r19495 - in /branches/relax_disp: ./ lib/__init__.py lib/stats.py pipe_control/monte_carlo.py -- April 19, 2013 - 19:53

Author: bugman
Date: Fri Apr 19 19:53:06 2013
New Revision: 19495

URL: http://svn.gna.org/viewcvs/relax?rev=19495&view=rev
Log:
Merged revisions 19494 via svnmerge from 
svn+ssh://bugman@xxxxxxxxxxx/svn/relax/trunk

........
  r19494 | bugman | 2013-04-19 19:52:10 +0200 (Fri, 19 Apr 2013) | 7 lines
  
  Shifted the standard deviation code from the Monte Carlo error_analysis() 
function to the lib package.
  
  The new function lib.stats.std() is now used to simplify the 
error_analysis() function and allow the
  code to be reused.  This will be useful for expanding the 
pipe_control.monte_carlo.error_analysis()
  function to handle parameters which are dictionaries, for example as in the 
relax_disp branch.
........

Added:
    branches/relax_disp/lib/stats.py
      - copied unchanged from r19494, trunk/lib/stats.py
Modified:
    branches/relax_disp/   (props changed)
    branches/relax_disp/lib/__init__.py
    branches/relax_disp/pipe_control/monte_carlo.py

Propchange: branches/relax_disp/
------------------------------------------------------------------------------
--- svnmerge-integrated (original)
+++ svnmerge-integrated Fri Apr 19 19:53:06 2013
@@ -1,1 +1,1 @@
-/trunk:1-19489
+/trunk:1-19494

Modified: branches/relax_disp/lib/__init__.py
URL: 
http://svn.gna.org/viewcvs/relax/branches/relax_disp/lib/__init__.py?rev=19495&r1=19494&r2=19495&view=diff
==============================================================================
--- branches/relax_disp/lib/__init__.py (original)
+++ branches/relax_disp/lib/__init__.py Fri Apr 19 19:53:06 2013
@@ -45,6 +45,7 @@
     'regex',
     'selection',
     'spectral_densities',
+    'stats',
     'structure',
     'text',
     'warnings'

Modified: branches/relax_disp/pipe_control/monte_carlo.py
URL: 
http://svn.gna.org/viewcvs/relax/branches/relax_disp/pipe_control/monte_carlo.py?rev=19495&r1=19494&r2=19495&view=diff
==============================================================================
--- branches/relax_disp/pipe_control/monte_carlo.py (original)
+++ branches/relax_disp/pipe_control/monte_carlo.py Fri Apr 19 19:53:06 2013
@@ -24,14 +24,14 @@
 
 # Python module imports.
 from copy import deepcopy
-from math import sqrt
 from numpy import ndarray
 from random import gauss
 
 # relax module imports.
+from lib.errors import RelaxError, RelaxNoSequenceError
+from lib import stats
 from pipe_control.mol_res_spin import exists_mol_res_spin_data
 from pipe_control import pipes
-from lib.errors import RelaxError, RelaxNoSequenceError
 from specific_analyses.setup import get_specific_fn
 
 
@@ -156,49 +156,9 @@
             if param_array == None:
                 break
 
-            # Simulation parameters with values (ie not None).
+            # SD of simulation parameters with values (ie not None).
             if param_array[0] != None:
-                # The total number of simulations.
-                n = 0
-                for i in range(len(param_array)):
-                    # Skip deselected simulations.
-                    if not select_sim[i]:
-                        continue
-
-                    # Increment n.
-                    n = n + 1
-
-                # Calculate the sum of the parameter value for all 
simulations.
-                Xsum = 0.0
-                for i in range(len(param_array)):
-                    # Skip deselected simulations.
-                    if not select_sim[i]:
-                        continue
-
-                    # Sum.
-                    Xsum = Xsum + param_array[i]
-
-                # Calculate the mean parameter value for all simulations.
-                if n == 0:
-                    Xav = 0.0
-                else:
-                    Xav = Xsum / float(n)
-
-                # Calculate the sum part of the standard deviation.
-                sd = 0.0
-                for i in range(len(param_array)):
-                    # Skip deselected simulations.
-                    if not select_sim[i]:
-                        continue
-
-                    # Sum.
-                    sd = sd + (param_array[i] - Xav)**2
-
-                # Calculate the standard deviation.
-                if n <= 1:
-                    sd = 0.0
-                else:
-                    sd = sqrt(sd / (float(n) - 1.0))
+                sd = stats.std(values=param_array, skip=select_sim)
 
             # Simulation parameters with the value None.
             else: