hm_data = np.random.rand(100, 20)
data_indices = np.arange(20)

contours = # get 20 contours

hm_graphic = plot.heatmap(hm_data, indices=data_indices)

# plot the other graphic in the same or some other scene

contour_graphic = plot.multi_line(contours, indices=data_indices)

hm_options = dict(
    feature="row",
    update_color=[1, 1, 1, 0.5],
    update_data=None,  # can change the data if desired
    event="double_click"
)

contour_options = dict(
    feature="line",
    update_color=[1, 1, 1, 1],
    update_data=None,  # if desired
    event="click"
)

# bi-directional linking
# heatmap -> contours
linker = hm_graphic.link(source_options=hm_options, target=contour_graphic, target_options=contour_options)

# contours -> heatmap
linker2 = contour_graphic.link(source_options=contour_options, target=hm_graphic, target_options=hm_options)

# to unlink
hm_graphic.unlink(linker)

# continue from above, so the previous heatmap is also present somewhere in the renderer/canvas

img_data = np.random.rand(512, 512)

image_graphic = plot.image(img_data)

def get_closest_contour(indices) -> np.array:
    # convert source graphic indices to target graphic indices
    # stuff to map image indices -> contour indices
    return contour_indices

image_options = dict(
    feature="pixel",
    update_data=None, # we don't want to change anything in the image
    event="click",
    indices_mapper=get_closest_contour,
)

contour_options_img = dict(
    feature="line",
    update_color=[1, 1, 1, 1],
    event=None,
    chain_event=True, # this graphic will pass on the source's event to its target if a target exists
)

linker_img = image_graphic.link(source_options=image_options, target=contour_graphic, target_options=contour_options_img)