repo_name stringlengths 6 130 | hexsha list | file_path list | code list | apis list |
|---|---|---|---|---|
latonaio/detect-abnormal-set-of-temperatures | [
"e5cda1156e23f77f0feb16b56e3624807592fafb"
] | [
"src/detect-abnormal-temps/calc_temperature.py"
] | [
"# coding: utf-8\n\n# Copyright (c) 2019-2020 Latona. All rights reserved.\n\nimport os\nimport sys\n\ntry:\n from aion.logger import lprint\nexcept:\n lprint = print\n\nimport numpy as np\nimport cv2\n\n# CONST PARAMETER\nDETECT_ABNORMAL_RATIO = 0.3\nABNORMAL_THRESHOLD_BASE = 38\nABASE = ABNORMAL_THRESHOLD_B... | [
[
"numpy.count_nonzero",
"numpy.loadtxt",
"numpy.interp"
]
] |
yimingchen95/veidt | [
"90f201f856d2f71c578f74b7391c0c9ff284986b"
] | [
"veidt/rfxas/tests/test_core.py"
] | [
"\nfrom veidt.rfxas.core import XANES\nfrom veidt.rfxas.prediction import CenvPrediction\nimport pandas as pd\nimport os, unittest\nimport warnings\n\ncomp_test_df_path = os.path.join(os.path.dirname(__file__), 'comp_spectra_test.pkl')\ncomp_test_df = pd.read_pickle(comp_test_df_path)\nFe_tsv = os.path.join(os.path... | [
[
"pandas.read_pickle"
]
] |
AurelianTactics/rl-baselines3-zoo | [
"ef8f7350108568a8b199efa56a24eba2f104db54"
] | [
"utils/exp_manager.py"
] | [
"import argparse\nimport os\nimport time\nimport warnings\nfrom collections import OrderedDict\nfrom pprint import pprint\nfrom typing import Any, Callable, Dict, List, Optional, Tuple\n\nimport gym\nimport numpy as np\nimport optuna\nimport yaml\nfrom optuna.integration.skopt import SkoptSampler\nfrom optuna.prune... | [
[
"numpy.ones",
"numpy.zeros"
]
] |
jonathanfrawley/PyAutoArray_copy | [
"c21e8859bdb20737352147b9904797ac99985b73",
"c21e8859bdb20737352147b9904797ac99985b73"
] | [
"test_autoarray/structures/grids/two_d/test_sparse_util.py",
"test_autoarray/inversion/test_regularization.py"
] | [
"import autoarray as aa\r\nimport os\r\n\r\nimport numpy as np\r\n\r\n\r\nclass TestUnmaskedSparseForSparse:\r\n def test__mask_full_false__image_mask_and_pixel_centres_fully_overlap__each_sparse_maps_to_unmaked_sparse(\r\n self,\r\n ):\r\n\r\n ma = aa.Mask2D.manual(\r\n mask=np.array... | [
[
"numpy.array"
],
[
"numpy.array"
]
] |
zhuzhenyuan/uiautomator2 | [
"87da38153c05823ba8ccfadc9ba9ae6d22d97fd8"
] | [
"uiautomator2/ext/perf/__init__.py"
] | [
"# coding: utf-8\n#\n\nfrom __future__ import absolute_import, print_function\n\nimport threading\nimport re\nimport time\nimport datetime\nimport csv\nimport sys\nimport atexit\nfrom collections import namedtuple\n\n_MEM_PATTERN = re.compile(r'TOTAL[:\\s]+(\\d+)')\n# acct_tag_hex is a socket tag\n# cnt_set==0 are ... | [
[
"matplotlib.pyplot.gca",
"matplotlib.pyplot.xlabel",
"matplotlib.pyplot.ylim",
"matplotlib.pyplot.plot",
"matplotlib.pyplot.legend",
"matplotlib.ticker.NullFormatter",
"matplotlib.pyplot.ylabel",
"matplotlib.pyplot.clf",
"pandas.read_csv",
"matplotlib.pyplot.subplot"
]
] |
pevdh/openpilot | [
"fca82ba503a663ec97b7ba89c2c3da80aef739b2"
] | [
"selfdrive/debug/internal/design_lqr.py"
] | [
"#!/usr/bin/env python3\nimport numpy as np\nimport control\n\ndt = 0.01\nA = np.array([[ 0. , 1. ], [-0.78823806, 1.78060701]])\nB = np.array([[-2.23399437e-05], [ 7.58330763e-08]])\nC = np.array([[1., 0.]])\n\n\n# Kalman tuning\nQ = np.diag([1, 1])\nR = np.atleast_2d(1e5)\n\n(_, _, L) ... | [
[
"numpy.array",
"numpy.diag",
"numpy.atleast_2d"
]
] |
rohankumardubey/npx | [
"3dc43cbf765a748f5197286ed70f5cbccf11e2bf"
] | [
"tests/test_unique.py"
] | [
"import numpy as np\n\nimport npx\n\n\ndef test_unique_tol():\n a = [0.1, 0.15, 0.7]\n\n a_unique = npx.unique(a, 2.0e-1)\n print(a_unique)\n assert np.all(a_unique == [0.1, 0.7])\n\n a_unique, inv = npx.unique(a, 2.0e-1, return_inverse=True)\n assert np.all(a_unique == [0.1, 0.7])\n assert np.... | [
[
"numpy.all"
]
] |
jakeybob/brexit-maps | [
"649479d9e9a0eaf94599d73844ca0d44eee4bd75"
] | [
"plot4.py"
] | [
"import matplotlib.pyplot as plt\nimport numpy as np\nimport pandas as pd\nimport mapMisc as mapMisc\nfrom sklearn import cluster\nimport fiona\nimport matplotlib.patches as patches\nfrom matplotlib.lines import Line2D\n\n\nGBRshpfile = 'data/boundaryline/district_borough_unitary_region.shp'\nNIshpfile = 'data/OSNI... | [
[
"matplotlib.pyplot.savefig",
"sklearn.cluster.KMeans",
"numpy.shape",
"matplotlib.pyplot.figure",
"numpy.argsort",
"pandas.concat",
"numpy.unique"
]
] |
thieu1995/permetrics | [
"b00ff1786a765e88006fd2a695fbdf342191cc6b",
"b00ff1786a765e88006fd2a695fbdf342191cc6b"
] | [
"examples/regression/SMAPE.py",
"permetrics/singleloss.py"
] | [
"#!/usr/bin/env python\n# ------------------------------------------------------------------------------------------------------%\n# Created by \"Thieu Nguyen\" at 11:01, 19/07/2020 %\n# ... | [
[
"numpy.array"
],
[
"numpy.isnan",
"numpy.log",
"numpy.round",
"numpy.any",
"numpy.isfinite",
"numpy.abs"
]
] |
carlogrisetti/ludwig | [
"5c0887f14867e1577e0ddc3806c5cf7a781fb665"
] | [
"ludwig/features/set_feature.py"
] | [
"#! /usr/bin/env python\n# coding=utf-8\n# Copyright (c) 2019 Uber Technologies, Inc.\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n# http://www.apache.org/licenses/LICENS... | [
[
"torch.greater_equal",
"torch.sigmoid",
"torch.Size"
]
] |
elias-1/NiftyNet | [
"05cd2ffbff5043d9a40b524a6d72f6bd5cd072d2"
] | [
"niftynet/layer/crop.py"
] | [
"# -*- coding: utf-8 -*-\nfrom __future__ import absolute_import, print_function\n\nimport numpy as np\nimport tensorflow as tf\n\nfrom niftynet.layer import layer_util\nfrom niftynet.layer.base_layer import Layer\n\n\nclass CropLayer(Layer):\n \"\"\"\n This class defines a cropping operation:\n Removing `... | [
[
"tensorflow.concat",
"tensorflow.expand_dims",
"tensorflow.constant",
"tensorflow.nn.convolution",
"numpy.hstack",
"tensorflow.unstack"
]
] |
Taghurei/DreamBackend | [
"ca73adb19010f8ac3a12156659066730128883ab"
] | [
"Backend/src/FunctionML.py"
] | [
"import pandas as pd\nimport matplotlib.pyplot as plt\nimport numpy as np\nfrom sklearn import ensemble\nfrom sklearn import metrics\nfrom statistics import mean\n\ndef etudeRelationSigne(df_knockouts,df_wildtype,v=.12):\n m = len(df_knockouts.values)\n mat = np.zeros((m,m))\n\n for i in range(m):\n ... | [
[
"numpy.sign",
"numpy.zeros"
]
] |
mesnardo/petibm-rollingpitching | [
"39f7ed9b88973727bed6955e31d99754d7627c9f"
] | [
"runs/independence/scripts/plot_velocity_profiles_compare_dx_dt.py"
] | [
"\"\"\"Plot profiles of the velocity at different locations in the x direction.\"\"\"\n\nfrom matplotlib import pyplot\nimport pathlib\n\nimport rodney\n\n\ndef get_velocity_profiles(datadir,config, time, xlocs):\n \"\"\"Get the velocity profiles at given time and x locations.\"\"\"\n profiles = {'u': {'locs'... | [
[
"matplotlib.pyplot.show",
"matplotlib.pyplot.subplots",
"matplotlib.pyplot.rc"
]
] |
michaelriedl/alpha-transform | [
