extract_intervals: Extract intervals from _mnirs_ data

In mnirs: Muscle Near-Infrared Spectroscopy Processing and Analysis

Extract intervals from mnirs data

Description

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,
  group_intervals = c("distinct", "ensemble"),
  group_channels = NULL,
  start = NULL,
  end = NULL,
  span = list(c(-60, 60)),
  zero_time = FALSE,
  verbose = TRUE,
  event_groups = deprecated()
)

Arguments

data	A data frame of class "mnirs" containing time series data and metadata, or a list() of such data frames.
nirs_channels	A character vector of mNIRS channel names to operate on. Names must match column names in data exactly. If NULL (default), channels are retrieved from "mnirs" metadata. Passing a list() for per-group channel selection is deprecated; use group_channels.
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).
group_intervals	Either a character string or a non-empty list() of non-empty integer-valued numeric vectors specifying how to group intervals (see Details). Custom indices must be between 1 and the number of detected intervals. "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.
group_channels	A character vector or a list() of character vectors selecting which nirs_channels are ensemble-averaged within each interval group (see Details). If NULL (default), all nirs_channels are used for every group. Only relevant when group_intervals contains "ensemble"-averaged intervals; with group_intervals = "distinct" no channel processing occurs.
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(). Multiple specifications can be combined with list() (e.g. list(by_time(30), by_label("go"))); see Details.
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(). Multiple specifications can be combined with list() (e.g. list(by_time(30), by_label("go"))); see Details.
span	A one- or two-element numeric vector expanding the time bounds around c(start, end), 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)).
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. TRUE (default) will display, and FALSE will silence warnings and information messages helpful for troubleshooting. Global default can be set via options(mnirs.verbose = FALSE).
event_groups	Renamed to group_intervals for naming consistency across the package.

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:

• Numeric -> by_time()

• Character -> by_label(),

• Explicit integer (e.g. 2L) -> by_lap().

• Use by_sample() explicitly for sample indices.

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

Multiple specification types can be combined for a single boundary with list() (e.g. start = list(by_time(30), by_label("go"))). Resolved boundary times are concatenated in the order supplied. Combined specifications must use the by_ helpers directly: raw values are ignored with a warning.

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-group channel selection with group_channels

When group_intervals = "ensemble" or a list of numeric grouped intervals, group_channels can be specified as a list of column names to override which channels are ensemble-averaged within each group. For example, to exclude a channel from one interval:

group_channels = list(
  c(A, B, C),
  c(A, C) ## channel "B" data are excluded from the second interval
)

If all grouped intervals include all nirs_channels, group_channels can be left as NULL (the default) and all channels are ensemble-averaged within every group.

Grouping intervals

group_intervals 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 group_intervals are returned as distinct.

group_intervals 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 group_intervals is a list of numeric interval numbers, list items in group_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.

Value

A named list() of tibbles of class "mnirs", each with metadata available via attributes(). When data is a list of data frames, results are flattened into a single-layer list with interval names indicating nested number of data frame and interval as ⁠interval_<df>.<interval>⁠. Other interval names (e.g. "ensemble" or custom group names) are suffixed as ⁠<name>_<df>⁠.

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),
    group_intervals = "ensemble", ## ensemble-average across two intervals
    start = by_time(368, 1084),   ## manually identified interval start times
    span = c(-20, 90),            ## include the last 180-sec of each interval (recycled)
    zero_time = TRUE              ## re-calculate common time to start from `0`
)

interval_list[[1L]]


  if (requireNamespace("ggplot2", quietly = TRUE)) {
    plot(interval_list, time_labels = TRUE) +
      ggplot2::geom_vline(xintercept = 0, linetype = "dotted")
  }

mnirs documentation built on Sept. 13, 2026, 1:06 a.m.