimport pandas as pd\nimport math, os\nimport matplotlib.pyplot as plt\nimport matplotlib.ticker as ticker\nfrom scipy.optimize import curve_fit\nfrom collections import defaultdict\nplt.style.use('seaborn-whitegrid')\n\nfrom scipy import stats\nfrom sklearn.impute import SimpleImputer\n\ndef re... | [
[
"numpy.matrix",
"matplotlib.pyplot.legend",
"pandas.concat",
"pandas.read_csv",
"numpy.rint",
"sklearn.impute.SimpleImputer",
"matplotlib.pyplot.subplots",
"matplotlib.pyplot.ylabel",
"matplotlib.pyplot.bar",
"pandas.DataFrame.from_dict",
"numpy.exp",
"matplotlib.py... |
DevranCanikli/imsafe | [
"b5f97a39fe4e7393ea0b497254655c44bb872b63"
] | [
"api/encryption/ImageEncryption.py"
] | [
"from api.util import Utility as Util\nimport base64\nfrom PIL import Image\nimport cv2\nfrom io import StringIO, BytesIO\nimport numpy as np\n\nclass ImageEncryption:\n\n @staticmethod\n def readb64(base64_string):\n sbuf = BytesIO()\n sbuf.write(base64.b64decode(base64_string))\n pimg =... | [
[
"numpy.array"
]
] |
essamhassan/trinity | [
"26adfde72fab1e362304d97856658937010d5521"
] | [
"basic.py"
] | [
"import matplotlib\nimport matplotlib.pyplot as plt\nimport matplotlib.ticker as mticker\nimport matplotlib.dates as mdates\nimport numpy as np\nimport time\n\nglobalStartTime = time.time()\n\n\n\ndate, bid, ask = np.loadtxt('GBPUSD1d.txt', unpack=True,\n delimiter = ',', converters={0:mdates.strpdate2num('%... | [
[
"matplotlib.pyplot.gca",
"matplotlib.dates.DateFormatter",
"matplotlib.dates.strpdate2num",
"matplotlib.pyplot.plot",
"matplotlib.pyplot.grid",
"matplotlib.pyplot.subplots_adjust",
"matplotlib.pyplot.show",
"matplotlib.pyplot.subplot2grid",
"matplotlib.pyplot.figure"
]
] |
cbjuan/aihwkit | [
"3109c7d0a8c256c22f2272648e15cc2c60c80392",
"3109c7d0a8c256c22f2272648e15cc2c60c80392"
] | [
"tests/test_layers_linear.py",
"examples/04_lenet5_training.py"
] | [
"# -*- coding: utf-8 -*-\n\n# (C) Copyright 2020, 2021 IBM. All Rights Reserved.\n#\n# This code is licensed under the Apache License, Version 2.0. You may\n# obtain a copy of this license in the LICENSE.txt file in the root directory\n# of this source tree or at http://www.apache.org/licenses/LICENSE-2.0.\n#\n# An... | [
[
"torch.nn.Sequential",
"torch.Tensor",
"torch.manual_seed",
"torch.nn.Linear",
"numpy.testing.assert_array_almost_equal"
],
[
"matplotlib.pyplot.legend",
"torch.max",
"torch.utils.data.DataLoader",
"matplotlib.pyplot.plot",
"torch.no_grad",
"torch.cuda.is_available"... |
AlbertYoung0112/segmentation_models.pytorch | [
"bc067141850366d59fb6e4f7ecb9b831dfebd13e"
] | [
"segmentation_models_pytorch/decoders/fpn/decoder.py"
] | [
"import torch\nimport torch.nn as nn\nimport torch.nn.functional as F\nfrom segmentation_models_pytorch.utils.functional import grad_logger\n\n\nclass Conv3x3GNReLU(nn.Module):\n def __init__(self, in_channels, out_channels, upsample=False):\n super().__init__()\n self.upsample = upsample\n ... | [
[
"torch.nn.Sequential",
"torch.nn.Dropout2d",
"torch.cat",
"torch.nn.Conv2d",
"torch.nn.functional.interpolate",
"torch.nn.GroupNorm",
"torch.nn.ReLU"
]
] |
milandesai/incubator-mxnet | [
"3051c49e3454df3b5f8909d3d76c6213d13539ad"
] | [
"tests/python/mkl/test_mkldnn.py"
] | [
"# Licensed to the Apache Software Foundation (ASF) under one\n# or more contributor license agreements. See the NOTICE file\n# distributed with this work for additional information\n# regarding copyright ownership. The ASF licenses this file\n# to you under the Apache License, Version 2.0 (the\n# \"License\"); y... | [
[
"numpy.random.uniform",
"numpy.random.normal",
"numpy.ones"
]
] |
SimuJenni/Correspondences | [
"384c0272e438ad3e7c936f5ae78fe6154b188c54",
"384c0272e438ad3e7c936f5ae78fe6154b188c54"
] | [
"models/AlexNet_self_sim.py",
"datasets/dataset_utils.py"
] | [
"import tensorflow as tf\nimport tensorflow.contrib.slim as slim\nfrom layers import conv_group\n\n\ndef alexnet_argscope(activation=tf.nn.relu, kernel_size=(3, 3), padding='SAME', training=True, center=True,\n w_reg=0.0001, fix_bn=False):\n \"\"\"Defines default parameter values for all the... | [
[
"tensorflow.concat",
