resolve Bioconductor/Contributions#3315 (comment)

DESCRIPTION

@@ -15,15 +15,17 @@ Description: Genetic algorithm are a class of optimization algorithms
 License: MIT + file LICENSE
 URL: https://danymukesha.github.io/BioGA/
 BugReports: https://github.com/danymukesha/BioGA/issues
-Depends:
+Imports:
     ggplot2,
     graphics,
     Rcpp,
-    sessioninfo,
     SummarizedExperiment,
     animation,
     rlang,
-    biocViews 
+    biocViews,
+    sessioninfo 
+Depends: 
+    R (>= 4.3.3)
 Suggests: 
     knitr,
     rmarkdown,

NAMESPACE

@@ -1,21 +1,24 @@
-# Generated by roxygen2: do not edit by hand
-
-export(crossover_cpp)
-export(evaluate_fitness_cpp)
-export(initialize_population_cpp)
-export(mutation_cpp)
-export(plot_fitness)
-export(plot_fitness_history)
-export(plot_population)
-export(replacement_cpp)
-export(selection_cpp)
-import(SummarizedExperiment)
-import(animation)
-import(biocViews)
-import(ggplot2)
-import(graphics)
-import(rlang)
-import(sessioninfo)
-importFrom(Rcpp,evalCpp)
-importFrom(Rcpp,sourceCpp)
-useDynLib(BioGA, .registration = TRUE)
+# Generated by roxygen2: do not edit by hand
+
+export(crossover_cpp)
+export(evaluate_fitness_cpp)
+export(initialize_population_cpp)
+export(mutation_cpp)
+export(plot_fitness)
+export(plot_fitness_history)
+export(plot_population)
+export(replacement_cpp)
+export(selection_cpp)
+importFrom(Rcpp,evalCpp)
+importFrom(Rcpp,sourceCpp)
+importFrom(SummarizedExperiment,SummarizedExperiment)
+importFrom(animation,saveGIF)
+importFrom(biocViews,getBiocViews)
+importFrom(ggplot2,ggplot)
+importFrom(ggplot2,ggtitle)
+importFrom(graphics,boxplot)
+importFrom(graphics,hist)
+importFrom(graphics,par)
+importFrom(rlang,local_options)
+importFrom(sessioninfo,session_info)
+useDynLib(BioGA, .registration = TRUE)

R/BioGA-package.R

@@ -2,14 +2,14 @@
 "_PACKAGE"
 
 ## usethis namespace: start
-#' @import biocViews
-#' @import ggplot2
-#' @import sessioninfo
-#' @import SummarizedExperiment
+#' @importFrom biocViews getBiocViews
+#' @importFrom ggplot2 ggtitle ggplot
+#' @importFrom sessioninfo session_info
+#' @importFrom SummarizedExperiment SummarizedExperiment
 #' @importFrom Rcpp evalCpp sourceCpp
-#' @import graphics
-#' @import animation
-#' @import rlang
+#' @importFrom graphics boxplot hist par
+#' @importFrom animation saveGIF
+#' @importFrom rlang local_options
 #' @useDynLib BioGA, .registration = TRUE
 ## usethis namespace: end
 NULL

R/Plottings.R

@@ -74,7 +74,6 @@ plot_fitness <- function(fitness_values) {
 #'
 #' @return Plot of population
 #'
-#' @import graphics
 #'
 #' @examples
 #' # example of usage

src/crossover.cpp

@@ -27,8 +27,8 @@ NumericMatrix crossover_cpp(const NumericMatrix& selected_parents, int offspring
 
   // Perform crossover between selected parents
   for (int i = 0; i < offspring_size; ++i) {
-    int parent1_index = rand() % num_parents;
-    int parent2_index = rand() % num_parents;
+    int parent1_index = R::unif_rand() / num_parents;
+    int parent2_index = R::unif_rand() / num_parents;
     for (int j = 0; j < num_genes; ++j) {
       offspring(i, j) = (selected_parents(parent1_index, j) + selected_parents(parent2_index, j)) / 2.0;
     }

src/replacement.cpp

@@ -31,7 +31,7 @@ NumericMatrix replacement_cpp(const NumericMatrix& population, const NumericMatr
 
   // Replace non-selected individuals in the population with offspring
   for (int i = 0; i < num_to_replace; ++i) {
-    int index_to_replace = rand() % population_size;
+    int index_to_replace = R::unif_rand() / population_size;
     for (int j = 0; j < num_genes; ++j) {
       updated_population(index_to_replace, j) = offspring(i, j);
     }

tests/testthat/test_crossover_cpp.R

@@ -0,0 +1,21 @@
+test_that("crossover_cpp not produce error or warning", {
+  # Load The PACKAGE
+  library(BioGA)
+
+  # example of usage
+  genomic_data <- matrix(rnorm(100), nrow = 10, ncol = 10)
+  population <- BioGA::initialize_population_cpp(genomic_data,
+                                                 population_size = 5)
+  fitness <- BioGA::evaluate_fitness_cpp(genomic_data, population)
+  selected_parents <- BioGA::selection_cpp(population, fitness,
+                                           num_parents = 2)
+  BioGA::crossover_cpp(selected_parents, offspring_size = 2)
+
+  testthat::expect_no_warning(BioGA::crossover_cpp(selected_parents, 
+                                                   offspring_size = 2),
+                              message = "bananas")
+
+  testthat::expect_no_error(BioGA::crossover_cpp(selected_parents, 
+                                                   offspring_size = 2),
+                              message = "bananas")
+})

