FUNCTION median_with_mask, data, mask, NOSTDDEV = nostddev, NO_PAR_CHECK = no_par_check

; Description: This function calculates the median and standard deviation of a set of data 
;              values ignoring any masked/bad values. 
; 
; Input Parameters:
;   
;   data - FLOAT/DOUBLE ARRAY - A data array of any dimensions containing the set of data 
;                               values for which the median is to be calculated.
;   mask - BYTE/INTEGER/LONG ARRAY - An array of the same size and dimensions as "data", 
;                                    that contains the mask of good and bad data points. 
;                                    Good data points should be flagged with a value of "1",
;                                    and bad data values flagged with any other value, 
;                                    although setting bad data values to have mask values of
;                                    "0" is the common practice. If this array does not have
;                                    the same number of elements as "data", then all the 
;                                    data values are considered good.
;
; Return value:
;       
; The function returns an IDL structure with the following tags:
;
;   median - DOUBLE - The median of the good data values.
;   stddev - DOUBLE - The standard deviation of the good data values.
;   ngood - LONG - The number of good data values used in the calculation of "median". 
;   
; Keywords:
;              
;   If the keyword NOSTDDEV is set (as "/NOSTDDEV"), then the function will not include the 
;   standard deviation with the tag name "stddev" in the IDL structure that is returned. Set
;   this keyword if the standard deviation is not required in order to obtain a faster 
;   execution of this function.
;
;   If the keyword NO_PAR_CHECK is set (as "/NO_PAR_CHECK"), then the program will not
;   perform parameter checking on the input parameters, reducing program overheads. 
;
; Author: Dan Bramich (dan.bramich@hotmail.co.uk)
;
; History:
;
;   02/05/2008 - Module created (dmb)  

;Perform parameter checking if not instructed otherwise

  ;Check that "data" contains numbers of the correct type, and determine the number of elements
  ;in "data"

  ;Check that "mask" contains numbers of the correct type

;If "mask" does not have the same number of elements as "data", then assume that all data points are good

;If "mask" does have the same number of elements as "data", then find the subscripts of the "good" data points

;If there are at least 2 good data points

  ;Calculate the median and standard deviation of the data array ignoring bad data points

;If there is 1 good data value

;If there are no good data values

;Return the median and number of good pixels used in the calculation. Also return the
;standard deviation if required.