date:20140930

Hi again,

Thanks for all the suggestions.
I'm a bit ashamed I overlooked the part of the documentation about types.
I skimmed through the DataFrames documentation and I don't think there's a 
way to access data via keys.
As far as the two other solutions are concerned, I compared their 
performance on a very simple test case, here it is if it can be of any 
interest :

n = 10

# Method 1: Type

type parameters
p1::Float64
p2::Float64
p3::Float64
end

p_method_1 = parameters(3.6, 0.6, 600.0)

function f1(p)
for i = 1:n
p.p1 += 0.1
p.p2 += 0.1
p.p3 += 0.1
end
end

# Method 2: Dictionnary

p_method_2 = {p1 = 3.6, p2 = 0.6, p3 = 600.0}

function f2(p)
for i = 1:n
p[p1] += 0.1
p[p2] += 0.1
p[p3] += 0.1
end
end

println(Method 1)
println(p_method_1)
@time f1(p_method_1)
println(p_method_1)

println(Method 2)
println(p_method_2)
@time f2(p_method_2)
println(p_method_2)

Here are the results:

Method 1
parameters(3.6,0.6,600.0)
elapsed time: 0.020289272 seconds (6610188 bytes allocated)
parameters(10003.60018861,1.6001885,10600.00020964)
Method 2
{p3=600.0,p2=0.6,p1=3.6}
elapsed time: 0.120914516 seconds (16193368 bytes allocated)
{p3=10600.00020964,p2=1.6001885,p1=10003.60018861}

The first method is by far the most efficient.

[julia-users] curl: (22) The requested URL returned error: 403

2014-09-30 Thread Staro Pickle

Hi.

I am installing julia on SUSE linux through SSH. I met this problem:

:~/julia make
Submodule 'deps/Rmath' () registered for path 'deps/Rmath'
Submodule 'deps/libmojibake' () registered for path 'deps/libmojibake'
Submodule 'deps/libuv' () registered for path 'deps/libuv'
Submodule 'deps/openlibm' () registered for path 'deps/openlibm'
Submodule 'deps/openspecfun' () registered for path 'deps/openspecfun'
Submodule 'doc/juliadoc' () registered for path 'doc/juliadoc'
  % Total% Received % Xferd  Average Speed   TimeTime Time 
 Current
 Dload  Upload   Total   SpentLeft 
 Speed
  0 00 00 0  0  0 --:--:--  0:00:14 --:--:--   
  0curl: (28) SSL connection timeout
  % Total% Received % Xferd  Average Speed   TimeTime Time 
 Current
 Dload  Upload   Total   SpentLeft 
 Speed
  0 00 00 0  0  0 --:--:-- --:--:-- --:--:--   
  0
curl: (22) The requested URL returned error: 403
make[2]: *** [patchelf-0.8.tar.gz] Error 22
make[1]: *** [julia-release] Error 2
make: *** [release] Error 2

How to fix this problem? Or how to skip this to complete the make process?

Thank you.

[julia-users] Re: Nested functions - maximize over integrals

Thanks for this, should have thought of this myself. I made some progress 
by defining the functions as follows:

for y = 1:Y
function f2(x, y_now = y)
y_l = y_now-1
y_h = y_now+1
f(y) = f3(x, y)*pdf(LogNormal(mu_y, sig_y), y)
quadgk(f, y_l, y_h)
end
end

With this, I get back one single-valued function f2 for each value of y in 
the loop, that I can evaluate at x:

 f2(5)

1-element Array{Float64,1}:
 134.112

However, the optimization fails, since the function I construct seems to be 
incorrectly specified for the Optim package to work:

 using Optim
 fminbox(f2, 1, 0, 2)  # minimize over interval [0, 2], start at 1

`fminbox` has no method matching fminbox(::Function)

 optimize(f2, 0, 2)  # minimize over interval [0, 2] using Brent's method

`eps` has no method matching eps(::Type{Int64})

I believe the second way of doing it would be the correct one, however I can't 
interpret the error being thrown here. The only place eps appears in the source 
code of Optim is when the tolerance levels for convergence of Brent's method 
are set (both in optimize.jl 
https://github.com/JuliaOpt/Optim.jl/blob/master/src/optimize.jl and 
brent.jl), https://github.com/JuliaOpt/Optim.jl/blob/master/src/brent.jl but 
I can't figure out what this error means or how I could fix it.  
https://github.com/JuliaOpt/Optim.jl/blob/master/src/brent.jl

[julia-users] Re: Label vector components

2014-09-30 Thread Jutho

While it is certainly expected that a custom type will be more performant, 
you cannot really trust your timings. You should not time with variables 
defined in global scope, and you should add a warm-up phase to compile your 
functions.

Defining all of this:


# Method 1: Type

type parameters
p1::Float64
p2::Float64
p3::Float64
end

function f1(n,p)
for i = 1:n
p.p1 += 0.1
p.p2 += 0.1
p.p3 += 0.1
end
end

# Method 2: Dictionary

function f2(n,p)
for i = 1:n
p[p1] += 0.1
p[p2] += 0.1
p[p3] += 0.1
end
end

# Time function
function correcttime()
p_method_1 = parameters(3.6, 0.6, 600.0)
p_method_2 = {p1 = 3.6, p2 = 0.6, p3 = 600.0}
f1(10,p_method_1)
f2(10,p_method_2)

println(Method 1)
println(p_method_1)
@time f1(10,p_method_1)
println(p_method_1)

println(Method 2)
println(p_method_2)
@time f2(10,p_method_2)
println(p_method_2)
end

and then running

correcttime()

gives

Method 1

parameters(4.598,1.6003,601.2)

elapsed time: 0.000275517 seconds (0 bytes allocated)

parameters(10004.60018865,10001.60018854,10601.00020967)

Method 2

{p3=601.2,p2=1.6003,p1=4.598}

elapsed time: 0.079420021 seconds (960 bytes allocated)

{p3=10601.00020967,p2=10001.60018854,p1=10004.60018865}




Op dinsdag 30 september 2014 11:09:38 UTC+2 schreef ami...@gmail.com:

 Hi again,

 Thanks for all the suggestions.
 I'm a bit ashamed I overlooked the part of the documentation about types.
 I skimmed through the DataFrames documentation and I don't think there's a 
 way to access data via keys.
 As far as the two other solutions are concerned, I compared their 
 performance on a very simple test case, here it is if it can be of any 
 interest :

 n = 10

 # Method 1: Type

 type parameters
 p1::Float64
 p2::Float64
 p3::Float64
 end

 p_method_1 = parameters(3.6, 0.6, 600.0)

 function f1(p)
 for i = 1:n
 p.p1 += 0.1
 p.p2 += 0.1
 p.p3 += 0.1
 end
 end

 # Method 2: Dictionnary

 p_method_2 = {p1 = 3.6, p2 = 0.6, p3 = 600.0}

 function f2(p)
 for i = 1:n
 p[p1] += 0.1
 p[p2] += 0.1
 p[p3] += 0.1
 end
 end

 println(Method 1)
 println(p_method_1)
 @time f1(p_method_1)
 println(p_method_1)

 println(Method 2)
 println(p_method_2)
 @time f2(p_method_2)
 println(p_method_2)

 Here are the results:

 Method 1
 parameters(3.6,0.6,600.0)
 elapsed time: 0.020289272 seconds (6610188 bytes allocated)
 parameters(10003.60018861,1.6001885,10600.00020964)
 Method 2
 {p3=600.0,p2=0.6,p1=3.6}
 elapsed time: 0.120914516 seconds (16193368 bytes allocated)
 {p3=10600.00020964,p2=1.6001885,p1=10003.60018861}

 The first method is by far the most efficient.

[julia-users] Module issues

2014-09-30 Thread Gerry Weaver

Hello All,

I am trying to define and use a module. I have the following code.


module TestModule

export test_func

function test_func(val)
  println(val)
end

end


---


#!/usr/bin/julia

using TestModule

println(LOAD_PATH)

test_func(TestVal)


I have put the module source file under the path 
LOAD_PATH/TestModule/src/TestModule.jl. I've tried a variety of other 
variations, but to no avail. Is there something that I am doing wrong? I 
get Warning: requiring TestModule did not define a corresponding 
module. when I try to use (using)  the module.

Thanks,
Gerry

Re: [julia-users] Package installation directory: dealing with multiple Julia version

2014-09-30 Thread Giulio Valentino Dalla Riva

Wouldn't this also change the behavior of my Julia?

Re: [julia-users] Package installation directory: dealing with multiple Julia version

On Tuesday, September 30, 2014 02:48:23 AM Giulio Valentino Dalla Riva wrote:
 Wouldn't this also change the behavior of my Julia?

Not if you have different aliases, `myjulia` and `centraljulia`. You can define 
each one to do something different.

--Tim

Re: [julia-users] Re: Nested functions - maximize over integrals

Hi Tim, 

Thanks so much for your answer, indeed this was the issue here. Specifying 
the function the way you said indeed gets rid of the error (and raises a 
new one, namely 

`isless` has no method matching isless(::Array{Float64,1}, ::Array{Float64,1}), 
I'll try to figure this one out later...).
Can I bother you with one related but general question: How do I interpret the 
first curly brackets in the function definition? The function definition says 
optimize{T:Real}(f::Function,

lower::T:Real,upper::T:Real), where I understand the f::Function, 
lower::T:Real, upper::T:Real give the expected inputs and their 
respective types, but what exactly does the {T:Real} tell me?

You can tell I'm coming from Matlab and even though I've been doing data 
analysis in Python for a while, object oriented programming still doesn't 
come naturally to me...

Best,
Nils

Re: [julia-users] Re: Nested functions - maximize over integrals

There's some difference in how `methods` prints the signature and how it looks 
in code. The version in code is usually clearer, so let's focus on that.

The `lower::T` means `lower` has type `T`. The `{T:Real}` means that T has to 
be a real number. This could have been written
optimize(f::Function, lower::Real, upper::Real, ...)
except that, later on, there's a default value provided for `rel_tol` and 
`abs_tol` which depends on the number type `T`. The intention behind that 
construct is that, for example, you want to use a different tolerence for 
convergence depending on whether you're optimizing a function of a Float32 or 
a Float64.

The issue is that if you pass `0` and `2`, these are both Ints. And `eps(Int)` 
doesn't exist.

Since you're obviously still pretty new to Julia, I'm just going to do this 
for you. Here's the commit:
https://github.com/JuliaOpt/Optim.jl/commit/2c812c9cbdbca95aaf00e703289f1297844698d4
You can study how it works and see how to fix such things in the future.
(Studying how people fix bugs that bit you is a great way to learn more about 
Julia.)

Best,
--Tim

On Tuesday, September 30, 2014 03:30:01 AM nils.gu...@gmail.com wrote:
 Hi Tim,
 
 Thanks so much for your answer, indeed this was the issue here. Specifying
 the function the way you said indeed gets rid of the error (and raises a
 new one, namely
 
 `isless` has no method matching isless(::Array{Float64,1},
 ::Array{Float64,1}), I'll try to figure this one out later...). Can I
 bother you with one related but general question: How do I interpret the
 first curly brackets in the function definition? The function definition
 says optimize{T:Real}(f::Function,
 
 lower::T:Real,upper::T:Real), where I understand the f::Function,
 lower::T:Real, upper::T:Real give the expected inputs and their
 respective types, but what exactly does the {T:Real} tell me?
 
 You can tell I'm coming from Matlab and even though I've been doing data
 analysis in Python for a while, object oriented programming still doesn't
 come naturally to me...
  
 Best,
 Nils

Re: [julia-users] Re: Nested functions - maximize over integrals

Oh, and to get the fix, you're going to have to say `Pkg.checkout(Optim)` 
until a new release gets tagged.

--Tim

On Tuesday, September 30, 2014 03:30:01 AM nils.gu...@gmail.com wrote:
 Hi Tim,
 
 Thanks so much for your answer, indeed this was the issue here. Specifying
 the function the way you said indeed gets rid of the error (and raises a
 new one, namely
 
 `isless` has no method matching isless(::Array{Float64,1},
 ::Array{Float64,1}), I'll try to figure this one out later...). Can I
 bother you with one related but general question: How do I interpret the
 first curly brackets in the function definition? The function definition
 says optimize{T:Real}(f::Function,
 
 lower::T:Real,upper::T:Real), where I understand the f::Function,
 lower::T:Real, upper::T:Real give the expected inputs and their
 respective types, but what exactly does the {T:Real} tell me?
 
