def onFitPeak(self, evt=None):
gname = self.groupname
dtext = []
model = self.fit_model.GetStringSelection().lower()
dtext.append('Fit Model: %s' % model)
bkg = self.fit_bkg.GetStringSelection()
if bkg == 'None':
bkg = None
if bkg is None:
dtext.append('No Background')
else:
dtext.append('Background: %s' % bkg)
step = self.fit_step.GetStringSelection().lower()
if model in ('step', 'rectangle'):
dtext.append('Step form: %s' % step)
try:
lgroup = getattr(self.larch.symtable, gname)
x = lgroup._xdat
y = lgroup._ydat
except AttributeError:
self.write_message('need data to fit!')
return
if step.startswith('error'):
step = 'erf'
elif step.startswith('arctan'):
step = 'atan'
pgroup = fit_peak(x,
y,
model,
background=bkg,
step=step,
_larch=self.larch)
dtext = '\n'.join(dtext)
dtext = '%s\n%s\n' % (
dtext, fit_report(
pgroup.params, min_correl=0.25, _larch=self.larch))
self.fit_report.SetEditable(True)
self.fit_report.SetValue(dtext)
self.fit_report.SetEditable(False)
lgroup.plot_yarrays = [(lgroup._ydat, PLOTOPTS_1, lgroup.plot_ylabel)]
if bkg is None:
lgroup._fit = pgroup.fit[:]
lgroup.plot_yarrays.append((lgroup._fit, PLOTOPTS_2, 'fit'))
else:
lgroup._fit = pgroup.fit[:]
lgroup._fit_bgr = pgroup.bkg[:]
lgroup.plot_yarrays.append((lgroup._fit, PLOTOPTS_2, 'fit'))
lgroup.plot_yarrays.append(
(lgroup._fit_bgr, PLOTOPTS_2, 'background'))
self.plot_group(gname, new=True)
def onFitPeak(self, evt=None):
gname = self.groupname
dtext = []
model = self.fit_model.GetStringSelection().lower()
dtext.append('Fit Model: %s' % model)
bkg = self.fit_bkg.GetStringSelection()
if bkg == 'None':
bkg = None
if bkg is None:
dtext.append('No Background')
else:
dtext.append('Background: %s' % bkg)
step = self.fit_step.GetStringSelection().lower()
if model in ('step', 'rectangle'):
dtext.append('Step form: %s' % step)
try:
lgroup = getattr(self.larch.symtable, gname)
x = lgroup._xdat_
y = lgroup._ydat_
except AttributeError:
self.write_message('need data to fit!')
return
if step.startswith('error'):
step = 'erf'
elif step.startswith('arctan'):
step = 'atan'
pgroup = fit_peak(x, y, model, background=bkg, step=step,
_larch=self.larch)
dtext = '\n'.join(dtext)
dtext = '%s\n%s\n' % (dtext, fit_report(pgroup.params, min_correl=0.25,
_larch=self.larch))
self.fit_report.SetEditable(True)
self.fit_report.SetValue(dtext)
self.fit_report.SetEditable(False)
popts1 = dict(style='solid', linewidth=3,
marker='None', markersize=4)
popts2 = dict(style='short dashed', linewidth=2,
marker='None', markersize=4)
lgroup.plot_yarrays = [(lgroup._ydat_, popts1, lgroup.plot_ylabel)]
if bkg is None:
lgroup._fit = pgroup.fit[:]
lgroup.plot_yarrays.append((lgroup._fit, popts2, 'fit'))
else:
lgroup._fit = pgroup.fit[:]
lgroup._fit_bgr = pgroup.bkg[:]
lgroup.plot_yarrays.append((lgroup._fit, popts2, 'fit'))
lgroup.plot_yarrays.append((lgroup._fit_bgr, popts2, 'background'))
self.onPlot()
def onFitPeak(self, evt=None):
gname = self.groupname
if self.dtcorr.IsChecked():
print('fit needs to dt correct!')
dtext = []
model = self.fit_model.GetStringSelection().lower()
dtext.append('Fit Model: %s' % model)
bkg = self.fit_bkg.GetStringSelection()
if bkg == 'None':
bkg = None
if bkg is None:
dtext.append('No Background')
else:
dtext.append('Background: %s' % bkg)
step = self.fit_step.GetStringSelection().lower()
if model in ('step', 'rectangle'):
dtext.append('Step form: %s' % step)
lgroup = getattr(self.larch.symtable, gname)
x = lgroup._x1_
y = lgroup._y1_
pgroup = fit_peak(x,
y,
model,
background=bkg,
step=step,
_larch=self.larch)
text = fit_report(pgroup.params, _larch=self.larch)
dtext.append('Parameters: ')
for pname in dir(pgroup.params):
par = getattr(pgroup.params, pname)
if isParameter(par):
ptxt = " %s= %.4f" % (par.name, par.value)
if (hasattr(par, 'stderr') and par.stderr is not None):
ptxt = "%s(%.4f)" % (ptxt, par.stderr)
dtext.append(ptxt)
dtext = '\n'.join(dtext)
# plotframe = self.get_plotwindow()
# plotframe.oplot(x, pgroup.fit, label='fit (%s)' % model)
text = fit_report(pgroup.params, _larch=self.larch)
self.fit_report.SetLabel(dtext)
def onFitPeak(self, evt=None):
gname = self.groupname
if self.dtcorr.IsChecked():
print('fit needs to dt correct!')
dtext = []
model = self.fit_model.GetStringSelection().lower()
dtext.append('Fit Model: %s' % model)
bkg = self.fit_bkg.GetStringSelection()
if bkg == 'None':
bkg = None
if bkg is None:
dtext.append('No Background')
else:
dtext.append('Background: %s' % bkg)
step = self.fit_step.GetStringSelection().lower()
if model in ('step', 'rectangle'):
dtext.append('Step form: %s' % step)
lgroup = getattr(self.larch.symtable, gname)
x = lgroup._x1_
y = lgroup._y1_
pgroup = fit_peak(x, y, model, background=bkg, step=step,
_larch=self.larch)
text = fit_report(pgroup.params, _larch=self.larch)
dtext.append('Parameters: ')
for pname in dir(pgroup.params):
par = getattr(pgroup.params, pname)
if isParameter(par):
ptxt = " %s= %.4f" % (par.name, par.value)
if (hasattr(par, 'stderr') and par.stderr is not None):
ptxt = "%s(%.4f)" % (ptxt, par.stderr)
dtext.append(ptxt)
dtext = '\n'.join(dtext)
# plotframe = self.get_plotwindow()
# plotframe.oplot(x, pgroup.fit, label='fit (%s)' % model)
text = fit_report(pgroup.params, _larch=self.larch)
self.fit_report.SetLabel(dtext)
def show_report(self, fitresult, evt=None):
shown = False
try:
self.report_frame.Raise()
shown = True
except:
del self.report_frame
if not shown:
self.report_frame = ReportFrame(self.wxparent)
model_repr = fitresult.model._reprstring(long=True)
report = fit_report(fitresult, show_correl=True,
min_correl=0.25, sort_pars=True)
self.report_frame.SetFont(Font(8))
self.report_frame.set_text(report)
self.report_frame.SetFont(Font(8))
self.report_frame.Raise()
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))
def fit_report(self, params=None, min_correl=0.2, **kws):
if params is None:
params = self.params
return fitting.fit_report(params, min_correl=min_correl,
_larch=self._larch, **kws)
