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numpy.asanyarray(a, dtype=None, order=None)[source] -
Convert the input to an ndarray, but pass ndarray subclasses through.
Parameters: a : array_like
Input data, in any form that can be converted to an array. This includes scalars, lists, lists of tuples, tuples, tuples of tuples, tuples of lists, and ndarrays.
dtype : data-type, optional
By default, the data-type is inferred from the input data.
order : {?C?, ?F?}, optional
Whether to use row-major (C-style) or column-major (Fortran-style) memory representation. Defaults to ?C?.
Returns: out : ndarray or an ndarray subclass
Array interpretation of
a. Ifais an ndarray or a subclass of ndarray, it is returned as-is and no copy is performed.See also
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asarray - Similar function which always returns ndarrays.
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ascontiguousarray - Convert input to a contiguous array.
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asfarray - Convert input to a floating point ndarray.
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asfortranarray - Convert input to an ndarray with column-major memory order.
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asarray_chkfinite - Similar function which checks input for NaNs and Infs.
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fromiter - Create an array from an iterator.
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fromfunction - Construct an array by executing a function on grid positions.
Examples
Convert a list into an array:
>>> a = [1, 2] >>> np.asanyarray(a) array([1, 2])
Instances of
ndarraysubclasses are passed through as-is:>>> a = np.matrix([1, 2]) >>> np.asanyarray(a) is a True
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numpy.asanyarray()
2017-01-10 18:12:50
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