Hi, Is this fixed? How does this compare now?
Cheers, Edward On 29 August 2014 12:19, Troels Emtekær Linnet <[email protected]> wrote: > Ugh. > > This must be a weighting issue. > > I will fix it. > > Best > Troels > > 2014-08-29 12:08 GMT+02:00 Edward d'Auvergne <[email protected]>: >> I also don't understand the printout from this system test: >> >> """ >> Fitting with minfx to: 52V @N >> ----------------------------- >> >> min_algor='Newton', c_code=True, constraints=False, chi2_jacobian?=False >> ------------------------------------------------------------------------ >> >> R1rho at 799.8 MHz, for offset=118.078 ppm and dispersion point 431.0, >> with 4 time points. r2eff=8.646 r2eff_err=37.6189, i0=202664.2, >> i0_err=912343.8776, chi2=3.758. >> R1rho at 799.8 MHz, for offset=118.078 ppm and dispersion point 651.2, >> with 5 time points. r2eff=10.377 r2eff_err=17.2901, i0=206049.6, >> i0_err=145291.5784, chi2=27.291. >> R1rho at 799.8 MHz, for offset=118.078 ppm and dispersion point 800.5, >> with 5 time points. r2eff=10.506 r2eff_err=25.6159, i0=202586.3, >> i0_err=563484.3693, chi2=13.357. >> R1rho at 799.8 MHz, for offset=118.078 ppm and dispersion point 984.0, >> with 5 time points. r2eff=10.903 r2eff_err=16.0355, i0=203455.0, >> i0_err=157857.4220, chi2=33.632. >> R1rho at 799.8 MHz, for offset=118.078 ppm and dispersion point >> 1341.1, with 5 time points. r2eff=10.684 r2eff_err=16.1640, >> i0=218670.4, i0_err=143374.0758, chi2=35.818. >> R1rho at 799.8 MHz, for offset=118.078 ppm and dispersion point >> 1648.5, with 5 time points. r2eff=10.501 r2eff_err=32.8259, >> i0=206502.5, i0_err=267820.8718, chi2=7.356. >> R1rho at 799.8 MHz, for offset=124.247 ppm and dispersion point >> 1341.1, with 5 time points. r2eff=11.118 r2eff_err=22.9196, >> i0=216447.2, i0_err=202909.6970, chi2=15.587. >> R1rho at 799.8 MHz, for offset=130.416 ppm and dispersion point 800.5, >> with 5 time points. r2eff=7.866 r2eff_err=21.4617, i0=211869.7, >> i0_err=215319.4005, chi2=14.585. >> R1rho at 799.8 MHz, for offset=130.416 ppm and dispersion point >> 1341.1, with 5 time points. r2eff=9.259 r2eff_err=7.7769, i0=217703.2, >> i0_err=65512.4065, chi2=79.498. >> R1rho at 799.8 MHz, for offset=130.416 ppm and dispersion point >> 1648.5, with 5 time points. r2eff=9.565 r2eff_err=145.3091, >> i0=211988.9, i0_err=1935377.4765, chi2=0.447. >> R1rho at 799.8 MHz, for offset=142.754 ppm and dispersion point 800.5, >> with 5 time points. r2eff=3.240 r2eff_err=36.8835, i0=214417.4, >> i0_err=479401.1539, chi2=1.681. >> R1rho at 799.8 MHz, for offset=142.754 ppm and dispersion point >> 1341.1, with 5 time points. r2eff=5.084 r2eff_err=9.1163, i0=226358.7, >> i0_err=96611.2513, chi2=23.170. >> R1rho at 799.8 MHz, for offset=179.768 ppm and dispersion point >> 1341.1, with 5 time points. r2eff=2.208 r2eff_err=6.1992, i0=228620.6, >> i0_err=163754.5521, chi2=7.794. >> R1rho at 799.8 MHz, for offset=241.459 ppm and dispersion point >> 1341.1, with 5 time points. r2eff=1.711 r2eff_err=7.0183, i0=224087.5, >> i0_err=124876.2539, chi2=21.230. >> >> >> Fitting with minfx to: 52V @N >> ----------------------------- >> >> min_algor='BFGS', c_code=False, constraints=False, chi2_jacobian?