dim_rmsd_Wrap
Computes the root-mean-square-difference between two variables' rightmost dimension at all other dimensions.
Prototype
load "$NCARG_ROOT/lib/ncarg/nclscripts/csm/contributed.ncl" function dim_rmsd_Wrap ( 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-2 dimensions of the input variable. That is, the dimension rank of the input variable will be reduced by one.
Description
The dim_rmsd_Wrap function computes the root-mean-square difference of all elements of the n-1 dimension for each index of the dimensions 0...n-2. A wrapper function. Missing values are ignored.
Use dim_rmsd_n_Wrap if you want to specify which dimensions to do the calculations on.
See Also
dim_rmsd_n_Wrap, dim_rmsd, dim_rmsd_n, dim_rmsd_n_Wrap, dim_avg, dim_median, dim_num, dim_product, dim_rmsd, dim_rmvmean, dim_rmvmed, dim_standardize, dim_stat4, dim_rmsd, dim_sum, dim_rmsd
Examples
Example 1
Create two variables q and 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)
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)
Generally, users prefer that the returned variable have
metadata associated with it. This can be accomplished via the
dim_rmsd_Wrap function:
rmsdLon = dim_rmsd_Wrap( x,y ) ; ==> rmsdLon(time,lat)
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 NCL's Named Subscripting to reorder the input array such that "time" is the rightmost dimension.
Note: in V5.1.1, you will be able to use dim_rmsd_n_Wrap to avoid having to reorder your data.
rmsdTime = dim_rmsd( x(lat|:,lon|:,time|:), y(lat|:,lon|:,time|:) ) ; ==> rmsdTime(nlat,nlon)
rmsdTime = dim_rmsd_n( x, y,0 ) ; no reordering needed
If metadata is desired use:
rmsdTime = dim_rmsd_Wrap( x(lat|:,lon|:,time|:),y(lat|:,lon|:,time|:) ) ; ==> rmsdTime(lat,lon)
rmsdTime = dim_rmsd_n_Wrap( x,y,0 ) ; no reordering needed