2nd try!!

[ape.git] / R / ace.R

diff --git a/R/ace.R b/R/ace.R
index f728ee7c6045f9478e21fa0edd1e12fafa5aa4fa..9ea659001688562e42f6e6f557b22720ad0830b2 100644 (file)
--- a/R/ace.R
+++ b/R/ace.R
@@ -1,4 +1,4 @@
-## ace.R (2010-02-03)
+## ace.R (2010-04-23)
 
 ##   Ancestral Character Estimation
 
@@ -157,9 +157,10 @@ as the number of categories in `x'")
         phy <- reorder(phy, "pruningwise")
 
         Q <- matrix(0, nl, nl)
-        ## from Rich FitzJohn:
-        comp <- numeric(nb.tip + nb.node) # Storage...
         dev <- function(p, output.liks = FALSE) {
+            if (any(is.nan(p)) || any(is.infinite(p))) return(1e50)
+            ## from Rich FitzJohn:
+            comp <- numeric(nb.tip + nb.node) # Storage...
             Q[] <- c(p, 0)[rate]
             diag(Q) <- -rowSums(Q)
             for (i  in seq(from = 1, by = 2, length.out = nb.node)) {
@@ -177,7 +178,7 @@ as the number of categories in `x'")
             -2 * sum(log(comp[-TIPS]))
         }
         out <- nlminb(rep(ip, length.out = np), function(p) dev(p),
-                      lower = rep(0, np), upper = rep(Inf, np))
+                      lower = rep(0, np), upper = rep(1e50, np))
         obj$loglik <- -out$objective/2
         obj$rates <- out$par
         oldwarn <- options("warn")
@@ -229,3 +230,24 @@ anova.ace <- function(object, ...)
     structure(table, heading = "Likelihood Ratio Test Table",
               class = c("anova", "data.frame"))
 }
+
+print.ace <- function(x, digits = 4, ...)
+{
+    cat("\n    Ancestral Character Reconstruction\n\n")
+    cat("Call: ")
+    print(x$call)
+    cat("\n")
+    cat("    Log-likelihood:", x$loglik, "\n\n")
+    cat("Rate index matrix:\n")
+    ratemat <- x$index.matrix
+    dimnames(ratemat)[1:2] <- dimnames(x$lik.anc)[2]
+    print(ratemat, na.print = ".")
+    cat("\n")
+    npar <- length(x$rates)
+    estim <- data.frame(1:npar, round(x$rates, digits), round(x$se, digits))
+    cat("Parameter estimates:\n")
+    names(estim) <- c("rate index", "estimate", "std-err")
+    print(estim, row.names = FALSE)
+    cat("\nScaled likelihoods at the root (type 'x$lik.anc' to get them for all nodes):\n")
+    print(x$lik.anc[1, ])
+}