for s, scaling in ((0.3, True), (1.0, False)):
pm = ProcrusteanMapper(scaling=scaling)
t1, t2 = 0.2, 0.5
// Create source/target data
d = d_orig[:, :nf_s]
d_s = d + t1
After Change
// train bloody mapper(s)
pm.train(d_s, d_t)
ds2 = Dataset(samples=d_s, labels=d_t)
pm2.train(ds2)
// verify that both created the same transformation
self.failUnless(norm(pm._T - pm2._T) <= 1e-12)