00_write_voice.ipynb

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    "import numpy as np\n",
    "import wave\n",
    "import struct\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "# frequency is the number of times a wave repeats a second\n",
    "frequency = 1000\n",
    "num_samples = 48000\n",
    " \n",
    "# The sampling rate of the analog to digital convert\n",
    "sampling_rate = 48000.0\n",
    "amplitude = 16000\n",
    "file = \"test.wav\"\n"
   ]
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   "cell_type": "markdown",
   "id": "92e14c85-2b49-4b34-a823-5c15c539e4a0",
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   "source": [
    "## 设置波形变量"
   ]
  },
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   "source": [
    "sine_wave = [np.sin(2 * np.pi * frequency * x/sampling_rate) for x in range(num_samples)]\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1ed97b86-4df8-47d3-a195-c283a10280d0",
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    "## 将正弦波写入文件了。\n",
    "我们将使用Python的内置wave库。在这里我们设置参数.\n",
    "- `nframes`是帧数或样本数.\n",
    "- `comptype`和`compname`都表示同样的事情：数据未压缩.\n",
    "- `nchannels`是通道数，即1.\n",
    "- `sampwidth`是以字节为单位的样本宽度。正如我前面提到的，波形文件通常是每个样本16位或2个字节"
   ]
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    "nframes=num_samples\n",
    "comptype=\"NONE\"\n",
    "compname=\"not compressed\" \n",
    "nchannels=1\n",
    "sampwidth=2\n"
   ]
  },
  {
   "cell_type": "code",
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   "id": "fc0de220-4994-447c-ae84-b4c8c2110743",
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   "outputs": [
    {
     "data": {
      "text/plain": [
       "b'\\xd8\\xf7'"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "wav_file=wave.open(file, 'w')\n",
    "wav_file.setparams((nchannels, sampwidth, int(sampling_rate), nframes, comptype, compname))\n",
    "\n",
    "for s in sine_wave:\n",
    "   wav_file.writeframes(struct.pack('h', int(s*amplitude)))\n",
    "\n",
    "struct.pack('h', int(s*amplitude))\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "d3af78c7-d974-426c-91e1-212f831f7149",
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