Persistent homology of chromatic Delaunay filtrations

These details have been verified by PyPI

Project links

GitHub Statistics

Maintainers

abhinavnatarajan

These details have not been verified by PyPI

Project description

Chalc

PyPI - Version Documentation GitHub Workflow Status (with event)

Chalc is a Python package to compute chromatic Delaunay filtrations from labelled datasets in Euclidean space. Chromatic Delaunay filtrations are a family of combinatorial objects that capture spatial relations among the classes of a labelled dataset. You can find more details on the math behind chromatic Delaunay filtrations in the following papers:

Chromatic Alpha Complexes
Morse Theory for Chromatic Delaunay Triangulations

For instructions on how to install and use chalc, read the documentation.

[!IMPORTANT] Since the release of NumPy 2.0, versions of chalc older than 2.0.0 won't work correctly. This is due to a bug in these package versions related to dependency specification. If you are using an older version of chalc, please make sure to install a compatible version of NumPy (≥ 1.24.2 and < 2.0.0).

Project details

These details have been verified by PyPI

Project links

GitHub Statistics

Maintainers

abhinavnatarajan

These details have not been verified by PyPI

Release history Release notifications | RSS feed

7.0.2

Oct 30, 2024

7.0.1

Sep 24, 2024

7.0.0

Sep 23, 2024

6.0.1

Sep 21, 2024

6.0.0

Sep 20, 2024

This version

5.0.0

Sep 18, 2024

4.0.1

Sep 11, 2024

4.0.0

Sep 9, 2024

4.0.0.dev1 pre-release

Sep 9, 2024

3.1.3

Aug 13, 2024

3.1.2

Aug 6, 2024

3.1.1

Aug 5, 2024

3.0.1

Jul 22, 2024

3.0.0

Jul 15, 2024

2.0.0

Jul 4, 2024

1.0.0

May 31, 2024

0.11.0

Apr 24, 2024

0.10.0

Nov 22, 2023

0.9.0

Nov 1, 2023

0.8.2

Oct 30, 2023

0.8.1

Oct 26, 2023

0.8.0

Oct 26, 2023

0.7.1

Oct 20, 2023

0.7.0

Oct 19, 2023

0.6.1

Oct 15, 2023

0.6.0

Oct 14, 2023

0.5.6

Oct 12, 2023

0.5.5

Oct 9, 2023

0.5.4

Sep 29, 2023

0.5.3

Sep 11, 2023

0.5.2

Sep 6, 2023

0.5.0

Sep 6, 2023

0.4.0

Sep 3, 2023

0.3.0.post3

Sep 3, 2023

0.3.0

Aug 31, 2023

Download files

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

Source Distribution

chalc-5.0.0.tar.gz (83.7 kB view hashes)

Uploaded Sep 18, 2024 Source

Built Distributions

chalc-5.0.0-cp312-cp312-win_amd64.whl (767.5 kB view hashes)

Uploaded Sep 18, 2024 CPython 3.12 Windows x86-64

chalc-5.0.0-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (780.5 kB view hashes)

Uploaded Sep 18, 2024 CPython 3.12 manylinux: glibc 2.17+ x86-64

chalc-5.0.0-cp312-cp312-macosx_11_0_arm64.whl (586.4 kB view hashes)

Uploaded Sep 18, 2024 CPython 3.12 macOS 11.0+ ARM64

chalc-5.0.0-cp312-cp312-macosx_10_9_x86_64.whl (710.3 kB view hashes)

Uploaded Sep 18, 2024 CPython 3.12 macOS 10.9+ x86-64

chalc-5.0.0-cp311-cp311-win_amd64.whl (766.7 kB view hashes)

Uploaded Sep 18, 2024 CPython 3.11 Windows x86-64

chalc-5.0.0-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (782.0 kB view hashes)

Uploaded Sep 18, 2024 CPython 3.11 manylinux: glibc 2.17+ x86-64

chalc-5.0.0-cp311-cp311-macosx_11_0_arm64.whl (587.5 kB view hashes)

Uploaded Sep 18, 2024 CPython 3.11 macOS 11.0+ ARM64

chalc-5.0.0-cp311-cp311-macosx_10_9_x86_64.whl (710.9 kB view hashes)

Uploaded Sep 18, 2024 CPython 3.11 macOS 10.9+ x86-64

chalc-5.0.0-cp310-cp310-win_amd64.whl (764.0 kB view hashes)

Uploaded Sep 18, 2024 CPython 3.10 Windows x86-64

chalc-5.0.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (779.9 kB view hashes)

Uploaded Sep 18, 2024 CPython 3.10 manylinux: glibc 2.17+ x86-64

chalc-5.0.0-cp310-cp310-macosx_11_0_arm64.whl (584.8 kB view hashes)

