#' #' Header for all (concatenated) test files #' #' Require spatstat.geom #' Obtain environment variable controlling tests. #' #' $Revision: 1.5 $ $Date: 2020/04/30 05:31:37 $ require(spatstat.geom) FULLTEST <- (nchar(Sys.getenv("SPATSTAT_TEST", unset="")) > 0) ALWAYS <- TRUE cat(paste("--------- Executing", if(FULLTEST) "** ALL **" else "**RESTRICTED** subset of", "test code -----------\n")) # # tests/hyperframe.R # # test "[.hyperframe" etc # # $Revision: 1.11 $ $Date: 2023/02/03 06:17:16 $ # if(FULLTEST) { local({ lambda <- runif(4, min=50, max=100) X <- lapply(as.list(lambda), function(x) { runifrect(rpois(1, x)) }) h <- hyperframe(lambda=lambda, X=X) h$lambda2 <- lambda^2 h[, "lambda3"] <- lambda^3 h[, "Y"] <- X h[, "X"] <- lapply(X, flipxy) h[, c("X", "Y")] <- hyperframe(X=X, Y=X) names(h) <- LETTERS[1:5] print(h) summary(h) str(h) head(h) tail(h) rn <- rownames(h) r.n <- row.names(h) if(!identical(rn, r.n)) stop("rownames and row.names conflict for hyperframes") dn <- dimnames(h) dimnames(h) <- dn dimnames(h)[[2]][2] <- "copacetic" dimnames(h)[[1]][2] <- "second" #' hyperframe with a hyperatom H <- hyperframe(A=runif(3), B=1:3, D=runifrect(10)) H[,3] H[,3,drop=TRUE] #' special cases of [<- H$B <- H[,1] H[2:3,1] <- H[2:3,2] H[2:3,1] <- H[2,2] H[2,1:2] <- H[3,1:2] #' split f <- factor(c("a", "a", "b")) G <- split(H, f) G[["a"]]$B <- 42 split(H, f) <- G #' [[ and [[<- junk <- pyramidal a <- junk[["group"]] junk[["group"]] <- sample(a) a <- junk[[2]] a <- junk[[15,2]] junk[[15,2]] <- "schizoaffective" junk[[15,2]] <- "z" # Warning given. a <- junk[[2]] # The warned-about NA appears as entry 15. junk[[10,1]] <- cells a <- junk[[10,1]] a <- junk[[10,"Neurons"]] }) } # # tests/imageops.R # # $Revision: 1.42 $ $Date: 2023/07/17 06:34:00 $ # if(FULLTEST) { local({ #' cases of 'im' data tab <- table(sample(factor(letters[1:10]), 30, replace=TRUE)) b <- im(tab, xrange=c(0,1), yrange=c(0,10)) b <- update(b) mat <- matrix(sample(0:4, 12, replace=TRUE), 3, 4) a <- im(mat) levels(a$v) <- 0:4 a <- update(a) levels(mat) <- 0:4 b <- im(mat) b <- update(b) D <- as.im(mat, letterR) df <- as.data.frame(D) DD <- as.im(df, step=c(D$xstep, D$ystep)) #' various manipulations AA <- A <- as.im(owin()) BB <- B <- as.im(owin(c(1.1, 1.9), c(0,1))) Z <- imcov(A, B) stopifnot(abs(max(Z) - 0.8) < 0.1) Frame(AA) <- Frame(B) Frame(BB) <- Frame(A) ## handling images with 1 row or column ycov <- function(x, y) y E <- as.im(ycov, owin(), dimyx = c(2,1)) G <- cut(E, 2) H <- as.tess(G) E12 <- as.im(ycov, owin(), dimyx = c(1,2)) G12 <- cut(E12, 2) H12 <- as.tess(G12) AAA <- as.array(AA) EEE <- as.array(E) AAD <- as.double(AA) EED <- as.double(E) aaa <- xtfrm(AAA) eee <- xtfrm(E) ## d <- distmap(cells, dimyx=32) D6 <- (d <= 0.06) Z <- connected(D6, method="interpreted") Z <- connected(D6, connect=4) Z <- connected(D6, method="interpreted", connect=4) a <- where.max(d, first=FALSE) a <- where.min(d, first=FALSE) dx <- raster.x(d) dy <- raster.y(d) dxy <- raster.xy(d) xyZ <- raster.xy(Z, drop=TRUE) horosho <- conform.imagelist(cells, list(d, Z)) #' split.im W <- square(1) X <- as.im(function(x,y){x}, W) Y <- dirichlet(runifrect(7, W)) Z <- split(X, as.im(Y)) ## ........... cases of "[.im" ........................ ## index window has zero overlap area with image window Out <- owin(c(-0.5, 0), c(0,1)) oo <- X[Out] oo <- X[Out, drop=FALSE] if(!is.im(oo)) stop("Wrong format in [.im with disjoint index window") oon <- X[Out, drop=TRUE, rescue=FALSE] if(is.im(oon)) stop("Expected a vector of values, not an image, from [.im") if(!all(is.na(oon))) stop("Expected a vector of NA values in [.im") ## Empty <- cells[FALSE] ff <- d[Empty] gg <- d[2,] gg <- d[,2] gg <- d[j=2] gg <- d[2:4, 3:5] hh <- d[2:4, 3:5, rescue=TRUE] if(!is.im(hh)) stop("rectangle was not rescued in [.im") ## factor and NA values f <- cut(d, breaks=4) f <- f[f != levels(f)[1], drop=FALSE] fff <- f[, , drop=FALSE] fff <- f[cells] fff <- f[cells, drop=FALSE] fff <- f[Empty] ## ........... cases of "[<-.im" ....................... d[,] <- d[] + 1 d[Empty] <- 42 ## smudge() and rasterfilter() dd <- smudge(d) ## rgb/hsv options X <- setcov(owin()) M <- Window(X) Y <- as.im(function(x,y) x, W=M) Z <- as.im(function(x,y) y, W=M) # convert after rescaling RGBscal <- rgbim(X, Y, Z, autoscale=TRUE, maxColorValue=1) HSVscal <- hsvim(X, Y, Z, autoscale=TRUE) #' cases of [.im Ma <- as.mask(M, dimyx=37) ZM <- Z[raster=Ma, drop=FALSE] ZM[solutionset(Y+Z > 0.4)] <- NA ZF <- cut(ZM, breaks=5) ZL <- (ZM > 0) P <- list(x=c(0.511, 0.774, 0.633, 0.248, 0.798), y=c(0.791, 0.608, 0.337, 0.613, 0.819)) zmp <- ZM[P, drop=TRUE] zfp <- ZF[P, drop=TRUE] zlp <- ZL[P, drop=TRUE] P <- as.ppp(P, owin()) zmp <- ZM[P, drop=TRUE] zfp <- ZF[P, drop=TRUE] zlp <- ZL[P, drop=TRUE] #' miscellaneous ZZ <- zapsmall.im(Z, digits=6) ZZ <- zapsmall.im(Z) ZS <- shift(Z, origin="centroid") ZS <- shift(Z, origin="bottomleft") ZA <- affine(Z, mat=diag(c(-1,-2))) U <- scaletointerval(Z) C <- as.im(1, W=U) U <- scaletointerval(C) #' hist.im h <- hist(Z) h <- hist(Z, probability=TRUE) h <- hist(Z, plot=FALSE) Zcut <- cut(Z, breaks=5) h <- hist(Zcut) # barplot hp <- hist(Zcut, probability=TRUE) # barplot plot(h) # plot.barplotdata #' plot.im code blocks plot(Z, ribside="left") plot(Z, ribside="top") plot(Z, riblab="value") plot(Z, clipwin=square(0.5)) plot(Z - mean(Z), log=TRUE) plot(Z, valuesAreColours=TRUE) # rejected with a warning IX <- as.im(function(x,y) { as.integer(round(3*x)) }, square(1)) co <- colourmap(rainbow(4), inputs=0:3) plot(IX, col=co) CX <- eval.im(col2hex(IX+1L)) plot(CX, valuesAreColours=TRUE) plot(CX, valuesAreColours=FALSE) #' plot.im contour code logarithmic case V0 <- setcov(owin()) V2 <- exp(2*V0+1) plot(V2, log=TRUE, addcontour=TRUE, contourargs=list(col="white")) plot(V2, log=TRUE, addcontour=TRUE, contourargs=list(col="white", nlevels=2)) plot(V2, log=TRUE, addcontour=TRUE, contourargs=list(col="white", nlevels=20)) V4 <- exp(4*V0+1) plot(V4, log=TRUE, addcontour=TRUE, contourargs=list(col="white")) plot(V4, log=TRUE, addcontour=TRUE, contourargs=list(col="white", nlevels=2)) plot(V4, log=TRUE, addcontour=TRUE, contourargs=list(col="white", nlevels=20)) #' pairs.im pairs(solist(Z)) pairs(solist(A=Z)) #' handling and plotting of character and factor images Afactor <- as.im(col2hex("green"), letterR, na.replace=col2hex("blue")) Acharacter <- as.im(col2hex("green"), letterR, na.replace=col2hex("blue"), stringsAsFactors=FALSE) plot(Afactor) plot(Acharacter, valuesAreColours=TRUE) print(summary(Afactor)) print(summary(Acharacter)) #' substitute for runifpoint rup <- function(n, W) { runifrect(n, Frame(W))[W] } #' safelookup (including extrapolation case) Z <- as.im(function(x,y) { x - y }, letterR) Zcut <- cut(Z, breaks=4) B <- grow.rectangle(Frame(letterR), 1) X <- superimpose(rup(10, letterR), rup(20, setminus.owin(B, letterR)), vertices(Frame(B)), W=B) a <- safelookup(Z, X) aa <- safelookup(Z, X, factor=100) b <- safelookup(Zcut, X) bb <- safelookup(Zcut, X, factor=100) cc <- lookup.im(Z, X) #' im.apply Z <- im.apply(bei.extra, sd) #' Math.imlist, Ops.imlist, Complex.imlist U <- Z+2i B <- U * (2+1i) print(summary(B)) V <- solist(A=U, B=B) negV <- -V E <- Re(V) negE <- -E }) } if(ALWAYS) { local({ #' check nearest.valid.pixel W <- Window(demopat) set.seed(911911) X <- runifrect(1000, Frame(W))[W] Z <- quantess(W, function(x,y) { x }, 9)$image nearest.valid.pixel(numeric(0), numeric(0), Z) x <- X$x y <- X$y a <- nearest.valid.pixel(x, y, Z, method="interpreted") b <- nearest.valid.pixel(x, y, Z, method="C") if(!isTRUE(all.equal(a,b))) stop("Unequal results in nearest.valid.pixel") if(!identical(a,b)) stop("Equal, but not identical, results in nearest.valid.pixel") }) }