[julia-users] Re: Deprecation warnings using julia on Atom

[colintbowers]

The problem magically fixed itself today. I was running a Pkg.checkout() on 
"Distributions" to move to the master branch there to get rid of 
deprecation warnings generated by qq.jl. In the process, I ran a 
Pkg.update(), and re-compiled other pre-compiled packages. Problem gone.

At this stage I've only one possible explanation. I had not re-compiled 
Atom.jl and CodeTools.jl since moving the master branch for the Atom 
plugins "language-julia", "julia-client", and "ink". Perhaps the order 
there is important, i.e. one needs to move to master branch for Atom 
plugins, and THEN move to master branch for Atom.jl and CodeTools.jl and 
pre-compile. I could test this theory out I suppose, but then I face the 
very real possibility of re-introducing the problem and not being able to 
get rid of it...

I hope this is of help to someone.

Cheers,

Colin

On Wednesday, 28 October 2015 10:57:43 UTC+11, colint...@gmail.com wrote:
>
> Hi all,
>
> I'm using Julia v0.4 with the Atom package, on Atom 1.0 with the packages 
> ink, julia-client, and language-julia (and I'm really enjoying this as an 
> IDE solution).
>
> I can toggle the Julia console in Atom, and enter code directly into it 
> without any errors or warnings. However, as soon as I try to evaluate a 
> line of code from the Atom editor, I get a large number of deprecation 
> warnings, either of the form:
>
> WARNING: Base.Uint8 is deprecated, use UInt8 instead.
>   likely near no file:422
>
> or
>
> WARNING: Base.Uint8 is deprecated, use UInt8 instead.
>   likely near no file:422
> in skip at /home/colin/.julia/v0.4/LNR/src/LNR.jl:171
>
> Has anyone else encountered this and is there a fix? I had a look through 
> the LNR source, and there is nothing in it that should be triggering a 
> deprecation warning, nor is there even a line 171 (it only goes up to about 
> line 130).
>
> Note, I can just ignore the deprecation warnings, and continue on working 
> without a problem, so this isn't an urgent issue. Just wondering if I've 
> stuffed up the install process somehow.
>
> Cheers,
>
> Colin
>

[julia-users] question about Hessian in ForwardDiff return InexactError()

[Tony Kelman]

You probably need to initialize the destination array with a floating point, 
rather than integer, element type.

[julia-users] Re: [help]: configuring Julia and Sublime text 2 on windows 8.1

[John Wasa]

Donald,

I installed Julia 4.0 and Sublime-IJulia on Windows 7 (64bit).
Sublime shows that Ijulia kernel is working, but none of the shortcut keys 
(shift+Enter, Ctrl+Enter, etc.) are working.
Could you confirm that you also installed 64-bit Julia 4.0?  (My Version 
is: 0.4.0 (2015-10-08 06:20 UTC) Official http://julialang.org/ release 
x86_64-w64-mingw32)

Thanks.

Re: [julia-users] Re: installing julia via cygwin

[tony]

I searched the log for the word error.


The julia executable ends up at ./usr/bin/julia.exe, unlike a unix source build 
Windows doesn't support symbolic links very well so we do not create a ./julia 
convenience link.




On Sun, Nov 1, 2015 at 6:15 PM -0800, "Seth"  wrote:
It sounds like you don't have '.' in your path. In cygwin, in your bin
directory, type ./julia and see if that works.



On Sunday, November 1, 2015 at 3:31:42 PM UTC-8, digxx wrote:
>
> Thank you. After hours of compilation it finally finished without errors.
> Now I have the Julia.exe file in my bin folder but when trying to run it
> from there by typing
> Julia.exe or just Julia or -c Julia.exe it tells me: command not found?
>
> Btw: how did u see it was m4? I mean u didnt really read these 1000 lines
> of code?
> Vollständigen Inhalt anzeigen
>

[julia-users] question about Hessian in ForwardDiff return InexactError()

[jamesmnason]

Hi All:

I am trying to compute a Hessian of a log likelihood function in a 
Metropolis-Hastings MCMC algorithm.  The coefficient vector of the model 
has seven elements. 

A call to

   ForwardDiff.hessian(PF_RE_AR1_outer_alt, parms)

returns

ERROR: LoadError: InexactError()
 in setindex! at array.jl:314
 in PF_RE_AR1_outer_alt at 
/home/jim_nason/jmn_work/smith/NS4/jl_code_Summer2015/RE_rho/MH_PF_test/PF_RE_AR1_outer_alt.jl:55
 in _calc_hessian at 
/home/jim_nason/.julia/v0.4/ForwardDiff/src/api/hessian.jl:98

Lines 52 and 55 of PF_RE_AR1_outer_alt.jl are

 cs00V = eye(dsts)
 cs22n = sigu*sigu
 cs22d = 1/(1.0 - rho1*rho1)
cs00V[2,2] = cs22n*cs22d

where sigu and rho1 are two coefficients of the model restricted as sigu > 
0 and -1 < rho1 < 1 and dsts = 2.

Suggestions or advice to fix the problem are welcome.

Thanks.

Best,

Jim

[julia-users] Re: installing julia via cygwin

[Seth]

It sounds like you don't have '.' in your path. In cygwin, in your bin 
directory, type ./julia and see if that works.



On Sunday, November 1, 2015 at 3:31:42 PM UTC-8, digxx wrote:
>
> Thank you. After hours of compilation it finally finished without errors.
> Now I have the Julia.exe file in my bin folder but when trying to run it 
> from there by typing
> Julia.exe or just Julia or -c Julia.exe it tells me: command not found?
>
> Btw: how did u see it was m4? I mean u didnt really read these 1000 lines 
> of code?
> Vollständigen Inhalt anzeigen 
>

Re: [julia-users] IJulia not printing output

[Simon Kornblith]

Yes, I get normal output in a Python notebook.

