isobands

An easy way to make filled contour maps with Python.

isobands converts a regular two-dimensional xarray raster into filled contour polygons backed by a GeoPandas GeoDataFrame.

Install

isobands needs an installed, matching osgeo.gdal Python binding. If your Conda or system-managed environment already provides one of the tested baselines, install the package directly:

pip install isobands

For a pip-managed binding, install matching native GDAL 3.13.2 development files, then use the recommended newest tested and installable extra:

pip install "isobands[gdal313]"

GDAL 3.10.2, 3.11.5, and 3.12.2 remain tested compatibility choices through the matching gdal310, gdal311, and gdal312 extras. See the installation guide for exact versions and platform instructions.

Quick start

import numpy as np
import xarray as xr

import isobands

data = xr.DataArray(
    np.array([[0.0, 1.0, 2.0], [1.0, 2.0, 3.0], [2.0, 3.0, 4.0]]),
    dims=("y", "x"),
    coords={"x": [0.0, 1.0, 2.0], "y": [2.0, 1.0, 0.0]},
)
bands = isobands.from_raster(data, levels=[1.5, 2.5], crs="EPSG:4326")
print(bands[["min_value", "max_value", "geometry"]])

The result always has the stable min_value, max_value, and geometry columns and a GeoPandas CRS. Exactly one of levels or interval is required. Use levels for strictly increasing interior thresholds, or interval for integral thresholds. Values equal to a threshold belong to the upper band.

Regular one-dimensional rectilinear coordinates are required, and coordinate names do not imply a CRS. Pass crs= explicitly when metadata is absent or ambiguous. Explicit finite nodata takes precedence over _FillValue and missing_value; otherwise nonfinite cells are excluded. Dask-backed arrays are materialized eagerly for GDAL's in-memory dataset. See the guide for usage examples and the API reference.

Real-world example

The runnable NOAA/NCEP example uses the pinned fixture in examples/data/, calls from_raster() with Kelvin levels and EPSG:4326, checks the schema, CRS, and geometry validity, and dissolves components with GeoPandas:

python examples/air_temperature.py

The ERA5 MapLibre example downloads the global daily high temperature for August 16, 2020, creates five-degree Celsius isobands, and writes GeoJSON for the accompanying era5_maplibre.html page. It requires a Copernicus Climate Data Store API key and the optional cdsapi, h5netcdf, and h5py packages.

Documentation

The hosted documentation is intended for palewi.re/docs/isobands/. The source is in docs/, with a single-page guide covering installation, quick start, the API reference, and the MapLibre example. Benchmarks and their reference data remain in benchmarks/.

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