Merge pull request #106 from mforets/mforets/104

Fix some compatibility issues

src/MAT_HDF5.jl

@@ -32,6 +32,12 @@ using HDF5
 using Compat
 using Compat.SparseArrays
 
+@static if VERSION < v"0.7-"
+    _finalizer(f, x) = finalizer(x, f)
+else
+    _finalizer = finalizer
+end
+
 import Base: read, write, close
 import HDF5: names, exists, HDF5ReferenceObj, HDF5BitsKind
 
@@ -47,7 +53,7 @@ mutable struct MatlabHDF5File <: HDF5.DataFile
     function MatlabHDF5File(plain, toclose::Bool=true, writeheader::Bool=false, refcounter::Int=0)
         f = new(plain, toclose, writeheader, refcounter)
         if toclose
-            finalizer(f, close)
+            _finalizer(close, f)
         end
         f
     end
@@ -130,9 +136,9 @@ function read_complex(dtype::HDF5Datatype, dset::HDF5Dataset, ::Type{Array{T}})
     HDF5.h5d_read(dset.id, memtype.id, HDF5.H5S_ALL, HDF5.H5S_ALL, HDF5.H5P_DEFAULT, buf)
 
     if T == Float32
-        d = reinterpret(Complex64, dbuf, sz)
+        d = reinterpret(ComplexF32, dbuf, sz)
     elseif T == Float64
-        d = reinterpret(Complex128, dbuf, sz)
+        d = reinterpret(ComplexF64, dbuf, sz)
     else
         d = slicedim(dbuf, 1, 1) + im * slicedim(dbuf, 1, 2)
     end
@@ -156,7 +162,7 @@ function m_read(dset::HDF5Dataset)
             end
         else
             T = mattype == "canonical empty" ? Union{} : str2eltype_matlab[mattype]
-            return Array{T}(dims...)
+            return Array{T}(undef, dims...)
         end
     end
 
@@ -165,7 +171,7 @@ function m_read(dset::HDF5Dataset)
     if mattype == "cell"
         # Cell arrays, represented as an array of refs
         refs = read(dset, Array{HDF5ReferenceObj})
-        out = Array{Any}(size(refs))
+        out = Array{Any}(undef, size(refs))
         f = file(dset)
         for i = 1:length(refs)
             dset = f[refs[i]]
@@ -466,7 +472,7 @@ function m_write(mfile::MatlabHDF5File, parent::HDF5Parent, name::String, data::
             close(a)
         end
         # Write the items to the reference group
-        refs = Array{HDF5ReferenceObj}(size(data))
+        refs = Array{HDF5ReferenceObj}(undef, size(data))
         for i = 1:length(data)
             mfile.refcounter += 1
             itemname = string(mfile.refcounter)
@@ -492,7 +498,7 @@ end
 
 # Check that keys are valid for a struct, and convert them to an array of ASCIIStrings
 function check_struct_keys(k::Vector)
-    asckeys = Vector{String}(length(k))
+    asckeys = Vector{String}(undef, length(k))
     for i = 1:length(k)
         key = k[i]
         if !isa(key, AbstractString)

src/MAT_v5.jl

@@ -152,7 +152,7 @@ function read_data(f::IO, swap_bytes::Bool, ::Type{T}, dimensions::Vector{Int32}
 end
 
 function read_cell(f::IO, swap_bytes::Bool, dimensions::Vector{Int32})
-    data = Array{Any}(convert(Vector{Int}, dimensions)...)
+    data = Array{Any}(undef, convert(Vector{Int}, dimensions)...)
     for i = 1:length(data)
         (ignored_name, data[i]) = read_matrix(f, swap_bytes)
     end
@@ -168,11 +168,11 @@ function read_struct(f::IO, swap_bytes::Bool, dimensions::Vector{Int32}, is_obje
     n_fields = div(length(field_names), field_length)
 
     # Get field names as strings
-    field_name_strings = Vector{String}(n_fields)
+    field_name_strings = Vector{String}(undef, n_fields)
     n_el = prod(dimensions)
     for i = 1:n_fields
         sname = field_names[(i-1)*field_length+1:i*field_length]
-        index = findfirst(sname, 0)
+        index = something(findfirst(iszero, sname), 0)
         field_name_strings[i] = String(index == 0 ? sname : sname[1:index-1])
     end
 
@@ -190,7 +190,7 @@ function read_struct(f::IO, swap_bytes::Bool, dimensions::Vector{Int32}, is_obje
     else
         # Read multiple structs into a dict of arrays
         for field_name in field_name_strings
-            data[field_name] = Array{Any}(dimensions...)
+            data[field_name] = Array{Any}(undef, dimensions...)
         end
         for i = 1:n_el
             for field_name in field_name_strings
@@ -257,7 +257,7 @@ function read_string(f::IO, swap_bytes::Bool, dimensions::Vector{Int32})
         if dimensions[1] <= 1
             data = String(chars)
         else
-            data = Vector{String}(dimensions[1])
+            data = Vector{String}(undef, dimensions[1])
             for i = 1:dimensions[1]
                 data[i] = rstrip(String(chars[i:dimensions[1]:end]))
             end
@@ -310,7 +310,7 @@ function read_matrix(f::IO, swap_bytes::Bool)
         #     a = {[], [], []}
         # then MATLAB does not save the empty cells as zero-byte matrices. To avoid
         # surprises, we produce an empty array in both cases.
-        return ("", Matrix{Union{}}(0, 0))
+        return ("", Matrix{Union{}}(undef, 0, 0))
     end
 
