def create_figure(self):
self.figure = utils.create_figure(
window_title=("Figure " + self.title if self.title else None))
canvas = self.figure.canvas
self._background = canvas.copy_from_bbox(self.figure.bbox)
self.figure.canvas.mpl_connect('draw_event', self._on_draw)
utils.on_figure_window_close(self.figure, self.close)
def plot(self, auto_update_plot = True):
"""Plots the current spectrum to the screen and a map with a cursor to
explore the SI.
"""
# If new coordinates are assigned
self.spectrum.plot()
_plot = self.spectrum._plot
l1 = _plot.spectrum_plot.ax_lines[0]
color = l1.line.get_color()
l1.line_properties_helper(color, 'scatter')
l1.set_properties()
l2 = hyperspy.drawing.spectrum.SpectrumLine()
l2.data_function = self._model2plot
l2.line_properties_helper('blue', 'line')
# Add the line to the figure
_plot.spectrum_plot.add_line(l2)
l2.plot()
self.connect_parameters2update_plot()
on_figure_window_close(_plot.spectrum_plot.figure,
self.disconnect_parameters2update_plot)
self.set_auto_update_plot(True)
self._plot = self.spectrum._plot
def plot_signal(self):
if self.signal_plot is not None:
self.signal_plot.plot()
return
# Create the figure
self.xlabel = '%s' % str(self.axes_manager.signal_axes[0])
if self.axes_manager.signal_axes[0].units is not Undefined:
self.xlabel += ' (%s)' % self.axes_manager.signal_axes[0].units
self.ylabel = 'Intensity'
self.axis = self.axes_manager.signal_axes[0].axis
sf = spectrum.SpectrumFigure(title=self.signal_title + " Signal")
sf.xlabel = self.xlabel
sf.ylabel = self.ylabel
sf.axis = self.axis
sf.create_axis()
sf.axes_manager = self.axes_manager
self.signal_plot = sf
# Create a line to the left axis with the default indices
sl = spectrum.SpectrumLine()
sl.autoscale = True
sl.data_function = self.signal_data_function
sl.plot_indices = True
if self.pointer is not None:
color = self.pointer.color
else:
color = 'red'
sl.set_line_properties(color=color, type='step')
# Add the line to the figure
sf.add_line(sl)
# If the data is complex create a line in the left axis with the
# default coordinates
sl = spectrum.SpectrumLine()
sl.data_function = self.signal_data_function
sl.plot_coordinates = True
sl.get_complex = any(np.iscomplex(sl.data_function()))
if sl.get_complex:
sl.set_line_properties(color="blue", type='step')
# Add extra line to the figure
sf.add_line(sl)
self.signal_plot = sf
sf.plot()
if self.navigator_plot is not None and sf.figure is not None:
utils.on_figure_window_close(self.navigator_plot.figure,
self._on_navigator_plot_closing)
utils.on_figure_window_close(sf.figure, self.close_navigator_plot)
self._key_nav_cid = \
self.signal_plot.figure.canvas.mpl_connect(
'key_press_event',
self.axes_manager.key_navigator)
self._key_nav_cid = \
self.navigator_plot.figure.canvas.mpl_connect(
'key_press_event',
self.axes_manager.key_navigator)
self.signal_plot.figure.canvas.mpl_connect(
'key_press_event', self.key2switch_right_pointer)
self.navigator_plot.figure.canvas.mpl_connect(
'key_press_event', self.key2switch_right_pointer)
def create_figure(self):
self.figure = utils.create_figure(
window_title=("Figure " + self.title
if self.title
else None))
canvas = self.figure.canvas
self._background = canvas.copy_from_bbox(self.figure.bbox)
self.figure.canvas.mpl_connect('draw_event', self._on_draw)
utils.on_figure_window_close(self.figure, self.close)
def create_figure(self, max_size=8, min_size=2):
if self.plot_scalebar is True:
wfactor = 1.1
else:
wfactor = 1
height = abs(self._extent[3] - self._extent[2]) * self._aspect
width = abs(self._extent[1] - self._extent[0])
figsize = np.array((width * wfactor, height)) * max_size / max((width * wfactor, height))
self.figure = utils.create_figure(
window_title=("Figure " + self.title if self.title else None), figsize=figsize.clip(min_size, max_size)
)
self.figure.canvas.mpl_connect("draw_event", self._on_draw)
utils.on_figure_window_close(self.figure, self.close)
def enable_adjust_position(self,
components=None,
fix_them=True,
show_label=True):
"""Allow changing the *x* position of component by dragging
a vertical line that is plotted in the signal model figure
Parameters
----------
components : {None, list of components}
If None, the position of all the active components of the
model that has a well defined *x* position with a value
in the axis range will get a position adjustment line.
