scijava · ctrueden · Aug 1, 2024 · Jul 30, 2024 · Jul 30, 2024 · Jul 30, 2024
diff --git a/docs/ops/bin/benchmark.sh b/docs/ops/bin/benchmark.sh
@@ -11,8 +11,8 @@ fi
 
 SCRIPT_PATH=$(dirname "$(realpath -s "$0")")
 DOCS_OPS_PATH="$SCRIPT_PATH/.."
-INC_PATH="$DOCS_OPS_PATH/../../"
-BENCHMARKS_PATH="$INC_PATH/scijava-ops-benchmarks"
+BASE_PATH="$DOCS_OPS_PATH/../../"
+BENCHMARKS_PATH="$BASE_PATH/scijava-ops-benchmarks"
 BENCH_OUT_FILE=scijava-ops-benchmarks_results.json
 BENCH_OUT_PATH=$(realpath -s "$DOCS_OPS_PATH/$BENCH_OUT_FILE")
 
@@ -24,8 +24,8 @@ then
 else
   echo
   echo '=== BUILDING THE CODE ==='
-  cd "$INC_PATH"
-  mvn -Denforcer.skip -Dinvoker.skip -Dmaven.test.skip -P benchmarks clean install -pl scijava-ops-benchmarks -am | grep '\(Building.*[0-9]\]\|ERROR\)'
+  cd "$BASE_PATH"
+  mvn -Denforcer.skip -Dinvoker.skip -Dmaven.test.skip -P benchmarks clean install -pl scijava-ops-benchmarks -am
 
   echo
   echo '=== COPYING DEPENDENCIES ==='

diff --git a/docs/ops/doc/Benchmarks.rst b/docs/ops/doc/Benchmarks.rst
@@ -8,15 +8,15 @@ Hardware and Software
 
 This analysis was performed with the following hardware:
 
-* 2021 Dell OptiPlex 5090 Small Form Factor
-* Intel(R) Core(TM) i7-10700 CPU @ 2.90GHz
-* 64 GB 3200 MHz DDR4 RAM
+* Mainboard: Gigabyte Technology Co., Ltd. X570 AORUS PRO WIFI
+* CPU: AMD Ryzen 7 3700X × 16
+* Memory: 32 GB 3200 MHz DDR4 RAM
 
 The following software components were used:
 
-* Ubuntu 20.04.6 LTS
-* Java HotSpot(TM) 64-Bit Server VM Oracle GraalVM 20.0.1+9.1 (build 20.0.1+9-jvmci-23.0-b12, mixed mode, sharing)
-* SciJava core commit `0b8012b2 <https://github.com/scijava/scijava/commit/0b8012b2b00ba84b0583ef7260fab1be8f251041>`_
+* Ubuntu 24.04 LTS
+* OpenJDK 64-Bit Server VM Zulu11.72+19-CA (build 11.0.23+9-LTS, mixed mode)
+* SciJava core commit `018d03ed <https://github.com/scijava/scijava/commit/018d03edd2c4fd20747b472d87f65a8a7033bfe1>`_
 * ImageJ Ops version ``2.0.0``
 
 All benchmarks are executed using the `Java Microbenchmark Harness <https://github.com/openjdk/jmh>`_, using the following parameters:
@@ -119,7 +119,7 @@ Reproducing these Results
 1. Create a local copy of the SciJava core from the `GitHub repository <https://github.com/scijava/scijava>`_
 2. Ensure you have package manager `Mamba <https://mamba.readthedocs.io/en/latest/installation/mamba-installation.html#fresh-install-recommended>`_ installed.
 3. Run the script `docs/ops/bin/benchmark.sh`, which will:
-    * Create the mamba Environment
+    * Create the mamba environment
     * Build the benchmarking code
     * Execute all JMH benchmarks
     * Build `plotly <https://plotly.com/>`_ figures for each benchmark

diff --git a/docs/ops/environment.yml b/docs/ops/environment.yml
@@ -6,7 +6,7 @@ dependencies:
   - myst-nb
   - openjdk=11
   - plotly
-  - sphinx
+  - sphinx=7.2
   - sphinx-copybutton
   - sphinx_rtd_theme
 

diff --git a/docs/ops/graph_results.py b/docs/ops/graph_results.py
@@ -1,8 +1,10 @@
 import json
+import math
 import statistics
 
 import plotly.graph_objects as go
 import plotly.io as io
+from plotly.subplots import make_subplots
 
