RandomPoint

RandomPoint[reg]

gives a pseudorandom point uniformly distributed in the region reg.

RandomPoint[reg,n]

gives a list of n pseudorandom points uniformly distributed in the region reg.

RandomPoint[reg,{n1,n2,}]

gives an n1× n2× array of pseudorandom points.

RandomPoint[reg,,{{xmin,xmax},}]

restricts to the bounds .

Details and Options

Examples

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Basic Examples  (3)

Generate a list of points in a unit disk:

Generate multiple lists of points on a unit circle:

Generate a list of points in a standard cylinder:

Scope  (22)

Basic Uses  (5)

Generate a point in a unit ball region:

Generate a list of points for a triangle region:

Generate multiple lists of points for a unit disk region:

Generate points on an unbounded region within given bounds:

The random points are restricted to :

Generate points on an unbounded region within given bounds in :

Special Regions  (6)

Regions in :

Regions in :

Visualize region points in :

Regions in :

Visualize region points in :

Regions in :

Formula Regions  (3)

Implicit regions:

Visualize region points in :

Parametric regions:

Mesh Regions  (4)

MeshRegion in 2D:

In 3D:

BoundaryMeshRegion in 2D:

BoundaryMeshRegion in 3D:

Derived Regions  (4)

RegionIntersection of two regions:

RegionUnion of mixed-dimensional regions:

Points are generated for the maximum dimensional component:

TransformedRegion:

RegionBoundary:

Applications  (24)

2D Galleries  (9)

Generate a list of uniform random unit vectors in :

Visualize a parametric heart curve:

Parametric butterfly curve:

Implicit trifolium curve:

Graphics scene:

Implicit Lissajous region:

Mixed implicit and parametric region:

Country polygon:

Text primitive:

3D Galleries  (6)

Generate a list of uniform random unit vectors in :

Parametric helix curve:

Implicit Viviani's curve:

Parametric torus surface:

Implicit eight solid:

Graphics3D scene:

Monte Carlo Methods  (2)

Perform Monte Carlo integration to estimate the area of a unit disk:

Get the region bounds:

Uniformly sample over the bounding box of the region:

Count the number of samples inside the region:

Get the ratio of samples inside the region to the total number of sample points:

Get the bounding area:

Get the approximate area of the region:

Visualize the Minkowski sum (orange) of two regions:

Sum of points from two regions gives points of the Minkowski sum region:

Region Relations  (3)

Compute an approximate bounding box for a region from random samples. The resulting bounding will be a subset of the true bounding box:

Compare with its region bounds:

Show that a region is not a subset of another:

Check if any point from a set of random points in the disk are not in the square:

Visualize the random points in the disk that are not in the square:

Determine that two regions are not equal:

Check if any point from a set of random points in the disk is not in the square, or vice versa:

Approximate Convexity  (2)

Determine that a region is not convex by sampling, and show that there is a convex combination of the samples that is not a member of the original region:

Generate pairwise convex combinations of random points within the region:

If a point on a pairwise convex combination is not in the region, then the region is not convex:

Alternatively generate and test points in a convex hull of points:

Compute the approximate convex hull of a region from random points within the region:

Nearest and Farthest Points  (2)

Find an approximate nearest point in a region by sampling the region and computing the nearest point to the samples. This gives an upper bound for the distance to the region:

Find the nearest point from a set of random points in the region:

Compare the resulting distance to the true minimum distance to the region:

Define a function that finds an approximate farthest point in a region:

Find the farthest point on a region from a given point:

Properties & Relations  (6)

RandomPoint will generate points with uniform density:

Choosing random coordinate points from a region of points:

Corresponds to RandomChoice of coordinate points:

Choosing random points from a Cuboid region:

Corresponds to RandomVariate of a UniformDistribution:

Choosing random points from a Disk region:

Corresponds to RandomVariate of a WignerSemicircleDistribution:

Choosing random coordinate points from a Triangle region:

Corresponds to RandomVariate of a TriangularDistribution:

FindInstance can generate exact instances for special and formula regions:

However, instances are not uniform:

Introduced in 2015
 (10.2)