repo_name stringlengths 6 130 | hexsha list | file_path list | code list | apis list |
|---|---|---|---|---|
GeorgeMironov/albumentations | [
"fe3f36a0285bce9abb6496c410ba672f53f15be6"
] | [
"tests/test_core.py"
] | [
"from __future__ import absolute_import\n\nimport cv2\nimport numpy as np\nimport pytest\n\nfrom albumentations.core.transforms_interface import to_tuple, ImageOnlyTransform, DualTransform\nfrom albumentations.augmentations.bbox_utils import check_bboxes\nfrom albumentations.core.composition import OneOrOther, Comp... | [
[
"numpy.array_equal",
"numpy.ones"
]
] |
scuervo91/dcapy | [
"46c9277e607baff437e5707167476d5f7e2cf80c"
] | [
"dcapy/wiener/brownian.py"
] | [
"# External Imports\nimport numpy as np \nimport pandas as pd\nfrom scipy import stats\nfrom pydantic import BaseModel, Field, Extra\nfrom typing import List, Union, Optional\nfrom datetime import date\n#Local Imports\nfrom ..dca import list_freq, converter_factor, ProbVar\nfrom ..dca import FreqEnum\n#from ..model... | [
[
"numpy.sqrt",
"numpy.linspace",
"numpy.power",
"pandas.period_range",
"numpy.arange",
"numpy.broadcast_to",
"numpy.exp",
"numpy.zeros"
]
] |
trendscenter/fsl-parser-package | [
"84e519f797cfe3c442a66ee4d48f57649f1ee994"
] | [
"fslparser/parsers.py"
] | [
"#!/usr/bin/env python3\n\n\nimport os\nimport pandas as pd\n\n\ndef parse_for_y(args, y_files, y_labels):\n \"\"\"Read contents of fsl files into a dataframe\"\"\"\n y = pd.DataFrame(index=y_labels)\n\n for file in y_files:\n if file:\n try:\n y_ = pd.read_csv(\n ... | [
[
"pandas.DataFrame.from_dict",
"pandas.merge",
"pandas.DataFrame",
"pandas.get_dummies"
]
] |
Cybsloth/LightAutoML | [
"77b49ecb08b4cd655fda7564a7e55c0bf2d124da"
] | [
"lightautoml/automl/presets/base.py"
] | [
"\"\"\"AutoML presets base class.\"\"\"\n\nimport logging\nimport os\nimport shutil\n\nfrom typing import Any\nfrom typing import Iterable\nfrom typing import Optional\nfrom typing import Sequence\n\nimport torch\nimport yaml\n\nfrom ...dataset.base import LAMLDataset\nfrom ...tasks import Task\nfrom ...utils.loggi... | [
[
"torch.cuda.device_count"
]
] |
neo-empresarial/covid-19 | [
"cef10ee79d955c9e84148c3c8da542788a1f7395"
] | [
"demos/prey-predator/prey_predator_sd/model/parts/lotka_volterra.py"
] | [
"import numpy as np\n\n## Policies\n\ndef p_reproduce_prey(params, substep, state_history, prev_state):\n born_population = prev_state['prey_population']\n born_population *= params['prey_reproduction_rate']\n born_population *= params['dt']\n return {'add_prey': born_population}\n\n\ndef p_reproduce_pr... | [
[
"numpy.ceil"
]
] |
MacIver-Lab/Ergodic-Information-Harvesting | [
"6b06033852d511c682f1a38d84d6c3e0d735659b"
] | [
"SimulationCode/RunAllSims.py"
] | [
"from ErgodicHarvestingLib.SimulationMainQueue import SimulationMainQueue\nfrom datetime import datetime\nimport time\nimport warnings\nimport sys\nfrom multiprocessing import cpu_count\nfrom os import scandir\nimport numpy as np\n\n# Suppress all warnings\nnp.seterr(all=\"ignore\")\nwarnings.filterwarnings(\"ignor... | [
[
"numpy.seterr"
]
] |
wsh32/blurin8r | [
"ad251fccc2675a73c1ba5e83300440d21537503c"
] | [
"blurin8r/process.py"
] | [
"import cv2\nimport numpy as np\nfrom utils import *\n\n\ndef find_faces_haar(img, classifier_filename, scale_factor=1.3, min_neighbors=5, debug=False):\n gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)\n classifier = cv2.CascadeClassifier(classifier_filename)\n faces = classifier.detectMultiScale(gray, scale... | [
[
"numpy.size",
"numpy.argmax",
"numpy.where"
]
] |
ConsVin/hls4ml | [
"4cea8ae0845b26a9b9c9295e9178ca457e897da9"
] | [
"hls4ml/model/profiling.py"
] | [
"from hls4ml.model.hls_model import HLSModel\nfrom hls4ml.model.hls_layers import IntegerPrecisionType, FixedPrecisionType\nimport matplotlib.pyplot as plt\nimport numpy as np\nimport pandas\nimport seaborn as sb\n\nfrom hls4ml.model.hls_model import HLSModel\n\ntry:\n from tensorflow import keras\n import qk... | [
[
"matplotlib.pyplot.legend",
"pandas.DataFrame",
"matplotlib.pyplot.plot",
"numpy.histogram",
"matplotlib.pyplot.gca",
"matplotlib.pyplot.tight_layout",
"numpy.arange",
"matplotlib.pyplot.gcf",
"numpy.zeros",
"matplotlib.pyplot.figure",
"matplotlib.pyplot.title",
"te... |
weiliuxm/Dassl.pytorch | [
"8084b66332623c7a2394ea1404f2d043ef415ebb"
] | [
"dassl/engine/ssl/entmin.py"
] | [
"import torch\nfrom torch.nn import functional as F\n\nfrom dassl.engine import TRAINER_REGISTRY, TrainerXU\nfrom dassl.metrics import compute_accuracy\n\n\n@TRAINER_REGISTRY.register()\nclass EntMin(TrainerXU):\n \"\"\"Entropy Minimization.\n\n http://papers.nips.cc/paper/2740-semi-supervised-learning-by-ent... | [
[
"torch.nn.functional.cross_entropy",
"torch.log"
]
] |
WCMetrics/SurveyAnalysis | [
"38e387cab749c613e5f6ecc4765186ba6939233c"
] | [
"delphi-analysis.py"
] | [
"from google_auth_oauthlib import flow\nfrom google.oauth2.credentials import Credentials\nimport gspread\nimport numpy as np\nfrom sklearn.decomposition import PCA\nimport matplotlib.pyplot as plt\n\ndef getUserCredetials():\n appflow = flow.InstalledAppFlow.from_client_secrets_file(\n '/Users/almo/Devel... | [
[
"numpy.median",
"matplotlib.pyplot.subplots",
"numpy.save",
"numpy.std",
"numpy.apply_along_axis",
"numpy.mean",
"numpy.transpose",
"matplotlib.pyplot.show"
]
] |
MingSun-Tse/EECE7311_Project_NST | [
"78f918771a6d725bfeac1af10af8d913508ac6f2"
] | [
"utils.py"
] | [
"import torch\nimport torch.nn as nn\nimport torch.nn.init as init\nfrom torch.utils.data import Dataset\nimport torch.nn.functional as F\nimport torchvision\nfrom torch.autograd import Variable\nfrom pprint import pprint\nimport time, math, os, sys, copy, numpy as np, shutil as sh\nimport matplotlib.pyplot as plt\... | [
[
"torch.nn.functional.kl_div",
"torch.nn.functional.softmax",
"torch.load",
"torch.randperm",
"numpy.mean",
"torch.no_grad",
"torch.pow",
"torch.nn.CrossEntropyLoss",
"numpy.random.beta",
"torch.einsum",
"torch.from_numpy",
"torch.rand",
"matplotlib.pyplot.close"... |
robertnishihara/arrow | [
"27f990a503f8d9370037bd12c235aae1c1378fb9"
] | [
"python/pyarrow/tests/test_convert_pandas.py"
] | [
"# -*- coding: utf-8 -*-\n# 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.... | [
[
"pandas.to_datetime",
"pandas.Series",
"numpy.sqrt",
"numpy.random.random_sample",
"pandas.DataFrame",
"numpy.dtype",
"pandas.util.testing.assert_frame_equal",
"numpy.random.randn",
"numpy.iinfo",
"numpy.bool_",
"numpy.random.randint",
"numpy.testing.assert_equal",
... |
shuaggar-sys/pandas | [
"f79468b8642be1ebc24b806117505a6fa7bf50b7"
