Author: bugman
Date: Sat Nov 23 18:23:15 2013
New Revision: 21615
URL: http://svn.gna.org/viewcvs/relax?rev=21615&view=rev
Log:
Converted the dispersion api method _back_calc_r2eff() into a function of the
optimisation module.
Modified:
branches/relax_disp/specific_analyses/relax_disp/api.py
branches/relax_disp/specific_analyses/relax_disp/optimisation.py
Modified: branches/relax_disp/specific_analyses/relax_disp/api.py
URL:
http://svn.gna.org/viewcvs/relax/branches/relax_disp/specific_analyses/relax_disp/api.py?rev=21615&r1=21614&r2=21615&view=diff
==============================================================================
--- branches/relax_disp/specific_analyses/relax_disp/api.py (original)
+++ branches/relax_disp/specific_analyses/relax_disp/api.py Sat Nov 23
18:23:15 2013
@@ -46,7 +46,7 @@
from specific_analyses.api_common import API_common
from specific_analyses.relax_disp.checks import check_c_modules,
check_disp_points, check_exp_type, check_exp_type_fixed_time,
check_model_type, check_pipe_type, check_spectra_id_setup
from specific_analyses.relax_disp.disp_data import average_intensity,
find_intensity_keys, get_curve_type, has_exponential_exp_type,
has_proton_mmq_cpmg, loop_cluster, loop_exp_frq_point,
loop_exp_frq_point_time, loop_frq, loop_time, pack_back_calc_r2eff,
return_cpmg_frqs, return_index_from_disp_point, return_index_from_exp_type,
return_index_from_frq, return_offset_data, return_param_key_from_data,
return_r1_data, return_r2eff_arrays, return_spin_lock_nu1,
spin_ids_to_containers
-from specific_analyses.relax_disp.optimisation import Disp_memo,
Disp_minimise_command, grid_search_setup
+from specific_analyses.relax_disp.optimisation import Disp_memo,
Disp_minimise_command, back_calc_r2eff, grid_search_setup
from specific_analyses.relax_disp.parameters import assemble_param_vector,
assemble_scaling_matrix, disassemble_param_vector, get_param_names,
linear_constraints, param_index_to_param_info, param_num
from specific_analyses.relax_disp.variables import EXP_TYPE_CPMG_PROTON_MQ,
EXP_TYPE_CPMG_PROTON_SQ, MODEL_LIST_FULL, MODEL_LM63, MODEL_LM63_3SITE,
MODEL_CR72, MODEL_CR72_FULL, MODEL_DPL94, MODEL_IT99, MODEL_LIST_MMQ,
MODEL_M61, MODEL_M61B, MODEL_MMQ_2SITE, MODEL_MP05, MODEL_MQ_CR72,
MODEL_NOREX, MODEL_NS_CPMG_2SITE_3D, MODEL_NS_CPMG_2SITE_3D_FULL,
MODEL_NS_CPMG_2SITE_EXPANDED, MODEL_NS_CPMG_2SITE_STAR,
MODEL_NS_CPMG_2SITE_STAR_FULL, MODEL_NS_R1RHO_2SITE, MODEL_R2EFF,
MODEL_TAP03, MODEL_TP02, MODEL_TSMFK01
from target_functions.relax_disp import Dispersion
@@ -105,65 +105,6 @@
self.PARAMS.add_min_data(min_stats_global=False, min_stats_spin=True)
- def _back_calc_r2eff(self, spin=None, spin_id=None):
- """Back-calculation of R2eff/R1rho values for the given spin.
-
- @keyword spin: The specific spin data container.
- @type spin: SpinContainer instance
- @keyword spin_id: The spin ID string for the spin container.
- @type spin_id: str
- @return: The back-calculated R2eff/R1rho value for the
given spin.
- @rtype: numpy rank-1 float array
- """
-
- # Skip protons for MMQ data.
- if spin.model in MODEL_LIST_MMQ and spin.isotope == '1H':
- return
-
- # Create the initial parameter vector.
- param_vector = assemble_param_vector(spins=[spin])
-
- # Create a scaling matrix.
- scaling_matrix = assemble_scaling_matrix(spins=[spin], scaling=False)
-
- # Number of spectrometer fields.
- fields = [None]
- field_count = 1
- if hasattr(cdp, 'spectrometer_frq_count'):
- fields = cdp.spectrometer_frq_list
- field_count = cdp.spectrometer_frq_count
-
- # Initialise the data structures for the target function.