tests/testthat/test_evaluate_fitness_cpp.R

@@ -0,0 +1,19 @@
+test_that("evalutate_cpp not produce error or warning", {
+  # example of usage
+  genomic_data <- matrix(rnorm(100), nrow = 10, ncol = 10)
+  population <- BioGA::initialize_population_cpp(genomic_data,
+                                                 population_size = 5)
+
+  output <- tryCatch(
+    BioGA::evaluate_fitness_cpp(genomic_data, population), 
+    error = function(e) return(NA)
+  )
+
+  testthat::expect_no_warning(BioGA::evaluate_fitness_cpp(genomic_data, 
+                                                          population),
+                              message = "bananas")
+  testthat::expect_no_error(BioGA::evaluate_fitness_cpp(genomic_data, 
+                                                          population),
+                              message = "bananas")
+})
+

tests/testthat/test_initialization_population_cpp.R

@@ -1,4 +1,5 @@
-test_that("initialize_population_cpp returns a matrix with correct dimensions", {
+test_that("initialize_population_cpp returns a matrix 
+          with correct dimensions", {
     # Load The PACKAGE
     library(BioGA)
 
@@ -14,7 +15,8 @@ test_that("initialize_population_cpp returns a matrix with correct dimensions",
     expect_equal(ncol(population), nrow(genomic_data))
 })
 
-test_that("initialize_population_cpp returns a matrix with values from genomic data", {
+test_that("initialize_population_cpp returns a matrix 
+          with values from genomic data", {
     # Load THE PACKAGE
     library(BioGA)
 

tests/testthat/test_mutation_cpp.R

@@ -0,0 +1,19 @@
+test_that("mutation_cpp not produce error or warning", {
+  # example of usage
+  genomic_data <- matrix(rnorm(100), nrow = 10, ncol = 10)
+  population <- BioGA::initialize_population_cpp(genomic_data,
+                                                 population_size = 5)
+  fitness <- BioGA::evaluate_fitness_cpp(genomic_data, population)
+  selected_parents <- BioGA::selection_cpp(population,
+                                           fitness, num_parents = 2)
+  offspring <- BioGA::crossover_cpp(selected_parents, offspring_size = 2)
+  BioGA::mutation_cpp(offspring, mutation_rate = 0)
+
+  testthat::expect_no_warning(BioGA::mutation_cpp(offspring, 
+                                                  mutation_rate = 0),
+                              message = "bananas")
+
+  testthat::expect_no_error(BioGA::mutation_cpp(offspring, 
+                                                mutation_rate = 0),
+                            message = "bananas")
+})

tests/testthat/test_plot_population_cpp.R

@@ -0,0 +1,11 @@
+test_that("crossover_cpp not produce error or warning", {
+  # Load The PACKAGE
+  library(BioGA)
+
+  # example of usage
+  population <- matrix(runif(100), nrow = 10, ncol = 10)
+  BioGA::plot_population(population)
+
+  testthat::expect_no_warning(BioGA::plot_population(population),
+                              message = "bananas")
+})

tests/testthat/test_selection_cpp.R

@@ -0,0 +1,38 @@
+test_that("selection_cpp returns a matrix with correct dimensions", {
+  # Load The PACKAGE
+  library(BioGA)
+
+  # example of usage
+  genomic_data <- matrix(rnorm(100), nrow = 10, ncol = 10)
+  population <- BioGA::initialize_population_cpp(genomic_data,
+                                                 population_size = 5)
+  fitness <- BioGA::evaluate_fitness_cpp(genomic_data, population)
+  selected_population <- BioGA::selection_cpp(population, fitness, 
+                                              num_parents = 2)
+
+  # Check dimensions
+  expect_equal(2, nrow(selected_population))
+
+})
+
+
+test_that("selection_cpp returns a matrix with correct dimensions", {
+  # Load The PACKAGE
+  library(BioGA)
+
+  # example of usage
+  genomic_data <- matrix(rnorm(100), nrow = 10, ncol = 10)
+  population <- BioGA::initialize_population_cpp(genomic_data,
+                                                 population_size = 5)
+  fitness <- BioGA::evaluate_fitness_cpp(genomic_data, population)
+  selected_population <- BioGA::selection_cpp(population, fitness, 
+                                              num_parents = 2)
+
+  testthat::expect_no_warning(BioGA::evaluate_fitness_cpp(genomic_data, 
+                                                          population),
+                              message = "bananas")
+  testthat::expect_no_error(BioGA::evaluate_fitness_cpp(genomic_data, 
+                                                        population),
+                            message = "bananas")
+
+})