Dear Ivan Thanks a lot for this very nice example. Is it true that all.equal just compares y values? Based on this help here I think so and the value I got is the difference for the y-values. https://www.statology.org/all-equal-function-r/ However, here I see x and y testing? https://www.rdocumentation.org/packages/base/versions/3.6.2/topics/all.equal I am actually interested in the x values (x-y coordinates). Test if x-y coordinates of both 25-m-pixel rasters are the same. Ther may be a small shift or differences in the number of decimal places. Kind regards Sibylle -----Original Message----- From: Ivan Krylov <ikrylov at disroot.org> Sent: Friday, August 16, 2024 11:45 AM To: sibylle.stoeckli at gmx.ch Cc: 'SIBYLLE ST?CKLI via R-help' <r-help at r-project.org> Subject: Re: [R] allequal diff ? Fri, 16 Aug 2024 11:32:58 +0200 <sibylle.stoeckli at gmx.ch> ?????:> # values and mask r1 > r1 <- getValues(r1) > mask1 <- is.na(r1) > # Do the same for r2 > r2 <- getValues(r2_resampled) > mask2 <- is.na(r2) > > # Combine the masks > all.equal(r1[!(mask1 & mask2)], r2[!(mask1 & mask2)])Let's consider a more tangible example: # The vectors `x` and `y` start out equal x <- y <- 1:10 # But then their different elements are made missing x[c(1,3,4)] <- NA y[c(3,8)] <- NA Now, `is.na(x) & is.na(y)` gives the third element as the only element missing in both x and y: mask1 <- is.na(x) mask2 <- is.na(y) all.equal( # not the comparison you are looking for x[!(mask1 & mask2)], # still two more elements missing y[!(mask1 & mask2)] # still one more element missing ) If you want to ignore all missing elements, you should combine the masks using the element-wise "or" operation ("missing in x and/or y"), not the element-wise "and" operation ("missing in both x and y at the same time"): mask1 & mask2 # drops element 3 # [1] FALSE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE mask1 | mask2 # drops elements 1, 3, 4, 8 # [1] TRUE FALSE TRUE TRUE FALSE FALSE FALSE TRUE FALSE FALSE -- Best regards, Ivan
? To do this, I think you'll have to compare the extent (using the extent() function) and/or number of rows and columns and/or resolution of the two rasters. (Print the source code of compareRasters() and dig through it to see what's being compared ...) On 8/18/24 14:00, SIBYLLE ST?CKLI via R-help wrote:> Dear Ivan > > Thanks a lot for this very nice example. > > Is it true that all.equal just compares y values? > Based on this help here I think so and the value I got is the difference for the y-values. > https://www.statology.org/all-equal-function-r/ > > However, here I see x and y testing? > https://www.rdocumentation.org/packages/base/versions/3.6.2/topics/all.equal > I am actually interested in the x values (x-y coordinates). Test if x-y coordinates of both 25-m-pixel rasters are the same. Ther may be a small shift or differences in the number of decimal places. > > Kind regards > Sibylle > > > > -----Original Message----- > From: Ivan Krylov <ikrylov at disroot.org> > Sent: Friday, August 16, 2024 11:45 AM > To: sibylle.stoeckli at gmx.ch > Cc: 'SIBYLLE ST?CKLI via R-help' <r-help at r-project.org> > Subject: Re: [R] allequal diff > > ? Fri, 16 Aug 2024 11:32:58 +0200 > <sibylle.stoeckli at gmx.ch> ?????: > >> # values and mask r1 >> r1 <- getValues(r1) >> mask1 <- is.na(r1) >> # Do the same for r2 >> r2 <- getValues(r2_resampled) >> mask2 <- is.na(r2) >> >> # Combine the masks >> all.equal(r1[!(mask1 & mask2)], r2[!(mask1 & mask2)]) > Let's consider a more tangible example: > > # The vectors `x` and `y` start out equal x <- y <- 1:10 # But then their different elements are made missing x[c(1,3,4)] <- NA y[c(3,8)] <- NA > > Now, `is.na(x) & is.na(y)` gives the third element as the only element missing in both x and y: > > mask1 <- is.na(x) > mask2 <- is.na(y) > all.equal( # not the comparison you are looking for > x[!(mask1 & mask2)], # still two more elements missing > y[!(mask1 & mask2)] # still one more element missing > ) > > If you want to ignore all missing elements, you should combine the masks using the element-wise "or" operation ("missing in x and/or y"), not the element-wise "and" operation ("missing in both x and y at the same time"): > > mask1 & mask2 # drops element 3 > # [1] FALSE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE > mask1 | mask2 # drops elements 1, 3, 4, 8 # [1] TRUE FALSE TRUE TRUE FALSE FALSE FALSE TRUE FALSE FALSE > > -- > Best regards, > Ivan > > ______________________________________________ > R-help at r-project.org mailing list -- To UNSUBSCRIBE and more, see > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide https://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code.
