Fix in plots (#21)

* Fix in plots

* Fix in plots

* Fix CI/CD

* Fix CI/CD

* Fix CI/CD

Author: ternaus

.github/workflows/ci.yml

@@ -13,7 +13,7 @@ jobs:
     strategy:
       fail-fast: true
       matrix:
-        python-version: ["3.12"]
+        python-version: ["3.13"]
     steps:
     - name: Checkout
       uses: actions/checkout@v4
@@ -26,4 +26,7 @@ jobs:
       run: |
         python -m pip install --upgrade uv
         uv pip install --system -r requirements-dev.txt
-        uv pip install --system .
+
+    - name: Check code formatting with pre-commit
+      run: |
+        pre-commit run --all-files

benchmark/runner.py

@@ -1,5 +1,6 @@
 import importlib
 import json
+import logging
 import os
 import time
 from pathlib import Path
@@ -12,6 +13,13 @@
 from .transforms.specs import TRANSFORM_SPECS
 from .utils import get_image_loader, get_library_versions, get_system_info, time_transform, verify_thread_settings
 
+# Configure logging
+logging.basicConfig(
+    level=logging.INFO,
+    format="%(asctime)s - %(name)s - %(levelname)s - %(message)s",
+)
+logger = logging.getLogger(__name__)
+
 # Environment variables for various libraries
 os.environ["OMP_NUM_THREADS"] = "1"
 os.environ["OPENBLAS_NUM_THREADS"] = "1"
@@ -89,7 +97,7 @@ def load_images(self) -> list[Any]:
             raise ValueError("No valid RGB images found in the directory")
 
         if len(rgb_images) < self.num_images:
-            print(f"Warning: Only found {len(rgb_images)} valid RGB images, requested {self.num_images}")
+            logger.warning("Only found %d valid RGB images, requested %d", len(rgb_images), self.num_images)
 
         return rgb_images
 
@@ -228,7 +236,7 @@ def run_transform(self, transform_spec: Any, images: list[Any]) -> dict[str, Any
 
     def run(self, output_path: Path | None = None) -> dict[str, Any]:
         """Run all benchmarks"""
-        print(f"\nRunning benchmarks for {self.library}")
+        logger.info("Running benchmarks for %s", self.library)
         images = self.load_images()
 
         # Collect metadata
@@ -263,7 +271,7 @@ def run(self, output_path: Path | None = None) -> dict[str, Any]:
         if output_path:
             output_path = Path(output_path)
             output_path.parent.mkdir(parents=True, exist_ok=True)
-            with open(output_path, "w") as f:
+            with output_path.open("w") as f:
                 json.dump(full_results, f, indent=2)
 
         return full_results

docs/images/images_speedup_analysis.png

@@ -34,7 +34,7 @@ license = { file = "LICENSE" }
 maintainers = [ { name = "Vladimir Iglovikov" } ]
 
 authors = [ { name = "Vladimir Iglovikov" } ]
-requires-python = ">=3.12"
+requires-python = ">=3.13"
 
 classifiers = [
   "Development Status :: 5 - Production/Stable",
@@ -44,7 +44,6 @@ classifiers = [
   "Operating System :: OS Independent",
   "Programming Language :: Python",
   "Programming Language :: Python :: 3 :: Only",
-  "Programming Language :: Python :: 3.12",
   "Programming Language :: Python :: 3.13",
   "Topic :: Scientific/Engineering :: Artificial Intelligence",
   "Topic :: Scientific/Engineering :: Image Processing",
@@ -63,12 +62,12 @@ exclude = [ "output*", "output_videos*", ".venv*", "tests*" ]
 
 [tool.ruff]
 # Exclude a variety of commonly ignored directories.
-target-version = "py312"
+target-version = "py313"
 
 line-length = 120
 indent-width = 4
 
-# Assume Python 3.12
+# Assume Python 3.13
 exclude = [
   ".bzr",
   ".direnv",
@@ -121,6 +120,7 @@ lint.ignore = [
   "D101",
   "D102",
   "D103",
+  "D104",
   "D105",
   "D107",
   "D415",
@@ -152,7 +152,7 @@ lint.dummy-variable-rgx = "^(_+|(_+[a-zA-Z0-9_]*[a-zA-Z0-9]+?))$"
 lint.pydocstyle.convention = "google"
 
