port to python3HEADmaster

1 files changed, 7 insertions, 6 deletions

diff --git a/mpdvis.py b/mpdvis.py
index df1f525..34a8f78 100644
--- a/mpdvis.py
+++ b/mpdvis.py
@@ -1,8 +1,9 @@
-#!/usr/bin/env python2
+#!/usr/bin/env python3
 import hyperion
 import array
 import colorsys
 import numpy
+from past.builtins import map
 
 DEBUG_MODE = False
 FIFO = '/tmp/mpd.fifo'
@@ -51,7 +52,7 @@ class SoundToColorProcessor:
         return magnitudes
 
     def getFrequencyIndex(self, freq):
-        return freq/(self.RATE/self.CHUNK)
+        return int(freq/(self.RATE/self.CHUNK))
 
     def convertPercentToColorValue(self, percent):
         return int(round(percent*255))
@@ -77,7 +78,7 @@ class SoundToColorProcessor:
             import matplotlib.pyplot as plt
 
         # open the audio stream on the sound card
-        stream = open(FIFO)
+        stream = open(FIFO, 'rb')
 
         if DEBUG_MODE:
             # Plots and canvas initialization
@@ -98,8 +99,8 @@ class SoundToColorProcessor:
             results = numpy.fft.fft(nums)
             freq_bins = numpy.fft.fftfreq(len(nums), 1.0/self.RATE)
 
-            results = results[0:(len(results)/2 - 1)]
-            freq_bins = 2 * freq_bins[0:(len(freq_bins)/2 - 1)]
+            results = results[0:(len(results)//2 - 1)]
+            freq_bins = 2 * freq_bins[0:(len(freq_bins)//2 - 1)]
 
             mags = self.calculateMagnitude(results.real, results.imag)
 
@@ -116,7 +117,7 @@ class SoundToColorProcessor:
 
             rms = numpy.sqrt(numpy.mean(numpy.square(nums)))
             value = val_iir.update(rms) / self.MAX_LOUDNESS
-            if value > 1.0:
+            if value > 1.0 or numpy.isnan(value):
                 value = 1.0
             averaged_frequency = hue_iir.update(new_frequency)
             hue = self.mapFrequencyToHue(averaged_frequency)