Smoothing in charts

Neptune may transform the data displayed on charts by applying the following:

• Rendering algorithm when fetching data from the servers, if the original values are too many to be displayed.
• Smoothing function controlled by the slider next to the chart.

Rendering algorithm ("downsampling")

Neptune renders charts based on all data points. If there are too many original points to display at once, Neptune renders aggregated values.

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Neptune can always retrieve 100% accurate values. You can increase the precision of displayed values by zooming in.

To ensure uniform distribution of all data points, the rendering algorithm divides the X axis of a chart into ranges of the same length, then selects a data point to display for each range.

• If a series has multiple values logged in a given range, the average of the y values is displayed. In addition, the shaded area on the chart represents the minimum and maximum values for that range.

• If a series doesn't have values logged in a given range, the displayed data point is interpolated based on the values of the surrounding points.

Smoothing function

Graph smoothing is manually controlled with the slider in the chart settings.

When you move the smoothing slider, Neptune applies a simple moving average (SMA) calculation on the y-values that are displayed on the chart. Increasing the smoothing increases the size of the window that's used to determine each point's y-value.

The slider position determines the size of the window as follows:

• With maximum smoothing, the window comprises 50% of the total rendered points.

  Because data points are typically distributed uniformly over the X axis, this approximately corresponds to 50% of the chart width.

  

• With the smoothing slider in some middle position, the window size is scaled down linearly. For example: With the slider halfway, the window size is 25% of the total points.

  

The window is centered, so that the average is calculated from an equal number of values on each side.

Near the edges of the chart, the smoothing window shrinks to include fewer points. For example, at the very left edge, the window consists of the point itself plus the right part of the window.

Current limitations

• In case data points aren't distributed uniformly over the X axis, the average value, as calculated by the SMA smoothing algorithm, may differ from actual average value of the continuous function over the given range.
• When a chart is zoomed in, only points in the visible range are retrieved and taken into account when smoothing is performed. This can lead to reduced smoothing precision at the edges of the visible range.