nestSearch | R Documentation |
Finds the closest HEALPix pixel center to a given target
point,
specified in Cartesian coordinates, using an efficient nested search
algorithm. HEALPix indices are all assumed to be in the "nested"
ordering scheme.
nestSearch(target, nside, index.only = FALSE, save.dots = FALSE)
target |
A data.frame, matrix or vector of Cartesian (x,y,z) coordinates for the target point. If a data.frame is used then spherical coordinates can be specified with row names theta and phi. |
nside |
An integer, the target resolution at which the resulting pixels are returned. |
index.only |
A boolean indicating whether to return only the pixel index (TRUE), or cartesian coordinates as well (FALSE). |
save.dots |
A logical. A If |
if index.only = TRUE
then the output will be a HEALPix index.
If index.only
FALSE then the output is the list containing the HEALPix index
and Cartesian coordinate vector of the HEALPix point closest to target
at resolution nside
.
## Find the closest HEALPix pixel center at resolution j=2 for ## the point (0.6,0.8,0) point <- c(0.6,0.8,0) j <- 2 cpoint <- nestSearch(point, nside = 2^j) ## Plot the closest pixel center in blue and the point (0.6,0.8,0) in red displayPixels(j, j, plot.j=j, spix=c(cpoint$pix), size=5, incl.labels =FALSE) rgl::plot3d(point[1], point[2], point[3], col="red", size = 5, add = TRUE) ## Repeat the above for 4 points in a data.frame points <- data.frame(x = c(1,0,0,0.6), y = c(0,1,0,0.8), z = c(0,0,1,0)) points j <- 2 cpoints <- nestSearch(points, nside = 2^j) ## Plot the closest pixel center in blue and the point (0.6,0.8,0) in red displayPixels(j, j, plot.j=j, spix=c(cpoints$pix), size=5, incl.labels =FALSE) rgl::plot3d(points[,1], points[,2], points[,3], col="red", size = 5, add = TRUE)
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