In this entry, I am showing a way of plotting path in MATLAB, which is often seen in pattern recognition and statistical modelling technique, for example, the Needleman-Wunsch algorithm and the Hidden Markov Models. Provided that the length of the output sequence is relatively short, and there are limit number of states, it may be beneficial to be able to visualize the path.
Below is an example based on the Needleman-Wunsch algorithm for sequence alignment. Note that all the cells are shown in the plot as text objects, and the available path is shown as thin lines while the optimal path obtained from the back tracking process is shown as thicker lines.
Note that even though the lines appear as broken segments in the plot, they are not drawn as such. It is rather difficult to figure out the starting and ending points of the line to produce a consistent and nice-looking plot. Instead, the lines are drawn between the centers of the text boxes. It looks like segments because there are solid white circles drawn on top of the lines, effectively, we are covering parts of the lines using white circles. Note that
you can use rectangle(), which is a MATLAB function, to draw the circles, and you can set their facecolor and edgecolor to white, which will give the circles with solid white background.
The trick is to know that all the graphic objects are being placed on differently layers (or stacks). Usually, the objects that are added to the figure last will always appear on the top of everything else. So, depending on the order of how you draw things, the plot may appear different if there is any overlap between the objects.
To generate the above plot, plot the lines first, and then the white circle, and finally the text boxes. Note that in the case where the lines have to be drawn last, you can always use to
uistack function to send the lines back to the bottom layer of the figure.
This rather messy m-file contains the code that produces the above plot.
