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Plotting Missing Data


The MAX_VALUE and MIN_VALUE keywords to PLOT can be used to create missing data plots wherein bad data values are not plotted. Data values greater than the value of the MAX_VALUE keyword or less than the value of the MIN_VALUE keyword are treated as missing and are not plotted. The following code creates a dataset with bad data values and plots it with and without these keywords:

; Make a 100-element array where each element is  
; set equal to its index: 
A = FINDGEN(100) 
; Set 20 random point in the array equal to 400. 
; This simulates "bad" data values above the range 
; of the "real" data. 
A(RANDOMU(SEED, 20)*100)=400 
; Set 20 random point in the array equal to -10. 
; This simulates "bad" data values below the range 
; of the "real" data. 
A(RANDOMU(SEED, 20)*100)=-10 
; Plot the dataset with the bad values. Looks pretty bad! 
PLOT, A 
; Plot the dataset, but don't plot any value over 101. 
; The resulting plot looks better, but still shows spurious values: 
PLOT, A, MAX_VALUE=101 
; This time leave out both high and low spurious values. 
; The resulting plot more accurately reflects the "real" data: 
PLOT, A, MAX_VALUE=101, MIN_VALUE=0 

The following plotting routines allow you to set maximum and minimum values in this manner: CONTOUR,  PLOT,  SHADE_SURF, SURFACE.

In addition to the maximum and minimum values specified with the MAX_VALUE and MIN_VALUE keywords, these plotting routines treat the IEEE floating-point value NaN (Not A Number) as missing data automatically. (For more information on NaN, see Special Floating-Point Values.)


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