SPOQ

Project Description

The goal of the project is to reimplement the SPOQ-Sparse-Restoration-Toolbox-v1.0 from Matlab to python

Files Description

.

• inputs
  • x : Original data
  • K : Observation operator
  • noise : noise data
  • y : measurment data
  • [params] (./inputs/params.config) : Hyperparameters of the algorithm
• src : The source code of the SPOQ library
• docs : The documentation (static files for website deployment)

Dependencies

• numpy
• Matplotlib
• scipy

Usage

Install Dependencies

pip install numpy

pip install matplotlib

pip install scipy

Running The algorithm

The algorithm can run in two modes either from files in the input directory (x,K,y,noise) or by generating a random sparse signal for simulation purposes. The simulated signal is caracterized by :

• nsamples : number of samples
• npeaks : number of samples different than 0
• peakw : the peaks width

First you have to install the dependencies and clone the project :

git clone https://gitlab-student.centralesupelec.fr/Anas.Laaroussi/spoq.git

To run the code from on inputs from inputs folder, in the root directory of the project run:

python main.py

To run the code on simulated signal with default values (nsample = 500, npeak = 20, peakw = 5)

python main.py -s

To change the caracterisitcs of the signal, let's say nsamples = 1000, npeak = 50 and peakw = 7 :

python main.py -s -nsample 1000 -npeak 50 -peakw 7

Documentation

The documentation of the project is to be find here doc