"add5818b168551cb0c2138c65101c9cdac2bf3d9",
"add5818b168551cb0c2138c65101c9cdac2bf3d9"
] | [
"alpha_transform/MotherShearlets.py",
"alpha_transform/__init__.py"
] | [
"#!/usr/bin/env python3\nr\"\"\"\nThe classes, functions and objects in this module make it (comparatively)\neasy to define custom generating functions which act as \"Mother shearlets\".\n\n.. warning::\n Implementing custom \"Mother shearlets\" is a complex task and thus should\n only be done if really neede... | [
[
"numpy.greater_equal",
"numpy.less_equal",
"numpy.abs",
"numpy.greater"
],
[
"numpy.true_divide",
"numpy.load",
"numpy.min",
"numpy.broadcast_to",
"numpy.max",
"numpy.linalg.norm",
"numpy.empty",
"numpy.prod",
"numpy.arange",
"numpy.sqrt",
"numpy.isf... |
semperparatusalpha/Restaurant-chatbot | [
"6b01a9395ff08873d3f0572edd09db8d7aac9d2b"
] | [
"helper_scripts/tsne_visualizer.py"
] | [
"from sklearn.manifold import TSNE\nimport json\nimport numpy as np\nfrom sklearn.cluster import KMeans\n\n# embedded data has fasttext vectors of the sentences\nwith open(\"embedded_data_short.json\") as file:\n data = json.load(file)\n\nX = []\n\nfor intent in data['intents']:\n\n for pattern in intent['pat... | [
[
"numpy.array",
"sklearn.cluster.KMeans"
]
] |
HEXRD/hexrdgui | [
"d92915463f237e0521b5830655ae73bc5bcd9f80"
] | [
"hexrd/ui/overlays/rotation_series.py"
] | [
"import numpy as np\n\nfrom hexrd import constants\n\nfrom hexrd.ui.constants import ViewType\n\n\nclass RotationSeriesSpotOverlay:\n def __init__(self, plane_data, instr,\n crystal_params=None,\n eta_ranges=None,\n ome_ranges=None,\n ome_period=Non... | [
[
"numpy.array",
"numpy.tile",
"numpy.degrees",
"numpy.hstack",
"numpy.linspace"
]
] |
harisankarh/NeMo | [
"27bfb1aed24a786626e1c27c37417ebcd226ca8a",
"27bfb1aed24a786626e1c27c37417ebcd226ca8a"
] | [
"collections/nemo_nlp/nemo_nlp/callbacks/joint_intent_slot.py",
"collections/nemo_nlp/nemo_nlp/data/datasets/token_classification.py"
] | [
"# Copyright (c) 2019 NVIDIA Corporation\nimport os\nimport random\nimport time\n\nimport matplotlib\nfrom matplotlib import pyplot as plt\nimport numpy as np\nfrom sklearn.metrics import confusion_matrix, classification_report\n\nfrom nemo.utils.exp_logging import get_logger\nmatplotlib.use(\"TkAgg\")\n\n\nlogger ... | [
[
"matplotlib.use",
"sklearn.metrics.confusion_matrix",
"numpy.asarray",
"matplotlib.pyplot.xlabel",
"matplotlib.pyplot.title",
"matplotlib.pyplot.figure",
"sklearn.metrics.classification_report",
"matplotlib.pyplot.ylabel"
],
[
"numpy.array"
]
] |
aschwa/happy_city_tweets | [
"80a240492860a6cda48f75b825cb0b54cc369c8b"
] | [
"src/scripts/label_park_tweets/park_split_s.py"
] | [
"#!/usr/bin/env python\n# -*- coding: utf-8 -*-\nimport json\nimport argparse\nfrom pathlib import Path\nimport geopandas as gpd\nimport pandas as pd\nfrom shapely.geometry import Point\nfrom geopandas.tools import sjoin\nfrom pyproj import Proj, transform\n\n\ndef parse_args():\n parser = argparse.ArgumentParse... | [
[
"pandas.read_json"
]
] |
amulyahwr/acl2018 | [
"53521950397f79e47738bb7177ad664b7dce38e5"
] | [
"treelstm_dep_attn/mda/main.py"
] | [
"from __future__ import division\nfrom __future__ import print_function\n\nimport os\nimport random\nimport logging\n\nimport torch.optim as optim\n\n# IMPORT CONSTANTS\nimport Constants\n# NEURAL NETWORK MODULES/LAYERS\nfrom model import *\n# DATA HANDLING CLASSES\nfrom tree import Tree\nfrom vocab import Vocab\n#... | [
[
"torch.optim.Adadelta",
"torch.optim.Adam",
"torch.optim.Adagrad",
"torch.optim.SGD"
]
] |
braysia/covertrace | [
"cb3f91964bd7b524eb10bfce972136eb921ab689"
] | [
"covertrace/utils/single_frame_cleaning.py"
] | [
"from __future__ import division\nimport numpy as np\nfrom collections import OrderedDict\nfrom covertrace.data_array import Sites, DataArray\n\ndef modify_prop(func):\n def wrapper(arr, **args):\n if isinstance(arr, OrderedDict):\n for key, value in arr.iteritems():\n bool_arr =... | [
[
"numpy.nanpercentile",
"numpy.max",
"numpy.expand_dims"
]
] |
leonbett/debuggingbook | [
"ae1fa940c306160429232fbc93a7a7f14b44efb7"
] | [
"notebooks/shared/ipypublish/scripts/ipynb_latex_setup.py"
] | [
"#!/usr/bin/env python\n\"\"\"\nSome setup for improved latex/pdf output\n\nat top of workbook, use\n\n from ipynb_latex_setup import *\n\n\"\"\"\n\nfrom __future__ import division as _division\n# Py2/Py3 compatibility\n# =====================\nfrom __future__ import print_function as _print_function\n\n# PYTHON... | [
[
"pandas.set_option"
]
] |
brigaldies/search_with_machine_learning_course | [
"ae55c88d0b22a396fe830a587a86aee11e66a366"
] | [
"week3/__init__.py"
] | [
"import os\n\nfrom flask import Flask\nfrom flask import render_template\nimport pandas as pd\nimport fasttext\nfrom pathlib import Path\n\ndef create_app(test_config=None):\n # create and configure the app\n app = Flask(__name__, instance_relative_config=True)\n \n if test_config is None:\n # lo... | [
[
"pandas.read_csv"
]
] |
FirefoxMetzger/ropy | [
"ee6f1d3451a3c61a6fa122cc42efc4dd67afc9c9"
] | [
"skbot/ignition/sdformat/generic_sdf/joint.py"
] | [
"import warnings\nfrom typing import List, Union, Dict, Any, Tuple\nfrom itertools import chain\nimport numpy as np\n\nfrom .base import (\n BoolElement,\n ElementBase,\n FloatElement,\n Pose,\n StringElement,\n vector3,\n should_warn_unsupported,\n)\nfrom .sensor import Sensor\nfrom .frame imp... | [
[
"numpy.clip"
]
] |
xiedotscene/Open3D | [
"483f6682d04e447a267d920bf48b9e3a91b56e7b"
] | [
"src/Python/Tutorial/Basic/rgbd_tum.py"
] | [
"# Open3D: www.open3d.org\n# The MIT License (MIT)\n# See license file or visit www.open3d.org for details\n\n#conda install pillow matplotlib\nfrom py3d import *\nimport matplotlib.pyplot as plt\n\n\nif __name__ == \"__main__\":\n\tprint(\"Read TUM dataset\")\n\tcolor_raw = read_image(\"../../TestData/RGBD/other_f... | [
[
"matplotlib.pyplot.imshow",
"matplotlib.pyplot.show",
"matplotlib.pyplot.title",
"matplotlib.pyplot.subplot"
]
] |
faezakamran/sentence-transformers | [
"2158fff3aa96651b10fe367c41fdd5008a33c5c6"
] | [
"examples/unsupervised_learning/query_generation/example_query_generation.py"
] | [
"import torch\nimport numpy as np\nimport random\nfrom transformers import T5Tokenizer, T5ForConditionalGeneration\n\n#Set all seeds to make output deterministic\ntorch.manual_seed(0)\nnp.random.seed(0)\nrandom.seed(0)\n\n\n#Paragraphs for which we want to generate queries\nparagraphs = [\n\"Python is an interprete... | [
[
"torch.manual_seed",
"torch.no_grad",
"torch.cuda.is_available",
"numpy.random.seed"
]
] |
anbasile/arxiv2018-bayesian-ensembles | [
"52e2741540ce0466666aaca9fe9dd148c144123a",
"52e2741540ce0466666aaca9fe9dd148c144123a"
] | [
"src/taggers/lample_lstm_tagger/optimization.py",
"src/experiments/EMNLP2019/error_analysis.py"
