class FitWidgetMixin(CurveWidgetMixin):
def __init__(self, wintitle="guiqwt plot", icon="guiqwt.svg",
toolbar=False, options=None, panels=None, param_cols=1,
legend_anchor='TR', auto_fit=True):
if wintitle is None:
wintitle = _('Curve fitting')
self.x = None
self.y = None
self.fitfunc = None
self.fitargs = None
self.fitkwargs = None
self.fitparams = None
self.autofit_prm = None
self.data_curve = None
self.fit_curve = None
self.legend = None
self.legend_anchor = legend_anchor
self.xrange = None
self.show_xrange = False
self.param_cols = param_cols
self.auto_fit_enabled = auto_fit
self.button_list = [] # list of buttons to be disabled at startup
self.fit_layout = None
self.params_layout = None
CurveWidgetMixin.__init__(self, wintitle=wintitle, icon=icon,
toolbar=toolbar, options=options,
panels=panels)
self.refresh()
# QWidget API --------------------------------------------------------------
def resizeEvent(self, event):
QWidget.resizeEvent(self, event)
self.get_plot().replot()
# CurveWidgetMixin API -----------------------------------------------------
def setup_widget_layout(self):
self.fit_layout = QHBoxLayout()
self.params_layout = QGridLayout()
params_group = create_groupbox(self, _("Fit parameters"),
layout=self.params_layout)
if self.auto_fit_enabled:
auto_group = self.create_autofit_group()
self.fit_layout.addWidget(auto_group)
self.fit_layout.addWidget(params_group)
self.plot_layout.addLayout(self.fit_layout, 1, 0)
vlayout = QVBoxLayout(self)
vlayout.addWidget(self.toolbar)
vlayout.addLayout(self.plot_layout)
self.setLayout(vlayout)
def create_plot(self, options):
CurveWidgetMixin.create_plot(self, options)
for plot in self.get_plots():
plot.SIG_RANGE_CHANGED.connect(self.range_changed)
# Public API ---------------------------------------------------------------
def set_data(self, x, y, fitfunc=None, fitparams=None,
fitargs=None, fitkwargs=None):
if self.fitparams is not None and fitparams is not None:
self.clear_params_layout()
self.x = x
self.y = y
if fitfunc is not None:
self.fitfunc = fitfunc
if fitparams is not None:
self.fitparams = fitparams
if fitargs is not None:
self.fitargs = fitargs
if fitkwargs is not None:
self.fitkwargs = fitkwargs
self.autofit_prm = AutoFitParam(title=_("Automatic fitting options"))
self.autofit_prm.xmin = x.min()
self.autofit_prm.xmax = x.max()
self.compute_imin_imax()
if self.fitparams is not None and fitparams is not None:
self.populate_params_layout()
self.refresh()
def set_fit_data(self, fitfunc, fitparams, fitargs=None, fitkwargs=None):
if self.fitparams is not None:
self.clear_params_layout()
self.fitfunc = fitfunc
self.fitparams = fitparams
self.fitargs = fitargs
self.fitkwargs = fitkwargs
self.populate_params_layout()
self.refresh()
def clear_params_layout(self):
for i, param in enumerate(self.fitparams):
for widget in param.get_widgets():
if widget is not None:
self.params_layout.removeWidget(widget)
widget.hide()
def populate_params_layout(self):
add_fitparam_widgets_to(self.params_layout, self.fitparams,
self.refresh, param_cols=self.param_cols)
def create_autofit_group(self):
auto_button = QPushButton(get_icon('apply.png'), _("Run"), self)
auto_button.clicked.connect(self.autofit)
autoprm_button = QPushButton(get_icon('settings.png'), _("Settings"),
self)
autoprm_button.clicked.connect(self.edit_parameters)
xrange_button = QPushButton(get_icon('xrange.png'), _("Bounds"), self)
xrange_button.setCheckable(True)
xrange_button.toggled.connect(self.toggle_xrange)
auto_layout = QVBoxLayout()
auto_layout.addWidget(auto_button)
auto_layout.addWidget(autoprm_button)
auto_layout.addWidget(xrange_button)
self.button_list += [auto_button, autoprm_button, xrange_button]
return create_groupbox(self, _("Automatic fit"), layout=auto_layout)
def get_fitfunc_arguments(self):
"""Return fitargs and fitkwargs"""
fitargs = self.fitargs
if self.fitargs is None:
fitargs = []
fitkwargs = self.fitkwargs
if self.fitkwargs is None:
fitkwargs = {}
return fitargs, fitkwargs
def refresh(self, slider_value=None):
"""Refresh Fit Tool dialog box"""
# Update button states
enable = self.x is not None and self.y is not None \
and self.x.size > 0 and self.y.size > 0 \
and self.fitfunc is not None and self.fitparams is not None \
and len(self.fitparams) > 0
for btn in self.button_list:
btn.setEnabled(enable)
if not enable:
# Fit widget is not yet configured
return
fitargs, fitkwargs = self.get_fitfunc_arguments()
yfit = self.fitfunc(self.x, [p.value for p in self.fitparams],
*fitargs, **fitkwargs)
plot = self.get_plot()
if self.legend is None:
self.legend = make.legend(anchor=self.legend_anchor)
plot.add_item(self.legend)
if self.xrange is None:
self.xrange = make.range(0., 1.)
