Author: bugman
Date: Fri Jun 19 16:07:41 2009
New Revision: 9103
URL: http://svn.gna.org/viewcvs/relax?rev=9103&view=rev
Log:
Preliminary support for optimisation against alignment tensors.
Added the func_iso_cone() and __init_iso_cone() methods.
Modified:
branches/frame_order/maths_fns/frame_order_models.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=9103&r1=9102&r2=9103&view=diff
==============================================================================
--- branches/frame_order/maths_fns/frame_order_models.py (original)
+++ branches/frame_order/maths_fns/frame_order_models.py Fri Jun 19 16:07:41
2009
@@ -24,24 +24,35 @@
"""Module containing the target functions of the Frame Order theories."""
# Python module imports.
-from numpy import dot, float64, ones, transpose, zeros
+from copy import deepcopy
+from numpy import float64, ones, zeros
# relax module imports.
from maths_fns.chi2 import chi2
-from maths_fns.frame_order_matrix_ops import populate_2nd_eigenframe_iso_cone
-from maths_fns.kronecker_product import kron_prod, transpose_14
-from maths_fns.rotation_matrix import R_euler_zyz
+from maths_fns.frame_order_matrix_ops import compile_2nd_matrix_iso_cone
from relax_errors import RelaxError
class Frame_order:
"""Class containing the target function of the optimisation of Frame
Order matrix components."""
- def __init__(self, model=None, frame_order_2nd=None):
+ def __init__(self, model=None, init_params=None, full_tensors=None,
red_tensors=None, red_errors=None, frame_order_2nd=None):
"""Set up the target functions for the Frame Order theories.
@keyword model: The name of the Frame Order model.
@type model: str
+ @keyword init_params: The initial parameter values.
+ @type init_params: numpy float64 array
+ @keyword full_tensors: A list of the full alignment tensors in
5D, rank-1 form of {Sxx,
+ Syy, Sxy, Sxz, Syz} values.
+ @type full_tensors: list of 5D, rank-1 arrays
+ @keyword red_tensors: An array of the {Sxx, Syy, Sxy, Sxz,
Syz} values for all reduced
+ tensors. The format is [Sxx1, Syy1,
Sxy1, Sxz1, Syz1, Sxx2,
+ Syy2, Sxy2, Sxz2, Syz2, ..., Sxxn, Syyn,
Sxyn, Sxzn, Syzn]
+ @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 red_tensors.
+ @type red_errors: numpy nx5D, rank-1 float64 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.
@@ -52,11 +63,57 @@
if not model:
raise RelaxError, "The type of Frame Order model must be
specified."
+ # Store the initial parameter (as a copy).
+ self.params = deepcopy(init_params)
+
# 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 optimisation.
+ if full_tensors != None:
+ self.__init_iso_cone_elements(full_tensors, red_tensors,
red_errors)
+
# Optimisation to the 2nd degree Frame Order matrix components
directly.
if frame_order_2nd != None:
self.__init_iso_cone_elements(frame_order_2nd)
+
+
+ def __init_iso_cone(self, full_tensors, red_tensors, red_errors):
+ """Set up isotropic cone optimisation against the alignment tensor
data.
+
+ @keyword full_tensors: A list of the full alignment tensors in
5D, rank-1 form of {Sxx,
+ Syy, Sxy, Sxz, Syz} values.
+ @type full_tensors: list of 5D, rank-1 arrays
+ @keyword red_tensors: An array of the {Sxx, Syy, Sxy, Sxz,
Syz} values for all reduced
+ tensors. The format is [Sxx1, Syy1,
Sxy1, Sxz1, Syz1, Sxx2,
+ Syy2, Sxy2, Sxz2, Syz2, ..., Sxxn, Syyn,
Sxyn, Sxzn, Syzn]
+ @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 red_tensors.
+ @type red_errors: numpy nx5D, rank-1 float64 array
+ """
+
+ # Checks.
+ if red_tensors != None:
+ raise RelaxError, "The reduced tensors have not been supplied."
+
+ # Tensor set up.
+ self.full_tensors = array(full_tensors, float64)
+ self.num_tensors = len(self.full_tensors)
+ self.red_tensors = red_tensors
+ self.red_errors = red_errors
+
+ # The rotation to the Frame Order eigenframe.
+ self.rot = zeros((3, 3), float64)
+
+ # 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):
@@ -84,12 +141,12 @@
self.func = self.func_iso_cone_elements
- def func_iso_cone_elements(self, params):
- """Target function for isotropic cone model optimisation using the
Frame Order matrix.
-
- This function optimises by directly matching the elements of the 2nd
degree Frame Order
- super matrix. The Frame Order eigenframe via the alpha, beta, and
gamma Euler angles, and
- the cone angle theta are the 4 parameters optimised in this model.
+ def func_iso_cone(self, params):
+ """Target function for isotropic cone model optimisation using the
alignment tensors.
+
+ This function optimises against alignment tensors. The Frame Order
eigenframe via the
+ alpha, beta, and gamma Euler angles, and the cone angle theta are
the 4 parameters optimised
+ in this model.
@param params: The vector of parameter values {alpha, beta, gamma,
theta} where the first
three are the Euler angles for the Frame Order
eigenframe and theta is the
@@ -102,25 +159,38 @@
# Break up the parameters.
alpha, beta, gamma, theta = params
- # Populate the Frame Order matrix in the eigenframe.
- populate_2nd_eigenframe_iso_cone(self.frame_order_2nd, theta)
-
- # Generate the rotation matrix.
- R_euler_zyz(self.rot, alpha, beta, gamma)
-
- # The outer product of R.
- R_kron = kron_prod(self.rot, self.rot)
-
- # Perform the T14 transpose to obtain the Kronecker product matrix!
- self.frame_order_2nd = transpose_14(self.frame_order_2nd)
-
- # Rotate.
- self.frame_order_2nd = dot(R_kron, dot(self.frame_order_2nd,
transpose(R_kron)))
-
- # Perform T14 again to return back.
- self.frame_order_2nd = transpose_14(self.frame_order_2nd)
-
- # Make the Frame Order contiguous.
+ # Generate the 2nd degree Frame Order super matrix.
+ compile_2nd_matrix_iso_cone(self.frame_order_2nd, self.rot, alpha,
beta, gamma, theta)
+
+ # Get the chi-squared value.
+ val = chi2(self.data, self.frame_order_2nd, self.errors)
+
+ # Return the chi2 value.
+ return val
+
+
+ def func_iso_cone_elements(self, params):
+ """Target function for isotropic cone model optimisation using the
Frame Order matrix.
+
+ This function optimises by directly matching the elements of the 2nd
degree Frame Order
+ super matrix. The Frame Order eigenframe via the alpha, beta, and
gamma Euler angles, and
+ the cone angle theta are the 4 parameters optimised in this model.
+
+ @param params: The vector of parameter values {alpha, beta, gamma,
theta} where the first
+ three are the Euler angles for the Frame Order
eigenframe and theta is the
+ isotropic cone angle.
+ @type params: list of float
+ @return: The chi-squared or SSE value.
+ @rtype: float
+ """
+
+ # Break up the parameters.
+ alpha, beta, gamma, theta = params
+
+ # Generate the 2nd degree Frame Order super matrix.
+ compile_2nd_matrix_iso_cone(self.frame_order_2nd, self.rot, alpha,
beta, gamma, theta)
+
+ # Make the Frame Order matrix contiguous.
self.frame_order_2nd = self.frame_order_2nd.copy()
# Reshape the numpy arrays for use in the chi2() function.
r9103 - /branches/frame_order/maths_fns/frame_order_models.py