date:20150413

It's kind of unclear what you're trying to do. Are you printing an array
and the repl hangs?

On Mon, Apr 13, 2015 at 10:49 PM, Siyi Deng mr.siyi.d...@gmail.com wrote:

 Hi, I have a coefficient array which looks like b =
 [4.67933552111843e-07,-6.32591924726271e-05,-0.000160070579209537, ],
 with about 320 elements. The entire array in ascii is about 7000 chars.

 I cannot paste the array directly in REPL, julia simply stuck. I cannot
 put it in a script and include it, also stuck the session.

 Is this a known issue? What shall I do to get my coefficients?

Re: [julia-users] Re: Speeding up indexing into a Dict{Vector,Vector}

If you want to have the original mutable vector around, you may want to
keep it as a value instead of a key. You can do something like map the
Vector{Int} to a single Int value, use that as a key and then keep the
Vector{Int} as part of the Dict value.

On Mon, Apr 13, 2015 at 6:06 PM, Seth catch...@bromberger.com wrote:

 Two ideas that *might* work:

 1) is hashing the key - that is, if you can represent the Vector{Int} as
 an immutable type (say, by somehow quickly changing it into an Int64 or
 Int128, perhaps using hash()) then you store the computed result as the
 key. The thing to keep in mind here is that if you mutate the vector, you
 will mutate the hash as well. That is likely what you want, but it's good
 to be explicit. You will also not be able to go back unless you create a
 separate dict with the hash values as a key and the Vector{Int} as the
 value.

 2) is creating two data structures: one is a Vector{Vector{Int}}, the
 other a Dict{Int, Vector{Float64}}. The index of the first data structure
 is the key of the second, and it should be* faster to check the former
 against a given vector then going through a dict. Unlike #1, the index will
 NOT change if you mutate the inner vector.




 On Monday, April 13, 2015 at 1:56:55 PM UTC-7, Will Kearney wrote:

 I'm hoping I can get some advice on optimizing some code.

 I have a data structure which is very conveniently represented as a
 Dict{Vector{Int},Vector{Float64}}. That is, I need to look up
 floating-point vectors stored at certain multidimensional (usually 2-10)
 positions represented as a Vector{Int}. Before I construct this Dict, I
 don't have a priori knowledge of what position vectors will be represented.

 I'm aware of the problems of using mutable objects as Dict keys, but
 let's assume that's not really an issue.

 Profiling reveals that the real time sink is testing arrays for equality
 when indexing into this data structure, and indexing happens very
 frequently. What would be a good way to speed this process up?

 Is there a way to represent the keys which will be cheaper to compare? I
 could convert the keys to tuples, but it's helpful to have them as mutable
 arrays to do some calculations with them at certain points.

 Is there a different data structure which might work better? Should I
 roll my own hash table implementation which is particularly optimized for
 vector keys?

Re: [julia-users] Re: :(::) rather than Symbol in args[1] in :lambda Expr for cartesianarray

2015-04-13 Thread Isaiah Norton


 This shows the first lambda arg again as :(j::Any) of type :(::).  In my
 real code, it was at least figuring out in the second lambda arg to type
 j as {:j,Int64,0} but in this example it doesn't even figure out that j
 has to be of some Unsigned type and punts back to Any ({:j, Any, 0}).


I'm not sure I follow -- I don't see any type annotation of `:(::)`.
However, more generally, there are currently some (known) limitations of
Julia's type inference for anonymous functions. A do-block creates an
anonymous function, so I would guess that is the underlying issue with the
inferred types here.

(By the way, have you seen the Cartesian macros in base?
http://julia.readthedocs.org/en/release-0.3/devdocs/cartesian/)

On Mon, Apr 13, 2015 at 7:46 PM, Todd Anderson drtod...@comcast.net wrote:

 Here's a small example:

 function nef(weights, input_B)
 delta_B = cartesianarray(Float64, (input_B),) do j
 sum(weights[spikes_A, j])
   end
 end

 ct = code_typed(nef, (Array{Float64,2}, Int64))

 println(ct)

 Here's the output:

 {:($(Expr(:lambda, {:weights,:input_B},
 {{:#s2,:delta_B},{{:weights,Array{Float64,2},1},{:input_B,Int64,0},{:#s2,Any,18},{:delta_B,Any,18}},{}},
 :(begin
 #s2 = cartesianarray(AST(:($(Expr(:lambda, {:(j::Any)},
 {{},{{:j,Any,0}},{{:weights,Array{Float64,2},1}}}, :(begin  #
 /mnt/home/taanders/pse-hpc/benchmarks2/nengo/ex2.jl, line 3:
 return sum(getindex(weights,spikes_A,j))
 end),Float64,input_B::Int64)
 delta_B = #s2
 return #s2
 end}

 This shows the first lambda arg again as :(j::Any) of type :(::).  In my
 real code, it was at least figuring out in the second lambda arg to type
 j as {:j,Int64,0} but in this example it doesn't even figure out that j
 has to be of some Unsigned type and punts back to Any ({:j, Any, 0}).

[julia-users] Julia stuck at large floating point number array from source code

Hi, I have a coefficient array which looks like b = 
[4.67933552111843e-07,-6.32591924726271e-05,-0.000160070579209537, ], 
with about 320 elements. The entire array in ascii is about 7000 chars. 

I cannot paste the array directly in REPL, julia simply stuck. I cannot put 
it in a script and include it, also stuck the session.

Is this a known issue? What shall I do to get my coefficients?

Re: [julia-users] Using Cartesian to define multidimensional convolution

2015-04-13 Thread Tim Holy

By the way, you can do this more easily now, without macros, like this:

for IA in CartesianRange(size(A))
for IB in CartesianRange(size(B))
ret[IA+IB] = A[IA] * B[IB]
end
end

--Tim

On Monday, April 13, 2015 08:05:15 AM Derek Thomas wrote:
 Hi all,
 
 I'm trying to implement a multidimensional convolution defined like this in
 2d:
 
 We initialize to zero a matrix c and add to it, starting at the (i,j)th
 position, submatrices b[i, j] * a[:, :] padded with zeros.
 
 I have this function:
 stagedfunction convn{T,N}(A::Array{T,N}, B::Array{T,N})
 quote
 retsize = [size(A)...] + [size(B)...]
 retsize = tuple(retsize...)
 ret = zeros(T, retsize)
 @nloops $N i A begin
 @nloops $N j B begin
 (@nref $N ret k-(i_d + j_d)) = (@nref A i) * (@nref B j)
 end
 end
 return ret
 end
 end
 
 but I'm getting a cryptic ERROR: wrong number of arguments message to this
 input
 
 A = randn(5, 5)
 
 convn(A, A)
 
 Any help is appreciated.  Thanks,
 
 Derek

Re: [julia-users] Using Cartesian to define multidimensional convolution

2015-04-13 Thread Derek Thomas

Thanks.  I noticed that right after I posted but couldn't find my post to 
fix it.  Here's a working version

using Base.Cartesian
stagedfunction convn{T,N}(A::Array{T,N}, B::Array{T,N})
quote
retsize = [size(A)...] + [size(B)...] - 1
retsize = tuple(retsize...)
ret = zeros(T, retsize)
@nloops $N i A begin
@nloops $N j B begin
(@nref $N ret d-(i_d + j_d - 1)) += (@nref $N A i) * 
(@nref $N B j)
end
end
return ret
end
end


On Monday, April 13, 2015 at 8:06:08 PM UTC-5, Tim Holy wrote:

 You forgot the $N on the two @nref on the right hand side: 

 On Monday, April 13, 2015 08:05:15 AM Derek Thomas wrote: 
  (@nref $N ret k-(i_d + j_d)) = (@nref A i) * (@nref B 
 j) 

 --Tim

Re: [julia-users] Infinite Dimensional Vectors

Hard to say what underlying data structure you want here, but it may well
be helpful for the keys to be lexicographically ordered – you may want to
try a SortedDict as provided by the DataStructures
https://github.com/JuliaLang/DataStructures.jl package. You may also want
to define a WordVector type that can wrap arbitrary
Associative{UTF8String,Int} structures and provides a default value of
zero, has methods for various vector operations and norms and such. You may
also want to look at the TextAnalysis
https://github.com/johnmyleswhite/TextAnalysis.jl package.

On Mon, Apr 13, 2015 at 4:41 PM, Mark Tabor mtab...@slu.edu wrote:

 Hello All,

 I am looking for an efficient way to represent vectors that exist in an
 infinite dimensional space.  Specifically I am working with large amounts
 of text data and will be receiving a lot of data that contains previously
 unseen words.  Each text represents a vector that exists in the space of
 all possible strings and each word in the text represents a dimension.  As
 such these vectors are extremely sparse.  Currently we handle this by using
 a dictionary to represent each text as a bag of words
 http://en.wikipedia.org/wiki/Bag-of-words_model vector.  If a word does
 not exist in the vector we return zero.  This allows use to perform
 computations as so:

 [the=3,and=2,is=4] + [this=5,was=1,where=6] =
 [where=6,the=3,is=4,this=5,was=1,and=2]

 euclidean([the=3,and=2,is=4], [this=5,was=1,where=6]) =
 9.539392014169456

 Is a dictionary the proper associative structure, or should we use a
 different data structure like a JudyArray or Trie?

