Or in: r2effs = optimisation.back_calc_r2eff(spin=cur_spin, spin_id=cur_spin_id)
2014-06-13 17:52 GMT+02:00 Troels Emtekær Linnet <[email protected]>: > Hi Ed. > > I think I have broken something somewhere? > > It must be something with: > specific_analyses.relax_disp.data > loop_offset_point > > Best > Troels > > > ---------- Forwarded message ---------- > From: <[email protected]> > Date: 2014-06-13 17:31 GMT+02:00 > Subject: r23942 - /branches/disp_spin_speed/target_functions/relax_disp.py > To: [email protected] > > > Author: tlinnet > Date: Fri Jun 13 17:31:40 2014 > New Revision: 23942 > > URL: http://svn.gna.org/viewcvs/relax?rev=23942&view=rev > Log: > Replaced target function for model ns_cpmg_2site_expanded, to use higher > dimensional numpy array structures. > > That makes the model much faster. > > I cannot get system test: Relax_disp.test_cpmg_synthetic_dx_map_points > to pass. > > ------- > File > "/Users/tlinnet/software/disp_spin_speed/test_suite/system_tests/relax_disp.py", > line 1671, in test_cpmg_synthetic_dx_map_points > self.assertEqual(res_file[i], lines[i]) > AssertionError: '0.76981 3.9169 0.41353 1\n' != > '0.0098838 1.4654 18.661 1\n' > ------- > > 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=23942&r1=23941&r2=23942&view=diff > > ============================================================================== > --- branches/disp_spin_speed/target_functions/relax_disp.py (original) > +++ branches/disp_spin_speed/target_functions/relax_disp.py Fri Jun 13 > 17:31:40 2014 > @@ -396,7 +396,7 @@ > > > # Setup special numpy array structures, for higher dimensional > computation. > - test_models = [MODEL_B14, MODEL_B14_FULL, MODEL_CR72, > MODEL_CR72_FULL, MODEL_DPL94, MODEL_IT99, MODEL_LM63, MODEL_M61, > MODEL_M61B, MODEL_MP05, MODEL_TAP03, MODEL_TP02, MODEL_TSMFK01] > + test_models = [MODEL_B14, MODEL_B14_FULL, MODEL_CR72, > MODEL_CR72_FULL, MODEL_DPL94, MODEL_IT99, MODEL_LM63, MODEL_M61, > MODEL_M61B, MODEL_MP05, MODEL_NS_CPMG_2SITE_EXPANDED, MODEL_TAP03, > MODEL_TP02, MODEL_TSMFK01] > > if model in test_models + [MODEL_NOREX]: > # Get the shape of back_calc structure. > @@ -457,10 +457,10 @@ > self.phi_ex_struct = deepcopy(zeros_a) > > if model in [MODEL_B14, MODEL_B14_FULL, MODEL_MMQ_CR72, > MODEL_NS_CPMG_2SITE_3D, MODEL_NS_CPMG_2SITE_3D_FULL, > MODEL_NS_CPMG_2SITE_EXPANDED, MODEL_NS_CPMG_2SITE_STAR, > MODEL_NS_CPMG_2SITE_STAR_FULL, MODEL_NS_MMQ_2SITE, MODEL_NS_MMQ_3SITE, > MODEL_NS_MMQ_3SITE_LINEAR, MODEL_TSMFK01, MODEL_NS_R1RHO_2SITE, > MODEL_NS_R1RHO_3SITE, MODEL_NS_R1RHO_3SITE_LINEAR]: > - # Expand relax times. > - self.inv_relax_times_a = 1.0 / multiply.outer( > tile(self.relax_times[:,None],(1, 1, self.NS)).reshape(self.NE, self.NS, > self.NM), self.no_nd_struct ) > - self.power_a = ones(self.numpy_array_shape, int16) > + self.relax_times_a = deepcopy(zeros_a) > + self.inv_relax_times_a = deepcopy(zeros_a) > self.tau_cpmg_a = deepcopy(zeros_a) > + self.power_a = zeros(self.numpy_array_shape, int16) > > # For R1rho data. > if model in MODEL_LIST_R1RHO_FULL: > @@ -501,8 +501,13 @@ > self.has_missing = True > missing_a[ei][si][mi][oi][di] = 1.0 > if model in [MODEL_B14, MODEL_B14_FULL, > MODEL_MMQ_CR72, MODEL_NS_CPMG_2SITE_3D, MODEL_NS_CPMG_2SITE_3D_FULL, > MODEL_NS_CPMG_2SITE_EXPANDED, MODEL_NS_CPMG_2SITE_STAR, > MODEL_NS_CPMG_2SITE_STAR_FULL, MODEL_NS_MMQ_2SITE, MODEL_NS_MMQ_3SITE, > MODEL_NS_MMQ_3SITE_LINEAR, MODEL_TSMFK01, MODEL_NS_R1RHO_2SITE, > MODEL_NS_R1RHO_3SITE, MODEL_NS_R1RHO_3SITE_LINEAR]: > - 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] > + > self.relax_times_a[ei][si][mi][oi][di] = self.relax_times[ei][mi] > + self.tau_cpmg_a[ei][si][mi][oi][di] = > self.tau_cpmg[ei][mi][di] > + self.power_a[ei][si][mi][oi][di] = > self.power[ei][mi][di] > + > + if model != MODEL_TSMFK01: > + > self.inv_relax_times_a[ei][si][mi][oi][di] = self.inv_relax_times[ei][mi] > + > # For R1rho data. > if model in MODEL_LIST_R1RHO_FULL and > model != MODEL_NOREX: > self.disp_struct[ei][si][mi][oi][di] > = 1.0 > @@ -1500,37 +1505,25 @@ > pA = params[self.end_index[1]] > kex = params[self.end_index[1]+1] > > - # Once off parameter conversions. > - pB = 1.0 - pA > - k_BA = pA * kex > - k_AB = pB * kex > - > - # Chi-squared initialisation. > - 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. > - r20_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_ns_cpmg_2site_expanded(r20=R20[r20_index], pA=pA, > dw=dw_frq, k_AB=k_AB, k_BA=k_BA, relax_time=self.relax_times[0][mi], > inv_relax_time=self.inv_relax_times[0][mi], 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], num_cpmg=self.power[0][mi]) > - > - # 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]) > - > - # Return the total chi-squared value. > - return chi2_sum > + # 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_a, out=self.dw_struct ) > + > + # Reshape R20A and R20B to per experiment, spin and frequency. > + self.r20_struct[:] = multiply.outer( R20.reshape(self.NE, > self.NS, self.NM), self.no_nd_struct ) > + > + # Back calculate the R2eff values. > + r2eff_ns_cpmg_2site_expanded(r20=self.r20_struct, pA=pA, > dw=self.dw_struct, dw_orig=dw, kex=kex, relax_time=self.relax_times_a, > inv_relax_time=self.inv_relax_times_a, tcp=self.tau_cpmg_a, > back_calc=self.back_calc_a, num_cpmg=self.power_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] > + > + ## Calculate the chi-squared statistic. > + return chi2_rankN(self.values_a, self.back_calc_a, self.errors_a) > > > def func_ns_cpmg_2site_star(self, params): > > > _______________________________________________ > 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
