Module forma.subpattern

Sub-pattern finders.

Functions for the selection of sub-patterns of various forms from a parent pattern. The simplest of these is the random sampling of a fraction of cells from the parent.

Several of these finders return a table of all relevant sub-patterns. For example the segments method which returns a table of all contiguous (according to some neighbourhood) sub-patterns by using a floodfill.

In addition to the subpattern finders, a print_patterns utility is provided to render these tables of sub-patterns into text.

Sub-patterns

mask (ip, mask) Masked subpattern.
random (ip, ncells, rng) Random subpattern.
poisson_disc (ip, distance, radius, rng) Poisson-disc random subpattern.
mitchell_sample (ip, distance, n, k, rng) Mitchell's best candidate sampling.
perlin (ip, freq, depth, thresholds, rng) Perlin noise sampling.
floodfill (ip, ipt, nbh) Returns the contiguous sub-pattern of ip that surrounts cell ipt
maxrectangle (ip) Find the maximal contiguous rectangular area within a pattern.

Lists of sub-patterns

segments (ip, nbh) Generate a table of contiguous 'segments' or sub-patterns.
enclosed (ip, nbh) Returns a table of 'enclosed' segments of a pattern.
bsp (ip, th_volume) Generate subpatterns by binary space partition.
neighbourhood_categories (ip, nbh) Determine subpatterns for all neighbourhood categories.
voronoi (seeds, domain, measure) Generate Voronoi tesselations of cells in a domain.
voronoi_relax (seeds, domain, measure, max_ite) Generate (approx) centroidal Voronoi tessellation.

Utilities

print_patterns (domain, segments, chars) Print a table of forma.patterns.


Sub-patterns

mask (ip, mask)
Masked subpattern. Generate a subpattern by applying a boolean mask to an input pattern.

Parameters:

  • ip the pattern to be masked.
  • mask a function that takes a cell and returns true if the cell passes the mask

Returns:

    A pattern consisting only of those cells in domain which pass the mask argument.
random (ip, ncells, rng)
Random subpattern. For a given domain, returns a pattern sampling randomly from it, generating a random subset with a fixed fraction of the size of the domain.

Parameters:

  • ip pattern for sampling a random pattern from
  • ncells the number of desired cells in the sample
  • rng (optional) a random number generator, following the signature of math.random.

Returns:

    a pattern of ncells cells sampled randomly from domain
poisson_disc (ip, distance, radius, rng)
Poisson-disc random subpattern. Sample a domain according to the Poisson-disc procedure. For a given distance measure distance, this generates samples that are never closer together than a specified radius. While much slower than subpattern.random, it provides a more uniform distribution of points in the domain (simmilar to that of subpattern.voronoi_relax).

Parameters:

  • ip domain pattern to sample from
  • distance a measure of distance between two cells d(a,b) e.g cell.euclidean
  • radius the minimum separation in distance between two sample points.
  • rng (optional) a random number generator, following the signature of math.random.

Returns:

    a Poisson-disc sample of domain
mitchell_sample (ip, distance, n, k, rng)
Mitchell's best candidate sampling. Generates an approximate Poisson-disc sampling by Mitchell's algorithm. Picks 'k' sample point attempts at every iteration, and picks the candidate that maximises the distance to existing samples. Halts when n samples are picked.

Parameters:

  • ip domain pattern to sample from
  • distance a measure of distance between two cells d(a,b) e.g cell.euclidean
  • n the requested number of samples
  • k the number of candidates samples at each iteration
  • rng (optional) a random number generator, following the signature of math.random.

Returns:

    an approximate Poisson-disc sample of domain
perlin (ip, freq, depth, thresholds, rng)
Perlin noise sampling. Samples an input pattern by thresholding a Perlin-noise pattern in the domain. This function takes an initial sampling frequency, and computes perlin noise over the input pattern by taking the product of depth successively halved frequencies. A table of subpatterns are then returned, consisting of the perlin noise function thresholded at requested levels.

Parameters:

  • ip pattern upon which the thresholded noise sampling is to be performed.
  • freq (float) frequency of desired perlin noise
  • depth (int), sampling depth.
  • thresholds table of sampling thresholds (between 0 and 1).
  • rng (optional) a random number generator, following the signature of math.random.

Returns:

    a table of patterns, one per threshold entry.
floodfill (ip, ipt, nbh)
Returns the contiguous sub-pattern of ip that surrounts cell ipt

Parameters:

  • ip pattern upon which the flood fill is to be performed
  • ipt a cell specifying the origin of the flood fill
  • nbh defines which neighbourhood to scan in while flood-filling (default 8/moore)

Returns:

    a forma.pattern consisting of the contiguous segment about cell
maxrectangle (ip)
Find the maximal contiguous rectangular area within a pattern.

Parameters:

  • ip the input pattern

Returns:

    The subpattern of ip consisting of its largest contiguous rectangular area.

Lists of sub-patterns

segments (ip, nbh)
Generate a table of contiguous 'segments' or sub-patterns. This performs a series of flood-fill operations until all pattern cells are accounted for in the sub-patterns

Parameters:

  • ip pattern for which the segments are to be extracted
  • nbh defines which neighbourhood to scan in while flood-filling (default 8/moore)

Returns:

    A table of forma.patterns consisting of contiguous sub-patterns of ip.
enclosed (ip, nbh)
Returns a table of 'enclosed' segments of a pattern. Enclosed areas are the inactive areas of a pattern which are completely surrounded by active areas

Parameters:

  • ip pattern for which the enclosed areas should be computed
  • nbh defines which directions to scan in while flood-filling (default 4/vn)

Returns:

    A table of forma.patterns comprising the enclosed areas of ip.
bsp (ip, th_volume)
Generate subpatterns by binary space partition. This works by finding all the contiguous rectangular volumes in the input pattern and running a binary space partition on all of them. The partitions are then returned in a table.

The BSP is controlled by the threshold volume parameter. The algorithm will recursively subdivide every rectangular area evenly in two until the volume of the largest remaining area is less than th_volume.

Parameters:

  • ip the pattern for which the BSP will be run over
  • th_volume the highest acceptable volume for each final partition
neighbourhood_categories (ip, nbh)
Determine subpatterns for all neighbourhood categories. Each neighbourhood has a number of possible combinations or categories of active cells. This function categorises each cell in an input pattern into one of the neighbourhood's categories.

Parameters:

  • ip the pattern in which cells are to be categorised
  • nbh the forma.neighbourhood used for the categorisation

Returns:

    A table of #nbh patterns, where each cell in ip is categorised.
voronoi (seeds, domain, measure)
Generate Voronoi tesselations of cells in a domain.

Parameters:

  • seeds the set of seed cells for the tesselation
  • domain the domain of the tesselation
  • measure the measure used to judge distance between cells

Returns:

    A table of Voronoi segments.
voronoi_relax (seeds, domain, measure, max_ite)
Generate (approx) centroidal Voronoi tessellation. Given a set of prior seeds and a domain, this iterates the position of the seeds until they are approximately located at the centre of their Voronoi segments. Lloyd's algorithm is used.

Parameters:

  • seeds the original seed points to be relaxed
  • domain the domain to be tesselated
  • measure the distance measure to be used between cells
  • max_ite (optional) maximum number of iterations of relaxation (default 30)

Returns:

  1. A table of resuling Voronoi segments.
  2. A pattern consisting of the voronoi segment centres.
  3. A bool, true if the algorithm converged, false if not.

Utilities

print_patterns (domain, segments, chars)
Print a table of forma.patterns. Prints a table of pattern segments to io.output. If provided, a table of segment labels can be used, with one entry per segment.

Parameters:

  • domain the basic pattern from which the segments were generated.
  • segments the table of segments to be drawn.
  • chars the characters to be printed for each segment (optional).
generated by LDoc 1.4.6 Last updated 2019-01-07 21:10:29