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Update Entity Management wiki with Entity(grid_pos=), .animate(), SpatialHash, current callback signatures, Timer objects

John McCardle 2026-02-07 22:16:21 +00:00
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Entity-Management.md

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# Entity Management
Entities are game objects that implement behavior and live on Grids. While Grids handle rendering and mediate interactions, Entities encapsulate game logic like movement, combat, and AI.
## Quick Reference
**Parent System:** [[Grid-System]]
**Key Types:**
- `mcrfpy.Entity` - Game entities on grids
- `mcrfpy.Grid` - Spatial container for entities
- `mcrfpy.EntityCollection` - Collection of entities on a grid
**Key Files:**
- `src/UIEntity.h` / `src/UIEntity.cpp`
- `src/UIEntityCollection.h` / `.cpp`
- `src/SpatialHash.h` / `src/SpatialHash.cpp` - Spatial indexing
**Related Issues:**
- [#115](../issues/115) - SpatialHash for fast queries ✅ Implemented
- [#117](../issues/117) - Memory Pool for entities (Deferred)
- [#159](../issues/159) - EntityCollection iterator optimization ✅ Fixed
---
## What Are Entities?
Entities are game objects that:
- **Live on a Grid** (0 or 1 grid at a time)
- **Have a sprite** for visual rendering
- **Have grid position** (integer cell coordinates)
- **Implement behavior** (movement, AI, combat, inventory)
- **Track visibility** (which cells they can see / have seen)
**Key distinction:** Entities implement behavior. Grids mediate interaction between entities and render them to screen.
---
## Entity-Grid Relationship
The Entity-Grid relationship mirrors the UIDrawable parent-child pattern:
| Relationship | Property | Automatic Behavior |
|--------------|----------|-------------------|
| Entity → Grid | `entity.grid` | Set when added to `grid.entities` |
| Grid → Entities | `grid.entities` | Collection of all entities on grid |
```python
import mcrfpy
# Create grid and entity
grid = mcrfpy.Grid(grid_size=(50, 50), pos=(0, 0), size=(400, 400))
player = mcrfpy.Entity(pos=(10, 10), sprite_index=0)
# Before adding: entity has no grid
print(player.grid) # None
# Add to grid
grid.entities.append(player)
# After adding: bidirectional link established
print(player.grid == grid) # True
print(player in grid.entities) # True
# Removing breaks the link
grid.entities.remove(player)
print(player.grid) # None
```
**Important:** An entity can only be on 0 or 1 grids at a time. Adding to a new grid automatically removes from the old one.
---
## Entity Properties
### Position
```python
# Grid coordinates (integer cells)
entity.x = 15
entity.y = 20
entity.pos = (15, 20) # Tuple form
# Draw position (float, for animation interpolation)
print(entity.draw_pos) # Actual render position
```
### Sprite
```python
entity.sprite_index = 5 # Index in texture sprite sheet
```
### Visibility
```python
entity.visible = True
entity.opacity = 0.8 # 0.0 to 1.0
```
### Grid Reference
```python
current_grid = entity.grid # Read-only, set by collection operations
```
---
## Spatial Queries with SpatialHash
As of commit 7d57ce2, grids use **SpatialHash** for efficient spatial queries. This provides O(k) query time where k is the number of nearby entities, instead of O(n) scanning all entities.
### entities_in_radius()
```python
# Query entities within a radius (uses SpatialHash internally)
nearby = grid.entities_in_radius(x, y, radius)
# Example: Find all entities within 10 cells of position (50, 50)
threats = grid.entities_in_radius(50, 50, 10)
for entity in threats:
print(f"Entity at ({entity.x}, {entity.y})")
```
### Performance Comparison
| Entity Count | O(n) Query | SpatialHash | Speedup |
|--------------|------------|-------------|---------|
| 100 | 0.037ms | 0.008ms | 4.6× |
| 500 | 0.061ms | 0.009ms | 7.2× |
| 1,000 | 0.028ms | 0.004ms | 7.8× |
| 2,000 | 0.043ms | 0.003ms | 13× |
| 5,000 | 0.109ms | 0.003ms | **37×** |
### N×N Visibility (AI "What can everyone see?")
| Entity Count | O(n) approach | SpatialHash | Speedup |
|--------------|---------------|-------------|---------|
| 1,000 | 21ms | 1ms | 35× |
| 2,000 | 85ms | 1ms | 87× |
| 5,000 | 431ms | 2ms | **217×** |
### When to Use Which Method
| Use Case | Method | Complexity |
|----------|--------|------------|
| Nearby entities (AI, combat) | `grid.entities_in_radius(x, y, r)` | O(k) |
| FOV-based visibility | `entity.visible_entities()` | O(n) + FOV |
| All entities iteration | `for e in grid.entities` | O(n) |
| Single cell lookup | `grid.at(x, y).entities` | O(n) filter |
---
## Field of View & Visibility
Entities track what they can see via `gridstate` - a per-cell record of visible and discovered states.
### FOV Configuration
```python
# Grid-level FOV settings
grid.fov = mcrfpy.FOV.SHADOW # Algorithm (BASIC, DIAMOND, SHADOW, etc.)
grid.fov_radius = 10 # Default view radius
# Module-level default
mcrfpy.default_fov = mcrfpy.FOV.PERMISSIVE_2
```
### Updating Visibility
```python
# Compute FOV from entity's position and update gridstate
entity.update_visibility()
# This also updates any ColorLayers bound via apply_perspective()
```
### Querying Visible Entities
```python
# Get list of other entities this entity can see (uses FOV + line-of-sight)
visible_enemies = entity.visible_entities()
# With custom FOV settings
nearby = entity.visible_entities(radius=5)
visible = entity.visible_entities(fov=mcrfpy.FOV.BASIC, radius=8)
```
**Note:** `visible_entities()` checks FOV and line-of-sight. For pure distance queries without FOV, use `grid.entities_in_radius()`.
### Fog of War with ColorLayers
```python
# Create a ColorLayer for fog of war
fov_layer = grid.add_layer('color', z_index=-1)
fov_layer.fill((0, 0, 0, 255)) # Start black (unknown)
# Bind to entity - layer auto-updates when entity.update_visibility() is called
fov_layer.apply_perspective(
entity=player,
visible=(0, 0, 0, 0), # Transparent when visible
discovered=(40, 40, 60, 180), # Dark overlay when discovered
unknown=(0, 0, 0, 255) # Black when never seen
)
# Now whenever player moves:
player.x = new_x
player.y = new_y
player.update_visibility() # Automatically updates the fog layer
```
### One-Time FOV Draw
```python
# Draw FOV without binding (useful for previews, spell ranges, etc.)
fov_layer.draw_fov(
source=(player.x, player.y),
radius=10,
fov=mcrfpy.FOV.SHADOW,
visible=(255, 255, 200, 64),
discovered=(100, 100, 100, 128),
unknown=(0, 0, 0, 255)
)
```
### Gridstate Access
```python
# Entity's per-cell visibility memory
for state in entity.gridstate:
print(f"visible={state.visible}, discovered={state.discovered}")
# Access specific cell state
state = entity.at((x, y))
if state.visible:
print("Entity can currently see this cell")
elif state.discovered:
print("Entity has seen this cell before")
```
### GridPointState.point - Accessing Cell Data (#16)
The `GridPointState.point` property provides access to the underlying `GridPoint` from an entity's perspective:
```python
state = entity.at((x, y))
# If entity has NOT discovered this cell, point is None
if not state.discovered:
print(state.point) # None - entity doesn't know what's here
# If entity HAS discovered the cell, point gives access to GridPoint
if state.discovered:
point = state.point # Live reference to GridPoint
print(f"walkable: {point.walkable}")
print(f"transparent: {point.transparent}")
print(f"entities here: {point.entities}") # List of entities at cell
```
**Key behaviors:**
- Returns `None` if `discovered=False` (entity has never seen this cell)
- Returns live `GridPoint` reference if `discovered=True`
- Changes to the `GridPoint` are immediately visible through `state.point`
- This is intentionally **not** a cached copy - for historical memory, implement your own system in Python
---
## EntityCollection
`grid.entities` is an `EntityCollection` with list-like operations:
```python
# Add entities
grid.entities.append(entity)
grid.entities.extend([entity1, entity2, entity3])
grid.entities.insert(0, entity) # Insert at index
# Remove entities
grid.entities.remove(entity)
entity = grid.entities.pop() # Remove and return last
entity = grid.entities.pop(0) # Remove and return at index
# Query
count = len(grid.entities)
idx = grid.entities.index(entity)
n = grid.entities.count(entity)
found = grid.entities.find("entity_name") # Find by name
# Iteration (O(n) - optimized in #159)
for entity in grid.entities:
print(entity.pos)
```
### Iterator Performance (#159)
EntityCollection iteration was optimized in commit 8f2407b:
- **Before:** O(n²) due to index-based list traversal
- **After:** O(n) using proper list iterators
- **Speedup:** 103× at 2,000 entities
---
## Entity Lifecycle
### Creation
```python
# Basic creation
entity = mcrfpy.Entity(pos=(10, 10), sprite_index=0)
# With name for later lookup
entity = mcrfpy.Entity(pos=(10, 10), sprite_index=0, name="player")
```
### Adding to Grid
```python
grid.entities.append(entity)
# entity.grid is now set to grid
# Entity is automatically added to SpatialHash for fast queries
```
### Movement
```python
# Direct position change (automatically updates SpatialHash)
entity.pos = (new_x, new_y)
# Animated movement
mcrfpy.Animation("x", target_x, 0.3, "easeOutQuad").start(entity)
mcrfpy.Animation("y", target_y, 0.3, "easeOutQuad").start(entity)
# Update visibility after movement
entity.update_visibility()
```
### Removal
```python
# Method 1: Remove from collection
grid.entities.remove(entity)
# Method 2: Entity.die() - removes from parent grid and SpatialHash
entity.die()
# After removal: entity.grid is None
```
### Transfer Between Grids
```python
def transfer_entity(entity, to_grid, new_pos):
"""Move entity to a different grid."""
