name: geo-infer description: Geospatial Active Inference framework with 44 modules for ecological, civic, and commercial spatial analysis. Use when working with geospatial data, Active Inference, Bayesian modeling, H3 hexagonal indexing, spatial statistics, or any domain-specific geographic analysis (agriculture, health, economics, risk, climate, energy, transport, marine, forestry, water).

GEO-INFER

A 44-module Python monorepo implementing Active Inference principles for geospatial analysis.

Instructions

Module Discovery

Modules are in GEO-INFER-{NAME}/ directories. Each has its own SKILL.md for detailed guidance.

Analytical Core

| Module | Import | Purpose | |--------|--------|---------| | MATH | geo_infer_math | Spatial statistics, topology, graph theory | | ACT | geo_infer_act | Active Inference (free energy, belief updating) | | BAYES | geo_infer_bayes | Bayesian inference (PyMC, TFP, variational) | | AI | geo_infer_ai | ML pipelines, model selection, spatial features | | COG | geo_infer_cog | Cognitive modeling (attention, memory, trust) | | SPM | geo_infer_spm | Statistical Parametric Mapping (GLM, RFT) |

Spatial-Temporal & Infrastructure

| Module | Import | Purpose | |--------|--------|---------| | SPACE | geo_infer_space | H3 v4 hexagonal indexing, spatial backends | | TIME | geo_infer_time | Time series, temporal analysis, forecasting | | IOT | geo_infer_iot | IoT sensor ingestion (MQTT, streaming) | | DATA | geo_infer_data | ETL pipelines, connectors, format loaders | | API | geo_infer_api | FastAPI REST/GraphQL endpoints | | SEC | geo_infer_sec | Security, threat detection, access control | | OPS | geo_infer_ops | Monitoring, alerting, observability |

Domain Modules

| Module | Import | Purpose | |--------|--------|---------| | AG | geo_infer_ag | Agriculture, soil health, carbon (IPCC Tier 1) | | HEALTH | geo_infer_health | Epidemiology, health access, SaTScan | | ECON | geo_infer_econ | Bioregional markets, call auctions | | RISK | geo_infer_risk | Catastrophe models, Monte Carlo loss | | LOG | geo_infer_log | Logistics, routing, supply chain (PuLP) | | BIO | geo_infer_bio | Biodiversity, habitat connectivity | | CLIMATE | geo_infer_climate | Climate projections, SPI/PDSI indices | | ENERGY | geo_infer_energy | LCOE, renewable siting, grid analysis | | FOREST | geo_infer_forest | Forest cover, carbon stocks, wildfire | | MARINE | geo_infer_marine | Ocean currents, coastal, MPA planning | | EMERGENCY | geo_infer_emergency | SAR, disaster response, evacuation | | TRANSPORT | geo_infer_transport | Traffic (BPR), EWMA forecasting, emissions | | WATER | geo_infer_water | Watershed, hydrology, flood risk |

Agents & Simulation

| Module | Import | Purpose | |--------|--------|---------| | AGENT | geo_infer_agent | Multi-agent systems, telemetry | | ANT | geo_infer_ant | ACO, PSO, ABC swarm optimization | | SIM | geo_infer_sim | Agent-based simulation, Monte Carlo |

Community & Governance

| Module | Import | Purpose | |--------|--------|---------| | CIV | geo_infer_civ | Civic engagement, STEW-MAP | | PEP | geo_infer_pep | Public engagement, CRM | | ORG | geo_infer_org | Organizational modeling | | COMMS | geo_infer_comms | Messaging, notifications, spatial routing | | METAGOV | geo_infer_metagov | Polycentric governance, Ostrom | | NORMS | geo_infer_norms | Compliance, normative inference (Jaccard) | | REQ | geo_infer_req | Requirements, traceability, P3IF |

Presentation & Operations

| Module | Import | Purpose | |--------|--------|---------| | APP | geo_infer_app | Dashboards, agent widgets, map views | | ART | geo_infer_art | Generative geo-art, cartographic design | | EDU | geo_infer_edu | Curricula, exercises, assessment | | PLACE | geo_infer_place | Geocoding, catchment analysis, H3 | | GIT | geo_infer_git | Spatial data versioning, lineage | | TEST | geo_infer_test | Unified test runner, fixtures, markers | | EXAMPLES | geo_infer_examples | Orchestration patterns, workflows | | INTRA | geo_infer_intra | Documentation hub, integration guides |

