multimodars

"One package to fuse them all."

— The Lord of the Rings (probably)

A high‑performance, Rust‑accelerated toolkit for multi‑modality cardiac image fusion and registration ﮩ٨ـﮩﮩ٨ـ♡ﮩ٨ـﮩﮩ٨ـ.

Overview

multimoda-rs aligns and fuses diverse cardiac imaging modalities — IVUS, OCT and CCTA — into unified high-resolution 3D models. Originally developed to quantify dynamic lumen deformation in coronary artery anomalies (CAAs), it is equally applicable to longitudinal studies (e.g., pre/post-stenting) and general coronary artery disease workflows. The Rust backend parallelizes computationally intensive registration steps for speeds well beyond pure Python.

Key Features

Intravascular Registration: align pullback sequences (rest/stress, diastole/systole) using Hausdorff distance on vessel contours and catheter centroids; four modes: full, double-pair, single-pair, single.
Centerline Alignment: register intravascular geometries onto a CCTA-derived centerline via three-point landmark or manual rotation.
CCTA Fusion: automatically label CCTA geometries by vessel region and morph them to match intravascular measurements.
Flexible Input: accepts CSV files (AIVUS format) or raw NumPy arrays.

Installation

pip install multimodars

Optional extras:

pip install "multimodars[viz]"      # mesh visualisation (pyglet)
pip install "multimodars[meshlab]"  # MeshLab integration

For building from source or the full developer setup (tests, linting, docs), see the Installation guide.

Quick Example

Checkout our Documentation for in-depth explanations of the functionality and preloaded notebooks including 3D plots. Otherwise clone the repo to follow along the different examples:

import multimodars as mm
import numpy as np

# Align four intravascular phases (rest-dia, rest-sys, stress-dia, stress-sys)
rest, stress, dia, sys, _ = mm.from_file_full(
    "examples/data/ivus_rest",    # input_path_ab
    "examples/data/ivus_stress",  # input_path_cd
    write_obj=True,
    output_path_ab="output/rest",
    output_path_cd="output/stress",
    output_path_ac="output/diastole",
    output_path_bd="output/systole",
)

# Align geometry onto a CCTA-derived centerline
cl_raw = np.genfromtxt("examples/data/centerline_raw.csv", delimiter=",")
centerline = mm.numpy_to_centerline(cl_raw)
aligned_pair, cl_resampled = mm.align_three_point(
    centerline, rest,
    main_ref_pt=(12.2605, -201.3643, 1751.0554),
    counterclockwise_ref_pt=(11.7567, -202.1920, 1754.7975),
    clockwise_ref_pt=(15.6605, -202.1920, 1749.9655),
    write=True,
    output_dir="output/aligned",
)

Pipeline

1. Intrapullback alignment — frames within each pullback are co-registered to remove cardiac-motion artefacts, yielding clean diastolic and systolic geometries:

Dynamic lumen changes

2. Inter-pullback alignment — registered pullbacks (rest vs. stress, diastole vs. systole) are aligned against each other to reveal stress-induced and pulsatile deformation:

Stress-induced diastolic lumen deformation

3. CCTA labeling — the CCTA-derived geometry is automatically segmented by vessel region (aorta, RCA, LCA, intramural) to prepare it for fusion:

Initial CCTA labeling

4. CCTA–morphing — the labeled CCTA geometry is morphed along the centerline to match the high-resolution intravascular geometry:

CCTA scaling

5. CCTA/intravascular fusio — the morphed CCTA geometry is stitched to the intravascular geometry, replacing a section with a high resolution verison:

CCTA fusion

Documentation

Full documentation — installation, step-by-step tutorials, interactive (preloaded) Jupyter notebooks, and API reference — is available at multimoda-rs.readthedocs.io.

License

Distributed under the MIT License. See LICENSE for details.

Citation

Please kindly cite the following paper if you use this repository.

