Author: bugman
Date: Fri Mar 22 11:49:43 2013
New Revision: 18944
URL: http://svn.gna.org/viewcvs/relax?rev=18944&view=rev
Log:
Next block of the manual merger of the frame_order_testing branch.
The commands used were:
svn merge -r15040:15041
svn+ssh://bugman@xxxxxxxxxxx/svn/relax/branches/frame_order_testing .
svn merge -r15041:15042
svn+ssh://bugman@xxxxxxxxxxx/svn/relax/branches/frame_order_testing .
svn merge -r15042:15043
svn+ssh://bugman@xxxxxxxxxxx/svn/relax/branches/frame_order_testing .
svn merge -r15043:15044
svn+ssh://bugman@xxxxxxxxxxx/svn/relax/branches/frame_order_testing .
svn merge -r15044:15045
svn+ssh://bugman@xxxxxxxxxxx/svn/relax/branches/frame_order_testing .
svn merge -r15045:15046
svn+ssh://bugman@xxxxxxxxxxx/svn/relax/branches/frame_order_testing .
svn merge -r15046:15047
svn+ssh://bugman@xxxxxxxxxxx/svn/relax/branches/frame_order_testing .
svn merge -r15047:15048
svn+ssh://bugman@xxxxxxxxxxx/svn/relax/branches/frame_order_testing .
svn merge -r15048:15049
svn+ssh://bugman@xxxxxxxxxxx/svn/relax/branches/frame_order_testing .
svn merge -r15049:15050
svn+ssh://bugman@xxxxxxxxxxx/svn/relax/branches/frame_order_testing .
A few missing user functions in prompt/ had to be resolved.
Modified:
trunk/generic_fns/align_tensor.py
trunk/maths_fns/frame_order.py
trunk/specific_fns/frame_order.py
Modified: trunk/generic_fns/align_tensor.py
URL:
http://svn.gna.org/viewcvs/relax/trunk/generic_fns/align_tensor.py?rev=18944&r1=18943&r2=18944&view=diff
==============================================================================
--- trunk/generic_fns/align_tensor.py (original)
+++ trunk/generic_fns/align_tensor.py Fri Mar 22 11:49:43 2013
@@ -247,7 +247,9 @@
if tensor:
tensors = [tensor]
else:
- tensors = cdp.align_ids
+ tensors = []
+ for i in range(len(cdp.align_tensors)):
+ tensors.append(cdp.align_tensors[i].name)
# Loop over the tensors.
for tensor in tensors:
@@ -672,7 +674,7 @@
return data
-def init(tensor=None, params=None, scale=1.0, angle_units='deg',
param_types=0, errors=False):
+def init(tensor=None, params=None, scale=1.0, angle_units='deg',
param_types=0, align_id=None, domain=None, errors=False):
"""Function for initialising the alignment tensor.
@keyword tensor: The alignment tensor identification string.
@@ -683,11 +685,13 @@
@type scale: float
@keyword angle_units: The units for the angle parameters (either 'deg'
or 'rad').
@type angle_units: str
- @keyword param_types: The type of parameters supplied. The flag
values correspond to, 0:
- {Axx, Ayy, Axy, Axz, Ayz}, and 1: {Azz, Axx-yy,
Axy, Axz, Ayz}.
+ @keyword param_types: The type of parameters supplied. The flag
values correspond to, 0: {Axx, Ayy, Axy, Axz, Ayz}, and 1: {Azz, Axx-yy, Axy,
Axz, Ayz}.
@type param_types: int
- @keyword errors: A flag which determines if the alignment tensor
data or its errors are
- being input.
+ @keyword align_id: The alignment ID string that the tensor
corresponds to.
+ @type align_id: str or None
+ @keyword domain: The domain label.
+ @type domain: str or None
+ @keyword errors: A flag which determines if the alignment tensor
data or its errors are being input.
@type errors: bool
"""
@@ -703,11 +707,16 @@
if not angle_units in valid_types:
raise RelaxError("The alignment tensor 'angle_units' argument " +
repr(angle_units) + " should be either 'deg' or 'rad'.")
- # Add the tensor ID to the current data pipe.
- if not hasattr(cdp, 'align_ids'):
- cdp.align_ids = []
- if tensor not in cdp.align_ids:
- cdp.align_ids.append(tensor)
+ # Check that the domain is defined.
+ if domain and (not hasattr(cdp, 'domain') or domain not in
cdp.domain.keys()):
+ raise RelaxError("The domain '%s' has not been defined. Please use
the domain user function." % domain)
+
+ # Add the align ID to the current data pipe if needed.