] | [
"pandas/core/dtypes/cast.py"
] | [
"\"\"\"\nRoutines for casting.\n\"\"\"\n\nfrom __future__ import annotations\n\nfrom contextlib import suppress\nfrom datetime import datetime, timedelta\nfrom typing import (\n TYPE_CHECKING,\n Any,\n Dict,\n List,\n Optional,\n Sequence,\n Set,\n Sized,\n Tuple,\n Type,\n Union,\n... | [
[
"pandas.util._validators.validate_bool_kwarg",
"pandas._libs.tslibs.ints_to_pydatetime",
"pandas.core.dtypes.common.is_datetime64_dtype",
"pandas.core.dtypes.common.ensure_object",
"numpy.min_scalar_type",
"numpy.place",
"numpy.full",
"pandas.core.dtypes.common.is_float_dtype",
... |
Romance-Zhang/nl2sql-chinese | [
"d4b0fa9c3baa524544646bac24378fe49ae8d6c1"
] | [
"code/sqlnet/utils.py"
] | [
"import json\nfrom sqlnet.lib.dbengine import DBEngine\nimport numpy as np\nfrom tqdm import tqdm\nimport torch\nimport os\nfrom bert.modeling import BertConfig, BertModel\nimport bert.tokenization as tokenization\nfrom torch.autograd import Variable\ndevice = torch.device(\"cuda:0\" if torch.cuda.is_available() el... | [
[
"torch.load",
"torch.zeros",
"torch.tensor",
"torch.cuda.is_available",
"numpy.zeros",
"torch.autograd.Variable"
]
] |
NurmanZahin/smile_detector | [
"fde21c5d590bfc0e9b2d978d4f486b64a15b9186"
] | [
"src/inference.py"
] | [
"import numpy as np\nimport argparse\nimport cv2\nimport tensorflow as tf\nimport io\nimport logging\nimport matplotlib.pyplot as plt\n\nfrom PIL import Image\nfrom tensorflow.keras.applications.mobilenet_v2 import preprocess_input\n\nlogging.basicConfig(level=logging.INFO, format='%(asctime)s:%(levelname)s:%(name)... | [
[
"tensorflow.keras.models.load_model",
"matplotlib.pyplot.imshow",
"numpy.expand_dims",
"tensorflow.keras.applications.mobilenet_v2.preprocess_input",
"numpy.argmax",
"numpy.array",
"matplotlib.pyplot.show"
]
] |
ashtou/spec17-ml | [
"1c79d3f2fe242b1e5abc87e4db9e2c1485c28284"
] | [
"spec/predict/data_load_clean.py"
] | [
"#### JS to download all the urls from the page: https://www.spec.org/cpu2017/results/cpu2017.html\n#### Save the results in the corresponding text files and remove the '[' and ']' chars.\n# all_hrefs = []\n# all_csvs = document.getElementById(\"CINT2017_speeddiv\").querySelectorAll('table > tbody> tr > td > span >... | [
[
"numpy.std",
"pandas.isna",
"numpy.mean",
"numpy.log"
]
] |
yaroslavvb/imperative | [
"d08f08b4febc9005f7d91feaeb59ca18fbbca486"
] | [
"tests/extra/histogram_ops_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.histogram_fixed_width",
"numpy.random.RandomState",
"tensorflow.test.main"
]
] |
evankrause/covid-path-planning | [
"a65c29e752de9a07437cbde7e381330729ea6048"
] | [
"final_pipeline/order_path.py"
] | [
"from __future__ import print_function\nimport math\nimport sys\n\nfrom dijkstar import Graph, find_path\nfrom pandas import np\nfrom ortools.constraint_solver import routing_enums_pb2\nfrom ortools.constraint_solver import pywrapcp\n\n\n# TODO: optimize this method to get rid of the terribly slow image iterations\... | [
[
"pandas.np.shape",
"pandas.np.sqrt"
]
] |
csinva/covid-19-analysis | [
"e7b1e82cb6b25d62a868ff61025d88e17452de28"
] | [
"viz/viz_map.py"
] | [
"from bokeh.sampledata import us_states, us_counties\nfrom bokeh.plotting import figure, show, output_notebook, output_file, save\nfrom bokeh import palettes\nfrom bokeh.models import ColorBar,HoverTool,LinearColorMapper,ColumnDataSource,FixedTicker, LogColorMapper\noutput_notebook()\nimport re\nimport numpy as np\... | [
[
"numpy.array"
]
] |
InfuseAI/showcase | [
"54a177168c6e173580ed5c58fe97fe6018ecd06e"
] | [
"pycaret_classification/src/pycaret_classification_training.py"
] | [
"import pandas as pd\nfrom pycaret.classification import *\n\n\nclass PycaretClassificationTraining:\n def __init__(self, data_path):\n self.df = pd.read_csv(data_path)\n\n def automl_training(self, target_column, mlflow_experiment_name):\n # Initializing setup\n clf1 = setup(\n ... | [
[
"pandas.read_csv",
"pandas.DataFrame"
]
] |
bprevost/brad_demo | [
"7c071709f763627d870e2b9e55be332e6af5f4c3"
] | [
"deep/minivggnet.py"
] | [
"from tensorflow.keras import backend as K\nfrom tensorflow.keras.models import Sequential\nfrom tensorflow.keras.layers import Conv2D\nfrom tensorflow.keras.layers import Activation\nfrom tensorflow.keras.layers import BatchNormalization\nfrom tensorflow.keras.layers import MaxPooling2D\nfrom tensorflow.keras.laye... | [
[
"tensorflow.keras.layers.Activation",
"tensorflow.keras.backend.image_data_format",
"tensorflow.keras.layers.Dense",
"tensorflow.keras.layers.Conv2D",
"tensorflow.keras.layers.BatchNormalization",
"tensorflow.keras.layers.Dropout",
"tensorflow.keras.layers.MaxPooling2D",
"tensorflo... |
sahahn/BPt | [
"1a2967f4ca3fa070b7417a4f59a218ae171daadd"
] | [
"BPt/pipeline/BPtFeatureSelector.py"
] | [
"from sklearn.feature_selection._base import SelectorMixin\nfrom .helpers import update_mapping, check_om, proc_mapping\nfrom .ScopeObjs import ScopeTransformer\nimport numpy as np\nimport pandas as pd\n\n\nclass BPtFeatureSelector(ScopeTransformer, SelectorMixin):\n\n def _update_feat_mapping(self, X, mapping):... | [
[
"numpy.concatenate",
"numpy.array",
"pandas.Series"
]
] |
bjonnh/NP-Classifier | [
"9d45422a213b26747458bae24fabad7326c62c80"
] | [
"training/fingerprint_handler.py"
] | [
"import pandas as pd\r\nfrom tqdm import tqdm\r\nimport numpy as np\r\n\r\nimport rdkit\r\nfrom rdkit import Chem\r\nfrom rdkit.Chem import rdMolDescriptors\r\nfrom rdkit.Chem import Descriptors\r\nfrom rdkit.Chem import AllChem\r\nfrom rdkit import DataStructs\r\n\r\n#Fingerprint generation\r\n#(@ming if we want t... | [
[
"numpy.zeros"
]
] |
Sahil-Chavan/Vehicle_Object_Detection | [
"c3e4022f03a3c5e54f272869ee9e2f8fe1a3df96"
] | [
"app.py"
] | [
"import cv2\nimport base64\nimport numpy as np\nimport matplotlib.pyplot as plt\nfrom flask import Flask, render_template,flash,request,redirect,url_for,jsonify\nfrom functions import load_model,show_inference\n\napp = Flask(__name__)\n\napp.secret_key = \"sahilsc\"\n\nclass ClientApp:\n def __init__(self):\n ... | [
[
"numpy.frombuffer"
]
] |
chaozhong2010/Faster-RCNN_Tensorflow | [
"9e68a7f20620890018ec6e7b4596c0b5f3aa6524"
] | [
"tools/inference_result_jinnan2.py"
] | [
"# -*- coding:utf-8 -*-\r\n\r\nfrom __future__ import absolute_import\r\nfrom __future__ import print_function\r\nfrom __future__ import division\r\n\r\nimport os, sys\r\nimport tensorflow as tf\r\nimport time\r\nimport cv2\r\nimport argparse\r\nimport numpy as np\r\nimport json\r\nsys.path.append(\"../\")\r\n\r\nf... | [
[
