Re: r23741 - /branches/disp_spin_speed/target_functions/relax_disp.py -- June 10, 2014 - 14:11

Hi,

For reference, as missing data is quite common in real analyses, a
much, much faster implementation for handling missing data is
described in:

http://article.gmane.org/gmane.science.nmr.relax.devel/5726

This would be orders of magnitude faster for this component.

Regards,

Edward






On 8 June 2014 22:22,  <tlinnet@xxxxxxxxxxxxx> wrote:
> Author: tlinnet
> Date: Sun Jun  8 22:22:24 2014
> New Revision: 23741
>
> URL: http://svn.gna.org/viewcvs/relax?rev=23741&view=rev
> Log:
> Added self.has_missing keyword in initialization of the Dispersion class.
>
> This is to test once, per spin or cluster.
> This saves a looping over the dipsersion points, when collection the data.
>
> Task #7807 (https://gna.org/task/index.php?7807): Speed-up of dispersion 
> models for Clustered analysis.
>
> Modified:
>     branches/disp_spin_speed/target_functions/relax_disp.py
>
> Modified: branches/disp_spin_speed/target_functions/relax_disp.py
> URL: 
> http://svn.gna.org/viewcvs/relax/branches/disp_spin_speed/target_functions/relax_disp.py?rev=23741&r1=23740&r2=23741&view=diff
> ==============================================================================
> --- branches/disp_spin_speed/target_functions/relax_disp.py     (original)
> +++ branches/disp_spin_speed/target_functions/relax_disp.py     Sun Jun  8 
> 22:22:24 2014
> @@ -417,6 +417,7 @@
>              self.cpmg_frqs_a = np.ones(back_calc_shape + 
> [self.max_num_disp_points])
>              self.num_disp_points_a = np.ones(back_calc_shape + 
> [self.max_num_disp_points])
>              self.back_calc_a = np.ones(back_calc_shape + 
> [self.max_num_disp_points])
> +            self.has_missing = False
>
>              # Loop over the experiment types.
>              for ei in range(self.num_exp):
> @@ -433,6 +434,10 @@
>                              
> self.cpmg_frqs_a[ei][si][mi][oi][:num_disp_points] = 
> self.cpmg_frqs[ei][mi][oi]
>                              
> self.num_disp_points_a[ei][si][mi][oi][:num_disp_points] = 
> self.num_disp_points[ei][si][mi][oi]
>
> +                            for di in 
> range(self.num_disp_points[ei][si][mi][oi]):
> +                                if self.missing[ei][si][mi][oi][di]:
> +                                    self.has_missing = True
> +
>
>      def calc_B14_chi2(self, R20A=None, R20B=None, dw=None, pA=None, 
> kex=None):
>          """Calculate the chi-squared value of the Baldwin (2014) 2-site 
> exact solution model for all time scales.
> @@ -541,7 +546,6 @@
>          chi2_sum = 0.0
>
>          # Now return the values back to the structure of self.back_calc 
> object.
> -        ## For all missing data points, set the back-calculated value to 
> the measured values so that it has no effect on the chi-squared value.
>          # Loop over the spins.
>          for si in range(self.num_spins):
>              # Loop over the spectrometer frequencies.
> @@ -551,10 +555,11 @@
>
>                  self.back_calc[0][si][mi][0] = 
> self.back_calc_a[0][si][mi][0][:num_disp_points]
>
> -
> -                for di in range(self.num_disp_points[0][si][mi][0]):
> -                    if self.missing[0][si][mi][0][di]:
> -                        self.back_calc[0][si][mi][0][di] = 
> self.values[0][si][mi][0][di]
> +                ## For all missing data points, set the back-calculated 
> value to the measured values so that it has no effect on the chi-squared 
> value.
> +                if self.has_missing:
> +                    for di in range(self.num_disp_points[0][si][mi][0]):
> +                        if self.missing[0][si][mi][0][di]:
> +                            self.back_calc[0][si][mi][0][di] = 
> self.values[0][si][mi][0][di]
>
>                  ## Calculate and return the chi-squared value.
>                  chi2_sum += chi2(self.values[0][si][mi][0], 
> self.back_calc[0][si][mi][0], self.errors[0][si][mi][0])
>
>
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