Graphing and Interpretation

This guide focuses on the practical use of OpenPinch graph outputs after a case has been solved.

Question This Guide Answers

Which graph should I inspect first, and how do I connect graph changes back to the summary metrics?

Fastest Graph Workflow

Python:

gcc = problem.plot.grand_composite_curve()
cc = problem.plot.composite_curve()

Best Default Graph

If you only inspect one graph after the summary, inspect the grand composite curve.

It is usually the best graph for:

• utility placement questions

• residual thermal pocket interpretation

• Heat Pump opportunity screening

Recommended Interpretation Order

1. read the summary table first

2. identify the target row and scope

3. inspect the GCC

4. move to composite or shifted composite curves if you need overlap detail

5. move to site-level graph families only when the workflow is multiscale

Exporting Graphs

Use Python when you want direct plotly figures. Install openpinch[notebook] or openpinch[dashboard] first.

Use problem.plot.export(…) when you want portable HTML output for sharing or review outside Python.

Common Mistakes

• reading a graph without checking the target scope first

• treating a graph improvement as enough without checking the utility numbers

• comparing process-level and site-level views as though they were the same question

Next Steps

• For graph meaning, see Graphs and Interpretation.

• For multiscale workflows, see Zonal and Total Site Workflows.