lomb-scargle-periodogram
Lomb-Scargle periodogram for finding periodic signals in unevenly sampled time series data. Use when analyzing light curves, radial velocity data, or any astronomical time series to detect periodic variations. Works for stellar rotation, pulsation, eclipsing binaries, and general periodic phenomena. Based on lightkurve library.
npx skills add majiayu000/claude-skill-registry --skill lomb-scargle-periodogram --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# Lomb-Scargle Periodogram The Lomb-Scargle periodogram is the standard tool for finding periods in unevenly sampled astronomical time series data. It's particularly useful for detecting periodic signals in light curves from space missions like Kepler, K2, and TESS. ## Overview The Lomb-Scargle periodogram extends the classical periodogram to handle unevenly sampled data, which is common in astronomy due to observing constraints, data gaps, and variable cadences. ## Basic Usage with Lightkurve ```python import lightkurve as lk import numpy as np # Create a light curve object lc = lk.LightCurve(time=time, flux=flux, flux_err=error) # Create periodogram (specify maximum period to search) pg = lc.to_periodogram(maximum_period=15) # Search up to 15 days # Find strongest period strongest_period = pg.period_at_max_power max_power = pg.max_power print(f"Strongest period: {strongest_period:.5f} days") print(f"Power: {max_power:.5f}") ``` ## Plotting Periodograms ```python import matplotlib.pyplot as plt pg.plot(view='period') # View vs period (not frequency) plt.xlabel('Period [days]') plt.ylabel('Power') plt.show() ``` **Important**: Use `view='period'` to see periods directly, not freque
- Overview
- Basic Usage with Lightkurve
- Plotting Periodograms
- Period Range Selection
- Interpreting Results
- Power Significance
- Common Patterns
- Model Fitting
- Dependencies
- References
- When to Use This vs. Other Methods
pip install lightkurve numpy matplotlib
What does the lomb-scargle-periodogram skill do?
Lomb-Scargle periodogram for finding periodic signals in unevenly sampled time series data. Use when analyzing light curves, radial velocity data, or any astronomical time series to detect periodic variations. Works for stellar rotation, pulsation, eclipsing binaries, and general periodic phenomena. Based on lightkurve library.
How do I install it?
Run `npx skills add majiayu000/claude-skill-registry --skill lomb-scargle-periodogram --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From majiayu000/claude-skill-registry, a repository with 534 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.