{ "nbformat": 4, "nbformat_minor": 0, "metadata": { "colab": { "provenance": [] }, "kernelspec": { "name": "python3", "display_name": "Python 3" }, "language_info": { "name": "python" } }, "cells": [ { "cell_type": "markdown", "source": [ "# Guide to Extracting Data w/ APIs from the Whoop Strap 4.0" ], "metadata": { "id": "Q9GBydEgCv5O" } }, { "cell_type": "markdown", "source": [ "\n", "\n" ], "metadata": { "id": "8OL7u_fWDbTk" } }, { "cell_type": "markdown", "source": [ "As Kanye once [said](https://www.youtube.com/watch?v=8fbyfDbi-MI),\n", "\n", "> Scoop-diddy-whoop\n", ">\n", "> Whoop-diddy-scoop\n", "\n", "While we certainly won't be rapping in this notebook, we will be using the [WHOOP 4.0](https://www.whoop.com/membership/strap/), a small wearable that fits onto your wrist as shown above! Featuring a light, discreet wristband that is also waterproof, the WHOOP 4.0 offers comfortable [physical activity](https://github.com/alrojo/wearipedia/tree/main/metrics/physical-activity) and [sleep](https://github.com/alrojo/wearipedia/tree/main/metrics/sleep) tracking with wireless charging and an app with useful calculated metrics such as strain and recovery. \n", "\n", "\n", "We've used the WHOOP 4.0 for a while now, and we'll show you how to extract its data, visualize steep stages, and compute correlations and other statistical measures based on your data! While you will need a WHOOP 4.0 set up to actually collect the data, the data *extraction* requires only an internet connection and your username and password.\n", "\n", "This is a comprehensive, clear guide to extract your data from the WHOOP 4.0 using an unofficial WHOOP [Application Programming Interface (API)](https://en.wikipedia.org/wiki/API).\n", "\n", "If you want to know more about WHOOP 4.0, see the [README](https://github.com/alrojo/wearipedia/tree/main/wearables/whoop-strap-4.0) for a detailed analysis of performances, sensors, data privacy, and extraction pipelines.\n", "\n", "We will be able to extract the following parameters:\n", "\n", "Parameter Name | Sampling Frequency \n", "-------------------|------------------\n", "Average heart rate | Daily \n", "Maximum heart rate | Daily\n", "Kilojoules (energy burned) | Daily\n", "Strain score | Daily\n", "Number of naps | Daily\n", "Baseline sleep need | Daily\n", "Sleep debt | Daily\n", "Sleep need strain (extra sleep required due to strain) | Daily\n", "Total sleep need (calculated with other values) | Daily\n", "Sleep quality duration | Daily\n", "Respiratory rate | Daily (during core sleep)\n", "Blood oxygen | Daily (during core sleep)\n", "Resting heart rate | Daily (during core sleep)\n", "Heart rate variability | Daily (during core sleep)\n", "Skin temperature | Daily (during core sleep)\n", "Heart rate | Every 7 seconds\n", "\n", "Note that some of the parameters are for an entire 24-hour period, while others are measured and reported only for the time the user is in a core sleep (contrasted with a nap, the core sleep is the \"main\" sleep, which usually occurs at night).\n", "\n", "

\n", "In this guide, we sequentially cover the following **five** topics to extract from the WHOOP 4.0 API:\n", "1. **Setup**\n", "2. **Authentication/Authorization**\n", " - Requires only username and password, no OAuth(2).\n", "3. **Data extraction**\n", " - You can get data from the API in a couple lines of code.\n", "4. **Data visualization**\n", " - 4.1: We reproduce a day-by-day week-long plot of hours slept and sleep needed, which is displayed in the mobile app originally. We do this with matplotlib.\n", " - 4.2: We reproduce a time series plot of heart rate over the course of a day, sampled every 6 seconds, which is shown in the WHOOP app (both the webapp and the mobile app, if you turn the phone sideways). In this plot, we deal with missing data (when the user takes off the device for a long time) and also combine sleep information to color in intervals of the time series where the user is sleeping, allowing you to quickly see how the heart rate responds to sleep.\n", "5. **Data analysis**\n", " - 5.1: We try to find a correlation between the length of a sleep period and the median heart rate for that sleep period. We find that the correlation is not statistically significant, unless excluding an outlier.\n", " - 5.2: We try to check whether the median heart rate is correlated to whether the sleep is a nap or a night sleep. We find that for our data this is statistically significant.\n", "\n", "\n", "Disclaimer: this notebook is purely for educational purposes. All of the data currently stored in this notebook is purely *synthetic*, meaning randomly generated according to rules we created. Despite this, the end-to-end data extraction pipeline has been tested on our own data, meaning that if you enter your own email and password on your own Colab instance, you can visualize your own *real* data. That being said, we were unable to thoroughly test the timezone functionality, though, since we only have one account, so beware." ], "metadata": { "id": "2TRGazbwEPf5" } }, { "cell_type": "markdown", "source": [ "# 1. Setup\n", "\n", "## 1.1 Study participant setup and usage\n", "\n", "Setting the watch up for data collection was fairly straightforward in our experience: just download the [WHOOP app](https://www.whoop.com/membership/app/) and follow the instructions there. Since the watch does not connect to internet, all you need to do is connect your phone to the watch via bluetooth, and all data transfer will happen (1) between the watch and the phone via Bluetooth and (2) between the phone and Withings' servers via Wi-Fi. The watch can store up to [3 days' worth of data](https://support.whoop.com/Connectivity/Commonly_Asked_Questions/Why_is_my_WHOOP_%22Catching_Up%22%3F), so it does not need to be connected to the phone all of the time." ], "metadata": { "id": "9qDNBmSFkRH4" } }, { "cell_type": "markdown", "source": [ "# 2. Authentication/Authorization\n", "\n", "To obtain access to data, authorization is required. All you'll need to do here is just put in your email and password for your WHOOP 4.0 device. We'll use this username and password to extract the data in the sections below.\n", "\n", "In this notebook, we use a blank email and password, which indicates that we would like to use synthetic data rather than real biometric data. Though, if you put in your real email and password, everything should work as intended and pull your data from the servers in an identical data format. All demo plots should run identically (assuming data is available for the given dates, etc.)