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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)
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
Installation from wheel (recommended for non-developers)
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 lasppip install -e .
Installation - (x86_64) Windows (with WinPython), build with MSYS2
Prerequisites
- Download and install WinPython
From wheel
- Download latest wheel from LASP releases and
download the latest
.whl. Then install withpip.
From source
- Download and install MSYS2. Make sure to install the x86_64 version.
- When unzipping WinPython, make sure to choose a proper and simple path, i.e. C:\winpython
- Download and install Git for Windows
- Open an MSYS2 MINGW64 terminal, and install some tools we require:
$ pacman -S git
- Create a new virtualenv:
$ /c/winpython/<py-distr-dir>/python.exe -m venv venv
- Add the venv-python to the path (eases a lot of commands)
$ export PATH=$PATH:~/venv/Scripts
- Install
build:$ pip install build
- Clone LASP:
$ git clone --recurse-submodules https://code.ascee.nl/ascee/lasp && cd lasp
- If run for the first time, we have to install the libraries we depend on in
MSYS2 (this only has to be done on a fresh MSYS2 installation):
$ scripts/install_msys2_builddeps.sh
- Copy over required DLL's to be included in distribution:
scripts/copy_windows_dlls.sh
- And... build!
pyproject-build
- Lastly: the generated wheel can be installed in the current virtualenv:
pip install dist/lasp*.whl
Documentation
Online
In directory (Linux/Debian)
$ 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.