Here we demonstrate how to create a Angular Fan Chart using SciChart.js. Zoom in and out to see the detail you can go to using our JavaScript Charts
drawExample.ts
angular.ts
RandomWalkGenerator.ts
theme.ts
1import { appTheme } from "../../../theme";
2import { RandomWalkGenerator } from "../../../ExampleData/RandomWalkGenerator";
3
4import {
5 MouseWheelZoomModifier,
6 ZoomExtentsModifier,
7 ZoomPanModifier,
8 XyyDataSeries,
9 NumericAxis,
10 SciChartSurface,
11 XyDataSeries,
12 ENumericFormat,
13 WaveAnimation,
14 SplineLineRenderableSeries,
15 TextAnnotation,
16 EVerticalAnchorPoint,
17 SplineBandRenderableSeries,
18} from "scichart";
19// tslint:disable:max-line-length
20
21const animation = new WaveAnimation({ duration: 700, fadeEffect: true });
22
23export type TVarPoint = {
24 date: number;
25 actual: number;
26 varMax: number;
27 var4: number;
28 var3: number;
29 var2: number;
30 var1: number;
31 varMin: number;
32};
33
34export function getVarianceData(): TVarPoint[] {
35 const varianceData: TVarPoint[] = [];
36 const startDate = 1546300800; // 1st Jan 2019
37 const dateStep = 1546387200 - startDate; // one day;
38
39 const length: number = 10;
40 const yValues: number[] = new RandomWalkGenerator().Seed(923478).getRandomWalkSeries(length).yValues;
41 for (let i = 0; i < length; i++) {
42 const date = startDate + dateStep * i;
43
44 let varMax: number = NaN;
45 let var4: number = NaN;
46 let var3: number = NaN;
47 let var2: number = NaN;
48 let var1: number = NaN;
49 let varMin: number = NaN;
50
51 if (i > 4) {
52 varMax = yValues[i] + (i - 5) * 0.3;
53 var4 = yValues[i] + (i - 5) * 0.2;
54 var3 = yValues[i] + (i - 5) * 0.1;
55 var2 = yValues[i] - (i - 5) * 0.1;
56 var1 = yValues[i] - (i - 5) * 0.2;
57 varMin = yValues[i] - (i - 5) * 0.3;
58 }
59
60 varianceData.push({ date, actual: yValues[i], varMax, var4, var3, var2, var1, varMin });
61 }
62
63 return varianceData;
64}
65
66export const drawExample = async (rootElement: string | HTMLDivElement) => {
67 // Create a SciChartSurface
68 const { wasmContext, sciChartSurface } = await SciChartSurface.create(rootElement, {
69 theme: appTheme.SciChartJsTheme,
70 });
71
72 // Add an XAxis, YAxis
73 sciChartSurface.xAxes.add(new NumericAxis(wasmContext, { labelFormat: ENumericFormat.Date_DDMMYYYY }));
74 sciChartSurface.yAxes.add(new NumericAxis(wasmContext));
75
76 // Generates some data for the example as an array of TVarPoint: {
77 // date: number;
78 // actual: number;
79 // varMax: number;
80 // var4: number;
81 // var3: number;
82 // var2: number;
83 // var1: number;
84 // varMin: number;
85 // }
86 const varianceData = getVarianceData();
87
88 // To render the fan chart, we use a Line Chart with XyDataSeries
89 // and three Band charts with XyyDataSeries
90 const actualDataSeries = new XyDataSeries(wasmContext);
91 const variance3DataSeries = new XyyDataSeries(wasmContext);
92 const variance2DataSeries = new XyyDataSeries(wasmContext);
93 const variance1DataSeries = new XyyDataSeries(wasmContext);
94
95 actualDataSeries.appendRange(
96 varianceData.map((v) => v.date),
97 varianceData.map((v) => v.actual)
98 );
99 variance3DataSeries.appendRange(
100 varianceData.map((v) => v.date),
101 varianceData.map((v) => v.varMin),
102 varianceData.map((v) => v.varMax)
103 );
104 variance2DataSeries.appendRange(
105 varianceData.map((v) => v.date),
106 varianceData.map((v) => v.var1),
107 varianceData.map((v) => v.var4)
108 );
109 variance1DataSeries.appendRange(
110 varianceData.map((v) => v.date),
111 varianceData.map((v) => v.var2),
112 varianceData.map((v) => v.var3)
113 );
114
115 // Add a line series with the Xy data (the actual data)
116 // Note use FastLineRenderableSeries for non-spline version
117 sciChartSurface.renderableSeries.add(
118 new SplineLineRenderableSeries(wasmContext, {
119 strokeThickness: 2,
120 dataSeries: actualDataSeries,
121 stroke: appTheme.VividPink,
122 animation,
123 })
124 );
125
126 // Add band series with progressively higher opacity for the fan variance data
