Masked values of True exclude the corresponding element from any computation.

Construction:

x = MaskedArray(data, mask=nomask, dtype=None, copy=False, subok=True,
                ndmin=0, fill_value=None, keep_mask=True, hard_mask=None,
                shrink=True, order=None)

Parameters

data : array_like

Input data.

mask : sequence, optional

Mask. Must be convertible to an array of booleans with the same shape as :None:None:`data`. True indicates a masked (i.e. invalid) data.

dtype : dtype, optional

Data type of the output. If dtype is None, the type of the data argument ( data.dtype ) is used. If dtype is not None and different from data.dtype , a copy is performed.

copy : bool, optional

Whether to copy the input data (True), or to use a reference instead. Default is False.

subok : bool, optional

Whether to return a subclass of MaskedArray if possible (True) or a plain MaskedArray . Default is True.

ndmin : int, optional

Minimum number of dimensions. Default is 0.

fill_value : scalar, optional

Value used to fill in the masked values when necessary. If None, a default based on the data-type is used.

keep_mask : bool, optional

Whether to combine :None:None:`mask` with the mask of the input data, if any (True), or to use only :None:None:`mask` for the output (False). Default is True.

hard_mask : bool, optional

Whether to use a hard mask or not. With a hard mask, masked values cannot be unmasked. Default is False.

shrink : bool, optional

Whether to force compression of an empty mask. Default is True.

order : {'C', 'F', 'A'}, optional

Specify the order of the array. If order is 'C', then the array will be in C-contiguous order (last-index varies the fastest). If order is 'F', then the returned array will be in Fortran-contiguous order (first-index varies the fastest). If order is 'A' (default), then the returned array may be in any order (either C-, Fortran-contiguous, or even discontiguous), unless a copy is required, in which case it will be C-contiguous.

An array class with possibly masked values.

Examples

The mask can be initialized with an array of boolean values with the same shape as data .

This example is valid syntax, but we were not able to check execution

>>> data = np.arange(6).reshape((2, 3))
... np.ma.MaskedArray(data, mask=[[False, True, False],
...                               [False, False, True]])
masked_array(
  data=[[0, --, 2],
        [3, 4, --]],
  mask=[[False,  True, False],
        [False, False,  True]],
  fill_value=999999)

Alternatively, the mask can be initialized to homogeneous boolean array with the same shape as data by passing in a scalar boolean value:

This example is valid syntax, but we were not able to check execution

>>> np.ma.MaskedArray(data, mask=False)
masked_array(
  data=[[0, 1, 2],
        [3, 4, 5]],
  mask=[[False, False, False],
        [False, False, False]],
  fill_value=999999)

This example is valid syntax, but we were not able to check execution

>>> np.ma.MaskedArray(data, mask=True)
masked_array(
  data=[[--, --, --],
        [--, --, --]],
  mask=[[ True,  True,  True],
        [ True,  True,  True]],
  fill_value=999999,
  dtype=int64)

>>> np.False_ is np.ma.nomask
True

See :

Back References

The following pages refer to to this document either explicitly or contain code examples using this.

numpy.ma.core.getmaskarray numpy.ma.core.getmask scipy.sparse.csgraph._tools.csgraph_from_masked numpy.ma.core.filled numpy.ma.core.putmask numpy.ma.core.MaskedArray dask.array.ma.masked_array numpy.ma.core.MaskedArray.real dask.array.ma.getmaskarray numpy.ma.core.MaskedArray.imag scipy.special._logsumexp.logsumexp numpy.ma.core.asanyarray numpy.ma.extras.flatnotmasked_edges numpy.ma.core.asarray numpy.ma.core.array

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GitHub : /numpy/ma/core.py#2703
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