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# This is the original test case that Timo & I wrote back in Spring 2013.
#options(error = utils::recover) # uncomment for more help with debugging
library(OpenMx)
library(mvtnorm)
#mxOption(key="Parallel diagnostics", value = "Yes")
set.seed(1)
more.noise <- 0
#more.noise <- 1
gen.data <- function(n) {
data.cov <- matrix(c(1, .2, .2, 1), byrow=TRUE, nrow=2)
latent <- rmvnorm(n, mean=c(0,0), sigma=data.cov)
colnames(latent) <- c("A","B")
latent <- as.data.frame(latent)
df <- data.frame(C=latent$A + latent$B,
D=latent$A - latent$B)
if (more.noise) {
df$C <- df$C + rnorm(1, sd=more.noise)
df$D <- df$D + rnorm(1, sd=more.noise)
}
df
}
fanout <- 5
school.data <- cbind(id=1:fanout, gen.data(fanout))
#school.data$C <- school.data$id * 1000
teacher.data <- cbind(schoolId=1:fanout, id=seq(1,fanout^2),
gen.data(fanout^2))
#teacher.data$C <- teacher.data$id * 100
student.data <- cbind(teacherId=seq(1,fanout^2),
id=seq(1,fanout^3), gen.data(fanout^3))
stack.data <- function(key, upper, lower) {
for (pk in upper$id) {
mask <- lower[[key]] == pk
for (col in c('C','D')) {
lower[mask, col] <-
lower[mask, col] + upper[upper$id == pk, 'C']
}
}
lower
}
teacher.data <- stack.data("schoolId", school.data, teacher.data)
student.data <- stack.data("teacherId", teacher.data, student.data)
manifests<-c("C","D")
latents<-c("A","B")
student <- mxModel(
"student", type="RAM",
manifestVars = manifests,
latentVars = latents,
mxPath(from="A",to=c("C","D"), free=c(FALSE,FALSE),
value=c(1,1), arrows=1,
label=c("A_TO_C","A_TO_D") ),
mxPath(from="B",to=c("C","D"), free=c(FALSE,FALSE), value=c(1,-1) ,
arrows=1, label=c("B_TO_C","B_TO_D") ),
mxPath(from="A",to=c("A","B"), free=c(TRUE,TRUE),
value=c(1,0), arrows=2,
label=c("VAR_A","COV_A_B") ),
mxPath(from="B",to=c("B"), free=c(TRUE), value=c(1) , arrows=2,
label=c("VAR_B") ),
mxPath(from="C",to=c("C"), free=as.logical(more.noise),
value=more.noise, arrows=2, label=c("VAR_C") ),
mxPath(from="D",to=c("D"), free=as.logical(more.noise),
value=more.noise, arrows=2, label=c("VAR_D") ),
mxPath(from="one", to=c(manifests, latents), value=0, free=FALSE)
);
relabel <- function(m, prefix) {
for (mat in c("A","S")) {
lab <- m[[mat]]$labels
lab[!is.na(lab)] <- paste0(prefix, lab[!is.na(lab)])
m[[mat]]$labels <- lab
}
m
}
teacher <- relabel(mxModel(student, name="teacher"), "tea_")
school <- relabel(mxModel(student, name="school"), "sch_")
student <- relabel(student, "st_")
school <- mxModel(
school,
mxData(school.data, type="raw", primaryKey="id"))
teacher <- mxModel(
teacher, school,
mxData(teacher.data, type="raw", primaryKey="id"),
mxPath('school.C', 'A', free=FALSE, value=1, joinKey="schoolId"))
student <- mxModel(
student, teacher,
mxData(student.data, type="raw", primaryKey="id"),
mxPath('teacher.C', 'A', free=FALSE, value=1, joinKey="teacherId"))
#student$expectation$verbose <- 1L
student$expectation$.rampartCycleLimit <- 0L
pt1 <- mxRun(mxModel(
student,
mxComputeSequence(list(
mxComputeOnce('fitfunction', 'fit'),
mxComputeNumericDeriv(checkGradient=FALSE,
iterations=2, hessian=FALSE),
mxComputeReportDeriv(),
mxComputeReportExpectation()))))
student$expectation$.rampartCycleLimit <- as.integer(NA)
pt2 <- mxRun(mxModel(
student,
mxComputeSequence(list(
mxComputeOnce('fitfunction', 'fit'),
mxComputeNumericDeriv(checkGradient=FALSE,
iterations=2, hessian=FALSE),
mxComputeReportDeriv(),
mxComputeReportExpectation()))))
omxCheckCloseEnough(pt2$expectation$debug$rampartUsage,
c((fanout-1)*fanout^2, (fanout-1)*fanout), 1)
omxCheckCloseEnough(pt2$expectation$debug$numGroups, 3)
if (0) {
layout <- pt2$expectation$debug$layout
head(layout[layout$group==3, ],n=20)
}
omxCheckCloseEnough(pt1$output$fit, pt2$output$fit, 1e-7)
omxCheckCloseEnough(pt1$output$gradient, pt2$output$gradient, 1e-2)
student <- mxRun(student)
if (!more.noise) {
omxCheckCloseEnough(student$output$fit, 1055.161, 1e-2)
} else {
omxCheckCloseEnough(student$output$fit, 1132.713, 1e-2) # but code RED
}
#print(student$expectation$debug$rampartUsage)
if (.Platform$OS.type != 'windows' && parallel::detectCores() > 1) {
omxCheckTrue(student$compute$steps[['GD']]$output$maxThreads > 1)
}
if (0) {
ex <- student$expectation
eo = ex$output
ed = ex$debug
ed$layout
}
got <- mxGenerateData(student)
omxCheckTrue(setequal(names(got), c("school", "teacher", "student")))
omxCheckTrue(setequal(colnames(got[['school']]),
colnames(student$school$data$observed)))
omxCheckTrue(all(got[['school']]$C != student$school$data$observed$C))
omxCheckError(mxGenerateData(student, 10, returnModel=TRUE),
paste("Specification of the number of rows",
"is not supported for relational models"))
got <- mxGenerateData(student, returnModel=TRUE)
omxCheckTrue(is(got, "MxModel"))
omxCheckTrue(all(got$school$data$observed$C != student$school$data$observed$C))
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