def test_ChunkFitter(self):
peaknames = ['LaB6_110', 'LaB6_111', 'LaB6_200', 'LaB6_210',
'LaB6_211', 'LaB6_220', 'LaB6_300', 'LaB6_310',
'LaB6_311', 'LaB6_222', 'LaB6_320', 'LaB6_321',
'LaB6_400', 'LaB6_410', 'LaB6_411', 'LaB6_331',
'LaB6_420', 'LaB6_421']
parnames = ['centre','width','area','eta','asymmetry','background']
pks = from_unitcell(self.x,self.y,[4.15695,4.15695,4.15695,90,90,90],'pm-3m',2,7,name='LaB6')
fitter = ChunkFitter(self.x,pks)
fitter.refine(self.y)
result = fitter.lastresult
yfit = fitter.lastfit
saveplot(self.x,self.y,yfit,'chunkfitter.png')
self.assertListEqual(peaknames,[p.name for p in pks])
self.assertItemsEqual(result['LaB6_110'].keys(),parnames)
self.assertTupleEqual(yfit.shape,(4096,))
cens = [p.centre.nominal_value for p in pks]
self.assertEquals(len(cens),18)
self.assertAlmostEquals(cens[0],2.1391,4)
self.assertAlmostEquals(cens[2],3.0249,4)
self.assertAlmostEquals(cens[4],3.7053,4)
self.assertAlmostEquals(cens[8],5.0154,4)
self.assertAlmostEquals(cens[12],6.0520,4)
self.assertAlmostEquals(cens[16],6.7653,4)
def fit(source,x,material,qmin,qmax,reestimate=True,**kwargs):
counts,info = source.next() #build fitter on first go
ymin_on_ymax = kwargs.pop('ymin_on_ymax',None)
if hasattr(material,'space_group'):
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]
def test_PeakFitterAdd(self):
peaknames = ['LaB6_110', 'LaB6_111', 'LaB6_200', 'LaB6_210', 'LaB6_211']
pks = from_unitcell(self.x,self.y,[4.15695,4.15695,4.15695,90,90,90],'pm-3m',2,4,name='LaB6')
fitter = PeakFitter(self.x,[])
for p in pks:
fitter.add(p)
fitter.refine(self.y)
self.assertListEqual(peaknames,[p.name for p in pks])
cens = [p.centre.nominal_value for p in pks]
self.assertEquals(len(cens),5)
self.assertAlmostEquals(cens[0],2.1391,4)
self.assertAlmostEquals(cens[1],2.6195,4)
self.assertAlmostEquals(cens[2],3.0249,4)
pks = from_unitcell(self.x,self.y,[4.15695,4.15695,4.15695,90,90,90],'pm-3m',2,4,name='LaB6')
fitter = PeakFitter(self.x,[])
fitter.add_many(pks)
fitter.refine(self.y)
self.assertListEqual(peaknames,[p.name for p in pks])
cens = [p.centre.nominal_value for p in pks]
self.assertEquals(len(cens),5)
self.assertAlmostEquals(cens[0],2.1391,4)
self.assertAlmostEquals(cens[1],2.6195,4)
self.assertAlmostEquals(cens[2],3.0249,4)
pks = from_unitcell(self.x,self.y,[4.15695,4.15695,4.15695,90,90,90],'pm-3m',2,4,name='LaB6')
fitter = PeakFitter(self.x,pks[0:2])
for p in pks[2:]:
fitter.add(p)
fitter.refine(self.y)
self.assertListEqual(peaknames,[p.name for p in pks])
cens = [p.centre.nominal_value for p in pks]
self.assertEquals(len(cens),5)
self.assertAlmostEquals(cens[0],2.1391,4)
self.assertAlmostEquals(cens[1],2.6195,4)
self.assertAlmostEquals(cens[2],3.0249,4)
def test_PeakFitterUncertainties(self):
y = unumpy.uarray((self.y,np.sqrt(self.y)))
peaknames = ['LaB6_110', 'LaB6_111', 'LaB6_200', 'LaB6_210', 'LaB6_211']
pks = from_unitcell(self.x,y,[4.15695,4.15695,4.15695,90,90,90],'pm-3m',2,4,name='LaB6')
fitter = PeakFitter(self.x,pks)
fitter.refine(y)
saveplot(self.x,unumpy.nominal_values(y),fitter.lastfit,'peakfitter_uncertainties.png')
self.assertListEqual(peaknames,[p.name for p in pks])
cens = [p.centre.nominal_value for p in pks]
self.assertEquals(len(cens),5)
self.assertAlmostEquals(cens[0],2.1391,4)
self.assertAlmostEquals(cens[1],2.6195,4)
self.assertAlmostEquals(cens[2],3.0249,4)
def test_PeakFitter(self):
peaknames = ['LaB6_110', 'LaB6_111', 'LaB6_200', 'LaB6_210', 'LaB6_211']
pks = from_unitcell(self.x,self.y,[4.15695,4.15695,4.15695,90,90,90],'pm-3m',2,4,name='LaB6')
fitter = PeakFitter(self.x,pks)
fitter.refine(self.y)
result = fitter.lastresult
saveplot(self.x,self.y,fitter.lastfit,'peakfitter.png')
cens = [v['centre'].nominal_value for v in result.itervalues()]
censu = [v['centre'].std_dev() for v in result.itervalues()]
self.assertListEqual([p.centre.nominal_value for p in pks],cens)
self.assertListEqual([p.centre.std_dev() for p in pks],censu)
self.assertListEqual(peaknames,[p.name for p in pks])
self.assertEquals(len(cens),5)
self.assertAlmostEquals(cens[0],2.1391,4)
self.assertAlmostEquals(cens[1],2.6195,4)
self.assertAlmostEquals(cens[2],3.0249,4)
def makepeaks(x,y):
return from_unitcell(x,y,[4.15695,4.15695,4.15695,90,90,90],'pm-3m',2,5,name='LaB6')
for line in ax.xaxis.get_ticklines()+ax.yaxis.get_ticklines():
line.set_markeredgewidth(1)
ax.minorticks_off()
f.savefig('wavelet_peaksearch.png',dpi=100)
if 1:
from edxrd.test import get_test_data
edxdata = get_test_data.getedxdata()
x,y = edxdata['LaB6']
x=np.poly1d([1e-9, 0.001942,0.005])(x)
unit_cell = [4.15695,4.15695,4.15695,90,90,90]
space_group = 'pm-3m'
from edxrd.peaksearch import from_unitcell
pks = from_unitcell(x,y,unit_cell,space_group,2,4.4,
name='LaB6',shape='g')
print pks[0].centre
yfit = np.zeros_like(x)
for pk in pks:
yfit+=pk.profile(x)
f,ax = plt.subplots(1,1,figsize=(7,4))
f.subplots_adjust(bottom=0.15)
ax.plot(x,y,'b-')
ax.plot(x,yfit,'r-',lw=1)
ax.set_yticks([])
ax.set_xbound(0.8,6)
ax.set_xlabel('$\mathrm{Q} (\AA^{-1})$')
f.savefig('unitcell_peaksearch.png',dpi=100)
#plt.show()
