def _oppositeAngle(p1, p2, p3):
"""_oppositeAngle(p1, p2, p3)
Given the triangle (p1, p2, p3), returns angle at p3 (in radians)"""
a = p1 - p3
b = p2 - p3
c = dot(a, b) / \
math.sqrt(squaredNorm(a)*squaredNorm(b))
if abs(c) < 1:
return math.acos(c)
elif abs(c) > 0:
return 0
return math.pi
def _oppositeAngle(p1, p2, p3):
"""_oppositeAngle(p1, p2, p3)
Given the triangle (p1, p2, p3), returns angle at p3 (in radians)"""
a = p1 - p3
b = p2 - p3
c = dot(a, b) / \
math.sqrt(squaredNorm(a)*squaredNorm(b))
if abs(c) < 1:
return math.acos(c)
elif abs(c) > 0:
return 0
return math.pi
def pruneByMorphologicalSignificance(skel, ratio = 0.1):
for edge in skel.edgeIter():
edge.setFlag(IS_BARB, False)
if edge.startNode().hasDegree(1):
edge.setFlag(IS_BARB, True)
endSide = edge.endSide[0]-edge.endSide[1]
minDist = ratio * numpy.linalg.norm(endSide)
endNormal = Vector2(endSide[1], -endSide[0])
endNormal /= numpy.linalg.norm(endNormal)
for p in edge:
if abs(dot(p - edge[-1], endNormal)) > minDist:
edge.setFlag(IS_BARB, False)
break
if edge.flag(IS_BARB):
continue # no need to test other side
if edge.endNode().hasDegree(1):
edge.setFlag(IS_BARB, True)
startSide = edge.startSide[0]-edge.startSide[1]
minDist = ratio * max(1.0, numpy.linalg.norm(startSide))
startNormal = Vector2(startSide[1], -startSide[0])
startNormal /= numpy.linalg.norm(startNormal)
for p in edge:
if abs(dot(p - edge[0], startNormal)) > minDist:
edge.setFlag(IS_BARB, False)
break
return _pruneBarbsInternal(skel)
def pruneByMorphologicalSignificance(skel, ratio = 0.1):
for edge in skel.edgeIter():
edge.setFlag(IS_BARB, False)
if edge.startNode().hasDegree(1):
edge.setFlag(IS_BARB, True)
endSide = edge.endSide[0]-edge.endSide[1]
minDist = ratio * numpy.linalg.norm(endSide)
endNormal = Vector2(endSide[1], -endSide[0])
endNormal /= numpy.linalg.norm(endNormal)
for p in edge:
if abs(dot(p - edge[-1], endNormal)) > minDist:
edge.setFlag(IS_BARB, False)
break
if edge.flag(IS_BARB):
continue # no need to test other side
if edge.endNode().hasDegree(1):
edge.setFlag(IS_BARB, True)
startSide = edge.startSide[0]-edge.startSide[1]
minDist = ratio * max(1.0, numpy.linalg.norm(startSide))
startNormal = Vector2(startSide[1], -startSide[0])
startNormal /= numpy.linalg.norm(startNormal)
for p in edge:
if abs(dot(p - edge[0], startNormal)) > minDist:
edge.setFlag(IS_BARB, False)
break
return _pruneBarbsInternal(skel)
