From http://michaelhatherly.github.io/Lexicon.jl/manual/#viewing-documentation
:
Lexicon hooks into the REPL's ? mode (help-mode) once using Lexicon has
been called from the REPL. Other environments, such as editors, are not
currently supported.
Am Mittwoch, 11. Februar 2015 17:08:24 UTC+1
[The Juno mailing list seems dead? Hence I am re-posting my question here;
apologies for posting twice.]
Juno doesn't seem to recognise doc strings, or am I getting something
wrong? Here is a short piece of code:
using Docile, Lexicon
@doc docSome doc with `markdown`.-function blah()
Thank you for kind answer.
Always I am afraid of unintended copy of buffers because I'm a such a C/C++
guy.
I have read the performance tips when it is early 0.3 version.
I surprised that there were lots of updates since then. (julia is
developing so fast!)
I will try the profiling
It’s not just Juno — I just haven’t gotten around to implementing output
for anything but console yet. I won’t have a chance to add this for the
next few weeks though, so here’s the issue
https://github.com/MichaelHatherly/Lexicon.jl/issues/29 in case you’ve
got any ideas you’d like to
The Juno forum isn't dead but is is unfortunately a bit slow, which
basically comes down to the fact that there are far fewer people who know a
lot about its internals (and most of them have other commitments, at least
for the very near future). I try to respond to everything within a few
days, or
For further reference the files base/multidimensional.jl,
base/broadcast.jl, and some others (just grepping for the cartesian macros)
are great places to see them in action.
— Mike
On Wednesday, 11 February 2015 17:28:09 UTC+2, Christoph Ortner wrote:
that simple - thanks!
Christoph
Hi,
I was trying to find out, what the best way is to have some local, constant
storage for a function, which is only accessible from inside the function
So something like this:
begin
const local a = []
test() = dosomething(a)
end
I was quite surprised, that you can't do this efficiently.
Or at
On Wednesday, February 11, 2015 08:27:26 AM Kyunghun Kim wrote:
By the way, my another wish is about performance of loading packages.
In my code, Image.jl takes ~5 sec for just loading libraries,
(new) Interpolation.jl takes even ~20 sec. (maybe cause of metaprogramming
codes I think)
I
No problem, glad you like it!
On 11 February 2015 at 16:52, Christoph Ortner christophortn...@gmail.com
wrote:
ah - just saw your reply there
http://discuss.junolab.org/t/julia-0-4-docile-doc-strings/120/2
Thanks a lot!
Also: I am quite enjoying working with Juno, even though I normally
Trying to work with subroutines (I am a MATLAB person without fortran and
julia knowledge)
File Name : fsbrtn.f90
SUBROUTINE MULTIPLY(A,B,C)
DOUBLE PRECISION A,B,C
C = A*B
RETURN
END
gfortran -shared -O2 fsbrtn.f90 -fPIC -o fsbrtn.so
a = 100.0
b = 10.0
c = 1.0
ppmm = ccall((:multiply_,
ah - just saw your reply there
http://discuss.junolab.org/t/julia-0-4-docile-doc-strings/120/2
Thanks a lot!
Also: I am quite enjoying working with Juno, even though I normally use
only EMACS - I just found that neither the standard Julia mode more the ESS
Mode are quite mature enough. So
Also don't forget the attendees, otherwise we cannot hear their questions
and comments all of which adds to the experince and knowledge base.
a = 100.0
b = 10.0
c = Array(Float64)
ppmm = ccall((:multiply_, /home/juser/ManUTD/fortran_try/fsbrtn),
Void,(Ptr{Float64},Ptr{Float64},Ptr{Float64}),a,b,c)
println(c)
0.0
On Wednesday, February 11, 2015 at 11:15:57 PM UTC+5:30, DP wrote:
Trying to work with subroutines (I am a MATLAB
You don't have an on c – even if you did, the syntax doesn't let you
write values, so that still wouldn't work. You can try setting c =
Array(Float64) and then pulling the value written to it out as c[].
