标准化轴以具有平方图

Question

考虑以下系列

lift = {}
lift['correct']=[0.0, 10.0, 18.0, 34.0, 44.0, 58.0, 66.0, 76.0, 84.0, 86.0, 88.0, 92.0, 92.0, 94.0, 98.0, 98.0, 100.0, 100.0, 100.0, 100.0, 100.0]
lift['avg'] = [0.0, 5.0, 10.0, 15.0, 20.0, 25.0, 30.0, 35.0, 40.0, 45.0, 50.0, 55.0, 60.0, 65.0, 70.0, 75.0, 80.0, 85.0, 90.0, 95.0, 100.0]

fig, ax = plt.subplots()
fig.canvas.draw()

handles = []
handles.append(ax.plot(lift['correct'], 'r-', label='Percent Correct'))
handles.append(ax.plot(lift['avg'], 'b-', label='Average Case'))
ax.set_xlabel('Total Population (%)')
ax.set_ylabel('Number of Respondents (%)')
ax.set_ylim([0, 100])

num_xticks = 20
xtick_step = 100/num_xticks
ax.set_xticks([int(v) for v in range(0,num_xticks+1)])
ax.set_xticklabels([int(v*xtick_step) for v in range(0,num_xticks+1)])
#question 1
#ax.set_xlim([0, 100])
#fig.gca().set_aspect('equal', adjustable='box')

#question 2
#num_yticks = 20
#ytick_step = 100/num_yticks
#ax.set_yticks([int(v) for v in range(0,num_yticks+1)])
#ax.set_yticklabels([int(v*ytick_step) for v in 
#   range(0,num_yticks+1)])
fig.legend(handles, labels=[h[0].get_label() for h in handles])
fig.show()

我得到的是

我想将2个轴归一化，以使绘图在两个轴上都像这样平方 我尝试了Q1评论行并得到

问题1.如何正确获得平方轴？

问题2。如何以类似x轴的刻度线间隔y轴，让我们说第10步或第5步。我尝试了Q2注释行并得到了

问题fig.legend(handles, labels=[h[0].get_label() for h in handles])没有显示任何图例！

问题4.欢迎使用任何替代且更简单的方法来获得期望的结果。 我遵循了在线示例，并认为我当前的方法不是那么直观，特别是从分为fig和ax

Answer 1

在针对y绘制x时，不要忘记提供x。

import matplotlib.pyplot as plt

lift = {}
lift['correct']=[0.0, 10.0, 18.0, 34.0, 44.0, 58.0, 66.0, 76.0, 84.0, 86.0, 88.0, 92.0, 92.0, 94.0, 98.0, 98.0, 100.0, 100.0, 100.0, 100.0, 100.0]
lift['avg'] = [0.0, 5.0, 10.0, 15.0, 20.0, 25.0, 30.0, 35.0, 40.0, 45.0, 50.0, 55.0, 60.0, 65.0, 70.0, 75.0, 80.0, 85.0, 90.0, 95.0, 100.0]

fig, ax = plt.subplots()

ax.plot(lift['avg'], lift['correct'], 'r-', label='Percent Correct')
ax.plot(lift['avg'], lift['avg'],  'b-', label='Average Case')
ax.set_xlabel('Total Population (%)')
ax.set_ylabel('Number of Respondents (%)')

ax.set_aspect("equal")
ax.legend()

plt.show()