def _do_plot_test():

    from numpy.random import multivariate_normal
    p = np.array([[32, 15],[15., 40.]])

    x,y = multivariate_normal(mean=(0,0), cov=p, size=5000).T
    sd = 2
    a,w,h = covariance_ellipse(p,sd)
    print(np.degrees(a), w, h)

    count = 0
    color=[]
    for i in range(len(x)):
        if _is_inside_ellipse(x[i], y[i], 0, 0, a, w, h):
            color.append('b')
            count += 1
        else:
            color.append('r')
    plt.scatter(x,y,alpha=0.2, c=color)


    plt.axis('equal')

    plot_covariance_ellipse(mean=(0., 0.),
                            cov = p,
                            std=sd,
                            facecolor='none')

    print(len(x) / count)
dataset/ETHPy150Open rlabbe/filterpy/filterpy/stats/stats.py/_do_plot_test/swapped operands of `/`