Author: bugman
Date: Thu Jul 2 23:13:13 2009
New Revision: 9183
URL: http://svn.gna.org/viewcvs/relax?rev=9183&view=rev
Log:
Created and now using the full_in_ref_frame data structure (copy of N-state
model).
Modified:
branches/frame_order/maths_fns/frame_order_models.py
branches/frame_order/specific_fns/frame_order.py
Modified: branches/frame_order/maths_fns/frame_order_models.py
URL:
http://svn.gna.org/viewcvs/relax/branches/frame_order/maths_fns/frame_order_models.py?rev=9183&r1=9182&r2=9183&view=diff
==============================================================================
--- branches/frame_order/maths_fns/frame_order_models.py (original)
+++ branches/frame_order/maths_fns/frame_order_models.py Thu Jul 2 23:13:13
2009
@@ -39,7 +39,7 @@
class Frame_order:
"""Class containing the target function of the optimisation of Frame
Order matrix components."""
- def __init__(self, model=None, init_params=None, full_tensors=None,
red_tensors=None, red_errors=None, frame_order_2nd=None):
+ def __init__(self, model=None, init_params=None, full_tensors=None,
red_tensors=None, red_errors=None, full_in_ref_frame=None,
frame_order_2nd=None):
"""Set up the target functions for the Frame Order theories.
@keyword model: The name of the Frame Order model.
@@ -57,6 +57,9 @@
@keyword red_errors: An array of the {Sxx, Syy, Sxy, Sxz,
Syz} errors for all reduced
tensors. The array format is the same
as for full_tensors.
@type red_errors: numpy nx5D, rank-1 float64 array
+ @keyword full_in_ref_frame: An array of flags specifying if the
tensor in the reference
+ frame is the full or reduced tensor.
+ @type full_in_ref_frame: numpy rank-1 array
@keyword frame_order_2nd: The numerical values of the 2nd degree
Frame Order matrix. If
supplied, the target functions will
optimise directly to these
values.
@@ -72,13 +75,21 @@
# Isotropic cone model.
if model == 'iso cone':
+ # Some checks.
+ if red_tensors == None or not len(red_tensors):
+ raise RelaxError, "The red_tensors argument " +
`red_tensors` + " must be supplied."
+ if red_errors == None or not len(red_errors):
+ raise RelaxError, "The red_errors argument " + `red_errors`
+ " must be supplied."
+ if full_in_ref_frame == None or not len(full_in_ref_frame):
+ raise RelaxError, "The full_in_ref_frame argument " +
`full_in_ref_frame` + " must be supplied."
+
# Mix up.
if full_tensors != None and frame_order_2nd != None:
raise RelaxError, "Tensors and Frame Order matrices cannot
be supplied together."
# Tensor optimisation.
elif full_tensors != None:
- self.__init_iso_cone(full_tensors, red_tensors, red_errors)
+ self.__init_iso_cone(full_tensors, red_tensors, red_errors,
full_in_ref_frame)
# Optimisation to the 2nd degree Frame Order matrix components
directly.
elif frame_order_2nd != None:
@@ -115,6 +126,7 @@
self.red_tensors = red_tensors
self.red_errors = red_errors
self.red_tensors_bc = zeros(self.num_tensors*5, float64)
+ self.full_in_ref_frame = full_in_ref_frame
# The cone axis storage and molecular frame z-axis.
self.cone_axis = zeros(3, float64)
@@ -192,9 +204,19 @@
# Reduce the tensor.
reduce_alignment_tensor(self.frame_order_2nd,
self.full_tensors[index1:index2], self.red_tensors_bc[index1:index2])
- # Rotate the tensor.
+ # Convert the tensor to 3D, rank-2 form.
to_tensor(self.tensor_3D, self.red_tensors_bc[index1:index2])
- to_5D(self.red_tensors_bc[index1:index2], dot(self.rot,
dot(self.tensor_3D, transpose(self.rot))))
+
+ # Rotate the tensor (normal R.X.RT rotation).
+ if self.full_in_ref_frame[i]:
+ self.tensor_3D = dot(self.rot, dot(self.tensor_3D,
transpose(self.rot)))
+
+ # Rotate the tensor (inverse RT.X.R rotation).
+ else:
+ self.tensor_3D = dot(transpose(self.rot),
dot(self.tensor_3D, self.rot))
+
+ # Convert the tensor back to 5D, rank-1 form.
+ to_5D(self.red_tensors_bc[index1:index2], self.tensor_3D)
# Return the chi-squared value.
return chi2(self.red_tensors, self.red_tensors_bc, self.red_errors)
Modified: branches/frame_order/specific_fns/frame_order.py
URL:
http://svn.gna.org/viewcvs/relax/branches/frame_order/specific_fns/frame_order.py?rev=9183&r1=9182&r2=9183&view=diff
==============================================================================
--- branches/frame_order/specific_fns/frame_order.py (original)
+++ branches/frame_order/specific_fns/frame_order.py Thu Jul 2 23:13:13 2009
@@ -68,6 +68,7 @@
full_tensors = zeros(n*5, float64)
red_tensors = zeros(n*5, float64)
red_err = ones(n*5, float64) * 1e-5
+ full_in_ref_frame = zeros(n, float64)
# Loop over the full tensors.
for i, tensor in self.__tensor_loop(red=False):
@@ -77,6 +78,10 @@
full_tensors[5*i + 2] = tensor.Axy
full_tensors[5*i + 3] = tensor.Axz
full_tensors[5*i + 4] = tensor.Ayz
+
+ # The full tensor corresponds to the frame of reference.
+ if cdp.ref_domain == tensor.domain:
+ full_in_ref_frame[i] = 1
# Loop over the reduced tensors.
for i, tensor in self.__tensor_loop(red=True):
@@ -105,7 +110,7 @@
red_err[5*i + 4] = tensor.Ayz_err
# Return the data structures.
- return full_tensors, red_tensors, red_err
+ return full_tensors, red_tensors, red_err, full_in_ref_frame
def __tensor_loop(self, red=False):
@@ -268,10 +273,10 @@
param_vector = array([cdp.alpha, cdp.beta, cdp.gamma,
cdp.theta_axis, cdp.phi_axis, cdp.theta_cone], float64)
# Get the data structures for optimisation using the tensors as
base data sets.
- full_tensors, red_tensors, red_tensor_err =
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_models.Frame_order(model=cdp.model,
full_tensors=full_tensors, red_tensors=red_tensors, red_errors=red_tensor_err)
+ target = frame_order_models.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)
# Make a single function call. This will cause back calculation
and the data will be stored in the class instance.
target.func(param_vector)
@@ -304,10 +309,10 @@
param_vector = array([cdp.alpha, cdp.beta, cdp.gamma,
cdp.theta_axis, cdp.phi_axis, cdp.theta_cone], float64)
# Get the data structures for optimisation using the tensors as
base data sets.
- full_tensors, red_tensors, red_tensor_err =
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_models.Frame_order(model=cdp.model,
full_tensors=full_tensors, red_tensors=red_tensors, red_errors=red_tensor_err)
+ target = frame_order_models.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)
# Make a single function call. This will cause back calculation
and the data will be stored in the class instance.
chi2 = target.func(param_vector)
@@ -623,10 +628,10 @@
param_vector = array([cdp.alpha, cdp.beta, cdp.gamma,
cdp.theta_axis, cdp.phi_axis, cdp.theta_cone], float64)
# Get the data structures for optimisation using the tensors as
base data sets.
- full_tensors, red_tensors, red_tensor_err =
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_models.Frame_order(model=cdp.model,
full_tensors=full_tensors, red_tensors=red_tensors, red_errors=red_tensor_err)
+ target = frame_order_models.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)
# Minimisation.
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=1,
print_flag=verbosity)
@@ -682,7 +687,7 @@
"""
# Get the tensor data structures.
- full_tensors, red_tensors, red_tensor_err =
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
r9183 - in /branches/frame_order: maths_fns/frame_order_models.py specific_fns/frame_order.py