Author: bugman
Date: Mon Oct 8 19:56:55 2012
New Revision: 17767
URL: http://svn.gna.org/viewcvs/relax?rev=17767&view=rev
Log:
Fix for the reading of relax 1.2 model-free results files for the diffusion
tensor structure redesign.
Modified:
branches/tensor_data/specific_fns/model_free/results.py
Modified: branches/tensor_data/specific_fns/model_free/results.py
URL:
http://svn.gna.org/viewcvs/relax/branches/tensor_data/specific_fns/model_free/results.py?rev=17767&r1=17766&r2=17767&view=diff
==============================================================================
--- branches/tensor_data/specific_fns/model_free/results.py (original)
+++ branches/tensor_data/specific_fns/model_free/results.py Mon Oct 8
19:56:55 2012
@@ -23,7 +23,6 @@
"""Module for the creation and processing of model-free results files."""
# Python module imports.
-from data.diff_tensor import DiffTensorSimList
from math import pi
from numpy import float64, array, transpose
from re import search
@@ -626,7 +625,7 @@
file_data = file_data[1:]
# Sort the column numbers.
- col = self._read_col_numbers(header)
+ col = self._read_1_2_col_numbers(header)
# Test the file.
if len(col) < 2:
@@ -660,6 +659,20 @@
# Sequence.
self._generate_sequence(file_line, col, verbosity)
+ # Count the number of simulations.
+ for file_line in file_data:
+ # The data set.
+ data_set = file_line[col['data_set']]
+
+ # Simulation number.
+ if data_set != 'value' and data_set != 'error':
+ # Extract the number from the data_set string.
+ sim_num = data_set.split('_')
+ try:
+ sim_num = int(sim_num[1])
+ except:
+ raise RelaxError("The simulation number '%s' is
invalid." % sim_num)
+ cdp.sim_number = sim_num + 1
# Loop over the lines of the file data.
for file_line in file_data:
@@ -744,17 +757,21 @@
# Diffusion tensor data.
if data_set == 'value' and not diff_data_set:
- self._set_diff_tensor(file_line, col, data_set, verbosity)
+ self._read_1_2_set_diff_tensor(file_line, col, data_set,
verbosity, sim_num=sim_num)
diff_data_set = True
# Diffusion tensor errors.
elif data_set == 'error' and not diff_error_set:
- self._set_diff_tensor(file_line, col, data_set, verbosity)
+ self._read_1_2_set_diff_tensor(file_line, col, data_set,
verbosity, sim_num=sim_num)
diff_error_set = True
# Diffusion tensor simulation data.
elif data_set != 'value' and data_set != 'error' and sim_num !=
diff_sim_set:
- self._set_diff_tensor(file_line, col, data_set, verbosity)
+ # Set up the diffusion tensor.
+ if not hasattr(cdp.diff_tensor, '_sim_num') or
cdp.diff_tensor._sim_num == None:
+ cdp.diff_tensor.set_sim_num(cdp.sim_number)
+
+ self._read_1_2_set_diff_tensor(file_line, col, data_set,
verbosity, sim_num=sim_num)
diff_sim_set = sim_num
# Model type.
@@ -789,7 +806,7 @@
cdp.sim_state = False
- def _read_col_numbers(self, header):
+ def _read_1_2_col_numbers(self, header):
"""Determine the column indices from the header line.
@param header: The header line.
@@ -911,19 +928,19 @@
return col
- def _set_diff_tensor(self, spin_line, col, data_set, verbosity=1):
+ def _read_1_2_set_diff_tensor(self, spin_line, col, data_set,
verbosity=1, sim_num=None):
"""Set up the diffusion tensor.
@param spin_line: The line of data for a single spin.
@type spin_line: list of str
@param col: The column indices.
@type col: dict of int
- @param data_set: The data set type, one of 'value', 'error', or
'sim_xxx' (where xxx is
- a number).
+ @param data_set: The data set type, one of 'value', 'error', or
'sim_xxx' (where xxx is a number).
@type data_set: str
- @keyword verbosity: A variable specifying the amount of information
to print. The higher
- the value, the greater the verbosity.
+ @keyword verbosity: A variable specifying the amount of information
to print. The higher the value, the greater the verbosity.
@type verbosity: int
+ @keyword sim_num: The Monte Carlo simulation index.
+ @type sim_num: int or None
"""
# The diffusion tensor type.
@@ -955,16 +972,12 @@
# Errors.
elif data_set == 'error':
- cdp.diff.tm_err = tm
+ cdp.diff_tensor.set(param='tm', value=tm, category='err')
# Simulation values.
else:
- # Create the data structure if it doesn't exist.
- if not hasattr(cdp.diff_tensor, 'tm_sim'):
- cdp.diff.tm_sim = DiffTensorSimList('tm',
cdp.diff_tensor)
-
- # Append the value.
- cdp.diff_tensor.tm_sim.append(tm)
+ # Set the value.
