{
 "cells": [
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Rapid eye movements analysis"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Introductory notes:\n",
    "This notebook presents REMs detection functionality.\n",
    "\n",
    "Recommended reading:\n",
    "1. [YASA: FAQ](https://raphaelvallat.com/yasa/build/html/faq.html#event-detection)\n",
    "2. [YASA: Rapid Eye Movements (REMs) detection](https://github.com/raphaelvallat/yasa/blob/master/notebooks/07_REMs_detection.ipynb)\n",
    "3. [YASA: REMResults class](https://raphaelvallat.com/yasa/build/html/generated/yasa.REMResults.html#yasa.REMResults)"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Import module"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2024-08-06T08:14:08.680302Z",
     "start_time": "2024-08-06T08:14:08.665883Z"
    }
   },
   "outputs": [],
   "source": [
    "from sleepeegpy.pipeline import RapidEyeMovementsPipe\n",
    "from os import makedirs,path"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## REMs detection"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "If you wish to change the path for output_dir ot input dir, change it below.\n",
    "If no such folders, they will be created automatically."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2024-08-06T08:13:39.962293Z",
     "start_time": "2024-08-06T08:13:39.958601Z"
    }
   },
   "outputs": [],
   "source": [
    "output_dir  = \"output_folder\" # Output path and name can be changed here\n",
    "input_dir = \"input_files\" # input files dir can be changed here\n",
    "makedirs(input_dir, exist_ok=True)\n",
    "makedirs(output_dir, exist_ok=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Add required files and data\n",
    "* Put all your files in the input folder.\n",
    "* Modify your eeg file name below. The file can be any format supported by the mne.read_raw() function.\n",
    "* Modify your hypnogram file name below\n",
    "* Make sure the hypno_freq is the right frequency.\n",
    "* For more information about the supported formats, see [mne documentation](https://mne.tools/stable/generated/mne.io.Raw.html)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2024-08-06T08:13:42.518760Z",
     "start_time": "2024-08-06T08:13:42.515322Z"
    }
   },
   "outputs": [],
   "source": [
    "eeg_file_name= \"resampled_raw.fif\" #None # add your eeg_path here\n",
    "hypnogram_filename = \"staging.txt\" # Hypnogram filename can be changed here (file must be in the input dir)\n",
    "hypno_freq = 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2024-08-06T08:13:45.998074Z",
     "start_time": "2024-08-06T08:13:43.208440Z"
    }
   },
   "outputs": [],
   "source": [
    "path_to_eeg = path.join(input_dir,eeg_file_name)\n",
    "hypnogram_path = path.join(input_dir,hypnogram_filename)\n",
    "\n",
    "assert path.isfile(path_to_eeg) and path.isfile(hypnogram_path), f\"{path_to_eeg} or {hypnogram_path} not exist\"\n",
    "rems_pipe = RapidEyeMovementsPipe(\n",
    "    path_to_eeg=path_to_eeg,\n",
    "    output_dir=output_dir,\n",
    "    path_to_hypno=hypnogram_path,\n",
    "    hypno_freq=hypno_freq,\n",
    ")"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Please refer to the YASA's [documentation](https://raphaelvallat.com/yasa/build/html/generated/yasa.rem_detect.html) for details about the arguments."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2024-08-06T08:13:52.198217Z",
     "start_time": "2024-08-06T08:13:49.549609Z"
    }
   },
   "outputs": [],
   "source": [
    "rems_pipe.detect(\n",
    "    reference=\"average\",\n",
    "    loc_chname=\"E46\",\n",
    "    roc_chname=\"E238\",\n",
    "    include=4,\n",
    "    freq_rem=(0.5, 5),\n",
    "    duration=(0.3, 1.2),\n",
    "    amplitude=(50, 325),\n",
    "    remove_outliers=False,\n",
    "    save=True,\n",
    ")"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Please refer to the YASA's [documentation](https://raphaelvallat.com/yasa/build/html/generated/yasa.REMResults.html#yasa.REMResults.summary) for details about the arguments."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2024-08-06T08:13:55.786477Z",
     "start_time": "2024-08-06T08:13:55.770089Z"
    }
   },
   "outputs": [
                {
                    "data": {
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                            "\n",
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                            "<table border=\"1\" class=\"dataframe\">\n",
                            "  <thead>\n",
                            "    <tr style=\"text-align: right;\">\n",
                            "      <th></th>\n",
                            "      <th>Start</th>\n",
                            "      <th>Peak</th>\n",
                            "      <th>End</th>\n",
                            "      <th>Duration</th>\n",
                            "      <th>LOCAbsValPeak</th>\n",
                            "      <th>ROCAbsValPeak</th>\n",
                            "      <th>LOCAbsRiseSlope</th>\n",
                            "      <th>ROCAbsRiseSlope</th>\n",
                            "      <th>LOCAbsFallSlope</th>\n",
                            "      <th>ROCAbsFallSlope</th>\n",
                            "      <th>Stage</th>\n",
                            "    </tr>\n",
                            "  </thead>\n",
                            "  <tbody>\n",
                            "    <tr>\n",
                            "      <th>0</th>\n",
                            "      <td>11050.544</td>\n",
                            "      <td>11050.904</td>\n",
                            "      <td>11051.096</td>\n",
                            "      <td>0.552</td>\n",
                            "      <td>95.514371</td>\n",
                            "      <td>30.423478</td>\n",
                            "      <td>130.506125</td>\n",
