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Fits a PCA model with n_comp components to the masked reference data, then corrects the data by dividing by the PCA reconstruction (ratio correction, not subtractive). Mirrors newref_tools.train_pca().

Usage

.train_pca(ref_data, n_comp = 5L)

Arguments

ref_data

Numeric matrix (n_masked_bins, n_samples).

n_comp

Number of PCA components (default 5).

Value

A list with:

corrected

Numeric matrix (n_masked_bins, n_samples) — ratio- corrected data.

components

Numeric matrix (n_comp, n_masked_bins) — PCA rotation (loadings).

center

Numeric vector of length n_masked_bins — PCA column means.