问题描述
当我单击 Basemap Matplotlib Plot 中的一个点时,我目前正在使用此代码在地图上弹出注释.
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?
What I am wondering, is how to show the annotations using mouse hover rather than clicking on a point?
我见过motion_notify_event",但是当我在绘图区域周围移动鼠标时,代码似乎出错了.有什么想法吗?
I have seen "motion_notify_event" but it seems the code gets errors when i move the mouse around the plot area. Any Thoughts?
推荐答案
看看this question 和 demo:
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()