Skip to main content

A package for CSEMRI with C++ accelerated components.

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


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-0.1.2-cp312-cp312-musllinux_1_2_x86_64.whl (3.1 MB view details)

Uploaded CPython 3.12musllinux: musl 1.2+ x86-64

pycsemri-0.1.2-cp312-cp312-musllinux_1_2_i686.whl (3.2 MB view details)

Uploaded CPython 3.12musllinux: musl 1.2+ i686

pycsemri-0.1.2-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-0.1.2-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-0.1.2-cp312-cp312-macosx_11_0_arm64.whl (2.1 MB view details)

Uploaded CPython 3.12macOS 11.0+ ARM64

pycsemri-0.1.2-cp311-cp311-musllinux_1_2_x86_64.whl (3.1 MB view details)

Uploaded CPython 3.11musllinux: musl 1.2+ x86-64

pycsemri-0.1.2-cp311-cp311-musllinux_1_2_i686.whl (3.2 MB view details)

Uploaded CPython 3.11musllinux: musl 1.2+ i686

pycsemri-0.1.2-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-0.1.2-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-0.1.2-cp311-cp311-macosx_11_0_arm64.whl (2.1 MB view details)

Uploaded CPython 3.11macOS 11.0+ ARM64

pycsemri-0.1.2-cp310-cp310-musllinux_1_2_x86_64.whl (3.1 MB view details)

Uploaded CPython 3.10musllinux: musl 1.2+ x86-64

pycsemri-0.1.2-cp310-cp310-musllinux_1_2_i686.whl (3.2 MB view details)

Uploaded CPython 3.10musllinux: musl 1.2+ i686

pycsemri-0.1.2-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-0.1.2-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-0.1.2-cp310-cp310-macosx_11_0_arm64.whl (2.1 MB view details)

Uploaded CPython 3.10macOS 11.0+ ARM64

pycsemri-0.1.2-cp39-cp39-musllinux_1_2_x86_64.whl (3.1 MB view details)

Uploaded CPython 3.9musllinux: musl 1.2+ x86-64

pycsemri-0.1.2-cp39-cp39-musllinux_1_2_i686.whl (3.2 MB view details)

Uploaded CPython 3.9musllinux: musl 1.2+ i686

pycsemri-0.1.2-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-0.1.2-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-0.1.2-cp39-cp39-macosx_11_0_arm64.whl (2.1 MB view details)

Uploaded CPython 3.9macOS 11.0+ ARM64

pycsemri-0.1.2-cp38-cp38-musllinux_1_2_x86_64.whl (3.1 MB view details)

Uploaded CPython 3.8musllinux: musl 1.2+ x86-64

pycsemri-0.1.2-cp38-cp38-musllinux_1_2_i686.whl (3.2 MB view details)

Uploaded CPython 3.8musllinux: musl 1.2+ i686

pycsemri-0.1.2-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-0.1.2-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-0.1.2-cp38-cp38-macosx_11_0_arm64.whl (2.1 MB view details)

Uploaded CPython 3.8macOS 11.0+ ARM64

PyCSEMRI-0.1.2-cp36-cp36m-musllinux_1_2_x86_64.whl (3.1 MB view details)

Uploaded CPython 3.6mmusllinux: musl 1.2+ x86-64

PyCSEMRI-0.1.2-cp36-cp36m-musllinux_1_2_i686.whl (3.2 MB view details)

Uploaded CPython 3.6mmusllinux: musl 1.2+ i686

PyCSEMRI-0.1.2-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-0.1.2-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-0.1.2-cp312-cp312-musllinux_1_2_x86_64.whl.

File metadata

File hashes

Hashes for pycsemri-0.1.2-cp312-cp312-musllinux_1_2_x86_64.whl
Algorithm Hash digest
SHA256 e62e17d2609e07f38f4d5caf003e640da9deb3c11870b88df6f4dd016d2898a9
MD5 c20c9c921e1c69fa76dc1c74d0fd5891
BLAKE2b-256 e55aab68b538dc44b1192ead28c91eade554e4b04a3c78406e1fd7d32a2b12f8

See more details on using hashes here.

File details

Details for the file pycsemri-0.1.2-cp312-cp312-musllinux_1_2_i686.whl.

File metadata

File hashes

Hashes for pycsemri-0.1.2-cp312-cp312-musllinux_1_2_i686.whl
Algorithm Hash digest
SHA256 32f5bd2eb19731c34616388794c8ed249e5c25638140f574134d86def0d52c47
MD5 7203eb8bb4c38d43a1d531d0d904cd00
BLAKE2b-256 c06599ef433a7d53d7835bca22ec534cbd197aa67591c9c719a2985f2e03d63a

See more details on using hashes here.

File details

Details for the file pycsemri-0.1.2-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for pycsemri-0.1.2-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 ee47ca16ee084774bffabbfd9d7a4cab71793dfe101d1dc73dbe458eabf6f2ee
MD5 5a4e2b6127e62b96ac9258840f2ff32b
BLAKE2b-256 714351e3f761cb92fdfa056efd6ddfc9d4d70c0846b663dcb061b7f3d9d3d0ce

See more details on using hashes here.

File details

Details for the file pycsemri-0.1.2-cp312-cp312-manylinux_2_12_i686.manylinux2010_i686.manylinux_2_17_i686.manylinux2014_i686.whl.

File metadata

File hashes

Hashes for pycsemri-0.1.2-cp312-cp312-manylinux_2_12_i686.manylinux2010_i686.manylinux_2_17_i686.manylinux2014_i686.whl
Algorithm Hash digest
SHA256 ab4f2b9b25d498c752ab1fded4bfafcd256724a6b1c68314c6576f5c834ec6ef
MD5 bdb8c0b69ae511ce243431b2c4a2d126
BLAKE2b-256 4e5e01a72eff6581fd59cd626f90b05a015354003e4b6a37ba1f4719a32c3384

See more details on using hashes here.

File details

Details for the file pycsemri-0.1.2-cp312-cp312-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for pycsemri-0.1.2-cp312-cp312-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 e2f51d23f91a9722a8f6c7716b6dddd0d4a04fe5d6545f32dca3ce6fcd94623c
MD5 5e263ea1ea81c4af0cfaa3183efd2682
BLAKE2b-256 cf4bbe9096914d421b56df0c0be84992230684a44b2168e1961ba81051034cb6

See more details on using hashes here.

File details

Details for the file pycsemri-0.1.2-cp311-cp311-musllinux_1_2_x86_64.whl.

File metadata

File hashes

Hashes for pycsemri-0.1.2-cp311-cp311-musllinux_1_2_x86_64.whl
Algorithm Hash digest
SHA256 c3c0c75692f6281c5f3a4abf357781ea619649bab612cac651c5d9724a8a2114
MD5 50e6f1871a2f6300134348fa26eccd05
BLAKE2b-256 7a387512f30d626d99a599cfb3b2558b35711656ea39d5f8ab707a316425465c

See more details on using hashes here.

File details

Details for the file pycsemri-0.1.2-cp311-cp311-musllinux_1_2_i686.whl.

File metadata

File hashes

Hashes for pycsemri-0.1.2-cp311-cp311-musllinux_1_2_i686.whl
Algorithm Hash digest
SHA256 bf7a52161d1ef451a9345ca92260945e7297196576adf545184b91a8b64bf90e
MD5 276c83d05b77c962f6b5abc087733065
BLAKE2b-256 87a7310dd65d058df149d5c99ad23b0b6c2837fde9405d92c873486b94b1ae72

See more details on using hashes here.

File details

Details for the file pycsemri-0.1.2-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for pycsemri-0.1.2-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 d8e8ea1f579c7e7af0993499f1511132440142002f329654f908791ad7c9e7f3
MD5 4c393ceec69078ec5eeaba850f4e6a33
BLAKE2b-256 2db3bc188f3fb34cd3b12eafdb1c1b572a04f9781fbc0d76cad98b96d735df5a

See more details on using hashes here.

File details

Details for the file pycsemri-0.1.2-cp311-cp311-manylinux_2_12_i686.manylinux2010_i686.manylinux_2_17_i686.manylinux2014_i686.whl.

