Update spectral.py

spectral.py

@@ -1,9 +1,3 @@
-# spectral.py
-# ============================================================
-# Spectral Analysis Module for Audio Forensic Analyzer
-# Logic preserved exactly from original app.py (cleaned + modular)
-# ============================================================
-
 import numpy as np
 import librosa
 import scipy.signal as sps
@@ -30,7 +24,7 @@ def compute_spectral_analysis(y, sr, n_fft=4096):
     S_db = librosa.amplitude_to_db(S, ref=np.max)
 
     # ============================================================
-    # 90th Percentile Energy Envelope (Major Improvement)
+    # 90th Percentile Energy Envelope
     # ============================================================
     S_power = S ** 2
     energy = np.percentile(S_power, 90, axis=1) + 1e-20
@@ -118,10 +112,7 @@ def compute_spectral_analysis(y, sr, n_fft=4096):
     flatness = float(np.mean(librosa.feature.spectral_flatness(S=S)))
     rolloff = float(np.mean(librosa.feature.spectral_rolloff(S=S, sr=sr)))
 
-    # ============================================================
-    # FINAL RETURN STRUCTURE
-    # (Matches original format exactly)
-    # ============================================================
+
     return {
         "S_db": S_db,
         "freqs": freqs,
@@ -144,7 +135,6 @@ def compute_spectral_analysis(y, sr, n_fft=4096):
         "spectral_flatness": flatness,
         "spectral_rolloff": rolloff,
 
-        # Added envelopes for downstream detectors (unchanged logic)
         "hf_env": mean_db_per_bin,
         "lf_env": mean_db_per_bin[:200] if len(mean_db_per_bin) > 200 else mean_db_per_bin
     }