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Julia extensions to provide high performance computational support

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While invoking the Pkg.update() command in Julia 1.0: ERROR: Unsatisfiable requirements detected for package NumericExtensions [d47e95ee]: NumericExtensions [d47e95ee] log: ├─possible versions are: [0.2.0-0.2.2, 0.2.4-0.2.20, 0.3.0-0.3.6, 0.4.0-0.4.3, 0.5.0-0.5.6, 0.6.0-0.6.2] or uninstalled...

julia> using NumericExtensions: logsumexp INFO: Precompiling module ArrayViews. WARNING: Method definition (::Type{ArrayViews.UnsafeContiguousView})(Ptr{#T

On Julia Version 0.4.1-pre+16 (2015-10-24 06:33 UTC) Commit 2cdef5d (5 days old release-0.4) x86_64-redhat-linux I get the error below as soon as I type julia> using NumericExtensions ERROR: LoadError: LoadError:...

I am just starting to move some of my code from Julia 0.3 to the new 0.4 release. When I discovered NumericExtensions in 0.3 it dramatically sped up some of...

just to let you know: ``` julia> using NumericExtensions Warning: could not import Base.add! into NumericExtensions WARNING: deprecated syntax "(ASCIIString=>Int)[]" at /home/workerm/.julia/v0.4/NumericExtensions/src/benchmark.jl:16. Use "Dict{ASCIIString,Int}()" instead. julia> ``` julia> versioninfo() Julia...

The only changes since the last tagged version are to a couple of imports and to the documentation, so I don't think a new tagged version will break anything, but...

[PackageEvaluator.jl](https://github.com/IainNZ/PackageEvaluator.jl) is a script that runs nightly. It attempts to load all Julia packages and run their tests (if available) on both the stable version of Julia (0.3) and the...

Hi everyone, I am an R and MATLAB user who is moving to Julia. I am trying the Numeric Extensions package. In the documentation (http://numericextensionsjl.readthedocs.org/en/latest/functors.html), they show an example of...

With 440c9bcdf2204d85e6dc31231eb0c8208756fd1b: ``` julia> mean([1, 2], 1) ERROR: InexactError() in scale! at linalg/generic.jl:16 julia> @which mean([1, 2], 1) mean(::DenseArray{T

``` jlcon julia> a = [ i*j for i in 0.0:3.0, j in 0.0:4.0] 4x5 Array{Float64,2}: 0.0 0.0 0.0 0.0 0.0 0.0 1.0 2.0 3.0 4.0 0.0 2.0 4.0 6.0...