{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Read single-trial EEG epochs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "from matplotlib import pyplot as plt\n",
    "from spudtr import get_demo_df, P3_1500_FEATHER\n",
    "from spudtr import epf"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>epoch_id</th>\n",
       "      <th>time_ms</th>\n",
       "      <th>sub_id</th>\n",
       "      <th>eeg_artifact</th>\n",
       "      <th>dblock_path</th>\n",
       "      <th>log_evcodes</th>\n",
       "      <th>log_ccodes</th>\n",
       "      <th>dblock_srate</th>\n",
       "      <th>ccode</th>\n",
       "      <th>instrument</th>\n",
       "      <th>...</th>\n",
       "      <th>RMOc</th>\n",
       "      <th>LLTe</th>\n",
       "      <th>RLTe</th>\n",
       "      <th>LLOc</th>\n",
       "      <th>RLOc</th>\n",
       "      <th>MiOc</th>\n",
       "      <th>A2</th>\n",
       "      <th>HEOG</th>\n",
       "      <th>rle</th>\n",
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       "      <td>-1.507812</td>\n",
       "      <td>3.947266</td>\n",
       "      <td>-15.648438</td>\n",
       "      <td>-10.085938</td>\n",
       "      <td>-11.171875</td>\n",
       "      <td>8.367188</td>\n",
       "      <td>102.062500</td>\n",
       "      <td>-33.656250</td>\n",
       "      <td>43.718750</td>\n",
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       "      <td>-8.015625</td>\n",
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       "    <tr>\n",
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       "</table>\n",
       "<p>225000 rows × 47 columns</p>\n",
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      ],
      "text/plain": [
       "        epoch_id  time_ms  sub_id  eeg_artifact      dblock_path  log_evcodes  \\\n",
       "0              0     -748  sub000             0  sub000/dblock_0            0   \n",
       "1              0     -744  sub000             0  sub000/dblock_0            0   \n",
       "2              0     -740  sub000             0  sub000/dblock_0            0   \n",
       "3              0     -736  sub000             0  sub000/dblock_0            0   \n",
       "4              0     -732  sub000             0  sub000/dblock_0            0   \n",
       "...          ...      ...     ...           ...              ...          ...   \n",
       "224995       600      732  sub000             0  sub000/dblock_4            0   \n",
       "224996       600      736  sub000             0  sub000/dblock_4            0   \n",
       "224997       600      740  sub000             0  sub000/dblock_4            0   \n",
       "224998       600      744  sub000             0  sub000/dblock_4            0   \n",
       "224999       600      748  sub000             0  sub000/dblock_4            0   \n",
       "\n",
       "        log_ccodes  dblock_srate  ccode instrument  ...       RMOc       LLTe  \\\n",
       "0                0         250.0      1        eeg  ... -25.093750  -0.753906   \n",
       "1                0         250.0      1        eeg  ... -24.593750   0.502441   \n",
       "2                0         250.0      1        eeg  ... -16.484375  -1.507812   \n",
       "3                0         250.0      1        eeg  ... -11.804688 -15.070312   \n",
       "4                0         250.0      1        eeg  ...  -6.394531  -4.019531   \n",
       "...            ...           ...    ...        ...  ...        ...        ...   \n",
       "224995           0         250.0      0        cal  ...  -4.671875  -3.517578   \n",
       "224996           0         250.0      0        cal  ...  -4.179688  -4.019531   \n",
       "224997           0         250.0      0        cal  ...  -4.425781  -3.767578   \n",
       "224998           0         250.0      0        cal  ...  -4.425781  -4.269531   \n",
       "224999           0         250.0      0        cal  ...  -4.179688  -4.019531   \n",
       "\n",
       "            RLTe       LLOc       RLOc       MiOc        A2        HEOG  \\\n",
       "0       1.480469 -13.414062 -18.937500 -17.734375  5.660156   98.875000   \n",
       "1      -2.466797 -17.640625 -17.468750 -15.304688  1.968750  104.750000   \n",
       "2       3.947266 -15.648438 -10.085938 -11.171875  8.367188  102.062500   \n",
       "3       9.867188 -14.906250  -7.378906  -8.742188  9.351562  100.562500   \n",
       "4       9.125000 -10.679688  -6.886719  -8.015625  8.125000   98.375000   \n",
       "...          ...        ...        ...        ...       ...         ...   \n",
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       "224996 -4.195312  -4.222656  -4.425781  -3.644531 -4.429688   -4.160156   \n",
       "224997 -4.441406  -3.974609  -4.425781  -3.400391 -4.429688   -4.160156   \n",
       "224998 -4.195312  -4.222656  -4.425781  -3.886719 -4.429688   -4.406250   \n",
       "224999 -3.947266  -4.222656  -4.179688  -3.400391 -4.183594   -4.406250   \n",
       "\n",
       "              rle        rhz  \n",
       "0      -39.500000  38.375000  \n",
       "1      -38.031250  41.281250  \n",
       "2      -33.656250  43.718750  \n",
       "3      -42.906250  37.406250  \n",
       "4      -43.875000  37.906250  \n",
       "...           ...        ...  \n",
       "224995  -3.900391  -4.371094  \n",
       "224996  -3.412109  -4.371094  \n",
       "224997  -3.900391  -4.859375  \n",
       "224998  -3.900391  -4.371094  \n",
       "224999  -3.412109  -4.371094  \n",
       "\n",
       "[225000 rows x 47 columns]"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "epochs_df = get_demo_df(P3_1500_FEATHER)\n",
    "\n",
    "# example: four midline EEG channels\n",
    "eeg_channels = ['MiPf', 'MiCe', 'MiPa', 'MiOc']\n",
    "\n",
    "# check the epochs format\n",
    "epf.check_epochs(epochs_df, eeg_channels, epoch_id=\"epoch_id\", time=\"time_ms\")\n",
    "\n",
    "# preview the entire dataframe\n",
    "epochs_df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Common A1 to average mastoid reference\n",
    "\n",
    "a.k.a. \"bimastoid\", \"linked mastoid\"\n",
    "\n",
    "**Warning, only valid for EEG recorded with a common A1 reference**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
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       "      <th></th>\n",
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       "      <td>-38.031250</td>\n",
       "      <td>41.281250</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0</td>\n",
       "      <td>-740</td>\n",
       "      <td>sub000</td>\n",
       "      <td>0</td>\n",
       "      <td>sub000/dblock_0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>250.0</td>\n",
       "      <td>1</td>\n",
       "      <td>eeg</td>\n",
       "      <td>...</td>\n",
       "      <td>-16.484375</td>\n",
       "      <td>-1.507812</td>\n",
       "      <td>3.947266</td>\n",
       "      <td>-15.648438</td>\n",
       "      <td>-10.085938</td>\n",
       "      <td>-15.355469</td>\n",
       "      <td>8.367188</td>\n",
       "      <td>102.062500</td>\n",
       "      <td>-33.656250</td>\n",
       "      <td>43.718750</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0</td>\n",
       "      <td>-736</td>\n",
       "      <td>sub000</td>\n",
       "      <td>0</td>\n",
       "      <td>sub000/dblock_0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>250.0</td>\n",
       "      <td>1</td>\n",
       "      <td>eeg</td>\n",
       "      <td>...</td>\n",
       "      <td>-11.804688</td>\n",
       "      <td>-15.070312</td>\n",
       "      <td>9.867188</td>\n",
       "      <td>-14.906250</td>\n",
       "      <td>-7.378906</td>\n",
       "      <td>-13.417969</td>\n",
       "      <td>9.351562</td>\n",
       "      <td>100.562500</td>\n",
       "      <td>-42.906250</td>\n",
       "      <td>37.406250</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0</td>\n",
       "      <td>-732</td>\n",
       "      <td>sub000</td>\n",
       "      <td>0</td>\n",
       "      <td>sub000/dblock_0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>250.0</td>\n",
       "      <td>1</td>\n",
       "      <td>eeg</td>\n",
       "      <td>...</td>\n",
       "      <td>-6.394531</td>\n",
       "      <td>-4.019531</td>\n",
       "      <td>9.125000</td>\n",
       "      <td>-10.679688</td>\n",
       "      <td>-6.886719</td>\n",
       "      <td>-12.078125</td>\n",
       "      <td>8.125000</td>\n",
       "      <td>98.375000</td>\n",
       "      <td>-43.875000</td>\n",
       "      <td>37.906250</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",
       "      <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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>224995</th>\n",
       "      <td>600</td>\n",
       "      <td>732</td>\n",
       "      <td>sub000</td>\n",
       "      <td>0</td>\n",
       "      <td>sub000/dblock_4</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>250.0</td>\n",
       "      <td>0</td>\n",
       "      <td>cal</td>\n",
       "      <td>...</td>\n",
       "      <td>-4.671875</td>\n",
       "      <td>-3.517578</td>\n",
       "      <td>-4.441406</td>\n",
       "      <td>-4.718750</td>\n",
       "      <td>-4.671875</td>\n",
       "      <td>-1.185547</td>\n",
       "      <td>-4.429688</td>\n",
       "      <td>-4.406250</td>\n",
       "      <td>-3.900391</td>\n",
       "      <td>-4.371094</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>224996</th>\n",
       "      <td>600</td>\n",
       "      <td>736</td>\n",
       "      <td>sub000</td>\n",
       "      <td>0</td>\n",
       "      <td>sub000/dblock_4</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>250.0</td>\n",
       "      <td>0</td>\n",
       "      <td>cal</td>\n",
       "      <td>...</td>\n",
       "      <td>-4.179688</td>\n",
       "      <td>-4.019531</td>\n",
       "      <td>-4.195312</td>\n",
       "      <td>-4.222656</td>\n",
       "      <td>-4.425781</td>\n",
       "      <td>-1.429688</td>\n",
       "      <td>-4.429688</td>\n",
       "      <td>-4.160156</td>\n",
       "      <td>-3.412109</td>\n",
       "      <td>-4.371094</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>224997</th>\n",
       "      <td>600</td>\n",
       "      <td>740</td>\n",
       "      <td>sub000</td>\n",
       "      <td>0</td>\n",
       "      <td>sub000/dblock_4</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>250.0</td>\n",
       "      <td>0</td>\n",
       "      <td>cal</td>\n",
       "      <td>...</td>\n",
       "      <td>-4.425781</td>\n",
       "      <td>-3.767578</td>\n",
       "      <td>-4.441406</td>\n",
       "      <td>-3.974609</td>\n",
