Anyone know of a good iPhone/iPad keyboard for typing out Julia and
Markdown code? I think I just want a regular keyboard with extra rows with
common keys like `, $, ^, 0…9, etc.
I found "SciKey" but it doesn't look like it does everything on one screen.
"Markdown Keyboard" looks better,
Thank you, Tobi.
michele
On Sun, Oct 23, 2016 at 7:35 PM, 'Tobias Knopp' via julia-users <
julia-users@googlegroups.com> wrote:
> Dear Michele,
>
> yes the assumption is absolutely valid. Julia arrays are stored
> column-major ordered in memory and this will not change. Since write does
> only
See also here:
https://groups.google.com/d/msg/julia-users/hIVawSgFvOs/9EpbqwWWBgAJ and
the conclusion was: avoid writing 1. (which will not be allowed by the
parser some time) and write 1.0 instead.
On Mon, Oct 24, 2016 at 3:40 AM, J Luis wrote:
> It parses .+ as
On Sun, Oct 23, 2016 at 1:22 PM, 中山慎太郎 wrote:
> Hello,
>
> I'm trying to ccall my DLL as follows :
>
> function start(args :: Array{String, 1})
> return ccall((:TestFunction, "mydll.dll"), Int32, (Int32,
> Ptr{Ptr{UInt8}}), length(args), args)
> end
>
> The C declaration is
It parses .+ as broadcasting of two Ints. Do instead
typeof(1. +1)
Float64
segunda-feira, 24 de Outubro de 2016 às 02:33:15 UTC+1,
christop...@unibas.ch escreveu:
>
> What is the difference between 1.0 and 1. ?
> Both are of type Float64, but adding 1 leads to the result 2.0, i.e.,
>
Hello,
I'm trying to ccall my DLL as follows :
function start(args :: Array{String, 1})
return ccall((:TestFunction, "mydll.dll"), Int32, (Int32, Ptr{Ptr{UInt8
}}), length(args), args)
end
The C declaration is as follows :
extern int TestFunction(int argc, char * argv[]);
The problem
What is the difference between 1.0 and 1. ?
Both are of type Float64, but adding 1 leads to the result 2.0, i.e.,
Float64, in the first case,
and 2, i.e., Int64 in the second.
_
_ _ _(_)_ | A fresh approach to technical computing
(_) | (_) (_)|
At least with my experience on a mac, I've never seen real linear algebra
code (not just peakflps) in Julia + OpenBLAS saturate more than 2 cores,
even when setting the thread count to 4 on a machine with 4 real cores.
When I try similar code on a linux machine I have access to, I never have
Well it downloads some source as well, but it isn't used.
On 23 October 2016 at 21:59, digxx wrote:
> or does it try to download the source here upon Pkg.build("Nemo") ?
>
or does it try to download the source here upon Pkg.build("Nemo") ?
Well so far nothing has changed ;)
So:
while loading C:\cygwin64\home\Diger\.julia\v0.5\Nemo\deps\build.jl, in
expression starting on line 1
% Total% Received % Xferd Average Speed TimeTime Time
Current
Dload Upload Total SpentLeft
No, on Windows it doesn't build from source, but downloads binaries. After
the downloading is done, that's it. It should be ready to use.
If you still have the same problem, maybe we need to rebuild one of the
binaries for you. I'll have to talk to Tommy and see what he knows about
this problem.
Maybe I should have pointed out that I'm on windows...
What do u mean that explains why it doesn't go any further?
Is Nemo not finished yet for Windows?
Ah, you are on Windows. That explains why it doesn't go on any further.
I will have to ask Tommy why he thought this was a Pari problem. I don't
see it from the error you reported.
Bill.
On 23 October 2016 at 21:28, digxx wrote:
> No it does not go on...When I manually
>
> No it does not go on...When I manually start Pkg.build("Nemo") in the same
> session I get:
>
julia> Pkg.build("Nemo")
INFO: Building Nemo
WARNING: `@windows` is deprecated, use `@static is_windows()` instead
in depwarn(::String, ::Symbol) at .\deprecated.jl:64
in @windows(::Any, ::Any) at
The above shows that everything downloaded ok, I think. Did it not then go
on and rebuild everything?
Bill.
On 23 October 2016 at 21:11, digxx wrote:
> It does not work either. When I run Pkg.build("Nemo") it starts
>
> julia> Pkg.build("Nemo")
> INFO: Building Nemo
>
It does not work either. When I run Pkg.build("Nemo") it starts
julia> Pkg.build("Nemo")
INFO: Building Nemo
WARNING: `@windows` is deprecated, use `@static is_windows()` instead
in depwarn(::String, ::Symbol) at .\deprecated.jl:64
in @windows(::Any, ::Any) at .\deprecated.jl:472
in
Reviewers needed help us bring #JuliaLang website to your native language
...one string at a time!
Kudos to Akis Vassiliadis for completing 33% of the Greek translations by
himself and with that moving his language to the top of the list!
Hi Simon,
Simon Danisch writes:
> There is a speed difference, which you can see beautifully like this:
>
> function _sum{T}(::Type{T}, A)
> r = zero(T)
> @inbounds for i in eachindex(A)
> r += T(A[i])
> end
> r
> end
>
great, thanks. My machine seems to be way slower that
Dear Michele,
yes the assumption is absolutely valid. Julia arrays are stored
column-major ordered in memory and this will not change. Since write does
only dump the memory on disk this is also not going to change.
Cheers,
Tobi
Am Mittwoch, 19. Oktober 2016 09:03:49 UTC+2 schrieb Michele
21 matches
Mail list logo