Author: semor
Date: Tue Jan 13 04:13:54 2009
New Revision: 8428
URL: http://svn.gna.org/viewcvs/relax?rev=8428&view=rev
Log:
Converted the function linear_constraints() for relaxation dispersion needs.
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=8428&r1=8427&r2=8428&view=diff
==============================================================================
--- branches/relax_disp/specific_fns/relax_disp.py (original)
+++ branches/relax_disp/specific_fns/relax_disp.py Tue Jan 13 04:13:54 2009
@@ -725,27 +725,34 @@
Standard notation
=================
- The relaxation rate constraints are::
-
- Rx >= 0
-
- The intensity constraints are::
-
- I0 >= 0
- Iinf >= 0
+ The different constraints are::
+
+ R2 >= 0
+ Rex >= 0
+ kex >= 0
+
+ R2A >= 0
+ kA >= 0
+ dw >= 0
Matrix notation
===============
- In the notation A.x >= b, where A is an matrix of coefficients, x is
an array of parameter
+ In the notation A.x >= b, where A is a matrix of coefficients, x is an
array of parameter
values, and b is a vector of scalars, these inequality constraints
are::
- | 1 0 0 | | Rx | | 0 |
+ | 1 0 0 | | R2 | | 0 |
| | | | | |
- | 1 0 0 | . | I0 | >= | 0 |
+ | 1 0 0 | . | Rex | | 0 |
| | | | | |
- | 1 0 0 | | Iinf | | 0 |
+ | 1 0 0 | | kex | | 0 |
+ | | | | >= | |
+ | 1 0 0 | | R2A | | 0 |
+ | | | | | |
+ | 1 0 0 | | kA | | 0 |
+ | | | | | |
+ | 1 0 0 | | dw | | 0 |
@keyword spin: The spin data container.
@@ -764,17 +771,25 @@
# Loop over the parameters.
for k in xrange(len(spin.params)):
- # Relaxation rate.
- if spin.params[k] == 'Rx':
- # Rx >= 0.
+ # Relaxation rates and Rex.
+ if search('^R', spin.params[k]):
+ # R2, Rex, R2A >= 0.
A.append(zero_array * 0.0)
A[j][i] = 1.0
b.append(0.0)
j = j + 1
- # Intensity parameter.
- elif search('^I', spin.params[k]):
- # I0, Iinf >= 0.
+ # Exchange rates.
+ elif search('^k', spin.params[k]):
+ # kex, kA >= 0.
+ A.append(zero_array * 0.0)
+ A[j][i] = 1.0
+ b.append(0.0)
+ j = j + 1
+
+ # Chemical exchange difference.
+ elif spin.params[k] == 'dw':
+ # dw >= 0.
A.append(zero_array * 0.0)
A[j][i] = 1.0
b.append(0.0)
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