lot is constructed (nrows=ncols=1), the resulting
        single Axis object is returned as a scalar.
        - for Nx1 or 1xN subplots, the returned object is a 1-d numpy object
        array of Axis objects are returned as numpy 1-d arrays.
        - for NxM subplots with N>1 and M>1 are returned as a 2d array.

      If False, no squeezing is done: the returned axis object is always
      a 2-d array containing Axis instances, even if it ends up being 1x1.

    subplot_kw : dict
      Dict with keywords passed to the add_subplot() call used to create each
      subplots.

    ax : Matplotlib axis object, optional

    layout : tuple
      Number of rows and columns of the subplot grid.
      If not specified, calculated from naxes and layout_type

    layout_type : {'box', 'horizontal', 'vertical'}, default 'box'
      Specify how to layout the subplot grid.

    fig_kw : Other keyword arguments to be passed to the figure() call.
        Note that all keywords not recognized above will be
        automatically included here.

    Returns
    -------
    fig, ax : tuple
      - fig is the Matplotlib Figure object
      - ax can be either a single axis object or an array of axis objects if
      more than one subplot was created.  The dimensions of the resulting array
      can be controlled with the squeeze keyword, see above.

    Examples
    --------
    x = np.linspace(0, 2*np.pi, 400)
    y = np.sin(x**2)

    # Just a figure and one subplot
    f, ax = plt.subplots()
    ax.plot(x, y)
    ax.set_title('Simple plot')

    # Two subplots, unpack the output array immediately
    f, (ax1, ax2) = plt.subplots(1, 2, sharey=True)
    ax1.plot(x, y)
    ax1.set_title('Sharing Y axis')
    ax2.scatter(x, y)

    # Four polar axes
    plt.subplots(2, 2, subplot_kw=dict(polar=True))
    r