Plot FitBit sleep schedule using Matplotlib.

plot-sleep-schedule.py

#!/usr/bin/env python3
import glob
import csv
import itertools

from datetime import datetime, timedelta, time
from collections import namedtuple

import numpy as np
import matplotlib.pyplot as plt
import matplotlib.patches as mpatches


def consume(iterator, n=None):
    "Advance the iterator n-steps ahead. If n is None, consume entirely."
    if n is None:
        collections.deque(iterator, maxlen=0)
    else:
        next(itertools.islice(iterator, n, n), None)


SleepEntry = namedtuple("SleepEntry", ["start", "end"])
DATE_FORMAT = "%Y-%m-%d %I:%M%p"
BLOCKS_PER_DAY = 24 * 2

SPLIT_HOUR = 12 + 4

if __name__ == "__main__":
    sleep_entries = []
    for file in glob.iglob("./data/*.csv"):
        with open(file, "r") as f:
            reader = csv.reader(f)
            consume(reader, 2)
            for row in reader:
                if len(row) > 2:
                    sleep_entries.append(
                        SleepEntry(
                            start=datetime.strptime(row[0], DATE_FORMAT),
                            end=datetime.strptime(row[1], DATE_FORMAT),
                        )
                    )

    earliest_time = min([e.start for e in sleep_entries])
    latest_time = max([e.end for e in sleep_entries])
    print("Earliest Time: %s, Latest Time: %s" % (earliest_time, latest_time))
    print(len(sleep_entries), "entries.")

    start_date = datetime.combine(earliest_time.date(), time(SPLIT_HOUR, 0))
    end_date = datetime.combine(latest_time.date(), time(SPLIT_HOUR, 0))

    days = (end_date - start_date).days
    print(days, "days.")
    sleep_matrix = np.zeros((BLOCKS_PER_DAY, days))

    for i, j in itertools.product(range(BLOCKS_PER_DAY), range(days)):
        dt = start_date + timedelta(days=j, hours=i // 2, minutes=30 * (i % 2))
        if any([(dt >= entry.start and dt < entry.end) for entry in sleep_entries]):
            sleep_matrix[i, j] = 1.0

    fig, ax = plt.subplots()
    im = ax.imshow(sleep_matrix)
    ax.set_yticks(range(BLOCKS_PER_DAY))
    ax.set_yticklabels(
        [
            time((SPLIT_HOUR + i // 2) % 24, 30 * (i % 2)).strftime("%-I:%M%p")
            for i in range(BLOCKS_PER_DAY)
        ]
    )

    ax.set_xticks(range(days))
    ax.set_xticklabels(
        [(start_date + timedelta(days=j)).strftime("%b-%-d") for j in range(days)],
        rotation="vertical",
    )

    patches = [
        mpatches.Patch(color=im.cmap(im.norm(0)), label="Awake"),
        mpatches.Patch(color=im.cmap(im.norm(1)), label="Sleep"),
    ]
    ax.legend(handles=patches)

    for label in ax.yaxis.get_ticklabels()[1::2]:
        label.set_visible(False)
    for label in ax.xaxis.get_ticklabels():
        label.set_visible(False)
    for label in ax.xaxis.get_ticklabels()[::5]:
        label.set_visible(True)
    plt.show()

x-README.md

Plot FitBit Sleep Schedule using Matplotlib

Go to https://www.fitbit.com/export/user/data and export sleep data CSV's month by month. Place it in a folder called data/. Run the python script.