Python code to plot dim-time relation of four sorting algorithms using matplotlib

plot-dim-time-relateion.py

import matplotlib.pyplot as plt
plt.rc('font',family='Times New Roman') # 使用Times New Roman

# 定义标题和坐标
titles = ['Selection sort', 'Insertion sort', 'Bubble sort', 'Quick sort']
x_ticks = [10, 100, 1000, 10000, 100000]
x_labels = ['10', '100', '1k', '10k', '100k']

# 填充数据
data_avg = {
    "selection": [1,2,3,4,5],
    "insertion": [1,2,3,4,5],
    "bubble": [1,2,3,4,5],
    "quick": [1,2,3,4,5],
}

data_min = {
    "selection": [1,1,1,1,1],
    "insertion": [1,1,1,1,1],
    "bubble": [1,1,1,1,1],
    "quick": [1,1,1,1,1],
}

# 创建图像，绘制子图
fig = plt.figure(figsize=(10, 10), dpi=150)

ax = fig.add_subplot(221)
plt.plot(x_ticks, data_avg['selection'], marker='o', color="blue",label="average")
plt.plot(x_ticks, data_min['selection'], marker='o',linestyle='dashed', color="blue",label="min")

ax.set_xlabel('dim', fontsize=20)
ax.set_ylabel('$t_{avg}$', fontsize=12)
ax.set_xticks(x_ticks)
ax.set_xscale('log') 
ax.set_title(titles[0], fontsize=20)
plt.legend()
plt.grid('on')

ax = fig.add_subplot(222)
plt.plot(x_ticks, data_avg['insertion'], marker='o', color="blue",label="average")
plt.plot(x_ticks, data_min['insertion'], marker='o',linestyle='dashed', color="blue",label="min")
ax.set_xlabel('dim', fontsize=20)
ax.set_ylabel('$t_{avg}$', fontsize=12)
ax.set_xticks(x_ticks)
ax.set_xscale('log') 
ax.set_title(titles[1], fontsize=20)
plt.legend()
plt.grid('on')

ax = fig.add_subplot(223)
plt.plot(x_ticks, data_avg['bubble'], marker='o', color="blue",label="average")
plt.plot(x_ticks, data_min['bubble'], marker='o',linestyle='dashed', color="blue",label="min")
ax.set_xlabel('dim', fontsize=20)
ax.set_ylabel('$t_{avg}$', fontsize=12)
ax.set_xticks(x_ticks)
ax.set_xscale('log') 
ax.set_title(titles[2], fontsize=20)
plt.legend()
plt.grid('on')

ax = fig.add_subplot(224)
plt.plot(x_ticks, data_avg['quick'], marker='o', color="blue",label="average")
plt.plot(x_ticks, data_min['quick'], marker='o',linestyle='dashed', color="blue",label="min")
ax.set_xlabel('dim', fontsize=20)
ax.set_ylabel('$t_{avg}$', fontsize=12)
ax.set_xticks(x_ticks)
ax.set_xscale('log') 
ax.set_title(titles[3], fontsize=20)
plt.legend()
plt.grid('on')

plt.tight_layout(pad=0.4, w_pad=1, h_pad=1.0)
plt.savefig("compare.png") # 位图格式
plt.savefig("compare.svg") # 矢量格式
plt.show()