Otherwise the feature is added only to the given components.
The components can be specified by name, index or themselves.
fix_them : bool
If True the position parameter of the components will be
temporarily fixed until adjust position is disable.
This can
be useful to iteratively adjust the component positions and
fit the model.
show_label : bool, optional
If True, a label showing the component name is added to the
plot next to the vertical line.
See also
--------
disable_adjust_position
"""
if (self._plot is None or self._plot.is_active() is False):
self.plot()
if self._position_widgets:
self.disable_adjust_position()
on_figure_window_close(self._plot.signal_plot.figure,
self.disable_adjust_position)
if components:
components = [self._get_component(x) for x in components]
else:
self._adjust_position_all = (fix_them, show_label)
components = components if components else self
if not components:
# The model does not have components so we do nothing
return
components = [
component for component in components if component.active
]
for component in components:
self._make_position_adjuster(component, fix_them, show_label)
def plot_signal(self):
if self.signal_plot is not None:
self.signal_plot.plot()
return
# Create the figure
self.xlabel = '%s (%s)' % (
self.axes_manager.signal_axes[0].name,
self.axes_manager.signal_axes[0].units)
self.ylabel = 'Intensity'
self.axis = self.axes_manager.signal_axes[0].axis
sf = spectrum.SpectrumFigure()
sf.xlabel = self.xlabel
sf.ylabel = self.ylabel
sf.title = self.signal_title
sf.axis = self.axis
sf.create_axis()
sf.axes_manager = self.axes_manager
self.signal_plot = sf
# Create a line to the left axis with the default indices
sl = spectrum.SpectrumLine()
sl.data_function = self.signal_data_function
sl.plot_indices = True
if self.pointer is not None:
color = self.pointer.color
else:
color = 'red'
sl.line_properties_helper(color, 'step')
# Add the line to the figure
sf.add_line(sl)
self.signal_plot = sf
sf.plot()
if self.navigator_plot is not None and sf.figure is not None:
utils.on_figure_window_close(self.navigator_plot.figure,
self._disconnect)
utils.on_figure_window_close(sf.figure,
self.close_navigator_plot)
self._key_nav_cid = \
self.signal_plot.figure.canvas.mpl_connect(
'key_press_event',
self.axes_manager.key_navigator)
self._key_nav_cid = \
self.navigator_plot.figure.canvas.mpl_connect(
'key_press_event',
self.axes_manager.key_navigator)
self.signal_plot.figure.canvas.mpl_connect(
'key_press_event', self.key2switch_right_pointer)
self.navigator_plot.figure.canvas.mpl_connect(
'key_press_event', self.key2switch_right_pointer)
def create_figure(self, max_size=8, min_size=2):
if self.scalebar is True:
wfactor = 1.1
else:
wfactor = 1
height = abs(self._extent[3] - self._extent[2]) * self._aspect
width = abs(self._extent[1] - self._extent[0])
figsize = np.array((width * wfactor, height)) * max_size / max(
(width * wfactor, height))
self.figure = utils.create_figure(
window_title=("Figure " + self.title if self.title else None),
figsize=figsize.clip(min_size, max_size))
self.figure.canvas.mpl_connect('draw_event', self._on_draw)
utils.on_figure_window_close(self.figure, self._on_close)
def enable_adjust_position(
self, components=None, fix_them=True, show_label=True):
"""Allow changing the *x* position of component by dragging
a vertical line that is plotted in the signal model figure
Parameters
----------
components : {None, list of components}
If None, the position of all the active components of the
model that has a well defined *x* position with a value
in the axis range will get a position adjustment line.
