text string |
|---|
<filename>AnalysisCurlDemo/testdemo.py
# coding: utf-8
import xlrd
import matplotlib.pyplot as plt
import numpy as np
from scipy.interpolate import spline
def readDataFromExcelFile(fileName, start, end):
workbook = xlrd.open_workbook(fileName)
sheetNames = workbook.sheet_names()
sheetName = sheetNames[0]
... |
# -*- coding: utf-8 -*-
"""Main module."""
### Libraries ###
import pandas as pd
from datetime import datetime
import croissance
from croissance import process_curve
from croissance.estimation.outliers import remove_outliers
import re
import os
import matplotlib.pyplot as plt
import matplotlib
import numpy as np
from... |
<filename>scripts/score_links4.py
#!/usr/bin/env python3
#
# Copyright 2015 Dovetail Genomics LLC
#
#
from __future__ import print_function
from builtins import str
from builtins import map
import sys
import networkx as nx
import chicago_edge_scores as ces
import numpy as np
from scipy.stats import poisson
import mat... |
import argparse
import json
import os
from typing import List
import nltk
import numpy as np
import pandas as pd
import spacy
from allennlp.data.tokenizers.word_splitter import SpacyWordSplitter
from scipy import sparse
from sklearn.feature_extraction.text import CountVectorizer
from spacy.tokenizer import Tokenizer
f... |
# This file is part of the pyMOR project (https://www.pymor.org).
# Copyright pyMOR developers and contributors. All rights reserved.
# License: BSD 2-Clause License (https://opensource.org/licenses/BSD-2-Clause)
import os
import tempfile
import numpy as np
import pytest
import scipy.io as spio
import scipy.sparse as... |
<filename>supervised_learning/test_attention.py<gh_stars>0
import argparse
# Data Loading
from tensorflow.python.keras import Model
from tensorflow.keras.backend import squeeze
from global_utils import read_sample
import numpy as np
import matplotlib.pyplot as plt
from supervised_learning.config import *
import rand... |
<filename>krysztalki/workDir/tests/test matrices/test_matrices_like_hex_m6_00z.py
import matrices_new_extended as mne
import numpy as np
import sympy as sp
from equality_check import Point
x, y, z = sp.symbols("x y z")
Point.base_point = np.array([x, y, z, 1])
class Test_Axis_hex_m6_00z:
def test_matrix_hex_m6_... |
<filename>basis_sparsity.py
import numpy as np
import spams
from scipy.spatial import distance
from scipy.stats import spearmanr, entropy
from union_of_transforms import double_sparse_nmf,smaf
import sys
THREADS = 5
MAX_BASIS = 1000
MIN_BASIS = 10
ERROR_THRESH = 0.005
MIN_FIT = 0.90
if __name__ == "__main__":
inpath... |
<filename>rating.py
#!/usr/bin/env python3
# This library is free software; you can redistribute it and/or
# modify it under the terms of the GNU Lesser General Public
# License as published by the Free Software Foundation; either
# version 2.1 of the License, or (at your option) any later version.
#
# This library is... |
<reponame>callumparr/TALON-paper-2020<gh_stars>1-10
import pandas as pd
import scipy.stats as stats
import argparse
def get_args():
parser = argparse.ArgumentParser()
parser.add_argument('-sim_files', dest='sim_files',
help='Comma-separated list of simulated fasta header files')
