是否有与 MATLAB 的 datacursormode 等效的 matplotlib？

Question

在 MATLAB 中，当用户将鼠标悬停在图形上时，可以使用 datacursormode 向图形添加注释。 matplotlib中有这样的东西吗？或者我需要使用matplotlib.text.Annotation 编写自己的事件？

Answer 1

后期编辑/无耻插件：现在可以使用mpldatacursor（具有更多功能）。调用 mpldatacursor.datacursor() 将为所有 matplotlib 艺术家启用它（包括对图像中 z 值的基本支持等）。

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据我所知，目前还没有实现，但编写类似的东西并不难：

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

似乎至少有几个人在使用它，所以我在下面添加了一个更新版本。

新版本的用法更简单，文档也更多（即，至少一点点）。

基本上你会像这样使用它：

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()

主要区别是 a) 不需要手动调用line.set_picker(...)，b) 不需要手动调用fig.canvas.mpl_connect，c) 这个版本可以处理多轴多图形。

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()