def mean_ia(inp,limit,only=None):
"""
Calculate the internal angle for each peak and store in inp.mena_ia[inp.no_grains][inp.nrefl[i]]
Jette Oddershede Januar 2009
"""
import build_fcn
build_fcn.FCN(inp)
import fcn
reload(fcn)
delete = 0
for i in range(inp.no_grains):
if i+1 in inp.fit['skip']:
pass
else:
rod = n.array([inp.rod[i][0]+inp.values['rodx%s' %i],inp.rod[i][1]+inp.values['rody%s' %i],inp.rod[i][2]+inp.values['rodz%s' %i]])
for j in range(inp.nrefl[i]-1,-1,-1):
Omega = tools.form_omega_mat_general(inp.w[inp.id[i][j]]*n.pi/180,inp.values['wx']*n.pi/180,inp.values['wy']*n.pi/180)
gexp = fcn.gexp(inp.w[inp.id[i][j]],inp.dety[inp.id[i][j]],inp.detz[inp.id[i][j]],
inp.values['wx'],inp.values['wy'],inp.values['tx'],inp.values['ty'],inp.values['tz'],
inp.values['py'],inp.values['pz'],inp.values['cy'],inp.values['cz'],inp.values['L'],
inp.values['x%s' %i],inp.values['y%s' %i],inp.values['z%s' %i])
gcalc = fcn.gcalc(inp.values['a'],inp.values['b'],inp.values['c'],inp.values['alpha'],inp.values['beta'],inp.values['gamma'],
inp.h[i][j],inp.k[i][j],inp.l[i][j],
rod[0],rod[1],rod[2],
inp.values['epsaa%s' %i],inp.values['epsab%s' %i],inp.values['epsac%s' %i],
inp.values['epsbb%s' %i],inp.values['epsbc%s' %i],inp.values['epscc%s' %i])
# gexp = n.dot(Omega,gexp)
# gcalc = n.dot(Omega,gcalc)
inp.mean_ia[i][j] = IA(n.transpose(gexp)[0],n.transpose(gcalc)[0])
# print i+1,inp.mean_ia[i][j]
if inp.mean_ia[i][j] > limit:
delete = delete + 1
reject(inp,i,j,'ia')
if only != []:
print 'Rejected', delete, 'reflection based on internal angles'
insignificant(inp)
def mean_ia_old(inp,limit,only=None):
"""
Calculate the internal angle for each peak and store in inp.mena_ia[inp.no_grains][inp.nrefl[i]]
Jette Oddershede Januar 2009
"""
import build_fcn
build_fcn.FCN(inp)
import fcn
reload(fcn)
for i in range(inp.no_grains):
if i+1 in inp.fit['skip']:
pass
else:
rod = n.array([inp.rod[i][0]+inp.values['rodx%s' %i],inp.rod[i][1]+inp.values['rody%s' %i],inp.rod[i][2]+inp.values['rodz%s' %i]])
for j in range(inp.nrefl[i]):
Omega = tools.form_omega_mat_general(inp.w[inp.id[i][j]]*n.pi/180,inp.values['wx']*n.pi/180,inp.values['wy']*n.pi/180)
gexp = fcn.gexp(inp.w[inp.id[i][j]],inp.dety[inp.id[i][j]],inp.detz[inp.id[i][j]],
inp.values['wx'],inp.values['wy'],inp.values['tx'],inp.values['ty'],inp.values['tz'],
inp.values['py'],inp.values['pz'],inp.values['cy'],inp.values['cz'],inp.values['L'],
inp.values['x%s' %i],inp.values['y%s' %i],inp.values['z%s' %i])
gcalc = fcn.gcalc(inp.values['a'],inp.values['b'],inp.values['c'],inp.values['alpha'],inp.values['beta'],inp.values['gamma'],
inp.h[i][j],inp.k[i][j],inp.l[i][j],
rod[0],rod[1],rod[2],
inp.values['epsaa%s' %i],inp.values['epsab%s' %i],inp.values['epsac%s' %i],
inp.values['epsbb%s' %i],inp.values['epsbc%s' %i],inp.values['epscc%s' %i])
gexp = n.dot(Omega,gexp)
gcalc = n.dot(Omega,gcalc)
# print int(inp.h[i][j]), int(inp.k[i][j]), int(inp.l[i][j]),inp.w[inp.id[i][j]],inp.dety[inp.id[i][j]],inp.detz[inp.id[i][j]],'gexp', 2*n.pi*n.transpose(gexp)[0]/inp.param['wavelength']
# print int(inp.h[i][j]), int(inp.k[i][j]), int(inp.l[i][j]),inp.w[inp.id[i][j]],inp.dety[inp.id[i][j]],inp.detz[inp.id[i][j]],'gcalc', 2*n.pi*n.transpose(gcalc)[0]/inp.param['wavelength']
inp.mean_ia[i][j] = IA(n.transpose(gexp)[0],n.transpose(gcalc)[0])
# inp.mean_ia[i][j] = IAforrod(n.transpose(gexp)[0],n.transpose(gcalc)[0],rod)
# print inp.h[i][j], inp.k[i][j], inp.l[i][j], inp.id[i][j], inp.mean_ia[i][j]
data = deepcopy(inp.mean_ia)
maxia = [0]*inp.no_grains
for i in range(inp.no_grains):
data[i].sort()
if i+1 in inp.fit['skip']:
pass
else:
mean = n.sum(data[i])/len(data[i])
medi = median(data[i])
# print i, len(data[i]), medi, mean,'\n',data[i]
while mean > limit*medi:
data[i].pop()
mean = n.sum(data[i])/inp.nrefl[i]
medi = median(data[i])
maxia[i] = max(data[i])
# print i, len(data[i]),medi,mean,'\n',data[i],'\n'
delete = 0
if only==None:
only = range(1,1+inp.no_grains)
for i in range(inp.no_grains):
if i+1 in inp.fit['skip'] or i+1 not in only:
pass
else:
for j in range(inp.nrefl[i]-1,-1,-1): # loop backwards to make pop work
if inp.mean_ia[i][j] > maxia[i]:
delete = delete + 1
reject(inp,i,j,'ia')
if only != []:
print 'Rejected', delete, 'reflection based on internal angles'
insignificant(inp)