Classe « Axes »

Méthode matplotlib.pyplot.Axes.secondary_xaxis

Signature de la méthode secondary_xaxis

def secondary_xaxis(self, location, *, functions=None, **kwargs) 

Description

secondary_xaxis.__doc__

Add a second x-axis to this Axes.

For example if we want to have a second scale for the data plotted on
the xaxis.


Warnings
--------
This method is experimental as of 3.1, and the API may change.

Parameters
----------
location : {'top', 'bottom', 'left', 'right'} or float
    The position to put the secondary axis.  Strings can be 'top' or
    'bottom' for orientation='x' and 'right' or 'left' for
    orientation='y'. A float indicates the relative position on the
    parent axes to put the new axes, 0.0 being the bottom (or left)
    and 1.0 being the top (or right).

functions : 2-tuple of func, or Transform with an inverse

    If a 2-tuple of functions, the user specifies the transform
    function and its inverse.  i.e.
    ``functions=(lambda x: 2 / x, lambda x: 2 / x)`` would be an
    reciprocal transform with a factor of 2.

    The user can also directly supply a subclass of
    `.transforms.Transform` so long as it has an inverse.

    See :doc:`/gallery/subplots_axes_and_figures/secondary_axis`
    for examples of making these conversions.

Returns
-------
ax : axes._secondary_axes.SecondaryAxis

Other Parameters
----------------
**kwargs : `~matplotlib.axes.Axes` properties.
    Other miscellaneous axes parameters.


Examples
--------
The main axis shows frequency, and the secondary axis shows period.

.. plot::

    fig, ax = plt.subplots()
    ax.loglog(range(1, 360, 5), range(1, 360, 5))
    ax.set_xlabel('frequency [Hz]')

    def invert(x):
        # 1/x with special treatment of x == 0
        x = np.array(x).astype(float)
        near_zero = np.isclose(x, 0)
        x[near_zero] = np.inf
        x[~near_zero] = 1 / x[~near_zero]
        return x

    # the inverse of 1/x is itself
    secax = ax.secondary_xaxis('top', functions=(invert, invert))
    secax.set_xlabel('Period [s]')
    plt.show()