 -MT

Re: [julia-users] Julia stuck at large floating point number array from source code

2015-04-13 Thread Jacob Quinn

Can you share the script? It's hard to troubleshoot this kind of problem
without seeing exactly what you're running.

On Mon, Apr 13, 2015 at 9:37 PM, Siyi Deng mr.siyi.d...@gmail.com wrote:

 No, I'm copy and pasting the array, from a text editor to the REPL, and it
 hangs there.

 On Monday, April 13, 2015 at 7:53:29 PM UTC-7, Stefan Karpinski wrote:

 It's kind of unclear what you're trying to do. Are you printing an array
 and the repl hangs?

 On Mon, Apr 13, 2015 at 10:49 PM, Siyi Deng mr.siy...@gmail.com wrote:

 Hi, I have a coefficient array which looks like b =
 [4.67933552111843e-07,-6.32591924726271e-05,-0.000160070579209537,
 ], with about 320 elements. The entire array in ascii is about 7000
 chars.

 I cannot paste the array directly in REPL, julia simply stuck. I cannot
 put it in a script and include it, also stuck the session.

 Is this a known issue? What shall I do to get my coefficients?

Re: [julia-users] Julia stuck at large floating point number array from source code

Hi, my array as follows:


b = 
[4.67933552111843e-07,-6.32591924726271e-05,-0.000160070579209537,-0.000332845978767382,-0.000588690359282295,
 

-0.000924685049847179,-0.00131849652730193,-0.00172663844738962,-0.00208786977252048,-0.00233221212288082,
 

-0.00239463249655303,-0.00223084413415438,-0.00183153503523871,-0.00123096220524368,-0.000506656901088092,
 

0.000231273247512499,0.000860169184825533,0.00127049209181452,0.00139133627405064,0.00120931235016613,
 

0.000775243960106711,0.000195783532681523,-0.000389333441868186,-0.000839715315002484,-0.00104874482507810,
 

-0.000971082976220408,-0.000635588269858116,-0.000139316676086390,0.000376823211516953,0.000765144786939901,
 

0.000911381735418337,0.000767069729306576,0.000364716481529794,-0.000189255166775865,-0.000742853249617161,
 

-0.00114090399749477,-0.00126989294326956,-0.00109238473975333,-0.000660599971040823,-0.000104137167563394,
 

0.000405603863401683,0.000704810151823340,0.000686449793195227,0.000334652310940532,-0.000266860012267053,
 

-0.000955811497614575,-0.00153703335145101,-0.00184017465821164,-0.00177248602611196,-0.00135043224798997,
 

-0.000699772991238628,-2.20952367649259e-05,0.000463080417609062,0.000584671530928735,0.000274639234341784,
 

-0.000406253385432046,-0.00128088558535365,-0.00210457446485342,-0.00263694553018369,-0.00271607763844648,
 

-0.00231211432643654,-0.00154295258453597,-0.000645162310074997,9.30623752723795e-05,0.000418248208810247,
 

0.000191535169468778,-0.000562773863174475,-0.00165664584627324,-0.00278826438187876,-0.00362966080543623,
 

-0.00392678199601546,-0.00358172954744133,-0.00269079897606094,-0.00152435244151553,-0.000451787547517668,
 

0.000167885370887781,9.77532529617552e-05,-0.000697522948378624,-0.00203068838350111,-0.00353881580196248,
 

-0.00478700223086237,-0.00539960290566932,-0.00517967374898320,-0.00417899466767010,-0.00269445536778436,
 

-0.00118825003033828,-0.000152730366029521,4.08989266963567e-05,-0.000736069064388297,-0.00231761657719439,
 

-0.00427961363828440,-0.00605844774593019,-0.00711896455145624,-0.00712217721790469,-0.00604060957165538,
 

-0.00418280179774257,-0.00211471511846733,-0.000497104824650714,0.000115009784236061,-0.000549582574749379,
 

-0.00237902012751033,-0.00489297896606703,-0.00737250869105017,-0.00907094519283787,-0.00944469951647819,
 

-0.0082955737742,-0.00603030886114787,-0.00321654433831640,-0.000769870161381384,0.000497241843209471,
 

9.42673474216162e-05,-0.0019763469977,-0.0051916587014,-0.00864083031861910,-0.0112859793931032,
 

-0.012268458734,-0.0112312476909986,-0.00837390013709095,-0.00451267862397702,-0.000818957743044659,
 

0.00151305882838224,0.00163675539214858,-0.000660398517845471,-0.00484819866174476,-0.00976807860243673,
 

-0.0139500017269034,-0.0160478371765713,-0.0152671906488912,-0.0116534872041850,-0.00614172383099131,
 

-0.000335212041994754,0.00393904297918806,0.00517924921134713,0.00270245065682847,-0.00307207700391787,
 

-0.0106530390555229,-0.0178381403614641,-0.0223253306966040,-0.0224124046400330,-0.0175833758777929,
 

-0.00879634423103870,0.00164096711938262,0.0106118431964252,0.0150317893165007,0.0127790454275655,
 

0.00345979321865954,-0.0112219144884763,-0.0276295433851027,-0.0409003922756233,-0.0460536030548546,
 

-0.0392442385172429,-0.0188523667724536,0.0138805014852943,0.0548558827557978,0.0977996803069081,
 

0.135488956158212,0.161253124368556,0.170403259362864,0.161253124368556,0.135488956158212,0.0977996803069081,
 

0.0548558827557978,0.0138805014852943,-0.0188523667724536,-0.0392442385172429,-0.0460536030548546,
 

-0.0409003922756233,-0.0276295433851027,-0.0112219144884763,0.00345979321865954,0.0127790454275655,
 

0.0150317893165007,0.0106118431964252,0.00164096711938262,-0.00879634423103870,-0.0175833758777929,
 

-0.0224124046400330,-0.0223253306966040,-0.0178381403614641,-0.0106530390555229,-0.00307207700391787,
 

0.00270245065682847,0.00517924921134713,0.00393904297918806,-0.000335212041994754,-0.00614172383099131,
 

-0.0116534872041850,-0.0152671906488912,-0.0160478371765713,-0.0139500017269034,-0.00976807860243673,
 

-0.00484819866174476,-0.000660398517845471,0.00163675539214858,0.00151305882838224,-0.000818957743044659,
 

-0.00451267862397702,-0.00837390013709095,-0.0112312476909986,-0.012268458734,-0.0112859793931032,
 

-0.00864083031861910,-0.0051916587014,-0.0019763469977,9.42673474216162e-05,0.000497241843209471,
 

-0.000769870161381384,-0.00321654433831640,-0.00603030886114787,-0.0082955737742,-0.00944469951647819,
 

-0.00907094519283787,-0.00737250869105017,-0.00489297896606703,-0.00237902012751033,-0.000549582574749379,
 

0.000115009784236061,-0.000497104824650714,-0.00211471511846733,-0.00418280179774257,-0.00604060957165538,

Re: [julia-users] Re: Julia installation issue

2015-04-13 Thread Isaiah Norton

Thanks for following up with the answer! I'm sure others will find this
helpful.

On Tue, Apr 14, 2015 at 12:30 AM, Yudong Ma mayud...@gmail.com wrote:

 It turns out I have to update R to the latest version. Older version R is
 not compatible with the updated version of libpcre3 (v1:8.30) shipped
 with Julia.
 I have included the link as follow.

 https://www.mail-archive.com/debian-bugs-dist@lists.debian.org/msg1006573.html

 Hopefully this is useful for any user who has this issue too.
 Best.


 On Monday, April 13, 2015 at 4:37:54 PM UTC-7, Yudong Ma wrote:

 Hi
 I am very new to Julia, and I have encountered an installation issue of
 Julia.
 I did successfully install Julia in my Ubuntu precise.
 However it seems Julia also updated libpcre3, libpcrecpp2, libpcre3-dev
 etc..., and these updates broke my original R installation (R installed as
 a shared library)
 After the installation of Julia, /usr/lib/libR.so is complaining that the
 symbol _pcre_valid_utf8 is undefined.

 I am wondering does anyone else have had this problems, and how can I
 resolve this?
 Best Regards

[julia-users] Re: Julia installation issue

2015-04-13 Thread Yudong Ma

It turns out I have to update R to the latest version. Older version R is 
not compatible with the updated version of libpcre3 (v1:8.30) shipped with 
Julia.
I have included the link as follow.
https://www.mail-archive.com/debian-bugs-dist@lists.debian.org/msg1006573.html

Hopefully this is useful for any user who has this issue too.
Best.

On Monday, April 13, 2015 at 4:37:54 PM UTC-7, Yudong Ma wrote:

 Hi 
 I am very new to Julia, and I have encountered an installation issue of 
 Julia.
 I did successfully install Julia in my Ubuntu precise.
 However it seems Julia also updated libpcre3, libpcrecpp2, libpcre3-dev 
 etc..., and these updates broke my original R installation (R installed as 
 a shared library)
 After the installation of Julia, /usr/lib/libR.so is complaining that the 
 symbol _pcre_valid_utf8 is undefined.

