R Under development (unstable) (2023-12-13 r85679 ucrt) -- "Unsuffered Consequences"
Copyright (C) 2023 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.

> 
>  library(aster)
> 
>  # needed because of the change in R function "sample" in R-devel
>  suppressWarnings(RNGversion("3.5.2"))
> 
>  set.seed(42)
> 
>  nind <- 25
> 
>  vars <- c("l2", "l3", "f2", "f3", "h2", "h3")
>  pred <- c(0, 1, 1, 2, 3, 4)
>  fam <- c(1, 1, 1, 1, 3, 3)
>  length(pred) == length(fam)
[1] TRUE
>  nnode <- length(pred)
> 
>  theta <- matrix(0, nind, nnode)
>  root <- matrix(1, nind, nnode)
>  x <- raster(theta, pred, fam, root)
>  dimnames(x) <- list(NULL, vars)
> 
>  data <- as.data.frame(x)
>  site <- factor(sample(LETTERS[1:4], nind, replace = TRUE))
>  foo <- rnorm(nind)
>  data <- data.frame(x, site = site, foo = foo, root = 1)
> 
>  redata <- reshape(data, varying = list(vars),
+      direction = "long", timevar = "varb", times = as.factor(vars),
+      v.names = "resp")
> 
>  out <- aster(resp ~ foo + site + varb, pred, fam, varb, id, root,
+      data = redata)
>  sout1 <- summary(out, show.graph = TRUE)
> 
>  out2 <- aster(x, root, pred, fam, modmat = out$modmat)
>  sout2 <- summary(out2)
> 
>  out3 <- aster(x, root, pred, fam, modmat = out$modmat, type = "cond")
>  sout3 <- summary(out3)
> 
>  foo <- new.env(parent = emptyenv())
>  bar <- suppressWarnings(try(load("gradmat.rda", foo), silent = TRUE))
>  if (inherits(bar, "try-error")) {
+      save(sout1, sout2, sout3, file = "gradmat.rda")
+  } else {
+      print(all.equal(sout1, foo$sout1))
+      print(all.equal(sout2, foo$sout2))
+      print(all.equal(sout3, foo$sout3))
+  }
[1] TRUE
[1] TRUE
[1] TRUE
> 
>  foo <- match(sort(unique(site)), site)
>  modmat.pred <- out$modmat[foo, , ]
> 
>  ##### case 1: eta = theta, zeta = phi
> 
>  beta.hat <- out3$coef
> 
>  modmat.pred.mat <- matrix(modmat.pred, ncol = length(beta.hat))
> 
>  theta.hat <- matrix(modmat.pred.mat %*% beta.hat, nrow = dim(modmat.pred)[1])
> 
>  nind <- dim(modmat.pred)[1]
>  nnode <- dim(modmat.pred)[2]
>  ncoef <- dim(modmat.pred)[3]
> 
>  aster:::setfam(fam.default())
> 
>  phi.hat <- .C(aster:::C_aster_theta2phi,
+      nind = as.integer(nind),
+      nnode = as.integer(nnode),
+      pred = as.integer(pred),
+      fam = as.integer(fam),
+      theta = as.double(theta.hat),
+      phi = matrix(as.double(0), nind, nnode))$phi
> 
>  my.phi.hat <- theta.hat
>  my.phi.hat[ , 4] <- my.phi.hat[ , 4] - log(exp(exp(theta.hat[ , 6])) - 1)
>  my.phi.hat[ , 3] <- my.phi.hat[ , 3] - log(exp(exp(theta.hat[ , 5])) - 1)
>  my.phi.hat[ , 2] <- my.phi.hat[ , 2] - log(1 + exp(theta.hat[ , 4]))
>  my.phi.hat[ , 1] <- my.phi.hat[ , 1] - log(1 + exp(theta.hat[ , 3]))
>  my.phi.hat[ , 1] <- my.phi.hat[ , 1] - log(1 + exp(theta.hat[ , 2]))
>  all.equal(my.phi.hat, phi.hat)
[1] TRUE
>  
>  gradmat <- 0 * modmat.pred
>  storage.mode(gradmat) <- "double"
> 
