RW support for function handles

src/MAT.jl

@@ -37,7 +37,7 @@ include("MAT_v4.jl")
 using .MAT_HDF5, .MAT_v5, .MAT_v4, .MAT_subsys
 
 export matopen, matread, matwrite, @read, @write
-export MatlabStructArray, MatlabClassObject, MatlabOpaque, MatlabTable
+export MatlabStructArray, MatlabClassObject, MatlabOpaque, MatlabTable, FunctionHandle
 
 # Open a MATLAB file
 const HDF5_HEADER = UInt8[0x89, 0x48, 0x44, 0x46, 0x0d, 0x0a, 0x1a, 0x0a]

src/MAT_HDF5.jl

@@ -45,7 +45,8 @@ import ..MAT_types:
     MatlabStructArray,
     MatlabTable,
     ScalarOrArray,
-    StructArrayField
+    StructArrayField,
+    FunctionHandle
 
 const HDF5Parent = Union{HDF5.File, HDF5.Group}
 const HDF5BitsOrBool = Union{HDF5.BitsType,Bool}
@@ -160,6 +161,10 @@ const object_type_attr_matlab = "MATLAB_object_decode"
 const object_decode_attr_matlab = "MATLAB_object_decode"
 const struct_field_attr_matlab = "MATLAB_fields"
 
+const matlab_function_decode = UInt32(1)
+const matlab_object_decode = UInt32(2)
+const matlab_opaque_decode = UInt32(3)
+
 ### Reading
 function read_complex(dtype::HDF5.Datatype, dset::HDF5.Dataset, ::Type{T}) where T
     if !check_datatype_complex(dtype)
@@ -324,7 +329,9 @@ function m_read(g::HDF5.Group, subsys::Subsystem)
         if haskey(attr, sparse_attr_matlab)
             return read_sparse_matrix(g, mattype)
         elseif mattype == "function_handle"
-            # TODO: fall through for now, will become a Dict
+            if haskey(attr, object_decode_attr_matlab) && read_attribute(g, object_decode_attr_matlab)==1
+                is_object = true
+            end
         else
             if haskey(attr, object_decode_attr_matlab) && read_attribute(g, object_decode_attr_matlab)==2
                 # I think this means it's an old object class similar to mXOBJECT_CLASS in MAT_v5
@@ -727,6 +734,22 @@ function check_struct_keys(k::Vector)
     asckeys
 end
 
+function m_write(mfile::MatlabHDF5File, parent::HDF5Parent, name::String, obj::FunctionHandle)
+    g = create_group(parent, name)
+    try
+        write_attribute(g, name_type_attr_matlab, "function_handle")
+        write_attribute(g, object_decode_attr_matlab, matlab_function_decode)
+        obj_struct = obj.d
+        all_keys = collect(keys(obj_struct))
+        _write_struct_fields(mfile, g, all_keys)
+        for (ki, vi) in zip(all_keys, values(obj_struct))
+            m_write(mfile, g, ki, vi)
+        end
+    finally
+        close(g)
+    end
+end
+
 function m_write(mfile::MatlabHDF5File, parent::HDF5Parent, name::String, arr::AbstractArray{MatlabClassObject})
     m_write(mfile, parent, name, MatlabStructArray(arr))
 end
@@ -735,7 +758,7 @@ function m_write(mfile::MatlabHDF5File, parent::HDF5Parent, name::String, obj::M
     g = create_group(parent, name)
     try
         write_attribute(g, name_type_attr_matlab, obj.class)
-        write_attribute(g, object_decode_attr_matlab, UInt32(2))
+        write_attribute(g, object_decode_attr_matlab, matlab_object_decode)
         all_keys = collect(keys(obj))
         _write_struct_fields(mfile, g, all_keys)
         for (ki, vi) in zip(all_keys, values(obj))
@@ -825,7 +848,7 @@ function m_write(mfile::MatlabHDF5File, parent::HDF5Parent, name::String, obj::M
     try
         write_dataset(dset, dtype, metadata)
         write_attribute(dset, name_type_attr_matlab, obj.class)
-        write_attribute(dset, object_type_attr_matlab, UInt32(3))
+        write_attribute(dset, object_type_attr_matlab, matlab_opaque_decode)
     finally
         close(dset)
         close(dtype)
@@ -839,7 +862,7 @@ function m_write(mfile::MatlabHDF5File, parent::HDF5Parent, name::String, obj::A
         # TODO: Handle empty array case
         write_dataset(dset, dtype, metadata)
         write_attribute(dset, name_type_attr_matlab, first(obj).class)
-        write_attribute(dset, object_type_attr_matlab, UInt32(3))
+        write_attribute(dset, object_type_attr_matlab, matlab_opaque_decode)
     finally
         close(dset)
         close(dtype)

