Feature: Add top-aligned ribbon flow plot type

docs/examples/plot_types/11_topic_ribbon.py

@@ -0,0 +1,105 @@
+"""
+Top-aligned ribbon flow
+=======================
+
+Fixed-row ribbon flows for category transitions across adjacent periods.
+
+Why UltraPlot here?
+-------------------
+This is a distinct flow layout from Sankey: topic rows are fixed globally and
+flows are stacked from each row top, so vertical position is semantically stable.
+
+Key function: :py:meth:`ultraplot.axes.PlotAxes.ribbon`.
+
+See also
+--------
+* :doc:`2D plot types </2dplots>`
+* :doc:`Layered Sankey diagram <07_sankey>`
+"""
+
+import numpy as np
+import pandas as pd
+
+import ultraplot as uplt
+
+GROUP_COLORS = {
+    "Group A": "#2E7D32",
+    "Group B": "#6A1B9A",
+    "Group C": "#5D4037",
+    "Group D": "#0277BD",
+    "Group E": "#F57C00",
+    "Group F": "#C62828",
+    "Group G": "#D84315",
+}
+
+TOPIC_TO_GROUP = {
+    "Topic 01": "Group A",
+    "Topic 02": "Group A",
+    "Topic 03": "Group B",
+    "Topic 04": "Group B",
+    "Topic 05": "Group C",
+    "Topic 06": "Group C",
+    "Topic 07": "Group D",
+    "Topic 08": "Group D",
+    "Topic 09": "Group E",
+    "Topic 10": "Group E",
+    "Topic 11": "Group F",
+    "Topic 12": "Group F",
+    "Topic 13": "Group G",
+    "Topic 14": "Group G",
+}
+
+
+def build_assignments():
+    """Synthetic entity-category assignments by period."""
+    state = np.random.RandomState(51423)
+    countries = [f"Entity {i:02d}" for i in range(1, 41)]
+    periods = ["1990-1999", "2000-2009", "2010-2019", "2020-2029"]
+    topics = list(TOPIC_TO_GROUP.keys())
+
+    rows = []
+    for country in countries:
+        topic = state.choice(topics)
+        rows.append((country, periods[0], topic))
+        for period in periods[1:]:
+            if state.rand() < 0.68:
+                next_topic = topic
+            else:
+                group = TOPIC_TO_GROUP[topic]
+                same_group = [
+                    t for t in topics if TOPIC_TO_GROUP[t] == group and t != topic
+                ]
+                next_topic = state.choice(
+                    same_group if same_group and state.rand() < 0.6 else topics
+                )
+            topic = next_topic
+            rows.append((country, period, topic))
+    return pd.DataFrame(rows, columns=["country", "period", "topic"]), periods
+
+
+df, periods = build_assignments()
+
+group_order = list(GROUP_COLORS)
+topic_order = []
+for group in group_order:
+    topic_order.extend(sorted([t for t, g in TOPIC_TO_GROUP.items() if g == group]))
+
+fig, axs = uplt.subplots(nrows=2, hratios=(3.0, 0.8), refwidth=6.3, share=False)
+axs[0].ribbon(
+    df,
+    id_col="country",
+    period_col="period",
+    topic_col="topic",
+    period_order=periods,
+    topic_order=topic_order,
+    group_map=TOPIC_TO_GROUP,
+    group_order=group_order,
+    group_colors=GROUP_COLORS,
+    composition=True,
+    composition_ax=axs[1],
+    composition_ylabel="Assigned topics",
+)
+
+axs[0].format(title="Category transitions with fixed top-aligned rows")
+fig.format(suptitle="Top-aligned ribbon flow by period")
+fig.show()

ultraplot/axes/plot.py

@@ -2305,6 +2305,116 @@ def _looks_like_links(values):
         diagrams = sankey.finish()
         return diagrams[0] if len(diagrams) == 1 else diagrams
 
+    @docstring._snippet_manager
+    def ribbon(
+        self,
+        data: Any,
+        *,
+        id_col: str = "id",
+        period_col: str = "period",
+        topic_col: str = "topic",
+        value_col: str | None = None,
+        period_order: Sequence[Any] | None = None,
+        topic_order: Sequence[Any] | None = None,
+        group_map: Mapping[Any, Any] | None = None,
+        group_order: Sequence[Any] | None = None,
+        group_colors: Mapping[Any, Any] | None = None,
+        xmargin: float = 0.12,
+        ymargin: float = 0.08,
+        row_height_ratio: float = 2.2,
+        node_width: float = 0.018,
+        flow_curvature: float = 0.45,
+        flow_alpha: float = 0.58,
+        show_topic_labels: bool = True,
+        topic_label_offset: float = 0.028,
+        topic_label_size: float = 7.4,
+        topic_label_box: bool = True,
+        composition_ax: Any | None = None,
+        composition: bool = False,
+        composition_alpha: float = 0.86,
+        composition_ylabel: str = "Assigned topics",
+    ) -> dict[str, Any]:
+        """
+        Draw a fixed-row, top-aligned ribbon flow diagram from long-form records.
+
+        Parameters
+        ----------
+        data : pandas.DataFrame or mapping-like
+            Long-form records with entity id, period, and topic columns.
+        id_col, period_col, topic_col : str, optional
+            Column names for entity id, period, and topic.
+        value_col : str, optional
+            Optional weight column. If omitted, each record is weighted as 1.
+        period_order, topic_order : sequence, optional
+            Explicit ordering for periods and topic rows.
+        group_map : mapping, optional
+            Topic-to-group mapping used for grouped ordering and colors.
+        group_order : sequence, optional
+            Group ordering for row arrangement and composition stacking.
+        group_colors : mapping, optional
+            Group-to-color mapping. Missing groups use the patch color cycle.
+        xmargin, ymargin : float, optional
+            Plot-space margins in normalized axes coordinates.
+        row_height_ratio : float, optional
+            Scale factor controlling row occupancy by nodes/flows.
+        node_width : float, optional
+            Node column width in normalized axes coordinates.
+        flow_curvature : float, optional
+            Bezier curvature for ribbons.
+        flow_alpha : float, optional
+            Ribbon alpha.
+        show_topic_labels : bool, optional
+            Whether to draw topic labels on the right.
+        topic_label_offset : float, optional
+            Offset for right-side topic labels.
+        topic_label_size : float, optional
+            Topic label font size.
+        topic_label_box : bool, optional
+            Whether to draw white backing boxes behind topic labels.
+        composition_ax : `~ultraplot.axes.Axes`, optional
+            Optional secondary axes for a stacked group composition panel.
+        composition : bool, optional
+            Whether to draw composition stackplot on `composition_ax`.
+        composition_alpha : float, optional
+            Alpha for composition stack areas.
+        composition_ylabel : str, optional
+            Y label for composition panel.
+
+        Returns
+        -------
+        dict
+            Mapping of created artists and resolved orders.
+        """
+        from .plot_types.ribbon import ribbon_diagram
+
+        return ribbon_diagram(
+            self,
+            data,
+            id_col=id_col,
+            period_col=period_col,
+            topic_col=topic_col,
+            value_col=value_col,
+            period_order=period_order,
+            topic_order=topic_order,
+            group_map=group_map,
+            group_order=group_order,
+            group_colors=group_colors,
+            xmargin=xmargin,
+            ymargin=ymargin,
+            row_height_ratio=row_height_ratio,
+            node_width=node_width,
+            flow_curvature=flow_curvature,
+            flow_alpha=flow_alpha,
+            show_topic_labels=show_topic_labels,
+            topic_label_offset=topic_label_offset,
+            topic_label_size=topic_label_size,
+            topic_label_box=topic_label_box,
+            composition_ax=composition_ax,
+            composition=composition,
+            composition_alpha=composition_alpha,
+            composition_ylabel=composition_ylabel,
+        )
+
     def circos(
         self,
         sectors: Mapping[str, Any],