       "      <td>-4.425781</td>\n",
       "      <td>-1.185547</td>\n",
       "      <td>-4.429688</td>\n",
       "      <td>-4.160156</td>\n",
       "      <td>-3.900391</td>\n",
       "      <td>-4.859375</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>224998</th>\n",
       "      <td>600</td>\n",
       "      <td>744</td>\n",
       "      <td>sub000</td>\n",
       "      <td>0</td>\n",
       "      <td>sub000/dblock_4</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>250.0</td>\n",
       "      <td>0</td>\n",
       "      <td>cal</td>\n",
       "      <td>...</td>\n",
       "      <td>-4.425781</td>\n",
       "      <td>-4.269531</td>\n",
       "      <td>-4.195312</td>\n",
       "      <td>-4.222656</td>\n",
       "      <td>-4.425781</td>\n",
       "      <td>-1.671875</td>\n",
       "      <td>-4.429688</td>\n",
       "      <td>-4.406250</td>\n",
       "      <td>-3.900391</td>\n",
       "      <td>-4.371094</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>224999</th>\n",
       "      <td>600</td>\n",
       "      <td>748</td>\n",
       "      <td>sub000</td>\n",
       "      <td>0</td>\n",
       "      <td>sub000/dblock_4</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>250.0</td>\n",
       "      <td>0</td>\n",
       "      <td>cal</td>\n",
       "      <td>...</td>\n",
       "      <td>-4.179688</td>\n",
       "      <td>-4.019531</td>\n",
       "      <td>-3.947266</td>\n",
       "      <td>-4.222656</td>\n",
       "      <td>-4.179688</td>\n",
       "      <td>-1.308594</td>\n",
       "      <td>-4.183594</td>\n",
       "      <td>-4.406250</td>\n",
       "      <td>-3.412109</td>\n",
       "      <td>-4.371094</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>225000 rows × 47 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        epoch_id  time_ms  sub_id  eeg_artifact      dblock_path  log_evcodes  \\\n",
       "0              0     -748  sub000             0  sub000/dblock_0            0   \n",
       "1              0     -744  sub000             0  sub000/dblock_0            0   \n",
       "2              0     -740  sub000             0  sub000/dblock_0            0   \n",
       "3              0     -736  sub000             0  sub000/dblock_0            0   \n",
       "4              0     -732  sub000             0  sub000/dblock_0            0   \n",
       "...          ...      ...     ...           ...              ...          ...   \n",
       "224995       600      732  sub000             0  sub000/dblock_4            0   \n",
       "224996       600      736  sub000             0  sub000/dblock_4            0   \n",
       "224997       600      740  sub000             0  sub000/dblock_4            0   \n",
       "224998       600      744  sub000             0  sub000/dblock_4            0   \n",
       "224999       600      748  sub000             0  sub000/dblock_4            0   \n",
       "\n",
       "        log_ccodes  dblock_srate  ccode instrument  ...       RMOc       LLTe  \\\n",
       "0                0         250.0      1        eeg  ... -25.093750  -0.753906   \n",
       "1                0         250.0      1        eeg  ... -24.593750   0.502441   \n",
       "2                0         250.0      1        eeg  ... -16.484375  -1.507812   \n",
       "3                0         250.0      1        eeg  ... -11.804688 -15.070312   \n",
       "4                0         250.0      1        eeg  ...  -6.394531  -4.019531   \n",
       "...            ...           ...    ...        ...  ...        ...        ...   \n",
       "224995           0         250.0      0        cal  ...  -4.671875  -3.517578   \n",
       "224996           0         250.0      0        cal  ...  -4.179688  -4.019531   \n",
       "224997           0         250.0      0        cal  ...  -4.425781  -3.767578   \n",
       "224998           0         250.0      0        cal  ...  -4.425781  -4.269531   \n",
       "224999           0         250.0      0        cal  ...  -4.179688  -4.019531   \n",
       "\n",
       "            RLTe       LLOc       RLOc       MiOc        A2        HEOG  \\\n",
       "0       1.480469 -13.414062 -18.937500 -20.564453  5.660156   98.875000   \n",
       "1      -2.466797 -17.640625 -17.468750 -16.289062  1.968750  104.750000   \n",
       "2       3.947266 -15.648438 -10.085938 -15.355469  8.367188  102.062500   \n",
       "3       9.867188 -14.906250  -7.378906 -13.417969  9.351562  100.562500   \n",
       "4       9.125000 -10.679688  -6.886719 -12.078125  8.125000   98.375000   \n",
       "...          ...        ...        ...        ...       ...         ...   \n",
       "224995 -4.441406  -4.718750  -4.671875  -1.185547 -4.429688   -4.406250   \n",
       "224996 -4.195312  -4.222656  -4.425781  -1.429688 -4.429688   -4.160156   \n",
       "224997 -4.441406  -3.974609  -4.425781  -1.185547 -4.429688   -4.160156   \n",
       "224998 -4.195312  -4.222656  -4.425781  -1.671875 -4.429688   -4.406250   \n",
       "224999 -3.947266  -4.222656  -4.179688  -1.308594 -4.183594   -4.406250   \n",
       "\n",
       "              rle        rhz  \n",
       "0      -39.500000  38.375000  \n",
       "1      -38.031250  41.281250  \n",
       "2      -33.656250  43.718750  \n",
       "3      -42.906250  37.406250  \n",
       "4      -43.875000  37.906250  \n",
       "...           ...        ...  \n",
       "224995  -3.900391  -4.371094  \n",
       "224996  -3.412109  -4.371094  \n",
       "224997  -3.900391  -4.859375  \n",
       "224998  -3.900391  -4.371094  \n",
       "224999  -3.412109  -4.371094  \n",
       "\n",
       "[225000 rows x 47 columns]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "epf.re_reference(\n",
    "    epochs_df, \n",
    "    eeg_channels, \n",
    "    'A2', \n",
    "    \"linked_pair\",\n",
    "    epoch_id=\"epoch_id\", time=\"time_ms\",\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# New common reference\n",
    "\n",
    "> Note: Only valid for common reference EEG data.\n",
    "\n",
    "For example change from common A1 reference to a vertex or nose tip common reference.\n",
    "\n",
    "Note: new the new reference = 0 as expected."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "        vertical-align: top;\n",
       "    }\n",
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       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>epoch_id</th>\n",
       "      <th>time_ms</th>\n",
       "      <th>sub_id</th>\n",
       "      <th>eeg_artifact</th>\n",
       "      <th>dblock_path</th>\n",
       "      <th>log_evcodes</th>\n",
       "      <th>log_ccodes</th>\n",
       "      <th>dblock_srate</th>\n",
       "      <th>ccode</th>\n",
       "      <th>instrument</th>\n",
       "      <th>...</th>\n",
       "      <th>RMOc</th>\n",
       "      <th>LLTe</th>\n",
       "      <th>RLTe</th>\n",
       "      <th>LLOc</th>\n",
       "      <th>RLOc</th>\n",
       "      <th>MiOc</th>\n",
       "      <th>A2</th>\n",
       "      <th>HEOG</th>\n",
       "      <th>rle</th>\n",
       "      <th>rhz</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>-748</td>\n",
       "      <td>sub000</td>\n",
       "      <td>0</td>\n",
       "      <td>sub000/dblock_0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>250.0</td>\n",
       "      <td>1</td>\n",
       "      <td>eeg</td>\n",
       "      <td>...</td>\n",
       "      <td>-25.093750</td>\n",
       "      <td>-0.753906</td>\n",
       "      <td>1.480469</td>\n",
       "      <td>-13.414062</td>\n",
       "      <td>-18.937500</td>\n",
       "      <td>-20.515625</td>\n",
       "      <td>5.660156</td>\n",
       "      <td>98.875000</td>\n",
       "      <td>-39.500000</td>\n",
       "      <td>38.375000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0</td>\n",
       "      <td>-744</td>\n",
       "      <td>sub000</td>\n",
       "      <td>0</td>\n",
       "      <td>sub000/dblock_0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>250.0</td>\n",
       "      <td>1</td>\n",
       "      <td>eeg</td>\n",
       "      <td>...</td>\n",
       "      <td>-24.593750</td>\n",
       "      <td>0.502441</td>\n",
       "      <td>-2.466797</td>\n",
       "      <td>-17.640625</td>\n",
       "      <td>-17.468750</td>\n",
       "      <td>-11.257812</td>\n",
       "      <td>1.968750</td>\n",
       "      <td>104.750000</td>\n",
       "      <td>-38.031250</td>\n",
       "      <td>41.281250</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0</td>\n",
       "      <td>-740</td>\n",
       "      <td>sub000</td>\n",
       "      <td>0</td>\n",
       "      <td>sub000/dblock_0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>250.0</td>\n",
       "      <td>1</td>\n",
       "      <td>eeg</td>\n",
       "      <td>...</td>\n",
       "      <td>-16.484375</td>\n",
       "      <td>-1.507812</td>\n",
       "      <td>3.947266</td>\n",
       "      <td>-15.648438</td>\n",
       "      <td>-10.085938</td>\n",
       "      <td>-7.882812</td>\n",
       "      <td>8.367188</td>\n",
       "      <td>102.062500</td>\n",
       "      <td>-33.656250</td>\n",
       "      <td>43.718750</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0</td>\n",
       "      <td>-736</td>\n",
       "      <td>sub000</td>\n",
       "      <td>0</td>\n",
       "      <td>sub000/dblock_0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>250.0</td>\n",
       "      <td>1</td>\n",
       "      <td>eeg</td>\n",
       "      <td>...</td>\n",
       "      <td>-11.804688</td>\n",
       "      <td>-15.070312</td>\n",
       "      <td>9.867188</td>\n",
       "      <td>-14.906250</td>\n",
       "      <td>-7.378906</td>\n",
       "      <td>-6.212891</td>\n",
       "      <td>9.351562</td>\n",
       "      <td>100.562500</td>\n",
       "      <td>-42.906250</td>\n",
       "      <td>37.406250</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0</td>\n",
       "      <td>-732</td>\n",
       "      <td>sub000</td>\n",
       "      <td>0</td>\n",
       "      <td>sub000/dblock_0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>250.0</td>\n",
       "      <td>1</td>\n",
       "      <td>eeg</td>\n",
       "      <td>...</td>\n",
       "      <td>-6.394531</td>\n",
       "      <td>-4.019531</td>\n",
       "      <td>9.125000</td>\n",
       "      <td>-10.679688</td>\n",
       "      <td>-6.886719</td>\n",
       "      <td>-12.062500</td>\n",
       "      <td>8.125000</td>\n",
       "      <td>98.375000</td>\n",
       "      <td>-43.875000</td>\n",
       "      <td>37.906250</td>\n",
