192 lines
6.0 KiB
Markdown
192 lines
6.0 KiB
Markdown
Library for Acoustic Signal Processing
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======================================
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Welcome to LASP: Library for Acoustic Signal Processing. LASP is a C++ library
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with a Python interface which is supposed to acquire and process (multi) sensor data in real time on a PC and output results.
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Current features that are implemented:
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- Communication with data acquisition (DAQ) devices, of which:
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- Internal sound cards via the [RtAudio](http://www.music.mcgill.ca/~gary/rtaudio) backend. Many thanks to Gary P. Scavone et al.
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- [Measurement Computing](https://www.mccdaq.com) [DT9838A](https://www.mccdaq.com/Products/Sound-Vibration-DAQ/DT9837) signal analyzer.
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- Configuration of DAQ devices: AC coupling, IEPE, sensitivity physical
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quantities.
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- Recording of signals from these DAQ devices, and storing in a HDF5 file.
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- Filter designers to create A/C sound pressure weighting
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- Biquad filter designers for low pass, high pass, peaking and notch filters
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- A Peak Programme Meter (PPM) to monitor signal levels from DAQ and to watch
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for signal clipping.
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- A signal generator to create sine waves, sweeps and noise (white / pink).
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- Equalizers to equalize the output prior to sending.
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- Averaged power spectra and power spectral density determination
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using Welch' method. Taper functions of Hann, Hamming, Bartlett and
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Blackman are provided.
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- (One third) octave filter bank filters designed to comply with IEC 61260
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(1995).
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- Slow and fast time updates of (A/C/Z) weighted sound pressure levels
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- Full Sound Level Meter implementation
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- Real time Sound Level meter, Power / Transfer function estimator
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- Spectra data smoothing algorithms
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- Sensor calibration for microphones
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Future features (wish-list)
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- Conventional and delay-and-sum beam-forming algorithms
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- Impedance tube measurement processing
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For now, the source code is well-documented on [lasp.ascee.nl](https://lasp.ascee.nl) but it requires some
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additional documentation (the math behind it). This is maintained
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in a sister repository [lasp-doc](https://code.ascee.nl/ascee/lasp-doc).
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If you have any question(s), please feel free to contact us: [email](info@ascee.nl).
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# Installation - Linux (Ubuntu-based)
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## Prerequisites
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Run the following on the command line to install all prerequisites on
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Debian-based Linux, x86-64:
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- `sudo apt install python3-pip libfftw3-3 libopenblas-base libusb-1.0-0 libpulse0`
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## Installation from wheel (recommended for non-developers)
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Go to: [LASP releases](https://code.ascee.nl/ASCEE/lasp/releases/latest/) and
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download the latest `.whl`. Then run:
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- `pip install lasp-*-linux_x86_64.whl`
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## From source (Ubuntu-based)
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### Prerequisites
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Run the following one-liner:
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- `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`
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If building RtAudio with the ALSA backend, you will also require the following packages:
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- `sudo apt install libclalsadrv-dev`
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If building RtAudio with the Jack Audio Connection Kit (JACK) backend, you will also require the following packages:
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- `sudo apt install libjack-jackd2-dev`
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### Download & build
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- `$ git clone --recursive https://code.ascee.nl/ASCEE/lasp.git`
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- `$ cd lasp`
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- `pip install -e .`
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# Building and installation for Raspberry Pi (Raspberry Pi OS)
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Run the following on the command line to install all prerequisites on
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Raspberry Pi OS:
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- `sudo apt install libfftw3-dev libopenblas64-dev libhdf5-dev libclalsadrv-dev`
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In a virtualenv: install `build`
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- `$ pip install build`
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Then run:
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- `$ git clone --recursive https://code.ascee.nl/ASCEE/lasp.git`
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- `$ cd lasp`
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- `$ pyproject-build`
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Which will generate a `whl` in the `dist` folder, that is redistributable for Raspberry Pis that run Raspberry Pi OS.
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When installing the `whl`, it appears that H5PY takes quite some time to install. To follow this process, run it it verbose mode.
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# Installation - (x86_64) Windows (with WinPython), build with MSYS2
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## Prerequisites
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- Download and install [WinPython](https://winpython.github.io)
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## From wheel
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- Download latest wheel from [LASP releases](https://code.ascee.nl/ASCEE/lasp/releases/latest/) and
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download the latest `.whl`. Then install with `pip`.
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## From source
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- Download and install [MSYS2](https://msys2.org). Make sure to install the
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x86_64 version.
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- When unzipping WinPython, make sure to choose a proper and simple path, i.e.
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C:\winpython
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- Download and install [Git for Windows](https://git-scm.com)
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- Open an MSYS2 **MINGW64** terminal, and install some tools we require:
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- `$ pacman -S git`
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- Create a new virtualenv:
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- `$ /c/winpython/<py-distr-dir>/python.exe -m venv venv`
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- Add the venv-python to the path (eases a lot of commands)
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- `$ export PATH=$PATH:~/venv/Scripts`
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- Install `build`:
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- `$ pip install build`
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- Clone LASP:
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- `$ git clone --recurse-submodules https://code.ascee.nl/ascee/lasp && cd lasp`
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- If run for the first time, we have to install the libraries we depend on in
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MSYS2 (this only has to be done on a fresh MSYS2 installation):
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- `$ scripts/install_msys2_builddeps.sh`
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- Copy over required DLL's to be included in distribution:
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- `scripts/copy_windows_dlls.sh`
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- And... build!
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- `pyproject-build`
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- Lastly: the generated wheel can be installed in the current virtualenv:
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- `pip install dist/lasp*.whl`
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# Documentation
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## Online
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[Online LASP documentation](https://lasp.ascee.nl/).
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## In directory (Linux/Debian)
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`$ sudo apt install doxygen graphviz`
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`$ pip install doxypypy`
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While still in lasp dir:
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`$ doxygen`
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This will build the documentation. It can be read by:
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`$ <YOUR-BROWSER> doc/html/index.html`
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# Usage
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- See examples directories for IPython notebooks.
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- Please refer to the [documentation](https://lasp.ascee.nl/) for features.
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# Development docs
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## Bumping version number
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When bumping the version number, please update the number in
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- `pyproject.toml`
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- `CMakeLists.txt`
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Then, create a commit with tag `vX.X.X`, and push it.
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## Updating to latest version (editable mode)
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When updating to the latest version of LASP in editable mode:
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```bash
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- $ git pull
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- $ git submodule update
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- $ pip install -e . -v
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``` |