res <- mod$simulate_population_trajectories()
-#> INFO [2024-11-19 13:53:20] Summarising fits
-#> INFO [2024-11-19 13:53:24] Adjusting by regression coefficients
-#> INFO [2024-11-19 13:53:26] Summarising into quantiles
+#> INFO [2024-12-02 14:42:55] Summarising fits
+#> INFO [2024-12-02 14:42:58] Adjusting by regression coefficients
+#> INFO [2024-12-02 14:43:01] Summarising into quantiles
head(res)
#> time_since_last_exp me lo hi titre_type infection_history
#> <int> <num> <num> <num> <char> <char>
@@ -193,11 +196,11 @@ Figure 4
res <- mod$population_stationary_points(n_draws = 2000)
-#> INFO [2024-11-19 13:53:27] Extracting parameters
-#> INFO [2024-11-19 13:53:27] Adjusting by covariates
-#> INFO [2024-11-19 13:53:27] Calculating peak and switch titre values
-#> INFO [2024-11-19 13:53:28] Recovering covariate names
-#> INFO [2024-11-19 13:53:28] Calculating medians
+#> INFO [2024-12-02 14:43:02] Extracting parameters
+#> INFO [2024-12-02 14:43:02] Adjusting by covariates
+#> INFO [2024-12-02 14:43:02] Calculating peak and switch titre values
+#> INFO [2024-12-02 14:43:02] Recovering covariate names
+#> INFO [2024-12-02 14:43:02] Calculating medians
head(res)
#> infection_history titre_type mu_p mu_s rel_drop_me mu_p_me mu_s_me
#> <char> <char> <num> <num> <num> <num> <num>
@@ -263,15 +266,15 @@ Figure 5
res <- mod$simulate_individual_trajectories(n_draws = 250)
-#> INFO [2024-11-19 13:53:29] Extracting parameters
-#> INFO [2024-11-19 13:53:32] Simulating individual trajectories
-#> INFO [2024-11-19 13:53:36] Recovering covariate names
-#> INFO [2024-11-19 13:53:37] Calculating exposure days. Adjusting exposures by 0 days
-#> INFO [2024-11-19 13:53:40] Resampling
+#> INFO [2024-12-02 14:43:03] Extracting parameters
+#> INFO [2024-12-02 14:43:07] Simulating individual trajectories
+#> INFO [2024-12-02 14:43:11] Recovering covariate names
+#> INFO [2024-12-02 14:43:11] Calculating exposure days. Adjusting exposures by 0 days
+#> INFO [2024-12-02 14:43:15] Resampling
#> Registered S3 method overwritten by 'mosaic':
#> method from
#> fortify.SpatialPolygonsDataFrame ggplot2
-#> INFO [2024-11-19 13:53:50] Summarising into population quantiles
+#> INFO [2024-12-02 14:43:25] Summarising into population quantiles
head(res)
#> calendar_day titre_type me lo hi time_shift
#> <IDat> <char> <num> <num> <num> <num>
@@ -350,72 +353,72 @@ Figure 5 shift <- time_shift_values[index]
mod$simulate_individual_trajectories(n_draws = 50, time_shift = shift)
})
-#> INFO [2024-11-19 13:53:51] Extracting parameters
-#> INFO [2024-11-19 13:53:55] Simulating individual trajectories
-#> INFO [2024-11-19 13:53:55] Recovering covariate names
-#> INFO [2024-11-19 13:53:55] Calculating exposure days. Adjusting exposures by -75 days
-#> INFO [2024-11-19 13:53:56] Resampling
-#> INFO [2024-11-19 13:53:58] Summarising into population quantiles
-#> INFO [2024-11-19 13:53:58] Extracting parameters
-#> INFO [2024-11-19 13:54:01] Simulating individual trajectories
-#> INFO [2024-11-19 13:54:02] Recovering covariate names
-#> INFO [2024-11-19 13:54:02] Calculating exposure days. Adjusting exposures by -60 days
-#> INFO [2024-11-19 13:54:03] Resampling
-#> INFO [2024-11-19 13:54:04] Summarising into population quantiles
-#> INFO [2024-11-19 13:54:05] Extracting parameters
-#> INFO [2024-11-19 13:54:08] Simulating individual trajectories
