Author: bugman
Date: Mon Dec 1 10:51:10 2008
New Revision: 8073
URL: http://svn.gna.org/viewcvs/relax?rev=8073&view=rev
Log:
Removal of the mean_and_error() method. This is now part of
generic_fns.spectrum.
Modified:
branches/spectral_errors/specific_fns/relax_fit.py
Modified: branches/spectral_errors/specific_fns/relax_fit.py
URL:
http://svn.gna.org/viewcvs/relax/branches/spectral_errors/specific_fns/relax_fit.py?rev=8073&r1=8072&r2=8073&view=diff
==============================================================================
--- branches/spectral_errors/specific_fns/relax_fit.py (original)
+++ branches/spectral_errors/specific_fns/relax_fit.py Mon Dec 1 10:51:10
2008
@@ -584,128 +584,6 @@
b = array(b, float64)
return A, b
-
-
- def mean_and_error(self, verbosity=0):
- """Calculate the average intensity and standard deviation of all
spectra.
-
- @keyword verbosity: The amount of information to print. The higher
the value, the greater
- the verbosity.
- @type verbosity: int
- """
-
- # Alias the current data pipe.
- cdp = pipes.get_pipe()
-
- # Test if the standard deviation has already been calculated.
- if hasattr(cdp, 'sigma_I'):
- raise RelaxError, "The average intensity and standard deviation
of all spectra has already been calculated."
-
- # Print out.
- print "\nCalculating the average intensity and standard deviation of
all spectra."
-
- # Initialise.
- cdp.sigma_I = []
- cdp.var_I = []
-
- # Loop over the time points.
- for time_index in xrange(len(cdp.relax_times)):
- # Print out.
- print "\nTime point: " + `cdp.relax_times[time_index]` + " s"
- print "Number of spectra: " + `cdp.num_spectra[time_index]`
- if verbosity:
- print "%-5s%-6s%-20s%-20s" % ("Num", "Name", "Average", "SD")
-
- # Append zero to the global variance structure.
- cdp.var_I.append(0.0)
-
- # Test for multiple spectra.
- if cdp.num_spectra[time_index] == 1:
- multiple_spectra = 0
- else:
- multiple_spectra = 1
-
- # Calculate the mean value.
- for spin in spin_loop():
- # Skip deselected spins.
- if not spin.select:
- continue
-
- # Skip and deselect spins which have no data.
- if not hasattr(spin, 'intensities'):
- spin.select = False
- continue
-
- # Initialise the average intensity and standard deviation
data structures.
- if not hasattr(spin, 'ave_intensities'):
- spin.ave_intensities = []
- if not hasattr(spin, 'var_I'):
- spin.var_I = []
-
- # Average intensity.
-
spin.ave_intensities.append(average(spin.intensities[time_index]))
-
- # Sum of squared errors.
- SSE = 0.0
- for j in xrange(cdp.num_spectra[time_index]):
- SSE = SSE + (spin.intensities[time_index][j] -
spin.ave_intensities[time_index]) ** 2
-
- # Variance.
- #
- # 1
- # sigma^2 = ----- * sum({Xi - Xav}^2)]
- # n - 1
- #
- if cdp.num_spectra[time_index] == 1:
- var_I = 0.0
- else:
- var_I = 1.0 / (cdp.num_spectra[time_index] - 1.0) * SSE
- spin.var_I.append(var_I)
-
- # Print out.
- if verbosity:
- print "%-5i%-6s%-20s%-20s" % (spin.num, spin.name,
`spin.ave_intensities[time_index]`, `spin.var_I[time_index]`)
-
- # Sum of variances (for average).
- cdp.var_I[time_index] = cdp.var_I[time_index] +
spin.var_I[time_index]
-
- # Average variance.
- cdp.var_I[time_index] = cdp.var_I[time_index] /
float(count_spins())
-
- # Print out.
- print "Standard deviation for time point %s: %s" %
(`time_index`, `sqrt(cdp.var_I[time_index])`)
-
-
- # Average across all spectra if there are time points with a single
spectrum.
- if 0.0 in cdp.var_I:
- # Initialise.
- var_I = 0.0
- num_dups = 0
-
- # Loop over all time points.
- for i in xrange(len(cdp.relax_times)):
- # Single spectrum (or extraordinarily accurate NMR spectra!).
- if cdp.var_I[i] == 0.0:
- continue
-
- # Sum and count.
- var_I = var_I + cdp.var_I[i]
- num_dups = num_dups + 1
-
- # Average value.
- var_I = var_I / float(num_dups)
-
- # Assign the average value to all time points.
- for i in xrange(len(cdp.relax_times)):
- cdp.var_I[i] = var_I
-
- # Print out.
- print "\nStandard deviation (averaged over all spectra): " +
`var_I`
-
- # Create the standard deviation data structure.
- cdp.sigma_I = []
- for var_I in cdp.var_I:
- cdp.sigma_I.append(sqrt(var_I))
def minimise(self, min_algor=None, min_options=None, func_tol=None,
grad_tol=None, max_iterations=None, constraints=False, scaling=True,
verbosity=0, sim_index=None, lower=None, upper=None, inc=None):
r8073 - /branches/spectral_errors/specific_fns/relax_fit.py