Author: bugman
Date: Sun Aug 17 19:12:21 2008
New Revision: 7207
URL: http://svn.gna.org/viewcvs/relax?rev=7207&view=rev
Log:
The RDC and PCS errors data structures are now created by the
__minimise_setup_*() methods.
These are also passed into the minimisation code.
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=7207&r1=7206&r2=7207&view=diff
==============================================================================
--- branches/rdc_analysis/specific_fns/n_state_model.py (original)
+++ branches/rdc_analysis/specific_fns/n_state_model.py Sun Aug 17 19:12:21
2008
@@ -402,6 +402,7 @@
# Initialise.
pcs = []
+ pcs_err = []
unit_vect = []
r = []
pcs_const = []
@@ -418,6 +419,12 @@
# Append the PCSs to the list.
pcs.append(spin.pcs)
+
+ # Append the PCS errors (or a list of None).
+ if hasattr(spin, 'pcs_err'):
+ pcs_err.append(spin.pcs_err)
+ else:
+ pcs_err.append([None]*len(spin.pcs))
# Add empty lists to the r and unit_vector lists.
unit_vect.append([])
@@ -473,14 +480,16 @@
# Initialise the numpy objects (the pcs matrix is transposed!).
pcs_numpy = zeros((len(pcs[0]), len(pcs)), float64)
+ pcs_err_numpy = zeros((len(pcs[0]), len(pcs)), float64)
unit_vect_numpy = zeros((len(unit_vect), len(unit_vect[0]), 3),
float64)
# Loop over the spins.
for spin_index in xrange(len(pcs)):
# Loop over the alignments.
for align_index in xrange(len(pcs[spin_index])):
- # Transpose and store the PCS value.
+ # Transpose and store the PCS value and error.
pcs_numpy[align_index, spin_index] =
pcs[spin_index][align_index]
+ pcs_err_numpy[align_index, spin_index] =
pcs_err[spin_index][align_index]
# Loop over the N states.
for state_index in xrange(len(unit_vect[spin_index])):
@@ -489,9 +498,10 @@
# Convert the PCS from ppm to no units.
pcs_numpy = pcs_numpy * 1e-6
+ pcs_err_numpy = pcs_err_numpy * 1e-6
# Return the data structures.
- return pcs_numpy, unit_vect_numpy, array(pcs_const)
+ return pcs_numpy, pcs_err_numpy, unit_vect_numpy, array(pcs_const)
def __minimise_setup_rdcs(self, param_vector=None, scaling_matrix=None):
@@ -510,6 +520,7 @@
# Initialise.
rdcs = []
+ rdc_err = []
xh_vectors = []
dj = []
@@ -524,6 +535,7 @@
# Add rows of None if other data exists.
if hasattr(spin, 'pcs'):
rdcs.append([None]*len(cdp.align_tensors))
+ rdc_err.append([None]*len(cdp.align_tensors))
xh_vectors.append([None]*3)
dj.append(None)
@@ -538,6 +550,7 @@
# Add rows of None if other data exists.
if hasattr(spin, 'pcs'):
rdcs.append([None]*len(cdp.align_tensors))
+ rdc_err.append([None]*len(cdp.align_tensors))
xh_vectors.append([None]*3)
dj.append(None)
@@ -548,6 +561,12 @@
rdcs.append(spin.rdc)
xh_vectors.append(spin.xh_vect)
+ # Append the PCS errors (or a list of None).
+ if hasattr(spin, 'rdc_err'):
+ rdc_err.append(spin.rdc_err)
+ else:
+ rdc_err.append([None]*len(cdp.align_tensors))
+
# Gyromagnetic ratios.
gx = return_gyromagnetic_ratio(spin.heteronuc_type)
gh = return_gyromagnetic_ratio(spin.proton_type)
@@ -557,14 +576,16 @@
# Initialise the numpy objects (the rdc matrix is transposed!).
rdcs_numpy = zeros((len(rdcs[0]), len(rdcs)), float64)
+ rdc_err_numpy = zeros((len(rdcs[0]), len(rdcs)), float64)
xh_vect_numpy = zeros((len(xh_vectors), len(xh_vectors[0]), 3),
float64)
# Loop over the spins.
for spin_index in xrange(len(rdcs)):
# Loop over the alignments.
for align_index in xrange(len(rdcs[spin_index])):
- # Transpose and store the RDC value.
+ # Transpose and store the RDC value and error.
rdcs_numpy[align_index, spin_index] =
rdcs[spin_index][align_index]
+ rdc_err_numpy[align_index, spin_index] =
rdc_err[spin_index][align_index]
# Loop over the N states.
for state_index in xrange(len(xh_vectors[spin_index])):
@@ -572,7 +593,7 @@
xh_vect_numpy[spin_index, state_index] =
xh_vectors[spin_index][state_index]
# Return the data structures.
- return rdcs_numpy, xh_vect_numpy, array(dj, float64)
+ return rdcs_numpy, rdc_err_numpy, xh_vect_numpy, array(dj, float64)
def __minimise_setup_tensors(self):
@@ -1081,17 +1102,17 @@
full_tensors, red_tensor_elem, red_tensor_err, full_in_ref_frame
= self.__minimise_setup_tensors()
# Get the data structures for optimisation using PCSs as base data
sets.
- pcs, pcs_vect, pcs_dj = None, None, None
+ pcs, pcs_err, pcs_vect, pcs_dj = None, None, None, None
if 'pcs' in data_types:
- pcs, pcs_vect, pcs_dj = self.__minimise_setup_pcs()
+ pcs, pcs_err, pcs_vect, pcs_dj = self.__minimise_setup_pcs()
# Get the data structures for optimisation using RDCs as base data
sets.
- rdcs, xh_vect, rdc_dj = None, None, None
+ rdcs, rdc_err, xh_vect, rdc_dj = None, None, None, None
if 'rdc' in data_types:
- rdcs, xh_vect, rdc_dj = self.__minimise_setup_rdcs()
+ rdcs, rdc_err, 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, pcs=pcs, rdcs=rdcs, pcs_vect=pcs_vect,
xh_vect=xh_vect, pcs_const=pcs_dj, dip_const=rdc_dj,
scaling_matrix=scaling_matrix)
+ 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, pcs=pcs, rdcs=rdcs, pcs_errors=pcs_err,
rdc_errors=rdc_err, pcs_vect=pcs_vect, xh_vect=xh_vect, pcs_const=pcs_dj,
dip_const=rdc_dj, scaling_matrix=scaling_matrix)
# Minimisation.
if constraints:
r7207 - /branches/rdc_analysis/specific_fns/n_state_model.py