You could easily add these two lines of function definitions to your code.
sind(x) = sin(degrees2radians(x))
cosd(x) = cos(degrees2radians(x))
and your haversine function stands as is, not littered with conversions.
On Tuesday, February 4, 2014 6:55:13 PM UTC+1, Jacob Quinn wrote:
As
Hans W Borchers: Your definition is not equivalent.
julia sin(pi)
1.2246467991473532e-16
julia sind(180)
0.0
julia sinpi(1)
0
julia sin(big(pi))
1.096917440979352076742130626395698021050758236508687951179005716992142688513354e-77
with 256 bits of precision
The answer for sin(pi) is
I think Github will set up redirects if you use the move functionality.
On Wednesday, February 5, 2014 2:54:36 AM UTC+1, John Myles White wrote:
Hi all,
Over the coming weekend, I am going to move Clustering.jl to JuliaStats. I
hope the move will go smoothly, but am always wary about
If you want elementwise division you have to use the ./ operator. Then each
element gets divided by the corresponding element in the other vector.
On Wednesday, February 5, 2014 8:16:42 AM UTC+1, Andreas Noack Jensen wrote:
I different framing of Kevin's answer could be that it solves your
As I understand it, the original reason for the degree functions was for
matlab compatibility, but they were later modified (and pi-multiple
functions sinpi/cospi introduced) so as to be more accurate outside the the
interval [-pi/2,pi/2], as Ivar points out. Note that we haven't improved on
It would be great to recreate knitr-style functionality purely with
ipython: i.e. feed in a markdown file, and the result is converted to a
notebook with the flagged code blocks automatically run.
On Tuesday, 4 February 2014 22:44:14 UTC, Douglas Bates wrote:
On Tuesday, February 4, 2014
On a related note, emacs users can enjoy a very nice literate
programming system that supports Julia using org-mode and ess. See
https://github.com/gjkerns/ob-julia/blob/master/ob-julia-doc.org
Best,
Ista
On Wed, Feb 5, 2014 at 5:57 AM, Simon Byrne simonby...@gmail.com wrote:
It would be great
Oh, you beat me to it. I was just about to say that using a Degree type and
dispatching on it would be a lot more Julian. In fact, I had this great
idea on how to use the degree sign to construct degrees:
module DegreeModule
export Degree, DegreeSign, °
immutable Degree{T:Number} :Number
I doesn't run the flagged code blocks but this
(https://github.com/jverzani/WeavePynb.jl/blob/master/src/WeavePynb.jl)
steals parts of Judo's (nee Gadfly's) weave function to create ipynb files
from markdown. Running of code blocks could be done, but it seems easiest
for my use to just tell
Since updating DataFrames and DataArrays recently, operators and basic
functions are not working on DataFrames anymore. Is this a new design
decision, or only temporary due to restructuring the code base?
julia Pkg.status()
- DataFrames0.5.1
- DataArrays
Issue #484 https://github.com/JuliaStats/DataFrames.jl/pull/484 seems to
indicate it is on purpose.
On Wednesday, February 5, 2014 3:00:39 PM UTC+2, Christian Groll wrote:
Since updating DataFrames and DataArrays recently, operators and basic
functions are not working on DataFrames anymore.
Ah, very nice, that looks really useful. As far as running the notebook,
the ipython wiki has some useful scripts, including one for running a
notebook from the command line:
https://github.com/ipython/ipython/wiki/Cookbook%3a-Notebook-utilities
I also noticed that they have an issue open for
This is definitely on purpose.
Quick summary:
* DataMatrix is a mathematical object
* DataFrame is a database
We're going to encourage use of colwise for some of these use cases. But for
many of them we're going to encourage the use of DataMatrix instead.
-- John
On Feb 5, 2014, at 5:07 AM,
1. Done
2. I am not sure what you mean by running the paralel computation over D
and E directly, then scaling it down afterwards but I do the scaling
element-wise now instead of at the end
3. I will consider it in the future
4. Done although it won't allow me to name the output (A,B,C). It gives
I rather like the Degree type idea. Radians are unitless so they don't need
a type – i.e. PiMultiple is just the default for all trig functions. You
could, however, also have things angular units like Turns.
On Wed, Feb 5, 2014 at 7:48 AM, Johan Sigfrids johan.sigfr...@gmail.comwrote:
Oh, you
I think the Degree types will be too hard to discover, so it will not be
used enough that it is worth the extra work with all functions you might
want to call on that number. This belongs more in a unit package like
https://github.com/loladiro/SIUnits.jl , where some missing functions might
be
On Tuesday, February 4, 2014 8:21:48 PM UTC-5, Steven Siew wrote:
I think that it should be made absolutely clear to newbies (to Julia) that
plotting is NOT working by default.
