def __init__(self):
# Allocating Data
self.data = collections.deque([0.] * length, maxlen=length)
self.wnd = np.array(window.hamming(length)) # For FFT
# TODO: Maybe break into an object
self.lastWhistleTime = None
self.group = []
self.th = None
self.finishedUpdate = False
# Define the rospy publisher
self.pub = rospy.Publisher("/voice", String, queue_size=10)
# Setting up parameters
# TODO : define rospy.get_param('~..') for these
self.searchFreq = 100 # Hz; minimum time between checking for whistles.
self.minAmp = 0.0001 # Minimum absolute amplitude of a whistle
self.minSharp = 0.0001 # Minimum "sharpness" of a whistle
self.maxSlope = 0.02 # Log hz per second; beyond this it's considered two separate whistles
self.slopeAvgLen = 5 # Number of samples to average the slope
self.minWhistleLen = 0.3 # seconds; below this, whistles are not processed. Expect strange behavior if == 0.
self.maxVariance = 0.5 # Maximum variance in frequency for a whistle
self.tonicResetLen = 2 # Seconds to reset the scale
self.maxGroupSpacing = 3 # Seconds between whistles for a group
def partial():
smix.add(octave_duration, partial_cached()) # Next track/partial event
# Octave-based frequency values sequence
scale = 2 ** line(duration, finish=True)
partial_freq = (scale - 1) * (max_freq - min_freq) + min_freq
# Envelope to "hide" the partial beginning/ending
env = [k ** 2 for k in window.hamming(int(round(duration)))]
# The generator, properly:
for el in env * sinusoid(partial_freq) / noctaves:
data.append(el)
yield el
def partial():
smix.add(octave_duration, partial_cached()) # Next track/partial event
# Octave-based frequency values sequence
scale = 2**line(duration, finish=True)
partial_freq = (scale - 1) * (max_freq - min_freq) + min_freq
# Envelope to "hide" the partial beginning/ending
env = [k**2 for k in window.hamming(int(round(duration)))]
# The generator, properly:
for el in env * sinusoid(partial_freq) / noctaves:
data.append(el)
yield el
from __future__ import division
from audiolazy import sHz, chunks, AudioIO, line, pi, window
from matplotlib import pyplot as plt
from matplotlib.animation import FuncAnimation
from numpy.fft import rfft
import numpy as np
import collections, sys, threading
# AudioLazy init
rate = 44100
s, Hz = sHz(rate)
ms = 1e-3 * s
length = 2**12
data = collections.deque([0.] * length, maxlen=length)
wnd = np.array(window.hamming(length)) # For FFT
api = sys.argv[1] if sys.argv[1:] else None # Choose API via command-line
chunks.size = 1 if api == "jack" else 16
# Creates a data updater callback
def update_data():
with AudioIO(api=api) as rec:
for el in rec.record(rate=rate):
data.append(el)
if update_data.finish:
break
# Creates the data updater thread
from __future__ import division
from audiolazy import sHz, chunks, AudioIO, line, pi, window
from matplotlib import pyplot as plt
from matplotlib.animation import FuncAnimation
from numpy.fft import rfft
import numpy as np
import collections, sys, threading
# AudioLazy init
rate = 44100
s, Hz = sHz(rate)
ms = 1e-3 * s
length = 2 ** 12
data = collections.deque([0.] * length, maxlen=length)
wnd = np.array(window.hamming(length)) # For FFT
api = sys.argv[1] if sys.argv[1:] else None # Choose API via command-line
chunks.size = 1 if api == "jack" else 16
# Creates a data updater callback
def update_data():
with AudioIO(api=api) as rec:
for el in rec.record(rate=rate):
data.append(el)
if update_data.finish:
break
# Creates the data updater thread
update_data.finish = False
th = threading.Thread(target=update_data)
