ModelArray class

A ModelArray wraps one or more element-wise scalar matrices (e.g., FD, FC, log_FC for fixel data) read lazily via DelayedArray, along with any previously saved analysis results. The object holds references to the underlying storage and reads data on demand, making it suitable for large-scale neuroimaging datasets.

Prints a summary of the ModelArray including file path, source count, each scalar with its element count, and any saved analysis names.

Usage

ModelArray(
  filepath,
  scalar_types = c("FD"),
  analysis_names = character(0),
  backend = c("auto", "hdf5", "tiledb")
)

# S4 method for class 'ModelArray'
show(object)

Arguments

object: A ModelArray object.

Value

Invisible NULL. Called for its side effect of printing to the console.

Details

ModelArray is an S4 class that represents element-wise scalar data and associated statistical results backed by an HDF5 file or TileDB store on disk.

Each scalar is stored at /scalars/<name>/values as a matrix of elements (rows) by source files (columns). Source filenames are read from storage metadata or companion datasets. Analysis results, if present, live under /results/<analysis_name>/results_matrix.

ModelArray objects are typically created with the ModelArray constructor function. Element-wise models are fit with ModelArray.lm, ModelArray.gam, or ModelArray.wrap.

Slots

sources: A named list of character vectors. Each element corresponds to a scalar and contains the source filenames (one per input file/subject).
scalars: A named list of DelayedArray::DelayedArray matrices. Each matrix has elements as rows and source files as columns.
results: A named list of analysis results. Each element is itself a list containing at minimum results_matrix (a DelayedArray::DelayedArray).
path: Character. Path(s) to the HDF5 file(s) or TileDB store(s) on disk.
backend: Character. Resolved storage backend(s) for path: "hdf5" or "tiledb".

Usage

Arguments

Value

Details

Slots

See also