TsRegressionPreventer::SetResult:
  adjusted: true
  havePreSegment: false
  preActiveAdjusted: false
  preActiveAdjustedWidth: 0.000000
  preOppositeAdjusted: false
  preOppositeAdjustedWidth: 0.000000
  havePostSegment: true
  postActiveAdjusted: true
  postActiveAdjustedWidth: 1.165675
  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 1.165675, 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('0x1.2a69b463e86acp+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 0.000006
0.009950 0.000025
0.014925 0.000055
0.019900 0.000099
0.024876 0.000155
0.029851 0.000224
0.034826 0.000307
0.039801 0.000402
0.044776 0.000512
0.049751 0.000634
0.054726 0.000771
0.059701 0.000922
0.064677 0.001087
0.069652 0.001267
0.074627 0.001461
0.079602 0.001670
0.084577 0.001894
0.089552 0.002134
0.094527 0.002389
0.099502 0.002660
0.104478 0.002946
0.109453 0.003250
0.114428 0.003569
0.119403 0.003906
0.124378 0.004259
0.129353 0.004630
0.134328 0.005019
0.139303 0.005425
0.144279 0.005850
0.149254 0.006293
0.154229 0.006754
0.159204 0.007235
0.164179 0.007736
0.169154 0.008256
0.174129 0.008796
0.179104 0.009357
0.184080 0.009938
0.189055 0.010541
0.194030 0.011165
0.199005 0.011812
0.203980 0.012481
0.208955 0.013172
0.213930 0.013887
0.218905 0.014626
0.223881 0.015388
0.228856 0.016176
0.233831 0.016988
0.238806 0.017827
0.243781 0.018691
0.248756 0.019582
0.253731 0.020501
0.258706 0.021447
0.263682 0.022422
0.268657 0.023426
0.273632 0.024460
0.278607 0.025524
0.283582 0.026619
0.288557 0.027746
0.293532 0.028906
0.298507 0.030099
0.303483 0.031326
0.308458 0.032588
0.313433 0.033887
0.318408 0.035221
0.323383 0.036594
0.328358 0.038005
0.333333 0.039457
0.338308 0.040949
0.343284 0.042483
0.348259 0.044060
0.353234 0.045681
0.358209 0.047348
0.363184 0.049062
0.368159 0.050824
0.373134 0.052637
0.378109 0.054500
0.383085 0.056417
0.388060 0.058389
0.393035 0.060416
0.398010 0.062503
0.402985 0.064650
0.407960 0.066859
0.412935 0.069134
0.417910 0.071475
0.422886 0.073887
0.427861 0.076370
0.432836 0.078929
0.437811 0.081566
0.442786 0.084285
0.447761 0.087089
0.452736 0.089982
0.457711 0.092967
0.462687 0.096049
0.467662 0.099232
0.472637 0.102522
0.477612 0.105924
0.482587 0.109443
0.487562 0.113086
0.492537 0.116860
0.497512 0.120772
0.502488 0.124830
0.507463 0.129044
0.512438 0.133422
0.517413 0.137977
0.522388 0.142721
0.527363 0.147666
0.532338 0.152830
0.537313 0.158228
0.542289 0.163881
0.547264 0.169811
0.552239 0.176045
0.557214 0.182613
0.562189 0.189553
0.567164 0.196907
0.572139 0.204729
0.577114 0.213089
0.582090 0.222075
0.587065 0.231807
0.592040 0.242458
0.597015 0.254289
0.601990 0.267728
0.606965 0.283529
0.611940 0.303156
0.616915 0.329660
0.621891 0.369687
0.626866 0.362173
0.631841 0.400800
0.636816 0.485153
0.641791 0.718144
0.646766 0.758641
0.651741 0.784578
0.656716 0.804898
0.661692 0.821311
0.666667 0.835134
0.671642 0.847095
0.676617 0.857642
0.681592 0.867069
0.686567 0.875585
0.691542 0.883340
0.696517 0.890449
0.701493 0.897003
0.706468 0.903072
0.711443 0.908714
0.716418 0.913976
0.721393 0.918898
0.726368 0.923513
0.731343 0.927850
0.736318 0.931933
0.741294 0.935783
0.746269 0.939419
0.751244 0.942857
0.756219 0.946112
0.761194 0.949195
0.766169 0.952120
0.771144 0.954896
0.776119 0.957531
0.781095 0.960036
0.786070 0.962417
0.791045 0.964681
0.796020 0.966834
0.800995 0.968883
0.805970 0.970832
0.810945 0.972687
0.815920 0.974452
0.820896 0.976131
0.825871 0.977728
0.830846 0.979247
0.835821 0.980692
0.840796 0.982064
0.845771 0.983368
0.850746 0.984606
0.855721 0.985781
0.860697 0.986894
0.865672 0.987949
0.870647 0.988947
0.875622 0.989891
0.880597 0.990782
0.885572 0.991623
0.890547 0.992414
0.895522 0.993158
0.900498 0.993856
0.905473 0.994509
0.910448 0.995120
0.915423 0.995689
0.920398 0.996217
0.925373 0.996706
0.930348 0.997157
0.935323 0.997571
0.940299 0.997949
0.945274 0.998292
0.950249 0.998600
0.955224 0.998876
0.960199 0.999120
0.965174 0.999332
0.970149 0.999513
0.975124 0.999665
0.980100 0.999787
0.985075 0.999881
1.000000 1.000000
1.200000 1.000000
