def test_loop_exp_frq_cpmg(self):
"""Unit test of the loop_exp_frq() function.
This uses the data of the saved state attached to U{bug #21665<https://gna.org/bugs/?21665>}.
"""
# Load the state.
statefile = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'bug_21665.bz2'
state.load_state(statefile, force=True)
# Original data (exp_type, frq).
data = [
['SQ CPMG', 499862140.0],
['SQ CPMG', 599890858.69999993]
]
# Original indices (ei, mi).
indices = [
[0, 0],
[0, 1]
]
# Check the number of iterations.
print("Checking the number of iterations of the loop.")
count = 0
for exp_type, frq, ei, mi in loop_exp_frq(return_indices=True):
print(exp_type, frq, ei, mi)
count += 1
self.assertEqual(count, 2)
# Check the values.
print("Checking the values returned by the loop.")
index = 0
for exp_type, frq, ei, mi in loop_exp_frq(return_indices=True):
# Check the experiment info.
self.assertEqual(exp_type, data[index][0])
self.assertEqual(ei, indices[index][0])
# Check the frequency info.
self.assertEqual(frq, data[index][1])
self.assertEqual(mi, indices[index][1])
# Increment the data index.
index += 1
def test_loop_exp_frq_cpmg(self):
"""Unit test of the loop_exp_frq() function.
This uses the data of the saved state attached to U{bug #21665<https://web.archive.org/web/https://gna.org/bugs/?21665>}.
"""
# Load the state.
statefile = status.install_path + sep + 'test_suite' + sep + 'shared_data' + sep + 'dispersion' + sep + 'bug_21665.bz2'
state.load_state(statefile, force=True)
# Original data (exp_type, frq).
data = [['SQ CPMG', 499862140.0], ['SQ CPMG', 599890858.69999993]]
# Original indices (ei, mi).
indices = [[0, 0], [0, 1]]
# Check the number of iterations.
print("Checking the number of iterations of the loop.")
count = 0
for exp_type, frq, ei, mi in loop_exp_frq(return_indices=True):
print(exp_type, frq, ei, mi)
count += 1
self.assertEqual(count, 2)
# Check the values.
print("Checking the values returned by the loop.")
index = 0
for exp_type, frq, ei, mi in loop_exp_frq(return_indices=True):
# Check the experiment info.
self.assertEqual(exp_type, data[index][0])
self.assertEqual(ei, indices[index][0])
# Check the frequency info.
self.assertEqual(frq, data[index][1])
self.assertEqual(mi, indices[index][1])
# Increment the data index.
index += 1
pipe_name = '%s - relax_disp' % (model)
pipes.append(pipe_name)
pipe.switch(pipe_name=pipe_name)
print("\nModel: %s" % (model))
# Loop over the spins.
for cur_spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True):
# Generate spin string.
spin_string = generate_spin_string(spin=cur_spin, mol_name=mol_name, res_num=resi, res_name=resn)
# Loop over the parameters.
print("\nOptimised parameters for spin: %s" % (spin_string))
for param in cur_spin.params + ['chi2']:
# Get the value.
if param in ['r1', 'r2']:
for exp_type, frq, ei, mi in loop_exp_frq(return_indices=True):
# Generate the R20 key.
r20_key = generate_r20_key(exp_type=exp_type, frq=frq)
# Get the value.
value = getattr(cur_spin, param)[r20_key]
# Print value.
print("%-10s %-6s %-6s %3.8f" % ("Parameter:", param, "Value:", value))
# For all other parameters.
else:
# Get the value.
value = getattr(cur_spin, param)
# Print value.
def sherekhan_input(spin_id=None, force=False, dir='ShereKhan'):
"""Create the ShereKhan input files.
@keyword spin_id: The spin ID string to restrict the file creation to.
@type spin_id: str
@keyword force: A flag which if True will cause all pre-existing files to be overwritten.
@type force: bool
@keyword dir: The optional directory to place the files into. If None, then the files will be placed into the current directory.
@type dir: str or None
"""
# Test if the current pipe exists.
check_pipe()
# Test if sequence data is loaded.
if not exists_mol_res_spin_data():
raise RelaxNoSequenceError
# Test if the experiment type has been set.
if not hasattr(cdp, 'exp_type'):
raise RelaxError("The relaxation dispersion experiment type has not been specified.")
# Test if the model has been set.
if not hasattr(cdp, 'model_type'):
raise RelaxError("The relaxation dispersion model has not been specified.")
# Directory creation.
if dir != None:
mkdir_nofail(dir, verbosity=0)
# Loop over the spin blocks.
cluster_index = 0
for spin_ids in loop_cluster():
# The spin containers.
spins = spin_ids_to_containers(spin_ids)
# Loop over the magnetic fields.
for exp_type, frq, ei, mi in loop_exp_frq(return_indices=True):
# Loop over the time, and count it.
time_i = 0
for time, ti in loop_time(exp_type=exp_type, frq=frq, return_indices=True):
time_i += 1
# Check that not more than one time point is returned.
if time_i > 1:
raise RelaxError("Number of returned time poins is %i. Only 1 time point is expected."%time_i)
# The ShereKhan input file for the spin cluster.
file_name = 'sherekhan_frq%s.in' % (mi+1)
if dir != None:
dir_name = dir + sep + 'cluster%s' % (cluster_index+1)
else:
dir_name = 'cluster%s' % (cluster_index+1)
file = open_write_file(file_name=file_name, dir=dir_name, force=force)
# The B0 field for the nuclei of interest in MHz (must be positive to be accepted by the server).
file.write("%.10f\n" % abs(frq / periodic_table.gyromagnetic_ratio('1H') * periodic_table.gyromagnetic_ratio('15N') / 1e6))
# The constant relaxation time for the CPMG experiment in seconds.
file.write("%s\n" % (time))
# The comment line.
file.write("# %-18s %-20s %-20s\n" % ("nu_cpmg (Hz)", "R2eff (rad/s)", "Error"))
# Loop over the spins of the cluster.
for i in range(len(spins)):
# Get the residue container.
res = return_residue(spin_ids[i])
# Name the residue if needed.
res_name = res.name
if res_name == None:
res_name = 'X'
# Initialise the lines to output (to be able to catch missing data).
lines = []
# The residue ID line.
lines.append("# %s%s\n" % (res_name, res.num))
# Loop over the dispersion points.
for offset, point in loop_offset_point(exp_type=exp_type, frq=frq, skip_ref=True):
# The parameter key.
param_key = return_param_key_from_data(exp_type=exp_type, frq=frq, offset=offset, point=point)
# No data.
if param_key not in spins[i].r2eff:
continue
# Store the data.
lines.append("%20.15g %20.13g %20.13g\n" % (point, spins[i].r2eff[param_key], spins[i].r2eff_err[param_key]))
# No data.
if len(lines) == 1:
continue
# Write out the data.
for line in lines:
file.write(line)
# Close the file.
file.close()
# Increment the cluster index.
cluster_index += 1
def loop_parameters(spins=None):
"""Generator function for looping of the parameters of the cluster.
@keyword spins: The list of spin data containers for the block.
@type spins: list of SpinContainer instances
@return: The parameter name, the parameter index (for the parameter vector), the spin index (for the cluster), and the R20 parameter key (for R20, R20A, and R20B parameters stored as dictionaries).
