[julia-users] Julia package style / learning
Hey all, I decided to start learning Julia over the weekend and am having fun so far. I implemented the wikipedia single layer perceptron algorithm as well as kendall's tau to see what it would be like to develop a medium sized package in the language. Link to the repo is below (the title just popped into my head there's no amazing product or grand plan meant by the name.) https://github.com/rgehring/SimpleNets As a student of the language I'd love to hear anyone's thoughts on any style issues or mistakes they see, I'm sure there are plenty. Here are some things I think I did wrong right off the top of my head... - Submodule importing. In src/util/association_measures.jl I wanted to just expose KendallsTau.kendallstau as AssociationMeasures.kendallstau and I think I should have used import rather than include / using ? - Test inclusion strategy: I thought it would make sense to have a unit test file for every src file and to import the src file at the top of each test, but this makes the tests brittle to directory changes, is it a better idea to include all the files in test_runner.jl? - Excessively specific typing and casting to ints and floats. - Arrays of Arrays - should I have used matrices or the native multidimensional array structure? Here are some things that I think might be good: - Tried to keep a reasonable degree of abstraction on all the files, although I may have been too heavy on the use of submodules. - Test coverage + a (very basic) actual statistical validation script for the algorithms. - Tried to be explicit about public API's to the submodules. I may have carried this too far with src/util/association_measures.jl which is basically an interface module designed to only expose the public API's of each included submodule (presently only KendallsTau). I'm potentially interested in contributing to the codebase as a way to keep learning, does anyone have any small, bite-sized github issues they'd be interested in help with or seeing a pull request for?
Re: [julia-users] Yet another licensing question: Building a Julia version of an R package
Thanks John! Another reason why I brought up the last question is the fear that following an R-style implementation will produce a Julia package that is riddled with sub-optimal legacy code. But I guess Julia is not mature enough that one could make such conclusions. On Sunday, March 23, 2014 5:59:58 PM UTC-7, John Myles White wrote: Yes, including the same GPL-3 license is sufficient if you’ve derived your work from a GPL-3 project. You may also need to include the original headers of the files if they contain attribution information that you are required to preserve. I don’t think there’s anything dishonest about creating a GPL-3 package. If you would like to release something under a permissive license, you’ll have to implement your code from scratch without ever reading any of the code from a GPL or closed-source implementation. What’s most beneficial depends on context. Many businesses prohibit GPL software, so many people in the Julia (and Python) communities intentionally produce MIT or BSD software. But Julia benefits a lot from having GPL packages when there’s no reasonable alternative. — John On Mar 23, 2014, at 1:17 PM, Ted Fujimoto tftu...@gmail.com javascript: wrote: Hi all, I'm trying to familiarize myself with Julia by seeing how it compares to other languages. I would also like to open-source my code if it seems useful to others. Unfortunately, licenses have made this process complicated. A tangible example: I am trying to implement a Julia version of the R package pcalg ( http://cran.r-project.org/web/packages/pcalg/index.html). Like most R packages, it is protected under the GPL-3http://cran.r-project.org/web/licenses/GPL-3 license. Also, the license states that it would consider my implementation a modification of the R package. Say I feel that my project is ready to be open-sourced and put it in a github repository. Is it enough to follow the RmathDist.jl https://github.com/JuliaStats/RmathDist.jl lead and do the following?: 1. Include the same license in the repository. 2. Cite the R package I modified. A more long term question: I'm guessing a better (and more honest) alternative to the above would be to implement the relevant algorithms by looking at the pseudocode and applying it in a way that is friendlier to future improvements using idiomatic Julia (if it exists yet). After that, open-source it under the MIT license. Would this be a more beneficial approach than the Julia version of an R package approach?
Re: [julia-users] Yet another licensing question: Building a Julia version of an R package
Thanks Jake! I'll also ask if they are willing to participate in the Julia community by implementing a Julia version too! :) On Sunday, March 23, 2014 6:14:33 PM UTC-7, Jake Bolewski wrote: Another strategy is to contact the authors directly and ask them if they would consider relicensing their work. Many people do not really consider the implications of choosing one license over another and just go with a default. On Sunday, March 23, 2014 8:59:58 PM UTC-4, John Myles White wrote: Yes, including the same GPL-3 license is sufficient if you’ve derived your work from a GPL-3 project. You may also need to include the original headers of the files if they contain attribution information that you are required to preserve. I don’t think there’s anything dishonest about creating a GPL-3 package. If you would like to release something under a permissive license, you’ll have to implement your code from scratch without ever reading any of the code from a GPL or closed-source implementation. What’s most beneficial depends on context. Many businesses prohibit GPL software, so many people in the Julia (and Python) communities intentionally produce MIT or BSD software. But Julia benefits a lot from having GPL packages when there’s no reasonable alternative. — John On Mar 23, 2014, at 1:17 PM, Ted Fujimoto tftu...@gmail.com wrote: Hi all, I'm trying to familiarize myself with Julia by seeing how it compares to other languages. I would also like to open-source my code if it seems useful to others. Unfortunately, licenses have made this process complicated. A tangible example: I am trying to implement a Julia version of the R package pcalg ( http://cran.r-project.org/web/packages/pcalg/index.html). Like most R packages, it is protected under the GPL-3http://cran.r-project.org/web/licenses/GPL-3 license. Also, the license states that it would consider my implementation a modification of the R package. Say I feel that my project is ready to be open-sourced and put it in a github repository. Is it enough to follow the RmathDist.jl https://github.com/JuliaStats/RmathDist.jl lead and do the following?: 1. Include the same license in the repository. 2. Cite the R package I modified. A more long term question: I'm guessing a better (and more honest) alternative to the above would be to implement the relevant algorithms by looking at the pseudocode and applying it in a way that is friendlier to future improvements using idiomatic Julia (if it exists yet). After that, open-source it under the MIT license. Would this be a more beneficial approach than the Julia version of an R package approach?
[julia-users] Re: Calculus2: A new proposed interface for Calculus
I like the unified interface for differentiation. My only qualm is with flattening out the hierarchy of packages by including DualNumbers. There was some discussion on this here: https://github.com/johnmyleswhite/Calculus.jl/pull/44 To start out, what is the intended scope of Calculus.jl? Once you start getting into including automatic differentiation it opens up a whole can of worms. For example, why swallow up DualNumbers and not PowerSeries? What about reverse mode for gradients and Hessians? There are too many different approaches, and I don't think they all belong under one package. We're using DualNumbers now because it's stable and mostly just works, but we should be leaving room for future developments. Proposal: 1. Low-level package (SymbolicDerivatives.jl?) that exports a table of symbolic derivatives that can be shared among different implementations. gradexpr and hessexpr can go here too. 2. Differentiation packages: DualNumbers, PowerSeries, ReverseDiffOverload, ReverseDiffSparse, ReverseDiffSource, etc. 3. Unified interface like the one implemented in Calculus2 with grad/hess. (Call this Derivatives.jl?) On Sunday, March 23, 2014 1:28:03 PM UTC-4, John Myles White wrote: I recently had a project where I made heavy use of the Calculus package and found that the interface has really fallen out of sync with the functionality that’s available. I also found myself wanting to have easier access to forward-mode automatic differentation. So I wrote up a variant of the Calculus package, which I’m calling Calculus2, to provide a demonstration of a new interface that I’d like to propose for the Calculus package. You can try the new interface here: https://github.com/johnmyleswhite/Calculus2.jl This package takes the old Calculus code and cleans it up, but also fully incorporates the DualNumbers package, so that you can switch between many different styles of differentiation using two keyword arguments: using Calculus2 grad(sin, 1.0, method = :finite) grad(sin, 1.0, method = :finite, direction = :complex) grad(sin, 1.0, method = :ad) hess(sin, 1.0, method = :finite) I’d be really interested to see if people think this interface is worth pursuing. I’m hopeful that this interface or something similar can help to surface all of the useful functionality that’s been hidden inside of the Calculus package. — John
[julia-users] Re: Build a constructor with fewer inputs than values
Is this question not clear or just uninteresting?
Re: [julia-users] Re: Build a constructor with fewer inputs than values
On Monday, March 24, 2014 03:02:37 AM RecentConvert wrote:
Is this question not clear or just uninteresting?
You're not showing how you're actually calling the constructor. If I
copy/paste your type definition, and then say Status([1:12]), it works just
fine
for me. What version of Julia are you running? I'm on master from about a week
ago.
A few comments:
- Your arrays have ambiguous dimensionality, so this will be slow. Presumably
it would be better to declare the fields as Valve1::Vector{Bool}. Or if you
need multiple dimensionalities, put the dimensionality N as a parameter of the
type, Status{N}, and declare them as Array{Bool, N}.
- I don't see the reason for int64 in int64(length(vals)).
- You probably already know this, but in case it's useful to you: BitArrays
represent an Int64 (or vector of Int64s) as an array of bits.
