Demonstrates how to create a JavaScript Chart with Logarithmic axis using SciChart.js, High Performance JavaScript Charts
drawExample.ts
index.tsx
ExampleDataProvider.ts
theme.ts
1import {
2 ENumericFormat,
3 EllipsePointMarker,
4 FastLineRenderableSeries,
5 LegendModifier,
6 LogarithmicAxis,
7 MouseWheelZoomModifier,
8 NumericAxis,
9 RubberBandXyZoomModifier,
10 SciChartSurface,
11 SweepAnimation,
12 XyDataSeries,
13 Thickness,
14 ZoomExtentsModifier,
15} from "scichart";
16import { appTheme } from "../../../theme";
17import { ExampleDataProvider } from "../../../ExampleData/ExampleDataProvider";
18
19const Y_AXIS_LINEAR_ID = "Y_AXIS_LINEAR_ID";
20const X_AXIS_LINEAR_ID = "X_AXIS_LINEAR_ID";
21
22export const drawExample = async (rootElement: string | HTMLDivElement) => {
23 // Create a SciChartSurface
24 const { sciChartSurface, wasmContext } = await SciChartSurface.create(rootElement, {
25 theme: {
26 ...appTheme.SciChartJsTheme,
27 majorGridLineBrush: appTheme.MutedSkyBlue + "55",
28 minorGridLineBrush: appTheme.MutedSkyBlue + "22",
29 },
30 title: "Logarithmic X & Y Axis",
31 titleStyle: {
32 fontSize: 20,
33 fontWeight: "bold",
34 placeWithinChart: true,
35 color: appTheme.ForegroundColor + "C4",
36 padding: Thickness.fromString("10 0 4 0"),
37 },
38 });
39
40 // Create an X and Y Axis
41 const xAxisLogarithmic = new LogarithmicAxis(wasmContext, {
42 logBase: 10,
43 labelFormat: ENumericFormat.Scientific,
44 labelPrecision: 2,
45 minorsPerMajor: 10,
46 useNativeText: false,
47 });
48 sciChartSurface.xAxes.add(xAxisLogarithmic);
49
50 // The LogarithmicAxis will apply logarithmic scaling and labelling to your data.
51 // Simply replace a NumericAxis for a LogarithmicAxis on X or Y to apply this scaling
52 // Note options logBase, labelFormat which lets you specify exponent on labels
53 const yAxisLogarithmic = new LogarithmicAxis(wasmContext, {
54 logBase: 10,
55 labelFormat: ENumericFormat.Scientific,
56 labelPrecision: 2,
57 minorsPerMajor: 10,
58 useNativeText: false,
59 });
60 sciChartSurface.yAxes.add(yAxisLogarithmic);
61
62 const xAxisLinear = new NumericAxis(wasmContext, {
63 labelFormat: ENumericFormat.Decimal,
64 labelPrecision: 2,
65 isVisible: false,
66 id: X_AXIS_LINEAR_ID,
67 });
68 sciChartSurface.xAxes.add(xAxisLinear);
69
70 const yAxisLinear = new NumericAxis(wasmContext, {
71 labelFormat: ENumericFormat.Decimal,
72 labelPrecision: 2,
73 isVisible: false,
74 id: Y_AXIS_LINEAR_ID,
75 });
76 sciChartSurface.yAxes.add(yAxisLinear);
77
78 // Create some data
79 const data0 = ExampleDataProvider.getExponentialCurve(2, 100);
80 const data1 = ExampleDataProvider.getExponentialCurve(2.2, 100);
81 const data2 = ExampleDataProvider.getExponentialCurve(2.4, 100);
82
83 sciChartSurface.renderableSeries.add(
84 new FastLineRenderableSeries(wasmContext, {
85 dataSeries: new XyDataSeries(wasmContext, {
86 xValues: data0.xValues,
87 yValues: data0.yValues,
88 dataSeriesName: "y = x ^ 2",
89 }),
90 stroke: appTheme.VividSkyBlue,
91 strokeThickness: 3,
92 pointMarker: new EllipsePointMarker(wasmContext, {
93 width: 7,
94 height: 7,
95 fill: appTheme.VividSkyBlue,
96 strokeThickness: 0,
97 }),
98 animation: new SweepAnimation({ duration: 800, delay: 0 }),
99 })
100 );
101
102 sciChartSurface.renderableSeries.add(
103 new FastLineRenderableSeries(wasmContext, {
104 dataSeries: new XyDataSeries(wasmContext, {
