Added minimal Python example

compute_mca.py

+import numpy as np
+from supersvd import supersvd
+import matplotlib.pyplot as plt
+
+ts = np.fromfile('ts.std', dtype=np.float32).reshape(1147, 28, 31)
+ps = np.fromfile('ps.std', dtype=np.float32).reshape(1147, 28, 31)
+
+svd = supersvd(ts, ps, 4)
+
+first_mode_ts = svd.x_vect[0]
+
+plt.matshow(first_mode_ts)
+plt.savefig('first_mode_ts.png')
+
+first_ps_timeseries = svd.x_coeff[0]
+
+plt.figure()
+plt.plot(first_ps_timeseries)
+plt.savefig('first_ps_timeseries.png')
+
+print('Correlation coefficient between first_ts_timeseries. and first_ps_timeseries:', svd.corrcoeff[0])
+
+
+