Try unix2datetime
I don't know but I'm based in Gothenburg and often visit Stockholm so if
you gather a group please keep me informed and I'll see if I can join.
Or if there are more people based in Gothenburg please reply to this thread
and maybe we can help strengthen the Julia community here in Sweden.
Thanks Ivar, that's perfect:
julia now = Dates.now()
2014-10-27T06:35:08
julia ut=datetime2unix(dt) # to Float64
3.374784e8
julia unix2datetime(ut)
2014-10-27T06:35:08
On Mon, Oct 27, 2014 at 9:09 AM, Ivar Nesje iva...@gmail.com wrote:
Try unix2datetime
Julia is located at `C:\Users\NN\AppData\Local\Julia-0.3.2\bin\julia.exe`
I should I add it in path?
I do not think it is correctly there since I ran the command prompt and
typed julia and it does not recognize the command
On Sunday, October 26, 2014 4:15:42 AM UTC-7, ccsv.1...@gmail.com
You can squeeze a tiny bit extra out of the implementation by using the
inplace gemv!, i.e.
function mgs2(X)
# mgs speed project
nobs, nvars = size(X)
R = eye(nvars)
for l=1:nvars-1
v_i = view(X,:,l+1:nvars)
s = view(X,:,l);
r = vec(view(R,l,l+1:nvars))
On Friday, October 24, 2014 04:27:46 AM Ján Dolinský wrote:
I assume some mat-vec (or mat-mat) operations like (v_i' * s) are
directly
translated into a BLAS call e.g. BLAS.gemv('T',v_i,s), right ? Is there
a
way to find out what is being called under the hood ?
@which
--Tim
Thanks for your answers. I was aware of the principle, but since I am
working on a problem in which my functions have to access only a couple of
values stored in fairly large Arrays, I was wondering whether there could
be situations in which it is too costly to pass the array to the function,
And, as an addition to that, does this principle also hold for functions;
i.e., if I define some function and use it inside another function, should
that previously defined function be passed as well?
Is this still a problem? I'd guess this is
https://github.com/JuliaLang/Color.jl/issues/68
--Tim
On Sunday, October 19, 2014 11:31:04 AM Bruno Gomes wrote:
version 0.3.1
Arrays are pass-by-reference, so only the reference is copied to the
function. The data in the array is not moved or copied at all. This means
it costs the same no matter how big the array is.
On Monday, October 27, 2014 12:27:30 PM UTC+2, Nils Gudat wrote:
Thanks for your answers. I was
Thanks! I will try it later, when I get back from work.
On Mon, Oct 27, 2014 at 2:24 AM, Tony Kelman t...@kelman.net wrote:
Okay, it turns out it's not very hard at all to use the opensuse build
service, fork the package that's causing trouble, and revert it back to the
last working state.
Hi!
I have programmed a very simple function that takes any permutation p of
[1:n] and finds the next permutation in dictionary order. I know this is
well-programmed already, but I am learning.
I have programmed the same algorithm both in Julia and Matlab. It is not a
sophisticated algorithm,
https://www.google.ch/webhp?q=windows+7+add+to+path
...
first
hit:
http://geekswithblogs.net/renso/archive/2009/10/21/how-to-set-the-windows-path-in-windows-7.aspx
or whats the problem here?
It would be easier to just adjust your ijulia sublime settings (as written
in the sublime ijulia
Have you read through the performance tips section of the manual, and used the
various tools it advertises?
Best,
--Tim
On Monday, October 27, 2014 05:50:49 AM Felipe Jiménez l wrote:
Hi!
I have programmed a very simple function that takes any permutation p of
[1:n] and finds the next
Today, I tried to install RDatasets again and mysteriously no problem
arised. Before the 'Pkg.add' command I just typed
Pkg.build()
Pkg.update()
After that, the command
Pkg.add(RDatasets)
ran normally.
Could someone please explain this? '-'
Em sábado, 11 de outubro de 2014 14h45min10s
On Mon, Oct 27, 2014 at 5:25 AM, Ján Dolinský jan.dolin...@2bridgz.com
wrote:
Speed is pretty much the same. I assume copy() and deepcopy() works the
same for arrays.
Yes, they do the same thing, although deepcopy probably creates a small
(unnecessary) dictionary, but for this it may not be
There are a number of idioms here that Matlab has heavily optimized that we
haven't because there are more straightforward (if not always easier to
use) alternatives in Julia. In particular, the Matlabism of passing an
array and then assigning back to it is identified and translated into an
Hi,
There is a package NamedArray that attempts to make it possible to work
with named indices and dimensions in native Julia arrays, just like you are
used to in R. There is no interface to Rif.jl, though. Would this be a
useful extension?
---david
On Sunday, October 26, 2014 11:01:51 PM
Related to this:
On Sunday, October 26, 2014 8:17:16 PM UTC+1, Stefan Karpinski wrote:
If you do `git checkout release-0.3` then you will be on the `release-0.3`
branch instead of `master`; you can then proceed exactly as you used to but
will only get the relatively conservative changes on
Yes, Tim, I have read the performance tips. I am trying to see why my
function does a lot of memory allocation, but I don't see why.
I thought that someone more expert than me could spot the problem in no
time...
On Monday, October 27, 2014 2:01:02 PM UTC+1, Tim Holy wrote:
Have you read
Thank you, Stefan.
It is true that my programming style is heavily influenced by years of
Matlab (and I'm not a good programmer in anything). However I'm staying
with Julia, so the learning will come.
For the time being I will try to find out why my function allocates so much
memory
P.S. I have tried using in-place
sort!(p[fp:end])
rather than
p[fp:end] = sort(p[fp:end])
but it does not do what I expected.
The thing here is quite subtle, but the problem is that currently p[fp:end]
returns a copy, rather than a reference. This will change in 0.4, but there
I tried sort!(sub(p,fp:length(p))) but it any faster. I suspect that if you
want to keep with the general shape of this code, it gets kind of verbose.
You can probably do something that's different and much more efficient
though – similar to what the standard library does.
On Mon, Oct 27, 2014 at
Speaking of which, what's wrong with the standard library function for
producing permutations? They're not produced in the order you want them in?
On Mon, Oct 27, 2014 at 12:26 PM, Stefan Karpinski ste...@karpinski.org
wrote:
I tried sort!(sub(p,fp:length(p))) but it any faster. I suspect that
One of the nice things about git is that as long as things have been
committed sometime in the past, things tend to be pretty resilient to
screwing up, unless you do Dangerous Things (TM). (These are things like
force pushes, rebases, etc...)
To speak in specifics, merely running git checkout
I think this was being done as a learning exercise, not an attempt to generate
production code.
That said, reading Julia's Base code is a great way to learn Julia.
-- John
On Oct 27, 2014, at 9:27 AM, Stefan Karpinski ste...@karpinski.org wrote:
Speaking of which, what's wrong with the
It took me a long time to understand R's dimension indication, coming
myself from octave before R. I think I never really got used to it, I
always need to think twice in R. My way of remembering the R semantics is
that the dimensions indicate the dimensions that you are left with after
the
The fonts aren't readable (present?) when rendering web charts on osx.
For example, using gadfly:
plot(posts, x=:score, Geom.histogram)
Opens Safari with the following rendered chart:
http://i.imgur.com/3BxEHmh.png
If you store the plot and write it to png with Draw, the fonts look fine.
Hi all,
I have created a Julia wrapper for the Fast Artificial Neural Networks C
library (http://leenissen.dk/fann/wp/) http://leenissen.dk/fann/wp/, in
the hope it will be useful for someone else. You can find it in this
https://github.com/gasagna/FANN Github repo.
Any comments, testing and
Even more simply, once the previous code (from my previous post) is loaded,
just cutting and pasting this into Julia Studio does not seem to work.
(The value for theta can be changed to 0.2 or something to observe that a
change has not been made.)
The problem seems to be with the white space
I am actually experiencing a similar problem on Julia Studio on my Mac OSX
10.9.3. The code below is a clip from an optimization algorithm I am
writing. If I have theta (which is a 4-element vector; it is called at
the bottom) already set to some value, then copying and pasting the code
Best to post an issue on Gadfly: https://github.com/dcjones/Gadfly.jl/issues
On Mon, Oct 27, 2014 at 4:22 PM, James Kyle li...@jameskyle.org wrote:
The fonts aren't readable (present?) when rendering web charts on osx.
For example, using gadfly:
plot(posts, x=:score, Geom.histogram)
I just compiled Julia with MKL using the intel compilers and when I try to
do a simple plot using Pyplot julia segfaults
julia using PyPlot
INFO: Loading help data...
julia plot(linspace(0,1,100))
signal (11): Segmentation fault
signal (11): Segmentation fault
mkl_blas_avx2_xdcopy at
Thanks a lot. It worked with the hide_overlaps set to false. Is there a way to
set the label’s color too? I couldn’t find that in the documentation.
On 25 Oct 2014, at 12:24, Darwin Darakananda darwinda...@gmail.com wrote:
There's a Geom.label element you can use. Although I don't think it
I was trying to experimentally find the maximum number for type float64.
The number I got is 8.98846567431158e 307. However built-in function
realmax(Float64) returns 1.7976931348623157e308. What is the reason of
this difference?
This is my code to find maximum number:
temp = 1.
max = 1.
If your goal is to reproduce the bug, your best chance is to say `using Color`
before calling any Pkg commands :-).
