Python 和 Matplotlib 以及鼠标悬停注释

I am currently employing this code to have pop up annotatations on a map when i click on a point in a Basemap Matplotlib Plot.

dcc = DataCursor(self.figure.gca())
self.figure.canvas.mpl_connect('pick_event',dcc)
plot_handle.set_picker(5)
self.figure.canvas.draw()

class DataCursor(object):

    import matplotlib.pyplot as plt

    text_template = 'x: %0.2f
y: %0.2f' 
    x, y = 0.0, 0.0 
    xoffset, yoffset = -20 , 20
    text_template = 'A: %s
B: %s
C: %s'


    def __init__(self, ax): 
        self.ax = ax 
        self.annotation = ax.annotate(self.text_template,  
                xy=(self.x, self.y), xytext=(0,0),
                textcoords='axes fraction', ha='left', va='bottom', fontsize=10,
                bbox=dict(boxstyle='round,pad=0.5', fc='yellow', alpha=1), 
                arrowprops=dict(arrowstyle='->', connectionstyle='arc3,rad=0') 
                ) 
        self.annotation.set_visible(False)
        self.annotation.draggable()


    def __call__(self, event):

        self.event = event 
        self.x, self.y = event.mouseevent.xdata, event.mouseevent.ydata

        if self.x is not None:
            glim = pickle.load(open("ListA.py","rb"))
            tlim = pickle.load(open("ListB.py","rb"))
            vlim = pickle.load(open("ListC.py","rb"))
            a = glim[event.ind[0]] # ['Name'][event.ind[0]]
            b = tlim[event.ind[0]]
            c = vlim[event.ind[0]]
            temp_temp=self.text_template % (a, b, c)
            if temp_temp == self.annotation.get_text() and self.annotation.get_visible(): 
                self.annotation.set_visible(False) 
                event.canvas.draw() 
                return 
            self.annotation.xy = self.x, self.y
            self.annotation.set_text(self.text_template % (a, b, c))
            self.annotation.set_visible(True)

            event.canvas.draw()

我想知道的是，如何使用鼠标悬停而不是单击某个点来显示注释?

from matplotlib.pyplot import figure, show
import numpy as npy
from numpy.random import rand


if 1: # picking on a scatter plot (matplotlib.collections.RegularPolyCollection)

    x, y, c, s = rand(4, 100)
    def onpick3(event):
        ind = event.ind
        print 'onpick3 scatter:', ind, npy.take(x, ind), npy.take(y, ind)

    fig = figure()
    ax1 = fig.add_subplot(111)
    col = ax1.scatter(x, y, 100*s, c, picker=True)
    #fig.savefig('pscoll.eps')
    fig.canvas.mpl_connect('pick_event', onpick3)

show()