rename make_epi_inference_model -> make_epi_aware

CDCgov · Feb 28, 2024 · 8f0c5df · 8f0c5df
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Showing 5 changed files with 11 additions and 11 deletions.
diff --git a/EpiAware/README.md b/EpiAware/README.md
@@ -50,7 +50,7 @@ DelayObservations"]
 
 E["Turing model constructor
 ---------------------
-make_epi_inference_model"]
+make_epi_aware"]
 
 G[Posterior draws]
 H[Posterior checking]

diff --git a/EpiAware/src/EpiAware.jl b/EpiAware/src/EpiAware.jl
@@ -39,7 +39,7 @@ export EpiData, Renewal, ExpGrowthRate, DirectInfections, AbstractEpiModel,
        AbstractLatentModel, AbstractObservationModel
 
 # Exported Turing model constructors
-export make_epi_inference_model
+export make_epi_aware
 
 include("epi-models.jl")
 include("utilities.jl")

diff --git a/EpiAware/src/models.jl b/EpiAware/src/models.jl
@@ -1,4 +1,4 @@
-@model function make_epi_inference_model(y_t,
+@model function make_epi_aware(y_t,
         time_steps;
         epi_model::AbstractEpiModel,
         latent_model_model::AbstractLatentModel,

diff --git a/EpiAware/test/predictive_checking/toy_model_log_infs_RW.jl b/EpiAware/test/predictive_checking/toy_model_log_infs_RW.jl
@@ -107,7 +107,7 @@ obs_model = EpiAware.DelayObservations([1.0],
 We don't have observed data, so we use `missing` value for `y_t`.
 =#
 
-log_infs_model = make_epi_inference_model(missing, time_horizon, ; epi_model = epi_model,
+log_infs_model = make_epi_aware(missing, time_horizon, ; epi_model = epi_model,
     latent_model_model = rwp, observation_model = obs_model,
     pos_shift = 1e-6)
 
@@ -140,7 +140,7 @@ We treat the generated data as observed data and attempt to infer underlying inf
 
 truth_data = random_epidemic.y_t
 
-model = make_epi_inference_model(truth_data, time_horizon, ; epi_model = epi_model,
+model = make_epi_aware(truth_data, time_horizon, ; epi_model = epi_model,
     latent_model_model = rwp, observation_model = obs_model,
     pos_shift = 1e-6)
 @time chn = sample(model,

diff --git a/EpiAware/test/test_models.jl b/EpiAware/test/test_models.jl
@@ -1,5 +1,5 @@
 
-@testitem "`make_epi_inference_model` with direct infections and RW latent process runs" begin
+@testitem "`make_epi_aware` with direct infections and RW latent process runs" begin
     using Distributions, Turing, DynamicPPL
     # Define test inputs
     y_t = missing # Data will be generated from the model
@@ -26,7 +26,7 @@
         Δd = Δd)
 
     # Create full epi model and sample from it
-    test_mdl = make_epi_inference_model(y_t, time_horizon; epi_model = epi_model,
+    test_mdl = make_epi_aware(y_t, time_horizon; epi_model = epi_model,
         latent_model_model = rwp,
         observation_model = obs_model, pos_shift)
     gen = generated_quantities(test_mdl, rand(test_mdl))
@@ -37,7 +37,7 @@
     @test length(gen.I_t) == time_horizon
 end
 
-@testitem "`make_epi_inference_model` with Exp growth rate and RW latent process runs" begin
+@testitem "`make_epi_aware` with Exp growth rate and RW latent process runs" begin
     using Distributions, Turing, DynamicPPL
     # Define test inputs
     y_t = missing# rand(1:10, 365) # Data will be generated from the model
@@ -60,7 +60,7 @@ end
         truncated(Gamma(5, 0.05 / 5), 1e-3, 1.0))
 
     # Create full epi model and sample from it
-    test_mdl = make_epi_inference_model(y_t,
+    test_mdl = make_epi_aware(y_t,
         time_horizon;
         epi_model = epi_model,
         latent_model_model = rwp,
@@ -76,7 +76,7 @@ end
     @test length(gens[1].I_t) == time_horizon
 end
 
-@testitem "`make_epi_inference_model` with Renewal and RW latent process runs" begin
+@testitem "`make_epi_aware` with Renewal and RW latent process runs" begin
     using Distributions, Turing, DynamicPPL
     # Define test inputs
     y_t = missing# rand(1:10, 365) # Data will be generated from the model
@@ -99,7 +99,7 @@ end
         truncated(Gamma(5, 0.05 / 5), 1e-3, 1.0))
 
     # Create full epi model and sample from it
-    test_mdl = make_epi_inference_model(y_t,
+    test_mdl = make_epi_aware(y_t,
         time_horizon;
         epi_model = epi_model,
         latent_model_model = rwp,