dynasaur
Science Score: 44.0%
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○Scientific vocabulary similarity
Low similarity (7.5%) to scientific vocabulary
Repository
Basic Info
- Host: GitHub
- Owner: jcbayley
- Language: Jupyter Notebook
- Default Branch: main
- Size: 1.02 MB
Statistics
- Stars: 2
- Watchers: 1
- Forks: 0
- Open Issues: 7
- Releases: 2
Metadata Files
README.md
dynasaur
Project to find the mass and dynamics of a system from the gravitational wavestrain time series. Use normalising flows conditioned on strain to find polynomial coefficients of mass motion
For a test case we trained a model on circular orbits with random radii, masses and initial phase angle. These were simulated in the x,y plane, however were reconstructed in 3d space.
The black points in the left panel are the true injected point masses where their true waveform is shown in the right hand panel in black. The left panel of each of these plots also shows many pairs of blue and orange points, these are points sampled from a normalising flow conditioned on the black waveforms in the left panels. For each of these pairs we can reconstruct the waveform again, the 90% confidence region of all of these reconstructions are shown in the right hand plots.
The main goal here was to train on lots of random orbits, where the fourier components of the positions of the masses are randomly sampled between [0,1].
Installation
In the root directory run:
bash
pip install .
Usage
To use train a model based on a config (examples can be found in the examples directory):
bash
python -m dynasaur.train_model --config config.ini --train
To test the model
bash
python -m dynasaur.train_model --config config.ini --test --ntest 10 --makeplots
Owner
- Login: jcbayley
- Kind: user
- Repositories: 2
- Profile: https://github.com/jcbayley
Citation (CITATION.cff)
cff-version: 1.1.0 message: "If you use this software, please cite it as below." authors: - family-names: Joe given-names: Bayley orcid: https://orcid.org/0000-0003-2306-4106 title:jcbayley/dynasaur: 0.0.2 version: 0.0.2 date-released: 2024-09-11
GitHub Events
Total
- Issues event: 3
- Push event: 3
- Create event: 3
Last Year
- Issues event: 3
- Push event: 3
- Create event: 3
Dependencies
- matplotlib *
- numpy *
- scipy *
- torch *