Dense Timeline plot

dense_timeline_plot.py

import pandas as pd
import matplotlib.pyplot as plt
import itertools
from datetime import datetime, timedelta
from matplotlib.patches import Patch

plt.figure(figsize=(30, 10), constrained_layout=True)
xscale = 3

sleep_start, sleep_end = 0.75, 1.375
min_per_day = 24 * 60

xd = hdf['date'].unique()
xs, xe, xt = hdf['date'].min(), hdf['date'].max(), hdf['date'].nunique()

period = pd.date_range(start=xs, end=xe)
days = len(period)
todate = datetime.now().replace(hour=0, minute=0, second=0, microsecond=0)
tr = range(int(sleep_start*min_per_day), int(sleep_end*min_per_day)+1, 60)

for cur_date in period:
    t = cur_date.day - xs.day
    blocks = 1+(1+days)*xscale
    xoff = (1+t)*xscale
    x1, x2, x3 = round((xoff-.48)/blocks, 5), round((xoff+.55)/blocks, 5), round((xoff+1.48)/blocks, 5)

    hhdf = hdf.query('date == @cur_date').eval('''
    ys = (start.dt.hour * 60 + start.dt.minute) / @min_per_day
    ye = (end.dt.hour * 60 + end.dt.minute) / @min_per_day
    yd = 1 - ys + ye
    ''')
    ahdf = hhdf.query('source == "apollo"')
    ohdf = hhdf.query('source == "oura"')
    if ahdf.size > 0:
        plt.bar(x=t*xscale, align='edge',width=-1, color='dodgerblue', bottom=ahdf['ys'].values[0], height=ahdf['yd'].values[0])
    if ohdf.size > 0:
        plt.bar(x=t*xscale, align='edge', width=1, color='tomato', bottom=ohdf['ys'].values[0], height=ohdf['yd'].values[0])

    for ts in sa_times:
        tm = (ts.hour*60+ts.minute)/min_per_day
        if ts.date() == cur_date and tm >= sleep_start:
            plt.axhline(y=tm, xmin=x1, xmax=x2, color='lightsteelblue')
        if ts.date() == cur_date + timedelta(days=1) and 1+tm <= sleep_end:
            plt.axhline(y=1+tm, xmin=x1, xmax=x2, color='lightsteelblue')

    for ts in dist_times:
        tm = (ts.hour*60+ts.minute)/min_per_day
        if ts.date() == cur_date and tm >= sleep_start:
            plt.axhline(y=tm, xmin=x2, xmax=x3, color='brown')
        if ts.date() == cur_date + timedelta(days=1) and 1+tm <= sleep_end:
            plt.axhline(y=1+tm, xmin=x2, xmax=x3, color='brown')

plt.ylim((sleep_end, sleep_start))
plt.yticks([z/min_per_day for z in tr], [(todate + timedelta(minutes=m)).strftime("%I %p") for m in tr])
plt.xticks([t*xscale for t in range(days)], [d.strftime("%Y/%m/%d\n%a") for d in period], rotation=90)
plt.xlabel('bedtime start date')
plt.ylabel('local bedtime')
plt.legend([Patch(color='dodgerblue'), Patch(color='tomato'), plt.axhline(color='lightsteelblue'), plt.axhline(color='brown')], ['apollo', 'oura', 'stay asleep vibes', 'disturbances (oura)'])
plt.title("Timeline chart depicting the sleeping activity of a user over a time span")
plt.tight_layout()
plt.show()

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