forth attempt's first commit
This commit is contained in:
emil
@@ -1,301 +1,141 @@
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import pygame as pg
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import time
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MAP_SIZE = 9
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start = (0, 0)
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neo = start
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observer = neo
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keymaster = ()
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class Cell:
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green_cells = [] #open cells +
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coordinates = (0, 0)
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red_cells = [] #closed cells -
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position = (0, 0)
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black_cells = [] #blocked cells =
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size = 50
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blue_cells = [] #traversed cells #
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perceptor = None
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content = None
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rect = pg.Rect(0, 0, size, size)
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border_width = 2
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closed = False
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g = 1
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h = 2
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f = g + h
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def __init__(self, position):
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self.set_position(position)
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self.rect = pg.Rect(self.coordinates[0], self.coordinates[1],
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self.size - self.border_width, self.size - self.border_width)
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def set_position(self, position):
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self.position = position
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self.coordinates = (self.position[0] * self.size,
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self.position[1] * self.size)
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def set_content(self, content):
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self.content = content
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self.content
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def set_perceptor(self, perceptor):
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self.perceptor = perceptor
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def clear_perceptor(self):
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self.perceptor = None
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def draw(self):
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pg.draw.rect(screen, "white", self.rect)
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if self.perceptor == None:
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pg.draw.rect(screen, "white", self.rect)
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else:
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pg.draw.rect(screen, self.perceptor.color, self.rect)
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g_font = pg.font.Font(None, 14)
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text = g_font.render((str)(self.g), True, "black")
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screen.blit(text, ((self.coordinates[0] + self.size * 0.05, self.coordinates[1] + self.size * 0.75)))
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h_font = pg.font.Font(None, 14)
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text = h_font.render((str)(self.h), True, "black")
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screen.blit(text, ((self.coordinates[0] + self.size * 0.8, self.coordinates[1] + self.size * 0.75)))
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f_font = pg.font.Font(None, 16)
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text = f_font.render((str)(self.f), True, "maroon")
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screen.blit(text, ((self.coordinates[0] + self.size * 0.425, self.coordinates[1] + self.size * 0.7)))
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def calculate_cost(self):
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self.g = abs(self.position[0] - neo.position[0]) + abs(self.position[1] - neo.position[1])
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def calculate_heuristic(self):
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self.h = abs(self.position[0] - keymaker.position[0]) + abs(self.position[1] - keymaker.position[1])
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def calculate_estimated(self):
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self.f = self.g + self.h
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class Map:
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steps_count = 0
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cell_matrix = []
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#accumulated_g = 0
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dimensions = (8, 8)
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map_dict = dict()
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def __init__(self, dimensions:tuple):
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self.dimensions = dimensions
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def initialize_weighted_map_dict():
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for x in range(dimensions[0]):
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for x in range(MAP_SIZE):
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column = []
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for y in range(MAP_SIZE):
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for y in range(dimensions[1]):
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map_dict[(x, y)] = [float("inf"), float("inf"), float("inf"), '.'] # (x,y) : (h, g, f, status)
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column.append(Cell((x,y)))
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self.cell_matrix.append(column)
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def get_cell(self, x, y):
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if (x < self.dimensions[0] and y < self.dimensions[1]):
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return self.cell_matrix[x][y]
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def calculate_costs(self):
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for x in range(self.dimensions[0]):
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for y in range(self.dimensions[1]):
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self.get_cell(x, y).calculate_cost()
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self.get_cell(x, y).calculate_heuristic()
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self.get_cell(x, y).calculate_estimated()
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def draw(self):
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for x in range(self.dimensions[0]):
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for y in range(self.dimensions[1]):
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self.get_cell(x, y).draw()
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class Entity:
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def print_map():
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coordinates = (0, 0)
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map_str = ""
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position = (0, 0)
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offset = (0, 0)
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cell = None
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name = ""
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color = "black"
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font_size = 32
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def __init__(self, cell_position):
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self.set_cell(map.get_cell(cell_position[0], cell_position[1]))
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def set_cell(self, cell):
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self.cell = cell
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self.position = cell.position
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self.coordinates = (self.cell.coordinates[0] + self.offset[0],
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self.cell.coordinates[1] + self.offset[1])
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self.cell.set_content(self)
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def set_position(self, x, y):
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self.set_cell(map.get_cell(x, y))
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def draw(self):
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font = pg.font.Font(None, self.font_size)
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text = font.render(self.name, True, self.color)
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screen.blit(text, ((self.cell.coordinates[0] + self.offset[0], self.cell.coordinates[1] + self.offset[1])))
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for x in range(MAP_SIZE):
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for y in range(MAP_SIZE):
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if map_dict[(x,y)][3] in "kon":
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set_status((x,y), '.')
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pass
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for x in range(MAP_SIZE):
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class Actor(Entity):
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for y in range(MAP_SIZE):
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perception_radius = 1
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percepted_cells = []
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pass
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class Neo(Actor):
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open_set = []
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def __init__(self, cell_position):
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super().__init__(cell_position)
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self.color = (100, 100, 255)
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self.name = "neo"
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def set_position(self, x, y):
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map.get_cell(x, y).closed = True
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self.update_open_set()
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return super().set_position(x, y)
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def update_open_set(self):
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self.open_set = []
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estimated_cells = []
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estimated_cells.append((self.position[0] + 1, self.position[1]))
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estimated_cells.append((self.position[0] - 1, self.position[1]))
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estimated_cells.append((self.position[0], self.position[1] + 1))
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estimated_cells.append((self.position[0], self.position[1] - 1))
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for i in estimated_cells:
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if 0 <= i[0] < map.dimensions[0] and 0 <= i[1] < map.dimensions[1]:
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if (map.get_cell(i[0], i[0]).closed == False):
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self.open_set.append(map.get_cell(i[0], i[1]))
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def percept(self):
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#clear percepted celles
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for i in self.percepted_cells:
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if (i != None):
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i.clear_perceptor()
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self.percepted_cells = []
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self.open_set = []
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for x in range(self.position[0] - self.perception_radius,
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set_status(keymaster, 'k')
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self.position[0] + self.perception_radius + 1):
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set_status(observer, 'o')
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for y in range(self.position[1] - self.perception_radius,
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set_status(neo, 'n')
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self.position[1] + self.perception_radius + 1):
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if 0 <= x < map.dimensions[0] and 0 <= y < map.dimensions[1]:
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if (x != self.position[0] or y != self.position[1]):
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self.percepted_cells.append(map.get_cell(x, y)) #set current percieved cells
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#set perceptors
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map_str += " " + map_dict[(x, y)][3] + " "
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for i in self.percepted_cells:
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map_str += "\n"
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if (i != None):
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print(map_str)
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i.set_perceptor(self)
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map.draw()
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def get_g(cell, accumulated_g): # TODO MAYBE FIX NEEDED
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pg.display.update()
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return accumulated_g + 1
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def get_h(cell):
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return abs(keymaster[0] - cell[0]) + abs(keymaster[1] - cell[1])
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def get_f(cell, accumulated_g):
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if map_dict[cell][3] == '=':
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return float("inf")
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return get_g(cell, accumulated_g) + get_h(cell)
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def get_walkable_cells(actor:tuple):
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potential_positions = [
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(actor[0], actor[1] + 1), (actor[0], actor[1] - 1),
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(actor[0] - 1, actor[1]), (actor[0] + 1, actor[1])
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]
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return [pos for pos in potential_positions if pos[0] in range(MAP_SIZE) and pos[1] in range(MAP_SIZE)]
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def get_position_input():
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position_input_list = input().split(" ")
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return int(position_input_list[0]), int(position_input_list[1])
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def set_status(position:tuple, status:str):
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map_dict[position][3] = status
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def print_cells_paremeters(cells:list):
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str = ""
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for cell in cells:
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str += f"({cell[0]},{cell[1]}): {map_dict[cell][0]} + {map_dict[cell][1]} = {map_dict[cell][2]} ({map_dict[cell][3]}) | "
