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remove Woodbury special matrix type #10024

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Feb 2, 2015
Merged

remove Woodbury special matrix type #10024

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28fbec3
remove Woodbury special matrix type from Base
jakebolewski Feb 2, 2015
54acbba
fix tests by wrapping tridiag / pinv in let blocks
jakebolewski Feb 2, 2015
fba5188
update DOCS / NEWS now that Woodbury has been removed
jakebolewski Feb 2, 2015
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2 changes: 2 additions & 0 deletions NEWS.md
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Expand Up @@ -170,6 +170,8 @@ Library improvements
Deprecated or removed
---------------------

* Woodbury special matrix type has been removed from LinAlg ([#10023]).

* `median` and `median!` no longer accept a `checknan` keyword argument ([#8605]).

* `inf` and `nan` are now deprecated in favor of `T(Inf)` and `NaN`, respectively ([#8776]).
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1 change: 0 additions & 1 deletion base/linalg.jl
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Expand Up @@ -211,7 +211,6 @@ include("linalg/lu.jl")

include("linalg/bunchkaufman.jl")
include("linalg/symmetric.jl")
include("linalg/woodbury.jl")
include("linalg/diagonal.jl")
include("linalg/bidiag.jl")
include("linalg/uniformscaling.jl")
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92 changes: 0 additions & 92 deletions base/linalg/woodbury.jl
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4 changes: 0 additions & 4 deletions doc/stdlib/linalg.rst
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Expand Up @@ -443,10 +443,6 @@ Linear algebra functions in Julia are largely implemented by calling functions f

Construct a real symmetric tridiagonal matrix from the diagonal and upper diagonal, respectively. The result is of type ``SymTridiagonal`` and provides efficient specialized eigensolvers, but may be converted into a regular matrix with :func:`full`.

.. function:: Woodbury(A, U, C, V)

Construct a matrix in a form suitable for applying the Woodbury matrix identity.

.. function:: rank(M)

Compute the rank of a matrix.
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139 changes: 69 additions & 70 deletions test/linalg/pinv.jl
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Expand Up @@ -89,104 +89,103 @@ end


function test_pinv(a,m,n,tol1,tol2,tol3)
debug && println("=== julia/matlab pinv, default tol=eps(1.0)*max(size(a)) ===")
apinv = pinv(a);

debug && println("=== julia/matlab pinv, default tol=eps(1.0)*max(size(a)) ===")
apinv = pinv(a);
@test_approx_eq_eps vecnorm(a*apinv*a - a)/vecnorm(a) 0 tol1
x0 = randn(n); b = a*x0; x = apinv*b;
@test_approx_eq_eps vecnorm(a*x-b)/vecnorm(b) 0 tol1
debug && println(vecnorm(a*apinv*a - a)/vecnorm(a))
debug && println(vecnorm(a*x-b)/vecnorm(b))

@test_approx_eq_eps vecnorm(a*apinv*a - a)/vecnorm(a) 0 tol1
x0 = randn(n); b = a*x0; x = apinv*b;
@test_approx_eq_eps vecnorm(a*x-b)/vecnorm(b) 0 tol1
debug && println(vecnorm(a*apinv*a - a)/vecnorm(a))
debug && println(vecnorm(a*x-b)/vecnorm(b))

debug && println("=== julia pinv, tol=sqrt(eps(1.0)) ===")
apinv = pinv(a,sqrt(eps(real(one(eltype(a))))));

debug && println("=== julia pinv, tol=sqrt(eps(1.0)) ===")
apinv = pinv(a,sqrt(eps(real(one(eltype(a))))));

@test_approx_eq_eps vecnorm(a*apinv*a - a)/vecnorm(a) 0 tol2
x0 = randn(n); b = a*x0; x = apinv*b;
@test_approx_eq_eps vecnorm(a*x-b)/vecnorm(b) 0 tol2
debug && println(vecnorm(a*apinv*a - a)/vecnorm(a))
debug && println(vecnorm(a*x-b)/vecnorm(b))

@test_approx_eq_eps vecnorm(a*apinv*a - a)/vecnorm(a) 0 tol2
x0 = randn(n); b = a*x0; x = apinv*b;
@test_approx_eq_eps vecnorm(a*x-b)/vecnorm(b) 0 tol2
debug && println(vecnorm(a*apinv*a - a)/vecnorm(a))
debug && println(vecnorm(a*x-b)/vecnorm(b))
end


srand(12345)

for eltya in (Float64, Complex128)
let
for eltya in (Float64, Complex128)

debug && println("\n\n<<<<<", eltya, ">>>>>")
debug && println("\n\n<<<<<", eltya, ">>>>>")

m = 1000
n = 100
debug && println("\n\n n = ", n, ", m = ",m)
m = 1000
n = 100
debug && println("\n\n n = ", n, ", m = ",m)

default_tol = (real(one(eltya))) * max(m,n) * 10
default_tol = (real(one(eltya))) * max(m,n) * 10

