Ok, forget about my last message at http://article.gmane.org/gmane.science.nmr.relax.devel/6102 :)
Edward On 7 June 2014 23:18, <[email protected]> wrote: > Author: tlinnet > Date: Sat Jun 7 23:18:18 2014 > New Revision: 23727 > > URL: http://svn.gna.org/viewcvs/relax?rev=23727&view=rev > Log: > Moved the creation of special numpy structures outside target function. > > 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=23727&r1=23726&r2=23727&view=diff > ============================================================================== > --- branches/disp_spin_speed/target_functions/relax_disp.py (original) > +++ branches/disp_spin_speed/target_functions/relax_disp.py Sat Jun 7 > 23:18:18 2014 > @@ -394,6 +394,43 @@ > if model == MODEL_NS_MMQ_3SITE_LINEAR: > self.func = self.func_ns_mmq_3site_linear > > + # Setup special numpy array structures, for higher dimensional > computation. > + if model == MODEL_CR72_FULL: > + # Get the shape of back_calc structure. > + back_calc_shape = list( np.asarray(self.back_calc).shape ) > + > + # Find which frequency has the maximum number of disp points. > + # To let the numpy array operate well together, the broadcast > size has to be equal for all shapes. > + self.max_num_disp_points = np.max(self.num_disp_points) > + > + # Create numpy arrays to pass to the lib function. > + # All numpy arrays have to have same shape to allow to multiply > together. > + # The dimensions should be [ei][si][mi][oi][di]. > [Experiment][spins][spec. frq][offset][disp points]. > + # The number of disp point can change per spectrometer, so we > make the maximum size. > + self.R20A_a = np.ones(back_calc_shape + > [self.max_num_disp_points]) > + self.R20B_a = np.ones(back_calc_shape + > [self.max_num_disp_points]) > + self.pA_a = np.ones(back_calc_shape + [self.max_num_disp_points]) > + self.dw_frq_a = np.ones(back_calc_shape + > [self.max_num_disp_points]) > + self.kex_a = np.ones(back_calc_shape + > [self.max_num_disp_points]) > + 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]) > + > + # Loop over the experiment types. > + for ei in range(self.num_exp): > + # 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 offsets. > + for oi in range(self.num_offsets[ei][si][mi]): > + # Extract number of dispersion points. > + num_disp_points = > self.num_disp_points[ei][si][mi][oi] > + > + # Extract cpmg_frqs and num_disp_points from > lists. > + > 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] > + > > 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. > @@ -471,26 +508,6 @@ > @rtype: float > """ > > - # Get the shape of back_calc structure. > - back_calc_shape = list( np.asarray(self.back_calc).shape ) > - > - # Find which frequency has the maximum number of disp points. > - # To let the numpy array operate well together, the broadcast size > has to be equal for all shapes. > - max_num_disp_points = np.max(self.num_disp_points) > - > - # Create numpy arrays to pass to the lib function. > - # All numpy arrays have to have same shape to allow to multiply > together. > - # The dimensions should be [ei][si][mi][oi][di]. > [Experiment][spins][spec. frq][offset][disp points]. > - # The number of disp point can change per spectrometer, so we make > the maximum size. > - R20A_a = np.ones(back_calc_shape + [max_num_disp_points]) > - R20B_a = np.ones(back_calc_shape + [max_num_disp_points]) > - pA_a = np.ones(back_calc_shape + [max_num_disp_points]) > - dw_frq_a = np.ones(back_calc_shape + [max_num_disp_points]) > - kex_a = np.ones(back_calc_shape + [max_num_disp_points]) > - cpmg_frqs_a = np.ones(back_calc_shape + [max_num_disp_points]) > - num_disp_points_a = np.ones(back_calc_shape + [max_num_disp_points]) > - back_calc_a = np.ones(back_calc_shape + [max_num_disp_points]) > - > # Loop over the experiment types. > for ei in range(self.num_exp): > # Loop over the spins. > @@ -506,25 +523,21 @@ > r20_index = mi + si*self.num_frq > > # Store r20a and r20b values per disp point. > - R20A_a[ei][si][mi][oi] = np.array( [R20A[r20_index]] > * max_num_disp_points, float64) > - R20B_a[ei][si][mi][oi] = np.array( > [R20B[r20_index]] * max_num_disp_points, float64) > + self.R20A_a[ei][si][mi][oi] = np.array( > [R20A[r20_index]] * self.max_num_disp_points, float64) > + self.R20B_a[ei][si][mi][oi] = np.array( > [R20B[r20_index]] * self.max_num_disp_points, float64) > > # Convert dw from ppm to rad/s. > dw_frq = dw[si] * self.frqs[ei][si][mi] > > # Store dw_frq per disp point. > - dw_frq_a[ei][si][mi][oi] = np.array( [dw_frq] * > max_num_disp_points, float64) > + self.dw_frq_a[ei][si][mi][oi] = np.array( [dw_frq] * > self.max_num_disp_points, float64) > > # Store pA and kex per disp point. > - pA_a[ei][si][mi][oi] = np.array( [pA] * > max_num_disp_points, float64) > - kex_a[ei][si][mi][oi] = np.array( [kex] * > max_num_disp_points, float64) > - > - # Extract cpmg_frqs and num_disp_points from lists. > - cpmg_frqs_a[ei][si][mi][oi][:num_disp_points] = > self.cpmg_frqs[ei][mi][oi] > - num_disp_points_a[ei][si][mi][oi][:num_disp_points] > = self.num_disp_points[ei][si][mi][oi] > + self.pA_a[ei][si][mi][oi] = np.array( [pA] * > self.max_num_disp_points, float64) > + self.kex_a[ei][si][mi][oi] = np.array( [kex] * > self.max_num_disp_points, float64) > > ## Back calculate the R2eff values. > - r2eff_CR72(r20a=R20A_a, r20b=R20B_a, pA=pA_a, dw=dw_frq_a, > kex=kex_a, cpmg_frqs=cpmg_frqs_a, back_calc = back_calc_a, > num_points=num_disp_points_a) > + r2eff_CR72(r20a=self.R20A_a, r20b=self.R20B_a, pA=self.pA_a, > dw=self.dw_frq_a, kex=self.kex_a, cpmg_frqs=self.cpmg_frqs_a, > back_calc=self.back_calc_a, num_points=self.num_disp_points_a) > > # Initialise. > chi2_sum = 0.0 > @@ -542,7 +555,7 @@ > # Extract number of dispersion points. > num_disp_points = > self.num_disp_points[ei][si][mi][oi] > > - self.back_calc[ei][si][mi][oi] = > back_calc_a[ei][si][mi][oi][:num_disp_points] > + self.back_calc[ei][si][mi][oi] = > self.back_calc_a[ei][si][mi][oi][:num_disp_points] > > > for di in > range(self.num_disp_points[ei][si][mi][oi]): > > > _______________________________________________ > 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
