text string |
|---|
import face_recognition
import cv2
import os
import argparse
import face_recognition
import numpy as np
import demo_texture
import tensorflow as tf
from face_detection import select_face
from face_swap import face_swap
from api import PRN
from utils.render import render_texture
import numpy as np
import os
from glob... |
# 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 in writing, software
# distribu... |
"""Abstract tensor product."""
from __future__ import print_function, division
from sympy import Expr, Add, Mul, Matrix, Pow, sympify
from sympy.core.compatibility import u
from sympy.core.trace import Tr
from sympy.printing.pretty.stringpict import prettyForm
from sympy.physics.quantum.qexpr import QuantumError
fro... |
from abc import ABC
from abc import abstractmethod
from pathlib import Path
from typing import Collection
from typing import Dict
from typing import Iterable
from typing import Union
import numpy as np
import scipy.signal
import soundfile
from typeguard import check_argument_types
from typeguard import check_return_ty... |
<reponame>nlpsoc/STEL<gh_stars>1-10
"""
STYLE similarity is at 1 if the same style (also for cosine-sim)
at 0 or -1 if distinct style
"""
from abc import ABC
import nltk
from typing import Tuple, List
import numpy
import logging
# from sentence_transformers import SentenceTransformer, models
from to_add_... |
<filename>dataloader.py<gh_stars>1-10
import numpy as np
from abc import abstractmethod
from torch.utils.data import DataLoader
import torch
from torchvision import datasets, transforms
import networkx as nx
import typing
import scipy
import scipy.io as spio
import numpy as np
import os
def loadmat(filename):
'''... |
<reponame>201518015029022/zzzzzz
'''
load and preprocess data
'''
import numpy as np
import scipy.io as sio
from keras import backend as K
from keras.models import model_from_json
from core import util
from core import pairs
def get_data(params):
'''
load data
data_list contains the multi-view data for... |
<reponame>FutureYu/ButingButing<gh_stars>1-10
import matplotlib.pyplot as plt
import numpy as np
import scipy.misc
import os
import csv
import pandas as pd
import random
from skimage import io
from rpi_define import *
import shutil
npy_dir = BUTING_PATH + r"\data_npy" # npy文件夹路径
dest_dir = BUTING_PATH + r"\data" # 训... |
"""
Copyright 2017 <NAME>
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 in writing, software
distrib... |
from simulator.simulatorBases.CrownstoneCore import CrownstoneCore
from simulator.simulatorBases.GuiCrownstoneCore import GuiCrownstoneCore
import math
import operator
import string
import numpy as np
from scipy.stats import norm
import numpy as np
import numpy
class SimulatorCrownstone(GuiCrownstoneCore):
""... |
<reponame>jarvisqi/machine_learning
from sklearn.preprocessing import LabelEncoder
from sklearn.preprocessing import Binarizer
from sklearn.preprocessing import OneHotEncoder
from sklearn.preprocessing import scale
from sklearn.preprocessing import StandardScaler
from sklearn import preprocessing
import numpy as np
im... |
<gh_stars>10-100
__author__ = 'jules'
import deepThought.ORM.ORM as ORM
import pymc
import gamma_model
import numpy as np
from numpy import mean
from scipy.stats import gamma
import matplotlib.pylab as plt
def main():
model=pymc.MCMC(gamma_model)
model.sample(iter=1000, burn=500, thin=2)
alpha = mean(... |
# coding: utf-8
# # Photometry
# @author: <NAME>
# From astropy and [Photutils](http://photutils.readthedocs.io/en/stable/).
from astropy import units as u
from astropy.table import Table
from astropy.table import Column
from astropy.coordinates import SkyCoord
from astropy.coordinates import EarthLocation
from ph... |
<filename>Chapter 6-7/fn_PSHA_given_M_lambda.py<gh_stars>0
# Note: The codes were originally created by Prof. <NAME> in the MATLAB
import numpy as np
from scipy.stats import norm
from scipy.interpolate import interp1d
from gmpe_eval import gmpe_eval
# Compute PSHA, with rupture rates for each M precomputed
#########... |
<gh_stars>0
"""
BSD 3-Clause License
Copyright (c) 2020, <NAME>, <NAME>, <NAME>
All rights reserved.
"""
import logging
import sys
from functools import lru_cache
import numpy as np
from scipy.special import binom
logging.basicConfig(
stream=sys.stdout,
level=logging.INFO,
format='%(asctime)s - %(levelna... |
<gh_stars>1-10
from scipy.ndimage import binary_erosion, binary_dilation
from scipy.io import savemat
from nibabel import processing
import nibabel as nib
import numpy as np
import glob
import os
tag = "mri_4688"
nii_list = glob.glob("../data/"+tag+"/*.nii.gz")
nii_list.sort()
for nii_path in nii_list:
print(nii_p... |
import numpy as np
import time
from .constants import log
from . import util
from . import convex
from . import nsphere
from . import grouping
from . import triangles
from . import transformations
try:
from scipy import spatial
from scipy import optimize
except ImportError:
log.warning('Scipy import fail... |
<gh_stars>0
import numpy as np
from scipy.stats import ttest_rel, ttest_ind
X = [0.1, 0.2, 0.6, 0.7, 0.9]
Y = [0.05, 0.1, 0.3, 0.4, 0.8]
print("X: ", X, "mean is", np.mean(X), "\nY: ", Y, "mean is", np.mean(Y))
print("\nPair: ", round(ttest_rel(X, Y).pvalue, 3))
print("Unpair: ", round(ttest_ind(X, Y).pvalue, 3))
s... |
#
#
# littletable.py
#
# littletable is a simple in-memory database for ad-hoc or user-defined objects,
# supporting simple query and join operations - useful for ORM-like access
# to a collection of data objects, without dealing with SQL
#
#
# Copyright (c) 2010-2021 <NAME>
#
# Permission is hereby granted, free of c... |
# --------------
# Importing header files
import numpy as np
import pandas as pd
from scipy.stats import mode
import warnings
warnings.filterwarnings('ignore')
#Reading file
bank_data = pd.read_csv(path)
#Code starts here
bank=pd.DataFrame(bank_data)
categorical_var=bank.select_dtypes(include='obj... |
r"""Y-Path Factory :mod:`abelfunctions.ypath_factory`
=================================================
This module defines the y-skeleton of the Riemann surface. That is, a means of
not only computing the a- and b-cycles of the first homology group of the
Riemann surface but also mechanisms for travelling from one sh... |
<reponame>simone-mastrogiovanni/gdr_gwcosmo_tutorial_2020<gh_stars>1-10
"""
Module with Schechter magnitude function:
(C) <NAME> (2014)
"""
from numpy import *
from scipy.integrate import quad
import numpy as np
class SchechterMagFunctionInternal(object):
def __init__(self, Mstar, alpha, phistar):
self.Ms... |
import scipy as sp
from scipy import interpolate
def estimate(pv, m=None, verbose=False, lowmem=False, pi0=None):
"""
Estimates q-values from p-values
Args
=====
m: number of tests. If not specified m = pv.size
verbose: print verbose messages? (default False)
lowmem: use memory-efficient... |
from __future__ import print_function
from __future__ import absolute_import
from __future__ import division
from numpy import asarray
from numpy import hstack
from numpy import ones
from numpy import vectorize
from numpy import tile
from scipy.linalg import solve
from compas.geometry import cross_vectors
__all__ ... |
import logging
import math
import numpy as np
import scipy.stats
from datetime import datetime, timedelta
from django.utils import timezone
from django.db.models import QuerySet
from src.apps.runs.models import Run
logger = logging.getLogger(__name__)
def random_weighted_choice(networks):
probability_to_be_pic... |
<reponame>habichta/ETHZDeepReinforcementLearning
'''
Contains functions to simplify transofrmation of the input data. This can be illuminance data or cloud images
Author: <NAME> <EMAIL>
'''
import os
import re
from .abb_clouddrl_constants import ABB_Solarstation as abb_st
from .abb_clouddrl_constants import abb_filepa... |
<reponame>Ditskih/Project
# -*- coding: utf-8 -*-
"""
Created on Thu May 2 19:42:57 2019
@author: Ditskih
"""
import numpy as np
import pandas as pd
import re
import matplotlib.pyplot as plt
from scipy.sparse import csr_matrix
from sklearn.feature_extraction.text import TfidfVectorizer
from sklearn.de... |
<reponame>BjoernBiltzinger/astromodels
import collections
import astropy.units as u
import numpy as np
import os
import pandas as pd
from pandas.api.types import infer_dtype
import re
import scipy.interpolate
import warnings
from pandas import HDFStore
from astromodels.core.parameter import Parameter
from astromodels... |
# -*- coding: utf-8 -*-
"""
Created on Fri Feb 25 15:28:21 2022
@author: NeoChen
[note]
1. score check ok
2. IOread and plot check ok
3. denoise ok
4. model tran ?