--Tim
[julia-users] Re: Build a constructor with fewer inputs than values
Sorry that you did not get any response, I did not comprehend what you were
trying to do last time.
The code you posted seems to work fine for me on 0.2.1 and 0.3-prerelease.
How did you trigger the error?
As a side note if efficiency is important, I would recommend that you use
Valve2::Array{Bool, 1} or the equivalent Valve2::Vector{Bool} in the type
declaration, so that Julia knows it will not get a matrix or tensor of
booleans from your type.
Ivar
kl. 11:02:37 UTC+1 mandag 24. mars 2014 skrev RecentConvert følgende:
Is this question not clear or just uninteresting?
[julia-users] Re: Build a constructor with fewer inputs than values
Thanks for the quick replies. *Purpose:* Given a double, convert it to a collection of boolean values representing the statuses of various valves and settings. I'm still torn about whether I want to input an array of values and store arrays of statuses in one type or create an array of the type with individual collections. This implementation is *intended* to be for arrays. It's partly to teach myself Julia so learning how to do it this way is important but I am also open to *just do it this really easy way*. Once I have the parsed statuses I can use it separate calibration data from the rest of the data, among other things. I call it with the following line: statuses = Status(vector(Dstc[StatusW])) The original format is a data frame. Julia Version 0.2.1 Commit e44b593* (2014-02-11 06:30 UTC) Platform Info: System: Windows (x86_64-w64-mingw32) WORD_SIZE: 64
Re: [julia-users] Re: Build a constructor with fewer inputs than values
On Monday, March 24, 2014 03:56:08 AM RecentConvert wrote: statuses = Status(vector(Dstc[StatusW])) That's still not very helpful, because we have no idea what vector(Dstc[StatusW]) yields. Does Status([1:12]) work? If so, the problem is in the particular inputs you're supplying. If not, then I'm not sure what's going on. --Tim
[julia-users] Re: Trying to understand how to structure parallel computation
Maybe the pmap example from the doc can be useful, it feeds work to other processes: http://julia.readthedocs.org/en/latest/manual/parallel-computing/#synchronization-with-remote-references
Re: [julia-users] Yet another licensing question: Building a Julia version of an R package
Instead of asking the package authors to do extra work, it might be better to offer to convert their package to a Julia package. Then, you can ask the authors if the converted package could be released with an MIT license. On Mon, Mar 24, 2014 at 2:18 AM, Ted Fujimoto tftur...@gmail.com wrote: Thanks Jake! I'll also ask if they are willing to participate in the Julia community by implementing a Julia version too! :) On Sunday, March 23, 2014 6:14:33 PM UTC-7, Jake Bolewski wrote: Another strategy is to contact the authors directly and ask them if they would consider relicensing their work. Many people do not really consider the implications of choosing one license over another and just go with a default. On Sunday, March 23, 2014 8:59:58 PM UTC-4, John Myles White wrote: Yes, including the same GPL-3 license is sufficient if you've derived your work from a GPL-3 project. You may also need to include the original headers of the files if they contain attribution information that you are required to preserve. I don't think there's anything dishonest about creating a GPL-3 package. If you would like to release something under a permissive license, you'll have to implement your code from scratch without ever reading any of the code from a GPL or closed-source implementation. What's most beneficial depends on context. Many businesses prohibit GPL software, so many people in the Julia (and Python) communities intentionally produce MIT or BSD software. But Julia benefits a lot from having GPL packages when there's no reasonable alternative. -- John On Mar 23, 2014, at 1:17 PM, Ted Fujimoto tftu...@gmail.com wrote: Hi all, I'm trying to familiarize myself with Julia by seeing how it compares to other languages. I would also like to open-source my code if it seems useful to others. Unfortunately, licenses have made this process complicated. A tangible example: I am trying to implement a Julia version of the R package pcalg (http://cran.r-project.org/web/packages/pcalg/index.html). Like most R packages, it is protected under the GPL-3 license. Also, the license states that it would consider my implementation a modification of the R package. Say I feel that my project is ready to be open-sourced and put it in a github repository. Is it enough to follow the RmathDist.jl lead and do the following?: 1. Include the same license in the repository. 2. Cite the R package I modified. A more long term question: I'm guessing a better (and more honest) alternative to the above would be to implement the relevant algorithms by looking at the pseudocode and applying it in a way that is friendlier to future improvements using idiomatic Julia (if it exists yet). After that, open-source it under the MIT license. Would this be a more beneficial approach than the Julia version of an R package approach?
[julia-users] Constructing arrays with dim 2
Hi! I'm trying to construct a 3 dimensional array from a number of 1 dimensional arrays. Essentially what i would like to do is a = [f(i, j) for i in 1:n, j in 1:m] where f(i, j) is a function that returns an array (note, f has to construct the entire array at the same time). The code above creates a 2-dimensional array of arrays, but I would like to get a 3-dimensional array with the arrays returned by f in the first dimension with i and j in the second and third dimension, hope you understand a[:,:,1] = [f(1,1) f(2,1) ... f(n,1)] a[:,:,2] = [f(1,2) f(2,2) ... f(n,2)] . . . a[:,:,m] = [f(1,m) f(2,m) ... f(n,m)] f(i,j) are column arrays above. It can be achieved by first creating the large matrix and then filling it a = zeros(Int64, k, n, m) for i in 1:n, j in 1:m a[:,i,j] = f(i,j) end Is this the only way? I find it sort of ugly when its usually possible to do nice construction using comprehensions in other cases.
Re: [julia-users] Re: Build a constructor with fewer inputs than values
The updated code works the same with Status([1:12]) as it does with
vector(Dstc[StatusW]).
type Status
Valve1::Vector{Bool}
Valve2::Vector{Bool}
Valve3::Vector{Bool}
Valve4::Vector{Bool}
Valve5::Vector{Bool}
Valve6::Vector{Bool}
Valve7::Vector{Bool}
Valve8::Vector{Bool}
# Constructor for Status type
function Status(vals::Array{Int64})
l = int64(length(vals))
Valve1 = Array(Bool,l)
Valve2 = Array(Bool,l)
Valve3 = Array(Bool,l)
Valve4 = Array(Bool,l)
Valve5 = Array(Bool,l)
Valve6 = Array(Bool,l)
Valve7 = Array(Bool,l)
Valve8 = Array(Bool,l)
# Parse Inputs
for i=1:l
# Byte 1
Valve1[i] = vals[i] 2^(1-1) 0
Valve2[i] = vals[i] 2^(2-1) 0
Valve3[i] = vals[i] 2^(3-1) 0
Valve4[i] = vals[i] 2^(4-1) 0
Valve5[i] = vals[i] 2^(5-1) 0
Valve6[i] = vals[i] 2^(6-1) 0
Valve7[i] = vals[i] 2^(7-1) 0
Valve8[i] = vals[i] 2^(8-1) 0
end # End of conversion
new(Valve1,Valve2,Valve3,Valve4,Valve5,Valve6,Valve7,Valve8)
end # End of constructor
end # End of type
statuses = Status(vector(Dstc[StatusW]))
julia typeof(statuses) Nothing (constructor with 1 method)
julia statuses.Valve1 ErrorException(type Nothing has no field Valve1)
julia x = Status([1:12])
julia typeof(x) Nothing (constructor with 1 method)
julia x.Valve1 ErrorException(type Nothing has no field Valve1)
[julia-users] Julia package style / learning
I'm definitely not an expert but I thought I would chime in on your arrays of
arrays vrs matrices question.
I recently developed a project where I started out using:
Array{Array{Float64,1},1} as a container for a set of state vectors in an ODE
flow. This seemed most natural but I figured once I got it to work, I would
speed it up by representing everything in a compact matrix representation:
Array{Float64,2}. However, I was never able to speed things up much with
Array{Float64,2} over the Array{Array{Float64,1},1} container.
I ended up with the impression (experts can confirm or deny this) that
although Array{Float64,2} may be stored in memory more compactly than
Array{Array{Float64,1},1}, the latter container is already very efficient so
that any speed gains were marginal.
Is this the experience of others?
Cheers,
Ethan
Re: [julia-users] Julia package style / learning
I think comparisons between those two will depend a lot on context. If you need
to use linear algebra functions, the Array{Array{Float64, 1}, 1} approach won’t
work at all, so it’ll be infinitely slow. If you’re constantly just grabbing
columns stored that way, it might be faster since you might avoid some copying
— at the moment, for an array, A, A[:, i] does a copy which you might slow
things down depending on context.
— John
On Mar 24, 2014, at 7:33 AM, Ethan Anderes ethanande...@gmail.com wrote:
I'm definitely not an expert but I thought I would chime in on your arrays
of arrays vrs matrices question.
I recently developed a project where I started out using:
Array{Array{Float64,1},1} as a container for a set of state vectors in an ODE
flow. This seemed most natural but I figured once I got it to work, I would
speed it up by representing everything in a compact matrix representation:
Array{Float64,2}. However, I was never able to speed things up much with
Array{Float64,2} over the Array{Array{Float64,1},1} container.
