For any infix operator O, O(x,y) is equivalent to x O y. Since in is an infix
operator, it follows the same convention.
On Monday, January 12, 2015 at 11:26:31 AM UTC-5, Peter Brady wrote:
So I take it that no one else has this issue? Maybe I should compile
julia myself and see if the problem goes away.
I've never seen this issue reported. Can you post a simple self-contained
test script that illustrates
On Monday, January 12, 2015 at 8:36:28 AM UTC-5, Andras Niedermayer wrote:
It's still not entirely satisfactory that sorting arrays of tuples is so
much slower in Julia than in Python,
(Note that for sorting an untyped array of tuples, Julia may never have
much if any advantage over
It would be nice to provide some explanation in the README of why you
implemented each method. What are the circumstances in which you would
use each one?
On Monday, January 12, 2015 at 3:40:39 PM UTC-5, Kevin Squire wrote:
If the functions take arguments that are typed as LTISystem, then there
shouldn't be any conflict. That's what multiple dispatch is for!
To expand on this, the key behavior of Julia is that it allows you to add
new methods
On Monday, January 12, 2015 at 2:52:51 PM UTC-5, Douglas Bates wrote:
This is trivial to write myself but I wanted to check that I am not
missing an already-defined function. I need to scan an Int32 array
replacing all instances of typemin(Int32), which is the missing value
sentinel
On Thursday, January 8, 2015 at 5:28:39 PM UTC-5, Jake Bolewski wrote:
Julia is space sensitive, and errors like this can crop up. I don't see
how this is behavior is inconsistent. Use whitespace! :-)
It's inconsistent because 5.≤x and 5.=x are tokenized differently.
See the manual on how to use git from behind a firewall:
http://docs.julialang.org/en/latest/manual/packages/
In particular, you can run
git config --global url.https://.insteadOf git://
to tell git to use https instead of git protocol, in order to work with
your firewall.
On Friday, January 9, 2015 at 4:56:29 PM UTC-5, John Hall wrote:
I've seen both the git manual and the https/git workaround before. Neither
seem to work.
If you do git clone manually from the command line with an https or http
URL, does it work? It would be good to diagnose the specific
In Julia it is usually considered bad style to have the output type of
function depend on the input values --- it is a good idea to get into the
habit of writing type-stable functions whose output types depend only on
their input types, and not on the values of their inputs, because this is
On Tuesday, January 6, 2015 5:15:13 AM UTC-5, Andreas Lobinger wrote:
Hello colleagues,
is there a counterpart for the string literal split to multiple lines like
in python?
d = '09ab\
eff1\
a2a4'
You can always just concatenate:
d = 09ab *
eff1 *
a2a4
In addition to putting your main loops into a function, I would also just
inline the normalized_iterations function rather than passing it as an
itmap parameter, and inline the function f. i.e. specialize your
boundedorbit function to the mandelbrot case. (Anonymous functions like x
- x^2 +
On Tuesday, January 6, 2015 12:37:24 PM UTC-5, Tim Holy wrote:
For running mean, cumsum gives you an easy approach, if you don't mind a
little floating-point error.
Yikes, just noticed that cumsum is significantly less accurate than sum;
basically, cumsum is no better than naive
My understanding is that the distinction between ASCIIString and UTF8String
will be removed in a future Julia release.
On Tuesday, January 13, 2015 at 7:43:07 PM UTC-5, ele...@gmail.com wrote:
Which can present problems if the UTF8String is displayed or otherwise
used where valid UTF8 is required.
It will display as mojibake, but you will still be able to open the file.
There doesn't seem to be much
On Tuesday, January 13, 2015 at 6:52:02 AM UTC-5, Куракин Александр wrote:
Is there some way to use Shogun Toolbox (http://shogun-toolbox.org/) with
Julia?
Since it is a C++ library, you can't call it directly from Julia with
ccall. (The next Julia release will make it much easier to
On Tuesday, January 13, 2015 at 12:04:49 AM UTC-5, Ivar Nesje wrote:
Octave uses Float64 numbers by default, so factorial(20) in octave is
equivalent to factorial(20.0) in Julia.
