Replace int64 by int

.github/workflows/ci.yml

@@ -0,0 +1,44 @@
+name: CI
+on:
+  - push
+  - pull_request
+jobs:
+  test:
+    name: Julia ${{ matrix.version }} - ${{ matrix.os }} - ${{ matrix.arch }}
+    runs-on: ${{ matrix.os }}
+    strategy:
+      matrix:
+        version:
+          - '1.5'
+        os:
+          - ubuntu-latest
+        arch:
+          - x64
+    steps:
+      - uses: actions/checkout@v2
+      - uses: julia-actions/setup-julia@v1
+        with:
+          version: ${{ matrix.version }}
+          arch: ${{ matrix.arch }}
+      - uses: julia-actions/julia-buildpkg@latest
+      - uses: julia-actions/julia-runtest@latest
+#      - uses: julia-actions/julia-uploadcodecov@latest
+#        env:
+#          CODECOV_TOKEN: ${{ secrets.CODECOV_TOKEN }}
+#  docs:
+#    name: Documentation
+#    runs-on: ubuntu-latest
+#    steps:
+#      - uses: actions/checkout@v2
+#      - uses: julia-actions/setup-julia@v1
+#        with:
+#          version: '1.5'
+#      - run: |
+#          julia --project=docs -e '
+#            using Pkg
+#            Pkg.develop(PackageSpec(path=pwd()))
+#            Pkg.instantiate()'
+#      - run: julia --project=docs docs/make.jl
+#        env:
+#          GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
+#          DOCUMENTER_KEY: ${{ secrets.DOCUMENTER_KEY }}

NEWS.md

@@ -10,6 +10,8 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
 - Added additional tensor operations and new double contraction notation `⋅²`. Implemented a `zero` constructor for `ThirdOrderTensorValues` to allow integration of 3-tensors. Since PR [#415](https://github.com/gridap/Gridap.jl/pull/415/).
 - Added `compile/create_gridap_image.jl` Julia script that lets one to create a custom sysimage of Gridap using the so-called `PackageCompiler.jl` Julia package; see `compile/README.md` for additional details. Since PR [#432](https://github.com/gridap/Gridap.jl/pull/432/).
 
+### Fixed
+ - Bug-fix for 32-bit Julia: Replace all occurences of Int64 by Int. Since PR [#445](https://github.com/gridap/Gridap.jl/pull/445).
 
 ## [0.14.1] - 2020-09-17 
 

src/Polynomials/MonomialBases.jl

@@ -4,7 +4,7 @@
 
 Type representing a basis of multivariate scalar-valued, vector-valued, or
 tensor-valued, iso- or aniso-tropic monomials. The fields
-of this `struct` are not public  
+of this `struct` are not public
 This type fully implements the [`Field`](@ref) interface, with up to second order
 derivatives.
 """
@@ -83,7 +83,7 @@ exponents = get_exponents(b)
 println(exponents)
 