-#> INFO [2024-11-19 13:54:09] Recovering covariate names
-#> INFO [2024-11-19 13:54:09] Calculating exposure days. Adjusting exposures by -45 days
-#> INFO [2024-11-19 13:54:09] Resampling
-#> INFO [2024-11-19 13:54:11] Summarising into population quantiles
-#> INFO [2024-11-19 13:54:12] Extracting parameters
-#> INFO [2024-11-19 13:54:15] Simulating individual trajectories
-#> INFO [2024-11-19 13:54:16] Recovering covariate names
-#> INFO [2024-11-19 13:54:16] Calculating exposure days. Adjusting exposures by -30 days
-#> INFO [2024-11-19 13:54:17] Resampling
-#> INFO [2024-11-19 13:54:19] Summarising into population quantiles
-#> INFO [2024-11-19 13:54:19] Extracting parameters
-#> INFO [2024-11-19 13:54:22] Simulating individual trajectories
-#> INFO [2024-11-19 13:54:23] Recovering covariate names
-#> INFO [2024-11-19 13:54:23] Calculating exposure days. Adjusting exposures by -15 days
-#> INFO [2024-11-19 13:54:23] Resampling
-#> INFO [2024-11-19 13:54:25] Summarising into population quantiles
-#> INFO [2024-11-19 13:54:26] Extracting parameters
-#> INFO [2024-11-19 13:54:29] Simulating individual trajectories
-#> INFO [2024-11-19 13:54:30] Recovering covariate names
-#> INFO [2024-11-19 13:54:30] Calculating exposure days. Adjusting exposures by 0 days
-#> INFO [2024-11-19 13:54:30] Resampling
-#> INFO [2024-11-19 13:54:32] Summarising into population quantiles
-#> INFO [2024-11-19 13:54:33] Extracting parameters
-#> INFO [2024-11-19 13:54:36] Simulating individual trajectories
-#> INFO [2024-11-19 13:54:36] Recovering covariate names
-#> INFO [2024-11-19 13:54:36] Calculating exposure days. Adjusting exposures by 15 days
-#> INFO [2024-11-19 13:54:37] Resampling
-#> INFO [2024-11-19 13:54:39] Summarising into population quantiles
-#> INFO [2024-11-19 13:54:39] Extracting parameters
-#> INFO [2024-11-19 13:54:43] Simulating individual trajectories
-#> INFO [2024-11-19 13:54:43] Recovering covariate names
-#> INFO [2024-11-19 13:54:43] Calculating exposure days. Adjusting exposures by 30 days
-#> INFO [2024-11-19 13:54:44] Resampling
-#> INFO [2024-11-19 13:54:46] Summarising into population quantiles
-#> INFO [2024-11-19 13:54:46] Extracting parameters
-#> INFO [2024-11-19 13:54:49] Simulating individual trajectories
-#> INFO [2024-11-19 13:54:50] Recovering covariate names
-#> INFO [2024-11-19 13:54:50] Calculating exposure days. Adjusting exposures by 45 days
-#> INFO [2024-11-19 13:54:50] Resampling
-#> INFO [2024-11-19 13:54:52] Summarising into population quantiles
-#> INFO [2024-11-19 13:54:53] Extracting parameters
-#> INFO [2024-11-19 13:54:56] Simulating individual trajectories
-#> INFO [2024-11-19 13:54:57] Recovering covariate names
-#> INFO [2024-11-19 13:54:57] Calculating exposure days. Adjusting exposures by 60 days
-#> INFO [2024-11-19 13:54:57] Resampling
-#> INFO [2024-11-19 13:54:59] Summarising into population quantiles
-#> INFO [2024-11-19 13:55:00] Extracting parameters
-#> INFO [2024-11-19 13:55:03] Simulating individual trajectories
-#> INFO [2024-11-19 13:55:04] Recovering covariate names
-#> INFO [2024-11-19 13:55:04] Calculating exposure days. Adjusting exposures by 75 days
-#> INFO [2024-11-19 13:55:04] Resampling
-#> INFO [2024-11-19 13:55:06] Summarising into population quantiles
+#> INFO [2024-12-02 14:43:26] Extracting parameters
+#> INFO [2024-12-02 14:43:29] Simulating individual trajectories
