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FastPlot

Ultra-fast time series plotting for MATLAB and GNU Octave.

FastPlot enables fluid interactive visualization of massive datasets (1K to 100M+ points). It dynamically downsamples data to screen resolution on every zoom/pan interaction, rendering only ~4,000 points regardless of dataset size. This eliminates GPU memory bottlenecks and keeps the UI responsive at 200+ FPS.

Key Metrics

Metric	Value
10M point zoom cycle	4.7 ms (212 FPS)
Point reduction	99.96% (10M to ~4K displayed)
GPU memory (10M pts)	0.06 MB vs 153 MB for plot()
Implementation	Pure MATLAB + optional C MEX (AVX2/NEON SIMD)

Features

• Smart downsampling — per-pixel MinMax and LTTB algorithms, auto-selected per zoom level
• Lazy pyramid cache — multi-resolution pre-computation for instant zoom-out on 50M+ datasets
• MEX acceleration — optional C with SIMD (AVX2/NEON), auto-fallback to pure MATLAB
• Dashboard layouts — tiled grids (FastPlotFigure) and tabbed containers (FastPlotDock)
• Interactive toolbar — data cursor, crosshair, grid/legend toggle, autoscale, PNG export
• 6 built-in themes — default, dark, light, industrial, scientific, ocean (with colorblind palette)
• Linked axes — synchronized zoom/pan across subplots
• Datetime support — datenum and MATLAB datetime with auto-formatting tick labels
• NaN gap handling — seamless visualization of missing data regions
• Uneven sampling — works with any monotonically increasing X (no uniform spacing required)
• Sensor system — state-dependent thresholds with condition-based rules and violation markers
• Event detection — group violations into events with statistics, Gantt viewer, click-to-plot
• Live mode — file polling with auto-refresh (preserve/follow/reset view modes)
• Console progress bars — hierarchical progress display during batch rendering
• Disk-backed storage — SQLite-backed chunked DataStore for 100M+ point datasets that exceed memory
• Navigator overlay — minimap zoom navigator for quick orientation
• Sensor detail view — specialized plot with state bands and threshold context

Quick Start

setup;

% Basic plot with 10M points
fp = FastPlot('Theme', 'dark');
x = linspace(0, 100, 1e7);
y = sin(x) + 0.1 * randn(size(x));
fp.addLine(x, y, 'DisplayName', 'Sensor');
fp.addThreshold(0.8, 'Direction', 'upper', 'ShowViolations', true, 'Label', 'High');
fp.render();

% Dashboard with tiled layout
fig = FastPlotFigure(2, 2, 'Theme', 'dark');
fig.setTileSpan(1, [1 2]);

fp1 = fig.tile(1);
fp1.addLine(x, sin(x), 'DisplayName', 'Pressure');
fp1.addBand(0.8, 1.0, 'FaceColor', [1 0.3 0.3], 'FaceAlpha', 0.15, 'Label', 'Alarm');
fig.tileTitle(1, 'Pressure Monitor');

fp2 = fig.tile(2);
fp2.addLine(x, cos(x), 'DisplayName', 'Temperature');
fig.tileTitle(2, 'Temperature');

fig.renderAll();

% Sensor with state-dependent thresholds
s = Sensor('pressure', 'Name', 'Chamber Pressure');
s.X = linspace(0, 100, 1e6);
s.Y = randn(1, 1e6) * 10 + 50;

sc = StateChannel('machine');
sc.X = [0 30 60 80]; sc.Y = [0 1 2 1];
s.addStateChannel(sc);
s.addThresholdRule(struct('machine', 1), 70, 'Direction', 'upper', 'Label', 'Run HI');
s.resolve();

fp = FastPlot('Theme', 'industrial');
fp.addSensor(s, 'ShowThresholds', true);
fp.render();

Requirements

• MATLAB R2020b+ or GNU Octave 7+
• C compiler (optional) for MEX acceleration
• No toolbox dependencies

Libraries

FastPlot consists of five libraries:

Library	Path	Description
FastPlot	libs/FastPlot/	Core plotting engine, dashboard layouts, toolbar, themes, disk-backed storage
SensorThreshold	libs/SensorThreshold/	Sensor data containers, state channels, threshold rules
EventDetection	libs/EventDetection/	Event detection, viewer UI, live pipeline, notifications
Dashboard	libs/Dashboard/	Serializable dashboard engine with JSON persistence
WebBridge	libs/WebBridge/	TCP server for web-based visualization

Wiki Navigation

Getting Started

• Installation — setup, MEX compilation, verification
• Getting Started — tutorial with code examples

API Reference

• FastPlot — core plotting class
• Dashboard — FastPlotFigure, FastPlotDock, FastPlotToolbar
• Themes — theme presets, customization, color palettes
• Sensors — Sensor, StateChannel, ThresholdRule, SensorRegistry (with printTable and viewer)
• Event Detection — EventDetector, Event, EventConfig, EventViewer (with Gantt hover tooltips)
• Utilities — ConsoleProgressBar, FastPlotDefaults

Guides

• Live Mode Guide — file polling, view modes, live dashboards
• Datetime Guide — working with time series data
• Dashboard Engine Guide — DashboardEngine + DashboardBuilder usage

Internals

• Architecture — render pipeline, zoom callback, data flow
• MEX Acceleration — SIMD details, build, fallback
• Performance — benchmarks and optimization tips
• Examples — categorized guide to 40+ runnable examples