gemseo.uncertainty.distributions.scipy.distribution_fitter module

Fitting a probability distribution to data using the SciPy library.

class SPDistributionFitter(variable, data)

Bases: BaseDistributionFitter[SPDistribution]

Fit a probability distribution to data using the SciPy library.

Initialize self. See help(type(self)) for accurate signature.

Parameters:

• variable (str) -- The name of the variable.

• data (RealArray) -- A data array.

class DistributionName(*values)

Bases: StrEnum

alpha = 'alpha'

anglit = 'anglit'

arcsine = 'arcsine'

argus = 'argus'

beta = 'beta'

betaprime = 'betaprime'

bradford = 'bradford'

burr = 'burr'

burr12 = 'burr12'

cauchy = 'cauchy'

chi = 'chi'

chi2 = 'chi2'

cosine = 'cosine'

crystalball = 'crystalball'

dgamma = 'dgamma'

dpareto_lognorm = 'dpareto_lognorm'

dweibull = 'dweibull'

expon = 'expon'

exponnorm = 'exponnorm'

exponpow = 'exponpow'

exponweib = 'exponweib'

f = 'f'

fatiguelife = 'fatiguelife'

foldcauchy = 'foldcauchy'

foldnorm = 'foldnorm'

gamma = 'gamma'

gausshyper = 'gausshyper'

genexpon = 'genexpon'

genextreme = 'genextreme'

gengamma = 'gengamma'

genhalflogistic = 'genhalflogistic'

genhyperbolic = 'genhyperbolic'

geninvgauss = 'geninvgauss'

genlogistic = 'genlogistic'

gennorm = 'gennorm'

genpareto = 'genpareto'

gibrat = 'gibrat'

gompertz = 'gompertz'

gumbel_l = 'gumbel_l'

gumbel_r = 'gumbel_r'

halfcauchy = 'halfcauchy'

halfgennorm = 'halfgennorm'

halflogistic = 'halflogistic'

halfnorm = 'halfnorm'

hypsecant = 'hypsecant'

invgamma = 'invgamma'

invgauss = 'invgauss'

invweibull = 'invweibull'

irwinhall = 'irwinhall'

jf_skew_t = 'jf_skew_t'

johnsonsb = 'johnsonsb'

johnsonsu = 'johnsonsu'

kappa3 = 'kappa3'

kappa4 = 'kappa4'

ksone = 'ksone'

kstwo = 'kstwo'

kstwobign = 'kstwobign'

landau = 'landau'

laplace = 'laplace'

laplace_asymmetric = 'laplace_asymmetric'

levy = 'levy'

levy_l = 'levy_l'

levy_stable = 'levy_stable'

loggamma = 'loggamma'

logistic = 'logistic'

loglaplace = 'loglaplace'

lognorm = 'lognorm'

lomax = 'lomax'

maxwell = 'maxwell'

mielke = 'mielke'

moyal = 'moyal'

nakagami = 'nakagami'

ncf = 'ncf'

nct = 'nct'

ncx2 = 'ncx2'

norm = 'norm'

norminvgauss = 'norminvgauss'

pareto = 'pareto'

pearson3 = 'pearson3'

powerlaw = 'powerlaw'

powerlognorm = 'powerlognorm'

powernorm = 'powernorm'

rayleigh = 'rayleigh'

rdist = 'rdist'

recipinvgauss = 'recipinvgauss'

reciprocal = 'reciprocal'

rel_breitwigner = 'rel_breitwigner'

rice = 'rice'

rv_histogram = 'rv_histogram'

semicircular = 'semicircular'

skewcauchy = 'skewcauchy'

skewnorm = 'skewnorm'

studentized_range = 'studentized_range'

t = 't'

trapezoid = 'trapezoid'

triang = 'triang'

truncexpon = 'truncexpon'

truncnorm = 'truncnorm'

truncpareto = 'truncpareto'

truncweibull_min = 'truncweibull_min'

tukeylambda = 'tukeylambda'

uniform = 'uniform'

vonmises = 'vonmises'

weibull_max = 'weibull_max'

weibull_min = 'weibull_min'

wrapcauchy = 'wrapcauchy'

class FittingCriterion(*values)

Bases: StrEnum

ANDERSON_DARLING = 'AndersonDarling'

CRAMER_VON_MISES = 'CramerVonMises'

FILLIBEN = 'Filliben'

KOLMOGOROV_SMIRNOV = 'KolmogorovSmirnov'

SignificanceTest

alias of FittingCriterion

fit(distribution)

Fit a probability distribution to the data.

Parameters:

distribution (DistributionName) -- The name of a probability distribution in the UQ library.

Returns:

The probability distribution fitted to the data.

Return type:

SPDistribution

default_fitting_criterion: ClassVar[FittingCriterion] = 'AndersonDarling'

The names of the default fitting criterion.