 I am wondering does anyone else have had this problems, and how can I 
 resolve this?
 Best Regards

Re: [julia-users] Julia stuck at large floating point number array from source code

2015-04-13 Thread Isaiah Norton

Are you using Windows? Pasting into the REPL there is especially bad, but
`include` should work fine (and I just tested it). I also pasted this array
into a putty session to a linux box and it only took a few seconds (due to
putty not Julia, pretty sure it would be instant in a local login).

I cannot put it in a script and include it, also stuck the session.


Can you explain why not?

On Tue, Apr 14, 2015 at 12:36 AM, Siyi Deng mr.siyi.d...@gmail.com wrote:

 Hi, my array as follows:


 b =
 [4.67933552111843e-07,-6.32591924726271e-05,-0.000160070579209537,-0.000332845978767382,-0.000588690359282295,

 -0.000924685049847179,-0.00131849652730193,-0.00172663844738962,-0.00208786977252048,-0.00233221212288082,

 -0.00239463249655303,-0.00223084413415438,-0.00183153503523871,-0.00123096220524368,-0.000506656901088092,

 0.000231273247512499,0.000860169184825533,0.00127049209181452,0.00139133627405064,0.00120931235016613,

 0.000775243960106711,0.000195783532681523,-0.000389333441868186,-0.000839715315002484,-0.00104874482507810,

 -0.000971082976220408,-0.000635588269858116,-0.000139316676086390,0.000376823211516953,0.000765144786939901,

 0.000911381735418337,0.000767069729306576,0.000364716481529794,-0.000189255166775865,-0.000742853249617161,

 -0.00114090399749477,-0.00126989294326956,-0.00109238473975333,-0.000660599971040823,-0.000104137167563394,

 0.000405603863401683,0.000704810151823340,0.000686449793195227,0.000334652310940532,-0.000266860012267053,

 -0.000955811497614575,-0.00153703335145101,-0.00184017465821164,-0.00177248602611196,-0.00135043224798997,

 -0.000699772991238628,-2.20952367649259e-05,0.000463080417609062,0.000584671530928735,0.000274639234341784,

 -0.000406253385432046,-0.00128088558535365,-0.00210457446485342,-0.00263694553018369,-0.00271607763844648,

 -0.00231211432643654,-0.00154295258453597,-0.000645162310074997,9.30623752723795e-05,0.000418248208810247,

 0.000191535169468778,-0.000562773863174475,-0.00165664584627324,-0.00278826438187876,-0.00362966080543623,

 -0.00392678199601546,-0.00358172954744133,-0.00269079897606094,-0.00152435244151553,-0.000451787547517668,

 0.000167885370887781,9.77532529617552e-05,-0.000697522948378624,-0.00203068838350111,-0.00353881580196248,

 -0.00478700223086237,-0.00539960290566932,-0.00517967374898320,-0.00417899466767010,-0.00269445536778436,

 -0.00118825003033828,-0.000152730366029521,4.08989266963567e-05,-0.000736069064388297,-0.00231761657719439,

 -0.00427961363828440,-0.00605844774593019,-0.00711896455145624,-0.00712217721790469,-0.00604060957165538,

 -0.00418280179774257,-0.00211471511846733,-0.000497104824650714,0.000115009784236061,-0.000549582574749379,

 -0.00237902012751033,-0.00489297896606703,-0.00737250869105017,-0.00907094519283787,-0.00944469951647819,

 -0.0082955737742,-0.00603030886114787,-0.00321654433831640,-0.000769870161381384,0.000497241843209471,

 9.42673474216162e-05,-0.0019763469977,-0.0051916587014,-0.00864083031861910,-0.0112859793931032,

 -0.012268458734,-0.0112312476909986,-0.00837390013709095,-0.00451267862397702,-0.000818957743044659,

 0.00151305882838224,0.00163675539214858,-0.000660398517845471,-0.00484819866174476,-0.00976807860243673,

 -0.0139500017269034,-0.0160478371765713,-0.0152671906488912,-0.0116534872041850,-0.00614172383099131,

 -0.000335212041994754,0.00393904297918806,0.00517924921134713,0.00270245065682847,-0.00307207700391787,

 -0.0106530390555229,-0.0178381403614641,-0.0223253306966040,-0.0224124046400330,-0.0175833758777929,

 -0.00879634423103870,0.00164096711938262,0.0106118431964252,0.0150317893165007,0.0127790454275655,

 0.00345979321865954,-0.0112219144884763,-0.0276295433851027,-0.0409003922756233,-0.0460536030548546,

 -0.0392442385172429,-0.0188523667724536,0.0138805014852943,0.0548558827557978,0.0977996803069081,

 0.135488956158212,0.161253124368556,0.170403259362864,0.161253124368556,0.135488956158212,0.0977996803069081,

 0.0548558827557978,0.0138805014852943,-0.0188523667724536,-0.0392442385172429,-0.0460536030548546,

 -0.0409003922756233,-0.0276295433851027,-0.0112219144884763,0.00345979321865954,0.0127790454275655,

 0.0150317893165007,0.0106118431964252,0.00164096711938262,-0.00879634423103870,-0.0175833758777929,

 -0.0224124046400330,-0.0223253306966040,-0.0178381403614641,-0.0106530390555229,-0.00307207700391787,

 0.00270245065682847,0.00517924921134713,0.00393904297918806,-0.000335212041994754,-0.00614172383099131,

 -0.0116534872041850,-0.0152671906488912,-0.0160478371765713,-0.0139500017269034,-0.00976807860243673,

 -0.00484819866174476,-0.000660398517845471,0.00163675539214858,0.00151305882838224,-0.000818957743044659,

 -0.00451267862397702,-0.00837390013709095,-0.0112312476909986,-0.012268458734,-0.0112859793931032,

 -0.00864083031861910,-0.0051916587014,-0.0019763469977,9.42673474216162e-05,0.000497241843209471,

 -0.000769870161381384,-0.00321654433831640,-0.00603030886114787,-0.0082955737742,-0.00944469951647819,

Re: [julia-users] Julia stuck at large floating point number array from source code

Yes I am using windows. Is there a way to help the pasting issue? because 
it severely limits the usefulness of REPL if you cannot paste directly into 
it.Including this array in a script hanged for me the first time I 
tried (was like  2 minutes). But seems to be working fine when I tested it 
again separately, so I guess it was because of other parts of my script, 
not the array.

On Monday, April 13, 2015 at 9:51:54 PM UTC-7, Isaiah wrote:

 Are you using Windows? Pasting into the REPL there is especially bad, but 
 `include` should work fine (and I just tested it). I also pasted this array 
 into a putty session to a linux box and it only took a few seconds (due to 
 putty not Julia, pretty sure it would be instant in a local login).

 I cannot put it in a script and include it, also stuck the session.


 Can you explain why not? 

 On Tue, Apr 14, 2015 at 12:36 AM, Siyi Deng mr.siy...@gmail.com 
 javascript: wrote:

 Hi, my array as follows:


 b = 
 [4.67933552111843e-07,-6.32591924726271e-05,-0.000160070579209537,-0.000332845978767382,-0.000588690359282295,
  
 
 -0.000924685049847179,-0.00131849652730193,-0.00172663844738962,-0.00208786977252048,-0.00233221212288082,
  
 
 -0.00239463249655303,-0.00223084413415438,-0.00183153503523871,-0.00123096220524368,-0.000506656901088092,
  
 
 0.000231273247512499,0.000860169184825533,0.00127049209181452,0.00139133627405064,0.00120931235016613,
  
 
 0.000775243960106711,0.000195783532681523,-0.000389333441868186,-0.000839715315002484,-0.00104874482507810,
  
 
 -0.000971082976220408,-0.000635588269858116,-0.000139316676086390,0.000376823211516953,0.000765144786939901,
  
 
 0.000911381735418337,0.000767069729306576,0.000364716481529794,-0.000189255166775865,-0.000742853249617161,
  
 
 -0.00114090399749477,-0.00126989294326956,-0.00109238473975333,-0.000660599971040823,-0.000104137167563394,
  
 
 0.000405603863401683,0.000704810151823340,0.000686449793195227,0.000334652310940532,-0.000266860012267053,
  
 
 -0.000955811497614575,-0.00153703335145101,-0.00184017465821164,-0.00177248602611196,-0.00135043224798997,
  
 
 -0.000699772991238628,-2.20952367649259e-05,0.000463080417609062,0.000584671530928735,0.000274639234341784,
  
 
 -0.000406253385432046,-0.00128088558535365,-0.00210457446485342,-0.00263694553018369,-0.00271607763844648,
  
 
 -0.00231211432643654,-0.00154295258453597,-0.000645162310074997,9.30623752723795e-05,0.000418248208810247,
  
 
 0.000191535169468778,-0.000562773863174475,-0.00165664584627324,-0.00278826438187876,-0.00362966080543623,
  
 
 -0.00392678199601546,-0.00358172954744133,-0.00269079897606094,-0.00152435244151553,-0.000451787547517668,
  
