map_mnirs_intervals: Apply an mnirs function over each interval of a...

In mnirs: Muscle Near-Infrared Spectroscopy Processing and Analysis

Apply an mnirs function over each interval of a multi-interval input

Description

Shared entry point for ⁠*_mnirs()⁠ transformer functions accepting a list of data frames or a grouped data frame. Normalises data to a named list via as_data_list(), then re-evaluates the captured user-facing call once per interval with data swapped, so all arguments (including NSE channel expressions) are forwarded verbatim.

Usage

map_mnirs_intervals(data, call, eval_env, env = rlang::caller_env())

Arguments

data	A data frame of class "mnirs" containing time series data and metadata, a list of data frames, or a grouped data frame (see Details).
call	The matched call from the user-facing function, re-evaluated with data swapped for each interval data frame.
eval_env	Environment in which to re-evaluate call, i.e. the user-facing function's parent.frame(), so NSE arguments resolve against the original caller.
env	The calling environment or a defused call, used to report errors and warnings as coming from the user-facing function rather than the validator.

Value

A named list of class "mnirs" containing processed "mnirs" data frames, one per interval.

Data input formats

mnirs processing functions accept data in multiple formats:

• A single "mnirs" data frame is processed and returned directly.

• A list of "mnirs" data frames: each interval is processed separately and returned as a named list.

• A grouped "mnirs" data frame, e.g. with dplyr::group_by(): the data frame is split by grouping levels and each group is processed as a separate interval, returned as a named list.

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