Think of a special function not (yet) implemented in Julia, like Lambert W,
or Struve, or ... So you define it yourself, e.g. by applying
Newton-Raphson. How would you symbolically differentiate that? Or your
application forces you to define a procedure with if-else constructs and
loops, how
I also agree with your approach, John. Based on your criteria, here
are some other things to consider for the chopping block.
- expression-based indexing
- NamedArray (you already have an issue on this)
- with, within, based_on and variants
- @transform, @DataFrame
- select, filter
- DataStream
Sorry, but I don't see it. Using Calculus it says
julia finite_difference_hessian(sin, 1.0)
ERROR: finite_difference_hessian not defined
and calling hessian alone returns the old, inaccurate result:
julia hessian(sin, 1.0)
-0.841471649579559
Looking at the definition of
When I came here, I thought Julia was meant for technical computing and
not so much for pure Math exercises. In scientific computing, calculating
numerical derivatives and gradients is essential for many applications.
Julia is not meant to be unusable for pure Math exercises. It is
Ivar, if I sounded impolite, I feel sorry. And I don't want to 'criticize'
the Calculus package, I am just trying to understand the status of the
package and where it is going. I'd love to use Julia as a technical
computing platform in the future, but for this I would require a strong
calculus
Looks like you're having a DNS issue. I'm not sure how to fix it, however.
One thing you could try is doing
git config --global url.https://github.com/.insteadOf git://github.com/
at a terminal and then see if that fixes things. That will modify your
global git config file, so to go back to a
I've just installed Julia Studio last night to try and do some work on
cellular automata.
I've been familiarising myself with the language, and so far it's worked
fine. But when I try to use the if command, I get the following error:
ERROR: no method getindex(Array{Any,1},ASCIIString) in
I don't think the issue is with if – it's with I/O. Can you do
println(hello) by itself?
On Tue, Jan 21, 2014 at 9:56 AM, Ben Simmons benno.simm...@gmail.comwrote:
I've just installed Julia Studio last night to try and do some work on
cellular automata.
I've been familiarising myself with
git config --global --unset url.https://github.com/.insteadOf
(or)
git config --global --edit
On Tuesday, January 21, 2014 8:44:18 AM UTC-6, Stefan Karpinski wrote:
Looks like you're having a DNS issue. I'm not sure how to fix it, however.
One thing you could try is doing
git config
On Tuesday, January 21, 2014 05:32:13 AM Hans W Borchers wrote:
When you say, Calculus is not developed much at the moment,
maybe it's too early for me to change.
Writing finite-differencing algorithms isn't that hard. That should not be a
make-or-break issue for your decision about whether to
Just to chime in: the biggest problem with the Calculus isn’t the absence of
usable functionality, it’s that the published interface isn’t a very good one
and the more reliable interface, including things like
finite_difference_hessian, isn’t exported.
To fix this, we need someone to come in
I agree with everything on this list, including my always neglected DataStreams
project.
I think it would be nice to get rid of expression-based indexing + select and
focus on getting something like LINQ working. For another interesting
perspective, check out the nearly created query function
Julia's singleton types are abstract types whose only instance is a single
type object. This is useful for writing methods that dispatch on type
values rather than on the type of an argument. They are abstract types –
they don't have fields and they don't hold data.
If you want an object to store
Sorry, I cannot reproduce this behavior.
I could imagine you having problems the other way round, entering
multi-line input in the console. We made fixes for several problems there
that will be released soon.
What platform are you on?
Kees
On Tuesday, January 21, 2014 6:56:34 AM UTC-8, Ben
Ok, thanks.
I got the idea.
On Tuesday, January 21, 2014 8:31:19 PM UTC+4, Stefan Karpinski wrote:
Julia's singleton types are abstract types whose only instance is a single
type object. This is useful for writing methods that dispatch on type
values rather than on the type of an argument.
Thanks for these encouraging words. I have already written an R package
with more than a hundred numerical functions (incl. several numerical
derivatives), and I would be willing to help build up a numerical package
in Julia. But of course, someone from the Julia community will be needed to
I use within! pretty frequently. What should I be using instead if that is
on the chopping block?
--Blake
On Tuesday, January 21, 2014 7:42:39 AM UTC-5, tshort wrote:
I also agree with your approach, John. Based on your criteria, here
are some other things to consider for the chopping
Hi Jeff,
Here is a strategy inspired by the hashing function in Python and
Julia. I hope it covers all bases in integers, float, rationals, complex
and arbitrary precision. Please go through it and provide your feedback.
Please note that the code is supposed to be pseudocode and it is not
Can you do something like df[“ColA”] = f(df)?
