DeprecationWarning: 'shape' argument should be used instead of 'dims'

Question

In my practice on Gradient Descent, to plot the MSE in a 3d Graph, following code is use :

ij_min = np.unravel_index(indices=plot_cost.argmin(), dims=plot_cost.shape)

ij_min are the theta0 and theta1 values in the linear regression while plot_cost is the MSE array.

While running the above command, I got the following deprecation warning :

:2: DeprecationWarning: 'shape' argument should be used instead of 'dims'

I am confused as to what should be used in place of dims=plot_cost.shape.

Can someone help please ?

Answer 1

The DeprecationWarning indicates that the keyword argument dims is available but its use is discouraged because it will be removed in a future version. Instead of dims, shape should be used. This can be done like so:

ij_min = np.unravel_index(indices=plot_cost.argmin(), shape=plot_cost.shape)

The help function is a useful tool for examining the public documentation of Python functions and classes.

help(np.unravel_index)

Help on function unravel_index in module numpy:

unravel_index(...)
    unravel_index(indices, shape, order='C')

    Converts a flat index or array of flat indices into a tuple
    of coordinate arrays.

    Parameters
    ----------
    indices : array_like
        An integer array whose elements are indices into the flattened
        version of an array of dimensions ``shape``. Before version 1.6.0,
        this function accepted just one index value.
    shape : tuple of ints
        The shape of the array to use for unraveling ``indices``.

        .. versionchanged:: 1.16.0
            Renamed from ``dims`` to ``shape``.

    order : {'C', 'F'}, optional
        Determines whether the indices should be viewed as indexing in
        row-major (C-style) or column-major (Fortran-style) order.

        .. versionadded:: 1.6.0

    Returns
    -------
    unraveled_coords : tuple of ndarray
        Each array in the tuple has the same shape as the ``indices``
        array.

    See Also
    --------
    ravel_multi_index

    Examples
    --------
    >>> np.unravel_index([22, 41, 37], (7,6))
    (array([3, 6, 6]), array([4, 5, 1]))
    >>> np.unravel_index([31, 41, 13], (7,6), order='F')
    (array([3, 6, 6]), array([4, 5, 1]))

    >>> np.unravel_index(1621, (6,7,8,9))
    (3, 1, 4, 1)

You'll note that dims is unavailable in my version of numpy, 1.18.1. The help output indicates that dims was removed in version 1.16.0.