Add ktx

2026-06-14 19:09:18 +01:00
parent 14bd1a9271
commit 13fa90a0e9
3958 changed files with 999286 additions and 4 deletions
@@ -0,0 +1,127 @@
+#!/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())