Re: r23908 - /branches/disp_spin_speed/target_functions/relax_disp.pyRe: r23908 - /branches/disp_spin_speed/target_functions/relax_disp.pyCan one profile the systemtests ? Best Troels 2014-06-13 10:56 GMT+02:00 Edward d'Auvergne <edward@xxxxxxxxxxxxx>:
For me the system tests are not much faster compared to trunk. Now at r23912, the disp_spin_speed branch takes ~216 seconds for all Relax_disp system tests. But for the trunk it is ~233 seconds. From your profiling script it's pretty clear though that there are insane speed ups happening, but it's not reflected so much in the system tests. It might be interesting to see what is causing these system tests to take so long - it's clear that it's not the target functions. Regards, Edward On 13 June 2014 10:46, Troels Emtekær Linnet <tlinnet@xxxxxxxxxxxxx> wrote:Yeahaa! I realised, that if I wanted to have the systemtests go faster, I should kill this one. It is nice to see, that systemtest suite just runs faster and faster, the more models i kill. 2014-06-13 10:37 GMT+02:00 Edward d'Auvergne <edward@xxxxxxxxxxxxx>:Now this code might be too fast for the user - they may not be fast enough to even see it in the log files ;) Regards, Edward On 13 June 2014 10:10, <tlinnet@xxxxxxxxxxxxx> wrote:Author: tlinnet Date: Fri Jun 13 10:10:04 2014 New Revision: 23908 URL: http://svn.gna.org/viewcvs/relax?rev=23908&view=rev Log: Made the NOREX model af faster numpy array calculation. Task #7807 (https://gna.org/task/index.php?7807): Speed-up ofdispersionmodels 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=23908&r1=23907&r2=23908&view=diff==============================================================================--- branches/disp_spin_speed/target_functions/relax_disp.py (original) +++ branches/disp_spin_speed/target_functions/relax_disp.py FriJun13 10:10:04 2014 @@ -394,8 +394,11 @@ if model == MODEL_NS_MMQ_3SITE_LINEAR: self.func = self.func_ns_mmq_3site_linear + # Setup special numpy array structures, for higherdimensionalcomputation. - if model in [MODEL_B14, MODEL_B14_FULL, MODEL_CR72, MODEL_CR72_FULL, MODEL_DPL94, MODEL_TAP03, MODEL_TP02, MODEL_TSMFK01]: + test_models = [MODEL_B14, MODEL_B14_FULL, MODEL_CR72, MODEL_CR72_FULL, MODEL_DPL94, MODEL_TAP03, MODEL_TP02, MODEL_TSMFK01] + + if model in test_models + [MODEL_NOREX]: # 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]. @@ -443,8 +446,11 @@ self.r20b_struct = deepcopy(zeros_a) self.dw_struct = deepcopy(zeros_a) - # Extract the frequencies to numpy array. - self.frqs_a = multiply.outer( asarray(self.frqs).reshape(self.NE, self.NS, self.NM),self.no_nd_struct )+ # Setup special numpy array structures, for higherdimensionalcomputation. + if model in test_models + [MODEL_NOREX]: + if model in test_models: + # Extract the frequencies to numpy array. + self.frqs_a = multiply.outer( asarray(self.frqs).reshape(self.NE, self.NS, self.NM),self.no_nd_struct )if model in MODEL_LIST_CPMG_FULL: self.cpmg_frqs_a = deepcopy(ones_a) @@ -476,7 +482,7 @@ # Extract number of dispersion points. num_disp_points = self.num_disp_points[ei][si][mi][oi] - if model in MODEL_LIST_CPMG_FULL: + if model in MODEL_LIST_CPMG_FULL andmodel!= MODEL_NOREX: # Extract cpmg_frqs andnum_disp_pointsfrom 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] @@ -497,7 +503,7 @@ 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] # For R1rho data. - if model in MODEL_LIST_R1RHO_FULL: + if model in MODEL_LIST_R1RHO_FULL and model != MODEL_NOREX: self.disp_struct[ei][si][mi][oi][di] = 1.0 # Extract the frequencies tonumpyarray. @@ -511,11 +517,12 @@ else: self.num_disp_points_a[ei][si][mi][oi][di] = 0 + if model in test_models: + # Pre calculate frqs structure + self.frqs_struct = self.frqs_a * self.disp_struct + # Make copy of values structure. self.back_calc_a = deepcopy(self.values_a) - - # Pre calculate frqs structure - self.frqs_struct = self.frqs_a * self.disp_struct # Find the numpy mask, which tells where values should be replaced. self.mask_replace_blank = masked_equal(missing_a, 1.0) @@ -1465,34 +1472,16 @@ # Unpack the parameter values. R20 = params - # Initialise. - chi2_sum = 0.0 - - # 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): - # The R20 index. - r20_index = mi + si*self.num_frq - - # Loop over the offsets. - for oi in range(self.num_offsets[ei][si][mi]): - # The R2eff values as R20 values. - for di in range(self.num_disp_points[ei][si][mi][oi]): - self.back_calc[ei][si][mi][oi][di] = R20[r20_index] - - # For all missing data points, set the back-calculated value to the measured values so that it has no effecton thechi-squared value. - for di in range(self.num_disp_points[ei][si][mi][oi]): - if self.missing[ei][si][mi][oi][di]: - self.back_calc[ei][si][mi][oi][di] = self.values[ei][si][mi][oi][di] - - # Calculate and return the chi-squared value. - chi2_sum += chi2(self.values[ei][si][mi][oi], self.back_calc[ei][si][mi][oi], self.errors[ei][si][mi][oi]) + # Reshape R20 to per experiment, spin and frequency. + self.back_calc_a[:] = multiply.outer( R20.reshape(self.NE, self.NS, self.NM), self.no_nd_struct ) + + ## For all missing data points, set the back-calculated value to the measured values so that it has no effect on the chi-squaredvalue.+ 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) def func_ns_cpmg_2site_3D(self, params): _______________________________________________ relax (http://www.nmr-relax.com) This is the relax-commits mailing list relax-commits@xxxxxxx 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 relax-devel@xxxxxxx 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