 You can tell I'm coming from Matlab and even though I've been doing data
 analysis in Python for a while, object oriented programming still doesn't
 come naturally to me...
 
 Best,
 Nils

Re: [julia-users] All packages for numerical math

2014-09-30 Thread Hans W Borchers

Sorry for reviving an old thread.

I got interested in timings for vectorized vs. unvectorized versions of 
functions in MATLAB. So I wrote MATLAB versions of  the `trapz` functions 
mentioned in this thread, and measured their running times by applying the
`timeit` macro several hundred times. The results did surprise me:

trapz1  (vectorized)  :  ~ 35 µs
trapz2  (unvectorized):  ~ 12 µs  -- per loop

for evaluating the trapezoidal rule on `x=linspace(0,pi); y=sin(x)`.

I know one should not draw conclusions from such simple benchmarks. Still, 
does 
this comparison imply the old myth to 
*vectorize MATLAB functions to make them faster* is not true any more?

The JIT compiler that MATLAB is equipped with is not as powerful as Julia's 
LLVM-based compiler, but it seems to be at work. Have others had similar 
experiences, or am I on a wrong path here?


On Wednesday, April 23, 2014 11:20:50 PM UTC+2, Tomas Lycken wrote:



 On Wednesday, April 23, 2014 11:10:15 PM UTC+2, Cameron McBride wrote:

 Or you can use the non-vectorized version and save the overhead of the 
 temporary arrays being created by the addition and multiplication steps.


 There's really no way I can hide that I learnt scientific computing in 
 Matlab, is there? :P
  


 On Wed, Apr 23, 2014 at 7:52 AM, Tomas Lycken tomas@gmail.com 
 wrote:

 The trapezoidal rule (http://en.wikipedia.org/wiki/Trapezoidal_rule) 
 would probably be almost trivial to implement.

 function trapz{T:Real}(x::Vector{T}, y::Vector{T})
if (length(y) != length(x))
error(Vectors must be of same length)
end
sum( (x[2:end] .- x[1:end-1]).*(y[2:end].+y[1:end-1]) ) / 2
 end
 
 x = [0:0.01:pi]
 y = sin(x)

 trapz(x,y) # 1.820650436642

 This, of course, only currently works on vectors of real numbers, but 
 it's easy to extend it if you want.

 And there might be more accurate methods as well, of course (see e.g. 
 http://en.wikipedia.org/wiki/Simpson%27s_rule) but this one's often 
 good enough.

 // T

 On Wednesday, April 23, 2014 8:43:48 AM UTC+2, Evgeny Shevchenko wrote:

 Hi, John. 
 No, I didn't. I didn't find it and it seems to be not what i need:

 no method quadgk(Array{Float64,1}, Array{Float64,1})

 quadgk(f,a,b,...) expects a function as its first argument but I mean 
 the case when y = f(x), but i don't have f, e.g. obtained experimental 
 data, so x and y are 1-D arrays of floats.


 On Tue, Apr 22, 2014 at 7:49 PM, John Myles White johnmyl...@gmail.com
  wrote:

 Have you tried the quadgk function?
  
  -- John

 On Apr 22, 2014, at 7:32 AM, Evgeny Shevchenko eu...@ya.ru wrote:

 Hi 

 Is there a package for numeric integration of obtained arrays, say x 
 and y? Couldn't find one, the led me to use @pyimport and numpy.trapz.

 --
 pupoque@IRC

Re: [julia-users] Re: Calling Julia from .NET

I should mention that it is necessary to change the project target CPU from
the default Any to x64 or x86 to match the libjulia architecture.
On Sep 29, 2014 11:58 PM, Isaiah Norton isaiah.nor...@gmail.com wrote:

 I tried this some time ago during 0.2, so to make sure it still works I
 made a minimal translation of the embedding example to C#:

 ```
 using System;
 using System.Runtime.InteropServices;

 namespace ConsoleApplication2
 {
 class Program
 {
 [DllImport(libjulia.dll)]
 static extern void jl_init();
 [DllImport(libjulia.dll)]
 static extern void jl_eval_string(string message);

 static void Main(string[] args)
 {
 jl_init();
 jl_eval_string(print(sqrt(2.0)));
 }
 }
 }
 ```

 I compiled this, copied the binary into `Julia-0.3.0\bin`, and it works:

 ```
 C:\cmn\Julia-0.3.0bin\ConsoleApplication2.exe
 1.4142135623730951
 ```


 On Mon, Sep 29, 2014 at 4:11 PM, Tobias Knopp tobias.kn...@googlemail.com
  wrote:

 yep, I have done this (mostly for fun) before and it works. One needs
 some experience with P/Invoke of course but this is no magic but similar to
 our ccall.

 Cheers,

 Tobi

 Am Montag, 29. September 2014 20:52:10 UTC+2 schrieb Stefan Karpinski:

 I assume that you can call C libraries from .NET, right? The C library
 for Julia is libjulia – how to call it from C is explained in the embedding
 docs, calling it from .NET should be similar.


  On Sep 29, 2014, at 12:37 PM, Guido De Bouver guido.d...@telenet.be
 wrote:
 
  I have not found the C# examples, but I have not looked for them.
 Sorry for that.
 
  So, any help on this, how could we call Julia from .NET

[julia-users] Re: Module issues


Your code should work fine if you put the module in a directory that can be 
accessed.  
If you running julia in the directory where the module is located, you can 
recall the full path with:

joinpath(pwd(), TestModule.jl)

*j*ulia using TestModule

julia println(LOAD_PATH)

Union(UTF8String,ASCIIString)[/Users/maximilianosuster/julia/usr/local/share/julia/site/v0.3,/Users/maximilianosuster/julia/usr/share/julia/site/v0.3]

julia test_func

test_func (generic function with 1 method)

julia test_func(TestVal)

TestVal





On Tuesday, September 30, 2014 11:45:38 AM UTC+2, Gerry Weaver wrote:

 Hello All,

 I am trying to define and use a module. I have the following code.


 module TestModule

 export test_func

 function test_func(val)
   println(val)
 end

 end


 ---


 #!/usr/bin/julia

 using TestModule

 println(LOAD_PATH)

 test_func(TestVal)


 I have put the module source file under the path 
 LOAD_PATH/TestModule/src/TestModule.jl. I've tried a variety of other 
 variations, but to no avail. Is there something that I am doing wrong? I 
 get Warning: requiring TestModule did not define a corresponding 
 module. when I try to use (using)  the module.

 Thanks,
 Gerry

Re: [julia-users] Re: Benchmarking julia parallel computing

2014-09-30 Thread Erik Schnetter

There is a package MPI.jl that allows calling MPI from Julia. With
this, any MPI-based algorithm can be translated to Julia, and the
speed of MPI should be the same as for any other language.

-erik

On Tue, Sep 30, 2014 at 12:12 AM, Tony Kelman t...@kelman.net wrote:
 I'm not aware of any such data comparing Julia on large-scale parallel tasks
 with nontrivial communication patterns vs a more conventional HPC cluster
 approach using MPI. There are some benchmark problems (generally intended
 for serial or small-scale parallel execution, I believe) under test/perf,
 but it might be more interesting if you have your own parallel application
 you want to test with.

 Keep us posted as you get further into this.


 On Monday, September 29, 2014 11:58:33 AM UTC-7, Kapil Agarwal wrote:

 Hi

 I am looking to benchmark some standard parallel algorithms using Julia. I
 am thinking of comparing its performance with MPI and other parallel
 programming paradigms. Although I couldn't find much on any existing
 benchmarks, I was looking forward to any benchmarks that may have been done
 by the julia-dev team or in case any one is aware of any such benchmarks
 that could help me go about it.

 Thanks

 Kapil



-- 
Erik Schnetter schnet...@cct.lsu.edu
http://www.perimeterinstitute.ca/personal/eschnetter/

[julia-users] Re: Label vector components

Thanks Jutho for this warning, I will be more careful as of now.

[julia-users] Reflection, access members of a defined type

Dear all,

This is somewhat the following of a previous topic: 
https://groups.google.com/forum/#!topic/julia-users/CvQMwq2rN9I but since 
the two issues have little in common, I thought it was better to create a 
new topic.

I'd like to access the members of a type via a string, i.e. if I define:

type parameters
p1::Float64
p2::Float64
p3::Float64
end

p = parameters(3.6, 0.6, 600.0)

label = p1

is there a way to access p.p1 through something like:

p.names(label)

I guess this has to do with reflection in julia. I know there is a way to 
get the names through

names(p)

but there's nothing in the documentation about what I'm looking for. I did 
some research and I came across this reflection.jl file: 
https://github.com/JuliaLang/julia/blob/master/base/reflection.jl that I 
tried to decypher, but with little success. (Incidentally, I'd be 
interested in understanding what happens here if there's some resource 
helping to do so.)

Thanks a lot,

AS

[julia-users] Re: Reflection, access members of a defined type

 

julia type parameters

   p1::Float64

   p2::Float64

   p3::Float64

   end

julia params = parameters(1,2,3)

parameters(1.0,2.0,3.0)

julia label = p1

p1

julia params.(symbol(label))

1.0




On Tuesday, September 30, 2014 2:43:57 PM UTC+2, ami...@gmail.com wrote:

 Dear all,

 This is somewhat the following of a previous topic: 
 https://groups.google.com/forum/#!topic/julia-users/CvQMwq2rN9I but since 
 the two issues have little in common, I thought it was better to create a 
 new topic.

 I'd like to access the members of a type via a string, i.e. if I define:

 type parameters
 p1::Float64
 p2::Float64
 p3::Float64
 end

 p = parameters(3.6, 0.6, 600.0)

 label = p1

 is there a way to access p.p1 through something like:

 p.names(label)

 I guess this has to do with reflection in julia. I know there is a way to 
 get the names through

 names(p)

 but there's nothing in the documentation about what I'm looking for. I did 
 some research and I came across this reflection.jl file: 
 https://github.com/JuliaLang/julia/blob/master/base/reflection.jl that I 
 tried to decypher, but with little success. (Incidentally, I'd be 
 interested in understanding what happens here if there's some resource 
 helping to do so.)

 Thanks a lot,

 AS

[julia-users] Re: Reflection, access members of a defined type

Wonderful, many thanks Max.

Re: [julia-users] Re: Calling Julia from .NET

2014-09-30 Thread Stefan Babinec

Hi Isaiah.

I tried and got this error:
System image file  ?l\../lib/julia/sys.ji not found

System Image sys.ji looks to be on his place and I have no problem running 
Julia.

Thanks.


On Tuesday, September 30, 2014 2:03:42 PM UTC+2, Isaiah wrote:

 I should mention that it is necessary to change the project target CPU 
 from the default Any to x64 or x86 to match the libjulia architecture.
 On Sep 29, 2014 11:58 PM, Isaiah Norton isaiah...@gmail.com 
 javascript: wrote:

 I tried this some time ago during 0.2, so to make sure it still works I 
 made a minimal translation of the embedding example to C#:

 ```
 using System;
 using System.Runtime.InteropServices;

 namespace ConsoleApplication2
 {
 class Program
 {
 [DllImport(libjulia.dll)]
 static extern void jl_init();
 [DllImport(libjulia.dll)]
 static extern void jl_eval_string(string message);

 static void Main(string[] args)
 {
 jl_init();
 jl_eval_string(print(sqrt(2.0)));
 }
 }
 }
 ```

 I compiled this, copied the binary into `Julia-0.3.0\bin`, and it works:

 ```
 C:\cmn\Julia-0.3.0bin\ConsoleApplication2.exe
 1.4142135623730951
 ```


 On Mon, Sep 29, 2014 at 4:11 PM, Tobias Knopp tobias...@googlemail.com 
 javascript: wrote:

 yep, I have done this (mostly for fun) before and it works. One needs 
 some experience with P/Invoke of course but this is no magic but similar to 
 our ccall.

 Cheers,

 Tobi

 Am Montag, 29. September 2014 20:52:10 UTC+2 schrieb Stefan Karpinski:

 I assume that you can call C libraries from .NET, right? The C library 
 for Julia is libjulia – how to call it from C is explained in the 
 embedding 
 docs, calling it from .NET should be similar. 


  On Sep 29, 2014, at 12:37 PM, Guido De Bouver guido.d...@telenet.be 
 wrote: 
  
  I have not found the C# examples, but I have not looked for them. 
 Sorry for that. 
  