"""
#import pytest
import numpy as np
import scipy.io.wavfile
import soundfile as sf
from scipy import signal
from pathlib import Path
from pesq... |
<gh_stars>1-10
from __future__ import division
import datetime
import os
import numpy as np
from scipy import linalg, stats
import sympy
import matplotlib
if os.environ.get('DISPLAY') is None:
matplotlib.use('Agg')
else:
matplotlib.use('Qt5Agg')
from matplotlib import rcParams
import matplotlib.pyplot as plt
fr... |
from scipy.optimize import fmin_cobyla
import openopt
from openopt.kernel.setDefaultIterFuncs import *
from openopt.kernel.ooMisc import WholeRepr2LinConst, xBounds2Matrix
from openopt.kernel.baseSolver import baseSolver
from numpy import inf, array, copy
#from openopt.kernel.setDefaultIterFuncs import SMALL_DELTA_X, ... |
#! /usr/bin/env python
"""
Functions involving masked arrays
Some functions are general array operations, others involve geospatial information
"""
import sys
import os
import glob
import numpy as np
from osgeo import gdal
from pygeotools.lib import iolib
#Notes on geoma
#Note: Need better init overloading
#http:... |
""" FILE: convolveRadiallySymmetricFunctions.py
Module implementing 2D convolution of two radially symmetric functions
based on two differnt approaches to compute Fourier-Bessel functions
as explained in Refs. [2] and [3].
Refs:
[1] Operational and convolution properties of two-dimensional Fourier
tran... |
<filename>tests/printing/test_inifile.py<gh_stars>1-10
from os.path import join
import pytest
from sympy import atan, sqrt, symbols
from sympy.printing.printer import Printer
from sympy.printing.str import StrPrinter
from qalgebra.core.operator_algebra import LocalSigma
from qalgebra.core.state_algebra import BasisKe... |
# Author: <NAME>
# ENF estimation from video recordings using Rolling Shutter Mechanism
# Import required packages
import numpy as np
import cv2
import pickle
import pyenf
#from scipy import signal, io
import scipy.io.wavfile
import math
from scipy.fftpack import fftshift
import matplotlib.pyplot as plt
i... |
<reponame>fact-project/DrsTemperatureCalibration<filename>drs4Calibration/other_studys/photon_reconstruction/plot.py<gh_stars>0
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from scipy.interpolate import griddata
# Define a class that forces representation of float to look a certain way
# Th... |
<reponame>jorisvandenbossche/scipy-lecture-notes
import numpy as np
from scipy import ndimage
import matplotlib.pyplot as plt
from sklearn.mixture import GMM
np.random.seed(1)
n = 10
l = 256
im = np.zeros((l, l))
points = l*np.random.random((2, n**2))
im[(points[0]).astype(np.int), (points[1]).astype(np.int)] = 1
im =... |
import numpy as np
from scipy import signal
def diagonal_potential(d_1: int, d_2: int,
rng: np.random.RandomState) -> np.ndarray:
factor_potential = rng.randint(4, 6, size=(d_1, d_2)) * 1.0
dim = np.min([d_1, d_2])
identity = np.eye(dim)
if rng.normal(size=1) > 1:
identi... |
<reponame>okfang/ssd_tf_master
# Copyright 2018 <NAME>
# 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... |
from scipy.stats import beta
from typing import List, Optional
class IncrementalFsum:
""" Incremental version of https://en.wikipedia.org/wiki/Kahan_summation_algorithm """
def __init__(self):
self.partials = []
def __iadd__(self, x):
i = 0
for y in self.partials:
if a... |
from scipy.spatial import distance
import numpy as np
import utils4knets
import APKnet
import CSKnet
from sklearn.metrics import pairwise_distances
'''
Brief K-nets description.
