r19342 - /branches/relax_disp/specific_analyses/relax_disp.py -- April 04, 2013 - 09:27

Author: bugman
Date: Thu Apr  4 09:27:40 2013
New Revision: 19342

URL: http://svn.gna.org/viewcvs/relax?rev=19342&view=rev
Log:
The dispersion specific methods now handle one R2eff and I0 parameter per 
exponential curve.


Modified:
    branches/relax_disp/specific_analyses/relax_disp.py

Modified: branches/relax_disp/specific_analyses/relax_disp.py
URL: 
http://svn.gna.org/viewcvs/relax/branches/relax_disp/specific_analyses/relax_disp.py?rev=19342&r1=19341&r2=19342&view=diff
==============================================================================
--- branches/relax_disp/specific_analyses/relax_disp.py (original)
+++ branches/relax_disp/specific_analyses/relax_disp.py Thu Apr  4 09:27:40 
2013
@@ -102,25 +102,27 @@
             # Alias the spin.
             spin = spins[spin_index]
 
-            # Loop over the model parameters.
-            for i in range(len(spin.params)):
-                # Effective transversal relaxation rate.
-                if spin.params[i] == 'R2eff':
-                    if sim_index != None:
-                        param_vector.append(spin.r2eff_sim[sim_index])
-                    elif spin.r2eff == None:
-                        param_vector.append(0.0)
-                    else:
-                        param_vector.append(spin.r2eff)
-
-                # Initial intensity.
-                elif spin.params[i] == 'I0':
-                    if sim_index != None:
-                        param_vector.append(spin.i0_sim[sim_index])
-                    elif spin.i0 == None:
-                        param_vector.append(0.0)
-                    else:
-                        param_vector.append(spin.i0)
+            # Loop over each exponential curve.
+            for exp_i in range(cdp.curve_count):
+                # Loop over the model parameters.
+                for i in range(len(spin.params)):
+                    # Effective transversal relaxation rate.
+                    if spin.params[i] == 'R2eff':
+                        if sim_index != None:
+                            param_vector.append(spin.r2eff_sim[sim_index])
+                        elif spin.r2eff == None:
+                            param_vector.append(0.0)
+                        else:
+                            param_vector.append(spin.r2eff)
+
+                    # Initial intensity.
+                    elif spin.params[i] == 'I0':
+                        if sim_index != None:
+                            param_vector.append(spin.i0_sim[sim_index])
+                        elif spin.i0 == None:
+                            param_vector.append(0.0)
+                        else:
+                            param_vector.append(spin.i0)
 
         # Then the spin block specific parameters, taking the values from 
the first spin.
         spin = spins[0]
@@ -208,13 +210,15 @@
             # Alias the spin.
             spin = spins[spin_index]
 
-            # Effective transversal relaxation rate scaling.
-            scaling_matrix[param_index, param_index] = 1e-1
-            param_index += 1
-
-            # Initial intensity scaling.
-            scaling_matrix[param_index, param_index] = 1.0 / 
max(spin.intensities.values())
-            param_index += 1
+            # Loop over each exponential curve.
+            for exp_i in range(cdp.curve_count):
+                # Effective transversal relaxation rate scaling.
+                scaling_matrix[param_index, param_index] = 1e-1
+                param_index += 1
+
+                # Initial intensity scaling.
+                scaling_matrix[param_index, param_index] = 1.0 / 
max(spin.intensities.values())
+                param_index += 1
 
         # Then the spin block specific parameters.
         spin = spins[0]
@@ -537,18 +541,20 @@
             # Alias the spin.
             spin = spins[spin_index]
 
-            # Loop over the parameters.
-            for i in range(len(spin.params)):
-                # R2eff relaxation rate (from 0 to 40 s^-1).
-                if spin.params[i] == 'R2eff':
-                    min_options.append([inc[j], 0.0, 40.0])
-
-                # Intensity.
-                elif spin.params[i] == 'I0':
-                    min_options.append([inc[j], 0.0, 
max(spin.intensities.values())])
-
-                # Increment j.
-                j += 1
+            # Loop over each exponential curve.
+            for exp_i in range(cdp.curve_count):
+                # Loop over the parameters.
+                for i in range(len(spin.params)):
+                    # R2eff relaxation rate (from 0 to 40 s^-1).
+                    if spin.params[i] == 'R2eff':
+                        min_options.append([inc[j], 0.0, 40.0])
+
+                    # Intensity.
+                    elif spin.params[i] == 'I0':
+                        min_options.append([inc[j], 0.0, 
max(spin.intensities.values())])
+
+                    # Increment j.
+                    j += 1
 
         # Then the spin block specific parameters.
         spin = spins[0]
@@ -659,14 +665,16 @@
             # Alias the spin.
             spin = spins[spin_index]
 
-            # Loop over the parameters.
-            for k in range(len(spin.params)):
-                # The transversal relaxation rate >= 0.
-                if spin.params[k] == 'R2':
-                    A.append(zero_array * 0.0)
-                    A[j][i] = 1.0
-                    b.append(0.0)
-                    j += 1
+            # Loop over each exponential curve.
+            for exp_i in range(cdp.curve_count):
+                # Loop over the parameters.
+                for k in range(len(spin.params)):
+                    # The transversal relaxation rate >= 0.
+                    if spin.params[k] == 'R2':
+                        A.append(zero_array * 0.0)
+                        A[j][i] = 1.0
+                        b.append(0.0)
+                        j += 1
 
         # Then the spin block specific parameters.
         spin = spins[0]