The Fourier transform (FT) decomposes a function of time (a signal) into the frequencies that make it up, in a way similar to how a musical chord can be expressed as the frequencies (or pitches) of its constituent notes. In this sort repository I will be implementing a general Fourier Transform algorithm capable of decomposing a function f(x) = sin(2apix) + sin(2bpix) ... for constants a,b,.. > 0.
Here is an image of the man who came up with this idea.
The Code is written in Python 3.6.5 . If you don't have Python installed you can find it here. If you are using a lower version of Python you can upgrade using the pip package, ensuring you have the latest version of pip.
To install pip run in the command Line
python -m ensurepip -- default-pip
to upgrade it
python -m pip install -- upgrade pip setuptools wheel
to upgrade Python
pip install python -- upgrade
Additional Packages that are required are: Numpy and MatplotLib\
You can download them using pip
pip install numpy MatplotLib
or conda
conda install numpy MatplotLib
- Create a fake signal and apply the fourier Transform with
run.py- Basic Usage :
python run.py -s a b ... - Plots the signal, then the decomposition and saves the figures
- Option:
python run.py -s a b --n True- Uses my own implementation of the FFT
- Basic Usage :
python run.py -s 10 20
python run.py -s 50 200
python run -s 50 100 250 600
Please read CONTRIBUTING for the process for submitting pull requests.
- Fotios Kapotos - Initial work
This project is licensed under the MIT License - see the LICENSE.md file for details