"tensorflow.reduce_sum",
"tensorflow.contrib.slim.l2_regularizer",
"tensorflow.contrib.slim.flatten",
"tensorflow.contrib.layers.variance_scaling_initializer",
"tensorflow.nn.top_k",
"tensorflow.square",
"tensorflow.matmul",
"tensorflow.gather_nd",
"ten... |
Awni00/3d-object-classification | [
"ca287f27a66fdce5abc2e2e9814abae9528d6aff"
] | [
"models/rgbd_model_run29.py"
] | [
"import os\nimport pathlib\n\nimport numpy as np\nimport tensorflow as tf\nimport tensorflow_hub as hub\nfrom tensorflow.keras.layers import (Concatenate, Convolution2D, Dense,\n Dropout, Flatten, GlobalAveragePooling2D,\n GlobalMaxPooling2D, I... | [
[
"tensorflow.keras.layers.Concatenate",
"tensorflow.keras.layers.Dense",
"tensorflow.keras.Model",
"tensorflow.keras.layers.Convolution2D",
"numpy.float",
"tensorflow.keras.layers.Dropout",
"tensorflow.keras.layers.MaxPooling2D",
"tensorflow.keras.layers.Flatten",
"tensorflow.ke... |
andrewsoong/wrf_hydro_gis_preprocessor | [
"e5fba95aba83a90f64b380e61e63f89d69e0e990"
] | [
"wrfhydro_gis/Forecast_Point_Tools.py"
] | [
"# *=*=*=*=*=*=*=*=*=*=*=*=*=*=*=*=*=*=*=*=*=*=*=*=*=*=*=*=*=*=*=*=*=*=*=*=*=*=*=\n# Copyright UCAR (c) 2019\n# University Corporation for Atmospheric Research(UCAR)\n# National Center for Atmospheric Research(NCAR)\n# Research Applications Laboratory(RAL)\n# P.O.Box 3000, Boulder, Colorado, 80307-3000, USA\n# 24/0... | [
[
"numpy.empty",
"numpy.dtype"
]
] |
davidstutz/disentangling-robustness-generalization | [
"220ff8a79a5f08665f4755dc76d4e592ae66c6d6"
] | [
"training/attack_classifier_distal.py"
] | [
"import os\nimport sys\nsys.path.insert(1, os.path.dirname(os.path.realpath(__file__)) + '/../')\nfrom common import utils\nimport models\nfrom common.log import log, Log, LogLevel\nfrom common.state import State\nfrom common import cuda\nfrom common import paths\nimport common.torch\nimport common.numpy\nimport ma... | [
[
"numpy.expand_dims",
"numpy.ones",
"numpy.max",
"numpy.any",
"numpy.zeros",
"numpy.random.randint"
]
] |
JoseFilipeFerreira/AdventOfCode | [
"bb689d2da65ac483dc83e433a683be90d0231315"
] | [
"2018/6/6.py"
] | [
"import numpy\nimport operator\n\ndef main():\n with open(\"input.txt\", 'r') as file:\n file = file.read()\n file = file.split(\"\\n\")\n file = file[:-1]\n\n points = []\n for line in file:\n i = line.split(',')\n x = int(i[0]) \n ... | [
[
"numpy.zeros"
]
] |
falbav/Image-Analysis-San-Salvador | [
"c2cb2a27ffed3b134ceb329d9358563d374bddd9"
] | [
"ImageAnalysisSanSalvadorCNN.py"
] | [
"\"\"\"\r\nThis code explores Different Models of Convolutional Neural Networks\r\nfor the San Salvador Gang Project\r\n@author: falba and ftop\r\n\"\"\"\r\nimport os\r\nimport google_streetview.api\r\nimport pandas as pd\r\nimport numpy as np\r\nimport sys\r\n\r\nimport matplotlib.image as mp_img\r\nfrom matplotli... | [
[
"matplotlib.pyplot.legend",
"pandas.read_csv",
"matplotlib.pyplot.title",
"numpy.reshape",
"sklearn.model_selection.train_test_split",
"matplotlib.pyplot.plot",
"matplotlib.pyplot.subplot",
"numpy.ravel",
"matplotlib.pyplot.show"
]
] |
knowledgetechnologyuhh/goal_conditioned_RL_baselines | [
"915fc875fd8cc75accd0804d99373916756f726e",
"915fc875fd8cc75accd0804d99373916756f726e",
"915fc875fd8cc75accd0804d99373916756f726e"
] | [
"baselines/logger.py",
"plot/plot_ac_net.py",
"baselines/herhrl/rollout.py"
] | [
"import os\nimport sys\nimport shutil\nimport os.path as osp\nimport json\nimport time\nimport datetime\nimport tempfile\nfrom collections import defaultdict\n\nDEBUG = 10\nINFO = 20\nWARN = 30\nERROR = 40\n\nDISABLED = 50\n\nclass KVWriter(object):\n def writekvs(self, kvs):\n raise NotImplementedError\n... | [
[
"tensorflow.python.util.compat.as_bytes",
"pandas.read_csv",
"tensorflow.train.summary_iterator",
"pandas.DataFrame"
],
[
"matplotlib.pyplot.legend",
"numpy.nanmedian",
"numpy.concatenate",
"matplotlib.pyplot.plot",
"numpy.max",
"numpy.mean",
"numpy.iinfo",
"num... |
tgisaturday/pytorch-lightning | [
"ecc7ea4d425cdeadf8a25dc572c278e9c157e07d"
] | [
"tests/loops/test_closure.py"
] | [
