hextraj

Hex labelling of trajectory data.

Hex region	OD connectivity

hex_aggregation.ipynb	hex_conn_dask.ipynb

Maps lon/lat positions to a projected hexagonal grid and provides tools for aggregation and connectivity analysis.

hex_counts — heat maps and density aggregation
hex_connectivity — origin-destination matrices
hex_connectivity_power — multi-generation transport probabilities
hex_connectivity_dask — lazy dask-native connectivity for large datasets
Full dask support throughout

Getting started

Explore the notebooks:

hex_conn.ipynb — Label NW Shelf trajectories, compute OD connectivity, visualise choropleth + edge overlay.
hex_aggregation.ipynb — Grid construction, choropleth aggregation, and weighted edges.
hex_grid_construction.ipynb — Rectangle and region hex grids.
hex_analysis.ipynb — Analysis functions (hex_counts, hex_connectivity, hex_connectivity_power).
hex_conn_dask.ipynb — Dask-native connectivity for large datasets.

Installation

pip install hextraj

With dask, scipy, and cartopy:

pip install hextraj[full]

Or from source:

pip install git+https://github.com/willirath/hextraj.git@main

Quick example

from hextraj import HexProj

hp = HexProj(lon_origin=-3.0, lat_origin=54.0, hex_size_meters=50_000)

# Label positions → int64 hex IDs
hex_ids = hp.label(lon, lat)

# Build a GeoDataFrame with Polygon geometries
gdf = hp.to_geodataframe(hp.region_of_hexes(region_polygon))
gdf["count"] = counts.reindex(gdf.index).fillna(0)
gdf.plot(column="count", cmap="YlOrRd")

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