Demonstrates how to use a ScaleOffsetFilter to convert data to a Percentage Change with realtime updates, using SciChart.js, High Performance JavaScript Charts
drawExample.ts
index.tsx
RandomWalkGenerator.ts
theme.ts
1import { appTheme } from "../../../theme";
2import { RandomWalkGenerator } from "../../../ExampleData/RandomWalkGenerator";
3import {
4 SciChartSurface,
5 NumericAxis,
6 NumberRange,
7 EAutoRange,
8 XyDataSeries,
9 XyScaleOffsetFilter,
10 FastLineRenderableSeries,
11 HitTestInfo,
12 XySeriesInfo,
13 SeriesInfo,
14 ZoomPanModifier,
15 ZoomExtentsModifier,
16 RolloverModifier,
17 TextAnnotation,
18 EHorizontalAnchorPoint,
19 EVerticalAnchorPoint,
20 ECoordinateMode,
21 EAnnotationLayer,
22 ENumericFormat,
23} from "scichart";
24
25// Custom formatNumber function to avoid conflicts
26const customFormatNumber = (value: number, format: ENumericFormat, precision: number) => {
27 return value.toFixed(precision);
28};
29
30const getScaleValue = (dataSeries: XyDataSeries, zeroXValue: number) => {
31 const dataLength = dataSeries.count();
32 let zeroIndex = -1;
33 for (let i = 0; i < dataLength; i++) {
34 const xValue = dataSeries.getNativeXValues().get(i);
35 if (xValue >= zeroXValue) {
36 zeroIndex = i;
37 break;
38 }
39 }
40 if (zeroIndex === -1) {
41 return 1;
42 }
43 return 100 / dataSeries.getNativeYValues().get(zeroIndex);
44};
45
46class TransformedSeries extends FastLineRenderableSeries {
47 public originalSeries: XyDataSeries;
48
49 public override getSeriesInfo(hitTestInfo: HitTestInfo): SeriesInfo {
50 const info = new XySeriesInfo(this, hitTestInfo);
51 if (this.originalSeries && info.dataSeriesIndex !== undefined) {
52 info.yValue = this.originalSeries.getNativeYValues().get(info.dataSeriesIndex);
53 }
54 return info;
55 }
56}
57
58export const drawExample = async (rootElement: string | HTMLDivElement, usePercentage: boolean) => {
59 const { sciChartSurface, wasmContext } = await SciChartSurface.create(rootElement, {
60 theme: appTheme.SciChartJsTheme,
61 });
62
63 const xAxis = new NumericAxis(wasmContext);
64 sciChartSurface.xAxes.add(xAxis);
65
66 const yAxis = new NumericAxis(wasmContext, {
67 autoRange: EAutoRange.Always,
68 labelPostfix: usePercentage ? "%" : "",
69 labelPrecision: usePercentage ? 0 : 1,
70 growBy: new NumberRange(0.1, 0.1),
71 });
72
73 yAxis.labelProvider.formatCursorLabel = (value: number) => customFormatNumber(value, ENumericFormat.Decimal, 1);
74 sciChartSurface.yAxes.add(yAxis);
75
76 const lineSeries = new TransformedSeries(wasmContext, {
77 strokeThickness: 3,
78 stroke: appTheme.VividSkyBlue,
79 });
80 sciChartSurface.renderableSeries.add(lineSeries);
81
82 const data0 = new RandomWalkGenerator().Seed(1337).getRandomWalkSeries(100);
83 const dataSeries1 = new XyDataSeries(wasmContext, { xValues: data0.xValues, yValues: data0.yValues });
84
85 const transform1 = new XyScaleOffsetFilter(dataSeries1, { offset: -100 });
86
87 xAxis.visibleRangeChanged.subscribe(
88 (args) => (transform1.scale = getScaleValue(dataSeries1, args.visibleRange.min))
89 );
90
91 if (usePercentage) {
92 lineSeries.dataSeries = transform1;
93 lineSeries.originalSeries = dataSeries1;
94 } else {
95 lineSeries.dataSeries = dataSeries1;
96 }
97
98 const lineSeries2 = new TransformedSeries(wasmContext, {
99 strokeThickness: 3,
100 stroke: appTheme.VividOrange,
101 });
102 sciChartSurface.renderableSeries.add(lineSeries2);
103
104 const data1 = new RandomWalkGenerator().Seed(0).getRandomWalkSeries(100);
105 const dataSeries2 = new XyDataSeries(wasmContext, { xValues: data1.xValues, yValues: data1.yValues });
106
107 const transform2 = new XyScaleOffsetFilter(dataSeries2, { offset: -100 });