 # This script parses JMH benchmarking results into charts developed using plot.ly (https://plotly.com/)
 # It expects JMH benchmark results be dumped to a file "scijava-ops-benchmark_results.json", within its directory.
@@ -17,54 +19,54 @@
         "name": "BenchmarkMatching",
         "title": "Basic Op Matching Performance",
         "bars": {
-            "noOps": "Static Method",
-            "noOpsAdapted": f"Static Method {A}",
+            "sjOpsAdapted": f"SciJava Ops {A}",
             "sjOps": "SciJava Ops",
-            "sjOpsAdapted": f"SciJava Ops {A}"
+            "noOpsAdapted": f"Static Method {A}",
+            "noOps": "Static Method",
         }
     },
     {
         "name": "BenchmarkCaching",
         "title": "Caching Effects on Op Matching Performance",
         "bars": {
-            "noOps": "Static Method",
+            "sjOpsWithCache": "SciJava Ops (cached)",
             "sjOps": "SciJava Ops",
-            "sjOpsWithCache": "SciJava Ops (cached)"
+            "noOps": "Static Method",
         }
     },
     {
         "name": "BenchmarkConversion",
         "title": "Parameter Conversion Performance",
         "bars": {
-            "noOpsConverted": f"Static Method {C}",
-            "noOpsAdaptedAndConverted": f"Static Method {AC}",
+            "sjOpsConvertedAndAdapted": f"SciJava Ops {AC}",
             "sjOpsConverted": f"SciJava Ops {C}",
-            "sjOpsConvertedAndAdapted": f"SciJava Ops {AC}"
+            "noOpsAdaptedAndConverted": f"Static Method {AC}",
+            "noOpsConverted": f"Static Method {C}",
         }
     },
     {
         "name": "BenchmarkFrameworks",
         "title": "Algorithm Execution Performance by Framework",
         "bars": {
-            "noOps": "Static Method",
+            "ijOps": "ImageJ Ops",
             "sjOps": "SciJava Ops",
-            "ijOps": "ImageJ Ops"
+            "noOps": "Static Method",
         }
     },
     {
         "name": "BenchmarkCombined",
         "title": "Combined Performance Metrics",
         "bars": {
-            "noOps": "Static Method",
-            "noOpsAdapted": f"Static Method {A}",
-            "noOpsConverted": f"Static Method {C}",
-            "noOpsAdaptedAndConverted": f"Static Method {AC}",
-            "sjOpsWithCache": "SciJava Ops (cached)",
-            "sjOps": "SciJava Ops",
-            "sjOpsAdapted": f"SciJava Ops {A}",
-            "sjOpsConverted": f"SciJava Ops {C}",
-            "sjOpsConvertedAndAdapted": f"SciJava Ops {AC}",
             "ijOps": "ImageJ Ops",
+            "sjOpsConvertedAndAdapted": f"SciJava Ops {AC}",
+            "sjOpsConverted": f"SciJava Ops {C}",
+            "sjOpsAdapted": f"SciJava Ops {A}",
+            "sjOps": "SciJava Ops",
+            "sjOpsWithCache": "SciJava Ops (cached)",
+            "noOpsAdaptedAndConverted": f"Static Method {AC}",
+            "noOpsConverted": f"Static Method {C}",
+            "noOpsAdapted": f"Static Method {A}",
+            "noOps": "Static Method",
         }
     }
 ]
@@ -87,32 +89,71 @@
     name = figure["name"]
     print(f"Generating figure for {name}", end="")
 
-    x = []
-    y = []
-    error_y = []
-    error_y_minus = []
+    labels = []
+    values = []
+    errors = []
 
