Implementation of Diamond Square algorithm.
This project uses a Makefile
in which several targets are provided for ease of use.
For a minimal setup run make setup to install requirements:
matplotlib==1.5.3numpy==1.11.2)
Running make run will run the code.
Input values are the G_SIZE which defines grid size according to (2^G_SIZE + 1) & G_MAX_RND for minimum and maximum random number. G_SIZE serves as a measure of level which is looped 0 -> G_SIZE. where 0 starts with large shapes and G_SIZE represents the smallest shapes according to below image. Source.
The function _rnjesus takes single input value N and generates a random value between -N -> +N.
The grid is seeded with 4 random values in range -G_MAX_RND -> +G_MAX_RND. Each point is computed by taking the average and adding a random number to it. This random number is reduced at each level see image according to G_SIZE/(level+1). This is a crude implementation but allows for sufficiently random terrain & sufficient smoothness.
Square step (so called as reference points form a square) is computed simply. C is the computed point using marked points below.
NW NE
C
SW SE
Diamond step (so called a reference points form a diamond) requires a wrapping if the index are minimum and maximum values. The loop also has some redundancies as two points will be looked at twice however once a point has been assigned a value it will not be recomputed.
N,W,S,E are computed using surrounding reference points. NN, WW, EE, SS are points which wrap if outside index range.
NN
NW N NE
WW W C E EE
SW S SE
SS