." ], "metadata": { "id": "q_R9WhAHIbE9" } }, { "cell_type": "code", "source": [ "#@title Enter your username and password\n", "\n", "# download external file we've written to condense the API pinging\n", "# and parsing process\n", "!wget https://pastebin.com/raw/n4KG2wky -q -O whoop_user.py\n", "\n", "import requests\n", "import json\n", "from datetime import datetime\n", "import pytz\n", "import csv\n", "import os\n", "import pandas as pd\n", "import numpy as np\n", "import matplotlib as mpl\n", "import matplotlib.pyplot as plt\n", "import seaborn as sns\n", "from scipy.ndimage import gaussian_filter\n", "from math import ceil\n", "from tqdm import tqdm\n", "\n", "tqdm.pandas() # activate for pandas\n", "\n", "from whoop_user import WhoopUser\n", "\n", "email = '' #@param {type:\"string\"}\n", "password = '' #@param {type:\"string\"}\n", "\n", "print('Username:', email)\n", "print('Password:', password)" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "8FnxGK2Hjwox", "outputId": "ec239858-a510-43fb-f78a-b24784ebc9dd", "cellView": "form" }, "execution_count": null, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "Username: \n", "Password: \n" ] } ] }, { "cell_type": "markdown", "source": [ "# 3. Data Extraction\n", "\n", "Data can be extracted via an [unofficial API](https://app.swaggerhub.com/apis/DovOps/whoop-unofficial-api/1.0.1#/), which is also documented [here](https://www.reddit.com/r/whoop/comments/kjqf6w/i_created_a_python_wrapper_around_the_unofficial/) and [here](https://github.com/ianm199/unofficialWhoopAPI). This documented unofficial API works by replicating the requests your phone or browser makes when viewing your WHOOP data interactively either in the [WHOOP app](https://www.whoop.com/membership/app/) or the [WHOOP web app](https://app.whoop.com/login).\n", "\n", "We go into a bit of detail as to how this works below. This is not strictly necessary for extracting your data once, but it can be necessary if you want to extend this notebook for your own usage.\n", "\n", "### How data is uploaded to WHOOP\n", "\n", "Below, the first figure shows how data is uploaded to WHOOP servers. The watch stores very little (only up to 3 days worth of data if you do not connect your phone) and sends all of its data immediately to the phone, whereas the phone is responsible for uploading the data to the server at a relatively low rate (i.e. once every few minutes). Therefore, the phone is the mediator for data transfer.\n", "\n", "![WHOOP 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"\n", "\n", "### How data is downloaded from WHOOP\n", "\n", "To actually view data, the watch is not involved at all. Instead, the phone makes requests to WHOOP servers. The unofficial API aims to replicate these requests from your own computer.\n", "\n", "![WHOOP Figure download.png](https://drive.google.com/uc?export=view&id=1SSzkL4Xz8JCux4aBdiRUQFI6_rkPzBer)" ], "metadata": { "id": "BbaKJhcbkiq8" } }, { "cell_type": "markdown", "source": [ "Unfortunately, the API is fairly locked down, so it only allows you to make requests for information that is directly displayed onto the app or web app. This means that, as far as we know, we cannot extract continuous skin temperature measurements, as an example. That being said, we can still extract quite a bit:\n", "\n", "- Continuous all-day *heart rate* measurements (once every six seconds)\n", " - since many values can be derived from this (e.g. time slept, calories, heart rate variability, respiratory rate), heart rate is a pretty fundamental measurement that should be useful for many analyses\n", "- Coarse statistics for *blood oxygen level* and *skin temperature*\n", " - the WHOOP 4.0 [does in fact](https://www.whoop.com/thelocker/whoop-4-0-vs-3-0-whats-new/) contain sensors that measure both of these, but unfortunately only summary statistics (mean, variation) about these measurements over the course of a given sleep cycle\n", "\n", "

\n", "Now let's extract!\n", "\n", "Let's get some coarse statistics about every single sleep cycle you've had! You can also set custom start and end dates to get information only within that time range." ], "metadata": { "id": "D4jB5mQlXf-v" } }, { "cell_type": "code", "execution_count": null, "metadata": { "id": "JqfUZibhfB3L", "cellView": "form" }, "outputs": [], "source": [ "user = WhoopUser(email, password)\n", "user.SEED = 2\n", "user.SEED = 17\n", "#user = WhoopUser('', '')\n", "#@title Enter start and end dates (in the format yyyy-mm-dd)\n", "\n", "#set start and end dates - this will give you all the data from 2000-01-01 (January 1st, 2000) to 2100-02-03 (February 3rd, 2100), for example\n", "startStr='2000-01-01' #@param {type:\"string\"}\n", "endStr='2100-02-03' #@param {type:\"string\"}\n", "# get cycle data from start to end\n", "start_end ={\n", " 'start': startStr+'T00:00:00.000Z',\n", " 'end': endStr+'T00:00:00.000Z'\n", "}\n", "\n", "#show information for sleep cycles of interest \n", "cycles_df = user.get_cycles_df(params=start_end)\n", "\n", "#gives summary statistics for various metrics\n", "metrics_df = user.get_health_metrics_df(params=start_end)" ] }, { "cell_type": "markdown", "source": [ "This data provides a bird's eye view of your entire usage of the device. With `cycles_df` can see what your resting heart rate was for each day, your max heart rate for each day, and how much you slept each day (in milliseconds). With `metrics_df` you see other metrics (which are displayed under the \"Health Monitor\" tab in the phone app).\n", "\n", "# 4. Data Visualization \n", "Let's plot how much sleep you have had, replicating the plot from the app..." ], "metadata": { "id": "yzlY6g0vKrKn" } }, { "cell_type": "markdown", "source": [ "\n", "\n", "*Above is a plot from the app*" ], "metadata": { "id": "VuygEs3AR1Hu" } }, { "cell_type": "markdown", "source": [ "## 4.1 Plot Sleep\n", "\n", "Here we use matplotlib to reproduce the plot above. There's a lot of code here, but we added comments to help guide your reading." ], "metadata": { "id": "RXa6GR4TB41d" } }, { "cell_type": "code", "source": [ "#@title Plot sleep throughout the week\n", "start_date = \"2022-04-28\" #@param {type:\"date\"}\n", "\n", "start_idx = np.where(cycles_df.day == start_date)[0][0]\n", "\n", "\n", "from scipy import interpolate\n", "from datetime import datetime\n", "\n", "# only plotting a week\n", "PLOT_LENGTH = 7\n", "\n", "# custom font\n", "# https://stackoverflow.com/questions/35668219/how-to-set-up-a-custom-font-with-custom-path-to-matplotlib-global-font\n", "# download the font and unzip (quiet so it does not print)\n", "!wget -q 'https://dl.dafont.com/dl/?f=gymkhana'\n", "!unzip -qo \"index.html?f=gymkhana\"\n", "\n", "# move to directory where