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Re-scale data range

Source: R/rescale_mnirs.R
rescale_mnirs.Rd

Expand or reduce the range (min and max values) of data channels to a new amplitude/dynamic range, e.g. re-scale the range of NIRS data to c(0, 100).

Usage

rescale_mnirs(
  data,
  nirs_channels = list(NULL),
  range,
  verbose = TRUE
)

Arguments

data

A data frame of class "mnirs" containing time series data and metadata.

nirs_channels

A list() of character vectors indicating grouping structure of mNIRS channel names to operate on (see Details). Must match column names in data exactly. Retrieved from metadata if not defined explicitly.

list("A", "B", "C")

Will operate on each channel independently, losing the relative scaling between channels.

list(c("A", "B", "C"))

Will operate on all channels together, preserving the relative scaling between channels.

list(c("A", "B"), c("C", "D"))

Will operate on channels A & B in one group, and C & D in another group, preserving relative scaling within, but not between groups.

range

A numeric vector in the form c(min, max), indicating the range of output values to which data channels will be re-scaled.

verbose

A logical to display (the default) or silence (FALSE) warnings and information messages used for troubleshooting.

Value

A tibble of class "mnirs" with metadata available with attributes().

Details

nirs_channels = list() can be used to group data channels (column names) to preserve absolute or relative scaling.

  • Channels grouped together in a vector (e.g. list(c("A", "B"))) will be re-scaled to a common range, and the relative scaling within that group will be preserved.

  • Channels in separate list vectors (e.g. list("A", "B")) will be re-scaled independently, and relative scaling between groups will be lost.

  • A single vector of channel names (e.g. c("A", "B")) will group channels together.

  • Channels (columns) in data not explicitly defined in nirs_channels will be passed through untouched to the output data frame.

nirs_channels can be retrieved automatically from data of class "mnirs" which has been processed with {mnirs}, if not defined explicitly. This will default to returning all nirs_channels grouped together, and should be defined explicitly for other grouping arrangements.

Examples


options(mnirs.verbose = FALSE)

## read example data
data <- read_mnirs(
    file_path = example_mnirs("moxy_ramp"),
    nirs_channels = c(smo2_right = "SmO2 Live",
                      smo2_left = "SmO2 Live(2)"),
    time_channel = c(time = "hh:mm:ss")
) |>
    resample_mnirs() |>
    replace_mnirs(
        invalid_values = c(0, 100),
        outlier_cutoff = 3,
        width = 10,
        method = "linear"
    ) |>
    filter_mnirs(na.rm = TRUE) |>
    rescale_mnirs(
        nirs_channels = list(c(smo2_right, smo2_left)),
        range = c(0, 100)   ## rescale to a 0-100% functional exercise range
    )
#> ℹ `nirs_channel` = "smo2_right": `smooth.spline(spar = 0.056)`
#> ℹ `nirs_channel` = "smo2_left": `smooth.spline(spar = 0.056)`

library(ggplot2)
plot(data, label_time = TRUE) +
    geom_hline(yintercept = c(0, 100), linetype = "dotted")