>  gradmat <- .C(aster:::C_aster_D_beta2theta2phi,
+      nind = as.integer(nind),
+      nnode = as.integer(nnode),
+      ncoef = as.integer(ncoef),
+      pred = as.integer(pred),
+      fam = as.integer(fam),
+      theta = as.double(theta.hat),
+      modmat = as.double(modmat.pred),
+      gradmat = gradmat)$gradmat
> 
>  my.gradmat <- 0 * gradmat
>  epsilon <- 1e-9
>  for (k in 1:ncoef) {
+      beta.epsilon <- beta.hat
+      beta.epsilon[k] <- beta.hat[k] + epsilon
+      theta.epsilon <- matrix(modmat.pred.mat %*% beta.epsilon, nrow = nind)
+      phi.epsilon <- .C(aster:::C_aster_theta2phi,
+          nind = as.integer(nind),
+          nnode = as.integer(nnode),
+          pred = as.integer(pred),
+          fam = as.integer(fam),
+          theta = as.double(theta.epsilon),
+          phi = matrix(as.double(0), nind, nnode))$phi
+      my.gradmat[ , , k] <- (phi.epsilon - phi.hat) / epsilon
+  }
> 
>  all.equal(gradmat, my.gradmat, tolerance = sqrt(epsilon))
[1] TRUE
> 
>  ##### case 2: eta = phi, zeta = theta
> 
>  beta.hat <- out2$coef
> 
>  phi.hat <- matrix(modmat.pred.mat %*% beta.hat, nrow = nind)
> 
>  theta.hat <- .C(aster:::C_aster_phi2theta,
+      nind = as.integer(nind),
+      nnode = as.integer(nnode),
+      pred = as.integer(pred),
+      fam = as.integer(fam),
+      phi = as.double(phi.hat),
+      theta = matrix(as.double(0), nind, nnode))$theta
> 
>  gradmat <- .C(aster:::C_aster_D_beta2phi2theta,
+      nind = as.integer(nind),
+      nnode = as.integer(nnode),
+      ncoef = as.integer(ncoef),
+      pred = as.integer(pred),
+      fam = as.integer(fam),
+      theta = as.double(theta.hat),
+      modmat = as.double(modmat.pred),
+      gradmat = gradmat)$gradmat
> 
>  my.gradmat <- 0 * gradmat
>  epsilon <- 1e-9
>  for (k in 1:ncoef) {
+      beta.epsilon <- beta.hat
+      beta.epsilon[k] <- beta.hat[k] + epsilon
+      phi.epsilon <- matrix(modmat.pred.mat %*% beta.epsilon, nrow = nind)
+      theta.epsilon <- .C(aster:::C_aster_phi2theta,
+          nind = as.integer(nind),
+          nnode = as.integer(nnode),
+          pred = as.integer(pred),
+          fam = as.integer(fam),
+          phi = as.double(phi.epsilon),
+          theta = matrix(as.double(0), nind, nnode))$theta
+      my.gradmat[ , , k] <- (theta.epsilon - theta.hat) / epsilon
+  }
> 
>  all.equal(gradmat, my.gradmat, tolerance = sqrt(epsilon))
[1] TRUE
> 
>  ##### case 3: eta = phi, zeta = tau
> 
>  root.pred <- matrix(1, nind, nnode)
> 
>  beta.hat <- out2$coef
> 
>  beta2tau <- function(beta) {
+ 
+      phi <- matrix(modmat.pred.mat %*% beta, nrow = nind)
+ 
+      theta <- .C(aster:::C_aster_phi2theta,
+          nind = as.integer(nind),
+          nnode = as.integer(nnode),
+          pred = as.integer(pred),
+          fam = as.integer(fam),
+          phi = as.double(phi),
+          theta = matrix(as.double(0), nind, nnode))$theta
+ 
+      ctau <- .C(aster:::C_aster_theta2ctau,
