text string |
|---|
import os
import torch
import numpy as np
import scipy.ndimage as nd
from embryovision.util import (
load_and_crop_image,
augment_focus,
sort_azimuthally)
from embryovision.localfolders import embryovision_folder
from embryovision.predictor import Predictor, load_maskrcnn
from embryovision.managedata impo... |
<gh_stars>1-10
#!/usr/bin/env python3
from argparse import ArgumentParser
import os
os.environ['TF_CPP_MIN_LOG_LEVEL'] = '3'
parser = ArgumentParser()
parser.add_argument("mode")
parser.add_argument("image_path")
parser.add_argument("stats_path")
parser.add_argument("model_path")
parser.add_argument("output_file")
p... |
''' Header reading functions for SPM version of analyze format '''
import warnings
import numpy as np
from nifti.volumeutils import HeaderDataError, HeaderTypeError, \
allopen
from nifti import filetuples # module import
from nifti.batteryrunners import Report
from nifti import analyze # module import
''' Suppor... |
import os
import h5py
import matplotlib.pyplot as plt
from pathlib import Path
from time import time, strftime
import pandas as pd
import numpy as np
import scipy.ndimage as ndi
import argparse
from rabbitccs.data.utilities import load, save, print_orthogonal
from rabbitccs.inference.thickness_analysis import _local_... |
<reponame>yjzhang2013/pancanatlas_code_public<filename>alt_splice/outliers/sf_utils.py
import os
import sys
import h5py
import numpy as np
import scipy as sp
import pandas as pd
def run_preproc_tests(psi, psi_is_fin=None):
'''Prints a table showing how many rows/cols left at each thold.
'''
if psi_is_fin i... |
<gh_stars>1-10
import os
import pickle
import scipy.stats as stats
import MixtureOfExperts
from MixtureOfExperts.utils import simulate_data as sd
import matplotlib.pyplot as plt
import numpy as np
import logging
def true_density(xbins, ybins, mu1, mu2, tau1, tau2, coef1, coef2, factor1, factor2, noise):
"""
Ge... |
<reponame>maierbn/opendihu
#! /usr/bin/python3
# Plot the fiber to MU assignment that is given in a file, e.g. MU_fibre_distribution_37x37_10.txt
# usage: ./plot_fiber_distribution <filename>
#
import sys
import random
import time
import numpy as np
import scipy
import scipy.integrate
import scipy.signal
import matplo... |
<reponame>deepankur797/random
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
#%matplotlib inline
plt.rcParams['figure.figsize'] = (10.0, 8.0)
import seaborn as sns
from scipy import stats
from scipy.stats import norm
train = pd.read_csv("D:\\cygwin\\COLLEGE STUFF(A)\\8th sem\\major 2\\... |
<gh_stars>1-10
# !/usr/bin/env python
# -*- coding:utf-8 _*-
# @Author: swang
# @Contact: <EMAIL>
# @Project Name: keyword_spotting_system
# @File: test.py
# @Time: 2021/11/11/21:51
# @Software: PyCharm
import os, sys
CRT_DIR = os.path.dirname(os.path.abspath(__file__))
sys.path.append(CRT_DIR)
# print('sys.path:', sy... |
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import seaborn as sns
from scipy.sparse import csr_matrix, hstack
from sklearn import decomposition
from sklearn.preprocessing import StandardScaler
from sklearn.feature_extraction.text import TfidfVectorizer
from sklearn.model_selection import Str... |
# Copyright 1999-2018 Alibaba Group Holding 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 a... |
<filename>pymixconsole/processors/convreverb.py
FFT_TYPE = "scipy"
import os
import pathlib
import warnings
import numpy as np
import scipy.signal
from scipy.io import wavfile
from ..parameter import Parameter
from ..processor import Processor
from ..parameter_list import ParameterList
if FFT_TYPE == "scipy":
f... |
import matplotlib
#matplotlib.use("agg")
#matplotlib.use("tkagg")
import matplotlib.pyplot as plt
import matplotlib.gridspec as gridspec
import importlib as imp
import numpy as np
import os
from scipy import ndimage
import torch
import torch.nn as nn
import torch.nn.functional as F
import torch.autograd as autograd
i... |
# -*- coding: utf-8 -*-
import os
import time
from datetime import datetime
import logging
from scipy.sparse import lil_matrix
from sklearn.model_selection import train_test_split
from sklearn.ensemble import RandomForestRegressor
from sklearn.linear_model import LinearRegression
from sklearn.metrics import mean_squar... |
'''
Copyright (c) 2018 <NAME>, Rutgers University
http://www.cs.rutgers.edu/~hxp1/
This code is free to use for academic/research purpose.
