class PrePeakPanel(wx.Panel):
def __init__(self, parent=None, controller=None, **kws):
wx.Panel.__init__(self, parent, -1, size=(550, 625), **kws)
self.parent = parent
self.controller = controller
self.larch = controller.larch
self.fit_components = OrderedDict()
self.fit_model = None
self.fit_params = None
self.user_added_params = None
self.summary = None
self.sizer = wx.GridBagSizer(10, 6)
self.build_display()
self.pick2_timer = wx.Timer(self)
self.pick2_group = None
self.Bind(wx.EVT_TIMER, self.onPick2Timer, self.pick2_timer)
self.pick2_t0 = 0.
self.pick2_timeout = 15.
self.pick2erase_timer = wx.Timer(self)
self.pick2erase_panel = None
self.Bind(wx.EVT_TIMER, self.onPick2EraseTimer, self.pick2erase_timer)
def onPanelExposed(self, **kws):
# called when notebook is selected
try:
fname = self.controller.filelist.GetStringSelection()
gname = self.controller.file_groups[fname]
dgroup = self.controller.get_group(gname)
# print(" Fill prepeak panel from group ", fname, gname, dgroup)
self.fill_form(dgroup)
except:
pass # print(" Cannot Fill prepeak panel from group ")
def larch_eval(self, cmd):
"""eval"""
self.controller.larch.eval(cmd)
def build_display(self):
self.mod_nb = flat_nb.FlatNotebook(self, -1, agwStyle=FNB_STYLE)
self.mod_nb.SetTabAreaColour(wx.Colour(250,250,250))
self.mod_nb.SetActiveTabColour(wx.Colour(254,254,195))
self.mod_nb.SetNonActiveTabTextColour(wx.Colour(10,10,128))
self.mod_nb.SetActiveTabTextColour(wx.Colour(128,0,0))
self.mod_nb.Bind(wx.EVT_NOTEBOOK_PAGE_CHANGED, self.onNBChanged)
pan = self.panel = GridPanel(self, ncols=4, nrows=4, pad=2, itemstyle=LCEN)
self.wids = {}
def FloatSpinWithPin(name, value, **kws):
s = wx.BoxSizer(wx.HORIZONTAL)
self.wids[name] = FloatSpin(pan, value=value, **kws)
bb = BitmapButton(pan, get_icon('pin'), size=(25, 25),
action=partial(self.onSelPoint, opt=name),
tooltip='use last point selected from plot')
s.Add(self.wids[name])
s.Add(bb)
return s
opts = dict(digits=2, increment=0.1)
ppeak_e0 = FloatSpinWithPin('ppeak_e0', value=0, **opts)
ppeak_elo = FloatSpinWithPin('ppeak_elo', value=-15, **opts)
ppeak_ehi = FloatSpinWithPin('ppeak_ehi', value=-5, **opts)
ppeak_emin = FloatSpinWithPin('ppeak_emin', value=-30, **opts)
ppeak_emax = FloatSpinWithPin('ppeak_emax', value=0, **opts)
self.fitbline_btn = Button(pan,'Fit Baseline', action=self.onFitBaseline,
size=(150, 25))
self.fitmodel_btn = Button(pan, 'Fit Model',
action=self.onFitModel, size=(150, 25))
self.fitsel_btn = Button(pan, 'Fit Selected Groups',
action=self.onFitSelected, size=(150, 25))
self.fitmodel_btn.Disable()
self.fitsel_btn.Disable()
self.array_choice = Choice(pan, size=(150, -1),
choices=list(Array_Choices.keys()))
self.array_choice.SetSelection(1)
models_peaks = Choice(pan, size=(150, -1),
choices=ModelChoices['peaks'],
action=self.addModel)
models_other = Choice(pan, size=(150, -1),
choices=ModelChoices['other'],
action=self.addModel)
self.plot_choice = Choice(pan, size=(150, -1),
choices=PlotChoices,
action=self.onPlot)
self.message = SimpleText(pan,
'first fit baseline, then add peaks to fit model.')
self.msg_centroid = SimpleText(pan, '----')
opts = dict(default=True, size=(75, -1), action=self.onPlot)
self.show_centroid = Check(pan, label='show?', **opts)
self.show_peakrange = Check(pan, label='show?', **opts)
self.show_fitrange = Check(pan, label='show?', **opts)
self.show_e0 = Check(pan, label='show?', **opts)
opts = dict(default=False, size=(200, -1), action=self.onPlot)
self.plot_sub_bline = Check(pan, label='Subtract Baseline?', **opts)
def add_text(text, dcol=1, newrow=True):
pan.Add(SimpleText(pan, text), dcol=dcol, newrow=newrow)
titleopts = dict(font=Font(12), colour='#AA0000')
pan.Add(SimpleText(pan, ' Pre-edge Peak Fitting', **titleopts), dcol=5)
add_text(' Run Fit:', newrow=False)
add_text('Array to fit: ')
pan.Add(self.array_choice, dcol=3)
pan.Add((10, 10))
pan.Add(self.fitbline_btn)
add_text('E0: ')
pan.Add(ppeak_e0)
pan.Add((10, 10), dcol=2)
pan.Add(self.show_e0)
pan.Add(self.fitmodel_btn)
add_text('Fit Energy Range: ')
pan.Add(ppeak_emin)
add_text(' : ', newrow=False)
pan.Add(ppeak_emax)
pan.Add(self.show_fitrange)
pan.Add(self.fitsel_btn)
t = SimpleText(pan, 'Pre-edge Peak Range: ')
t.SetToolTip('Range used as mask for background')
pan.Add(t, newrow=True)
pan.Add(ppeak_elo)
add_text(' : ', newrow=False)
pan.Add(ppeak_ehi)
pan.Add(self.show_peakrange)
add_text( 'Peak Centroid: ')
pan.Add(self.msg_centroid, dcol=3)
pan.Add(self.show_centroid, dcol=1)
# plot buttons
ts = wx.BoxSizer(wx.HORIZONTAL)
ts.Add(self.plot_choice)
ts.Add(self.plot_sub_bline)
pan.Add(SimpleText(pan, 'Plot: '), newrow=True)
pan.Add(ts, dcol=7)
# add model
ts = wx.BoxSizer(wx.HORIZONTAL)
ts.Add(models_peaks)
ts.Add(models_other)
pan.Add(SimpleText(pan, 'Add Component: '), newrow=True)
pan.Add(ts, dcol=7)
pan.Add(SimpleText(pan, 'Messages: '), newrow=True)
pan.Add(self.message, dcol=7)
pan.pack()
sizer = wx.BoxSizer(wx.VERTICAL)
sizer.Add((5,5), 0, LCEN, 3)
sizer.Add(HLine(self, size=(550, 2)), 0, LCEN, 3)
sizer.Add(pan, 0, LCEN, 3)
sizer.Add((5,5), 0, LCEN, 3)
sizer.Add(HLine(self, size=(550, 2)), 0, LCEN, 3)
sizer.Add((5,5), 0, LCEN, 3)
sizer.Add(self.mod_nb, 1, LCEN|wx.GROW, 10)
pack(self, sizer)
def get_config(self, dgroup=None):
"""get processing configuration for a group"""
if dgroup is None:
dgroup = self.controller.get_group()
conf = getattr(dgroup, 'prepeak_config', {})
if 'e0' not in conf:
conf = dict(e0 = dgroup.e0, elo=-10, ehi=-5,
emin=-40, emax=0, yarray='norm')
dgroup.prepeak_config = conf
if not hasattr(dgroup, 'prepeaks'):
dgroup.prepeaks = Group()
return conf
def fill_form(self, dat):
if isinstance(dat, Group):
self.wids['ppeak_e0'].SetValue(dat.e0)
if hasattr(dat, 'prepeaks'):
self.wids['ppeak_emin'].SetValue(dat.prepeaks.emin)
self.wids['ppeak_emax'].SetValue(dat.prepeaks.emax)
self.wids['ppeak_elo'].SetValue(dat.prepeaks.elo)
self.wids['ppeak_ehi'].SetValue(dat.prepeaks.ehi)
elif instance(dat, dict):
self.wids['ppeak_e0'].SetValue(dat['e0'])
self.wids['ppeak_emin'].SetValue(dat['emin'])
self.wids['ppeak_emax'].SetValue(dat['emax'])
self.wids['ppeak_elo'].SetValue(dat['elo'])
self.wids['ppeak_ehi'].SetValue(dat['ehi'])
self.array_choice.SetStringSelection(dat['array_desc'])