entity.die() # Remove from current grid
entity.pos = new_pos
to_grid.entities.append(entity)
```
---
## Common Patterns
### Player Entity with FOV
```python
class Player:
def __init__(self, grid, start_pos):
self.entity = mcrfpy.Entity(pos=start_pos, sprite_index=0, name="player")
grid.entities.append(self.entity)
# Set up fog of war
self.fov_layer = grid.add_layer('color', z_index=-1)
self.fov_layer.fill((0, 0, 0, 255))
self.fov_layer.apply_perspective(
entity=self.entity,
visible=(0, 0, 0, 0),
discovered=(30, 30, 50, 180),
unknown=(0, 0, 0, 255)
)
self.entity.update_visibility()
def move(self, dx, dy):
new_x = self.entity.x + dx
new_y = self.entity.y + dy
point = self.entity.grid.at(new_x, new_y)
if point and point.walkable:
self.entity.pos = (new_x, new_y)
self.entity.update_visibility() # Update FOV after move
return True
return False
def get_visible_enemies(self):
"""Get enemies this player can currently see."""
return [e for e in self.entity.visible_entities()
if e.name and e.name.startswith("enemy")]
```
### Enemy AI with SpatialHash
```python
class Enemy:
def __init__(self, grid, pos, aggro_range=10):
self.entity = mcrfpy.Entity(pos=pos, sprite_index=1, name="enemy")
self.aggro_range = aggro_range
self.health = 100
self.grid = grid
grid.entities.append(self.entity)
def update(self):
# Use SpatialHash for efficient nearby entity detection
nearby = self.grid.entities_in_radius(
self.entity.x, self.entity.y, self.aggro_range
)
# Find player in nearby entities
player = None
for e in nearby:
if e.name == "player":
player = e
break
if player:
self.chase((player.x, player.y))
else:
self.wander()
def chase(self, target):
# Use pathfinding
path = self.entity.grid.find_path(
self.entity.x, self.entity.y, target[0], target[1]
)
if path and len(path) > 1:
next_cell = path[1] # path[0] is current position
self.entity.pos = next_cell
def wander(self):
import random
dx = random.choice([-1, 0, 1])
dy = random.choice([-1, 0, 1])
new_pos = (self.entity.x + dx, self.entity.y + dy)
point = self.entity.grid.at(*new_pos)
if point and point.walkable:
self.entity.pos = new_pos
```
### Efficient Multi-Entity AI Loop
```python
def update_all_enemies(grid, enemies):
"""Update all enemies efficiently using SpatialHash."""
for enemy in enemies:
# Each query is O(k) not O(n)
nearby = grid.entities_in_radius(enemy.x, enemy.y, enemy.aggro_range)
enemy.react_to_nearby(nearby)
```
### Item Entity
```python
class Item:
def __init__(self, grid, pos, item_type):
self.entity = mcrfpy.Entity(pos=pos, sprite_index=10 + item_type)
self.item_type = item_type
grid.entities.append(self.entity)
def pickup(self, collector):
"""Called when another entity picks up this item."""
collector.inventory.append(self.item_type)
self.entity.die() # Remove from grid
```
For more interaction patterns (click handling, selection, context menus), see [[Grid-Interaction-Patterns]].