src/MAT_subsys.jl

@@ -36,7 +36,8 @@ const MCOS_IDENTIFIER = 0xdd000000
 
 const matlab_saveobj_ret_types = String[
     "string",
-    "timetable"
+    "timetable",
+    "function_handle_workspace"
 ]
 
 # Warning message for unknown regions
@@ -556,22 +557,27 @@ end
 
 save_nested_props(prop_value, subsys::Subsystem) = prop_value
 
+# Prop values are copied to avoid mutating original with object metadata
+# Should be cheap as underlying data will be shared by reference unless modified
+
 function save_nested_props(
     prop_value::Union{AbstractDict,MatlabStructArray}, subsys::Subsystem
 )
     # Save nested objects in structs
+    prop_value_copy = copy(prop_value)
     for (key, value) in prop_value
-        prop_value[key] = save_nested_props(value, subsys)
+        prop_value_copy[key] = save_nested_props(value, subsys)
     end
-    return prop_value
+    return prop_value_copy
 end
 
 function save_nested_props(prop_value::Array{Any}, subsys::Subsystem)
     # Save nested objects in a Cell
+    prop_value_copy = copy(prop_value)
     for i in eachindex(prop_value)
-        prop_value[i] = save_nested_props(prop_value[i], subsys)
+        prop_value_copy[i] = save_nested_props(prop_value[i], subsys)
     end
-    return prop_value
+    return prop_value_copy
 end
 
 function save_nested_props(prop_value::Union{MatlabOpaque, Array{MatlabOpaque}}, subsys::Subsystem)
@@ -581,8 +587,8 @@ function save_nested_props(prop_value::Union{MatlabOpaque, Array{MatlabOpaque}},
 
     # FIXME: Does this overwrite prop_value from the user dict?
     # Might have to create a copy instead - Test needed
-    prop_value = set_mcos_object_metadata(subsys, prop_value)
-    return prop_value
+    prop_metadata = set_mcos_object_metadata(subsys, prop_value)
+    return prop_metadata
 end
 
 function serialize_object_props!(subsys::Subsystem, obj::MatlabOpaque, obj_prop_metadata::Vector{UInt32})
@@ -629,7 +635,7 @@ function set_object_id(subsys::Subsystem, obj::MatlabOpaque, saveobj_ret_type=fa
         # This is a deleted object
         # MATLAB keeps weak references to deleted objects for some reason
         class_id = set_class_id!(subsys, obj.class)
-        obj_id = 0
+        obj_id = UInt32(0)
         return obj_id, class_id
     end
 

src/MAT_types.jl

@@ -41,6 +41,7 @@ export MatlabClassObject
 export MatlabOpaque, convert_opaque
 export MatlabTable
 export ScalarOrArray
+export FunctionHandle
 
 const ScalarOrArray{T} = Union{T, AbstractArray{T}}
 
@@ -176,7 +177,7 @@ function Base.:(==)(m1::MatlabStructArray{N}, m2::MatlabStructArray{N}) where {N
 end
 
 function Base.isapprox(m1::MatlabStructArray, m2::MatlabStructArray; kwargs...)
-    return isequal(m1.class, m2.class) && issetequal(m1.names, m2.names) && 
+    return isequal(m1.class, m2.class) && issetequal(m1.names, m2.names) &&
     key_based_isapprox(m1.names, m1, m2; kwargs...)
 end
 
@@ -300,6 +301,13 @@ struct EmptyStruct
 end
 class(m::EmptyStruct) = ""
 
