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Data · Analysis

Pump interlock Karnaugh map

This pump-interlock example turns a truth-table output into a four-variable grid that can be reviewed with the control logic. Repeated ones in adjacent positions highlight candidates for eliminating variables, while the fully asserted third row offers a larger grouping opportunity. A Karnaugh map is most useful when the function has few variables and the person reviewing it needs to see why a term disappears. Verify the resulting expression against the original truth table before putting it into a programmable controller. Before sharing it, compare the chart with the source table and make the scope explicit. A clear date range, population and unit help another reader interpret the pattern correctly and decide whether follow-up analysis is needed.

Type echarts-heatmapEngine echarts-heatmapUpdated 9/24/2026
Pump Interlock — F(A,B,C,D)
Drawing preview
The request

“Generate a 4-variable Karnaugh map for pump interlock output F(A,B,C,D) with minterms 0, 3, 4, 7, 12, 13, 14 and 15 in Gray-code order.”

Then tryChange minterm 14 to 0.Rename the output to Pump enable.
What is in this drawing

Read the decisions behind it.

01Set the scope

Use one reporting period and one clear unit.

02Read the pattern

Identify the largest concentration or directional change.

03Check the source

Confirm the displayed values against the underlying data.

Use this heatmap when the stated values and labels are the information the reader needs to compare.

More like this

Other examples in this family.

Browse all heatmap templates →

FAQ

Common questions

What does this heatmap show?

A heatmap uses colour to show the size of a value at the intersection of two categories. It helps readers spot concentrations, gaps and repeated patterns quickly.

How should I read this heatmap?

Choose a colour scale whose minimum and maximum match the data, and include cell labels when precise values matter to the decision.

Can I adapt this heatmap example?

Yes. Replace the title, labels and values with your own data, then check that the prompt still describes every important element in the chart.