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 numba and is therefore highly performant. This is useful if you want to do feature calculations on a large number of traces.
Quick start
import matplotlib.pyplot as plt
import numpy as np
from scipy.integrate import solve_ivp
import ap_features as apf
time = np.linspace(0, 999, 1000)
res = solve_ivp(
apf.testing.fitzhugh_nagumo,
[0, 1000],
[0.0, 0.0],
t_eval=time,
)
trace = apf.Beats(y=res.y[0, :], t=time)
print(f"Number of beats: {trace.num_beats}")
print(f"Beat rates: {trace.beat_rates}")
# Get a list of beats
beats = trace.beats
# Pick out the second beat
beat = beats[1]
# Compute features
print(f"APD30: {beat.apd(30):.3f}s, APD80: {beat.apd(80):.3f}s")
print(f"cAPD30: {beat.capd(30):.3f}s, cAPD80: {beat.capd(80):.3f}s")
print(f"Time to peak: {beat.ttp():.3f}s")
print(f"Decay time from max to 90%: {beat.tau(a=0.1):.3f}s")
Number of beats: 5
Beat rates: [779.2207792207793, 769.2307692307693, 779.2207792207793, 759.493670886076]
APD30: 37.823s, APD80: 56.564s
cAPD30: 88.525s, cAPD80: 132.387s
Time to peak: 21.000s
Decay time from max to 90%: 53.618s
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
1 maintainer
Release files for ap-features 2026.2.1
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