+#> INFO [2024-12-02 14:43:30] Recovering covariate names
+#> INFO [2024-12-02 14:43:30] Calculating exposure days. Adjusting exposures by -75 days
+#> INFO [2024-12-02 14:43:31] Resampling
+#> INFO [2024-12-02 14:43:33] Summarising into population quantiles
+#> INFO [2024-12-02 14:43:33] Extracting parameters
+#> INFO [2024-12-02 14:43:36] Simulating individual trajectories
+#> INFO [2024-12-02 14:43:37] Recovering covariate names
+#> INFO [2024-12-02 14:43:37] Calculating exposure days. Adjusting exposures by -60 days
+#> INFO [2024-12-02 14:43:38] Resampling
+#> INFO [2024-12-02 14:43:39] Summarising into population quantiles
+#> INFO [2024-12-02 14:43:40] Extracting parameters
+#> INFO [2024-12-02 14:43:43] Simulating individual trajectories
+#> INFO [2024-12-02 14:43:44] Recovering covariate names
+#> INFO [2024-12-02 14:43:44] Calculating exposure days. Adjusting exposures by -45 days
+#> INFO [2024-12-02 14:43:44] Resampling
+#> INFO [2024-12-02 14:43:46] Summarising into population quantiles
+#> INFO [2024-12-02 14:43:47] Extracting parameters
+#> INFO [2024-12-02 14:43:50] Simulating individual trajectories
+#> INFO [2024-12-02 14:43:51] Recovering covariate names
+#> INFO [2024-12-02 14:43:51] Calculating exposure days. Adjusting exposures by -30 days
+#> INFO [2024-12-02 14:43:51] Resampling
+#> INFO [2024-12-02 14:43:53] Summarising into population quantiles
+#> INFO [2024-12-02 14:43:54] Extracting parameters
+#> INFO [2024-12-02 14:43:57] Simulating individual trajectories
+#> INFO [2024-12-02 14:43:58] Recovering covariate names
+#> INFO [2024-12-02 14:43:58] Calculating exposure days. Adjusting exposures by -15 days
+#> INFO [2024-12-02 14:43:58] Resampling
+#> INFO [2024-12-02 14:44:00] Summarising into population quantiles
+#> INFO [2024-12-02 14:44:00] Extracting parameters
+#> INFO [2024-12-02 14:44:04] Simulating individual trajectories
+#> INFO [2024-12-02 14:44:04] Recovering covariate names
+#> INFO [2024-12-02 14:44:04] Calculating exposure days. Adjusting exposures by 0 days
+#> INFO [2024-12-02 14:44:05] Resampling
+#> INFO [2024-12-02 14:44:06] Summarising into population quantiles
+#> INFO [2024-12-02 14:44:07] Extracting parameters
+#> INFO [2024-12-02 14:44:10] Simulating individual trajectories
+#> INFO [2024-12-02 14:44:11] Recovering covariate names
+#> INFO [2024-12-02 14:44:11] Calculating exposure days. Adjusting exposures by 15 days
+#> INFO [2024-12-02 14:44:11] Resampling
+#> INFO [2024-12-02 14:44:13] Summarising into population quantiles
+#> INFO [2024-12-02 14:44:14] Extracting parameters
+#> INFO [2024-12-02 14:44:17] Simulating individual trajectories
+#> INFO [2024-12-02 14:44:18] Recovering covariate names
+#> INFO [2024-12-02 14:44:18] Calculating exposure days. Adjusting exposures by 30 days
+#> INFO [2024-12-02 14:44:18] Resampling
+#> INFO [2024-12-02 14:44:20] Summarising into population quantiles
+#> INFO [2024-12-02 14:44:21] Extracting parameters
+#> INFO [2024-12-02 14:44:24] Simulating individual trajectories
+#> INFO [2024-12-02 14:44:25] Recovering covariate names
+#> INFO [2024-12-02 14:44:25] Calculating exposure days. Adjusting exposures by 45 days
+#> INFO [2024-12-02 14:44:25] Resampling
+#> INFO [2024-12-02 14:44:27] Summarising into population quantiles
+#> INFO [2024-12-02 14:44:27] Extracting parameters
+#> INFO [2024-12-02 14:44:31] Simulating individual trajectories
