Bug summary

Bug report

matplotlib.cbook.boxplot_stats() raises an IndexError when given a masked array in which all values are masked.

Minimal reproducible example

import numpy as np
from matplotlib import cbook

data = np.ma.masked_array(
    [10.0, 20.0],
    mask=[True, True]
)

cbook.boxplot_stats(data)

Expected behavior

The function should handle an all-masked dataset gracefully, following the existing empty-data behavior, instead of raising an exception.

Actual behavior

After the masked values are removed, the resulting array is empty. The subsequent percentile calculation raises an IndexError.

Additional context

Partially masked data appears to be covered by the existing test_boxplot_masked test, but an all-masked dataset does not appear to be covered.

I reproduced this behavior using the local Matplotlib checkout. The proposed fix has not yet been submitted for review.

Code for reproduction

import numpy as np
from matplotlib import cbook

data = np.ma.masked_array([10.0, 20.0], mask=[True, True])
cbook.boxplot_stats(data)

Actual outcome

The code raises an IndexError when all elements of the masked array are masked.

Example error with NumPy 2.x:

IndexError: index -1 is out of bounds for axis 0 with size 0

The exact error message may vary depending on the NumPy version.

Expected outcome

The function should handle an array with all values masked gracefully, without raising an exception. It should return appropriate statistics for the empty data remaining after masked values are excluded, consistent with the function's existing empty-data behavior.

Additional information

No response

Operating system

No response

Matplotlib Version

3.11.1

Matplotlib Backend

No response

Python version

No response

Jupyter version

No response

Installation

None