有matplotlib等价于MATLAB的datacursormode吗？

Question

在MATLAB中，当用户鼠标悬停时，可以使用datacursormode为图形添加注释。 matplotlib中有这样的东西吗？或者我需要使用matplotlib.text.Annotation写我自己的活动？

Answer 1

延迟编辑/无耻插件：这是现在可用（功能更多）作为mpldatacursor。调用mpldatacursor.datacursor()将为所有matplotlib艺术家启用它（包括基本支持图像中的z值等）。

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据我所知，没有一个已经实现，但它不是太难写类似的东西：因为它看起来至少

import matplotlib.pyplot as plt 

class DataCursor(object): 
    text_template = 'x: %0.2f\ny: %0.2f' 
    x, y = 0.0, 0.0 
    xoffset, yoffset = -20, 20 
    text_template = 'x: %0.2f\ny: %0.2f' 

    def __init__(self, ax): 
     self.ax = ax 
     self.annotation = ax.annotate(self.text_template, 
       xy=(self.x, self.y), xytext=(self.xoffset, self.yoffset), 
       textcoords='offset points', ha='right', va='bottom', 
       bbox=dict(boxstyle='round,pad=0.5', fc='yellow', alpha=0.5), 
       arrowprops=dict(arrowstyle='->', connectionstyle='arc3,rad=0') 
       ) 
     self.annotation.set_visible(False) 

    def __call__(self, event): 
     self.event = event 
     # xdata, ydata = event.artist.get_data() 
     # self.x, self.y = xdata[event.ind], ydata[event.ind] 
     self.x, self.y = event.mouseevent.xdata, event.mouseevent.ydata 
     if self.x is not None: 
      self.annotation.xy = self.x, self.y 
      self.annotation.set_text(self.text_template % (self.x, self.y)) 
      self.annotation.set_visible(True) 
      event.canvas.draw() 

fig = plt.figure() 
line, = plt.plot(range(10), 'ro-') 
fig.canvas.mpl_connect('pick_event', DataCursor(plt.gca())) 
line.set_picker(5) # Tolerance in points 

很少有人使用它，我在下面添加了更新版本。

新版本有一个更简单的用法和更多的文档（即至少一点点）。

基本上你会用它与此类似：

plt.figure() 
plt.subplot(2,1,1) 
line1, = plt.plot(range(10), 'ro-') 
plt.subplot(2,1,2) 
line2, = plt.plot(range(10), 'bo-') 

DataCursor([line1, line2]) 

plt.show() 

主要的区别在于：a）没有必要手动调用line.set_picker(...)，B）没有必要手动调用fig.canvas.mpl_connect，以及c）本版本处理多个轴和多个数字。

from matplotlib import cbook 

class DataCursor(object): 
    """A simple data cursor widget that displays the x,y location of a 
    matplotlib artist when it is selected.""" 
    def __init__(self, artists, tolerance=5, offsets=(-20, 20), 
       template='x: %0.2f\ny: %0.2f', display_all=False): 
     """Create the data cursor and connect it to the relevant figure. 
     "artists" is the matplotlib artist or sequence of artists that will be 
      selected. 
     "tolerance" is the radius (in points) that the mouse click must be 
      within to select the artist. 
     "offsets" is a tuple of (x,y) offsets in points from the selected 
      point to the displayed annotation box 
     "template" is the format string to be used. Note: For compatibility 
      with older versions of python, this uses the old-style (%) 
      formatting specification. 
     "display_all" controls whether more than one annotation box will 
      be shown if there are multiple axes. Only one will be shown 
      per-axis, regardless. 
     """ 
     self.template = template 
     self.offsets = offsets 
     self.display_all = display_all 
     if not cbook.iterable(artists): 
      artists = [artists] 
     self.artists = artists 
     self.axes = tuple(set(art.axes for art in self.artists)) 
     self.figures = tuple(set(ax.figure for ax in self.axes)) 

     self.annotations = {} 
     for ax in self.axes: 
      self.annotations[ax] = self.annotate(ax) 

     for artist in self.artists: 
      artist.set_picker(tolerance) 
     for fig in self.figures: 
      fig.canvas.mpl_connect('pick_event', self) 

    def annotate(self, ax): 
     """Draws and hides the annotation box for the given axis "ax".""" 
     annotation = ax.annotate(self.template, xy=(0, 0), ha='right', 
       xytext=self.offsets, textcoords='offset points', va='bottom', 
       bbox=dict(boxstyle='round,pad=0.5', fc='yellow', alpha=0.5), 
       arrowprops=dict(arrowstyle='->', connectionstyle='arc3,rad=0') 
       ) 
     annotation.set_visible(False) 
     return annotation 

    def __call__(self, event): 
     """Intended to be called through "mpl_connect".""" 
     # Rather than trying to interpolate, just display the clicked coords 
     # This will only be called if it's within "tolerance", anyway. 
     x, y = event.mouseevent.xdata, event.mouseevent.ydata 
     annotation = self.annotations[event.artist.axes] 
     if x is not None: 
      if not self.display_all: 
       # Hide any other annotation boxes... 
       for ann in self.annotations.values(): 
        ann.set_visible(False) 
      # Update the annotation in the current axis.. 
      annotation.xy = x, y 
      annotation.set_text(self.template % (x, y)) 
      annotation.set_visible(True) 
      event.canvas.draw() 

if __name__ == '__main__': 
    import matplotlib.pyplot as plt 
    plt.figure() 
    plt.subplot(2,1,1) 
    line1, = plt.plot(range(10), 'ro-') 
    plt.subplot(2,1,2) 
    line2, = plt.plot(range(10), 'bo-') 

    DataCursor([line1, line2]) 

    plt.show()