You'll see why if you type `methods(mmap_array)`: the dims has to be represented as a tuple.
Currently, the only way I know of to create a fixed-sized buffer as an element of a "struct" in julia is via immutables with one field per object. Here's one example: https://github.com/JuliaGPU/CUDArt.jl/blob/1742a19b35a52ecec4ee14cfbec823f8bcb22e0f/gen/gen_libcudart_h.jl#L403-L660 It has not escaped notice that this is less than ideal :-). --Tim On Friday, November 21, 2014 11:57:10 AM Joshua Adelman wrote: > I'm playing around with Julia for the first time in an attempt to see if I > can replace a Python + Cython component of a system I'm building. Basically > I have a file of bytes representing a numpy structured/recarray (in memory > this is an array of structs). This gets memory mapped into a numpy array as > (Python code): > > f = open(data_file, 'r+') > cmap = mmap.mmap(f.fileno(), nbytes) > data_array = np.ndarray(size, dtype=dtype, buffer=cmap) > > > where dtype=[('x', np.int32), ('y', np.float64), ('name', 'S17')]. > > In cython I would create a C packed struct and to deal with the fixed > length string elements, I would specify them as char[N] arrays: > > cdef packed struct atype: > np.int32_t x > np.float64 y > char[17] name > > I'm trying to figure out how I would accomplish something similar in Julia. > Setting aside the issue of the fixed length strings for a moment, I thought > to initially create a composite type: > > immutable AType > x::Int32 > y::Float64 > name::??? > end > > and then if I had an file containing 20 records use: > > f = open("test1.dat", "r") > data = mmap_array(AType, 20, f) > > but I get an error: > > ERROR: `mmap_array` has no method matching mmap_array(::Type{AType}, > > ::Int64, ::IOStream) > > Is there a way to memory map a file into an array of custom > records/composite types in Julia? And if there is, how should one represent > the fixed length string fields? > > Any suggestions would be much appreciated. > > Josh
