Metadata-Version: 2.1
Name: Py-OMA
Version: 1.3
Summary: PyOMA allows the experimental estimation of the modal parameters (natural frequencies, mode shapes, damping ratios) of a structure from measurements of the vibration response in operational condition.
Home-page: https://github.com/dagghe/PyOMA
Author: Dag Pasquale Pasca, Angelo Aloisio, Marco Martino Rosso, Stefanos Sotiropoulos
Author-email: <supportPyOMA@polito.it>
License: GNU General Public License v3 (GPLv3)
Description: 
        # PyOMA
        This software was created to perform output-only modal identification (Operational Modal Analysis, OMA).
        
        OMA allows the experimental estimation of the modal parameters (natural frequencies, mode shapes, damping ratios) of a structure from measurements of the vibration response in operational condition.
        
        
        
        
        ## What is PyOMA?
        PyOMA is a python module that allows to perform OMA on ambient vibration measurments datasets.
        
        PyOMA include the following algorithms:
        
        1. Frequency Domain Decomposition (FDD)
        
        	1a. Original Frequency Domain Decomposition (FDD)
        	
        	2a. Enhanced Frequency Domain Decomposition (EFDD)
        	
        	3a. Frequency Spatial Domain Decomposition (FSDD)
        	
        2. Stochastic Subspace Identification (SSI)
        
        	2a. Covariance-driven Stochastic Subspace Identification (cov-SSI)
        	
        	2b. Data-driven Stochastic Subspace Identification (dat-SSI)	
        	
        
        To better untersdand the workflow of the functions, see the workflow [here](https://github.com/dagghe/PyOMA#workflow).
        
        
        ## Installing PyOMA
        As a prerequisite to install PyOMA, you need to install [Anaconda](https://docs.anaconda.com/anaconda/install/) first.
        You should install a Python version greather equal 3.5 or the software may run in troubles.
        
        To fully install PyOMA, you need to run the following commands (in the following order):
        
        - pip install pandas
        - pip install scipy
        - pip install matplotlib
        - pip install seaborn
        - pip install mplcursors
        
        - pip install Py-OMA
        
        
        To import PyOMA in your workspace, simply type:
        
        - import PyOMA
         
         ### Dependencies
         - numpy (https://numpy.org/)
         - pandas (https://pandas.pydata.org/)
         - scipy -> signal (https://www.scipy.org/)
         - scipy.optimize -> curve_fit (https://www.scipy.org/)
         - scipy->linalg (https://www.scipy.org/)
         - matplotlib.pyplot (https://matplotlib.org/)
         - matplotlib.ticker -> [MultipleLocator,FormatStrFormatter] (https://matplotlib.org/)
         - matplotlib.patches (https://matplotlib.org/)
         - seaborn (https://seaborn.pydata.org/)
         - mplcursors (https://mplcursors.readthedocs.io/en/stable/)
        
        
        # Workflow
        
        ![Flowchart PyOMA](https://raw.githubusercontent.com/dagghe/PyOMA/master/Images/FlowChartPyomaNEW.png)
        
        FDD:
        
        	1. run FDDsvp
        
        		2.a run FDDmodEX to run original FDD
        			
        			and/or
        			
        		2.b run EFDDmodEX(method='EFDD') to run EFDD
        			
        			and/or
        			
        		2.c run EFDDmodEX(method='FSDD') to run FSDD
        
        SSI
        
        	1.a run SSIcovStaDiag 
        		
        		2. run SSImodEX to run cov-SSI
        
        			and/or
        
        	1.b run SSIdatStaDiag 
        		
        		2. run SSImodEX to run dat-SSI 
        
        
        # Function Description
        
        A complete description of the functions available in PyOMA can be found in the page [Function Description](https://github.com/dagghe/PyOMA/wiki/Function-Description).
        
        
        # What is PyOMA_GUI? A brief software overview
        
        PyOMA_GUI is a graphical user interface software developed in [PyQt5](https://pypi.org/project/PyQt5/), which implements in a single integrated tool the operational modal analysis of civil structures with output-only measurement data. This software utilises the aforementioned functionalities offered by the [PyOMA](https://github.com/dagghe/PyOMA) python module. Therefore, PyOMA_GUI provides a remarkably user-friendly interface to improve the accessibility of the PyOMA module, ensuring widespread usage both for scientists, researchers, and even for applied civil and structural engineers. The main features PyOMA_GUI provides are listed below:
        - Importing data tab;
        - Definition of the geometry of the structure and the monitoring system (channels and degrees of freedom, DOFs);
        - Preprocessing of signals tool with detrending and decimation options;
        - Dynamic identification algorithms with visualization of the results (graphs, modal shapes);
        - Post-processing tabs and output exportation functionalities;
        
        ![`PyOMA_GUI` general overview.](https://github.com/dagghe/PyOMA/blob/master/paper/Fig2.png)
        
        The executable file PyOMA_GUI.exe for windows is already available [here](https://github.com/dagghe/PyOMA/blob/master/PyOMA_GUI/PyOMA_GUI.exe).
        
        A short manual to guide the user into an introductory example is available [here](PyOMA_V2.0/manual_v1.docx).
        
        # Acknowledgements
        The developers acknowledge the meaningful contribution of [Professor Rocco Alaggio](http://diceaa.univaq.it/team-view/prof_alaggio/) from UniversitÃ  degli Studi dell'Aquila, who encouraged the authors to study and develop these topics. Furthermore, the developers acknowledge the meaningful contribution of [Professor Giuseppe Carlo Marano](https://www.diseg.polito.it/en/personale/scheda/(nominativo)/giuseppe.marano) from Politecnico di Torino for promoting the Graphical User Interface programming and coordinating the team activities.
        
        
        # How to cite
        If you use this code, please don't forget to cite this work:
        
        > Pasca, D. P., Aloisio, A., Rosso, M. M., & Sotiropoulos, S. (2022). PyOMA and PyOMA_GUI: A Python module and software for Operational Modal Analysis. Software X, (In press)
Keywords: operational modal analysis,ambient vibration modal test,structural dynamics,frequency domain decomposition,stochastic subspace identification,structural health monitoring
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Description-Content-Type: text/markdown