+          nind = as.integer(nind),
+          nnode = as.integer(nnode),
+          pred = as.integer(pred),
+          fam = as.integer(fam),
+          theta = as.double(theta),
+          ctau = double(nind * nnode))$ctau
+ 
+      tau <- .C(aster:::C_aster_ctau2tau,
+          nind = as.integer(nind),
+          nnode = as.integer(nnode),
+          pred = as.integer(pred),
+          fam = as.integer(fam),
+          root = as.double(root.pred),
+          ctau = as.double(ctau),
+          tau = double(nind * nnode))$tau
+ 
+      return(tau)
+  }
> 
>  tau.hat <- beta2tau(beta.hat)
> 
>  gradmat <- .C(aster:::C_aster_D_beta2phi2tau,
+      nind = as.integer(nind),
+      nnode = as.integer(nnode),
+      ncoef = as.integer(ncoef),
+      pred = as.integer(pred),
+      fam = as.integer(fam),
+      beta = as.double(beta.hat),
+      root = as.double(root.pred),
+      origin = rep(as.double(0), nind * nnode),
+      modmat = as.double(modmat.pred),
+      gradmat = gradmat)$gradmat
> 
>  my.gradmat <- 0 * gradmat
>  epsilon <- 1e-9
>  for (k in 1:ncoef) {
+      beta.epsilon <- beta.hat
+      beta.epsilon[k] <- beta.hat[k] + epsilon
+      tau.epsilon <- beta2tau(beta.epsilon)
+      my.gradmat[ , , k] <- (tau.epsilon - tau.hat) / epsilon
+  }
> 
>  all.equal(gradmat, my.gradmat, tolerance = sqrt(epsilon))
[1] TRUE
> 
>  ##### case 4: eta = theta, zeta = tau
> 
>  beta.hat <- out3$coef
> 
>  beta2tau <- function(beta) {
+ 
+      theta <- matrix(modmat.pred.mat %*% beta, nrow = nind)
+ 
+      ctau <- .C(aster:::C_aster_theta2ctau,
+          nind = as.integer(nind),
+          nnode = as.integer(nnode),
+          pred = as.integer(pred),
+          fam = as.integer(fam),
+          theta = as.double(theta),
+          ctau = double(nind * nnode))$ctau
+ 
+      tau <- .C(aster:::C_aster_ctau2tau,
+          nind = as.integer(nind),
+          nnode = as.integer(nnode),
+          pred = as.integer(pred),
+          fam = as.integer(fam),
+          root = as.double(root.pred),
+          ctau = as.double(ctau),
+          tau = double(nind * nnode))$tau
+ 
+      return(tau)
+  }
> 
>  tau.hat <- beta2tau(beta.hat)
> 
>  gradmat <- .C(aster:::C_aster_D_beta2theta2tau,
+      nind = as.integer(nind),
+      nnode = as.integer(nnode),
+      ncoef = as.integer(ncoef),
+      pred = as.integer(pred),
+      fam = as.integer(fam),
+      beta = as.double(beta.hat),
+      root = as.double(root.pred),
+      modmat = as.double(modmat.pred),
+      gradmat = gradmat)$gradmat
> 
>  my.gradmat <- 0 * gradmat
>  for (k in 1:ncoef) {
+      beta.epsilon <- beta.hat
+      beta.epsilon[k] <- beta.hat[k] + epsilon
+      tau.epsilon <- beta2tau(beta.epsilon)
+      my.gradmat[ , , k] <- (tau.epsilon - tau.hat) / epsilon
+  }
> 
>  all.equal(gradmat, my.gradmat, tolerance = sqrt(epsilon))
[1] TRUE
> 
> 
> proc.time()
   user  system elapsed 
   0.25    0.03    0.26