fonts should be kept\n", "!mv gymkhana-bk.ttf /usr/share/fonts/truetype/\n", "\n", "# build cache, redirect to /dev/null to suppress stdout output\n", "!fc-cache -f -v > /dev/null\n", "\n", "import matplotlib as mpl\n", "import matplotlib.font_manager as fm\n", "\n", "# try and except, just in case something fails we fallback onto the\n", "# default font\n", "try:\n", " fe = fm.FontEntry(\n", " #font name\n", " fname='/usr/share/fonts/truetype/gymkhana-bk.ttf',\n", " name='gymkhana')\n", " fm.fontManager.ttflist.insert(0, fe) # or append is fine\n", " mpl.rcParams['font.family'] = fe.name # = 'your custom ttf font name'\n", "except:\n", " pass\n", "\n", "weekdays = ['Mon', 'Tue', 'Wed', 'Thu', 'Fri', 'Sat', 'Sun']\n", "\n", "def ms_to_hm(ms):\n", " hours = int(ms / (60 * 60 * 1000))\n", " minutes = round((ms / (60 * 1000)) % 60)\n", "\n", " return hours, minutes\n", "\n", "def ms_to_text(ms):\n", " hours, minutes = ms_to_hm(ms)\n", "\n", " return f'{hours:02}:{minutes:02}'\n", "\n", "def determine_offset(i, values):\n", " \"\"\"\n", " Takes in array-like values and an index for that array, then\n", " computes what offset the text annotation should have. Intuition\n", " is that text annotation should not collide with the lines.\n", "\n", " NOTE: We attempted to use https://github.com/Phlya/adjustText, but\n", " could not get it to work.\n", " \"\"\"\n", "\n", " if i == 0:\n", " # put above if going down, otherwise below\n", " offset = (values[0] > values[1]) * 2 - 1\n", " elif i == sleep_dur.shape[0] - 1:\n", " # put above if going up, otherwise below\n", " offset = (values[i] > values[i - 1]) * 2 - 1\n", " elif values[i] < values[i+1] and values[i] < values[i-1]:\n", " # valley\n", " offset = -1\n", " elif values[i] > values[i+1] and values[i] > values[i-1]:\n", " # peak\n", " offset = 1\n", " elif values[i] > values[i+1] and values[i] < values[i-1]:\n", " # maintain same sign of slope (downwards)\n", " if values[i] - values[i+1] > values[i-1] - values[i]:\n", " offset = 1\n", " else:\n", " offset = -1\n", " elif values[i] < values[i+1] and values[i] > values[i-1]:\n", " # maintain same sign of slope (upwards)\n", " if values[i+1] - values[i] > values[i] - values[i-1]:\n", " offset = -1\n", " else:\n", " offset = 1\n", " \n", " return offset\n", "\n", "def plot_line_fancy(X, Y, label, color=None):\n", "\n", " plt.plot(X, Y / (60 * 60 * 1000), marker='o', markerfacecolor='black',\n", " markeredgewidth=1, markersize=10, linewidth=3, label=label,\n", " color=color)\n", "\n", " # add text annotations\n", " for i, dur in enumerate(Y):\n", " offset = determine_offset(i, np.array(Y))\n", " plt.text(i, 0.6 * offset + dur / (60 * 60 * 1000), ms_to_text(dur).lstrip('0'),\n", " ha='center', fontsize=15, color=color)\n", "\n", " # set to maximum y-value (in this case it is 12 hours)\n", " max_sleep_hours = 13\n", " plt.ylim(0, max_sleep_hours)\n", "\n", " # this function turns a string like '2022-04-28' into 'Thu\\n28'\n", " def day_label_to_fig_label(day):\n", " weekday = weekdays[datetime.strptime(day, '%Y-%m-%d').weekday()]\n", " day_num = str(int(day.split('-')[-1]))\n", "\n", " return weekday + '\\n' + day_num\n", "\n", " # set the labels on the left and bottom to match the app's plot\n", " plt.xticks(ticks=np.arange(PLOT_LENGTH),\n", " labels=[day_label_to_fig_label(day) for day in X],\n", " fontsize=15)\n", "\n", " plt.yticks(ticks = list(range(max_sleep_hours + 1))[::2],\n", " labels = [f'{i}:00' for i in range(max_sleep_hours + 1)][::2], \n", " rotation = 'horizontal',fontweight='bold', fontsize=15)\n", "\n", " # get rid of the little tickmarks on the bottom and side\n", " plt.tick_params(\n", " axis='x', # changes apply to the x-axis\n", " which='both', # both major and minor ticks are affected\n", " bottom=False, # ticks along the bottom edge are off\n", " top=False, # ticks along the top edge are off\n", " labelbottom=True)\n", "\n", " plt.tick_params(\n", " axis='y', # changes apply to the x-axis\n", " which='both', # both major and minor ticks are affected\n", " left=False, # ticks along the left edge are off\n", " labelbottom=True)\n", "\n", "with plt.style.context('dark_background'):\n", " sleep_dur = cycles_df.sleep_quality_duration.iloc[start_idx:start_idx+PLOT_LENGTH]\n", " sleep_need = cycles_df.sleep_need_total.iloc[start_idx:start_idx+PLOT_LENGTH]\n", " day = cycles_df.day.iloc[start_idx:start_idx+PLOT_LENGTH]\n", "\n", " # we'll use the same dark blue shade for the background color\n", " # throughout this plot\n", " background_color = '#13191C'\n", "\n", " # create the figure\n", " plt.figure(figsize=(12,8), facecolor=background_color)\n", "\n", " # plot both values over time\n", " plot_line_fancy(day, sleep_dur, 'Hours of Sleep', color='#6c97b2')\n", " plot_line_fancy(day, sleep_need, 'Sleep Need', color='#00fb9b')\n", "\n", " # insert legend\n", " plt.legend(facecolor=background_color, # ensure same background color\n", " frameon=False, # turn off boundaries\n", " ncol=2, # arrange horizontally\n", " prop={'size': 15}) # set font size\n", "\n", " # get rid of the axis lines\n", " for d in [\"left\", \"top\", \"bottom\", \"right\"]:\n", " plt.gca().spines[d].set_visible(False)\n", "\n", " # set background color *inside the figure*\n", " plt.gca().set_facecolor(color=background_color)\n", "\n", " # add horizontal grid\n", " plt.gca().grid(False)\n", " plt.gca().grid(axis='y', color='black')" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 505 }, "id": "_Bzi-CbWKiuR", "outputId": "f95f0c4b-db80-42de-bdcb-ef47be064504", "cellView": "form" }, "execution_count": null, "outputs": [ { "output_type": "display_data", "data": { "text/plain": [ "
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\n" }, "metadata": {} } ] }, { "cell_type": "markdown", "source": [ "*Above is a plot we created ourselves!*" ], "metadata": { "id": "gYDRBioPYGqk" } }, { "cell_type": "markdown", "source": [ "We can also dig into other statistics, such as skin temperature, taking advantage of that extra sensor. In fact, here we'll actually plot something you simply *cannot* see in the phone app nor web app! On the app, you can only see last night's skin temperature, but not previous night's skin temperature. Here, we'll plot the skin temperature the same week's sleep cycles." ], "metadata": { "id": "mfHOIvfi06kb" } }, { "cell_type": "code", "source": [ "#@title Skin Temperature Plot\n", "start_date = \"2022-04-28\" #@param {type:\"date\"}\n", "\n", "start_idx = np.where(metrics_df.day == start_date)[0][0]\n", "\n", "\n", "with plt.style.context('dark_background'):\n", " #start_idx = 2\n", " temps = metrics_df['SKIN_TEMPERATURE_FAHRENHEIT.current_value'].iloc[start_idx:start_idx+7]\n", " day = metrics_df.day.iloc[start_idx:start_idx+7]\n", "\n", " plt.figure(figsize=(12,8))\n", "\n", " plt.plot(day, temps, marker='o', markerfacecolor='black',\n", " markeredgewidth=1, markersize=10, linewidth=3)\n", "\n", " plt.title('Skin Temperature', fontsize=30)\n", " plt.ylabel('Temperature', fontsize=20)\n", " plt.xlabel('Day', fontsize=20)\n", "\n", " plt.yticks(fontsize=15)\n", " plt.xticks(ticks=day, labels=['-'.join(d.split('-')[1:]) for d in day], fontsize=15)" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 541 }, "id": "2vjl1dpZ0--3", "outputId": "8c262bbf-f122-4dca-f524-807f68a3f511", "cellView": "form" }, "execution_count": null, "outputs": [ { "output_type": "display_data", "data": { "text/plain": [ "
" ], "image/png": 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}, "metadata": {} } ] }, { "cell_type": "markdown", "source": [ "# 4.2 Plot Heart Rate\n", "\n", "Now let's dig a little deeper and look at our raw heart rate data! Let's get all of our heart rate data in the week 04-28 to 05-05. Feel free to change this to some other week of your choosing!\n", "\n", "Also, specify the timezone for which you were using this device (see [this list](https://en.wikipedia.org/wiki/List_of_tz_database_time_zones) for exact strings, under the column `TZ database name`)." ], "metadata": { "id": "NqIIv8UYbkbn" } }, { "cell_type": "code", "source": [ "#@title Set date range and timezone\n", "start = \"2022-04-28\" #@param {type:\"date\"}\n", "end = \"2022-05-05\" #@param {type:\"date\"}\n", "timezone = \"US/Pacific\" #@param {type:\"string\"}\n", "params = {\n", " 'start': f'{start}T00:00:00.000Z',\n", " 'end': f'{end}T00:00:00.000Z'\n", "}" ], "metadata": { "id": "vaqjksPbgtNA", "cellView": "form" }, "execution_count": null, "outputs": [] }, { "cell_type": "markdown", "source": [ "We'll use our WhoopUser class that we already initialized to extract the heart rate data first." ], "metadata": { "id": "Ztyd1j_EDFiF" } }, { "cell_type": "code", "source": [ "hr_df = user.get_heart_rate_df(params=params, timezone=timezone)" ], "metadata": { "id": "eCDHwdMRcdTT", "colab": { "base_uri": "https://localhost:8080/" }, "outputId": "f46fd535-2605-4d47-8fcd-c95eb266e9cc" }, "execution_count": null, "outputs": [ { "output_type": "stream", "name": "stderr", "text": [ "/content/whoop_user.py:223: FutureWarning: The pandas.np module is deprecated and will be removed from pandas in a future version. Import numpy directly instead\n", " hr_df_syn = pd.DataFrame(pd.np.empty((N, 2)) * pd.np.nan, columns=['heart_rate', 'timestamp'])\n", "100%|██████████| 275000/275000 [00:17<00:00, 16070.07it/s]\n", "43it [00:00, 294.60it/s]\n", "100%|██████████| 275000/275000 [00:13<00:00, 20977.43it/s]\n" ] } ] }, { "cell_type": "markdown", "source": [ "Let's see what `hr_df` contains in its raw form." ], "metadata": { "id": "dCqNOiepF7Yo" } }, { "cell_type": "code", "source": [ "hr_df" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 424 }, "id": "7EwVFmJksvTt", "outputId": "45722ef8-e80d-4766-f56c-ca6d40c9397b" }, "execution_count": null, "outputs": [ { "output_type": "execute_result", "data": { "text/plain": [ " heart_rate timestamp\n", "24686 71 2022-04-27 17:00:02-07:00\n", "24687 62 2022-04-27 17:00:09-07:00\n", "24688 98 2022-04-27 17:00:16-07:00\n", "24689 72 2022-04-27 17:00:23-07:00\n", "24690 59 2022-04-27 17:00:30-07:00\n", "... ... ...\n", "111081 78 2022-05-04 16:59:27-07:00\n", "111082 89 2022-05-04 16:59:34-07:00\n", "111083 78 2022-05-04 16:59:41-07:00\n", "111084 73 2022-05-04 16:59:48-07:00\n", "111085 86 2022-05-04 16:59:55-07:00\n", "\n", "[86400 rows x 2 columns]" ], "text/html": [ "\n", "
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heart_ratetimestamp
24686712022-04-27 17:00:02-07:00
24687622022-04-27 17:00:09-07:00
24688982022-04-27 17:00:16-07:00
24689722022-04-27 17:00:23-07:00
24690592022-04-27 17:00:30-07:00
.........
111081782022-05-04 16:59:27-07:00
111082892022-05-04 16:59:34-07:00
111083782022-05-04 16:59:41-07:00
111084732022-05-04 16:59:48-07:00
111085862022-05-04 16:59:55-07:00
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86400 rows × 2 columns

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\n", " \n", " \n", " \n", "\n", " \n", "
\n", "
\n", " " ] }, "metadata": {}, "execution_count": 7 } ] }, { "cell_type": "markdown", "source": [ "Now let's try to reproduce the heart rate line graph from the app, as shown below.\n", "\n", "\n", "\n", "*Above is a plot from the app*" ], "metadata": { "id": "z58aSrsdc1ql" } }, { "cell_type": "markdown", "source": [ "First, to satiate our curiosity, let's just see what the heart rate graph looks like for the entire week..." ], "metadata": { "id": "Z-vA6Vr4fWgD" } }, { "cell_type": "code", "source": [ "with plt.style.context('seaborn-darkgrid'):\n", "\n", " plt.figure(figsize=(18,8))\n", "\n", " plt.title('Heart Rate', fontsize=20)\n", "\n", " plt.plot(hr_df.timestamp, hr_df.heart_rate, linewidth=0.5, color='dimgrey')\n", " plt.fill_between(hr_df.timestamp, hr_df.heart_rate, color='grey', alpha=0.3)\n", "\n", " plt.ylim(0, 180)\n", " plt.ylabel('Heart Rate', fontsize=15)\n", " plt.xlabel('Time', fontsize=15)" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 519 }, "id": "3z5gybLMcp2m", "outputId": "4728dd72-6f93-4c8d-c2e2-933ffb2d08c0" }, "execution_count": null, "outputs": [ { "output_type": "display_data", "data": { "text/plain": [ "
" ], "image/png": 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\n" }, "metadata": {} } ] }, { "cell_type": "markdown", "source": [ "Great! We can see some periodic patterns arise! Let's do some simple Gaussian smoothing to try to see what these patterns really are. We use the [`gaussian_filter` method](https://docs.scipy.org/doc/scipy/reference/generated/scipy.ndimage.gaussian_filter.html) from SciPy for this." ], "metadata": { "id": "5G_E6dQAihlE" } }, { "cell_type": "code", "source": [ "stdev_minutes = 30\n", "# multiply by 60 to get stdev_seconds, then divide by 6 to get\n", "# this in units of measurements (once every six seconds)\n", "stdev = stdev_minutes * 60 / 6\n", "\n", "with plt.style.context('fivethirtyeight'):\n", "\n", " plt.figure(figsize=(18,8))\n", "\n", " plt.title('Heart Rate', fontsize=20)\n", "\n", " plt.plot(hr_df.timestamp, hr_df.heart_rate, linewidth=0.5, color='dimgrey', label='Raw')\n", " plt.fill_between(hr_df.timestamp, hr_df.heart_rate, color='grey', alpha=0.3)\n", "\n", " plt.plot(hr_df.timestamp, gaussian_filter(np.array(hr_df.heart_rate), sigma=stdev), linewidth=3, color='black', label='Smoothed')\n", "\n", " plt.ylabel('Heart Rate', fontsize=15)\n", " plt.xlabel('Time', fontsize=15)\n", " plt.legend(prop={'size': 20})" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 554 }, "id": "_X3Rlmh8jOWV", "outputId": "1567e010-048d-4343-e562-3faac2506a94" }, "execution_count": null, "outputs": [ { "output_type": "display_data", "data": { "text/plain": [ "
