For about two weeks now, Zac Cranko, Pasquale Minervini, and I (Alireza
Nejati a.k.a. anj1) have been working on a new package for neural networks
in julia: NeuralNets.jl https://github.com/anj1/NeuralNets.jl.
The goal is to create a clean, modular implementation of neural networks
that can
Hi,
I get the following error:
julia using Images
ERROR: syntax: invalid assignment location
in include at ./boot.jl:245
in include_from_node1 at ./loading.jl:128
in include at ./boot.jl:245
in include_from_node1 at ./loading.jl:128
in reload_path at loading.jl:152
in _require at
It still needs relative imports with one dot:
julia module A
module B
foo()=4
export foo
end
using .B
foo()
end
Which is a bit odd. Because at the REPL, which is in module Main, this
is not needed. This both works:
julia module T
end
Hi Steve
The more obvious way to implement the loop would be to put the body BEFORE
the 'next' statement, and at first I thought that maybe the manual has a
typo. But then I checked the file dict.jl, and I found indeed the code:
done(t::ObjectIdDict, i) = is(next(t,i),())
So this means
I don't have a Mac to test on, so others will hopefully be more useful. But
here's an explanation of what you're seeing:
- The error is being triggered when the package is first loaded. The reason
commenting out those lines didn't fix it is that they only affect whether it's
used when you read
Also, it's always fine to open an issue; those of us who get ~300 julia-related
emails a day can easily miss a post, but an issue has permanence and will
eventually get noticed.
I opened one for you here: https://github.com/timholy/Images.jl/issues/128
--Tim
On Wednesday, July 23, 2014
Yes, that's my fault, I should have run the tests one last time. I fixed
it and tagged a new version (0.2.47) a few ours ago, hoping no one would
notice. A `Pkg.update()` should fix it for you.
I see. Yes, that fixed it. But I learned quite a bit about github and julia
in the meantime. :)
I've noted the fix in the github issue.
On Wednesday, 23 July 2014 12:32:29 UTC+1, ron.s...@gmail.com wrote:
Yes, that's my fault, I should have run the tests one last time. I fixed
it and
Hello collague,
On Tuesday, July 22, 2014 4:25:46 PM UTC+2, Mauro wrote:
I agree that there should be some means of resolving conflicts (by
warning,
by precedence) but just dropping a whole set of methods because they
conincidentially have the same name AND at the same time advertising
There is another option, which won’t necessarily work for plot but might
resolve many other issues (and is frequently used on functions like push!):
make both modules import a common function to extend.
What took me a while to understand in this context, is the distinction
between a
Hi guys,
I have 2 short numpy-related questions.
In numpy, if one can invert an arbitrary array *arr* along a given axis
using the syntax
*arr[::-1,...]*
What is the equivalent idiom in Julia?
The other issue is, how can I truncate an array between a lower and upper
bound?
In numpy,
Check out `clamp` for your second question:
http://docs.julialang.org/en/latest/stdlib/base/#Base.clamp
On Wed, Jul 23, 2014 at 10:07 AM, Andrei Berceanu andreiberce...@gmail.com
wrote:
Hi guys,
I have 2 short numpy-related questions.
In numpy, if one can invert an arbitrary array *arr*
On Wednesday, July 23, 2014 10:07:20 AM UTC-4, Andrei Berceanu wrote:
In numpy, if one can invert an arbitrary array *arr* along a given axis
using the syntax
*arr[::-1,...]*
And with regards to this, I think you're after `flipdim`
—
A[end:-1:1, ...]
On Wednesday, July 23, 2014 07:07:20 AM Andrei Berceanu wrote:
Hi guys,
I have 2 short numpy-related questions.
In numpy, if one can invert an arbitrary array *arr* along a given axis
using the syntax
*arr[::-1,...]*
What is the equivalent idiom in Julia?
The
Is there anything that is intermediate between the manual and the
introductory material that is kind of a taste of?
I've looked in the documentation and teaching sections (not sure if the
latter is relevant if I don't plan to teach with Julia), but haven't found
anything that looked right. I
Thanks guys, works like a charm!
A
On Wednesday, July 23, 2014 4:32:56 PM UTC+2, Tim Holy wrote:
A[end:-1:1, ...]