 
 0.000167885370887781,9.77532529617552e-05,-0.000697522948378624,-0.00203068838350111,-0.00353881580196248,
  
 
 -0.00478700223086237,-0.00539960290566932,-0.00517967374898320,-0.00417899466767010,-0.00269445536778436,
  
 
 -0.00118825003033828,-0.000152730366029521,4.08989266963567e-05,-0.000736069064388297,-0.00231761657719439,
  
 
 -0.00427961363828440,-0.00605844774593019,-0.00711896455145624,-0.00712217721790469,-0.00604060957165538,
  
 
 -0.00418280179774257,-0.00211471511846733,-0.000497104824650714,0.000115009784236061,-0.000549582574749379,
  
 
 -0.00237902012751033,-0.00489297896606703,-0.00737250869105017,-0.00907094519283787,-0.00944469951647819,
  
 
 -0.0082955737742,-0.00603030886114787,-0.00321654433831640,-0.000769870161381384,0.000497241843209471,
  
 
 9.42673474216162e-05,-0.0019763469977,-0.0051916587014,-0.00864083031861910,-0.0112859793931032,
  
 
 -0.012268458734,-0.0112312476909986,-0.00837390013709095,-0.00451267862397702,-0.000818957743044659,
  
 
 0.00151305882838224,0.00163675539214858,-0.000660398517845471,-0.00484819866174476,-0.00976807860243673,
  
 
 -0.0139500017269034,-0.0160478371765713,-0.0152671906488912,-0.0116534872041850,-0.00614172383099131,
  
 
 -0.000335212041994754,0.00393904297918806,0.00517924921134713,0.00270245065682847,-0.00307207700391787,
  
 
 -0.0106530390555229,-0.0178381403614641,-0.0223253306966040,-0.0224124046400330,-0.0175833758777929,
  
 
 -0.00879634423103870,0.00164096711938262,0.0106118431964252,0.0150317893165007,0.0127790454275655,
  
 
 0.00345979321865954,-0.0112219144884763,-0.0276295433851027,-0.0409003922756233,-0.0460536030548546,
  
 
 -0.0392442385172429,-0.0188523667724536,0.0138805014852943,0.0548558827557978,0.0977996803069081,
  
 
 0.135488956158212,0.161253124368556,0.170403259362864,0.161253124368556,0.135488956158212,0.0977996803069081,
  
 
 0.0548558827557978,0.0138805014852943,-0.0188523667724536,-0.0392442385172429,-0.0460536030548546,
  
 
 -0.0409003922756233,-0.0276295433851027,-0.0112219144884763,0.00345979321865954,0.0127790454275655,

Re: [julia-users] Julia stuck at large floating point number array from source code

No, I'm copy and pasting the array, from a text editor to the REPL, and it 
hangs there.

On Monday, April 13, 2015 at 7:53:29 PM UTC-7, Stefan Karpinski wrote:

 It's kind of unclear what you're trying to do. Are you printing an array 
 and the repl hangs?

 On Mon, Apr 13, 2015 at 10:49 PM, Siyi Deng mr.siy...@gmail.com 
 javascript: wrote:

 Hi, I have a coefficient array which looks like b = 
 [4.67933552111843e-07,-6.32591924726271e-05,-0.000160070579209537, ], 
 with about 320 elements. The entire array in ascii is about 7000 chars. 

 I cannot paste the array directly in REPL, julia simply stuck. I cannot 
 put it in a script and include it, also stuck the session.

 Is this a known issue? What shall I do to get my coefficients?

[julia-users] Re: Advice on vectorizing functions

2015-04-13 Thread elextr



On Tuesday, April 14, 2015 at 9:40:49 AM UTC+10, SixString wrote:

 For code outside of my inner loops, I still prefer vectorized functions 
 for compactness and readability.

 This works:

 function ldexp!(x::Array{Float64}, e::Int)
 for i=1:length(x)
 x[i] = ldexp(x[i], e)
 end
 x
 end

 Why does this version result in complaints about no matching method for 
 (::Array(Float64,1), ::Int64)?  super(Float64) is FloatingPoint, and 
 ldexp() has methods for all subtypes of FloatingPoint paired with Int.


But Float64 : FloatingPoint does not imply Array{Float64} : 
Array{FloatingPoint}, 
see 
http://en.wikipedia.org/wiki/Covariance_and_contravariance_%28computer_science%29#Arrays
 
for why.

Cheers
Lex
 


 function ldexp!(x::Array{FloatingPoint}, e::Int)
 for i=1:length(x)
 x[i] = ldexp(x[i], e)
 end
 x
 end

[julia-users] Re: pre-allocation for sparse matrices

2015-04-13 Thread Kristoffer Carlsson

If you are overwriting all your previous values you can just send in the 
matrix into the function and update with A[i,j] = v



On Monday, April 13, 2015 at 6:47:21 PM UTC+2, Andrei Berceanu wrote:

 Yes but so how do I update it inplace?

 On Monday, April 13, 2015 at 5:37:50 PM UTC+2, Kristoffer Carlsson wrote:

 If you have the same sparse structures in your matrices then it should be 
 sufficient to to the IJV - CSC sparse matrix conversion only once and then 
 update A in place instead of generating a new IJV and converting to CSC 
 again and again.

Re: [julia-users] Re: ApproxFun First Order PDE Question

2015-04-13 Thread Dominic Steinitz

Thanks very much for this. I had assumed by specifying `\[f]` that I *had* 
given just one boundary condition. I tried your solution but ran into a problem 
which I have raised as a ticket as you suggest: 
https://github.com/ApproxFun/ApproxFun.jl/issues/159 
https://github.com/ApproxFun/ApproxFun.jl/issues/159

Dominic Steinitz
domi...@steinitz.org
http://idontgetoutmuch.wordpress.com

 On 13 Apr 2015, at 03:00, Sheehan Olver dlfivefi...@gmail.com wrote:
 
 You have too many boundary conditions: dirichlet conditions on a rectangle 
 defaults to conditions on all 4 sides.  Imposing on just the left side gives 
 an answer:
 
 d = domain(Fun(identity,[0.0,1.0]))
 f = Fun(x-exp(-x^2),d)
 D = Derivative(d)
 L = 2.0D⊗I+I⊗D
 u = [ldirichlet(d)⊗I,L]\[f]
 
 though you may need another boundary condition.  to get the answer you are 
 looking for. 
 
 PS I'm more likely to see this if you post it as a git issue on ApproxFun's 
 github page.
 
 
 On Sunday, April 12, 2015 at 12:10:24 AM UTC+10, idontgetoutmuch wrote:
 I am trying to solve a first order PDE to which I know the solution $2u_x + 
 u_y = 0$ with boundary condition $u(x,0) = exp{-x^2}$. The solution is 
 $exp{-(x-2t)^2}$. I have tried the code below
 
 Pkg.checkout(ApproxFun)
 
 using ApproxFun
 
 d = domain(Fun(identity,[0.0,1.0]))
 
 f = Fun(x-exp(-x^2),d)
 
 D = Derivative(d)
 
 L = 2.0D⊗I+I⊗D
 
 u = [dirichlet(d^2),L]\[f]
 
 
 but I get endless
 
 WARNING: Maximum number of iterations 10 reached
 WARNING: Maximum number of iterations 10 reached
 WARNING: Maximum number of iterations 10 reached
 
 Any help would be gratefully received.

Re: [julia-users] string processing after readdlm

2015-04-13 Thread JKpie

ok, here is the example:

a = Array{Float32}[]
push!(a,[1 2 3])
push!(a,[4 5 4])
push!(a,[7 8 9])
println(typeof(a))
writedlm(joinpath(path,text.txt),a)
b = readdlm(joinpath(path,text.txt))
println(typeof(b))
println(b[1,:])

the result is:

Array{Array{Float32,N},1}
Array{Any,2}
Any[Float32[1.0 2.0 3.0]]

and the same behawior here:

a = {}
push!(a,rand(5))
push!(a,rand(3))
push!(a,rand(7))
println(typeof(a))
writedlm(joinpath(path,text.txt),a)
b = readdlm(joinpath(path,text.txt))
println(typeof(b))
println(b[1,:])
println(typeof(b[1,1]))


and the result:

   - 
  - 
  - 
  - 
   

   - 
   
   - 
   
   - 
   
   
cljs

   

Array{Any,1} 
Array{Any,2}
Any[[0.054008985630280115,0.8947273976690304,0.14961853234717193,0.72895523733,0.8907801902141823]]
 
SubString{ASCIIString}

in both cases I would like to have a method to write the data and next to 
read it and have it with the same structure and types
(or just a function to process this substrings).

J



On Sunday, April 12, 2015 at 7:55:30 PM UTC+2, Mauro wrote:

 An example which can be copy-pasted would be helpful.  M 

 On Sun, 2015-04-12 at 16:47, JKpie fable...@gmail.com javascript: 
 wrote: 
  Hi, 
  
  I am new Julia coder (I started to learn Julia two weeks ago). I have a 
  problem with writedlm and readdlm functions. 
  I have an array of vectors: 
  
  Vector Array{Float32,N},4 
  
  When I try to save it using writedlm to txt file and next read that file 
  using readdlm I obtain a matrix: 
  
  Matrix Any, 4 
  
  which contains four substrings like: Float32[1,2,3... 
  
  so my question is: is there any simple way to convert that strings into 
  arrays of floats? 
  
  I also need to write and read files of Any type arrays which contains 
 float 
  vectors of different lengths. 
  
  Thank you very much for your help, 
  J

[julia-users] Problem with addprocs

2015-04-13 Thread John

I'm unable to add a remote instance using addprocs (or a machine file).

This works (without prompt):
ssh xxx.xxx.xxx.xxx

This command hangs with no output for the first minute:
addprocs([usern...@xxx.xxx.xxx.xxx])
Then after one minute, the following message appears:
Master process (id 1) could not connect within 60.0 seconds

This command works:
addprocs([username@mycurrenthostname])

Thanks in advance for your help!
John

[julia-users] how to test if object is a Vector{(Symbol,T)} with T : Real

Hi,

I had some code like

if isa(spec, Symbol)
  A[i,spec] = 1
elseif isa(spec, Vector{(Symbol,Float64)})
  @assert(isapprox(sum(map(x - x[2],spec)),1))
  for (obs,prob) = spec
A[i,obs] = prob
  end
else
  error(don't know how to parse $spec for aggregation)
end

but got bittenby a spec = [(:I,0),(:U,1)] which is valid for my problem,
so I realized I need to test for Real, not Float64.

If this was a method of a generic fuction, I could simply use T : Real
and then use Vector{(Symbol,T)} in the type signature --- but it isn't,
so I would be interested in how to test for the condition in the subject
line in an if branch.

isa(Vector{(Symbol,Real)}) won't work, my understanding is that this is
because of invariance.

Best,

Tamas

[julia-users] Re: Symbolic relations package

2015-04-13 Thread Marcus Appelros

How about Equations? It captures the main theme so that people scrolling 
through the list of packages will instantly gather its purpose. Any other 
suggestions or objections?

On Sunday, 12 April 2015 14:02:02 UTC+3, Marcus Appelros wrote:

 Am working on code to derive mathematical relations, its initial purpose 
 was in the field of non-commutative geometry however it appears to have 
 become generally useful, feels like a good idea if we make the base self 
 contained and release it as a separate package upon which more specialized 
 ones can be built.

 The code is here: https://github.com/jhlq/fys/tree/master/ncg
 quin@Nicol:~/fys/ncg$ julia -L equations -q

 Let's start from the top, the most recent file is matchers.jl which 
 currently contains one matcher function that checks if an equation matches 
 the pattern ax^2+bx+c=0. By writing such matchers (and introducing types 
 for new operators) the base can readily be extended to solve custom 
 equations. The quadratic matcher in action: 

 julia @time solve(:a*(:x*:y*:z)^2+:b*:y*:z*:x+:c,Function)[end] #the type 
 specifies which kind of operator to apply
 elapsed time: 1.779767594 seconds (426648608 bytes allocated, 25.89% gc 
 time)

 Equation(Expression({:x,:z,:y}),Expression({-1,:b,÷(Expression({2,:a})),:+,-1,Sqrt(Expression({:b,:b,:+,-4,:a,:c})),÷(Expression({2,:a}))}))

 The Equation type is specified in equations.jl, it has two fields, lhs and 
 rhs. The solve function when given an expression assumes it is the lhs of 
 an equation with rhs=0 and finds solutions by calling the matches function 
 which so far also accepts the Sqrt and Div types as ops, these types 
 implement their own simplify methods. The original matches passes terms and 
 factors from left to right:

 julia matches(:x+:y)
 6-element Array{Equation,1}:
  Equation(:y,Expression({-1,:x}))
  Equation(1,Expression({-1,:x,÷(:y)}))   
  Equation(0,Expression({-1,:x,:+,-1,:y}))
  Equation(:x,Expression({-1,:y}))
  Equation(1,Expression({-1,:y,÷(:x)}))   
  Equation(0,Expression({-1,:y,:+,-1,:x}))

 Now we descend into the base at common.jl. The function simplify is 
 essential and called everywhere (probably too manywhere), it resolves 
 nested expressions and sums it all up:

 julia ex=(:x+3+9*:x)^3

 Expression({Expression({:x,:+,3,:+,Expression({9,:x})}),Expression({Expression({:x,:+,3,:+,Expression({9,:x})}),Expression({:x,:+,3,:+,Expression({9,:x})})})})

 julia simex=simplify(ex)
 Expression({1000,:x,:x,:x,:+,900,:x,:x,:+,270,:x,:+,27})

 julia evaluate(ex,[:x=1])==evaluate(simex,[:x=1])
 true

 A crucial component of simplify is componify which is the trustable cookie 
 unwrapper (technical term), it extracts components without eating anyting:

 julia ex=:x-(:x-3)+(:y+3)^2

 Expression({:x,:+,-1,:x,:+,-1,-1,3,:+,Expression({Expression({:y,:+,3}),Expression({:y,:+,3})})})

 julia ex=componify(ex)
 Expression({:x,:+,-1,:x,:+,-1,-1,3,:+,:y,:y,:+,:y,3,:+,3,:y,:+,3,3})

 One final frequently used internal function is addparse, it returns an 
 array of arrays with factors. For many cases the iterative shorthand will 
 be sufficient:

 julia for term in ex;print(term);end
 {:x}{-1,:x}{-1,3}{:y,:y}{:y,3}{3,:y}{3,3}

 There are a whole host of additional details that optimization pros 
 presumably can have many field days, camping trips and holidays with. Will 
 continue nurturing these wines to climb toward quantum gravity and desire 
 the community to be involved so everyone is very welcome to hack away at 
 the jungle, add branches and tread the paths created.

 We have a choice to make, representing a structural birth for the code: 
 What shall this package be named?

Re: [julia-users] string processing after readdlm

Is that supposed to be a lot of blank lines or is there something missing
from the message?

On Mon, Apr 13, 2015 at 6:56 AM, JKpie fablekil...@gmail.com wrote:

 ok, here is the example:

 a = Array{Float32}[]
 push!(a,[1 2 3])
 push!(a,[4 5 4])
 push!(a,[7 8 9])
 println(typeof(a))
 writedlm(joinpath(path,text.txt),a)
 b = readdlm(joinpath(path,text.txt))
 println(typeof(b))
 println(b[1,:])

 the result is:

 Array{Array{Float32,N},1}
 Array{Any,2}
 Any[Float32[1.0 2.0 3.0]]

 and the same behawior here:

 a = {}
 push!(a,rand(5))
 push!(a,rand(3))
 push!(a,rand(7))
 println(typeof(a))
 writedlm(joinpath(path,text.txt),a)
 b = readdlm(joinpath(path,text.txt))
 println(typeof(b))
 println(b[1,:])
 println(typeof(b[1,1]))


 and the result:

-
   -
   -
   -


-

-

-


 cljs



 Array{Any,1}
 Array{Any,2}

 Any[[0.054008985630280115,0.8947273976690304,0.14961853234717193,0.72895523733,0.8907801902141823]]
 SubString{ASCIIString}

 in both cases I would like to have a method to write the data and next to
 read it and have it with the same structure and types
 (or just a function to process this substrings).

 J



 On Sunday, April 12, 2015 at 7:55:30 PM UTC+2, Mauro wrote:

 An example which can be copy-pasted would be helpful.  M

 On Sun, 2015-04-12 at 16:47, JKpie fable...@gmail.com wrote:
  Hi,
 
  I am new Julia coder (I started to learn Julia two weeks ago). I have a
  problem with writedlm and readdlm functions.
  I have an array of vectors:
 
  Vector Array{Float32,N},4
 
  When I try to save it using writedlm to txt file and next read that
 file
  using readdlm I obtain a matrix:
 
  Matrix Any, 4
 
  which contains four substrings like: Float32[1,2,3...
 
  so my question is: is there any simple way to convert that strings into
  arrays of floats?
 
  I also need to write and read files of Any type arrays which contains
 float
  vectors of different lengths.
 
  Thank you very much for your help,
  J

[julia-users] how to test if object is a Vector{(Symbol,T)} with T : Real

2015-04-13 Thread Toivo Henningsson

You could make a typealias with a type parameter T for your type and check 
against that with isa.

