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XyDataSeries Data Limit

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I am using SciCharts for a data viewer of IQ data from a spectrum analyzer, sampling at 80MS/s.

What is the limit of the XyDataSeries, as i am getting an “Array dimensions exceeded supported range.”

With StackTrace of:
at eel1.set_ufk(Int32 value)
at eel
1.esy(Int32 tdw)
at eel1.InsertRange(Int32 index, IEnumerable1 collection)
at SciChart.Charting.Model.DataSeries.XyDataSeries2.InsertRange(Int32 startIndex, IEnumerable1 x, IEnumerable1 y, IEnumerable1 metadata)
at SciChart.Charting.Model.DataSeries.XyDataSeries2.InsertRange(Int32 startIndex, IEnumerable1 x, IEnumerable`1 y)
at XXX

The count of the dataseries is 134,217,728, and I am trying to append another 524,288 records to it.

I have compiled the application using 64bit and have tried with multiple versions of scicharts up to the latest one on nuget, all of which appear to show the same issue.

If this is a limit of the XyDataSeries, is there any other mechanisms to load the FastLineRenderableSeries that would be able to handle more data?

Thanks for any help in this matter,


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Hi Daniel,

Thanks for your question.
There are no internal limits for our DataSeries. Data types themselves can only provide the limitations.
Could you please share a small sample project reproducing the issue for investigation?

You can also submit a support ticket if you do not wish to share the code publicly. Here is a link:

With best regards,

  • Daniel
    On further investigation, I came across a limitation on Arrays being limited to 2GB… after applying the following configuration change in the App.Config my app now works up to running out of system memory which is perfect! I am not planning on going above the int.MaxValue number of elements range…
  • Andrew Burnett-Thompson
    I’ve just seen this comment Daniel but yes this is a .NET limitation not a scichart one. By adding the line to App.config as you have above this allows for very large objects on the heap. The only limit is then having an array size larger than int.Maxvalue. Any larger than that and you’ll have to split into several DataSeries!
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