thanks
在 2015年12月27日星期日 UTC+8下午5:44:10,Tony Kelman写道:
>
> Set ENV["JULIA_PKGDIR"]
>
> On Saturday, December 26, 2015 at 7:02:28 PM UTC-8, Yao Lu wrote:
>>
>> I have installed julia in F:\julia\, and I run "Pkg.add(***)", then Julia
>> installed my package in C:\User\***\.julia\. But I would like
Set ENV["JULIA_PKGDIR"]
On Saturday, December 26, 2015 at 7:02:28 PM UTC-8, Yao Lu wrote:
>
> I have installed julia in F:\julia\, and I run "Pkg.add(***)", then Julia
> installed my package in C:\User\***\.julia\. But I would like to install it
> in F:\julia\. How could I achieve that?
>
Briefly,
1. Robust dataframes is a key thrust area for this work. At this point the work
is exploratory, but we all are expecting this being one of the first areas to
see rapid progress on. Julia’s db support has improved a lot, independently,
and will keep getting better. As soon as there is
I want to ccall a file which is relative to the packages dir, but
const path = joinpath(@__FILE__,"..","bin","lib.so")
ccall((:fn, path),...)
fails with the same error as above
first argument not a pointer or valid constant expression
How can I fix this?
On Monday, November 30, 2015 at
I've thought a few times about reimplementing Stan in Julia. I wonder how
much of Stan's codebase is about parsing/code-generation (which would be
drastically simpler in Julia) versus fine-tuning their NUTS sampler. And
how much of that work about automatic differentiation/code generation could
You can just do:
@assert subtypes(Type) == [DataType, TypeConstructor, Union]
I just tested this:
julia> @time for i in 1:1000
@assert subtypes(Type) == [DataType, TypeConstructor, Union]
end
3.025415 seconds (767.00 k allocations: 224.075 MB, 0.49% gc time)
El sábado, 26
has anyone successfully built Julia for Raspberry Pi 2? I understand that
it's able to build now. If anyone has been able to do this ...could you
share your binary? I'm building it right now, but it seems it's going to
take ages, and I have yet to see it fail or not!
I want to build a
I just tested and the output seems to be deterministically ordered:
julia> x = map(string, subtypes(Any));
julia> y = sort!(map(string, subtypes(Any)));
julia> x == y
true
El sábado, 26 de diciembre de 2015, 12:52:51 (UTC-6), Ray Toal escribió:
>
> I noticed that
>
> *julia>
In Julia 0.4 anonymous functions are non-generic (in 0.5 they will,
however, be generic), so that's one way to create a non-generic function.
Aside from anonymous functions, the only non-generic are the builtins,
defined in C code using the add_builtin_func function:
$ ack add_builtin_func src
We could use something like this:
julia> isbuiltin(x) = in(symbol(x), builtins())
isbuiltin (generic function with 1 method)
julia> isbuiltin(is)
true
We could also change this functions documentation, something like this:
help?> is
search: ind2sub ind2sub! @ip_str include_string @int128_str
I think this would be useful even if not exported so we can give better
error messages, ie:
julia> @which 1 === 1
ERROR: ArgumentError: argument is not a generic function
in methods at reflection.jl:140
Ok, so it's not a generic function, then what it is?
julia> @which 1 === 1
ERROR:
Alan please don't double post the same
question: https://groups.google.com/forum/#!topic/julia-users/2AoQQKVP2Do
It makes it difficult to follow the thread, thanks!
El domingo, 27 de diciembre de 2015, 11:21:35 (UTC-6), alan souza escribió:
>
> Hi. I was wondering what is the correct way to
I needed to ad a `convert(Vector{Symbol}, .)`, since map can't tell
it's a Symbol array, why?
function builtins()
nams = filter(s -> isdefined(Base, s), names(Base, true, true))
objs = map(s -> Base.(s), nams)
funcs = filter(x -> isa(x, Function) && isa(x.env, Symbol), objs)
Hi,
I'm trying the following,
plot(x = [1;1], y = [1;2], color = [1;2], Geom.rectbin)
but it produces an empty plot. On the other hand, both of the following do
produces meaningful plots,
plot(x = [1;1], y = [1;2], color = [1;2], Geom.point)
plot(x = [1;2], y = [1;2], color = [1;2],
Viral and Symon,
Since you asked, I will write out some rough and probably excessively
abstract Ideas that have been floating around in my head below. I don't
have time to formally polish, so please forgive the inchoate nature of
these thoughts:
Yes, composability and generality are the
Have you seen Simon D's viz stuff at juliacon? I believe a lot of that
stuff is soon going to be ready for wider use. I am sure he will chime in
further on this thread.
-viral
On 27 Dec 2015 11:59 pm, "Lampkld" wrote:
>
> Viral and Symon,
>
> Since you asked, I will write
Le dimanche 27 décembre 2015 à 10:24 -0800, axsk a écrit :
> I want to ccall a file which is relative to the packages dir, but
>
> const path = joinpath(@__FILE__,"..","bin","lib.so")
> ccall((:fn, path),...)
>
> fails with the same error as above
> first argument not a pointer or valid
Ah, I didn't think about performance. I was simply thinking that sets make
more sense semantically when the order does not matter, and arrays or lists
make sense when the order does matter. I thought there would be no point in
using an array for unordered items, but it sounds like the point is
Thanks for everybody's help. I got something working which satisfies
me.
Regarding Cedric's question, I am trying to compute the Feigenbaum
number delta to arbitrary high precision.
https://en.wikipedia.org/wiki/Feigenbaum_constants
I am using a brute-force method to compute delta. The basic
Perhaps, but all of this is going to change fairly soon. Why is this
information useful?
On Sun, Dec 27, 2015 at 4:03 PM, Ismael Venegas Castelló <
ismael.vc1...@gmail.com> wrote:
> We could use something like this:
>
> julia> isbuiltin(x) = in(symbol(x), builtins())
> isbuiltin (generic
Hi. I was wondering what is the correct way to pass a function as argument
preserving the return type information of this function
For instance in the following code:
*function sinc{T<:Real}(x::T)return T((x != zero(T)
Hi. I was wondering what is the correct way to pass a function as argument
preserving the return type information
For instance in the following code:
*function sinc{T<:Real}(x::T)return T((x != zero(T)
)?(sin(pi*x)/(pi*x)):(one(T)))endfunction
In the REPL
*julia> **methods(is)*
*ERROR: ArgumentError: argument is not a generic function*
* in methods at reflection.jl:180*
and ditto for isa and typeof and perhaps others.
Two quick questions:
- Is it possible for the programmer to create nongeneric functions in
Julia?
- If
So `is` is a builtin anonymous function?
julia> Base.function_name(is)
:anonymous
Stefan perhaps we should add a builtins function to inference.jl? Indeed
it's not obvious at all!
julia> function builtins()
nams = filter(s -> isdefined(Base, s), names(Base, true, true))
It seems adding typecheck is 2x improvements in my laptop.
y = zeros(T, n)
for i in eachindex(X)
y[i] = F(X[i])::T
end
return y
Hey Stuart,
I used to do research on whether the Maunder Minimum was caused by the sun
being pushed out of its chaotic basin of attraction, so this was
interesting to me! I don't think you need code generation. Here is the
fastest code that I could come up with, I'm sure that others might make
For calcF your variables:
Variables:
X::Array{Float64,1}
F::F
n::Int64
y::Array{Float64,1}
#s76::Int64
i::Int64
##dims#7321::Tuple{Int64}
and return value:
return y::Array{Float64,1}
end::Array{Float64,1}
Are correctly inferred if I use floats so it seems fine.
But if I use
Thank you Milan I will test this ASAP :D
El domingo, 27 de diciembre de 2015, 16:46:45 (UTC-6), Milan Bouchet-Valat
escribió:
>
> Le dimanche 27 décembre 2015 à 11:47 -0800, Ismael Venegas Castelló a
> écrit :
> > has anyone successfully built Julia for Raspberry Pi 2? I understand
> > that
Kevin I tested in my Win laptop with 0.3.11, 0.4.2, 0.4, 0.5+ also the same
versions in julia box, and the output is deterministically sorted, It seems
this has been the way it works for some time now, then I looked at the code
and it’s indeed sorted (should have done that first! :P ):
-
I just found this Rpi Emulator (I don't want to hinder the build process in
my Rpi2 rigth now), but it dosen't say which Rpi it's emulating.
* http://sourceforge.net/projects/rpiqemuwindows
El domingo, 27 de diciembre de 2015, 17:05:05 (UTC-6), Ismael Venegas
Castelló escribió:
>
> Thank you
Ray, thanks for the clarification--makes sense. In fact, for introspection
code like 'subtypes', performance is probably the wrong argument--it's
unlikely that it occurs in performance-critical code. I think it's really
that arrays are just simpler.
One aesthetic change I could imagine would be
Thanks for looking and posting (I've been on my phone). I think I might
have written that code, actually. ;-)
Cheers!
Kevin
On Sunday, December 27, 2015, Ismael VC wrote:
> Kevin I tested in my Win laptop with 0.3.11, 0.4.2, 0.4, 0.5+ also the
> same versions in
Le dimanche 27 décembre 2015 à 11:47 -0800, Ismael Venegas Castelló a
écrit :
> has anyone successfully built Julia for Raspberry Pi 2? I understand
> that it's able to build now. If anyone has been able to do this
> ...could you share your binary? I'm building it right now, but it
> seems it's
I think Gadfly is treating your x-values as continuous values for some
reason. This should do what you want
plot(x = [1;2], y = [1;2], color = [1;2], Geom.rectbin, Scale.x_discrete)
On Sunday, December 27, 2015 at 7:49:28 AM UTC-8, Uri Patish wrote:
>
> Hi,
>
> I'm trying the following,
>
>
I'm sure the order won't ever change, but I'd still find it odd if the
documentation of subtypes were to say
"Returns a list of subtypes, sorted by the name of the subtype"
because, well, what about namespaces? What about all sorts of Unicode
collation definitions that would have to be a part
Hi Ray,
You're probably the first person to make this observation. I can see your
point, and I don't really have a strong argument or opinion, really--the
main reason it's sorted is probably because it looks nicer--at least if I
did write that code, that would have been my reasoning.
If you're
I installed MATLAB packages.
"Pkg.add("MATLAB")
ENV["MATLAB_HOME"]="F:\\MATLAB\\R2015b\\bin"
using MATLAB
x=[1,2,3]"
The codes above are OK.
When I type "@mxput x",
it shows "ERROR: UndefVarError: @mput not defined".
What's wrong?
What is the functionality you fancy the most from ggplot and ggvis?
Am Mittwoch, 11. November 2015 02:24:27 UTC+1 schrieb Lampkld:
>
> Congratulations on the exciting news!
>
> I have played around with Julia A bit and love the language , But Found
> Its Lacking Some robust stats/ml/data
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