iOS & macOS Charting Documentation - SciChart iOS & macOS Charts SDK v4.x

What is Data Resampling and how does it work?

By default, SciChart uses resampling (culling) of data to ensure the minimum viable data-set is displayed on the screen. Resampling is intended to be lossless, and automatic. It occurs for every RenderableSeries before the series is rendered, if required.

Resampling methods make assumptions about the data in order to produce a valid output. SciChart provides variety of the SCIResamplingMode, and auto detects the most suitable one.

However, there are cases when data input cannot be resampled accurately. Good examples could be plotting unsorted data or using logarithmic scale on an axis. We recommend using SCIResamplingMode.SCIResamplingMode_None in such situations, which in other word means switching Resampling off.

NOTE: Please be aware that if you disable resampling you will experience a degradation in performance.

Resampling Modes

There are several SCIResamplingMode available in SciChart:

Resampling Modes	Description
`SCIResamplingMode.SCIResamplingMode_Auto`	This is the default mode. It auto-detects the most suitable resampling algorithm - fastest and most accurate - for the type of data appended.
`SCIResamplingMode.SCIResamplingMode_None`	switches off Resampling on a `ISCIRenderableSeries`.
`SCIResamplingMode.SCIResamplingMode_MinMax`	suitable for evenly-spaced data. Resamples by taking the min-max of oversampled data.
`SCIResamplingMode.SCIResamplingMode_MinOrMax`	suitable for evenly-spaced. Resamples by taking the min or max of oversampled data.
`SCIResamplingMode.SCIResamplingMode_Min`	suitable for evenly-spaced data. Resamples by taking the minimum point of oversampled data.
`SCIResamplingMode.SCIResamplingMode_Max`	suitable for evenly-spaced data. Resamples by taking the maximum point of oversampled data.
`SCIResamplingMode.SCIResamplingMode_Mid`	suitable for evenly-spaced data. Resamples by taking the median point of oversampled data.

Setting Resampling Mode

Most of the time, you don’t need to set SCIResamplingMode manually. SciChart auto detects the best one for a given data and uses it internally. However, when it is necessary, the ResamplingMode can be set explicitly via the ISCIRenderableSeries.resamplingMode property:

    // Create a DataSeries with unsorted data
    SCIXyDataSeries *unsortedDataSeries = [[SCIXyDataSeries alloc] initWithXType:SCIDataType_Double yType:SCIDataType_Double];
    unsortedDataSeries.acceptsUnsortedData = YES;
    
    SCIFastLineRenderableSeries *rSeries = [SCIFastLineRenderableSeries new];
    // Set a DataSeries with unsorted data
    rSeries.dataSeries = unsortedDataSeries;
    
    // Switch off Resampling because the DataSeries is unsorted
    rSeries.resamplingMode = SCIResamplingMode_None;

    // Create a DataSeries with unsorted data
    let unsortedDataSeries = SCIXyDataSeries(xType: .double, yType: .double)
    unsortedDataSeries.acceptsUnsortedData = true
    
    let rSeries = SCIFastLineRenderableSeries()
    // Set a DataSeries with unsorted data
    rSeries.dataSeries = unsortedDataSeries
    
    // Switch off Resampling because the DataSeries is unsorted
    rSeries.resamplingMode = SCIResamplingMode_None

    // Create a DataSeries with unsorted data
    var unsortedDataSeries = new XyDataSeries<double, double>();
    unsortedDataSeries.AcceptsUnsortedData = true;

    var rSeries = new SCIFastLineRenderableSeries();
    // Set a DataSeries with unsorted data
    rSeries.DataSeries = unsortedDataSeries;

    // Switch off Resampling because the DataSeries is unsorted
    rSeries.ResamplingMode = SCIResamplingMode.None;

Resampling Performance

Resampling makes drawing many millions of points possible with SciChart. For instance, in the Performance Demo example, we push 1000 points every 10ms to three series on a chart. The point count quickly rises to the millions of points, and SciChart is still rendering at interactive rates. Also, the example allows to play around with different SCIResamplingMode and see their impact on performance.

In addition, we compared performance of the most popular iOS charting packages with SciChart. The results can be found in the Performance Comparison article.