] | [
"import numpy as np\nimport theano\nimport theano.tensor as T\n\nfloatX = theano.config.floatX\ndevice = theano.config.device\n\n\nclass Optimization:\n\n def __init__(self, clip=None):\n \"\"\"\n Initialization\n \"\"\"\n self.clip = clip\n\n def get_gradients(self, cost, params):... | [
[
"numpy.float32",
"numpy.zeros"
],
[
"numpy.concatenate",
"numpy.array",
"numpy.zeros_like",
"numpy.savetxt",
"numpy.zeros",
"numpy.sum",
"numpy.genfromtxt",
"numpy.ones",
"numpy.where",
"numpy.arange",
"numpy.cumsum",
"numpy.in1d",
"numpy.argwhere",
... |
ruohoruotsi/nevergrad | [
"68ec2ebddcc388b0fea5bc274c6f7ef098e34589"
] | [
"nevergrad/benchmark/test_plotting.py"
] | [
"# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved.\n#\n# This source code is licensed under the MIT license found in the\n# LICENSE file in the root directory of this source tree.\n\nfrom . import plotting # pylint: disable=wrong-import-position, wrong-import-order\nfrom unittest.mock import ... | [
[
"matplotlib.use",
"numpy.testing.assert_equal",
"pandas.DataFrame",
"numpy.testing.assert_array_equal",
"numpy.identity"
]
] |
BenjaminMidtvedt/DeepTrack-2.0 | [
"64245f31e63011fb48d38f211134774bbce28cf4"
] | [
"deeptrack/benchmarks/test_image.py"
] | [
"import sys\nimport numpy as np\nimport itertools\nimport deeptrack as dt\nimport pytest\nimport itertools\nimport cupy as cp\n\nu = dt.units\n\n\ndef create_pipeline(elements=1024):\n value = dt.Value(np.zeros((elements,)))\n value = value + 14\n value = value * (np.ones((elements,)) * 2)\n value = val... | [
[
"numpy.ones",
"numpy.random.randn",
"numpy.zeros"
]
] |
jiahuei/tf-sparse-captioning | [
"9d7b8ecdd44fb1541500ca4f920d6c94fd15bad1"
] | [
"common/nets/i3d_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 required... | [
[
"tensorflow.argmax",
"tensorflow.random_uniform",
"tensorflow.Graph",
"tensorflow.test.main",
"tensorflow.global_variables_initializer"
]
] |
jurajHasik/peps-torch | [
"bc5068b2026e670a2795fc3fc060a3313bc1e3fb"
] | [
"optim/ad_optim.py"
] | [
"import time\nimport json\nimport logging\nlog = logging.getLogger(__name__)\nimport torch\n#from memory_profiler import profile\nimport config as cfg\n\ndef store_checkpoint(checkpoint_file, state, optimizer, current_epoch, current_loss,\\\n verbosity=0):\n r\"\"\"\n :param checkpoint_file: target file\n ... | [
[
"torch.optim.LBFGS",
"torch.load"
]
] |
match4healthcare/match4healthcare | [
"acf69e3b781d715f0a947c2a9df6646e94f1ca6b"
] | [
"backend/apps/accounts/views_staff.py"
] | [
"from django.contrib.admin.views.decorators import staff_member_required\nfrom django.contrib.auth.decorators import login_required\nfrom django.shortcuts import render\nimport matplotlib\nimport matplotlib.pyplot as plt\nfrom matplotlib.ticker import MaxNLocator\nimport mpld3\n\nfrom .db_stats import DataBaseStats... | [
[
"matplotlib.use",
"matplotlib.ticker.MaxNLocator",
"matplotlib.pyplot.subplots"
]
] |
miguelggaspar/neuronalFEM | [
"78e001b4306f39bf7e5d67361c67182a6a9b80e2"
] | [
"1D/dataset/functions.py"
] | [
"# function that returns [deps/dt, dX/dt, dR/dt]\nimport math\nimport numpy as np\nfrom scipy.integrate import odeint\n\n\nclass viscoPlastic1D:\n\n def __init__(self, K, n, H, D, h, d):\n self.K = K\n self.n = n\n self.H = H\n self.D = D\n self.h = h\n self.d = d\n\n# f... | [
[
"numpy.sign",
"scipy.integrate.odeint",
"numpy.empty_like"
]
] |
grantsrb/langpractice | [
"59cf8f53b85fa8b4d639ffc6e175ec22c0d2362c"
] | [
"langpractice/utils/analysis.py"
] | [
"import torch\nimport os\nimport pandas as pd\nimport langpractice.utils.save_io as lpio\nfrom tqdm import tqdm\n\ndef get_stats_dataframe(model_folders,\n names=None,\n incl_hyps=False,\n verbose=False):\n \"\"\"\n Sorts through all checkpo... | [
[
"pandas.DataFrame"
]
] |
morrislab/plos-medicine-joint-patterns | [
"cfdc6dd4854ec33e7e2efbf36d648b65d278df33"
] | [
"scripts/validation_projections/compare_frequencies.py"
] | [
"\"\"\"\nCompares frequencies between the validation and discovery cohorts.\n\nFor each patient group, the Euclidean distance is used.\n\"\"\"\n\nimport numpy as np\nimport pandas as pd\n\nfrom click import *\nfrom logging import *\n\n\n@command()\n@option(\n '--validation-input',\n required=True,\n help='... | [
[
"pandas.read_csv"
]
] |
kshitijd20/pyrsa | [
"3090d88362b26e6b2ee807e62d483a0158530e2a"
] | [
"tests/test_inference.py"
] | [
"#!/usr/bin/env python3\n# -*- coding: utf-8 -*-\n\"\"\"\nCreated on Fri Jan 10 10:00:26 2020\n\n@author: heiko\n\"\"\"\n\nimport unittest\nimport numpy as np\n\n\nclass TestBootstrap(unittest.TestCase):\n \"\"\" bootstrap tests\n \"\"\"\n\n def test_bootstrap_sample(self):\n from pyrsa.inference im... | [
[
"numpy.all",
"numpy.array",
"numpy.random.rand"
]
] |
noabauma/Mirheo | [
"bf7979bfbbf402d33c26ac5dc879f880e78e7017"
] | [
"tests/ic/uniform.py"
] | [
"#!/usr/bin/env python\n\nimport numpy as np\nimport mirheo as mir\nimport argparse\n\nparser = argparse.ArgumentParser()\nparser.add_argument(\"--domain\", type=float, nargs=3, default=[4., 2., 3.])\nargs = parser.parse_args()\n\nranks = (1, 1, 1)\ndomain = args.domain\ndensity = 8\n\nu = mir.Mirheo(ranks, tuple(... | [
[
"numpy.savetxt"
]
] |
yuleiniu/introd | [
"a40407c7efee9c34e3d4270d7947f5be2f926413"
] | [
"css/dataset.py"
] | [
"from __future__ import print_function\r\nfrom __future__ import unicode_literals\r\n\r\nimport os\r\nimport json\r\nimport cPickle\r\nfrom collections import Counter\r\n\r\nimport numpy as np\r\nimport utils\r\nimport h5py\r\nimport torch\r\nfrom torch.utils.data import Dataset\r\nfrom tqdm import tqdm\r\nfrom ran... | [
[
"torch.zeros",
"numpy.array",
"torch.from_numpy"
]
] |
coreyauger/daytrader-utils | [
"cdb5b4b7f32e75814486a8e186a8fd9b35dfd8a7"
] | [
"label_dist.py"
] | [
"\nimport numpy as np\nimport os\nimport dtdata as dt\nfrom sklearn.neighbors import NearestNeighbors\nfrom sklearn.decomposition import PCA\nimport matplotlib.pyplot as plt\nimport seaborn as sns\nsns.set(color_codes=True)\n\nplt.rcParams['interactive'] == True\n\n# fix random seed for reproducibility\nnp.random.s... | [
[
"numpy.random.seed",
"matplotlib.pyplot.show",
"numpy.sort"
]
] |
lisc119/Soiling-Loss-Analysis | [
"979424a9b355a0ad6196492d105d1905844cd238"
] | [
"src/scripts/calc_gaps.py"
] | [
"import pandas as pd\n\nimport matplotlib.pyplot as plt\nimport seaborn as sns\n\n# Get times that fall within one SD of mean in distribution\ndef get_1sd_times(df_std, sd = 1):\n mean = df_std.mean()\n lb = mean - (df_std.std() * sd)\n ub = mean + (df_std.std() * sd)\n try: \n temp = df_std.to_f... | [
[
"matplotlib.pyplot.show",
"matplotlib.pyplot.style.use",
"matplotlib.pyplot.subplots",
"pandas.Series"
]
] |
LiGuihong/Capsule | [
"c445f7d5f4357e4d60ea87fe64865192ba051023"
] | [
"main_v2.py"
] | [