plot.add_item(self.xrange)
self.xrange.set_range(self.autofit_prm.xmin, self.autofit_prm.xmax)
self.xrange.setVisible(self.show_xrange)
if self.data_curve is None:
self.data_curve = make.curve([], [],
_("Data"), color="b", linewidth=2)
plot.add_item(self.data_curve)
self.data_curve.set_data(self.x, self.y)
if self.fit_curve is None:
self.fit_curve = make.curve([], [],
_("Fit"), color="r", linewidth=2)
plot.add_item(self.fit_curve)
self.fit_curve.set_data(self.x, yfit)
plot.replot()
plot.disable_autoscale()
def range_changed(self, xrange_obj, xmin, xmax):
self.autofit_prm.xmin, self.autofit_prm.xmax = xmin, xmax
self.compute_imin_imax()
def toggle_xrange(self, state):
self.xrange.setVisible(state)
plot = self.get_plot()
plot.replot()
if state:
plot.set_active_item(self.xrange)
self.show_xrange = state
def edit_parameters(self):
if self.autofit_prm.edit(parent=self):
self.xrange.set_range(self.autofit_prm.xmin, self.autofit_prm.xmax)
plot = self.get_plot()
plot.replot()
self.compute_imin_imax()
def compute_imin_imax(self):
self.i_min = self.x.searchsorted(self.autofit_prm.xmin)
self.i_max = self.x.searchsorted(self.autofit_prm.xmax, side='right')
def errorfunc(self, params):
x = self.x[self.i_min:self.i_max]
y = self.y[self.i_min:self.i_max]
fitargs, fitkwargs = self.get_fitfunc_arguments()
return y - self.fitfunc(x, params, *fitargs, **fitkwargs)
def autofit(self):
meth = self.autofit_prm.method
x0 = np.array([p.value for p in self.fitparams])
if meth == "lq":
x = self.autofit_lq(x0)
elif meth=="simplex":
x = self.autofit_simplex(x0)
elif meth=="powel":
x = self.autofit_powel(x0)
elif meth=="bfgs":
x = self.autofit_bfgs(x0)
elif meth=="l_bfgs_b":
x = self.autofit_l_bfgs(x0)
elif meth=="cg":
x = self.autofit_cg(x0)
else:
return
for v, p in zip(x, self.fitparams):
p.value = v
self.refresh()
for prm in self.fitparams:
prm.update()
def get_norm_func(self):
prm = self.autofit_prm
err_norm = eval(prm.err_norm)
def func(params):
err = np.linalg.norm(self.errorfunc(params), err_norm)
return err
return func
def autofit_simplex(self, x0):
prm = self.autofit_prm
from scipy.optimize import fmin
x = fmin(self.get_norm_func(), x0, xtol=prm.xtol, ftol=prm.ftol)
return x
def autofit_powel(self, x0):
prm = self.autofit_prm
from scipy.optimize import fmin_powell
x = fmin_powell(self.get_norm_func(), x0, xtol=prm.xtol, ftol=prm.ftol)
return x
def autofit_bfgs(self, x0):
prm = self.autofit_prm
from scipy.optimize import fmin_bfgs
x = fmin_bfgs(self.get_norm_func(), x0, gtol=prm.gtol,
norm=eval(prm.norm))
return x
def autofit_l_bfgs(self, x0):
prm = self.autofit_prm
bounds = [(p.min, p.max) for p in self.fitparams]
from scipy.optimize import fmin_l_bfgs_b
x, _f, _d = fmin_l_bfgs_b(self.get_norm_func(), x0, pgtol=prm.gtol,
approx_grad=1, bounds=bounds)
return x
def autofit_cg(self, x0):
prm = self.autofit_prm
from scipy.optimize import fmin_cg
x = fmin_cg(self.get_norm_func(), x0, gtol=prm.gtol,
norm=eval(prm.norm))
return x
def autofit_lq(self, x0):
prm = self.autofit_prm
def func(params):
err = self.errorfunc(params)
return err
from scipy.optimize import leastsq
x, _ier = leastsq(func, x0, xtol=prm.xtol, ftol=prm.ftol)
return x
def get_values(self):
"""Convenience method to get fit parameter values"""
return [param.value for param in self.fitparams]
class FitWidgetMixin(CurveWidgetMixin):
def __init__(self,
wintitle="guiqwt plot",
icon="guiqwt.svg",
toolbar=False,
options=None,
panels=None,
param_cols=1,
legend_anchor='TR',
auto_fit=True):
if wintitle is None:
wintitle = _('Curve fitting')
self.x = None
self.y = None
self.fitfunc = None
self.fitargs = None
self.fitkwargs = None
self.fitparams = None
self.autofit_prm = None
self.data_curve = None
self.fit_curve = None
self.legend = None
self.legend_anchor = legend_anchor
self.xrange = None
self.show_xrange = False
self.param_cols = param_cols
self.auto_fit_enabled = auto_fit
self.button_list = [] # list of buttons to be disabled at startup
self.fit_layout = None
self.params_layout = None