" ], "image/png": 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}, "metadata": {} } ] }, { "cell_type": "markdown", "source": [ "Now let's get back to trying to reproduce the specific plot we see in the app. While the plotting code is long (which is necessary to reproduce as close as possible), it has lots of comments to guide you through what each component does, if you want to adapt it for your own usage. Regardless, here are some high-level pointers:\n", "\n", "- We define gaps (when the user takes off the device) as any space between measurements that exceeds 12 seconds. To find the gaps, we compute the consecutive pairwise differences between measurement timestamps, and find where the difference exceeds 12 seconds.\n", "- `plt.fill_between` and `plt.plot` are ordered in such a way that subsequent ones are *overlayed* ontop of the previous ones, allowing us to worry less about iterating through in the right way from left to right and instead just plotting waking hours, sleep hours, and gaps completely separately.\n", "- For some weird reason, when requesting cycles or sleep data, the API does not care about time, only date. Since both sleeps are on the same day (in the UTC timezone), we just have to request one day of sleep information, and the time is arbitrary for both parameters fed into `user.get_sleeps_df()`." ], "metadata": { "id": "zGGWHuueNtcm" } }, { "cell_type": "code", "source": [ "#@title Reproduce 24 hour heart rate plot\n", "from matplotlib.ticker import FormatStrFormatter\n", "from dateutil import tz\n", "import datetime\n", "\n", "# measurements are taken every six seconds\n", "HEART_RATE_RECORDING_LENGTH = 6\n", "\n", "day_num = 1\n", "\n", "params_day = {\n", " 'start': f'2022-05-{str(day_num+1).zfill(2)} T00:00:00.000Z',\n", " 'end': f'2022-05-{str(day_num+1).zfill(2)} T23:00:00.000Z' # arbitrary time choice\n", "}\n", "\n", "sleeps = user.get_sleeps_df(params=params_day, timezone='US/Pacific')\n", "from datetime import datetime\n", "\n", "stdev_minutes = .5\n", "# multiply by 60 to get stdev_seconds, then divide by 6 to get\n", "# this in units of measurements (once every six seconds)\n", "stdev = stdev_minutes * 60 / 6\n", "\n", "with plt.style.context('seaborn-darkgrid'):\n", " # get the start and end times as timestamps by using the datetime library\n", " start_ts = datetime.strptime(f'2022-05-{str(day_num).zfill(2)} 21:50:00-07:00', '%Y-%m-%d %H:%M:%S%z').timestamp()\n", " end_ts = datetime.strptime(f'2022-05-{str(day_num+1).zfill(2)} 21:50:00-07:00', '%Y-%m-%d %H:%M:%S%z').timestamp()\n", "\n", " # now find the indices in hr_df.timestamp that match as closely as possible\n", " start_idx = np.argmin(np.abs(hr_df.timestamp.apply(lambda x: x.timestamp()) - start_ts))\n", " end_idx = np.argmin(np.abs(hr_df.timestamp.apply(lambda x: x.timestamp()) - end_ts))\n", "\n", " x = np.array(hr_df.timestamp.iloc[start_idx:end_idx])\n", " y = hr_df.heart_rate.iloc[start_idx:end_idx]\n", "\n", " # make it not as bumpy with gaussian filter\n", " y = gaussian_filter(y, sigma=stdev)\n", "\n", " plt.figure(figsize=(22,8), facecolor='white')\n", "\n", " x_timestamp = np.array([x_.timestamp() for x_ in x])\n", "\n", " # get the gaps. we include [6] as well because when you do np.diff,\n", " # it actually leaves out exactly one element\n", " differences = np.concatenate((np.diff(x_timestamp), [6]))\n", "\n", " # interpret a gap (i.e. when a user takes off the device for some prolonged\n", " # period of time) as any two measurements that are taken more than\n", " # 6 * 2 = 12 seconds apart, to account for minor variations around 6s\n", " gap_idxes = np.where(differences > HEART_RATE_RECORDING_LENGTH * 2)[0]\n", "\n", " # get the sleeps\n", " sleep_idxes = []\n", " for lower, upper in zip(sleeps.time_lower_bound, sleeps.time_upper_bound):\n", " # get the location in the timestamp array that is closest to `lower`\n", " lower_idx = np.argmin(np.abs((x_timestamp - lower.timestamp()) - 0))\n", " # get the location in the timestamp array that is closest to `upper`\n", " upper_idx = np.argmin(np.abs((x_timestamp - upper.timestamp()) - 0))\n", "\n", " sleep_idxes.append((lower_idx, upper_idx))\n", "\n", " # fill in the area under the curve with different colors depending\n", " # on whether it is a gap or a sleep\n", "\n", " # first, we just plot the entire thing\n", " plt.plot(x, y, linewidth=0.75, color='#d1d1d1')\n", " plt.fill_between(x, y, color='#e3e3e3', alpha=0.3)\n", "\n", " # now we overlay sleeps\n", " for sleep_start, sleep_end in sleep_idxes:\n", " plt.plot(x[sleep_start:sleep_end], y[sleep_start:sleep_end], linewidth=0.75, color='#3f8fc5')\n", " if sleep_start >= sleep_end:\n", " continue\n", "\n", " plt.fill_between(x[sleep_start:sleep_end], y[sleep_start:sleep_end], color='#eaf1f6', alpha=0.3)\n", "\n", " # now we overlay gaps by overlaying with white\n", " for gap_idx in gap_idxes:\n", " plt.plot(x[gap_idx-2:gap_idx+2], y[gap_idx-2:gap_idx+2], linewidth=1, color='white')\n", " plt.fill_between(x[gap_idx-2:gap_idx+2], y[gap_idx-100:gap_idx+100].max(), color='white')\n", "\n", " plt.ylim(0, 225)\n", " plt.xlim(x[0] - pd.Timedelta(minutes=30), x[-1])\n", "\n", " # set the x ticks to be every 4 hours, just like the app's plot\n", " datetimes = [\n", " datetime.strptime(f'2022-05-{str(day_num).zfill(2)} 22:00:00-0700', '%Y-%m-%d %H:%M:%S%z'),\n", " datetime.strptime(f'2022-05-{str(day_num+1).zfill(2)} 02:00:00-0700', '%Y-%m-%d %H:%M:%S%z'),\n", " datetime.strptime(f'2022-05-{str(day_num+1).zfill(2)} 06:00:00-0700', '%Y-%m-%d %H:%M:%S%z'),\n", " datetime.strptime(f'2022-05-{str(day_num+1).zfill(2)} 10:00:00-0700', '%Y-%m-%d %H:%M:%S%z'),\n", " datetime.strptime(f'2022-05-{str(day_num+1).zfill(2)} 14:00:00-0700', '%Y-%m-%d %H:%M:%S%z'),\n", " datetime.strptime(f'2022-05-{str(day_num+1).zfill(2)} 18:00:00-0700', '%Y-%m-%d %H:%M:%S%z')\n", " ]\n", "\n", " plt.xticks(ticks=datetimes,\n", " labels=['10:00pm', '2:00am', '6:00am', '10:00am', '2:00pm', '6:00pm'],\n", " fontsize=12,\n", " color='grey')\n", " \n", " # ensure that the bottom labels are padded\n", " plt.tick_params(\n", " axis='x', # changes apply to the x-axis\n", " which='both', # both major and minor ticks are affected\n", " bottom=False, # ticks along the bottom edge are off\n", " pad=15)\n", "\n", " # set y ticks so that they are major and minor, so that we can have gridlines\n", " # on a larger