search for: combined_mask

...; what do you mean by use is.na() in getValues(). So I need to call > getValues a second time? Not necessarily, but it's one of the options. I was thinking along the lines of: values1 <- getValues(r1) mask1 <- is.na(values1) # Do the same for r2 # Combine the masks all.equal(values1[!combined_mask], values2[!combined_mask]) Unlike compareRaster(), this assumes that the coordinate grid of r1 and r2 is already the same and that only some of the values may differ. > I suppose you mean to first prepare a mask using is.na without > getValues and then in the second step your code? '...

...what do you mean by use is.na() in getValues(). So I need to call > getValues a second time? Not necessarily, but it's one of the options. I was thinking along the lines of: values1 <- getValues(r1) mask1 <- is.na(values1) # Do the same for r2 # Combine the masks all.equal(values1[!combined_mask], values2[!combined_mask]) Unlike compareRaster(), this assumes that the coordinate grid of r1 and r2 is already the same and that only some of the values may differ. > I suppose you mean to first prepare a mask using is.na without > getValues and then in the second step your code? 'r...

Many thanks Ivan Use is.na() on getValues() outputs, combine the two masks using the | operator to get a mask of values that are missing in either raster, then negate the mask to choose the non-missing values: all.equal(getValues(r1)[!mask], getValues(r2)[!mask]) --> what do you mean by use is.na() in getValues(). So I need to call getValues a second time? I suppose you mean to first