gw-foutstep
Implements the method of Valencia et al. (2024) to compute Fourier transforms of discrete data with step-like behaviors.
Installation steps
gw-foutstep is available in PyPI. Please, use the following command to install it
using pip:
$ pip install foutstep
Citing this work
If this package has been useful for you work, please cite the following paper:
@article{Valencia:2024zhi,
author = "Valencia, Jorge and Tenorio, Rodrigo and Rossell\'o-Sastre, Maria and Husa, Sascha",
title = "{Mind the step: On the frequency-domain analysis of gravitational-wave memory waveforms}",
eprint = "2406.16636",
archivePrefix = "arXiv",
primaryClass = "gr-qc",
reportNumber = "LIGO-P2400263",
month = "6",
year = "2024",
journal ="arXiv e-print",
}
Metadata
Release files for foutstep 0.1.4
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| foutstep-0.1.4.tar.gz | 232.8 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| foutstep-0.1.4-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 237.6 kB
Release files / foutstep-0.1.4.tar.gz
| Download URL | foutstep-0.1.4.tar.gz |
|---|---|
| Size | 232.8 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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Transparency logRelease files / foutstep-0.1.4-py3-none-any.whl
| Download URL | foutstep-0.1.4-py3-none-any.whl |
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| Size | 4.8 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
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Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/5.1.1 CPython/3.12.7
|
Provenance
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