interval\n", " plt.gca().set_yticks(np.arange(0, 250, 25)[::2], minor=False)\n", " plt.gca().set_yticks(np.arange(0, 250, 25)[1::2], minor=True)\n", " plt.gca().yaxis.set_minor_formatter(FormatStrFormatter(\"%d\"))\n", "\n", " # get rid of the ticks for the y-axis\n", " plt.tick_params(\n", " axis='y', # changes apply to the x-axis\n", " which='minor', # both major and minor ticks are affected\n", " bottom=False, # ticks along the bottom edge are off\n", " labelcolor='grey')\n", "\n", " # set background color *inside the figure*\n", " plt.gca().set_facecolor(color='white')\n", "\n", " # add horizontal grid\n", " plt.gca().grid(axis='x', color='#e5e5e5')\n", " plt.gca().grid(axis='y', color='#e5e5e5', which='major')\n", "\n", " # ensure the bottom axis is slightly darker and extends all the way\n", " # to the left\n", " plt.gca().spines['bottom'].set_edgecolor('grey')\n", " plt.gca().spines['bottom'].set_linewidth(1)\n", " plt.gca().spines['bottom'].set_visible(True)" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 498 }, "id": "SONwTbouNs7y", "outputId": "5b71e8bb-8c21-4c28-f8c3-2dcef84c5042", "cellView": "form" }, "execution_count": null, "outputs": [ { "output_type": "display_data", "data": { "text/plain": [ "
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\n" }, "metadata": {} } ] }, { "cell_type": "markdown", "source": [ "*Above is a plot we created ourselves!*\n", "\n", "As you can see, we are able to reproduce not only just the heart rate over time, but also when the heart rate is not recorded, and also when the user goes to sleep, either for a night sleep or for a nap." ], "metadata": { "id": "BqeR6aZBFDGY" } }, { "cell_type": "markdown", "source": [ "# 5. Data Analysis\n", "\n", "Data isn't much without some analysis, so we're going to do some in this section.\n", "\n", "DISCLAIMER: the analyses below may not be 100% biologically or scientifically grounded; the code is here to assist in your process, if you are interested in asking these kinds of questions." ], "metadata": { "id": "cFTN-_UhzJX2" } }, { "cell_type": "markdown", "source": [ "## 5.1 Heart rate vs. sleep period length\n", "Maybe the heart rate is correlated with how long a particular sleep period was. Let's see if this hypothesis is true. First, we get all sleeps. We just give a time period from 2020 until May 29nd, 2022, because that'll catch everything for this user up until the time this notebook and the associated analyses below were run (so that our analysis results stay the same)." ], "metadata": { "id": "jXiKwtAV1b7p" } }, { "cell_type": "code", "source": [ "#@title Set date range and timezone\n", "start = \"2020-01-01\" #@param {type:\"date\"}\n", "end = \"2022-05-22\" #@param {type:\"date\"}\n", "timezone = \"US/Pacific\" #@param {type:\"string\"}\n", "params_all = {\n", " 'start': f'{start}T00:00:00.000Z',\n", " 'end': f'{end}T00:00:00.000Z'\n", "}" ], "metadata": { "id": "JJw2PGO3DYtU", "cellView": "form" }, "execution_count": null, "outputs": [] }, { "cell_type": "code", "source": [ "sleeps = user.get_sleeps_df(params=params_all, timezone=timezone)\n", "sleeps" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 1000 }, "id": "X_YcZ9XU0ILf", "outputId": "8702a7e7-83e6-4e10-f169-3ada5a21d4ed" }, "execution_count": null, "outputs": [ { "output_type": "execute_result", "data": { "text/plain": [ " cycle_id sleep_id cycles_count disturbance_count \\\n", "0 786 831 1 14 \n", "1 499 877 0 14 \n", "2 930 331 0 7 \n", "3 217 598 1 20 \n", "4 803 117 2 7 \n", "5 69 365 0 23 \n", "6 810 354 3 9 \n", "7 98 51 2 12 \n", "8 983 848 2 11 \n", "9 78 6 2 13 \n", "10 775 454 3 14 \n", "11 358 563 0 12 \n", "12 620 729 1 18 \n", "13 924 941 1 14 \n", "14 869 839 1 7 \n", "15 168 368 0 14 \n", "16 293 996 1 11 \n", "17 446 652 1 9 \n", "18 575 376 0 16 \n", "19 444 566 1 14 \n", "20 607 193 0 14 \n", "21 685 647 1 11 \n", "22 513 113 2 13 \n", "23 797 919 1 9 \n", "24 926 679 0 12 \n", "25 465 290 1 15 \n", "26 427 977 0 11 \n", "27 151 324 1 15 \n", "28 236 107 0 11 \n", "29 327 554 1 10 \n", "30 721 850 0 11 \n", "31 566 369 2 18 \n", "32 548 944 0 16 \n", "33 669 534 0 5 \n", "34 709 979 2 9 \n", "35 142 538 0 13 \n", "36 171 572 2 8 \n", "37 396 796 1 20 \n", "38 855 235 0 13 \n", "39 203 23 0 15 \n", "40 392 938 1 12 \n", "41 139 373 1 10 \n", "42 582 687 0 18 \n", "\n", " time_upper_bound time_lower_bound is_nap \\\n", "0 2022-04-26 09:17:57-07:00 2022-04-26 01:00:00-07:00 False \n", "1 2022-04-26 15:28:26-07:00 2022-04-26 15:00:00-07:00 True \n", "2 2022-04-27 09:27:38-07:00 2022-04-27 01:00:00-07:00 False \n", "3 2022-04-27 15:53:37-07:00 2022-04-27 15:00:00-07:00 True \n", "4 2022-04-28 08:50:54-07:00 2022-04-28 01:00:00-07:00 False \n", "5 2022-04-28 15:47:20-07:00 2022-04-28 15:00:00-07:00 True \n", "6 2022-04-29 09:53:54-07:00 2022-04-29 01:00:00-07:00 False \n", "7 2022-04-29 15:59:27-07:00 2022-04-29 15:00:00-07:00 True \n", "8 2022-04-30 10:07:15-07:00 2022-04-30 01:00:00-07:00 False \n", "9 2022-04-30 16:36:27-07:00 2022-04-30 15:00:00-07:00 True \n", "10 2022-05-01 10:04:16-07:00 2022-05-01 01:00:00-07:00 False \n", "11 2022-05-01 15:19:30-07:00 2022-05-01 15:00:00-07:00 True \n", "12 2022-05-02 09:22:25-07:00 2022-05-02 01:00:00-07:00 False \n", "13 2022-05-02 15:47:45-07:00 2022-05-02 15:00:00-07:00 True \n", "14 2022-05-03 07:59:17-07:00 2022-05-03 01:00:00-07:00 False \n", "15 2022-05-03 15:41:16-07:00 2022-05-03 15:00:00-07:00 True \n", "16 2022-05-04 08:50:26-07:00 2022-05-04 01:00:00-07:00 False \n", "17 2022-05-04 16:05:48-07:00 2022-05-04 15:00:00-07:00 True \n", "18 2022-05-05 08:25:51-07:00 2022-05-05 01:00:00-07:00 False \n", "19 2022-05-05 17:21:47-07:00 2022-05-05 15:00:00-07:00 True \n", "20 2022-05-06 08:15:01-07:00 2022-05-06 01:00:00-07:00 False \n", "21 2022-05-06 15:28:59-07:00 2022-05-06 15:00:00-07:00 True \n", "22 2022-05-07 09:09:54-07:00 2022-05-07 01:00:00-07:00 False \n", "23 2022-05-07 15:40:09-07:00 2022-05-07 15:00:00-07:00 True \n", "24 2022-05-08 09:27:00-07:00 2022-05-08 01:00:00-07:00 False \n", "25 2022-05-08 15:46:39-07:00 2022-05-08 15:00:00-07:00 True \n", "26 2022-05-09 07:14:30-07:00 2022-05-09 01:00:00-07:00 False \n", "27 2022-05-09 16:35:34-07:00 2022-05-09 15:00:00-07:00 True \n", "28 2022-05-10 08:14:47-07:00 2022-05-10 01:00:00-07:00 False \n", "29 2022-05-10 15:44:41-07:00 2022-05-10 15:00:00-07:00 True \n", "30 2022-05-11 07:49:22-07:00 2022-05-11 01:00:00-07:00 False \n", "31 2022-05-11 15:12:00-07:00 2022-05-11 15:00:00-07:00 True \n", "32 2022-05-12 07:06:42-07:00 2022-05-12 01:00:00-07:00 False \n", "33 2022-05-12 16:00:59-07:00 2022-05-12 15:00:00-07:00 True \n", "34 2022-05-13 09:02:03-07:00 2022-05-13 01:00:00-07:00 