File size: 3,015 Bytes
0be92ce | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 | import os
from pathlib import Path
import numpy as np
from upscaling_scoring import (
calculate_final_score,
calculate_length_score,
calculate_preliminary_score,
calculate_quality_score,
)
def calculate_score_grid(pieapp_values, content_lengths):
scores = np.zeros((len(pieapp_values), len(content_lengths)))
for i, pieapp_score in enumerate(pieapp_values):
quality_score = calculate_quality_score(float(pieapp_score))
for j, content_length in enumerate(content_lengths):
length_score = calculate_length_score(float(content_length))
preliminary_score = calculate_preliminary_score(quality_score, length_score)
scores[i, j] = calculate_final_score(preliminary_score)
return scores
def plot_upscaling_scores(output_path=None):
import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D # noqa: F401
pieapp_values = np.linspace(0.0, 2.0, 200)
length_ranges = [
(5.0, 10.0, "Current support: 5-10s"),
(5.0, 320.0, "Full range: 5-320s"),
]
fig, axes = plt.subplots(
2,
len(length_ranges),
figsize=(6 * len(length_ranges), 11),
gridspec_kw={"height_ratios": [1, 1.2]},
)
for col, (min_length, max_length, title) in enumerate(length_ranges):
content_lengths = np.linspace(min_length, max_length, 200)
scores = calculate_score_grid(pieapp_values, content_lengths)
ax_heat = axes[0, col]
im = ax_heat.imshow(
scores,
aspect="auto",
origin="lower",
extent=[content_lengths[0], content_lengths[-1], pieapp_values[0], pieapp_values[-1]],
cmap="viridis",
)
ax_heat.set_xlabel("Content Length (s)")
ax_heat.set_ylabel("PIEAPP Score (lower is better)")
ax_heat.set_title(title)
fig.colorbar(im, ax=ax_heat, label="Final Score")
ax_3d = fig.add_subplot(2, len(length_ranges), len(length_ranges) + col + 1, projection="3d")
axes[1, col].set_visible(False)
length_grid, pieapp_grid = np.meshgrid(content_lengths, pieapp_values)
ax_3d.plot_surface(length_grid, pieapp_grid, scores, cmap="viridis", edgecolor="none", alpha=0.9)
ax_3d.set_xlabel("Content Length (s)")
ax_3d.set_ylabel("PIEAPP")
ax_3d.set_zlabel("Score")
ax_3d.set_title(title)
ax_3d.view_init(elev=30, azim=-135)
fig.suptitle("Upscaling Final Score vs PIEAPP & Content Length", fontsize=15, y=0.98)
plt.tight_layout(rect=[0, 0, 1, 0.96])
if output_path is None:
output_path = Path(__file__).resolve().with_name("upscaling_scoring_plot.png")
else:
output_path = Path(output_path)
plt.savefig(output_path, dpi=200, bbox_inches="tight")
plt.close(fig)
return output_path
if __name__ == "__main__":
out_path = plot_upscaling_scores(os.environ.get("UPSCALING_SCORING_PLOT_PATH"))
print(f"Upscaling plot saved to {out_path}")
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