Merge pull request #14424 from JuliaLang/anj/rankupdate

Rename rank one up- and downdate functions for Cholesky to rank(up/down)date

Author: andreasnoack

NEWS.md

@@ -70,6 +70,9 @@ Library improvements
       appropriate. The `sparsevec` function returns a one-dimensional sparse
       vector instead of a one-column sparse matrix. ([#13440])
 
+    * Rank one update and downdate functions, `lowrankupdate`, `lowrankupdate!`, `lowrankdowndate`,
+    and `lowrankdowndate!`, for dense Cholesky factorizations ([#14243],[#14424])
+
   * New `foreach` function for calling a function on every element of a collection when
     the results are not needed.
 

base/linalg/cholesky.jl

@@ -267,11 +267,11 @@ chkfullrank(C::CholeskyPivoted) = C.rank < size(C.factors, 1) && throw(RankDefic
 rank(C::CholeskyPivoted) = C.rank
 
 """
-    update!(C::Cholesky, v::StridedVector) -> CC::Cholesky
+    lowrankupdate!(C::Cholesky, v::StridedVector) -> CC::Cholesky
 
 Update a Cholesky factorization `C` with the vector `v`. If `A = C[:U]'C[:U]` then `CC = cholfact(C[:U]'C[:U] + v*v')` but the computation of `CC` only uses `O(n^2)` operations. The input factorization `C` is updated in place such that on exit `C == CC`. The vector `v` is destroyed during the computation.
 """
-function update!(C::Cholesky, v::StridedVector)
+function lowrankupdate!(C::Cholesky, v::StridedVector)
     A = C.factors
     n = length(v)
     if size(C, 1) != n
@@ -310,11 +310,11 @@ function update!(C::Cholesky, v::StridedVector)
 end
 
 """
-    downdate!(C::Cholesky, v::StridedVector) -> CC::Cholesky
+    lowrankdowndate!(C::Cholesky, v::StridedVector) -> CC::Cholesky
 
 Downdate a Cholesky factorization `C` with the vector `v`. If `A = C[:U]'C[:U]` then `CC = cholfact(C[:U]'C[:U] - v*v')` but the computation of `CC` only uses `O(n^2)` operations. The input factorization `C` is updated in place such that on exit `C == CC`. The vector `v` is destroyed during the computation.
 """
-function downdate!(C::Cholesky, v::StridedVector)
+function lowrankdowndate!(C::Cholesky, v::StridedVector)
     A = C.factors
     n = length(v)
     if size(C, 1) != n
@@ -360,15 +360,15 @@ function downdate!(C::Cholesky, v::StridedVector)
 end
 
 """
-    update(C::Cholesky, v::StridedVector) -> CC::Cholesky
+    lowrankupdate(C::Cholesky, v::StridedVector) -> CC::Cholesky
 
 Update a Cholesky factorization `C` with the vector `v`. If `A = C[:U]'C[:U]` then `CC = cholfact(C[:U]'C[:U] + v*v')` but the computation of `CC` only uses `O(n^2)` operations.
 """
-update(C::Cholesky, v::StridedVector) = update!(copy(C), copy(v))
+lowrankupdate(C::Cholesky, v::StridedVector) = lowrankupdate!(copy(C), copy(v))
 
 """
-    downdate(C::Cholesky, v::StridedVector) -> CC::Cholesky
+    lowrankdowndate(C::Cholesky, v::StridedVector) -> CC::Cholesky
 
 Downdate a Cholesky factorization `C` with the vector `v`. If `A = C[:U]'C[:U]` then `CC = cholfact(C[:U]'C[:U] - v*v')` but the computation of `CC` only uses `O(n^2)` operations.
 """
-downdate(C::Cholesky, v::StridedVector) = downdate!(copy(C), copy(v))
+lowrankdowndate(C::Cholesky, v::StridedVector) = lowrankdowndate!(copy(C), copy(v))

doc/stdlib/linalg.rst

@@ -161,25 +161,25 @@ Linear algebra functions in Julia are largely implemented by calling functions f
 
 .. currentmodule:: Base.LinAlg
 
-.. function:: update(C::Cholesky, v::StridedVector) -> CC::Cholesky
+.. function:: lowrankupdate(C::Cholesky, v::StridedVector) -> CC::Cholesky
 
    .. Docstring generated from Julia source
 
    Update a Cholesky factorization ``C`` with the vector ``v``\ . If ``A = C[:U]'C[:U]`` then ``CC = cholfact(C[:U]'C[:U] + v*v')`` but the computation of ``CC`` only uses ``O(n^2)`` operations.
 
-.. function:: downdate(C::Cholesky, v::StridedVector) -> CC::Cholesky
+.. function:: lowrankdowndate(C::Cholesky, v::StridedVector) -> CC::Cholesky
 
    .. Docstring generated from Julia source
 
    Downdate a Cholesky factorization ``C`` with the vector ``v``\ . If ``A = C[:U]'C[:U]`` then ``CC = cholfact(C[:U]'C[:U] - v*v')`` but the computation of ``CC`` only uses ``O(n^2)`` operations.
 
-.. function:: update!(C::Cholesky, v::StridedVector) -> CC::Cholesky
+.. function:: lowrankupdate!(C::Cholesky, v::StridedVector) -> CC::Cholesky
 
    .. Docstring generated from Julia source
 
    Update a Cholesky factorization ``C`` with the vector ``v``\ . If ``A = C[:U]'C[:U]`` then ``CC = cholfact(C[:U]'C[:U] + v*v')`` but the computation of ``CC`` only uses ``O(n^2)`` operations. The input factorization ``C`` is updated in place such that on exit ``C == CC``\ . The vector ``v`` is destroyed during the computation.
 
-.. function:: downdate!(C::Cholesky, v::StridedVector) -> CC::Cholesky
+.. function:: lowrankdowndate!(C::Cholesky, v::StridedVector) -> CC::Cholesky
 
    .. Docstring generated from Julia source
 

test/linalg/cholesky.jl

@@ -152,7 +152,7 @@ let A = complex(randn(10,5), randn(10, 5)), v = complex(randn(5), randn(5))
     for uplo in (:U, :L)
         AcA = A'A
         F = cholfact(AcA, uplo)
-        @test LinAlg.update(F, v)[uplo] ≈ cholfact(AcA + v*v')[uplo]
-        @test LinAlg.downdate(F, v)[uplo] ≈ cholfact(AcA - v*v')[uplo]
+        @test LinAlg.lowrankupdate(F, v)[uplo] ≈ cholfact(AcA + v*v')[uplo]
+        @test LinAlg.lowrankdowndate(F, v)[uplo] ≈ cholfact(AcA - v*v')[uplo]
     end
 end