On Sunday, November 1, 2015 at 7:57:55 PM UTC-5, Yichao Yu wrote:
>
> On Sun, Nov 1, 2015 at 7:25 PM, Simon Kornblith  > wrote: 
> > I'm trying to figure out why IJulia appears to stopped working for me. 
> It 
> > executes code, but it never prints the output. It looks like the kernel 
> is 
> > trying to send it back, but for some reason it's not making it back to 
> the 
> > client. With verbose = true, for a cell that contains println("hello 
> world") 
> > I see: 
>
> Possibly dumb question but does (I)Python kernel work? 
>
> > 
> > got msg part 0571B1504EE5BDDD5DD2FB31E826 
> > got msg part  
> > RECEIVED IPython Msg [ idents 0571B1504EE5BDDD5DD2FB31E826 ] { 
> >  header = 
> > 
> Dict{AbstractString,Any}("msg_id"=>"B1BF99EE7ECC4CFD8BD3EE2EF2ACBAF1","msg_type"=>"execute_request","username"=>"username","version"=>"5.0","session"=>"0
>  
>
> > 571B1504EE5BDDD5DD2FB31E826"), 
> >  metadata = Dict{AbstractString,Any}(), 
> >  content = 
> > 
> Dict{AbstractString,Any}("store_history"=>true,"user_expressions"=>Dict{AbstractString,Any}(),"allow_stdin"=>true,"code"=>"println(\"hello
>  
>
> > world\")","si 
> > lent"=>false,"stop_on_error"=>true) 
> > } 
> > SENDING IPython Msg [ idents status ] { 
> >  header = 
> > 
> Dict("msg_id"=>"638d0490-61db-4d5c-94c8-f8d88e154c5f","msg_type"=>"status","username"=>"jlkernel","version"=>"5.0","session"=>"0571B1504EE5BDDD5DD2FB
>  
>
> > 31E826"), 
> >  metadata = Dict{AbstractString,Any}(), 
> >  content = Dict("execution_state"=>"busy") 
> > } 
> > EXECUTING println("hello world") 
> > SENDING IPython Msg [ idents execute_input ] { 
> >  header = 
> > 
> Dict("msg_id"=>"312c5e9c-2981-4187-ba2a-a79f9bfbeb8a","msg_type"=>"execute_input","username"=>"username","version"=>"5.0","session"=>"0571B1504EE5BDD
>  
>
> > D5DD2FB31E826"), 
> >  metadata = Dict{AbstractString,Any}(), 
> >  content = Dict{ASCIIString,Any}("code"=>"println(\"hello 
> > world\")","execution_count"=>2) 
> > } 
> > SENDING IPython Msg [ idents stdout ] { 
> >  header = 
> > 
> Dict("msg_id"=>"052a8a7f-c576-4a71-a60e-546be2d6e25d","msg_type"=>"stream","username"=>"username","version"=>"5.0","session"=>"0571B1504EE5BDDD5DD2FB
>  
>
> > 31E826"), 
> >  metadata = Dict{AbstractString,Any}(), 
> >  content = Dict("name"=>"stdout","text"=>"hello world\n") 
> > } 
> > SENDING IPython Msg [ idents 0571B1504EE5BDDD5DD2FB31E826 ] { 
> >  header = 
> > 
> Dict("msg_id"=>"5b8b2b53-483d-4e3a-9b7d-99763a352266","msg_type"=>"execute_reply","username"=>"username","version"=>"5.0","session"=>"0571B1504EE5BDD
>  
>
> > D5DD2FB31E826"), 
> >  metadata = Dict{AbstractString,Any}(), 
> >  content = 
> > 
> Dict{ASCIIString,Any}("status"=>"ok","payload"=>"","user_expressions"=>Dict{Any,Any}(),"execution_count"=>2)
>  
>
> > } 
> > SENDING IPython Msg [ idents status ] { 
> >  header = 
> > 
> Dict("msg_id"=>"43a9b3d2-d335-4dde-a8ea-662aa25f30ce","msg_type"=>"status","username"=>"jlkernel","version"=>"5.0","session"=>"0571B1504EE5BDDD5DD2FB
>  
>
> > 31E826"), 
> >  metadata = Dict{AbstractString,Any}(), 
> >  content = Dict("execution_state"=>"idle") 
> > } 
> > 
> > But nothing shows up in the browser. This is probably an issue with my 
> > configuration, but I have no idea what. Any idea on how I could debug 
> this 
> > further? I have notebook server 4.0.6 and IJulia 1.1.8 on julia 
> 0.4.1-pre+8. 
> > 
> > Thanks, 
> > Simon 
>

Re: [julia-users] IJulia not printing output

[Yichao Yu]

On Sun, Nov 1, 2015 at 7:25 PM, Simon Kornblith  wrote:
> I'm trying to figure out why IJulia appears to stopped working for me. It
> executes code, but it never prints the output. It looks like the kernel is
> trying to send it back, but for some reason it's not making it back to the
> client. With verbose = true, for a cell that contains println("hello world")
> I see:

Possibly dumb question but does (I)Python kernel work?

>
> got msg part 0571B1504EE5BDDD5DD2FB31E826
> got msg part 
> RECEIVED IPython Msg [ idents 0571B1504EE5BDDD5DD2FB31E826 ] {
>  header =
> Dict{AbstractString,Any}("msg_id"=>"B1BF99EE7ECC4CFD8BD3EE2EF2ACBAF1","msg_type"=>"execute_request","username"=>"username","version"=>"5.0","session"=>"0
> 571B1504EE5BDDD5DD2FB31E826"),
>  metadata = Dict{AbstractString,Any}(),
>  content =
> Dict{AbstractString,Any}("store_history"=>true,"user_expressions"=>Dict{AbstractString,Any}(),"allow_stdin"=>true,"code"=>"println(\"hello
> world\")","si
> lent"=>false,"stop_on_error"=>true)
> }
> SENDING IPython Msg [ idents status ] {
>  header =
> Dict("msg_id"=>"638d0490-61db-4d5c-94c8-f8d88e154c5f","msg_type"=>"status","username"=>"jlkernel","version"=>"5.0","session"=>"0571B1504EE5BDDD5DD2FB
> 31E826"),
>  metadata = Dict{AbstractString,Any}(),
>  content = Dict("execution_state"=>"busy")
> }
> EXECUTING println("hello world")
> SENDING IPython Msg [ idents execute_input ] {
>  header =
> Dict("msg_id"=>"312c5e9c-2981-4187-ba2a-a79f9bfbeb8a","msg_type"=>"execute_input","username"=>"username","version"=>"5.0","session"=>"0571B1504EE5BDD
> D5DD2FB31E826"),
>  metadata = Dict{AbstractString,Any}(),
>  content = Dict{ASCIIString,Any}("code"=>"println(\"hello
> world\")","execution_count"=>2)
> }
> SENDING IPython Msg [ idents stdout ] {
>  header =
> Dict("msg_id"=>"052a8a7f-c576-4a71-a60e-546be2d6e25d","msg_type"=>"stream","username"=>"username","version"=>"5.0","session"=>"0571B1504EE5BDDD5DD2FB
> 31E826"),
>  metadata = Dict{AbstractString,Any}(),
>  content = Dict("name"=>"stdout","text"=>"hello world\n")
> }
> SENDING IPython Msg [ idents 0571B1504EE5BDDD5DD2FB31E826 ] {
>  header =
> Dict("msg_id"=>"5b8b2b53-483d-4e3a-9b7d-99763a352266","msg_type"=>"execute_reply","username"=>"username","version"=>"5.0","session"=>"0571B1504EE5BDD
> D5DD2FB31E826"),
>  metadata = Dict{AbstractString,Any}(),
>  content =
> Dict{ASCIIString,Any}("status"=>"ok","payload"=>"","user_expressions"=>Dict{Any,Any}(),"execution_count"=>2)
> }
> SENDING IPython Msg [ idents status ] {
>  header =
> Dict("msg_id"=>"43a9b3d2-d335-4dde-a8ea-662aa25f30ce","msg_type"=>"status","username"=>"jlkernel","version"=>"5.0","session"=>"0571B1504EE5BDDD5DD2FB
> 31E826"),
>  metadata = Dict{AbstractString,Any}(),
>  content = Dict("execution_state"=>"idle")
> }
>
> But nothing shows up in the browser. This is probably an issue with my
> configuration, but I have no idea what. Any idea on how I could debug this
> further? I have notebook server 4.0.6 and IJulia 1.1.8 on julia 0.4.1-pre+8.
>
> Thanks,
> Simon