self.show_e0.Enable(dat['show_e0'])
self.show_centroid.Enable(dat['show_centroid'])
self.show_fitrange.Enable(dat['show_fitrange'])
self.show_peakrange.Enable(dat['show_peakrange'])
self.plot_sub_bline.Enable(dat['plot_sub_bline'])
def read_form(self):
"read for, returning dict of values"
dgroup = self.controller.get_group()
array_desc = self.array_choice.GetStringSelection()
form_opts = {'gname': dgroup.groupname,
'array_desc': array_desc.lower(),
'array_name': Array_Choices[array_desc],
'baseline_form': 'lorentzian'}
form_opts['e0'] = self.wids['ppeak_e0'].GetValue()
form_opts['emin'] = self.wids['ppeak_emin'].GetValue()
form_opts['emax'] = self.wids['ppeak_emax'].GetValue()
form_opts['elo'] = self.wids['ppeak_elo'].GetValue()
form_opts['ehi'] = self.wids['ppeak_ehi'].GetValue()
form_opts['plot_sub_bline'] = self.plot_sub_bline.IsChecked()
form_opts['show_centroid'] = self.show_centroid.IsChecked()
form_opts['show_peakrange'] = self.show_peakrange.IsChecked()
form_opts['show_fitrange'] = self.show_fitrange.IsChecked()
form_opts['show_e0'] = self.show_e0.IsChecked()
return form_opts
def onFitBaseline(self, evt=None):
opts = self.read_form()
cmd = """{gname:s}.ydat = 1.0*{gname:s}.{array_name:s}
pre_edge_baseline(energy={gname:s}.energy, norm={gname:s}.ydat, group={gname:s},
form='{baseline_form:s}', with_line=True,
elo={elo:.3f}, ehi={ehi:.3f}, emin={emin:.3f}, emax={emax:.3f})
"""
self.larch_eval(cmd.format(**opts))
dgroup = self.controller.get_group()
ppeaks = dgroup.prepeaks
dgroup.centroid_msg = "%.4f +/- %.4f eV" % (ppeaks.centroid,
ppeaks.delta_centroid)
self.msg_centroid.SetLabel(dgroup.centroid_msg)
if 'loren_' not in self.fit_components:
self.addModel(model='Lorentzian', prefix='loren_', isbkg=True)
if 'line_' not in self.fit_components:
self.addModel(model='Linear', prefix='line_', isbkg=True)
for prefix in ('loren_', 'line_'):
cmp = self.fit_components[prefix]
# cmp.bkgbox.SetValue(1)
self.fill_model_params(prefix, dgroup.prepeaks.fit_details.params)
self.fill_form(dgroup)
self.fitmodel_btn.Enable()
# self.fitallmodel_btn.Enable()
i1, i2 = self.get_xranges(dgroup.energy)
dgroup.yfit = dgroup.xfit = 0.0*dgroup.energy[i1:i2]
self.plot_choice.SetStringSelection(PLOT_BASELINE)
self.onPlot()
def fill_model_params(self, prefix, params):
comp = self.fit_components[prefix]
parwids = comp.parwids
for pname, par in params.items():
pname = prefix + pname
if pname in parwids:
wids = parwids[pname]
if wids.minval is not None:
wids.minval.SetValue(par.min)
if wids.maxval is not None:
wids.maxval.SetValue(par.max)
wids.value.SetValue(par.value)
varstr = 'vary' if par.vary else 'fix'
if par.expr is not None:
varstr = 'constrain'
if wids.vary is not None:
wids.vary.SetStringSelection(varstr)
def onPlot(self, evt=None):
plot_choice = self.plot_choice.GetStringSelection()
opts = self.read_form()
dgroup = self.controller.get_group()
ppeaks = getattr(dgroup, 'prepeaks', None)
if ppeaks is None:
return
i1, i2 = self.get_xranges(dgroup.xdat)
# i2 = len(ppeaks.baseline) + i1
if len(dgroup.yfit) > len(ppeaks.baseline):
i2 = i1 + len(ppeaks.baseline)
# print(" Indexes: ", i1, i2, i2-i1, len(dgroup.yfit), len(ppeaks.baseline))
xdat = 1.0*dgroup.energy
ydat = 1.0*dgroup.ydat
yfit = 1.0*dgroup.ydat
baseline = 1.0*dgroup.ydat
yfit[i1:i2] = dgroup.yfit[:i2-i1]
baseline[i1:i2] = ppeaks.baseline[:i2-i1]
if opts['plot_sub_bline']:
ydat = ydat - baseline
if plot_choice in (PLOT_FIT, PLOT_RESID):
yfit = yfit - baseline
if plot_choice == PLOT_RESID:
resid = ydat - yfit
_xs = dgroup.energy[i1:i2]
xrange = max(_xs) - min(_xs)
pxmin = min(_xs) - 0.05 * xrange
pxmax = max(_xs) + 0.05 * xrange
jmin = index_of(dgroup.energy, pxmin)
jmax = index_of(dgroup.energy, pxmax) + 1
_ys = ydat[jmin:jmax]
yrange = max(_ys) - min(_ys)
pymin = min(_ys) - 0.05 * yrange
pymax = max(_ys) + 0.05 * yrange
title = ' pre-edge fit'
if plot_choice == PLOT_BASELINE:
title = ' pre-edge baseline'
if opts['plot_sub_bline']:
title = ' pre-edge peaks'
array_desc = self.array_choice.GetStringSelection()
plotopts = {'xmin': pxmin, 'xmax': pxmax,
'ymin': pymin, 'ymax': pymax,
'title': '%s: %s' % (opts['gname'], title),
'xlabel': 'Energy (eV)',
'ylabel': '%s $\mu$' % opts['array_desc'],
'label': '%s $\mu$' % opts['array_desc'],
'delay_draw': True,
'show_legend': True}
plot_extras = []
if opts['show_fitrange']:
popts = {'color': '#DDDDCC'}
emin = opts['emin']
emax = opts['emax']
imin = index_of(dgroup.energy, emin)
imax = index_of(dgroup.energy, emax)
plot_extras.append(('vline', emin, None, popts))
plot_extras.append(('vline', emax, None, popts))
if opts['show_peakrange']:
popts = {'marker': '+', 'markersize': 6}
elo = opts['elo']
ehi = opts['ehi']
ilo = index_of(dgroup.xdat, elo)
ihi = index_of(dgroup.xdat, ehi)
plot_extras.append(('marker', elo, ydat[ilo], popts))
plot_extras.append(('marker', ehi, ydat[ihi], popts))
if opts['show_centroid']:
popts = {'color': '#EECCCC'}
ecen = getattr(dgroup.prepeaks, 'centroid', -1)
if ecen > min(dgroup.energy):
plot_extras.append(('vline', ecen, None, popts))
pframe = self.controller.get_display(win=2,
stacked=(plot_choice==PLOT_RESID))
ppanel = pframe.panel
axes = ppanel.axes
plotopts.update(PLOTOPTS_1)
ppanel.plot(xdat, ydat, **plotopts)
if plot_choice == PLOT_BASELINE:
if not opts['plot_sub_bline']:
ppanel.oplot(dgroup.prepeaks.energy,
dgroup.prepeaks.baseline,
label='baseline', **PLOTOPTS_2)
elif plot_choice in (PLOT_FIT, PLOT_RESID):
ppanel.oplot(dgroup.energy, yfit,
label='fit', **PLOTOPTS_1)
if hasattr(dgroup, 'ycomps'):
ncomp = len(dgroup.ycomps)
icomp = 0
for label, ycomp in dgroup.ycomps.items():
icomp +=1
fcomp = self.fit_components[label]
# print("ycomp: ", plot_choice, label, len(ycomp), len(dgroup.xfit),
# fcomp.bkgbox.IsChecked(), opts['plot_sub_bline'], icomp, ncomp)
if not (fcomp.bkgbox.IsChecked() and opts['plot_sub_bline']):
ppanel.oplot(dgroup.xfit, ycomp, label=label,
delay_draw=(icomp!=ncomp), style='short dashed')
if plot_choice == PLOT_RESID:
_ys = resid
yrange = max(_ys) - min(_ys)
plotopts['ymin'] = min(_ys) - 0.05 * yrange
plotopts['ymax'] = max(_ys) + 0.05 * yrange
plotopts['delay_draw'] = False
plotopts['ylabel'] = 'data-fit'
plotopts['label'] = '_nolegend_'
