TsRegressionPreventer::SetResult:
  adjusted: true
  havePreSegment: true
  preActiveAdjusted: false
  preActiveAdjustedWidth: 1.300000
  preOppositeAdjusted: true
  preOppositeAdjustedWidth: 0.530268
  havePostSegment: false
  postActiveAdjusted: false
  postActiveAdjustedWidth: 0.000000
  postOppositeAdjusted: false
  postOppositeAdjustedWidth: 0.000000
-----
Spline:
  hermite false
  preExtrap Held
  postExtrap Held
Knots:
  0.000000: 0.000000, Curve, preSlope 0.000000, postSlope 0.000000, preLen 0.000000, postLen 0.530268, auto false / false
  1.000000: 1.000000, Curve, preSlope 0.000000, postSlope 0.000000, preLen 1.300000, postLen 0.000000, auto false / false
-----
Ts.TsTest_SplineData(isHermite = False, preExtrapolation = Ts.TsTest_SplineData.Extrapolation(method = Ts.TsTest_SplineData.ExtrapHeld), postExtrapolation = Ts.TsTest_SplineData.Extrapolation(method = Ts.TsTest_SplineData.ExtrapHeld), knots = [Ts.TsTest_SplineData.Knot(time = float.fromhex('0x0p+0'), nextSegInterpMethod = Ts.TsTest_SplineData.InterpCurve, value = float.fromhex('0x0p+0'), preSlope = float.fromhex('0x0p+0'), postSlope = float.fromhex('0x0p+0'), preLen = float.fromhex('0x0p+0'), postLen = float.fromhex('0x1.0f7f3ae9122b3p-1'), preAuto = False, postAuto = False), Ts.TsTest_SplineData.Knot(time = float.fromhex('0x1p+0'), nextSegInterpMethod = Ts.TsTest_SplineData.InterpCurve, value = float.fromhex('0x1p+0'), preSlope = float.fromhex('0x0p+0'), postSlope = float.fromhex('0x0p+0'), preLen = float.fromhex('0x1.4cccccccccccdp+0'), postLen = float.fromhex('0x0p+0'), preAuto = False, postAuto = False)])
-----
-0.200000 0.000000
0.000000 0.000000
0.004975 0.000030
0.009950 0.000121
0.014925 0.000276
0.019900 0.000498
0.024876 0.000789
0.029851 0.001155
0.034826 0.001597
0.039801 0.002120
0.044776 0.002728
0.049751 0.003426
0.054726 0.004219
0.059701 0.005111
0.064677 0.006110
0.069652 0.007222
0.074627 0.008453
0.079602 0.009812
0.084577 0.011307
0.089552 0.012949
0.094527 0.014747
0.099502 0.016715
0.104478 0.018866
0.109453 0.021216
0.114428 0.023782
0.119403 0.026586
0.124378 0.029650
0.129353 0.033003
0.134328 0.036677
0.139303 0.040712
0.144279 0.045153
0.149254 0.050058
0.154229 0.055500
0.159204 0.061567
0.164179 0.068377
0.169154 0.076085
0.174129 0.084906
0.179104 0.095147
0.184080 0.107279
0.189055 0.122050
0.194030 0.140801
0.199005 0.166004
0.203980 0.213550
0.208955 0.464854
0.213930 0.526064
0.218905 0.562318
0.223881 0.589479
0.228856 0.611618
0.233831 0.630489
0.238806 0.647029
0.243781 0.661806
0.248756 0.675192
0.253731 0.687449
0.258706 0.698766
0.263682 0.709284
0.268657 0.719116
0.273632 0.728350
0.278607 0.736694
0.283582 0.745053
0.288557 0.752947
0.293532 0.760434
0.298507 0.767558
0.303483 0.774356
0.308458 0.780856
0.313433 0.787085
0.318408 0.793063
0.323383 0.798811
0.328358 0.804343
0.333333 0.809674
0.338308 0.814818
0.343284 0.819786
0.348259 0.824588
0.353234 0.829234
0.358209 0.833733
0.363184 0.838091
0.368159 0.842317
0.373134 0.846416
0.378109 0.850395
0.383085 0.854260
0.388060 0.858016
0.393035 0.861667
0.398010 0.865218
0.402985 0.868674
0.407960 0.872037
0.412935 0.875312
0.417910 0.878503
0.422886 0.881611
0.427861 0.884641
0.432836 0.887596
0.437811 0.890477
0.442786 0.893288
0.447761 0.896030
0.452736 0.898706
0.457711 0.901319
0.462687 0.903870
0.467662 0.906361
0.472637 0.908793
0.477612 0.911170
0.482587 0.913492
0.487562 0.915761
0.492537 0.917978
0.497512 0.920145
0.502488 0.922264
0.507463 0.924335
0.512438 0.926360
0.517413 0.928340
0.522388 0.930276
0.527363 0.932170
0.532338 0.934021
0.537313 0.935832
0.542289 0.937604
0.547264 0.939337
0.552239 0.941032
0.557214 0.942690
0.562189 0.944312
0.567164 0.945898
0.572139 0.947450
0.577114 0.948969
0.582090 0.950454
0.587065 0.951907
0.592040 0.953329
0.597015 0.954719
0.601990 0.956079
0.606965 0.957410
0.611940 0.958711
0.616915 0.959983
0.621891 0.961228
0.626866 0.962445
0.631841 0.963635
0.636816 0.964799
0.641791 0.965936
0.646766 0.967048
0.651741 0.968135
0.656716 0.969198
0.661692 0.970236
0.666667 0.971250
0.671642 0.972242
0.676617 0.973210
0.681592 0.974156
0.686567 0.975079
0.691542 0.975981
0.696517 0.976861
0.701493 0.977721
0.706468 0.978559
0.711443 0.979377
0.716418 0.980175
0.721393 0.980953
0.726368 0.981712
0.731343 0.982451
0.736318 0.983172
0.741294 0.983874
0.746269 0.984558
0.751244 0.985223
0.756219 0.985871
0.761194 0.986501
0.766169 0.987114
0.771144 0.987710
0.776119 0.988289
0.781095 0.988851
0.786070 0.989397
0.791045 0.989927
0.796020 0.990441
0.800995 0.990940
0.805970 0.991423
0.810945 0.991890
0.815920 0.992343
0.820896 0.992781
0.825871 0.993204
0.830846 0.993612
0.835821 0.994006
0.840796 0.994386
0.845771 0.994752
0.850746 0.995105
0.855721 0.995443
0.860697 0.995769
0.865672 0.996081
0.870647 0.996380
0.875622 0.996665
0.880597 0.996938
0.885572 0.997199
0.890547 0.997447
0.895522 0.997682
0.900498 0.997905
0.905473 0.998117
0.910448 0.998316
0.915423 0.998503
0.920398 0.998679
0.925373 0.998843
0.930348 0.998996
0.935323 0.999137
0.940299 0.999267
0.945274 0.999387
0.950249 0.999495
0.955224 0.999592
0.960199 0.999679
0.965174 0.999755
0.970149 0.999821
0.975124 0.999876
0.980100 0.999921
0.985075 0.999956
1.000000 1.000000
1.200000 1.000000
