bigPCAcpp (version 0.9.0)

pca_plot_scores: Plot sampled PCA scores

Description

Streams a subset of observations through the PCA rotation and plots their scores on the requested components. Sampling keeps the drawn subset small so graphics remain interpretable even when the source big matrix contains millions of rows.

Usage

pca_plot_scores(
  x,
  rotation,
  center = numeric(),
  scale = numeric(),
  components = c(1L, 2L),
  max_points = 5000L,
  sample = c("uniform", "head"),
  seed = NULL,
  draw = TRUE,
  ...
)

Value

A list containing indices (the sampled row indices) and scores

(the corresponding score matrix) is returned invisibly. When draw = TRUE

a scatter plot is produced.

Arguments

x

Either a bigmemory::big.matrix, a standard matrix, or a data frame.

rotation

A rotation matrix such as pca_result$rotation.

center

Optional centering vector. Use numeric() when no centering was applied.

scale

Optional scaling vector. Use numeric() when no scaling was applied.

components

Length-two integer vector selecting the principal components to display.

max_points

Maximum number of observations to sample for the plot.

sample

Strategy for selecting rows. "uniform" draws a random sample without replacement, whereas "head" takes the first max_points rows.

seed

Optional seed to make the sampling reproducible.

draw

Logical; set to FALSE to skip plotting and only return the sampled scores.

...

Additional graphical parameters forwarded to plot().