问如何在python中绘制k-距离图

EN

import numpy as np
import pandas as pd
import math

def k_distances(X, n=None, dist_func=None):
    """Function to return array of k_distances.

    X - DataFrame matrix with observations
    n - number of neighbors that are included in returned distances (default number of attributes + 1)
    dist_func - function to count distance between observations in X (default euclidean function)
    """
    if type(X) is pd.DataFrame:
        X = X.values
    k=0
    if n == None:
        k=X.shape[1]+2
    else:
        k=n+1

    if dist_func == None:
        # euclidean distance square root of sum of squares of differences between attributes
        dist_func = lambda x, y: math.sqrt(
            np.sum(
                np.power(x-y, np.repeat(2,x.size))
            )
        )

    Distances = pd.DataFrame({
        "i": [i//10 for i in range(0, len(X)*len(X))],
        "j": [i%10 for i in range(0, len(X)*len(X))],
        "d": [dist_func(x,y) for x in X for y in X]
    })
    return np.sort([g[1].iloc[k].d for g in iter(Distances.groupby(by="i"))])

import matplotlib.pyplot as plt

d = k_distances(X,n,dist_func)
plt.plot(d)
plt.ylabel("k-distances")
plt.grid(True)
plt.show()