Yet another PR for Julia v1

.travis.yml

@@ -3,14 +3,16 @@ os:
     - linux
     - osx
 julia:
-    - 0.6
-    - 0.7
     - 1.0
+    - 1.1
     - nightly
+addons:
+#  apt:
+#    packages:
+#        - hdf5-tools
+before_script:
+#    - if [ $TRAVIS_OS_NAME = osx ]; then brew install gcc; brew link --overwrite gcc; brew install hdf5; fi
 notifications:
     email: false
-script:
-    - if [[ -a .git/shallow ]]; then git fetch --unshallow; fi
-    - julia -e 'Pkg.clone(pwd()); Pkg.build("MAT"); Pkg.test("MAT"; coverage=true)'
 after_success:
     - julia -e 'cd(Pkg.dir("MAT")); Pkg.add("Coverage"); using Coverage; Coveralls.submit(Coveralls.process_folder())'

REQUIRE

@@ -1,5 +1,4 @@
-julia 0.6
-HDF5
+julia 0.7
+HDF5 0.11.0
 BufferedStreams 0.2.0
 Libz
-Compat 1.0

src/MAT.jl

@@ -22,12 +22,9 @@
 # OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION
 # WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
 
-VERSION >= v"0.4.0-dev+6521" && __precompile__()
-
 module MAT
 
-using HDF5, Compat
-using Compat.SparseArrays
+using HDF5, SparseArrays
 
 include("MAT_HDF5.jl")
 include("MAT_v5.jl")
@@ -144,7 +141,7 @@ end
 Write a dictionary containing variable names as keys and values as values
 to a Matlab file, opening and closing it automatically.
 """
-function matwrite(filename::AbstractString, dict::AbstractDict{S, T}) where {S,T}
+function matwrite(filename::AbstractString, dict::AbstractDict{S, T}) where {S, T}
     file = matopen(filename, "w")
     try
         for (k, v) in dict

src/MAT_HDF5.jl

@@ -28,15 +28,7 @@
 
 module MAT_HDF5
 
-using HDF5
-using Compat
-using Compat.SparseArrays
-
-@static if VERSION < v"0.7-"
-    _finalizer(f, x) = finalizer(x, f)
-else
-    _finalizer = finalizer
-end
+using HDF5, SparseArrays
 
 import Base: read, write, close
 import HDF5: names, exists, HDF5ReferenceObj, HDF5BitsKind
@@ -53,7 +45,7 @@ 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(close, f)
+            finalizer(close, f)
         end
         f
     end
@@ -70,7 +62,11 @@ function close(f::MatlabHDF5File)
         if f.writeheader
             magic = zeros(UInt8, 512)
             identifier = "MATLAB 7.3 MAT-file" # minimal but sufficient
-            magic[1:length(identifier)] = Vector{UInt8}(identifier)
+            GC.@preserve magic identifier begin
+                magicptr = pointer(magic)
+                idptr = pointer(identifier)
+                unsafe_copyto!(magicptr, idptr, length(identifier))
+            end
             magic[126] = 0x02
             magic[127] = 0x49
             magic[128] = 0x4d
@@ -123,7 +119,7 @@ const sparse_attr_matlab = "MATLAB_sparse"
 const int_decode_attr_matlab = "MATLAB_int_decode"
 
 ### Reading
-function read_complex(dtype::HDF5Datatype, dset::HDF5Dataset, ::Type{Array{T}}) where {T}
+function read_complex(dtype::HDF5Datatype, dset::HDF5Dataset, ::Type{Array{T}}) where T
     if !check_datatype_complex(dtype)
         close(dtype)
         error("Unrecognized compound data type when reading ", name(dset))
@@ -301,7 +297,7 @@ toarray(x::Bool) = UInt8[x]
 toarray(x) = [x]
 
