Author: bugman
Date: Wed Jul 21 13:38:29 2010
New Revision: 11328
URL: http://svn.gna.org/viewcvs/relax?rev=11328&view=rev
Log:
Created the func_pseudo_ellipse() optimisation target fn. for the
pseudo-elliptic cone model.
The structure of the Frame_order class has been simplified for handling
multiple frame order models.
Modified:
1.3/maths_fns/frame_order.py
Modified: 1.3/maths_fns/frame_order.py
URL:
http://svn.gna.org/viewcvs/relax/1.3/maths_fns/frame_order.py?rev=11328&r1=11327&r2=11328&view=diff
==============================================================================
--- 1.3/maths_fns/frame_order.py (original)
+++ 1.3/maths_fns/frame_order.py Wed Jul 21 13:38:29 2010
@@ -31,7 +31,7 @@
from generic_fns.frame_order import print_frame_order_2nd_degree
from maths_fns.alignment_tensor import to_5D, to_tensor
from maths_fns.chi2 import chi2
-from maths_fns.frame_order_matrix_ops import compile_2nd_matrix_iso_cone,
reduce_alignment_tensor
+from maths_fns.frame_order_matrix_ops import compile_2nd_matrix_iso_cone,
compile_2nd_matrix_pseudo_ellipse, reduce_alignment_tensor
from maths_fns.rotation_matrix import euler_to_R_zyz as euler_to_R
from relax_errors import RelaxError
@@ -65,65 +65,63 @@
# Store the initial parameter (as a copy).
self.params = deepcopy(init_params)
+ # Store the agrs.
+ self.model = model
+ self.full_tensors = full_tensors
+ self.red_tensors = red_tensors
+ self.red_errors = red_errors
+ self.full_in_ref_frame = full_in_ref_frame
+
+ # Mix up.
+ if full_tensors != None and frame_order_2nd != None:
+ raise RelaxError("Tensors and Frame Order matrices cannot be
supplied together.")
+ if full_tensors == None and frame_order_2nd == None:
+ raise RelaxError("The arguments have been incorrectly supplied,
cannot determine the optimisation mode.")
+
+ # Tensor setup.
+ if full_tensors != None:
+ self.__init_tensors()
+
# The rigid model.
if model == 'rigid':
- # Tensor optimisation.
- self.__init_tensors(full_tensors, red_tensors, red_errors,
full_in_ref_frame)
-
# Alias the target function.
self.func = self.func_rigid
# Isotropic cone model.
if model == 'iso cone':
- # Mix up.
- if full_tensors != None and frame_order_2nd != None:
- raise RelaxError("Tensors and Frame Order matrices cannot be
supplied together.")
-
- # Tensor setup.
- if full_tensors != None:
- self.__init_tensors(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:
+ if frame_order_2nd != None:
self.__init_iso_cone_elements(frame_order_2nd)
-
- # Badly supplied arguments.
- else:
- raise RelaxError("The arguments have been incorrectly
supplied, cannot determine the optimisation mode.")
# The cone axis storage and molecular frame z-axis.
self.cone_axis = zeros(3, float64)
self.z_axis = array([0, 0, 1], float64)
-
- def __init_tensors(self, full_tensors, red_tensors, red_errors,
full_in_ref_frame):
- """Set up isotropic cone optimisation against the alignment tensor
data.
-
- @keyword full_tensors: An array of the {Sxx, Syy, Sxy, Sxz,
Syz} values for all full alignment tensors. The format is [Sxx1, Syy1, Sxy1,
Sxz1, Syz1, Sxx2, Syy2, Sxy2, Sxz2, Syz2, ..., Sxxn, Syyn, Sxyn, Sxzn, Syzn].
- @type full_tensors: numpy nx5D, rank-1 float64 array
- @keyword red_tensors: An array of the {Sxx, Syy, Sxy, Sxz,
Syz} values for all reduced tensors. The array format is the same as for
full_tensors.
- @type red_tensors: numpy nx5D, rank-1 float64 array
- @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
- """
+ # Alias the target function.
+ self.func = self.func_iso_cone
+
+ # Pseudo-ellipse cone model.