"import os\nimport sys\nimport numpy as np\nimport tensorflow as tf\nfrom tqdm import tqdm\n\nfrom config import cfg\nfrom utils import load_data\nfrom capsNet import CapsNet\n\n\ndef save_to():\n if not os.path.exists(cfg.results):\n os.mkdir(cfg.results)\n if cfg.is_training:\n loss = cfg.resu... | [
[
"numpy.isnan",
"tensorflow.train.latest_checkpoint",
"tensorflow.train.Supervisor",
"tensorflow.logging.info",
"tensorflow.contrib.tfprof.ProfileContext",
"tensorflow.ConfigProto",
"tensorflow.app.run"
]
] |
Ynjxsjmh/Tensorflow-2-Reinforcement-Learning-Cookbook | [
"aa27bbbcc532e5e8b239aa019c3ca1e0bc2cf059"
] | [
"Chapter06/2_call_to_action_agent.py"
] | [
"#!/usr/bin/env python\n# Agent training script for completing call-to-action tasks on websites\n# Chapter 6, TensorFlow 2 Reinforcement Learning Cookbook | Praveen Palanisamy\n\nimport argparse\nimport os\nfrom datetime import datetime\n\nimport gym\nimport numpy as np\nimport tensorflow as tf\nfrom tensorflow.ker... | [
[
"tensorflow.keras.models.Model",
"tensorflow.keras.layers.Dense",
"numpy.mean",
"tensorflow.clip_by_value",
"tensorflow.keras.initializers.he_normal",
"tensorflow.keras.backend.set_floatx",
"numpy.zeros_like",
"numpy.random.normal",
"tensorflow.GradientTape",
"tensorflow.ma... |
youdar/work | [
"d5f32015e7be1d58ede255eeadbd1d12acb3f270"
] | [
"work/Clashes/Old work/clash_draw.py"
] | [
"from __future__ import division\nimport numpy as nm\nimport matplotlib.pyplot as plt\n\nclass draw_circle(object):\n def __init__(self,x,y,r,col,opt):\n '''\n \n '''\n theta = range(start=0, stop=nm.pi, step=0.1)\n \n \n \ndef run():\n fig = plt.figure()\n ... | [
[
"matplotlib.pyplot.ylim",
"matplotlib.pyplot.xlim",
"matplotlib.pyplot.figure"
]
] |
2010019970909/design_of_experiments | [
"72030c2916f938637c86302b311eab25dd52cbe3"
] | [
"src/design_of_experiments.py"
] | [
"\"\"\"\nThe aim of this script is to automate some process in\nthe Design of experiments (DoE) workflow.\n\"\"\"\n__author__ = \"Vincent STRAGIER\"\n\n# Maths modules\nfrom itertools import permutations, combinations\nfrom scipy.special import erfinv\nimport numpy as np\n\n# Plotting module\nimport matplotlib.pypl... | [
[
"numpy.array",
"numpy.dot",
"matplotlib.pyplot.subplots",
"numpy.multiply",
"numpy.arange",
"scipy.special.erfinv",
"numpy.abs",
"numpy.sqrt",
"matplotlib.pyplot.show",
"numpy.log2"
]
] |
yuanyuan0057/ReAgent | [
"b43ceca1fe83458e2f7ea1cf8d9c447cddb7f202"
] | [
"reagent/training/c51_trainer.py"
] | [
"#!/usr/bin/env python3\n# Copyright (c) Facebook, Inc. and its affiliates. All rights reserved.\n\nfrom typing import List\n\nimport reagent.types as rlt\nimport torch\nfrom reagent.core.configuration import resolve_defaults\nfrom reagent.core.dataclasses import field\nfrom reagent.optimizer import Optimizer__Unio... | [
[
"torch.no_grad",
"torch.linspace",
"torch.full_like",
"torch.zeros_like",
"torch.argmax"
]
] |
HFTshoon/deep-learning-from-scratch | [
"c7c85abb33fbb710f055daec6d2c31322401fa02"
] | [
"exercise/ch04/loss_functions.py"
] | [
"import numpy as np\n\ndef sum_squares_error(y,t):\n\treturn 0.5*np.sum((y-t)**2)\n\n\"\"\"\ndef cross_entropy_error(y,t)\n\tdelta=1e-7\n\treturn -np.sum(t*np.log(y+delta))\n\"\"\"\n\ndef cross_entropy_error(y,t):\n\tif y.ndim==1:\n\t\tt=t.reshape(1,t.size)\n\t\ty=y.reshape(1,y.size)\n\n\tbatch_size=y.shape[0]\n\td... | [
[
"numpy.sum",
"numpy.arange"
]
] |
VectorInstitute/DANER | [
"2b5feadda6c1d35ab7be09277339c490396bc49e"
] | [
"backend/models/huggingface_model.py"
] | [
"from typing import List\nfrom copy import deepcopy\n\nimport spacy\nimport torch\n\nuse_cuda = torch.cuda.is_available()\nDEFAULT_LABEL = ['O', 'B-PER', 'I-PER', 'B-ORG',\n 'I-ORG', 'B-LOC', 'I-LOC', 'B-MISC', 'I-MISC']\nBIO_MAP = {\n \"B\": 3,\n \"I\": 1,\n \"O\": 2\n}\n\nnlp = spacy.load... | [
[
"torch.cuda.is_available"
]
] |
aribornstein/ignite-learning-paths | [
"cb7415d3bb26d8e6dbda1cf94c4e78578130f97a"
] | [
"aiml/aiml21/code/explore.py"
] | [
"#!/usr/bin/env python\n# coding: utf-8\n\n# # Explore Dataset \n\n# We will explore the **data_train.csv dataset** from the Tailwind Traders support team department. \n# \n# This is historical data about the features of each support ticket submitted. This data could unlock insights to help the support team become ... | [
[
"matplotlib.pyplot.xlabel",
"matplotlib.pyplot.pie",
"matplotlib.pyplot.figure",
"matplotlib.pyplot.hist",
"numpy.sort",
"matplotlib.pyplot.ylabel",
"matplotlib.pyplot.axis",
"matplotlib.pyplot.show",
"pandas.read_csv",
"matplotlib.pyplot.bar",
"matplotlib.pyplot.xticks... |
Therealchainman/Algorithms-for-Automated-Driving | [
"dfa55498e5ab6e26307b5e1ce8fce695fb4e6ec5"
] | [
"code/util/carla_util.py"
] | [
"import carla\r\nimport pygame\r\n\r\nimport queue\r\nimport numpy as np\r\n\r\ndef carla_vec_to_np_array(vec):\r\n return np.array([vec.x,\r\n vec.y,\r\n vec.z])\r\n\r\nclass CarlaSyncMode(object):\r\n \"\"\"\r\n Context manager to synchronize output from different ... | [
[
"numpy.array",
"numpy.reshape",
"numpy.dtype"
]
] |
IPL-UV/LatentGranger | [
"78d25621f94f338c3c1957a216679c94b2d9b764"
] | [
"explain.py"
] | [
"#!/usr/bin/env python3\n# -*- coding: utf-8 -*-\n\n# BSD 3-Clause License (see LICENSE file)\n# Copyright (c) Image and Signaling Process Group (ISP) IPL-UV 2021\n# All rights reserved.\n\n\"\"\"\nExplain latent space of LatentGranger\n\"\"\"\n\nimport os\nimport git\nimport numpy as np\nimport argparse, yaml\nfro... | [
[
"torch.zeros",
"numpy.zeros",
"torch.amax",
"numpy.mean",
"torch.amin",
"torch.std_mean",
"torch.mean",
"torch.reshape"
]
] |
kate-sann5100/tutorials | [
"49e78ffeb7b0a473c9a74112ee4020610c5659e7",
"49e78ffeb7b0a473c9a74112ee4020610c5659e7"
] | [
"3d_classification/ignite/densenet_training_dict.py",
"modules/engines/gan_training.py"
] | [
"# Copyright 2020 MONAI Consortium\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n# http://www.apache.org/licenses/LICENSE-2.0\n# Unless required by applicable law or agreed to i... | [
[
"numpy.array",
"torch.cuda.is_available",
"torch.nn.CrossEntropyLoss"
],
[
"torch.cuda.is_available",
"torch.nn.BCELoss",
"torch.nn.Sigmoid"
]
] |
DonnieKim411/apex | [
"fb00a5a1d569c7b118aa672b3dacac3663ca3911"
] | [
"apex/contrib/multihead_attn/fast_self_multihead_attn_norm_add_func.py"
] | [
"import torch\nfrom torch import nn\nfrom torch.nn import Parameter\nimport torch.nn.functional as F\nfrom torch.autograd.variable import Variable\n\nimport fast_self_multihead_attn_norm_add\n\nclass FastSelfAttnNormAddFunc(torch.autograd.Function) :\n @staticmethod\n def forward(ctx, use_time_mask, is_train... | [
[
"torch.tensor"
]
] |
garrett-yoon/amr-uti-stm | [
"440759e466ac9c31a2bbcea571aca3084fa44464"
] | [
"analysis_utils/best_case_baseline_utils.py"
] | [