I ended up with the impression (experts can confirm or deny this) that
although Array{Float64,2} may be stored in memory more compactly than
Array{Array{Float64,1},1}, the latter container is already very efficient so
that any speed gains were marginal.
Is this the experience of others?
Cheers,
Ethan
Re: [julia-users] Julia package style / learning
Yep, that was my situation: no linear algebra but a lot of grabbing columns within for loops. Looking forward to non-copying array slices:) Thanks, Ethan
Re: [julia-users] Re: Terminate a task
Yes, we need this ability. Externally terminating and otherwise interacting with tasks is a good way to deal with things like timeouts and cancelling distributed work. On Mon, Mar 24, 2014 at 1:01 AM, Amit Murthy amit.mur...@gmail.com wrote: I think currently the only way to interrupt a task is when it is blocked on a condition variable by using the notify call. Will be good to have a terminate(t::Task) call. On Sun, Mar 23, 2014 at 9:08 PM, Bob Cowdery bobcowd...@gmail.com wrote: Could you clarify please. If its on a blocking call how do I throw an error and if its not complete why would the gc delete it. On Sunday, March 23, 2014 3:27:18 PM UTC, Bob Cowdery wrote: Is there any way to terminate a task that is stuck on a blocking call. I can see that I can call istaskdone() or start a Timeout to know that the task is potentially blocked but I don't see anything in Task that lets me terminate it. Bob
Re: [julia-users] Julia package style / learning
Just for the record. To convert from Array{Array{Float64, 1}, 1} to
Array{Float64,2} you can use hcat(a...)
Ivar
kl. 15:50:36 UTC+1 mandag 24. mars 2014 skrev Ethan Anderes følgende:
Yep, that was my situation: no linear algebra but a lot of grabbing
columns within for loops. Looking forward to non-copying array slices:)
Thanks,
Ethan
Re: [julia-users] Yet another licensing question: Building a Julia version of an R package
I probably was not clear in my response to Jake but what I meant was that I would ask the authors if they wanted to use the GPL because they felt that license was most appropriate. If not, I would then give them the choice to *assist* me at any level they choose with a Julia version of their package under an MIT license (since they are academics, my guess is that they would want to be a part of popularizing their work with different versions), and decline to help if they choose to do so. I think would be best not to keep them in the dark. On Monday, March 24, 2014 4:47:08 AM UTC-7, tshort wrote: Instead of asking the package authors to do extra work, it might be better to offer to convert their package to a Julia package. Then, you can ask the authors if the converted package could be released with an MIT license. On Mon, Mar 24, 2014 at 2:18 AM, Ted Fujimoto tftu...@gmail.comjavascript: wrote: Thanks Jake! I'll also ask if they are willing to participate in the Julia community by implementing a Julia version too! :) On Sunday, March 23, 2014 6:14:33 PM UTC-7, Jake Bolewski wrote: Another strategy is to contact the authors directly and ask them if they would consider relicensing their work. Many people do not really consider the implications of choosing one license over another and just go with a default. On Sunday, March 23, 2014 8:59:58 PM UTC-4, John Myles White wrote: Yes, including the same GPL-3 license is sufficient if you've derived your work from a GPL-3 project. You may also need to include the original headers of the files if they contain attribution information that you are required to preserve. I don't think there's anything dishonest about creating a GPL-3 package. If you would like to release something under a permissive license, you'll have to implement your code from scratch without ever reading any of the code from a GPL or closed-source implementation. What's most beneficial depends on context. Many businesses prohibit GPL software, so many people in the Julia (and Python) communities intentionally produce MIT or BSD software. But Julia benefits a lot from having GPL packages when there's no reasonable alternative. -- John On Mar 23, 2014, at 1:17 PM, Ted Fujimoto tftu...@gmail.com wrote: Hi all, I'm trying to familiarize myself with Julia by seeing how it compares to other languages. I would also like to open-source my code if it seems useful to others. Unfortunately, licenses have made this process complicated. A tangible example: I am trying to implement a Julia version of the R package pcalg (http://cran.r-project.org/web/packages/pcalg/index.html). Like most R packages, it is protected under the GPL-3 license. Also, the license states that it would consider my implementation a modification of the R package. Say I feel that my project is ready to be open-sourced and put it in a github repository. Is it enough to follow the RmathDist.jl lead and do the following?: 1. Include the same license in the repository. 2. Cite the R package I modified. A more long term question: I'm guessing a better (and more honest) alternative to the above would be to implement the relevant algorithms by looking at the pseudocode and applying it in a way that is friendlier to future improvements using idiomatic Julia (if it exists yet). After that, open-source it under the MIT license. Would this be a more beneficial approach than the Julia version of an R package approach?
Re: [julia-users] Yet another licensing question: Building a Julia version of an R package
I probably was not clear in my response to Jake but what I meant was that I would ask the authors if they wanted to use the GPL because they felt that license was most appropriate. If not, I would then give them the choice to *assist* me at any level they choose with a Julia version of their package under an MIT license (since they are academics, my guess is that they would want to be a part of popularizing their work with different versions), and they can decline to help if they choose to do so. I think it would be best not to keep them in the dark. On Monday, March 24, 2014 4:47:08 AM UTC-7, tshort wrote: Instead of asking the package authors to do extra work, it might be better to offer to convert their package to a Julia package. Then, you can ask the authors if the converted package could be released with an MIT license. On Mon, Mar 24, 2014 at 2:18 AM, Ted Fujimoto tftu...@gmail.comjavascript: wrote: Thanks Jake! I'll also ask if they are willing to participate in the Julia community by implementing a Julia version too! :) On Sunday, March 23, 2014 6:14:33 PM UTC-7, Jake Bolewski wrote: Another strategy is to contact the authors directly and ask them if they would consider relicensing their work. Many people do not really consider the implications of choosing one license over another and just go with a default. On Sunday, March 23, 2014 8:59:58 PM UTC-4, John Myles White wrote: Yes, including the same GPL-3 license is sufficient if you've derived your work from a GPL-3 project. You may also need to include the original headers of the files if they contain attribution information that you are required to preserve. I don't think there's anything dishonest about creating a GPL-3 package. If you would like to release something under a permissive license, you'll have to implement your code from scratch without ever reading any of the code from a GPL or closed-source implementation. What's most beneficial depends on context. Many businesses prohibit GPL software, so many people in the Julia (and Python) communities intentionally produce MIT or BSD software. But Julia benefits a lot from having GPL packages when there's no reasonable alternative. -- John On Mar 23, 2014, at 1:17 PM, Ted Fujimoto tftu...@gmail.com wrote: Hi all, I'm trying to familiarize myself with Julia by seeing how it compares to other languages. I would also like to open-source my code if it seems useful to others. Unfortunately, licenses have made this process complicated. A tangible example: I am trying to implement a Julia version of the R package pcalg (http://cran.r-project.org/web/packages/pcalg/index.html). Like most R packages, it is protected under the GPL-3 license. Also, the license states that it would consider my implementation a modification of the R package. Say I feel that my project is ready to be open-sourced and put it in a github repository. Is it enough to follow the RmathDist.jl lead and do the following?: 1. Include the same license in the repository. 2. Cite the R package I modified. A more long term question: I'm guessing a better (and more honest) alternative to the above would be to implement the relevant algorithms by looking at the pseudocode and applying it in a way that is friendlier to future improvements using idiomatic Julia (if it exists yet). After that, open-source it under the MIT license. Would this be a more beneficial approach than the Julia version of an R package approach?