K-networks: Exemplar based clustering algorithm. It can be operated as a deterministic or stochastic process.
The basic K-nets parameter is... |
<gh_stars>1-10
import os
import numpy as np
from numpy.lib.type_check import imag
from sklearn import cluster
from scipy.sparse.linalg import svds
from sklearn.preprocessing import normalize
from sklearn.metrics import normalized_mutual_info_score, adjusted_rand_score, adjusted_mutual_info_score
import torch
import... |
from sympy import symbols, lambdify, diff, sqrt, I
from sympy import besselj, hankel1, atan2, exp, pi, tanh
import scipy.special as scp
import numpy as np
from scipy.sparse.linalg import gmres
# gmres iteration counter
# https://stackoverflow.com/questions/33512081/getting-the-number-of-iterations-of-scipys-gmres-ite... |
###############################################################################
# Imports
import argparse # Argument parser
import logging # DEBUG, INFO, WARNING, ERROR, CRITICAL
import Utility
import YawlToMetagraph
import TriplesToMetagraph
import PolicyAnalysisHelper
from mgtoolkit.library import *
from ortools... |
<gh_stars>10-100
# Authors: <NAME> <<EMAIL>>
#
# License: BSD 3 clause
""" Non-stationary kernels that can be used with sklearn's GP module. """
import numpy as np
from scipy.special import gamma, kv
from sklearn.cluster import KMeans
from sklearn.metrics.pairwise import pairwise_kernels
from sklearn.gaussian_proce... |
<reponame>josephmje/niworkflows<gh_stars>10-100
# emacs: -*- mode: python; py-indent-offset: 4; indent-tabs-mode: nil -*-
# vi: set ft=python sts=4 ts=4 sw=4 et:
#
# Copyright 2021 The NiPreps Developers <<EMAIL>>
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in ... |
<filename>0_Test_Device/Python/test_Models.py
import tclab
import numpy as np
import time
import matplotlib.pyplot as plt
from scipy.integrate import odeint
# FOPDT model
Kp = 0.5 # degC/%
tauP = 120.0 # seconds
thetaP = 10 # seconds (integer)
Tss = 23 # degC (ambient temperature)
Qss = 0 ... |
<gh_stars>100-1000
import pickle
import gzip
from sparse_gp import SparseGP
import scipy.stats as sps
import numpy as np
import os.path
import rdkit
from rdkit.Chem import MolFromSmiles, MolToSmiles
from rdkit.Chem import Descriptors
import torch
import torch.nn as nn
from jtnn import create_var, JTNNVAE, Vocab
from... |
<reponame>tfrere/music-to-led-server<filename>visualizations/visualizer.py
import numpy as np
from copy import deepcopy
from scipy.ndimage.filters import gaussian_filter1d
from visualizations.pixelReshaper import PixelReshaper
from helpers.audio.expFilter import ExpFilter
from visualizations.functions.sound.scroll... |
<filename>xcs_soxs/spectra.py
from __future__ import division
import numpy as np
import subprocess
import tempfile
import shutil
import os
from xcs_soxs.utils import soxs_files_path, mylog, \
parse_prng, parse_value, soxs_cfg, line_width_equiv, \
DummyPbar
from xcs_soxs.lib.broaden_lines import broaden_lines
f... |
# -*- coding: utf-8 -*-
"""
Created on Sat Jul 05 09:54:39 2014
@author: rlabbe
"""
from __future__ import division, print_function
import matplotlib.pyplot as plt
from scipy.integrate import ode
import math
import numpy as np
from numpy import random, radians, cos, sin
class BallTrajectory2D(object)... |
<gh_stars>0
import matplotlib.pyplot as plt
import numpy as np
from scipy import ndimage as ndi
import scipy
import cv2
import os
from skimage import data
from skimage.util import img_as_float
from skimage.filters import gabor_kernel
import utility_functions
from sklearn.svm import SVC, LinearSVC
from sklearn.model_sel... |
"""Wald distribution."""
