Non-negative Matrix Factorisation

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Prerequisites

python >= 3.8

We used the following pip package versions, though any up-to-date versions should be fine:

numpy==1.19.2
Pillow==8.0.0
sklearn==0.23.2
pre-commit==2.7.1
wandb==0.10.5
termcolor==1.1.0

Getting Started

Make sure to install all python requirements like so:

pip install -r requirements.txt

Download the ORL and Cropped YaleB datasets, and place them in the code/data folder. After unzipping the datasets, the code/data should contain a README file, along with a folder called CroppedYaleB containing the YaleB dataset and a folder called ORL containing the ORL dataset.

By default, code/algorithm/main.py will run a standard NMF model on a 90% subset of the ORL dataset, with no additional noise applied to the training data. Results will be logged to the terminal as well as to a .jsonl file in code/algorithm/results.

Changing the noise

To change the type of noise used, you can specify the --noise parameter along with any additional noise parameters required for the chosen noise type:

Uniform noise:

python code/algorithm/main.py --noise uniform --noise_mean 0 --noise_std 0.1

Gaussian noise:

python code/algorithm/main.py --noise gaussian --noise_mean 0 --noise_std 0.1

Salt and pepper noise:

python code/algorithm/main.py --noise salt_and_pepper --noise_p 0.1 --noise_r 0.5

Missing block noise:

python code/algorithm/main.py --noise missing_block --noise_blocksize 4 --noise_blocks 8

You should only specify the noise parameters for the chosen type of noise, e.g. if using uniform noise, only specify --noise_mean and --noise_std, and not other parameters like --noise_p.

Changing the model

To change the type of noise used, you can specify the --model parameter along with either standard for standard NMF (the default), l1_robust for RNMF or l21 for L2,1 NMF:

Standard NMF:

python code/algorithm/main.py --model standard

RNMF:

python code/algorithm/main.py --model l1_robust

L2,1 NMF:

python code/algorithm/main.py --model l21

Additional configuration

To view additional command line arguments that are not mentioned here, you can use the help command as follows:

python code/algorithm/main.py --help

Contributing

If you are making changes to the code base, make sure to install the pre-commit hook for the project to enable automatic code formatting and linting.