This repository provides the 'novathesis' LaTeX class and template for formatting MSc dissertations, PhD theses, and other academic documents. It is primarily targeted at Portuguese universities (25+ supported schools) but can be adapted for other institutions. The architecture is modular: a core engine (nt-core.sty) built on LaTeX3 (Expl3) manages metadata, file registration, hooks, and download utilities; separate style files handle covers (nt-covers.sty), spines (nt-spine.sty), rendering of front/main/back matter (nt-render-matter.sty), and options (nt-options.sty). Users configure the document via files in the 0-Config/ directory, and the main entry point is template.tex which calls \ntprint commands. The build system uses latexmk with a Makefile, supports multiple LaTeX engines (pdfLaTeX, LuaLaTeX, XeLaTeX), and includes CI via GitHub Actions. External dependencies include a full LaTeX distribution, biber for bibliography, bib2gls (requires Java) for glossaries, and Ghostscript for PDF post-processing. The template is actively maintained with a comprehensive changelog and version 8.3.0.
SciencePlots is a Python library that provides curated Matplotlib style sheets for producing publication-quality scientific figures. It bundles a comprehensive set of .mplstyle files that configure figure dimensions, font families, tick marks, color cycles, and LaTeX rendering to meet the formatting requirements of academic journals, theses, and presentations. The package includes a small registration module (`styles_discovery.py`) that automatically discovers all stylesheets in its subdirectories and integrates them into Matplotlib's style system. It also offers styles tailored for specific journals (IEEE, Nature), language support (CJK, Russian, Turkish), and colorblind-safe palettes based on Paul Tol's schemes. The codebase is minimal, well-structured, and actively maintained with robust CI testing across multiple Python and Matplotlib versions. It is not a data research repo; it is a pure software library for Matplotlib customization.