THanks, much better
On Wednesday, September 7, 2016 at 3:59:56 AM UTC-4, Kristoffer Carlsson
wrote:
>
> After discussion with the Julia community stewards I have decided to
> rename this package. It is now named "OhMyREPL" and can be found at:
> https://github.com/KristofferC/OhMyREPL.jl. I
Is there any difference between
version1:
let x
x = 0
end
vs.
version2:
let
local x = 0
end
vs
version3:
let x = 0
end
version 1 and 2
; Function Attrs: uwtable
define i64 @julia_t2_67462() #0 {
top:
ret i64 0
Patiently waiting on stefan's talk
On Sunday, July 3, 2016 at 1:58:48 PM UTC-4, Viral Shah wrote:
>
> They will keep trickling in. We will announce widely when everything is
> up.
>
> -viral
>
>
> > On 03-Jul-2016, at 9:25 AM, dnm
> wrote:
> >
> > Will Stefan's talk and
The docs read
@static()
Partially evaluates an expression at parse time.
For example, @static is_windows() ? foo : bar will evaluateis_windows() and
insert either foo or bar into the expression. This is useful in cases where
a construct would be invalid on other platforms, such as a ccall to
I mean the revised script runs just as fast if not a tad faster with the
latest master as it does on 0.4.5 : )
On Sunday, May 8, 2016 at 5:20:08 PM UTC-4, Patrick Kofod Mogensen wrote:
>
> Same as v0.4, or same as before you changed the code?
>
> On Sunday, May 8, 2016 at 8:55:00 PM
roughly the same speed.
On Sunday, May 8, 2016 at 2:44:19 PM UTC-4, Patrick Kofod Mogensen wrote:
>
> out of curiosity, what about v0.5?
With all that done, the julia code runs about the same if not better than
matlab (using 4 threads)
On Sunday, May 8, 2016 at 2:21:42 PM UTC-4, feza wrote:
>
> Well first problem was that the vectorized version of my code was very
> slow.
> Then I devectorized still slow, because
1:nz
>> to
>>for k in 1:nz, j in 1:ny, i in 1:nx
>> because your arrays are defined like a[i,j,k]?
>>
>> Another question is, how many cores is your Matlab code using?
>>
>>
>> On Monday, May 9, 2016 at 2:03:58 AM UTC+9, fez
; Also try:
> julia -O --check-bounds=no yourcode.jl
>
> On Monday, May 9, 2016 at 2:03:58 AM UTC+9, feza wrote:
>>
>> Milan
>>
>> Script is here:
>> https://gist.github.com/musmo/27436a340b41c01d51d557a655276783
>>
>>
>> On Sunday, May 8, 20
Milan
Script is
here: https://gist.github.com/musmo/27436a340b41c01d51d557a655276783
On Sunday, May 8, 2016 at 12:40:44 PM UTC-4, feza wrote:
>
> Thanks for the tip (initially I just transllated the matlab verbatim)
>
> Now I have made all the changes. In place operations, and dir
ke your
> life harder in the end (
> http://c2.com/cgi/wiki?GlobalVariablesAreBad)---it's
> not a bad thing that julia provides gentle encouragement to avoid using
> them,
> and you're losing out on opportunities by trying to sidestep that
> encouragement.
>
>
That's no surprise your CPU is better :)
Regarding devectorization
for l in 1:q
for k in 1:nz
for j in 1:ny
for i in 1:nx
u = ux[i,j,k]
v = uy[i,j,k]
w = uz[i,j,k]
cu = c[k,1]*u + c[k,2]*v +
nstant array of Ints, and its elements multiply ux, uy
> and uz in a loop, where ux, uy and uz are arrays of floats, so there's a
> type stability problem.
>
> On Sunday, May 8, 2016 at 9:18:09 AM UTC+2, feza wrote:
>>
>> https://gist.github.com/musmo/27436a340b41c01d51d557a
https://gist.github.com/musmo/27436a340b41c01d51d557a655276783
On Sunday, May 8, 2016 at 3:17:39 AM UTC-4, feza wrote:
>
> I have read the performance section and believe I have followed all the
> suggested guidelines
>
> The same matlab script takes less than 3 seconds, julia 0.
I have read the performance section and believe I have followed all the
suggested guidelines
The same matlab script takes less than 3 seconds, julia 0.45 9.7 seconds
(julia 0.5 is even worse...)
https://gist.github.com/musmo/27436a340b41c01d51d557a655276783.js">
.
