Author: bugman
Date: Wed Oct 17 15:03:30 2012
New Revision: 17897
URL: http://svn.gna.org/viewcvs/relax?rev=17897&view=rev
Log:
All of the alignment tensor data from the frame order base data loop methods
have been removed.
This also includes the assembly of the alignment tensor data.
Modified:
branches/frame_order_testing/specific_fns/frame_order.py
Modified: branches/frame_order_testing/specific_fns/frame_order.py
URL:
http://svn.gna.org/viewcvs/relax/branches/frame_order_testing/specific_fns/frame_order.py?rev=17897&r1=17896&r2=17897&view=diff
==============================================================================
--- branches/frame_order_testing/specific_fns/frame_order.py (original)
+++ branches/frame_order_testing/specific_fns/frame_order.py Wed Oct 17
15:03:30 2012
@@ -390,7 +390,7 @@
# The axis.
axis = zeros(3, float64)
spherical_to_cartesian([1.0, getattr(cdp, 'axis_theta'),
getattr(cdp, 'axis_phi')], axis)
- print("Central axis: %s." % axis)
+ print(("Central axis: %s." % axis))
# Rotations and inversions.
axis_pos = axis
@@ -427,7 +427,7 @@
# The axis system.
axes = zeros((3, 3), float64)
euler_to_R_zyz(cdp.eigen_alpha, cdp.eigen_beta, cdp.eigen_gamma,
axes)
- print("Axis system:\n%s" % axes)
+ print(("Axis system:\n%s" % axes))
# Rotations and inversions.
axes_pos = axes
@@ -933,21 +933,12 @@
# Loop over the full tensors.
for i, tensor in self._tensor_loop(red=False):
- # The full tensor (simulation data).
- if sim_index != None:
- full_tensors[5*i + 0] = tensor.Axx_sim[sim_index]
- full_tensors[5*i + 1] = tensor.Ayy_sim[sim_index]
- full_tensors[5*i + 2] = tensor.Axy_sim[sim_index]
- full_tensors[5*i + 3] = tensor.Axz_sim[sim_index]
- full_tensors[5*i + 4] = tensor.Ayz_sim[sim_index]
-
# The full tensor.
- else:
- full_tensors[5*i + 0] = tensor.Axx
- full_tensors[5*i + 1] = tensor.Ayy
- full_tensors[5*i + 2] = tensor.Axy
- full_tensors[5*i + 3] = tensor.Axz
- full_tensors[5*i + 4] = tensor.Ayz
+ full_tensors[5*i + 0] = tensor.Axx
+ full_tensors[5*i + 1] = tensor.Ayy
+ 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:
@@ -1533,14 +1524,14 @@
def base_data_loop(self):
"""Generator method for looping over the base data - alignment
tensors, RDCs, PCSs.
- This loop first yields the string 'A' representing the alignment
tensors, and then iterates for each data point (RDC, PCS) for each spin,
returning the identification information.
-
- @return: The alignment tensor or a list of the spin ID string,
the data type ('rdc', 'pcs') and the alignment ID.
- @rtype: string or list of str
- """
-
- # First the tensors.
- yield 'A'
+ This loop yields the following:
+
+ - The RDC identification data for the interatomic data container
and alignment.
+ - The PCS identification data for the spin data container and
alignment.
+
+ @return: The base data type ('rdc' or 'pcs'), the spin or
interatomic data container information (either one or two spin IDs), and the
alignment ID string.
+ @rtype: list of str
+ """
# The moving domain ID.
id = cdp.domain[self._domain_moving()]
@@ -1604,7 +1595,7 @@
"""Create the Monte Carlo data by back calculating the reduced
tensor data.
@keyword data_id: The data set as yielded by the base_data_loop()
generator method.
- @type data_id: str or list of str
+ @type data_id: list of str
@return: The Monte Carlo simulation data.
@rtype: list of floats
"""
@@ -1612,19 +1603,8 @@
# Initialise the MC data structure.
mc_data = []
- # Alignment tensor data.
- if data_id == 'A':
- # Loop over the full tensors.
- for i, tensor in self._tensor_loop(red=False):
- # Append the data.
- mc_data.append(tensor.Axx)
- mc_data.append(tensor.Ayy)
- mc_data.append(tensor.Axy)
- mc_data.append(tensor.Axz)
- mc_data.append(tensor.Ayz)
-
# The RDC data.
- elif data_id[0] == 'rdc':
+ if data_id[0] == 'rdc':
# Unpack the set.
data_type, spin_id1, spin_id2, align_id = data_id
@@ -2007,7 +1987,7 @@
"""Return the alignment tensor error structure.
@param data_id: The data set as yielded by the base_data_loop()
generator method.
- @type data_id: str or list of str
+ @type data_id: list of str
@return: The array of tensor error values.
@rtype: list of float
"""
@@ -2015,19 +1995,8 @@
# Initialise the MC data structure.
mc_errors = []
- # Alignment tensor data.
- if data_id == 'A':
- # Loop over the full tensors.
- for i, tensor in self._tensor_loop(red=False):
- # Append the errors.
- mc_errors.append(tensor.Axx_err)
- mc_errors.append(tensor.Ayy_err)
- mc_errors.append(tensor.Axy_err)
- mc_errors.append(tensor.Axz_err)
- mc_errors.append(tensor.Ayz_err)
-
# The RDC data.
- elif data_id[0] == 'rdc':
+ if data_id[0] == 'rdc':
# Unpack the set.
data_type, spin_id1, spin_id2, align_id = data_id
@@ -2195,29 +2164,13 @@
"""Pack the Monte Carlo simulation data.
@param data_id: The data set as yielded by the base_data_loop()
generator method.
- @type data_id: str or list of str
+ @type data_id: list of str
@param sim_data: The Monte Carlo simulation data.
@type sim_data: list of float
"""
- # Alignment tensor data.
- if data_id == 'A':
- # Loop over the full tensors.
- for i, tensor in self._tensor_loop(red=False):
- # Set the simulation number.
- tensor.set_sim_num(cdp.sim_number)
-
- # Loop over the simulations.
- for j in range(cdp.sim_number):
- # Set the full tensor simulation data.
- tensor.set(param='Axx', value=sim_data[5*i + 0][j],
category='sim', sim_index=j)
- tensor.set(param='Ayy', value=sim_data[5*i + 1][j],
category='sim', sim_index=j)
- tensor.set(param='Axy', value=sim_data[5*i + 2][j],
category='sim', sim_index=j)
- tensor.set(param='Axz', value=sim_data[5*i + 3][j],
category='sim', sim_index=j)
- tensor.set(param='Ayz', value=sim_data[5*i + 4][j],
category='sim', sim_index=j)
-
# The RDC data.
- elif data_id[0] == 'rdc':
+ if data_id[0] == 'rdc':
# Unpack the set.
data_type, spin_id1, spin_id2, align_id = data_id
r17897 - /branches/frame_order_testing/specific_fns/frame_order.py