On Wed, Feb 11, 2015 at 12:45 PM, DP deepraj...@gmail.com wrote:
Trying to work with
I have written the following function for generating a sparse matrix:
*function genspmat(ω0::Float64; N=pm[N], α=pm[α], γ=pm[γ],
κ=pm[κ])# Determine memory usagenz = countnonzeros(; N=N)#
Preallocate
Hi Ken,
That looks awesome. You're much further along than I am, so I can learn alot
from what you've done. Thank you for sharing!
Just curious--in this case how slow?
Anyway, you should check out the FastAnonymous.jl package--it should help
in your case.
Cheers,
Kevin
On Wednesday, February 11, 2015, Andrei Berceanu andreiberce...@gmail.com
wrote:
I have written the following function for generating a sparse matrix:
that simple - thanks!
Christoph
Yes, we had neglected to mic speakers. we'll try not to forget this time.
I do not see how this comment is appropriate for this list.
Thanks,
Jiahao Chen
Staff Research Scientist
MIT Computer Science and Artificial Intelligence Laboratory
On Wed, Feb 11, 2015 at 7:06 AM, Andreas Lobinger lobing...@gmail.com
wrote:
this falls under SCNR and is some kind of insider
A[:, indx] currently makes a copy. Try replacing it with slice(A, :, indx) (if
you're on julia 0.4) or use ArrayViews if you're on julia 0.3.
For performance questions, if you aren't using the tools advertised at
http://docs.julialang.org/en/release-0.3/manual/performance-tips/
you will likely
Hi, all.
I am sorry that I am writing repeating these questions again. (performance
compared to ~)
I have some signal processing code written in MATLAB, and rewriting the
code with Julia.
The signal processing function take about 1024 x 1024 floating number array
as input called in loop
You probably don't want `eval` unless there's no other way. It's hard to
tell how you want to use the variables, so it's hard to recommend
alternatives. Keyword arguments can be useful for this sort of thing:
function f(; a = 1, b = 2)
a + b
end
f(a = 99, b = 2)
You can also use Dict's to
It's actually a zero-dimensional array that holds only one element. I'm not
sure why it's getting written to, but then again, I have no idea how one
correctly writes through a pointer in Fortran, so I can't really say what
I'd expect that code to do.
On Wed, Feb 11, 2015 at 4:15 PM, Dawid
How about simply iterating over the dict?
for (key, value) in dict
set(simulation, key, value)
end
Note, that you can actually access a type like this:
type T
a::Int
end
x = T(1)
x.(:a) = 10 #- :a is a symbol, which can be created like this
symbol(string)
x.(:a) is equivalent to
Hi again,
There were some bugs in my implementations. I updated the gist
https://gist.github.com/pabloferz/01675f1bf4c8be359767#file-levicivita-jl
with the corrected versions and added a simpler looking function (but of
O(n²) running time).
I did some tests and found (with my slow processor)
Hi,
If I have a dictionary
params = {N: 10, M: 2.0}
how can I use it to define two variables N and M with the corresponding
values?
This sounds like it should be easy and obvious, say using `eval`?
E.g. extract the keys and values into strings and then use
eval(parse(N=10))
Is this
Try initializing the c with some value, because right now you are creating
an empty array with no storage allocated.
a = 100.0
b = 10.0
c = [0.0] # or Array(Float64,1)
ppmm = ccall((:multiply_, /home/juser/ManUTD/fortran_try/fsbrtn),
Void,(Ptr{Float64},Ptr{Float64},Ptr{Float64}),a,b,c)
Just stumbled on this, which seems not bad (though I haven't looked in
detail):
http://en.wikibooks.org/wiki/Introducing_Julia
El miércoles, 11 de febrero de 2015, 14:49:53 (UTC-6), tshort escribió:
You probably don't want `eval` unless there's no other way. It's hard to
tell how you want to use the variables, so it's hard to recommend
alternatives. Keyword arguments can be useful for this sort of thing:
Right, that should certainly work, but having a and b as scalars and using
the syntax should also.