pframe.plot(dgroup.energy, resid, panel='bot', **plotopts)
pframe.Show()
# print(" RESIDUAL PLOT margins: ")
# print(" top : ", pframe.panel.conf.margins)
# print(" bot : ", pframe.panel_bot.conf.margins)
for etype, x, y, opts in plot_extras:
if etype == 'marker':
popts = {'marker': 'o', 'markersize': 4,
'label': '_nolegend_',
'markerfacecolor': 'red',
'markeredgecolor': '#884444'}
popts.update(opts)
axes.plot([x], [y], **popts)
elif etype == 'vline':
popts = {'ymin': 0, 'ymax': 1.0, 'color': '#888888',
'label': '_nolegend_'}
popts.update(opts)
axes.axvline(x, **popts)
ppanel.canvas.draw()
def onNBChanged(self, event=None):
idx = self.mod_nb.GetSelection()
def addModel(self, event=None, model=None, prefix=None, isbkg=False):
if model is None and event is not None:
model = event.GetString()
if model is None or model.startswith('<'):
return
if prefix is None:
p = model[:5].lower()
curmodels = ["%s%i_" % (p, i+1) for i in range(1+len(self.fit_components))]
for comp in self.fit_components:
if comp in curmodels:
curmodels.remove(comp)
prefix = curmodels[0]
label = "%s(prefix='%s')" % (model, prefix)
title = "%s: %s " % (prefix[:-1], model)
title = prefix[:-1]
mclass_kws = {'prefix': prefix}
if 'step' in model.lower():
form = model.lower().replace('step', '').strip()
if form.startswith('err'): form = 'erf'
label = "Step(form='%s', prefix='%s')" % (form, prefix)
title = "%s: Step %s" % (prefix[:-1], form[:3])
mclass = lm_models.StepModel
mclass_kws['form'] = form
minst = mclass(form=form, prefix=prefix)
else:
if model in ModelFuncs:
mclass = getattr(lm_models, ModelFuncs[model])
else:
mclass = getattr(lm_models, model+'Model')
minst = mclass(prefix=prefix)
panel = GridPanel(self.mod_nb, ncols=2, nrows=5, pad=2, itemstyle=CEN)
def SLabel(label, size=(80, -1), **kws):
return SimpleText(panel, label,
size=size, style=wx.ALIGN_LEFT, **kws)
usebox = Check(panel, default=True, label='Use in Fit?', size=(100, -1))
bkgbox = Check(panel, default=False, label='Is Baseline?', size=(125, -1))
if isbkg:
bkgbox.SetValue(1)
delbtn = Button(panel, 'Delete Component', size=(125, -1),
action=partial(self.onDeleteComponent, prefix=prefix))
pick2msg = SimpleText(panel, " ", size=(125, -1))
pick2btn = Button(panel, 'Pick Values from Data', size=(150, -1),
action=partial(self.onPick2Points, prefix=prefix))
# SetTip(mname, 'Label for the model component')
SetTip(usebox, 'Use this component in fit?')
SetTip(bkgbox, 'Label this component as "background" when plotting?')
SetTip(delbtn, 'Delete this model component')
SetTip(pick2btn, 'Select X range on Plot to Guess Initial Values')
panel.Add(SLabel(label, size=(275, -1), colour='#0000AA'),
dcol=3, style=wx.ALIGN_LEFT, newrow=True)
panel.Add(usebox, dcol=1)
panel.Add(bkgbox, dcol=2, style=LCEN)
panel.Add(delbtn, dcol=1, style=wx.ALIGN_LEFT)
panel.Add(pick2btn, dcol=2, style=wx.ALIGN_LEFT, newrow=True)
panel.Add(pick2msg, dcol=2, style=wx.ALIGN_RIGHT)
# panel.Add((10, 10), newrow=True)
# panel.Add(HLine(panel, size=(150, 3)), dcol=4, style=wx.ALIGN_CENTER)
panel.Add(SLabel("Parameter "), style=wx.ALIGN_LEFT, newrow=True)
panel.AddMany((SLabel(" Value"), SLabel(" Type"), SLabel(' Bounds'),
SLabel(" Min", size=(60, -1)),
SLabel(" Max", size=(60, -1)), SLabel(" Expression")))
parwids = OrderedDict()
parnames = sorted(minst.param_names)
for a in minst._func_allargs:
pname = "%s%s" % (prefix, a)
if (pname not in parnames and
a in minst.param_hints and
a not in minst.independent_vars):
parnames.append(pname)
for pname in parnames:
sname = pname[len(prefix):]
hints = minst.param_hints.get(sname, {})
par = Parameter(name=pname, value=0, vary=True)
if 'min' in hints:
par.min = hints['min']
if 'max' in hints:
par.max = hints['max']
if 'value' in hints:
par.value = hints['value']
if 'expr' in hints:
par.expr = hints['expr']
pwids = ParameterWidgets(panel, par, name_size=100, expr_size=125,
float_size=80, prefix=prefix,
widgets=('name', 'value', 'minval',
'maxval', 'vary', 'expr'))
parwids[par.name] = pwids
panel.Add(pwids.name, newrow=True)
panel.AddMany((pwids.value, pwids.vary, pwids.bounds,
pwids.minval, pwids.maxval, pwids.expr))
for sname, hint in minst.param_hints.items():
pname = "%s%s" % (prefix, sname)
if 'expr' in hint and pname not in parnames:
par = Parameter(name=pname, value=0, expr=hint['expr'])
pwids = ParameterWidgets(panel, par, name_size=100, expr_size=225,
float_size=80, prefix=prefix,
widgets=('name', 'value', 'expr'))
parwids[par.name] = pwids
panel.Add(pwids.name, newrow=True)
panel.Add(pwids.value)
panel.Add(pwids.expr, dcol=4, style=wx.ALIGN_RIGHT)
pwids.value.Disable()
fgroup = Group(prefix=prefix, title=title, mclass=mclass,
mclass_kws=mclass_kws, usebox=usebox, panel=panel,
parwids=parwids, float_size=65, expr_size=150,
pick2_msg=pick2msg, bkgbox=bkgbox)
self.fit_components[prefix] = fgroup
panel.pack()
self.mod_nb.AddPage(panel, title, True)
sx,sy = self.GetSize()
self.SetSize((sx, sy+1))
self.SetSize((sx, sy))
def onDeleteComponent(self, evt=None, prefix=None):
fgroup = self.fit_components.get(prefix, None)
if fgroup is None:
return
for i in range(self.mod_nb.GetPageCount()):
if fgroup.title == self.mod_nb.GetPageText(i):
self.mod_nb.DeletePage(i)
for attr in dir(fgroup):
setattr(fgroup, attr, None)
self.fit_components.pop(prefix)
# sx,sy = self.GetSize()
# self.SetSize((sx, sy+1))
# self.SetSize((sx, sy))
def onPick2EraseTimer(self, evt=None):
"""erases line trace showing automated 'Pick 2' guess """
self.pick2erase_timer.Stop()
panel = self.pick2erase_panel
ntrace = panel.conf.ntrace - 1
trace = panel.conf.get_mpl_line(ntrace)
panel.conf.get_mpl_line(ntrace).set_data(np.array([]), np.array([]))
panel.conf.ntrace = ntrace
panel.draw()
def onPick2Timer(self, evt=None):
"""checks for 'Pick 2' events, and initiates 'Pick 2' guess
for a model from the selected data range
"""
try:
plotframe = self.controller.get_display()
curhist = plotframe.cursor_hist[:]
plotframe.Raise()
except:
return
if (time.time() - self.pick2_t0) > self.pick2_timeout:
msg = self.pick2_group.pick2_msg.SetLabel(" ")
plotframe.cursor_hist = []
self.pick2_timer.Stop()
return
if len(curhist) < 2:
self.pick2_group.pick2_msg.SetLabel("%i/2" % (len(curhist)))
return
self.pick2_group.pick2_msg.SetLabel("done.")