CurveWidgetMixin.__init__(self,
wintitle=wintitle,
icon=icon,
toolbar=toolbar,
options=options,
panels=panels)
self.refresh()
# QWidget API --------------------------------------------------------------
def resizeEvent(self, event):
QWidget.resizeEvent(self, event)
self.get_plot().replot()
# CurveWidgetMixin API -----------------------------------------------------
def setup_widget_layout(self):
self.fit_layout = QHBoxLayout()
self.params_layout = QGridLayout()
params_group = create_groupbox(self,
_("Fit parameters"),
layout=self.params_layout)
if self.auto_fit_enabled:
auto_group = self.create_autofit_group()
self.fit_layout.addWidget(auto_group)
self.fit_layout.addWidget(params_group)
self.plot_layout.addLayout(self.fit_layout, 1, 0)
vlayout = QVBoxLayout(self)
vlayout.addWidget(self.toolbar)
vlayout.addLayout(self.plot_layout)
self.setLayout(vlayout)
def create_plot(self, options):
CurveWidgetMixin.create_plot(self, options)
for plot in self.get_plots():
plot.SIG_RANGE_CHANGED.connect(self.range_changed)
# Public API ---------------------------------------------------------------
def set_data(self,
x,
y,
fitfunc=None,
fitparams=None,
fitargs=None,
fitkwargs=None):
if self.fitparams is not None and fitparams is not None:
self.clear_params_layout()
self.x = x
self.y = y
if fitfunc is not None:
self.fitfunc = fitfunc
if fitparams is not None:
self.fitparams = fitparams
if fitargs is not None:
self.fitargs = fitargs
if fitkwargs is not None:
self.fitkwargs = fitkwargs
self.autofit_prm = AutoFitParam(title=_("Automatic fitting options"))
self.autofit_prm.xmin = x.min()
self.autofit_prm.xmax = x.max()
self.compute_imin_imax()
if self.fitparams is not None and fitparams is not None:
self.populate_params_layout()
self.refresh()
def set_fit_data(self, fitfunc, fitparams, fitargs=None, fitkwargs=None):
if self.fitparams is not None:
self.clear_params_layout()
self.fitfunc = fitfunc
self.fitparams = fitparams
self.fitargs = fitargs
self.fitkwargs = fitkwargs
self.populate_params_layout()
self.refresh()
def clear_params_layout(self):
for i, param in enumerate(self.fitparams):
for widget in param.get_widgets():
if widget is not None:
self.params_layout.removeWidget(widget)
widget.hide()
def populate_params_layout(self):
add_fitparam_widgets_to(self.params_layout,
self.fitparams,
self.refresh,
param_cols=self.param_cols)
def create_autofit_group(self):
auto_button = QPushButton(get_icon('apply.png'), _("Run"), self)
auto_button.clicked.connect(self.autofit)
autoprm_button = QPushButton(get_icon('settings.png'), _("Settings"),
self)
autoprm_button.clicked.connect(self.edit_parameters)
xrange_button = QPushButton(get_icon('xrange.png'), _("Bounds"), self)
xrange_button.setCheckable(True)
xrange_button.toggled.connect(self.toggle_xrange)
auto_layout = QVBoxLayout()
auto_layout.addWidget(auto_button)
auto_layout.addWidget(autoprm_button)
auto_layout.addWidget(xrange_button)
self.button_list += [auto_button, autoprm_button, xrange_button]
return create_groupbox(self, _("Automatic fit"), layout=auto_layout)
def get_fitfunc_arguments(self):
"""Return fitargs and fitkwargs"""
fitargs = self.fitargs
if self.fitargs is None:
fitargs = []
fitkwargs = self.fitkwargs
if self.fitkwargs is None:
fitkwargs = {}
return fitargs, fitkwargs
def refresh(self, slider_value=None):
"""Refresh Fit Tool dialog box"""
# Update button states
enable = self.x is not None and self.y is not None \
and self.x.size > 0 and self.y.size > 0 \
and self.fitfunc is not None and self.fitparams is not None \
and len(self.fitparams) > 0
for btn in self.button_list:
btn.setEnabled(enable)
if not enable:
# Fit widget is not yet configured
return
fitargs, fitkwargs = self.get_fitfunc_arguments()
yfit = self.fitfunc(self.x, [p.value for p in self.fitparams],
*fitargs, **fitkwargs)
plot = self.get_plot()
if self.legend is None:
self.legend = make.legend(anchor=self.legend_anchor)
plot.add_item(self.legend)
if self.xrange is None:
self.xrange = make.range(0., 1.)
