matplotlib是否与MATLAB的datacursormode等效？

Question

在MATLAB中，当用户鼠标移过时，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/无耻的插件：现在可以作为^{}使用（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，还没有一个已经实现，但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，我在下面添加了一个更新版本。

新版本有一个更简单的用法和更多的文档（至少是一点点）。

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()

主要区别在于a）不需要手动调用line.set_picker(...)，b）不需要手动调用fig.canvas.mpl_connect，以及c）此版本处理多轴和多图形。

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()