fmm3dpy

This pacakge contains basic routines for Laplace and Helmholtz fast multipole methods in three dimensions

These details have not been verified by PyPI

Project description

Flatiron Institute Fast Multipole Libraries

This codebase is a set of libraries to compute N-body interactions governed by the Laplace and Helmholtz equations, to a specified precision, in three dimensions, on a multi-core shared-memory machine.

Please see the online documentation, or its equivalent user manual.

Project details

These details have not been verified by PyPI

Release history Release notifications | RSS feed

1.0.0

Nov 16, 2021

0.0.5

Aug 20, 2020

This version

0.0.4

Aug 19, 2020

0.0.3

Jul 31, 2020

0.0.2

Jul 31, 2020

0.0.1

Jul 24, 2020

0.0.0

Jul 24, 2020

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distributions

No source distribution files available for this release.See tutorial on generating distribution archives.

Built Distributions

fmm3dpy-0.0.4-cp38-cp38-win_amd64.whl (4.2 MB view hashes)

Uploaded Aug 19, 2020 CPython 3.8 Windows x86-64

fmm3dpy-0.0.4-cp38-cp38-manylinux2014_x86_64.whl (4.2 MB view hashes)

Uploaded Aug 19, 2020 CPython 3.8

fmm3dpy-0.0.4-cp38-cp38-macosx_10_9_x86_64.whl (4.4 MB view hashes)

Uploaded Aug 19, 2020 CPython 3.8 macOS 10.9+ x86-64

fmm3dpy-0.0.4-cp37-cp37m-win_amd64.whl (4.2 MB view hashes)

Uploaded Aug 19, 2020 CPython 3.7m Windows x86-64

fmm3dpy-0.0.4-cp37-cp37m-manylinux2014_x86_64.whl (4.1 MB view hashes)

Uploaded Aug 19, 2020 CPython 3.7m

fmm3dpy-0.0.4-cp37-cp37m-macosx_10_9_x86_64.whl (4.4 MB view hashes)

Uploaded Aug 19, 2020 CPython 3.7m macOS 10.9+ x86-64

fmm3dpy-0.0.4-cp36-cp36m-win_amd64.whl (4.2 MB view hashes)

Uploaded Aug 19, 2020 CPython 3.6m Windows x86-64

fmm3dpy-0.0.4-cp36-cp36m-manylinux2014_x86_64.whl (4.1 MB view hashes)

Uploaded Aug 19, 2020 CPython 3.6m

fmm3dpy-0.0.4-cp36-cp36m-macosx_10_9_x86_64.whl (4.4 MB view hashes)

Uploaded Aug 19, 2020 CPython 3.6m macOS 10.9+ x86-64

fmm3dpy-0.0.4-cp35-cp35m-manylinux2014_x86_64.whl (4.0 MB view hashes)

Uploaded Aug 19, 2020 CPython 3.5m

Hashes for fmm3dpy-0.0.4-cp38-cp38-win_amd64.whl

Hashes for fmm3dpy-0.0.4-cp38-cp38-win_amd64.whl
Algorithm	Hash digest
SHA256	`2de0efc5aae5e54c4da1c0578987515531e7aeb2acd6d905226d806da6d2850f`
MD5	`aca9262cecbc92b6241a4343d36f75e3`
BLAKE2b-256	`5aebcdfb7ab667eb319e243a1c7ac66027cdcf6c4df636525cafa1c60df4da7d`

Hashes for fmm3dpy-0.0.4-cp38-cp38-manylinux2014_x86_64.whl

Hashes for fmm3dpy-0.0.4-cp38-cp38-manylinux2014_x86_64.whl
Algorithm	Hash digest
SHA256	`4c23a974572233c1ec9d3e1ff78841da4dc5dc7f85f0b137a9ebc9b315922611`
MD5	`83c7635c9db90c4176d0fe201fbda47a`
BLAKE2b-256	`7fd37bf01dd8eceaee202b2211c76e283e7652a41ecd323f6c7ecda052990e0d`

Hashes for fmm3dpy-0.0.4-cp38-cp38-macosx_10_9_x86_64.whl

Hashes for fmm3dpy-0.0.4-cp38-cp38-macosx_10_9_x86_64.whl
Algorithm	Hash digest
SHA256	`0193ea14e0d678397be85acffe188552d5ac02e32c4d4d455eb0c99f77d6fdbc`
MD5	`3a38cd04701d21d448a66bad1c10c622`
BLAKE2b-256	`d7e7c2aca0c2002d55be3c5ae72e7a18df65a0ae0000fd00f092ee8996a6019c`