"tensorflow.constant",
"tensorflow.local_variables_initializer",
"numpy.squeeze",
"tensorflow.cast",
"tensorflow.expand_dims",
"tensorflow.placeholder",
"tensorflow.ConfigProto",
"tensorflow.global_variables_initializer",
"tensorflow.Session",
"tensorflow.train.Saver"
]
] |
dominiquesydow/dynophores | [
"16b924e266b9a1a4e20edc5d2d0a43d40c225dea"
] | [
"dynophores/tests/core/test_envpartner.py"
] | [
"\"\"\"\nUnit tests for dynophore.core.envpartner.EnvPartner class.\n\nUses fixture tests.conftest.envpartner.\n\"\"\"\n\nfrom pathlib import Path\n\nimport pytest\nimport numpy as np\n\nfrom dynophores import parsers\nfrom dynophores.core.envpartner import EnvPartner\n\nPATH_TEST_DATA = Path(__name__).parent / \"d... | [
[
"numpy.array"
]
] |
mcmonster/tensorflow | [
"fb8a14fde29f2dc19331d73795c2ead0e8ef0e8e"
] | [
"tensorflow/contrib/distribute/python/keras_test.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.python.keras.layers.Lambda",
"tensorflow.python.distribute.values.ReplicaDeviceMap",
"tensorflow.python.keras.layers.Dense",
"tensorflow.python.keras.callbacks.LearningRateScheduler",
"tensorflow.python.keras.layers.BatchNormalization",
"tensorflow.python.keras.layers.concatena... |
pvtodorov/systox | [
"746c6ed67db735c580b456a4d9daa53f4850be5b"
] | [
"process_data/process_data_genes_02.py"
] | [
"import pandas as pd\nimport os\n\n# using the merged_medianData.csv create dose-response files for each compound\n\ninfolder = '../data/processed_data/01/LISS/01/'\noutfolder = '../data/processed_data/01/LISS/02/'\n\nif not os.path.exists(outfolder):\n os.makedirs(outfolder)\n\ngeneList = pd.read_csv('../data/l... | [
[
"pandas.read_csv",
"pandas.DataFrame"
]
] |
jimwatt/P5-vehicledetection | [
"b90a0651056f8288ced0f09141651b5767ef89f7"
] | [
"measurement.py"
] | [
"import numpy as np\n\nclass Measurement:\n def __init__(self,x,y,sx,sy):\n self.xy = np.array([x,y])\n self.sxy = np.array([sx,sy]) "
] | [
[
"numpy.array"
]
] |
esalesky/visrep | [
"b1d9f2384d3f3e2a1e813c830581a8b0b9cda1f5"
] | [
"fairseq/data/vis_align_language_pair_dataset.py"
] | [
"# Copyright (c) Facebook, Inc. and its affiliates.\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\nimport numpy as np\nimport torch\n\n#from . import data_utils, FairseqDataset\nfrom fairseq.data import data_utils, FairseqDataset\n... | [
[
"torch.LongTensor",
"torch.from_numpy",
"numpy.max",
"torch.unique",
"numpy.argsort",
"numpy.array"
]
] |
dstrain115/Stim | [
"82a161741c05d637fe16ea20b1d99a48b4ca4750"
] | [
"src/circuit/circuit_pybind_test.py"
] | [
"# Copyright 2021 Google LLC\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n# http://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless required by applicable law or agreed ... | [
[
"numpy.count_nonzero"
]
] |
AlexBrady/FlaskMLService | [
"7a2286a831b683c03635bd5d98da9421c44725a5"
] | [
"defenders/sdg_predict.py"
] | [
"import math\r\nimport pandas as pd\r\nimport numpy as np\r\nfrom sklearn import metrics\r\nfrom sklearn.model_selection import train_test_split\r\nfrom sklearn.linear_model import LinearRegression, SGDRegressor\r\nfrom sklearn.cross_validation import cross_val_score\r\nfrom sklearn.metrics import mean_squared_erro... | [
[
"pandas.concat",
"pandas.read_csv",
"sklearn.linear_model.SGDRegressor",
"numpy.round",
"pandas.cut"
]
] |
Midnighter/conifer-analysis | [
"4cce4a55227603668feb24079c5ab884944527b4"
] | [
"src/conifer_analysis/pipeline.py"
] | [
"# Copyright (c) 2022, Moritz E. Beber.\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n# https://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless required by applicable law... | [
[
"numpy.linspace"
]
] |
jxqhhh/PytorchPointCNN | [
"a19748b9b1c89a869c0785b059b844abd1d3ffd9"
] | [
"util/vis/misc_functions.py"
] | [
"\"\"\"\nCreated on Thu Oct 21 11:09:09 2017\n\n@author: Utku Ozbulak - github.com/utkuozbulak\n\"\"\"\nimport copy\nimport os\n\nimport matplotlib.cm as mpl_color_map\nimport numpy as np\nimport torch\nfrom PIL import Image\nfrom torch.autograd import Variable\nfrom torchvision import models\n\n\ndef convert_to_gr... | [
[
"numpy.expand_dims",
"numpy.maximum",
"numpy.abs",
"numpy.clip",
"numpy.min",
"numpy.uint8",
"torch.from_numpy",
"numpy.percentile",
"numpy.round",
"numpy.max",
"numpy.float32",
"matplotlib.cm.get_cmap",
"numpy.repeat",
"torch.autograd.Variable"
]
] |
HEEJOWOO/RDCAB-RecursivSRNet-Split-Version- | [
"198dbaaa1b1d5e45aacc6a2da19136bda50cc125"
] | [
"models.py"
] | [
"from torch import nn\nimport torch\nimport torch.nn.functional as F\nclass Scale(nn.Module):\n def __init__(self, init_value=1e-3):\n super().__init__()\n self.scale = nn.Parameter(torch.FloatTensor([init_value]))\n\n def forward(self, input):\n return input * self.scale\n \ndef m... | [
[
"torch.nn.functional.dim",
"torch.cat",
"torch.nn.Conv2d",
"torch.nn.PixelShuffle",
"torch.nn.Sigmoid",
"torch.nn.AdaptiveAvgPool2d",
"torch.FloatTensor",
"torch.nn.functional.interpolate",
"torch.split",
"torch.nn.functional.size",
"torch.nn.functional.sum",
"torch... |
slim-sst/kendryte-model-compiler | [
"ff287df871ed1fdc0dce895d63608307a94b0171"
] | [
"k210_layer.py"
] | [
"# coding=utf-8\n'''\n * Copyright 2018 Canaan Inc.\n *\n * Licensed under the Apache License, Version 2.0 (the \"License\");\n * you may not use this file except in compliance with the License.\n * You may obtain a copy of the License at\n *\n * http://www.apache.org/licenses/LICENSE-2.0\n *\n * Unless require... | [
[
"numpy.product",
"numpy.sqrt",
"numpy.min",
"numpy.power",
"numpy.round",
"numpy.max"
]
] |
jdagdelen/matscholar-web | [
"3bfc22cb1b584c5cf508bea45241a790022f39d7"
] | [
"matscholar_web/callbacks/extract_callbacks.py"
] | [
"import dash_html_components as html\nimport string\nimport os\nimport json\nimport urllib\nimport numpy as np\nfrom dash.dependencies import Input, Output, State\nfrom matscholar.rest import Rester\n\n# Get the rester and random docs on import\nrester = Rester()\nlocal_dir = os.path.dirname(__file__)\nwith open(os... | [
[
"numpy.random.choice"
]
] |
dimazest/fowler.corpora | [
"ffcd6dff5af1a75b72553f9b7ce22d4186b1afce"
] | [
"fowler/corpora/bnc/corpus.py"
] | [
"import logging\n\nfrom itertools import chain, islice, count\n\nimport pandas as pd\n\nfrom chrono import Timer\nfrom more_itertools import peekable\n\nfrom .util import co_occurrences\n\nlogger = logging.getLogger(__name__)\n\n\nclass Corpus:\n\n # The peak memory usage per worker is about:\n #\n # * 3GB... | [
[
"pandas.DataFrame"
]
] |
computationalgeography/lue | [
"71993169bae67a9863d7bd7646d207405dc6f767"
