Perhaps https://github.com/JuliaComputing/NDSparseData.jl?
--Tim
On Sunday, August 21, 2016 8:14:48 AM CDT Kristof Cools wrote:
> Just wondering whether there have emerged any packages for this in the
> meantime. I need a rank 3 sparse matrix to implement a retarded potential
> integral equation
Just wondering whether there have emerged any packages for this in the
meantime. I need a rank 3 sparse matrix to implement a retarded potential
integral equation solver. The structure will have non zero entries for all
values of the first two indices and a varying but fixed length set for the
On Tuesday, September 15, 2015 at 11:02:26 PM UTC-4, Jack Poulson wrote:
>
> I believe that Tony is suggesting manually applying the sparse operator
> rather than explicitly constructing it and then applying it. This is a
> common (and significant) performance optimization when a sparse
I believe that Tony is suggesting manually applying the sparse operator
rather than explicitly constructing it and then applying it. This is a
common (and significant) performance optimization when a sparse operator is
only used once or twice, as the construction of the sparse matrix is often
Instead of constructing a sparse matrix in the inner loop it would be more
efficient to write an in place stencil kernel function to perform the
equivalent operation.
Could you post a link to the part of the documentation that describes how
to do that?
On Tuesday, September 15, 2015 at 3:53:11 AM UTC-4, Tony Kelman wrote:
>
> Instead of constructing a sparse matrix in the inner loop it would be more
> efficient to write an in place stencil kernel function to
I'm doing sequential linear programming on quadratic constraints. Using
matrices makes this much more straight-forward. Without 4th rank matrices,
I have to generate a large number of 2nd rank matrices for every iteration.
However, I gather from your answer that only 2nd rank sparse matrices
There aren't built-in data structures defined in Julia's standard library
right now for higher-dimensional sparse matrices, no. But you can certainly
come up with your own data structure and use it however you like. Are there
any dimensions in your problem along which every 2-dimensional slice
This is the code that uses sparse matrices:
for i = 1:n
for j = i:n
if i == j
sp = start'*sparse([i,n+i,2n+1],[i,n+i,2n+1],[1,1,-1])
lhs[rctr,:] = -2*sp -2*radii[i]*c
rhs[rctr] = -(sp*start)[1] -radii[i]^2
Doesn't 'diag([1,1,1])` have a rank of 3?
On Saturday, September 12, 2015 at 6:09:11 PM UTC+2, Frank Kampas wrote:
>
> Is it possible to create sparse matrices with a rank other than 2?
>
On Saturday, September 12, 2015 at 12:09:11 PM UTC-4, Frank Kampas wrote:
>
> Is it possible to create sparse matrices with a rank other than 2?
>
I've been using 4th rank sparse matrices in Mathematica for circle packing.
The constraints
can be expressed using 2nd rank matrices and
In JuMP you can do indexing over constraints and variables with any number
of indexes. You probably don't need to worry about explicitly forming
constraint matrices at all, since the flattened individual indexes of
optimization variables and constraints are somewhat arbitrary and will
mostly
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