Otherwise the feature is added only to the given components.
The components can be specified by name, index or themselves.
fix_them : bool
If True the position parameter of the components will be
temporarily fixed until adjust position is disable.
This can
be useful to iteratively adjust the component positions and
fit the model.
show_label : bool, optional
If True, a label showing the component name is added to the
plot next to the vertical line.
See also
--------
disable_adjust_position
"""
if (self._plot is None or
self._plot.is_active() is False):
self.plot()
if self._position_widgets:
self.disable_adjust_position()
on_figure_window_close(self._plot.signal_plot.figure,
self.disable_adjust_position)
if components:
components = [self._get_component(x) for x in components]
else:
self._adjust_position_all = (fix_them, show_label)
components = components if components else self
if not components:
# The model does not have components so we do nothing
return
components = [
component for component in components if component.active]
for component in components:
self._make_position_adjuster(component, fix_them, show_label)
def create_figure(self, **kwargs):
"""Create matplotlib figure
Parameters
----------
**kwargs
All keyword arguments are passed to ``plt.figure``.
"""
self.figure = utils.create_figure(
window_title="Figure " + self.title if self.title
else None, **kwargs)
utils.on_figure_window_close(self.figure, self._on_close)
if self.figure.canvas.supports_blit:
self._draw_event_cid = self.figure.canvas.mpl_connect(
'draw_event', self._on_blit_draw)
def create_figure(self, **kwargs):
"""Create matplotlib figure
Parameters
----------
**kwargs
All keyword arguments are passed to ``plt.figure``.
"""
self.figure = utils.create_figure(window_title="Figure " +
self.title if self.title else None,
**kwargs)
utils.on_figure_window_close(self.figure, self._on_close)
if self.figure.canvas.supports_blit:
self._draw_event_cid = self.figure.canvas.mpl_connect(
'draw_event', self._on_blit_draw)
def virtual_aperture(self, signal=None, annulus=False, navigate=False):
ui = self.ui
if signal is None:
signal = ui.get_selected_signal()
dd = np.array([
a.high_value + a.low_value for a in signal.axes_manager.signal_axes
]) / 2.0
r = hs.roi.CircleROI(dd[0], dd[1],
signal.axes_manager.signal_axes[0].scale * 3)
if annulus:
r.r_inner = signal.axes_manager.signal_axes[0].scale * 2
s_virtual = r.interactive(signal,
None,
axes=signal.axes_manager.signal_axes)
s_nav = hs.interactive(s_virtual.mean,
s_virtual.events.data_changed,
axis=s_virtual.axes_manager.signal_axes)
s_nav.axes_manager.set_signal_dimension(2)
if navigate:
signal.plot(navigator=s_nav)
signal._plot.navigator_plot.update()
s_nav.events.data_changed.connect(
signal._plot.navigator_plot.update, [])
utils.on_figure_window_close(signal._plot.navigator_plot.figure,
partial(self._on_close, r))
else:
s_nav.plot()
utils.on_figure_window_close(s_nav._plot.signal_plot.figure,
partial(self._on_close, r))
if navigate:
r.add_widget(signal,
axes=signal.axes_manager.signal_axes,
color='darkorange')
else:
r.add_widget(signal, axes=signal.axes_manager.signal_axes)
self._rois.append(r)
self.record_code("<p>.virtual_aperture(navigate=%s)" % navigate)
def virtual_aperture(self, signal=None, annulus=False, navigate=False):
ui = self.ui
if signal is None:
signal = ui.get_selected_signal()
dd = np.array([a.high_value + a.low_value for a in
signal.axes_manager.signal_axes]) / 2.0
r = hs.roi.CircleROI(dd[0], dd[1],
signal.axes_manager.signal_axes[0].scale*3)
if annulus:
r.r_inner = signal.axes_manager.signal_axes[0].scale*2
