The next assignment was to rewrite the sliding plates using an implicit scheme. Here is a video of the animation produced using Visual Python arrows.

Colored according to speed. The initial velocity of the fluid is zero and the upper plate moves at a constant speed.
The visualization setup using Visual Python looks like this:

#SET UP VISUALIZATION SCENE
scene = display(title='Velocity profile', width=800, height=800, center=(u/2,y_divs/2,0), 
                autoscale=True, fullscreen=False)
base = box(pos=(u/2,-0.5,-2), length=u, height=0.4, width=4)
plate = box(pos=(u/2,y_divs+1.5,-2), length=u, height=0.4, width=4)
quiver = [] #TO HOLD ALL THE VELOCITY VECTOR ARROWS
quiver.append( arrow(pos=(0,0,0), axis=(BOUNDS[0,0],0,0),
                         shaftwidth=0.5, color=color.blue) )
for each in xrange(y_divs):
    quiver.append( arrow(pos=(0,each+1,0), axis=(UM[each,0],0,0),
                         shaftwidth=0.5, color=color.blue) )
quiver.append( arrow(pos=(0,y_divs+1,0), axis=(BOUNDS[-1,0],0,0),
                         shaftwidth=0.5, color=color.red) )
scene.autoscale = False

The main loop with the visualization update looks like this:

    for t in arange(t_divs-1): #START FROM 1, SKIP ZERO
        B = zeros(y_divs)
        B[:] = -1 * UM[:,t]
        B[ 0] -= BOUNDS[ 0,t+1] * alpha
        B[-1] -= BOUNDS[-1,t+1] * alpha
        
        UMnext = linalg.solve( A, B )
        UM[:,t+1] = UMnext[:]
        
        for y in arange(y_divs):
            #UPDATE VECTOR LENGTH BASED ON SPEED
            quiver[y+1].axis = (UM[y,t+1],0,0)
            #CHANGE ARROW COLOR BASED ON SPEED: Blue is slow, Red is fast
            quiver[y+1].color = (UM[y,t+1]/u,0.3,1.-UM[y,t+1]/u)