User guide

Comprehensive guides for working with DPF IronPython.

Core concepts

Understanding DPF

Learn the fundamental concepts and architecture of DPF.

Operators and workflows

Learn about DPF's operator-based processing model.

Working with data

Working with fields

Fields are the primary data containers in DPF. Learn how to create, manipulate, and extract data from fields.

Working with meshes

Access and manipulate mesh data including nodes, elements, and connectivity.

Working with results

Extract and process simulation results such as stress, strain, displacement, and more.

Scoping and support

Learn about data scoping (entity selection) and support (spatial/temporal context).

Best practices

• Always dispose of large objects when finished
• Use operators for complex data transformations
• Leverage server-side processing for large datasets
• Cache frequently accessed data
• Use appropriate data types for your use case