[julia-users] Re: installing julia via cygwin

[Kristoffer Carlsson]

Try ./Julia.exe

[julia-users] IJulia not printing output

[Simon Kornblith]

I'm trying to figure out why IJulia appears to stopped working for me. It 
executes code, but it never prints the output. It looks like the kernel is 
trying to send it back, but for some reason it's not making it back to the 
client. With verbose = true, for a cell that contains println("hello 
world") I see:

got msg part 0571B1504EE5BDDD5DD2FB31E826 
got msg part  
RECEIVED IPython Msg [ idents 0571B1504EE5BDDD5DD2FB31E826 ] { 
 header = 
Dict{AbstractString,Any}("msg_id"=>"B1BF99EE7ECC4CFD8BD3EE2EF2ACBAF1","msg_type"=>"execute_request","username"=>"username","version"=>"5.0","session"=>"0
571B1504EE5BDDD5DD2FB31E826"), 
 metadata = Dict{AbstractString,Any}(), 
 content = 
Dict{AbstractString,Any}("store_history"=>true,"user_expressions"=>Dict{AbstractString,Any}(),"allow_stdin"=>true,"code"=>"println(\"hello
 
world\")","si
lent"=>false,"stop_on_error"=>true) 
} 
SENDING IPython Msg [ idents status ] { 
 header = 
Dict("msg_id"=>"638d0490-61db-4d5c-94c8-f8d88e154c5f","msg_type"=>"status","username"=>"jlkernel","version"=>"5.0","session"=>"0571B1504EE5BDDD5DD2FB
31E826"), 
 metadata = Dict{AbstractString,Any}(), 
 content = Dict("execution_state"=>"busy") 
} 
EXECUTING println("hello world") 
SENDING IPython Msg [ idents execute_input ] { 
 header = 
Dict("msg_id"=>"312c5e9c-2981-4187-ba2a-a79f9bfbeb8a","msg_type"=>"execute_input","username"=>"username","version"=>"5.0","session"=>"0571B1504EE5BDD
D5DD2FB31E826"), 
 metadata = Dict{AbstractString,Any}(), 
 content = Dict{ASCIIString,Any}("code"=>"println(\"hello 
world\")","execution_count"=>2) 
} 
SENDING IPython Msg [ idents stdout ] { 
 header = 
Dict("msg_id"=>"052a8a7f-c576-4a71-a60e-546be2d6e25d","msg_type"=>"stream","username"=>"username","version"=>"5.0","session"=>"0571B1504EE5BDDD5DD2FB
31E826"), 
 metadata = Dict{AbstractString,Any}(), 
 content = Dict("name"=>"stdout","text"=>"hello world\n") 
} 
SENDING IPython Msg [ idents 0571B1504EE5BDDD5DD2FB31E826 ] { 
 header = 
Dict("msg_id"=>"5b8b2b53-483d-4e3a-9b7d-99763a352266","msg_type"=>"execute_reply","username"=>"username","version"=>"5.0","session"=>"0571B1504EE5BDD
D5DD2FB31E826"), 
 metadata = Dict{AbstractString,Any}(), 
 content = 
Dict{ASCIIString,Any}("status"=>"ok","payload"=>"","user_expressions"=>Dict{Any,Any}(),"execution_count"=>2)
 

} 
SENDING IPython Msg [ idents status ] { 
 header = 
Dict("msg_id"=>"43a9b3d2-d335-4dde-a8ea-662aa25f30ce","msg_type"=>"status","username"=>"jlkernel","version"=>"5.0","session"=>"0571B1504EE5BDDD5DD2FB
31E826"), 
 metadata = Dict{AbstractString,Any}(), 
 content = Dict("execution_state"=>"idle") 
}

But nothing shows up in the browser. This is probably an issue with my 
configuration, but I have no idea what. Any idea on how I could debug this 
further? I have notebook server 4.0.6 and IJulia 1.1.8 on julia 0.4.1-pre+8.

Thanks,
Simon

Re: [julia-users] Re: Deprecation warnings using julia on Atom

[Colin Bowers]

Hi Jeremy,

This sounded promising, as at some point I did have IPython installed so I
could use Jacob Quinn's Sublime-IJulia package. It is possible that
something was left behind. However, unfortunately I haven't been able to
find anything that looks suspicious (I'm on Ubuntu 14.04). For those who
are interested, I was only able to locate the following files on my OS:

sudo find /home/colin -name "*ipython*" -print
/home/colin/.local/share/Trash/files/v0.3_OLD/IJulia/deps/ipython.jl
/home/colin/.julia/v0.3/IJulia/deps/ipython.jl

and

sudo find /usr -name "*ipython*" -print
/usr/share/app-install/icons/ipython.svg
/usr/share/app-install/icons/ipython3.svg
/usr/share/app-install/desktop/ipython3:ipython3.desktop
/usr/share/app-install/desktop/ipython:ipython.desktop
/usr/share/app-install/desktop/ipython-qtconsole:ipython-qtconsole.desktop
/usr/share/app-install/desktop/ipython3-qtconsole:ipython3-qtconsole.desktop
/usr/lib/calibre/calibre/utils/ipython.py

Searches for "*Jupyter*" did not turn up anything.

Cheers and thanks again for responding.

Colin



On 31 October 2015 at 21:29, Jeremy Cavanagh 
wrote:

> Hi Colin,
>
> I was having the same problems while trying to get julia to work in atom
> and was hoping that this thread would provide a solution. However, I was
> alao trying to get the hydrogen to work as well but kept getting an error
> which I could not figure out the cause so posted to an issue:
>
> https://github.com/willwhitney/hydrogen/issues/127#issuecomment-152661805
>
> After following this great advice not only does hydrogen run without
> errors, but, the deprecation warnings that you and I were getting also
> disappeared. I am assuming that you are working on OS X.
>
> Hope this helps.
>
>
> On Wednesday, October 28, 2015 at 12:57:43 AM UTC+1, colint...@gmail.com
> wrote:
>>
>> Hi all,
>>
>> I'm using Julia v0.4 with the Atom package, on Atom 1.0 with the packages
>> ink, julia-client, and language-julia (and I'm really enjoying this as an
>> IDE solution).
>>
>> I can toggle the Julia console in Atom, and enter code directly into it
>> without any errors or warnings. However, as soon as I try to evaluate a
>> line of code from the Atom editor, I get a large number of deprecation
>> warnings, either of the form:
>>
>> WARNING: Base.Uint8 is deprecated, use UInt8 instead.
>>   likely near no file:422
>>
>> or
>>
>> WARNING: Base.Uint8 is deprecated, use UInt8 instead.
>>   likely near no file:422
>> in skip at /home/colin/.julia/v0.4/LNR/src/LNR.jl:171
>>
>> Has anyone else encountered this and is there a fix? I had a look through
>> the LNR source, and there is nothing in it that should be triggering a
>> deprecation warning, nor is there even a line 171 (it only goes up to about
>> line 130).
>>
>> Note, I can just ignore the deprecation warnings, and continue on working
>> without a problem, so this isn't an urgent issue. Just wondering if I've
>> stuffed up the install process somehow.
>>
>> Cheers,
>>
>> Colin
>>
>

[julia-users] Re: "using Gadfly" (using a package) only if needed

[Felipe Jiménez]

I found a way to include a "using" command inside a function without the 
Requires.jl package or needing to qualify the "new" package functions' 
names with a prefix. It is an easy way to achieve a "lazymode" effect. So I 
am sharing in case someone is interested.