"import pandas as pd\nimport os\nimport sys\n\nsys.path.append('../../')\nfrom models.indirect.policy_learning_thresholding import get_iat_broad\nfrom utils.evaluation_utils import calculate_ci\n\ndef get_best_case_idsa_baseline(resist_df,\n switch_props,\n ... | [
[
"pandas.DataFrame"
]
] |
yynst2/basenji | [
"6d7cc6e2fecade5cd9a66ab29452131dcb1d618e"
] | [
"bin/basenji_sad_ref.py"
] | [
"#!/usr/bin/env python\n# Copyright 2017 Calico LLC\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n# https://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless required by ap... | [
[
"numpy.concatenate",
"numpy.max",
"numpy.array",
"pandas.read_table",
"numpy.percentile",
"numpy.copy",
"tensorflow.Session",
"tensorflow.train.Saver",
"numpy.min",
"tensorflow.data.Dataset.from_generator",
"tensorflow.Dimension",
"numpy.arange",
"numpy.log2"
... |
Tak-Man/ML-rapid-text-labeling | [
"c5fa5439bfcd3ba652be1dfdd101831fbd02d9d4"
] | [
"web-testing/simulation_results/selenium recommended texts/007/web_automate2.py"
] | [
"# -*- coding: utf-8 -*-\n\"\"\"\nCreated on Sat Oct 23 08:58:37 2021\n\n@author: michp-ai\n\"\"\"\n\n# This script is web automation for the Capstone project on ML rapid text labeling\n# Before running this script in a different console start the web server by running main.py for the web app\n# This is a simple de... | [
[
"pandas.DataFrame",
"sklearn.metrics.accuracy_score"
]
] |
vsaase/dicom2nifti | [
"6722420a7673d36437e4358ce3cb2a7c77c91820"
] | [
"dicom2nifti/convert_siemens.py"
] | [
"# -*- coding: utf-8 -*-\n\"\"\"\ndicom2nifti\n\n@author: abrys\n\"\"\"\nimport os\nimport re\nimport traceback\n\nimport logging\nimport nibabel\nimport numpy\n\nfrom pydicom.tag import Tag\n\nimport dicom2nifti.common as common\nimport dicom2nifti.convert_generic as convert_generic\nfrom dicom2nifti.exceptions im... | [
[
"numpy.array",
"numpy.linalg.norm",
"numpy.dot",
"numpy.zeros",
"numpy.shape",
"numpy.transpose",
"numpy.cross"
]
] |
DinoMan/dino-tk | [
"b3937b816667f8c2d7bb0751a7107a6d78a222e1"
] | [
"dtk/metrics/image.py"
] | [
"from skimage.color import rgb2grey\nfrom scipy import fftpack\nimport numpy as np\nimport numpy.ma as ma\n\n\ndef _dict_divide_(dividends, divisors):\n ret = dict()\n for key, dividend in dividends.items():\n ret[key] = dividend / divisors.get(key, 1)\n return ret\n\n\ndef _get_hashable_key_(key):\... | [
[
"numpy.logical_or",
"scipy.fftpack.fftshift",
"numpy.sum",
"numpy.rollaxis",
"numpy.logical_and",
"numpy.ma.masked_array",
"numpy.abs",
"numpy.all",
"scipy.fftpack.fft2"
]
] |
tonyyang-svail/elasticdl | [
"f7d266cf600c7205d68f59447abd55eff222ac2b"
] | [
"elasticdl/python/common/model_handler.py"
] | [
"import abc\n\nimport numpy as np\nimport tensorflow as tf\nfrom tensorflow.python.feature_column import feature_column_v2 as fc_lib\n\nfrom elasticdl.python.common.constants import DistributionStrategy\nfrom elasticdl.python.common.log_utils import default_logger as logger\nfrom elasticdl.python.common.save_utils ... | [
[
"tensorflow.python.feature_column.feature_column_v2.embedding_column",
"numpy.zeros",
"tensorflow.keras.layers.DenseFeatures",
"tensorflow.keras.layers.Embedding",
"tensorflow.keras.backend.clear_session",
"tensorflow.keras.models.clone_model",
"tensorflow.keras.initializers.serialize"... |
QinganZhao/Introduction-to-Machine-Learning | [
"57edb519aaff3851e94c1917c9556180e0bb281a",
"57edb519aaff3851e94c1917c9556180e0bb281a"
] | [
"Boosting and CNN/CNN/viz_features.py",
"SVM and kNN/world_values_pipelines.py"
] | [
"from sklearn.metrics import confusion_matrix\nimport matplotlib.pyplot as plt\nimport random\nimport cv2\nimport IPython\nimport numpy as np\n\n\n\nclass Viz_Feat(object):\n\n\n def __init__(self,val_data,train_data, class_labels,sess):\n\n self.val_data = val_data\n self.train_data = train_data\n... | [
[
"numpy.array",
"numpy.zeros"
],
[
"sklearn.linear_model.Lasso",
"sklearn.preprocessing.StandardScaler",
"sklearn.neighbors.KNeighborsClassifier",
"sklearn.linear_model.Ridge",
"sklearn.preprocessing.RobustScaler",
"sklearn.svm.SVC",
"sklearn.tree.DecisionTreeClassifier",
... |
BrianTillman/captum | [
"edf41d31bd12bd38846b1214ade0ad897063a4d4"
] | [
"captum/insights/api.py"
] | [
"#!/usr/bin/env python3\nfrom collections import namedtuple\nfrom typing import Callable, Iterable, List, NamedTuple, Optional, Tuple, Union\n\nimport torch\nfrom captum.attr import IntegratedGradients\nfrom captum.attr._utils.batching import _batched_generator\nfrom captum.attr._utils.common import _run_forward, s... | [
[
"torch.norm",
"torch.tensor"
]
] |
RicardLake/FedDetection | [
"a4004593a4d07126447db73b98b53a7e56e0472b"
] | [
"experiments/distributed/detection/transforms.py"
] | [
"import torch\r\nimport torchvision\r\n\r\nfrom torch import nn, Tensor\r\nfrom torchvision.transforms import functional as F\r\nfrom torchvision.transforms import transforms as T\r\nfrom typing import List, Tuple, Dict, Optional\r\n\r\n\r\ndef _flip_coco_person_keypoints(kps, width):\r\n flip_inds = [0, 2, 1, 4... | [
[
"torch.rand",
"torch.jit.is_scripting",
"torch.randperm",
"torch.tensor"
]
] |
sarveshbhatnagar/sparse | [
"73d5a2f61da5ad45a501f37279c1784f65001dc3"
] | [
"sparse/tests/test_coo.py"
] | [
"import contextlib\nimport operator\nimport pickle\nimport sys\nfrom functools import reduce\n\nimport numpy as np\nimport pytest\nimport scipy.sparse\nimport scipy.stats\n\nimport sparse\nfrom sparse import COO\nfrom sparse._settings import NEP18_ENABLED\nfrom sparse._utils import assert_eq, random_value_array, ht... | [
[
"numpy.int8",
"numpy.isclose",
"numpy.random.rand",
"numpy.random.choice",
"numpy.copy",
"numpy.resize",
"numpy.where",
"numpy.outer",
"numpy.random.random",
"numpy.issubdtype",
"numpy.dtype",
"numpy.full_like",
"numpy.concatenate",
"numpy.full",
"numpy.... |
ZaydH/malware_gan | [
"ea3f4e5139e6343c26273db0299a4b9d96d814af"
] | [
"malgan/discriminator.py"
] | [
"# -*- coding: utf-8 -*-\nr\"\"\"\n malgan.discriminator\n ~~~~~~~~~~~~~~~~~\n\n Discriminator (i.e., substitute detector) block for MalGAN.\n\n Based on the paper: \"Generating Adversarial Malware Examples for Black-Box Attacks Based on GAN\"\n By Weiwei Hu and Ying Tan.\n\n :version: 0.1.0\n ... | [
[
"torch.nn.Sequential",
"torch.nn.Linear",
"torch.clamp",
"torch.nn.Sigmoid"
]
] |
gpageinin/puzzle | [
"7aa12751bc0cb4d22aa91c2dd5b5fbc84ff65686"
] | [
"train.py"
] | [
"import gym\nimport numpy as np\nimport torch\nimport torch.optim as opt\nfrom tqdm import tqdm\n\nimport gym_puzzle\nfrom agent import Agent\n\n\n# ハイパーパラメータ\nHIDDEN_NUM = 128 # エージェントの隠れ層のニューロン数\nEPISODE_NUM = 10000 # エピソードを何回行うか\nMAX_STEPS = 1000 # 1エピソード内で最大何回行動するか\nGAMMA = .99 # 時間割引率\n\nenv = gym.make('pu... | [
[
"torch.eye",
"torch.no_grad",
"torch.tensor"
]
] |
awesome-archive/Paddle | [
"7bfcea5da0cc31d71c6f445c132cd673eb16bd2e"
] | [
"python/paddle/vision/ops.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 ... | [
[
"numpy.prod"
]
] |
ishine/Mutiband-HIFIGAN | [
"6eeab0fbb17c83f6afe3d933553a996c9499c988"
] | [
"stftloss.py"
] | [
"# -*- coding: utf-8 -*-\n\n# Copyright 2019 Tomoki Hayashi\n# MIT License (https://opensource.org/licenses/MIT)\n\n\"\"\"STFT-based Loss modules.\"\"\"\n\nimport torch\nimport torch.nn.functional as F\n\nfrom distutils.version import LooseVersion\n\nis_pytorch_17plus = LooseVersion(torch.__version__) >= LooseVers... | [
[
"torch.nn.ModuleList",
"torch.norm",
"torch.clamp",
"torch.log",
"torch.stft"
]
] |
ajaybhaga/MGSim | [
"adf0bb4a8af42a4b42bc47a2d191a7c40ceab459"
] | [
"test_perf.py"
] | [
"#import tensorflow as tf\n#import tensorflow as tf; print(tf.__version__); tf.test.is_gpu_available(cuda_only=False,min_cuda_compute_capability=None)\nimport tensorflow.compat.v1 as tf\ntf.disable_v2_behavior()\n\n\nimport time\ncpu_times = []\nsizes = [1, 10, 100, 500, 1000, 2000, 3000, 4000, 5000, 8000, 10000]\n... | [
[
"tensorflow.compat.v1.global_variables_initializer",
"tensorflow.compat.v1.disable_v2_behavior",
"matplotlib.pyplot.xlabel",
"matplotlib.pyplot.legend",
"matplotlib.pyplot.subplots",
"tensorflow.compat.v1.matmul",
"tensorflow.compat.v1.Session",
"tensorflow.compat.v1.reset_default_... |
tsommerfeld/Psi4_to_OLDMOS | [
"5ed66db6ea5b1da7af66c0ad9bd9990066aa04e4"
] | [
"lib/.ipynb_checkpoints/SO_aux-checkpoint.py"
] | [
"#!/usr/bin/env python3\n# -*- coding: utf-8 -*-\n\"\"\"\nCreated on Sun Jan 2 12:13:12 2022\n\n@author: Thomas Sommerfeld\n\nClass for dealing with Psi4 to Cfour SO mapping/transformation\n\n\"\"\"\n\nimport numpy as np\n\nclass SymOrbs:\n \"\"\" \n SOs for one irrep \n each SO is a column; each ... | [
[
"numpy.nonzero",
"numpy.zeros"
]
] |
mcerruti/gammapy | [
"544f33dd0f43bccfa0a8e9810f166d3730437ae2"
] | [
"gammapy/maps/tests/test_hpxnd.py"
] | [
"# Licensed under a 3-clause BSD style license - see LICENSE.rst\nimport pytest\nimport numpy as np\nfrom numpy.testing import assert_allclose\nfrom astropy import units as u\nfrom astropy.coordinates import SkyCoord\nfrom astropy.io import fits\nfrom regions import CircleSkyRegion\nfrom gammapy.maps import HpxGeom... | [
[
"numpy.max",
"numpy.testing.assert_allclose",
"numpy.ones_like",
"numpy.sum",
"numpy.nansum",
"numpy.ones",
"numpy.random.uniform",
"numpy.arange",
"numpy.logspace"
]
] |
KSomi/models | [
"cc6c45ca6b701426d35bbbab104ad32a2e80a3cf"
] | [
"research/deeplab/evaluation/panoptic_quality_test.py"
] | [
"# Copyright 2019 The TensorFlow Authors All Rights Reserved.\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n# http://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless requi... | [
[
"numpy.array",
"numpy.zeros_like",
"numpy.zeros",
"numpy.testing.assert_array_equal",
"numpy.testing.assert_array_almost_equal"
]
] |
andyjpaddle/Paddle | [
"7a0cc0a99996d6449256b08d4c7e4360d8fdd724"
] | [
"python/paddle/fluid/tests/unittests/interpreter/test_standalone_executor.py"
] | [
"# Copyright (c) 2021 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... | [
[
"numpy.array",
"numpy.ones",
"numpy.array_equal"
]
] |
mjziebarth/gmt-python-extensions | [
"a6a42b0d2ae123117c780d4ce3f93563ad3ad4d8"
] | [
"gmt_extensions/grid.py"
] | [
"# A grid class.\n#from scipy.interpolate import SmoothSphereBivariateSpline\nfrom scipy.interpolate import LinearNDInterpolator,NearestNDInterpolator\nfrom tempfile import NamedTemporaryFile\nimport numpy as np\nimport gmt\nfrom os import remove\nfrom shutil import copyfile\nfrom math import gcd\n\ndef same_shape(... | [
[
"numpy.logical_or",
"numpy.count_nonzero",
"numpy.array",
"numpy.array_equal",
"numpy.savetxt",
"numpy.zeros",
"scipy.interpolate.NearestNDInterpolator",
"numpy.round",
"numpy.sin",
"scipy.interpolate.LinearNDInterpolator",
"numpy.isnan",
"numpy.issorted",
"nump... |
alexban94/msci_project | [
"6f449e1462d0634ca6623f835c074702ed05054e"
] | [
"code/evaluation.py"
] | [
"import os\nimport sys\nimport math\n\nimport numpy as np\nfrom PIL import Image\nimport scipy.linalg\n\nimport chainer\nimport chainer.cuda\nfrom chainer import Variable\nfrom chainer import serializers\nfrom chainer import cuda\nimport chainer.functions as F\n\nsys.path.append(os.path.dirname(__file__))\nsys.path... | [
[
"numpy.concatenate",
"numpy.array",
"numpy.dot",
"numpy.asarray",
"numpy.random.seed",
"numpy.sum",
"numpy.load",
"numpy.real",
"numpy.mean",
"numpy.std",
"numpy.arange",
"numpy.linalg.svd",
"numpy.clip"
]
] |
hristog/distributed | [
"25a2867e8e950d9cb51b071337ffc43ddaf0bb52"
] | [
"distributed/protocol/numpy.py"
] | [
"import math\nimport numpy as np\n\nfrom .serialize import dask_serialize, dask_deserialize\nfrom . import pickle\n\nfrom ..utils import log_errors\n\n\ndef itemsize(dt):\n \"\"\"Itemsize of dtype\n\n Try to return the itemsize of the base element, return 8 as a fallback\n \"\"\"\n result = dt.base.item... | [
[
"numpy.ascontiguousarray",
"numpy.ndarray",
"numpy.require",
"numpy.ma.masked_array",
"numpy.dtype"
]
] |
Bhare8972/LOFAR-LIM | [
"89f25be8c02cb8980c2e237da3eaac279d40a06a"
] | [
"LIM_scripts/examples/histogram_planewave_fits.py"
] | [
"#!/usr/bin/env python3\n\n\nfrom os import mkdir\nfrom os.path import isdir\n\nfrom pickle import load\n\nfrom matplotlib import pyplot as plt\nimport numpy as np\n\nfrom LoLIM.make_planewave_fits import planewave_fits\nfrom LoLIM.IO.raw_tbb_IO import filePaths_by_stationName\nfrom LoLIM.utilities import v_air, p... | [
[
"numpy.average",
"matplotlib.pyplot.savefig",
"matplotlib.pyplot.hist",
"matplotlib.pyplot.close"
]
] |
tntek/G2KD | [
"28bfc5420b319a1ab1ce6d0374906f3bf0b93c36"
] | [
"G2KD_VIT/loss.py"
] | [
"import numpy as np\nimport torch\nimport torch.nn as nn\nfrom torch.autograd import Variable\nimport math\nimport torch.nn.functional as F\nimport pdb\n\ndef Entropy(input_):\n bs = input_.size(0)\n epsilon = 1e-5\n entropy = -input_ * torch.log(input_ + epsilon)\n entropy = torch.sum(entropy, dim=1)\n... | [
[
"torch.cuda.is_available",
"torch.eye",
"torch.exp",
"torch.nn.CrossEntropyLoss",
"torch.sum",
"torch.unbind",
"torch.nn.BCELoss",
"torch.device",
"numpy.array",
"torch.nn.functional.one_hot",
"torch.log_softmax",
"torch.max",
"torch.clamp",
"torch.nn.functi... |
Ariyl/AerialDetection | [
"dc3384ff42d06e0ba9c9df2e2d053d8df7d1b726"
] | [
"tools/test_mRI.py"
] | [
"import argparse\nimport os\nimport os.path as osp\nimport shutil\nimport tempfile\n\nimport mmcv\nimport torch\nimport torch.distributed as dist\nfrom mmcv.runner import load_checkpoint, get_dist_info\nfrom mmcv.parallel import MMDataParallel, MMDistributedDataParallel\n\nfrom mmdet.apis import init_dist\nfrom mmd... | [
[
"torch.no_grad",
"torch.distributed.barrier",
"torch.full",
"torch.distributed.broadcast"
]
] |
JunMa11/MICCAI2020-Refuge2 | [