 [tool.mypy]
-python_version = "3.12"
+python_version = "3.13"
 ignore_missing_imports = true
 follow_imports = "silent"
 warn_redundant_casts = true

docs/videos/videos_speedup_analysis.png

@@ -2,4 +2,5 @@ matplotlib
 pandas
 pre_commit>=3.5.0
 pytest>=8.3.3
+seaborn
 tabulate

pyproject.toml

@@ -8,8 +8,8 @@
 from typing import Any
 
 import matplotlib.pyplot as plt
-import numpy as np
 import pandas as pd
+import seaborn as sns
 
 # Configure logging
 logging.basicConfig(
@@ -138,37 +138,31 @@ def plot_speedup_distribution(
         plt.close()
         return
 
+    # Set seaborn style for better aesthetics
+    sns.set_style("whitegrid")
+    sns.set_context("paper", font_scale=1.1)
+
+    palette = sns.color_palette("tab10", 4)
+    hist_color = palette[0]  # Blue
+    top_color = palette[2]  # Green
+    bottom_color = palette[3]  # Red
+
     # Create figure with three subplots
-    fig = plt.figure(figsize=(15, 5))
+    fig = plt.figure(figsize=(15, 6.5))  # Increased height for better spacing
     gs = plt.GridSpec(1, 3, width_ratios=[1.5, 1, 1])
     ax1 = fig.add_subplot(gs[0])
     ax2 = fig.add_subplot(gs[1])
     ax3 = fig.add_subplot(gs[2])
 
-    # Use colorblind-friendly colors
-    hist_color = "#4878D0"  # Blue
-    top_color = "#60BD68"  # Green
-    bottom_color = "#EE6677"  # Red
-
     # 1. Histogram of typical speedups (< max_speedup)
     typical_speedups = comparison_df[comparison_df["Speedup"] < max_speedup]["Speedup"]
 
     if len(typical_speedups) > 0:
-        ax1.hist(typical_speedups, bins=15, color=hist_color, alpha=0.7, edgecolor="black")
-        ax1.axvline(
-            typical_speedups.median(),
-            color="#404040",
-            linestyle="--",
-            linewidth=1.5,
-            label=f"Median: {typical_speedups.median():.2f}x",
-        )
-        ax1.axvline(1, color="#404040", linestyle=":", linewidth=1.5, alpha=0.7, label="No speedup (1x)")
-        ax1.grid(True, alpha=0.3)
+        sns.histplot(typical_speedups, bins=15, color=hist_color, alpha=0.7, edgecolor="black", ax=ax1)
 
         ax1.set_xlabel("Speedup (x)", fontsize=12)
         ax1.set_ylabel("Number of transforms", fontsize=12)
-        ax1.set_title(f"(a) Distribution of Typical Speedups\n(< {max_speedup}x)", fontsize=14)
-        ax1.legend(fontsize=10)
+        ax1.set_title(f"(a) Distribution of Speedups < {max_speedup}x", fontsize=14)
     else:
         ax1.text(0.5, 0.5, "No speedup data < 20x", ha="center", va="center", fontsize=12)
         ax1.set_axis_off()
@@ -177,24 +171,32 @@ def plot_speedup_distribution(
     top_n = min(10, len(comparison_df))
     if top_n > 0:
         top_10 = comparison_df.nlargest(top_n, "Speedup")
-        bars = ax2.barh(np.arange(len(top_10)), top_10["Speedup"], color=top_color, alpha=0.7, edgecolor="black")
-        ax2.set_yticks(np.arange(len(top_10)))
-        ax2.set_yticklabels(top_10["Transform"], fontsize=10)
+        sns.barplot(
+            x="Speedup",
+            y="Transform",
+            data=top_10,
+            color=top_color,
+            alpha=0.7,
+            edgecolor="black",
+            ax=ax2,
+        )
         ax2.grid(True, alpha=0.3)
 
