https://github.com/snhobbs/pulse_transitions
Python implementation of the Matlab Pulse Transitions Library. Useful for step responses, control systems analysis, risetime, overshoot, undershoot, settling time, etc.
https://github.com/snhobbs/pulse_transitions
control matlab octave pulse python signal-processing signals-and-systems step-functions step-response
Last synced: 9 months ago
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Python implementation of the Matlab Pulse Transitions Library. Useful for step responses, control systems analysis, risetime, overshoot, undershoot, settling time, etc.
- Host: GitHub
- URL: https://github.com/snhobbs/pulse_transitions
- Owner: snhobbs
- License: lgpl-2.1
- Created: 2025-05-17T15:37:37.000Z (about 1 year ago)
- Default Branch: master
- Last Pushed: 2025-07-28T18:26:49.000Z (10 months ago)
- Last Synced: 2025-08-29T08:24:51.190Z (9 months ago)
- Topics: control, matlab, octave, pulse, python, signal-processing, signals-and-systems, step-functions, step-response
- Language: Python
- Homepage: https://maskset.net/blog/2025/07/26/pulse-transitions-library/
- Size: 265 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# pulse_transitions
This library implements a python version of the [Pulse and Transition Metrics function category](https://www.mathworks.com/help/signal/pulse-and-transition-metrics.html?s_tid=CRUX_lftnav) in Matlab.
## Example Use Case
For the full example see [examples/second_order_system.py](https://github.com/snhobbs/pulse_transitions/examples/second_order_system.py).
```python
import numpy as np
from scipy.signal import lsim
from scipy.signal import lti
from pulse_transitions import detect_edges
from pulse_transitions import detect_signal_levels
from pulse_transitions import get_edge_metrics
# Example: synthetic underdamped step response
def generate_step_response(t, damping=0.2, freq=10):
# Second-order system parameters
wn = freq # Natural frequency (rad/s)
zeta = damping # Damping ratio
# Transfer function: H(s) = wn^2 / (s^2 + 2*zeta*wn*s + wn^2)
num = [wn**2]
den = [1, 2*zeta*wn, wn**2]
# Create the system
system = lti(num, den)
u = [0]*len(t[t<0]) + [1]*len(t[t>=0])
t_shift = t-min(t)
t_out, y_out, _ = lsim(system, U=u, T=t_shift)
return t, y_out
# Generate data
t = np.linspace(-0.25, 1, 1000)
t_out, y = generate_step_response(t, freq=25/(max(t)))
threshold_fractions=(0.1, 0.9)
# Estimate levels (e.g. using histogram or endpoints)
levels = detect_signal_levels(x=t, y=y, method="histogram")
low, high = levels
# Detect edges
edge = detect_edges(t, y, levels=levels, thresholds=threshold_fractions)[0]
# Compute overshoot / undershoot
metrics = get_edge_metrics(x=t, y=y, thresholds=threshold_fractions, levels=levels)
```
## Installation
### pypi
```bash
pip install pulse_transitions
```
### GitHub Release
```bash
pip install https://github.com/snhobbs/pulse_transitions/archive/refs/tags/.zip
```
### From Source
```bash
git clone https://github.com/snhobbs/pulse_transitions/
pip install .
```
## Matpulse Functions
| Function | Description | | Implemented?
| --------------------------------------------------------------------------- | ----------------------------------------------------------------- | ---------------- |---------
| [midcross](https://www.mathworks.com/help/signal/ref/midcross.html) | Mid-reference level crossing for bilevel waveform | | ☑️
| [statelevels](https://www.mathworks.com/help/signal/ref/statelevels.html) | State-level estimation for bilevel waveform with histogram method | | ☑️
| [falltime](https://www.mathworks.com/help/signal/ref/falltime.html) | Fall time of negative-going bilevel waveform transitions | | ☑️
| [overshoot](https://www.mathworks.com/help/signal/ref/overshoot.html) | Overshoot metrics of bilevel waveform transitions | | ☑️
| [risetime](https://www.mathworks.com/help/signal/ref/risetime.html) | Rise time of positive-going bilevel waveform transitions | | ☑️
| [settlingtime](https://www.mathworks.com/help/signal/ref/settlingtime.html) | Settling time for bilevel waveform | | ☑️
| [slewrate](https://www.mathworks.com/help/signal/ref/slewrate.html) | Slew rate of bilevel waveform | | ☑️
| [undershoot](https://www.mathworks.com/help/signal/ref/undershoot.html) | Undershoot metrics of bilevel waveform transitions | | ☑️
| [dutycycle](https://www.mathworks.com/help/signal/ref/dutycycle.html) | Duty cycle of pulse waveform | | ❌
| [pulseperiod](https://www.mathworks.com/help/signal/ref/pulseperiod.html) | Period of bilevel pulse | | ❌
| [pulsesep](https://www.mathworks.com/help/signal/ref/pulsesep.html) | Separation between bilevel waveform pulses | | ❌
| [pulsewidth](https://www.mathworks.com/help/signal/ref/pulsewidth.html) | Bilevel waveform pulse width | | ❌
## Background & Resources
### HP Journal
There's an excellent description of the algorithms used by HP [here](https://hparchive.com/Journals/HPJ-1996-12.pdf).
### Control Library
+ [GitHub](https://github.com/python-control/python-control)
+ [Docs](https://python-control.readthedocs.io)