Collected Daily Dosing

1library(yamaa)23ec <- yamaa_domain("spec.yaml")$output4ec

1import yamaa23ec = yamaa.yamaa_domain("spec.yaml").output4ec

1# Reference solution for the yamaa benchmark sdtm-ec-collected-exposure (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)910log <- read_csv(11  "/app/input/dosing_log.csv",12  col_types = cols(.default = col_character())13)1415ec <- log |>16  mutate(17    DOMAIN = "EC",18    ECTRT = "Study Drug",19    ECMOOD = "PERFORMED",20    ECOCCUR = DOSE_TAKEN,21    ECREASND = ifelse(DOSE_TAKEN == "Y", NA_character_, na_if(MISSREAS, "")),22    ECDOSE = suppressWarnings(as.integer(ifelse(DOSE_TAKEN == "Y", TABLETS, NA_character_))),23    ECDOSU = "tablet",24    ECDOSFRM = "TABLET",25    ECDOSFRQ = "QD",26    ECROUTE = "ORAL",27    ECSTDTC = suppressWarnings(as.Date(LOGDATE)),28    ECENDTC = suppressWarnings(as.Date(LOGDATE)),29    ECADJ = na_if(DOSE_ADJ, "")30  ) |>31  arrange(STUDYID, USUBJID, ECSTDTC) |>32  group_by(STUDYID, USUBJID) |>33  mutate(ECSEQ = row_number()) |>34  ungroup() |>35  select(36    DOMAIN, STUDYID, USUBJID, ECSEQ, ECTRT, ECMOOD, ECOCCUR, ECREASND,37    ECDOSE, ECDOSU, ECDOSFRM, ECDOSFRQ, ECROUTE, ECSTDTC, ECENDTC, ECADJ38  )3940dir.create("/app/output", showWarnings = FALSE)41write_csv(ec, "/app/output/ec.csv", na = "")

1# Reference solution for the yamaa benchmark sdtm-ec-collected-exposure (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 pl1011log = pl.read_csv("/app/input/dosing_log.csv", infer_schema=False)1213ec = (14    log.with_columns(15        DOMAIN=pl.lit("EC"),16        ECTRT=pl.lit("Study Drug"),17        ECMOOD=pl.lit("PERFORMED"),18        ECOCCUR=pl.col("DOSE_TAKEN"),19        ECREASND=pl.when(pl.col("DOSE_TAKEN") == "Y")20        .then(None)21        .otherwise(pl.col("MISSREAS"))22        .map_elements(lambda v: None if v == "" else v, return_dtype=pl.String),23        ECDOSE=pl.when(pl.col("DOSE_TAKEN") == "Y")24        .then(pl.col("TABLETS").cast(pl.Int64, strict=False))25        .otherwise(None),26        ECDOSU=pl.lit("tablet"),27        ECDOSFRM=pl.lit("TABLET"),28        ECDOSFRQ=pl.lit("QD"),29        ECROUTE=pl.lit("ORAL"),30        ECSTDTC=pl.col("LOGDATE"),31        ECENDTC=pl.col("LOGDATE"),32        ECADJ=pl.col("DOSE_ADJ").map_elements(33            lambda v: None if v == "" or v is None else v, return_dtype=pl.String34        ),35    )36    .with_columns(LOGDATE_DT=pl.col("LOGDATE").str.to_date(strict=False))37    .sort(["STUDYID", "USUBJID", "LOGDATE_DT"])38    .with_columns(ECSEQ=pl.col("USUBJID").cum_count().over(["STUDYID", "USUBJID"]))39    .with_columns(ECSEQ=pl.col("ECSEQ").cast(pl.Int64))40    .select(41        "DOMAIN",42        "STUDYID",43        "USUBJID",44        "ECSEQ",45        "ECTRT",46        "ECMOOD",47        "ECOCCUR",48        "ECREASND",49        "ECDOSE",50        "ECDOSU",51        "ECDOSFRM",52        "ECDOSFRQ",53        "ECROUTE",54        "ECSTDTC",55        "ECENDTC",56        "ECADJ",57    )58)5960Path("/app/output").mkdir(exist_ok=True)61ec.write_csv("/app/output/ec.csv")

1/* opensas reference solution for the yamaa benchmark sdtm-ec-collected-exposure.2   Reads the benchmark inputs and derives the requested output.3   Execute with the existing opensas runtime: opensas /app/output/result.sas. */45data dosing_log;6  length STUDYID USUBJID LOGDATE TABLETS DOSE_TAKEN MISSREAS DOSE_ADJ $1024;7  infile "/app/input/dosing_log.csv" dsd dlm="," firstobs=2 truncover lrecl=32767;8  input STUDYID : $char1024. USUBJID : $char1024. LOGDATE : $char1024. TABLETS : $char1024. DOSE_TAKEN : $char1024. MISSREAS : $char1024. DOSE_ADJ : $char1024.;9run;1011data prepared; set dosing_log; length DOMAIN $2 ECTRT ECMOOD ECOCCUR ECREASND ECDOSU ECDOSFRM ECDOSFRQ ECROUTE ECSTDTC ECENDTC ECADJ $1024;12DOMAIN='EC'; ECTRT='Study Drug'; ECMOOD='PERFORMED'; ECOCCUR=DOSE_TAKEN; ECDOSE=.; ECREASND='';13if ECOCCUR='Y' then ECDOSE=input(TABLETS,best32.); else ECREASND=MISSREAS;14ECDOSU='tablet'; ECDOSFRM='TABLET'; ECDOSFRQ='QD'; ECROUTE='ORAL'; ECSTDTC=LOGDATE; ECENDTC=LOGDATE; ECADJ=DOSE_ADJ; run;15proc sort data=prepared; by STUDYID USUBJID ECSTDTC; run;16data result; set prepared; by STUDYID USUBJID; retain ECSEQ;17  if first.USUBJID then ECSEQ=0;18  ECSEQ+1;19run;2021proc sql;22  create table final as select DOMAIN, STUDYID, USUBJID, ECSEQ, ECTRT, ECMOOD, ECOCCUR, ECREASND, ECDOSE, ECDOSU, ECDOSFRM, ECDOSFRQ, ECROUTE, ECSTDTC, ECENDTC, ECADJ from result;23quit;24proc export data=final outfile="/app/output/ec.csv" dbms=csv replace; run;