'''
import numpy as np
import cntk as C
import cv2
from scipy.signal import medfilt
import time
import ShapeUtils2 as SU
from SysUtils import make_dir, get_items, get_current_ti... |
<gh_stars>1-10
#Import required packages
from pycc.rt.utils import FWHM
from scipy.fft import fft
import numpy as np
import pytest
def test_FWHM():
#Define function
np.random.seed(10)
timestep = 0.001
t = np.arange(0, 1, timestep)
f = np.cos(2*np.pi*12*t) + np.sin(2*np.pi*50*t)
f = f + np.rando... |
"""Evaluation metrics."""
import numpy as np
import pdb
import time
import warnings
import os
import re
import copy
import itertools
from dcCustom.metrics.cindex_measure import cindex
from multiprocessing import Pool
from time import gmtime, strftime
from deepchem.utils.save import log
from sklearn.metrics import roc_... |
from glob import glob
from math import exp
from os import path
from typing import List, Dict
import cv2
import numpy as np
import skimage.measure
from scipy.optimize import linear_sum_assignment
detection = ''
ground_truth = ''
def get_region_props(image: np.ndarray) -> List[skimage.measure._regionprops._RegionProp... |
<reponame>BUAA-BDA/FedShapley<gh_stars>10-100
from __future__ import absolute_import, division, print_function
import tensorflow_federated as tff
import tensorflow.compat.v1 as tf
import numpy as np
import time
from scipy.special import comb, perm
import os
# tf.compat.v1.enable_v2_behavior()
# tf.compat.v1... |
<filename>summary_consumer.py<gh_stars>0
from kafka import KafkaConsumer
from json import loads
from sqlalchemy import create_engine
import statistics
if __name__ == "__main__":
engine = create_engine('sqlite:///bank.db', echo = True)
db = engine.connect()
consumer = KafkaConsumer('transactions',
... |
<gh_stars>0
#! /usr/bin/env python
from math import sqrt
from sympy import sieve
import time
def count_squarefree(N):
'''Return the number of squarefree integers below N.'''
mobius = [1] * int(sqrt(N))
for p in sieve.primerange(2, int(sqrt(N))):
for i in xrange(p, int(sqrt(N)), p):
mobius[i-1] = -mob... |
<gh_stars>0
import requests
from scipy.io import wavfile
from scipy import signal
import numpy as np
import matplotlib.pyplot as plt
# fileName = "1-103995-A-30.wav"
fileName = "1-100038-A-14.wav"
response = requests.get(f"https://github.com/karolpiczak/ESC-50/raw/master/audio/{fileName}")
with open(fileName, "wb") ... |
import os
import matplotlib.pyplot as plt
import seaborn as sns
import numpy as np
from scipy.stats import beta
from bayes_cv_prune.StanModel import BayesStanPruner
"""Plot the second 3 graphs in section 2.3: The prior.
"""
def plot():
CURRENT_PATH = os.path.dirname(os.path.realpath(__file__))
# Final mode... |
<filename>ibench/benchmarks/qr.py
# Copyright (C) 2016-2017 Intel Corporation
#
# SPDX-License-Identifier: MIT
import numpy as np
import scipy
from .bench import Bench
class Qr(Bench):
sizes = {'large': 10000, 'small': 5000, 'tiny': 1000, 'test': 2}
def _ops(self, n):
return (4./3.)*n*n*n*1e-9
... |
#!/usr/bin/env python
# Copyright 2019 Calico LLC
# 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
# https://www.apache.org/licenses/LICENSE-2.0
# Unless required by applicable law or agr... |
<reponame>laekov/akg<filename>tests/common/test_run/distr_normal_diag_logprob_run.py
# Copyright 2019 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://w... |
<gh_stars>1-10
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Wed Dec 2 15:23:46 2020
Copyright 2020 by <NAME>.
