repo_name stringlengths 6 130 | hexsha list | file_path list | code list | apis list |
|---|---|---|---|---|
LBJ-Wade/astrofunc_lensing_profile | [
"d2223705bc44d07575a5e93291375ab8e69ebfa8"
] | [
"astrofunc/LensingProfiles/sis_truncate.py"
] | [
"__author__ = 'sibirrer'\n\nimport numpy as np\n\nclass SIS_truncate(object):\n \"\"\"\n this class contains the function and the derivatives of the Singular Isothermal Sphere\n \"\"\"\n def function(self, x, y, theta_E, r_trunc, center_x=0, center_y=0):\n x_shift = x - center_x\n y_shift ... | [
[
"numpy.zeros_like",
"numpy.sqrt"
]
] |
ksasi/pytorch-lightning | [
"0009f29848a62d6a05226ec503631c3d4ed5081e"
] | [
"pytorch_lightning/trainer/training_loop.py"
] | [
"# Copyright The PyTorch Lightning team.\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n# http://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless required by applicable law... | [
[
"torch.distributed.destroy_process_group",
"torch.cuda.device",
"torch.cuda.empty_cache",
"numpy.argmax",
"numpy.cumsum",
"torch.cuda.amp.GradScaler"
]
] |
uncbiag/ICON | [
"2c34a1e876726cf2de105157675213ffb2f640ba"
] | [
"src/icon_registration/itk_wrapper.py"
] | [
"import itk\nimport matplotlib.pyplot as plt\nimport numpy as np\nimport torch\nimport torch.nn.functional as F\n\nimport icon_registration.pretrained_models\nimport icon_registration.network_wrappers\n\nimport icon_registration.config as config\n\ndef register_pair(model, image_A, image_B)->\"(itk.CompositeTransfo... | [
[
"numpy.array",
"torch.Tensor",
"torch.no_grad",
"torch.nn.functional.interpolate"
]
] |
Mapharazzo/video-palette | [
"900e690c78934872078047f42fa8e57ddd9c6663"
] | [
"plotting.py"
] | [
"import matplotlib.pyplot as plt\nimport numpy as np\n\n# Recommended parameters for (K, P)\n# Outputs variance, mean, x_axis\ngaussian_dict = {\n (4, 4): (0.02, 0.5, 200),\n (4, 6): (0, 0, 200),\n (4, 8): (0, 0, 200),\n (8, 4): (0, 0, 200),\n (8, 6): (0, 0, 200),\n (8, 8): (0, 0, 200),\n (12, ... | [
[
"numpy.load",
"numpy.exp",
"numpy.float32",
"numpy.sqrt",
"matplotlib.pyplot.show",
"matplotlib.pyplot.stackplot",
"matplotlib.pyplot.axis"
]
] |
HaemanthSP/keras-contrib | [
"f183ff70afb0450475b9d0381d4b9c7c07941fbc"
] | [
"keras_contrib/optimizers/ftml.py"
] | [
"from __future__ import absolute_import\nfrom tensorflow.keras.optimizers import Optimizer\nfrom tensorflow.keras import backend as K\n\n\nclass FTML(Optimizer):\n \"\"\"FTML optimizer.\n\n # Arguments\n lr: float >= 0. Learning rate.\n beta_1: float, 0 < beta < 1. Generally close to 0.5.\n ... | [
[
"tensorflow.keras.backend.int_shape",
"tensorflow.keras.backend.variable",
"tensorflow.keras.backend.zeros",
"tensorflow.keras.backend.square",
"tensorflow.keras.backend.update",
"tensorflow.keras.backend.pow",
"tensorflow.keras.backend.get_value",
"tensorflow.keras.backend.update_... |
amyymaa/dowhy | [
"88fa5c04d8b90e0eb7d044597470d552bf5ac89d"
] | [
"dowhy/causal_refuters/bootstrap_refuter.py"
] | [
"from dowhy.causal_refuter import CausalRefuter, CausalRefutation\nfrom dowhy.causal_estimator import CausalEstimator\nimport numpy as np\nimport random\nfrom sklearn.utils import resample\nimport logging\n\nclass BootstrapRefuter(CausalRefuter):\n \"\"\"\n Refute an estimate by running it on a random sample ... | [
[
"numpy.logical_not",
"numpy.random.normal",
"numpy.zeros",
"sklearn.utils.resample",
"numpy.mean",
"numpy.where",
"numpy.random.uniform"
]
] |
csayres/kaiju | [
"0b4ca4fab5322351b97b8316b2d755d91bc05c16"
] | [
"tests/test_unevenCBs.py"
] | [
"import pytest\nimport numpy\nfrom kaiju import RobotGrid, RobotGridCalib\nfrom kaiju import utils\nimport time\nnumpy.random.seed(0)\n\n\ndef test_unevenCBs(plot=False):\n hasApogee = True\n greed = 0.8\n phobia = 0.2\n\n xPos, yPos = utils.hexFromDia(17, pitch=22.4)\n seed = 1\n # cb = 2.5\n ... | [
[
"numpy.random.seed",
"numpy.random.uniform"
]
] |
tuanmp/MCGenerators | [
"d1befa2fd5e351171faddb2a12fab4e530703921"
] | [
"G4/HadronicInteractions/scripts/read.py"
] | [
"#!/usr/bin/env python\n\n# %%\nimport argparse\nimport numpy as np\n\ndef process_file(file_path, ouput_path):\n data = None\n with open(file_path, 'r') as f:\n for line in f.readlines():\n new_data = np.array(line.split()).reshape((-1, 5)).astype(np.float16)\n if not new_data.sh... | [
[
"numpy.savetxt",
"numpy.append"
]
] |
Quester-one/PFN | [
"2c77f81026a061e80f397c7889cca980819dddf3"
] | [
"PFN-nested/eval.py"
] | [
"import json\r\nimport logging\r\nimport sys\r\nimport torch\r\nimport argparse\r\nimport pickle\r\nimport numpy as np\r\nfrom utils.metrics import *\r\nfrom utils.helper import *\r\nfrom dataloader.dataloader import *\r\nfrom tqdm import tqdm\r\nfrom model.pfn import *\r\n\r\nlogging.basicConfig(format='%(asctime)... | [
[
"torch.no_grad",
"torch.cuda.is_available",
"torch.load"
]
] |
indra-ipd/SQN | [
"1e2f532117642f2207f7936ec8cdf47e96efe10d"
] | [
"sampleSY.py"
] | [
"#!/usr/bin/env python\n# -*- coding: utf-8 -*-\n# Copyright (C) 2019 Albert Berahas, Majid Jahani, Martin Takáč\n# \n# All Rights Reserved.\n# \n# Authors: Albert Berahas, Majid Jahani, Martin Takáč\n# \n# Please cite:\n# \n# A. S. Berahas, M. Jahani, and M. Takáč, \"Quasi-Newton Methods for \n# Deep Learning:... | [
[
"numpy.linalg.norm",
"numpy.matmul",
"numpy.zeros",
"numpy.squeeze",
"numpy.sum",
"numpy.linalg.inv",
"numpy.random.randn",
"numpy.diag"
]
] |
dragaosemchama/faceswap | [
"5c6f9370a18f1a1ca1e2d0175c9c9abfd405ab87"
] | [
"main.py"
] | [
"# coding: utf-8\nimport cv2\nimport numpy\nimport time\nfrom PIL import Image, ImageOps, ImageDraw, ImageEnhance\n\ndef detect(img, classifier):\n \"\"\"Função de detecção de padrão\n\n Entrada:\n img: uma imagem\n classifier: o classificador representando qual padrão deve s... | [
[
"numpy.array"
]
] |
zyouc518/crow | [
"e3fe92e329649fb82b3fef6c0ab5b732f1918900"
] | [
"Re-ID/newfeat_extract_feature.py"
] | [
"import sys\nsys.path.insert(0, '.')\nsys.path.append('../../')\n#from PCBModel_concat_norelu import PCBModel as Model\nfrom PCBModel_concat_res101_norelu import PCBModel as Model\nfrom torch.nn.parallel import DataParallel\nfrom utils import set_devices\nfrom utils import load_state_dict\nfrom torch.utils.data imp... | [
[
"numpy.concatenate",
"numpy.save",
"torch._utils._rebuild_tensor",
"torch.utils.data.DataLoader",
"torch.load",
"torch.nn.parallel.DataParallel"
]
] |
stungkit/Copycat-abstractive-opinion-summarizer | [
"04fe5393a7bb6883516766b762f6a0c530e95375"
] | [
"mltoolkit/mlmo/layers/mu_sigma_ffnn.py"
] | [
"import torch as T\nfrom torch.nn import Module\nfrom mltoolkit.mlmo.layers import Ffnn\n\n\nclass MuSigmaFfnn(Module):\n \"\"\"\n A single hidden layer feed-forward nn that outputs mu and sigma of a\n Gaussian distribution. The produced sigma is a vector with non-negative\n values.\n \"\"\"\n\n d... | [
[
"torch.exp"
]
] |
adamreeve/pytorch-lightning | [
"908e05880d4271ad32876311320d4465a008a710"
] | [
