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| author | fourtysixandtwo <fourtysixandtwo@sliderr.net> | 2025-05-10 01:50:15 +0700 |
|---|---|---|
| committer | Willy Sudiarto Raharjo <willysr@slackbuilds.org> | 2025-05-10 12:07:41 +0700 |
| commit | 55056e5c4569f5fc1465985a51846dfe28acc5c9 (patch) | |
| tree | 624ac8647406b77e75b9279b7c2bdd12b045a611 /python/python3-lap/README | |
| parent | 5781c4182da82e76e5729aee7a0d750161b5370b (diff) | |
python/python3-lap: Added (Linear Assignment Problem solver).
Signed-off-by: Willy Sudiarto Raharjo <willysr@slackbuilds.org>
Diffstat (limited to 'python/python3-lap/README')
| -rw-r--r-- | python/python3-lap/README | 14 |
1 files changed, 14 insertions, 0 deletions
diff --git a/python/python3-lap/README b/python/python3-lap/README new file mode 100644 index 0000000000..113326c257 --- /dev/null +++ b/python/python3-lap/README @@ -0,0 +1,14 @@ +python3-lap (Linear Assignment Problem solver LAPJV/LAPMOD). + +lap is a linear assignment problem solver using Jonker-Volgenant +algorithm for dense LAPJV¹ or sparse LAPMOD² matrices. Both algorithms +are implemented from scratch based solely on the papers¹˒² and the +public domain Pascal implementation provided by A. Volgenant³. The +LAPMOD implementation seems to be faster than the LAPJV implementation +for matrices with a side of more than ~5000 and with less than 50% +finite coefficients. + +NOTE: While python3-numpy will build without it I highly suggest + installing OpenBLAS before building numpy. I would add it to the + REQUIRES for python3-lap but it will not be in the proper order + for numpy to build against OpenBLAS. |