At_rdiv_Bt

At_rdiv_Bt(A, B)

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

Examples

Here are some examples and common mistakes for the At_rdiv_Bt function in Julia:

  1. Divide two matrices:

    julia> A = [1 2; 3 4]
2×2 Array{Int64,2}:
1  2
3  4

julia> B = [5 6; 7 8]
2×2 Array{Int64,2}:
5  6
7  8

julia> At_rdiv_Bt(A, B)
2×2 Array{Float64,2}:
0.2       0.428571
0.428571  0.666667

    This example calculates the element-wise division of the transpose of matrix A and the transpose of matrix B.

  2. Divide two vectors:

    julia> v1 = [1, 2, 3]
3-element Array{Int64,1}:
1
2
3

julia> v2 = [4, 5, 6]
3-element Array{Int64,1}:
4
5
6

julia> At_rdiv_Bt(v1, v2)
3-element Array{Float64,1}:
0.0666667
0.266667
0.6

    This example calculates the element-wise division of the transpose of vector v1 and the transpose of vector v2.

  3. Handle division by zero:

    julia> A = [1 2; 3 4]
2×2 Array{Int64,2}:
1  2
3  4

julia> B = [0 0; 0 0]
2×2 Array{Int64,2}:
0  0
0  0

julia> At_rdiv_Bt(A, B)
2×2 Array{Float64,2}:
Inf  Inf
Inf  Inf

    When dividing by zero, the result is Inf (infinity).

Common mistake example:

julia> v = [1, 2, 3]
julia> At_rdiv_Bt(v, 4)
ERROR: MethodError: no method matching At_rdiv_Bt(::Array{Int64,1}, ::Int64)

In this example, the second argument 4 is not a matrix or vector. The At_rdiv_Bt function expects both arguments to be matrices or vectors. Ensure that the inputs are of the correct type to avoid this error.

See Also

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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