[Matplotlib-users] Replacing deprecated use of pyplot.subplot

[Rory Yorke]

Hi,

I'm a contributor to the Python Control Systems Library [1], which uses
Matplotlib for plotting.

We recently noticed deprecation warnings due to how we use
pyplot.subplot.  We use it in the Matlab manner of either getting a
handle to an existing axis, or creating one if no suitable axis exists.

The warning is

  MatplotlibDeprecationWarning: Adding an axes using the same arguments
  as a previous axes currently reuses the earlier instance.  In a future
  version, a new instance will always be created and returned.
  Meanwhile, this warning can be suppressed, and the future behavior
  ensured, by passing a unique label to each axes instance.

For example, to plot the frequency response a linear dynamical system
(AKA Bode plot of the system), the relevant function could be simplified
to:

    def bode_plot(g):
       freq, mag, phase = freq_resp(g)
       subplot(211)
       semilogx(freq, 20*log10(mag))
       subplot(212)
       semilogx(freq, phase)

We've replaced that with code like this:

    def bode_plot(g):
       freq, mag, phase = freq_resp(g)

       ax_mag = None
       ax_phase = None
       for ax in gcf.axes():
           if ax.get_label() == 'control-bode-magnitude':
             ax_mag = ax
           elif ax.get_label() == 'control-bode-phase':
             ax_phase = ax

       if ax_mag is None or ax_phase is None:
         clf()
         ax_mag = subplot(211, label = 'control-bode-magnitude')
         ax_phase = subplot(212, label = 'control-bode-phase)

       ax_mag.semilogx(freq, 20*log10(mag))
       ax_phase.semilogx(freq, phase)
       
This means that calls like

    bode_plot(g)
    bode_plot(h)

will show the response of g and h on the same figure.

Is this method of using labels to check for existing axes reasonable?
Is there a better way?

Actual code exhibiting warnings at [2]; new code at [3].  The latter
link is to an as-yet unmerged branch, and may disappear.

Thanks,

Rory

[1] https://github.com/python-control/python-control
[2] https://github.com/python-control/python-control/blob/af8d4ee39dfa574c2b3b335f4cdb4be858ae469a/control/freqplot.py#L175
[3] https://github.com/murrayrm/python-control/blob/dc1820a4e64d73937c7de8df078c41ec1773e048/control/freqplot.py#L138