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print(str)
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def calculate_next_cell(actor, accumulated_g):
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fs = []
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for cell in get_walkable_cells(actor):
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fs.append(get_f(cell, accumulated_g))
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min_f = min(fs)
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min_cells_by_f = []
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for cell in get_walkable_cells(actor):
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if get_f(cell, accumulated_g) == min_f:
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min_cells_by_f.append(cell)
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hs = []
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for cell in min_cells_by_f:
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hs.append(get_h(cell))
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min_h = min(hs)
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min_cells_by_h = []
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for cell in min_cells_by_f:
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if get_h(cell) == min_h:
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min_cells_by_h.append(cell)
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next_cell = min_cells_by_h[0]
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return next_cell
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def regenerate_route():
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global green_cells, red_cells, black_cells, neo, observer
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accumulated_g = 0
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observer = neo
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previous_cell = ()
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finish = False
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while not finish:
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pass
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class Smith(Actor):
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def __init__(self, cell_position):
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super().__init__(cell_position)
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self.color = "red"
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self.name = "smith"
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self.font_size = 26
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def percept(self):
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#clear percepted celles
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for i in self.percepted_cells:
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i.clear_perceptor()
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self.percepted_cells = []
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for x in range(self.position[0] - self.perception_radius,
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self.position[0] + self.perception_radius + 1):
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for y in range(self.position[1] - self.perception_radius,
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self.position[1] + self.perception_radius + 1):
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if (x != self.position[0] or y != self.position[1]):
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self.percepted_cells.append(map.get_cell(x, y)) #set current percieved cells
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#set perceptors
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for i in self.percepted_cells:
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i.set_perceptor(self)
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pass
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class Sentinel(Actor):
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def __init__(self, cell_position):
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super().__init__(cell_position)
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self.color = "orange"
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self.name = "sentinel"
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self.font_size = 18
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def percept(self):
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#clear percepted celles
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for i in self.percepted_cells:
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i.clear_perceptor()
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self.percepted_cells = []
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stencil_cells_positions = []
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stencil_cells_positions.append((self.position[0], self.position[1] + 1))
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stencil_cells_positions.append((self.position[0] - 1, self.position[1]))
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stencil_cells_positions.append((self.position[0], self.position[1]))
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stencil_cells_positions.append((self.position[0] + 1, self.position[1]))
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stencil_cells_positions.append((self.position[0], self.position[1] - 1))
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for i in stencil_cells_positions:
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# setting green cells
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if (i[0] != self.position[0] or i[1] != self.position[1]):
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for cell in get_walkable_cells(observer):
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self.percepted_cells.append(map.get_cell(i[0], i[1])) #set current percieved cells
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if map_dict[cell][3] not in "kon-#=":
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set_status(cell, '+')
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#set perceptors
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for i in self.percepted_cells:
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for cell in get_walkable_cells(observer):
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i.set_perceptor(self)
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map_dict[cell][0] = get_h(cell)
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pass
