Hacky attempt at automatically adjusting the number of tick labels

auto_ticker_example.py

"""
Automatically adjust the number of ticklabels based on label width.

This is a hacky attempt at an auto tick locator and misses *many* use cases.
To test, stretch and shrink the x-axis.
"""
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.ticker as mtick
import matplotlib.axis as maxis


class AutoLocator(mtick.MaxNLocator):
    """Tick locator that tries to be smart.

    Parameters
    ----------
    nbins : int
        Maximum number of bins---i.e., tick intervals.

    steps : list of numbers
        Allowable steps for lowest displayed digit. This is a sequence of
        "nice" numbers starting with 1 and ending with 10.

    """
    def __init__(self, nbins=9, steps=[1, 2, 5, 10], fontsize=None):
        mtick.MaxNLocator.__init__(self, nbins=nbins, steps=steps)

        if fontsize is None:
            fontsize = plt.rcParams['font.size']
        self.fontsize = fontsize
        self._nbins_cached = nbins

    def bin_boundaries(self, vmin, vmax):
        """Return bin boundaries (a.k.a. tick locations)."""

        # The calculation of the label width should actually depend on the
        # tick Formatter instance.
        label_width = max(len('%g' % v) for v in (vmin, vmax))
        # This is only an approximate calculation of the label width
        label_px_width = label_width * self.fontsize

        w, h = self.axis.axes.figure.canvas.get_width_height()

        if not isinstance(self.axis, maxis.XAxis):
            raise NotImplementedError("Currently only XAxis is supported.")
        # Use figure width to calculate the number of bins---only valid for x-axis.
        # The following nbins calculation is approximate since it should vary
        # with subplot parameters---i.e. padding on the left and right of
        # subplots and multiple columns in a subplot grid.
        self._nbins = min(self._nbins_cached, int(w / label_px_width))
        return mtick.MaxNLocator.bin_boundaries(self, vmin, vmax)


if __name__ == '__main__':
    fig, ax = plt.subplots()

    x = np.linspace(0, 7000000)
    y = np.sin(x)
    ax.plot(x, y)

    ax.xaxis.set_major_locator(AutoLocator())
    plt.tight_layout()

    plt.show()