"pytorch_lightning/core/lightning.py"
] | [
"# Copyright The PyTorch Lightning team.\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n# http://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless required by applicable law... | [
[
"torch.distributed.is_available",
"torch._C._log_api_usage_once",
"torch.no_grad",
"torch.jit.save",
"torch.tensor",
"torch.onnx.export"
]
] |
sebhaner/OpenSfM | [
"99e647243a97acc3ae59d7cba6813d089a793f09"
] | [
"annotation_gui_gcp/run_ba.py"
] | [
"import argparse\nimport json\nimport logging\nimport os\nimport sys\nfrom collections import defaultdict\n\nimport numpy as np\nimport opensfm.reconstruction as orec\nfrom opensfm import dataset, log, multiview, pygeometry\nfrom opensfm import transformations as tf\nfrom opensfm import types\nfrom opensfm.align im... | [
[
"numpy.max",
"numpy.array",
"numpy.linalg.norm",
"numpy.isnan",
"numpy.median",
"numpy.linalg.det",
"numpy.mean",
"numpy.linalg.svd",
"numpy.sqrt"
]
] |
altosaar/deep-exponential-families-gluon | [
"80d69b54081f622c0012bb181aa6d8ab9a740f15"
] | [
"tests/test_fast_bernoulli.py"
] | [
"import numpy as np\nimport time\nimport distributions\nimport scipy.stats\nimport scipy.special\nimport mxnet as mx\nfrom mxnet import nd\n\n\nmx.random.seed(13343)\nnp.random.seed(2324)\n\n\ndef test_bernoulli_sampling():\n n_samples = 10000\n K = 10 # num factors\n C = 2 # num classes\n # latent variable i... | [
[
"numpy.testing.assert_allclose",
"numpy.array",
"numpy.random.binomial",
"numpy.random.rand",
"numpy.random.seed",
"numpy.sum",
"numpy.nonzero"
]
] |
vitskvara/shape-guided-anomaly-detection | [
"6685b2e0b97968a6d0f478d2920486da107b277f"
] | [
"scripts/basic_training/save_generated_images.py"
] | [
"# generic libraries\nimport numpy as np\nimport torch\nimport os, sys\nimport argparse\nfrom torchvision.utils import save_image\n\nparser = argparse.ArgumentParser()\nparser.add_argument('input',\n help='name of the input file')\nargs = parser.parse_args()\n\n# sgad\nSGADHOME='/home/skvara/work... | [
[
"torch.load"
]
] |
arav-agarwal2/MultiBench | [
"60a726ad205710fa9778ac9372762972f495149b"
] | [
"private_test_scripts/avgb.py"
] | [
"from unimodals.common_models import LeNet, MLP, Constant\nfrom private_test_scripts.all_in_one import all_in_one_train, all_in_one_test\nimport torch\nfrom torch import nn\nfrom datasets.avmnist.get_data import get_dataloader\nfrom fusions.common_fusions import Concat\nfrom training_structures.gradient_blend impor... | [
[
"torch.cuda.is_available",
"torch.load"
]
] |
jzhang1198/project5 | [
"21fe3c2aafa959081e291b2f4e79407fc1f19804"
] | [
"cluster/silhouette.py"
] | [
"import numpy as np\nfrom scipy.spatial.distance import cdist\n\nclass Silhouette:\n def __init__(self, metric: str = \"euclidean\"):\n \"\"\"\n inputs:\n metric: str\n the name of the distance metric to use\n \"\"\"\n\n self.metric = metric\n\n def score(... | [
[
"numpy.where",
"numpy.sum",
"scipy.spatial.distance.cdist",
"numpy.zeros"
]
] |
PAV-Laboratory/crypto_data_fetcher | [
"6cd79260a68add5283255f1e6ff03a9d79dd21ea",
"6cd79260a68add5283255f1e6ff03a9d79dd21ea"
] | [
"tests/test_bybit.py",
"tests/test_ftx.py"
] | [
"import time\nimport ccxt\nimport pandas as pd\nfrom unittest import TestCase\nfrom crypto_data_fetcher.bybit import BybitFetcher\n\nclass TestBybit(TestCase):\n def test_fetch_ohlcv_initial(self):\n bybit = ccxt.bybit()\n fetcher = BybitFetcher(ccxt_client=bybit)\n\n df = fetcher.fetch_ohlc... | [
[
"pandas.to_datetime"
],
[
"pandas.to_datetime"
]
] |
briancpark/greykite | [
"2f484978a7ed206ebd9356e02fc1fb881cd25205"
] | [
"greykite/tests/sklearn/estimator/test_base_silverkite_estimator.py"
] | [
"import datetime\n\nimport numpy as np\nimport modin.pandas as pd\nimport pytest\nfrom sklearn.exceptions import NotFittedError\nfrom sklearn.metrics import mean_absolute_error\nfrom sklearn.metrics import mean_squared_error\nfrom testfixtures import LogCapture\n\nimport greykite.common.constants as cst\nfrom greyk... | [
[
"numpy.repeat",
"numpy.arange",
"sklearn.metrics.mean_squared_error",
"numpy.random.randn"
]
] |
dashmoment/facerecognition | [
"d19217e9a146cac65579ff8e0251e9ca26c2ec95"
] | [
"py/facerec/classifier.py"
] | [
"#!/usr/bin/env python\n# -*- coding: utf-8 -*-\n\n# Copyright (c) Philipp Wagner. All rights reserved.\n# Licensed under the BSD license. See LICENSE file in the project root for full license information.\n\nfrom facerec.distance import EuclideanDistance\nfrom facerec.util import asRowMatrix\nimport logging\nimpor... | [
[
"numpy.bincount",
"numpy.array",
"numpy.asarray",
"sklearn.svm.SVC",
"numpy.argsort",
"numpy.append"
]
] |
WeiwenRen/spark-timeseries | [
"f50592901a169c2ade4593dd6035372b121b20ca"
] | [
"python/sparkts/models/test/test_GARCH.py"
] | [
"import numpy as np\n\nfrom sparkts.models import ARGARCH, GARCH\nfrom sparkts.models.ARGARCH import ARGARCHModel\nfrom sparkts.models.GARCH import GARCHModel\nfrom sparkts.test.test_utils import PySparkTestCase\n\n\nclass FitGARCHModelTestCase(PySparkTestCase):\n def test_log_likelihood(self):\n model = ... | [
[
"numpy.array"
]
] |
antonyvm1102/Redbox | [
"8aa7feeaa6513275e7e78ed6cc049bed50bf1ec2"
] | [
"validate_rms_frequency_domain.py"
] | [
"import signal_processing as sp\r\nimport time\r\nimport matplotlib.pyplot as plt\r\nimport numpy as np\r\nimport math\r\n\r\n\"\"\"\r\nValidate translation of known time signal to RMS values per 1/3 octave band frequencies\r\n\"\"\"\r\n\r\nstart_time = time.time()\r\n\r\nsampling_rate = 400\r\nn_samples = 2**19\r\... | [
[
"numpy.zeros_like",
"numpy.sin",
"matplotlib.pyplot.xscale",
"matplotlib.pyplot.xlim",
"matplotlib.pyplot.grid",
"matplotlib.pyplot.xlabel",
"matplotlib.pyplot.plot",
"matplotlib.pyplot.legend",
"matplotlib.pyplot.suptitle",
"matplotlib.pyplot.ylabel",
"matplotlib.pyplo... |
cc13ny/keras | [
"172fa11ecce5aff8f359c8eec32b3cf1f76d1312"
] | [
"tests/keras/losses_test.py"
] | [
"import pytest\nimport numpy as np\n\nfrom keras import losses\nfrom keras import backend as K\n\n\nallobj = [losses.mean_squared_error,\n losses.mean_absolute_error,\n losses.mean_absolute_percentage_error,\n losses.mean_squared_logarithmic_error,\n losses.squared_hinge,\n ... | [
[
"numpy.random.random",
"numpy.random.randint"
]
] |
lippman1125/SSH_RESNET50 | [
"77c5e19e03d07834c4beaa8cbf85fc714ca0f4d6"
] | [
"lib/setup.py"
] | [
"# --------------------------------------------------------\n# Fast R-CNN\n# Copyright (c) 2015 Microsoft\n# Licensed under The MIT License [see LICENSE for details]\n# Written by Ross Girshick\n# --------------------------------------------------------\n\nimport os\nfrom os.path import join as pjoin\nfrom setuptoo... | [
[
"numpy.get_numpy_include",
"numpy.get_include"
]
] |
wanglab-georgetown/JOINT | [
"044a2ee6122d7e0cf61108d486e6f2cd12240d9f"
] | [
"joint/init_clusters.py"
] | [
