def setUp(self):
"""Set 'self.align_data' to an empty instance of the AlignTensorData class."""
self.align_data = AlignTensorData('test')
class Test_align_tensor(TestCase):
"""Unit tests for the data.align_tensor relax module."""
def calc_objects(self, Axx, Ayy, Axy, Axz, Ayz):
"""Function for calculating the alignment tensor objects."""
# The parameter values.
Azz = - Axx - Ayy
Axxyy = Axx - Ayy
# Matrices.
tensor = array([[ Axx, Axy, Axz],
[ Axy, Ayy, Ayz],
[ Axz, Ayz, Azz]])
# Return the objects.
return Azz, Axxyy, tensor
def setUp(self):
"""Set 'self.align_data' to an empty instance of the AlignTensorData class."""
self.align_data = AlignTensorData('test')
def test_append_sim(self):
"""Test the appending of Monte Carlo simulation alignment tensor parameters.
The following parameters will be appended to empty lists:
- Axx: -16.6278 Hz
- Ayy: 6.13037 Hz
- Axy: 7.65639 Hz
- Axz: -1.89157 Hz
- Ayz: 19.2561 Hz
"""
# The MC sim parameter values.
Axx = -16.6278 / kappa() * 1.02e-10**3
Ayy = 6.13037 / kappa() * 1.02e-10**3
Axy = 7.65639 / kappa() * 1.02e-10**3
Axz = -1.89157 / kappa() * 1.02e-10**3
Ayz = 19.2561 / kappa() * 1.02e-10**3
# Set the number of MC sims.
self.align_data.set_sim_num(1)
# Set the values.
self.align_data.set(param='Axx', value=Axx, category='sim', sim_index=0)
self.align_data.set(param='Ayy', value=Ayy, category='sim', sim_index=0)
self.align_data.set(param='Axy', value=Axy, category='sim', sim_index=0)
self.align_data.set(param='Axz', value=Axz, category='sim', sim_index=0)
self.align_data.set(param='Ayz', value=Ayz, category='sim', sim_index=0)
# Test the set values.
self.assertEqual(self.align_data.Axx_sim[0], Axx)
self.assertEqual(self.align_data.Ayy_sim[0], Ayy)
self.assertEqual(self.align_data.Axy_sim[0], Axy)
self.assertEqual(self.align_data.Axz_sim[0], Axz)
self.assertEqual(self.align_data.Ayz_sim[0], Ayz)
# Calculate the diffusion tensor objects.
Azz, Axxyy, tensor = self.calc_objects(Axx, Ayy, Axy, Axz, Ayz)
# Test the automatically created values.
self.assertEqual(self.align_data.Azz_sim[0], Azz)
self.assertEqual(self.align_data.Axxyy_sim[0], Axxyy)
# Test the matrices.
self.assertEqual(self.align_data.A_sim[0].tostring(), tensor.tostring())
def test_set_Szz(self):
"""Test that the Szz parameter cannot be set."""
# Assert that a RelaxError occurs when Szz is set.
self.assertRaises(RelaxError, setattr, self.align_data, 'Szz', -23.0)
# Make sure that the Szz parameter has not been set.
self.assert_(not hasattr(self.align_data, 'Szz'))
def test_set_errors(self):
"""Test the setting of spheroidal diffusion tensor parameter errors.
The following parameter errors will be set:
- Axx: 0.3 Hz
- Ayy: 0.5 Hz
- Axy: 0.4 Hz
- Axz: 0.1 Hz
- Ayz: 0.2 Hz
"""
# The parameter errors.
Axx = 0.3 / kappa() * 1.02e-10**3
Ayy = 0.5 / kappa() * 1.02e-10**3
Axy = 0.4 / kappa() * 1.02e-10**3
Axz = 0.1 / kappa() * 1.02e-10**3
Ayz = 0.2 / kappa() * 1.02e-10**3
# Set the diffusion parameters.
self.align_data.set(param='Axx', value=Axx, category='err')
self.align_data.set(param='Ayy', value=Ayy, category='err')
self.align_data.set(param='Axy', value=Axy, category='err')
self.align_data.set(param='Axz', value=Axz, category='err')
self.align_data.set(param='Ayz', value=Ayz, category='err')
# Test the set values.
self.assertEqual(self.align_data.Axx_err, Axx)
self.assertEqual(self.align_data.Ayy_err, Ayy)
self.assertEqual(self.align_data.Axy_err, Axy)
self.assertEqual(self.align_data.Axz_err, Axz)
self.assertEqual(self.align_data.Ayz_err, Ayz)
# Calculate the diffusion tensor objects.
Azz, Axxyy, tensor = self.calc_objects(Axx, Ayy, Axy, Axz, Ayz)
# Test the automatically created values.
self.assertEqual(self.align_data.Azz_err, Azz)
self.assertEqual(self.align_data.Axxyy_err, Axxyy)
# Test the matrices.
self.assertEqual(self.align_data.A_err.tostring(), tensor.tostring())
def test_set_params(self):
"""Test the setting of alignment tensor parameters.
