def plot_navigator(self):
if self.axes_manager.navigation_dimension == 0:
return
if self.navigator_data_function is None:
navigation_sliders(self.axes_manager.navigation_axes,
title=self.signal_title + " navigation sliders")
return
if self.navigator_plot is not None:
self.navigator_plot.plot()
return
elif len(self.navigator_data_function().shape) == 1:
# Create the figure
sf = spectrum.SpectrumFigure(
title=self.signal_title +
' Navigator' if self.signal_title else "")
axis = self.axes_manager.navigation_axes[0]
sf.xlabel = '%s' % str(axis)
if axis.units is not Undefined:
sf.xlabel += ' (%s)' % axis.units
sf.ylabel = r'$\Sigma\mathrm{data\,over\,all\,other\,axes}$'
sf.axis = axis.axis
sf.axes_manager = self.axes_manager
self.navigator_plot = sf
# Create a line to the left axis with the default
# indices
sl = spectrum.SpectrumLine()
sl.data_function = self.navigator_data_function
sl.set_line_properties(color='blue', type='step')
# Add the line to the figure
sf.add_line(sl)
sf.plot()
self.pointer.add_axes(sf.ax)
if self.axes_manager.navigation_dimension > 1:
navigation_sliders(self.axes_manager.navigation_axes,
title=self.signal_title +
" navigation sliders")
for axis in self.axes_manager.navigation_axes[:-2]:
axis.connect(sf.update)
self.navigator_plot = sf
elif len(self.navigator_data_function().shape) >= 2:
imf = image.ImagePlot()
imf.data_function = self.navigator_data_function
# Navigator labels
if self.axes_manager.navigation_dimension == 1:
imf.yaxis = self.axes_manager.navigation_axes[0]
imf.xaxis = self.axes_manager.signal_axes[0]
elif self.axes_manager.navigation_dimension >= 2:
imf.yaxis = self.axes_manager.navigation_axes[1]
imf.xaxis = self.axes_manager.navigation_axes[0]
if self.axes_manager.navigation_dimension > 2:
navigation_sliders(self.axes_manager.navigation_axes,
title=self.signal_title +
" navigation sliders")
for axis in self.axes_manager.navigation_axes[2:]:
axis.connect(imf.update)
imf.title = self.signal_title + ' Navigator'
imf.plot()
self.pointer.add_axes(imf.ax)
self.navigator_plot = imf
def plot_signal(self, **kwargs):
"""
Parameters
----------
**kwargs : dict
The kwargs are passed to plot method of the image figure.
"""
super().plot_signal()
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
# Set all kwargs value to the image figure before passing the rest
# of the kwargs to plot method of the image figure
for key, value in list(kwargs.items()):
if hasattr(imf, key):
setattr(imf, key, kwargs.pop(key))
imf.quantity_label = self.quantity_label
kwargs['data_function_kwargs'] = self.signal_data_function_kwargs
if "cmap" not in kwargs.keys() or kwargs['cmap'] is None:
kwargs["cmap"] = preferences.Plot.cmap_signal
imf.plot(**kwargs)
self.signal_plot = imf
if imf.figure is not None:
if self.axes_manager.navigation_axes:
self.signal_plot.figure.canvas.mpl_connect(
'key_press_event', self.axes_manager.key_navigator)
if self.navigator_plot is not None:
self.navigator_plot.figure.canvas.mpl_connect(
'key_press_event', self.axes_manager.key_navigator)
imf.events.closed.connect(self.close_navigator_plot, [])
imf.events.closed.connect(self._on_signal_plot_closing, [])
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_signal(self,
colorbar=True,
scalebar=True,
scalebar_color="white",
axes_ticks=None,
axes_off=False,
saturated_pixels=0,
vmin=None,
vmax=None,
no_nans=False,
centre_colormap="auto",
norm="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.
axes_off : bool, optional
If True, the axes labels are not plotted.
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.
