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path: root/release/scripts/freestyle/style_modules/PredicatesU1D.py
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-rw-r--r--release/scripts/freestyle/style_modules/PredicatesU1D.py358
1 files changed, 358 insertions, 0 deletions
diff --git a/release/scripts/freestyle/style_modules/PredicatesU1D.py b/release/scripts/freestyle/style_modules/PredicatesU1D.py
new file mode 100644
index 00000000000..3938bbb2d02
--- /dev/null
+++ b/release/scripts/freestyle/style_modules/PredicatesU1D.py
@@ -0,0 +1,358 @@
+from freestyle_init import *
+from Functions1D import *
+
+count = 0
+class pyNFirstUP1D(UnaryPredicate1D):
+ def __init__(self, n):
+ UnaryPredicate1D.__init__(self)
+ self.__n = n
+ def __call__(self, inter):
+ global count
+ count = count + 1
+ if count <= self.__n:
+ return 1
+ return 0
+
+class pyHigherLengthUP1D(UnaryPredicate1D):
+ def __init__(self,l):
+ UnaryPredicate1D.__init__(self)
+ self._l = l
+ def getName(self):
+ return "HigherLengthUP1D"
+ def __call__(self, inter):
+ return (inter.length_2d > self._l)
+
+class pyNatureUP1D(UnaryPredicate1D):
+ def __init__(self,nature):
+ UnaryPredicate1D.__init__(self)
+ self._nature = nature
+ self._getNature = CurveNatureF1D()
+ def getName(self):
+ return "pyNatureUP1D"
+ def __call__(self, inter):
+ if(self._getNature(inter) & self._nature):
+ return 1
+ return 0
+
+class pyHigherNumberOfTurnsUP1D(UnaryPredicate1D):
+ def __init__(self,n,a):
+ UnaryPredicate1D.__init__(self)
+ self._n = n
+ self._a = a
+ def getName(self):
+ return "HigherNumberOfTurnsUP1D"
+ def __call__(self, inter):
+ count = 0
+ func = Curvature2DAngleF0D()
+ it = inter.vertices_begin()
+ while not it.is_end:
+ if func(it) > self._a:
+ count = count+1
+ if count > self._n:
+ return 1
+ it.increment()
+ return 0
+
+class pyDensityUP1D(UnaryPredicate1D):
+ def __init__(self,wsize,threshold, integration = IntegrationType.MEAN, sampling=2.0):
+ UnaryPredicate1D.__init__(self)
+ self._wsize = wsize
+ self._threshold = threshold
+ self._integration = integration
+ self._func = DensityF1D(self._wsize, self._integration, sampling)
+ def getName(self):
+ return "pyDensityUP1D"
+ def __call__(self, inter):
+ if self._func(inter) < self._threshold:
+ return 1
+ return 0
+
+class pyLowSteerableViewMapDensityUP1D(UnaryPredicate1D):
+ def __init__(self,threshold, level,integration = IntegrationType.MEAN):
+ UnaryPredicate1D.__init__(self)
+ self._threshold = threshold
+ self._level = level
+ self._integration = integration
+ def getName(self):
+ return "pyLowSteerableViewMapDensityUP1D"
+ def __call__(self, inter):
+ func = GetSteerableViewMapDensityF1D(self._level, self._integration)
+ v = func(inter)
+ print(v)
+ if v < self._threshold:
+ return 1
+ return 0
+
+class pyLowDirectionalViewMapDensityUP1D(UnaryPredicate1D):
+ def __init__(self,threshold, orientation, level,integration = IntegrationType.MEAN):
+ UnaryPredicate1D.__init__(self)
+ self._threshold = threshold
+ self._orientation = orientation
+ self._level = level
+ self._integration = integration
+ def getName(self):
+ return "pyLowDirectionalViewMapDensityUP1D"
+ def __call__(self, inter):
+ func = GetDirectionalViewMapDensityF1D(self._orientation, self._level, self._integration)
+ v = func(inter)
+ #print(v)
+ if v < self._threshold:
+ return 1
+ return 0
+
+class pyHighSteerableViewMapDensityUP1D(UnaryPredicate1D):
+ def __init__(self,threshold, level,integration = IntegrationType.MEAN):
+ UnaryPredicate1D.__init__(self)
+ self._threshold = threshold
+ self._level = level
+ self._integration = integration
+ self._func = GetSteerableViewMapDensityF1D(self._level, self._integration)
+ def getName(self):
