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Extract intervals from mnirs data

Source: R/extract_intervals.R
extract_intervals.Rd

Extract intervals from "mnirs" time series data, specifying interval start and end boundaries by time value, event label, lap number, or sample index.

Usage

extract_intervals(
  data,
  nirs_channels = NULL,
  time_channel = NULL,
  event_channel = NULL,
  sample_rate = NULL,
  start = NULL,
  end = NULL,
  span = list(c(-60, 60)),
  event_groups = c("distinct", "ensemble"),
  zero_time = FALSE,
  verbose = TRUE
)

Arguments

data

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

nirs_channels

A character vector or a list() of character vectors of mNIRS channel names to operate on within each interval (see Details). Names must match column names in data exactly.

  • Must only be specified when event_groups contains "ensemble"- averaged intervals. If event_groups = "distinct" no channel processing occurs.

  • If NULL (default), channels are retrieved from "mnirs" metadata.

time_channel

A character string naming the time or sample column. Must match a column name in data exactly.

  • If NULL (default), the time_channel metadata attribute of data is used.

event_channel

An optional character string giving the name of an event/lap column. The column may contain character event labels or integer lap numbers.

  • Required when using by_label() or by_lap() for start or end.

  • Retrieved from metadata if not defined explicitly.

sample_rate

An optional numeric sample rate (Hz) used to bin time values for ensemble-averaging. If NULL, will be estimated from time_channel (see Details).

start

Specifies where intervals begin. Either raw values – numeric for time values, character for event labels, explicit integer (e.g. 2L) for lap numbers – or created with by_time(), by_label(), by_lap(), or by_sample().

end

Specifies where intervals end. Either raw values – numeric for time values, character for event labels, explicit integer (e.g. 2L) for lap numbers – or created with by_time(), by_label(), by_lap(), or by_sample().

span

A one- or two-element numeric vector c(before, after) in units of time_channel, or a list() of such vectors. (default span = c(-60, 60). Applied additively to interval boundaries:

  • When both start and end are specified: span[1] shifts start times, span[2] shifts end times.

  • When only start or only end is specified: both span[1] and span[2] apply as a window around the event).

  • A single positive value is recycled to shift the end times (e.g. span = 60 -> c(0, 60)).

  • A single negative value is recycled to shift the start times (e.g. span = -60 -> c(-60, 0)).

event_groups

Either a character string or a list() of integer vectors specifying how to group intervals (see Details).

"distinct"

The default. Extract each interval as an independent data frame.

"ensemble"

Ensemble-average each specified nirs_channel across all detected intervals, returning a single data frame.

list(c(1, 2), c(3, 4))

Ensemble-average each specified nirs_channel within each group and return one data frame per group.

zero_time

Logical. Default is FALSE. If TRUE, re-calculates numeric time_channel values to start from zero within each interval data frame.

verbose

Logical. Default is TRUE. Display or silence (if FALSE) warnings and information messages helpful for troubleshooting. Ad global default can be set via options(mnirs.verbose = FALSE).

Value

A named list() of tibbles of class "mnirs", each with metadata available via attributes().

Details

Interval specification

Interval start and end boundaries are specified using helper functions, or by passing raw values directly:

by_time()

Time values in units of time_channel.

by_label()

Strings to match in event_channel. All matching occurrences are returned.

by_lap()

Lap numbers to match in event_channel. Resolves to the first sample of each lap for start, and the last lap sample for end

by_sample()

Integer sample indices (row numbers).

Raw values supplied to start/end are auto-coerced:

start and end can use different specification types (e.g., start by label, end by time). When lengths differ, the shorter is recycled.

Time span window

span additively expands the time span window around interval boundaries.

  • A two-value vector expands the start and end, respectively: span = c(-60, 60) expands the start earlier by 60, and the end later by 60. For example, start = by_time(30), end = by_time(60), span = c(-5, 10) returns an interval of [25, 70].

  • A single numeric value is recycled according to the sign: span = -60 becomes c(-60, 0) to expand the start earlier. span = 60 becomes c(0, 60) to expand the end later.

  • If only start is specified alone, both span values expand the single boundary window: start = by_time(30), span = c(-5, 60) returns [25, 90].

Per-interval nirs_channels for ensemble-averaging

When event_groups = "ensemble" or a list of numeric grouped intervals, nirs_channels can be specified as a list of column names to override ensemble-averaging across interval. For example, to exclude a channel in one interval:

nirs_channels = list(
  c(A, B, C),
  c(A, C) ## channel "B" is excluded
)

If all grouped intervals can include all nirs_channels, or if event_groups = "distinct", a single nirs_channels character vector can be supplied and recycled to all groups, or left as NULL for channels to be taken from "mnirs" metadata.

Grouping intervals

event_groups controls whether extracted intervals are returned as distinct data frames or ensemble-averaged.

"distinct"

The default. Extract each interval and return a list of independent data frames.

"ensemble"

Ensemble-average each specified nirs_channel across all detected intervals and return a one-item list with a single data frame.

list(c(1, 2), c(3, 4))

Ensemble-average each specified nirs_channel within each group and return a list with one data frame for each group. Any intervals detected but not specified in event_groups are returned as distinct.

event_groups lists can be named (e.g. list(low = c(1, 2), high = c(3, 4))) and will pass those names to the returned list of data frames.

When event_groups is a list of numeric interval numbers, list items in nirs_channels and span are recycled to the number of groups. If lists are only partially specified, the final item is recycled forward as needed. Extra items are ignored.

Examples

## read example data
data <- read_mnirs(
    example_mnirs("train.red"),
    nirs_channels = c(
        smo2_left = "SmO2 unfiltered",
        smo2_right = "SmO2 unfiltered"
    ),
    time_channel = c(time = "Timestamp (seconds passed)"),
    zero_time = TRUE,
    verbose = FALSE
) |>
    ## avoid issues ensemble-averaging irregular samples
    resample_mnirs(method = "linear", verbose = FALSE) 

## ensemble-average across multiple intervals
interval_list <- extract_intervals(
    data,                       ## channels recycled to all intervals by default
    nirs_channels = c(smo2_left, smo2_right),
    start = by_time(368, 1084), ## manually identified interval start times
    span = c(-20, 90),          ## include the last 180-sec of each interval (recycled)
    event_groups = "ensemble",  ## ensemble-average across two intervals
    zero_time = TRUE            ## re-calculate common time to start from `0`
)

interval_list[[1L]]
#> # A tibble: 1,101 × 3
#>     time smo2_left smo2_right
#>    <dbl>     <dbl>      <dbl>
#>  1 -20        56.3       59.2
#>  2 -19.9      56.1       59.2
#>  3 -19.8      56.1       59.2
#>  4 -19.7      56.2       58.9
#>  5 -19.6      56.4       58.9
#>  6 -19.5      56.5       58.9
#>  7 -19.4      56.9       58.7
#>  8 -19.3      57.0       58.7
#>  9 -19.2      56.9       59.0
#> 10 -19.1      56.7       58.8
#> # ℹ 1,091 more rows

# \donttest{
  if (requireNamespace("ggplot2", quietly = TRUE)) {
    plot(interval_list[[1L]], time_labels = TRUE) +
      ggplot2::geom_vline(xintercept = 0, linetype = "dotted")
  }

# }