The following parameters will be set:
- Axx: -16.6278 Hz
- Ayy: 6.13037 Hz
- Axy: 7.65639 Hz
- Axz: -1.89157 Hz
- Ayz: 19.2561 Hz
"""
# The parameter values.
Axx = -16.6278 / kappa() * 1.02e-10**3
Ayy = 6.13037 / kappa() * 1.02e-10**3
Axy = 7.65639 / kappa() * 1.02e-10**3
Axz = -1.89157 / kappa() * 1.02e-10**3
Ayz = 19.2561 / kappa() * 1.02e-10**3
# Set the diffusion parameters.
self.align_data.set(param='Axx', value=Axx)
self.align_data.set(param='Ayy', value=Ayy)
self.align_data.set(param='Axy', value=Axy)
self.align_data.set(param='Axz', value=Axz)
self.align_data.set(param='Ayz', value=Ayz)
# Test the set values.
self.assertEqual(self.align_data.Axx, Axx)
self.assertEqual(self.align_data.Ayy, Ayy)
self.assertEqual(self.align_data.Axy, Axy)
self.assertEqual(self.align_data.Axz, Axz)
self.assertEqual(self.align_data.Ayz, Ayz)
# Calculate the diffusion tensor objects.
Azz, Axxyy, tensor = self.calc_objects(Axx, Ayy, Axy, Axz, Ayz)
# Test the automatically created values.
self.assertEqual(self.align_data.Azz, Azz)
self.assertEqual(self.align_data.Axxyy, Axxyy)
# Test the matrices.
self.assertEqual(self.align_data.A.tostring(), tensor.tostring())
def test_set_sim(self):
"""Test the setting of Monte Carlo simulation alignment tensor parameters.
Firstly the following parameters will be appended to empty lists:
- Axx: -16.6278 Hz
- Ayy: 6.13037 Hz
- Axy: 7.65639 Hz
- Axz: -1.89157 Hz
- Ayz: 19.2561 Hz
These MC sim values will then be explicity overwritten by setting the first elements of the
lists to:
- Axx: 0.3 Hz
- Ayy: 0.5 Hz
- Axy: 0.4 Hz
- Axz: 0.1 Hz
- Ayz: 0.2 Hz
"""
# Set the number of MC sims.
self.align_data.set_sim_num(1)
# Append the initial values.
self.align_data.set(param='Axx', value=-16.6278 / kappa() * 1.02e-10**3, category='sim', sim_index=0)
self.align_data.set(param='Ayy', value=6.13037 / kappa() * 1.02e-10**3, category='sim', sim_index=0)
self.align_data.set(param='Axy', value=7.65639 / kappa() * 1.02e-10**3, category='sim', sim_index=0)
self.align_data.set(param='Axz', value=-1.89157 / kappa() * 1.02e-10**3, category='sim', sim_index=0)
self.align_data.set(param='Ayz', value=19.2561 / kappa() * 1.02e-10**3, category='sim', sim_index=0)
# The new MC sim parameter values.
Axx = 0.3 / kappa() * 1.02e-10**3
Ayy = 0.5 / kappa() * 1.02e-10**3
Axy = 0.4 / kappa() * 1.02e-10**3
Axz = 0.1 / kappa() * 1.02e-10**3
Ayz = 0.2 / kappa() * 1.02e-10**3
# Set the MC sim parameter values (overwriting the initial values).
self.align_data.set(param='Axx', value=Axx, category='sim', sim_index=0)
self.align_data.set(param='Ayy', value=Ayy, category='sim', sim_index=0)
self.align_data.set(param='Axy', value=Axy, category='sim', sim_index=0)
self.align_data.set(param='Axz', value=Axz, category='sim', sim_index=0)
self.align_data.set(param='Ayz', value=Ayz, category='sim', sim_index=0)
# Test the set values.
self.assertEqual(self.align_data.Axx_sim[0], Axx)
self.assertEqual(self.align_data.Ayy_sim[0], Ayy)
self.assertEqual(self.align_data.Axy_sim[0], Axy)
self.assertEqual(self.align_data.Axz_sim[0], Axz)
self.assertEqual(self.align_data.Ayz_sim[0], Ayz)
# Calculate the diffusion tensor objects.
Azz, Axxyy, tensor = self.calc_objects(Axx, Ayy, Axy, Axz, Ayz)
# Test the automatically created values.
self.assertEqual(self.align_data.Azz_sim[0], Azz)
self.assertEqual(self.align_data.Axxyy_sim[0], Axxyy)
# Test the matrices.
self.assertEqual(self.align_data.A_sim[0].tostring(), tensor.tostring())
def test_set_Axx(self):
"""Test the setting of the Axx parameter."""
