Hi. Another way is:
ml = params[:end_index[1]].reshape(num_spins*2, num_frq) R20A = ml[::2].flatten() R20B = ml[1::2].flatten() Best Troels 2014-06-06 11:39 GMT+02:00 Troels Emtekær Linnet <[email protected]>: > There is no doubt that it is the unpacking of the R20A and R20B in the > target function. > > I was thinking of creating a function, which do the the unpacking. > > This unpacking function could then be tested with a unit test? > > What do you think? > Where should I position such a function? > > Best > Troels > > > > 2014-06-06 11:26 GMT+02:00 Edward d'Auvergne <[email protected]>: > >> Hi Troels, >> >> >> The best way to handle this is to first create a unit test of the >> specific_analyses.relax_disp.parameters.disassemble_param_vector() >> where the problem is likely to be most easily found. I don't >> understand how this could be a problem as the assemble_param_vector() >> and disassemble_param_vector() functions both call the same >> loop_parameters() function for the ordering of the parameter values! >> Maybe the problem is in the unpacking of the parameter vector in the >> target functions themselves, for example in the full B14 model: >> >> >> def func_B14_full(self, params): >> """Target function for the Baldwin (2014) 2-site exact >> solution model for all time scales. >> >> This assumes that pA > pB, and hence this must be implemented >> as a constraint. >> >> >> @param params: The vector of parameter values. >> @type params: numpy rank-1 float array >> @return: The chi-squared value. >> @rtype: float >> """ >> >> # Scaling. >> if self.scaling_flag: >> params = dot(params, self.scaling_matrix) >> >> # Unpack the parameter values. >> R20A = params[:self.end_index[0]] >> R20B = params[self.end_index[0]:self.end_index[1]] >> dw = params[self.end_index[1]:self.end_index[2]] >> pA = params[self.end_index[2]] >> kex = params[self.end_index[2]+1] >> >> # Calculate and return the chi-squared value. >> return self.calc_B14_chi2(R20A=R20A, R20B=R20B, dw=dw, pA=pA, >> kex=kex) >> >> >> This R20A and R20B unpacking might be the failure point as this may >> not match the loop_parameters() function - which it must! In any >> case, having a unit or system test catch the problem would be very >> useful for the stability of the dispersion analysis in relax. >> >> A code example might be useful: >> >> R20_params = array([1, 2, 3, 4]) >> R20A, R20B = transpose(R20_params.reshape(2, 2) >> print(R20A) >> print(R20B) >> >> You should see that R20A is [1, 3], and R20B is [2, 4]. This is how >> the parameters are handled in the loop_parameters() function which >> defines the parameter vector in all parts of relax. There might be a >> quicker way to unpack the parameters, but such an idea could be used >> for the target functions. >> >> Cheers, >> >> Edward >> >> On 6 June 2014 11:08, Troels E. Linnet <[email protected]> >> wrote: >> > URL: >> > <http://gna.org/bugs/?22146> >> > >> > Summary: Unpacking of R2A and R2B is performed wrong >> for >> > clustered "full" dispersion models >> > Project: relax >> > Submitted by: tlinnet >> > Submitted on: Fri 06 Jun 2014 09:08:58 AM UTC >> > Category: relax's source code >> > Specific analysis category: Relaxation dispersion >> > Priority: 9 - Immediate >> > Severity: 4 - Important >> > Status: None >> > Assigned to: None >> > Originator Name: >> > Originator Email: >> > Open/Closed: Open >> > Release: Repository: trunk >> > Discussion Lock: Any >> > Operating System: All systems >> > >> > _______________________________________________________ >> > >> > Details: >> > >> > The unpacking of the R2A and R2B parameters in the "full" model is >> performed >> > wrong. >> > This will happen performing a clustered analysis, using one of the >> "full" >> > models. >> > >> > This bug affect all analysis performed running with a "full" model, with >> > clustered residues. >> > >> > The bug is located in the target function: >> > ./target_functions/relax_disp.py >> > >> > For all the "func_MODEL_full", the unpacking of: >> > R20A = params[:self.end_index[0]] >> > R20B = params[self.end_index[0]:self.end_index[1]] >> > >> > This is wrong, since the "params" list, is ordered: >> > [spin, spin, spin, [dw], pA, kex], where spin = [nr_frq*r2a, nr_frq*r2b] >> > >> > This ordering happens in: >> > ./specific_analysis/relax_disp/parameters.py >> > in the loop_parameters.py >> > >> > A possible solutions i shown below. >> > This alter the unpacking of the parameters. >> > >> > An example of profiling_cr72.py is attached. >> > This can be downloaded, and run in base folder of relax: >> > ./profiling_cr72.py . >> > >> > This is with 3 frq, and 3 spins. >> > >> > The current implementations would unpack: >> > ('R20A', array([ 2., 2., 2., 4., 4., 4., 12., 12., 12.]), >> 9) >> > ('R20B', array([ 14., 14., 14., 22., 22., 22., 24., 24., 24.]), >> 9) >> > >> > R2A is 2, 12, 22 for the spins 0-3 >> > R2B is, 4, 14, 24 for the spins 0-3 >> > >> > The suggested unpacking loop, unpacks to: >> > ('R20A', array([ 2., 2., 2., 12., 12., 12., 22., 22., 22.]), >> 9) >> > ('R20B', array([ 4., 4., 4., 14., 14., 14., 24., 24., 24.]), >> 9) >> > >> > >> > ------- >> > from numpy import array, concatenate, delete, index_exp >> > import numpy >> > >> > p = array([ 1.000000000000000e+01, 1.000000000000000e+01, >> > 1.100000000000000e+01 >> > , 1.100000000000000e+01, 1.000000000000000e+01, 1.000000000000000e+01 >> > , 1.100000000000000e+01, 1.100000000000000e+01, 1.000000000000000e+00 >> > , 1.000000000000000e+00, 9.000000000000000e-01, 1.000000000000000e+03]) >> > >> > e = [4, 8, 10] >> > >> > # Now >> > r2a = p[:e[0]] >> > print r2a >> > r2b = p[e[0]:e[1]] >> > print r2b >> > dw = p[e[1]:e[2]] >> > print dw >> > pA = p[e[2]] >> > print pA >> > kex = p[e[2]+1] >> > print kex >> > >> > print "new" >> > ns = 2 >> > nf = 2 >> > >> > ml = p[:e[1]] >> > >> > R20A = array([]) >> > R20B = array([]) >> > for i in range(0, ns): >> > # Array sorted per [spin, spin, spin], where spin = [nr_frq*r2a, >> > nr_frq*r2b] >> > spin_AB = ml[:nf*2] >> > ml = delete(ml, numpy.s_[:nf*2]) >> > R20A = concatenate([R20A, spin_AB[:nf] ]) >> > R20B = concatenate([R20B, spin_AB[nf:] ]) >> > >> > print R20A >> > print R20B >> > print dw >> > print pA >> > print kex >> > >> > >> > >> > _______________________________________________________ >> > >> > File Attachments: >> > >> > >> > ------------------------------------------------------- >> > Date: Fri 06 Jun 2014 09:08:58 AM UTC Name: profiling_cr72.py Size: >> 17kB >> > By: tlinnet >> > >> > <http://gna.org/bugs/download.php?file_id=20938> >> > >> > _______________________________________________________ >> > >> > Reply to this item at: >> > >> > <http://gna.org/bugs/?22146> >> > >> > _______________________________________________ >> > Message sent via/by Gna! >> > http://gna.org/ >> > >> > >> > _______________________________________________ >> > 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 >> > > _______________________________________________ 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
