# An implementation of the Fourier Transform using Python

## Fourier Transform

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.

## Prerequisites

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 donwload them using pip

```
pip install numpy MatplotLib
```

or conda

```
conda install numpy MatplotLib
```

## Usage

- 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 :

## Examples

`python run.py -s 10 20`

`python run.py -s 50 200`

`python run -s 50 100 250 600`

## GitHub

### Comments

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