@article{Stark2026, 
  doi = {10.21105/joss.10131}, 
  url = {https://doi.org/10.21105/joss.10131}, 
  year = {2026}, 
  publisher = {The Open Journal}, 
  volume = {11}, 
  number = {121}, 
  pages = {10131}, 
  author = {Stark, Anselm W. and Ilic, Marc and Mokhtari, Ali and Kazaj, Pooya Mohammadi and Gräni, Christoph and Shiri, Isaac}, 
  title = {multimodars: A Rust-powered toolkit for multi-modality cardiac image fusion and registration}, 
  journal = {Journal of Open Source Software} 
}

Stark et al., (2026). multimodars: A Rust-powered toolkit for multi-modality cardiac image fusion and registration. Journal of Open Source Software, 11(121), 10131, https://doi.org/10.21105/joss.10131.

Download files

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

Source Distribution

multimodars-0.5.4.tar.gz (6.1 MB view details)

Uploaded Aug 3, 2026 Source

Built Distributions

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

The dropdown lists show the available interpreters, ABIs, and platforms. Enable javascript to be able to filter the list of wheel files.

multimodars-0.5.4-pp311-pypy311_pp73-musllinux_1_2_x86_64.whl (3.3 MB view details)

Uploaded Aug 3, 2026 PyPymusllinux: musl 1.2+ x86-64

multimodars-0.5.4-pp311-pypy311_pp73-musllinux_1_2_i686.whl (3.4 MB view details)

Uploaded Aug 3, 2026 PyPymusllinux: musl 1.2+ i686

multimodars-0.5.4-pp311-pypy311_pp73-musllinux_1_2_armv7l.whl (3.2 MB view details)

Uploaded Aug 3, 2026 PyPymusllinux: musl 1.2+ ARMv7l

multimodars-0.5.4-pp311-pypy311_pp73-musllinux_1_2_aarch64.whl (3.2 MB view details)

Uploaded Aug 3, 2026 PyPymusllinux: musl 1.2+ ARM64

multimodars-0.5.4-pp311-pypy311_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (3.1 MB view details)

Uploaded Aug 3, 2026 PyPymanylinux: glibc 2.17+ x86-64

multimodars-0.5.4-pp311-pypy311_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl (3.0 MB view details)

Uploaded Aug 3, 2026 PyPymanylinux: glibc 2.17+ ARM64

multimodars-0.5.4-cp315-cp315t-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (3.1 MB view details)

Uploaded Aug 3, 2026 CPython 3.15tmanylinux: glibc 2.17+ x86-64

multimodars-0.5.4-cp315-cp315-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (3.1 MB view details)

Uploaded Aug 3, 2026 CPython 3.15manylinux: glibc 2.17+ x86-64

multimodars-0.5.4-cp314-cp314t-musllinux_1_2_x86_64.whl (3.3 MB view details)

Uploaded Aug 3, 2026 CPython 3.14tmusllinux: musl 1.2+ x86-64

multimodars-0.5.4-cp314-cp314t-musllinux_1_2_i686.whl (3.4 MB view details)

Uploaded Aug 3, 2026 CPython 3.14tmusllinux: musl 1.2+ i686

multimodars-0.5.4-cp314-cp314t-musllinux_1_2_armv7l.whl (3.2 MB view details)

Uploaded Aug 3, 2026 CPython 3.14tmusllinux: musl 1.2+ ARMv7l

multimodars-0.5.4-cp314-cp314t-musllinux_1_2_aarch64.whl (3.1 MB view details)

Uploaded Aug 3, 2026 CPython 3.14tmusllinux: musl 1.2+ ARM64

multimodars-0.5.4-cp314-cp314t-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (3.1 MB view details)

Uploaded Aug 3, 2026 CPython 3.14tmanylinux: glibc 2.17+ x86-64

multimodars-0.5.4-cp314-cp314t-manylinux_2_17_aarch64.manylinux2014_aarch64.whl (3.0 MB view details)

Uploaded Aug 3, 2026 CPython 3.14tmanylinux: glibc 2.17+ ARM64

multimodars-0.5.4-cp314-cp314-win_amd64.whl (2.7 MB view details)

Uploaded Aug 3, 2026 CPython 3.14Windows x86-64

multimodars-0.5.4-cp314-cp314-musllinux_1_2_x86_64.whl (3.3 MB view details)

