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### Running command:
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###   /home/biocbuild/R/R/bin/R CMD check --install=check:smoppix.install-out.txt --library=/home/biocbuild/R/R/site-library --no-vignettes --timings smoppix_1.1.9.tar.gz
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* using log directory ‘/home/biocbuild/bbs-3.22-bioc/meat/smoppix.Rcheck’
* using R version 4.5.0 (2025-04-11)
* using platform: aarch64-unknown-linux-gnu
* R was compiled by
    aarch64-unknown-linux-gnu-gcc (GCC) 14.2.0
    GNU Fortran (GCC) 14.2.0
* running under: openEuler 24.03 (LTS)
* using session charset: UTF-8
* using option ‘--no-vignettes’
* checking for file ‘smoppix/DESCRIPTION’ ... OK
* checking extension type ... Package
* this is package ‘smoppix’ version ‘1.1.9’
* package encoding: UTF-8
* checking package namespace information ... OK
* checking package dependencies ... OK
* checking if this is a source package ... OK
* checking if there is a namespace ... OK
* checking for hidden files and directories ... OK
* checking for portable file names ... OK
* checking for sufficient/correct file permissions ... OK
* checking whether package ‘smoppix’ can be installed ... OK
* used C++ compiler: ‘aarch64-unknown-linux-gnu-g++ (GCC) 14.2.0’
* checking installed package size ... OK
* checking package directory ... OK
* checking ‘build’ directory ... OK
* checking DESCRIPTION meta-information ... OK
* checking top-level files ... OK
* checking for left-over files ... OK
* checking index information ... OK
* checking package subdirectories ... OK
* checking code files for non-ASCII characters ... OK
* checking R files for syntax errors ... OK
* checking whether the package can be loaded ... OK
* checking whether the package can be loaded with stated dependencies ... OK
* checking whether the package can be unloaded cleanly ... OK
* checking whether the namespace can be loaded with stated dependencies ... OK
* checking whether the namespace can be unloaded cleanly ... OK
* checking loading without being on the library search path ... OK
* checking dependencies in R code ... NOTE
Unexported object imported by a ':::' call: ‘lmerTest:::as_lmerModLT’
  See the note in ?`:::` about the use of this operator.
* checking S3 generic/method consistency ... OK
* checking replacement functions ... OK
* checking foreign function calls ... OK
* checking R code for possible problems ... NOTE
plotCells: no visible binding for global variable ‘gene’
plotCells: no visible binding for global variable ‘cell’
plotWf: no visible binding for global variable ‘minP’
plotWf: no visible binding for global variable ‘maxP’
plotWf: no visible binding for global variable ‘Weight’
Undefined global functions or variables:
  Weight cell gene maxP minP
* checking Rd files ... OK
* checking Rd metadata ... OK
* checking Rd cross-references ... OK
* checking for missing documentation entries ... OK
* checking for code/documentation mismatches ... OK
* checking Rd \usage sections ... OK
* checking Rd contents ... OK
* checking for unstated dependencies in examples ... OK
* checking contents of ‘data’ directory ... OK
* checking data for non-ASCII characters ... OK
* checking data for ASCII and uncompressed saves ... OK
* checking line endings in C/C++/Fortran sources/headers ... OK
* checking compiled code ... NOTE
Note: information on .o files is not available
* checking files in ‘vignettes’ ... OK
* checking examples ... OK
Examples with CPU (user + system) or elapsed time > 5s
                     user system elapsed
plotTopResults     10.818  5.444  11.002
estPis             11.350  3.952   5.962
evalWeightFunction  5.364  9.853   9.253
writeToXlsx         8.645  5.545   8.319
fitLMMs             7.746  5.597   7.922
buildDataFrame      4.285  2.556   5.645
plotWf              3.985  2.784   5.175
plotExplore         5.225  0.309   5.546
estGradients        3.759  1.516  12.089
* checking for unstated dependencies in ‘tests’ ... OK
* checking tests ...
  Running ‘testthat.R’

