pythonとmatplotlibを使ったバイオリンチューナー

Question

私はバイオリンチューナー/リアルタイムスペクトラムディスプレイとして動作するpythonスクリプトを書こうとしています。今のところ私はマイクロホンからのデータのブロックを記録するためにパイオディオを得て、短時間の一連のオーディオの周波数スペクトルを計算することができます。私はmatplotlibを使ってそれらをリアルタイムでプロットしたいと思いますが、データが記録されている間に私のFigureウィンドウは空白で、最後のプロットだけが画面上で更新されます。私は間違って何をしていますか？

# -*- coding: utf-8 -*- 
""" 
Created on Mon May 1 00:03:55 2017 

@author: Hugo. 
""" 

import pyaudio 
import struct 
import numpy as np 
import matplotlib.pyplot as plt 
from time import sleep 


CHUNK = 2**14 #2**15 #4096 
WIDTH = 2 
FORMAT = pyaudio.paInt16 
CHANNELS = 2 
RATE = 44100 
dt = 1.0/RATE 


### frequencies of the strings for the violin (tunned in A), in Hz 
f4 = 195.998 ## G3 
f3 = 293.665 ## D4 
f2 = 440.000 ## A4 
f1 = 659.255 ## E5 

n = CHUNK 
freqs = np.fft.rfftfreq(n, d = dt) 

def Frequency_of_position(position): 
    """ Returns the frequency (Hz) of the note in from its position (halftones) 
    relative to A4 in an equal tempered scale. Ex: 0 -> 440 Hz (A4), 
    12 -> 880 Hz (A5).""" 
    return 440.0*(2**(1.0/12.0))**position 


def Position_to_note(position): 
    "A A# B C C# D D# E F F# G G#" 
    SCALE = ["A", "A#", "B", "C", "C#", "D", "D#", "E", "F", "F#", "G", "G#"] 
    LETTER = SCALE[position % 12] 
    NUMBER = str(int((position+48)/12)) 
    return LETTER+NUMBER 

pos = np.array(range(-36,48)) 
vnote_freqs = np.vectorize(Frequency_of_position) 
note_freqs = vnote_freqs(pos) 


def get_frequency(spectrum): 
    return freqs[np.argmax(spectrum)] 



class Freq_analysis(object): 
    def __init__(self): 
     self.pa = pyaudio.PyAudio() 
     self.stream = self.open_mic_stream() 
     self.plots = self.prepare_figure() 
     #self.fig_and_axes = self.prepare_figure() 
     #self.first_plot = self.plot_first_figure() 


    def stop(self): 
     self.stream.close() 

    def open_mic_stream(self): 
     device_index = self.find_input_device() 

     stream = self.pa.open( format = FORMAT, 
           channels = CHANNELS, 
           rate = RATE, 
           input = True, 
           input_device_index = device_index, 
           frames_per_buffer = CHUNK) 

     return stream 

    def find_input_device(self): 
     device_index = None    
     for i in range(self.pa.get_device_count()):  
      devinfo = self.pa.get_device_info_by_index(i) 
      print("Device %d: %s"%(i,devinfo["name"])) 

      for keyword in ["mic","input"]: 
       if keyword in devinfo["name"].lower(): 
        print("Found an input: device %d - %s"% (i,devinfo["name"])) 
        device_index = i 
        return device_index 

     if device_index == None: 
      print("No preferred input found; using default input device.") 

     return device_index 

    def prepare_figure(self): 
     fig1 = plt.figure(1, figsize = (16,6)) 
     wide_plot = plt.subplot(2,1,1) 
     plt.vlines([f1,f2,f3,f4],1,1e17, linestyles = 'dashed') 
     plt.xlabel("freq (Hz)") 
     plt.ylabel("S^2 (u. arb.)") 
     plt.xscale('log') 
     plt.yscale('log') 
     plt.xlim([80,4000]) 
     #plt.xlim([600,700]) 
     #plt.xlim([400,500]) 
     plt.ylim([1e0,1e17]) 
     spec_w, = plt.plot([1,1],[1,1], '-',c = 'blue') 

     f4_plot = plt.subplot(2,4,5) 
     plt.vlines(f4,1,1e17, linestyles = 'dashed') 
     plt.xlabel("freq (Hz)") 
     plt.ylabel("S^2 (u. arb.)") 
     plt.yscale('log') 
     plt.xlim([140,260]) 
     plt.ylim([1e0,1e17]) 
     spec_f4, = plt.plot([1,1],[1,1], '-',c = 'blue') 

     f3_plot = plt.subplot(2,4,6) 
     plt.vlines(f3,1,1e17, linestyles = 'dashed') 
     plt.xlabel("freq (Hz)") 
     plt.yscale('log') 
     plt.xlim([220,380]) 
     plt.ylim([1e0,1e17]) 
     spec_f3, = plt.plot([1,1],[1,1], '-',c = 'blue') 

     f2_plot = plt.subplot(2,4,7) 
     plt.vlines(f2,1,1e17, linestyles = 'dashed') 
     plt.xlabel("freq (Hz)") 
     plt.yscale('log') 
     plt.xlim([400,500]) 
     plt.ylim([1e0,1e17]) 
     spec_f2, = plt.plot([1,1],[1,1], '-',c = 'blue') 

     f1_plot = plt.subplot(2,4,8) 
     plt.vlines(f1,1,1e17, linestyles = 'dashed') 
     plt.xlabel("freq (Hz)") 
     plt.yscale('log') 
     plt.xlim([600,700]) 
     plt.ylim([1e0,1e17]) 
     spec_f1, = plt.plot([1,1],[1,1], '-',c = 'blue') 

     plt.show() 

