NumPy

Miscellaneous Python tools (monorepo).

Pyralysis is a Python library for radio interferometry: visibility simulation, gridding, optimization-based image reconstruction, and analysis pipelines with Dask-friendly scaling, documented APIs, and optional cluster (SLURM) workflows. GPL-3.0.

Python libraries and utilities for custom measurement and control devices.

A procedural ambient sound synthesiser with a desktop GUI. All audio is generated in real-time — no samples or audio files required.

MCODAC is a Fortran library for the numerical evaluation of fiber composite damage. The library contains analysis methods specifically tailored to fiber composites, from micromechanical homogenization approaches to macroscopic fatigue models of orthotropic multilayer composites.

Explore and analyze data provided by Motivate, a bike share system provider for many major cities in the United States. This tool uncovers bike share usage patterns and compares system usage between Chicago, New York City, and Washington, DC. The challenge involves building a robust, interactive Command Line Interface (CLI) application capable of quickly filtering, crunching, and displaying descriptive statistics on large datasets.

Python creative coding workspace for automated video generation, animation experiments, procedural media, OpenCV, MoviePy, NumPy and FFmpeg.

The python-native Latina Conservatory version of the SMS (Spectral Modeling Synthesis) tools developed by Xavier Serra in his Phd thesis in 1989.

PyVISA libraries for measurement and control devices.

Provides fractional delay filter design and evaluation routines for Numpy arrays

These Python scripts and batch files stand alone for One Shot Color (OSC) narrowband data captures, but they can also be used in conjunction with my Siril Seestar Narrowband Extraction Scripts to produce a SOO (Sulfur Oxygen Oxygen) master image file from narrowband astronomy data. The Align script is mandatory, but most users will also want the other scripts as well to complete the full SOO workflow. Both the Multiscale, and the SOO APOD scripts call a user adjustable parameter file that can be tweaked from object to object... Also included are two renaming scripts, and a way to archive your completed project with a SHA256 manifest. Clear skies!

These Python scripts and batch files stand alone for One Shot Color (OSC) narrowband data captures, but they can also be used in conjunction with my Siril Seestar Narrowband Extraction Scripts to produce a SHO (Hubble Pallet) master image file from narrowband astronomy data. The Align script is mandatory, but most users will also want the other scripts as well to complete the full SHO workflow. Both the Multiscale, and the SHO APOD scripts call a user adjustable parameter file that can be tweaked from object to object... Also included are two renaming scripts, and a way to archive your completed project with a SHA256 manifest. Clear skies!

These Python scripts and batch files stand alone for One Shot Color (OSC) narrowband data captures, but they can also be used in conjunction with my Siril Seestar Narrowband Extraction Scripts to produce a HOO (Hydrogen Oxygen Oxygen) master image file from narrowband astronomy data. The Align script is mandatory, but most users will also want the other scripts as well to complete the full HOO workflow. Both the Multiscale, and the HOO APOD scripts call a user adjustable parameter file that can be tweaked from object to object... Also included are two renaming scripts, and a way to archive your completed project with a SHA256 manifest. Clear skies!

Experimental implementations of mathematical functions focusing on HPC techniques

Introduction to classification using machine learning and deep learning (PyTorch, TensorFlow, Keras)

Analysis of Kilter Board data, along with predictive models for V-grades based on holds and angle.

Analysis of Tension Board 2 data, along with predictive models for V-grades based on holds and angle.

Ejercicios de SQL, Python, y analítica de datos con Python del curso "Data Analytics" en la IT Academy de Barcelona Activa / Cibernarium.

Projet pédagogique en algorithmie et intelligence artificielle consistant à créer un agent (Kevin) capable de résoudre un labyrinthe.

Le projet explore plusieurs approches :

Génération de labyrinthes (DFS, Prim) Algorithmes de recherche de chemin (A*, Dijkstra) Apprentissage supervisé (Imitation Learning avec CNN) Apprentissage par renforcement (Deep Q-Network)

Des outils de visualisation permettent de générer des images et des GIFs montrant Kevin se déplacer dans le labyrinthe.

Projet réalisé dans le cadre de la formation Développeur en Intelligence Artificielle (Simplon).