parser.add_argument('-sim_name', d... |
<filename>paperII/abundace_evolution.py
from galaxy_analysis.plot.plot_styles import *
import numpy as np
import matplotlib.pyplot as plt
import deepdish as dd
import h5py, glob, sys
from galaxy_analysis.utilities import utilities
from galaxy_analysis.analysis import Galaxy
from mpl_toolkits.axes_grid1 import make_a... |
from collections import namedtuple
import cv2
import numpy as np
import pandas as pd
from collections import defaultdict
import math
from scipy import ndimage
from torch.utils.data import Dataset
import skimage.color
import skimage.io
from tqdm import tqdm
import utils
import glob
import pickle
import enum
import s... |
<gh_stars>10-100
# Copyright (c) Microsoft Corporation
# Copyright (c) <NAME> Laboratory
# All rights reserved.
#
# MIT License
#
# Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated
# documentation files (the "Software"), to deal in the Software without restric... |
import numpy as np
from numpy.testing import run_module_suite
from skimage import filter, data, color
from skimage import img_as_uint, img_as_ubyte
class TestTvDenoise():
def test_tv_denoise_2d(self):
"""
Apply the TV denoising algorithm on the lena image provided
by scipy
"""
... |
<gh_stars>10-100
import unittest
import tempfile
import shutil
from unittest import mock
import numpy as np
import scipy.stats
import torch
from torch.utils.data import Subset
import model
import dataset
import trainer
class TestTrainer(unittest.TestCase):
def setUp(self):
seed = 42
torch.manual... |
<gh_stars>0
from estimation import least_squares as least_squares_estimation
from estimation import weighted_least_squares as weighted_least_squares_estimation
from registration import apply_tensor_trf
from scalars import (
axial_diffusivity, fractional_anisotropy, mean_diffusivity,
radial_diffusivity)
from st... |
<gh_stars>0
from __future__ import division
import torch
from torch import nn
import torch.nn.functional as F
from tool.torch_utils import *
from tool.yolo_layer import YoloLayer
from tool.utils import load_class_names, plot_boxes_cv2
from tool.torch_utils import do_detect
import pathlib
from fnmatch import fnmatch
imp... |
<reponame>lime-lang/lime<gh_stars>1-10
from error import RuntimeError
import fractions
class AST:
pass
class BinaryOperation(AST):
def __init__(self, left, operation, right):
self.left = left
self.token = operation
self.operation = operation
self.right = right
class Equalit... |
from numpy import *
from scipy.constants import c
import scipy.stats as stats
from numpy.linalg import lstsq, norm
from matplotlib.pyplot import *
from matplotlib.mlab import find
from least_squares_linear import *
from least_squares_non_linear import *
#Assignment 09,2 as a test (GPS)
def gn(x, F, J, tol=1e-6, maxi... |
from types import ModuleType
from scipy.sparse import csr_matrix, csc_matrix
import numpy as np
from scanpy._utils import descend_classes_and_funcs, check_nonnegative_integers
from anndata.tests.helpers import assert_equal, asarray
import pytest
def test_descend_classes_and_funcs():
# create module hierarchy
... |
# Original filename: dewarp.py
#
# Author: <NAME>
# Email: <EMAIL>
# Date: March 2011
#
# Summary: Dewarp, recenter, and rotate an image.
#
import re
import pyfits as pyf
import scipy.ndimage
import time
import warnings
def distortion_interp_flux(flux, y, x):
flux[:, :] = scipy.ndimage.map_coordinates(flux,... |
<filename>python/sklearn/sklearn/neighbors/classification.py
"""Nearest Neighbor Classification"""
# Authors: <NAME> <<EMAIL>>
# <NAME> <<EMAIL>>
# <NAME> <<EMAIL>>
# Sparseness support by <NAME> <<EMAIL>>
#
# License: BSD, (C) INRIA, University of Amsterdam
import numpy as np
from scipy im... |
# -*- coding: utf-8 -*-
from scipy.spatial.distance import cdist
from torchvision import transforms
from market1501 import Market1501
from __init__ import DEVICE, cmc, mean_ap, creat_test_data_set_loader
from pyrmaid import Pyramid, load_ckpt
import os
import torch
from torch import nn, optim
import numpy as np
import ... |
"""
This program provides various functions to correct data or to to process data.
All of these functions have been translated from the 'Data Proccessing' section of the manual. Many values are interpretations and are bound to be incorrrect.
