Demo failing #5
Description
Failing demo with fmri.lm:
library(fmri)
#> Loading required package: awsMethods
#>
#> Use the function setCores() to change the number of CPU cores.
#> Loading required package: nlme
demo("fmri", package = "fmri")
#>
#>
#> demo(fmri)
#> ---- ~~~~
#>
#> > require(fmri)
#>
#> > gkernsm <- function(y,h=1) {
#> + grid <- function(d) {
#> + d0 <- d%/%2+1
#> + gd <- seq(0,1,length=d0)
#> + if (2*d0==d+1) gd <- c(gd,-gd[d0:2]) else gd <- c(gd,-gd[(d0-1):2])
#> + gd
#> + }
#> + dy <- dim(y)
#> + if (is.null(dy)) dy<-length(y)
#> + ldy <- length(dy)
#> + if (length(h)!=ldy) h <- rep(h[1],ldy)
#> + kern <- switch(ldy,dnorm(grid(dy),0,2*h/dy),
#> + outer(dnorm(grid(dy[1]),0,2*h[1]/dy[1]),
#> + dnorm(grid(dy[2]),0,2*h[2]/dy[2]),"*"),
#> + outer(outer(dnorm(grid(dy[1]),0,2*h[1]/dy[1]),
#> + dnorm(grid(dy[2]),0,2*h[2]/dy[2]),"*"),
#> + dnorm(grid(dy[3]),0,2*h[3]/dy[3]),"*"))
#> + kern <- kern/sum(kern)
#> + kernsq <- sum(kern^2)
#> + list(gkernsm=convolve(y,kern,conj=TRUE),kernsq=kernsq)
#> + }
#>
#> > create.mask <- function(){
#> + mask <- array(0,dim=c(65,65,26))
#> + mask[5:10,5:10,] <- 1
#> + mask[7:8,7:8,] <- 0
#> + mask[8:10,8:10,] <- 0
#> + mask[14:17,14:17,] <- 1
#> + mask[16:17,16:17,] <- 0
#> + mask[21:23,21:23,] <- 1
#> + mask[22:23,23,] <- 0
#> + mask[23,22,] <- 0
#> + mask[27:28,27:28,] <- 1
#> + mask[28,28,] <- 0
#> + mask[5:7,29:33,] <- 1
#> + mask[7,32:33,] <- 0
#> + mask[14:15,30:33,] <- 1
#> + mask[15,30,] <- 0
#> + mask[21,31:33,] <- 1
#> + mask[22,33,] <- 1
#> + mask[27,32:33,] <- 1
#> + mask[29:33,5:7,] <- 1
#> + mask[32:33,7,] <- 0
#> + mask[30:33,14:15,] <- 1
#> + mask[30,15,] <- 0
#> + mask[31:33,21,] <- 1
#> + mask[33,22,] <- 1
#> + mask[32:33,27,] <- 1
#> + mask[34:65,1:33,] <- mask[32:1,1:33,]
#> + mask[1:33,34:65,] <- mask[1:33,32:1,]
#> + mask[34:65,34:65,] <- mask[32:1,32:1,]
#> + mask
#> + }
#>
#> > create.sig <- function(signal=1.5,efactor=1.2){
#> + sig <- array(0,dim=c(65,65,26))
#> + sig[29:37,38:65,] <- signal
#> + sig[38:65,38:65,] <- signal * efactor
#> + sig[38:65,29:37,] <- signal * efactor^2
#> + sig[38:65,1:28,] <- signal * efactor^3
#> + sig[29:37,1:28,] <- signal * efactor^4
#> + sig[1:28,1:28,] <- signal * efactor^5
#> + sig[1:28,29:37,] <- signal * efactor^6
#> + sig[1:28,38:65,] <- signal * efactor^7
#> + sig * create.mask()
#> + }
#>
#> > # some values describing the data
#> > signal <- 1.5
#>
#> > noise <- 20
#>
#> > arfactor <- .3
#>
#> > # maximaum bandwidth for adaptive smoothing
#> > hmax <- 3.06
#>
#> > # datacube dimension
#> > i <- 65
#>
#> > j <- 65
#>
#> > k <- 26
#>
#> > scans <- 107
#>
#> > # define needed arrays
#> > ttt <- array(0,dim=c(i,j,k,scans))
#>
#> > sig <- array(0,dim=c(i,j,k))
#>
#> > # create the mask for activation
#> > mask <- create.mask()
#>
#> > # assign amplitudes of signals to activated areas
#> > sig <- create.sig(signal)
#>
#> > # expected BOLD response for some stimulus
#> > hrf <- signal * fmri.stimulus(scans, c(18, 48, 78), 15, 2)
#>
#> > # create time series
#> > dim(sig) <- c(i*j*k,1)
#>
#> > dim(hrf) <- c(1,scans)
#>
#> > sig4 <- sig %*% hrf
#>
#> > dim(sig) <- c(i,j,k)
#>
#> > dim(sig4) <- c(i,j,k,scans)
#>
#> > # create noise with spatial and temporal correlation
#> > set.seed(1)
#>
#> > noisy4 <- rnorm(i*j*k*scans,0,noise)
#>