# Set the Axx value to 0.0001.
self.align_data.set(param='Axx', value=0.0001)
# Test that the Axx parameter has been set correctly.
self.assert_(hasattr(self.align_data, 'Axx'))
self.assertEqual(self.align_data.Axx, 0.0001)
class Test_align_tensor(TestCase):
"""Unit tests for the data.align_tensor relax module."""
def calc_objects(self, Axx, Ayy, Axy, Axz, Ayz):
"""Function for calculating the alignment tensor objects."""
# The parameter values.
Azz = - Axx - Ayy
Axxyy = Axx - Ayy
# Matrices.
tensor = array([[ Axx, Axy, Axz],
[ Axy, Ayy, Ayz],
[ Axz, Ayz, Azz]])
# Return the objects.
return Azz, Axxyy, tensor
def setUp(self):
"""Set 'self.align_data' to an empty instance of the AlignTensorData class."""
self.align_data = AlignTensorData('test')
def test_append_sim(self):
"""Test the appending of Monte Carlo simulation alignment tensor parameters.
The following parameters will be appended to empty lists:
- Axx: -16.6278 Hz
- Ayy: 6.13037 Hz
- Axy: 7.65639 Hz
- Axz: -1.89157 Hz
- Ayz: 19.2561 Hz
"""
# The MC sim parameter values.
Axx = -16.6278 / kappa() * 1.02e-10**3
Ayy = 6.13037 / kappa() * 1.02e-10**3
Axy = 7.65639 / kappa() * 1.02e-10**3
Axz = -1.89157 / kappa() * 1.02e-10**3
Ayz = 19.2561 / kappa() * 1.02e-10**3
# Set the number of MC sims.
self.align_data.set_sim_num(1)
# Set the values.
self.align_data.set(param='Axx', value=Axx, category='sim', sim_index=0)
self.align_data.set(param='Ayy', value=Ayy, category='sim', sim_index=0)
self.align_data.set(param='Axy', value=Axy, category='sim', sim_index=0)
self.align_data.set(param='Axz', value=Axz, category='sim', sim_index=0)
self.align_data.set(param='Ayz', value=Ayz, category='sim', sim_index=0)
# Test the set values.
self.assertEqual(self.align_data.Axx_sim[0], Axx)
self.assertEqual(self.align_data.Ayy_sim[0], Ayy)
self.assertEqual(self.align_data.Axy_sim[0], Axy)
self.assertEqual(self.align_data.Axz_sim[0], Axz)
self.assertEqual(self.align_data.Ayz_sim[0], Ayz)
# Calculate the diffusion tensor objects.
Azz, Axxyy, tensor = self.calc_objects(Axx, Ayy, Axy, Axz, Ayz)
# Test the automatically created values.
self.assertEqual(self.align_data.Azz_sim[0], Azz)
self.assertEqual(self.align_data.Axxyy_sim[0], Axxyy)
# Test the matrices.
self.assertEqual(self.align_data.A_sim[0].tostring(), tensor.tostring())
def test_irreducible_params(self):
"""Test the irreducible parameters {A-2, A-1, A0, A1, A2}.
This is to test if the Pales results can be matched. The example is::
DATA SAUPE_MATRIX S(zz) S(xx-yy) S(xy) S(xz) S(yz)
DATA SAUPE -1.2856e-04 -5.6870e-04 -3.1704e-04 3.5099e-04 -1.7937e-04
DATA IRREDUCIBLE_REP A0 A1R A1I A2R A2I
DATA IRREDUCIBLE -2.0380e-04 -4.5433e-04 -2.3218e-04 -3.6807e-04 4.1038e-04
DATA IRREDUCIBLE GENERAL_MAGNITUDE 1.0816e-03
"""
