1 # -*- coding: utf-8 -*-
2 import numpy as np
3 import matplotlib.pyplot as plt
4 import pandas as pd
5 import math
6 plt.rcParams['font.sans-serif'] = ['SimHei']
7 plt.rcParams['axes.unicode_minus'] = False
8 # matplotlib画图中中文显示会有问题，需要这两行设置默认字体
9
10 plt.xlabel('n')
11 plt.ylabel('Time/ns')
12 plt.xlim(xmax=30, xmin=5)
13 plt.ylim(ymax=50, ymin=5)
14 # 画两条（0-9）的坐标轴并设置轴标签x，y
15 data1 = [8.28, 10.76, 12.88, 13.2, 15.08, 15.6, 17.64, 19.0, 21.08, 20.82,
16 22.52, 24.8, 23.6, 27.86, 29.72,32.38, 32.14, 37.68, 35.6, 36.44,
17 35.96, 38.6, 39.52, 40.7, 42.74, 44.52]
18 data2 = [9.7, 11.8, 13.48, 15.78, 15.36, 17.84, 18.64, 19.76, 21.96, 22.42,
19 24.48, 31.08, 29.8, 31.26, 32.8, 36.24, 35.46, 39.0, 35.58, 41.64,
20 41.42, 42.44, 44.46, 45.22, 46.06, 47.44]
21 plt.title("约瑟夫问题的两种解法时间分析")
22
23 x1 = np.arange(5,31,1)
24 y1 = np.array(data1)
25 y2 = np.array(data2)
26 #线性拟合
27 p1 = np.polyfit(x1,y1,1)
28 ry1 = np.polyval(p1,x1)
29 p2 = np.polyfit(x1,y2,1)
30 ry2 = np.polyval(p2,x1)
31
32 colors1 = '#fab1a0' # 点的颜色
33 colors2 = '#0984e3'
34 area = np.pi * 4 ** 2 # 点面积
35 # 画散点图
36 plt.plot(x1,ry1,colors1,label='数组_拟合曲线')
37 plt.plot(x1,ry2,colors2,label ='链表_拟合曲线')
38 plt.scatter(x1, y1, s=area, c=colors1, alpha=0.8, label='循环数组')
39 plt.scatter(x1, y2, s=area, c=colors2, alpha=0.8, label='循环链表')
40 #plt.plot([5, 30], [8.9, 46], linewidth='1', color='#000000')
41 plt.legend()
42 #plt.grid('True')
43 plt.savefig('1.png', dpi=300)
44 plt.show()
45 '''
46 df = pd.DataFrame(columns=['人数n'],data = x1)
47 df['CArray_time'] = data1
48 df['CList_time'] = data2
49 print(df)
50 print('')
51 print(df.corr('pearson'))
52 '''