Please read through the manual to modify these functions based on your needs.... |
import pandas as pd
import numpy as np
import datetime as dt
import dateutil
from retention import utils
import logging
from scipy import stats
from scipy.optimize import minimize
from scipy.special import beta
logger = logging.getLogger(__name__)
class ShiftedBetaGeom():
""" Implementation of shifted-beta-geomet... |
<gh_stars>1-10
import gpflow
from gpflow import Parameter
import tensorflow as tf
import scipy
from scipy import sparse
import networkx as nx
from . import utils
from . import kernels
def get_adj_matrix(graph):
element = list(graph.nodes())[0]
if nx.is_weighted(graph):
return sparse.csr_matrix(nx.l... |
import numpy as np
from tqdm import tqdm
import scipy.io as sio
import os
import pkg_resources
# cosmology assumption
from astropy.cosmology import FlatLambdaCDM
cosmo = FlatLambdaCDM(H0=70, Om0=0.3)
from .priors import *
from .gp_sfh import *
import fsps
mocksp = fsps.StellarPopulation(compute_vega_mags=False, zcon... |
<filename>evaluation/niqe.py
from __future__ import division
"""
Video Quality Metrics
Copyright (c) 2015 <NAME> <<EMAIL>>
This program is free software: you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation, either version 3 of the Lic... |
import pdb
import numpy as np
from collections import defaultdict
#from sklearn.cross_validation import KFold
from sklearn.model_selection import KFold
from sklearn.metrics import precision_recall_curve, roc_curve, accuracy_score
from sklearn.metrics import auc
from scipy import sparse
import scipy.io as sio
... |
# -*- coding: utf-8 -*-
"""
pytest
@author: chris
Test values against references.
"""
import os
import sys
import pytest
import numpy as np
from numpy.testing import assert_allclose
from scipy.io import loadmat
import spaudiopy as spa
current_file_dir = os.path.dirname(__file__)
sys.path.insert(0, os.path.abspath(... |
# LVDSim.py
""" A suite of tools for running LotkaVolterraSND simulations."""
# from LotkaVolterraND import LotkaVolterraND
from eugene.src.virtual_sys.LotkaVolterraND import LotkaVolterraND
from eugene.src.virtual_sys.LotkaVolterraSND import LotkaVolterraSND
from eugene.src.virtual_sys.LotkaVolterra2OND import Lotka... |
import numpy as np
from numba import jit
import math
from turbofats.Base import Base
from scipy.optimize import minimize, minimize_scalar
@jit(nopython=True)
def iar_phi_kalman_numba(x, t, y, yerr, standarized):
n = len(y)
Sighat = np.float(1.0)
if not standarized:
Sighat = np.var(y) * Sighat
... |
import numpy as np
from math import cos, sin, pi
import math
import cv2
from scipy.spatial import Delaunay
def softmax(x):
x -= np.max(x,axis=1, keepdims=True)
a = np.exp(x)
b = np.sum(np.exp(x), axis=1, keepdims=True)
return a/b
def draw_axis(img, yaw, pitch, roll, tdx=None, tdy=None, size = 100):
... |
<reponame>YasmeenVH/growspace
mport gym
import numpy as np
from scipy.spatial import distance
import os
import cv2
#env = gym.make("GrowSpaceEnv-Images-v0")
from itertools import chain
from scripts.save_img_movie import save_file_movie_oracle, filter, natural_keys
#from growspace.envs.growspaceenv import GrowSpaceEnv
... |
<gh_stars>0
import math
import numpy as np
import scipy.misc
import PIL.Image
import sys
import csv
import matplotlib as mpl
mpl.use('WebAgg')
import matplotlib.pyplot as plt
import matplotlib.axes as pltax
# from functools import reduce
# plt.ion()
# plt.close('all')
# plt.show()
N = int(sys.argv[1])
amin = (float('... |
<gh_stars>1-10
from libs.effects.effect import Effect # pylint: disable=E0611, E0401
from scipy.ndimage.filters import gaussian_filter1d
import numpy as np
import random
class EffectTwinkle(Effect):
def __init__(self, device):
# Call the constructor of the base class.
super().__init__(device)
... |
<filename>becpy/physics/hartree_fock.py<gh_stars>0
#!/usr/bin/env python
# -*- coding: utf-8 -*-
#
# Create: 12-2018 - <NAME> <carmelo> <<EMAIL>>
"""Module docstring
"""
