wip

process

@@ -13,17 +13,12 @@ RECORDINGS_DIR = "recordings"
 PROCESSED_RECORDINGS_DIR = "recordings/processed"
 DETECTIONS_DIR = "events"
 
-DETECT_FREQUENCY = 211
-DETECT_FREQUENCY_TOLERANCE = 2
-DETECT_FREQUENCY_FROM = DETECT_FREQUENCY - DETECT_FREQUENCY_TOLERANCE
-DETECT_FREQUENCY_TO = DETECT_FREQUENCY + DETECT_FREQUENCY_TOLERANCE
-ADJACENCY_FACTOR = 2
-
-CLIP_SECONDS = 3
-THRESHOLD_BASE = 0.1
-OCTAVE_FACTOR = 0.1
-CLIP_PADDING_BEFORE = 1
-CLIP_PADDING_AFTER = 6
+DETECT_FREQUENCY = 211 # Hz
+DETECT_FREQUENCY_TOLERANCE = 2 # Hz
+DETECT_FREQUENCY_FROM = DETECT_FREQUENCY - DETECT_FREQUENCY_TOLERANCE # Hz
+DETECT_FREQUENCY_TO = DETECT_FREQUENCY + DETECT_FREQUENCY_TOLERANCE # Hz
+ADJACENCY_FACTOR = 2 # area to look for noise around the target frequency
+AMPLITUDE_THRESHOLD = 200 # rDB
 
 
 def process_recording(filename):
@@ -41,6 +36,7 @@ def process_recording(filename):
 
     # iterate blocks
     for num, block in enumerate(soundfile.blocks(path, blocksize=blocksize, overlap=int(blocksize*0.8))):
+        block_date = recording_date + datetime.timedelta(seconds=num * CLIP_SECONDS)
         complex_amplitudes = rfft(block)
         amplitudes = np.abs(complex_amplitudes)
         labels = rfftfreq(len(block), d=1/samplerate)
@@ -54,10 +50,13 @@ def process_recording(filename):
         max_amplitude_index = np.argmax(adjacent_amplitudes)
         max_freq = adjacent_labels[max_amplitude_index]
 
-        if DETECT_FREQUENCY_FROM <= max_freq <= DETECT_FREQUENCY_TO:
-            print(f'{recording_date + datetime.timedelta(seconds=num * CLIP_SECONDS)}: {max_amplitude:.2f}rDB @ {max_freq:.2f}Hz')
-            breakpoint()
+        # check for detection criteria
+        max_freq_detected = DETECT_FREQUENCY_FROM <= max_freq <= DETECT_FREQUENCY_TO
+        amplitude_detected = max_amplitude > AMPLITUDE_THRESHOLD
 
+        # conclude detection
+        if max_freq_detected and amplitude_detected:
+            print(f'{block_date}: {max_amplitude:.2f}rDB @ {max_freq:.2f}Hz')