Re: r23788 - /branches/disp_spin_speed/target_functions/relax_disp.py -- June 10, 2014 - 17:04

Hi Troels,

Is it possible to shift the mask_replace part into __init__()?  That
might give more speed ups.  I'm not so familiar with numpy masks, so I
couldn't have helped you with that.  Anyway, those 4 hours invested is
guaranteed to save you much more than 4 hours when you use this later.

Regards,

Edward



On 10 June 2014 16:51,  <tlinnet@xxxxxxxxxxxxx> wrote:
> Author: tlinnet
> Date: Tue Jun 10 16:51:33 2014
> New Revision: 23788
>
> URL: http://svn.gna.org/viewcvs/relax?rev=23788&view=rev
> Log:
> Implemented a masked array search for where "missing" array is equal 1.
>
> This makes it possible to replace all values with this mask, from the value 
> array.
>
> This eliminates the last loops over the missing values.
>
> It took over 4 hours to figure out, that the mask should be called with 
> mask.mask,
> to return the same fulls structure,
>
> 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=23788&r1=23787&r2=23788&view=diff
> ==============================================================================
> --- branches/disp_spin_speed/target_functions/relax_disp.py     (original)
> +++ branches/disp_spin_speed/target_functions/relax_disp.py     Tue Jun 10 
> 16:51:33 2014
> @@ -29,6 +29,7 @@
>  from math import pi
>  from numpy import array, asarray, complex64, dot, float64, int16, max, 
> ones, sqrt, sum, zeros
>  import numpy as np
> +from numpy.ma import masked_equal
>
>  # relax module imports.
>  from lib.dispersion.b14 import r2eff_B14
> @@ -418,6 +419,7 @@
>              # The number of disp point can change per spectrometer, so we 
> make the maximum size.
>              self.values_a = deepcopy(self.zeros_a)
>              self.errors_a = deepcopy(self.ones_a)
> +            self.missing_a = zeros(self.numpy_array_shape)
>
>              self.cpmg_frqs_a = deepcopy(self.ones_a)
>              self.num_disp_points_a = deepcopy(self.zeros_a)
> @@ -456,6 +458,7 @@
>                              for di in 
> range(self.num_disp_points[ei][si][mi][oi]):
>                                  if self.missing[ei][si][mi][oi][di]:
>                                      self.has_missing = True
> +                                    self.missing_a[ei][si][mi][oi][di] = 
> 1.0
>
>              # Make copy of values structure.
>              self.back_calc_a = deepcopy(self.values_a)
> @@ -574,15 +577,11 @@
>
>          ## 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:
> -            # Loop over the spins.
> -            for si in range(self.num_spins):
> -                # Loop over the spectrometer frequencies.
> -                for mi in range(self.num_frq):
> -                    # Loop over the dispersion 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]
> -                            self.back_calc_a[0][si][mi][0][di] = 
> self.values[0][si][mi][0][di]
> +            # Find the numpy mask, which tells where values should be 
> replaced.
> +            mask_replace = masked_equal(self.missing_a, 1.0)
> +
> +            # Replace with values.
> +            self.back_calc_a[mask_replace.mask] = 
> self.values_a[mask_replace.mask]
>
>          ## Calculate the chi-squared statistic.
>          return sum((1.0 / self.errors_a * (self.values_a - 
> self.back_calc_a))**2)
>
>
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