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       "      <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",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>224995</th>\n",
       "      <td>600</td>\n",
       "      <td>732</td>\n",
       "      <td>sub000</td>\n",
       "      <td>0</td>\n",
       "      <td>sub000/dblock_4</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>250.0</td>\n",
       "      <td>0</td>\n",
       "      <td>cal</td>\n",
       "      <td>...</td>\n",
       "      <td>-4.671875</td>\n",
       "      <td>-3.517578</td>\n",
       "      <td>-4.441406</td>\n",
       "      <td>-4.718750</td>\n",
       "      <td>-4.671875</td>\n",
       "      <td>0.392578</td>\n",
       "      <td>-4.429688</td>\n",
       "      <td>-4.406250</td>\n",
       "      <td>-3.900391</td>\n",
       "      <td>-4.371094</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>224996</th>\n",
       "      <td>600</td>\n",
       "      <td>736</td>\n",
       "      <td>sub000</td>\n",
       "      <td>0</td>\n",
       "      <td>sub000/dblock_4</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>250.0</td>\n",
       "      <td>0</td>\n",
       "      <td>cal</td>\n",
       "      <td>...</td>\n",
       "      <td>-4.179688</td>\n",
       "      <td>-4.019531</td>\n",
       "      <td>-4.195312</td>\n",
       "      <td>-4.222656</td>\n",
       "      <td>-4.425781</td>\n",
       "      <td>0.148438</td>\n",
       "      <td>-4.429688</td>\n",
       "      <td>-4.160156</td>\n",
       "      <td>-3.412109</td>\n",
       "      <td>-4.371094</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>224997</th>\n",
       "      <td>600</td>\n",
       "      <td>740</td>\n",
       "      <td>sub000</td>\n",
       "      <td>0</td>\n",
       "      <td>sub000/dblock_4</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>250.0</td>\n",
       "      <td>0</td>\n",
       "      <td>cal</td>\n",
       "      <td>...</td>\n",
       "      <td>-4.425781</td>\n",
       "      <td>-3.767578</td>\n",
       "      <td>-4.441406</td>\n",
       "      <td>-3.974609</td>\n",
       "      <td>-4.425781</td>\n",
       "      <td>0.392578</td>\n",
       "      <td>-4.429688</td>\n",
       "      <td>-4.160156</td>\n",
       "      <td>-3.900391</td>\n",
       "      <td>-4.859375</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>224998</th>\n",
       "      <td>600</td>\n",
       "      <td>744</td>\n",
       "      <td>sub000</td>\n",
       "      <td>0</td>\n",
       "      <td>sub000/dblock_4</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>250.0</td>\n",
       "      <td>0</td>\n",
       "      <td>cal</td>\n",
       "      <td>...</td>\n",
       "      <td>-4.425781</td>\n",
       "      <td>-4.269531</td>\n",
       "      <td>-4.195312</td>\n",
       "      <td>-4.222656</td>\n",
       "      <td>-4.425781</td>\n",
       "      <td>-0.093750</td>\n",
       "      <td>-4.429688</td>\n",
       "      <td>-4.406250</td>\n",
       "      <td>-3.900391</td>\n",
       "      <td>-4.371094</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>224999</th>\n",
       "      <td>600</td>\n",
       "      <td>748</td>\n",
       "      <td>sub000</td>\n",
       "      <td>0</td>\n",
       "      <td>sub000/dblock_4</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>250.0</td>\n",
       "      <td>0</td>\n",
       "      <td>cal</td>\n",
       "      <td>...</td>\n",
       "      <td>-4.179688</td>\n",
       "      <td>-4.019531</td>\n",
       "      <td>-3.947266</td>\n",
       "      <td>-4.222656</td>\n",
       "      <td>-4.179688</td>\n",
       "      <td>0.646484</td>\n",
       "      <td>-4.183594</td>\n",
       "      <td>-4.406250</td>\n",
       "      <td>-3.412109</td>\n",
       "      <td>-4.371094</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>225000 rows × 47 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        epoch_id  time_ms  sub_id  eeg_artifact      dblock_path  log_evcodes  \\\n",
       "0              0     -748  sub000             0  sub000/dblock_0            0   \n",
       "1              0     -744  sub000             0  sub000/dblock_0            0   \n",
       "2              0     -740  sub000             0  sub000/dblock_0            0   \n",
       "3              0     -736  sub000             0  sub000/dblock_0            0   \n",
       "4              0     -732  sub000             0  sub000/dblock_0            0   \n",
       "...          ...      ...     ...           ...              ...          ...   \n",
       "224995       600      732  sub000             0  sub000/dblock_4            0   \n",
       "224996       600      736  sub000             0  sub000/dblock_4            0   \n",
       "224997       600      740  sub000             0  sub000/dblock_4            0   \n",
       "224998       600      744  sub000             0  sub000/dblock_4            0   \n",
       "224999       600      748  sub000             0  sub000/dblock_4            0   \n",
       "\n",
       "        log_ccodes  dblock_srate  ccode instrument  ...       RMOc       LLTe  \\\n",
       "0                0         250.0      1        eeg  ... -25.093750  -0.753906   \n",
       "1                0         250.0      1        eeg  ... -24.593750   0.502441   \n",
       "2                0         250.0      1        eeg  ... -16.484375  -1.507812   \n",
       "3                0         250.0      1        eeg  ... -11.804688 -15.070312   \n",
       "4                0         250.0      1        eeg  ...  -6.394531  -4.019531   \n",
       "...            ...           ...    ...        ...  ...        ...        ...   \n",
       "224995           0         250.0      0        cal  ...  -4.671875  -3.517578   \n",
       "224996           0         250.0      0        cal  ...  -4.179688  -4.019531   \n",
       "224997           0         250.0      0        cal  ...  -4.425781  -3.767578   \n",
       "224998           0         250.0      0        cal  ...  -4.425781  -4.269531   \n",
       "224999           0         250.0      0        cal  ...  -4.179688  -4.019531   \n",
       "\n",
       "            RLTe       LLOc       RLOc       MiOc        A2        HEOG  \\\n",
       "0       1.480469 -13.414062 -18.937500 -20.515625  5.660156   98.875000   \n",
       "1      -2.466797 -17.640625 -17.468750 -11.257812  1.968750  104.750000   \n",
       "2       3.947266 -15.648438 -10.085938  -7.882812  8.367188  102.062500   \n",
       "3       9.867188 -14.906250  -7.378906  -6.212891  9.351562  100.562500   \n",
       "4       9.125000 -10.679688  -6.886719 -12.062500  8.125000   98.375000   \n",
       "...          ...        ...        ...        ...       ...         ...   \n",
       "224995 -4.441406  -4.718750  -4.671875   0.392578 -4.429688   -4.406250   \n",
       "224996 -4.195312  -4.222656  -4.425781   0.148438 -4.429688   -4.160156   \n",
       "224997 -4.441406  -3.974609  -4.425781   0.392578 -4.429688   -4.160156   \n",
       "224998 -4.195312  -4.222656  -4.425781  -0.093750 -4.429688   -4.406250   \n",
       "224999 -3.947266  -4.222656  -4.179688   0.646484 -4.183594   -4.406250   \n",
       "\n",
       "              rle        rhz  \n",
       "0      -39.500000  38.375000  \n",
       "1      -38.031250  41.281250  \n",
       "2      -33.656250  43.718750  \n",
       "3      -42.906250  37.406250  \n",
       "4      -43.875000  37.906250  \n",
       "...           ...        ...  \n",
       "224995  -3.900391  -4.371094  \n",
       "224996  -3.412109  -4.371094  \n",
       "224997  -3.900391  -4.859375  \n",
       "224998  -3.900391  -4.371094  \n",
       "224999  -3.412109  -4.371094  \n",
       "\n",
       "[225000 rows x 47 columns]"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# vertex location is MiCe\n",
    "epf.re_reference(\n",
    "    epochs_df, \n",
    "    eeg_channels, \n",
    "    'MiCe',\n",
    "    \"new_common\", \n",
    "    epoch_id='epoch_id', \n",
    "    time='time_ms'\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Common average reference\n",
    "\n",
    "Note: for demonstration only, a real application would use all scalp locations"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "\n",
       "    .dataframe tbody tr th {\n",
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       "    }\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>epoch_id</th>\n",
       "      <th>time_ms</th>\n",
       "      <th>sub_id</th>\n",
       "      <th>eeg_artifact</th>\n",
       "      <th>dblock_path</th>\n",
       "      <th>log_evcodes</th>\n",
       "      <th>log_ccodes</th>\n",
       "      <th>dblock_srate</th>\n",
       "      <th>ccode</th>\n",
       "      <th>instrument</th>\n",
       "      <th>...</th>\n",
       "      <th>RMOc</th>\n",
       "      <th>LLTe</th>\n",
       "      <th>RLTe</th>\n",
       "      <th>LLOc</th>\n",
       "      <th>RLOc</th>\n",
       "      <th>MiOc</th>\n",
       "      <th>A2</th>\n",
       "      <th>HEOG</th>\n",
       "      <th>rle</th>\n",
       "      <th>rhz</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>-748</td>\n",
       "      <td>sub000</td>\n",
       "      <td>0</td>\n",
       "      <td>sub000/dblock_0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>250.0</td>\n",
       "      <td>1</td>\n",
       "      <td>eeg</td>\n",
       "      <td>...</td>\n",
       "      <td>-25.093750</td>\n",
       "      <td>-0.753906</td>\n",
       "      <td>1.480469</td>\n",
       "      <td>-13.414062</td>\n",
       "      <td>-18.937500</td>\n",
       "      <td>-3.210156</td>\n",
       "      <td>5.660156</td>\n",
       "      <td>98.875000</td>\n",
       "      <td>-39.500000</td>\n",
       "      <td>38.375000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0</td>\n",
       "      <td>-744</td>\n",
       "      <td>sub000</td>\n",
       "      <td>0</td>\n",
       "      <td>sub000/dblock_0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>250.0</td>\n",
       "      <td>1</td>\n",
       "      <td>eeg</td>\n",
       "      <td>...</td>\n",
       "      <td>-24.593750</td>\n",
       "      <td>0.502441</td>\n",
       "      <td>-2.466797</td>\n",
       "      <td>-17.640625</td>\n",
       "      <td>-17.468750</td>\n",
       "      <td>1.857813</td>\n",
       "      <td>1.968750</td>\n",
       "      <td>104.750000</td>\n",
       "      <td>-38.031250</td>\n",
       "      <td>41.281250</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0</td>\n",
       "      <td>-740</td>\n",
       "      <td>sub000</td>\n",
       "      <td>0</td>\n",
       "      <td>sub000/dblock_0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>250.0</td>\n",
