def overlay_image(ax, images, y_pos, x_pos, yx_range, offset, arrowprops=None, cmap=None, vmin=None, vmax=None):
"""
ax [matplotlib axis]
images [np.ndarray] of shape [num_images_per_edge, num_images_per_edge, channels, height, weidth] images for each mesh point
"""
num_images_per_edge = images.shape[0]
image_y_pos = data_utils.remap_axis_index_to_dataset_index(
axis_index=y_pos,
axis_min=yx_range[0][0],
axis_max=yx_range[0][1],
num_images=num_images_per_edge)
image_x_pos = data_utils.remap_axis_index_to_dataset_index(
axis_index=x_pos,
axis_min=yx_range[1][0],
axis_max=yx_range[1][1],
num_images=num_images_per_edge)
height_ratio = images.shape[3] / np.maximum(*images.shape[3:])
width_ratio = images.shape[4] / np.maximum(*images.shape[3:])
inset_height = 0.35 * height_ratio
inset_width = 0.35 * width_ratio
arr_img = np.squeeze(images[image_y_pos, image_x_pos, ...].transpose((1,2,0)))
imagebox = OffsetImage(arr_img, zoom=0.75, cmap=cmap)
img = imagebox.get_children()[0]
img.set_clim(vmin=vmin, vmax=vmax)
imagebox.image.axes = ax
if arrowprops is None:
arrowprops = dict(
linestyle='--',
lw=1,
arrowstyle='->',
color='r'
)
ab = AnnotationBbox(imagebox,
xy=[x_pos, y_pos],
xybox=offset,
xycoords=ax.transData,
boxcoords='offset points',
pad=0.0,
arrowprops=arrowprops
)
ax.add_artist(ab)
return arr_img