 # Write the MATLAB type string for dset
-m_writetypeattr(dset, ::Type{Complex{T}}) where {T} = m_writetypeattr(dset, T)
+m_writetypeattr(dset, ::Type{Complex{T}}) where T = m_writetypeattr(dset, T)
 function m_writetypeattr(dset, T)
     if !haskey(type2str_matlab, T)
         error("Type ", T, " is not (yet) supported")
@@ -316,7 +312,7 @@ function m_writetypeattr(dset, T)
 end
 
 # Writes an empty scalar or array
-function m_writeempty(parent::HDF5Parent, name::String, data::Array)
+function m_writeempty(parent::HDF5Parent, name::String, data::AbstractArray)
     adata = [size(data)...]
     dset, dtype = d_create(parent, name, adata)
     try
@@ -330,7 +326,7 @@ function m_writeempty(parent::HDF5Parent, name::String, data::Array)
 end
 
 # Write an array to a dataset in a MATLAB file, returning the dataset
-function m_writearray(parent::HDF5Parent, name::String, adata::Array{T}) where {T<:HDF5BitsOrBool}
+function m_writearray(parent::HDF5Parent, name::String, adata::AbstractArray{T}) where {T<:HDF5BitsOrBool}
     dset, dtype = d_create(parent, name, adata)
     try
         HDF5.writearray(dset, dtype.id, adata)
@@ -342,14 +338,14 @@ function m_writearray(parent::HDF5Parent, name::String, adata::Array{T}) where {
         close(dtype)
     end
 end
-function m_writearray(parent::HDF5Parent, name::String, adata::Array{Complex{T}}) where {T<:HDF5BitsOrBool}
+function m_writearray(parent::HDF5Parent, name::String, adata::AbstractArray{Complex{T}}) where {T<:HDF5BitsOrBool}
     dtype = build_datatype_complex(T)
     try
         stype = dataspace(adata)
         obj_id = HDF5.h5d_create(parent.id, name, dtype.id, stype.id)
         dset = HDF5Dataset(obj_id, file(parent))
         try
-            arr = reinterpret(T, adata, tuple(2, size(adata)...))
+            arr = reshape(reinterpret(T, adata), tuple(2, size(adata)...))
             HDF5.writearray(dset, dtype.id, arr)
         catch e
             close(dset)
@@ -378,16 +374,16 @@ function m_write(mfile::MatlabHDF5File, parent::HDF5Parent, name::String, data::
 end
 
 # Write sparse arrays
-function m_write(mfile::MatlabHDF5File, parent::HDF5Parent, name::String, data::SparseMatrixCSC{T}) where {T}
+function m_write(mfile::MatlabHDF5File, parent::HDF5Parent, name::String, data::SparseMatrixCSC{T}) where T
     g = g_create(parent, name)
     try
         m_writetypeattr(g, T)
         a_write(g, sparse_attr_matlab, UInt64(size(data, 1)))
         if !isempty(data.nzval)
             close(m_writearray(g, "data", toarray(data.nzval)))
-            close(m_writearray(g, "ir", add!(isa(data.rowval, Vector{UInt64}) ? copy(data.rowval) : convert(Vector{UInt64}, data.rowval), reinterpret(UInt64, convert(Int64, -1)))))
+            close(m_writearray(g, "ir", add!(isa(data.rowval, Vector{UInt64}) ? copy(data.rowval) : convert(Vector{UInt64}, data.rowval), typemax(UInt64))))
         end
-        close(m_writearray(g, "jc", add!(isa(data.colptr, Vector{UInt64}) ? copy(data.colptr) : convert(Vector{UInt64}, data.colptr), reinterpret(UInt64, convert(Int64, -1)))))
+        close(m_writearray(g, "jc", add!(isa(data.colptr, Vector{UInt64}) ? copy(data.colptr) : convert(Vector{UInt64}, data.colptr), typemax(UInt64))))
     finally
         close(g)
     end
@@ -431,7 +427,7 @@ function m_write(mfile::MatlabHDF5File, parent::HDF5Parent, name::String, str::A
 end
 
