Scitex Dsp

Digital signal-processing utilities tuned for neuroscience workflows. `hilbert(x)` returns analytic signal; `psd(x, fs, ...)` and `band_powers(x, fs, bands)` compute spectral density. `pac(x, lo, hi, ...)` and `modulation_index(x, ...)` quantify phase-amplitude coupling. `detect_ripples(x, fs, ...)` runs the Buzsaki-style ripple detector with edge handling, find-events, and column sorting baked in. Pre-/post-processing: `crop`, `ensure_3d`, `resample`, `demo_sig` (synthetic test signal). Submodules: `filt` (Butterworth bandpass/bandstop), `norm` (z-score, min-max, robust), `reference` (CAR, bipolar, Laplacian), `add_noise` (white, pink, ar1), `params` (canonical band definitions), `example` (worked examples). All functions accept `(channels, samples)` or `(batch, channels, samples)`. Drop-in replacement for hand-rolled `scipy.signal.butter` + `lfilter` chains and bespoke ripple detectors.

mkdir -p ~/.claude/skills/scitex-dsp
curl -L https://claudskills.com/skills/scitex-dsp/SKILL.md \
  -o ~/.claude/skills/scitex-dsp/SKILL.md

@misc{scitex-dsp-2026,
  author    = {ClaudSkills},
  title     = {Scitex Dsp [Claude Code skill]},
  year      = {2026},
  publisher = {ClaudSkills},
  url       = {https://claudskills.com/skills/scitex-dsp/}
}