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⚑ Bolt: Optimize maximum matrix rows calculation with vapply #90

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⚑ Bolt: Optimize maximum matrix rows calculation with vapply #90

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4 changes: 4 additions & 0 deletions .jules/bolt.md
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Original file line number Diff line number Diff line change
Expand Up @@ -15,3 +15,7 @@
## 2024-05-15 - [R Performance: ifelse Overhead]
**Learning:** In R, ifelse evaluates both true and false branches entirely before subsetting, which is very inefficient for vector operations.
**Action:** Optimize this by preallocating with res <- Y * 0 to preserve attributes and using vectorized subsetting like if any cond res subset <- ...

## 2024-08-17 - Optimize sapply overhead with vapply in R
**Learning:** Using `sapply` over a list involves significant overhead to deduce and simplify the return type.
**Action:** When the return type and length are known, prefer `vapply(..., FUN.VALUE = type)` over `sapply(...)` for better performance and safety.
3 changes: 2 additions & 1 deletion R/llcont.R
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Expand Up @@ -407,7 +407,8 @@ llcont.lavaan <- function(x, ...){
if(tolower(lavInspect(x, "options")$missing) == "ml.x") stop("cannot handle lavaan models with missing='ml.x'. consider using missing='ml'.", call. = FALSE)
mispatts <- lavInspect(x, "patterns")
if(any(class(mispatts) == "list")){
npatts <- max(sapply(mispatts, nrow))
## Bolt: replaced sapply with vapply for performance
npatts <- max(vapply(mispatts, nrow, numeric(1)))
} else {
npatts <- nrow(mispatts)
}
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