Derive mean arterial pressure records

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

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

1# Reference solution for the yamaa benchmark adam-advs-map (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)910raw <- read_csv(11  "/app/input/advs.csv",12  col_types = cols(AVAL = col_double(), .default = col_character())13)1415# Every collected record stays in place.16collected <- raw |>17  transmute(STUDYID, USUBJID, PARAMCD, PARAM, AVAL, VISIT, DTYPE = NA_character_)1819# The visit's systolic and diastolic results.20sysbp <- raw |>21  filter(PARAMCD %in% "SYSBP", !is.na(AVAL)) |>22  group_by(STUDYID, USUBJID, VISIT) |>23  summarise(SYSBP_VAL = first(AVAL), .groups = "drop")2425diabp <- raw |>26  filter(PARAMCD %in% "DIABP", !is.na(AVAL)) |>27  group_by(STUDYID, USUBJID, VISIT) |>28  summarise(DIABP_VAL = first(AVAL), .groups = "drop")2930# One mean arterial pressure record for each visit with both results,31# counting the diastolic pressure twice.32map_records <- sysbp |>33  inner_join(diabp, by = c("STUDYID", "USUBJID", "VISIT")) |>34  transmute(35    STUDYID, USUBJID,36    PARAMCD = "MAP", PARAM = "Mean Arterial Pressure (mmHg)",37    AVAL = (SYSBP_VAL + 2 * DIABP_VAL) / 3,38    VISIT, DTYPE = "CALCULATION"39  )4041advs <- bind_rows(collected, map_records) |>42  arrange(USUBJID, VISIT, PARAMCD)4344dir.create("/app/output", showWarnings = FALSE)45write_csv(advs, "/app/output/advs.csv", na = "")

1# Reference solution for the yamaa benchmark adam-advs-map (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 1.67import csv8from collections import OrderedDict910INPUT_PATH = "/app/input/advs.csv"11OUTPUT_PATH = "/app/output/advs.csv"1213COLUMNS = ["STUDYID", "USUBJID", "PARAMCD", "PARAM", "AVAL", "VISIT", "DTYPE"]141516def main():17    with open(INPUT_PATH, newline="") as f:18        rows = list(csv.DictReader(f))1920    # Group collected records by (subject, visit), preserving input order.21    groups = OrderedDict()22    for row in rows:23        key = (row["USUBJID"], row["VISIT"])24        groups.setdefault(key, []).append(row)2526    out_rows = []27    for (usubjid, visit), group in groups.items():28        for row in group:29            out_rows.append({30                "STUDYID": row["STUDYID"],31                "USUBJID": row["USUBJID"],32                "PARAMCD": row["PARAMCD"],33                "PARAM": row["PARAM"],34                "AVAL": row["AVAL"],35                "VISIT": row["VISIT"],36                "DTYPE": "",37            })3839        values = {}40        for row in group:41            if row["PARAMCD"] in ("SYSBP", "DIABP"):42                aval = row["AVAL"]43                if aval is not None and aval.strip() != "":44                    values[row["PARAMCD"]] = float(aval)4546        if "SYSBP" in values and "DIABP" in values:47            map_aval = (2.0 / 3.0) * values["DIABP"] + (1.0 / 3.0) * values["SYSBP"]48            out_rows.append({49                "STUDYID": group[0]["STUDYID"],50                "USUBJID": usubjid,51                "PARAMCD": "MAP",52                "PARAM": "Mean Arterial Pressure (mmHg)",53                "AVAL": repr(map_aval),54                "VISIT": visit,55                "DTYPE": "CALCULATION",56            })5758    with open(OUTPUT_PATH, "w", newline="") as f:59        writer = csv.DictWriter(f, fieldnames=COLUMNS)60        writer.writeheader()61        writer.writerows(out_rows)626364if __name__ == "__main__":65    main()

1/* opensas reference solution for the yamaa benchmark adam-advs-map.2   Reads the benchmark inputs and derives the requested output.3   Execute with the existing opensas runtime: opensas /app/output/result.sas. */45data advs;6  length STUDYID USUBJID PARAMCD PARAM VISIT $1024;7  infile "/app/input/advs.csv" dsd dlm="," firstobs=2 truncover lrecl=32767;8  input STUDYID : $char1024. USUBJID : $char1024. PARAMCD : $char1024. PARAM : $char1024. AVAL VISIT : $char1024.;9run;1011proc sql;12  create table computed as select a.STUDYID,a.USUBJID,'MAP' as PARAMCD,'Mean Arterial Pressure (mmHg)' as PARAM,(a.AVAL+2*b.AVAL)/3 as AVAL,a.VISIT,'CALCULATION' as DTYPE from advs as a inner join advs as b on a.STUDYID=b.STUDYID and a.USUBJID=b.USUBJID and a.VISIT=b.VISIT13  where a.PARAMCD='SYSBP' and b.PARAMCD='DIABP' and not missing(a.AVAL) and not missing(b.AVAL);14quit;15data collected; length DTYPE $11; set advs; run;16data result; set collected computed; run;1718proc sql;19  create table final as select STUDYID, USUBJID, PARAMCD, PARAM, AVAL, VISIT, DTYPE from result;20quit;21proc export data=final outfile="/app/output/advs.csv" dbms=csv replace; run;