Calculate each subject's mean result

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

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

1# Reference solution for the yamaa benchmark adam-adlb-mean (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)910lb <- read_csv(11  "/app/input/lb.csv",12  col_types = cols(13    LBSEQ = col_integer(),14    LBSTRESN = col_double(),15    .default = col_character()16  )17)1819# Mean of the subject's collected values for the parameter, repeated on20# every record for that subject and parameter.21means <- lb |>22  filter(!is.na(LBSTRESN)) |>23  group_by(STUDYID, USUBJID, LBTESTCD) |>24  summarise(AVALMEAN = mean(LBSTRESN), .groups = "drop")2526adlb <- lb |>27  left_join(means, by = c("STUDYID", "USUBJID", "LBTESTCD")) |>28  mutate(AVAL = LBSTRESN, PARAMCD = LBTESTCD) |>29  arrange(USUBJID, LBSEQ) |>30  select(STUDYID, USUBJID, LBSEQ, PARAMCD, AVAL, AVALMEAN)3132dir.create("/app/output", showWarnings = FALSE)33write_csv(adlb, "/app/output/adlb.csv", na = "")

1# Reference solution for the yamaa benchmark adam-adlb-mean (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 ADLB from the collected LB dataset.89One record per collected laboratory record. AVAL is the collected10numeric result (LBSTRESN); AVALMEAN is the mean of the subject's11non-missing AVAL values for the record's parameter, repeated on every12record for that subject and parameter.13"""1415import csv16from decimal import Decimal, InvalidOperation17from pathlib import Path1819INPUT_DIR = Path("/app/input")20OUTPUT_DIR = Path("/app/output")212223def parse_number(text):24    """Return the Decimal value of a collected result, or None."""25    if text is None:26        return None27    text = text.strip()28    if not text:29        return None30    try:31        return Decimal(text)32    except InvalidOperation:33        return None343536def format_number(value):37    """Format a Decimal without rounding, dropping trailing zeros."""38    if value is None:39        return ""40    text = format(value.normalize(), "f")41    return text424344def main():45    with open(INPUT_DIR / "lb.csv", newline="", encoding="utf-8") as handle:46        rows = list(csv.DictReader(handle))4748    records = []49    totals = {}50    counts = {}51    for row in rows:52        aval = parse_number(row.get("LBSTRESN"))53        key = (row["USUBJID"], row["LBTESTCD"])54        if aval is not None:55            totals[key] = totals.get(key, Decimal(0)) + aval56            counts[key] = counts.get(key, 0) + 157        records.append((row, aval))5859    OUTPUT_DIR.mkdir(parents=True, exist_ok=True)60    fieldnames = ["STUDYID", "USUBJID", "LBSEQ", "PARAMCD", "AVAL", "AVALMEAN"]61    with open(OUTPUT_DIR / "adlb.csv", "w", newline="", encoding="utf-8") as handle:62        writer = csv.DictWriter(handle, fieldnames=fieldnames)63        writer.writeheader()64        for row, aval in records:65            key = (row["USUBJID"], row["LBTESTCD"])66            mean = None67            if counts.get(key):68                mean = totals[key] / counts[key]69            writer.writerow(70                {71                    "STUDYID": row["STUDYID"],72                    "USUBJID": row["USUBJID"],73                    "LBSEQ": row["LBSEQ"],74                    "PARAMCD": row["LBTESTCD"],75                    "AVAL": format_number(aval),76                    "AVALMEAN": format_number(mean),77                }78            )798081if __name__ == "__main__":82    main()

1/* opensas reference solution for the yamaa benchmark adam-adlb-mean.2   Reads the benchmark inputs and derives the requested output.3   Execute with the existing opensas runtime: opensas /app/output/result.sas. */45data lb;6  length STUDYID USUBJID LBTESTCD $1024;7  infile "/app/input/lb.csv" dsd dlm="," firstobs=2 truncover lrecl=32767;8  input STUDYID : $char1024. USUBJID : $char1024. LBSEQ LBTESTCD : $char1024. LBSTRESN;9run;1011proc sql;12  create table result as13  select a.*,a.LBTESTCD as PARAMCD,a.LBSTRESN as AVAL,b.AVALMEAN from lb as a left join (select STUDYID,USUBJID,LBTESTCD,mean(LBSTRESN) as AVALMEAN from lb group by STUDYID,USUBJID,LBTESTCD) as b on a.STUDYID=b.STUDYID and a.USUBJID=b.USUBJID and a.LBTESTCD=b.LBTESTCD;14quit;1516proc export data=result(keep=STUDYID USUBJID LBSEQ PARAMCD AVAL AVALMEAN) outfile="/app/output/adlb.csv" dbms=csv replace; run;