Changed extract_estimates argument order so the output from run() can… (

#53) * Changed extract_estimates argument order so the output from run() can be piped into the first arg as a fit. * Updated documentation. * In the extract_estimates function, extract model name from the fit object as it's part of the stan fit structure anyway. Also now includes the model name as an item in the returned estimates list. * Updated calls of extract_estimates to not have the model name. * Removed model name from args for extract_estimates function.
traitecoevo · Jan 21, 2025 · 24884ae · 24884ae
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diff --git a/R/hmde_extract_estimates.R b/R/hmde_extract_estimates.R
@@ -1,6 +1,5 @@
 #' Extract samples and return measurement, individual, and population-level estimates
 #'
-#' @param model model name character string
 #' @param fit fitted model Stan fit
 #' @param input_measurement_data data used to fit the model with ind_id, y_obs, time, obs_index tibble
 #'
@@ -9,8 +8,7 @@
 #' @import dplyr
 #' @importFrom stats quantile
 
-hmde_extract_estimates <- function(model = NULL,
-                                   fit = NULL,
+hmde_extract_estimates <- function(fit = NULL,
                                    input_measurement_data = NULL){
   #Check for fit
   if(is.null(fit)){
@@ -21,9 +19,11 @@ hmde_extract_estimates <- function(model = NULL,
     stop("Fit not S4 stanfit type.")
   }
 
+  model <- fit@model_name
   #Check for model
   if(!model %in% hmde_model_names()){
-    stop("Model name not recognised. Run hmde_model_names() to see available models.")
+    stop(paste0("Model name not recognised: ", model,
+                " Run hmde_model_names() to see available models."))
   }
 
   #Check for input measurement data
@@ -33,7 +33,7 @@ hmde_extract_estimates <- function(model = NULL,
     }
   }
 
-  estimate_list <- list()
+  estimate_list <- list(model_name = model)
   par_names <- hmde_model_pars(model)
 
   if(grepl("multi", model)){ #Get n_ind for multi-individual

diff --git a/inst/stan/affine_single_ind.stan b/inst/stan/affine_single_ind.stan
@@ -66,8 +66,8 @@ data {
   real time[n_obs];
   real y_bar;
   int int_method;
-  real prior_means[2]; #vector of means for beta parameter priors
-  real prior_sds[2]; #Vector of SDs for beta parameter priors
+  real prior_means[2]; //vector of means for beta parameter priors
+  real prior_sds[2]; //Vector of SDs for beta parameter priors
 }
 
 // The parameters accepted by the model.

diff --git a/man/hmde_extract_estimates.Rd b/man/hmde_extract_estimates.Rd
diff --git a/tests/testthat/test-hmde_extract_estimates.R b/tests/testthat/test-hmde_extract_estimates.R
@@ -7,16 +7,13 @@ test_that("Execution and output: extract_estimates function", {
   )
 
   suppressWarnings(
-    constant_single_fit <- hmde_model("constant_single_ind") |>
+    output <- hmde_model("constant_single_ind") |>
       hmde_assign_data(data = data) |>
       hmde_run(chains = 1, iter = 20, cores = 1,
-               verbose = FALSE, show_messages = FALSE)
+               verbose = FALSE, show_messages = FALSE) |>
+      hmde_extract_estimates(input_measurement_data = data)
   )
 
-  output <- hmde_extract_estimates(model = "constant_single_ind",
-                                   fit = constant_single_fit,
-                                   input_measurement_data = data)
-
   expect_named(output)
 
   expect_visible(output)

diff --git a/tests/testthat/test-hmde_plot_de_pieces.R b/tests/testthat/test-hmde_plot_de_pieces.R
@@ -6,8 +6,7 @@ test_that("Execution and output: plot_de_pieces function", {
                verbose = FALSE, show_messages = FALSE)
   )
 
-  output <- hmde_extract_estimates(model = "constant_multi_ind",
-                                   fit = multi_ind_trout,
+  output <- hmde_extract_estimates(fit = multi_ind_trout,
                                    input_measurement_data = Trout_Size_Data)
 
   plot <- hmde_plot_de_pieces(model = "constant_multi_ind",
@@ -33,8 +32,7 @@ test_that("Execution and output: bad input", {
                verbose = FALSE, show_messages = FALSE)
   )
 
-  output <- hmde_extract_estimates(model = "constant_multi_ind",
-                                   fit = multi_ind_trout,
+  output <- hmde_extract_estimates(fit = multi_ind_trout,
                                    input_measurement_data = Trout_Size_Data)
 
   expect_error(

diff --git a/vignettes/canham.Rmd b/vignettes/canham.Rmd
@@ -83,8 +83,7 @@ tree_canham_fit <- hmde_model("canham_multi_ind") |>
   hmde_assign_data(data = Tree_Size_Data)  |>
   hmde_run(chains = 4, cores = 4, iter = 2000)
 
-tree_canham_estimates <- hmde_extract_estimates(model = "canham_multi_ind",
-                                 fit = tree_canham_fit,
+tree_canham_estimates <- hmde_extract_estimates(fit = tree_canham_fit,
                                  input_measurement_data = Tree_Size_Data)
 
 #saveRDS(tree_canham_fit, "tree_canham_fit.rds")

diff --git a/vignettes/constant-growth.Rmd b/vignettes/constant-growth.Rmd
@@ -215,7 +215,7 @@ trout_constant_fit <- hmde_model("constant_multi_ind") |>
 Once the model has finished running, we can extract the model estimates and have a look at the distribution of estimated sizes, estimated growth increments, and annualised growth rates at the level of sizes over time.
 
 ```{r}
-trout_constant_estimates <- hmde_extract_estimates(model = "constant_multi_ind",
+trout_constant_estimates <- hmde_extract_estimates(                                 
                                  fit = trout_constant_fit,
                                  input_measurement_data = Trout_Size_Data)
 ```

diff --git a/vignettes/here_be_dragons.Rmd b/vignettes/here_be_dragons.Rmd
@@ -167,8 +167,7 @@ for(i in 1:runs){
   )
   
   #Extract parameter estimates
-  ests <- hmde_extract_estimates(model = "affine_single_ind",
-                                 fit = fit,
+  ests <- hmde_extract_estimates(fit = fit,
                                  input_measurement_data = obs_data_frame)
   
   temp <- tibble(

diff --git a/vignettes/hmde_for_mathematicians.Rmd b/vignettes/hmde_for_mathematicians.Rmd
@@ -104,8 +104,7 @@ canham_multi_ind_fit <- hmde_model("canham_multi_ind") |>
   hmde_assign_data(data = Tree_Size_Data)  |>
   hmde_run(chains = 1, cores = 1, iter = 1000)
 
-Tree_Size_Ests <- hmde_extract_estimates(model = "canham_multi_ind",
-                                 fit = canham_multi_ind_fit,
+Tree_Size_Ests <- hmde_extract_estimates(fit = canham_multi_ind_fit,
                                  input_measurement_data = Tree_Size_Data)
 ```
 

diff --git a/vignettes/von-bertalanffy.Rmd b/vignettes/von-bertalanffy.Rmd
@@ -100,8 +100,7 @@ lizard_vb_fit <- hmde_model("vb_multi_ind") |>
   hmde_assign_data(data = Lizard_Size_Data)  |>
   hmde_run(chains = 4, cores = 1, iter = 2000)
 
-lizard_estimates <- hmde_extract_estimates(model = "vb_multi_ind",
-                                           fit = lizard_vb_fit,
+lizard_estimates <- hmde_extract_estimates(fit = lizard_vb_fit,
                                            input_measurement_data = Lizard_Size_Data)
 ```