[julia-users] Re: pre-allocation for sparse matrices

OK so I'm not sure how to directly access the CSC structure. 
Anyway, for clarity, here is the method which generates my sparse matrix. In 
a typical usage scenario, I need to generate and diagonalize a lot of these 
matrices, which are obtained varying the *s* Function.
I guess this qualifies as a low-order method?
















































































*function 
genspmat(l::Function,r::Function,u::Function,d::Function,s::Function, 
N::Int,nz::Int,α::Float64)# PreallocateI = Array(Int64,nz)J = 
Array(Int64,nz)V = Array(Complex{Float64},nz) function 
setnzelem(i::Int,n::Int,m::Int; pos::ASCIIString = self)if 
pos==leftk += 1J[k] = i-N; I[k] = i; V[k] = 
l(n,m,α)elseif pos==rightk += 1J[k] = 
i+N; I[k] = i; V[k] = r(n,m,α)elseif pos==upk += 
1J[k] = i-1; I[k] = i; V[k] = u(n,m,α)elseif 
pos==downk += 1J[k] = i+1; I[k] = i; V[k] = 
d(n,m,α)elseif pos==selfk += 1J[k] = i; 
I[k] = i; V[k] = s(n,m,α)endend# maximum value 
of m or n indicesmaxm = div(N-1,2) k = 0for i in 1:N^2m 
= getm(i,N)n = getn(i,N)setnzelem(i,n,m; pos=self)
#corners#top leftif n==maxm  m==-maxm
setnzelem(i,n,m; pos=right)setnzelem(i,n,m; 
pos=down)#top rightelseif n==maxm  m==maxm
setnzelem(i,n,m; pos=left)setnzelem(i,n,m; pos=down)
#bottom rightelseif n==-maxm  m==maxm 
setnzelem(i,n,m; pos=left)setnzelem(i,n,m; pos=up)
#bottom leftelseif n==-maxm  m==-maxm 
setnzelem(i,n,m; pos=right)setnzelem(i,n,m; pos=up)
#edges#topelseif n == maxmsetnzelem(i,n,m; 
pos=right)setnzelem(i,n,m; pos=left)
setnzelem(i,n,m; pos=down)#rightelseif m == 
maxmsetnzelem(i,n,m; pos=left)setnzelem(i,n,m; 
pos=up)setnzelem(i,n,m; pos=down)#bottom
elseif n == -maxmsetnzelem(i,n,m; pos=left)
setnzelem(i,n,m; pos=up)setnzelem(i,n,m; pos=right)
#leftelseif m == -maxmsetnzelem(i,n,m; 
pos=down)setnzelem(i,n,m; pos=up)
setnzelem(i,n,m; pos=right)else #bulksetnzelem(i,n,m; 
pos=down)setnzelem(i,n,m; pos=up)
setnzelem(i,n,m; pos=right)setnzelem(i,n,m; 
pos=left)endendreturn sparse(I,J,V)end*

On Friday, April 10, 2015 at 10:15:22 PM UTC+2, Christoph Ortner wrote:


 For example, for finite elements or finite differences, the connectivity 
 information gives you the sparsity pattern, which you could assemble once 
 and for all and then change the entries as needed. If it is a low-order 
 method, then you have few elements in each column and it would be very 
 efficient (and easy to implement) to make these changes by directly 
 accessing the CSC structure.

 Christoph

Re: [julia-users] string processing after readdlm

2015-04-13 Thread Mauro

I think you're expecting too much from writedlm/readdlm.  I don't think
it is all that useful beyond 2D arrays of simple datatype.  An array of
an array is not simple.  What it seems to be doing write a string
representation of `a` to the file:

repr(a)

You can recover its meaning with eval(parse(repr(a)))

b = readdlm(joinpath(path,text.txt), '\n')
b = map(x-eval(parse(x)), b)
  or
b= Array{Float32}[eval(parse(bb)) for bb in b]

However, it would be better, faster and safer to just a more powerful
file fromat like HDF5.jl.

On Mon, 2015-04-13 at 12:56, JKpie fablekil...@gmail.com wrote:
 ok, here is the example:

 a = Array{Float32}[]
 push!(a,[1 2 3])
 push!(a,[4 5 4])
 push!(a,[7 8 9])
 println(typeof(a))
 writedlm(joinpath(path,text.txt),a)
 b = readdlm(joinpath(path,text.txt))
 println(typeof(b))
 println(b[1,:])

 the result is:

 Array{Array{Float32,N},1}
 Array{Any,2}
 Any[Float32[1.0 2.0 3.0]]

 and the same behawior here:

 a = {}
 push!(a,rand(5))
 push!(a,rand(3))
 push!(a,rand(7))
 println(typeof(a))
 writedlm(joinpath(path,text.txt),a)
 b = readdlm(joinpath(path,text.txt))
 println(typeof(b))
 println(b[1,:])
 println(typeof(b[1,1]))


 and the result:

- 
   - 
   - 
   - 


- 

- 

- 


 cljs



 Array{Any,1} 
 Array{Any,2}
 Any[[0.054008985630280115,0.8947273976690304,0.14961853234717193,0.72895523733,0.8907801902141823]]
  
 SubString{ASCIIString}

 in both cases I would like to have a method to write the data and next to 
 read it and have it with the same structure and types
 (or just a function to process this substrings).

 J



 On Sunday, April 12, 2015 at 7:55:30 PM UTC+2, Mauro wrote:

 An example which can be copy-pasted would be helpful.  M 

 On Sun, 2015-04-12 at 16:47, JKpie fable...@gmail.com javascript: 
 wrote: 
  Hi, 
  
  I am new Julia coder (I started to learn Julia two weeks ago). I have a 
  problem with writedlm and readdlm functions. 
  I have an array of vectors: 
  
  Vector Array{Float32,N},4 
  
  When I try to save it using writedlm to txt file and next read that file 
  using readdlm I obtain a matrix: 
  
  Matrix Any, 4 
  
  which contains four substrings like: Float32[1,2,3... 
  
  so my question is: is there any simple way to convert that strings into 
  arrays of floats? 
  
  I also need to write and read files of Any type arrays which contains 
 float 
  vectors of different lengths. 
  
  Thank you very much for your help, 
  J

[julia-users] Re: Holt-Winters D-E Smoothing in Julia

2015-04-13 Thread Philip Tellis

On Saturday, April 11, 2015 at 1:19:39 AM UTC-4, colint...@gmail.com wrote:

 Great! If you decide to open source it when done then please feel free to 
 post a link into this thread or start a new thread on julia-stats as I for 
 one would definitely be interested.


Will do.

Re: [julia-users] how to test if object is a Vector{(Symbol,T)} with T : Real

2015-04-13 Thread Mauro


On Mon, 2015-04-13 at 16:22, Tamas Papp tkp...@gmail.com wrote:
 On Mon, Apr 13 2015, Mauro mauro...@runbox.com wrote:

 Why can you not make it into a function?

 function foo!(spec::Symbol, A, i)
 A[i,spec] = 1
 end
 function foo!{T:Real}(spec::Vector{(Symbol,T), A, i)
   @assert(isapprox(sum(map(x - x[2],spec)),1))
   for (obs,prob) = spec
 A[i,obs] = prob
   end
 A[i,spec] = 1
 end
 foo!(spec, A, i)  = error( ...)

 that way your code will be cleaner too:

 foo!(spec, A, i)

 Sure, I can do this, but since foo! would be used in one place only, I
 would consider this suboptimal design.

 In Julia, when you use an isa, then ask yourself whether it might not be
 cleaner using methods instead.

 I am not sure I understand the reasoning behind this. I find polluting
 the namespace with wrapping up trivial code that is used in exactly one
 place icky.

Then you have to use Toivo's trick or wait for
https://github.com/JuliaLang/julia/issues/8974 which should make this
possible (as far as I understand it).

I've used above approach and I like it.  If foo! is well named then
reading of the main function becomes much easier.

Re: [julia-users] Re: non-concatenating vector creation

This is perfect --- I think I will end up with something like

typealias NCA Any

and then I can use NCA[1,2,[3,4]] and later on remove NCA from my code
easily.

Thanks,

Tamas

On Mon, Apr 13 2015, Matt Bauman mbau...@gmail.com wrote:

 Is this what you're after?  I think this should still work after the 
 concatenation change is applied.

 julia Any[1,2,[3,4]]
 3-element Array{Any,1}:
  1
  2
   [3,4]


 On Monday, April 13, 2015 at 8:55:19 AM UTC-4, Tamas Papp wrote:

 Hi, 

 I have been following issue 7128 [1] and the related other issues, and 
 noticed that constructs like [1,2,[3,4]] give a warning in the dev 
 version I am using at the moment (v0.4.0-dev+4219), but I am wondering 
 if there is a construct that I can use for non-concatenating vector 
 creation _at the moment_, that is reasonably future-proof (eg it works 
 for a couple of months and when it does not, it fails with an error). 

 Best, 

 Tamas 

 [1] https://github.com/JuliaLang/julia/issues/7128

Re: [julia-users] how to test if object is a Vector{(Symbol,T)} with T : Real

On Mon, Apr 13 2015, Mauro mauro...@runbox.com wrote:

 Why can you not make it into a function?

 function foo!(spec::Symbol, A, i)
 A[i,spec] = 1
 end
 function foo!{T:Real}(spec::Vector{(Symbol,T), A, i)
   @assert(isapprox(sum(map(x - x[2],spec)),1))
   for (obs,prob) = spec
 A[i,obs] = prob
   end
 A[i,spec] = 1
 end
 foo!(spec, A, i)  = error( ...)

 that way your code will be cleaner too:

 foo!(spec, A, i)

Sure, I can do this, but since foo! would be used in one place only, I
would consider this suboptimal design.

 In Julia, when you use an isa, then ask yourself whether it might not be
 cleaner using methods instead.