import matplotlib.pyplot as plt
import sys
import numpy as np
from uncertainties import unumpy as unp
from scipy.integrate import cumtrapz, quad
fro... |
<reponame>TahaEntezari/ramstk
# pylint: skip-file
# type: ignore
# -*- coding: utf-8 -*-
#
# tests.analyses.statistics.exponential_unit_test.py is part of The RAMSTK Project
#
# All rights reserved.
# Copyright since 2007 Doyle "weibullguy" Rowland doyle.rowland <AT> reliaqual <DOT> com
"""Test class for the Expo... |
<filename>src/aleatoire/io.py<gh_stars>0
import json
import numpy as np
import scipy.stats
import scipy.special
from scipy.special import gamma as gamma_func
def _weibull_mean(shape,scale):
r"""
\mathrm{E}(X)=\lambda \Gamma\left(1+\frac{1}{k}\right)
"""
return scale*gamma_func(1+1/shape)
def _weibull_... |
<gh_stars>0
import os
import subprocess
import warnings
from datetime import datetime
from functools import partial
import numpy as np
import pop_tools
import scipy.sparse as sps
import xarray as xr
regrid_dir = f"{os.environ['TMPDIR']}/regridding"
os.makedirs(regrid_dir, exist_ok=True)
class grid(object):
"""g... |
<reponame>EgorOrachyov/MachineLearning
import numpy as np
import scipy.sparse as ss
a = np.zeros((5,1))
b = np.zeros((5,2))
print(a.transpose().dot(b))
print(a.transpose() + 1)
a[1][0] = 10
b[1][0] = 2
b[1][1] = 4
aa = ss.csc_matrix(a)
bb = ss.csc_matrix(b)
cc = aa.multiply(bb)
print(np.asarray([[1,1]]))
print(b ... |
# -*- coding: utf-8 -*-
# Copyright 2021 Huawei Technologies Co., Ltd
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by app... |
<reponame>hvanwyk/atomic_data_uncertainties
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Wed Apr 21 11:09:08 2021
@author: loch
"""
import numpy as np
import sys
import matplotlib.pyplot as plt
import emcee
import corner
import scipy.stats as stats
import math
from recombination_methods import State... |
<reponame>iTitus/factorio_balancers
import random
from fractions import Fraction
from factorio_balancers.graph import Splitter, Belt
from factorio_balancers import Balancer
from tests.test_blueprint import TestBase
def random_priority(allow_off=False):
choices = [Splitter.Priority.left.value, Splitter.Priority.... |
<filename>ion_functions/data/prs_functions.py
#!/usr/bin/env python
"""
@package ion_functions.data.prs_functions
@file ion_functions/data/prs_functions.py
@author <NAME>, <NAME>
@brief Module containing calculations related to instruments in the Seafloor
Pressure family.
"""
import pkg_resources
import numexpr as ... |
<reponame>Avanish14/smartModem<filename>sciKitScript.py
import scipy, pickle
import numpy as np
from scipy import stats
from scipy import signal
import pytest
pytest.importorskip('sklearn')
from sklearn import svm
def setup(fileName):
Xd = pickle.load(open(fileName, 'rb'))
