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3 changes: 3 additions & 0 deletions .jules/bolt.md
Original file line number Diff line number Diff line change
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.
## 2026-07-20 - R 언어에서 데이터프레임 서브셋팅 시 직접 벡터 참조(Direct Vector Subsetting) 최적화
**Learning:** R에서 `df[condition, "column"] <- value` 같은 2차원 서브셋팅(two-dimensional subsetting)은 S3 메서드 디스패치와 데이터프레임 차원 검사를 수행합니다. 직접 열 할당은 이 고정 오버헤드를 줄이지만, 논리 인덱스 계산과 copy-on-modify 비용은 데이터 크기에 비례하므로 시간 복잡도는 O(N)으로 유지됩니다.
**Action:** `mirt::mod2values()` 결과를 data.frame과 필수 열 스키마로 명시적 검증한 뒤 `df$column[condition] <- value` 형태의 직접 열 할당을 사용합니다. 기존 2차원 할당과 결과·속성이 동일한지는 대표 파라미터 테이블과 Rasch 분기 회귀 테스트로 보존합니다.
101 changes: 70 additions & 31 deletions R/aFIPC.R
Original file line number Diff line number Diff line change
@@ -1,3 +1,45 @@
.validate_scale_parameter_table <- function(parameters, label) {
if (!is.data.frame(parameters)) {
stop(
sprintf("Security Error: %s parameter table must be a data.frame", label),
call. = FALSE
)
}

required_columns <- c("item", "name", "value", "est")
missing_columns <- setdiff(required_columns, names(parameters))
if (length(missing_columns) > 0) {
stop(
sprintf(
"Security Error: %s parameter table is missing required column(s): %s",
label,
paste(missing_columns, collapse = ", ")
),
call. = FALSE
)
}

invisible(parameters)
}

.prepare_scale_parameters <- function(new_parameters, old_parameters, itemtype) {
.validate_scale_parameter_table(new_parameters, "new-form")
.validate_scale_parameter_table(old_parameters, "old-form")

new_parameters$est[new_parameters$item == 'GROUP'] <- FALSE
old_parameters$est[old_parameters$item == 'GROUP'] <- FALSE

new_parameters$est[new_parameters$name == "COV_11"] <- TRUE
old_parameters$est[old_parameters$name == "COV_11"] <- TRUE

if (itemtype == 'Rasch') {
new_parameters$est[new_parameters$name == "a1"] <- FALSE
old_parameters$est[old_parameters$name == "a1"] <- FALSE
}

list(new = new_parameters, old = old_parameters)
}

#' automated fixed item parameter linking
#'
#' @import mirt
Expand Down Expand Up @@ -64,7 +106,7 @@ autoFIPC <-
if (!isS4(x) || !methods::is(x, "SingleGroupClass")) return(FALSE)
ok <- tryCatch({
vals <- mirt::mod2values(x)
is.data.frame(vals) || is.matrix(vals)
is.data.frame(vals)
}, error = function(e) FALSE, warning = function(w) FALSE)
if (!isTRUE(ok)) return(FALSE)
required_slots <- c("OptimInfo", "ParObjects")
Expand Down Expand Up @@ -597,17 +639,14 @@ 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[NewScaleParms$name == "COV_11", "est"] <- TRUE
OldScaleParms[OldScaleParms$name == "COV_11", "est"] <- TRUE

if (itemtype == 'Rasch') {
NewScaleParms[NewScaleParms$name == "a1", "est"] <- FALSE
OldScaleParms[OldScaleParms$name == "a1", "est"] <- FALSE
}
prepared_parameters <- .prepare_scale_parameters(
NewScaleParms,
OldScaleParms,
itemtype
)
NewScaleParms <- prepared_parameters$new
OldScaleParms <- prepared_parameters$old
rm(prepared_parameters)

#IPD
if (checkIPD == T) {
Expand Down Expand Up @@ -785,15 +824,15 @@ autoFIPC <-
newIdx <- newScaleParmsItemIdxCache[[newFormItemStr]]
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 = ' '))
# ⚡ Bolt: Use cached rows with direct column access to avoid 2D dispatch
message(' Newform Parms: ', paste(NewScaleParms$value[newIdx], collapse = ' '))
message(' Oldform Parms: ', paste(OldScaleParms$value[oldIdx], collapse = ' '))