Although we don't currently define factorial for non-integer values, you
can use the gamma function with
See https://github.com/JuliaLang/julia/pull/9754
In any module, if you define function signif, it will completely replace
Base's signif (for *all* argument types), but only within that module;
other modules will not be affected. Defining things in the REPL is
equivalent to defining them within the module Main.
If, instead, you want to add
On Tuesday, January 13, 2015 at 2:50:34 PM UTC-5, Evan Pu wrote:
what is the convention? I kept getting
`convert` has no method matching convert(::Type{SubString(UTF8String)}},
::ASCIIString)
all the time, every time
What are you doing that triggers this error? I'm guessing that you have
You're right, there are dot versions of .≤, just not other Unicode
operators. As Mauro said, the parser is just tokenizing 5.≤x as 5. ≤ x.
It is annoyingly inconsistent here:
julia parse(5.≤x)
:(5.0 ≤ x)
julia parse(5.=x)
:(5 .= x)
For comparison, the NumPy vander function
https://github.com/numpy/numpy/blob/f4be1039d6fe3e4fdc157a22e8c071ac10651997/numpy/lib/twodim_base.py#L490-L577
does all its work in multiply.accumulate. Here is the outer loop of
multiply.accumulate (written in C):
On Monday, January 12, 2015 at 2:42:59 AM UTC-5, Ivar Nesje wrote:
Note that there might be a security issue, because whoever inputs data to
your program also get the ability to run arbitrary code on the computer. In
a local setting where everyone who input data, also have access to changing
On Sunday, January 11, 2015 at 4:38:29 PM UTC-5, William Macready wrote:
I've been using Julia for about a month now, and I'm really enjoying the
language. My thanks to all who've contributed to it's development!
I'm developing a parser for first-order logic, and wanted to use the logic
On Thursday, February 5, 2015 at 10:41:23 AM UTC-8, Martin Johansson wrote:
If you by Density plot refer to Mathematica's 'DensityPlot' than maybe
simply using contourf could be OK. Unfortunately I don't know much about
the plotting facilities in Julia (read: PyPlot).
You can use pcolor,
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
On Monday, January 5, 2015 9:09:41 AM UTC-5, Kevin Squire wrote:
FWIW, I believe that there was concern that the behavior of open(process)
might cause confusion when it was defined in this way. (A quick search
didn't locate the issue.)
See the discussion at
On Thursday, January 8, 2015 10:45:54 AM UTC-5, Steven G. Johnson wrote:
However, I'm inclined to think that this is ambiguous, and hence there is
a bug here: when you define your method, it should issue a method ambiguity
just as it would in the non-varargs case
Issue filed: https
On Thursday, January 8, 2015 9:59:13 AM UTC-5, Andreas Lobinger wrote:
Actually i do not want to pass by value. I thought composite types are
references by a pointer (to the first element, like in C) and having mytype
as the type of input parameter would pass the pointer to the library
On Thursday, January 8, 2015 6:59:55 AM UTC-5, Nils Gudat wrote:
Bumping the thread - has anyone tried this/is it possible?
Works fine for me, e.g.:
using PyCall, PyPlot
@pyimport seaborn as sns
sns.rugplot(randn(30))
Note that you'll want to use PyPlot as well as PyCall, because PyPlot
Non-varargs methods take precedence over varargs methods in dispatch,
assuming both are applicable and there are no other ambiguities. For
example:
julia f(x...) = 3
f (generic function with 1 method)
julia f(x,y) = 4
f (generic function with 2 methods)
julia f(3,4)
4
julia f(7)
3
On Thursday, January 8, 2015 11:00:58 AM UTC-5, Andreas Lobinger wrote:
Looks interesting. But what do i pass with ccall(:flip, Void, (mytype,),
t)?
That syntax means that you are attempting to pass mytype as a struct by
value, which currently does not work reliably due to ABI issues.
On a separate note, I agree that this should be better documented.
