Thanks for all the replies. I considered working with BigFloats and other
data types. However, after reading this article by John Cook
http://www.codeproject.com/Articles/29637/Five-Tips-for-Floating-Point-Programming,
I got the idea that the main problem I'm having is the subtraction when
On Friday, 13 February 2015 04:34:43 UTC, Sheehan Olver wrote:
For completeness, here is the definition I ended up using (probably using
map is bad performance wise but I don’t actually use that yet):
You can use @vectorize_1arg macro for this:
@vectorize_1arg sqrtx2 Number
Hi,
I need to run a script which generates a large number of plots using the
PyPlot module but the output of the script is filled with messages from
PyPlot. How can i suppress this output?
Here is an example:
julia using PyPlot
INFO: Loading help data...
julia pygui(false)
false
julia
I don't know many of the details on type inference, but I do know that
there is a bounded limit to the number of times inference is iteratively
run. I remember seeing the number 4 in this context, too, but I don't know
if it's the same 4.
My naive assumption is that without this bound, Julia
I'm using RHEL 6.5 and running into an issue using the very basic example
for HttpServer. When using the example for HttpServer, I see that it
listens on port 8000.
using HttpServer
http = HttpHandler() do req::Request, res::Response
Response( ismatch(r^/hello/,req.resource) ? string(Hello
I have a Uint32 array, ARGB formatted. How do I convert that back to an
Image so that I can call imwrite? (The alpha component is unimportant, but
it would be nice to save it if the file format supports it)
imagearray = reinterpret(RGB24,imagearray)
image = Image(imagearray)
imagearray =
I'm guessing that you have run into
const MAX_TYPE_DEPTH = 4
in inference.jl. You can try increasing this number and rebuilding the base
library.
As I understand it, the decidability of Julia's type system remains an open
research question.
Thanks,
Jiahao Chen
Staff Research Scientist
MIT
I posted at 5:20PM EST yesterday, so I'm bumping this thread. Any thoughts
on how to fix this or what could be causing this?
On Thursday, February 12, 2015 at 5:20:10 PM UTC-5, José S. wrote:
Hi, everyone. I'm new to Julia, but so far I love what I've seen.
Whenever I try to use Winston, I
Hello colleague,
first of all it's not a bad idea to raise this as issue on Winston.jl
itself: https://github.com/nolta/Winston.jl/issues
and btw this here looks similar:
https://github.com/nolta/Winston.jl/issues/204
afaik getgc methods are usually located in the drawing libraries (like
Thank you for your response, Andreas.
I searched on Google for other threads describing the same issue, but found
none. It's good to know that others have run into this problem and that a
fix is in the works.
I manually made the changes mentioned in the pull request
Thanks for the clarficiation Mauro, although it seems like right now Julia
is somewhere in between the two approaches according to that thread.
I guess I'll just have to write my own version of findn which assumes that
zeros have been purged, and if they haven't it's not that big of a deal in
my
On Fri, Feb 13, 2015 at 11:58 AM, Jiahao Chen jia...@mit.edu wrote:
As I understand it, the decidability of Julia's type system remains an
open research question.
Type checking Julia is definitely undecidable. Subtyping in Julia is
probably decidable but it hasn't been proved to be.
Your last one should have worked, and does on master. I guess I need to tag a
new version.
This is the most direct, though:
B = reinterpret(BGRA{Ufixed8}, A) # assuming little-endian
imwrite(B, file.png)
It does seem Color could use some more functions for converting to and from
ARGB32.
On Thursday, February 12, 2015 at 10:03:04 PM UTC-6, Zouhair Mahboubi wrote:
I'm trying to find the column indices of non-zero elements of a given row
in a sparse matrix A
I figured using findn would be a fast way to do that, but I was curious to
see how the implementation was done since
Thanks everyone for the replies.
Jiahao: Thanks especially for the pointer to MAX_TYPE_DEPTH. This is
exactly what I hit, and now I'm trying to learn what its consequences are.
I appreciate the need for constraints to keep type inference efficient, but
I'm not sure why what I am doing is
On Friday, February 13, 2015 at 4:58:44 AM UTC-5, gdmsl wrote:
julia plot(rand(10),rand(10));
Figure(PyObject matplotlib.figure.Figure object at 0x7f7979d24dd8)
Figure(PyObject matplotlib.figure.Figure object at 0x7f7979d24dd8)
I really need to suppress output like Figure(PyObject
That works. I don't know why, but it is what I needed. Thanks.
On Friday, February 13, 2015 01:38:41 PM Christopher Lee wrote:
That works. I don't know why, but it is what I needed. Thanks.
BGRA is stored in the same byte-order as UInt32.
But now if you do Pkg.update() you should be able to say
imwrite(reinterpret(ARGB32,imagearray), filename)
Best,
So is there some resolution for this question? I also ran into the problem
of not being able to call a C function inside a finalizer
(cudaEventDestroy), so I have exactly the same question.
On Monday, 9 February 2015 11:14:40 UTC-5, Jameson wrote:
I believe there is some sort of
Hi,
I just found this very interesting thing for debugging.
For Julia codes that 'talk' to C DLLs we can step in the the DLLs using
Visual Studio by simply doing:
- In VS go to TOOLS - Attach to Process... and select the julia.exe
process
- Set the breakpoints in the C code and launch your
bump
So what is the currently recommended Travis CI script that generates
coverage data?
A bunch of packages have been switched over to the new scripts with
language: julia and now have 0 coverage. See, for example:
https://github.com/JuliaLang/Color.jl/issues/79
On Friday, December 12, 2014
You're really going to like when we switch to a newer version of llvm then.
LLVM is able to expose much of that same native info to the debugger for
the code that it JITs, so you may soon be able to use that same debugger to
inspect and walk through Julia code. (there's also a minimal amount of
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