Minimization problem for sampling histograms

sampling.py

import cvxpy
import numpy as np

if __name__ == "__main__":
    
    #The histogram data, 250 histograms with 3 bins
    D = cvxpy.parameter(250,3,name='D')
    D.value = cvxpy.matrix(np.random.randint(0,100,(250,3)))
    
    #The weights, one for each histogram
    w = cvxpy.variable(D.shape[0],name='w')
    constraints = []
    for i in range(D.shape[0]):
        constraints.append(cvxpy.geq(w[i,0],0))
    
    #Put the maximum difference as minimization objective
    pairwise_difference = cvxpy.vstack([w.T*D]*D.shape[1])-cvxpy.hstack([(w.T*D).T]*D.shape[1])
    p = cvxpy.program(cvxpy.minimize(cvxpy.max(pairwise_difference)),constraints)
    p.solve()
    
    

>>> cvxpy.max(pairwise_difference).is_dcp()
True