-        for _, bar in enumerate(bars):
-            width = bar.get_width()
+        # Add text labels for speedup values
+        for i, v in enumerate(top_10["Speedup"]):
             ax2.text(
-                width + 0.05,
-                bar.get_y() + bar.get_height() / 2,
-                f"{width:.2f}x",
+                v + 0.05,
+                i,
+                f"{v:.2f}x",
                 ha="left",
                 va="center",
                 fontsize=10,
                 bbox={"facecolor": "white", "alpha": 0.8, "edgecolor": "none"},
             )
 
         ax2.set_xlabel("Speedup (x)", fontsize=12)
+        # Remove y-label "Transform"
+        ax2.set_ylabel("")
         ax2.set_title("(b) Top 10 Speedups", fontsize=14)
     else:
         ax2.text(0.5, 0.5, "No speedup data", ha="center", va="center", fontsize=12)
@@ -204,30 +206,32 @@ def plot_speedup_distribution(
     bottom_n = min(10, len(comparison_df))
     if bottom_n > 0:
         bottom_10 = comparison_df.nsmallest(bottom_n, "Speedup")
-        bars = ax3.barh(
-            np.arange(len(bottom_10)),
-            bottom_10["Speedup"],
+        sns.barplot(
+            x="Speedup",
+            y="Transform",
+            data=bottom_10,
             color=bottom_color,
             alpha=0.7,
             edgecolor="black",
+            ax=ax3,
         )
-        ax3.set_yticks(np.arange(len(bottom_10)))
-        ax3.set_yticklabels(bottom_10["Transform"], fontsize=10)
         ax3.grid(True, alpha=0.3)
 
-        for _, bar in enumerate(bars):
-            width = bar.get_width()
+        # Add text labels for speedup values
+        for i, v in enumerate(bottom_10["Speedup"]):
             ax3.text(
-                width + 0.05,
-                bar.get_y() + bar.get_height() / 2,
-                f"{width:.2f}x",
+                v + 0.05,
+                i,
+                f"{v:.2f}x",
                 ha="left",
                 va="center",
                 fontsize=10,
                 bbox={"facecolor": "white", "alpha": 0.8, "edgecolor": "none"},
             )
 
         ax3.set_xlabel("Speedup (x)", fontsize=12)
+        # Remove y-label "Transform"
+        ax3.set_ylabel("")
         ax3.set_title("(c) Bottom 10 Speedups", fontsize=14)
     else:
         ax3.text(0.5, 0.5, "No speedup data", ha="center", va="center", fontsize=12)
@@ -256,23 +260,28 @@ def plot_speedup_distribution(
         f"{total_transforms} transforms with multiple library support"
     )
 
-    # Add the stats text to the bottom right of the figure
+    # Add the stats text to the right side of the left plot with larger font
+    ax1_pos = ax1.get_position()
+    # Calculate 10% of the plot width
+    plot_width = ax1_pos.x1 - ax1_pos.x0
+    shift_amount = plot_width * 0.1
+
     plt.figtext(
-        0.98,
-        0.02,
+        ax1_pos.x1 - 0.02 - shift_amount,  # Shifted left by 10% of plot width
+        ax1_pos.y1 - 0.02,  # Slightly below the top edge of the left plot
         stats_text,
         ha="right",
-        va="bottom",
-        bbox={"facecolor": "white", "alpha": 0.9, "edgecolor": "none"},
-        fontsize=10,
+        va="top",
+        bbox={"facecolor": "white", "alpha": 0.9, "edgecolor": "lightgray", "boxstyle": "round,pad=0.5"},
+        fontsize=14,  # Significantly increased font size
     )
 
-    # Add title with information about the reference library
-    plt.suptitle(f"Speedup Analysis: {reference_library.capitalize()} vs Other Libraries", fontsize=16)
+    # Add title with information about the reference library with more space
+    plt.suptitle(f"Speedup Analysis: {reference_library.capitalize()} vs Other Libraries", fontsize=16, y=1.02)
 
     # Adjust layout and save
     plt.tight_layout()
-    plt.subplots_adjust(top=0.9, bottom=0.15)  # Make room for the suptitle and stats
+    plt.subplots_adjust(top=0.88)  # Increased top margin for suptitle
     plt.savefig(output_path, dpi=300, bbox_inches="tight")
     plt.close()