Metadata-Version: 2.1
Name: pyRaTS
Version: 0.13
Summary: processing of (RAndom) TimeSeries for vibration fatigue
Home-page: https://github.com/ArvidTrapp/pyRaTS
Author: Arvid Trapp
Author-email: arvid.trapp@hm.edu
Maintainer: Arvid Trapp, Peter Wolfsteiner
Maintainer-email: arvid.trapp@hm.edu
Keywords: vibration fatigue, non-stationarity matrix, structural dynamics,Fatigue Damage Spectrum
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.6
Description-Content-Type: text/markdown

pyRaTS - processing of (RAndom) TimeSeries for vibration fatigue
---------------------------------------------

Providing an object-oriented framework to analyze and process time series with the focus on random vibration fatigue. 
Implementation of the non-stationarity matrix, the Fatigue Damage Spectrum and quasi-stationary signal definitions to deal with the challenges of non-stationary loading. 


Installing this package
-----------------------

Use `pip` to install it by:

.. code-block:: console

    $ pip install pyRaTS

	
Simple example
---------------

Here is a simple example for running a basic code. Further examples can be found on: 
https://github.com/ArvidTrapp/pyRaTS

.. code-block:: python

import pyRaTS as ts
import numpy as np

# Defining the series by pseudo-random generator...

T  = 10
fs = 1024
N  = T*fs
dt = 1/fs
t  = np.arange(N)/fs
x  = np.random.randn(N)

# Initialize series and some basic plots...

sig = ts.timeseries(x,t,name = 'sample timeseries')
sig.plot()
sig.plot_prob()
sig.plot_psd()

# derive response series and some further basic plots...

respsig, _ = sig.der_sdofResponse(fD = 50)
respsig.plot_psd()
respsig.plot_ls()
	
Some methods for a statistical analysis of random time series / estimation of statistical descriptors
-----------------------------------------
Estimation of statistical descriptors:
	- spectral moments (est_specMoms)
	- Dirlik estimator (est_dirlik/est_dirlikD)
	- PSD (est_psd)
	- load spectra (est_ls)
	- Fatigue Damage Spectrum (est_fds) ...accepts list of FLife methods for damage estimation
	- non-stationarity matrix (est_nonstat)

Some plot methods
-----------------------------------------
Plot methods:
	- time series (plot)
	- PSD (plot_psd)
	- absolute of Fourier transform (plot_X)
	- load spectra (plot_ls) ...accepts list of FLife methods with PDF definition
	- transfer function (plot_tf)
	- Fatigue Damage Spectrum (plot_fds) 
	- non-stationarity matrix (plot_nonstat)

Some methods to process time series
-----------------------------------------
Processing methods:
	- statistical response...PSD & Non-stat.-Matrix (der_statResponse(f,H)) 
	- response timeseries of single-degree-of-freedom system (der_sdofResponse(fD, D, func))
	- response timeseries for linear transfer function (der_response(f,H))
	- quasi-stationary load definition on the basis of the load spectra of the Fatigue Damage Spectrum (der_lsEquivalent())
	- load definition on the basis of the inverse Fatigue Damage Spectrum (der_iFDS())
	- ideal high pass filtered signal (der_highpass(f))
	- ideal low pass filtered signal  (der_lowpass(f))
	- ideal band pass filtered signal (der_bandpass(f))