 # Write cell arrays
-function m_write(mfile::MatlabHDF5File, parent::HDF5Parent, name::String, data::Array{T}) where {T}
+function m_write(mfile::MatlabHDF5File, parent::HDF5Parent, name::String, data::Array{T}) where T
     pathrefs = "/#refs#"
     fid = file(parent)
     local g
@@ -538,7 +534,7 @@ end
 
 ## Type conversion operations ##
 
-struct MatlabString; end
+struct MatlabString end
 
 const str2type_matlab = Dict(
     "canonical empty" => nothing,
@@ -607,14 +603,14 @@ function read(obj::HDF5Object, ::Type{Bool})
     tf = read(obj, UInt8)
     tf > 0
 end
-function read(obj::HDF5Object, ::Type{Array{Bool}})
+function read(obj::HDF5Dataset, ::Type{Array{Bool}})
     if HDF5.isnull(obj)
         return Bool[]
     end
     # Use the low-level HDF5 API to put the data directly into a Bool array
     tf = Array{Bool}(undef, size(obj))
     HDF5.h5d_read(obj.id, HDF5.hdf5_type_id(UInt8), tf, obj.xfer)
-    tf
+    return tf
 end
 
 ## Utilities for handling complex numbers

src/MAT_v5.jl

@@ -26,18 +26,12 @@
 # http://www.mathworks.com/help/pdf_doc/matlab/matfile_format.pdf
 
 module MAT_v5
-using Libz, BufferedStreams, HDF5, Compat
-using Compat.SparseArrays
+using Libz, BufferedStreams, HDF5, SparseArrays
 import Base: read, write, close
 import HDF5: names, exists
 
-if VERSION < v"0.6.0-dev.1632"
-    round_uint8(data) = round(UInt8, data)
-    complex_array(a, b) = complex(a, b)
-else
-    round_uint8(data) = round.(UInt8, data)
-    complex_array(a, b) = complex.(a, b)
-end
+round_uint8(data) = round.(UInt8, data)
+complex_array(a, b) = complex.(a, b)
 
 mutable struct Matlabv5File <: HDF5.DataFile
     ios::IOStream
@@ -85,9 +79,9 @@ const CONVERT_TYPES = Type[
     Union{}, Float64, Float32, Int8, UInt8,
     Int16, UInt16, Int32, UInt32, Int64, UInt64]
 
-read_bswap(f::IO, swap_bytes::Bool, ::Type{T}) where {T} =
+read_bswap(f::IO, swap_bytes::Bool, ::Type{T}) where T =
     swap_bytes ? bswap(read(f, T)) : read(f, T)
-function read_bswap(f::IO, swap_bytes::Bool, ::Type{T}, dim::Union{Int, Tuple{Vararg{Int}}}) where {T}
+function read_bswap(f::IO, swap_bytes::Bool, ::Type{T}, dim::Union{Int, Tuple{Vararg{Int}}}) where T
     d = read!(f, Array{T}(undef, dim))
     if swap_bytes
         for i = 1:length(d)
@@ -96,6 +90,15 @@ function read_bswap(f::IO, swap_bytes::Bool, ::Type{T}, dim::Union{Int, Tuple{Va
     end
     d
 end
+function read_bswap(f::IO, swap_bytes::Bool, d::AbstractArray{T}) where T
+    readbytes!(f, reinterpret(UInt8, d))
+    if swap_bytes
+        for i = 1:length(d)
+            @inbounds d[i] = bswap(d[i])
+        end
+    end
+    d
+end
 
 skip_padding(f::IO, nbytes::Int, hbytes::Int) = if nbytes % hbytes != 0
     skip(f, hbytes-(nbytes % hbytes))
@@ -115,7 +118,7 @@ function read_header(f::IO, swap_bytes::Bool)
 end
 
