When I run this code in Julia 0.5.0-rc4 the code is much shorter and most
of the red indicating type instability is gone.
Cheers.
Hi Kristoffer,
yes, the return type is stable because I explicitly declared weights as
Array{T,N}. With order being a 1D array it needs to be "converted" to a
tuple to initialize the weights array and I don't see too many ways of
doing this. The problem seems to be present is the following
I wrote a generate function to compute Chebyshev weights using Chebyshev
regression. I'm sure that there are many ways the code could be improved,
but at the top of my list is eliminating what appears to be a type
instability whose source I'm having trouble locating using @code_warntype.
Any
Thanks Cedric. I've found a way to construct the product I needed.
Richard
I'm fiddling around with expressions and I'm puzzled why the following
tells me that k is not defined. Any thoughts would be appreciated.
# a = is a 3D array
# b = a vector of vectors
vars = [[symbol("i1")]; [symbol("i2")]; [symbol("i3")]]
glomp = :( inner_prod = a[$(vars...)];
Hi,
after I type using GtkIDE I get the following. Any thoughts?
-
INFO: Precompiling module Immerse...
-
ERROR: LoadError: LoadError: UndefVarError: absolute_native_units not defined
in include at boot.jl:261
in include_from_node1 at loading.jl:320
in
I get crashes a lot running Julia on Windows when running long simulations.
In my case, it seems to be related to @parallel as it does not happen when
I take these out and run the program on one core. It happens on both my
desktop and my laptop, both Windows machines.
Why is the following not okay?
s = [0.1 0.09; 0.09 0.5]
z = chol(s)
t = z[:,1]
This gives a dimension error.
The following does work
s = [0.1 0.09; 0.09 0.5]
z = chol(s)
y = convert(Array,z)
t = z[:,1]
Somehow it seems to me that the convert() should not be needed.
---you'll save future users the confusion you're suffering
(sorry), and other developers the time in answering.
https://github.com/JuliaLang/julia/blob/master/CONTRIBUTING.md#improving-documentation
--Tim
On Tuesday, July 21, 2015 03:58:19 PM Richard Dennis wrote:
Running 0.4.0-dev
Running 0.4.0-dev+5933. I expected the print outs from this code to be the
same and to equal zero. What am I doing wrong? Thanks in advance.
addprocs(4);
@everywhere function test(state)
return state.^2.0
end
const n = 1;
const m = 1;
states = randn(n);
store = zeros(n,m);
for i =
Mauro,
are there any new scoping issues raised by the use of parallelization? Are
variables in global scope automatically available to different processors?
R
Hi All,
I have added some new functionality to SolveDSGE that allows the solution
of various linear-quadratic optimal policy problems to be computed.
Specifically, for various model forms, SolveDSGE can compute policies
under:1) discretion; 2) commitment; 3) quasi-commitment; and 4)
Hi Sebastien,
some collaboration down the line would make sense. Thus far, I haven't
been working on a unified framework like Dynare, but rather trying to
develop a set of solution tools that give people flexibility over how they
solve their problems. Will you be at either of the SNDE or CEF
,
but not for real computation.
-viral
On Tuesday, December 2, 2014 1:34:01 AM UTC+5:30, Richard Dennis wrote:
Hi All,
I have posted a package called SolveDSGE on github:
https://github.com/RJDennis/SolveDSGE
The package contains a variety of methods for solving Dynamic
Hi All,
I have posted a package called SolveDSGE on github:
https://github.com/RJDennis/SolveDSGE
The package contains a variety of methods for solving Dynamic Stochastic
General Equilibrium (DSGE) models to to first- or second-order accuracy.
The package will be of most interest to
Thanks David. I understand the general advice, but once PyPlot is ungraded
to version 1.4 the error occurs in Julia 0.3.1 as well. So the problem is
to do with changes in PyPlot and not with changes in Julia.
I'll report the issue with PyPlot.
On Tuesday, 14 October 2014 14:38:04 UTC+1,
Hi All,
does anyone else get an error when they run the following in REPL:
addprocs(1)
using PyPlot
a = @spawn randn(2,2)
fetch(a)
After fetch(a) I get the following:
Worker 2 terminated. Error: ProcessExitedException() in wait at task.jl:284
Thanks,
Richard
Right. I don't get the error in version 0.3.1 either. But I do get it in
version 0.4.0-dev+371 commit c6036da.
On Monday, 13 October 2014 23:10:52 UTC+1, Richard Dennis wrote:
Hi All,
does anyone else get an error when they run the following in REPL:
addprocs(1)
using PyPlot
It has something to do with the update of PyPlot from 1.3.0 to 1.4.0. It
does not occur with the former, but does with the latter.
On Monday, 13 October 2014 23:10:52 UTC+1, Richard Dennis wrote:
Hi All,
does anyone else get an error when they run the following in REPL:
addprocs(1)
using
The follow (contrived) code illustrates a problem that I would like to
overcome. The problem seems to be one of getting the contents of a module
seen by multiple processors. Is there any solution other than stripping
the functions out of the module, putting them into a separate file and then
Thanks Sam. Your suggestion combined with using require on the two
functions and it works.
On Sunday, 7 September 2014 14:31:53 UTC+1, Sam Kaplan wrote:
Hi Richard,
Give
@everywhere using NLSolve
a try. Hope that helps.
Sam
Nice work. You might also want to check out
https://github.com/billmclean/GaussQuadrature.jl
On Monday, September 1, 2014 10:33:31 PM UTC+1, Alex Townsend wrote:
I have written a package FastGauss.jl available here:
https://github.com/ajt60gaibb/FastGauss.jl
to compute Gauss quadrature
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