r22436 - /trunk/specific_analyses/relax_disp/disp_data.py -- March 07, 2014 - 13:21

Author: tlinnet
Date: Fri Mar  7 13:21:24 2014
New Revision: 22436

URL: http://svn.gna.org/viewcvs/relax?rev=22436&view=rev
Log:
Implemented the return of Delta_omega = "average resonance offset in the 
rotating frame" in specific_analysis.relax_disp.return_offset_data.

Regarding sr #3124, (https://gna.org/support/index.php?3124) - Grace graphs 
production for R1rho analysis with R2_eff as function of Omega_eff.

Modified:
    trunk/specific_analyses/relax_disp/disp_data.py

Modified: trunk/specific_analyses/relax_disp/disp_data.py
URL: 
http://svn.gna.org/viewcvs/relax/trunk/specific_analyses/relax_disp/disp_data.py?rev=22436&r1=22435&r2=22436&view=diff
==============================================================================
--- trunk/specific_analyses/relax_disp/disp_data.py     (original)
+++ trunk/specific_analyses/relax_disp/disp_data.py     Fri Mar  7 13:21:24 
2014
@@ -2686,7 +2686,7 @@
     @type field_count:      int
     @keyword fields:        The spin-lock field strengths to use instead of 
the user loaded values - to enable interpolation.  The dimensions are {Ei, 
Mi}.
     @type fields:           rank-2 list of floats
-    @return:                The numpy array structures of the chemical 
shifts in rad/s {Ei, Si, Mi}, spin-lock offsets in rad/s {Ei, Si, Mi, Oi}, 
and rotating frame tilt angles {Ei, Si, Mi, Oi, Di}.
+    @return:                The numpy array structures of the chemical 
shifts in rad/s {Ei, Si, Mi}, spin-lock offsets in rad/s {Ei, Si, Mi, Oi}, 
rotating frame tilt angles {Ei, Si, Mi, Oi, Di} and the average resonance 
offset in the rotating frame {Ei, Si, Mi, Oi, Di} in rad/s.
     @rtype:                 rank-3 list of floats, rank-4 list of floats, 
rank-5 list of floats
     """
 
@@ -2702,21 +2702,26 @@
     shifts = []
     offsets = []
     theta = []
+    Domega = []
     for exp_type, ei in loop_exp(return_indices=True):
         shifts.append([])
         offsets.append([])
         theta.append([])
+        Domega.append([])
         for si in range(spin_num):
             shifts[ei].append([])
             offsets[ei].append([])
             theta[ei].append([])
+            Domega[ei].append([])
             for frq, mi in loop_frq(return_indices=True):
                 shifts[ei][si].append(None)
                 offsets[ei][si].append([])
                 theta[ei][si].append([])
+                Domega[ei][si].append([])
                 for offset, oi in loop_offset(exp_type=exp_type, frq=frq, 
return_indices=True):
                     offsets[ei][si][mi].append(None)
                     theta[ei][si][mi].append([])
+                    Domega[ei][si][mi].append([])
 
     # Assemble the data.
     data_flag = False
@@ -2806,6 +2811,7 @@
                 # Calculate the tilt angle.
                 omega1 = point * 2.0 * pi
                 Delta_omega = shifts[ei][si][mi] - offsets[ei][si][mi][oi]
+                Domega[ei][si][mi][oi].append(Delta_omega)
                 if Delta_omega == 0.0:
                     theta[ei][si][mi][oi].append(pi / 2.0)
                 else:
@@ -2825,7 +2831,7 @@
     #            theta[ei][si][mi] = array(theta[ei][si][mi], float64)
 
     # Return the structures.
-    return shifts, offsets, theta
+    return shifts, offsets, theta, Domega
 
 
 def return_param_key_from_data(exp_type=None, frq=0.0, offset=0.0, 
point=0.0):