Author: bugman
Date: Wed Jul 9 15:40:54 2008
New Revision: 6885
URL: http://svn.gna.org/viewcvs/relax?rev=6885&view=rev
Log:
Changed the N_state_opt functions to be model dependent.
The func_rdcs() method is now func_population(), and the func_tensors()
method is now
func_2domain().
Modified:
branches/rdc_analysis/maths_fns/n_state_model.py
Modified: branches/rdc_analysis/maths_fns/n_state_model.py
URL:
http://svn.gna.org/viewcvs/relax/branches/rdc_analysis/maths_fns/n_state_model.py?rev=6885&r1=6884&r2=6885&view=diff
==============================================================================
--- branches/rdc_analysis/maths_fns/n_state_model.py (original)
+++ branches/rdc_analysis/maths_fns/n_state_model.py Wed Jul 9 15:40:54 2008
@@ -68,8 +68,8 @@
self.params = 1.0 * init_params # Force a copy of the data to be
stored.
self.total_num_params = len(init_params)
- # Using alignment tensors.
- if full_tensors:
+ # The 2-domain N-state model.
+ if model == '2-domain':
# Some checks.
if red_data == None and not len(red_data):
raise RelaxError, "The red_data argument " + `red_data` + "
must be supplied."
@@ -96,10 +96,10 @@
self.red_bc_vector = zeros(self.num_tensors*5, float64)
# Set the target function.
- self.func = self.func_tensors
+ self.func = self.func_2domain
- # Using RDCs.
- elif rdcs:
+ # The flexible population N-state model.
+ elif model == 'population':
# Some checks.
if xh_vect == None and not len(xh_vect):
raise RelaxError, "The xh_vect argument " + `xh_vect` + "
must be supplied."
@@ -113,27 +113,11 @@
self.xh_vect.append(array(xh_vect[i], float64))
# Set the target function.
- self.func = self.func_rdcs
+ self.func = self.func_population
- def func_rdcs(self, params):
- """The target function for optimisation using RDCs.
-
- This function should be passed to the optimisation algorithm. It
accepts, as an array, a
- vector of parameter values and, using these, returns the single
chi-squared value
- corresponding to that coordinate in the parameter space. If no RDC
errors are supplied,
- then the SSE (the sum of squares error) value is returned instead.
The chi-squared is
- simply the SSE normalised to unit variance (the SSE divided by the
error squared).
-
- @param params: The vector of parameter values.
- @type params: list of float
- @return: The chi-squared or SSE value.
- @rtype: float
- """
-
-
- def func_tensors(self, params):
- """The target function for optimisation using alignment tensors.
+ def func_2domain(self, params):
+ """The target function for optimisation of the 2-domain N-state
model.
This function should be passed to the optimisation algorithm. It
accepts, as an array, a
vector of parameter values and, using these, returns the single
chi-squared value
@@ -188,3 +172,20 @@
# Return the chi-squared value.
return chi2(self.red_data, self.red_bc_vector, self.red_errors)
+
+
+ def func_population(self, params):
+ """The target function for optimisation of the flexible population
N-state model.
+
+ This function should be passed to the optimisation algorithm. It
accepts, as an array, a
+ vector of parameter values and, using these, returns the single
chi-squared value
+ corresponding to that coordinate in the parameter space. If no RDC
errors are supplied,
+ then the SSE (the sum of squares error) value is returned instead.
The chi-squared is
+ simply the SSE normalised to unit variance (the SSE divided by the
error squared).
+
+ @param params: The vector of parameter values.
+ @type params: list of float
+ @return: The chi-squared or SSE value.
+ @rtype: float
+ """
+
r6885 - /branches/rdc_analysis/maths_fns/n_state_model.py