Beginner Tutorial Matplotlib Visualization

Example 3: Slice Comparison

Introduction

We will adapt the previously created macro module to be able to overlay two defined slices to compare their grayscale distributions.

The module we are adapting has been set up in the Example 1: Module Setup tutorial.
The panel and two-dimensional plotting functionality has been added in [Example 2: 2D Plotting] (/tutorials/thirdparty/matplotlib/2dplotting).

Steps to do

At first, we will extend the panel: Open your BaseNetwork macro module within an empty MeVisLab workspace and select the .script file from its related files.

Add the following code into your .script file, between the “Single Slice” and the “Sequence” box.

BaseNetwork.script

        Box {
          title = "Comparison"
          Field "SubImage.z" {
            title = "Compare slice"
          }
          Field "SubImage.sz" {
            title = "With slice"
          }
          Button {
            title   = "Plot"
            command = "comparison"
          }
        }

Your panel should now be altered to look like this:

We will now add the “comparison” function, to give the “Plot” button in our “Comparison” box a purpose. To do so, change into your modules .py file and choose a cosy place for the following piece of code:

BaseNetwork.py

def comparison():
    clearFigure()
    figure = ctx.control("canvas").object().figure()

    values = [startSlice, endSlice]
    ctx.field("SubImage.z").value = values[0]
    ctx.field("SubImage.sz").value = values[0]
    y1 = getY()
    x1 = getX()
    ctx.field("SubImage.z").value = values[1]
    ctx.field("SubImage.sz").value = values[1]
    y2 = getY()
    x2 = getX()

    subplot = figure.add_subplot(211)
    subplot.bar(x1, y1, bins, color='r')
    subplot.bar(x2, y2, bins, color='b')
    subplot.legend([f'Slice {i}' for i in values])
    subplot.plot()
    subplot = figure.add_subplot(212)
    subplot.bar(x2, y2, bins, color='b')
    subplot.bar(x1, y1, bins, color='r')
    subplot.legend([f'Slice {i}' for i in values])
    figure.canvas.draw()
    ctx.field("SubImage.z").value = values[0]

You should now be able to reproduce results like these: