TsRegressionPreventer::SetResult:
  adjusted: true
  havePreSegment: true
  preActiveAdjusted: false
  preActiveAdjustedWidth: 0.250000
  preOppositeAdjusted: true
  preOppositeAdjustedWidth: 0.130900
  havePostSegment: true
  postActiveAdjusted: false
  postActiveAdjustedWidth: 0.250000
  postOppositeAdjusted: false
  postOppositeAdjustedWidth: 0.250000
-----
Spline:
  hermite false
  preExtrap Held
  postExtrap Held
Knots:
  1.000000: 1.000000, Curve, preSlope 0.000000, postSlope -0.250000, preLen 0.000000, postLen 0.250000, auto false / false
  3.000000: 1.000000, Curve, preSlope -0.250000, postSlope -0.250000, preLen 0.250000, postLen 0.130900, auto false / false
  3.200000: 2.000000, Curve, preSlope 0.250000, postSlope 0.250000, preLen 0.250000, postLen 0.250000, auto false / false
  4.000000: 2.000000, Curve, preSlope 0.250000, postSlope 0.000000, preLen 0.250000, 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('0x1p+0'), nextSegInterpMethod = Ts.TsTest_SplineData.InterpCurve, value = float.fromhex('0x1p+0'), preSlope = float.fromhex('0x0p+0'), postSlope = float.fromhex('-0x1p-2'), preLen = float.fromhex('0x0p+0'), postLen = float.fromhex('0x1p-2'), preAuto = False, postAuto = False), Ts.TsTest_SplineData.Knot(time = float.fromhex('0x1.8p+1'), nextSegInterpMethod = Ts.TsTest_SplineData.InterpCurve, value = float.fromhex('0x1p+0'), preSlope = float.fromhex('-0x1p-2'), postSlope = float.fromhex('-0x1p-2'), preLen = float.fromhex('0x1p-2'), postLen = float.fromhex('0x1.0c1524411f46fp-3'), preAuto = False, postAuto = False), Ts.TsTest_SplineData.Knot(time = float.fromhex('0x1.999999999999ap+1'), nextSegInterpMethod = Ts.TsTest_SplineData.InterpCurve, value = float.fromhex('0x1p+1'), preSlope = float.fromhex('0x1p-2'), postSlope = float.fromhex('0x1p-2'), preLen = float.fromhex('0x1p-2'), postLen = float.fromhex('0x1p-2'), preAuto = False, postAuto = False), Ts.TsTest_SplineData.Knot(time = float.fromhex('0x1p+2'), nextSegInterpMethod = Ts.TsTest_SplineData.InterpCurve, value = float.fromhex('0x1p+1'), preSlope = float.fromhex('0x1p-2'), postSlope = float.fromhex('0x0p+0'), preLen = float.fromhex('0x1p-2'), postLen = float.fromhex('0x0p+0'), preAuto = False, postAuto = False)])
-----
0.400000 1.000000
1.000000 1.000000
1.014925 0.996762
1.029851 0.994243
1.044776 0.992203
1.059701 0.990512
1.074627 0.989088
1.089552 0.987878
1.104478 0.986844
1.119403 0.985957
1.134328 0.985197
1.149254 0.984546
1.164179 0.983991
1.179104 0.983521
1.194030 0.983126
1.208955 0.982799
1.223881 0.982534
1.238806 0.982325
1.253731 0.982167
1.268657 0.982056
1.283582 0.981987
1.298507 0.981959
1.313433 0.981968
1.328358 0.982010
1.343284 0.982085
1.358209 0.982190
1.373134 0.982322
1.388060 0.982480
1.402985 0.982663
1.417910 0.982869
1.432836 0.983097
1.447761 0.983344
1.462687 0.983611
1.477612 0.983896
1.492537 0.984199
1.507463 0.984517
1.522388 0.984850
1.537313 0.985198
1.552239 0.985559
1.567164 0.985934
1.582090 0.986320
1.597015 0.986718
1.611940 0.987127
1.626866 0.987546
1.641791 0.987974
1.656716 0.988412
1.671642 0.988859
1.686567 0.989313
1.701493 0.989776
1.716418 0.990245
1.731343 0.990721
1.746269 0.991203
1.761194 0.991692
1.776119 0.992185
1.791045 0.992684
1.805970 0.993188
1.820896 0.993695
1.835821 0.994207
1.850746 0.994723
1.865672 0.995241
1.880597 0.995763
1.895522 0.996287
1.910448 0.996813
1.925373 0.997341
1.940299 0.997871
1.955224 0.998402
1.970149 0.998934
1.985075 0.999467
2.000000 1.000000
2.014925 1.000533
2.029851 1.001066
2.044776 1.001598
2.059701 1.002129
2.074627 1.002659
2.089552 1.003187
2.104478 1.003713
2.119403 1.004237
2.134328 1.004759
2.149254 1.005277
2.164179 1.005793
2.179104 1.006305
2.194030 1.006812
2.208955 1.007316
2.223881 1.007815
2.238806 1.008308
2.253731 1.008797
2.268657 1.009279
2.283582 1.009755
2.298507 1.010224
2.313433 1.010687
2.328358 1.011141
2.343284 1.011588
2.358209 1.012026
2.373134 1.012454
2.388060 1.012873
2.402985 1.013282
2.417910 1.013680
2.432836 1.014066
2.447761 1.014441
2.462687 1.014802
2.477612 1.015150
2.492537 1.015483
2.507463 1.015801
2.522388 1.016104
2.537313 1.016389
2.552239 1.016656
2.567164 1.016903
2.582090 1.017131
2.597015 1.017337
2.611940 1.017520
2.626866 1.017678
2.641791 1.017810
2.656716 1.017915
2.671642 1.017990
2.686567 1.018032
2.701493 1.018041
2.716418 1.018013
2.731343 1.017944
2.746269 1.017833
2.761194 1.017675
2.776119 1.017466
2.791045 1.017201
2.805970 1.016874
2.820896 1.016479
2.835821 1.016009
2.850746 1.015454
2.865672 1.014803
2.880597 1.014043
2.895522 1.013156
2.910448 1.012122
2.925373 1.010912
2.940299 1.009488
2.955224 1.007797
2.970149 1.005757
2.985075 1.003238
3.000000 1.000000
3.014925 1.001055
3.029851 1.016827
3.044776 1.069087
3.059701 1.619385
3.074627 1.773281
3.089552 1.846883
3.104478 1.894343
3.119403 1.927734
3.134328 1.952065
3.149254 1.969960
3.164179 1.982999
3.179104 1.992210
3.194030 1.998310
3.200000 2.000000
3.208955 2.002154
3.223881 2.005382
3.238806 2.008180
3.253731 2.010576
3.268657 2.012594
3.283582 2.014258
3.298507 2.015591
3.313433 2.016614
3.328358 2.017347
3.343284 2.017811
3.358209 2.018023
3.373134 2.018003
3.388060 2.017766
3.402985 2.017330
3.417910 2.016711
3.432836 2.015925
3.447761 2.014986
3.462687 2.013910
3.477612 2.012711
3.492537 2.011403
3.507463 2.010000
3.522388 2.008516
3.537313 2.006964
3.552239 2.005357
3.567164 2.003708
3.582090 2.002032
3.597015 2.000339
3.611940 1.998644
3.626866 1.996960
3.641791 1.995298
3.656716 1.993673
3.671642 1.992098
3.686567 1.990585
3.701493 1.989148
3.716418 1.987800
3.731343 1.986556
3.746269 1.985429
3.761194 1.984433
3.776119 1.983584
3.791045 1.982896
3.805970 1.982385
3.820896 1.982067
3.835821 1.981958
3.850746 1.982075
3.865672 1.982436
3.880597 1.983059
3.895522 1.983964
3.910448 1.985170
3.925373 1.986699
3.940299 1.988573
3.955224 1.990815
4.000000 2.000000
4.600000 2.000000
