generate_sounds.ipynb

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  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib inline\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "import os\n",
    "import scipy.io.wavfile\n",
    "import random\n",
    "from scipy import signal"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
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   "outputs": [],
   "source": [
    "# data_filepath = 'C:/Users/Emily/emi_biconditional/cache/other'\n",
    "data_filepath = 'E:/code/emi_biconditional/cache/other'"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Click"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "frequency = 10\n",
    "n_seconds = 12\n",
    "amplitude = 10\n",
    "fs = 44100\n",
    "time = np.linspace(0, 1, fs * n_seconds)\n",
    "click = signal.sawtooth(2 * np.pi * frequency * n_seconds * time) * amplitude"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "plt.plot(click)\n",
    "plt.xlim([0, 10000])\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "filename = os.path.join(data_filepath, 'click.wav')\n",
    "scipy.io.wavfile.write(filename, fs, click)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# White noise"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "fs = 44100\n",
    "n_seconds = 12\n",
    "amplitude = 1\n",
    "noise = np.random.uniform(-1 * amplitude, 1 * amplitude, fs * n_seconds) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "plt.plot(noise)\n",
    "plt.xlim([0,100])\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "filename = os.path.join(data_filepath, 'noise.wav')\n",
    "scipy.io.wavfile.write(filename, fs, noise)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Tone"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "frequency = 1500\n",
    "amplitude = 20000\n",
    "n_seconds = 12\n",
    "fs = 44100\n",
    "\n",
    "time = np.arange(0, n_seconds, 1./fs)\n",
    "tone = amplitude * np.cos(2 * np.pi * frequency * time)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "plt.plot(tone)\n",
    "plt.xlim([0,100])\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "filename = os.path.join(data_filepath, 'tone.wav')\n",
    "scipy.io.wavfile.write(filename, fs, tone.astype(np.dtype('i2')))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
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