---
## Pathfinding
Entities have built-in pathfinding via libtcod:
```python
# A* pathfinding to target (via Grid)
path = grid.find_path(entity.x, entity.y, target_x, target_y)
# Returns list of (x, y) tuples, or empty if no path
if path:
next_step = path[1] # path[0] is current position
entity.pos = next_step
# Dijkstra for multi-target pathfinding
grid.compute_dijkstra(goal_x, goal_y)
distance = grid.get_dijkstra_distance(entity.x, entity.y)
path = grid.get_dijkstra_path(entity.x, entity.y)
```
Pathfinding respects `GridPoint.walkable` properties set on the grid.
---
## Performance Considerations
### Current Performance (as of 2025-12-28)
| Operation | Performance | Notes |
|-----------|-------------|-------|
| Entity Creation | ~90,000/sec | Sufficient for level generation |
| Iteration | ~9M reads/sec | Optimized iterators (#159) |
| Spatial Query | 0.003ms | SpatialHash O(k) (#115) |
| N×N Visibility (5000) | 2ms | 217× faster than O(n) |
### Recommendations
1. **Use `entities_in_radius()` for AI** - O(k) queries instead of iterating all entities
2. **Batch visibility updates** - Call `update_visibility()` once after all moves
3. **Use timer callbacks for AI** - Don't run expensive logic every frame
4. **Entity counts up to 5,000+** - SpatialHash makes large counts feasible
### Internal Architecture
- **SpatialHash:** Bucket-based spatial indexing (32-cell buckets)
- **Automatic updates:** Hash updates on entity add/remove/move
- **Weak references:** Hash doesn't prevent entity garbage collection
See [[Performance-and-Profiling]] for detailed optimization guidance.
---
## Related Systems
- [[Grid-System]] - Spatial container for entities
- [[Grid-Interaction-Patterns]] - Click handling, selection, context menus
- [[Animation-System]] - Smooth entity movement
- [[Performance-and-Profiling]] - Entity performance metrics
---
*Last updated: 2025-12-28*
# Entity Management
Entities are game objects that implement behavior and live on Grids. While Grids handle rendering and mediate interactions, Entities encapsulate game logic like movement, combat, and AI.
## Quick Reference
**Parent System:** [[Grid-System]]
**Key Types:**
- `mcrfpy.Entity` - Game entities on grids
- `mcrfpy.Grid` - Spatial container for entities
- `mcrfpy.EntityCollection` - Collection of entities on a grid
**Key Files:**
- `src/UIEntity.h` / `src/UIEntity.cpp`
- `src/UIEntityCollection.h` / `.cpp`
- `src/SpatialHash.h` / `src/SpatialHash.cpp` - Spatial indexing
**Related Issues:**
- [#115](../issues/115) - SpatialHash for fast queries - Implemented
- [#117](../issues/117) - Memory Pool for entities (Deferred)
- [#159](../issues/159) - EntityCollection iterator optimization - Fixed
---
## Creating Entities
```python
import mcrfpy
# Basic creation with keyword arguments
entity = mcrfpy.Entity(grid_pos=(10, 10), sprite_index=0)
# With name for lookup
player = mcrfpy.Entity(grid_pos=(5, 5), sprite_index=0, name="player")
# Default (origin, no sprite)
e = mcrfpy.Entity() # grid_pos=(0, 0), sprite_index=0
```
### Entity Properties
| Property | Type | Description |
|----------|------|-------------|
| `grid_x`, `grid_y` | float | Grid cell position |
| `draw_x`, `draw_y` | float | Visual draw position (for animation) |
| `sprite_index` | int | Index in texture sprite sheet |
| `sprite_scale` | float | Scale of the entity sprite |
| `name` | str | Entity name for lookup |
| `visible` | bool | Whether entity is rendered |
| `grid` | Grid or None | Parent grid (read-only, set by collection) |
---
## Entity-Grid Relationship
```python
grid = mcrfpy.Grid(grid_size=(50, 50), pos=(0, 0), size=(400, 400))
player = mcrfpy.Entity(grid_pos=(10, 10), sprite_index=0, name="player")
# Before adding: entity has no grid
print(player.grid) # None
# Add to grid
grid.entities.append(player)
# After adding: bidirectional link established
print(player.grid is not None) # True
print(player in grid.entities) # True
# Removing breaks the link
grid.entities.remove(player)
print(player.grid) # None
```
**Important:** An entity can only be on 0 or 1 grids at a time. Adding to a new grid automatically removes from the old one.
