R/plotting_functions.R
plot_eigenvalues.Rdplot_eigenvalues() visualizes the dominant eigenvalue(s) from
running the S-map model on the community time series
plot_svd_values() visualizes the dominant singular value(s)
from running the S-map model on the community time series
plot_eigenvalues(eigenvalues, num_values = 1, id_var = "censusdate", highlight_complex = FALSE, line_size = 1, base_size = 16, plot_file = NULL, width = 6, height = NULL) plot_svd_values(singular_values, num_values = 1, id_var = "censusdate", line_size = 1, base_size = 16, plot_file = NULL, width = 6, height = NULL)
| eigenvalues | a list of vectors for the eigenvalues: the number of elements in the list corresponds to the time points of the s-map model, and each element is a vector of the eigenvalues, computed from the matrix of the s-map coefficients at that time step |
|---|---|
| num_values | the number of eigenvalues to plot |
| id_var | when constructing the long-format tibble, what should be the variable name containing the time index |
| highlight_complex | whether to also draw points to indicate when the dominant eigenvalue is complex |
| line_size | the line width for the plot |
| base_size | the base font size |
| plot_file | the filepath to where to save the plot; if |
| width | width of the saved plot |
| height | height of the saved plot |
| singular_values | a list of vectors for the singular values: the number of elements in the list corresponds to the time points of the s-map model, and each element is a vector of the singular values, computed from the matrix of the s-map coefficients at that time step |
A ggplot object of the plot