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\name{mxComputeLoadMatrix}
\alias{mxComputeLoadMatrix}
\alias{MxComputeLoadMatrix-class}
\title{Load data from CSV files directly into the backend}
\usage{
mxComputeLoadMatrix(dest, method=c('csv','data.frame'), ...,
path=NULL, originalDataIsIndexOne=FALSE,
row.names=FALSE, col.names=FALSE, observed=NULL)
}
\arguments{
\item{dest}{a character vector of matrix names}
\item{method}{name of the conduit used to load the data.}
\item{...}{Not used. Forces remaining arguments to be specified by name.}
\item{path}{a character vector of paths}
\item{originalDataIsIndexOne}{logical. Whether to use the initial data
for index 1}
\item{row.names}{logical. Whether row names are present}
\item{col.names}{logical. Whether column names are present}
\item{observed}{data frame. The reservoir of data for \code{method='data.frame'}}
}
\description{
THIS INTERFACE IS EXPERIMENTAL AND SUBJECT TO CHANGE.
For method='csv', the file must be formatted in a specific way.
The number of columns must match the number of entries available
in the mxMatrix. Matrix types (e.g., symmetric or diagonal) are
respected (see \link{mxMatrix}). For example, a \emph{Full} 2x2
matrix will require 4 entries, but a diagonal matrix of the same size
will only require 2 entries.
CSV data must be stored space separated and without row or column
names.
The destination \code{mxMatrix} can have free parameters, but cannot
have square bracket populated entries.
If \code{originalDataIsIndexOne} is TRUE then this
compute step does nothing when the loop index is 1.
The purpose of \code{originalDataIsIndexOne} is to
permit usage of the dataset that was initially
included with the model.
}
\seealso{
\link{mxComputeLoadData}, \link{mxComputeCheckpoint}
}
\examples{
library(OpenMx)
dir <-tempdir() # safe place to create files
Cov <- rWishart(4, 20, toeplitz(c(2,1)/20))
write.table(t(apply(Cov, 3, vech)),
file=file.path(dir, "cov.csv"),
col.names=FALSE, row.names=FALSE)
Mean <- matrix(rnorm(8),4,2)
write.table(Mean, file=file.path(dir, "mean.csv"),
col.names=FALSE, row.names=FALSE)
m1 <- mxModel(
"test1",
mxMatrix("Full", 1,2, values=0, name="mean"),
mxMatrix("Symm", 2,2, values=diag(2), name="cov"),
mxMatrix("Full", 1,2, values=-1, name="lbound"),
mxMatrix("Full", 1,2, values=1, name="ubound"),
mxAlgebra(omxMnor(cov,mean,lbound,ubound), name="area"),
mxFitFunctionAlgebra("area"),
mxComputeLoop(list(
mxComputeLoadMatrix(c('mean', 'cov'),
path=file.path(dir, c('mean.csv', 'cov.csv'))),
mxComputeOnce('fitfunction', 'fit'),
mxComputeCheckpoint(path=file.path(dir, "loadMatrix.csv"))
), i=1:4))
m1 <- mxRun(m1)
}
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