add comments to tuner

code/tuner/main.py

@@ -15,6 +15,7 @@ DEBUG = True
 NOTES = "A B♭/A♯ B C D♭/C♯ D E♭/D♯ E F F♯/G♭ G A♭/G♯".split()
 
 
+# Get the note and octave using known note forumla
 def calculate_note(frequency):
     if frequency > 0:
         note_num = round(math.log2(frequency / 440) * 12)
@@ -25,6 +26,8 @@ def calculate_note(frequency):
     return 0
 
 
+# Attempt to get the dominant frequency by windowing our data sample, and taking an FFT
+# In theory, the highest magnitude frequency of the FFT result should reflect what the human is trying to play in the signal
 def dominant_frequency(data, samplerate):
     windowed_data = data * np.hanning(len(data))
     fft_result = np.fft.rfft(windowed_data)
@@ -44,6 +47,7 @@ def audio_callback(indata: np.ndarray, frames: int, time: Any, status: Any):
         print(f"Status: {status}")
     rms = calculate_rms(indata)
 
+    # Ignore low noise to prevent spammy-ness and keep last audible result shown 
     if rms > QUIET_THRESHOLD:
         mono_data = np.mean(indata, axis=1)
         frequency = dominant_frequency(mono_data, SAMPLE_RATE)
@@ -81,5 +85,3 @@ except KeyboardInterrupt:
 finally:
     print("Stream closed.")
 
-# https://python-sounddevice.readthedocs.io/en/0.5.1/examples.html#plot-microphone-signal-s-in-real-time
-# https://github.com/mzucker/python-tuner/blob/master/tuner.py