def fitDataRigidScaleNoCorr_TwoSurfaces( X1,X2,data1,data2, xtol=1e-5, maxfev=0, t0=None ): """ fit list of points X to list of points data by minimising least squares distance between each point in X and closest neighbour in data """ if t0==None: t0 = scipy.array([0.0,0.0,0.0,0.0,0.0,0.0,1.0]) data1Tree = cKDTree( data1 ) data2Tree = cKDTree( data2 ) X1 = scipy.array(X1) X2 = scipy.array(X2) def obj( t ): x1R = transformRigid3D( X1, t[:6] ) x1RS = transformScale3D( x1R, scipy.ones(3)*t[6] ) d1 = data1Tree.query( list(x1RS) )[0] x2R = transformRigid3D( X2, t[:6] ) x2RS = transformScale3D( x2R, scipy.ones(3)*t[6] ) d2 = data2Tree.query( list(x2RS) )[0] d=concatenate((d1,d2),0) return d*d tOpt = leastsq( obj, t0, xtol=xtol, maxfev=maxfev )[0] X1Opt = transformRigid3D( X1, tOpt[:6] ) X2Opt = transformRigid3D( X2, tOpt[:6] ) X1Opt = transformScale3D( X1Opt, tOpt[6:] ) X2Opt = transformScale3D( X2Opt, tOpt[6:] ) return tOpt, X1Opt,X2Opt
def obj( t ): x1R = transformRigid3D( X1, t[:6] ) x1RS = transformScale3D( x1R, scipy.ones(3)*t[6] ) d1 = data1Tree.query( list(x1RS) )[0] x2R = transformRigid3D( X2, t[:6] ) x2RS = transformScale3D( x2R, scipy.ones(3)*t[6] ) d2 = data2Tree.query( list(x2RS) )[0] d=concatenate((d1,d2),0) return d*d
def obj( t ): x1R = transformRigid3D( X1, t[:6] ) x1SR = transformScale3D( x1R, t[6:] ) x1SRTree = cKDTree(x1SR) d1 = x1SRTree.query( list(data1) )[0] x2R = transformRigid3D( X2, t[:6] ) x2SR = transformScale3D( x2R, t[6:] ) x2SRTree = cKDTree(x2SR) d2 = x2SRTree.query( list(data2) )[0] d=concatenate((d1,d2),0) return d*d
def obj( t ): x1S = transformScale3D( X1, t[6:] ) x1RS = transformRigid3D( x1S, t[:6] ) x1RSTree = cKDTree(x1RS) d1 = x1RSTree.query( list(data1) )[0] x2S = transformScale3D( X2, t[6:] ) x2RS = transformRigid3D( x2S, t[:6] ) x2RSTree = cKDTree(x2RS) d2 = x2RSTree.query( list(data2) )[0] d=concatenate((d1,d2),0) #print t SSQ.append(scipy.sum(d*d)) return d*d
def fitDataAnisotropicScaleRigidNoCorr_ModelTree_TwoSurfaces(X1, X2, data1, data2, filename, xtol=1e-5, maxfev=0,
t0=None):
""" fit list of points X to list of points data by minimising
least squares distance between each point in X and closest neighbour
in data
"""
if t0 == None:
t0 = scipy.array([0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 1.0, 1.0, 1.0])
data1 = scipy.array(data1)
data2 = scipy.array(data2)
SSQ = []
def obj(t):
x1S = transformScale3D(X1, t[6:])
x1RS = transformRigid3D(x1S, t[:6])
x1RSTree = cKDTree(x1RS)
d1 = x1RSTree.query(list(data1))[0]
x2S = transformScale3D(X2, t[6:])
x2RS = transformRigid3D(x2S, t[:6])
x2RSTree = cKDTree(x2RS)
d2 = x2RSTree.query(list(data2))[0]
d = concatenate((d1, d2), 0)
#print t
SSQ.append(scipy.sum(d * d))
return d * d
[tOpt, err] = leastsq(obj, t0, xtol=xtol, maxfev=maxfev)
X1Opt = transformScale3D(X1, tOpt[6:])
X2Opt = transformScale3D(X2, tOpt[6:])
X1Opt = transformRigid3DFinal(X1Opt, tOpt[:6])
X2Opt = transformRigid3DFinal(X2Opt, tOpt[:6])
#t_translate_scale = []
#t_translate_scale[0:3] = tOpt[0:3]
#t_translate_scale[3:5] = tOpt[6:]
