From 94dc1248657896fd134608a065500be05556a46e Mon Sep 17 00:00:00 2001 From: seonghobae <8172694+seonghobae@users.noreply.github.com> Date: Sun, 19 Jul 2026 16:28:58 +0000 Subject: [PATCH] =?UTF-8?q?=E2=9A=A1=20Bolt:=20=EB=8D=B0=EC=9D=B4=ED=84=B0?= =?UTF-8?q?=ED=94=84=EB=A0=88=EC=9E=84=20=ED=95=A0=EB=8B=B9=EC=9D=84=20?= =?UTF-8?q?=EC=A7=81=EC=A0=91=20=EB=B2=A1=ED=84=B0=20=EC=84=9C=EB=B8=8C?= =?UTF-8?q?=EC=85=8B=ED=8C=85=EC=9C=BC=EB=A1=9C=20=EB=B3=80=EA=B2=BD?= =?UTF-8?q?=ED=95=98=EC=97=AC=20dispatch=20=EC=98=A4=EB=B2=84=ED=97=A4?= =?UTF-8?q?=EB=93=9C=20=EC=B5=9C=EC=86=8C=ED=99=94?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit 2D 데이터프레임 할당(df[idx, 'col'] <- val)을 사용할 경우 발생하는 R의 `[<-.data.frame` method dispatch 오버헤드 및 잠재적인 메모리 복사를 방지하기 위해, 이를 1D 직접 벡터 서브셋팅 (df$col[idx] <- val)으로 개선함. --- .jules/bolt.md | 3 +++ R/aFIPC.R | 51 +++++++++++++++++++++++++++----------------------- 2 files changed, 31 insertions(+), 23 deletions(-) diff --git a/.jules/bolt.md b/.jules/bolt.md index 7d3c603..55c794b 100644 --- a/.jules/bolt.md +++ b/.jules/bolt.md @@ -16,3 +16,6 @@ ## 2025-02-12 - R 언어에서 반복적인 mirt 모델 생성 시 불필요한 데이터프레임 부분집합 추출 최적화 **Learning:** R에서 데이터프레임의 특정 열을 추출하는 작업(`df[cols]`)은 O(N)의 메모리 복사를 수반합니다. `autoFIPC`에서 `mirt` 모델의 파라미터를 설정하거나 호출하는 과정 중에 `newformXDataK[colnames(newFormModel@Data$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$data)]`로 캐싱(caching)한 뒤, `ncol(linkedFormData)`와 `data = linkedFormData` 형태로 재사용하여 메모리 복사와 O(N) 오버헤드를 방지해야 합니다. +## 2024-07-19 - R Dataframe Dispatch Overhead Optimization +**Learning:** In R, updating a specific column based on a conditional match is significantly faster using direct vector subsetting (e.g., `df$col[df$idx == 'val'] <- new_val`) compared to two-dimensional subsetting (e.g., `df[df$idx == 'val', 'col'] <- new_val`). Direct vector assignment bypasses the `[<-.data.frame` method dispatch overhead (which checks dimensions, factor levels, and often deeply copies the data frame) in favor of O(1) list access and C-level vector modification. +**Action:** Always prefer 1D vector subsetting for assignments in R dataframes to avoid performance degradation from method dispatch and memory copies, especially inside iterative processes or large data updates. diff --git a/R/aFIPC.R b/R/aFIPC.R index 6254651..eaea807 100644 --- a/R/aFIPC.R +++ b/R/aFIPC.R @@ -598,15 +598,16 @@ 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 + # ⚡ Bolt: Use direct vector subsetting (O(1)) instead of 2D data frame assignment to avoid `[<-.data.frame` dispatch overhead + 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 } #IPD @@ -641,9 +642,10 @@ autoFIPC <- colnames(IPDData) <- paste0('X', 1:IPDItemCount) print(IPDItemNamesOldForm) print(IPDItemNamesNewForm) + # ⚡ Bolt: Fix range evaluation for row assignments IPDData[1:nrow(oldformYDataK), ] <- oldformYDataK[, IPDItemNamesOldForm] - IPDData[nrow(oldformYDataK) + 1:nrow(newformXDataK), ] <- + IPDData[(nrow(oldformYDataK) + 1):(nrow(oldformYDataK) + nrow(newformXDataK)), ] <- newformXDataK[, IPDItemNamesNewForm] # IPD estimation @@ -789,11 +791,12 @@ autoFIPC <- message(' Newform Parms: ', paste(NewScaleParms[newIdx, "value"], collapse = ' ')) message(' Oldform Parms: ', paste(OldScaleParms[oldIdx, "value"], collapse = ' ')) - NewScaleParms[newIdx, "value"] <- - OldScaleParms[oldIdx, "value"] - message(' Linkedform Parms: ', paste(NewScaleParms[newIdx, "value"], collapse = ' '), '\n') + # ⚡ Bolt: Direct vector subsetting + NewScaleParms$value[newIdx] <- + OldScaleParms$value[oldIdx] + message(' Linkedform Parms: ', paste(NewScaleParms$value[newIdx], collapse = ' '), '\n') - NewScaleParms[newIdx, "est"] <- + NewScaleParms$est[newIdx] <- FALSE } else { message( @@ -813,9 +816,10 @@ autoFIPC <- newBetaIdx <- NewScaleParms$item == 'BETA' oldBetaIdx <- OldScaleParms$item == 'BETA' - NewScaleParms[newBetaIdx, "value"] <- - OldScaleParms[oldBetaIdx, "value"] - NewScaleParms[newBetaIdx, "est"] <- + # ⚡ Bolt: Direct vector subsetting + NewScaleParms$value[newBetaIdx] <- + OldScaleParms$value[oldBetaIdx] + NewScaleParms$est[newBetaIdx] <- FALSE message('applying BETA parameter as linking') @@ -823,7 +827,7 @@ autoFIPC <- message( ' Linkedform Parms: ', paste0( - NewScaleParms[newBetaIdx, "value"], + NewScaleParms$value[newBetaIdx], ' ' ), '\n' @@ -858,13 +862,14 @@ 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 + # ⚡ Bolt: Direct vector subsetting + 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 <- @@ -875,8 +880,8 @@ 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(