peaks = from_unitcell(x.mean(axis=0),counts.mean(axis=0),material.unit_cell,
material.space_group,qmin,qmax,name=material.name,
ymin_on_ymax=ymin_on_ymax)
else:
peaks=[]
for mat in material:
peaks.extend(from_unitcell(x.mean(axis=0),counts.mean(axis=0),mat.unit_cell,
mat.space_group,qmin,qmax,name=mat.name,
ymin_on_ymax=ymin_on_ymax))
print 'fitting %i peaks'%len(peaks)
print [p.name for p in peaks]
fc = FitterCollection()
fc.create_many(['element_%i'%i for i in range(counts.shape[0])],x,peaks,**kwargs)
fc.backup()
fc(counts,reestimate=False)
yield fc.lastfit_condensed,fc.lastresult_condensed,info
for counts,info in source:
fc.restore()
fc(counts,reestimate=reestimate)
yield fc.lastfit_condensed,fc.lastresult_condensed,info
def calcstrain(source,phi,Q0=None,allow_shear=True):
if len(phi) > 2:
take = np.ones(len(phi)).astype(bool)
take[5] = take[8] = False
else:
take=np.ones(2).astype(bool)
