ppgrid
mrzk.io- Category
- Developer Tools
- Rank
- No. 2346Tools index
Previous survey · No. 2261 ·
- Pricing
- Open Source
- Type
- TOOL
- Use case
- Data Processing
- Date
About
ppgrid is an open-source GIS library that rasterizes large point datasets using a modified Inverse Distance Weighting algorithm, precalculating which points intersect which grid cells to avoid the multiplicative O(N×M) cost of traditional IDW implementations like those in gdal_grid or GRASS. Its author reports processing 16 million points on a modest laptop, roughly 17 times faster than standard IDW tools, though it has not yet been validated for statistical correctness beyond visualization use.
What it does
The author's blog post presents ppgrid as a package on PyPI for turning very large point datasets into smooth map rasters. Points are binned to grid cells once, then a coarse-to-fine pyramid fills sparse areas, approximating inverse distance weighting. The author frames it as a visualisation aid, not a source of values for further calculation.
Stated on the product site
- Distribution
- Package on PyPI, source code on GitHub (per the author)
- Maturity
- Alpha, by the author's own description
- Intended use
- Visualisation only; the author does not rely on raster accuracy
- Method
- Pull-push pyramid approximation of inverse distance weighting
- Output format
- Percentile values stored in an int16 GeoTIFF
- Support raster
- Second output records the spatial scale behind each estimate
- Calibration
- Fill distance chosen by spatially blocked cross-validation
- Author-reported benchmark
- gdal_grid about 17x slower at 100m resolution on a synthetic 100K-point set
Not stated on the site
- The page does not report how closely the output matches exact inverse distance weighting; the author lists that comparison as future work.
- The page does not state a license.
- The page shows benchmarks for 100K synthetic points on one laptop only; timings at tens of millions of points are not shown.
- Behaviour with global extents and awkward coordinate systems is not shown; the author says those quirks have not been addressed yet.
- Supported Python versions, install steps and the programming interface are not shown on the page.
Written from the product site at mrzk.io.
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