def test_residue_loop(self):
"""Test the proper operation of the residue loop with residue selection.
The function tested is pipe_control.mol_res_spin.residue_loop().
"""
# Loop over the residues.
for res in mol_res_spin.residue_loop('#Ap4Aase:Glu'):
# Test the selection.
self.assertEqual(res.num, 2)
# Test loop length.
self.assertEqual(len(list(mol_res_spin.residue_loop('#Ap4Aase:Glu'))), 1)
def test_residue_loop(self):
"""Test the proper operation of the residue loop with residue selection.
The function tested is pipe_control.mol_res_spin.residue_loop().
"""
# Loop over the residues.
for res in mol_res_spin.residue_loop('#Ap4Aase:Glu'):
# Test the selection.
self.assertEqual(res.num, 2)
# Test loop length.
self.assertEqual(len(list(mol_res_spin.residue_loop('#Ap4Aase:Glu'))),
1)
def test_calc(self):
"""The spectral density calculation test."""
# Execute the script.
self.script_exec(status.install_path + sep + 'test_suite' + sep +
'system_tests' + sep + 'scripts' + sep +
'jw_mapping_calc_test.py')
# Correct jw values.
j0 = [4.0703318681008998e-09, 3.7739393907014834e-09]
jwx = [1.8456254300773903e-10, 1.6347516082378241e-10]
jwh = [1.5598167512718012e-12, 2.9480536599037041e-12]
# Loop over residues.
index = 0
for res in residue_loop():
# Residues -2 and -1 have data.
if res.num == -2 or res.num == -1:
self.assert_(res.spin[0].select)
self.assertAlmostEqual(res.spin[0].j0 * 1e9, j0[index] * 1e9)
self.assertAlmostEqual(res.spin[0].jwh * 1e10,
jwh[index] * 1e10)
self.assertAlmostEqual(res.spin[0].jwx * 1e12,
jwx[index] * 1e12)
index = index + 1
# Other residues have insufficient data.
else:
self.assert_(not res.spin[0].select)
def test_calc(self):
"""The consistency testing calculation test."""
# Execute the script.
self.script_exec(status.install_path + sep+'test_suite'+sep+'system_tests'+sep+'scripts'+sep+'consistency_tests_calc_test.py')
# Correct consistency functions values.
j0 = [4.0703318681008998e-09, 3.7739393907014834e-09]
f_eta = [0.20413244790407614, 0.18898977395296815]
f_r2 = [2.0482909381655862e-09, 1.8998154021753067e-09]
# Loop over residues.
index = 0
for res in residue_loop():
# Residues -2 and -1 have data.
if res.num == -2 or res.num == -1:
self.assert_(res.spin[0].select)
self.assertAlmostEqual(res.spin[0].j0, j0[index])
self.assertAlmostEqual(res.spin[0].f_eta, f_eta[index])
self.assertAlmostEqual(res.spin[0].f_r2, f_r2[index])
index = index + 1
# Other residues have insufficient data.
else:
self.assert_(not res.spin[0].select)
def test_calc(self):
"""The consistency testing calculation test."""
# Execute the script.
self.script_exec(status.install_path + sep+'test_suite'+sep+'system_tests'+sep+'scripts'+sep+'consistency_tests_calc_test.py')
# Correct consistency functions values.
j0 = [4.0703318681008998e-09, 3.7739393907014834e-09]
f_eta = [0.20413244790407614, 0.18898977395296815]
f_r2 = [2.0482909381655862e-09, 1.8998154021753067e-09]
# Loop over residues.
index = 0
for res in residue_loop():
# Residues -2 and -1 have data.
if res.num == -2 or res.num == -1:
self.assert_(res.spin[0].select)
self.assertAlmostEqual(res.spin[0].j0, j0[index])
self.assertAlmostEqual(res.spin[0].f_eta, f_eta[index])
self.assertAlmostEqual(res.spin[0].f_r2, f_r2[index])
index = index + 1
# Other residues have insufficient data.
else:
self.assert_(not res.spin[0].select)
def test_calc(self):
"""The spectral density calculation test."""
