mesa.ecospatial.local_spatial_stats
- mesa.ecospatial.local_spatial_stats(grid, mode='MoranI', tissue_only=False, p_value=0.01, seed=42, plot_weights=False, return_stats=False)
Compute local indicators of spatial association (LISA) for local spatial autocorrelation, and return significant hotspots and coldspots.
- Parameters:
grid (numpy.ndarray) – The 2D grid of diversity indices to be analyzed.
mode (str, optional (default='MoranI')) – The spatial statistic to use. One of {‘MoranI’, ‘GearyC’, ‘GetisOrdG’}.
tissue_only (bool, optional (default=False)) – If True, the analysis is restricted to tissue regions.
p_value (float, optional (default=0.01)) – The p-value cutoff for significance.
seed (int, optional (default=42)) – Random seed for reproducibility.
plot_weights (bool, optional (default=False)) – If True, visualize the spatial weights matrix.
return_stats (bool, optional (default=False)) – If True, return LISA alongwith hot/cold spots
- Returns:
hotspots (numpy.ndarray) – Boolean array indicating hotspots (high value surrounded by high values).
coldspots (numpy.ndarray) – Boolean array indicating coldspots (low value surrounded by low values).