import numpy
from scipy import special
from ..baseclass import Dist
from ..operators.addition import Add
class wald(Dist):
"""Wald distribution."""
def __init__(self, mu):
Dist.__init__(self, mu=mu)
def _pdf(self, x, mu):
out = numpy.zeros(x.shape)
indic... |
<filename>replay/models/admm_slim.py
from typing import Optional, Tuple
import numba as nb
import numpy as np
import pandas as pd
from pyspark.sql import DataFrame
from scipy.sparse import coo_matrix, csr_matrix
from replay.models.base_rec import NeighbourRec
from replay.session_handler import State
# pylint: disab... |
<reponame>Air-Factories-2-0/af2-hyperledger
# coding: utf-8
"""Common tools to optical flow algorithms.
"""
import numpy as np
from scipy import ndimage as ndi
from ..transform import pyramid_reduce
from ..util.dtype import _convert
def get_warp_points(grid, flow):
"""Compute warp point coordinates.
Param... |
<filename>models.py
# Copyright (c) Microsoft Corporation. All rights reserved.
# Licensed under the MIT License.
import torch
import torch.nn as nn
from torch import Tensor
import torch.nn.functional as F
import torch.optim as optim
from torch.autograd import Variable
import torch.utils.data as data_utils
import num... |
<reponame>duangsuse-valid-projects/extract-subtitles<filename>deprecated/extract_subtitles_old.py
#!/bin/env python3
# -*- coding: utf-8 -*-
from typing import Tuple
from argparse import ArgumentParser, FileType
from re import findall
from pathlib import Path
from os import remove
from progressbar import ProgressBar
... |
<gh_stars>10-100
import functools
import numpy as np
from scipy.stats import norm as ndist
import regreg.api as rr
from selection.tests.instance import gaussian_instance
from selection.learning.Rutils import lasso_glmnet
from selection.learning.utils import (full_model_inference,
... |
# -*- coding: utf-8 -*-
#!/usr/bin/env python
#compatible chiner 1.5
import os
import chainer
import argparse
import os
import numpy as np
from chainer import cuda
import chainer.functions as F
from chainer import cuda, Function, FunctionSet, gradient_check, Variable, optimizers
from chainer import serializers
from... |
import scipy.sparse as sp
import scipy.sparse.linalg as slinalg
from numpy import linalg
import scipy.misc
from sklearn.preprocessing import normalize
from gcn.utils import Test21, absorption_probability, smooth, load_data, taubin_smoothing
import gcn.utils
from config import configuration
import matplotlib.pyplot as p... |
<reponame>lucasmaystre/kickscore
import numpy as np
from kickscore.item import Item
from kickscore.kernel import Constant
from kickscore.observation.observation import Observation
from math import log, pi, sqrt
from scipy.stats import norm
class DummyObservation(Observation):
def match_moments(self, mean_cav, ... |
<reponame>shilpiprd/sympy<gh_stars>1000+
from sympy import Rational, I, expand_mul, S, simplify, sqrt
from sympy.matrices.matrices import NonSquareMatrixError
from sympy.matrices import Matrix, zeros, eye, SparseMatrix
from sympy.abc import x, y, z
from sympy.testing.pytest import raises, slow
from sympy.testing.matric... |
#!/usr/bin/env python3
'''
Rank which offensive statistics by how well they correlated from
2017 to 2018
'''
