TransitionCompassModel — Multi-Sector Climate Pathway Calculation Engine

Python library that computes emission, energy, and environmental indicator pathways sector by sector, given policy lever settings. Powers the TransitionCompassViz visualization platform.

Live Platforms

• Production: https://transition-compass.epfl.ch/
• Development: https://transition-compass-dev.epfl.ch/

Dual-Repository Architecture

This project is split into two repositories:

• Model researchers (sector calculations, data, parameters): work here
• App developers (frontend, API, charts, UI): work in speed-to-zero

Architecture

The model is structured around independent sector modules coordinated by an interaction runner:

transition_compass_model/
├── model/
│   ├── interactions.py          # Runs all sectors and resolves cross-sector dependencies
│   ├── agriculture_module.py
│   ├── ammonia_module.py
│   ├── buildings_module.py
│   ├── buildings/               # Sub-modules for buildings sector
│   ├── climate_module.py
│   ├── district_heating_module.py
│   ├── emissions_module.py
│   ├── energy_module.py         # EnergyScope LP (Pyomo/AMPL)
│   ├── energy/                  # Sub-modules for energy sector
│   ├── forestry_module.py
│   ├── industry_module.py
│   ├── landuse_module.py
│   ├── lca_module.py
│   ├── lifestyles_module.py
│   ├── minerals_module.py
│   ├── oilrefinery_module.py
│   ├── power_module.py
│   ├── transport_module.py
│   └── transport/               # Sub-modules for transport sector
├── config/
│   └── lever_position.json      # Default lever settings (1–4 ambition levels)
└── _database/
    └── data/
        └── datamatrix/          # Regional data matrices (Vaud, Switzerland, EU27)

Sectors: Agriculture, Ammonia, Buildings, Climate, District Heating, Emissions, Energy (LP), Forestry, Industry, Land Use, LCA, Lifestyles, Minerals, Oil Refinery, Power, Transport

Given a set of policy lever values (integers 1–4 representing ambition levels), interactions.py runs the relevant sector modules and returns time-series results for emissions, energy demand, and environmental indicators.

Install

The package is published on PyPI:

pip install transition-compass-model

Pin to a specific version:

pip install transition-compass-model==1.2.3

Binary data files (.pickle) are bundled directly in the PyPI wheel — no Git LFS required.

Git LFS (for developers)

The repository uses Git LFS to store binary data files (.pickle, .pdf). If you clone the repo (for development or research), you need Git LFS installed:

git lfs install   # once per machine
git clone https://github.com/2050Calculators/transition-compass-model.git

After cloning, LFS files are fetched automatically. If you see small pointer files instead of real data, run git lfs pull.

Usage

from transition_compass_model.model.common.config_loader import load_lever_config
from transition_compass_model.model.common.auxiliary_functions import (
    filter_country_and_load_data_from_pickles,
)
from transition_compass_model.model.interactions import runner
import logging

logger = logging.getLogger(__name__)

lever_setting = load_lever_config()
years_setting = [1990, 2023, 2025, 2050, 5]  # [start_ots, end_ots, start_fts, end_fts, fts_step]
country_list = ["Switzerland", "EU27", "Vaud"]
sectors = ["climate", "lifestyles", "buildings", "transport", "industry",
           "forestry", "agriculture", "ammonia", "lca"]

DM_input = filter_country_and_load_data_from_pickles(
    country_list=country_list, modules_list=sectors
)

output, KPI = runner(lever_setting, years_setting, DM_input, sectors, logger)

To customise lever settings, edit transition_compass_model/config/lever_position.json (each value is an integer 1–4).

Local Development

Standalone (model only)

git lfs install  # If not already done
git clone https://github.com/2050Calculators/transition-compass-model.git
cd transition-compass-model
make install     # Install deps + activate pre-commit hooks

Run the full model:

uv run python -m transition_compass_model.model.interactions_localrun

Run individual sector modules:

uv run python -m transition_compass_model.model.transport_module
uv run python -m transition_compass_model.model.buildings_module
# etc.

With the app (see model changes in the UI)

Clone both repos as siblings and use the app's local install:

parent-dir/
├── speed-to-zero/                  ← app repo
└── transition-compass-model/       ← this repo

cd speed-to-zero
make install-dev   # Installs deps + editable model from sibling folder
make run           # Start app — model changes are reflected immediately

Verify which model is active:

# From speed-to-zero/
cd backend && make check-model
# Local mode:  path points to ../../transition-compass-model/
# Remote mode: path points inside .venv/lib/.../site-packages/

See DEVELOPMENT.md for full details (IDE setup, switching between local/remote model, etc.) and CONTRIBUTING.md for the contribution workflow (branching, commits, pull requests).

Versioning and Releases

Releases follow Semantic Versioning: vMAJOR.MINOR.PATCH

Release flow

1. Commit and push all model changes to main
2. Tag and push: git tag v1.2.3 && git push origin v1.2.3
3. GitHub Actions publishes the new version to PyPI and dispatches a model-updated event to the app repo
4. A bump PR is created automatically in speed-to-zero (chore/bump-model-v1.2.3 → dev) — pins the new PyPI version and regenerates the lock file
5. Review and merge the PR — CI validates the build, then deploys

License

Apache License 2.0