pyyeti 1.4.2

Description:

pyyeti 1.4.2

pyYeti
pyYeti has tools mostly related to structural dynamics:

Solve matrix equations of motion in the time and frequency domains
Shock response spectrum (SRS)
Fatigue damage equivalent power spectral densities (PSD)
Hurty-Craig-Bampton model checks
Coupled loads analysis tools
Statistics tools for computing k-factors (for tolerance bounds and intervals) and for order statistics
A data-cursor for interacting with 2D/3D matplotlib plots
Eigensystem Realization Algorithm
Force limiting analysis tools
Read/write Nastran output4 (.op4) files
Limited capability to read Nastran output2 (.op2) files
Rainflow cycle counting
Resample data with the Lanczos method
A "vectorized" writing module
Eigensolution with the subspace iteration method
Tools for working with the "nas2cam" Nastran DMAP
Other miscellaneous tools

Installation
pyYeti runs on Python 3.10 or later. The dependencies are NumPy, SciPy,
Matplotlib, pandas and setuptools. These are all conveniently provided
by the Anaconda Python distribution:
https://www.anaconda.com/distribution/.
You can install pyYeti via pip:
python -m pip install pyyeti

or:
python -m pip install --user --upgrade pyyeti

You can also install from source, doing something like this:
git clone https://github.com/twmacro/pyyeti.git
cd pyyeti
python -m build -n
cd dist
python -m pip install <filename>.whl

Note that for the C version of the rainflow cycle counter, you also
need a C compiler installed. However, the speed of the pure Python
version is on par with the C version if you have Numba installed. In
fact, the C version may be removed in the future after making Numba a
required dependency.
Documentation
pyYeti documentation is here:
http://pyyeti.readthedocs.org/
Tutorials
The documentation contains several tutorials in the documentation.
These are also available (in their original form) as Jupyter
notebooks:
https://github.com/twmacro/pyyeti/tree/master/docs/tutorials
License
BSD. See LICENSE.txt
Contributing to pyYeti
Contributions are much appreciated. Bug reports, documentation
updates, feature requests, and code enhancements are all great
ways to contribute.