A package for CSEMRI with C++ accelerated components.

Navigation

Verified details

These details have been verified by PyPI
Maintainers
Avatar for dtamada from gravatar.com dtamada

Unverified details

These details have not been verified by PyPI
Project links
Meta
Report project as malware

Project description

PyCSEMRI: Python Water-Fat Separation Package for CSE-MRI

Overview

PyWaterFat is a Python package for water-fat separation in Chemical Shift Encoding Magnetic Resonance Imaging (CSE-MRI). This package is based on Diego Hernando's MATLAB fat-water toolbox, with modifications to improve performance and compatibility with Python ecosystems. The confidence map function will be integrated in the near future.

Key Features:

  • Implements complex, mixed, and magnitude fitting algorithms for water-fat separation
  • No GSL dependency
  • Utilizes Eigen C++ library for fast and efficient computations
  • Highly portable and easy to install in various environments, including MRI scanners

Background

This package builds upon the work presented at the ISMRM Workshop on Fat-Water Separation: ISMRM Fat-Water Separation Workshop

Advantages of Using Eigen:

  • No need to install third-party C++ libraries
  • Increased portability and ease of installation in various environments, including MRI scanners

Installation

This package contains C++ components and requires a compiler for installation from source. However, pre-compiled wheels are provided for common platforms (macOS, Linux), making installation easy via pip.

From PyPI (Recommended for Users)

If you just want to use the package, you can install it directly from the Python Package Index (PyPI). This method will automatically download the correct pre-compiled version for your system.

pip install PyCSEMRI

Usage

A sample code is provided in Example_ChanComb_h5.py.

Project details

Verified details

These details have been verified by PyPI
Maintainers
Avatar for dtamada from gravatar.com dtamada

Unverified details

These details have not been verified by PyPI
Project links
Meta

Release history Release notifications | RSS feed

0.2.4

0.2.2

0.1.9

0.1.7

This version

0.1.6

0.1.4

0.1.2

0.1.0

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

If you're not sure about the file name format, learn more about wheel file names.

pycsemri-0.1.6-cp312-cp312-musllinux_1_2_x86_64.whl (3.1 MB view details)

Uploaded CPython 3.12musllinux: musl 1.2+ x86-64

pycsemri-0.1.6-cp312-cp312-musllinux_1_2_i686.whl (3.2 MB view details)

Uploaded CPython 3.12musllinux: musl 1.2+ i686

pycsemri-0.1.6-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (2.1 MB view details)

Uploaded CPython 3.12manylinux: glibc 2.17+ x86-64

pycsemri-0.1.6-cp312-cp312-manylinux_2_12_i686.manylinux2010_i686.manylinux_2_17_i686.manylinux2014_i686.whl (2.1 MB view details)

Uploaded CPython 3.12manylinux: glibc 2.12+ i686manylinux: glibc 2.17+ i686

pycsemri-0.1.6-cp312-cp312-macosx_11_0_arm64.whl (2.1 MB view details)

Uploaded CPython 3.12macOS 11.0+ ARM64

pycsemri-0.1.6-cp311-cp311-musllinux_1_2_x86_64.whl (3.1 MB view details)

Uploaded CPython 3.11musllinux: musl 1.2+ x86-64

pycsemri-0.1.6-cp311-cp311-musllinux_1_2_i686.whl (3.2 MB view details)

Uploaded CPython 3.11musllinux: musl 1.2+ i686

pycsemri-0.1.6-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (2.1 MB view details)

Uploaded CPython 3.11manylinux: glibc 2.17+ x86-64

pycsemri-0.1.6-cp311-cp311-manylinux_2_12_i686.manylinux2010_i686.manylinux_2_17_i686.manylinux2014_i686.whl (2.1 MB view details)

Uploaded CPython 3.11manylinux: glibc 2.12+ i686manylinux: glibc 2.17+ i686

pycsemri-0.1.6-cp311-cp311-macosx_11_0_arm64.whl (2.1 MB view details)

Uploaded CPython 3.11macOS 11.0+ ARM64

pycsemri-0.1.6-cp310-cp310-musllinux_1_2_x86_64.whl (3.1 MB view details)