As example, inside the function I mentioned initially (fwhm, which 
estimates the full width at half maximum of a noisy peak), instead of 
adding:

   if dodraw
  using Gadfly
   end

(which errors), I add the line:

   dodraw && eval(parse("using Gadfly"))

To my surprise, this works for me. Of course the first time fwhm(..., 
dodraw = true) is called, the function has an overhead wait while loading 
the Gadfly package. But the next times it is fast.

And inside the function I do not need to be writing Gadfly.plot(...) or 
gadfly().plot(...), etc.; plot(...) just works.

I am sure this must be a terrible hack in some ways I don't know and very 
bad Julian manners in general for reasons I ignore. Or maybe this would not 
have worked in v.0.3. But in v.0.4 it just does the trick for me. When I 
call fwhm(...,dodraw=true) I am normally not so interested in performance; 
and if I want it fast I do dodraw=false and the command eval(parse("using 
Gadfly")) is not even executed.

[julia-users] Re: installing julia via cygwin

[digxx]

Thank you. After hours of compilation it finally finished without errors.
Now I have the Julia.exe file in my bin folder but when trying to run it 
from there by typing
Julia.exe or just Julia or -c Julia.exe it tells me: command not found?

Btw: how did u see it was m4? I mean u didnt really read these 1000 lines 
of code?
Vollständigen Inhalt anzeigen 

[julia-users] Re: installing julia via cygwin

[digxx]

Thank you. After hours of compilation it finally finished without errors.
Now I have the Julia.exe file in my bin folder but when trying to run it 
from there by typing
Julia.exe or just Julia or -c Julia.exe it tells me: command not found?

Btw: how did u know it was m4? It didnt complain specifically about m4?!

[julia-users] Re: ANN: NearestNeighbors.jl

[Kristoffer Carlsson]

My plan is to deprecate KDTrees.jl in favor of NearestNeighbors.jl. The KDTree 
in NN.jl is slightly faster and uses slightly less memory so there isn't really 
any point to KDTrees.jl anymore. Also, the tree in KDTrees.jl can only use 
Euclidian distance while the one in NN.jl can use the more general Minkowski 
distance.

I don't have any large plans to develop the package further (except to play 
around with threading support) but if anyone wants to use it as a sort of 
backend to another package I would (to the best of my ability) happily assist 
in solving any issues that arise.

[julia-users] Re: Problem with (lib)fontconfig

[Tony Kelman]

As far as I can tell Fontconfig is an optional dependency.

The C library can either be placed somewhere Julia can see it, or the Julia 
wrapper package can be adjusted to use an absolute path based on where it's 
obtaining the library from.


On Sunday, November 1, 2015 at 9:23:52 AM UTC-8, digxx wrote:
>
> I want to use Gadfly and apparently it's dependent on fontconfig.
> So I installed fontconfig and now when he tries to load fontconfig I get 
> this error.
> So where/how would I store my C-library?
> Right now im installing cygwin but cant even get Julia installed...I 
> opened a new thread for this problem.
>

[julia-users] Re: ANN: NearestNeighbors.jl

[Dawid Crivelli]

Well done, I've been trying also your package KDTrees.jl which is very 
useful to have! Is this going to be the backbone for a future 
fast-multipole-method code?

[julia-users] ANN: NearestNeighbors.jl

[Kristoffer Carlsson]

Hello everyone,

I took the last few days to finish a package I started many months ago. It 
is a package written in pure Julia for nearest neighbor searches in 
arbitrary dimensions by the use of either kd trees or ball trees (metric 
trees).
The ball trees can use any metric and the kd trees can use one of the 
Minkowski metrics.

There are currently no extensive benchmarks yet but this gist: 
https://gist.github.com/KristofferC/ba95bb6d9c04489bbed9 shows
 NearestNeighbors.jl beating the cKDTree in scipy version 0.15.1 with a 
factor of around 4 for knn searches with k = 5 for a tree with 100 000 
points in 4 dimensions.

I submitted a pull request to register it in METADATA but until then 
Pkg.clone should work. The link to the repo is 
https://github.com/KristofferC/NearestNeighbors.jl

Next step would be to add multithreading support but maybe that will have 
to wait until the thread support in base gets more mature and I have more 
time :)

Thank you for your time,

// Kristoffer

[julia-users] Re: [ANN] Word2Vec.jl, a Julia interface to word2vec

[Sergey Bartunov]

AdaGram.jl is parallel via processes and SharedArrays.

воскресенье, 1 ноября 2015 г., 17:55:14 UTC+3 пользователь Viral Shah 
написал:
>
> Are either of these parallel? Any plans to parallelize?
>
> -viral
>
> On Sunday, November 1, 2015 at 6:21:52 PM UTC+5:30, Sergey Bartunov wrote:
>>
>> There is also our package for an extension of word2vec - 
>> https://github.com/sbos/AdaGram.jl which has almost the same speed and 
>> functionality as original word2vec and may additionally learn vectors 
>> corresponding to different meanings of a word. 
>>
>> воскресенье, 1 ноября 2015 г., 12:10:28 UTC+3 пользователь Weijian Zhang 
>> написал:
>>>
>>> Hello,
>>>
>>> We just registered Word2Vec.jl v0.0.1 (
>>> https://github.com/weijianzhang/Word2Vec.jl), a Julia interface to 
>>> word2vec. 
>>> It takes a text corpus as input and produces the word vectors as output.
>>>
>>> You can see a IJulia notebook demo at: 
>>> http://nbviewer.ipython.org/github/weijianzhang/Word2Vec.jl/blob/master/examples/demo.ipynb
>>>
>>> Best wishes,
>>>
>>> Weijian
>>>
>>

Re: [julia-users] Re: Julia and Spark

[ssarkarayushnetdev]

Yes.

On Sunday, November 1, 2015 at 9:34:26 AM UTC-8, Jey Kottalam wrote:
>
> Are you asking about Spark Streaming support?
>
> On Sun, Nov 1, 2015 at 4:42 AM, Sisyphuss  > wrote:
>
>> http://dl.acm.org/citation.cfm?id=2228301
>>
>> On Saturday, October 31, 2015 at 5:18:01 PM UTC+1, Jey Kottalam wrote:
>>>
>>> Could you please define "streams of RDDs"?
>>>
>>> On Sat, Oct 31, 2015 at 12:59 AM,  wrote:
>>>
 Is there any implementation with streams of RDDs for Julia ? 


