The numpy.ma module — NumPy v2.6.dev0 Manual

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NumPy v2.6.dev0 Manual - Home

Building from source

NumPy’s module structure

The N-dimensional array (ndarray)

Data type objects (dtype)

Data type promotion in NumPy

Iterating over arrays

Standard array subclasses

Constants of the numpy.ma module

Masked array operations

The array interface protocol

Datetimes and timedeltas

Universal functions (ufunc)

Routines and objects by topic

Typing (numpy.typing)

Array API standard compatibility

CPU/SIMD optimizations

Global Configuration Options

Testing guidelines

Status of numpy.distutils and migration advice

numpy.ma.masked_array

array(data[, dtype, copy, order, mask, ...]) An array class with possibly masked values. masked_array alias of MaskedArray

numpy.ma.asanyarray

Yet another possibility is to use any of the following functions:

numpy.ma.fix_invalid

Yet another possibility is to use any of the following functions:

numpy.ma.masked_equal

Yet another possibility is to use any of the following functions:

numpy.ma.masked_greater

Yet another possibility is to use any of the following functions:

masked_greater_equal

Yet another possibility is to use any of the following functions:

numpy.ma.masked_inside

Yet another possibility is to use any of the following functions:

numpy.ma.masked_invalid

Yet another possibility is to use any of the following functions:

numpy.ma.masked_less

Yet another possibility is to use any of the following functions:

numpy.ma.masked_less_equal

Yet another possibility is to use any of the following functions:

numpy.ma.masked_not_equal

Yet another possibility is to use any of the following functions:

numpy.ma.masked_object

Yet another possibility is to use any of the following functions:

numpy.ma.masked_outside

Yet another possibility is to use any of the following functions:

numpy.ma.masked_values

Yet another possibility is to use any of the following functions:

numpy.ma.masked_where

Yet another possibility is to use any of the following functions:

numpy.ma.MaskedArray.__array__

through the __array__ method. The output is then a numpy.ndarray.

numpy.ma.getmaskarray

array(data[, dtype, copy, order, mask, ...]) An array class with possibly masked values. masked_array alias of MaskedArray

numpy.ma.compressed

array(data[, dtype, copy, order, mask, ...]) An array class with possibly masked values. masked_array alias of MaskedArray

numpy.ma.soften_mask

array(data[, dtype, copy, order, mask, ...]) An array class with possibly masked values. masked_array alias of MaskedArray

numpy.ma.harden_mask

array(data[, dtype, copy, order, mask, ...]) An array class with possibly masked values. masked_array alias of MaskedArray

previous Masked arrays