Merge branch 'COMODO-research:main' into main

Manifest.toml

@@ -2,7 +2,7 @@
 
 julia_version = "1.10.1"
 manifest_format = "2.0"
-project_hash = "d4eb882a44fc91c1fbf111dd9aa6f52b208dd65c"
+project_hash = "605ab7cd5a06e8048cf84924cbec19c5085ec0ef"
 
 [[deps.AbstractFFTs]]
 deps = ["LinearAlgebra"]
@@ -308,6 +308,17 @@ git-tree-sha1 = "23163d55f885173722d1e4cf0f6110cdbaf7e272"
 uuid = "b552c78f-8df3-52c6-915a-8e097449b14b"
 version = "1.15.1"
 
+[[deps.Distances]]
+deps = ["LinearAlgebra", "Statistics", "StatsAPI"]
+git-tree-sha1 = "66c4c81f259586e8f002eacebc177e1fb06363b0"
+uuid = "b4f34e82-e78d-54a5-968a-f98e89d6e8f7"
+version = "0.10.11"
+weakdeps = ["ChainRulesCore", "SparseArrays"]
+
+    [deps.Distances.extensions]
+    DistancesChainRulesCoreExt = "ChainRulesCore"
+    DistancesSparseArraysExt = "SparseArrays"
+
 [[deps.Distributed]]
 deps = ["Random", "Serialization", "Sockets"]
 uuid = "8ba89e20-285c-5b6f-9357-94700520ee1b"

Project.toml

@@ -6,6 +6,7 @@ version = "0.1.0"
 [deps]
 BSplineKit = "093aae92-e908-43d7-9660-e50ee39d5a0a"
 DataStructures = "864edb3b-99cc-5e75-8d2d-829cb0a9cfe8"
+Distances = "b4f34e82-e78d-54a5-968a-f98e89d6e8f7"
 FEBio = "c57eab10-e7d7-41f3-9039-a27761009b26"
 FileIO = "5789e2e9-d7fb-5bc7-8068-2c6fae9b9549"
 GLMakie = "e9467ef8-e4e7-5192-8a1a-b1aee30e663a"

README.md

@@ -1,8 +1,12 @@
 [![License: Apache 2.0](https://img.shields.io/badge/License-Apache-blue.svg)](https://github.com/COMODO-research/Comodo.jl/blob/main/LICENSE)
 [![example workflow](https://github.com/COMODO-research/Comodo.jl/actions/workflows/test.yml/badge.svg)](https://github.com/COMODO-research/Comodo.jl/blob/main/.github/workflows/test.yml) 
+[![Join the chat at https://gitter.im/Comodo.jl](https://badges.gitter.im/Comodo.jl.svg)](https://app.gitter.im/#/room/#comodo:gitter.im?utm_source=badge&utm_medium=badge&utm_campaign=pr-badge&utm_content=badge)
 ![](assets/img/COMODO.png)
 [![Mastodon](https://img.shields.io/badge/-MASTODON-%232B90D9?style=for-the-badge&logo=mastodon&logoColor=white)](https://fosstodon.org/@kevinmoerman) 
 
+
+
+
 # About Comodo
 Comodo is a [Julia](https://julialang.org/) package **computational (bio)mechanics and computational design**, and offers functionality for geometry processing, meshing, finite element analysis, automated design, topology optimisation, and image-based modelling. 
 

examples/demo_dist.jl

@@ -11,7 +11,7 @@ the minimum distances are visualised on the mesh.
 
 # Defining icosahedron
 r = 1 # radius of icosahedron
-n = 1 # Number of refinement steps
+n = 3 # Number of refinement steps
 
 # Define an icosahedron
 M = platonicsolid(4,r) # GeometryBasics mesh description of icosahedron
@@ -20,7 +20,7 @@ F = faces(M) # Get the mesh faces
 
 # Created refined version
 Fn,Vn = subtri(F,V,n) # Subdevide/refine the mesh linearly 
-
+F,V = subtri(F,V,2)
 # Use distND to compute distances from all in set 1 to all in set 2
 DD = dist(Vn,V)
 

examples/demo_mindist.jl

@@ -3,36 +3,42 @@ using GeometryBasics # For point and mesh format
 using GLMakie
 
