Add basic mesh and use it in examples

examples/build_delaunay_triangulation.jl

@@ -1,12 +1,11 @@
 using Smesh
 
 # Create data points
-# Note: the transpose + collect is just such that we can write the matrix in human readable
-# form here
-data_points = collect([0.0 0.0
-                       1.0 0.0
-                       1.0 1.0
-                       0.0 1.0]')
+coordinates_min = [0.0, 0.0]
+coordinates_max = [1.0, 1.0]
+n_points_x = 4
+n_points_y = 5
+data_points = mesh_basic(coordinates_min, coordinates_max, n_points_x, n_points_y)
 
 # Create triangulation
 vertices = build_delaunay_triangulation(data_points; verbose = true)

examples/build_polygon_mesh.jl

@@ -1,16 +1,11 @@
 using Smesh
 
 # Create data points
-corners = collect([0.0 0.0
-                   1.0 0.0
-                   1.0 1.0
-                   0.0 1.0]')
-# inner points (randomly generated)
-# n_points = 10
-# data_points = rand(Float64, 2, n_points)
-data_points = [0.110127  0.995047  0.636537  0.942174   0.22912   0.162025  0.616885  0.376891  0.475242  0.448486;
-               0.554234  0.431985  0.540326  0.0252587  0.702442  0.379256  0.80191   0.237447  0.745391  0.868326]
-data_points = hcat(data_points, corners)
+coordinates_min = [0.0, 0.0]
+coordinates_max = [1.0, 1.0]
+n_points_x = 4
+n_points_y = 5
+data_points = mesh_basic(coordinates_min, coordinates_max, n_points_x, n_points_y)
 
 # Create triangulation
 vertices = build_delaunay_triangulation(data_points; verbose = false)

src/Smesh.jl

@@ -4,6 +4,7 @@ using Preferences: @load_preference
 using smesh_jll: smesh_jll
 
 export build_delaunay_triangulation, delaunay_compute_neighbors, build_polygon_mesh, voronoi_compute_neighbors
+export mesh_basic
 
 const libsmesh = @load_preference("libsmesh", smesh_jll.libsmesh)
 
@@ -112,4 +113,6 @@ function voronoi_compute_neighbors(vertices, voronoi_vertices, voronoi_vertices_
 
     return voronoi_neighbors
 end
+
+include("standard_meshes.jl")
 end # module Smesh

src/standard_meshes.jl

@@ -0,0 +1,25 @@
+function mesh_basic(coordinates_min, coordinates_max, n_points_x, n_points_y)
+    dx = (coordinates_max[1] - coordinates_min[1]) / n_points_x
+    dy = (coordinates_max[2] - coordinates_min[2]) / n_points_y
+
+    points = Matrix{eltype(coordinates_min)}(undef, 2, n_points_x * n_points_y  +
+                                                       div(n_points_y - n_points_y % 2, 2))
+    count = 1
+    for j in 1:n_points_y
+        for i in 1:n_points_x
+            points[1, count] = coordinates_min[1] + (i - 1) * dx
+            points[2, count] = coordinates_min[2] + (j - 1) * dy
+            if j % 2 == 0 && i != 1
+                points[1, count] -= 0.5dx
+            end
+            count += 1
+            if j % 2 == 0 && i == n_points_x
+                points[1, count] = points[1, count - 1] + 0.5dx
+                points[2, count] = points[2, count - 1]
+                count += 1
+            end
+        end
+    end
+
+    return points
+end