A simple example script that embeds a matrix of distances into 2D using MDS

embed_matrix_mds.py

#!/usr/bin/env python3
#
# Embeds a distance matrix into 2D using MDS. Distances are normalized
# to [0,1] in order to facilitate comparing embedded matrices.

import numpy
import sys

from sklearn.manifold import MDS

M = numpy.loadtxt(sys.argv[1])
M = ( M - M.min() ) / ( M.max() - M.min() )

mds    = MDS(dissimilarity="precomputed", n_init=10, eps=1e-9, max_iter=3000)
points = mds.fit_transform(M)

for point in points:
  x,y = point
  print(x,y)