python - cursor tracking using matplotlib and twinx -

i track coordinates of mouse respect data coordinates on 2 axes simultaneously. can track mouse position respect 1 axis fine. the problem is: when add second axis twinx(), both cursors report data coordinates respect second axis only.

for example, cursors (fern , muffy) report y-value 7.93

fern: (1597.63, 7.93) muffy: (1597.63, 7.93) 

if use:

    inv = ax.transdata.inverted()     x, y = inv.transform((event.x, event.y)) 

i indexerror.

so question is: how can modify code track data coordinates respect both axes?

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import numpy np import matplotlib.pyplot plt import logging logger = logging.getlogger(__name__)  class cursor(object):     def __init__(self, ax, name):         self.ax = ax         self.name = name         plt.connect('motion_notify_event', self)      def __call__(self, event):         x, y = event.xdata, event.ydata         ax = self.ax         # inv = ax.transdata.inverted()         # x, y = inv.transform((event.x, event.y))         logger.debug('{n}: ({x:0.2f}, {y:0.2f})'.format(n=self.name,x=x,y=y))   logging.basicconfig(level=logging.debug,                     format='%(message)s',) fig, ax = plt.subplots()  x = np.linspace(1000, 2000, 500) y = 100*np.sin(20*np.pi*(x-1500)/2000.0) fern = cursor(ax, 'fern') ax.plot(x,y) ax2 = ax.twinx() z = x/200.0 muffy = cursor(ax2, 'muffy') ax2.semilogy(x,z) plt.show() 

due way call backs work, event returns in top axes. need bit of logic check if event happens in axes 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 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 subtle bug down in transform stack (or correct usage , luck worked tuples before), @ rate, make work. issue code @ line 1996 in transform.py expects 2d ndarray back, identity transform returns tuple handed it, generates errors.