dim_rmsd
Computes the root-mean-square-difference between two variables' rightmost dimension at all other dimensions.
Prototype
function dim_rmsd ( x : numeric, y : numeric ) return_val : float or double
Arguments
xA variable of numeric type and any dimensionality.
yA variable of numeric type and same dimensionality as x.
Return value
The output will be double if x is double, and float otherwise.
The output dimensionality is the same as the first n-1 dimensions of the input variable. That is, the dimension rank of the input variable will be reduced by one.
Description
The dim_rmsd function computes the root-mean-square-difference of all elements of the n-1 dimension for each index of the dimensions 0...n-2. Missing values are ignored.
Use dim_rmsd_n if you want to specify which dimension(s) to do the calculation on.
Use the dim_rmsd_Wrap function if metadata retention is desired. The interface is identical.
See Also
dim_rmsd_Wrap, dim_rmsd_n, dim_rmsd_n_Wrap, dim_avg, dim_median, dim_num, dim_product, dim_rmsd_n, dim_rmvmean, dim_rmvmed, dim_standardize, dim_stat4, dim_sum
Examples
Example 1
Create two variables q nd r of size (3,5,10) array. Then calculate the root-mean-square-difference of the rightmost dimension.
q = random_uniform(-20,100,(/3,5,10/))
r = random_uniform(-50, 99,(/3,5,10/))
rmsd= dim_rmsd(q,r) ;==> rmsd(3,5)
; Use dim_rmsd_Wrap if metadata retention is desired
; rmsd= dim_rmsd_Wrap(q,r) ;==> rmsd(3,5)
Example 2 Let x and y be of size (ntim,nlat,mlon) and with named dimensions "time", "lat" and "lon", respectively. Then, for each time and latitude, the root-mean-square-difference is:
rmsdLon= dim_rmsd( x,y ) ; ==> rmsdLon(ntim,nlat)
; Use dim_rmsd_Wrap if metadata retention is desired
; rmsdLon= dim_rmsd_Wrap( x,y ) ; ==> rmsdLon(ntim,nlat)
Example 3 Let x be defined as in Example 2: x(time,lat,lon). Compute the temporal root-mean-square-difference at each latitude/longitude grid point. Use named subscripting to reorder the input array such that "time" is the rightmost dimension.
rmsdTime = dim_rmsd( x(lat|:,lon|:,time|:), \
y(lat|:,lon|:,time|:) )
; ==> rmsdTime(nlat,nlon)
; Use dim_rmsd_Wrap if metadata retention is desired
; rmsdTime = dim_rmsd_Wrap( x(lat|:,lon|:,time|:), \
; y(lat|:,lon|:,time|:) )
; ==> rmsdTime(nlat,nlon)
Important note: reordering arrays can be an expensive operation, especially if your variable is large or you are repeatedly reordering arrays in your script. Use the dim_rmsd_n or dim_rmsd_n_Wrap functions to avoid reordering:
rmsdTime = dim_rmsd_n( x, y, 0 )
; ==> no reordering needed
; Use dim_rmsd_n_Wrap if metadata retention is desired
; rmsdTime = dim_rmsd_n_Wrap( x, y, 0 )