Author: bugman
Date: Wed Nov 25 09:39:48 2009
New Revision: 9957
URL: http://svn.gna.org/viewcvs/relax?rev=9957&view=rev
Log:
Converted the frame order private methods into non-API methods.
Modified:
1.3/specific_fns/frame_order.py
Modified: 1.3/specific_fns/frame_order.py
URL:
http://svn.gna.org/viewcvs/relax/1.3/specific_fns/frame_order.py?rev=9957&r1=9956&r2=9957&view=diff
==============================================================================
--- 1.3/specific_fns/frame_order.py (original)
+++ 1.3/specific_fns/frame_order.py Wed Nov 25 09:39:48 2009
@@ -66,7 +66,7 @@
return array([cdp.alpha, cdp.beta, cdp.gamma, cdp.theta_axis,
cdp.phi_axis, cdp.theta_cone], float64)
- def __grid_row(self, incs, lower, upper, dist_type=None):
+ def _grid_row(self, incs, lower, upper, dist_type=None):
"""Set up a row of the grid search for a given parameter.
@param incs: The number of increments.
@@ -108,7 +108,7 @@
return list(row)
- def __minimise_setup_tensors(self, sim_index=None):
+ def _minimise_setup_tensors(self, sim_index=None):
"""Set up the data structures for optimisation using alignment
tensors as base data sets.
@keyword sim_index: The simulation index. This should be None if
normal optimisation is
@@ -127,7 +127,7 @@
raise RelaxError("The reference domain has not been set up.")
if not hasattr(cdp.align_tensors, 'reduction'):
raise RelaxError("The tensor reductions have not been
specified.")
- for i, tensor in self.__tensor_loop():
+ for i, tensor in self._tensor_loop():
if not hasattr(tensor, 'domain'):
raise RelaxError("The domain that the '%s' tensor is
attached to has not been set" % tensor.name)
@@ -139,7 +139,7 @@
full_in_ref_frame = zeros(n, float64)
# Loop over the full tensors.
- for i, tensor in self.__tensor_loop(red=False):
+ for i, tensor in self._tensor_loop(red=False):
# The full tensor.
full_tensors[5*i + 0] = tensor.Axx
full_tensors[5*i + 1] = tensor.Ayy
@@ -152,7 +152,7 @@
full_in_ref_frame[i] = 1
# Loop over the reduced tensors.
- for i, tensor in self.__tensor_loop(red=True):
+ for i, tensor in self._tensor_loop(red=True):
# The reduced tensor (simulation data).
if sim_index != None:
red_tensors[5*i + 0] = tensor.Axx_sim[sim_index]
@@ -181,7 +181,7 @@
return full_tensors, red_tensors, red_err, full_in_ref_frame
- def __tensor_loop(self, red=False):
+ def _tensor_loop(self, red=False):
"""Generator method for looping over the full or reduced tensors.
@keyword red: A flag which if True causes the reduced tensors to
be returned, and if False
@@ -209,7 +209,7 @@
yield i, data[list[i][index]]
- def __update_model(self):
+ def _update_model(self):
"""Update the model parameters as necessary."""
# Initialise the list of model parameters.
@@ -252,7 +252,7 @@
cdp.theta_cone = 0.0
- def __unpack_opt_results(self, results, sim_index=None):
+ def _unpack_opt_results(self, results, sim_index=None):
"""Unpack and store the Frame Order optimisation results.
@param results: The results tuple returned by the minfx
generic_minimise() function.
@@ -367,7 +367,7 @@
param_vector = self._assemble_param_vector()
# Get the data structures for optimisation using the tensors as base
data sets.
- full_tensors, red_tensors, red_tensor_err, full_in_ref_frame =
self.__minimise_setup_tensors()
+ full_tensors, red_tensors, red_tensor_err, full_in_ref_frame =
self._minimise_setup_tensors()
# Set up the optimisation function.
target = frame_order.Frame_order(model=cdp.model,
full_tensors=full_tensors, red_tensors=red_tensors,
red_errors=red_tensor_err, full_in_ref_frame=full_in_ref_frame)
@@ -398,7 +398,7 @@
param_vector = self._assemble_param_vector()
# Get the data structures for optimisation using the tensors as base
data sets.
- full_tensors, red_tensors, red_tensor_err, full_in_ref_frame =
self.__minimise_setup_tensors()
+ full_tensors, red_tensors, red_tensor_err, full_in_ref_frame =
self._minimise_setup_tensors()
# Set up the optimisation function.
target = frame_order.Frame_order(model=cdp.model,
full_tensors=full_tensors, red_tensors=red_tensors,
red_errors=red_tensor_err, full_in_ref_frame=full_in_ref_frame)
@@ -695,7 +695,7 @@
upper.append(pi)
# Get the grid row.
- row = self.__grid_row(incs[i], lower[i], upper[i],
dist_type=dist_type)
+ row = self._grid_row(incs[i], lower[i], upper[i],
dist_type=dist_type)
# Remove the end point.
row = row[:-1]
@@ -739,7 +739,7 @@
# Get the grid row.
if not row:
- row = self.__grid_row(incs[i], lower[i], upper[i],
dist_type=dist_type)
+ row = self._grid_row(incs[i], lower[i], upper[i],
dist_type=dist_type)
# Append the grid row.
grid.append(row)
@@ -821,7 +821,7 @@
param_vector = self._assemble_param_vector()
# Get the data structures for optimisation using the tensors as base
data sets.
- full_tensors, red_tensors, red_tensor_err, full_in_ref_frame =
self.__minimise_setup_tensors(sim_index)
+ full_tensors, red_tensors, red_tensor_err, full_in_ref_frame =
self._minimise_setup_tensors(sim_index)
# Set up the optimisation function.
target = frame_order.Frame_order(model=cdp.model,
full_tensors=full_tensors, red_tensors=red_tensors,
red_errors=red_tensor_err, full_in_ref_frame=full_in_ref_frame)
@@ -835,7 +835,7 @@
results = generic_minimise(func=target.func, args=(),
x0=param_vector, min_algor=min_algor, min_options=min_options,
func_tol=func_tol, grad_tol=grad_tol, maxiter=max_iterations,
full_output=True, print_flag=verbosity)
# Unpack the results.
- self.__unpack_opt_results(results, sim_index)
+ self._unpack_opt_results(results, sim_index)
def model_loop(self):
@@ -934,7 +934,7 @@
cdp.ref_domain = ref
# Update the model.
- self.__update_model()
+ self._update_model()
def return_data_name(self, param):
@@ -981,7 +981,7 @@
"""
# Get the tensor data structures.
- full_tensors, red_tensors, red_tensor_err, full_in_ref_frame =
self.__minimise_setup_tensors()
+ full_tensors, red_tensors, red_tensor_err, full_in_ref_frame =
self._minimise_setup_tensors()
# Return the errors.
return red_tensor_err
@@ -1042,7 +1042,7 @@
cdp.params = []
# Update the model.
- self.__update_model()
+ self._update_model()
def set_error(self, nothing, index, error):
@@ -1154,7 +1154,7 @@
sim_data = transpose(sim_data)
# Loop over the reduced tensors.
- for i, tensor in self.__tensor_loop(red=True):
+ for i, tensor in self._tensor_loop(red=True):
# Set the reduced tensor simulation data.
tensor.Axx_sim = sim_data[5*i + 0]
tensor.Ayy_sim = sim_data[5*i + 1]
r9957 - /1.3/specific_fns/frame_order.py