I am not sure I understand the reasoning behind this. I find polluting
the namespace with wrapping up trivial code that is used in exactly one
place icky.

Best,

Tamas

[julia-users] Re: Problem with addprocs

2015-04-13 Thread John

Oops, let me clarify: mycurrenthostname is not the same computer 
as xxx.xxx.xxx.xxx, it's my local computer's name on the network, 
whereas xxx.xxx.xxx.xxx is remote.

On Monday, April 13, 2015 at 3:02:40 PM UTC+1, wil...@gmail.com wrote:

 This could be DNS issue. Try add 'mycurrenthostname xxx.xxx.xxx.xxx' to 
 the 'hosts' file.

 On Monday, April 13, 2015 at 6:10:11 AM UTC-4, John wrote:

 I'm unable to add a remote instance using addprocs (or a machine file).

 This works (without prompt):
 ssh xxx.xxx.xxx.xxx

 This command hangs with no output for the first minute:
 addprocs([usern...@xxx.xxx.xxx.xxx])
 Then after one minute, the following message appears:
 Master process (id 1) could not connect within 60.0 seconds

 This command works:
 addprocs([username@mycurrenthostname])

 Thanks in advance for your help!
 John

Re: [julia-users] Is the official name of the language Julia or julia?

2015-04-13 Thread cormullion

About that font:

Twitter discussion with Muthu Nedumaran:
https://twitter.com/typographica/status/572304422610452480

FontsInUse entry: 
http://fontsinuse.com/typefaces/38527/mn-latin

[julia-users] Re: non-concatenating vector creation

2015-04-13 Thread Matt Bauman

Is this what you're after?  I think this should still work after the 
concatenation change is applied.

julia Any[1,2,[3,4]]
3-element Array{Any,1}:
 1
 2
  [3,4]


On Monday, April 13, 2015 at 8:55:19 AM UTC-4, Tamas Papp wrote:

 Hi, 

 I have been following issue 7128 [1] and the related other issues, and 
 noticed that constructs like [1,2,[3,4]] give a warning in the dev 
 version I am using at the moment (v0.4.0-dev+4219), but I am wondering 
 if there is a construct that I can use for non-concatenating vector 
 creation _at the moment_, that is reasonably future-proof (eg it works 
 for a couple of months and when it does not, it fails with an error). 

 Best, 

 Tamas 

 [1] https://github.com/JuliaLang/julia/issues/7128

Re: [julia-users] how to test if object is a Vector{(Symbol,T)} with T : Real

2015-04-13 Thread Mauro

Why can you not make it into a function?

function foo!(spec::Symbol, A, i)
A[i,spec] = 1
end
function foo!{T:Real}(spec::Vector{(Symbol,T), A, i)
  @assert(isapprox(sum(map(x - x[2],spec)),1))
  for (obs,prob) = spec
A[i,obs] = prob
  end
A[i,spec] = 1
end
foo!(spec, A, i)  = error( ...)

that way your code will be cleaner too:

foo!(spec, A, i)

In Julia, when you use an isa, then ask yourself whether it might not be
cleaner using methods instead.

If that is not an option you have to make a function for the check...

On Mon, 2015-04-13 at 14:06, Tamas Papp tkp...@gmail.com wrote:
 Hi,

 I had some code like

 if isa(spec, Symbol)
   A[i,spec] = 1
 elseif isa(spec, Vector{(Symbol,Float64)})
   @assert(isapprox(sum(map(x - x[2],spec)),1))
   for (obs,prob) = spec
 A[i,obs] = prob
   end
 else
   error(don't know how to parse $spec for aggregation)
 end

 but got bittenby a spec = [(:I,0),(:U,1)] which is valid for my problem,
 so I realized I need to test for Real, not Float64.

 If this was a method of a generic fuction, I could simply use T : Real
 and then use Vector{(Symbol,T)} in the type signature --- but it isn't,
 so I would be interested in how to test for the condition in the subject
 line in an if branch.

 isa(Vector{(Symbol,Real)}) won't work, my understanding is that this is
 because of invariance.

 Best,

 Tamas

Re: [julia-users] how to test if object is a Vector{(Symbol,T)} with T : Real

Thanks. Is there a local solution that does not interfere with the
namespace?

Best,

Tamas

On Mon, Apr 13 2015, Toivo Henningsson toivo@gmail.com wrote:

 You could make a typealias with a type parameter T for your type and check 
 against that with isa.

Re: [julia-users] Re: in-place matrix division

The problem is, as I loop though my parameter space, I need to solve a lot 
of linear systems of the type \(A,B), where B stays the same but A changes 
depending on the parameters. Therefore a method that overwrites B doen't 
really help.

On Friday, April 10, 2015 at 6:19:34 PM UTC+2, Andreas Noack wrote:

 Yes. This has to be made more clear. The problem is that the libraries we 
 are using for sparse factorizations don't allow us to update b in place.

 2015-04-10 4:26 GMT-07:00 Kristoffer Carlsson kcarl...@gmail.com 
 javascript::

 I think it should be A_ldiv_B! however this seems inconcistent to me:

 julia a = rand(3,3); b = rand(3)
 3-element Array{Float64,1}:
  0.95134 
  0.43887 
  0.719551

 julia A_ldiv_B!(sparse(a), b) 
 3-element Array{Float64,1}:
  0.455667
  0.712479
  0.326213


 julia b # Note: b is not overwritten
 3-element Array{Float64,1}:
  0.95134 
  0.43887 
  0.719551


 julia A_ldiv_B!(lufact(a), b)
 3-element Array{Float64,1}:
  0.455667
  0.712479
  0.326213


 julia b # For this, b is overwritten
 3-element Array{Float64,1}:
  0.455667
  0.712479
  0.326213




 On Friday, April 10, 2015 at 11:19:45 AM UTC+2, Andrei Berceanu wrote:

 I am solving a linear system of the type A*X == B, where A is a sparse 
 matrix. I use the matrix division function
 \(*A*, *B*)

 Is there an in-place version of this function, where one can 
 pre-allocate the output X and then pass it, i.e.

 \!(A,B,X)

[julia-users] non-concatenating vector creation

Hi,

I have been following issue 7128 [1] and the related other issues, and
noticed that constructs like [1,2,[3,4]] give a warning in the dev
version I am using at the moment (v0.4.0-dev+4219), but I am wondering
if there is a construct that I can use for non-concatenating vector
creation _at the moment_, that is reasonably future-proof (eg it works
for a couple of months and when it does not, it fails with an error).

Best,

Tamas

[1] https://github.com/JuliaLang/julia/issues/7128

[julia-users] Re: Problem with addprocs

2015-04-13 Thread wildart

This could be DNS issue. Try add 'mycurrenthostname xxx.xxx.xxx.xxx' to the 
'hosts' file.

On Monday, April 13, 2015 at 6:10:11 AM UTC-4, John wrote:

 I'm unable to add a remote instance using addprocs (or a machine file).

 This works (without prompt):
 ssh xxx.xxx.xxx.xxx

 This command hangs with no output for the first minute:
 addprocs([usern...@xxx.xxx.xxx.xxx])
 Then after one minute, the following message appears:
 Master process (id 1) could not connect within 60.0 seconds

 This command works:
 addprocs([username@mycurrenthostname])

 Thanks in advance for your help!
 John

Re: [julia-users] code review: my first outer constructor :)

Hi Gabriel, thanks a lot for your reply!

(1) I use the WaveFunction type inside the Spectrum type, which as you can
see is a collection of wavefunctions. For a typical usage case, have a look
at
http://nbviewer.ipython.org/github/berceanu/topo-photon/blob/master/anc/exploratory.ipynb
I am not quite sure what you mean with defining a methods for the int
attribute.
(2) As you can see, the gauge is an attribute of the Spectrum type, which
is what I use in practice so I didn't see much point in storing it inside
every wavefunction. Do you have a suggestion for a better implementation?
In fact there are only these 2 gauge choices, landau and symmetric.
(3) P should be a Vector of length N^2, and I thought that declaring N to
be an int means implicit conversion as well - is that not so?
(4) genspmat generates the (sparse) matrix of the Hamiltonian, so
countnonzeros() simply counts beforehand how many nonzero elements there
will be in this sparse matrix. If you think of an NxN 2D lattice,
countnonzeros() simply counts the number of neighbours of each site (4 for
a center site, 3 for an edge site and 2 for a corner site).

What do you mean by irrelevant in this case? Are you refering to the gauge
parameter?

On Sunday, April 12, 2015 at 11:28:48 PM UTC+2, Gabriel Mitchell wrote:

Hi Andrei. I am not really Julia expert, but I do have a couple of high
level questions about your code, which might help anyone that feels
inclined to contribute a review.