"import numpy as np\n\nfrom sklearn.impute import SimpleImputer,KNNImputer\nfrom sklearn.decomposition import PCA\nfrom sklearn.cluster import KMeans\nfrom sklearn.cluster import SpectralClustering\nfrom sklearn.metrics.cluster import adjusted_rand_score\nfrom sklearn.preprocessing import StandardScaler\n\n\ndef ge... | [
[
"sklearn.metrics.cluster.adjusted_rand_score",
"sklearn.impute.KNNImputer",
"numpy.mean",
"numpy.where",
"numpy.cumsum",
"sklearn.impute.SimpleImputer",
"sklearn.cluster.SpectralClustering",
"numpy.log",
"sklearn.decomposition.PCA",
"numpy.reshape",
"numpy.zeros",
"... |
TheVinhLuong102/HuggingFace-DataSets | [
"98261e8b0b7be4dbaaa71ae188b950f7fbe51bbd"
] | [
"tests/features/test_array_xd.py"
] | [
"import os\nimport random\nimport tempfile\nimport unittest\n\nimport numpy as np\nimport pandas as pd\nimport pytest\nfrom absl.testing import parameterized\n\nimport datasets\nfrom datasets.arrow_writer import ArrowWriter\nfrom datasets.features import Array2D, Array3D, Array3DExtensionType, Array4D, Array5D, Val... | [
[
"numpy.concatenate",
"numpy.array",
"numpy.isnan",
"numpy.random.rand",
"numpy.testing.assert_equal",
"numpy.allclose",
"numpy.dtype"
]
] |
egoodman92/semi-supervised-surgery | [
"42f7af7e707e71ecd64b9f215fab5c07e2b71d70",
"42f7af7e707e71ecd64b9f215fab5c07e2b71d70"
] | [
"MULTITASK_FILES/RETINANET_FILES/src/pytorch-retinanet/retinanet/dataloader.py",
"MULTITASK_FILES/TSM_FILES/train.py"
] | [
"from __future__ import print_function, division\nimport sys\nimport os\nimport torch\nimport numpy as np\nimport random\nimport csv\n\nfrom torch.utils.data import Dataset, DataLoader\nfrom torchvision import transforms, utils\nfrom torch.utils.data.sampler import Sampler\nfrom future.utils import raise_from\nfrom... | [
[
"torch.zeros",
"numpy.array",
"numpy.random.rand",
"numpy.zeros",
"torch.from_numpy",
"numpy.append"
],
[
"torch.cat",
"numpy.zeros",
"torch.nn.functional.softmax",
"pandas.DataFrame",
"torch.FloatTensor",
"sklearn.metrics.accuracy_score",
"torch.DoubleTenso... |
castorfou/scikit-learn-mooc | [
"235748eff57409eb17d8355024579c6df44c0563",
"235748eff57409eb17d8355024579c6df44c0563"
] | [
"jupyter-book/linear_models/module 4 - wrap-up-quizz.py",
"jupyter-book/tuning/tuning_questions.py"
] | [
"#!/usr/bin/env python\n# coding: utf-8\n\n# # 🏁 Wrap-up quiz\n# \n# **This quiz requires some programming to be answered.**\n# \n# Open the dataset `house_prices.csv` with the following command:\n\n# In[2]:\n\n\nimport pandas as pd\n\names_housing = pd.read_csv(\"../datasets/house_prices.csv\", na_values=\"?\")\n... | [
[
"sklearn.compose.make_column_selector",
"sklearn.impute.SimpleImputer",
"sklearn.linear_model.LinearRegression",
"sklearn.preprocessing.StandardScaler",
"sklearn.model_selection.cross_validate",
"matplotlib.pyplot.title",
"sklearn.linear_model.Ridge",
"sklearn.linear_model.Logistic... |
AlexsaseXie/occupancy_networks | [
"972119ae7a7c9f782e1fc1df48a5b85b678edd31"
] | [
"im2mesh/onet_m/models/__init__.py"
] | [
"import torch\nimport torch.nn as nn\nfrom torch import distributions as dist\nfrom im2mesh.onet.models import encoder_latent, decoder\n\n# Encoder latent dictionary\nencoder_latent_dict = {\n 'simple': encoder_latent.Encoder,\n}\n\n# Decoder dictionary\ndecoder_dict = {\n 'simple': decoder.Decoder,\n 'cba... | [
[
"torch.Size",
"torch.zeros",
"torch.rand",
"torch.distributions.Bernoulli",
"torch.tensor",
"torch.distributions.kl_divergence",
"torch.empty",
"torch.exp"
]
] |
onetask-ai/onetask-python | [
"ea810a3092a029d5b30f6af9e9a5f17567e0b901"
] | [
"onetask/embedding.py"
] | [
"# -*- coding: utf-8 -*-\nfrom abc import ABC, abstractmethod\nfrom sentence_transformers import SentenceTransformer, models\nfrom torch import nn\nimport numpy as np\nfrom wasabi import msg\nfrom sklearn.feature_extraction.text import CountVectorizer\nfrom sklearn.preprocessing import OneHotEncoder\nfrom transform... | [
[
"torch.nn.Tanh",
"numpy.array",
"sklearn.preprocessing.OneHotEncoder",
"sklearn.feature_extraction.text.CountVectorizer"
]
] |
econti/FaucetML | [
"af28569ce7446e2db497c9b9b92e4845fbb34942"
] | [
"faucetml/preprocessing/identify_types.py"
] | [
"\"\"\"\nCode taken from Facebook ReAgent and modified for Faucet ML.\n\nOriginal copyright:\n Copyright (c) Facebook, Inc. and its affiliates. All rights reserved.\n\nOriginal BSD License:\n https://github.com/facebookresearch/ReAgent/blob/master/LICENSE\n\"\"\"\n\n\nimport numpy as np\n\n\nBINARY = \"BINARY... | [
[
"numpy.max",
"numpy.logical_or",
"numpy.min",
"numpy.all",
"numpy.unique"
]
] |
comRamona/Neural-Statistician | [
"7ff41fdf97e0e4ca3a335901d107f6de0edb5481"
] | [
"SentEval/words/words_test.py"
] | [
"from wordsdata import WikipediaDataset\nimport os\nimport argparse\nfrom torch.utils import data\n\n\nparser = argparse.ArgumentParser(description='test')\n\n\nparser.add_argument('--data-dir', required=True, type=str, default=None,\n help='location of formatted Omniglot data')\n\nargs = parser.... | [
[
"torch.utils.data.DataLoader"
]
] |
FocusDS7/FianceAI_Test | [
"f9310ee0723165007890a89b5e9865154e1c315f"
] | [
"cmdtzz/3.py"
] | [
"# -*- coding: UTF-8 -*-\nimport pandas as pd\nimport matplotlib.pyplot as plt\nimport matplotlib.dates as mdates\nfrom datetime import datetime\n#import numpy as np\n\nplt.figure(1)\nax1 = plt.subplot(111)\nax1.xaxis.set_major_locator(mdates.DayLocator())\nax1.xaxis.set_major_formatter(mdates.DateFormatter('%y/%m/... | [
[
"matplotlib.pyplot.sca",
"matplotlib.pyplot.plot",
"matplotlib.dates.DateFormatter",
"pandas.date_range",
"matplotlib.pyplot.figure",
"matplotlib.pyplot.show",
"pandas.read_csv",
"matplotlib.dates.DayLocator",
"matplotlib.pyplot.subplot"
]
] |
arunkumaraqm/Polynomial-Interpolation | [
"0718e488cff63517de0877ded7650b38c24d9c56"
] | [
"constants.py"
] | [
"FPS = 20 # frames per second\n\nimport pandas as pd\nimport pygame as game\n\ncdf = pd.read_csv('colors.csv')\n\n# convert to dictionary with name as key and list of r, g, b values as value\ndel cdf['common_name']\ndel cdf['hex']\ncolors = cdf.set_index('name').T.to_dict('list')\n\n\ncolors.update({\n\t'black': \t... | [
[
"pandas.read_csv"
]
] |
wilson1yan/tgan | [
"53fde1bcb59e2a57f76b9b26097226ec0423811f"
] | [
"infer.py"
] | [
"#!/usr/bin/env python\n# -*- coding: utf-8 -*-\n\nimport argparse\nimport glob\nimport imp\nimport os\nimport subprocess\nimport sys\n\nimport numpy as np\nimport yaml\n\nimport chainer\nimport chainer.functions as F\nimport cv2 as cv\nfrom chainer import Variable\nfrom chainer import serializers\n\n\ndef make_vid... | [
[
"numpy.random.seed",
"numpy.sqrt"
]
] |
Ishaan28malik/tensorflow | [
"07da23bfa2a9ca10cd7c1dd6bea0f85d981c013e"
] | [
"tensorflow/api_template_v1.__init__.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.tools.component_api_helper.package_hook"
]
] |
PaulMAnderson/phy | [
"134264e6c1ec586f797459633fa4e71352fafb4e"
] | [
"phy/apps/template/gui.py"
] | [
