TsRegressionPreventer::SetResult:
  adjusted: false
  havePreSegment: true
  preActiveAdjusted: false
  preActiveAdjustedWidth: 1.300000
  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 1.300000, 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('0x1.4cccccccccccdp+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 0.000214
0.024876 0.000337
0.029851 0.000489
0.034826 0.000672
0.039801 0.000886
0.044776 0.001132
0.049751 0.001411
0.054726 0.001724
0.059701 0.002071
0.064677 0.002455
0.069652 0.002876
0.074627 0.003336
0.079602 0.003835
0.084577 0.004376
0.089552 0.004958
0.094527 0.005585
0.099502 0.006257
0.104478 0.006976
0.109453 0.007745
0.114428 0.008564
0.119403 0.009435
0.124378 0.010362
0.129353 0.011346
0.134328 0.012389
0.139303 0.013495
0.144279 0.014665
0.149254 0.015903
0.154229 0.017213
0.159204 0.018596
0.164179 0.020058
0.169154 0.021602
0.174129 0.023232
0.179104 0.024953
0.184080 0.026770
0.189055 0.028689
0.194030 0.030716
0.199005 0.032857
0.203980 0.035120
0.208955 0.037514
0.213930 0.040047
0.218905 0.042729
0.223881 0.045573
0.228856 0.048590
0.233831 0.051797
0.238806 0.055209
0.243781 0.058845
0.248756 0.062729
0.253731 0.066887
0.258706 0.071349
0.263682 0.076154
0.268657 0.081345
0.273632 0.086978
0.278607 0.093124
0.283582 0.099870
0.288557 0.107333
0.293532 0.115673
0.298507 0.125113
0.303483 0.135987
0.308458 0.148836
0.313433 0.164631
0.318408 0.185500
0.323383 0.684222
0.328358 0.704008
0.333333 0.720385
0.338308 0.734481
0.343284 0.746918
0.348259 0.758082
0.353234 0.768231
0.358209 0.777547
0.363184 0.786163
0.368159 0.794183
0.373134 0.801686
0.378109 0.808736
0.383085 0.815385
0.388060 0.821676
0.393035 0.827644
0.398010 0.833321
0.402985 0.838732
0.407960 0.843900
0.412935 0.848844
0.417910 0.853581
0.422886 0.858127
0.427861 0.862494
0.432836 0.866694
0.437811 0.870739
0.442786 0.874638
0.447761 0.878399
0.452736 0.882031
0.457711 0.885540
0.462687 0.888934
0.467662 0.892217
0.472637 0.895396
0.477612 0.898476
0.482587 0.901461
0.487562 0.904356
0.492537 0.907164
0.497512 0.909890
0.502488 0.912537
0.507463 0.915108
0.512438 0.917607
0.517413 0.920035
0.522388 0.922396
0.527363 0.924693
0.532338 0.926927
0.537313 0.929101
0.542289 0.931217
0.547264 0.933276
0.552239 0.935282
0.557214 0.937235
0.562189 0.939137
0.567164 0.940991
0.572139 0.942796
0.577114 0.944556
0.582090 0.946270
0.587065 0.947942
0.592040 0.949570
0.597015 0.951158
0.601990 0.952706
0.606965 0.954215
0.611940 0.955686
0.616915 0.957121
0.621891 0.958519
0.626866 0.959883
0.631841 0.961212
0.636816 0.962509
0.641791 0.963772
0.646766 0.965005
0.651741 0.966206
0.656716 0.967377
0.661692 0.968519
0.666667 0.969632
0.671642 0.970716
0.676617 0.971773
0.681592 0.972804
0.686567 0.973807
0.691542 0.974785
0.696517 0.975738
0.701493 0.976666
0.706468 0.977570
0.711443 0.978449
0.716418 0.979306
0.721393 0.980140
0.726368 0.980951
0.731343 0.981740
0.736318 0.982508
0.741294 0.983255
0.746269 0.983981
0.751244 0.984686
0.756219 0.985372
0.761194 0.986037
0.766169 0.986684
0.771144 0.987311
0.776119 0.987920
0.781095 0.988511
0.786070 0.989083
0.791045 0.989638
0.796020 0.990175
0.800995 0.990695
0.805970 0.991199
0.810945 0.991685
0.815920 0.992156
0.820896 0.992610
0.825871 0.993049
0.830846 0.993472
0.835821 0.993879
0.840796 0.994272
0.845771 0.994649
0.850746 0.995012
0.855721 0.995361
0.860697 0.995695
0.865672 0.996015
0.870647 0.996322
0.875622 0.996614
0.880597 0.996894
0.885572 0.997160
0.890547 0.997413
0.895522 0.997653
0.900498 0.997881
0.905473 0.998095
0.910448 0.998298
0.915423 0.998488
0.920398 0.998667
0.925373 0.998833
0.930348 0.998988
0.935323 0.999131
0.940299 0.999262
0.945274 0.999383
0.950249 0.999492
0.955224 0.999590
0.960199 0.999678
0.965174 0.999754
0.970149 0.999820
0.975124 0.999876
0.980100 0.999921
0.985075 0.999956
1.000000 1.000000
1.200000 1.000000
