wip

process

@@ -6,14 +6,19 @@ import numpy as np
 import matplotlib.pyplot as plt
 import soundfile
 import scipy.signal
-from scipy.fft import fft, fftfreq
+from scipy.fft import rfft, rfftfreq
 import shutil
 
 RECORDINGS_DIR = "recordings"
 PROCESSED_RECORDINGS_DIR = "recordings/processed"
 DETECTIONS_DIR = "events"
-DETECT_FREQUENCY_FROM = 208
-DETECT_FREQUENCY_TO = 214
+
+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
@@ -21,31 +26,50 @@ CLIP_PADDING_BEFORE = 1
 CLIP_PADDING_AFTER = 6
 
 
-def process_chunk(filename):
+def process_recording(filename):
     print('processing', filename)
+
+    # get ISO 8601 nanosecond recording date from filename
+    date_string_from_filename = os.path.splitext(filename)[0]
+    recording_date = datetime.datetime.strptime(date_string_from_filename, "%Y-%m-%d_%H-%M-%S.%f%z")
+
+    # get samplerate and blocksize
     path = os.path.join(RECORDINGS_DIR, filename)
     info = soundfile.info(path)
     samplerate = info.samplerate
     blocksize = int(CLIP_SECONDS * samplerate)
 
-    print(info)
-
+    # iterate blocks
     for num, block in enumerate(soundfile.blocks(path, blocksize=blocksize, overlap=int(blocksize*0.8))):
-        strengths = fft(block)
-        labels = fftfreq(len(block), d=1/samplerate)
-        # get the frequency with the highest strength
-        max_freq = labels[np.argmax(np.abs(strengths))]
+        complex_amplitudes = rfft(block)
+        amplitudes = np.abs(complex_amplitudes)
+        labels = rfftfreq(len(block), d=1/samplerate)
+
+        # get amplitudes only between 100 and 1000 Hz
+        adjacent_amplitudes = amplitudes[(labels >= DETECT_FREQUENCY_FROM/ADJACENCY_FACTOR) & (labels <= DETECT_FREQUENCY_TO*ADJACENCY_FACTOR)]
+        adjacent_labels = labels[(labels >= DETECT_FREQUENCY_FROM/ADJACENCY_FACTOR) & (labels <= DETECT_FREQUENCY_TO*ADJACENCY_FACTOR)]
+
+        # get the frequency with the highest amplitude
+        max_amplitude = max(adjacent_amplitudes)
+        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'{num}: {max_freq:.1f}')
+            print(f'{recording_date + datetime.timedelta(seconds=num * CLIP_SECONDS)}: {max_amplitude:.2f}rDB @ {max_freq:.2f}Hz')
+            breakpoint()
+
+
+
+
 
 
 def main():
     os.makedirs(RECORDINGS_DIR, exist_ok=True)
     os.makedirs(PROCESSED_RECORDINGS_DIR, exist_ok=True)
 
-    for file in os.listdir(RECORDINGS_DIR):
-        if file.endswith(".flac"):
-            process_chunk(file)
+    for filename in os.listdir(RECORDINGS_DIR):
+        if filename.endswith(".flac"):
+            process_recording(filename)
 
 
 if __name__ == "__main__":

record

@@ -5,20 +5,10 @@ mkdir -p recordings
 while true
 do
     # get date in ISO 8601 format with nanoseconds
-
-    OS=$(uname)
-
-    if [ "$OS" = "Darwin" ]; then
-        DATE=$(gdate --iso-8601=ns)
-    elif [ "$OS" = "Linux" ]; then
-        DATE=$(date --iso-8601=ns)
-    else
-        echo "Unsupported OS: $OS"
-        exit 2
-    fi
+    PROGRAMM=$(test $(uname) = "Darwin" && echo "gdate" || echo "date")
+    DATE=$($PROGRAMM "+%Y-%m-%d_%H-%M-%S.%6N%z")
 
     # record audio using ffmpeg
-
     ffmpeg \
         -y \
         -f pulse \