=True >> ---------------------------------------------------------------------- >> >> R1rho at 799.8 MHz, for offset=118.078 ppm and dispersion point 431.0, >> with 4 time points. r2eff=8.646 r2eff_err=0.0524, i0=202664.2, >> i0_err=1239.0827, chi2=3.758. >> R1rho at 799.8 MHz, for offset=118.078 ppm and dispersion point 651.2, >> with 5 time points. r2eff=10.377 r2eff_err=0.0228, i0=206049.6, >> i0_err=178.1907, chi2=27.291. >> R1rho at 799.8 MHz, for offset=118.078 ppm and dispersion point 800.5, >> with 5 time points. r2eff=10.506 r2eff_err=0.0345, i0=202586.3, >> i0_err=705.7630, chi2=13.357. >> R1rho at 799.8 MHz, for offset=118.078 ppm and dispersion point 984.0, >> with 5 time points. r2eff=10.903 r2eff_err=0.0206, i0=203455.0, >> i0_err=186.0857, chi2=33.632. >> R1rho at 799.8 MHz, for offset=118.078 ppm and dispersion point >> 1341.1, with 5 time points. r2eff=10.684 r2eff_err=0.0198, >> i0=218670.4, i0_err=165.0420, chi2=35.818. >> R1rho at 799.8 MHz, for offset=118.078 ppm and dispersion point >> 1648.5, with 5 time points. r2eff=10.501 r2eff_err=0.0407, >> i0=206502.5, i0_err=321.3685, chi2=7.356. >> R1rho at 799.8 MHz, for offset=124.247 ppm and dispersion point >> 1341.1, with 5 time points. r2eff=11.118 r2eff_err=0.0301, >> i0=216447.2, i0_err=248.9394, chi2=15.587. >> R1rho at 799.8 MHz, for offset=130.416 ppm and dispersion point 800.5, >> with 5 time points. r2eff=7.866 r2eff_err=0.0280, i0=211869.7, >> i0_err=259.8845, chi2=14.585. >> R1rho at 799.8 MHz, for offset=130.416 ppm and dispersion point >> 1341.1, with 5 time points. r2eff=9.259 r2eff_err=0.0108, i0=217703.2, >> i0_err=88.1514, chi2=79.498. >> R1rho at 799.8 MHz, for offset=130.416 ppm and dispersion point >> 1648.5, with 5 time points. r2eff=9.565 r2eff_err=0.1630, i0=211988.9, >> i0_err=2054.6615, chi2=0.447. >> R1rho at 799.8 MHz, for offset=142.754 ppm and dispersion point 800.5, >> with 5 time points. r2eff=3.240 r2eff_err=0.0485, i0=214417.4, >> i0_err=611.7573, chi2=1.681. >> R1rho at 799.8 MHz, for offset=142.754 ppm and dispersion point >> 1341.1, with 5 time points. r2eff=5.084 r2eff_err=0.0124, i0=226358.7, >> i0_err=122.7341, chi2=23.170. >> R1rho at 799.8 MHz, for offset=179.768 ppm and dispersion point >> 1341.1, with 5 time points. r2eff=2.208 r2eff_err=0.0086, i0=228620.6, >> i0_err=219.4208, chi2=7.794. >> R1rho at 799.8 MHz, for offset=241.459 ppm and dispersion point >> 1341.1, with 5 time points. r2eff=1.711 r2eff_err=0.0101, i0=224087.5, >> i0_err=166.9081, chi2=21.230. >> """ >> >> >> Obviously the errors in the top one are too big. But I don't know >> what they should be. The bottom one has "chi2_jacobian?=True", so I >> guess that this is activating your func_exp_chi2_grad() function. >> However if you look at the code in the C module, you will see that it >> is exactly the same as the func_exp_chi2_grad() function. Therefore >> they should return identical errors. I'm quite confused as to why the >> numbers are not identical in the top and bottom printouts! >> >> Regards, >> >> Edward >> >> >> >> On 29 August 2014 11:59, Troels Emtekær Linnet <[email protected]> wrote: >>> You may want to look here: >>> >>> relax -s Relax_disp.test_estimate_r2eff_err_methods -d >>> >>> 2014-08-29 11:57 GMT+02:00 Troels Emtekær Linnet <[email protected]>: >>>> Hi Edward. >>>> >>>> There is something totally wrong with the C, Jacobian. >>>> Errors are estimated to: >>>> >>>> 37.619 17.290 25.616 16.036 16.164 32.826 22.920 21.462 7.777 145.309 >>>> 36.884 9.116 6.199 7.018 sum= 402.235 >>>> >>>> Which is much different to: >>>> 0.041 0.040 0.040 0.054 0.041 0.044 0.042 0.037 0.034 0.043 0.013 >>>> 0.018 0.007 0.010 sum= 0.462 >>>> >>>> You can see how the error estimation develops in: >>>> verify_estimate_r2eff_err_compare_mc >>>> >>>> You will see, that just 50 monte carlo simulations is better than >>>> estimating. >>>> >>>> Best >>>> Troels >>>> >>>> >>>> 2014-08-29 11:51 GMT+02:00 Edward d'Auvergne <[email protected]>: >>>>> Hi, >>>>> >>>>> I saw the results from that 'hidden' system test and was wondering >>>>> what was happening? The Jacobian of the chi-squared function should >>>>> remove the factor of 2, as it has a factor of minus two. But it also >>>>> includes the difference between the measured and back-calculated peak >>>>> intensities divided by the variance as well. So why does this >>>>> Jacobian, which is much closer to the 2000 MC simulations, not work? >>>>> I cannot understand this as it is totally illogical. If your error >>>>> estimate is closer to the real thing, then you should get closer to >>>>> the real optimisation results. >>>>> >>>>> Do you have a log file somewhere which contains the results from the >>>>> 2000 MC simulations? It might be worth creating a file which compares >>>>> this, or even more simulations, 100,000 for example, to the covariance >>>>> technique. Once the error estimate technique is functional and >>>>> debugged, then we can work out why the models are optimisating >>>>> differently. These two problems need to be separated and solved >>>>> independently, otherwise you can encounter the common yet fatal coding >>>>> problem of two opposing bugs partially cancelling out their effects. >>>>> >>>>> Regards, >>>>> >>>>> Edward >>>>> >>>>> On 29 August 2014 11:01, Troels Emtekær Linnet <[email protected]> >>>>> wrote: >>>>>> Hi Edward. >>>>>> >>>>>> Would it be possible to have both? >>>>>> >>>>>> The exponential Jacobian, and the chi2 Jacobian. >>>>>> >>>>>> My tests last night showed something weird. >>>>>> >>>>>> Using the chi2 Jacobian, the errors come closer to the ones reported >>>>>> my MC calculations. >>>>>> The direct jacobian would have double error on R2eff. >>>>>> >>>>>> But when fitting for R1rho models, using the errors from the direct >>>>>> jacobian, was much better in agreement with >>>>>> MC error fitting. >>>>>> >>>>>> The parameters from chi2 Jacobian, was worse. >>>>>> >>>>>> See verify_r1rho_kjaergaard_missing_r1() in systemtest for comparison. >>>>>> >>>>>> Look at the 'kex' parameter! >>>>>> >>>>>> # Compare values. >>>>>> if spin_id == ':52@N': >>>>>> if param == 'r1': >>>>>> if model == MODEL_NOREX: >>>>>> if r2eff_estimate == 'direct': >>>>>> self.assertAlmostEqual(value, 1.46138805) >>>>>> elif r2eff_estimate == 'MC2000': >>>>>> self.assertAlmostEqual(value, 1.46328102) >>>>>> elif