Merge pull request #341 from spsanderson/development

Fix #340

DESCRIPTION

@@ -16,7 +16,7 @@ License: MIT + file LICENSE
 Encoding: UTF-8
 LazyData: false
 Roxygen: list(markdown = TRUE)
-RoxygenNote: 7.3.1
+RoxygenNote: 7.3.2.9000
 URL: https://www.spsanderson.com/healthyR.ai/, https://github.com/spsanderson/healthyR.ai
 BugReports: https://github.com/spsanderson/healthyR.ai/issues
 Imports: 

NAMESPACE

@@ -30,6 +30,7 @@ export(color_blind)
 export(enquo)
 export(enquos)
 export(expr)
+export(generate_mesh_data)
 export(get_juiced_data)
 export(hai_auto_c50)
 export(hai_auto_cubist)

NEWS.md

@@ -4,7 +4,7 @@
 None
 
 ## New Features
-None
+1. Fix #340 - Add mesh generator function.
 
 ## Minor Fixes and Improvements
 1. Fix #337 - Fix typo in `hai_earth_data_prepper()` that caused it to not fully

R/utils-mesh-generator.R

@@ -0,0 +1,158 @@
+#' Generate Mesh Data
+#'
+#' This function generates a mesh of nodes and edges based on the provided side
+#' length and number of segments.
+#'
+#' @author Steven P. Sanderson II, MPH
+#'
+#' @description This function creates a square mesh by sampling nodes uniformly
+#' on a square and then connecting these nodes with edges. The nodes are
+#' distributed based on the provided side length and number of segments. Horizontal,
+#' vertical, and diagonal edges are generated to fully connect the mesh.
+#' The function returns a list containing the nodes and edges, along with data
+#' frames and a ggplot object for visualization.
+#'
+#' @details This function creates a square mesh of nodes and edges, where the
+#' nodes are sampled uniformly on a square. The edges are generated to connect
+#' the nodes horizontally, vertically, and diagonally.
+#'
+#' @param .side_length A single numeric value representing the side length of
+#' the square.
+#' @param .n_seg A positive integer representing the number of segments along
+#' each side of the square.
+#'
+#' @examples
+#' generate_mesh_data(1, 1)
+#' generate_mesh_data(1, 2)
+#'
+#' @return A list containing:
+#' \describe{
+#'   \item{nodes}{A matrix with coordinates of the nodes.}
+#'   \item{edges}{A list of edges connecting the nodes.}
+#'   \item{nodes_df}{A data frame of nodes for ggplot.}
+#'   \item{edges_df}{A data frame of edges for ggplot.}
+#'   \item{plot}{A ggplot object visualizing the nodes and edges.}
+#' }
+#' Additionally, the list contains attributes:
+#' \describe{
+#'   \item{side_length}{The side length used to generate the mesh.}
+#'   \item{n_seg}{The number of segments used to generate the mesh.}
+#'   \item{nodes_df_dim}{Dimensions of the nodes data frame.}
+#'   \item{edges_df_dim}{Dimensions of the edges data frame.}
+#' }
+#'
+#' @name generate_mesh_data
+NULL
+
+#' @rdname generate_mesh_data
+#' @export
+generate_mesh_data <- function(.side_length = 1, .n_seg = 1) {
+    side_length <- .side_length
+    n_seg <- .n_seg
+
+    # Check if side_length and n_seg are numeric
+    if (!is.numeric(side_length) || length(side_length) != 1) {
+        abort("side_length must be a single numeric value")
+    }
+
+    if (!is.numeric(n_seg) || length(n_seg) != 1 || n_seg <= 0 || floor(n_seg) != n_seg) {
+        abort("n_seg must be a positive integer")
+    }
+
+    # Check if side_length is positive
+    if (side_length <= 0) {
+        abort("side_length must be positive")
+    }
+    # sample nodes uniformly on a square
+    x <- matrix(0, nrow = (n_seg + 1) ^ 2, ncol = 2)
+    step <- side_length / n_seg
+    for (i in 0:n_seg) {
+        for (j in 0:n_seg) {
+            x[i * (n_seg + 1) + j + 1, ] <- c(-side_length / 2 + i * step, -side_length / 2 + j * step)
+        }
+    }
+
+    # connect the nodes with edges
+    e <- list()
+    # horizontal edges
+    for (i in 0:(n_seg - 1)) {
+        for (j in 0:n_seg) {
+            e <- append(e, list(c(i * (n_seg + 1) + j + 1, (i + 1) * (n_seg + 1) + j + 1)))
+        }
+    }
+    # vertical edges
+    for (i in 0:n_seg) {
+        for (j in 0:(n_seg - 1)) {
+            e <- append(e, list(c(i * (n_seg + 1) + j + 1, i * (n_seg + 1) + j + 2)))
+        }
+    }
+    # diagonals
+    for (i in 0:(n_seg - 1)) {
+        for (j in 0:(n_seg - 1)) {
+            e <- append(e, list(c(i * (n_seg + 1) + j + 1, (i + 1) * (n_seg + 1) + j + 2)))
+            e <- append(e, list(c((i + 1) * (n_seg + 1) + j + 1, i * (n_seg + 1) + j + 2)))
+        }
+    }
+
+    nodes <- x
+    edges <- e
+    # Convert nodes to data frame for ggplot
+    nodes_df <- as.data.frame(nodes)
+    colnames(nodes_df) <- c("x", "y")
+
+    # Create a data frame for edges
+    edges_df <- data.frame(
+        x = numeric(0),
+        y = numeric(0),
+        xend = numeric(0),
+        yend = numeric(0)
+    )
+
+    for (edge in edges) {
+        edges_df <- rbind(edges_df, data.frame(
+            x = nodes[edge[1], 1],
+            y = nodes[edge[1], 2],
+            xend = nodes[edge[2], 1],
+            yend = nodes[edge[2], 2]
+        ))
+    }
+
+    # Visualize the nodes and edges
+    # Plot the nodes and edges
+    p <- ggplot2::ggplot() +
+        ggplot2::geom_point(
+            data = nodes_df,
+            ggplot2::aes(x = x, y = y),
+            color = "blue", size = 3
+        ) +
+        ggplot2::geom_segment(
+            data = edges_df,
+            ggplot2::aes(x = x, y = y, xend = xend, yend = yend),
+            color = "red"
+        ) +
+        ggplot2::coord_equal() +
+        ggplot2::labs(
+            title = "Generated Nodes and Edges",
+            x = "X Coordinate",
+            y = "Y Coordinate"
+        ) +
+        ggplot2::theme_minimal()
+
+    # Make output
+    output <- list(
+        nodes = nodes,
+        edges = edges,
+        nodes_df = nodes_df,
+        edges_df = edges_df,
+        plot = p
+    )
+
+    # Add attributes
+    attr(output, "side_length") <- side_length
+    attr(output, "n_seg") <- n_seg
+    attr(output, "nodes_df_dim") <- dim(nodes_df)
+    attr(output, "edges_df_dim") <- dim(edges_df)
+
+    # Final return
+    return(output)
+}