# From Pales (S(zz) S(xx-yy) S(xy) S(xz) S(yz))
Azz = 2.0 / 3.0 * -1.2856e-04
Axxyy = 2.0 / 3.0 * -5.6870e-04
Axy = 2.0 / 3.0 * -3.1704e-04
Axz = 2.0 / 3.0 * 3.5099e-04
Ayz = 2.0 / 3.0 * -1.7937e-04
# Parameter conversion.
Axx = (Axxyy - Azz) / 2.0
Ayy = (-Axxyy - Azz) / 2.0
# Set the values.
self.align_data.set(param='Axx', value=Axx)
self.align_data.set(param='Ayy', value=Ayy)
self.align_data.set(param='Axy', value=Axy)
self.align_data.set(param='Axz', value=Axz)
self.align_data.set(param='Ayz', value=Ayz)
# Pales equivalent printout.
print("Pales output:\n")
print("DATA SAUPE_MATRIX S(zz) S(xx-yy) S(xy) S(xz) S(yz)")
print("DATA SAUPE -1.2856e-04 -5.6870e-04 -3.1704e-04 3.5099e-04 -1.7937e-04")
print("")
print("DATA IRREDUCIBLE_REP A0 A1R A1I A2R A2I ")
print("DATA IRREDUCIBLE -2.0380e-04 -4.5433e-04 -2.3218e-04 -3.6807e-04 4.1038e-04")
print("DATA IRREDUCIBLE GENERAL_MAGNITUDE 1.0816e-03")
print("")
print("Calculated values:\n")
print("A0: %15.4e" % self.align_data.A0)
print("A1: %15.4e %11.4ei" % (self.align_data.A1.real, self.align_data.A1.imag))
print("Am1: %15.4e %11.4ei" % (self.align_data.Am1.real, self.align_data.Am1.imag))
print("A2: %15.4e %11.4ei" % (self.align_data.A2.real, self.align_data.A2.imag))
print("Am2: %15.4e %11.4ei" % (self.align_data.Am2.real, self.align_data.Am2.imag))
# Check that the values match Pales (guessing that Pales is using the negative indices).
self.assertAlmostEqual(self.align_data.A0, -2.0380e-04)
self.assertAlmostEqual(self.align_data.A1.real, 4.5433e-04)
self.assertAlmostEqual(self.align_data.A1.imag, -2.3218e-04)
self.assertAlmostEqual(self.align_data.Am1.real, -4.5433e-04)
self.assertAlmostEqual(self.align_data.Am1.imag, -2.3218e-04)
self.assertAlmostEqual(self.align_data.A2.real, -3.6807e-04)
self.assertAlmostEqual(self.align_data.A2.imag, -4.1038e-04)
self.assertAlmostEqual(self.align_data.Am2.real, -3.6807e-04)
self.assertAlmostEqual(self.align_data.Am2.imag, 4.1038e-04)
def test_set_Szz(self):
"""Test that the Szz parameter cannot be set."""
# Assert that a RelaxError occurs when Szz is set.
self.assertRaises(RelaxError, setattr, self.align_data, 'Szz', -23.0)
# Make sure that the Szz parameter has not been set.
self.assert_(not hasattr(self.align_data, 'Szz'))
def test_set_errors(self):
"""Test the setting of spheroidal diffusion tensor parameter errors.
The following parameter errors will be set:
- Axx: 0.3 Hz
- Ayy: 0.5 Hz
- Axy: 0.4 Hz
- Axz: 0.1 Hz
- Ayz: 0.2 Hz
"""
# The parameter errors.
Axx = 0.3 / kappa() * 1.02e-10**3
Ayy = 0.5 / kappa() * 1.02e-10**3
Axy = 0.4 / kappa() * 1.02e-10**3
Axz = 0.1 / kappa() * 1.02e-10**3
Ayz = 0.2 / kappa() * 1.02e-10**3
# Set the diffusion parameters.
self.align_data.set(param='Axx', value=Axx, category='err')
self.align_data.set(param='Ayy', value=Ayy, category='err')
self.align_data.set(param='Axy', value=Axy, category='err')
self.align_data.set(param='Axz', value=Axz, category='err')
self.align_data.set(param='Ayz', value=Ayz, category='err')
# Test the set values.
self.assertEqual(self.align_data.Axx_err, Axx)
self.assertEqual(self.align_data.Ayy_err, Ayy)
self.assertEqual(self.align_data.Axy_err, Axy)
self.assertEqual(self.align_data.Axz_err, Axz)
self.assertEqual(self.align_data.Ayz_err, Ayz)
# Calculate the diffusion tensor objects.
Azz, Axxyy, tensor = self.calc_objects(Axx, Ayy, Axy, Axz, Ayz)
# Test the automatically created values.
self.assertEqual(self.align_data.Azz_err, Azz)
self.assertEqual(self.align_data.Axxyy_err, Axxyy)
# Test the matrices.
self.assertEqual(self.align_data.A_err.tostring(), tensor.tostring())
def test_set_params(self):
"""Test the setting of alignment tensor parameters.
