sigpropy 0.2.0

A Python package for digital signal processing.

SigProPy - A Python package for digital signal processing

Joseph Vantassel, The University of Texas at Austin

Table of Contents

• About sigpropy
• TimeSeries
• FourierTransform

About sigpropy

sigpropy is a Python package for digital signal processing. It includes two main class definitions, TimeSeries and FourierTransform. These classes include methods to perform common signal processing techniques (e.g., trimming and resampling) and properties to make using them readable and intuitive.

This package and the classes therein are being used in several other Python projects, some of which have been released publically and others are still in the development stage, so if you do not see a feature you would like it may very well be under development and released in the near future. To be notified of future releases, you can either watch the repository on Github or Subscribe to releases on the Python Package Index (PyPI).

TimeSeries

A simple example:

import sigpropy
import matplotlib.pyplot as plt
import numpy as np

dt = 0.002
time = np.arange(0, 1, dt)
s1 = 1*np.sin(2*np.pi*10*time)
s2 = 2*np.sin(2*np.pi*20*time)
s3 = 5*np.sin(2*np.pi*30*time)
amplitude = s1 + s2 + s3

tseries = sigpropy.TimeSeries(amplitude, dt)
fseries = sigpropy.FourierTransform.from_timeseries(tseries)

plt.plot(tseries.time, tseries.amplitude)
plt.xlabel("Time (s)")
plt.ylabel("Amplitude")
plt.show()

FourierTransform

A simple example:

import sigpropy
import matplotlib.pyplot as plt
import numpy as np

dt=0.002
time = np.arange(0, 1, dt)
s1 = 1*np.sin(2*np.pi*10*time)
s2 = 2*np.sin(2*np.pi*20*time)
s3 = 5*np.sin(2*np.pi*30*time)
amplitude = s1 + s2 + s3

tseries = sigpropy.TimeSeries(amplitude, dt)
fseries = sigpropy.FourierTransform.from_timeseries(tseries)

plt.plot(fseries.frequency, fseries.mag)
plt.xscale("log")
plt.xlabel("Frequency (Hz)")
plt.ylabel("|FFT Amplitude|")
plt.show()