LISA Data Challenge software
Project description
LISA Data Challenge software
LDC provides a set of tools to generate and analyse the LDC datasets.
Installation of the latest released version
pip install lisa-data-challenge
Installation of the dev version
Cloning the gitlab project
The default working branch is named develop.
git clone -b develop https://gitlab.in2p3.fr/LISA/LDC.git
Installation
By default, pyproject.toml will be used to generate a temporary
environement to build the package (see
https://pip.pypa.io/en/stable/reference/build-system/pyproject-toml/)
pip install .
For older version of setuptools, a setup.py file is also provided.
python setup.py install
Troubleshooting
Prerequisites
- GSL :
apt-get install libgsl-devorconda install gsl - FFTW3 :
apt-get install libfftw3-devorconda install fftw
Paths to FFTW and GSL can be set explicitly by editing setup.cfg.
Python dependencies
Make sure that all requirements are met.
The requirements.txt file defines the reference version for most of
the dependencies for a python3.9 installation as recommended by
LISA-CDE, but other versions
of the listed package might work.
To comply with the CDE environement:
pip install -r requirements.txt
Extensions for specific fast waveform generator can be disabled in the installation command line:
python setup.py install --no-fastGB --no-imrphenomD --no-fastAK
Extra dependencies
Some external tools are interfaced by the LDC and need separate installation:
- EMRI waveform with few: see https://bhptoolkit.org/FastEMRIWaveforms/html/index.html
- Fast BH waveform with lisabeta: see https://gitlab.in2p3.fr/marsat/lisabeta
Documentation
Use policy
Do not forget to associate the authors of this software to your research:
-
Please cite the DOI (see badge above) and acknowledge the LDC working group in any publication which makes use of it
-
Do not hesitate to send an email for help and/or collaboration: ldc-at-lisamission.org, ldc-chairs-at-lisamission.org
Project status
This toolbox has been developed to support the simulation production and analysis of the LISA Data Challenges, over the 2020-2024 period. These are the LDC codenamed:
-
Sangria LDC2a: mild enchilada (GB, MBHB), simple noise
-
Spritz LDC2b: single source type (GB, MBHB), instrumental artifacts (glitches, gaps)
-
Yorsh LDC1b: single source type: SOBH, EMRI
Following on the LISA adoption by space agencies in 2024, multiple projects to support this activity have been put in place, to address the forthcoming increase in complexity of the future LDC. Thus this toolbox is under a decommissioning phase.
The following table gives pointers to those new projects, for the different parts covered by this toolbox.
| Topic | LDC toolbox submodule | New projects URL |
|---|---|---|
| Fast waveform | ldc/waveform/fastgb | https://gitlab.in2p3.fr/lisa/fastgb |
| Waveform h+/hx | ldc/waveform/waveform | |
| Catalogs | ldc/waveform/source | |
| LISA response | ldc/lisa/projection | https://gitlab.in2p3.fr/lisa-simulation/gw-response |
| LISA analytic noise | ldc/lisa/noise | https://gitlab.in2p3.fr/LISA/fomweb |
| LISA analytic orbits | ldc/isa/orbits | https://gitlab.in2p3.fr/lisa-simulation/orbits |
| Time/freq series management | ldc/common/series | https://gitlab.in2p3.fr/lisa-apc/typed-lisa-toolkit |
| LISA constants | ldc/common/constants | https://gitlab.in2p3.fr/lisa-simulation/constants |
| Simulation production pipeline | data_generation/ | see notebooks showing how to use the above tools presented during the sim workshops https://indico.in2p3.fr/event/33255/ |
| Submission evaluation | evaluation |
Project details
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