Currently, the manual just says, When a function is applied to a
particular tuple of arguments, the most specific method applicable to those
arguments is applied. The precise partial order really needs to be
defined
On Monday, January 5, 2015 11:31:05 PM UTC-5, Tony Kelman wrote:
Yes, actually. If you're on a 64 bit machine, then the integer literal 0
is an Int64. So int64(0) - 0x12345678 promotes and does the subtraction in
Int64. -0x12345678 wraps around to the unsigned integer 0xedcba988 which is
My preference would be for Julia not to touch the CPU affinity at all:
https://github.com/JuliaLang/julia/pull/9639
On Thursday, January 8, 2015 at 4:15:09 PM UTC-5, Jiahao Chen wrote:
Furthermore Vandermonde is not a good test with larger matrix sizes since
you are basically testing the speed of multiplying things by infinity,
which may not be representative of typical computations as it may incur
On Thursday, January 8, 2015 at 3:29:01 PM UTC-5, Joshua Adelman wrote:
You're reading it correctly. I'm not sure exactly why numpy is performing
better for the larger matrices, but I suspect that numpy's accumulate
function that np.vander uses may be taking advantage of simd, sse or mkl
Currently, there are no dot versions of the unicode operators. This is a
future possibility that I mentioned in:
https://github.com/JuliaLang/julia/pull/6929#issuecomment-44099346
but it is not currently implemented.
On Wednesday, February 18, 2015 at 9:40:48 PM UTC-5, Kuba Roth wrote:
Interstingly Julia's example using Integer in mod operation is slower:
a+=exp(a%2);
elapsed time: 0.049916461 seconds (304116 bytes allocated)
div/rem/mod are currently slower in Julia than C++ because Julia performs
If we're doing a 31 ways to to compute pi, I would suggest that most of
them should be more aimed at fun than trying to compute a huge number of
digits. Like Monte Carlo integration of the area of a unit circle, or
summing a slowly converging series, using quadgk(x - 1/(1+x^2), 0,1)[1]*4,
or
On Monday, March 9, 2015 at 11:24:06 AM UTC-4, Hans W Borchers wrote:
@Steven
Do you think it was no fun to implement the droplet/spigot algorithm? Then
you may be completely wrong.
I'm sure it was fun. The point I meant to make was that fun is not
restricted to efficient algorithms,
On Monday, March 9, 2015 at 2:31:58 PM UTC-4, Jerry Xiong wrote:
When I ran below codes:
using PyCall
@pyimport pylab as plb
cmap1=plb.get_cmap(jet)
pycall(cmap1,PyAny,0.5)
Every thing goes fine, output result
(0.4901960784313725,1.0,0.4775458570524984,1.0)
However, after I loaded
On Monday, March 9, 2015 at 5:18:52 PM UTC-4, Steven G. Johnson wrote:
Yes, I should probably define a pycall method for ColorMap. For now,
you can do pycall(cmap2.o, PyAny, 0.5).
Just fixed it in PyCall (master branch on github).
On Monday, March 9, 2015 at 5:24:22 PM UTC-4, Steven G. Johnson wrote:
On Monday, March 9, 2015 at 5:18:52 PM UTC-4, Steven G. Johnson wrote:
Yes, I should probably define a pycall method for ColorMap. For now,
you can do pycall(cmap2.o, PyAny, 0.5).
Just fixed it in PyCall (master
On Tuesday, March 10, 2015 at 2:40:24 PM UTC-4, Amit Jamadagni wrote:
Thank you very much for the response.
But the behavior of the same in scipy is different i.e., it omits the
elements. Is this not the expected behavior ??
Why would you expect the function to silently ignore some of
For my numerics class at MIT http://math.mit.edu/~stevenj/18.335/, I used
the following notebook to talk about cache effects and matrix
multiplication:
http://nbviewer.ipython.org/url/math.mit.edu/~stevenj/18.335/Matrix-multiplication-experiments.ipynb
It includes some code to benchmark
On Friday, March 6, 2015 at 9:42:34 AM UTC-5, Andrei Berceanu wrote:
ok so now im doing import PyPlot, but have some problems with the latex
axis labels
you could try
using LaTeXStrings
to pull in the L_str macro separately from PyPlot. (I'm not sure if there
is any nice syntax
On Thursday, March 5, 2015 at 4:58:10 PM UTC-5, Sheehan Olver wrote:
Hmm, maybe I’m posing the wrong problem then… I wanted a fast way to
calculate the null space of a sparse matrix, where the basis spanning the
null space is also sparse. And the dimension of the vector space is in the
On Thursday, March 5, 2015 at 12:51:07 PM UTC-5, Iain Dunning wrote:
I don't think anything in JuliaOpt other than NLOpt is going to play
nicely with that non-convex L2 norm constraint.