On Wednesday, July 23, 2014 07:07:20 AM Andrei Berceanu wrote:
Hi guys,
I have 2 short numpy-related questions.
In numpy, if one can invert an arbitrary array
Hello,
I am running Julia 0.2.1 and for some reason I can no longer install any
packages. Here is an example:
julia Pkg.add(Cosmology)
ERROR: failed process: Process(`git
--git-dir=/home/daniel/.julia/.cache/Stats merge-base
87d1c8d890962dfcfd0b45b82907464787ac7c64
Main is the root module so /T and ./T are the same thing in Main.
On Wed, Jul 23, 2014 at 3:36 AM, Mauro mauro...@runbox.com wrote:
It still needs relative imports with one dot:
julia module A
module B
foo()=4
export foo
end
using .B
foo()
On Wed, 2014-07-23 at 16:29, Stefan Karpinski ste...@karpinski.org wrote:
Main is the root module so /T and ./T are the same thing in Main.
but doesn't the same hold for any other folder?
/MyMod/T and /MyMod/./T are the same thing
On Wed, Jul 23, 2014 at 3:36 AM, Mauro mauro...@runbox.com
You can also write that range as `end:-1:1` in Julia (similar to Matlab).
On Wed, Jul 23, 2014 at 8:14 AM, Andrei Berceanu andreiberce...@gmail.com
wrote:
Thanks guys, works like a charm!
A
On Wednesday, July 23, 2014 4:32:56 PM UTC+2, Tim Holy wrote:
A[end:-1:1, ...]
On Wednesday,
I've read the Embedding Julia docs which seem straightforward, except they
seem to lack how to construct and communicate composite types. The type ***
jl_value_t*** seems generic. Is this answered by reading the source?
Also this: http://learnxinyminutes.com/docs/julia/. David Sander's tutorial
is a nice start as well, although it's quite a long video:
https://www.youtube.com/watch?v=vWkgEddb4-A.
On Wed, Jul 23, 2014 at 8:15 AM, João Felipe Santos joao@gmail.com
wrote:
There's this nice programming by
got it, tnx
On Wed, 2014-07-23 at 16:51, Stefan Karpinski ste...@karpinski.org wrote:
Not quite. Note the initial /. When you do `using M` or `import M` it is
like `cat /M` – it is relative to the root of the module system, not the
current level of module. When you do `using .M` it is like
On Wed, Jul 23, 2014 at 6:06 AM, Andreas Lobinger lobing...@gmail.com
wrote:
In principle i agree, everything that is defined in the Modules is usable
regarding its own namespace. But then, why do we have the export of
functions? It's not even needed...
If you strictly prefix all functions
For what's it's worth, we originally looked relative first and then
absolute, but it was a usability nightmare. This is more explicit and, once
you get it, I think much simpler.
On Wed, Jul 23, 2014 at 9:06 AM, Mauro mauro...@runbox.com wrote:
got it, tnx
On Wed, 2014-07-23 at 16:51, Stefan
As suggested by a few of you, I put everything in a function and now it
runs in 1/4 s, that is nearly 32 x improvement for 'no change' that is one
of the aspects I don't like in julia.
Anyway, lesson learnt I will now put everything inside functions and will
learn how to use the profiler
Well spotted, not quite right, when not paying attention I regularly get
confused with in and = although in this case it does not really matter.
On Tuesday, 22 July 2014 23:45:21 UTC+1, J Luis wrote:
Hmmm, is this right?
for j in 1:f[i]
Why not view this as a learning opportunity to discover that changes you
perceive to be minor are, in fact, not minor -- but are instead substantive
changes to the semantics of your program?
-- John
On Jul 23, 2014, at 9:38 AM, Arnaud Amiel aam...@gmail.com wrote:
As suggested by a few of
I can see that but it was not directly obvious to me. I guess that is why I
am playing with Julia. Now onto Euler 26 should not be too hard...
On Wednesday, 23 July 2014 17:40:07 UTC+1, John Myles White wrote:
Why not view this as a learning opportunity to discover that changes you
perceive
You don't like getting 32x speed improvements with almost no changes? There are
plenty of languages where things are slow in both global and local scope, in
which case you won't have that problem. I suspect, however, that is not
actually preferable.
