how to find number components dynamically such given in following Matlab code of PCA?

Question

In the following link fixed number of principal components analysis parameter is pre-defined but should be dynamically defined as Matlab code. How it is possible?

https://scikit-learn.org/stable/modules/generated/sklearn.decomposition.PCA.html

how to find the number of principal components dynamically such as given in Matlab code:

[coeff,score,~,~,explained] = pca(train);            
sm = 0;
no_components = 0;
for k = 1:size(explained,1)
    sm = sm+explained(k);
    if sm <= 99.4029
       no_components= no_components+1;
    end
end
no_components

here train variable is a 2D matrix.

Answer 1

there is slight variation with the explained variable with MatLab and python that I got so it is resolved as follow:

[x,y] = train.shape

pca = PCA(n_components=(x-1))
varPca = pca.fit(train)   

explainedVariance = pca.explained_variance_ratio_*100

sm = 0
no_components = 0
for k in range(0, x-1):
    sm = sm+explainedVariance[k]        
    if sm <= 99.4029:
        no_components= no_components+1    

print(no_components)