self.pick2_timer.Stop()
# guess param values
xcur = (curhist[0][0], curhist[1][0])
xmin, xmax = min(xcur), max(xcur)
dgroup = getattr(self.larch.symtable, self.controller.groupname)
x, y = dgroup.xdat, dgroup.ydat
i0 = index_of(dgroup.xdat, xmin)
i1 = index_of(dgroup.xdat, xmax)
x, y = dgroup.xdat[i0:i1+1], dgroup.ydat[i0:i1+1]
mod = self.pick2_group.mclass(prefix=self.pick2_group.prefix)
parwids = self.pick2_group.parwids
try:
guesses = mod.guess(y, x=x)
except:
return
for name, param in guesses.items():
if name in parwids:
parwids[name].value.SetValue(param.value)
dgroup._tmp = mod.eval(guesses, x=dgroup.xdat)
plotframe = self.controller.get_display()
plotframe.cursor_hist = []
plotframe.oplot(dgroup.xdat, dgroup._tmp)
self.pick2erase_panel = plotframe.panel
self.pick2erase_timer.Start(5000)
def onPick2Points(self, evt=None, prefix=None):
fgroup = self.fit_components.get(prefix, None)
if fgroup is None:
return
plotframe = self.controller.get_display()
plotframe.Raise()
plotframe.cursor_hist = []
fgroup.npts = 0
self.pick2_group = fgroup
if fgroup.pick2_msg is not None:
fgroup.pick2_msg.SetLabel("0/2")
self.pick2_t0 = time.time()
self.pick2_timer.Start(250)
def onSaveFitResult(self, event=None):
dgroup = self.controller.get_group()
deffile = dgroup.filename.replace('.', '_') + '.modl'
outfile = FileSave(self, 'Save Fit Result',
default_file=deffile,
wildcard=ModelWcards)
if outfile is not None:
try:
self.save_fit_result(dgroup.fit_history[-1], outfile)
except IOError:
print('could not write %s' % outfile)
def onLoadFitResult(self, event=None):
mfile = FileOpen(self, 'Load Fit Result',
default_file='', wildcard=ModelWcards)
if mfile is not None:
self.load_modelresult(mfile)
def save_fit_result(self, fitresult, outfile):
"""saves a customized ModelResult"""
save_modelresult(fitresult, outfile)
def load_modelresult(self, inpfile):
"""read a customized ModelResult"""
result = load_modelresult(inpfile)
for prefix in list(self.fit_components.keys()):
self.onDeleteComponent(self, prefix=prefix)
for comp in result.model.components:
isbkg = comp.prefix in result.user_options['bkg_components']
self.addModel(model=comp.func.__name__,
prefix=comp.prefix, isbkg=isbkg)
for comp in result.model.components:
parwids = self.fit_components[comp.prefix].parwids
for pname, par in result.params.items():
if pname in parwids:
wids = parwids[pname]
if wids.minval is not None:
wids.minval.SetValue(par.min)
if wids.maxval is not None:
wids.maxval.SetValue(par.max)
val = result.init_values.get(pname, par.value)
wids.value.SetValue(val)
self.fill_form(result.user_options)
return result
def onExportFitResult(self, event=None):
dgroup = self.controller.get_group()
deffile = dgroup.filename.replace('.', '_') + '_result.xdi'
wcards = 'All files (*.*)|*.*'
outfile = FileSave(self, 'Export Fit Result',
default_file=deffile, wildcard=wcards)
if outfile is not None:
i1, i2 = self.get_xranges(dgroup.xdat)
x = dgroup.xdat[i1:i2]
y = dgroup.ydat[i1:i2]
yerr = None
if hasattr(dgroup, 'yerr'):
yerr = 1.0*dgroup.yerr
if not isinstance(yerr, np.ndarray):
yerr = yerr * np.ones(len(y))
else:
yerr = yerr[i1:i2]
export_modelresult(dgroup.fit_history[-1],
filename=outfile,
datafile=dgroup.filename,
ydata=y, yerr=yerr, x=x)
def onSelPoint(self, evt=None, opt='__', relative_e0=False, win=None):
"""
get last selected point from a specified plot window
and fill in the value for the widget defined by `opt`.
by default it finds the latest cursor position from the
cursor history of the first 20 plot windows.
"""
if opt not in self.wids:
return None
_x, _y = last_cursor_pos(win=win, _larch=self.larch)
if _x is not None:
if relative_e0 and 'e0' in self.wids:
_x -= self.wids['e0'].GetValue()
self.wids[opt].SetValue(_x)
def get_xranges(self, x):
opts = self.read_form()
dgroup = self.controller.get_group()
en_eps = min(np.diff(dgroup.energy)) / 5.