"""
# %% Imports.
# Standard library import:
from math import pi
from matplotlib import cm
import matplotlib.pyplot as plt
import numpy as np
from scipy.sparse import csc_matrix, eye, kron
f... |
"""
This file is for preprocessing of dataset.
Dataset: Avenue
Original dataset distribution link: http://www.cse.cuhk.edu.hk/leojia/projects/detectabnormal/dataset.html
"""
import os
import cv2
import glob
pwd = os.getcwd()
DATASET_NAME = 'avenue'
def download_dataset(delete_archive=False):
os.chdir(os.path.join... |
<filename>source/banco/bd_sensores.py
# -*- coding: latin-1 -*-
import sqlite3, scipy, datetime
def cria_tabela(caminho_banco):
'''
Cira a tabela 'dados_forno' caso ela não exista, criando o esquema e as
colunas no formato correto. O nome do arquivo do banco de dados é
caminho_banco e esta na mesma pasta /bandoDad... |
import numpy as np
from numpy.random import randn
import pytest
import pandas.util._test_decorators as td
import pandas as pd
from pandas import DataFrame, Series, isna, notna
import pandas._testing as tm
import pandas.tseries.offsets as offsets
def _check_moment_func(
static_comp,
name,
raw,
has_m... |
import numpy as np
from scipy.signal import savgol_filter
from scipy.interpolate import interp1d
class Lane(object):
"""
Utility class for extracting useful properties of a lane. It is assumed
that there is a one-to-one mapping between the x- and y-coordinates.
Parameters:
x: array
Array... |
<filename>lifetime_value/zero_inflated_lognormal_test.py
# Copyright 2019 The Lifetime Value Authors.
#
# 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
#
# https://www.apache.org/licenses/L... |
# -*- coding:utf-8 _*-
"""
@author:yaoli
@file: label2rgb.py.py
@time: 2019/01/22
Test change one_chanel label to 3 channel RGB image.
"""
import os
import numpy as np
import scipy.misc
from tqdm import tqdm
def annotation2color(input_path, output_path):
img = scipy.misc.imread(input_path)
color = np.zero... |
<reponame>Hephaestus12/applications
import pandas as pd
import shogun as sg
from pathlib import Path
import matplotlib.pyplot as plt
from scipy import stats
|
<filename>camFingerprint.py
import numpy as np
#from matplotlib.image import imread,imsave
import cv2
import pywt
import matplotlib.pyplot as plt
import sys
from numba import jit,njit
from scipy.signal import correlate2d
def matshow(title,mat):
mat = mat.astype(float)
mi = np.min(mat)
ma = np.m... |
# -*- coding: utf-8 -*-
from __future__ import print_function
from collections import OrderedDict
from acq4.util import Qt
from .CanvasItem import CanvasItem
import numpy as np
import scipy.ndimage as ndimage
import acq4.pyqtgraph as pg
import acq4.pyqtgraph.flowchart
import acq4.util.DataManager as DataManager
import ... |
import importlib
from hydroDL import kPath, utils
from hydroDL.app import waterQuality
from hydroDL.master import basins
from hydroDL.data import usgs, gageII, gridMET, ntn
from hydroDL.master import slurm
from hydroDL.post import axplot, figplot
import numpy as np
import matplotlib.pyplot as plt
import os
import panda... |
<reponame>subercui/velocyto.py
import numpy as np
from numba import jit
from sklearn.neighbors import kneighbors_graph, NearestNeighbors
from scipy import sparse
import logging
from typing import *
# Mutual KNN functions
@jit(signature_or_function="Tuple((float64[:,:], int64[:,:], int64[:]))(int64[:,:], float64[:, :... |
import pandas as pd
import numpy as np
from pandas.tseries.offsets import *
import scipy.optimize as opt
import scipy.cluster.hierarchy as sch
from scipy import stats
class FHBacktestAncilliaryFunctions(object):
"""
This class contains a set of ancilliary supporting functions for performing backtests.
The... |
import os
import numpy
import scipy.integrate
def AB(wave, flambda, AB_wave):
"""Returns the AB magnitude at `AB_wave` (nm) of spectrum specified by
`wave` (in nm), and `flambda` (in erg/s/cm^2/Ang).
"""
speed_of_light = 2.99792458e18 # units are Angstrom Hz
fNu = flambda * (wave * 10)**2 / speed_... |
"""Convert MATLAB data file into Spectre txt format
divik2spectre.py
Converts MATLAB data file into Spectre txt format
Copyright 2017 Spectre Team
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
... |
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Sun Jun 23 11:41:26 2019
@author: roshanprakash
"""
import time
import numpy as np
import tensorflow as tf
from scipy.stats import ttest_ind
from sklearn.tree import DecisionTreeRegressor as DT
from sklearn.preprocessing import scale
from sklearn.model_sele... |
import cv2
import numpy as np
import os
import math
from scipy.spatial import distance as dist
from collections import OrderedDict
lower_green = np.array([89, 250, 250])
upper_green = np.array([90, 255, 255])
lower_rgb = np.array([10,180,120])
upper_rgb = np.array([40,255,250])
class Bouncing_point():
def __in... |
"""
Classes and tools to easily set up a FEM model made of beam elements
References:
[2] <NAME>, <NAME>
"Dynamik Flexibler Mehrkoerpersysteme : Methoden Der Mechanik
"""
import pandas as pd
import numpy as np
import scipy
from welib.FEM.utils import skew
from welib.system.eva import eig
# ----------... |
<filename>multiframe_star/database/genDB_old.py
import numpy as np
import h5py
import scipy.io as io
import poppy
import sys
import scipy.special as sp
import pyfftw
from astropy import units as u
import matplotlib.pyplot as pl
from ipdb import set_trace as stop
def even(x):
return x%2 == 0
def zernike_parity(j, ... |
import math
import matplotlib.pyplot as plt
from prettytable import PrettyTable
from sympy import *
import numpy as np
x = symbols('x')
#Raízes de Equações
##Método da Bissecção
def plot2d(f, inicio, fim):
z = np.arange(inicio,fim,0.1)
y = []
for i in range(len(z)):
y.append(f.subs(x,z[i]))
... |
<reponame>flowerah/PythoMS
"""
IGNORE:
CHANGELOG:
-
---2.7 building
to add:
try to extract timepoints and tic from chromatogramList (x values are sorted, so this probably won't work)
IGNORE
"""
import sys
import os
import zlib
import gzip
import base64
import struct
import subprocess
import xml.dom.minidom
import ... |
<gh_stars>1-10
from typing import Any, Callable, List, Dict, Union, Optional, Sequence, Tuple
from numpy import ndarray
from collections import OrderedDict
from scipy import sparse
import os
import sklearn
import numpy
import typing
# Custom import commands if any
import warnings
import numpy as np
from sklearn.utils ... |
<filename>mvsnet/preprocess.py
#!/usr/bin/env python
"""
Copyright 2019, <NAME>, HKUST.
Training preprocesses.
"""
from __future__ import print_function
import os
import time
import glob
import random
import math
import re
import sys
import imageio
import cv2
import numpy as np
import tensorflow as tf
import scipy.i... |
#!/bin/env python3
# This class will perform fisher's exact test to evalutate the significance of connection between
# a list of source nodes with certain qnode_id in KG and each of the target nodes with specified type.
# relative imports
import scipy.stats as stats
import traceback
import sys
import os
import multipr... |
<reponame>oo92/Deep3dPortrait<filename>restore_from_crop.py
import os
import numpy as np
import cv2
from scipy.io import loadmat
def realign(img, crop_param, raw_w, raw_h, interpolation, crop_h=256, crop_w=256):
scale = crop_param[0]
left, up = int(crop_param[1]), int(crop_param[2])
canvas = np.zeros([4 ... |
<reponame>wei-mao-2019/gsps
import numpy as np
import argparse
import os
import sys
import pickle
import csv
from scipy.spatial.distance import pdist
sys.path.append(os.getcwd())
from utils import *
from motion_pred.utils.config import Config
from motion_pred.utils.dataset_h36m import DatasetH36M
from motion_pred.util... |
<reponame>simpeg-research/iris-mt-scratch
"""
follows Gary's TRegression.m in
iris_mt_scratch/egbert_codes-20210121T193218Z-001/egbert_codes/matlabPrototype_10-13-20/TF/classes
There are some high-level decisions to make about usage of xarray.Dataset,
xarray.DataArray and numpy arrays. For now I am going to cast X,Y... |
<filename>userlib/analysislib/paco_analysis/imageprocss/analyse.py
from __future__ import division
import numpy as np
from os import listdir
from os.path import isfile, join
import h5py
import matplotlib.pyplot as plt
from scipy.linalg import pinv, lu, solve
from sklearn.linear_model import Lasso
plt.clf()
__author__ ... |
import numpy as np
from scipy.optimize import minimize
import libSolver
class Species:
def __init__(self, charge, mass, density, vpara, vperp, fv, ns):
"""Constructs a species object with the required fields. """
assert(vpara.shape[0] == fv.shape[0])
assert(vperp.shape[0] == fv.shape[1])
... |
"""Evaluation routines for point spread functions."""
import numbers
from prysm.fttools import fftrange
from scipy import optimize
from .mathops import (
np, jinc,
ndimage,
special
)
from .coordinates import uniform_cart_to_polar
FIRST_AIRY_ZERO = 1.220
SECOND_AIRY_ZERO = 2.233
THIRD_AIRY_ZERO = 3.238
F... |
#-----------------------------------------------------------------------------------
#-----------------------------------------------------------------------------------
#-------------------------------B-SPLINE EXAMPLE CODE-------------------------------
#----------------------------------------------------------------... |
<gh_stars>0
#! /usr/bin/env python
#############################################################################
# Created in 2013 by <NAME> and <NAME>, USGS Rocky Mountain
# Geographic Science Center
# Created Python script to loop through all the individual burn probability
# (BP) images and then create a burne... |
<reponame>minrk/sympy<gh_stars>1-10
from sympy.core import S, C, sympify
from sympy.core.basic import Basic
from sympy.core.containers import Tuple
from sympy.core.operations import LatticeOp, ShortCircuit
from sympy.core.function import Application, Lambda
from sympy.core.expr import Expr
from sympy.core.singleton imp... |
"""
This code performs Reversible Jump Markov Chain Monte Carlo for the
Lennard-Jones fluid. The target property is heat of vaporization, which
only depends on epsilon. Therefore, the expected outcome is that RJMC
favors the single parameter model (just epsilon) over the two parameter
model (both ... |
import os
import re
import glob
import fire
import pickle
import numpy as np
import pandas as pd
import matplotlib.patches as patches
import matplotlib.pyplot as plt
from sklearn.neighbors import KDTree
from scipy.special import digamma
import warnings
warnings.filterwarnings('error')