Uploaded Aug 3, 2026 CPython 3.14musllinux: musl 1.2+ x86-64

multimodars-0.5.4-cp314-cp314-musllinux_1_2_i686.whl (3.4 MB view details)

Uploaded Aug 3, 2026 CPython 3.14musllinux: musl 1.2+ i686

multimodars-0.5.4-cp314-cp314-musllinux_1_2_armv7l.whl (3.2 MB view details)

Uploaded Aug 3, 2026 CPython 3.14musllinux: musl 1.2+ ARMv7l

multimodars-0.5.4-cp314-cp314-musllinux_1_2_aarch64.whl (3.1 MB view details)

Uploaded Aug 3, 2026 CPython 3.14musllinux: musl 1.2+ ARM64

multimodars-0.5.4-cp314-cp314-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (3.1 MB view details)

Uploaded Aug 3, 2026 CPython 3.14manylinux: glibc 2.17+ x86-64

multimodars-0.5.4-cp314-cp314-manylinux_2_17_aarch64.manylinux2014_aarch64.whl (3.0 MB view details)

Uploaded Aug 3, 2026 CPython 3.14manylinux: glibc 2.17+ ARM64

multimodars-0.5.4-cp314-cp314-macosx_11_0_arm64.whl (2.8 MB view details)

Uploaded Aug 3, 2026 CPython 3.14macOS 11.0+ ARM64

multimodars-0.5.4-cp314-cp314-macosx_10_12_x86_64.whl (2.9 MB view details)

Uploaded Aug 3, 2026 CPython 3.14macOS 10.12+ x86-64

multimodars-0.5.4-cp313-cp313-win_amd64.whl (2.7 MB view details)

Uploaded Aug 3, 2026 CPython 3.13Windows x86-64

multimodars-0.5.4-cp313-cp313-musllinux_1_2_x86_64.whl (3.3 MB view details)

Uploaded Aug 3, 2026 CPython 3.13musllinux: musl 1.2+ x86-64

multimodars-0.5.4-cp313-cp313-musllinux_1_2_i686.whl (3.4 MB view details)

Uploaded Aug 3, 2026 CPython 3.13musllinux: musl 1.2+ i686

multimodars-0.5.4-cp313-cp313-musllinux_1_2_armv7l.whl (3.2 MB view details)

Uploaded Aug 3, 2026 CPython 3.13musllinux: musl 1.2+ ARMv7l

multimodars-0.5.4-cp313-cp313-musllinux_1_2_aarch64.whl (3.1 MB view details)

Uploaded Aug 3, 2026 CPython 3.13musllinux: musl 1.2+ ARM64

multimodars-0.5.4-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (3.1 MB view details)

Uploaded Aug 3, 2026 CPython 3.13manylinux: glibc 2.17+ x86-64

multimodars-0.5.4-cp313-cp313-manylinux_2_17_aarch64.manylinux2014_aarch64.whl (3.0 MB view details)

Uploaded Aug 3, 2026 CPython 3.13manylinux: glibc 2.17+ ARM64

multimodars-0.5.4-cp313-cp313-macosx_11_0_arm64.whl (2.8 MB view details)

Uploaded Aug 3, 2026 CPython 3.13macOS 11.0+ ARM64

multimodars-0.5.4-cp313-cp313-macosx_10_12_x86_64.whl (2.9 MB view details)

Uploaded Aug 3, 2026 CPython 3.13macOS 10.12+ x86-64

multimodars-0.5.4-cp312-cp312-win_amd64.whl (2.7 MB view details)

Uploaded Aug 3, 2026 CPython 3.12Windows x86-64

multimodars-0.5.4-cp312-cp312-musllinux_1_2_x86_64.whl (3.3 MB view details)

Uploaded Aug 3, 2026 CPython 3.12musllinux: musl 1.2+ x86-64

multimodars-0.5.4-cp312-cp312-musllinux_1_2_i686.whl (3.4 MB view details)

Uploaded Aug 3, 2026 CPython 3.12musllinux: musl 1.2+ i686

multimodars-0.5.4-cp312-cp312-musllinux_1_2_armv7l.whl (3.2 MB view details)

Uploaded Aug 3, 2026 CPython 3.12musllinux: musl 1.2+ ARMv7l

multimodars-0.5.4-cp312-cp312-musllinux_1_2_aarch64.whl (3.1 MB view details)