] | [
"source/framework/python/test/algorithm/downstream_test.py"
] | [
"import lue.framework as lfr\nimport lue_test\nimport numpy as np\n\n\ndef setUpModule():\n lue_test.start_hpx_runtime()\n\n\ndef tearDownModule():\n pass\n # lue_test.stop_hpx_runtime()\n\n\nclass DownstreamTest(lue_test.TestCase):\n\n def test_overloads(self):\n\n array_shape = (60, 40)\n ... | [
[
"numpy.dtype"
]
] |
Safeaspie/Team-Computer | [
"0c6378408fccbe1ff573267802802c8c61e20b79"
] | [
"ApplicationWithSentiment/app/src/main/python/processData.py"
] | [
"import pandas as pd\nfrom openpyxl import Workbook\nfrom time import sleep\n\nangry = pd.read_csv(\"Emotion(angry).csv\")\nhappy = pd.read_csv(\"Emotion(happy).csv\")\nsad = pd.read_csv(\"Emotion(sad).csv\")\nangry = angry[:]\nhappy = happy[:]\nsad = sad[:]\ndatas = [angry, happy, sad]\n\n#Open library for working... | [
[
"pandas.read_csv"
]
] |
premprabhat/treelite | [
"997cbfc3a8541c2ce81cd082825e5ac6879d9b96"
] | [
"tests/python/test_invalid_categorical_input.py"
] | [
"# -*- coding: utf-8 -*-\n# pylint: disable=missing-function-docstring\n\"\"\"Test whether Treelite handles invalid category values correctly\"\"\"\nimport os\n\nimport treelite\nimport treelite_runtime\nimport numpy as np\nimport pytest\nfrom treelite.contrib import _libext\n\nfrom .util import os_compatible_toolc... | [
[
"numpy.testing.assert_equal",
"numpy.array",
"numpy.zeros",
"numpy.column_stack"
]
] |
boolean5/VirtualSign | [
"bdb1ade73996049bdd12a9fedc38252c7572eed2"
] | [
"evaluate.py"
] | [
"import argparse\n\nimport numpy as np\nfrom keras.models import load_model\nfrom keras.utils import np_utils\n\nfrom utils import create_dataset\n\n# Parsing from terminal\nparser = argparse.ArgumentParser(description='Evaluate a trained model')\nparser.add_argument('model_path', help='Path of the model to be eval... | [
[
"numpy.expand_dims",
"numpy.hsplit"
]
] |
memfagor/spectconv | [
"69002c2a95ee0113a4b117dc5ebb87044687941b"
] | [
"convbase.py"
] | [
"#!/usr/bin/env python3\n\nimport os\nimport json\nimport pandas as pd\n\n\ndef get_config(filename):\n with open(os.path.join(os.getcwd(), filename), 'r') as config_file:\n config = json.load(config_file)\n return config\n\ndef get_files_list(dir_path, extension):\n return [f for f in os.listdir(di... | [
[
"pandas.ExcelWriter"
]
] |
yck011522/motion-planners | [
"8665bbfd6e502ebc25b68e8a34b58b459e65cfd2"
] | [
"motion_planners/trajectory/limits.py"
] | [
"import time\nimport numpy as np\n\nfrom .retime import EPSILON, get_max_velocity, poly_from_spline\nfrom ..utils import INF, elapsed_time\nfrom .retime import get_interval\n\ndef old_check_spline(spline, v_max=None, a_max=None, start_idx=None, end_idx=None):\n # TODO: be careful about time vs index (here is ind... | [
[
"numpy.poly1d",
"numpy.greater",
"numpy.isnan",
"numpy.linalg.norm",
"scipy.optimize.minimize",
"numpy.random.uniform"
]
] |
bthtsang/DeepClassifierNoveltyDetection | [
"cb12d5ef3064f878ff0db9d68413ad13b86538d8"
] | [
"classify_noveltydetect.py"
] | [
"import numpy as np\nimport keras.backend as K\nimport os\nimport matplotlib\nmatplotlib.use('Agg')\nimport matplotlib.pyplot as plt\n\nimport joblib\nfrom light_curve import LightCurve # For using Naul's LightCurve class\nfrom keras.preprocessing.sequence import pad_sequences\nfrom sklearn.model_selection import S... | [
[
"matplotlib.pyplot.legend",
"matplotlib.pyplot.imshow",
"numpy.savez",
"sklearn.metrics.confusion_matrix",
"numpy.concatenate",
"sklearn.metrics.precision_recall_fscore_support",
"sklearn.preprocessing.LabelEncoder",
"numpy.where",
"numpy.trace",
"matplotlib.pyplot.tight_la... |
megvii-research/tlsc | [
"b6c7c927666dc3020e8f7d25a1342fc421cf50c8"
] | [
"setup.py"
] | [
"# ------------------------------------------------------------------------\n# Copyright (c) 2021 megvii-model. All Rights Reserved.\n# ------------------------------------------------------------------------\n# Modified from BasicSR (https://github.com/xinntao/BasicSR)\n# Copyright 2018-2020 BasicSR Authors\n# ---... | [
[
"torch.cuda.is_available"
]
] |
nightstorm0909/pEvoNAS | [
"293963f7dd9a46d93a5bf180719e4f7220a24ea6"
] | [
"s2/consensus.py"
] | [
"import torch\n\nclass consensus:\n def __init__(self, arch_flag, population, edge2index, op_dict, op_position, topk, weighted = False):\n self.arch_flag = arch_flag\n self.population = population\n self.pop_size = population.get_population_size()\n self.population.print_population_fitness()\n self.... | [
[
"torch.topk",
"torch.zeros_like"
]
] |
VietDunghacker/VarifocalNet | [
"f57917afb3c29ceba1d3c4f824d10b9cc53aaa40"
] | [
"mmdet/models/roi_heads/bbox_heads/bbox_head.py"
] | [
"import torch\nimport torch.nn as nn\nimport torch.nn.functional as F\nfrom mmcv.runner import auto_fp16, force_fp32\nfrom torch.nn.modules.utils import _pair\n\nfrom mmdet.core import build_bbox_coder, multi_apply, multiclass_nms\nfrom mmdet.models.builder import HEADS, build_loss\nfrom mmdet.models.losses import ... | [
[
"torch.nn.functional.softmax",
"torch.cat",
"torch.nn.init.constant_",
"torch.gather",
"torch.sum",
"torch.nn.Linear",
"torch.nn.AvgPool2d",
"torch.nn.init.normal_",
"torch.nonzero",
"torch.nn.modules.utils._pair",
"torch.stack"
]
] |
PythonBiellaGroup/ModernDataEngineering | [
"369fcb89d119ccd1d73882e492cf7c5331087d20"
] | [
"scripts/etl-anagrafica-ospedali.py"
] | [
"import pandas as pd\nimport os\nimport numpy as np\nfrom sqlalchemy import create_engine\n\ncurrent_dir = os.getcwd()\nextract_folder = os.path.join(current_dir, \"data/ospedali.csv\")\n\n# Extract data\ndf_ospedali = pd.read_csv(extract_folder)\n\n# Transform data\n\n# --------------------------------------------... | [
[
"pandas.read_csv",
"pandas.to_datetime",
"numpy.select"
]
] |
spcornelius/symopt | [
"6f276ca07cc266af1cd58758a0cf413ab85f2591"
] | [
"symopt/solvers/scipy.py"
] | [
"from scipy.optimize import minimize\nfrom sympy import Equality\n\nfrom symopt.exceptions import IncompatibleSolverError\nfrom symopt.util import negated\n\n__all__ = []\n__all__.extend([\n 'prepare_scipy',\n 'solve_slsqp',\n 'solve_cobyla'\n])\n\n\ndef prepare_scipy(prob, *param_vals):\n \"\"\" Conver... | [
[
"scipy.optimize.minimize"
]
] |
wendychen0521/DualStyleGAN | [
"67751d90d1a23358f6cbe5d23e3475cbe2cebff2"
] | [
"refine_exstyle.py"
] | [
"import os\r\n\r\nimport numpy as np\r\nimport torch\r\nfrom torch import optim\r\nfrom util import save_image\r\nimport argparse\r\nfrom argparse import Namespace\r\nfrom torchvision import transforms\r\nfrom torch.nn import functional as F\r\nimport torchvision\r\nfrom PIL import Image\r\nfrom tqdm import tqdm\r\... | [