fields = 'a0_sym,a0_stct,a0_scor... |
<filename>P4.py
#!/usr/bin/env python3
# Copyright (C) 2021 <NAME>.
# SPDX-License-Identifier: MIT
from PIL import Image
from scipy.fft import fft
import numpy as np
import matplotlib.pyplot as plt
import time
def fuente_info(imagen):
'''Una función que simula una fuente de
información al importar una image... |
<filename>perceptual_loss.py<gh_stars>10-100
from __future__ import absolute_import
import sys
import scipy
import scipy.misc
import numpy as np
import torch
from torch.autograd import Variable
import models
use_gpu = True
ref_path = './imgs/ex_ref.png'
pred_path = './imgs/ex_p1.png'
ref_img = scipy.misc.imread(r... |
<gh_stars>0
from sklearn.neighbors import KNeighborsClassifier
from deepview.embeddings import init_inv_umap
import scipy.spatial.distance as distan
import numpy as np
import umap
def leave_one_out_knn_dist_err(dists, labs, n_neighbors=5):
nn = KNeighborsClassifier(n_neighbors=5, metric="precomputed")
nn.fit(d... |
<filename>scripts/tip-post-processing.py
import numpy as np
import matplotlib.pyplot as plt
from matplotlib.figure import Figure
from matplotlib.backends.backend_agg import FigureCanvas
from scipy.ndimage import gaussian_filter
# First pass for drop-shadow
fig = Figure(figsize=(6,1.5))
canvas = FigureCanvas(fig)
ax = ... |
<reponame>trentford/iem<filename>scripts/iemre/grid_climate_prism.py
"""Grid climate for netcdf usage"""
from __future__ import print_function
import sys
import datetime
import numpy as np
import psycopg2.extras
from scipy.interpolate import NearestNDInterpolator
from pyiem import iemre, datatypes
from pyiem.network i... |
__author__ = '<NAME>'
# Copyright <NAME> 2015
import math
import numpy as np
from scipy.interpolate import interp1d
import matplotlib.pyplot as plt
from ContourPoint import ContourPoint
contourPointsFile = 'contours2D.csv'
with open(contourPointsFile, "rt") as fin:
# split the first line
line = fin.readline... |
<reponame>deepdialog/PanGu-alpha-tf
import os
import jieba
import numpy as np
from scipy.special import softmax
from onnxruntime import GraphOptimizationLevel, InferenceSession, SessionOptions, get_all_providers
from tokenization_jieba import JIEBATokenizer
def create_model_for_provider(model_path: str, provider: st... |
<reponame>m4webb/numerical_computing<filename>Labs/IsingModel/plots.py
import matplotlib
matplotlib.rcParams = matplotlib.rc_params_from_file('../../matplotlibrc')
import isingmodel
import scipy.misc as spmisc
import matplotlib.pyplot as plt
def initialize():
spinconfig = isingmodel.initialize(100)
spmisc.ims... |
<reponame>visten92/CAE-FFNN
import tensorflow as tf
import numpy as np
import scipy.io
from matplotlib import pyplot as plt
import time
# Load data and set hyperparameters
data_1 = scipy.io.loadmat('data_train_batch_1.mat')
data_2 = scipy.io.loadmat('data_train_batch_2.mat')
data_3 = scipy.io.loadmat('data_tr... |
<reponame>bolero2/DeepLearning-dc
import numpy as np
import matplotlib,pylab as plt
import scipy.io
matfile_name = "C:\\dataset\\mpii_human_pose_v1_u12_2\\mpii_human_pose_v1_u12_1.mat"
matfile = scipy.io.loadmat(matfile_name, struct_as_record=False)
print(matfile.get('RELEASE')[0, 0].get('annolist'))
# print(ma... |
"""
This script generates data used to estimate spar mass as a function of lift force (i.e. total weight) and span.
"""
### Imports
from aerosandbox.structures.beams import *
import scipy.io as sio
import copy
### Set up sweep variables
masses = np.linspace(50, 800, 50)
spans = np.linspace(30, 90, 50)
Masses, Spans ... |
import numpy as np
import sympy as sp
import pytest
from devito import (Grid, Function, TimeFunction, Eq, Coefficient, Substitutions,
Dimension, solve, Operator, NODE)
from devito.finite_differences import Differentiable
from devito.tools import as_tuple
_PRECISION = 9
class TestSC(object):
... |
######################################################################################################
######################################################################################################
######################################################################################################
# IMPORT L... |
<filename>test/src/supervised/LinearRegressionV2/SimpleLinearRegression.py<gh_stars>0
import sys, os
sys.path.append(os.path.abspath(__file__).split('test')[0])
import pandas as pd
import scipy.io as io
import matplotlib.pyplot as plt
import numpy as np
from pyml.supervised.linear_regression.LinearRegressionV2 import... |
# coding=utf-8
import glob
import inspect
import os
import dask.array as da
import numpy as np
import scipy.sparse as sp
import scipy.stats as sst
import xarray as xr
import yaml
from scipy.sparse import linalg as ln
from dtscalibration.calibrate_utils import calibration_double_ended_ols
from dtscalibration.calibrate... |
import random
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from scipy import stats
from one_time_scripts.visualisations.visualise_ea_runs import convert_file_into_dict
month_shorts = ['jan', 'feb', 'mar', 'apr',
'may', 'june', 'july', 'aug',
'sep', 'oct', 'no... |
#!/usr/bin/env python
# -*- coding: utf-8 -*-
# 2値分類、他クラス分類に関する結果表示(csv出力もする)
import os
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from math import sqrt
from scipy import stats
from .utils.utils import clopper_pearson
from .utils.folder import folder_create
from sklearn.metrics import roc_... |
<reponame>daviddralle/daviddralle.github.io
# -*- coding: utf-8 -*-
'''
Functions for calculation of potential and actual evaporation
from meteorological data.
