Interactive Waterfall Spectral Chart

Interactive Waterfall Chart (JavaScript)

Overview

This example demonstrates an interactive waterfall chart implementation using SciChart.js in a JavaScript environment. The chart visualizes spectral data generated by performing a Fourier transform on simulated time series data with the help of the Radix2FFT class. The waterfall design is achieved by layering multiple series – each with its own custom offset for the X and Y axes – across a main chart, while two additional cross-section charts update dynamically based on user interaction.

Technical Implementation

The implementation creates the waterfall effect by configuring a unique pair of numeric axes for each of the fifty series using properties such as the overrideOffset. Each series’ data is generated by simulating time-based signals and then applying a Fourier transform to extract a limited number of spectral components. Data rendering is optimized using the FastLineRenderableSeries, which is designed for high performance with large datasets. In addition, a custom palette provider is implemented to dynamically adjust the stroke colors of the series – for instance, to highlight values around a user-draggable annotation. For details on custom palette providers and extending the chart’s appearance, refer to the PaletteProvider API.

Interactive elements are integrated through chart modifiers such as ZoomPanModifier, MouseWheelZoomModifier, and the SeriesSelectionModifier. The example uses a draggable CustomAnnotation – implemented via SciChart.js’s Editable Annotations – to allow users to select a specific spectral slice. This selection is then synchronized with the cross-section charts using the Series Selection functionality. Additionally, the setup for multiple axes is illustrated in the Adding Multiple Axis Tutorial.

Features and Capabilities

Multi-Axis Configuration: Each series in the waterfall chart uses its own X and Y axes with distinct offsets, a technique that produces the layered waterfall effect. More details on configuring multiple axes can be found in the Tutorial on Adding Multiple Axes.

Performance Optimization: By using the FastLineRenderableSeries, the example ensures a smooth rendering experience even with numerous series and large datasets. Developers looking to learn more about performance optimizations in SciChart.js should consult the Performance Tips & Tricks documentation.

Interactive Annotations and Cross-Chart Communication: The example leverages interactive, draggable annotations to update cross-sectional views in real time. This synchronization across multiple chart surfaces demonstrates how to implement cross-chart interactions using the Annotations API Overview and the SeriesSelectionModifier detailed in the Series Selection documentation.

Integration and Best Practices

This implementation is done entirely with JavaScript, which means that it directly utilizes SciChart.js’s robust API without additional framework abstractions such as Angular or React. Developers are encouraged to incorporate efficient data processing techniques – for example, generating spectral data through Fourier transforms – and to structure the chart using modular functions that update only when necessary. For enhanced visual presentation, advanced rendering features like gradient fills in area series can be explored in the Mountain / Area Series Documentation.

Overall, this example provides a comprehensive guide to building interactive and high-performance waterfall charts with SciChart.js, showcasing the ability to customize series coloring, manage multiple axes, and synchronize interactive updates across chart surfaces in a pure JavaScript environment.