Module veloren_world::sim::util

Structs

• HybridMulti
  Noise function that outputs hybrid Multifractal noise.
• Worley
  Noise function that outputs Worley noise.

Functions

• build_sources 🔒
• cdf_irwin_hall
  Computes the cumulative distribution function of the weighted sum of k independent, uniformly distributed random variables between 0 and 1. For each variable i, we use weights[i] as the weight to give samples[i] (the weights should all be positive).
• downhill
  Compute the neighbor “most downhill” from all chunks.
• get_horizon_map
  Finds the horizon map for sunlight for the given chunks.
• get_oceans
  Find all ocean tiles from a height map, using an inductive definition of ocean as one of:
• local_cells
  Iterate through all cells adjacent and including four chunks whose top-left point is posi. This isn’t just the immediate neighbors of a chunk plus the center, because it is designed to cover neighbors of a point in the chunk’s “interior.”
• map_edge_factor
  Calculates the smallest distance along an axis (x, y) from an edge of the world. This value is maximal at map_size_lg.chunks() / 2 and minimized at the extremes (0 or map_size_lg.chunks() on one or more axes). It then divides the quantity by cell_size, so the final result is 1 when we are not in a cell along the edge of the world, and ranges between 0 and 1 otherwise (lower when the chunk is closer to the edge).
• uniform_noise
  Compute inverse cumulative distribution function for arbitrary function f, the hard way. We pre-generate noise values prior to worldgen, then sort them in order to determine the correct position in the sorted order. That lets us use (index + 1) / (WORLDSIZE.y * WORLDSIZE.x) as a uniformly distributed (from almost-0 to 1) regularization of the chunks. That is, if we apply the computed “function” F⁻¹(x, y) to (x, y) and get out p, it means that approximately (100 * p)% of chunks have a lower value for F⁻¹ than p. The main purpose of doing this is to make sure we are using the entire range we want, and to allow us to apply the numerous results about distributions on uniform functions to the procedural noise we generate, which lets us much more reliably control the number of features in the world while still letting us play with the shape of those features, without having arbitrary cutoff points / discontinuities (which tend to produce ugly-looking / unnatural terrain).
• uphill

Type Aliases

• DistanceFunction 🔒
• HorizonMap
  NOTE: First component is estimated horizon angles at each chunk; second component is estimated heights of maximal occluder at each chunk (used for making shadows volumetric).
• InverseCdf
  First component of each element of the vector is the computed CDF of the noise function at this index (i.e. its position in a sorted list of value returned by the noise function applied to every chunk in the game). Second component is the cached value of the noise function that generated the index.