1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
|
## @kaskr points out that this may not be the most effective timing check
## as repeated data may be optimized away by subexpression elimination:
## https://github.com/glmmTMB/glmmTMB/pull/652#issuecomment-821025662
## timingFuns.R _should_ be in the working directory (.../vignettes) but ??
if (file.exists("timingFuns.R")) {
source("timingFuns.R")
data(InstEval,package="lme4")
library("lme4")
library("glmmTMB")
library("plyr") ## load before dplyr; for ldply()
library("tidyr")
library("dplyr")
## make sure this is run with optimized build of glmmTMB,
## i.e. "make install" rather than "make quick-install/quick-check"
## (or at least document)
nvals <- seq(0.1, 1, by=0.1)
form <- y~service+lectage+studage+(1|d)+(1|s)+(1|dept)
tmat <- ldply(nvals, getTimes, basedata=InstEval,
form=form, family=NULL, which=c("glmmTMB", "lmer"),
.progress="text")
## reshape: wide-to-long, add n values
ff <- function(dd, n=seq(nrow(dd))) {
mutate(dd, n = nvals) %>%
gather(pkg, time, -n)
}
tmatInstEval <- ff(tmat)
save("tmatInstEval", file="InstEvalTimings.rda")
} ## if timingFuns.R is available
|
