For a high-level overview of nan and masked array support, see also SciPy FAQ.

MaskedArray is a numpy ndarray look-alike that allows one to keep track of missing values.

MaskedArray is implemented in the [source:trunk/numpy/core/ma.py numpy.core.ma] module. The numpy ma module is originally written for Numeric by Paul Dubois and adapted for numpy by Travis Oliphant and (mainly) Paul Dubois.

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Migration Guide

describe migration from Numeric.MA to numpy.ma here

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Remaining Issues

Some of the same issues that were resolved in numpy need to be revisited for ma. (See Numeric3.0 Design Document)

• What does single element indexing return? Scalars or rank-0 arrays?
  An additional complication is that that single element may be masked.
  
  
  • What should a single element indexing return for an unmasked element?
    
    
  • What should a single element indexing return for a masked element?
    
    As of changeset:1882, the answer is ma.masked. The singleton ma.masked is defined in [source:tags/0.9.2/numpy/core/ma.py ma.py] as follows:

    masked = MaskedArray([0], int, mask=[1])[0:0]
    masked = masked[0:0]
    

    This changed from MA, where masked was defined as a rank-0 array. This definition leads to some surprizing properties:

    >>> from numpy.core.ma import *
    >>> x = array([1,2,3.0])
    >>> x[1].shape
    (0,)
    

    At the same time

    >>> x[0].shape
    ()
    

    This can easily be fixed by changing the definition of "masked" back to rank-0 array. (Done in changeset:1888)

    >>> x[1].dtype
    <type 'int64_arrtype'>
    

    At the same time

     >>> x[0].dtype
    <type 'float64_arrtype'>
    

    Unlike the first problem, this one cannot be easily fixed without giving up the ability to check for mising values using

    >>> x[1] is masked
    True
    >>> x[0] is masked
    False
    

    It is tempting to eliminate the special case and just use x[i].mask.all() and x[i].mask.any(), the constructs that have clear meaning for any number of elements. The downside of changing the return value of x[i] for masked elements is that "x[i] is masked" will silently break in a dangerous way - it will always be false.

It may be safer to also change the name "masked" to say "missing" and educate users that x[i] is masked should be changed to x[i].mask.any(), x[i].mask.all() or even just x[i].mask as appropriate and x[i] = masked should be changed to x[i] = missing.

• Can arrays be used as truth values directly?