Right on the download page (http://julialang.org/downloads/), there is a
section Graphics in Julia that says
May be an implicit conclusion: Has similarities with Matlab then it has to
work all out of the box ;-)
Am Mittwoch, 5. Februar 2014 17:26:39 UTC+1 schrieb Steven G. Johnson:
On Tuesday, February 4, 2014 8:21:48 PM UTC-5, Steven Siew wrote:
I think that it should be made absolutely clear to
I'm developing an iterative optimization algorithm in Julia along the lines
of other contributions to the Iterative Solvers
projecthttps://github.com/JuliaLang/IterativeSolvers.jlor Krylov
Subspace
https://github.com/JuliaLang/IterativeSolvers.jl/blob/master/src/krylov.jlmodule
whose
only
I'm working on integrating Julia into our platform which is a long running
service, there are a few concerns around keeping the Julia environment
running for an extended period. Or if it might be possible to destroy the
environment after it is initialized. We are investigating whether we
No there don't seem to be a cleanup method. And multiple julia environments
are currently not possible.
But from my perspective it would be great to work towards putting all the
globals into a struct so that multiple Julia threads per process become
feasible.
Am Mittwoch, 5. Februar 2014
You can run julia under gdb and set a breakpoint as needed in the C code
(so, immediately prior to the error condition). eg:
bash$ gdb julia
...
(gdb) break xyz.c:123
(gdb) run
...
julia include(myfile)
...
breakpoint at ...
(gdb)
(Continuing will return to the Julia prompt)
On Wed,
Memory access is typically a significant bottleneck in sparse mat-vec, so
unfortunately I'm skeptical that one could achieve good performance using
Julia's current distributed memory approach on a multicore machine. This
really calls for something like OpenMP.
On Wednesday, February 5, 2014
Hi,
I really like the looks of Julia, but don't want to use it *yet*.
IMO, what Julia is really lacking is a (runtime choice of) industry grade
garbage collector implementation(s).
The reason I care is that I want to implement various immutable data
structures in Julia.
But such structures
Does the network i/o package support UDP as it only seems to have TCP
functions.
Thanks
Bob
Hi Robbert,
I'm not sure if this goes in the direction you need, but check out:
https://github.com/JuliaLang/julia/pull/5227
Have you also seen https://github.com/zachallaun/FunctionalCollections.jl?
Cheers,
Kevin
On Wed, Feb 5, 2014 at 11:44 AM, Robbert van Dalen
We have the capabilities, but it's not hooked up yet, mostly because I
don't know enough about UDP to write a meaningful test case and I hate
having broken functionality in Base.
On Wed, Feb 5, 2014 at 2:57 PM, Bob Cowdery bobcowd...@gmail.com wrote:
Does the network i/o package support UDP as
Hi Randy,
The following works for me:
where $enc is the encoded creds as you had above.
post(URI(https://api.twitter.com/oauth2/token;),grant_type=client_credentials,{Authorization
= Basic $enc,Content-Type =
application/x-www-form-urlencoded;charset=UTF-8})
Note the URI() before the url. We
Hi folks,
We are pleased to announce the fourth Bay Area Julia Users
meetuphttp://www.meetup.com/Bay-Area-Julia-Users/events/157317652/!
The gathering will take place at 6:30 PM on 19 February in SoMa. We will
have two presenters:
Iain Dunning will join us via teleconference to talk about
#2 should work, the problem right now is that we only have support for json
encoded data, and so the post method is overriding Content-Type
(https://github.com/loladiro/Requests.jl/blob/master/src/Requests.jl#L269).
I've just filed https://github.com/loladiro/Requests.jl/issues/15 to track
On
Miles, you're right that writing sparse matrix vector products in native
Julia probably won't be the best idea given Julia's model of parallelism.
That's why I'm interested in calling an outside library like PETSc.
I see it's possible to link Julia with MKL. I haven't tried this yet, but
if I do,
But speaking of writing parallel matrix vector products in native
Julia, this might be a great use case for shared arrays (although
right now I think only dense shared arrays exist). Amit, can you
comment on this?
On Wed, Feb 5, 2014 at 1:41 PM, Madeleine Udell
madeleine.ud...@gmail.com wrote:
Thanks for confirming Bassem, your code worked on my machine. It does seem
awkward that it requires the URI() before the url, especially given that
some of the examples on the Github page work without using that.
On Wednesday, February 5, 2014 4:11:11 PM UTC-5, Bassem Youssef wrote:
Hi Randy,
A*b will not call MKL when A is sparse. There has been some writing about
making a MKL package that overwrites A_mul_B(Matrix,Vector) with the MKL
versions and I actually wrote wrappers for the sparse MKL subroutines in
the fall for the same reason.
2014-02-05 Madeleine Udell
But speaking of writing parallel matrix vector products in native
Julia, this might be a great use case for shared arrays (although
right now I think only dense shared arrays exist). Amit, can you
comment on this?
Actually you could use a shared array for both the sparse matrix and output
I'm trying to figure out how to compute/recover the standard error of the
estimates for a simple linear regression using MLE and simulated. Here is
the code I'm using to generate data, compute the likelihood function, and
optimize the function.
using Optim
using Distributions
xmat =
Just to be clear, this could be implemented in about an hour, probably. We
should just do it. Keno, what stuff do I need to hook up to make UDP work?
