Visualsize an audio signal through the tail

nyan/pcm.py

@@ -0,0 +1,33 @@
+#!/usr/bin/env python3
+
+from nyancat import Nyancat
+
+INTERVAL = 1 / 20
+WAVE_FACTOR = 3
+
+class NyancatSignal(Nyancat):
+    def __init__(self, w, h, signal):
+        super().__init__(w, h)
+        self.signal = signal
+        self.samples_history = [[0] * int(INTERVAL * signal.sample_rate * WAVE_FACTOR)] * 6
+
+    def plot_tail(self, width):
+        # Calculate the wave
+        samples = self.signal.get_signal(INTERVAL)
+        samples_offset = 0
+        smallest_diff = float('inf')
+        # Find a part in the new sample window that resembles the previous one.
+        for i in range(min(len(samples), len(self.samples_history[-1])) - width * WAVE_FACTOR):
+            z = zip(self.samples_history[-1][0:width], samples[i:i + width * WAVE_FACTOR])
+            diff = sum(map(lambda t: (t[0] - t[1]) ** 2, z))
+            if diff < smallest_diff:
+                samples_offset = i
+                smallest_diff = diff
+        assert samples_offset + width * WAVE_FACTOR < len(samples), 'w=%d < len=%d' % (samples_offset + width * WAVE_FACTOR, len(samples))
+        self.samples_history.append(samples[samples_offset:samples_offset + width * WAVE_FACTOR])
+        self.samples_history.pop(0)
+
+        # Render the tail
+        for x in range(width):
+            amplitude = sum(map(lambda hist: hist[x * WAVE_FACTOR], self.samples_history)) / len(self.samples_history) * 3
+            yield int((amplitude * .5 - .5) * self.height) + self.height