Welcome to eqsig’s documentation!

Release v1.2.4

The eqsig package is for signal processing of earthquake related data.

It provides two main objects the Signal and AccSignal objects that represent time series data of any type and acceleration time series data.

The objects have common signal processing methods available (e.g. Butterworth filtering) and common parameters (eg. Fourier Spectra).

Most functions and intensity measures have been written using the signal objects as inputs but have also be seperately defined to allow inputs as a numpy array and time step, these functions typically have _array in the function name.


  • Compute the acceleration response spectrum and elastic response time series using the fast Nigam and Jennings (1968) algorithm.
  • Compute the Fourier amplitude spectrum (using the scipy.signal.fft algorithm)
  • Compute the smooth Fourier amplitude spectrum according to Konno and Ohmachi (1998)
  • Compute velocity and displacement from acceleration time series
  • Compute peak ground motion quantities (PGA, PGV, PGD)
  • Compute common ground motion intensity measures (Arias intensity, CAV, CAV_dp5, significant duration, bracketed duration, dominant period)
  • Compute signal features (zero crossings, global peaks, local peaks)
  • Compute rotated ground motion or intensity measure from two ground motion components
  • Resampling of ground motion through interpolation or periodic resampling
  • Butterworth filter (using scipy), running average, polynomial fitting
  • Fast loading of, and saving of, plain text to and from Signal objects


Generate response spectra

import numpy as np
import matplotlib.pyplot as plt
import eqsig.single

bf, sub_fig = plt.subplots()
a = np.loadtxt("<path-to-acceleration-time-series>")
dt = 0.005  # time step of acceleration time series
periods = np.linspace(0.2, 5, 100)  # compute the response for 100 periods between T=0.2s and 5.0s
record = eqsig.AccSignal(a * 9.8, dt)
times = record.response_times

sub_fig.plot(times, record.s_a, label="eqsig")