Re: [julia-users] Yet another licensing question: Building a Julia version of an R package
I think Tom’s point is that most people prefer that you assist them rather than offer them the chance to assist you. — John On Mar 24, 2014, at 8:58 AM, Ted Fujimoto tftur...@gmail.com wrote: I probably was not clear in my response to Jake but what I meant was that I would ask the authors if they wanted to use the GPL because they felt that license was most appropriate. If not, I would then give them the choice to assist me at any level they choose with a Julia version of their package under an MIT license (since they are academics, my guess is that they would want to be a part of popularizing their work with different versions), and they can decline to help if they choose to do so. I think it would be best not to keep them in the dark. On Monday, March 24, 2014 4:47:08 AM UTC-7, tshort wrote: Instead of asking the package authors to do extra work, it might be better to offer to convert their package to a Julia package. Then, you can ask the authors if the converted package could be released with an MIT license. On Mon, Mar 24, 2014 at 2:18 AM, Ted Fujimoto tftu...@gmail.com wrote: Thanks Jake! I'll also ask if they are willing to participate in the Julia community by implementing a Julia version too! :) On Sunday, March 23, 2014 6:14:33 PM UTC-7, Jake Bolewski wrote: Another strategy is to contact the authors directly and ask them if they would consider relicensing their work. Many people do not really consider the implications of choosing one license over another and just go with a default. On Sunday, March 23, 2014 8:59:58 PM UTC-4, John Myles White wrote: Yes, including the same GPL-3 license is sufficient if you've derived your work from a GPL-3 project. You may also need to include the original headers of the files if they contain attribution information that you are required to preserve. I don't think there's anything dishonest about creating a GPL-3 package. If you would like to release something under a permissive license, you'll have to implement your code from scratch without ever reading any of the code from a GPL or closed-source implementation. What's most beneficial depends on context. Many businesses prohibit GPL software, so many people in the Julia (and Python) communities intentionally produce MIT or BSD software. But Julia benefits a lot from having GPL packages when there's no reasonable alternative. -- John On Mar 23, 2014, at 1:17 PM, Ted Fujimoto tftu...@gmail.com wrote: Hi all, I'm trying to familiarize myself with Julia by seeing how it compares to other languages. I would also like to open-source my code if it seems useful to others. Unfortunately, licenses have made this process complicated. A tangible example: I am trying to implement a Julia version of the R package pcalg (http://cran.r-project.org/web/packages/pcalg/index.html). Like most R packages, it is protected under the GPL-3 license. Also, the license states that it would consider my implementation a modification of the R package. Say I feel that my project is ready to be open-sourced and put it in a github repository. Is it enough to follow the RmathDist.jl lead and do the following?: 1. Include the same license in the repository. 2. Cite the R package I modified. A more long term question: I'm guessing a better (and more honest) alternative to the above would be to implement the relevant algorithms by looking at the pseudocode and applying it in a way that is friendlier to future improvements using idiomatic Julia (if it exists yet). After that, open-source it under the MIT license. Would this be a more beneficial approach than the Julia version of an R package approach?
Re: [julia-users] Yet another licensing question: Building a Julia version of an R package
OK. How about asking if I could assist *them* on a Julia version under an MIT license? The result is the same but I guess language does make a difference... On Monday, March 24, 2014 9:08:23 AM UTC-7, John Myles White wrote: I think Tom’s point is that most people prefer that you assist them rather than offer them the chance to assist you. — John On Mar 24, 2014, at 8:58 AM, Ted Fujimoto tftu...@gmail.com javascript: wrote: I probably was not clear in my response to Jake but what I meant was that I would ask the authors if they wanted to use the GPL because they felt that license was most appropriate. If not, I would then give them the choice to *assist* me at any level they choose with a Julia version of their package under an MIT license (since they are academics, my guess is that they would want to be a part of popularizing their work with different versions), and they can decline to help if they choose to do so. I think it would be best not to keep them in the dark. On Monday, March 24, 2014 4:47:08 AM UTC-7, tshort wrote: Instead of asking the package authors to do extra work, it might be better to offer to convert their package to a Julia package. Then, you can ask the authors if the converted package could be released with an MIT license. On Mon, Mar 24, 2014 at 2:18 AM, Ted Fujimoto tftu...@gmail.com wrote: Thanks Jake! I'll also ask if they are willing to participate in the Julia community by implementing a Julia version too! :) On Sunday, March 23, 2014 6:14:33 PM UTC-7, Jake Bolewski wrote: Another strategy is to contact the authors directly and ask them if they would consider relicensing their work. Many people do not really consider the implications of choosing one license over another and just go with a default. On Sunday, March 23, 2014 8:59:58 PM UTC-4, John Myles White wrote: Yes, including the same GPL-3 license is sufficient if you've derived your work from a GPL-3 project. You may also need to include the original headers of the files if they contain attribution information that you are required to preserve. I don't think there's anything dishonest about creating a GPL-3 package. If you would like to release something under a permissive license, you'll have to implement your code from scratch without ever reading any of the code from a GPL or closed-source implementation. What's most beneficial depends on context. Many businesses prohibit GPL software, so many people in the Julia (and Python) communities intentionally produce MIT or BSD software. But Julia benefits a lot from having GPL packages when there's no reasonable alternative. -- John On Mar 23, 2014, at 1:17 PM, Ted Fujimoto tftu...@gmail.com wrote: Hi all, I'm trying to familiarize myself with Julia by seeing how it compares to other languages. I would also like to open-source my code if it seems useful to others. Unfortunately, licenses have made this process complicated. A tangible example: I am trying to implement a Julia version of the R package pcalg (http://cran.r-project.org/web/packages/pcalg/index.html). Like most R packages, it is protected under the GPL-3 license. Also, the license states that it would consider my implementation a modification of the R package. Say I feel that my project is ready to be open-sourced and put it in a github repository. Is it enough to follow the RmathDist.jl lead and do the following?: 1. Include the same license in the repository. 2. Cite the R package I modified. A more long term question: I'm guessing a better (and more honest) alternative to the above would be to implement the relevant algorithms by looking at the pseudocode and applying it in a way that is friendlier to future improvements using idiomatic Julia (if it exists yet). After that, open-source it under the MIT license. Would this be a more beneficial approach than the Julia version of an R package approach?
Re: [julia-users] Terminate a task
Alternatively, might be fun to make a ccall_in_worker_thread intrinsic which handles all of the fiddly gc details and only blocks the local task (and/or returns a remoteref) On Monday, March 24, 2014, Stefan Karpinski ste...@karpinski.org wrote: Yes, we need this ability. Externally terminating and otherwise interacting with tasks is a good way to deal with things like timeouts and cancelling distributed work. On Mon, Mar 24, 2014 at 1:01 AM, Amit Murthy amit.mur...@gmail.comjavascript:_e(%7B%7D,'cvml','amit.mur...@gmail.com'); wrote: I think currently the only way to interrupt a task is when it is blocked on a condition variable by using the notify call. Will be good to have a terminate(t::Task) call. On Sun, Mar 23, 2014 at 9:08 PM, Bob Cowdery bobcowd...@gmail.comjavascript:_e(%7B%7D,'cvml','bobcowd...@gmail.com'); wrote: Could you clarify please. If its on a blocking call how do I throw an error and if its not complete why would the gc delete it. On Sunday, March 23, 2014 3:27:18 PM UTC, Bob Cowdery wrote: Is there any way to terminate a task that is stuck on a blocking call. I can see that I can call istaskdone() or start a Timeout to know that the task is potentially blocked but I don't see anything in Task that lets me terminate it. Bob
[julia-users] Re: Gauss quadrature package
Hallo Bill; could you please explain or post some reference about that specialised version you mention of the QL iteration to get directly the first components of the normalised eigenvectors. As I am working with complex, non-hermitian, symmetric eigenvalue problems it would be of great help. Thanks! El miércoles, 16 de octubre de 2013 03:16:33 UTC+2, Bill McLean escribió: Steven, thanks for pointing out Base.gauss. My package relies, via eig, on the Lapack eigensystem routines for a symmetric tridiagonal matrix, but it would be possible to write such an eigensolver in Julia and so support higher precision. If I find the time I will try to do this. In fact, to generate the Gauss rules you need only the eigenvalues and the first component of each normalized eigenvector, and there is a specialised version of the QL iteration that does this without having to compute the other components of the eigenvectors. On Tuesday, October 15, 2013 6:38:54 AM UTC+11, Steven G. Johnson wrote: Note that this functionality (for constant weight functions) is already in Base, e.g. x, w = Base.gauss(Float64, 17) gives a 17-point Gauss rule on [-1,1]. There is also Base.kronrod for Gauss-Kronrod rules. (Currently, these are not documented; that functionality use used internally by the quadgk function.) It is nice to have Gauss quadrature rules for different weight functions, though. You might want to look at the Base implementation (in base/quadgk.jl), however, and possibly exploit some of its subroutines, since the Base implementation supports computation of points and weights in arbitrary precision. On Saturday, October 12, 2013 9:05:53 PM UTC-4, Bill McLean wrote: I have written a Julia package to generate the points and weights of the classical Gauss quadrature rules. I did not succeed in following the instructions in the manual to add it to the list of available packages, but you can obtain the package from https://github.com/billmclean/GaussQuadrature.jl
[julia-users] Re: Constructing arrays with dim 2
This runs fine for me, running Version 0.3.0-prerelease (2014-02-28 04:44
UTC):
f(i,j) = [i,j]
n=3; m=2
a = [f(i, j) for i in 1:n, j in 1:m]
Out[91]:
3x2 Array{Any,2}:
[1,1] [1,2]
[2,1] [2,2]
[3,1] [3,2]
On Monday, March 24, 2014 10:07:49 AM UTC-4, Linus Mellberg wrote:
Hi!
I'm trying to construct a 3 dimensional array from a number of 1
dimensional arrays. Essentially what i would like to do is
a = [f(i, j) for i in 1:n, j in 1:m]
where f(i, j) is a function that returns an array (note, f has to
construct the entire array at the same time). The code above creates a
2-dimensional array of arrays, but I would like to get a 3-dimensional
array with the arrays returned by f in the first dimension with i and j in
the second and third dimension, hope you understand
a[:,:,1] = [f(1,1) f(2,1) ... f(n,1)]
a[:,:,2] = [f(1,2) f(2,2) ... f(n,2)]
.
