Peaks of the Loadings of a PCA

Finds the wavelengths that contribute most to the components of a PCA: the largest positive and negative local extrema of the loadings, or the largest maxima of the variance explained by wavelength, optionally matched to emission lines. plot_loadings() labels the same peaks.

Usage

loading_peaks(
  model,
  components = NULL,
  type = c("loadings", "contribution"),
  top = 10,
  lines = NULL,
  tol = 0.1,
  span = 5
)

Arguments

model: A stats::prcomp() fit or an object returned by robpca(), rospca() or macropca(). The variable names must be the wavelengths; otherwise, the variables are numbered.
components: The components to show (numbers). Default is the first three (or all of them, if fewer).
type: "loadings" (default) for one panel of loadings per component, or "contribution" for the variance of each wavelength explained by components.
top: The number of peaks labeled per component (per panel). Default is 10; use 0 for no labels.
lines: Optional line list returned by libs_lines(), to label the peaks with the emission lines they match.
tol: The largest distance, in nm, between a peak and a line it matches. Default is 0.1.
span: The half-width, in channels, of the window in which a peak is a local extremum. Default is 5.

Value

A tibble with one row per peak, sorted by component and by decreasing absolute value, and columns component, variable (the column name), wavelength, value (the loading, or the explained variance), sign ("positive" or "negative") and, for loadings, derivative. With lines, it also has the columns species and line_wavelength of the matched line (NA when none is within tol) and candidates, all the lines within tol, from the nearest.

Details

See plot_loadings() for the definitions of the peaks, of the explained variance, of the orientation of the components and of the line matching. A peak is flagged as part of a derivative shape (derivative = TRUE) when a local extremum of the opposite sign, at least half as large, lies within 2 * span channels on the same detector segment: this usually means a shift or a broadening of the line between spectra.

Author

Christian L. Goueguel

Examples

spectra_id <- forageLIBS |> dplyr::select(1:2) |> names()
minerals <- forageLIBS |> dplyr::select(3:14) |> names()
spectra <- forageLIBS |> dplyr::select(-dplyr::all_of(c(spectra_id, minerals)))
set.seed(1)
fit <- robpca(center(spectra))
loading_peaks(fit, top = 5)
#> # A tibble: 15 × 6
#>    component variable    wavelength  value sign     derivative
#>    <chr>     <chr>            <dbl>  <dbl> <chr>    <lgl>     
#>  1 PC1       399.2983211       399.  0.223 positive FALSE     
#>  2 PC1       280.2738304       280.  0.215 positive FALSE     
#>  3 PC1       387.525507        388.  0.213 positive FALSE     
#>  4 PC1       588.9148516       589.  0.212 positive FALSE     
#>  5 PC1       393.1932396       393.  0.191 positive FALSE     
#>  6 PC2       588.9148516       589.  0.465 positive FALSE     
#>  7 PC2       589.5059874       590.  0.437 positive FALSE     
#>  8 PC2       602.3070443       602.  0.213 positive FALSE     
#>  9 PC2       602.8928422       603.  0.147 positive FALSE     
#> 10 PC2       769.7510958       770. -0.102 negative FALSE     
#> 11 PC3       769.7510958       770.  0.275 positive FALSE     
#> 12 PC3       393.1932396       393. -0.211 negative FALSE     
#> 13 PC3       390.9190545       391. -0.199 negative FALSE     
#> 14 PC3       766.220248        766.  0.196 positive FALSE     
#> 15 PC3       396.6935378       397. -0.174 negative FALSE