Building health scorecard

camber.scorecard synthesizes FDD findings into the one-glance summary an owner or portfolio manager reads: per-category scores (energy, comfort, ventilation, maintenance) and an overall grade.

flowchart LR
  findings["findings"] --> cat["RULE_CATEGORY map"]
  cat --> energy["energy"]
  cat --> comfort["comfort"]
  cat --> vent["ventilation"]
  cat --> maint["maintenance"]
  energy --> pen["deduct by severity (clamp 0-100)"]
  comfort --> pen
  vent --> pen
  maint --> pen
  pen --> roll["weighted mean (category_weights)"]
  roll --> grade["overall_score / overall_grade (A-F)"]

Findings map to categories, penalise from 100 by severity, then roll up to one overall grade.

from camber.scorecard import build_scorecard

sc = build_scorecard(findings)
sc.overall_score, sc.overall_grade  # e.g. 90.0, "A"
for c in sc.categories:
    print(c.category, c.score, c.grade, c.n_faults, c.n_warnings)

Each category starts at 100; every actionable finding deducts by severity (fault_penalty / warn_penalty), clamped to 0–100, graded A–F. The overall is a weighted mean across categories (category_weights, equal by default). Rules map to categories via RULE_CATEGORY, with unmapped rules in other. Pairs with camber.actionplan (what to do) and camber.fault_economics (what it's worth). stdlib only.