Uploaded Aug 3, 2026 CPython 3.12musllinux: musl 1.2+ ARM64

multimodars-0.5.4-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (3.1 MB view details)

Uploaded Aug 3, 2026 CPython 3.12manylinux: glibc 2.17+ x86-64

multimodars-0.5.4-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl (3.0 MB view details)

Uploaded Aug 3, 2026 CPython 3.12manylinux: glibc 2.17+ ARM64

multimodars-0.5.4-cp312-cp312-macosx_11_0_arm64.whl (2.8 MB view details)

Uploaded Aug 3, 2026 CPython 3.12macOS 11.0+ ARM64

multimodars-0.5.4-cp312-cp312-macosx_10_12_x86_64.whl (2.9 MB view details)

Uploaded Aug 3, 2026 CPython 3.12macOS 10.12+ x86-64

multimodars-0.5.4-cp311-cp311-win_amd64.whl (2.7 MB view details)

Uploaded Aug 3, 2026 CPython 3.11Windows x86-64

multimodars-0.5.4-cp311-cp311-musllinux_1_2_x86_64.whl (3.3 MB view details)

Uploaded Aug 3, 2026 CPython 3.11musllinux: musl 1.2+ x86-64

multimodars-0.5.4-cp311-cp311-musllinux_1_2_i686.whl (3.4 MB view details)

Uploaded Aug 3, 2026 CPython 3.11musllinux: musl 1.2+ i686

multimodars-0.5.4-cp311-cp311-musllinux_1_2_armv7l.whl (3.2 MB view details)

Uploaded Aug 3, 2026 CPython 3.11musllinux: musl 1.2+ ARMv7l

multimodars-0.5.4-cp311-cp311-musllinux_1_2_aarch64.whl (3.2 MB view details)

Uploaded Aug 3, 2026 CPython 3.11musllinux: musl 1.2+ ARM64

multimodars-0.5.4-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (3.1 MB view details)

Uploaded Aug 3, 2026 CPython 3.11manylinux: glibc 2.17+ x86-64

multimodars-0.5.4-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl (3.0 MB view details)

Uploaded Aug 3, 2026 CPython 3.11manylinux: glibc 2.17+ ARM64

multimodars-0.5.4-cp311-cp311-macosx_11_0_arm64.whl (2.8 MB view details)

Uploaded Aug 3, 2026 CPython 3.11macOS 11.0+ ARM64

multimodars-0.5.4-cp311-cp311-macosx_10_12_x86_64.whl (2.8 MB view details)

Uploaded Aug 3, 2026 CPython 3.11macOS 10.12+ x86-64

multimodars-0.5.4-cp310-cp310-win_amd64.whl (2.7 MB view details)

Uploaded Aug 3, 2026 CPython 3.10Windows x86-64

multimodars-0.5.4-cp310-cp310-musllinux_1_2_x86_64.whl (3.3 MB view details)

Uploaded Aug 3, 2026 CPython 3.10musllinux: musl 1.2+ x86-64

multimodars-0.5.4-cp310-cp310-musllinux_1_2_i686.whl (3.4 MB view details)

Uploaded Aug 3, 2026 CPython 3.10musllinux: musl 1.2+ i686

multimodars-0.5.4-cp310-cp310-musllinux_1_2_armv7l.whl (3.2 MB view details)

Uploaded Aug 3, 2026 CPython 3.10musllinux: musl 1.2+ ARMv7l

multimodars-0.5.4-cp310-cp310-musllinux_1_2_aarch64.whl (3.2 MB view details)

Uploaded Aug 3, 2026 CPython 3.10musllinux: musl 1.2+ ARM64

multimodars-0.5.4-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (3.1 MB view details)

Uploaded Aug 3, 2026 CPython 3.10manylinux: glibc 2.17+ x86-64

multimodars-0.5.4-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl (3.0 MB view details)

Uploaded Aug 3, 2026 CPython 3.10manylinux: glibc 2.17+ ARM64

File details

Details for the file multimodars-0.5.4.tar.gz.

