Compose data into a list suitable to be passed into a Bayesian model (JAGS, BUGS, Stan, etc).
compose_data(..., .n_name = n_prefix("n"))
Data to be composed into a list suitable for being passed into
Stan, JAGS, etc. Named arguments will have their name used as the
as_data_list when translated; unnamed arguments that are
not lists or data frames will have their bare value (passed through
make.names) used as the
name argument to
Each argument is evaluated using
eval_tidy in an environment that
includes all list items composed so far.
A function that is used to form dimension index variables (a variable
whose value is number of levels in a factor or the length of a data frame in
...). For example, if a data frame with 20 rows and a factor
(having 3 levels) is passed to
compose_data, the list returned by
compose_data will include an element named
by default would be "n_foo", containing the value 3, and a column named "n"
containing the value 20. See
A list where each element is a translated variable as described above.
This function recursively translates each argument into list elements using
as_data_list(), merging all resulting lists together. By
default this means that:
numerics are included as-is.
logicals are translated into numeric using
factors are translated into numeric using
and an additional element named
.n_name(argument_name) is added
with the number of levels in the factor. The default
"n_" before the factor name; e.g. a factor
foo will have an element named
n_foo added containing
the number of levels in
character vectors are converted into factors then translated into numeric in the same manner as factors are.
lists are translated by translating all elements of the list (recursively) and adding them to the result.
data.frames are translated by translating every column of the data.frame
and adding them to the result. A variable named
.n_name(argument_name) if the data.frame is passed as a named
argument_name) is also added containing the number of rows
in the data frame.
NULL values are dropped. Setting a named argument to
can be used to drop that item from the resulting list (if an unwanted
element was added to the list by a previous argument, such as a column
from a data frame that is not needed in the model).
all other types are dropped (and a warning given)
As in functions like
mutate(), each expression is evaluated in an
environment containing the data list built up so far.
For example, this means that if the first argument to
is a data frame, subsequent arguments can include direct references to columns
from that data frame. This allows you, for example, to easily use
x_at_y() to generate indices for nested models.
If you wish to add support for additional types not described above,
provide an implementation of
as_data_list() for the type. See
the implementations of
as_data_list.logical, etc for examples.
library(magrittr) df = data.frame( plot = factor(paste0("p", rep(1:8, times = 2))), site = factor(paste0("s", rep(1:4, each = 2, times = 2))) ) # without changing `.n_name`, compose_data() will prefix indices # with "n" by default df %>% compose_data() #> $plot #>  1 2 3 4 5 6 7 8 1 2 3 4 5 6 7 8 #> #> $n_plot #>  8 #> #> $site #>  1 1 2 2 3 3 4 4 1 1 2 2 3 3 4 4 #> #> $n_site #>  4 #> #> $n #>  16 #> # you can use n_prefix() to define a different prefix (e.g. "N"): df %>% compose_data(.n_name = n_prefix("N")) #> $plot #>  1 2 3 4 5 6 7 8 1 2 3 4 5 6 7 8 #> #> $N_plot #>  8 #> #> $site #>  1 1 2 2 3 3 4 4 1 1 2 2 3 3 4 4 #> #> $N_site #>  4 #> #> $N #>  16 #> # If you have nesting, you may want a nested index, which can be generated using x_at_y() # Here, site[p] will give the site for plot p df %>% compose_data(site = x_at_y(site, plot)) #> $plot #>  1 2 3 4 5 6 7 8 1 2 3 4 5 6 7 8 #> #> $n_plot #>  8 #> #> $site #>  1 1 2 2 3 3 4 4 #> #> $n_site #>  4 #> #> $n #>  16 #>