+ return "pyHighSteerableViewMapDensityUP1D"
+ def __call__(self, inter):
+ v = self._func(inter)
+ if v > self._threshold:
+ return 1
+ return 0
+
+class pyHighDirectionalViewMapDensityUP1D(UnaryPredicate1D):
+ def __init__(self,threshold, orientation, level,integration = IntegrationType.MEAN, sampling=2.0):
+ UnaryPredicate1D.__init__(self)
+ self._threshold = threshold
+ self._orientation = orientation
+ self._level = level
+ self._integration = integration
+ self._sampling = sampling
+ def getName(self):
+ return "pyLowDirectionalViewMapDensityUP1D"
+ def __call__(self, inter):
+ func = GetDirectionalViewMapDensityF1D(self._orientation, self._level, self._integration, self._sampling)
+ v = func(inter)
+ if v > self._threshold:
+ return 1
+ return 0
+
+class pyHighViewMapDensityUP1D(UnaryPredicate1D):
+ def __init__(self,threshold, level,integration = IntegrationType.MEAN, sampling=2.0):
+ UnaryPredicate1D.__init__(self)
+ self._threshold = threshold
+ self._level = level
+ self._integration = integration
+ self._sampling = sampling
+ self._func = GetCompleteViewMapDensityF1D(self._level, self._integration, self._sampling) # 2.0 is the smpling
+ def getName(self):
+ return "pyHighViewMapDensityUP1D"
+ def __call__(self, inter):
+ #print("toto")
+ #print(func.getName())
+ #print(inter.getExactTypeName())
+ v= self._func(inter)
+ if v > self._threshold:
+ return 1
+ return 0
+
+class pyDensityFunctorUP1D(UnaryPredicate1D):
+ def __init__(self,wsize,threshold, functor, funcmin=0.0, funcmax=1.0, integration = IntegrationType.MEAN):
+ UnaryPredicate1D.__init__(self)
+ self._wsize = wsize
+ self._threshold = float(threshold)
+ self._functor = functor
+ self._funcmin = float(funcmin)
+ self._funcmax = float(funcmax)
+ self._integration = integration
+ def getName(self):
+ return "pyDensityFunctorUP1D"
+ def __call__(self, inter):
+ func = DensityF1D(self._wsize, self._integration)
+ res = self._functor(inter)
+ k = (res-self._funcmin)/(self._funcmax-self._funcmin)
+ if func(inter) < self._threshold*k:
+ return 1
+ return 0
+
+class pyZSmallerUP1D(UnaryPredicate1D):
+ def __init__(self,z, integration=IntegrationType.MEAN):
+ UnaryPredicate1D.__init__(self)
+ self._z = z
+ self._integration = integration
+ def getName(self):
+ return "pyZSmallerUP1D"
+ def __call__(self, inter):
+ func = GetProjectedZF1D(self._integration)
+ if func(inter) < self._z:
+ return 1
+ return 0
+
+class pyIsOccludedByUP1D(UnaryPredicate1D):
+ def __init__(self,id):
+ UnaryPredicate1D.__init__(self)
+ self._id = id
+ def getName(self):
+ return "pyIsOccludedByUP1D"
+ def __call__(self, inter):
+ func = GetShapeF1D()
+ shapes = func(inter)
+ for s in shapes:
+ if(s.id == self._id):
+ return 0
+ it = inter.vertices_begin()
+ itlast = inter.vertices_end()
+ itlast.decrement()
+ v = it.object
+ vlast = itlast.object
+ tvertex = v.viewvertex
+ if type(tvertex) is TVertex:
+ print("TVertex: [ ", tvertex.id.first, ",", tvertex.id.second," ]")
+ eit = tvertex.edges_begin()
+ while not eit.is_end:
+ ve, incoming = eit.object
+ if ve.id == self._id:
+ return 1
+ print("-------", ve.id.first, "-", ve.id.second)
+ eit.increment()
+ tvertex = vlast.viewvertex
+ if type(tvertex) is TVertex:
+ print("TVertex: [ ", tvertex.id.first, ",", tvertex.id.second," ]")
+ eit = tvertex.edges_begin()
+ while not eit.is_end:
+ ve, incoming = eit.object
+ if ve.id == self._id:
+ return 1
+ print("-------", ve.id.first, "-", ve.id.second)
+ eit.increment()
+ return 0
+
+class pyIsInOccludersListUP1D(UnaryPredicate1D):
+ def __init__(self,id):
+ UnaryPredicate1D.__init__(self)
+ self._id = id
+ def getName(self):
+ return "pyIsInOccludersListUP1D"
+ def __call__(self, inter):
