Question or problem about Python programming:
I have a very simple question. I need to have a second x-axis on my plot and I want that this axis has a certain number of tics that correspond to certain position of the first axis.
Let’s try with an example. Here I am plotting the dark matter mass as a function of the expansion factor, defined as 1/(1+z), that ranges from 0 to 1.
semilogy(1/(1+z),mass_acc_massive,'-',label='DM') xlim(0,1) ylim(1e8,5e12)
I would like to have another x-axis, on the top of my plot, showing the corresponding z for some values of the expansion factor. Is that possible? If yes, how can I have xtics ax
How to solve the problem:
I’m taking a cue from the comments in @Dhara’s answer, it sounds like you want to set a list of
new_tick_locations by a function from the old x-axis to the new x-axis. The
tick_function below takes in a numpy array of points, maps them to a new value and formats them:
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_xlim(ax1.get_xlim()) 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()
You can use twiny to create 2 x-axis scales. For Example:
import numpy as np import matplotlib.pyplot as plt fig = plt.figure() ax1 = fig.add_subplot(111) ax2 = ax1.twiny() a = np.cos(2*np.pi*np.linspace(0, 1, 60.)) ax1.plot(range(60), a) ax2.plot(range(100), np.ones(100)) # Create a dummy plot ax2.cla() plt.show()
If You want Your upper axis to be a function of the lower axis tick-values:
import matplotlib.pyplot as plt fig, ax1 = plt.subplots() ax1 = fig.add_subplot(111) ax1.plot(range(5), range(5)) ax1.grid(True) ax2 = ax1.twiny() ax1Xs = ax1.get_xticks() ax2Xs =  for X in ax1Xs: ax2Xs.append(X * 2) ax2.set_xticks(ax1Xs) ax2.set_xbound(ax1.get_xbound()) ax2.set_xticklabels(ax2Xs) title = ax1.set_title("Upper x-axis ticks are lower x-axis ticks doubled!") title.set_y(1.1) fig.subplots_adjust(top=0.85) fig.savefig("1.png")
Answering your question in Dhara’s answer comments: “I would like on the second x-axis these tics: (7,8,99) corresponding to the x-axis position 10, 30, 40. Is that possible in some way?”
Yes, it is.
import numpy as np import matplotlib.pyplot as plt fig = plt.figure() ax1 = fig.add_subplot(111) a = np.cos(2*np.pi*np.linspace(0, 1, 60.)) ax1.plot(range(60), a) ax1.set_xlim(0, 60) ax1.set_xlabel("x") ax1.set_ylabel("y") ax2 = ax1.twiny() ax2.set_xlabel("x-transformed") ax2.set_xlim(0, 60) ax2.set_xticks([10, 30, 40]) ax2.set_xticklabels(['7','8','99']) plt.show()
From matplotlib 3.1 onwards you may use
import numpy as np import matplotlib.pyplot as plt x = np.linspace(1,13, num=301) y = (np.sin(x)+1.01)*3000 # Define function and its inverse f = lambda x: 1/(1+x) g = lambda x: 1/x-1 fig, ax = plt.subplots() ax.semilogy(x, y, label='DM') ax2 = ax.secondary_xaxis("top", functions=(f,g)) ax2.set_xlabel("1/(x+1)") ax.set_xlabel("x") plt.show()
I’m forced to post this as an answer instead of a comment due to low reputation.
I had a similar problem to Matteo. The difference being that I had no map from my first x-axis to my second x-axis, only the x-values themselves. So I wanted to set the data on my second x-axis directly, not the ticks, however, there is no
axes.set_xdata. I was able to use Dhara’s answer to do this with a modification:
ax2.lines = 
instead of using:
When in use also cleared my plot from