VSCode warnings (#423)

Changed a bunch of iterations from `for i in 1:length(vec)` to `for i in eachindex(vec)`. I substituted a loop with a list comprehension because it seemed faster and clearer to read. I correct some spelling typos in comments in the code. I replaced comparisons of the type `a == nothing` with `isnothing(a)`.

Author: damianodegaspari

benchmark/serial/edges.jl

@@ -5,11 +5,7 @@ const P = Pair{Int,Int}
 convert(::Type{Tuple}, e::Pair) = (e.first, e.second)
 
 function fille(n)
-    t = Vector{Graphs.Edge}(undef, n)
-    for i in 1:n
-        t[i] = Graphs.Edge(i, i + 1)
-    end
-    return t
+    return [Graphs.Edge(i, i + 1) for i in 1:n]
 end
 
 function fillp(n)
@@ -22,8 +18,8 @@ end
 
 function tsum(t)
     x = 0
-    for i in 1:length(t)
-        u, v = Tuple(t[i])
+    for item in t
+        u, v = Tuple(item)
         x += u
         x += v
     end

src/Experimental/vf2.jl

@@ -278,10 +278,10 @@ function vf2check_feasibility(
         vf2rule_self_loops(u, v, state, problemtype)
     syntactic_feasability || return false
 
-    if vertex_relation != nothing
+    if !isnothing(vertex_relation)
         vertex_relation(u, v) || return false
     end
-    if edge_relation != nothing
+    if !isnothing(edge_relation)
         E1 = edgetype(state.g1)
         E2 = edgetype(state.g2)
         for u2 in outneighbors(state.g1, u)

src/SimpleGraphs/simpledigraph.jl

@@ -335,7 +335,7 @@ function _SimpleDiGraphFromIterator(iter)::SimpleDiGraph
     fadjlist = Vector{Vector{T}}()
     badjlist = Vector{Vector{T}}()
 
-    while next != nothing
+    while !isnothing(next)
         (e, state) = next
 
         if !(e isa E)

src/SimpleGraphs/simplegraph.jl

@@ -316,7 +316,7 @@ function _SimpleGraphFromIterator(iter)::SimpleGraph
     g = SimpleGraph{T}()
     fadjlist = Vector{Vector{T}}()
 
-    while next != nothing
+    while !isnothing(next)
         (e, state) = next
 
         if !(e isa E)

src/cycles/basis.jl

@@ -36,7 +36,7 @@ function cycle_basis(g::AbstractGraph, root=nothing)
     nv(g) == 0 && return cycles
 
     gnodes = Set(vertices(g))
-    r::T = (root == nothing) ? pop!(gnodes) : T(root)
+    r::T = isnothing(root) ? pop!(gnodes) : T(root)
     while true
         stack = [r]
         pred = Dict(r => r)

src/dominatingset/minimal_dom_set.jl

@@ -42,7 +42,7 @@ function dominating_set(
         # Check if any vertex is depending on v to be dominated
         dependent = findfirst(u -> !in_dom_set[u] && dom_degree[u] <= 1, neighbors(g, v))
 
-        (dependent != nothing) && continue
+        !isnothing(dependent) && continue
         in_dom_set[v] = false
         length_ds -= 1
         dom_degree[neighbors(g, v)] .-= 1

test/experimental/isomorphism.jl

@@ -84,32 +84,32 @@ cubic_graphs = [
 cubic_graphs_perm = []
 
 rng = StableRNG(1)
-for i in 1:length(cubic_graphs)
-    push!(cubic_graphs_perm, shuffle_vertices(cubic_graphs[i], randperm(rng, 8)))
+for graph in cubic_graphs
+    push!(cubic_graphs_perm, shuffle_vertices(graph, randperm(rng, 8)))
 end
 
 @testset "Isomorphism" begin
     @test has_isomorph(grid([2, 3]), grid([3, 2]))
 
-    # the cubic graphs should only be isomorph to themself
+    # the cubic graphs should only be isomorphic to themselves
     # the same holds for subgraph isomorphism and induced subgraph isomorphism
-    for i in 1:length(cubic_graphs), j in 1:length(cubic_graphs)
+    for i in eachindex(cubic_graphs), j in eachindex(cubic_graphs)
         @test (i == j) == has_isomorph(cubic_graphs[i], cubic_graphs[j])
         @test (i == j) == has_subgraphisomorph(cubic_graphs[i], cubic_graphs[j])
         @test (i == j) == has_induced_subgraphisomorph(cubic_graphs[i], cubic_graphs[j])
     end
 
-    # the cubic graphs should only be isomorph a permutation of themself
+    # the cubic graphs should only be isomorphic to a permutation of themselves
     # the same holds for subgraph isomorphism and induced subgraph isomorphism
-    for i in 1:length(cubic_graphs), j in 1:length(cubic_graphs_perm)
+    for i in eachindex(cubic_graphs), j in eachindex(cubic_graphs_perm)
         @test (i == j) == has_isomorph(cubic_graphs[i], cubic_graphs_perm[j])
         @test (i == j) == has_subgraphisomorph(cubic_graphs[i], cubic_graphs_perm[j])
         @test (i == j) ==
             has_induced_subgraphisomorph(cubic_graphs[i], cubic_graphs_perm[j])
     end
 
     # count_isomorph, count_subgraphisomorph and count_induced_subgraphisomorph are commutative
-    for i in 1:length(cubic_graphs)
+    for i in eachindex(cubic_graphs)
         g1 = cubic_graphs[i]
         g2 = cubic_graphs_perm[i]
         @test count_isomorph(g1, g1) ==
@@ -126,7 +126,7 @@ end
             count_subgraphisomorph(g2, g2)
     end
 
-    for i in 1:length(cubic_graphs)
+    for i in eachindex(cubic_graphs)
         g1 = cubic_graphs[i]
         g2 = cubic_graphs_perm[i]
         length(collect(all_isomorph(g1, g1))) == count_isomorph(g1, g2)

test/linalg/graphmatrices.jl

@@ -200,7 +200,7 @@ using ArnoldiMethod: LM, SR, LR, partialschur, partialeigen
         abs(l1 - 1) < 1e-8 || error("failed to compute stationary distribution") # TODO 0.7: should we change the error type to InexactError?
         p = real(er[2][:, 1])
         if p[1] < 0
-            for i in 1:length(p)
+            for i in eachindex(p)
                 p[i] = -p[i]
             end
         end