File metadata

File hashes

Hashes for pycsemri-0.1.2-cp311-cp311-manylinux_2_12_i686.manylinux2010_i686.manylinux_2_17_i686.manylinux2014_i686.whl
Algorithm Hash digest
SHA256 5fb8525fdcca5825781e137f95e1992d5eb670736504e6df92fc717c0268d949
MD5 003f8fe33621e24aade22083b1c0e9c4
BLAKE2b-256 b84241b56a0e19dbeb9e672f10569df272eda82eff322e392150c7ad64fd1fd4

See more details on using hashes here.

File details

Details for the file pycsemri-0.1.2-cp311-cp311-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for pycsemri-0.1.2-cp311-cp311-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 679a1775796a80a01c462223a9fdfbac682d45157c5ad74054d221139fe54162
MD5 e417b480c1d2525fc2785fd6ee3f70fb
BLAKE2b-256 4df8cf7adc18d63820971513691bdf7d0a65c80c3ef306700f5fbdde558f2714

See more details on using hashes here.

File details

Details for the file pycsemri-0.1.2-cp310-cp310-musllinux_1_2_x86_64.whl.

File metadata

File hashes

Hashes for pycsemri-0.1.2-cp310-cp310-musllinux_1_2_x86_64.whl
Algorithm Hash digest
SHA256 e9fd4848579593633d6ff9364983a92fd1ed524cfcb4f24c016ab564cb4ca80e
MD5 89f1b01f9c4e3e91e05c5afcf4b8cf0c
BLAKE2b-256 1cc3de59d561719a97d5033880881722151af0b2cb0da1ba863f94716b5a21cb

See more details on using hashes here.

File details

Details for the file pycsemri-0.1.2-cp310-cp310-musllinux_1_2_i686.whl.

File metadata

File hashes

Hashes for pycsemri-0.1.2-cp310-cp310-musllinux_1_2_i686.whl
Algorithm Hash digest
SHA256 3833e6cfbc322955ba4fd433ccfae2222160ec90f27a1f5b13362ce90db25db0
MD5 cb119f12e8888549f1a96399d5ffb877
BLAKE2b-256 b54fc3c3d7e539b2ecd1d393fbe7039ecea3f0ff5eafd8e06c75f3e977fb4424

See more details on using hashes here.

File details

Details for the file pycsemri-0.1.2-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for pycsemri-0.1.2-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 942d5778e8b1058e664b4eeaa7e8c85ab3e86cf53c22470ee0d835e6a87454f7
MD5 b831d27d4ba8c10d4534180caaed7ee9
BLAKE2b-256 4fd153ce8a418221e2624639703b15f4f192083948367b871c86bdbedba48d91

See more details on using hashes here.

File details

Details for the file pycsemri-0.1.2-cp310-cp310-manylinux_2_12_i686.manylinux2010_i686.manylinux_2_17_i686.manylinux2014_i686.whl.

File metadata

File hashes

Hashes for pycsemri-0.1.2-cp310-cp310-manylinux_2_12_i686.manylinux2010_i686.manylinux_2_17_i686.manylinux2014_i686.whl
Algorithm Hash digest
SHA256 6b0138c9f324110d56d74f36a16fe5faa3169452bdf91811934da63a05e0670b
MD5 de8aa115c888eab818ae5f921a480696
BLAKE2b-256 8b2695c42d865cd60c941a7a8d1c65e42471eb0d666b80c9ce05655c1a89599d

See more details on using hashes here.

File details

Details for the file pycsemri-0.1.2-cp310-cp310-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for pycsemri-0.1.2-cp310-cp310-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 33c5d3b16b9cd001fcf5e344cfe61d01c85eefa3c97365a701a708c7a16b48c0
MD5 c737ad51da136933242112a8b23ce546
BLAKE2b-256 3f3eeccbdb727e8e2420ed6da6f15d77b40d7a490974ca6d6b6e11b7452d829d

See more details on using hashes here.

File details

Details for the file pycsemri-0.1.2-cp39-cp39-musllinux_1_2_x86_64.whl.

File metadata

File hashes

Hashes for pycsemri-0.1.2-cp39-cp39-musllinux_1_2_x86_64.whl
Algorithm Hash digest
SHA256 03237da70fd5034690fc33ae50d88ba3ab8ca215928074e4767ae8b766f27b7a
MD5 85729f3c4919c504d0998a5b2af7251c
BLAKE2b-256 65bd9342ae5b1431e7efe4f760230d8a8795625ef22ff7dfcb3ed5edc692ea1e

See more details on using hashes here.

File details

Details for the file pycsemri-0.1.2-cp39-cp39-musllinux_1_2_i686.whl.

File metadata

File hashes

Hashes for pycsemri-0.1.2-cp39-cp39-musllinux_1_2_i686.whl
Algorithm Hash digest
SHA256 f3af2c985609ae85dbabf262b84e5436a2c35dfaf05751140d73005f6e99119d
MD5 4acd7dc87e227c433606bd42ed93577c
BLAKE2b-256 73fa023479a6e64e684a1fbb786992d1d96930c277bf1b906f9f69d5fc721740

See more details on using hashes here.

File details

Details for the file pycsemri-0.1.2-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for pycsemri-0.1.2-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 d3347c3cc55058e564445bce85a862c032da4952e4fd4190a9b7796e93797b82
MD5 9c21fc9de00dea7482727388f200a02e
BLAKE2b-256 dd2833a7644b1dcf1edeadde8641a5837b9f2f77be0fd5ab62d4f829ac45fce0

See more details on using hashes here.

File details

Details for the file pycsemri-0.1.2-cp39-cp39-manylinux_2_12_i686.manylinux2010_i686.manylinux_2_17_i686.manylinux2014_i686.whl.

File metadata

File hashes

Hashes for pycsemri-0.1.2-cp39-cp39-manylinux_2_12_i686.manylinux2010_i686.manylinux_2_17_i686.manylinux2014_i686.whl
Algorithm Hash digest
SHA256 9d2f113475c1520caf316fd568a455219c3cef9032812c6f00b6a71dfbc4f659
MD5 8bf9e7d4df2d0d88cb0a6579cec361e7
BLAKE2b-256 5cb4a4432b9453b6541a82d0ba6cd797a00397d1488a66863cac05002fe764f1

See more details on using hashes here.

File details

Details for the file pycsemri-0.1.2-cp39-cp39-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for pycsemri-0.1.2-cp39-cp39-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 7341cfe1ffc0f0b58e4c36417e474e5287e917513b1daab2d41e327d18e51839
MD5 6ac775ce693c7ac61c8adb6e246309ab
BLAKE2b-256 55a5e2120b2de561b221af85e1330d2db3e330e23fa25e96872f155aeef2a709

See more details on using hashes here.

File details

Details for the file pycsemri-0.1.2-cp38-cp38-musllinux_1_2_x86_64.whl.

File metadata

File hashes

Hashes for pycsemri-0.1.2-cp38-cp38-musllinux_1_2_x86_64.whl
Algorithm Hash digest
SHA256 abf8327b5c40f56a658ff29636c518837b77bbc5ff520ff37361ebf327c89656
MD5 2214643948b59243a2a88775da6e9c33
BLAKE2b-256 45d92e41d94b247568cef5d297f2ad5e90ff3a933ccae498de145af20293b15b

See more details on using hashes here.

File details

Details for the file pycsemri-0.1.2-cp38-cp38-musllinux_1_2_i686.whl.

File metadata

File hashes

Hashes for pycsemri-0.1.2-cp38-cp38-musllinux_1_2_i686.whl
Algorithm Hash digest
SHA256 03dbb7a067d3fd135df2c8fca019dc565bc71b1a950ce5add71634d79069ba7e
MD5 2a1ba8bdc871edfc627fd5844a6c5fbc
BLAKE2b-256 14c44e9225f485d603972a2e6c3862189587ecca94010eda0ca8396ecd5dbd94

See more details on using hashes here.

File details

Details for the file pycsemri-0.1.2-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for pycsemri-0.1.2-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 7780669cf500765ef84fa40bbddc03681904a0ca4599ae2fd84ab8d0c172c4e8
MD5 e631e2407e6da9b7ec48bc1f7d323c63
BLAKE2b-256 2a37b0105fefec59147dfaf464fd4b1f719a3e764a5aafbbdb423034521f3fa2

See more details on using hashes here.

File details

Details for the file pycsemri-0.1.2-cp38-cp38-manylinux_2_12_i686.manylinux2010_i686.manylinux_2_17_i686.manylinux2014_i686.whl.

File metadata

File hashes

Hashes for pycsemri-0.1.2-cp38-cp38-manylinux_2_12_i686.manylinux2010_i686.manylinux_2_17_i686.manylinux2014_i686.whl
Algorithm Hash digest
SHA256 7556167d483ff6f9b2c1fa8e379cfe226310f372a32e19222e4ff4847710efd9
MD5 8d8918b3b94ddb711212d44098c6f3e9
BLAKE2b-256 3a8056bf94f87218d59a401cdf3c76a3488d3e2a6598d51488d650d3908bd706

See more details on using hashes here.

File details

Details for the file pycsemri-0.1.2-cp38-cp38-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for pycsemri-0.1.2-cp38-cp38-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 be3617d8cfedcdd401d6ff6f59e5724b8f83f7a23f4b14a3642263e3be8cfe3b
MD5 f0bab28a46bd073428364902a9517f81
BLAKE2b-256 0854632e12c6049187005afff71bd476aee94423943712a924440888e9dd1379

See more details on using hashes here.

File details

Details for the file PyCSEMRI-0.1.2-cp36-cp36m-musllinux_1_2_x86_64.whl.

File metadata

File hashes

Hashes for PyCSEMRI-0.1.2-cp36-cp36m-musllinux_1_2_x86_64.whl
Algorithm Hash digest
SHA256 e5cb2086c5fc93ba4b2d97cae2d641255c4e2cda0af223b042af5c84fed956ae
MD5 25f0dafe1d5190472da8a0a0b7ce42b2
BLAKE2b-256 45a066b96a4d5646e16ce25f81d8aa08c8f974bea684aa7e6decfb18ee11d49a

See more details on using hashes here.

File details

Details for the file PyCSEMRI-0.1.2-cp36-cp36m-musllinux_1_2_i686.whl.

File metadata

File hashes

Hashes for PyCSEMRI-0.1.2-cp36-cp36m-musllinux_1_2_i686.whl
Algorithm Hash digest
SHA256 f2d2659e182003e3dbd287e59d27ac5547ebddce683b4ffdc28c760052841ee7
MD5 e2a2ef5e88234741065eaee474080040
BLAKE2b-256 dcc7adf8c582673e6df8f441a4a444633a343dcc9040310b19aeb8e89b1a6a93

See more details on using hashes here.

File details

Details for the file PyCSEMRI-0.1.2-cp36-cp36m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for PyCSEMRI-0.1.2-cp36-cp36m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 01aaa87242c8cdb8e8dca462a833067a6710a7837de36f70c1dbd9bc9a9a4ac8
MD5 dbe09e28790d59b782099dd9fbb7e4d0
BLAKE2b-256 26e96c9502b84688ea026195b00a1aa7a316c0efe20b4ba7c806c2e1ed338a5f

See more details on using hashes here.

File details

Details for the file PyCSEMRI-0.1.2-cp36-cp36m-manylinux_2_12_i686.manylinux2010_i686.manylinux_2_17_i686.manylinux2014_i686.whl.

File metadata

File hashes

Hashes for PyCSEMRI-0.1.2-cp36-cp36m-manylinux_2_12_i686.manylinux2010_i686.manylinux_2_17_i686.manylinux2014_i686.whl
Algorithm Hash digest
SHA256 d487d7d75fea652fadd7199d2c3643ba0e3011c874adadb1c3e41ba8479e5eb8
MD5 ed8117edabdaaf0d9c4f199e9e8fb08b
BLAKE2b-256 a84fbb3899dee75e22b9f428ef975163e5326ce4a149ed359b97baa50b1512a6

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