# SPDX-License-Identifier: BSD-2-Clause

# Copyright (C) 2016, 2024 embedded brains GmbH & Co. KG
#
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions
# are met:
# 1. Redistributions of source code must retain the above copyright
#    notice, this list of conditions and the following disclaimer.
# 2. Redistributions in binary form must reproduce the above copyright
#    notice, this list of conditions and the following disclaimer in the
#    documentation and/or other materials provided with the distribution.
#
# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
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# IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE
# ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE
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import json
import math
import re
import statistics
import matplotlib.pyplot as plt  # type: ignore
from matplotlib import ticker  # type: ignore


def _normed_coefficient_of_variation(counter: list[int]) -> float:
    return (statistics.stdev(counter) / statistics.mean(counter)) / math.sqrt(
        len(counter))


def _plot(data: dict) -> None:
    _, axes = plt.subplots()
    axes.set_title("SMP Lock Fairness")
    axes.set_xlabel("Active Workers")
    axes.set_ylabel("Normed Coefficient of Variation")
    axes.set_yscale("symlog", linthresh=1e-6)
    x = list(range(2, len(data[0]["results"]) + 1))
    axes.xaxis.set_major_locator(ticker.FixedLocator(x))
    for samples in data:
        if samples["lock-object"] != "global":
            continue
        if samples["section-type"] != "local counter":
            continue
        y = [
            _normed_coefficient_of_variation(results["counter"])
            for results in samples["results"][1:]
        ]
        axes.plot(x, y, label=samples["lock-type"], marker="o")
    axes.legend(loc="best")
    plt.savefig("smplock01fair.png")
    plt.savefig("smplock01fair.pdf")
    plt.close()


_JSON_DATA = re.compile(
    r"\*\*\* BEGIN OF JSON DATA \*\*\*(.*)"
    r"\*\*\* END OF JSON DATA \*\*\*", re.DOTALL)

with open("smplock01.scn", "r", encoding="utf-8") as src:
    match = _JSON_DATA.search(src.read())
    data = json.loads(match.group(1))

_plot(data)