debug && println("\n--- dense/ill-conditioned matrix ---\n");
### a = randn_float64(m,n) * hilb(eltya,n);
a = hilb(eltya,m,n);
test_pinv(a,m,n,1e-2,1e-5,1e-5)
debug && println("\n--- dense/ill-conditioned matrix ---\n");
### a = randn_float64(m,n) * hilb(eltya,n);
a = hilb(eltya,m,n);
test_pinv(a,m,n,1e-2,1e-5,1e-5)

debug && println("\n--- dense/diagonal matrix ---\n");
a = onediag(eltya,m,n);
test_pinv(a,m,n,default_tol,default_tol,default_tol)
debug && println("\n--- dense/diagonal matrix ---\n");
a = onediag(eltya,m,n);
test_pinv(a,m,n,default_tol,default_tol,default_tol)

debug && println("\n--- dense/tri-diagonal matrix ---\n");
a = tridiag(eltya,m,n);
test_pinv(a,m,n,default_tol,1e-5,default_tol)
debug && println("\n--- dense/tri-diagonal matrix ---\n");
a = tridiag(eltya,m,n);
test_pinv(a,m,n,default_tol,1e-5,default_tol)

debug && println("\n--- Diagonal matrix ---\n");
a = onediag_sparse(eltya,m);
test_pinv(a,m,m,default_tol,default_tol,default_tol)
debug && println("\n--- Diagonal matrix ---\n");
a = onediag_sparse(eltya,m);
test_pinv(a,m,m,default_tol,default_tol,default_tol)

m = 100
n = 100
debug && println("\n\n n = ", n, ", m = ",m)
m = 100
n = 100
debug && println("\n\n n = ", n, ", m = ",m)

default_tol = (real(one(eltya))) * max(m,n) * 10
default_tol = (real(one(eltya))) * max(m,n) * 10

debug && println("\n--- dense/ill-conditioned matrix ---\n");
### a = randn_float64(m,n) * hilb(eltya,n);
a = hilb(eltya,m,n);
test_pinv(a,m,n,1e-2,1e-5,1e-5)
debug && println("\n--- dense/ill-conditioned matrix ---\n");
### a = randn_float64(m,n) * hilb(eltya,n);
a = hilb(eltya,m,n);
test_pinv(a,m,n,1e-2,1e-5,1e-5)

debug && println("\n--- dense/diagonal matrix ---\n");
a = onediag(eltya,m,n);
test_pinv(a,m,n,default_tol,default_tol,default_tol)
debug && println("\n--- dense/diagonal matrix ---\n");
a = onediag(eltya,m,n);
test_pinv(a,m,n,default_tol,default_tol,default_tol)

debug && println("\n--- dense/tri-diagonal matrix ---\n");
a = tridiag(eltya,m,n);
test_pinv(a,m,n,default_tol,1e-5,default_tol)
debug && println("\n--- dense/tri-diagonal matrix ---\n");
a = tridiag(eltya,m,n);
test_pinv(a,m,n,default_tol,1e-5,default_tol)

debug && println("\n--- Diagonal matrix ---\n");
a = onediag_sparse(eltya,m);
test_pinv(a,m,m,default_tol,default_tol,default_tol)
debug && println("\n--- Diagonal matrix ---\n");
a = onediag_sparse(eltya,m);
test_pinv(a,m,m,default_tol,default_tol,default_tol)

m = 100
n = 1000
debug && println("\n\n n = ", n, ", m = ",m)
m = 100
n = 1000
debug && println("\n\n n = ", n, ", m = ",m)

default_tol = (real(one(eltya))) * max(m,n) * 10
default_tol = (real(one(eltya))) * max(m,n) * 10

debug && println("\n--- dense/ill-conditioned matrix ---\n");
### a = randn_float64(m,n) * hilb(eltya,n);
a = hilb(eltya,m,n);
test_pinv(a,m,n,1e-2,1e-5,1e-5)
debug && println("\n--- dense/ill-conditioned matrix ---\n");
### a = randn_float64(m,n) * hilb(eltya,n);
a = hilb(eltya,m,n);
test_pinv(a,m,n,1e-2,1e-5,1e-5)

debug && println("\n--- dense/diagonal matrix ---\n");
a = onediag(eltya,m,n);
test_pinv(a,m,n,default_tol,default_tol,default_tol)
debug && println("\n--- dense/diagonal matrix ---\n");
a = onediag(eltya,m,n);
test_pinv(a,m,n,default_tol,default_tol,default_tol)

debug && println("\n--- dense/tri-diagonal matrix ---\n");
a = tridiag(eltya,m,n);
test_pinv(a,m,n,default_tol,1e-5,default_tol)

debug && println("\n--- Diagonal matrix ---\n");
a = onediag_sparse(eltya,m);
test_pinv(a,m,m,default_tol,default_tol,default_tol)
debug && println("\n--- dense/tri-diagonal matrix ---\n");
a = tridiag(eltya,m,n);
test_pinv(a,m,n,default_tol,1e-5,default_tol)

debug && println("\n--- Diagonal matrix ---\n");
a = onediag_sparse(eltya,m);
test_pinv(a,m,m,default_tol,default_tol,default_tol)
end
end


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