File metadata

Download URL: multimodars-0.5.4.tar.gz
Upload date: Aug 3, 2026
Size: 6.1 MB
Tags: Source
Uploaded using Trusted Publishing? No
Uploaded via: maturin/1.14.1

File hashes

Hashes for multimodars-0.5.4.tar.gz
Algorithm	Hash digest
SHA256	`2533d1efd015a924536833ba2309dd0cf5d31c7e1d842554bb14cb7ac98539af`
MD5	`7be936bb3f687e3119b68575d5ef7380`
BLAKE2b-256	`0807c681ae3eff18d3da4610ddb9c5c62ddba481df8f94d8d926ed492da173a0`

Algorithm	Hash digest
SHA256	`e0f2ac95f786329753ed86ea3595f674bd40494c2c50a8ceab2208d211fa1607`
MD5	`8e0b82017470d42f59e9d52537aeaa44`
BLAKE2b-256	`f56357687bdddbcf19cca9939f99d26e8b18625c3b462a618eb76b8f6d81e29a`

Algorithm	Hash digest
SHA256	`c79353140c7afa4b387d5d2a70b3ee53598381636947a450e8a4c45815fa7453`
MD5	`bfa7f53c72c765f3c36b5cc18897f9fb`
BLAKE2b-256	`a503b12c2a259dcf9df4abaff8c056cf6d2465c54707528b131869827b7c8f8a`

Algorithm	Hash digest
SHA256	`9bae815309bd9b3522144ab14d08016e7ff3e2b49f68bfb1c1b0d77195a8f1a6`
MD5	`017c3fd9420add8ba5e66bb0e4959eed`
BLAKE2b-256	`3868dc70d87d3df002476a23d1b913b1f5dd3f8593b1f14290443612f7263d70`

Algorithm	Hash digest
SHA256	`a19fcdd1b5ac75695ccdaa1ac46c52c2b4500b9f72411e7b8a277781f1f39536`
MD5	`d2c3eaa9a50664fd806ebe471463397d`
BLAKE2b-256	`7530d9789a3415fe1def0997d7887f0add8adc05ffdc9d34a243880de8739312`

Algorithm	Hash digest
SHA256	`6ee038cd8728e36aecf184b6c85e48cbabea51b6bf0a4680c5649e290375cc01`
MD5	`e8c0ed42eaaf0cab60cb0068af55c80a`
BLAKE2b-256	`5ca52a589a988e9d54cb5d34024970c58494fb2b1fdea04a9734757496c115f0`

Algorithm	Hash digest
SHA256	`c543f9efc2db05dd686e57088e1e934e42b4b42b6f85f4fa3e4a41a17bd2211c`
MD5	`cd442ef3d7f586eaad84213867915b3c`
BLAKE2b-256	`e1a0fb1aecfae71cbcadab906945923a9b4eb90a27b5c9ef892e4730680865cd`

Algorithm	Hash digest
SHA256	`7a694b54fd263cbc5f768b7214713da1e72625b5fd07d828757cd854b76bcf1b`
MD5	`9bccd5d475fb4eed569f213f705318d7`
BLAKE2b-256	`10ee9e065fa65414f1ee7c5d66b48dadd9bb585b2dec857381a7780f9dc53cd0`

Algorithm	Hash digest
SHA256	`8d21736435d8cb7d1a82e8413e7c89a51a378d4d24fa9a88177d5c7bb72c911e`
MD5	`ba072b424ddb51558c2038516cb1075b`
BLAKE2b-256	`60e51ec532a73720970395f03d4ead0e4f2acabdf32d9ad5dd0787c6e953c00c`

Algorithm	Hash digest
SHA256	`5265d341ad55f65db9ff9bc338681b78ce95df0469b13724224729e4c4d327e5`
MD5	`2bdc8b44cd066a60251ef49fdad8959a`
BLAKE2b-256	`21729759cdaaf38980c989947ac7c2c64dd5aed3e2a7384bcab44ccb22f5ffc8`

Algorithm	Hash digest
SHA256	`689b7ae928a553dd44c8400bd31cdb02974cf7658312c70040e0bd7f3d332ba7`
MD5	`ab2052c64313a6d39d764c475e8ba04f`
BLAKE2b-256	`b0e522b17b61b0fc03976c468efdcd3de37d20341c821880ab9386887765c085`

