forked from bartvdbraak/blender
343 lines
10 KiB
Python
343 lines
10 KiB
Python
# ##### BEGIN GPL LICENSE BLOCK #####
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#
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# This program is free software; you can redistribute it and/or
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# modify it under the terms of the GNU General Public License
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# as published by the Free Software Foundation; either version 2
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# of the License, or (at your option) any later version.
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#
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# This program is distributed in the hope that it will be useful,
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# but WITHOUT ANY WARRANTY; without even the implied warranty of
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# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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# GNU General Public License for more details.
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#
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# You should have received a copy of the GNU General Public License
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# along with this program; if not, write to the Free Software Foundation,
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# Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301, USA.
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#
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# ##### END GPL LICENSE BLOCK #####
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# Filename : PredicatesU1D.py
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# Authors : Fredo Durand, Stephane Grabli, Francois Sillion, Emmanuel Turquin
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# Date : 08/04/2005
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# Purpose : Unary predicates (functors) to be used for 1D elements
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from freestyle import Curvature2DAngleF0D, CurveNatureF1D, DensityF1D, GetCompleteViewMapDensityF1D, \
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GetDirectionalViewMapDensityF1D, GetOccludersF1D, GetProjectedZF1D, GetShapeF1D, GetSteerableViewMapDensityF1D, \
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IntegrationType, ShapeUP1D, TVertex, UnaryPredicate1D
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from Functions1D import pyDensityAnisotropyF1D, pyViewMapGradientNormF1D
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class pyNFirstUP1D(UnaryPredicate1D):
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def __init__(self, n):
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UnaryPredicate1D.__init__(self)
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self.__n = n
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self.__count = 0
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def __call__(self, inter):
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self.__count = self.__count + 1
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if self.__count <= self.__n:
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return 1
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return 0
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class pyHigherLengthUP1D(UnaryPredicate1D):
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def __init__(self,l):
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UnaryPredicate1D.__init__(self)
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self._l = l
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def __call__(self, inter):
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return (inter.length_2d > self._l)
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class pyNatureUP1D(UnaryPredicate1D):
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def __init__(self,nature):
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UnaryPredicate1D.__init__(self)
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self._nature = nature
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self._getNature = CurveNatureF1D()
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def __call__(self, inter):
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if(self._getNature(inter) & self._nature):
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return 1
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return 0
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class pyHigherNumberOfTurnsUP1D(UnaryPredicate1D):
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def __init__(self,n,a):
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UnaryPredicate1D.__init__(self)
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self._n = n
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self._a = a
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def __call__(self, inter):
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count = 0
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func = Curvature2DAngleF0D()
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it = inter.vertices_begin()
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while not it.is_end:
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if func(it) > self._a:
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count = count+1
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if count > self._n:
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return 1
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it.increment()
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return 0
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class pyDensityUP1D(UnaryPredicate1D):
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def __init__(self,wsize,threshold, integration = IntegrationType.MEAN, sampling=2.0):
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UnaryPredicate1D.__init__(self)
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self._wsize = wsize
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self._threshold = threshold
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self._integration = integration
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self._func = DensityF1D(self._wsize, self._integration, sampling)
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def __call__(self, inter):
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if self._func(inter) < self._threshold:
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return 1
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return 0
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class pyLowSteerableViewMapDensityUP1D(UnaryPredicate1D):
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def __init__(self,threshold, level,integration = IntegrationType.MEAN):
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UnaryPredicate1D.__init__(self)
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self._threshold = threshold
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self._level = level
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self._integration = integration
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def __call__(self, inter):
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func = GetSteerableViewMapDensityF1D(self._level, self._integration)
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v = func(inter)
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#print(v)
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if v < self._threshold:
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return 1
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return 0
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class pyLowDirectionalViewMapDensityUP1D(UnaryPredicate1D):
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def __init__(self,threshold, orientation, level,integration = IntegrationType.MEAN):
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UnaryPredicate1D.__init__(self)
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self._threshold = threshold
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self._orientation = orientation
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self._level = level
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self._integration = integration
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def __call__(self, inter):
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func = GetDirectionalViewMapDensityF1D(self._orientation, self._level, self._integration)
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v = func(inter)
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#print(v)
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if v < self._threshold:
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return 1
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return 0
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class pyHighSteerableViewMapDensityUP1D(UnaryPredicate1D):
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def __init__(self,threshold, level,integration = IntegrationType.MEAN):
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UnaryPredicate1D.__init__(self)
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self._threshold = threshold
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self._level = level
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self._integration = integration
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self._func = GetSteerableViewMapDensityF1D(self._level, self._integration)
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def __call__(self, inter):
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v = self._func(inter)
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if v > self._threshold:
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return 1
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return 0
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class pyHighDirectionalViewMapDensityUP1D(UnaryPredicate1D):
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def __init__(self,threshold, orientation, level,integration = IntegrationType.MEAN, sampling=2.0):
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UnaryPredicate1D.__init__(self)
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self._threshold = threshold
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self._orientation = orientation
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self._level = level
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self._integration = integration
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self._sampling = sampling
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def __call__(self, inter):
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func = GetDirectionalViewMapDensityF1D(self._orientation, self._level, self._integration, self._sampling)
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v = func(inter)
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if v > self._threshold:
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return 1
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return 0
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class pyHighViewMapDensityUP1D(UnaryPredicate1D):
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def __init__(self,threshold, level,integration = IntegrationType.MEAN, sampling=2.0):
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UnaryPredicate1D.__init__(self)
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self._threshold = threshold
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self._level = level
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self._integration = integration
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self._sampling = sampling
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self._func = GetCompleteViewMapDensityF1D(self._level, self._integration, self._sampling) # 2.0 is the smpling
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def __call__(self, inter):
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#print("toto")
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#print(func.name)
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#print(inter.name)
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v= self._func(inter)
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if v > self._threshold:
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return 1
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return 0
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class pyDensityFunctorUP1D(UnaryPredicate1D):
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def __init__(self,wsize,threshold, functor, funcmin=0.0, funcmax=1.0, integration = IntegrationType.MEAN):
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UnaryPredicate1D.__init__(self)
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self._wsize = wsize
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self._threshold = float(threshold)
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self._functor = functor
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self._funcmin = float(funcmin)
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self._funcmax = float(funcmax)
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self._integration = integration
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def __call__(self, inter):
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func = DensityF1D(self._wsize, self._integration)
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res = self._functor(inter)
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k = (res-self._funcmin)/(self._funcmax-self._funcmin)
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if func(inter) < self._threshold*k:
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return 1
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return 0
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class pyZSmallerUP1D(UnaryPredicate1D):
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def __init__(self,z, integration=IntegrationType.MEAN):
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UnaryPredicate1D.__init__(self)
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self._z = z
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self._integration = integration
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def __call__(self, inter):
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func = GetProjectedZF1D(self._integration)
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if func(inter) < self._z:
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return 1
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return 0
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class pyIsOccludedByUP1D(UnaryPredicate1D):
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def __init__(self,id):
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UnaryPredicate1D.__init__(self)
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self._id = id
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def __call__(self, inter):
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func = GetShapeF1D()
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shapes = func(inter)
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for s in shapes:
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if(s.id == self._id):
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return 0
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it = inter.vertices_begin()
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itlast = inter.vertices_end()
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itlast.decrement()
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v = it.object
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vlast = itlast.object
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tvertex = v.viewvertex
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if type(tvertex) is TVertex:
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#print("TVertex: [ ", tvertex.id.first, ",", tvertex.id.second," ]")
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eit = tvertex.edges_begin()
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while not eit.is_end:
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ve, incoming = eit.object
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if ve.id == self._id:
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return 1
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#print("-------", ve.id.first, "-", ve.id.second)
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eit.increment()
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tvertex = vlast.viewvertex
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if type(tvertex) is TVertex:
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#print("TVertex: [ ", tvertex.id.first, ",", tvertex.id.second," ]")
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eit = tvertex.edges_begin()
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while not eit.is_end:
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ve, incoming = eit.object
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if ve.id == self._id:
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return 1
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#print("-------", ve.id.first, "-", ve.id.second)
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eit.increment()
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return 0
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class pyIsInOccludersListUP1D(UnaryPredicate1D):
