Plot Diagnostics: Original, Fitted, and Residual Matrices as Heatmaps

This function generates a side-by-side plot of three heatmaps: the original observation matrix Y, the fitted matrix XB (from NMF), and the residual matrix E (Y - XB). This visualization aids in diagnosing whether the chosen rank Q is adequate by assessing if the residual matrix E appears to be random noise.

The axis labels (X-axis: Samples, Y-axis: Features) are integrated into the main title of each plot to maximize the plot area, reflecting the compact layout settings.

Usage

nmfkc.residual.plot(
  Y,
  result,
  Y_XB_palette = (grDevices::colorRampPalette(c("white", "orange", "red")))(256),
  E_palette = (grDevices::colorRampPalette(c("blue", "white", "red")))(256),
  ...
)

Arguments

Y

The original observation matrix (P x N).

result

The result object returned by the nmfkc function.

Y_XB_palette

A vector of colors used for Y and XB heatmaps. Defaults to a white-orange-red gradient.

E_palette

A vector of colors used for the residuals (E) heatmap. Defaults to a blue-white-red gradient.

...

Additional graphical parameters passed to the internal image calls.

Value

NULL. The function generates a plot.