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
super().plot_signal()
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.quantity_label = self.quantity_label
imf.scalebar = scalebar
imf.axes_ticks = axes_ticks
imf.axes_off = axes_off
imf.vmin, imf.vmax = vmin, vmax
imf.saturated_pixels = saturated_pixels
imf.no_nans = no_nans
imf.scalebar_color = scalebar_color
imf.centre_colormap = centre_colormap
imf.norm = norm
kwargs['data_function_kwargs'] = self.signal_data_function_kwargs
imf.plot(**kwargs)
self.signal_plot = imf
if imf.figure is not None:
if self.axes_manager.navigation_axes:
self.signal_plot.figure.canvas.mpl_connect(
'key_press_event', self.axes_manager.key_navigator)
if self.navigator_plot is not None:
self.navigator_plot.figure.canvas.mpl_connect(
'key_press_event', self.axes_manager.key_navigator)
self.navigator_plot.events.closed.connect(
self._on_navigator_plot_closing, [])
imf.events.closed.connect(self.close_navigator_plot, [])
def plot_navigator(self,
colorbar=True,
scalebar=True,
scalebar_color="white",
axes_ticks=None,
saturated_pixels=None,
vmin=None,
vmax=None,
no_nans=False,
centre_colormap="auto",
title=None,
min_aspect=0.1,
**kwds):
if self.axes_manager.navigation_dimension == 0:
return
if self.navigator_data_function is None:
return
if self.navigator_data_function == "slider":
self._get_navigation_sliders()
return
title = title or self.signal_title + " Navigator" if self.signal_title else ""
if self.navigator_plot is not None:
self.navigator_plot.plot()
return
elif len(self.navigator_data_function().shape) == 1:
# Create the figure
sf = signal1d.Signal1DFigure(title=title)
axis = self.axes_manager.navigation_axes[0]
sf.xlabel = '%s' % str(axis)
if axis.units is not Undefined:
sf.xlabel += ' (%s)' % axis.units
sf.ylabel = r'$\Sigma\mathrm{data\,over\,all\,other\,axes}$'
sf.axis = axis
sf.axes_manager = self.axes_manager
self.navigator_plot = sf
# Create a line to the left axis with the default
# indices
sl = signal1d.Signal1DLine()
sl.data_function = self.navigator_data_function
sl.set_line_properties(color='blue', type='step')
# Add the line to the figure
sf.add_line(sl)
sf.plot()
self.pointer.set_mpl_ax(sf.ax)
if self.axes_manager.navigation_dimension > 1:
self._get_navigation_sliders()
for axis in self.axes_manager.navigation_axes[:-2]:
axis.events.index_changed.connect(sf.update, [])
sf.events.closed.connect(
partial(axis.events.index_changed.disconnect,
sf.update), [])
self.navigator_plot = sf
elif len(self.navigator_data_function().shape) >= 2:
imf = image.ImagePlot()
imf.data_function = self.navigator_data_function
imf.colorbar = colorbar
imf.scalebar = scalebar
imf.scalebar_color = scalebar_color
imf.axes_ticks = axes_ticks
imf.saturated_pixels = saturated_pixels
imf.vmin = vmin
imf.vmax = vmax
imf.no_nans = no_nans
imf.centre_colormap = centre_colormap
imf.min_aspect = min_aspect
# Navigator labels
if self.axes_manager.navigation_dimension == 1:
imf.yaxis = self.axes_manager.navigation_axes[0]
imf.xaxis = self.axes_manager.signal_axes[0]
elif self.axes_manager.navigation_dimension >= 2:
imf.yaxis = self.axes_manager.navigation_axes[1]
imf.xaxis = self.axes_manager.navigation_axes[0]
if self.axes_manager.navigation_dimension > 2:
self._get_navigation_sliders()
for axis in self.axes_manager.navigation_axes[2:]:
axis.events.index_changed.connect(imf.update, [])
imf.events.closed.connect(
partial(axis.events.index_changed.disconnect,
imf.update), [])
imf.title = title
if "cmap" not in kwds.keys() or kwds['cmap'] is None:
kwds["cmap"] = preferences.Plot.cmap_navigator
imf.plot(**kwds)
self.pointer.set_mpl_ax(imf.ax)
self.navigator_plot = imf
def plot_navigator(self, title=None, **kwargs):
"""
Parameters
----------
title : str, optional
Title of the navigator. The default is None.
**kwargs : dict
The kwargs are passed to plot method of
:py:meth:`hyperspy.drawing.image.ImagePlot` or
:py:meth:`hyperspy.drawing.signal1d.Signal1DLine`.
