Rename random variables in rtperiodicdiff

docs/source/tutorials/basic_renewal_model.qmd

@@ -152,7 +152,7 @@ class MyRt(RandomVariable):
                     reparam=LocScaleReparam(0),
                 ),
                 init_rv=DistributionalRV(
-                    name="init_log_Rt_rv",
+                    name="init_log_rt",
                     dist=dist.Normal(jnp.log(1), jnp.log(1.2)),
                 ),
             ),

docs/source/tutorials/extending_pyrenew.qmd

@@ -69,9 +69,7 @@ rt = TransformedRandomVariable(
         step_rv=DistributionalRV(
             name="rw_step_rv", dist=dist.Normal(0, 0.025)
         ),
-        init_rv=DistributionalRV(
-            name="init_log_Rt_rv", dist=dist.Normal(0, 0.2)
-        ),
+        init_rv=DistributionalRV(name="init_log_rt", dist=dist.Normal(0, 0.2)),
     ),
     transforms=t.ExpTransform(),
 )

docs/source/tutorials/hospital_admissions_model.qmd

@@ -202,7 +202,7 @@ class MyRt(metaclass.RandomVariable):
                     name="rw_step_rv", dist=dist.Normal(0, sd_rt.value)
                 ),
                 init_rv=metaclass.DistributionalRV(
-                    name="init_log_Rt_rv", dist=dist.Normal(0, 0.2)
+                    name="init_log_rt", dist=dist.Normal(0, 0.2)
                 ),
             ),
             transforms=transformation.ExpTransform(),

docs/source/tutorials/periodic_effects.qmd

@@ -27,13 +27,13 @@ from pyrenew import process, deterministic
 rt_proc = process.RtWeeklyDiffProcess(
     name="rt_weekly_diff",
     offset=0,
-    log_rt_prior=deterministic.DeterministicVariable(
-        name="log_rt_prior", value=jnp.array([0.1, 0.2])
+    log_rt_rv=deterministic.DeterministicVariable(
+        name="log_rt", value=jnp.array([0.1, 0.2])
     ),
-    autoreg=deterministic.DeterministicVariable(
+    autoreg_rv=deterministic.DeterministicVariable(
         name="autoreg", value=jnp.array([0.7])
     ),
-    periodic_diff_sd=deterministic.DeterministicVariable(
+    periodic_diff_sd_rv=deterministic.DeterministicVariable(
         name="periodic_diff_sd", value=jnp.array([0.1])
     ),
 )

model/src/pyrenew/process/rtperiodicdiff.py

@@ -52,9 +52,9 @@ def __init__(
         name: str,
         offset: int,
         period_size: int,
-        log_rt_prior: RandomVariable,
-        autoreg: RandomVariable,
-        periodic_diff_sd: RandomVariable,
+        log_rt_rv: RandomVariable,
+        autoreg_rv: RandomVariable,
+        periodic_diff_sd_rv: RandomVariable,
     ) -> None:
         """
         Default constructor for RtPeriodicDiffProcess class.
@@ -66,11 +66,11 @@ def __init__(
         offset : int
             Relative point at which data starts, must be between 0 and
             period_size - 1.
-        log_rt_prior : RandomVariable
+        log_rt_rv : RandomVariable
             Log Rt prior for the first two observations.
-        autoreg : RandomVariable
+        autoreg_rv : RandomVariable
             Autoregressive parameter.
-        periodic_diff_sd : RandomVariable
+        periodic_diff_sd_rv : RandomVariable
             Standard deviation of the noise.
 
         Returns
@@ -85,45 +85,45 @@ def __init__(
         )
 
         self.validate(
-            log_rt_prior=log_rt_prior,
-            autoreg=autoreg,
-            periodic_diff_sd=periodic_diff_sd,
+            log_rt_rv=log_rt_rv,
+            autoreg_rv=autoreg_rv,
+            periodic_diff_sd_rv=periodic_diff_sd_rv,
         )
 
         self.period_size = period_size
         self.offset = offset
-        self.log_rt_prior = log_rt_prior
-        self.autoreg = autoreg
-        self.periodic_diff_sd = periodic_diff_sd
+        self.log_rt_rv = log_rt_rv
+        self.autoreg_rv = autoreg_rv
+        self.periodic_diff_sd_rv = periodic_diff_sd_rv
 
         return None
 
     @staticmethod
     def validate(
-        log_rt_prior: any,
-        autoreg: any,
-        periodic_diff_sd: any,
+        log_rt_rv: any,
+        autoreg_rv: any,
+        periodic_diff_sd_rv: any,
     ) -> None:
         """
         Validate the input parameters.
 
         Parameters
         ----------
-        log_rt_prior : any
+        log_rt_rv : any
             Log Rt prior for the first two observations.
-        autoreg : any
+        autoreg_rv : any
             Autoregressive parameter.
-        periodic_diff_sd : any
+        periodic_diff_sd_rv : any
             Standard deviation of the noise.
 
         Returns
         -------
         None
         """
 
-        _assert_sample_and_rtype(log_rt_prior)
-        _assert_sample_and_rtype(autoreg)
-        _assert_sample_and_rtype(periodic_diff_sd)
+        _assert_sample_and_rtype(log_rt_rv)
+        _assert_sample_and_rtype(autoreg_rv)
+        _assert_sample_and_rtype(periodic_diff_sd_rv)
 
         return None
 
@@ -175,9 +175,9 @@ def sample(
         """
 
         # Initial sample
-        log_rt_prior = self.log_rt_prior.sample(**kwargs)[0].value
-        b = self.autoreg.sample(**kwargs)[0].value
-        s_r = self.periodic_diff_sd.sample(**kwargs)[0].value
+        log_rt_rv = self.log_rt_rv.sample(**kwargs)[0].value
+        b = self.autoreg_rv.sample(**kwargs)[0].value
+        s_r = self.periodic_diff_sd_rv.sample(**kwargs)[0].value
 
         # How many periods to sample?
         n_periods = int(jnp.ceil(duration / self.period_size))
@@ -186,8 +186,8 @@ def sample(
         ar_diff = FirstDifferenceARProcess("trend_rw", autoreg=b, noise_sd=s_r)
         log_rt = ar_diff.sample(
             duration=n_periods,
-            init_val=log_rt_prior[1],
-            init_rate_of_change=log_rt_prior[1] - log_rt_prior[0],
+            init_val=log_rt_rv[1],
+            init_rate_of_change=log_rt_rv[1] - log_rt_rv[0],
         )[0]
 
         return RtPeriodicDiffProcessSample(
@@ -208,9 +208,9 @@ def __init__(
         self,
         name: str,
         offset: int,
-        log_rt_prior: RandomVariable,
-        autoreg: RandomVariable,
-        periodic_diff_sd: RandomVariable,
+        log_rt_rv: RandomVariable,
+        autoreg_rv: RandomVariable,
+        periodic_diff_sd_rv: RandomVariable,
     ) -> None:
         """
         Default constructor for RtWeeklyDiffProcess class.
@@ -221,11 +221,11 @@ def __init__(
             Name of the site.
         offset : int
             Relative point at which data starts, must be between 0 and 6.
-        log_rt_prior : RandomVariable
+        log_rt_rv : RandomVariable
             Log Rt prior for the first two observations.
-        autoreg : RandomVariable
+        autoreg_rv : RandomVariable
             Autoregressive parameter.
-        periodic_diff_sd : RandomVariable
+        periodic_diff_sd_rv : RandomVariable
             Standard deviation of the noise.
 
