Author: tlinnet
Date: Tue Jan 20 12:41:23 2015
New Revision: 27230
URL: http://svn.gna.org/viewcvs/relax?rev=27230&view=rev
Log:
Expanded the STD acronym, to the meaning of Standard deviation.
This is in the user function 'monte_carlo.create_data'.
Task #7882 (https://gna.org/task/?7882): Implement Monte-Carlo simulation,
where errors are generated with width of standard deviation or residuals.):
Implement Monte-Carlo simulation, where errors are generated with width of
standard deviation or residuals.
Modified:
trunk/user_functions/monte_carlo.py
Modified: trunk/user_functions/monte_carlo.py
URL:
http://svn.gna.org/viewcvs/relax/trunk/user_functions/monte_carlo.py?rev=27230&r1=27229&r2=27230&view=diff
==============================================================================
--- trunk/user_functions/monte_carlo.py (original)
+++ trunk/user_functions/monte_carlo.py Tue Jan 20 12:41:23 2015
@@ -104,7 +104,7 @@
uf.desc[-1].add_paragraph("The method can either be set to back
calculation (Monte Carlo) or direct (bootstrapping), the choice of which
determines the simulation type. If the values or parameters are calculated
rather than minimised, this option will have no effect. Errors should only
be propagated via Monte Carlo simulations if errors have been measured. ")
uf.desc[-1].add_paragraph("For error analysis, the method should be set to
back calculation which will result in proper Monte Carlo simulations. The
data used for each simulation is back calculated from the minimised model
parameters and is randomised using Gaussian noise where the standard
deviation is from the original error set. When the method is set to back
calculation, this function should only be called after the model is fully
minimised.")
uf.desc[-1].add_paragraph("The simulation type can be changed by setting
the method to direct. This will result in bootstrapping simulations which
cannot be used in error analysis (and which are no longer Monte Carlo
simulations). However, these simulations are required for certain model
selection techniques (see the documentation for the model selection user
function for details), and can be used for other purposes. Rather than the
data being back calculated from the fitted model parameters, the data is
generated by taking the original data and randomising using Gaussian noise
with the standard deviations set to the original error set.")
-uf.desc[-1].add_paragraph("The errors generated per simulation can either
be generated indidual per datapoint and drawn from a gauss distrubtion
described by the STD of the indidual point, or it can be generated from a
overall gauss distribution described by the STD_fit of the goodness of fit,
where STD_fit = sqrt(chi2/(N-p)). The last possibility is to supply a
fixed value of STD, from which gauss distribution to draw errors from.")
+uf.desc[-1].add_paragraph("The errors generated per simulation can either
be generated indidual per datapoint and drawn from a gauss distrubtion
described by the standard deviation of the indidual point, or it can be
generated from a overall gauss distribution described by the standard
deviation of the goodness of fit, where SD_fit = sqrt(chi2/(N-p)). The
last possibility is to supply a fixed value of the standard deviation, from
which gauss distribution to draw errors from.")
uf.desc.append(monte_carlo_desc)
uf.backend = error_analysis.monte_carlo_create_data
uf.menu_text = "&create_data"
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Re: r27230 - /trunk/user_functions/monte_carlo.py