Merge branch 'devel'

DESCRIPTION

@@ -1,40 +1,40 @@
-Type: Package
-Package: BioGA
-Title: Bioinformatics Genetic Algorithm (BioGA)
-Version: 0.99.0
-Authors@R: 
-    person("Dany", "Mukesha", , "danymukesha@gmail.com", 
-            role = c("aut", "cre"),
-           comment = c(ORCID = "0009-0001-9514-751X"))
-Description: Genetic algorithm are a class of optimization algorithms
-    inspired by the process of natural selection and genetics. This
-    package allows users to analyze and optimize high throughput genomic
-    data using genetic algorithms.  The functions provided are implemented
-    in C++ for improved speed and efficiency, with an easy-to-use
-    interface for use within R.
-License: MIT + file LICENSE
-URL: https://danymukesha.github.io/BioGA/
-BugReports: https://github.com/danymukesha/BioGA/issues
-Imports:
-    ggplot2,
-    graphics,
-    Rcpp,
-    sessioninfo,
-    SummarizedExperiment,
-    animation,
-    rlang,
-    biocViews 
-Suggests: 
-    knitr,
-    rmarkdown,
-    testthat (>= 3.0.0)
-LinkingTo: 
-    Rcpp
-VignetteBuilder: 
-    knitr
-biocViews: ExperimentalDesign, Technology
-Encoding: UTF-8
-LazyData: false
-Roxygen: list(markdown = TRUE)
-RoxygenNote: 7.3.1
-Config/testthat/edition: 3
+Type: Package
+Package: BioGA
+Title: Bioinformatics Genetic Algorithm (BioGA)
+Version: 0.99.2
+Authors@R: 
+    person("Dany", "Mukesha", , "danymukesha@gmail.com", 
+            role = c("aut", "cre"),
+           comment = c(ORCID = "0009-0001-9514-751X"))
+Description: Genetic algorithm are a class of optimization algorithms
+    inspired by the process of natural selection and genetics. This
+    package allows users to analyze and optimize high throughput genomic
+    data using genetic algorithms.  The functions provided are implemented
+    in C++ for improved speed and efficiency, with an easy-to-use
+    interface for use within R.
+License: MIT + file LICENSE
+URL: https://danymukesha.github.io/BioGA/
+BugReports: https://github.com/danymukesha/BioGA/issues
+Imports:
+    ggplot2,
+    graphics,
+    Rcpp,
+    sessioninfo,
+    SummarizedExperiment,
+    animation,
+    rlang,
+    biocViews 
+Suggests: 
+    knitr,
+    rmarkdown,
+    testthat (>= 3.0.0)
+LinkingTo: 
+    Rcpp
+VignetteBuilder: 
+    knitr
+biocViews: ExperimentalDesign, Technology
+Encoding: UTF-8
+LazyData: false
+Roxygen: list(markdown = TRUE)
+RoxygenNote: 7.3.1
+Config/testthat/edition: 3

NAMESPACE

@@ -1,6 +1,5 @@
 # Generated by roxygen2: do not edit by hand
 
-export(animate_fitness_history)
 export(crossover_cpp)
 export(evaluate_fitness_cpp)
 export(initialize_population_cpp)

NEWS.md

@@ -1,3 +1,7 @@
-# BioGA 0.99.0
-
-* Added a `NEWS.md` file to track changes to the package.
+# BioGA 0.99.2
+
+# BioGA 0.99.1
+
+# BioGA 0.99.0
+
+* Added a `NEWS.md` file to track changes to the package.

R/Plottings.R

@@ -0,0 +1,89 @@
+#' Plot Fitness Change Over Generations
+#'
+#' Plot the change in fitness values over generations.
+#'
+#' @param fitness_history A list containing fitness values for
+#' each generation.
+#'
+#' @return Plot of fitness history
+#'
+#' @examples
+#' # example of usage
+#' fitness_history <- list(c(10, 8, 6, 4, 2), c(9, 7, 5, 3, 1))
+#' plot_fitness_history(fitness_history)
+#'
+#' @export
+plot_fitness_history <- function(fitness_history) {
+  # Extract fitness values
+  fitness_values <- unlist(fitness_history)
+
+  # Create generation index
+  generations <-
+    rep(
+      seq_along(fitness_history),
+      vapply(fitness_history, length, integer(1))
+    )
+
+  # Create data frame
+  df <- data.frame(
+    Generation = generations,
+    Fitness = fitness_values
+  )
+
+  # Plot
+  ggplot2::ggplot(df, ggplot2::aes_string(
+    x = "Generation",
+    y = "Fitness"
+  )) +
+    geom_line() +
+    labs(x = "Generation", y = "Fitness") +
+    ggplot2::ggtitle("Fitness Change Over Generations")
+}
+
+
+
+#' Plot Fitness Values
+#'
+#' Plot the fitness values of the population over generations.
+#'
+#' @param fitness_values A numeric vector containing fitness values.
+#'
+#' @return Plot of fitness
+#'
+#' @examples
+#' # example of usage
+#' fitness_values <- c(10, 8, 6, 4, 2)
+#' plot_fitness(fitness_values)
+#'
+#' @export
+plot_fitness <- function(fitness_values) {
+  generations <- seq_along(fitness_values)
+  plot(generations, fitness_values,
+       type = "l",
+       xlab = "Generations", ylab = "Fitness",
+       main = "Fitness Values Over Generations"
+  )
+}
+
+
+#' Plot Population Distribution
+#'
+#' Plot the distribution of individuals in the population.
+#'
+#' @param population A numeric matrix containing the population data.
+#'
+#' @return Plot of population
+#'
+#' @import graphics
+#'
+#' @examples
+#' # example of usage
+#' population <- matrix(runif(100), nrow = 10, ncol = 10)
+#' plot_population(population)
+#'
+#' @export
+plot_population <- function(population) {
+  par(mfrow = c(1, 2))
+  boxplot(population, main = "Boxplot of Population")
+  hist(population, main = "Histogram of Population")
+}