snrs, mods = map(lambda j: sorted(list(set(... |
# SPDX-FileCopyrightText: Copyright 2021, <NAME> <<EMAIL>>
# SPDX-License-Identifier: BSD-3-Clause
# SPDX-FileType: SOURCE
#
# This program is free software: you can redistribute it and/or modify it
# under the terms of the license found in the LICENSE.txt file in the root
# directory of this source tree.
# =======
#... |
# Copyright 2017 <NAME> All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agree... |
from os.path import join, isdir, exists
from os import listdir, mkdir
from shutil import rmtree
import gc
from copy import deepcopy
import pandas as pd
import numpy as np
from scipy.ndimage import binary_erosion
import matplotlib.pyplot as plt
from matplotlib.path import Path
from collections import Counter
from ..vis... |
#!/usr/bin/env python3
import argparse
import h5py
import pandas as pd
import numpy as np
from ogb.graphproppred import DglGraphPropPredDataset
#from ogb.graphproppred.mol_encoder import AtomEncoder, BondEncoder
from scipy import sparse as sp
from rdkit.Chem import MolFromSmiles
def read_smiles():
smiles = pd.read_... |
<filename>algorithms/HC/hc.py
import gym
import sys
sys.path.insert(0, '../../benchmarking')
from model_tester import TesterAgent
import numpy as np
import scipy.ndimage as snd
from PIL import Image
def rgb_to_gray(img):
return img[:, :, 0] * 0.299 + img[:, :, 1] * 0.587 + img[:, :, 2] * 0.114
def detect_edge(img... |
from bs4 import BeautifulSoup
import re
from os import listdir
from os.path import isfile, join
import numpy as np
from scipy.optimize import curve_fit
# Initialise some arrays for analyses later
exam_difficulties = []
master_questions_arr = []
# Allow user to choose which folder to ultimately extract conv... |
<reponame>Anirban166/tstl<gh_stars>10-100
import sys
import sut
import random
import inspect
import time
import scipy
def traceLOC(frame,event,arg):
global lastLOCs,lastFuncs,verbose
if event != "call":
return traceLOC
co = frame.f_code
n = co.co_name
if (n, co.co_filename) in lastFuncs:
... |
<filename>src/forward_term.py
#!/usr/bin/env python
import numpy as np
import pandas as pd
import scipy.stats
from scipy.linalg import cholesky
from scipy.linalg import sqrtm
from pars import Inp_Pars
from fit_simpars import Fit_Simpars
from forward_rates import Forward_Rates
class Forward_Term(object):
"""
... |
<gh_stars>1-10
import os
import numpy as np
import scipy
from data_structures import *
if 'jobfile.py' in os.listdir():
from jobfile import *
from read_vec_file import *
import yaml
def check_str_bool(s):
return s in ['True' ,'true', '1', 't', 'y','YES' ,'Yes','yes', 'yeah','Yeah', 'yup', 'certainly', 'uh-huh... |
#!/usr/bin/env python
# coding: utf-8
import argparse
parser = argparse.ArgumentParser('Vox2Vox training and validation script', add_help=False)
## training parameters
parser.add_argument('-g', '--gpu', default=0, type=int, help='GPU position')
parser.add_argument('-nc', '--num_classes', default=4, type=int, help='n... |
from collections import defaultdict
import math
import numpy
import re
from scipy.stats import norm
from scipy.optimize import curve_fit
from fitting import gaussian
from wrappers import samtools
def calculate_bias_distribution(_iter, ref_fn, output):
'''
For an iterable, create a histogram of s... |
<reponame>DLarisa/FMI-Materials-BachelorDegree<filename>Calcul Numeric (CN)/Teme/Tema 4/ex 1 + 2.py
import numpy as np
import sympy as sym
from math import e
def f1(x):
return e ** x
def CuadraturaNewton(func, a, b,):
"""
Calculeaza Formula de cuadratura Newton pentru o diviziune de n = 3 sub... |
import cv2
import scipy.io as sio
import os
from centerface import CenterFace
# 顔認識器の設定
landmarks = True
centerface = CenterFace(landmarks=landmarks)
# 編集ファイルを開く
path_r = '/home/babaamata/workspace/Cat-faces-dataset/dataset-part3/'
# カウント変数
image_count = 0
face_count = 0
files = os.listdir(path_r)
for file in files... |
import math
import numpy as np
import matplotlib.pyplot as plt
from scipy.optimize import minimize
from scipy.stats import norm
from scipy.special import comb
def process_data(D,M_os):
'''
Function to generate the data in the format convenient for optimization procedure
'''
# Number of elemnts
... |
<reponame>chbrown/topic-sentiment-authorship<filename>tsa/science/numpy_ext.py
import time
import scipy
import numpy as np
def _type_raise(prototype_array, force_dtype=None):
'''
For integer inputs, the default is float64;
for floating point inputs, it is the same as the input dtype.
