设置 X 轴限制后填充绘图之间的区域

Question

当我在同一个图表上绘制两条曲线时，我很难设置 X 轴的特定限制。

我的数据有两条曲线（PERMEABILITY 和 POROSITY），DEPTH 将像索引一样工作。所以我设法将它们绘制在同一张图上，并在一些帮助下填充它们之间的区域。这是我的代码：

df = pd.DataFrame({'DEPTH': [100, 150, 200, 250, 300, 350, 400, 450, 500, 550],
       'PERMEABILITY': [1000, 800, 900, 600, 200, 250, 400, 300, 100, 200],
       'POROSITY': [0.30, 0.25, 0.15, 0.19, 0.15, 0.10, 0.15, 0.19, 0.10, 0.15]})

f, ax1 = plt.subplots()

ax1.set_xlabel('PERMEABILITY') 
ax1.set_ylabel('DEPTH')
ax1.set_ylim(df['DEPTH'].max(), df['DEPTH'].min())

ax1.plot(df['PERMEABILITY'], df['DEPTH'], color='red')
ax1.tick_params(axis='x', labelcolor='red')

ax2 = ax1.twiny()

ax2.set_xlabel('POROSITY')
ax2.plot(df['POROSITY'], df['DEPTH'], color='blue')
ax2.tick_params(axis='x', labelcolor='blue')

# convert POROSITY axis to PERMEABILITY
# value-min / range -> normalized POROSITY (normp)
# normp*newrange + newmin -> stretched POROSITY to PERMEABILITY
z=df['POROSITY']
x=df['PERMEABILITY']
nz=((z-np.min(z))/(np.max(z)-np.min(z)))*(np.max(x)-np.min(x))+np.min(x)

# fill between in green where PERMEABILITY is larger
ax1.fill_betweenx(df['DEPTH'],x,nz,where=x>=nz,interpolate=True,color='g')
# fill between in yellow where POROSITY is larger
ax1.fill_betweenx(df['DEPTH'],x,nz,where=x<=nz,interpolate=True,color='y')
plt.show()

但是，当我尝试为 X 轴设置特定限制时，该填充区域不遵循新的“曲线大小”，如下左图所示。我的结果应该像右边的图像（我在 Paint 上做了这个）。例如，如果我添加：

ax1.set_xlim(0, 1500)
ax2.set_xlim(-0.10, 0.45)

有人可以帮我解决这个问题吗？提前致谢！

Answer 1

您对nz 的计算在两个 x 轴刻度之间转换。当您将两个比例更改不同的数量时，您必须更改nz 的计算。你需要弄清楚如何精确地做到这一点，但在这里我只是观察斜率并偏移直到它匹配。

import pandas as pd
import matplotlib.pyplot as plt
import numpy as np

df = pd.DataFrame({'DEPTH': [100, 150, 200, 250, 300, 350, 400, 450, 500, 550],
       'PERMEABILITY': [1000, 800, 900, 600, 200, 250, 400, 300, 100, 200],
       'POROSITY': [0.30, 0.25, 0.15, 0.19, 0.15, 0.10, 0.15, 0.19, 0.10, 0.15]})

f, ax1 = plt.subplots()

ax1.set_xlabel('PERMEABILITY') 
ax1.set_ylabel('DEPTH')
ax1.set_ylim(df['DEPTH'].max(), df['DEPTH'].min())

ax1.plot(df['PERMEABILITY'], df['DEPTH'], color='red')
ax1.tick_params(axis='x', labelcolor='red')

ax2 = ax1.twiny()

ax2.set_xlabel('POROSITY')
ax2.plot(df['POROSITY'], df['DEPTH'], color='blue')
ax2.tick_params(axis='x', labelcolor='blue')

# convert POROSITY axis to PERMEABILITY
# value-min / range -> normalized POROSITY (normp)
# normp*newrange + newmin -> stretched POROSITY to PERMEABILITY
z=df['POROSITY']
x=df['PERMEABILITY']
nz=((z-np.min(z))/(np.max(z)-np.min(z)))*(np.max(x)-np.min(x))*0.6+np.min(x)+450
#                                                          slope ^      offset ^

ax1.set_xlim(0, 1500)
ax2.set_xlim(-0.10, 0.45)
# fill between in green where PERMEABILITY is larger
ax1.fill_betweenx(df['DEPTH'],x,nz,where=x>=nz,interpolate=True,color='g')
# fill between in yellow where POROSITY is larger
ax1.fill_betweenx(df['DEPTH'],x,nz,where=x<=nz,interpolate=True,color='y')
plt.show()

此外，如果您在代码 sn-p 中包含所有必要的导入，则更容易回答您的问题。