     flags = read_element(f, swap_bytes, UInt32)

test/read.jl

@@ -1,4 +1,10 @@
-using MAT, Base.Test
+using MAT
+
+@static if VERSION < v"0.7-"
+    using Base.Test
+else
+    using Test
+end
 
 function check(filename, result)
     matfile = matopen(filename)
@@ -45,7 +51,7 @@ end
 
 global format
 for _format in ["v6", "v7", "v7.3"]
-    format = _format
+    global format = _format
     cd(joinpath(dirname(@__FILE__), format))
 
     result = Dict(
@@ -72,7 +78,7 @@ for _format in ["v6", "v7", "v7.3"]
     end
 
     result = Dict(
-        "imaginary" => Complex128[1 -1 1+im 1-im -1+im -1-im im]
+        "imaginary" => ComplexF64[1 -1 1+im 1-im -1+im -1-im im]
     )
     check("complex.mat", result)
 
@@ -89,7 +95,7 @@ for _format in ["v6", "v7", "v7.3"]
         "a1x2" => [1.0 2.0],
         "a2x1" => zeros(2, 1)+[1.0, 2.0],
         "a2x2" => [1.0 3.0; 4.0 2.0],
-        "a2x2x2" => cat(3, [1.0 3.0; 4.0 2.0], [1.0 2.0; 3.0 4.0]),
+        "a2x2x2" => Compat.cat([1.0 3.0; 4.0 2.0], [1.0 2.0; 3.0 4.0], dims=3),
         "empty" => zeros(0, 0),
         "string" => "string"
     )
@@ -127,8 +133,8 @@ for _format in ["v6", "v7", "v7.3"]
     check("empty_cells.mat", result)
 
     result = Dict(
-        "sparse_empty" => sparse(Matrix{Float64}(0, 0)),
-        "sparse_eye" => speye(20),
+        "sparse_empty" => sparse(Matrix{Float64}(undef, 0, 0)),
+        "sparse_eye" => sparse(1.0I, 20, 20),
         "sparse_logical" => SparseMatrixCSC{Bool,Int64}(5, 5, [1:6;], [1:5;], fill(true, 5)),
         "sparse_random" => sparse([0 6. 0; 8. 0 1.; 0 0 9.]),
         "sparse_complex" => sparse([0 6. 0; 8. 0 1.; 0 0 9.]*(1. + 1.0im)),

test/runtests.jl

@@ -1,2 +1,4 @@
+using Compat
+
 include("read.jl")
 include("write.jl")

test/write.jl

@@ -33,10 +33,10 @@ test_write(Dict(
 ))
 
 test_write(Dict(
-	"Complex128" => [1.0 -1.0 1.0+1.0im 1.0-1.0im -1.0+1.0im -1.0-1.0im 1.0im],
+	"ComplexF64" => [1.0 -1.0 1.0+1.0im 1.0-1.0im -1.0+1.0im -1.0-1.0im 1.0im],
 	"ComplexPair" => [1 2-3im 4+5im]
 ))
-test_write(Dict("Complex128" => 1.0im, "ComplexPair" => 2-3im))
+test_write(Dict("ComplexF64" => 1.0im, "ComplexPair" => 2-3im))
 
 test_write(Dict(
 	"simple_string" => "the quick brown fox",
@@ -50,7 +50,7 @@ test_write(Dict(
 	"a1x2" => [1.0 2.0],
 	"a2x1" => zeros(2, 1)+[1.0, 2.0],
 	"a2x2" => [1.0 3.0; 4.0 2.0],
-	"a2x2x2" => cat(3, [1.0 3.0; 4.0 2.0], [1.0 2.0; 3.0 4.0]),
+	"a2x2x2" => Compat.cat([1.0 3.0; 4.0 2.0], [1.0 2.0; 3.0 4.0], dims=3),
 	"empty" => zeros(0, 0),
 	"string" => "string"
 ))
@@ -69,8 +69,8 @@ test_write(Dict(
 ))
 
 test_write(Dict(
-	"sparse_empty" => sparse(Matrix{Float64}(0, 0)),
-	"sparse_eye" => speye(20),
+	"sparse_empty" => sparse(Matrix{Float64}(undef, 0, 0)),
+	"sparse_eye" => sparse(1.0I, 20, 20),
 	"sparse_logical" => SparseMatrixCSC{Bool,Int64}(5, 5, [1:6;], [1:5;], fill(true, 5)),
 	"sparse_random" => sparse([0 6. 0; 8. 0 1.; 0 0 9.]),
 	"sparse_complex" => sparse([0 6. 0; 8. 0 1.; 0 0 9.]*(1. + 1.0im)),
@@ -100,7 +100,7 @@ close(fid)
 using DataStructures
 sd = SortedDict(Dict(
 	"uint16" => UInt16(1),
-	"Complex128" => [1.0 -1.0 1.0+1.0im 1.0-1.0im -1.0+1.0im -1.0-1.0im 1.0im],
+	"ComplexF64" => [1.0 -1.0 1.0+1.0im 1.0-1.0im -1.0+1.0im -1.0-1.0im 1.0im],
 	"simple_string" => "the quick brown fox",
 	"a1x2" => [1.0 2.0],
 	"sparse_empty" => sparse(Matrix{Float64}(0, 0))