Author: bugman
Date: Wed Dec 15 18:33:22 2010
New Revision: 11833
URL: http://svn.gna.org/viewcvs/relax?rev=11833&view=rev
Log:
Converted the specific relaxation curve fitting code to use the dictionary
data structures.
Modified:
branches/peak_list_handling/specific_fns/relax_fit.py
Modified: branches/peak_list_handling/specific_fns/relax_fit.py
URL:
http://svn.gna.org/viewcvs/relax/branches/peak_list_handling/specific_fns/relax_fit.py?rev=11833&r1=11832&r2=11833&view=diff
==============================================================================
--- branches/peak_list_handling/specific_fns/relax_fit.py (original)
+++ branches/peak_list_handling/specific_fns/relax_fit.py Wed Dec 15 18:33:22
2010
@@ -151,13 +151,13 @@
return scaling_matrix
- def _back_calc(self, spin=None, relax_time_index=None):
+ def _back_calc(self, spin=None, relax_time_id=None):
"""Back-calculation of peak intensity for the given relaxation time.
@keyword spin: The spin container.
@type spin: SpinContainer instance
- @keyword relax_time_index: The index for the desired relaxation
time.
- @type relax_time_index: int
+ @keyword relax_time_id: The ID string for the desired relaxation
time.
+ @type relax_time_id: str
@return: The peak intensity for the desired
relaxation time.
@rtype: float
"""
@@ -168,8 +168,20 @@
# Create a scaling matrix.
scaling_matrix = self._assemble_scaling_matrix(spin=spin,
scaling=False)
+ # The keys.
+ keys = spin.intensities.keys()
+
+ # The peak intensities and times.
+ values = []
+ errors = []
+ times = []
+ for key in keys:
+ values.append(spin.intensities[key])
+ errors.append(spin.intensity_err[key])
+ times.append(cdp.relax_times[key])
+
# Initialise the relaxation fit functions.
- setup(num_params=len(spin.params), num_times=len(cdp.relax_times),
values=spin.intensities, sd=spin.intensity_err, relax_times=cdp.relax_times,
scaling_matrix=scaling_matrix)
+ setup(num_params=len(spin.params), num_times=len(cdp.relax_times),
values=values, sd=errors, relax_times=times, scaling_matrix=scaling_matrix)
# Make a single function call. This will cause back calculation and
the data will be stored in the C module.
func(param_vector)
@@ -178,7 +190,7 @@
results = back_calc_I()
# Return the correct peak height.
- return results[relax_time_index]
+ return results[keys.index(relax_time_id)]
def _disassemble_param_vector(self, param_vector=None, spin=None,
sim_index=None):
@@ -282,12 +294,16 @@
# Intensity
elif search('^I', spin.params[i]):
- # Find the position of the first time point.
- pos = cdp.relax_times.index(min(cdp.relax_times))
+ # Find the ID of the first time point.
+ min_time = min(cdp.relax_times.values())
+ for key in cdp.relax_times.keys():
+ if cdp.relax_times[key] == min_time:
+ id = key
+ break
# Defaults.
lower.append(0.0)
- upper.append(average(spin.intensities[pos]))
+ upper.append(average(spin.intensities[id]))
# Parameter scaling.
for i in range(n):
@@ -407,22 +423,12 @@
if spectrum_id not in cdp.spectrum_ids:
raise RelaxError("The peak heights corresponding to spectrum id
'%s' have not been loaded." % spectrum_id)
- # The index.
- index = cdp.spectrum_ids.index(spectrum_id)
-
# Initialise the global relaxation time data structure if needed.
if not hasattr(cdp, 'relax_times'):
- cdp.relax_times = [None] * len(cdp.spectrum_ids)
-
- # Index not present in the global relaxation time data structure.
- while True:
- if index > len(cdp.relax_times) - 1:
- cdp.relax_times.append(None)
- else:
- break
+ cdp.relax_times = {}
# Add the time at the correct position.
- cdp.relax_times[index] = time
+ cdp.relax_times[spectrum_id] = time
def _select_model(self, model='exp'):
@@ -472,7 +478,7 @@
"""
# Initialise the MC data data structure.
- mc_data = []
+ mc_data = {}
# Get the spin container.
spin = return_spin(data_id)
@@ -490,12 +496,12 @@
raise RelaxNoModelError
# Loop over the spectral time points.
- for j in xrange(len(cdp.relax_times)):
+ for id in cdp.relax_times.keys():
# Back calculate the value.
- value = self._back_calc(spin=spin, relax_time_index=j)
+ value = self._back_calc(spin=spin, relax_time_id=id)
# Append the value.
- mc_data.append(value)
+ mc_data[id] = value
# Return the MC data.
return mc_data
@@ -736,12 +742,27 @@
# Initialise the function to minimise.
######################################
- if sim_index == None:
- values = spin.intensities
- else:
- values = spin.sim_intensities[sim_index]
-
- setup(num_params=len(spin.params),
num_times=len(cdp.relax_times), values=values, sd=spin.intensity_err,
relax_times=cdp.relax_times, scaling_matrix=scaling_matrix)
+ # The keys.
+ keys = spin.intensities.keys()
+
+ # The peak intensities and times.
+ values = []
+ errors = []
+ times = []
+ for key in keys:
+ # The values.
+ if sim_index == None:
+ values.append(spin.intensities[key])
+ else:
+ values.append(spin.sim_intensities[sim_index][key])
+
+ # The errors.
+ errors.append(spin.intensity_err[key])
+
+ # The relaxation times.
+ times.append(cdp.relax_times[key])
+
+ setup(num_params=len(spin.params),
num_times=len(cdp.relax_times), values=values, sd=errors, relax_times=times,
scaling_matrix=scaling_matrix)
# Setup the minimisation algorithm when constraints are present.
r11833 - /branches/peak_list_handling/specific_fns/relax_fit.py