This algorithm distributes points randomly across the plane with uniform distribution.
Each point's position is independent of other points.
points: 256, dimension: 800x600
Metric
Value
How to Read the Metrics
Avg Nearest Neighbor Distance: The average distance between each point and its
nearest neighbor. Lower values indicate denser clustering.
Voronoi Cell Area Variation: The standard deviation of the areas of the Voronoi
cells. Lower values suggest a more uniform distribution.
Grid-Based Density: The standard deviation of the number of points in each grid
cell. Lower values indicate a more uniform density distribution.
Clark-Evans Index: Compares the observed mean nearest neighbor distance to the
expected mean nearest neighbor distance in a random distribution. Values less than 1 indicate
clustering, values around 1 indicate randomness, and values greater than 1 indicate uniformity.
Spatial Autocorrelation (Moran's I): Measures the degree to which points are
clustered or dispersed. Positive values indicate clustering, negative values indicate dispersion,
and values around 0 indicate randomness.