repo_name stringlengths 6 130 | hexsha list | file_path list | code list | apis list |
|---|---|---|---|---|
jec34/molecool | [
"7c47a568c4964a851c026b667aa7fe12d99128d2"
] | [
"molecool/tests/test_molecule.py"
] | [
"\"\"\"\nTests for the molecule module\n\"\"\"\nimport molecool\nimport pytest\nimport numpy as np\n\ndef test_molecular_mass():\n symbols = ['C', 'H', 'H', 'H', 'H']\n\n calculated_mass = molecool.calculate_molecular_mass(symbols)\n\n actual_mass = 16.04\n\n assert pytest.approx(actual_mass, abs=1e-2) ... | [
[
"numpy.array",
"numpy.array_equal"
]
] |
astutespruce/sarp-connectivity | [
"d2f80c1de6cb0ac35ae35c9023d8bf482684b026"
] | [
"analysis/export/summarize.py"
] | [
"from pathlib import Path\n\nimport pandas as pd\nfrom openpyxl.styles import Alignment, NamedStyle\nfrom openpyxl.utils import get_column_letter\n\nfrom api.constants import DOMAINS\n\nprimary_col_style = NamedStyle(\n name=\"PrimaryColumnStyle\", alignment=Alignment(horizontal=\"left\", wrap_text=True)\n)\n\n\... | [
[
"pandas.crosstab",
"pandas.DataFrame",
"pandas.ExcelWriter",
"pandas.read_feather"
]
] |
acured/nni | [
"03ff374189837d28d98c3e0a14ea248d9a231f82"
] | [
"test/ut/retiarii/test_strategy.py"
] | [
"import random\nimport time\nimport threading\nfrom typing import *\n\nimport nni.retiarii.execution.api\nimport nni.retiarii.nn.pytorch as nn\nimport nni.retiarii.strategy as strategy\nimport torch\nimport torch.nn.functional as F\nfrom nni.retiarii import Model\nfrom nni.retiarii.converter import convert_to_graph... | [
[
"torch.jit.script",
"torch.nn.functional.max_pool2d",
"torch.nn.functional.log_softmax"
]
] |
yohokuno/dl4nlp | [
"818db943835195397cd999e98806cabdc3499c19"
] | [
"dl4nlp/word2vec.py"
] | [
"import numpy as np\nfrom dl4nlp.utilities import softmax\n\n\ndef softmax_cost_gradient(parameters, input, output):\n \"\"\"\n Softmax cost and gradient function for word2vec models\n :param parameters: word vectors for input and output (shape: (2, vocabulary_size, vector_size))\n :param input: index t... | [
[
"numpy.array",
"numpy.zeros_like",
"numpy.log"
]
] |
krishna-bala/gym-collision-avoidance | [
"a4dc1284d602808f3f96a25871327f7b2b4c4040"
] | [
"gym_collision_avoidance/envs/agent.py"
] | [
"import numpy as np\nfrom gym_collision_avoidance.envs import Config\nfrom gym_collision_avoidance.envs.util import wrap, find_nearest\nimport operator\nimport math\n\nclass Agent(object):\n \"\"\" A disc-shaped object that has a policy, dynamics, sensors, and can move through the environment\n\n :param start... | [
[
"numpy.array",
"numpy.linalg.norm",
"numpy.empty",
"numpy.dot",
"numpy.zeros",
"numpy.sin",
"numpy.ones",
"numpy.roll",
"numpy.arctan2",
"numpy.cos",
"numpy.linalg.inv"
]
] |
rajflume/tf-quant-finance | [
"5cb9474f6f2e74617735d38ef26aaef28ce69aff"
] | [
"tf_quant_finance/models/__init__.py"
] | [
"# Lint as: python3\n# Copyright 2019 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# https://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless required by appli... | [
[
"tensorflow.python.util.all_util.remove_undocumented"
]
] |
zacc23/freevirgil | [
"9099b1447dd764f8bb0f6c32cbb3b6bedf135920"
] | [
"examples/plot.py"
] | [
"import math\nimport freevirgil as fv\nfrom matplotlib import pyplot as plt\n\nspin = fv.spin_conf(N=10)\nham = fv.hamiltonian(J=-2, mu=1.1)\n\nirange = 100\nT = [0] * irange\nE = [0] * irange\nM = [0] * irange\nHC = [0] * irange\nMS = [0] * irange\n\nfor i in range(0, irange):\n\n T[i] = 0.1 * (i + 1)\n E[i]... | [
[
"matplotlib.pyplot.savefig",
"matplotlib.pyplot.xlabel",
"matplotlib.pyplot.plot",
"matplotlib.pyplot.legend",
"matplotlib.pyplot.figure"
]
] |
vmarkovtsev/ml | [
"22699b2f44901b84507d15e732003955024e6755"
] | [
"sourced/ml/algorithms/id_splitter/features.py"
] | [
"import logging\nimport string\nimport tarfile\nfrom typing import List, Tuple\n\nfrom modelforge.progress_bar import progress_bar\nimport numpy\n\n\ndef read_identifiers(csv_path: str, use_header: bool, max_identifier_len: int, identifier_col: int,\n split_identifier_col: int, shuffle: bool = T... | [
[
"numpy.random.shuffle"
]
] |
iCarrrot/Evol-algs | [
"51a51f9a0c7bca3731097160c40a96a7f40fa8f5"
] | [
"2/SGA.py"
] | [
"import numpy as np\nimport matplotlib.pyplot as plt\nimport time\nfrom MutationLocalSearch import mutation_local_search\n\n\ndef SGA(\n population_size,\n chromosome_length,\n number_of_offspring,\n crossover_probability,\n mutation_probability,\n number_of_iterations,\n tsp_objective_function... | [
[
"numpy.mod",
"numpy.random.choice",
"numpy.zeros",
"numpy.random.permutation",
"numpy.ones",
"numpy.min",
"numpy.random.random",
"numpy.argsort",
"numpy.hstack",
"numpy.vstack"
]
] |
seansegal/fastMRI | [
"44ebd517d792c5f6e66c64c004d0e0603057e7e1"
] | [
"models/sensitivity/espirit.py"
] | [
"# Uecker, M., Lai, P., Murphy, M. J., Virtue, P., Elad, M., Pauly, J. M., ... & Lustig, M. (2014). ESPIRiT—an eigenvalue approach to autocalibrating parallel MRI: where SENSE meets GRAPPA. Magnetic resonance in medicine, 71(3), 990-1001.\n# https://github.com/mikgroup/espirit-python\nimport numpy as np\n\nfft = l... | [
[
"numpy.reshape",
"numpy.zeros",
"numpy.sum",
"numpy.fft.ifftshift",
"numpy.shape",
"numpy.linalg.svd",
"numpy.sqrt"
]
] |
DDTR/learning_task2 | [
"3a235edb6515d1c83dee996d90df7da11661fb61"
] | [
"retrain_proc/example/mlp_policy.py"
] | [
"from baselines.common.mpi_running_mean_std import RunningMeanStd\nimport baselines.common.tf_util as U\nimport tensorflow as tf\nimport gym\nfrom baselines.common.distributions import make_pdtype\nimport numpy as np\nimport pdb\n\n# almost same parametrization of NN policies as in functioning_implementations/own_a... | [
[
"tensorflow.zeros_initializer",
"numpy.array",
"tensorflow.zeros",
"tensorflow.concat",
"tensorflow.nn.relu",
"numpy.sum",
"tensorflow.matmul",
"tensorflow.constant",
"tensorflow.variable_scope",
"tensorflow.clip_by_value",
"tensorflow.placeholder",
"numpy.amax",
... |
jungomi/swiss-language-model | [
"d071598b63c6f9d261dbcf056c0249b00bce1823"
] | [
"evaluate.py"
] | [
"import argparse\nimport multiprocessing\nimport os\nimport time\nfrom collections import OrderedDict\nfrom typing import Dict\n\nimport lavd\nimport torch\nimport torch.distributed as dist\nimport torch.multiprocessing as mp\nimport torch.nn as nn\nfrom torch.nn.parallel import DistributedDataParallel\nfrom torch.... | [
[
"torch.device",
"torch.distributed.init_process_group",
"torch.distributed.all_gather",
"torch.multiprocessing.spawn",
"torch.nn.parallel.DistributedDataParallel",
"torch.cuda.device_count",
"torch.manual_seed",
"torch.cuda.current_device",
"torch.cuda.set_device",
"torch.c... |
JCSDA-internal/pycrtm | [
"fbad865c3c369c8454944790949e5e19172767f0"
] | [
"testCases/test_atms_threads.py"
] | [
"#!/usr/bin/env python3\nimport os, h5py, sys \nimport numpy as np\nfrom matplotlib import pyplot as plt\nfrom pyCRTM import pyCRTM, profilesCreate\n \ndef main(sensor_id):\n thisDir = os.path.dirname(os.path.abspath(__file__))\n casesIn = os.listdir( os.path.join(thisDir,'data') )\n casesIn.sort()\n ca... | [
