TsRegressionPreventer::SetResult:
  adjusted: true
  havePreSegment: true
  preActiveAdjusted: true
  preActiveAdjustedWidth: 1.000000
  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 1.000000, 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('0x1p+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 0.000118
0.019900 0.000212
0.024876 0.000334
0.029851 0.000484
0.034826 0.000664
0.039801 0.000874
0.044776 0.001114
0.049751 0.001386
0.054726 0.001690
0.059701 0.002027
0.064677 0.002398
0.069652 0.002803
0.074627 0.003244
0.079602 0.003721
0.084577 0.004235
0.089552 0.004788
0.094527 0.005380
0.099502 0.006012
0.104478 0.006685
0.109453 0.007402
0.114428 0.008161
0.119403 0.008966
0.124378 0.009818
0.129353 0.010717
0.134328 0.011665
0.139303 0.012664
0.144279 0.013716
0.149254 0.014821
0.154229 0.015982
0.159204 0.017201
0.164179 0.018479
0.169154 0.019819
0.174129 0.021223
0.179104 0.022692
0.184080 0.024231
0.189055 0.025840
0.194030 0.027523
0.199005 0.029283
0.203980 0.031123
0.208955 0.033046
0.213930 0.035055
0.218905 0.037155
0.223881 0.039349
0.228856 0.041641
0.233831 0.044037
0.238806 0.046540
0.243781 0.049158
0.248756 0.051894
0.253731 0.054756
0.258706 0.057750
0.263682 0.060883
0.268657 0.064164
0.273632 0.067601
0.278607 0.071204
0.283582 0.074984
0.288557 0.078950
0.293532 0.083118
0.298507 0.087501
0.303483 0.092115
0.308458 0.096977
0.313433 0.102109
0.318408 0.107532
0.323383 0.113273
0.328358 0.119362
0.333333 0.125832
0.338308 0.132725
0.343284 0.140085
0.348259 0.147969
0.353234 0.156442
0.358209 0.165586
0.363184 0.175497
0.368159 0.186298
0.373134 0.198142
0.378109 0.211227
0.383085 0.225814
0.388060 0.242256
0.393035 0.261040
0.398010 0.282862
0.402985 0.308737
0.407960 0.340128
0.412935 0.378904
0.417910 0.426123
0.422886 0.478338
0.427861 0.527387
0.432836 0.568582
0.437811 0.602325
0.442786 0.630358
0.447761 0.654158
0.452736 0.674775
0.457711 0.692934
0.462687 0.709145
0.467662 0.723777
0.472637 0.737103
0.477612 0.749331
0.482587 0.760622
0.487562 0.771102
0.492537 0.780876
0.497512 0.790027
0.502488 0.798612
0.507463 0.806717
0.512438 0.814374
0.517413 0.821624
0.522388 0.828506
0.527363 0.835049
0.532338 0.841282
0.537313 0.847227
0.542289 0.852909
0.547264 0.858343
0.552239 0.863548
0.557214 0.868539
0.562189 0.873329
0.567164 0.877930
0.572139 0.882353
0.577114 0.886610
0.582090 0.890708
0.587065 0.894656
0.592040 0.898462
0.597015 0.902134
0.601990 0.905677
0.606965 0.909098
0.611940 0.912403
0.616915 0.915596
0.621891 0.918683
0.626866 0.921668
0.631841 0.924556
0.636816 0.927350
0.641791 0.930054
0.646766 0.932671
0.651741 0.935206
0.656716 0.937660
0.661692 0.940038
0.666667 0.942341
0.671642 0.944572
0.676617 0.946733
0.681592 0.948828
0.686567 0.950858
0.691542 0.952825
0.696517 0.954731
0.701493 0.956579
0.706468 0.958369
0.711443 0.960104
0.716418 0.961786
0.721393 0.963415
0.726368 0.964993
0.731343 0.966522
0.736318 0.968003
0.741294 0.969437
0.746269 0.970827
0.751244 0.972171
0.756219 0.973473
0.761194 0.974733
0.766169 0.975952
0.771144 0.977131
0.776119 0.978271
0.781095 0.979372
0.786070 0.980437
0.791045 0.981466
0.796020 0.982459
0.800995 0.983417
0.805970 0.984342
0.810945 0.985233
0.815920 0.986092
0.820896 0.986920
0.825871 0.987716
0.830846 0.988482
0.835821 0.989218
0.840796 0.989926
0.845771 0.990604
0.850746 0.991255
0.855721 0.991878
0.860697 0.992474
0.865672 0.993044
0.870647 0.993588
0.875622 0.994107
0.880597 0.994601
0.885572 0.995070
0.890547 0.995515
0.895522 0.995937
0.900498 0.996336
0.905473 0.996711
0.910448 0.997065
0.915423 0.997396
0.920398 0.997706
0.925373 0.997995
0.930348 0.998263
0.935323 0.998510
0.940299 0.998737
0.945274 0.998945
0.950249 0.999132
0.955224 0.999301
0.960199 0.999450
0.965174 0.999581
0.970149 0.999694
0.975124 0.999789
0.980100 0.999865
0.985075 0.999925
1.000000 1.000000
1.200000 1.000000
