benchmark_ringbuffer.py

# License: MIT
# Copyright © 2022 Frequenz Energy-as-a-Service GmbH

"""
Performance test for the `Ringbuffer` class
"""

import random
from datetime import datetime, timedelta

import numpy as np

from frequenz.sdk.util.ringbuffer import (
    ArrayContainer,
    ListContainer,
    OrderedRingBuffer,
    RingBuffer,
)

MINUTES_IN_29_DAYS = 29 * 24 * 60


def fill_buffer(days, buffer):
    """Fill the given buffer up to the given amount of days, one sample per
    minute"""
    random.seed(0)
    basetime = datetime(2022, 1, 1)

    for day in range(days):
        # Push in random order
        for i in random.sample(range(24 * 60), 24 * 60):
            buffer.update(basetime + timedelta(days=day, minutes=i, seconds=i % 3), i)


# Fills a buffer completely up and then gets the data for each of the 29 days
def test_days(days, buffer):
    print(".", end="", flush=True)

    fill_buffer(days, buffer)

    basetime = datetime(2022, 1, 1)

    for day in range(days):
        minutes = buffer.window(
            basetime + timedelta(days=day), basetime + timedelta(days=day + 1)
        )

# Takes a buffer, fills it up and then excessively gets the data for each day to
# calculate the average/median.
def test_slices(days, buffer):
    print(".", end="", flush=True)
    fill_buffer(days, buffer)

    # Chose uneven starting point so that for the first/last window data has to
    # be copied
    basetime = datetime(2022, 1, 1, 0, 5, 13, 88)

    total = 0

    for _ in range(5):
        for day in range(days):
            minutes = buffer.window(
                basetime + timedelta(days=day), basetime + timedelta(days=day + 1)
            )

            total += np.average(minutes)
            (f"{basetime + timedelta(days=day)} average {np.average(minutes)}")
            (f"{basetime + timedelta(days=day)} median {np.median(minutes)}")
    # print(total)


# Fills a buffer completely up and then gets the data for each of the 29 days
def test_29_days_list():
    test_days(29, OrderedRingBuffer([0] * MINUTES_IN_29_DAYS, 60))


def test_29_days_array():
    test_days(
        29,
        OrderedRingBuffer(
            np.empty(
                shape=MINUTES_IN_29_DAYS,
            ),
            60,
        ),
    )


def test_29_days_slicing_list():
    test_slices(29, OrderedRingBuffer([0] * MINUTES_IN_29_DAYS, 60))


def test_29_days_slicing_array():
    test_slices(
        29,
        OrderedRingBuffer(
            np.empty(
                shape=MINUTES_IN_29_DAYS,
            ),
            60,
        ),
    )


import timeit

num_runs = 40

print(f"       {''.join(['='] * (num_runs + 1))}")
print("Array: ", end="")
duration_array = timeit.Timer(test_29_days_array).timeit(number=num_runs)
print("\nList:  ", end="")
duration_list = timeit.Timer(test_29_days_list).timeit(number=num_runs)
print("")

print(
    f"Time to fill 29 days with data:\n\t"
    + f"Array: {duration_array/num_runs} seconds\n\t"
    + f"List:  {duration_list/num_runs} seconds\n\t"
    + f"Diff:  {duration_array/num_runs -  duration_list/num_runs}"
)

print(f"       {''.join(['='] * (num_runs + 1))}")
print("Array: ", end="")
duration_array = timeit.Timer(test_29_days_slicing_array).timeit(number=num_runs)
print("\nList:  ", end="")
duration_list = timeit.Timer(test_29_days_slicing_list).timeit(number=num_runs)
print("")

print(
    f"Filling 29 days and running average & mean on every day:\n\t"
    + f"Array: {duration_array/num_runs} seconds\n\t"
    + f"List:  {duration_list/num_runs} seconds\n\t"
    + f"Diff:  {duration_array/num_runs -  duration_list/num_runs}"
)