2023 R2 Documentation - IntroductionLast update: 12.07.2023
The Data Processing Framework (DPF) provides numerical simulation users/engineers with a toolbox for accessing and transforming simulation data. It is used to handle complex pre- or post-processing of simulation data within a simulation workflow.
DPF is an independent, physics-agnostic tool that can be plugged into many applications for both data input and data output (result plots, visualization, and so on).
DPF can access data from solver result files and other neutral formats (for example, CSV, HDF5, and VTK). Various operators are available, allowing you to manipulate and transform this data. You can chain operators together to create simple or complex data-processing workflows that can be reused for repeated or future evaluations.
The data in DPF is defined based on physics-agnostic mathematical quantities described in self-sufficient entities called fields. This allows DPF to be a modular and easy-to-use tool with a large range of capabilities. It is designed to handle large amounts of data.
Here is how you open a result file generated by MAPDL (or another ANSYS solver) and extract results:
The result file can be found under dpf/testfiles folder of the Ansys Inc product.
Accessing and enriching DPF capabilities
The following sections are summaries. For more detailed content, see Ways of Using DPF.
Most of the DPF capabilities can be accessed using the operators. For a list of DPF existing operators, see Operators section.
DPF capabilities are accessible when DPF Server files are available. These files can be accessed using:
- The Ansys installer. To use it, download the standard installation using your preferred distribution channel, and install Ansys following the installer instructions. For information on getting a licensed copy of Ansys, visit the Ansys website.
- The DPF Server package. It is independent of the Ansys installer and is available on the DPF Pre-Release page of the Ansys Customer Portal. DPF Server is protected by an Ansys license mechanism.
Accessing capabilities with scripting
- C++ documentation:
- CPython modules documentation:
- Mechanical scripting (IronPython):
Enriching DPF capabilities
See Getting started section to know how to get started with DPF.
For comprehensive examples on how to use PyDPF-Core, see Examples section.
For more detailed articles about DPF capabilities, see User guide section.