Hi guys,
A few months back I ran into what I thought was a rather annoying design
decision: if A is an array and b is a number, then A + b is meaningless,
and if we want to add b to all elements of A individually we need to use A
.+ b. All of this was discussed in:
I noticed that deepcopy of a vector doesn't know that the result is the
same type. Regular copy does, see below. Is this intentional or a bug?
In [24]:
v=rand(5)
@code_typed deepcopy(v)
Out[24]:
1-element Array{Any,1}:
:($(Expr(:lambda, {:x},
On Tuesday, July 15, 2014 3:10:50 AM UTC-4, Sheehan Olver wrote:
I noticed that deepcopy of a vector doesn't know that the result is the
same type. Regular copy does, see below. Is this intentional or a bug?
It looks to me like this is the reason
function _deepcopy_array_t(x, T,
The thing that happened was that lots of people disliked the new behavior and
the depreciation was reverted. Consistency lost over convenience.
See https://github.com/JuliaLang/julia/pull/5810#issuecomment-45773715
On Tuesday, 15 July 2014 17:56:16 UTC+10, Ivar Nesje wrote:
The thing that happened was that lots of people disliked the new behavior
and the depreciation was reverted. Consistency lost over convenience.
See https://github.com/JuliaLang/julia/pull/5810#issuecomment-45773715
Wahoo!
I will address the warning about add! today.
Dahua
On Monday, July 14, 2014 3:43:58 PM UTC-5, Kevin Squire wrote:
Although annoying, these warnings won't actually cause any problems.
The best bet to remove the warnings is to file an issue with
NumericExtensions.jl, preferably (but not
thanks kevin,
that just cut my run time into half! brilliant.
I'm sure other users would benefit from adding this to the documentation.
then there's so many places where to add documentation in julia that it's
hard to even think about where to start. :-)
cheers
florian
On 14 July 2014 22:01,
If you read dot as point
Then pointwise ops make a kind of sense
I just added `coordinates`, which lets you access the coordinates of the
contour lines as follows:
```
c = contours(x,y,z,0) # get contour level at z==0
for line in c.lines # line is a Curve2, which is basically a wrapper around
a Vector{Vector2}
xs, ys = coordinates(line)
plot(xs,ys) #
OS X 10.8.5 + Fresh installation of Julia 0.3rc1
after installing Winston and import it, the warning Could not import
Base.add! into DataStructures pops up and the `add` function in Winston
cannot be used in the following example
x = linspace(0, 3pi, 100)
c = cos(x)
s = sin(x)
p =
Thanks! Hadn't heard of PolitiHacks - looks interesting
On Monday, July 14, 2014 12:17:52 PM UTC-7, Tony Kelman wrote:
Cool, there are a lot of interesting this you can do at the intersection
of politics and data. I know a guy who runs a little organization called
PolitiHacks, I doubt he's
Functions deprecated after 0.2 were removed from 0.3-rc1 recently,
including Base.add. The warning is happening because packages are trying to
import add from Base and it no longer exists. The warning does not actually
cause any issues and can be ignored in this case. add(p,
am I doing something worng?
On Tuesday, 15 July 2014 14:36:47 UTC-4, Zahirul ALAM wrote:
the following line of code does not suppress output.
a = λ ; #comment
however
a = λ ; does suppress output
the following line of code does not suppress output.
a = λ ; #comment
however
a = λ ; does suppress output
Yes, this is a known bug; the output suppression in the REPL (and IJulia,
and IPython) is a quick hack that doesn't really parse the source code, so
it gets confused by comments. (Doing it properly is complicated because
you have to distinguish real comments from # embedded in strings.) See:
Stepfan, I highly recommend you to use the Anaconda Python Distribution, if
you are using Windows! Then you would also need pandoc, MiKTeX and some
LaTeX editor to output the PDF. But you are right, Julia's package system
is so much better! Genius.
The only thing I don't get is how to install
Looking forward to it!
And thanks for helping out, Yee siang Ng!
On Monday, 14 July 2014 19:10:47 UTC+2, Stefan Karpinski wrote:
Thank you! I'll work no getting this posted and hopefully we'll get an
InfoQ video soon.
On Mon, Jul 14, 2014 at 12:58 AM, Yee Sian Ng ngye...@gmail.com
I found this short talk about the Jupyter project on reddit: video
https://www.youtube.com/watch?v=JDrhn0-r9Egt=4m10s, slide deck
https://speakerdeck.com/fperez/project-jupyter. Project site: jupyter.org
.
I haven't heard of it before, but if I understand correctly, the Jupyter
project is
Wow, excellent explanation! Thanks for all your answers! And yes, I'm
definitely going to print out BLAS cheat sheet :)
(By the way, I'm really impressed how friendly and helpful Julia community
is. I hope it will stay the same when it grows up N times larger!)
On Tue, Jul 15, 2014 at 4:09 AM,
On Tue, Jul 15, 2014 at 1:10 PM, Andrei faithlessfri...@gmail.com wrote:
(By the way, I'm really impressed how friendly and helpful Julia community
is. I hope it will stay the same when it grows up N times larger!)
I hope this too! This is a lovely community – thanks everyone for being so
Thanks, Sam! There are some other packages having similar issues. I'll just
wait for updates.
Xiaowei
在 2014年7月16日星期三UTC+8上午1时07分14秒，Sam L写道：
Functions deprecated after 0.2 were removed from 0.3-rc1 recently,
including Base.add. The warning is happening because packages are trying to
Hi everyone, I'm trying to start using Julia for some Monte Carlo
simulations
(not MCMC) which I'd like to parallelize. I haven't found any documentation
for setting the RNG's seed for parallelization. The naive approach gives
different results than non-parallel execution (which is not
Hi,
I am working on a Markov chain Monte Carlo script right now and am trying
to figure out the parameter generation part of the script. In pseudocode, I
am trying to do
a = 0.1
b = 0.1
c = 0.1
function gen()
a = a + rand()
b = b + rand()
c = c + rand()
if a b c = 0
I think you want something more like a = 0 b = 0 c = 0
Also, you probably don't want to use global variables for code where
performance matters. You should pass a, b and c to gen() as parameters gen(a,
b, c).
-- John
On Jul 15, 2014, at 6:31 PM, yaoismyh...@gmail.com wrote:
Hi,
I am
Should insert! not be able to insert a collection?
x = [1,2,7,8]
y = [3,4,5,6]
insert!(x,2+1,y)
Is then unable to complete the insertion and create [1,2,3,4,5,6,7,8].
There is a costlier way to do this at the moment however.
splice! almost replicates the required functionality but it replaces
Hi Michael,
You can actually use splice!:
julia splice!(x, 3:2, y)
0-element Array{Int64,1}
julia x
8-element Array{Int64,1}:
1
2
3
4
5
6
7
8
3:2 is a convention in julia that indicates the (empty) location in the
array between index 2 and index 3 (e.g., searchsorted(x,3) for your
I did the following on a DataFrame, but got error. What should I do
instead?
julia df = insert!(df, 25, dfa)
ERROR: `insert!` has no method matching insert!(::DataFrame, ::Int64,
::DataFrame)
You'll have to set the seed on each process, i.e. fetch 2 srand(1); fetch 3
srand(2); However, I am not sure what our random number generator (dsfmt)
promises about independence of the different streams. We should look into
that to ensure that you get good random number when running in parallel.
If your goal is that each call to rand(), regardless of process,
sequentially pulls a number from the RNG stream, then perhaps you just need
to create a MersenneTwister([seed]) object.
mystream = MersenneTwister(1)
## Parallel execution
srand(1)
parfor = @parallel (vcat) for i=1:4
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