  So, any help on this, how could we call Julia from .NET

[julia-users] cannot add any packages - Julia on Windows7 x64

2014-09-30 Thread xaphoon

Hello, maybe somebody face same problem? I cannot add any Julia packages. 
The error message is always different, but result is the same.  What I'm 
doing wrong?

julia Pkg.add(Gadfly)
ERROR: key not found: StatsBase
 in wait at task.jl:51

julia Pkg.add(Jewel)
ERROR: key not found: WinRPM
 in wait at task.jl:51
 in add at pkg/entry.jl:319

julia Pkg.add(Curl)
INFO: Cloning cache of Curl from git://github.com/forio/Curl.jl.git
INFO: Installing Curl v0.0.3
error: internal error: refs/remotes/origin/master is not a valid packed 
reference!
error: internal error: refs/tags/v0.0.2 is not a valid packed reference!
error: Trying to write ref refs/heads/master with nonexistent object 
fd0e393f4f3b5c78f4174ccc2d62b239a8370ad4
fatal: Cannot update the ref 'HEAD'.
fatal: The remote end hung up unexpectedly
ERROR: failed process: Process(`git clone -q 'S:\.julia\.cache\Curl' Curl`, 
ProcessExited(128)) [128]
 in wait at task.jl:284

julia Pkg.add(Example)
fatal: Not a git repository: 'S:\.julia\Curl\.git'
ERROR: failed process: Process(`git '--work-tree=S:\.julia\Curl' 
'--git-dir=S:\.julia\Curl\.git' rev-parse HEAD`, ProcessExited(128)) [128]
 in wait at task.jl:51
 in add at pkg/entry.jl:319

julia Pkg.add(GZip)
fatal: Not a git repository: 'S:\.julia\Curl\.git'
ERROR: failed process: Process(`git '--work-tree=S:\.julia\Curl' 
'--git-dir=S:\.julia\Curl\.git' rev-parse HEAD`, ProcessExited(128)) [128]
 in wait at task.jl:51
 in add at pkg/entry.jl:319

julia Pkg.add(Helpme)
fatal: Not a git repository: 'S:\.julia\Curl\.git'
ERROR: failed process: Process(`git '--work-tree=S:\.julia\Curl' 
'--git-dir=S:\.julia\Curl\.git' rev-parse HEAD`, ProcessExited(128)) [128]
 in wait at task.jl:51
 in add at pkg/entry.jl:319

julia

Bst regards, Igor.

Re: [julia-users] Re: Control system library for Julia?

2014-09-30 Thread Spencer Russell

I'm looking forward to some sort of flag or option to turn on the
incremental GC, and trying to understand a bit more about the design space.
My naive thought process goes something like this:

   1. The total time to collect garbage probably grows with number of
   objects and total size to be freed (though maybe size doesn't matter much
   here?)
   2. An incremental GC will collect until it runs out of time, then hand
   control back to the application until it's time to run again
   3. It seems like there's a rate of garbage generation where you're
   building up garbage faster than the GC can collect it without missing its
   deadline
   4. It seems like if you stay below this rate you can consider your
   maximum pause time to be bounded and memory won't be leaking. We hold hands
   and sing songs.
   5. So the issue is what to do when you're above that rate. Either you:
  1. make sure memory consumption doesn't grow indefinitely by having
  some heuristic for when the GC decides to give up on the deadline, OR
  2. make sure the GC never violates its deadline and run the risk of
  running out of memory

Are there other options besides those two?

I would definitely welcome an actual hard-realtime bounded-pause-time GC,
but it also seems valuable (and possibly more feasible) to have a GC where
the pause time is bounded with caveats and more careful programming. I'm
not sure whether this qualifies as *hard *realtime, though it seems like it
might if you can make those guarantees about your application code.

It's also worth mentioning for other folks interested in latency that that
JIT compilation is a killer as well, so you need to guarantee that you're
pre-compiled all the possible methods that might get dispatched to.


peace,
s

On Mon, Sep 29, 2014 at 4:25 PM, Stefan Karpinski ste...@karpinski.org
wrote:

 On Mon, Sep 29, 2014 at 4:21 PM, Uwe Fechner uwe.fechner@gmail.com
 wrote:

 Jeff Bezanson suggested in the following discussion (
 https://github.com/JuliaLang/julia/pull/5227 ):
  It would be great to have the option to build with a low-pause GC for
 users who might want that.

 This is exactly what I am looking for: To have two different garbage
 collectors for Julia, a fast collector for non-real-time applications and a
 low-latency GC
 for real-time applications. Uwe


 Yeah, that would be great.

[julia-users] NEAT / HyperNEAT

2014-09-30 Thread Keyan Ghazi-Zahedi

Hi,

is anyone working on a NEAT / HyperNEAT package for julia?

Cheers,
Keyan

Re: [julia-users] cannot add any packages - Julia on Windows7 x64

2014-09-30 Thread Andreas Noack

What do you get from versioninfo()?

Med venlig hilsen

Andreas Noack

2014-09-30 3:06 GMT-04:00 xaph...@ymail.com:

 Hello, maybe somebody face same problem? I cannot add any Julia packages.
 The error message is always different, but result is the same.  What I'm
 doing wrong?

 julia Pkg.add(Gadfly)
 ERROR: key not found: StatsBase
  in wait at task.jl:51

 julia Pkg.add(Jewel)
 ERROR: key not found: WinRPM
  in wait at task.jl:51
  in add at pkg/entry.jl:319

 julia Pkg.add(Curl)
 INFO: Cloning cache of Curl from git://github.com/forio/Curl.jl.git
 INFO: Installing Curl v0.0.3
 error: internal error: refs/remotes/origin/master is not a valid packed
 reference!
 error: internal error: refs/tags/v0.0.2 is not a valid packed reference!
 error: Trying to write ref refs/heads/master with nonexistent object
 fd0e393f4f3b5c78f4174ccc2d62b239a8370ad4
 fatal: Cannot update the ref 'HEAD'.
 fatal: The remote end hung up unexpectedly
 ERROR: failed process: Process(`git clone -q 'S:\.julia\.cache\Curl'
 Curl`, ProcessExited(128)) [128]
  in wait at task.jl:284

 julia Pkg.add(Example)
 fatal: Not a git repository: 'S:\.julia\Curl\.git'
 ERROR: failed process: Process(`git '--work-tree=S:\.julia\Curl'
 '--git-dir=S:\.julia\Curl\.git' rev-parse HEAD`, ProcessExited(128)) [128]
  in wait at task.jl:51
  in add at pkg/entry.jl:319

 julia Pkg.add(GZip)
 fatal: Not a git repository: 'S:\.julia\Curl\.git'
 ERROR: failed process: Process(`git '--work-tree=S:\.julia\Curl'
 '--git-dir=S:\.julia\Curl\.git' rev-parse HEAD`, ProcessExited(128)) [128]
  in wait at task.jl:51
  in add at pkg/entry.jl:319

 julia Pkg.add(Helpme)
 fatal: Not a git repository: 'S:\.julia\Curl\.git'
 ERROR: failed process: Process(`git '--work-tree=S:\.julia\Curl'
 '--git-dir=S:\.julia\Curl\.git' rev-parse HEAD`, ProcessExited(128)) [128]
  in wait at task.jl:51
  in add at pkg/entry.jl:319

 julia

 Bst regards, Igor.

[julia-users] Re: Reflection, access members of a defined type

2014-09-30 Thread Michael Hatherly



It’s worth noting this open issue 
https://github.com/JuliaLang/julia/issues/6268 when using the syntax 
params.(symbol(label)). You could use getfield(params, symbol(label)) 
instead.

— Mike

[julia-users] Re: a good IDE for Julia ? (Julia Studio does not work with Julia v 0.3.0)

2014-09-30 Thread Ján Dolinský

Hello guys,

Indeed, www.junolab.org makes me want to go with Julia farther too :).

I was asking about debugging because I implemented a custom type (in a 
module) of which constructor is failing somewhere but I just get an error 
about some array multiplication in some julia file instead of a concrete 
line number in the constructor function. Any idea how to get through this ?

Thanks a lot,
Jan   


Dňa pondelok, 29. septembra 2014 12:27:07 UTC+2 Viral Shah napísal(-a):

 The light table work that Mike Innes has done is now packaged and 
 available at http://www.junolab.org/

 We are hoping to work towards making self-sufficient binaries and getting 
 it to a point where it is usable with a single download. The real fun is to 
 then try and do more interesting things. I don't know what those are, but I 
 do feel that we are setting ourselves up with a good base.

 -viral

 On Saturday, September 27, 2014 12:38:39 PM UTC+5:30, colint...@gmail.com 
 wrote:

 No, I don't think it has debugging a la the Matlab IDE or R-Studio (yet). 
 My understanding is that for now the Debug package is all that is 
 available. Personally I make do with sending blocks of code to a console in 
 Sublime-IJulia (you can do this with shift+enter, just like in R-Studio).

 Cheers,

 Colin

 On Friday, September 26, 2014 7:00:09 PM UTC+10, Ján Dolinský wrote:

 Hello,

 I cloned the master branch of Julia Studio and compiled it. I am however 
 getting this error when running ./JuliaStudio :
 libExtensionSystem.so.1: cannot open shared object file: No such file or 
 directory

 however when running using ./julia-studio.sh it runs but fails to open a 
 console with the following errors:
 Error: Failed to start Julia.
 Expected location: /usr/local/Julia_Studio/julia

 I am little bit lost here but exploring the Julia Studio menu I assume 
 that it doe not provide debugging capability (I had an impression that it 
 does).

 Thanks,
 Jan


 Dňa piatok, 19. septembra 2014 11:57:47 UTC+2 Uwe Fechner napísal(-a):

 I think that this branch is already merged into the master branch:
 https://github.com/forio/julia-studio/tree/julia-0.3-compatibility

 On Friday, September 19, 2014 11:54:41 AM UTC+2, Uwe Fechner wrote:

 If you compile Julia Studio from source it should work with Julia 0.3. 
 See:
 https://github.com/forio/julia-studio/issues/241

 Regards:

 Uwe

 On Friday, September 19, 2014 10:58:26 AM UTC+2, Ján Dolinský wrote:

 Hello guys,

 After upgrading to Julia 0.3.0 Julia Studio stopped working (I 
 changed the symbolic links in Julia Studio directory but nevertheless 
 ...). 
 Can somebody suggest any workaround ? Is it true that Julia Studio will 
 not 
 support newer versions of Julia ?
 What are you guys using now ? 

 Thanks a lot,
 Jan

[julia-users] Re: Reflection, access members of a defined type

Thanks for the warning Mike.

[julia-users] Re: Reflection, access members of a defined type

Mike, 

Thank you for pointing this out.  I am wondering, should I drop using 
params.(symbol(label))? 
Is there an easy way to keep updated on changes that are imminent in Julia 
syntax (e.g., in 0.4) vs personal preferences? 

Thanks,
Max


On Tuesday, September 30, 2014 3:36:32 PM UTC+2, Michael Hatherly wrote:

 It’s worth noting this open issue 
 https://github.com/JuliaLang/julia/issues/6268 when using the syntax 
 params.(symbol(label)). You could use getfield(params, symbol(label)) 
 instead.

 — Mike

Re: [julia-users] Re: Calling Julia from .NET

Try running it from the Julia directory as `bin\CommandLine2.exe`. This is
very much a minimal example; for general use, the bin directory should be
passed as an argument to `jl_init`:

https://github.com/JuliaLang/julia/blob/1ee440bee5035ccb33f82b8a45febddd2f973baa/src/jlapi.c#L70-L73

To go much further than this will really require to dig in to both jlapi.c
and the general Julia source code. Be aware that dealing with type
translation and garbage collection are both non-trivial. See also
`examples/embedding.c` in the julia tree, and several previous discussion
on the mailing list.

On Tue, Sep 30, 2014 at 9:08 AM, Stefan Babinec sysli...@gmail.com wrote:

 Hi Isaiah.

 I tried and got this error:
 System image file  ?l\../lib/julia/sys.ji not found

 System Image sys.ji looks to be on his place and I have no problem running
 Julia.

 Thanks.