                            "      <td>69.111908</td>\n",
                            "      <td>567.494181</td>\n",
                            "      <td>147.051950</td>\n",
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                            "    <tr>\n",
                            "      <th>1</th>\n",
                            "      <td>11094.860</td>\n",
                            "      <td>11095.436</td>\n",
                            "      <td>11095.712</td>\n",
                            "      <td>0.852</td>\n",
                            "      <td>112.146842</td>\n",
                            "      <td>40.051066</td>\n",
                            "      <td>200.957633</td>\n",
                            "      <td>50.196786</td>\n",
                            "      <td>420.903964</td>\n",
                            "      <td>135.024205</td>\n",
                            "      <td>4</td>\n",
                            "    </tr>\n",
                            "    <tr>\n",
                            "      <th>2</th>\n",
                            "      <td>11095.964</td>\n",
                            "      <td>11096.508</td>\n",
                            "      <td>11097.108</td>\n",
                            "      <td>1.144</td>\n",
                            "      <td>83.861166</td>\n",
                            "      <td>33.723120</td>\n",
                            "      <td>64.100500</td>\n",
                            "      <td>46.741223</td>\n",
                            "      <td>186.273207</td>\n",
                            "      <td>46.131956</td>\n",
                            "      <td>4</td>\n",
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                            "    <tr>\n",
                            "      <th>3</th>\n",
                            "      <td>11482.476</td>\n",
                            "      <td>11482.772</td>\n",
                            "      <td>11483.136</td>\n",
                            "      <td>0.660</td>\n",
                            "      <td>59.031067</td>\n",
                            "      <td>45.284152</td>\n",
                            "      <td>75.523086</td>\n",
                            "      <td>237.193022</td>\n",
                            "      <td>142.850213</td>\n",
                            "      <td>153.438315</td>\n",
                            "      <td>4</td>\n",
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                            "    <tr>\n",
                            "      <th>4</th>\n",
                            "      <td>15971.100</td>\n",
                            "      <td>15971.276</td>\n",
                            "      <td>15971.560</td>\n",
                            "      <td>0.460</td>\n",
                            "      <td>61.745377</td>\n",
                            "      <td>60.780729</td>\n",
                            "      <td>572.829439</td>\n",
                            "      <td>183.557890</td>\n",
                            "      <td>102.135926</td>\n",
                            "      <td>308.358956</td>\n",
                            "      <td>4</td>\n",
                            "    </tr>\n",
                            "    <tr>\n",
                            "      <th>...</th>\n",
                            "      <td>...</td>\n",
                            "      <td>...</td>\n",
                            "      <td>...</td>\n",
                            "      <td>...</td>\n",
                            "      <td>...</td>\n",
                            "      <td>...</td>\n",
                            "      <td>...</td>\n",
                            "      <td>...</td>\n",
                            "      <td>...</td>\n",
                            "      <td>...</td>\n",
                            "      <td>...</td>\n",
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                            "    <tr>\n",
                            "      <th>80</th>\n",
                            "      <td>23049.292</td>\n",
                            "      <td>23049.600</td>\n",
                            "      <td>23049.904</td>\n",
                            "      <td>0.612</td>\n",
                            "      <td>104.243540</td>\n",
                            "      <td>28.876271</td>\n",
                            "      <td>330.751289</td>\n",
                            "      <td>95.426070</td>\n",
                            "      <td>314.121445</td>\n",
                            "      <td>92.583937</td>\n",
                            "      <td>4</td>\n",
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                            "    <tr>\n",
                            "      <th>81</th>\n",
                            "      <td>23056.604</td>\n",
                            "      <td>23057.204</td>\n",
                            "      <td>23057.520</td>\n",
                            "      <td>0.916</td>\n",
                            "      <td>77.727534</td>\n",
                            "      <td>32.451615</td>\n",
                            "      <td>58.396074</td>\n",
                            "      <td>63.557268</td>\n",
                            "      <td>256.425427</td>\n",
                            "      <td>99.318708</td>\n",
                            "      <td>4</td>\n",
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                            "    <tr>\n",
                            "      <th>82</th>\n",
                            "      <td>23075.852</td>\n",
                            "      <td>23076.452</td>\n",
                            "      <td>23076.592</td>\n",
                            "      <td>0.740</td>\n",
                            "      <td>116.082740</td>\n",