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### Running command:
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###   /home/biocbuild/R/R/bin/R CMD INSTALL smoppix
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* installing to library ‘/home/biocbuild/R/R-4.5.0/site-library’
* installing *source* package ‘smoppix’ ...
** this is package ‘smoppix’ version ‘1.1.9’
** using staged installation
** libs
using C++ compiler: ‘aarch64-unknown-linux-gnu-g++ (GCC) 14.2.0’
/opt/ohpc/pub/compiler/gcc/14.2.0/bin/aarch64-unknown-linux-gnu-g++ -std=gnu++17 -I"/home/biocbuild/R/R-4.5.0/include" -DNDEBUG  -I'/home/biocbuild/R/R-4.5.0/site-library/Rcpp/include' -I/usr/local/include    -fPIC  -g -O2  -Wall -Werror=format-security  -c RcppExports.cpp -o RcppExports.o
/opt/ohpc/pub/compiler/gcc/14.2.0/bin/aarch64-unknown-linux-gnu-g++ -std=gnu++17 -I"/home/biocbuild/R/R-4.5.0/include" -DNDEBUG  -I'/home/biocbuild/R/R-4.5.0/site-library/Rcpp/include' -I/usr/local/include    -fPIC  -g -O2  -Wall -Werror=format-security  -c crossdistFast.cpp -o crossdistFast.o
/opt/ohpc/pub/compiler/gcc/14.2.0/bin/aarch64-unknown-linux-gnu-g++ -std=gnu++17 -I"/home/biocbuild/R/R-4.5.0/include" -DNDEBUG  -I'/home/biocbuild/R/R-4.5.0/site-library/Rcpp/include' -I/usr/local/include    -fPIC  -g -O2  -Wall -Werror=format-security  -c findRanksDist.cpp -o findRanksDist.o
/opt/ohpc/pub/compiler/gcc/14.2.0/bin/aarch64-unknown-linux-gnu-g++ -std=gnu++17 -shared -L/home/biocbuild/R/R-4.5.0/lib -L/usr/local/lib -o smoppix.so RcppExports.o crossdistFast.o findRanksDist.o -L/home/biocbuild/R/R-4.5.0/lib -lR
installing to /home/biocbuild/R/R-4.5.0/site-library/00LOCK-smoppix/00new/smoppix/libs
** R
** data
** inst
** byte-compile and prepare package for lazy loading
** help
Loading required namespace: smoppix
*** installing help indices
** building package indices
** installing vignettes
** testing if installed package can be loaded from temporary location
** checking absolute paths in shared objects and dynamic libraries
** testing if installed package can be loaded from final location
** testing if installed package keeps a record of temporary installation path
* DONE (smoppix)

R version 4.5.0 (2025-04-11) -- "How About a Twenty-Six"
Copyright (C) 2025 The R Foundation for Statistical Computing
Platform: aarch64-unknown-linux-gnu

R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.

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Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.

Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
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> library(testthat)
> library(smoppix)
> library(spatstat.random)
Loading required package: spatstat.data
Loading required package: spatstat.univar
spatstat.univar 3.1-4
Loading required package: spatstat.geom
spatstat.geom 3.6-0
spatstat.random 3.4-2
> library(BiocParallel)
> n <- 4000 # number of molecules
> ng <- 8 # number of genes
> nfov <- 3 # Number of fields of view
> conditions <- 3
> # sample xy-coordinates in [0, 1]
> x <- runif(n)
> y <- runif(n)
> # assign each molecule to some gene-cell pair
> gs <- paste0("gene", seq(ng))
> gene <- sample(gs, n, TRUE)
> fov <- as.character(sample(nfov, n, TRUE))
> condition <- as.character(sample(conditions, n, TRUE))
> f = paste(fov, condition, sep = "_")
> age = unsplit(lapply(split(integer(n), f = f), function(x) {rep(runif(1, 18, 98))}), f = f)
> # construct data.frame of molecule coordinates
> df <- data.frame(gene, x, y, fov, condition = condition, age = age)
> # A list of point patterns
> listPPP <- tapply(seq(nrow(df)), df$fov, function(i) {
+     ppp(x = df$x[i], y = df$y[i], marks = df[i, c("gene", "condition", "fov", "age"), drop = FALSE])
+ }, simplify = FALSE)
> # Regions of interest (roi): Diamond in the center plus four triangles
> w1 <- owin(poly = list(x = c(0, 0.5, 1, 0.5), y = c(0.5, 0, 0.5, 1)))
> w2 <- owin(poly = list(x = c(0, 0, 0.5), y = c(0.5, 0, 0)))
> w3 <- owin(poly = list(x = c(0, 0, 0.5), y = c(1, 0.5, 1)))
> w4 <- owin(poly = list(x = c(1, 1, 0.5), y = c(0.5, 1, 1)))
> w5 <- owin(poly = list(x = c(1, 1, 0.5), y = c(0, 0.5, 0)))
> wWrong <- owin(poly = list(x = c(0, 1, 1, 0), y = c(0.75, 0.5, 0.75, 1)))
> hypFrame <- buildHyperFrame(df, coordVars = c("x", "y"), imageVars = c(
+     "condition", "fov", "age"
+ ), imageIdentifier = c("fov", "condition"))
Found 9 unique images
> nDesignFactors <- length(unique(hypFrame$image))
> wList <- lapply(seq_len(nDesignFactors), function(x) {
+     Li <- list(w1 = w1, w2 = w2, w3 = w3, w4 = w4, w5 = w5)
+     names(Li) <- paste0(names(Li), "_", x)
+     Li
+ })
> wList2 <- lapply(seq_len(nDesignFactors), function(x) {
+     list(w1 = w1, w2 = w2, w3 = w3, w4 = w4, w5 = w5, wWrong = wWrong)
+ })
> unCells <- unlist(lapply(wList, names))
> cellTypesDf <- data.frame(cell = unCells, cellType = sample(paste0("CellType_", LETTERS[seq_len(5)]),
+     length(unCells),
+     replace = TRUE
+ ))
> names(wList) <- names(wList2) <- rownames(hypFrame)
> hypFrame2 <- addCell(hypFrame, wList, cellTypes = cellTypesDf, verbose = FALSE)
> # The nuclei
> n1 <- owin(poly = list(x = c(0.2, .4, 0.8, .4), y = c(.4, .2, .4, .8)))
> n2 <- owin(poly = list(x = c(0.1, 0.1, .4), y = c(.4, .1, .1)))
> n3 <- owin(poly = list(x = c(0.1, 0.1, .4), y = c(1, .75, 1)))
> n4 <- owin(poly = list(x = c(1, 1, .6), y = c(.7, .9, .9)))
> n5 <- owin(poly = list(x = c(.95, .95, .7), y = c(.1, .4, .1)))
> nLarge <- owin(poly = list(x = c(1.1, 1.1, .7), y = c(.1, .4, .1)))
> nList <- lapply(seq_len(nDesignFactors), function(x) {
+     Li <- list("w1" = n1, "w2" = n2, "w3" = n3, "w4" = n4, "w5" = n5)
+     names(Li) <- paste0(names(Li), "_", x)
+     Li
+ })
> nList2 <- lapply(seq_len(nDesignFactors), function(x) {
+     Li <- list("w1" = n1, "w2" = n2, "w3" = n3, "w4" = n4, "w5" = nLarge)
+     names(Li) <- paste0(names(Li), "_", x)
+     Li
+ })
> names(nList) <- names(nList2) <- rownames(hypFrame) # Matching names is necessary
> hypFrame2 <- addNuclei(hypFrame2, nList, verbose = FALSE)
> # Register the parallel backend
> nCores <- 2
> if(.Platform$OS.type == "unix"){
+   #On unix-based systems, use MulticoreParam
+   register(MulticoreParam(nCores))
+ } else {
+   #On windows, use makeCluster
+   library(doParallel)
+   Clus = makeCluster(nCores)
+   registerDoParallel(Clus)
+   register(DoparParam(), default = TRUE)
+ }
> #register(SerialParam()) # Switch on when mapping test coverage
> pis <- c("nn", "nnPair", "edge", "centroid", "nnCell", "nnPairCell")
> piEstsBG <- estPis(hypFrame2, pis = pis, null = "background", verbose = FALSE)
> piEstsCSR <- estPis(hypFrame2, pis = pis, null = "CSR", verbose = FALSE)
> piEstsBG2 <- estPis(hypFrame2[, c("ppp", "image", "tabObs")],
+     pis = "nn", null = "background",
+     verbose = FALSE
+ )
> # Add weight functions
> objBG <- addWeightFunction(piEstsBG, designVars = "condition")
> objCSR <- addWeightFunction(piEstsCSR, designVars = "condition")
> # Fit Yang models too
> data(Yang)
> hypYang <- buildHyperFrame(Yang[Yang$section %in% paste0("section", seq_len(3)),], 
+                            coordVars = c("x", "y"), imageVars = c("day", "root", "section"
+ )) #Subset for speed
Found 18 unique images
> yangPims <- estPis(hypYang, features = getFeatures(hypYang)[12:21], 
+                    pis = c("nn", "nnPair"), verbose = FALSE, nPointsAll = 2e3)
> yangPims <- addWeightFunction(yangPims, lowestLevelVar = "section")
> data(Eng)
> hypEng <- buildHyperFrame(Eng, coordVars = c("x", "y"), imageVars = c("fov", "experiment"))
Found 17 unique images
There were 13 warnings (use warnings() to see them)
> hypEng <- addCell(hypEng, EngRois, verbose = FALSE)