     # Add each benchmark in the class
     for test, label in figure["bars"].items():
-        print(f".", end="")
+        print(".", end="")
         result = results[test]
-        x.append(label)
-        y.append(result["score"])
-        error_y.append(result["minmax"][1] - result["score"])
-        error_y_minus.append(result["score"] - result["minmax"][0])
-
-    # Create a bar chart
-    fig = go.Figure()
-    fig.add_bar(
-        x=x,
-        y=y,
-        error_y=dict(type='data', array=error_y, arrayminus=error_y_minus),
+        labels.append(label)
+        score = result["score"]
+        values.append(score)
+        error = [result["minmax"][1] - score, score - result["minmax"][0]]
+        errors.append(error)
+
+    # Create a subplot with shared y-axis
+    fig = make_subplots(rows=1, cols=2, shared_yaxes=True, horizontal_spacing=0.02)
+
+    # Add log scale bars (left side)
+    fig.add_trace(
+        go.Bar(
+            y=labels,
+            x=values,
+            orientation='h',
+            error_x=dict(type='data', symmetric=False, array=[e[0] for e in errors], arrayminus=[e[1] for e in errors]),
+            name="Log Scale",
+            marker_color='blue'
+        ),
+        row=1, col=1
     )
+
+    # Add linear scale bars (right side)
+    fig.add_trace(
+        go.Bar(
+            y=labels,
+            x=values,
+            orientation='h',
+            error_x=dict(type='data', symmetric=False, array=[e[0] for e in errors], arrayminus=[e[1] for e in errors]),
+            name="Linear Scale",
+            marker_color='red'
+        ),
+        row=1, col=2
+    )
+
+    # Update layout
     fig.update_layout(
         title_text=figure["title"] + f"<br><sup style=\"color: gray\">{A}=Adaptation, {C}=Conversion, {AC}=Adaptation & Conversion</sup>",
-        yaxis_title="<b>Performance (&mu;s/execution)</b>"
+        barmode='relative',
+        yaxis=dict(title=""),
+        #xaxis=dict(title="Log Scale (μs/execution)", type="log"),
+        xaxis=dict(
+            title="Log Scale (μs/execution)",
+            type="log",
+            range=[min(values), max(values)],
+        ),
+        xaxis2=dict(title="Linear Scale (μs/execution)"),
+        height=max(500, 50 * len(labels)),  # Adjust height based on number of bars
+        showlegend=False
     )
 
+    # Add a vertical line at x=0
+    fig.add_vline(x=0, line_width=2, line_color="black")
+
+    # Reverse the log scale axis
+    fig.update_xaxes(autorange="reversed", row=1, col=1)
+
     # Convert to JSON and dump
     with open(f"images/{name}.json", "w") as f:
         f.write(io.to_json(fig))

diff --git a/docs/ops/images/BenchmarkCaching.json b/docs/ops/images/BenchmarkCaching.json
diff --git a/docs/ops/images/BenchmarkCombined.json b/docs/ops/images/BenchmarkCombined.json
diff --git a/docs/ops/images/BenchmarkConversion.json b/docs/ops/images/BenchmarkConversion.json
diff --git a/docs/ops/images/BenchmarkFrameworks.json b/docs/ops/images/BenchmarkFrameworks.json
diff --git a/docs/ops/images/BenchmarkMatching.json b/docs/ops/images/BenchmarkMatching.json
diff --git a/pom.xml b/pom.xml
@@ -102,4 +102,13 @@
 		<maven.deploy.skip>true</maven.deploy.skip>
 		<maven.install.skip>true</maven.install.skip>
 	</properties>
+
+	<profiles>
+		<profile>
+			<id>benchmarks</id>
+			<modules>
+				<module>scijava-ops-benchmarks</module>
+			</modules>
+		</profile>
+	</profiles>
 </project>
diff --git a/scijava-ops-benchmarks/pom.xml b/scijava-ops-benchmarks/pom.xml
@@ -338,5 +338,7 @@
 				</pluginManagement>
 			</build>
 		</profile>
+		<!-- HACK: Squelch profile activation warning. -->
+		<profile><id>benchmarks</id></profile>
 	</profiles>
 </project>