如何从 matplotlib 中创建包含元数据的压缩可缩放矢量图形

Question

• matplotlib allows generation of svgz files, compression rate mor than 90%
• external compression of svg files with gzip -9 worse to extremely worse
• xml.etree.ElementTree allows definition of metadata to svg dataset, but export apparently only to svg, not svgz.

Is there a way in python to add metadata to the xml tree and export it to svgz at the compression rate achieved by matplotlib.pyplot.savefig(..., format='svgz') ?

Answer 1

Maybe you would like to do this

import io
from matplotlib.figure import Figure
from matplotlib.backends.backend_svg import FigureCanvasSVG

fig = Figure()
# do your fig stuffs

output = io.BytesIO()
FigureCanvasSVG(fig).print_svg(output)

Now, the SGV can be extracted as fol:

output.getvalue()

If you are looking for SGVZ (gzip compressed) try:

FigureCanvasSVG(fig).print_svgz(output)