def _draw_boxplots()

in clearbox/visualization.py [0:0]

• 18 lines of code
• 4 McCabe index (conditional complexity)

  def _draw_boxplots(self, named_dfs: list[tuple[str, pd.DataFrame]]):
    """Draw comparison boxplot for each metric from `_metrics` attribute.

    Args:
      named_dfs: List of `(name, dataframe)` tuples.
        - `name` is the string ID associated with the `dataframe` (typically
          feature name for a baseline, but it can be the name of other model as
          well).
        - `dataframe` contains `valid_{metric.name}` float column for each
          `metric` from `_metrics` attribute. The data frame of such format is
          typically the result of `trainer.get_feature_baseline` call.
    """
    f, axes = plt.subplots(
        1, len(self._metrics), sharey=True, squeeze=False
    )
    f.set_figheight(self._boxplot_height)
    f.set_figwidth(self._boxplot_width * len(self._metrics))
    for i, metric in enumerate(self._metrics):
      axes[0, i].set_xlabel(metric.name)
      axes[0, i].boxplot(
          [df[f"valid_{metric.name}"] for _, df in named_dfs],
          patch_artist=True,
          vert=False,
          medianprops={"color": "white", "linewidth": 1.5},
          boxprops={"color": "C0", "facecolor": "C0", "linewidth": 1.5},
          whiskerprops={"color": "C0", "linewidth": 1.5},
          capprops={"color": "C0", "linewidth": 1.5},
          labels=[x for x, _ in named_dfs],
      )