Potential and actual evaporation functions
==========================================
- E0: Calculate Penman (1948, 1956) open water evaporation.
... |
<filename>res/Tools/HistPlot.py
#!/usr/bin/env python3
#
# main.py
#
# Author:
# <NAME> <<EMAIL>>
#
# Copyright (c) 2011 <NAME>
#
# 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, eith... |
#!/usr/bin/env python
# -*- coding: utf-8 -*-
import numpy as np
from scipy import linalg
from sklearn import mixture
cv_types = ['spherical', 'tied', 'diag', 'full']
def clustering(the_image_autoencoded, the_image_shape, number_of_clusters, extra_parameters='spherical'):
cv_type = extra_parameters
n_compon... |
<filename>Scripts/simulation/clubs/club_service.py
# uncompyle6 version 3.7.4
# Python bytecode 3.7 (3394)
# Decompiled from: Python 3.7.9 (tags/v3.7.9:13c94747c7, Aug 17 2020, 18:58:18) [MSC v.1900 64 bit (AMD64)]
# Embedded file name: T:\InGame\Gameplay\Scripts\Server\clubs\club_service.py
# Compiled at: 2020-07-17 2... |
import pandas as pd
import scanpy as sc
import anndata as ad
from scipy.stats import zscore
import tensorflow.keras as keras
from sklearn import preprocessing
import pickle
from collections import Counter
#------------------------------------------------------
def prelabel(ada, df_meta, raw=True, z=1.2):
#load to ... |
#!/usr/bin/env python3
import sys
import cv2
import numpy as np
import math
import rospy
from std_msgs.msg import Header
from sensor_msgs.msg import Image
from sensor_msgs.msg import CameraInfo
from sensor_msgs import point_cloud2
from sensor_msgs.msg import PointCloud2, PointField
from visualization_msgs.msg import... |
<gh_stars>1-10
__author__ = 'alex'
import os
import sys
import numpy as np
import config
import log
from astropy.io import fits as pyfits
from astropy.stats import sigma_clipped_stats
from scipy.ndimage import rotate
import matplotlib.pyplot as plt
# http://photutils.readthedocs.org/en/latest/photutils/... |
<gh_stars>10-100
import cv2
import os
import numpy as np
from PIL import Image
from skimage.color import rgb2hed
from scipy import stats
def nuclei_inpaint(img_path, lbl_path, out_path):
try:
os.stat(os.path.dirname(out_path + '/'))
except:
os.mkdir(os.path.dirname(out_path + '/'))
im... |
import FrEIA.framework as Ff
import FrEIA.modules as Fm
import FrEIA as Fr
import numpy as np
import torch
import torch.nn as nn
import torch.nn.functional as F
from typing import Callable
from scipy.stats import special_ortho_group
from attn_modules.attention_step import ISDP
class Only_isdpAttnBlock(Fm.AllInOneBlock... |
import sys
import os
import numpy as np
from scipy import ndimage
import pandas as pd
import geopandas as gpd
from shapely.geometry import Point, Polygon
import shapefile
from utility import *
from visualize import *
from process_risk_maps import *
PARK = 'SWS_May2019'
RESOLUTION = 1000
KERNEL_WIDTH = 5
PATROL_EFF... |
import os
import sys
import torch
import numpy as np
import torch.nn as nn
import torch.nn.functional as F
import torch.utils.data
from ASIS_Exps.network.pointnet2_utils import PointNetSetAbstractionMsg, PointNetSetAbstraction, PointNetFeaturePropagation
from scipy.optimize import linear_sum_assignment
from AS... |
#!/usr/bin/env python
#
from __future__ import print_function