Actually, I would tend to transform the problem to eliminate the equality
constraint:
min |Lx|_1 /
I seem to recall having similar problems last year too, so it may be an
openblas thing.
As a general rule, with Julia one needs to unlearn the instinct (from
Matlab or Python) that efficiency == clever use of library functions,
which turns all optimization questions into is there a built-in function
for X (and if the answer is no you are out of luck). Loops are fast,
and you
On Thursday, March 12, 2015 at 10:08:47 AM UTC-4, Ján Dolinský wrote:
Hi,
Is this an efficient way to swap two columns of a matrix ?
e.g. 1st column with the 5th
X = rand(10,5)
X[:,1], X[:,5] = X[:,5], X[:,1]
It is not optimal, because it allocates temporary arrays. Instead, you can
On Friday, March 13, 2015 at 12:28:50 PM UTC-4, Stefan Karpinski wrote:
Yes, but the representation is quite inefficient. This would be an
efficient scalar type.
Couldn't you just represent it by Dates.Second (if you want second
resolution) or Dates.Millisecond (if you want millisecond
On Friday, March 13, 2015 at 1:25:14 PM UTC-4, Jake Bolewski wrote:
This is falling back to factor() for generic integers, so the GMP method
does not looked to be wrapped. The generic version will be terribly slow
for bigints. Would be easy to add if you would like to submit a Pull
But when I give in
julia spdiagm(x, 1, length(x), length(x))
ERROR: BoundsError
in sparse at sparse/csparse.jl:50
in spdiagm at sparse/sparsematrix.jl:2133
in spdiagm at sparse/sparsematrix.jl:2141
I get the above error. Any leads on this would be great. Thanks.
You need to use
See also the discussion at:
https://github.com/ipython/ipython/issues/4111
On Friday, March 13, 2015 at 9:06:28 AM UTC-4, David Anthoff wrote:
is there a Time datatype, analogous to the Date type? I ran into a
situation where I need to represent times (like 12:34 pm) that don’t have a
date associated. I understand that in the case of dates that don’t have a
On Friday, March 13, 2015 at 11:44:57 AM UTC-4, Randy Zwitch wrote:
You can also use plain HTML in a markdown cell.
Yes, you can use img ... tags, but then the image data is not included in
the notebook file itself, so unless the image is on a server somewhere that
makes it more annoying
Just a quick follow-up on this thread: for my numerics class at MIT
http://math.mit.edu/~stevenj/18.335/, I put together a little Julia
notebook on the Wilkinson polynomial, along with a little tutorial on how
to define a basic polynomial type (although pointing to Polynomials.jl for
a more
Note that when you update Julia you need to re-run Pkg.build(IJulia) to
tell IPython about the new Julia location.
In general, you need to unlearn the intuition from Matlab/Python that
vectorized/built-in functions are fast, and functions or loops you write
yourself are slow. There's not the same drive to vectorize everything in
Julia because not only are your own loops fast, but writing your own loops
Just use e.g. slider(1:10, value=2)
On Friday, March 27, 2015 at 12:31:45 PM UTC-4, Andrei Berceanu wrote:
Is there any way of setting a default value for a slider object, different
from the middle of the slider interval (which is automatically chosen)?
As I understand it, you are asking whether there is a Julia option (e.g. a
runtime flag) that will cause Julia to throw an error if you try to parse
code where local variables are not explicitly declared, analogous to use
strict in Perl or implicit none in Fortran.There is no such thing in
On Friday, February 27, 2015 at 9:11:10 AM UTC-5, antony schutz wrote:
I have a question about the best way to implement a grid similar to a mesh
grid:
Note that you normally don't need mesh-grid like things, because you can
use broadcasting operations instead. e.g. in order to compute
On Tuesday, March 3, 2015 at 2:52:06 PM UTC-5, Stefan Karpinski wrote:
Then again, using type wrappers for this – bare numbers are Radians while
an immutable Degree wrapper could wrap values in degrees – would eliminate
a large class of common programming errors when working with angles.
