mxComputeLoadMatrix | R Documentation |
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 mxMatrix). For example, a 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 mxMatrix
can have free parameters, but cannot
have square bracket populated entries.
If originalDataIsIndexOne
is TRUE then this
compute step does nothing when the loop index is 1.
The purpose of originalDataIsIndexOne
is to
permit usage of the dataset that was initially
included with the model.
mxComputeLoadMatrix(dest, method=c('csv','data.frame'), ...,
path=NULL, originalDataIsIndexOne=FALSE,
row.names=FALSE, col.names=FALSE, observed=NULL)
dest |
a character vector of matrix names |
method |
name of the conduit used to load the data. |
... |
Not used. Forces remaining arguments to be specified by name. |
path |
a character vector of paths |
originalDataIsIndexOne |
logical. Whether to use the initial data for index 1 |
row.names |
logical. Whether row names are present |
col.names |
logical. Whether column names are present |
observed |
data frame. The reservoir of data for |
mxComputeLoadData, mxComputeCheckpoint
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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