 On Tuesday, September 30, 2014 2:03:42 PM UTC+2, Isaiah wrote:

 I should mention that it is necessary to change the project target CPU
 from the default Any to x64 or x86 to match the libjulia architecture.
 On Sep 29, 2014 11:58 PM, Isaiah Norton isaiah...@gmail.com wrote:

 I tried this some time ago during 0.2, so to make sure it still works I
 made a minimal translation of the embedding example to C#:

 ```
 using System;
 using System.Runtime.InteropServices;

 namespace ConsoleApplication2
 {
 class Program
 {
 [DllImport(libjulia.dll)]
 static extern void jl_init();
 [DllImport(libjulia.dll)]
 static extern void jl_eval_string(string message);

 static void Main(string[] args)
 {
 jl_init();
 jl_eval_string(print(sqrt(2.0)));
 }
 }
 }
 ```

 I compiled this, copied the binary into `Julia-0.3.0\bin`, and it works:

 ```
 C:\cmn\Julia-0.3.0bin\ConsoleApplication2.exe
 1.4142135623730951
 ```


 On Mon, Sep 29, 2014 at 4:11 PM, Tobias Knopp tobias...@googlemail.com
 wrote:

 yep, I have done this (mostly for fun) before and it works. One needs
 some experience with P/Invoke of course but this is no magic but similar to
 our ccall.

 Cheers,

 Tobi

 Am Montag, 29. September 2014 20:52:10 UTC+2 schrieb Stefan Karpinski:

 I assume that you can call C libraries from .NET, right? The C library
 for Julia is libjulia – how to call it from C is explained in the 
 embedding
 docs, calling it from .NET should be similar.


  On Sep 29, 2014, at 12:37 PM, Guido De Bouver guido.d...@telenet.be
 wrote:
 
  I have not found the C# examples, but I have not looked for them.
 Sorry for that.
 
  So, any help on this, how could we call Julia from .NET

Re: [julia-users] Re: Nested functions - maximize over integrals

Hi Tim,

thanks again for your detailed reply, I understood what was going wrong 
now. 
And another thank you for fixing the issue, after doing the Pkg.checkout 
the optimization now works with integers as well.
However, I still can't get a result because I'm still getting the error 
alluded to above:

 optimize(f, 0, 2)
`isless` has no method matching isless(::Array{Float64,1}, ::Array{Float64,1})
while loading In[15], in expression starting on line 1

 in = at operators.jl:34

If I understand correctly, this means that two arrays are being passed to the 
isless function, which doesn't support arrays. 
I figured out that isless is contained in operators.jl, which in itself is part 
of the julia base, so it's probably not a bug 
in the function here. How can I figure out where the arrays being passed to 
isless are created? 
Sorry for bombarding you with questions here, but my debugging skills in julia 
are pretty much non-existant and I have to get used
to the logic of the julia error messages!

Re: [julia-users] Re: a good IDE for Julia ? (Julia Studio does not work with Julia v 0.3.0)

2014-09-30 Thread Leah Hanson

Maybe you could start a new julia-users thread, and post the code and the
error message so we can help? It's hard to make specific recommendations
without seeing the code/error.

-- Leah

On Tue, Sep 30, 2014 at 9:27 AM, Ján Dolinský jan.dolin...@2bridgz.com
wrote:

 Hello guys,

 Indeed, www.junolab.org makes me want to go with Julia farther too :).

 I was asking about debugging because I implemented a custom type (in a
 module) of which constructor is failing somewhere but I just get an error
 about some array multiplication in some julia file instead of a concrete
 line number in the constructor function. Any idea how to get through this ?

 Thanks a lot,
 Jan


 Dňa pondelok, 29. septembra 2014 12:27:07 UTC+2 Viral Shah napísal(-a):

 The light table work that Mike Innes has done is now packaged and
 available at http://www.junolab.org/

 We are hoping to work towards making self-sufficient binaries and getting
 it to a point where it is usable with a single download. The real fun is to
 then try and do more interesting things. I don't know what those are, but I
 do feel that we are setting ourselves up with a good base.

 -viral

 On Saturday, September 27, 2014 12:38:39 PM UTC+5:30, colint...@gmail.com
 wrote:

 No, I don't think it has debugging a la the Matlab IDE or R-Studio
 (yet). My understanding is that for now the Debug package is all that is
 available. Personally I make do with sending blocks of code to a console in
 Sublime-IJulia (you can do this with shift+enter, just like in R-Studio).

 Cheers,

 Colin

 On Friday, September 26, 2014 7:00:09 PM UTC+10, Ján Dolinský wrote:

 Hello,

 I cloned the master branch of Julia Studio and compiled it. I am
 however getting this error when running ./JuliaStudio :
 libExtensionSystem.so.1: cannot open shared object file: No such file
 or directory

 however when running using ./julia-studio.sh it runs but fails to open
 a console with the following errors:
 Error: Failed to start Julia.
 Expected location: /usr/local/Julia_Studio/julia

 I am little bit lost here but exploring the Julia Studio menu I assume
 that it doe not provide debugging capability (I had an impression that it
 does).

 Thanks,
 Jan


 Dňa piatok, 19. septembra 2014 11:57:47 UTC+2 Uwe Fechner napísal(-a):

 I think that this branch is already merged into the master branch:
 https://github.com/forio/julia-studio/tree/julia-0.3-compatibility

 On Friday, September 19, 2014 11:54:41 AM UTC+2, Uwe Fechner wrote:

 If you compile Julia Studio from source it should work with Julia
 0.3. See:
 https://github.com/forio/julia-studio/issues/241

 Regards:

 Uwe

 On Friday, September 19, 2014 10:58:26 AM UTC+2, Ján Dolinský wrote:

 Hello guys,

 After upgrading to Julia 0.3.0 Julia Studio stopped working (I
 changed the symbolic links in Julia Studio directory but nevertheless 
 ...).
 Can somebody suggest any workaround ? Is it true that Julia Studio will 
 not
 support newer versions of Julia ?
 What are you guys using now ?

 Thanks a lot,
 Jan

Re: [julia-users] Re: Nested functions - maximize over integrals

Is that really all the backtrace you get from your error?

My guess is you have a problem with your function definition. You may need 
`.=` rather than `=` (note the dot out front, just like .* in Matlab).

Anyway, to help more we'd need a more complete example. In your first post, 
most of the variables (at least Y,mu_y, sig_y,  x_l, x_h, y_l, y_h) are 
undefined.

--Tim

On Tuesday, September 30, 2014 08:57:38 AM nils.gu...@gmail.com wrote:
 Hi Tim,
 
 thanks again for your detailed reply, I understood what was going wrong
 now.
 And another thank you for fixing the issue, after doing the Pkg.checkout
 the optimization now works with integers as well.
 However, I still can't get a result because I'm still getting the error
 
 alluded to above:
  optimize(f, 0, 2)
 
 `isless` has no method matching isless(::Array{Float64,1},
 ::Array{Float64,1}) while loading In[15], in expression starting on line 1
 
  in = at operators.jl:34
 
 If I understand correctly, this means that two arrays are being passed to
 the isless function, which doesn't support arrays. I figured out that
 isless is contained in operators.jl, which in itself is part of the julia
 base, so it's probably not a bug in the function here. How can I figure out
 where the arrays being passed to isless are created? Sorry for bombarding
 you with questions here, but my debugging skills in julia are pretty much
 non-existant and I have to get used to the logic of the julia error
 messages!

Re: [julia-users] Re: Nested functions - maximize over integrals

Hi Tim,

Good that you asked for the backtrace, I did indeed miss a line; 
specifically, the issue arises in Optim\src\brent.jl:117

You're also right that my question gets increasingly specific and hard to 
answer, so I've put together a minimum working example 
that does what I'm trying to do in my original code and reproduces the 
issue:

using Distributions
using Optim

z1 = 1.7
z2 = 0.1
z3 = 1.9
z4 = 0.1
z5 = 0.2
z6 = 40
stdz = 0.22
coeffz = rand(7,1)
expz1 = LogNormal(2, 0.3)
expand(x, z1, z2, z3, z4, z5, z6) = [x^2, z1^2, z2^2, z3^2, z4^2, z5^2, 
z6^2] 

function f2(x, z1=z1, z2=z2, z3=z3, z4=z4, z5=z5, z6=z6)
z1_l = z1 - 3*stdz
z1_h = z1 + 3*stdz

f(z1) = expand(x, z1, z2, z3, z4, z5, z6)'*coeffz*pdf(expz1, z1)

quadgk(f, z1_l, z1_h)[1]
end

 f2(5)
1x1 Array{Float64,2}:
 0.0683061

 optimize(f2, 0, 2)

`isless` has no method matching isless(::Array{Float64,2}, ::Array{Float64,2})
while loading In[4], in expression starting on line 1

 in = at operators.jl:34
 in brent at C:\Users\tew207\.julia\v0.3\Optim\src\brent.jl:117
Let me know if this works for you in producing the same output!

Re: [julia-users] All packages for numerical math

Quite interesting indeed. Thanks for sharing.
--Tim

On Tuesday, September 30, 2014 04:52:22 AM Hans W Borchers wrote:
 Sorry for reviving an old thread.
 
 I got interested in timings for vectorized vs. unvectorized versions of
 functions in MATLAB. So I wrote MATLAB versions of  the `trapz` functions
 mentioned in this thread, and measured their running times by applying the
 `timeit` macro several hundred times. The results did surprise me:
 
 trapz1  (vectorized)  :  ~ 35 µs
 trapz2  (unvectorized):  ~ 12 µs  -- per loop
 
 for evaluating the trapezoidal rule on `x=linspace(0,pi); y=sin(x)`.
 
 I know one should not draw conclusions from such simple benchmarks. Still,
 does
 this comparison imply the old myth to 
 *vectorize MATLAB functions to make them faster* is not true any more?
 
 The JIT compiler that MATLAB is equipped with is not as powerful as Julia's
 LLVM-based compiler, but it seems to be at work. Have others had similar
 experiences, or am I on a wrong path here?
 
 On Wednesday, April 23, 2014 11:20:50 PM UTC+2, Tomas Lycken wrote:
  On Wednesday, April 23, 2014 11:10:15 PM UTC+2, Cameron McBride wrote:
  Or you can use the non-vectorized version and save the overhead of the
  temporary arrays being created by the addition and multiplication steps.
  
  There's really no way I can hide that I learnt scientific computing in
  Matlab, is there? :P
  
  On Wed, Apr 23, 2014 at 7:52 AM, Tomas Lycken tomas@gmail.com
  
  wrote:
  The trapezoidal rule (http://en.wikipedia.org/wiki/Trapezoidal_rule)
  would probably be almost trivial to implement.
  
  function trapz{T:Real}(x::Vector{T}, y::Vector{T})
  
 if (length(y) != length(x))
 
 error(Vectors must be of same length)
 
 end
 sum( (x[2:end] .- x[1:end-1]).*(y[2:end].+y[1:end-1]) ) / 2
  
  end
  
  x = [0:0.01:pi]
  y = sin(x)
  
  trapz(x,y) # 1.820650436642
  
  This, of course, only currently works on vectors of real numbers, but
  it's easy to extend it if you want.
  
  And there might be more accurate methods as well, of course (see e.g.
  http://en.wikipedia.org/wiki/Simpson%27s_rule) but this one's often
  good enough.
  
  // T
  
  On Wednesday, April 23, 2014 8:43:48 AM UTC+2, Evgeny Shevchenko wrote:
  Hi, John.
  No, I didn't. I didn't find it and it seems to be not what i need:
  
  no method quadgk(Array{Float64,1}, Array{Float64,1})
  
  quadgk(f,a,b,...) expects a function as its first argument but I mean
  the case when y = f(x), but i don't have f, e.g. obtained experimental
  data, so x and y are 1-D arrays of floats.
  
  
  On Tue, Apr 22, 2014 at 7:49 PM, John Myles White johnmyl...@gmail.com
  
   wrote:
  Have you tried the quadgk function?
  
   -- John
  
  On Apr 22, 2014, at 7:32 AM, Evgeny Shevchenko eu...@ya.ru wrote:
  
  Hi
  
  Is there a package for numeric integration of obtained arrays, say x
  and y? Couldn't find one, the led me to use @pyimport and numpy.trapz.
  
  --
  pupoque@IRC

Re: [julia-users] Re: Nested functions - maximize over integrals

f2 is returning a matrix, not a scalar. (Try running f2(5).) brent needs a 
scalar.

--Tim

On Tuesday, September 30, 2014 09:38:00 AM nils.gu...@gmail.com wrote:
 Hi Tim,
 
 Good that you asked for the backtrace, I did indeed miss a line;
 specifically, the issue arises in Optim\src\brent.jl:117
 
 You're also right that my question gets increasingly specific and hard to
 answer, so I've put together a minimum working example
 that does what I'm trying to do in my original code and reproduces the
 issue:
 
 using Distributions
 using Optim
 
 z1 = 1.7
 z2 = 0.1
 z3 = 1.9
 z4 = 0.1
 z5 = 0.2
 z6 = 40
 stdz = 0.22
 coeffz = rand(7,1)
 expz1 = LogNormal(2, 0.3)
 expand(x, z1, z2, z3, z4, z5, z6) = [x^2, z1^2, z2^2, z3^2, z4^2, z5^2,
 z6^2]
 
 function f2(x, z1=z1, z2=z2, z3=z3, z4=z4, z5=z5, z6=z6)
 z1_l = z1 - 3*stdz
 z1_h = z1 + 3*stdz
 
 f(z1) = expand(x, z1, z2, z3, z4, z5, z6)'*coeffz*pdf(expz1, z1)
 
 quadgk(f, z1_l, z1_h)[1]
 end
 
  f2(5)
 
 1x1 Array{Float64,2}:
  0.0683061
 
  optimize(f2, 0, 2)
 
 `isless` has no method matching isless(::Array{Float64,2},
 ::Array{Float64,2}) while loading In[4], in expression starting on line 1
 
  in = at operators.jl:34
  in brent at C:\Users\tew207\.julia\v0.3\Optim\src\brent.jl:117
 Let me know if this works for you in producing the same output!

[julia-users] Pkg.add fail

2014-09-30 Thread Laszlo Hars

Under Windows, in the Julia 0.3.1 REPL I get a weird Pkg.add() error:

 ...Version 0.3.1 (2014-09-21 21:30 UTC)

 ...x86_64-w64-mingw32


 julia Pkg.add(Jewel)

 ERROR: IJulia can't be installed because it has no versions that support 
 0.3.1 of julia

  in wait at task.jl:284

  in wait at task.jl:194

  in wait at task.jl:48

  in sync_end at task.jl:311

  in add at pkg/entry.jl:319

  in add at pkg/entry.jl:71

  in anonymous at pkg/dir.jl:28

  in cd at file.jl:30

  in cd at pkg/dir.jl:28

  in add at pkg.jl:20

  

It is weird, because IJulia is installed and works well, and I wanted to 
add Jewel, not IJulia again. Here is the same thing from IJulia:

Python 2.7.7 |Anaconda 2.0.1 (64-bit)| (default, Jun 11 2014, 10:40:02) 
 [MSC v.1500 64 bit (AMD64)]

 Type copyright, credits or license for more information.


 IPython 2.1.0 -- An enhanced Interactive Python...


 In [3]: Pkg.add(Jewel)

 IJulia can't be installed because it has no versions that support 0.3.1 of 
 julia

 while loading In[3], in expression starting on line 1

  in wait at task.jl:284

  in wait at task.jl:194

  in wait at task.jl:48

  in sync_end at task.jl:311

  in add at pkg/entry.jl:319

  in add at pkg/entry.jl:71

  in anonymous at pkg/dir.jl:28

  in cd at file.jl:30

  in cd at pkg/dir.jl:28

  in add at pkg.jl:20


 Because of this error Juno (LightTable) cannot connect to Julia. What can 
I do?

[julia-users] Re: Reflection, access members of a defined type

2014-09-30 Thread Michael Hatherly



Hi Max,

If you have a GitHub account then you could watch the julia repo, otherwise 
there’s also https://github.com/JuliaLang/julia/pulse/weekly that should be 
viewable even without an account.
There’s also the “breaking” label on the issues list that probably covers 
important changes 
https://github.com/JuliaLang/julia/issues?q=is%3Aopen+is%3Aissue+label%3Abreaking
The NEWS file https://github.com/JuliaLang/julia/blob/master/NEWS.md gets 
updated quite regularly from the looks of things as well.

With regards to stopping using that syntax: I’ve not used it for a while 
and getfield isn’t that much longer to write. I’ll leave it to one of the 
core devs to clarify whether it is *really*
deprecated, but I’d assume it is.

— Mike

[julia-users] Re: Reflection, access members of a defined type

Hi Mike, 

Thanks for the clarification.  I will have a close eye on the one with the 
“breaking” 
label from now on. . .

Max


On Tuesday, September 30, 2014 7:27:29 PM UTC+2, Michael Hatherly wrote:

 Hi Max,

 If you have a GitHub account then you could watch the julia repo, 
 otherwise there’s also https://github.com/JuliaLang/julia/pulse/weekly 
 https://www.google.com/url?q=https%3A%2F%2Fgithub.com%2FJuliaLang%2Fjulia%2Fpulse%2Fweeklysa=Dsntz=1usg=AFQjCNGTJ5dU7XZOkEOceOQN96ebhGS8lA
  
 that should be viewable even without an account.
 There’s also the “breaking” label on the issues list that probably covers 
 important changes 
 https://github.com/JuliaLang/julia/issues?q=is%3Aopen+is%3Aissue+label%3Abreaking
  
 https://www.google.com/url?q=https%3A%2F%2Fgithub.com%2FJuliaLang%2Fjulia%2Fissues%3Fq%3Dis%253Aopen%2Bis%253Aissue%2Blabel%253Abreakingsa=Dsntz=1usg=AFQjCNHZfWAHoZLyubSBk-wuhvnp_7OwmA
 The NEWS file https://github.com/JuliaLang/julia/blob/master/NEWS.md gets 
 updated quite regularly from the looks of things as well.

 With regards to stopping using that syntax: I’ve not used it for a while 
 and getfield isn’t that much longer to write. I’ll leave it to one of the 
 core devs to clarify whether it is *really*
 deprecated, but I’d assume it is.

 — Mike

[julia-users] Re: Module issues

2014-09-30 Thread Gerry Weaver

Hi Max,

I was trying to figure out where to put modules, so that Julia would be 
able to use them by default. In my case, /usr/share/julia/site/v3.0 is in 
LOAD_PATH. However, when I put my code there Julia can't see it. Is there 
something that I'm missing?

Thanks,
Gerry

On Tuesday, September 30, 2014 7:07:07 AM UTC-5, Max Suster wrote:


 Your code should work fine if you put the module in a directory that can 
 be accessed.  
 If you running julia in the directory where the module is located, you can 
 recall the full path with:

 joinpath(pwd(), TestModule.jl)

 *j*ulia using TestModule

 julia println(LOAD_PATH)


 Union(UTF8String,ASCIIString)[/Users/maximilianosuster/julia/usr/local/share/julia/site/v0.3,/Users/maximilianosuster/julia/usr/share/julia/site/v0.3]

 julia test_func

 test_func (generic function with 1 method)

 julia test_func(TestVal)

 TestVal





 On Tuesday, September 30, 2014 11:45:38 AM UTC+2, Gerry Weaver wrote:

 Hello All,

 I am trying to define and use a module. I have the following code.


 module TestModule

 export test_func

 function test_func(val)
   println(val)
 end

 end


 ---


 #!/usr/bin/julia

 using TestModule

 println(LOAD_PATH)

 test_func(TestVal)


 I have put the module source file under the path 
 LOAD_PATH/TestModule/src/TestModule.jl. I've tried a variety of other 
 variations, but to no avail. Is there something that I am doing wrong? I 
 get Warning: requiring TestModule did not define a corresponding 
 module. when I try to use (using)  the module.

 Thanks,
 Gerry

[julia-users] Re: SharedArray, featuring another extreme newbie question

2014-09-30 Thread Travis Porco

I assume pmap works the same way...? References to a SharedArray within the 
call of a pmap are treated as references, not copied and transferred? I 
suppose @profile is the only way to measure the amount of communications 
overhead going on; it is hard to fix what you can't measure! 

Thanks much.  

On Monday, September 29, 2014 8:47:57 PM UTC-7, Travis Porco wrote:

 Configuration:
 Version 0.3.0 (2014-08-20 20:43 UTC), x86_64-apple-darwin13.3.0
 julia -p 1

 Make a shared array, no problem:
 julia S = SharedArray(Int, (5,11), init = S - S[localindexes(S)] = 
 myid(),pids=[1, 2])

 A similar nonshared array, also no problem:
 julia nonshared = zeros(5,11)

 Toy function, no problem:
 @everywhere function ssq(x)
   sum(x .^ 2)
   end

 Test ability to do something on the workers, seems to work fine:
 julia for ww in workers()
remotecall(ww,println,ww)
end

 julia From worker 2:2

 I don't expect the nonshared object to be visible:
 julia @sync for ww in workers()
   remotecall_fetch(ww, 
 x-println(ssq(nonshared[myid()-1,:])),ww)
   end
 exception on 2: ERROR: nonshared not defined
  in anonymous at none:2
  in anonymous at multi.jl:855
  in run_work_thunk at multi.jl:621
  in anonymous at task.jl:855

 Try to reference the shared array on the workers:
 julia for ww in workers()
   remotecall_fetch(ww, x-println(ssq(S[myid()-1,:])),ww)  
 # I know the ww does nothing here
   end
 exception on 2: ERROR: S not defined
  in anonymous at none:2
  in anonymous at multi.jl:855
  in run_work_thunk at multi.jl:621
  in anonymous at task.jl:855

 S was supposed to be a shared array, but it can't find it; I expected S to 
 be visible, since it's supposed to be a shared array.

 I can call the function on S:
 julia for ww in workers()
   remotecall_fetch(ww, x-println(ssq(x[myid()-1,:])),S)
   end
 From worker 2:26

 but then again, the nonshared version works in this context too, and so I 
 have to think it's moving the data from pid 1 over to 2, and then doing the 
 computation. This makes me think the operation above with S is actually 
 doing the same thing--moving the data in S from pid 1 to 2 rather than 
 having 2 just having access to it. However, I don't fully understand the 
 issues.
 julia for ww in workers()
   remotecall_fetch(ww, 
 x-println(ssq(x[myid()-1,:])),nonshared)
   end
 From worker 2:0

 So the question: is this normal behavior? If so, what is the right way to 
 access S on the workers, avoiding moving data? 
 The manual describes the SharedArray as experimental, so I have to 
 check... I've looked around for some very elementary examples of this sort 
 but must have missed them.

 Thanks.

Re: [julia-users] Package installation directory: dealing with multiple Julia version

2014-09-30 Thread Giulio Valentino Dalla Riva

Gotcha! I'll try that now. Thanks!

[julia-users] curl: (22) The requested URL returned error: 403

2014-09-30 Thread Ivar Nesje

Try again later and check your Internet connection.

[julia-users] Concurrent programming in Julia

2014-09-30 Thread Vladimir Matveev

Hi!

I'm new to Julia and I find it wonderful (especially for maths 
programming), but I have difficulties writing concurrent programs in it - 
it seems that I don't understand some basic concepts here.

I usually work with languages which support thread-based concurrency and 
allow spawning a number of threads/tasks sharing the same memory space 
(e.g. Scala, Rust, etc.). However, now I need to write a few math programs 
in Julia. The algorithms are quite CPU-heavy but can easily be parallelized 
(most of them boil down to for loops with independent iterations), and 
Julia does have an ability to write parallel programs. However, I just 
don't understand *how* to write them properly.

Here is an outline of one of the programs (not in any particular language):

(1) coeffs - compute approximation of function

(2) f(s) = a function which uses coeffs

(3) data - compute some data using f

(4) plot data

My current implementation (partially working) can be found here 
https://gist.github.com/netvl/8cfc0fb8dc487b0f536c: 

(1), (2), (3) and (4) must obviously be executed in order because each step 
depends on the results of previous step. However, algorithms in (1) and 
(3), which are the most time-consuming ones, can easily be parallelized 
(they are two big for loops filling one-dimensional and two-dimensional 
arrays, correspondingly).

In conventional language I would just spawn a bunch of threads or start a 
thread pool which will compute these arrays in parallel, and then just use 
their data directly in the main thread. This is the most straightforward 
and easiest way with regular thread-based concurrency. The thread pool is 
only used locally in steps (1) and (3), and spawned threads are not 
concerned with the rest of the program *at all*.

Julia, however, does not have thread abstraction. Instead it provides 
workers, which are separate processes, and it also provides means to 
transfer data between processes. Unfortunately, I couldn't find proper 
documentation on how to use these tools in nontrivial situations (official 
Julia documentation is just not sufficient), and this is a big problem - 
conventional approach just doesn't work here. The biggest problem, as far 
as I can see, is that these workers are not local - they must know 
about other parts of the program to work correctly, even if they are used 
only for several specific computations locally.