import re
from scipy import stats
import pandas as pd
# Contains various per-season stats and limited descriptive info for
# all hitters with at least 200 PAs in either 2017 or 2018.
# Obtained via exporting ... |
# Copyright 2018 The Cornac Authors. 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 ... |
#!/usr/bin/env python3
# Copyright (c) 2020 Leedehai. All rights reserved.
# Use of this source code is governed under the MIT LICENSE.txt file.
# -----
# Generate a static site to show the test results, read from the
# result log file.
# This is the second iteration; formerly score_view.py.
import argparse
import dat... |
import numpy as np
from scipy import stats
import matplotlib
matplotlib.use('tkagg')
import matplotlib.pyplot as plt
import matplotlib.colors as colors
from scipy.stats import kde
def print_stats(labels_test, labels_predict):
''''
Calculate the following statistics from machine learning tests.
RMSE, Bias,... |
import numpy
from scipy.fftpack import fft
import sys
eps = 0.00000001
def mtFeatureExtraction(signal,Fs, mtWin, mtStep, stWin, stStep):
"""
Mid-term feature extraction
"""
mtWinRatio = int(round(mtWin / stStep))
mtStepRatio = int(round(mtStep / stStep))
stFeatures = stFeatureExtraction2(s... |
import tensorflow as tf
import numpy as np
np.set_printoptions(precision=2, linewidth=200)
import cv2
import os
import time
import sys
import tf_nndistance
import argparse
import glob
import PIL
import scipy.ndimage as ndimage
sys.path.append(os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
from utils impo... |
<gh_stars>1-10
#!/usr/bin/env python
#-*- coding:utf-8 -*-
import scipy
import pylab
import scipy.linalg as sl
import random
from collections import defaultdict
import h5py
def normalize(x):
n = scipy.sqrt(scipy.inner(x,x))
#n = sl.norm(x, scipy.inf)
if n > 0:
return x/n
else:
return x
... |
import logging
import multiprocessing
from multiprocessing import Lock, Pool
multiprocessing.set_start_method("spawn", True) # ! must be at top for VScode debugging
import argparse
import glob
import json
import math
import multiprocessing as mp
import os
import pathlib
import pickle
import re
import sys
import warni... |
from mpl_toolkits.mplot3d import axes3d
import matplotlib.pyplot as plt
import numpy as np
def Pn3m(x, y, z):
"""
:param x: a vector of coordinates (x1, x2, x3)
:return: An approximation of the Schwarz D "Diamond" infinite periodic minimal surface
"""
a = np.sin(x)*np.sin(y)*np.sin(z)
b = np.... |
#!/usr/bin/env python
#############################################
# Title: Satellite utilities #
# Project: TLE Match #
# Date: Jan 2018 #
# Author: <NAME>, KJ4QLP #
#############################################
import sys
import os
import... |
<reponame>MasterMilkX/codenames_autobots
# WEIGHTED TRANSFORMER CODEMASTER
# CODE BY <NAME>
import nltk
from nltk.stem import WordNetLemmatizer
from nltk.stem.lancaster import LancasterStemmer
from nltk.corpus import gutenberg
from nltk.corpus import stopwords
from nltk.tokenize import word_tokenize
from players.c... |
"""
Solve Biharmonic equation on the unit disc
Using polar coordinates and numerical method from:
"Efficient spectral-Galerkin methods III: Polar and cylindrical geometries",
<NAME>, SIAM J. Sci Comput. 18, 6, 1583-1604
"""
import matplotlib.pyplot as plt
from shenfun import *
from shenfun.la import SolverGeneric2N... |
<gh_stars>0
"""Base class used to define the interface for derivative approximation schemes."""