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$est[newIdx] <-
FALSE
} else {
message(
Expand All @@ -813,17 +852,17 @@ autoFIPC <-
newBetaIdx <- NewScaleParms$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$value[newBetaIdx],
' '
),
'\n'
Expand Down Expand Up @@ -858,13 +897,13 @@ autoFIPC <-
new_mean11_idx <- NewScaleParms$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 +914,8 @@ 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
146 changes: 146 additions & 0 deletions tests/testthat/test-optimization-equivalence.R
Original file line number Diff line number Diff line change
Expand Up @@ -78,3 +78,149 @@ test_that("IPD anchor extraction keeps old/new rows and screened columns (#99)",
expect_identical(actual_old, legacy_old)
expect_identical(actual_new, legacy_new)
})

test_that("Direct column assignment matches 2D assignment behavior", {
# Mock Data setup equivalent to scale parms
NewScaleParms_2D <- data.frame(
item = c("GROUP", "Item1", "BETA", "Item2"),
name = c("MEAN_1", "a1", "COV_11", "d"),
value = c(0, 1.5, 1, -0.5),
est = c(TRUE, TRUE, FALSE, TRUE),
stringsAsFactors = FALSE
)
OldScaleParms_2D <- NewScaleParms_2D
OldScaleParms_2D$value <- c(1, 2.0, 0, -1.0)

NewScaleParms_1D <- NewScaleParms_2D
OldScaleParms_1D <- OldScaleParms_2D

# 2D Assignment (Legacy)
NewScaleParms_2D[NewScaleParms_2D$item == 'GROUP', "est"] <- FALSE
OldScaleParms_2D[OldScaleParms_2D$item == 'GROUP', "est"] <- FALSE
NewScaleParms_2D[NewScaleParms_2D$name == "COV_11", "est"] <- TRUE
OldScaleParms_2D[OldScaleParms_2D$name == "COV_11", "est"] <- TRUE
NewScaleParms_2D[NewScaleParms_2D$name == "a1", "est"] <- FALSE
OldScaleParms_2D[OldScaleParms_2D$name == "a1", "est"] <- FALSE

newBetaIdx <- NewScaleParms_2D$item == 'BETA'
oldBetaIdx <- OldScaleParms_2D$item == 'BETA'
NewScaleParms_2D[newBetaIdx, "value"] <- OldScaleParms_2D[oldBetaIdx, "value"]
NewScaleParms_2D[newBetaIdx, "est"] <- FALSE

# 1D Assignment (Optimized)
NewScaleParms_1D$est[NewScaleParms_1D$item == 'GROUP'] <- FALSE
OldScaleParms_1D$est[OldScaleParms_1D$item == 'GROUP'] <- FALSE
NewScaleParms_1D$est[NewScaleParms_1D$name == "COV_11"] <- TRUE
OldScaleParms_1D$est[OldScaleParms_1D$name == "COV_11"] <- TRUE
NewScaleParms_1D$est[NewScaleParms_1D$name == "a1"] <- FALSE
OldScaleParms_1D$est[OldScaleParms_1D$name == "a1"] <- FALSE

newBetaIdx_1D <- NewScaleParms_1D$item == 'BETA'
oldBetaIdx_1D <- OldScaleParms_1D$item == 'BETA'
NewScaleParms_1D$value[newBetaIdx_1D] <- OldScaleParms_1D$value[oldBetaIdx_1D]
NewScaleParms_1D$est[newBetaIdx_1D] <- FALSE

expect_identical(NewScaleParms_2D, NewScaleParms_1D)
expect_identical(OldScaleParms_2D, OldScaleParms_1D)

