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⚡ Bolt: 데이터 프레임 2차원 할당 병목 최적화 #156

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⚡ Bolt: 데이터 프레임 2차원 할당 병목 최적화 #156

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e7d0e2a
perf(R/aFIPC.R): 최적화된 데이터프레임 할당
seonghobae Jul 20, 2026
e5993e7
test(perf): prove parameter assignment equivalence
seonghobae Jul 21, 2026
016790e
perf(R/aFIPC.R): 최적화된 데이터프레임 할당 및 벡터 참조 전환
seonghobae Jul 21, 2026
512a877
fix(perf): preserve strict parameter semantics
seonghobae Jul 21, 2026
649aa63
perf(R/aFIPC.R): 데이터 프레임의 2차원 요소 할당 오버헤드 최적화
seonghobae Jul 21, 2026
b1335b6
fix(autoFIPC): preserve parameter table contract
seonghobae Jul 21, 2026
1e6cf72
test(autoFIPC): isolate assignment indices
seonghobae Jul 21, 2026
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3 changes: 3 additions & 0 deletions .jules/bolt.md
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Expand Up @@ -16,3 +16,6 @@
## 2025-02-12 - R 언어에서 반복적인 mirt 모델 생성 시 불필요한 데이터프레임 부분집합 추출 최적화
**Learning:** R에서 데이터프레임의 특정 열을 추출하는 작업(`df[cols]`)은 O(N)의 메모리 복사를 수반합니다. `autoFIPC`에서 `mirt` 모델의 파라미터를 설정하거나 호출하는 과정 중에 `newformXDataK[colnames(newFormModel@Data$data)]` 코드가 반복해서 사용되었고, 심지어 `ncol()`을 위해 단순히 개수를 구할 때도 사용되어 불필요한 메모리 할당과 오버헤드를 초래했습니다.
**Action:** 조건문이나 반복문 내부에서 불필요하게 데이터프레임 부분집합 연산이 반복되지 않도록 외부에서 한 번만 `linkedFormData <- newformXDataK[colnames(newFormModel@Data$data)]`로 캐싱(caching)한 뒤, `ncol(linkedFormData)`와 `data = linkedFormData` 형태로 재사용하여 메모리 복사와 O(N) 오버헤드를 방지해야 합니다.
## 2024-07-20 - R 언어에서 데이터프레임 서브셋팅 시 직접 벡터 참조(Direct Vector Subsetting) 최적화
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**Learning:** R에서 `df[condition, "column"] <- value` 같은 2차원 서브셋팅(two-dimensional subsetting)은 S3 메서드 디스패치 오버헤드와 데이터프레임 전체 차원 검사 등을 수행하므로 루프나 반복문 내에서 매우 큰 오버헤드를 발생시킵니다.
**Action:** `df$column[condition] <- value` 형태의 직접 벡터 참조 및 할당으로 변경하면 O(1) 수준의 접근이 이루어져 메모리 및 연산 오버헤드 없이 수 배 이상 빠른 속도 향상을 얻을 수 있습니다.
48 changes: 24 additions & 24 deletions R/aFIPC.R
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Expand Up @@ -598,15 +598,15 @@ autoFIPC <-
# Preserve mirt's structural estimability flags. Forcing every row TRUE
# frees boundary parameters such as 2PL g/u and makes the Hessian unstable.

NewScaleParms[NewScaleParms$item == 'GROUP', "est"] <- FALSE
OldScaleParms[OldScaleParms$item == 'GROUP', "est"] <- FALSE
NewScaleParms$est[NewScaleParms$item == 'GROUP'] <- FALSE
OldScaleParms$est[OldScaleParms$item == 'GROUP'] <- FALSE

