core.py 文件源码

def masked_invalid(a, copy=True):
    """
    Mask an array where invalid values occur (NaNs or infs).

    This function is a shortcut to ``masked_where``, with
    `condition` = ~(np.isfinite(a)). Any pre-existing mask is conserved.
    Only applies to arrays with a dtype where NaNs or infs make sense
    (i.e. floating point types), but accepts any array_like object.

    See Also
    --------
    masked_where : Mask where a condition is met.

    Examples
    --------
    >>> import numpy.ma as ma
    >>> a = np.arange(5, dtype=np.float)
    >>> a[2] = np.NaN
    >>> a[3] = np.PINF
    >>> a
    array([  0.,   1.,  NaN,  Inf,   4.])
    >>> ma.masked_invalid(a)
    masked_array(data = [0.0 1.0 -- -- 4.0],
          mask = [False False  True  True False],
          fill_value=1e+20)

    """
    a = np.array(a, copy=copy, subok=True)
    mask = getattr(a, '_mask', None)
    if mask is not None:
        condition = ~(np.isfinite(getdata(a)))
        if mask is not nomask:
            condition |= mask
        cls = type(a)
    else:
        condition = ~(np.isfinite(a))
        cls = MaskedArray
    result = a.view(cls)
    result._mask = condition
    return result


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