The following parameters will be set:
- Axx: -16.6278 Hz
- Ayy: 6.13037 Hz
- Axy: 7.65639 Hz
- Axz: -1.89157 Hz
- Ayz: 19.2561 Hz
"""
# The parameter values.
Axx = -16.6278 / kappa() * 1.02e-10**3
Ayy = 6.13037 / kappa() * 1.02e-10**3
Axy = 7.65639 / kappa() * 1.02e-10**3
Axz = -1.89157 / kappa() * 1.02e-10**3
Ayz = 19.2561 / kappa() * 1.02e-10**3
# Set the diffusion parameters.
self.align_data.set(param='Axx', value=Axx)
self.align_data.set(param='Ayy', value=Ayy)
self.align_data.set(param='Axy', value=Axy)
self.align_data.set(param='Axz', value=Axz)
self.align_data.set(param='Ayz', value=Ayz)
# Test the set values.
self.assertEqual(self.align_data.Axx, Axx)
self.assertEqual(self.align_data.Ayy, Ayy)
self.assertEqual(self.align_data.Axy, Axy)
self.assertEqual(self.align_data.Axz, Axz)
self.assertEqual(self.align_data.Ayz, Ayz)
# Calculate the diffusion tensor objects.
Azz, Axxyy, tensor = self.calc_objects(Axx, Ayy, Axy, Axz, Ayz)
# Test the automatically created values.
self.assertEqual(self.align_data.Azz, Azz)
self.assertEqual(self.align_data.Axxyy, Axxyy)
# Test the matrices.
self.assertEqual(self.align_data.A.tostring(), tensor.tostring())
def test_set_sim(self):
"""Test the setting of Monte Carlo simulation alignment tensor parameters.
Firstly the following parameters will be appended to empty lists:
- Axx: -16.6278 Hz
- Ayy: 6.13037 Hz
- Axy: 7.65639 Hz
- Axz: -1.89157 Hz
- Ayz: 19.2561 Hz
These MC sim values will then be explicity overwritten by setting the first elements of the
lists to:
- Axx: 0.3 Hz
- Ayy: 0.5 Hz
- Axy: 0.4 Hz
- Axz: 0.1 Hz
- Ayz: 0.2 Hz
"""
# Set the number of MC sims.
self.align_data.set_sim_num(1)
# Append the initial values.
self.align_data.set(param='Axx', value=-16.6278 / kappa() * 1.02e-10**3, category='sim', sim_index=0)
self.align_data.set(param='Ayy', value=6.13037 / kappa() * 1.02e-10**3, category='sim', sim_index=0)
self.align_data.set(param='Axy', value=7.65639 / kappa() * 1.02e-10**3, category='sim', sim_index=0)
self.align_data.set(param='Axz', value=-1.89157 / kappa() * 1.02e-10**3, category='sim', sim_index=0)
self.align_data.set(param='Ayz', value=19.2561 / kappa() * 1.02e-10**3, category='sim', sim_index=0)
# The new MC sim parameter values.
Axx = 0.3 / kappa() * 1.02e-10**3
Ayy = 0.5 / kappa() * 1.02e-10**3
Axy = 0.4 / kappa() * 1.02e-10**3
Axz = 0.1 / kappa() * 1.02e-10**3
Ayz = 0.2 / kappa() * 1.02e-10**3
# Set the MC sim parameter values (overwriting the initial values).
self.align_data.set(param='Axx', value=Axx, category='sim', sim_index=0)
self.align_data.set(param='Ayy', value=Ayy, category='sim', sim_index=0)
self.align_data.set(param='Axy', value=Axy, category='sim', sim_index=0)
self.align_data.set(param='Axz', value=Axz, category='sim', sim_index=0)
self.align_data.set(param='Ayz', value=Ayz, category='sim', sim_index=0)
# Test the set values.
self.assertEqual(self.align_data.Axx_sim[0], Axx)
self.assertEqual(self.align_data.Ayy_sim[0], Ayy)
self.assertEqual(self.align_data.Axy_sim[0], Axy)
self.assertEqual(self.align_data.Axz_sim[0], Axz)
self.assertEqual(self.align_data.Ayz_sim[0], Ayz)
# Calculate the diffusion tensor objects.
Azz, Axxyy, tensor = self.calc_objects(Axx, Ayy, Axy, Axz, Ayz)
# Test the automatically created values.
self.assertEqual(self.align_data.Azz_sim[0], Azz)
self.assertEqual(self.align_data.Axxyy_sim[0], Axxyy)
# Test the matrices.
self.assertEqual(self.align_data.A_sim[0].tostring(), tensor.tostring())
def test_set_Axx(self):
"""Test the setting of the Axx parameter."""