False \n", "35 2022-05-13 15:37:05-07:00 2022-05-13 15:00:00-07:00 True \n", "36 2022-05-14 08:52:12-07:00 2022-05-14 01:00:00-07:00 False \n", "37 2022-05-14 16:04:40-07:00 2022-05-14 15:00:00-07:00 True \n", "38 2022-05-15 10:03:46-07:00 2022-05-15 01:00:00-07:00 False \n", "39 2022-05-15 15:22:28-07:00 2022-05-15 15:00:00-07:00 True \n", "40 2022-05-16 09:11:34-07:00 2022-05-16 01:00:00-07:00 False \n", "41 2022-05-16 16:17:13-07:00 2022-05-16 15:00:00-07:00 True \n", "42 2022-05-17 08:21:22-07:00 2022-05-17 01:00:00-07:00 False \n", "\n", " in_bed_duration light_sleep_duration latency_duration no_data_duration \\\n", "0 8.299187 4.149593 0 0 \n", "1 0.474137 0.237069 0 0 \n", "2 8.460614 4.230307 0 0 \n", "3 0.893689 0.446844 0 0 \n", "4 7.848470 3.924235 0 0 \n", "5 0.789084 0.394542 0 0 \n", "6 8.898347 4.449174 0 0 \n", "7 0.990975 0.495487 0 0 \n", "8 9.120842 4.560421 0 0 \n", "9 1.607619 0.803809 0 0 \n", "10 9.071268 4.535634 0 0 \n", "11 0.325271 0.162635 0 0 \n", "12 8.373860 4.186930 0 0 \n", "13 0.796051 0.398026 0 0 \n", "14 6.988255 3.494128 0 0 \n", "15 0.687900 0.343950 0 0 \n", "16 7.840609 3.920304 0 0 \n", "17 1.096686 0.548343 0 0 \n", "18 7.430997 3.715498 0 0 \n", "19 2.363327 1.181663 0 0 \n", "20 7.250415 3.625207 0 0 \n", "21 0.483293 0.241646 0 0 \n", "22 8.165274 4.082637 0 0 \n", "23 0.669218 0.334609 0 0 \n", "24 8.450036 4.225018 0 0 \n", "25 0.777598 0.388799 0 0 \n", "26 6.241848 3.120924 0 0 \n", "27 1.592799 0.796399 0 0 \n", "28 7.246474 3.623237 0 0 \n", "29 0.744898 0.372449 0 0 \n", 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sws_duration wake_duration quality_duration \n", "0 0.374207 2.489756 0.829919 7.469268 \n", "1 0.373756 0.142241 0.047414 0.426724 \n", "2 0.352968 2.538184 0.846061 7.614553 \n", "3 0.544819 0.268107 0.089369 0.804320 \n", "4 0.383946 2.354541 0.784847 7.063623 \n", "5 0.425368 0.236725 0.078908 0.710176 \n", "6 0.609418 2.669504 0.889835 8.008512 \n", "7 0.809198 0.297292 0.099097 0.891877 \n", "8 0.355837 2.736253 0.912084 8.208758 \n", "9 0.252681 0.482286 0.160762 1.446857 \n", "10 0.862854 2.721380 0.907127 8.164141 \n", "11 0.474888 0.097581 0.032527 0.292744 \n", "12 0.497271 2.512158 0.837386 7.536474 \n", "13 0.516666 0.238815 0.079605 0.716446 \n", "14 0.595472 2.096477 0.698826 6.289430 \n", "15 0.676832 0.206370 0.068790 0.619110 \n", "16 0.885807 2.352183 0.784061 7.056548 \n", "17 0.394750 0.329006 0.109669 0.987017 \n", "18 0.674037 2.229299 0.743100 6.687897 \n", "19 0.218315 0.708998 0.236333 2.126994 \n", "20 0.901105 2.175124 0.725041 6.525373 \n", "21 0.641838 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\n", "
\n", " \n", " \n", " \n", "\n", " \n", "
\n", "
\n", " " ] }, "metadata": {}, "execution_count": 12 } ] }, { "cell_type": "markdown", "source": [ "Then, let's get the heart rate over time for each sleep. Note that requesting all of the heart rate data will take just a bit of time, depending on how many weeks we have to request data for. We'll use the `verbose` parameter to ensure that we maintain our sanity as we wait for it to complete." ], "metadata": { "id": "XDOqecIA1sRM" } }, { "cell_type": "code", "source": [ "hr_df = user.get_heart_rate_df(params_all, timezone='US/Pacific', verbose=True)" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "HaxN3BQ95x6f", "outputId": "3e0ed93c-0722-4c46-ee3d-6d905512b299" }, "execution_count": null, "outputs": [ { "output_type": "stream", "name": "stderr", "text": [ "100%|██████████| 275000/275000 [00:13<00:00, 20516.82it/s]\n" ] } ] }, { "cell_type": "markdown", "source": [ "Now let's take this raw heart rate data over the course of several weeks and analyze it against sleep." ], "metadata": { "id": "s8RaDEjzFvgx" } }, { "cell_type": "code", "source": [ "heart_rates = []\n", "lengths = []\n", "\n", "for lower, upper in zip(sleeps.time_lower_bound, sleeps.time_upper_bound):\n", " heart_rate = np.array(hr_df[np.logical_and(lower < hr_df.timestamp, hr_df.timestamp < upper)].heart_rate)\n", " length = (upper - lower).seconds / 3600 # hours\n", "\n", " heart_rates.append(heart_rate)\n", " lengths.append(length)\n", "\n", "sleeps['length_in_hours'] = np.array(lengths)\n", "sleeps['median_heart_rate'] = np.array([np.median(hr) for hr in heart_rates]) # median heart rates" ], "metadata": { "id": "4rWt2bBTF0dk" }, "execution_count": null, "outputs": [] }, { "cell_type": "markdown", "source": [ "Let's make a quick plot to get some intuition. Here we just use [seaborn](https://seaborn.pydata.org/), as it's very quick to get beautiful plots out with minimal effort." ], "metadata": { "id": "aiYLeHrcRBbW" } }, { "cell_type": "code", "source": [ "p = sns.jointplot(x='length_in_hours', y='median_heart_rate', data=sleeps, kind='reg')" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 441 }, "id": "6939iJ-VScX8", "outputId": "52eed209-029d-4b7b-f047-e1e70721ee1c" }, "execution_count": null, "outputs": [ { "output_type": "display_data", "data": { "text/plain": [ "
" ], "image/png": 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\n" }, "metadata": { "needs_background": "light" } } ] }, { "cell_type": "markdown", "source": [ "As we can see from the scatterplot above, it looks like there might be a correlation there. Let's compute $R^2$ just to see exactly how correlated.\n", "\n", "We'll follow [this documentation](https://docs.scipy.org/doc/scipy-0.15.1/reference/generated/scipy.stats.linregress.html) and perform a linear regression to obtain the coefficient of determination." ], "metadata": { "id": "qAUwwFCSLJR6" } }, { "cell_type": "code", "source": [ "from scipy import stats\n", "slope, intercept, r_value, p_value, std_err = stats.linregress(sleeps['length_in_hours'], sleeps['median_heart_rate'])\n", "\n", "print(f'Slope: {slope:.3g}')\n", "print(f'Coefficient of determination: {r_value**2:.3g}')\n", "print(f'p-value: {p_value:.3g}')" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "ZtF5zjQOImFD", "outputId": "5a0bb669-1dde-4fab-f900-bfb6d0f10386" }, "execution_count": null, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "Slope: -2.75\n", "Coefficient of determination: 0.957\n", "p-value: 1.4e-29\n" ] } ] }, { "cell_type": "markdown", "source": [ "We also see that the p-value, which is determined by scipy to be the two-sided p-value for a hypothesis test whose null hypothesis is that the slope is zero, is significant ($<$0.05).\n", "\n", "So given this evidence from this particular data, maybe length of a sleep period is correlated with your heart rate.