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Resample: switch from approximate() to interpolate, which seems to be more stable

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DeepSOIC 2015-11-18 02:47:18 +03:00
parent c0aca13264
commit dda1d5c3d2
1 changed files with 14 additions and 8 deletions
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22
latticeInterpolatorUtil.py
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@ -36,22 +36,28 @@ class InterpolateF:
# we want to make sure the smallest X step is way larger than possible # we want to make sure the smallest X step is way larger than possible
# Y step, so only X points affect knotting. This is what we are using # Y step, so only X points affect knotting. This is what we are using
# _x_multiplicator for - it is the scaling applied to X coordinates of # _y_multiplicator for - it is the scaling applied to Y coordinates of
# the interpolation points. Doing this will make u parameter of the # the interpolation points. Doing this will make u parameter of the
# spline equivalent to X coordinate. # spline equivalent to X coordinate.
self._x_multiplicator = 1e20*(y_max - y_min)/min_x_step
# This fixes nan outut if y span is zer length
if y_max - y_min < 1e-40: if y_max - y_min < 1e-40:
self._x_multiplicator = 1.0 self._y_multiplicator = 1.0
else:
self._y_multiplicator = 1e-20*min_x_step/(y_max - y_min)
self._y_demultiplicator = 1.0/self._y_multiplicator
# create the spline # create the spline
if not hasattr(self,"_spline"): if not hasattr(self,"_spline"):
self._spline = Part.BSplineCurve() self._spline = Part.BSplineCurve()
spline = self._spline spline = self._spline
points_for_spline = [App.Vector(XPoints[i]*self._x_multiplicator, YPoints[i], 0.0) for i in range(0,len(XPoints))] points_for_spline = [App.Vector(XPoints[i], YPoints[i]*self._y_multiplicator, 0.0) for i in range(0,len(XPoints))]
spline.approximate(points_for_spline) spline.interpolate(points_for_spline)
#precache some scaling values for faster calculation of value()
self._u1 = spline.FirstParameter
self._u2 = spline.LastParameter
self._x_to_u_scale = (self._u2 - self._u1) / (self._x_max - self._x_min)
def value(self, x): def value(self, x):
return self._spline.value( (x - self._x_min) / (self._x_max - self._x_min) ).y return self._spline.value( self._u1 + x*self._x_to_u_scale ).y * self._y_demultiplicator