Merge branch 'master' into dev

Author: esabo

test/iterators_test.jl

@@ -1,8 +1,8 @@
 @testitem "iterators.jl" begin 
     @testset "SubsetGrayCode iterates over all weight k subsets of {1,..,n} (single iterator)" begin
-        len = 15
-        weight = 7
-        sgc = CodingTheory.SubsetGrayCode(len, weight)
+        len = 7 
+        weight = 5
+        sgc = CodingTheory.SubsetGrayCode(len, weight, UInt(21), UInt(0))
         all_subsets_gray = fill(fill(0, weight), length(sgc))
         subset = collect(1:sgc.k)
         state = (subset, 1, fill(-1, 3))
@@ -16,44 +16,7 @@
         sort!(all_subsets_gray)
         all_subsets_hecke = CodingTheory.Oscar.subsets(collect(1:len), weight)
         sort!(all_subsets_hecke)
-        @test length(all_subsets_gray) == 6435 
-        @test all_subsets_gray == all_subsets_hecke 
-    end
-
-    @testset "SubsetGrayCode iterates over all weight k subsets of {1,..,n} (split iterator)" begin
-        len = 15
-        weight = 7
-        num_threads = 3 # split the iterator into 3 parts 
-        itrs = CodingTheory._subset_gray_codes_from_num_threads(len, weight, num_threads)
-        @test length(itrs) == num_threads
-        initial_subset_vecs = fill(fill(0, weight), length(itrs))
-        bin = extended_binomial(len, weight)
-        for j in eachindex(itrs) 
-            itr = itrs[j]
-            @test length(itr) == fld(bin, num_threads)
-            subset_vec = zeros(Int, itr.k)
-            CodingTheory._subset_unrank!(itr.init_rank, UInt(itr.n), subset_vec)
-            initial_subset_vecs[j] = subset_vec
-        end
-    
-        all_subsets_gray = fill(fill(0, weight), bin)
-    
-        for j in 0:length(itrs)-1
-            sgc = itrs[j + 1]
-            subset_vec = initial_subset_vecs[j + 1] 
-            state = (subset_vec, 1, fill(-1, 3))
-            for i in 1:length(sgc)
-                all_subsets_gray[j * fld(bin, num_threads) + i] = deepcopy(subset_vec)
-                next = iterate(sgc, state)
-                isnothing(next) && break 
-                (_, state) = next
-                (subset_vec, _, _) = state
-            end
-        end
-        sort!(all_subsets_gray)
-        all_subsets_hecke = CodingTheory.Oscar.subsets(collect(1:len), weight)
-        sort!(all_subsets_hecke)
-        @test length(all_subsets_gray) == 6435 
+        @test length(all_subsets_gray) == 21
         @test all_subsets_gray == all_subsets_hecke 
     end
 
@@ -79,28 +42,28 @@
         k1 = UInt(3)
         n1 = UInt(5)
         rank1 = CodingTheory._subset_rank(subset1, k1)
-        @test rank1 == 0
+        @test rank1 == 1
         result1 = zeros(Int, k1)
-        CodingTheory._subset_unrank!(rank1, n1, result1)
+        CodingTheory._subset_unrank!(UInt128(rank1), n1, result1)
         @test result1 == subset1
 
         subset2 = UInt.([1, 3, 5])
         k2 = UInt(3)
         n2 = UInt(5)
         rank2 = CodingTheory._subset_rank(subset2, k2)
-        @test rank2 == 7
+        @test rank2 == 8
         result2 = zeros(Int, k2)
-        CodingTheory._subset_unrank!(rank2, n2, result2)
+        CodingTheory._subset_unrank!(UInt128(rank2), n2, result2)
         @test result2 == subset2 
 
         k3 = UInt(3)
         n3 = UInt(5)
         result3 = zeros(Int, k3)
-        results = Set()
+        results = Set{Vector{UInt64}}()
         bin = binomial(n3, k3) 
-        for i::BigInt in collect(0: bin - 1)
-          CodingTheory._subset_unrank!(i, n3, result3)
-          pushOrDel!(results, deepcopy(result3))
+        for i::BigInt in collect(1: bin)
+          CodingTheory._subset_unrank!(UInt128(i), n3, result3)
+          pushOrDel!(results, deepcopy(Vector{UInt64}(result3)))
         end
         all_subsets_hecke = Set(CodingTheory.Hecke.subsets(collect(1:n3), Int(k3)))
         @test results == all_subsets_hecke