def METHOD_NAME(self):
    """Plot parameter probability"""
    source_x, source_y = nest.GetPosition(self.source)
    # Calculate reference values
    ref_probability = np.zeros(self.plot_shape[::-1])
    for i, x in enumerate(np.linspace(self.plot_edges[0], self.plot_edges[1], self.plot_shape[0])):
        positions = np.array(
            [[x, y] for y in np.linspace(self.plot_edges[2], self.plot_edges[3], self.plot_shape[1])]
        )
        ref_distances = np.sqrt((positions[:, 0] - source_x) ** 2 + (positions[:, 1] - source_y) ** 2)
        values = self._probability_calculation(ref_distances)
        ref_probability[:, i] = np.maximum(np.minimum(np.array(values), 1.0), 0.0)
    # Create the parameter
    parameter = self._probability_calculation(nest.spatial.distance)
    fig, ax = plt.subplots()
    nest.PlotProbabilityParameter(self.source, parameter, ax=ax, shape=self.plot_shape, edges=self.plot_edges)
    assert len(ax.images) >= 1
    img = ax.images[0]
    img_data = img.get_array().data
    assert img_data == pytest.approx(ref_probability)