Algorithm	Hash digest
SHA256	`a18657db03ef3b13c42c8f1aa0b4fdb934bec6e50b76faa50d6198b0b25b115e`
MD5	`605d1c88d869b81ddb05c1f2ceb1b54a`
BLAKE2b-256	`71a38cc134a0f64ad1cf7e188dfbd590e9d5c5cb799c98e790c75127afc605f6`

Algorithm	Hash digest
SHA256	`801840aa8d162bc0dc444419d84f5ac66cdee89d8364cf41220d05c6debfab32`
MD5	`03c307b454b3db77805d5cc6a544dfd3`
BLAKE2b-256	`08e90a8735fc98f1491051727f5e377b2399b9824925973bc56c776e45957448`

Algorithm	Hash digest
SHA256	`76ca2a9237ac10a16d7dcfbb433f49675a70d7608099d60028f024aaf7b189e0`
MD5	`55dafaf613b08abe25da95ab47e7cd32`
BLAKE2b-256	`1c92db2e8292bf3e3ea3c2d07b453c60ff2401deabcf06894a81e4ef1f02d51e`

Algorithm	Hash digest
SHA256	`194f9c95ac08bceb0c46203ff2de9fd4694b99ddc63a713b6f5de39a74e7e0f2`
MD5	`cfe803417a24fd8bdf8645ea4af53fb0`
BLAKE2b-256	`6b3921f42d63b0b5472c058a70f4ca982f9fc7fd05177275118e960f02dd8c9d`

Algorithm	Hash digest
SHA256	`bc7753aa03e7354335199829a488a795e1a823df289aedc963f41d9b9f9f26b6`
MD5	`4ece9385590b9ec262dfc883eb671890`
BLAKE2b-256	`05b18b372bdec9d6c20a4f4ebe5862f123a8aa0fee3a7a80f8f92964ef080ba3`

Algorithm	Hash digest
SHA256	`1d77f954b41453baf27157e44b118d465278e21d8524eca10a6a645855e3de5b`
MD5	`bd980ec8d654336e76fab7f0a616327a`
BLAKE2b-256	`832b93d05f1ebd31f2a24db3d5174438877785751c4244a2aca2eda761d1ed71`

Algorithm	Hash digest
SHA256	`a6e873fa02e6f01ffcec0f1b2f6b740d399f4da6c2a443f592f85774223f8903`
MD5	`7757ee68d5a394bb650300e7506e5afa`
BLAKE2b-256	`472f2207c7a552bd1cbf1c09139b66faca614acbd1040d2aa6ae8b5ff769ab7b`

Algorithm	Hash digest
SHA256	`476af02bcffb058be0947b281fbe406d07985cf15db016fecae55c022f2c94d0`
MD5	`5745f25c6861dc83f550513df1cb4960`
BLAKE2b-256	`55b3a90f11338a00944e3d896367123ed992531e2877332b315a069c5ee2dbe2`

Algorithm	Hash digest
SHA256	`397e9c7a333889b15f1d27175b74599ab504f9a030fc368e7a75340a1623f082`
MD5	`1e0e9c886941ab85df63d36e7a36b89b`
BLAKE2b-256	`1d4923708b79f485949708f0bb58500e1c49cd86a1cb35d3d4c178d814ced137`

Algorithm	Hash digest
SHA256	`8ff65e4276f0ba524c663e7dda5f90b61b154b12e54e51ab2aaa342888ec5724`
MD5	`e468de7d86c5e65cc31c4b40aebb28b6`
BLAKE2b-256	`678f50a24dd31983a671f59b2e99518fe63b232e7b1f75e1fab4d89396ffd172`

