{
 "cells": [
  {
   "cell_type": "raw",
   "id": "gross-fever",
   "metadata": {},
   "source": [
    "Notebook extracts ENF signal by pyenf_extraction application\n",
    "Uses reference (002_ref.wav) and original (002.wav) signal"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "complete-exchange",
   "metadata": {
    "scrolled": true,
    "tags": []
   },
   "outputs": [],
   "source": [
    "!wget https://github.com/ghuawhu/ENF-WHU-Dataset/blob/master/ENF-WHU-Dataset/H1/002.wav?raw=true\n",
    "!wget https://github.com/ghuawhu/ENF-WHU-Dataset/blob/master/ENF-WHU-Dataset/H1_ref/002_ref.wav?raw=true\n",
    "!git clone https://github.com/deerajnagothu/pyenf_extraction"
   ]
  },
  {
   "cell_type": "raw",
   "id": "fixed-aging",
   "metadata": {},
   "source": [
    "pip install scipy==1.1.0\n",
    "pip install numpy==1.21.0\n",
    "pip install matplotlib==3.4.2\n",
    "pip install librosa==0.8.1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "premier-minimum",
   "metadata": {},
   "outputs": [],
   "source": [
    "import sys\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "regular-boundary",
   "metadata": {},
   "outputs": [],
   "source": [
    "sys.path.append('./pyenf_extraction/')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "remarkable-ready",
   "metadata": {
    "scrolled": true,
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
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    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/radekludacka/miniconda3/envs/enf/lib/python3.7/site-packages/numpy/core/fromnumeric.py:1970: VisibleDeprecationWarning: Creating an ndarray from ragged nested sequences (which is a list-or-tuple of lists-or-tuples-or ndarrays with different lengths or shapes) is deprecated. If you meant to do this, you must specify 'dtype=object' when creating the ndarray.\n",
      "  result = asarray(a).shape\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
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    }
   ],
   "source": [
    "audio = extract_enf_signal('002.wav?raw=true')\n",
    "audio_reference = extract_enf_signal('002_ref.wav?raw=true')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "cutting-click",
   "metadata": {},
   "outputs": [],
   "source": [
    "np.save('audio.npy', audio)\n",
    "np.save('audio_reference.npy', audio_reference)"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Conda Python 3.7 (pyenf)",
   "language": "python",
   "name": "pyenf"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.10"
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 },
 "nbformat": 4,
 "nbformat_minor": 5
}