"# Copyright The PyTorch Lightning team.\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n# http://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless required by applicable law... | [
[
"torch.tensor"
]
] |
franalli/CS221 | [
"a03755c35813f58b4be9fabd14865747f25dbbd1"
] | [
"feature_extraction_CNN.py"
] | [
"#copyright: https://github.com/aqibsaeed/Urban-Sound-Classification/blob/master/Urban%20Sound%20Classification%20using%20NN.ipynb\r\n\r\nimport glob\r\nimport os\r\nimport librosa\r\nimport librosa.display\r\nimport numpy as np\r\nimport matplotlib.pyplot as plt\r\nfrom matplotlib.pyplot import specgram\r\nfrom IP... | [
[
"numpy.expand_dims",
"numpy.array",
"numpy.zeros",
"numpy.vstack"
]
] |
uc-cdis/ncov | [
"acf5865f5ffc37b69b5f4d429f3a5806ad97ec63"
] | [
"gen3-augur/tests/test_combine_df.py"
] | [
"\"\"\"Test gen3_augur_pyutils.common.combine_df module\"\"\"\n\nimport unittest\n\nimport pandas as pd\nfrom pandas.testing import assert_frame_equal\n\nfrom gen3_augur_pyutils.common.combine_df import merge_multiple_columns\n\n\nclass TestCombine(unittest.TestCase):\n def test_combine_df(self):\n left_d... | [
[
"pandas.testing.assert_frame_equal",
"pandas.DataFrame"
]
] |
patrick-wilken/sockeye | [
"5144d25e6af3ca45baa33eb2c5c1ce7369364c61"
] | [
"test/unit/test_utils.py"
] | [
"# Copyright 2017 Amazon.com, Inc. or its affiliates. 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. A copy of the License\n# is located at\n#\n# http://aws.amazon.com/apache2.0/\n#\n# or in the \"l... | [
[
"numpy.asarray",
"numpy.random.rand",
"numpy.random.uniform",
"numpy.zeros",
"numpy.isclose"
]
] |
SARScripts/openeo_odc_driver | [
"c5c8f0cdf687c9e4e57797e2b0158a92b7862963"
] | [
"odc_wrapper.py"
] | [
"# coding=utf-8\n# Author: Claus Michele - Eurac Research - michele (dot) claus (at) eurac (dot) edu\n# Date: 10/05/2021\n\nimport datacube\nimport numpy as np\nimport copy\nfrom datetime import datetime\nimport shapely\nfrom shapely.geometry import shape\n#libraries for polygon and polygon mask\nimport fiona\nim... | [
[
"numpy.min",
"numpy.datetime64",
"numpy.timedelta64",
"numpy.max",
"numpy.bitwise_and"
]
] |
ZLCao/photon_correlation | [
"02cd285cfb0be8ca694638f4009e1b2faf641c64"
] | [
"python/photon_correlation/G2.py"
] | [
"import csv\nimport fractions\nimport statistics\n\nimport matplotlib.pyplot as plt\n\nfrom .GN import GN\nfrom .util import *\n\nt3_center = (-0.5, 0.5)\nt3_side = (0.5, 1.5)\n\nclass G2_T3(GN):\n @property\n def time_resolution(self):\n corr = next(iter(self._counts.keys()))\n return(numpy.dif... | [
[
"matplotlib.pyplot.figure"
]
] |
lstoltz/ooi-data-explorations | [
"83ffb39c71e91bf720aca5465556a8928f66174f"
] | [
"python/ooi_data_explorations/uncabled/process_nutnr.py"
] | [
"#!/usr/bin/env python\n# -*- coding: utf-8 -*-\nimport datetime\nimport numpy as np\nimport os\n\nfrom ooi_data_explorations.common import inputs, m2m_collect, m2m_request, get_deployment_dates, \\\n get_vocabulary, update_dataset, dict_update, ENCODINGS\n\n# load configuration settings\nATTRS = {\n 'spectru... | [
[
"numpy.isnan",
"numpy.datetime64"
]
] |
drewszurko/tensorflow | [
"e6785ff6cc9c0dfe688c3ab7c22d27134de75368"
] | [
"tensorflow/python/keras/engine/training_eager.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.python.keras.utils.losses_utils.scale_loss_for_distribution",
"tensorflow.python.platform.tf_logging.warning",
"tensorflow.python.keras.utils.losses_utils.squeeze_or_expand_dimensions",
"tensorflow.python.keras.backend.name_scope",
"tensorflow.python.ops.math_ops.add_n",
"tenso... |
kylegilde/feature_engine | [
"39bc2ff328d7b2eecba0e5d385d603a39992b092"
] | [
"feature_engine/transformation/yeojohnson.py"
] | [
"# Authors: Soledad Galli <solegalli@protonmail.com>\n# License: BSD 3 clause\n\nfrom typing import List, Optional, Union\n\nimport pandas as pd\nimport scipy.stats as stats\n\nfrom feature_engine.base_transformers import BaseNumericalTransformer\nfrom feature_engine.variable_manipulation import _check_input_parame... | [
[
"scipy.stats.yeojohnson"
]
] |
uibcdf/Modelo_infeccion | [
"f6ce28d199fe0713b9b175ab0174db5c0d894a89"
] | [
"examples/Talk/EpiModel.py"
] | [
