Hi Ed,
I am not so familiar with scaling in minimization...
How can I determine if a given parameter would benefit from scaling ?
Is only speed affected when scaling is used ?
Thanks !
Séb
sebastien.morin.1@xxxxxxxxx wrote:
Author: semor
Date: Tue Jan 13 04:24:37 2009
New Revision: 8429
URL: http://svn.gna.org/viewcvs/relax?rev=8429&view=rev
Log:
Started to implement the scaling matrix for scaling the 'R2eff' values.
This might change in the future as other possible curve fitting
parameters ('R2', 'Rex', 'kex',
'R2A', 'kA', 'dw') might need some scaling.
Modified:
branches/relax_disp/specific_fns/relax_disp.py
Modified: branches/relax_disp/specific_fns/relax_disp.py
URL:
http://svn.gna.org/viewcvs/relax/branches/relax_disp/specific_fns/relax_disp.py?rev=8429&r1=8428&r2=8429&view=diff
==============================================================================
--- branches/relax_disp/specific_fns/relax_disp.py (original)
+++ branches/relax_disp/specific_fns/relax_disp.py Tue Jan 13 04:24:37
2009
@@ -143,17 +143,17 @@
# Loop over the parameters.
for i in xrange(len(spin.params)):
- # Relaxation rate.
- if spin.params[i] == 'Rx':
- pass
-
- # Intensity scaling.
elif search('^i', spin.params[i]):
+ # Effective transversal relaxation rate scaling.
+ if spin.params[i] == 'R2eff':
# Find the position of the first CPMG pulse train
frequency point.
pos = cdp.cpmg_frqs.index(min(cdp.cpmg_frqs))
# Scaling.
- scaling_matrix[i, i] = 1.0 /
average(spin.intensities[pos])
+ scaling_matrix[i, i] = 1.0 / average(spin.r2effs[pos])
+
+ # No scaling for other parameters.
+ else:
+ pass
# Increment i.
i = i + 1
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