Uncollected Exposure

1library(yamaa)23adex <- yamaa_domain("spec.yaml")$output4adex

1import yamaa23adex = yamaa.yamaa_domain("spec.yaml").output4adex

1# Reference solution for the yamaa benchmark adam-adex-uncollected (R track).2#3# Written from the benchmark's full prompt and its inputs alone, as an agent4# would write it. Harbor's oracle agent runs it to check that the prompt can5# be solved and that the grader scores a correct answer 1.67library(dplyr, warn.conflicts = FALSE)8library(readr)910trt <- read_csv(11  "/app/input/subject_treatment.csv",12  col_types = cols(.default = col_character())13)14ex <- read_csv(15  "/app/input/ex.csv",16  col_types = cols(EXDOSE = col_double(), .default = col_character())17)1819# Per treatment: total dose, record count, and count of recorded doses.20agg <- ex |>21  group_by(STUDYID, USUBJID, EXTRT) |>22  summarise(23    DOSE_SUM = sum(EXDOSE, na.rm = TRUE),24    NDOSREC = n(),25    NDOSVAL = sum(!is.na(EXDOSE)),26    .groups = "drop"27  ) |>28  mutate(DOSECUM = if_else(NDOSVAL > 0, DOSE_SUM, NA_real_)) |>29  select(STUDYID, USUBJID, EXTRT, DOSECUM, NDOSREC, NDOSVAL)3031adex <- trt |>32  left_join(agg, by = c("STUDYID", "USUBJID", "EXTRT")) |>33  select(STUDYID, USUBJID, EXTRT, DOSECUM, NDOSREC, NDOSVAL)3435dir.create("/app/output", showWarnings = FALSE)36write_csv(adex, "/app/output/adex.csv", na = "")

1# Reference solution for the yamaa benchmark adam-adex-uncollected (Python track).2#3# Written from the benchmark's full prompt and its inputs alone, as an agent4# would write it. Harbor's oracle agent runs it to check that the prompt can5# be solved and that the grader scores a correct answer 1.67from pathlib import Path89import polars as pl1011trt = pl.read_csv("/app/input/subject_treatment.csv", infer_schema=False)12ex = pl.read_csv("/app/input/ex.csv", infer_schema=False).with_columns(13    pl.col("EXDOSE").cast(pl.Float64, strict=False)14)1516# Per treatment: total dose, record count, and count of recorded doses.17agg = (18    ex.group_by("STUDYID", "USUBJID", "EXTRT")19    .agg(20        pl.col("EXDOSE").sum().alias("DOSE_SUM"),21        pl.len().cast(pl.Int64).alias("NDOSREC"),22        pl.col("EXDOSE").count().cast(pl.Int64).alias("NDOSVAL"),23    )24    .with_columns(25        DOSECUM=pl.when(pl.col("NDOSVAL") > 0)26        .then(pl.col("DOSE_SUM"))27        .otherwise(None)28    )29    .select("STUDYID", "USUBJID", "EXTRT", "DOSECUM", "NDOSREC", "NDOSVAL")30)3132adex = trt.join(33    agg, on=["STUDYID", "USUBJID", "EXTRT"], how="left", maintain_order="left"34).select("STUDYID", "USUBJID", "EXTRT", "DOSECUM", "NDOSREC", "NDOSVAL")3536Path("/app/output").mkdir(exist_ok=True)37adex.write_csv("/app/output/adex.csv")

1/* opensas reference solution for the yamaa benchmark adam-adex-uncollected.2   Reads the benchmark inputs and derives the requested output.3   Execute with the existing opensas runtime: opensas /app/output/result.sas. */45data ex;6  length STUDYID USUBJID EXTRT $1024;7  infile "/app/input/ex.csv" dsd dlm="," firstobs=2 truncover lrecl=32767;8  input STUDYID : $char1024. USUBJID : $char1024. EXTRT : $char1024. EXSEQ EXDOSE;9run;1011data subject_treatment;12  length STUDYID USUBJID EXTRT $1024;13  infile "/app/input/subject_treatment.csv" dsd dlm="," firstobs=2 truncover lrecl=32767;14  input STUDYID : $char1024. USUBJID : $char1024. EXTRT : $char1024.;15run;1617proc sql;18  create table totals as select STUDYID,USUBJID,EXTRT,sum(EXDOSE) as DOSECUM,count(*) as NDOSREC,count(EXDOSE) as NDOSVAL from ex group by STUDYID,USUBJID,EXTRT;19  create table result as select a.*,b.DOSECUM,b.NDOSREC,b.NDOSVAL from subject_treatment as a left join totals as b on a.STUDYID=b.STUDYID and a.USUBJID=b.USUBJID and a.EXTRT=b.EXTRT;20quit;2122proc sql;23  create table final as select STUDYID, USUBJID, EXTRT, DOSECUM, NDOSREC, NDOSVAL from result;24quit;25proc export data=final outfile="/app/output/adex.csv" dbms=csv replace; run;