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Randomize the output of the Genetic Algorithm

Source: R/random_search.R
random_search.Rd

Jitter the best GA layouts inside their grid cells and re-evaluate energy. Use this as a short post-search after genetic_algorithm(). Terrain and Weibull follow the GA flags when terrain / weibull are NULL. Terrain rasters from the GA are reused when stored in result; pass a DEM to rebuild. Weibull rasters are not stored; pass weibull_src again if needed.

Usage

random_search(
  result,
  area,
  runs = 20,
  best = 1,
  plot = FALSE,
  max_dist = 2.2,
  terrain = NULL,
  weibull = NULL,
  weibull_src = NULL,
  ccl = NULL,
  ccl_roughness = NULL
)

Arguments

result

The resulting matrix of the function genetic_algorithm

area

Site polygon (sf, SpatialPolygons, or coordinate matrix). Must be projected in metres.

runs

How many jittered layouts to try per best start. Default is 20.

best

How many distinct best layouts to refine. Default is 1.

plot

Draw the random-search layouts

max_dist

A numeric value multiplied by the rotor radius to perform collision checks. Default is 2.2

terrain

NULL (default) follows the GA and reuses result$terrainModel. TRUE downloads only if nothing is stored. A DEM rebuilds the model. FALSE skips terrain.

weibull

NULL follows the GA flag. Weibull rasters are not stored; pass weibull_src (or a speed raster as weibull) again. Giving weibull_src is enough; you do not also need weibull = TRUE.

weibull_src

list(k, a) shape and scale rasters (e.g. Global Wind Atlas combined-Weibull-k / combined-Weibull-A).

ccl

Path to a Corine Land Cover raster when terrain is on.

ccl_roughness

Path to the CLC legend CSV (Rauhigkeit_z column).

Value

Returns a list.

See also

Other Randomization: plot_random_search(), random_search_single()

Examples

# \donttest{
new <- random_search(resultrect, sp_polygon, runs = 20, best = 4)
plot_random_search(resultRS = new, result = resultrect, area = sp_polygon, best = 2)


# }