3D Point Clustering

Mix.install([
  {:plotly_ex, "~> 0.3"},
  {:kino, "~> 0.18"}
])

Section

To visualize clustered 3D data, use one Scatter3d trace per cluster — each gets its own name: (legend entry) and marker.color:. This is preferable to a single trace with per-point colors because each cluster can be toggled via the legend independently. :rand.normal() generates standard-normal samples; multiply by σ and add μ for any Gaussian.

alias Plotly.{Figure, Scatter3d}

:rand.seed(:exsplus, {42, 0, 0})

gen_cluster = fn n, cx, cy, cz, sigma ->
  xs = for(_ <- 1..n, do: cx + :rand.normal() * sigma)
  ys = for(_ <- 1..n, do: cy + :rand.normal() * sigma)
  zs = for(_ <- 1..n, do: cz + :rand.normal() * sigma)
  {xs, ys, zs}
end

{x1, y1, z1} = gen_cluster.(100, 0, 0, 0, 0.5)
{x2, y2, z2} = gen_cluster.(100, 3, 3, 3, 0.5)
{x3, y3, z3} = gen_cluster.(100, 0, 3, 6, 0.5)

Figure.new()
|> Figure.add_trace(Scatter3d.new(x: x1, y: y1, z: z1, mode: "markers", name: "Cluster A",
     marker: %{size: 4, color: "blue", opacity: 0.7}))
|> Figure.add_trace(Scatter3d.new(x: x2, y: y2, z: z2, mode: "markers", name: "Cluster B",
     marker: %{size: 4, color: "red", opacity: 0.7}))
|> Figure.add_trace(Scatter3d.new(x: x3, y: y3, z: z3, mode: "markers", name: "Cluster C",
     marker: %{size: 4, color: "green", opacity: 0.7}))
|> Figure.update_layout(
  title: "3D Point Clustering",
  scene: %{
    xaxis: %{title: "X"},
    yaxis: %{title: "Y"},
    zaxis: %{title: "Z"}
  }
)
|> Plotly.show()