 # output
-Tuple{Int64,Int64}[(0, 0), (1, 0), (2, 0), (0, 1), (1, 1), (2, 1), (0, 2), (1, 2), (2, 2)]
+Tuple{Int,Int}[(0, 0), (1, 0), (2, 0), (0, 1), (1, 1), (2, 1), (0, 2), (1, 2), (2, 2)]
 ```
 """
 function get_exponents(b::MonomialBasis)
@@ -418,4 +418,3 @@ end
 
 _maximum(orders::Tuple{}) = 0
 _maximum(orders) = maximum(orders)
-

src/ReferenceFEs/CDLagrangianRefFEs.jl

@@ -153,13 +153,13 @@ function _compute_cd_face_own_nodes(p::ExtrusionPolytope{D},orders::NTuple{D,<:I
   nodes, _ = cd_compute_nodes(p,orders)
   _ord = convert(NTuple{D,Float64},orders)
   _nodes = map(i -> i.data.*_ord,nodes)
-  _nodes = map(i -> convert(NTuple{D,Int64},i),_nodes)
+  _nodes = map(i -> convert(NTuple{D,Int},i),_nodes)
   perm = Dict(_nodes[i] => i for i = 1:length(_nodes))
-  face_owned_nodes = Vector{Int64}[]
+  face_owned_nodes = Vector{Int}[]
   for nf in p.dface.nfaces
     anc = nf.anchor
     ext = nf.extrusion
-    fns = UnitRange{Int64}[]
+    fns = UnitRange{Int}[]
     for (i,(e,a,c,o)) in enumerate(zip(ext,anc,cont,orders))
       if e==0 && c == DISC
         push!(fns,0:-1)
@@ -174,7 +174,7 @@ function _compute_cd_face_own_nodes(p::ExtrusionPolytope{D},orders::NTuple{D,<:I
     end
     n_ijk = map(i->i.I,collect(CartesianIndices(Tuple(fns))))
     if length(n_ijk) == 0
-      n_i = Int64[]
+      n_i = Int[]
     else
       n_i = sort(reshape([perm[i] for i in n_ijk],length(n_ijk)))
     end
@@ -210,7 +210,7 @@ function _move_nodes(p::ExtrusionPolytope,orders,act_f,nodes,f_own)
     tr = map(i -> i == 0 ? 1 : 0,orders)
     nfs = p.dface.nfaces
     con(ext,anc) = f -> ( f.extrusion == ext && f.anchor == anc )
-    perm = zeros(Int64,length(nfs))
+    perm = zeros(Int,length(nfs))
     for i in findall(act_f)
       nf  =nfs[i]
       ext = VectorValue(map(+,nf.extrusion,tr))

src/ReferenceFEs/ExtrusionPolytopes.jl

@@ -20,7 +20,7 @@ struct DFace{D} <: GridapType
   dimranges::Vector{UnitRange{Int}}
   dims::Vector{Int}
   nf_nfs::Vector{Vector{Int}}
-  nf_dimranges::Vector{Vector{UnitRange{Int64}}}
+  nf_dimranges::Vector{Vector{UnitRange{Int}}}
   nf_dims::Vector{Vector{Int}}
 end
 
@@ -359,7 +359,7 @@ function _polytopenfaces(anchor, extrusion)
   numnfs = length(nf_nfs)
   nfsdim = [_nfdim(nf_nfs[i].extrusion) for i = 1:numnfs]
   dnf = _nfdim(extrusion)
-  dimnfs = Array{UnitRange{Int64},1}(undef, dnf + 1)
+  dimnfs = Array{UnitRange{Int},1}(undef, dnf + 1)
   dim = 0
   i = 1
   for iface = 1:numnfs

src/ReferenceFEs/Polytopes.jl

@@ -4,7 +4,7 @@
 
 Abstract type representing a polytope (i.e., a polyhedron in arbitrary dimensions).
 `D` is the environment dimension (typically, 0, 1, 2, or 3).
-This type parameter is needed since there are functions in the 
+This type parameter is needed since there are functions in the
 `Polytope` interface that return containers with `Point{D}` objects.
 We adopt the [usual nomenclature](https://en.wikipedia.org/wiki/Polytope) for polytope-related objects.
 All objects in a polytope (from vertices to the polytope itself) are called *n-faces* or simply *faces*.
@@ -53,7 +53,7 @@ to the first 0-face. Consecutive increasing ids are assigned to the other
 0-faces, then to 1-faces, and so on. The polytope itself receives the largest id
 which coincides with `num_faces(p)`. For a face id `iface`, `get_faces(p)[iface]`
 is a vector of face ids, corresponding to the faces that are *incident* with the face
-labeled with `iface`. That is, faces that are either on its boundary or the face itself. 
+labeled with `iface`. That is, faces that are either on its boundary or the face itself.
 In this vector of incident face ids, faces are ordered by dimension, starting with 0-faces.
 Within each dimension, the labels are ordered in a consistent way with the polyope object
 for the face `iface` itself.
@@ -67,14 +67,14 @@ faces = get_faces(SEGMENT)
 println(faces)
 
 # output
-Array{Int64,1}[[1], [2], [1, 2, 3]]
+Array{Int,1}[[1], [2], [1, 2, 3]]
 ```
 
 The constant [`SEGMENT`](@ref) is bound to a predefined instance of polytope
 that represents a segment.
-The face labels associated with a segment are `[1,2,3]`, being `1` and `2` for the vertices and 
+The face labels associated with a segment are `[1,2,3]`, being `1` and `2` for the vertices and
 `3` for the segment itself. In this case, this function returns the vector of vectors
-`[[1],[2],[1,2,3]]` meaning that vertex `1` is incident with vertex `1` (idem for vertex 2), and that 
+`[[1],[2],[1,2,3]]` meaning that vertex `1` is incident with vertex `1` (idem for vertex 2), and that
 the segment (id `3`) is incident with the vertices `1` and `2` and the segment itself.
 
 """
@@ -97,7 +97,7 @@ ranges = get_dimranges(SEGMENT)
 println(ranges)
 
 # output
-UnitRange{Int64}[1:2, 3:3]
+UnitRange{Int}[1:2, 3:3]
 ```
 Face ids for the vertices in the segment range from 1 to 2 (2 vertices),
 the face ids for edges in the segment range from 3 to 3 (only one edge with id 3).
@@ -142,7 +142,7 @@ end
 """
     (==)(a::Polytope{D},b::Polytope{D}) where D
 
-Returns `true` if the polytopes `a` and `b` are equivalent. Otherwise, it 
+Returns `true` if the polytopes `a` and `b` are equivalent. Otherwise, it
 returns `false`.
 Note that the operator `==` returns `false` by default for polytopes
 of different dimensions. Thus, this function has to be overloaded only
@@ -207,7 +207,7 @@ perms = get_vertex_permutations(SEGMENT)
 println(perms)
 
 # output
-Array{Int64,1}[[1, 2], [2, 1]]
+Array{Int,1}[[1, 2], [2, 1]]
 
 ```
 The first admissible permutation for a segment is `[1,2]`,i.e., the identity.
@@ -252,7 +252,7 @@ num_point_dims(::Type{<:Polytope{D}}) where D = D
     num_dims(::Type{<:Polytope{D}}) where D
     num_dims(p::Polytope{D}) where D
 
-Returns `D`. 
+Returns `D`.
 """
 num_dims(p::Polytope) = num_dims(typeof(p))
 
@@ -351,7 +351,7 @@ println(dims)
 
 ```
 
-The first two faces in the segment (the two vertices) have dimension 0 and the 
+The first two faces in the segment (the two vertices) have dimension 0 and the
 third face (the segment itself) has dimension 1
 
 """
@@ -444,8 +444,8 @@ vertex_to_edges_around = get_faces(QUAD,0,1)
 println(vertex_to_edges_around)
 
 # output
-Array{Int64,1}[[1, 2], [3, 4], [1, 3], [2, 4]]
-Array{Int64,1}[[1, 3], [1, 4], [2, 3], [2, 4]]
+Array{Int,1}[[1, 2], [3, 4], [1, 3], [2, 4]]
+Array{Int,1}[[1, 3], [1, 4], [2, 3], [2, 4]]
 ```
 """
 function get_faces(p::Polytope,dimfrom::Integer,dimto::Integer)
@@ -557,7 +557,7 @@ end
     get_face_type(p::Polytope,d::Integer) -> Vector{Int}
 
 Return a vector of integers denoting, for each face of dimension `d`, an index to the
-vector `get_reffaces(Polytope{d},p)` 
+vector `get_reffaces(Polytope{d},p)`
 
 # Examples
 
@@ -741,5 +741,3 @@ function Quadrature(p::Polytope{D},degree) where D
   end
   quad
 end
-
-

test/AlgebraTests/SparseMatrixCSC.jl

@@ -9,7 +9,7 @@ module SparseMatrixCSCTests
     maxrows=5
     maxcols=5
 
-    for T in (Int32,Int64,Float32,Float64)
+    for T in (Int32,Int,Float32,Float64)
         I = Vector{Int}()
         J = Vector{Int}()
         V = Vector{T}()
@@ -69,5 +69,5 @@ module SparseMatrixCSCTests
 
 
     end
-    
+
 end

test/AlgebraTests/SparseMatrixCSR.jl

@@ -9,7 +9,7 @@ module SparseMatrixCSRTests
     maxrows=5
     maxcols=5
     maxrowsorcols=7
-    int_types=(Int32,Int64)
+    int_types=(Int32,Int)
     float_types=(Float32,Float64)
     Bi_types=(0,1)
 

test/AlgebraTests/SymSparseMatrixCSR.jl

@@ -8,7 +8,7 @@ module SymSparseMatrixCSRTests
     maxnz=5
     maxrows=5
     maxcols=5
-    int_types=(Int32,Int64)
+    int_types=(Int32,Int)
     float_types=(Float32,Float64)
     Bi_types=(0,1)
 

test/ArraysTests/LocalToGlobalArraysTests.jl

@@ -19,7 +19,7 @@ r = reindex(ca,ids)
 test_array(r,ca[ids])
 
 i_to_v=[[1, 2], [5, 6], [1, 5], [2, 6], [2, 3], [6, 7], [3, 7], [3, 4], [7, 8], [4, 8], [9, 10], [5, 9], [6, 10], [10, 11], [7, 11], [11, 12], [8, 12], [13, 14], [9, 13], [10, 14], [14, 15], [11, 15], [15, 16], [12, 16]]
-j_to_i=Int64[]
+j_to_i=Int[]
 lid_to_gid=reindex(i_to_v,j_to_i)
 gid_to_val=VectorValue{2,Float64}[(0.0, 0.25), (0.25, 0.25), (0.5, 0.25), (0.75, 0.25), (0.0, 0.5), (0.25, 0.5), (0.5, 0.5), (0.75, 0.5), (0.0, 0.75), (0.25, 0.75), (0.5, 0.75), (0.75, 0.75), (0.0, 1.0), (0.25, 1.0), (0.5, 1.0), (0.75, 1.0)]
 f2=LocalToGlobalArray(lid_to_gid,gid_to_val)

test/ArraysTests/LocalToGlobalPosNegArraysTests.jl

@@ -11,11 +11,11 @@ gid_to_val_pos = [p, 2*p, 3*p, -p, p]
 gid_to_val_neg = [3*p, -p, p]
 lid_to_gid = Table(data,ptrs)
 ca = LocalToGlobalPosNegArray(lid_to_gid,gid_to_val_pos,gid_to_val_neg)
-a = Vector{Int64}[[2, 3, 3], [], [3, -1, -1], [3, 2, 1, -1, 1, -1]]
+a = Vector{Int}[[2, 3, 3], [], [3, -1, -1], [3, 2, 1, -1, 1, -1]]
 test_array( ca, a )
 
 i_to_v=[[1, 2], [5, 6], [1, 5], [2, 6], [2, 3], [6, 7], [3, 7], [3, 4], [7, 8], [4, 8], [9, 10], [5, 9], [6, 10], [10, 11], [7, 11], [11, 12], [8, 12], [13, 14], [9, 13], [10, 14], [14, 15], [11, 15], [15, 16], [12, 16]]
-j_to_i=Int64[]
+j_to_i=Int[]
 lid_to_gid=reindex(i_to_v,j_to_i)
 gid_to_val=VectorValue{2,Float64}[(0.0, 0.25), (0.25, 0.25), (0.5, 0.25), (0.75, 0.25), (0.0, 0.5), (0.25, 0.5), (0.5, 0.5), (0.75, 0.5), (0.0, 0.75), (0.25, 0.75), (0.5, 0.75), (0.75, 0.75), (0.0, 1.0), (0.25, 1.0), (0.5, 1.0), (0.75, 1.0)]
 f2=LocalToGlobalPosNegArray(lid_to_gid,gid_to_val,gid_to_val)

test/ArraysTests/TablesTests.jl

@@ -22,16 +22,16 @@ d = Table(data,ptrs)
 e = [ data[ptrs[i]:ptrs[i+1]-1] for i in 1:length(ptrs)-1]
 test_array(d,e)
 
-data = Int64[2,3,1,3,6,7,3,2,5,6,3,4]
+data = Int[2,3,1,3,6,7,3,2,5,6,3,4]
 ptrs = [1,4,4,7,13]
 a = Table(data,ptrs)
 
-data  = reinterpret(Int64,Vector{Float64}(undef,12))
+data  = reinterpret(Int,Vector{Float64}(undef,12))
 data[1:6] .= a.data[7:12]
 data[7:9] .= a.data[4:6]
 data[10:12] .= a.data[1:3]
 
-perm = Vector{Int64}(undef,12)
+perm = Vector{Int}(undef,12)
 perm[1:3]  .= 10:12
 perm[4:6]  .= 7:9
 perm[7:12] .= 1:6

test/IoTests/JLD2Tests.jl

@@ -19,15 +19,11 @@ to_jld2_file(foo,f)
 @test foo == from_jld2_file(typeof(foo),f)
 
 f = joinpath(d,"dict.jld2")
-foo = Dict("a"=>Int32(1),2=>Int64(3),4.0=>Float32(5),"six"=>Float64(7),:s=>"Symbol")
+foo = Dict("a"=>Int32(1),2=>Int(3),4.0=>Float32(5),"six"=>Float64(7),:s=>"Symbol")
 
 to_jld2_file(foo,f)
 @test foo == from_jld2_file(typeof(foo),f)
 
 rm(d,recursive=true)
 
 end # module
-
-
-
-

test/ReferenceFEsTests/CLagrangianRefFEsTests.jl

@@ -54,7 +54,7 @@ b = MonomialBasis(VectorValue{2,Int},VERTEX,())
 reffe = LagrangianRefFE(VectorValue{2,Int},VERTEX,())
 @test get_face_own_nodes(reffe) == [[1]]
 @test get_face_own_dofs(reffe) == [[1,2]]
-@test get_face_own_dofs_permutations(reffe) == [[[1, 2]]] 
+@test get_face_own_dofs_permutations(reffe) == [[[1, 2]]]
 test_lagrangian_reference_fe(reffe)
 @test ReferenceFE{0}(reffe,1) === reffe
 
@@ -79,11 +79,11 @@ refface = ReferenceFE{1}(reffe,8)
 orders = (4,)
 reffe = LagrangianRefFE(VectorValue{2,Float64},SEGMENT,orders)
 @test get_own_nodes_permutations(reffe) == [[1, 2, 3], [3, 2, 1]]
-@test get_own_dofs_permutations(reffe) == [[1, 2, 3, 4, 5, 6], [3, 2, 1, 6, 5, 4]] 
+@test get_own_dofs_permutations(reffe) == [[1, 2, 3, 4, 5, 6], [3, 2, 1, 6, 5, 4]]
 
 orders = (2,3)
 reffe = LagrangianRefFE(VectorValue{2,Float64},QUAD,orders)
-@test get_own_nodes_permutations(reffe) ==[[1, 2], [0, 0], [1, 2], [0, 0], [0, 0], [2, 1], [0, 0], [2, 1]] 
+@test get_own_nodes_permutations(reffe) ==[[1, 2], [0, 0], [1, 2], [0, 0], [0, 0], [2, 1], [0, 0], [2, 1]]
 @test get_own_dofs_permutations(reffe) == [
   [1, 2, 3, 4], [0, 0, 0, 0], [1, 2, 3, 4], [0, 0, 0, 0],
   [0, 0, 0, 0], [2, 1, 4, 3], [0, 0, 0, 0], [2, 1, 4, 3]]
@@ -138,7 +138,7 @@ reffe = LagrangianRefFE(VectorValue{2,Float64},QUAD,orders)
 @test num_nodes(reffe) == 1
 test_lagrangian_reference_fe(reffe)
 
-@test get_face_own_dofs(reffe) == Array{Int64,1}[[], [], [], [], [], [], [], [], [1, 2]] 
+@test get_face_own_dofs(reffe) == Array{Int,1}[[], [], [], [], [], [], [], [], [1, 2]]
 #@test get_face_own_dofs_permutations(reffe) == [
 #  [[]],[[]],[[]],[[]],[[],[]],[[],[]],[[],[]],[[],[]],[[1,2],[1,2],[1,2],[1,2],[1,2],[1,2],[1,2],[1,2]]]
 @test get_face_own_dofs_permutations(reffe) == [

test/TensorValuesTests/OperationsTests.jl

@@ -355,7 +355,7 @@ v = TensorValue{2,3}(1,0,0,1,0,0)
 
 v = TensorValue{2,3}(1,0,0,1,1,0)
 @test meas(v) ≈ sqrt(2)
- 
+
 # Broadcasted operations
 
 a = VectorValue(1,2,3)
@@ -503,7 +503,7 @@ Sym4TensorIndexing = [1111, 1121, 1131, 1122, 1132, 1133, 2111, 2121, 2131, 2122
                       3111, 3121, 3131, 3122, 3132, 3133, 2211, 2221, 2231, 2222, 2232, 2233,
                       2311, 2321, 2331, 2322, 2332, 2333, 3311, 3321, 3331, 3322, 3332, 3333]
 test1 = test2 = SymFourthOrderTensorValue(1:36...)
-result = Int64[]
+result = Int[]
 for off_index in Sym4TensorIndexing
   i = parse(Int,string(off_index)[1]); j = parse(Int,string(off_index)[2]);
   m = parse(Int,string(off_index)[3]); p = parse(Int,string(off_index)[4]);

test/TensorValuesTests/TypesTests.jl

@@ -317,11 +317,11 @@ v = TensorValue{3,2,Float64}(1,2,3,4,5,6)
 s = "(1.0, 2.0, 3.0, 4.0, 5.0, 6.0)"
 @test string(v) == s
 
-v = SymTensorValue{3,Int64}(1, 0, 0, 1, 0, 1)
+v = SymTensorValue{3,Int}(1, 0, 0, 1, 0, 1)
 s = "(1, 0, 0, 1, 0, 1)"
 @test string(v) == s
 
-v = SymFourthOrderTensorValue{2,Int64}(1111,1121,1122, 2111,2121,2122, 2211,2221,2222)
+v = SymFourthOrderTensorValue{2,Int}(1111,1121,1122, 2111,2121,2122, 2211,2221,2222)
 s = "(1111, 1121, 1122, 2111, 2121, 2122, 2211, 2221, 2222)"
 @test string(v) == s