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def __init__(self,id):
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UnaryPredicate1D.__init__(self)
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self._id = id
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def __call__(self, inter):
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func = GetOccludersF1D()
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occluders = func(inter)
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for a in occluders:
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if a.id == self._id:
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return 1
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return 0
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class pyIsOccludedByItselfUP1D(UnaryPredicate1D):
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def __init__(self):
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UnaryPredicate1D.__init__(self)
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self.__func1 = GetOccludersF1D()
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self.__func2 = GetShapeF1D()
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def __call__(self, inter):
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lst1 = self.__func1(inter)
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lst2 = self.__func2(inter)
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for vs1 in lst1:
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for vs2 in lst2:
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if vs1.id == vs2.id:
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return 1
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return 0
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class pyIsOccludedByIdListUP1D(UnaryPredicate1D):
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def __init__(self, idlist):
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UnaryPredicate1D.__init__(self)
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self._idlist = idlist
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self.__func1 = GetOccludersF1D()
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def __call__(self, inter):
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lst1 = self.__func1(inter)
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for vs1 in lst1:
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for _id in self._idlist:
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if vs1.id == _id:
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return 1
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return 0
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class pyShapeIdListUP1D(UnaryPredicate1D):
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def __init__(self,idlist):
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UnaryPredicate1D.__init__(self)
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self._idlist = idlist
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self._funcs = []
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for _id in idlist :
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self._funcs.append(ShapeUP1D(_id.first, _id.second))
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def __call__(self, inter):
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for func in self._funcs :
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if func(inter) == 1:
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return 1
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return 0
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## deprecated
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class pyShapeIdUP1D(UnaryPredicate1D):
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def __init__(self, _id):
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UnaryPredicate1D.__init__(self)
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self._id = _id
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def __call__(self, inter):
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func = GetShapeF1D()
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shapes = func(inter)
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for a in shapes:
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if a.id == self._id:
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return 1
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return 0
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class pyHighDensityAnisotropyUP1D(UnaryPredicate1D):
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def __init__(self,threshold, level, sampling=2.0):
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UnaryPredicate1D.__init__(self)
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self._l = threshold
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self.func = pyDensityAnisotropyF1D(level, IntegrationType.MEAN, sampling)
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def __call__(self, inter):
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return (self.func(inter) > self._l)
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class pyHighViewMapGradientNormUP1D(UnaryPredicate1D):
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def __init__(self,threshold, l, sampling=2.0):
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UnaryPredicate1D.__init__(self)
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self._threshold = threshold
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self._GetGradient = pyViewMapGradientNormF1D(l, IntegrationType.MEAN)
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def __call__(self, inter):
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gn = self._GetGradient(inter)
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#print(gn)
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return (gn > self._threshold)
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class pyDensityVariableSigmaUP1D(UnaryPredicate1D):
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def __init__(self,functor, sigmaMin,sigmaMax, lmin, lmax, tmin, tmax, integration = IntegrationType.MEAN, sampling=2.0):
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UnaryPredicate1D.__init__(self)
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self._functor = functor
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self._sigmaMin = float(sigmaMin)
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self._sigmaMax = float(sigmaMax)
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self._lmin = float(lmin)
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self._lmax = float(lmax)
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self._tmin = tmin
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self._tmax = tmax
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self._integration = integration
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self._sampling = sampling
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def __call__(self, inter):
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sigma = (self._sigmaMax-self._sigmaMin)/(self._lmax-self._lmin)*(self._functor(inter)-self._lmin) + self._sigmaMin
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t = (self._tmax-self._tmin)/(self._lmax-self._lmin)*(self._functor(inter)-self._lmin) + self._tmin
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if sigma < self._sigmaMin:
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sigma = self._sigmaMin
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self._func = DensityF1D(sigma, self._integration, self._sampling)
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d = self._func(inter)
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if d < t:
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return 1
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return 0
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class pyClosedCurveUP1D(UnaryPredicate1D):
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def __call__(self, inter):
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it = inter.vertices_begin()
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itlast = inter.vertices_end()
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itlast.decrement()
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vlast = itlast.object
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v = it.object
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#print(v.id.first, v.id.second)
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#print(vlast.id.first, vlast.id.second)
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if v.id == vlast.id:
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return 1
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return 0
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