Using Matplotlib sliders with multiple plots on the same axes

Question

I have multiple lines plots that are plotted on the same axes in Matplotlib. I'm trying to use the Slider widget to adjust the lines, but for some reason only the first line plot is showing, and nothing is updated when I move the slider:

import matplotlib.pyplot as p
from matplotlib.widgets import Slider, Button, RadioButtons

Kd=0.0 
Ks=0.0
mass=0.02 

width=900
yPosition = []
yVelocity = []
yTarget = []
yForce = []
lpos= []
lvel = []
ltarget = []
lforce = []

def runSimulation(positionGain=1.5, velocityGain=60.0):
    global Kd, Ks, mass, yPosition, yVelocity, yTarget, yForce, width

    velocity = 0.0
    acceleration = 0.0
    reference = 100.0
    target = 0.0
    position = 0.0
    force = 0.0
    T=0.0005

    yPosition = []
    yVelocity = []
    yTarget = []
    yForce = []

    for i in range(0,width*10):
        acceleration = (force - Kd*velocity - Ks*position)/mass

        # Equations of motion for constant acceleration
        position = position + (velocity*T) + (0.5*acceleration*T*T)
        velocity = velocity + acceleration*T 

        e1 = target - position # Output of 1st control system
        e2 = positionGain * e1 - velocity # Output of 2nd control system
        force = velocityGain * e2

        if i % 10 == 0: #Plot 1 point for every 10 iterations of simulation
            if i>=30:
                target = reference
            else:
                target = 0
            yPosition.append(position)
            yVelocity.append(velocity*0.1)
            yTarget.append(target)
            yForce.append(force*0.001)

def plotGraph():
    global yPosition, yVelocity, yTarget, yForce, lpos, lvel, ltarget, lforce
    x = range(0,width)
    ax = p.subplot(111)
    lpos, = ax.plot(x,yPosition,'r')
    lvel, = ax.plot(x,yVelocity,'g')
    ltarget, = ax.plot(x,yTarget,'k')
    lforce, = ax.plot(x,yForce,'b')

ax = p.subplot(111)
p.subplots_adjust(left=0.25, bottom=0.25)
runSimulation()
plotGraph()

p.axis([0, 1, -10, 10])

axcolor = 'lightgoldenrodyellow'
axpos = p.axes([0.25, 0.1, 0.65, 0.03], axisbg=axcolor)
axvel  = p.axes([0.25, 0.15, 0.65, 0.03], axisbg=axcolor)

spos = Slider(axpos, 'Position Gain', 1.0, 20.0, valinit=1.5)
svel = Slider(axvel, 'Velocity Gain', 5.0, 500.0, valinit=60.0)

def update(val):
    global yPosition,yVelocity,yTarget,yForce
    runSimulation(round(spos.val,2),round(svel.val,2))
    lpos.set_ydata(yPosition)
    lvel.set_ydata(yVelocity)
    ltarget.set_ydata(yTarget)
    lforce.set_ydata(yForce)
    p.draw()

spos.on_changed(update)
svel.on_changed(update)
p.show()

If you remove the lines between plotGraph() and p.show() you can see the original plots.

Gerrit · Accepted Answer · 2012-12-10 16:12:42Z

To be honest, you made a little mess with the axis positioning and on the update function. I took the liberty to write again the plotting part and put the comment in there:

# run your simulation like usual
runSimulation()

#create a ordered grid of axes, not one in top of the others
axcolor = 'lightgoldenrodyellow'
fig = p.figure()
axdata = p.subplot2grid((7,4),(0,0),colspan=4,rowspan=4)
axpos = p.subplot2grid((7,4),(-2,0),colspan=4, axisbg=axcolor)
axvel = p.subplot2grid((7,4),(-1,0),colspan=4, axisbg=axcolor)

# create your plots in the global space.
# you are going to reference these lines, so you need to make them visible
# to the update functione, instead of creating them inside a function 
# (and thus losing them at the end of the function)
x = range(width)
lpos, = axdata.plot(x,yPosition,'r')
lvel, = axdata.plot(x,yVelocity,'g')
ltarget, = axdata.plot(x,yTarget,'k')
lforce, = axdata.plot(x,yForce,'b')

# same as usual
spos = Slider(axpos, 'Position Gain', 1.0, 20.0, valinit=1.5)
svel = Slider(axvel, 'Velocity Gain', 5.0, 500.0, valinit=60.0)


def update(val):
    # you don't need to declare the variables global, as if you don't
    # assign a value to them python will recognize them as global
    # without problem
    runSimulation(round(spos.val,2),round(svel.val,2))
    lpos.set_ydata(yPosition)
    lvel.set_ydata(yVelocity)
    ltarget.set_ydata(yTarget)
    lforce.set_ydata(yForce)
    # you need to update only the canvas of the figure
    fig.canvas.draw()

spos.on_changed(update)
svel.on_changed(update)
p.show()

By the way, if you want to simulate an damped oscillation, I strongly suggest you to give a look to the integrate module of scipy, wich contain the odeint function to integrate differential equation in a better way than what are you doing (that is called Euler integration, and is really error-prone)

Excellent - thank you! I was just expanding on the slider_demo.py example in the Matplotlib docs (matplotlib.org/examples/widgets/slider_demo.html), but your approach using subplot2grid is much clearer.

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