MatPlotLibNet 1.2.0

MatPlotLibNet

A .NET 10 / .NET 8 charting library inspired by matplotlib. Fluent API, dependency injection, parallel SVG rendering, polymorphic export (SVG / PNG / PDF / GIF), and multi-platform output to Blazor, MAUI, ASP.NET Core, Angular, React, and Vue.

v1.2.0 — Bidirectional SignalR interactive charts. Browser wheel-zoom, drag-pan, reset, and legend-toggle now round-trip through ChartHub to a server-authoritative Figure that is mutated on a per-chart channel-drained background task and re-published through the existing SignalR fan-out. Pure .NET, no JavaScript charting library, server stays the source of truth. See MatPlotLibNet.AspNetCore README or the Samples/MatPlotLibNet.Samples.AspNetCore + Interactive.razor demos.

Packages

Quick start

using MatPlotLibNet;
using MatPlotLibNet.Styling;

double[] x = [1, 2, 3, 4, 5];
double[] y = [2, 4, 3, 5, 1];

Plt.Create()
    .WithTitle("My First Chart")
    .WithTheme(Theme.Dark)
    .Plot(x, y, s => { s.Color = Color.Blue; s.Label = "Data"; })
    .WithLegend()
    .Save("chart.svg");

61 series types — line, scatter, bar, histogram, pie, box, violin, heatmap, contour, candlestick, OHLC, treemap, sunburst, Sankey, polar, polar heatmap, 3D surface, Bar3D, PlanarBar3D, radar, waterfall, funnel, gauge, and more.

Bidirectional SignalR (v1.2.0) — FigureBuilder.WithServerInteraction("chart-id", i => i.All()) opts a figure into server-authoritative interaction. The embedded dispatcher script invokes ChartHub.OnZoom / OnPan / OnReset / OnLegendToggle, a FigureRegistry-owned background reader task mutates the figure through a stacked-record event hierarchy (ZoomEvent : AxisRangeEvent : FigureInteractionEvent), and the updated SVG streams back through the existing publish fan-out. Natural coalescing — bursts of wheel events produce exactly one re-render per batch. Works with any @microsoft/signalr host page; first-class Blazor sample ships in Samples/MatPlotLibNet.Samples.Blazor.

Accessibility — SVG exports carry role="img", <title>/<desc>, and ARIA labels on all structural groups; all 5 interactive JS features are keyboard-navigable; Okabe-Ito color-blind safe palette (Theme.ColorBlindSafe); WCAG AAA high-contrast theme (Theme.HighContrast).

Matplotlib look-alike themes — Theme.MatplotlibClassic mimics matplotlib's pre-2.0 default (white background, the iconic bgrcmyk cycle, DejaVu Sans 12pt). Theme.MatplotlibV2 mimics the modern matplotlib default since 2017 (white background, soft-black text, the tab10 10-color cycle, DejaVu Sans 10pt). Drop-in matplotlib look in pure .NET — no Python runtime required.

Series capability interfaces — IHasColor, IHasAlpha, IHasEdgeColor, ILabelable allow polymorphic access to common series properties without casting; enables generic theming and rendering utilities.

NumPy-style numerics — Mat matrix type with SIMD operators, Linalg (Solve/Inv/Det/Eigh/Svd), NpStats (Diff/Median/Histogram/Argsort/Unique/Cov/Corrcoef), NpRandom (Normal/Uniform/Lognormal/Integers), and Fft.Inverse/Frequencies/Shift — all zero new dependencies, pure C# + TensorPrimitives.

Broken / discontinuous axis — AxisBreak + BreakStyle (Zigzag, Straight, None); WithXBreak / WithYBreak on the fluent builder; visual markers drawn at break boundaries.

DataFrame indicator + regression bridges — MatPlotLibNet.DataFrame now includes DataFrameIndicatorExtensions (16 methods: SMA, EMA, RSI, Bollinger, OBV, MACD, DrawDown, ADX, ATR, CCI, WilliamsR, Stochastic, ParabolicSar, KeltnerChannels, VWAP) and DataFrameNumericsExtensions (PolyFit, PolyEval, ConfidenceBand) — compute indicators and polynomial regressions directly from named DataFrame columns.

Documentation

Full documentation is on the GitHub Wiki:

• Getting Started — installation, output formats, subplots
• Package Map — all packages in detail
• DataFrame — MatPlotLibNet.DataFrame: charting, indicators, and regression from Microsoft.Data.Analysis.DataFrame
• Notebooks — Polyglot Notebooks + Jupyter inline rendering
• Chart Types — all 61 series with examples
• Styling — themes, colormaps, PropCycler
• Matplotlib Themes — Theme.MatplotlibClassic and Theme.MatplotlibV2 look-alikes
• Accessibility — SVG semantics, keyboard navigation, color-blind palette, high-contrast theme
• Advanced — date axes, math text, animations, GIF, real-time
• Benchmarks — SVG rendering, SIMD transforms, indicators
• Roadmap — version history and planned phases
• Contributing — build, test, coding conventions

License

MIT — free for any use, open-source or commercial, with no copyleft conditions.