s_virtual = r.interactive(signal, None,
axes=signal.axes_manager.signal_axes)
s_nav = hs.interactive(
s_virtual.mean,
s_virtual.events.data_changed,
axis=s_virtual.axes_manager.signal_axes)
s_nav.axes_manager.set_signal_dimension(2)
if navigate:
signal.plot(navigator=s_nav)
signal._plot.navigator_plot.update()
s_nav.events.data_changed.connect(
signal._plot.navigator_plot.update, [])
utils.on_figure_window_close(
signal._plot.navigator_plot.figure,
partial(self._on_close, r))
else:
s_nav.plot()
utils.on_figure_window_close(
s_nav._plot.signal_plot.figure,
partial(self._on_close, r))
if navigate:
r.add_widget(signal, axes=signal.axes_manager.signal_axes,
color='darkorange')
else:
r.add_widget(signal, axes=signal.axes_manager.signal_axes)
self._rois.append(r)
self.record_code("<p>.virtual_aperture(navigate=%s)" % navigate)
def plot_signal(self):
if self.signal_plot is not None:
self.signal_plot.plot()
return
imf = image.ImagePlot()
imf.axes_manager = self.axes_manager
imf.data_function = self.signal_data_function
imf.title = self.signal_title + " Signal"
imf.xaxis, imf.yaxis = self.axes_manager.signal_axes
imf.plot_colorbar = True
imf.plot()
self.signal_plot = imf
if self.navigator_plot is not None and imf.figure is not None:
utils.on_figure_window_close(self.navigator_plot.figure,
self.close_navigator_plot)
utils.on_figure_window_close(imf.figure, self.close_navigator_plot)
self._key_nav_cid = \
self.signal_plot.figure.canvas.mpl_connect(
'key_press_event', self.axes_manager.key_navigator)
self._key_nav_cid = \
self.navigator_plot.figure.canvas.mpl_connect(
'key_press_event', self.axes_manager.key_navigator)
def plot(self, plot_components=False):
"""Plots the current spectrum to the screen and a map with a
cursor to explore the SI.
Parameters
----------
plot_components : bool
If True, add a line per component to the signal figure.
"""
# If new coordinates are assigned
self.spectrum.plot()
_plot = self.spectrum._plot
l1 = _plot.signal_plot.ax_lines[0]
color = l1.line.get_color()
l1.set_line_properties(color=color, type='scatter')
l2 = hyperspy.drawing.spectrum.SpectrumLine()
l2.data_function = self._model2plot
l2.set_line_properties(color='blue', type='line')
# Add the line to the figure
_plot.signal_plot.add_line(l2)
l2.plot()
on_figure_window_close(_plot.signal_plot.figure,
self._close_plot)
self._model_line = l2
self._plot = self.spectrum._plot
self._connect_parameters2update_plot(self)
if plot_components is True:
self.enable_plot_components()
else:
# If we were plotted before, make sure we reset state here
self.disable_plot_components()
# If we were plotted before, make sure we reset state here
self.disable_adjust_position()
def plot_signal(self):
if self.signal_plot is not None:
self.signal_plot.plot()
return
imf = image.ImagePlot()
imf.axes_manager = self.axes_manager
imf.data_function = self.signal_data_function
imf.title = self.signal_title + " Signal"
imf.xaxis, imf.yaxis = self.axes_manager.signal_axes
imf.plot_colorbar = True
imf.plot()
self.signal_plot = imf
if self.navigator_plot is not None and imf.figure is not None:
utils.on_figure_window_close(self.navigator_plot.figure,
self.close_navigator_plot)
utils.on_figure_window_close(
imf.figure, self.close_navigator_plot)
self._key_nav_cid = \
self.signal_plot.figure.canvas.mpl_connect(
'key_press_event', self.axes_manager.key_navigator)
self._key_nav_cid = \
self.navigator_plot.figure.canvas.mpl_connect(
'key_press_event', self.axes_manager.key_navigator)
def plot(self, plot_components=False):
"""Plots the current spectrum to the screen and a map with a
cursor to explore the SI.