 #=
-This demo shows the use of distND to compute distances for ND points. A 3D 
-point set is defined on an icosahedron. Next a refined (using subtri) version is
-created and the distance from the refined to the unrefined are computed. Next
-the minimum distances are visualised on the mesh. 
+This demo shows the use of dist to compute distances for ND points. A 3D 
+point set is defined on an geodesic sphere. Next another, more refined version
+is created, and the distance from this sphere to the coarser one is computed. 
+Next the minimum distances are visualised on the mesh. 
 =#
 
 # Defining icosahedron
 r = 1 # radius of icosahedron
-n = 3 # Number of refinement steps
+n = 5 # Number of refinement steps
 
-# Define an icosahedron
-M = platonicsolid(4,r) # GeometryBasics mesh description of icosahedron
-V = coordinates(M) # Get the mesh coordinates
-F = faces(M) # Get the mesh faces
+# Define a mesh
+F,V = geosphere(1,r) 
 
-# Created refined version
-Fn,Vn = subtri(F,V,n) # Subdevide/refine the mesh linearly 
+# Define a mesh
+Fn,Vn = geosphere(n,r)  # Subdevide/refine the mesh linearly 
 
 # Compute nearest point distances
-Dn = mindist(Vn,V; getIndex = false)
+Dn,indMin = mindist(Vn,V; getIndex = true)
 
 # Visualization
-fig = Figure(size = (800,800))
+fig = Figure(size = (1200,500))
 
-ax=Axis3(fig[1, 1], aspect = :data, xlabel = "X", ylabel = "Y", zlabel = "Z")
+ax1=Axis3(fig[1, 1], aspect = :data, xlabel = "X", ylabel = "Y", zlabel = "Z")
 
-hp = poly!(ax,GeometryBasics.Mesh(Vn,Fn),strokewidth=0,color=Dn, shading=FastShading, overdraw=false)
-hs1 = scatter!(ax, V,markersize=35,color=:black)
-hs2 = scatter!(ax, Vn,markersize=15,color=Dn,strokewidth=1)
+hp1 = poly!(ax1,GeometryBasics.Mesh(Vn,Fn),strokewidth=0,color=Dn,shading=FastShading, overdraw=false)
+hs1 = scatter!(ax1, V,markersize=35,color=:black)
+
+Colorbar(fig[1, 2], hp1,label="Distance")
+Legend(fig[1, 3],[hp1,hs1],["Distances on mesh","Point set"])
+
+ax2=Axis3(fig[1, 4], aspect = :data, xlabel = "X", ylabel = "Y", zlabel = "Z")
+
+hp2 = poly!(ax2,GeometryBasics.Mesh(Vn,Fn),strokewidth=0,color=indMin,shading=FastShading, overdraw=false)
+hs2 = scatter!(ax2, V,markersize=35,color=:black)
+
+Colorbar(fig[1, 5], hp2,label="Nearest point index")
+Legend(fig[1, 6],[hp2,hs2],["Point indices","Point set"])
 
-Colorbar(fig[1, 2], hs2,label="Distance")
-Legend(fig[1, 3],[hp,hs1],["Distances on mesh","Point set"])
 fig

src/Comodo.jl

@@ -11,6 +11,8 @@ import Statistics
 import SparseArrays
 import GLMakie
 import Rotations
+import BSplineKit
+import Distances
 
 include("functions.jl")
 

src/functions.jl

@@ -8,6 +8,8 @@ using Statistics # For: mean
 using GLMakie # For slidercontrol
 using SparseArrays # For meshconnectivity
 using Rotations 
+using BSplineKit
+using Distances
 
 function comododir()
     joinpath(@__DIR__, "..")
@@ -206,7 +208,7 @@ function dist(V1,V2)
     D = Matrix{Float64}(undef,length(V1),length(V2))   
     for i ∈ eachindex(V1)
         for j ∈ eachindex(V2)          
-            D[i,j] = norm((V1[i].-V2[j]))       
+            D[i,j] = euclidean(V1[i],V2[j]) # norm(V1[i]-V2[j])       
         end
     end
     return D
@@ -223,7 +225,7 @@ function mindist(V1,V2; getIndex=false, skipSelf = false )
             if skipSelf && i==j
                 d[j] = Inf
             else
-                d[j] = sqrt(sum((V1[i].-V2[j]).^2)) 
+                d[j] = euclidean(V1[i],V2[j]) # norm(V1[i]-V2[j]) 
             end       
         end
         if getIndex