用图像替换Matplotlib图例的标签

Question

我想在图例中使用图像而不是标签.

例如,我画了2行并显示了一个图例:

import matplotlib.pyplot as plt
plt.plot([1,2],label="first_image")
plt.plot([2,1],label="second_image")
plt.legend()
plot.show()

但我希望有这样的东西:

请注意,这不是matplotlib图例中插入图像的重复,我的问题是"将标签更改为图像",而另一个是"将图例的符号更改为图像"

Answer 1

在图例中已经显示了在图例中创建图像的概念(在matplotlib图例中插入图像),其中图像用作图例条目的艺术家.

如果你想要一个线条句柄和图例中的图像,我们的想法是创建一个由两个组合在一起的句柄,彼此相邻.唯一的问题是微调参数,使其看起来很吸引人.

import matplotlib.pyplot as plt
import matplotlib.lines
from matplotlib.transforms import Bbox, TransformedBbox
from matplotlib.legend_handler import HandlerBase
from matplotlib.image import BboxImage

class HandlerLineImage(HandlerBase):

    def __init__(self, path, space=15, offset = 10 ):
        self.space=space
        self.offset=offset
        self.image_data = plt.imread(path)        
        super(HandlerLineImage, self).__init__()

    def create_artists(self, legend, orig_handle,
                       xdescent, ydescent, width, height, fontsize, trans):

        l = matplotlib.lines.Line2D([xdescent+self.offset,xdescent+(width-self.space)/3.+self.offset],
                                     [ydescent+height/2., ydescent+height/2.])
        l.update_from(orig_handle)
        l.set_clip_on(False)
        l.set_transform(trans)

        bb = Bbox.from_bounds(xdescent +(width+self.space)/3.+self.offset,
                              ydescent,
                              height*self.image_data.shape[1]/self.image_data.shape[0],
                              height)

        tbb = TransformedBbox(bb, trans)
        image = BboxImage(tbb)
        image.set_data(self.image_data)

        self.update_prop(image, orig_handle, legend)
        return [l,image]


plt.figure(figsize=(4.8,3.2))
line,  = plt.plot([1,2],[1.5,3], color="#1f66e0", lw=1.3)
line2,  = plt.plot([1,2],[1,2], color="#efe400", lw=1.3)
plt.ylabel("Flower power")

plt.legend([line, line2], ["", ""],
   handler_map={ line: HandlerLineImage("icon1.png"), line2: HandlerLineImage("icon2.png")}, 
   handlelength=2, labelspacing=0.0, fontsize=36, borderpad=0.15, loc=2, 
    handletextpad=0.2, borderaxespad=0.15)

plt.show()