Add performance benchmarking scripts and run in CI

.github/workflows/benchmarks.yml

@@ -0,0 +1,77 @@
+name: Performance benchmarks
+
+on:
+  pull_request_target:
+    types: [opened, ready_for_review]
+    branches:
+      - main
+  issue_comment:
+    types: [created]
+
+permissions:
+  issues: write
+  pull-requests: write
+
+jobs:
+  run-benchmarks:
+    if: >
+      github.event_name == 'pull_request' || 
+      (github.event_name == 'issue_comment' && contains(github.event.comment.body, '/rerun-benchmarks'))
+    runs-on: ubuntu-latest
+    steps:
+      - name: Checkout PR branch
+        uses: actions/checkout@v4
+      - name: Set up Python
+        uses: actions/setup-python@v5
+        with:
+          python-version: '3.12'
+      - name: Add project directory to PYTHONPATH
+        run: echo "PYTHONPATH=$PYTHONPATH:$(pwd)" >> $GITHUB_ENV
+      - name: Install dependencies
+        run: pip install numpy pandas tqdm tabulate
+#      - name: Checkout main branch
+#        uses: actions/checkout@v4
+#        with:
+#          ref: main
+#          repository: projectmesa/mesa
+      - name: Run benchmarks on main branch
+        working-directory: benchmarks
+        run: python global_benchmark.py
+      - name: Upload benchmark results
+        uses: actions/upload-artifact@v4
+        with:
+          name: timings-main
+          path: benchmarks/timings_1.pickle
+      - name: Checkout PR branch
+        uses: actions/checkout@v4
+        with:
+          ref: ${{ github.event.pull_request.head.ref }}
+          repository: ${{ github.event.pull_request.head.repo.full_name }}
+          clean: false
+      - name: Download benchmark results
+        uses: actions/download-artifact@v4
+        with:
+          name: timings-main
+          path: benchmarks
+      - name: Run benchmarks on PR branch
+        working-directory: benchmarks
+        run: python global_benchmark.py
+      - name: Run compare timings and encode output
+        working-directory: benchmarks
+        run: |
+          TIMING_COMPARISON=$(python compare_timings.py | base64 -w 0)  # Base64 encode the output
+          echo "TIMING_COMPARISON=$TIMING_COMPARISON" >> $GITHUB_ENV
+
+      - name: Comment PR
+        uses: actions/github-script@v7
+        with:
+          github-token: ${{ GITHUB_TOKEN }}
+          script: |
+            const output = Buffer.from(process.env.TIMING_COMPARISON, 'base64').toString('utf-8');
+            const issue_number = context.issue.number;
+            github.rest.issues.createComment({
+              issue_number: issue_number,
+              owner: context.repo.owner,
+              repo: context.repo.repo,
+              body: 'Benchmark Comparison:\n\n' + output
+            });

.gitignore

@@ -1,3 +1,6 @@
+# Benchmarking
+benchmarking/**/*.pickle
+
 # Byte-compiled / optimized / DLL files
 __pycache__/
 *.py[cod]

benchmarks/Flocking/Flocking.py

@@ -0,0 +1,80 @@
+"""
+Flockers
+=============================================================
+A Mesa implementation of Craig Reynolds's Boids flocker model.
+Uses numpy arrays to represent vectors.
+"""
+
+import numpy as np
+
+from mesa import Model
+from mesa.space import ContinuousSpace
+from mesa.time import RandomActivation
+
+from .boid import Boid
+
+
+class BoidFlockers(Model):
+    """
+    Flocker model class. Handles agent creation, placement and scheduling.
+    """
+
+    def __init__(
+        self,
+        seed,
+        population,
+        width,
+        height,
+        vision,
+        speed=1,
+        separation=1,
+        cohere=0.03,
+        separate=0.015,
+        match=0.05,
+    ):
+        """
+        Create a new Flockers model.
+
+        Args:
+            population: Number of Boids
+            width, height: Size of the space.
+            speed: How fast should the Boids move.
+            vision: How far around should each Boid look for its neighbors
+            separation: What's the minimum distance each Boid will attempt to
+                    keep from any other
+            cohere, separate, match: factors for the relative importance of
+                    the three drives.        """
+        super().__init__(seed=seed)
+        self.population = population
+        self.vision = vision
+        self.speed = speed
+        self.separation = separation
+        self.schedule = RandomActivation(self)
+        self.space = ContinuousSpace(width, height, True)
+        self.factors = dict(cohere=cohere, separate=separate, match=match)
+        self.make_agents()
+
+    def make_agents(self):
+        """
+        Create self.population agents, with random positions and starting headings.
+        """
+        for i in range(self.population):
+            x = self.random.random() * self.space.x_max
+            y = self.random.random() * self.space.y_max
+            pos = np.array((x, y))
+            velocity = np.random.random(2) * 2 - 1
+            boid = Boid(
+                i,
+                self,
+                pos,
+                self.speed,
+                velocity,
+                self.vision,
+                self.separation,
+                **self.factors
+            )
+            self.space.place_agent(boid, pos)
+            self.schedule.add(boid)
+
+    def step(self):
+        self.schedule.step()