neighbors
Calculates universal matrix for neighbor's indices depending on the CellularPopulation.dimens. To calculate actual coordinates of neighbors for a target cell, need to sum coordinates from the universal matrix with the target cell coordinates.
NOTE Be careful, before applying the calculated coordinates of neighbors they must go through a toroidalShapeIndicesFilter.
Example if usage universal matrix for calculating neighbor's indices for different target cells:
val moore = VonNeumann(radius = 1)
val dimens = Dimens.square(length = 3)
val (indicesOneArray, indicesNArray) = moore.neighborsIndicesMatrix(dimens)
println("Universal matrix in a projection one-dimensional array: ${indicesOneArray.joinToString()}")
println("Universal matrix in n-dimensional array: ${indicesNArray.joinToString { "(${it.joinToString()})" }}")
val actualNeighborsPosition2 = toroidalShapeIndicesFilter(
position = 2,
dimens = dimens,
indicesOneArray = indicesOneArray,
indicesNArray = indicesNArray,
)
val actualNeighborsPosition3 = toroidalShapeIndicesFilter(
position = 3,
dimens = dimens,
indicesOneArray = indicesOneArray,
indicesNArray = indicesNArray,
)
println("Actual neighbors indices for position 2: ${actualNeighborsPosition2.joinToString()}")
println("Actual neighbors indices for position 3: ${actualNeighborsPosition3.joinToString()}")
// Console:
Universal matrix in a projection one-dimensional array: -1, -3, 3, 1
Universal matrix in n-dimensional array: (-1, 0), (0, -1), (0, 1), (1, 0)
Actual neighbors indices for position 2: 1, 8, 5, 0
Actual neighbors indices for position 3: 5, 0, 6, 4Content copied to clipboard
Return
pair of neighbors indices where:
first - initial neighbors coordinates (indices) in a projection one-dimensional array of CellularPopulation
second - initial neighbors coordinates (indices) in an n-dimensional array of CellularPopulation
See also
toroidal