Replace LightGraphs.jl with Graphs.jl (#154)

* Use Graphs.jl instead of LightGraphs.jl

* Formatting

* Don't test on Julia 1.0

* Update changelog

* Fix tests and docs example

* Don't test ambiguities

.github/workflows/Test.yml

@@ -12,13 +12,10 @@ jobs:
     runs-on: ubuntu-latest
     strategy:
       matrix:
-        julia-version: ['1.0', '1', 'nightly']
+        julia-version: ['1.6', '1', 'nightly']
     name: ${{ matrix.julia-version }}
     steps:
       - uses: actions/checkout@v2
-      - name: MiniQHull deps
-        run: sudo apt-get install gcc libqhull-r7 libqhull-dev
-        if: ${{ matrix.julia-version == '1.0' }}
       - uses: julia-actions/setup-julia@latest
         with:
           version: ${{ matrix.julia-version }}

CHANGELOG.md

@@ -1,3 +1,7 @@
+# v0.16.9
+
+Replace LightGraps with Graphs.
+
 # v0.16.4
 
 Add [MLJ.jl](https://github.com/alan-turing-institute/MLJ.jl) support.
@@ -17,7 +21,7 @@ External changes:
 
 Interface changes:
 
-* All filtration constructors should now have to take `verbose` as a keyword argument.
+* All filtration constructors now have to take `verbose` as a keyword argument.
 * Replaced vectors of `ChainElement`s with `Chain`s.
 * Added `AbstractCell`.
 * `Cube` is now an `AbstractCell`, `AbstractSimplex` is reserved for actual simplices.

Project.toml

@@ -1,15 +1,15 @@
 name = "Ripserer"
 uuid = "aa79e827-bd0b-42a8-9f10-2b302677a641"
 authors = ["mtsch <matijacufar@gmail.com>"]
-version = "0.16.8"
+version = "0.16.9"
 
 [deps]
 Compat = "34da2185-b29b-5c13-b0c7-acf172513d20"
 DataStructures = "864edb3b-99cc-5e75-8d2d-829cb0a9cfe8"
 Distances = "b4f34e82-e78d-54a5-968a-f98e89d6e8f7"
 Future = "9fa8497b-333b-5362-9e8d-4d0656e87820"
+Graphs = "86223c79-3864-5bf0-83f7-82e725a168b6"
 IterTools = "c8e1da08-722c-5040-9ed9-7db0dc04731e"
-LightGraphs = "093fc24a-ae57-5d10-9952-331d41423f4d"
 LinearAlgebra = "37e2e46d-f89d-539d-b4ee-838fcccc9c8e"
 MLJModelInterface = "e80e1ace-859a-464e-9ed9-23947d8ae3ea"
 MiniQhull = "978d7f02-9e05-4691-894f-ae31a51d76ca"
@@ -24,8 +24,8 @@ TupleTools = "9d95972d-f1c8-5527-a6e0-b4b365fa01f6"
 Compat = "3.10.0"
 DataStructures = "0.17, 0.18"
 Distances = "0.8, 0.9, 0.10"
+Graphs = "1"
 IterTools = "1"
-LightGraphs = "1.3.3"
 MLJModelInterface = "^0.3.5, 0.4, 1"
 MiniQhull = "0.2, 0.3"
 PersistenceDiagrams = "0.9"

benchmark/utils.jl

@@ -3,7 +3,7 @@ using SparseArrays
 
 function load_points(filename)
     # ripser uses Float32
-    table = CSV.File(filename; header=0, type=Float32, delim=' ')
+    table = CSV.File(filename; header=0, types=Float32, delim=' ')
     nrow = length(table)
     dim = length(table[1])
     result = Vector{NTuple{dim,Float32}}(undef, nrow)

docs/src/examples/malaria.jl

@@ -23,8 +23,8 @@ nothing # hide
 # pretend we were only given 200 images to work with. We have chosen the 200 images
 # randomly.
 
-uninfected = shuffle!(load.(readdir(joinpath(data_dir, "uninfected"); join=true)))
-infected = shuffle!(load.(readdir(joinpath(data_dir, "infected"); join=true)))
+uninfected = shuffle!(Images.load.(readdir(joinpath(data_dir, "uninfected"); join=true)))
+infected = shuffle!(Images.load.(readdir(joinpath(data_dir, "infected"); join=true)))
 
 images = [uninfected; infected]
 classes = [fill(false, length(uninfected)); fill(true, length(infected))]

src/Ripserer.jl

@@ -17,7 +17,7 @@ using SparseArrays
 using DataStructures
 using Distances
 using IterTools
-using LightGraphs
+using Graphs
 using MiniQhull
 using PersistenceDiagrams
 using ProgressMeter
@@ -29,7 +29,7 @@ import MLJModelInterface
 
 # This functionality is imported to avoid having to deal with name clashes. There is no
 # piracy involved here.
-import LightGraphs: vertices, edges, nv, adjacency_matrix
+import Graphs: vertices, edges, nv, adjacency_matrix
 
 # Reexporting basics makes Ripserer usable without having to import another package.
 import PersistenceDiagrams: birth, threshold, dim

src/extra/cycles.jl

@@ -33,9 +33,9 @@ _in(σ, g::OneSkeleton) = !isnothing(σ) && birth(σ) ≤ g.threshold && σ ∉
 _linear(g, i) = LinearIndices(vertices(g.filtration))[i]
 _inv_linear(g, i) = vertices(g.filtration)[i]
 
-LightGraphs.edgetype(::OneSkeleton) = Edge{Int}
+Graphs.edgetype(::OneSkeleton) = Edge{Int}
 
-function LightGraphs.has_edge(g::OneSkeleton, u::Integer, v::Integer)
+function Graphs.has_edge(g::OneSkeleton, u::Integer, v::Integer)
     if u ∉ vertices(g) || v ∉ vertices(g)
         return false
     else
@@ -44,7 +44,7 @@ function LightGraphs.has_edge(g::OneSkeleton, u::Integer, v::Integer)
     end
 end
 
-function LightGraphs.edges(g::OneSkeleton)
+function Graphs.edges(g::OneSkeleton)
     result = edgetype(g)[]
     for sx in Ripserer.edges(g.filtration)
         if _in(sx, g)
@@ -54,7 +54,7 @@ function LightGraphs.edges(g::OneSkeleton)
     end
     return result
 end
-function LightGraphs.outneighbors(g::OneSkeleton, u::Integer)
+function Graphs.outneighbors(g::OneSkeleton, u::Integer)
     root = simplex(g.filtration, Val(0), (_inv_linear(g, u),))
     neighbors = Int[]
     for sx in Ripserer.coboundary(g.filtration, root)
@@ -69,18 +69,18 @@ function LightGraphs.outneighbors(g::OneSkeleton, u::Integer)
     end
     return neighbors
 end
-LightGraphs.inneighbors(g::OneSkeleton, u::Integer) = outneighbors(g, u)
+Graphs.inneighbors(g::OneSkeleton, u::Integer) = outneighbors(g, u)
 
 Base.eltype(::OneSkeleton) = Int
-LightGraphs.has_vertex(g::OneSkeleton, u) = 1 ≤ u ≤ nv(g)
-LightGraphs.ne(g::OneSkeleton) = length(edges(g))
-LightGraphs.nv(g::OneSkeleton) = nv(g.filtration)
-LightGraphs.vertices(g::OneSkeleton) = Base.OneTo(nv(g))
-LightGraphs.is_directed(::OneSkeleton) = false
-LightGraphs.is_directed(::Type{<:OneSkeleton}) = false
+Graphs.has_vertex(g::OneSkeleton, u) = 1 ≤ u ≤ nv(g)
+Graphs.ne(g::OneSkeleton) = length(edges(g))
+Graphs.nv(g::OneSkeleton) = nv(g.filtration)
+Graphs.vertices(g::OneSkeleton) = Base.OneTo(nv(g))
+Graphs.is_directed(::OneSkeleton) = false
+Graphs.is_directed(::Type{<:OneSkeleton}) = false
 
 # need default dist for filtrations...
-LightGraphs.weights(g::OneSkeleton) = g.weights
+Graphs.weights(g::OneSkeleton) = g.weights
 
 _heuristic(filtration, src, distances) = dst -> distances[dst, src]
 function _path_length(dists, cyc)

test/extra/cycles.jl

@@ -1,10 +1,10 @@
-using LightGraphs
+using Graphs
 using Ripserer
 using Test
 
 using Ripserer: distance_matrix, OneSkeleton
 
-@testset "OneSkeleton respects the LightGraphs interface" begin
+@testset "OneSkeleton respects the Graphs interface" begin
     @testset "no threshold or removed simplices" begin
         flt = Rips(
             [

test/extra/mlj.jl

@@ -11,26 +11,26 @@ function test_mlj_model(model, X)
     Xt = transform(mach, X)
 
     @test nrows(Xt) == length(X)
-    @test length(first(Xt)) ≥ 30
+    @test length(propertynames(Xt)) ≥ 30
 
     model.vectorizer = PersistenceCurveVectorizer()
     fit!(mach; verbosity=0)
     Xt = transform(mach, X)
 
     @test nrows(Xt) == length(X)
-    @test length(first(Xt)) == 20
+    @test length(propertynames(Xt)) == 20
 
     model.vectorizer.length = 100
     fit!(mach; verbosity=0)
     Xt = transform(mach, X)
     @test nrows(Xt) == length(X)
-    @test length(first(Xt)) == 200
+    @test length(propertynames(Xt)) == 200
 
     model.dim_max = 2
     fit!(mach; verbosity=0)
     Xt = transform(mach, X)
     @test nrows(Xt) == length(X)
-    @test length(first(Xt)) == 300
+    @test length(propertynames(Xt)) == 300
 end
 
 @testset "Rips" begin