# Instructions

### 1) Setting up the environment

The code works with `python v3.8.3` ( but any version of python above 3.5 should work)

We recommend creating a virtual environment so as to not create conflicts with your local installation.

Unzip the code folder. Within that directory :

- Run `python -m venv myvirtualenv` to create a virtual environment named `myvirtualenv`
- Activate the environment by using running `source myvirtualenv/bin/activate`
- Then install all the dependencies with `pip install -r requirements.txt`

### 2) Downlading the datasets

Head to https://www.csie.ntu.edu.tw/~cjlin/libsvmtools/datasets/ to download the datasets. They should be saved in a folder named `datasets` . The folder should be in the same directory as `isotropic_norm_effects.py`

### 4) How to run the anistropic experiment

Set the dimension in the file `script_anisotropic_effects.py`

Simply run `python script_anisotropic_effects.py`

### 3) How to run the experiment "isotropic_norm_effects.py"

Set the dataset list in the `isotropic_norm_effects.py` file.

Run with `python isotropic_norm_effects.py [PICKLE_FILE_NAME]` where `[PICKLE_FILE_NAME]`is a name of your choice where the experimental data will be saved in a binary formal.

Run `python csv_maker.py [PICKLE_FILE_NAME] [OUTPUT_CSV_NAME]` to obtain a csv file containing the averaged out train/test errors.



