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Computes the median of a variable's rightmost dimension at all other dimensions.


	function dim_median (
		x  : numeric   

	return_val  :  float or double



A variable of numeric type and any dimensionality.

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.


The dim_median function determines the median of all elements of the n-1th (rightmost) dimension for each index of the dimensions 0...n-2. Missing values are ignored.

The median is a robust estimate of the mean.

Use dim_median_n if you want to specify which dimension(s) to do the median across.

See Also

dim_median_n, dim_avg, dim_max, dim_min, dim_num, dim_product, dim_rmsd, dim_rmvmean, dim_rmvmed, dim_standardize, dim_stat4, dim_stddev, dim_sum, dim_variance, copy_VarMeta


Example 1

Let x be a 1-dimensional array, then:

   xMed = dim_median(x)   ; xMed is a scalar
Example 2

Create a variable (q) of size (3,5,10) array. Then calculate the median of the rightmost dimension.

    q    = random_uniform(-20,100,(/3,5,10/))
    qMed = dim_median(q)   ;==>  qMed(3,5)
Example 3

Let x be of size (ntim,nlat,mlon) and with named dimensions "time", "lat" and "lon", respectively. Then, for each time and latitude, the median longitude value may be obtained via:

    xMedLon = dim_median( x )    ; ==> xMedLon(ntim,nlat)
Example 4

Let x be defined as in Example 3: x(time,lat,lon). Determine the median value over all time 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_median_n to avoid having to reorder your data.

    xMedTime = dim_median( x(lat|:, lon|:, time|:) )    ; ==> xMedTime(nlat,nlon)

    xMedTime = dim_median_n( x, 0 )                     ; no reordering needed