 On Monday, April 20, 2015 at 11:54:10 AM UTC-7, wil...@gmail.com wrote:
>
> Unfortunately, Spark.jl is an incorrect RDD implementation. Instead of 
> creating transformations as independent abstraction operations with a 
> lazy 
> evaluation, the package has all transformations immediately executed upon 
> their call. This is completely undermines whole purpose of RDD as 
> fault-tolerant parallel data structure.
>
> On Saturday, April 18, 2015 at 4:04:23 AM UTC-4, Tanmay K. Mohapatra 
> wrote:
>>
>> There was some attempt made towards a pure Julia RDD in Spark.jl (
>> https://github.com/d9w/Spark.jl).
>> We also have DistributedArrays (
>> https://github.com/JuliaParallel/DistributedArrays.jl), Blocks (
>> https://github.com/JuliaParallel/Blocks.jl) and (
>> https://github.com/JuliaStats/DataFrames.jl).
>>
>> I wonder if it is possible to leverage any of these for a pure Julia 
>> RDD.
>> And MachineLearning.jl 
>> 
>>  or 
>> something similar could probably be the equivalent of MLib.
>>
>>
>> On Friday, April 17, 2015 at 9:24:03 PM UTC+5:30, wil...@gmail.com 
>> wrote:
>>>
>>> Of course, a Spark data access infrastructure is unbeatable, due to 
>>> mature JVM-based libraries for accessing various data sources and 
>>> formats 
>>> (avro, parquet, hdfs). That includes SQL support as well. But, look at 
>>> Python and R bindings, these are just facades for JVM calls. MLLib is 
>>> written in Scala, Streaming API as well, and then all this called from 
>>> Python or R, all data transformations happen on JVM level. It would be 
>>> more 
>>> efficient write code in Scala then use any non-JVM bindings. Think of 
>>> overhead for RPC and data serialization over huge volumes of data 
>>> needed to 
>>> be processed and you'll understand why Dpark exists. BTW, machine 
>>> learning 
>>> libraries in JVM, good luck. It only works because of large 
>>> computational 
>>> resources used, but even that has its limits.
>>>
>>> On Thursday, April 16, 2015 at 6:29:58 PM UTC-4, Andrei Zh wrote:

 Julia bindings for Spark would provide much more than just RDD, 
 they will give us access to multiple big data components for 
 streaming, 
 machine learning, SQL capabilities and much more. 

 On Friday, April 17, 2015 at 12:54:32 AM UTC+3, wil...@gmail.com 
 wrote:
>
> However, I wonder, how hard it would be to implement RDD in Julia? 
> It looks straight forward from a RDD paper 
>  
> how to implement it. It is a robust abstraction that can be used in 
> any 
> parallel computation.
>
> On Thursday, April 16, 2015 at 3:32:32 AM UTC-4, Steven Sagaert 
> wrote:
>>
>> yes that's a solid approach. For my personal julia - java 
>> integrations I also run the JVM in a separate process.
>>
>> On Wednesday, April 15, 2015 at 9:30:28 PM UTC+2, 
>> wil...@gmail.com wrote:
>>>
>>> 1) simply wrap the Spark java API via JavaCall. This is the low 
 level approach. BTW I've experimented with javaCall and found it 
 was 
 unstable & also lacking functionality (e.g. there's no way to 
 shutdown the 
 jvm or create a pool of JVM analogous to DB connections) so that 
 might need 
 some work before trying the Spark integration.

>>>
>>> Using JavaCall is not an option, especially when JVM became 
>>> close-sourced, see https://github.com/aviks/JavaCall.jl/issues/7
>>> .
>>>
>>> Python bindings are done through Py4J, which is RPC to JVM. If 
>>> you look at the sparkR 
>>> , it is done in 
>>> a same way. sparkR uses a RPC interface to communicate with a 
>>> Netty-based 
>>> Spark JVM backend that translates R calls into JVM calls, keeps 
>>> SparkContext on a JVM side, and ships serialized data to/from R.
>>>
>>> So it is

[julia-users] Re: how to restore a variable to its default value?

[Kuan Xu]

Thanks Cedric. It works now for me.

K

On Sunday, November 1, 2015 at 6:12:16 PM UTC, Cedric St-Jean wrote:
>
> Ivar's solution worked for me.
>
> pi = Base.pi
>
>
> On Sunday, November 1, 2015 at 12:48:23 PM UTC-5, Kuan Xu wrote:
>>
>> I have the same question harven asked - how to reset pi to its factory 
>> value if it was overwritten?
>>
>> It seems that nobody answered his questions and I didn't any other 
>> threads discussing this. So bump this.
>>
>>
>> On Sunday, October 27, 2013 at 4:44:17 PM UTC, harven wrote:
>>>
>>> I sometimes make the mistake to redefine a bound variable at the repl, 
>>> e.g.
>>>
>>> julia> count = 0   # let us make a counter
>>> 0# I forgot count is a function provided by 
>>> the default library
>>> ...
>>> julia> count(iseven,[1,2,3])# oops
>>> ERROR: type: apply: expected Function, got Int64
>>>
>>> Is there a way to set count back to its default value (namely to the 
>>> function count)?
>>>
>>> By the way, a warning is issued when I try to redefine the constant pi. 
>>> Maybe this could be extended to all symbols provided by the standard 
>>> library?
>>>
>>> julia> pi = 3
>>> Warning: imported binding for pi overwritten in module Main
>>> 3
>>>
>>

[julia-users] Re: how to restore a variable to its default value?

[Cedric St-Jean]

Ivar's solution worked for me.

pi = Base.pi


On Sunday, November 1, 2015 at 12:48:23 PM UTC-5, Kuan Xu wrote:
>
> I have the same question harven asked - how to reset pi to its factory 
> value if it was overwritten?
>
> It seems that nobody answered his questions and I didn't any other threads 
> discussing this. So bump this.
>
>
> On Sunday, October 27, 2013 at 4:44:17 PM UTC, harven wrote:
>>
>> I sometimes make the mistake to redefine a bound variable at the repl, 
>> e.g.
>>
>> julia> count = 0   # let us make a counter
>> 0# I forgot count is a function provided by 
>> the default library
>> ...
>> julia> count(iseven,[1,2,3])# oops
>> ERROR: type: apply: expected Function, got Int64
>>
>> Is there a way to set count back to its default value (namely to the 
>> function count)?
>>
>> By the way, a warning is issued when I try to redefine the constant pi. 
>> Maybe this could be extended to all symbols provided by the standard 
>> library?
>>
>> julia> pi = 3
>> Warning: imported binding for pi overwritten in module Main
>> 3
>>
>

[julia-users] Re: how to restore a variable to its default value?

