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   "source": [
    "# Parse and load data-sets\n",
    "\n",
    "´APR-pipelines´ makes it easy to automatically load a data-set. Several parser method are provided:\n",
    "1. A general parser where each tile is saved as ´row_col.tif´ (it can be 3D tiffs or 2D tiffs saved in a folder named ´row_col´)\n",
    "2. COLM (Clarity Optimised Lightsheet Microscope) data\n",
    "3. ClearScope data\n",
    "\n",
    "Note that it is very easy to support new data architecture, you can get in touch for a given implementation. For the first case we use the ´tileParser´ class:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "import paprica\n",
    "\n",
    "tiles = paprica.tileParser(path='path to the folder containing the data',\n",
    "                          frame_size=2048,\n",
    "                          ftype='apr')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
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   "source": [
    "For the second case we use the ´colmParser´ class (less inputs are required since the sensor size and data type is fixed by the microscope):"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
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   "outputs": [],
   "source": [
    "tiles = paprica.parser.colmParser(path='path to the COLM folder acquisition')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%% md\n"
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   "source": [
    "And finally for the third case we use the ´clearscopeParser´ class:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "tiles = paprica.parser.clearscopeParser(path='path to the ClearScope folder acquisition')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "Note that each channel must be parsed independently (this implementation choice was made to give more flexibility to the user):"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "tiles_ch0 = paprica.parser.colmParser(path='path to the COLM folder acquisition', channel=0)\n",
    "tiles_ch1 = paprica.parser.colmParser(path='path to the COLM folder acquisition', channel=1)\n",
    "tiles_ch2 = paprica.parser.colmParser(path='path to the COLM folder acquisition', channel=2)"
   ]
  }
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