def onFitPeaks(self, event=None):
print( 'Fit Peaks')
opts = {}
filters, peaks = [], []
sig, det, bgr = {}, {}, {}
opts['flyield'] = self.wids.flyield_use.IsChecked()
opts['xray_en'] = self.wids.xray_en.GetValue()
opts['emin'] = self.wids.fit_emin.GetValue()
opts['emax'] = self.wids.fit_emax.GetValue()
det['use'] = self.wids.det_use.IsChecked()
det['thickness'] = self.wids.det_thk.GetValue()
det['material'] = self.wids.det_mat.GetStringSelection()
bgr['use'] = self.wids.bgr_use.IsChecked()
bgr['width'] = self.wids.bgr_width.GetValue()
bgr['compress'] = int(self.wids.bgr_compress.GetStringSelection())
bgr['exponent'] = int(self.wids.bgr_exponent.GetStringSelection())
sig['offset'] = self.wids.sig_offset.param
sig['slope'] = self.wids.sig_slope.param
sig['quad'] = self.wids.sig_quad.param
for k in self.wids.filters:
f = (k[0].GetStringSelection(), k[1].GetValue(), k[2].param)
filters.append(f)
for k in self.wids.peaks:
p = (k[0].IsChecked(), k[1].param, k[2].param, k[3].param)
peaks.append(p)
opts = {'det': det, 'bgr': bgr, 'sig': sig,
'filters': filters, 'peaks': peaks}
for key, val in opts.items():
print( key, val)
mca = self.mca
mca.data = mca.counts*1.0
energy = mca.energy
_larch = self.parent.larch
if bgr.pop('use'):
xrf_background(energy=mca.energy, counts=mca.counts,
group=mca, _larch=_larch, **bgr)
mca.data = mca.data - mca.bgr
if det.pop('use'):
# mu in 1/mm, note energy is needed in eV
mu = material_mu(det['material'], energy*1000.0, _larch=_larch)/10.0
t = det['thickness']
mca.det_atten = np.exp(-t*mu)
mca.data = mca.data / np.maximum(1.e-49, (1.0 - mca.det_atten))
def onShowBgr(self, event=None):
mca = self.mca
parent = self.parent
width = self.wids['bgr_width'].GetValue()/1000.0
expon = int(self.wids['bgr_expon'].GetStringSelection())
xrf_background(energy=mca.energy, counts=mca.counts, group=mca,
width=width, exponent=expon, _larch=parent.larch)
mca.bgr_width = width
mca.bgr_expoent = expon
parent.plotmca(mca)
parent.oplot(mca.energy, mca.bgr, label='background',
color=parent.conf.bgr_color, linewidth=2, style='--')
def onShowBgr(self, event=None):
wids = self.wids
mca = self.mca
parent = self.parent
width = wids.bgr_width.GetValue()
compress = int(wids.bgr_compress.GetStringSelection())
exponent = int(wids.bgr_exponent.GetStringSelection())
xrf_background(energy=mca.energy, counts=mca.counts,
group=mca, width=width, compress=compress,
exponent=exponent, _larch=parent.larch)
mca.bgr_width = width
mca.bgr_compress = compress
mca.bgr_exponent = exponent
parent.plotmca(mca)
parent.oplot(mca.energy, mca.bgr, label='background',
color=parent.conf.bgr_color)
def onShowBgr(self, event=None):
wids = self.wids
mca = self.mca
parent = self.parent
width = wids.bgr_width.GetValue()
compress = int(wids.bgr_compress.GetStringSelection())
exponent = int(wids.bgr_exponent.GetStringSelection())
xrf_background(energy=mca.energy, counts=mca.counts,
group=mca, width=width, compress=compress,
exponent=exponent, _larch=parent.larch)
mca.bgr_width = width
mca.bgr_compress = compress
mca.bgr_exponent = exponent
parent.plotmca(mca)
parent.oplot(mca.energy, mca.bgr, label='background',
color=parent.conf.bgr_color, linewidth=1, style='--')
def onFitPeaks(self, event=None):
opts = {}
filters, peaks = [], []
sig, det, bgr = {}, {}, {}
opts['flyield'] = self.wids.flyield_use.IsChecked()
opts['xray_en'] = self.wids.xray_en.GetValue()
opts['emin'] = self.wids.fit_emin.GetValue()
opts['emax'] = self.wids.fit_emax.GetValue()
det['use'] = self.wids.det_use.IsChecked()
det['thickness'] = self.wids.det_thk.GetValue()
det['material'] = self.wids.det_mat.GetStringSelection()
bgr['use'] = self.wids.bgr_use.IsChecked()
bgr['width'] = self.wids.bgr_width.GetValue()
bgr['compress'] = int(self.wids.bgr_compress.GetStringSelection())
bgr['exponent'] = int(self.wids.bgr_exponent.GetStringSelection())
sig['offset'] = self.wids.sig_offset.param
sig['slope'] = self.wids.sig_slope.param
sig['quad'] = self.wids.sig_quad.param
for k in self.wids.filters:
f = (k[0].GetStringSelection(), k[1].GetValue(), k[2].param)
filters.append(f)
for k in self.wids.peaks:
use = k[0].IsChecked()
p = (k[0].IsChecked(), k[1].param, k[2].param, k[3].param)
peaks.append(p)
if not use:
k[1].param.vary = False
k[2].param.vary = False
k[3].param.vary = False
opts['det'] = det
opts['bgr'] = bgr
opts['sig'] = sig
opts['filters'] = filters
opts['peaks'] = peaks
mca = self.mca
mca.data = mca.counts * 1.0
energy = mca.energy
_larch = self.parent.larch
if bgr['use']:
bgr.pop('use')
xrf_background(energy=mca.energy,
counts=mca.counts,
group=mca,
_larch=_larch,
**bgr)
opts['use_bgr'] = True
opts['mca'] = mca
if det['use']:
mu = material_mu(det['material'], energy * 1000.0,
_larch=_larch) / 10.0
t = det['thickness']
mca.det_atten = np.exp(-t * mu)
fit = Minimizer(xrf_resid,
self.paramgroup,
toler=1.e-4,
_larch=_larch,
fcn_kws=opts)
fit.leastsq()
parent = self.parent
parent.oplot(mca.energy,
mca.model,
label='fit',
style='solid',
color='#DD33DD')
print(fitting.fit_report(self.paramgroup, _larch=_larch))
def onFitPeaks(self, event=None):
opts = {}
filters, peaks = [], []
sig, det, bgr = {}, {}, {}
opts['flyield'] = self.wids.flyield_use.IsChecked()
opts['xray_en'] = self.wids.xray_en.GetValue()
opts['emin'] = self.wids.fit_emin.GetValue()
opts['emax'] = self.wids.fit_emax.GetValue()
det['use'] = self.wids.det_use.IsChecked()
det['thickness'] = self.wids.det_thk.GetValue()
det['material'] = self.wids.det_mat.GetStringSelection()
bgr['use'] = self.wids.bgr_use.IsChecked()
bgr['width'] = self.wids.bgr_width.GetValue()
bgr['compress'] = int(self.wids.bgr_compress.GetStringSelection())
bgr['exponent'] = int(self.wids.bgr_exponent.GetStringSelection())
sig['offset'] = self.wids.sig_offset.param
sig['slope'] = self.wids.sig_slope.param
sig['quad'] = self.wids.sig_quad.param
for k in self.wids.filters:
f = (k[0].GetStringSelection(), k[1].GetValue(), k[2].param)
filters.append(f)
for k in self.wids.peaks:
use = k[0].IsChecked()
p = (k[0].IsChecked(), k[1].param, k[2].param, k[3].param)
peaks.append(p)
if not use:
k[1].param.vary = False
k[2].param.vary = False
k[3].param.vary = False
opts['det'] = det
opts['bgr'] = bgr
opts['sig'] = sig
opts['filters'] = filters
opts['peaks'] = peaks
mca = self.mca
mca.data = mca.counts*1.0
energy = mca.energy
_larch = self.parent.larch
if bgr['use']:
bgr.pop('use')
xrf_background(energy=mca.energy, counts=mca.counts,
group=mca, _larch=_larch, **bgr)
opts['use_bgr']=True
opts['mca'] = mca
if det['use']:
mu = material_mu(det['material'], energy*1000.0,
_larch=_larch)/10.0
t = det['thickness']
mca.det_atten = np.exp(-t*mu)
fit = Minimizer(xrf_resid, self.paramgroup, toler=1.e-4,
_larch=_larch, fcn_kws = opts)
fit.leastsq()
parent = self.parent
parent.oplot(mca.energy, mca.model,
label='fit', style='solid',
color='#DD33DD')
print( fitting.fit_report(self.paramgroup, _larch=_larch))
