套索示範

使用套索選取一組點，並取得選取點的索引。回呼用於變更選取點的顏色。

注意事項

此範例練習 Matplotlib 的互動功能，這不會出現在靜態文件中。請在您的機器上執行此程式碼以查看互動性。

您可以複製和貼上個別部分，或使用頁面底部的連結下載整個範例。

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()