discretized {opm} | R Documentation |
Get the discretised kinetic data or the discretisation
settings used. (See do_disc
for generating
discretised data.)
## S4 method for signature 'MOPMX' disc_settings(object, join = NULL) ## S4 method for signature 'NULL' disc_settings(object, ...) ## S4 method for signature 'OPMD' disc_settings(object, join = NULL) ## S4 method for signature 'OPMS' disc_settings(object, join = NULL) ## S4 method for signature 'character' disc_settings(object, ...) ## S4 method for signature 'logical' disc_settings(object, ...) ## S4 method for signature 'numeric' disc_settings(object, ...) ## S4 method for signature 'MOPMX' discretized(object, ...) ## S4 method for signature 'OPMD' discretized(object, full = FALSE, in.parens = TRUE, max = opm_opt("max.chars"), ...) ## S4 method for signature 'OPMS' discretized(object, ...)
object |
|
full |
Logical scalar passed to |
in.parens |
Logical scalar also passed to that function. |
max |
Numeric scalar also passed to that function. |
join |
Empty or character scalar. Works like the
eponymous argument of |
... |
Optional arguments passed between the methods
or to |
Logical vector or matrix in the case of
discretized
, named list in the case of
disc_settings
. See the examples for details.
Other getter-functions: aggr_settings
,
aggregated
, anyDuplicated
,
anyNA
, contains
,
csv_data
, dim
,
duplicated
, has_aggr
,
has_disc
, hours
,
max
, measurements
,
minmax
, seq
,
subset
, thin_out
,
well
# 'OPM' methods
(x <- discretized(vaas_1))[1:3] # => logical vector
## A01 A02 A03
## FALSE TRUE TRUE
stopifnot(is.logical(x), !is.matrix(x), length(x) == dim(x)[2L])
stopifnot(names(x) == colnames(aggregated(vaas_1)))
(x <- discretized(vaas_1, full = TRUE))[1:3] # => with full names
## A01 (Negative Control) A02 (Dextrin) A03 (D-Maltose)
## FALSE TRUE TRUE
stopifnot(names(x) == colnames(aggregated(vaas_1, full = TRUE)))
# settings
(x <- disc_settings(vaas_1)) # => named list
## $method
## [1] "kmeans"
##
## $options
## $options$cutoffs
## [1] 129.0670 241.2105
##
## $options$datasets
## [1] 1
##
## $options$parameter
## [1] "A"
##
##
## $software
## [1] "opm"
##
## $version
## [1] "0.7-0"
stopifnot(is.list(x), !is.null(names(x)))
(x <- disc_settings(vaas_1, join = "yaml")) # matrix, one row per plate
## method
## [1,] "kmeans"
## options
## [1,] "---\ncutoffs:\n- 129.06705\n- 241.2105\ndatasets: 1\nparameter: A\n\n"
## software version
## [1,] "opm" "0.7-0"
stopifnot(is.matrix(x), is.character(x), nrow(x) == 1)
# 'OPMS' methods
(x <- discretized(vaas_4))[, 1:3] # => logical matrix
## A01 A02 A03
## [1,] FALSE NA FALSE
## [2,] NA TRUE TRUE
## [3,] FALSE FALSE FALSE
## [4,] FALSE FALSE FALSE
stopifnot(is.logical(x), is.matrix(x), ncol(x) == dim(x)[2L])
stopifnot(colnames(x) == colnames(aggregated(vaas_1)))
# settings
summary(x <- disc_settings(vaas_4)) # => list of named lists, one per plate
## Length Class Mode
## [1,] 4 -none- list
## [2,] 4 -none- list
## [3,] 4 -none- list
## [4,] 4 -none- list
stopifnot(is.list(x), is.null(names(x)), length(x) == length(vaas_4))
stopifnot(duplicated(x)[-1])
(x <- disc_settings(vaas_4, join = "json")) # matrix, one row per plate
## method
## [1,] "kmeans"
## [2,] "kmeans"
## [3,] "kmeans"
## [4,] "kmeans"
## options
## [1,] "{\"cutoffs\":[111.8537965869,230.912480834744],\"datasets\":4,\"parameter\":\"A\"}"
## [2,] "{\"cutoffs\":[111.8537965869,230.912480834744],\"datasets\":4,\"parameter\":\"A\"}"
## [3,] "{\"cutoffs\":[111.8537965869,230.912480834744],\"datasets\":4,\"parameter\":\"A\"}"
## [4,] "{\"cutoffs\":[111.8537965869,230.912480834744],\"datasets\":4,\"parameter\":\"A\"}"
## software version
## [1,] "opm" "0.7-0"
## [2,] "opm" "0.7-0"
## [3,] "opm" "0.7-0"
## [4,] "opm" "0.7-0"
stopifnot(is.matrix(x), is.character(x), nrow(x) == 4)