cb840cb2da9012a3df001889370c131e8ac96498,rankeval/visualization/effectiveness.py,,plot_query_wise_performance,#Any#Any#,291

Before Change

                axes[j].set_xlabel("Bins")
                axes[j].legend(performance.coords["model"].values)
                axes[j].yaxis.set_ticks(np.arange(0, 1, 0.1))
            plt.tight_layout()


def plot_document_graded_relevance(performance):
    for dataset in performance.coords["dataset"].values:

After Change

                axes[i, 0].legend(performance.coords["metric"].values)
                axes[i, 0].yaxis.set_ticks(np.arange(0, 1, 0.1))

        elif compare == "metics":
            fig, axes = plt.subplots(len(performance.coords["metric"].values),
                                     sharex=True, queeze=False)
            for j, metric in enumerate(performance.coords["metric"].values):
                for i, model in enumerate(performance.coords["model"].values):
                    k_values = performance.sel(dataset=dataset,
                                               model=model,
                                               metric=metric)
                    axes[j, 0].plot(k_values.values)

                axes[j, 0].set_title(performance.name + " for " +
                                     dataset.name + "and metric " + str(metric))
                axes[j, 0].set_ylabel("Number of queries")
                axes[j, 0].set_xlabel("Bins")
                axes[j, 0].legend(performance.coords["model"].values)
                axes[j, 0].yaxis.set_ticks(np.arange(0, 1, 0.1))

Instances