Metadata-Version: 1.0
Name: pyNNST
Version: 0.1
Summary: Definition of non-stationary index for time-series
Home-page: https://github.com/LolloCappo/pyNNST
Author: Lorenzo Capponi
Author-email: lorenzocapponi@outlook.it
License: UNKNOWN
Description: ï»¿Index of non-stationarity
        ---------------------------------------------
        
        Obtaining non-stationary index for time-series.
        
        Installing this package
        -----------------------
        
        Use `pip` to install it by:
        
        .. code-block:: console
        
            $ pip install pyNNST
        
        
        Simple examples
        ---------------
        
        Here is a simple example on how to use the code:
        
        .. code-block:: python
        
            # Import packages 
            import pyNNST
            import numpy as np
        
            # Define a sample signal x
            T = 20                                # Time length of x
            fs = 400                              # Sampling frequency of x
            dt = 1 / fs                           # Time between discreete signal values
            x = np.random.rand(T * fs)            # Signal
            time = np.linspace(0, T - dt, T * fs) # Time vector
            std = np.std(x, ddof = 1)             # Standard deviation of x
            mean = np.mean(x)                     # Mean value of x
        
            # Class initialization
            example = pyNNST.nnst(x, nperseg = 100, noverlap = 0, confidence = 95)
            
            # Compute the run test for non-stationarity
            example.idns() 
            outcome = example.get_outcome()  # Get the results of the test as a string
            index = example.get_index()      # Get the index of non-stationarity
            limits = example.get_limits()    # Get the limits outside of which the signal is non-stationary
        
        
        Reference:
        
        Non-stationarity index in vibration fatigue: Theoretical and experimental research; L. Capponi, M. Cesnik, J. Slavic, F. Cianetti, M. Boltezar; International Journal of Fatigue 104, 221-230
        https://www.sciencedirect.com/science/article/abs/pii/S014211231730316X
        
Platform: UNKNOWN