Uploaded CPython 3.10musllinux: musl 1.2+ x86-64

pycsemri-0.1.6-cp310-cp310-musllinux_1_2_i686.whl (3.2 MB view details)

Uploaded CPython 3.10musllinux: musl 1.2+ i686

pycsemri-0.1.6-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (2.1 MB view details)

Uploaded CPython 3.10manylinux: glibc 2.17+ x86-64

pycsemri-0.1.6-cp310-cp310-manylinux_2_12_i686.manylinux2010_i686.manylinux_2_17_i686.manylinux2014_i686.whl (2.1 MB view details)

Uploaded CPython 3.10manylinux: glibc 2.12+ i686manylinux: glibc 2.17+ i686

pycsemri-0.1.6-cp310-cp310-macosx_11_0_arm64.whl (2.1 MB view details)

Uploaded CPython 3.10macOS 11.0+ ARM64

pycsemri-0.1.6-cp39-cp39-musllinux_1_2_x86_64.whl (3.1 MB view details)

Uploaded CPython 3.9musllinux: musl 1.2+ x86-64

pycsemri-0.1.6-cp39-cp39-musllinux_1_2_i686.whl (3.2 MB view details)

Uploaded CPython 3.9musllinux: musl 1.2+ i686

pycsemri-0.1.6-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (2.1 MB view details)

Uploaded CPython 3.9manylinux: glibc 2.17+ x86-64

pycsemri-0.1.6-cp39-cp39-manylinux_2_12_i686.manylinux2010_i686.manylinux_2_17_i686.manylinux2014_i686.whl (2.1 MB view details)

Uploaded CPython 3.9manylinux: glibc 2.12+ i686manylinux: glibc 2.17+ i686

pycsemri-0.1.6-cp39-cp39-macosx_11_0_arm64.whl (2.1 MB view details)

Uploaded CPython 3.9macOS 11.0+ ARM64

pycsemri-0.1.6-cp38-cp38-musllinux_1_2_x86_64.whl (3.1 MB view details)

Uploaded CPython 3.8musllinux: musl 1.2+ x86-64

pycsemri-0.1.6-cp38-cp38-musllinux_1_2_i686.whl (3.2 MB view details)

Uploaded CPython 3.8musllinux: musl 1.2+ i686

pycsemri-0.1.6-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (2.1 MB view details)

Uploaded CPython 3.8manylinux: glibc 2.17+ x86-64

pycsemri-0.1.6-cp38-cp38-manylinux_2_12_i686.manylinux2010_i686.manylinux_2_17_i686.manylinux2014_i686.whl (2.1 MB view details)

Uploaded CPython 3.8manylinux: glibc 2.12+ i686manylinux: glibc 2.17+ i686

pycsemri-0.1.6-cp38-cp38-macosx_11_0_arm64.whl (2.1 MB view details)

Uploaded CPython 3.8macOS 11.0+ ARM64

PyCSEMRI-0.1.6-cp36-cp36m-musllinux_1_2_x86_64.whl (3.1 MB view details)

Uploaded CPython 3.6mmusllinux: musl 1.2+ x86-64

PyCSEMRI-0.1.6-cp36-cp36m-musllinux_1_2_i686.whl (3.2 MB view details)

Uploaded CPython 3.6mmusllinux: musl 1.2+ i686

PyCSEMRI-0.1.6-cp36-cp36m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (2.1 MB view details)

Uploaded CPython 3.6mmanylinux: glibc 2.17+ x86-64

PyCSEMRI-0.1.6-cp36-cp36m-manylinux_2_12_i686.manylinux2010_i686.manylinux_2_17_i686.manylinux2014_i686.whl (2.1 MB view details)

Uploaded CPython 3.6mmanylinux: glibc 2.12+ i686manylinux: glibc 2.17+ i686

File details

Details for the file pycsemri-0.1.6-cp312-cp312-musllinux_1_2_x86_64.whl.

File metadata

File hashes

Hashes for pycsemri-0.1.6-cp312-cp312-musllinux_1_2_x86_64.whl
Algorithm Hash digest
SHA256 a0519c7dc2d5ade97b51a50b3cbae3014b39b1b69c704b28f3c78fc76baafa67
MD5 e8a6b42b7bf8a0a2fd9bc03acd2bf268
BLAKE2b-256 8e1f1114ec363e9dde68e088689205b33b302f5471257c8ce376a39c57b6d2f8

See more details on using hashes here.

File details

Details for the file pycsemri-0.1.6-cp312-cp312-musllinux_1_2_i686.whl.

File metadata

File hashes

Hashes for pycsemri-0.1.6-cp312-cp312-musllinux_1_2_i686.whl
Algorithm Hash digest
SHA256 e096f306d5b90aac7fd8a4e1e73dccdfa9239fb9d7b19f5d467232901439995c
MD5 6c4d9f691c29909766716fce4bee1264
BLAKE2b-256 b36e765e3be06e799d1d51ecbad474b8f91b88331ed84bd3c29e0c5cfc742ad3

See more details on using hashes here.

File details

Details for the file pycsemri-0.1.6-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for pycsemri-0.1.6-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 607af89596e31c5370f6846ac2b5730b3a01f745083735114837ca69f371536c
MD5 24a37f9934e7ccd4bd0367d1a3d938bf
BLAKE2b-256 665a92899d27ced5aa8dabce1ab6cb3c0c6604263dc211df2d8ad90e90c11459

See more details on using hashes here.

File details

Details for the file pycsemri-0.1.6-cp312-cp312-manylinux_2_12_i686.manylinux2010_i686.manylinux_2_17_i686.manylinux2014_i686.whl.

File metadata

File hashes

Hashes for pycsemri-0.1.6-cp312-cp312-manylinux_2_12_i686.manylinux2010_i686.manylinux_2_17_i686.manylinux2014_i686.whl
Algorithm Hash digest
SHA256 7013eb0b93b0ad06e6fe6d6743f8f421544ae5c19f342def4c4747b25258c446
MD5 1a286759f45f7ced16496fe238f2b7b9
BLAKE2b-256 6599c4a84aae22912d3206256523ed5b11ccf61f9be7cc1063f76c6bc8efa483

See more details on using hashes here.

File details

Details for the file pycsemri-0.1.6-cp312-cp312-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for pycsemri-0.1.6-cp312-cp312-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 8dd8977264b8e4d10c654de36ebf32ad6ec3b79adf6556c1eeae81154f06f6a5
MD5 f8203853554ec511e38ee38887f7cc0c
BLAKE2b-256 bd7305eb822f4d14a20b38e558bcd489a09e74a5864b4bb7eac44055b415e46d

See more details on using hashes here.

File details

Details for the file pycsemri-0.1.6-cp311-cp311-musllinux_1_2_x86_64.whl.

File metadata

File hashes

Hashes for pycsemri-0.1.6-cp311-cp311-musllinux_1_2_x86_64.whl
Algorithm Hash digest
SHA256 66021c7b01a024e6d9b009ae088587156c065b90e69dacc93cd3b88de12dc21c
MD5 e41f0e3a43b57eb73559b7a7452ffc83
BLAKE2b-256 c53039180926871d0772c60def7dc8b51bae80cc5c255efd75f9af028cc8d838

See more details on using hashes here.

File details

Details for the file pycsemri-0.1.6-cp311-cp311-musllinux_1_2_i686.whl.

File metadata

File hashes

Hashes for pycsemri-0.1.6-cp311-cp311-musllinux_1_2_i686.whl
Algorithm Hash digest
SHA256 fa4463f86e8de1ce7e2e5ae29b631cf2b3258fab0735b4b30956fabf8171c995
MD5 583332033c1a2ff18f15f594de38b4ab
BLAKE2b-256 2d52adcf2f1b799352d9dbc9e0cccd3116fc0095e04407139cd32fc02406aaa3

See more details on using hashes here.

File details

Details for the file pycsemri-0.1.6-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for pycsemri-0.1.6-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 2aca1c0d69f2ac13634be636662a334e3dc134328da91b319450a2bc3bba6793
MD5 2b0bed5138f2dc2c0bd6b6689bba2118
BLAKE2b-256 161ee52273708c6bbbc97d73f630b1df30be2e86a7cfc7f1bf2dbc356e3aa923

See more details on using hashes here.

File details

Details for the file pycsemri-0.1.6-cp311-cp311-manylinux_2_12_i686.manylinux2010_i686.manylinux_2_17_i686.manylinux2014_i686.whl.

File metadata

File hashes

Hashes for pycsemri-0.1.6-cp311-cp311-manylinux_2_12_i686.manylinux2010_i686.manylinux_2_17_i686.manylinux2014_i686.whl
Algorithm Hash digest
SHA256 f7b6abb4983baa38a370e7ccce839bbfb5119c39d7f2ee2e286a657429022e19
MD5 7d156bcc233164e24da3e4908b0c2cb7
BLAKE2b-256 3d202ece98652a10377cbdb14d75cf78e0777c513bbe6efaa35bf23104e63020

See more details on using hashes here.

File details

Details for the file pycsemri-0.1.6-cp311-cp311-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for pycsemri-0.1.6-cp311-cp311-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 98fe97b80823f879c6601750d53f85e6b5edc1114399614d9fe342e7f7e445e2
MD5 159a9bdd10ae5d40eb7b356f0c521cbd
BLAKE2b-256 d89ffc99e48026ed64ce6b78b75ac851b29ed0a5ab87828452ca35297e522c26

See more details on using hashes here.

File details

Details for the file pycsemri-0.1.6-cp310-cp310-musllinux_1_2_x86_64.whl.

File metadata

File hashes

Hashes for pycsemri-0.1.6-cp310-cp310-musllinux_1_2_x86_64.whl
Algorithm Hash digest
SHA256 e3f167881893e39961aea1d50a40995247fec7faaa71d7fab42d77151af77234
MD5 e72633bb86b9b9f344c6d92eb290aa1b
BLAKE2b-256 2277c6763d3c01fb366cc38857e86b917d55192340840b5770420df81a62138c

See more details on using hashes here.

File details

Details for the file pycsemri-0.1.6-cp310-cp310-musllinux_1_2_i686.whl.

File metadata

File hashes

Hashes for pycsemri-0.1.6-cp310-cp310-musllinux_1_2_i686.whl
Algorithm Hash digest
SHA256 221980f264f9c6a617fa280949e659325ef7ddf599170862c634dee7d568b646
MD5 9159bd261b9af440cfae12eb892dc4fd
BLAKE2b-256 aa31f76068eaa918f1cbdd003ed66085239ef8ba0efccb1afd371f8b30c1eac9

See more details on using hashes here.

File details

Details for the file pycsemri-0.1.6-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for pycsemri-0.1.6-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 46890b5bb826bbde61f7baf8c5c53ace4d1dc8dd1d4d2209a5600aa10f420651
MD5 5938b1a3f15c461184733c451c63941a
BLAKE2b-256 ee69ae95ba76507413ca00a5085d418dc877edc281137b02eda679e47f11d770

See more details on using hashes here.

File details

Details for the file pycsemri-0.1.6-cp310-cp310-manylinux_2_12_i686.manylinux2010_i686.manylinux_2_17_i686.manylinux2014_i686.whl.

File metadata

File hashes

Hashes for pycsemri-0.1.6-cp310-cp310-manylinux_2_12_i686.manylinux2010_i686.manylinux_2_17_i686.manylinux2014_i686.whl
Algorithm Hash digest
SHA256 13677e5589774c27d4d848053cac74a63e96c71e5c702e18c408873f9fee6628
MD5 6ebe9ab3e32f938a054d1eaf19208758
BLAKE2b-256 e3accb17143533be940e3e9eedaec36bebed25d963d7de4197d17735e2d6022e

See more details on using hashes here.

File details

Details for the file pycsemri-0.1.6-cp310-cp310-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for pycsemri-0.1.6-cp310-cp310-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 1b6e170cf44214c23a6e55e6f4a96906fedace6104d8efc8bb55db615f752632
MD5 f590e1c815fb06017ccc29bf91144a05
BLAKE2b-256 9dea7e866710fb8d69820064db281dd052666d630bb603227f29374f484b2b61

See more details on using hashes here.

