{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Exercise 6.1: Detecting dropped frames\n",
    "\n",
    "<hr>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In [our lesson on scripting](l35_intro_to_scripting.ipynb), we worked on parsing a directory of images from a Leica microscope. The frame rate at which those data were taken was really fast for that microscope. On occasion, the system may miss a frame. Determine if any TIFF files are missing from the directory and, if so, which frame numbers are missing.\n",
    "\n",
    "This is an exercise in scripting and file management."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<br />"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Solution \n",
    "\n",
    "<hr>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "import glob\n",
    "import os\n",
    "import re"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Determining which frames were dropped is quite easy after completing [the scripting lesson](l31_intro_to_scripting.ipynb) where we have renamed the files. We just search through our renamed files and find any numbers that are out of order. *Note that the code below will not work if the files have not been renamed.*"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The following frames were dropped:  [33, 113]\n"
     ]
    }
   ],
   "source": [
    "# Specify Leica directory\n",
    "leica_dir = 'data/leica_tiffs_renamed'\n",
    "\n",
    "# Get list of files\n",
    "file_list = sorted(glob.glob(os.path.join(leica_dir, '*_t*.tif')))\n",
    "\n",
    "# String to search for (the time stamp)\n",
    "regex = re.compile('_t\\d+_')\n",
    "\n",
    "# Pull frame numbers and check against running list\n",
    "correct_frame_num = 0\n",
    "dropped_frames = []\n",
    "for fname in file_list:\n",
    "    # Pull out _t00000000_ string\n",
    "    time_str = regex.search(fname).group()\n",
    "\n",
    "    # Get integer frame number\n",
    "    fnum = int(time_str[2:-1])\n",
    "    \n",
    "    # Compare\n",
    "    if fnum > correct_frame_num:\n",
    "        # Record which frames were dropped\n",
    "        dropped_frames += list(range(correct_frame_num, fnum))\n",
    "        correct_frame_num = fnum + 1\n",
    "    else:\n",
    "        correct_frame_num += 1\n",
    "\n",
    "# Which frames were dropped?\n",
    "print('The following frames were dropped: ', dropped_frames)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Computing environment"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "tags": [
     "hide-input"
    ]
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Python implementation: CPython\n",
      "Python version       : 3.11.3\n",
      "IPython version      : 8.12.0\n",
      "\n",
      "jupyterlab: 3.6.3\n",
      "\n"
     ]
    }
   ],
   "source": [
    "%load_ext watermark\n",
    "%watermark -v -p jupyterlab"
   ]
  }
 ],
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  "anaconda-cloud": {},
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
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  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.11.3"
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