+ if align_id:
+ if not hasattr(cdp, 'align_ids'):
+ cdp.align_ids = []
+ if align_id not in cdp.align_ids:
+ cdp.align_ids.append(align_id)
# Add the align_tensors object to the data pipe.
if not errors:
@@ -869,6 +878,12 @@
# Unknown parameter combination.
else:
raise RelaxUnknownParamCombError('param_types', param_types)
+
+ # Set the domain and alignment ID.
+ if domain:
+ set_domain(tensor=tensor, domain=domain)
+ if align_id:
+ set_domain(tensor=tensor, align_id=align_id)
def map_bounds(param):
@@ -1841,6 +1856,28 @@
"""
+def set_align_id(tensor=None, align_id=None):
+ """Set the align ID string for the given tensor.
+
+ @keyword tensor: The alignment tensor label.
+ @type tensor: str
+ @keyword align_id: The alignment ID string.
+ @type align_id: str
+ """
+
+ # Loop over the tensors.
+ match = False
+ for tensor_cont in cdp.align_tensors:
+ # Find the matching tensor and then store the ID.
+ if tensor_cont.name == tensor:
+ tensor_cont.align_id = align_id
+ match = True
+
+ # The tensor label doesn't exist.
+ if not match:
+ raise RelaxNoTensorError('alignment', tensor)
+
+
def set_domain(tensor=None, domain=None):
"""Set the domain label for the given tensor.
Modified: trunk/maths_fns/frame_order.py
URL:
http://svn.gna.org/viewcvs/relax/trunk/maths_fns/frame_order.py?rev=18944&r1=18943&r2=18944&view=diff
==============================================================================
--- trunk/maths_fns/frame_order.py (original)
+++ trunk/maths_fns/frame_order.py Fri Mar 22 11:49:43 2013
@@ -45,7 +45,7 @@
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,
full_in_ref_frame=None, rdcs=None, rdc_errors=None, rdc_weights=None,
rdc_vect=None, rdc_const=None, pcs=None, pcs_errors=None, pcs_weights=None,
pcs_atoms=None, temp=None, frq=None, paramag_centre=None,
scaling_matrix=None, pivot_opt=False):
+ def __init__(self, model=None, init_params=None, full_tensors=None,
full_in_ref_frame=None, rdcs=None, rdc_errors=None, rdc_weights=None,
rdc_vect=None, rdc_const=None, pcs=None, pcs_errors=None, pcs_weights=None,
pcs_atoms=None, temp=None, frq=None, paramag_centre=None,
scaling_matrix=None, pivot=None, pivot_opt=False):
"""Set up the target functions for the Frame Order theories.
@keyword model: The name of the Frame Order model.
@@ -82,6 +82,8 @@
@type paramag_centre: numpy rank-1, 3D array or rank-2, Nx3
array
@keyword scaling_matrix: The square and diagonal scaling matrix.
@type scaling_matrix: numpy rank-2 array
+ @keyword pivot: The pivot point for the ball-and-socket
joint motion. This is needed if PCS or PRE values are used.
+ @type pivot: numpy rank-1, 3D array or None
@keyword pivot_opt: A flag which if True will allow the
pivot point of the motion to be optimised.
@type pivot_opt: bool
"""
@@ -108,6 +110,7 @@
self.frq = frq
self.paramag_centre = paramag_centre
self.total_num_params = len(init_params)
+ self._param_pivot = pivot
self.pivot_opt = pivot_opt
# Tensor setup.
@@ -189,8 +192,8 @@
if self.rdc_flag or self.pcs_flag:
for i in xrange(self.num_align):
# Loop over the RDCs.
- for j in xrange(self.num_rdc):
- if self.rdc_flag:
+ if self.rdc_flag:
+ for j in xrange(self.num_rdc):
if isNaN(self.rdc[i, j]):
# Set the flag.
self.missing_rdc[i, j] = 1
@@ -209,8 +212,8 @@
self.rdc_error[i, j] = self.rdc_error[i, j] /
sqrt(rdc_weights[i, j])
# Loop over the PCSs.
- for j in xrange(self.num_pcs):
- if self.pcs_flag:
+ if self.pcs_flag:
+ for j in xrange(self.num_pcs):
if isNaN(self.pcs[i, j]):
# Set the flag.
self.missing_pcs[i, j] = 1
@@ -243,14 +246,16 @@
self.pcs_const[i] = pcs_constant(self.temp[i], self.frq[i],
1.0) * 1e30
# PCS function, gradient, and Hessian matrices.
- self.pcs_theta = zeros((self.num_align, self.num_pcs), float64)
- self.dpcs_theta = zeros((self.total_num_params, self.num_align,
self.num_pcs), float64)
- self.d2pcs_theta = zeros((self.total_num_params,
self.total_num_params, self.num_align, self.num_pcs), float64)
+ if self.pcs_flag:
+ self.pcs_theta = zeros((self.num_align, self.num_pcs), float64)
+ self.dpcs_theta = zeros((self.total_num_params, self.num_align,
self.num_pcs), float64)
+ self.d2pcs_theta = zeros((self.total_num_params,
self.total_num_params, self.num_align, self.num_pcs), float64)
