Merge branch 'main' into dhm-make-generate-predictive-use-dirname

pipelines/build_pyrenew_model.py

@@ -4,6 +4,7 @@
 from pathlib import Path
 
 import jax.numpy as jnp
+import polars as pl
 from pyrenew.deterministic import DeterministicVariable
 
 from pyrenew_hew.pyrenew_hew_data import PyrenewHEWData
@@ -88,8 +89,14 @@ def build_model_from_dir(
         else None
     )
 
-    # placeholder
-    data_observed_disease_wastewater = None if fit_wastewater else None
+    data_observed_disease_wastewater = (
+        pl.DataFrame(
+            model_data["data_observed_disease_wastewater"],
+            schema_overrides={"date": pl.Date},
+        )
+        if sample_wastewater
+        else None
+    )
 
     population_size = jnp.array(model_data["state_pop"])
 
@@ -175,6 +182,7 @@ def build_model_from_dir(
         right_truncation_offset=right_truncation_offset,
         first_ed_visits_date=first_ed_visits_date,
         first_hospital_admissions_date=first_hospital_admissions_date,
+        population_size=population_size,
     )
 
     return (my_model, my_data)

pipelines/forecast_state.py

@@ -22,6 +22,7 @@
 from generate_predictive import (  # noqa
     generate_and_save_predictions,
 )
+from prep_ww_data import clean_nwss_data, preprocess_ww_data
 
 
 def record_git_info(model_run_dir: Path):
@@ -192,6 +193,7 @@ def main(
     state: str,
     facility_level_nssp_data_dir: Path | str,
     state_level_nssp_data_dir: Path | str,
+    nwss_data_dir: Path | str,
     param_data_dir: Path | str,
     priors_path: Path | str,
     output_dir: Path | str,
@@ -333,6 +335,23 @@ def main(
             "No data available for the requested report date " f"{report_date}"
         )
 
+    available_nwss_reports = get_available_reports(nwss_data_dir)
+    # assming NWSS_vintage directory follows naming convention
+    # using as of date
+    # need to be modified otherwise
+
+    if report_date in available_nwss_reports:
+        nwss_data_raw = pl.scan_parquet(
+            Path(nwss_data_dir, f"{report_date}.parquet")
+        )
+        nwss_data_cleaned = clean_nwss_data(nwss_data_raw).filter(
+            (pl.col("location") == state)
+            & (pl.col("date") >= first_training_date)
+        )
+        state_level_nwss_data = preprocess_ww_data(nwss_data_cleaned)
+    else:
+        state_level_nwss_data = None  ## TO DO: change
+
     param_estimates = pl.scan_parquet(Path(param_data_dir, "prod.parquet"))
     model_batch_dir_name = (
         f"{disease.lower()}_r_{report_date}_f_"
@@ -357,6 +376,7 @@ def main(
         disease=disease,
         facility_level_nssp_data=facility_level_nssp_data,
         state_level_nssp_data=state_level_nssp_data,
+        state_level_nwss_data=state_level_nwss_data,
         report_date=report_date,
         first_training_date=first_training_date,
         last_training_date=last_training_date,
@@ -497,6 +517,13 @@ def main(
         ),
     )
 
+    parser.add_argument(
+        "--nwss-data-dir",
+        type=Path,
+        default=Path("private_data", "nwss_vintages"),
+        help=("Directory in which to look for NWSS data."),
+    )
+
     parser.add_argument(
         "--param-data-dir",
         type=Path,

pipelines/prep_data.py

@@ -8,6 +8,7 @@
 from pathlib import Path
 
 import forecasttools
+import jax.numpy as jnp
 import polars as pl
 import polars.selectors as cs
 
@@ -354,6 +355,7 @@ def process_and_save_state(
     logger: Logger = None,
     facility_level_nssp_data: pl.LazyFrame = None,
     state_level_nssp_data: pl.LazyFrame = None,
+    state_level_nwss_data: pl.LazyFrame = None,
     credentials_dict: dict = None,
 ) -> None:
     logging.basicConfig(level=logging.INFO)
@@ -449,6 +451,12 @@ def process_and_save_state(
         "hospital_admissions"
     ).to_list()
 
+    data_observed_disease_wastewater = (
+        state_level_nwss_data.to_dict(as_series=False)
+        if state_level_nwss_data is not None
+        else None
+    )
+
     data_for_model_fit = {
         "inf_to_ed_pmf": delay_pmf,
         "generation_interval_pmf": generation_interval_pmf,
@@ -462,7 +470,9 @@ def process_and_save_state(
         "nhsn_step_size": nhsn_step_size,
         "state_pop": state_pop,
         "right_truncation_offset": right_truncation_offset,
+        "data_observed_disease_wastewater": data_observed_disease_wastewater,
     }
+
     data_dir = Path(model_run_dir, "data")
     os.makedirs(data_dir, exist_ok=True)