Hashes for fmm3dpy-0.0.4-cp37-cp37m-win_amd64.whl

Hashes for fmm3dpy-0.0.4-cp37-cp37m-win_amd64.whl
Algorithm	Hash digest
SHA256	`86ed2991dbd4de0910eb41d96e958978bd0e74845d217cfdca3258378d1cba59`
MD5	`35f3447735323b8d3216315c3ac7d29c`
BLAKE2b-256	`884749e94d12f163f648407da9f3006a1e62083220822abd82a4741b88e8b98c`

Hashes for fmm3dpy-0.0.4-cp37-cp37m-manylinux2014_x86_64.whl

Hashes for fmm3dpy-0.0.4-cp37-cp37m-manylinux2014_x86_64.whl
Algorithm	Hash digest
SHA256	`298cc2ccf7f9f915cb76575dac1e3f28c0bf64a42ae94363df8f0214cd08c137`
MD5	`f12a2df27efb6469f6ab0e2ee830a81f`
BLAKE2b-256	`591d6b709eaa1a5e9aaf8036a7384358b1033c24da1acccedc7671d211d4c687`

Hashes for fmm3dpy-0.0.4-cp37-cp37m-macosx_10_9_x86_64.whl

Hashes for fmm3dpy-0.0.4-cp37-cp37m-macosx_10_9_x86_64.whl
Algorithm	Hash digest
SHA256	`c0968af847e5476744c2f4255b8146e06d2915acdeca3aafe57dd0a0e1a36cba`
MD5	`c1b177af7bdae94bbaef0ed075df0ed0`
BLAKE2b-256	`f00a79119f5e11f66f3ab96b6716f8b320d5de3eaa93b759c1f8bf8b9e6a84fd`

Hashes for fmm3dpy-0.0.4-cp36-cp36m-win_amd64.whl

Hashes for fmm3dpy-0.0.4-cp36-cp36m-win_amd64.whl
Algorithm	Hash digest
SHA256	`ee180bf10dcbc06196722cbecd4b306ad3d359a2b7f92095dfc427657aee556f`
MD5	`2701d98749f5f21ac6b0f6dee0ac58a2`
BLAKE2b-256	`2d887e1f287f04fee4b3e92a9c5d395ecea78cbbcda1c2053c2577fe462ecaf5`

Hashes for fmm3dpy-0.0.4-cp36-cp36m-manylinux2014_x86_64.whl

Hashes for fmm3dpy-0.0.4-cp36-cp36m-manylinux2014_x86_64.whl
Algorithm	Hash digest
SHA256	`9e0530ba669ae053b237f8534b93ba773c9eef7855d262c4ad2604df4c3e4a55`
MD5	`a611177cc45848971cae24362932be16`
BLAKE2b-256	`470517384ae3d2cd2242e0a9c9dcef34354ab901a00ca00591147b2060a99b77`

Hashes for fmm3dpy-0.0.4-cp36-cp36m-macosx_10_9_x86_64.whl

Hashes for fmm3dpy-0.0.4-cp36-cp36m-macosx_10_9_x86_64.whl
Algorithm	Hash digest
SHA256	`b53c0d03ee61215f59dfdbceafa93f9f9790d29902fa0bc15d755cb85cb31662`
MD5	`ad54d8fc0000f6066cc603ffa3b453e2`
BLAKE2b-256	`3472e54997be54ea00a06843d025545d1336a195f1c150a06816ff86fd263358`

Hashes for fmm3dpy-0.0.4-cp35-cp35m-manylinux2014_x86_64.whl

Hashes for fmm3dpy-0.0.4-cp35-cp35m-manylinux2014_x86_64.whl
Algorithm	Hash digest
SHA256	`32451040f3af3b10440f2acf938aacd903774978d4b7bcc71200611583e34925`
MD5	`3118986d0726e819ff2e434a3f3c5e47`
BLAKE2b-256	`d6ca8eecc76c62f32ea7d10c587bbbc6b4a9677a2c4af023fe741ae993e399f6`