def plot_old_new_clusters(filenr, limb1, limb2, path="C:/Users/Cassandra/Documents/GitHub/Body_measurement/Python/Data/Test 4 - Normal"):
    cloud1 = np.loadtxt(str(path + '/' + str(filenr) + '_' + limb1 + '.txt'), delimiter=',')
    cloud2 = np.loadtxt(str(path + '/' + str(filenr) + '_' + limb2 + '.txt'), delimiter=',')
    A = np.column_stack((cloud1[:,0],cloud1[:,1],cloud1[:,2]))
    B = np.column_stack((cloud2[:,0],cloud2[:,1],cloud2[:,2]))
    A_center = cloud_linalg.get_cloud_center(A)
    B_center = cloud_linalg.get_cloud_center(B)
    full_cloud, new_cluster_centers, n_clusters_, labels = cloud_meanshift.perform_meanshift(A, B)
    
    colors = cycle('bgrcmykbgrcmykbgrcmykbgrcmyk')
    fig = plt.figure()
    ax = fig.gca(projection='3d')
    for k, col in zip(range(n_clusters_), colors):
        my_members = labels == k
        cluster_center = new_cluster_centers[k]
        ax.plot(full_cloud[my_members, 0], full_cloud[my_members, 1], full_cloud[my_members, 2], '.')
        ax.plot([cluster_center[0]], [cluster_center[1]], [cluster_center[2]],'o', markersize=14)
    
    fig2 = plt.figure()
    ax2 = fig2.gca(projection='3d')

    ax2.plot(A[:,0], A[:,1], A[:,2], '.')
    ax2.plot([A_center[0]], [A_center[1]], [A_center[2]],'o', markersize=14)
    
    ax2.plot(B[:,0], B[:,1], B[:,2], '.')
    ax2.plot([B_center[0]], [B_center[1]], [B_center[2]],'o', markersize=14)

    plt.show()
def plot_old_new_cluster_centers(filenr, limb1, limb2, path="C:/Users/Cassandra/Documents/GitHub/Body_measurement/Python/Data/Test 4 - Normal"):
    cloud1 = np.loadtxt(str(path + '/' + str(filenr) + '_' + limb1 + '.txt'), delimiter=',')
    cloud2 = np.loadtxt(str(path + '/' + str(filenr) + '_' + limb2 + '.txt'), delimiter=',')
    A = np.column_stack((cloud1[:,0],cloud1[:,1],cloud1[:,2]))
    B = np.column_stack((cloud2[:,0],cloud2[:,1],cloud2[:,2]))
    A_center = cloud_linalg.get_cloud_center(A)
    B_center = cloud_linalg.get_cloud_center(B)
    full_cloud, new_cluster_centers, n_clusters_, labels = cloud_meanshift.perform_meanshift(A, B)
    
    fig = plt.figure()
    ax = fig.gca(projection='3d')
    
    ax.plot(full_cloud[:,0], full_cloud[:,1], full_cloud[:,2], '.')
    ax.plot([A_center[0]], [A_center[1]], [A_center[2]],'o', markersize=14)
    ax.plot([B_center[0]], [B_center[1]], [B_center[2]],'o', markersize=14)
    ax.plot([new_cluster_centers[0][0]], [new_cluster_centers[0][1]], [new_cluster_centers[0][2]],'o', markersize=14)
    ax.plot([new_cluster_centers[1][0]], [new_cluster_centers[1][1]], [new_cluster_centers[1][2]],'o', markersize=14)

    plt.show()