From 3344d1a9bfb8897a450aee1e4489bada1fac13c2 Mon Sep 17 00:00:00 2001
From: hnu202309010107 <2215403613@qq.com>
Date: Sun, 26 May 2024 21:40:08 +0800
Subject: [PATCH] Delete 'AI_map.py'

---
 AI_map.py | 345 ------------------------------------------------------
 1 file changed, 345 deletions(-)
 delete mode 100644 AI_map.py

diff --git a/AI_map.py b/AI_map.py
deleted file mode 100644
index be7ae59..0000000
--- a/AI_map.py
+++ /dev/null
@@ -1,345 +0,0 @@
-import random
-import map_game
-import copy
-import math
-
-class AIMap:
-    def __init__(self,boardMap: list = None):
-        self.map = [[0 for i in range(4)] for i in range(4)] #初始化 全部清零
-        self.map = [[boardMap[i][j]for i in range(4)] for j in range(4)] #复制
-
-    #AI:向左转！
-    def ai_go_left(self):
-        isAdd = 0 # 表示是否成功移动
-        for row in range(0,4):
-            index = 0
-            for col in range(1,4):
-                if self.map[row][col] > 0:
-                    if self.map[row][col] == self.map[row][index]:
-                        self.map[row][index] = self.map[row][col] + self.map[row][index]
-                        self.map[row][col] = 0
-                        index += 1
-                        isAdd = 1
-                    elif self.map[row][index] == 0:
-                        self.map[row][index] = self.map[row][col]
-                        self.map[row][col] = 0
-                        isAdd = 1
-                    else:
-                        index += 1
-
-                    if self.map[row][index] == 0:
-                        self.map[row][index] = self.map[row][col]
-                        self.map[row][col] = 0
-                        isAdd = 1
-        return isAdd
-
-    #AI:向右转！
-    def ai_go_right(self):
-        isAdd = 0 # 表示是否成功移动
-        for row in range(0,4):
-            index = 3
-            for col in range(2,-1,-1):
-                if self.map[row][col] > 0:
-                    if self.map[row][col] == self.map[row][index]:
-                        self.map[row][index] = self.map[row][col] + self.map[row][index]
-                        self.map[row][col] = 0
-                        index -= 1
-                        isAdd = 1
-                    elif self.map[row][index] == 0:
-                        self.map[row][index] = self.map[row][col]
-                        self.map[row][col] = 0
-                        isAdd = 1
-                    else:
-                        index -= 1
-
-                    if self.map[row][index] == 0:
-                        self.map[row][index] = self.map[row][col]
-                        self.map[row][col] = 0
-                        isAdd = 1
-        return isAdd
-
-    #AI:向前进
-    def ai_go_up(self):
-        isAdd = 0 # 表示是否成功移动
-        for col in range(0,4):
-            index = 0
-            for row in range(1,4):
-                if self.map[row][col] > 0:
-                    if self.map[row][col] == self.map[index][col]:
-                        self.map[index][col] = self.map[row][col] + self.map[index][col]
-                        self.map[row][col] = 0
-                        index += 1
-                        isAdd = 1
-                    elif self.map[index][col] == 0:
-                        self.map[index][col] = self.map[row][col]
-                        self.map[row][col] = 0
-                        isAdd = 1
-                    else:
-                        index += 1
-
-                    if self.map[index][col] == 0:
-                        self.map[index][col] = self.map[row][col]
-                        self.map[row][col] = 0
-                        isAdd = 1
-        return isAdd
-
-    #AI:向后退
-    def ai_go_down(self):
-        isAdd = 0 # 表示是否成功移动
-        for col in range(0,4):
-            index = 3
-            for row in range(2,-1,-1):
-                if self.map[row][col] > 0:
-                    if self.map[row][col] == self.map[index][col]:
-                        self.map[index][col] = self.map[row][col] + self.map[index][col]
-                        self.map[row][col] = 0
-                        index -= 1
-                        isAdd = 1
-                    elif self.map[index][col] == 0:
-                        self.map[index][col] = self.map[row][col]
-                        self.map[row][col] = 0
-                        isAdd = 1
-                    else:
-                        index -= 1
-
-                    if self.map[index][col] == 0:
-                        self.map[index][col] = self.map[row][col]
-                        self.map[row][col] = 0
-                        isAdd = 1
-        return isAdd
-
-    #控制AI走不同的方向 走成功为True 走失败为False
-    def ai_go(self,dir):#0左 1右 2上 3下
-        if dir == 0:#左
-            if self.ai_go_left() == 1:
-                return True
-            else:
-                return False
-        elif dir == 1:#右
-            if self.ai_go_right() == 1:
-                return True
-            else:
-                return False
-        elif dir == 2:#上
-            if self.ai_go_up() == 1:
-                return True
-            else:
-                return False
-        elif dir == 3:#下
-            if self.ai_go_down() == 1:
-                return True
-            else:
-                return False
-#数值分析
-#格局评价
-#作为算法的核心，如何评价当前格局的价值是重中之重。
-#在2048中，除了终局外，中间格局并无非常明显的价值评价指标，因此需要用一些启发式的指标来评价格局。
-#那些分数高的好格局是容易引向胜利的格局，而分低的坏格局是容易引向失败的格局。
-    def ai_evaluation(self):
-        #参数需要进行调试
-        #否则会变成人工智障
-        #smoothWeight = 0.5 
-        #monoWeight = 0.03  
-        #emptyWeight = 2.7  
-        #maxWeight = 4
-        #disWeight = 10 
-
-        #人工智障2.0参数
-        smoothWeight = 0.5
-        monoWeight = 0.03
-        emptyWeight = 2.7  
-        maxWeight = 4
-        disWeight = 10 
-
-        result = [disWeight*math.log2(self.dis_weight()), smoothWeight * self.smothness(), monoWeight * self.monotonicity(), 
-                  emptyWeight*math.log2(self.empty_num() + 1), maxWeight*self.max_and_submax_num()]
-        
-        #人工智障3.0参数
-        #smoothWeight = 0.1  # 0.5
-        #monoWeight = 1.0  # 0.03
-        #emptyWeight = 2.7  # 2.7
-        #maxWeight = 1  # 0.01
-        #disWeight = 0
-
-        #smoothWeight = 0.5
-        #monoWeight = 0.03
-        #emptyWeight = 2.7  
-        #maxWeight = 4
-        #disWeight = 10 
-
-        #result = [disWeight*self.dis_weight(), smoothWeight * self.smothness(), monoWeight *
-        #          self.monotonicity(), emptyWeight*math.log(self.empty_num()), maxWeight*self.max_num()]
-   
-        return result
-    #单调性
-    #单调性指方块从左到右、从上到下均遵从递增或递减。
-    ##一般来说，越单调的格局越好。
-    #下面是一个具有良好单调格局的例子
-    #  8    32    64    512
-    #  4     8    16    256
-    #  2     4     8     32
-    #  0     0     4      8
-    def monotonicity(self):
-        totals = [0,0,0,0]  # 四个方向的单调性评估  左 右 上 下（单调递增）
-        #1.横着
-        for i in range(4):
-            current = 0
-            next = current+1
-            while next < 4:
-                while next < 4 and self.map[i][next] == 0:
-                    next += 1
-                if next >= 4:
-                    next -= 1
-
-                if self.map[i][current] != 0: 
-                    currentValue = math.log2(self.map[i][current])
-                else:
-                    currentValue = 0
-
-                if self.map[i][next] != 0: 
-                    nextValue = math.log2(self.map[i][next])
-                else:
-                    nextValue = 0
-
-                if currentValue > nextValue:
-                    totals[0] += nextValue-currentValue
-                else:
-                    totals[1] += currentValue-nextValue
-                current = next
-                next += 1
-        #2.竖着
-        for i in range(4):
-            current = 0
-            next = current+1
-            while next < 4:
-                while next < 4 and self.map[next][i] == 0:
-                    next += 1
-                if next >= 4:
-                    next -= 1
-
-                if self.map[current][i] != 0:
-                    currentValue = math.log2(self.map[current][i])
-                else:
-                    currentValue = 0
-
-                if self.map[next][i] != 0:
-                    nextValue = math.log2(self.map[next][i])
-                else:
-                    nextValue = 0
-
-                if currentValue > nextValue:
-                    totals[2] += nextValue-currentValue
-                else:
-                    totals[3] += currentValue-nextValue
-                current = next
-                next += 1
-        return max(totals[:2])+max(totals[2:])
-
-    #平滑度
-    #平滑性是指每个方块与其直接相邻方块数值的差，其中差越小越平滑。
-    #例如2旁边是4就比2旁边是128平滑。
-    #一般认为越平滑的格局越好。
-    #下面是一个具有极端平滑性的例子
-    #  1024    1024    1024
-    #  1024    1024    1024    1024
-    #  1024    1024    1024    1024
-    #  1024    1024    1024    1024
-    def smothness(self):
-        lubricity = 0
-        for i in range(4):
-            for j in range(4):
-                if self.map[i][j] != 0:
-                    if i >= 1:
-                        # 左边减去该值
-                        lubricity -= abs(math.log2(self.map[i-1][j]+1) - math.log2(self.map[i][j]+1))
-                    if i < 3:
-                        # 右边减去该值
-                        lubricity -= abs(math.log2(self.map[i+1][j]+1) - math.log2(self.map[i][j]+1))
-                    if j > 0:
-                        # 上面减去该值
-                        lubricity -= abs(math.log2(self.map[i][j-1]+1) - math.log2(self.map[i][j]+1))
-                    if j < 3:
-                        # 下面减去该值
-                        lubricity -= abs(math.log2(self.map[i][j+1]+1) - math.log2(self.map[i][j]+1))
-        return lubricity
-
-    #空格数
-    #因为一般来说，空格子越少对玩家越不利。
-    #空格越多的格局越好。
-    def empty_num(self):
-        empty_num = 0
-        for i in range(4):
-            for j in range(4):
-                if self.map[i][j] == 0:
-                    empty_num += 1
-        return empty_num
-
-    #单个最大的值
-    def max_num(self):
-        max_num = 0
-        for i in range(4):
-            for j in range(4):
-                if max_num < self.map[i][j]:
-                    max_num = self.map[i][j]
-        return max_num
-
-    #这个指标评价棋盘的单个数的最大值和总体和
-    #值越大格局越好
-    def max_and_submax_num(self):
-        max_num = 0
-        subMaxNum = 0
-        for row in range(4):
-            for col in range(4):
-                if max_num < self.map[row][col]:
-                    subMaxNum = max_num + subMaxNum;
-                    max_num = self.map[row][col]
-
-        return math.log2(subMaxNum/3+max_num*2/3)  #2.0
-        #return subMaxNum/3+max_num*2/3  #3.0
-
-    #分布位置权重
-    #整体分布越往下，越往右格局越好
-    def dis_weight(self):
-        #wei = [[12, 13, 25, 50],
-        #       [11, 10, 9, 8],
-        #       [4, 5, 6, 7],
-        #       [3, 2, 1, 0]]
-        wei = [[3, 2, 1, 0],
-               [4, 5, 6, 7],
-               [16, 10, 9, 8],
-               [32,64,128,256]]
-        dis_sum = 0
-        for j in range(4):
-            for i in range(4):
-                if self.map[i][j] == 0:  #对数取值不能为0 否则会计算错误
-                    continue
-                dis_sum += math.log2(self.map[i][j])*wei[i][j]  #对数形式
-        return dis_sum
-
-    # 计算分散度，越分散得分越高
-    def islands(self):  
-        islandsMark = 0
-        self.marked = [[True]*4]*4
-        for i in range(4):
-            for j in range(4):
-                if self.map[i][j] != 0:
-                    self.marked[i][j] = False
-        for i in range(4):
-            for j in range(4):
-                if self.map[i][j] != 0 and not self.marked[i][j]:
-                    islandsMark += 1
-                    self.mark(i, j, self.map[i][j])
-        return islandsMark
-
-    def mark(self, x, y, value):
-        # 四个方向向量，方便遍历时使用
-        vectors = [[0, 1], [1, 0], [-1, 0], [0, -1]]
-        if x >= 0 and x <= 3 and y >= 0 and y <= 3 and self.map[x][y] != 0 and self.map[x][y] == value and not self.marked[x][y]:
-            self.marked[x][y] = True
-            for direction in range(4):
-                vector = vectors[direction]
-                self.mark(x+vector[0], y+vector[1], value)
-
-
-
-