Parameters
----------
plot_components : bool
If True, add a line per component to the signal figure.
"""
# If new coordinates are assigned
self.spectrum.plot()
_plot = self.spectrum._plot
l1 = _plot.signal_plot.ax_lines[0]
color = l1.line.get_color()
l1.set_line_properties(color=color, type='scatter')
l2 = hyperspy.drawing.spectrum.SpectrumLine()
l2.data_function = self._model2plot
l2.set_line_properties(color='blue', type='line')
# Add the line to the figure
_plot.signal_plot.add_line(l2)
l2.plot()
on_figure_window_close(_plot.signal_plot.figure, self._close_plot)
self._model_line = l2
self._plot = self.spectrum._plot
self._connect_parameters2update_plot(self)
if plot_components is True:
self.enable_plot_components()
else:
# If we were plotted before, make sure we reset state here
self.disable_plot_components()
# If we were plotted before, make sure we reset state here
self.disable_adjust_position()
def connect(self, ax):
"""Connect to the matplotlib Axes' events.
"""
on_figure_window_close(ax.figure, self.close)
if self._navigating:
self.connect_navigate()
def create_figure(self):
self.figure = utils.create_figure(
window_title="Figure " + self.title if self.title
else None)
utils.on_figure_window_close(self.figure, self.close)
self.figure.canvas.mpl_connect('draw_event', self._on_draw)
def create_figure(self):
self.figure = utils.create_figure(window_title="Figure " +
self.title if self.title else None)
utils.on_figure_window_close(self.figure, self.close)
self.figure.canvas.mpl_connect('draw_event', self._on_draw)
def plot_signal(self,
colorbar=True,
scalebar=True,
scalebar_color="white",
axes_ticks=None,
auto_contrast=True,
saturated_pixels=0.2,
vmin=None,
vmax=None,
no_nans=False,
**kwargs
):
"""Plot image.
Parameters
----------
colorbar : bool, optional
If true, a colorbar is plotted for non-RGB images.
scalebar : bool, optional
If True and the units and scale of the x and y axes are the same a
scale bar is plotted.
scalebar_color : str, optional
A valid MPL color string; will be used as the scalebar color.
axes_ticks : {None, bool}, optional
If True, plot the axes ticks. If None axes_ticks are only
plotted when the scale bar is not plotted. If False the axes ticks
are never plotted.
auto_contrast : bool, optional
If True, the contrast is stretched for each image using the
`saturated_pixels` value. Default True
saturated_pixels: scalar
The percentage of pixels that are left out of the bounds. For
example, the low and high bounds of a value of 1 are the
0.5% and 99.5% percentiles. It must be in the [0, 100] range.
vmin, vmax : scalar, optional
`vmin` and `vmax` are used to normalize luminance data. If
`auto_contrast` is True (i.e. default) these values are ignore.
no_nans : bool, optional
If True, set nans to zero for plotting.