"# -*- coding: utf-8 -*-\n\n\"\"\"Template GUI.\"\"\"\n\n\n#------------------------------------------------------------------------------\n# Imports\n#------------------------------------------------------------------------------\n\nimport logging\nfrom operator import itemgetter\nfrom pathlib import Path\n\nimpor... | [
[
"numpy.average",
"numpy.max"
]
] |
danthe42/drlnd_p1 | [
"2c04835b487d5cea232aa452fbc8ee25dad2caeb"
] | [
"SumTree.py"
] | [
"#\n#\n# Binary Tree implementation for Prioritized replay buffers, based on the code: \n# https://github.com/MorvanZhou/Reinforcement-learning-with-tensorflow/blob/master/contents/5.2_Prioritized_Replay_DQN/RL_brain.py\n#\n#\n\nimport numpy as np\n\nclass SumTree(object):\n \"\"\"\n This SumTree code is a mo... | [
[
"numpy.zeros"
]
] |
shikiw/shape-invariant-adversarial-point-clouds | [
"9c0879b20fef2bf356898575da7b313d6d0538c6"
] | [
"utils/set_distance.py"
] | [
"\"\"\"Adopted from https://github.com/XuyangBai/FoldingNet/blob/master/loss.py\"\"\"\nimport torch\nimport torch.nn as nn\n\n\nclass _Distance(nn.Module):\n\n def __init__(self):\n super(_Distance, self).__init__()\n self.use_cuda = torch.cuda.is_available()\n\n def forward(self, preds, gts):\n... | [
[
"torch.min",
"torch.arange",
"torch.max",
"torch.cuda.is_available",
"torch.mean"
]
] |
universuen/RVGAN-TL | [
"d370673063a3dfd9cc4a20bfd1c18bc95aadabca"
] | [
"tests/test_gan.py"
] | [
"import context\n\nimport random\n\nimport torch\nimport numpy as np\nimport seaborn as sns\nimport matplotlib.pyplot as plt\nfrom sklearn.manifold import TSNE\n\nimport src\n\nTARGET_GAN = src.gans.RGAN\n\nif __name__ == '__main__':\n result = dict()\n src.utils.set_random_state()\n datasets = random.choi... | [
[
"numpy.array",
"matplotlib.pyplot.legend",
"matplotlib.pyplot.close",
"matplotlib.pyplot.subplots",
"sklearn.manifold.TSNE",
"matplotlib.pyplot.show"
]
] |
gavinatthu/YOLOP | [
"97db090da990c28dbc166bf51877e7707e5c0747"
] | [
"tools/train.py"
] | [
"import argparse\nimport os, sys\nimport math\nBASE_DIR = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))\nsys.path.append(BASE_DIR)\n\nimport pprint\nimport time\nimport torch\nimport torch.nn.parallel\nfrom torch.nn.parallel import DistributedDataParallel as DDP\nfrom torch.cuda import amp\nimport tor... | [
[
"torch.device",
"numpy.array",
"torch.distributed.destroy_process_group",
"torch.distributed.init_process_group",
"torch.save",
"torch.nn.parallel.DistributedDataParallel",
"torch.cuda.device_count",
"torch.cuda.set_device",
"torch.cuda.amp.GradScaler",
"torch.utils.data.di... |
lealex262/DeepSpeaker-pytorch | [
"99724865fe5658115698f2f36ea6db984829d7af"
] | [
"audio_processing.py"
] | [
"import numpy as np\r\nfrom python_speech_features import fbank, delta\r\nimport torch\r\ntry:\r\n from . import constants as c\r\nexcept ValueError:\r\n import constants as c\r\nimport librosa\r\nfrom librosa.feature import melspectrogram\r\nfrom librosa.core import ifgram\r\n\r\nimport os\r\nimport random\r... | [
[
"torch.zeros",
"torch.FloatTensor",
"numpy.mean",
"numpy.std",
"numpy.hstack",
"numpy.maximum"
]
] |
julesGoullee/jesse | [
"2ff415f6768f9ef7cca3e86d8f2f87988d3e7129"
] | [
"jesse/indicators/dti.py"
] | [
"from typing import Union\n\nimport numpy as np\nimport talib\n\nimport jesse.helpers as jh\n\n\ndef dti(candles: np.ndarray, r=14, s=10, u=5, sequential=False) -> Union[float, np.ndarray]:\n \"\"\"\n DTI by William Blau\n\n :param candles: np.ndarray\n :param r: int - default=14\n :param s: int - de... | [
[
"numpy.where",
"numpy.isnan",
"numpy.absolute"
]
] |
Keck-FOBOS/enyo | [
"82dd4324083d456c78bcbafdd081bee53f0c7ba9"
] | [
"enyo/scripts/wfos_etc.py"
] | [
"#!/usr/bin/env python3\n\nimport os\nimport time\nimport warnings\nimport argparse\n\nfrom IPython import embed\n\nimport numpy\nfrom scipy import interpolate\n\nfrom matplotlib import pyplot, ticker\n\nfrom astropy import units\n\nfrom enyo.etc import source, efficiency, telescopes, spectrum, extract, aperture, d... | [
[
"numpy.square",
"scipy.interpolate.interp1d",
"numpy.log",
"numpy.sum",
"numpy.mean",
"matplotlib.pyplot.figure",
"numpy.any",
"numpy.radians",
"numpy.arange",
"numpy.atleast_1d",
"matplotlib.ticker.NullFormatter",
"matplotlib.pyplot.show",
"numpy.log10",
"m... |
Magixxxxxx/Detectron2-iOD | [
"26da9e390e66bf3b84638898790cebd3923c6c36"
] | [
"detectron2/modeling/backbone/PBresnet.py"
] | [
"# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved\nimport logging\n# from myILOD.piggyback_detection.layers import ElementWiseConv2d\nimport numpy as np\nimport fvcore.nn.weight_init as weight_init\nimport torch\nimport torch.nn.functional as F\nfrom torch import nn\n\nfrom detectron2.layers i... | [
[
"torch.nn.functional.relu_",
"torch.cat",
"torch.flatten",
"torch.nn.init.constant_",
"torch.nn.Sequential",
"torch.nn.init.normal_",
"numpy.prod",
"torch.nn.AdaptiveAvgPool2d",
"torch.nn.functional.max_pool2d",
"torch.chunk"
]
] |
Amitav507/lstm-electric-load-forecast | [
"702e0a78ef478a089ad62dddb71c7dff918c5e93"
] | [
"data.py"
] | [
"import numpy as np\nimport csv\n\ndef load_data(dataset_path, sequence_length=60, prediction_steps=5, ratio_of_data=1.0):\n max_values = ratio_of_data * 2075259 # 2075259 is the total number of measurements from Dec 2006 to Nov 2010\n\n # Load data from file\n with open(dataset_path) as file:\n da... | [
[
"numpy.array",
"numpy.reshape"
]
] |
nkolbeck/Lego-Harry-Potter-Musik | [
"8b54c1ddefc047d3b708d4371f06a2cfa1fcf875"
] | [
"markings.py"
] | [
"import numpy as np\nfrom cv2 import cv2\nimport rtmidi\nimport mido\n\nfrom flask import Flask, render_template, Response\napp = Flask(__name__)\n\nprint(\"Midi output ports: \", mido.get_output_names())\n# midiOutput = mido.open_output(\"LoopBe Internal MIDI 1\") # für Windows\nmidiOutput = mido.open_output(\... | [
[
"numpy.array",
"numpy.zeros"
]
] |
som-shahlab/psych-audio | [
"83125f0ab0a6fa0193412fa09fd0c5171d88cabf"
] | [
"evaluation/02_compute_metrics.py"
] | [
"\"\"\"\nCreates a Table 2 using session-level data.\n\"\"\"\nimport os\nimport sys\nimport nltk\nimport math\nimport time\nimport argparse\nimport numpy as np\nimport pandas as pd\nfrom typing import *\nfrom tqdm import tqdm\nfrom queue import Queue\nfrom threading import Thread\nimport scipy.spatial.distance\nimp... | [
[
"pandas.read_csv",
"numpy.asarray"
]
] |
candidechamp/reeds | [
"601e4327132f80d7e7fd90d47eecc85cecc0fdd8"
] | [
"reeds/function_libs/pipeline/worker_scripts/analysis_workers/RE_EDS_soptimization_final.py"
] | [
"import glob\nimport os\nimport pickle\n\nimport numpy as np\nimport pandas as pd\nfrom typing import Union, List\n\nfrom pygromos.files import repdat\nfrom pygromos.utils import bash\n\nimport reeds.function_libs.visualization.re_plots\nfrom reeds.function_libs.analysis.parameter_optimization import get_s_optimiza... | [
[
"pandas.DataFrame",
"numpy.sum",
"numpy.mean",
"numpy.std",
"numpy.abs",
"numpy.unique"
]
] |
nitiniisc/20_news_group_CNN | [
