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 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**What does this notebook do?**\n",
    "- Load the exported CGM values from NutriSense\n",
    "- Print out what days are included in the dataset\n",
    "- Filter down CGM data to only one day\n",
    "- Extract data for meals and exercise\n",
    "- Interpolate missing data and smooth curve\n",
    "- Plot CGM data for that day\n",
    "- Add meals and exercise events into the chart "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import plotly.express as px\n",
    "import datetime\n",
    "\n",
    "# Read in CSV file\n",
    "df = pd.read_csv('export.csv')\n",
    "\n",
    "# Remove \"time zone offset\" from \"occurred_at\" column and add new \"occurred_at_day\" column\n",
    "df['occurred_at_day'] = df['occurred_at'].apply(lambda x: x[:len(x) - 15])\n",
    "df['occurred_at'] = df['occurred_at'].apply(lambda x: x[:len(x) - 6])\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Print all days with data\n",
    "daysWithData = df['occurred_at_day'].unique()\n",
    "print(daysWithData)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Filter down to one day, pick the second day in the dataset\n",
    "day = daysWithData[2]\n",
    "df = df[df['occurred_at_day']==day]\n",
    "\n",
    "# Create a datasets just with glucose measurments\n",
    "gm = df[df['class']=='GlucoseMeasurement']\n",
    "\n",
    "# Create a dataset for meals and exercise, sort it\n",
    "mealsExercise = df[((df['class']=='Meal') | (df['class']=='ExerciseActivity') )]\n",
    "mealsExerciseSorted = mealsExercise.sort_values(by=[\"occurred_at\"], ascending=True)\n",
    "\n",
    "# Only keep the columns that we need\n",
    "gm_data = gm.filter(['occurred_at', 'value'])\n",
    "\n",
    "# rename the columns for easier readability\n",
    "gm_data.columns = ['time', 'value']\n",
    "\n",
    "# turn time column into the index and delete time column\n",
    "gm_data['time']= pd.to_datetime(gm_data['time'])\n",
    "gm_data.index = gm_data['time']\n",
    "del gm_data['time']\n",
    "\n",
    "gm_data = gm_data.resample('1T').mean() # add rows for every 1 minute\n",
    "gm_data = gm_data.interpolate(method='cubic') # interpolate the new 1 minute points with data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Chart the data\n",
    "fig = px.line(gm_data, y=\"value\")\n",
    "\n",
    "# Set defaults for color and text placement\n",
    "yText = 60\n",
    "eventColor = \"green\"\n",
    "\n",
    "# Loop through all meals and exercise events\n",
    "for index, row in mealsExerciseSorted.iterrows():\n",
    "\n",
    "    # Pick a different color depending on the event\n",
    "    if (row['class'] == \"Meal\"):\n",
    "        eventColor = \"black\"\n",
    "    else:\n",
    "        eventColor = \"green\"\n",
    "\n",
    "    # Convert the time in pandas to something that we can use as an index for the x-axis placement\n",
    "    time = datetime.datetime.strptime(row['occurred_at'], '%Y-%m-%d %H:%M:%S')\n",
    "    \n",
    "    # draw a vertical line at the time of the meal/exercise\n",
    "    fig.add_shape(type=\"line\", xref=\"x\", yref=\"y\", x0=time, y0=70, x1=time , y1=140, line_color=eventColor,)\n",
    "    \n",
    "    # Alternate text placement so adjacent text doesn't overlap\n",
    "    if (yText == 60): yText = 65\n",
    "    else: yText = 60\n",
    "\n",
    "    # Add text\n",
    "    fig.add_annotation(text=row['description'], xref=\"x\", yref=\"y\", x=time, y=yText, showarrow=False, font=dict(color=eventColor))\n",
    "\n",
    "# Add axis titles\n",
    "fig.update_xaxes(title_text=str(day), tickformat='%H:%M')\n",
    "fig.update_yaxes(title_text='mg/dL')\n",
    "\n",
    "# Show the chart\n",
    "fig.show()"
   ]
  }
 ],
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