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| author | TAKATSU Tomonari <tota@FreeBSD.org> | 2023-04-23 02:53:20 +0000 |
|---|---|---|
| committer | TAKATSU Tomonari <tota@FreeBSD.org> | 2023-04-23 12:03:35 +0000 |
| commit | ce15b4171b5c1a16995da9e5a8e9748f5c6fb392 (patch) | |
| tree | 078ee66f93155f081427e1272591a1d0adad95f0 | |
| parent | fd933d91c42d00bd2a55a7824a1d78e614f2767a (diff) | |
| download | ports-ce15b4171b5c1a16995da9e5a8e9748f5c6fb392.tar.gz ports-ce15b4171b5c1a16995da9e5a8e9748f5c6fb392.zip | |
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)
| -rw-r--r-- | math/R-cran-irlba/Makefile | 2 | ||||
| -rw-r--r-- | math/R-cran-irlba/distinfo | 6 | ||||
| -rw-r--r-- | 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. |