mailletf

import pyaudio
import librosa
import numpy as np
import requests

# ring buffer will keep the last 2 seconds worth of audio
ringBuffer = RingBuffer(2 * 22050)

def callback(in_data, frame_count, time_info, flag):
    audio_data = np.fromstring(in_data, dtype=np.float32)

mailletf

# Mostly taken from: http://nbviewer.ipython.org/github/bmcfee/librosa/blob/master/examples/LibROSA%20demo.ipynb

import librosa
import matplotlib.pyplot as plt

# Load sound file
y, sr = librosa.load("filename.mp3")

# Let's make and display a mel-scaled power (energy-squared) spectrogram
S = librosa.feature.melspectrogram(y, sr=sr, n_mels=128)

mailletf

import time
from phue import Bridge

# connect to the hue bridge
b = Bridge(bridge_ip)
b.connect()

# Setup colors
colors = {
    "bleu":  [0.1393, 0.0813],