From 743e94d293053635c3c1694eb004cdd4a3858ca7 Mon Sep 17 00:00:00 2001
From: polyfloyd <floyd@polyfloyd.net>
Date: Tue, 10 Oct 2017 23:55:40 +0200
Subject: [PATCH] Perform some tweaking on the PCM visualizer

---
 nyan/nyancat.py | 12 ++++++------
 nyan/pcm.py     | 31 +++++++++++++++++++++----------
 2 files changed, 27 insertions(+), 16 deletions(-)

diff --git a/nyan/nyancat.py b/nyan/nyancat.py
index 8898be9..4a61c4d 100644
--- a/nyan/nyancat.py
+++ b/nyan/nyancat.py
@@ -4,14 +4,14 @@ import sys
 import time
 from PIL import Image # Requires the Pillow library
 
-background_color = (0x0f, 0x4d, 0x8f)
+background_color = (0x07, 0x26, 0x47)
 tail_colors = [
     (0xff, 0x00, 0x00),
     (0xff, 0x99, 0x00),
     (0xff, 0xff, 0x00),
     (0x00, 0xff, 0x00),
-    (0x00, 0x99, 0xff),
-    (0x66, 0x33, 0xff),
+    (0x00, 0x88, 0xcc),
+    (0xaa, 0x00, 0xaa),
 ]
 
 anim_cat = []
@@ -40,8 +40,8 @@ class Nyancat(object):
         self.sparkles = []
 
     def render(self):
-        self.frame_index = (self.frame_index + 1) % len(anim_cat)
-        anim_frame = anim_cat[self.frame_index]
+        self.frame_index = (self.frame_index + 1) % (len(anim_cat) * 2)
+        anim_frame = anim_cat[self.frame_index // 2]
 
         if len(self.sparkles) < 32:
             self.sparkles.append(Sparkle(self.width, self.height))
@@ -52,7 +52,7 @@ class Nyancat(object):
             frame[i*3:i*3+3] = background_color
 
         # Render the tail
-        for (x, tail_y) in enumerate(self.plot_tail(self.width - 10)):
+        for (x, tail_y) in enumerate(self.plot_tail(self.width - 24)):
             for (y, color) in enumerate(tail_colors, tail_y - len(tail_colors) // 2):
                 if 0 <= y < self.height:
                     i = y * self.width + x
diff --git a/nyan/pcm.py b/nyan/pcm.py
index d58e01f..291bfff 100644
--- a/nyan/pcm.py
+++ b/nyan/pcm.py
@@ -1,36 +1,47 @@
 #!/usr/bin/env python3
 
+import math
+import sys
 from nyancat import Nyancat
 
 INTERVAL = 1 / 20
-WAVE_FACTOR = 3
+FACTOR = 3
+AMPLIFICATION = 3
+HISTORY_SIZE = 4
 
 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
+        self.samples_history = [[0] * int(INTERVAL * signal.sample_rate * FACTOR)] * HISTORY_SIZE
 
     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])
+        # Find a part in the new sample window that resembles the previous one,
+        # this makes the wave seem stand still.
+        for i in range(min(len(samples), len(self.samples_history[-1])) - width * FACTOR):
+            z = zip(self.samples_history[-1][0:width], samples[i:i + width * 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])
+        assert samples_offset + width * FACTOR < len(samples), 'w=%d < len=%d' % (samples_offset + width * FACTOR, len(samples))
+
+        selected_window = samples[samples_offset:samples_offset + width * FACTOR]
+        # Make sure the mean of the selected window is equal to 0, this
+        # lowers vertical stuttering.
+        win_avg = sum(selected_window) / len(selected_window)
+        stabilized_window = [sample + win_avg for sample in selected_window]
+        # Append to the history.
+        self.samples_history.append(stabilized_window)
         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
+            amplitude = sum([samples[x * FACTOR] for samples in self.samples_history]) / len(self.samples_history) * AMPLIFICATION
+            yield int((amplitude * .5 + .5) * self.height)
 
     def sleep(self):
         pass # Handled by a blocking read from the audio source