# Check type preservation
expect_type(NewScaleParms_1D$value, "double")
expect_type(NewScaleParms_1D$est, "logical")
})

test_that("direct parameter-column assignment preserves table semantics (#156)", {
new_parameters <- data.frame(
item = c("GROUP", "item_1", "item_1", "item_2", "BETA", "GROUP"),
name = c("MEAN_1", "a1", "d", "COV_11", "beta", "MEAN_11"),
value = c(0, 0.8, -0.4, 0.9, 0.2, 0.1),
est = c(TRUE, TRUE, TRUE, FALSE, TRUE, TRUE),
stringsAsFactors = FALSE
)
old_parameters <- data.frame(
item = c("GROUP", "old_1", "old_1", "old_2", "BETA", "GROUP"),
name = c("MEAN_1", "a1", "d", "COV_11", "beta", "MEAN_11"),
value = c(0, 1.1, -0.7, 1.2, 0.5, -0.1),
est = c(TRUE, TRUE, TRUE, FALSE, TRUE, TRUE),
stringsAsFactors = FALSE
)

legacy_new <- new_parameters
legacy_old <- old_parameters
direct_new <- new_parameters
direct_old <- old_parameters

legacy_new[legacy_new$item == "GROUP", "est"] <- FALSE
legacy_old[legacy_old$item == "GROUP", "est"] <- FALSE
direct_new$est[direct_new$item == "GROUP"] <- FALSE
direct_old$est[direct_old$item == "GROUP"] <- FALSE

legacy_new[legacy_new$name == "COV_11", "est"] <- TRUE
legacy_old[legacy_old$name == "COV_11", "est"] <- TRUE
direct_new$est[direct_new$name == "COV_11"] <- TRUE
direct_old$est[direct_old$name == "COV_11"] <- TRUE

new_anchor <- legacy_new$item == "item_1"
old_anchor <- legacy_old$item == "old_1"
direct_new_anchor <- direct_new$item == "item_1"
direct_old_anchor <- direct_old$item == "old_1"
legacy_new[new_anchor, "value"] <- legacy_old[old_anchor, "value"]
legacy_new[new_anchor, "est"] <- FALSE
direct_new$value[direct_new_anchor] <- direct_old$value[direct_old_anchor]
direct_new$est[direct_new_anchor] <- FALSE

new_beta <- legacy_new$item == "BETA"
old_beta <- legacy_old$item == "BETA"
direct_new_beta <- direct_new$item == "BETA"
direct_old_beta <- direct_old$item == "BETA"
legacy_new[new_beta, "value"] <- legacy_old[old_beta, "value"]
legacy_new[new_beta, "est"] <- FALSE
direct_new$value[direct_new_beta] <- direct_old$value[direct_old_beta]
direct_new$est[direct_new_beta] <- FALSE

expect_identical(direct_new, legacy_new)
expect_identical(direct_old, legacy_old)
})

test_that("scale-parameter preparation validates schema and preserves Rasch semantics (#156)", {
parameters <- data.frame(
item = c("GROUP", "item_1", "item_2"),
name = c("MEAN_1", "a1", "COV_11"),
value = c(0, 1, 1),
est = c(TRUE, TRUE, FALSE),
stringsAsFactors = FALSE
)

legacy_new <- parameters
legacy_old <- parameters
legacy_new[legacy_new$item == "GROUP", "est"] <- FALSE
legacy_old[legacy_old$item == "GROUP", "est"] <- FALSE
legacy_new[legacy_new$name == "COV_11", "est"] <- TRUE
legacy_old[legacy_old$name == "COV_11", "est"] <- TRUE
legacy_new[legacy_new$name == "a1", "est"] <- FALSE
legacy_old[legacy_old$name == "a1", "est"] <- FALSE

actual <- aFIPC:::.prepare_scale_parameters(parameters, parameters, "Rasch")

expect_identical(actual$new, legacy_new)
expect_identical(actual$old, legacy_old)
expect_false(actual$new$est[actual$new$name == "a1"])

expect_error(
aFIPC:::.prepare_scale_parameters(
as.matrix(parameters),
parameters,
"Rasch"
),
"new-form parameter table must be a data.frame",
fixed = TRUE
)

for (missing_column in c("item", "name", "value", "est")) {
incomplete <- parameters[setdiff(names(parameters), missing_column)]
expect_error(
aFIPC:::.prepare_scale_parameters(incomplete, parameters, "Rasch"),
paste0("missing required column\\(s\\): ", missing_column),
fixed = FALSE
)
}
})
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