filters.chroma({sr:22050, n_fft:2048}) rendered as a 12 × 1025 heatmap
(the "chroma filterbank" plot): each row is a pitch class (C at the
bottom, base_c grid), x-axis is FFT bin frequency 0 → 11025 Hz. You should see the
Gaussian pitch-class bumps repeating each octave and the octave-dominance envelope
fading the extremes. Proofs: the pitch class with the most weight at the FFT bin
nearest 440 Hz must be 9 (A), and every column's L2 norm must be ≤ 1 + 1e-6
(per-bin norm=2 column normalization, then dominance weighting only ever shrinks it).