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_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_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_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_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_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_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())