Add cartopy comparison benchmarks

benchmarks/bench_cartopy_coastlines.py

@@ -0,0 +1,198 @@
+"""
+Benchmark PyGMT and cartopy when plotting simple global coastlines.
+"""
+
+import statistics
+import time
+from pathlib import Path
+
+import cartopy.crs as ccrs
+import cartopy.feature as cfeature
+import pygmt
+
+import matplotlib.pyplot as plt  # noqa: E402
+
+
+OUTPUT_DIR = Path("plots/coastlines")
+REPEATS = 10
+CARTOPY_RESOLUTIONS = ("110m", "50m", "10m")
+PYGMT_RESOLUTIONS = ("crude", "low", "intermediate", "high", "full")
+LAND_COLOR = "#cccccc"
+WATER_COLOR = "#b9d9ea"
+
+
+def plot_cartopy_global(resolution: str):
+    """Create a simple global coastline plot with cartopy."""
+    fig = plt.figure(figsize=(6, 4), dpi=300)
+    ax = fig.add_subplot(1, 1, 1, projection=ccrs.Robinson())
+    ax.set_global()
+    ax.add_feature(cfeature.LAND, facecolor=LAND_COLOR)
+    ax.add_feature(cfeature.OCEAN, facecolor=WATER_COLOR)
+    ax.coastlines(resolution=resolution, linewidth=0.5)
+    ax.gridlines(color="0.8", linewidth=0.4)
+    return fig
+
+
+def plot_cartopy_regional(resolution: str):
+    """Create a regional coastline plot with cartopy."""
+    fig = plt.figure(figsize=(6, 4), dpi=300)
+    ax = fig.add_subplot(1, 1, 1, projection=ccrs.Mercator())
+    ax.set_extent([110, 160, -45, -10], crs=ccrs.PlateCarree())
+    ax.add_feature(cfeature.LAND, facecolor=LAND_COLOR)
+    ax.add_feature(cfeature.OCEAN, facecolor=WATER_COLOR)
+    ax.coastlines(resolution=resolution, linewidth=0.5)
+    ax.gridlines(color="0.8", linewidth=0.4)
+    return fig
+
+
+def save_cartopy(fig, output: Path) -> None:
+    """Save a cartopy/matplotlib figure and release it."""
+    fig.savefig(output)
+    plt.close(fig)
+
+
+def plot_pygmt_global(resolution: str) -> pygmt.Figure:
+    """Create a simple global coastline plot with PyGMT."""
+    fig = pygmt.Figure()
+    fig.coast(
+        region="d",
+        projection="R6i",
+        resolution=resolution,
+        land=LAND_COLOR,
+        water=WATER_COLOR,
+        shorelines="1/0.5p,black",
+        frame="afg",
+    )
+    return fig
+
+def plot_pygmt_regional(resolution: str) -> pygmt.Figure:
+    """Create a regional coastline plot with PyGMT."""
+    fig = pygmt.Figure()
+    fig.coast(
+        region=[110, 160, -45, -10],
+        projection="M6i",
+        resolution=resolution,
+        land=LAND_COLOR,
+        water=WATER_COLOR,
+        shorelines="1/0.5p,black",
+        frame="afg",
+    )
+    return fig
+
+
+def save_pygmt(fig: pygmt.Figure, output: Path) -> None:
+    """Save a PyGMT figure."""
+    fig.savefig(output)
+
+
+def benchmark(
+    name: str,
+    plot_func,
+    save_func,
+    output_dir: Path,
+    repeats: int,
+    resolution: str,
+) -> tuple[list[float], list[float]]:
+    """Time repeated coastline plot creation and figure export runs."""
+    output_dir.mkdir(parents=True, exist_ok=True)
+
+    # Warm up each backend once before recording timings.
+    fig = plot_func(resolution)
+    save_func(fig, output_dir / f"{name}_warmup.png")
+
+    plot_timings = []
+    save_timings = []
+    for run_id in range(repeats):
+        output = output_dir / f"{name}_{run_id + 1}.png"
+
+        start = time.perf_counter()
+        fig = plot_func(resolution)
+        plot_timings.append(time.perf_counter() - start)
+
+        save_func(fig, output)
+        save_timings.append(time.perf_counter() - start)
+
+    return plot_timings, save_timings
+
+
+def format_summary(name: str, timings: list[float]) -> str:
+    """Format benchmark timing statistics."""
+    mean = statistics.fmean(timings)
+    median = statistics.median(timings)
+    minimum = min(timings)
+    maximum = max(timings)
+    return (
+        f"{name:10s} "
+        f"mean={mean:.4f}s "
+        f"median={median:.4f}s "
+        f"min={minimum:.4f}s "
+        f"max={maximum:.4f}s"
+    )
+
+
+def main() -> None:
+    """Run the coastline plotting benchmark."""
+    print(f"Running {REPEATS} timed run(s) per backend")
+    print(f"Writing PNG files to {OUTPUT_DIR}")
+
+    print("Benchmarking cartopy global...", flush=True)
+    for resolution in CARTOPY_RESOLUTIONS:
+        print(f"Resolution: {resolution}")
+        plot_timings, save_timings = benchmark(
+            name=f"cartopy_global_{resolution}",
+            plot_func=plot_cartopy_global,
+            save_func=save_cartopy,
+            output_dir=OUTPUT_DIR,
+            repeats=REPEATS,
+            resolution=resolution,
+        )
+        print(format_summary("cartopy plot", plot_timings))
+        print(format_summary("cartopy savefig", save_timings))
+
+    print("Benchmarking cartopy regional...", flush=True)
+    for resolution in CARTOPY_RESOLUTIONS[2:]:
+        print(f"Resolution: {resolution}")
+        plot_timings, save_timings = benchmark(
+            name=f"cartopy_regional_{resolution}",
+            plot_func=plot_cartopy_regional,
+            save_func=save_cartopy,
+            output_dir=OUTPUT_DIR,
+            repeats=REPEATS,
+            resolution=resolution,
+        )
+        print(format_summary("cartopy plot", plot_timings))
+        print(format_summary("cartopy savefig", save_timings))
+
+
+    print("Benchmarking pygmt global...", flush=True)
+    for resolution in PYGMT_RESOLUTIONS[0:3]:
+        print(f"Resolution: {resolution}")
+        plot_timings, save_timings = benchmark(
+            name=f"pygmt_global_{resolution}",
+            plot_func=plot_pygmt_global,
+            save_func=save_pygmt,
+            output_dir=OUTPUT_DIR,
+            repeats=REPEATS,
+            resolution=resolution,
+        )
+        print(format_summary("pygmt plot", plot_timings))
+        print(format_summary("pygmt savefig", save_timings))
+
+    print("Benchmarking pygmt regional...", flush=True)
+    for resolution in PYGMT_RESOLUTIONS[2:]:
+        print(f"Resolution: {resolution}")
+        plot_timings, save_timings = benchmark(
+            name=f"pygmt_regional_{resolution}",
+            plot_func=plot_pygmt_regional,
+            save_func=save_pygmt,
+            output_dir=OUTPUT_DIR,
+            repeats=REPEATS,
+            resolution=resolution,
+        )
+        print(format_summary("pygmt plot", plot_timings))
+        print(format_summary("pygmt savefig", save_timings))
+
+
+
+if __name__ == "__main__":
+    main()