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dim_rmvmed

Calculates and removes the median of the (rightmost) dimension at all other dimensions.

Prototype

	function dim_rmvmed (
		x  : numeric   
	)

	return_val [dimsizes(x)] :  float or double

Arguments

x

A variable of numeric type and any dimensionality.

Return value

The output is of type double if the input is double, and float otherwise.

The dimensionality is the same as the input dimensionality.

Description

The dim_rmvmed function calculates and removes the median from all elements of the n-1th (rightmost) dimension for each index of the dimensions 0...n-2. Missing values are ignored.

Use dim_rmvmed_n if you want to specify which dimension(s) to remove the median from.

Use dim_rmvmed_Wrap if retention of metadata is desired.

See Also

dim_rmvmed_n, dim_rmvmean, dim_rmvmean_Wrap, dim_rmvmed_Wrap, dim_rmvmean_n_Wrap, dim_rmvmed_n_Wrap

Examples

Example 1:

Let x be a 1-dimensional array: (a) Create a new variable, xNew, that contains just the deviations from the median; (b) replace the variable x with the deviations.

  xNew = dim_rmvmed(x)      ; new variable
  x    = dim_rmvmed(x)      ; overwrite with deviations
Example 2:

Let x be a 3-dimensional array with dimension sizes (ntim, nlat, nlon). To remove the medians of the "nlon" dimension:

   xRmvLon = dim_rmvmed (x)         ; new variable containing deviations (no metadata)
   xRmvLon = dim_rmvmed_Wrap (x)    ; with metadata
   x       = dim_rmvmed (x)         ; overwrite with deviations from median
Example 3:

Let x be a 3-dimensional array with named dimensions (time, lat, lon) and dimension sizes (ntim, nlat, nlon). To remove the median of the time dimension from all lat/lon indices, 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_rmvmed_n to avoid having to reorder your data.

   xRmvTime = dim_rmvmed(x(lat|:, lon|:, time|:))

   xRmvTime = dim_rmvmed_n(x,0)   ; no reordering needed
Example 4: Let x be as in Example 3 and let x contain monthly medians for (say) 10 years of data (ntim=120). Monthly anomalies for each month could be calculated using array subscripting and Named Subscripting to reorder the input array such that "time" is the rightmost dimension.
   xRmvJan  = dim_rmvmed(x(lat|:, lon|:, time|0:ntim-1:12))
   xRmvJuly = dim_rmvmed(x(lat|:, lon|:, time|6:ntim-1:12))

   xRmvJan  = dim_rmvmed_n(x(0:ntim-1:12,:,:),0)   ; no reordering needed
   xRmvJuly = dim_rmvmed_n(x(6:ntim-1:12,:,:),0)