# Set the Axx value to 0.0001.
self.align_data.set(param='Axx', value=0.0001)
# Test that the Axx parameter has been set correctly.
self.assert_(hasattr(self.align_data, 'Axx'))
self.assertEqual(self.align_data.Axx, 0.0001)
def setUp(self):
"""Set 'self.align_data' to an empty instance of the AlignTensorData class."""
self.align_data = AlignTensorData('test')
class Test_align_tensor(TestCase):
"""Unit tests for the data.align_tensor relax module."""
def calc_objects(self, Axx, Ayy, Axy, Axz, Ayz):
"""Function for calculating the alignment tensor objects."""
# The parameter values.
Azz = - Axx - Ayy
Axxyy = Axx - Ayy
# Matrices.
tensor = array([[ Axx, Axy, Axz],
[ Axy, Ayy, Ayz],
[ Axz, Ayz, Azz]])
# Return the objects.
return Azz, Axxyy, tensor
def setUp(self):
"""Set 'self.align_data' to an empty instance of the AlignTensorData class."""
self.align_data = AlignTensorData('test')
def test_append_sim(self):
"""Test the appending of Monte Carlo simulation alignment tensor parameters.
The following parameters will be appended to empty lists:
- Axx: -16.6278 Hz
- Ayy: 6.13037 Hz
- Axy: 7.65639 Hz
- Axz: -1.89157 Hz
- Ayz: 19.2561 Hz
"""
# The MC sim parameter values.
Axx = -16.6278 / kappa() * 1.02e-10**3
Ayy = 6.13037 / kappa() * 1.02e-10**3
Axy = 7.65639 / kappa() * 1.02e-10**3
Axz = -1.89157 / kappa() * 1.02e-10**3
Ayz = 19.2561 / kappa() * 1.02e-10**3
# Set the number of MC sims.
self.align_data.set_sim_num(1)
# Set the values.
self.align_data.set(param='Axx', value=Axx, category='sim', sim_index=0)
self.align_data.set(param='Ayy', value=Ayy, category='sim', sim_index=0)
self.align_data.set(param='Axy', value=Axy, category='sim', sim_index=0)
self.align_data.set(param='Axz', value=Axz, category='sim', sim_index=0)
self.align_data.set(param='Ayz', value=Ayz, category='sim', sim_index=0)
# Test the set values.
self.assertEqual(self.align_data.Axx_sim[0], Axx)
self.assertEqual(self.align_data.Ayy_sim[0], Ayy)
self.assertEqual(self.align_data.Axy_sim[0], Axy)
self.assertEqual(self.align_data.Axz_sim[0], Axz)
self.assertEqual(self.align_data.Ayz_sim[0], Ayz)
# Calculate the diffusion tensor objects.
Azz, Axxyy, tensor = self.calc_objects(Axx, Ayy, Axy, Axz, Ayz)
# Test the automatically created values.
self.assertEqual(self.align_data.Azz_sim[0], Azz)
self.assertEqual(self.align_data.Axxyy_sim[0], Axxyy)
# Test the matrices.
self.assertEqual(self.align_data.A_sim[0].tostring(), tensor.tostring())
def test_irreducible_params(self):
"""Test the irreducible parameters {A-2, A-1, A0, A1, A2}.
This is to test if the Pales results can be matched. The example is::
DATA SAUPE_MATRIX S(zz) S(xx-yy) S(xy) S(xz) S(yz)
DATA SAUPE -1.2856e-04 -5.6870e-04 -3.1704e-04 3.5099e-04 -1.7937e-04
DATA IRREDUCIBLE_REP A0 A1R A1I A2R A2I
DATA IRREDUCIBLE -2.0380e-04 -4.5433e-04 -2.3218e-04 -3.6807e-04 4.1038e-04
DATA IRREDUCIBLE GENERAL_MAGNITUDE 1.0816e-03
"""
