Package to compute features of traces from action potential models

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Project links

Homepage

Project description

Action Potential features

ap_features is package for computing features of action potential traces. This includes chopping, background correction and feature calculations.

Parts of this library is written in C and numba and is therefore highly performant. This is useful if you want to do feature calculations on a large number of traces.

Install

Install the package with pip

python -m pip install ap_features

See installation instructions for more options.

Available features

The list of currently implemented features are as follows

Action potential duration (APD)
Corrected action potential duration (cAPD)
Decay time (Time for the signal amplitude to go from maximum to (1 - a) * 100 % of maximum)
Time to peak (ttp)
Upstroke time (time from (1-a)*100 % signal amplitude to peak)
Beating frequency
APD up (The duration between first intersections of two APD lines)
Maximum relative upstroke velocity
Maximum upstroke velocity
APD integral (integral of the signals above the APD line)

Documentation

Documentation is hosted at GitHub pages: https://computationalphysiology.github.io/ap_features/

Note that the documentation is written using jupyterbook and contains an interactive demo

License

Free software: LGPLv2.1

Source Code

https://github.com/ComputationalPhysiology/ap_features

Project details

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Project links

Homepage

Release history Release notifications | RSS feed

2024.0.0

Aug 4, 2024

2023.7.4

Oct 18, 2023

2023.7.3

Oct 17, 2023

2023.7.2

Sep 26, 2023

2023.7.1

Sep 26, 2023

2023.7.0

Sep 24, 2023

2023.6.3

Sep 6, 2023

2023.6.2

Sep 6, 2023

2023.6.1

Aug 24, 2023

2023.6.0

Aug 23, 2023

2023.5.1

Aug 3, 2023

2023.5.0

Aug 3, 2023

2023.4.0

Jun 18, 2023

2023.3.1

Jun 7, 2023

2023.3.0

Jun 7, 2023

2023.2.0

May 21, 2023

2023.1.3

Feb 8, 2023

2023.1.0

Jan 27, 2023

2023.0.0

Jan 19, 2023

2022.5.0

Jan 27, 2023

2022.4.2

Nov 9, 2022

2022.4.1

Nov 9, 2022

2022.4.0

Oct 7, 2022

This version

2022.3.10

Aug 18, 2022

2022.3.9

Jul 9, 2022

2022.3.8

Jul 9, 2022

2022.3.7

Jun 28, 2022

2022.3.6

Jun 17, 2022

2022.3.3

Jun 17, 2022

2022.3.2

Jun 17, 2022

2022.3.1

May 15, 2022

2022.3.0

May 14, 2022

2022.2.0

May 9, 2022

2022.1.1

Feb 17, 2022

2022.0.0

Jan 13, 2022

2021.0.5

Nov 25, 2021

2021.0.4

Nov 1, 2021

2021.0.3

Oct 27, 2021

2021.0.2

Sep 8, 2021

2021.0.1

Aug 13, 2021

2021.0.0

Jun 18, 2021

1.0.0

Jun 2, 2021

0.1.2

May 31, 2021

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Hashes for ap_features-2022.3.10-cp38-cp38-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl
Algorithm	Hash digest
SHA256	`1386035194ab3367f45ab508f0c64d4ec2b105d14ba43957ec5ccf27d5df3bb6`
MD5	`3a2df8ecbd66a298228387bb88ce9ac7`
BLAKE2b-256	`54a780d5f651670f3a412c95bbfbd8441f9a95a619bc83242e403292b72a7b5d`

Hashes for ap_features-2022.3.10-cp38-cp38-macosx_11_0_arm64.whl

Hashes for ap_features-2022.3.10-cp38-cp38-macosx_11_0_arm64.whl
Algorithm	Hash digest
SHA256	`0d1ae2324dfca4d4d961c61f3ea4e2ce4f4fd877a589bdc2aa9b18c48e8b93a0`
MD5	`e8fcb1442b7779ff2e5e97d5e2000d98`
BLAKE2b-256	`4a14eeb4887923894d98957ca01a945bfc5f922197b8d7413cf21c153e6079c2`