[Kuan Xu]

I have the same question harven asked - how to reset pi to its factory 
value if it was overwritten?

It seems that nobody answered his questions and I didn't any other threads 
discussing this. So bump this.


On Sunday, October 27, 2013 at 4:44:17 PM UTC, harven wrote:
>
> I sometimes make the mistake to redefine a bound variable at the repl, e.g.
>
> julia> count = 0   # let us make a counter
> 0# I forgot count is a function provided by 
> the default library
> ...
> julia> count(iseven,[1,2,3])# oops
> ERROR: type: apply: expected Function, got Int64
>
> Is there a way to set count back to its default value (namely to the 
> function count)?
>
> By the way, a warning is issued when I try to redefine the constant pi. 
> Maybe this could be extended to all symbols provided by the standard 
> library?
>
> julia> pi = 3
> Warning: imported binding for pi overwritten in module Main
> 3
>

Re: [julia-users] Re: Julia and Spark

[Jey Kottalam]

Are you asking about Spark Streaming support?

On Sun, Nov 1, 2015 at 4:42 AM, Sisyphuss  wrote:

> http://dl.acm.org/citation.cfm?id=2228301
>
> On Saturday, October 31, 2015 at 5:18:01 PM UTC+1, Jey Kottalam wrote:
>>
>> Could you please define "streams of RDDs"?
>>
>> On Sat, Oct 31, 2015 at 12:59 AM,  wrote:
>>
>>> Is there any implementation with streams of RDDs for Julia ?
>>>
>>>
>>> On Monday, April 20, 2015 at 11:54:10 AM UTC-7, wil...@gmail.com wrote:

 Unfortunately, Spark.jl is an incorrect RDD implementation. Instead of
 creating transformations as independent abstraction operations with a lazy
 evaluation, the package has all transformations immediately executed upon
 their call. This is completely undermines whole purpose of RDD as
 fault-tolerant parallel data structure.

 On Saturday, April 18, 2015 at 4:04:23 AM UTC-4, Tanmay K. Mohapatra
 wrote:
>
> There was some attempt made towards a pure Julia RDD in Spark.jl (
> https://github.com/d9w/Spark.jl).
> We also have DistributedArrays (
> https://github.com/JuliaParallel/DistributedArrays.jl), Blocks (
> https://github.com/JuliaParallel/Blocks.jl) and (
> https://github.com/JuliaStats/DataFrames.jl).
>
> I wonder if it is possible to leverage any of these for a pure Julia
> RDD.
> And MachineLearning.jl
> 
>  or
> something similar could probably be the equivalent of MLib.
>
>
> On Friday, April 17, 2015 at 9:24:03 PM UTC+5:30, wil...@gmail.com
> wrote:
>>
>> Of course, a Spark data access infrastructure is unbeatable, due to
>> mature JVM-based libraries for accessing various data sources and formats
>> (avro, parquet, hdfs). That includes SQL support as well. But, look at
>> Python and R bindings, these are just facades for JVM calls. MLLib is
>> written in Scala, Streaming API as well, and then all this called from
>> Python or R, all data transformations happen on JVM level. It would be 
>> more
>> efficient write code in Scala then use any non-JVM bindings. Think of
>> overhead for RPC and data serialization over huge volumes of data needed 
>> to
>> be processed and you'll understand why Dpark exists. BTW, machine 
>> learning
>> libraries in JVM, good luck. It only works because of large computational
>> resources used, but even that has its limits.
>>
>> On Thursday, April 16, 2015 at 6:29:58 PM UTC-4, Andrei Zh wrote:
>>>
>>> Julia bindings for Spark would provide much more than just RDD, they
>>> will give us access to multiple big data components for streaming, 
>>> machine
>>> learning, SQL capabilities and much more.
>>>
>>> On Friday, April 17, 2015 at 12:54:32 AM UTC+3, wil...@gmail.com
>>> wrote:

 However, I wonder, how hard it would be to implement RDD in Julia?
 It looks straight forward from a RDD paper
 
 how to implement it. It is a robust abstraction that can be used in any
 parallel computation.

 On Thursday, April 16, 2015 at 3:32:32 AM UTC-4, Steven Sagaert
 wrote:
>
> yes that's a solid approach. For my personal julia - java
> integrations I also run the JVM in a separate process.
>
> On Wednesday, April 15, 2015 at 9:30:28 PM UTC+2, wil...@gmail.com
> wrote:
>>
>> 1) simply wrap the Spark java API via JavaCall. This is the low
>>> level approach. BTW I've experimented with javaCall and found it was
>>> unstable & also lacking functionality (e.g. there's no way to 
>>> shutdown the
>>> jvm or create a pool of JVM analogous to DB connections) so that 
>>> might need
>>> some work before trying the Spark integration.
>>>
>>
>> Using JavaCall is not an option, especially when JVM became
>> close-sourced, see https://github.com/aviks/JavaCall.jl/issues/7.
>>
>> Python bindings are done through Py4J, which is RPC to JVM. If
>> you look at the sparkR
>> , it is done in a
>> same way. sparkR uses a RPC interface to communicate with a 
>> Netty-based
>> Spark JVM backend that translates R calls into JVM calls, keeps
>> SparkContext on a JVM side, and ships serialized data to/from R.
>>
>> So it is just a matter of writing Julia RPC to JVM and wrapping
>> necessary Spark methods in a Julia friendly way.
>>
>
>>

[julia-users] Re: Problem with (lib)fontconfig

[digxx]

I want to use Gadfly and apparently it's dependent on fontconfig.
So I installed fontconfig and now when he tries to load fontconfig I get 
this error.
So where/how would I store my C-library?
Right now im installing cygwin but cant even get Julia installed...I opened 
a new thread for this problem.

[julia-users] Why does setting ENV["TZ"] in the REPL behave differently?

[Josef Sachs]

Works as expected with `julia -e`, but the environment variable
does not seem to be respected when set in the REPL.  Can someone
explain the reason, and possibly provide a workaround?

$ TZ=UTC julia -e 'println(now())'
2015-11-01T16:02:37
$ julia -e 'println(now())'
2015-11-01T11:02:42
$ julia -e 'ENV["TZ"] = "UTC"; println(now())'
2015-11-01T16:03:07
$ julia
   _
   _   _ _(_)_ |  A fresh approach to technical computing
  (_) | (_) (_)|  Documentation: http://docs.julialang.org
   _ _   _| |_  __ _   |  Type "?help" for help.
  | | | | | | |/ _` |  |
  | | |_| | | | (_| |  |  Version 0.4.1-pre+22 (2015-11-01 00:06 UTC)
 _/ |\__'_|_|_|\__'_|  |  Commit 669222e (0 days old release-0.4)
|__/   |  x86_64-linux-gnu

julia> ENV["TZ"] = "UTC"; println(now())
2015-11-01T11:03:28

[julia-users] Re: [ANN] Word2Vec.jl, a Julia interface to word2vec

[Weijian Zhang]

The training is done using the original c code which uses threads to 
paralleize 
(splits the corpus into n parts and each thread process a part in parallel).
The function word2vec in Word2Vec.jl allows you to change the number of 
threads.

