Hi Troels,
This still has the same problems with the R2eff model as mentioned at
http://thread.gmane.org/gmane.science.nmr.relax.scm/24963/focus=7490.
Regards,
Edward
On 17 January 2015 at 17:25, <tlinnet@xxxxxxxxxxxxx> wrote:
Author: tlinnet
Date: Sat Jan 17 17:25:20 2015
New Revision: 27219
URL: http://svn.gna.org/viewcvs/relax?rev=27219&view=rev
Log:
Added API function in relaxation dispersion to return error structure
from the reduced chi2 distribution.
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/specific_analyses/relax_disp/api.py
Modified: trunk/specific_analyses/relax_disp/api.py
URL:
http://svn.gna.org/viewcvs/relax/trunk/specific_analyses/relax_disp/api.py?rev=27219&r1=27218&r2=27219&view=diff
==============================================================================
--- trunk/specific_analyses/relax_disp/api.py (original)
+++ trunk/specific_analyses/relax_disp/api.py Sat Jan 17 17:25:20 2015
@@ -27,7 +27,7 @@
# Python module imports.
import bmrblib
from copy import deepcopy
-from numpy import int32, zeros
+from numpy import int32, sqrt, zeros
from re import match, search
import string
import sys
@@ -1035,6 +1035,44 @@
# Return the error list.
return errors
+
+
+ def return_error_red_chi2(self, data_id=None):
+ """Return the standard deviation data structure, where standard
deviation is from the overall gauss distribution described by the STD_fit
of the goodness of fit, where STD_fit = sqrt(chi2/(N-p))
+
+ @param data_id: The tuple of the spin container and the
exponential curve identifying key, as yielded by the base_data_loop()
generator method.
+ @type data_id: SpinContainer instance and float
+ @return: The standard deviation data structure.
+ @rtype: list of float
+ """
+
+ # Get the errors structure as above.
+ errors = self.return_error(data_id=data_id)
+
+ # Unpack the data.
+ spin, spin_id = data_id
+
+ # Loop over the spin groupings for the model.
+ for spin_ids in self.model_loop():
+ # If the spin of interest is in the returned spin cluster.
+ if spin_id in spin_ids:
+ # Get the statistics
+ k, n, chi2 = self.model_statistics(model_info=spin_ids)
+
+ # Calculate degrees of freedom.
+ dof = n - k
+
+ # Calculate reduced chi2, or named as the variance of
the squared residuals.
+ red_chi2 = chi2 / float(dof)
+
+ # Calculated the standard deviation.
+ std_red_chi2 = sqrt(red_chi2)
+
+ # Replace values with the stored value.
+ for id in errors:
+ errors[id] = std_red_chi2
+
+ return errors
def return_value(self, spin, param, sim=None, bc=False):
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Re: r27219 - /trunk/specific_analyses/relax_disp/api.py