Hashes for ap_features-2022.3.10-cp38-cp38-macosx_10_9_x86_64.whl

Hashes for ap_features-2022.3.10-cp38-cp38-macosx_10_9_x86_64.whl
Algorithm	Hash digest
SHA256	`cc768e1012bb66b5b24a34e77df712dde57a94df11fcacb0653c56ac950c6a4e`
MD5	`cbc3de669ace60b599ffdd1ec80dea76`
BLAKE2b-256	`9cde962abafc3ed14bdd7ac65c2ca7668b428e077601ca721f99532eef25a9de`

Hashes for ap_features-2022.3.10-cp37-cp37m-win_amd64.whl

Hashes for ap_features-2022.3.10-cp37-cp37m-win_amd64.whl
Algorithm	Hash digest
SHA256	`92fb490ee92336f3d68731b8b19c37a601be15d1c0ca882d35f46fe72a123997`
MD5	`225035d312a7fbc46113d77a0605cb21`
BLAKE2b-256	`5936718ba507cb07677263a7cc517897caf5dfe0e3ff44f9fe7a1275461c94b8`

Hashes for ap_features-2022.3.10-cp37-cp37m-win32.whl

Hashes for ap_features-2022.3.10-cp37-cp37m-win32.whl
Algorithm	Hash digest
SHA256	`efa9a9f48b818ec0309f76a150e981ce0af7fe90e182c174430ef5d77beff4ba`
MD5	`616c722e2bf9b64a470be3ac5a12de49`
BLAKE2b-256	`2dc22fef5e16e182c0972570f24cdc1bd9ee7c1096239578b52cf3cfb0441c87`

Hashes for ap_features-2022.3.10-cp37-cp37m-musllinux_1_1_x86_64.whl

Hashes for ap_features-2022.3.10-cp37-cp37m-musllinux_1_1_x86_64.whl
Algorithm	Hash digest
SHA256	`26046b38a525e43f25ff43eb9760f5e8865f3cd77dd37eabe1660a0d65794b93`
MD5	`2e4d6b8a8d10d08c8ea0a6154d7f4c31`
BLAKE2b-256	`94db8992c75f994ccf525cce83ce83b75e1d602e735f88b1ea502b5d423d1536`

Hashes for ap_features-2022.3.10-cp37-cp37m-musllinux_1_1_i686.whl

Hashes for ap_features-2022.3.10-cp37-cp37m-musllinux_1_1_i686.whl
Algorithm	Hash digest
SHA256	`b390452e7e63eea087540e19c674c09fde1c2926b4ffec7cb4f53a5422fbab6a`
MD5	`d7e8b1844b2e790d4677954aa3d4c3b7`
BLAKE2b-256	`9d2e2a050a198a9d4480656cc6b7cd414e719b5eb05e1677f6949cf44dbfecb1`

Hashes for ap_features-2022.3.10-cp37-cp37m-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl

Hashes for ap_features-2022.3.10-cp37-cp37m-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm	Hash digest
SHA256	`439b7fd2f54930d7fc17f317e3ce7029bfbf452e4d61da7eecb5bc9d4da59466`
MD5	`bc5cf2f946e91f2a646626e0bb950315`
BLAKE2b-256	`30f28cdc64dfa4a2ecdef2dfd5453c6d0ab350608b66252ea0e499194f043673`

Hashes for ap_features-2022.3.10-cp37-cp37m-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl

Hashes for ap_features-2022.3.10-cp37-cp37m-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl
Algorithm	Hash digest
SHA256	`5a9d3e462f84b049d60aea2998c89275a6b078eb9bff5411c6f0af813645aa9a`
MD5	`1735504ab90b425418481c22217952d7`
BLAKE2b-256	`70a7b645298ce06ac7a1869720ec5404df4efd211a1e3fb21f4920d5da9cec58`

Hashes for ap_features-2022.3.10-cp37-cp37m-macosx_10_9_x86_64.whl

Hashes for ap_features-2022.3.10-cp37-cp37m-macosx_10_9_x86_64.whl
Algorithm	Hash digest
SHA256	`088122cc0eac8aaf661a3f7216f54841d7e96a6b47c41d86b9782f63eae86e25`
MD5	`8dc6abe0419be10a693bf867b6d04585`
BLAKE2b-256	`66ff9f3e66a3fde571d4cbdcc1085026e99502783a95bde123a36a6bdf84bc09`