{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**What does this notebook do?**\n",
    "- Load the exported CGM values from NutriSense\n",
    "- Retrieve sleep data from an outside Excel file for that day\n",
    "- Pull in Garmin step information and \"run activities\"\n",
    "- Print out what days are included in the dataset\n",
    "- Loop through the data, producing one chart vor every day in the dataset\n",
    "  - Smooth CGM data and interpolate missing values\n",
    "  - Calculate key metrics for that day, both glucose and steps\n",
    "  - Create a chart of the glucose values, meals, activities, steps, sleep and include some metrics"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import plotly.express as px\n",
    "from plotly.subplots import make_subplots\n",
    "import plotly.graph_objects as go\n",
    "import datetime\n",
    "from datetime import date\n",
    "from garminconnect import (\n",
    "    Garmin,\n",
    "    GarminConnectConnectionError,\n",
    "    GarminConnectTooManyRequestsError,\n",
    "    GarminConnectAuthenticationError,\n",
    ")\n",
    "from openpyxl import Workbook, load_workbook\n",
    "\n",
    "# Read in CSV file\n",
    "df = pd.read_csv('export2.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",
    "\n",
    "# Read Excel file\n",
    "workbook = load_workbook(filename = 'tracking.xlsx')\n",
    "# Load the sheet with the data I am interested in\n",
    "todaySheet = workbook['Today']\n",
    "\n",
    "# Get Garmin Data\n",
    "# This may not be so great, defaulting to simply retrieving the last 100 activities on Garmin.\n",
    "# If the day that is plotted is further in the past, this may not work.\n",
    "numberOfActivities = 100\n",
    "try:\n",
    "    # Read UserID and Password from config file\n",
    "    config  = {}\n",
    "    with open(\"config.dat\") as myfile:\n",
    "        for line in myfile:\n",
    "            name, var = line.partition(\"=\")[::2]\n",
    "            config[name.strip()] = str(var).strip()\n",
    "    # Initialize Garmin client with credentials\n",
    "    client = Garmin(config[\"uid\"], config[\"password\"])\n",
    "    # Login to Garmin Connect portal\n",
    "    client.login()\n",
    "    # Get running activities\n",
    "    allActivities = client.get_activities(0,numberOfActivities) # 0=start, numberOfActivities=limit  \n",
    "except (GarminConnectConnectionError, GarminConnectAuthenticationError, GarminConnectTooManyRequestsError,) as err:\n",
    "    print(\"Error occured during Garmin Connect Client init: %s\" % err)\n",
    "    quit()\n",
    "except Exception:\n",
    "    print(\"Unknown error occured during Garmin Connect Client init.\")"
   ]
  },
  {
   "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": {
    "scrolled": false
   },
   "outputs": [],
   "source": [
    "# Go through the data and create a plot for the last 5 days\n",
    "for y in range(1, 5):\n",
    "    df1 = df[df['occurred_at_day']==daysWithData[y]]\n",
    "    day = daysWithData[y]\n",
    "\n",
    "    # Create a datasets just with glucose measurments\n",
    "    gm = df1[df1['class']=='GlucoseMeasurement']\n",
    "\n",
    "    # Create a dataset for meals and exercise, sort it\n",
    "    mealsExercise = df1[((df1['class']=='Meal') | (df1['class']=='ExerciseActivity') )]\n",
    "    mealsExerciseSorted = mealsExercise.sort_values(by=[\"occurred_at\"], ascending=True)\n",
    "\n",
    "    # Get steps of the day from Garmin\n",
    "    dayOfInterest = datetime.datetime.strptime(day, '%Y-%m-%d').date()\n",
    "    allDayStepData = client.get_steps_data(dayOfInterest.isoformat())\n",
    "\n",
    "    # convert Garmin data in list form to Pandas dataframe\n",
    "    dfGarmin = pd.DataFrame.from_dict(allDayStepData)\n",
    "\n",
    "    # manipulate start time so that it is local (And not GMT)\n",
    "    dfGarmin['time'] = dfGarmin['startGMT'].apply(lambda x: x[:len(x) - 5])\n",
    "    dfGarmin['time'] = dfGarmin['time'].apply(lambda x: x[11:])\n",
    "    offset = dfGarmin[\"time\"][0]\n",
    "    offsetHour = int(offset.split(':')[0])\n",
    "    offsetMinutes=int(offset.split(':')[1])\n",
    "    dfGarmin['time'] = pd.to_datetime(dfGarmin['startGMT'])\n",
    "    dfGarmin['time'] = dfGarmin['time'].apply(lambda x: x - datetime.timedelta(hours=offsetHour, minutes=offsetMinutes))\n",
    "    dfGarmin = dfGarmin[dfGarmin.steps != 0]\n",
    "\n",
    "    # Create a dataset with just 2 columns, and rename columns\n",
    "    gm_data = gm.filter(['occurred_at', 'value'])\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",
    "    # Add rows and interpolate missing data\n",
    "    gm_data = gm_data.resample('1T').mean()\n",
    "    gm_data = gm_data.interpolate(method='cubic')\n",
    "\n",
    "    # Calculate a few metrics\n",
    "    threshold = 120  # this is an arbitrary threshold\n",
    "    above = gm_data[gm_data['value'] > threshold] # create a dataset with glucose measuremnts over threshold\n",
    "    minutesAboveThreshold = above.count()\n",
    "    percentageAboveThreshold = int(round(minutesAboveThreshold/(60*24)*100,0))\n",
    "    averageGlucose = int(round(gm_data['value'].mean()))\n",
    "    medianGlucose = int(round(gm_data['value'].median()))\n",
    "\n",
    "    # Calculate statistics on the Garmin data\n",
    "    numberOfRunningActivitiesToday = 0\n",
    "    numberOfActivitiesToday = 0\n",
    "    for i in range(numberOfActivities):\n",
    "        activity = allActivities[i]\n",
    "        activityDateTime = activity['startTimeLocal']\n",
    "        activityDate = datetime.datetime.strptime(activityDateTime, \"%Y-%m-%d %H:%M:%S\")\n",
    "        if str(activityDate.date()) == day:\n",
    "            numberOfActivitiesToday = numberOfActivitiesToday + 1\n",
    "            if activity[\"activityType\"][\"typeKey\"] == \"running\":\n",
    "                numberOfRunningActivitiesToday = numberOfRunningActivitiesToday + 1\n",
    "\n",
    "    # Retrieve sleep data\n",
    "    for rowInExcel in range(3,55):\n",
    "        cell = todaySheet[str(\"A\"+str(rowInExcel))]\n",
    "        # Skip over \"empty\" cells\n",
    "        if cell.value is None: continue\n",
    "        # Assume the cell contains a date value, thus convert it\n",
    "        cellDate = cell.value.date()\n",
    "        if str(cellDate) == str(day):\n",
    "            sleepEnd = todaySheet[str(\"E\"+str(rowInExcel))].value\n",
    "            sleepBegin = todaySheet[str(\"F\"+str(rowInExcel))].value\n",
    "            sleepBegin = datetime.datetime.combine(date.min, datetime.datetime.strptime('23:59', '%H:%M').time()) - datetime.datetime.combine(date.min, sleepBegin)\n",
    "            break\n",
    "\n",
    "    # using subplots here to easily get a secondary y-axis\n",
    "    fig = make_subplots(specs=[[{\"secondary_y\": True}]])\n",
    "    # first add the glucose measurement data\n",
    "    fig.add_trace( go.Scatter(x=gm_data.index, y=gm_data.value, mode='lines',line=dict(color=\"purple\")))\n",
    "\n",
    "    # add meals and exercise to the chart\n",
    "    yText = 145\n",
    "    eventColor = \"green\"\n",
    "    for index, row in mealsExerciseSorted.iterrows():\n",
    "\n",
    "        # If the activity has \"run\" in the description, don't use it as it is a duplicate from Garmin\n",
    "        if \"run\" in str(row['description']).lower(): continue\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",
    "        # Pick a different color depending on the event\n",
    "        if (row['class'] == \"Meal\"): eventColor = \"black\"\n",
    "        else: eventColor = \"green\"\n",
    "\n",
    "        # Alternate text placement so adjacent text doesn't overlap\n",
    "        if (yText >= 175): yText = 145\n",
    "        else: yText = yText + 8\n",
    "\n",
    "        # draw a vertical line at the time of the meal/exercise\n",
    "        gmAtThatTime = gm_data.loc[str(time.replace(second=0))].value\n",
    "        fig.add_shape(type=\"line\", xref=\"x\", yref=\"y\", x0=time, y0=gmAtThatTime, x1=time , y1=yText-2, line_color=eventColor,)\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 Garmin running activities\n",
    "    for i in range(numberOfActivities):\n",
    "        activity = allActivities[i]\n",
    "        # only activities that are of type \"running\"\n",
    "        if activity[\"activityType\"][\"typeKey\"] == \"running\":\n",
    "            activityDateTime = activity['startTimeLocal']\n",
    "            activityDate = datetime.datetime.strptime(activityDateTime, \"%Y-%m-%d %H:%M:%S\")\n",
    "            if str(activityDate.date()) == day:\n",
    "                # draw a vertical line at the time of the running activity\n",
    "                gmAtThatTime = gm_data.loc[str(activityDate.replace(second=0))].value\n",
    "                fig.add_shape(type=\"line\", xref=\"x\", yref=\"y\", x0=activityDateTime, y0=gmAtThatTime, x1=activityDateTime , y1=133, line_color=\"green\",)\n",
    "                # Add text... yes this is specific to kilometers. This may need changes for miles.\n",
    "                textDescr = str(activity['activityName']) + \" \" + str(int(round(activity['distance']/1000))) + \"K run\"\n",
    "                fig.add_annotation(text=textDescr, xref=\"x\", yref=\"y\", x=activityDateTime, y=135, showarrow=False, font=dict(color=\"green\"))\n",
    "\n",
    "    # Draw a line at the threshold\n",
    "    fig.add_shape(type=\"line\", xref=\"x\", yref=\"y\",\n",
    "        x0=gm_data.index[0], y0=threshold, x1=gm_data.index.max(), y1=threshold, line_color=\"red\",)\n",
    "\n",
    "    # Show text box with summary values\n",
    "    fig.add_annotation(\n",
    "                    text='Glucose Threshold = '+str(threshold)+\n",
    "                    '<br>Minutes above Threshold = '+str(int(round(minutesAboveThreshold,0)))+\n",
    "                    '<br>Time above Threshold = '+str(percentageAboveThreshold)+\"%\"+\n",
    "                    '<br>Average Glucose = '+str(averageGlucose)+\n",
    "                    '<br>Median Glucose = '+str(medianGlucose)+\n",
    "                    '<br>Steps Today = '+str(dfGarmin.steps.sum()),\n",
    "                    align='right', showarrow=False,\n",
    "                    xref='paper', yref='paper', x=0.001, y=0.005,\n",
    "                    bordercolor='black', borderwidth=1\n",
    "                )\n",
    "\n",
    "    # Setting primary and secondary y axis titles and ticks\n",
    "    fig.update_layout(yaxis = dict(range=[0, 180], tick0=0, dtick=20, title_text='mg/dL'),yaxis2=dict(tick0=0, dtick=500, range=[0,4500], title_text='Steps'))\n",
    "    # Adding step data to the chart, using the secondary y axis\n",
    "    fig.add_trace( go.Bar(x=dfGarmin.time, y=dfGarmin.steps), secondary_y=True)\n",
    "\n",
    "    # Set x axis title\n",
    "    fig.update_xaxes(title_text=str(dayOfInterest.strftime('%A'))+ \", \" +str(day), tickformat='%H:%M')\n",
    "    # Hide the legend\n",
    "    fig.update_layout(showlegend=False)\n",
    "\n",
    "    # Draw morning sleep\n",
    "    fig.add_shape(type=\"rect\", xref=\"x\", yref=\"y\",\n",
    "        x0=gm_data.index[0], y0=57, x1=datetime.datetime.strptime(str(day) + \" \" + str(sleepEnd), '%Y-%m-%d %H:%M:%S'), y1=150,\n",
    "        line=dict(color=\"RoyalBlue\"),fillcolor=\"LightSkyBlue\",opacity=0.5,line_width=0,)\n",
    "    # Draw evening sleep\n",
    "    fig.add_shape(type=\"rect\", xref=\"x\", yref=\"y\",\n",
    "        x0=gm_data.index.max(), y0=57, x1=datetime.datetime.strptime(str(day) + \" \" + str(sleepBegin), '%Y-%m-%d %H:%M:%S'), y1=150,\n",
    "        line=dict(color=\"RoyalBlue\"),fillcolor=\"LightSkyBlue\",opacity=0.5,line_width=0,)\n",
    "\n",
    "    # Size the chart\n",
    "    fig.update_layout(autosize=False, width=1400, height=400,margin=dict(l=20, r=20, t=40, b=20),)\n",
    "    fig.show()"
   ]
  }
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