https://github.com/avivajpeyi/imbh_pe
Science Score: 36.0%
This score indicates how likely this project is to be science-related based on various indicators:
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○CITATION.cff file
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✓codemeta.json file
Found codemeta.json file -
✓.zenodo.json file
Found .zenodo.json file -
○DOI references
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○Academic publication links
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✓Committers with academic emails
2 of 3 committers (66.7%) from academic institutions -
○Institutional organization owner
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○JOSS paper metadata
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○Scientific vocabulary similarity
Low similarity (3.3%) to scientific vocabulary
Last synced: 10 months ago
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JSON representation
Repository
Basic Info
- Host: GitHub
- Owner: avivajpeyi
- Language: HTML
- Default Branch: master
- Size: 58.7 MB
Statistics
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 3
- Releases: 0
Created about 7 years ago
· Last pushed over 1 year ago
Metadata Files
Readme
README.md
IMBH Parameter Estimation
Posterior Prob of a signal hypothesis
- Generate a list of IMBH GW parameters and use them to simulate GW signals.
- Inject simulated signals into LIGO noise data.
- Use a nested sampling to generate a list of posterior samples of potential IMBH parameters based on the hypothesis that data=noise+signal.
- The posterior samples give us
- p(θ|d) posterior of parameters given the data
- p(θi|d) marginalised posteriors for our parameters
- Z (evidence of the hypothesis)
Population Inference
- Calculate p(θ|d) and Z for several injected signals
- Use the numerous p(θ|d) to begin collecting a list of population posterior density samples, based on a population model hypothesis
- Use population posterior density samples to marginalise hyper-parameters:
- Duty-cycle: % of data that is modeled well by the current hypothesis d=n+s
- Mass distribution
- Spin distribution
Distributions to give prior info to future detections
- Mass, spin, duty cycle marginalised posteriors provide an idea of how probable certain events are
Owner
- Name: Avi Vajpeyi
- Login: avivajpeyi
- Kind: user
- Company: Monash University
- Website: https://avivajpeyi.github.io/
- Repositories: 28
- Profile: https://github.com/avivajpeyi
Astrophysics PhD student
GitHub Events
Total
- Push event: 5
- Pull request event: 1
- Create event: 1
Last Year
- Push event: 5
- Pull request event: 1
- Create event: 1
Committers
Last synced: over 1 year ago
Top Committers
| Name | Commits | |
|---|---|---|
| Avi Vajpeyi | a****i@l****g | 109 |
| Avi Vajpeyi | a****i@g****m | 89 |
| Avi Vajpeyi | a****i@l****u | 2 |
Committer Domains (Top 20 + Academic)
Issues and Pull Requests
Last synced: about 1 year ago
All Time
- Total issues: 0
- Total pull requests: 3
- Average time to close issues: N/A
- Average time to close pull requests: N/A
- Total issue authors: 0
- Total pull request authors: 2
- Average comments per issue: 0
- Average comments per pull request: 0.0
- Merged pull requests: 0
- Bot issues: 0
- Bot pull requests: 3
Past Year
- Issues: 0
- Pull requests: 1
- Average time to close issues: N/A
- Average time to close pull requests: N/A
- Issue authors: 0
- Pull request authors: 1
- Average comments per issue: 0
- Average comments per pull request: 0.0
- Merged pull requests: 0
- Bot issues: 0
- Bot pull requests: 1
Top Authors
Issue Authors
Pull Request Authors
- dependabot[bot] (3)
- pre-commit-ci[bot] (2)
Top Labels
Issue Labels
Pull Request Labels
dependencies (3)
Dependencies
requirements.txt
pypi
- argparse *
- astropy ==2.0.9
- bilby *
- bilby-pipe *
- deepdish *
- gwpy *
- h5py *
- hurry.filesize *
- lalsuite *
- matplotlib *
- numpy ==1.15.4
- opencv-python-headless *
- pandas *
- plotly *
- pluggy ==0.12
- pytest ==2.8
- scikit-learn *
- scipy *
- tables ==3.4.4
- theano *
- typing *