# AlmostBlockDiagonals

Partial pivoting LU factorization and linear solver for almost block diagonal matrices. Mainly designed for linear solving in BoundaryValueDiffEq.jl. Users who only want to use this package should use with caution.

a1 = [ 0.1   2.0  -0.1  -0.1
0.2  -0.2  -0.2   4.0
-1.0   0.3  -0.3   0.3 ]
a2 = [-0.4  0.4  -5.0
3.0  0.5  -0.5 ]
a3 = [ 0.6  -0.6  -0.6   5.0
0.5   4.0   0.5  -0.5
3.0   0.4  -0.4   0.4 ]
a4 = [ 0.3  -0.3  0.3  7.0 ]
a5 = [ 0.2  -0.2  -0.2   8.0
6.0   0.1  -0.1  -0.1 ]
A = AlmostBlockDiagonal([a1, a2, a3, a4, a5], [2, 3, 1, 1, 4])
11×11 AlmostBlockDiagonal{Float64, Int64, Matrix{Float64}}:
0.1   2.0  -0.1  -0.1   0.0  0.0   0.0   0.0   0.0   0.0   0.0
0.2  -0.2  -0.2   4.0   0.0  0.0   0.0   0.0   0.0   0.0   0.0
-1.0   0.3  -0.3   0.3   0.0  0.0   0.0   0.0   0.0   0.0   0.0
0.0   0.0  -0.4   0.4  -5.0  0.0   0.0   0.0   0.0   0.0   0.0
0.0   0.0   3.0   0.5  -0.5  0.0   0.0   0.0   0.0   0.0   0.0
0.0   0.0   0.0   0.0   0.0  0.6  -0.6  -0.6   5.0   0.0   0.0
0.0   0.0   0.0   0.0   0.0  0.5   4.0   0.5  -0.5   0.0   0.0
0.0   0.0   0.0   0.0   0.0  3.0   0.4  -0.4   0.4   0.0   0.0
0.0   0.0   0.0   0.0   0.0  0.0   0.3  -0.3   0.3   7.0   0.0
0.0   0.0   0.0   0.0   0.0  0.0   0.0   0.2  -0.2  -0.2   8.0
0.0   0.0   0.0   0.0   0.0  0.0   0.0   6.0   0.1  -0.1  -0.1

Linear solving with pivoting LU factorization:

B = [1.94,3.04,-0.83,-3.54,2.75,1.32,2.35,1.96,1.52,0.78,2.40]
x = A\B
11-element Vector{Float64}:
1.0999999999999999
1.0
0.9
0.8
0.7
0.6
0.5000000000000001
0.39999999999999997
0.30000000000000004
0.2
0.1

For details about algorithms, please see: SOLVEBLOK: A Package for Solving Almost Block Diagonal Linear Systems. SOLVEBLOK is originally a FORTRAN program for the solution of an almost block diagonal system by gaussian elimination with scale row pivoting.