added unzipping functionality for mimic iv example

MIMIC-IV_Example/joint_script.sh

@@ -11,10 +11,11 @@ function display_help() {
     echo "sharding events, splitting patients, converting to sharded events, and merging into a MEDS cohort."
     echo
     echo "Arguments:"
-    echo "  MIMICIV_RAW_DIR        Directory containing raw MIMIC-IV data files."
-    echo "  MIMICIV_PREMEDS_DIR    Output directory for pre-MEDS data."
-    echo "  MIMICIV_MEDS_DIR       Output directory for processed MEDS data."
-    echo "  N_PARALLEL_WORKERS     Number of parallel workers for processing."
+    echo "  MIMICIV_RAW_DIR                               Directory containing raw MIMIC-IV data files."
+    echo "  MIMICIV_PREMEDS_DIR                           Output directory for pre-MEDS data."
+    echo "  MIMICIV_MEDS_DIR                              Output directory for processed MEDS data."
+    echo "  N_PARALLEL_WORKERS                            Number of parallel workers for processing."
+    echo "  (OPTIONAL) do_unzip=true OR do_unzip=false    Optional flag to unzip csv files before processing."
     echo
     echo "Options:"
     echo "  -h, --help          Display this help message and exit."
@@ -37,7 +38,39 @@ MIMICIV_PREMEDS_DIR="$2"
 MIMICIV_MEDS_DIR="$3"
 N_PARALLEL_WORKERS="$4"
 
-shift 4
+# Default do_unzip value
+DO_UNZIP="false"
+
+# Check if the 5th argument is either do_unzip=true or do_unzip=false
+if [ $# -ge 5 ]; then
+  case "$5" in
+    do_unzip=true)
+      DO_UNZIP="true"
+      shift 5
+      ;;
+    do_unzip=false)
+      DO_UNZIP="false"
+      shift 5
+      ;;
+    do_unzip=*)
+      echo "Error: Invalid do_unzip value. Use 'do_unzip=true' or 'do_unzip=false'."
+      exit 1
+      ;;
+    *)
+      # If the 5th argument is not related to do_unzip, leave it for other_args
+      shift 4
+      ;;
+  esac
+else
+  shift 4
+fi
+
+if [ "$DO_UNZIP" == "true" ]; then
+  echo "Unzipping csv files."
+    for file in "${MIMICIV_RAW_DIR}"/*/*.csv.gz; do gzip -d --force "$file"; done
+else
+  echo "Skipping unzipping."
+fi
 
 echo "Running pre-MEDS conversion."
 ./MIMIC-IV_Example/pre_MEDS.py raw_cohort_dir="$MIMICIV_RAW_DIR" output_dir="$MIMICIV_PREMEDS_DIR"

MIMIC-IV_Example/pre_MEDS.py

@@ -1,36 +1,20 @@
 #!/usr/bin/env python
 
 """Performs pre-MEDS data wrangling for MIMIC-IV."""
-import rootutils
 
-root = rootutils.setup_root(__file__, dotenv=True, pythonpath=True, cwd=True)
-
-import gzip
 from datetime import datetime
+from functools import partial
 from pathlib import Path
 
 import hydra
 import polars as pl
 from loguru import logger
 from omegaconf import DictConfig
 
+from MEDS_transforms.extract.utils import get_supported_fp
 from MEDS_transforms.utils import get_shard_prefix, hydra_loguru_init, write_lazyframe
 
 
-def load_raw_mimic_file(fp: Path, **kwargs) -> pl.LazyFrame:
-    """Load a raw MIMIC file into a Polars DataFrame.
-
-    Args:
-        fp: The path to the MIMIC file.
-
-    Returns:
-        The Polars DataFrame containing the MIMIC data.
-    """
-
-    with gzip.open(fp, mode="rb") as f:
-        return pl.read_csv(f, infer_schema_length=100000, **kwargs).lazy()
-
-
 def add_discharge_time_by_hadm_id(
     df: pl.LazyFrame, discharge_time_df: pl.LazyFrame, out_column_name: str = "hadm_discharge_time"
 ) -> pl.LazyFrame:
@@ -82,14 +66,29 @@ def main(cfg: DictConfig):
     raw_cohort_dir = Path(cfg.raw_cohort_dir)
     MEDS_input_dir = Path(cfg.output_dir)
 
-    all_fps = list(raw_cohort_dir.glob("**/*.csv.gz"))
+    all_fps = list(raw_cohort_dir.glob("**/*.*"))
 
     dfs_to_load = {}
+    seen_fps = {}
 
     for in_fp in all_fps:
         pfx = get_shard_prefix(raw_cohort_dir, in_fp)
 
