Oh no! A(A==0)=NaN is turning my matrix into all zeros!!

Okay, I'm feeling like an idiot, what on earth could I be doing wrong?

>> whos KoppenDsb_airT
  Name                  Size                     Bytes  Class     Attributes

    KoppenDsb_airT      360x720x361            374284800  single       

>> min(min(KoppenDsb_airT))

ans(:,:,1) =

    -26.5479

ans(:,:,2) =

    -23.5349

ans(:,:,3) =

    -22.6819

ans(:,:,4) =

    -17.3890

ans(:,:,5) =

    -12.0117

ans(:,:,6) =

     -8.7705

ans(:,:,7) =

     -5.3165

ans(:,:,8) =

       0

ans(:,:,9) =

       0

etc...

KoppenDsb_airT(KoppenDsa_airT==0)= nan;     

>> min(min(KoppenDsb_airT))

ans(:,:,1) =

       0

ans(:,:,2) =

       0

ans(:,:,3) =

       0

ans(:,:,4) =

       0

ans(:,:,5) =

       0

ans(:,:,6) =

       0

ans(:,:,7) =

       0

ans(:,:,8) =

       0

ans(:,:,9) =

       0

etc...

Any idea what I'm doing wrong? Thanks!

Answer 1

[the cyclist]

I think you may be mixing up your variables

KoppenDsa_airT

and

KoppenDsb_airT

Still, the result is puzzling to me.

Is the array the same shape after that operation?

[Kate]

That was it! Thanks for catching that.

[Kate]

Another question: I'm trying to look at my whole KoppenDsb (monthly data) over my 30 year climate period.

KoppenDsb_airT(KoppenDsb_airT==0)= nan;
Dsb_airT_climatology=mean(reshape(KoppenDsb_airT,[],361),1);

but now my min and max are NaN's. Is there a better way to do this?

[Matt Kindig]

If you have the Statistics toolbox installed, you can you nanmean() to take the mean and ignore NaN's.

doc nanmean