Scientific Software
I develop research software at the intersection of mathematics, scientific computing, acoustic analysis, and reproducible data workflows. The projects presented on this page are publicly available through my GitHub profile.
Featured projects
Symbolic Operator Calculus
Python · SymPy · Operator Theory
A research-oriented Python package for symbolic experiments with noncommutative integral-operator compositions. The project provides structured representations of operators, kernels, assumptions, domains, and symbolic transformations, together with automated tests and thesis-oriented notebooks.
Scientific purpose. To make formal calculations involving singular integral and Wiener–Hopf operators more explicit, reproducible, and auditable.
Current status. Active research prototype, currently identified as version 0.1.0.
git clone https://github.com/EnriqueDiazO/symbolic-operator-calculus.git
cd symbolic-operator-calculus
python3 -m venv .venv
source .venv/bin/activate
pip install -e ".[dev]"
pytestMath Knowledge Base
Python · Streamlit · MongoDB · LaTeX · Quarto
A mathematical knowledge-management platform for registering, connecting, visualizing, and exporting definitions, theorems, examples, references, and research notes.
The system supports structured mathematical content, LaTeX and PDF generation, concept graphs, Cornell-style notes, CPI learning materials, and long-form book exports with Quarto.
Scientific purpose. To organize mathematical knowledge as a reusable and interconnected research database rather than as isolated documents.
Current status. Stable version 0.13.0.
git clone https://github.com/EnriqueDiazO/math-knowledge-base.git
cd math-knowledge-base
python3 -m venv mathdbmongo
source mathdbmongo/bin/activate
pip install --upgrade pip
pip install -r requirements.txt
pip install -e .MongoDB is required for persistent storage. A full LaTeX installation and Quarto are required for PDF and book exports.
Acoustic Analysis with Praat–Parselmouth
Python · Praat–Parselmouth · Matplotlib · Audio Analysis
A collection of reproducible examples for acoustic analysis of cough and voice recordings using Praat functionality from Python.
The repository includes workflows for spectrogram generation, pitch tracking, voiced–unvoiced segmentation, envelope extraction, fundamental-frequency statistics, formant measurements, and vocal-tract-length estimation.
Scientific purpose. To demonstrate how acoustic measurements and Praat scripts can be incorporated into automated Python workflows.
Current status. Functional example repository with installation instructions for Ubuntu and Windows.
git clone https://github.com/EnriqueDiazO/Practice-Praat-Parselmouth.git
cd Practice-Praat-Parselmouth
python3 -m venv .venv
source .venv/bin/activate
pip install --upgrade pip
pip install -r requirements.txtAdditional public work
- Manim Figures for Böttcher–Karlovich — mathematical-animation experiments for concepts related to operator theory.
- Probability in One Variable — reproducible materials on univariate probability distributions and simulations.
- Probability in Multiple Variables — examples and analyses involving relationships among multiple random variables.
- Python Data Science Diploma — structured teaching material for scientific programming and data analysis with Python.
- UML Diagram Creator — Python utilities for creating software and system diagrams.
Additional research repositories will be included here only after their code, documentation, data policy, and installation procedure are ready for public release.