Cumulative Dose

1library(yamaa)23yamaa_spec("spec.yaml")$run()$output

1import yamaa23yamaa.spec("spec.yaml").run().output

1# Reference solution for the yamaa benchmark adam-adex-cumulative-dose (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)910ex <- read_csv(11  "/app/input/ex.csv",12  col_types = cols(EXSEQ = col_integer(), .default = col_character())13)14trt <- read_csv(15  "/app/input/subject_treatment.csv",16  col_types = cols(17    PLANDOSE = col_double(), PLANCYC = col_integer(), .default = col_character()18  )19)2021# Every exposure record counts, even one with a zero or missing dose; a22# missing dose adds nothing. A duplicated record counts once per entry.23doses <- ex |>24  mutate(EXDOSE_NUM = suppressWarnings(as.numeric(EXDOSE))) |>25  group_by(USUBJID, EXTRT) |>26  summarise(27    DOSECUM = sum(EXDOSE_NUM, na.rm = TRUE),28    NCYCLES = n(),29    .groups = "drop"30  )3132adex <- trt |>33  left_join(doses, by = c("USUBJID", "EXTRT")) |>34  mutate(35    PLANTOT = PLANDOSE * PLANCYC,36    # Not rounded; no value when the planned total is zero or when there is37    # no cumulative dose to compare.38    RDI = case_when(39      is.na(DOSECUM) ~ NA_real_,40      is.na(PLANTOT) | PLANTOT == 0 ~ NA_real_,41      .default = DOSECUM / PLANTOT * 10042    )43  ) |>44  select(STUDYID, USUBJID, EXTRT, EXDOSU, DOSECUM, NCYCLES, RDI)4546dir.create("/app/output", showWarnings = FALSE)47write_csv(adex, "/app/output/adex.csv", na = "")

1# Reference solution for the yamaa benchmark adam-adex-cumulative-dose (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 1.67"""Create ADEX: one record per subject per treatment, with cumulative8dose, number of cycles, and relative dose intensity."""910import csv11from collections import defaultdict12from pathlib import Path1314INPUT = Path("/app/input")15OUTPUT = Path("/app/output")1617COLUMNS = ["STUDYID", "USUBJID", "EXTRT", "EXDOSU", "DOSECUM", "NCYCLES", "RDI"]181920def fmt(value):21    """Write a number without a trailing .0 when it is whole."""22    if value is None:23        return ""24    if value == int(value):25        return str(int(value))26    return repr(value)272829def main():30    with open(INPUT / "subject_treatment.csv", newline="") as f:31        treatments = list(csv.DictReader(f))32    with open(INPUT / "ex.csv", newline="") as f:33        exposure = list(csv.DictReader(f))3435    doses = defaultdict(list)36    for row in exposure:37        key = (row["STUDYID"], row["USUBJID"], row["EXTRT"])38        doses[key].append(row["EXDOSE"])3940    out_rows = []41    for trt in treatments:42        key = (trt["STUDYID"], trt["USUBJID"], trt["EXTRT"])43        records = doses.get(key)44        if records:45            ncycles = len(records)46            dosecum = sum(float(d) for d in records if d.strip() != "")47        else:48            ncycles = None49            dosecum = None50        planned_total = float(trt["PLANDOSE"]) * float(trt["PLANCYC"])51        if dosecum is None or planned_total == 0:52            rdi = None53        else:54            rdi = dosecum / planned_total * 10055        out_rows.append(56            {57                "STUDYID": trt["STUDYID"],58                "USUBJID": trt["USUBJID"],59                "EXTRT": trt["EXTRT"],60                "EXDOSU": trt["EXDOSU"],61                "DOSECUM": fmt(dosecum),62                "NCYCLES": "" if ncycles is None else str(ncycles),63                "RDI": fmt(rdi),64            }65        )6667    OUTPUT.mkdir(parents=True, exist_ok=True)68    with open(OUTPUT / "adex.csv", "w", newline="") as f:69        writer = csv.DictWriter(f, fieldnames=COLUMNS)70        writer.writeheader()71        writer.writerows(out_rows)727374if __name__ == "__main__":75    main()

1/* opensas reference solution for the yamaa benchmark adam-adex-cumulative-dose.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 EXDOSU $1024;13  infile "/app/input/subject_treatment.csv" dsd dlm="," firstobs=2 truncover lrecl=32767;14  input STUDYID : $char1024. USUBJID : $char1024. EXTRT : $char1024. EXDOSU : $char1024. PLANDOSE PLANCYC;15run;1617proc sql;18  create table totals as select STUDYID,USUBJID,EXTRT,sum(EXDOSE) as DOSECUM,count(*) as NCYCLES from ex group by STUDYID,USUBJID,EXTRT;19  create table result as select a.*,b.DOSECUM,b.NCYCLES,case when a.PLANDOSE*a.PLANCYC ne 0 then 100*b.DOSECUM/(a.PLANDOSE*a.PLANCYC) else . end as RDI 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 export data=result(keep=STUDYID USUBJID EXTRT EXDOSU DOSECUM NCYCLES RDI) outfile="/app/output/adex.csv" dbms=csv replace; run;