[
"numpy.asarray",
"numpy.zeros",
"matplotlib.pyplot.legend",
"matplotlib.pyplot.figure",
"numpy.linspace"
]
] |
archer2balls/Practice | [
"77301e3203a1fe01c850f38b9eb5eac1dec28fe0"
] | [
"StockWebApp.py"
] | [
"#Description: Stock market dashboard to show some charts and data on some stock\n\n#Import the libraries\nimport streamlit as st\nimport pandas as pd\nfrom PIL import Image\n\n#Add a title and an image\nst.write(\"\"\"\n#Stock Market Web Application\n**Visually** show data on a stock! Date range from Jan 01, 2020 ... | [
[
"pandas.to_datetime",
"pandas.DataFrame",
"pandas.read_csv",
"pandas.DatetimeIndex"
]
] |
dymbe/ad-versarial | [
"8fd46cd198baff03f11a5202e27e9a602bd3bb08"
] | [
"page-based/data-collection/generator.py"
] | [
"#! /usr/bin/env python3\n\nfrom skimage import draw, transform, util, filters, color, io\nimport math\nfrom io import BytesIO\nimport os\nimport argparse\nimport hashlib\nimport json\nimport random\nimport numpy as np\nimport threading\nimport concurrent.futures\nimport sys\n\nimport logging\nlogger = logging.getL... | [
[
"numpy.append",
"numpy.clip"
]
] |
TaeMiKim/Siamusic | [
"d529b098588bd361d978239169684e2a071bea11"
] | [
"augmentation.py"
] | [
"'''\ninput : torch.tensor() (16,1,48000)\noutput : augmented audio tensor\n'''\nimport pedalboard\nimport random\nimport time\nfrom utils import listen\nfrom dataset import MTA, GTZAN\nimport torch\nfrom torch.utils.data import DataLoader\nimport numpy as np\nfrom pedalboard import (Pedalboard, \n ... | [
[
"torch.tensor",
"torch.utils.data.DataLoader"
]
] |
JunzuoWan/Add-subtraction-multiplication-and-division | [
"eccad7adf0068e322c52c51ce87ad2f6a8be4401"
] | [
"tfLinearRegressionBest.py"
] | [
"# -*- coding: utf-8 -*-\r\n\"\"\"\r\nCreated on Mon Apr 2 10:21:56 2018\r\n\r\n@author: J.Wan\r\n\"\"\"\r\n\r\n#linear regression\r\n##linear regression: find the linear fit to generated data\r\n\r\nfrom __future__ import absolute_import\r\nfrom __future__ import division\r\nfrom __future__ import print_function\... | [
[
"numpy.random.normal",
"tensorflow.multiply",
"matplotlib.pyplot.xlabel",
"matplotlib.pyplot.savefig",
"matplotlib.pyplot.plot",
"matplotlib.pyplot.title",
"tensorflow.Session",
"numpy.random.randn",
"matplotlib.pyplot.figure",
"tensorflow.placeholder",
"matplotlib.pypl... |
kenchan0226/AbsThenExtPublic | [
"567811d6c76fe51c2c368eeaca1761eb322db2a2"
] | [
"model/copy_cond_summ.py"
] | [
"import torch\nfrom torch import nn\nfrom torch.nn import init\nfrom torch.nn import functional as F\n\nfrom .attention import step_attention\nfrom .util import sequence_mean, len_mask\nfrom .copy_summ import CopySumm, CopyLSTMDecoder\nfrom . import beam_search as bs\nfrom .rnn import lstm_encoder\n\n\nclass CopyCo... | [
[
"torch.nn.Linear",
"torch.cat",
"torch.nn.LSTM",
"torch.stack",
"torch.nn.Tanh",
"torch.mm",
"torch.matmul",
"torch.LongTensor",
"torch.nn.init.xavier_normal_",
"torch.Tensor"
]
] |
phetdam/npy_openblas_demo | [
"ff5f9932b19f82162bc0d9d46b341d42805f942b"
] | [
"npypacke/regression/tests/conftest.py"
] | [
"\"\"\"pytest test fixtures for regression.tests subpackage.\n\n.. codeauthor:: Derek Huang <djh458@stern.nyu.edu>\n\"\"\"\n\nimport numpy as np\nimport pytest\nfrom sklearn.datasets import make_regression\n\n# pylint: disable=no-name-in-module\nfrom .._linreg import LinearRegression\n\n\n@pytest.fixture\ndef lr_de... | [
[
"numpy.linalg.svd",
"numpy.array",
"numpy.linalg.matrix_rank",
"sklearn.datasets.make_regression"
]
] |
SirPopiel/IWDA | [
"5693b0704f1abf9f69f92fba243599c5f4056a3c"
] | [
"Examples/Electricity_test.py"
] | [
"from skmultiflow.meta import AdaptiveRandomForestRegressor\nfrom skmultiflow.trees import HoeffdingAdaptiveTreeRegressor, HoeffdingAdaptiveTreeClassifier\nfrom skmultiflow.evaluation import EvaluatePrequential\nfrom skmultiflow.data import DataStream\nfrom src.Environment import *\nfrom sklearn.linear_model import... | [
[
"matplotlib.pyplot.xlabel",
"matplotlib.pyplot.savefig",
"matplotlib.pyplot.legend",
"matplotlib.pyplot.subplots",
"matplotlib.pyplot.rc",
"matplotlib.pyplot.margins",
"matplotlib.pyplot.ylabel"
]
] |
JoleProject/Jole | [
"24739e6d9a28840acccbb531de415a5ef0eea0c8"
] | [
"src/garage/tf/algos/jole_ddpg_v1.py"
] | [
"\"\"\"Deep Deterministic Policy Gradient (DDPG) implementation in TensorFlow.\"\"\"\nfrom collections import deque\n\nfrom dowel import logger, tabular\nimport numpy as np\nimport tensorflow as tf\nimport tensorflow.contrib as tc\nimport random\nfrom garage.misc.overrides import overrides\nfrom garage.np.algos.off... | [
[
"numpy.concatenate",
"tensorflow.compat.v1.placeholder",
"tensorflow.compat.v1.squared_difference",
"numpy.max",
"numpy.sum",
"tensorflow.nn.moments",
"numpy.mean",
"numpy.std",
"numpy.random.uniform",
"tensorflow.name_scope",
"numpy.abs",
"numpy.clip",
"tensorf... |
jokfun/reservoirpy | [
"da978670a8a940847ad799ff0e92524dda873df0"
] | [
"minimalESN_MackeyGlass.py"
] | [
"# -*- coding: utf-8 -*-\n\"\"\"\nA minimalistic Echo State Networks demo with Mackey-Glass (delay 17) data\nin \"plain\" scientific Python.\nby Mantas LukoÅ¡eviÄ?ius 2012\nhttp://minds.jacobs-university.de/mantas\n---\nModified by Xavier Hinaut: 2015-2016\nhttp://www.xavierhinaut.com\n\"\"\"\n#from numpy import *\... | [
[
"numpy.square",
"numpy.dot",
"numpy.random.rand",
"numpy.zeros",
"numpy.random.seed",
"matplotlib.pyplot.ylim",
"matplotlib.pyplot.title",
"matplotlib.pyplot.plot",
"matplotlib.pyplot.legend",
"matplotlib.pyplot.figure",
"scipy.linalg.pinv",
"numpy.eye",
"numpy.... |
WorldChanger01/CORE_VAE | [
"702cc05f721b128ba219667b79357dcac88988ed"
] | [
"models/COREVAE.py"
] | [
"from __future__ import print_function\n\nimport numpy as np\n\nimport math\n\nfrom scipy.misc import logsumexp\n\n\nimport torch\nimport torch.utils.data\nimport torch.nn as nn\nfrom torch.nn import Linear\nfrom torch.autograd import Variable\nfrom torch.nn.functional import normalize\n\nfrom utils.distributions i... | [
[
"torch.nn.Linear",
"torch.nn.functional.normalize",
"torch.nn.Dropout",
"torch.max",
"torch.nn.Sequential",
"torch.nn.Tanh",
"torch.nn.Sigmoid",
"torch.clamp",
"numpy.prod",
"torch.nn.Hardtanh",
"torch.mean"
]
] |
Seanforfun/Distributed-Tensorflow-Framework | [
"a765505a068104a997f021a6d0fead3377652053"
] | [
"distribute.py"
] | [
"# ====================================================\n# Filename: distribute.py\n# Author: Botao Xiao\n# Function: This is the entrance of the distributed training system.\n# We run the training program by calling this file.\n# ====================================================\nimport os\nimport sys... | [
[
"tensorflow.train.Server",
"tensorflow.train.AdamOptimizer",
"tensorflow.train.ClusterSpec",
"tensorflow.FixedLenFeature",
"tensorflow.app.run"
]
] |
CapFreddy/BUAA-DL | [
"42be01f7a5d09e0336d0a3462f3e2d94131fedd1"
] | [
