语音识别（一）：绘制图像

1、读取和绘制音频数据
波形文件：wav，时间函数

# -*- coding: utf-8 -*-
import os
import sys
import platform
import numpy as np 
import scipy.io.wavfile as wf 
import matplotlib.pyplot as mp 

def show_signal(sigs,sample_rate):
  print(sigs.shape)
  print(sample_rate/1000,'KHz')
  print(len(sigs)*1000/sample_rate,'ms')

def read_signals(filename):
  sample_rate,sigs = wf.read(filename)
  show_signal(sigs,sample_rate)
  sigs = sigs[:30]/2**15
  #存储的音频文件已经经过归一化处理了，所以得线性还原回去
  times = np.arange(30)/sample_rate
  return sigs,sample_rate,times

def init_chart():
  mp.gcf().set_facecolor(np.ones(3)*240/255)
  mp.title('Audio Signal',fontsize=20)
  mp.xlabel('Time(ms)',fontsize=14)
  mp.ylabel('Signal',fontsize=14)
  mp.tick_params(which='both',top=True,right=True,labelright=True,labelsize=10)
  mp.grid(linestyle=':')

def draw_chart(times,sigs):
  times *= 1000
  mp.plot(times,sigs,c='dodgerblue',label='Signal',zorder=0)
  mp.scatter(times,sigs,edgecolor='orangered',facecolor='white',s=80,label='Sample',zorder=1)
  mp.legend()

def show_chart():
  mng = mp.get_current_fig_manager()
  if 'Windows' in platform.system():
    mng.window.state('zoomed')
  else:
    mng.resize(*mng.window.maxsize())
  mp.show()

def main(argc,argv,envp):
  sigs,sample_rate,times = read_signals('/Users/youkechaung/Desktop/算法/数据分析/AI/day02/day02/data/signal.wav')
  init_chart()
  draw_chart(times,sigs)
  show_chart()
  return 0

if __name__ == '__main__':
  sys.exit(main(len(sys.argv),sys.argv,os.environ))