from __future__ import print_function, division
from six import iteritems
from collections import defaultdict
from scipy.sparse import coo_matrix
import numpy as np
from openmdao.utils.array_utils import sub2full_indices, g... |
<reponame>googlearchive/rgc-models
# Copyright 2018 Google 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
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applic... |
from sympy.polys.domains import ZZ
from sympy.polys.domains import GF
from sympy.polys.galoistools import gf_rem, gf_quo, gf_mul, gf_add
from sympy.polys.galoistools import gf_sub, gf_degree, gf_irreducible_p
from sympy.ntheory.modular import solve_congruence
import time
import math
import numpy as np
import logging
im... |
'''extra statistical function and helper functions
contains:
* goodness-of-fit tests
- powerdiscrepancy
- gof_chisquare_discrete
- gof_binning_discrete
Author: <NAME>
License : BSD-3
changes
-------
2013-02-25 : add chisquare_power, effectsize and "value"
'''
from statsmodels.compat.python import lrange
im... |
<filename>bin/bin_onePT/extra/mvir-3b-fitS01-zTrend.py<gh_stars>1-10
from os.path import join
import numpy as n
import astropy.io.fits as fits
import sys
import os
import lib_functions_1pt as lib
import cPickle
import astropy.cosmology as co
cosmo = co.Planck13
import astropy.units as uu
import matplotlib
#matplotlib... |
"""Module for querying SymPy objects about assumptions."""
from __future__ import print_function, division
from sympy.core import sympify
from sympy.core.cache import cacheit
from sympy.logic.boolalg import (to_cnf, And, Not, Or, Implies, Equivalent,
BooleanFunction, BooleanAtom)
from sympy.logic.inference import ... |
import pyParz as parallelize
import sys
# Dictionary of sncosmo CCSN model names and their corresponding SN sub-type
SubClassDict_SNANA = { 'ii':{ 'snana-2007ms':'IIP', # sdss017458 (Ic in SNANA)
'snana-2004hx':'IIP', # sdss000018 PSNID
'sn... |
<reponame>lruthotto/DeepGenerativeModelingIntro
import torch
import torchvision
import argparse
import numpy as np
import matplotlib.pyplot as plt
device = torch.device("cuda:0" if torch.cuda.is_available() else "cpu")
parser = argparse.ArgumentParser('DCGAN')
parser.add_argument("--batch_size" , type=int, default... |
<reponame>DarkDisasters/winglets_python
import math;
import numpy as np;
from scipy import stats;
from skimage import measure;
from sklearn.cluster import KMeans
from .geoOperation import getGeoInfo;
from shapely.geometry import Point;
from shapely.geometry import Polygon;
import seaborn as sns
import numpy as np
imp... |
import pickle, glob, sys, csv, warnings
from sklearn.preprocessing import PolynomialFeatures, StandardScaler
from sklearn.metrics import accuracy_score, confusion_matrix, auc, roc_curve
from feature_extraction_utils import _load_file, _save_file, _get_node_info
from scipy.stats import multivariate_normal
from ... |
#!/usr/bin/env python3
import json
import statistics
import sys
if __name__ == '__main__':
if len(sys.argv) != 2:
sys.stderr.write('Usage: {} <file.json>\n'.format(sys.argv[0]))
sys.exit(1)
file_name = sys.argv[1]
with open(file_name, 'r') as fd:
content = fd.read()
process_... |
import math
import numpy as np
import matplotlib.pyplot as plt
from scipy.misc import comb
def ensemble_error(n_classifier, error):
k_start = math.ceil(n_classifier / 2.0)
probs = [comb(n_classifier, k) * error ** k * (1 - error) ** (n_classifier - k)
for k in range(k_start, n_classifier + 1)]
... |
<reponame>hanzy1110/ProbabilisticFatigue
#%%
import pymc3 as pm
import arviz as az
import pandas as pd
import numpy as np
from pymc3.gp.util import plot_gp_dist
from scipy import stats
from typing import Dict
import theano.tensor as tt
import matplotlib.pyplot as plt
def basquin_rel(N, B,b):
return B*(N**b)
B ... |
<filename>test.py<gh_stars>0
import pandas as pd