(1) Why have you made the WaveFunction type in the first place? In
particular, is there any reason that you just don't use alias
Vector{Complex{Float64}}
and define a methods for the int attribute?
(2) the outer construction seems to allow for the option for different
gauges (which, in my unsophisticated mindset, I think of as alternative
parameterizations). Since different gauge choices in some sense imply
different semantics for the values in Psi (although presumably not other
function invariant to the gauge choice), it would seem that the user (or a
function naive to the gauge choice) would want a means to inspect this
change in the object. In other words why is the gauge not an attribute of
the WaveFunction object, assuming you actually want this type? A related
question would be how many different gauges choices does one expect the
user to want to use. Just these two? These two plus a few more? All of them?
(3) Line 17 asserts that N is an integer, but sqrt(length(P)) could be
non-integral.
(4) I don't really understand what is going on with countnonzeros, but
maybe a pattern matching syntax ala Match.jl could help to make a more
declarative version of this function?

As a side note, I think the problem of how to describe and take advantage
of irrelevant degrees of freedom in numerical computations is pretty
interesting and certainly has applications in all kids of fields, so it
would be cool if you had some ideas about how to systematically approach
this problem.

On Sunday, April 12, 2015 at 10:06:10 PM UTC+2, Andrei Berceanu wrote:

Hi Mauro, I realised after posting this that I should have been much more
specific.
I apologise for that!

Anyway, thanks for you reply. Not sure what you mean by OO programming,
as I thought Julia uses multiple dispatch and not OO.

PS: You're the first person I see that also uses runbox, that makes us
email brothers I guess :p

On Sunday, April 12, 2015 at 8:29:44 PM UTC+2, Mauro wrote:

Hi Andrei,

just a general note, unless someone is actually interested in using your
code, a code review might be too much to ask of people. Thus the lack
in responses. See:

https://groups.google.com/forum/#!searchin/julia-users/karpinski$20reivew/julia-users/C5cVjAuGA8U/HLV5rAjIuLMJ

The way to get most feedback, is to condense your problem into a small
snippet which can just be run with copy-paste (you're gists fails there)
and ask something specific. An exception seem to be questions of the
kind I ported this from C/Fortran/... and it is 100x slower, where did
I go wrong, which seem to regularly attract much feedback.

I didn't look into the code in detail:

It's the first time I try to use Julia constructors properly (or
improperly?!) so I need your opinion on a couple of points.

Use of constructors seem to be fine.

1. On Julia's IRC channel I was told that using AbstractArray instead
of
e.g. Matrix/Vector might yield a performance boost - is that the case?

No, I don't think so. Did you read the Performance section of the
manual? There it also tells you how to profile your code.

2. Can you spot any major performance killers in my code?
3. Coming from Python, I am used to things like enumerate etc, but
perhaps
that is not very Julian? :) So this last aspect concerns more the
coding
style, I guess.

Using enumerate is totally fine. Just don't do object-oriented
programming.

Looks all good

Re: [julia-users] Julia gets a mention in phys.org

2015-04-13 Thread Ivan Ogasawara

very interesting!

2015-04-13 13:30 GMT-03:00 René Donner li...@donner.at:

 You can find more information on Picture here:
 http://mrkulk.github.io/www_cvpr15/

 Am 13.04.2015 um 18:24 schrieb Seth catch...@bromberger.com:

  http://phys.org/news/2015-04-probabilistic-lines-code-thousands.html
 
  Joining Kulkarni on the paper are his adviser, professor of brain and
 cognitive sciences Josh Tenenbaum; Vikash Mansinghka, a research scientist
 in MIT's Department of Brain and Cognitive Sciences; and Pushmeet Kohli of
 Microsoft Research Cambridge. For their experiments, they created a
 probabilistic programming language they call Picture, which is an extension
 of Julia, another language developed at MIT.

[julia-users] Re: pre-allocation for sparse matrices

Yes but so how do I update it inplace?

On Monday, April 13, 2015 at 5:37:50 PM UTC+2, Kristoffer Carlsson wrote:

 If you have the same sparse structures in your matrices then it should be 
 sufficient to to the IJV - CSC sparse matrix conversion only once and then 
 update A in place instead of generating a new IJV and converting to CSC 
 again and again.

Re: [julia-users] Is the official name of the language Julia or julia?

Thanks for the additional info!

On Mon, Apr 13, 2015 at 10:45 AM, cormull...@mac.com wrote:

 About that font:

 Twitter discussion with Muthu Nedumaran:
 https://twitter.com/typographica/status/572304422610452480

 FontsInUse entry:
 http://fontsinuse.com/typefaces/38527/mn-latin

[julia-users] Method fieldnames not defined

2015-04-13 Thread 'Antoine Messager' via julia-users

Hi,

I would like to find the field of SolverResults{Float64}. So according to 
the manual http://julia.readthedocs.org/en/latest/manual/types/, I just 
need to use the method fieldnames but unfortunately it is not defined. 
What can I do?

Thank you,
Antoine

[julia-users] Re: Error using pcolor

2015-04-13 Thread Tim Wheeler

The same code works fine on my machine.
Maybe try running Pkg.update()?

[julia-users] Julia gets a mention in phys.org

2015-04-13 Thread Seth

http://phys.org/news/2015-04-probabilistic-lines-code-thousands.html

Joining Kulkarni on the paper are his adviser, professor of brain and 
 cognitive sciences Josh Tenenbaum; Vikash Mansinghka, a research scientist 
 in MIT's Department of Brain and Cognitive Sciences; and Pushmeet Kohli of 
 Microsoft Research Cambridge. For their experiments, they created a 
 probabilistic programming language they call Picture, which is an extension 
 of Julia, another language developed at MIT.

Re: [julia-users] Is the official name of the language Julia or julia?

2015-04-13 Thread cormullion

The only remaining question is the significance of the four colored circles in 
the logo... :) Where's a symbologist when you need one?

Re: [julia-users] string processing after readdlm

No need to apologize – I was just trying to figure out if there was
supposed to be an image there or something.

On Mon, Apr 13, 2015 at 11:58 AM, JKpie fablekil...@gmail.com wrote:


 Thank you very much Mauro and Peter, hdf5 and JLD is a good solution.
 I just didn't know if it was a standard behavior of writedlm and readdlm
 functions.

 Stefan: I do apologize for the white space in the massage. It was
 copy-pasted output from Juno console and I have noticed that the space
 appeared when the message was posted.

 thank you once again for quick answer,
 Jakub



 On Monday, April 13, 2015 at 5:13:20 PM UTC+2, Peter Simon wrote:

 Also, if you don't need a .csv file, consider using the HDF5 and JLD
 packages which preserve the types of stored values:

 julia  a = [1.,2.,3.,4]
 4-element Array{Float64,1}:
  1.0
  2.0
  3.0
  4..0


 julia b = Vector{Float64}[copy(a),2*copy(a),3*copy(a)]
 3-element Array{Array{Float64,1},1}:
  [1.0,2.0,3.0,4.0]
  [2.0,4.0,6.0,8.0]
  [3.0,6.0,9.0,12.0]

 julia using HDF5, JLD

 julia save(myfile.jld,b,b)

 julia c = load(myfile.jld,b)
 3-element Array{Array{Float64,1},1}:
  [1.0,2.0,3.0,4.0]
  [2.0,4.0,6.0,8.0]
  [3.0,6.0,9.0,12.0]

Re: [julia-users] string processing after readdlm

2015-04-13 Thread Peter Simon

Also, if you don't need a .csv file, consider using the HDF5 and JLD 
packages which preserve the types of stored values:

julia  a = [1.,2.,3.,4]
4-element Array{Float64,1}:
 1.0
 2.0
 3.0
 4..0


julia b = Vector{Float64}[copy(a),2*copy(a),3*copy(a)]
3-element Array{Array{Float64,1},1}:
 [1.0,2.0,3.0,4.0]
 [2.0,4.0,6.0,8.0]
 [3.0,6.0,9.0,12.0]

julia using HDF5, JLD

julia save(myfile.jld,b,b)

julia c = load(myfile.jld,b)
3-element Array{Array{Float64,1},1}:
 [1.0,2.0,3.0,4.0]
 [2.0,4.0,6.0,8.0]
 [3.0,6.0,9.0,12.0]

Re: [julia-users] Problem with addprocs

2015-04-13 Thread René Donner

Can you try whether using tunnel = true helps?

  http://docs.julialang.org/en/release-0.3/stdlib/parallel/#Base.addprocs

When tunnel==false (the default), the workers need to be able to see each other 
directly, which will not work through firewalls which allow only ssh etc.



Am 13.04.2015 um 12:10 schrieb John john.d.schul...@gmail.com:

 I'm unable to add a remote instance using addprocs (or a machine file).
 
 This works (without prompt):
 ssh xxx.xxx.xxx.xxx
 
 This command hangs with no output for the first minute:
 addprocs([usern...@xxx.xxx.xxx.xxx])
 Then after one minute, the following message appears:
 Master process (id 1) could not connect within 60.0 seconds
 
 This command works:
 addprocs([username@mycurrenthostname])
 
 Thanks in advance for your help!
 John

[julia-users] Re: pre-allocation for sparse matrices

2015-04-13 Thread Kristoffer Carlsson

If you have the same sparse structures in your matrices then it should be 
sufficient to to the IJV - CSC sparse matrix conversion only once and then
update A in place instead of generating a new IJV and converting to CSC again 
and again.

Re: [julia-users] Method fieldnames not defined