"8d36f98af4928e7f48d5110d63eb1115e5faf59d"
] | [
"CNN_using_self_embedding.py"
] | [
"\n# coding: utf-8\n\n# In[1]:\n\nimport numpy as np\nimport os\nimport tensorflow as tf\nfrom tensorflow.contrib import learn\nfrom data_utils import *\nembedding_size = 128\nfilter_sizes =[3,4]\nnum_filters = 32\nnum_classes =20\nbatch_size = 64\nnum_epochs = 10\n\n\n# In[2]:\n\ndef weight_variable(shape):\n i... | [
[
"tensorflow.nn.softmax_cross_entropy_with_logits",
"tensorflow.contrib.learn.preprocessing.VocabularyProcessor",
"tensorflow.nn.conv2d",
"tensorflow.matmul",
"tensorflow.reshape",
"tensorflow.nn.embedding_lookup",
"tensorflow.nn.softmax",
"tensorflow.global_variables_initializer",
... |
Icebreaker454/MRNet-1 | [
"6dca2619d0afcbd97decc3e36609c3baec83411a"
] | [
"src/predict_per_plane.py"
] | [
"#!/usr/bin/env python3.6\n\"\"\"Calculates predictions on the validation dataset, using CNN models specified\nin src/cnn_models_paths.txt\n\nUsage:\n predict_per_plane.py <valid_paths_csv> <cnn_models_paths> <output_dir> [options]\n predict_per_plane.py (-h | --help)\n\nGeneral options:\n -h --help Sho... | [
[
"pandas.read_csv",
"torch.cuda.is_available",
"torch.load"
]
] |
mmolari/morbidostat-genome-analysis | [
"246cf12c07c724a76485cac7aa9a1f7fa660fa9c"
] | [
"scripts/pileupplots_consensus_frequency.py"
] | [
"# %%\nimport numpy as np\nimport pathlib as pth\nimport matplotlib.pyplot as plt\nimport re\n\ntry:\n from pileupplots_utils import *\nexcept:\n from .pileupplots_utils import *\n\n\n# %%\n\nif __name__ == \"__main__\":\n\n parser = argparser()\n args = parser.parse_args()\n data_path = pth.Path(arg... | [
[
"numpy.ceil",
"matplotlib.pyplot.subplots",
"numpy.unravel_index",
"matplotlib.pyplot.tight_layout",
"numpy.linspace",
"matplotlib.pyplot.subplot_mosaic"
]
] |
epsilonethan/einsteinpy | [
"a63f2f9ff7e9010d80d7cbd4a519fd8b523ab865"
] | [
"src/einsteinpy/geodesic/utils.py"
] | [
"\"\"\"\nUtilities for Geodesic Module\n\nUnit System: M-Units => :math:`c = G = M = k_e = 1`\nMetric Signature => :math:`(-, +, +, +)`\n\n\"\"\"\nimport numpy as np\n\nfrom einsteinpy.utils.dual import DualNumber\n\n\ndef _P(g, g_prms, q, p, time_like=True):\n \"\"\"\n Utility function to compute 4-Momentum ... | [
[
"numpy.array",
"numpy.sin",
"numpy.zeros",
"numpy.sqrt",
"numpy.cos"
]
] |
jscott6/greengraph | [
"bf745e78485f0acc1a95f27c0f391f3aba80f42e"
] | [
"greengraph/ggraph.py"
] | [
"from .map import Map\nimport numpy as np\nimport geopy\nfrom mock import Mock, patch\n\nclass Greengraph(object):\n\n def __init__(self, start, end):\n self.start=start\n self.end=end\n self.geocoder=geopy.geocoders.GoogleV3(\n domain=\"maps.google.co.uk\")\n\n def geolocate(s... | [
[
"numpy.linspace",
"numpy.vstack"
]
] |
WERimagin/torch_QuestionGeneration | [
"25e53ce2e00d77bbcb1cf2fd38e73c9ab723b3a4"
] | [
"model/seq2seq2.py"
] | [
"#https://www.pytry3g.com/entry/pytorch-seq2seq\n\nimport torch\nimport torch.nn as nn\nimport torch.nn.functional as F\nimport torch.optim as optim\nfrom func import constants\nfrom func.utils import Word2Id,make_tensor,make_vec,make_vec_c,to_var\nimport numpy as np\n\nclass Encoder(nn.Module):\n def __init__(s... | [
[
"torch.nn.Linear",
"torch.nn.GRU",
"numpy.zeros",
"torch.unsqueeze",
"torch.squeeze",
"torch.transpose",
"torch.nn.Embedding"
]
] |
ReinholdM/play_football_with_human | [
"9ac2f0a8783aede56f4ac1f6074db7daa41b6b6c"
] | [
"malib/algorithm/ppo/loss.py"
] | [
"import torch\n\nfrom typing import Dict, Tuple, Any\n\nfrom torch.distributions.categorical import Categorical\n\nfrom malib.algorithm.common.loss_func import LossFunc\nfrom malib.backend.datapool.offline_dataset_server import Episode\nfrom malib.utils.typing import TrainingMetric\n\n\ndef cal_entropy(logits):\n ... | [
[
"torch.max",
"torch.square",
"torch.maximum",
"torch.clip",
"torch.distributions.categorical.Categorical",
"torch.abs",
"torch.log",
"torch.exp",
"torch.sum"
]
] |
wangyuefengGH/QUANTAXIS | [
"4f988776a4b08ac2bbd46c0cbef31a3112771920"
] | [
"QUANTAXIS/QAARP/QARisk.py"
] | [
"# coding:utf-8\n#\n# The MIT License (MIT)\n#\n# Copyright (c) 2016-2018 yutiansut/QUANTAXIS\n#\n# Permission is hereby granted, free of charge, to any person obtaining a copy\n# of this software and associated documentation files (the \"Software\"), to deal\n# in the Software without restriction, including withou... | [
[
"matplotlib.use",
"pandas.to_datetime",
"numpy.cov",
"pandas.DataFrame",
"matplotlib.pyplot.title",
"matplotlib.pyplot.legend",
"matplotlib.pyplot.subplots",
"matplotlib.pyplot.figure",
"matplotlib.pyplot.style.use",
"matplotlib.pyplot.show",
"matplotlib.pyplot.axis",
... |
petercunning/notebook | [
"5b26f2dc96bcb36434542b397de6ca5fa3b61a0a",
"5b26f2dc96bcb36434542b397de6ca5fa3b61a0a"
] | [
"ERDDAP/ERDDAP_Brad.py",
"system-test/Theme_1_Baseline/Scenario_1F_Temperature/utilities.py"
] | [
"\n# coding: utf-8\n\n# #Read realtime data from NERACOOS ERDDAP\n# Exploring use of Python to formulate [NERACOOS ERDDAP](http://www.neracoos.org/erddap) data requests and process the responses. \n\n# ##Initialize\n\n# In[1]:\n\nimport pandas as pd\nimport urllib2\nimport numpy as np\nimport seawater as sw\nimpor... | [
[
"pandas.date_range",
"matplotlib.pyplot.subplots",
"numpy.arange",
"pandas.read_csv",
"numpy.meshgrid"
],
[
"numpy.array",
"numpy.ceil",
"pandas.DataFrame",
"numpy.diff",
"numpy.where",
"numpy.remainder",
"numpy.sqrt",
"pandas.concat",
"numpy.isfinite"
... |
thautwarm/BioInfoPlus | [
"b3f404d3f13cfccf4694cfba586ac7efcbf5bf29"
] | [
"research/original/specific_regular.py"
] | [
"# -*- coding: utf-8 -*-\n\"\"\"\nCreated on Tue Oct 31 17:36:38 2017\n\n@author: misaka-wa\n\"\"\"\n\n\n\nimport numpy as np\nfrom collections import defaultdict\nfrom typing import Dict, Union, Any\n\ndef specific_report(numpy_arr:np.ndarray, specific:Union[np.ndarray, Dict[int, Any]]):\n \"\"\"\n numpy_arr... | [
[
"numpy.array"
]
] |
mattwthompson/openmmforcefields | [
"ddea4f61d508f0cc06ad09dd29d0943721890038"
] | [
"openmmforcefields/tests/test_template_generators.py"
] | [
"import os, sys\nimport unittest\nimport tempfile\n\nfrom openmmforcefields.utils import get_data_filename\n\nfrom openmmforcefields.generators import GAFFTemplateGenerator\nfrom openmmforcefields.generators import SMIRNOFFTemplateGenerator\n\nimport logging\n_logger = logging.getLogger(\"openmmforcefields.tests.te... | [
[
"numpy.all",
"numpy.allclose",
"numpy.array",
"numpy.random.random"
]
] |
RickyMexx/3D-Sound-Localization | [
"8ba9a05e52fecce68864919464f1d495aed31896"
] | [
"Code/complexnn/conv.py"
] | [
"#!/usr/bin/env python\r\n# -*- coding: utf-8 -*-\r\n\r\n# Contributors : Titouan Parcollet\r\n# Initial Authors: Chiheb Trabelsi\r\n\r\nfrom keras import backend as K\r\nfrom keras import activations, initializers, regularizers, constraints\r\nfrom keras.layers import Lambda, Layer, InputSpec, Convolution1D, Convo... | [
[
"numpy.random.randint"
]