import numpy as np
from scipy.special import comb
import getparameter
from keras import backend as K
celllinename=pd.read_excel("cell-line-name.xlsx",header=None)
drugname=pd.read_excel("drug-name.xlsx",header=None)
drug = pd.read_csv("drugfeature.csv",header=No... |
<reponame>mzy2240/GridCal
#!/usr/local/bin/python
import sys, math
from math import sin, cos, atan2, sqrt, exp, log, pi
import cmath
Euler = 0.577215664901532860606512
gamma = exp(Euler)
ln2g = log(2.0/gamma)
lng = Euler
tpi = 2.0*pi
tworoot = sqrt(2.0)
Nmax = 150
F = [ 0.0 ]*Nmax
# Generate table of factorials, no... |
<reponame>moritzblum/pytorch_geometric<gh_stars>1-10
import torch
import scipy.sparse
import networkx as nx
from torch_geometric.data import Data
from torch_geometric.utils import (to_scipy_sparse_matrix,
from_scipy_sparse_matrix)
from torch_geometric.utils import to_networkx, from_n... |
<gh_stars>0
import inspect
import math
import sys
from abc import ABC, abstractmethod
from typing import Union, Tuple
import numpy as np
from scipy import stats
from scipy.special import erfcinv
from autoconf import conf
from autofit import exc
from autofit.mapper.model_object import ModelObject
from aut... |
<gh_stars>0
#!/usr/bin/env python
# coding: utf-8
# In[1]:
import sklearn
import matplotlib.pyplot as plt
import pandas as pd
import numpy as np
import seaborn as sns
import scipy.stats as ss
import os
data_dir ='data'
# # Question 2.1 - Load Data
# Download prostate data from https://web.stanford.edu/~hastie/El... |
<gh_stars>1-10
import os
import time
import pickle
import cv2
import hashlib
import numpy as np
import nibabel as nib
import statsmodels.api as sm
from scipy.signal import argrelextrema
def hash_file(filename):
""""This function returns the SHA-1 hash
of the file passed into it"""
# make a hash object
... |
# coding: utf-8
# In[ ]:
from keras.layers import Input, Dense, Flatten, Dropout
from keras.layers.core import Reshape
from keras.models import Model
from keras.callbacks import ModelCheckpoint
from keras.layers.convolutional import MaxPooling2D,UpSampling2D,Conv2DTranspose
from keras.layers.convolutional import Co... |
<gh_stars>0
"""This module defines parameters and parameter declaration for usage in pulse modelling.
Classes:
- Parameter: A base class representing a single pulse parameter.
- ConstantParameter: A single parameter with a constant value.
- MappedParameter: A parameter whose value is mathematically compute... |
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Fri Oct 29 13:21:27 2021
@author: christiansaintlouis
"""
import pandas as pd
from scipy.stats import shapiro
import scipy.stats as stats
from matplotlib import pyplot
from scipy.stats import ttest_ind
# dataframe
diabetes = pd.read_csv('https://raw.gith... |
__author__ = 'Prateek'
from sympy import primerange
def phi(n):
value = n
for i in primerange(1, n):
if n % i == 0:
value = value * (1 - i ** -1)
return int(value)
if __author__ == 'Prateek':
print phi(666) |
# -*- coding: utf-8 -*-
"""
Created on Sat Dec 28 20:06:03 2019
@author: <NAME>
Email: <EMAIL>
"""
from scipy import stats
from statsmodels.formula.api import ols
from statsmodels.stats.anova import anova_lm
from statsmodels.stats.multicomp import pairwise_tukeyhsd
import warnings
import pandas as pd
warnings.filter... |
#(c) Coded by <NAME> 2014
#Functions related with the XTCAV pulse retrieval
import logging
logger = logging.getLogger(__name__)
import numpy as np
import scipy.interpolate
import time
import cv2
import scipy.io
import math
import psana.xtcav.Constants as cons
import collections
import psana.xtcav.Spli... |
import matplotlib.patches as mpatches
import numpy as np
from sympy import Symbol, latex
class Pool():
def __init__(
self,
x,
y,
size,
pool_color,
pool_alpha,
pipe_alpha,
connectionstyle,
arrowstyle,
... |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.