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Gravitational Wave Event Analyzer

Name: Gravitational Wave Event Analyzer
Author: yash-kavaiya

作者 Yash Kavaiya · GitHub ↗ · v1.0.0 · MIT-0

cross-platform ✓ 安全检测通过

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总下载

当前安装

版本数

在 OpenClaw 中安装

/install gravitational-wave-analyzer

功能描述

Fetch real LIGO/Virgo/KAGRA gravitational wave events from the GWOSC (Gravitational Wave Open Science Center) catalog, download detector strain data, run sig...

使用说明 (SKILL.md)

Gravitational Wave Event Analyzer

A skill for fetching and analyzing real gravitational wave events from LIGO/Virgo/KAGRA using public GWOSC data.

What This Skill Does

Catalog Query — Fetch events from GWTC (Gravitational-Wave Transient Catalog) via GWOSC API
Strain Download — Pull real detector strain timeseries data for any event
Signal Processing — Whiten, bandpass filter, and Q-transform the strain
Merger Classification — Classify event type: BBH (binary black hole), BNS (binary neutron star), or NSBH
Visualization — Generate spectrograms, waveform plots, and summary figures

Usage

Analyze a specific event

from gw_analyzer import GWEventAnalyzer

analyzer = GWEventAnalyzer()
result = analyzer.analyze_event("GW150914")
result.plot()
result.summary()

List recent events

events = analyzer.list_events(catalog="GWTC-3", min_far=1e-3)

Full pipeline

python gw_analyzer.py --event GW150914 --detector H1 --output ./output/
python gw_analyzer.py --event GW231123_135430 --detector L1 --output ./output/
python gw_analyzer.py --list-events --catalog GWTC-3 --top 10

Key Events to Try

Event	Type	Description
GW150914	BBH	First detection ever (2015)
GW170817	BNS	First neutron star merger (multi-messenger)
GW200105	NSBH	First neutron star–black hole merger
GW231123_135430	BBH	Most massive merger ever detected

Output

{event}_waveform.png — Raw + whitened + filtered strain timeseries
{event}_qtransform.png — Time-frequency Q-transform (chirp signature)
{event}_summary.json — Event parameters, classification, SNR estimate
{event}_report.txt — Human-readable analysis report

Data Source

All data fetched from GWOSC — publicly released under CC BY 4.0. Catalog: GWTC (Gravitational-Wave Transient Catalog), updated through O4a run.

Dependencies

gwpy>=3.0.0
gwosc>=0.7.0
numpy>=1.24.0
scipy>=1.10.0
matplotlib>=3.7.0
astropy>=5.3.0

安全使用建议

This skill appears to do what it claims: it downloads public GWOSC data, runs signal-processing using standard Python science packages, and writes plots/reports to disk. Before installing, note: (1) it requires installing a moderate scientific Python stack (gwpy/gwosc/astropy/etc.) which can pull compiled dependencies — consider using a virtualenv or container; (2) it will perform network downloads from gwosc.org and may download multi-second/high-sample-rate strain segments (bandwidth and disk use can be non-trivial); (3) it writes output files to the specified output directory; (4) no credentials or secrets are required; (5) because the package source is 'unknown' in the registry metadata, if you want extra assurance inspect the full gw_analyzer.py (provided) and run in an isolated environment (or read-only sandbox) before granting broader runtime privileges.

功能分析

Type: OpenClaw Skill Name: gravitational-wave-analyzer Version: 1.0.0 The skill bundle is a legitimate scientific tool for analyzing gravitational wave data from the Gravitational Wave Open Science Center (GWOSC). The code in 'gw_analyzer.py' uses standard scientific libraries (gwpy, gwosc, numpy) and interacts only with official GWOSC APIs (gwosc.org) to fetch public astronomical data. There are no signs of data exfiltration, malicious execution, or prompt injection.

能力评估

✓ Purpose & Capability

Name/description match the included Python code and SKILL.md. The code uses gwosc/gwpy and related scientific packages to query GWOSC, download strain data, run whitening/Q-transform/matched-filter steps, classify mergers, and produce plots — all expected for a gravitational-wave analysis tool. No unrelated credentials, binaries, or config paths are requested.

✓ Instruction Scope

SKILL.md and gw_analyzer.py keep scope to GW event lookup, strain download, signal processing, and output generation. The runtime behavior involves network access to GWOSC (public API), optional HTTP fallback, and writing analysis outputs (images, JSON, text) to a local output directory — all consistent with the stated functionality. There are no instructions to read unrelated system files or environment variables.

ℹ Install Mechanism

Install spec is a Python package install (gwpy, gwosc, numpy, scipy, matplotlib, astropy) which is appropriate for this domain. This is higher-risk than an instruction-only skill only in that it will install non-trivial scientific packages (some with compiled components) into the runtime environment; the packages are standard PyPI scientific libraries and not obscure external archive downloads.

✓ Credentials

The skill requires no environment variables, no credentials, and no config paths. Network access to gwosc.org and GWOSC API endpoints is used, which is proportionate to the stated purpose of fetching public gravitational-wave data.

✓ Persistence & Privilege

always is false (not force-included). The skill does not request persistent platform-wide privileges or modify other skills' configs. It writes outputs to its own output directory only.

如何使用

确保已安装 OpenClaw（本地或 Docker 部署）
在对话框中输入安装命令：/install gravitational-wave-analyzer
安装完成后，直接呼叫该 Skill 的名称或使用 /gravitational-wave-analyzer 触发
根据 Skill 的参数说明提供必要输入，即可获得结构化输出

版本历史

v1.0.0

First release: fetch real LIGO/Virgo/KAGRA strain data, run Q-transform analysis, classify BBH/BNS/NSBH mergers via GWOSC public catalog

元数据

Slug gravitational-wave-analyzer

版本 1.0.0

许可证 MIT-0

累计安装 0

当前安装数 0

历史版本数 1

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