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 _______________________________________________ Matplotlib-users mailing list [hidden email] https://mail.python.org/mailman/listinfo/matplotlib-users |
Hey Rory, In general, especially for library code, you should avoid relying on the pyplot state machine. That means explicitly passing Axes and Figure object around to and from your functions. For me, making that switch meant added an `ax=None` kwarg to the end of my function signatures. Then I carry around an axes_validator function that looks something like this: But that's not really necessary. So in your case, I think you should do something like this: import numpy as np import matplotlib.pyplot as plt def bode_plot(g, ax_mag=None, ax_phase=None, mag_opts=None, phase_opts=None): # create axes if they're not both supplied if not ax_mag or not ax_phase: fig, (ax_mag, ax_phase) = plt.subplots(nrows=2) # make the plotting options empty dicts if # not supplied if not mag_opts: mag_opts = {} if not phase_opts: phase_opts = {} # compute signal stuff freq, mag, phase = freq_resp(g) # 99% sure semilogx returns a tuple of artists, so I unpack it # you should check this though mag_artist, = ax_mag.semilogx(freq, 20 * np.log10(mag), **mag_opts) phase_artist, = ax_phase.semilogx(freq, phase, **phase_opts) # package the output for later (if you want to modify artists) output = { 'fig': fig, 'axes': (ax_mag, ax_phase), 'arists': (mag_artist, phase_artist) } return output And then you'd use the code like this: fig, (ax_mag, ax_phase) = plt.subplots(nrows=2, figsize=(12, 6)) g_mpl = bode_plot(g, ax_mag=ax_mag, ax_phase=ax_phase, color='r', linewidth=2, label='G') h_mpl = bode_plot(h, ax_mag=ax_mag, ax_phase=ax_phase, color='b'm linewidth=1, label='H') ax_mag.legend() Or do something like this: g_mpl = bode_plot(g, color='r', linewidth=2, label='G') h_mpl = bode_plot(h, ax_mag=g_mpl['axes'][0], ax_phase=g_mpl['axes'][0]) Does that help? -Paul On Sat, Jan 20, 2018 at 11:44 AM, Rory Yorke <[hidden email]> wrote: Hi, _______________________________________________ Matplotlib-users mailing list [hidden email] https://mail.python.org/mailman/listinfo/matplotlib-users |
Errr, make that last line: h_mpl = bode_plot(h, ax_mag=g_mpl['axes'][0], ax_phase=g_mpl['axes'][1]) On Sat, Jan 20, 2018 at 1:02 PM, Paul Hobson <[hidden email]> wrote:
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In reply to this post by Rory Yorke-2
Rory,
The general direction of Matplotlib's evolution is toward encouraging more explicit code, so that the programmer or user has more responsibility for specifying which figure and axes are to be used, rather than relying on the state machine and the concepts of "current figure" and "current axes". Therefore we recommend using pyplot functions very sparingly. If you need to keep your API exactly as it is, your approach using labels looks reasonable. I think it can be simplified, though, by defining a helper function something like this: def _get_bode_axes(): fig = plt.gcf() if not hasattr(fig, '_bode_axes'): fig.clf() fig._bode_axes = fig.subplots(2, 1, sharex=True) return fig._bode_axes Then, outside any loop in plot_bode but conditional on the Plot kwarg, use a single call: ax_mag, ax_phase = _get_bode_axes() Also conditional on Plot, put your loop over syslist to do the plotting. I would make that loop separate from the calculation. In general, code is clearer and easier to test when calculations are separated from plotting, ideally with separate functions. You could also use the initialization block inside _get_bode_axes to customize the axes with respect to grid, labels...anything that you don't want to change as you add lines to the plot, and that you can set once with the first call to plot_bode and won't potentially need to change in subsequent calls that write to the same figure. Or you could do that sort of customization outside and after the loop that plots the lines. Eric On 2018/01/20 9:44 AM, Rory Yorke wrote: > 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 > _______________________________________________ > Matplotlib-users mailing list > [hidden email] > https://mail.python.org/mailman/listinfo/matplotlib-users > _______________________________________________ Matplotlib-users mailing list [hidden email] https://mail.python.org/mailman/listinfo/matplotlib-users |
In reply to this post by Paul Hobson-2
Hi Paul,
Paul Hobson <[hidden email]> writes: >> In general, especially for library code, you should avoid relying on the >> pyplot state machine. OK, thanks. Eric said much the same in his reply. Thanks for the example code, that helps. It seems like the recommended overall approach is "if axes are provided, used them, else create new ones; return the axes used". For now we'll use the approach I've implemented, perhaps with Eric's suggested improvement. I'll propose creating a new suite of plot functions (there are several specialized plots we do: Bode, Nichols, etc.) that adopt the no-state-machine approach. Thanks, both to you and Eric. Regards, Rory _______________________________________________ Matplotlib-users mailing list [hidden email] https://mail.python.org/mailman/listinfo/matplotlib-users |
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