multimodars 0.5.4

Overview

Key Features

Installation

Quick Example

Pipeline

Documentation

License

Citation

Project links

Key dates

1 maintainer

Credits

License

Requires

Classifiers

Download files

Source Distribution

Built Distributions

File details

File metadata

File hashes

File details

File metadata

File hashes

File details

File metadata

File hashes

File details

File metadata

File hashes

File details

File metadata

File hashes

File details

File metadata

File hashes

File details

File metadata

File hashes

File details

File metadata

File hashes

File details

File metadata

File hashes

File details

File metadata

File hashes

File details

File metadata

File hashes

File details

File metadata

File hashes

File details

File metadata

File hashes

File details

File metadata

File hashes

File details

File metadata

File hashes

File details

File metadata

File hashes

File details

File metadata

File hashes

File details

File metadata

File hashes

File details

File metadata

File hashes

File details

File metadata

File hashes

File details

Algorithm	Hash digest
SHA256	`5d66d616d77804b50ffc46cb09ba25fc997377c661099e5bbe0d40c3d4e7f5a6`
MD5	`57feb4790c39b6f83f45e5f20de77f94`
BLAKE2b-256	`6039741b5f8ef2dfc832e7b4c4074820e90b67c64662efaa1cc4b8dba52edc87`

Algorithm	Hash digest
SHA256	`a57ecbfb98be247db524766130e5a5c11feb79c5db819e4837deec817ccbadf3`
MD5	`6a0c79e32c1fe21cfbbc103dc9959c28`
BLAKE2b-256	`c25fa5fbe3ef73c411b35d726ca7fd51cf3a8cac05409c3d7641138b7fbf6d05`

Algorithm	Hash digest
SHA256	`e143631b2b0d1de0c3775046ead9138ac8f622e39df0fc2de254200a67bf9677`
MD5	`e080cf0691e395597cd57f3e64f12dc4`
BLAKE2b-256	`e46a91b2610565899c2845659477f21b1b7c5cbda2c0049c9d37868512d3f78b`

Algorithm	Hash digest
SHA256	`53cdfd14eafc6edb2fd37bf4ddc70bebcb0faa7d99438288d5f171e9619e18be`
MD5	`0313962cbd21dcae02185f2c274d5c1e`
BLAKE2b-256	`5465900d772a6936a8359f57eb51dbe267c4b0e5b64099d1d4e2de65210a08e1`

Algorithm	Hash digest
SHA256	`e8028fd10d56e45f939cbbccb0e09a10d3d3e8eac7d758d7d3650b011eb7df39`
MD5	`50a92784e65b93d954081e023a4099cf`
BLAKE2b-256	`c7f998829935622b4a4d14347e8bf042d8bdff21520271d3522a84ce81bd0d75`

Algorithm	Hash digest
SHA256	`02db72e712c641f0c005dccf55e4ce4bb5431c22c7a251540e732e116a3a0db5`
MD5	`5168cd3098046e74d9e86fbae3843707`
BLAKE2b-256	`9b5e2b2502db05042dd31e47a434b09aec0c5192338d64bf64aae4dcac7714f0`

Algorithm	Hash digest
SHA256	`831d3dee5b9946848287b7990e81beb96bbcad66544459fb88825d5b20c48188`
MD5	`a434c1f17ef6a95118e3e4794988042b`
BLAKE2b-256	`b48d55b6454f04f60041f7281b6df8f2164307c204a8597d8c07fd9244617671`

Algorithm	Hash digest
SHA256	`7e5b88621f8b5b35831ff4f5299e94e2ff9d873a23c216ed4a727f8c9ea30787`
MD5	`a7f1f700c4b4872284d317f9aa9d789f`
BLAKE2b-256	`134cad0b95bac738f24fe52ade6d1f5f62eba510511400d5bc48dc25d900484d`

Algorithm	Hash digest
SHA256	`93a63e6ba34c8018086cfec2ea8c8ba4c4e949cb5c46df745581795691e50638`
MD5	`1bf4ca18a3b9a5cc73b3ac5bac6e54df`
BLAKE2b-256	`bc760129da7792c6de2f6cc3c1fee72f97f3a06f64f979538031a711cbc83260`

Algorithm	Hash digest
SHA256	`04cef924f8b64109db2be41261b060deaaee627385aab84ba1a4ebee7683d300`
MD5	`342899012f88503c2cac7ed55a2c5cae`
BLAKE2b-256	`6db618824667652f6a85941f54894e545bee2440a73c4a6af770e0f322a0ad03`