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使用 RTL_SDR 我正在尝试使用 python 播放频率。我可以通过不解调 FM 信号的简化脚本从扬声器中获取音频。但是，当运行代码以实际清除音频时，需要的字符串作为元组出现，而 pyaudio 需要像对象这样的字节。

显示错误

Traceback (most recent call last):
 File "C:/Users/nated/Desktop/New Program/sdr5.py", line 105, in <module>
   stream.write(data)
 File "C:\Users\nated\AppData\Local\Programs\Python\Python39\lib\site-packages\pyaudio.py", line 585, in write
   pa.write_stream(self._stream, frames, num_frames,
TypeError: a bytes-like object is required, not 'tuple

这是代码

import matplotlib.pyplot as plt
from rtlsdr import RtlSdr
from scipy import signal
from time import sleep
import numpy as np
from scipy.io import wavfile
import pyaudio
import threading
import queue
 
sdr = RtlSdr()
samples = queue.Queue()
sounds = queue.Queue()
 
class readThread (threading.Thread):
   def __init__(self, sdr, samples):
      threading.Thread.__init__(self)
      self.srd = sdr
      self.samples = samples
      self.stopit = False
   def run(self):
        print ("Starting read")
        while not self.stopit:
            self.samples.put(sdr.read_samples(8192000/4))
 
class processThread (threading.Thread):
    def __init__(self, samples, sounds):
        threading.Thread.__init__(self)
        self.samples = samples
        self.sounds = sounds
        self.stopit = False
    def run(self):
        while not self.stopit:
            print('getting')
            samples = self.samples.get()
 
            x1 = np.array(samples).astype("complex64")
            fc1 = np.exp(-1.0j*2.0*np.pi* F_offset/Fs*np.arange(len(x1))) 
            x2 = x1 * fc1
            bandwidth = 2500#khz broadcast radio.
            n_taps = 64
            # Use Remez algorithm to design filter coefficients
            lpf = signal.remez(n_taps, [0, bandwidth, bandwidth+(Fs/2-bandwidth)/4, Fs/2], [1,0], Hz=Fs)  
            x3 = signal.lfilter(lpf, 1.0, x2)
            dec_rate = int(Fs / bandwidth)
            x4 = x3[0::dec_rate]
            Fs_y = Fs/dec_rate
            f_bw = 200000 
            dec_rate = int(Fs / f_bw)  
            x4 = signal.decimate(x2, dec_rate) 
            # Calculate the new sampling rate
            Fs_y = Fs/dec_rate  
            y5 = x4[1:] * np.conj(x4[:-1])
            x5 = np.angle(y5)
 
            # The de-emphasis filter
            # Given a signal 'x5' (in a numpy array) with sampling rate Fs_y
            d = Fs_y * 75e-6   # Calculate the # of samples to hit the -3dB point  
            x = np.exp(-1/d)   # Calculate the decay between each sample  
            b = [1-x]          # Create the filter coefficients  
            a = [1,-x]  
            x6 = signal.lfilter(b,a,x5)  
            audio_freq = 41000.0 
            dec_audio = int(Fs_y/audio_freq)  
            Fs_audio = Fs_y / dec_audio
            self.Fs_audio = Fs_audio
            x7 = signal.decimate(x6, dec_audio) 
 
            #sounddevice.play(x7,Fs_audio) 
            x7 *= 10000 / np.max(np.abs(x7))  
            self.sounds.put(x7)
            print("processed")
 
thread1 = readThread(sdr, samples)
thread2 = processThread(samples, sounds)
thread1.start()
thread2.start()
 
# configure device
Freq = 162.400e6 #mhz
Fs = 1140000
F_offset = 2500
Fc = Freq - F_offset
sdr.sample_rate = Fs
sdr.center_freq = Fc
sdr.gain = 'auto'
Fs_audio = 0
try:
    while True:
        x7 = sounds.get()
        #sounddevice.play(x7,Fs_audio)
        #x7.astype("int16").tofile("wbfm-mono.raw")  #Raw file.
        #wavfile.write('wav.wav',int(thread2.Fs_audio), x7.astype("int16"))
        print('playing...')
        audio = (x7.astype("int16"),thread2.Fs_audio)
        p = pyaudio.PyAudio()
        stream = p.open(format=pyaudio.paFloat32,
                         channels= 1,
                         rate=4800,
                         output=True,
                         frames_per_buffer = 2048
                         )
# Assuming you have a numpy array called samples
        data = audio
        stream.write(data)
except KeyboardInterrupt:
    print("bye")
    thread1.stopit = True
    thread2.stopit = True
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