# All your models belong to us: how to combine package archivist and function trace()

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Let’s see how to collect all linear regression models that you will ever create in R.

It’s easy with the *trace()* function. A really powerful, yet not that popular function, that allows you to inject any R code in any point of a body of any function.

Useful in debugging and have other interesting applications.

Below I will show how to use this function to store a copy of every linear model that is created with lm(). In the same way you may store copies of plots/other models/data frames/anything.

To store a persistent copy of an object one can simply use the *save()* function. But we are going to use the archivist package instead. It stores objects in a repository and give you some nice features, like searching within repository, sharing the repository with other users, checking session info for a particular object or restoring packages to versions consistent with a selected object.

To use archivist with the *trace()* function you just need to call two lines. First one will create an empty repo, and the second will execute ‘saveToLocalRepo()’ at the end of each call to the *lm()* function.

library(archivist) # create an empty repo createLocalRepo ("allModels", default = TRUE) # add tracing code trace(lm, exit = quote(saveToRepo(z)))

Now, at the end of every *lm()* function the fitted model will be stored in the repository.

Let’s see this in action.

> lm(Sepal.Length~., data=iris) -> m1 Tracing lm(Sepal.Length ~ ., data = iris) on exit > lm(Sepal.Length~ Petal.Length, data=iris) -> m1 Tracing lm(Sepal.Length ~ Petal.Length, data = iris) on exit > lm(Sepal.Length~-Species, data=iris) -> m1 Tracing lm(Sepal.Length ~ -Species, data = iris) on exit

All models are stored as rda files in a disk based repository.

You can load them to R with the *asearch()* function.

Let’s get all lm objects, apply the AIC function to each of them and sort along AIC.

> asearch("class:lm") %>% sapply(., AIC) %>% sort 4c3ae060f3aaa2509b2faf63d857358e 5c5751e36b31b2251d2767d96993320a 79.11602 160.04042 ed2f4d257fd568c5c6f231fadc7aa645 372.07953

The *aread()* function will download the selected model.

> aread("4c3ae060f3aaa2509b2faf63d857358e") Call: lm(formula = Sepal.Length ~ ., data = iris) Coefficients: (Intercept) Sepal.Width Petal.Length Petal.Width 2.1713 0.4959 0.8292 -0.3152 Speciesversicolor Speciesvirginica -0.7236 -1.0235

Now you can just create model after model and if needed they all can be restored.

Read more about the archivist here: http://pbiecek.github.io/archivist/.

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