commit 712bef23379d895c5ca309a573095cbdba594542
Author: Nekkowe! <nekkowe@gmail.com>
Date:   Sat Sep 30 16:53:32 2023 +0200

    rendering & simulation steps

diff --git a/.gitignore b/.gitignore
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+++ b/.gitignore
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+__pycache__
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diff --git a/.vscode/launch.json b/.vscode/launch.json
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+++ b/.vscode/launch.json
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+{
+    // Use IntelliSense to learn about possible attributes.
+    // Hover to view descriptions of existing attributes.
+    // For more information, visit: https://go.microsoft.com/fwlink/?linkid=830387
+    "version": "0.2.0",
+    "configurations": [
+        {
+            "name": "Python: main.py",
+            "type": "python",
+            "request": "launch",
+            //"program": "${file}",
+            "program": "main.py",
+            "console": "integratedTerminal",
+            "justMyCode": true
+        }
+    ]
+}
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diff --git a/main.py b/main.py
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+++ b/main.py
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+from sim import Environment, CAMSReverseAndSidestepAgent, Direction
+import time
+import matplotlib.pyplot as plt
+import numpy as np
+
+STEPS = 1000
+FRAME_DELAY = 1/60
+
+
+# Fixing random state for reproducibility
+np.random.seed(12345)
+
+env = Environment((40, 30))
+first_agent = CAMSReverseAndSidestepAgent(
+    environment=env, 
+    position=(20,15), 
+    initial_direction=Direction.NORTH
+)
+
+fig, ax = plt.subplots()
+im = ax.imshow(env.render(), aspect="equal", origin="lower")
+fig.show()
+
+for i in range(1, STEPS+1):
+    print(i)
+    plt.pause(FRAME_DELAY)
+    env.step()
+    im.set_data(env.render())
+    fig.canvas.draw()
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diff --git a/sim.py b/sim.py
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+++ b/sim.py
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+import numpy as np
+from enum import Enum, auto
+import matplotlib.pyplot as plt
+
+class Direction(Enum):
+    NORTH = (0, 1)
+    SOUTH = (0, -1)
+    WEST = (-1, 0)
+    EAST = (1, 0)
+
+class CellState(Enum):
+    OPEN = auto()
+    WALL = auto()
+
+class Colours(Enum):
+    WALL = [30,30,30]
+    STOCKED = [200,100,0]
+    DEPLETED = [0,50,50]
+    UNDEFINED = [255,0,255]
+    AGENT = [0,255,0]
+
+class Cell():
+    def __init__(self, state, resources):
+        self.state = state
+        self.resources = resources
+    
+    def get_colour(self):
+        if self.state is CellState.WALL:
+            return Colours.WALL
+        elif self.state is CellState.OPEN:
+            if self.resources > 0:
+                return Colours.STOCKED
+            elif self.resources == 0:
+                return Colours.DEPLETED
+            else:
+                return Colours.UNDEFINED
+        else:
+            return Colours.UNDEFINED
+
+class Environment:
+    def __init__(self, shape):
+        self.shape = shape
+        self.agents = []
+
+        self.resource_map = np.round(
+            np.random.normal(loc=50, scale=10, size=shape)
+        )
+
+        cols, rows = shape
+        self.cells = [[] for _ in range(rows)]
+        for y in range(rows):
+            for x in range(cols):
+                if (x == 0 or y == 0 or x+1==cols or y+1==rows):
+                    self.cells[y].append(Cell(CellState.WALL, 0))
+                else:
+                    self.cells[y].append(Cell(CellState.OPEN, self.resource_map[x,y]))
+    
+    def step(self):
+        for agent in self.agents:
+            agent.step()
+
+    def render(self):
+        cols, rows = self.shape
+        pixel_data = [[] for _ in range(rows)]
+        
+        for y in range(self.shape[1]):
+            for x in range(self.shape[0]):
+                #print((x, y, self.cell((x,y)).state, self.cell((x,y)).get_colour().value))
+                pixel_data[y].append(self.cell((x,y)).get_colour().value)
+        
+        for agent in self.agents:
+            x, y = agent.position
+            pixel_data[y][x] = Colours.AGENT.value
+        
+        return np.array(pixel_data)
+    
+    def cell(self, position):
+        x, y = tuple(position)
+        return self.cells[y][x]
+
+    def is_wall(self, position):
+        x, y = tuple(position)
+        return self.cells[y][x].state == CellState.WALL
+
+    def register_agent(self, agent):
+        self.agents.append(agent)
+    
+    def unregister_agent(self, agent):
+        self.agents.remove(agent)
+
+class Agent:
+    def __init__(self, environment, position):
+        self.position = np.array(position)
+        self.environment = environment
+        self.environment.register_agent(self)
+    
+    def step(self):
+        pass
+
+    def move(self, direction, respect_walls=True):
+        new_position = self.position + direction.value
+        if respect_walls and self.environment.is_wall(new_position):
+            return False
+        else:
+            self.position = new_position
+            return True
+    
+    def die(self):
+        self.environment.unregister_agent(self)
+
+class DirectionalAgent(Agent):
+    def __init__(self, environment, position, initial_direction):
+        super().__init__(environment, position)
+        self.direction = initial_direction
+    
+    def get_cell_in_front(self):
+        position_in_front = self.position + self.direction.value
+        return self.environment.cell(position_in_front)
+    
+    def wall_in_front(self):        
+        position_in_front = self.position + self.direction.value
+        return self.environment.is_wall(position_in_front)
+    
+    def turn_left(self):
+        raise NotImplementedError
+
+    def turn_right(self):
+        raise NotImplementedError
+
+    def reverse_direction(self):
+        new_vector = np.array(self.direction.value) * -1
+        self.direction = Direction(tuple(new_vector))
+
+class CAMSReverseAndSidestepAgent(DirectionalAgent):
+    def __init__(self, environment, position, initial_direction, required_resources = 100):
+        super().__init__(environment, position, initial_direction)
+        self.resources = 0
+        self.required_resources = required_resources
+    
+    def step(self):
+        if self.wall_in_front():
+            self.reverse_direction()
+        self.move(self.direction)