                            "      <td>33.233345</td>\n",
                            "      <td>120.322005</td>\n",
                            "      <td>19.386448</td>\n",
                            "      <td>859.366479</td>\n",
                            "      <td>219.808008</td>\n",
                            "      <td>4</td>\n",
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                            "    <tr>\n",
                            "      <th>83</th>\n",
                            "      <td>23076.672</td>\n",
                            "      <td>23077.272</td>\n",
                            "      <td>23077.544</td>\n",
                            "      <td>0.872</td>\n",
                            "      <td>129.179400</td>\n",
                            "      <td>56.446968</td>\n",
                            "      <td>116.311652</td>\n",
                            "      <td>61.487780</td>\n",
                            "      <td>395.069480</td>\n",
                            "      <td>239.110792</td>\n",
                            "      <td>4</td>\n",
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                            "    <tr>\n",
                            "      <th>84</th>\n",
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                            "      <td>23078.224</td>\n",
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                            "      <td>129.250414</td>\n",
                            "      <td>220.010889</td>\n",
                            "      <td>106.752248</td>\n",
                            "      <td>4</td>\n",
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                            "<p>85 rows × 11 columns</p>\n",
                            "</div>"
                        ],
                        "text/plain": [
                            "        Start       Peak        End  Duration  LOCAbsValPeak  ROCAbsValPeak  \\\n",
                            "0   11050.544  11050.904  11051.096     0.552      95.514371      30.423478   \n",
                            "1   11094.860  11095.436  11095.712     0.852     112.146842      40.051066   \n",
                            "2   11095.964  11096.508  11097.108     1.144      83.861166      33.723120   \n",
                            "3   11482.476  11482.772  11483.136     0.660      59.031067      45.284152   \n",
                            "4   15971.100  15971.276  15971.560     0.460      61.745377      60.780729   \n",
                            "..        ...        ...        ...       ...            ...            ...   \n",
                            "80  23049.292  23049.600  23049.904     0.612     104.243540      28.876271   \n",
                            "81  23056.604  23057.204  23057.520     0.916      77.727534      32.451615   \n",
                            "82  23075.852  23076.452  23076.592     0.740     116.082740      33.233345   \n",
                            "83  23076.672  23077.272  23077.544     0.872     129.179400      56.446968   \n",
                            "84  23077.856  23078.224  23078.712     0.856     112.166788      44.556604   \n",
                            "\n",
                            "    LOCAbsRiseSlope  ROCAbsRiseSlope  LOCAbsFallSlope  ROCAbsFallSlope  Stage  \n",
                            "0        130.506125        69.111908       567.494181       147.051950      4  \n",
                            "1        200.957633        50.196786       420.903964       135.024205      4  \n",
                            "2         64.100500        46.741223       186.273207        46.131956      4  \n",
                            "3         75.523086       237.193022       142.850213       153.438315      4  \n",
                            "4        572.829439       183.557890       102.135926       308.358956      4  \n",
                            "..              ...              ...              ...              ...    ...  \n",
                            "80       330.751289        95.426070       314.121445        92.583937      4  \n",
                            "81        58.396074        63.557268       256.425427        99.318708      4  \n",
                            "82       120.322005        19.386448       859.366479       219.808008      4  \n",
                            "83       116.311652        61.487780       395.069480       239.110792      4  \n",
                            "84       274.326404       129.250414       220.010889       106.752248      4  \n",
                            "\n",
                            "[85 rows x 11 columns]"
                        ]
                    },
                    "execution_count": 4,
                    "metadata": {},
                    "output_type": "execute_result"
                }
],
   "source": [
    "rems_pipe.results.summary(\n",
    "    grp_stage=False, \n",
    "    mask=None, \n",
    "    aggfunc='mean', \n",
    "    sort=True\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2024-08-06T08:13:59.102285Z",
     "start_time": "2024-08-06T08:13:58.942192Z"
    }
   },
   "outputs": [
                {
                    "data": {
                        "image/png": 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",
                        "text/plain": [
                            "<Figure size 600x450 with 1 Axes>"
                        ]
                    },
                    "metadata": {},
                    "output_type": "display_data"
                }
],
   "source": [
    "rems_pipe.plot_average( \n",
    "    save=True, \n",
    "    center=\"Peak\",\n",
    "    time_before=0.5,\n",
    "    time_after=0.5,\n",
    "    filt=(None,None),\n",
    "    mask=None,\n",
    "    )"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.11.8"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}