Is this skill suitable for LaTeX users?

Yes, it follows a standardized workflow that stores graphics in a 'figures/' folder and provides the exact LaTeX code needed to include the image in your document.

Does it support biological pathways?

Yes, by using NetworkX and custom rendering, it can visualize biological pathways, molecular interactions, and hierarchical structures.

What file formats are generated by Scientific Schematics?

It generates high-resolution vector formats including SVG, EPS, and PDF, ensuring the diagrams remain sharp at any scale in printed publications.

Which Python libraries does this skill use for diagrams?

The skill utilizes Graphviz for layouts, Matplotlib for general plotting, Schemdraw for electrical circuits, and NetworkX for biological or network topologies.

Can it handle complex AI model architectures?

Absolutely. It is specialized in rendering multi-layer architectures like Transformers, including encoder-decoder stacks, attention mechanisms, and skip connections.

Scientific Schematics & Diagrams

Name: Scientific Schematics & Diagrams
Author: jimmc414

byjimmc414

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324

Ciencia de Datos y ML

Generates publication-quality scientific diagrams, neural network architectures, and flowcharts using specialized Python libraries.

Acerca de

This skill automates the creation of professional, vector-based scientific visualizations for research papers, posters, and technical documentation. By leveraging industry-standard Python libraries like Graphviz, Matplotlib, Schemdraw, and NetworkX, it transforms complex concepts into clear diagrams. Whether you need a detailed Transformer architecture, a CONSORT flowchart, or a complex electrical circuit, this skill manages the entire generation workflow—from code creation to high-resolution SVG/EPS export and LaTeX-ready integration snippets.

Características Principales

Professional circuit schematic drafting using Schemdraw
324 GitHub stars
Automated neural network architecture visualization (Transformers, CNNs, RNNs)
Automated folder management and LaTeX reference snippet generation
Multi-format vector output (SVG, EPS, and PDF) for lossless scaling
Generation of publication-standard flowcharts and methodology diagrams

Casos de Uso

Visualizing deep learning architectures for machine learning research papers
Creating clinical trial and methodology flowcharts for medical journals
Designing technical system architecture and data flow diagrams for software documentation

Acerca de

Características Principales

Professional circuit schematic drafting using Schemdraw
324 GitHub stars
Automated neural network architecture visualization (Transformers, CNNs, RNNs)
Automated folder management and LaTeX reference snippet generation
Multi-format vector output (SVG, EPS, and PDF) for lossless scaling
Generation of publication-standard flowcharts and methodology diagrams

Casos de Uso

Visualizing deep learning architectures for machine learning research papers
Creating clinical trial and methodology flowcharts for medical journals
Designing technical system architecture and data flow diagrams for software documentation