cursor tracking using matplotlib and twinx

Question

I would like to track the coordinates of the mouse with respect to data coordinates on two axes simultaneously. I can track the mouse position with respect to one a

Answer 1

You can track both axis coordinates with one cursor (or event handler) this way:

import numpy as np
import matplotlib.pyplot as plt
import logging
logger = logging.getLogger(__name__)

class Cursor(object):
    def __init__(self):
        plt.connect('motion_notify_event', self)

    def __call__(self, event):
        if event.inaxes is None:
            return
        x, y1 = ax1.transData.inverted().transform((event.x,event.y))
        x, y2 = ax2.transData.inverted().transform((event.x,event.y))
        logger.debug('(x,y1,y2)=({x:0.2f}, {y1:0.2f}, {y2:0.2f})'.format(x=x,y1=y1,y2=y2))

logging.basicConfig(level=logging.DEBUG,
                    format='%(message)s',)
fig, ax1 = plt.subplots()

x = np.linspace(1000, 2000, 500)
y = 100*np.sin(20*np.pi*(x-1500)/2000.0)
fern = Cursor()
ax1.plot(x,y)
ax2 = ax1.twinx()
z = x/200.0
ax2.plot(x,z)
plt.show()

(I got "too many indices" when I used ax2.semilogy(x,z) like the OP, but didn't work through that problem.)

The ax1.transData.inverted().transform((event.x,event.y)) code performs a transform from display to data coordinates on the specified axis and can be used with either axis at will.

Answer 2

Due to the way that the call backs work, the event always returns in the top axes. You just need a bit of logic to check which if the event happens in the axes we want:

class Cursor(object):
    def __init__(self, ax, x, y, name):
        self.ax = ax
        self.name = name
        plt.connect('motion_notify_event', self)

    def __call__(self, event):
        if event.inaxes is None:
            return
        ax = self.ax
        if ax != event.inaxes:
            inv = ax.transData.inverted()
            x, y = inv.transform(np.array((event.x, event.y)).reshape(1, 2)).ravel()
        elif ax == event.inaxes:
            x, y = event.xdata, event.ydata
        else:
            return
        logger.debug('{n}: ({x:0.2f}, {y:0.2f})'.format(n=self.name,x=x,y=y))

This might be a subtle bug down in the transform stack (or this is the correct usage and it was by luck it worked with tuples before), but at any rate, this will make it work. The issue is that the code at line 1996 in transform.py expects to get a 2D ndarray back, but the identity transform just returns the tuple that get handed into it, which is what generates the errors.