Adding image to legend in matplotlib returns error: AttributeError: 'BarContainer' object has no attribute '_transform'

Question

Given the following code:

import numpy as np
import matplotlib.pyplot as plt
import os, sys

labels = ['G1', 'G2', 'G3', 'G4', 'G5']
men_means = [20, 34, 30, 35, 27]
women_means = [25, 32, 34, 20, 25]

x = np.arange(len(labels))  # the label locations
width = 0.35

fig, ax = plt.subplots()
rects1 = ax.bar(x - width/2, men_means, width, label='Men')
rects2 = ax.bar(x + width/2, women_means, width, label='Women')

# Add some text for labels, title and custom x-axis tick labels, etc.
ax.set_ylabel('Scores')
ax.set_title('Scores by group and gender')
ax.set_xticks(x)
ax.legend() # oringinal legend

ax.bar_label(rects1, padding=3)
ax.bar_label(rects2, padding=3)
fig.tight_layout()
plt.savefig('bar.png')

which returns this barplot:

I'd like to replace the legend ['Men', 'Women'] with emojis of and which are saved in my directory from emojipedia.

To do so, I have the following class ImageHandler added to my script, taken from here:

from matplotlib.transforms import Bbox, TransformedBbox
from matplotlib.legend_handler import HandlerBase
from matplotlib.image import BboxImage

class ImageHandler(HandlerBase):
    def create_artists(self, legend, orig_handle, Xd_, Yd_, W_, H_, fontsize, trans):
        # enlarge the image by these margins
        sx, sy = self.image_stretch 

        # create a bounding box to house the image
        bb = Bbox.from_bounds(Xd_ - sx, Yd_ - sy, W_ + sx, H_ + sy )
        tbb = TransformedBbox(bb, trans)
        image = BboxImage(tbb)
        image.set_data(self.image_data)
        self.update_prop(image, orig_handle, legend)
        return [image]

    def set_image(self, image_path, image_stretch=(0, 0)):
        self.image_data = plt.imread(image_path)
        self.image_stretch = image_stretch
 

Therefore, I replace ax.legend() with:

emoji_dataset = os.path.join( os.environ['HOME'], 'Datasets', 'Emojis')
h1 = ImageHandler()
h2 = ImageHandler()

h1.set_image(os.path.join(emoji_dataset, 'man.png'), image_stretch=(0, 20))
h2.set_image(os.path.join(emoji_dataset, 'woman.png'), image_stretch=(0, 20))

ax.legend(  handler_map={rects1: h1, rects2: h2}, 
                        handlelength=2, labelspacing=0.0, 
                        fontsize=36, borderpad=0.15, loc='best', 
                        handletextpad=0.2, borderaxespad=0.15)

However, I get the following error:

Traceback (most recent call last):
  File "img_in_legend.py", line 117, in <module>
    handletextpad=0.2, borderaxespad=0.15)
  File "/home/xenial/anaconda3/envs/py37/lib/python3.7/site-packages/matplotlib/pyplot.py", line 2886, in legend
    return gca().legend(*args, **kwargs)
  File "/home/xenial/anaconda3/envs/py37/lib/python3.7/site-packages/matplotlib/axes/_axes.py", line 290, in legend
    self.legend_ = mlegend.Legend(self, handles, labels, **kwargs)
  File "/home/xenial/anaconda3/envs/py37/lib/python3.7/site-packages/matplotlib/legend.py", line 503, in __init__
    self._init_legend_box(handles, labels, markerfirst)
  File "/home/xenial/anaconda3/envs/py37/lib/python3.7/site-packages/matplotlib/legend.py", line 767, in _init_legend_box
    fontsize, handlebox))
  File "/home/xenial/anaconda3/envs/py37/lib/python3.7/site-packages/matplotlib/legend_handler.py", line 117, in legend_artist
    fontsize, handlebox.get_transform())
  File "img_in_legend.py", line 48, in create_artists
    self.update_prop(image, orig_handle, legend)
  File "/home/xenial/anaconda3/envs/py37/lib/python3.7/site-packages/matplotlib/legend_handler.py", line 74, in update_prop
    self._update_prop(legend_handle, orig_handle)
  File "/home/xenial/anaconda3/envs/py37/lib/python3.7/site-packages/matplotlib/legend_handler.py", line 65, in _update_prop
    self._default_update_prop(legend_handle, orig_handle)
  File "/home/xenial/anaconda3/envs/py37/lib/python3.7/site-packages/matplotlib/legend_handler.py", line 70, in _default_update_prop
    legend_handle.update_from(orig_handle)
  File "/home/xenial/anaconda3/envs/py37/lib/python3.7/site-packages/matplotlib/artist.py", line 1133, in update_from
    self._transform = other._transform
AttributeError: 'BarContainer' object has no attribute '_transform'

It seems that class ImageHandler does not work with ax.bar() in my sample example.

How could I add images to legend of barplot in matplotlib?

Cheers,

Answer 1

It looks like you are right and that ImageHandler doesn't work with ax.bar(). A very hacky workaround would be to create two placeholder line2d objects in order to use the HandlerLineImage code form Trenton McKinney's link. You can define them with:

line1, = ax.plot([],[],label='men',color='tab:blue',lw=15)
line2, = ax.plot([],[],label='women',color='tab:orange',lw=15)

[],[] ensures that nothing gets plotted on top of your bar chart.

Overall, the code looks like that:

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
import numpy as np
import os, sys

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)
labels = ['G1', 'G2', 'G3', 'G4', 'G5']
men_means = [20, 34, 30, 35, 27]
women_means = [25, 32, 34, 20, 25]

x = np.arange(len(labels))  # the label locations
width = 0.35

fig, ax = plt.subplots()
rects1 = ax.bar(x - width/2, men_means, width,color='tab:blue')
rects2 = ax.bar(x + width/2, women_means, width,color='tab:orange')
line1, = ax.plot([],[],label='men',color='tab:blue',lw=15)
line2, = ax.plot([],[],label='women',color='tab:orange',lw=15)

# Add some text for labels, title and custom x-axis tick labels, etc.
ax.set_ylabel('Scores')
ax.set_title('Scores by group and gender')
ax.set_xticks(x)
ax.legend() # oringinal legend

ax.bar_label(rects1, padding=3)
ax.bar_label(rects2, padding=3)

fig.tight_layout()

leg=plt.legend([line1, line2], ["", ""],
    handler_map={line1: HandlerLineImage("man.png"), line2: HandlerLineImage("woman.png")}, 
    handlelength=2, labelspacing=0.0, fontsize=36, borderpad=0.15, loc=2, 
    handletextpad=0.2, borderaxespad=0.15)

plt.show()

And the output of this code gives: