matplotlib-visualization

To generate publication-ready engineering plots with Matplotlib, you can use styling and color palettes to create crisp visualizations for reports. The Skill requires installing matplotlib and numpy, and includes example workflows in examples.py to produce reference figures.

Yes, you can visualize CFD velocity and pressure results using Matplotlib. The Skill supports generating velocity contours and 3D surface plots, allowing you to process computational fluid dynamics data for presentations and engineering reports.

The best way to create multi-panel figures for engineering reports is using Matplotlib styling and color palettes. This approach allows you to combine multiple plots into a single publication-quality figure, reducing time-consuming scripting for your engineering presentations.

Yes, you need numpy installed to plot pump curves in Matplotlib. The Skill requires both matplotlib and numpy as dependencies to process pump design analysis data and generate publication-quality reference plots.

Matplotlib handles 3D surface plotting by applying built-in styling and color palettes to your engineering data. This allows you to generate publication-quality 3D visualizations for reports without time-consuming manual scripting.