Importing an svg file into a matplotlib figure

Question

I like to produce high quality plots and therefore avoid rasterized graphics as much as possible.

I am trying to import an svg file on to a matplotlib figure:

import matplotlib.pyplot as plt earth   = plt.imread('./gfx/earth.svg') fig, ax = plt.subplots() im      = ax.imshow(earth) plt.show() 

This works with png perfectly. Can somebody tell me how to do it with svg or at least point my to proper documentation.

I know that a similar question has been asked (but not answered): here. Has anything changed since?

P.S. I know that I could just export a high resolution png and achieve a similar effect. This is not the solution I am looking for.

Here is the image I would like to import:

.

Answer 1

Maybe what you are looking for is svgutils

import svgutils.compose as sc from IPython.display import SVG # /!\ note the 'SVG' function also in svgutils.compose import numpy as np  # drawing a random figure on top of your SVG fig, ax = plt.subplots(1, figsize=(4,4)) ax.plot(np.sin(np.linspace(0,2.*np.pi)), np.cos(np.linspace(0,2.*np.pi)), 'k--', lw=2.) ax.plot(np.random.randn(20)*.3, np.random.randn(20)*.3, 'ro', label='random sampling') ax.legend() ax2 = plt.axes([.2, .2, .2, .2]) ax2.bar([0,1], [70,30]) plt.xticks([0.5,1.5], ['water  ', ' ground']) plt.yticks([0,50]) plt.title('ratio (%)') fig.savefig('cover.svg', transparent=True) # here starts the assembling using svgutils  sc.Figure("8cm", "8cm",      sc.Panel(sc.SVG("./Worldmap_northern.svg").scale(0.405).move(36,29)),     sc.Panel(sc.SVG("cover.svg"))     ).save("compose.svg") SVG('compose.svg') 

Output:

Answer 2

to anyone ending up here in 2021...

I'd suggest having a look at the cairosvg package
(conda install -c conda-forge cairosvg)

https://cairosvg.org/

import cairosvg import matplotlib.pyplot as plt from PIL import Image from io import BytesIO  img = cairosvg.svg2png("... the content of the svg file ...") img = Image.open(BytesIO(img_png)) plt.imshow(img)