def test_sample_all_blocks(self, verbose=False):
data, XYZ, mask, XYZvol, vardata, signal = make_data(n=20, dim=20, r=3, mdim=15, maskdim=15, amplitude=5, noise=1, jitter=1, activation=True)
D = df.displacement_field(XYZ, sigma=2.5, n=data.shape[0], mask=mask)
for i in xrange(data.shape[0]):
if verbose:
print 'sampling field', i
U, V, W, I = D.sample_all_blocks(1e-2)
D.U[:, i] = U
D.V[:, i] = V
D.W[:, i] = W
D.I[i] = I
def test_sample_prior(self, verbose=False):
data, XYZ, mask, XYZvol, vardata, signal = make_data(n=20, dim=20, r=3, mdim=15, maskdim=15, amplitude=5, noise=1, jitter=1, activation=True)
D = df.displacement_field(XYZ, sigma=2.5, n=data.shape[0], mask=mask)
B = len(D.block)
for b in np.random.permutation(range(B)):
for i in xrange(data.shape[0]):
if verbose:
print 'sampling field', i, 'block', b
U, V, L, W, I = D.sample(i, b, 'prior', 1)
block = D.block[b]
D.U[:, i, b] = U
D.V[:, i, block] = V
D.W[:, i, L] = W
D.I[i, L] = I
