def test_calibrate_no_search(self):
#from uncertainties import unumpy
x,y = self.edxdata['LaB6']
searcher = WaveletPeakSearcher(1.2,25,1.15,critical_sep=2,noiselevel=20,min_ridge_length=9,
min_child_length=8,ridge_skip=0)
searcher.set_data(x,y)
pks = searcher.identify_peaks()
cf = ChunkFitter(x,pks,shape='g')
cf.refine(y)
candidates = np.array([peak.centre for peak in cf.peaks])
#uncertainty = unumpy.std_devs(candidates)
#uncertainty[uncertainty==0] = 1
#candidates = unumpy.nominal_values(candidates)
unit_cell = [4.15695,4.15695,4.15695,90,90,90]
space_group = 'pm-3m'
c = match_fit(candidates,unit_cell,space_group)
self.assertLess(abs(c.values[0]),1e-9)
self.assertAlmostEqual(c.values[1], 0.001942,5)
self.assertLess(abs(c.values[2]),0.005)
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 test_ChunkFitterWaveletSearch(self):
wps2 = WaveletPeakSearcher(1.5,30,1.15,critical_sep=1,noiselevel=10,min_ridge_length=9,
min_child_length=8,ridge_skip=0)
wps2.set_data(self.x,self.y)
pks = wps2.identify_peaks()
fitter = ChunkFitter(self.x,pks)
fitter.refine(self.y)
def test_WeirdPeakAdding(self):
l,h = self.x.searchsorted([2,2.5])
pk1 = estimate_peak(self.x[l:h],self.y[l:h],name='peak1')
l,h = self.x.searchsorted([2.5,2.75])
pk2 = estimate_peak(self.x[l:h],self.y[l:h])
l,h = self.x.searchsorted([2.8,3.2])
pk3 = estimate_peak(self.x[l:h],self.y[l:h])
pks = [pk1,pk2,pk3]
self.assertRaises(FitterError,ChunkFitter,self.x,pks)
pks[2] = estimate_peak(self.x[l:h],self.y[l:h],name='peak3')
fitter = ChunkFitter(self.x,pks)
fitter.refine(self.y)
cens = [p.centre.nominal_value for p in pks]
cens2 = [v['centre'].nominal_value for v in fitter.lastresult.itervalues()]
self.assertListEqual(cens,cens2)