    #return fig1, wide_plot, f1_plot, f2_plot, f3_plot, f4_plot 
     return spec_w, spec_f1, spec_f2, spec_f3, spec_f4 


    def PrintFreq(self, S2): 
     dominant = get_frequency(S2) 
     dist = np.abs(note_freqs-dominant) 
     closest_pos = pos[np.argmin(dist)] 
     closest_note = Position_to_note(closest_pos) 
     print(dominant, "(",closest_note, "=",Frequency_of_position(closest_pos),")") 

    def listen(self): 
     try: 
      block = self.stream.read(CHUNK) 
     except IOError: 
      # An error occurred. 
      print("Error recording.") 
      return 
     indata = np.array(struct.unpack("%dh"%(len(block)/2),block)) 
     n = indata.size 
     freqs = np.fft.rfftfreq(n, d = dt) 
     data_rfft = np.fft.rfft(indata) 
     S2 = np.abs(data_rfft)**2 
     #self.PrintFreq(block) 
     #self.update_fig(block) 
     self.PrintFreq(S2) 
     self.update_fig(freqs, S2) 

    def update_fig(self, freqs, S2): 
     self.plots[0].set_xdata(freqs) 
     self.plots[1].set_xdata(freqs) 
     self.plots[2].set_xdata(freqs) 
     self.plots[3].set_xdata(freqs) 
     self.plots[4].set_xdata(freqs) 

     self.plots[0].set_ydata(S2) 
     self.plots[1].set_ydata(S2) 
     self.plots[2].set_ydata(S2) 
     self.plots[3].set_ydata(S2) 
     self.plots[4].set_ydata(S2) 

    #plt.draw() 
    #plt.show() 

if __name__ == "__main__": 
    Tuner = Freq_analysis() 

    for i in range(1000): 
     Tuner.listen() 
     plt.show() 

Answer 1

私はコードを実行できないので、私は推測することができません。しかし、それはあなたが実際にキャンバスを描くことは決してないようです。 update_fig関数の最後に

self.plots[0].figure.canvas.draw_idle() 

を追加

してみてください。

これは機能しない場合があります。したがって、対話モードを試してみることもできます。 plt.ion()を回してupdate_fig関数の最後で

plt.draw() 
plt.pause(0.0001) 

を追加します。最後にplt.ioff()に電話し、plt.show()に電話をかけて図を開いたままにしてください。

次のコードは、私のために正常に動作：

import pyaudio 
import struct 
import numpy as np 
import matplotlib.pyplot as plt 
from time import sleep 


CHUNK = 2**14 #2**15 #4096 
WIDTH = 2 
FORMAT = pyaudio.paInt16 
CHANNELS = 2 
RATE = 44100 
dt = 1.0/RATE 


### frequencies of the strings for the violin (tunned in A), in Hz 
f4 = 195.998 ## G3 
f3 = 293.665 ## D4 
f2 = 440.000 ## A4 
f1 = 659.255 ## E5 

n = CHUNK 
freqs = np.fft.rfftfreq(n, d = dt) 

def Frequency_of_position(position): 
    """ Returns the frequency (Hz) of the note in from its position (halftones) 
    relative to A4 in an equal tempered scale. Ex: 0 -> 440 Hz (A4), 
    12 -> 880 Hz (A5).""" 
    return 440.0*(2**(1.0/12.0))**position 


def Position_to_note(position): 
    "A A# B C C# D D# E F F# G G#" 
    SCALE = ["A", "A#", "B", "C", "C#", "D", "D#", "E", "F", "F#", "G", "G#"] 
    LETTER = SCALE[position % 12] 
    NUMBER = str(int((position+57)/12)) 
    return LETTER+NUMBER 

pos = np.array(range(-36,48)) 
vnote_freqs = np.vectorize(Frequency_of_position) 
note_freqs = vnote_freqs(pos) 


def get_frequency(spectrum): 
    return freqs[np.argmax(spectrum)] 



class Freq_analysis(object): 
    def __init__(self): 
     self.pa = pyaudio.PyAudio() 
     self.stream = self.open_mic_stream() 
     self.plots = self.prepare_figure() 
     #self.fig_and_axes = self.prepare_figure() 
     #self.first_plot = self.plot_first_figure() 


    def stop(self): 
     self.stream.close() 

    def open_mic_stream(self): 
     device_index = self.find_input_device() 

     stream = self.pa.open( format = FORMAT, 
           channels = CHANNELS, 
           rate = RATE, 
           input = True, 
           input_device_index = device_index, 
           frames_per_buffer = CHUNK) 

     return stream 

    def find_input_device(self): 
     device_index = None    
     for i in range(self.pa.get_device_count()):  
      devinfo = self.pa.get_device_info_by_index(i) 
      print("Device %d: %s"%(i,devinfo["name"])) 

      for keyword in ["mic","input"]: 
       if keyword in devinfo["name"].lower(): 
        print("Found an input: device %d - %s"% (i,devinfo["name"])) 
        device_index = i 
        return device_index 

     if device_index == None: 
      print("No preferred input found; using default input device.") 