       "      <td>1</td>\n",
       "      <td>eeg</td>\n",
       "      <td>...</td>\n",
       "      <td>-16.484375</td>\n",
       "      <td>-1.507812</td>\n",
       "      <td>3.947266</td>\n",
       "      <td>-15.648438</td>\n",
       "      <td>-10.085938</td>\n",
       "      <td>2.100781</td>\n",
       "      <td>8.367188</td>\n",
       "      <td>102.062500</td>\n",
       "      <td>-33.656250</td>\n",
       "      <td>43.718750</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0</td>\n",
       "      <td>-736</td>\n",
       "      <td>sub000</td>\n",
       "      <td>0</td>\n",
       "      <td>sub000/dblock_0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>250.0</td>\n",
       "      <td>1</td>\n",
       "      <td>eeg</td>\n",
       "      <td>...</td>\n",
       "      <td>-11.804688</td>\n",
       "      <td>-15.070312</td>\n",
       "      <td>9.867188</td>\n",
       "      <td>-14.906250</td>\n",
       "      <td>-7.378906</td>\n",
       "      <td>3.550977</td>\n",
       "      <td>9.351562</td>\n",
       "      <td>100.562500</td>\n",
       "      <td>-42.906250</td>\n",
       "      <td>37.406250</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0</td>\n",
       "      <td>-732</td>\n",
       "      <td>sub000</td>\n",
       "      <td>0</td>\n",
       "      <td>sub000/dblock_0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>250.0</td>\n",
       "      <td>1</td>\n",
       "      <td>eeg</td>\n",
       "      <td>...</td>\n",
       "      <td>-6.394531</td>\n",
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       "      <td>9.125000</td>\n",
       "      <td>-10.679688</td>\n",
       "      <td>-6.886719</td>\n",
       "      <td>0.596875</td>\n",
       "      <td>8.125000</td>\n",
       "      <td>98.375000</td>\n",
       "      <td>-43.875000</td>\n",
       "      <td>37.906250</td>\n",
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       "      <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",
       "      <td>...</td>\n",
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       "    <tr>\n",
       "      <th>224995</th>\n",
       "      <td>600</td>\n",
       "      <td>732</td>\n",
       "      <td>sub000</td>\n",
       "      <td>0</td>\n",
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       "      <td>0</td>\n",
       "      <td>250.0</td>\n",
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       "      <td>cal</td>\n",
       "      <td>...</td>\n",
       "      <td>-4.671875</td>\n",
       "      <td>-3.517578</td>\n",
       "      <td>-4.441406</td>\n",
       "      <td>-4.718750</td>\n",
       "      <td>-4.671875</td>\n",
       "      <td>0.482812</td>\n",
       "      <td>-4.429688</td>\n",
       "      <td>-4.406250</td>\n",
       "      <td>-3.900391</td>\n",
       "      <td>-4.371094</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>224996</th>\n",
       "      <td>600</td>\n",
       "      <td>736</td>\n",
       "      <td>sub000</td>\n",
       "      <td>0</td>\n",
       "      <td>sub000/dblock_4</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>250.0</td>\n",
       "      <td>0</td>\n",
       "      <td>cal</td>\n",
       "      <td>...</td>\n",
       "      <td>-4.179688</td>\n",
       "      <td>-4.019531</td>\n",
       "      <td>-4.195312</td>\n",
       "      <td>-4.222656</td>\n",
       "      <td>-4.425781</td>\n",
       "      <td>0.287500</td>\n",
       "      <td>-4.429688</td>\n",
       "      <td>-4.160156</td>\n",
       "      <td>-3.412109</td>\n",
       "      <td>-4.371094</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>224997</th>\n",
       "      <td>600</td>\n",
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       "      <td>sub000/dblock_4</td>\n",
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       "      <td>0</td>\n",
       "      <td>250.0</td>\n",
       "      <td>0</td>\n",
       "      <td>cal</td>\n",
       "      <td>...</td>\n",
       "      <td>-4.425781</td>\n",
       "      <td>-3.767578</td>\n",
       "      <td>-4.441406</td>\n",
       "      <td>-3.974609</td>\n",
       "      <td>-4.425781</td>\n",
       "      <td>0.482812</td>\n",
       "      <td>-4.429688</td>\n",
       "      <td>-4.160156</td>\n",
       "      <td>-3.900391</td>\n",
       "      <td>-4.859375</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>224998</th>\n",
       "      <td>600</td>\n",
       "      <td>744</td>\n",
       "      <td>sub000</td>\n",
       "      <td>0</td>\n",
       "      <td>sub000/dblock_4</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>250.0</td>\n",
       "      <td>0</td>\n",
       "      <td>cal</td>\n",
       "      <td>...</td>\n",
       "      <td>-4.425781</td>\n",
       "      <td>-4.269531</td>\n",
       "      <td>-4.195312</td>\n",
       "      <td>-4.222656</td>\n",
       "      <td>-4.425781</td>\n",
       "      <td>0.093750</td>\n",
       "      <td>-4.429688</td>\n",
       "      <td>-4.406250</td>\n",
       "      <td>-3.900391</td>\n",
       "      <td>-4.371094</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>224999</th>\n",
       "      <td>600</td>\n",
       "      <td>748</td>\n",
       "      <td>sub000</td>\n",
       "      <td>0</td>\n",
       "      <td>sub000/dblock_4</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>250.0</td>\n",
       "      <td>0</td>\n",
       "      <td>cal</td>\n",
       "      <td>...</td>\n",
       "      <td>-4.179688</td>\n",
       "      <td>-4.019531</td>\n",
       "      <td>-3.947266</td>\n",
       "      <td>-4.222656</td>\n",
       "      <td>-4.179688</td>\n",
       "      <td>0.436719</td>\n",
       "      <td>-4.183594</td>\n",
       "      <td>-4.406250</td>\n",
       "      <td>-3.412109</td>\n",
       "      <td>-4.371094</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>225000 rows × 47 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        epoch_id  time_ms  sub_id  eeg_artifact      dblock_path  log_evcodes  \\\n",
       "0              0     -748  sub000             0  sub000/dblock_0            0   \n",
       "1              0     -744  sub000             0  sub000/dblock_0            0   \n",
       "2              0     -740  sub000             0  sub000/dblock_0            0   \n",
       "3              0     -736  sub000             0  sub000/dblock_0            0   \n",
       "4              0     -732  sub000             0  sub000/dblock_0            0   \n",
       "...          ...      ...     ...           ...              ...          ...   \n",
       "224995       600      732  sub000             0  sub000/dblock_4            0   \n",
       "224996       600      736  sub000             0  sub000/dblock_4            0   \n",
       "224997       600      740  sub000             0  sub000/dblock_4            0   \n",
       "224998       600      744  sub000             0  sub000/dblock_4            0   \n",
       "224999       600      748  sub000             0  sub000/dblock_4            0   \n",
       "\n",
       "        log_ccodes  dblock_srate  ccode instrument  ...       RMOc       LLTe  \\\n",
       "0                0         250.0      1        eeg  ... -25.093750  -0.753906   \n",
       "1                0         250.0      1        eeg  ... -24.593750   0.502441   \n",
       "2                0         250.0      1        eeg  ... -16.484375  -1.507812   \n",
       "3                0         250.0      1        eeg  ... -11.804688 -15.070312   \n",
       "4                0         250.0      1        eeg  ...  -6.394531  -4.019531   \n",
       "...            ...           ...    ...        ...  ...        ...        ...   \n",
       "224995           0         250.0      0        cal  ...  -4.671875  -3.517578   \n",
       "224996           0         250.0      0        cal  ...  -4.179688  -4.019531   \n",
       "224997           0         250.0      0        cal  ...  -4.425781  -3.767578   \n",
       "224998           0         250.0      0        cal  ...  -4.425781  -4.269531   \n",
       "224999           0         250.0      0        cal  ...  -4.179688  -4.019531   \n",
       "\n",
       "            RLTe       LLOc       RLOc      MiOc        A2        HEOG  \\\n",
       "0       1.480469 -13.414062 -18.937500 -3.210156  5.660156   98.875000   \n",
       "1      -2.466797 -17.640625 -17.468750  1.857813  1.968750  104.750000   \n",
       "2       3.947266 -15.648438 -10.085938  2.100781  8.367188  102.062500   \n",
       "3       9.867188 -14.906250  -7.378906  3.550977  9.351562  100.562500   \n",
       "4       9.125000 -10.679688  -6.886719  0.596875  8.125000   98.375000   \n",
       "...          ...        ...        ...       ...       ...         ...   \n",
       "224995 -4.441406  -4.718750  -4.671875  0.482812 -4.429688   -4.406250   \n",
       "224996 -4.195312  -4.222656  -4.425781  0.287500 -4.429688   -4.160156   \n",
       "224997 -4.441406  -3.974609  -4.425781  0.482812 -4.429688   -4.160156   \n",
       "224998 -4.195312  -4.222656  -4.425781  0.093750 -4.429688   -4.406250   \n",
       "224999 -3.947266  -4.222656  -4.179688  0.436719 -4.183594   -4.406250   \n",
       "\n",
       "              rle        rhz  \n",
       "0      -39.500000  38.375000  \n",
       "1      -38.031250  41.281250  \n",
       "2      -33.656250  43.718750  \n",
       "3      -42.906250  37.406250  \n",
       "4      -43.875000  37.906250  \n",
       "...           ...        ...  \n",
       "224995  -3.900391  -4.371094  \n",
       "224996  -3.412109  -4.371094  \n",
       "224997  -3.900391  -4.859375  \n",
       "224998  -3.900391  -4.371094  \n",
       "224999  -3.412109  -4.371094  \n",
       "\n",
       "[225000 rows x 47 columns]"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "reference_channels = [\"MiPf\", \"MiCe\", \"MiPa\", \"MiOc\", \"A2\"]\n",
    "epf.re_reference(\n",
    "    epochs_df, \n",
    "    eeg_channels, \n",
    "    reference_channels ,\n",
    "    \"common_average\", \n",
    "    epoch_id='epoch_id', \n",
    "    time='time_ms'\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Center EEG data in an interval (baseline)\n",
    "\n",
    "> The `start` and `stop` interval units are the same as the time channel"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>epoch_id</th>\n",
       "      <th>time_ms</th>\n",
       "      <th>sub_id</th>\n",
       "      <th>eeg_artifact</th>\n",
       "      <th>dblock_path</th>\n",
       "      <th>log_evcodes</th>\n",
       "      <th>log_ccodes</th>\n",
       "      <th>dblock_srate</th>\n",
       "      <th>ccode</th>\n",
