使用python和matplotlib的小提琴调谐器

Question

我正在尝试你写一个python脚本充当小提琴调谐器/实时光谱显示。 到目前为止，我得到了pyaudio来记录来自麦克风的数据块，并且可以计算短时间系列音频的频谱。 我想使用matplotlib实时绘制这些图，但我的图形窗口是空白的，而数据已被记录，并且在脚本结束后，只有最后一个图在屏幕上更新。 我究竟做错了什么？

# -*- 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

我想你只需要在剧情更新之间增加一些休眠时间。 因为你已经输入了sleep ，所以你可能会这样说。

from time import sleep

...

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

但是，更好的做法是使用matplotlib.animation模块，查看官方示例 ！

Answer 2

由于我无法运行代码，我只能猜测。 但似乎你从来没有真正重绘画布。

尝试添加

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

在update_fig函数的末尾。

这可能会也可能不会奏效。 所以你可能也想尝试交互模式。 转动plt.ion()并添加

plt.draw()
plt.pause(0.0001)

在update_fig函数的末尾。 最后你可以打开plt.ioff()并调用plt.show()来保持图形打开。

以下代码对我来说运行正常：

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()