+ elif model == 'pseudo-ellipse':
+ # Alias the target function.
+ self.func = self.func_pseudo_ellipse
+
+
+ def __init_tensors(self):
+ """Set up isotropic cone optimisation against the alignment tensor
data."""
# Some checks.
- if full_tensors == None or not len(full_tensors):
- raise RelaxError("The full_tensors argument " +
repr(full_tensors) + " must be supplied.")
- if red_tensors == None or not len(red_tensors):
- raise RelaxError("The red_tensors argument " + repr(red_tensors)
+ " must be supplied.")
- if red_errors == None or not len(red_errors):
- raise RelaxError("The red_errors argument " + repr(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 " +
repr(full_in_ref_frame) + " must be supplied.")
+ if self.full_tensors == None or not len(self.full_tensors):
+ raise RelaxError("The full_tensors argument " +
repr(self.full_tensors) + " must be supplied.")
+ if self.red_tensors == None or not len(self.red_tensors):
+ raise RelaxError("The red_tensors argument " +
repr(self.red_tensors) + " must be supplied.")
+ if self.red_errors == None or not len(self.red_errors):
+ raise RelaxError("The red_errors argument " +
repr(self.red_errors) + " must be supplied.")
+ if self.full_in_ref_frame == None or not len(self.full_in_ref_frame):
+ raise RelaxError("The full_in_ref_frame argument " +
repr(self.full_in_ref_frame) + " must be supplied.")
# Tensor set up.
- self.num_tensors = len(full_tensors) / 5
- self.full_tensors = full_tensors
- self.red_tensors = red_tensors
- self.red_errors = red_errors
+ self.num_tensors = len(self.full_tensors) / 5
self.red_tensors_bc = zeros(self.num_tensors*5, float64)
- self.full_in_ref_frame = full_in_ref_frame
# The rotation to the Frame Order eigenframe.
self.rot = zeros((3, 3), float64)
@@ -131,9 +129,6 @@
# Initialise the Frame Order matrices.
self.frame_order_2nd = zeros((9, 9), float64)
-
- # Alias the target function.
- self.func = self.func_iso_cone
def __init_iso_cone_elements(self, frame_order_2nd):
@@ -288,3 +283,48 @@
# Return the chi2 value.
return val
+
+
+ def func_pseudo_ellipse(self, params):
+ """Target function for pseudo-elliptic cone model optimisation using
alignment tensors.
+
+ @param params: The vector of parameter values {alpha, beta, gamma,
eigen_alpha, eigen_beta, eigen_gamma, cone_theta_x, cone_theta_y,
cone_sigma_max} where the first 3 are the average position rotation Euler
angles, the next 3 are the Euler angles defining the eigenframe, and the last
3 are the pseudo-elliptic cone geometric parameters.
+ @type params: list of float
+ @return: The chi-squared or SSE value.
+ @rtype: float
+ """
+
+ # Unpack the parameters.
+ alpha, beta, gamma, eigen_alpha, eigen_beta, eigen_gamma,
cone_theta_x, cone_theta_y, cone_sigma_max = params
+
+ # Generate the 2nd degree Frame Order super matrix.
+ self.frame_order_2nd =
compile_2nd_matrix_pseudo_ellipse(self.frame_order_2nd, self.rot,
eigen_alpha, eigen_beta, eigen_gamma, cone_theta_x, cone_theta_y,
cone_sigma_max)
+
+ # Average position rotation.
+ euler_to_R(alpha, beta, gamma, self.rot)
+
+ # Back calculate the reduced tensors.
+ for i in range(self.num_tensors):
+ # Tensor indices.
+ index1 = i*5
+ index2 = i*5+5
+
+ # Reduce the tensor.
+ reduce_alignment_tensor(self.frame_order_2nd,
self.full_tensors[index1:index2], self.red_tensors_bc[index1:index2])
+
+ # Convert the tensor to 3D, rank-2 form.
+ to_tensor(self.tensor_3D, self.red_tensors_bc[index1:index2])
+
+ # 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)
r11328 - /1.3/maths_fns/frame_order.py