From f86cd966b06cd22463d9e5ebd8a0b39643da884a Mon Sep 17 00:00:00 2001
From: CroneKorkN <i@ckn.li>
Date: Fri, 30 May 2025 22:00:57 +0200
Subject: [PATCH] wip

---
 process_chunks.py | 11 ++++++-----
 1 file changed, 6 insertions(+), 5 deletions(-)

diff --git a/process_chunks.py b/process_chunks.py
index 0ae328e..0f4a5ab 100755
--- a/process_chunks.py
+++ b/process_chunks.py
@@ -4,7 +4,7 @@ import concurrent.futures
 import datetime
 import numpy as np
 import matplotlib.pyplot as plt
-import soundfile as sf
+import soundfile
 import scipy.signal
 from scipy.fft import fft, fftfreq
 import shutil
@@ -29,7 +29,7 @@ def process_chunk(filename):
     print(f"🔍 Verarbeite {input_path}...")
 
     # Frequenzanalyse und Event-Erkennung
-    data, samplerate = sf.read(input_path)
+    data, samplerate = soundfile.read(input_path)
     if data.ndim > 1:
         data = data[:, 0]  # nur Kanal 1
 
@@ -43,6 +43,7 @@ def process_chunk(filename):
 
     i = 0
     last_event = -skip_samples
+
     while i + chunk_samples <= len(data):
         clip = data[i:i+chunk_samples]
 
@@ -53,7 +54,7 @@ def process_chunk(filename):
             return False
         base_energy = np.mean(Sxx[idx_base])
         oct_energy = np.mean(Sxx[idx_oct])
-        total_energy = np.mean(Sxx, axis=0).max()
+        total_energy = np.mean(Sxx[freqs <= 1000, :], axis=0).max()
 
         fft_vals = np.abs(fft(clip))
         freqs = fftfreq(len(clip), 1/samplerate)
@@ -73,7 +74,7 @@ def process_chunk(filename):
 
             flac_out = os.path.join(EVENT_DIR, f"{event_time}.flac")
             png_out = os.path.join(EVENT_DIR, f"{event_time}.png")
-            sf.write(flac_out, clip, samplerate, format='FLAC')
+            soundfile.write(flac_out, clip, samplerate, format='FLAC')
 
             plt.figure()
             plt.specgram(clip, Fs=samplerate, NFFT=NFFT, noverlap=NFFT//2, cmap='inferno', vmin=-90, vmax=-20)
@@ -84,7 +85,7 @@ def process_chunk(filename):
             plt.savefig(png_out)
             plt.close()
 
-            print(f"Event: {event_time} peak_freq: {peak_freq:.9f} Hz, base_energy: {base_energy:.9f}, oct_energy: {oct_energy:.9f}, total_energy: {total_energy:.9f}")
+            print(f"Event: {event_time} peak_freq: {peak_freq:.9f} Hz, base_energy: {base_energy/total_energy:.9f}, oct_energy: {oct_energy/total_energy:.9f}, total_energy: {total_energy:.9f}")
             last_event = i
             i += skip_samples
         else: