python等值线图绘制,计算合适的等值线间距

python按照给定坐标点进行插值并绘制等值线图

import matplotlib.pyplot as plt
import numpy as np
import math
import pandas as pd
import io
import copy

def get_gap(gap):
    gap = str(gap)
    gap_len = len(gap)
    gap_list = list(map(int, gap))
    top_value = int(gap_list[0])

    gap_bottom = top_value * (10 ** (gap_len - 1))
    gap_mid = gap_bottom + int((10 ** (gap_len - 1) / 2))
    gap_top = (top_value + 1) * (10 ** (gap_len - 1))
    gap_value = [gap_bottom, gap_mid, gap_top]

    gap_bottom_dis = abs(int(gap) - gap_bottom)
    gap_mid_dis = abs(int(gap) - gap_mid)
    gap_top_dis = abs(int(gap) - gap_top)
    range_list = [gap_bottom_dis, gap_mid_dis, gap_top_dis]

    min_i = 0
    for i in range(len(range_list)):
        if range_list[i] < range_list[min_i]:
            min_i = i
    final_gap = gap_value[min_i]
    return int(final_gap)

def interpolation(lon, lat, lst):
    # 网格插值——反距离权重法
    p0 = [lon, lat]
    sum0 = 0
    sum1 = 0
    temp = []

    for point in lst:
        if lon == point[0] and lat == point[1]:
            return point[2]
        Di = distance(p0, point)

        ptn = copy.deepcopy(point)
        ptn = list(ptn)
        ptn.append(Di)
        temp.append(ptn)

    temp1 = sorted(temp, key=lambda point: point[3])

    for point in temp1[0:15]:
        sum0 += point[2] / math.pow(point[3], 2)
        sum1 += 1 / math.pow(point[3], 2)
    return sum0 / sum1

def distance(p, pi):
    dis = (p[0] - pi[0]) * (p[0] - pi[0]) + (p[1] - pi[1]) * (p[1]