2 ms·
LaTeX, LLMs and Boring Technology
- gbacon 1y agoTikZ is definitely nice. For generating vector versions of your matplotlib plots, use FigureCanvasPgf. https://matplotlib.org/stable/api/backend_pgf_api.html#matplotlib.backends.backend_pgf.FigureCanvasPgf https://matplotlib.org/stable/api/backend_pgf_api.html#matpl... In Jupyter, that looks like !sudo apt-get -y install \ texlive-xetex texlive-fonts-recommended texlive-plain-generic \ texlive-latex-extra texlive-fonts-recommended dvipng cm-super \ >/dev/null import matplotlib from matplotlib.backends.backend_pgf import FigureCanvasPgf matplotlib.backend_bases.register_backend('pdf', FigureCanvasPgf) import matplotlib.pyplot as plt from pdf2image import convert_from_path plt.rcParams.update({ 'font.family': 'serif', 'font.serif': [], 'font.size': 8, 'text.usetex': True, 'pgf.rcfonts': False, }) Using `convert_from_path` is for showing cached images. Generate your figure with plt.savefig('foo.pdf', transparent=True)