Rewrite Matlab into Python: Try to fit parametric probability distributions - Equivalent functions in Python

Has anyone an idea how to rewrite this Mathlab Distribution Fitting function into Python code?

%%file distribution_fitting.m
function pd = distribution_fitting(feature)
    distnames =["Poisson", "Exponential", "Gamma", "ExtremeValue", "Kernel"];    
    values_must_be_positive =["Poisson", "Exponential", "Gamma"];
    x=feature.';
    x_values = linspace(min(x),max(x));
    for dn=distnames
        if min(x)<0 & ~isempty(find(strcmp(dn, values_must_be_positive)))
          continue;
        end
        distname = char(dn);
        pd = fitdist(x.',distname);
        res1=kstest(x, 'CDF', pd); 
        res2=chi2gof(x, 'CDF', pd);
        if (~res1 && ~res2)
            fprintf('%s with 5%% significance level\r',distname);
            cdfplot(x)
            hold on
            plot(x_values,cdf(pd,x_values),'r-')
            plot(x_values,pdf(pd,x_values),'g-')
            legend('Empirical CDF',[distname ' CDF'],[distname ' PDF'],'Location','best');
            %title(['Empirical CDF and ', [distname ' CDF/PDF']);
            hold off 
            return;
        else 
            fprintf('Not %s with 5%% significance level\n',distname);
        end
    end
end

My approach starts with

i

mport scipy.stats
import scipy
from sklearn.preprocessing import StandardScaler

def distribution_fitting(feature):
        distnames = ["Poisson", "Exponential", "Gamma", "ExtremeValue", "Kernel"]
        values_must_be_positive = ["Poisson", "Exponential", "Gamma"]
        x = feature
        x_values = np.linspace(np.min(x), np.max(x))
        
        for dn in distnames:
            distname = getattr(scipy.stats, dn)
            probDist = distname.fit(x.T)
            
            res1= scipy.stats.kstest(x, dn, args=param)[1]
            
           ...
               
           

I'm not sure, if my way is right, because there are so many functions I couldn't find equivalent Python functions to them.

Answer 1

[Mayank]

The major strength of python is currently is libraries. You need not rewrite this function as there is a library available for this purpose.

Please check this article. The library (`fitter`) source code is available at github.