For sparse arrays, you can use `blkdiag()`.
For v0.3, the method David posted is probably the best approach.
Starting in v0.4, you can call `cat([1,2], matrices...)` where the
`matrices` variable is your array of arrays. Note that the splat is
undesirable if this container is quite large.
On Wednesday, June 3, 2015 at 12:07:19 PM UTC-5, Marc Gallant wrote:
>
> If I have an array of square matrices of different sizes; e.g.,
>
> 3-element Array{Array{Float64,2},1}:
> 2x2 Array{Float64,2}:
> 0.539932 0.429322
> 0.623487 0.0397795
> 2x2 Array{Float64,2}:
> 0.35508 0.700551
> 0.768214 0.954056
> 3x3 Array{Float64,2}:
> 0.953354 0.453831 0.991583
> 0.159975 0.116518 0.355275
> 0.791447 0.0104295 0.151609
>
>
> Where the number of elements may be much larger than 3 (e.g., 1000), how
> do I construct a block diagonal matrix, where the blocks are the matrices
> in the array? For the array above, this would be
>
> 7x7 Array{Float64,2}:
> 0.539932 0.429322 0.0 0.0 0.0 0.0 0.0
> 0.623487 0.0397795 0.0 0.0 0.0 0.0 0.0
> 0.0 0.0 0.35508 0.700551 0.0 0.0 0.0
> 0.0 0.0 0.768214 0.954056 0.0 0.0 0.0
> 0.0 0.0 0.0 0.0 0.953354 0.453831 0.991583
> 0.0 0.0 0.0 0.0 0.159975 0.116518 0.355275
> 0.0 0.0 0.0 0.0 0.791447 0.0104295 0.151609
>
>
