TsRegressionPreventer::SetResult:
  adjusted: true
  havePreSegment: false
  preActiveAdjusted: false
  preActiveAdjustedWidth: 0.000000
  preOppositeAdjusted: false
  preOppositeAdjustedWidth: 0.000000
  havePostSegment: true
  postActiveAdjusted: true
  postActiveAdjustedWidth: 0.199994
  postOppositeAdjusted: true
  postOppositeAdjustedWidth: 0.799994
-----
Spline:
  hermite false
  preExtrap Held
  postExtrap Held
Knots:
  0.400000: 0.000000, Curve, preSlope 0.000000, postSlope 0.000000, preLen 0.000000, postLen 0.199994, auto false / false
  1.000000: 1.000000, Curve, preSlope 0.000000, postSlope 0.000000, preLen 0.799994, 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('0x1.9996744b2b777p-3'), 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('0x1.9998d045fe11p-1'), postLen = float.fromhex('0x0p+0'), preAuto = False, postAuto = False)])
-----
0.280000 0.000000
0.400000 0.000000
0.402985 0.000076
0.405970 0.000314
0.408955 0.000727
0.411940 0.001332
0.414925 0.002148
0.417910 0.003198
0.420896 0.004506
0.423881 0.006103
0.426866 0.008026
0.429851 0.010320
0.432836 0.013038
0.435821 0.016248
0.438806 0.020038
0.441791 0.024521
0.444776 0.029848
0.447761 0.036231
0.450746 0.043978
0.453731 0.053559
0.456716 0.065739
0.459701 0.082330
0.462687 0.104203
0.465672 0.157725
0.468657 0.405624
0.471642 0.460548
0.474627 0.496212
0.477612 0.523776
0.480597 0.546640
0.483582 0.566363
0.486567 0.583804
0.489552 0.599499
0.492537 0.613803
0.495522 0.626968
0.498507 0.639178
0.501493 0.650574
0.504478 0.661267
0.507463 0.671344
0.510448 0.680875
0.513433 0.689919
0.516418 0.698526
0.519403 0.706737
0.522388 0.714587
0.525373 0.722107
0.528358 0.729324
0.531343 0.736260
0.534328 0.742935
0.537313 0.749369
0.540299 0.755577
0.543284 0.761574
0.546269 0.767373
0.549254 0.772985
0.552239 0.778415
0.555224 0.783687
0.558209 0.788801
0.561194 0.793765
0.564179 0.798588
0.567164 0.803275
0.570149 0.807834
0.573134 0.812269
0.576119 0.816587
0.579104 0.820793
0.582090 0.824892
0.585075 0.828887
0.588060 0.832783
0.591045 0.836585
0.594030 0.840294
0.597015 0.843915
0.600000 0.847451
0.602985 0.850905
0.605970 0.854280
0.608955 0.857578
0.611940 0.860803
0.614925 0.863956
0.617910 0.867040
0.620896 0.870056
0.623881 0.873007
0.626866 0.875895
0.629851 0.878722
0.632836 0.881489
0.635821 0.884198
0.638806 0.886851
0.641791 0.889449
0.644776 0.891994
0.647761 0.894488
0.650746 0.896930
0.653731 0.899324
0.656716 0.901669
0.659701 0.903968
0.662687 0.906221
0.665672 0.908429
0.668657 0.910594
0.671642 0.912717
0.674627 0.914798
0.677612 0.916837
0.680597 0.918838
0.683582 0.920800
0.686567 0.922724
0.689552 0.924610
0.692537 0.926461
0.695522 0.928275
0.698507 0.930055
0.701493 0.931800
0.704478 0.933512
0.707463 0.935191
0.710448 0.936838
0.713433 0.938453
0.716418 0.940037
0.719403 0.941591
0.722388 0.943115
0.725373 0.944610
0.728358 0.946076
0.731343 0.947513
0.734328 0.948923
0.737313 0.950305
0.740299 0.951661
0.743284 0.952990
0.746269 0.954294
0.749254 0.955572
0.752239 0.956825
0.755224 0.958053
0.758209 0.959257
0.761194 0.960437
0.764179 0.961594
0.767164 0.962727
0.770149 0.963838
0.773134 0.964927
0.776119 0.965993
0.779104 0.967038
0.782090 0.968061
0.785075 0.969063
0.788060 0.970045
0.791045 0.971006
0.794030 0.971947
0.797015 0.972867
0.800000 0.973769
0.802985 0.974650
0.805970 0.975513
0.808955 0.976357
0.811940 0.977183
0.814925 0.977990
0.817910 0.978779
0.820896 0.979551
0.823881 0.980304
0.826866 0.981041
0.829851 0.981760
0.832836 0.982462
0.835821 0.983148
0.838806 0.983817
0.841791 0.984470
0.844776 0.985107
0.847761 0.985728
0.850746 0.986333
0.853731 0.986923
0.856716 0.987498
0.859701 0.988057
0.862687 0.988602
0.865672 0.989131
0.868657 0.989646
0.871642 0.990147
0.874627 0.990633
0.877612 0.991106
0.880597 0.991564
0.883582 0.992009
0.886567 0.992440
0.889552 0.992857
0.892537 0.993261
0.895522 0.993652
0.898507 0.994030
0.901493 0.994395
0.904478 0.994748
0.907463 0.995087
0.910448 0.995415
0.913433 0.995730
0.916418 0.996032
0.919403 0.996323
0.922388 0.996601
0.925373 0.996868
0.928358 0.997123
0.931343 0.997366
0.934328 0.997598
0.937313 0.997818
0.940299 0.998027
0.943284 0.998225
0.946269 0.998412
0.949254 0.998588
0.952239 0.998753
0.955224 0.998908
0.958209 0.999051
0.961194 0.999185
0.964179 0.999307
0.967164 0.999420
0.970149 0.999522
0.973134 0.999614
0.976119 0.999696
0.979104 0.999768
0.982090 0.999830
0.985075 0.999882
0.988060 0.999925
0.991045 0.999958
1.000000 1.000000
1.120000 1.000000
