Remove unused datasets (#742)

Author: dylanhmorris

docs/tutorials/day_of_week_effects.qmd

@@ -95,7 +95,9 @@ The only difference is whether `day_of_week_rv` is provided.
 ```{python}
 # | label: create-processes
 hosp_delay_pmf = jnp.array(
-    datasets.load_infection_admission_interval()["probability_mass"].to_numpy()
+    datasets.load_example_infection_admission_interval()[
+        "probability_mass"
+    ].to_numpy()
 )
 delay_rv = DeterministicPMF("inf_to_hosp_delay", hosp_delay_pmf)
 ihr_rv = DeterministicVariable("ihr", 0.01)

docs/tutorials/observation_processes_counts.qmd

@@ -76,7 +76,7 @@ We load a delay distribution from PyRenew's example datasets, compute summary st
 
 ```{python}
 # | label: delay-distribution
-inf_hosp_int = datasets.load_infection_admission_interval()
+inf_hosp_int = datasets.load_example_infection_admission_interval()
 hosp_delay_pmf = jnp.array(inf_hosp_int["probability_mass"].to_numpy())
 delay_rv = DeterministicPMF("inf_to_hosp_delay", hosp_delay_pmf)
 

docs/tutorials/random_variables.qmd

@@ -161,7 +161,9 @@ The model code is identical whether the rate is fixed or estimated:
 ```{python}
 # | label: interchangeability
 hosp_delay_pmf = jnp.array(
-    datasets.load_infection_admission_interval()["probability_mass"].to_numpy()
+    datasets.load_example_infection_admission_interval()[
+        "probability_mass"
+    ].to_numpy()
 )
 
 # Fixed ascertainment rate

docs/tutorials/right_truncation.qmd

@@ -158,7 +158,9 @@ We construct two `Counts` observation processes: one without right-truncation (t
 ```{python}
 # | label: create-processes
 hosp_delay_pmf = jnp.array(
-    datasets.load_infection_admission_interval()["probability_mass"].to_numpy()
+    datasets.load_example_infection_admission_interval()[
+        "probability_mass"
+    ].to_numpy()
 )
 delay_rv = DeterministicPMF("inf_to_hosp_delay", hosp_delay_pmf)
 ihr_rv = DeterministicVariable("ihr", 0.01)

pyrenew/datasets/__init__.py

@@ -1,17 +1,13 @@
 # numpydoc ignore=GL08
 
-from pyrenew.datasets.generation_interval import load_generation_interval
 from pyrenew.datasets.hospital_admissions import load_hospital_data_for_state
 from pyrenew.datasets.infection_admission_interval import (
-    load_infection_admission_interval,
+    load_example_infection_admission_interval,
 )
-from pyrenew.datasets.wastewater import load_wastewater
 from pyrenew.datasets.wastewater_nwss import load_wastewater_data_for_state
 
 __all__ = [
-    "load_wastewater",
-    "load_infection_admission_interval",
-    "load_generation_interval",
+    "load_example_infection_admission_interval",
     "load_hospital_data_for_state",
     "load_wastewater_data_for_state",
 ]

pyrenew/datasets/generation_interval.py

@@ -1,16 +1,19 @@
-# numpydoc ignore=GL08
+"""
+Example infection to admission delay distribution
+"""
 
 from importlib.resources import files
 
 import polars as pl
 
 
-def load_infection_admission_interval() -> pl.DataFrame:
+def load_example_infection_admission_interval() -> pl.DataFrame:
     """
-    Load the infection to admission interval
+    Load an example infection to hospital admission interval
+    distribution.
 
-    This dataset contains the infection to admission interval distribution for
-    COVID-19.
+    This dataset contains an example infection to admission interval
+    distribution for COVID-19.
 
     Returns
     -------
@@ -20,7 +23,7 @@ def load_infection_admission_interval() -> pl.DataFrame:
     Notes
     -----
     This dataset was downloaded directly from:
-    https://raw.githubusercontent.com/CDCgov/wastewater-informed-covid-forecasting/0962c5d1652787479ac72caebf076ab55fe4e10c/input/saved_pmfs/inf_to_hosp.csv
+    [github.com/cdcgov/wastewater-informed-covid-forecasting](https://raw.githubusercontent.com/CDCgov/wastewater-informed-covid-forecasting/0962c5d1652787479ac72caebf076ab55fe4e10c/input/saved_pmfs/inf_to_hosp.csv)
 
     The dataset contains the following columns:
         - `timepoint`