TsRegressionPreventer::SetResult:
  adjusted: true
  havePreSegment: false
  preActiveAdjusted: false
  preActiveAdjustedWidth: 0.000000
  preOppositeAdjusted: false
  preOppositeAdjustedWidth: 0.000000
  havePostSegment: true
  postActiveAdjusted: true
  postActiveAdjustedWidth: 1.000000
  postOppositeAdjusted: false
  postOppositeAdjustedWidth: 0.800000
-----
Spline:
  hermite false
  preExtrap Held
  postExtrap Held
Knots:
  0.000000: 0.000000, Curve, preSlope 0.000000, postSlope 0.000000, preLen 0.000000, postLen 1.000000, auto false / false
  1.000000: 1.000000, Curve, preSlope 0.000000, postSlope 0.000000, preLen 0.800000, 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('0x1p+0'), 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('0x1.999999999999ap-1'), postLen = float.fromhex('0x0p+0'), preAuto = False, postAuto = False)])
-----
-0.200000 0.000000
0.000000 0.000000
0.004975 0.000008
0.009950 0.000033
0.014925 0.000075
0.019900 0.000135
0.024876 0.000211
0.029851 0.000306
0.034826 0.000419
0.039801 0.000550
0.044776 0.000699
0.049751 0.000868
0.054726 0.001055
0.059701 0.001263
0.064677 0.001490
0.069652 0.001737
0.074627 0.002005
0.079602 0.002294
0.084577 0.002604
0.089552 0.002935
0.094527 0.003289
0.099502 0.003664
0.104478 0.004063
0.109453 0.004485
0.114428 0.004930
0.119403 0.005399
0.124378 0.005893
0.129353 0.006412
0.134328 0.006956
0.139303 0.007526
0.144279 0.008122
0.149254 0.008745
0.154229 0.009396
0.159204 0.010074
0.164179 0.010782
0.169154 0.011518
0.174129 0.012284
0.179104 0.013080
0.184080 0.013908
0.189055 0.014767
0.194030 0.015658
0.199005 0.016583
0.203980 0.017541
0.208955 0.018534
0.213930 0.019563
0.218905 0.020628
0.223881 0.021729
0.228856 0.022869
0.233831 0.024048
0.238806 0.025267
0.243781 0.026527
0.248756 0.027829
0.253731 0.029173
0.258706 0.030563
0.263682 0.031997
0.268657 0.033478
0.273632 0.035007
0.278607 0.036585
0.283582 0.038214
0.288557 0.039896
0.293532 0.041631
0.298507 0.043421
0.303483 0.045269
0.308458 0.047175
0.313433 0.049142
0.318408 0.051172
0.323383 0.053267
0.328358 0.055428
0.333333 0.057659
0.338308 0.059962
0.343284 0.062340
0.348259 0.064794
0.353234 0.067329
0.358209 0.069946
0.363184 0.072650
0.368159 0.075444
0.373134 0.078332
0.378109 0.081317
0.383085 0.084404
0.388060 0.087597
0.393035 0.090902
0.398010 0.094323
0.402985 0.097866
0.407960 0.101538
0.412935 0.105344
0.417910 0.109292
0.422886 0.113390
0.427861 0.117647
0.432836 0.122070
0.437811 0.126671
0.442786 0.131461
0.447761 0.136452
0.452736 0.141657
0.457711 0.147091
0.462687 0.152773
0.467662 0.158718
0.472637 0.164951
0.477612 0.171494
0.482587 0.178376
0.487562 0.185626
0.492537 0.193283
0.497512 0.201388
0.502488 0.209973
0.507463 0.219124
0.512438 0.228898
0.517413 0.239378
0.522388 0.250669
0.527363 0.262897
0.532338 0.276223
0.537313 0.290855
0.542289 0.307066
0.547264 0.325225
0.552239 0.345842
0.557214 0.369642
0.562189 0.397675
0.567164 0.431418
0.572139 0.472613
0.577114 0.521662
0.582090 0.573877
0.587065 0.621096
0.592040 0.659872
0.597015 0.691263
0.601990 0.717138
0.606965 0.738960
0.611940 0.757744
0.616915 0.774186
0.621891 0.788773
0.626866 0.801858
0.631841 0.813702
0.636816 0.824503
0.641791 0.834414
0.646766 0.843558
0.651741 0.852031
0.656716 0.859915
0.661692 0.867275
0.666667 0.874168
0.671642 0.880638
0.676617 0.886727
0.681592 0.892468
0.686567 0.897891
0.691542 0.903023
0.696517 0.907885
0.701493 0.912499
0.706468 0.916882
0.711443 0.921050
0.716418 0.925016
0.721393 0.928796
0.726368 0.932399
0.731343 0.935836
0.736318 0.939117
0.741294 0.942250
0.746269 0.945244
0.751244 0.948106
0.756219 0.950842
0.761194 0.953460
0.766169 0.955963
0.771144 0.958359
0.776119 0.960651
0.781095 0.962845
0.786070 0.964945
0.791045 0.966954
0.796020 0.968877
0.800995 0.970717
0.805970 0.972477
0.810945 0.974160
0.815920 0.975769
0.820896 0.977308
0.825871 0.978777
0.830846 0.980181
0.835821 0.981521
0.840796 0.982799
0.845771 0.984018
0.850746 0.985179
0.855721 0.986284
0.860697 0.987336
0.865672 0.988335
0.870647 0.989283
0.875622 0.990182
0.880597 0.991034
0.885572 0.991839
0.890547 0.992598
0.895522 0.993315
0.900498 0.993988
0.905473 0.994620
0.910448 0.995212
0.915423 0.995765
0.920398 0.996279
0.925373 0.996756
0.930348 0.997197
0.935323 0.997602
0.940299 0.997973
0.945274 0.998310
0.950249 0.998614
0.955224 0.998886
0.960199 0.999126
0.965174 0.999336
0.970149 0.999516
0.975124 0.999666
0.980100 0.999788
0.985075 0.999882
1.000000 1.000000
1.200000 1.000000