'''
if force_... |
<reponame>mdd423/wobble_jax<filename>jabble/plottings.py
import numpy as np
import matplotlib; #matplotlib.use("Agg")
import matplotlib.pyplot as plt
import astropy.table as at
import jax.numpy as jnp
import pickle
import model as wobble_model
import dataset as wobble_data
import scipy.constants as const
import... |
<reponame>JulianPL/Non-Rectangular_Convolution
#!/usr/bin/python3
from fractions import Fraction
import unittest
import nrconv
import sympy
class TestEdgeCase(unittest.TestCase):
def test_non_rectangular_convolution_edge_diagonal1(self):
list1 = [1, 1, 1, 1, 1, 1, 1, 1]
list2 = [1, 1, 1, 1, 1,... |
import logging
import warnings
import numpy as np
from scipy.sparse.linalg import lsqr
from scipy.signal import filtfilt
from pylops import Diagonal, Identity, Transpose
from pylops.signalprocessing import FFT, Fredholm1
from pylops.utils import dottest as Dottest
from pylops.optimization.solver import cgls
from pylo... |
import numpy as np
from scipy.optimize import fminbound
from scipy.special import expit
from girth.utilities import (validate_estimation_options,
get_true_false_counts, create_beta_LUT, INVALID_RESPONSE)
from girth.utilities.utils import _get_quadrature_points
from girth.unidimensional.dichotomous.partial_inte... |
#Multivariate kernel density estimate using a normal kernel
import numpy as np
from scipy.linalg import expm
#KDE multivariate
def p_mkde_M(x,X,h):
X = np.asmatrix(X)
x = np.asmatrix(x)
N,d = X.shape
X = X.T
x = x.T
Sxy = np.cov(X)
invS = np.linalg.inv(Sxy)
detS... |
<filename>multi_agents/metrics/plot_data.py
import json
import os
import statistics
import numpy as np
import scipy.stats as st
import plotly.graph_objects as go
from multi_agents import config
BASE_DIR = "/home/matias/Desktop/HFO/matias_hfo/models/4vs5/metrics/tese"
RESULT_FILE_PATH = os.path.join(BASE_DIR, "{teamm... |
<gh_stars>0
#!/usr/bin/env python
# coding: utf-8
# <center>
# <h1><b>Lab 3</b></h1>
# <h1>PHYS 580 - Computational Physics</h1>
# <h2>Prof<NAME></h2>
# </br>
# <h3><b><NAME></b></h3>
# <h4>https://www.github.com/ethank5149</h4>
# <h4><EMAIL></h4>
# </br>
# </br>
# <h3><b>September 17, 2020</b></h3>
# </center>
# ###... |
<filename>ihna/kozhukhov/imageanalysis/gui/mapfilterdlg/basicwindow.py<gh_stars>0
# -*- coding: utf-8
import numpy as np
from scipy.stats import linregress
import wx
from ihna.kozhukhov.imageanalysis.tracereading import TraceReader
from ihna.kozhukhov.imageanalysis.accumulators import MapFilter
from ihna.kozhukhov.ima... |
#!/usr/bin/env python
# -*- coding: utf-8 -*-
"""
This file is part of series of experiments trying to reproduce the results in quantum chemistry
using quantum computing. Contributions, corrections and clarifications welcome!
Author : <NAME>
Copyright : Copyright 2019 - <NAME>
License : MIT
Ver... |
"""
"""
import sys, os, argparse, logging,random
sys.path.insert(0, os.path.abspath(os.path.join(os.path.dirname(__file__), '..')))
