def _fitRotation_lsq(Rparams, gIs,angles0, U,wavelength):
out = []
Rmat = Rotations.rotMatOfExpMap(Rparams)
Fmat = dot(Rmat,U)
for i in range(len(gIs)):
gI,angles = gIs[i], angles0[i]
r_i = _fitR_residual(angles,gI, Fmat, wavelength)
if weighting:
weight = uncertainty_analysis.propagateUncertainty(_fitR_residual, weighting[i], 1e-8,angles,gI,Fmat,wavelength)
maxiter = 100
ct = 0
while weight==0:
weight = uncertainty_analysis.propagateUncertainty(_fitR_residual, weighting[i], 1e-8,angles,gI,Fmat,wavelength)
ct+=1
if ct>=maxiter:
print 'zero weight error, i = ',i
weight = 1
break
else:
weight = 1.
out.append(r_i/weight)
if weight == 0:
print 'wefiht0',i,weighting[i],Fmat
out = num.array(out)
# print out
return out
def _fitC(Cparams,gIs,angles,wavelength):
Cmat = gw.vec_to_sym(Cparams)
invCmat = inv(Cmat)
out = []
for i in range(len(gIs)):
gI = gIs[i]
angCOM = angles[i] #, spot in gI_spots:
r_i = _fitC_residual(angCOM,gI, invCmat, wavelength)
if weighting:
weight = uncertainty_analysis.propagateUncertainty(_fitC_residual, weighting[i], 1e-8,angCOM,gI,invCmat,wavelength)
else:
weight = 1
out.append(r_i/weight)
return num.array(out)