First of all, `f` must be available on all workers in order for (3) to work 
at all. The suggested approach is to use `@everywhere` macro:

coeffs = approx(...)

@everywhere function f(s) 
# coeffs are used here
end

But `f` uses `coeffs` computed on the previous step, so `coeffs` should 
also be `@everywhere`'d - otherwise step (3) fails in workers. But this 
means that approximation will be computed multiple times, one on each 
worker, correct? I have some text printed in step (1), and if I write 
something like

@everywhere coeffs = approx(...)

I can see that `approx()` is called from all of the workers (though for 
some reason their output is only printed after step (4), just before the 
program ends). So, the first problem is that I don't know how to define a 
piece of data which should only be computed once, probably in parallel, and 
then shared among all workers. `@everywhere` is close, as it defines a 
binding in all workers, but it invokes the computation multiple times. I 
couldn't come up with simple workaround for this.

Second, by extension of the above I have put `@everywhere` literally 
everywhere. You can see in the gist that the main script contains 
@everywhere on almost every line. It looks weird and I just don't believe 
that this is the right way, but without all of these `@everywhere`s workers 
will fail with various kinds of undefined errors. This *may* be expected 
as the workers are independent programs, but this is rather surprising from 
thread-based point of view.

And finally, when I rewrote my program to run in parallel, plotting on step 
(4) just stopped working. I mean, when I run my program, it just hangs in 
`plot()` function after writing done. and the plot window is not 
displayed. It looks like some kind of interference with PyPlot, but I don't 
know the exact reason and I don't know how to debug it.

So, my question is: how do I write a program which has multiple local 
parallel sections which should be executed sequentially due to data 
dependencies between them? As a subquestion, how to transfer data between 
workers if it should only be computed once and if this data is used 
indirectly through other definitions? As an another subquestion, how do you 
avoid writing `@everywhere` everywhere when there is a lot of definitions 
which should be available for all workers? And why plotting stopped working?

Thanks in advance,

Vladimir.

[julia-users] Pkg.add fail

2014-09-30 Thread Ivar Nesje

A good start would be to post the output from Pkg.status() here. That makes it 
easier to see how packages might interact to cause this situation.

Re: [julia-users] curl: (22) The requested URL returned error: 403

2014-09-30 Thread Mike Nolta

Looks like patchelf-0.8.tar.gz didn't have the right permissions on
our mirror. Should be fixed now.

-Mike

On Tue, Sep 30, 2014 at 4:49 PM, Ivar Nesje iva...@gmail.com wrote:
 Try again later and check your Internet connection.

[julia-users] Re: cannot add any packages - Julia on Windows7 x64

2014-09-30 Thread Ivar Nesje

Seems like you are self compiling on Windows?

I think I heard something about git being broken in one of the Unix like 
environments on Windows. Did you follow the instructions in README.md and 
README.windows?

[julia-users] Re: Module issues


To be able to access your modules by default, you can simply place the 
TestModule.jl file in 

/Users/username/.julia/v0.3 

This folder should contain all the Julia packages/modules. 

Then type using TestModule to use your function in the Julia console.
Max


On Tuesday, September 30, 2014 9:18:15 PM UTC+2, Gerry Weaver wrote:

 Hi Max,

 I was trying to figure out where to put modules, so that Julia would be 
 able to use them by default. In my case, /usr/share/julia/site/v3.0 is in 
 LOAD_PATH. However, when I put my code there Julia can't see it. Is there 
 something that I'm missing?

 Thanks,
 Gerry

 On Tuesday, September 30, 2014 7:07:07 AM UTC-5, Max Suster wrote:


 Your code should work fine if you put the module in a directory that can 
 be accessed.  
 If you running julia in the directory where the module is located, you 
 can recall the full path with:

 joinpath(pwd(), TestModule.jl)

 *j*ulia using TestModule

 julia println(LOAD_PATH)


 Union(UTF8String,ASCIIString)[/Users/maximilianosuster/julia/usr/local/share/julia/site/v0.3,/Users/maximilianosuster/julia/usr/share/julia/site/v0.3]

 julia test_func

 test_func (generic function with 1 method)

 julia test_func(TestVal)

 TestVal





 On Tuesday, September 30, 2014 11:45:38 AM UTC+2, Gerry Weaver wrote:

 Hello All,

 I am trying to define and use a module. I have the following code.


 module TestModule

 export test_func

 function test_func(val)
   println(val)
 end

 end


 ---


 #!/usr/bin/julia

 using TestModule

 println(LOAD_PATH)

 test_func(TestVal)


 I have put the module source file under the path 
 LOAD_PATH/TestModule/src/TestModule.jl. I've tried a variety of other 
 variations, but to no avail. Is there something that I am doing wrong? I 
 get Warning: requiring TestModule did not define a corresponding 
 module. when I try to use (using)  the module.

 Thanks,
 Gerry

[julia-users] Re: Pkg.add fail

2014-09-30 Thread Laszlo Hars

julia  Pkg.status()
7 required packages:
 - CUDA  0.1.0  2caa0935 (dirty)
 - Cairo 0.2.12 f2f8203f (dirty)
 - Gaston0.0.0  3ac1410f (dirty)
 - IJulia0.1.12
 - Quaternions   0.0.4
 - Tk0.2.13
 - Winston   0.11.2
28 additional packages:
 - BinDeps   0.2.14
 - Calculus  0.1.4
 - Cartesian 0.2.2
 - Color 0.2.10
 - DualNumbers   0.1.0
 - GLAbstraction 0.0.0- master (unregistered)
 - GLFW  1.0.0-alpha.1
 - GLPlot0.0.0- master (unregistered, 
dirty)
 - GLWindow  0.0.0- master (unregistered)
 - HTTPClient0.1.4
 - Images0.2.47
 - ImmutableArrays   0.0.6
 - IniFile   0.2.2
 - JSON  0.3.7
 - LibCURL   0.1.3
 - LibExpat  0.0.4
 - ModernGL  0.0.0- master (unregistered)
 - Mustache  0.0.3
 - Nettle0.1.4
 - REPLCompletions   0.0.1
 - React 0.1.3
 - SIUnits   0.0.2
 - TexExtensions 0.0.1
 - URIParser 0.0.2
 - URLParse  0.0.0
 - WinRPM0.1.1
 - ZMQ   0.1.13
 - Zlib  0.1.7

On Tuesday, September 30, 2014 2:57:05 PM UTC-6, Ivar Nesje wrote:

 A good start would be to post the output from Pkg.status() here. That 
 makes it easier to see how packages might interact to cause this situation.

[julia-users] Re: Pkg.add fail

2014-09-30 Thread Laszlo Hars

...and Pkg.update() lists thousands of errors, finishing with:

WARNING: Images and Cairo had build errors...

After these Jewel can be added. Strange...

Re: [julia-users] Re: Calling Julia from .NET

The  indicates the cmd prompt working directory:
```
C:\cmn\Julia-0.3.0bin\ConsoleApplication2.exe
1.4142135623730951
```
Otherwise, try passing the bin path as a char* to jl_init as suggested.


On Tue, Sep 30, 2014 at 11:24 AM, Stefan Babinec sysli...@gmail.com wrote:

 I've copied exe file directly to julia's bin directory Isaiah.

 And I get the above mentioned error when I try to run it in the bin
 directory.


 On Tuesday, September 30, 2014 4:57:41 PM UTC+2, Isaiah wrote:

 Try running it from the Julia directory as `bin\CommandLine2.exe`. This
 is very much a minimal example; for general use, the bin directory should
 be passed as an argument to `jl_init`:

 https://github.com/JuliaLang/julia/blob/1ee440bee5035ccb33f82b8a45febd
 dd2f973baa/src/jlapi.c#L70-L73

 To go much further than this will really require to dig in to both
 jlapi.c and the general Julia source code. Be aware that dealing with type
 translation and garbage collection are both non-trivial. See also
 `examples/embedding.c` in the julia tree, and several previous discussion
 on the mailing list.

 On Tue, Sep 30, 2014 at 9:08 AM, Stefan Babinec sysl...@gmail.com
 wrote:

 Hi Isaiah.

 I tried and got this error:
 System image file  ?l\../lib/julia/sys.ji not found

 System Image sys.ji looks to be on his place and I have no problem
 running Julia.

 Thanks.


 On Tuesday, September 30, 2014 2:03:42 PM UTC+2, Isaiah wrote:

 I should mention that it is necessary to change the project target CPU
 from the default Any to x64 or x86 to match the libjulia architecture.
 On Sep 29, 2014 11:58 PM, Isaiah Norton isaiah...@gmail.com wrote:

 I tried this some time ago during 0.2, so to make sure it still works
 I made a minimal translation of the embedding example to C#:

 ```
 using System;
 using System.Runtime.InteropServices;

 namespace ConsoleApplication2
 {
 class Program
 {
 [DllImport(libjulia.dll)]
 static extern void jl_init();
 [DllImport(libjulia.dll)]
 static extern void jl_eval_string(string message);

 static void Main(string[] args)
 {
 jl_init();
 jl_eval_string(print(sqrt(2.0)));
 }
 }
 }
 ```

 I compiled this, copied the binary into `Julia-0.3.0\bin`, and it
 works:

 ```
 C:\cmn\Julia-0.3.0bin\ConsoleApplication2.exe
 1.4142135623730951
 ```


 On Mon, Sep 29, 2014 at 4:11 PM, Tobias Knopp 
 tobias...@googlemail.com wrote:

 yep, I have done this (mostly for fun) before and it works. One needs
 some experience with P/Invoke of course but this is no magic but similar 
 to
 our ccall.

 Cheers,

 Tobi

 Am Montag, 29. September 2014 20:52:10 UTC+2 schrieb Stefan Karpinski:

 I assume that you can call C libraries from .NET, right? The C
 library for Julia is libjulia – how to call it from C is explained in 
 the
 embedding docs, calling it from .NET should be similar.


  On Sep 29, 2014, at 12:37 PM, Guido De Bouver 
 guido.d...@telenet.be wrote:
 
  I have not found the C# examples, but I have not looked for them.
 Sorry for that.
 
  So, any help on this, how could we call Julia from .NET

Re: [julia-users] change location of .julia folderd on windows xp

2014-09-30 Thread Adrian Torrie

Thanks Isaiah,

I created a system variable JULIA_PKGDIR with the path I wanted.

Restarted Julia and ran 
Pkg.init()



On Tuesday, 30 September 2014 12:32:01 UTC+10, Isaiah wrote:

 That batch file doesn't start Julia. You will need to add JULIA_PKGDIR to 
 your environment, or set it via a batch file that does start julia.exe.

 On Mon, Sep 29, 2014 at 10:09 PM, Adrian Torrie adrian...@gmail.com 
 javascript: wrote:

 Hi,

 Current location of the .julia folder is not appropriate due to size 
 limitations of roaming profile set by corporate domain admins. I cannot 
 change the size of my roaming profile as I do not have domain admin rights.

 I would like to be able to change the package install directory to 
 another place on my C:\ drive. I have local admin rights. I have installed 
 julia to: C:\Julia\Julia-0.3.1\

 I tried changing C:\Julia\Julia-0.3.1\bin\prepare-julia-env.bat by 
 adding the line set JULIA_PKGDIR=C:\Julia\Julia-0.3.1\share\packages 
 without 
 any success (it still initialises in %APPDATA%\.julia):
 @rem
 @rem  This file attempts to auto detect and configure the environment
 @rem  for starting julia and julia-web-server
 @rem
 @rem  It sets the path as needed to reference various lib and bin
 @rem  files, and builds sys.ji if needed.
 @rem


 set JULIA_PKGDIR=C:\Julia\Julia-0.3.1\share\packages
 set SYS_PATH=%PATH%
 set PATH=%~dp0;%~dp0bin;%~dp0usr\bin;%~dp0..\usr\bin;%~dp0..\..\usr\bin;%
 SYS_PATH%
 set JULIA_EXE=julia.exe
 for %%A in (%JULIA_EXE%) do set JULIA_HOME=%%~dp$PATH:A
 set JULIA=%JULIA_HOME%%JULIA_EXE%
 set PATH=%SYS_PATH%


 set private_libdir=bin
 if not exist %JULIA_HOME%..\lib\julia\sys.ji ( ^
 echo Preparing Julia for first launch. This may take a while  ^
 echo You may see two git related errors. This is completely normal  ^
 cd %JULIA_HOME%..\share\julia\base  ^
 %JULIA% --build %JULIA_HOME%..\lib\julia\sys0 sysimg.jl  ^
 %JULIA% --build %JULIA_HOME%..\lib\julia\sys -J sys0.ji sysimg.jl  
 ^
 popd  pushd %cd% )

 Unsure of how to proceed to put the package installs into a custom 
 location, any help would be appreciated.