from utils.io_parameters import read_and_set_parameters
from utils.io_trajectories import read_and_filter
from utils.io_trajectories import partition_train_test
from utils.manip_trajectori... |
<gh_stars>1-10
from __future__ import division
from __future__ import print_function
import argparse
import time
import numpy as np
import scipy.sparse as sp
import torch
from torch import optim
import warnings
import os
from model import GCNModelVAE
from optimizer import loss_function
from utils impo... |
# Copyright (c) <NAME>.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory.
# The gbea TopTrump benchmark is a carefully designed real world benchmark.
# Both its single objective and multi-objective fitness functions reflect the requirements of
# a real world To... |
## Imports
import numpy as np
import statsmodels
import seaborn as sns
from matplotlib import pyplot as plt
import pandas as pd
import pystan
from sklearn.kernel_ridge import KernelRidge
import os
import xlrd
os.chdir('C:\\Users\\lakshd5\\Dropbox\\Heteroscedasticity\\Final Data')
import statsmodels
import r... |
<reponame>siboles/pyCellAnalyst
from __future__ import print_function
from __future__ import division
from builtins import zip
from builtins import map
from builtins import str
from builtins import range
from past.utils import old_div
import febio
import pickle
import subprocess
import os
import tkinter.filedialog
impo... |
<filename>pydy/viz/camera.py
from sympy.matrices.expressions import Identity
from .visualization_frame import VisualizationFrame
__all__ = ['PerspectiveCamera', 'OrthoGraphicCamera']
class PerspectiveCamera(VisualizationFrame):
"""
Creates a Perspective Camera for visualization.
The camera is inherited f... |
# Copyright (c) 2020 <NAME>
import os
os.environ["CUDA_DEVICE_ORDER"]="PCI_BUS_ID"
import sparsechem as sc
import scipy.io
import scipy.sparse
import numpy as np
import pandas as pd
import torch
import argparse
import os
import sys
import os.path
import time
import json
import functools
import csv
#from apex import amp... |
<reponame>johnbachman/bayessb
from texttable import Texttable
import TableFactory as tf
from inspect import ismodule
from bayessb.multichain import MCMCSet
import cPickle
import inspect
import scipy.cluster.hierarchy
from matplotlib import pyplot as plt
from matplotlib import cm
from matplotlib.figure import Figure
fro... |
import os
import pandas as pd
import anndata as ad
import scipy.sparse
import numpy as np
def load(data_dir, sample_fn, **kwargs):
fn = [
os.path.join(data_dir, f"GSE114374_Human_{sample_fn}_expression_matrix.txt.gz"),
os.path.join(data_dir, f"{sample_fn.lower()}_meta_data_stromal_with_donor.txt")... |
"""
Numerical integration of the SIR disease model
"""
import numpy as np
import matplotlib.pyplot as plt
from scipy.integrate import odeint
# right hand side of the equation
def compute_SIR_rhs(y, t, N, beta, gamma):
S, I, R = y
dSdt = - beta * I * S / N # number of uninfected people
dIdt = beta * I * S ... |
<filename>gpflux/architectures/constant_input_dim_deep_gp.py
#
# Copyright (c) 2021 The GPflux Contributors.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/lice... |
#!/usr/bin/env python
# encoding: utf-8
from __future__ import division, print_function
from collections import defaultdict
import numpy as np
import pandas as pd
from sympy.parsing.mathematica import mathematica
try:
from tqdm import tqdm
except ImportError:
tqdm = lambda iterator: iterator
def parse_ct... |
<gh_stars>1-10
import cv2
import numpy as np
import pylab
from keras.models import Sequential
from keras.layers import Dense
from keras.models import model_from_json
import skimage
from skimage import io
import matplotlib.pyplot as plt
from skimage import transform
from skimage.morphology import skeletonize_3d
import ... |
<gh_stars>0
#!/usr/bin/env python
__author__ = "<NAME>"
__copyright__ = "Copyright 2014, The Materials Project"
__version__ = "1.0"
__maintainer__ = "<NAME>"
__email__ = "<EMAIL>"
__status__ = "Development"
__date__ = "Aug 22, 2016"
import os
import csv
from math import log
import numpy as np
from scipy import integ... |
<filename>predictor.py<gh_stars>1-10
"""CNN for predicting activity of a guide sequence: classification and
regression.
