Merge in code to run and score retrospective evaluation

.gitignore

@@ -9,6 +9,7 @@
 *.bin
 *.xls
 *.xlsx
+*.rds
 
 # Documents
 *.doc

.pre-commit-config.yaml

@@ -2,7 +2,7 @@ repos:
   #####
   # Basic file cleanliness
   - repo: https://github.com/pre-commit/pre-commit-hooks
-    rev: v4.6.0
+    rev: v5.0.0
     hooks:
       - id: check-added-large-files
       - id: check-yaml
@@ -13,7 +13,7 @@ repos:
   #####
   # Python
   - repo: https://github.com/astral-sh/ruff-pre-commit
-    rev: v0.6.8
+    rev: v0.7.1
     hooks:
       # Sort imports
       - id: ruff
@@ -26,13 +26,13 @@ repos:
   #####
   # R
   - repo: https://github.com/lorenzwalthert/precommit
-    rev: v0.4.3
+    rev: v0.4.3.9001
     hooks:
       - id: style-files
       - id: lintr
   # Secrets
   - repo: https://github.com/Yelp/detect-secrets
-    rev: v1.4.0
+    rev: v1.5.0
     hooks:
       - id: detect-secrets
         args: ["--baseline", ".secrets.baseline"]

Containerfile

@@ -12,8 +12,9 @@ WORKDIR pyrenew-hew
 COPY .ContainerBuildRprofile .Rprofile
 
 RUN Rscript -e "install.packages('pak')"
+RUN Rscript -e "pak::pkg_install('cmu-delphi/epiprocess@main')"
+RUN Rscript -e "pak::pkg_install('cmu-delphi/epipredict@main')"
 RUN Rscript -e "pak::local_install('hewr')"
 
 COPY . .
-
 RUN pip install --root-user-action=ignore .

hewr/DESCRIPTION

@@ -9,14 +9,15 @@ License: `use_mit_license()`, `use_gpl3_license()` or friends to pick a
     license
 Encoding: UTF-8
 Roxygen: list(markdown = TRUE)
-RoxygenNote: 7.3.1
+RoxygenNote: 7.3.2
 Imports:
     argparser,
     arrow,
     cowplot,
     dplyr,
     fable,
     feasts,
+    forcats,
     fs,
     ggplot2,
     glue,
@@ -25,6 +26,7 @@ Imports:
     purrr,
     readr,
     scales,
+    scoringutils (>= 2.0.0),
     stringr,
     tibble,
     tidybayes,

hewr/R/parse_path.R

@@ -0,0 +1,63 @@
+disease_map_lower <- list(
+  "covid-19" = "COVID-19",
+  "influenza" = "Influenza"
+)
+
+#' Parse the name of a model batch directory
+#' (i.e. a directory representing a single
+#' report date and disease pair, but potentially
+#' with fits for multiple locations), returning
+#' a named list of quantities of interest.
+#'
+#' @param model_batch_dir_name Name of the model batch
+#' directory (not the full path to it, just the directory
+#' base name) to parse.
+#' @return A list of quantities: `disease`, `report_date`,
+#' `first_training_date`, and `last_training_date`.
+#' @export
+parse_model_batch_dir <- function(model_batch_dir_name) {
+  pattern <- "(.+)_r_(.+)_f_(.+)_t_(.+)"
+
+  matches <- stringr::str_match(
+    model_batch_dir_name,
+    pattern
+  )
+
+  if (is.na(matches[1])) {
+    stop(
+      "Invalid format for model batch directory name; ",
+      "could not parse. Expected ",
+      "'<disease>_r_<report_date>_f_<first_training_date>_t_",
+      "<last_training_date>'."
+    )
+  }
+
+  return(list(
+    disease = disease_map_lower[[matches[2]]],
+    report_date = lubridate::ymd(matches[3]),
+    first_training_date = lubridate::ymd(matches[4]),
+    last_training_date = lubridate::ymd(matches[5])
+  ))
+}
+
+#' Parse path to a model run directory
+#' (i.e. a directory representing a run for a
+#' particular location, disease, and reference
+#' date, and extract key quantities of interest.
+#'
+#' @param model_run_dir_path Path to parse.
+#' @return A list of parsed attributes:
+#' `location`, `disease`, `report_date`,
+#' `first_training_date`, and `last_training_date`.
+#'
+#' @export
+parse_model_run_dir <- function(model_run_dir_path) {
+  batch_dir <- fs::path_dir(model_run_dir_path) |>
+    fs::path_file()
+  location <- fs::path_file(model_run_dir_path)
+
+  return(c(
+    list(location = location),
+    parse_model_batch_dir(batch_dir)
+  ))
+}

nssp_demo/batch/setup_eval_job.py

@@ -0,0 +1,219 @@
+"""
+Set up a multi-location, multi-date,
+potentially multi-disease end to end
+retrospective evaluation run for pyrenew-hew
+on Azure Batch.
+"""
+
+import argparse
+import datetime
+import itertools
+
+import polars as pl
+from azure.batch import models
+from azuretools.auth import EnvCredentialHandler
+from azuretools.client import get_batch_service_client
+from azuretools.job import create_job_if_not_exists
+from azuretools.task import get_container_settings, get_task_config
+
+
+def main(
+    job_id: str,
+    pool_id: str,
+    diseases: str,
+    container_image_name: str = "pyrenew-hew",
+    container_image_version: str = "latest",
+    excluded_locations: list[str] = [
+        "AS",
+        "GU",
+        "MO",
+        "MP",
+        "PR",
+        "UM",
+        "VI",
+        "WY",
+    ],
+) -> None:
+    """
+    job_id
+        Name for the Batch job.
+
+    pool_id
+        Azure Batch pool on which to run the job.
+
+    diseases
+        Name(s) of disease(s) to run as part of the job,
+        as a whitespace-separated string. Supported
+        values are 'COVID-19' and 'Influenza'.
+
+    container_image_name:
+        Name of the container to use for the job.
+        This container should exist within the Azure
+        Container Registry account associated to
+        the job. Default 'pyrenew-hew'.
+        The container registry account name and endpoint
+        will be obtained from local environment variables
+        via a :class``azuretools.auth.EnvCredentialHandler`.
+
+    container_image_version
+        Version of the container to use. Default 'latest'.
+
+    excluded_locations
+        List of two letter USPS location abbreviations to
+        exclude from the job. Defaults to locations for which
+        we typically do not have available NSSP ED visit data:
+        ``["AS", "GU", "MO", "MP", "PR", "UM", "VI", "WY"]``.
+
+    Returns
+    -------
+    None
+    """
+    supported_diseases = ["COVID-19", "Influenza"]
+
+    disease_list = diseases.split()
+    invalid_diseases = set(disease_list) - set(supported_diseases)
+    if invalid_diseases:
+        raise ValueError(
+            f"Unsupported diseases: {', '.join(invalid_diseases)}; "
+            f"supported diseases are: {', '.join(supported_diseases)}"
+        )
+
+    creds = EnvCredentialHandler()
+    client = get_batch_service_client(creds)
+    job = models.JobAddParameter(
+        id=job_id,
+        pool_info=models.PoolInformation(pool_id=pool_id),
+    )
+    create_job_if_not_exists(client, job, verbose=True)
+
+    container_image = (
+        f"{creds.azure_container_registry_account}."
+        f"{creds.azure_container_registry_domain}/"
+        f"{container_image_name}:{container_image_version}"
+    )
+    container_settings = get_container_settings(
+        container_image,
+        working_directory="containerImageDefault",
+        mount_pairs=[
+            {
+                "source": "nssp-etl",
+                "target": "/pyrenew-hew/nssp_demo/nssp-etl",
+            },
+            {
+                "source": "nssp-archival-vintages",
+                "target": "/pyrenew-hew/nssp_demo/nssp-archival-vintages",
+            },
+            {
+                "source": "prod-param-estimates",
+                "target": "/pyrenew-hew/nssp_demo/params",
+            },
+            {
+                "source": "pyrenew-test-output",
+                "target": "/pyrenew-hew/nssp_demo/private_data",
+            },
+        ],
+    )
+
+    base_call = (
+        "/bin/bash -c '"
+        "python nssp_demo/forecast_state.py "
+        "--disease {disease} "
+        "--state {state} "
+        "--n-training-days 365 "
+        "--n-warmup 1000 "
+        "--n-samples 500 "
+        "--facility-level-nssp-data-dir nssp_demo/nssp-etl/gold "
+        "--state-level-nssp-data-dir "
+        "nssp_demo/nssp-archival-vintages/gold "
+        "--param-data-dir nssp_demo/params "
+        "--output-data-dir nssp_demo/private_data "
+        "--report-date {report_date:%Y-%m-%d} "
+        "--exclude-last-n-days 2 "
+        "--score "
+        "--eval-data-path "
+        "nssp_demo/nssp-archival-vintages/latest_comprehensive.parquet"
+        "'"
+    )
+
+    locations = pl.read_csv(
+        "https://www2.census.gov/geo/docs/reference/state.txt", separator="|"
+    )
+
+    all_locations = (
+        locations.filter(~pl.col("STUSAB").is_in(excluded_locations))
+        .get_column("STUSAB")
+        .to_list()
+    )
+
+    report_dates = [
+        datetime.date(2023, 10, 11) + datetime.timedelta(weeks=x)
+        for x in range(30)
+    ]
+
+    for disease, report_date, loc in itertools.product(
+        disease_list, report_dates, all_locations
+    ):
+        task = get_task_config(
+            f"{job_id}-{loc}-{disease}-{report_date}",
+            base_call=base_call.format(
+                state=loc,
+                disease=disease,
+                report_date=report_date,
+            ),
+            container_settings=container_settings,
+        )
+        client.task.add(job_id, task)
+
+    return None
+
+
+parser = argparse.ArgumentParser()
+
+parser.add_argument("job_id", type=str, help="Name for the Azure batch job")
+parser.add_argument(
+    "pool_id",
+    type=str,
+    help=("Name of the Azure batch pool on which to run the job"),
+)
+parser.add_argument(
+    "diseases",
+    type=str,
+    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'."
+    ),
+)
+
+parser.add_argument(
+    "--container-image-name",
+    type=str,
+    help="Name of the container to use for the job.",
+    default="pyrenew-hew",
+)
+
+parser.add_argument(
+    "--container-image-version",
+    type=str,
+    help="Version of the container to use for the job.",
+    default="latest",
+)
+
+parser.add_argument(
+    "--excluded-locations",
+    type=str,
+    help=(
+        "Two-letter USPS location abbreviations to "
+        "exclude from the job, as a whitespace-separated "
+        "string. Defaults to a set of locations for which "
+        "we typically do not have available NSSP ED visit "
+        "data: 'AS GU MO MP PR UM VI WY'."
+    ),
+    default="AS GU MO MP PR UM VI WY",
+)
+
+
+if __name__ == "__main__":
+    args = parser.parse_args()
+    args.excluded_locations = args.excluded_locations.split()
+    main(**vars(args))