 Regards,
 Adrian

Re: [julia-users] Re: a good IDE for Julia ? (Julia Studio does not work with Julia v 0.3.0)

2014-09-30 Thread Bradley Setzler

If anyone can get Julia Studio to work with Julia 0.3, that would great,
but I have had no luck. You can read here
https://groups.google.com/forum/#!searchin/julia-users/julia$20studio/julia-users/N-__nw3Wd04/eHshKzndRqgJ

about Forio discontinuing support for Julia Studio.

Best,
Bradley

On Tuesday, September 30, 2014 10:58:42 AM UTC-5, Leah Hanson wrote:

Maybe you could start a new julia-users thread, and post the code and the
error message so we can help? It's hard to make specific recommendations
without seeing the code/error.

-- Leah

On Tue, Sep 30, 2014 at 9:27 AM, Ján Dolinský jan.do...@2bridgz.com
javascript: wrote:

Hello guys,

Indeed, www.junolab.org makes me want to go with Julia farther too :).

I was asking about debugging because I implemented a custom type (in a
module) of which constructor is failing somewhere but I just get an error
about some array multiplication in some julia file instead of a concrete
line number in the constructor function. Any idea how to get through this ?

Thanks a lot,
Jan

Dňa pondelok, 29. septembra 2014 12:27:07 UTC+2 Viral Shah napísal(-a):

The light table work that Mike Innes has done is now packaged and
available at http://www.junolab.org/

We are hoping to work towards making self-sufficient binaries and
getting it to a point where it is usable with a single download. The real
fun is to then try and do more interesting things. I don't know what those
are, but I do feel that we are setting ourselves up with a good base.

-viral

On Saturday, September 27, 2014 12:38:39 PM UTC+5:30,
colint...@gmail.com wrote:

No, I don't think it has debugging a la the Matlab IDE or R-Studio
(yet). My understanding is that for now the Debug package is all that is
available. Personally I make do with sending blocks of code to a console
in
Sublime-IJulia (you can do this with shift+enter, just like in R-Studio).

Cheers,

Colin

On Friday, September 26, 2014 7:00:09 PM UTC+10, Ján Dolinský wrote:

Hello,

I cloned the master branch of Julia Studio and compiled it. I am
however getting this error when running ./JuliaStudio :
libExtensionSystem.so.1: cannot open shared object file: No such file
or directory

however when running using ./julia-studio.sh it runs but fails to open
a console with the following errors:
Error: Failed to start Julia.
Expected location: /usr/local/Julia_Studio/julia

I am little bit lost here but exploring the Julia Studio menu I assume
that it doe not provide debugging capability (I had an impression that it
does).

Thanks,
Jan

Dňa piatok, 19. septembra 2014 11:57:47 UTC+2 Uwe Fechner napísal(-a):

I think that this branch is already merged into the master branch:
https://github.com/forio/julia-studio/tree/julia-0.3-compatibility

On Friday, September 19, 2014 11:54:41 AM UTC+2, Uwe Fechner wrote:

If you compile Julia Studio from source it should work with Julia
0.3. See:
https://github.com/forio/julia-studio/issues/241

Regards:

Uwe

On Friday, September 19, 2014 10:58:26 AM UTC+2, Ján Dolinský wrote:

Hello guys,

After upgrading to Julia 0.3.0 Julia Studio stopped working (I
changed the symbolic links in Julia Studio directory but nevertheless
...).
Can somebody suggest any workaround ? Is it true that Julia Studio
will not
support newer versions of Julia ?
What are you guys using now ?

Thanks a lot,
Jan

[julia-users] Simple benchmark improvement question

2014-09-30 Thread dextorious

Greetings,

I'm a reasonably proficient user of MATLAB and Python/NumPy/SciPy doing 
computational physics. Since Julia appears to be designed to be very well 
suited to many such applications, I was curious to test its performance 
before investing much time in converting any research code. To start out, I 
wrote up the classic 2D regular finite difference Laplace benchmark in 
Julia, Python and MATLAB in both vectorized and loop versions and tested 
them all. 

The results shown in the following Google spreadsheet (all results obtained 
using a 5000x5000 grid and doing 100 iterations for a reasonable sample 
using a Haswell i7-4710HQ CPU on Windows 8.1, using Julia 0.3.1, Anaconda 
2.0.1 and MATLAB R2014a):
https://docs.google.com/spreadsheets/d/1mJ8wNiyYVszkVapRVHvRJZG9j9XQhLLPvaUJwiWrJXY/pubhtml

The code itself is published as follows:
Julia: http://pastebin.com/AAdXXYZC
Python: http://pastebin.com/5hqi9xzf

As can be clearly seen, Julia does handily beat both MATLAB and basic 
Python/NumPy. It does however lose by a factor of 1.65 to a Numba-jitted 
version of the same Python code (obtained by simply adding a 
@jit(target='cpu') decorator on top of the appropriate function in naive 
Python code), which compiles to the same LLVM stack Julia uses. I 
deliberately avoided using more complex JIT techniques for Python (such as 
using Pythran to compile to OpenMP-enabled C code by specifying function 
signatures) to stick to single core performance only.

Given these results and the virtual given that my Julia code is naive, 
non-idiomatic and just plain bad, I'd like to know if there's anything I 
could improve to match or (if possible) beat JIT-compiled Python.

Re: [julia-users] Simple benchmark improvement question

2014-09-30 Thread Stefan Karpinski

Your code looks quite good – and the devectorized version avoids creating
copies of slices, which is currently one of the major performance issues
with this kind of code (to be fixed in the next major release). You can see
the inferred types of all the local variables like this: (@code_typed
laplace_unvectorized())[1].args[2][2] – and everything has a concrete type,
so there's nothing to improve in terms of typing.

Adding the @inbounds annotation to the innermost for loop was one of the
first things I thought to try, but that doesn't seem to have any benefit –
I think the array accesses are all inlined and LLVM can hoist the bounds
checks out of the loop (or eliminate them entirely).

What does end up making a big difference is swapping the iteration order of
i and j. Instead of doing `for i=2:nx-1, j=2:ny-1` do `for j=2:ny-1,
i=2:nx-1` – I don't recall whether NumPy arrays are row-major (I think they
are) but Julia is column-major like Fortran and you want to iterate along
columns innermost. On my machine, doing it in the original order is 1.61x
slower, which may be exactly the explanation of the difference you're
seeing between Julia and Numba.

On Tue, Sep 30, 2014 at 7:08 PM, dextori...@gmail.com wrote:

 Greetings,

 I'm a reasonably proficient user of MATLAB and Python/NumPy/SciPy doing
 computational physics. Since Julia appears to be designed to be very well
 suited to many such applications, I was curious to test its performance
 before investing much time in converting any research code. To start out, I
 wrote up the classic 2D regular finite difference Laplace benchmark in
 Julia, Python and MATLAB in both vectorized and loop versions and tested
 them all.

 The results shown in the following Google spreadsheet (all results
 obtained using a 5000x5000 grid and doing 100 iterations for a reasonable
 sample using a Haswell i7-4710HQ CPU on Windows 8.1, using Julia 0.3.1,
 Anaconda 2.0.1 and MATLAB R2014a):

 https://docs.google.com/spreadsheets/d/1mJ8wNiyYVszkVapRVHvRJZG9j9XQhLLPvaUJwiWrJXY/pubhtml

 The code itself is published as follows:
 Julia: http://pastebin.com/AAdXXYZC
 Python: http://pastebin.com/5hqi9xzf

 As can be clearly seen, Julia does handily beat both MATLAB and basic
 Python/NumPy. It does however lose by a factor of 1.65 to a Numba-jitted
 version of the same Python code (obtained by simply adding a
 @jit(target='cpu') decorator on top of the appropriate function in naive
 Python code), which compiles to the same LLVM stack Julia uses. I
 deliberately avoided using more complex JIT techniques for Python (such as
 using Pythran to compile to OpenMP-enabled C code by specifying function
 signatures) to stick to single core performance only.

 Given these results and the virtual given that my Julia code is naive,
 non-idiomatic and just plain bad, I'd like to know if there's anything I
 could improve to match or (if possible) beat JIT-compiled Python.

[julia-users] ANN: ValidatedNumerics.jl 0.0.1 -- interval arithmetic for Julia

2014-09-30 Thread David P. Sanders


This is an announcement of a preliminary version of ValidatedNumerics.jl,
a Julia package for performing validated floating-point calculations via 
interval arithmetic.

Currently, the package consists of a pure-Julia implementation of interval 
arithmetic. It uses macros extensively to produce intervals that are 
rigorously guaranteed to enclose the user's input. These can then be 
manipulated using standard arithmetic operations and elementary functions:

julia a = @interval(π)
[3.1415926535897931e+00, 3.1415926535897936e+00] with 53 bits of precision

julia b = @interval(0.1+pi, pi^2)
[3.2415926535897928e+00, 9.8696044010893615e+00] with 53 bits of precision

julia a * b
[1.0183763666448336e+01, 3.1006276680299834e+01] with 53 bits of precision

julia exp(a-b)
[1.196910353930426e-03, 9.0483741803596041e-01] with 53 bits of precision

Further examples are given in the README at

https://github.com/dpsanders/ValidatedNumerics.jl

Functionality building on top of this base, such as root-finding methods, 
are currently in active development. A comparison and/or tests with the 
MPFI.jl wrapper around the MPFI interval library is also planned.

Suggestions and contributions are warmly welcomed.

The authors of the package are Luis Benet and David P. Sanders.

[julia-users] Geometry package

2014-09-30 Thread Yakir Gagnon

A Geometry package has been discussed here 
https://groups.google.com/d/topic/julia-dev/vZpZ8NBX_z8/discussion and 
here https://groups.google.com/d/topic/julia-dev/fqwnyOojRdg/discussion 
(Spherical, 
Geographic, Homogeneous coordinate systems in 1 to 4 dimensions and more).

I'm in need of something significantly simpler: a Geometry module for a 
Cartesian coordinate system in 3D with Point, Direction, and Line types. 
Has anyone written something like that? Maybe that ambitious Geometry 
package is further along or been announced and I missed it?

Thanks a bunch!

Re: [julia-users] ANN: ValidatedNumerics.jl 0.0.1 -- interval arithmetic for Julia

2014-09-30 Thread Stefan Karpinski

This is super cool.

On Tue, Sep 30, 2014 at 8:01 PM, David P. Sanders dpsand...@gmail.com
wrote:


 This is an announcement of a preliminary version of ValidatedNumerics.jl,
 a Julia package for performing validated floating-point calculations via
 interval arithmetic.

 Currently, the package consists of a pure-Julia implementation of interval
 arithmetic. It uses macros extensively to produce intervals that are
 rigorously guaranteed to enclose the user's input. These can then be
 manipulated using standard arithmetic operations and elementary functions:

 julia a = @interval(π)
 [3.1415926535897931e+00, 3.1415926535897936e+00] with 53 bits of precision

 julia b = @interval(0.1+pi, pi^2)
 [3.2415926535897928e+00, 9.8696044010893615e+00] with 53 bits of precision

 julia a * b
 [1.0183763666448336e+01, 3.1006276680299834e+01] with 53 bits of precision

 julia exp(a-b)
 [1.196910353930426e-03, 9.0483741803596041e-01] with 53 bits of precision

 Further examples are given in the README at

 https://github.com/dpsanders/ValidatedNumerics.jl

 Functionality building on top of this base, such as root-finding methods,
 are currently in active development. A comparison and/or tests with the
 MPFI.jl wrapper around the MPFI interval library is also planned.

 Suggestions and contributions are warmly welcomed.

 The authors of the package are Luis Benet and David P. Sanders.

Re: [julia-users] ANN: ValidatedNumerics.jl 0.0.1 -- interval arithmetic for Julia

2014-09-30 Thread David P. Sanders



El martes, 30 de septiembre de 2014 19:11:56 UTC-5, Stefan Karpinski 
escribió:

 This is super cool.


