Temperature comfort

Question: how compatible is a 24 °C measurement with the concepts Comfort and Warm? Follow the self-contained quick start to construct the scale and compute both grades.

On the descending side of Triangle(16, 22, 28), the comfort grade is

\[ \mu_{\mathrm{Comfort}}(24)=\frac{28-24}{28-22}=\frac{2}{3}. \]

The first half of the quadratic shoulder gives

\[ \mu_{\mathrm{Warm}}(24)=2\left(\frac{24-22}{30-22}\right)^2=\frac{1}{8}. \]

The strongest grade selects Comfort. The result does not claim that comfort has a 66.7% probability. Both grades describe the same measurement under two definitions. Their sum is not constrained to one.

Engineering check: the universe includes both endpoints, so membership at 0 and 40 °C is legal. Coordinates outside it raise a domain error. This minimal scale leaves a low-temperature gap: both grades are zero below or at 16 °C. Add a cold term and audit the scale if complete coverage is required.

Use in your project: retain the full membership vector for a dashboard or subsequent policy calculation; use selectedTerms only when a single label is useful. Do not discard a weak winning grade. The next scenario shows abstention.

python -I examples/guide.py --scenario temperature

Continue with severity labels and abstention.