Amritbir Singh Gill Amritbir Singh Gill - 1 month ago 22
Python Question

How to add second x-axis at the bottom of the first one in matplotlib.?

I am refering to the question already asked here.

In this example the users have solved the second axis problem by adding it to the upper part of the graph where it coincide with the title.

Question:
Is it possible to add the second x-axis at the bottom of the first one.?

Code:

import numpy as np
import matplotlib.pyplot as plt

fig = plt.figure()
ax1 = fig.add_subplot(111)
ax2 = ax1.twiny()

X = np.linspace(0,1,1000)
Y = np.cos(X*20)

ax1.plot(X,Y)
ax1.set_xlabel(r"Original x-axis: $X$")

new_tick_locations = np.array([.2, .5, .9])

def tick_function(X):
V = 1/(1+X)
return ["%.3f" % z for z in V]

ax2.set_xticks(new_tick_locations)
ax2.set_xticklabels(tick_function(new_tick_locations))
ax2.set_xlabel(r"Modified x-axis: $1/(1+X)$")
plt.show()


Any help will be appreciated.!

tom tom
Answer

As an alternative to the answer from @DizietAsahi, you can use spines in a similar way to the matplotlib example posted here.

import numpy as np
import matplotlib.pyplot as plt

fig = plt.figure()
ax1 = fig.add_subplot(111)
ax2 = ax1.twiny()

# Add some extra space for the second axis at the bottom
fig.subplots_adjust(bottom=0.2)

X = np.linspace(0,1,1000)
Y = np.cos(X*20)

ax1.plot(X,Y)
ax1.set_xlabel(r"Original x-axis: $X$")

new_tick_locations = np.array([.2, .5, .9])

def tick_function(X):
    V = 1/(1+X)
    return ["%.3f" % z for z in V]

# Move twinned axis ticks and label from top to bottom
ax2.xaxis.set_ticks_position("bottom")
ax2.xaxis.set_label_position("bottom")

# Offset the twin axis below the host
ax2.spines["bottom"].set_position(("axes", -0.15))

# Turn on the frame for the twin axis, but then hide all 
# but the bottom spine
ax2.set_frame_on(True)
ax2.patch.set_visible(False)
for sp in ax2.spines.itervalues():
    sp.set_visible(False)
ax2.spines["bottom"].set_visible(True)

ax2.set_xticks(new_tick_locations)
ax2.set_xticklabels(tick_function(new_tick_locations))
ax2.set_xlabel(r"Modified x-axis: $1/(1+X)$")
plt.show()

enter image description here