# RDC function, gradient, and Hessian matrices.
- self.rdc_theta = zeros((self.num_align, self.num_rdc), float64)
- self.drdc_theta = zeros((self.total_num_params, self.num_align,
self.num_rdc), float64)
- self.d2rdc_theta = zeros((self.total_num_params,
self.total_num_params, self.num_align, self.num_rdc), float64)
+ if self.rdc_flag:
+ self.rdc_theta = zeros((self.num_align, self.num_rdc), float64)
+ self.drdc_theta = zeros((self.total_num_params, self.num_align,
self.num_rdc), float64)
+ self.d2rdc_theta = zeros((self.total_num_params,
self.total_num_params, self.num_align, self.num_rdc), float64)
# The target function aliases.
if model == 'pseudo-ellipse':
@@ -550,7 +555,7 @@
# Unpack the parameters.
if self.pivot_opt:
- pivot = params[:3]
+ self._param_pivot = params[:3]
ave_pos_alpha, ave_pos_beta, ave_pos_gamma, axis_theta,
axis_phi, sigma_max = params[3:]
else:
ave_pos_alpha, ave_pos_beta, ave_pos_gamma, axis_theta,
axis_phi, sigma_max = params
@@ -575,36 +580,37 @@
RT_ave = transpose(self.R_ave)
# Pre-calculate all the necessary vectors.
- if self.pivot_opt:
- self.calc_vectors(pivot)
+ self.calc_vectors(self._param_pivot)
# Loop over each alignment.
for i in xrange(self.num_align):
- # Loop over the RDCs.
- for j in xrange(self.num_rdc):
- # The back calculated RDC.
- if self.rdc_flag and not self.missing_rdc[i, j]:
- self.rdc_theta[i, j] = rdc_tensor(self.rdc_const[j],
self.rdc_vect[j], self.A_3D_bc[i])
-
- # Loop over the PCSs.
- for j in xrange(self.num_pcs):
- # The back calculated PCS.
- if self.pcs_flag and not self.missing_pcs[i, j]:
- # Forwards and reverse rotations.
- if self.full_in_ref_frame[i]:
- R_ave = RT_ave
- else:
- R_ave = self.R_ave
-
- # The numerical integration.
- self.pcs_theta[i, j] =
pcs_numeric_int_rotor(sigma_max=sigma_max, c=self.pcs_const[i],
r_pivot_atom=self.r_pivot_atom[j], r_ln_pivot=self.r_ln_pivot,
A=self.A_3D[i], R_ave=R_ave, R_eigen=self.R_eigen, RT_eigen=RT_eigen,
Ri_prime=self.Ri_prime)
-
- # Calculate and sum the single alignment chi-squared value (for
the RDC).
+ # RDCs.
if self.rdc_flag:
+ # Loop over the RDCs.
+ for j in xrange(self.num_rdc):
+ # The back calculated RDC.
+ if not self.missing_rdc[i, j]:
+ self.rdc_theta[i, j] = rdc_tensor(self.rdc_const[j],
self.rdc_vect[j], self.A_3D_bc[i])
+
+ # Calculate and sum the single alignment chi-squared value
(for the RDC).
chi2_sum = chi2_sum + chi2(self.rdc[i], self.rdc_theta[i],
self.rdc_error[i])
- # Calculate and sum the single alignment chi-squared value (for
the PCS).
+ # PCS.
if self.pcs_flag:
+ # Loop over the PCSs.
+ for j in xrange(self.num_pcs):
+ # The back calculated PCS.
+ if not self.missing_pcs[i, j]:
+ # Forwards and reverse rotations.
+ if self.full_in_ref_frame[i]:
+ R_ave = RT_ave
+ else:
+ R_ave = self.R_ave
+
+ # The numerical integration.
+ self.pcs_theta[i, j] =
pcs_numeric_int_rotor(sigma_max=sigma_max, c=self.pcs_const[i],
r_pivot_atom=self.r_pivot_atom[j], r_ln_pivot=self.r_ln_pivot,
A=self.A_3D[i], R_ave=R_ave, R_eigen=self.R_eigen, RT_eigen=RT_eigen,
Ri_prime=self.Ri_prime)
+
+ # Calculate and sum the single alignment chi-squared value
(for the PCS).