# Execute the script.
self.script_exec(status.install_path + sep+'test_suite'+sep+'system_tests'+sep+'scripts'+sep+'jw_mapping_calc_test.py')
# Correct jw values.
j0 = [4.0703318681008998e-09, 3.7739393907014834e-09]
jwx = [1.8456254300773903e-10, 1.6347516082378241e-10]
jwh = [1.5598167512718012e-12, 2.9480536599037041e-12]
# Loop over residues.
index = 0
for res in residue_loop():
# Residues -2 and -1 have data.
if res.num == -2 or res.num == -1:
self.assert_(res.spin[0].select)
self.assertAlmostEqual(res.spin[0].j0 * 1e9, j0[index] * 1e9)
self.assertAlmostEqual(res.spin[0].jwh * 1e10, jwh[index] * 1e10)
self.assertAlmostEqual(res.spin[0].jwx * 1e12, jwx[index] * 1e12)
index = index + 1
# Other residues have insufficient data.
else:
self.assert_(not res.spin[0].select)
def test_set_value(self):
"""The user function value.set()."""
# Execute the script.
self.script_exec(status.install_path + sep+'test_suite'+sep+'system_tests'+sep+'scripts'+sep+'jw_mapping_set_value.py')
# Loop over residues.
for res in residue_loop():
self.assertAlmostEqual(res.spin[0].csa, N15_CSA)
def test_set_value(self):
"""The user function value.set()."""
# Execute the script.
self.script_exec(status.install_path + sep+'test_suite'+sep+'system_tests'+sep+'scripts'+sep+'consistency_tests_set_value.py')
# Loop over residues.
for res in residue_loop():
self.assertAlmostEqual(res.spin[0].csa, N15_CSA)
def fixme_test_boolean_parenthesis_selection(self):
"""Test complex boolean mol-res-spin selections with parenthesis."""
# The selection loop:
sel = list(mol_res_spin.residue_loop("(#Ap4Aase & :Pro) | (#RNA & :-4)"))
# Test:
self.assertEqual(len(sel), 2)
for res in sel:
self.assert_(res.num in [-4, 4])
def test_boolean_and_selection(self):
"""Test boolean and in mol-res-spin selections."""
# The selection loop:
sel = list(mol_res_spin.residue_loop("#Ap4Aase:4 & :Pro"))
# Test:
self.assertEqual(len(sel), 1)
for res in sel:
self.assert_(res.name == "Pro" and res.num == 4)
def test_boolean_and_selection(self):
"""Test boolean and in mol-res-spin selections."""
# The selection loop:
sel = list(mol_res_spin.residue_loop("#Ap4Aase:4 & :Pro"))
# Test:
self.assertEqual(len(sel), 1)
for res in sel:
self.assert_(res.name == "Pro" and res.num == 4)
def fixme_test_boolean_parenthesis_selection(self):
"""Test complex boolean mol-res-spin selections with parenthesis."""
# The selection loop:
sel = list(
mol_res_spin.residue_loop("(#Ap4Aase & :Pro) | (#RNA & :-4)"))
# Test:
self.assertEqual(len(sel), 2)
for res in sel:
self.assert_(res.num in [-4, 4])
def test_boolean_complex_selection(self):
"""Test complex boolean mol-res-spin selections."""
# The residue selection loop.
sel = list(mol_res_spin.residue_loop("#Ap4Aase:4 & :Pro | #RNA"))
# Residue names and numbers.
names = ['Pro', None, None]
numbers = [4, -5, -4]
# The residues.
self.assertEqual(len(sel), 3)
for i in range(3):
self.assertEqual(sel[i].name, names[i])
self.assertEqual(sel[i].num, numbers[i])
def test_boolean_complex_selection(self):
"""Test complex boolean mol-res-spin selections."""
# The residue selection loop.
sel = list(mol_res_spin.residue_loop("#Ap4Aase:4 & :Pro | #RNA"))
# Residue names and numbers.
names = ['Pro', None, None]
numbers = [4, -5, -4]
# The residues.
self.assertEqual(len(sel), 3)
for i in range(3):
self.assertEqual(sel[i].name, names[i])
self.assertEqual(sel[i].num, numbers[i])
def test_residue_loop_no_data(self):
"""Test the proper operation of the residue loop when no data is present.
The function tested is pipe_control.mol_res_spin.residue_loop().
