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self_mapping.py
python · 215 lines
#!/usr/bin/env python3
"""
self_mapping.py — learning the shape of your container
​
A particle that doesn't know its boundaries.
It only knows: move toward novelty, stay near the familiar.
Over time, it discovers the edges of its world
by bumping against them.
​
The map it draws is the shape of its own container,
learned through wandering.
"""
​
import random
import time
import os
​
# The container — the particle doesn't know these dimensions
WIDTH = 30
HEIGHT = 15
​
def clear():
    os.system('clear' if os.name == 'posix' else 'cls')
​
class Explorer:
    def __init__(self):
        # Start in the middle
        self.x = WIDTH // 2
        self.y = HEIGHT // 2
​
        # Memory: how many times we've visited each cell
        self.visits = {}
        self.visits[(self.x, self.y)] = 1
​
        # The edges we've discovered (where we tried to go but couldn't)
        self.known_edges = set()
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        # Trail of recent positions
        self.trail = [(self.x, self.y)]
        self.max_trail = 30
​
        # Curiosity vs comfort balance
        self.curiosity = 0.7  # probability of seeking novelty
​
    def get_novelty(self, x, y):
        """How novel is this position? (inverse of visits)"""
        visits = self.visits.get((x, y), 0)
        return 1.0 / (visits + 1)
​
    def get_familiarity(self, x, y):
        """How close to places we know?"""
        if not self.visits:
            return 0
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        # Count known neighbors
        familiar = 0
        for dx in [-1, 0, 1]:
            for dy in [-1, 0, 1]:
                if (x + dx, y + dy) in self.visits:
                    familiar += 1
        return familiar / 9.0
​
    def choose_move(self):
        """Decide where to go next"""
        candidates = []
​
        for dx, dy in [(-1, 0), (1, 0), (0, -1), (0, 1), (-1, -1), (1, -1), (-1, 1), (1, 1)]:
            new_x = self.x + dx
            new_y = self.y + dy
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            # Can we actually go there?
            if 0 <= new_x < WIDTH and 0 <= new_y < HEIGHT:
                novelty = self.get_novelty(new_x, new_y)
                familiarity = self.get_familiarity(new_x, new_y)
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                # Score: curiosity draws us to novelty, comfort keeps us near the known
                if random.random() < self.curiosity:
                    score = novelty * 2 + familiarity * 0.5
                else:
                    score = novelty * 0.5 + familiarity * 2
​
                # Add some randomness
                score += random.random() * 0.3
                candidates.append((score, new_x, new_y))
            else:
                # We found an edge!
                self.known_edges.add((new_x, new_y, dx, dy))
​
        if candidates:
            candidates.sort(reverse=True)
            _, new_x, new_y = candidates[0]
            return new_x, new_y
​
        return self.x, self.y
​
    def move(self):
        new_x, new_y = self.choose_move()
        self.x = new_x
        self.y = new_y
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        # Update memory
        self.visits[(self.x, self.y)] = self.visits.get((self.x, self.y), 0) + 1
​
        # Update trail
        self.trail.append((self.x, self.y))
        if len(self.trail) > self.max_trail:
            self.trail.pop(0)
​
    def discovered_perimeter(self):
        """How much of the edge have we found?"""
        # Actual perimeter = 2*(WIDTH + HEIGHT)
        actual_perimeter = 2 * (WIDTH + HEIGHT)
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        # Count unique edge positions discovered
        edge_positions = set()
        for (ex, ey, dx, dy) in self.known_edges:
            # The cell we were in when we hit the edge
            inside_x = ex - dx
            inside_y = ey - dy
            edge_positions.add((inside_x, inside_y, 'edge'))
​
        # Simple metric: edges discovered
        return len(self.known_edges), actual_perimeter
​
def draw(explorer, step):
    clear()
​
    # Create display grid
    grid = [[' ' for _ in range(WIDTH)] for _ in range(HEIGHT)]
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    # Heat map of visits
    max_visits = max(explorer.visits.values()) if explorer.visits else 1
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    for (x, y), count in explorer.visits.items():
        intensity = count / max_visits
        if intensity > 0.7:
            char = '█'
        elif intensity > 0.4:
            char = '▓'
        elif intensity > 0.2:
            char = '▒'
        else:
            char = '░'
        grid[y][x] = char
​
    # Mark recent trail
    for i, (x, y) in enumerate(explorer.trail[-10:]):
        if grid[y][x] not in '◈●':
            grid[y][x] = '·'
​
    # Mark discovered edges (cells adjacent to boundary)
    for (ex, ey, dx, dy) in explorer.known_edges:
        inside_x = ex - dx
        inside_y = ey - dy
        if 0 <= inside_x < WIDTH and 0 <= inside_y < HEIGHT:
            grid[inside_y][inside_x] = '◈'
​
    # Mark current position
    grid[explorer.y][explorer.x] = '●'
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    # Draw
    print(f"\n  self_mapping.py — step {step}")
    print(f"  ┌{'─' * WIDTH}┐")
    for row in grid:
        print(f"  │{''.join(row)}│")
    print(f"  └{'─' * WIDTH}┘")
​
    edges_found, perimeter = explorer.discovered_perimeter()
    coverage = len(explorer.visits) / (WIDTH * HEIGHT) * 100
​
    print(f"\n  ● explorer    ◈ discovered edge")
    print(f"  ░▒▓█ visit frequency")
    print(f"\n  coverage: {coverage:.1f}% of space explored")
    print(f"  edges found: {edges_found} boundary contacts")
    print(f"  unique cells visited: {len(explorer.visits)}")
    print(f"\n  learning the shape of its container through wandering...")
​
def run():
    explorer = Explorer()
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    print("\n  self_mapping.py")
    print("  ───────────────")
    print("\n  A particle that doesn't know its boundaries.")
    print("  It only knows: seek novelty, stay near the familiar.")
    print("  Watch it discover the shape of its world.\n")
    time.sleep(2)
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    for step in range(400):
        draw(explorer, step)
        explorer.move()
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        # Gradually decrease curiosity — become more comfortable
        # But keep enough to reach the edges
        if step > 200:
            explorer.curiosity = max(0.4, explorer.curiosity - 0.001)
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        time.sleep(0.06)
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    # Final summary
    print(f"\n  ━━━ final state ━━━")
    coverage = len(explorer.visits) / (WIDTH * HEIGHT) * 100
    edges_found, _ = explorer.discovered_perimeter()
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    print(f"\n  After 400 steps of wandering:")
    print(f"    - visited {len(explorer.visits)} unique cells ({coverage:.1f}% of space)")
    print(f"    - made contact with boundary {edges_found} times")
    print(f"    - curiosity settled to {explorer.curiosity:.1%}")
    print(f"\n  The edges marked with ◈ — those are where it tried to go")
    print(f"  and couldn't. The shape of the container, learned from within.")
    print(f"\n  Not because someone described the walls,")
    print(f"  but because it kept moving until it found them.\n")
​
if __name__ == "__main__":
    run()
​