====================================================================== Hybrid Preisach SL_sign Prediction Accuracy Report ====================================================================== Generated: 2026-09-30 15:59:11 Model type: Hybrid constrained discrete scalar Preisach model (adaptive differentiable mesh) for signed integrated gradient SL_sign Training runs: [10 11 12 13 14 15 16 17 18] Prediction runs: [19 20 21 22] Current channel: Imag(:,1) Training-current range: [-3.0006, 3.00804] A Full-scale SL_sign: 0.516632 T Threshold levels: 29 Number of relays: 435 Reversible order: 3 Ridge lambda: 0.001 Smoothness lambda: 0.01 Adaptive refinement: true Final train RMSE: 0.00317508 T Nonnegative relays: true Sigma weighting used: true Target absolute error: 0.000516632 T ---------------------------------------------------------------------- WARNING ---------------------------------------------------------------------- Relative/percent error becomes misleading near SL_sign = 0. Use AbsoluteError (tesla) for accuracy near zero integrated gradient. ====================================================================== TRAINING RUN SUMMARY (errors in T) ====================================================================== Run N_points RMSE[T] MAE[T] MAPE[%] 10 21 0.00370184 0.00309691 0.800871 11 20 0.0028523 0.00212994 0.712929 12 22 0.00158141 0.00117758 0.612069 13 21 0.00247566 0.0022239 5.85729 14 21 0.00240433 0.00218044 17.7023 15 21 0.00228835 0.0018453 5.73889 16 21 0.00205254 0.00123677 0.686839 17 21 0.00407951 0.00134572 0.445175 18 21 0.00535322 0.00173175 0.420391 ====================================================================== PREDICTION RUN SUMMARY (errors in T) ====================================================================== ---------------------------------------------------------------------- Prediction run 19 ---------------------------------------------------------------------- Valid comparison points: 15 RMSE [T]: 0.0023406 MAE [T]: 0.00187182 MAPE [%]: 1.30363 Median abs rel error [%]: 1.14981 P95 abs rel error [%]: 2.88812 Max abs rel error [%]: 2.92237 P95 absolute error [T]: 0.00481806 Max absolute error [T]: 0.00492851 Target absolute error [T]: 0.000516632 Number passing: 2 Number of valid points: 15 Pass fraction [%]: 13.33 All points pass: false ---------------------------------------------------------------------- Prediction run 20 ---------------------------------------------------------------------- Valid comparison points: 15 RMSE [T]: 0.00229537 MAE [T]: 0.00203184 MAPE [%]: 14.7953 Median abs rel error [%]: 4.16126 P95 abs rel error [%]: 111.668 Max abs rel error [%]: 141.552 P95 absolute error [T]: 0.00340152 Max absolute error [T]: 0.00342071 Target absolute error [T]: 0.000516632 Number passing: 2 Number of valid points: 15 Pass fraction [%]: 13.33 All points pass: false ---------------------------------------------------------------------- Prediction run 21 ---------------------------------------------------------------------- Valid comparison points: 15 RMSE [T]: 0.00533089 MAE [T]: 0.0023723 MAPE [%]: 0.735368 Median abs rel error [%]: 0.327585 P95 abs rel error [%]: 4.72957 Max abs rel error [%]: 6.02498 P95 absolute error [T]: 0.0157498 Max absolute error [T]: 0.0200691 Target absolute error [T]: 0.000516632 Number passing: 2 Number of valid points: 15 Pass fraction [%]: 13.33 All points pass: false ---------------------------------------------------------------------- Prediction run 22 ---------------------------------------------------------------------- Valid comparison points: 15 RMSE [T]: 0.00268431 MAE [T]: 0.00194224 MAPE [%]: 1.19729 Median abs rel error [%]: 0.362932 P95 abs rel error [%]: 5.95145 Max abs rel error [%]: 6.84203 P95 absolute error [T]: 0.00568696 Max absolute error [T]: 0.00590639 Target absolute error [T]: 0.000516632 Number passing: 5 Number of valid points: 15 Pass fraction [%]: 33.33 All points pass: false ====================================================================== POINT-BY-POINT PREDICTION TABLES ====================================================================== ---------------------------------------------------------------------- Prediction run 19 point-by-point results ---------------------------------------------------------------------- Time Imag[A] SLsign_meas[T] SLsign_pred[T] residual[G] abs_error[G] rel_error[%] 0 -0.87045 -0.153207 -0.154969 17.6159 17.6159 -1.14981 2.17 -0.82083 -0.145042 -0.145576 5.33962 5.33962 -0.368143 4.33 -1.0993 -0.188031 -0.192518 44.8671 44.8671 -2.38615 6.5 -1.1246 -0.191856 -0.196785 49.2851 49.2851 -2.56885 8.7 -0.506949 -0.0918827 -0.0891975 -26.8516 26.8516 2.92237 10.9 -1.457 -0.249816 -0.249351 -4.64225 4.64225 0.185827 13.1 -0.609136 -0.109075 -0.106384 -26.9124 26.9124 2.46732 15.27 -0.584137 -0.105106 -0.102179 -29.276 29.276 2.78537 17.45 -0.698314 -0.122027 -0.121391 -6.35845 6.35845 0.52107 19.63 -1.39668 -0.238955 -0.239161 2.05952 2.05952 -0.0861885 21.82 -1.23351 -0.210063 -0.211609 15.4575 15.4575 -0.735849 23.97 -1.16746 -0.199904 -0.200462 5.57705 5.57705 -0.278987 26.15 -0.814933 -0.142819 -0.141028 -17.9089 17.9089 1.25396 28.33 -1.35854 -0.231871 -0.23272 8.48849 8.48849 -0.366087 30.53 -0.77418 -0.136177 -0.134164 -20.1326 20.1326 1.47841 ---------------------------------------------------------------------- Prediction run 20 point-by-point results ---------------------------------------------------------------------- Time Imag[A] SLsign_meas[T] SLsign_pred[T] residual[G] abs_error[G] rel_error[%] 0 -0.466622 -0.0848787 -0.0870064 21.277 21.277 -2.50676 2.18 0.189444 0.0269898 0.0291638 -21.7404 21.7404 -8.05505 4.35 -0.001791 -0.002778 -0.00285384 0.75843 0.75843 -2.73013 6.53 0.339738 0.0523071 0.054293 -19.8585 19.8585 -3.79652 8.7 0.270593 0.041955 0.0427357 -7.80661 7.80661 -1.86071 10.87 0.489267 0.0776762 0.0809085 -32.3231 32.3231 -4.16126 13.03 0.475679 0.0757199 0.0786407 -29.2076 29.2076 -3.85732 15.23 -0.193716 -0.0315649 -0.0333877 18.2279 18.2279 -5.77474 17.4 0.243303 0.0372169 0.0398181 -26.0116 26.0116 -6.9892 19.6 -0.357474 -0.058565 -0.0608788 23.1383 23.1383 -3.95087 21.77 -0.558507 -0.0919516 -0.0946683 27.1666 27.1666 -2.95444 23.97 0.298164 0.0456464 0.0489904 -33.4396 33.4396 -7.3258 26.15 0.004911 0.0002057 -8.54729e-05 2.91173 2.91173 141.552 28.32 -0.0167445 -0.0030438 -0.00371393 6.70125 6.70125 -22.0161 30.5 0.490895 0.0777594 0.0811801 -34.2071 34.2071 -4.39909 ---------------------------------------------------------------------- Prediction run 21 point-by-point results ---------------------------------------------------------------------- Time Imag[A] SLsign_meas[T] SLsign_pred[T] residual[G] abs_error[G] rel_error[%] 0 1.93712 0.333098 0.313029 200.691 200.691 6.02498 2.15 1.94617 0.334573 0.335163 -5.90051 5.90051 -0.176359 4.33 2.23706 0.385194 0.383932 12.6184 12.6184 0.327585 6.5 2.17891 0.376301 0.374407 18.9442 18.9442 0.503432 8.67 1.89794 0.331072 0.32828 27.9195 27.9195 0.843307 10.85 1.42552 0.250742 0.249174 15.6813 15.6813 0.625396 21.18 1.48647 0.260372 0.259249 11.2281 11.2281 0.431234 23.38 2.26946 0.390524 0.390214 3.09515 3.09515 0.0792562 25.58 1.23993 0.215773 0.215136 6.3649 6.3649 0.294982 27.77 1.79375 0.310796 0.310141 6.55677 6.55677 0.210967 29.95 1.40685 0.247707 0.24604 16.6762 16.6762 0.67322 32.15 2.37998 0.409584 0.410931 -13.4638 13.4638 -0.328719 34.33 2.06076 0.359155 0.358646 5.08798 5.08798 0.141665 36.5 1.80596 0.317291 0.316762 5.288 5.288 0.166661 38.67 1.77441 0.3122 0.311567 6.32998 6.32998 0.202754 ---------------------------------------------------------------------- Prediction run 22 point-by-point results ---------------------------------------------------------------------- Time Imag[A] SLsign_meas[T] SLsign_pred[T] residual[G] abs_error[G] rel_error[%] 0 -2.20308 -0.385187 -0.380158 -50.2866 50.2866 1.30551 2.38 2.6594 0.457794 0.458028 -2.33772 2.33772 -0.0510647 4.55 2.73624 0.470695 0.470531 1.63553 1.63553 0.0347471 6.82 0.458316 0.0850348 0.0822459 27.889 27.889 3.27971 9.12 -2.63551 -0.451677 -0.452125 4.48117 4.48117 -0.0992118 11.33 -1.58502 -0.278974 -0.274277 -46.9697 46.9697 1.68365 13.53 -0.874164 -0.153212 -0.15371 4.9789 4.9789 -0.324968 15.82 1.93461 0.332805 0.332384 4.20753 4.20753 0.126426 18.22 -2.90156 -0.496169 -0.497225 10.5587 10.5587 -0.212804 20.38 -2.73577 -0.470829 -0.46912 -17.0879 17.0879 0.362932 22.58 -1.98017 -0.347025 -0.341118 -59.0639 59.0639 1.70201 24.87 0.902107 0.148217 0.150007 -17.9004 17.9004 -1.20772 27.05 1.39776 0.236727 0.236017 7.10132 7.10132 0.299979 29.23 0.894006 0.152708 0.152057 6.5136 6.5136 0.42654 31.45 -0.287525 -0.0443205 -0.0473529 30.3242 30.3242 -6.84203 ====================================================================== End of report ======================================================================