Add basic batch postprocessing script

pipelines/batch/setup_prod_job.py

@@ -192,12 +192,14 @@ def main(
     help=("Name of the Azure batch pool on which to run the job"),
 )
 parser.add_argument(
-    "diseases",
+    "--diseases",
     type=str,
+    default="COVID-19 Influenza",
     help=(
         "Name(s) of disease(s) to run as part of the job, "
         "as a whitespace-separated string. Supported "
-        "values are 'COVID-19' and 'Influenza'."
+        "values are 'COVID-19' and 'Influenza'. "
+        "Default 'COVID-19 Influenza' (i.e. run for both)."
     ),
 )
 

pipelines/postprocess_all_locations.py

@@ -1,13 +1,12 @@
 import argparse
-import logging
 import subprocess
 from pathlib import Path
 
 import collate_plots as cp
 from utils import get_all_forecast_dirs, parse_model_batch_dir_name
 
 
-def create_hubverse_table(model_batch_dir: Path) -> None:
+def create_hubverse_table(base_path: Path, model_batch_dir: Path) -> None:
     batch_info = parse_model_batch_dir_name(model_batch_dir)
 
     output_file_name = (
@@ -16,13 +15,14 @@ def create_hubverse_table(model_batch_dir: Path) -> None:
         "hubverse-table.tsv"
     )
 
-    output_path = Path(model_batch_dir, output_file_name)
+    model_batch_path = Path(base_path, model_batch_dir)
+    output_path = Path(model_batch_path, output_file_name)
 
     result = subprocess.run(
         [
             "Rscript",
             "pipelines/create_hubverse_table.R",
-            f"{model_batch_dir}",
+            f"{model_batch_path}",
             f"{output_path}",
         ],
         capture_output=True,
@@ -32,15 +32,23 @@ def create_hubverse_table(model_batch_dir: Path) -> None:
     return None
 
 
-def process_model_batch_dir(model_batch_dir: Path) -> None:
-    cp.process_dir(model_batch_dir)
-    create_hubverse_table(model_batch_dir)
+def process_model_batch_dir(base_dir: Path, model_batch_dir: Path) -> None:
+    plot_types = ["Disease", "Other", "prop_disease_ed_visits"]
+    plots_to_collate = [f"{x}_forecast_plot.pdf" for x in plot_types] + [
+        f"{x}_forecast_plot_log.pdf" for x in plot_types
+    ]
+    cp.process_dir(
+        Path(base_dir, model_batch_dir), target_filenames=plots_to_collate
+    )
+    create_hubverse_table(base_dir, model_batch_dir)
 
 
-def main(base_forecast_dir: Path):
-    to_process = get_all_forecast_dirs(base_forecast_dir)
+def main(
+    base_forecast_dir: Path, diseases: list[str] = ["COVID-19", "Influenza"]
+):
+    to_process = get_all_forecast_dirs(base_forecast_dir, diseases)
     for batch_dir in to_process:
-        process_model_batch_dir(batch_dir)
+        process_model_batch_dir(base_forecast_dir, batch_dir)
 
 
 if __name__ == "__main__":
@@ -50,9 +58,21 @@ def main(base_forecast_dir: Path):
     parser.add_argument(
         "base_forecast_dir",
         type=Path,
-        required=True,
         help="Directory containing forecast subdirectories.",
     )
 
+    parser.add_argument(
+        "--diseases",
+        type=str,
+        default="COVID-19 Influenza",
+        help=(
+            "Name(s) of disease(s) to postprocess, "
+            "as a whitespace-separated string. Supported "
+            "values are 'COVID-19' and 'Influenza'. "
+            "Default 'COVID-19 Influenza' (i.e. postprocess both)."
+        ),
+    )
+
     args = parser.parse_args()
+    args.diseases = args.diseases.split()
     main(**vars(args))

pipelines/utils.py

@@ -67,11 +67,11 @@ def parse_model_batch_dir_name(model_batch_dir_name):
         )
     return dict(
         disease=disease_map_lower_[disease],
-        report_date=datetime.strptime(report_date, "%Y-%m-%d").date(),
-        first_training_date=datetime.strptime(
+        report_date=datetime.datetime.strptime(report_date, "%Y-%m-%d").date(),
+        first_training_date=datetime.datetime.strptime(
             first_training_date, "%Y-%m-%d"
         ).date(),
-        last_training_date=datetime.strptime(
+        last_training_date=datetime.datetime.strptime(
             last_training_date, "%Y-%m-%d"
         ).date(),
     )