Library for Acoustic Signal Processing

Welcome to LASP: Library for Acoustic Signal Processing. LASP is a C++ library with a Python interface which is supposed to acquire and process (multi) sensor data in real time on a PC and output results.

Current features that are implemented:

• Communication with data acquisition (DAQ) devices, of which:
  • Internal sound cards via the RtAudio backend. Many thanks to Gary P. Scavone et al.
  • Measurement Computing DT9838A signal analyzer.
• Configuration of DAQ devices: AC coupling, IEPE, sensitivity physical quantities.
• Recording of signals from these DAQ devices, and storing in a HDF5 file.
• Filter designers to create A/C sound pressure weighting
• Biquad filter designers for low pass, high pass, peaking and notch filters
• A Peak Programme Meter (PPM) to monitor signal levels from DAQ and to watch for signal clipping.
• A signal generator to create sine waves, sweeps and noise (white / pink).
• Equalizers to equalize the output prior to sending.
• Averaged power spectra and power spectral density determination using Welch' method. Taper functions of Hann, Hamming, Bartlett and Blackman are provided.
• (One third) octave filter bank filters designed to comply with IEC 61260 (1995).
• Slow and fast time updates of (A/C/Z) weighted sound pressure levels
• Full Sound Level Meter implementation
• Real time Sound Level meter, Power / Transfer function estimator
• Spectra data smoothing algorithms
• Sensor calibration for microphones

Future features (wish-list)

• Conventional and delay-and-sum beam-forming algorithms
• Impedance tube measurement processing

For now, the source code is well-documented on lasp.ascee.nl but it requires some additional documentation (the math behind it). This is maintained in a sister repository lasp-doc.

If you have any question(s), please feel free to contact us: email.

Installation - Linux (Ubuntu-based)

From wheel (recommended for non-developers)

Prerequisites

Run the following on the command line to install all prerequisites on Debian-based Linux:

• sudo apt install python3-pip libfftw3-3 libopenblas-base libusb-1.0-0 libpulse0

Download and install LASP

Go to: LASP releases and download the latest .whl. Then run:

• pip install lasp-*-linux_x86_64.whl

From source (Ubuntu-based)

Prerequisites

Run the following one-liner:

• sudo apt install -y git python3 python3-virtualenv python3-venv libopenblas-dev python3-pip libfftw3-dev libusb-1.0-0-dev libpulse-dev python3-build

If building RtAudio with the ALSA backend, you will also require the following packages:

• sudo apt install libclalsadrv-dev

If building RtAudio with the Jack Audio Connection Kit (JACK) backend, you will also require the following packages:

• sudo apt install libjack-jackd2-dev

Download & build

• $ git clone --recursive https://code.ascee.nl/ASCEE/lasp.git
• $ cd lasp
• pip install -e .

Installation - (x86_64) Windows (with WinPython), build with MSYS2 (NOT YET UPDATED!!)

Prerequisites

• Download and install WinPython

• Download and install MSYS2. Make sure to install the x86_64 version.

• Download and install Git for Windows

• When unzipping WinPython, make sure to choose a proper and simple path, i.e. C:\winpython

• Append C:\winpython\ to the PATH environment variable.

• Run Python and install Pybind11

  • python -m pip install pybind11

• Open a msys2 MINGW64 terminal. And run:

  • pacman -S git

• Then clone the LASP repo:

  • git clone https://code.ascee.nl/ascee/lasp
  • cd lasp

• Configure MSYS2 further, and run cmake:

  • scripts/install_msys2_buiddeps.sh
  • scripts/configur_cmake_msys2.sh

Documentation

Online

Online LASP documentation.

In directory

$ sudo apt install doxygen graphviz $ pip install doxypypy

While still in lasp dir:

$ doxygen

This will build the documentation. It can be read by:

$ <YOUR-BROWSER> doc/html/index.html

Usage

• See examples directories for IPython notebooks.
• Please refer to the documentation for features.