https://github.com/alvii147/discretetimelib
Python library for analysis of discrete time signals and systems
https://github.com/alvii147/discretetimelib
numpy pandas scipy signals-and-systems sympy
Last synced: about 2 months ago
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Python library for analysis of discrete time signals and systems
- Host: GitHub
- URL: https://github.com/alvii147/discretetimelib
- Owner: alvii147
- License: bsd-3-clause
- Created: 2021-10-13T14:15:25.000Z (over 4 years ago)
- Default Branch: master
- Last Pushed: 2022-04-11T22:11:28.000Z (about 4 years ago)
- Last Synced: 2025-06-02T20:38:29.660Z (about 1 year ago)
- Topics: numpy, pandas, scipy, signals-and-systems, sympy
- Language: Python
- Homepage:
- Size: 6.37 MB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# DiscreteTimeLib
**DiscreteTimeLib** is a Python library for the analysis of discrete-time signals and systems. See [documentation](https://alvii147.github.io/DiscreteTimeLib/build/html/index.html) for more information.
## Overview
### Discrete-Time Signals
The `DiscreteTimeSignal` class can be used to model a discrete-time signal:
```python
>>> from DiscreteTimeLib import DiscreteTimeSignal
>>> import numpy as np
>>> import matplotlib.pyplot as plt
```
```python
>>> data = [
... (n, np.sin(x)) for n, x in enumerate(np.linspace(0, 2 * np.pi, num=100))
... ]
>>> x_n = DiscreteTimeSignal(data)
>>> print(x_n)
x[n]
0 0.000000e+00
1 6.342392e-02
2 1.265925e-01
3 1.892512e-01
4 2.511480e-01
.. ...
95 -2.511480e-01
96 -1.892512e-01
97 -1.265925e-01
98 -6.342392e-02
99 -2.449294e-16
[100 rows x 1 columns]
```
```python
>>> markerline, stemlines, baseline = plt.stem(x_n.keys(), x_n.values())
>>> plt.setp(markerline, 'markerfacecolor', 'salmon')
>>> plt.setp(markerline, 'markeredgecolor', 'firebrick')
>>> plt.setp(stemlines, 'color', 'orangered')
>>> plt.setp(baseline, 'color', 'red')
>>> plt.show()
```
### Convolution
`DiscreteTimeSignal` supports various operations, including **convolution**:
```python
>>> data = [
... (n, np.cos(x)) for n, x in enumerate(np.linspace(0, 2 * np.pi, num=100))
... ]
>>> h_n = DiscreteTimeSignal(data)
>>> y_n = h_n * x_n
>>> print(y_n)
x[n]
0 0.000000e+00
1 6.342392e-02
2 1.898887e-01
3 3.785025e-01
4 6.278700e-01
.. ...
194 -6.278700e-01
195 -3.785025e-01
196 -1.898887e-01
197 -6.342392e-02
198 -2.449294e-16
[199 rows x 1 columns]
```
```python
>>> markerline, stemlines, baseline = plt.stem(y_n.keys(), y_n.values())
>>> plt.setp(markerline, 'markerfacecolor', 'lawngreen')
>>> plt.setp(markerline, 'markeredgecolor', 'olive')
>>> plt.setp(stemlines, 'color', 'palegreen')
>>> plt.setp(baseline, 'color', 'green')
>>> plt.show()
```
### Filtering
The `DiscreteTimeSystem` class can be used to model a discrete-time system and apply the system filter on a signal:
```python
>>> from DiscreteTimeLib import DiscreteTimeSystem
```
```python
>>> b = (1,)
>>> a = (1, -1)
>>> H = DiscreteTimeSystem(b, a)
>>> y_n = H.filter(x_n)
>>> print(y_n)
x[n]
0 0.000000e+00
1 6.342392e-02
2 1.900164e-01
3 3.792676e-01
4 6.304156e-01
.. ...
95 3.792676e-01
96 1.900164e-01
97 6.342392e-02
98 1.665335e-15
99 1.420405e-15
[100 rows x 1 columns]
```
```python
>>> markerline, stemlines, baseline = plt.stem(y_n.keys(), y_n.values())
>>> plt.setp(markerline, 'markerfacecolor', 'deepskyblue')
>>> plt.setp(markerline, 'markeredgecolor', 'teal')
>>> plt.setp(stemlines, 'color', 'turquoise')
>>> plt.setp(baseline, 'color', 'cyan')
>>> plt.show()
```
### Inverse z-transforms
The `DiscreteTimeSystem` class can also compute the **inverse z-transform** in the form of a [Sympy](https://www.sympy.org/) expression:
```python
>>> h_n, n = H.iztrans()
>>> print(h_n)
1.0*Heaviside(n, 1)
```
## Installation
Clone the repository:
```
git clone https://github.com/alvii147/DiscreteTimeLib.git
```
Install dependencies:
```
cd DiscreteTimeLib/
pip3 install -r requirements.txt
```