Dendrograms

Hierarchical-clustering visualisation: every internal node is a merge whose vertical position equals the merge distance produced by the clustering algorithm. Leaves are evenly spaced along the leaf-axis; "U"-shaped segments connect each merge to its children, matching SciPy's scipy.cluster.hierarchy.dendrogram rendering convention.

DendrogramSeries accepts any TreeNode tree where internal-node Value carries the merge distance — bring your own clustering output (HierarchicalClustering.Cluster() from the MatPlotLibNet.Numerics namespace, or any external algorithm).

Basic dendrogram

var tree = new TreeNode
{
    Label = "root", Value = 3.0,
    Children =
    [
        new TreeNode
        {
            Label = "left", Value = 2.0,
            Children =
            [
                new TreeNode
                {
                    Label = "AB", Value = 1.0,
                    Children = [new TreeNode { Label = "A" }, new TreeNode { Label = "B" }],
                },
                new TreeNode { Label = "C" },
            ],
        },
        new TreeNode
        {
            Label = "DE", Value = 1.0,
            Children = [new TreeNode { Label = "D" }, new TreeNode { Label = "E" }],
        },
    ],
};

Plt.Create()
    .WithTitle("Hierarchical clustering")
    .WithSize(640, 420)
    .Dendrogram(tree)
    .Save("dendrogram_basic.svg");

Cut-height with cluster colours

Set CutHeight to draw a dashed reference line at the chosen merge distance and recolour each connected component below the cut from a qualitative colormap. The default colormap is QualitativeColorMaps.Tab10 (10 distinct categorical colours).

Plt.Create()
    .WithTitle("Cut at distance 1.5 → 3 clusters")
    .WithSize(640, 420)
    .Dendrogram(tree, s =>
    {
        s.CutHeight = 1.5;
        s.CutLineColor = Colors.Red;
        s.ColorByCluster = true;
        s.ColorMap = QualitativeColorMaps.Tab10;
    })
    .Save("dendrogram_cut.svg");

CutHeight semantics use strict less-than (node.Value < cut), matching SciPy's dendrogram(color_threshold=…) visual convention. A node whose Value equals the cut exactly is treated as above the cut and is rendered in the default series colour.

Orientations

DendrogramOrientation has four values: Top (default), Bottom, Left, Right. Left/Right are essential for the row dendrogram in a forthcoming ClustermapSeries (Phase 3 of the v1.10 Pair-Selection Visualisation Pack).

foreach (var orient in new[]
{
    DendrogramOrientation.Top,
    DendrogramOrientation.Bottom,
    DendrogramOrientation.Left,
    DendrogramOrientation.Right,
})
{
    Plt.Create()
        .WithTitle($"Orientation: {orient}")
        .WithSize(480, 320)
        .Dendrogram(tree, s => s.Orientation = orient)
        .Save($"dendrogram_{orient.ToString().ToLowerInvariant()}.svg");
}

For Left and Right, leaf labels are rotated 90° so they read along the leaf axis.

Notes

Binary-tree assumption. Internal-node leaf-coordinates are computed as the mean of immediate children. For binary trees (the standard scipy.linkage output), this matches SciPy's (left + right) / 2 placement exactly. N-ary trees are accepted but may render off-centre relative to a leftmost+rightmost-descendant midpoint.
Degenerate inputs. Single-leaf trees render the lone label at the plot centre. All-zero merge distances collapse the U-shapes to the leaf baseline (the renderer falls back to a unit maxMerge to avoid division by zero).
Disable labels. Set ShowLabels = false to suppress every leaf label — useful for embedding the tree in a clustermap margin where the heatmap rows already carry labels.

Table of Contents

Dendrograms

Basic dendrogram

Cut-height with cluster colours

Orientations

Notes