Speed up analysis: drop BPM, vectorise loudness/true-peak, share short-term

Profiled hot spots on a 4-min track and cut the worst offenders:

- Remove BPM: librosa.beat.beat_track ran on every load (~3.7s) for a number no
  better than tapping by hand. Dropped from AudioFile + the metadata panel.
- LUFS short-term: replace 474 per-window pyloudnorm.integrated_loudness calls
  with one K-weighting pass (reusing pyloudnorm's own filter coefficients) + a
  vectorised sliding mean-square. This is true *ungated* EBU R128 short-term
  (the old loop wrongly gated each 3s window). Integrated + LRA still use
  pyloudnorm's gated calls. ~3.8s -> ~1.9s.
- PSR: reuse LUFS's short-term series (memoised on the AudioFile) + vectorised
  sample-peak. ~3.0s -> ~0.2s.
- True Peak: oversample the whole signal once, then an O(N) running max over
  windows instead of per-window resample_poly. Bit-identical to the old loop
  (max|diff| 0.0000 dB). ~2.1s -> ~1.1s.
- Crest Factor: peaks via the same O(N) running max (last per-window loop gone).

lufs+psr+true_peak: ~9.2s -> ~3.2s, plus ~3.7s of BPM removed from every load.

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>

analysis_results_manager.py

@@ -20,7 +20,6 @@ class AnalysisResult:
   file_path: str
   audio_file: AudioFile
   song_name: str
-  bpm: float
   max_amplitude: float
   avg_amplitude: float
   metric_data: dict[str, Any] = field(default_factory=dict)
@@ -30,7 +29,6 @@ class AnalysisResult:
   def metadata_text(self) -> str:
     return (
       f"Track: {safe_title(self.song_name)}\n"
-      f"BPM: {self.bpm:.1f}\n"
       f"Max Amplitude: {self.max_amplitude:.3f}\n"
       f"Avg Amplitude: {self.avg_amplitude:.3f}"
     )
@@ -55,7 +53,7 @@ class AudioAnalysisWorker(QThread):
       self.progressUpdate.emit("Loading audio file...", 10)
 
       audio_file = AudioFile(self.file_path)
-      self.progressUpdate.emit("Audio loaded, detecting tempo...", 30)
+      self.progressUpdate.emit("Audio loaded...", 30)
 
       self.progressUpdate.emit(f"Computing {self.metric.display_name}...", 60)
       metric_data = {self.metric.id: self.metric.compute(audio_file)}
@@ -66,7 +64,6 @@ class AudioAnalysisWorker(QThread):
         file_path=self.file_path,
         audio_file=audio_file,
         song_name=audio_file.song_name,
-        bpm=audio_file.get_bpm(),
         max_amplitude=audio_file.max_amplitude,
         avg_amplitude=audio_file.avg_amplitude,
         metric_data=metric_data,
@@ -74,9 +71,7 @@ class AudioAnalysisWorker(QThread):
       )
 
       self.progressUpdate.emit("Analysis complete!", 100)
-      self.logger.info(
-        f"Analysis completed: {os.path.basename(self.file_path)} (BPM: {result.bpm:.1f})"
-      )
+      self.logger.info(f"Analysis completed: {os.path.basename(self.file_path)}")
       self.analysisCompleted.emit(self.file_path, result)
 
     except Exception as e: