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");

Annotated heatmap (correlation matrix)

ShowValues = true renders each cell's numeric value on top of the colour fill. The text colour auto-contrasts black/white per cell using Rec. 709 luminance, so labels stay readable across the colour map. Use CellValueFormat with any standard .NET numeric format string — "F2" (default) for two decimals, "P1" for percent.

double[,] corr = ComputeCorrelationMatrix(returns);

Plt.Create()
    .AddSubPlot(1, 1, 1, ax => ax
        .WithTitle("Asset Correlation Matrix")
        .Heatmap(corr, s =>
        {
            s.ColorMap = ColorMaps.RdBu_r;
            s.ShowValues = true;
            s.CellValueFormat = "F2";
        })
        .WithColorBar())
    .Save("heatmap_annotated.svg");

Override the auto-contrast text colour with CellValueColor when you want the labels to match a brand colour or stay constant across the matrix.

Triangular-mask heatmap

Symmetric matrices (correlation, covariance, distance) are redundant above and below the diagonal — MaskMode hides the redundant half so the eye focuses on each pair once. The strict variants also hide the diagonal (constant 1 for correlation matrices).

Plt.Create()
    .AddSubPlot(1, 1, 1, ax => ax
        .WithTitle("Lower-triangle correlation")
        .Heatmap(corr, s =>
        {
            s.ColorMap = ColorMaps.RdBu_r;
            s.ShowValues = true;
            s.MaskMode = HeatmapMaskMode.UpperTriangleStrict;  // hide upper half + diagonal
        })
        .WithColorBar())
    .Save("heatmap_lower_triangle.svg");

HeatmapMaskMode values:

Value	Hides cells where	Diagonal kept?
None	(nothing)	yes
UpperTriangle	col > row	yes
LowerTriangle	col < row	yes
UpperTriangleStrict	col >= row	no
LowerTriangleStrict	col <= row	no

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");