NeurOptimiser Dataset
Experiment codes and datasets for the NeurOptimiser framework, including BBOB benchmark results with linear and Izhikevich spiking neuron models.
This repository contains datasets and scripts generated from experiments conducted with the NeurOptimiser framework.
About This Dataset
This Zenodo repository serves exclusively for reproducibility, providing:
- Raw experimental data from all performed benchmark runs
- Experimental configurations and parameter files
- Scripts and processing routines used to generate the experimental figures and tables reported in the paper
The complete experiments cover functionality, scalability, and runtime performance of the NeurOptimiser framework over the BBOB test suite using both linear and Izhikevich spiking neuron models.
Contents
Datasets
| File | Description |
|---|---|
exconf.zip |
YAML configuration files used to launch each batch of experiments |
exdata-ioh.zip |
Resulting plots from experiments with IOHexperimenter |
exdata-coco.zip |
Raw results dataset generated using COCO platform |
ppdata-coco.zip |
Postprocessed datasets generated by cocopp |
exdata-time.zip |
Raw data for timing analysis and runtime scalability evaluation |
Scripts
| File | Description |
|---|---|
Example0.ipynb |
Simplest optimisation procedure using NeurOptimiser |
Example1.ipynb |
NeurOptimiser with default parameters on BBOB (IOH) |
Example2.ipynb |
NeurOptimiser with custom parameters on BBOB (COCO) |
exp_00-ioh.py |
Script for IOHexperimenter experiments |
exp_01-coco.py |
Script for COCO platform experiments |
exp_02-time.ipynb |
Timing analysis and runtime scalability evaluation |
How to Use
The experiments can be reproduced using the provided scripts and configuration files:
python exp_01-coco.py ./exconf/toy.yaml 1 1
# Args: <config_file> <num_batches> <batch>
Full Framework
The complete NeurOptimiser framework implementation is available at the GitHub repository.
Citation
@dataset{Cruz2025neuroptimiser-dataset,
author = {Cruz-Duarte, Jorge M. and Talbi, El-Ghazali},
title = {NeurOptimiser: A General Framework for Neuromorphic Optimisation - Experiment Codes and Dataset},
month = jun,
year = 2025,
publisher = {Zenodo},
version = {1.0.0},
doi = {10.5281/zenodo.15592900},
url = {https://doi.org/10.5281/zenodo.15592900},
}