Add spectrogram, native-rate loading, and always-labelled axis extremes

- SpectrogramMetric: log-frequency STFT power heatmap over time, magma
  colormap, -80 dB floor. Adaptive hop caps time bins at ~4000 so long
  tracks stay responsive on redraw; N_FFT=4096 keeps low-freq resolution.
- master_core: load audio at native sample rate (librosa.load sr=None)
  instead of librosa's 22050 Hz default, so the full band up to the
  file's own nyquist (~22 kHz at 44.1 kHz) is analysed. ~2x heavier on
  44.1/48 kHz files, by design.
- metrics: shared _show_axis_extents helper forces each axis's exact
  min/max onto the tick list with compact labels (_fmt_tick), so the
  true range is always readable -- notably the spectrogram's 22 kHz top,
  which otherwise sits unlabelled between log-scale decade ticks. Applied
  to all metric renders.
- Docs: README + CLAUDE updated for the new metric, native-rate loading,
  and axis-readability behaviour.

Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>

master_core.py

@@ -27,8 +27,10 @@ class AudioFile:
     else:
       self.song_name = safe_title(os.path.basename(self.file_path))
 
-    # librosa.load normalises to [-1.0, 1.0]
-    self.y, self.sr = librosa.load(file_path)
+    # librosa.load normalises to [-1.0, 1.0]. sr=None preserves the file's
+    # native sample rate; without it librosa resamples to 22050 Hz, which would
+    # discard everything above ~11 kHz (the entire top octave) before analysis.
+    self.y, self.sr = librosa.load(file_path, sr=None)
     self.y_mono = librosa.to_mono(self.y)
     self.max_amplitude = np.max(np.abs(self.y_mono))
     self.avg_amplitude = np.mean(np.abs(self.y_mono))