TsRegressionPreventer::SetResult:
  adjusted: true
  havePreSegment: true
  preActiveAdjusted: true
  preActiveAdjustedWidth: 1.165675
  preOppositeAdjusted: false
  preOppositeAdjustedWidth: 0.800000
  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 0.800000, auto false / false
  1.000000: 1.000000, Curve, preSlope 0.000000, postSlope 0.000000, preLen 1.165675, 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('0x1.999999999999ap-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('0x1.2a69b463e86acp+0'), postLen = float.fromhex('0x0p+0'), preAuto = False, postAuto = False)])
-----
-0.200000 0.000000
0.000000 0.000000
0.004975 0.000013
0.009950 0.000052
0.014925 0.000119
0.019900 0.000213
0.024876 0.000335
0.029851 0.000487
0.034826 0.000668
0.039801 0.000880
0.044776 0.001124
0.049751 0.001400
0.054726 0.001708
0.059701 0.002051
0.064677 0.002429
0.069652 0.002843
0.074627 0.003294
0.079602 0.003783
0.084577 0.004311
0.089552 0.004880
0.094527 0.005491
0.099502 0.006144
0.104478 0.006842
0.109453 0.007586
0.114428 0.008377
0.119403 0.009218
0.124378 0.010109
0.129353 0.011053
0.134328 0.012051
0.139303 0.013106
0.144279 0.014219
0.149254 0.015394
0.154229 0.016632
0.159204 0.017936
0.164179 0.019308
0.169154 0.020753
0.174129 0.022272
0.179104 0.023869
0.184080 0.025548
0.189055 0.027313
0.194030 0.029168
0.199005 0.031117
0.203980 0.033166
0.208955 0.035319
0.213930 0.037583
0.218905 0.039964
0.223881 0.042469
0.228856 0.045104
0.233831 0.047880
0.238806 0.050805
0.243781 0.053888
0.248756 0.057143
0.253731 0.060581
0.258706 0.064217
0.263682 0.068067
0.268657 0.072150
0.273632 0.076487
0.278607 0.081102
0.283582 0.086024
0.288557 0.091286
0.293532 0.096928
0.298507 0.102997
0.303483 0.109551
0.308458 0.116660
0.313433 0.124415
0.318408 0.132931
0.323383 0.142358
0.328358 0.152905
0.333333 0.164866
0.338308 0.178689
0.343284 0.195102
0.348259 0.215422
0.353234 0.241359
0.358209 0.281856
0.363184 0.514847
0.368159 0.599200
0.373134 0.637827
0.378109 0.630313
0.383085 0.670340
0.388060 0.696844
0.393035 0.716471
0.398010 0.732272
0.402985 0.745711
0.407960 0.757542
0.412935 0.768193
0.417910 0.777925
0.422886 0.786911
0.427861 0.795271
0.432836 0.803093
0.437811 0.810447
0.442786 0.817387
0.447761 0.823955
0.452736 0.830189
0.457711 0.836119
0.462687 0.841772
0.467662 0.847170
0.472637 0.852334
0.477612 0.857279
0.482587 0.862023
0.487562 0.866578
0.492537 0.870956
0.497512 0.875170
0.502488 0.879228
0.507463 0.883140
0.512438 0.886914
0.517413 0.890557
0.522388 0.894076
0.527363 0.897478
0.532338 0.900768
0.537313 0.903951
0.542289 0.907033
0.547264 0.910018
0.552239 0.912911
0.557214 0.915715
0.562189 0.918434
0.567164 0.921071
0.572139 0.923630
0.577114 0.926113
0.582090 0.928525
0.587065 0.930866
0.592040 0.933141
0.597015 0.935350
0.601990 0.937497
0.606965 0.939584
0.611940 0.941611
0.616915 0.943583
0.621891 0.945500
0.626866 0.947363
0.631841 0.949176
0.636816 0.950938
0.641791 0.952652
0.646766 0.954319
0.651741 0.955940
0.656716 0.957517
0.661692 0.959051
0.666667 0.960543
0.671642 0.961995
0.676617 0.963406
0.681592 0.964779
0.686567 0.966113
0.691542 0.967412
0.696517 0.968674
0.701493 0.969901
0.706468 0.971094
0.711443 0.972254
0.716418 0.973381
0.721393 0.974476
0.726368 0.975540
0.731343 0.976574
0.736318 0.977578
0.741294 0.978553
0.746269 0.979499
0.751244 0.980418
0.756219 0.981309
0.761194 0.982173
0.766169 0.983012
0.771144 0.983824
0.776119 0.984612
0.781095 0.985374
0.786070 0.986113
0.791045 0.986828
0.796020 0.987519
0.800995 0.988188
0.805970 0.988835
0.810945 0.989459
0.815920 0.990062
0.820896 0.990643
0.825871 0.991204
0.830846 0.991744
0.835821 0.992264
0.840796 0.992765
0.845771 0.993246
0.850746 0.993707
0.855721 0.994150
0.860697 0.994575
0.865672 0.994981
0.870647 0.995370
0.875622 0.995741
0.880597 0.996094
0.885572 0.996431
0.890547 0.996750
0.895522 0.997054
0.900498 0.997340
0.905473 0.997611
0.910448 0.997866
0.915423 0.998106
0.920398 0.998330
0.925373 0.998539
0.930348 0.998733
0.935323 0.998913
0.940299 0.999078
0.945274 0.999229
0.950249 0.999366
0.955224 0.999488
0.960199 0.999598
0.965174 0.999693
0.970149 0.999776
0.975124 0.999845
0.980100 0.999901
0.985075 0.999945
1.000000 1.000000
1.200000 1.000000