>
> On Thursday, April 28, 2016 at 1:13:56 PM UTC-7, feza wrote:
>>
>> Hi All,
>>
>> Has anyone here had experience using Julia programming using Nvidia's
>> Tesla K80 or K40 GPU? What was the experience, is it buggy or does Julia
>> have no problem.?
>>
>
Hi All,
Has anyone here had experience using Julia programming using Nvidia's
Tesla K80 or K40 GPU? What was the experience, is it buggy or does Julia
have no problem.?
I suggest clarification in the documents regarding which mode of automatic
differentiation since this can have a large impact on computation time.
It seems like this 'ForwardDiff is only used for used-defined functions
with the autodiff=true option. ReverseDiffSparse is used for all other
I don't think that's the reason, since:
```
if x == 0
r = y/one(x) # Why not just return y?
```
This can only happen if x = 0 or x = 0.0 and y = NaN or x = 0 or
x = 0.0 and y = 0 or y = 0.0
Sorry I meant without using ;
I.e. to have it permanently without ;
On Saturday, March 26, 2016 at 6:40:16 PM UTC-4, Miguel Bazdresch wrote:
>
> 3;
>
> On the REPL the ; acts just like it does in Matlab, suppressing the output.
>
> -- mb
>
> On Sat, Mar 26, 2016
julia> 3
3
How can I suppress this during an interactive julia session
Thanks
0) is +0, hypot(±∞, qNaN) is +∞, and
>> hypot(qNaN, ±∞) is +∞ -- IEEE 754-2008 (page 43)
>
>
>
>
>
>>
>
> For the hypot function, hypot(±0, ±0) is +0, hypot(±∞, qNaN) is +∞, and
>> hypot(qNaN, ±∞) is +∞
>
>
> On Saturday, March 26, 2016 at 4:1
UTC-4, feza wrote:
>
> Good catch Jeffrey. I will file a bug report!
>
> On Saturday, March 26, 2016 at 3:50:31 PM UTC-4, Jeffrey Sarnoff wrote:
>>
>> Looking at your note, I noticed this:
>>
>> * hypot(Inf,NaN) == hypot(NaN,Inf) == Inf*
>>
>>
Why is hypot1 preferred (in Base) over hypot2 ? To me it seems better to
just return yin the one commented line
function hypot2{T<:AbstractFloat}(x::T, y::T)
x = abs(x)
y = abs(y)
Nice I will try this! BTW which theme are you using :)
On Sunday, March 20, 2016 at 2:58:15 PM UTC-4, James Dang wrote:
>
> Hi All, Julia has been great for me, and I wanted to give back a little.
> LightTable and Atom are great editors, but I was really starting to miss
> good
Hi all how can install both julia 4 and julia 5 on fedora
I have read
http://julialang.org/downloads/platform.html
I have performed
sudo dnf copr enable nalimilan/julia-nightlies
sudo dnf copr enable nalimilan/julia
and then dnf install julia
this only gets me julia0.5 . Is there a way
posted issue : https://github.com/JuliaLang/julia/issues/15393
On Friday, March 4, 2016 at 3:48:43 AM UTC-5, pev...@gmail.com wrote:
>
> Hello all,
> I was polishing my call and I have found the following definition of
> daxpy! I was not aware of
>
>
> function axpy!{Ti<:Integer,Tj<:Integer}(α,
Package looks like great. In light of this comment, how's the 2d graphics?
Can we expect some processing style API, I would love to help anyway I can.
Also I find some of the examples to be rough (antialiasing issues?)
Thanks.
On Thursday, March 3, 2016 at 7:05:44 AM UTC-5, Job van der Zwan
I think I am misunderstanding the temporary array allocation process. Is it
allocating one or two temp arrays? Where have I gone wrong here:
tmp = 2y (allocates a temporary array to store result)
tmp .-= 4z (also allocates a temporary array for 4z? Why not just use z
directly, thus tmp[i] =
Why not use
foo{I<:Integer}(u::UnitRange{I}) = 1
On Sunday, November 22, 2015 at 7:38:29 AM UTC-5, andrew cooke wrote:
>
>
> Out of my depth here - no idea if this is a bug or me...
>
> julia> foo{I<:Integer,U<:UnitRange{I}}(u::U) = 1
> ERROR: TypeError: UnitRange: in T, expected T<:Real, got
;
> You need to escape certain characters in your terminal so that they are
> passed faithfully to Julia.