       "      <th>instrument</th>\n",
       "      <th>...</th>\n",
       "      <th>RMOc</th>\n",
       "      <th>LLTe</th>\n",
       "      <th>RLTe</th>\n",
       "      <th>LLOc</th>\n",
       "      <th>RLOc</th>\n",
       "      <th>MiOc</th>\n",
       "      <th>A2</th>\n",
       "      <th>HEOG</th>\n",
       "      <th>rle</th>\n",
       "      <th>rhz</th>\n",
       "    </tr>\n",
       "  </thead>\n",
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       "      <td>0</td>\n",
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       "      <td>250.0</td>\n",
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       "      <td>...</td>\n",
       "      <td>-25.093750</td>\n",
       "      <td>-0.753906</td>\n",
       "      <td>1.480469</td>\n",
       "      <td>-13.414062</td>\n",
       "      <td>-18.937500</td>\n",
       "      <td>-23.419617</td>\n",
       "      <td>5.660156</td>\n",
       "      <td>98.875000</td>\n",
       "      <td>-39.500000</td>\n",
       "      <td>38.375000</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
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       "      <td>-744</td>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>250.0</td>\n",
       "      <td>1</td>\n",
       "      <td>eeg</td>\n",
       "      <td>...</td>\n",
       "      <td>-24.593750</td>\n",
       "      <td>0.502441</td>\n",
       "      <td>-2.466797</td>\n",
       "      <td>-17.640625</td>\n",
       "      <td>-17.468750</td>\n",
       "      <td>-20.989929</td>\n",
       "      <td>1.968750</td>\n",
       "      <td>104.750000</td>\n",
       "      <td>-38.031250</td>\n",
       "      <td>41.281250</td>\n",
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       "    <tr>\n",
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       "      <td>sub000/dblock_0</td>\n",
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       "      <td>0</td>\n",
       "      <td>250.0</td>\n",
       "      <td>1</td>\n",
       "      <td>eeg</td>\n",
       "      <td>...</td>\n",
       "      <td>-16.484375</td>\n",
       "      <td>-1.507812</td>\n",
       "      <td>3.947266</td>\n",
       "      <td>-15.648438</td>\n",
       "      <td>-10.085938</td>\n",
       "      <td>-16.857117</td>\n",
       "      <td>8.367188</td>\n",
       "      <td>102.062500</td>\n",
       "      <td>-33.656250</td>\n",
       "      <td>43.718750</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0</td>\n",
       "      <td>-736</td>\n",
       "      <td>sub000</td>\n",
       "      <td>0</td>\n",
       "      <td>sub000/dblock_0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>250.0</td>\n",
       "      <td>1</td>\n",
       "      <td>eeg</td>\n",
       "      <td>...</td>\n",
       "      <td>-11.804688</td>\n",
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       "      <td>-14.906250</td>\n",
       "      <td>-7.378906</td>\n",
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       "      <td>-42.906250</td>\n",
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       "      <td>0</td>\n",
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       "      <td>250.0</td>\n",
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       "      <td>0</td>\n",
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       "      <td>-4.160156</td>\n",
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       "      <td>-4.859375</td>\n",
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       "    <tr>\n",
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       "      <td>0</td>\n",
       "      <td>sub000/dblock_4</td>\n",
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       "      <td>250.0</td>\n",
       "      <td>0</td>\n",
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       "      <td>...</td>\n",
       "      <td>-4.425781</td>\n",
       "      <td>-4.269531</td>\n",
       "      <td>-4.195312</td>\n",
       "      <td>-4.222656</td>\n",
       "      <td>-4.425781</td>\n",
       "      <td>-3.908455</td>\n",
       "      <td>-4.429688</td>\n",
       "      <td>-4.406250</td>\n",
       "      <td>-3.900391</td>\n",
       "      <td>-4.371094</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>224999</th>\n",
       "      <td>600</td>\n",
       "      <td>748</td>\n",
       "      <td>sub000</td>\n",
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       "      <td>sub000/dblock_4</td>\n",
       "      <td>0</td>\n",
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       "      <td>-4.179688</td>\n",
       "      <td>-4.019531</td>\n",
       "      <td>-3.947266</td>\n",
       "      <td>-4.222656</td>\n",
       "      <td>-4.179688</td>\n",
       "      <td>-3.422127</td>\n",
       "      <td>-4.183594</td>\n",
       "      <td>-4.406250</td>\n",
       "      <td>-3.412109</td>\n",
       "      <td>-4.371094</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>225000 rows × 47 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        epoch_id  time_ms  sub_id  eeg_artifact      dblock_path  log_evcodes  \\\n",
       "0              0     -748  sub000             0  sub000/dblock_0            0   \n",
       "1              0     -744  sub000             0  sub000/dblock_0            0   \n",
       "2              0     -740  sub000             0  sub000/dblock_0            0   \n",
       "3              0     -736  sub000             0  sub000/dblock_0            0   \n",
       "4              0     -732  sub000             0  sub000/dblock_0            0   \n",
       "...          ...      ...     ...           ...              ...          ...   \n",
       "224995       600      732  sub000             0  sub000/dblock_4            0   \n",
       "224996       600      736  sub000             0  sub000/dblock_4            0   \n",
       "224997       600      740  sub000             0  sub000/dblock_4            0   \n",
       "224998       600      744  sub000             0  sub000/dblock_4            0   \n",
       "224999       600      748  sub000             0  sub000/dblock_4            0   \n",
       "\n",
       "        log_ccodes  dblock_srate  ccode instrument  ...       RMOc       LLTe  \\\n",
       "0                0         250.0      1        eeg  ... -25.093750  -0.753906   \n",
       "1                0         250.0      1        eeg  ... -24.593750   0.502441   \n",
       "2                0         250.0      1        eeg  ... -16.484375  -1.507812   \n",
       "3                0         250.0      1        eeg  ... -11.804688 -15.070312   \n",
       "4                0         250.0      1        eeg  ...  -6.394531  -4.019531   \n",
       "...            ...           ...    ...        ...  ...        ...        ...   \n",
       "224995           0         250.0      0        cal  ...  -4.671875  -3.517578   \n",
       "224996           0         250.0      0        cal  ...  -4.179688  -4.019531   \n",
       "224997           0         250.0      0        cal  ...  -4.425781  -3.767578   \n",
       "224998           0         250.0      0        cal  ...  -4.425781  -4.269531   \n",
       "224999           0         250.0      0        cal  ...  -4.179688  -4.019531   \n",
       "\n",
       "            RLTe       LLOc       RLOc       MiOc        A2        HEOG  \\\n",
       "0       1.480469 -13.414062 -18.937500 -23.419617  5.660156   98.875000   \n",
       "1      -2.466797 -17.640625 -17.468750 -20.989929  1.968750  104.750000   \n",
       "2       3.947266 -15.648438 -10.085938 -16.857117  8.367188  102.062500   \n",
       "3       9.867188 -14.906250  -7.378906 -14.427429  9.351562  100.562500   \n",
       "4       9.125000 -10.679688  -6.886719 -13.700867  8.125000   98.375000   \n",
       "...          ...        ...        ...        ...       ...         ...   \n",
       "224995 -4.441406  -4.718750  -4.671875  -3.422127 -4.429688   -4.406250   \n",
       "224996 -4.195312  -4.222656  -4.425781  -3.666268 -4.429688   -4.160156   \n",
       "224997 -4.441406  -3.974609  -4.425781  -3.422127 -4.429688   -4.160156   \n",
       "224998 -4.195312  -4.222656  -4.425781  -3.908455 -4.429688   -4.406250   \n",
       "224999 -3.947266  -4.222656  -4.179688  -3.422127 -4.183594   -4.406250   \n",
       "\n",
       "              rle        rhz  \n",
       "0      -39.500000  38.375000  \n",
       "1      -38.031250  41.281250  \n",
       "2      -33.656250  43.718750  \n",
       "3      -42.906250  37.406250  \n",
       "4      -43.875000  37.906250  \n",
       "...           ...        ...  \n",
       "224995  -3.900391  -4.371094  \n",
       "224996  -3.412109  -4.371094  \n",
       "224997  -3.900391  -4.859375  \n",
       "224998  -3.900391  -4.371094  \n",
       "224999  -3.412109  -4.371094  \n",
       "\n",
       "[225000 rows x 47 columns]"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "start = -500\n",
    "stop = -4\n",
    "centered_eeg_df = epf.center_eeg(\n",
    "    epochs_df, \n",
    "    eeg_channels, \n",
    "    start, \n",
    "    stop, \n",
    "    epoch_id='epoch_id', \n",
    "    time='time_ms'\n",
    ")\n",
    "centered_eeg_df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Exclude previously tagged artifacts\n",
    "\n",
    "This special-purpose filter drops entire epochs where the time-locking event at time 0 is tagged as bad for some reason on the specified `bads_column`. \n",
    "\n",
    "This implements a simple convention for pruning epochs based on tags generated by artifact screening functions.\n",
    "\n",
    "Any column can be used or constructed for this purpose."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Example: drop all epochs where `eeg_artifact` is other than 0 at `time_ms` == 0 "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Total number of epoch ids:  600\n",
      "Number of good epoch ids:  542\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>epoch_id</th>\n",
       "      <th>time_ms</th>\n",
       "      <th>sub_id</th>\n",
       "      <th>eeg_artifact</th>\n",
       "      <th>dblock_path</th>\n",
       "      <th>log_evcodes</th>\n",
       "      <th>log_ccodes</th>\n",
       "      <th>dblock_srate</th>\n",
       "      <th>ccode</th>\n",
       "      <th>instrument</th>\n",
       "      <th>...</th>\n",
       "      <th>RMOc</th>\n",
       "      <th>LLTe</th>\n",
       "      <th>RLTe</th>\n",
       "      <th>LLOc</th>\n",
       "      <th>RLOc</th>\n",
       "      <th>MiOc</th>\n",
       "      <th>A2</th>\n",
       "      <th>HEOG</th>\n",
       "      <th>rle</th>\n",
       "      <th>rhz</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>-748</td>\n",