"svhn/Q4/regularizer.py"
] | [
"from __future__ import absolute_import\nfrom __future__ import division\nfrom __future__ import print_function\n\nimport numbers\n\nfrom tensorflow.python.framework import constant_op\nfrom tensorflow.python.framework import ops\nfrom tensorflow.python.ops import math_ops\nfrom tensorflow.python.ops import nn\nfro... | [
[
"tensorflow.python.ops.standard_ops.multiply",
"tensorflow.python.ops.math_ops.abs",
"tensorflow.python.platform.tf_logging.info",
"tensorflow.python.framework.ops.convert_to_tensor",
"tensorflow.python.framework.ops.name_scope"
]
] |
ahmadghizzawi/quantify-unfairness-emd | [
"b4dfccfdf839387a048fa9a49227438a82ab47d0"
] | [
"disparity/helpers.py"
] | [
"import csv\nimport math\nimport time\nimport json\nimport numpy as np\nfrom beautifultable import BeautifulTable\nfrom pymongo import MongoClient\n\nclass Helper:\n def __init__(self,\n db_name=\"WorkerSet100K\",\n collection_name=\"workers\",\n configuration=\"tr... | [
[
"numpy.mean"
]
] |
seanrsinclair/ORSuite | [
"54e05db3d6d34e60ce8982ef4e25eefdbe07b11e"
] | [
"or_suite/agents/ambulance/command_line_metric.py"
] | [
"import numpy as np\nimport sys\nfrom .. import Agent\n\nclass commandLineAgent(Agent):\n \"\"\"\n Allows the user to act as the agent by entering locations for each of the ambulances through the command line. Only works with the metric environment.\n \n Methods:\n reset() : clears data and call_... | [
[
"numpy.zeros"
]
] |
mahnooranjum/UpperConfidenceBound_ReinforcementLearning | [
"4c242d6bb39821bb63db5e5e14df674eee7ba6d7"
] | [
"upper_confidence_bound.py"
] | [
"##############################################################################\n#\n# Mahnoor Anjum\n# manomaq@gmail.com\n# References:\n# SuperDataScience,\n# Official Documentation\n#\t Dataset by:\n#\t\thttps://www.kaggle.com/c/criteo-display-ad-challenge\n#################################... | [
[
"matplotlib.pyplot.xlabel",
"matplotlib.pyplot.title",
"matplotlib.pyplot.hist",
"matplotlib.pyplot.ylabel",
"matplotlib.pyplot.show",
"pandas.read_csv"
]
] |
NamNguyen0905/FaceRecognition_MobileBio | [
"8a674906f6b4f12216cf72c37fd76d18cf628546"
] | [
"Nghia/get_landmarks.py"
] | [
"import dlib\r\nimport matplotlib.pyplot as plt\r\nimport numpy as np\r\nimport cv2\r\nimport math\r\nimport os\r\nimport time\r\n\r\n#from pyimagesearch.helpers import convert_and_trim_bb\r\n\r\ndef distances(points):\r\n dist = []\r\n for i in range(points.shape[0]):\r\n for j in range(points.shape[0... | [
[
"numpy.array",
"numpy.zeros",
"matplotlib.pyplot.savefig",
"matplotlib.pyplot.close",
"matplotlib.pyplot.figure",
"matplotlib.pyplot.imshow"
]
] |
hauntsaninja/pytorch | [
"83b45fe1666fd8ecc697078ca99ff46dabe0286b"
] | [
"torch/ao/quantization/quantization_mappings.py"
] | [
"import copy\n\nimport torch\nfrom torch import nn\n\nimport torch.nn.functional as F\nimport torch.nn.intrinsic as nni\nimport torch.nn.intrinsic.quantized as nniq\nimport torch.nn.intrinsic.quantized.dynamic as nniqd\nimport torch.nn.intrinsic.qat as nniqat\nimport torch.nn.quantized as nnq\nimport torch.nn.quant... | [
[
"torch.ao.quantization.utils.get_combined_dict"
]
] |
bilzard/Pedestrian-Synthesis-GAN | [
"adaf6efdf94ce99abf27bd613ade5d2722cfcd8a"
] | [
"models/pix2pix_model.py"
] | [
"import numpy as np\nimport torch\nimport os\nfrom collections import OrderedDict\nfrom torch.autograd import Variable\nimport util.util as util\nfrom util.image_pool import ImagePool\nfrom .base_model import BaseModel\nfrom copy import deepcopy\nfrom . import networks\nfrom PIL import Image\nimport torchvision.tra... | [
[
"torch.autograd.Variable",
"torch.cat",
"torch.nn.L1Loss"
]
] |
DecodEPFL/eiv-grid-id | [
"093a0f6f3537ee2d4003b6af6a10caaca986fa7a",
"093a0f6f3537ee2d4003b6af6a10caaca986fa7a"
] | [
"identify_network.py",
"src/models/bayesian_prior.py"
] | [
"import click\nimport numpy as np\n\nfrom src.identification import run, run3ph\nimport conf.identification\nfrom conf import simulation\nfrom src.simulation.lines import admittance_phase_to_sequence, measurement_phase_to_sequence\n\n\n@click.command()\n@click.option('--network', \"-n\", default=\"bolognani56\", he... | [
[
"numpy.delete",
"numpy.load",
"numpy.any",
"numpy.savez",
"numpy.sqrt"
],
[
"numpy.concatenate",
"numpy.array",
"numpy.ones_like",
"numpy.zeros",
"numpy.vstack"
]
] |
xiaoxiaoheimei/SeqDialN | [
"0675a4e3737a2f849e273123330ad6fddbfb2fba"
] | [
"visdialch/attention/dense_att_enc.py"
] | [
"import torch\nimport torch.nn as nn\nimport torch.nn.functional as F\nfrom visdialch.utils import DynamicRNN_v2\nimport numpy as np\nimport pdb\n\nclass DenseCoAttLayer(nn.Module):\n '''\n This layer implements the image-feature/content-feature dense co-attention mechanisum proposed by:\n \"Improve... | [
[
"torch.nn.Linear",
"torch.zeros",
"torch.nn.init.kaiming_uniform_",
"torch.cat",
"torch.nn.LSTM",
"torch.arange",
"torch.nn.init.constant_",
"torch.nn.ReLU",
"torch.LongTensor",
"numpy.sqrt",
"torch.matmul"
]
] |
statisticalbiotechnology/exactpermutation | [
"fd8fbca9fedad7fbdfeb3c1e203f1aa35baa91b0"
] | [
"exp/cll/cll_scatter.py"
] | [
"import pandas as pd\nimport numpy as np\nimport numpy.random as rnd\nimport scipy.stats as stat\nimport seaborn as sns\nimport matplotlib.pyplot as plt\nimport sys\nsys.path.append(\"../../src/\")\n\nfrom scatter_plots import *\n\ncll_data = pd.read_csv(\"eig_stat_cll.csv\", delimiter=\"\\t\")\nscatter_from_df(cl... | [
[
"pandas.read_csv"
]
] |
SamuelSchmidgall/EvolutionarySelfReplication | [
"1a6f8225378b59423a97b439b56710bbed2754e9"
] | [
"evo_gym/vector/tests/test_vector_env.py"
] | [
"import pytest\nimport numpy as np\n\nfrom evo_gym.vector.tests.utils import make_env\n\nfrom evo_gym.vector.async_vector_env import AsyncVectorEnv\nfrom evo_gym.vector.sync_vector_env import SyncVectorEnv\n\n@pytest.mark.parametrize('shared_memory', [True, False])\ndef test_vector_env_equal(shared_memory):\n en... | [
[
"numpy.all"
]
] |
omarmohamed15/Scalo_CAE | [
"7ca9d27b1e57be00a8b3817c5671fec211a9f8f5"
] | [
"Utils.py"
] | [
"from matplotlib.colors import ListedColormap\nimport h5py\nimport matplotlib.pyplot as plt\nimport numpy as np\nimport scipy.io\nfrom sklearn.cluster import KMeans\nfrom sklearn.mixture import GaussianMixture\nfrom sklearn.cluster import MeanShift\nfrom scipy import ndimage, misc\nimport obspy\nfrom obspy.imaging.... | [
[
"numpy.zeros_like",
"sklearn.cluster.KMeans",
"numpy.min",
"matplotlib.pyplot.subplots",
"numpy.shape",
"numpy.mean",
"numpy.where",
"numpy.std",
"numpy.arange",
"numpy.sort",
"numpy.abs"
]
] |
rvencu/clip-retrieval | [
"6d77497a98aab323c0d2b259d83a7afa97902f85"
] | [
"clip_retrieval/clip_back.py"
] | [
"from flask import Flask, request, make_response\nfrom flask_restful import Resource, Api\nfrom flask_cors import CORS\nimport clip\nimport faiss\nimport torch\nimport json\nfrom PIL import Image\nfrom io import BytesIO\nfrom PIL import Image\nimport base64\nimport os\nimport fire\nfrom pathlib import Path\nimport ... | [