"""
# Reset relax.
reset()
# Add a data pipe to the data store.
ds.add(pipe_name='orig', pipe_type='mf')
# Loop over the residues.
i = 0
for residue in mol_res_spin.residue_loop():
i = i + 1
# Test loop length.
self.assertEqual(i, 0)
def test_residue_loop_no_data(self):
"""Test the proper operation of the residue loop when no data is present.
The function tested is pipe_control.mol_res_spin.residue_loop().
"""
# Reset relax.
reset()
# Add a data pipe to the data store.
ds.add(pipe_name='orig', pipe_type='mf')
# Loop over the residues.
i = 0
for residue in mol_res_spin.residue_loop():
i = i + 1
# Test loop length.
self.assertEqual(i, 0)
def test_residue_loop_no_selection(self):
"""Test the proper operation of the residue loop when no selection is present.
The function tested is pipe_control.mol_res_spin.residue_loop().
"""
# Spin data.
num = [1, 2, 4, -5, -4]
name = [None, 'Glu', 'Pro', None, None]
# Loop over the residues.
i = 0
for res in mol_res_spin.residue_loop():
# Test the residue numbers.
self.assertEqual(res.num, num[i])
# Test the residue names.
self.assertEqual(res.name, name[i])
# Increment i.
i = i + 1
# Test loop length.
self.assertEqual(i, 5)
def test_residue_loop_no_selection(self):
"""Test the proper operation of the residue loop when no selection is present.
The function tested is pipe_control.mol_res_spin.residue_loop().
"""
# Spin data.
num = [1, 2, 4, -5, -4]
name = [None, 'Glu', 'Pro', None, None]
# Loop over the residues.
i = 0
for res in mol_res_spin.residue_loop():
# Test the residue numbers.
self.assertEqual(res.num, num[i])
# Test the residue names.
self.assertEqual(res.name, name[i])
# Increment i.
i = i + 1
# Test loop length.
self.assertEqual(i, 5)
def fail_test():
for residue in mol_res_spin.residue_loop():
pass
def create_script(file, model_type, algor):
"""Create the Dasha script file.
@param file: The opened file descriptor.
@type file: file object
@param model_type: The model-free model type.
@type model_type: str
@param algor: The optimisation algorithm to use. This can be the Levenberg-Marquardt algorithm 'LM' or the Newton-Raphson algorithm 'NR'.
@type algor: str
"""
# Delete all data.
file.write("# Delete all data.\n")
file.write("del 1 10000\n")
# Nucleus type.
file.write("\n# Nucleus type.\n")
nucleus = None
for spin in spin_loop():
# Skip protons.
if spin.isotope == '1H':
continue
# Can only handle one spin type.
if nucleus and spin.isotope != nucleus:
raise RelaxError(
"The nuclei '%s' and '%s' do not match, relax can only handle one nucleus type in Dasha."
% (nucleus, spin.isotope))
# Set the nucleus.
if not nucleus:
nucleus = spin.isotope
# Convert the name and write it.
if nucleus == '15N':
nucleus = 'N15'
elif nucleus == '13C':
nucleus = 'C13'
else:
raise RelaxError("Cannot handle the nucleus type '%s' within Dasha." %
nucleus)
file.write("set nucl %s\n" % nucleus)
# Number of frequencies.
file.write("\n# Number of frequencies.\n")
file.write("set n_freq %s\n" % cdp.spectrometer_frq_count)
# Frequency values.
file.write("\n# Frequency values.\n")
count = 1
for frq in loop_frequencies():
file.write("set H1_freq %s %s\n" % (frq / 1e6, count))
count += 1
# Set the diffusion tensor.
file.write("\n# Set the diffusion tensor.\n")
if model_type != 'local_tm':
# Sphere.
if cdp.diff_tensor.type == 'sphere':
file.write("set tr %s\n" % (cdp.diff_tensor.tm / 1e-9))
# Spheroid.
elif cdp.diff_tensor.type == 'spheroid':
file.write('set tr %s\n' % (cdp.diff_tensor.tm / 1e-9))
# Ellipsoid.
elif cdp.diff_tensor.type == 'ellipsoid':