On Jul 23, 2014, at 9:38 AM, Arnaud Amiel
On Wed, Jul 23, 2014 at 9:38 AM, Arnaud Amiel aam...@gmail.com wrote:
As suggested by a few of you, I put everything in a function and now it
runs in 1/4 s, that is nearly 32 x improvement for 'no change' that is one
of the aspects I don't like in julia.
I've used Julia for a couple of years
There's
https://github.com/JuliaLang/julia/issues/524
https://github.com/JuliaLang/julia/issues/964
And Jeff has mentioned it in his compiler list:
https://github.com/JuliaLang/julia/issues/3440
-Jacob
On Wed, Jul 23, 2014 at 1:18 PM, Kevin Squire kevin.squ...@gmail.com
wrote:
On Wed, Jul
I definitely agree that the current status is suboptimal. Lord only knows
I've spent a lot of time thinking about ways to fix the slow global scope
issue. Many but by no means all of these thoughts are in the issues Jacob
linked to. If we figure out a solution that seems to be the right way to do
It makes sense now, thanks.
Latest thoughts on the issue:
https://github.com/JuliaLang/julia/issues/524#issuecomment-49914439
On Wed, Jul 23, 2014 at 10:48 AM, Stefan Karpinski ste...@karpinski.org
wrote:
I definitely agree that the current status is suboptimal. Lord only knows
I've spent a lot of time thinking about
https://github.com/JuliaLang/julia/issues/7392
-Mike
On Wed, Jul 23, 2014 at 11:17 AM, Daniel Carrera dcarr...@gmail.com wrote:
Hello,
I am running Julia 0.2.1 and for some reason I can no longer install any
packages. Here is an example:
julia Pkg.add(Cosmology)
ERROR: failed process:
Admit that you really want to program in OCaml ;-)
On Jul 23, 2014, at 11:39 AM, John Myles White johnmyleswh...@gmail.com
wrote:
I think the difficulty here is that the people who are worst affected by
these kinds of performance changes may be people who also might not know that
they
Very close!
There were actually some changes recently to hashing in general that make
it a bit easier to get this working (although undocumented
https://github.com/JuliaLang/julia/issues/6833, *cough*, Stefan
Karpinski, *cough*).
Here are the only changes I made to get `@test_approx_eq` working:
You can't use push! on multidimentional arrays. You can push onto a 1d
array, and then reshape. Another way is to collect all the row/column
vectors and use hcat(c...) or vcat(c...) to create an array.
Ivar
kl. 21:22:01 UTC+2 onsdag 23. juli 2014 skrev john pollack følgende:
Hi. I want to
On Wed, 2014-07-23 at 11:15 -0400, João Felipe Santos wrote:
There's this nice programming by example-style tutorial that you can
skim to get a grasp of the syntax, features, and standard libraries,
as well as some plotting
libs: http://bogumilkaminski.pl/files/julia_express.pdf.
--
João
On Wed, 2014-07-23 at 09:00 -0700, Stefan Karpinski wrote:
Also this: http://learnxinyminutes.com/docs/julia/.
That was one of the first things I looked at; I liked it a lot, but then
needed something more.
Ross
David Sander's tutorial is a nice start as well, although it's quite a
long video:
I for one am thrilled to be able to program every day in such a beautiful,
flexible, clean language with generally good performance and in which
sparkling performance is possible. By comparison, performance instability
is a minor matter.
There, I have thoroughly discredited myself by banal
Thanks!
On 23 July 2014 20:48, Mike Nolta m...@nolta.net wrote:
https://github.com/JuliaLang/julia/issues/7392
-Mike
On Wed, Jul 23, 2014 at 11:17 AM, Daniel Carrera dcarr...@gmail.com
wrote:
Hello,
I am running Julia 0.2.1 and for some reason I can no longer install any
packages.
Some additional comments:
1. vcat will always create a new array, and copies the contents of the
arrays to be concatenated into the new one.