[
"pandas.DataFrame",
"pandas.read_parquet",
"torch.cuda.is_available"
]
] |
nakul-shahdadpuri/sunpy | [
"e0555ae1c47749bf85cf5d58c0b38b731cd623eb"
] | [
"sunpy/map/mapbase.py"
] | [
"\"\"\"\nMap is a generic Map class from which all other Map classes inherit from.\n\"\"\"\nimport copy\nimport html\nimport textwrap\nimport warnings\nimport webbrowser\nfrom io import BytesIO\nfrom base64 import b64encode\nfrom tempfile import NamedTemporaryFile\nfrom collections import namedtuple\n\nimport matpl... | [
[
"numpy.dot",
"numpy.min",
"numpy.cos",
"numpy.ma.getdata",
"numpy.deg2rad",
"numpy.max",
"numpy.sin",
"matplotlib.pyplot.get_cmap",
"numpy.flipud",
"matplotlib.backend_bases.FigureCanvasBase",
"matplotlib.patches.Circle",
"numpy.isfinite",
"matplotlib.pyplot.sci... |
wh3248/pf-xarray | [
"f971e0c3e9962958fcf807e45d2623a0784cba8c"
] | [
"pf_xarray/io.py"
] | [
"from collections.abc import Iterable\nimport itertools\nfrom numba import jit\nimport numpy as np\nimport struct\nfrom typing import Mapping, List, Union\nfrom numbers import Number\nfrom pprint import pprint\n\n\ndef read_pfb(file: str, mode: str='full', z_first: bool=True):\n \"\"\"\n Read a single pfb fil... | [
[
"numpy.max",
"numpy.concatenate",
"numpy.array",
"numpy.empty",
"numpy.flatnonzero",
"numpy.min",
"numpy.prod",
"numpy.arange",
"numpy.all",
"numpy.hstack",
"numpy.floor"
]
] |
ygan/IRNet | [
"d52b1f3a72624dbe3146a587dbfae74fa19b0a24"
] | [
"eval.py"
] | [
"# Copyright (c) Microsoft Corporation.\r\n# Licensed under the MIT license.\r\n\r\n# -*- coding: utf-8 -*-\r\n\"\"\"\r\n# @Time : 2019/5/27\r\n# @Author : Jiaqi&Zecheng\r\n# @File : eval.py\r\n# @Software: PyCharm\r\n\"\"\"\r\n\r\n\r\nimport torch\r\nfrom src import args as arg\r\nfrom src import utils\r\nf... | [
[
"torch.load"
]
] |
weselyj/jesse | [
"24ce05c17494b6ac7b4201cf06b4fa9d16d4d709"
] | [
"jesse/modes/optimize_mode/fitness.py"
] | [
"\"\"\"\nFor the multiprocessing to work property, it's best to pass around pure functions into workers instead\nof methods of a class. Below functions have been designed with that in mind.\n\"\"\"\nfrom math import log10\nimport jesse.helpers as jh\nfrom jesse.research.backtest import _isolated_backtest as isolate... | [
[
"numpy.isnan"
]
] |
ayandeephazra/Chemical_Origins_Of_Life | [
"5858b51063c53b2db00529fe79a67d321193171e"
] | [
"Approach 1/Model that was derived from reactions and had all relevant terms/forwardSimulation.py"
] | [
"from scipy.integrate import solve_ivp\nimport numpy as np\nfrom ode_helpers import state_plotter\n\n\ndef f(t, y, model1, model2):\n dydt = [1]\n for i in range(len(model1.equations())):\n\n sumT = 0\n string = model1.equations()[i]\n listOfWords = string.split()\n # print(listOfW... | [
[
"numpy.linspace"
]
] |
deimqs/ClusterModel | [
"a073ffff012ad3404acd9ce12396f63fe7e81109"
] | [
"ClusterTools/cluster_xspec.py"
] | [
"\"\"\"\nThis script contains Xspec tools.\nIt requires to have xspec installed on your machine.\n\n\"\"\"\n\nimport os\nimport re\nimport numpy as np\nimport matplotlib.pyplot as plt\n\nfrom ClusterModel.ClusterTools import map_tools\n\n\n#==================================================\n# Get the hydrogen colu... | [
[
"numpy.zeros",
"numpy.median",
"matplotlib.pyplot.xlabel",
"numpy.roll",
"matplotlib.pyplot.figure",
"numpy.std",
"matplotlib.pyplot.hist",
"matplotlib.pyplot.ylabel",
"numpy.log10",
"matplotlib.pyplot.show",
"numpy.linspace"
]
] |
matteobarato/Upsampling_Vocoder | [
"f7659bee8c89223fe9c13e9cb39cb683acd2fc7f"
] | [
"model.py"
] | [
"import torch\nimport torch.nn as nn\nimport torch.nn.functional as F\nimport numpy as np\n\n\nclass LinearNorm(torch.nn.Module):\n def __init__(self, in_dim, out_dim, bias=True, w_init_gain='linear'):\n super(LinearNorm, self).__init__()\n self.linear_layer = torch.nn.Linear(in_dim, out_dim, bias=... | [
[
"torch.nn.Linear",
"torch.cat",
"torch.nn.LSTM",
"torch.nn.ConvTranspose1d",
"torch.nn.ModuleList",
"torch.nn.Conv1d",
"torch.nn.BatchNorm1d",
"torch.nn.init.calculate_gain"
]
] |
pawelkobojek/pytorch-lightning-bolts | [
"2f3f58045a44ffb32103a3644c2ee2be920a508b",
"2f3f58045a44ffb32103a3644c2ee2be920a508b"
] | [
"pl_bolts/datamodules/kitti_datamodule.py",
"pl_bolts/models/self_supervised/moco/moco2_module.py"
] | [
"import os\n\nimport torch\nimport torchvision.transforms as transforms\nfrom pytorch_lightning import LightningDataModule\nfrom torch.utils.data import DataLoader\nfrom torch.utils.data.dataset import random_split\n\nfrom pl_bolts.datasets.kitti_dataset import KittiDataset\n\n\nclass KittiDataModule(LightningDataM... | [
[
"torch.Generator",
"torch.utils.data.DataLoader"
],
[
"torch.zeros",
"torch.nn.functional.normalize",
"torch.cat",
"torch.nn.Linear",
"torch.distributed.get_world_size",
"torch.einsum",
"torch.no_grad",
"torch.argsort",
"torch.distributed.all_gather",
"torch.ran... |
Pakketeretet2/lammps-tools | [
"1e2109018a7412c33c80bb3eceb1f97003495341"
] | [
"python/lammpstools/normal_mode_analysis.py"
] | [
"\"\"\"!\nThis module contains some normal mode analysis tools\n\n\\ingroup lammpstools\n\"\"\"\n\nimport dumpreader\nimport lammpstools\nimport numpy as np\nimport scipy\nimport sys, os\nimport math\nfrom typecasts import *\nfrom ctypes import *\n\n\nfrom multiprocessing import Process\n\ndef normal_mode_analysis(... | [
[
"numpy.linspace",
"numpy.linalg.eig",
"numpy.zeros"
]
] |
AlexTintin/Face_Recognition_CV_Project | [
"6becb159dd3d8f547d617983bd422e3f2a9fb52e"
] | [
"correlationmodel.py"
] | [
"\nimport argparse\nimport os\nimport sys\nimport torch as t\nimport torch.nn as nn\nimport torch.nn.functional as F\n\nfrom torch.autograd import Variable\nfrom torchvision import models, transforms\n\nimport numpy as np\n\nnormalize = transforms.Normalize(\n mean=[0.485, 0.456, 0.406],\n std=[0.229, 0.224, 0.... | [
[
"torch.autograd.Variable",
"torch.stack",
"torch.nn.functional.conv2d"
]
] |
CryptoBerryBot/Okapi | [
"3e58c159b488ae5c1eebe383e6ea8185d80dd912"
] | [
"src/okapi/api/market.py"
] | [
"# Copyright 2022 Romain Brault\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 to... | [
[
"pandas.to_datetime",
"pandas.DataFrame",
"numpy.asarray",
"pandas.DataFrame.from_dict"
]
] |
ceavelasquezpi/neuralnilm | [
"184b2301333e49828d29064c59496f82c89dcbad"
] | [
"neuralnilm/trainer.py"
] | [
"from __future__ import print_function, division\nfrom functools import partial\nimport os\nimport shutil\nfrom copy import copy\nimport numpy as np\nimport pandas as pd\nimport matplotlib.pyplot as plt\nimport theano\nfrom time import time\nfrom pymongo import MongoClient\n\nfrom lasagne.updates import nesterov_mo... | [
[
"numpy.isnan",
"matplotlib.pyplot.savefig",
"pandas.DataFrame",
"numpy.ones",
"matplotlib.pyplot.close",
"matplotlib.pyplot.subplots"
]
] |
dham/sum_factorisation_scaling_tests | [
"abe90cd92725224a2695bbc30f9a74c57bbdb68e"
] | [
"plot.py"
] | [
