[spectrum-basic] Frequency Spectrum Plot

[MarkusNeusinger]

A frequency spectrum plot displaying signal amplitude or power across frequencies. Shows the frequency domain representation of time-series data, commonly used for audio, vibration, and signal analysis.

[claude]

✅ Spec ID: spectrum-basic

Rationale: A basic frequency spectrum plot is a fundamental signal analysis visualization that doesn't exist yet in the repository.

This is a valid and useful plot type commonly used in audio processing, vibration analysis, and electrical engineering. No existing specs cover frequency domain representations.

Add label approved to begin generation.

[github-actions]

✅ Specification Ready: spectrum-basic

PR: #2932

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specification.md

spectrum-basic: Frequency Spectrum Plot

Description

A frequency spectrum plot displays signal amplitude or power across a range of frequencies, showing the frequency domain representation of time-series data. This visualization reveals the frequency components present in a signal, making it essential for identifying dominant frequencies, harmonics, and noise characteristics. It is fundamental in signal processing, audio engineering, and vibration analysis.

Applications

• Analyzing audio signals to identify frequency content such as musical notes, speech formants, or noise interference
• Detecting machinery vibration patterns and identifying potential mechanical faults based on characteristic frequencies
• Examining electrical signals to find interference frequencies or verify filter performance

Data

• frequency (numeric) - frequency values in Hz, typically from FFT computation
• amplitude (numeric) - signal amplitude or magnitude at each frequency, often in dB or linear scale
• Size: 256-4096 frequency bins (typical FFT sizes)
• Example: FFT output of a synthetic signal with multiple frequency components

Notes

• Use logarithmic scale for frequency axis when spanning wide frequency ranges
• Power spectral density (dB scale) is common for comparing signals with different amplitudes
• Include clear axis labels with units (Hz for frequency, dB or linear for amplitude)
• Consider highlighting peak frequencies or annotating dominant components

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