Generating random raster landscapes for generating performance benchmarking cases

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Generating random raster landscapes for generating performance benchmarking cases

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Last edited May 8, 2024

Created on May 8, 2024

This example generates 500 discrete and 500 continuous random raster landscapes as ASCII grid files for performance benchmarking. It uses the `nlmpy.mpd` function to create midpoint displacement neutral landscape models, then classifies the discrete layers with `nlmpy.classifyArray` and random integer thresholds. Each raster is exported with `nlmpy.exportASCIIGrid`, including randomized georeferencing metadata via a lambda function that jitters the corner coordinates. The code relies on NumPy’s seeded random number generator and Python’s `random` module to ensure reproducible but varied outputs across the 100×100 cell grids.

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