But there are rooms for improvement. I noticed a blog post on paralleizing 
word2vec in Python:
http://rare-technologies.com/parallelizing-word2vec-in-python/

It looks promising. I will look into it.

Thanks,

Weijian





On Sunday, 1 November 2015 14:55:14 UTC, Viral Shah wrote:
>
> Are either of these parallel? Any plans to parallelize?
>
> -viral
>
> On Sunday, November 1, 2015 at 6:21:52 PM UTC+5:30, Sergey Bartunov wrote:
>>
>> There is also our package for an extension of word2vec - 
>> https://github.com/sbos/AdaGram.jl which has almost the same speed and 
>> functionality as original word2vec and may additionally learn vectors 
>> corresponding to different meanings of a word. 
>>
>> воскресенье, 1 ноября 2015 г., 12:10:28 UTC+3 пользователь Weijian Zhang 
>> написал:
>>>
>>> Hello,
>>>
>>> We just registered Word2Vec.jl v0.0.1 (
>>> https://github.com/weijianzhang/Word2Vec.jl), a Julia interface to 
>>> word2vec. 
>>> It takes a text corpus as input and produces the word vectors as output.
>>>
>>> You can see a IJulia notebook demo at: 
>>> http://nbviewer.ipython.org/github/weijianzhang/Word2Vec.jl/blob/master/examples/demo.ipynb
>>>
>>> Best wishes,
>>>
>>> Weijian
>>>
>>

[julia-users] Re: [ANN] Word2Vec.jl, a Julia interface to word2vec

[Viral Shah]

Are either of these parallel? Any plans to parallelize?

-viral

On Sunday, November 1, 2015 at 6:21:52 PM UTC+5:30, Sergey Bartunov wrote:
>
> There is also our package for an extension of word2vec - 
> https://github.com/sbos/AdaGram.jl which has almost the same speed and 
> functionality as original word2vec and may additionally learn vectors 
> corresponding to different meanings of a word. 
>
> воскресенье, 1 ноября 2015 г., 12:10:28 UTC+3 пользователь Weijian Zhang 
> написал:
>>
>> Hello,
>>
>> We just registered Word2Vec.jl v0.0.1 (
>> https://github.com/weijianzhang/Word2Vec.jl), a Julia interface to 
>> word2vec. 
>> It takes a text corpus as input and produces the word vectors as output.
>>
>> You can see a IJulia notebook demo at: 
>> http://nbviewer.ipython.org/github/weijianzhang/Word2Vec.jl/blob/master/examples/demo.ipynb
>>
>> Best wishes,
>>
>> Weijian
>>
>

[julia-users] Distribute a Julia application without exposing the cose

[Lee Bates]

I'm trying to distribute an application written in Julia without exposing the 
code. I've tried using build_executable, however when using a Pkg interfacing 
with code written in another language (Tk, Cbc) the process seems to have 
errors I'm not capable of resolving.

I've also thought of creating a Pkg which contains the application and 
compiling it (creating a ji file) using the precompile functionality. This 
would require Julia to be installed on the user machine, but that doesn't worry 
me. However, the compiled package doesn't work without the Pkg source existing 
in the pkg directory.

Does anyone have any advice for distributing an application written in Julia 
without exposing the source code?

[julia-users] Re: Problem with (lib)fontconfig

[Tony Kelman]

http://www.freedesktop.org/wiki/Software/fontconfig/

What are you trying to use the Fontconfig.jl Julia package for? That Julia 
package can't do anything if the underlying C library isn't available.


On Sunday, November 1, 2015 at 5:22:10 AM UTC-8, digxx wrote:
>
> Thanks for your reply.
> Unfortunately I have no experience with linux/unix (and objectoriented 
> programming)
> So: I dont quite understand what libfontconfig is...? Is it just some 
> allocating path or really some intrinsic programming thing and therefore 
> would require complete rewriting of the package?
>

[julia-users] Re: Problem with (lib)fontconfig

[digxx]

Thanks for your reply.
Unfortunately I have no experience with linux/unix (and objectoriented 
programming)
So: I dont quite understand what libfontconfig is...? Is it just some 
allocating path or really some intrinsic programming thing and therefore 
would require complete rewriting of the package?

[julia-users] Re: [ANN] Word2Vec.jl, a Julia interface to word2vec

[Sergey Bartunov]

There is also our package for an extension of word2vec 
- https://github.com/sbos/AdaGram.jl which has almost the same speed and 
functionality as original word2vec and may additionally learn vectors 
corresponding to different meanings of a word. 

воскресенье, 1 ноября 2015 г., 12:10:28 UTC+3 пользователь Weijian Zhang 
написал:
>
> Hello,
>
> We just registered Word2Vec.jl v0.0.1 (
> https://github.com/weijianzhang/Word2Vec.jl), a Julia interface to 
> word2vec. 
> It takes a text corpus as input and produces the word vectors as output.
>
> You can see a IJulia notebook demo at: 
> http://nbviewer.ipython.org/github/weijianzhang/Word2Vec.jl/blob/master/examples/demo.ipynb
>
> Best wishes,
>
> Weijian
>

Re: [julia-users] Re: Julia and Spark

[Sisyphuss]

http://dl.acm.org/citation.cfm?id=2228301

On Saturday, October 31, 2015 at 5:18:01 PM UTC+1, Jey Kottalam wrote:
>
> Could you please define "streams of RDDs"?
>
> On Sat, Oct 31, 2015 at 12:59 AM, > 
> wrote:
>
>> Is there any implementation with streams of RDDs for Julia ? 
>>
>>
>> On Monday, April 20, 2015 at 11:54:10 AM UTC-7, wil...@gmail.com wrote:
>>>
>>> Unfortunately, Spark.jl is an incorrect RDD implementation. Instead of 
>>> creating transformations as independent abstraction operations with a lazy 
>>> evaluation, the package has all transformations immediately executed upon 
>>> their call. This is completely undermines whole purpose of RDD as 
>>> fault-tolerant parallel data structure.
>>>
>>> On Saturday, April 18, 2015 at 4:04:23 AM UTC-4, Tanmay K. Mohapatra 
>>> wrote:

 There was some attempt made towards a pure Julia RDD in Spark.jl (
 https://github.com/d9w/Spark.jl).
 We also have DistributedArrays (
 https://github.com/JuliaParallel/DistributedArrays.jl), Blocks (
 https://github.com/JuliaParallel/Blocks.jl) and (
 https://github.com/JuliaStats/DataFrames.jl).

 I wonder if it is possible to leverage any of these for a pure Julia 
 RDD.
 And MachineLearning.jl 
 
  or 
 something similar could probably be the equivalent of MLib.