Architecture & Data Flow

┌──────────────────────────────────────────────────────────┐
│                      Data Sources                        │
│  (files, DBs, APIs, MQTT sensors)                        │
└───────────────────────┬──────────────────────────────────┘
                        ▼
┌──────────────────────────────────────────────────────────┐
│              DATA / IOT (Ingestion Layer)                 │
└───────────────────────┬──────────────────────────────────┘
                        ▼
┌──────────────────────────────────────────────────────────┐
│         SPACE / TIME / PLACE (Indexing Layer)             │
│  H3 v4 tessellation, CRS transforms, temporal indexing   │
└───────────────────────┬──────────────────────────────────┘
                        ▼
┌──────────────────────────────────────────────────────────┐
│     MATH / BAYES / ACT / SPM (Analysis Layer)            │
│  Spatial statistics, Bayesian models, Active Inference    │
└───────────────────────┬──────────────────────────────────┘
                        ▼
┌──────────────────────────────────────────────────────────┐
│    AI / AGENT / ANT / SIM (Intelligence Layer)           │
│  ML pipelines, agent systems, swarm optimization         │
└───────────────────────┬──────────────────────────────────┘
                        ▼
┌──────────────────────────────────────────────────────────┐
│   Domain Modules (Application Layer)                     │
│  AG, HEALTH, ECON, RISK, LOG, BIO, CLIMATE, ENERGY,     │
│  FOREST, MARINE, EMERGENCY, TRANSPORT, WATER             │
└───────────────────────┬──────────────────────────────────┘
                        ▼
┌──────────────────────────────────────────────────────────┐
│      API / APP / ART (Presentation Layer)                │
│  REST endpoints, dashboards, visualizations              │
└──────────────────────────────────────────────────────────┘

Common Patterns

# Graceful dependency imports (every __init__.py)
try:
    from .core.engine import Engine
    HAS_ENGINE = True
except ImportError:
    HAS_ENGINE = False

# H3 v4 API (never use legacy h3.geo_to_h3)
import h3
cell = h3.latlng_to_cell(lat, lng, resolution)
lat, lng = h3.cell_to_latlng(cell)

# Module installation
# uv pip install -e ./GEO-INFER-MATH

Testing

# All modules
uv run python GEO-INFER-TEST/run_unified_tests.py

# Single module
uv run python -m pytest GEO-INFER-MATH/tests/ -v

# With coverage
uv run python -m pytest GEO-INFER-MATH/tests/ --cov=GEO-INFER-MATH/src

Modular Hygiene

uv sync --all-packages --all-extras
uv run python GEO-INFER-TEST/validate_repo_contracts.py --strict-source-language --skip-import-smoke

Root pyproject.toml, uv.lock, and .python-version define the uv workspace.
Each module keeps importable behavior under src/ and at least four pytest files under tests/.
Planned work belongs in root TODO.md or a tracked issue, not source or test task markers.
Importable modules use logging.getLogger(__name__); CLI entrypoints configure process-wide logging.

Examples

Source-backed spatial indexing example

from geo_infer_space import cell_to_latlng, latlng_to_cell

cell = latlng_to_cell(37.7749, -122.4194, resolution=9)
latitude, longitude = cell_to_latlng(cell)
print(cell, latitude, longitude)

Cross-module examples belong in GEO-INFER-EXAMPLES/examples/ and must be checked against the current exports of every participating package before being described as runnable.

GeoLibre export example

Emit an H3 grid as a .geolibre.json project for the GeoLibre viewer (mirrors opengeos/GeoLibre's project format, version 0.1.0; one-way integration — GEO-INFER produces, GeoLibre presents):

from geo_infer_space.core import (
    build_h3_grid_project, geojson_layer, write_project,
)

project = build_h3_grid_project(
    "H3 grid", grid_geojson, center=[-122.25, 37.65], zoom=9
)
write_project(project, "h3_grid.geolibre.json")

Related optional surfaces: geo_infer_space.core.h3_policy (resolution suggestion + hard-cap guard), geo_infer_space.core.algorithm_registry, geo_infer_space.core.whitebox_bridge, geo_infer_data.utils.duckdb_spatial, and geo_infer_agent.core.llm_proxy. See the runnable example at GEO-INFER-EXAMPLES/examples/getting_started/geolibre_export/.

Guidelines

No mock/stub/placeholder code — every function must have real logic
Active Inference first — ground implementations in free energy minimization
Type hints everywhere — full annotations on all parameters and returns
H3 v4 only — use latlng_to_cell, not legacy geo_to_h3
Graceful degradation — optional deps via try/except ImportError
Logger, not print — use structured logging in all modules
Root task ledger — use TODO.md or issues for future work; keep source and tests free of task markers
uv workspace hygiene — keep root pyproject.toml, .python-version, and uv.lock as the shared environment contract
Check each module's SKILL.md for domain-specific rules and integrations

Geo-Infer : analyse géospatiale avancée

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