r19797 - /branches/relax_disp/specific_analyses/relax_disp/__init__.py -- May 30, 2013 - 16:50

Author: bugman
Date: Thu May 30 16:50:09 2013
New Revision: 19797

URL: http://svn.gna.org/viewcvs/relax?rev=19797&view=rev
Log:
Modified the dispersion calculate() method for the R2eff values to use the 
analytic equation.

For the R2eff/R1rho values calculated for the fixed time period dispersion 
experiments via the calc
user function, the very slow and tedious bootstrapping approach has been 
replaced by the very quick
direct error calculation.  The two techniques produce the same results as the 
bootstrap simulation
number approaches infinity.


Modified:
    branches/relax_disp/specific_analyses/relax_disp/__init__.py

Modified: branches/relax_disp/specific_analyses/relax_disp/__init__.py
URL: 
http://svn.gna.org/viewcvs/relax/branches/relax_disp/specific_analyses/relax_disp/__init__.py?rev=19797&r1=19796&r2=19797&view=diff
==============================================================================
--- branches/relax_disp/specific_analyses/relax_disp/__init__.py (original)
+++ branches/relax_disp/specific_analyses/relax_disp/__init__.py Thu May 30 
16:50:09 2013
@@ -940,10 +940,6 @@
             # Initialise the data structures.
             if not hasattr(spin, 'r2eff'):
                 spin.r2eff = {}
-            if not hasattr(spin, 'r2eff_sim'):
-                spin.r2eff_sim = []
-                for i in range(cdp.bootstrap_sim_num):
-                    spin.r2eff_sim.append({})
             if not hasattr(spin, 'r2eff_err'):
                 spin.r2eff_err = {}
 
@@ -976,19 +972,8 @@
                 # Calculate the R2eff value.
                 spin.r2eff[param_key] = 
calc_two_point_r2eff(relax_time=time, I_ref=ref_intensity, I=intensity)
 
-                # Bootstrapping error propagation.
-                values = []
-                for i in range(cdp.bootstrap_sim_num):
-                    # Randomise the data.
-                    I_ref = gauss(ref_intensity, ref_intensity_err)
-                    I = gauss(intensity, intensity_err)
-
-                    # Calculate the simulation R2eff value.
-                    spin.r2eff_sim[i][param_key] = 
calc_two_point_r2eff(relax_time=time, I_ref=I_ref, I=I)
-                    values.append(spin.r2eff_sim[i][param_key])
-
-                # The standard deviation.
-                spin.r2eff_err[param_key] = std(values)
+                # The R2eff error.
+                spin.r2eff_err[param_key] = sqrt((ref_intensity_err / 
ref_intensity)**2 + (intensity_err / intensity)**2) / time
 
 
     def constraint_algorithm(self):