.
.
a[:,:,m] = [f(1,m) f(2,m) ... f(n,m)]
f(i,j) are column arrays above.
It can be achieved by first creating the large matrix and then filling it
a = zeros(Int64, k, n, m)
for i in 1:n, j in 1:m
a[:,i,j] = f(i,j)
end
Is this the only way? I find it sort of ugly when its usually possible to
do nice construction using comprehensions in other cases.
Re: [julia-users] Re: Build a constructor with fewer inputs than values
I get
julia x.Valve1
12-element Array{Bool,1}:
true
false
true
false
true
false
true
false
true
false
true
false
I even went to the trouble to build Julia 0.2.1 and test it there, too; same
result. So I can't replicate your problem. (I'm on Linux.)
How are you getting Julia? Building it yourself? Binary download? Anyway, it
sounds like you want to try a different way of getting Julia.
--Tim
On Monday, March 24, 2014 07:18:42 AM RecentConvert wrote:
The updated code works the same with Status([1:12]) as it does with
vector(Dstc[StatusW]).
type Status
Valve1::Vector{Bool}
Valve2::Vector{Bool}
Valve3::Vector{Bool}
Valve4::Vector{Bool}
Valve5::Vector{Bool}
Valve6::Vector{Bool}
Valve7::Vector{Bool}
Valve8::Vector{Bool}
# Constructor for Status type
function Status(vals::Array{Int64})
l = int64(length(vals))
Valve1 = Array(Bool,l)
Valve2 = Array(Bool,l)
Valve3 = Array(Bool,l)
Valve4 = Array(Bool,l)
Valve5 = Array(Bool,l)
Valve6 = Array(Bool,l)
Valve7 = Array(Bool,l)
Valve8 = Array(Bool,l)
# Parse Inputs
for i=1:l
# Byte 1
Valve1[i] = vals[i] 2^(1-1) 0
Valve2[i] = vals[i] 2^(2-1) 0
Valve3[i] = vals[i] 2^(3-1) 0
Valve4[i] = vals[i] 2^(4-1) 0
Valve5[i] = vals[i] 2^(5-1) 0
Valve6[i] = vals[i] 2^(6-1) 0
Valve7[i] = vals[i] 2^(7-1) 0
Valve8[i] = vals[i] 2^(8-1) 0
end # End of conversion
new(Valve1,Valve2,Valve3,Valve4,Valve5,Valve6,Valve7,Valve8)
end # End of constructor
end # End of type
statuses = Status(vector(Dstc[StatusW]))
julia typeof(statuses) Nothing (constructor with 1 method)
julia statuses.Valve1 ErrorException(type Nothing has no field Valve1)
julia x = Status([1:12])
julia typeof(x) Nothing (constructor with 1 method)
julia x.Valve1 ErrorException(type Nothing has no field Valve1)
[julia-users] Re: Constructing arrays with dim 2
Hi, I guess you want a 3d array instead of a 2D array containing 1D arrays. I tried this: arrayLength = 10; matrixCols = 10; matrixSlices= 10; function arrayTest(arrayLength,i,j)singleArray = ones(1,arrayLength)*(i+j); #each array has a unique value i+jreturn singleArrayend matrix3d = [arrayTest(arrayLength,i,j)[k] for k=1:arrayLength, i=1:matrixCols, j=1:matrixSlices ]; matrix3d[:,1,1] It works fine ;) Le lundi 24 mars 2014 15:07:49 UTC+1, Linus Mellberg a écrit : Hi! I'm trying to construct a 3 dimensional array from a number of 1 dimensional arrays. Essentially what i would like to do is a = [f(i, j) for i in 1:n, j in 1:m] where f(i, j) is a function that returns an array (note, f has to construct the entire array at the same time). The code above creates a 2-dimensional array of arrays, but I would like to get a 3-dimensional array with the arrays returned by f in the first dimension with i and j in the second and third dimension, hope you understand a[:,:,1] = [f(1,1) f(2,1) ... f(n,1)] a[:,:,2] = [f(1,2) f(2,2) ... f(n,2)] . . . a[:,:,m] = [f(1,m) f(2,m) ... f(n,m)] f(i,j) are column arrays above. It can be achieved by first creating the large matrix and then filling it a = zeros(Int64, k, n, m) for i in 1:n, j in 1:m a[:,i,j] = f(i,j) end Is this the only way? I find it sort of ugly when its usually possible to do nice construction using comprehensions in other cases.
[julia-users] Re: Constructing arrays with dim 2
If you really want a 3d matrix and not a 2d array containing arrays, I
would have tried this :
arrayLength= 10 ;
matrixCol = 10;
matrixSlices= 10;
function arrayTest(arrayLength,i,j)
singleArray = ones(1,arrayLength)*(i+j); #each array has a unique value
i+j
return singleArray
end
matrix3d = [arrayTest(arrayLength,i,j)[k] for k=1:arrayLength, i=1:matrixCol,
j=1:matrixSlices ];
matrix3d[:,1,1]
Le lundi 24 mars 2014 19:25:56 UTC+1, Keith Campbell a écrit :
This runs fine for me, running Version 0.3.0-prerelease (2014-02-28 04:44
UTC):
f(i,j) = [i,j]
n=3; m=2
a = [f(i, j) for i in 1:n, j in 1:m]
Out[91]:
3x2 Array{Any,2}:
[1,1] [1,2]
[2,1] [2,2]
[3,1] [3,2]
On Monday, March 24, 2014 10:07:49 AM UTC-4, Linus Mellberg wrote:
Hi!
I'm trying to construct a 3 dimensional array from a number of 1
dimensional arrays. Essentially what i would like to do is
a = [f(i, j) for i in 1:n, j in 1:m]
where f(i, j) is a function that returns an array (note, f has to
construct the entire array at the same time). The code above creates a
2-dimensional array of arrays, but I would like to get a 3-dimensional
array with the arrays returned by f in the first dimension with i and j in
the second and third dimension, hope you understand
a[:,:,1] = [f(1,1) f(2,1) ... f(n,1)]
a[:,:,2] = [f(1,2) f(2,2) ... f(n,2)]
.
.
.
a[:,:,m] = [f(1,m) f(2,m) ... f(n,m)]
f(i,j) are column arrays above.
It can be achieved by first creating the large matrix and then filling it
a = zeros(Int64, k, n, m)
for i in 1:n, j in 1:m
a[:,i,j] = f(i,j)
end
Is this the only way? I find it sort of ugly when its usually possible to
do nice construction using comprehensions in other cases.
[julia-users] Re: Constructing arrays with dim 2
Thinking about it, it is probably not so ... efficient. Le lundi 24 mars 2014 19:41:14 UTC+1, Antoine Chevalier a écrit : Hi, I guess you want a 3d array instead of a 2D array containing 1D arrays. I tried this: arrayLength = 10; matrixCols = 10; matrixSlices= 10; function arrayTest(arrayLength,i,j)singleArray = ones(1,arrayLength)*(i+j); #each array has a unique value i+jreturn singleArrayend matrix3d = [arrayTest(arrayLength,i,j)[k] for k=1:arrayLength, i=1:matrixCols, j=1:matrixSlices ]; matrix3d[:,1,1] It works fine ;) Le lundi 24 mars 2014 15:07:49 UTC+1, Linus Mellberg a écrit : Hi! I'm trying to construct a 3 dimensional array from a number of 1 dimensional arrays. Essentially what i would like to do is a = [f(i, j) for i in 1:n, j in 1:m] where f(i, j) is a function that returns an array (note, f has to construct the entire array at the same time). The code above creates a 2-dimensional array of arrays, but I would like to get a 3-dimensional array with the arrays returned by f in the first dimension with i and j in the second and third dimension, hope you understand a[:,:,1] = [f(1,1) f(2,1) ... f(n,1)] a[:,:,2] = [f(1,2) f(2,2) ... f(n,2)] . . . a[:,:,m] = [f(1,m) f(2,m) ... f(n,m)] f(i,j) are column arrays above. It can be achieved by first creating the large matrix and then filling it a = zeros(Int64, k, n, m) for i in 1:n, j in 1:m a[:,i,j] = f(i,j) end Is this the only way? I find it sort of ugly when its usually possible to do nice construction using comprehensions in other cases.
