套索演示

使用套索选择一组点，并获取所选点的索引。回调用于更改所选点的颜色。

注意

此示例演示了 Matplotlib 的交互功能，这在静态文档中不会出现。请在您的机器上运行此代码以查看交互性。

您可以复制和粘贴各个部分，或使用页面底部的链接下载整个示例。

import matplotlib.pyplot as plt
import numpy as np

from matplotlib import colors as mcolors
from matplotlib import path
from matplotlib.collections import RegularPolyCollection
from matplotlib.widgets import Lasso


class LassoManager:
    def __init__(self, ax, data):
        # The information of whether a point has been selected or not is stored in the
        # collection's array (0 = out, 1 = in), which then gets colormapped to blue
        # (out) and red (in).
        self.collection = RegularPolyCollection(
            6, sizes=(100,), offset_transform=ax.transData,
            offsets=data, array=np.zeros(len(data)),
            clim=(0, 1), cmap=mcolors.ListedColormap(["tab:blue", "tab:red"]))
        ax.add_collection(self.collection)
        canvas = ax.figure.canvas
        canvas.mpl_connect('button_press_event', self.on_press)
        canvas.mpl_connect('button_release_event', self.on_release)

    def callback(self, verts):
        data = self.collection.get_offsets()
        self.collection.set_array(path.Path(verts).contains_points(data))
        canvas = self.collection.figure.canvas
        canvas.draw_idle()
        del self.lasso

    def on_press(self, event):
        canvas = self.collection.figure.canvas
        if event.inaxes is not self.collection.axes or canvas.widgetlock.locked():
            return
        self.lasso = Lasso(event.inaxes, (event.xdata, event.ydata), self.callback)
        canvas.widgetlock(self.lasso)  # acquire a lock on the widget drawing

    def on_release(self, event):
        canvas = self.collection.figure.canvas
        if hasattr(self, 'lasso') and canvas.widgetlock.isowner(self.lasso):
            canvas.widgetlock.release(self.lasso)


if __name__ == '__main__':
    np.random.seed(19680801)
    ax = plt.figure().add_subplot(
        xlim=(0, 1), ylim=(0, 1), title='Lasso points using left mouse button')
    manager = LassoManager(ax, np.random.rand(100, 2))
    plt.show()