         Returns
@@ -237,9 +237,9 @@ def __init__(
             name=name,
             offset=offset,
             period_size=7,
-            log_rt_prior=log_rt_prior,
-            autoreg=autoreg,
-            periodic_diff_sd=periodic_diff_sd,
+            log_rt_rv=log_rt_rv,
+            autoreg_rv=autoreg_rv,
+            periodic_diff_sd_rv=periodic_diff_sd_rv,
         )
 
         return None

model/src/test/test_forecast.py

@@ -38,7 +38,7 @@ def test_forecast():
                 name="rw_step_rv", dist=dist.Normal(0, 0.025)
             ),
             init_rv=DistributionalRV(
-                name="init_log_Rt_rv", dist=dist.Normal(0, 0.2)
+                name="init_log_rt", dist=dist.Normal(0, 0.2)
             ),
         ),
         transforms=t.ExpTransform(),

model/src/test/test_latent_admissions.py

@@ -28,7 +28,7 @@ def test_admissions_sample():
                 name="rw_step_rv", dist=dist.Normal(0, 0.025)
             ),
             init_rv=DistributionalRV(
-                name="init_log_Rt_rv", dist=dist.Normal(0, 0.2)
+                name="init_log_rt", dist=dist.Normal(0, 0.2)
             ),
         ),
         transforms=t.ExpTransform(),

model/src/test/test_latent_infections.py

@@ -26,7 +26,7 @@ def test_infections_as_deterministic():
                 name="rw_step_rv", dist=dist.Normal(0, 0.025)
             ),
             init_rv=DistributionalRV(
-                name="init_log_Rt_rv", dist=dist.Normal(0, 0.2)
+                name="init_log_rt", dist=dist.Normal(0, 0.2)
             ),
         ),
         transforms=t.ExpTransform(),

model/src/test/test_model_basic_renewal.py

@@ -41,7 +41,7 @@ def get_default_rt():
                 name="rw_step_rv", dist=dist.Normal(0, 0.025)
             ),
             init_rv=DistributionalRV(
-                name="init_log_Rt_rv", dist=dist.Normal(0, 0.2)
+                name="init_log_rt", dist=dist.Normal(0, 0.2)
             ),
         ),
         transforms=t.ExpTransform(),

model/src/test/test_model_hosp_admissions.py

@@ -51,7 +51,7 @@ def get_default_rt():
                 name="rw_step_rv", dist=dist.Normal(0, 0.025)
             ),
             init_rv=DistributionalRV(
-                name="init_log_Rt_rv", dist=dist.Normal(0, 0.2)
+                name="init_log_rt", dist=dist.Normal(0, 0.2)
             ),
         ),
         transforms=t.ExpTransform(),

model/src/test/test_predictive.py

@@ -36,9 +36,7 @@
         step_rv=DistributionalRV(
             name="rw_step_rv", dist=dist.Normal(0, 0.025)
         ),
-        init_rv=DistributionalRV(
-            name="init_log_Rt_rv", dist=dist.Normal(0, 0.2)
-        ),
+        init_rv=DistributionalRV(name="init_log_rt", dist=dist.Normal(0, 0.2)),
     ),
     transforms=t.ExpTransform(),
 )

model/src/test/test_random_key.py

@@ -42,7 +42,7 @@ def create_test_model():  # numpydoc ignore=GL08
                 name="rw_step_rv", dist=dist.Normal(0, 0.025)
             ),
             init_rv=DistributionalRV(
-                name="init_log_Rt_rv", dist=dist.Normal(0, 0.2)
+                name="init_log_rt", dist=dist.Normal(0, 0.2)
             ),
         ),
         transforms=t.ExpTransform(),