[julia-users] Re: Constructing arrays with dim 2
Ok, one might be less redundant if reading the thread properly before posting. Sorry about the noise. Den måndagen den 24:e mars 2014 kl. 23:12:03 UTC+1 skrev Gunnar Farnebäck: [f(i,j)[k] for k in 1:K, i in 1:n, j in i:m] Den måndagen den 24:e mars 2014 kl. 15:07:49 UTC+1 skrev Linus Mellberg: Hi! I'm trying to construct a 3 dimensional array from a number of 1 dimensional arrays. Essentially what i would like to do is a = [f(i, j) for i in 1:n, j in 1:m] where f(i, j) is a function that returns an array (note, f has to construct the entire array at the same time). The code above creates a 2-dimensional array of arrays, but I would like to get a 3-dimensional array with the arrays returned by f in the first dimension with i and j in the second and third dimension, hope you understand a[:,:,1] = [f(1,1) f(2,1) ... f(n,1)] a[:,:,2] = [f(1,2) f(2,2) ... f(n,2)] . . . a[:,:,m] = [f(1,m) f(2,m) ... f(n,m)] f(i,j) are column arrays above. It can be achieved by first creating the large matrix and then filling it a = zeros(Int64, k, n, m) for i in 1:n, j in 1:m a[:,i,j] = f(i,j) end Is this the only way? I find it sort of ugly when its usually possible to do nice construction using comprehensions in other cases.
Re: [julia-users] Embedding Julia in an app / calling from C++
The error message I got was: System image file C:\project\Debug\../lib/julia/sys.ji not found This occurred when I called jl_init() with NULL. It seems that it is trying to find files relative to the executable file location. I tried setting JULIA_HOME environment variable but that did not help. I then changed the argument to c:\julia\bin which worked. It takes about 2 seconds to startup on my laptop (2009 Intel duo Mac). I was wondering if I could modify Julia to only be a language - i.e. remove all the standard library and therefore most (all?) of the dependencies. As an embedded language I don't really want all these external dependencies. Is this possible? Where should I start? Are any of the dependencies must have? Is there a developer's guide for Julia? Thanks and Regards Dibyendu
Re: [julia-users] Embedding Julia in an app / calling from C++
This isn't really possible right now--large, essential parts of Julia are written in Julia, and there's not full differentiation between the core needed just to get the language running and the other components included in Base. Please see https://github.com/JuliaLang/julia/issues/5155 and recent comments on https://github.com/JuliaLang/julia/issues/1906 for a bit more of the current discussion on this topic. On Monday, March 24, 2014 5:43:41 PM UTC-5, Dibyendu Majumdar wrote: The error message I got was: System image file C:\project\Debug\../lib/julia/sys.ji not found This occurred when I called jl_init() with NULL. It seems that it is trying to find files relative to the executable file location. I tried setting JULIA_HOME environment variable but that did not help. I then changed the argument to c:\julia\bin which worked. It takes about 2 seconds to startup on my laptop (2009 Intel duo Mac). I was wondering if I could modify Julia to only be a language - i.e. remove all the standard library and therefore most (all?) of the dependencies. As an embedded language I don't really want all these external dependencies. Is this possible? Where should I start? Are any of the dependencies must have? Is there a developer's guide for Julia? Thanks and Regards Dibyendu
Re: [julia-users] ANN / RFC: SGEArray iterator
Hello, On Friday, March 21, 2014 4:31:59 AM UTC+1, Jiahao Chen wrote: I wrote a similar package long ago for Python and remember SGE array jobs well. If ClusterManager's addprocs_sge function doesn't respect the current working directory in the worker processes, it would be nice to file an issue about it. It would be really nice to have your code integrated OK, I might do that. I feel a bit hesitant, though, to call this an issue. Maybe the behaviour is by design. more tightly with ClusterManager rather than exist as a separate package. It is just a few lines of code---if anybody form ClusterManagers is willing to integrate it---by all means. ---david Thanks, Jiahao Chen Staff Research Scientist MIT Computer Science and Artificial Intelligence Laboratory On Thu, Mar 13, 2014 at 4:07 AM, David van Leeuwen david.va...@gmail.com javascript: wrote: Hello, I've got a tiny package that makes certain Sun Grid Engine array processing jobs easier with Julia. I've put it up at Pkg.clone(https://github.com/davidavdav/SGEArrays.jl.git;) The premise is that your main Julia script needs to process a large number of files, which are given as a list. Rather than splitting the files in separate lists outside Julia, and spawning an array of jobs calling the Julia script with a different list files for every job, this splitting is done in an iterator. Your main julia script `bin/julia-script` could look like using SGEArrays listfile = ARGS[1] files = readdlm(listfile) for file in SGEArray(files) ## process file $file end i,e., the `SGEArray(files)` replaces the bit where you would normally have `files`. Calling the script as an SGE task array of size 80 would go like: find data/input/ -type f filelist qsub -t1:80 -b y -cwd bin/julia-script filelist but the code would also work outside SGE bin/julia-script filelist For certain computing tasks I find this somewhat easier than using ClusterManagers.addprocs_sge, which also doesn't seem to respect the current working directory in the worker processes. Cheers, ---david
[julia-users] Fastest method to create a matrix of random integers
Hi,
What is the fastest way to create a matrix containing random integers: 1 or
-1 with equal probability?
I have tried the following options but was wondering if I am missing
something.
(I also need 1, 0 or -1 with different probabilities later, which is why I
don't just use a boolean random matrix.)
Thanks,
David.
julia function rand_pm1_matrix(L)
matrix::Array{Int8, 2} = 2 .* randbool(L,L) .- 1
end
rand_pm1_matrix (generic function with 1 method)
julia function elementwise(L)
A = Array(Int8, (L, L))
for i in 1:length(A)
if rand() 0.5
A[i] = -1
else
A[i] = 1
end
end
A
end
elementwise (generic function with 1 method)
julia function elementwise_random_block(L)
r = rand(L, L)
A = Array(Int8, (L, L))
for i in 1:length(A)
if r[i] 0.5
A[i] = -1
else
A[i] = 1
end
end
A
end
elementwise_random_block (generic function with 1 method)
julia L = 10
10
julia rand_pm1_matrix(L);
julia elementwise(L);
julia elementwise_random_block(L);
julia
julia L = 100
100
julia @time rand_pm1_matrix(L);
elapsed time: 6.5661e-5 seconds (188588 bytes allocated)
julia @time elementwise(L);
elapsed time: 0.001172332 seconds (10160 bytes allocated)
julia @time elementwise_random_block(L);
elapsed time: 0.000131455 seconds (90240 bytes allocated)
julia
julia L = 1000
1000
julia @time rand_pm1_matrix(L);
elapsed time: 0.013428217 seconds (18125456 bytes allocated)
julia @time elementwise(L);
elapsed time: 0.074257183 seconds (1000176 bytes allocated)
julia @time elementwise_random_block(L);
elapsed time: 0.007721683 seconds (9000288 bytes allocated)
julia
julia L = 1
1
julia @time rand_pm1_matrix(L);
elapsed time: 2.75006866 seconds (1812500448 bytes allocated)
julia @time elementwise(L);
elapsed time: 6.727148454 seconds (10176 bytes allocated)
julia @time elementwise_random_block(L);
elapsed time: 2.819847794 seconds (90288 bytes allocated)
\
Re: [julia-users] Fastest method to create a matrix of random integers
How about
In [186]: @time rand(-1:2:1,1,1);
elapsed time: 2.29940616 seconds (80224 bytes allocated)
No need for an extra function. This uses a range from -1 to 1 with a step
size of 2 so you only get those two numbers.
-Jacob
On Mon, Mar 24, 2014 at 7:21 PM, David P. Sanders dpsand...@gmail.comwrote:
Hi,
What is the fastest way to create a matrix containing random integers: 1
or -1 with equal probability?
I have tried the following options but was wondering if I am missing
something.
(I also need 1, 0 or -1 with different probabilities later, which is why I
don't just use a boolean random matrix.)
Thanks,
David.