+#> INFO [2024-12-02 14:44:31] Recovering covariate names
+#> INFO [2024-12-02 14:44:31] Calculating exposure days. Adjusting exposures by 60 days
+#> INFO [2024-12-02 14:44:32] Resampling
+#> INFO [2024-12-02 14:44:34] Summarising into population quantiles
+#> INFO [2024-12-02 14:44:34] Extracting parameters
+#> INFO [2024-12-02 14:44:37] Simulating individual trajectories
+#> INFO [2024-12-02 14:44:38] Recovering covariate names
+#> INFO [2024-12-02 14:44:38] Calculating exposure days. Adjusting exposures by 75 days
+#> INFO [2024-12-02 14:44:38] Resampling
+#> INFO [2024-12-02 14:44:40] Summarising into population quantiles
combined_data <- data.table::data.table(data.table::rbindlist(results_list))
Plotting the median values:
diff --git a/articles/data.html b/articles/data.html
index cf9e58e..bb1aa52 100644
--- a/articles/data.html
+++ b/articles/data.html
@@ -54,6 +54,9 @@
A guide to biokinetics input and output data
+
+ Model diagnostics and plotting
+
Summary of the Stan Model
diff --git a/articles/diagnostics.html b/articles/diagnostics.html
new file mode 100644
index 0000000..65d32ef
--- /dev/null
+++ b/articles/diagnostics.html
@@ -0,0 +1,180 @@
+
+
+
+
+
+
+
+Model diagnostics and plotting • epikinetics
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ Model diagnostics and plotting
+
+
+
+ diagnostics.Rmd
+
+
+
+
+
+
+Plotting model inputs
+
+
+Priors
+
+Calling plot on an object of type biokinetics_priors will
+generate a plot of the kinetics predicted by the given priors.
+
+priors <- epikinetics::biokinetics_priors()
+plot(priors)
+
+You can optionally pass a dataset to compare against the predicted
+kinetics. Required columns are time_since_last_exp and
+value and values should be on the scale required by the
+model.
+
+data <- data.table::fread(system.file("delta_full.rds", package = "epikinetics"))
+data[, time_since_last_exp := as.integer(day - last_exp_day, units = "days")]
+data <- epikinetics::convert_log2_scale(data, min(data$value))
+priors <- epikinetics::biokinetics_priors()
+plot(priors, data = data)
+
+If you have an instance of the biokinetics class, the method
+plot_prior_predictive generates this plot for the priors
+and data given to the model.
+
+data <- data.table::fread(system.file("delta_full.rds", package = "epikinetics"))
+priors <- epikinetics::biokinetics_priors()
+mod <- epikinetics::biokinetics$new(priors = priors, data = data)
+#> INFO [2024-12-02 14:44:51] Preparing data for stan
+#> INFO [2024-12-02 14:44:51] Retrieving compiled model
+#> CmdStan path set to: /home/runner/.cmdstan/cmdstan-2.35.0
+mod$plot_prior_predictive()
+
+
+
+Data
+
+If you have an instance of the biokinetics class, the method
+plot_model_inputs plots the input data used to fit the
+model, disaggregated by the covariates in the covariate formula.
+
+mod <- epikinetics::biokinetics$new(priors = priors, data = data, covariate_formula = ~0 + infection_history)
+#> INFO [2024-12-02 14:44:53] Preparing data for stan
+#> INFO [2024-12-02 14:44:53] Retrieving compiled model
+mod$plot_model_inputs()
+#> `geom_smooth()` using method = 'loess' and formula = 'y ~ x'
+
+
+
+
+Interactive data exploration
+
+To play around with different priors and visualise input data
+filtered and disaggregated in different ways, the function biokinetics$inspect
+runs a local RShiny app with interactive plots.