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map_dict[cell][1] = get_g(cell, accumulated_g)
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class Keymaker(Entity):
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map_dict[cell][2] = get_f(cell, accumulated_g)
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def __init__(self, cell_position):
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super().__init__(cell_position)
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self.color = "green"
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next_cell = calculate_next_cell(observer, accumulated_g)
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self.name = "key maker"
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self.font_size = 14
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print_cells_paremeters(get_walkable_cells(observer))
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pass
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print_map()
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class Backdoor_key(Entity):
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pass
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previous_cell = observer
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observer = next_cell
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set_status(previous_cell, '-')
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accumulated_g += 1
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red_cells.append(next_cell)
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time.sleep(0.5)
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if observer == keymaster:
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finish = True
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perception_radius = 2 #input()
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keymaster = (6,4) #get_position_input()
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def read_initial_inputs():
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initialize_weighted_map_dict()
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neo.perception_radius = (int)(input())
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set_status((0,4),'=')
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keymaker_position = input().split(" ")
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set_status((1,3),'=') # TODO FIX STUCK IN A DEAD END ISSUE
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keymaker.set_position((int)(keymaker_position[0]), (int)(keymaker_position[1]))
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regenerate_route()
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def read_input():
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inpt = input().split(" ")
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return inpt
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def move(x, y):
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for i in neo.open_set:
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print(i.position)
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if map.get_cell(x, y) in neo.open_set: #TODO: FIX CHECK
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neo.set_position(x, y)
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print(f"m {x} {y}")
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else:
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print("ERROR: CAN'T MOVE HERE")
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neo.update_open_set()
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map = Map((8, 8))
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neo = Neo((3, 3))
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neo.perception_radius = 2
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smith = Smith((1,1))
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sentinel = Sentinel((3,4))
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keymaker = Keymaker((5,5))
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pg.init()
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screen = pg.display.set_mode([1124,1124])
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pg.display.set_caption("Matrix Universe")
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running = True
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#pg.time.delay(7000)
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neo.set_position(0, 0) #TODO: ITS TEMPORARY
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neo.update_open_set()
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move(0, 0)
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read_initial_inputs()
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pg.time.delay(1500)
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while running:
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for event in pg.event.get():
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if event.type == pg.QUIT:
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|
||||||
running = False
|
|
||||||
screen.fill("black")
|
|
||||||
map.calculate_costs()
|
|
||||||
map.draw()
|
|
||||||
neo.percept()
|
|
||||||
neo.draw()
|
|
||||||
|
|
||||||
keymaker.draw()
|
|
||||||
pg.display.update()
|
|
||||||
|
|
||||||
move_input = read_input()
|
|
||||||
pg.time.delay(1500)
|
|
||||||
|
|
||||||
move((int)(move_input[0]), (int)(move_input[1]))
|
|
||||||
|
|
||||||
|
|
||||||
pg.display.update()
|
|
||||||
'''
|
|
||||||
|
|
||||||
|
|
||||||
|
|
||||||
neo.set_position(5,6)
|
|
||||||
|
|
||||||
smith.draw()
|
|
||||||
smith.percept()
|
|
||||||
|
|
||||||
sentinel.draw()
|
|
||||||
sentinel.percept()
|
|
||||||
|
|
||||||
keymaker.draw()
|
|
||||||
|
|
||||||
'''
|
|
||||||
|
|
||||||
|
|
||||||
#pg.time.delay(1000)
|
|
||||||
|
|
||||||
|
|||||||
@@ -125,7 +125,7 @@ while not finish:
|
|||||||
next_cell = min(min_f_cell_list, key=lambda cell: get_h(cell))
|
next_cell = min(min_f_cell_list, key=lambda cell: get_h(cell))
|
||||||
neo = next_cell
|
neo = next_cell
|
||||||
accumulated_g += 1 # TODO ENSURE THAT g WORKS PROPERLY
|
accumulated_g += 1 # TODO ENSURE THAT g WORKS PROPERLY
|
||||||
closed_cells.append(next_cell)
|
closed_cells.append(next_cell) # TODO DELETE
|
||||||
passed_cells.append(next_cell)
|
passed_cells.append(next_cell)
|
||||||
print(f"m {next_cell[1]} {next_cell[0]}") # TODO FIX OR ENSURE THAT x,y OR y,x DOES NOT MAKE ANY DIFFERENCE
|
print(f"m {next_cell[1]} {next_cell[0]}") # TODO FIX OR ENSURE THAT x,y OR y,x DOES NOT MAKE ANY DIFFERENCE
|
||||||
steps_count += 1
|
steps_count += 1
|
||||||
|
|||||||
Reference in New Issue
Block a user