R Under development (unstable) (2025-06-04 r88278 ucrt) -- "Unsuffered Consequences"
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> ###<--- BEGIN TESTS --->
> suppressPackageStartupMessages(require(vegan))
> 
> # Test data
> # data(varespec)
> set.seed(252)
> testdata <- matrix(round(runif(1000, 0, 100)), nrow = 20)
> testdata <- testdata - 50
> testdata[testdata < 0] <- 0
> rownames(testdata) <- paste0("row", seq_len(nrow(testdata)))
> colnames(testdata) <- paste0("col", seq_len(ncol(testdata)))
> 
> # Calculates relative abundance table
> relative <- decostand(testdata, "total")
> 
> # Count and relative data with pseudocount
> testdata.with.pseudo <- testdata + 1
> relative.with.pseudo <- decostand(testdata + 1, "total")
> 
> # NAs correctly assigned
> a1 <- testdata
> a2 <- decostand(a1, "rclr", na.rm = FALSE)
> a3 <- decostand(a1, "rclr", na.rm = TRUE)
> all(is.na(a2[a1 == 0]))
[1] FALSE
> all(!is.na(a3[a1 == 0]))
[1] TRUE
> 
> # aitchison equals to CLR + Euclid (pseudocount is necessary with clr)
> a1 <- vegdist(testdata + 1, method = "aitchison", na.rm = TRUE)
> a2 <- vegdist(decostand(testdata + 1, "clr"), method = "euclidean", na.rm = TRUE)
> max(abs(a1-a2)) < 1e-6 # Tolerance
[1] TRUE
> 
> # Robust aitchison equals to rCLR + Euclid when na.rm = TRUE (matrix completion applied)
> # and works without pseudocount
> a1 <- vegdist(testdata, method = "robust.aitchison", na.rm = TRUE)
> a2 <- vegdist(decostand(testdata, "rclr"), method = "euclidean", na.rm = TRUE)
> max(abs(a1-a2)) < 1e-6 # Tolerance
[1] TRUE
> 
> # Robust aitchison and aitchison are equal when there are no zeroes
> a1 <- vegdist(testdata.with.pseudo, method = "robust.aitchison")
> a2 <- vegdist(testdata.with.pseudo, method = "aitchison")
> max(abs(a1 - a2)) < 1e-6 # Tolerance
[1] TRUE
> 
> # It is possible to pass pseudocount as a function argument to decostand
> a1 <- vegdist(testdata, method = "aitchison", pseudocount = 1)
> a2 <- vegdist(testdata + 1, method = "aitchison")
> max(abs(a1 - a2)) < 1e-6 # Tolerance
[1] TRUE
> 
> # Robust rclr+Euclid should give same result than robust.aitchison
> d1 <- vegdist(decostand(testdata, "rclr"), "euclidean", na.rm = TRUE)
> d2 <- vegdist(testdata, "robust.aitchison", na.rm = TRUE)
> max(abs(d1 - d2)) < 1e-6 # Tolerance
[1] TRUE
> 
> # Robust rclr+Euclid should give same result than robust.aitchison
> d1 <- vegdist(decostand(testdata + 1, "rclr"), "euclidean", na.rm = FALSE)
> d2 <- vegdist(testdata + 1, "robust.aitchison", na.rm = FALSE)
> max(abs(d1 - d2)) < 1e-6 # Tolerance
[1] TRUE
> 
> # Compare the outcomes with an external package that also provides compositional transformations
> # Adding these would demand adding Suggested packages in DESCRIPTION
> # skipped for now but can be useful for manual testing.
> #skip <- TRUE
> #if (!skip) {
> #
> #    sum(compositions::clr(testdata.with.pseudo) - decostand(testdata.with.pseudo, "clr")) < 1e-6
> #    sum(compositions::clr(testdata.with.pseudo) - decostand(testdata.with.pseudo, "clr", MARGIN = 1)) < 1e-6
> #    sum(t(compositions::clr(t(testdata.with.pseudo))) - decostand(testdata.with.pseudo, "clr", MARGIN = 2)) < 1e-6
> #    sum(rgr::clr(testdata.with.pseudo) - decostand(testdata.with.pseudo, "clr"))<1e-6#
> #
> #    sum(compositions::alr(testdata.with.pseudo, ivar = 1) - decostand(testdata.with.pseudo, "alr")) < 1e-6
> #    sum(compositions::alr(testdata.with.pseudo, ivar = 1) - decostand(testdata.with.pseudo, "alr", MARGIN = 1)) < 1e-6
> #    sum(t(compositions::alr(t(testdata.with.pseudo), ivar = 1)) - decostand(testdata.with.pseudo, "alr", MARGIN = 2)) < 1e-6
> #    sum(rgr::alr(testdata.with.pseudo, j = 1) - decostand(testdata.with.pseudo, "alr", reference = 1))<1e-6#
> #
> #}
> 
> # --------------------------------------------------------------------------------------------------------------
> 
> proc.time()
   user  system elapsed 
   1.43    0.17    1.59