matrix or data frame to use as source of arguments
.fun
function to apply to each piece
...
other arguments passed on to .fun
.expand
should output be 1d (expand = FALSE), with an element for
each row; or nd (expand = TRUE), with a dimension for each variable.
.progress
name of the progress bar to use, see
create_progress_bar
.inform
produce informative error messages? This is turned off
by default because it substantially slows processing speed, but is very
useful for debugging
.parallel
if TRUE, apply function in parallel, using parallel
backend provided by foreach
.paropts
a list of additional options passed into
the foreach function when parallel computation
is enabled. This is important if (for example) your code relies on
external data or packages: use the .export and .packages
arguments to supply them so that all cluster nodes have the correct
environment set up for computing.
Input
Call a multi-argument function with values taken from
columns of an data frame or array
Output
If there are no results, then this function will return
a list of length 0 (list()).
Details
The m*ply functions are the plyr version of mapply,
specialised according to the type of output they produce. These functions
are just a convenient wrapper around a*ply with margins = 1
and .fun wrapped in splat.
References
Hadley Wickham (2011). The Split-Apply-Combine Strategy
for Data Analysis. Journal of Statistical Software, 40(1), 1-29.
https://www.jstatsoft.org/v40/i01/.
See Also
Other multiple arguments input:
m_ply(),
maply(),
mdply()