conditioning
CommunityCondition GW data for fast, accurate analysis.
Data & Analytics#resampling#gravitational-waves#psd#data-conditioning#high-pass#matched-filtering#pycbc
AuthorKaiserWhoLearns
Version1.0.0
Installs0
System Documentation
What problem does it solve?
Data conditioning is essential before matched filtering. Raw gravitational wave detector data contains low-frequency noise, instrumental artifacts, and needs proper sampling rates for computational efficiency.
Core Features & Use Cases
- High-pass filtering to remove low-frequency noise
- Resampling to an efficient sampling rate for matched filtering
- Crop wraparound removal to suppress edge artifacts
- PSD estimation for informed template matching
Quick Start
Preprocess your raw gravitational-wave strain data by applying a 15 Hz high-pass filter, downsampling to 2048 Hz, cropping edge artifacts, and estimating the PSD.
Dependency Matrix
Required Modules
None requiredComponents
Standard package💻 Claude Code Installation
Recommended: Let Claude install automatically. Simply copy and paste the text below to Claude Code.
Please help me install this Skill: Name: conditioning Download link: https://github.com/KaiserWhoLearns/skillsbench/archive/main.zip#conditioning Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
Agent Skills Search Helper
Install a tiny helper to your Agent, search and equip skill from 471,000+ vetted skills library on demand.