Building Interactive Charts with PlotLab in FireMonkey and VCLCreating interactive charts for Delphi applications can significantly improve how users explore and understand data. PlotLab is a versatile charting library that supports both VCL (Visual Component Library) for traditional Windows desktop apps and FireMonkey (FMX) for cross-platform GUI development. This article walks through the fundamentals, practical examples, best practices, and performance tips for building interactive charts with PlotLab in both FireMonkey and VCL.
Why PlotLab?
PlotLab provides:
- High-quality plotting primitives for lines, bars, areas, scatter, and more.
- Interactive features such as zooming, panning, tooltips, and cursors.
- Support for both VCL (Windows) and FireMonkey (cross-platform), allowing reuse of charting concepts across different UI frameworks.
- Customizable rendering and efficient handling of large datasets.
1. Conceptual Differences: FireMonkey vs VCL
VCL and FireMonkey differ in rendering models and platform targets:
- VCL is tightly integrated with the Windows GDI/GDI+ and is optimized for native Windows look-and-feel. Components are windowed controls (each has a Windows handle).
- FireMonkey uses a retained-mode, GPU-accelerated scene graph that targets multiple platforms (Windows, macOS, iOS, Android). FMX controls are typically lightweight and rendered by the framework.
Implications for PlotLab usage:
- Rendering performance for large datasets may be better in FMX on GPUs, but behavior depends on the platform and the hardware.
- Event handling (mouse/touch) differs: FMX provides unified touch/mouse events, while VCL provides mouse events and Windows messages.
- Visual styling and DPI handling vary: FMX is resolution-independent; VCL may need manual scaling on high-DPI displays.
2. Getting Started: Project Setup
Prerequisites:
- Delphi (version compatible with your PlotLab edition).
- PlotLab library installed (VCL and FMX packages if available).
- Basic familiarity with Delphi IDE, forms, and components.
VCL project:
- Create a new VCL Forms Application.
- Install PlotLab VCL components into the component palette if not already installed.
- Drop a PlotLab chart component onto the form (commonly named TPlotLabChart or similar).
FireMonkey project:
- Create a new Multi-Device Application (FireMonkey).
- Install PlotLab FMX packages.
- Place the PlotLab FMX component on a form or frame.
Note: Package/component names may vary by PlotLab version—consult the PlotLab docs for exact component class names and package names.
3. Basic Chart Construction
Common steps for both frameworks:
- Define data series (line, bar, scatter).
- Populate series with data points.
- Configure axes, labels, and legend.
- Enable interactive features (zoom, pan, tooltips).
Example (conceptual Delphi-style pseudocode):
var Series: TPlotSeries; begin Series := PlotLabChart1.Series.Add(TPlotLineSeries); Series.Name := 'Temperature'; Series.AddXY(0, 21.5); Series.AddXY(1, 22.0); Series.AddXY(2, 23.1); PlotLabChart1.AxisX.Title := 'Time'; PlotLabChart1.AxisY.Title := '°C'; PlotLabChart1.Legend.Visible := True; end;
Differences to watch:
- Component class names and method names may differ slightly between VCL and FMX ports.
- In FMX, ensure data updates occur on the main UI thread (use TThread.Synchronize/Queue if updating from background threads).
4. Interactivity: Zooming, Panning, and Tooltips
Zooming and panning:
- PlotLab typically provides built-in mouse handlers for rubber-band zoom and click-drag panning.
- In VCL, zooming often uses mouse wheel + drag; in FMX, consider touch gestures (pinch to zoom) and map them to the chart’s zoom methods.
Example: enabling mouse wheel zoom (conceptual):
PlotLabChart1.Interaction.MouseWheelZoom := True; PlotLabChart1.Interaction.DragPan := True;
Tooltips and hit-testing:
- Use the library’s hit-test API to detect nearest data point on mouse move or touch.
- Display a small tooltip or a custom floating control showing point values.
Example: on mouse move, find nearest point:
procedure TForm1.PlotLabChart1MouseMove(Sender: TObject; Shift: TShiftState; X, Y: Integer); var HitInfo: TPlotHitInfo; begin HitInfo := PlotLabChart1.HitTest(X, Y); if HitInfo.HasSeries then StatusBar1.SimpleText := Format('Series: %s, X=%.2f Y=%.2f', [HitInfo.Series.Name, HitInfo.XValue, HitInfo.YValue]) else StatusBar1.SimpleText := ''; end;
In FMX, convert touch coordinates appropriately if using high-DPI or scaled layouts.