+
+RShiny demonstration
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
diff --git a/articles/diagnostics_files/figure-html/unnamed-chunk-2-1.png b/articles/diagnostics_files/figure-html/unnamed-chunk-2-1.png
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new file mode 100644
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diff --git a/articles/diagnostics_files/figure-html/unnamed-chunk-5-1.png b/articles/diagnostics_files/figure-html/unnamed-chunk-5-1.png
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diff --git a/articles/index.html b/articles/index.html
index 742ea2a..6ff4686 100644
--- a/articles/index.html
+++ b/articles/index.html
@@ -37,6 +37,9 @@
A guide to biokinetics input and output data
+
+ Model diagnostics and plotting
+
Summary of the Stan Model
@@ -61,6 +64,8 @@ All vignettes
A guide to biokinetics input and output data
+ Model diagnostics and plotting
+
Summary of the Stan Model
diff --git a/articles/model.html b/articles/model.html
index f602b95..25905b4 100644
--- a/articles/model.html
+++ b/articles/model.html
@@ -54,6 +54,9 @@
A guide to biokinetics input and output data
+
+ Model diagnostics and plotting
+
Summary of the Stan Model
diff --git a/articles/shiny.webm b/articles/shiny.webm
new file mode 100644
index 0000000..75e2122
Binary files /dev/null and b/articles/shiny.webm differ
diff --git a/authors.html b/authors.html
index 63b9899..99e8d35 100644
--- a/authors.html
+++ b/authors.html
@@ -37,6 +37,9 @@
A guide to biokinetics input and output data
+
+ Model diagnostics and plotting
+
Summary of the Stan Model
diff --git a/index.html b/index.html
index 178afed..a6f3c35 100644
--- a/index.html
+++ b/index.html
@@ -55,6 +55,9 @@
A guide to biokinetics input and output data
+
+ Model diagnostics and plotting
+
Summary of the Stan Model
@@ -118,6 +121,8 @@ Testing
To run all tests locally:
{r} devtools::test()
+To run tests in a single file:
+{r} devtools::test(filter="filename")
Some tests are skipped on CI to avoid exorbitantly long build times, but this means it is important to run all tests locally at least once before merging a pull request.
For snapshot testing of stan model outputs, we need the outputs to be exactly reproducible. As well as setting a seed, this requires the machine environment to be exactly the same, so on CI we run these inside a Docker container, via a bash script:
{shell} ./tests/snapshots/test-snapshots
diff --git a/pkgdown.yml b/pkgdown.yml
index 42078ed..e18d1f1 100644
--- a/pkgdown.yml
+++ b/pkgdown.yml
@@ -4,5 +4,6 @@ pkgdown_sha: ~
articles:
biokinetics: biokinetics.html
data: data.html
+ diagnostics: diagnostics.html
model: model.html
-last_built: 2024-11-19T13:48Z
+last_built: 2024-12-02T14:38Z
diff --git a/reference/add_exposure_data.html b/reference/add_exposure_data.html
index 74be5e9..a1b9d30 100644
--- a/reference/add_exposure_data.html
+++ b/reference/add_exposure_data.html
@@ -39,6 +39,9 @@
A guide to biokinetics input and output data
+
+ Model diagnostics and plotting
+
Summary of the Stan Model
diff --git a/reference/biokinetics.html b/reference/biokinetics.html
index ef689b7..887006e 100644
--- a/reference/biokinetics.html
+++ b/reference/biokinetics.html
@@ -38,6 +38,9 @@
A guide to biokinetics input and output data
+
+ Model diagnostics and plotting
+
Summary of the Stan Model
@@ -71,6 +74,7 @@ Public methodsMethod plot_model_inputs()
Usage
-biokinetics$plot_model_inputs(tmax = 150)
+biokinetics$plot_model_inputs(tmax = 150, ncol = NULL)
@@ -194,6 +198,10 @@ Arguments
@@ -201,10 +209,18 @@ Returns
Method get_stan_data()
View the data that is passed to the stan model, for debugging purposes.
@@ -216,7 +232,7 @@ Returns
Method get_covariate_lookup_table()
View the mapping of human readable covariate names to the model variable p.
@@ -228,7 +244,7 @@ Returns
Method fit()
Fit the model and return CmdStanMCMC fitted model object.
@@ -249,7 +265,7 @@ Returns
Method extract_population_parameters()
Extract fitted population parameters
-Usage
+Usage
biokinetics$extract_population_parameters(
n_draws = 2000,
human_readable_covariates = TRUE
@@ -276,7 +292,7 @@ Returns
Method extract_individual_parameters()
Extract fitted individual parameters
-Usage
+Usage
biokinetics$extract_individual_parameters(
n_draws = 2000,
include_variation_params = TRUE,
@@ -308,7 +324,7 @@ Returns
Method simulate_population_trajectories()
Process the model results into a data table of titre values over time.
