vkgs-sim / third_party /ktx-src /external /astc-encoder /Test /astc_test_competitive_plot.py

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#!/usr/bin/env python3
# SPDX-License-Identifier: Apache-2.0
# -----------------------------------------------------------------------------
# Copyright 2022 Arm Limited
#
# Licensed under the Apache License, Version 2.0 (the "License"); you may not
# use this file except in compliance with the License. You may obtain a copy
# of the License at:
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS, WITHOUT
# WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the
# License for the specific language governing permissions and limitations
# under the License.
# -----------------------------------------------------------------------------
"""
This script is a simple test result plotter for sweeps on multiple compressors.
"""
import csv
import numpy as np
import matplotlib.pyplot as plt
import sys

DATABASE = "competitive.csv"


class Series:

    def __init__(self, name, perf, qual):
        self.name = name
        self.perf = perf
        self.qual = qual


def get_series(database, compressor, quality, block_size):
    title = f"{compressor} {quality} {block_size}"
    in_section = False

    perf = []
    qual = []

    with open(database) as csvfile:
        reader = csv.reader(csvfile)
        for row in reader:
            if len(row) == 1:
                in_section = row[0] == title
                continue

            if in_section:
                perf.append(float(row[2]))
                qual.append(float(row[3]))

    return (perf, qual)


def plot(block_size, series_set):

    for series in series_set:
        plt.scatter(series.perf, series.qual, s=2, label=series.name)

    plt.xlabel("Speed (MT/s)")
    plt.ylabel("PSNR dB")
    plt.legend(loc='lower right', prop={'size': 6})

    plt.tight_layout()
    plt.savefig(f"ASTC_v_ISPC_{block_size}.png")
    plt.clf()


def plot_diff(series_a, series_b):

    diff_perf = np.divide(series_a.perf, series_b.perf)
    diff_qual = np.subtract(series_a.qual, series_b.qual)
    label = f"{series_a.name} vs {series_b.name}"

    plt.scatter(diff_perf, diff_qual, s=2, c="#0091BD", label=label)
    plt.scatter(np.mean(diff_perf), np.mean(diff_qual), s=10, c="#FFA500", marker="*")

    plt.axhline(y=0, color="r", linestyle="dotted", lw=0.5)
    plt.axvline(x=1, color="r", linestyle="dotted", lw=0.5)

    plt.xlabel("Relative speed")
    plt.ylabel("PSNR diff (dB)")
    plt.legend(loc='lower right', prop={'size': 6})

    plt.tight_layout()
    file_name = label.replace(" ", "_") + ".png"
    plt.savefig(file_name)
    plt.clf()


def main():

    block_sizes = ["4x4", "6x6", "8x8"]

    for block_size in block_sizes:
        series_set = []

        perf, qual = get_series(DATABASE, "ISPC", "rgba", block_size)
        series_set.append(Series(f"{block_size} IPSC Slow", perf, qual))

        perf, qual = get_series(DATABASE, "ISPC", "rgb", block_size)
        series_set.append(Series(f"{block_size} IPSC Fast", perf, qual))

        perf, qual = get_series(DATABASE, "ASTC", "60", block_size)
        series_set.append(Series(f"{block_size} ASTC 60", perf, qual))

        perf, qual = get_series(DATABASE, "ASTC", "50", block_size)
        series_set.append(Series(f"{block_size} ASTC 50", perf, qual))

        perf, qual = get_series(DATABASE, "ASTC", "10", block_size)
        series_set.append(Series(f"{block_size} ASTC 10", perf, qual))

        perf, qual = get_series(DATABASE, "ASTC", "8", block_size)
        series_set.append(Series(f"{block_size} ASTC 8", perf, qual))

        plot(block_size, series_set)

        plot_diff(series_set[3], series_set[0])

    return 0


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

	#!/usr/bin/env python3
	# SPDX-License-Identifier: Apache-2.0
	# -----------------------------------------------------------------------------
	# Copyright 2022 Arm Limited
	#
	# Licensed under the Apache License, Version 2.0 (the "License"); you may not
	# use this file except in compliance with the License. You may obtain a copy
	# of the License at:
	#
	# http://www.apache.org/licenses/LICENSE-2.0
	#
	# Unless required by applicable law or agreed to in writing, software
	# distributed under the License is distributed on an "AS IS" BASIS, WITHOUT
	# WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the
	# License for the specific language governing permissions and limitations
	# under the License.
	# -----------------------------------------------------------------------------
	"""
	This script is a simple test result plotter for sweeps on multiple compressors.
	"""
	import csv
	import numpy as np
	import matplotlib.pyplot as plt
	import sys

	DATABASE = "competitive.csv"


	class Series:

	def __init__(self, name, perf, qual):
	self.name = name
	self.perf = perf
	self.qual = qual


	def get_series(database, compressor, quality, block_size):
	title = f"{compressor} {quality} {block_size}"
	in_section = False

	perf = []
	qual = []

	with open(database) as csvfile:
	reader = csv.reader(csvfile)
	for row in reader:
	if len(row) == 1:
	in_section = row[0] == title
	continue

	if in_section:
	perf.append(float(row[2]))
	qual.append(float(row[3]))

	return (perf, qual)


	def plot(block_size, series_set):

	for series in series_set:
	plt.scatter(series.perf, series.qual, s=2, label=series.name)

	plt.xlabel("Speed (MT/s)")
	plt.ylabel("PSNR dB")
	plt.legend(loc='lower right', prop={'size': 6})

	plt.tight_layout()
	plt.savefig(f"ASTC_v_ISPC_{block_size}.png")
	plt.clf()


	def plot_diff(series_a, series_b):

	diff_perf = np.divide(series_a.perf, series_b.perf)
	diff_qual = np.subtract(series_a.qual, series_b.qual)
	label = f"{series_a.name} vs {series_b.name}"

	plt.scatter(diff_perf, diff_qual, s=2, c="#0091BD", label=label)
	plt.scatter(np.mean(diff_perf), np.mean(diff_qual), s=10, c="#FFA500", marker="*")

	plt.axhline(y=0, color="r", linestyle="dotted", lw=0.5)
	plt.axvline(x=1, color="r", linestyle="dotted", lw=0.5)

	plt.xlabel("Relative speed")
	plt.ylabel("PSNR diff (dB)")
	plt.legend(loc='lower right', prop={'size': 6})

	plt.tight_layout()
	file_name = label.replace(" ", "_") + ".png"
	plt.savefig(file_name)
	plt.clf()


	def main():

	block_sizes = ["4x4", "6x6", "8x8"]

	for block_size in block_sizes:
	series_set = []

	perf, qual = get_series(DATABASE, "ISPC", "rgba", block_size)
	series_set.append(Series(f"{block_size} IPSC Slow", perf, qual))

	perf, qual = get_series(DATABASE, "ISPC", "rgb", block_size)
	series_set.append(Series(f"{block_size} IPSC Fast", perf, qual))

	perf, qual = get_series(DATABASE, "ASTC", "60", block_size)
	series_set.append(Series(f"{block_size} ASTC 60", perf, qual))

	perf, qual = get_series(DATABASE, "ASTC", "50", block_size)
	series_set.append(Series(f"{block_size} ASTC 50", perf, qual))

	perf, qual = get_series(DATABASE, "ASTC", "10", block_size)
	series_set.append(Series(f"{block_size} ASTC 10", perf, qual))

	perf, qual = get_series(DATABASE, "ASTC", "8", block_size)
	series_set.append(Series(f"{block_size} ASTC 8", perf, qual))

	plot(block_size, series_set)

	plot_diff(series_set[3], series_set[0])

	return 0


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