R Under development (unstable) (2024-03-16 r86144 ucrt) -- "Unsuffered Consequences"
Copyright (C) 2024 The R Foundation for Statistical Computing
Platform: x86_64-w64-mingw32/x64

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.

R is a collaborative project with many contributors.
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.
Type 'q()' to quit R.

> # Test constructors
> 
> library(testthat)
> library(SPUTNIK)
> 
> # msiDataset
> 
> imageShape <- c(100, 100)
> numPixels <- prod(imageShape)
> numPeaks <- 500
> mzVector <- sort(sample(seq(150, 1000), numPeaks))
> print(is.numeric(mzVector))
[1] TRUE
> print(is.array(mzVector))
[1] FALSE
> randIntensity <- matrix(rnorm(numPixels * numPeaks), numPixels, numPeaks)
> 
> test_that("msi.dataset constructor", {
+   msX <- msiDataset(
+     values = randIntensity, mz = mzVector, rsize = imageShape[1],
+     csize = imageShape[2]
+   )
+   expect_s4_class(msX, "msi.dataset")
+ })
Creating msiDataset object...
Detecting constant peaks...
Generating image of detected peaks...
Generating total-ion-count image...
Test passed 😸
> 
> # msImage
> 
> randPixels <- matrix(rnorm(numPixels), imageShape[1], imageShape[2])
> 
> test_that("ms.image constructor", {
+   msIm <- msImage(values = randPixels, name = "Test", scale = TRUE)
+   expect_s4_class(msIm, "ms.image")
+ })
Test passed 😸
> 
> # peakFilter
> 
> numKeep <- 100
> keepIdx <- sample(numPeaks, numKeep)
> names(keepIdx) <- mzVector[keepIdx]
> 
> test_that("peak.filter constructor", {
+   filt <- createPeaksFilter(peaksIndices = keepIdx)
+   expect_is(filt, "list")
+   expect_equal(attr(filt, "peak.filter"), TRUE)
+   expect_equal(attr(filt, "filter"), "custom")
+ })
Test passed 😀
> 
> proc.time()
   user  system elapsed 
   5.92    1.07    7.00