"import pylab as plt\nimport json\nimport numpy as np\n\ndataset = json.load(file(\"data.json\", \"r\"))\n\nscaling = {\"matrix\": lambda dim: 2 * dim + 1,\n \"action\": lambda dim: dim + 1}\n\n\nfor dim in (2, 3):\n for operation, data in dataset[str(dim)].iteritems():\n\n plt.figure()\n\n ... | [
[
"numpy.array"
]
] |
dhermes/foreign-fortran | [
"725d39b243fdf379dec4ce37a53e9e9b0b98c5a0"
] | [
"cython/check_cython.py"
] | [
"from __future__ import print_function\n\nimport numpy as np\n\nfrom check_ctypes import MAKE_UDF_TEMPLATE\nfrom check_ctypes import SEPARATOR\nimport example\n\n\ndef main():\n print(SEPARATOR)\n # foo()\n bar = 1.0\n baz = 16.0\n quux = example.foo(bar, baz)\n print(\"quux = foo({}, {}) = {}\".f... | [
[
"numpy.asfortranarray"
]
] |
pedro-abundio-wang/image-classification | [
"952719d7561b9998add0daf71d61e55cb6103eaf"
] | [
"vision/image_classification/inception/inceptionV1_model.py"
] | [
"\"\"\"GoogLeNet model for Keras.\n\nRelated papers:\n- https://arxiv.org/abs/1409.4842\n\n\"\"\"\n\nfrom __future__ import absolute_import\nfrom __future__ import division\nfrom __future__ import print_function\n\nfrom tensorflow.keras import backend\nfrom tensorflow.keras import models\nfrom tensorflow.keras impo... | [
[
"tensorflow.keras.layers.Permute",
"tensorflow.keras.layers.Input",
"tensorflow.keras.layers.Activation",
"tensorflow.keras.backend.image_data_format",
"tensorflow.keras.layers.MaxPool2D",
"tensorflow.keras.models.Model",
"tensorflow.keras.layers.Dropout",
"tensorflow.keras.layers.... |
mbbroberg/SEODeploy | [
"5de0c3f8f3658638128445e78854e6a6e2daa8cf"
] | [
"src/seodeploy/lib/__init__.py"
] | [
"#! /usr/bin/env python\n# coding: utf-8\n#\n# Copyright (c) 2020 JR Oakes\n#\n# Permission is hereby granted, free of charge, to any person obtaining\n# a copy of this software and associated documentation files (the\n# \"Software\"), to deal in the Software without restriction, including\n# without limitation the... | [
[
"pandas.DataFrame"
]
] |
cew8/mcf | [
"c71a3de528e418db5539eefbcb980877cafc824e"
] | [
"mcf/mcf_iate_functions.py"
] | [
"\"\"\"\nProcedures needed for IATE estimation.\n\nCreated on Thu Dec 8 15:48:57 2020.\n\n@author: MLechner\n\n# -*- coding: utf-8 -*-\n\"\"\"\nfrom concurrent import futures\nimport numpy as np\nimport pandas as pd\nfrom sklearn.cluster import KMeans\nfrom sklearn.metrics import silhouette_score\nimport scipy.stat... | [
[
"numpy.median",
"numpy.copy",
"numpy.mean",
"numpy.size",
"pandas.concat",
"pandas.read_csv",
"numpy.concatenate",
"numpy.count_nonzero",
"numpy.empty",
"pandas.set_option",
"pandas.DataFrame",
"matplotlib.pyplot.subplots",
"numpy.arange",
"numpy.sqrt",
... |
gherbin/ComputerVisionKUL | [
"c1367c812007d4533aca24d0d09b06590c0193a5"
] | [
"assignment1/template_matching_test.py"
] | [
"import cv2\nimport numpy as np\nfrom matplotlib import pyplot as plt\n\nimg = cv2.imread('D:/Videos/Test/image_test_template.png',0)\nimg2 = img.copy()\ntemplate = cv2.imread('D:/Videos/template_91_91.png',0)\nw, h = template.shape[::-1]\n\n# All the 6 methods for comparison in a list\nmethods = ['cv2.TM_CCOEFF', ... | [
[
"matplotlib.pyplot.subplot",
"matplotlib.pyplot.suptitle",
"matplotlib.pyplot.title",
"matplotlib.pyplot.yticks",
"matplotlib.pyplot.show",
"matplotlib.pyplot.xticks",
"matplotlib.pyplot.imshow"
]
] |
OctopusRice/LineNet | [
"a03ce3bf741dc497ae6bc680cd779128bda1a34b",
"a03ce3bf741dc497ae6bc680cd779128bda1a34b"
] | [
"core/sample/cornernet.py",
"core/test/linenet.py"
] | [
"import cv2\nimport math\nimport numpy as np\nimport torch\n\nfrom .utils import random_crop, draw_gaussian, gaussian_radius, normalize_, color_jittering_, lighting_\n\n\ndef _resize_image(image, detections, size):\n detections = detections.copy()\n height, width = image.shape[0:2]\n new_height, new_width ... | [
[
"numpy.random.uniform",
"torch.from_numpy",
"numpy.zeros",
"numpy.clip"
],
[
"numpy.concatenate",
"numpy.array",
"numpy.zeros",
"torch.from_numpy",
"torch.cuda.FloatTensor",
"numpy.clip",
"numpy.partition"
]
] |
hymenoby/ucacity-image-classifier | [
"f84e822f10e4fb6a1d2b40861a7e5714caf4a0eb"
] | [
"train.py"
] | [
"import argparse\nimport errno\nimport sys\nimport time\nimport torch\nimport os\nimport utils\nfrom torchvision import models\nfrom torch import nn\nfrom torch import optim\n\n# get arguments\nparser = argparse.ArgumentParser(description=\"Training neural network\")\nparser.add_argument('data_directory', action='s... | [
[
"torch.nn.NLLLoss",
"torch.device",
"torch.no_grad",
"torch.cuda.is_available"
]
] |
JWTAmsterdam/RockTheRoad | [
"1806e44005dfe328dbe89df2edd8793333eed8ba"
] | [
"plot/plot.py"
] | [
"#very simple plotter for the csv data\n#this example works specifically for the ice.csv data\n#run on your terminal python plot.py\n#how to change data here\n\nfrom matplotlib import pyplot\nimport numpy as np\n\nall_data = np.loadtxt(open(\"data/sample.csv\",\"r\"),\n delimiter=\",\",\n skiprows=1,\n dty... | [
[
"matplotlib.pyplot.subplot",
"matplotlib.pyplot.show",
"matplotlib.pyplot.figure"
]
] |
gitter-badger/bokeh | [
"5481346de1642a4e6710d32b70262fd6c2674360"
] | [
"examples/embed/app_reveal.py"
] | [
"# -*- coding: utf-8 -*-\n\nimport time\nfrom threading import Thread\n\nimport numpy as np\nimport scipy.special\n\nfrom bokeh.embed import autoload_server\nfrom bokeh.objects import Glyph\nfrom bokeh.plotting import (annular_wedge, curplot, cursession, figure, hold,\n legend, line, outp... | [
[
"numpy.random.normal",
"numpy.zeros_like",
"numpy.histogram",
"numpy.sin",
"numpy.roll",
"numpy.exp",
"numpy.cos",
"numpy.sqrt",
"numpy.linspace"
]
] |
JoseALermaIII/lightkurve | [
"174eae6a6470f40a26eec67225f1d84238ea6670"
] | [
"lightkurve/mast.py"
] | [
"\"\"\"Functions which wrap `astroquery.mast` to obtain Kepler/K2 data from MAST.\"\"\"\n\nfrom __future__ import division, print_function\nimport os\nimport logging\nimport numpy as np\n\nfrom astroquery.mast import Observations\nfrom astroquery.exceptions import ResolverError\nfrom astropy.coordinates import SkyC... | [
[
"numpy.array",
"numpy.asarray",
"numpy.shape",
"numpy.any",
"numpy.where",
"numpy.arange",
"numpy.unique"
]
] |
jianzhnie/d2nlp | [
"94da74ec9be3aeee699b358f6bba9fde43bd80c0"
] | [
"nlptoolkit/models/elmo/elmo_model.py"
] | [
"'''\nAuthor: jianzhnie\nDate: 2022-01-05 17:00:54\nLastEditTime: 2022-01-20 10:20:20\nLastEditors: jianzhnie\nDescription:\n\n'''\nimport os\n\nimport torch\nimport torch.nn as nn\nimport torch.nn.functional as F\nfrom torch.nn.utils.rnn import pack_padded_sequence, pad_packed_sequence\n\n\nclass Highway(nn.Module... | [
[
"torch.nn.Linear",
"torch.sigmoid",
"torch.cat",
"torch.nn.LSTM",
"torch.nn.ModuleList",
"torch.nn.Conv1d",
"torch.max",
"torch.arange",
"torch.nn.functional.dropout",
"torch.nn.utils.rnn.pad_packed_sequence",
"torch.nn.functional.relu"
]
] |
Xuduoteng/ProblemJudgment | [
"cf6664f5b77c3b9defa30126b2db193d3cc8debd"
] | [
"image_process.py"
] | [