       "      <td>sub000</td>\n",
       "      <td>0</td>\n",
       "      <td>sub000/dblock_0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>250.0</td>\n",
       "      <td>1</td>\n",
       "      <td>eeg</td>\n",
       "      <td>...</td>\n",
       "      <td>-25.093750</td>\n",
       "      <td>-0.753906</td>\n",
       "      <td>1.480469</td>\n",
       "      <td>-13.414062</td>\n",
       "      <td>-18.937500</td>\n",
       "      <td>-17.734375</td>\n",
       "      <td>5.660156</td>\n",
       "      <td>98.875000</td>\n",
       "      <td>-39.500000</td>\n",
       "      <td>38.375000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0</td>\n",
       "      <td>-744</td>\n",
       "      <td>sub000</td>\n",
       "      <td>0</td>\n",
       "      <td>sub000/dblock_0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>250.0</td>\n",
       "      <td>1</td>\n",
       "      <td>eeg</td>\n",
       "      <td>...</td>\n",
       "      <td>-24.593750</td>\n",
       "      <td>0.502441</td>\n",
       "      <td>-2.466797</td>\n",
       "      <td>-17.640625</td>\n",
       "      <td>-17.468750</td>\n",
       "      <td>-15.304688</td>\n",
       "      <td>1.968750</td>\n",
       "      <td>104.750000</td>\n",
       "      <td>-38.031250</td>\n",
       "      <td>41.281250</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0</td>\n",
       "      <td>-740</td>\n",
       "      <td>sub000</td>\n",
       "      <td>0</td>\n",
       "      <td>sub000/dblock_0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>250.0</td>\n",
       "      <td>1</td>\n",
       "      <td>eeg</td>\n",
       "      <td>...</td>\n",
       "      <td>-16.484375</td>\n",
       "      <td>-1.507812</td>\n",
       "      <td>3.947266</td>\n",
       "      <td>-15.648438</td>\n",
       "      <td>-10.085938</td>\n",
       "      <td>-11.171875</td>\n",
       "      <td>8.367188</td>\n",
       "      <td>102.062500</td>\n",
       "      <td>-33.656250</td>\n",
       "      <td>43.718750</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0</td>\n",
       "      <td>-736</td>\n",
       "      <td>sub000</td>\n",
       "      <td>0</td>\n",
       "      <td>sub000/dblock_0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>250.0</td>\n",
       "      <td>1</td>\n",
       "      <td>eeg</td>\n",
       "      <td>...</td>\n",
       "      <td>-11.804688</td>\n",
       "      <td>-15.070312</td>\n",
       "      <td>9.867188</td>\n",
       "      <td>-14.906250</td>\n",
       "      <td>-7.378906</td>\n",
       "      <td>-8.742188</td>\n",
       "      <td>9.351562</td>\n",
       "      <td>100.562500</td>\n",
       "      <td>-42.906250</td>\n",
       "      <td>37.406250</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0</td>\n",
       "      <td>-732</td>\n",
       "      <td>sub000</td>\n",
       "      <td>0</td>\n",
       "      <td>sub000/dblock_0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>250.0</td>\n",
       "      <td>1</td>\n",
       "      <td>eeg</td>\n",
       "      <td>...</td>\n",
       "      <td>-6.394531</td>\n",
       "      <td>-4.019531</td>\n",
       "      <td>9.125000</td>\n",
       "      <td>-10.679688</td>\n",
       "      <td>-6.886719</td>\n",
       "      <td>-8.015625</td>\n",
       "      <td>8.125000</td>\n",
       "      <td>98.375000</td>\n",
       "      <td>-43.875000</td>\n",
       "      <td>37.906250</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",
       "      <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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>224995</th>\n",
       "      <td>600</td>\n",
       "      <td>732</td>\n",
       "      <td>sub000</td>\n",
       "      <td>0</td>\n",
       "      <td>sub000/dblock_4</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>250.0</td>\n",
       "      <td>0</td>\n",
       "      <td>cal</td>\n",
       "      <td>...</td>\n",
       "      <td>-4.671875</td>\n",
       "      <td>-3.517578</td>\n",
       "      <td>-4.441406</td>\n",
       "      <td>-4.718750</td>\n",
       "      <td>-4.671875</td>\n",
       "      <td>-3.400391</td>\n",
       "      <td>-4.429688</td>\n",
       "      <td>-4.406250</td>\n",
       "      <td>-3.900391</td>\n",
       "      <td>-4.371094</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>224996</th>\n",
       "      <td>600</td>\n",
       "      <td>736</td>\n",
       "      <td>sub000</td>\n",
       "      <td>0</td>\n",
       "      <td>sub000/dblock_4</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>250.0</td>\n",
       "      <td>0</td>\n",
       "      <td>cal</td>\n",
       "      <td>...</td>\n",
       "      <td>-4.179688</td>\n",
       "      <td>-4.019531</td>\n",
       "      <td>-4.195312</td>\n",
       "      <td>-4.222656</td>\n",
       "      <td>-4.425781</td>\n",
       "      <td>-3.644531</td>\n",
       "      <td>-4.429688</td>\n",
       "      <td>-4.160156</td>\n",
       "      <td>-3.412109</td>\n",
       "      <td>-4.371094</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>224997</th>\n",
       "      <td>600</td>\n",
       "      <td>740</td>\n",
       "      <td>sub000</td>\n",
       "      <td>0</td>\n",
       "      <td>sub000/dblock_4</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>250.0</td>\n",
       "      <td>0</td>\n",
       "      <td>cal</td>\n",
       "      <td>...</td>\n",
       "      <td>-4.425781</td>\n",
       "      <td>-3.767578</td>\n",
       "      <td>-4.441406</td>\n",
       "      <td>-3.974609</td>\n",
       "      <td>-4.425781</td>\n",
       "      <td>-3.400391</td>\n",
       "      <td>-4.429688</td>\n",
       "      <td>-4.160156</td>\n",
       "      <td>-3.900391</td>\n",
       "      <td>-4.859375</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>224998</th>\n",
       "      <td>600</td>\n",
       "      <td>744</td>\n",
       "      <td>sub000</td>\n",
       "      <td>0</td>\n",
       "      <td>sub000/dblock_4</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>250.0</td>\n",
       "      <td>0</td>\n",
       "      <td>cal</td>\n",
       "      <td>...</td>\n",
       "      <td>-4.425781</td>\n",
       "      <td>-4.269531</td>\n",
       "      <td>-4.195312</td>\n",
       "      <td>-4.222656</td>\n",
       "      <td>-4.425781</td>\n",
       "      <td>-3.886719</td>\n",
       "      <td>-4.429688</td>\n",
       "      <td>-4.406250</td>\n",
       "      <td>-3.900391</td>\n",
       "      <td>-4.371094</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>224999</th>\n",
       "      <td>600</td>\n",
       "      <td>748</td>\n",
       "      <td>sub000</td>\n",
       "      <td>0</td>\n",
       "      <td>sub000/dblock_4</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>250.0</td>\n",
       "      <td>0</td>\n",
       "      <td>cal</td>\n",
       "      <td>...</td>\n",
       "      <td>-4.179688</td>\n",
       "      <td>-4.019531</td>\n",
       "      <td>-3.947266</td>\n",
       "      <td>-4.222656</td>\n",
       "      <td>-4.179688</td>\n",
       "      <td>-3.400391</td>\n",
       "      <td>-4.183594</td>\n",
       "      <td>-4.406250</td>\n",
       "      <td>-3.412109</td>\n",
       "      <td>-4.371094</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>203250 rows × 47 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        epoch_id  time_ms  sub_id  eeg_artifact      dblock_path  log_evcodes  \\\n",
       "0              0     -748  sub000             0  sub000/dblock_0            0   \n",
       "1              0     -744  sub000             0  sub000/dblock_0            0   \n",
       "2              0     -740  sub000             0  sub000/dblock_0            0   \n",
       "3              0     -736  sub000             0  sub000/dblock_0            0   \n",
       "4              0     -732  sub000             0  sub000/dblock_0            0   \n",
       "...          ...      ...     ...           ...              ...          ...   \n",
       "224995       600      732  sub000             0  sub000/dblock_4            0   \n",
       "224996       600      736  sub000             0  sub000/dblock_4            0   \n",
       "224997       600      740  sub000             0  sub000/dblock_4            0   \n",
       "224998       600      744  sub000             0  sub000/dblock_4            0   \n",
       "224999       600      748  sub000             0  sub000/dblock_4            0   \n",
       "\n",
       "        log_ccodes  dblock_srate  ccode instrument  ...       RMOc       LLTe  \\\n",
       "0                0         250.0      1        eeg  ... -25.093750  -0.753906   \n",
       "1                0         250.0      1        eeg  ... -24.593750   0.502441   \n",
       "2                0         250.0      1        eeg  ... -16.484375  -1.507812   \n",
       "3                0         250.0      1        eeg  ... -11.804688 -15.070312   \n",
       "4                0         250.0      1        eeg  ...  -6.394531  -4.019531   \n",
       "...            ...           ...    ...        ...  ...        ...        ...   \n",
       "224995           0         250.0      0        cal  ...  -4.671875  -3.517578   \n",
       "224996           0         250.0      0        cal  ...  -4.179688  -4.019531   \n",
       "224997           0         250.0      0        cal  ...  -4.425781  -3.767578   \n",
       "224998           0         250.0      0        cal  ...  -4.425781  -4.269531   \n",
       "224999           0         250.0      0        cal  ...  -4.179688  -4.019531   \n",
       "\n",
       "            RLTe       LLOc       RLOc       MiOc        A2        HEOG  \\\n",
       "0       1.480469 -13.414062 -18.937500 -17.734375  5.660156   98.875000   \n",
       "1      -2.466797 -17.640625 -17.468750 -15.304688  1.968750  104.750000   \n",
       "2       3.947266 -15.648438 -10.085938 -11.171875  8.367188  102.062500   \n",
       "3       9.867188 -14.906250  -7.378906  -8.742188  9.351562  100.562500   \n",
       "4       9.125000 -10.679688  -6.886719  -8.015625  8.125000   98.375000   \n",
       "...          ...        ...        ...        ...       ...         ...   \n",
       "224995 -4.441406  -4.718750  -4.671875  -3.400391 -4.429688   -4.406250   \n",
       "224996 -4.195312  -4.222656  -4.425781  -3.644531 -4.429688   -4.160156   \n",
       "224997 -4.441406  -3.974609  -4.425781  -3.400391 -4.429688   -4.160156   \n",
       "224998 -4.195312  -4.222656  -4.425781  -3.886719 -4.429688   -4.406250   \n",
       "224999 -3.947266  -4.222656  -4.179688  -3.400391 -4.183594   -4.406250   \n",
