def testParamToXFM(self):
def compare_matrices(par, ref):
if not np.allclose(par, ref):
print("Matrix mismatch:", ref, par)
return False
return True
ref = minc.xfm_identity_transform_par()
par_mat = minc.param_to_xfm(ref)
for i in range(3):
for r in [-10, -10, 10, 20]:
ref = minc.xfm_identity_transform_par()
ref.translations[i] = r
cmd = ["param2xfm", "-translation"] + [
str(j) for j in ref.translations
] + [self.tmp, "-clobber"]
check_call_out(cmd)
ref_mat = minc.read_xfm(self.tmp)
par_mat = minc.param_to_xfm(ref)
self.assertTrue(par_mat.lin)
self.assertFalse(par_mat.inv)
self.assertTrue(
compare_matrices(par_mat.trans, ref_mat[0].trans),
"Error in translations i={} r={}".format(i, r))
for i in range(3):
for r in [-10, -10, 10, 20]:
ref = minc.xfm_identity_transform_par()
ref.rotations[i] = r
cmd = ["param2xfm", "-rotations"
] + [str(j)
for j in ref.rotations] + [self.tmp, "-clobber"]
check_call_out(cmd)
ref_mat = minc.read_xfm(self.tmp)
par_mat = minc.param_to_xfm(ref)
self.assertTrue(par_mat.lin)
self.assertFalse(par_mat.inv)
self.assertTrue(
compare_matrices(par_mat.trans, ref_mat[0].trans),
"Error in rotations i={} r={}".format(i, r))
for i in range(3):
for r in [0.9, 1.1, 1.2, 1.3]:
ref = minc.xfm_identity_transform_par()
ref.scales[i] = r
cmd = ["param2xfm", "-scales"] + [str(j) for j in ref.scales
] + [self.tmp, "-clobber"]
check_call_out(cmd)
ref_mat = minc.read_xfm(self.tmp)
par_mat = minc.param_to_xfm(ref)
self.assertTrue(par_mat.lin)
self.assertFalse(par_mat.inv)
self.assertTrue(
compare_matrices(par_mat.trans, ref_mat[0].trans),
"Error in scales i={} r={}".format(i, r))
def test_xfm_components(self):
# TODO: add a test with nonlinear component
check_call_out(
["param2xfm", "-rotations", "30", "0", "0", self.tmp, "-clobber"])
x = minc.read_xfm(self.tmp)
N_lin, N_nl = minc.check_xfm_components(x)
self.assertEqual(N_lin, 1)
self.assertEqual(N_nl, 0)
r = minc.reduce_xfm_components(x)
self.assertEqual(r, x)
def xfmavg(inputs, output, verbose=False):
# TODO: handl inversion flag correctly
all_linear = True
all_nonlinear = True
input_xfms = []
for j in inputs:
x = minc.read_xfm(j)
if x[0].lin and len(x) == 1 and (not x[0].inv):
# this is a linear matrix
input_xfms.append(x[0])
else:
all_linear &= False
# strip identity matrixes
nl = []
_identity = np.asmatrix(np.identity(4))
_eps = 1e-6
for i in x:
if i.lin:
if scipy.linalg.norm(
_identity -
i.trans) > _eps: # this is non-identity matrix
all_nonlinear &= False
else:
if i.inv:
raise Exception(
"Trying to average inverted nonlinear transform")
nl.append(i)
if len(nl) != 1:
all_nonlinear &= False
else:
input_xfms.append(nl[0])
if all_linear:
acc = np.asmatrix(np.zeros([4, 4], dtype=np.complex))
for i in input_xfms:
acc += scipy.linalg.logm(i.trans)
acc /= len(input_xfms)
out_xfm = [minc.xfm_entry(True, False, scipy.linalg.expm(acc).real)]
minc.write_xfm(output, out_xfm)
elif all_nonlinear:
input_grids = []
for i in input_xfms:
input_grids.append(i.trans)
output_grid = output.rsplit('.xfm', 1)[0] + '_grid_0.mnc'
cmds = ['mincaverage', '-clob']
cmds.extend(input_grids)
cmds.append(output_grid)
do_cmd(cmds, verbose=verbose)
out_xfm = [minc.xfm_entry(False, False, output_grid)]
minc.write_xfm(output, out_xfm)
else:
raise Exception("Mixed XFM files provided as input")
def testXfmRead(self):
# generate xfm file first
check_call_out(
["param2xfm", "-rotations", "30", "0", "0", self.tmp, "-clobber"])
xfm = minc.read_xfm(self.tmp)
#print(xfm)
reference_matrix = np.array([[1.0, 0.0, 0.0, 0.0],
[0.0, 0.866025388240814, -0.5, 0.0],
[0.0, 0.5, 0.866025388240814, 0.0],
[0.0, 0.0, 0.0, 1.0]])
self.assertTrue(len(xfm) == 1)
self.assertTrue(xfm[0].lin)
self.assertTrue(np.allclose(reference_matrix, xfm[0].trans))
def testXfmToParam(self):
def compare_parameters(par, ref):
if not np.allclose(ref.rotations, par.rotations):
print("rotations mismatch:", ref.rotations, par.rotations)
return False
if not np.allclose(ref.translations, par.translations):
print("translations mismatch:", ref.translations,
par.translations)
return False
if not np.allclose(ref.scales, par.scales):
print("scales mismatch:", ref.translations, par.translations)
return False
if not np.allclose(ref.translations, par.translations):
print("translations mismatch:", ref.translations,
par.translations)
return False
if not np.allclose(ref.shears, par.shears):
print("shears mismatch:", ref.shears, par.shears)
return False
return True
for i in range(3):
for r in [-10, -10, 10, 20]:
ref = minc.xfm_identity_transform_par()
ref.rotations[i] = r
cmd = ["param2xfm", "-rotations"
] + [str(j)
for j in ref.rotations] + [self.tmp, "-clobber"]
check_call_out(cmd)
par = minc.xfm_to_param(minc.read_xfm(self.tmp))
self.assertTrue(compare_parameters(ref, par),
"Error in rotations i={} r={}".format(i, r))
for i in range(3):
for r in [-10, -10, 10, 20]:
ref = minc.xfm_identity_transform_par()
ref.translations[i] = r
cmd = ["param2xfm", "-translation"] + [
str(j) for j in ref.translations
] + [self.tmp, "-clobber"]
check_call_out(cmd)
par = minc.xfm_to_param(minc.read_xfm(self.tmp))
self.assertTrue(compare_parameters(ref, par),
"Error in translations i={} r={}".format(i, r))
for i in range(3):
for r in [0.9, 1.1, 1.2, 1.3]:
ref = minc.xfm_identity_transform_par()
ref.scales[i] = r
cmd = ["param2xfm", "-scales"] + [str(j) for j in ref.scales
] + [self.tmp, "-clobber"]
check_call_out(cmd)
par = minc.xfm_to_param(minc.read_xfm(self.tmp))
self.assertTrue(compare_parameters(ref, par),
"Error in scales i={} r={}".format(i, r))