# Get the eigenvales.
Dx, Dy, Dz = diffusion_tensor.return_eigenvalues()
# Geometric parameters.
file.write("set tr %s\n" % (cdp.diff_tensor.tm / 1e-9))
file.write("set D1/D3 %s\n" % (Dx / Dz))
file.write("set D2/D3 %s\n" % (Dy / Dz))
# Orientational parameters.
file.write("set alfa %s\n" % (cdp.diff_tensor.alpha /
(2.0 * pi) * 360.0))
file.write("set betta %s\n" % (cdp.diff_tensor.beta /
(2.0 * pi) * 360.0))
file.write("set gamma %s\n" % (cdp.diff_tensor.gamma /
(2.0 * pi) * 360.0))
# Reading the relaxation data.
file.write("\n# Reading the relaxation data.\n")
file.write("echo Reading the relaxation data.\n")
noe_index = 1
r1_index = 1
r2_index = 1
for ri_id in cdp.ri_ids:
# NOE.
if cdp.ri_type[ri_id] == 'NOE':
# Data set number.
number = noe_index
# Data type.
data_type = 'noe'
# Increment the data set index.
noe_index = noe_index + 1
# R1.
elif cdp.ri_type[ri_id] == 'R1':
# Data set number.
number = r1_index
# Data type.
data_type = '1/T1'
# Increment the data set index.
r1_index = r1_index + 1
# R2.
elif cdp.ri_type[ri_id] == 'R2':
# Data set number.
number = r2_index
# Data type.
data_type = '1/T2'
# Increment the data set index.
r2_index = r2_index + 1
# Set the data type.
if number == 1:
file.write("\nread < %s\n" % data_type)
else:
file.write("\nread < %s %s\n" % (data_type, number))
# The relaxation data.
for residue in residue_loop():
# Alias the spin.
spin = residue.spin[0]
# Skip deselected spins.
if not spin.select:
continue
# Skip and deselect spins for which relaxation data is missing.
if len(spin.ri_data) != len(
cdp.ri_ids) or spin.ri_data[ri_id] == None:
spin.select = False
continue
# Data and errors.
file.write(
"%s %s %s\n" %
(residue.num, spin.ri_data[ri_id], spin.ri_data_err[ri_id]))
# Terminate the reading.
file.write("exit\n")
# Individual residue optimisation.
if model_type == 'mf':
# Loop over the residues.
for residue in residue_loop():
# Alias the spin.
spin = residue.spin[0]
# Skip deselected spins.
if not spin.select:
continue
# Get the interatomic data containers.
interatoms = return_interatom_list(spin_hash=spin._hash)
if len(interatoms) == 0:
raise RelaxNoInteratomError
elif len(interatoms) > 1:
raise RelaxError(
"Only one interatomic data container, hence dipole-dipole interaction, is supported per spin."
)
# Comment.
file.write("\n\n\n# Residue %s\n\n" % residue.num)
# Echo.
file.write("echo Optimisation of residue %s\n" % residue.num)
# Select the spin.
file.write("\n# Select the residue.\n")
file.write("set cres %s\n" % residue.num)
# The angle alpha of the XH vector in the spheroid diffusion frame.
if cdp.diff_tensor.type == 'spheroid':
file.write("set teta %s\n" % spin.alpha)
# The angles theta and phi of the XH vector in the ellipsoid diffusion frame.
elif cdp.diff_tensor.type == 'ellipsoid':
file.write(
"\n# Setting the spherical angles of the XH vector in the ellipsoid diffusion frame.\n"
)
file.write("set teta %s\n" % spin.theta)
file.write("set fi %s\n" % spin.phi)
# The 'jmode'.
if 'ts' in spin.params:
jmode = 3
elif 'te' in spin.params:
jmode = 2
elif 's2' in spin.params:
jmode = 1
# Chemical exchange.
if 'rex' in spin.params:
exch = True
else:
exch = False
# Anisotropic diffusion.
if cdp.diff_tensor.type == 'sphere':
anis = False
else:
anis = True
# Axial symmetry.
if cdp.diff_tensor.type == 'spheroid':
sym = True
else:
sym = False
# Set the jmode.
file.write("\n# Set the jmode.\n")
file.write("set def jmode %s" % jmode)
if exch:
file.write(" exch")
if anis:
file.write(" anis")
if sym:
file.write(" sym")
file.write("\n")
# Parameter default values.
file.write("\n# Parameter default values.\n")
file.write("reset jmode %s\n" % residue.num)
# Bond length.
file.write("\n# Bond length.\n")
file.write("set r_hx %s\n" % (interatoms[0].r / 1e-10))
