aggregated: Get aggregated data
In opm: Analysing Phenotype Microarray and Growth Curve Data

Description Usage Arguments Details Value See Also Examples

Get the aggregated kinetic data or the aggregation settings used. (See do_aggr for generating aggregated data.)

  ## S4 method for signature 'MOPMX'
aggr_settings(object, join = NULL) 
  ## S4 method for signature 'OPMA'
aggr_settings(object, join = NULL) 
  ## S4 method for signature 'OPMS'
aggr_settings(object, join = NULL) 

  ## S4 method for signature 'MOPMX'
aggregated(object, ...) 
  ## S4 method for signature 'OPMA'
aggregated(object, subset = NULL, ci = TRUE,
    trim = c("no", "full", "medium"), full = FALSE, in.parens = TRUE,
    max = opm_opt("max.chars"), ...) 
  ## S4 method for signature 'OPMS'
aggregated(object, ...)

`object`	`OPMA`, `OPMS` or `MOPMX` object.
`subset`	Character vector. If not `NULL`, restrict to this or these parameter(s). See `param_names` for the possible values.
`ci`	Logical scalar. Include the estimates of confidence intervals (CIs) in the output?
`trim`	Character scalar. Parameter estimates from intrinsically negative reactions (i.e., no respiration) are sometimes biologically unreasonable because they are too large or too small, and some corrections might be appropriate. no No modification. full Negative lambda estimates are set to zero. medium Lambda estimates larger than `hours(object)` (i.e., the maximum time value observed) are set to that value. Negative lambda estimates smaller than `-hours(object)` are set to this value (i.e., the negative maximum time). full Like ‘medium’, but all negative values are set to zero, which is a less moderate treatment. Currently the other parameters are not checked, and all `NA` values, if any, also remain unchanged.
`full`	Logical scalar passed to `wells`. This and the following arguments affect the column names of the resulting matrix.
`in.parens`	Logical scalar also passed to that function.
`max`	Numeric scalar also passed to that function.
`join`	Empty or character scalar. If empty, a list is returned; a nested list in the case of `OPMS` objects with one contained list per plate. Otherwise this nested list is converted to a matrix or data frame, depending on the value of `join`. The following values yield a matrix in character mode and differ in how they would convert non-scalar values in a matrix in list mode, if encountered: json Converts to a JSON string. yaml Converts to a YAML string. rcode Converts by deparsing, yielding an R code string. All other values of `join` are passed as `what` argument to the `collect` method form the pkgutils package, with `dataframe` and `keep.unnamed` set to `TRUE` but `stringsAsFactors` to `FALSE`.
`...`	Optional arguments passed between the methods or to `wells`.

Note that the conversion of the settings list to a matrix or data frame might not work for all combinations of object and join, mainly because the options entry can hold arbitrary content. For similar conversions of the metadata, see the OPMX methods of to_metadata.

aggregated yields a numeric matrix of aggregated values (a.k.a. the curve parameters). If bootstrapping was used, their CIs are included. The columns represent the wells, the rows the estimated parameters and their CIs.

aggr_settings returns a named list if join is empty. Other values yield a matrix or data frame (or an error). See the description of the argument above and the examples below for further details.

Other getter-functions: anyDuplicated, anyNA, contains, csv_data, dim, disc_settings, discretized, duplicated, has_aggr, has_disc, hours, max, measurements, minmax, seq, subset, thin_out, well

# 'OPMA' methods
# Get full matrix
(x <- aggregated(vaas_1))[, 1:3]
stopifnot(is.matrix(x), dim(x) == c(12, 96))
(y <- aggregated(vaas_1, full = TRUE))[, 1:3] # full names
stopifnot(x == y, nchar(colnames(x)) < nchar(colnames(y)))
# Subsetting
(x <- aggregated(vaas_1, "lambda"))[, 1:3]
stopifnot(is.matrix(x), dim(x) == c(3, 96), any(x < 0))
# Now with lambda correction
(x <- aggregated(vaas_1, "lambda", trim = "full"))[, 1:3]
stopifnot(is.matrix(x), dim(x) == c(3, 96), !any(x < 0))

# settings
(x <- aggr_settings(vaas_1)) # yields named list
stopifnot(is.list(x), !is.null(names(x)))
(x <- aggr_settings(vaas_1, join = "json")) # yields a matrix
stopifnot(is.matrix(x), is.character(x), nrow(x) == 1)

# 'OPMS' methods
summary(x <- aggregated(vaas_4)) # => one matrix per OPM object
stopifnot(is.list(x), length(x) == length(vaas_4), sapply(x, is.matrix))

# settings
summary(x <- aggr_settings(vaas_4)) # list of named lists, one per plate
stopifnot(is.list(x), length(x) == length(vaas_4), sapply(x, is.list))
(x <- aggr_settings(vaas_4, join = "yaml")) # matrix, one row per plate
stopifnot(is.matrix(x), is.character(x), nrow(x) == 4)