**kwargs, optional
Additional key word arguments passed to matplotlib.imshow()
"""
if self.signal_plot is not None:
self.signal_plot.plot(**kwargs)
return
imf = image.ImagePlot()
imf.axes_manager = self.axes_manager
imf.data_function = self.signal_data_function
imf.title = self.signal_title + " Signal"
imf.xaxis, imf.yaxis = self.axes_manager.signal_axes
imf.colorbar = colorbar
imf.scalebar = scalebar
imf.axes_ticks = axes_ticks
imf.vmin, imf.vmax = vmin, vmax
imf.saturated_pixels = saturated_pixels
imf.no_nans = no_nans
imf.scalebar_color = scalebar_color
imf.auto_contrast = auto_contrast
imf.plot(**kwargs)
self.signal_plot = imf
if self.navigator_plot is not None and imf.figure is not None:
utils.on_figure_window_close(self.navigator_plot.figure,
self.close_navigator_plot)
utils.on_figure_window_close(
imf.figure, self.close_navigator_plot)
self._key_nav_cid = \
self.signal_plot.figure.canvas.mpl_connect(
'key_press_event', self.axes_manager.key_navigator)
self._key_nav_cid = \
self.navigator_plot.figure.canvas.mpl_connect(
'key_press_event', self.axes_manager.key_navigator)
def plot_signal(self):
if self.signal_plot is not None:
self.signal_plot.plot()
return
# Create the figure
self.xlabel = '%s' % str(self.axes_manager.signal_axes[0])
if self.axes_manager.signal_axes[0].units is not Undefined:
self.xlabel += ' (%s)' % self.axes_manager.signal_axes[0].units
self.ylabel = 'Intensity'
self.axis = self.axes_manager.signal_axes[0]
sf = spectrum.SpectrumFigure(title=self.signal_title +
" Signal")
sf.xlabel = self.xlabel
sf.ylabel = self.ylabel
sf.axis = self.axis
sf.create_axis()
sf.axes_manager = self.axes_manager
self.signal_plot = sf
# Create a line to the left axis with the default indices
sl = spectrum.SpectrumLine()
sl.autoscale = True
sl.data_function = self.signal_data_function
sl.plot_indices = True
if self.pointer is not None:
color = self.pointer.color
else:
color = 'red'
sl.set_line_properties(color=color, type='step')
# Add the line to the figure
sf.add_line(sl)
# If the data is complex create a line in the left axis with the
# default coordinates
sl = spectrum.SpectrumLine()
sl.data_function = self.signal_data_function
sl.plot_coordinates = True
sl.get_complex = any(np.iscomplex(sl.data_function()))
if sl.get_complex:
sl.set_line_properties(color="blue", type='step')
# Add extra line to the figure
sf.add_line(sl)
self.signal_plot = sf
sf.plot()
if self.navigator_plot is not None and sf.figure is not None:
utils.on_figure_window_close(self.navigator_plot.figure,
self._on_navigator_plot_closing)
utils.on_figure_window_close(sf.figure,
self.close_navigator_plot)
self._key_nav_cid = \
self.signal_plot.figure.canvas.mpl_connect(
'key_press_event',
self.axes_manager.key_navigator)
self._key_nav_cid = \
self.navigator_plot.figure.canvas.mpl_connect(
'key_press_event',
self.axes_manager.key_navigator)
self.signal_plot.figure.canvas.mpl_connect(
'key_press_event', self.key2switch_right_pointer)
self.navigator_plot.figure.canvas.mpl_connect(
'key_press_event', self.key2switch_right_pointer)
def connect(self, ax):
"""Connect to the matplotlib Axes' events.
"""
on_figure_window_close(ax.figure, self.close)
if self._navigating:
self.connect_navigate()
def plot_signal(self,
colorbar=True,
scalebar=True,
scalebar_color="white",
axes_ticks=None,
auto_contrast=True,
saturated_pixels=0.2,
vmin=None,
vmax=None,
no_nans=False,
centre_colormap="auto",
**kwargs
):
"""Plot image.
Parameters
----------
colorbar : bool, optional
If true, a colorbar is plotted for non-RGB images.
scalebar : bool, optional
If True and the units and scale of the x and y axes are the same a
scale bar is plotted.
scalebar_color : str, optional
A valid MPL color string; will be used as the scalebar color.
axes_ticks : {None, bool}, optional
If True, plot the axes ticks. If None axes_ticks are only
plotted when the scale bar is not plotted. If False the axes ticks
are never plotted.
auto_contrast : bool, optional
If True, the contrast is stretched for each image using the
`saturated_pixels` value. Default True
saturated_pixels: scalar
The percentage of pixels that are left out of the bounds. For
example, the low and high bounds of a value of 1 are the
0.5% and 99.5% percentiles. It must be in the [0, 100] range.
vmin, vmax : scalar, optional
`vmin` and `vmax` are used to normalize luminance data. If
`auto_contrast` is True (i.e. default) these values are ignore.
no_nans : bool, optional
If True, set nans to zero for plotting.