2. Julia stores arrays in column-major order, so vcat(A, [1 2]) does the
following
- copy column 1 of A to temp array
- copy the 1 from
It seems odd that [1; 2] != [1 2]'; typeof shows the former is
1-dimensional and the latter 2-dimensional (if I'm interpreting
correctly), but that seems kind of inconsistent.
A similar issue with indexing surprised me recently. If A is a 2-d array,
A[:, 1] is a 1-d array but A[1, :]
John, just to give some explanation: push! is there as an efficient push
operation - one that ideally takes O(1) time because it simply extends the
vector in-place rather than copying everything to a new vector. (In
practice, though, it takes slightly longer than O(1) time because of the
This explanation should maybe go straight in our FAQ :-)
On Jul 23, 2014, at 3:12 PM, Alireza Nejati alireza@gmail.com wrote:
John, just to give some explanation: push! is there as an efficient push
operation - one that ideally takes O(1) time because it simply extends the
vector
Dear Julia users,
Thank you for all your thoughtful replies on this matter. Indeed, you are
all correct, and I misunderstood the construct. (The point that confused
me was that in the call (i,state)=next(I,state), I mistakenly assumed that
the returned state should correspond with returned
My inclination is to include type checking and linting in base Julia,
automatically invoked by a paranoid mode that also ignores inbounds
annotations and such. Then the testing infrastructure should run tests in
paranoid mode, linting and type checking the code to be tested. This seems like
a
Glad it makes sense. Maybe we could explain that better.
On Jul 23, 2014, at 3:20 PM, vava...@uwaterloo.ca wrote:
Dear Julia users,
Thank you for all your thoughtful replies on this matter. Indeed, you are
all correct, and I misunderstood the construct. (The point that confused me
I am trying to access parts of a distributed array that belongs to the
current worker
res=dzeros((1,length(workers())), workers(), [1,length(workers())])
(for some reason res=dzeros((length(workers())), workers(),
[length(workers())]) throws an error )
@spawnat 2 localpart(res)[1]+=rand()
What is the best way to capture STDOUT and STDERR from an external program?
If it can't be done separately, is there an equivalent to the bash-ism
./myprogram 21 log.txt
On Wed, 2014-07-23 at 14:43 -0700, Sam L wrote:
It seems odd that [1; 2] != [1 2]'; typeof shows the former
is
1-dimensional and the latter 2-dimensional (if I'm
interpreting
correctly), but that seems kind of inconsistent.
A similar
Oops, not sure where I got that idea, you are correct! I could have sworn I
tried that in the REPL... Brain glitch I suppose.
On Wednesday, July 23, 2014 4:52:08 PM UTC-7, Ross Boylan wrote:
On Wed, 2014-07-23 at 14:43 -0700, Sam L wrote:
It seems odd that [1; 2] != [1
Wonderful! Thank you!
The associated problem here is that the error message didn't really help
me. I know the developers are busy, but I hope that there's a way to
eventually improve the error message for this situation.
Thanks again.
Daniel
On Tuesday, July 22, 2014 9:22:31 PM UTC-5,
I think what would really be helpful here are explicit interfaces. There's
an open issue about it: https://github.com/JuliaLang/julia/issues/6975
In a world with interfaces, you would have been told at some point (either
inheriting from number or calling certain methods), that your type was
While I'm not a programming wizard like so many in this community, I do
hope that the developers are familiar with the interfaces in Go. I didn't
see any mention of Go in that issue, though.
I like how in Julia the types and methods are decoupled, in that the
methods aren't bound to the type,
Hi,
I'm trying to do the attached code, which fails due to no method
matching. What am I doing wrong?
The #dostuff was just asserts so I fixed it by commenting out the
interior constructor, but would like to understand better.
Cheers,
Sheehan
type
Live editor/IDE integration of linting (and type-checking) a la Matlab
would be quite nice to have one of these days. Julia seems to self-select
for the type of people who actually listen to suggestions and are willing
to experiment with refactoring and profiling, but I still fear the piles of
The DArray has been distributed only on the workers. localpart(res) on the
master process returns 0x0 Array{Float64,2} and hence the BoundsError()
You need to pass the DArray object to dowork. The following will work.
@everywhere function dowork(res)
localpart(res)[1]+=rand()
end
@spawnat 2
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