[
"torch.optim.Adam",
"torch.roll",
"torch.cat",
"torch.load",
"torch.tensor",
"torch.no_grad",
"torch.stack",
"numpy.load"
]
] |
fadeevla/pytorch-deeplab-xception | [
"dd4e092ecc47ec94e851b36523d243a484f6c672"
] | [
"dataloaders/datasets/MFCDataset.py"
] | [
"\r\nfrom torch.utils.data import Dataset\r\nfrom torchvision import transforms\r\nfrom PIL import Image\r\nimport os\r\nfrom os.path import join\r\nimport random\r\nimport numpy as np\r\nimport sys\r\n\r\n\r\n\r\nseed = random.randrange(sys.maxsize)\r\n\r\nclass MFCDataset(Dataset):\r\n \r\n def _listdir(sel... | [
[
"numpy.array",
"numpy.zeros_like"
]
] |
jatinchowdhury18/RNNAudioEffects | [
"df4de8e1549bbe1d27fc1760a35c1557039fe64f"
] | [
"hysteresis/hysteresis_drive.py"
] | [
"# %%\n# Load dependencies\nimport numpy as np\nimport matplotlib.pyplot as plt\nimport audio_dspy as adsp\nimport scipy.signal as signal\nimport tensorflow as tf\nfrom tensorflow import keras\nimport librosa\nfrom tqdm import tqdm\nimport os\nimport random\nimport sys\n\nsys.path.append('..')\nfrom utils.utils imp... | [
[
"matplotlib.pyplot.legend",
"numpy.split",
"numpy.asarray",
"tensorflow.keras.layers.InputLayer",
"matplotlib.pyplot.plot",
"numpy.ones_like",
"numpy.reshape",
"numpy.stack",
"tensorflow.keras.layers.GRU",
"matplotlib.pyplot.figure",
"matplotlib.pyplot.semilogx",
"m... |
ireina7/zsl-seg | [
"6dc214bd418c8ca12458095e59459487c0b07893"
] | [
"src/model/util.py"
] | [
"# -*- coding: utf-8 -*-\n\nimport numpy as np\nimport math\nimport os\nimport sys\nsys.path.append(\"..\")\nfrom src.config import *\nfrom src.util import error\n\ndef get_embeddings():\n file = [\"fasttext.txt\", \"word2vec.txt\", \"all.txt\"]\n embeddings = {}\n for i in file:\n dic = {}\n ... | [
[
"numpy.concatenate",
"numpy.zeros"
]
] |
pierreolivierbonin/test_dash_app | [
"e21b78d5d8a75d9f77498900438c89da3968301c"
] | [
"Sunny Street Viz for Social Good app.py"
] | [
"import plotly.graph_objects as go\r\nimport dash\r\nimport plotly.express as px\r\nimport pandas as pd\r\nimport dash_bootstrap_components as dbc\r\nimport dash_core_components as dcc\r\nimport dash_html_components as html\r\nfrom dash.dependencies import Input, Output, State\r\n# dash bootstrap 1.0 or higher\r\n\... | [
[
"pandas.read_csv",
"pandas.to_datetime",
"pandas.pivot_table"
]
] |
morristai/qlib | [
"c459f9b5378ce6bd2395593a57be70c956b6ce04"
] | [
"qlib/contrib/estimator/estimator.py"
] | [
"# Copyright (c) Microsoft Corporation.\n# Licensed under the MIT License.\n\n# coding=utf-8\n\nimport pandas as pd\n\nimport os\nimport copy\nimport json\nimport yaml\nimport pickle\n\nimport qlib\nfrom ..evaluate import risk_analysis\nfrom ..evaluate import backtest as normal_backtest\nfrom ..evaluate import long... | [
[
"pandas.concat"
]
] |
rolandqli/arkouda | [
"d5bc98177c74338cea829e98cd3efa318c9aa76e"
] | [
"benchmarks/reduce.py"
] | [
"#!/usr/bin/env python3 \n\nimport time, argparse\nimport numpy as np\nimport arkouda as ak\n\nOPS = ('sum', 'prod', 'min', 'max')\n\ndef time_ak_reduce(N_per_locale, trials, dtype, random):\n print(\">>> arkouda reduce\")\n cfg = ak.get_config()\n N ... | [
[
"numpy.arange",
"numpy.random.random",
"numpy.random.randint",
"numpy.isclose"
]
] |
sethah/deeptennis | [
"a689c5f1d6f5ff1d665aec99b8db6262d3442c3a"
] | [
"scripts/make_tracking_video.py"
] | [
"import argparse\nfrom typing import List\n\nimport cv2\nimport numpy as np\nfrom typing import NamedTuple, Tuple\nimport logging\nimport json\nimport os\nfrom pathlib import Path\nimport tqdm\nimport shutil\n\nimport deeptennis.utils as utils\n\n\nclass Box(NamedTuple):\n score: float\n coords: np.ndarray\n ... | [
[
"numpy.linalg.inv",
"numpy.int32",
"numpy.array",
"numpy.ones"
]
] |
brian-j-cao/models | [
"e0ed507504b4efa6780e244677ded563b36b0ee7"
] | [
"official/projects/movinet/tools/export_saved_model.py"
] | [
"# Copyright 2022 The TensorFlow Authors. All Rights Reserved.\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n# http://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless requ... | [
[
"tensorflow.train.Checkpoint",
"tensorflow.keras.models.save_model",
"tensorflow.ones",
"tensorflow.function",
"tensorflow.keras.layers.InputSpec",
"tensorflow.TensorSpec"
]
] |
mehta-lab/pysero | [
"c8dbdc8c98c134dd9647e691bc92eaef4301effa"
] | [
"array_analyzer/extract/image_parser.py"
] | [
"import cv2 as cv\nimport numpy as np\nimport itertools\nimport math\nimport pandas as pd\nfrom types import SimpleNamespace\nfrom scipy import spatial\n\nfrom skimage.transform import hough_circle, hough_circle_peaks\nfrom skimage.feature import canny\nfrom skimage.morphology import binary_closing, binary_dilation... | [
[
"numpy.expand_dims",
"numpy.sum",
"numpy.abs",
"numpy.sqrt",
"numpy.median",
"pandas.DataFrame",
"numpy.bitwise_xor",
"numpy.ones",
"numpy.argmax",
"numpy.mean",
"numpy.argmin",
"numpy.average",
"numpy.argsort",
"numpy.array",
"numpy.zeros",
"scipy.s... |
toujika/fairseq | [
"0e68173babf843b543d909723bd5de2b7390e375"
] | [
"generate.py"
] | [
"#!/usr/bin/env python3 -u\n# Copyright (c) 2017-present, Facebook, Inc.\n# All rights reserved.\n#\n# This source code is licensed under the license found in the LICENSE file in\n# the root directory of this source tree. An additional grant of patent rights\n# can be found in the PATENTS file in the same directory... | [
[
"torch.cuda.is_available"
]
] |
davidgolub/QuestionGeneration | [
"6b31e1a8855774230051093ca24ba0a7750a6712"
] | [
"dnn_units/lstm_attention.py"
] | [
"\"\"\"Sequence to Sequence models.\"\"\"\nimport torch\nimport torch.nn as nn\nfrom torch.autograd import Variable\nimport math\nimport torch.nn.functional as F\nimport numpy as np\nfrom helpers import torch_utils\n\n\nclass StackedAttentionLSTM(nn.Module):\n \"\"\"Deep Attention LSTM.\"\"\"\n\n def __init__... | [
[
"torch.nn.Softmax",
"torch.nn.Dropout",
"torch.nn.functional.softmax",
"torch.Tensor",
"torch.nn.LSTM",
"torch.cat",
"torch.zeros",
"torch.nn.Embedding",
"torch.nn.Tanh",
"torch.nn.Linear",
"torch.nn.functional.sigmoid",
"torch.bmm",
"torch.stack",
"torch.nn... |
priyathamkat/unpaired-image-denoising | [
"de059cd0ad6bda7d615dadcdb4f7408b165cdc8e"
] | [
"src/glow/invertible_layers/additive.py"
] | [
"import torch\nimport torch.nn as nn\n\nfrom .invertible import InvertibleModule\n\ncuda_device = torch.device(\"cuda:0\")\n\n\nclass Additive(InvertibleModule):\n def __init__(self, num_channels, net_channels=128):\n super().__init__()\n assert num_channels % 2 == 0\n self.split_size = num_... | [
