nmr_pca_plots: Plotting functions for PCA

In AlpsNMR: Automated spectraL Processing System for NMR

Description

Plotting functions for PCA

Usage

nmr_pca_plot_variance(pca_model)

nmr_pca_scoreplot(nmr_dataset, pca_model, comp = seq_len(2), ...)

nmr_pca_loadingplot(pca_model, comp)

Arguments

pca_model	A PCA model trained with nmr_pca_build_model
nmr_dataset	an nmr_dataset_1D object
comp	Components to represent
...	Additional aesthetics passed on to ggplot2::aes (use bare unquoted names)

Value

Plot of PCA

See Also

Other PCA related functions: nmr_pca_build_model(), nmr_pca_outliers_filter(), nmr_pca_outliers_plot(), nmr_pca_outliers_robust(), nmr_pca_outliers()

Examples

dir_to_demo_dataset <- system.file("dataset-demo", package = "AlpsNMR")
dataset <- nmr_read_samples_dir(dir_to_demo_dataset)
dataset_1D <- nmr_interpolate_1D(dataset, axis = c(min = -0.5, max = 10, by = 2.3E-4))
model <- nmr_pca_build_model(dataset_1D)
nmr_pca_plot_variance(model)

dir_to_demo_dataset <- system.file("dataset-demo", package = "AlpsNMR")
dataset <- nmr_read_samples_dir(dir_to_demo_dataset)
dataset_1D <- nmr_interpolate_1D(dataset, axis = c(min = -0.5, max = 10, by = 2.3E-4))
model <- nmr_pca_build_model(dataset_1D)
nmr_pca_scoreplot(dataset_1D, model)

dir_to_demo_dataset <- system.file("dataset-demo", package = "AlpsNMR")
dataset <- nmr_read_samples_dir(dir_to_demo_dataset)
dataset_1D <- nmr_interpolate_1D(dataset, axis = c(min = -0.5, max = 10, by = 2.3E-4))
model <- nmr_pca_build_model(dataset_1D)
nmr_pca_loadingplot(model, 1)

AlpsNMR documentation built on April 1, 2021, 6:02 p.m.