\n", "\n", "However, let's suppose there was an anomaly in the heart rate (such as due to a measurement error or device failure) that skewed our results, such as below:" ], "metadata": { "id": "wa4p2YUML_di" } }, { "cell_type": "code", "source": [ "sleeps.loc[1, ['median_heart_rate']] = 800\n", "\n", "from scipy import stats\n", "slope, intercept, r_value, p_value, std_err = stats.linregress(sleeps['length_in_hours'], sleeps['median_heart_rate'])\n", "\n", "print(f'Slope: {slope:.3g}')\n", "print(f'Coefficient of determination: {r_value**2:.3g}')\n", "print(f'p-value: {p_value:.3g}')" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "jPOhXvI0TkIc", "outputId": "702917ae-1764-448c-c029-4fc22b078a5e" }, "execution_count": null, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "Slope: -8.17\n", "Coefficient of determination: 0.0653\n", "p-value: 0.098\n" ] } ] }, { "cell_type": "markdown", "source": [ "We see that if we perform the same p-value analysis as done before, we get that the p-value is not significant.\n", "\n", "Let's implement a system that assumes the data was sampled according to a multivariate normal distribution to automatically detect and remove outliers like this, based on the method described [here](https://medium.com/analytics-vidhya/outlier-detection-with-multivariate-normal-distribution-in-python-480033ba3a8a).\n", "\n", "Warning: anomaly/outlier detection is done just to show an example of data processing that can be done and may hide genuine values that have clinical significance. Use at your own risk.\n" ], "metadata": { "id": "2R7J6mGvTjrp" } }, { "cell_type": "code", "source": [ "from scipy.stats import multivariate_normal\n", "#calculate the covariance matrix\n", "data = np.stack((sleeps['length_in_hours'],sleeps['median_heart_rate']),axis=0)\n", "covariance_matrix = np.cov(data)\n", "\n", "#calculating the mean\n", "mean_values = [np.mean(sleeps['length_in_hours']),np.mean(sleeps['median_heart_rate'])]\n", "\n", "#multivariate normal distribution\n", "model = multivariate_normal(cov=covariance_matrix,mean=mean_values)\n", "data = np.stack((sleeps['length_in_hours'],sleeps['median_heart_rate']),axis=1)\n", "\n", "#finding the outliers\n", "\n", "#any point with a probability lower than the threshold value is considered an outlier and removed \n", "threshold = 1.0e-07\n", "outlier = model.pdf(data).reshape(-1) < threshold\n", "\n", "newData=data\n", "outlierValues=[]\n", "for boolean,i in enumerate(outlier):\n", " if i == True:\n", " print(data[boolean],\" is an Outlier\")\n", " print(np.where(data==(data[boolean])[0])[0].item(0))\n", " #delete outliers\n", " newData=np.delete(newData,np.where(newData==(data[boolean])[0])[0].item(0),axis=0)\n", "\n", "#plot new graph with outliers removed\n", "#newData[:,0] correspond to the new lengths, and newData[:,1] correspond to the new values\n", "p = sns.jointplot(x=newData[:,0], y=newData[:,1], kind='reg')" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 477 }, "id": "ItdN7ZRPTN1r", "outputId": "8b91cc14-40ce-4ee6-a24b-5dd4c70f4f18" }, "execution_count": null, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "[4.73888889e-01 8.00000000e+02] is an Outlier\n", "1\n" ] }, { "output_type": "display_data", "data": { "text/plain": [ "
" ], "image/png": 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\n" }, "metadata": { "needs_background": "light" } } ] }, { "cell_type": "markdown", "source": [ "Now let's perform a linear regression again to see how this affects our results." ], "metadata": { "id": "Xw7JYtcajQkM" } }, { "cell_type": "code", "source": [ "from scipy import stats\n", "slope, intercept, r_value, p_value, std_err = stats.linregress(newData[:,0], [np.median(hr) for hr in newData[:,1]])\n", "\n", "print(f'Slope: {slope:.3g}')\n", "print(f'Coefficient of determination: {r_value**2:.3g}')\n", "print(f'p-value: {p_value:.3g}')" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "MX5Gp6VAjP0h", "outputId": "ddca3208-553c-4389-8efb-50a97c345715" }, "execution_count": null, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "Slope: -2.73\n", "Coefficient of determination: 0.956\n", "p-value: 1.03e-28\n" ] } ] }, { "cell_type": "markdown", "source": [ "With the outlier removed, we can see that our results are return to statistical significance!" ], "metadata": { "id": "__WttZPOjaFs" } }, { "cell_type": "markdown", "source": [ "## 5.2: Heart rate vs. nap or sleep\n", "\n", "Now we'll look at whether the median heart rate changes depending on whether you are napping or sleeping.\n", "\n", "We've already extracted the heart rate time series data for each sleep, so now all we need to do is just get `is_nap` column." ], "metadata": { "id": "K4PobApQP2mZ" } }, { "cell_type": "code", "source": [ "plt.figure(figsize=(14,9))\n", "sns.set_style('darkgrid')\n", "\n", "# just return the sleeps dataframe back to normal\n", "sleeps.loc[1, ['median_heart_rate']] = 62\n", "\n", "sns.stripplot(x='is_nap',y='median_heart_rate', data=sleeps)" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 570 }, "id": "6U0Rjgl4VENk", "outputId": "ff5fff1f-fc37-4226-d9cf-3114415f844a" }, "execution_count": null, "outputs": [ { "output_type": "execute_result", "data": { "text/plain": [ "" ] }, "metadata": {}, "execution_count": 20 }, { "output_type": "display_data", "data": { "text/plain": [ "
" ], "image/png": 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\n" }, "metadata": { "needs_background": "light" } } ] }, { "cell_type": "markdown", "source": [ "In the plot above, we do see that the heart rate does seem to vary a bit depending on whether the user is napping or not. Here, we see that when the the sleep is marked as a nap (whether by the user or automatic detection, [depending on when it occurs during the day](https://support.whoop.com/WHOOP_Data/Activities__Auto-Detection/Sleep_Auto-Detection)), we tend to get a median heart rate higher than otherwise.\n", "\n", "Note: WHOOP calculates hours of sleep without including naps, [while sleep need is calculated with naps taken into account](https://www.whoop.com/thelocker/how-long-should-you-nap/).\n", "\n", "Let's do a T-test to see if the difference in heart rate is significant." ], "metadata": { "id": "BSz1nebkWFF6" } }, { "cell_type": "code", "source": [ "result = stats.ttest_ind(sleeps.median_heart_rate[sleeps.is_nap == True],\n", " sleeps.median_heart_rate[sleeps.is_nap == False])\n", "\n", "print(f'P-value is {result.pvalue:.3g}')" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "Hbkw2JgFWNjk", "outputId": "ef438e83-b3f2-48a9-86d5-afcebbd85a98" }, "execution_count": null, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "P-value is 2.94e-43\n" ] } ] }, { "cell_type": "markdown", "source": [ "Looks significant (<0.05)!" ], "metadata": { "id": "PpvwsKasW4xr" } } ] }