Lasso 演示

使用套索选择一组点并获取所选点的索引。使用回调函数来改变所选点的颜色。

备注

这个例子展示了 Matplotlib 的交互能力，这在静态文档中不会出现。请在你的机器上运行此代码以查看交互效果。

您可以复制并粘贴单个部分，或者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()