TsRegressionPreventer::SetResult:
  adjusted: true
  havePreSegment: true
  preActiveAdjusted: true
  preActiveAdjustedWidth: 1.203475
  preOppositeAdjusted: true
  preOppositeAdjustedWidth: 0.740596
  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 0.740596, auto false / false
  1.000000: 1.000000, Curve, preSlope 0.000000, postSlope 0.000000, preLen 1.203475, 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('0x1.7b2f6f1ab02dfp-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('0x1.3416f3213ad1cp+0'), postLen = float.fromhex('0x0p+0'), preAuto = False, postAuto = False)])
-----
-0.200000 0.000000
0.000000 0.000000
0.004975 0.000015
0.009950 0.000061
0.014925 0.000139
0.019900 0.000249
0.024876 0.000393
0.029851 0.000572
0.034826 0.000785
0.039801 0.001036
0.044776 0.001324
0.049751 0.001650
0.054726 0.002017
0.059701 0.002425
0.064677 0.002875
0.069652 0.003369
0.074627 0.003908
0.079602 0.004495
0.084577 0.005130
0.089552 0.005815
0.094527 0.006552
0.099502 0.007343
0.104478 0.008191
0.109453 0.009096
0.114428 0.010062
0.119403 0.011091
0.124378 0.012185
0.129353 0.013348
0.134328 0.014582
0.139303 0.015891
0.144279 0.017277
0.149254 0.018745
0.154229 0.020298
0.159204 0.021942
0.164179 0.023679
0.169154 0.025516
0.174129 0.027458
0.179104 0.029510
0.184080 0.031680
0.189055 0.033974
0.194030 0.036400
0.199005 0.038966
0.203980 0.041683
0.208955 0.044560
0.213930 0.047610
0.218905 0.050846
0.223881 0.054282
0.228856 0.057935
0.233831 0.061826
0.238806 0.065975
0.243781 0.070410
0.248756 0.075159
0.253731 0.080258
0.258706 0.085748
0.263682 0.091681
0.268657 0.098120
0.273632 0.105139
0.278607 0.112837
0.283582 0.121340
0.288557 0.130819
0.293532 0.141506
0.298507 0.153741
0.303483 0.168044
0.308458 0.185192
0.313433 0.206914
0.318408 0.236990
0.323383 0.283549
0.328358 0.544163
0.333333 0.598571
0.338308 0.631827
0.343284 0.656848
0.348259 0.658861
0.353234 0.685155
0.358209 0.704744
0.363184 0.720526
0.368159 0.733944
0.373134 0.745759
0.378109 0.756404
0.383085 0.766144
0.388060 0.775151
0.393035 0.783545
0.398010 0.791415
0.402985 0.798827
0.407960 0.805833
0.412935 0.812477
0.417910 0.818793
0.422886 0.824812
0.427861 0.830558
0.432836 0.836053
0.437811 0.841317
0.442786 0.846367
0.447761 0.851217
0.452736 0.855880
0.457711 0.860369
0.462687 0.864694
0.467662 0.868865
0.472637 0.872891
0.477612 0.876779
0.482587 0.880537
0.487562 0.884172
0.492537 0.887690
0.497512 0.891096
0.502488 0.894396
0.507463 0.897594
0.512438 0.900696
0.517413 0.903705
0.522388 0.906625
0.527363 0.909460
0.532338 0.912213
0.537313 0.914888
0.542289 0.917486
0.547264 0.920013
0.552239 0.922469
0.557214 0.924858
0.562189 0.927182
0.567164 0.929442
0.572139 0.931642
0.577114 0.933783
0.582090 0.935867
0.587065 0.937895
0.592040 0.939870
0.597015 0.941794
0.601990 0.943667
0.606965 0.945491
0.611940 0.947268
0.616915 0.948999
0.621891 0.950685
0.626866 0.952327
0.631841 0.953927
0.636816 0.955486
0.641791 0.957005
0.646766 0.958484
0.651741 0.959925
0.656716 0.961329
0.661692 0.962697
0.666667 0.964029
0.671642 0.965326
0.676617 0.966590
0.681592 0.967821
0.686567 0.969019
0.691542 0.970186
0.696517 0.971322
0.701493 0.972428
0.706468 0.973504
0.711443 0.974551
0.716418 0.975570
0.721393 0.976562
0.726368 0.977526
0.731343 0.978463
0.736318 0.979375
0.741294 0.980261
0.746269 0.981122
0.751244 0.981958
0.756219 0.982770
0.761194 0.983559
0.766169 0.984324
0.771144 0.985066
0.776119 0.985787
0.781095 0.986485
0.786070 0.987161
0.791045 0.987817
0.796020 0.988451
0.800995 0.989065
0.805970 0.989659
0.810945 0.990233
0.815920 0.990788
0.820896 0.991323
0.825871 0.991840
0.830846 0.992338
0.835821 0.992818
0.840796 0.993280
0.845771 0.993724
0.850746 0.994151
0.855721 0.994561
0.860697 0.994954
0.865672 0.995330
0.870647 0.995690
0.875622 0.996034
0.880597 0.996362
0.885572 0.996674
0.890547 0.996971
0.895522 0.997253
0.900498 0.997519
0.905473 0.997771
0.910448 0.998009
0.915423 0.998232
0.920398 0.998440
0.925373 0.998635
0.930348 0.998816
0.935323 0.998984
0.940299 0.999138
0.945274 0.999279
0.950249 0.999406
0.955224 0.999521
0.960199 0.999623
0.965174 0.999713
0.970149 0.999790
0.975124 0.999855
0.980100 0.999907
0.985075 0.999948
1.000000 1.000000
1.200000 1.000000