 # Read data element as a vector of a given type
-function read_element(f::IO, swap_bytes::Bool, ::Type{T}) where {T}
+function read_element(f::IO, swap_bytes::Bool, ::Type{T}) where T
     (dtype, nbytes, hbytes) = read_header(f, swap_bytes)
     data = read_bswap(f, swap_bytes, T, Int(div(nbytes, sizeof(T))))
     skip_padding(f, nbytes, hbytes)
@@ -134,7 +137,7 @@ end
 # Read data element as encoded type with given dimensions, converting
 # to another type if necessary and collapsing one-element matrices to
 # scalars
-function read_data(f::IO, swap_bytes::Bool, ::Type{T}, dimensions::Vector{Int32}) where {T}
+function read_data(f::IO, swap_bytes::Bool, ::Type{T}, dimensions::Vector{Int32}) where T
     (dtype, nbytes, hbytes) = read_header(f, swap_bytes)
     read_type = READ_TYPES[dtype]
     if (read_type === UInt8) && (T === Bool)
@@ -244,11 +247,7 @@ function read_sparse(f::IO, swap_bytes::Bool, dimensions::Vector{Int32}, flags::
     SparseMatrixCSC(m, n, jc, ir, pr)
 end
 
-if VERSION >= v"0.4.0-dev+1039"
-    truncate_to_uint8(x) = x % UInt8
-else
-    truncate_to_uint8(x) = convert(UInt8, x)
-end
+truncate_to_uint8(x) = x % UInt8
 
 function read_string(f::IO, swap_bytes::Bool, dimensions::Vector{Int32})
     (dtype, nbytes, hbytes) = read_header(f, swap_bytes)

test/read.jl

@@ -1,10 +1,4 @@
-using MAT
-
-@static if VERSION < v"0.7-"
-    using Base.Test
-else
-    using Test
-end
+using MAT, Test
 
 function check(filename, result)
     matfile = matopen(filename)
@@ -95,7 +89,7 @@ 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" => Compat.cat([1.0 3.0; 4.0 2.0], [1.0 2.0; 3.0 4.0], dims=3),
+        "a2x2x2" => 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"
     )
@@ -123,7 +117,7 @@ for _format in ["v6", "v7", "v7.3"]
             true false false
             false true false
             true false false
-        ]
+           ]
     )
     check("logical.mat", result)
 

test/runtests.jl

@@ -1,6 +1,4 @@
-using Compat
-using Compat.SparseArrays
-using Compat.LinearAlgebra
+using SparseArrays, LinearAlgebra
 
 include("read.jl")
 include("write.jl")

test/write.jl

@@ -1,6 +1,6 @@
 using MAT
 
-tmpfile = string(tempname, ".mat")
+tmpfile = string(tempname(), ".mat")
 
 function test_write(data)
 	matwrite(tmpfile, data)
@@ -33,6 +33,8 @@ test_write(Dict(
 ))
 
 test_write(Dict(
+	"ComplexInt" => Complex{Int}[1 -1 1+1im 1-1im -1+1im -1-1im 1im],
+	"ComplexF32" => ComplexF32[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]
 ))
@@ -50,7 +52,7 @@ 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" => Compat.cat([1.0 3.0; 4.0 2.0], [1.0 2.0; 3.0 4.0], dims=3),
+	"a2x2x2" => 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"
 ))
@@ -81,7 +83,7 @@ test_write(Dict(
 @test_throws ErrorException test_write(Dict("another invalid key" => "invalid characters"))
 @test_throws ErrorException test_write(Dict("yetanotherinvalidkeyyetanotherinvalidkeyyetanotherinvalidkeyyetanotherinvalidkey" => "too long"))
 
-type TestCompositeKind
+struct TestCompositeKind
 	field1::AbstractString
 end
 fid = matopen(tmpfile, "w")
@@ -103,6 +105,6 @@ sd = SortedDict(Dict(
 	"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))
+	"sparse_empty" => sparse(Matrix{Float64}(undef, 0, 0))
 ))
 test_write(sd)