       "\n",
       "              rle        rhz  \n",
       "0      -39.500000  38.375000  \n",
       "1      -38.031250  41.281250  \n",
       "2      -33.656250  43.718750  \n",
       "3      -42.906250  37.406250  \n",
       "4      -43.875000  37.906250  \n",
       "...           ...        ...  \n",
       "224995  -3.900391  -4.371094  \n",
       "224996  -3.412109  -4.371094  \n",
       "224997  -3.900391  -4.859375  \n",
       "224998  -3.900391  -4.371094  \n",
       "224999  -3.412109  -4.371094  \n",
       "\n",
       "[203250 rows x 47 columns]"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "good_epochs = epf.drop_bad_epochs(\n",
    "    epochs_df, \n",
    "    bads_column=\"eeg_artifact\",\n",
    "    epoch_id='epoch_id', \n",
    "    time='time_ms',\n",
    ")\n",
    "\n",
    "print(\"Total number of epoch ids: \", len(epochs_df[\"epoch_id\"].unique()))\n",
    "print(\"Number of good epoch ids: \", len(good_epochs[\"epoch_id\"].unique()))\n",
    "good_epochs"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Filter EEG epochs: "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Configure the filter**\n",
    "\n",
    "If left unspecified in `show_filter()` the optional parameters `width_hz`, `ripple_db` and `window` default to reasonable values.\n",
    "\n",
    "However, to **apply** the filter **all** parameters must be explicitly specified. You can use the defaults or something else."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/mnt/cube/home/turbach/TPU_Projects/spudtr/spudtr/filters.py:492: UserWarning: using default window='kaiser'\n",
      "  warnings.warn(f\"using default window='{window}'\")\n",
      "/mnt/cube/home/turbach/TPU_Projects/spudtr/spudtr/filters.py:504: UserWarning: using default width_hz=5.000\n",
      "  warnings.warn(f\"using default width_hz={width_hz:0.3f}\")\n",
      "/mnt/cube/home/turbach/TPU_Projects/spudtr/spudtr/filters.py:508: UserWarning: using default ripple_db=53.000\n",
      "  warnings.warn(f\"using default ripple_db={ripple_db:0.3f}\")\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "lowpass filter\n",
      "sampling rate (samples / s): 250.000\n",
      "1/2 amplitude cutoff (Hz): 20.000\n",
      "transition width (Hz): 5.000\n",
      "ripple (dB): 53.000\n",
      "window: kaiser\n",
      "length (coefficients): 159\n",
      "delay (samples): 79\n",
      "edge distortion: first and last 0.3160 seconds of the data(= 79 samples at 250.0 samples / s)\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/mnt/cube/home/turbach/TPU_Projects/spudtr/spudtr/filters.py:885: UserWarning: linestyle is redundantly defined by the 'linestyle' keyword argument and the fmt string \".-\" (-> linestyle='-'). The keyword argument will take precedence.\n",
      "  ax.plot(t, y, \".-\", color=\"c\", linestyle=\"-\", label=\"input\")\n",
      "/mnt/cube/home/turbach/TPU_Projects/spudtr/spudtr/filters.py:886: UserWarning: linestyle is redundantly defined by the 'linestyle' keyword argument and the fmt string \".-\" (-> linestyle='-'). The keyword argument will take precedence.\n",
      "  ax.plot(t, y1, \".-\", color=\"b\", linestyle=\"-\", label=\"ideal output\")\n",
      "/mnt/cube/home/turbach/TPU_Projects/spudtr/spudtr/filters.py:887: UserWarning: linestyle is redundantly defined by the 'linestyle' keyword argument and the fmt string \".-\" (-> linestyle='-'). The keyword argument will take precedence.\n",
      "  ax.plot(\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 3 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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eX7Y24/YCll15Qtb95Xq9u+w4jI4Nm7Yb1C6lvyQDhf+/GiWuOe2d/X4WSvV5y/TdTvJ9SSn2d7Uc54VCE1lBiUDSXsAZwJnA68CdwMVmNjHhQRuB/wM+CKwAniAqSTwb2+Z4oquWjwcOAa43s0Ny7TffRDCQX46DQfqHL58vSX8yfUEH+qVPue70qVk/6G3z27nwzgVZnzulZWRfFU4hJ95qLBH0l5w61ndnTXrQ//s50O9IKT8LKaX8LNeafEtjUHgi6AV+D3wyNhfBi2a2R8KDHgp81cxmhMezAMzsitg2PwIeMbPbw+MlwJFmtirbfvNNBKkv9XlP/5I93vD+1SVRgm+kJKaMHUnLjtvWyXe81c2LHRvozfLzVxKjdtja9LX+b1vI9Bkf0tjA9IljMu4j4zEETUMaGTok2YBzG7q3MHL49k1wm7f00rWlZ5v3q6FB7NGy/WuNx/PCmg0ZX0f89WZ7rbmOkWvfBanns3MZvPi2Vn50QNQ8m6SkF5crEeRqLP4QUYngYUm/Bu4g+jcn1Qosjz1eQfSrv79tWoFtEoGkc4FzAXbfffc8QvBhfssi3y9+gpOFmbF0zVu0r+vqO/lu3tKb81drppNdthPdlp5eFi7vzHpiH97YQG8DdG/pYfiQRibs1JT1RJ2vjre6Wb62i+4tPUhieGMDq9d3s3p993bbZkocKemvN1eS7O01lq7O8H5m2XfBPAmUTTHPbbnmLL4HuEfSSGAm8AVgV0k/BO4xs7n97DtT0kj/mCTZBjO7CbgJohJBP8fdxm7NTbR3dvVlUVc5meqTp319Lus25q46mNIS1fenj96Z7rrTp/KutKLyROBTWY7RX1VPqcYDmgi8K9w//Ud/zrlttqqk1HsZf70TgeX9VJslaT9JP0bq/zWQdh9XfMUcwrzfcq6ZbTCz28zsRGA8sAC4LMG+VwATYo/HAysL2GZALpmxN01DG4u5y0GpIaTk1uYmrjt9KtedPpXW8EHLpxiYTdPQxoyNipeftF+//58XOjbwQkfuJNDa3JS1vrQzS6IpZIKZcssWY69Zxtc7c1pr3/8t8/O2vp+5ZPp/zZzWyjWnvbMo36f0z9tLV57AdadPpblp6ID3ne1YxfgcV4tiD2Ge5DqCPma2FvhRuPXnCWDPMIx1O1E100fStpkDXCDpDqJqozdytQ8UIvVBruVeQ9l6Cwy0xwTk7pFRrIa/JMcYyC/N/r4UqVJhukyTxXSs7+4bKvqwKx8qaTfDtvntfb/4sw1xPayxIWMyyPVrMNM8CvlolLI2RKaWleqzEP9s53uMJD3n0vdbT72GcknUfbTgnUe9gq4j6j56i5l9U9L5AGZ2Y+g++gPgWKLuo+eYWc6W4Hq9jiAfSbrLFvphyucLmk8/8EJ7riTtvphp30MaxMSdRvSdfNMv9oLCemckkSmmVLVNPJ6XXt9AT9pXNElMhVbj5HvdQSk+C+nHKNVnud4M+DqCauKJoDqU4oKdfE9exThpxU++hXbtLER/XVQzJSUobXJNklSzHccv3qp+hfYaci6reDG+mPsEEp28clVfZNv31Q8u2S4R9Fo0a1jLqOFlnWA+2z5TMSxf15WxTWTEsCF5vWZIVu02kJJPKT4Lrrzyn4XbuRKaOa2VK07dP2ejYbaG5/70d/It5wTz2faZiqFYSSlJA++YEUNLUv3laocnAld1Zk5rZcHlx2zTc6lRUZ+P1uamgk9auU7oHeu7mTCmqa+HSUqpJpjP1JutQdEk9x0ZridIKSQppZJrpvfyutOnMv8rx3gSqHPeRuDqRn915kMaxJbe8tVvx+vWUxpDz5JM38pSNVy7+pCrjcBLBK5upH4Zp34Rp9vSu3V47FRJoJQn3ZnTWrcrGfRkSQL5tok4lw9PBK6uzJzWSm+CUnBqYpdSSzqxTrYLyJwrBk8Eru4krWcvxzhVSY9RigZr51I8Ebi6k3TYkXKcfJMco1QN1s6leCJwdae/tgIo38m3v6TkbQOuHDwRuLqUq399OfvV57puotDrJZzLl19Z7OpWfEDClZ1d7Fah4RBSV+amupNWMhZXn2ruOgJJa4CXC3x6C9BRxHCKqVpjq9a4wGMrRLXGBdUbW7XGBfnFNtHMxmZaUXOJYCAkzct2QUWlVWts1RoXeGyFqNa4oHpjq9a4oHixeRuBc87VOU8EzjlX5+otEdxU6QByqNbYqjUu8NgKUa1xQfXGVq1xQZFiq6s2Auecc9urtxKBc865NJ4InHOuztVNIpB0rKQlkpZKuqyCcUyQ9LCk5yQtlvT5sHwnSb+R9Nfwd0wFY2yUNF/SfdUSm6RmSXdLej68d4dWQ1whti+E/+Uzkm6XtEOlYpN0i6TVkp6JLcsai6RZ4TuxRNKMMsd1dfh/Pi3pHknN5Y4rW2yxdRdLMkkt5Y4tW1ySPhuOvVjSt4sSl5kN+hvQCLwA7AEMAxYC+1YolnHAgeH+KOD/gH2BbwOXheWXAVdV8P36IvBz4L7wuOKxAT8DPhXuDwOaqySuVmAZ0BQe3wWcXanYgPcBBwLPxJZljCV87hYCw4HJ4TvSWMa4jgGGhPtXVSKubLGF5ROAB4kuYG2pkvfsKOC3wPDweJdixFUvJYKDgaVm9qKZbQLuAE6pRCBmtsrMngr31wPPEZ1MTiE62RH+zqxEfJLGAycAP44trmhskkYTfSl+AmBmm8yss9JxxQwBmiQNAUYAK6lQbGb2O2Bt2uJssZwC3GFm3Wa2DFhK9F0pS1xmNtfMtoSHjwHjyx1XttiCa4FL2XauoIq+Z8BngCvNrDtss7oYcdVLImgFlscerwjLKkrSJGAa8Diwq5mtgihZALtUKKzriD788dnTKx3bHsAa4KehyurHkkZWQVyYWTvwHeAVYBXwhpnNrYbYYrLFUk3fi08Avwr3Kx6XpJOBdjNbmLaq0rHtBbxX0uOSHpV0UDHiqpdEkGm84Yr2m5W0I/AL4EIze7OSsaRIOhFYbWZPVjqWNEOIisg/NLNpwAaiKo6KC/XtpxAVx3cDRkr6aGWjSqwqvheSvgRsAW5LLcqwWdnikjQC+BLwlUyrMywr53s2BBgDvBu4BLhLkgYaV70kghVE9X0p44mK7xUhaShRErjNzGaHxa9JGhfWjwNWZ3t+CR0GnCzpJaLqs6Ml3VoFsa0AVpjZ4+Hx3USJodJxAXwAWGZma8xsMzAbeE+VxJaSLZaKfy8kfRw4ETjLQmV3FcQ1hSixLwzfhfHAU5LeXgWxrQBmW+QvRCX3loHGVS+J4AlgT0mTJQ0DzgDmVCKQkL1/AjxnZt+NrZoDfDzc/zjwy3LHZmazzGy8mU0ieo8eMrOPVjo2M3sVWC4pNVPM+4FnKx1X8Arwbkkjwv/2/UTtPtUQW0q2WOYAZ0gaLmkysCfwl3IFJelY4F+Bk81sY1q8FYvLzBaZ2S5mNil8F1YQdfB4tdKxAW3A0QCS9iLqONEx4LhK1RJfbTfgeKIeOi8AX6pgHIcTFdmeBhaE2/HAzsD/An8Nf3eq8Pt1JFt7DVU8NmAqMC+8b21ExeOKxxVi+xrwPPAM8D9EPTcqEhtwO1FbxWaiE9gnc8VCVAXyArAEOK7McS0lqtdOfQ9uLHdc2WJLW/8SoddQFbxnw4Bbw2ftKeDoYsTlQ0w451ydq5eqIeecc1l4InDOuTrnicA55+qcJwLnnKtzngicc67OeSJwdU/ShZL+qQLHPVvSDwp43lhJvy5FTK4+eSJwdS0MFPcJotFWa4KZrQFWSTqs0rG4wcETgRuUJE0K8xbcHMZtnyupKcOmRwNPWRgFU9LnJD0bxsi/Iyw7WNKfwoB3f0pd4Rx+0bdJulfSMkkXSPpi2O4xSTuF7R6RdF147jOSthsVMvzK/4WkJ8LtsLD8CEkLwm2+pFHhKW3AWUV/41xd8kTgBrM9gRvMbD+gE/hQhm0OA+KD7F0GTDOzA4Dzw7LngfdZNODdV4BvxbZ/B/ARoiF/vwlsDNv9GYhXN400s/cA/wzckiGO64FrzeygEGdqGPCLgX8xs6nAe4GusHxeeOzcgA2pdADOldAyM1sQ7j8JTMqwzTiisYFSngZuk9RG9Ksb4G3AzyTtSTQ8yNDY9g9bNK/EeklvAPeG5YuAA2Lb3Q7RGPOSRis2G1fwAWDfaLgiAEaHX/9/BL4r6TaiwcZWhPWriUY7dW7AvETgBrPu2P0eMv/w6QJ2iD0+AbgBeBfwZGhD+AbRCf8dwElp28eP0Rt73Jt2vPSxXNIfNwCHmtnUcGs1s/VmdiXwKaAJeEzSPmH7HdhaOnBuQDwRuHr3HPB3AJIagAlm9jDR5DzNwI5EJYL2sP3ZBR7n9HCMw4kmr3kjbf1c4ILUA0lTw98pFo2GeRVRdVAqEexFNPCYcwPmicDVu18RTYMJ0dzWt0paBMwnqrPvJJrz9wpJfwzbFGKdpD8BNxKNIpnuc8D00Ej9LFvbJy4MDcwLiUoAqVm8jgLuLzAW57bho4+6uifpHuBSM/trifb/CHCxmc0r4j5/B5xiZuuKtU9Xv7xE4FzUU2hcpYNIStJY4LueBFyxeInAOefqnJcInHOuznkicM65OueJwDnn6pwnAlcTJB0exup5Q9JaSX+UdFBYd7akP1Q6RudqlQ8x4aqepNHAfcBngLuAYUTj7HTnel6JYhFRJ4vech/buVLxEoGrBXsBmNntZtZjZl1mNtfMnpb090QXaR0q6S1JnQCShkv6jqRXJL0m6cbU6KOSjpS0QtK/SeqQ9JKkrCN5htFDvxkuKNsI7CFpH0m/CaWTJZJOi21/fBjBdL2kdkkXJzmupLdJ+m9JayS9LOnL4WrnvlJPeE3rwminx8Wee7akF8Mxl6Xt9xOKRmJdJ+lBSROL8l9xg4YnAlcL/g/okfQzScdJGpNaYWbPEV2F+2cz29HMmsOqq4gSyFSiISRaiUYOTXk70BKWfxy4KTW8dBYfA84FRgFrgN8QzWGwC3Am8J+S9gvb/gQ4z8xGEY1O+lDC436faDiLPYAjiEYvPSf23EOAJeH53wZ+oshI4HvAceGY7wEWAEiaCfwbcCowFvg9YQA851I8EbiqZ2ZvAocTDdR2M7BG0hxJu2baPlTffBr4gpmtDaODfgs4I23TfzezbjN7lGi4htPI7r/MbHGYt+BY4CUz+6mZbTGzp4BfAP8Ytt1MNJLoaDNbF9bnPK6kRqLxiGaFweZeAq4hSkApL5vZzWbWA/yM6CK41HvQC7xDUpOZrTKzxWH5ecAVZvZciP1bwFQvFbg4TwSuJoQT2dlmNp7oV/ZuwHVZNh8LjCAaPbQzVBf9OixPWWdmG2KPXyb3sM7LY/cnAoek9h32fxbRr32I5hM4HnhZ0qOSDk1w3Baito+X09a1xh6/mrpjZhvD3R3D/k4nKhmtknR/bJTSicD1sTjXAkrbr6tznghczTGz54H/IkoIsP2Qzh1EA7TtZ2bN4fY2M9sxts2YUKWSsjuwMtdhY/eXA4/G9t0cqqU+E+J7wsxOIao2aiNq4O7vuB1EJYmJaevaScDMHjSzDxKVEp4nKjmlYj0vLdYmM/tTkv26+uCJwFW90DB7kaTx4fEEonr5x8ImrwHjJQ0DCD16bgaulbRLeE6rpBlpu/6apGGS3gucCPy/hCHdB+wl6WOShobbQZL+PuzvLElvM7PNwJtEcyHkPG6o7rkL+KakUaHq5ovArQnen10lnRwSTDfwVuyYNwKzUu0XoUH6wwlfp6sTnghcLVhP1FD6uKQNRAngGeCisP4hYDHwqqSOsOxfgaVEk7m8CfwWiDcGvwqsI/o1fhtwfihp9Cu0ORxD1OawMuzrKmB42ORjwEvhuOcDH0143M8CG4AXgT8QNUZnmtYyXQPRe7GSqOrnCKIpMTGze0Jsd4R4ngGOy7IfV6d80DlXdyQdCdwa2hsG/XGd64+XCJxzrs55InDOuTrnVUPOOVfnvETgnHN1ruYGnWtpabFJkyZVOgznnKspTz75ZIeZjc20ruYSwaRJk5g3r2hzgDtXNm3z27n6wSW0d3bRKNFjRmtzE5fM2JuZ0/xCX1dakl7Ots6rhpwrg7b57cyavYj2zi4AekLbXHtnFxfeuYBpX59L2/xEFxE7V3SeCJwrg6sfXELX5vQLjLdat3Ezs2Yv8mTgKsITgXMl1ja/va8kkEvX5h4uumuhJwNXdjXXRuBcLUlVCSXVY9a3fT7tBpnaH9L/enuEy6bmriOYPn26eWOxqxWHXflQotJAukaJa057Z78n7bb57Xx1zmI6uzYn3veYEUO5/KT9EieEJEmmGMkm/bU0CHqNoiay9GPk+17UMklPmtn0jOtKlQgk3UI0suJqM3tHhvUCricat30jcHaGCTy244nA1ZLJl92/3RjZSTUNbeSKU/fPeJIqJAGky3USjJ/8C5F+Eu/vr9h+LPFi7TvJMQrdZz7HLNYxCk2IlUoE7yMaDve/sySC44lGWzyeaGTJ683skP7264nA1Yq2+e1cdNfCvh5CccMaG5gwpokXOjZkeOZWmUoGX25bxG2PvVJwgkmXfoLK56TsKiPXj4RsciWCkrURmNnvJE3KsckpREnCiIYKbpY0zsxWlSom58ol1TaQKQk0CCaMaaJlVDRq9bLXN9Cb5czbY8aFdy7ga/cu5oQDxnHfwlUDKgVkkjp2KlZPAtWva3MPVz+4pGhVWpXsNdTKttP/rSDL9HmSzpU0T9K8NWvWlCU45wYiV3fRyTuP7EsCLaOGM3nnkRm3i1u3cTO3PvZK0ZOAq10rC6y2y6SSiUAZlmX8MWJmN5nZdDObPnZsxiuknasqub6kqSQQfzylZSQNmb4RzmWxW3NT0fZVye6jK4AJscfjyT1nrHM1Y7fmpowNrcMaM//2SiWH/toMchnSICbuNGK7RAPQsb6bl17fQI/X+wwKTUMbuWTG3v1vmFAlE8Ec4AJJdxA1Fr/h7QNusLhkxt7Mmr1om+qhVNtANknaDLLZZcdhTB67Y859t4waPqCEkGrgzpRoIEo2y9d1samnN/+dx44hGVMnjCn6vtOPMb55RNH2WU6luB6kZIlA0u3AkUCLpBXA5cBQADO7EXiAqMfQUqLuo+eUKhbnyi31Jb307qfZ1NPb70k0JbU+6ck6Vykg2/5TCaG