i1 = index_of(x, opts['emin'] + en_eps)
i2 = index_of(x, opts['emax'] + en_eps) + 1
return i1, i2
def build_fitmodel(self):
""" use fit components to build model"""
dgroup = self.controller.get_group()
fullmodel = None
params = Parameters()
self.summary = {'components': [], 'options': {}}
peaks = []
for comp in self.fit_components.values():
_cen, _amp = None, None
if comp.usebox is not None and comp.usebox.IsChecked():
for parwids in comp.parwids.values():
params.add(parwids.param)
#print(" add param ", parwids.param)
if parwids.param.name.endswith('_center'):
_cen = parwids.param.name
elif parwids.param.name.endswith('_amplitude'):
_amp = parwids.param.name
self.summary['components'].append((comp.mclass.__name__, comp.mclass_kws))
thismodel = comp.mclass(**comp.mclass_kws)
if fullmodel is None:
fullmodel = thismodel
else:
fullmodel += thismodel
if not comp.bkgbox.IsChecked() and _cen is not None and _amp is not None:
peaks.append((_amp, _cen))
if len(peaks) > 0:
denom = '+'.join([p[0] for p in peaks])
numer = '+'.join(["%s*%s "% p for p in peaks])
params.add('fit_centroid', expr="(%s)/(%s)" %(numer, denom))
self.fit_model = fullmodel
self.fit_params = params
if dgroup is not None:
i1, i2 = self.get_xranges(dgroup.xdat)
xsel = dgroup.xdat[i1:i2]
dgroup.xfit = xsel
dgroup.yfit = self.fit_model.eval(self.fit_params, x=xsel)
dgroup.ycomps = self.fit_model.eval_components(params=self.fit_params,
x=xsel)
return dgroup
def onFitSelected(self, event=None):
dgroup = self.build_fitmodel()
opts = self.read_form()
print("fitting selected groups in progress")
def onFitModel(self, event=None):
dgroup = self.build_fitmodel()
opts = self.read_form()
i1, i2 = self.get_xranges(dgroup.xdat)
dgroup.xfit = dgroup.xdat[i1:i2]
ysel = dgroup.ydat[i1:i2]
# print('onFit Model : xrange ', i1, i2, len(dgroup.xfit), len(dgroup.yfit))
weights = np.ones(len(ysel))
if hasattr(dgroup, 'yerr'):
yerr = 1.0*dgroup.yerr
if not isinstance(yerr, np.ndarray):
yerr = yerr * np.ones(len(ysel))
else:
yerr = yerr[i1:i2]
yerr_min = 1.e-9*ysel.mean()
yerr[np.where(yerr < yerr_min)] = yerr_min
weights = 1.0/yerr
result = self.fit_model.fit(ysel, params=self.fit_params,
x=dgroup.xfit, weights=weights,
method='leastsq')
self.summary['xmin'] = dgroup.xdat[i1]
self.summary['xmax'] = dgroup.xdat[i2]
for attr in ('aic', 'bic', 'chisqr', 'redchi', 'ci_out', 'covar',
'flatchain', 'success', 'nan_policy', 'nfev', 'ndata',
'nfree', 'nvarys', 'init_values'):
self.summary[attr] = getattr(result, attr)
self.summary['params'] = result.params
dgroup.yfit = result.best_fit
dgroup.ycomps = self.fit_model.eval_components(params=result.params,
x=dgroup.xfit)
result.model_repr = self.fit_model._reprstring(long=True)
## hacks to save user options
result.user_options = opts
bkg_comps = []
for label, comp in self.fit_components.items():
if comp.bkgbox.IsChecked():
bkg_comps.append(label)
result.user_options['bkg_components'] = bkg_comps
self.autosave_modelresult(result)
if not hasattr(dgroup, 'fit_history'):
dgroup.fit_history = []
dgroup.fit_history.append(result)
self.plot_choice.SetStringSelection(PLOT_FIT)
self.onPlot()
self.parent.show_subframe('prepeak_result_frame', FitResultFrame,
datagroup=dgroup, peakframe=self)
self.parent.subframes['prepeak_result_frame'].show_fitresult()
[m.Enable(True) for m in self.parent.afterfit_menus]
def update_start_values(self, params):
"""fill parameters with best fit values"""
allparwids = {}
for comp in self.fit_components.values():
if comp.usebox is not None and comp.usebox.IsChecked():
for name, parwids in comp.parwids.items():
allparwids[name] = parwids
for pname, par in params.items():
if pname in allparwids:
allparwids[pname].value.SetValue(par.value)
def autosave_modelresult(self, result, fname=None):
"""autosave model result to user larch folder"""
xasguidir = os.path.join(site_config.usr_larchdir, 'xasgui')
if not os.path.exists(xasguidir):
try:
os.makedirs(xasguidir)
except OSError:
print("Warning: cannot create XAS GUI user folder")
return
if not HAS_MODELSAVE:
print("Warning: cannot save model results: upgrade lmfit")
return
if fname is None:
fname = 'autosave.fitresult'
fname = os.path.join(xasguidir, fname)
self.save_fit_result(result, fname)
class PrePeakPanel(TaskPanel):
def __init__(self, parent=None, controller=None, **kws):
TaskPanel.__init__(self, parent, controller,
configname='prepeaks_config',
config=defaults, **kws)
self.fit_components = OrderedDict()
self.user_added_params = None
self.pick2_timer = wx.Timer(self)
self.pick2_group = None
self.Bind(wx.EVT_TIMER, self.onPick2Timer, self.pick2_timer)
self.pick2_t0 = 0.
self.pick2_timeout = 15.
self.pick2erase_timer = wx.Timer(self)
self.pick2erase_panel = None
self.Bind(wx.EVT_TIMER, self.onPick2EraseTimer, self.pick2erase_timer)
def onPanelExposed(self, **kws):
# called when notebook is selected
try:
fname = self.controller.filelist.GetStringSelection()
gname = self.controller.file_groups[fname]
dgroup = self.controller.get_group(gname)
self.fill_form(dgroup)
except:
pass # print(" Cannot Fill prepeak panel from group ")
def build_display(self):
self.mod_nb = flatnotebook(self, {})
pan = self.panel = GridPanel(self, ncols=4, nrows=4, pad=2, itemstyle=LEFT)
self.wids = {}
fsopts = dict(digits=2, increment=0.1, with_pin=True)
ppeak_e0 = self.add_floatspin('ppeak_e0', value=0, **fsopts)
ppeak_elo = self.add_floatspin('ppeak_elo', value=-15, **fsopts)
ppeak_ehi = self.add_floatspin('ppeak_ehi', value=-5, **fsopts)
ppeak_emin = self.add_floatspin('ppeak_emin', value=-30, **fsopts)
ppeak_emax = self.add_floatspin('ppeak_emax', value=0, **fsopts)
self.fitbline_btn = Button(pan,'Fit Baseline', action=self.onFitBaseline,
size=(125, -1))
self.plotmodel_btn = Button(pan, 'Plot Model',
action=self.onPlotModel, size=(125, -1))
self.fitmodel_btn = Button(pan, 'Fit Model',
action=self.onFitModel, size=(125, -1))
self.loadmodel_btn = Button(pan, 'Load Model',
action=self.onLoadFitResult, size=(125, -1))
self.fitmodel_btn.Disable()
self.array_choice = Choice(pan, size=(175, -1),
choices=list(Array_Choices.keys()))
self.array_choice.SetSelection(1)
models_peaks = Choice(pan, size=(150, -1),
choices=ModelChoices['peaks'],
action=self.addModel)
models_other = Choice(pan, size=(150, -1),
choices=ModelChoices['other'],
action=self.addModel)
self.models_peaks = models_peaks
self.models_other = models_other
self.message = SimpleText(pan,
'first fit baseline, then add peaks to fit model.')
