Dear Terry,
The following approach may be more suitable:
fits <- lapply(argument, function)
fits.df = do.call(rbind, fits);
It works if all the lists returned by "function" have the same number of
elements.
Example:
fits.df = lapply(seq(3), function(id) {
list(
beta =
I find your original sapply(List, function(element)element$name) easy to
understand. However replacing sapply with vapply makes for more robust
code. vapply requires you to supply the expected mode (type) and length of
element$name and if any of the elements don't comply with that, vapply
gives
Thanks everyone for prodding my gray matter, which seems to be getting stiffer
as I
approach 70 (< 90 days).
-- I'll continue to use the $ or [[ forms. That will suffice.
-- I thought there might be a base R variant, e.g. something like extract(
list,
element-name); probably cross
Well, I prefer Greg's approach, but if you want to avoid calls to $ or
`[[` then you could do:
unlist(fits)[ rep(names(fits[[1]]) == 'iter', length(fits))]
Cheers,
Bert
On Tue, Dec 27, 2022 at 9:46 AM Greg Snow <538...@gmail.com> wrote:
>
> Another option is the map family of functions in the
Another option is the map family of functions in the purrr package
(yes, this depends on another package being loaded, which may affect
things if you are including this in your own package, creating a
dependency).
In map and friends, if the "function" is a string or integer, then it
is taken as
Terry,
I don't know if it is much cleaner or not, but you can use:
sapply(fits, `[[`, 'iter')
This calls the `[[` function (to extract list elements) on each
element of the top list, with the extra argument of `iter` to say
which element.
On Tue, Dec 27, 2022 at 10:16 AM Therneau, Terry M.,
I not uncommonly have the following paradym
fits <- lapply(argument, function)
resulting in a list of function results. Often, the outer call is to
mclapply, and the
function encodes some long calculation, e.g. multiple chains in an MCMC.
Assume for illustration that each function returns
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