+ func = GetOccludersF1D()
+ occluders = func(inter)
+ for a in occluders:
+ if a.id == self._id:
+ return 1
+ return 0
+
+class pyIsOccludedByItselfUP1D(UnaryPredicate1D):
+ def __init__(self):
+ UnaryPredicate1D.__init__(self)
+ self.__func1 = GetOccludersF1D()
+ self.__func2 = GetShapeF1D()
+ def getName(self):
+ return "pyIsOccludedByItselfUP1D"
+ def __call__(self, inter):
+ lst1 = self.__func1(inter)
+ lst2 = self.__func2(inter)
+ for vs1 in lst1:
+ for vs2 in lst2:
+ if vs1.id == vs2.id:
+ return 1
+ return 0
+
+class pyIsOccludedByIdListUP1D(UnaryPredicate1D):
+ def __init__(self, idlist):
+ UnaryPredicate1D.__init__(self)
+ self._idlist = idlist
+ self.__func1 = GetOccludersF1D()
+ def getName(self):
+ return "pyIsOccludedByIdListUP1D"
+ def __call__(self, inter):
+ lst1 = self.__func1(inter)
+ for vs1 in lst1:
+ for _id in self._idlist:
+ if vs1.id == _id:
+ return 1
+ return 0
+
+class pyShapeIdListUP1D(UnaryPredicate1D):
+ def __init__(self,idlist):
+ UnaryPredicate1D.__init__(self)
+ self._idlist = idlist
+ self._funcs = []
+ for _id in idlist :
+ self._funcs.append(ShapeUP1D(_id.first, _id.second))
+ def getName(self):
+ return "pyShapeIdUP1D"
+ def __call__(self, inter):
+ for func in self._funcs :
+ if func(inter) == 1:
+ return 1
+ return 0
+
+## deprecated
+class pyShapeIdUP1D(UnaryPredicate1D):
+ def __init__(self, _id):
+ UnaryPredicate1D.__init__(self)
+ self._id = _id
+ def getName(self):
+ return "pyShapeIdUP1D"
+ def __call__(self, inter):
+ func = GetShapeF1D()
+ shapes = func(inter)
+ for a in shapes:
+ if a.id == self._id:
+ return 1
+ return 0
+
+class pyHighDensityAnisotropyUP1D(UnaryPredicate1D):
+ def __init__(self,threshold, level, sampling=2.0):
+ UnaryPredicate1D.__init__(self)
+ self._l = threshold
+ self.func = pyDensityAnisotropyF1D(level, IntegrationType.MEAN, sampling)
+ def getName(self):
+ return "pyHighDensityAnisotropyUP1D"
+ def __call__(self, inter):
+ return (self.func(inter) > self._l)
+
+class pyHighViewMapGradientNormUP1D(UnaryPredicate1D):
+ def __init__(self,threshold, l, sampling=2.0):
+ UnaryPredicate1D.__init__(self)
+ self._threshold = threshold
+ self._GetGradient = pyViewMapGradientNormF1D(l, IntegrationType.MEAN)
+ def getName(self):
+ return "pyHighViewMapGradientNormUP1D"
+ def __call__(self, inter):
+ gn = self._GetGradient(inter)
+ #print(gn)
+ return (gn > self._threshold)
+
+class pyDensityVariableSigmaUP1D(UnaryPredicate1D):
+ def __init__(self,functor, sigmaMin,sigmaMax, lmin, lmax, tmin, tmax, integration = IntegrationType.MEAN, sampling=2.0):
+ UnaryPredicate1D.__init__(self)
+ self._functor = functor
+ self._sigmaMin = float(sigmaMin)
+ self._sigmaMax = float(sigmaMax)
+ self._lmin = float(lmin)
+ self._lmax = float(lmax)
+ self._tmin = tmin
+ self._tmax = tmax
+ self._integration = integration
+ self._sampling = sampling
+ def getName(self):
+ return "pyDensityUP1D"
+ def __call__(self, inter):
+ sigma = (self._sigmaMax-self._sigmaMin)/(self._lmax-self._lmin)*(self._functor(inter)-self._lmin) + self._sigmaMin
+ t = (self._tmax-self._tmin)/(self._lmax-self._lmin)*(self._functor(inter)-self._lmin) + self._tmin
+ if sigma < self._sigmaMin:
+ sigma = self._sigmaMin
+ self._func = DensityF1D(sigma, self._integration, self._sampling)
+ d = self._func(inter)
+ if d < t:
+ return 1
+ return 0
+
+class pyClosedCurveUP1D(UnaryPredicate1D):
+ def __call__(self, inter):
+ it = inter.vertices_begin()
+ itlast = inter.vertices_end()
+ itlast.decrement()
+ vlast = itlast.object
+ v = it.object
+ print(v.id.first, v.id.second)
+ print(vlast.id.first, vlast.id.second)
+ if v.id == vlast.id:
+ return 1
+ return 0
generated by cgit v1.2.3 (git 2.25.1) at 2024-07-20 20:08:06 +0300