r2eff_estimate == 'chi2': >>>>>> self.assertAlmostEqual(value, 1.43820629) >>>>>> elif model == MODEL_DPL94: >>>>>> if r2eff_estimate == 'direct': >>>>>> self.assertAlmostEqual(value, 1.44845742) >>>>>> elif r2eff_estimate == 'MC2000': >>>>>> self.assertAlmostEqual(value, 1.45019848) >>>>>> elif r2eff_estimate == 'chi2': >>>>>> self.assertAlmostEqual(value, 1.44666512) >>>>>> elif model == MODEL_TP02: >>>>>> if r2eff_estimate == 'direct': >>>>>> self.assertAlmostEqual(value, 1.54354392) >>>>>> elif r2eff_estimate == 'MC2000': >>>>>> self.assertAlmostEqual(value, 1.54352369) >>>>>> elif r2eff_estimate == 'chi2': >>>>>> self.assertAlmostEqual(value, 1.55964020) >>>>>> elif model == MODEL_TAP03: >>>>>> if r2eff_estimate == 'direct': >>>>>> self.assertAlmostEqual(value, 1.54356410) >>>>>> elif r2eff_estimate == 'MC2000': >>>>>> self.assertAlmostEqual(value, 1.54354367) >>>>>> elif r2eff_estimate == 'chi2': >>>>>> self.assertAlmostEqual(value, 1.55967157) >>>>>> elif model == MODEL_MP05: >>>>>> if r2eff_estimate == 'direct': >>>>>> self.assertAlmostEqual(value, 1.54356416) >>>>>> elif r2eff_estimate == 'MC2000': >>>>>> self.assertAlmostEqual(value, 1.54354372) >>>>>> elif r2eff_estimate == 'chi2': >>>>>> self.assertAlmostEqual(value, 1.55967163) >>>>>> elif model == MODEL_NS_R1RHO_2SITE: >>>>>> if r2eff_estimate == 'direct': >>>>>> self.assertAlmostEqual(value, 1.41359221, 5) >>>>>> elif r2eff_estimate == 'MC2000': >>>>>> self.assertAlmostEqual(value, 1.41321968, 5) >>>>>> elif r2eff_estimate == 'chi2': >>>>>> self.assertAlmostEqual(value, 1.36303129, 5) >>>>>> >>>>>> elif param == 'r2': >>>>>> if model == MODEL_NOREX: >>>>>> if r2eff_estimate == 'direct': >>>>>> self.assertAlmostEqual(value, 11.48392439) >>>>>> elif r2eff_estimate == 'MC2000': >>>>>> self.assertAlmostEqual(value, 11.48040934) >>>>>> elif r2eff_estimate == 'chi2': >>>>>> self.assertAlmostEqual(value, 11.47224488) >>>>>> elif model == MODEL_DPL94: >>>>>> if r2eff_estimate == 'direct': >>>>>> self.assertAlmostEqual(value, 10.15688372, 6) >>>>>> elif r2eff_estimate == 'MC2000': >>>>>> self.assertAlmostEqual(value, 10.16304887, 6) >>>>>> elif r2eff_estimate == 'chi2': >>>>>> self.assertAlmostEqual(value, 9.20037797, 6) >>>>>> elif model == MODEL_TP02: >>>>>> if r2eff_estimate == 'direct': >>>>>> self.assertAlmostEqual(value, 9.72654896, 6) >>>>>> elif r2eff_estimate == 'MC2000': >>>>>> self.assertAlmostEqual(value, 9.72772726, 6) >>>>>> elif r2eff_estimate == 'chi2': >>>>>> self.assertAlmostEqual(value, 9.53948340, 6) >>>>>> elif model == MODEL_TAP03: >>>>>> if r2eff_estimate == 'direct': >>>>>> self.assertAlmostEqual(value, 9.72641887, 6) >>>>>> elif r2eff_estimate == 'MC2000': >>>>>> self.assertAlmostEqual(value, 9.72759374, 6) >>>>>> elif r2eff_estimate == 'chi2': >>>>>> self.assertAlmostEqual(value, 9.53926913, 6) >>>>>> elif model == MODEL_MP05: >>>>>> if r2eff_estimate == 'direct': >>>>>> self.assertAlmostEqual(value, 9.72641723, 6) >>>>>> elif r2eff_estimate == 'MC2000': >>>>>> self.assertAlmostEqual(value, 9.72759220, 6) >>>>>> elif r2eff_estimate == 'chi2': >>>>>> self.assertAlmostEqual(value, 9.53926778, 6) >>>>>> elif model == MODEL_NS_R1RHO_2SITE: >>>>>> if r2eff_estimate == 'direct': >>>>>> self.assertAlmostEqual(value, 9.34531535, 5) >>>>>> elif r2eff_estimate == 'MC2000': >>>>>> self.assertAlmostEqual(value, 9.34602793, 5) >>>>>> elif r2eff_estimate == 'chi2': >>>>>> self.assertAlmostEqual(value, 9.17631409, 5) >>>>>> >>>>>> # For all other parameters. >>>>>> else: >>>>>> # Get the value. >>>>>> value = getattr(cur_spin, param) >>>>>> >>>>>> # Print value. >>>>>> print("%-10s %-6s %-6s %3.8f" % ("Parameter:", param, "Value:", value)) >>>>>> >>>>>> # Compare values. >>>>>> if spin_id == ':52@N': >>>>>> if param == 'phi_ex': >>>>>> if model == MODEL_DPL94: >>>>>> if r2eff_estimate == 'direct': >>>>>> self.assertAlmostEqual(value, 0.07599563) >>>>>> elif r2eff_estimate == 'MC2000': >>>>>> self.assertAlmostEqual(value, 0.07561937) >>>>>> elif r2eff_estimate == 'chi2': >>>>>> self.assertAlmostEqual(value, 0.12946061) >>>>>> >>>>>> elif param == 'pA': >>>>>> if model == MODEL_TP02: >>>>>> if r2eff_estimate == 'direct': >>>>>> self.assertAlmostEqual(value, 0.88827040) >>>>>> elif r2eff_estimate == 'MC2000': >>>>>> self.assertAlmostEqual(value, 0.88807487) >>>>>> elif r2eff_estimate == 'chi2': >>>>>> self.assertAlmostEqual(value, 0.87746233) >>>>>> elif model == MODEL_TAP03: >>>>>> if r2eff_estimate == 'direct': >>>>>> self.assertAlmostEqual(value, 0.88828922) >>>>>> elif r2eff_estimate == 'MC2000': >>>>>> self.assertAlmostEqual(value, 0.88809318) >>>>>> elif r2eff_estimate == 'chi2': >>>>>> self.assertAlmostEqual(value, 0.87747558) >>>>>> elif model == MODEL_MP05: >>>>>> if r2eff_estimate == 'direct': >>>>>> self.assertAlmostEqual(value, 0.88828924) >>>>>> elif r2eff_estimate == 'MC2000': >>>>>> self.assertAlmostEqual(value, 0.88809321) >>>>>> elif r2eff_estimate == 'chi2': >>>>>> self.assertAlmostEqual(value, 0.87747562) >>>>>> elif model == MODEL_NS_R1RHO_2SITE: >>>>>> if r2eff_estimate == 'direct': >>>>>> self.assertAlmostEqual(value, 0.94504369, 6) >>>>>> elif r2eff_estimate == 'MC2000': >>>>>> self.assertAlmostEqual(value, 0.94496541, 6) >>>>>> elif r2eff_estimate == 'chi2': >>>>>> self.assertAlmostEqual(value, 0.92084707, 6) >>>>>> >>>>>> elif param == 'dw': >>>>>> if model == MODEL_TP02: >>>>>> if r2eff_estimate == 'direct': >>>>>> self.assertAlmostEqual(value, 1.08875840, 6) >>>>>> elif r2eff_estimate == 'MC2000': >>>>>> self.assertAlmostEqual(value, 1.08765638, 6) >>>>>> elif r2eff_estimate == 'chi2': >>>>>> self.assertAlmostEqual(value, 1.09753230, 6) >>>>>> elif model == MODEL_TAP03: >>>>>> if r2eff_estimate == 'direct': >>>>>> self.assertAlmostEqual(value, 1.08837238, 6) >>>>>> elif r2eff_estimate == 'MC2000': >>>>>> self.assertAlmostEqual(value, 1.08726698, 6) >>>>>> elif r2eff_estimate == 'chi2': >>>>>> self.assertAlmostEqual(value, 1.09708821, 6) >>>>>> elif model == MODEL_MP05: >>>>>> if r2eff_estimate == 'direct': >>>>>> self.assertAlmostEqual(value, 1.08837241, 6) >>>>>> elif r2eff_estimate == 'MC2000': >>>>>> self.assertAlmostEqual(value, 1.08726706, 6) >>>>>> elif r2eff_estimate == 'chi2': >>>>>> self.assertAlmostEqual(value, 1.09708832, 6) >>>>>> elif model == MODEL_NS_R1RHO_2SITE: >>>>>> if r2eff_estimate == 'direct': >>>>>> self.assertAlmostEqual(value, 1.56001812, 5) >>>>>> elif