dianna.visualization.image
==========================

.. py:module:: dianna.visualization.image


Functions
---------

.. autoapisummary::

   dianna.visualization.image._determine_vmax
   dianna.visualization.image.plot_image


Module Contents
---------------

.. py:function:: _determine_vmax(max_data_value)

.. py:function:: plot_image(heatmap: numpy.ndarray, original_data: Optional[numpy.ndarray] = None, heatmap_cmap='bwr', heatmap_range=(None, None), data_cmap=None, show_plot: bool = True, output_filename=None, ax: Optional[matplotlib.pyplot.Axes] = None) -> matplotlib.pyplot.Figure

   Plots a heatmap image.

   Optionally, the heatmap (typically a saliency map of an explainer) can be
   plotted on top of the original data. In that case both images are plotted
   transparantly with alpha = 0.5.

   :param heatmap: the saliency map or other heatmap to be plotted.
   :param original_data: the data to plot together with the heatmap, both with
                         alpha = 0.5 (optional).
   :param heatmap_cmap: color map for the heatmap plot (see mpl.Axes.imshow
                        documentation for options).
   :param heatmap_range: a tuple (vmin, vmax) to set the range of the heatmap.
                         By default, the colormap covers the complete value range of
                         the supplied heatmap.
   :param data_cmap: color map for the (optional) data image (see mpl.Axes.imshow
                     documentation for options). By default, if the image is two
                     dimensional, the color map is set to 'gray'.
   :param show_plot: Shows plot if true (for testing or writing plots to disk
                     instead).
   :param output_filename: Name of the file to save the plot to (optional).
   :param ax: matplotlib.Axes object to plot on (optional).

   :returns: None