Please also check Boltzmann.jl (https://github.com/dfdx/Boltzmann.jl) for
DBN pre-training integration example with Mocha.jl!
On Friday, February 27, 2015 at 1:32:02 AM UTC-5, Chiyuan Zhang wrote:
Mocha.jl https://github.com/pluskid/Mocha.jl v0.0.6: Mocha is an
efficient and flexible deep
Mocha.jl https://github.com/pluskid/Mocha.jl v0.0.6: Mocha is an
efficient and flexible deep learning framework for Julia. This time we
include some small but very useful updates.
v0.0.7 2015.02.27
- Infrastructure
- Clearer Nesterov solver (@the-moliver)
- Staged momentum
This is more of a curiousity question than an actual use case. Is there any
way to have Julia manage heap allocated memory that is initialized by a C
function? By this, I mean suppose I had a function:
void foo(void *x) {
...initize some structure in C here from the memory passed in by
Considering below code:
str=abc
str*=def
Is the new string def just be appended after the memory space of abc,
or both strings were copied to a new momory space? Is str*=def equal to
str=str*def and str=$(str)def in speed and memory level? Is below code
in O(n) or in O(n^2) speed?
s=
for
@everywhere srand(seed) would give reproducibility, but it would probably
not be a good idea since the exact same random variates will be generated
on each process. Maybe something like
for p in workers()
@spawnat p srand(seed + p)
end
However, out RNG gives no guarantees about independence of
On Thu, Feb 26, 2015 at 3:44 AM, lapeyre.math1...@gmail.com wrote:
(I am resending because, this my message to Ondřej did not go to the list)
I can see my message right here:
https://groups.google.com/d/msg/julia-users/jP1VlOe80HQ/e4KzNARuI9AJ
Do you know much about the SymPy interface ? (or
Hi Jordan,
I don't have an answer, but if you don't get a response here, I would
suggest opening up an issue with Gadfly.jl.
Cheers,
Kevin
On Wednesday, February 25, 2015, Jordan Meyer jlme...@umich.edu wrote:
I was playing around with using Gadfly's Geom.ribbon to make plots showing
Filed here https://github.com/JuliaLang/julia/issues/10339.
There is a really nice example of using pmap for parallel bootstrapping
purposes
on
http://juliaeconomics.com/2014/06/18/parallel-processing-in-julia-bootstrapping-the-mle/
.
If you rerun the code however, it's clear that the pmap function does not
respect the set seed command srand. I've
There's also a RopeString type.
--Tim
On Thursday, February 26, 2015 07:32:27 AM David P. Sanders wrote:
El jueves, 26 de febrero de 2015, 9:15:38 (UTC-6), Josh Langsfeld escribió:
It's equivalent to str = str * def. I believe that's the case for all
+=, *=, etc operators and all types.
Not directly with base Julia, but there is a very neat package with the
capability to call directly C++, using Clang to generate IR and then
JIT'ing (all in-memory, no files involved).
https://github.com/Keno/Cxx.jl
Is LLVM IR code portable across different LLVM and Clang versions?
No.
On
El miércoles, 25 de febrero de 2015, 20:32:59 (UTC-6), Tim Holy escribió:
On Wednesday, February 25, 2015 06:21:24 PM David P. Sanders wrote:
To continue the theme:
What is [[3, 4], [5, 6]] supposed to do now? I thought this was
supposed
to give me an array of arrays, but it
It's equivalent to str = str * def. I believe that's the case for all +=,
*=, etc operators and all types.
On Thursday, February 26, 2015 at 9:23:19 AM UTC-5, Jerry Xiong wrote:
Considering below code:
str=abc
str*=def
Is the new string def just be appended after the memory space of abc,
Thanks again! I'm finally satisfied with my current setup. Now I can stop
playing around with GitHub and actually focus on the code! :D
Cheers!
On Thu, Feb 26, 2015 at 5:22 AM, Tony Kelman t...@kelman.net wrote:
32 bit Linux is sort of doable, by manually downloading and extracting the
No, that is not possible with pmap.
I think something like @everywhere srand(seed) would partially work, but you'd
still suffer from non determinism in the scheduler that might run different
portions of the array in different processes depending on the current load on
your computer.
El jueves, 26 de febrero de 2015, 9:15:38 (UTC-6), Josh Langsfeld escribió:
It's equivalent to str = str * def. I believe that's the case for all
+=, *=, etc operators and all types.
That's correct. So the original code is O(n^2). A good way to do this is
using IOBuffer, as below.
str=abc
str*=def
Is the new string def just be appended after the memory space of abc,
or both strings were copied to a new momory space? Is str=str*def equal
to str*=def in speed and memory level? Is below code O(n) or O(n^2)?
s=
for i=1:1
end
Hello! Julia is build around LLVM and uses it for JIT compilation. Can I
use LLVM library bundled with Julia from within Julia code? I'd like to use
Julia to read LLVM IR code generated by Clang, modify it and write it back.
Is it possible to do with Julia? Can you give me some directions on
I opened an issue to further discuss some related questions regarding
concatenation and construction of matrices:
https://github.com/JuliaLang/julia/issues/10338
Thanks a lot! I tested them on Julia 0.3.6:
julia N=10;
julia @time concat1(N);
elapsed time: 37.870699284 seconds (23955546560 bytes allocated, 82.31% gc
time)
julia @time concat2(N);
elapsed time: 0.016476456 seconds (9538836 bytes allocated)
I also tried another way:
julia function
We're rebooting the New York City Julia meetup. The first event will be
next Tuesday, March 3rd – I'll be giving a talk entitled The Julian Way:
Learning to Think in Julia:
http://www.meetup.com/julia-nyc/events/220762254/. I suspect there's a lot
of people using and interested in Julia in the NYC
I didn't find a clear description of the difference in the documentation.