self.msg_centroid = SimpleText(pan, '----')
opts = dict(default=True, size=(75, -1), action=self.onPlot)
self.show_centroid = Check(pan, label='show?', **opts)
self.show_peakrange = Check(pan, label='show?', **opts)
self.show_fitrange = Check(pan, label='show?', **opts)
self.show_e0 = Check(pan, label='show?', **opts)
opts = dict(default=False, size=(200, -1), action=self.onPlot)
def add_text(text, dcol=1, newrow=True):
pan.Add(SimpleText(pan, text), dcol=dcol, newrow=newrow)
pan.Add(SimpleText(pan, ' Pre-edge Peak Fitting',
**self.titleopts), dcol=5)
add_text(' Run Fit:', newrow=False)
add_text('Array to fit: ')
pan.Add(self.array_choice, dcol=3)
pan.Add((10, 10))
pan.Add(self.fitbline_btn)
add_text('E0: ')
pan.Add(ppeak_e0)
pan.Add((10, 10), dcol=2)
pan.Add(self.show_e0)
pan.Add(self.plotmodel_btn)
add_text('Fit Energy Range: ')
pan.Add(ppeak_emin)
add_text(' : ', newrow=False)
pan.Add(ppeak_emax)
pan.Add(self.show_fitrange)
pan.Add(self.fitmodel_btn)
t = SimpleText(pan, 'Pre-edge Peak Range: ')
SetTip(t, 'Range used as mask for background')
pan.Add(t, newrow=True)
pan.Add(ppeak_elo)
add_text(' : ', newrow=False)
pan.Add(ppeak_ehi)
pan.Add(self.show_peakrange)
# pan.Add(self.fitsel_btn)
add_text( 'Peak Centroid: ')
pan.Add(self.msg_centroid, dcol=3)
pan.Add(self.show_centroid, dcol=1)
pan.Add(self.loadmodel_btn)
# add model
ts = wx.BoxSizer(wx.HORIZONTAL)
ts.Add(models_peaks)
ts.Add(models_other)
pan.Add(SimpleText(pan, 'Add Component: '), newrow=True)
pan.Add(ts, dcol=7)
pan.Add(SimpleText(pan, 'Messages: '), newrow=True)
pan.Add(self.message, dcol=7)
pan.pack()
sizer = wx.BoxSizer(wx.VERTICAL)
sizer.Add((10, 10), 0, LEFT, 3)
sizer.Add(pan, 0, LEFT, 3)
sizer.Add((10, 10), 0, LEFT, 3)
sizer.Add(HLine(self, size=(550, 2)), 0, LEFT, 3)
sizer.Add((10, 10), 0, LEFT, 3)
sizer.Add(self.mod_nb, 1, LEFT|wx.GROW, 10)
pack(self, sizer)
def get_config(self, dgroup=None):
"""get processing configuration for a group"""
if dgroup is None:
dgroup = self.controller.get_group()
conf = getattr(dgroup, 'prepeak_config', {})
if 'e0' not in conf:
conf = defaults
conf['e0'] = getattr(dgroup, 'e0', -1)
dgroup.prepeak_config = conf
if not hasattr(dgroup, 'prepeaks'):
dgroup.prepeaks = Group()
return conf
def fill_form(self, dat):
if isinstance(dat, Group):
self.wids['ppeak_e0'].SetValue(dat.e0)
if hasattr(dat, 'prepeaks'):
self.wids['ppeak_emin'].SetValue(dat.prepeaks.emin)
self.wids['ppeak_emax'].SetValue(dat.prepeaks.emax)
self.wids['ppeak_elo'].SetValue(dat.prepeaks.elo)
self.wids['ppeak_ehi'].SetValue(dat.prepeaks.ehi)
elif isinstance(dat, dict):
self.wids['ppeak_e0'].SetValue(dat['e0'])
self.wids['ppeak_emin'].SetValue(dat['emin'])
self.wids['ppeak_emax'].SetValue(dat['emax'])
self.wids['ppeak_elo'].SetValue(dat['elo'])
self.wids['ppeak_ehi'].SetValue(dat['ehi'])
self.array_choice.SetStringSelection(dat['array_desc'])
self.show_e0.Enable(dat['show_e0'])
self.show_centroid.Enable(dat['show_centroid'])
self.show_fitrange.Enable(dat['show_fitrange'])
self.show_peakrange.Enable(dat['show_peakrange'])
def read_form(self):
"read for, returning dict of values"
dgroup = self.controller.get_group()
array_desc = self.array_choice.GetStringSelection()
form_opts = {'gname': dgroup.groupname,
'filename': dgroup.filename,
'array_desc': array_desc.lower(),
'array_name': Array_Choices[array_desc],
'baseline_form': 'lorentzian',
'bkg_components': []}
form_opts['e0'] = self.wids['ppeak_e0'].GetValue()
form_opts['emin'] = self.wids['ppeak_emin'].GetValue()
form_opts['emax'] = self.wids['ppeak_emax'].GetValue()
form_opts['elo'] = self.wids['ppeak_elo'].GetValue()
form_opts['ehi'] = self.wids['ppeak_ehi'].GetValue()
form_opts['plot_sub_bline'] = False # self.plot_sub_bline.IsChecked()
form_opts['show_centroid'] = self.show_centroid.IsChecked()
form_opts['show_peakrange'] = self.show_peakrange.IsChecked()
form_opts['show_fitrange'] = self.show_fitrange.IsChecked()
form_opts['show_e0'] = self.show_e0.IsChecked()
return form_opts
def onFitBaseline(self, evt=None):
opts = self.read_form()
cmd = """{gname:s}.ydat = 1.0*{gname:s}.{array_name:s}
pre_edge_baseline(energy={gname:s}.energy, norm={gname:s}.ydat, group={gname:s}, form='{baseline_form:s}',
with_line=True, elo={elo:.3f}, ehi={ehi:.3f}, emin={emin:.3f}, emax={emax:.3f})"""
self.larch_eval(cmd.format(**opts))
dgroup = self.controller.get_group()
ppeaks = dgroup.prepeaks
dgroup.centroid_msg = "%.4f +/- %.4f eV" % (ppeaks.centroid,
ppeaks.delta_centroid)
self.msg_centroid.SetLabel(dgroup.centroid_msg)
if 'bpeak_' not in self.fit_components:
self.addModel(model='Lorentzian', prefix='bpeak_', isbkg=True)
if 'bline_' not in self.fit_components:
self.addModel(model='Linear', prefix='bline_', isbkg=True)
for prefix in ('bpeak_', 'bline_'):
cmp = self.fit_components[prefix]
# cmp.bkgbox.SetValue(1)
self.fill_model_params(prefix, dgroup.prepeaks.fit_details.params)
self.fill_form(dgroup)
self.fitmodel_btn.Enable()
# self.fitallmodel_btn.Enable()
i1, i2 = self.get_xranges(dgroup.energy)
dgroup.yfit = dgroup.xfit = 0.0*dgroup.energy[i1:i2]
# self.plot_choice.SetStringSelection(PLOT_BASELINE)
self.onPlot(baseline_only=True)
def fill_model_params(self, prefix, params):
comp = self.fit_components[prefix]
parwids = comp.parwids
for pname, par in params.items():
pname = prefix + pname
if pname in parwids:
wids = parwids[pname]
if wids.minval is not None:
wids.minval.SetValue(par.min)
if wids.maxval is not None:
wids.maxval.SetValue(par.max)
wids.value.SetValue(par.value)
varstr = 'vary' if par.vary else 'fix'
if par.expr is not None:
varstr = 'constrain'
if wids.vary is not None:
wids.vary.SetStringSelection(varstr)
def onPlotModel(self, evt=None):
dgroup = self.controller.get_group()
g = self.build_fitmodel(dgroup)
self.onPlot(show_init=True)
def onPlot(self, evt=None, baseline_only=False, show_init=False):
opts = self.read_form()
dgroup = self.controller.get_group()
opts['group'] = opts['gname']
self.larch_eval(COMMANDS['prepeaks_setup'].format(**opts))
cmd = "plot_prepeaks_fit"
args = ['{gname}']
if baseline_only:
cmd = "plot_prepeaks_baseline"
else:
args.append("show_init=%s" % (show_init))
cmd = "%s(%s)" % (cmd, ', '.join(args))
self.larch_eval(cmd.format(**opts))
def addModel(self, event=None, model=None, prefix=None, isbkg=False):
if model is None and event is not None:
model = event.GetString()
if model is None or model.startswith('<'):
return
self.models_peaks.SetSelection(0)
self.models_other.SetSelection(0)
if prefix is None:
p = model[:5].lower()
curmodels = ["%s%i_" % (p, i+1) for i in range(1+len(self.fit_components))]
for comp in self.fit_components:
if comp in curmodels:
curmodels.remove(comp)
prefix = curmodels[0]
label = "%s(prefix='%s')" % (model, prefix)
title = "%s: %s " % (prefix[:-1], model)
title = prefix[:-1]
mclass_kws = {'prefix': prefix}
if 'step' in model.lower():
form = model.lower().replace('step', '').strip()
if form.startswith('err'):
form = 'erf'
label = "Step(form='%s', prefix='%s')" % (form, prefix)
title = "%s: Step %s" % (prefix[:-1], form[:3])
mclass = lm_models.StepModel
mclass_kws['form'] = form
minst = mclass(form=form, prefix=prefix)
else:
if model in ModelFuncs:
mclass = getattr(lm_models, ModelFuncs[model])
else:
mclass = getattr(lm_models, model+'Model')
minst = mclass(prefix=prefix)
panel = GridPanel(self.mod_nb, ncols=2, nrows=5, pad=1, itemstyle=CEN)
def SLabel(label, size=(80, -1), **kws):
return SimpleText(panel, label,
size=size, style=wx.ALIGN_LEFT, **kws)
usebox = Check(panel, default=True, label='Use in Fit?', size=(100, -1))
bkgbox = Check(panel, default=False, label='Is Baseline?', size=(125, -1))
if isbkg:
bkgbox.SetValue(1)
delbtn = Button(panel, 'Delete This Component', size=(200, -1),
action=partial(self.onDeleteComponent, prefix=prefix))
pick2msg = SimpleText(panel, " ", size=(125, -1))
pick2btn = Button(panel, 'Pick Values from Plotted Data', size=(200, -1),
action=partial(self.onPick2Points, prefix=prefix))
# SetTip(mname, 'Label for the model component')
SetTip(usebox, 'Use this component in fit?')
