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

[Elan Ernest]

The fact that Opion 1 does not work is a bug. This has been fixed in the 
meantime, so it should work with the yet to be released matplotlib 3.2.

The fact that Opion 2 does not work can be considered a missing feature. 
Feel free to open an issue about it, which can be tagged as feature 
request/wishlist feature. 
(https://github.com/matplotlib/matplotlib/pull/14463 might be related.)

Am 14.10.2019 um 17:38 schrieb 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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