"### −∗− mode : python ; −∗−\n# @file EpiModel.py\n# @author Bruno Goncalves\n######################################################\n\nimport networkx as nx\nimport numpy as np\nimport scipy.integrate\nimport pandas as pd\nimport matplotlib.pyplot as plt\n\nclass EpiModel(object):\n \"\"\"Simple Epidemic Model ... | [
[
"numpy.arange",
"numpy.sum",
"matplotlib.pyplot.gcf"
]
] |
godspeed1989/self-supervised-depth-completion | [
"1d4b3e45f1d2d5c35c1a4a4efb094dd384e9ae39"
] | [
"dataloaders/kitti_loader.py"
] | [
"import os\nimport os.path\nimport glob\nimport fnmatch # pattern matching\nimport numpy as np\nfrom numpy import linalg as LA\nfrom random import choice\nfrom PIL import Image\nimport torch\nimport torch.utils.data as data\nimport cv2\nfrom dataloaders import transforms\nfrom dataloaders.pose_estimator import get... | [
[
"numpy.expand_dims",
"numpy.eye",
"numpy.linalg.norm",
"numpy.max",
"numpy.random.binomial",
"numpy.random.uniform",
"numpy.array",
"numpy.zeros"
]
] |
mfkiwl/py-pde | [
"d127784fd0db7d04dde5a9cc7ef18afb5f04d151"
] | [
"tests/performance_boundaries.py"
] | [
"#!/usr/bin/env python3\n\"\"\"\nThis script tests the performance of the implementation of different boundary conditions\n\"\"\"\n\nimport sys\nfrom pathlib import Path\n\nPACKAGE_PATH = Path(__file__).resolve().parents[1]\nsys.path.append(str(PACKAGE_PATH))\n\nimport numpy as np\n\nfrom pde import ScalarField, Un... | [
[
"numpy.ones"
]
] |
Samorodowv/naiveslam | [
"6c09ff2416a32c0b1eee92a0b605a6a946cb47f9"
] | [
"naiveslam/helpers.py"
] | [
"import os\nimport numpy as np\n\n# https://github.com/MagicLeapResearch/SuperPointPretrainedNetwork/blob/master/demo_superpoint.py\nmyjet = np.array([[0. , 0. , 0.5 ],\n [0. , 0. , 0.99910873],\n [0. , 0.37843137, 1. ],\n ... | [
[
"numpy.diag",
"numpy.dot",
"numpy.linalg.svd",
"numpy.abs",
"numpy.sqrt",
"numpy.arange",
"numpy.eye",
"numpy.ones",
"numpy.linalg.det",
"numpy.bitwise_xor",
"numpy.array",
"numpy.zeros",
"numpy.sum",
"numpy.mat"
]
] |
hahaxun/PyTorch-BigGraph | [
"daed286bc3f7b843fb9fec2f6e2b8e4a1d3c89c3"
] | [
"torchbiggraph/converters/importers.py"
] | [
"#!/usr/bin/env python3\n\n# Copyright (c) Facebook, Inc. and its affiliates.\n# All rights reserved.\n#\n# This source code is licensed under the BSD-style license found in the\n# LICENSE.txt file in the root directory of this source tree.\n\nimport datetime\nimport random\nimport time\nimport pandas as pd\nimport... | [
[
"torch.tensor"
]
] |
qwertyflagstop/qwertyflagtext | [
"74eb2521886f62d21aa5f6dd306feaa0aba70f60"
] | [
"reddit.py"
] | [
"import numpy as np\nimport requests\n\nclass PushShift(object):\n\n def __init__(self, subreddit):\n super(PushShift, self).__init__()\n self.api_base = 'https://api.pushshift.io/reddit/search/submission/'\n self.sub = subreddit\n self.fp = 'trainTexts/{}.txt'.format(subreddit)\n ... | [
[
"numpy.arange"
]
] |
geligeli/rpi_color_detector | [
"e00b6939633ac3d92987aad7ef9ae21b84d5ea69"
] | [
"classifier/image_provider.py"
] | [
"#!/usr/bin/env python3\n\nimport argparse\nimport glob\nimport itertools\nimport os\nimport shutil\n\nimport tensorflow as tf\n\nAUTOTUNE = tf.data.AUTOTUNE\n\n\nclass ImageProvider():\n def __init__(self):\n self.IMAGES_BASE_DIR = '/nfs/general/shared/images'\n\n def safePath(self, p):\n p = o... | [
[
"tensorflow.constant",
"tensorflow.saved_model.load",
"tensorflow.image.crop_to_bounding_box",
"tensorflow.io.decode_jpeg",
"tensorflow.cast",
"tensorflow.io.read_file",
"tensorflow.argmax",
"tensorflow.TensorSpec"
]
] |
nicohrubec/trends_3d_resnet | [
"4cad56dfb49f63a768179eda19bcaf57a487658e"
] | [
"src/resnet.py"
] | [
"import torch\nimport torch.nn as nn\nimport torch.nn.functional as F\nfrom torch.autograd import Variable\nimport math\nfrom functools import partial\n\n__all__ = [\n 'resnet10', 'resnet18'\n]\n\ndef conv3x3x3(in_planes, out_planes, stride=1, dilation=1):\n # 3x3x3 convolution with padding\n return nn.Con... | [
[
"torch.nn.Sequential",
"torch.cat",
"torch.nn.functional.adaptive_avg_pool3d",
"torch.nn.MaxPool3d",
"torch.nn.Conv3d",
"torch.nn.Linear",
"torch.nn.functional.avg_pool3d",
