我只编程了一两个星期(如你所见(，我正在制作一个回合制战略游戏。 我想在回合开始时显示玩家的可移动范围，并在移动时更新。我还需要一种用于靶场攻击、战争迷雾和 AI 寻路的方法。
在分配狩猎之后，我在 https://www.redblobgames.com/pathfinding/a-star/introduction.html 遇到了一个洪水填充示例，并试图对其进行模式化。 大多数其他例子都是深奥的类和方法，所以我从头开始。这是我想到的。 我有点知道问题在哪里，但不知道如何纠正它。
def mob_cost_calc((：
#toymatrix is a fictional map for testing
toymatrix = [[column for column in range(20)]for row in range(20)]
#move wieght is a fictional weighted map for testing
move_weight = [
[3,5,2,7,3, 3,6,4,2,2, 4,2,3,4,2, 3,4,4,5,2],
[7,6,4,9,8, 7,5,1,9,8, 7,8,6,5,4, 4,8,6,5,4],
[9,3,8,4,6, 5,1,9,8,4, 7,3,5,6,1, 1,8,4,8,1],
[1,9,3,7,4, 8,5,1,9,3, 8,4,0,0,7, 9,9,8,7,9],
[4,9,6,5,5, 2,6,4,9,4, 8,7,9,8,7, 3,4,2,9,8],
[7,5,3,8,9, 3,4,7,6,5, 1,7,6,4,6, 8,7,4,2,5],
[6,1,2,8,3, 4,6,1,8,7, 1,3,4,7,6, 1,3,8,7,4],
[3,4,8,2,7, 5,6,1,8,3, 4,7,6,1,3, 8,7,4,6,5],
[1,8,3,7,4, 5,0,2,9,8, 4,3,7,5,8, 3,4,7,1,2],
[7,3,4,6,5, 1,8,2,3,7, 0,5,6,9,8, 4,7,5,1,9],
[3,4,8,5,9, 2,7,3,4,6, 1,1,5,5,4, 1,1,8,7,2],
[4,6,0,8,3, 7,4,1,9,1, 8,7,4,1,1, 9,2,8,1,3],
[4,7,5,9,5, 8,1,3,4,2, 6,1,0,7,8, 1,3,6,4,1],
[8,7,5,6,1, 9,4,3,8,5, 1,9,1,3,8, 4,7,5,1,9],
[2,9,3,8,4, 7,5,2,9,3, 4,8,7,1,9, 1,8,6,6,4],
[5,7,8,1,5, 6,4,2,3,4, 4,9,3,7,5, 1,9,4,3,8],
[7,5,2,1,8, 7,3,4,6,7, 8,5,6,2,1, 3,4,8,9,4],
[5,7,4,9,3, 8,7,1,2,9, 8,7,3,4,5, 6,8,7,6,2],
[1,3,8,4,7, 5,6,1,8,7, 4,3,8,9,2, 3,2,4,5,9],
[8,7,7,2,3, 9,7,8,4,6, 1,5,4,1,7, 8,2,3,9,5]
]
#map attributes
TILE_SIZE =50
#initializing the matrix format appropriae to the given map size
#1. max_range_matrix is a map of zeroes to store movement potential
#2. mod_draw_matrix is for drawing reachable tiles on the screen
#3. playerpos is the player's mobility check start position
#4. mobility is a unit's movement attribute
max_range_matrix = [ 20*[0] for row in range(20)]
mob_draw_matrix = [ 20*[0] for row in range(20)]
playerpos = [10,10]
mobility = 6
#adds map mobility value in a a radius around the player position on a map
#of zeros
#1.1 zeros are discarded as impassable and act as a floodfill range
#note:to see this, run program and adjust window to line up the matrix.
for row in range(20):
for column in range(20):
if abs(playerpos[0] - column) + abs(playerpos[1] - row) <=mobility:
max_range_matrix[row][column] = move_weight[row][column]
#zeros flood fill origin to exclude from distance addition
max_range_matrix[playerpos[1]][playerpos[0]] = 0
#Initializing variable for flood fill recursion
#1. nodes i and j represents a floodfill + shape mapping the area
#2. the various check dicts swap data for flood fill recursion process
#3. nodeC starts at player position and cycles through old open checks
#4. close check stores processed checks for path efficiency calcs
NODEj = ((0,-1),(0,1))
NODEi = ((1,0),(-1,0))
mob_newOpenCheck_dict = {}
mob_oldOpenCheck_dict = {}
mob_closedCheck_dict = {}
nodec = playerpos
new_openCheck_update_dict = {}
counter = 0
while True:
if nodec != playerpos:
for old_position, old_move_cost in mob_oldOpenCheck_dict.items():
nodec = [old_position[0], old_position[1]]
#checking mobility cost down ,left, up, right from current nodeC position.