On Monday, March 2, 2015 at 7:57:10 PM UTC-5, MA Laforge wrote:
The real question is how much programming overhead is required to use
these types (assuming the compiler does the grunt work reducing the
*performance* overhead)
No, the real question is whether the benefit of using special
On Wednesday, March 4, 2015 at 11:48:28 AM UTC-5, Pooya wrote:
I have a function with two outputs. The second one is computationally
expensive, so I want to avoid the computation unless the user needs it. I
read on another post in the group that the solution in this case is usually
to
Maybe use a non-interactive backend? Does it do what you want if you use
Python?
You can also use fill, e.g.:
fill(convert(Ptr{Uint8},0), 2)
On Thursday, March 5, 2015 at 4:52:54 AM UTC-5, Sheehan Olver wrote:
Are there any packages that can do L1 minimization? I want to do
something like
min ||Lx||_1 subject to ||x||_2=1
You can always transform the L1 objective into 2N affine inequality
constraints, in which case there
On Wednesday, March 4, 2015 at 6:38:28 PM UTC-5, Pooya wrote:
Thanks for your response. I am not sure what you mean by a lower-level
subroutine. Is that a function inside another one? If yes, How does the
scope of variables work for that?
From your description, right now you have:
On Thursday, March 5, 2015 at 1:16:19 AM UTC-5, Dejan Miljkovic wrote:
Thanks,
Using reinterpret julia version is
function exp_approx(val::Float64)
return reinterpret(Float64, int(1512775 * val + 1072632447)32)
end
You probably want int64, not int, so that it doesn't break on
On Wednesday, March 4, 2015 at 2:40:42 PM UTC-5, Josh Langsfeld wrote:
Ok, I got it working by doing pygui(:qt) or pygui(:gtk) before the 'using
PyPlot' call and mentioned in your docs.
I'm not totally clear what 'non-interactive' means for the backend.
Non-interactive backends are ones
The errors in sin and cos can be much larger than 1ulp for sin or cos of large
phase angles ( 360) in degrees, because pi is not exactly representable in fp
while 180 is.
No. f' - ctranspose(f) occurs in the parse stage, I believe.
On Sunday, February 22, 2015 at 3:32:34 AM UTC-5, Viral Shah wrote:
Best to file an issue.
See https://github.com/JuliaLang/julia/issues/3250
On Monday, February 23, 2015 at 6:52:25 AM UTC-5, gdmsl wrote:
thank you for the tips but the second method return an error:
Oh, right, withfig currently only works with IJulia (which has a display
queue and an undisplay function to remove things from the queue).It
won't work with the
On Sunday, February 22, 2015 at 10:06:44 AM UTC-5, DumpsterDoofus wrote:
Nope, I was just manually typing them in, but thanks for pointing that
out. I tried it by calling `import Base.Math.@horner` and then implemented
it like this:
f = @horner(x, a0, a1, a2, a3, a4)
fP = @horner(x, a1,
On Wednesday, February 25, 2015 at 12:37:35 PM UTC-5, Brandon Booth wrote:
I'm trying to read a csv file from a thumb drive using IJulia and keep
getting an error.
My code reads:
params = readcsv(/media/brandon/ED2F-0842/Parameters.csv,',')
You don't pass the delimiter to readcsv, you
On Tuesday, February 24, 2015 at 8:25:30 AM UTC-5, Bill Hart wrote:
So long as your shared library has no other dependencies, you can set
Julia's DL_LOAD_PATH to specify the location of the shared library (I'm not
sure if this is considered best practice or not)
Best practice (in a
Make sure GMT.GMT_RESOURCE is declared as an immutable type if you want
Array{GMT.GMT_RESOURCE} to correspond to the memory layout of an array of C
structs.
Yes, something like the EasyDialogs http://pymotw.com/2/EasyDialogs/
Python package would be great.
On Tuesday, February 24, 2015 at 10:16:25 PM UTC-5, Steven G. Johnson wrote:
Yes, something like the EasyDialogs http://pymotw.com/2/EasyDialogs/
Python package would be great.
