fix: Remove O(n²) list-building from compute_fov() (closes #146)

compute_fov() was iterating through the entire grid to build a Python
list of visible cells, causing O(grid_size) performance instead of
O(radius²). On a 1000×1000 grid this was 15.76ms vs 0.48ms.

The fix returns None instead - users should use is_in_fov() to query
visibility, which is the pattern already used by existing code.

Performance: 33x speedup (15.76ms → 0.48ms on 1M cell grid)

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude <noreply@anthropic.com>
This commit is contained in:
John McCardle 2025-11-28 21:26:32 -05:00
commit f769c6c5f5
3 changed files with 217 additions and 35 deletions

View file

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#!/usr/bin/env python3
"""
Regression test for issue #146: compute_fov() returns None
The compute_fov() method had O() performance because it built a Python list
of all visible cells by iterating the entire grid. The fix removes this
list-building and returns None instead. Users should use is_in_fov() to query
visibility.
Bug: 15.76ms for compute_fov() on 1000x1000 grid (iterating 1M cells)
Fix: Return None, actual FOV check via is_in_fov() takes 0.21ms
"""
import mcrfpy
import sys
import time
def run_test(runtime):
print("=" * 60)
print("Issue #146 Regression Test: compute_fov() returns None")
print("=" * 60)
# Create a test grid
mcrfpy.createScene("test")
ui = mcrfpy.sceneUI("test")
texture = mcrfpy.Texture("assets/kenney_ice.png", 16, 16)
grid = mcrfpy.Grid(pos=(0,0), size=(400,300), grid_size=(50, 50), texture=texture)
ui.append(grid)
# Set walkability for center area
for y in range(50):
for x in range(50):
cell = grid.at(x, y)
cell.walkable = True
cell.transparent = True
# Add some walls to test blocking
for i in range(10, 20):
grid.at(i, 25).transparent = False
grid.at(i, 25).walkable = False
print("\n--- Test 1: compute_fov() returns None ---")
result = grid.compute_fov(25, 25, radius=10)
if result is None:
print(" PASS: compute_fov() returned None")
else:
print(f" FAIL: compute_fov() returned {type(result).__name__} instead of None")
sys.exit(1)
print("\n--- Test 2: is_in_fov() works after compute_fov() ---")
# Center should be visible
if grid.is_in_fov(25, 25):
print(" PASS: Center (25,25) is in FOV")
else:
print(" FAIL: Center should be in FOV")
sys.exit(1)
# Cell within radius should be visible
if grid.is_in_fov(20, 25):
print(" PASS: Cell (20,25) within radius is in FOV")
else:
print(" FAIL: Cell (20,25) should be in FOV")
sys.exit(1)
# Cell behind wall should NOT be visible
if not grid.is_in_fov(15, 30):
print(" PASS: Cell (15,30) behind wall is NOT in FOV")
else:
print(" FAIL: Cell behind wall should not be in FOV")
sys.exit(1)
# Cell outside radius should NOT be visible
if not grid.is_in_fov(0, 0):
print(" PASS: Cell (0,0) outside radius is NOT in FOV")
else:
print(" FAIL: Cell outside radius should not be in FOV")
sys.exit(1)
print("\n--- Test 3: Performance sanity check ---")
# Create larger grid for timing
grid_large = mcrfpy.Grid(pos=(0,0), size=(400,300), grid_size=(200, 200), texture=texture)
for y in range(0, 200, 5): # Sample for speed
for x in range(200):
cell = grid_large.at(x, y)
cell.walkable = True
cell.transparent = True
# Time compute_fov (should be fast now - no list building)
times = []
for i in range(5):
t0 = time.perf_counter()
grid_large.compute_fov(100, 100, radius=15)
elapsed = (time.perf_counter() - t0) * 1000
times.append(elapsed)
avg_time = sum(times) / len(times)
print(f" compute_fov() on 200x200 grid: {avg_time:.3f}ms avg")
# Should be under 1ms without list building (was ~4ms with list on 200x200)
if avg_time < 2.0:
print(f" PASS: compute_fov() is fast (<2ms)")
else:
print(f" WARNING: compute_fov() took {avg_time:.3f}ms (expected <2ms)")
# Not a hard failure, just a warning
print("\n" + "=" * 60)
print("All tests PASSED")
print("=" * 60)
sys.exit(0)
# Initialize and run
mcrfpy.createScene("init")
mcrfpy.setScene("init")
mcrfpy.setTimer("test", run_test, 100)