Excitation signals as used in structural dynamics and vibration fatigue.
Project description
pyExSi - Excitation signals as used in structural dynamics and vibration fatigue
Supported excitation signals are:
pulse (e.g. half-sine)
random:
uniform random distribution
normal random distribution
pseudorandom distribution
random, defined by power spectral density (PSD):
stationary Gaussian
stationary non-Gaussian
non-stationary non-Gaussian random process
burst random
sine sweep
Simple example
A simple example on how to generate random signals on PSD basis:
import pyExSi as es
import numpy as np
N = 2**16 # number of data points of time signal
fs = 1024 # sampling frequency [Hz]
t = np.arange(0,N)/fs # time vector
# define frequency vector and one-sided flat-shaped PSD
M = N//2 + 1 # number of data points of frequency vector
freq = np.arange(0, M, 1) * fs / N # frequency vector
freq_lower = 50 # PSD lower frequency limit [Hz]
freq_upper = 100 # PSD upper frequency limit [Hz]
PSD = es.get_psd(freq, freq_lower, freq_upper) # one-sided flat-shaped PSD
#get gaussian stationary signal
gausian_signal = es.random_gaussian((N, PSD, fs)
#get non-gaussian non-stationary signal, with kurtosis k_u=10
#amplitude modulation, modulating signal defined by PSD
PSD_modulating = es.get_psd(freq, freq_lower=1, freq_upper=10)
#define array of parameters delta_m and p
delta_m_list = np.arange(.1,2.1,.5)
p_list = np.arange(.1,2.1,.5)
#get signal
nongaussian_nonstationary_signal = es.nonstationary_signal(N,PSD,fs,k_u=5,modulating_signal=('PSD', PSD_modulating),param1_list=p_list,param2_list=delta_m_list)
Project details
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
Filter files by name, interpreter, ABI, and platform.
If you're not sure about the file name format, learn more about wheel file names.
Copy a direct link to the current filters
File details
Details for the file pyexsi-0.43.3.tar.gz.
File metadata
- Download URL: pyexsi-0.43.3.tar.gz
- Upload date:
- Size: 4.3 MB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/6.1.0 CPython/3.9.21
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
5169aeaea379b33b8466c7283ffdc061249801e9efd0175470c99353de4ab495
|
|
| MD5 |
c523af60425bf6eb881031ade5dca355
|
|
| BLAKE2b-256 |
acef6b8a5d5fec6e4dfee1aa5dd4408aa1abc8feee1894fc47905baf9e59fd30
|
File details
Details for the file pyexsi-0.43.3-py3-none-any.whl.
File metadata
- Download URL: pyexsi-0.43.3-py3-none-any.whl
- Upload date:
- Size: 10.2 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/6.1.0 CPython/3.9.21
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
00b75cbd15a027c4109d237c69fad223153637adc072564e0c09c71e5eeff605
|
|
| MD5 |
a0cfaeaa223bc88bb1b61bf532030f1f
|
|
| BLAKE2b-256 |
9e1c5cccf0ff600cda03ee411de5326734a3f368b7e9bb518cf087098b70d7fd
|