| Fill Missing values with NaN [message #94666] |
Thu, 10 August 2017 12:00  |
idlusr
Messages: 2
Registered: August 2017
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Junior Member |
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How can one do the following in IDL:
time = [1, 4, 7, 8]
dens =[80,60,30,50]
alltimes = [0,1,2,3,4,5,6,7,8,9]
densnew = [NaN, 80, NaN, NaN, 60, NaN, NaN, 30, 50, NaN]
i.e., compare time to all times, allowing densnew to have same # of elements as all times but ONLY the densities in dens. Missing elements in densnew (depending on time) are given NaN value.
Thank you!
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| Re: Fill Missing values with NaN [message #94667 is a reply to message #94666] |
Thu, 10 August 2017 12:03  |
idlusr
Messages: 2
Registered: August 2017
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Junior Member |
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On Thursday, August 10, 2017 at 12:00:41 PM UTC-7, idlusr wrote:
> How can one do the following in IDL:
>
> time = [1, 4, 7, 8]
> dens =[80,60,30,50]
>
> alltimes = [0,1,2,3,4,5,6,7,8,9]
> densnew = [NaN, 80, NaN, NaN, 60, NaN, NaN, 30, 50, NaN]
>
> i.e., compare time to all times, allowing densnew to have same # of elements as all times but ONLY the densities in dens. Missing elements in densnew (depending on time) are given NaN value.
>
> Thank you!
Forgot to mention, the values in my data set are type double for time & float for density. Thanks again!
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| Re: Fill Missing values with NaN [message #94672 is a reply to message #94666] |
Fri, 11 August 2017 05:31 |
Matthew Argall
Messages: 286
Registered: October 2011
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Senior Member |
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The example below works well with integer times. For floats, you should define "alltimes" as the beginning of the sampling interval and "times" as the center of the sampling interval. This is in-part because of how Value_Locate works and in-part because of the discreteness of floating point values.
;Time Arrays
time = [1, 4, 7, 8]
alltimes = IndGen(10)
;Data Arrays
dens = [80, 60, 30, 50]
densnew = Replicate( !Values.D_NaN, N_Elements(alltimes) )
;Locate "time" within "alltimes"
iTime = Value_Locate(alltimes, time)
;Fill the new density array
densnew[iTime] = dens
;Result
print, densnew, FORMAT='(10(f5.2, 2x))'
NaN 80.00 NaN NaN 60.00 NaN NaN 30.00 50.00 NaN
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