Uploaded Sep 18, 2024 CPython 3.10 macOS 11.0+ ARM64

chalc-5.0.0-cp310-cp310-macosx_10_9_x86_64.whl (707.6 kB view hashes)

Uploaded Sep 18, 2024 CPython 3.10 macOS 10.9+ x86-64

chalc-5.0.0-cp39-cp39-win_amd64.whl (762.2 kB view hashes)

Uploaded Sep 18, 2024 CPython 3.9 Windows x86-64

chalc-5.0.0-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (780.2 kB view hashes)

Uploaded Sep 18, 2024 CPython 3.9 manylinux: glibc 2.17+ x86-64

chalc-5.0.0-cp39-cp39-macosx_11_0_arm64.whl (585.1 kB view hashes)

Uploaded Sep 18, 2024 CPython 3.9 macOS 11.0+ ARM64

chalc-5.0.0-cp39-cp39-macosx_10_9_x86_64.whl (707.8 kB view hashes)

Uploaded Sep 18, 2024 CPython 3.9 macOS 10.9+ x86-64

Hashes for chalc-5.0.0.tar.gz

Hashes for chalc-5.0.0.tar.gz
Algorithm	Hash digest
SHA256	`222c3a6b5d1f748de45772365d03c6aae8fbed08887d0bd3a274b7ff048a4576`
MD5	`d78fe12499a57a20734cf91074a545c2`
BLAKE2b-256	`35d7ae8de4527f969cf549a58dad222642f5baf36891d218462ea3dd6594b147`

Hashes for chalc-5.0.0-cp312-cp312-win_amd64.whl

Hashes for chalc-5.0.0-cp312-cp312-win_amd64.whl
Algorithm	Hash digest
SHA256	`e123398e2f9c1b4be76e0d3ca30af613fa8a52d7761482a122039907d9f7fd39`
MD5	`c568ac68319d8f7d46d6a5fc45d2b256`
BLAKE2b-256	`f41ffce754fbaa50751d41aecab1d0ac5495ef5048baf7e869eda73385e28f29`

Hashes for chalc-5.0.0-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl

Hashes for chalc-5.0.0-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm	Hash digest
SHA256	`e31603031f4f111e240aacb9f315d27eea80aa7498894fbba3ae55d75dee9f5f`
MD5	`0e2634913d168375788bae70f1dd646e`
BLAKE2b-256	`2b1e0285a7feeee6a1108506644a07f7e099154aadd2c5860cf52e83a5339c51`

Hashes for chalc-5.0.0-cp312-cp312-macosx_11_0_arm64.whl

Hashes for chalc-5.0.0-cp312-cp312-macosx_11_0_arm64.whl
Algorithm	Hash digest
SHA256	`ed303797d97b2209e1f5dc9aec604de7c8b4a280ce31f7c1162a5dc0e29b5765`
MD5	`c4e3584a1ccf8f61286bb0801c6b182f`
BLAKE2b-256	`5cb46130fc2d58620792c59fe41291210194589f6d0309395bbc0f09bdca3b8c`

Hashes for chalc-5.0.0-cp312-cp312-macosx_10_9_x86_64.whl

Hashes for chalc-5.0.0-cp312-cp312-macosx_10_9_x86_64.whl
Algorithm	Hash digest
SHA256	`1f941d6bb76a1f6ba36fd1850c12b7655469423af0d18924a3a8a3319fdedb4d`
MD5	`221e102346b938c9a9ecb0332ece3f5b`
BLAKE2b-256	`aaa62428ff6bb39490a9b8021565994a37acc210d3146131a014d929cf31b61b`

Hashes for chalc-5.0.0-cp311-cp311-win_amd64.whl

Hashes for chalc-5.0.0-cp311-cp311-win_amd64.whl
Algorithm	Hash digest
SHA256	`0aea6eb133ef51b44626693026baf5ea9ebb72cb37fc4a89217fa889fd115bbe`
MD5	`1fb1310fffde161efd8220bbb53f6b4e`
BLAKE2b-256	`56b0986720aa77c91f83848aa20330ed6d1077885aca183169b57c237e92b8ee`

Hashes for chalc-5.0.0-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl

Hashes for chalc-5.0.0-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm	Hash digest
SHA256	`8693bcaabf2215635cb6bf0db336411e0bbb15b13789a8d11168ef6ff4039c0e`
MD5	`2d487f79456d6c01fded192a1ab475ed`
BLAKE2b-256	`d0d0d2d27ba43b33afe082d5c3b69fd45b02c528d4361844c3be6a61fa53e8ea`

Hashes for chalc-5.0.0-cp311-cp311-macosx_11_0_arm64.whl

Hashes for chalc-5.0.0-cp311-cp311-macosx_11_0_arm64.whl
Algorithm	Hash digest
SHA256	`a97bfe0a7eeee6e3d76b5215b901bceff666468c5d4b23b095999017055324dc`
MD5	`d266f19ed9dfa5f740f645be11f8cf7a`
BLAKE2b-256	`ee3fa1d34cbc9e8160f46d16b7ef10a7063c75e824090f2df67099a8c8468198`

