function barrier in npzreadarray and introduce readheader

[jishnub]

This PR does two things:

• Make the Header type parametric and concrete: this seems to cut down on allocations while reading arrays

On master:

julia> npzwrite("abc.npy", ones(3,4));

julia> @btime npzread("abc.npy");
  23.639 μs (91 allocations: 5.80 KiB)

After this PR:

julia> @btime npzread("abc.npy");
  20.911 μs (80 allocations: 5.28 KiB)

The difference in run-time is marginal.

• Introduce a function readheader that returns the header. This might be convenient to get the eltype and size of the array without reading it in (eg. to pre-allocate an array of the correct size). This function is not exported.

julia> npzwrite("abc.npy", ones(3,4));

julia> NPZ.readheader("abc.npy")
NPZ.Header{Float64,2,typeof(ltoh)}(ltoh, true, (3, 4))

julia> NPZ.readheader("abc.npy") |> size
(3, 4)

julia> NPZ.readheader("abc.npy") |> eltype
Float64

[codecov-io]

Codecov Report

Merging #44 (37374e4) into master (9a66947) will increase coverage by 0.85%. The diff coverage is 92.10%.

@@            Coverage Diff             @@
##           master      #44      +/-   ##
==========================================
+ Coverage   85.29%   86.15%   +0.85%     
==========================================
  Files           1        1              
  Lines         170      195      +25     
==========================================
+ Hits          145      168      +23     
- Misses         25       27       +2     

Impacted Files	Coverage Δ
src/NPZ.jl	86.15% <92.10%> (+0.85%)	:arrow_up:

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[jishnub]

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[fhs]

Thank you for your package! Could you tag a new version by commenting @JuliaRegistrator register on the merged commit?

Ok, commented

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