How to use the nanocomp.compplots function in NanoComp

To help you get started, we’ve selected a few NanoComp examples, based on popular ways it is used in public projects.

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github wdecoster / nanocomp / nanocomp / NanoComp.py View on Github external
plot=settings["plot"],
                title=settings["title"],
                palette=settings["colors"])
        )
    if "duration" in df:
        plots.extend(
            compplots.compare_sequencing_speed(
                df=df,
                figformat=settings["format"],
                path=settings["path"],
                title=settings["title"],
                palette=settings["colors"])
        )
    if "percentIdentity" in df:
        plots.extend(
            compplots.violin_or_box_plot(
                df=df[df["percentIdentity"] > np.percentile(df["percentIdentity"], 1)],
                y="percentIdentity",
                figformat=settings["format"],
                path=settings["path"],
                y_name="Percent reference identity",
                plot=settings["plot"],
                title=settings["title"],
                palette=settings["colors"])
        )
    if "start_time" in df:
        plots.extend(
            compplots.compare_cumulative_yields(
                df=df,
                path=settings["path"],
                title=settings["title"],
                palette=settings["colors"])
github wdecoster / nanocomp / nanocomp / NanoComp.py View on Github external
def make_plots(df, settings):
    utils.plot_settings(dict(), dpi=settings["dpi"])
    df["log length"] = np.log10(df["lengths"])
    plots = []
    plots.extend(
        compplots.output_barplot(
            df=df,
            figformat=settings["format"],
            path=settings["path"],
            title=settings["title"],
            palette=settings["colors"])
    )
    plots.extend(
        compplots.n50_barplot(
            df=df,
            figformat=settings["format"],
            path=settings["path"],
            title=settings["title"],
            palette=settings["colors"])
    )
    plots.extend(
        compplots.violin_or_box_plot(