Control the mouse click event with a subplot rather than a figure in matplotlib

Question

I have a figure with 5 subplots. I am using a mouse click event to create a shaded area in the 4th and 5th subplot only (see attached pic below).

The mouse click event is triggered when I click on any of the subplots in the figure. However, I would ideally like to be able to trigger the mouse click event only when clicked on the 4th and 5th subplots. I am wondering if this is possible using mpl_connect.

Here's my code

import numpy as np
from scipy.stats import norm, lognorm, uniform
import matplotlib.pyplot as plt
from matplotlib.widgets import Slider, Button, RadioButtons, CheckButtons
from matplotlib.patches import Polygon


#####Mean and standard deviation#####

mu_a1 = 1
mu_b1 = 10
mu_c1 = -13
sigma_a1 =  0.14
sigma_b1 =  1.16
sigma_c1 =  2.87
mu_x01 = -11
sigma_x01 =  1.9

#####_____#####



#####Generating random data#####

a1 = 0.75*mu_a1 + (1.25 - 0.75)*sigma_a1*np.random.sample(10000)
b1 = 8*mu_b1 + (12 - 8)*sigma_b1*np.random.sample(10000)
c1 = -12*mu_c1 + 2*sigma_c1*np.random.sample(10000)
x01 = (-b1 - np.sqrt(b1**2 - (4*a1*c1)))/(2*a1)

#####_____#####



#####Creating Subplots#####

fig = plt.figure()
plt.subplots_adjust(left=0.13,right=0.99,bottom=0.05)

ax1 = fig.add_subplot(331)                                                  #Subplot 1
ax1.set_xlabel('a' , fontsize = 14)
ax1.grid(True)

ax2 = fig.add_subplot(334)                                                  #Subplot 2
ax2.set_xlabel('b', fontsize = 14)
ax2.grid(True)

ax3 = fig.add_subplot(337)                                                  #Subplot 3
ax3.set_xlabel('c', fontsize = 14)
ax3.grid(True)

ax4 = fig.add_subplot(132)                                                  #Subplot 4
ax4.set_xlabel('x0', fontsize = 14)
ax4.set_ylabel('PDF', fontsize = 14)
ax4.grid(True)

ax5 = fig.add_subplot(133)                                                  #Subplot 5
ax5.set_xlabel('x0', fontsize = 14)
ax5.set_ylabel('CDF', fontsize = 14)
ax5.grid(True)

#####_____#####



#####Plotting Distributions#####

[n1,bins1,patches] = ax1.hist(a1, bins=50, color = 'red',alpha = 0.5, normed = True)
[n2,bins2,patches] = ax2.hist(b1, bins=50, color = 'red',alpha = 0.5, normed = True)
[n3,bins3,patches] = ax3.hist(c1, bins=50, color = 'red',alpha = 0.5, normed = True)
[n4,bins4,patches] = ax4.hist(x01, bins=50, color = 'red',alpha = 0.5, normed = True)
ax4.axvline(np.mean(x01), color = 'black', linestyle = 'dashed', lw = 2)
dx = bins4[1] - bins4[0]
CDF = np.cumsum(n4)*dx
ax5.plot(bins4[1:], CDF, color = 'red')

#####_____#####



#####Event handler for button_press_event#####

def enter_axes(event):
    print('enter_axes', event.inaxes)
    event.canvas.draw()

def leave_axes(event):
    print('leave_axes', event.inaxes)
    event.canvas.draw()

def onclick(event):
    '''
    Event handler for button_press_event
    @param event MouseEvent
    '''
    global ix
    ix = event.xdata
    if ix is not None:
        print 'x = %f' %(ix)

    ax4.clear()
    ax5.clear()
    ax4.grid(True)
    ax5.grid(True)
    [n4,bins4,patches] = ax4.hist(x01, bins=50, color = 'red',alpha = 0.5, normed = True)
    ax4.axvline(np.mean(x01), color = 'black', linestyle = 'dashed', lw = 2)
    xmin = ix
    xmax = ax4.get_xlim()[1]
    ax4.axvspan(xmin, xmax, facecolor='0.9', alpha=0.5)
    dx = bins4[1] - bins4[0]
    CDF = np.cumsum(n4)*dx
    ax5.plot(bins4[1:], CDF, color = 'red')
    ax5.axvspan(xmin, xmax, facecolor='0.9', alpha=0.5)
    plt.draw()
    return ix

cid = fig.canvas.mpl_connect('button_press_event', onclick)
#fig.canvas.mpl_disconnect(cid)

plt.show()

#####_____#####

Thanks in advance :-)

Answer 1

You can use the inaxes property of event to find which axes you are in. See the docs here. If you iterate through your subplot Axes, you can then compare the result of inaxes to each Axes instance, and then only go ahead with drawing the shaded region if you are in ax4 or ax5.

I've modified your onclick function to do that. For information, it also prints which axes the click was in, but you can turn that off once you satisfy yourself that it is working as planned.

def onclick(event):
    '''
    Event handler for button_press_event
    @param event MouseEvent
    '''
    global ix
    ix = event.xdata

    for i, ax in enumerate([ax1, ax2, ax3, ax4, ax5]):

        # For infomation, print which axes the click was in
        if ax == event.inaxes:
            print "Click is in axes ax{}".format(i+1)

    # Check if the click was in ax4 or ax5
    if event.inaxes in [ax4, ax5]:

        if ix is not None:
            print 'x = %f' %(ix)

        ax4.clear()
        ax5.clear()
        ax4.grid(True)
        ax5.grid(True)
        [n4,bins4,patches] = ax4.hist(x01, bins=50, color = 'red',alpha = 0.5, normed = True)
        ax4.axvline(np.mean(x01), color = 'black', linestyle = 'dashed', lw = 2)
        xmin = ix
        xmax = ax4.get_xlim()[1]
        ax4.axvspan(xmin, xmax, facecolor='0.9', alpha=0.5)
        dx = bins4[1] - bins4[0]
        CDF = np.cumsum(n4)*dx
        ax5.plot(bins4[1:], CDF, color = 'red')
        ax5.axvspan(xmin, xmax, facecolor='0.9', alpha=0.5)
        plt.draw()
        return ix

    else:
        return

Note: I took inspiration for this answer from this other SO answer.