"import cv2\nimport numpy as np\nimport matplotlib.pyplot as plt\nfrom PIL import Image\n \n# img = cv2.imread(r'C:\\\\Users\\\\27466\\\\Desktop\\\\RECENT\\\\yolov5-streamlit-by-xdt-master\\\\yolov5-streamlit-by-xdt-master\\\\data\\\\images\\\\3.jpg', cv2.IMREAD_GRAYSCALE)#GRAYSCALE\n\ndef imageGray(uploaded_fil... | [
[
"numpy.round"
]
] |
ForrestPi/3DfaceReconstruction | [
"d75a6f9112efc04f4912402835810f3e01d2a9f9"
] | [
"faceSwap/3DDFA/modules/Deep3DFaceReconstruction/preprocess_img.py"
] | [
"import numpy as np \nfrom scipy.io import loadmat,savemat\nfrom PIL import Image\n\n#calculating least sqaures problem\ndef POS(xp,x):\n\tnpts = xp.shape[1]\n\n\tA = np.zeros([2*npts,8])\n\n\tA[0:2*npts-1:2,0:3] = x.transpose()\n\tA[0:2*npts-1:2,3] = 1\n\n\tA[1:2*npts:2,4:7] = x.transpose()\n\tA[1:2*npts:2,7] = 1;... | [
[
"numpy.array",
"numpy.linalg.norm",
"numpy.zeros",
"numpy.stack",
"numpy.linalg.lstsq",
"numpy.expand_dims"
]
] |
scikit-maad/scikit-maad | [
"2052c6f5ffc2a973fa1676364cc1663d7da1715a"
] | [
"maad/sound/spectro_func.py"
] | [
"#!/usr/bin/env python\r\n\"\"\" \r\nCollection of functions transform an audio signal into spectrogram and \r\nmanipulate spectrograms.\r\n\"\"\"\r\n#\r\n# Authors: Juan Sebastian ULLOA <lisofomia@gmail.com>\r\n# Sylvain HAUPERT <sylvain.haupert@mnhn.fr>\r\n#\r\n# License: New BSD License\r\n\r\n# =====... | [
[
"numpy.max",
"numpy.array",
"scipy.signal.spectrogram",
"numpy.asarray",
"numpy.sum",
"numpy.min",
"numpy.mean",
"numpy.arange",
"numpy.sqrt",
"numpy.ndim"
]
] |
erichiggins/PyShoot | [
"f97dba8efecebb73c2cd7a04c29513dc8755c7da"
] | [
"PyShoot.py"
] | [
"#!/usr/bin/env python3\n\nimport argparse\nimport math\nimport random\nimport functools\n\nimport matplotlib.pyplot as plt\nimport numpy as np\nfrom scipy.spatial import ConvexHull\n\n\n# Application bounds\nLOWER_CAL = 0.17\nUPPER_CAL = 0.5\nMIN_SHOTS = 3\nMAX_SHOTS = 100000\n\n# Default Application variables\nAC... | [
[
"numpy.random.normal",
"matplotlib.pyplot.xlim",
"matplotlib.pyplot.ylim",
"matplotlib.pyplot.title",
"matplotlib.pyplot.plot",
"matplotlib.pyplot.subplots",
"matplotlib.pyplot.Circle",
"scipy.spatial.ConvexHull",
"matplotlib.pyplot.show",
"matplotlib.pyplot.gca"
]
] |
aztan2/charged-defects-framework | [
"db23be39f580bb110abe0b2a2fb5da415fb6a381"
] | [
"qdef2d/defects/corrections/alignment_correction_2d.py"
] | [
"import os\nimport time\nimport argparse\nimport numpy as np\nimport matplotlib.pyplot as plt\nplt.switch_backend('agg')\nfrom qdef2d import logging\n\n\ndef calc(vref,vdef,encut,q,threshold_slope=1e-3,threshold_C=1e-3,max_iter=20,\n vfile='vline-eV.dat',noplots=False,allplots=False,logfile=None):\n \n ... | [
[
"matplotlib.pyplot.switch_backend",
"matplotlib.pyplot.xlim",
"matplotlib.pyplot.xlabel",
"matplotlib.pyplot.plot",
"matplotlib.pyplot.legend",
"matplotlib.pyplot.close",
"matplotlib.pyplot.figure",
"numpy.sign",
"numpy.loadtxt",
"numpy.polyfit",
"matplotlib.pyplot.ylab... |
RichardScottOZ/bluecap | [
"9d06de2fbdb60080d448287099d8b5621fb642d2"
] | [
"Actions/ComparativeSensitivityAction.py"
] | [
"\"\"\"\nCopyright (C) 2019-2021, Monash University, Geoscience Australia\nCopyright (C) 2018, Stuart Walsh \n\nBluecap is released under the Apache License, Version 2.0 (the \"License\");\nyou may not use this software except in compliance with the License.\nYou may obtain a copy of the License at\n\n http://ww... | [
[
"numpy.array",
"numpy.isnan",
"numpy.abs",
"numpy.moveaxis",
"numpy.nanmax"
]
] |
EPFL-VILAB/omnidata | [
"a1e31eb26172ecf8a3e49ba8a5c82ab3038a9c01"
] | [
"paper_code/omnidata_sasha_edits/transforms.py"
] | [
"import json\nimport numpy as np\nimport os\nfrom PIL import Image\nimport h5py\nimport torch\nfrom scipy.ndimage.filters import convolve\nimport torchvision\nimport torchvision.transforms as transforms\nimport torch.nn as nn\nimport torch.nn.functional as F\nfrom typing import Optional\n\nimport task_configs\n\n... | [
[
"numpy.square",
"numpy.array",
"numpy.uint8",
"scipy.ndimage.filters.convolve",
"numpy.minimum",
"numpy.ones",
"numpy.load",
"numpy.sqrt",
"torch.Tensor",
"numpy.expand_dims"
]
] |
Shigangli/dace | [
"966365a572921a6916737e4292e581e767873cf0"
] | [
"dace/symbolic.py"
] | [
"# Copyright 2019-2021 ETH Zurich and the DaCe authors. All rights reserved.\nimport ast\nfrom functools import lru_cache\nimport sympy\nimport pickle\nimport re\nfrom typing import Any, Dict, Optional, Set, Tuple, Union\nimport warnings\nimport numpy\n\nimport sympy.abc\nimport sympy.printing.str\n\nfrom dace impo... | [
[
"numpy.any",
"numpy.int64"
]
] |
shenao-zhang/DCPU | [
"0da9aa2b7878b54ba4ee4dca894c2e86cdc0d559"
] | [
"exps/util.py"
] | [
"\"\"\"Utilities for GP-UCRL experiments.\"\"\"\nfrom itertools import chain\n\nimport gpytorch\nimport numpy as np\nimport torch\nimport torch.jit\nimport torch.nn as nn\nimport torch.optim as optim\nimport yaml\nfrom rllib.algorithms.mpc import CEMShooting, MPPIShooting, RandomShooting\nfrom rllib.model import Ab... | [
[
"torch.zeros",
"torch.tensor",
"torch.abs"
]
] |
TheScientist1900/Faster-rcnn-helmet-detection | [
"48485716e47bd80788d05b00d7f24a9f234571c7",
"48485716e47bd80788d05b00d7f24a9f234571c7"
] | [
"utils/utils.py",
"nets/vgg16.py"
] | [
"import logging\nimport pathlib\nimport time\nimport numpy as np\nfrom PIL import Image\nimport cv2\nimport os\n\nfrom tqdm import tqdm\n#---------------------------------------------------------#\n# 将图像转换成RGB图像，防止灰度图在预测时报错。\n# 代码仅仅支持RGB图像的预测，所有其它类型的图像都会转化成RGB\n#-------------------------------------------------... | [
[
"numpy.shape"
],
[
"torch.nn.Linear",
"torch.nn.Dropout",
"torch.flatten",
"torch.nn.MaxPool2d",
"torch.nn.Sequential",
"torch.nn.init.constant_",
"torch.nn.BatchNorm2d",
"torch.nn.init.kaiming_normal_",
"torch.nn.ReLU",
"torch.nn.Conv2d",
"torch.nn.init.normal_... |
nickpezzotti1/IIC3 | [
"9edd27b28d2bddec4c3979ea4591380f5c411c8e"
] | [
"code1/utils/cluster/eval_metrics.py"
] | [
"from __future__ import print_function\n\nimport numpy as np\nimport torch\nfrom sklearn import metrics\nfrom sklearn.utils.linear_assignment_ import linear_assignment\n\n\ndef _original_match(flat_preds, flat_targets, preds_k, targets_k):\n # map each output channel to the best matching ground truth (many to one)... | [
[
"sklearn.utils.linear_assignment_.linear_assignment",
"sklearn.metrics.adjusted_rand_score",
"sklearn.metrics.normalized_mutual_info_score",
"numpy.zeros"
]
] |
chebee7i/ipython | [
"85b169fa3afc3d374973295c7f1409ededddbaca"
] | [
"IPython/kernel/zmq/eventloops.py"
] | [
"# encoding: utf-8\n\"\"\"Event loop integration for the ZeroMQ-based kernels.\n\"\"\"\n\n#-----------------------------------------------------------------------------\n# Copyright (C) 2011 The IPython Development Team\n\n# Distributed under the terms of the BSD License. The full license is in\n# the file COP... | [
[
"matplotlib.backends.backend_macosx.show.mainloop",
"matplotlib.backends.backend_macosx.TimerMac"
]
] |
Sooner0931/pymc3 | [
"458e513e47ed764c1ec4efcfce50ea7bd9fefbfd"
] | [
"pymc3/theanof.py"
] | [