105 xValues: data1.xValues,
106 yValues: data1.yValues,
107 dataSeriesName: "y = x ^ 2.2",
108 }),
109 stroke: appTheme.VividPink,
110 strokeThickness: 3,
111 pointMarker: new EllipsePointMarker(wasmContext, {
112 width: 7,
113 height: 7,
114 fill: appTheme.VividPink,
115 strokeThickness: 0,
116 }),
117 animation: new SweepAnimation({ duration: 800, delay: 0 }),
118 })
119 );
120
121 sciChartSurface.renderableSeries.add(
122 new FastLineRenderableSeries(wasmContext, {
123 dataSeries: new XyDataSeries(wasmContext, {
124 xValues: data2.xValues,
125 yValues: data2.yValues,
126 dataSeriesName: "y = x ^ 2.4",
127 }),
128 stroke: appTheme.VividOrange,
129 strokeThickness: 3,
130 pointMarker: new EllipsePointMarker(wasmContext, {
131 width: 7,
132 height: 7,
133 fill: appTheme.VividOrange,
134 strokeThickness: 0,
135 }),
136 animation: new SweepAnimation({ duration: 800, delay: 0 }),
137 })
138 );
139
140 // Add some interactivity modifiers
141 sciChartSurface.chartModifiers.add(
142 new RubberBandXyZoomModifier(),
143 new MouseWheelZoomModifier(),
144 new ZoomExtentsModifier(),
145 new LegendModifier({ showCheckboxes: false })
146 );
147
148 sciChartSurface.zoomExtents();
149 return {
150 sciChartSurface,
151 wasmContext,
152 yAxisLogarithmic,
153 yAxisLinear,
154 xAxisLinear,
155 xAxisLogarithmic,
156 };
157};
158This example demonstrates how to create a high-performance SciChart.js chart featuring LogarithmicAxis configuration using JavaScript. The implementation plots exponential curves on both the X and Y axes while allowing runtime toggling between logarithmic and linear axis configurations.
The chart is asynchronously initialized using SciChartSurface.create, which loads the WebAssembly context and applies a custom theme for styling. Two LogarithmicAxis are configured with properties such as logBase, labelFormat, and labelPrecision; details of these configurations can be found in the Logarithmic Axis Documentation. Renderable series are created using FastLineRenderableSeries in combination with XyDataSeries to plot exponential curves, and each series is enhanced with a SweepAnimation for smooth visual transitions.
The example showcases real-time update capabilities by enabling users to seamlessly switch between logarithmic and linear axis states at runtime. It integrates interactive modifiers such as RubberBandXyZoomModifier and MouseWheelZoomModifier to facilitate intuitive zooming and panning. Additionally, the application of custom theming—including grid line brushes and title styling—illustrates how visual aspects can be tailored to meet specific design requirements. For additional context on building high-performance charts, refer to Getting Started with SciChart JS.
Despite being a JavaScript example, the implementation follows best practices in asynchronous initialization, interactive behavior, and dynamic configuration. The runtime axis switching is handled by toggling the visibility and primary status of the axes, ensuring that the currently active axes are correctly bound to the series data; this approach is in line with the guidance provided in the SciChart.js Documentation. Developers looking to optimize performance and customize their charts further can benefit from exploring the available Performance Tips & Tricks provided by SciChart.js.

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