BigNeuroVec-class: BigNeuroVec Class

In bbuchsbaum/neuroim2: Data Structures and IO for Neuroimaging Data with an Emphasis on Functional Magnetic Resonance Imaging (FMRI)

BigNeuroVec Class

Description

A class representing a sparse four-dimensional brain image backed by a disk-based big matrix. BigNeuroVec objects are designed for efficient handling of large-scale brain imaging data that exceeds available memory.

Details

BigNeuroVec leverages file-backed storage to manage large 4D neuroimaging datasets that would typically exceed available RAM. It combines the sparse representation framework of AbstractSparseNeuroVec with the disk-based storage capabilities of FBM, allowing for out-of-core computations on massive datasets.

Slots

data

An instance of class FBM from the bigstatsr package, containing time-series data. The FBM (File-Backed Big Matrix) is a matrix-like structure stored on disk, enabling efficient handling of large-scale data.

Inheritance

BigNeuroVec inherits from:

• NeuroVec: Base class for 4D brain images

• AbstractSparseNeuroVec: Provides sparse representation framework

• ArrayLike4D: Interface for 4D array-like operations

See Also

AbstractSparseNeuroVec-class for the parent sparse representation class. NeuroVec-class for the base 4D brain image class. FBM for details on File-Backed Big Matrix objects.

Examples

## Not run: 
# Create a BigNeuroVec object
library(bigstatsr)

# Create a file-backed big matrix
fbm <- FBM(10000, 1000, init = rnorm(10000000))

# Create a mask for sparse representation
mask <- LogicalNeuroVol(array(runif(100*100*100) > 0.7, dim=c(100,100,100)))

# Create a BigNeuroVec object
big_vec <- BigNeuroVec(data = fbm, mask = mask, space = NeuroSpace(dim=c(100,100,100)))

# Access a subset of the data
subset <- big_vec[,,, 1:10]

## End(Not run)

bbuchsbaum/neuroim2 documentation built on Jan. 2, 2025, 3:38 p.m.