context("spectralIndices") library(terra) ## Create test data-sets vals <- c(-1, 0, 0.5, 1, 2, NA) vals <- expand.grid(vals,vals) r <- ml <- rast(ncol= 6, nrow = 6) r[] <- vals[,1] r <- c(r,r) r[[2]]<-vals[,2] names(r) <- c("L1", "L2") ml[] <- 1 ml[,2] <- 10 ml[,3] <- NA names(ml) <- "henryMaske" r <- rast(r) ml <- rast(ml) test_that("errors and warnings are emitted", { expect_error(spectralIndices(r, red = 1, indices = "NDVI"), "you must specify \\*all\\* required bands") expect_error(spectralIndices(r, red = 1), "you must specify \\*all\\* required bands") expect_warning(spectralIndices(r, red = 1, nir = 2, indices = c("NDVI", "EVI")), "not specified: blue") expect_warning(spectralIndices(r, red = 1, nir = 2, blue = 1, index = c("NDVI", "EVI")), "Skipping EVI") expect_warning(spectralIndices(r, red = 1, nir = 2, blue = 1, index = "EVI", skipRefCheck = TRUE), "raster has no values") expect_error(spectralIndices(r, red = 1, nir = 2, blue = 1, maskLayer = FALSE, index = "ndvi", skipRefCheck = TRUE), "maskLayer must be") expect_error(spectralIndices(r, red = 1, nir = 2, blue = 1, maskLayer = "reginaHalmich", index = "ndvi", skipRefCheck = TRUE), "is not a layer") }) m_cfg <- list(ml, 3, "henryMaske") nadf <- data.frame("NDVI" = rep(NA_real_, 6)) # Suppresswarnings in the next section, we are still dealing with na data, guess raster does not throw a warning # with a valid raster even if every value is na test_that("maskLayer is considered regardless of input class", { for(i in 1:3){ expect_s4_class(nd <- suppressWarnings({spectralIndices(c(r,ml), red = 1, nir=2, indices = "NDVI", maskLayer = m_cfg[[i]], maskValue = 10)}), "SpatRaster") expect_equal(nd[,2], nadf) expect_s4_class(nd <- suppressWarnings({spectralIndices(c(r,ml), red = 1, nir=2, indices = "NDVI", maskLayer = m_cfg[[i]], maskValue = NA)}), "SpatRaster") expect_equal(nd[,3], nadf) } }) # Rebuild those test for landsat data test_that("returned classes", { vi <- list( spectralIndices(lsat, red = 4, nir = 5, indices = "NDVI"), spectralIndices(lsat, red = "B4_dn", nir = 5, indices = "NDVI"), spectralIndices(lsat, red = "B4_dn", nir = "B5_dn", indices = "NDVI"), spectralIndices(lsat, red = 4, nir = 5, indices = c("NDVI", "DVI", "MSAVI2")) ) ## Check numeric, mixed and character band indices expect_equal(vi[[1]], vi[[2]], info = "numeric vs. mixed band indexes") expect_equal(vi[[1]], vi[[3]], info = "numeric vs. character band indexes") ## Check layer numbers and names expect_equal(nlyr(vi[[1]]), 1) expect_identical(names(vi[[1]]), "NDVI") expect_identical(nlyr(suppressWarnings(spectralIndices(r, red = 1, nir = 2, indices = c("NDVI", "EVI")))), 1) expect_identical(nlyr(vi[[4]]), 3, info = "nlayers: 3 indices NDVI, MSAVI2, DVI") expect_identical(names(vi[[4]]), c("NDVI", "DVI", "MSAVI2"), info = "names: 3 indices NDVI, MSAVI2, DVI") ## Check index values ## NDVI like expect_lte(max(range(vi[[1]][], na.rm = TRUE)), 1) expect_gte(min(range(vi[[1]][], na.rm = TRUE)), -1) }) test_that("excercise all indices", { expect_is(sp <- spectralIndices(lsat, blue = 1, green=2, redEdge1=1, redEdge2=2, redEdge3=3, red=3, nir=4, swir2=5, swir3=7, coefs = list(L=0.4,s=0.3,swir2ccc=30,swir2coc=140), scaleFactor=255), "SpatRaster") expect_equal(nlyr(sp), length(.IDXdb)) }) ## Check for duplicate indices #tmat <- do.call(rbind, lapply(1:ncol(k), function(i){colSums(k[,i]-k, na.rm = T)==0})) #colnames(tmat) <- rownames(tmat) <- colnames(k)