--Tim
On Monday, October 27, 2014 06:59:12 AM Bruno Gomes wrote:
Today, I tried to install RDatasets again and mysteriously no problem
arised. Before the 'Pkg.add' command I
I just moved from Chicago and am curious.
Relatedly, a data science meetup in Broomfield, CO has a half Spark / half
Julia night
http://www.meetup.com/Data-Science-Business-Analytics/events/211746812/
coming up Wednesday Nov 5th, with Galen O'Neil running the Julia half. No
idea what the
You're skipping a lot of floating-point numbers every time you double your
max value. Your code computes the largest representable power of two, not
the largest representable Float64. The general representation
http://en.wikipedia.org/wiki/Double-precision_floating-point_format of a
Float64 is:
1
I can't speak to your particular issue, but I strongly advise against using
Julia Studio. It doesn't use the an even close to recent version of Julia,
and isn't really been actively maintained.
On Monday, October 27, 2014 6:09:53 PM UTC-4, Michael Wojnowicz wrote:
Even more simply, once the
Looks great, you should register that in METADATA (after renaming to
FANN.jl)
- Iain
On Monday, October 27, 2014 5:09:47 PM UTC-4, Davide Lasagna wrote:
Hi all,
I have created a Julia wrapper for the Fast Artificial Neural Networks C
library (http://leenissen.dk/fann/wp/)
Do you know whether you were using the LP64 or ILP64 interfaces in MKL? Can
you post the entire contents of your Make.user and say which MKL shell
scripts you ran beforehand?
On Sunday, October 26, 2014 2:19:25 PM UTC-7, Derek Tucker wrote:
I just compiled Julia with MKL using the intel
Might be worth noting whether make testall passes, as it will help determine
how much is PyPlot-specific.
--Tim
On Monday, October 27, 2014 04:23:11 PM Tony Kelman wrote:
Do you know whether you were using the LP64 or ILP64 interfaces in MKL? Can
you post the entire contents of your Make.user
I'll be there, since I'm the one talking. It's nice to know I'll have at
least a friendly face in the audience.
I have to admit I'm surprised that I was asked to speak, but there are
enough other talks available to draw from that I think I can do a
reasonable job.
I'm sure you will -- looking forward to meeting you. Have you come across
any other users in the area?
On Monday, October 27, 2014 5:57:10 PM UTC-6, g wrote:
I'll be there, since I'm the one talking. It's nice to know I'll have at
least a friendly face in the audience.
I have to
There is also
julia prevfloat(Inf)
1.7976931348623157e308
This is an announcement of Dierckx.jl, a Julia wrapper for the dierckx
Fortran library from netlib. This is the same library underlying the spline
classes in scipy.interpolate.
http://github.com/kbarbary/Dierckx.jl
Note: Some of the functionality here overlaps with Grid.jl, Tim Holy's
pure-Julia
Since Kyle is very polite, I'll be more direct: in those (limited) cases where
head-to-head comparison has been performed, Dierckx is considerably faster
than Grid. Grid's performance problems have been known for some time and were
already slated to be overhauled with a new package,
Sorry, mistyped, meant to say It doesn't use an even close to recent...
and so on.
Basically: Julia Studio is stuck (forever?) on Julia 0.2
On Tue, Oct 28, 2014 at 12:05 AM, Uwe Fechner uwe.fechner@gmail.com
wrote:
What do you mean with an?
On Tuesday, October 28, 2014 12:11:16 AM UTC+1,
I still don't understand your sentence. Perhaps you mean:
The read-evaluate-print loop (REPL) doesn't even come close to recent
versions of Julia?
This could (probably) be fixed by integrating ipython-qtconsole with the
ijulia profile.
And Julia Studio 0.4.5 supports Julia 0.3 (well, currently
What Iain meant is that Julia Studio (except on Windows) doesn't support a
modern version of Julia.
-- John
On Oct 27, 2014, at 9:26 PM, Uwe Fechner uwe.fechner@gmail.com wrote:
I still don't understand your sentence. Perhaps you mean:
The read-evaluate-print loop (REPL) doesn't even
I will try to fix this today or tomorrow.
Overly occupied by grant proposal and setting up a new lab in the past
month. Really sorry about the package.
Dahua
On Friday, October 24, 2014 2:33:10 AM UTC+8, Tim Holy wrote:
On Thursday, October 23, 2014 10:50:19 AM Douglas Bates wrote:
What
for the benefit of those whom may not have seen the latest Forio page:
Information regarding Julia version 0.3
Julia Studio 0.4.5 for Windows contains support for Julia 0.3.
Julia Studio 0.4.4 for Mac Linux only contains support for Julia 0.2.
In the mean time, you can try Juno
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