src/alpaca_eval/plotting.py [185:220]:
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    plt.show()
    return g


def plot_quality_vs_price(
    evaluator_leaderboard: pd.DataFrame, min_agreement: float = 0.55, config_kwargs=None, **preprocess_kwargs
):
    config_kwargs = config_kwargs or dict()
    df_all = _preprocess_evaluator_leaderboard(evaluator_leaderboard, min_agreement=min_agreement, **preprocess_kwargs)

    with plot_config(**config_kwargs):
        g = sns.relplot(
            data=df_all,
            x="Price [$/1000 examples]",
            y="Human agreement",
            kind="scatter",
            hue="Annotator",
            s=300,
            alpha=0.9,
            legend="full",
            aspect=1.3,
        )

        axes = g.axes.flatten()

        axes[0].yaxis.set_major_locator(plt.MaxNLocator(4))

        g.set_titles("")
        axes[0].set_xscale("symlog", linthresh=1)
        axes[0].set_xlim([-0.02, 400])
        axes[0].xaxis.set_minor_locator(LogLocator(base=10, subs=range(10)))

        sns.move_legend(g, "center right", bbox_to_anchor=(1.05, 0.6))

    plt.show()
    return g
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src/alpaca_eval/plotting.py [219:254]:
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    plt.show()
    return g


def plot_quality_vs_price(
    evaluator_leaderboard: pd.DataFrame, min_agreement: float = 0.55, config_kwargs=None, **preprocess_kwargs
):
    config_kwargs = config_kwargs or dict()
    df_all = _preprocess_evaluator_leaderboard(evaluator_leaderboard, min_agreement=min_agreement, **preprocess_kwargs)

    with plot_config(**config_kwargs):
        g = sns.relplot(
            data=df_all,
            x="Price [$/1000 examples]",
            y="Human agreement",
            kind="scatter",
            hue="Annotator",
            s=300,
            alpha=0.9,
            legend="full",
            aspect=1.3,
        )

        axes = g.axes.flatten()

        axes[0].yaxis.set_major_locator(plt.MaxNLocator(4))

        g.set_titles("")
        axes[0].set_xscale("symlog", linthresh=1)
        axes[0].set_xlim([-0.02, 400])
        axes[0].xaxis.set_minor_locator(LogLocator(base=10, subs=range(10)))

        sns.move_legend(g, "center right", bbox_to_anchor=(1.05, 0.6))

    plt.show()
    return g
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