chi2_sum = chi2_sum + chi2(self.pcs[i], self.pcs_theta[i],
self.pcs_error[i])
# Return the chi-squared value.
Modified: trunk/specific_fns/frame_order.py
URL:
http://svn.gna.org/viewcvs/relax/trunk/specific_fns/frame_order.py?rev=18944&r1=18943&r2=18944&view=diff
==============================================================================
--- trunk/specific_fns/frame_order.py (original)
+++ trunk/specific_fns/frame_order.py Fri Mar 22 11:49:43 2013
@@ -114,7 +114,7 @@
param_vect = []
# Pivot point.
- if 'pcs' in self._base_data_types():
+ if not self._pivot_fixed():
for i in range(3):
param_vect.append(cdp.pivot[i])
@@ -212,7 +212,7 @@
return scaling_matrix
# The pivot point.
- if 'pcs' in data_types:
+ if not self._pivot_fixed():
for i in range(3):
scaling_matrix[i, i] = 1e2
@@ -921,7 +921,7 @@
data_types = self._base_data_types()
# The pivot point.
- if 'pcs' in data_types:
+ if not self._pivot_fixed():
num += 3
# Average domain position parameters.
@@ -954,23 +954,42 @@
return num
- def _pivot(self, pivot=None):
+ def _pivot(self, pivot=None, fix=None):
"""Set the pivot point for the 2 body motion.
- @param pivot: The pivot point of the two bodies (domains, etc.) in
the structural
- coordinate system.
+ @keyword pivot: The pivot point of the two bodies (domains, etc.) in
the structural coordinate system.
@type pivot: list of num
+ @keyword fix: A flag specifying if the pivot point should be fixed
during optimisation.
+ @type fix: bool
"""
# Test if the current data pipe exists.
pipes.test()
- # Set the pivot point.
+ # Set the pivot point and fixed flag.
cdp.pivot = pivot
+ cdp.pivot_fixed = fix
# Convert to floats.
for i in range(3):
cdp.pivot[i] = float(cdp.pivot[i])
+
+
+ def _pivot_fixed(self):
+ """Determine if the pivot is fixed or not.
+
+ @return: The answer to the question.
+ @rtype: bool
+ """
+
+ # The PCS is loaded.
+ if 'pcs' in self._base_data_types():
+ # The fixed flag is not set.
+ if hasattr(cdp, 'pivot_fixed') and not cdp.pivot_fixed:
+ return False
+
+ # The point is fixed.
+ return True
def _ref_domain(self, ref=None):
@@ -1080,13 +1099,18 @@
if 'rdc' in data_types:
rdcs, rdc_err, rdc_weight, rdc_vect, rdc_const =
self._minimise_setup_rdcs(sim_index=sim_index)
+ # The fixed pivot point.
+ pivot = None
+ if hasattr(cdp, 'pivot'):
+ pivot = cdp.pivot
+
# Pivot optimisation.
- pivot_opt = False
- if 'pcs' in data_types:
- pivot_opt = True
+ pivot_opt = True
+ if self._pivot_fixed():
+ pivot_opt = False
# Set up the optimisation function.
- target = frame_order.Frame_order(model=cdp.model,
init_params=param_vector, full_tensors=full_tensors,
full_in_ref_frame=full_in_ref_frame, rdcs=rdcs, rdc_errors=rdc_err,
rdc_weights=rdc_weight, rdc_vect=rdc_vect, rdc_const=rdc_const, pcs=pcs,
pcs_errors=pcs_err, pcs_weights=pcs_weight, pcs_atoms=pcs_atoms, temp=temp,
frq=frq, paramag_centre=paramag_centre, scaling_matrix=scaling_matrix,
pivot_opt=pivot_opt)
+ target = frame_order.Frame_order(model=cdp.model,
init_params=param_vector, full_tensors=full_tensors,
full_in_ref_frame=full_in_ref_frame, rdcs=rdcs, rdc_errors=rdc_err,
rdc_weights=rdc_weight, rdc_vect=rdc_vect, rdc_const=rdc_const, pcs=pcs,
pcs_errors=pcs_err, pcs_weights=pcs_weight, pcs_atoms=pcs_atoms, temp=temp,
frq=frq, paramag_centre=paramag_centre, scaling_matrix=scaling_matrix,
pivot=pivot, pivot_opt=pivot_opt)
# Return the data.
return target, param_vector, data_types, scaling_matrix
@@ -1127,7 +1151,7 @@
cdp.params = []
# The pivot parameters.
- if 'pcs' in self._base_data_types():
+ if not self._pivot_fixed():
cdp.params.append('pivot_x')
cdp.params.append('pivot_y')
cdp.params.append('pivot_z')
@@ -1198,7 +1222,7 @@
raise RelaxNaNError('chi-squared')
# Pivot point.
- if 'pcs' in self._base_data_types():
+ if not self._pivot_fixed():
# Store the pivot.
cdp.pivot = param_vector[:3]
r18944 - in /trunk: generic_fns/align_tensor.py maths_fns/frame_order.py specific_fns/frame_order.py