import os, sys, re, json, time, astropy
import numpy as np
from astropy.table import Table, Column, hstack
from copy import copy
from numpy import log, log10, power, sum, sqrt, pi, exp
pow = power
lg = log10
ln = log
from scipy.interpolate import Interpol... |
<filename>util_bez2018.py
import numpy as np
import scipy.signal
def ffGn(N, tdres, Hinput, noiseType, mu, sigma=1):
"""
Python ffGn implementation based on MATLAB code (ffGn.m); modified from
https://github.com/mrkrd/cochlea/tree/master/cochlea/zilany2014/util.py
"""
# Check arguments are valid
... |
<gh_stars>0
from functools import reduce
import numpy as np
import scipy.sparse as sparse
from scipy.ndimage import zoom
def deconvolute(matrix, bias, invert=False):
"""
Applies bias factors to a sparse matrix.
Parameters
----------
matrix : scipy.sparse.spmatrix
The matrix to bias. Will... |
<reponame>jeyong/yakut
# Copyright (c) 2021 UAVCAN Consortium
# This software is distributed under the terms of the MIT License.
# Author: <NAME> <<EMAIL>>
# pylint: disable=too-many-locals
from __future__ import annotations
import sys
import functools
from typing import TYPE_CHECKING, Optional, Dict, Callable, List,... |
import cv2
import os
import numpy as np
from reader import Reader
from scipy import interpolate
import logging
logging.basicConfig(level=logging.INFO)
def read_lidar(lidar_path, mat):
lidar = np.fromfile(lidar_path, dtype=np.float32).reshape((-1, 4))
lidar[:, 3] = 1.0
camera = np.dot(mat, lidar.T)
ret... |
<gh_stars>1-10
#!/usr/bin/env python
# -*- coding: utf-8 -*-
# Author: <NAME> <sennrich [AT] cl.uzh.ch>
# This program handles the combination of Moses phrase tables, either through
# linear interpolation of the phrase translation probabilities/lexical weights,
# or through a recomputation based on the (weighted) comb... |
# coding=utf-8
# Copyright 2018 The Google AI Language Team Authors.
#
# 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 ... |
<filename>videoanalyst/evaluation/davis_benchmark/davis2017/davis_evaluation.py
import sys
from tqdm import tqdm
import warnings
warnings.filterwarnings("ignore", category=RuntimeWarning)
import numpy as np
#from evaluation.tracking.davis_benchmark.davis2017.davis import DAVIS
#from evaluation.tracking.davis_benchmark... |
from typing import Callable, List, Optional
import numpy as np
from scipy.interpolate import interp1d
from ..aliases import ParameterVector
from .data_structures import Chain
from .neb import run_NEB
# Nudged-Elastic-Band
def run_AutoNEB(
init_chain: Chain,
loss_function: Callable[[ParameterVector], float],... |
<reponame>junlulocky/BGMM
"""
Gibbs sampler for Sub clustering by Chinese restaurant process mixture model (SubCRPMM)
Date: 2017
"""
from scipy.misc import logsumexp
import numpy as np
import time
import math
import logging
from numpy import linalg as LA
from scipy.special import gammaln
from scipy.stats import berno... |
"""
This module contain utilities for the source finding routines
"""
import numpy
import math
import scipy.integrate
from tkp.sourcefinder.gaussian import gaussian
from tkp.utility import coordinates
def generate_subthresholds(min_value, max_value, num_thresholds):
"""
Generate a series of ``num_thresholds``... |
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