+ cdp.diff_tensor.set(param='tm', value=tm, category='sim',
sim_index=sim_num)
# Spheroid.
@@ -989,28 +1002,18 @@
# Errors.
elif data_set == 'error':
- cdp.diff_tensor.tm_err = tm
- cdp.diff_tensor.Da_err = Da
- cdp.diff_tensor.theta_err = theta
- cdp.diff_tensor.phi_err = phi
+ cdp.diff_tensor.set(param='tm', value=tm, category='err')
+ cdp.diff_tensor.set(param='Da', value=Da, category='err')
+ cdp.diff_tensor.set(param='theta', value=theta,
category='err')
+ cdp.diff_tensor.set(param='phi', value=phi, category='err')
# Simulation values.
else:
- # Create the data structure if it doesn't exist.
- if not hasattr(cdp.diff, 'tm_sim'):
- cdp.diff_tensor.tm_sim = DiffTensorSimList('tm',
cdp.diff_tensor)
- if not hasattr(cdp.diff, 'Da_sim'):
- cdp.diff_tensor.Da_sim = DiffTensorSimList('Da',
cdp.diff_tensor)
- if not hasattr(cdp.diff, 'theta_sim'):
- cdp.diff_tensor.theta_sim = DiffTensorSimList('theta',
cdp.diff_tensor)
- if not hasattr(cdp.diff, 'phi_sim'):
- cdp.diff_tensor.phi_sim = DiffTensorSimList('phi',
cdp.diff_tensor)
-
- # Append the value.
- cdp.diff_tensor.tm_sim.append(tm)
- cdp.diff_tensor.Da_sim.append(Da)
- cdp.diff_tensor.theta_sim.append(theta)
- cdp.diff_tensor.phi_sim.append(phi)
+ # Set the values.
+ cdp.diff_tensor.set(param='tm', value=tm, category='sim',
sim_index=sim_num)
+ cdp.diff_tensor.set(param='Da', value=Da, category='sim',
sim_index=sim_num)
+ cdp.diff_tensor.set(param='theta', value=theta,
category='sim', sim_index=sim_num)
+ cdp.diff_tensor.set(param='phi', value=phi, category='sim',
sim_index=sim_num)
# Ellipsoid.
@@ -1037,37 +1040,22 @@
# Errors.
elif data_set == 'error':
- cdp.diff_tensor.tm_err = tm
- cdp.diff_tensor.Da_err = Da
- cdp.diff_tensor.Dr_err = Dr
- cdp.diff_tensor.alpha_err = alpha
- cdp.diff_tensor.beta_err = beta
- cdp.diff_tensor.gamma_err = gamma
+ cdp.diff_tensor.set(param='tm', value=tm, category='err')
+ cdp.diff_tensor.set(param='Da', value=Da, category='err')
+ cdp.diff_tensor.set(param='Dr', value=Dr, category='err')
+ cdp.diff_tensor.set(param='alpha', value=alpha,
category='err')
+ cdp.diff_tensor.set(param='beta', value=beta, category='err')
+ cdp.diff_tensor.set(param='gamma', value=gamma,
category='err')
# Simulation values.
else:
- # Create the data structure if it doesn't exist.
- if not hasattr(cdp.diff_tensor, 'tm_sim'):
- cdp.diff_tensor.tm_sim = DiffTensorSimList('tm',
cdp.diff_tensor)
- if not hasattr(cdp.diff_tensor, 'Da_sim'):
- cdp.diff_tensor.Da_sim = DiffTensorSimList('Da',
cdp.diff_tensor)
- if not hasattr(cdp.diff_tensor, 'Dr_sim'):
- cdp.diff_tensor.Dr_sim = DiffTensorSimList('Dr',
cdp.diff_tensor)
- if not hasattr(cdp.diff_tensor, 'alpha_sim'):
- cdp.diff_tensor.alpha_sim = DiffTensorSimList('alpha',
cdp.diff_tensor)
- if not hasattr(cdp.diff_tensor, 'beta_sim'):
- cdp.diff_tensor.beta_sim = DiffTensorSimList('beta',
cdp.diff_tensor)
- if not hasattr(cdp.diff_tensor, 'gamma_sim'):
- cdp.diff_tensor.gamma_sim = DiffTensorSimList('gamma',
cdp.diff_tensor)
-
- # Append the value.
- cdp.diff_tensor.tm_sim.append(tm)
- cdp.diff_tensor.Da_sim.append(Da)
- cdp.diff_tensor.Dr_sim.append(Dr)
- cdp.diff_tensor.alpha_sim.append(alpha)
- cdp.diff_tensor.beta_sim.append(beta)
- cdp.diff_tensor.gamma_sim.append(gamma)
-
+ # Set the values.
+ cdp.diff_tensor.set(param='tm', value=tm, category='sim',
sim_index=sim_num)
+ cdp.diff_tensor.set(param='Da', value=Da, category='sim',
sim_index=sim_num)
+ cdp.diff_tensor.set(param='Dr', value=Dr, category='sim',
sim_index=sim_num)
+ cdp.diff_tensor.set(param='alpha', value=alpha,
category='sim', sim_index=sim_num)
+ cdp.diff_tensor.set(param='beta', value=beta,
category='sim', sim_index=sim_num)
+ cdp.diff_tensor.set(param='gamma', value=gamma,
category='sim', sim_index=sim_num)
# Set the diffusion tensor.
if data_set == 'value' and diff_type:
r17767 - /branches/tensor_data/specific_fns/model_free/results.py