5. Real-time and Large Dataset Handling
PlotLab can handle streaming data and large datasets with optimizations:
- Use buffered drawing and suspend redraws while updating batches of points:
- BeginUpdate / EndUpdate or similar methods help prevent repeated repaints.
- Downsample or decimate data for display resolution (keep important peaks).
- Use virtualized or incremental series that only store visible ranges.
- For real-time charts, append new points and remove old ones to maintain a sliding window.
Example pattern:
PlotLabChart1.BeginUpdate; try Series.AddXY(TimeStamp, NewValue); if Series.Count > MaxPoints then Series.Delete(0); // maintain sliding window finally PlotLabChart1.EndUpdate; end;
6. Styling and Theming
VCL:
- Use standard VCL properties for fonts, colors, and brushes.
- Consider high-DPI scaling and Windows themes.
FMX:
- Use styles (TStyleBook) for consistent look across platforms.
- FMX supports more advanced effects (gradients, shadows) via style elements.
- Ensure readability on different platforms by testing font sizes and contrast.
Common tips:
- Keep markers and line widths large enough for touch interaction on mobile.
- Use contrasting colors for multiple series; include a legend and direct labels where helpful.
7. Exporting and Printing
PlotLab usually supports exporting to raster/vector formats (PNG, JPEG, SVG, PDF):
- VCL: use chart’s ExportToBitmap or ExportToPDF methods, and use Windows printing APIs for hardcopy.
- FMX: export to bitmaps using TBitmap and write to files; PDF export may require platform-specific support or third-party libraries.
Example:
PlotLabChart1.ExportToPNG('chart.png', 1200, 800);
8. Touch & Mobile Considerations (FMX)
- Implement pinch-to-zoom and two-finger panning by handling FMX gesture events and translating them to chart zoom/pan methods.
- Provide larger touch targets and consider a “zoom reset” button.
- Minimize heavy redraws on low-powered devices; decimate points and reduce axis label frequency.
9. Cross-framework Porting Tips
When moving a chart from VCL to FMX (or keeping parity):
- Map component and property names; search PlotLab docs for FMX equivalents.
- Replace Windows-specific code (messages, handles) with FMX-friendly patterns.
- Rework styling: VCL properties may not map 1:1 to FMX styles.
- Re-test interactivity: mouse vs. touch event handling differences can change UX.
10. Debugging and Profiling
- Use BeginUpdate/EndUpdate to isolate rendering costs.
- Profile data preparation code separately from rendering.
- In FMX, GPU-bound rendering may bottleneck on fill/stroke complexity—reduce effects if slow.
- Log hit-test timing if tooltips feel laggy.
11. Example: Building a Small Interactive App (High-level Steps)
- Create a new FMX or VCL project.
- Place the PlotLab chart component and a few UI controls (buttons, combo boxes).
- Add two series: Line for primary data, Scatter for markers.
- Implement zoom/pan controls and hook mouse/touch events to show tooltips.
- Add a timer or background thread to append data for a live demo (use TThread.Queue for UI sync).
- Add export buttons (PNG, CSV for raw data).
12. Best Practices Summary
- Use BeginUpdate/EndUpdate around bulk changes.
- Decimate large datasets for display; keep full data for analysis/export.
- Prefer FMX styles for cross-platform consistency; account for touch on mobile.
- Test performance across target platforms and devices.
- Expose simple UX controls for zoom reset, auto-scaling, and series visibility.
13. Further Learning and Resources
Consult PlotLab’s official documentation for component names, API specifics, and code examples tailored to the exact version you’re using. Also review Delphi FMX and VCL documentation for framework-specific event models and styling techniques.
Building interactive charts with PlotLab across FireMonkey and VCL is largely about understanding the differences in rendering and input models, optimizing data handling, and providing polished interactivity (zoom, pan, tooltips). With careful attention to performance and platform-specific UX, you can deliver responsive, attractive charts that work well on desktop and mobile.