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我是 Python 新手，所以如果我需要澄清任何事情，请告诉我。我正在尝试获取过滤后的 wav 文件的 rms 值。我可以在 pyaudio 流中使用 USB 麦克风录制 wav 文件，并将数据存储在块中，获取该块的 rms 值并将其存储在一个数组中，然后在遍历所有样本后，它只需要该数组的最大 rms 值（全部在函数 mic0() 下完成）。我以可以应用于过滤信号的不同格式重复此过程（因为我正在读取 wav 文件而不是流）并获得相同的结果。

我想获取记录的 wav 文件，对其进行过滤，然后再次获取 rms 值。但是在我使用了 butter_bandpass_filter 函数之后，每当我尝试计算 rms 值时，我总是得到 18000 左右。在将数据存储到函数中之前，我对其进行了标准化，使其与原始信号匹配（我大胆地检查了它）但这并不影响最终结果，因为我尝试删除它（y / max_int16），它仍然给我 18000。我也尝试弄乱数据类型，但我尝试的几乎所有东西都不起作用或导致过滤后的信号显示为 0。

这是代码：

import pyaudio
import wave
import audioop
import numpy as np
import datetime
import threading
import time
import os
from scipy.signal import butter, lfilter
from scipy.io.wavfile import write, read


os.chdir('/home/pi/Desktop/test') #mounting process
form_1 = pyaudio.paInt16 # 16-bit resolution
chans = 1 # 1 channel
samp_rate = 48000 # 48 kHz sampling rate
lowcut = 200
highcut = 20000
chunk = 1024 # samples for buffer
record_secs = 5 # seconds to record
dev_index0 = 2 # device index found by p.get_device_info_by_index(ii)
dev_index1 = 3

audio = pyaudio.PyAudio() # create pyaudio instantiation
print("Start")

# create pyaudio stream
stream0 = audio.open(format = form_1,rate = samp_rate,channels = chans, \
                    input_device_index = dev_index0,input = True, \
                    frames_per_buffer=chunk)
print("recording mic 1")

stream1 = audio.open(format = form_1,rate = samp_rate,channels = chans, \
                    input_device_index = dev_index1,input = True, \
                    frames_per_buffer=chunk)
print("recording mic 2")


def butter_bandpass(lowcut, highcut, samp_rate, order=5):
    nyq = 0.5 * samp_rate
    low = lowcut / nyq
    high = highcut / nyq
    b, a = butter(order, [low, high], btype='band', analog=False)
    return b, a

def butter_bandpass_filter(data, lowcut, highcut, samp_rate, order=5):
    b, a = butter_bandpass(lowcut, highcut, samp_rate, order=order)
    y = lfilter(b, a, data)
    return y

def mic0():
    global frames0, rms0, max0
    rms0 = []
    frames0 = []
    # loop through stream and append audio chunks to frame array
    for ii in range(0,int((samp_rate/chunk)*record_secs)):
        data0 = stream0.read(chunk, exception_on_overflow=False)
        frames0.append(data0)
        rms0.append(audioop.rms(data0, 2))
        max0 = np.max(rms0)
    print(max0)
      
def mic1():
    global frames1
    frames1 = []
    # loop through stream and append audio chunks to frame array
    for ii in range(0,int((samp_rate/chunk)*record_secs)):
        data1 = stream1.read(chunk, exception_on_overflow=False)
        frames1.append(data1)
       


# start threading
t1 = threading.Thread(target=mic0)
t2 = threading.Thread(target=mic1)
t1.start()
t2.start()
t1.join()
t2.join()

     
dt = str(datetime.datetime.now())
wav_output_filename = 'mic1.wav' # name of .wav file
wavefile = wave.open(wav_output_filename,'wb')
wavefile.setnchannels(chans)
wavefile.setsampwidth(audio.get_sample_size(form_1))
wavefile.setframerate(samp_rate)
wavefile.writeframes(b''.join(frames0))
wavefile.close()

    
dt = str(datetime.datetime.now())
wav_output_filename = 'mic2.wav' # name of .wav file
wavefile = wave.open(wav_output_filename,'wb')
wavefile.setnchannels(chans)
wavefile.setsampwidth(audio.get_sample_size(form_1))
wavefile.setframerate(samp_rate)
wavefile.writeframes(b''.join(frames1))
wavefile.close()


# stop the stream, close it, and terminate the pyaudio instantiation
stream0.stop_stream()
stream0.close()
stream1.stop_stream()
stream1.close
audio.terminate()
print("end")

# check method, compare to max0
samplerate, data = read('mic1.wav')
rms = []
for i in range(0, 240000, 1024):
    j = i + 1024
    sub = data[i:j]
    rms.append(audioop.rms(sub, 2))
    max_rms = np.max(rms)
## max rms of unfiltered signal
print(max_rms)

##filtering
max_int16 = 2**15
y = butter_bandpass_filter(data, lowcut, highcut, samplerate, order=5)
write('mic1_filtered.wav', samplerate, y / max_int16)
      
samplerate, data_filtered = read('mic1_filtered.wav')
data_filtered = data_filtered * max_int16
rms_filtered = []
for i in range(0, 240000, 1024):
    j = i + 1024
    sub = data_filtered[i:j]
    rms_filtered.append(audioop.rms(sub, 2))
    max_filtered = np.max(rms_filtered)
## max rms of filtered signal
print(max_filtered)
4

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