Author: tlinnet
Date: Wed Aug 27 23:45:26 2014
New Revision: 25361

URL: http://svn.gna.org/viewcvs/relax?rev=25361&view=rev
Log:
Added keyword "exp_mc_sim_num", to the auto analyses in the GUI.

This sets the number of Monte Carlo simulations for R2eff error estimation in 
exponential curve fitting.

When setting to -1, the errors are estimated from the Covariance Matrix.

These errors are highly likely to be wrong, but can be used in Rapid testing of 
data and plotting.

task #7822(https://gna.org/task/index.php?7822): Implement user function to 
estimate R2eff and associated errors for exponential curve fitting.

Modified:
    trunk/auto_analyses/relax_disp.py
    trunk/gui/analyses/auto_relax_disp.py

Modified: trunk/auto_analyses/relax_disp.py
URL: 
http://svn.gna.org/viewcvs/relax/trunk/auto_analyses/relax_disp.py?rev=25361&r1=25360&r2=25361&view=diff
==============================================================================
--- trunk/auto_analyses/relax_disp.py   (original)
+++ trunk/auto_analyses/relax_disp.py   Wed Aug 27 23:45:26 2014
@@ -66,7 +66,7 @@
         @type grid_inc:                     int or None
         @keyword mc_sim_num:                The number of Monte Carlo 
simulations to be used for error analysis at the end of the analysis.
         @type mc_sim_num:                   int
-        @keyword exp_mc_sim_num:            The number of Monte Carlo 
simulations for the error analysis in the 'R2eff' model when exponential curves 
are fitted.  This defaults to the value of the mc_sim_num argument when not 
given.  For the 2-point fixed-time calculation for the 'R2eff' model, this 
argument is ignored.
+        @keyword exp_mc_sim_num:            The number of Monte Carlo 
simulations for the error analysis in the 'R2eff' model when exponential curves 
are fitted.  This defaults to the value of the mc_sim_num argument when not 
given.  When set to '-1', the R2eff errors are estimated from the Covariance 
matrix.  For the 2-point fixed-time calculation for the 'R2eff' model, this 
argument is ignored.
         @type exp_mc_sim_num:               int or None
         @keyword modsel:                    The model selection technique to 
use in the analysis to determine which model is the best for each spin cluster. 
 This can currently be one of 'AIC', 'AICc', and 'BIC'.
         @type modsel:                       str

Modified: trunk/gui/analyses/auto_relax_disp.py
URL: 
http://svn.gna.org/viewcvs/relax/trunk/gui/analyses/auto_relax_disp.py?rev=25361&r1=25360&r2=25361&view=diff
==============================================================================
--- trunk/gui/analyses/auto_relax_disp.py       (original)
+++ trunk/gui/analyses/auto_relax_disp.py       Wed Aug 27 23:45:26 2014
@@ -118,6 +118,7 @@
             ds.relax_gui.analyses[data_index].numeric_only = False
             ds.relax_gui.analyses[data_index].grid_inc = None
             ds.relax_gui.analyses[data_index].mc_sim_num = None
+            ds.relax_gui.analyses[data_index].exp_mc_sim_num = None
             ds.relax_gui.analyses[data_index].pre_run_dir = None
             ds.relax_gui.analyses[data_index].mc_sim_all_models = False
             ds.relax_gui.analyses[data_index].insignificance = 1.0
@@ -298,6 +299,7 @@
 
         # The number of Monte Carlo simulations to be used for error analysis 
at the end of the analysis.
         data.mc_sim_num = gui_to_int(self.mc_sim_num.GetValue())
+        data.exp_mc_sim_num = gui_to_int(self.exp_mc_sim_num.GetValue())
         data.mc_sim_all_models = self.mc_sim_all_models.GetValue()
 
         # The insignificance level.
@@ -370,6 +372,7 @@
 
         # The MC simulation settings.
         self.mc_sim_num = Spin_ctrl(box, self, text="Monte Carlo simulation 
number:", default=500, min=1, max=100000, tooltip="This is the number of Monte 
Carlo simulations performed for error propagation and analysis.  For best 
results, at least 500 is recommended.", width_text=self.width_text, 
width_button=self.width_button, spacer=self.spacer_horizontal)
+        self.exp_mc_sim_num = Spin_ctrl(box, self, text="Exponential Monte 
Carlo simulation:", default=500, min=-1, max=100000, tooltip="This is the 
number of Monte Carlo simulations performed for error propagation and analysis, 
when estimating R2eff errors from exponential curve fitting.  Setting to '-1', 
estimates error from the Covariance matrix.", width_text=self.width_text, 
width_button=self.width_button, spacer=self.spacer_horizontal)
         self.mc_sim_all_models = Boolean_ctrl(box, self, text="Per model error 
analysis:", default=False, tooltip="A flag which if True will cause Monte Carlo 
simulations to be performed for each individual model.  Otherwise Monte Carlo 
simulations will be reserved for the final model.", width_text=self.width_text, 
width_button=self.width_button, spacer=self.spacer_horizontal)
 
         # The speed up of grid search.
@@ -628,6 +631,12 @@
             self.data.mc_sim_num = gui_to_int(self.mc_sim_num.GetValue())
         elif hasattr(self.data, 'mc_sim_num'):
             self.mc_sim_num.SetValue(int(self.data.mc_sim_num))
+
+        # The EXP MC sim number.
+        if upload:
+            self.data.exp_mc_sim_num = 
gui_to_int(self.exp_mc_sim_num.GetValue())
+        elif hasattr(self.data, 'exp_mc_sim_num'):
+            self.exp_mc_sim_num.SetValue(int(self.data.exp_mc_sim_num))
 
         # The All model MC sim flag.
         if upload:
@@ -713,7 +722,7 @@
         Relax_disp.opt_max_iterations = self.data.opt_max_iterations
 
         # Execute.
-        Relax_disp(pipe_name=self.data.pipe_name, 
pipe_bundle=self.data.pipe_bundle, results_dir=self.data.save_dir, 
models=self.data.models, grid_inc=self.data.inc, 
mc_sim_num=self.data.mc_sim_num, pre_run_dir=self.data.pre_run_dir, 
mc_sim_all_models=self.data.mc_sim_all_models, 
insignificance=self.data.insignificance, numeric_only=self.data.numeric_only, 
r1_fit=self.data.r1_fit)
+        Relax_disp(pipe_name=self.data.pipe_name, 
pipe_bundle=self.data.pipe_bundle, results_dir=self.data.save_dir, 
models=self.data.models, grid_inc=self.data.inc, 
mc_sim_num=self.data.mc_sim_num, exp_mc_sim_num=self.data.exp_mc_sim_num, 
pre_run_dir=self.data.pre_run_dir, 
mc_sim_all_models=self.data.mc_sim_all_models, 
insignificance=self.data.insignificance, numeric_only=self.data.numeric_only, 
r1_fit=self.data.r1_fit)
 
         # Alias the relax data store data.
         data = ds.relax_gui.analyses[self.data_index]


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