2 Commits

Author	SHA1	Message	Date
Thomas Ales [M S E]	1caf6373cb	Replace zoom FFT peak search with a budget-bounded PyFFTW direct transform ... Drop the coarse+fine zoom refinement, the SciPy FFT backend, and the exact= audit path in favor of a single always-on full-transform peak search (_peak_bins). Block size is now derived from a per-thread memory budget (_fft_block_for/SRAS_FFT_PLAN_BUDGET_MB) instead of a fixed constant, so the existing block-parallel PyFFTW pool stays memory-safe at high pad factors without the zoom algorithm's bookkeeping. Also removes the now-unused threadpoolctl dependency and the FFT backend selector from the UI. Also includes a pre-existing min_freq_mhz peak-search floor (excludes bins below a caller-supplied frequency from the argmax) that was already implemented and tested in the working tree. Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>	2026-08-10 14:14:38 -05:00
Thomas Ales	3989c2a1b8	Implement row-averaged FFT feature for same-row SNR cleanup ... Add row-averaged FFT feature with configurable window size (row_avg_n parameter) for improved signal-to-noise ratio on noisy scans. Includes: - Gaussian-weighted same-row neighbor averaging (never crosses rows) - Masked/renormalized convolution handling for edge cases and masked samples - Cache format v2 with row_avg_n tracking to prevent silent cache mismatches - GUI dialog option for row-average window configuration - Comprehensive tests validating kernel properties, background subtraction invariance, and cache dispatch Co-Authored-By: Claude Haiku 4.5 <noreply@anthropic.com>	2026-08-07 21:50:05 -05:00