] |
QianLiGui/tfsnippet | [
"63adaf04d2ffff8dec299623627d55d4bacac598",
"63adaf04d2ffff8dec299623627d55d4bacac598"
] | [
"tfsnippet/layers/convolutional/pooling.py",
"tfsnippet/examples/classification/cifar10_conv.py"
] | [
"import tensorflow as tf\nfrom tensorflow.contrib.framework import add_arg_scope\n\nfrom tfsnippet.ops import flatten_to_ndims, unflatten_from_ndims\nfrom tfsnippet.utils import validate_enum_arg, add_name_arg_doc\n\nfrom .utils import validate_conv2d_strides_tuple, validate_conv2d_input\n\n__all__ = ['avg_pool2d',... | [
[
"tensorflow.reduce_mean",
"tensorflow.name_scope"
],
[
"tensorflow.trainable_variables",
"tensorflow.train.AdamOptimizer",
"tensorflow.get_default_graph",
"tensorflow.transpose",
"tensorflow.placeholder",
"tensorflow.losses.sparse_softmax_cross_entropy",
"tensorflow.device"... |
matteoschiav/lowtran | [
"5c34d9bff4882de58a69d9d976f73b680dcea866"
] | [
"ThermalRadiance.py"
] | [
"#!/usr/bin/env python\n\"\"\"\n\nTotal Radiance = atmosphere rad. or boundary rad. + atm. scat. or boundary refl.\n\nLowtran outputs W cm^-2 ster^-1 micron^-1\nwe want photons cm^-2 s^-1 ster^-1 micron^-1\n1 W cm^-2 = 10000 W m^-2\n\nh = 6.62607004e-34 m^2 kg s^-1\nI: irradiance\nNp: numer of photons\nNp = (Ilowtr... | [
[
"matplotlib.pyplot.show"
]
] |
strongh/GPy | [
"775ce9e64c1e8f472083b8f2430134047d97b2fa"
] | [
"GPy/models/sparse_gp_coregionalized_regression.py"
] | [
"# Copyright (c) 2012 - 2014 the GPy Austhors (see AUTHORS.txt)\n# Licensed under the BSD 3-clause license (see LICENSE.txt)\n\nimport numpy as np\nfrom ..core import SparseGP\nfrom ..inference.latent_function_inference import VarDTC\nfrom .. import likelihoods\nfrom .. import kern\nfrom .. import util\n\nclass Spa... | [
[
"numpy.random.permutation",
"numpy.asarray"
]
] |
bicycleman15/ivy | [
"de193946a580ca0f54d78fe7fc4031a6ff66d2bb"
] | [
"ivy_tests/test_ivy/test_functional/test_core/test_statistical.py"
] | [
"\"\"\"Collection of tests for statistical functions.\"\"\"\n# global\nimport numpy as np\nfrom hypothesis import given, assume, strategies as st\n\n# local\nimport ivy\nimport ivy_tests.test_ivy.helpers as helpers\nimport ivy.functional.backends.numpy as ivy_np\n\n\n@st.composite\ndef statistical_dtype_values(draw... | [
[
"numpy.arange",
"numpy.asarray"
]
] |
ManishBachhu/editsql | [
"c046dfbee72d3b54ebc7a2326b1eb7797b23d10e"
] | [
"model/model.py"
] | [
"\"\"\" Class for the Sequence to sequence model for ATIS.\"\"\"\n\nimport os\n\nimport torch\nimport torch.nn.functional as F\nfrom . import torch_utils\nfrom . import utils_bert\n\nfrom data_util.vocabulary import DEL_TOK, UNK_TOK\n\nfrom .encoder import Encoder\nfrom .embedder import Embedder\nfrom .token_predic... | [
[
"torch.zeros",
"torch.device",
"torch.cat",
"torch.optim.Adam",
"torch.cuda.FloatTensor"
]
] |
jwass/geopandas | [
"3ebcae071ddc8faa44a1ecb541154b6399af14a8"
] | [
"geopandas/geodataframe.py"
] | [
"from collections import defaultdict, OrderedDict\nimport json, os\n\nimport fiona\nfrom pandas import DataFrame\nfrom shapely.geometry import mapping, shape\n\nfrom geopandas import GeoSeries\nfrom plotting import plot_dataframe\n\nimport numpy as np\n\n\nclass GeoDataFrame(DataFrame):\n \"\"\"\n A GeoDataFr... | [
[
"numpy.zeros"
]
] |
stereoboy/object_detection | [
"002445d083da54e7b3c6e158e2d66d3c57a05f31"
] | [
"utils.py"
] | [
"import tensorflow as tf\nimport numpy as np\nfrom PIL import Image\nimport os\n\ndef maybe_download(directory, filename, url):\n print('Try to dwnloaded', url)\n if not tf.gfile.Exists(directory):\n tf.gfile.MakeDirs(directory)\n filepath = os.path.join(directory, filename)\n if not tf.gfile.Exists(filepath... | [
[
"numpy.array",
"tensorflow.shape",
"tensorflow.gfile.Exists",
"tensorflow.Variable",
"numpy.load",
"tensorflow.gfile.GFile",
"tensorflow.gfile.MakeDirs"
]
] |
JWDebelius/scikit-bio | [
"9df3edb46eb728f6efbd4f2db74529200ad40a77",
"9df3edb46eb728f6efbd4f2db74529200ad40a77"
] | [
"skbio/stats/_subsample/__init__.py",
"skbio/parse/sequences/fastq.py"
] | [
"# ----------------------------------------------------------------------------\n# Copyright (c) 2013--, scikit-bio development team.\n#\n# Distributed under the terms of the Modified BSD License.\n#\n# The full license is in the file COPYING.txt, distributed with this software.\n# ---------------------------------... | [
[
"numpy.testing.Tester"
],
[
"numpy.fromstring"
]
] |
tobykirk/PyBaMM | [
"c16b7df76c597468ecac1c40e768d94005f79145"
] | [
"pybamm/expression_tree/symbol.py"
] | [
"#\n# Base Symbol Class for the expression tree\n#\nimport copy\nimport numbers\n\nimport anytree\nimport numpy as np\nimport sympy\nfrom anytree.exporter import DotExporter\nfrom scipy.sparse import csr_matrix, issparse\n\nimport pybamm\nfrom pybamm.expression_tree.printing.print_name import prettify_print_name\n\... | [
[
"scipy.sparse.issparse",
"numpy.ones",
"numpy.prod",
"numpy.all",
"scipy.sparse.csr_matrix"
]
] |
joelgarde/flax | [
"7d12d20f8272ce9c639711e92db89fdaf7f1a94a"
] | [
"examples/mnist/train_test.py"
] | [
"# Copyright 2021 The Flax Authors.\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n# http://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless required by applicable law or a... | [
[
"tensorflow.config.experimental.set_visible_devices"
]
] |
maguirre1/deepLAI | [
"ff6961ffdf6d0f215c4bd295d84aa547d2049325"
] | [
"model/segnet.py"
] | [
"#!/usr/bin/env python\nimport tensorflow as tf\nfrom tensorflow import keras\nfrom tensorflow.keras import regularizers\nfrom tensorflow.keras.layers import Input, Dense, Activation, BatchNormalization, Conv1D\nfrom tensorflow.keras.layers import concatenate, MaxPooling1D, UpSampling1D, Dropout\nfrom tensorflow.ke... | [
[
"tensorflow.keras.layers.Conv1D",
"tensorflow.keras.layers.Input",
"tensorflow.keras.layers.Activation",
"tensorflow.keras.models.Model",
"tensorflow.keras.layers.Dense",
"tensorflow.keras.layers.Dropout",
"tensorflow.keras.regularizers.l2",
"tensorflow.keras.layers.BatchNormalizat... |
gjpcbecq/Robinson | [
"a7e9a15e7086002cbb4f4407a5c762ff6ac4e0c6"
] | [
"ER.py"
] | [
"\"\"\"\nEnders A. Robinson\n\"\"\"\n#_______________________________________________________________________________\n#_______________________________________________________________________________\nimport numpy\nimport math\nimport matplotlib.pyplot as plt\nfrom temp import *\n#__________________________________... | [
[
"numpy.array",
"numpy.empty",
"numpy.zeros",
"matplotlib.pyplot.plot",
"numpy.arange",
"matplotlib.pyplot.tight_layout",
"numpy.abs",
"matplotlib.pyplot.axis",
"matplotlib.pyplot.subplot"
]
] |
NadimOvi/tpu | [
"cfde494b3b0098afe272efb16124883ea3cbd38f"
] | [
"models/experimental/mask_rcnn/mask_rcnn_params.py"
] | [
"# Copyright 2018 The TensorFlow Authors. All Rights Reserved.\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n# http://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless requ... | [