-        out_fp = MEDS_input_dir / in_fp.relative_to(raw_cohort_dir)
+        try:
+            fp, read_fn = get_supported_fp(raw_cohort_dir, pfx)
+        except FileNotFoundError:
+            logger.info(f"Skipping {pfx} @ {str(in_fp.resolve())} as no compatible dataframe file was found.")
+            continue
+
+        if fp.suffix in [".csv", ".csv.gz"]:
+            read_fn = partial(read_fn, infer_schema_length=100000)
+
+        if str(fp.resolve()) in seen_fps:
+            continue
+        else:
+            seen_fps[str(fp.resolve())] = read_fn
+
+        out_fp = MEDS_input_dir / fp.relative_to(raw_cohort_dir)
 
         if out_fp.is_file():
             print(f"Done with {pfx}. Continuing")
@@ -99,10 +98,9 @@ def main(cfg: DictConfig):
 
         if pfx not in FUNCTIONS:
             logger.info(
-                f"No function needed for {pfx}: "
-                f"Symlinking {str(in_fp.resolve())} to {str(out_fp.resolve())}"
+                f"No function needed for {pfx}: " f"Symlinking {str(fp.resolve())} to {str(out_fp.resolve())}"
             )
-            relative_in_fp = in_fp.relative_to(out_fp.resolve().parent, walk_up=True)
+            relative_in_fp = fp.relative_to(out_fp.resolve().parent, walk_up=True)
             out_fp.symlink_to(relative_in_fp)
             continue
         else:
@@ -115,8 +113,8 @@ def main(cfg: DictConfig):
             if not need_df:
                 st = datetime.now()
                 logger.info(f"Processing {pfx}...")
-                df = load_raw_mimic_file(in_fp)
-                logger.info(f"  Loaded raw {in_fp} in {datetime.now() - st}")
+                df = read_fn(fp)
+                logger.info(f"  Loaded raw {fp} in {datetime.now() - st}")
                 processed_df = fn(df)
                 write_lazyframe(processed_df, out_fp)
                 logger.info(f"  Processed and wrote to {str(out_fp.resolve())} in {datetime.now() - st}")
@@ -125,19 +123,19 @@ def main(cfg: DictConfig):
                 if needed_pfx not in dfs_to_load:
                     dfs_to_load[needed_pfx] = {"fps": set(), "cols": set()}
 
-                dfs_to_load[needed_pfx]["fps"].add(in_fp)
+                dfs_to_load[needed_pfx]["fps"].add(fp)
                 dfs_to_load[needed_pfx]["cols"].update(needed_cols)
 
     for df_to_load_pfx, fps_and_cols in dfs_to_load.items():
         fps = fps_and_cols["fps"]
         cols = list(fps_and_cols["cols"])
 
-        df_to_load_fp = raw_cohort_dir / f"{df_to_load_pfx}.csv.gz"
+        df_to_load_fp, df_to_load_read_fn = get_supported_fp(raw_cohort_dir, df_to_load_pfx)
 
         st = datetime.now()
 
         logger.info(f"Loading {str(df_to_load_fp.resolve())} for manipulating other dataframes...")
-        df = load_raw_mimic_file(df_to_load_fp, columns=cols)
+        df = read_fn(df_to_load_fp, columns=cols)
         logger.info(f"  Loaded in {datetime.now() - st}")
 
         for fp in fps:
@@ -149,7 +147,7 @@ def main(cfg: DictConfig):
 
             fp_st = datetime.now()
             logger.info(f"    Loading {str(fp.resolve())}...")
-            fp_df = load_raw_mimic_file(fp)
+            fp_df = seen_fps[str(fp.resolve())](fp)
             logger.info(f"    Loaded in {datetime.now() - fp_st}")
             processed_df = fn(fp_df, df)
             write_lazyframe(processed_df, out_fp)

eICU_Example/pre_MEDS.py

@@ -4,9 +4,6 @@
 
 See the docstring of `main` for more information.
 """
-import rootutils
-
-root = rootutils.setup_root(__file__, dotenv=True, pythonpath=True, cwd=True)
 
 import gzip
 from collections.abc import Callable

pyproject.toml

@@ -23,7 +23,6 @@ dependencies = [
 [tool.setuptools_scm]
 
 [project.optional-dependencies]
-examples = ["rootutils"]
 dev = ["pre-commit"]
 tests = ["pytest", "pytest-cov", "rootutils"]
 local_parallelism = ["hydra-joblib-launcher"]