forked from makermovement/3.5-Sensor2Phone
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FFTwithGraph.py
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FFTwithGraph.py
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# -*- coding: utf-8 -*-
import sys,os,time,xaut
import threading,operator
import atexit
import pyaudio
import numpy as np
import matplotlib.pyplot as plt
from PyQt4 import QtGui, QtCore
from matplotlib.backends.backend_qt4agg import FigureCanvasQTAgg as FigureCanvas
from matplotlib.backends.backend_qt4agg import NavigationToolbar2QT as NavigationToolbar
# class taken from the SciPy 2015 Vispy talk opening example
# see https://github.com/vispy/vispy/pull/928
class MicrophoneRecorder(object):
def __init__(self, rate=44100 , chunksize=320):
self.rate = rate
self.chunksize = chunksize
self.p = pyaudio.PyAudio()
self.stream = self.p.open(format=pyaudio.paInt16,
channels=1,
rate=self.rate,
input=True,
frames_per_buffer=self.chunksize,
stream_callback=self.new_frame)
self.lock = threading.Lock()
self.stop = False
self.frames = []
atexit.register(self.close)
def new_frame(self, data, frame_count, time_info, status):
data = np.fromstring(data, 'int16')
with self.lock:
self.frames.append(data)
if self.stop:
return None, pyaudio.paComplete
return None, pyaudio.paContinue
def get_frames(self):
with self.lock:
frames = self.frames
self.frames = []
return frames
def start(self):
self.stream.start_stream()
def close(self):
with self.lock:
self.stop = True
self.stream.close()
self.p.terminate()
class MplFigure(object):
def __init__(self, parent):
self.figure = plt.figure(facecolor='white')
self.canvas = FigureCanvas(self.figure)
self.toolbar = NavigationToolbar(self.canvas, parent)
class LiveFFTWidget(QtGui.QWidget):
def __init__(self):
QtGui.QWidget.__init__(self)
# customize the UI
self.initUI()
# init class data
self.initData()
# connect slots
self.connectSlots()
# init MPL widget
self.initMplWidget()
def initUI(self):
hbox_gain = QtGui.QHBoxLayout()
autoGain = QtGui.QLabel('Auto gain for frequency spectrum')
autoGainCheckBox = QtGui.QCheckBox(checked=True)
hbox_gain.addWidget(autoGain)
hbox_gain.addWidget(autoGainCheckBox)
# reference to checkbox
self.autoGainCheckBox = autoGainCheckBox
hbox_fixedGain = QtGui.QHBoxLayout()
fixedGain = QtGui.QLabel('Manual gain level for frequency spectrum')
fixedGainSlider = QtGui.QSlider(QtCore.Qt.Horizontal)
hbox_fixedGain.addWidget(fixedGain)
hbox_fixedGain.addWidget(fixedGainSlider)
self.fixedGainSlider = fixedGainSlider
vbox = QtGui.QVBoxLayout()
vbox.addLayout(hbox_gain)
vbox.addLayout(hbox_fixedGain)
# mpl figure
self.main_figure = MplFigure(self)
vbox.addWidget(self.main_figure.toolbar)
vbox.addWidget(self.main_figure.canvas)
self.setLayout(vbox)
self.setGeometry(300, 300, 350, 300)
self.setWindowTitle('LiveFFT')
self.show()
# timer for calls, taken from:
# http://ralsina.me/weblog/posts/BB974.html
timer = QtCore.QTimer()
timer.timeout.connect(self.handleNewData)
timer.start(50)
# keep reference to timer
self.timer = timer
def initData(self):
mic = MicrophoneRecorder()
mic.start()
# keeps reference to mic
self.mic = mic
# computes the parameters that will be used during plotting
self.freq_vect = np.fft.rfftfreq(mic.chunksize,
1./mic.rate)
self.time_vect = np.arange(mic.chunksize, dtype=np.float32) / mic.rate * 1000
def connectSlots(self):
pass
def initMplWidget(self):
"""creates initial matplotlib plots in the main window and keeps
references for further use"""
# top plot
self.ax_top = self.main_figure.figure.add_subplot(211)
self.ax_top.set_ylim(-32768, 32768)
self.ax_top.set_xlim(0, self.time_vect.max())
self.ax_top.set_xlabel(u'time (ms)', fontsize=6)
# bottom plot
self.ax_bottom = self.main_figure.figure.add_subplot(212)
self.ax_bottom.set_ylim(0, 1)
self.ax_bottom.set_xlim(0, self.freq_vect.max())
self.ax_bottom.set_xlabel(u'frequency (Hz)', fontsize=6)
# line objects
self.line_top, = self.ax_top.plot(self.time_vect,
np.ones_like(self.time_vect))
self.line_bottom, = self.ax_bottom.plot(self.freq_vect,
np.ones_like(self.freq_vect))
# tight layout
#plt.tight_layout()
def handleNewData(self):
""" handles the asynchroneously collected sound chunks """
# gets the latest frames
frames = self.mic.get_frames()
mouse = xaut.mouse()
if len(frames) > 0:
# keeps only the last frame
current_frame = frames[-1]
# plots the time signal
self.line_top.set_data(self.time_vect, current_frame)
# computes and plots the fft signal
fft_frame = np.fft.rfft(current_frame) # absolute value of fft_frame will give the amplitude information
# print max(np.abs(fft_frame))
frq = np.fft.rfftfreq(len(fft_frame))
mY = np.abs(fft_frame) # Find magnitude
peakY = np.max(mY) # Fsaind max peak
locY = np.argmax(mY) # Find its location
try:
frqY = frq[locY]*44100#
# mouse.move(frqY/10,300)# maybe we can include another circuit to control y-axis
except:
pass
if self.autoGainCheckBox.checkState() == QtCore.Qt.Checked:
fft_frame /= np.abs(fft_frame).max()
else:
fft_frame *= (1 + self.fixedGainSlider.value()) / 5000000.
#print(np.abs(fft_frame).max())
self.line_bottom.set_data(self.freq_vect, np.abs(fft_frame))
# refreshes the plots
self.main_figure.canvas.draw()
if __name__ == "__main__":
app = QtGui.QApplication(sys.argv)
window = LiveFFTWidget()
sys.exit(app.exec_())