On Wed, Feb 11, 2015 at 6:50 PM, Dominique Orban dominique.or...@gmail.com
wrote:
This works for me:
a = Cdouble[100.0]
b = Cdouble[10.0]
c = Cdouble[1.0]
ppmm = ccall((:multiply_, fsbrtn),
I can't quite tell: are you aware the `begin end` does not introduce a
new scope?
This (sans begin-end) produces 'long'
local const aa = rand()
test2() = aa::Float64 + aa::Float64
@code_native test2()
and this short:
const aa = rand()
test2() = aa::Float64 + aa::Float64
@code_native test2()
set_default_plot_size changes the default size of all following plots, but
how can i set the size of a certain plot individually?
//A
This is surely cheating, but
julia a = rand()
0.7573462021713695
julia @eval begin
function test5()
a = $a
a + a
end
end
test5 (generic function with 1 method)
does give you the short version.
--Tim
On Wednesday, February 11, 2015
El miércoles, 11 de febrero de 2015, 15:44:46 (UTC-6), Simon Danisch
escribió:
How about simply iterating over the dict?
for (key, value) in dict
set(simulation, key, value)
end
Note, that you can actually access a type like this:
type T
a::Int
end
x = T(1)
x.(:a) = 10 #- :a
Hey guys,
Here is my brief code, figured I'd give it a try on ODBC since I'm
attempting to connect to a MS SQL Server. Here is my code I will blank out
sensitive information on purpose.
import ODBC
band_query = select band_lowerFreq, band_upperFreq from Band;
co =
I may be completely missing the point, but how about unused optional
arguments(s) to store the constant(s):
julia test9(x, aconst = 1.0) = x + aconst
test9 (generic function with 2 methods)
julia @code_native test9(4.2)
.text
Filename: none
Source line: 1
pushRBP
Hi Arch, all,
Thanks for looking into this, it's amazing to have experts here who
understand the depths of compilers. I'm stubbornly having difficulty
reproducing your timings, even though I see the same assembly generated for
clang. I've tried on an i5-3320M and on an E5-2650 and on both,
Ah yeah, sure...
And also my all time favorite staged functions could be misused:
stagedfunction test5()
quote
a = $(a = rand() )
a + a
end
end
But I'm actually searching for answers, why it is like this and what speaks
against a nice solution for such a common use
This works for me:
a = Cdouble[100.0]
b = Cdouble[10.0]
c = Cdouble[1.0]
ppmm = ccall((:multiply_, fsbrtn), Void,
(Ptr{Float64},Ptr{Float64},Ptr{Float64}),a,b,c)
println(c[1])
On Wednesday, February 11, 2015 at 12:45:57 PM UTC-5, DP wrote:
Trying to work with subroutines (I
Thank you for sharing, very nice!
On Wednesday, 11 February 2015 08:01:28 UTC+1, Arch Call wrote:
Quantitative Economics with Julia
http://quant-econ.net/_static/pdfs/jl-quant-econ.pdf
Check out the PDF file in the link above. It has 396 pages of excellent
documentation in the use of
Does anyone know about a package that allows reading from the windows
registry?
Thanks,
David
--
David Anthoff
University of California, Berkeley
http://www.david-anthoff.com
Hi Andrei,
You can do this using the draw function, like:
draw(SVG(20cm, 10cm), plot(...))
On Wednesday, February 11, 2015 at 3:42:47 PM UTC-8, Andrei Berceanu wrote:
set_default_plot_size changes the default size of all following plots, but
how can i set the size of a certain plot
okit does works...thanx everyone
On Thursday, February 12, 2015 at 8:01:46 AM UTC+5:30, Dominique Orban
wrote:
Oh I see, sorry. Yes, this works just as well for me:
a = 100.0
b = 10.0
c = Cdouble[1.0]
ppmm = ccall((:multiply_, fsbrtn), Void,
Oh I see, sorry. Yes, this works just as well for me:
a = 100.0
b = 10.0
c = Cdouble[1.0]
ppmm = ccall((:multiply_, fsbrtn), Void,
(Ptr{Float64},Ptr{Float64},Ptr{Float64}),a,b,c)
println(c[1])
On Wednesday, February 11, 2015 at 6:52:55 PM UTC-5, Stefan Karpinski wrote:
Right,
Thanks for posting these, Pablo. For my most frequent use case I care about
n = 3, but I suppose the O(n) algorithms would be more appropriate in Base.