"torch.nn.ReLU",
"torch.nn.BatchNorm3d",
"torch.nn.init.kaiming_normal_"
]
] |
ozgurdoganbirol/stepwisereg | [
"e32daa6f1050fa351032f92aa4a62a3855a230ec"
] | [
"StepwiseRegressionRsquared.py"
] | [
"#Required libraries\r\nimport numpy as np\r\nimport pandas as pd\r\nfrom sklearn.linear_model import LinearRegression\r\nfrom sklearn.metrics import r2_score, mean_squared_error\r\nfrom sklearn.model_selection import train_test_split\r\nimport scipy\r\nfrom IPython.display import display\r\n\r\n#data: Pandas dataf... | [
[
"sklearn.metrics.r2_score",
"sklearn.model_selection.train_test_split",
"pandas.DataFrame",
"sklearn.metrics.mean_squared_error",
"numpy.mean",
"sklearn.linear_model.LinearRegression",
"numpy.sum"
]
] |
Avighan/handwriting-ocr | [
"9731e4f5462a585d9b56218718bfb3a7023e2e1f"
] | [
"ocr/page.py"
] | [
"# -*- coding: utf-8 -*-\n\"\"\"\nCrop background and transform perspective from the photo of page\n\"\"\"\nimport numpy as np\nimport cv2\nfrom .helpers import *\n\ndef detection(image):\n \"\"\" Finding Page \"\"\"\n # Edge detection\n imageEdges = edgesDet(image, 200, 250)\n \n # Close gaps betwee... | [
[
"numpy.linalg.norm",
"numpy.ones",
"numpy.argmax",
"numpy.argmin",
"numpy.diff",
"numpy.array"
]
] |
X-CCS/mandarin_tacotron2_lpcnet | [
"92a955b2a9b9b360ba25b03beaa88eee90f39703"
] | [
"tacotron/models/Architecture_wrappers.py"
] | [
"\"\"\"A set of wrappers usefull for tacotron 2 architecture\nAll notations and variable names were used in concordance with originial tensorflow implementation\n\"\"\"\nimport collections\n\nimport numpy as np\nimport tensorflow as tf\nfrom tacotron.models.attention import _compute_attention\nfrom tensorflow.contr... | [
[
"tensorflow.python.ops.tensor_array_ops.TensorArray",
"tensorflow.python.framework.tensor_shape.TensorShape",
"tensorflow.concat",
"tensorflow.zeros",
"tensorflow.python.ops.check_ops.assert_equal",
"tensorflow.python.ops.array_ops.zeros",
"tensorflow.python.ops.array_ops.identity"
]... |
TobiasKoopmann/cobert | [
"279fc6ce938a81afa2b8f14e4cb20b13f842ff48",
"279fc6ce938a81afa2b8f14e4cb20b13f842ff48"
] | [
"util/create_dataset.py",
"util/analyse_dataset.py"
] | [
"import os\nimport json\nimport torch\nimport tqdm\nimport copy\nimport random\nimport multiprocessing\nimport numpy as np\nfrom collections import defaultdict\nfrom functools import partial\nfrom util.PaperEmbeddings import calculate_embeddings, init\n\n\ndef create_dataset(papers_path_old: str, paper_embedding_pa... | [
[
"numpy.array",
"numpy.zeros",
"numpy.random.choice",
"torch.tensor"
],
[
"pandas.DataFrame"
]
] |
SIMES-Aerospace-Research-Group/EMA | [
"605b767e304367715fe041719e9bdc1c3bfad8b3"
] | [
"modules/SHARP_PM10.py"
] | [
"import wiringpi\nfrom numpy import median\n\nclass sharpPM10:\n def __init__(self, led_pin, pm10_pin, adc, sampling_time=280, delta_time=40, sleep_time=9680):\n if led_pin is None:\n raise ValueError('led pin number is missing!')\n if pm10_pin is None:\n raise ValueError('pm1... | [
[
"numpy.median"
]
] |
uvchik/windpowerlib | [
"a338694a84e373ec2c2d0f2ac5a3037d4a1c0d0c"
] | [
"windpowerlib/power_output.py"
] | [
"\"\"\"\nThe ``power_output`` module contains functions to calculate the power output\nof a wind turbine.\n\nSPDX-FileCopyrightText: 2019 oemof developer group <contact@oemof.org>\nSPDX-License-Identifier: MIT\n\"\"\"\nimport numpy as np\nimport pandas as pd\n\n\ndef power_coefficient_curve(wind_speed, power_coeffi... | [
[
"numpy.array",
"numpy.interp",
"pandas.Series",
"numpy.power"
]
] |
konny0311/deep-learning-from-scratch | [
"590a547ca5613140dcef3d88af628ca5d171eb1b",
"590a547ca5613140dcef3d88af628ca5d171eb1b"
] | [
"myTrial/stepFunction.py",
"myTrial/trainNeuralNet.py"
] | [
"import numpy as np\nimport matplotlib.pylab as plt\n\ndef step_function(x):\n return np.array(x > 0, dtype = np.int)\n\nx = np.arange(-1.0, 4.0, 0.1)\ny = step_function(x)\nplt.plot(x,y)\nplt.ylim(-0.1,1.1)\nplt.show()\n",
"import sys, os\nsys.path.append(os.pardir)\nimport numpy as np\nimport matplotlib.pypl... | [
[
"matplotlib.pylab.show",
"numpy.arange",
"matplotlib.pylab.plot",
"matplotlib.pylab.ylim",
"numpy.array"
],
[
"matplotlib.pyplot.legend",
"numpy.random.choice",
"matplotlib.pyplot.ylim",
"matplotlib.pyplot.plot",
"matplotlib.pyplot.xlabel",
"matplotlib.pyplot.show",... |
KM3NeT/km3pipe | [
"e27df0ceea02bcb26d128494a4e1d6a55e2f2e54"
] | [
"km3pipe/tests/test_stats.py"
] | [
"# Filename: test_stats.py\n# pylint: disable=locally-disabled,C0111,R0904,C0103\n\nimport numpy as np\nfrom numpy.random import RandomState\nfrom pandas import DataFrame\nimport pytest\n\nfrom km3pipe.testing import TestCase\nfrom km3pipe.stats import mad, mad_std, drop_zero_variance, perc, bincenters\n\n__author_... | [
[
"numpy.linspace",
"numpy.random.seed",
"pandas.DataFrame",
"numpy.random.normal",
"numpy.array"
]
] |
Song655/arlo | [
"cee1613d4a2b2e1263da9d5b4b9930eef569509c",
"cee1613d4a2b2e1263da9d5b4b9930eef569509c"
] | [
"arl-python/arl/image/operations.py",
"arl-python/arl/image/deconvolution.py"
] | [
"\n#\n\"\"\"\nFunctions that define and manipulate images. Images are just data and a World Coordinate System.\n\"\"\"\n\nimport numpy\nimport copy\nimport warnings\n\nfrom astropy.io import fits\nfrom astropy.coordinates import SkyCoord\nfrom astropy.wcs import WCS\nfrom reproject import reproject_interp\n\nfrom a... | [
[
"numpy.polyfit",
"numpy.max",
"numpy.zeros_like",
"numpy.polyval",
"numpy.ones_like",
"numpy.arange",
"numpy.std",
"numpy.real",
"numpy.zeros",
"matplotlib.pyplot.figure",
"matplotlib.pyplot.title",
"numpy.min",
"numpy.power",
"numpy.median",
"numpy.arra... |
ihalage/AIMat | [
"5c0b8ff85afacdcd85177ead3e91c086bab487d0"
] | [
"sintering_run.py"
] | [
"import os\nimport pandas as pd\nimport pickle\nimport numpy as np\nfrom sklearn.ensemble import RandomForestRegressor\nfrom sklearn.model_selection import GridSearchCV\nfrom sklearn.metrics import mean_squared_error\nfrom sklearn.model_selection import train_test_split\n\nfrom sklearn.pipeline import Pipeline\nfro... | [
[
"sklearn.preprocessing.StandardScaler",
"pandas.read_csv",
"sklearn.model_selection.train_test_split"
]
] |
Onoddil/photutils | [
"433f3e54d3f53282ae04eadde9e1ddf657944590",
"433f3e54d3f53282ae04eadde9e1ddf657944590"
] | [
"photutils/utils/tests/test_random_state.py",
"photutils/background/background_2d.py"
] | [
"# Licensed under a 3-clause BSD style license - see LICENSE.rst\n\"\"\"\nTests for the random_state module.\n\"\"\"\n\nimport warnings\n\nfrom astropy.utils.exceptions import AstropyDeprecationWarning\nimport numpy as np\nimport pytest\n\nfrom .. import check_random_state\n\n\n@pytest.mark.parametrize('seed', [Non... | [
[
"numpy.random.RandomState"
],
[
"numpy.zeros_like",
"numpy.ma.is_masked",
"numpy.where",
"matplotlib.pyplot.gca",
"numpy.pad",
"numpy.ma.count_masked",
"scipy.ndimage.zoom",
"numpy.atleast_1d",
"numpy.copy",
"numpy.asanyarray",
"numpy.column_stack",
"numpy.r... |
mnguy3n/Berkeley_RL_Course_HW_1 | [
"bbc7eb372d937c8742467d1b1d81683c22800962"
] | [
"hw1/dagger.py"
] | [
"#!/usr/bin/env python\n\n\"\"\"\nCode to load an expert policy and generate roll-out data for behavioral cloning.\nExample usage:\n python3 dagger.py experts/RoboschoolHumanoid-v1.py --render \\\n --num_rollouts 20\n\"\"\"\n\nimport argparse\nimport pickle\nimport tensorflow as tf\nimport numpy as np... | [
[
"tensorflow.Graph",
"tensorflow.matmul",
"tensorflow.constant",
"tensorflow.truncated_normal",
"tensorflow.zeros",
"tensorflow.placeholder",
"tensorflow.global_variables_initializer",
"numpy.std",
"tensorflow.nn.l2_loss",
"numpy.mean",
"tensorflow.train.GradientDescentO... |
SudaTakeru/recomend_system | [
"7f9d31db18188a961562078c9bb02d585662fec6"
] | [
"rsys_by_suda/NeighborCF.py"
] | [
"# -*- coding: utf-8 -*-\r\n\"\"\"\r\nCreated on Sat Oct 6 17:05:48 2018\r\n\r\n@author: buryu-\r\n\r\n\"\"\"\r\nimport numpy as np\r\n\r\nclass NeighborCF:\r\n \r\n def __init__(self,Matrix,t=1,k1=1):\r\n # ExpandedNeighbor Collaborative Filtering:t=2\r\n self.Matrix = Matrix\r\n self.t... | [
[
"numpy.dot",
"numpy.ones",
"numpy.argsort",
"numpy.zeros",
"numpy.sum"
]
] |
junyuchen245/TransMorph_Transformer_for_Medical_Image_Registration | [
"dfa24a47a564a000aa9b4eea95a6e83a24568359",
"dfa24a47a564a000aa9b4eea95a6e83a24568359"
] | [
"RaFD/TransMorph2D/models/TransMorph_bspl.py",
"TransMorph/models/TransMorph.py"
] | [
"'''\r\nBSpline TransMorph\r\n\r\nJunyu Chen\r\njchen245@jhmi.edu\r\nJohns Hopkins University\r\n'''\r\n\r\nimport math\r\nimport torch\r\nfrom torch import nn as nn\r\nfrom torch.nn import functional as F\r\nimport models.transformation as transformation\r\nimport models.TransMorph as TM\r\nimport models.configs_T... | [
[
"torch.cat",
"torch.nn.ModuleList",
"torch.nn.init.kaiming_uniform_",
"torch.nn.AvgPool2d",
"torch.nn.LeakyReLU",
"torch.nn.functional.interpolate"
],
[
"torch.nn.Softmax",
"torch.cat",
"torch.zeros",
"torch.sin",
"torch.nn.functional.interpolate",
"torch.flatte... |
Cebtenzzre/cebnn | [
"9b6037c195e0b0eadd6ddade7f5ea5f0c10070fc"
] | [
"losses.py"
] | [
"# From https://github.com/dougbrion/pytorch-classification-uncertainty/blob/06fb2f6/losses.py\n# SPDX-License-Identifier: MIT\n\nfrom __future__ import annotations\n\nfrom functools import partial\nfrom typing import TYPE_CHECKING\n\nimport torch\nfrom torch import nn\nfrom torch.nn import functional as F\n\nif TY... | [
[
"torch.mean",
"torch.ones",
"torch.digamma",
"torch.sum",
"torch.tensor",
"torch.lgamma"
]
] |
myamada0321/pyCFM | [
"98a4e4aff4b2d36b72bc0e417d9df5247a4bc6a9"
] | [
"pyCFM.py"
] | [
"import numpy as np\nimport scipy.sparse as sp\nfrom scipy.sparse.linalg import LinearOperator\n\n\nclass CFM:\n \"\"\" Convex Factorization Machine with Hazan's algorithm (squared loss)\n Yamada, M. et. al., http://arxiv.org/abs/1507.01073\n\n\n Model:\n\n f(x;w,W) = w^t z + 0.5 trace(W (xx^t - dia... | [
[
"numpy.dot",
"numpy.sum",
"numpy.sqrt",
"scipy.sparse.linalg.cg",
"numpy.ones",
"numpy.real",
"numpy.mean",
"scipy.sparse.linalg.LinearOperator",
"numpy.array",
"numpy.zeros",
"scipy.sparse.linalg.eigsh"
]
] |
niyati-bhayani/greyatom-python-for-data-science | [
"2ef7378eaccb8316710f95e687394a959b3fb555"
] | [
"Manipulating-Census-Data-with-NumPY/code.py"
] | [
"# --------------\n# Importing header files\r\nimport numpy as np\r\n\r\n# Path of the file has been stored in variable called 'path'\r\ndata = np.genfromtxt(path, delimiter = \",\", skip_header = 1)\r\n\r\n#New record\r\nnew_record = [[50, 9, 4, 1, 0, 0, 40, 0]]\r\n\r\ncensus = np.concatenate((data, new_reco... | [
[
"numpy.concatenate",
"numpy.std",
"numpy.mean",
"numpy.genfromtxt"
]
] |
Kri-Ol/ProtonBub | [
"476949da8fd9545d22098bc92c4839750d0cbf3d"
] | [
"read_dose_out.py"
] | [
"#!/usr/bin/env python3\n\nimport numpy as np\nfrom mpl_toolkits.mplot3d import Axes3D\nimport matplotlib.pyplot as plt\n\nX = 0\nY = 1\nZ = 2\n\ndef read_phantom_head(fname):\n \"\"\"\n Given filename, read and parse phantom header file\n\n return voxels and dimensions\n \"\"\"\n\n lines = None\n ... | [
[
"numpy.float32",
"matplotlib.pyplot.show",
"numpy.zeros",
"numpy.empty",
"matplotlib.pyplot.figure"
]
] |
SamuelLRapp/data-analytics | [
"339844f96de8884b16530ccba5511425ee484c81"
] | [
"get-qualify-export-donor-data/qualify-data/qualify-data.py"
] | [
"#!/usr/bin/env python3\n# -*- coding: utf-8 -*-\n\"\"\"\ndescription: Qualify Tidepool datasets\nversion: 0.0.1\ncreated: 2018-02-21\nauthor: Ed Nykaza\ndependencies:\n *\nlicense: BSD-2-Clause\nTODO:\n* [] some of the todo-list moved to readme file\n* [] make saving the metadata optional, and by default to no\... | [
[
"pandas.concat",
"pandas.read_csv",
"pandas.to_datetime",
"pandas.merge",
"pandas.DatetimeIndex",
"pandas.DataFrame",
"pandas.Timedelta",
"pandas.date_range"
]
] |
SinaMostafanejad/MolSSI_project_FSHXF | [
"b6eb024b82b3d9c99f1458c93dfbc64afd6eaa23"
] | [
"thermostat.py"
] | [
"from __future__ import division\nfrom misc import eps, au_to_K, call_name, fs_to_au, cm_to_au\nimport textwrap\nimport numpy as np\n\n# In a model example, a specific routine should be devised separately.\nclass Thermostat(object):\n \"\"\" Object class for a thermostat. The type of given thermostat is classifi... | [
[
"numpy.exp",
"numpy.zeros",
"numpy.sqrt",
"numpy.ones"
]
] |
TomGoBravo/covid-data-model | [
"089e4e81db32befd6e86e4e105454629fd834ad2"