#1. nodes to shift mobility lookup in a cross patern
#2. storing coordinate(xy) and cumulative mobility values in new
#dictionary
#3. if cross checks overlap, it stores the lower of the two travel cost
#values
#note: i=y and j=x. Matrix[i][j] and Position(x,y) are reverse
for i in range(2):
for j in range(2):
i_adj = nodec[1] + NODEi[i][j]
j_adj = nodec[0] + NODEj[i][j]
current_move_cost = max_range_matrix[i_adj][j_adj]
+ old_move_cost
current_position = (j_adj, i_adj)
#testing for lowest travel cost on current tile
#evaluation
#swaping dicts to prevent self editing durring recursion
#problem!!!!!!!!!!!!!!!
new_openCheck_update_dict = {}
for new_position, new_move_cost in
mob_newOpenCheck_dict.items():
if current_position != new_position:
new_openCheck_update_dict[current_position] =
current_move_cost
elif current_position == new_position and
current_move_cost < new_move_cost:
new_openCheck_update_dict[current_position] =
current_move_cost
for current_position1, current_move_cost1 in
new_openCheck_update_dict.items():
mob_newOpenCheck_dict[current_position1] =
current_move_cost1
else:
#checking mobility cost down ,left, up, right from player position.
#1. nodes shift mobility lookup in a cross patern
#2. storing coordinate(xy) and mobility value in new open dictionary
#note: i=y and j=x. Matrix[i][j] and Position(x,y) are reverse.
for i in range(2):
for j in range(2):
i_adj = nodec[1] + NODEi[i][j]
j_adj = nodec[0] + NODEj[i][j]
move_cost = max_range_matrix[i_adj][j_adj]
move_cost_pos = (j_adj, i_adj)
mob_newOpenCheck_dict[move_cost_pos] = move_cost
nodec = [0,0]
#removing impassable area(s) from floodfill scan
#note:cannot delete from interating object so a list is used
#and cleaned at every pass
del_zero_positions = []
for position, move_cost in mob_newOpenCheck_dict.items():
if move_cost == 0:
del_zero_positions.append(position)
for position in del_zero_positions:
del mob_newOpenCheck_dict[position]
#dumping mobility old check into closed check
for position, mob_cost in mob_oldOpenCheck_dict.items():
mob_closedCheck_dict[position] = mob_cost
#replaceing mobility old check with with new check data for next
#floodfill pass.
#compare with closed to make sure fronteir doesn't move backwards
#problem!!!!!!!!!!!!!!!!!!
mob_oldOpenCheck_dict = {}
new_openCheck_update_dict = {}
for new_position, new_move_cost in mob_newOpenCheck_dict.items():
for closed_position, closed_move_cost in
mob_closedCheck_dict.items():
if new_position != closed_position:
new_openCheck_update_dict[new_position] = new_move_cost
for key, value in new_openCheck_update_dict.items():
mob_closedCheck_dict[key]=value
#clearing new check for next pass
mob_newOpenCheck_dict = {}
#set counter for experimentation
if counter == 2:
break
else:
counter += 1
continue
print('map matrix')
print(toymatrix)
print('nmax range_matrix')
print(max_range_matrix)
print('nmob_newOpenCheck_dict')
print(mob_newOpenCheck_dict)
print('nmob_oldOpenCheck_dict')
print(mob_oldOpenCheck_dict)
print('nmob_closedCheck_dict')
print(mob_closedCheck_dict)
mob_cost_calc((
将迭代检查替换为
如果在mob_newOpenCheck_dict中current_position，并且 current_move_cost <mob_newOpenCheck_dict[current_position]：>