bvn: Calculate bivariate normal density of image surface

In ClairBee/IO.Pixels: Functions for analysis of distribution of dead pixels (part of Inside Out project).

Description

Calculate the bivariate Gaussian density of an image surface with given parameters (rho fixed at 0)

Usage

bvn(par, obs)

Arguments

par	Vector of named parameters A (constant offset), x0 (x-origin), y0 (y-origin), sig.x (SD over x), sig.y (SD over y)
obs	Data frame with columns x and y containing coordinates at which to evaluate the function.

Value

Vector containing calculated density

Examples

gv <- setNames(melt(pw.m[,,"grey", "160430"]), nm = c("x", "y", "z"))
tmp <- bvn(c(A = 15000, x0 = 1024.5, y0 = 1024.5, sig.x = 500, sig.y = 500), gv)
pixel.image(array(tmp, dim = c(2048, 2048)))

ClairBee/IO.Pixels documentation built on May 6, 2019, 11:50 a.m.