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numpy.asanyarray
- numpy.asanyarray(a, dtype=None, order=None)[source]
- 
    Convert the input to an ndarray, but pass ndarray subclasses through. - Parameters
- 
      - aarray_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. 
- dtypedata-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
- 
      - outndarray 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 - asarray
- 
       Similar function which always returns ndarrays. 
- ascontiguousarray
- 
       Convert input to a contiguous array. 
- asfarray
- 
       Convert input to a floating point ndarray. 
- asfortranarray
- 
       Convert input to an ndarray with column-major memory order. 
- asarray_chkfinite
- 
       Similar function which checks input for NaNs and Infs. 
- fromiter
- 
       Create an array from an iterator. 
- fromfunction
- 
       Construct an array by executing a function on grid positions. 
 ExamplesConvert a list into an array: >>> a = [1, 2] >>> np.asanyarray(a) array([1, 2])Instances of ndarraysubclasses are passed through as-is:>>> a = np.array([(1.0, 2), (3.0, 4)], dtype='f4,i4').view(np.recarray) >>> np.asanyarray(a) is a True
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 https://numpy.org/doc/1.19/reference/generated/numpy.asanyarray.html