plot.add_item(self.xrange)
self.xrange.set_range(self.autofit_prm.xmin, self.autofit_prm.xmax)
self.xrange.setVisible(self.show_xrange)
if self.data_curve is None:
self.data_curve = make.curve([], [],
_("Data"),
color="b",
linewidth=2)
plot.add_item(self.data_curve)
self.data_curve.set_data(self.x, self.y)
if self.fit_curve is None:
self.fit_curve = make.curve([], [],
_("Fit"),
color="r",
linewidth=2)
plot.add_item(self.fit_curve)
self.fit_curve.set_data(self.x, yfit)
plot.replot()
plot.disable_autoscale()
def range_changed(self, xrange_obj, xmin, xmax):
self.autofit_prm.xmin, self.autofit_prm.xmax = xmin, xmax
self.compute_imin_imax()
def toggle_xrange(self, state):
self.xrange.setVisible(state)
plot = self.get_plot()
plot.replot()
if state:
plot.set_active_item(self.xrange)
self.show_xrange = state
def edit_parameters(self):
if self.autofit_prm.edit(parent=self):
self.xrange.set_range(self.autofit_prm.xmin, self.autofit_prm.xmax)
plot = self.get_plot()
plot.replot()
self.compute_imin_imax()
def compute_imin_imax(self):
self.i_min = self.x.searchsorted(self.autofit_prm.xmin)
self.i_max = self.x.searchsorted(self.autofit_prm.xmax, side='right')
def errorfunc(self, params):
x = self.x[self.i_min:self.i_max]
y = self.y[self.i_min:self.i_max]
fitargs, fitkwargs = self.get_fitfunc_arguments()
return y - self.fitfunc(x, params, *fitargs, **fitkwargs)
def autofit(self):
meth = self.autofit_prm.method
x0 = np.array([p.value for p in self.fitparams])
if meth == "lq":
x = self.autofit_lq(x0)
elif meth == "simplex":
x = self.autofit_simplex(x0)
elif meth == "powel":
x = self.autofit_powel(x0)
elif meth == "bfgs":
x = self.autofit_bfgs(x0)
elif meth == "l_bfgs_b":
x = self.autofit_l_bfgs(x0)
elif meth == "cg":
x = self.autofit_cg(x0)
else:
return
for v, p in zip(x, self.fitparams):
p.value = v
self.refresh()
for prm in self.fitparams:
prm.update()
def get_norm_func(self):
prm = self.autofit_prm
err_norm = eval(prm.err_norm)
def func(params):
err = np.linalg.norm(self.errorfunc(params), err_norm)
return err
return func
def autofit_simplex(self, x0):
prm = self.autofit_prm
from scipy.optimize import fmin
x = fmin(self.get_norm_func(), x0, xtol=prm.xtol, ftol=prm.ftol)
return x
def autofit_powel(self, x0):
prm = self.autofit_prm
from scipy.optimize import fmin_powell
x = fmin_powell(self.get_norm_func(), x0, xtol=prm.xtol, ftol=prm.ftol)
return x
def autofit_bfgs(self, x0):
prm = self.autofit_prm
from scipy.optimize import fmin_bfgs
x = fmin_bfgs(self.get_norm_func(),
x0,
gtol=prm.gtol,
norm=eval(prm.norm))
return x
def autofit_l_bfgs(self, x0):
prm = self.autofit_prm
bounds = [(p.min, p.max) for p in self.fitparams]
from scipy.optimize import fmin_l_bfgs_b
x, _f, _d = fmin_l_bfgs_b(self.get_norm_func(),
x0,
pgtol=prm.gtol,
approx_grad=1,
bounds=bounds)
return x
def autofit_cg(self, x0):
prm = self.autofit_prm
from scipy.optimize import fmin_cg
x = fmin_cg(self.get_norm_func(),
x0,
gtol=prm.gtol,
norm=eval(prm.norm))
return x
def autofit_lq(self, x0):
prm = self.autofit_prm
def func(params):
err = self.errorfunc(params)
return err
from scipy.optimize import leastsq
x, _ier = leastsq(func, x0, xtol=prm.xtol, ftol=prm.ftol)
return x
def get_values(self):
"""Convenience method to get fit parameter values"""
return [param.value for param in self.fitparams]