@rtype: str, int, int, str
"""
# Make sure that the R1 parameter is correctly set up.
r1_setup()
# The parameter index.
param_index = -1
# The R2eff model.
if cdp.model_type == 'R2eff':
# Loop over the spins.
for spin_index in range(len(spins)):
# Skip deselected spins.
if not spins[spin_index].select:
continue
# Yield the two parameters.
params = ['r2eff', 'i0']
for i in range(2):
# First increment the indices.
param_index += 1
# Yield the data.
yield params[i], param_index, spin_index, None
# All other models.
else:
# First the R1 fit parameter (one per spin per field strength).
for spin_index in range(len(spins)):
# Skip deselected spins.
if not spins[spin_index].select:
continue
# The R1 parameter.
if 'r1' in spins[spin_index].params:
for exp_type, frq in loop_exp_frq():
param_index += 1
yield 'r1', param_index, spin_index, generate_r20_key(exp_type=exp_type, frq=frq)
# Then the R2 parameters (one per spin per field strength).
for spin_index in range(len(spins)):
# Skip deselected spins.
if not spins[spin_index].select:
continue
# The R2 parameter.
if 'r2' in spins[spin_index].params:
for exp_type, frq in loop_exp_frq():
param_index += 1
yield 'r2', param_index, spin_index, generate_r20_key(exp_type=exp_type, frq=frq)
# The R2A parameter.
if 'r2a' in spins[spin_index].params:
for exp_type, frq in loop_exp_frq():
param_index += 1
yield 'r2a', param_index, spin_index, generate_r20_key(exp_type=exp_type, frq=frq)
# The R2B parameter.
if 'r2b' in spins[spin_index].params:
for exp_type, frq in loop_exp_frq():
param_index += 1
yield 'r2b', param_index, spin_index, generate_r20_key(exp_type=exp_type, frq=frq)
# Then the chemical shift difference parameters 'phi_ex', 'phi_ex_B', 'phi_ex_C', 'padw2', 'dw', 'dw_AB', 'dw_BC', 'dw_AB' (one per spin).
for spin_index in range(len(spins)):
# Skip deselected spins.
if not spins[spin_index].select:
continue
# Yield the data.
if 'phi_ex' in spins[spin_index].params:
param_index += 1
yield 'phi_ex', param_index, spin_index, None
if 'phi_ex_B' in spins[spin_index].params:
param_index += 1
yield 'phi_ex_B', param_index, spin_index, None
if 'phi_ex_C' in spins[spin_index].params:
param_index += 1
yield 'phi_ex_C', param_index, spin_index, None
if 'padw2' in spins[spin_index].params:
param_index += 1
yield 'padw2', param_index, spin_index, None
if 'dw' in spins[spin_index].params:
param_index += 1
yield 'dw', param_index, spin_index, None
if 'dw_AB' in spins[spin_index].params:
param_index += 1
yield 'dw_AB', param_index, spin_index, None
if 'dw_BC' in spins[spin_index].params:
param_index += 1
yield 'dw_BC', param_index, spin_index, None
if 'dw_AC' in spins[spin_index].params:
param_index += 1
yield 'dw_AC', param_index, spin_index, None
# Then a separate block for the proton chemical shift difference parameters for the MQ models (one per spin).
for spin_index in range(len(spins)):
# Skip deselected spins.
if not spins[spin_index].select:
continue
if 'dwH' in spins[spin_index].params:
param_index += 1
yield 'dwH', param_index, spin_index, None
if 'dwH_AB' in spins[spin_index].params:
param_index += 1
yield 'dwH_AB', param_index, spin_index, None
if 'dwH_BC' in spins[spin_index].params:
param_index += 1
yield 'dwH_BC', param_index, spin_index, None
if 'dwH_AC' in spins[spin_index].params:
param_index += 1
yield 'dwH_AC', param_index, spin_index, None
# All other parameters (one per spin cluster).
for param in spins[0].params:
if not param in ['r1', 'r2', 'r2a', 'r2b', 'phi_ex', 'phi_ex_B', 'phi_ex_C', 'padw2', 'dw', 'dw_AB', 'dw_BC', 'dw_AB', 'dwH', 'dwH_AB', 'dwH_BC', 'dwH_AB']:
param_index += 1
yield param, param_index, None, None
def param_num(spins=None):
"""Determine the number of parameters in the model.
@keyword spins: The list of spin data containers for the block.
@type spins: list of SpinContainer instances
@return: The number of model parameters.
@rtype: int
"""
# Initialise the number.
num = 0
# The R2eff model.
if cdp.model_type == 'R2eff':
# Count the selected spins.
spin_num = count_spins(spins)
# Exponential curves (with clustering).
if has_exponential_exp_type():
return 2 * spin_num
# Fixed time period experiments (with clustering).
return 1 * spin_num
# Check the spin cluster.
for spin in spins:
# Skip deselected spins.
if not spin.select:
continue
if len(spin.params) != len(spins[0].params):
raise RelaxError("The number of parameters for each spin in the cluster are not the same.")
# Count the number of R10 parameters.
for spin in spins:
# Skip deselected spins.
if not spin.select:
continue
for i in range(len(spin.params)):
if spin.params[i] in ['r1']:
for exp_type, frq in loop_exp_frq():
num += 1
# Count the number of R20 parameters.
for spin in spins:
# Skip deselected spins.
if not spin.select:
continue
for i in range(len(spin.params)):
if spin.params[i] in PARAMS_R20:
for exp_type, frq in loop_exp_frq():
num += 1
# Count the number of spin specific parameters for all spins.
spin_params = ['phi_ex', 'phi_ex_B', 'phi_ex_C', 'padw2', 'dw', 'dwH']
for spin in spins:
# Skip deselected spins.
if not spin.select:
continue
for i in range(len(spin.params)):
if spin.params[i] in spin_params:
num += 1
# Count all other parameters, but only for a single spin.
all_params = ['r1'] + PARAMS_R20 + spin_params
for spin in spins:
# Skip deselected spins.
if not spin.select:
continue
for i in range(len(spin.params)):
if not spin.params[i] in all_params:
num += 1
break
# Return the number.
return num
# Loop over the spins.
for cur_spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True,
return_id=True,
skip_desel=True):
# Generate spin string.
spin_string = generate_spin_string(spin=cur_spin,
mol_name=mol_name,
res_num=resi,
res_name=resn)
# Loop over the parameters.
print("\nOptimised parameters for spin: %s" % (spin_string))
for param in cur_spin.params + ['chi2']:
# Get the value.
if param in ['r1', 'r2']:
for exp_type, frq, ei, mi in loop_exp_frq(return_indices=True):
# Generate the R20 key.
r20_key = generate_r20_key(exp_type=exp_type, frq=frq)
# Get the value.
value = getattr(cur_spin, param)[r20_key]
# Print value.
print("%-10s %-6s %-6s %3.8f" %
("Parameter:", param, "Value:", value))
# For all other parameters.
else:
# Get the value.
value = getattr(cur_spin, param)
def sherekhan_input(spin_id=None, force=False, dir='ShereKhan'):
"""Create the ShereKhan input files.
@keyword spin_id: The spin ID string to restrict the file creation to.
@type spin_id: str
@keyword force: A flag which if True will cause all pre-existing files to be overwritten.
@type force: bool
@keyword dir: The optional directory to place the files into. If None, then the files will be placed into the current directory.
@type dir: str or None
"""
# Test if the current pipe exists.
check_pipe()
# Test if sequence data is loaded.
if not exists_mol_res_spin_data():
raise RelaxNoSequenceError
# Test if the experiment type has been set.
if not hasattr(cdp, 'exp_type'):
raise RelaxError("The relaxation dispersion experiment type has not been specified.")
# Test if the model has been set.
if not hasattr(cdp, 'model_type'):
raise RelaxError("The relaxation dispersion model has not been specified.")
# Directory creation.
if dir != None:
mkdir_nofail(dir, verbosity=0)
# Loop over the spin blocks.
cluster_index = 0
for spin_ids in loop_cluster():
# The spin containers.
spins = spin_ids_to_containers(spin_ids)
# Loop over the magnetic fields.
for exp_type, frq, ei, mi in loop_exp_frq(return_indices=True):
# Loop over the time, and count it.
time_i = 0
for time, ti in loop_time(exp_type=exp_type, frq=frq, return_indices=True):
time_i += 1
# Check that not more than one time point is returned.
if time_i > 1:
raise RelaxError("Number of returned time poins is %i. Only 1 time point is expected."%time_i)
# The ShereKhan input file for the spin cluster.
file_name = 'sherekhan_frq%s.in' % (mi+1)
if dir != None:
dir_name = dir + sep + 'cluster%s' % (cluster_index+1)
else:
dir_name = 'cluster%s' % (cluster_index+1)
file = open_write_file(file_name=file_name, dir=dir_name, force=force)
# The B0 field for the nuclei of interest in MHz (must be positive to be accepted by the server).
file.write("%.10f\n" % abs(frq / periodic_table.gyromagnetic_ratio('1H') * periodic_table.gyromagnetic_ratio('15N') / 1e6))
# The constant relaxation time for the CPMG experiment in seconds.
file.write("%s\n" % (time))
# The comment line.
file.write("# %-18s %-20s %-20s\n" % ("nu_cpmg (Hz)", "R2eff (rad/s)", "Error"))
# Loop over the spins of the cluster.
for i in range(len(spins)):
# Get the residue container.
res = return_residue(spin_ids[i])
# Name the residue if needed.
res_name = res.name
if res_name == None:
res_name = 'X'
# Initialise the lines to output (to be able to catch missing data).
lines = []
# The residue ID line.
lines.append("# %s%s\n" % (res_name, res.num))
# Loop over the dispersion points.
for offset, point in loop_offset_point(exp_type=exp_type, frq=frq, skip_ref=True):
# The parameter key.
param_key = return_param_key_from_data(exp_type=exp_type, frq=frq, offset=offset, point=point)
# No data.
if param_key not in spins[i].r2eff:
continue
# Store the data.
lines.append("%20.15g %20.13g %20.13g\n" % (point, spins[i].r2eff[param_key], spins[i].r2eff_err[param_key]))
# No data.
if len(lines) == 1:
continue
# Write out the data.
for line in lines:
file.write(line)
# Close the file.
file.close()
# Increment the cluster index.
cluster_index += 1
def param_num(spins=None):
"""Determine the number of parameters in the model.
@keyword spins: The list of spin data containers for the block.
@type spins: list of SpinContainer instances
@return: The number of model parameters.
@rtype: int
"""
# Initialise the number.
num = 0
# The R2eff model.
if cdp.model_type == 'R2eff':
# Count the selected spins.
spin_num = count_spins(spins)
# Exponential curves (with clustering).
if has_exponential_exp_type():
return 2 * spin_num
# Fixed time period experiments (with clustering).
return 1 * spin_num
# Check the spin cluster.
for spin in spins:
# Skip deselected spins.
if not spin.select:
continue
if len(spin.params) != len(spins[0].params):
raise RelaxError("The number of parameters for each spin in the cluster are not the same.")
# Count the number of R10 parameters.
for spin in spins:
# Skip deselected spins.
if not spin.select:
continue
for i in range(len(spin.params)):
if spin.params[i] in ['r1']:
for exp_type, frq in loop_exp_frq():
num += 1
# Count the number of R20 parameters.
for spin in spins:
# Skip deselected spins.
if not spin.select:
continue
for i in range(len(spin.params)):
if spin.params[i] in PARAMS_R20:
for exp_type, frq in loop_exp_frq():
num += 1
# Count the number of spin specific parameters for all spins.
spin_params = ['phi_ex', 'phi_ex_B', 'phi_ex_C', 'padw2', 'dw', 'dwH']
for spin in spins:
# Skip deselected spins.
if not spin.select:
continue
for i in range(len(spin.params)):
if spin.params[i] in spin_params:
num += 1
# Count all other parameters, but only for a single spin.
all_params = ['r1'] + PARAMS_R20 + spin_params
for spin in spins:
# Skip deselected spins.
if not spin.select:
continue
for i in range(len(spin.params)):
if not spin.params[i] in all_params:
num += 1
break
# Return the number.
return num
def loop_parameters(spins=None):
"""Generator function for looping of the parameters of the cluster.
