Heatmaps & Colormaps

Heatmap with colorbar

double[,] matrix = new double[10, 10];
for (int r = 0; r < 10; r++)
    for (int c = 0; c < 10; c++)
        matrix[r, c] = Math.Sin(r * 0.5) * Math.Cos(c * 0.5);

Plt.Create()
    .AddSubPlot(1, 1, 1, ax => ax
        .WithTitle("Heatmap — Plasma")
        .Heatmap(matrix)
        .WithColorMap("plasma")
        .WithColorBar(cb => cb with { Label = "Intensity" }))
    .TightLayout()
    .Save("heatmap.svg");

Colormap comparison

MatPlotLibNet ships 104 colormaps. Here are four popular ones side by side:

string[] maps = ["viridis", "turbo", "coolwarm", "greys"];
var builder = Plt.Create()
    .WithTitle("Colormap Comparison")
    .WithSize(1200, 800);

for (int i = 0; i < maps.Length; i++)
{
    var mapName = maps[i];
    builder.AddSubPlot(2, 2, i + 1, ax => ax
        .WithTitle(mapName)
        .Heatmap(matrix)
        .WithColorMap(mapName)
        .WithColorBar());
}

builder.TightLayout().Save("colormap_comparison.svg");

Colorbar customization

Plt.Create()
    .AddSubPlot(1, 1, 1, ax => ax
        .Heatmap(matrix)
        .WithColorMap("viridis")
        .WithColorBar(cb => cb with
        {
            Label = "Temperature (°C)",
            Orientation = ColorBarOrientation.Horizontal,
        }))
    .TightLayout()
    .Save("colorbar_custom.svg");

Color normalization

Control how data values map to colors:

// Log normalization — useful when data spans orders of magnitude
Plt.Create()
    .AddSubPlot(1, 1, 1, ax => ax
        .Heatmap(logData)
        .WithColorMap("plasma")
        .WithNormalizer(Normalizer.Log())
        .WithColorBar(cb => cb with { Label = "Log scale" }))
    .Save("heatmap_log.svg");

// Two-slope normalization — center on zero
Plt.Create()
    .AddSubPlot(1, 1, 1, ax => ax
        .Heatmap(divergingData)
        .WithColorMap("coolwarm")
        .WithNormalizer(Normalizer.TwoSlope(vCenter: 0))
        .WithColorBar(cb => cb with { Label = "Anomaly" }))
    .Save("heatmap_twoslope.svg");

Heatmap with custom series config

Plt.Create()
    .AddSubPlot(1, 1, 1, ax => ax
        .Heatmap(matrix, s =>
        {
            s.ColorMap = ColorMaps.Turbo;
        })
        .WithColorBar())
    .Save("heatmap_series.svg");

Image (imshow)

Display 2D arrays as images:

Plt.Create()
    .AddSubPlot(1, 1, 1, ax => ax
        .Image(matrix)
        .WithColorMap("gray")
        .WithColorBar())
    .Save("imshow.svg");

2D histogram (density)

var rng = new Random(42);
double[] x = Enumerable.Range(0, 5000).Select(_ => rng.NextGaussian(0, 1)).ToArray();
double[] y = Enumerable.Range(0, 5000).Select(_ => rng.NextGaussian(0, 1)).ToArray();

Plt.Create()
    .AddSubPlot(1, 1, 1, ax => ax
        .Histogram2D(x, y, bins: 30)
        .WithColorMap("viridis")
        .WithColorBar(cb => cb with { Label = "Count" }))
    .Save("hist2d.svg");

Pseudocolor mesh

Plt.Create()
    .AddSubPlot(1, 1, 1, ax => ax
        .Pcolormesh(xEdges, yEdges, data)
        .WithColorMap("inferno")
        .WithColorBar())
    .Save("pcolormesh.svg");

Popular colormaps

Category	Colormaps
Perceptual	viridis, plasma, inferno, magma, cividis
Sequential	greys, purples, blues, greens, oranges, reds
Diverging	coolwarm, RdBu, PiYG, PRGn, BrBG, seismic
Cyclic	twilight, hsv
Qualitative	tab10, tab20, Set1, Set2, Set3, Pastel1, Paired
Other	turbo, jet, hot, cool, spring, summer, autumn, winter

Calendar heatmap (GitHub-style)

A 52 × 7 heatmap where rows are weeks and columns are days of the week.

var rng = new Random(7);
var data = new double[52, 7];
for (int w = 0; w < 52; w++)
    for (int d = 0; d < 7; d++)
    {
        double base_ = (d < 5) ? rng.NextDouble() * 8 : rng.NextDouble() * 2;
        data[w, d] = Math.Max(0, base_ + w * 0.05 + rng.NextDouble() * 2 - 1);
    }

Plt.Create()
    .WithTitle("Calendar Heatmap — Contributions")
    .WithSize(1100, 300)
    .AddSubPlot(1, 1, 1, ax => ax
        .Heatmap(data, s => { s.ColorMap = ColorMaps.Viridis; })
        .WithColorBar()
        .SetXLabel("Week")
        .SetYLabel("Day"))
    .Save("calendar_heatmap.svg");