Interpolate a function of two variables by rounding (i.e. taking the nearest value), bilinear or bicubic interpolation.
Fint2d(X, Ws, s, method = c("round", "bilinear", "bicubic"), derivs = FALSE, ...)A numeric n by m matrix giving the value of the function at the old coordinates.
A numeric k by 2 matrix of new grid coordinates where k <= m * n.
A numeric k by 2 matrix of old grid coordinates where k <= m * n.
character naming one of “round” (default), “bilinear”, or “bicubic” giving the specific interpolation method to use.
logical, should the gradient interpolatants be returned?
Not used.
If deriv is FALSE, then a matrix is returned whose values correspond to the new coordinates. Otherwise a list is returned with components:
matrix whose values correspond to the new coordinates.
matrices giving the x and y direction gradients of the interpolation.
Method round simply returns the values at each grid point that correspond to the nearest points in the old grid.
Interpolation of a function, say H, is achieved by the following formula (cf. Gilleland et al 2010, sec. 3), where r and s represent the fractional part of their respective coordinate. that is, r = x - g( x ) and s = y - g( y ), where g( x ) is the greatest integer less than x.
sum_k sum_l b_k( r ) * b_l( s ) * H(g( x ) + l, g( y ) + k).
The specific choices for the values of b_l and b_k and their ranges depends on the type of interpolation. For bilinear interpolation, they both range from 0 to 1, and are given by: b_0( x ) = 1 - x and b_1( x ) = x. for bicubic interpolation, they both range from -1 to 2 and are given by:
b_-1( t ) = (2 * t^2 - t^3 - t) / 2
b_0( t ) = (3 * t^3 - 5 * t^2 + 2) / 2
b_1( t ) = (4 * t^2 - 3 * t^3 + t) / 2
b_2( t ) = ((t - 1) * t^2) / 2.
Gilleland and co-authors (2010) Spatial forecast verification: Image warping. NCAR Technical Note, NCAR/TN-482+STR, DOI: 10.5065/D62805JJ.
# NOT RUN {
# see rigider for an example.
# }
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