SetTip(bkgbox, 'Label this component as "background" when plotting?')
SetTip(delbtn, 'Delete this model component')
SetTip(pick2btn, 'Select X range on Plot to Guess Initial Values')
panel.Add(SLabel(label, size=(275, -1), colour='#0000AA'),
dcol=4, style=wx.ALIGN_LEFT, newrow=True)
panel.Add(usebox, dcol=2)
panel.Add(bkgbox, dcol=1, style=RIGHT)
panel.Add(pick2btn, dcol=2, style=wx.ALIGN_LEFT, newrow=True)
panel.Add(pick2msg, dcol=3, style=wx.ALIGN_RIGHT)
panel.Add(delbtn, dcol=2, style=wx.ALIGN_RIGHT)
# panel.Add(HLine(panel, size=(150, 3)), dcol=4, style=wx.ALIGN_CENTER)
panel.Add(SLabel("Parameter "), style=wx.ALIGN_LEFT, newrow=True)
panel.AddMany((SLabel(" Value"), SLabel(" Type"), SLabel(' Bounds'),
SLabel(" Min", size=(60, -1)),
SLabel(" Max", size=(60, -1)), SLabel(" Expression")))
parwids = OrderedDict()
parnames = sorted(minst.param_names)
for a in minst._func_allargs:
pname = "%s%s" % (prefix, a)
if (pname not in parnames and
a in minst.param_hints and
a not in minst.independent_vars):
parnames.append(pname)
for pname in parnames:
sname = pname[len(prefix):]
hints = minst.param_hints.get(sname, {})
par = Parameter(name=pname, value=0, vary=True)
if 'min' in hints:
par.min = hints['min']
if 'max' in hints:
par.max = hints['max']
if 'value' in hints:
par.value = hints['value']
if 'expr' in hints:
par.expr = hints['expr']
pwids = ParameterWidgets(panel, par, name_size=100, expr_size=150,
float_size=80, prefix=prefix,
widgets=('name', 'value', 'minval',
'maxval', 'vary', 'expr'))
parwids[par.name] = pwids
panel.Add(pwids.name, newrow=True)
panel.AddMany((pwids.value, pwids.vary, pwids.bounds,
pwids.minval, pwids.maxval, pwids.expr))
for sname, hint in minst.param_hints.items():
pname = "%s%s" % (prefix, sname)
if 'expr' in hint and pname not in parnames:
par = Parameter(name=pname, value=0, expr=hint['expr'])
pwids = ParameterWidgets(panel, par, name_size=100, expr_size=400,
float_size=80, prefix=prefix,
widgets=('name', 'value', 'expr'))
parwids[par.name] = pwids
panel.Add(pwids.name, newrow=True)
panel.Add(pwids.value)
panel.Add(pwids.expr, dcol=5, style=wx.ALIGN_RIGHT)
pwids.value.Disable()
fgroup = Group(prefix=prefix, title=title, mclass=mclass,
mclass_kws=mclass_kws, usebox=usebox, panel=panel,
parwids=parwids, float_size=65, expr_size=150,
pick2_msg=pick2msg, bkgbox=bkgbox)
self.fit_components[prefix] = fgroup
panel.pack()
self.mod_nb.AddPage(panel, title, True)
sx,sy = self.GetSize()
self.SetSize((sx, sy+1))
self.SetSize((sx, sy))
self.fitmodel_btn.Enable()
def onDeleteComponent(self, evt=None, prefix=None):
fgroup = self.fit_components.get(prefix, None)
if fgroup is None:
return
for i in range(self.mod_nb.GetPageCount()):
if fgroup.title == self.mod_nb.GetPageText(i):
self.mod_nb.DeletePage(i)
for attr in dir(fgroup):
setattr(fgroup, attr, None)
self.fit_components.pop(prefix)
if len(self.fit_components) < 1:
self.fitmodel_btn.Disable()
# sx,sy = self.GetSize()
# self.SetSize((sx, sy+1))
# self.SetSize((sx, sy))
def onPick2EraseTimer(self, evt=None):
"""erases line trace showing automated 'Pick 2' guess """
self.pick2erase_timer.Stop()
panel = self.pick2erase_panel
ntrace = panel.conf.ntrace - 1
trace = panel.conf.get_mpl_line(ntrace)
panel.conf.get_mpl_line(ntrace).set_data(np.array([]), np.array([]))
panel.conf.ntrace = ntrace
panel.draw()
def onPick2Timer(self, evt=None):
"""checks for 'Pick 2' events, and initiates 'Pick 2' guess
for a model from the selected data range
"""
try:
plotframe = self.controller.get_display(win=1)
curhist = plotframe.cursor_hist[:]
plotframe.Raise()
except:
return
if (time.time() - self.pick2_t0) > self.pick2_timeout:
msg = self.pick2_group.pick2_msg.SetLabel(" ")
plotframe.cursor_hist = []
self.pick2_timer.Stop()
return
if len(curhist) < 2:
self.pick2_group.pick2_msg.SetLabel("%i/2" % (len(curhist)))
return
self.pick2_group.pick2_msg.SetLabel("done.")
