def test_transform():
np.random.seed(1)
corrs = np.arange(-1, 1, 0.1)
corrs *= 0.999
for corr in corrs:
for scaleratio in [1, 0.001]:
covmatrix = np.array([[1., corr], [corr, 1.]])
points = np.random.multivariate_normal(np.zeros(2),
covmatrix,
size=1000)
print(corr, scaleratio, covmatrix.flatten(), points.shape)
points[:, 0] = points[:, 0] * 0.01 * scaleratio + 0.5
points[:, 1] = points[:, 1] * 0.01 + 0.5
layer = ScalingLayer()
layer.optimize(points, points)
tpoints = layer.transform(points)
assert tpoints.shape == points.shape, (tpoints.shape, points.shape)
points2 = layer.untransform(tpoints)
assert tpoints.shape == points2.shape, (tpoints.shape,
points2.shape)
assert (points2 == points).all(), (points, tpoints, points2)
# transform a single point
points = points[0]
tpoints = layer.transform(points)
assert tpoints.shape == points.shape, (tpoints.shape, points.shape)
points2 = layer.untransform(tpoints)
assert tpoints.shape == points2.shape, (tpoints.shape,
points2.shape)
assert (points2 == points).all(), (points, tpoints, points2)
def test_wrap(plot=False):
np.random.seed(1)
for Npoints in 10, 100, 1000:
for wrapids in [[], [0], [1], [0, 1]]:
print("Npoints=%d wrapped_dims=%s" % (Npoints, wrapids))
#wrapids = np.array(wrapids)
points = np.random.normal(0.5, 0.01, size=(Npoints, 2))
for wrapi in wrapids:
points[:, wrapi] = np.fmod(points[:, wrapi] + 0.5, 1)
assert (points > 0).all(), points
assert (points < 1).all(), points
layer = ScalingLayer(wrapped_dims=wrapids)
layer.optimize(points, points)
tpoints = layer.transform(points)
assert tpoints.shape == points.shape, (tpoints.shape, points.shape)
points2 = layer.untransform(tpoints)
assert tpoints.shape == points2.shape, (tpoints.shape,
points2.shape)
if plot:
plt.subplot(1, 2, 1)
plt.scatter(points[:, 0], points[:, 1])
plt.scatter(points2[:, 0], points2[:, 1], marker='x')
plt.subplot(1, 2, 2)
plt.scatter(tpoints[:, 0], tpoints[:, 1])
plt.savefig("testtransform_%d_wrap%d.pdf" %
(Npoints, len(wrapids)),
bbox_inches='tight')
plt.close()
assert np.allclose(points2, points), (points, tpoints, points2)
layer = AffineLayer(wrapped_dims=wrapids)
layer.optimize(points, points)
tpoints = layer.transform(points)
assert tpoints.shape == points.shape, (tpoints.shape, points.shape)
points2 = layer.untransform(tpoints)
assert tpoints.shape == points2.shape, (tpoints.shape,
points2.shape)