Allow to use solver for translate/transform_to

[jgosmann]

Allow to provide a solver for the translation between vocabularies. That can give better results than the simple outer product matrix.

v1 = spa.Vocabulary(d)
v2 = spa.Vocabulary(d)

s = 'A; B; C; D; E; F; G; H; I; J'
v1.populate(s)
v2.populate(s)

U1 = np.asarray([p.v for p in v1.parse_n(*s.split(';'))])
U2 = np.asarray([p.v for p in v2.parse_n(*s.split(';'))])

solver = nengo.solvers.Lstsq()
Ta = solver(U1, U2)[0].T
Tb = v1.transform_to(v2)

Va = Ta.dot(U1.T).T
Vb = Tb.dot(U1.T).T

Sa = spa.similarity(Va, v2)
Sb = spa.similarity(Vb, v2)

plt.title("Lstsq (%s)" % nengo.utils.numpy.rmse(Sa, np.eye(len(U1))))
plt.imshow(Sa, vmin=0, vmax=1)
plt.colorbar()
plt.show()

plt.title("transform_to (%s)" % nengo.utils.numpy.rmse(Sb, np.eye(len(U1))))
plt.imshow(Sb, vmin=0, vmax=1)
plt.colorbar()
plt.show()