julia function rand_pm1_matrix(L)
matrix::Array{Int8, 2} = 2 .* randbool(L,L) .- 1
end
rand_pm1_matrix (generic function with 1 method)
julia function elementwise(L)
A = Array(Int8, (L, L))
for i in 1:length(A)
if rand() 0.5
A[i] = -1
else
A[i] = 1
end
end
A
end
elementwise (generic function with 1 method)
julia function elementwise_random_block(L)
r = rand(L, L)
A = Array(Int8, (L, L))
for i in 1:length(A)
if r[i] 0.5
A[i] = -1
else
A[i] = 1
end
end
A
end
elementwise_random_block (generic function with 1 method)
julia L = 10
10
julia rand_pm1_matrix(L);
julia elementwise(L);
julia elementwise_random_block(L);
julia
julia L = 100
100
julia @time rand_pm1_matrix(L);
elapsed time: 6.5661e-5 seconds (188588 bytes allocated)
julia @time elementwise(L);
elapsed time: 0.001172332 seconds (10160 bytes allocated)
julia @time elementwise_random_block(L);
elapsed time: 0.000131455 seconds (90240 bytes allocated)
julia
julia L = 1000
1000
julia @time rand_pm1_matrix(L);
elapsed time: 0.013428217 seconds (18125456 bytes allocated)
julia @time elementwise(L);
elapsed time: 0.074257183 seconds (1000176 bytes allocated)
julia @time elementwise_random_block(L);
elapsed time: 0.007721683 seconds (9000288 bytes allocated)
julia
julia L = 1
1
julia @time rand_pm1_matrix(L);
elapsed time: 2.75006866 seconds (1812500448 bytes allocated)
julia @time elementwise(L);
elapsed time: 6.727148454 seconds (10176 bytes allocated)
julia @time elementwise_random_block(L);
elapsed time: 2.819847794 seconds (90288 bytes allocated)
\
[julia-users] setting Qt properties in PySide
Hi, I can't figure out the syntax to set Qt graphics properties in PySide.jl For example, how to translate the following Python code: sizer.setAlignment(Qt.AlignTop) or pw.layout().setSizeConstraint(QLayout.SetFixedSize) or cw.setFrameStyle(QFrame.StyledPanel|QFrame.Sunken) any help would be appreciated. Sam
[julia-users] Re: Managing objects and state
it's not completely clear to me what you're asking. julia isn't particularly object oriented (i just checked and there's no mention of objects or classes in the intro at http://julialang.org/) having said that, you can store and modify (unless the type is immutable) values in composite types. so, for example julia type State x::Int end julia function set(s::State, x::Int) s.x = x end set (generic function with 1 method) julia function read(s::State) return s.x end read (generic function with 1 method) julia s = State(12) State(12) julia s.x 12 julia s.x = 100 100 julia s.x 100 julia s State(100) julia set(s, 32) 32 julia s State(32) julia read(s) 32 maybe that helps? obviously set and read are trivial to do directly on the instance, but you could imagine more complex functions. andrew On Monday, 24 March 2014 16:32:41 UTC-3, Bob Cowdery wrote: Forgive me if this is daft and often answered question but I'm trying to get my head around Julia OO. Am I correct in thinking that as there is no binding between methods and types that I have to explicitly pass in an instance of a type to a method. If that is the case then how do I hold state on a remote object. I call a function that creates an instance of a type say something simple. type State sock end I just want to hold a socket reference. If the first remote function I call creates State then how can the next function I call obtain the state instance. Do I have to create a remote reference or something which it can use? Thanks Bob
[julia-users] Re: setting Qt properties in PySide
It varies. qt_enum(AlignTop) will do the first, Qt.QVBoxLayout()[:SetFixedSize] the second, and Qt.QFrame()[:Sunken] the third. The qt_enum() function is basically pyimport(PySide.QtCore)[Qt][:property_name] which is needed to fish properties out of the Qt object, as @pyimport will try to convert what it can into methods. On Monday, March 24, 2014 8:02:18 PM UTC-4, Samuele Carcagno wrote: Hi, I can't figure out the syntax to set Qt graphics properties in PySide.jl For example, how to translate the following Python code: sizer.setAlignment(Qt.AlignTop) or pw.layout().setSizeConstraint(QLayout.SetFixedSize) or cw.setFrameStyle(QFrame.StyledPanel|QFrame.Sunken) any help would be appreciated. Sam
[julia-users] set parent to None in PySide
another PySide.jl question, how to set the parent to None
after removing a widget? If I attempt it I get the following error:
julia pw_prm_sizer_0[:removeWidget](wd[fieldLabel][1])
julia wd[fieldLabel][1][:setParent](None)
ERROR: PyError (PyObject_Call) type 'exceptions.TypeError'
TypeError('PySide.QtGui.QWidget.setParent' called with wrong argument
types:\n PySide.QtGui.QWidget.setParent(PyCall.jlwrap)\nSupported
signatures:\n PySide.QtGui.QWidget.setParent(PySide.QtGui.QWidget)\n
PySide.QtGui.QWidget.setParent(PySide.QtGui.QWidget,
PySide.QtCore.Qt.WindowFlags),)
in pyerr_check at /home/sam/.julia/v0.3/PyCall/src/exception.jl:58
in pycall at /home/sam/.julia/v0.3/PyCall/src/PyCall.jl:85
in fn at /home/sam/.julia/v0.3/PyCall/src/conversions.jl:181
[julia-users] Re: set parent to None in PySide
I don't really know. This of course is an issue, as it likely won't get
garbage collected once removed. I thought setting the parent to `nothing`
would work, but it doesn't. If you find something that does work please let
me know.
On Monday, March 24, 2014 9:00:13 PM UTC-4, Samuele Carcagno wrote:
another PySide.jl question, how to set the parent to None
after removing a widget? If I attempt it I get the following error:
julia pw_prm_sizer_0[:removeWidget](wd[fieldLabel][1])
julia wd[fieldLabel][1][:setParent](None)
ERROR: PyError (PyObject_Call) type 'exceptions.TypeError'
TypeError('PySide.QtGui.QWidget.setParent' called with wrong argument
types:\n PySide.QtGui.QWidget.setParent(PyCall.jlwrap)\nSupported
signatures:\n PySide.QtGui.QWidget.setParent(PySide.QtGui.QWidget)\n
PySide.QtGui.QWidget.setParent(PySide.QtGui.QWidget,
PySide.QtCore.Qt.WindowFlags),)
in pyerr_check at /home/sam/.julia/v0.3/PyCall/src/exception.jl:58
in pycall at /home/sam/.julia/v0.3/PyCall/src/PyCall.jl:85
in fn at /home/sam/.julia/v0.3/PyCall/src/conversions.jl:181
[julia-users] Filling a long composite type
Let's say I have this composite type
julia type t
aa::ASCIIString;
bb::ASCIIString;
end
and try to fill it a la C (or Matlab)
julia tt=t
t (constructor with 1 method)
julia tt.aa=AA
ERROR: type DataType has no field aa
so bad surprise. I can't. So I have to do for instance
julia tt=t(AA,BB);
but my real type is 120 members long and I don't want to do it that way (I
would for sure make lots of mistakes). So I want to try like this
julia tt=t(,);
julia tt.aa=AA
AA
but do I avoid doing tt=t(,,,... 120 times?)
Tried this but no luck either
julia tt=t(repmat([],10));
ERROR: no method t(Array{ASCIIString,1})
Thanks
Re: [julia-users] Filling a long composite type
tt = t( [ for i = 1:120]... )
On Mon, Mar 24, 2014 at 9:43 PM, J Luis jmfl...@gmail.com wrote:
Let's say I have this composite type
julia type t
aa::ASCIIString;
bb::ASCIIString;
end
and try to fill it a la C (or Matlab)
julia tt=t
t (constructor with 1 method)
julia tt.aa=AA
ERROR: type DataType has no field aa
so bad surprise. I can't. So I have to do for instance
julia tt=t(AA,BB);
but my real type is 120 members long and I don't want to do it that way (I
would for sure make lots of mistakes). So I want to try like this
julia tt=t(,);
julia tt.aa=AA
AA
but do I avoid doing tt=t(,,,... 120 times?)
Tried this but no luck either
julia tt=t(repmat([],10));
ERROR: no method t(Array{ASCIIString,1})
Thanks
Re: [julia-users] Filling a long composite type
Thanks a lot
It would be nice to have a kind of repository for tricks where this one
would deserve a place
Terça-feira, 25 de Março de 2014 1:55:32 UTC, Jameson escreveu:
tt = t( [ for i = 1:120]... )
On Mon, Mar 24, 2014 at 9:43 PM, J Luis jmf...@gmail.com javascript:
wrote:
Let's say I have this composite type
julia type t
aa::ASCIIString;
bb::ASCIIString;
end
and try to fill it a la C (or Matlab)
julia tt=t
t (constructor with 1 method)
julia tt.aa=AA
ERROR: type DataType has no field aa
so bad surprise. I can't. So I have to do for instance
julia tt=t(AA,BB);
but my real type is 120 members long and I don't want to do it that way
(I
would for sure make lots of mistakes). So I want to try like this
julia tt=t(,);
julia tt.aa=AA
AA
but do I avoid doing tt=t(,,,... 120 times?)
Tried this but no luck either
julia tt=t(repmat([],10));
ERROR: no method t(Array{ASCIIString,1})
Thanks
Re: [julia-users] Filling a long composite type
On Monday, March 24, 2014 09:55:32 PM Jameson Nash wrote:
tt = t( [ for i = 1:120]... )
You can also define an inner constructor and leave many/all of the fields
uninitialized.
--Tim
On Mon, Mar 24, 2014 at 9:43 PM, J Luis jmfl...@gmail.com wrote:
Let's say I have this composite type
julia type t
aa::ASCIIString;
bb::ASCIIString;
end
and try to fill it a la C (or Matlab)
julia tt=t
t (constructor with 1 method)
julia tt.aa=AA
ERROR: type DataType has no field aa
so bad surprise. I can't. So I have to do for instance
julia tt=t(AA,BB);
but my real type is 120 members long and I don't want to do it that way (I
would for sure make lots of mistakes). So I want to try like this
julia tt=t(,);
julia tt.aa=AA
AA
but do I avoid doing tt=t(,,,... 120 times?)
