griddata: Distribute a point set onto a regular grid

In obreschkow/cooltools: Practical Tools for Scientific Computations and Visualizations

Distribute a point set onto a regular grid

Description

Distributes a set of points in D dimensions onto a regular, D-dimensional grid, using a fast nearest neighbor algorithm. Weights can be used optionally.

Usage

griddata(x, w = NULL, n = 10, min = NULL, max = NULL, type = "counts")

Arguments

x	N-element vector (if D=1) or N-by-D matrix (if D>1), giving the Cartesian coordinates of N points in D dimensions.
w	optional N-element vector with weights.
n	scalar or D-element vector specifying the number of equally space grid cells along each dimension.
min	optional scalar or D-element vector specifying the lower bound of the grid. If not given, min is adjusted to the range of x.
max	optional scalar or D-element vector specifying the upper bound of the grid. If not given, max is adjusted to the range of x.
type	character string ("counts", "density", "probability") specifying the normalization of the output: "counts" (default) returns the number of points (multiplied by their weights, if given) in each cell; thus the total number of points (or total mass, if weights are given) is sum(field). "density" returns the density, such that the total number of points (or total mass, if weights are given) is sum(field) dV. "probability" returns a probability density, such that sum(field) dV=1.

Value

Returns a list of items

field	D-dimensional array representing the value in each grid cell. See parameter type for more details.
grid	List of D elements with the grid properties along each dimension. n: number of grid cells; mid: n-vector of mid-cell coordinates; breaks: (n+1)-vector of cell edges; lim: 2-vector of considered range; delta: cell width.
dV	Single number representing the volume of the D-dimensional grid cells.

Author(s)

Danail Obreschkow

Examples

# Distribute 1-dimensional data onto a regular grid
npoints = 1e4
x = rnorm(npoints)
g = griddata(x,min=-3,max=3,n=100,type='probability')
curve(dnorm(x),-3,3)
points(g$grid$mid,g$field,pch=16)

# Distribute 2-dimensional data onto a regular grid
x = runif(100,max=2)
y = runif(100)
g = griddata(cbind(x,y),min=c(0,0),max=c(2,1),n=c(20,10))
image(g$grid[[1]]$breaks,g$grid[[2]]$breaks,g$field,
      asp=1,col=grey.colors(100,0,1),xlab='x',ylab='y')
points(x,y,col='red',pch=16)

# ... same with weights
w = runif(100)
g = griddata(cbind(x,y),w,min=c(0,0),max=c(2,1),n=c(20,10))
image(g$grid[[1]]$breaks,g$grid[[2]]$breaks,g$field,
      asp=1,col=grey.colors(100,0,1),xlab='x',ylab='y')
points(x,y,col='red',pch=16,cex=w)

obreschkow/cooltools documentation built on Nov. 16, 2024, 2:46 a.m.