[
"torch.cat",
"torch.nn.init.zeros_",
"torch.randn",
"torch.nn.Conv2d",
"torch.no_grad",
"torch.nn.BatchNorm2d",
"torch.split",
"torch.device",
"torch.allclose",
"torch.nn.ReLU"
]
] |
pleap-inc/face-match | [
"8a705e9f2a9258c66cb340cd6e16e316a7790873"
] | [
"code.py"
] | [
"import face_recognition\nimport matplotlib.pyplot as plt\nimport glob\nimport json\nimport array \nimport sys\nfrom tqdm import tqdm\n\nargs = sys.argv\n# フォルダ内の全画像ファイルのパスを取得\nfile_paths = []\n\nfiles = glob.glob(\"./tokyo_hot/*\")\nbar_analyze_img = tqdm(total = len(files))\nprint(\"____________________start appe... | [
[
"matplotlib.pyplot.Rectangle",
"matplotlib.pyplot.show",
"matplotlib.pyplot.subplots"
]
] |
devanshusomani99/myFM | [
"d8e3d93de7c4a3dc19551c07d5f1d71d13f6abc6"
] | [
"examples/ml-10m-regression.py"
] | [
"from myfm.gibbs import MyFMOrderedProbit\nfrom typing import List, Dict, Union\nimport pandas as pd\nimport argparse\nimport pickle\nimport numpy as np\nimport myfm\nfrom myfm import RelationBlock, MyFMOrderedProbit, MyFMRegressor\nfrom myfm.utils.benchmark_data import MovieLens10MDataManager\nfrom myfm.utils.call... | [
[
"pandas.concat",
"numpy.unique"
]
] |
hongxu-jia/tensorboard | [
"98d4dadc61fd5a0580bed808653c59fb37748893"
] | [
"tensorboard/plugins/scalar/scalars_plugin_test.py"
] | [
"# -*- coding: utf-8 -*-\n# Copyright 2017 The TensorFlow Authors. All Rights Reserved.\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n# http://www.apache.org/licenses/LICE... | [
[
"tensorflow.reduce_mean",
"tensorflow.reduce_sum",
"tensorflow.compat.v1.enable_eager_execution",
"tensorflow.test.main",
"tensorflow.compat.v1.summary.histogram"
]
] |
JaeZheng/unet | [
"f0fac997a1ee7ce962e14d51f97f704229fc1a75"
] | [
"main.py"
] | [
"from model import *\nfrom data import *\nimport os\nfrom keras.models import load_model\nimport tensorflow as tf\nimport keras.backend.tensorflow_backend as KTF\nfrom data import meanIOU\n\n# 指定显卡\nos.environ[\"CUDA_VISIBLE_DEVICES\"] = \"0\"\n# 自适应分配显存\nconfig = tf.ConfigProto()\nconfig.gpu_options.allow_growth=T... | [
[
"tensorflow.ConfigProto",
"tensorflow.Session"
]
] |
feklee/tensorflow | [
"8e073e237ed258dac220d3cc1a177a08e43f2c0d"
] | [
"tensorflow/python/ops/array_ops.py"
] | [
"# Copyright 2015 The TensorFlow Authors. All Rights Reserved.\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n# http://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless requ... | [
[
"tensorflow.python.ops.gen_math_ops.select_v2",
"tensorflow.python.util.tf_decorator.make_decorator",
"tensorflow.python.ops.gen_array_ops.list_diff",
"tensorflow.python.framework.ops.RegisterGradient",
"tensorflow.python.ops.gen_array_ops.strided_slice",
"tensorflow.python.ops.gen_array_o... |
thomas-li-sjtu/InterpretablePPSM | [
"72d6190c39cd80dbde562d99e813ebb1ba1be0e2"
] | [
"input_pipeline.py"
] | [
"import numpy as np\nimport tensorflow as tf\nimport os\nimport myPickle\n\nXNAME = 'X.txt'\nCMNAME = 'charmap.pickle'\nENCODING = 'ascii'\nbuffer_size = 10000\n\n# Special tokens\nMASK = 3\nEND = 2\nPAD = 0\n################\n\nMAX_MASKED = .3\n\n\n# def mask(x, xl):\n# if INCLUDE_END_SYMBOL: xl -= 1\n# k = ... | [
[
"numpy.array",
"numpy.zeros",
"tensorflow.data.Dataset.from_generator",
"numpy.random.randint"
]
] |
ddh-mulder/carvana-challenge | [
"a02626b5a9e06805d1e56a6f3a676216358dbba5"
] | [
"src/nn/losses.py"
] | [
"import torch.nn as nn\nimport torch.nn.functional as F\n\n\nclass BCELoss2d(nn.Module):\n def __init__(self, weight=None, size_average=True):\n super(BCELoss2d, self).__init__()\n self.bce_loss = nn.BCELoss(weight, size_average)\n\n def forward(self, logits, targets):\n probs = F.sigmoid... | [
[
"torch.nn.functional.sigmoid",
"torch.nn.BCELoss"
]
] |
basiralab/Kaggle-BrainNetPrediction-Toolbox | [
"1080c2b59cea98fb72e1e24578e1796e206b5131"
] | [
"Team 8/findparams.py"
] | [
"\"\"\"\nThis code uses built-in cross validation to find the most optimal hyper parameters for each model that is used in the mapping function.\nIt is recommended but not required to run this code before running main code to get a stronger model. Please keep in mind that running\nthis code uses all the cpu cores a... | [
[
"pandas.read_csv",
"sklearn.model_selection.RandomizedSearchCV",
"pandas.DataFrame",
"sklearn.ensemble.GradientBoostingRegressor",
"sklearn.neighbors.KNeighborsRegressor",
"sklearn.feature_selection.SelectKBest",
"sklearn.ensemble.AdaBoostRegressor"
]
] |
stibbs1998/admissions_internship | [
"43d0bd7152493966391418ffe21f844db4997f45"
] | [
"src/data/locate_school.py"
] | [
"############################\n############################\n\n# Import libraries\n\nimport numpy as np\nimport pandas as pd\nimport pickle as pkl\nimport operator\nimport warnings\nimport csv\nwarnings.filterwarnings('ignore')\n\n# Import a ProgressBar\n\nfrom progressbar import ProgressBar\npbar = ProgressBar()\n... | [
[
"pandas.read_csv"
]
] |
fanhenghui/NiftyNet | [
"1f740b554dfdf06be28899658a71218c4dcc2104"
] | [
"niftynet/engine/application_factory.py"
] | [
"# -*- coding: utf-8 -*-\n\"\"\"\nLoading modules from a string representing the class name\nor a short name that matches the dictionary item defined\nin this module\n\"\"\"\nfrom __future__ import absolute_import\nfrom __future__ import division\nfrom __future__ import print_function\n\nimport importlib\nimport os... | [
[
"tensorflow.logging.fatal"
]
] |
WanglinLi595/OpenCV_Image_Process_Study | [
"02401790f06b20e3e2a14a01940f65f28de31e5b"
] | [
"test_code/test_3_11_threshold.py"
] | [
"#!/usr/bin/env python\n# coding=utf-8\n'''\n@描述: 图片简单阈值化\n@版本: V1_0\n@作者: LiWanglin\n@创建时间: 2020.02.11\n@最后编辑人: LiWanglin\n@最后编辑时间: 2020.02.11\n'''\n\nimport cv2 as cv\nimport numpy as np\nfrom matplotlib import pyplot as plt\n\nimg = cv.imread('./test_image/gradient.png',0)\nret,thresh1 = cv.threshold(img,127,255... | [
[
"matplotlib.pyplot.imshow",
"matplotlib.pyplot.yticks",
"matplotlib.pyplot.title",
"matplotlib.pyplot.subplot",
"matplotlib.pyplot.xticks",
"matplotlib.pyplot.show"
]
] |
m2lines/subgrid | [
"3de5d14c5525a62529d43cbafccda716c74e32df"
] | [
"swm-master/swm-master/docu/matvis/scripts/forc_vis.py"
] | [
"import numpy as np\nimport matplotlib.pyplot as plt\nfrom matplotlib import gridspec\n\nplt.rcParams['mathtext.fontset'] = 'cm'\nplt.rcParams['mathtext.rm'] = 'serif'\n\nparam = dict()\n\nparam['nx'] = 128 # number of grid points in x-direction\nparam['ny'] = 128 # number of grid points... | [
[
"matplotlib.pyplot.tight_layout",
"numpy.arange",
"numpy.cos",