- values, errors, missing, frqs, frqs_H, exp_types, relax_times =
return_r2eff_arrays(spins=[spin], spin_ids=[spin_id], fields=fields,
field_count=field_count)
-
- # The offset and R1 data for R1rho off-resonance models.
- chemical_shifts, offsets, tilt_angles, r1 = None, None, None, None
- if spin.model in [MODEL_DPL94, MODEL_TP02, MODEL_TAP03, MODEL_MP05,
MODEL_NS_R1RHO_2SITE]:
- chemical_shifts, offsets, tilt_angles =
return_offset_data(spins=[spin], spin_ids=[spin_id], fields=fields,
field_count=field_count)
- r1 = return_r1_data(spins=[spin], spin_ids=[spin_id],
fields=fields, field_count=field_count)
-
- # The dispersion data.
- cpmg_frqs = return_cpmg_frqs(ref_flag=False)
- spin_lock_nu1 = return_spin_lock_nu1(ref_flag=False)
-
- # Initialise the relaxation dispersion fit functions.
- model = Dispersion(model=spin.model,
num_params=param_num(spins=[spin]), num_spins=1, num_frq=field_count,
exp_types=exp_types, values=values, errors=errors, missing=missing,
frqs=frqs, frqs_H=frqs_H, cpmg_frqs=cpmg_frqs, spin_lock_nu1=spin_lock_nu1,
chemical_shifts=chemical_shifts, spin_lock_offsets=offsets,
tilt_angles=tilt_angles, r1=r1, relax_times=relax_times,
scaling_matrix=scaling_matrix)
-
- # Make a single function call. This will cause back calculation and
the data will be stored in the class instance.
- chi2 = model.func(param_vector)
-
- # Store the chi2 value.
- spin.chi2 = chi2
-
- # Reconstruct the back_calc data structure.
- back_calc = model.back_calc
- if spin.model not in MODEL_LIST_MMQ:
- back_calc = [back_calc]
-
- # Return the structure.
- return back_calc
-
-
def _back_calc_peak_intensities(self, spin=None, exp_type=None,
frq=None, point=None):
"""Back-calculation of peak intensity for the given relaxation time.
@@ -749,7 +690,7 @@
proton = return_attached_protons(spin_id)[0]
# The back calculated values.
- back_calc = self._back_calc_r2eff(spin=spin, spin_id=spin_id)
+ back_calc = back_calc_r2eff(spin=spin, spin_id=spin_id)
# Pack the data.
pack_back_calc_r2eff(spin=spin, spin_id=spin_id,
spin_index=0, back_calc=back_calc, proton_mmq_flag=proton_mmq_flag)
@@ -792,12 +733,12 @@
spin, spin_id = data_id
# Back calculate the R2eff/R1rho data.
- back_calc = self._back_calc_r2eff(spin=spin, spin_id=spin_id)
+ back_calc = back_calc_r2eff(spin=spin, spin_id=spin_id)
# Get the attached proton data.
if proton_mmq_flag:
proton = return_attached_protons(spin_id)[0]
- proton_back_calc = self._back_calc_r2eff(spin=proton,
spin_id=spin_id)
+ proton_back_calc = back_calc_r2eff(spin=proton,
spin_id=spin_id)
# Convert to a dictionary matching the R2eff data structure.
values = {}
Modified: branches/relax_disp/specific_analyses/relax_disp/optimisation.py
URL:
http://svn.gna.org/viewcvs/relax/branches/relax_disp/specific_analyses/relax_disp/optimisation.py?rev=21615&r1=21614&r2=21615&view=diff
==============================================================================
--- branches/relax_disp/specific_analyses/relax_disp/optimisation.py
(original)
+++ branches/relax_disp/specific_analyses/relax_disp/optimisation.py Sat Nov
23 18:23:15 2013
@@ -36,9 +36,68 @@
from lib.text.sectioning import subsection
from multi import Memo, Result_command, Slave_command
from specific_analyses.relax_disp.disp_data import has_disp_data,
has_proton_mmq_cpmg, loop_exp_frq, loop_exp_frq_point, loop_point,
pack_back_calc_r2eff, return_cpmg_frqs, return_index_from_disp_point,
return_index_from_exp_type, return_index_from_frq, return_offset_data,
return_param_key_from_data, return_r1_data, return_r2eff_arrays,
return_spin_lock_nu1, return_value_from_frq_index
-from specific_analyses.relax_disp.parameters import assemble_param_vector,
disassemble_param_vector, linear_constraints, loop_parameters,
param_conversion, param_num
+from specific_analyses.relax_disp.parameters import assemble_param_vector,
assemble_scaling_matrix, disassemble_param_vector, linear_constraints,
loop_parameters, param_conversion, param_num
from specific_analyses.relax_disp.variables import EXP_TYPE_CPMG_PROTON_MQ,
EXP_TYPE_CPMG_PROTON_SQ, MODEL_CR72, MODEL_CR72_FULL, MODEL_DPL94,
MODEL_LIST_MMQ, MODEL_LM63, MODEL_M61, MODEL_M61B, MODEL_MP05,
MODEL_NS_R1RHO_2SITE, MODEL_TAP03, MODEL_TP02
from target_functions.relax_disp import Dispersion
+
+
+def back_calc_r2eff(spin=None, spin_id=None):
+ """Back-calculation of R2eff/R1rho values for the given spin.
+
+ @keyword spin: The specific spin data container.
+ @type spin: SpinContainer instance
+ @keyword spin_id: The spin ID string for the spin container.
+ @type spin_id: str
+ @return: The back-calculated R2eff/R1rho value for the given
spin.
+ @rtype: numpy rank-1 float array
+ """
+
+ # Skip protons for MMQ data.
+ if spin.model in MODEL_LIST_MMQ and spin.isotope == '1H':
+ return
+
+ # Create the initial parameter vector.
+ param_vector = assemble_param_vector(spins=[spin])
+
+ # Create a scaling matrix.
+ scaling_matrix = assemble_scaling_matrix(spins=[spin], scaling=False)
+
+ # Number of spectrometer fields.
+ fields = [None]
+ field_count = 1
+ if hasattr(cdp, 'spectrometer_frq_count'):
+ fields = cdp.spectrometer_frq_list
+ field_count = cdp.spectrometer_frq_count
+
+ # Initialise the data structures for the target function.
+ values, errors, missing, frqs, frqs_H, exp_types, relax_times =
return_r2eff_arrays(spins=[spin], spin_ids=[spin_id], fields=fields,
field_count=field_count)
+
+ # The offset and R1 data for R1rho off-resonance models.
+ chemical_shifts, offsets, tilt_angles, r1 = None, None, None, None
+ if spin.model in [MODEL_DPL94, MODEL_TP02, MODEL_TAP03, MODEL_MP05,
MODEL_NS_R1RHO_2SITE]:
+ chemical_shifts, offsets, tilt_angles =
return_offset_data(spins=[spin], spin_ids=[spin_id], fields=fields,
field_count=field_count)
+ r1 = return_r1_data(spins=[spin], spin_ids=[spin_id], fields=fields,
field_count=field_count)
+
+ # The dispersion data.
+ cpmg_frqs = return_cpmg_frqs(ref_flag=False)
+ spin_lock_nu1 = return_spin_lock_nu1(ref_flag=False)
+
+ # Initialise the relaxation dispersion fit functions.
+ model = Dispersion(model=spin.model, num_params=param_num(spins=[spin]),
num_spins=1, num_frq=field_count, exp_types=exp_types, values=values,
errors=errors, missing=missing, frqs=frqs, frqs_H=frqs_H,
cpmg_frqs=cpmg_frqs, spin_lock_nu1=spin_lock_nu1,
chemical_shifts=chemical_shifts, spin_lock_offsets=offsets,
tilt_angles=tilt_angles, r1=r1, relax_times=relax_times,
scaling_matrix=scaling_matrix)
+
+ # Make a single function call. This will cause back calculation and the
data will be stored in the class instance.
+ chi2 = model.func(param_vector)
+
+ # Store the chi2 value.
+ spin.chi2 = chi2
+
+ # Reconstruct the back_calc data structure.
+ back_calc = model.back_calc
+ if spin.model not in MODEL_LIST_MMQ:
+ back_calc = [back_calc]
+
+ # Return the structure.
+ return back_calc
def grid_search_setup(spins=None, spin_ids=None, param_vector=None,
lower=None, upper=None, inc=None, scaling_matrix=None):
r21615 - in /branches/relax_disp/specific_analyses/relax_disp: api.py optimisation.py