# From Pales (S(zz) S(xx-yy) S(xy) S(xz) S(yz))
Azz = 2.0 / 3.0 * -1.2856e-04
Axxyy = 2.0 / 3.0 * -5.6870e-04
Axy = 2.0 / 3.0 * -3.1704e-04
Axz = 2.0 / 3.0 * 3.5099e-04
Ayz = 2.0 / 3.0 * -1.7937e-04
# Parameter conversion.
Axx = (Axxyy - Azz) / 2.0
Ayy = (-Axxyy - Azz) / 2.0
# Set the values.
self.align_data.set(param='Axx', value=Axx)
self.align_data.set(param='Ayy', value=Ayy)
self.align_data.set(param='Axy', value=Axy)
self.align_data.set(param='Axz', value=Axz)
self.align_data.set(param='Ayz', value=Ayz)
# Pales equivalent printout.
print("Pales output:\n")
print("DATA SAUPE_MATRIX S(zz) S(xx-yy) S(xy) S(xz) S(yz)")
print("DATA SAUPE -1.2856e-04 -5.6870e-04 -3.1704e-04 3.5099e-04 -1.7937e-04")
print("")
print("DATA IRREDUCIBLE_REP A0 A1R A1I A2R A2I ")
print("DATA IRREDUCIBLE -2.0380e-04 -4.5433e-04 -2.3218e-04 -3.6807e-04 4.1038e-04")
print("DATA IRREDUCIBLE GENERAL_MAGNITUDE 1.0816e-03")
print("")
print("Calculated values:\n")
print("A0: %15.4e" % self.align_data.A0)
print("A1: %15.4e %11.4ei" % (self.align_data.A1.real, self.align_data.A1.imag))
print("Am1: %15.4e %11.4ei" % (self.align_data.Am1.real, self.align_data.Am1.imag))
print("A2: %15.4e %11.4ei" % (self.align_data.A2.real, self.align_data.A2.imag))
print("Am2: %15.4e %11.4ei" % (self.align_data.Am2.real, self.align_data.Am2.imag))
# Check that the values match Pales (guessing that Pales is using the negative indices).
self.assertAlmostEqual(self.align_data.A0, -2.0380e-04)
self.assertAlmostEqual(self.align_data.A1.real, 4.5433e-04)
self.assertAlmostEqual(self.align_data.A1.imag, -2.3218e-04)
self.assertAlmostEqual(self.align_data.Am1.real, -4.5433e-04)
self.assertAlmostEqual(self.align_data.Am1.imag, -2.3218e-04)
self.assertAlmostEqual(self.align_data.A2.real, -3.6807e-04)
self.assertAlmostEqual(self.align_data.A2.imag, -4.1038e-04)
self.assertAlmostEqual(self.align_data.Am2.real, -3.6807e-04)
self.assertAlmostEqual(self.align_data.Am2.imag, 4.1038e-04)
def test_set_Szz(self):
"""Test that the Szz parameter cannot be set."""
# Assert that a RelaxError occurs when Szz is set.
self.assertRaises(RelaxError, setattr, self.align_data, 'Szz', -23.0)
# Make sure that the Szz parameter has not been set.
self.assert_(not hasattr(self.align_data, 'Szz'))
def test_set_errors(self):
"""Test the setting of spheroidal diffusion tensor parameter errors.
The following parameter errors will be set:
- Axx: 0.3 Hz
- Ayy: 0.5 Hz
- Axy: 0.4 Hz
- Axz: 0.1 Hz
- Ayz: 0.2 Hz
"""
# The parameter errors.
Axx = 0.3 / kappa() * 1.02e-10**3
Ayy = 0.5 / kappa() * 1.02e-10**3
Axy = 0.4 / kappa() * 1.02e-10**3
Axz = 0.1 / kappa() * 1.02e-10**3
Ayz = 0.2 / kappa() * 1.02e-10**3
# Set the diffusion parameters.
self.align_data.set(param='Axx', value=Axx, category='err')
self.align_data.set(param='Ayy', value=Ayy, category='err')
self.align_data.set(param='Axy', value=Axy, category='err')
self.align_data.set(param='Axz', value=Axz, category='err')
self.align_data.set(param='Ayz', value=Ayz, category='err')
# Test the set values.
self.assertEqual(self.align_data.Axx_err, Axx)
self.assertEqual(self.align_data.Ayy_err, Ayy)
self.assertEqual(self.align_data.Axy_err, Axy)
self.assertEqual(self.align_data.Axz_err, Axz)
self.assertEqual(self.align_data.Ayz_err, Ayz)
# Calculate the diffusion tensor objects.
Azz, Axxyy, tensor = self.calc_objects(Axx, Ayy, Axy, Axz, Ayz)
# Test the automatically created values.
self.assertEqual(self.align_data.Azz_err, Azz)
self.assertEqual(self.align_data.Axxyy_err, Axxyy)
# Test the matrices.
self.assertEqual(self.align_data.A_err.tostring(), tensor.tostring())
def test_set_params(self):
"""Test the setting of alignment tensor parameters.