Hashes for chalc-5.0.0-cp311-cp311-macosx_10_9_x86_64.whl

Hashes for chalc-5.0.0-cp311-cp311-macosx_10_9_x86_64.whl
Algorithm	Hash digest
SHA256	`9dbac2daaafdb37bcb0649edb05e5054024fc9c3357b327421904b1a70b1f706`
MD5	`922cebabd26fd1267b00394a0599d2ec`
BLAKE2b-256	`3a24690dbb35de62e2f275d87f4fef356703fbe754b28c777482b8fc95a3bdca`

Hashes for chalc-5.0.0-cp310-cp310-win_amd64.whl

Hashes for chalc-5.0.0-cp310-cp310-win_amd64.whl
Algorithm	Hash digest
SHA256	`80a4012b0ee050c616a7fb32a2b49f4132c009c1347bb58b61aff34d75b901f3`
MD5	`859f040a06bc0aec8851b1fab0ea9f6e`
BLAKE2b-256	`a758119ddd665d42c747146fdabed81353ffbd1c500f5fc1b294e2efb40a7313`

Hashes for chalc-5.0.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl

Hashes for chalc-5.0.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm	Hash digest
SHA256	`afa1f017bd5eb52cc4bfa55bfd86b965f3074370f9f7f23b343738f694e0c077`
MD5	`8340d8426a92cbf3ac7df0f28400c26c`
BLAKE2b-256	`d8d6dbc6e5d6d18e91200fd5d706ecbd8c0d35de96f97c1390ee0628023ea42a`

Hashes for chalc-5.0.0-cp310-cp310-macosx_11_0_arm64.whl

Hashes for chalc-5.0.0-cp310-cp310-macosx_11_0_arm64.whl
Algorithm	Hash digest
SHA256	`4ea91f542feb8ef207fdcda2ca71971f3b167aa3177157651c1a59479d569354`
MD5	`bd5bd9fd0e787534cb7cbff8afc34547`
BLAKE2b-256	`1af54b47c07b592612bf2b9904ce4b64bbe1e5bd6517999d972ec4bf81ca815e`

Hashes for chalc-5.0.0-cp310-cp310-macosx_10_9_x86_64.whl

Hashes for chalc-5.0.0-cp310-cp310-macosx_10_9_x86_64.whl
Algorithm	Hash digest
SHA256	`fa732f45dcff25eb1273db2ef9f801bb4a2c03ab301d5bcc14b8bf414a5a9e48`
MD5	`dd60da3920c8df663fa5ee5700a6861e`
BLAKE2b-256	`b755a8b264046ac6ea6d3c67933e57db5a9096542dc3a8e5ca6ed83ab27d2bac`

Hashes for chalc-5.0.0-cp39-cp39-win_amd64.whl

Hashes for chalc-5.0.0-cp39-cp39-win_amd64.whl
Algorithm	Hash digest
SHA256	`62e7354f9980aaf58f78b6eee2b454f981c104187e9347a5f829193a71ad170d`
MD5	`ab182dcc460919a4b19e7f9ce8219b0f`
BLAKE2b-256	`33f39be04d20a2222987e1bda61a75283ee04f8d1dd6ce6417accc6d83710a58`

Hashes for chalc-5.0.0-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl

Hashes for chalc-5.0.0-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm	Hash digest
SHA256	`afca9185920780234179eba32ab64243371a3a19e96d0f577057e65b7f94900e`
MD5	`c4212442b8b01af36d55902a679d2ca0`
BLAKE2b-256	`9501f99420fc6362b16674d923bb2c3b4285fd2b02b42fc78fb7fcee428143ae`

Hashes for chalc-5.0.0-cp39-cp39-macosx_11_0_arm64.whl

Hashes for chalc-5.0.0-cp39-cp39-macosx_11_0_arm64.whl
Algorithm	Hash digest
SHA256	`319832f5ef3c5c27b804cb13e20c7fb0a0ef5ba5e40a21347daae9c3570380d2`
MD5	`572075864c3fd0e9aa9b52cc365210bf`
BLAKE2b-256	`a78522c309a85308af4c93d49e3cb837a554ea73781e5501f290cef64a65f946`

Hashes for chalc-5.0.0-cp39-cp39-macosx_10_9_x86_64.whl

Hashes for chalc-5.0.0-cp39-cp39-macosx_10_9_x86_64.whl
Algorithm	Hash digest
SHA256	`6acecc1231ddb88907222e76827df6772bc5317b2e91581b8dbb1e1d3b8a907b`
MD5	`789f3cdf72756d6e1864c2993896f421`
BLAKE2b-256	`d64ab150a5068877a754706cab473486402d94e4b0573cbeed4c5d2ca2c345a4`