File details

Details for the file pycsemri-0.1.6-cp39-cp39-musllinux_1_2_x86_64.whl.

File metadata

File hashes

Hashes for pycsemri-0.1.6-cp39-cp39-musllinux_1_2_x86_64.whl
Algorithm Hash digest
SHA256 01e8dc2ca39934820d1b142df4d5199b894c49dfe99d5d666406dbb3bf7bc311
MD5 29b3c34cab2dca42bcd408274f695f09
BLAKE2b-256 d286ae6ec41f86f511fd337e7b030c69a15269e754db033839fbf4e7a73908c0

See more details on using hashes here.

File details

Details for the file pycsemri-0.1.6-cp39-cp39-musllinux_1_2_i686.whl.

File metadata

File hashes

Hashes for pycsemri-0.1.6-cp39-cp39-musllinux_1_2_i686.whl
Algorithm Hash digest
SHA256 8e905fd56115cbc559082a87df4a3bb32aba299188b76dea65b89f942a0dedf7
MD5 54fc6079a25eaa24198f94a2d7594209
BLAKE2b-256 ab524a641db749b51728b62f4397c9bc7ee1f5678fe1d138e53333e5fad675fa

See more details on using hashes here.

File details

Details for the file pycsemri-0.1.6-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for pycsemri-0.1.6-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 bba7d98b47952d26e4a01332f422ec15f513b1e4e511873b6d10f84aa3948316
MD5 82136fb91f2a8aa606b58940bffed977
BLAKE2b-256 e0f7142606776e66bec21ae71014ddd05f731321b08118cebfacd07c4b569ee5

See more details on using hashes here.

File details

Details for the file pycsemri-0.1.6-cp39-cp39-manylinux_2_12_i686.manylinux2010_i686.manylinux_2_17_i686.manylinux2014_i686.whl.

File metadata

File hashes

Hashes for pycsemri-0.1.6-cp39-cp39-manylinux_2_12_i686.manylinux2010_i686.manylinux_2_17_i686.manylinux2014_i686.whl
Algorithm Hash digest
SHA256 6f70cc3969c29bc9230162bb6ff57e6f32e37db4d1ccd4ba13acd18ba51bfcc1
MD5 82998a708bd1a877c381b8294090c96d
BLAKE2b-256 3faa07387bc24af6f02dcedbc1fa243a368d3709f14f65feacb79f827276d6a6

See more details on using hashes here.

File details

Details for the file pycsemri-0.1.6-cp39-cp39-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for pycsemri-0.1.6-cp39-cp39-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 5c85bf8c923621482a39c6a4eb3d6f21e9daecfd6f46ced274178a98dc4f860a
MD5 52a991cb352e22af05a4dc5cf37580d9
BLAKE2b-256 e9a66ba9c8a396ff60c75920537e8279798cc18341f4432ac9374c3eb781d2ce

See more details on using hashes here.

File details

Details for the file pycsemri-0.1.6-cp38-cp38-musllinux_1_2_x86_64.whl.

File metadata

File hashes

Hashes for pycsemri-0.1.6-cp38-cp38-musllinux_1_2_x86_64.whl
Algorithm Hash digest
SHA256 cb424bb3cc3f8f5354212555a854897ef9332832e49de488238f0ea5748d9065
MD5 eaebbbd2764d23b1ffc2e34f1f302894
BLAKE2b-256 d30e5c940bfc84ca6b48debb6a4a23d6297291326852aef26218a98bd3addf9d

See more details on using hashes here.

File details

Details for the file pycsemri-0.1.6-cp38-cp38-musllinux_1_2_i686.whl.

File metadata

File hashes

Hashes for pycsemri-0.1.6-cp38-cp38-musllinux_1_2_i686.whl
Algorithm Hash digest
SHA256 101287568a009e1fc4159c410440ae09bd7f04662e810efafaf65b7087e8c6dc
MD5 2928bd27d7b7315eb8c3d768b64e011a
BLAKE2b-256 dedc452e835d190d7dcd5efffb50ffaf39869274879017108e4c881a3752eb55

See more details on using hashes here.