-Usage
+Usage
biokinetics$simulate_population_trajectories(
t_max = 150,
summarise = TRUE,
@@ -346,7 +362,7 @@ Returns
Method population_stationary_points()
Process the stan model results into a data.table.
@@ -369,7 +385,7 @@ ReturnsMethod simulate_individual_trajectories()
Simulate individual trajectories from the model. This is
computationally expensive and may take a while to run if n_draws is large.
-Usage
+Usage
biokinetics$simulate_individual_trajectories(
summarise = TRUE,
n_draws = 2000,
diff --git a/reference/biokinetics_priors.html b/reference/biokinetics_priors.html
index 2dc9880..d5f4755 100644
--- a/reference/biokinetics_priors.html
+++ b/reference/biokinetics_priors.html
@@ -40,6 +40,9 @@
A guide to biokinetics input and output data
+
+ Model diagnostics and plotting
+
Summary of the Stan Model
diff --git a/reference/convert_log2_scale.html b/reference/convert_log2_scale.html
index c1277df..51fe409 100644
--- a/reference/convert_log2_scale.html
+++ b/reference/convert_log2_scale.html
@@ -38,6 +38,9 @@
A guide to biokinetics input and output data
+
+ Model diagnostics and plotting
+
Summary of the Stan Model
diff --git a/reference/convert_log2_scale_inverse.html b/reference/convert_log2_scale_inverse.html
index a7c870c..4df7e6c 100644
--- a/reference/convert_log2_scale_inverse.html
+++ b/reference/convert_log2_scale_inverse.html
@@ -39,6 +39,9 @@
A guide to biokinetics input and output data
+
+ Model diagnostics and plotting
+
Summary of the Stan Model
diff --git a/reference/epikinetics-package.html b/reference/epikinetics-package.html
index ba85cce..9819344 100644
--- a/reference/epikinetics-package.html
+++ b/reference/epikinetics-package.html
@@ -37,6 +37,9 @@
A guide to biokinetics input and output data
+
+ Model diagnostics and plotting
+
Summary of the Stan Model
diff --git a/reference/index.html b/reference/index.html
index 22d57aa..94e0765 100644
--- a/reference/index.html
+++ b/reference/index.html
@@ -37,6 +37,9 @@
A guide to biokinetics input and output data
+
+ Model diagnostics and plotting
+
Summary of the Stan Model
diff --git a/reference/plot.biokinetics_population_trajectories.html b/reference/plot.biokinetics_population_trajectories.html
index 0eecbbb..19e3442 100644
--- a/reference/plot.biokinetics_population_trajectories.html
+++ b/reference/plot.biokinetics_population_trajectories.html
@@ -37,6 +37,9 @@
A guide to biokinetics input and output data
+
+ Model diagnostics and plotting
+
Summary of the Stan Model
diff --git a/reference/plot.biokinetics_priors.html b/reference/plot.biokinetics_priors.html
index 147e0e9..e9bcc0e 100644
--- a/reference/plot.biokinetics_priors.html
+++ b/reference/plot.biokinetics_priors.html
@@ -38,6 +38,9 @@
A guide to biokinetics input and output data
+
+ Model diagnostics and plotting
+
Summary of the Stan Model
diff --git a/reference/plot_sero_data.html b/reference/plot_sero_data.html
index fa47ef8..2c0d3a9 100644
--- a/reference/plot_sero_data.html
+++ b/reference/plot_sero_data.html
@@ -38,6 +38,9 @@
A guide to biokinetics input and output data
+
+ Model diagnostics and plotting
+
Summary of the Stan Model
@@ -65,6 +68,7 @@ Plot serological data
plot_sero_data(
data,
tmax = 150,
+ ncol = NULL,
covariates = character(0),
upper_censoring_limit = NULL,
lower_censoring_limit = NULL
@@ -83,6 +87,10 @@ Arguments
Integer. The number of time points in each simulated trajectory. Default 150.
ncol
+Integer. Optional number of columns to display facets in.
covariates
Optional vector of covariate names to facet by (these must correspond to columns in the data.table)
/LICENSE.html /articles/biokinetics.html /articles/data.html /articles/diagnostics.html /articles/index.html /articles/model.html /authors.html