[
"tensorflow.contrib.training.HParams"
]
] |
rexliu3/StockTradingBotCloud | [
"46b732b9c05f73bc0e856a3c4a16854b6d12e18e"
] | [
"venv/Lib/site-packages/tensorflow/compiler/tf2xla/ops/gen_xla_ops.py"
] | [
"\"\"\"Python wrappers around TensorFlow ops.\n\nThis file is MACHINE GENERATED! Do not edit.\nOriginal C++ source file: gen_xla_ops.cc\n\"\"\"\n\nimport collections\n\nfrom tensorflow.python import pywrap_tfe as pywrap_tfe\nfrom tensorflow.python.eager import context as _context\nfrom tensorflow.python.eager impor... | [
[
"tensorflow.python.eager.context.context",
"tensorflow.python.eager.execute.make_bool",
"tensorflow.python.framework.ops.raise_from_not_ok_status",
"tensorflow.python.eager.execute.must_record_gradient",
"tensorflow.python.framework.op_def_library._apply_op_helper",
"tensorflow.python.fram... |
mmakowski/svpnm | [
"0640023111b58734427265e78569e9d20aacf01d"
] | [
"src/make-linux-comparison-figure.py"
] | [
"#!/usr/bin/env python\nimport json\nimport os\nimport sys\n\nimport pandas as pd\nimport seaborn as sns\nimport sklearn.metrics\n\nimport report_resources\nimport matplotlib.pyplot as plt\n\nSCORES_COLS = ('id', 'label', 'score')\nMETRICS_COLS = ('Release', 'Model', 'Metric', 'Score')\n\n\ndef main(drf_results_dir... | [
[
"pandas.DataFrame",
"matplotlib.pyplot.subplots",
"pandas.concat"
]
] |
justanotherariel/hass_MagicLights | [
"61ac0db1f7c3575e52912b372176d45e647b728e"
] | [
"custom_components/magic_lights/plugin_effects/transitions/__init__.py"
] | [
"import asyncio\nimport enum\nfrom custom_components.magic_lights.plugin_effects import Effect\nimport logging\nfrom typing import Callable, List\nimport numpy as np\nimport re\n\nfrom colorspacious import cspace_convert\n\nCONFIG_SCHEMA = None\nPLUGIN_DOMAIN = \"transitions\"\nPLUGIN_NAME = \"Transitions\"\nPLUGIN... | [
[
"numpy.asarray"
]
] |
AIIP-DEV/Auto-PyTorch | [
"4a130145c106a813fc237114d1e062b30ab9d629",
"4a130145c106a813fc237114d1e062b30ab9d629"
] | [
"autoPyTorch/data_management/data_converter.py",
"autoPyTorch/core/api.py"
] | [
"import numpy as np\nimport pandas as pd\n\n__author__ = \"Max Dippel, Michael Burkart and Matthias Urban\"\n__version__ = \"0.0.1\"\n__license__ = \"BSD\"\n\nclass DataConverter(object):\n def __init__(self, is_classification=None,\n numerical_min_unique_values=3,\n force_numeric... | [
[
"pandas.isnull",
"numpy.array",
"numpy.reshape",
"numpy.zeros",
"numpy.sum",
"numpy.any",
"numpy.argmax",
"numpy.append",
"numpy.dtype",
"numpy.unique"
],
[
"torch.device",
"numpy.asanyarray"
]
] |
Kipok/expline | [
"0cd7705b5a787f8b9835e3e453b371c45d6a237b"
] | [
"example.py"
] | [
"from __future__ import print_function\nfrom six.moves import range\n\nimport numpy as np\nimport argparse\n\nfrom expline.base import BaseExperiment\n\n\nclass ExampleExperiment(BaseExperiment):\n \"\"\"Example experiment demostrating how to correctly inherit BaseExperiment.\n\n This class just runs a gradien... | [
[
"numpy.array"
]
] |
HaoGao1996/NeuronNetSimulation | [
"6a86d03aac8875ee96d2681a897ab91bb05287d3"
] | [
"simulation/simulation/utils/test/test_rand_lif_spikes_single.py"
] | [
"from fishSimulation.utils import generator as gen\nimport matplotlib.pyplot as plt\n\nsp = gen.rand_lif_spikes_single(size=(10000, 4), f=15, delta_tb=1, num=10, ratio=(0.8, 0.5))\nprint(sp.size)\n\nplt.plot(sp)\nplt.show()\n\n"
] | [
[
"matplotlib.pyplot.show",
"matplotlib.pyplot.plot"
]
] |
wangenau/eminus | [
"57b6876093e52a14fc044cac94d1963b94b4ce8a"
] | [
"tests/spin_paired/test_spin_paired.py"
] | [
"#!/usr/bin/env python3\n'''Test total energies for a small set of systems.'''\nimport eminus\nfrom eminus import Atoms, read_xyz, SCF\nfrom numpy.testing import assert_allclose\n\n# Total energies calculated with PWDFT.jl for He, H2, LiH, CH4, and Ne with same parameters as below\nEtot_ref = [-2.54356557, -1.10228... | [
[
"numpy.testing.assert_allclose"
]
] |
neurodata-dev/synaptome-stats | [
"7637432355d4ccc169e5c3847dd123616f4594cb"
] | [
"collman14v2/201710/synaptogramCubes.py"
] | [
"#!/usr/bin/env python3\n###\n### \n###\n### Jesse Leigh Patsolic \n### 2017 <jpatsol1@jhu.edu>\n### S.D.G \n#\nimport argparse\nimport math\nfrom intern.remote.boss import BossRemote\nfrom intern.resource.boss.resource import *\nimport configparser\n#import grequests # for async requests, conflicts with requests ... | [
[
"numpy.all",
"numpy.genfromtxt",
"numpy.asarray"
]
] |
john-drago/fluoro | [
"b757af60940c4395101a39a15f3ac4213f40fdce"
] | [
"code/jupyt/update_2019-Sep-17/model_prediction_vox_fluoro_norm_mse.py"
] | [
"'''\nThis module will attempt to predict model parameters by using a trained model.\n'''\n\nimport tensorflow as tf\nimport os\nimport h5py\nimport numpy as np\nimport pickle\n\nbase_dir = os.path.expanduser('~/fluoro/data/compilation')\n\nfile_base_name = 'vox_fluoro_norm_mse'\n\nhist_path = os.path.join(os.path.... | [
[
"numpy.max",
"numpy.random.choice",
"numpy.min",
"numpy.where",
"numpy.expand_dims"
]
] |
dp-isi/VaryingSkinTone | [
"2e595c1d668a8424d86b76dae1fef4b607c26fc8"
] | [
"data/data_loader_test.py"
] | [
"import sys\nsys.path.append('./')\nimport params\ndataset_path = params.dataset_path\nimport os \nfrom PIL import Image\n# import matplotlib.image as mpimg\nimport numpy as np\nimport cv2\nfrom scipy.misc import imresize,imread\n# ----------------------------------------\n\ndef get_reshaped(im):\n\tif(len(im.shape... | [
[
"numpy.ones",
"numpy.random.shuffle",
"numpy.zeros",
"scipy.misc.imresize"
]
] |
AustinT/at-tensorflow-template | [
"ed020f347b9a83ec721da2428c4058b8673e81a8"
] | [
"models/example_model.py"
] | [
"from base.base_model import BaseModel\nimport tensorflow as tf\n\n\nclass ExampleModel(BaseModel):\n def __init__(self, config):\n super().__init__(config)\n self.build_model()\n self.init_saver()\n\n def build_model(self):\n self.is_training = tf.placeholder(tf.bool)\n\n s... | [
[
"tensorflow.train.AdamOptimizer",
"tensorflow.train.Saver",
"tensorflow.placeholder",
"tensorflow.name_scope",
"tensorflow.layers.dense",
"tensorflow.square"
]
] |
KevinLTT/video2bvh | [
"312d18f53bf31c37adcaf07c97098b67dbf9804a"
] | [
"bvh_skeleton/h36m_skeleton.py"
] | [
"from . import math3d\nfrom . import bvh_helper\n\nimport numpy as np\n\n\nclass H36mSkeleton(object):\n\n def __init__(self):\n self.root = 'Hip'\n self.keypoint2index = {\n 'Hip': 0,\n 'RightHip': 1,\n 'RightKnee': 2,\n 'RightAnkle': 3,\n 'Le... | [
[
"numpy.array",
"numpy.rad2deg",
"numpy.linalg.norm",
"numpy.mean"
]
] |
MahdiFarnaghi/gtm | [
"adbec372786262607291f901a444a0ebe9e98b48"
] | [
"event_detector/gttm/cluster_detection/cluster_handler.py"
] | [
"import os\nfrom datetime import datetime\nfrom pathlib import Path\nfrom pprint import pprint\n\nimport sys\nfrom sklearn.cluster import DBSCAN\nimport geopandas as gp\nimport pandas as pd\nimport numpy as np\n# from sklearn.cluster.optics_ import OPTICS\n\nfrom sklearn.feature_extraction.text import TfidfVectoriz... | [