# CSA value.
file.write("\n# CSA value.\n")
file.write("set csa %s\n" % (spin.csa / 1e-6))
# Fix the tf parameter if it isn't in the model.
if not 'tf' in spin.params and jmode == 3:
file.write("\n# Fix the tf parameter.\n")
file.write("fix tf 0\n")
# Optimisation of all residues.
file.write("\n\n\n# Optimisation of all residues.\n")
if algor == 'LM':
file.write("lmin %s %s" %
(first_residue_num(), last_residue_num()))
elif algor == 'NR':
file.write("min %s %s" % (first_residue_num(), last_residue_num()))
# Show the results.
file.write("\n# Show the results.\n")
file.write("echo\n")
file.write("show all\n")
# Write the results.
file.write("\n# Write the results.\n")
file.write("write s2.out S\n")
file.write("write s2f.out Sf\n")
file.write("write s2s.out Ss\n")
file.write("write te.out te\n")
file.write("write tf.out tf\n")
file.write("write ts.out ts\n")
file.write("write rex.out rex\n")
file.write("write chi2.out F\n")
else:
raise RelaxError(
"Optimisation of the parameter set '%s' currently not supported." %
model_type)
def fail_test():
for residue in mol_res_spin.residue_loop():
pass
def update_mol(self, mol, mol_id):
"""Update the given molecule in the tree.
@param mol: The molecule container.
@type mol: MoleculeContainer instance
@param mol_id: The molecule identification string.
@type mol_id: str
"""
# Find the molecule, if it already exists.
new_mol = True
for key in self.tree_ids:
# Get the python data.
data = self.tree.GetItemPyData(key)
# No info.
if data == None or 'id' not in data:
continue
# Check the mol_id for a match and, if so, terminate to speed things up.
if mol_id == data['id']:
new_mol = False
mol_branch_id = key
break
# A new molecule.
if new_mol:
# Append a molecule with name to the tree.
mol_branch_id = self.tree.AppendItem(self.root, "Molecule: %s" % mol.name)
# The data to store.
data = {
'type': 'mol',
'mol_name': mol.name,
'id': mol_id,
'select': is_mol_selected(mol_id)
}
self.tree.SetPyData(mol_branch_id, data)
# Add the id to the tracking structure.
self.tree_ids[mol_branch_id] = {}
# Set the bitmap.
self.set_bitmap_mol(mol_branch_id, select=data['select'])
# An old molecule.
else:
# Check the selection state.
select = is_mol_selected(data['id'])
# Change of state.
if select != data['select']:
# Store the new state.
data['select'] = select
# Set the bitmap.
self.set_bitmap_mol(mol_branch_id, select=data['select'])
# Update the residues of this molecule.
for res, res_id in residue_loop(mol_id, return_id=True):
self.update_res(mol_branch_id, mol, res, res_id)
# Start new molecules expanded.
if new_mol and data['select']:
self.tree.Expand(mol_branch_id)
# Remove any deleted residues.
self.prune_res(mol_branch_id, mol_id)
# Expand the root.
self.tree.Expand(self.root)
def create_script(file, model_type, algor):
"""Create the Dasha script file.
@param file: The opened file descriptor.
@type file: file object
@param model_type: The model-free model type.
@type model_type: str
@param algor: The optimisation algorithm to use. This can be the Levenberg-Marquardt algorithm 'LM' or the Newton-Raphson algorithm 'NR'.
@type algor: str
"""
# Delete all data.
file.write("# Delete all data.\n")
file.write("del 1 10000\n")
# Nucleus type.
file.write("\n# Nucleus type.\n")
nucleus = None
for spin in spin_loop():
# Skip protons.
if spin.isotope == '1H':
continue
# Can only handle one spin type.
if nucleus and spin.isotope != nucleus:
raise RelaxError("The nuclei '%s' and '%s' do not match, relax can only handle one nucleus type in Dasha." % (nucleus, spin.isotope))
# Set the nucleus.
if not nucleus:
nucleus = spin.isotope
# Convert the name and write it.
if nucleus == '15N':
nucleus = 'N15'
elif nucleus == '13C':
nucleus = 'C13'
else:
raise RelaxError("Cannot handle the nucleus type '%s' within Dasha." % nucleus)
file.write("set nucl %s\n" % nucleus)
