pywayne-dsp
CommunityTurn raw sensor data into clean signals.
Authorwangyendt
Version1.0.0
Installs0
System Documentation
What problem does it solve?
Digital signal processing is essential for turning noisy sensor data into usable information. This skill provides a cohesive toolkit for filtering, detrending, peak detection, and curve similarity to streamline preprocessing and analysis.
Core Features & Use Cases
- Filtering: Butterworth filters and smoothing (OneEuro) to reduce noise in time-series data.
- Detrending: Multiple detrending options (linear, mean, LOESS, etc.) to reveal underlying trends.
- Peak Detection & Extremes: Functions to identify peaks, valleys, and sliding-window extrema for event detection.
- Curve Similarity: Dynamic time warping (DTW) based comparisons to measure similarity between time series.
- Online Statistics: Online standard deviation computation for real-time monitoring.
Quick Start
Load your sensor data and apply ButterworthFilter or OneEuroFilter to obtain a clean signal, then run peak_det and CurveSimilarity to compare patterns.
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: pywayne-dsp Download link: https://github.com/wangyendt/wayne-skills/archive/main.zip#pywayne-dsp 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 223,000+ vetted skills library on demand.