>
> On Wednesday, November 4, 2015 at 11:05:29 AM UTC-8, feza wrote:
>>
>> I must be doing something wrong but:
>>
>> julia -e "print("hello")"
>>
>> gives me
>> ERROR: syntax: incomplete: premature end of input
>>
>
I must be doing something wrong but:
julia -e "print("hello")"
gives me
ERROR: syntax: incomplete: premature end of input
first came npm, and then . jpm : )
On Tuesday, November 3, 2015 at 6:27:39 AM UTC-5, Stefan Karpinski wrote:
>
> On Mon, Nov 2, 2015 at 9:00 PM,
> wrote:
>
>> Would you like it if someone came along and forked all of Julia,
>> especially Pkg, and created forks
My only problem with `=` vs `in`
is that even the base julia code is inconsistent! Looking at one file ( I
can't remember which now)
it had both
i = 1:nr
and
i in 1:n
Again this was in the same file! Please tell me I am not being pedantic
when I saw this and thought this must be fixed if even
actually its more about simple confusion rather than mental cost @DNF.
Starting out you either use = or in then you see some other code and they
use something else and wonder, what is right, is one notation faster or
better, what's going on? Of course, it's not the simplest thing to try and
+1 @Tom Breloff .
I was confused about this when starting out. Comparing `for i in 1:3` vs
`for i = 1:3`, even though I regularly use matlab if you think about it
for `i = 1:10` doesn't really make a lot of sense. It would be nice if it
was just one way as opposed to the confusion about
How can I run julia without a terminal window poping up.
Something like where in python you have: pythonw.exe to do this and also
javaw.exe for java.
I
reabouts.
>
>
> On Thursday, October 15, 2015 at 9:36:50 PM UTC-7, feza wrote:
>>
>> Is Julia way slower on Windows? That's an interesting anecdote. Anyone
>> else have something to add regarding this. I don't know why this would be
>> true.
>> I did notice th
:
>
> We do just that on Windows, for now:
> https://github.com/JuliaLang/julia/blob/706600408aba8b142c47c2bc887bde0d9bf774cf/src/init.c#L73-L78
>
>
> On Thursday, October 15, 2015 at 11:03:11 PM UTC-7, feza wrote:
>>
>> Is there a way to have julia default to --pr
On a related note. What is the recommended procedure for dealing with
depreciations? Do we just update all the deprecations and push the changes?
This would make the package useless for 0.3 users or is this the
recommended procedure.
On Friday, October 16, 2015 at 7:39:05 PM UTC-4, Forrest
Is Julia way slower on Windows? That's an interesting anecdote. Anyone else
have something to add regarding this. I don't know why this would be true.
I did notice that when I built julia from source on my machine, my built
version of julia was consistently slower than the binaries available on
Same here on a 12gb ram machine
_
_ _ _(_)_ | A fresh approach to technical computing
(_) | (_) (_)| Documentation: http://docs.julialang.org
_ _ _| |_ __ _ | Type "?help" for help.
| | | | | | |/ _` | |
| | |_| | | | (_| | | Version
Finally was able to load it, but the process consumes a ton of memory.
julia> @time train = readtable("./test.csv");
124.575362 seconds (376.11 M allocations: 13.438 GB, 10.77% gc time)
On Tuesday, October 13, 2015 at 4:34:05 PM UTC-4, feza wrote:
>
> Same here on
Wow this looks great. Much better than google groups which is rather
annoying in many respects. Looking forward to using this sometime in the
future. Do you think mathjax support for latex equations would be useful
for a Julia forum?
On Saturday, September 19, 2015 at 8:16:36 PM UTC-4,
Looks like it works cheers
Building with 'Microsoft Visual C++ 2015 Professional'.
cl /c /Zp8 /GR /W3 /EHs /nologo /MD /O2 /Oy- /DNDEBUG
/D_CRT_SECURE_NO_DEPRECATE /D_SCL_SECURE_NO_DEPRECATE /D_SECURE_SCL=0
/DMATLAB_MEX_FILE -IC:\Julia\Julia-0.5.0-dev\include\julia -I"C:\Program
FYI this discussion is in relation to Julia 0.4. Initially I had some
deprecation warnings but they have mostly gone away. I have no real
objection, perhaps it's just a little weird that the repl returns
julia> x
linspace(0.0,10.0,50)
as opposed to printing it out like a full array. Perhaps
In matlab x = linspace(0,1,n) creates a vector of floats of length n. In
julia it seems like the only way to do this is to use x = collect(
linspace(0,1,n) ) . Is there a nicer syntax? I do mainly numeric computing
and I find this quite common in my code.
Thanks.
converts it to a vector. Though the returned t will
> be linspace object.
>
> On Wednesday, September 30, 2015 at 12:10:55 PM UTC+10, feza wrote:
>>
>> Here's the code I was using where I needed to use collect (I've been
>> playing around with Julia, so any suggestions
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