#> > dim(noisy4) <- c(i,j,k,scans)
#>
#> > for (t in 2:scans) noisy4[,,,t] <- noisy4[,,,t] + arfactor*noisy4[,,,t-1]
#>
#> > for (t in 1:scans) noisy4[,,,t] <- gkernsm(noisy4[,,,t],c(0.8,0.8,0.4))$gkernsm
#>
#> > # finally we got the data
#> > ttt <- sig4 + noisy4
#>
#> > data1 <- list(ttt=writeBin(as.numeric(ttt),raw(),4),
#> + dim=c(i,j,k,scans),weights=c(1,1,2),mask=array(1,c(i,j,k)),
#> + delta = rep(1, 4))
#>
#> > class(data1) <- "fmridata"
#>
#> > # create design matrix and estimate parameters from linear model
#> > hrf <- fmri.stimulus(scans, c(18, 48, 78), 15, 2)
#>
#> > z <- fmri.design(hrf)
#>
#> > spm <- fmri.lm(data1,z)
#> Error in optim(c(2, 2, 2), corrrisk, method = "L-BFGS-B", lower = c(0.59, : L-BFGS-B needs finite values of 'fn'Created on 2019-08-26 by the reprex package (v0.3.0)
Session info
devtools::session_info()
#> ─ Session info ──────────────────────────────────────────────────────────
#> setting value
#> version R version 3.6.0 (2019-04-26)
#> os macOS Mojave 10.14.6
#> system x86_64, darwin15.6.0
#> ui X11
#> language (EN)
#> collate en_US.UTF-8
#> ctype en_US.UTF-8
#> tz America/New_York
#> date 2019-08-26
#>
#> ─ Packages ──────────────────────────────────────────────────────────────
#> package * version date lib source
#> assertthat 0.2.1 2019-03-21 [1] CRAN (R 3.6.0)
#> aws 2.2-1 2019-05-08 [1] CRAN (R 3.6.0)
#> awsMethods * 1.1-1 2019-05-08 [1] CRAN (R 3.6.0)
#> backports 1.1.4 2019-04-10 [1] CRAN (R 3.6.0)
#> callr 3.3.1 2019-07-18 [1] CRAN (R 3.6.0)
#> cli 1.1.0 2019-03-19 [1] CRAN (R 3.6.0)
#> crayon 1.3.4 2017-09-16 [1] CRAN (R 3.6.0)
#> desc 1.2.0 2019-07-10 [1] Github (muschellij2/desc@b0c374f)
#> devtools 2.1.0 2019-07-06 [1] CRAN (R 3.6.0)
#> digest 0.6.20 2019-07-04 [1] CRAN (R 3.6.0)
#> evaluate 0.14 2019-05-28 [1] CRAN (R 3.6.0)
#> fmri * 1.9.1 2019-08-26 [1] Github (WIAS-BERLIN/fmri@7ec7719)
#> fs 1.3.1 2019-05-06 [1] CRAN (R 3.6.0)
#> glue 1.3.1 2019-03-12 [1] CRAN (R 3.6.0)
#> gsl 2.1-6 2019-03-25 [1] CRAN (R 3.6.0)
#> highr 0.8 2019-03-20 [1] CRAN (R 3.6.0)
#> htmltools 0.3.6 2017-04-28 [1] CRAN (R 3.6.0)
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#> magrittr 1.5 2014-11-22 [1] CRAN (R 3.6.0)
#> Matrix 1.2-17 2019-03-22 [1] CRAN (R 3.6.0)
#> memoise 1.1.0 2017-04-21 [1] CRAN (R 3.6.0)
#> metafor 2.1-0 2019-05-14 [1] CRAN (R 3.6.0)
#> nlme * 3.1-140 2019-05-12 [1] CRAN (R 3.6.0)
#> pkgbuild 1.0.3 2019-03-20 [1] CRAN (R 3.6.0)
#> pkgload 1.0.2 2018-10-29 [1] CRAN (R 3.6.0)
#> prettyunits 1.0.2 2015-07-13 [1] CRAN (R 3.6.0)
#> processx 3.4.1 2019-07-18 [1] CRAN (R 3.6.0)
#> ps 1.3.0 2018-12-21 [1] CRAN (R 3.6.0)
#> R6 2.4.0 2019-02-14 [1] CRAN (R 3.6.0)
#> Rcpp 1.0.2 2019-07-25 [1] CRAN (R 3.6.0)
#> remotes 2.1.0 2019-06-24 [1] CRAN (R 3.6.0)
#> rlang 0.4.0 2019-06-25 [1] CRAN (R 3.6.0)
#> rmarkdown 1.14 2019-07-12 [1] CRAN (R 3.6.0)
#> rprojroot 1.3-2 2018-01-03 [1] CRAN (R 3.6.0)
#> sessioninfo 1.1.1 2018-11-05 [1] CRAN (R 3.6.0)
#> stringi 1.4.3 2019-03-12 [1] CRAN (R 3.6.0)
#> stringr 1.4.0 2019-02-10 [1] CRAN (R 3.6.0)
#> testthat 2.1.1 2019-04-23 [1] CRAN (R 3.6.0)
#> usethis 1.5.1.9000 2019-08-15 [1] local
#> withr 2.1.2 2018-03-15 [1] CRAN (R 3.6.0)
#> xfun 0.8 2019-06-25 [1] CRAN (R 3.6.0)
#> yaml 2.2.0 2018-07-25 [1] CRAN (R 3.6.0)
#>
#> [1] /Library/Frameworks/R.framework/Versions/3.6/Resources/library