108 xAxis.visibleRangeChanged.subscribe(
109 (args) => (transform2.scale = getScaleValue(dataSeries2, args.visibleRange.min))
110 );
111
112 if (usePercentage) {
113 lineSeries2.dataSeries = transform2;
114 lineSeries2.originalSeries = dataSeries2;
115 } else {
116 lineSeries2.dataSeries = dataSeries2;
117 }
118
119 sciChartSurface.chartModifiers.add(new ZoomPanModifier({ enableZoom: true }));
120 sciChartSurface.chartModifiers.add(new ZoomExtentsModifier());
121 sciChartSurface.chartModifiers.add(new RolloverModifier({ rolloverLineStroke: appTheme.VividTeal }));
122
123 sciChartSurface.annotations.add(
124 new TextAnnotation({
125 text: "Toggle between original data & Percentage Changed on chart",
126 fontSize: 16,
127 textColor: appTheme.ForegroundColor,
128 x1: 0.5,
129 y1: 0,
130 opacity: 0.77,
131 horizontalAnchorPoint: EHorizontalAnchorPoint.Center,
132 xCoordinateMode: ECoordinateMode.Relative,
133 yCoordinateMode: ECoordinateMode.Relative,
134 })
135 );
136
137 const watermarkText = usePercentage ? "Percentage Changed" : "Original Data";
138 sciChartSurface.annotations.add(
139 new TextAnnotation({
140 text: watermarkText,
141 fontSize: 32,
142 textColor: appTheme.ForegroundColor,
143 x1: 0.5,
144 y1: 0.5,
145 opacity: 0.23,
146 horizontalAnchorPoint: EHorizontalAnchorPoint.Center,
147 verticalAnchorPoint: EVerticalAnchorPoint.Center,
148 xCoordinateMode: ECoordinateMode.Relative,
149 yCoordinateMode: ECoordinateMode.Relative,
150 annotationLayer: EAnnotationLayer.BelowChart,
151 })
152 );
153
154 return { sciChartSurface, wasmContext };
155};
156This example demonstrates how to integrate SciChart.js with Angular for real-time data visualization. It focuses on converting series data into percentage change values by applying a dynamic ScaleOffsetFilter transformation and allows users to toggle between displaying the original data and the percentage change view.
The implementation initializes a SciChartSurface with numeric X and Y axes and adds two line series that use random walk data as their source. A custom renderable series is created by extending the default series class to provide enhanced tooltip information. The key part of the logic involves subscribing to axis changes to update the scale factor of the filter dynamically, ensuring that percentage changes are calculated in real-time. Detailed technical insights on custom series development can be found in the Custom RenderableSeries API.
The example offers real-time data updates, dynamic percentage recalculations, and interactive features such as zooming and panning. It leverages Angular’s event handling to subscribe to axis range changes and apply corresponding transformations on the fly. Additionally, the sample emphasizes performance by updating only the necessary filter parameters, which optimizes rendering performance during continuous data updates. For further reading on real-time updates and performance optimization, refer to the Adding Realtime Updates documentation.
This example illustrates best practices for integrating SciChart.js into an Angular application. By utilizing component-based design and Angular’s robust event management system, developers can build charts that handle real-time data efficiently. Even though the source example originally demonstrates some concepts with React, the Angular integration follows a similar approach by using Angular-compatible toggle buttons and state management strategies. Developers interested in further Angular integrations should explore the scichart-angular package and review the Memory Best Practices to ensure efficient resource management in high-performance applications.

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