R: Load columns into an MxData object

mxComputeLoadData {OpenMx} | R Documentation

## Load columns into an MxData object

### Description

### Usage

    mxComputeLoadData(
      dest,
      column,
      method = c("csv", "data.frame"),
      ...,
      path = c(),
      originalDataIsIndexOne = FALSE,
      byrow = TRUE,
      row.names = c(),
      col.names = c(),
      skip.rows = 0,
      skip.cols = 0,
      verbose = 0L,
      cacheSize = 100L,
      checkpointMetadata = TRUE,
      na.strings = c("NA"),
      observed = NULL,
      rowFilter = c()
    )

### Arguments

`dest` | the name of the model where the columns will be loaded
`column` | a character vector. The column names to replace.
`method` | name of the conduit used to load the columns.
`...` | Not used. Forces remaining arguments to be specified by name.
`path` | the path to the file containing the data
`originalDataIsIndexOne` | logical. Whether to use the initial data for index 1
`byrow` | logical. Whether the data columns are stored in rows.
`row.names` | optional integer. Column containing the row names.
`col.names` | optional integer. Row containing the column names.
`skip.rows` | integer. Number of rows to skip before reading data.
`skip.cols` | integer. Number of columns to skip before reading data.
`verbose` | integer. Level of run-time diagnostic output. Set to zero to disable
`cacheSize` | integer. How many columns to cache per scan through the data. Only used when byrow=FALSE.
`checkpointMetadata` | logical. Whether to add per record metadata to the checkpoint
`na.strings` | character vector. A vector of strings that denote a missing value.
`observed` | data frame. The reservoir of data for `method='data.frame'`.
`rowFilter` | logical vector. Whether to skip the source row.

### Details

The purpose of this compute step is to help quickly perform many similar analyses. For example, if we are given a sample of people with a few million SNPs (single-nucleotide polymorphism) per person then we could fit a separate model for each SNP by iterating over the SNP data.

The column names given in the `column` parameter must already exist in the model's MxData object. Pre-existing data is assumed to be a placeholder and is not used unless `originalDataIsIndexOne` is set to TRUE.

For `method='csv'`, the highest performance arrangement is `byrow=TRUE` because entire columns are stored in single chunks (rows) on the disk and can be easily loaded. For `byrow=FALSE`, the data requires transposition. To load a single column of observed data, it is necessary to read through the whole file. This can be slow for large files. To amortize the cost of transposition, `cacheSize` columns are loaded on every pass through the file.

After `mxRun` returns, the `dest` mxData object will contain the most recently loaded data. Hence, any single analysis of a series can be reproduced by issuing `mxComputeLoadData` with the single index associated with a particular dataset, replacing the compute plan with something like `omxDefaultComputePlan`, and then passing the model back through `mxRun`. This can be a helpful approach when investigating unexpected results.

### See Also

mxComputeLoadMatrix, mxComputeCheckpoint, mxRun, omxDefaultComputePlan

[Package OpenMx version 2.19.5 Index]