#print t_translate_scale
print tOpt
writeTransformation_Scaling_Translation(tOpt, filename)
#writeTransformation_Scaling_Translation(t_translate_scale, filename)
#writeTransformation_Scaling(tOpt[6:],filename)
#print tOpt
#print 'Initial SSQ'
#print SSQ[0]
print 'Final SSQ'
Final_SSQ = scipy.sum(obj(tOpt))
#print SSQ
print Final_SSQ
return tOpt, X1Opt, X2Opt
def fitDataRigidAnisotropicScaleNoCorr_ModelTree_TwoSurfaces( X1,X2, data1,data2, filename,xtol=1e-5, maxfev=0, t0=None): """ fit list of points X to list of points data by minimising least squares distance between each point in X and closest neighbour in data """ if t0==None: t0 = scipy.array([0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,1.0]) data1 = scipy.array(data1) data2 = scipy.array(data2) def obj( t ): x1R = transformRigid3D( X1, t[:6] ) x1SR = transformScale3D( x1R, t[6:] ) x1SRTree = cKDTree(x1SR) d1 = x1SRTree.query( list(data1) )[0] x2R = transformRigid3D( X2, t[:6] ) x2SR = transformScale3D( x2R, t[6:] ) x2SRTree = cKDTree(x2SR) d2 = x2SRTree.query( list(data2) )[0] d=concatenate((d1,d2),0) return d*d tOpt = leastsq( obj, t0, xtol=xtol, maxfev=maxfev )[0] X1Opt = transformRigid3DFinal( X1, tOpt[:6] ) X2Opt = transformRigid3DFinal( X2, tOpt[:6] ) X1Opt = transformScale3D( X1Opt, tOpt[6:] ) X2Opt = transformScale3D( X2Opt, tOpt[6:] ) writeTransformation_Scaling(tOpt[6:],filename) print 'Final SSQ' Final_SSQ=scipy.sum(obj(tOpt)) print Final_SSQ return tOpt, X1Opt,X2Opt
def fitDataRigidAnisotropicScaleNoCorr_ModelTree( X, data, xtol=1e-5, maxfev=0, t0=None ): """ fit list of points X to list of points data by minimising least squares distance between each point in X and closest neighbour in data """ if t0==None: t0 = scipy.array([0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,1.0]) data = scipy.array(data) def obj( t ): xR = transformRigid3D( X, t[:6] ) xRS = transformScale3D( xR, t[6:] ) xRSTree = cKDTree(xRS) d = xRSTree.query( list(data) )[0] return d*d tOpt = leastsq( obj, t0, xtol=xtol, maxfev=maxfev )[0] XOpt = transformRigid3DFinal( X, tOpt[:6] ) XOpt = transformScale3D( XOpt, tOpt[6:] ) return tOpt, XOpt
def fitDataRigidScaleNoCorr( X, data, xtol=1e-5, maxfev=0, t0=None ): """ fit list of points X to list of points data by minimising least squares distance between each point in X and closest neighbour in data """ if t0==None: t0 = scipy.array([0.0,0.0,0.0,0.0,0.0,0.0,1.0]) dataTree = cKDTree( data ) X = scipy.array(X) def obj( t ): xR = transformRigid3D( X, t[:6] ) xRS = transformScale3D( xR, scipy.ones(3)*t[6] ) d = dataTree.query( list(xRS) )[0] #~ print d.mean() return d*d tOpt = leastsq( obj, t0, xtol=xtol, maxfev=maxfev )[0] XOpt = transformRigid3D( X, tOpt[:6] ) XOpt = transformScale3D( XOpt, tOpt[6:] ) return tOpt, XOpt
def obj( t ): xR = transformRigid3D( X, t[:6] ) xRS = transformScale3D( xR, t[6:] ) xRSTree = cKDTree(xRS) d = xRSTree.query( list(data) )[0] return d*d
def obj( t ): xR = transformRigid3D( X, t[:6] ) xRS = transformScale3D( xR, t[6:]) d = dataTree.query( list(xRS) )[0] #~ print d.mean() return d*d
