pyforestry Documentation

Contents:

• Architecture Overview
  • Purpose and Non-Goals
    • Purpose
    • Non-goals
  • Five Contexts and Ownership
    • Context 1: Data Contract Context
    • Context 2: Formula Context
    • Context 3: Model Context (regional /adapters and /systems)
    • Context 4: Simulation Policy + Runtime Context
    • Context 5: Integration/Application Context
  • Hard Rules
  • /adapters and /systems Policy
  • Transitional Exceptions
  • Dispatch and Single-Responsibility Rules
    • Examples
  • Play-Ready Regional Simulation Presets
  • Migration Guardrails
• Model catalog
  • API reference
• Model index
• pyforestry
  • pyforestry package
    • Subpackages
    • Submodules
    • pyforestry.catalog module
    • pyforestry.projection module
    • Module contents
• Helpers Overview
• Tree species basics
  • Notebook Objectives
  • Prerequisites
  • Sources
• Timber bucking demo
  • Notebook Objectives
  • Prerequisites
  • Sources
  • Create timber object
  • Load pricelist
  • Run bucking optimizer
  • Generate a small solution cube
• Stand metrics and site enums
  • Notebook Objectives
  • Prerequisites
  • Sources
    • Generate Site Categories From Requested SIS
• Marklund biomass with SweTimber
  • Notebook Objectives
  • Prerequisites
  • Sources
• Wikberg 2004 ingrowth demo
  • Notebook Objectives
  • Prerequisites
  • Sources
  • 1. Define site inputs
  • 2. Build a stand with trees
  • 3. Deterministic ingrowth (per ha)
  • 4. Convert to plot-level ingrowth trees
  • 5. Stochastic example (seeded RNG)
• Elfving 2010 growth demo
  • Notebook Objectives
  • Prerequisites
  • Sources
  • 1. Define a Swedish site
  • 2. Reconstruct a young stand (NYSKOG)
  • 3. Convert heights to DBH and apply sapling damage
  • 4. Hand over to Elfving 2010
  • 5. Growth + thinning + Söderberg helpers
  • 6. Run growth with thinning at age 50
  • 7. Plot summary results
• Elfving 2010 composite preset demo
  • Handover logic (pyforestry preset)
  • Genetic algorithm: best thinning routine (perpetuity objective)
  • Rent and Accounting Method Competitions (1%, 2%, 3%, 4%)
  • Site Index Spruce Sweep (12 to 36, step 2)
• Soderberg 1986 composite preset demo
  • Notes
• Young stand demo (NYSKOG + Näslund 1986)
  • Notebook Objectives
  • Prerequisites
  • Sources
  • 1. Define a Swedish site
  • 2. Reconstruct a young stand using NYSKOG equations
  • 3. Sample a tree list from reconstructed stand metrics
  • 4. DBH and Näslund damage proportions
  • 5. Simple forward simulation
  • 6. Damage vs no-damage comparison
• Competition indices on a simulated stand
  • Notebook objectives
  • Prerequisites
  • 1. Generate a random stand
  • 2. Fit and apply the Näslund height imputer
  • 3. Competition indices
  • 4. The selection rule is part of the index
    • The two screens
  • 5. Edge correction
  • 6. Where the numbers come from
  • Summary
    • Next steps
• Composable Callables & Full‑Stack GrowthModel — Practical Guide
  • Notebook Objectives
  • Prerequisites
  • Sources
  • 1) Imports & quick recap
  • 2) Define the scientific components as Callables
  • 3) A full‑stack GrowthModel that chains the callables inside grow()
  • 4) Build a Stand and run the model through a pipeline
  • 5) Angle‑Count stands → pseudo tree‑lists (safe adapter)
  • 6) Using triggers/schedules (DSL)
  • 7) Vectorized aggregate runs with ContextEnsemble
  • 8) Wrap‑up