"""
if self.axes_manager.navigation_dimension == 0:
return
if self.navigator_data_function is None:
return
if self.navigator_data_function == "slider":
self._get_navigation_sliders()
return
title = title or self.signal_title + " Navigator" if self.signal_title else ""
if len(self.navigator_data_function().shape) == 1:
# Create the figure
sf = signal1d.Signal1DFigure(title=title)
axis = self.axes_manager.navigation_axes[0]
sf.xlabel = '%s' % str(axis)
if axis.units is not Undefined:
sf.xlabel += ' (%s)' % axis.units
sf.ylabel = r'$\Sigma\mathrm{data\,over\,all\,other\,axes}$'
sf.axis = axis
sf.axes_manager = self.axes_manager
self.navigator_plot = sf
# Create a line to the left axis with the default indices
sl = signal1d.Signal1DLine()
sl.data_function = self.navigator_data_function
# Set all kwargs value to the image figure before passing the rest
# of the kwargs to plot method of the image figure
for key in list(kwargs.keys()):
if hasattr(sl, key):
setattr(sl, key, kwargs.pop(key))
sl.set_line_properties(color='blue',
type='step')
# Add the line to the figure
sf.add_line(sl)
sf.plot()
self.pointer.set_mpl_ax(sf.ax)
if self.axes_manager.navigation_dimension > 1:
self._get_navigation_sliders()
for axis in self.axes_manager.navigation_axes[:-2]:
axis.events.index_changed.connect(sf.update, [])
sf.events.closed.connect(
partial(axis.events.index_changed.disconnect,
sf.update), [])
self.navigator_plot = sf
elif len(self.navigator_data_function().shape) >= 2:
# Create the figure
imf = image.ImagePlot(title=title)
imf.data_function = self.navigator_data_function
# Set all kwargs value to the image figure before passing the rest
# of the kwargs to plot method of the image figure
for key, value in list(kwargs.items()):
if hasattr(imf, key):
setattr(imf, key, kwargs.pop(key))
# Navigator labels
if self.axes_manager.navigation_dimension == 1:
imf.yaxis = self.axes_manager.navigation_axes[0]
imf.xaxis = self.axes_manager.signal_axes[0]
elif self.axes_manager.navigation_dimension >= 2:
imf.yaxis = self.axes_manager.navigation_axes[1]
imf.xaxis = self.axes_manager.navigation_axes[0]
if self.axes_manager.navigation_dimension > 2:
self._get_navigation_sliders()
for axis in self.axes_manager.navigation_axes[2:]:
axis.events.index_changed.connect(imf.update, [])
imf.events.closed.connect(
partial(axis.events.index_changed.disconnect,
imf.update), [])
if "cmap" not in kwargs.keys() or kwargs['cmap'] is None:
kwargs["cmap"] = preferences.Plot.cmap_navigator
imf.plot(**kwargs)
self.pointer.set_mpl_ax(imf.ax)
self.navigator_plot = imf
if self.navigator_plot is not None:
self.navigator_plot.events.closed.connect(
self._on_navigator_plot_closing, [])
def plot_signal(self,
colorbar=True,
scalebar=True,
scalebar_color="white",
axes_ticks=None,
axes_off=False,
saturated_pixels=None,
vmin=None,
vmax=None,
no_nans=False,
centre_colormap="auto",
norm="auto",
min_aspect=0.1,
gamma=1.0,
linthresh=0.01,
linscale=0.1,
**kwargs):
"""Plot image.
Parameters
----------
%s
%s
"""
if self.signal_plot is not None:
self.signal_plot.plot(**kwargs)
return
super().plot_signal()
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.quantity_label = self.quantity_label
imf.scalebar = scalebar
imf.axes_ticks = axes_ticks
imf.axes_off = axes_off
imf.vmin, imf.vmax = vmin, vmax
imf.saturated_pixels = saturated_pixels
imf.no_nans = no_nans
imf.scalebar_color = scalebar_color
imf.centre_colormap = centre_colormap
imf.min_aspect = min_aspect
imf.norm = norm
imf.gamma = gamma
imf.linthresh = linthresh
imf.linscale = linscale
kwargs['data_function_kwargs'] = self.signal_data_function_kwargs
if "cmap" not in kwargs.keys() or kwargs['cmap'] is None:
kwargs["cmap"] = preferences.Plot.cmap_signal
imf.plot(**kwargs)
self.signal_plot = imf
if imf.figure is not None:
if self.axes_manager.navigation_axes:
self.signal_plot.figure.canvas.mpl_connect(
'key_press_event', self.axes_manager.key_navigator)
if self.navigator_plot is not None:
self.navigator_plot.figure.canvas.mpl_connect(
'key_press_event', self.axes_manager.key_navigator)
self.navigator_plot.events.closed.connect(
self._on_navigator_plot_closing, [])
imf.events.closed.connect(self.close_navigator_plot, [])
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)
