How to summarize the elements in a complex object? - r

Question

I have a very complex S4 object (output from a lavaan model) which has slots within slots within slots and variables ($) at the deepest level of each of the deepest slots. How do I extract and store the object.size(and potentially other functions like length and dim and the object name) of every element within this object so that I can compare it to another object of the same class?
I have tried storing the output from str(obj) and unclass(obj) and then manipulating the output to extract the information I want, but it's turning out to be very tedious. Looping over names is equally difficult. Is there a way to "flatten" the object into a list? Is there a recursive function anyone can think of to repeatedly dig into each slot?
Edit
Here's an example, using the lavaan package I referenced above, though ideally the solution shouldn't be dependent on the specific object class and could work across classes:
library(lavaan)
model <- '
# measurement model
ind60 =~ x1 + x2 + x3
dem60 =~ y1 + y2 + y3 + y4
dem65 =~ y5 + y6 + y7 + y8
# regressions
dem60 ~ ind60
dem65 ~ ind60 + dem60
# residual correlations
y1 ~~ y5
y2 ~~ y4 + y6
y3 ~~ y7
y4 ~~ y8
y6 ~~ y8
'
fit <- sem(model, data=PoliticalDemocracy)
The object fit contains many slots and objects inside. I can, of course, extract information from a particular element like object.size(fit#Data#X[[1]]), but I'm looking for a generalized solution. The challenge is that I want to extract the same information about each element, regardless of its "depth".
Thanks!

Answer 1

seems like purrr package might be of help here, especially functions like flatten, transpose, map / at_depth - combined with char vectors as input you can easily extract stuff from deeply nested lists. for example, you could write down the "extractor" functions that you need separatly, then store them all in a list and use invoke (also from purrr) with your object as sole arg or invoke_map on many such objects.
Edit
Here is some code to help you extract object.size(fit#Data#X[[1]]) from one or many lavaan objects. Since the slots you are interested in, in practice are most probably at different depths, my guess is that there is no easy general solution.
The idea is that once you know the exact elements you are interested in - it is fairly straightforward to code up some helper functions to manipulate single/multiple such objects. The functions that I mentioned above provide friendly shortcuts for achieving this.
Let me know if i can be of further help.
library("lavaan")
library("tidyverse")
model <- '
# measurement model
ind60 =~ x1 + x2 + x3
dem60 =~ y1 + y2 + y3 + y4
dem65 =~ y5 + y6 + y7 + y8
# regressions
dem60 ~ ind60
dem65 ~ ind60 + dem60
# residual correlations
y1 ~~ y5
y2 ~~ y4 + y6
y3 ~~ y7
y4 ~~ y8
y6 ~~ y8
'
# say you have 3 different models
fit1 <- sem(model, data=PoliticalDemocracy)
fit2 <- sem(model, data=PoliticalDemocracy)
fit3 <- sem(model, data=PoliticalDemocracy)
# S4 objects have function slot() function for accessing so
object.size(fit#Data#X[[1]])
# becomes
slot(slot(fit, "Data"), "X")[[1]]
# since fit is an S4 object - you have to wrap it up
# in a list to manipulate it easier.
# above code becomes :
list(fit1) %>%
map(~ slot(., "Data")) %>%
map(~ slot(., "X")) %>%
flatten %>%
map(object.size)
# wrap up the above code in a helper function ...
extr_obj_size <- function(lavaan_fit) {
list(lavaan_fit) %>%
map(~ slot(., "Data")) %>%
map(~ slot(., "X")) %>%
map(object.size)
}
extr_obj_size(fit1)
# which you can further wrap up in a function that operates
# on a vector of such objects
extr_multiple_obj_size <- function(vec_lavaan_fits) {
vec_lavaan_fits %>%
map(extr_obj_size) %>%
flatten
}
c(fit,fit2,fit3) %>% extr_multiple_obj_size
Edit2
I don't know how helpful would the following code be in general but i jumbled up something that, given that you know the name of the slot you are interested in - would check at depth 1 and 2 and return you the corresponding value.
fit <- sem(model, data=PoliticalDemocracy)
slot_of_interest <- "eq.constraints"
# slot names at depth 1
depth1 <- names(getSlots("lavaan"))
# slot names at depth 2
depth2 <- depth1 %>% map(~ slotNames(slot(fit,.)))
# helper fun to check if a slot name of interest is inside a slot
in_slot <- function(x) slot_of_interest %in% x
# so if its at depth 1 - then just map slot()-function with that name
if (slot_of_interest %in% depth1) {
list(fit1) %>% map(~slot(., slot_of_interest))
} else {
# otherwise you would need to detect at which index at depth2 does this name appear
index1 <- depth2 %>% detect_index(in_slot)
# and map first the slot-name at that index - then the corresponding slot of interest
list(fit1) %>% map(~ slot(., depth1[index1])) %>% map(~ slot(., slot_of_interest))
}