Glad you like it! :)
I have to get round to adding the cute `..` syntax from your notebook 
(which is great, by the way! And probably still mineable for more useful 
tidbits)
 


 On Tue, Sep 30, 2014 at 8:01 PM, David P. Sanders dpsa...@gmail.com 
 javascript: wrote:


 This is an announcement of a preliminary version of ValidatedNumerics.jl,
 a Julia package for performing validated floating-point calculations via 
 interval arithmetic.

 Currently, the package consists of a pure-Julia implementation of 
 interval arithmetic. It uses macros extensively to produce intervals that 
 are rigorously guaranteed to enclose the user's input. These can then be 
 manipulated using standard arithmetic operations and elementary functions:

 julia a = @interval(π)
 [3.1415926535897931e+00, 3.1415926535897936e+00] with 53 bits of precision

 julia b = @interval(0.1+pi, pi^2)
 [3.2415926535897928e+00, 9.8696044010893615e+00] with 53 bits of precision

 julia a * b
 [1.0183763666448336e+01, 3.1006276680299834e+01] with 53 bits of precision

 julia exp(a-b)
 [1.196910353930426e-03, 9.0483741803596041e-01] with 53 bits of precision

 Further examples are given in the README at

 https://github.com/dpsanders/ValidatedNumerics.jl

 Functionality building on top of this base, such as root-finding methods, 
 are currently in active development. A comparison and/or tests with the 
 MPFI.jl wrapper around the MPFI interval library is also planned.

 Suggestions and contributions are warmly welcomed.

 The authors of the package are Luis Benet and David P. Sanders.

Re: [julia-users] curl: (22) The requested URL returned error: 403

2014-09-30 Thread Staro Pickle

Thanks a lot.

On Wednesday, October 1, 2014 4:57:06 AM UTC+8, Mike Nolta wrote:

 Looks like patchelf-0.8.tar.gz didn't have the right permissions on 
 our mirror. Should be fixed now. 

 -Mike 

 On Tue, Sep 30, 2014 at 4:49 PM, Ivar Nesje iva...@gmail.com 
 javascript: wrote: 
  Try again later and check your Internet connection.

Re: [julia-users] ANN: ValidatedNumerics.jl 0.0.1 -- interval arithmetic for Julia

2014-09-30 Thread Stefan Karpinski

We may actually end up using that for real field access and allowing a.b
to be overloaded, so it may be ill advised to use a..b. I think that a ± b
should be safe though.

On Tue, Sep 30, 2014 at 8:21 PM, David P. Sanders dpsand...@gmail.com
wrote:



 El martes, 30 de septiembre de 2014 19:11:56 UTC-5, Stefan Karpinski
 escribió:

 This is super cool.


 Glad you like it! :)
 I have to get round to adding the cute `..` syntax from your notebook
 (which is great, by the way! And probably still mineable for more useful
 tidbits)



 On Tue, Sep 30, 2014 at 8:01 PM, David P. Sanders dpsa...@gmail.com
 wrote:


 This is an announcement of a preliminary version of ValidatedNumerics.jl,
 a Julia package for performing validated floating-point calculations via
 interval arithmetic.

 Currently, the package consists of a pure-Julia implementation of
 interval arithmetic. It uses macros extensively to produce intervals that
 are rigorously guaranteed to enclose the user's input. These can then be
 manipulated using standard arithmetic operations and elementary functions:

 julia a = @interval(π)
 [3.1415926535897931e+00, 3.1415926535897936e+00] with 53 bits of
 precision

 julia b = @interval(0.1+pi, pi^2)
 [3.2415926535897928e+00, 9.8696044010893615e+00] with 53 bits of
 precision

 julia a * b
 [1.0183763666448336e+01, 3.1006276680299834e+01] with 53 bits of
 precision

 julia exp(a-b)
 [1.196910353930426e-03, 9.0483741803596041e-01] with 53 bits of precision

 Further examples are given in the README at

 https://github.com/dpsanders/ValidatedNumerics.jl

 Functionality building on top of this base, such as root-finding
 methods, are currently in active development. A comparison and/or tests
 with the MPFI.jl wrapper around the MPFI interval library is also planned.

 Suggestions and contributions are warmly welcomed.

 The authors of the package are Luis Benet and David P. Sanders.

Re: [julia-users] ANN: ValidatedNumerics.jl 0.0.1 -- interval arithmetic for Julia

2014-09-30 Thread David P. Sanders

On Tue, Sep 30, 2014 at 7:27 PM, Stefan Karpinski ste...@karpinski.org
wrote:

 We may actually end up using that for real field access and allowing a.b
 to be overloaded, so it may be ill advised to use a..b. I think that a ± b
 should be safe though.


OK, good to know, thanks; I'll hold off for now, then.



 On Tue, Sep 30, 2014 at 8:21 PM, David P. Sanders dpsand...@gmail.com
 wrote:



 El martes, 30 de septiembre de 2014 19:11:56 UTC-5, Stefan Karpinski
 escribió:

 This is super cool.


 Glad you like it! :)
 I have to get round to adding the cute `..` syntax from your notebook
 (which is great, by the way! And probably still mineable for more useful
 tidbits)



 On Tue, Sep 30, 2014 at 8:01 PM, David P. Sanders dpsa...@gmail.com
 wrote:


 This is an announcement of a preliminary version of
 ValidatedNumerics.jl,
 a Julia package for performing validated floating-point calculations
 via interval arithmetic.

 Currently, the package consists of a pure-Julia implementation of
 interval arithmetic. It uses macros extensively to produce intervals that
 are rigorously guaranteed to enclose the user's input. These can then be
 manipulated using standard arithmetic operations and elementary functions:

 julia a = @interval(π)
 [3.1415926535897931e+00, 3.1415926535897936e+00] with 53 bits of
 precision

 julia b = @interval(0.1+pi, pi^2)
 [3.2415926535897928e+00, 9.8696044010893615e+00] with 53 bits of
 precision

 julia a * b
 [1.0183763666448336e+01, 3.1006276680299834e+01] with 53 bits of
 precision

 julia exp(a-b)
 [1.196910353930426e-03, 9.0483741803596041e-01] with 53 bits of
 precision

 Further examples are given in the README at

 https://github.com/dpsanders/ValidatedNumerics.jl

 Functionality building on top of this base, such as root-finding
 methods, are currently in active development. A comparison and/or tests
 with the MPFI.jl wrapper around the MPFI interval library is also planned.

 Suggestions and contributions are warmly welcomed.

 The authors of the package are Luis Benet and David P. Sanders.






-- 
Dr. David P. Sanders

Profesor Titular A / Associate Professor
Departamento de Física, Facultad de Ciencias
Universidad Nacional Autónoma de México (UNAM)

dpsand...@ciencias.unam.mx
http://sistemas.fciencias.unam.mx/~dsanders

Cubículo / office: #414, 4o. piso del Depto. de Física

Tel.: +52 55 5622 4965

[julia-users] Re: cannot add any packages - Julia on Windows7 x64

2014-09-30 Thread Felix

Try 
Pkg.clone(https://github.com/JuliaLang/WinRPM.jl.git;)

for WinRPM, it might fail because it needs Zlib
so 

Pkg.clone(https://github.com/dcjones/Zlib.jl.git;) first.

it worked for me on windows

[julia-users] JuliaBox early users

2014-09-30 Thread Viral Shah

Folks,

We are almost ready to accommodate more users on JuliaBox. It is already being 
used in a couple of classes. It is not yet ready to be thrown open publicly, 
but we need early users who will help us make it better, test it out, and 
demand interesting new things!

If you would like to use it in a class, let us know and we will send you a code 
and help out in any way we can to support teaching Julia in the classroom.

If you would just like to try it out, we will send you a code. However, you 
have to promise us that you will file lots of issues to help make it better. :-)

We hope that it should be generally available in a few weeks, and that we will 
magically get compute time grants!

-viral

[julia-users] JuliaBox early users

2014-09-30 Thread Thomas Covert

Great!  How do I get an invitation code?

[julia-users] Re: JuliaBox early users

2014-09-30 Thread Viral Shah

Just write to me or @Shashi (https://github.com/shashi).

-viral

On Wednesday, October 1, 2014 10:00:13 AM UTC+5:30, Thomas Covert wrote:

 Great!  How do I get an invitation code?

[julia-users] Re: JuliaBox early users

2014-09-30 Thread Viral Shah

And here's the mailing list:

https://groups.google.com/forum/#!forum/julia-box

-viral

On Wednesday, October 1, 2014 8:49:27 AM UTC+5:30, Viral Shah wrote:

 Folks, 

 We are almost ready to accommodate more users on JuliaBox. It is already 
 being used in a couple of classes. It is not yet ready to be thrown open 
 publicly, but we need early users who will help us make it better, test it 
 out, and demand interesting new things! 

 If you would like to use it in a class, let us know and we will send you a 
 code and help out in any way we can to support teaching Julia in the 
 classroom. 

 If you would just like to try it out, we will send you a code. However, 
 you have to promise us that you will file lots of issues to help make it 
 better. :-) 

 We hope that it should be generally available in a few weeks, and that we 
 will magically get compute time grants! 

 -viral

[julia-users] Re: cannot add any packages - Julia on Windows7 x64

2014-09-30 Thread xaphoon

Thanks for the information.
I installed another Julia version, but still cannot use packages; now error 
messages are different:

julia versioninfo()
Julia Version 0.3.1
Commit c03f413* (2014-09-21 21:30 UTC)
Platform Info:
  System: Windows (x86_64-w64-mingw32)
  CPU: Intel(R) Core(TM) i7-2600 CPU @ 3.40GHz
  WORD_SIZE: 64
  BLAS: libopenblas (USE64BITINT DYNAMIC_ARCH NO_AFFINITY Sandybridge)
  LAPACK: libopenblas
  LIBM: libopenlibm
  LLVM: libLLVM-3.3

julia Pkg.clone(https://github.com/dcjones/Zlib.jl.git;)
ERROR: stat: unknown error (UNKNOWN)
 in stat at stat.jl:40

julia Pkg.clone(https://github.com/JuliaLang/WinRPM.jl.git;)
ERROR: stat: unknown error (UNKNOWN)
 in stat at stat.jl:40

julia Pkg.add(Example)
INFO: Cloning cache of Example from 
git://github.com/JuliaLang/Example.jl.git
INFO: Installing Example v0.3.3
error: internal error: refs/remotes/origin/master is not a valid packed 
reference!
error: internal error: refs/tags/v0.0.1 is not a valid packed reference!
error: internal error: refs/tags/v0.0.2 is not a valid packed reference!
error: internal error: refs/tags/v0.1 is not a valid packed reference!
error: internal error: refs/tags/v0.1.0 is not a valid packed reference!
error: internal error: refs/tags/v0.2.0 is not a valid packed reference!
error: internal error: refs/tags/v0.2.1 is not a valid packed reference!
error: internal error: refs/tags/v0.3.0 is not a valid packed reference!
error: internal error: refs/tags/v0.3.1 is not a valid packed reference!
error: internal error: refs/tags/v0.3.2 is not a valid packed reference!
error: internal error: refs/tags/v0.3.3 is not a valid packed reference!
error: Trying to write ref refs/heads/master with nonexistent object 
98f978a0c5276e0df5445f0a3891380adda788bc
fatal: Cannot update the ref 'HEAD'.
fatal: The remote end hung up unexpectedly

ERROR: failed process: Process(`git clone -q 
'S:\.julia\v0.3\.cache\Example' Example`, ProcessExited(128)) [128]
 in wait at task.jl:51



julia
julia Pkg.add(Gadfly)
fatal: Not a git repository: 'S:\.julia\v0.3\Example\.git'
ERROR: failed process: Process(`git '--work-tree=S:\.julia\v0.3\Example' 
'--git-dir=S:\.julia\v0.3\Example\.git' rev-parse HEAD`, 
ProcessExited(128)) [128]
 in wait at task.jl:51
 in cmd_gen at process.jl:608
 in add at pkg/entry.jl:319
 in add at pkg/entry.jl:44

julia

julia Pkg.add(Helpme)
fatal: Not a git repository: 'S:\.julia\v0.3\Example\.git'
ERROR: failed process: Process(`git '--work-tree=S:\.julia\v0.3\Example' 
'--git-dir=S:\.julia\v0.3\Example\.git' rev-parse HEAD`, 
ProcessExited(128)) [128]
 in wait at task.jl:51
 in cmd_gen at process.jl:608
 in add at pkg/entry.jl:319
 in add at pkg/entry.jl:44

julia

What else can I try?

Regards, Igor

Re: [julia-users] Re: cannot add any packages - Julia on Windows7 x64