**kwargs, optional
Additional key word arguments passed to matplotlib.imshow()
"""
if self.signal_plot is not None:
self.signal_plot.plot(**kwargs)
return
imf = image.ImagePlot()
imf.axes_manager = self.axes_manager
imf.data_function = self.signal_data_function
imf.title = self.signal_title + " Signal"
imf.xaxis, imf.yaxis = self.axes_manager.signal_axes
imf.colorbar = colorbar
imf.scalebar = scalebar
imf.axes_ticks = axes_ticks
imf.vmin, imf.vmax = vmin, vmax
imf.saturated_pixels = saturated_pixels
imf.no_nans = no_nans
imf.scalebar_color = scalebar_color
imf.auto_contrast = auto_contrast
imf.centre_colormap = centre_colormap
imf.plot(**kwargs)
self.signal_plot = imf
if self.navigator_plot is not None and imf.figure is not None:
utils.on_figure_window_close(self.navigator_plot.figure,
self.close_navigator_plot)
utils.on_figure_window_close(
imf.figure, self.close_navigator_plot)
self._key_nav_cid = \
self.signal_plot.figure.canvas.mpl_connect(
'key_press_event', self.axes_manager.key_navigator)
self._key_nav_cid = \
self.navigator_plot.figure.canvas.mpl_connect(
'key_press_event', self.axes_manager.key_navigator)
def enable_adjust_position(self, components=None, fix_them=True):
"""Allow changing the *x* position of component by dragging
a vertical line that is plotted in the signal model figure
Parameters
----------
components : {None, list of components}
If None, the position of all the active components of the
model that has a well defined *x* position with a value
in the axis range will get a position adjustment line.
Otherwise the feature is added only to the given components.
fix_them : bool
If True the position parameter of the components will be
temporarily fixed until adjust position is disable.
This can
be useful to iteratively adjust the component positions and
fit the model.
See also
--------
disable_adjust_position
"""
if (self._plot is None or
self._plot.is_active() is False):
self.plot()
if self._position_widgets:
self.disable_adjust_position()
on_figure_window_close(self._plot.signal_plot.figure,
self.disable_adjust_position)
components = components if components else self
if not components:
# The model does not have components so we do nothing
return
components = [
component for component in components if component.active]
axis_dict = self.axes_manager.signal_axes[0].get_axis_dictionary()
axis_dict['index_in_array'] = 0
for component in self:
if (component._position is not None and
not component._position.twin):
set_value = component._position._setvalue
get_value = component._position._getvalue
else:
continue
# Create an AxesManager for the widget
am = AxesManager([axis_dict,])
am.axes[0].navigate = True
try:
am.axes[0].value = get_value()
except TraitError:
# The value is outside of the axis range
continue
# Create the vertical line and labels
self._position_widgets.extend((
DraggableVerticalLine(am),
DraggableLabel(am),))
# Store the component to reset its twin when disabling
# adjust position
self._position_widgets[-1].component = component
w = self._position_widgets[-1]
w.string = component._get_short_description().replace(
' component', '')
w.add_axes(self._plot.signal_plot.ax)
self._position_widgets[-2].add_axes(
self._plot.signal_plot.ax)
# Create widget -> parameter connection
am.axes[0].continuous_value = True
am.axes[0].on_trait_change(set_value, 'value')
# Create parameter -> widget connection
# This is done with a duck typing trick
# We disguise the AxesManager axis of Parameter by adding
# the _twin attribute
am.axes[0]._twins = set()
component._position.twin = am.axes[0]
