add functionality to restrict range and determine max 8 frequencies within that range

2 files changed, 25 insertions, 14 deletions

diff --git a/Sender.py b/Sender.py
index ca0183e..2a125e9 100644
--- a/Sender.py
+++ b/Sender.py
@@ -12,11 +12,9 @@ Play a single frequency.
 :param samplingRate: Sampling rate in Hz.
 """
 def play_frequency(freq, amplitude, duration=1.0, samplingRate=44100, p=None):
-
     # Generate sample for the given frequency as a float32 array
     samples = (amplitude * np.sin(2*np.pi*np.arange(samplingRate*duration)*freq/samplingRate)).astype(np.float32).tobytes()
 
-
     # Open stream
     stream = p.open(format=pyaudio.paFloat32,
                     channels=1,
@@ -29,7 +27,7 @@ def play_frequency(freq, amplitude, duration=1.0, samplingRate=44100, p=None):
     stream.stop_stream()
     stream.close()
 
-    # p.terminate()
+    p.terminate()
 
 
 # def play_frequency(freq, amplitude, duration=1.0, samplingRate=44100):
@@ -69,6 +67,7 @@ Use threads to play multiple frequencies simultaneously.
 """
 def play_frequencies_separately(freq_map, duration=1.0, samplingRate=44100):
     p = pyaudio.PyAudio()
+
     threads = []
     for freq, amplitude in freq_map.items():
         thread = threading.Thread(target=play_frequency, args=(freq, amplitude, duration, samplingRate, p))
diff --git a/visualize.py b/visualize.py
index d1b2a08..7a86373 100644
--- a/visualize.py
+++ b/visualize.py
@@ -43,13 +43,27 @@ class Test(object):
         scaled_spectrum = np.abs(spectrum)
         scaled_spectrum = scaled_spectrum / (np.linalg.norm(scaled_spectrum) + 1e-16)
 
-        # get the index of the max
-        np_max = max(scaled_spectrum)
-        max_index = np.where(scaled_spectrum == np_max)[0][0]
-
-        # the index corresponds to the following linspace
-        index_to_freq = np.linspace(0, self.RATE, self.CHUNK)
-        return index_to_freq[max_index], scaled_spectrum
+        # FIXME: update to self values, given if ur a sender or receiver
+        starting_freq = 18000
+        end_freq = 20000
+        freq_to_index_ratio = (self.CHUNK - 1) / self.RATE
+        # only accept the scaled spectrum from our starting range to 20000 Hz
+        starting_range_index = int(starting_freq * freq_to_index_ratio)
+        ending_range_index = int(end_freq * freq_to_index_ratio)
+        print(starting_freq, end_freq, starting_range_index, ending_range_index)
+        restricted_spectrum = scaled_spectrum[starting_range_index:ending_range_index + 1]
+
+        # get the n indices of the max peaks, within our confined spectrum
+        # FIXME: update to self values
+        bytes = 1
+        num_bits = bytes * 8 + 2
+        top8_indices = np.argpartition(restricted_spectrum, -num_bits)[-num_bits:]
+
+        # map the top 8 to indices to frequencies
+        top8_freqs = [int((top8_indices[i] + starting_freq) / freq_to_index_ratio) for i in range(len(top8_indices))]
+
+        # print(index_to_freq[max_index], max_index, max_index * self.RATE / (self.CHUNK - 1))
+        return top8_freqs[0], scaled_spectrum
 
     def read_audio_stream(self):
         data = self.stream.read(self.CHUNK)
@@ -61,10 +75,8 @@ class Test(object):
         while not self.pause:
             waveform = self.read_audio_stream()
             freq_max, scaled_spectrum = self.get_fundamental_frequency(waveform)
-            if 250 < freq_max < 550:
-                if freq_max not in self.seenvalues:
-                    print(freq_max)
-                self.seenvalues.add(freq_max)
+            if freq_max not in self.seenvalues:
+                print(freq_max)
 
             # update figure canvas if wanted
             if graphics: