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>
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@ -1183,41 +1183,10 @@ PyObject* UIGrid::py_compute_fov(PyUIGridObject* self, PyObject* args, PyObject*
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// Compute FOV
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self->data->computeFOV(x, y, radius, light_walls, (TCOD_fov_algorithm_t)algorithm);
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// Build list of visible cells as tuples (x, y, visible, discovered)
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PyObject* result_list = PyList_New(0);
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if (!result_list) return NULL;
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// Iterate through grid and collect visible cells
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for (int gy = 0; gy < self->data->grid_y; gy++) {
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for (int gx = 0; gx < self->data->grid_x; gx++) {
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if (self->data->isInFOV(gx, gy)) {
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// Create tuple (x, y, visible, discovered)
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PyObject* cell_tuple = PyTuple_New(4);
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if (!cell_tuple) {
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Py_DECREF(result_list);
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return NULL;
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}
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PyTuple_SET_ITEM(cell_tuple, 0, PyLong_FromLong(gx));
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PyTuple_SET_ITEM(cell_tuple, 1, PyLong_FromLong(gy));
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PyTuple_SET_ITEM(cell_tuple, 2, Py_True); // visible
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PyTuple_SET_ITEM(cell_tuple, 3, Py_True); // discovered
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Py_INCREF(Py_True); // Need to increment ref count for True
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Py_INCREF(Py_True);
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// Append to list
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if (PyList_Append(result_list, cell_tuple) < 0) {
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Py_DECREF(cell_tuple);
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Py_DECREF(result_list);
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return NULL;
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}
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Py_DECREF(cell_tuple); // List now owns the reference
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}
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}
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}
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return result_list;
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// Return None - use is_in_fov() to query visibility
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// See issue #146: returning a list had O(grid_size) performance
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Py_RETURN_NONE;
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}
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PyObject* UIGrid::py_is_in_fov(PyUIGridObject* self, PyObject* args)
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@ -0,0 +1,99 @@
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#!/usr/bin/env python3
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"""
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Isolated FOV benchmark - test if the slowdown is TCOD or Python wrapper
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"""
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import mcrfpy
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import sys
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import time
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def run_test(runtime):
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print("=" * 60)
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print("FOV Isolation Test - Is TCOD slow, or is it the Python wrapper?")
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print("=" * 60)
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# Create a 1000x1000 grid
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mcrfpy.createScene("test")
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ui = mcrfpy.sceneUI("test")
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texture = mcrfpy.Texture("assets/kenney_ice.png", 16, 16)
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print("\nCreating 1000x1000 grid...")
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t0 = time.perf_counter()
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grid = mcrfpy.Grid(pos=(0,0), size=(800,600), grid_size=(1000, 1000), texture=texture)
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ui.append(grid)
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print(f" Grid creation: {(time.perf_counter() - t0)*1000:.1f}ms")
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# Set walkability
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print("Setting walkability (this takes a while)...")
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t0 = time.perf_counter()
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for y in range(0, 1000, 10): # Sample every 10th row for speed
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for x in range(1000):
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cell = grid.at(x, y)
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cell.walkable = True
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cell.transparent = True
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print(f" Partial walkability: {(time.perf_counter() - t0)*1000:.1f}ms")
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# Test 1: compute_fov (now returns None - fast path after #146 fix)
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print("\n--- Test 1: grid.compute_fov() [returns None after #146 fix] ---")
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times = []
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for i in range(5):
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t0 = time.perf_counter()
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result = grid.compute_fov(500, 500, radius=15)
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elapsed = (time.perf_counter() - t0) * 1000
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times.append(elapsed)
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# Count visible cells using is_in_fov (the correct pattern)
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visible = sum(1 for dy in range(-15, 16) for dx in range(-15, 16)
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if 0 <= 500+dx < 1000 and 0 <= 500+dy < 1000
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and grid.is_in_fov(500+dx, 500+dy))
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print(f" Run {i+1}: {elapsed:.3f}ms, result={result}, ~{visible} visible cells")
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print(f" Average: {sum(times)/len(times):.3f}ms")
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# Test 2: Just check is_in_fov for cells in radius (what rendering would do)
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print("\n--- Test 2: Simulated render check (only radius cells) ---")
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times = []
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for i in range(5):
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# First compute FOV (we need to do this)
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grid.compute_fov(500, 500, radius=15)
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# Now simulate what rendering would do - check only nearby cells
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t0 = time.perf_counter()
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visible_count = 0
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for dy in range(-15, 16):
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for dx in range(-15, 16):
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x, y = 500 + dx, 500 + dy
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if 0 <= x < 1000 and 0 <= y < 1000:
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if grid.is_in_fov(x, y):
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visible_count += 1
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elapsed = (time.perf_counter() - t0) * 1000
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times.append(elapsed)
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print(f" Run {i+1}: {elapsed:.2f}ms checking ~961 cells, {visible_count} visible")
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print(f" Average: {sum(times)/len(times):.2f}ms")
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# Test 3: Time just the iteration overhead (no FOV, just grid access)
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print("\n--- Test 3: Grid iteration baseline (no FOV) ---")
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times = []
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for i in range(5):
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t0 = time.perf_counter()
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count = 0
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for dy in range(-15, 16):
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for dx in range(-15, 16):
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x, y = 500 + dx, 500 + dy
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if 0 <= x < 1000 and 0 <= y < 1000:
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cell = grid.at(x, y)
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if cell.walkable:
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count += 1
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elapsed = (time.perf_counter() - t0) * 1000
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times.append(elapsed)
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print(f" Average: {sum(times)/len(times):.2f}ms for ~961 grid.at() calls")
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print("\n" + "=" * 60)
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print("CONCLUSION:")
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print("After #146 fix, compute_fov() returns None instead of building")
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print("a list. Test 1 and Test 2 should now have similar performance.")
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print("The TCOD FOV algorithm is O(radius²) and fast.")
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print("=" * 60)
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sys.exit(0)
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mcrfpy.createScene("init")
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mcrfpy.setScene("init")
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mcrfpy.setTimer("test", run_test, 100)
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@ -0,0 +1,114 @@
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#!/usr/bin/env python3
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"""
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Regression test for issue #146: compute_fov() returns None
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The compute_fov() method had O(n²) performance because it built a Python list
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of all visible cells by iterating the entire grid. The fix removes this
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list-building and returns None instead. Users should use is_in_fov() to query
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visibility.
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Bug: 15.76ms for compute_fov() on 1000x1000 grid (iterating 1M cells)
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Fix: Return None, actual FOV check via is_in_fov() takes 0.21ms
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"""
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import mcrfpy
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import sys
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import time
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def run_test(runtime):
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print("=" * 60)
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print("Issue #146 Regression Test: compute_fov() returns None")
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print("=" * 60)
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# Create a test grid
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mcrfpy.createScene("test")
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ui = mcrfpy.sceneUI("test")
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texture = mcrfpy.Texture("assets/kenney_ice.png", 16, 16)
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grid = mcrfpy.Grid(pos=(0,0), size=(400,300), grid_size=(50, 50), texture=texture)
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ui.append(grid)
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# Set walkability for center area
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for y in range(50):
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for x in range(50):
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cell = grid.at(x, y)
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cell.walkable = True
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cell.transparent = True
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# Add some walls to test blocking
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for i in range(10, 20):
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grid.at(i, 25).transparent = False
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grid.at(i, 25).walkable = False
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print("\n--- Test 1: compute_fov() returns None ---")
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result = grid.compute_fov(25, 25, radius=10)
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if result is None:
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print(" PASS: compute_fov() returned None")
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else:
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print(f" FAIL: compute_fov() returned {type(result).__name__} instead of None")
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sys.exit(1)
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print("\n--- Test 2: is_in_fov() works after compute_fov() ---")
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# Center should be visible
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if grid.is_in_fov(25, 25):
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print(" PASS: Center (25,25) is in FOV")
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else:
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print(" FAIL: Center should be in FOV")
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sys.exit(1)
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# Cell within radius should be visible
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if grid.is_in_fov(20, 25):
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print(" PASS: Cell (20,25) within radius is in FOV")
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else:
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print(" FAIL: Cell (20,25) should be in FOV")
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sys.exit(1)
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# Cell behind wall should NOT be visible
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if not grid.is_in_fov(15, 30):
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print(" PASS: Cell (15,30) behind wall is NOT in FOV")
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else:
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print(" FAIL: Cell behind wall should not be in FOV")
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sys.exit(1)
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# Cell outside radius should NOT be visible
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if not grid.is_in_fov(0, 0):
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print(" PASS: Cell (0,0) outside radius is NOT in FOV")
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else:
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print(" FAIL: Cell outside radius should not be in FOV")
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sys.exit(1)
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print("\n--- Test 3: Performance sanity check ---")
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# Create larger grid for timing
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grid_large = mcrfpy.Grid(pos=(0,0), size=(400,300), grid_size=(200, 200), texture=texture)
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for y in range(0, 200, 5): # Sample for speed
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for x in range(200):
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cell = grid_large.at(x, y)
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cell.walkable = True
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cell.transparent = True
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# Time compute_fov (should be fast now - no list building)
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times = []
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for i in range(5):
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t0 = time.perf_counter()
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grid_large.compute_fov(100, 100, radius=15)
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elapsed = (time.perf_counter() - t0) * 1000
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times.append(elapsed)
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avg_time = sum(times) / len(times)
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print(f" compute_fov() on 200x200 grid: {avg_time:.3f}ms avg")
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# Should be under 1ms without list building (was ~4ms with list on 200x200)
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if avg_time < 2.0:
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print(f" PASS: compute_fov() is fast (<2ms)")
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else:
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print(f" WARNING: compute_fov() took {avg_time:.3f}ms (expected <2ms)")
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# Not a hard failure, just a warning
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print("\n" + "=" * 60)
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print("All tests PASSED")
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print("=" * 60)
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sys.exit(0)
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# Initialize and run
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mcrfpy.createScene("init")
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mcrfpy.setScene("init")
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mcrfpy.setTimer("test", run_test, 100)
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