Author: bugman
Date: Fri Aug 8 11:17:22 2008
New Revision: 7115
URL: http://svn.gna.org/viewcvs/relax?rev=7115&view=rev
Log:
Changed the way optimisation of the N-state model is set up.
This will allow multiple base data types to be used simultaneously.
Modified:
branches/rdc_analysis/specific_fns/n_state_model.py
Modified: branches/rdc_analysis/specific_fns/n_state_model.py
URL:
http://svn.gna.org/viewcvs/relax/branches/rdc_analysis/specific_fns/n_state_model.py?rev=7115&r1=7114&r2=7115&view=diff
==============================================================================
--- branches/rdc_analysis/specific_fns/n_state_model.py (original)
+++ branches/rdc_analysis/specific_fns/n_state_model.py Fri Aug 8 11:17:22
2008
@@ -777,13 +777,18 @@
if constraints:
A, b = self.__linear_constraints(data_types=data_types,
scaling_matrix=scaling_matrix)
- # Set up minimisation using alignment tensors.
+ # Get the data structures for optimisation using the tensors as base
data sets.
+ full_tensors, red_tensor_elem, red_tensor_err, full_in_ref_frame =
None, None, None, None
if 'tensor' in data_types:
- model = self.minimise_setup_tensors(param_vector=param_vector,
scaling_matrix=scaling_matrix)
-
- # Set up minimisation using RDCs or PCSs.
- elif 'rdc' in data_types or 'pcs' in data_types:
- model = self.minimise_setup_rdcs(param_vector=param_vector,
scaling_matrix=scaling_matrix)
+ full_tensors, red_tensor_elem, red_tensor_err, full_in_ref_frame
= self.minimise_setup_tensors()
+
+ # Get the data structures for optimisation using RDCs as base data
sets.
+ rdcs, xh_vect, rdc_dj = None, None, None
+ if 'rdc' in data_types:
+ rdcs, xh_vect, rdc_dj = self.minimise_setup_rdcs()
+
+ # Set up the class instance containing the target function.
+ model = N_state_opt(model=cdp.model, N=cdp.N,
init_params=param_vector, full_tensors=full_tensors,
red_data=red_tensor_elem, red_errors=red_tensor_err,
full_in_ref_frame=full_in_ref_frame, rdcs=rdcs, xh_vect=xh_vect,
dip_const=rdc_dj, scaling_matrix=scaling_matrix)
# Minimisation.
if constraints:
@@ -853,14 +858,14 @@
def minimise_setup_rdcs(self, param_vector=None, scaling_matrix=None):
- """Set up minimisation for the N-state model using RDCs.
-
- @keyword param_vector: The parameter vector.
- @type param_vector: list of str
- @scaling_matrix: The square and diagonal scaling matrix.
- @scaling_matrix: numpy rank-2 array
- @return: The initialised N_state_opt class for
minimisation.
- @rteyp: N_state_opt instance
+ """Set up the data structures for optimisation using RDCs as base
data sets.
+
+ @return: The assembled data structures for using RDCs as the base
data for optimisation.
+ These include:
+ - rdcs, the RDC values.
+ - xh_vectors, the heteronucleus to proton vectors.
+ - dj, the dipolar constants.
+ @rtype: tuple of (numpy rank-2 array, numpy rank-2 array, numpy
rank-2 array)
"""
# Alias the current data pipe.
@@ -913,22 +918,21 @@
# Store the unit vector.
xh_vect_numpy[spin_index, state_index] =
xh_vectors[spin_index][state_index]
- # Set up the class instance containing the target function.
- model = N_state_opt(model=cdp.model, N=cdp.N,
init_params=param_vector, rdcs=rdcs_numpy, xh_vect=xh_vect_numpy,
dip_const=dj, scaling_matrix=scaling_matrix)
-
- # Return the instantiated class.
- return model
-
-
- def minimise_setup_tensors(self, param_vector=None, scaling_matrix=None):
- """Set up minimisation for the N-state model using alignment tensors.
-
- @keyword param_vector: The parameter vector.
- @type param_vector: list of str
- @scaling_matrix: The square and diagonal scaling matrix.
- @scaling_matrix: numpy rank-2 array
- @return: The initialised N_state_opt class for
minimisation.
- @rteyp: N_state_opt instance
+ # Return the data structures.
+ return rdcs_numpy, xh_vect_numpy, dj
+
+
+ def minimise_setup_tensors(self):
+ """Set up the data structures for optimisation using alignment
tensors as base data sets.
+
+ @return: The assembled data structures for using alignment
tensors as the base data for
+ optimisation. These include:
+ - full_tensors, the data of the full alignment
tensors.
+ - red_tensor_elem, the tensors as concatenated
rank-1 5D arrays.
+ - red_tensor_err, the tensor errors as concatenated
rank-1 5D arrays.
+ - full_in_ref_frame, flags specifying if the tensor
in the reference frame
+ is the full or reduced tensor.
+ @rtype: tuple of (list, numpy rank-1 array, numpy rank-1 array,
numpy rank-1 array)
"""
# Alias the current data pipe.
@@ -950,7 +954,7 @@
else:
full_in_ref_frame.append(0)
- # Create a list of matricies consisting of all the full
alignment tensors.
+ # Create a list of matrices consisting of all the full
alignment tensors.
full_tensors.append(tensor.tensor)
# Create a list of all the reduced alignment tensor elements and
their errors (for the chi-squared function).
@@ -979,11 +983,8 @@
red_tensor_err = array(red_tensor_err, float64)
full_in_ref_frame = array(full_in_ref_frame, float64)
- # Set up the class instance containing the target function.
- model = N_state_opt(model=cdp.model, N=cdp.N,
init_params=param_vector, full_tensors=full_tensors,
red_data=red_tensor_elem, red_errors=red_tensor_err,
full_in_ref_frame=full_in_ref_frame, scaling_matrix=scaling_matrix)
-
- # Return the instantiated class.
- return model
+ # Return the data structures.
+ return full_tensors, red_tensor_elem, red_tensor_err,
full_in_ref_frame
def number_of_states(self, N=None):
r7115 - /branches/rdc_analysis/specific_fns/n_state_model.py