A_rdiv_Bt

A_rdiv_Bt(A, B)

For matrices or vectors $A$ and $B$, calculates $A / Báµ€$

Examples

Calculate matrix division:

julia> A = [1 2 3; 4 5 6; 7 8 9];
julia> B = [2 0 1; 3 2 1; 1 1 1];
julia> A_rdiv_Bt(A, B)
3×3 Array{Float64,2}:
-1.0   1.0  0.0
 2.0  -1.0  0.0
-1.0   1.0  0.0

This example calculates the matrix division of A by Bᵀ.

Calculate vector division:

julia> v1 = [1, 2, 3];
julia> v2 = [4, 5, 6];
julia> A_rdiv_Bt(v1, v2)
3×1 Array{Float64,2}:
-1.0
 1.0
 0.0

It calculates the division of the vector v1 by v2ᵀ.

Handle edge cases with empty matrices:

julia> empty_matrix = zeros(0, 0);
julia> A_rdiv_Bt(empty_matrix, empty_matrix)
0×0 Array{Float64,2}

It correctly handles the case where both matrices are empty.

Common mistake example:

julia> A = [1 2; 3 4];
julia> B = [5 6];
julia> A_rdiv_Bt(A, B)
ERROR: DimensionMismatch("A has dimensions (2,2) but Bᵀ has dimensions (1,2)")

In this example, the dimensions of matrix A and the transpose of matrix B are not compatible for division. It's crucial to make sure that the dimensions are compatible before using A_rdiv_Bt.

Ac_ldiv_B, Ac_ldiv_Bc, Ac_mul_B, Ac_mul_Bc, Ac_rdiv_B, Ac_rdiv_Bc, At_ldiv_B, At_ldiv_Bt, At_mul_B, At_mul_Bt, At_rdiv_B, At_rdiv_Bt, A_ldiv_Bc, A_ldiv_Bt, A_mul_B!, A_mul_Bc, A_mul_Bt, A_rdiv_Bc, A_rdiv_Bt, Bidiagonal, cond, conv2, det, diag, diagind, diagm, diff, eig, eigvals, eigvecs, expm, eye, full, inv, isdiag, ishermitian, isposdef, isposdef!, issym, istril, istriu, logabsdet, logdet, lyap, norm, qrfact, rank, repmat, rot180, rotl90, rotr90, sortrows, sqrtm, SymTridiagonal, trace, Tridiagonal, tril, tril!, triu, triu!, writedlm,

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A_rdiv_Bt

Examples

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