get_data | R Documentation |
Fetch the input data
get_data(
object,
views = "all",
groups = "all",
features = "all",
as.data.frame = FALSE,
add_intercept = TRUE,
denoise = FALSE,
na.rm = TRUE
)
object |
a |
views |
character vector with the view name(s), or numeric vector with the view index(es). Default is "all". |
groups |
character vector with the group name(s), or numeric vector with the group index(es). Default is "all". |
features |
a *named* list of character vectors. Example: list("view1"=c("feature_1","feature_2"), "view2"=c("feature_3","feature_4")) Default is "all". |
as.data.frame |
logical indicating whether to return a long data frame instead of a list of matrices. Default is |
add_intercept |
logical indicating whether to add feature intercepts to the data. Default is |
denoise |
logical indicating whether to return the denoised data (i.e. the model predictions). Default is |
na.rm |
remove NAs from the data.frame (only if as.data.frame is |
By default this function returns a list where each element is a data matrix with dimensionality (D,N)
where D is the number of features and N is the number of samples.
Alternatively, if as.data.frame
is TRUE
, the function returns a long-formatted data frame with columns (view,feature,sample,value).
Missing values are not included in the the long data.frame format by default. To include them use the argument na.rm=FALSE
.
A list of data matrices with dimensionality (D,N) or a data.frame
(if as.data.frame
is TRUE)
# Using an existing trained model on simulated data
file <- system.file("extdata", "model.hdf5", package = "MOFA2")
model <- load_model(file)
# Fetch data
data <- get_data(model)
# Fetch a specific view
data <- get_data(model, views = "view_0")
# Fetch data in data.frame format instead of matrix format
data <- get_data(model, as.data.frame = TRUE)
# Fetch centered data (do not add the feature intercepts)
data <- get_data(model, as.data.frame = FALSE)
# Fetch denoised data (do not add the feature intercepts)
data <- get_data(model, denoise = TRUE)
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.