plot-hr.py

#!/usr/bin/python3
#
# Copyright (C) 2020-2021 Julian Andres Klode <[email protected]>
#
# This Source Code Form is subject to the terms of the Mozilla
# Public License, v. 2.0. If a copy of the MPL was not distributed
# with this file, You can obtain one at
# https://mozilla.org/MPL/2.0/.
#
"""HR plotting script.

Usage: plot-hr.py [--png]

Plot HR of oura ring vs elite hrv export.
"""

from typing import (
    Iterator,
    List,
    Tuple,
    NewType,
)
import datetime
import matplotlib.pyplot as plt  # type: ignore
import matplotlib.animation as animation  # type: ignore
import sys
import itertools
from hrvanalysis import (  # type: ignore
    get_time_domain_features,
    remove_outliers,
    interpolate_nan_values,
    remove_ectopic_beats,
)

import json

# Type declarations
Time = datetime.datetime
Interval = NewType("Interval", int)
HR = NewType("HR", float)
RMSSD = NewType("RMSSD", float)
NaN = float("NaN")


def windows(
    times: List[Time], hrs: List[Interval], interval: Interval
) -> Iterator[Tuple[float, Iterator[int]]]:
    """Yields (_, indices) tuples for windows of length 5"""
    return itertools.groupby(
        range(len(hrs)), lambda k: times[k].timestamp() // interval
    )


def expand_rmssd5(stamps: List[Time], rrs: List[Interval]) -> List[RMSSD]:
    """Calculate RMSSD over 5 minute intervals.

    Takes a list of time stamps and the raw RR intervalls, and returns
    a list of RMSSD values.
    """
    out = []

    for group, indices in windows(stamps, rrs, Interval(5 * 60)):
        window_rrs = [rrs[i] for i in indices]
        time_domain_features = get_time_domain_features(window_rrs)

        for i in window_rrs:
            out.append(time_domain_features["rmssd"])

    return out


def read_elite() -> Tuple[List[Time], List[HR], List[RMSSD], RMSSD]:
    """Read EliteHRV RR export file"""
    times: List[Time] = []
    hrs: List[HR] = []
    rrs: List[Interval] = []

    stamp = datetime.datetime(
        year=2021,
        month=5,
        day=24,
        hour=23,
        minute=4,
        second=20,
        tzinfo=datetime.timezone(datetime.timedelta(seconds=7200)),
    )

    rr_intervals_list = [int(rr) for rr in open("2021-05-24 23-04-20.txt")]

    # This remove outliers from signal
    rr_intervals_without_outliers = remove_outliers(
        rr_intervals=rr_intervals_list, low_rri=300, high_rri=2000
    )
    # This replace outliers nan values with linear interpolation
    interpolated_rr_intervals = interpolate_nan_values(
        rr_intervals=rr_intervals_without_outliers, interpolation_method="linear"
    )

    # This remove ectopic beats from signal
    nn_intervals_list = remove_ectopic_beats(
        rr_intervals=interpolated_rr_intervals, method="malik"
    )
    # This replace ectopic beats nan values with linear interpolation
    interpolated_nn_intervals = interpolate_nan_values(rr_intervals=nn_intervals_list)

    for rr in interpolated_nn_intervals:
        stamp += datetime.timedelta(milliseconds=rr)
        hr = 1.0 / rr

        times.append(stamp)
        hrs.append(hr)
        rrs.append(rr)

    time_domain_features = get_time_domain_features(rrs)
    print("Elite:", time_domain_features["rmssd"])
    rmssds = expand_rmssd5(times, rrs)

    return times, hrs, rmssds, RMSSD(time_domain_features["rmssd"])


def read_oura() -> Tuple[List[Time], List[HR], List[RMSSD], RMSSD]:
    """Read oura ring export"""
    with open("/home/jak/Downloads/oura_2021-05-25T07-45-08.json") as fobj:
        oura = json.load(fobj)

    times: List[Time] = []
    hrs: List[HR] = []
    rmssds: List[RMSSD] = []
    sleep = oura["sleep"][-1]
    stamp = datetime.datetime.fromisoformat(sleep["bedtime_start"])

    for hr5, hrv5 in zip(sleep["hr_5min"], sleep["rmssd_5min"]):
        for second in range(5 * 60):
            times.append(stamp)
            hrs.append(HR(hr5) if hr5 else HR(NaN))
            rmssds.append(RMSSD(hrv5) if hrv5 else RMSSD(NaN))
            stamp += datetime.timedelta(seconds=1)

    return times, hrs, rmssds, sleep["rmssd"]


def do_plot(i: int) -> None:
    """Main entry point"""
    times, hrs, rmssds, rmssd = read_elite()
    times1, hrs1, rmssds1, rmssd1 = read_oura()

    plt.gcf().clear()

    # Plot the graphs
    plt.plot(times1, rmssds1, "-", label="oura hrv")
    plt.plot(times, rmssds, "-", label="tickr hrv", alpha=0.3)

    # Plot the averages
    plt.plot(times, [rmssd for _ in times], "--", label="tickr hrv average", alpha=0.5)
    plt.plot(
        times1, [rmssd1 for _ in times1], "--", label="oura hrv average", alpha=0.5
    )

    plt.grid()
    plt.legend()
    plt.gcf().autofmt_xdate()


def main(argv: List[str]) -> None:
    fig = plt.figure()

    if "--png" in argv:
        do_plot(0)
        plt.savefig("hr.png", bbox_inches="tight", dpi=150)
    else:
        ani = animation.FuncAnimation(fig, do_plot, interval=10000)
        plt.show()


if __name__ == "__main__":
    main(sys.argv)