"b6aed222f47146c739f7a6f64da5653f02e683cc"
] | [
"predict_Fovea_seg_stage1.py"
] | [
"import os\r\nimport numpy as np\r\nimport torch\r\nimport math\r\nimport segmentation_models_pytorch as smp\r\nimport pickle\r\nimport cv2\r\nimport argparse\r\nfrom utils import remove_small_areas, keep_large_area\r\nfrom skimage import exposure, io\r\nimport torch.nn as nn\r\nfrom skimage.measure import *\r\nimp... | [
[
"torch.sigmoid",
"numpy.zeros",
"numpy.ascontiguousarray",
"pandas.DataFrame",
"torch.no_grad",
"torch.from_numpy",
"torch.load",
"numpy.flip"
]
] |
gboeing/pylogit | [
"ac6b5ad988cb62443727ae70fcbcc7a3b47592ac"
] | [
"tests/test_nested_logit.py"
] | [
"\"\"\"\nTests for the nested_logit.py file. These tests do not include tests of\nthe functions that perform the mathematical calculations necessary to estimate\nthe Nested Logit model.\n\"\"\"\nimport warnings\nimport unittest\nfrom collections import OrderedDict\n\nimport numpy as np\nimport numpy.testing as npt\... | [
[
"numpy.concatenate",
"numpy.testing.assert_allclose",
"numpy.array",
"numpy.zeros",
"numpy.arange"
]
] |
SHMAKI/2021_TamoxifenResistance | [
"637a3e30222983d9bcb9881544ec613a7a2a99a3"
] | [
"Figure_4/biomass/ga/ga_continue.py"
] | [
"import time\nimport numpy as np\n\nfrom biomass.exec_model import ExecModel\nfrom .rcga import (UnimodalNormalDistributionXover,\n DistanceIndependentDiversityControl)\n\nclass GeneticAlgorithmContinue(ExecModel):\n def __init__(self, model, max_generation, allowable_error, p0_bounds):\n ... | [
[
"numpy.full",
"numpy.empty",
"numpy.random.choice",
"numpy.isfinite",
"numpy.clip",
"numpy.argsort",
"numpy.log10"
]
] |
cipherhacker/Pluto-Blink-Monitoring | [
"8e927690a2420e3500457d412413614f24735ab9"
] | [
"plt.py"
] | [
"import tkinter as tk\nimport matplotlib.pyplot as plt\nfrom matplotlib.backends.backend_tkagg import FigureCanvasTkAgg\nimport pandas as pd\nfrom pandas import DataFrame\nimport numpy as np\nimport time\n\nroot= tk.Tk()\n\n\nfileInstance = open('demofile.txt', 'r')\ntext = fileInstance.read().split(\",\")\n\ntext_... | [
[
"matplotlib.pyplot.Figure",
"pandas.DataFrame",
"matplotlib.backends.backend_tkagg.FigureCanvasTkAgg"
]
] |
nikon-petr/kohonen | [
"c23ae3032c58681040fe023bfa395d1ff9989876"
] | [
"core/net_neighboring_calculator.py"
] | [
"import pprint\n\nimport numpy as np\n\nfrom core.net_errors import NetIsNotInitialized\n\n\ndef calculate_average_neighboring(net_object):\n if net_object.net is None:\n raise NetIsNotInitialized()\n\n net = net_object.net\n\n zero_weights = np.zeros((net_object.config[0]))\n\n weights = np.ma.a... | [
[
"numpy.ndindex",
"numpy.reshape",
"numpy.zeros",
"numpy.nanmean",
"numpy.all",
"numpy.insert"
]
] |
HarryMellsop/chept-neural-chess | [
"656cb385e69d21c28117ef1fd0ecc671e01f1c1d"
] | [
"evaluate_commentary.py"
] | [
"import chess\nimport argparse\nimport questionary\nimport os\nimport json\nimport numpy as np\nimport torch\nfrom tqdm import tqdm\nimport model\nimport utils\nimport pickle\nimport chess.engine\nimport nltk\n\nfrom nltk.translate.bleu_score import SmoothingFunction\n\nMASK_CHAR = u\"\\u2047\"\nengine = chess.engi... | [
[
"torch.device",
"numpy.mean",
"torch.cuda.current_device",
"torch.cuda.is_available",
"torch.tensor"
]
] |
kvathupo/qfs-optimization | [
"e1d2c3f885ad422a0d1ad91b3a50c96f7ce183fa"
] | [
"MEAN_VAR-yahoo-visual/MV_yahoo_visual.py"
] | [
"# Note:\r\n#\r\n# When making edits, please adhere to PEP8 style guidelines and avoid\r\n# exceeding 75 characters in one line.\r\n#\r\n\r\nimport sys\r\nimport numpy as np\r\nimport pandas as pd\r\n\r\n#\r\n# Importing bokeh functions\r\n#\r\nfrom bokeh.plotting import figure, output_file, show, ColumnDataSource\... | [
[
"pandas.DataFrame",
"pandas.read_csv",
"numpy.linalg.inv"
]
] |
HermannLizard/pipcook-plugin-pytorch-yolov5-model-train | [
"04760b0301ea091af675e868b2a803674a3ca670"
] | [
"__init__.py"
] | [
"import os\nimport sys\nsys.path.append(os.path.join(os.path.dirname(__file__)))\n\nimport yaml\nimport logging\nimport torch\nimport torch.optim as optim\nimport torch.optim.lr_scheduler as lr_scheduler\nfrom torch.cuda import amp\nfrom tools.datasets import create_dataloader, preprocess\nfrom tqdm import tqdm\nim... | [
[
"numpy.concatenate",
"torch.zeros",
"numpy.array",
"torch.cuda.amp.autocast",
"numpy.zeros",
"torch.save",
"torch.optim.SGD",
"numpy.interp",
"torch.cuda.device_count",
"torch.cuda.is_available",
"torch.tensor",
"torch.cuda.amp.GradScaler",
"torch.cuda.memory_re... |
GEOS-ESM/GMAO_Shared | [
"022af23abbc7883891006b57379be96d9a50df23",
"022af23abbc7883891006b57379be96d9a50df23"
] | [
"GEOS_Util/coupled_diagnostics/analysis/clim/precip.py",
"GEOS_Util/coupled_diagnostics/verification/levitus/s_profile.py"
] | [
"#!/usr/bin/env python\n\nimport matplotlib\nmatplotlib.use('Agg')\n\nimport os, sys\nfrom importlib import import_module\nimport netCDF4 as nc\nimport scipy as sp\nimport matplotlib.pyplot as pl\nfrom matplotlib import colors\nfrom mpl_toolkits.basemap.cm import s3pcpn_l, sstanom\nimport g5lib.plotters as ptrs\nfr... | [
[
"matplotlib.use",
"matplotlib.pyplot.savefig",
"matplotlib.pyplot.figure",
"matplotlib.pyplot.show",
"matplotlib.colors.Normalize",
"matplotlib.pyplot.clf"
],
[
"matplotlib.ticker.MultipleLocator",
"matplotlib.pyplot.grid",
"matplotlib.pyplot.savefig",
"matplotlib.pyplo... |
qiushuiai/RLs | [
"a612ecaf3a47bdcbb412250a3bfdfa579578a183"
] | [
"rls/algos/single/tac.py"
] | [
"#!/usr/bin/env python3\r\n# encoding: utf-8\r\n\r\nimport numpy as np\r\nimport tensorflow as tf\r\nimport tensorflow_probability as tfp\r\n\r\nfrom rls.algos.base.off_policy import Off_Policy\r\nfrom rls.utils.tf2_utils import (tsallis_squash_rsample,\r\n gaussian_entropy,\r\n ... | [
[
"tensorflow.exp",
"tensorflow.square",
"tensorflow.multiply",
"tensorflow.minimum",
"tensorflow.GradientTape",
"numpy.log",
"tensorflow.argmax",
"tensorflow.one_hot",
"tensorflow.Variable",
"tensorflow.math.log",
"tensorflow.nn.softmax",
"tensorflow.device",
"te... |
lzzppp/DERT | [
"e1f9ee2489f76e2ed741d6637fd2b1e8bb225fb6"
] | [
"text_er/MCAN_hier/model/_utils.py"
] | [
"import pdb\n\nimport six\n\nimport deepmatcher as dm\nimport torch\n\nfrom deepmatcher.batch import AttrTensor\n\n\ndef sequence_mask(lengths, max_len=None):\n batch_size = lengths.numel()\n max_len = max_len or lengths.max()\n return (torch.arange(0, max_len).type_as(lengths).repeat(batch_size, 1).lt(\n ... | [
[
"torch.arange"
]
] |
Bradan/deepwriting | [
"1c2a9d030d691c88dfc70483adcccb671a313512"
] | [
"tf_train_hw_classification.py"
] | [
"import pickle\nimport json\nimport sys\nimport time\nimport os\nimport argparse\n\nimport tensorflow as tf\nfrom tensorflow.python.ops import math_ops\nfrom tensorflow.python.framework import dtypes\n\nfrom tf_dataset_hw import *\nfrom tf_data_feeder import *\nfrom tf_models_hw_classification import *\nfrom utils ... | [
