loadCache {R.cache}

Loads data from file cache

Description

Loads data from file cache, which is unique for an optional key object.

Usage

## Default S3 method:
loadCache(key=NULL, sources=NULL, suffix=".Rcache", removeOldCache=TRUE, pathname=NULL,
  dirs=NULL, ..., onError=c("warning", "error", "message", "quiet", "print"))

Arguments

key

An optional object from which a hexadecimal hash code will be generated and appended to the filename.

sources

Optional source objects. If the cache object has a timestamp older than one of the source objects, it will be ignored and removed.

suffix

A character string to be appended to the end of the filename.

removeOldCache

If TRUE and the cache is older than the sources, the cache file is removed, otherwise not.

pathname

The pathname to the cache file. If specified, arguments key and suffix are ignored. Note that this is only needed in order to read a cache file for which the key is unknown, for instance, in order to investigate an unknown cache file.

dirs

A character vector constituting the path to the cache subdirectory (of the cache root directory as returned by getCacheRootPath()) to be used. If NULL, the path will be the cache root path.

...

Not used.

onError

A character string specifying what the action is if an exception is thrown.

Details

The hash code calculated from the key object is a 32 characters long hexadecimal MD5 hash code. For more details, see getChecksum().

Value

Returns an R object or NULL, if cache does not exist.

Author(s)

Henrik Bengtsson

See Also

saveCache().

Examples

simulate <- function(mean, sd) {
  # 1. Try to load cached data, if already generated
  key <- list(mean, sd)
  data <- loadCache(key)
  if (!is.null(data)) {
    cat("Loaded cached data\n")
    return(data);
  }

  # 2. If not available, generate it.
  cat("Generating data from scratch...")
  data <- rnorm(1000, mean=mean, sd=sd)
  Sys.sleep(1)             # Emulate slow algorithm
  cat("ok\n")
  saveCache(data, key=key, comment="simulate()")

  data;
}

data <- simulate(2.3, 3.0)
data <- simulate(2.3, 3.5)
data <- simulate(2.3, 3.0) # Will load cached data

# Clean up
file.remove(findCache(key=list(2.3,3.0)))
file.remove(findCache(key=list(2.3,3.5)))