"matplotlib.pyplot.savefig",
"numpy.sin",
"matplotlib.pyplot.subplot",
"numpy.zeros_like",
"matplotlib.gridspec.GridSpec",
"numpy.meshgrid",
"matplotlib.pyplot.figure"
]
] |
levtelyatnikov/graph_edge_generation | [
"e1d867475bece351f9ed49fabf0505e39cf41f6b"
] | [
"models/edge_generation/bernulyEG.py"
] | [
"import torch\n\nclass GumbleSigmoid(torch.nn.Module):\n def __init__(self):\n super(GumbleSigmoid, self).__init__()\n self.temperature = torch.tensor([1], dtype=torch.float32).to(torch.device('cuda:2')) #torch.nn.Parameter(torch.Tensor([5]))\n self.eps = 10e-5\n\n def forward(self, x, ta... | [
[
"torch.empty_like",
"torch.tensor",
"torch.log",
"torch.arange",
"torch.stack",
"torch.device",
"torch.clamp"
]
] |
SaravananM21/pyNastran | [
"d89a59a918e8d2262e3d8e6abd01abdc37046cdf"
] | [
"pyNastran/bdf/cards/test/utils.py"
] | [
"\"\"\"defines testing utils\"\"\"\nimport os\nfrom io import StringIO\nimport inspect\nfrom typing import Tuple, List, Dict\n\nimport numpy as np\nfrom cpylog import SimpleLogger\n\nfrom pyNastran.bdf.bdf import BDF, read_bdf\nfrom pyNastran.bdf.mesh_utils.delete_bad_elements import element_quality\nfrom pyNastran... | [
[
"numpy.arange",
"numpy.zeros",
"numpy.allclose"
]
] |
elifesciences-publications/accumulating_puffs | [
"9ebed68416284cddc85c9aeb0879b87eff5fe598"
] | [
"hardware/ni845x.py"
] | [
"import ctypes\nimport numpy as np\n\nMAX_SIZE = 1024\nDEV_SIZE = 256\n\nni845x_dll = ctypes.windll.LoadLibrary('Ni845x.dll')\n\nclass Ni845xError(Exception):\n def __init__(self, status_code):\n\n message = ctypes.create_string_buffer(MAX_SIZE)\n \n ni845x_dll.ni845xStatusToString(status_co... | [
[
"numpy.asarray",
"numpy.arange",
"numpy.sum",
"numpy.ones"
]
] |
karolisjan/Project | [
"0f58b7cdf6c9b1b777c039ea4267da8e184a17d2"
] | [
"examples/utils.py"
] | [
"import matplotlib.pyplot as plt\nfrom matplotlib.patches import Rectangle\n\nfrom IPython.core.display import display, HTML\n\n# from rpy2.robjects import r, pandas2ri\n# pandas2ri.activate()\n\n\ndef toggle_code(hide_code_by_default: bool=False):\n return HTML('''\n <a id='index'></a>\n <script>\... | [
[
"matplotlib.patches.Rectangle",
"matplotlib.pyplot.subplots"
]
] |
msinkec/classla-stanfordnlp | [
"0390e2e23d9dceec6ac220a9ed0d2093b6246ba1"
] | [
"stanfordnlp/models/common/utils.py"
] | [
"\"\"\"\nUtility functions.\n\"\"\"\nimport os\nfrom collections import Counter\nimport random\nimport json\nimport unicodedata\nimport torch\n\nfrom stanfordnlp.models.common.constant import lcode2lang\nimport stanfordnlp.models.common.seq2seq_constant as constant\nimport stanfordnlp.utils.conll18_ud_eval as ud_ev... | [
[
"torch.optim.Adam",
"torch.optim.Adagrad",
"torch.optim.Adamax",
"torch.optim.SGD"
]
] |
allen-chiang/Time-Series-Transformer | [
"d1b9b7d4f2e674095b44af6ebdbcd0d25616f203"
] | [
"time_series_transform/io/numpy.py"
] | [
"import numpy as np\nimport pandas as pd\nfrom time_series_transform.io.base import io_base\nfrom time_series_transform.transform_core_api.base import (\n Time_Series_Data_Collection,\n Time_Series_Data\n )\n\n\nclass Numpy_IO (io_base):\n def __init__(self, time_series, timeSeriesColIx, mainCategoryCol... | [
[
"pandas.DataFrame"
]
] |
bundie1990/aimet | [
"3cee2b286df680bc9fce301a695a1e757b5b228f"
] | [
"TrainingExtensions/torch/src/python/aimet_torch/quantsim.py"
] | [
"# /usr/bin/env python3.5\n# -*- mode: python -*-\n# =============================================================================\n# @@-COPYRIGHT-START-@@\n#\n# Copyright (c) 2019-2020, Qualcomm Innovation Center, Inc. All rights reserved.\n#\n# Redistribution and use in source and binary forms, with or without... | [
[
"torch.onnx.export",
"torch.jit.load",
"torch.jit.trace",
"torch.no_grad",
"torch.save"
]
] |
RiverTate/vaspvis | [
"21d426be84b523d81afb9e4a9b43044f9a792b64"
] | [
"vaspvis/dos.py"
] | [
"import matplotlib.pyplot as plt\nfrom matplotlib.ticker import MaxNLocator, LogLocator\nfrom pymatgen.io.vasp.outputs import Vasprun\nfrom pymatgen.io.vasp.inputs import Poscar, Incar\nfrom pymatgen.electronic_structure.core import Spin, Orbital\nfrom pymatgen.core.periodic_table import Element\nfrom pychemia.code... | [
[
"numpy.squeeze",
"numpy.max",
"numpy.mean",
"scipy.interpolate.interp2d",
"numpy.where",
"numpy.hstack",
"numpy.arange",
"matplotlib.pyplot.gcf",
"numpy.diff",
"numpy.load",
"numpy.repeat",
"numpy.zeros",
"numpy.isin",
"numpy.logical_not",
"numpy.min",
... |
incognite-lab/myGym | [
"a093a4a0f75ba081fbcf3fef70aca14dc2078997"
] | [
"myGym/envs/base_env.py"
] | [
"import pybullet_data\nimport glob\nimport pybullet\nimport pybullet_utils.bullet_client as bc\nimport time\nimport numpy as np\nfrom gym.utils import seeding\nimport gym\nimport os\nimport inspect\nfrom myGym.envs.camera import Camera\nimport pkg_resources\ncurrentdir = pkg_resources.resource_filename(\"myGym\", \... | [
[
"numpy.arange",
"numpy.array"
]
] |
dmdu/rlmolecule | [
"5c9187775ef99ea6a06992788116754b1b308a8c"
] | [
"tests/alphazero/test_molecule_alphazero.py"
] | [
"import os\nfrom unittest.mock import MagicMock\n\nimport numpy as np\nimport pytest\nimport tensorflow as tf\n\nfrom rlmolecule.alphazero.alphazero import AlphaZero\nfrom rlmolecule.molecule.builder.builder import MoleculeBuilder\nfrom rlmolecule.tree_search.reward import LinearBoundedRewardFactory, RankedRewardFa... | [
[
"tensorflow.keras.Model",
"numpy.isfinite",
"numpy.isclose"
]
] |
daniellawson9999/compositional_reinforcement_learning | [
"aa20413485d654d29cfcaad8ddb8fd07efcafc8c"
] | [
"envs/cross_maze_ant_env.py"
] | [
"\"\"\"Implements an ant whose goal is to reach a target in a maze\"\"\"\n\nimport os\n\nimport numpy as np\n\nfrom rllab.core.serializable import Serializable\n#from sac.misc.utils import PROJECT_PATH\nfrom misc.utils import PROJECT_PATH\n\nfrom .helpers import random_point_in_circle, get_random_goal_logs\nfrom .r... | [
[
"numpy.array"
]
] |
laurafroelich/weather_wind_power | [
"851d023960ea6b27d2c70dff86e34670bae43370"
] | [
"code/src/visualisation/weather_forecast.py"
] | [
"import plotly.graph_objs as go\nimport numpy as np\nimport ipywidgets\n\nfrom weather_wind.visualisation.geography import get_rotated_basemap, get_coastline_traces, get_country_traces\nfrom weather_wind.data_retrieval.weather_forecast import get_data_as_cube_and_lats_lons\n\n\ndef rotate_data_and_lats(grb_matrix_d... | [
[
"numpy.hstack"
]
] |
gregyjames/PruferSequences | [
"da72bcafdc8f2a1c0414ac62dd49cff32070c566"
] | [
"GraphBonus.py"
] | [