"""
import argparse
from collections import defaultdict
import gzip
import os
import pickle
import fnn
import parse_data
import numpy as np
import scipy
import sklearn
import sklearn.metrics
import... |
import pandas as pd
import matplotlib.pyplot as plt
import numpy as np
import random as r
from sklearn.model_selection import train_test_split
from sklearn.svm import SVR
from sklearn.model_selection import KFold
from sklearn.decomposition import PCA
import csv
from sklearn.metrics import mean_squared_error, m... |
from copy import deepcopy
from keras import Sequential, activations, initializers, regularizers, constraints
from keras.engine import Layer
from keras.layers import Dense, Conv2D, Flatten
from keras.datasets import mnist
import numpy as np
import tensorflow as tf
import keras
from scipy.linalg import block_diag
from s... |
import os
import numpy as np
import tensorflow as tf
import shutil, sys
from datetime import datetime
import h5py
from xsleepnet import XSleepNet
from xsleepnet_config import Config
from sklearn.metrics import f1_score
from sklearn.metrics import accuracy_score
from sklearn.metrics import cohen_kappa_score
from dat... |
<reponame>chriskirchner/RoboND-Kinematics
from sympy import *
from time import time
from mpmath import radians
import tf
'''
Format of test case is [ [[EE position],[EE orientation as quaternions]],[WC location],[joint angles]]
You can generate additional test cases by setting up your kuka project and running `$ rosla... |
<reponame>BYUCamachoLab/autogator
# -*- coding: utf-8 -*-
#
# Copyright © Autogator Project Contributors
# Licensed under the terms of the MIT License
# (see autogator/__init__.py for details)
import os
os.environ['PATH'] = "C:\\Program Files\\ThorLabs\\Kinesis" + ";" + os.environ['PATH']
import atexit
import math
fr... |
<gh_stars>1-10
#Python program for continuous and discrete sine wave plot
import numpy as np
import scipy as sy
from matplotlib import pyplot as plt
t = np.arange(0,1,0.01)
#frequency = 2 Hz
f = 2
#Amplitude of sine wave = 1
PI = 22/7
a = np.sin(2*PI*2*t)
#Plot a continuous sine wave
fig, axs = plt.subplot... |
<filename>inpainting/model/coords6d.py
import numpy as np
import scipy
import scipy.spatial
# calculate dihedral angles defined by 4 sets of points
def get_dihedrals(a, b, c, d):
b0 = -1.0*(b - a)
b1 = c - b
b2 = d - c
b1 /= np.linalg.norm(b1, axis=-1)[:,None]
v = b0 - np.sum(b0*b1, axis=-1)[:,N... |
from utils.audio_feature_cluster import *
import pandas as pd
import numpy as np
from tqdm import tqdm
import scipy.sparse as sp
from utils.definitions import ROOT_DIR
from utils.datareader import Datareader
"""
This file is used to generate the hybrid icm for cat8 and cat10.
"""
import sys
arg = sys.argv[1:]
#arg ... |
# Copyright 2021 Huawei Technologies Co., Ltd
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to... |
import pydicom #for loading dicom
import SimpleITK as sitk #for loading mhd/raw
import os
import numpy as np
import scipy.ndimage
#DICOM: send path to any *.dcm file where containing dir has the other slices (dcm files), or path to the dir itself
#MHD/RAW: send path to the *.mhd file where containing die has the coori... |
"""Cosmological merger rates of gravitational-wave sources and detection rates.
Usage:
See results_class.py and plot_collated_detection_rate.py for how the detection rates and calculated and the plots are created.
License:
BSD 3-Clause License
Copyright (c) 2022, <NAME>.
All rights reserved except fo... |
"""Refactor file directories, save/rename images and partition the
train/val/test set, in order to support the unified dataset interface.
"""
from __future__ import print_function
import sys
sys.path.insert(0, '.')
from zipfile import ZipFile
import os.path as osp
import sys
import h5py
from scipy.misc import imsav... |
"""
imsize map_coordinates fourier_shift
50 0.016211 0.00944495
84 0.0397182 0.0161059
118 0.077543 0.0443089
153 0.132948 0.058187
187 0.191808 0.0953341
221 0.276543 0.... |
# init
#
from scipy import io as sio
import matplotlib
import numpy as np
import os,sys
import matplotlib.pyplot as plt
from scipy import io as sio
import h5py
from PIL import Image
# load data
# data = sio.loadmat('/home/enhaog/GANCS/srez/dataset_MRI/image_phantom_array.mat')
filename='/home/enhaog/GANCS/srez/dataset_... |
import sys
import numpy as np
import SimpleITK as sitk
from skimage import filters, measure
from scipy.stats import truncnorm, uniform
import random
from math import pi
from .utils import get_study_uid, one_hot_encode
class Compose(object):
def __init__(self, transformers):
self.transformers = transform... |
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