model/src/test/test_rtperiodicdiff.py

@@ -52,14 +52,14 @@ def test_rtweeklydiff() -> None:
     params = {
         "name": "test",
         "offset": 0,
-        "log_rt_prior": DeterministicVariable(
-            name="log_rt_prior", value=jnp.array([0.1, 0.2])
+        "log_rt_rv": DeterministicVariable(
+            name="log_rt", value=jnp.array([0.1, 0.2])
         ),
-        "autoreg": DeterministicVariable(
-            name="autoreg", value=jnp.array([0.7])
+        "autoreg_rv": DeterministicVariable(
+            name="autoreg_rv", value=jnp.array([0.7])
         ),
-        "periodic_diff_sd": DeterministicVariable(
-            name="periodic_diff_sd", value=jnp.array([0.1])
+        "periodic_diff_sd_rv": DeterministicVariable(
+            name="periodic_diff_sd_rv", value=jnp.array([0.1])
         ),
     }
     duration = 30
@@ -100,15 +100,15 @@ def test_rtweeklydiff_no_autoregressive() -> None:
     params = {
         "name": "test",
         "offset": 0,
-        "log_rt_prior": DeterministicVariable(
-            name="log_rt_prior", value=jnp.array([0.0, 0.0])
+        "log_rt_rv": DeterministicVariable(
+            name="log_rt", value=jnp.array([0.0, 0.0])
         ),
         # No autoregression!
-        "autoreg": DeterministicVariable(
-            name="autoreg", value=jnp.array([0.0])
+        "autoreg_rv": DeterministicVariable(
+            name="autoreg_rv", value=jnp.array([0.0])
         ),
-        "periodic_diff_sd": DeterministicVariable(
-            name="periodic_diff_sd",
+        "periodic_diff_sd_rv": DeterministicVariable(
+            name="periodic_diff_sd_rv",
             value=jnp.array([0.1]),
         ),
     }
@@ -141,15 +141,15 @@ def test_rtweeklydiff_manual_reconstruction() -> None:
     params = {
         "name": "test",
         "offset": 0,
-        "log_rt_prior": DeterministicVariable(
-            name="log_rt_prior",
+        "log_rt_rv": DeterministicVariable(
+            name="log_rt",
             value=jnp.array([0.1, 0.2]),
         ),
-        "autoreg": DeterministicVariable(
-            name="autoreg", value=jnp.array([0.7])
+        "autoreg_rv": DeterministicVariable(
+            name="autoreg_rv", value=jnp.array([0.7])
         ),
-        "periodic_diff_sd": DeterministicVariable(
-            name="periodic_diff_sd",
+        "periodic_diff_sd_rv": DeterministicVariable(
+            name="periodic_diff_sd_rv",
             value=jnp.array([0.1]),
         ),
     }
@@ -161,12 +161,12 @@ def test_rtweeklydiff_manual_reconstruction() -> None:
 
     _, ans0 = lax.scan(
         f=rtwd.autoreg_process,
-        init=np.hstack([params["log_rt_prior"]()[0].value, b]),
+        init=np.hstack([params["log_rt_rv"]()[0].value, b]),
         xs=noise,
     )
 
     ans1 = _manual_rt_weekly_diff(
-        log_seed=params["log_rt_prior"]()[0].value, sd=noise, b=b
+        log_seed=params["log_rt_rv"]()[0].value, sd=noise, b=b
     )
 
     assert_array_almost_equal(ans0, ans1)
@@ -180,15 +180,15 @@ def test_rtperiodicdiff_smallsample():
     params = {
         "name": "test",
         "offset": 0,
-        "log_rt_prior": DeterministicVariable(
-            name="log_rt_prior",
+        "log_rt_rv": DeterministicVariable(
+            name="log_rt",
             value=jnp.array([0.1, 0.2]),
         ),
-        "autoreg": DeterministicVariable(
-            name="autoreg", value=jnp.array([0.7])
+        "autoreg_rv": DeterministicVariable(
+            name="autoreg_rv", value=jnp.array([0.7])
         ),
-        "periodic_diff_sd": DeterministicVariable(
-            name="periodic_diff_sd",
+        "periodic_diff_sd_rv": DeterministicVariable(
+            name="periodic_diff_sd_rv",
             value=jnp.array([0.1]),
         ),
     }