[FIXED] How to plot fill_betweenx to fill the area between y1 and y2 with different scales using matplotlib.pyplot?

Issue

I am trying to fill the area between two vertical curves(RHOB and NPHI) using matplotlib.pyplot. Both RHOB and NPHI are having different scale of x-axis.

But when i try to plot i noticed that the fill_between is filling the area between RHOB and NPHI in the same scale.

#well_data is the data frame i am reading to get my data

#creating my subplot
fig, ax=plt.subplots(1,2,figsize=(8,6),sharey=True)
ax[0].get_xaxis().set_visible(False)
ax[0].invert_yaxis()

#subplot 1:
#ax01 to house the NPHI curve (NPHI curve are having values between 0-45)
ax01=ax[0].twiny()
ax01.set_xlim(-15,45)
ax01.invert_xaxis()
ax01.set_xlabel('NPHI',color='blue')
ax01.spines['top'].set_position(('outward',0))
ax01.tick_params(axis='x',colors='blue')
ax01.plot(well_data.NPHI,well_data.index,color='blue')

#ax02 to house the RHOB curve (RHOB curve having values between 1.95,2.95)
ax02=ax[0].twiny()
ax02.set_xlim(1.95,2.95)
ax02.set_xlabel('RHOB',color='red')
ax02.spines['top'].set_position(('outward',40))
ax02.tick_params(axis='x',colors='red')
ax02.plot(well_data.RHOB,well_data.index,color='red')


# ax03=ax[0].twiny()
# ax03.set_xlim(0,50)
# ax03.spines['top'].set_position(('outward',80))
# ax03.fill_betweenx(well_data.index,well_data.RHOB,well_data.NPHI,alpha=0.5)
plt.show() 

ax03=ax[0].twiny()
ax03.set_xlim(0,50)
ax03.spines['top'].set_position(('outward',80))
ax03.fill_betweenx(well_data.index,well_data.RHOB,well_data.NPHI,alpha=0.5)

above is the code that i tried, but the end result is not what i expected. it is filling area between RHOB and NPHI assuming RHOB and NPHI is in the same scale.

How can i fill the area between the blue and the red curve?

Solution

Since the data are on two different axes, but each artist needs to be on one axes alone, this is hard. What would need to be done here is to calculate all data in a single unit system. You might opt to transform both datasets to display-space first (meaning pixels), then plot those transformed data via fill_betweenx without transforming again (transform=None).

import numpy as np
import matplotlib.pyplot as plt


y = np.linspace(0, 22, 101)
x1 = np.sin(y)/2
x2 = np.cos(y/2)+20

fig, ax1 = plt.subplots()
ax2 = ax1.twiny()
ax1.tick_params(axis="x", colors="C0", labelcolor="C0")
ax2.tick_params(axis="x", colors="C1", labelcolor="C1")

ax1.set_xlim(-1,3)
ax2.set_xlim(15,22)

ax1.plot(x1,y, color="C0")
ax2.plot(x2,y, color="C1")

x1p, yp = ax1.transData.transform(np.c_[x1,y]).T
x2p, _ = ax2.transData.transform(np.c_[x2,y]).T
ax1.autoscale(False)
ax1.fill_betweenx(yp, x1p, x2p, color="C9", alpha=0.4, transform=None)

plt.show()

We might equally opt to transform the data from the second axes to the first. This has the advantage that it's not defined in pixel space and hence circumvents a problem that occurs when the figure size is changed after the figure is created.

x2p, _ = (ax2.transData + ax1.transData.inverted()).transform(np.c_[x2,y]).T
ax1.autoscale(False)
ax1.fill_betweenx(y, x1, x2p, color="grey", alpha=0.4)

Answered By - ImportanceOfBeingErnest