# Number of frequencies.
file.write("\n# Number of frequencies.\n")
file.write("set n_freq %s\n" % cdp.spectrometer_frq_count)
# Frequency values.
file.write("\n# Frequency values.\n")
count = 1
for frq in loop_frequencies():
file.write("set H1_freq %s %s\n" % (frq / 1e6, count))
count += 1
# Set the diffusion tensor.
file.write("\n# Set the diffusion tensor.\n")
if model_type != 'local_tm':
# Sphere.
if cdp.diff_tensor.type == 'sphere':
file.write("set tr %s\n" % (cdp.diff_tensor.tm / 1e-9))
# Spheroid.
elif cdp.diff_tensor.type == 'spheroid':
file.write('set tr %s\n' % (cdp.diff_tensor.tm / 1e-9))
# Ellipsoid.
elif cdp.diff_tensor.type == 'ellipsoid':
# Get the eigenvales.
Dx, Dy, Dz = diffusion_tensor.return_eigenvalues()
# Geometric parameters.
file.write("set tr %s\n" % (cdp.diff_tensor.tm / 1e-9))
file.write("set D1/D3 %s\n" % (Dx / Dz))
file.write("set D2/D3 %s\n" % (Dy / Dz))
# Orientational parameters.
file.write("set alfa %s\n" % (cdp.diff_tensor.alpha / (2.0 * pi) * 360.0))
file.write("set betta %s\n" % (cdp.diff_tensor.beta / (2.0 * pi) * 360.0))
file.write("set gamma %s\n" % (cdp.diff_tensor.gamma / (2.0 * pi) * 360.0))
# Reading the relaxation data.
file.write("\n# Reading the relaxation data.\n")
file.write("echo Reading the relaxation data.\n")
noe_index = 1
r1_index = 1
r2_index = 1
for ri_id in cdp.ri_ids:
# NOE.
if cdp.ri_type[ri_id] == 'NOE':
# Data set number.
number = noe_index
# Data type.
data_type = 'noe'
# Increment the data set index.
noe_index = noe_index + 1
# R1.
elif cdp.ri_type[ri_id] == 'R1':
# Data set number.
number = r1_index
# Data type.
data_type = '1/T1'
# Increment the data set index.
r1_index = r1_index + 1
# R2.
elif cdp.ri_type[ri_id] == 'R2':
# Data set number.
number = r2_index
# Data type.
data_type = '1/T2'
# Increment the data set index.
r2_index = r2_index + 1
# Set the data type.
if number == 1:
file.write("\nread < %s\n" % data_type)
else:
file.write("\nread < %s %s\n" % (data_type, number))
# The relaxation data.
for residue in residue_loop():
# Alias the spin.
spin = residue.spin[0]
# Skip deselected spins.
if not spin.select:
continue
# Skip and deselect spins for which relaxation data is missing.
if len(spin.ri_data) != len(cdp.ri_ids) or spin.ri_data[ri_id] == None:
spin.select = False
continue
# Data and errors.
file.write("%s %s %s\n" % (residue.num, spin.ri_data[ri_id], spin.ri_data_err[ri_id]))
# Terminate the reading.
file.write("exit\n")
# Individual residue optimisation.
if model_type == 'mf':
# Loop over the residues.
for residue in residue_loop():
# Alias the spin.
spin = residue.spin[0]
# Skip deselected spins.
if not spin.select:
continue
# Get the interatomic data containers.
interatoms = return_interatom_list(spin._spin_ids[0])
if len(interatoms) == 0:
raise RelaxNoInteratomError
elif len(interatoms) > 1:
raise RelaxError("Only one interatomic data container, hence dipole-dipole interaction, is supported per spin.")
# Comment.
file.write("\n\n\n# Residue %s\n\n" % residue.num)
# Echo.
file.write("echo Optimisation of residue %s\n" % residue.num)
# Select the spin.
file.write("\n# Select the residue.\n")
file.write("set cres %s\n" % residue.num)
# The angle alpha of the XH vector in the spheroid diffusion frame.
if cdp.diff_tensor.type == 'spheroid':
file.write("set teta %s\n" % spin.alpha)