Tried this but no luck either
julia tt=t(repmat([],10));
ERROR: no method t(Array{ASCIIString,1})
Thanks
[julia-users] Is a.(b) valid?
The doc of getfield says getfield(*value*, *name::Symbol*) Extract a named field from a value of composite type. The syntax a.b calls getfield(a, :b), and the syntax a.(b) calls getfield(a, b). but when I try the a.(b) variation, it errors (or it's me who errors?) julia gmt_modules.write ?I,?O julia gmt_modules.(write) ERROR: type: getfield: expected Symbol, got Function
Re: [julia-users] Is a.(b) valid?
You need to pass a variable containing a Symbol. Try write = :write On Mon, Mar 24, 2014 at 10:46 PM, J Luis jmfl...@gmail.com wrote: The doc of getfield says getfield(*value*, *name::Symbol*) Extract a named field from a value of composite type. The syntax a.b calls getfield(a, :b), and the syntax a.(b) calls getfield(a, b). but when I try the a.(b) variation, it errors (or it's me who errors?) julia gmt_modules.write ?I,?O julia gmt_modules.(write) ERROR: type: getfield: expected Symbol, got Function
[julia-users] Re: Is a.(b) valid?
After some experimentation, it looks like second way takes a symbol or variable who's value is a symbol. julia type MyType; a::Int; end julia x = MyType(3) MyType(3) julia x.a 3 julia x.(a) ERROR: a not defined julia x.(:a) 3 julia b = :a :a julia x.(b) 3 On Monday, March 24, 2014 7:46:38 PM UTC-7, J Luis wrote: The doc of getfield says getfield(*value*, *name::Symbol*) Extract a named field from a value of composite type. The syntax a.b calls getfield(a, :b), and the syntax a.(b) calls getfield(a, b). but when I try the a.(b) variation, it errors (or it's me who errors?) julia gmt_modules.write ?I,?O julia gmt_modules.(write) ERROR: type: getfield: expected Symbol, got Function
[julia-users] Re: Is a.(b) valid?
Thanks
So this means we cannot do the dynamic names as in Matlab (where the b is
the member name)
BTW, I needed to extract the member name as a string to compare with
another string and the only way I got it done was with
julia nomes=names(MyType)
1-element Array{Symbol,1}:
:a
julia @sprintf(%s, nomes[1])
a
but don't know how to do it the other way around. Not that I need it now
but Matlab dynamic names are quite handy.
Terça-feira, 25 de Março de 2014 3:01:13 UTC, Sam L escreveu:
After some experimentation, it looks like second way takes a symbol or
variable who's value is a symbol.
julia type MyType; a::Int; end
julia x = MyType(3)
MyType(3)
julia x.a
3
julia x.(a)
ERROR: a not defined
julia x.(:a)
3
julia b = :a
:a
julia x.(b)
3
On Monday, March 24, 2014 7:46:38 PM UTC-7, J Luis wrote:
The doc of getfield says
getfield(*value*, *name::Symbol*)
Extract a named field from a value of composite type. The syntax a.bcalls
getfield(a, :b), and the syntax a.(b) calls getfield(a, b).
but when I try the a.(b) variation, it errors (or it's me who errors?)
julia gmt_modules.write
?I,?O
julia gmt_modules.(write)
ERROR: type: getfield: expected Symbol, got Function
Re: [julia-users] Re: Is a.(b) valid?
dynamic names can be handy, but they are also quite slow.
symbol(string(nomes[1])) === nomes[1]
On Mon, Mar 24, 2014 at 11:13 PM, J Luis jmfl...@gmail.com wrote:
Thanks
So this means we cannot do the dynamic names as in Matlab (where the b is
the member name)
BTW, I needed to extract the member name as a string to compare with another
string and the only way I got it done was with
julia nomes=names(MyType)
1-element Array{Symbol,1}:
:a
julia @sprintf(%s, nomes[1])
a
but don't know how to do it the other way around. Not that I need it now but
Matlab dynamic names are quite handy.
Terça-feira, 25 de Março de 2014 3:01:13 UTC, Sam L escreveu:
After some experimentation, it looks like second way takes a symbol or
variable who's value is a symbol.
julia type MyType; a::Int; end
julia x = MyType(3)
MyType(3)
julia x.a
3
julia x.(a)
ERROR: a not defined
julia x.(:a)
3
julia b = :a
:a
julia x.(b)
3
On Monday, March 24, 2014 7:46:38 PM UTC-7, J Luis wrote:
The doc of getfield says
getfield(value, name::Symbol)
Extract a named field from a value of composite type. The syntax a.b
calls
getfield(a, :b), and the syntax a.(b) calls getfield(a, b).
but when I try the a.(b) variation, it errors (or it's me who errors?)
julia gmt_modules.write
?I,?O
julia gmt_modules.(write)
ERROR: type: getfield: expected Symbol, got Function
[julia-users] Re: Calculus2: A new proposed interface for Calculus
On Sunday, March 23, 2014 11:29:37 PM UTC-7, Miles Lubin wrote: I like the unified interface for differentiation. My only qualm is with flattening out the hierarchy of packages by including DualNumbers. There was some discussion on this here: https://github.com/johnmyleswhite/Calculus.jl/pull/44 To start out, what is the intended scope of Calculus.jl? Once you start getting into including automatic differentiation it opens up a whole can of worms. For example, why swallow up DualNumbers and not PowerSeries? What about reverse mode for gradients and Hessians? There are too many different approaches, and I don't think they all belong under one package. We're using DualNumbers now because it's stable and mostly just works, but we should be leaving room for future developments. Proposal: 1. Low-level package (SymbolicDerivatives.jl?) that exports a table of symbolic derivatives that can be shared among different implementations. gradexpr and hessexpr can go here too. 2. Differentiation packages: DualNumbers, PowerSeries, ReverseDiffOverload, ReverseDiffSparse, ReverseDiffSource, etc. 3. Unified interface like the one implemented in Calculus2 with grad/hess. (Call this Derivatives.jl?) I think this is a great idea. The same thing occurred to me as I was writing PowerSeries. I would like to get the derivative definitions in that package merged in with the rest of them so that there is only one big list of derivatives to maintain and test (or at least one fewer). On Sunday, March 23, 2014 1:28:03 PM UTC-4, John Myles White wrote: I recently had a project where I made heavy use of the Calculus package and found that the interface has really fallen out of sync with the functionality that’s available. I also found myself wanting to have easier access to forward-mode automatic differentation. So I wrote up a variant of the Calculus package, which I’m calling Calculus2, to provide a demonstration of a new interface that I’d like to propose for the Calculus package. You can try the new interface here: https://github.com/johnmyleswhite/Calculus2.jl This package takes the old Calculus code and cleans it up, but also fully incorporates the DualNumbers package, so that you can switch between many different styles of differentiation using two keyword arguments: using Calculus2 grad(sin, 1.0, method = :finite) grad(sin, 1.0, method = :finite, direction = :complex) grad(sin, 1.0, method = :ad) hess(sin, 1.0, method = :finite) I’d be really interested to see if people think this interface is worth pursuing. I’m hopeful that this interface or something similar can help to surface all of the useful functionality that’s been hidden inside of the Calculus package. — John
[julia-users] Re: Julia package style / learning
Thanks for the discussion and thanks to JMW for the pull request! On Sunday, March 23, 2014 9:42:19 PM UTC-7, Ryan Gehring wrote: Hey all, I decided to start learning Julia over the weekend and am having fun so far. I implemented the wikipedia single layer perceptron algorithm as well as kendall's tau to see what it would be like to develop a medium sized package in the language. Link to the repo is below (the title just popped into my head there's no amazing product or grand plan meant by the name.) https://github.com/rgehring/SimpleNets As a student of the language I'd love to hear anyone's thoughts on any style issues or mistakes they see, I'm sure there are plenty. Here are some things I think I did wrong right off the top of my head... - Submodule importing. In src/util/association_measures.jl I wanted to just expose KendallsTau.kendallstau as AssociationMeasures.kendallstau and I think I should have used import rather than include / using ? - Test inclusion strategy: I thought it would make sense to have a unit test file for every src file and to import the src file at the top of each test, but this makes the tests brittle to directory changes, is it a better idea to include all the files in test_runner.jl? - Excessively specific typing and casting to ints and floats. - Arrays of Arrays - should I have used matrices or the native multidimensional array structure? Here are some things that I think might be good: - Tried to keep a reasonable degree of abstraction on all the files, although I may have been too heavy on the use of submodules. - Test coverage + a (very basic) actual statistical validation script for the algorithms. - Tried to be explicit about public API's to the submodules. I may have carried this too far with src/util/association_measures.jl which is basically an interface module designed to only expose the public API's of each included submodule (presently only KendallsTau). I'm potentially interested in contributing to the codebase as a way to keep learning, does anyone have any small, bite-sized github issues they'd be interested in help with or seeing a pull request for?
