<jupyter_start><jupyter_text>Figure 4<jupyter_code>plist = list(
    A=readRDS("panels_rds/fig_4a.rds"),
    B=readRDS("panels_rds/fig_4b.rds"),
    C=readRDS("panels_rds/fig_4c.rds"),
    D=readRDS("panels_rds/fig_4d.rds"),
    D=readRDS("panels_rds/fig_4e.rds")
)
options(repr.plot.width=12, repr.plot.height=18)
p = plot_grid(
    plist[[1]],
    plot_grid(plotlist=plist[2:5], nrow=2, ncol=2, align="hv", axis="lt", labels=letters[2:5]),
    nrow=2, rel_heights=c(1,1.8), labels=letters[1]
)
p
save_and_plot(p, "figures/fig_4", width=10, height=15, formats=c("jpg", "png", "pdf"))<jupyter_output><empty_output><jupyter_text>Figure X4<jupyter_code>plist = list(
    A=readRDS("panels_rds/supp_fig_x4a.rds"),
    B=readRDS("panels_rds/supp_fig_x4b.rds")
)
options(repr.plot.width=15, repr.plot.height=5)
p = plot_grid(plotlist=plist, ncol=2, align="hv", axis="blt", labels="auto")
p
save_and_plot(p, "figures/supp_fig_x4", width=15, height=5, formats=c("jpg", "png", "pdf"))<jupyter_output><empty_output>
{'fraction_non_alphanumeric': 0.19980119284294234, 'fraction_numerical': 0.03777335984095427, 'mean_word_length': 7.254098360655738, 'pattern_counts': {'":': 0, '<': 9, '<?xml version=': 0, '>': 9, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
{'chain_length': '2', 'dir': 'jupyter-structured-clean-dedup', 'id': '636061', 'license': 'MIT', 'n_tokens_mistral': 491, 'n_tokens_neox': 472, 'n_words': 50, 'path': 'manuscript/2.0_figures.ipynb', 'repo_name': 'ggirelli/deconwolf-in-situ-transcriptomics', 'size': '1006'}