gwax
Gravitational-wave astronomy in JAX.
Install
- Install JAX following their instructions for your platform and hardware.
pip install gwax.
To install the latest development: pip install git+https://github.com/mdmould/gwax.
Implementations
- Flow-based variational inference for gravitational-wave population analysis.
Usage
See the examples.
Current limitations
- gwax is being actively developed and the interface is likely to undergo breaking changes.
- Currently the only thing implemented is variation inference of gravitational-wave populations.
- Variational population inference only interfaces with gwpopulation.
- Only univariate uniform priors are supported.
1 maintainer
Metadata
1 maintainer
Release files for gwax 0.1.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | Provenance | Actions |
|---|---|---|---|---|
| gwax-0.1.0.tar.gz | 9.9 kB | Without provenance | Details for gwax-0.1.0.tar.gz |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Actions Reset |
|---|---|---|---|---|
| gwax-0.1.0-py3-none-any.whl | Python 3 | none | any | Details for gwax-0.1.0-py3-none-any.whl |
Total release size: 20.2 kB
Release files / gwax-0.1.0.tar.gz
| Download URL | gwax-0.1.0.tar.gz |
|---|---|
| Size | 9.9 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/6.2.0 CPython/3.12.11
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Release files / gwax-0.1.0-py3-none-any.whl
| Download URL | gwax-0.1.0-py3-none-any.whl |
|---|---|
| Size | 10.3 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
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BLAKE2b-256 checksum How to use checksums |
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| Upload date | |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/6.2.0 CPython/3.12.11
|
Security for gwax 0.1.0
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