numpy.ma.MaskedArray.sort¶

method

ma.MaskedArray.sort(axis=- 1, kind=None, order=None, endwith=True, fill_value=None)[source]¶

Sort the array, in-place

Parameters

aarray_like: Array to be sorted.
axisint, optional: Axis along which to sort. If None, the array is flattened before sorting. The default is -1, which sorts along the last axis.
kind{‘quicksort’, ‘mergesort’, ‘heapsort’, ‘stable’}, optional: The sorting algorithm used.
orderlist, optional: When a is a structured array, this argument specifies which fields to compare first, second, and so on. This list does not need to include all of the fields.
endwith{True, False}, optional: Whether missing values (if any) should be treated as the largest values (True) or the smallest values (False) When the array contains unmasked values sorting at the same extremes of the datatype, the ordering of these values and the masked values is undefined.
fill_valuescalar or None, optional: Value used internally for the masked values. If fill_value is not None, it supersedes endwith.

Returns

sorted_arrayndarray: Array of the same type and shape as a.

See also

numpy.ndarray.sort: Method to sort an array in-place.
argsort: Indirect sort.
lexsort: Indirect stable sort on multiple keys.
searchsorted: Find elements in a sorted array.

Notes

See sort for notes on the different sorting algorithms.

Examples

>>> a = np.ma.array([1, 2, 5, 4, 3],mask=[0, 1, 0, 1, 0])
>>> # Default
>>> a.sort()
>>> a
masked_array(data=[1, 3, 5, --, --],
             mask=[False, False, False,  True,  True],
       fill_value=999999)

>>> a = np.ma.array([1, 2, 5, 4, 3],mask=[0, 1, 0, 1, 0])
>>> # Put missing values in the front
>>> a.sort(endwith=False)
>>> a
masked_array(data=[--, --, 1, 3, 5],
             mask=[ True,  True, False, False, False],
       fill_value=999999)

>>> a = np.ma.array([1, 2, 5, 4, 3],mask=[0, 1, 0, 1, 0])
>>> # fill_value takes over endwith
>>> a.sort(endwith=False, fill_value=3)
>>> a
masked_array(data=[1, --, --, 3, 5],
             mask=[False,  True,  True, False, False],
       fill_value=999999)

numpy.ma.MaskedArray.searchsorted

numpy.ma.MaskedArray.take