---
## Movement
```python
# Direct position change (updates SpatialHash automatically)
player.grid_x = 15
player.grid_y = 20
# Animated movement (smooth visual transition)
player.animate("x", 15.0, 0.3, mcrfpy.Easing.EASE_OUT_QUAD)
player.animate("y", 20.0, 0.3, mcrfpy.Easing.EASE_OUT_QUAD)
# Move with callback on completion
def on_move_complete(target, prop, value):
target.grid.compute_fov((int(target.grid_x), int(target.grid_y)), radius=8)
player.animate("x", 15.0, 0.3, mcrfpy.Easing.EASE_OUT_QUAD, callback=on_move_complete)
```
### Animatable Entity Properties
| Property | Type | Notes |
|----------|------|-------|
| `x`, `y` | float | Alias for draw position |
| `draw_x`, `draw_y` | float | Visual position in tile coords |
| `sprite_index` | int | Can animate through sprite frames |
| `sprite_scale` | float | Scale animation |
---
## Spatial Queries with SpatialHash
Grids use SpatialHash for efficient spatial queries with O(k) time complexity:
### entities_in_radius()
```python
# Query entities within a radius
nearby = grid.entities_in_radius((10, 10), 5.0)
for entity in nearby:
print(f"{entity.name} at ({entity.grid_x}, {entity.grid_y})")
```
**Note:** The first argument is a `(x, y)` tuple, not separate x and y arguments.
### Performance
| Entity Count | Linear Scan | SpatialHash | Speedup |
|--------------|-------------|-------------|---------|
| 100 | 0.037ms | 0.008ms | 4.6x |
| 1,000 | 0.028ms | 0.004ms | 7.8x |
| 5,000 | 0.109ms | 0.003ms | **37x** |
For N x N visibility checks (e.g., "what can everyone see?"):
| Entity Count | Linear | SpatialHash | Speedup |
|--------------|--------|-------------|---------|
| 1,000 | 21ms | 1ms | 35x |
| 5,000 | 431ms | 2ms | **217x** |
---
## EntityCollection
`grid.entities` is an `EntityCollection` with list-like operations:
```python
# Add entities
grid.entities.append(entity)
grid.entities.extend([entity1, entity2, entity3])
# Remove entities
grid.entities.remove(entity)
# Query
count = len(grid.entities)
idx = grid.entities.index(entity)
# Iteration (O(n) - optimized in #159)
for entity in grid.entities:
print(f"{entity.name}: ({entity.grid_x}, {entity.grid_y})")
```
---
## Entity Lifecycle
### Creation and Placement
```python
player = mcrfpy.Entity(grid_pos=(10, 10), sprite_index=0, name="player")
grid.entities.append(player)
# player.grid is now set
# Entity is added to SpatialHash for fast queries
```
### Removal
```python
# Method 1: Remove from collection
grid.entities.remove(player)
# Method 2: Entity.die() - removes from parent grid and SpatialHash
player.die()
# After removal: player.grid is None
```
### Transfer Between Grids
```python
def transfer_entity(entity, to_grid, new_pos):
entity.die() # Remove from current grid
entity.grid_x = new_pos[0]
entity.grid_y = new_pos[1]
to_grid.entities.append(entity)
```
---
## FOV and Visibility
### Computing FOV
```python
# Set up transparent cells
for x in range(50):
for y in range(50):
grid.at(x, y).transparent = True
# Mark walls
grid.at(5, 5).transparent = False
# Compute FOV from entity position
grid.compute_fov((int(player.grid_x), int(player.grid_y)), radius=10)
# Check if a cell is visible
if grid.is_in_fov((12, 14)):
print("Can see that cell!")