File details

Details for the file pycsemri-0.1.6-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for pycsemri-0.1.6-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 2448e0c96d641e5ef88cc016b475f59406602c59008a87264ad378c284a6d7dc
MD5 81ecb8aec58803fb1d1d2c99d4efed9e
BLAKE2b-256 bef7e264b4458707da3db8ac17888fd9ba5bc797d18a75a733b7de9628b94765

See more details on using hashes here.

File details

Details for the file pycsemri-0.1.6-cp38-cp38-manylinux_2_12_i686.manylinux2010_i686.manylinux_2_17_i686.manylinux2014_i686.whl.

File metadata

File hashes

Hashes for pycsemri-0.1.6-cp38-cp38-manylinux_2_12_i686.manylinux2010_i686.manylinux_2_17_i686.manylinux2014_i686.whl
Algorithm Hash digest
SHA256 4c1d6048c0f25a20605df909bbe9d90d2f676a02347e6efaf89eb70fb6ef3fe7
MD5 29ec44570ab76fac6da560741cbc99f6
BLAKE2b-256 dd48bf397070a4a15938fa8ef36c9e93ffd82553bfc7ff5cdf244e7d427c22af

See more details on using hashes here.

File details

Details for the file pycsemri-0.1.6-cp38-cp38-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for pycsemri-0.1.6-cp38-cp38-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 4c8f87e2b1c819b822a15daf895f22da4de873e9603657d79e6741a7fe798d07
MD5 918da7b454c45b262aeb5796e1beea27
BLAKE2b-256 2f498e19e7e3e22d58839c9efebb8d8904032b0924a48a5d2be5f8735a183424

See more details on using hashes here.

File details

Details for the file PyCSEMRI-0.1.6-cp36-cp36m-musllinux_1_2_x86_64.whl.

File metadata

File hashes

Hashes for PyCSEMRI-0.1.6-cp36-cp36m-musllinux_1_2_x86_64.whl
Algorithm Hash digest
SHA256 c472b26855ae66c1ef15e85876fe216d3f2f198292ea27669d6faa3339293c81
MD5 29c8caaabf9caf3ed0611bcc135c6260
BLAKE2b-256 d5d09a1b9f9752c7e835d5643d8b865d75fcdb33d5658019764324f21203dc8c

See more details on using hashes here.

File details

Details for the file PyCSEMRI-0.1.6-cp36-cp36m-musllinux_1_2_i686.whl.

File metadata

File hashes

Hashes for PyCSEMRI-0.1.6-cp36-cp36m-musllinux_1_2_i686.whl
Algorithm Hash digest
SHA256 4e5d3147c1f78a47d1631d8e7cd4e141be6341d0b318bdd1bbb2c94898a8ec4c
MD5 22027f3ee771288979435018b6953c7a
BLAKE2b-256 bf195cbaaa8509be1fb20e2a131129bbebb8931c2a61c6dc70aef0ce1d430fa0

See more details on using hashes here.

File details

Details for the file PyCSEMRI-0.1.6-cp36-cp36m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for PyCSEMRI-0.1.6-cp36-cp36m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 d5923b4e6e82d40ba32f9288bf8c4889a207222c38cecab25672c362c607ea4f
MD5 e89680f288290fb56ec9a06537c156de
BLAKE2b-256 b3adfa400fccbf3d070973cd1894f23cb30d2c47a9e6490810a3a7adc1f6ffa4

See more details on using hashes here.

File details

Details for the file PyCSEMRI-0.1.6-cp36-cp36m-manylinux_2_12_i686.manylinux2010_i686.manylinux_2_17_i686.manylinux2014_i686.whl.

File metadata

File hashes

Hashes for PyCSEMRI-0.1.6-cp36-cp36m-manylinux_2_12_i686.manylinux2010_i686.manylinux_2_17_i686.manylinux2014_i686.whl
Algorithm Hash digest
SHA256 81313158b21f6525a24b0ded6c35049f659e79c55e83428f99399bf1b0605af3
MD5 6fb48fdfb7227afe704a3353c1588e96
BLAKE2b-256 8660069f5db38d1cbcc061aa8ebf292f281f043007676e1fcc17134a2aed86e6

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page