+"""
+Function Handles which are stored as structs
+"""
+struct FunctionHandle
+    d::Dict{String,Any}
+end
+
 """
     MatlabClassObject(
         d::Dict{String, Any},
@@ -357,6 +365,8 @@ function convert_struct_array(d::AbstractDict{String,Any}, class::String="")
     else
         if isempty(class)
             return d
+        elseif class == "function_handle"
+            return FunctionHandle(d)
         else
             return MatlabClassObject(d, class)
         end

src/MAT_v5.jl

@@ -28,7 +28,7 @@
 module MAT_v5
 using CodecZlib, HDF5, SparseArrays
 import Base: read, write, close
-import ..MAT_types: MatlabStructArray, MatlabClassObject, MatlabTable
+import ..MAT_types: MatlabStructArray, MatlabClassObject, MatlabTable, FunctionHandle
 
 using ..MAT_subsys
 
@@ -325,6 +325,11 @@ function read_string(f::IO, swap_bytes::Bool, dimensions::Vector{Int32})
     data
 end
 
+function read_function_handle(f::IO, swap_bytes::Bool, subsys::Subsystem)
+    data = read_matrix(f, swap_bytes, subsys)[2] # read_matrix returns (var_name, data)
+    return FunctionHandle(data)
+end
+
 function read_opaque(f::IO, swap_bytes::Bool, subsys::Subsystem)
     type_name = String(read_element(f, swap_bytes, UInt8))
     classname = String(read_element(f, swap_bytes, UInt8))
@@ -375,7 +380,7 @@ function read_matrix(f::IO, swap_bytes::Bool, subsys::Subsystem)
     elseif class == mxCHAR_CLASS && length(dimensions) <= 2
         data = read_string(f, swap_bytes, dimensions)
     elseif class == mxFUNCTION_CLASS
-        data = read_matrix(f, swap_bytes, subsys)
+        data = read_function_handle(f, swap_bytes, subsys)
     elseif class == mxOPAQUE_CLASS
         data = read_opaque(f, swap_bytes, subsys)
     else

test/read.jl

@@ -219,17 +219,6 @@ let objtestfile = "figure.fig"
     @test vars["hgS_070000"]["type"] == "figure"
 end
 
-# test reading file containing Matlab function handle, table, and datetime objects
-let objtestfile = "function_handles.mat"
-    vars = matread(joinpath(dirname(@__FILE__), "v7.3", objtestfile))
-    @test "sin" in keys(vars)
-    @test typeof(vars["sin"]) == Dict{String, Any}
-    @test Set(keys(vars["sin"])) == Set(["function_handle", "sentinel", "separator", "matlabroot"])
-    @test "anonymous" in keys(vars)
-    @test typeof(vars["anonymous"]) == Dict{String, Any}
-    @test Set(keys(vars["anonymous"])) == Set(["function_handle", "sentinel", "separator", "matlabroot"])
-end
-
 for format in ["v7", "v7.3"]
     @testset "struct_table_datetime $format" begin
     let objtestfile = "struct_table_datetime.mat"

test/write.jl

@@ -15,8 +15,8 @@ function test_write_data(data; approx = false, kwargs...)
     end
 
     if approx
-        @test MAT.MAT_types.dict_isapprox(result, data)  
-    else  
+        @test MAT.MAT_types.dict_isapprox(result, data)
+    else
         @test isequal(result, data)
     end
 end
@@ -355,3 +355,28 @@ end
     test_write(Dict{String,Any}("ms" => ms))
     test_write(Dict{String,Any}("ms" => [ms, Millisecond(50000)]))
 end
+
+@testset "function handles" begin
+    let objtestfile = "function_handles.mat"
+        filepath = joinpath(dirname(@__FILE__), "v7.3", objtestfile)
+        vars = matread(filepath)
+
+        mktempdir() do tmpdir
+            tmpfile = joinpath(tmpdir, "test.mat")
+            matwrite(tmpfile, vars)
+            vars_write = matread(tmpfile)
+
+            @test haskey(vars_write, "sin")
+            @test haskey(vars_write, "anonymous")
+
+            @test isa(vars_write["sin"], FunctionHandle)
+            @test isa(vars_write["anonymous"], FunctionHandle)
+
+            @test Set(keys(vars_write["sin"].d)) == Set(["function_handle", "sentinel", "separator", "matlabroot"])
+            @test Set(keys(vars_write["anonymous"].d)) == Set(["function_handle", "sentinel", "separator", "matlabroot"])
+
+            @test isequal(vars_write["sin"].d, vars["sin"].d)
+            @test isequal(vars_write["anonymous"].d, vars["anonymous"].d)
+        end
+    end
+end