```
### Fog of War with ColorLayer
```python
# Create fog overlay
fog = mcrfpy.ColorLayer(name="fog", z_index=1)
grid.add_layer(fog)
# Initialize to fully dark
fog.fill(mcrfpy.Color(0, 0, 0, 255))
# Update fog based on FOV after each move
def update_fog(player, fog_layer, grid):
grid.compute_fov((int(player.grid_x), int(player.grid_y)), radius=8)
for x in range(grid.grid_w):
for y in range(grid.grid_h):
if grid.is_in_fov((x, y)):
fog_layer.set((x, y), mcrfpy.Color(0, 0, 0, 0)) # Clear
# Previously seen cells stay semi-transparent (don't re-darken)
```
### Perspective System
```python
# Set perspective entity (enables FOV-aware rendering)
grid.perspective = player
# Remove perspective (omniscient view)
grid.perspective = None
```
---
## Common Patterns
### Player Entity with Movement
```python
class Player:
def __init__(self, grid, start_pos):
self.entity = mcrfpy.Entity(
grid_pos=start_pos, sprite_index=0, name="player"
)
grid.entities.append(self.entity)
def move(self, dx, dy):
new_x = int(self.entity.grid_x + dx)
new_y = int(self.entity.grid_y + dy)
point = self.entity.grid.at(new_x, new_y)
if point and point.walkable:
self.entity.animate("x", float(new_x), 0.15, mcrfpy.Easing.EASE_OUT_QUAD)
self.entity.animate("y", float(new_y), 0.15, mcrfpy.Easing.EASE_OUT_QUAD)
self.entity.grid_x = new_x
self.entity.grid_y = new_y
return True
return False
```
### Enemy AI with SpatialHash
```python
class Enemy:
def __init__(self, grid, pos, aggro_range=10):
self.entity = mcrfpy.Entity(
grid_pos=pos, sprite_index=1, name="enemy"
)
self.aggro_range = aggro_range
grid.entities.append(self.entity)
def update(self):
grid = self.entity.grid
# Use SpatialHash for efficient nearby entity detection
nearby = grid.entities_in_radius(
(self.entity.grid_x, self.entity.grid_y),
self.aggro_range
)
# Find player in nearby entities
player = None
for e in nearby:
if e.name == "player":
player = e
break
if player:
self.chase(player)
else:
self.wander()
def chase(self, target):
grid = self.entity.grid
path = grid.find_path(
(int(self.entity.grid_x), int(self.entity.grid_y)),
(int(target.grid_x), int(target.grid_y))
)
if path and len(path) > 0:
next_step = path.walk()
self.entity.grid_x = next_step.x
self.entity.grid_y = next_step.y
def wander(self):
import random
dx = random.choice([-1, 0, 1])
dy = random.choice([-1, 0, 1])
new_x = int(self.entity.grid_x + dx)
new_y = int(self.entity.grid_y + dy)
point = self.entity.grid.at(new_x, new_y)
if point and point.walkable:
self.entity.grid_x = new_x
self.entity.grid_y = new_y
```
### Item Pickup
```python
class Item:
def __init__(self, grid, pos, item_type):
self.entity = mcrfpy.Entity(
grid_pos=pos, sprite_index=10 + item_type, name=f"item_{item_type}"
)
self.item_type = item_type
grid.entities.append(self.entity)
def pickup(self, collector_inventory):
collector_inventory.append(self.item_type)
self.entity.die() # Remove from grid
```
---
## Pathfinding
Entities use the grid's pathfinding capabilities:
```python
# A* pathfinding
path = grid.find_path(
(int(entity.grid_x), int(entity.grid_y)),
(target_x, target_y)
)
if path and len(path) > 0:
next_step = path.walk() # Get next step as Vector
entity.grid_x = next_step.x
entity.grid_y = next_step.y
# Dijkstra for multi-target pathfinding
dm = grid.get_dijkstra_map((goal_x, goal_y))
distance = dm.distance((entity.grid_x, entity.grid_y))
next_step = dm.step_from((int(entity.grid_x), int(entity.grid_y)))
```
Pathfinding respects `GridPoint.walkable` properties.
---
## Performance Considerations
| Operation | Performance | Notes |
|-----------|-------------|-------|
| Entity Creation | ~90,000/sec | Sufficient for level generation |
| Iteration | ~9M reads/sec | Optimized iterators (#159) |
| Spatial Query | 0.003ms | SpatialHash O(k) (#115) |
| N x N Visibility (5000) | 2ms | 217x faster than O(n) |
### Recommendations
1. **Use `entities_in_radius()` for AI** - O(k) queries instead of iterating all entities
2. **Batch visibility updates** - Compute FOV once after all moves, not per-move
3. **Use Timer for AI** - Don't run expensive logic every frame
4. **Entity counts up to 5,000+** - SpatialHash makes large counts feasible
---
## Related Systems
- [[Grid-System]] - Spatial container for entities
- [[Grid-Interaction-Patterns]] - Click handling, selection, context menus
- [[Animation-System]] - Smooth entity movement via `.animate()`
- [[AI-and-Pathfinding]] - FOV, pathfinding, AI patterns
- [[Input-and-Events]] - Callback signatures for mouse events
---
*Last updated: 2026-02-07*