get_default_mefisto_options {MOFA2} | R Documentation |
Function to obtain the default options for the usage of MEFISTO covariates with MEFISTO
get_default_mefisto_options(object)
object |
an untrained |
The options are the following:
scale_cov: logical: Scale covariates?
start_opt: integer: First iteration to start the optimisation of GP hyperparameters
n_grid: integer: Number of points for the grid search in the optimisation of GP hyperparameters
opt_freq: integer: Frequency of optimisation of GP hyperparameters
sparseGP: logical: Use sparse GPs to speed up the optimisation of the GP parameters?
frac_inducing: numeric between 0 and 1: Fraction of samples to use as inducing points (only relevant if sparseGP is TRUE
)
warping: logical: Activate warping functionality to align covariates between groups (requires a multi-group design)
warping_freq: numeric: frequency of the warping (only relevant if warping is TRUE
)
warping_ref: A character specifying the reference group for warping (only relevant if warping is TRUE
)
warping_open_begin: logical: Warping: Allow for open beginning? (only relevant warping is TRUE
)
warping_open_end: logical: Warping: Allow for open end? (only relevant warping is TRUE
)
model_groups: logical: Model covariance structure across groups (for more than one group, otherwise FALSE)? If FALSE, we assume the same patterns in all groups.
new_values: Values for which to predict the factor values (for interpolation / extrapolation). This should be numeric matrix in the same format with covariate(s) in rows and new values in columns. Default is NULL, leading to no interpolation.
Returns a list with default options for the MEFISTO covariate(s) functionality.
# generate example data dd <- make_example_data(sample_cov = seq(0,1,length.out = 200), n_samples = 200, n_factors = 4, n_features = 200, n_views = 4, lscales = c(0.5, 0.2, 0, 0)) # input data data <- dd$data # covariate matrix with samples in columns time <- dd$sample_cov rownames(time) <- "time" # create mofa and set covariates sm <- create_mofa(data = dd$data) sm <- set_covariates(sm, covariates = time) MEFISTO_opt <- get_default_mefisto_options(sm)