TsRegressionPreventer::SetResult:
  adjusted: true
  havePreSegment: false
  preActiveAdjusted: false
  preActiveAdjustedWidth: 0.000000
  preOppositeAdjusted: false
  preOppositeAdjustedWidth: 0.000000
  havePostSegment: true
  postActiveAdjusted: true
  postActiveAdjustedWidth: 0.599994
  postOppositeAdjusted: true
  postOppositeAdjustedWidth: 0.599994
-----
Spline:
  hermite false
  preExtrap Held
  postExtrap Held
Knots:
  0.400000: 0.000000, Curve, preSlope 0.000000, postSlope 0.000000, preLen 0.000000, postLen 0.599994, auto false / false
  1.000000: 1.000000, Curve, preSlope 0.000000, postSlope 0.000000, preLen 0.599994, 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('0x1.999999999999ap-2'), 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('0x1.333269df97aabp-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('0x1.333269df97aabp-1'), postLen = float.fromhex('0x0p+0'), preAuto = False, postAuto = False)])
-----
0.280000 0.000000
0.400000 0.000000
0.402985 0.000008
0.405970 0.000033
0.408955 0.000076
0.411940 0.000135
0.414925 0.000212
0.417910 0.000307
0.420896 0.000421
0.423881 0.000553
0.426866 0.000704
0.429851 0.000874
0.432836 0.001064
0.435821 0.001274
0.438806 0.001504
0.441791 0.001755
0.444776 0.002028
0.447761 0.002322
0.450746 0.002637
0.453731 0.002976
0.456716 0.003337
0.459701 0.003722
0.462687 0.004131
0.465672 0.004564
0.468657 0.005022
0.471642 0.005505
0.474627 0.006015
0.477612 0.006550
0.480597 0.007114
0.483582 0.007705
0.486567 0.008324
0.489552 0.008972
0.492537 0.009651
0.495522 0.010360
0.498507 0.011100
0.501493 0.011872
0.504478 0.012677
0.507463 0.013515
0.510448 0.014389
0.513433 0.015297
0.516418 0.016242
0.519403 0.017225
0.522388 0.018246
0.525373 0.019307
0.528358 0.020408
0.531343 0.021551
0.534328 0.022737
0.537313 0.023967
0.540299 0.025244
0.543284 0.026567
0.546269 0.027940
0.549254 0.029362
0.552239 0.030836
0.555224 0.032364
0.558209 0.033948
0.561194 0.035590
0.564179 0.037291
0.567164 0.039053
0.570149 0.040880
0.573134 0.042774
0.576119 0.044737
0.579104 0.046772
0.582090 0.048882
0.585075 0.051070
0.588060 0.053340
0.591045 0.055695
0.594030 0.058140
0.597015 0.060678
0.600000 0.063314
0.602985 0.066054
0.605970 0.068901
0.608955 0.071863
0.611940 0.074945
0.614925 0.078155
0.617910 0.081499
0.620896 0.084986
0.623881 0.088627
0.626866 0.092428
0.629851 0.096404
0.632836 0.100567
0.635821 0.104928
0.638806 0.109506
0.641791 0.114317
0.644776 0.119383
0.647761 0.124725
0.650746 0.130372
0.653731 0.136356
0.656716 0.142712
0.659701 0.149487
0.662687 0.156732
0.665672 0.164515
0.668657 0.172918
0.671642 0.182049
0.674627 0.192049
0.677612 0.203118
0.680597 0.215547
0.683582 0.229801
0.686567 0.246693
0.689552 0.267826
0.692537 0.296847
0.695522 0.343289
0.698507 0.431558
0.701493 0.568442
0.704478 0.656711
0.707463 0.703153
0.710448 0.732174
0.713433 0.753307
0.716418 0.770199
0.719403 0.784453
0.722388 0.796882
0.725373 0.807951
0.728358 0.817951
0.731343 0.827082
0.734328 0.835485
0.737313 0.843268
0.740299 0.850513
0.743284 0.857288
0.746269 0.863644
0.749254 0.869628
0.752239 0.875275
0.755224 0.880617
0.758209 0.885683
0.761194 0.890494
0.764179 0.895072
0.767164 0.899433
0.770149 0.903596
0.773134 0.907572
0.776119 0.911373
0.779104 0.915014
0.782090 0.918501
0.785075 0.921845
0.788060 0.925055
0.791045 0.928137
0.794030 0.931099
0.797015 0.933946
0.800000 0.936686
0.802985 0.939322
0.805970 0.941860
0.808955 0.944305
0.811940 0.946660
0.814925 0.948930
0.817910 0.951118
0.820896 0.953228
0.823881 0.955263
0.826866 0.957226
0.829851 0.959120
0.832836 0.960947
0.835821 0.962709
0.838806 0.964410
0.841791 0.966052
0.844776 0.967636
0.847761 0.969164
0.850746 0.970638
0.853731 0.972060
0.856716 0.973433
0.859701 0.974756
0.862687 0.976033
0.865672 0.977263
0.868657 0.978449
0.871642 0.979592
0.874627 0.980693
0.877612 0.981754
0.880597 0.982775
0.883582 0.983758
0.886567 0.984703
0.889552 0.985611
0.892537 0.986485
0.895522 0.987323
0.898507 0.988128
0.901493 0.988900
0.904478 0.989640
0.907463 0.990349
0.910448 0.991028
0.913433 0.991676
0.916418 0.992295
0.919403 0.992886
0.922388 0.993450
0.925373 0.993985
0.928358 0.994495
0.931343 0.994978
0.934328 0.995436
0.937313 0.995869
0.940299 0.996278
0.943284 0.996663
0.946269 0.997024
0.949254 0.997363
0.952239 0.997678
0.955224 0.997972
0.958209 0.998245
0.961194 0.998496
0.964179 0.998726
0.967164 0.998936
0.970149 0.999126
0.973134 0.999296
0.976119 0.999447
0.979104 0.999579
0.982090 0.999693
0.985075 0.999788
0.988060 0.999865
0.991045 0.999924
1.000000 1.000000
1.120000 1.000000
