numpy.ma.array¶
- numpy.ma.array(data, dtype=None, copy=False, order=False, mask=False, fill_value=None, keep_mask=True, hard_mask=False, shrink=True, subok=True, ndmin=0)[source]¶
An array class with possibly masked values.
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)
Parameters: data : array_like
Input data.
mask : sequence, optional
Mask. Must be convertible to an array of booleans with the same shape as 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 mask with the mask of the input data, if any (True), or to use only 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.