"# Copyright 2020 The PyMC Developers\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 appli... | [
[
"numpy.array",
"numpy.ones",
"numpy.asarray"
]
] |
IcarusWizard/monodepth-paddle | [
"ccd616b4416903fcff874d54888f34528a2275bb"
] | [
"eval/evaluate_kitti.py"
] | [
"import numpy as np\nimport cv2\nimport argparse\nfrom tqdm import tqdm\nfrom evaluation_utils import *\n\nparser = argparse.ArgumentParser(description='Evaluation on the KITTI dataset')\nparser.add_argument('--split', type=str, help='data split, kitti or eigen', required=True)\nparser.add_a... | [
[
"numpy.isinf",
"numpy.array",
"numpy.zeros",
"numpy.load",
"numpy.logical_and",
"numpy.abs"
]
] |
HPLegion/glue | [
"1843787ccb4de852dfe103ff58473da13faccf5f"
] | [
"glue/core/data_factories/tests/test_fits.py"
] | [
"import os\nfrom collections import namedtuple\nfrom copy import deepcopy\n\nimport pytest\nimport numpy as np\nfrom numpy.testing import assert_array_equal\n\nfrom glue.core import data_factories as df\n\nfrom glue.tests.helpers import requires_astropy, make_file\n\nfrom ..fits import fits_reader\n\n\nDATA = os.pa... | [
[
"numpy.array",
"numpy.testing.assert_array_equal",
"numpy.ones"
]
] |
Xinfeng-Yao/APEC | [
"0596e2c8947fd9eb3b4cb5acee8d298ebbe8408a"
] | [
"code_v1.0.6/generate_umap.py"
] | [
"import sys,getopt,numpy,pandas,umap,scipy.stats\nfrom sklearn.decomposition import PCA\nimport matplotlib\nmatplotlib.use('Agg')\nimport matplotlib.pyplot as plt\n#\n#\ndef get_parameters(argv):\n project, cellinfo, rand_stat, norm_method = '', '', 0, 'zscore'\n help_info = ['Plot UMAP figure \\n',\n ... | [
[
"matplotlib.use",
"numpy.array",
"pandas.DataFrame",
"matplotlib.pyplot.subplots",
"numpy.where",
"pandas.read_csv"
]
] |
kirillbobyrev/crawlboy | [
"a34297951cdd58e2c594fe0d24e7bd972a792aab"
] | [
"misc/visualize_doc2vec.py"
] | [
"from __future__ import absolute_import\nfrom __future__ import division\nfrom __future__ import print_function\n\nfrom gensim.models.doc2vec import Doc2Vec\nfrom sklearn.manifold import TSNE\n\nimport numpy as np\nimport matplotlib.pyplot as plt\nfrom matplotlib import offsetbox\n\n\ndef plot_embedding(X, title=No... | [
[
"numpy.max",
"numpy.array",
"numpy.sum",
"matplotlib.pyplot.title",
"matplotlib.offsetbox.OffsetImage",
"numpy.min",
"sklearn.manifold.TSNE",
"matplotlib.pyplot.figure",
"matplotlib.pyplot.yticks",
"matplotlib.pyplot.cm.Set1",
"matplotlib.pyplot.xticks",
"matplotlib... |
DMGW-Goethe/imripy | [
"8e5c2fd2af539f00b4ea66a285d4ed276c8df7a1"
] | [
"src/imripy/merger_system.py"
] | [
"import numpy as np\nimport imripy.cosmo as cosmo\nimport imripy.halo as halo\n#from scipy.constants import G, c\n\n\nhz_to_invpc = 1.029e8\ns_to_pc = 9.716e-9\nm_to_pc = 3.241e-17\nsolar_mass_to_pc = 4.8e-14\ng_cm3_to_invpc2 = 7.072e8\nyear_to_pc = 0.3064\n\n\n\nclass SystemProp:\n \"\"\"\n A class describin... | [
[
"numpy.shape"
]
] |
toccip/mnist_img_recog | [
"f304a3d4002248dc613d77db24d52b15923f9e99"
] | [
"neural_network.py"
] | [
"import numpy as np\nimport random\n\ndef sig(x):\n x = np.clip( x, -600, 600 )\n return 1.0 / (1.0 + np.exp(-x))\n \ndef sig_d(x):\n return sig(x) * (1.0 - sig(x))\n\n\ndef read_images(filename, data_size):\n img_data = list()\n with open(filename, 'rb') as f:\n f.read(4)\n img_num ... | [
[
"numpy.full",
"numpy.dot",
"numpy.empty",
"numpy.random.randn",
"numpy.exp",
"numpy.subtract",
"numpy.argmax",
"numpy.clip"
]
] |
NunoEdgarGub1/qiskit-toaster | [
"7981ccd073e06acce98309beac036ba8d8b71901"
] | [
"quantastica/qiskit_toaster/ToasterBackend.py"
] | [
"# This code is part of quantastica.qiskit_toaster\n#\n# (C) Copyright Quantastica 2019. \n# https://quantastica.com/\n#\n# This code is licensed under the Apache License, Version 2.0. You may\n# obtain a copy of this license in the LICENSE.txt file in the root directory\n# of this source tree or at http://www.apac... | [
[
"numpy.random.RandomState"
]
] |
arinachison/abides | [
"39356709ef5ee18be5f76b47ed90490865278a8b"
] | [
"cli/midpoint_plot.py"
] | [
"import ast\nimport matplotlib\nmatplotlib.use('TkAgg')\nimport matplotlib.pyplot as plt\nimport pandas as pd\nimport os\nimport sys\n\nfrom joblib import Memory\n\n# Auto-detect terminal width.\npd.options.display.width = None\npd.options.display.max_rows = 1000\npd.options.display.max_colwidth = 200\n\n# Initiali... | [
[
"matplotlib.use",
"pandas.read_pickle",
"matplotlib.pyplot.rcParams.update",
"pandas.to_datetime",
"pandas.date_range",
"matplotlib.pyplot.subplots",
"matplotlib.pyplot.show"
]
] |
GuillaumeLeclerc/armory | [
"c24928701b4ff6fc37cdb994ea784f9733a8e8da"
] | [
"tests/test_docker/test_metrics.py"
] | [
"\"\"\"\nTest cases for ARMORY datasets.\n\"\"\"\n\nimport json\n\nimport pytest\nimport numpy as np\n\nfrom armory.utils import metrics\n\n\ndef test_categorical_accuracy():\n y = [0, 1, 2, 3, 4]\n y_pred = [0, 1, 2, 2, 3]\n assert metrics.categorical_accuracy(y, y_pred) == [1, 1, 1, 0, 0]\n assert met... | [
[
"numpy.array",
"numpy.zeros",
"numpy.ones",
"numpy.eye",
"numpy.log10"
]
] |
tyomj/linucrl | [
"8438330bdc20bacf5f985835c1d2e70aec6b00b8"
] | [
"lucrl/scripts/ml_to_df.py"
] | [
"import os\nimport numpy as np\nimport pandas as pd\nimport yaml\nfrom tqdm import tqdm\nfrom joblib import Parallel, delayed\n\nproject_dir = os.path.normpath(os.path.dirname(os.path.abspath(__file__)) + os.sep + os.pardir)\n\nfrom lucrl.utils.coordinator import Coordinator\ncrd = Coordinator(project_dir)\n\nfrom ... | [
[
"numpy.stack",
"pandas.concat"
]
] |
afonit/bokeh | [
"37a9d6c81ed592d07effd0d3584befd0fc95b53c"
] | [
"examples/reference/models/Ray.py"
] | [
"import numpy as np\n\nfrom bokeh.models import ColumnDataSource, DataRange1d, Plot, LinearAxis, Grid\nfrom bokeh.models.glyphs import Ray\nfrom bokeh.io import curdoc, show\n\nN = 9\nx = np.linspace(-2, 2, N)\ny = x**2\nl = x*5 + 25\n\nsource = ColumnDataSource(dict(x=x, y=y, l=l))\n\nxdr = DataRange1d()\nydr = Da... | [
[
"numpy.linspace"
]
] |
fred4li/NLP-theory-and-implementation | [
"84a484e4c5ff387f8ae626cc4a7e8d1db1aa621e"
] | [
"utils.py"
] | [
"import re\nimport string\nimport numpy as np\n\nfrom nltk.corpus import stopwords\nfrom nltk.stem import PorterStemmer\nfrom nltk.tokenize import TweetTokenizer\n\n\ndef process_tweet(tweet):\n \"\"\"Process tweet function.\n Input:\n tweet: a string containing a tweet\n Output:\n tweets_cle... | [
[
"numpy.squeeze",
"numpy.zeros"
]
] |
oricon/ciftify | [
"40eff619dd2ba047280cd19f24f5049f15597c7a"
] | [
"ciftify/bin/ciftify_seed_corr.py"
] | [
"#!/usr/bin/env python3\n\"\"\"\nProduces a correlation map of the mean time series within the seed with\nevery voxel in the functional file.\n\nUsage:\n ciftify_seed_corr [options] <func> <seed>\n\nArguments:\n <func> functional data (nifti or cifti)\n <seed> seed mask (nifti, cifti or g... | [
[
"numpy.zeros",
"numpy.where",
"numpy.std",
"numpy.loadtxt",
"numpy.arange",
"numpy.intersect1d",
"numpy.corrcoef"
]
] |
peisuke/RANSAC-Flow | [
"2dab6708e6d025d2ef086e134f2353c246427c2e"
] | [
"utils/outil.py"
] | [
"import torch.nn.functional as F\nimport PIL.Image as Image \nimport torch \nimport numpy as np\n\ndef resizeImg(I, strideNet, minSize = 400, mode=Image.LANCZOS) :\n\n w, h = I.size\n ## resize img, the largest dimension is maxSize\n wratio, hratio = w / minSize, h / minSize\n resizeRatio = min(wratio, ... | [
[
"numpy.array",
"torch.stack",
"torch.argmax",
"numpy.zeros",
"numpy.reshape",
"torch.any",
"numpy.ones",
"torch.transpose",
"torch.det",
"torch.randint",
"numpy.linalg.lstsq",
"numpy.linalg.svd",
"torch.nn.functional.pad",
"torch.mean",
"torch.sum"
]
] |
aapeebles/mod3_project | [
"5a6babf4b59d0ee303d38d88253613b089460e4d"
] | [
"data_cleaning.py"
] | [
"\"\"\"\nThis module is for your data cleaning.\nIt should be repeatable.\n\n## PRECLEANING\nThere should be a separate script recording how you transformed the json api calls into a dataframe and csv.\n\n## SUPPORT FUNCTIONS\nThere can be an unlimited amount of support functions.\nEach support function should have... | [
[
"pandas.read_csv"
]
] |
dahatake/Azure-Machine-Learning-sample | [
"4cb093dbffa403df638f6ae186479cc0ea932262"
] | [
"6.AutoML-Probability/scoring_file_v_1_0_0.py"
] | [
"# ---------------------------------------------------------\n# Copyright (c) Microsoft Corporation. All rights reserved.\n# ---------------------------------------------------------\nimport json\nimport logging\nimport os\nimport pickle\nimport numpy as np\nimport pandas as pd\nfrom sklearn.externals import joblib... | [
[
"sklearn.externals.joblib.load",
"pandas.DataFrame",
"numpy.array",
"pandas.Series"
]
] |
helloyide/Cross-stitch-Networks-for-Multi-task-Learning | [
"c07edb758aad7e0a2eb8da82e63105eae2ef77a4"
] | [
"gender_age_multi_task_learning.py"
] | [
"import pickle\nfrom datetime import datetime\n\nimport sys\nimport argparse\nimport numpy as np\nimport tensorflow as tf\nimport tensorflow.contrib as contrib\nfrom keras.utils import to_categorical\n\n\ndef load_data():\n with open(\"saved_data\", \"rb\") as file:\n # data is a list with length 2000\n ... | [
[
"tensorflow.nn.softmax_cross_entropy_with_logits",
"tensorflow.contrib.layers.fully_connected",
"tensorflow.matmul",
"tensorflow.reshape",
"numpy.mean",
"tensorflow.initializers.identity",
"tensorflow.contrib.layers.flatten",
"tensorflow.global_variables_initializer",
"tensorfl... |
schen496/auditory-hallucinations | [
"31b89df838a9f3c4558c7c3b69dbcd43c7f9de19"
] | [
"extract_image_features/old_code/video_extraction.py"
] | [
"from skimage import transform, color, io\nimport scipy.io as sio\nimport skvideo.io\nimport os\nimport numpy as np\nimport imageio\nimport matplotlib.pyplot as plt\nimport re\nfrom skimage import transform, color, io\nimport warnings\nfrom tqdm import tqdm\nimport h5py\nimport pickle\n\n### LOADING VIDEOS ###\nvid... | [
[
"numpy.max",
"numpy.array",
"scipy.io.loadmat"
]
] |
tanishq1g/Author_Style_Recognition | [
"f39016eeeef99245384c6ef345d9d6135c4bd2ea"
] | [
"for TAs/run.py"
] | [
"#for TAs\r\n# we have provided the test set as two CSVs, one is Xtest and other is Ytest.\r\n# to reproduce results, follow these steps\r\n#first extract the test files from the zip file and place them in this folder.\r\n\r\n#1. import all packages\r\n#2. load pickle file, Xtest and Ytest files\r\n#3. run the mode... | [
[
"pandas.read_csv",
"sklearn.metrics.accuracy_score"
]
] |
nachovazquez98/COVID-19_Paper | [
"6d7b398b8e6c3eeb0f76cabd0aeb077ff575e3a6"
] | [
"tpot/models/df_caso5_1_tpot_pipeline.py"
] | [
"import numpy as np\nimport pandas as pd\nfrom sklearn.model_selection import train_test_split\nfrom sklearn.naive_bayes import BernoulliNB\nfrom sklearn.pipeline import make_pipeline\nfrom sklearn.preprocessing import PolynomialFeatures\nfrom tpot.builtins import OneHotEncoder\n\n# NOTE: Make sure that the outcome... | [
[
"sklearn.model_selection.train_test_split",
"pandas.read_csv",
"sklearn.naive_bayes.BernoulliNB",
"sklearn.preprocessing.PolynomialFeatures"
]
] |
Jorjeous/NeMo | [
"cafc21ee6a0c7781fb08e9821c327b1ece1f83e3"
] | [
"nemo/core/classes/modelPT.py"
] | [
"# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved.\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n# http://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless re... | [
[
"torch.cuda.is_available",
"torch.load",
"torch.cuda.current_device"
]
] |
ThomasLittrell1/udacity_deeprl_course | [
"b247cf0128623bbb8264ef35a977a8e640a0ccdd"
] | [
"lab-taxi/monitor.py"
] | [
"from collections import deque\nimport sys\nimport math\nimport numpy as np\n\ndef interact(env, agent, num_episodes=20000, window=100):\n \"\"\" Monitor agent's performance.\n \n Params\n ======\n - env: instance of OpenAI Gym's Taxi-v1 environment\n - agent: instance of class Agent (see Agent.py... | [
[
"numpy.mean"
]
] |
OttoStruve/muler | [
"61d3e1676b1dbbe5616c303e6a64bc24d7519f4f"
] | [
"tests/test_igrins.py"
] | [
"# from astropy.nddata.ccddata import _uncertainty_unit_equivalent_to_parent\nimport astropy\nimport pytest\nimport time\nfrom muler.igrins import IGRINSSpectrum, IGRINSSpectrumList\nfrom specutils import Spectrum1D\n\n# from astropy.nddata.nduncertainty import StdDevUncertainty\nimport numpy as np\nimport glob\n\n... | [
[
"numpy.all",
"numpy.median",
"numpy.isclose",
"numpy.nanmedian"
]
] |
serge-sans-paille/scipy | [
"7df7d350fb3156d6e1554eec6997be8bb59cb052"
] | [
"scipy/signal/setup.py"
] | [
"from scipy._build_utils import numpy_nodepr_api\nimport os\n\n\ndef configuration(parent_package='', top_path=None):\n from numpy.distutils.misc_util import Configuration\n from scipy._build_utils.compiler_helper import set_c_flags_hook\n\n config = Configuration('signal', parent_package, top_path)\n\n ... | [
[
"numpy.distutils.misc_util.Configuration"
]
] |
jfrygeo/Read-Headers-CSV-python | [
"bf5a225bac1186c7d30ab233154f2c4f17c7b5ce"
] | [
"SampleData/Read-Headers-CSV-python_Split_Data.py"
] | [
"#Reads one line in a large csv file\n#Gives total count of lines csv\n# __author__ = 'john6807'\nimport csv,os, pandas\n\n#Input the filepath to your csv file: i.e. \"C:\\\\MyFolder\\\\MyCSV.csv\"\n#filename = \"C:\\\\MyFolder\\\\MyCSV.csv\"\n#filename = os.path.join(os.path.dirname(__file__)+\"\\SampleData\\TestC... | [
[
"pandas.read_csv"
]
] |
ky0on/keras-vis | [
"5987b56e0717aaba9989f5c8cb4f5b90c459ad52"
] | [
"vis/backend/tensorflow_backend.py"
] | [
"from __future__ import absolute_import\n\nimport os\nimport tempfile\nimport inspect\nimport numpy as np\nimport tensorflow as tf\n\nfrom ..utils import utils\nfrom tensorflow.python.framework import ops\nimport keras\nfrom keras.models import load_model\nfrom keras.layers import advanced_activations, Activation\n... | [
[
"tensorflow.set_random_seed",
"tensorflow.get_default_graph",
"numpy.random.seed",
"tensorflow.Session",
"tensorflow.RegisterGradient",
"tensorflow.GPUOptions",
"tensorflow.cast"
]
] |
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