/k2A85mdXvcm+40Yn2vdAPbvqzZLtO36MYu8z17H6e+/yced5hxZtXyml7DV0Zj/rDfiXUh3fuUpJ9cFf2dnF0MYGprSMzOuEk+TX+5AG0djAdr+c8z2Gc+BDTDhXVKluo6kqoU09vSx7Par3z/fEm+nXe/qvdOeKwROBc0WUqdtor8HydV0F/wL3X++u1Hz0UeeKKFu30VprkHT1pd9EIGmEpH+XdHN4vKekE0sfmnO1J1vf7mzdRp2rBkk+nT8FuoFUU/UK4D9KFpFzNeySGXvTNLRxm2X9dRt1rtKSJIIpZvZtYDOAmXWR+apg5+rezGmtXHHq/n0lgGGNDdsMKeFcNUrSWLxJUhNh+AdJU4hKCM65DGZOa+X2v7xS6TCcSyxJIrgc+DUwQdJtwGHA2aUMyjnnXPn0mwjM7DeSngLeTVQl9Hkz6yh5ZM7VoPiELkmvJnau0rImAkkHpi1KjQO0u6Tdk8wm5lw9KebFZM6VU64SwTXh7w7AdGAhUYngAOBx4PDShuZcbSnFxWTOlUPWXkNmdpSZHQW8DBwY5gN4FzCNaKA451yMX0zmalWS7qP7mNmi1AMzewaYWrKInKtRfjGZq1VJPqHPSfqxpCMlHRGuMH6u1IE5V2v8YjJXq5J0Hz0H+Azw+fD4d8APSxaRczWq0DkInKu0JN1H/wZcG27OuRxSF5MVezIS50qp30QgaRkZJpU3sz1KEpFzzrmySlI1ND12fwfgw8BOpQnHOedcuSWpGno9bdF1kv4AfKU0ITlXe9Knp5QKmB3euQpJUjUUv8K4gaiEMKpkETlXYzJdUQzQsb7bG4pdTUhSNXRN7P4WYBlwWmnCca72ZLqiGPyKYlc7kiSCT5rZi/EFkiaXKB7nao5fUexqXZILyu5OuMy5uuRXFLtal/WTKmkfSR8C3ibp1NjtbKLeQ/2SdKykJZKWSrosw/ojJb0haUG4eQO0qzmZrigGv6LY1Y5cVUN7AycCzcBJseXrgU/3t2NJjcANwAeJ5jl+QtIcM3s2bdPfm9mJ+QTtXDXJdEWxZN4+4GpG1kRgZr8EfinpUDP7cwH7PhhYmmpfkHQHcAqQngicq3np01M+u+rNCkbjXH5yTUxzaZi0/iOSzkxfb2af62ffrcDy2OMVwCEZtjtU0kJgJXCxmS3OEMu5wLkAu+++ez+Hdc45l49cVUOpEUbnFbhvZViWfpXNU8BEM3tL0vFAG7Dndk8yuwm4CWD69Ol+pY5zzhVRrqqhe8PfnxW47xXAhNjj8US/+uPHeDN2/wFJ/ympxedEdrUi/YpiH23U1aJcVUP3kmGwuRQzO7mffT8B7BmuOWgHzgA+knaMtwOvmZlJOpioF1P6kBbOVaVccxQ7V0tyVQ19ZyA7NrMtki4AHgQagVvMbLGk88P6G4F/BD4jaQvQBZxhZl7142pCrjmKhw/1awhc7chVNfRo6r6kYcA+RCWEJWa2KcnOzewB4IG0ZTfG7v8A+EGeMTtXFXJdUeyJwNWSfj+tkk4AXgC+R3TSXirpuFIH5ly18yuK3WCR5BN7DXCUmR1pZkcAR+GzlTnncxS7QSNJIlhtZktjj18EVpcoHudqxsxprVxx6v59JYBhjQ1M3nmk9xpyNSfJ6KOLJT0A3EXURvBhouEiTgUws9kljM+5qpZ+RbFztShJItgBeA04IjxeQzRV5UlEicETgXPO1bAkU1WeU45AnHPOVUaSqSonA58FJsW3T3BBmXODll9R7AaTJFVDbcBPgHsBn3LJ1b1cVxR7MnC1KEki+JuZfa/kkThXI3JdUeyJwNWiJIngekmXA3OB7tRCM3uqZFE5V8V8jmI32CRJBPsDHwOOZmvVkIXHztWd3ZqbaM+QDPyKYlerkiSCfwD2SDq+kHOD3SUz9t6mjQD8imJX25L8hFlING+xcw6/otgNPklKBLsCz0t6gq1tBGZmp5QuLOeqm19R7AaTJIng8th9AYcD281h7JxzrjYlubL4UUlTiWYXOw1YBtyY80nODVJ+IZkbjHJNVbkX0fSSZxJNH3knIDM7qkyxOVdV/EIyN1jlaix+Hng/cJKZHW5m3wd6cmzv3KCW60Iy52pZrkTwIeBV4GFJN0t6P1EbgXN1yS8kc4NV1kRgZveY2elEcxU/AnwB2FXSDyUdU6b4nKsaPjWlG6z6/QSb2QYzu83MTgTGAwuAy0odmHPF0ja/ncOufIjJl93PYVc+RNv89oL241NTusEqSffRPma2FvhRuDlX1drmt/PVOYvp7Nrct6y9s4sv3LmAeS+v5T9m7p/X/mZOawXg0rufZlNPL8O815AbJPJKBM4VS6obZntnFyIavAqiX9i9Bq3NTVwyY+++k2+++05PAHEG3PrYK9z/9CouP2m/RMdI7zY6pcWvJHaDR0kTgaRjgeuBRuDHZnZl2nqF9ccDG4GzSzGqafyk0yjRY1b0v5lOZtV0rFwn1kzvTz7HSHLSznbiJ+1+b3jQ3tnFhXcu4Gv3Ls7rZJ0rAaRbt3Ezs2YvAug3du826gazkiUCSY3ADcAHgRVEE97PMbNnY5sdB+wZbocAPwx/iyb9S9xjVpK/mU5m1XSs1In1i3ct2Oaknn5SLuQY2fad7Rjx+/1Zt3Fzvwkh3wQQ17W5h4vuWghkTwY+/4Ab7EpZIjgYWGpmLwJIugM4BYgnglOA/zYzAx6T1CxpnJmtKlYQqS/xeU//kj3eKKyR0FWH7gfhzpBVJGG2NaXMGuC+N/9BPNkykpYdtz+xf+7F17M+b3TT0IzLN3RvYeTw0ta8luMYg/VYtfp6Xh07Ac47tCj7iivlO9EKLI89XsH2v/YzbdMKbJMIJJ0LnAuw++675xVEtr7frkaFc388CRRDb6+xdPVbtK/rYuiQrZ3pNm/Jfo3A8CGN7DtudFHjcC6XaX8/riT7LWUiyHTxWfq3N8k2mNlNwE0A06dPz+sMkJpE5EcH+GCp9WzE0OjkvnFz7ou/GkTfkNId67tZ9vqGvqqxuKahjVxx6v5MLKAx27lqU8orYVYAE2KPxwMrC9hmQDL1/Xb1Y8yIoVx3+lSe/cZxPPuN47ju9Kk0KvsF8r0GL3RsoGN9N8vXdWVMAo0SV5y6f0E9mpyrRqUsETwB7ClpMtBONIDdR9K2mQNcENoPDgHeKGb7AGxtAKzXXkPpDbX9Se0vyTHy3Xf6MbL1NhpI42/KmBFDMzYupx6nzzCW7oWODVnX9Zp5EnCDSskSgZltkXQB8CBR99FbzGyxpPPD+huBB4i6ji4l6j56TilimTmtta6/uEm6zxbabz+frrlJj5H6fxWSELIlgPT9A1x018K+nk/5yDbUhHO1SsVudCu16dOn27x58yodhiujUiWy9K7FSaTaBur5h4WrTZKeNLPpmdb5lcWu6pWqRFdIycCTgBuMfNhEV9dmTmvlmtPemahDQWtzkycBNyh5InB1b+a0Vq44dX+as1wcBlGV0CUz9i5jVM6VjycC54iSwYLLj+G606fSGhqDU91MW5ubvErIDWo111gsaQ3wcoFPbwE6ihhOMVVrbNUaF3hshajWuKB6Y6vWuCC/2Caa2dhMK2ouEQyEpHnZWs0rrVpjq9a4wGMrRLXGBdUbW7XGBcWLzauGnHOuznkicM65OldvieCmSgeQQ7XGVq1xgcdWiGqNC6o3tmqNC4oUW121ETjnnNtevZUInHPOpfFE4Jxzda5uEoGkYyUtkbRU0mUVjGOCpIclPSdpsaTPh+U7SfqNpL+Gv2MqGGOjpPmS7quW2MI0pndLej68d4dWQ1whti+E/+Uzkm6XtEOlYpN0i6TVkp6JLcsai6RZ4TuxRNKMMsd1dfh/Pi3pHknN5Y4rW2yxdRdLMkkt5Y4tW1ySPhuOvVjSt4sSl5kN+hvRMNgvAHsAw4CFwL4VimUccGC4Pwr4P2Bf4NvAZWH5ZcBVFXy/vgj8HLgvPK54bMDPgE+F+8OA5iqJqxVYBjSFx3cBZ1cqNuB9wIHAM7FlGWMJn7uFwHBgcviONJYxrmOAIeH+VZWIK1tsYfkEomH0XwZaquQ9Owr4LTA8PN6lGHHVS4ngYGCpmb1oZpuAO4CKzF1pZqvM7Klwfz3wHNHJ5BSikx3h78xKxCdpPHAC8OPY4orGJmk00ZfiJwBmtsnMOisdV8wQoEnSEGAE0Sx7FYnNzH4HrE1bnC2WU4A7zKzbzJYRzQtycLniMrO5ZrYlPHyMaIbCssaVLbbgWuBStp1/qaLvGfAZ4Eoz6w7brC5GXPWSCFqB5bHHK8KyipI0CZgGPA7samF2tvB3lwqFdR3Rhz8+uW+lY9sDWAP8NFRZ/VjSyCqICzNrB74DvAKsIpplb241xBaTLZZq+l58AvhVuF/xuCSdDLSb2cK0VZWObS/gvZIel/SopIOKEVe9JIJMk9RWtN+spB2BXwAXmtmblYwlRdKJwGoze7LSsaQZQlRE/qGZTQM2EFVxVFyobz+FqDi+GzBS0kcrG1ViVfG9kPQlYAtwW2pRhs3KFpekEcCXgK9kWp1hWTnfsyHAGODdwCXAXZI00LjqJRGsIKrvSxlPVHyvCElDiZLAbWY2Oyx+TdK4sH4csDrb80voMOBkSS8RVZ8dLenWKohtBbDCzB4Pj+8mSgyVjgvgA8AyM1tjZpuB2cB7qiS2lGyxVPx7IenjwInAWRYqu6sgrilEiX1h+C6MB56S9PYqiG0FMNsifyEqubcMNK56SQRPAHtKmixpGHAGMKcSgYTs/RPgOTP7bmzVHODj4f7HgV+WOzYzm2Vm481sEtF79JCZfbTSsZnZq8BySakJAd4PPFvpuIJXgHdLGhH+t+8navephthSssUyBzhD0nBJk4E9gb+UKyhJxwL/CpxsZhvT4q1YXGa2yMx2MbNJ4buwgqiDx6uVjg1oA44GkLQXUceJjgHHVaqW+Gq7AccT9dB5AfhSBeM4nKjI9jSwINyOB3YG/hf4a/i7U4XfryPZ2muo4rEBU4F54X1rIyoeVzyuENvXgOeBZ4D/Ieq5UZHYgNuJ2io2E53APpkrFqIqkBeAJcBxZY5rKVG9dup7cGO548oWW9r6lwi9hqrgPRsG3Bo+a08BRxcjLh9iwjnn6ly9VA0555zLwhOBc87VOU8EzjlX5zwROOdcnfNE4Jxzdc4Tgat7ki6U9E8VOO7Zkn5QwPPGSvp1KWJy9ckTgatrYaC4TxCNtloTzGwNsErSYZWOxQ0OngjcoCRpUpi34OYwbvtcSU0ZNj0aeMrCKJiSPifp2TBG/h1h2cGS/hQGvPtT6grn8Iu+TdK9kpZJukDSF8N2j0naKWz3iKTrwnOfkbTdqJDhV/4vJD0RboeF5UdIWhBu8yWNCk9pA84q+hvn6pInAjeY7QncYGb7AZ3AhzJscxgQH2TvMmCamR0AnB+WPQ+8z6IB774CfCu2/TuAjxAN+ftNYGPY7s9AvLpppJm9B/hn4JYMcVwPXGtmB4U4U8OAXwz8i5lNBd4LdIXl88Jj5wZsSKUDcK6ElpnZgnD/SWBShm3GEY0NlPI0cJukNqJf3QBvA34maU+i4UGGxrZ/2KJ5JdZLegO4NyxfBBwQ2+52iMaYlzRasdm4gg8A+0bDFQEwOvz6/yPwXUm3EQ02tiKsX0002qlzA+YlAjeYdcfu95D5h08XsEPs8QnADcC7gCdDG8I3iE747wBOSts+foze2OPetOOlj+WS/rgBONTMpoZbq5mtN7MrgU8BTcBjkvYJ2+/A1tKBcwPiicDVu+eAvwOQ1ABMMLOHiSbnaQZ2JCoRtIftzy7wOKeHYxxONHnNG2nr5wIXpB5Imhr+TrFoNMyriKqDUolgL6KBx5wbME8Ert79imgaTIjmtr5V0iJgPlGdfSfRnL9XSPpj2KYQ6yT9CbiRaBTJdJ8DpodG6mfZ2j5xYWhgXkhUAkjN4nUUcH+BsTi3DR991NU9SfcAl5rZX0u0/0eAi81sXhH3+TvgFDNbV6x9uvrlJQLnop5C4yodRFKSxgLf9STgisVLBM45V+e8ROCcc3XOE4FzztU5TwTOOVfnPBE451yd80TgnHN17v8DGs3Guj0z/PYAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "from spudtr import filters\n",
    "\n",
    "# note this fills in default transition width, ripple, and window values\n",
    "lp_params = {\n",
    "    \"ftype\": \"lowpass\",  # lowpass, bandpass, highpass\n",
    "    \"cutoff_hz\": 20,     # 1/2 amplitude frequency Hz\n",
    "    \"sfreq\": 250.0,      # sampling rate in samples/second\n",
    "}\n",
    "\n",
    "bode, imp, s_edge, n_edge = filters.show_filter(**lp_params);  # expand the dictionary with python ** trick"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Apply the filter**\n",
    "\n",
    "With **all** the parameters specified.\n",
    "\n",
    "Note the `**lp_params` python trick to expand the filter parameter dictionary for the keyword arguments."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'ftype': 'lowpass',\n",
       " 'cutoff_hz': 20,\n",
       " 'sfreq': 250.0,\n",
       " 'window': 'kaiser',\n",
       " 'width_hz': 5.0,\n",
       " 'ripple_db': 53.0}"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# update the filter specs with default values\n",
    "lp_params[\"window\"] = \"kaiser\"\n",
    "lp_params[\"width_hz\"] = 5.0\n",
    "lp_params[\"ripple_db\"] = 53.0\n",
    "display(lp_params)\n",
    "\n",
    "epochs_df_lp = epf.fir_filter_epochs(\n",
    "    epochs_df,\n",
    "    data_columns=eeg_channels,\n",
    "    epoch_id=\"epoch_id\",\n",
    "    time=\"time_ms\",\n",
    "    trim_edges=False,\n",
    "    **lp_params,\n",
    "    )\n",
    "\n",
    "times = epochs_df[\"time_ms\"].unique()\n",
    "epoch_ids = epochs_df[\"epoch_id\"].unique()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "3. Compare the output"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Filter EEG epochs, trim distorted edges\n",
    "\n",
    "\n",
    "Edge distortion is reduced by zero-padding, but not eliminated.\n",
    "\n",
    "How much to trim the epochs is your business."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "epochs_df_lp_trimmed = epf.fir_filter_epochs(\n",
    "    epochs_df,\n",
    "    data_columns=eeg_channels,\n",
    "    epoch_id=\"epoch_id\",\n",
    "    time=\"time_ms\",\n",
    "    trim_edges=True,\n",
    "    **lp_params,\n",
    "    )\n",
    "\n",
    "trimmed_times = epochs_df_lp_trimmed[\"time_ms\"].unique()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Compare the output"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# select some epochs to show\n",
    "epidxs = [0, 6, 20]\n",
    "channel = \"MiPa\"\n",
    "\n",
    "for epidx in epidxs:\n",
    "\n",
    "    qstr = f\"epoch_id == @epoch_ids[{epidx}]\"\n",
    "    f, ax = plt.subplots(figsize=(12,8))\n",
    "    ax.set_title(f\"epoch_id={epidx}\",  fontsize=18)\n",
    "    \n",
    "    # unfiltered\n",
    "    ax.plot(\n",
    "        times,\n",
    "        epochs_df.query(qstr)[channel],\n",
    "        color=\"black\", \n",
    "        label=\"unfiltered\"\n",
    "    )\n",
    "    \n",
    "    # filtered, phase compensated with distortion\n",
    "    ax.plot(\n",
    "        times,\n",
    "        epochs_df_lp.query(qstr)[channel],\n",
    "        color=\"red\", \n",
    "        label=\"filtered\"\n",
    "    )\n",
    "    \n",
    "    # filtered, phase compensated, distortion trimmed\n",
    "    ax.plot(\n",
    "        trimmed_times,\n",
    "        epochs_df_lp_trimmed.query(qstr)[channel], \n",
    "        color=\"blue\", \n",
    "        lw=3, \n",
    "        label=\"filtered, trimmed\"\n",
    "    )\n",
    "\n",
    "    # decorate the beginning and end of the delay shift distortion regions\n",
    "    for xtime in [trimmed_times[0], trimmed_times[-1]]:\n",
    "        \n",
    "        # beginning and end of the trimmed data\n",
    "        ax.axvline(xtime, color=\"red\")\n",
    "        ax.annotate(\n",
    "            text=f\"{str(xtime)} ms\", \n",
    "            xy=(xtime, ax.get_ylim()[1]), \n",
    "            fontsize=18, \n",
    "            ha=\"center\", \n",
    "            va=\"bottom\",\n",
    "            bbox=dict(boxstyle=\"round\", ec=\"red\",fc=\"white\")\n",
    "        )\n",
    "            \n",
    "        # highlight the trimmed region\n",
    "        for bound in [0, -1]:\n",
    "            ax.axvspan(\n",
    "                times[bound], \n",
    "                trimmed_times[bound], \n",
    "                color=\"pink\", \n",
    "                alpha=.2\n",
    "            )\n",
    "    \n",
    "    ax.legend()"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "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": "3.9.13"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}