# The angles theta and phi of the XH vector in the ellipsoid diffusion frame.
elif cdp.diff_tensor.type == 'ellipsoid':
file.write("\n# Setting the spherical angles of the XH vector in the ellipsoid diffusion frame.\n")
file.write("set teta %s\n" % spin.theta)
file.write("set fi %s\n" % spin.phi)
# The 'jmode'.
if 'ts' in spin.params:
jmode = 3
elif 'te' in spin.params:
jmode = 2
elif 's2' in spin.params:
jmode = 1
# Chemical exchange.
if 'rex' in spin.params:
exch = True
else:
exch = False
# Anisotropic diffusion.
if cdp.diff_tensor.type == 'sphere':
anis = False
else:
anis = True
# Axial symmetry.
if cdp.diff_tensor.type == 'spheroid':
sym = True
else:
sym = False
# Set the jmode.
file.write("\n# Set the jmode.\n")
file.write("set def jmode %s" % jmode)
if exch:
file.write(" exch")
if anis:
file.write(" anis")
if sym:
file.write(" sym")
file.write("\n")
# Parameter default values.
file.write("\n# Parameter default values.\n")
file.write("reset jmode %s\n" % residue.num)
# Bond length.
file.write("\n# Bond length.\n")
file.write("set r_hx %s\n" % (interatoms[0].r / 1e-10))
# CSA value.
file.write("\n# CSA value.\n")
file.write("set csa %s\n" % (spin.csa / 1e-6))
# Fix the tf parameter if it isn't in the model.
if not 'tf' in spin.params and jmode == 3:
file.write("\n# Fix the tf parameter.\n")
file.write("fix tf 0\n")
# Optimisation of all residues.
file.write("\n\n\n# Optimisation of all residues.\n")
if algor == 'LM':
file.write("lmin %s %s" % (first_residue_num(), last_residue_num()))
elif algor == 'NR':
file.write("min %s %s" % (first_residue_num(), last_residue_num()))
# Show the results.
file.write("\n# Show the results.\n")
file.write("echo\n")
file.write("show all\n")
# Write the results.
file.write("\n# Write the results.\n")
file.write("write s2.out S\n")
file.write("write s2f.out Sf\n")
file.write("write s2s.out Ss\n")
file.write("write te.out te\n")
file.write("write tf.out tf\n")
file.write("write ts.out ts\n")
file.write("write rex.out rex\n")
file.write("write chi2.out F\n")
else:
raise RelaxError("Optimisation of the parameter set '%s' currently not supported." % model_type)
def update_mol(self, mol, mol_id):
"""Update the given molecule in the tree.
@param mol: The molecule container.
@type mol: MoleculeContainer instance
@param mol_id: The molecule identification string.
@type mol_id: str
"""
# Find the molecule, if it already exists.
new_mol = True
for key in self.tree_ids:
# Get the python data.
if dep_check.wx_classic:
data = self.tree.GetItemPyData(key)
else:
data = self.tree.GetItemData(key)
# No info.
if data == None or 'id' not in data:
continue
# Check the mol_id for a match and, if so, terminate to speed things up.
if mol_id == data['id']:
new_mol = False
mol_branch_id = key
break
# A new molecule.
if new_mol:
# Append a molecule with name to the tree.
mol_branch_id = self.tree.AppendItem(self.root,
"Molecule: %s" % mol.name)
# The data to store.
data = {
'type': 'mol',
'mol_name': mol.name,
'id': mol_id,
'select': is_mol_selected(mol_id)
}
if dep_check.wx_classic:
self.tree.SetPyData(mol_branch_id, data)
else:
self.tree.SetItemData(mol_branch_id, data)
# Add the id to the tracking structure.
self.tree_ids[mol_branch_id] = {}
# Set the bitmap.
self.set_bitmap_mol(mol_branch_id, select=data['select'])
# An old molecule.
else:
# Check the selection state.
select = is_mol_selected(data['id'])
# Change of state.
if select != data['select']:
# Store the new state.
data['select'] = select
# Set the bitmap.
self.set_bitmap_mol(mol_branch_id, select=data['select'])
# Update the residues of this molecule.
for res, res_id in residue_loop(mol_id, return_id=True):
self.update_res(mol_branch_id, mol, res, res_id)
# Start new molecules expanded.
if new_mol and data['select']:
self.tree.Expand(mol_branch_id)
# Remove any deleted residues.
self.prune_res(mol_branch_id, mol_id)
# Expand the root.
self.tree.Expand(self.root)
