Sampling

StatsBase.sample — Function
sample([rng], object, method)

Sample elements or points from geometric object with method. Optionally, specify random number generator rng.

sample([rng], object, nsamples, [weights], replace=false)

Generate nsamples samples from spatial object uniformly or using weights, with or without replacement depending on replace option.

Meshes.DiscreteSamplingMethod — Type
DiscreteSamplingMethod

A method for sampling from discrete representations of geometric objects such as meshes or collections of geometries.

Meshes.ContinuousSamplingMethod — Type
ContinuousSamplingMethod

A method for sampling from continuous representations of geometric objects. In this case, geometric objects are interpreted as a set of points in the embedding space.

Discrete sampling

Meshes.UniformSampling — Type
UniformSampling(size, replace=false)

Sample elements uniformly from a given domain/data. Produce a sample of given size with or without replacement depending on the replace option.

Meshes.WeightedSampling — Type
WeightedSampling(size, [weights]; replace=false)

Sample elements from a given domain/data using weights. Produce a sample of given size with or without replacement depending on the replace option. By default weights are uniform.

Meshes.BallSampling — Type
BallSampling(radius; [options])

A method for sampling isolated elements from a given domain/data according to a norm-ball of given radius.

Options

  • metric - Metric for the ball (default to Euclidean())
  • maxsize - Maximum size of the resulting sample (default to none)

Continuous sampling

Meshes.RegularSampling — Type
RegularSampling(n1, n2, ..., np)

Generate samples regularly using n1 points along the first parametric dimension, n2 points along the second parametric dimension, ..., np points along the last parametric dimension.

Examples

Sample sphere regularly with 360 longitudes and 180 latitudes:

sample(Sphere((0,0,0), 1), RegularSampling(360, 180))
Meshes.HomogeneousSampling — Type
HomogeneousSampling(size)

Generate sample of given size from geometric object according to a homogeneous density.

Meshes.MinDistanceSampling — Type
MinDistanceSampling(α, ρ=0.65, δ=100, metric=Euclidean())

Generate sample from geometric object such that all pairs of points are at least α units of distance away from each other. Optionally specify the relative radius ρ for the packing pattern, the oversampling factor δ and the metric.

This method is sometimes referred to as Poisson disk sampling or blue noise sampling in the computer graphics community.

References