cronekorkn/bootshorn_investigation
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CroneKorkN 2025-06-01 13:31:05 +02:00
parent 666744086d
commit ba83fe23c9
Signed by: cronekorkn
SSH key fingerprint: SHA256:v0410ZKfuO1QHdgKBsdQNF64xmTxOF8osF1LIqwTcVw
1 changed files with 8 additions and 4 deletions
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12
process
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@ -18,8 +18,8 @@ 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
BLOCK_SECONDS = 1 # seconds
AMPLITUDE_THRESHOLD = 200 # relative DB (rDB) (because not calibrated)
BLOCK_SECONDS = 3 # seconds (longer means more frequency resolution, but less time resolution)
def process_recording(filename):
@ -51,13 +51,17 @@ def process_recording(filename):
max_amplitude_index = np.argmax(adjacent_amplitudes)
max_freq = adjacent_labels[max_amplitude_index]
# get the average amplitude of the adjacent frequencies
noise = np.mean(adjacent_amplitudes)/max_amplitude
# check for detection criteria
max_freq_detected = DETECT_FREQUENCY_FROM <= max_freq <= DETECT_FREQUENCY_TO
amplitude_detected = max_amplitude > AMPLITUDE_THRESHOLD
low_noise_detected = noise < 0.1
# conclude detection
if max_freq_detected and amplitude_detected:
print(f'{block_date}: {max_amplitude:.2f}rDB @ {max_freq:.2f}Hz')
if max_freq_detected and amplitude_detected and low_noise_detected:
print(f'{block_date}: {max_amplitude:.1f}rDB @ {max_freq:.1f}Hz ({noise:.3f}rDB noise)')