Metadata-Version: 2.1
Name: sdypy-EMA
Version: 0.27
Summary: Experimental and operational modal analysis.
Home-page: https://github.com/ladisk/pyEMA
Author: Klemen Zaletelj, Domen Gorjup, Janko Slavič, Tomaž Bregar, Miha Pogačar, et al.
Maintainer: Janko Slavič
Maintainer-email: janko.slavic@fs.uni-lj.si
License: UNKNOWN
Platform: UNKNOWN
License-File: LICENSE

sdypy-EMA
=========

Experimental and operational modal analysis

Check out the `documentation`_.

This project is successor of the `pyEMA`_ project. pyEMA is no longer developed after version 0.26.

New in version 0.27
-------------------
- UFF support: Import FRFs directly from UFF files. The `pyUFF`_ package is used to read the UFF files.
- Stability chart upgrade: Show/hide unstable poles to improve the clarity of the chart.
- Documentation update.


Basic usage
-----------

Import ``EMA`` module:
~~~~~~~~~~~~~~~~~~~~~~

.. code:: python

    from sdypy import EMA


Make an instance of ``Model`` class:
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

.. code:: python

   a = EMA.Model(
       frf_matrix,
       frequency_array,
       lower=50,
       upper=10000,
       pol_order_high=60
       )

Compute poles:
~~~~~~~~~~~~~~

.. code:: python

   a.get_poles()

Determine correct poles:
~~~~~~~~~~~~~~~~~~~~~~~~

The stable poles can be determined in two ways: 

1. Display **stability chart**

.. code:: python
    
    a.select_poles()

The stability chart displayes calculated poles and the user can hand-pick the stable ones.

2. If the approximate values of natural frequencies are already known, it is not necessary to display the stability chart:

.. code:: python

    approx_nat_freq = [314, 864]     
    a.select_closest_poles(approx_nat_freq)

After the stable poles are selected, the natural frequencies and damping coefficients can now be accessed:

.. code:: python

   a.nat_freq # natrual frequencies
   a.nat_xi # damping coefficients

Reconstruction:
~~~~~~~~~~~~~~~

There are two types of reconstruction possible: 

1. Reconstruction using **own** poles (the default option):

.. code:: python

    H, A = a.get_constants(whose_poles='own')

where **H** is reconstructed FRF matrix and **A** is a matrix of modal constants.

2. Reconstruction on **c** using poles from **a**:

.. code:: python

    c = EMA.Model(frf_matrix, frequency_array, lower=50, upper=10000, pol_order_high=60)

    H, A = c.get_constants(whose_poles=a)

|DOI|

.. _documentation: https://sdypy-ema.readthedocs.io/en/latest/

.. |DOI| image:: https://zenodo.org/badge/DOI/10.5281/zenodo.4016671.svg?
   :target: https://doi.org/10.5281/zenodo.4016671

.. _sdypy: https://github.com/sdypy/sdypy

.. _pyEMA: https://github.com/ladisk/pyEMA

.. _pyUFF: https://pypi.org/project/pyuff/

