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"""
Integration tests for MAP-Elites grid stability across checkpoints
"""
import os
import tempfile
import shutil
import unittest
from openevolve.database import ProgramDatabase, Program
from openevolve.config import DatabaseConfig
class TestGridStability(unittest.TestCase):
"""Integration tests for MAP-Elites grid stability when resuming from checkpoints"""
def setUp(self):
"""Set up test environment"""
self.test_dir = tempfile.mkdtemp()
def tearDown(self):
"""Clean up test environment"""
shutil.rmtree(self.test_dir)
def test_feature_ranges_preserved_across_checkpoints(self):
"""Test that feature ranges are preserved across checkpoint save/load cycles"""
config = DatabaseConfig(
db_path=self.test_dir,
feature_dimensions=["score", "prompt_length", "reasoning_sophistication"],
feature_bins=5, # Use smaller bins for easier testing
)
# Phase 1: Create initial population with specific range
db1 = ProgramDatabase(config)
# Create programs with known metrics to establish ranges
test_cases = [
{"combined_score": 0.2, "prompt_length": 100, "reasoning_sophistication": 0.1},
{"combined_score": 0.5, "prompt_length": 300, "reasoning_sophistication": 0.5},
{"combined_score": 0.8, "prompt_length": 500, "reasoning_sophistication": 0.9},
]
for i, metrics in enumerate(test_cases):
program = Program(
id=f"range_test_{i}", code=f"# Range test program {i}", metrics=metrics
)
db1.add(program)
# Record the established ranges
original_ranges = {}
for dim, stats in db1.feature_stats.items():
original_ranges[dim] = {
"min": stats["min"],
"max": stats["max"],
"value_count": len(stats["values"]),
}
# Save checkpoint
db1.save(self.test_dir, iteration=25)
# Phase 2: Resume from checkpoint
db2 = ProgramDatabase(config)
db2.load(self.test_dir)
# Verify all programs were loaded
self.assertEqual(len(db2.programs), len(test_cases))
# Verify feature ranges are preserved
for dim, original_range in original_ranges.items():
self.assertIn(dim, db2.feature_stats)
loaded_stats = db2.feature_stats[dim]
self.assertAlmostEqual(
loaded_stats["min"],
original_range["min"],
places=5,
msg=f"Min range changed for {dim}",
)
self.assertAlmostEqual(
loaded_stats["max"],
original_range["max"],
places=5,
msg=f"Max range changed for {dim}",
)
# Phase 3: Add new program within existing range - ranges should not contract
new_program = Program(
id="within_range_test",
code="# New program within established range",
metrics={
"combined_score": 0.35, # Between existing values
"prompt_length": 200, # Between existing values
"reasoning_sophistication": 0.3, # Between existing values
},
)
# Add new program
db2.add(new_program)
new_coords = db2._calculate_feature_coords(new_program)
# Verify ranges did not contract (should be same or expanded)
for dim, original_range in original_ranges.items():
current_stats = db2.feature_stats[dim]
self.assertLessEqual(
current_stats["min"], original_range["min"], f"Min range contracted for {dim}"
)
self.assertGreaterEqual(
current_stats["max"], original_range["max"], f"Max range contracted for {dim}"
)
def test_grid_expansion_behavior(self):
"""Test that grid expands correctly when new programs exceed existing ranges"""
config = DatabaseConfig(
db_path=self.test_dir, feature_dimensions=["score", "execution_time"], feature_bins=5
)
# Phase 1: Establish initial range
db1 = ProgramDatabase(config)
# Initial programs with limited range
for i in range(3):
program = Program(
id=f"initial_{i}",
code=f"# Initial program {i}",
metrics={
"combined_score": 0.4 + i * 0.1, # 0.4 to 0.6
"execution_time": 10 + i * 5, # 10 to 20
},
)
db1.add(program)
# Record feature ranges
original_score_min = db1.feature_stats["score"]["min"]
original_score_max = db1.feature_stats["score"]["max"]
original_time_min = db1.feature_stats["execution_time"]["min"]
original_time_max = db1.feature_stats["execution_time"]["max"]
# Save checkpoint
db1.save(self.test_dir, iteration=30)
# Phase 2: Resume and add program outside range
db2 = ProgramDatabase(config)
db2.load(self.test_dir)
# Verify ranges were preserved
self.assertAlmostEqual(db2.feature_stats["score"]["min"], original_score_min)
self.assertAlmostEqual(db2.feature_stats["score"]["max"], original_score_max)
self.assertAlmostEqual(db2.feature_stats["execution_time"]["min"], original_time_min)
self.assertAlmostEqual(db2.feature_stats["execution_time"]["max"], original_time_max)
# Add program outside existing range
expansion_program = Program(
id="expansion_test",
code="# Program to test range expansion",
metrics={
"combined_score": 0.9, # Higher than existing max (0.6)
"execution_time": 50, # Higher than existing max (20)
},
)
db2.add(expansion_program)
# Verify ranges expanded appropriately
self.assertLessEqual(db2.feature_stats["score"]["min"], original_score_min)
self.assertGreaterEqual(db2.feature_stats["score"]["max"], 0.9)
self.assertLessEqual(db2.feature_stats["execution_time"]["min"], original_time_min)
self.assertGreaterEqual(db2.feature_stats["execution_time"]["max"], 50)
def test_feature_stats_consistency_across_cycles(self):
"""Test that feature_stats remain consistent across multiple save/load cycles"""
config = DatabaseConfig(
db_path=self.test_dir, feature_dimensions=["score", "memory_usage"], feature_bins=4
)
# Initial program to establish baseline
reference_program = Program(
id="reference",
code="# Reference program for consistency testing",
metrics={"combined_score": 0.5, "memory_usage": 1024},
)
# Cycle 1: Establish initial feature stats
db1 = ProgramDatabase(config)
db1.add(reference_program)
# Record initial feature stats
cycle1_stats = {}
for dim, stats in db1.feature_stats.items():
cycle1_stats[dim] = {"min": stats["min"], "max": stats["max"]}
db1.save(self.test_dir, iteration=10)
# Cycle 2: Load and verify stats preservation
db2 = ProgramDatabase(config)
db2.load(self.test_dir)
# Verify feature stats were preserved
for dim, original_stats in cycle1_stats.items():
self.assertIn(dim, db2.feature_stats)
self.assertAlmostEqual(db2.feature_stats[dim]["min"], original_stats["min"])
self.assertAlmostEqual(db2.feature_stats[dim]["max"], original_stats["max"])
# Add another program and save again
db2.add(
Program(
id="cycle2_program",
code="# Cycle 2 program",
metrics={"combined_score": 0.3, "memory_usage": 512},
)
)
# Record expanded stats after adding new program
cycle2_stats = {}
for dim, stats in db2.feature_stats.items():
cycle2_stats[dim] = {"min": stats["min"], "max": stats["max"]}
db2.save(self.test_dir, iteration=20)
# Cycle 3: Verify stats are still preserved
db3 = ProgramDatabase(config)
db3.load(self.test_dir)
# Verify expanded feature stats were preserved
for dim, cycle2_stats_dim in cycle2_stats.items():
self.assertIn(dim, db3.feature_stats)
self.assertAlmostEqual(
db3.feature_stats[dim]["min"],
cycle2_stats_dim["min"],
msg=f"Min value changed for {dim} in cycle 3",
)
self.assertAlmostEqual(
db3.feature_stats[dim]["max"],
cycle2_stats_dim["max"],
msg=f"Max value changed for {dim} in cycle 3",
)
def test_feature_stats_accumulation(self):
"""Test that feature_stats accumulate correctly across checkpoint cycles"""
config = DatabaseConfig(
db_path=self.test_dir, feature_dimensions=["score", "complexity"], feature_bins=10
)
# Cycle 1: Initial programs
db1 = ProgramDatabase(config)
for i in range(3):
program = Program(
id=f"phase1_{i}",
code=f"# Phase 1 program {i}",
metrics={"combined_score": 0.2 + i * 0.2, "complexity": 100 + i * 50},
)
db1.add(program)
# Record phase 1 stats
phase1_score_values = set(db1.feature_stats["score"]["values"])
phase1_complexity_values = set(db1.feature_stats["complexity"]["values"])
db1.save(self.test_dir, iteration=15)
# Cycle 2: Load and add more programs
db2 = ProgramDatabase(config)
db2.load(self.test_dir)
for i in range(2):
program = Program(
id=f"phase2_{i}",
code=f"# Phase 2 program {i}",
metrics={"combined_score": 0.1 + i * 0.3, "complexity": 75 + i * 75},
)
db2.add(program)
# Verify that phase 1 values are still present
phase2_score_values = set(db2.feature_stats["score"]["values"])
phase2_complexity_values = set(db2.feature_stats["complexity"]["values"])
# Phase 1 values should be preserved (subset relationship)
self.assertTrue(
phase1_score_values.issubset(phase2_score_values),
"Phase 1 score values were lost after loading checkpoint",
)
self.assertTrue(
phase1_complexity_values.issubset(phase2_complexity_values),
"Phase 1 complexity values were lost after loading checkpoint",
)
if __name__ == "__main__":
unittest.main()
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