[
"tensorflow.train.start_queue_runners",
"tensorflow.clip_by_norm",
"tensorflow.clip_by_value",
"tensorflow.local_variables_initializer",
"tensorflow.global_variables_initializer",
"tensorflow.set_random_seed",
"tensorflow.trainable_variables",
"tensorflow.train.latest_checkpoint",
... |
yizhou-wang/RODNet | [
"389ff84ce4b111b36306dd22a49d3c64bded64ac"
] | [
"tools/train.py"
] | [
"import os\nimport time\nimport json\nimport argparse\n\nimport torch\nimport torch.nn as nn\nimport torch.optim as optim\nfrom torch.optim.lr_scheduler import StepLR\nfrom torch.utils.data import DataLoader\nfrom torch.utils.tensorboard import SummaryWriter\n\nfrom cruw import CRUW\n\nfrom rodnet.datasets.CRDatase... | [
[
"torch.optim.lr_scheduler.StepLR",
"torch.nn.MSELoss",
"torch.save",
"torch.utils.data.DataLoader",
"torch.load",
"torch.nn.BCELoss",
"torch.utils.tensorboard.SummaryWriter"
]
] |
Malga-Vision/fastervideo | [
"34e212fe04398262e5dac7f74ac4c2365fc1e03f"
] | [
"detectron2/data/build.py"
] | [
"# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved\nimport bisect\nimport copy\nimport itertools\nimport logging\nimport numpy as np\nimport pickle\nimport torch.utils.data\nfrom fvcore.common.file_io import PathManager\nfrom tabulate import tabulate\nfrom termcolor import colored\n\nfrom detec... | [
[
"numpy.histogram",
"numpy.array",
"numpy.zeros",
"numpy.random.randint",
"numpy.arange"
]
] |
gplatono/StructureLearning | [
"85e7174e12b88f83309ea8a8fb8e8e5e54325842"
] | [
"voxelnet.py"
] | [
"import bpy\nimport torch\nimport numpy as np\n\nobjects = bpy.context.scene.objects\n\ndef get_centroids():\n\treturn [np.array(obj.location) for obj in objects]\n\n#print (get_centroids())\n\ndef perturb(struct, size):\n\tperturbed = []\n\tamplitude = size / 5\n\tfor point in struct:\n\t\tperturb = np.random.mult... | [
[
"numpy.array",
"numpy.random.randint",
"numpy.random.multivariate_normal"
]
] |
d294270681/bert4keras | [
"18451a81761cc0d6c206ff5b64cfe47080f8273b"
] | [
"bert4keras/snippets.py"
] | [
"#! -*- coding: utf-8 -*-\n# 代码合集\n\nimport six\nimport logging\nimport numpy as np\nimport re\nimport sys\nfrom collections import defaultdict\nimport json\nimport tensorflow as tf\nfrom bert4keras.backend import K, keras\n\n_open_ = open\nis_py2 = six.PY2\n\nif not is_py2:\n basestring = str\n\n\ndef to_array(... | [
[
"numpy.exp",
"numpy.apply_along_axis",
"numpy.cumsum",
"numpy.concatenate",
"numpy.empty",
"numpy.log",
"tensorflow.get_default_graph",
"numpy.argmax",
"numpy.arange",
"numpy.pad",
"numpy.array",
"numpy.zeros",
"numpy.roll",
"numpy.shape",
"numpy.random.... |
hc07180011/IQA-testing | [
"29b0c61a4dafa57203098811190f7152c1a9bf33"
] | [
"IQA/index/colourcast.py"
] | [
"import cv2 as cv\nimport numpy as np\n\n\nclass ColourCast:\n\n def __init__(self, img_input: np.ndarray) -> None:\n self.img_input = img_input\n\n def color_cast(self):\n # RGB to La*b*\n img_float = self.img_input.astype(np.float32) / 255.0\n\n np_R = img_float[:, :, 2]\n ... | [
[
"numpy.var",
"numpy.sqrt"
]
] |
startable/pdtable | [
"693af4f4d49a27f54c79887a42a0b1a1b68d77a9"
] | [
"pdtable/io/parsers/columns.py"
] | [
"\"\"\"Machinery to parse columns in accordance with their unit indicator.\n\nParsers to convert column values of uncontrolled data types into values with a data type\nconsistent with the intended representation given the column's unit indicator.\n\nA data-type-specific parser is implemented for each of the allowab... | [
[
"pandas.to_datetime",
"numpy.array"
]
] |
JoeMWatson/trajopt | [
"8b98718721e0c373cd7dc01a35f42447c1134713"
] | [
"trajopt/ilqr/ilqr.py"
] | [
"#!/usr/bin/env python3\n# -*- coding: utf-8 -*-\n# @Filename: ilqr\n# @Date: 2019-06-23-14-00\n# @Author: Hany Abdulsamad\n# @Contact: hany@robot-learning.de\n\nimport autograd.numpy as np\n\nfrom trajopt.ilqr.objects import AnalyticalLinearDynamics, AnalyticalQuadraticCost\nfrom trajopt.ilqr.objects import Quadra... | [
[
"matplotlib.pyplot.show",
"matplotlib.pyplot.plot",
"matplotlib.pyplot.subplot",
"matplotlib.pyplot.figure"
]
] |
HugoBourdon/flatland-project | [
"bd459517c7774ecd0072969f7d548a084bc3b580"
] | [
"model.py"
] | [
"import torch.nn as nn\nimport torch.nn.functional as F\n\nclass PolicyNetwork(nn.Module):\n\n def __init__(self, state_size, action_size, hidsize1=128, hidsize2=128):\n super(PolicyNetwork, self).__init__()\n\n self.fc1 = nn.Linear(state_size, hidsize1)\n self.fc2 = nn.Linear(hidsize1, hids... | [
[
"torch.nn.Linear"
]
] |
1512159/tf-faster-rcnn-medico | [
"94c5cff76ef7bd271de050a8de53bd0145c6c8ec"
] | [
"tools/medico_classify.py"
] | [
"#!/usr/bin/env python\n\n# --------------------------------------------------------\n# Tensorflow Faster R-CNN\n# Licensed under The MIT License [see LICENSE for details]\n# Written by Xinlei Chen, based on code from Ross Girshick\n# --------------------------------------------------------\n\n\"\"\"\nDemo script s... | [
[
"matplotlib.use",
"matplotlib.pyplot.colorbar",
"numpy.zeros",
"matplotlib.pyplot.xlabel",
"matplotlib.pyplot.savefig",
"matplotlib.pyplot.title",
"tensorflow.Session",
"tensorflow.train.Saver",
"matplotlib.pyplot.yticks",
"matplotlib.pyplot.figure",
"tensorflow.ConfigP... |
albertogaspar/dts | [
"9fcad2c672cdcf5d2c6bd005dae05afc65f97e58"
] | [
"dts/utils/utils.py"
] | [
"import keras.backend as K\nimport numpy as np\nimport pandas as pd\nfrom datetime import time, datetime\nimport tensorflow as tf\nfrom argparse import ArgumentParser\n\n\ndef get_flops(model):\n run_meta = tf.RunMetadata()\n opts = tf.profiler.ProfileOptionBuilder.float_operation()\n\n # We use the Keras ... | [
[
"tensorflow.profiler.ProfileOptionBuilder.float_operation",
"pandas.DatetimeIndex",
"numpy.random.shuffle",
"tensorflow.RunMetadata",
"numpy.arange"
]
] |
AlexInJar/Explore_OT | [
"da9951ea98f728ec350bfcc7051537bdf0b21a64"
] | [
"networksimplex/Extremal.py"
] | [
"import numpy as np \nimport random \n\n\nclass extrema:\n\n def __init__(self, a, b):\n '''\n a, b are the row and column sum constraints\n '''\n self.a = a\n self.b = b\n self.P = None\n\n def NWC(self):\n P = np.zeros((len(self.a),len(self.b)))\n nR =... | [
[
"numpy.abs"
]
] |
williamd4112/curiosity_baselines | [
"45939f3f24c53cfff5153ef012486a6a058660be"
] | [
"rlpyt/utils/logging/context.py"
] | [
"import datetime\nimport json\nimport os\nimport os.path as osp\nfrom contextlib import contextmanager\ntry:\n from torch.utils.tensorboard.writer import SummaryWriter\nexcept ImportError:\n print(\"Unable to import tensorboard SummaryWriter, proceeding without.\")\n\nfrom rlpyt.utils.logging import logger\n\... | [
[
"torch.utils.tensorboard.writer.SummaryWriter"
]
] |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.