[
"sklearn.metrics.pairwise.cosine_distances",
"sklearn.preprocessing.normalize",
"sklearn.preprocessing.MinMaxScaler",
"numpy.concatenate",
"numpy.max",
"matplotlib.pyplot.savefig",
"sklearn.metrics.pairwise_distances",
"matplotlib.pyplot.close",
"sklearn.cluster.DBSCAN",
"s... |
nimily/roful | [
"0b1dfca55cb64b086848a9e5b22c950cf539677d"
] | [
"src/utils.py"
] | [
"import numpy as np\nimport numpy.linalg as npl\nimport numpy.random as npr\n\n\ndef sqrt_sym(x):\n u, d, v = npl.svd(x)\n\n return u @ np.diag(d ** 0.5) @ v\n\n\nclass DataSummary:\n xy: np.ndarray\n xx: np.ndarray\n\n _mean: np.ndarray\n _basis: np.ndarray\n _scale: np.ndarray\n _dirty: bo... | [
[
"numpy.array",
"numpy.zeros",
"numpy.random.RandomState",
"numpy.ones",
"numpy.eye",
"numpy.linalg.svd",
"numpy.outer",
"numpy.diag",
"numpy.maximum"
]
] |
ingridfausk/where | [
"b65398911075b7ddef3a3a1146efa428eae498fe",
"b65398911075b7ddef3a3a1146efa428eae498fe"
] | [
"where/estimation/parameters/slr_time_bias.py",
"where/writers/gnss_comparison.py"
] | [
"\"\"\"Calculate the slr station dependent time bias as a constant parameter over the arc\n\nDescription:\n------------\n\nCalculate the partial derivatives of the measurement with respect to the time bias. \n\nReferences:\n-----------\n\n\n\n\"\"\"\n# External library imports\nimport numpy as np\n\n# Midgard impor... | [
[
"numpy.in1d",
"numpy.linalg.norm",
"numpy.sum",
"numpy.asarray"
],
[
"numpy.square",
"numpy.array",
"numpy.absolute",
"numpy.nanpercentile",
"pandas.DataFrame",
"numpy.sqrt",
"pandas.concat",
"numpy.repeat"
]
] |
akeaveny/uwrt_arm_rl | [
"a14195b96b2f106f9d1bd7b7ce1c8af4c679e965"
] | [
"scripts/train_TD3.py"
] | [
"import glob\n\nimport os\nimport sys\nROOT_DIR = os.path.abspath('../')\nsys.path.append(ROOT_DIR)\nprint(\"********* cwd {} *********\".format(ROOT_DIR))\n\nimport argparse\n\nimport gym\nimport gym_uwrt_arm\n\nimport numpy as np\n\nfrom gym.wrappers import FlattenObservation\nfrom gym_uwrt_arm.wrappers.discrete_... | [
[
"numpy.mean",
"torch.utils.tensorboard.SummaryWriter",
"numpy.zeros",
"numpy.ones"
]
] |
SaraLatif99/napari | [
"b17235ee77d30e58492368a73d7c8d8189397fa4",
"b17235ee77d30e58492368a73d7c8d8189397fa4"
] | [
"napari/layers/shapes/_tests/test_shapes.py",
"napari/layers/shapes/_tests/test_shapes_key_bindings.py"
] | [
"import numpy as np\nfrom xml.etree.ElementTree import Element\nfrom napari.layers import Shapes\n\n\ndef test_empty_shapes():\n shp = Shapes()\n assert shp.dims.ndim == 2\n\n\ndef test_rectangles():\n \"\"\"Test instantiating Shapes layer with a random 2D rectangles.\"\"\"\n # Test a single four corner... | [
[
"numpy.concatenate",
"numpy.array",
"numpy.empty",
"numpy.random.seed",
"numpy.random.uniform",
"numpy.random.randint",
"numpy.arange",
"numpy.all",
"numpy.random.random",
"numpy.unique"
],
[
"numpy.random.random",
"numpy.zeros"
]
] |
soccermetrics/marcotti-events | [
"759f3a4ee130fa155fd48e216ef6197a69ee2a33",
"759f3a4ee130fa155fd48e216ef6197a69ee2a33"
] | [
"marcottievents/lib/match.py",
"marcottievents/etl/base/transform.py"
] | [
"from numpy import mean\nfrom sqlalchemy.sql.expression import false\n\nfrom .base import Analytics\nimport marcottievents.models.club as mc\nimport marcottievents.models.common.events as mce\nimport marcottievents.models.common.suppliers as mcs\nimport marcottievents.models.common.enums as enums\n\n\ndef coroutine... | [
[
"numpy.mean"
],
[
"pandas.notnull"
]
] |
Global19/revolver | [
"74fc12afff8a8747224d9e7098fe97542f81cea0"
] | [
"revolver/model/backbone.py"
] | [
"from collections import OrderedDict\n\nimport torch\nimport torch.nn as nn\nfrom torch.utils import model_zoo\nfrom torchvision import models\n\nfrom .fcn import convolutionalize\n\n\ndef vgg16(is_caffe=True):\n \"\"\"\n Load the VGG-16 net for use as a fully convolutional backbone.\n\n - cast to fully co... | [
[
"torch.utils.model_zoo.load_url"
]
] |
egarren/scSLE | [
"0d91f460e987d4be5b453b1d4e250d478653f690"
] | [
"code/1_GEX/07_velocity/1_scvelo.py"
] | [
"import numpy as np\nimport pandas as pd\nimport os, sys\nimport matplotlib.pyplot as pl\nfrom matplotlib import rcParams\nimport scanpy as sc\nimport rpy2.robjects as robjects\nimport anndata2ri\nimport scvelo as scv\nimport re\nimport anndata as adata1\nimport glob\nimport pickle\nfrom IPython.display import disp... | [
[
"matplotlib.pyplot.hist",
"numpy.flatnonzero"
]
] |
abefrandsen/numerical_computing | [
"90559f7c4f387885eb44ea7b1fa19bb602f496cb"
] | [
"Algorithms/PCA/plotting.py"
] | [
"import matplotlib\nmatplotlib.rcParams = matplotlib.rc_params_from_file('../../matplotlibrc')\n\nimport numpy as np\nimport matplotlib.pyplot as plt\nfrom sklearn import datasets\nfrom sklearn import decomposition\n\niris = datasets.load_iris()\n\ndef iris_base():\n fig = plt.figure(figsize=(10, 10))\n ax = ... | [
[
"numpy.array",
"matplotlib.pyplot.xlim",
"matplotlib.pyplot.xlabel",
"matplotlib.pyplot.ylim",
"matplotlib.pyplot.plot",
"matplotlib.rc_params_from_file",
"matplotlib.pyplot.savefig",
"matplotlib.pyplot.figure",
"matplotlib.pyplot.ylabel",
"matplotlib.pyplot.quiver",
"s... |
PanditPranav/covid-data-model | [
"dde5299dca09a178e1a1163ee856b5407f6ac503"
] | [
"libs/datasets/combined_datasets.py"
] | [
"from typing import Dict, Type, List, NewType\nimport logging\nimport functools\nimport pandas as pd\nimport structlog\n\nfrom libs.datasets import dataset_utils\nfrom libs.datasets import dataset_base\nfrom libs.datasets import data_source\nfrom libs.datasets.sources.test_and_trace import TestAndTraceData\nfrom li... | [
[
"pandas.DataFrame"
]
] |
rudolffu/Imbalance-XGBoost | [
"339298a6a2dcd1548387376f84595ee42148e5a0"
] | [
"imxgboost/imbalance_xgb.py"
] | [
"import numpy as np\nimport xgboost as xgb\nfrom imxgboost.weighted_loss import Weight_Binary_Cross_Entropy\nfrom imxgboost.focal_loss import Focal_Binary_Loss\nfrom sklearn.base import BaseEstimator, ClassifierMixin\nfrom sklearn.metrics import accuracy_score, precision_score, recall_score, f1_score, matthews_corr... | [
[
"numpy.concatenate",
"numpy.logical_not",
"numpy.reshape",
"numpy.round",
"sklearn.metrics.matthews_corrcoef",
"numpy.random.permutation",
"numpy.exp",
"numpy.shape",
"sklearn.metrics.accuracy_score",
"numpy.logical_and",
"numpy.argmax",
"sklearn.metrics.precision_s... |
phamdinhkhanh/HRNet-Facial-Landmark-Detection | [
"71de7378e8327bee71197030271dbb27d01218db"
] | [
"utils_landmarks.py"
] | [
"import cv2\nimport numpy as np\nimport matplotlib.pyplot as plt\n\n\ndef get_five_landmarks_from_net(landmarks):\n \"\"\"\n Return 5 landmarks needed in face alignment\n \"\"\"\n num_lmks = landmarks.shape[0]\n\n if num_lmks == 5:\n left_eye = landmarks[0]\n right_eye = landmarks[1]\n ... | [
[
"numpy.round",
"matplotlib.pyplot.show",
"numpy.array",
"matplotlib.pyplot.figure"
]
] |
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