Apply a function to measurement data along dimensions

Central dispatcher that enables 1D preprocessing operations to work on n-dimensional measurement data. For 1D data, it applies the function directly. For nD data, it slices along the specified dimensions, applies the function to each 1D slice, and rebuilds the nD structure.

Usage

measure_apply(x, fn, along = 1L, ...)

Arguments

x

A measure_tbl, measure_nd_tbl, measure_list, or measure_nd_list object.

fn

A function that accepts a measure_tbl and returns a measure_tbl. The function signature should be fn(x, ...).

along

Integer vector specifying which dimensions to apply the function along. For 2D data, along = 1 applies along dimension 1 (e.g., time in LC-DAD), treating dimension 2 slices as independent. Default is 1L (apply along the first dimension).

...

Additional arguments passed to fn.

Value

An object of the same class as the input, with the function applied to each 1D slice.

Details

The measure_apply() function is the workhorse for making 1D preprocessing steps work on nD data. It handles:

• 1D data: Direct function application

• nD data: Slice-apply-rebuild pattern

For nD data, the function extracts 1D slices along the specified dimension(s), applies the transformation function to each slice, and reassembles the result into the original nD structure.

Examples

# Create a simple 2D measurement
m2d <- new_measure_nd_tbl(
  location_1 = rep(1:10, each = 3),
  location_2 = rep(1:3, times = 10),
  value = rnorm(30)
)

# Define a simple smoothing function for 1D data
smooth_1d <- function(x) {
  x$value <- stats::filter(x$value, rep(1/3, 3), sides = 2)
  x[!is.na(x$value), ]
}

# Apply smoothing along dimension 1
result <- measure_apply(m2d, smooth_1d, along = 1)