Chart Shape

The Chart shape visualizes data as line plots, scatter plots, or combined views with regression curves and outlier markers.

Overview

A Chart shape plots one or more data series from your model. It supports computed series (from expressions), data series (from table data columns), and regression overlay curves. Outlier points are visually marked to aid data interpretation.

Toolbar

Screenshot: Chart toolbar with series picker, axis config, and options

The Chart toolbar provides:

Series picker — Choose which terms to plot on X and Y axes
Add series — Add another Y-axis series to the chart
Axis configuration — Set axis labels, ranges, and scaling
Color picker — Change shape accent color
Delete — Remove the chart from the board

Series Types

Type	Source	Appearance
Computed	Expression terms evaluated at each iteration	Continuous line
Data	User-entered values from a Table data column	Scatter points
Regression	Curve from a regression term	Smooth fitted line

Terms With Text Values

A term restricted to a set of labels — z \in \{green, blue, red\} — has no numeric scale to be plotted against, so a chart of such a term counts instead: one column per label, as tall as the number of iterations that held it. The horizontal axis carries the labels and the vertical axis carries whole counts, so the X-axis term is not used. Bars and lines both draw the counts.

A count chart has no range of its own to rescale, so the tick handles, the zoom selection and the focus marker are off while a term with text values is plotted.

Displaying Regression Curves

Screenshot: Chart with data scatter points and overlaid linear regression line

After performing a regression in a Table shape:

The regression term becomes available in the chart series picker
Add the regression term as a Y-axis series
The fitted curve overlays on the original scatter data
Compare the model prediction with the experimental data visually

Outlier Visualization

Screenshot: Chart with outlier points marked differently from normal data points

The chart automatically detects and marks outlier points when a regression is active:

Normal data points are shown as filled circles
Outlier points are marked with a distinct style (different color or shape)
The detection uses the isOutlierIteration method from the calculation engine
Outliers are determined by their distance from the regression curve

See Outliers for details on how outlier detection works and how to interpret the results.

Axis Configuration

Option	Description
X-axis term	Which term provides X values (default: independent variable)
Y-axis terms	One or more terms plotted vertically
Auto range	Automatically scale axes to fit all data
Manual range	Set specific min/max for each axis
Scale	Whether a value stands where its size puts it or where its logarithm does, Linear or Log, for the vertical axis. A logarithmic axis spreads its decades evenly and numbers them 1, 10, 100, is stretched a decade at a time by pulling one of its numbers, and given no positive end starts at 1, since nothing below zero has a logarithm
Axis labels	Custom labels displayed on each axis

Properties Panel

Screenshot: Chart properties panel

Property	Description
Series list	All series currently plotted, with their axis assignments
Grid lines	Show/hide background grid
Legend	Show/hide the series legend
Point markers	Show/hide individual data point markers