(EasyDialogs doesn't work anymore and was never cross-platform, but that
sort of interface seems useful.)
See the debugging IJulia section of the IJulia README
On Thursday, March 26, 2015 at 11:38:34 AM UTC-4, Andrei Berceanu wrote:
I seem to be getting this message, with no other error, quite often when
evaluating my notebook.
What is the recommended way of debugging such a thing? Since no
On Friday, January 23, 2015 at 10:39:42 AM UTC-5, J Luis wrote:
Than the confusion is even bigger (not intentional for sure)
julia parsefloat(a[2])
ERROR: `parsefloat` has no method matching parsefloat(::Char)
julia parseint(a[2])
2
We could certainly add a parsefloat(c::Char) =
Thanks for the clarification regarding the Unix situation.
On Tuesday, January 13, 2015 at 4:31:51 PM UTC-5, Milan Bouchet-Valat wrote:
So the best solution for Julia is to return it as a UTF8String, knowing
that in some cases invalid UTF-8 may appear.
(This is what Julia does now, it
Though we could define such a conversion method with:
convert{T:AbstractString}(::Type{SubString{T}}, s::AbstractString) =
let s′ = T(s); SubString(s′, 1, endof(s′)); end
Evan, what is your application here? What are you trying to do?
On Tuesday, January 13, 2015 at 1:47:12 AM UTC-5, ele...@gmail.com wrote:
But since those annoying operating systems can return filenames encoded in
non-UTF8 it probably will not be safe in 0.4 to just return a UTF8 string.
Whatever encoding the operating system uses, Julia (or actually
On Tuesday, January 13, 2015 at 4:10:54 PM UTC-5, Evan Pu wrote:
Steven,
The error is actually an issue with LightTable's Juno plugin and actually
has nothing to do with Julia.
Can you file an issue at:
https://github.com/one-more-minute/Jewel.jl
explaining how the error arose?
I tend to see NetCDF as a legacy format and would recommend HDF5 anyway...
On Thursday, April 2, 2015 at 1:35:34 PM UTC-4, Diego Tapias wrote:
Ok, thank you!
Sorry for my grammar, I often type very fast and don't check it.
I see your point but it's confusing for me that the same syntax worked a
few days ago. Do you know if this is a new feature of matplotlib?
On Saturday, April 25, 2015 at 11:21:24 AM UTC-4, Ferran Mazzanti wrote:
I'm new to Julia (but not to Python) and can't find he right way to use
PyPlot as I do in Python. In short, I have a program that should display a
plot, wait for the user to close the plot, then show a second plot and
Note that you only need the PyPlot. prefix if you do import PyPlot -- with
using PyPlot, symbols like ioff and plot are imported into your namespace.
As Tim says, you just want similar(a, eltype(b), 5)
On Wednesday, April 22, 2015 at 6:22:49 AM UTC-4, Mauro wrote:
A generated function works:
(I'm starting to be very suspicious of every time someone suggests using a
generated/staged function. It's too easy to turn this into a crutch; it's
PyPlot was updated for the tupocolypse; I don't know if it has broken again
in the last day or two, though, but it should be easy to fix up again.
What is the advantage of this over Matplotlib?
On Tuesday, April 21, 2015 at 5:16:12 AM UTC-4, Stephan Buchert wrote:
In Matlab I can do, for example, with daynum fractional day numbers:
idaynum = floor(daynum);
[umjd, im, iu] = unique(idaynum); % = how do I get the iu in Julia?
This is not implemented yet; see:
Yes, in general you can do anything from PyPlot that you can do from
Matplotlib, because PyPlot is just a thin wrapper around Matplotlib using
PyCall, and PyCall lets you call arbitrary Python code.
The pyplot.style module is not currently exported by PyCall, you can
access it via plt.style:
The DecFP package
https://github.com/stevengj/DecFP.jl
provides 32-bit, 64-bit, and 128-bit binary-encoded decimal floating-point
types following the IEEE 754-2008, implemented as a wrapper around the
(BSD-licensed) Intel Decimal Floating-Point Math Library
See https://github.com/JuliaLang/julia/pull/11043
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