127 // Note use FastBandRenderableSeries for non-spline version
128 sciChartSurface.renderableSeries.add(
129 new SplineBandRenderableSeries(wasmContext, {
130 dataSeries: variance3DataSeries,
131 opacity: 0.15,
132 fill: appTheme.VividPink,
133 strokeY1: "#00000000",
134 animation,
135 })
136 );
137 sciChartSurface.renderableSeries.add(
138 new SplineBandRenderableSeries(wasmContext, {
139 dataSeries: variance2DataSeries,
140 opacity: 0.33,
141 fill: appTheme.VividPink,
142 strokeY1: "#00000000",
143 animation,
144 })
145 );
146 sciChartSurface.renderableSeries.add(
147 new SplineBandRenderableSeries(wasmContext, {
148 dataSeries: variance1DataSeries,
149 opacity: 0.5,
150 fill: appTheme.VividPink,
151 strokeY1: "#00000000",
152 animation,
153 })
154 );
155
156 // Optional: Add some interactivity modifiers
157 sciChartSurface.chartModifiers.add(
158 new ZoomExtentsModifier(),
159 new ZoomPanModifier({ enableZoom: true }),
160 new MouseWheelZoomModifier(),
161 new ZoomExtentsModifier()
162 );
163
164 // Optional: Add some annotations (text) to show detail
165 sciChartSurface.annotations.add(
166 new TextAnnotation({
167 x1: varianceData[0].date,
168 y1: varianceData[0].actual,
169 verticalAnchorPoint: EVerticalAnchorPoint.Bottom,
170 yCoordShift: -50,
171 text: "Actual data",
172 opacity: 0.45,
173 textColor: appTheme.ForegroundColor,
174 })
175 );
176
177 sciChartSurface.annotations.add(
178 new TextAnnotation({
179 x1: varianceData[5].date,
180 y1: varianceData[5].actual,
181 text: "Forecast Variance",
182 verticalAnchorPoint: EVerticalAnchorPoint.Top,
183 yCoordShift: 50,
184 opacity: 0.45,
185 textColor: appTheme.ForegroundColor,
186 })
187 );
188
189 sciChartSurface.zoomExtents();
190 return { wasmContext, sciChartSurface };
191};
192This Angular example demonstrates how to implement a fan chart using SciChart.js within a standalone Angular component. The chart visualizes both actual data and forecast variance by combining a SplineLineRenderableSeries with multiple SplineBandRenderableSeries. The integration leverages the scichart-angular component to dynamically render advanced charts in an Angular environment.
In this example, the Angular standalone component makes use of asynchronous initialization through its input binding; the component passes the drawExample function to the scichart-angular component. Inside drawExample, the chart is set up using SciChartSurface.create() which not only initializes the WebGL-based rendering engine but also returns a WebAssembly context for high performance rendering. Developers can consult the Getting Started with SciChart JS guide as well as the Deploying Wasm (WebAssembly) and Data Files with your app documentation to understand these core concepts.
The fan chart combines a spline line series for actual data with three spline band series that provide progressively higher opacity bands to visualize forecast variance. Interactive modifiers such as ZoomExtentsModifier, ZoomPanModifier, and MouseWheelZoomModifier are integrated for intuitive chart interactions like zooming and panning. These interactive features enhance the user experience and allow detailed inspection of the data.
This example makes efficient use of Angular’s data binding and asynchronous patterns to manage chart initialization as highlighted in discussions like How to deal with async initialized data in Angular component?. In addition, the approach emphasizes proper resource management by encapsulating chart creation within a standalone component, facilitating easy integration and cleanup in Angular applications. The use of WebAssembly for rendering underscores performance optimization, ensuring smooth animations and rendering with minimal overhead. For further best practices in Angular component design and lifecycle management, developers are encouraged to review Angular’s official Component Lifecycle documentation.

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