@keyword spins: The list of spin data containers for the block.
@type spins: list of SpinContainer instances
@return: The parameter name, the parameter index (for the parameter vector), the spin index (for the cluster), and the R20 parameter key (for R20, R20A, and R20B parameters stored as dictionaries).
@rtype: str, int, int, str
"""
# Make sure that the R1 parameter is correctly set up.
r1_setup()
# The parameter index.
param_index = -1
# The R2eff model.
if cdp.model_type == 'R2eff':
# Loop over the spins.
for spin_index in range(len(spins)):
# Skip deselected spins.
if not spins[spin_index].select:
continue
# Yield the two parameters.
params = ['r2eff', 'i0']
for i in range(2):
# First increment the indices.
param_index += 1
# Yield the data.
yield params[i], param_index, spin_index, None
# All other models.
else:
# First the R1 fit parameter (one per spin per field strength).
for spin_index in range(len(spins)):
# Skip deselected spins.
if not spins[spin_index].select:
continue
# The R1 parameter.
if 'r1' in spins[spin_index].params:
for exp_type, frq in loop_exp_frq():
param_index += 1
yield 'r1', param_index, spin_index, generate_r20_key(exp_type=exp_type, frq=frq)
# Then the R2 parameters (one per spin per field strength).
for spin_index in range(len(spins)):
# Skip deselected spins.
if not spins[spin_index].select:
continue
# The R2 parameter.
if 'r2' in spins[spin_index].params:
for exp_type, frq in loop_exp_frq():
param_index += 1
yield 'r2', param_index, spin_index, generate_r20_key(exp_type=exp_type, frq=frq)
# The R2A parameter.
if 'r2a' in spins[spin_index].params:
for exp_type, frq in loop_exp_frq():
param_index += 1
yield 'r2a', param_index, spin_index, generate_r20_key(exp_type=exp_type, frq=frq)
# The R2B parameter.
if 'r2b' in spins[spin_index].params:
for exp_type, frq in loop_exp_frq():
param_index += 1
yield 'r2b', param_index, spin_index, generate_r20_key(exp_type=exp_type, frq=frq)
# Then the chemical shift difference parameters 'phi_ex', 'phi_ex_B', 'phi_ex_C', 'padw2', 'dw', 'dw_AB', 'dw_BC', 'dw_AB' (one per spin).
for spin_index in range(len(spins)):
# Skip deselected spins.
if not spins[spin_index].select:
continue
# Yield the data.
if 'phi_ex' in spins[spin_index].params:
param_index += 1
yield 'phi_ex', param_index, spin_index, None
if 'phi_ex_B' in spins[spin_index].params:
param_index += 1
yield 'phi_ex_B', param_index, spin_index, None
if 'phi_ex_C' in spins[spin_index].params:
param_index += 1
yield 'phi_ex_C', param_index, spin_index, None
if 'padw2' in spins[spin_index].params:
param_index += 1
yield 'padw2', param_index, spin_index, None
if 'dw' in spins[spin_index].params:
param_index += 1
yield 'dw', param_index, spin_index, None
if 'dw_AB' in spins[spin_index].params:
param_index += 1
yield 'dw_AB', param_index, spin_index, None
if 'dw_BC' in spins[spin_index].params:
param_index += 1
yield 'dw_BC', param_index, spin_index, None
if 'dw_AC' in spins[spin_index].params:
param_index += 1
yield 'dw_AC', param_index, spin_index, None
# Then a separate block for the proton chemical shift difference parameters for the MQ models (one per spin).
for spin_index in range(len(spins)):
# Skip deselected spins.
if not spins[spin_index].select:
continue
if 'dwH' in spins[spin_index].params:
param_index += 1
yield 'dwH', param_index, spin_index, None
if 'dwH_AB' in spins[spin_index].params:
param_index += 1
yield 'dwH_AB', param_index, spin_index, None
if 'dwH_BC' in spins[spin_index].params:
param_index += 1
yield 'dwH_BC', param_index, spin_index, None
if 'dwH_AC' in spins[spin_index].params:
param_index += 1
yield 'dwH_AC', param_index, spin_index, None
# All other parameters (one per spin cluster).
for param in spins[0].params:
if not param in ['r1', 'r2', 'r2a', 'r2b', 'phi_ex', 'phi_ex_B', 'phi_ex_C', 'padw2', 'dw', 'dw_AB', 'dw_BC', 'dw_AB', 'dwH', 'dwH_AB', 'dwH_BC', 'dwH_AB']:
param_index += 1
yield param, param_index, None, None
def loop_parameters(spins=None):
"""Generator function for looping of the model parameters of the cluster.
@keyword spins: The list of spin data containers for the block.
@type spins: list of SpinContainer instances
@return: The parameter name, the parameter index (for the parameter vector), the spin index (for the cluster), and the R20 parameter key (for R20, R20A, and R20B parameters stored as dictionaries).
@rtype: str, int, int, str
"""
# Make sure that the R1 parameter is correctly set up.
r1_setup()
# The parameter index.
param_index = -1
# The R2eff model.
if cdp.model_type == 'R2eff':
# Loop over the spins.
for spin_index in range(len(spins)):
# Skip deselected spins.
if not spins[spin_index].select:
continue
# One or two parameters.
params = ['r2eff']
if has_exponential_exp_type():
params = ['r2eff', 'i0']
# Yield the parameters.
for param in params:
# First increment the indices.
param_index += 1
# Yield the data.
yield param, param_index, spin_index, None
# All other models.
else:
# First the R1 fit parameter (one per spin per field strength).
for spin_index in range(len(spins)):
# Skip deselected spins.
if not spins[spin_index].select:
continue
# The parameters.
for param in PARAMS_R1:
if param in spins[spin_index].params:
for exp_type, frq in loop_exp_frq():
param_index += 1
yield param, param_index, spin_index, generate_r20_key(
exp_type=exp_type, frq=frq)
# Then the R2 parameters (one per spin per field strength).
for spin_index in range(len(spins)):
# Skip deselected spins.
if not spins[spin_index].select:
continue
# The parameters.
for param in PARAMS_R20:
if param in spins[spin_index].params:
for exp_type, frq in loop_exp_frq():
param_index += 1
yield param, param_index, spin_index, generate_r20_key(
exp_type=exp_type, frq=frq)
# Then the chemical shift difference parameters (one per spin).
for spin_index in range(len(spins)):
# Skip deselected spins.
if not spins[spin_index].select:
continue
# Yield the data.
for param in PARAMS_CHEM_SHIFT_DIFF:
if param in spins[spin_index].params:
param_index += 1
yield param, param_index, spin_index, None
# Then a separate block for the proton chemical shift difference parameters for the MQ models (one per spin).
for spin_index in range(len(spins)):
# Skip deselected spins.
if not spins[spin_index].select:
continue
# Yield the data.
for param in PARAMS_CHEM_SHIFT_DIFF_MMQ:
if param in spins[spin_index].params:
param_index += 1
yield param, param_index, spin_index, None
# All other parameters (one per spin cluster).
for spin_index in range(len(spins)):
# Skip deselected spins.
if not spins[spin_index].select:
continue
# The parameters.
for param in spins[0].params:
if not param in PARAMS_SPIN:
param_index += 1
yield param, param_index, None, None
# No more spins.
break