r2eff_estimate == 'MC2000': >>>>>> self.assertAlmostEqual(value, 1.55833321, 5) >>>>>> elif r2eff_estimate == 'chi2': >>>>>> self.assertAlmostEqual(value, 1.36406712, 5) >>>>>> >>>>>> elif param == 'kex': >>>>>> if model == MODEL_DPL94: >>>>>> if r2eff_estimate == 'direct': >>>>>> self.assertAlmostEqual(value, 4460.43711569, 2) >>>>>> elif r2eff_estimate == 'MC2000': >>>>>> self.assertAlmostEqual(value, 4419.03917195, 2) >>>>>> elif r2eff_estimate == 'chi2': >>>>>> self.assertAlmostEqual(value, 6790.22736344, 2) >>>>>> elif model == MODEL_TP02: >>>>>> if r2eff_estimate == 'direct': >>>>>> self.assertAlmostEqual(value, 4921.28602757, 3) >>>>>> elif r2eff_estimate == 'MC2000': >>>>>> self.assertAlmostEqual(value, 4904.70144883, 3) >>>>>> elif r2eff_estimate == 'chi2': >>>>>> self.assertAlmostEqual(value, 5146.20306591, 3) >>>>>> elif model == MODEL_TAP03: >>>>>> if r2eff_estimate == 'direct': >>>>>> self.assertAlmostEqual(value, 4926.42963491, 3) >>>>>> elif r2eff_estimate == 'MC2000': >>>>>> self.assertAlmostEqual(value, 4909.86877150, 3) >>>>>> elif r2eff_estimate == 'chi2': >>>>>> self.assertAlmostEqual(value, 5152.51105814, 3) >>>>>> elif model == MODEL_MP05: >>>>>> if r2eff_estimate == 'direct': >>>>>> self.assertAlmostEqual(value, 4926.44236315, 3) >>>>>> elif r2eff_estimate == 'MC2000': >>>>>> self.assertAlmostEqual(value, 4909.88110195, 3) >>>>>> elif r2eff_estimate == 'chi2': >>>>>> self.assertAlmostEqual(value, 5152.52097111, 3) >>>>>> elif model == MODEL_NS_R1RHO_2SITE: >>>>>> if r2eff_estimate == 'direct': >>>>>> self.assertAlmostEqual(value, 5628.66061488, 2) >>>>>> elif r2eff_estimate == 'MC2000': >>>>>> self.assertAlmostEqual(value, 5610.20221435, 2) >>>>>> elif r2eff_estimate == 'chi2': >>>>>> self.assertAlmostEqual(value, 5643.34067090, 2) >>>>>> >>>>>> elif param == 'chi2': >>>>>> if model == MODEL_NOREX: >>>>>> if r2eff_estimate == 'direct': >>>>>> self.assertAlmostEqual(value, 848.42016907, 5) >>>>>> elif r2eff_estimate == 'MC2000': >>>>>> self.assertAlmostEqual(value, 3363.95829122, 5) >>>>>> elif r2eff_estimate == 'chi2': >>>>>> self.assertAlmostEqual(value, 5976.49946726, 5) >>>>>> elif model == MODEL_DPL94: >>>>>> if r2eff_estimate == 'direct': >>>>>> self.assertAlmostEqual(value, 179.47041241) >>>>>> elif r2eff_estimate == 'MC2000': >>>>>> self.assertAlmostEqual(value, 710.24767560) >>>>>> elif r2eff_estimate == 'chi2': >>>>>> self.assertAlmostEqual(value, 612.72616697, 5) >>>>>> elif model == MODEL_TP02: >>>>>> if r2eff_estimate == 'direct': >>>>>> self.assertAlmostEqual(value, 29.33882530, 6) >>>>>> elif r2eff_estimate == 'MC2000': >>>>>> self.assertAlmostEqual(value, 114.47142772, 6) >>>>>> elif r2eff_estimate == 'chi2': >>>>>> self.assertAlmostEqual(value, 250.50838162, 5) >>>>>> elif model == MODEL_TAP03: >>>>>> if r2eff_estimate == 'direct': >>>>>> self.assertAlmostEqual(value, 29.29050673, 6) >>>>>> elif r2eff_estimate == 'MC2000': >>>>>> self.assertAlmostEqual(value, 114.27987534) >>>>>> elif r2eff_estimate == 'chi2': >>>>>> self.assertAlmostEqual(value, 250.04050719, 5) >>>>>> elif model == MODEL_MP05: >>>>>> if r2eff_estimate == 'direct': >>>>>> self.assertAlmostEqual(value, 29.29054301, 6) >>>>>> elif r2eff_estimate == 'MC2000': >>>>>> self.assertAlmostEqual(value, 114.28002272) >>>>>> elif r2eff_estimate == 'chi2': >>>>>> self.assertAlmostEqual(value, 250.04077478, 5) >>>>>> elif model == MODEL_NS_R1RHO_2SITE: >>>>>> if r2eff_estimate == 'direct': >>>>>> self.assertAlmostEqual(value, 34.44010543, 6) >>>>>> elif r2eff_estimate == 'MC2000': >>>>>> self.assertAlmostEqual(value, 134.14368365) >>>>>> elif r2eff_estimate == 'chi2': >>>>>> self.assertAlmostEqual(value, 278.55121388, 5) >>>>>> >>>>>> 2014-08-29 9:49 GMT+02:00 Edward d'Auvergne <[email protected]>: >>>>>>> Hi Troels, >>>>>>> >>>>>>> I've now converted the target_functions.relax_fit.jacobian() function >>>>>>> to be the Jacobian of the chi-squared function rather than the >>>>>>> Jacobian of the exponential function. This should match your >>>>>>> specific_analyses.relax_disp.estimate_r2eff.func_exp_chi2_grad() >>>>>>> function. I mixed up the two because the Levenberg-Marquardt >>>>>>> algorithm in minfx requires the Jacobian of the exponential, and it's >>>>>>> been 8 years since I last derived and implemented a Jacobian. >>>>>>> >>>>>>> Regards, >>>>>>> >>>>>>> Edward >>>>>>> >>>>>>> >>>>>>> >>>>>>> On 28 August 2014 21:43, <[email protected]> wrote: >>>>>>>> Author: tlinnet >>>>>>>> Date: Thu Aug 28 21:43:13 2014 >>>>>>>> New Revision: 25411 >>>>>>>> >>>>>>>> URL: http://svn.gna.org/viewcvs/relax?rev=25411&view=rev >>>>>>>> Log: >>>>>>>> Reverted the logic, that the chi2 Jacobian should be used. >>>>>>>> >>>>>>>> Instead, the direct Jacobian exponential is used instead. >>>>>>>> >>>>>>>> When fitting with the estimated errors from the Direct Jacobian, the >>>>>>>> results are MUCH better, and comparable >>>>>>>> to 2000 Monte-Carlo simulations. >>>>>>>> >>>>>>>> task #7822(https://gna.org/task/index.php?7822): Implement user >>>>>>>> function to estimate R2eff and associated errors for exponential curve >>>>>>>> fitting. >>>>>>>> >>>>>>>> Modified: >>>>>>>> trunk/specific_analyses/relax_disp/estimate_r2eff.py >>>>>>>> trunk/test_suite/system_tests/relax_disp.py >>>>>>>> trunk/user_functions/relax_disp.py >>>>>>>> >>>>>>>> Modified: trunk/specific_analyses/relax_disp/estimate_r2eff.py >>>>>>>> URL: >>>>>>>> http://svn.gna.org/viewcvs/relax/trunk/specific_analyses/relax_disp/estimate_r2eff.py?rev=25411&r1=25410&r2=25411&view=diff >>>>>>>> ============================================================================== >>>>>>>> --- trunk/specific_analyses/relax_disp/estimate_r2eff.py >>>>>>>> (original) >>>>>>>> +++ trunk/specific_analyses/relax_disp/estimate_r2eff.py Thu >>>>>>>> Aug 28 21:43:13 2014 >>>>>>>> @@ -90,7 +90,7 @@ >>>>>>>> return jacobian_matrix_exp_chi2 >>>>>>>> >>>>>>>> >>>>>>>> -def estimate_r2eff_err(chi2_jacobian=True, spin_id=None, epsrel=0.0, >>>>>>>> verbosity=1): >>>>>>>> +def estimate_r2eff_err(chi2_jacobian=False, spin_id=None, epsrel=0.0, >>>>>>>> verbosity=1): >>>>>>>> """This will estimate the R2eff and i0 errors from the covariance >>>>>>>> matrix Qxx. Qxx is calculated from the Jacobian matrix and the >>>>>>>> optimised parameters. >>>>>>>> >>>>>>>> @keyword chi2_jacobian: If the Jacobian derived from the chi2 >>>>>>>> function, should be used instead of the Jacobian from the exponential >>>>>>>> function. >>>>>>>> >>>>>>>> Modified: trunk/test_suite/system_tests/relax_disp.py >>>>>>>> URL: >>>>>>>> http://svn.gna.org/viewcvs/relax/trunk/test_suite/system_tests/relax_disp.py?rev=25411&r1=25410&r2=25411&view=diff >>>>>>>> ============================================================================== >>>>>>>> --- trunk/test_suite/system_tests/relax_disp.py (original) >>>>>>>> +++ trunk/test_suite/system_tests/relax_disp.py Thu Aug 28 21:43:13 >>>>>>>> 2014 >>>>>>>> @@ -2744,13 +2744,13 @@ >>>>>>>> self.interpreter.minimise.execute(min_algor='Newton', >>>>>>>> constraints=False, verbosity=1) >>>>>>>> >>>>>>>> # Estimate R2eff errors. >>>>>>>> - >>>>>>>> self.interpreter.relax_disp.r2eff_err_estimate(chi2_jacobian=False) >>>>>>>> + >>>>>>>> self.interpreter.relax_disp.r2eff_err_estimate(chi2_jacobian=True) >>>>>>>> >>>>>>>> # Run the analysis. >>>>>>>> relax_disp.Relax_disp(pipe_name=ds.pipe_name, >>>>>>>> pipe_bundle=ds.pipe_bundle, results_dir=result_dir_name, >>>>>>>> models=MODELS, grid_inc=GRID_INC, mc_sim_num=MC_NUM, modsel=MODSEL) >>>>>>>> >>>>>>>> # Verify the data. >>>>>>>> - self.verify_r1rho_kjaergaard_missing_r1(models=MODELS, >>>>>>>> result_dir_name=result_dir_name, r2eff_estimate='direct') >>>>>>>> + self.verify_r1rho_kjaergaard_missing_r1(models=MODELS, >>>>>>>> result_dir_name=result_dir_name, r2eff_estimate='chi2') >>>>>>>> >>>>>>>> >>>>>>>> def test_estimate_r2eff_err_auto(self): >>>>>>>> @@ -2849,7 +2849,7 @@ >>>>>>>> relax_disp.Relax_disp(pipe_name=pipe_name, >>>>>>>> pipe_bundle=pipe_bundle, results_dir=result_dir_name, models=MODELS, >>>>>>>> grid_inc=GRID_INC, mc_sim_num=MC_NUM, exp_mc_sim_num=EXP_MC_NUM, >>>>>>>> modsel=MODSEL, r1_fit=r1_fit) >>>>>>>> >>>>>>>> # Verify the data. >>>>>>>> - self.verify_r1rho_kjaergaard_missing_r1(models=MODELS, >>>>>>>> result_dir_name=result_dir_name, r2eff_estimate='chi2') >>>>>>>> + self.verify_r1rho_kjaergaard_missing_r1(models=MODELS, >>>>>>>> result_dir_name=result_dir_name, r2eff_estimate='direct') >>>>>>>> >>>>>>>> >>>>>>>> def test_estimate_r2eff_err_methods(self): >>>>>>>> >>>>>>>> Modified: trunk/user_functions/relax_disp.py >>>>>>>> URL: >>>>>>>> http://svn.gna.org/viewcvs/relax/trunk/user_functions/relax_disp.py?rev=25411&r1=25410&r2=25411&view=diff >>>>>>>> ============================================================================== >>>>>>>> --- trunk/user_functions/relax_disp.py (original) >>>>>>>> +++ trunk/user_functions/relax_disp.py Thu Aug 28 21:43:13 2014 >>>>>>>> @@ -636,7 +636,7 @@ >>>>>>>> uf.title_short = "Estimate R2eff errors." >>>>>>>> uf.add_keyarg( >>>>>>>> name = "chi2_jacobian", >>>>>>>> - default = True, >>>>>>>> + default = False, >>>>>>>> py_type = "bool", >>>>>>>> desc_short = "use of chi2 Jacobian", >>>>>>>> desc = "If the Jacobian derived from the chi2 function, should be >>>>>>>> used instead of the Jacobian from the exponential function." >>>>>>>> >>>>>>>> >>>>>>>> _______________________________________________ >>>>>>>> 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 _______________________________________________ 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