NewScaleParms[NewScaleParms$name == "COV_11", "est"] <- TRUE
OldScaleParms[OldScaleParms$name == "COV_11", "est"] <- TRUE
NewScaleParms$est[NewScaleParms$name == "COV_11"] <- TRUE
OldScaleParms$est[OldScaleParms$name == "COV_11"] <- TRUE

if (itemtype == 'Rasch') {
NewScaleParms[NewScaleParms$name == "a1", "est"] <- FALSE
OldScaleParms[OldScaleParms$name == "a1", "est"] <- FALSE
NewScaleParms$est[NewScaleParms$name == "a1"] <- FALSE
OldScaleParms$est[OldScaleParms$name == "a1"] <- FALSE
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}

#IPD
Expand Down Expand Up @@ -786,14 +786,14 @@ autoFIPC <-
oldIdx <- oldScaleParmsItemIdxCache[[oldFormItemStr]]

# ⚡ Bolt: Remove unnecessary paste0() array string generation overhead
message(' Newform Parms: ', paste(NewScaleParms[newIdx, "value"], collapse = ' '))
message(' Oldform Parms: ', paste(OldScaleParms[oldIdx, "value"], collapse = ' '))
message(' Newform Parms: ', paste(NewScaleParms$value[newIdx], collapse = ' '))
message(' Oldform Parms: ', paste(OldScaleParms$value[oldIdx], collapse = ' '))
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NewScaleParms[newIdx, "value"] <-
OldScaleParms[oldIdx, "value"]
message(' Linkedform Parms: ', paste(NewScaleParms[newIdx, "value"], collapse = ' '), '\n')
NewScaleParms$value[newIdx] <-
OldScaleParms$value[oldIdx]
message(' Linkedform Parms: ', paste(NewScaleParms$value[newIdx], collapse = ' '), '\n')

NewScaleParms[newIdx, "est"] <-
NewScaleParms$est[newIdx] <-
FALSE
} else {
message(
Expand All @@ -813,17 +813,17 @@ autoFIPC <-
newBetaIdx <- NewScaleParms$item == 'BETA'
oldBetaIdx <- OldScaleParms$item == 'BETA'

NewScaleParms[newBetaIdx, "value"] <-
OldScaleParms[oldBetaIdx, "value"]
NewScaleParms[newBetaIdx, "est"] <-
NewScaleParms$value[newBetaIdx] <-
OldScaleParms$value[oldBetaIdx]
NewScaleParms$est[newBetaIdx] <-
FALSE

message('applying BETA parameter as linking')

message(
' Linkedform Parms: ',
paste0(
NewScaleParms[newBetaIdx, "value"],
NewScaleParms$value[newBetaIdx],
' '
),
'\n'
Expand Down Expand Up @@ -858,13 +858,13 @@ autoFIPC <-
new_mean11_idx <- NewScaleParms$name == "MEAN_11"
old_mean11_idx <- OldScaleParms$name == "MEAN_11"

NewScaleParms[new_cov11_idx, "est"] <- FALSE
OldScaleParms[old_cov11_idx, "est"] <- FALSE
NewScaleParms[new_mean11_idx, "est"] <- FALSE
OldScaleParms[old_mean11_idx, "est"] <- FALSE
NewScaleParms$est[new_cov11_idx] <- FALSE
OldScaleParms$est[old_cov11_idx] <- FALSE
NewScaleParms$est[new_mean11_idx] <- FALSE
OldScaleParms$est[old_mean11_idx] <- FALSE

NewScaleParms[new_cov11_idx, "value"] <- 1
OldScaleParms[old_mean11_idx, "value"] <- 0
NewScaleParms$value[new_cov11_idx] <- 1
OldScaleParms$value[old_mean11_idx] <- 0
}
if (freeMEAN == T) {
LinkedModelSyntax <-
Expand All @@ -875,8 +875,8 @@ autoFIPC <-
'MEAN = F1'
))

NewScaleParms[NewScaleParms$name == "MEAN_1", "est"] <- TRUE
OldScaleParms[OldScaleParms$name == "MEAN_1", "est"] <- TRUE
NewScaleParms$est[NewScaleParms$name == "MEAN_1"] <- TRUE
OldScaleParms$est[OldScaleParms$name == "MEAN_1"] <- TRUE
} else {
LinkedModelSyntax <-
mirt::mirt.model(paste0(
Expand Down
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