How to use the perfplot.show function in perfplot

def test_speed(n=3):
    path_pts = [[0, 0], [0, 1], [1, 1], [1, 0]]
    path0 = path.Path(path_pts)
    path1 = pypathlib.ClosedPath(path_pts)

    def _mpl_path(pts):
        return path0.contains_points(pts)

    def _pypathlib_contains_points(pts):
        return path1.contains_points(pts)

    numpy.random.seed(0)

    perfplot.show(
        setup=lambda n: numpy.random.rand(n, 2),
        kernels=[_mpl_path, _pypathlib_contains_points],
        n_range=[2 ** k for k in range(n)],
        labels=["matplotlib.path.contains_points", "pypathlib.contains_points"],
        logx=True,
        logy=True,
        xlabel="num points",
    )

def test_speed(N=2):
    numpy.random.seed(1)
    osa = colorio.OsaUcs()
    cielab = colorio.CIELAB()
    # cam16 = colorio.CAM16(0.69, 20, L_A=64 / numpy.pi / 5)
    ciecam02 = colorio.CIECAM02(0.69, 20, L_A=64 / numpy.pi / 5)

    # This close probably means that another figure hasn't been properly closed.
    import matplotlib.pyplot as plt
    plt.close()

    perfplot.show(
        # Don't use numpy.random.rand(3, n) to avoid the CIECAM breakdown
        setup=lambda n: numpy.outer(numpy.random.rand(3), numpy.ones(n)) * 10,
        equality_check=None,
        kernels=[
            osa.to_xyz100,
            cielab.to_xyz100,
            # cam16.to_xyz100,
            lambda Jsh: ciecam02.to_xyz100(Jsh, "Jsh"),
            numpy.cbrt,
        ],
        labels=["OSA-UCS", "CIELAB", "CIECAM02", "cbrt"],
        n_range=[2 ** n for n in range(N)],
        logx=True,
        logy=True,
        # relative_to=3

def setup(n):
        out = numpy.empty((3, n))
        rgb = numpy.random.rand(3)
        for k in range(3):
            out[k] = rgb[k]
        return out

    Y_b = 20
    L_A = 64 / numpy.pi / 5
    c = 0.69  # average
    cam16 = colorio.CAM16(c, Y_b, L_A)

    cam16_legacy = CAM16Legacy(c, Y_b, L_A)

    perfplot.show(
        setup=setup,
        kernels=[cam16.from_xyz100, cam16_legacy.from_xyz100],
        labels=["new", "legacy"],
        n_range=1000 * numpy.arange(6),
        equality_check=False,
    )
    return

import numpy

import perfplot

perfplot.show(
    setup=numpy.random.rand,
    kernels=[
        lambda a: numpy.c_[a, a],
        lambda a: numpy.stack([a, a]).T,
        lambda a: numpy.vstack([a, a]).T,
        lambda a: numpy.column_stack([a, a]),
        lambda a: numpy.concatenate([a[:, None], a[:, None]], axis=1),
    ],
    labels=["c_", "stack", "vstack", "column_stack", "concat"],
    n_range=[2 ** k for k in range(15)],
    xlabel="len(a)",
)