 On Friday, April 17, 2015 at 9:24:03 PM UTC+5:30, wil...@gmail.com 
 wrote:
>
> Of course, a Spark data access infrastructure is unbeatable, due to 
> mature JVM-based libraries for accessing various data sources and formats 
> (avro, parquet, hdfs). That includes SQL support as well. But, look at 
> Python and R bindings, these are just facades for JVM calls. MLLib is 
> written in Scala, Streaming API as well, and then all this called from 
> Python or R, all data transformations happen on JVM level. It would be 
> more 
> efficient write code in Scala then use any non-JVM bindings. Think of 
> overhead for RPC and data serialization over huge volumes of data needed 
> to 
> be processed and you'll understand why Dpark exists. BTW, machine 
> learning 
> libraries in JVM, good luck. It only works because of large computational 
> resources used, but even that has its limits.
>
> On Thursday, April 16, 2015 at 6:29:58 PM UTC-4, Andrei Zh wrote:
>>
>> Julia bindings for Spark would provide much more than just RDD, they 
>> will give us access to multiple big data components for streaming, 
>> machine 
>> learning, SQL capabilities and much more. 
>>
>> On Friday, April 17, 2015 at 12:54:32 AM UTC+3, wil...@gmail.com 
>> wrote:
>>>
>>> However, I wonder, how hard it would be to implement RDD in Julia? 
>>> It looks straight forward from a RDD paper 
>>>  how 
>>> to implement it. It is a robust abstraction that can be used in any 
>>> parallel computation.
>>>
>>> On Thursday, April 16, 2015 at 3:32:32 AM UTC-4, Steven Sagaert 
>>> wrote:

 yes that's a solid approach. For my personal julia - java 
 integrations I also run the JVM in a separate process.

 On Wednesday, April 15, 2015 at 9:30:28 PM UTC+2, wil...@gmail.com 
 wrote:
>
> 1) simply wrap the Spark java API via JavaCall. This is the low 
>> level approach. BTW I've experimented with javaCall and found it was 
>> unstable & also lacking functionality (e.g. there's no way to 
>> shutdown the 
>> jvm or create a pool of JVM analogous to DB connections) so that 
>> might need 
>> some work before trying the Spark integration.
>>
>
> Using JavaCall is not an option, especially when JVM became 
> close-sourced, see https://github.com/aviks/JavaCall.jl/issues/7.
>
> Python bindings are done through Py4J, which is RPC to JVM. If you 
> look at the sparkR , 
> it is done in a same way. sparkR uses a RPC interface to communicate 
> with a 
> Netty-based Spark JVM backend that translates R calls into JVM calls, 
> keeps 
> SparkContext on a JVM side, and ships serialized data to/from R.
>
> So it is just a matter of writing Julia RPC to JVM and wrapping 
> necessary Spark methods in a Julia friendly way. 
>

>

[julia-users] Re: [ANN] UnicodePlots.jl v0.1.1

[Weijian Zhang]

Looks good! I will have a try. Here is link to the package if anyone is 
wondering: https://github.com/Evizero/UnicodePlots.jl

Best,

Weijian

On Sunday, 1 November 2015 09:35:56 UTC, Christof Stocker wrote:
>
> UnicodePlots.jl is a package for text-based plotting. It is designed for 
> interactive plotting in the REPL as well as to improve the quality of 
> custom show methods
>
> If you haven’t checked it out for a while, there were quite a few 
> improvements in the course of October.
> The most notable addition is that we finally have different types of 
> Canvas available (namely AsciiCanvas, DotCanvas, BlockCanvas). So if you 
> had issues with the Braille characters in the past, this change might be of 
> interest to you.
>
> Here is a screenshot of the AsciiCanvas in action
>
> [image: AsciiCanvas]
> ​
>

[julia-users] [ANN] Word2Vec.jl, a Julia interface to word2vec

[Weijian Zhang]

Hello,

We just registered Word2Vec.jl v0.0.1 
(https://github.com/weijianzhang/Word2Vec.jl), a Julia interface to 
word2vec. 
It takes a text corpus as input and produces the word vectors as output.

You can see a IJulia notebook demo 
at: 
http://nbviewer.ipython.org/github/weijianzhang/Word2Vec.jl/blob/master/examples/demo.ipynb

Best wishes,

Weijian

[julia-users] Re: Juno stopped working - error message

[Andre P.]

Hi all. I upgraded to 0.4.0 and basically lighttables + Jewel stopped 
working.  The errors are pretty mucb as above.


   - 
   
   WARNING: LightTable.jl: cannot resize array with shared data
in push! at 
/Applications/Julia-0.4.0.app/Contents/Resources/julia/lib/julia/sys.dylib
in read_operator at /Users/Andre/.julia/v0.4/JuliaParser/src/lexer.jl:368
in next_token at /Users/Andre/.julia/v0.4/JuliaParser/src/lexer.jl:752
in qualifiedname at /Users/Andre/.julia/v0.4/Jewel/src/parse/scope.jl:59
in nexttoken at /Users/Andre/.julia/v0.4/Jewel/src/parse/scope.jl:78
in nextscope! at /Users/Andre/.julia/v0.4/Jewel/src/parse/scope.jl:116
in scopes at /Users/Andre/.julia/v0.4/Jewel/src/parse/scope.jl:149
[inlined code] from /Users/Andre/.julia/v0.4/Lazy/src/macros.jl:141
in codemodule at /Users/Andre/.julia/v0.4/Jewel/src/parse/parse.jl:8
in getmodule at /Users/Andre/.julia/v0.4/Jewel/src/eval.jl:42
in anonymous at /Users/Andre/.julia/v0.4/Jewel/src/LightTable/eval.jl:51
in handlecmd at 
/Users/Andre/.julia/v0.4/Jewel/src/LightTable/LightTable.jl:70
in handlenext at 
/Users/Andre/.julia/v0.4/Jewel/src/LightTable/LightTable.jl:86
in server at /Users/Andre/.julia/v0.4/Jewel/src/LightTable/LightTable.jl:27
in server at /Users/Andre/.julia/v0.4/Jewel/src/Jewel.jl:23
in include at 
/Applications/Julia-0.4.0.app/Contents/Resources/julia/lib/julia/sys.dylib
in include_from_node1 at 
/Applications/Julia-0.4.0.app/Contents/Resources/julia/lib/julia/sys.dylib
in process_options at 
/Applications/Julia-0.4.0.app/Contents/Resources/julia/lib/julia/sys.dylib
in _start at 
/Applications/Julia-0.4.0.app/Contents/Resources/julia/lib/julia/sys.dylib
   
   - 
   
   
   
 I can no longer use Lighttable because of this. Tried some of the fixes 
above but no seemed to work. Has this been solved some how?

Julia Version 0.4.0

Commit 0ff703b* (2015-10-08 06:20 UTC)

Platform Info:

  System: Darwin (x86_64-apple-darwin13.4.0)

  CPU: Intel(R) Core(TM) i7-4650U CPU @ 1.70GHz

  WORD_SIZE: 64

  BLAS: libopenblas (USE64BITINT DYNAMIC_ARCH NO_AFFINITY Haswell)

  LAPACK: libopenblas64_

  LIBM: libopenlibm

  LLVM: libLLVM-3.3


THANKS,


Andre