nmr_pca_plots {AlpsNMR} | R Documentation

## Plotting functions for PCA

### 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)

[Package AlpsNMR version 3.2.3 Index]