"import graphClass\nimport networkx as nx\nimport matplotlib.pyplot as plt\nimport warnings\n\n#Filter all matplotlib warnings\nwarnings.filterwarnings(\"ignore\")\n\n#Find the leaf with the lowest label\ndef findLowestLeaf(G):\n #Empty array of vertexes\n vertexes = []\n #Look through every vertex of the ... | [
[
"matplotlib.pyplot.show"
]
] |
abishek-raju/EVA4B2 | [
"189f4062c85d91f43c1381087a9c89ff794e5428"
] | [
"S12/tensornet/data/datasets/tinyimagenet.py"
] | [
"import os\nimport csv\nimport random\nimport requests\nimport zipfile\nimport numpy as np\nfrom io import BytesIO\nfrom PIL import Image\nfrom torch.utils.data import Dataset\n\nfrom tensornet.data.datasets.dataset import BaseDataset\n\n\nclass TinyImageNet(BaseDataset):\n \"\"\"Load Tiny ImageNet Dataset.\"\"\... | [
[
"numpy.random.seed",
"numpy.random.shuffle",
"numpy.stack",
"numpy.transpose",
"numpy.array"
]
] |
amirhosseinh77/Autonomous-Vehicle-Environment-Perception | [
"f834ea23f80eda6e33796a0b97c909b43da37eb3"
] | [
"main.py"
] | [
"from elements.yolo import YOLO, YOLO_Sign\nfrom elements.PINet import LaneDetection\nfrom elements.SGD import Inference\nfrom elements.asset import cityscape_xyz, kitti_xyz, apply_mask, ROI, kitti_xyz_dist, cityscape_xyz_dist, plot_one_box\nfrom elements.asset import horiz_lines, detect_lines\nimport matplotlib.py... | [
[
"numpy.round",
"numpy.where"
]
] |
canturan10/satellighte | [
"09c906fdf8b538296c488d0c2d86c344007f8666"
] | [
"satellighte/module.py"
] | [
"import os\nfrom typing import Dict, List, Union\n\nimport numpy as np\nimport pytorch_lightning as pl\nimport torch\n\nfrom . import api\nfrom .core import _get_arch_cls, _get_model_dir, _parse_saved_model_name\nfrom .utils import configure_batch, convert_json\nimport torchmetrics as tm\n\n\nclass Classifier(pl.Li... | [
[
"torch.no_grad",
"torch.tensor"
]
] |
sovaso/GeneticAlgorithmForHumanoidRobotWalk | [
"b14d7a562226b32dd7b4c5f2b056cf1478700ce3"
] | [
"code/genetic_algorithm.py"
] | [
"import gym\nimport numpy as np\nimport torch\nimport time\nimport random\nfrom gym.wrappers import Monitor\nimport torch.nn as nn\nimport torch.nn.functional as F\nfrom torch.distributions import MultivariateNormal\nimport torch.optim as optim\nimport math\nimport copy\nimport warnings\nimport pybulletgym\nfrom tr... | [
[
"numpy.random.choice",
"numpy.random.uniform",
"numpy.mean",
"numpy.argsort",
"numpy.zeros",
"numpy.sum"
]
] |
jens-38/UCI-ML-API | [
"bda73d73cb5abd600b877f2f15934cb58012531a"
] | [
"UCI_ML_Functions.py"
] | [
"# Functions to read, analyze, and download from UCI ML portal\n\n# ==========================================\n# Function to read UCI ML datasets table\n# ==========================================\ndef read_dataset_table(\n url=\"https://archive.ics.uci.edu/ml/datasets.php\", msg_flag=True\n):\n \"\"\"\n ... | [
[
"pandas.set_option",
"pandas.read_csv",
"pandas.DataFrame",
"pandas.read_html"
]
] |
Zilleplus/MachineLearning | [
"13e4fe996386d3f66b7866cc133ae9b26a6333d6"
] | [
"HML/chapter18/simpleNeuralNetworkPolicy.py"
] | [
"import gym\nimport numpy as np\nimport tensorflow as tf\nimport tensorflow.keras as keras\n\nenv = gym.make(\"CartPole-v1\")\n\nobs = env.reset()\n\nenv.render()\n\nn_inputs = 4 # 4 states in the obs [x, \\dot{x}, \\theta, \\dot{\\theta}]\nmodel = keras.models.Sequential([\n keras.layers.Dense(units=5, activat... | [
[
"tensorflow.constant",
"tensorflow.keras.layers.Dense",
"tensorflow.random.uniform",
"tensorflow.cast",
"numpy.concatenate",
"tensorflow.keras.optimizers.Adam",
"numpy.array",
"tensorflow.GradientTape"
]
] |
TejasAvinashShetty/krotov | [
"e2dd0fad2f07f41004d7beef53e8ebc75b0d6d9b"
] | [
"src/krotov/objectives.py"
] | [
"import sys\nimport copy\nfrom functools import partial\n\nimport qutip\nfrom qutip.solver import Result as QutipSolverResult\nimport numpy as np\n\nfrom .structural_conversions import (\n _nested_list_shallow_copy, extract_controls, extract_controls_mapping,\n plug_in_pulse_values, control_onto_interval, dis... | [
[
"numpy.sqrt"
]
] |
ZHAOZHIHAO/ClusterRouting | [
"ce0a7cbe73656956bcbfbfab53c023c1fb2bd5c6"
] | [
"src/utils.py"
] | [
"from __future__ import print_function\r\nimport numpy as np\r\nimport torch\r\nimport torch.nn.functional as F\r\nfrom torch.utils.data import DataLoader, Dataset\r\n\r\n\r\ndef train(args, model, device, train_loader, optimizer, epoch):\r\n model.train()\r\n correct = 0\r\n total_loss = 0\r\n for batc... | [
[
"numpy.random.choice",
"torch.nn.functional.cross_entropy",
"numpy.setdiff1d",
"numpy.stack",
"numpy.random.permutation",
"torch.no_grad",
"torch.stack",
"numpy.array"
]
] |
emilienDespres/scikit-decide | [
"2a3dd2d93e5e6d07984e1bc02b6e969261aeefbc"
] | [
"skdecide/discrete_optimization/rcpsp_multiskill/solvers/calendar_solver_iterative.py"
] | [
"# Copyright (c) AIRBUS and its affiliates.\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 __future__ import annotations\n\nimport random\nimport time\nfrom datetime import timedelta\nfrom typing import Any, Iterable, Optional, U... | [
[
"numpy.argwhere"
]
] |
ColdMatter/PhotonBEC | [
"c6bcf9bdefd267c8adde0d299cf5920b010c5022"
] | [
"EMCCD/EMCCD/EMCCD_backend.py"
] | [
"'''\n\tWritten by:\t\tJoao Rodrigues\n\tLast Update: \tOctober 16th 2020\n\n'''\n\n\nimport numpy as np\nimport copy\nimport ctypes\nimport socket\nimport time\n\n########## Parameters\nif socket.gethostname() == \"ph-photonbec5\":\n\tdll_file = r\"D:\\Control\\EMCCD\\atmcd32d.dll\"\n\n\nclass EMCCD():\n\n\t##### ... | [
[
"numpy.reshape",
"numpy.array",
"numpy.flip"
]
] |
Sreehari-S/mask-rcnn-benchmark | [
"b4434c39fccda80575276308da86b6e944540445"
] | [
"train_net.py"
] | [
"# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved.\nr\"\"\"\nBasic training script for PyTorch\n\"\"\"\n\n# Set up custom environment before nearly anything else is imported\n# NOTE: this should be the first import (no not reorder)\nfrom maskrcnn_benchmark.utils.env import setup_environment #... | [
[
"torch.distributed.init_process_group",
"torch.cuda.set_device",
"torch.cuda.empty_cache",
"torch.device",
"torch.nn.parallel.DistributedDataParallel"
]
] |
sighingnow/numba | [
"ae88a6ff4a41f76e50672a1af9d9aa66c205b51b"
] | [
"numba/targets/npyimpl.py"
] | [
"\"\"\"\nImplementation of functions in the Numpy package.\n\"\"\"\n\nfrom __future__ import print_function, division, absolute_import\n\nimport math\nimport sys\nimport itertools\nfrom collections import namedtuple\n\nfrom llvmlite.llvmpy import core as lc\n\nimport numpy as np\nimport operator\n\nfrom . import bu... | [
[
"numpy.dtype"
]
] |
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