def addcellpeaks(self, limit=None):
"""
Adds unit cell predicted peaks for fitting against
Optional arg limit gives highest angle to use
Depends on parameters:
'cell__a','cell__b','cell__c', 'wavelength' # in angstrom
'cell_alpha','cell_beta','cell_gamma' # in degrees
'cell_lattice_[P,A,B,C,I,F,R]'
"""
#
# Given unit cell, wavelength and distance, compute the radial positions
# in microns of the unit cell peaks
#
pars = self.parameterobj.get_parameters()
cell = [
pars[name] for name in [
'cell__a', 'cell__b', 'cell__c', 'cell_alpha', 'cell_beta',
'cell_gamma'
]
]
lattice = pars['cell_lattice_[P,A,B,C,I,F,R]']
if "tth" not in self.colfile.titles:
self.compute_tth_eta()
# Find last peak in radius
if limit is None:
highest = numpy.maximum.reduce(self.getcolumn("tth"))
else:
highest = limit
w = pars['wavelength']
ds = 2 * numpy.sin(transform.radians(highest) / 2.) / w
self.dslimit = ds
self.unitcell = unitcell.unitcell(cell, lattice)
# If the space group is provided use xfab for generate unique hkls
if 'cell_sg' in pars:
self.theorypeaks = self.unitcell.gethkls_xfab(ds, pars['cell_sg'])
tths = []
self.theoryds = []
for i in range(len(self.theorypeaks)):
tths.append(2 * numpy.arcsin(w * self.theorypeaks[i][0] / 2.))
self.theoryds.append(self.theorypeaks[i][0])
else:
# HO: I have removed this part as it seems redundant ringds also calls gethkls
# JPW: It was not redundant. theorypeaks is not defined anywhere else and you
# can't write a g-vector file without it.
self.theorypeaks = self.unitcell.gethkls(ds)
self.unitcell.makerings(ds)
self.theoryds = self.unitcell.ringds
tths = [
numpy.arcsin(w * dstar / 2) * 2
for dstar in self.unitcell.ringds
]
self.theorytth = transform.degrees(numpy.array(tths))
def gof(self, args):
""" Compute how good is the fit of obs/calc peak positions in tth """
self.applyargs(args)
# Here, pars is a dictionary of name/value pairs to pass to compute_tth_eta
tth, eta = self.compute_tth_eta()
w = self.parameterobj.get("wavelength")
gof = 0.
npeaks = 0
for i in range(len(self.tthc)):# (twotheta_rad_cell.shape[0]):
self.tthc[i] = transform.degrees(math.asin(self.fitds[i] * w / 2) * 2)
diff = numpy.take(tth, self.indices[i]) - self.tthc[i]
# print "peak",i,"diff",maximum.reduce(diff),minimum.reduce(diff)
gof = gof + numpy.sum(diff * diff)
npeaks = npeaks + len(diff)
gof = gof / npeaks
return gof * 1e6