git: ce15b4171b5c - 2023Q2 - math/R-cran-irlba: Update to 2.3.5.1

The branch 2023Q2 has been updated by tota:

URL: https://cgit.FreeBSD.org/ports/commit/?id=ce15b4171b5c1a16995da9e5a8e9748f5c6fb392

commit ce15b4171b5c1a16995da9e5a8e9748f5c6fb392
Author:     TAKATSU Tomonari <tota@FreeBSD.org>
AuthorDate: 2023-04-23 02:53:20 +0000
Commit:     TAKATSU Tomonari <tota@FreeBSD.org>
CommitDate: 2023-04-23 12:03:35 +0000

    math/R-cran-irlba: Update to 2.3.5.1
    
    - Update to 2.3.5.1
    - Update pkg-descr
    
    Reported by:    pkg-fallout
    MFH:            2023Q2
    
    (cherry picked from commit 9b30bebfb38db266519d83aeb857f415a387d755)
---
 math/R-cran-irlba/Makefile  | 2 +-
 math/R-cran-irlba/distinfo  | 6 +++---
 math/R-cran-irlba/pkg-descr | 5 +++--
 3 files changed, 7 insertions(+), 6 deletions(-)

diff --git a/math/R-cran-irlba/Makefile b/math/R-cran-irlba/Makefile
index 53acecc39d67..cfbac8000332 100644
--- a/math/R-cran-irlba/Makefile
+++ b/math/R-cran-irlba/Makefile
@@ -1,5 +1,5 @@
 PORTNAME=	irlba
-PORTVERSION=	2.3.5
+PORTVERSION=	2.3.5.1
 CATEGORIES=	math
 DISTNAME=	${PORTNAME}_${PORTVERSION}
 
diff --git a/math/R-cran-irlba/distinfo b/math/R-cran-irlba/distinfo
index 9f321114c842..13732fd9a67e 100644
--- a/math/R-cran-irlba/distinfo
+++ b/math/R-cran-irlba/distinfo
@@ -1,3 +1,3 @@
-TIMESTAMP = 1638873363
-SHA256 (irlba_2.3.5.tar.gz) = 26fc8c0d36460e422ab77f43a597b8ec292eacd452628c54d34b8bf7d5269bb9
-SIZE (irlba_2.3.5.tar.gz) = 233388
+TIMESTAMP = 1682217904
+SHA256 (irlba_2.3.5.1.tar.gz) = 2cfe6384fef91c223a9920895ce89496f990d1450d731e44309fdbec2bb5c5cf
+SIZE (irlba_2.3.5.1.tar.gz) = 233555
diff --git a/math/R-cran-irlba/pkg-descr b/math/R-cran-irlba/pkg-descr
index e29a9edba353..94063de67b8e 100644
--- a/math/R-cran-irlba/pkg-descr
+++ b/math/R-cran-irlba/pkg-descr
@@ -1,2 +1,3 @@
-A fast and memory-efficient method for computing a few approximate
-singular values and singular vectors of large matrices.
+Fast and memory efficient methods for truncated singular value
+decomposition and principal components analysis of large sparse and
+dense matrices.