     return device_index 

    def prepare_figure(self): 
     plt.ion() 
     fig1 = plt.figure(1, figsize = (16,6)) 
     wide_plot = plt.subplot(2,1,1) 
     plt.vlines([f1,f2,f3,f4],1,1e17, linestyles = 'dashed') 
     plt.xlabel("freq (Hz)") 
     plt.ylabel("S^2 (u. arb.)") 
     plt.xscale('log') 
     plt.yscale('log') 
     plt.xlim([80,4000]) 
     #plt.xlim([600,700]) 
     #plt.xlim([400,500]) 
     plt.ylim([1e0,1e17]) 
     spec_w, = plt.plot([1,1],[1,1], '-',c = 'blue') 

     f4_plot = plt.subplot(2,4,5) 
     plt.vlines(f4,1,1e17, linestyles = 'dashed') 
     plt.xlabel("freq (Hz)") 
     plt.ylabel("S^2 (u. arb.)") 
     plt.yscale('log') 
     plt.xlim([140,260]) 
     plt.ylim([1e0,1e17]) 
     spec_f4, = plt.plot([1,1],[1,1], '-',c = 'blue') 

     f3_plot = plt.subplot(2,4,6) 
     plt.vlines(f3,1,1e17, linestyles = 'dashed') 
     plt.xlabel("freq (Hz)") 
     plt.yscale('log') 
     plt.xlim([220,380]) 
     plt.ylim([1e0,1e17]) 
     spec_f3, = plt.plot([1,1],[1,1], '-',c = 'blue') 

     f2_plot = plt.subplot(2,4,7) 
     plt.vlines(f2,1,1e17, linestyles = 'dashed') 
     plt.xlabel("freq (Hz)") 
     plt.yscale('log') 
     plt.xlim([400,500]) 
     plt.ylim([1e0,1e17]) 
     spec_f2, = plt.plot([1,1],[1,1], '-',c = 'blue') 

     f1_plot = plt.subplot(2,4,8) 
     plt.vlines(f1,1,1e17, linestyles = 'dashed') 
     plt.xlabel("freq (Hz)") 
     plt.yscale('log') 
     plt.xlim([600,700]) 
     plt.ylim([1e0,1e17]) 
     spec_f1, = plt.plot([1,1],[1,1], '-',c = 'blue') 

     plt.draw() 

    #return fig1, wide_plot, f1_plot, f2_plot, f3_plot, f4_plot 
     return spec_w, spec_f1, spec_f2, spec_f3, spec_f4 


    def PrintFreq(self, S2): 
     dominant = get_frequency(S2) 
     dist = np.abs(note_freqs-dominant) 
     closest_pos = pos[np.argmin(dist)] 
     closest_note = Position_to_note(closest_pos) 
     print(dominant, "(",closest_note, "=",Frequency_of_position(closest_pos),")") 

    def listen(self): 
     try: 
      block = self.stream.read(CHUNK) 
     except IOError: 
      # An error occurred. 
      print("Error recording.") 
      return 
     indata = np.array(struct.unpack("%dh"%(len(block)/2),block)) 
     n = indata.size 
     freqs = np.fft.rfftfreq(n, d = dt) 
     data_rfft = np.fft.rfft(indata) 
     S2 = np.abs(data_rfft)**2 
     #self.PrintFreq(block) 
     #self.update_fig(block) 
     self.PrintFreq(S2) 
     self.update_fig(freqs, S2) 

    def update_fig(self, freqs, S2): 
     self.plots[0].set_xdata(freqs) 
     self.plots[1].set_xdata(freqs) 
     self.plots[2].set_xdata(freqs) 
     self.plots[3].set_xdata(freqs) 
     self.plots[4].set_xdata(freqs) 

     self.plots[0].set_ydata(S2) 
     self.plots[1].set_ydata(S2) 
     self.plots[2].set_ydata(S2) 
     self.plots[3].set_ydata(S2) 
     self.plots[4].set_ydata(S2) 
     plt.draw() 
     plt.pause(0.001) 


if __name__ == "__main__": 
    Tuner = Freq_analysis() 

    for i in range(100): 
     Tuner.listen() 
    plt.ioff() 
    plt.show() 

Answer 2

私はプロット更新の間にいくつかのスリープ時間を追加する必要があると思います。あなたはsleepをインポートしたので、おそらくあなたはそうしています。

from time import sleep 

... 

for i in range(1000): 
    sleep(10) 
    Tuner.listen() 
    plt.show() 

しかし、より良い練習がofficial exampleをチェックアウトし、matplotlib.animationモジュールを使用することでしょう！