gradient: Calculate the x and y gradients for a 2D matrix
In richardsc/crMisc: Miscellaneous scripts for Clark Richards

Description Usage Arguments Details Value Author(s) Examples

Calculate the x and y gradients for a 2D matrix

1	gradient(f, x, y, dx, dy)

`f`	the 2D field for which to calculate the gradient
`x,y`	vectors of the `x,y` locations of the cells in `f`
`dx,dy`	scalar giving the `dx,dy` in each direction. If only `dx` is supplied it is assumed `dy` is the same and spits out a warning.

Calculates the gradient in each of the two directions, x and y, corresponding to rows and columns of f. Uses centred differencing in the interior, and forward/backward differencing at the edges. Is more or less equivalent to Matlab's gradient function, except that the sense of x,y is different in that they correspond to rows/columns.

A list containing the directional gradients corresponding to the x,y directions.

Clark Richards

library(oce) # for drawDirectionFields
x <- seq(-2, 2, 0.2)
y <- seq(-2, 2, 0.2)
X <- matrix(expand.grid(x,y)[,1], nrow=length(x))
Y <- matrix(expand.grid(x,y)[,2], nrow=length(x))
F <- X * exp(-X^2 - Y^2) 
g <- gradient(F, dx=0.2, dy=0.2)
contour(x, y, F)
drawDirectionField(as.vector(X), as.vector(Y), g$gx, g$gy, scalex=1, add=TRUE)