[Matplotlib-users] Bug with changing formatter and locator of a secondary axis ?

[Pierre Haessig]

Hello,

I've a question on the secondary axis feature introduced in matplotlib
3.1
<https://matplotlib.org/3.1.1/users/whats_new.html#secondary-x-y-axis-support>.
I'm on version 3.1.1.


My use case is to plot log values but also display the exponentiated
values. I can use a twin axes with the shared scale and a functional
formatter. Here is an example:

    import numpy as np
    import matplotlib.pyplot as plt
    from matplotlib.ticker import LogLocator, FuncFormatter

    fig, ax = plt.subplots(1,1)

    # twin ax with shared scale
    # cf. @ImportanceOfBeingErnest at
    https://stackoverflow.com/questions/55907892/matplotlib-secondary-axis-with-values-mapped-from-primary-axis
    ax2 = ax.twiny()
    ax.get_shared_x_axes().join(ax, ax2)

    # Plot
    ax.plot([-1,2,5], [1,2,3], 'd-')

    ax.grid()

    # x axis labeling
    ax.set_xlabel('log2 x-value')
    ax2.xaxis.set_major_formatter(FuncFormatter(lambda x,pos:
    f"{2**x:.3g}"))
    ax2.set_xlabel('x-value');


This twinx/y approach works, but I wanted originally to use the new
secondary axis feature. I see to options for this:

 1. use a secondary axes with the log transform
 2. use a secondary axes with no transform, and then transform the
    display ticks using a FuncFormatter

Option 1 works initially, but breaks when I want to use a LogLocator to
have equally spaced log values:

    fig, ax = plt.subplots(1,1)

    ax.plot([-1,2,5], [1,2,3], 'd-')

    ax2 = ax.secondary_xaxis('top', functions=(lambda x: 2**x, np.log2))
    # Place ticks at log equally spaced location [doesn't work]
    ax2.xaxis.set_major_locator(LogLocator(2))

Option 2 doesn't work either due. Setting the formatter has no effect

    fig, ax = plt.subplots(1,1)

    ax.plot([-1,2,5], [1,2,3], 'd-')

    ax2 = ax.secondary_xaxis('top')
    # Format the log values as exponentiated values [doesn't work]
    ax2.xaxis.set_major_formatter(FuncFormatter(lambda x,pos:
    f"{2**x:.3g}"))


Is it an expected behavior (or a known bug) that changing the locator
and the formatter of a secondary axis has no effect? Did I miss something?

In the examples
(https://matplotlib.org/3.1.1/gallery/subplots_axes_and_figures/secondary_axis.html),
there is one example (number 3, with interpolated transforms)  which
uses secax.xaxis.set_minor_locator(AutoMinorLocator()), but I don't know
if it is effective or not.

Best,

Pierre

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