self.pick2_timer.Stop()
# guess param values
xcur = (curhist[0][0], curhist[1][0])
xmin, xmax = min(xcur), max(xcur)
dgroup = getattr(self.larch.symtable, self.controller.groupname)
x, y = dgroup.xdat, dgroup.ydat
i0 = index_of(dgroup.xdat, xmin)
i1 = index_of(dgroup.xdat, xmax)
x, y = dgroup.xdat[i0:i1+1], dgroup.ydat[i0:i1+1]
mod = self.pick2_group.mclass(prefix=self.pick2_group.prefix)
parwids = self.pick2_group.parwids
try:
guesses = mod.guess(y, x=x)
except:
return
for name, param in guesses.items():
if name in parwids:
parwids[name].value.SetValue(param.value)
dgroup._tmp = mod.eval(guesses, x=dgroup.xdat)
plotframe = self.controller.get_display(win=1)
plotframe.cursor_hist = []
plotframe.oplot(dgroup.xdat, dgroup._tmp)
self.pick2erase_panel = plotframe.panel
self.pick2erase_timer.Start(5000)
def onPick2Points(self, evt=None, prefix=None):
fgroup = self.fit_components.get(prefix, None)
if fgroup is None:
return
plotframe = self.controller.get_display(win=1)
plotframe.Raise()
plotframe.cursor_hist = []
fgroup.npts = 0
self.pick2_group = fgroup
if fgroup.pick2_msg is not None:
fgroup.pick2_msg.SetLabel("0/2")
self.pick2_t0 = time.time()
self.pick2_timer.Start(250)
def onLoadFitResult(self, event=None):
dlg = wx.FileDialog(self, message="Load Saved File Model",
wildcard=ModelWcards, style=wx.FD_OPEN)
rfile = None
if dlg.ShowModal() == wx.ID_OK:
rfile = dlg.GetPath()
dlg.Destroy()
if rfile is None:
return
self.larch_eval("# peakmodel = lm_load_modelresult('%s')" %rfile)
result = load_modelresult(str(rfile))
for prefix in list(self.fit_components.keys()):
self.onDeleteComponent(self, prefix=prefix)
for comp in result.model.components:
isbkg = comp.prefix in result.user_options['bkg_components']
self.addModel(model=comp.func.__name__,
prefix=comp.prefix, isbkg=isbkg)
for comp in result.model.components:
parwids = self.fit_components[comp.prefix].parwids
for pname, par in result.params.items():
if pname in parwids:
wids = parwids[pname]
if wids.minval is not None:
wids.minval.SetValue(par.min)
if wids.maxval is not None:
wids.maxval.SetValue(par.max)
val = result.init_values.get(pname, par.value)
wids.value.SetValue(val)
self.fill_form(result.user_options)
def onSelPoint(self, evt=None, opt='__', relative_e0=False, win=None):
"""
get last selected point from a specified plot window
and fill in the value for the widget defined by `opt`.
by default it finds the latest cursor position from the
cursor history of the first 20 plot windows.
"""
if opt not in self.wids:
return None
_x, _y = last_cursor_pos(win=win, _larch=self.larch)
if _x is not None:
if relative_e0 and 'e0' in self.wids:
_x -= self.wids['e0'].GetValue()
self.wids[opt].SetValue(_x)
def get_xranges(self, x):
opts = self.read_form()
dgroup = self.controller.get_group()
en_eps = min(np.diff(dgroup.energy)) / 5.
i1 = index_of(x, opts['emin'] + en_eps)
i2 = index_of(x, opts['emax'] + en_eps) + 1
return i1, i2
def build_fitmodel(self, dgroup):
""" use fit components to build model"""
# self.summary = {'components': [], 'options': {}}
peaks = []
cmds = ["## set up pre-edge peak parameters", "peakpars = Parameters()"]
modcmds = ["## define pre-edge peak model"]
modop = " ="
opts = self.read_form()
opts['group'] = opts['gname']
self.larch_eval(COMMANDS['prepeaks_setup'].format(**opts))
for comp in self.fit_components.values():
_cen, _amp = None, None
if comp.usebox is not None and comp.usebox.IsChecked():
for parwids in comp.parwids.values():
this = parwids.param
pargs = ["'%s'" % this.name, 'value=%f' % (this.value),
'min=%f' % (this.min), 'max=%f' % (this.max)]
if this.expr is not None:
pargs.append("expr='%s'" % (this.expr))
elif not this.vary:
pargs.pop()
pargs.pop()
pargs.append("vary=False")
cmds.append("peakpars.add(%s)" % (', '.join(pargs)))
if this.name.endswith('_center'):
_cen = this.name
elif parwids.param.name.endswith('_amplitude'):
_amp = this.name
compargs = ["%s='%s'" % (k,v) for k,v in comp.mclass_kws.items()]
modcmds.append("peakmodel %s %s(%s)" % (modop, comp.mclass.__name__,
', '.join(compargs)))
modop = "+="
if not comp.bkgbox.IsChecked() and _cen is not None and _amp is not None:
peaks.append((_amp, _cen))
if len(peaks) > 0:
denom = '+'.join([p[0] for p in peaks])
numer = '+'.join(["%s*%s "% p for p in peaks])
cmds.append("peakpars.add('fit_centroid', expr='(%s)/(%s)')" % (numer, denom))
cmds.extend(modcmds)
cmds.append(COMMANDS['prepfit'].format(group=dgroup.groupname,
user_opts=repr(opts)))
self.larch_eval("\n".join(cmds))
def onFitSelected(self, event=None):
dgroup = self.controller.get_group()
self.build_fitmodel(dgroup)
def onFitModel(self, event=None):
dgroup = self.controller.get_group()
if dgroup is None:
return
self.build_fitmodel(dgroup)
opts = self.read_form()
dgroup = self.controller.get_group()
opts['group'] = opts['gname']
self.larch_eval(COMMANDS['prepeaks_setup'].format(**opts))
ppeaks = dgroup.prepeaks
# add bkg_component to saved user options
bkg_comps = []
for label, comp in self.fit_components.items():
if comp.bkgbox.IsChecked():
bkg_comps.append(label)
opts['bkg_components'] = bkg_comps
imin, imax = self.get_xranges(dgroup.xdat)
cmds = ["## do peak fit: "]
yerr_type = 'set_yerr_const'
yerr = getattr(dgroup, 'yerr', None)
if yerr is None:
if hasattr(dgroup, 'norm_std'):
cmds.append("{group}.yerr = {group}.norm_std")
yerr_type = 'set_yerr_array'
elif hasattr(dgroup, 'mu_std'):
cmds.append("{group}.yerr = {group}.mu_std/(1.e-15+{group}.edge_step)")
yerr_type = 'set_yerr_array'
else:
cmds.append("{group}.yerr = 1")
elif isinstance(dgroup.yerr, np.ndarray):
yerr_type = 'set_yerr_array'
cmds.extend([COMMANDS[yerr_type], COMMANDS['dofit']])
cmd = '\n'.join(cmds)
self.larch_eval(cmd.format(group=dgroup.groupname,
imin=imin, imax=imax,
user_opts=repr(opts)))
self.autosave_modelresult(self.larch_get("peakresult"))
self.onPlot()
self.show_subframe('prepeak_result_frame', FitResultFrame,
datagroup=dgroup, peakframe=self)
self.subframes['prepeak_result_frame'].show_results()
def update_start_values(self, params):
"""fill parameters with best fit values"""
allparwids = {}
for comp in self.fit_components.values():
if comp.usebox is not None and comp.usebox.IsChecked():
for name, parwids in comp.parwids.items():
allparwids[name] = parwids
for pname, par in params.items():
if pname in allparwids:
allparwids[pname].value.SetValue(par.value)
def autosave_modelresult(self, result, fname=None):
"""autosave model result to user larch folder"""
confdir = os.path.join(site_config.usr_larchdir, 'xas_viewer')
if not os.path.exists(confdir):
try:
os.makedirs(confdir)
except OSError:
print("Warning: cannot create XAS_Viewer user folder")
return
if not HAS_MODELSAVE:
print("Warning: cannot save model results: upgrade lmfit")
return
if fname is None:
fname = 'autosave.fitmodel'
save_modelresult(result, os.path.join(confdir, fname))