[hotfix] Fix the bug of matplotlib's plot_rank function

optuna/visualization/_rank.py

@@ -18,13 +18,19 @@
 from optuna.visualization._utils import _check_plot_args
 from optuna.visualization._utils import _is_log_scale
 from optuna.visualization._utils import _is_numerical
+from optuna.visualization.matplotlib._matplotlib_imports import _imports as matplotlib_imports
 
 
-if _imports.is_successful():
+plotly_is_available = _imports.is_successful()
+if plotly_is_available:
     from optuna.visualization._plotly_imports import go
     from optuna.visualization._plotly_imports import make_subplots
     from optuna.visualization._plotly_imports import plotly
     from optuna.visualization._plotly_imports import Scatter
+if matplotlib_imports.is_successful():
+    # TODO(c-bata): Refactor to remove matplotlib and plotly dependencies in `_get_rank_info()`.
+    # See https://github.com/optuna/optuna/pull/5133#discussion_r1414761672 for the discussion.
+    from optuna.visualization.matplotlib._matplotlib_imports import plt as matplotlib_plt
 
 _logger = get_logger(__name__)
 
@@ -212,7 +218,7 @@
         if constraints is not None and any([x > 0.0 for x in constraints]):
             infeasible_trial_ids.append(i)
 
-    colors[infeasible_trial_ids] = plotly.colors.hex_to_rgb("#cccccc")
+    colors[infeasible_trial_ids] = (204, 204, 204)  # equal to "#CCCCCC"
 
     filtered_ids = [
         i
@@ -422,7 +428,13 @@
 
 def _convert_color_idxs_to_scaled_rgb_colors(color_idxs: np.ndarray) -> np.ndarray:
     colormap = "RdYlBu_r"
-    # sample_colorscale requires plotly >= 5.0.0.
-    labeled_colors = plotly.colors.sample_colorscale(colormap, color_idxs)
-    scaled_rgb_colors = np.array([plotly.colors.unlabel_rgb(cl) for cl in labeled_colors])
-    return scaled_rgb_colors
+    if plotly_is_available:
+        # sample_colorscale requires plotly >= 5.0.0.
+        labeled_colors = plotly.colors.sample_colorscale(colormap, color_idxs)
+        scaled_rgb_colors = np.array([plotly.colors.unlabel_rgb(cl) for cl in labeled_colors])
+        return scaled_rgb_colors
+    else:
+        cmap = matplotlib_plt.get_cmap(colormap)
+        colors = cmap(color_idxs)[:, :3]  # Drop alpha values.
+        rgb_colors = np.asarray(colors * 255, dtype=int)
+        return rgb_colors