From 961e46c3478261ae21ece5e79f7c13cb35fe1fc4 Mon Sep 17 00:00:00 2001
From: ved1 <vedantdave14@gmail.com>
Date: Thu, 23 Feb 2023 12:39:03 +0100
Subject: [PATCH] Adding Klyubin Mazeworld

---
 empowerment/maze.py | 102 ++++++++++++++++++++++++++++++++++++++++++++
 1 file changed, 102 insertions(+)
 create mode 100644 empowerment/maze.py

diff --git a/empowerment/maze.py b/empowerment/maze.py
new file mode 100644
index 0000000..14af149
--- /dev/null
+++ b/empowerment/maze.py
@@ -0,0 +1,102 @@
+import numpy as np
+from collections import OrderedDict
+import matplotlib.pyplot as plt
+
+
+class Maze(object):
+    def __init__(self, height, width):
+        self.height = height
+        self.width = width
+
+        self.actions = OrderedDict()
+        self.actions["N"] = np.array([1, 0])  # UP
+        self.actions["S"] = np.array([-1, 0])  # DOWN
+        self.actions["E"] = np.array([0, 1])  # RIGHT
+        self.actions["W"] = np.array([0, -1])  # LEFT
+        self.actions["_"] = np.array([0, 0])  # STAY
+
+        self.opposite = OrderedDict()
+        self.opposite["N"] = "S"
+        self.opposite["S"] = "N"
+        self.opposite["W"] = "E"
+        self.opposite["E"] = "W"
+        
+        self.wall_states = []
+
+        self.vecmod = np.vectorize(lambda x, y : x % y)
+
+
+
+    def act(self, s, a, check_wall = True):
+        """ get updated state after action
+    
+        s  : state, index of grid position 
+        a : action 
+        prob : probability of performing action
+        """
+        state = self.state_to_cell(s)
+        new_state = state + self.actions[a]
+        if self.is_outside(new_state):
+            return s
+        if check_wall and (s, a) in self.wall_states:
+            return s
+        return self.cell_to_state(new_state)
+
+
+    def add_wall(self, cell, direction):
+        state = self.cell_to_state(cell)
+        self.wall_states.append((state, direction))
+        
+        resulting_states = self.act(state, direction, check_wall = False)
+        self.wall_states.append((resulting_states, self.opposite[direction]))
+
+
+    def is_outside(self, cell):
+        return cell[0] < 0 or cell[0] >= self.height or cell[1] < 0 or cell[1] >= self.width
+
+
+    def state_to_cell(self, s):
+        return np.array([int(s / self.width), s % self.width])
+
+    def cell_to_state(self, cell):
+        return cell[0] * self.width + cell[1]
+
+    
+    def plot(self):
+        G = np.zeros([self.height, self.width])
+        plt.pcolor(G, cmap = 'Greys')
+        plt.colorbar()
+
+        print(self.wall_states)
+        for states in self.wall_states:
+            s, a = states
+            if a == "N":
+                plt.hlines(y = self.state_to_cell(s)[0]+1, xmin=self.state_to_cell(s)[1], xmax=self.state_to_cell(s)[1]+1, color = 'w', linewidth = 2)
+            if a == "E":
+                plt.vlines(x = self.state_to_cell(s)[1]+1, ymin=self.state_to_cell(s)[0], ymax=self.state_to_cell(s)[0]+1, color = 'w', linewidth = 2)
+
+
+if __name__ == "__main__":
+    height, width = 10, 10
+    m = Maze(height, width)
+
+    for i in range(width-4):
+        m.add_wall([1, i], "N")
+    for i in range(width-3, width-1):
+        m.add_wall([1, i], "N")
+    for i in range(width-5, width-3):
+        m.add_wall([2, i], "E")
+        m.add_wall([3, i], "E")
+    m.add_wall([3,width-4], "N")
+
+    for i in range(2,5):
+        m.add_wall([5, i], "N")
+    m.add_wall([6, 4], "N")
+    m.add_wall([7, 4], "N")
+    m.add_wall([8, 3], "N")
+    m.add_wall([8, 3], "E")
+    m.add_wall([6, 4], "E")
+    m.add_wall([7, 4], "E")
+
+    m.plot()
+    plt.show()
\ No newline at end of file