Merge branch 'main' into 435-update-infectionswithfeedback-process-to…

…-handle-batch-input-within-numpyro-plate-context
CDCgov · Sep 10, 2024 · b7fb437 · b7fb437
2 parents f89aa9d + 145ced6
commit b7fb437
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diff --git a/README.md b/README.md
@@ -48,7 +48,7 @@ pip install git+https://github.com/CDCgov/PyRenew@main
 
 ## Models Implemented With PyRenew
 
-- [CDCgov/pyrenew-covid-wastewaterpyrenew-covid-wastewater](https://github.com/CDCgov/pyrenew-covid-wastewater): _Models and infrastructure for forecasting COVID-19 hospitalizations using wastewater data with PyRenew._
+- [CDCgov/pyrenew-covid-wastewater](https://github.com/CDCgov/pyrenew-covid-wastewater): _Models and infrastructure for forecasting COVID-19 hospitalizations using wastewater data with PyRenew._
 - [CDCgov/pyrenew-flu-light](https://github.com/CDCgov/pyrenew-flu-light/): _An instantiation in PyRenew of an influenza forecasting model used in the 2023-24 respiratory season._
 
 ## Resources

diff --git a/pyrenew/convolve.py b/pyrenew/convolve.py
@@ -169,9 +169,9 @@ def _new_scanner(
 
 
 def compute_delay_ascertained_incidence(
-    p_observed_given_incident: ArrayLike,
     latent_incidence: ArrayLike,
     delay_incidence_to_observation_pmf: ArrayLike,
+    p_observed_given_incident: ArrayLike = 1,
 ) -> ArrayLike:
     """
     Computes incidences observed according

diff --git a/pyrenew/latent/hospitaladmissions.py b/pyrenew/latent/hospitaladmissions.py
@@ -211,9 +211,9 @@ def sample(
         ) = self.infection_to_admission_interval_rv(**kwargs)
 
         latent_hospital_admissions = compute_delay_ascertained_incidence(
-            infection_hosp_rate.value,
             latent_infections.value,
             infection_to_admission_interval.value,
+            infection_hosp_rate.value,
         )
 
         # Applying the day of the week effect. For this we need to:

diff --git a/test/test_incidence_observed_with_delay.py b/test/test_incidence_observed_with_delay.py
@@ -42,8 +42,19 @@ def test(obs_rate, latent_incidence, delay_interval, expected_output):
     incidence observed with a delay
     """
     result = compute_delay_ascertained_incidence(
-        obs_rate,
         latent_incidence,
         delay_interval,
+        obs_rate,
     )
     assert_array_equal(result, expected_output)
+
+
+def test_default_obs_rate():
+    """
+    Compute incidence observed with a delay and default observation rate
+    """
+    result = compute_delay_ascertained_incidence(
+        jnp.array([1.0, 2.0, 3.0]),
+        jnp.array([1.0]),
+    )
+    assert_array_equal(result, jnp.array([1.0, 2.0, 3.0]))