view(self, dtype=None, type=None, fill_value=None)
a.view()
is used two different ways:
a.view(some_dtype)
or a.view(dtype=some_dtype)
constructs a view of the array's memory with a different data-type. This can cause a reinterpretation of the bytes of memory.
a.view(ndarray_subclass)
or a.view(type=ndarray_subclass)
just returns an instance of :None:None:`ndarray_subclass` that looks at the same array (same shape, dtype, etc.) This does not cause a reinterpretation of the memory.
If fill_value
is not specified, but dtype
is specified (and is not an ndarray sub-class), the fill_value
of the MaskedArray will be reset. If neither fill_value
nor dtype
are specified (or if dtype
is an ndarray sub-class), then the fill value is preserved. Finally, if fill_value
is specified, but dtype
is not, the fill value is set to the specified value.
For a.view(some_dtype)
, if some_dtype
has a different number of bytes per entry than the previous dtype (for example, converting a regular array to a structured array), then the behavior of the view cannot be predicted just from the superficial appearance of a
(shown by print(a)
). It also depends on exactly how a
is stored in memory. Therefore if a
is C-ordered versus fortran-ordered, versus defined as a slice or transpose, etc., the view may give different results.
Data-type descriptor of the returned view, e.g., float32 or int16. The default, None, results in the view having the same data-type as a. As with ndarray.view
, dtype can also be specified as an ndarray sub-class, which then specifies the type of the returned object (this is equivalent to setting the type
parameter).
Type of the returned view, either ndarray or a subclass. The default None results in type preservation.
The value to use for invalid entries (None by default). If None, then this argument is inferred from the passed dtype
, or in its absence the original array, as discussed in the notes below.
Return a view of the MaskedArray data.
numpy.ndarray.view
Equivalent method on ndarray object.
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