The affect Python package provides a API/library for processing meshes and field results of a finite element analysis.

BSD. Specifically the "new/modified BSD" license, also called the "BSD three clause license". See license file.

See the affect documentation here.

• Designed for use on many-core shared memory workstations or servers using threaded parallelism.
• Easy to use within a Python (Jupyter) Notebook and targets modern Python (>3.5).
• Support for faster operations on very large analysis results on unstructured grids (billions of elements/nodes) using a compact storage scheme and CPU threaded parallelism.
• Fast skinning of mesh/block boundaries.
• A clean Python Database class for reading mesh and fields from ExodusII files directly into Numpy arrays.
• Some optimized built in postprocessors, like the FRF (frequency response function).

affect requires Python 3.6+ with additional package dependencies. The easiest way to get going is by installing and using the Anaconda python environment.

• numpy
• numexpr
• netcdf4

The netcdf4 package has additional dependencies including the hdf4 and hdf5 libraries. For a complete list of dependencies see the requirements.txt file.

Setting OpenMP environment values for binding threads may improve performance. The matter of thread affinity becomes important on multi-socket nodes. Optimal settings of these environment variables will vary by platform.

Putting threads far apart, i.e. on different sockets

• May improve the aggregated memory bandwidth available to your application
• May improve the combined cache size available to your application
• May decrease performance of synchronization constructs

Putting threads close together, i.e. on two adjacent cores which possibly shared some caches

• May improve performance of synchronization constructs
• May decrease the available memory bandwidth and cache size

See the OpenMP documentation for documentation on setting the two variables OMP_PROC_BIND and OMP_PLACES. These can take on the following values:

One of OMP_PROC_BIND={false|true|master|close|spread}

And one of OMP_PLACES={sockets|cores|threads} or an explicit list of places that are described by non-negative numbers.

For example,

export OMP_PLACES=threads
export OMP_PROC_BIND=close

For building, testing, and documentation, the easiest way to work is using the makefile in the root directory of the project.

make clean; make build
make test
make docs
[...etc]

Some warnings are hidden during the make build process, notably the warning about the deprecated numpy API that always occur with cython builds. These warnings are filtered using the remove_warning.py script.

The following type of warning occurs when building on Linux with gcc:

cc1plus: warning: command line option "-Wstrict-prototypes" is valid for Ada/C/ObjC but not for C++

This is normal, and a side effect of using setuptools and distutils with the Extension(language='c++') parameter. These warnings may also be hidden during make build.

There are a few other dependencies required only for development purposes for building the code and documentation. affect is developed with Cython and the documentation is built using sphinx. For building a conda recipe using conda build you may also need jinja2.

• cython >= 0.24.1
• jinja2
• pytest >= 3.0.5
• pytest-cov >= 2.3.1
• pytest-runner >= 2.11.1
• sphinx >= 1.5.1
• sphinx_rtd_theme >= 0.1.9

Other command line tools required or that you may want to use on Mac or Linux are:

• ccache
• gcc6
• make

Using the Conda distribution is the easiest way to develop and manage the Python package dependencies. Each of these may be installed similar to:

conda install pytest-cov

If you find any of the dependencies are not in the default conda channel, first try adding the conda-forge channel (you may also wish to disable SSL verification behind firewalls or web proxies):

conda config --set ssl_verify false
conda config --add channels conda-forge

If the package is still not found, fall back to using pip:

pip install sphinx-autodoc-typehints

To build the conda recipe, make sure you install the prerequisites:

conda install conda-build

The file meta.yaml in the root directory controls the building of the conda package. Build the recipe using

conda build <project-directory>

• Write meshes in the ExodusII format (unstructured meshes)
• Read ExodusII meshes split across files, thus avoiding the need for executing the Seacas epu tool.
• Read and write CGNS mesh format (structured meshes)
• Provide a local least squares recovery for mesh fields. This is a smoothing algorithm that can be used to, for example, either promote a element field (piecewise constant) to a piecewise linear field, or provide a local error indicator for spatial interpolation error on each element.

• Fast visualization of mesh/block boundary.
• Divide mesh boundary (block skin) into separate non-intersecting surface regions at sharp edges. (This can be thought of as automatic creation of sidesets ExodusII terms).
• Fast search algorithm for nearest neighbor searches for element sides and nodes on the boundary surface.