measurements: Stored measurements

Description Usage Arguments Value Note See Also Examples

Description

Return the measurements, optionally only from selected wells and with or without the time points, or only the time points. Alternatively, selected measurements of interest from a larger matrix of mode ‘character’.

Usage

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  ## S4 method for signature 'MOPMX'
hours(object, ...) 
  ## S4 method for signature 'OPM'
hours(object,
    what = c("max", "all", "size", "summary", "interval", "minmax")) 
  ## S4 method for signature 'OPMS'
hours(object, ...) 

  ## S4 method for signature 'MOPMX'
measurements(object, ...) 
  ## S4 method for signature 'OPM'
measurements(object, i, logt0 = FALSE) 
  ## S4 method for signature 'OPMS'
measurements(object, ...) 
  ## S4 method for signature 'matrix'
measurements(object, wanted = NULL,
    transposed = TRUE, col.names = 1L, row.names = NULL, check.names = TRUE,
    stringsAsFactors = default.stringsAsFactors()) 

  ## S4 method for signature 'MOPMX'
well(object, ...) 
  ## S4 method for signature 'OPM'
well(object, i, drop = TRUE, use.names = TRUE) 
  ## S4 method for signature 'OPMS'
well(object, ...) 

Arguments

object

OPM, OPMS or MOPMX object; for measurements, also a matrix of mode ‘character’.

i

Optional character or numeric vector with name(s) or position(s) of well(s). Wells are originally named ‘A01’ to ‘H12’ but might have been subset beforehand. i can also be a formula, allowing for sequences of well coordinates. See the examples.

logt0

Logical scalar. Treat the data like cell counts and calculate log(N/N0)? This is useful to let the estimated slope represent the specific growth rate.

drop

Logical scalar. If only a single well was selected, simplify it to a vector?

use.names

Logical scalar indicating whether the time points should be used as names for the measurements.

what

Character scalar determining the output mode as follows:

all

Numeric vector: all time points, in order.

interval

The difference between each pair of adjacent time points, NA if this is irregular or only one time point is left.

max

Numeric scalar: the largest time point.

minmax

Numeric scalar: the smallest maximum. For OPM objects this is apparently identical to ‘max’.

size

Integer scalar: the number of time points.

summary

Display a summary.

wanted

Empty or character vector used by the matrix method for selecting columns. If of length one, used as a regular expression in that context. If empty, the methods selects the columns that can be interpreted as numeric throughout.

transposed

Logical scalar. For the matrix method, indicating whether the matrix shall be transposed prior to further processing.

col.names

Used by the matrix method. Empty or scalar indicating the position of the column names within the matrix (which is assumed to not yet contain proper column names).

row.names

Used by the matrix method. Empty or scalar indicating the position of the row names within the matrix (which is assumed to not yet contain proper row names).

check.names

Logical scalar. Used by the matrix method to indicate whether row and column names should be treated with make.names.

stringsAsFactors

Logical scalar used by the matrix method.

...

Optional arguments passed between the methods.

Value

measurements returns a numeric matrix with column names indicating the well coordinate and a first column containing the time points. The other columns contain the values from each well. There is one row per time point. Column names are appropriately set, but not translated (as, e.g., to substrate names). It is possible to select wells, but the time points are always included as first column (in contrast to well). The i argument refers only to the remaining matrix.

The matrix measurements returns a data frame containing the selected rows and columns only. This is intended as a helper method for inputting irregular data.

Do not confuse well with wells. well yields a numeric matrix or vector, depending on i and drop. It will always ignore the time points as values, in contrast to measurements. But depending on use.names they would be inserted as names.

The return value of hours is dependent on the what argument; see there.

Note

For quickly obtaining an overview of the running times in a MOPMX object see extract and heat_map.

See Also

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

Examples

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# 'OPM' methods

head(x <- measurements(vaas_1))[, 1:5] # => numeric matrix
stopifnot(is.matrix(x), is.numeric(x))
stopifnot(dim(x) == c(384, 97))
head(x <- measurements(vaas_1, "B03"))
stopifnot(is.matrix(x), is.numeric(x), dim(x) == c(384, 2))
head(y <- measurements(vaas_1, ~ B03)) # => same result with formula
stopifnot(identical(y, x))

head(x <- well(vaas_1, "B04")) # => numeric vector
stopifnot(is.numeric(x), length(x) == 384)
head(x <- well(vaas_1, c("B08", "C07"))) # => numeric matrix
stopifnot(is.matrix(x), dim(x) == c(384, 2))
# selecting adjacent wells is easer when using a formula
head(x <- well(vaas_1, c("B12", "C01", "C02")))
stopifnot(is.matrix(x), dim(x) == c(384, 3))
head(y <- well(vaas_1, ~ B12:C02)) # => same result
stopifnot(identical(x, y))

(x <- hours(vaas_1)) # the default is 'max'
stopifnot(identical(x, 95.75))
(x <- hours(vaas_1, "minmax"))
stopifnot(identical(x, 95.75))
(x <- hours(vaas_1, "summary"))
stopifnot(is.table(x))
(x <- hours(vaas_1, "interval"))
stopifnot(identical(x, 0.25))
(x <- hours(vaas_1, "size"))
stopifnot(identical(x, 384L))

# 'OPMS' methods

summary(x <- measurements(vaas_4)) # => list of numeric matrices
stopifnot(is.list(x), length(x) == length(vaas_4))
stopifnot(sapply(x, is.matrix), sapply(x, is.numeric))

head(x <- well(vaas_4, "B04"))[, 1:5] # => numeric matrix
stopifnot(is.matrix(x), dim(x) == c(4, 384))
head(y <- well(vaas_4, ~ B04))[, 1:5] # using a formula
stopifnot(identical(x, y)) # => same result

(x <- hours(vaas_4)) # all with the same overall running time
stopifnot(length(x) == 4, x == 95.75)

opm documentation built on May 2, 2019, 6:08 p.m.