For example, if I define a function Bar in a separate file, what is the
difference of using require(Bar) from include(Bar) in another
script?
Also, the documentation for modules says :
Given the statement using Foo,
Thanks for the comments. - nice to know it's not my usual programming
inadequacies. I like the
for p in workers()
@spawnat p srand(seed + p)
end
idea. It would be even better if instead of resetting the seed it did a
(imaginary) @spawnat p jumpahead(seed,(p*X)) where X was larger than the
Could you give a example code?
On Thursday, February 26, 2015 at 5:53:51 PM UTC+1, Tim Holy wrote:
There's also a RopeString type.
--Tim
On Thursday, February 26, 2015 07:32:27 AM David P. Sanders wrote:
El jueves, 26 de febrero de 2015, 9:15:38 (UTC-6), Josh Langsfeld
escribió:
Don't worry about the RopeString business. The IOBuffer way is better and
RopeString may go away in the relatively near future.
On Thu, Feb 26, 2015 at 2:59 PM, Jerry Xiong xiongji...@gmail.com wrote:
Could you give a example code?
On Thursday, February 26, 2015 at 5:53:51 PM UTC+1, Tim Holy
El jueves, 26 de febrero de 2015, 10:53:51 (UTC-6), Tim Holy escribió:
There's also a RopeString type.
Nice! Though this seems to be under-documented (i.e., there is no
documentation)?
--Tim
On Thursday, February 26, 2015 07:32:27 AM David P. Sanders wrote:
El jueves, 26 de
Yes you warned me that it may sometimes segv, but what else can I do to
get the pointer to a variable (a scalar or a composite type)?
I asked it once in
https://groups.google.com/forum/?fromgroups=#!topic/julia-users/i8DO3pBAHPU
and my safe was to box it in pointer([M]). What else
Just a tiny little note on:
[1; 2; 3] is precisely the same thing as [1, 2, 3]
julia [1; 2; 3] == [1,2,3]
true
julia [1; 2; 3] === [1,2,3]
false
Luis
Hello everyone!
I'd like to know your opinions about my atomic units implementation for
the artificial hydrocarbon networks algorithm, right now I'm working on the
molecular units
- atomic_units.jl http://bit.ly/1wkwO4C
I still don't have a clear picture of how to implement the other
David,
why don't you just set up a Julia Meetup group. This will make it much
easier
to organize meetings and to keep interested participants informed.
I guess in Europe there are Julia Meetups in London and Zürich only, and it
would be nice to have Berlin come in next.
On Wednesday, February
Yeah, but that's nothing to do with the syntax. After all:
julia [1, 2, 3] === [1, 2, 3]
false
julia [1; 2; 3] === [1; 2; 3]
false
On 26 February 2015 at 19:55, Luis Benet luis.bene...@gmail.com wrote:
Just a tiny little note on:
[1; 2; 3] is precisely the same thing as [1, 2, 3]
julia
You need to make new versions of both immutable objects, recursively
constructing the updated struct, then unsafe_store it back to the original
C location
On Thu, Feb 26, 2015 at 2:32 PM J Luis jmfl...@gmail.com wrote:
Yes you warned me that it may sometimes segv, but what else can I do to
get
Not sure, but two possibilities come to mind:
- I'm not sure it works with keyword functions. One way to check would be to
modify base to create an`svds_` function (note the underscore) that takes all
those parameters as regular arguments, and have `svds` call `svds_`. Then
precompile
(I am resending because, this my message to Ondřej did not go to the list)
Hi Ondřej,
The various sympy projects are very interesting, your work porting Rubi
especially.
SJulia is using SymPy for a lot of features (Integrate, Solve, ...) . Here
is some test code
BTW.
Do you know much about the SymPy interface ? (or maybe the authors are
reading this ?)
Francesco has already supplied a lot of information, but I am new to sympy.
Here, I ask for an integer to be converted with _to_mpmath
https://github.com/jlapeyre/SJulia/blob/master/src/sympy.jl#L89
Would that be to get the exact same variates as the serial execution would
create?
2015-02-26 15:04 GMT-05:00 Steve Kay stevekay...@googlemail.com:
Thanks for the comments. - nice to know it's not my usual programming
inadequacies. I like the
for p in workers()
@spawnat p srand(seed + p)
I was just recently trying to use the
wrap-a-pointer-to-an-immutable-in-a-1-element-array trick while wrapping
some library code where some important setter functions were unfortunately
only defined as inline in the headers.
I defined my own setters by assigning to the immutable in the array. The
I think PyCall already has what you need for conversion:
PyObject(big(pi)) will create a an mpf instance of a big float, like big(pi)
convert(BigFloat, PyObject(big(pi))) will return a BigFloat from an mpf
instance.
On Thursday, February 26, 2015 at 6:57:37 AM UTC-5, lapeyre@gmail.com
I made an `IndexedArrays` package with an `IndexedArray` data structure.
This acts like a `Vector` of unique elements, but also maintains the
reverse mapping in a dictionary that is updated in sync with the vector,
allowing for quick lookup of the index of any element. A simple example
is
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