Unidata / MetPy

from metpy.units import units

@pytest.mark.mpl_image_compare

def test_skewt_api():

    'Test the SkewT api'

    with style.context(test_style):

        fig = make_figure(figsize=(9, 9))

        skew = SkewT(fig)

        # Plot the data using normal plotting functions, in this case using

        # log scaling in Y, as dictated by the typical meteorological plot

        p = np.linspace(1000, 100, 10)

        t = np.linspace(20, -20, 10)

        u = np.linspace(-10, 10, 10)

        skew.plot(p, t, 'r')

        skew.plot_barbs(p, u, u)

        # Add the relevant special lines

        skew.plot_dry_adiabats()

        skew.plot_moist_adiabats()

        skew.plot_mixing_lines()

        hide_tick_labels(skew.ax)

        return fig

@pytest.mark.mpl_image_compare(savefig_kwargs={'bbox_inches': 'tight'})

        return fig

@pytest.mark.mpl_image_compare(savefig_kwargs={'bbox_inches': 'tight'})

def test_skewt_size():

    'Test that figure sizes are not inflated by ticks (#158)'

    with style.context(test_style):

        fig = make_figure(figsize=(9, 9))

        skew = SkewT(fig)

        # Plot the data using normal plotting functions, in this case using

        # log scaling in Y, as dictated by the typical meteorological plot

        p = np.linspace(1000, 100, 10)

        t = np.linspace(20, -20, 10)

        u = np.linspace(-10, 10, 10)

        skew.plot(p, t, 'r')

        skew.plot_barbs(p, u, u)

        # Add the relevant special lines

        skew.plot_dry_adiabats()

        skew.plot_moist_adiabats()

        skew.plot_mixing_lines()

        return fig

@pytest.mark.mpl_image_compare