One result, several checkpoints¶
Part II treats a numerical result as an evidence trail rather than a number that becomes trustworthy merely because code produced it. An array represents quantities with a shape, dtype, and indexing convention. A figure makes a selected relationship visible. A test checks stated behavior under stated conditions. A small type makes a recurring invariant or unit boundary visible where values enter a program.
These are connected checks, not four competing programming styles. A light curve, simulation output, laboratory series, or field observation can need all four: a sound representation, an honest visual argument, a behavioral check, and a clearly limited contract for the values that move through the analysis.
A return route, not another chapter¶
Use this recap after Chapters 7–10 or when a result needs diagnosis. It does not add a hidden requirement beyond the completed route. Start from the question that most closely resembles the uncertainty in front of you, then return to the chapter for the full explanation and examples.
| If you notice… | First question to ask | Return to… |
|---|---|---|
| a surprising mean, mask, or broadcast result | What do the array’s shape, axes, dtype, and missing values represent? | Chapter 7 |
| a persuasive-looking plot | What quantities, units, scale, uncertainty, and comparison make the visual claim warranted? | Chapter 8 |
| code that runs but is hard to trust | Which stated behavior, edge case, known solution, or convergence trend could expose an error? | Chapter 9 |
| repeated values whose meaning drifts across functions | Is there a small invariant, unit boundary, or meaningful operation that deserves an explicit type? | Chapter 10 |
Transfer prompt: trace a claim backward¶
Choose one figure or numerical conclusion from your own work. Write four short notes: what the stored values represent; what the visual or numerical result shows; what behavior you have tested; and which assumption would be worth making explicit in a function or small type. If a note is missing, you have found a productive next check—not evidence that the result is already wrong.
Next connection¶
Part III will extend this evidence trail from one array or measurement to a collection of records, their schemas, quality decisions, and provenance. It is in development, so it is not a prerequisite for the completed Parts I–II route. For a difficult foundational question, return to Part I Recap — Trustworthy Scientific Programming.