Hi Troels, This commit seems to be missing the lib.dispersion.tsmfk01 changes needed to make the model functional.
Cheers, Edward On 12 June 2014 13:56, <[email protected]> wrote: > Author: tlinnet > Date: Thu Jun 12 13:56:12 2014 > New Revision: 23880 > > URL: http://svn.gna.org/viewcvs/relax?rev=23880&view=rev > Log: > Large increase in speed for model TSMFK01 by changing target functions to use > multidimensional numpy arrays in calculation. > > This is done by restructuring data into multidimensional arrays of dimension > [NE][NS][NM][NO][ND], which are > number of spins, number of magnetic field strength, number of offsets, > maximum number of dispersion point. > > The speed comes from using numpy ufunc operations. > > The new version is 2.4X as fast per spin calculation, and 54X as fast for > clustered analysis. > > The different in timings for 3 spectrometer frequencies, calculated for 1 > spin or 100 clustered spins with 1000 iterations are: > > ---- > VERSION 3.2.2 > ---- > 1 spin: > ncalls tottime percall cumtime percall filename:lineno(function) > 1 0.000 0.000 0.262 0.262 <string>:1(<module>) > 100 spin: > ncalls tottime percall cumtime percall filename:lineno(function) > 1 0.000 0.000 25.391 25.391 <string>:1(<module>) > ---- > New version > --- > > 1 spin: > ncalls tottime percall cumtime percall filename:lineno(function) > 1 0.000 0.000 0.111 0.111 <string>:1(<module>) > 100 spin: > ncalls tottime percall cumtime percall filename:lineno(function) > 1 0.000 0.000 0.468 0.468 <string>:1(<module>) > > 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=23880&r1=23879&r2=23880&view=diff > ============================================================================== > --- branches/disp_spin_speed/target_functions/relax_disp.py (original) > +++ branches/disp_spin_speed/target_functions/relax_disp.py Thu Jun 12 > 13:56:12 2014 > @@ -395,7 +395,7 @@ > self.func = self.func_ns_mmq_3site_linear > > # Setup special numpy array structures, for higher dimensional > computation. > - if model in [MODEL_B14, MODEL_B14_FULL, MODEL_CR72, MODEL_CR72_FULL]: > + if model in [MODEL_B14, MODEL_B14_FULL, MODEL_CR72, MODEL_CR72_FULL, > MODEL_TSMFK01]: > # Get the shape of back_calc structure. > # If using just one field, or having the same number of > dispersion points, the shape would extend to that number. > # Shape has to be: [ei][si][mi][oi]. > @@ -478,7 +478,7 @@ > if self.missing[ei][si][mi][oi][di]: > self.has_missing = True > missing_a[ei][si][mi][oi][di] = 1.0 > - if model in [MODEL_B14, MODEL_B14_FULL]: > + if model in [MODEL_B14, MODEL_B14_FULL, > MODEL_TSMFK01]: > self.power_a[ei][si][mi][oi][di] = > int(round(self.cpmg_frqs[ei][mi][0][di] * self.relax_times[ei][mi])) > self.tau_cpmg_a[ei][si][mi][oi][di] = > 0.25 / self.cpmg_frqs[ei][mi][0][di] > > @@ -1989,29 +1989,22 @@ > dw = params[self.end_index[0]:self.end_index[1]] > k_AB = params[self.end_index[1]] > > - # Initialise. > - chi2_sum = 0.0 > - > - # Loop over the spins. > - for si in range(self.num_spins): > - # Loop over the spectrometer frequencies. > - for mi in range(self.num_frq): > - # The R20 index. > - r20a_index = mi + si*self.num_frq > - > - # Convert dw from ppm to rad/s. > - dw_frq = dw[si] * self.frqs[0][si][mi] > - > - # Back calculate the R2eff values. > - r2eff_TSMFK01(r20a=R20A[r20a_index], dw=dw_frq, dw_orig=dw, > k_AB=k_AB, tcp=self.tau_cpmg[0][mi], back_calc=self.back_calc[0][si][mi][0], > num_points=self.num_disp_points[0][si][mi][0]) > - > - # 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. > - 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]) > + # Convert dw from ppm to rad/s. Use the out argument, to pass > directly to structure. > + multiply( multiply.outer( dw.reshape(self.NE, self.NS), > self.nm_no_nd_struct ), self.frqs_struct, out=self.dw_struct ) > + > + # Reshape R20A and R20B to per experiment, spin and frequency. > + self.r20a_struct[:] = multiply.outer( R20A.reshape(self.NE, self.NS, > self.NM), self.no_nd_struct ) > + > + # Back calculate the R2eff values. > + r2eff_TSMFK01(r20a=self.r20a_struct, dw=self.dw_struct, dw_orig=dw, > k_AB=k_AB, tcp=self.tau_cpmg_a, back_calc=self.back_calc_a, > num_points=self.num_disp_points_a) > + > + # Clean the data for all values, which is left over at the end of > arrays. > + self.back_calc_a = self.back_calc_a*self.disp_struct > + > + ## 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: > + # Replace with values. > + self.back_calc_a[self.mask_replace_blank.mask] = > self.values_a[self.mask_replace_blank.mask] > > # Return the total chi-squared value. > - return chi2_sum > + return chi2_rankN(self.values_a, self.back_calc_a, self.errors_a) > > > _______________________________________________ > relax (http://www.nmr-relax.com) > > This is the relax-commits mailing list > [email protected] > > To unsubscribe from this list, get a password > reminder, or change your subscription options, > visit the list information page at > https://mail.gna.org/listinfo/relax-commits _______________________________________________ relax (http://www.nmr-relax.com) This is the relax-devel mailing list [email protected] To unsubscribe from this list, get a password reminder, or change your subscription options, visit the list information page at https://mail.gna.org/listinfo/relax-devel
