有matplotlib等價於MATLAB的datacursormode嗎？

Question

在MATLAB中，當用戶鼠標懸停時，可以使用datacursormode爲圖形添加註釋。 matplotlib中有這樣的東西嗎？或者我需要使用matplotlib.text.Annotation寫我自己的活動？

Answer 1

延遲編輯/無恥插件：這是現在可用（功能更多）作爲mpldatacursor。調用mpldatacursor.datacursor()將爲所有matplotlib藝術家啓用它（包括基本支持圖像中的z值等）。

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據我所知，沒有一個已經實現，但它不是太難寫類似的東西：因爲它看起來至少

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。

新版本有一個更簡單的用法和更多的文檔（即至少一點點）。

基本上你會用它與此類似：

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() 

主要的區別在於：a）沒有必要手動調用line.set_picker(...)，B）沒有必要手動調用fig.canvas.mpl_connect，以及c）本版本處理多個軸和多個數字。

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()