— John
On Jan 21, 2014, at 8:48 AM, Blake Johnson blakejohnso...@gmail.com wrote:
I use within! pretty frequently. What should I be using instead if that is on
the chopping block?
--Blake
On Tuesday, January 21, 2014 7:42:39 AM UTC-5,
Le mardi 21 janvier 2014 à 00:13 -0500, Jeff Bezanson a écrit :
The main reason is that there are many types of numbers, with more
added all the time. And for purposes of hash tables, it is difficult
to ensure that all numerically-equal numbers hash the same. So we had
isequal(), which is
Thanks for the heads up. I will use the master then. I am still interested
in implementing the hashing strategy for numbers. So any feedback would be
great.
Regards,
Sharmi
On Tue, Jan 21, 2014 at 10:53 PM, Milan Bouchet-Valat nalimi...@club.frwrote:
Le mardi 21 janvier 2014 à 00:13 -0500,
The filename /Applications/JuliaStudio.app/Contents/Resources/juliet/src/
modules/network/network.jl suggests OSX.
kl. 17:31:49 UTC+1 tirsdag 21. januar 2014 skrev Kees van Prooijen følgende:
Sorry, I cannot reproduce this behavior.
I could imagine you having problems the other way round,
This is very similar to how we used to do hashing. It would be fine if there
were a fixed collection of numeric types in Julia, but if course that's not the
case and user-defined types need to be able to participate in the hashing
behavior, which rapidly spirals out of control. That's what
I'm getting a little frustrated with these SVG issues. There is also the
problem that, for plots with zillions of data points, SVG display is
frighteningly slow. I'm thinking of just turning off SVG output in PyPlot,
by default, with a runtime option to re-enable it.
We can't repro this on OSX either.
Did you try Stefan's suggestion, enter even simpler one-liners in the
editor.
On Tuesday, January 21, 2014 6:56:34 AM UTC-8, Ben Simmons wrote:
I've just installed Julia Studio last night to try and do some work on
cellular automata.
I've been
I wrote a cluster manager for launching jobs on
HTCondorhttp://github.com/dbindel/ClusterManagers.jla little while back, and
was having good luck with it, but now I seem to be
having some trouble. The basic logic is that Julia starts a TCP server and
launches jobs on the cluster that then
I think the greedy solution is both behaviors? =D
Is it possible to give the option to the user? Maybe a keyword argument
for each variable or some other notation? Example
a::Int32
b::_Int32_
so a b are both Int32, but one allows promotion, the other doesn't? (or
some other
If you’re willing to wait, I’m happy to return to the Calculus package in the
spring. I’m focusing on DataFrames/DataArrays (and some database stuff that’s
closely related) until then.
— John
On Jan 21, 2014, at 8:42 AM, Hans W Borchers hwborch...@gmail.com wrote:
Thanks for these
Thanks, good point,
Summing up, this idiom is well suited for keeping constants, say
module MathConstants
export pi, e, speed_of_light
const pi = 3.14159265897
e = 2.718281828
speed_of_light = 3e9
...
end
after adding
using MathConstants
it is possible to use pi without prefix
I'm trying to understand the most Julian way to perform a particular
parallel programming task. Suppose I need function foo from module.jl to be
available everywhere. Let's call the following code map_foo.jl:
@everywhere include(module.jl)
@everywhere using MyModule
pmap(foo,1:100)
That works
This ought to work. The warning is interesting, since the
DataStructures package does (for me at least) define a DataStructures
module. Is it possible DataStructures is not fully installed, missing
files or something like that?
On Wed, Jan 22, 2014 at 1:01 AM, Madeleine Udell
amitm:/tmp$ julia -p 2 -e @everywhere include(\module.jl\)
Warning: requiring DataStructures did not define a corresponding module.
Warning: requiring DataStructures did not define a corresponding module.
amitm:/tmp$ julia -p 2 -e require(\module.jl\)
Only the include is throwing up the warning,
Just remember to declare all the variables in the module as const (not just the
first :D )
# Say I have a list of tasks, eg tasks i=1:n
# For each task I want to call a function foo
# that depends on that task and some fixed data
# I have many types of fixed data: eg, arrays, dictionaries, integers, etc
# Imagine the data comes from eg loading a file based on user input,
# so we can't
I have not gone through your post in detail, but would like to point out
that SharedArray can only be used for bitstypes.
On Wed, Jan 22, 2014 at 12:23 PM, Madeleine Udell madeleine.ud...@gmail.com
wrote:
# Say I have a list of tasks, eg tasks i=1:n
# For each task I want to call a function
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