You are also correct that sign(::AbstractVector) currently does an
element-wise sign(). I didn't realize before writing my post that
Done!
https://github.com/JuliaLang/julia/issues/10172
You need to wrap the @nref macro is parenthesis to avoid it consuming the =
t:
(@nref $N A i) = t
or
@nref($N, A, i) = t
Note that in your example $N and A should be swapped around.
— Mike
On Wednesday, 11 February 2015 11:24:31 UTC+2, Christoph Ortner wrote:
I just discovered the
ok,
I understood my error: I forgot to copy hidden .git files when doing moves.
No I have the versions of each package, and I guess Pkg.Build('ZMQ') would
burn and redo everything from git.
Why can't these absolute path in deps.jl files be only relative paths per
default ?
(at least when
1) is it julia 0.3 or 0.4 centric?
2) ... it's a nice description of statistics and statistical models, but
why do they call this economics?
Hmmm, did you read the whole file? After getting through the
preliminaries, it starts with dynamic programming, and discusses
economics problems. It looks like it follows the spirit of the
Sargent-Ljungqvist book quite closely.
On Wed, Feb 11 2015, Andreas Lobinger lobing...@gmail.com wrote:
1)
I just discovered the Cartesian package; what a nice set of tools! I have a
question though and couldn't find the answer anywhere (apologies if I've
missed it):
within an `@nloops` construct I can write, say
t = @nref A $N i
but I cannot write
@nref A $N i = t
and instead
I'm not sure what you are saying with that code. There is no possible way
to define the function mutate_immutable!! such that it modified a or c.
This does it:
immutable A; a::Int end
a = A(1)
c = a
A.mutable = true
a.a = 99
A.mutable = false
@show a, c #(A(99),A(99))
a===c===A(99) # true
I
this falls under SCNR and is some kind of insider joke.
Economics was for long time (and successfully) a social sciences. Economic
problems were e.g. Unemployment or Market Failure.
Nowadays this Quantitative Economics view drives topics like HFT where they
intentionally create market failure
Agreed and done.
On Tuesday, February 10, 2015 at 7:24:57 AM UTC+7, Ivar Nesje wrote:
I definitely agree that the info message has some confusing aspects.
Please open an issue (or a PR) with Lint.jl so that the info reads
something like.
INFO: In 0.4, replace int() with Int(), or some
I'm curious if someone has implemented a statistical accumulator in julia
similar to that in boost:
http://www.boost.org/doc/libs/1_55_0/doc/html/accumulators.html
I'm aware of the accumulator in DataStructures.jl, but if I read it right
it doesn't do statistical accumulation, just a
We posted a draft of a new package that performs multivariate interpolation
on a rectilinear grid. At the moment, it provides implementations of
multilinear and simplex interpolation.
https://github.com/sisl/GridInterpolations.jl
We have not registered the package with METADATA.jl (hoping to
In Julia, if I have multiple functions with the same name but different
arguments, the core of the language takes care of calling the right
function.
Let's say I have a cell which contains some functions which are related,
but each take slightly different arguments. I'd like to call each of
JMW just released StreamStats.jl:
https://github.com/johnmyleswhite/StreamStats.jl
Which is what you want I think?
Cheers,
Iain
On Wednesday, February 11, 2015 at 10:53:10 PM UTC-5, Christian Peel wrote:
I'm curious if someone has implemented a statistical accumulator in julia
similar to
59 matches
Mail list logo
