Author: bugman
Date: Tue Oct 21 17:25:06 2008
New Revision: 7893
URL: http://svn.gna.org/viewcvs/relax?rev=7893&view=rev
Log:
Shifted the relax_fit.mean_and_error() user function interface to
spectrum.mean_and_error().
Modified:
branches/spectral_errors/prompt/relax_fit.py
branches/spectral_errors/prompt/spectrum.py
Modified: branches/spectral_errors/prompt/relax_fit.py
URL:
http://svn.gna.org/viewcvs/relax/branches/spectral_errors/prompt/relax_fit.py?rev=7893&r1=7892&r2=7893&view=diff
==============================================================================
--- branches/spectral_errors/prompt/relax_fit.py (original)
+++ branches/spectral_errors/prompt/relax_fit.py Tue Oct 21 17:25:06 2008
@@ -40,60 +40,6 @@
# Place relax in the class namespace.
self.__relax__ = relax
-
-
- def mean_and_error(self):
- """Function for calculating the average intensity and standard
deviation of all spectra.
-
-
- Errors of individual spin at a single time point
- ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
-
- The variance for a single spin at a single time point is calculated
by the formula:
-
- -----
-
- sigma^2 = sum({Ii - Iav}^2) / (n - 1) ,
-
- -----
-
- where sigma^2 is the variance, sigma is the standard deviation, n is
the total number of
- collected spectra for the time point and i is the corresponding
index, Ii is the peak
- intensity for spectrum i, Iav is the mean over all spectra, ie the
sum of all peak
- intensities divided by n.
-
-
- Averaging of the errors
- ~~~~~~~~~~~~~~~~~~~~~~~
-
- As the value of n in the above equation is always very low, normally
only a couple of
- spectra are collected per time point, the variance of all spins is
averaged for a single
- time point. Although this results in all spins having the same
error, the accuracy of the
- error estimate is significantly improved.
-
-
- Errors across multiple time points
- ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
-
- If all spectra are collected in duplicate (triplicate or higher
number of spectra are
- supported), the each time point will have its own error estimate.
However, if there are
- time points in the series which only consist of a single spectrum,
then the variances of
- replicated time points will be averaged. Hence, for the entire
experiment there will be a
- single error value for all spins and for all time points.
-
- A better approach rather than averaging across all time points would
be to use a form of
- interpolation as the errors across time points generally decreases
for longer time periods.
- This is currently not implemented.
- """
-
-
- # Function intro text.
- if self.__relax__.interpreter.intro:
- text = sys.ps3 + "relax_fit.mean_and_error()"
- print text
-
- # Execute the functional code.
- relax_fit_obj.mean_and_error()
def read(self, file=None, dir=None, relax_time=0.0, format='sparky',
heteronuc='N', proton='HN', int_col=None):
Modified: branches/spectral_errors/prompt/spectrum.py
URL:
http://svn.gna.org/viewcvs/relax/branches/spectral_errors/prompt/spectrum.py?rev=7893&r1=7892&r2=7893&view=diff
==============================================================================
--- branches/spectral_errors/prompt/spectrum.py (original)
+++ branches/spectral_errors/prompt/spectrum.py Tue Oct 21 17:25:06 2008
@@ -85,6 +85,60 @@
# Execute the functional code.
intensity.set_error(error=error, spectrum_id=spectrum_id,
spin_id=spin_id)
+
+
+ def mean_and_error(self):
+ """Function for calculating the average intensity and standard
deviation of all spectra.
+
+
+ Errors of individual spin at a single time point
+ ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+
+ The variance for a single spin at a single time point is calculated
by the formula:
+
+ -----
+
+ sigma^2 = sum({Ii - Iav}^2) / (n - 1) ,
+
+ -----
+
+ where sigma^2 is the variance, sigma is the standard deviation, n is
the total number of
+ collected spectra for the time point and i is the corresponding
index, Ii is the peak
+ intensity for spectrum i, Iav is the mean over all spectra, ie the
sum of all peak
+ intensities divided by n.
+
+
+ Averaging of the errors
+ ~~~~~~~~~~~~~~~~~~~~~~~
+
+ As the value of n in the above equation is always very low, normally
only a couple of
+ spectra are collected per time point, the variance of all spins is
averaged for a single
+ time point. Although this results in all spins having the same
error, the accuracy of the
+ error estimate is significantly improved.
+
+
+ Errors across multiple time points
+ ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+
+ If all spectra are collected in duplicate (triplicate or higher
number of spectra are
+ supported), the each time point will have its own error estimate.
However, if there are
+ time points in the series which only consist of a single spectrum,
then the variances of
+ replicated time points will be averaged. Hence, for the entire
experiment there will be a
+ single error value for all spins and for all time points.
+
+ A better approach rather than averaging across all time points would
be to use a form of
+ interpolation as the errors across time points generally decreases
for longer time periods.
+ This is currently not implemented.
+ """
+
+
+ # Function intro text.
+ if self.__relax__.interpreter.intro:
+ text = sys.ps3 + "relax_fit.mean_and_error()"
+ print text
+
+ # Execute the functional code.
+ relax_fit_obj.mean_and_error()
def read_intensities(self, file=None, dir=None, spectrum_id=None,
heteronuc='N', proton='HN', int_col=None, mol_name_col=None,
res_num_col=None, res_name_col=None, spin_num_col=None, spin_name_col=None,
sep=None):
r7893 - in /branches/spectral_errors/prompt: relax_fit.py spectrum.py