python - Seaborn FacetGrid - 在最后一个子图之后放置单个颜色条

Question

我正在尝试将颜色条添加到 3 个 seaborn 绘图的网格中。我可以将颜色条添加到 3 个单独的图，或者在第三个图旁边挤压一个颜色条。我想在第三个图之后有一个颜色条，而不改变最后一个图的大小。

我从这个答案中得到了很多好主意，但无法解决我的确切问题:SO Question/Answer

这是我当前的代码:

import seaborn as sns

def masked_vs_unmasked_facets(output_dir, merged_df, target_col, thresholds):
    # defining the maximal values, to make the plot square
    z_min = merged_df[['z_full', 'z_masked']].min(axis=0, skipna=True).min(skipna=True)
    z_max = merged_df[['z_full', 'z_masked']].max(axis=0, skipna=True).max(skipna=True)
    z_range_value = max(abs(z_min), abs(z_max))

    # Setting the column values to create the facet grid
    for i, val in enumerate(thresholds):
        merged_df.loc[merged_df.info_score_masked > val, 'PlotSet'] = i

    # Start the actual plots
    g = sns.FacetGrid(merged_df, col='PlotSet', size=8)

    def facet_scatter(x, y, c, **kwargs):
        kwargs.pop("color")
        plt.scatter(x, y, c=c, **kwargs)
        # plt.colorbar() for multiple colourbars

    vmin, vmax = 0, 1
    norm=plt.Normalize(vmin=vmin, vmax=vmax)

    g = (g.map(facet_scatter, 'z_full', 'z_masked', 'info_score_masked', norm=norm, cmap='viridis'))

    ax = g.axes[0]
    for ax in ax:
        ax.set_xlim([-z_range_value * 1.1, z_range_value * 1.1])
        ax.set_ylim([-z_range_value * 1.1, z_range_value * 1.1])
        ax.plot(ax.get_xlim(), ax.get_ylim(), ls="--", c=".3")

    plt.colorbar() # Single squashed colorbar
    plt.show()

masked_vs_unmasked_facets(output_dir, masking_results, 'info_score_masked', [0, 0.7, 0.9])

单个颜色条，但第 3 个图被压扁 多个颜色条，但很拥挤

Answer 1

根据@ImportanceOfBeingEarnest 的建议，我发现我需要向 facetgrid 添加另一组轴，然后将这些轴分配给颜色条。为了将这个额外的元素保存到绘图中，我使用了 bbox_extra_artist kwarg 作为紧密边界框。另一个小的补充是一个小条款，用于捕获我的一个方面没有数据的边缘情况。在这种情况下，我附加了一个空行，其中包含一个类别实例，因此每个类别始终至少有 1 行。

import seaborn as sns

def masked_vs_unmasked_facets(output_dir, merged_df, target_col, thresholds):
    z_min = merged_df[['z_full', 'z_masked']].min(axis=0, skipna=True).min(skipna=True)
    z_max = merged_df[['z_full', 'z_masked']].max(axis=0, skipna=True).max(skipna=True)
    z_range_value = max(abs(z_min), abs(z_max))

    for i, val in enumerate(thresholds):
        merged_df.loc[merged_df.info_score_masked > val, 'PlotSet'] = i
        # Catch instances where there are no values in category, to ensure all facets are drawn each time
        if i not in merged_df['PlotSet'].unique():
            dummy_row = pd.DataFrame(columns=merged_df.columns, data={'PlotSet': [i]})
            merged_df = merged_df.append(dummy_row)

    g = sns.FacetGrid(merged_df, col='PlotSet', size=8)

    def facet_scatter(x, y, c, **kwargs):
        kwargs.pop("color")
        plt.scatter(x, y, c=c, **kwargs)

    vmin, vmax = 0, 1
    norm=plt.Normalize(vmin=vmin, vmax=vmax)

    g = (g.map(facet_scatter, 'z_full', 'z_masked', 'info_score_masked', norm=norm, cmap='viridis'))

    titles = ["Correlation for all masked / unmasked z-score with {} above {}".format(target_col, threshold) for threshold in thresholds]

    axs = g.axes.flatten()
    for i, ax in enumerate(axs):
        ax.set_title(titles[i])
        ax.set_xlim([-z_range_value * 1.1, z_range_value * 1.1])
        ax.set_ylim([-z_range_value * 1.1, z_range_value * 1.1])
        ax.plot(ax.get_xlim(), ax.get_ylim(), ls="--", c=".3")


    cbar_ax = g.fig.add_axes([1.015,0.13, 0.015, 0.8])
    plt.colorbar(cax=cbar_ax)
    # extra_artists used here
    plt.savefig(os.path.join(output_dir, 'masked_vs_unmasked_scatter_final.png'), bbox_extra_artists=(cbar_ax,),  bbox_inches='tight')

masked_vs_unmasked_facets(output_dir, masking_results, 'info_score_masked', [0, 0.7, 0.9])

这给了我: