Merge pull request #56 from spsanderson/development

Development

R/gen-brown-motion-geometric.R

@@ -98,6 +98,22 @@ geometric_brownian_motion <- function(.num_walks = 25, .n = 100,
     )
   }
 
+  # .mu and .sigma and .detla_time must be >= 0
+  if (mu < 0 | sigma < 0 | delta_time < 0){
+    rlang::abort(
+      message = "The parameters of `.mu`, `.sigma`, and `.delta_time` must be >= 0.",
+      use_cli_format = TRUE
+    )
+  }
+
+  # .num_walks and .n must be >= 1
+  if (num_sims < 1 | t < 1){
+    rlang::abort(
+      message = "The parameters of `.num_walks` and `.n` must be >= 1.",
+      use_cli_format = TRUE
+    )
+  }
+
   # matrix of random draws - one for each day for each simulation
   rand_matrix <- matrix(stats::rnorm(t * num_sims), ncol = num_sims, nrow = t)
   colnames(rand_matrix) <- 1:num_sims

R/gen-brown-motion.R

@@ -55,7 +55,7 @@ NULL
 #' @rdname brownian_motion
 
 brownian_motion <- function(.num_walks = 25, .n = 100, .delta_time = 1,
-                               .initial_value = 0, .return_tibble = TRUE) {
+                            .initial_value = 0, .return_tibble = TRUE) {
 
   # Tidyeval ----
   num_sims <- as.numeric(.num_walks)
@@ -73,6 +73,22 @@ brownian_motion <- function(.num_walks = 25, .n = 100, .delta_time = 1,
     )
   }
 
+  # .num_walks and .n must be >= 1
+  if (num_sims < 1 | t < 1){
+    rlang::abort(
+      message = "The parameters of `.num_walks` and `.n` must be >= 1.",
+      use_cli_format = TRUE
+    )
+  }
+
+  # .delta_time must be > 0
+  if (delta_time <= 0){
+    rlang::abort(
+      message = "The parameter `.delta_time` must be > 0.",
+      use_cli_format = TRUE
+    )
+  }
+
   if (!is.logical(return_tibble)){
     rlang::abort(
       message = "The parameter `.return_tibble` must be either TRUE/FALSE",

R/gen-discrete-walk.R

@@ -62,6 +62,49 @@ discrete_walk <- function(.num_walks = 25, .n = 100, .upper_bound = 1,
   lower_probability <- 1 - upper_probability
   initial_value <- as.numeric(.initial_value)
 
+  # Checks
+  if (!is.integer(num_walks) | num_walks < 1) {
+    rlang::abort(
+      message = "The number of walks must be an integer greater than 0.",
+      use_cli_format = TRUE
+    )
+  }
+
+  if (!is.integer(periods) | periods < 1) {
+    rlang::abort(
+      message = "The number of periods must be an integer greater than 0.",
+      use_cli_format = TRUE
+    )
+  }
+
+  if (!is.numeric(upper_bound)) {
+    rlang::abort(
+      message = "The upper bound must be a numeric value.",
+      use_cli_format = TRUE
+      )
+  }
+
+  if (!is.numeric(lower_bound)) {
+    rlang::abort(
+      message = "The lower bound must be a numeric value.",
+      use_cli_format = TRUE
+      )
+  }
+
+  if (!is.numeric(upper_probability) | upper_probability < 0 | upper_probability > 1) {
+    rlang::abort(
+      message = "The upper probability must be a numeric value between 0 and 1.",
+      use_cli_format = TRUE
+      )
+  }
+
+  if (!is.numeric(initial_value)) {
+    rlang::abort(
+      message = "The initial value must be a numeric value.",
+      use_cli_format = TRUE
+      )
+  }
+
   res <- tidyr::expand_grid(walk_number = factor(1:num_walks), x = 1:periods) |>
     dplyr::group_by(walk_number) |>
     dplyr::mutate(y = replicate(

R/gen-random-normal-walk-drift.R

@@ -47,6 +47,7 @@ NULL
 random_normal_drift_walk <- function(.num_walks = 25, .n = 100, .mu = 0,
                                      .sd = 1, .drift = 0.1, .initial_value = 0) {
 
+  # Convert inputs to appropriate types
   num_walks <- as.integer(.num_walks)
   num_steps <- as.integer(.n)
   mu <- as.numeric(.mu)
@@ -55,6 +56,49 @@ random_normal_drift_walk <- function(.num_walks = 25, .n = 100, .mu = 0,
   initial_value <- as.numeric(.initial_value)
   dr <- seq(from = drift, to = drift * num_steps, length.out = num_steps)
 
+  # Checks
+  if (num_walks <= 0) {
+    rlang::abort(
+      message = "Number of walks must be a positive integer.",
+      use_cli = TRUE
+      )
+  }
+
+  if (num_steps <= 0) {
+    rlang::abort(
+      message = "Number of steps must be a positive integer.",
+      use_cli = TRUE
+      )
+  }
+
+  if (sd <= 0) {
+    rlang::abort(
+      message = "Standard deviation must be a positive number.",
+      use_cli = TRUE
+      )
+  }
+
+  if (is.na(mu)) {
+    rlang::abort(
+      message = "Mean must be a number.",
+      use_cli = TRUE
+      )
+  }
+
+  if (is.na(drift)) {
+    rlang::abort(
+      message = "Drift must be a number.",
+      use_cli = TRUE
+      )
+  }
+
+  if (is.na(initial_value)) {
+    rlang::abort(
+      message = "Initial value must be a number.",
+      use_cli = TRUE
+      )
+  }
+
   # Function to generate a single random walk
   single_random_walk_with_drift <- function(num_steps, mu, sd, drift) {
     wn <- stats::rnorm(n = num_steps, mean = mu, sd = sd)