On Wed, Feb 5, 2014 at 5:04 PM, Bob Cowdery bobcowd...@gmail.com wrote:
OK, thanks. I do need UDP for my application so will check back in a
In the Calculus.jl package, there is a hessian function where you can stick
in you likelihood and the estimate.
2014-02-05 Bradley Fay bradley@gmail.com:
I'm trying to figure out how to compute/recover the standard error of the
estimates for a simple linear regression using MLE and
Basically just the uv_udp_t stuff. Have a look at the way TcpSocket is
implemented. It would be very similar. I'd be happy to review a pull
request. I'm just in a little bit of a crunch right now, so I probably
don't have the time to write it up and test it myself. There's examples of
the C udp
Julia is returning an ARPACKException(-3) with the following line:
(pVals,pVecs)=eigs(covariance;nev=sigComponents,sigma=1,which=LM,tol=0.0
,ritzvec=true,maxiter=1000)
running on a 64-bit windows machine, covariance is positive definite. I'm
not getting any useful debugging information, so I
That's true. I find the mechanism a little opaque, so it makes it
uncomfortable. But hopefully it will all work out.
-- John
On Feb 5, 2014, at 2:04 AM, Ivar Nesje iva...@gmail.com wrote:
I think Github will set up redirects if you use the move functionality.
On Wednesday, February 5,
Does this seem to be a reasonable approach? Are there other mechanisms
I should consider instead?
have you thought about JSON as a bridge for passing data between
processes? Stefan mentioned this to me, and there is clearly precedent
wih ipython.
Stephen
What version of julia are you on? Please send the output of
`versioninfo()`.
On Wed, Feb 5, 2014 at 2:39 PM, Micah McClimans also.also@gmail.comwrote:
Julia is returning an ARPACKException(-3) with the following line:
Hey Alex,
Great catch on #5 -- that was dumb on my part :)
Re #4: turns out it's a known bug involving parallel code specifically.
I've upadated https://github.com/JuliaLang/julia/issues/2669 to let them
know it's no longer a theoretic discussion.
Re: breaking the matrix in to pieces --
This is a superrecent change merged yesterday, so you'll need an even
fresher build.
Ref: https://github.com/JuliaLang/julia/pull/5538
On Wednesday, February 5, 2014 6:45:02 PM UTC-6, Madeleine Udell wrote:
I see documentation for the nfilled function, but I don't seem to be able
to access
If you for some reason can't upgrade now, you can see the 0.2 docs to find out
how it was until yesterday. Hopefully you will then get depreciation warnings
when you actually upgrade.
If you for some reason can't upgrade now, you can see the 0.2 docs to find out
how it was until yesterday. Hopefully you will then get depreciation warnings
when you actually upgrade.
Hi,
I'm using Julia compiled from git in Arch linux, and in the last weeks I've
been getting almost random segmentation faults, mainly, but not only, when
running Pkg.update().
I've followed the procedures from
https://gist.github.com/staticfloat/6188418 (except for the Github issue
opening)
Yes, you should have better luck with that. MCJIT is enabled when using
LLVM 3.4, and there are some bugs.
Please file an issue and link the gists, so this doesn't get lost. (if you
have any other reproducible test cases, those might be helpful too)
On Wed, Feb 5, 2014 at 10:01 PM, Cristóvão
Julia shows great promise for biology and bioinformatics-related
programming. It really blows the competition (Python, R) out of the water
in terms of language design, but a lot of work is needed to catch up to the
huge library advantage that's available in these languages.
I've set up a
Hi,
Are there equivalent functions to Matlab's nanmean and nanstd, i.e.
functions for computing mean and standard deviation while ignoring NaN's?
It's simple to put something together, of course, e.g.
function nanmean(x)
mean(~isnan(x))
end
but it would nice to have as part of Base, or
I had about an hour on a plane:
https://github.com/JuliaLang/julia/pull/5697
On Wed, Feb 5, 2014 at 5:37 PM, Keno Fischer
kfisc...@college.harvard.eduwrote:
Basically just the uv_udp_t stuff. Have a look at the way TcpSocket is
implemented. It would be very similar. I'd be happy to review a
The below code generates an expression consisting of multiple using
statements
pid = addprocs(1)[1]
e1 = Expr(:toplevel)
for (k,v) in Base.package_list
p = basename(k)
if endswith(p, .jl)
p = p[1:end-3]
end
push!(e1.args, Expr(:using,
Please have a look at the manual. It is explained
herehttp://docs.julialang.org/en/latest/manual/types/#parametric-composite-types
2014-02-06 Fil Mackay f...@vertigotechnology.com:
Hi all, I expected this to be true:
*Dict{ASCIIString,Int64}:Dict{String,Int64}# false*
Should not there be
The ARPACK error means
-3: NCV-NEV = 2 and less than or equal to N
where NCV is the number of Arnoldi vectors. The default value is NCV=20,
however, this is adjusted according to
(n = 6) (nev = max(n-1, nev))
ncv = blas_int(min(max(2*nev+2, ncv), n))
Which values do you use for N (size
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