Closed rorytboyle closed 1 year ago
furrr doesn't have quite enough information to know that the modelr package needs to be loaded on the worker so that the modelr:::as.data.frame.permutations()
method is registered. So you have to tell it to do that manually. This should work
library(dplyr)
library(modelr)
library(furrr)
#> Loading required package: future
plan(multisession, workers = 4)
reg_form <- 'mpg ~ cyl + disp + hp + wt'
perm_data <- permute(mtcars, 5000, 'hp')
perm_models_parallel <- future_map(
perm_data$perm,
~ lm(reg_form, data = .),
.options = furrr_options(packages = "modelr")
)
Created on 2022-11-29 with reprex v2.0.2.9000
Thank you for responding - that works fine now!
I am trying to replace purrr::map with furrr:future_map to run linear regressions on permuted data obtained from modelr::permute but I get the following error:
Error in as.data.frame.default(data) : cannot coerce class ‘"permutation"’ to a data.frame
I have read through the furrr page but I can't figure out if the gotchas they have described apply to my problem here: https://furrr.futureverse.org/articles/gotchas.html
Here's my code:
library(plyr); library(dplyr); library(modelr); library(purrr); library(furrr)
specify regression formula
reg_form <- 'mpg ~ cyl + disp + hp + wt'
plan(multisession, workers = 4)
Random permutations of 'hp'
perm_data <- permute(mtcars, 5000, 'hp')
permuted linear regressions with map
perm_models <- map(perm_data$perm, ~ lm(reg_form, data = .))
permuted linear regressions with future_map
perm_models_parallel <- future_map(perm_data$perm, ~ lm(reg_form, data = .))