The following parameters will be set:
- Axx: -16.6278 Hz
- Ayy: 6.13037 Hz
- Axy: 7.65639 Hz
- Axz: -1.89157 Hz
- Ayz: 19.2561 Hz
"""
# The parameter values.
Axx = -16.6278 / kappa() * 1.02e-10**3
Ayy = 6.13037 / kappa() * 1.02e-10**3
Axy = 7.65639 / kappa() * 1.02e-10**3
Axz = -1.89157 / kappa() * 1.02e-10**3
Ayz = 19.2561 / kappa() * 1.02e-10**3
# Set the diffusion parameters.
self.align_data.set(param='Axx', value=Axx)
self.align_data.set(param='Ayy', value=Ayy)
self.align_data.set(param='Axy', value=Axy)
self.align_data.set(param='Axz', value=Axz)
self.align_data.set(param='Ayz', value=Ayz)
# Test the set values.
self.assertEqual(self.align_data.Axx, Axx)
self.assertEqual(self.align_data.Ayy, Ayy)
self.assertEqual(self.align_data.Axy, Axy)
self.assertEqual(self.align_data.Axz, Axz)
self.assertEqual(self.align_data.Ayz, Ayz)
# Calculate the diffusion tensor objects.
Azz, Axxyy, tensor = self.calc_objects(Axx, Ayy, Axy, Axz, Ayz)
# Test the automatically created values.
self.assertEqual(self.align_data.Azz, Azz)
self.assertEqual(self.align_data.Axxyy, Axxyy)
# Test the matrices.
self.assertEqual(self.align_data.A.tostring(), tensor.tostring())
def test_set_sim(self):
"""Test the setting of Monte Carlo simulation alignment tensor parameters.
Firstly the following parameters will be appended to empty lists:
- Axx: -16.6278 Hz
- Ayy: 6.13037 Hz
- Axy: 7.65639 Hz
- Axz: -1.89157 Hz
- Ayz: 19.2561 Hz
These MC sim values will then be explicity overwritten by setting the first elements of the
lists to:
- Axx: 0.3 Hz
- Ayy: 0.5 Hz
- Axy: 0.4 Hz
- Axz: 0.1 Hz
- Ayz: 0.2 Hz
"""
# Set the number of MC sims.
self.align_data.set_sim_num(1)
# Append the initial values.
self.align_data.set(param='Axx', value=-16.6278 / kappa() * 1.02e-10**3, category='sim', sim_index=0)
self.align_data.set(param='Ayy', value=6.13037 / kappa() * 1.02e-10**3, category='sim', sim_index=0)
self.align_data.set(param='Axy', value=7.65639 / kappa() * 1.02e-10**3, category='sim', sim_index=0)
self.align_data.set(param='Axz', value=-1.89157 / kappa() * 1.02e-10**3, category='sim', sim_index=0)
self.align_data.set(param='Ayz', value=19.2561 / kappa() * 1.02e-10**3, category='sim', sim_index=0)
# The new MC sim parameter values.
Axx = 0.3 / kappa() * 1.02e-10**3
Ayy = 0.5 / kappa() * 1.02e-10**3
Axy = 0.4 / kappa() * 1.02e-10**3
Axz = 0.1 / kappa() * 1.02e-10**3
Ayz = 0.2 / kappa() * 1.02e-10**3
# Set the MC sim parameter values (overwriting the initial values).
self.align_data.set(param='Axx', value=Axx, category='sim', sim_index=0)
self.align_data.set(param='Ayy', value=Ayy, category='sim', sim_index=0)
self.align_data.set(param='Axy', value=Axy, category='sim', sim_index=0)
self.align_data.set(param='Axz', value=Axz, category='sim', sim_index=0)
self.align_data.set(param='Ayz', value=Ayz, category='sim', sim_index=0)
# Test the set values.
self.assertEqual(self.align_data.Axx_sim[0], Axx)
self.assertEqual(self.align_data.Ayy_sim[0], Ayy)
self.assertEqual(self.align_data.Axy_sim[0], Axy)
self.assertEqual(self.align_data.Axz_sim[0], Axz)
self.assertEqual(self.align_data.Ayz_sim[0], Ayz)
# Calculate the diffusion tensor objects.
Azz, Axxyy, tensor = self.calc_objects(Axx, Ayy, Axy, Axz, Ayz)
# Test the automatically created values.
self.assertEqual(self.align_data.Azz_sim[0], Azz)
self.assertEqual(self.align_data.Axxyy_sim[0], Axxyy)
# Test the matrices.
self.assertEqual(self.align_data.A_sim[0].tostring(), tensor.tostring())
def test_set_Axx(self):
"""Test the setting of the Axx parameter."""
# Set the Axx value to 0.0001.
self.align_data.set(param='Axx', value=0.0001)
# Test that the Axx parameter has been set correctly.
self.assert_(hasattr(self.align_data, 'Axx'))
self.assertEqual(self.align_data.Axx, 0.0001)