NumPy

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 have user adjustable parameters 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 have user adjustable parameters 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 have user adjustable parameters 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!

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

A practical, linear-algebra-first introduction to data science.

Practical tasks on Deep Learning (DL) and Neural Networks (NN). 🤖

Python libraries and utilities for custom measurement and control devices.

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.

Lecture note of Numerical Analysis and Practice

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.

Provides fractional delay filter design and evaluation routines for Numpy arrays

Fundamental theory and practice in Data Science (DS). 🧮

Materials on various sections in Computer Science (CS). 🎓

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).

Miscellaneous Python tools (monorepo).

ScaLAPACK for Python (scalapy) provides a high-level Python interface to distributed dense linear algebra using MPI, BLACS, and ScaLAPACK. It enables efficient computation on large matrices using a block-cyclic distribution, while exposing a NumPy-like API based on the DistributedMatrix abstraction.

This fork modernizes and stabilizes the original scalapy project with: • Support for Python 3.x on modern Linux systems • Clean MPI + ScaLAPACK detection (OpenMPI + Netlib ScaLAPACK) • Reproducible builds using a known-good NumPy / Cython / mpi4py stack • Documentation, examples, and automated tests • High-level wrappers for SVD, QR, LU, Cholesky, eigenproblems, and DMD workflows • Efficient distributed transposes via the new p?lapv2 wrapper

The project makes it possible to write dense parallel linear-algebra pipelines in Python while executing BLAS/PBLAS/ScaLAPACK kernels across an MPI communicator.