] | [
"pyseir/inference/fit_results.py"
] | [
"import os\nfrom pyseir.load_data import load_county_metadata\nfrom pyseir import OUTPUT_DIR\nimport pandas as pd\nfrom datetime import datetime\nfrom pyseir.utils import get_run_artifact_path, RunArtifact\n\n\ndef load_t0(fips):\n \"\"\"\n Load the simulation start time by county.\n\n Parameters\n ----... | [
[
"pandas.read_pickle",
"pandas.read_json"
]
] |
EitanTal/PyJigsaw | [
"db107bbb224c0d5ddd3c6d384ba19000e44f512f"
] | [
"2000/jigsaw2000.py"
] | [
"import numpy as np\nimport sys\nimport matplotlib.pyplot as plt\nimport matplotlib.image as mpimg\nfrom cv2 import cv2\n\nworkdir = r'C:\\jigsaw\\data\\2000\\npz'\n\n\ndef rotate(l, n):\n return l[n:] + l[:n]\n\t\ndef rotate_p(l, n):\n\tresult = l\n\tfor _ in range(n):\n\t\tresult = rotate_one(result)\n\treturn... | [
[
"matplotlib.pyplot.get_cmap",
"numpy.copy",
"numpy.savez_compressed",
"numpy.load",
"numpy.array",
"matplotlib.pyplot.show"
]
] |
XingangPan/GAN2Shape | [
"1c9b0480710212e1fe86ab75dcf0b30bd9f654e7"
] | [
"gan2shape/stylegan2/stylegan2-pytorch/lpips/__init__.py"
] | [
"\nfrom __future__ import absolute_import\nfrom __future__ import division\nfrom __future__ import print_function\n\nimport numpy as np\nimport torch\nfrom torch.autograd import Variable\n\nfrom lpips import dist_model\n\nclass PerceptualLoss(torch.nn.Module):\n def __init__(self, model='net-lin', net='alex', co... | [
[
"numpy.maximum",
"numpy.arange",
"torch.sum",
"numpy.concatenate",
"numpy.max",
"numpy.mean",
"numpy.prod",
"numpy.transpose",
"numpy.where",
"numpy.sum",
"numpy.isclose"
]
] |
Dhug95/MCLNN-tensorflow | [
"2a5f0ed4b96160ae089e66ee283a416021308048"
] | [
"MCLNN_MAIN.py"
] | [
"\"\"\"\nMasked ConditionaL Neural Networks (MCLNN)\n\"\"\"\nfrom __future__ import print_function\n\nimport keras as k\n\nprint(k.__version__)\n\nimport datetime\nimport gc\nimport glob\nimport os\nimport shutil\nimport tensorflow as tf\nfrom tensorflow.python import debug as tf_debug\nimport keras\nimport numpy a... | [
[
"tensorflow.summary.FileWriter",
"numpy.random.seed",
"numpy.asarray",
"numpy.arange",
"numpy.squeeze",
"sklearn.metrics.confusion_matrix",
"numpy.append",
"numpy.argmax",
"numpy.bincount",
"tensorflow.get_default_graph",
"sklearn.metrics.f1_score",
"numpy.zeros",
... |
laitoch/tree-bark-synthesis | [
"0bd43d6699d2e05f62d144f310874f986bbd91d2",
"0bd43d6699d2e05f62d144f310874f986bbd91d2"
] | [
"tree_bark_synthesis/TextureByNumbers/texture_by_numbers.py",
"tree_bark_synthesis/TextureByNumbers/init/edge_detector.py"
] | [
"import numpy as np\nfrom scipy.ndimage import imread\nfrom PIL import Image\n\nfrom image_pyramid import *\nfrom optimize import *\nfrom init.generate_initial_output import *\nfrom init.random_init import *\n\ndef tbn(ai\n , height_map=None\n , fdm=None\n , a=None\n , b=None\n , output_siz... | [
[
"numpy.concatenate"
],
[
"scipy.ndimage.filters.correlate",
"numpy.array",
"numpy.ndenumerate"
]
] |
Prajwal-Prathiksh/Museum-Path-Optimization | [
"f30a09e315544f64a38f74819fc23e5a8edbb6d3"
] | [
"code/branch_and_bound/time_opti.py"
] | [
"###########################################################################\n# In main directory\n# Usage: '$ python code/branch_and_bound/time_opti.py'\n#\n# Check '$ python code/branch_and_bound/time_opti.py -h' for help\n###########################################################################\n# Imports\n###... | [
[
"numpy.array",
"numpy.ones"
]
] |
app2147/molssi_best_practices_2021 | [
"3b504e9fcffaad94d1b98d163d8d1849879be3ed"
] | [
"molecool/visualize.py"
] | [
"'''\r\nFunctions for molecule visualization.\r\n'''\r\n\r\nimport numpy as np \r\nimport matplotlib.pyplot as plt\r\n\r\nfrom mpl_toolkits.mplot3d import Axes3D\r\n\r\nfrom .atom_data import atom_colors\r\n\r\n\r\ndef draw_molecule(coordinates, symbols, draw_bonds=None, save_location=None, dpi=300):\r\n \r\n ... | [
[
"numpy.linspace",
"matplotlib.pyplot.figure",
"matplotlib.pyplot.savefig",
"matplotlib.pyplot.xlabel",
"numpy.array",
"matplotlib.pyplot.ylabel"
]
] |
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