"Is it true that all.equal just compares y values?" The following may be a bit more than you may have wanted, but I hope it is nevertheless useful. The first place you should go to for questions like this is the Help system, not here, i.e. ?all.equal When you do this, you will find that all.equal() is a so-called S3 generic function, which, among other things, means that it works differently (i.e. "dispatches") depending on its (usually) first argument. So, for example, if the first argument is of (S3) class "numeric", it will call the default method, all.equal.default(); if it's a function, it will call all.equal.function(). Help for all.equal's basic methods is found in the single all.equal (base) Help page. However, for non-base R packages, there may be other different methods provided for classed objects, e.g. perhaps of class "raster" that would be found by ?all.equal.raster . Or maybe not, if the class "inherits" from another class, such as "matrix" (Warning: I am completely unfamiliar with the raster package, so these specifics are very likely wrong). To sort this sort of thing out, It would probably be useful for you to find a tutorial on R's S3 class system (which is really a form of multiple dispatch) and spend some time with it. There are many good ones out there. This S3 system is widely used within R and many packages, so doing this sort of homework now should serve you well in your future R journey. All IMO obviously. Cheers, Bert On Sun, Aug 18, 2024 at 11:00?AM SIBYLLE ST?CKLI via R-help <r-help at r-project.org> wrote:> > Dear Ivan > > Thanks a lot for this very nice example. > > Is it true that all.equal just compares y values? > Based on this help here I think so and the value I got is the difference for the y-values. > https://www.statology.org/all-equal-function-r/ > > However, here I see x and y testing? > https://www.rdocumentation.org/packages/base/versions/3.6.2/topics/all.equal > I am actually interested in the x values (x-y coordinates). Test if x-y coordinates of both 25-m-pixel rasters are the same. Ther may be a small shift or differences in the number of decimal places. > > Kind regards > Sibylle > > > > -----Original Message----- > From: Ivan Krylov <ikrylov at disroot.org> > Sent: Friday, August 16, 2024 11:45 AM > To: sibylle.stoeckli at gmx.ch > Cc: 'SIBYLLE ST?CKLI via R-help' <r-help at r-project.org> > Subject: Re: [R] allequal diff > > ? Fri, 16 Aug 2024 11:32:58 +0200 > <sibylle.stoeckli at gmx.ch> ?????: > > > # values and mask r1 > > r1 <- getValues(r1) > > mask1 <- is.na(r1) > > # Do the same for r2 > > r2 <- getValues(r2_resampled) > > mask2 <- is.na(r2) > > > > # Combine the masks > > all.equal(r1[!(mask1 & mask2)], r2[!(mask1 & mask2)]) > > Let's consider a more tangible example: > > # The vectors `x` and `y` start out equal x <- y <- 1:10 # But then their different elements are made missing x[c(1,3,4)] <- NA y[c(3,8)] <- NA > > Now, `is.na(x) & is.na(y)` gives the third element as the only element missing in both x and y: > > mask1 <- is.na(x) > mask2 <- is.na(y) > all.equal( # not the comparison you are looking for > x[!(mask1 & mask2)], # still two more elements missing > y[!(mask1 & mask2)] # still one more element missing > ) > > If you want to ignore all missing elements, you should combine the masks using the element-wise "or" operation ("missing in x and/or y"), not the element-wise "and" operation ("missing in both x and y at the same time"): > > mask1 & mask2 # drops element 3 > # [1] FALSE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE > mask1 | mask2 # drops elements 1, 3, 4, 8 # [1] TRUE FALSE TRUE TRUE FALSE FALSE FALSE TRUE FALSE FALSE > > -- > Best regards, > Ivan > > ______________________________________________ > R-help at r-project.org mailing list -- To UNSUBSCRIBE and more, see > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide https://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code.