def tree_timer_check():
for seed in seeds:
seed.timer += 1
if seed.is_grounded:
if seed.timer >= 250 + seed.timer_displace:
tree_colour_select(seed, 1)
sprouts.append(
Tree(seed.x, seed.y, seed.size, seed.colour,
seed.colour_value, 0, seed.timer_displace,
seed.leaf_colour, seed.type, seed.leaf_displace))
seeds.pop(seeds.index(seed))
for sprout in sprouts:
sprout.timer += 1
if sprout.timer >= 500 + sprout.timer_displace * 2:
tree_colour_select(sprout, 2)
leaf_colour_select(sprout, 2)
saplings.append(
Tree(sprout.x, sprout.y, sprout.size, sprout.colour,
sprout.colour_value, 0, sprout.timer_displace,
sprout.leaf_colour, sprout.type, sprout.leaf_displace))
sprouts.pop(sprouts.index(sprout))
for sapling in saplings:
sapling.timer += 1
if sapling.timer >= 750 + sapling.timer_displace * 3:
tree_colour_select(sapling, 3)
leaf_colour_select(sapling, 3)
trees.append(
Tree(sapling.x, sapling.y, sapling.size, sapling.colour,
sapling.colour_value, 0, sapling.timer_displace,
sapling.leaf_colour, sapling.type, sapling.leaf_displace))
saplings.pop(saplings.index(sapling))
def p_assignment_new_name(p):
"""
assignment : NAME ASSIGN arithmeticexpr
"""
global noOfAssignDecl
noOfAssignDecl += 1
p[0] = Tree(Tree(p[1], None, 'VAR'), p[3][0], 'ASGN')
if (not p[3][1]):
print("syntax error at =")
sys.exit()
def p_startwithany_define(p):
"""
startwithany : POINTER startwithany
| AMPERSAND startwithany
| NAME
"""
if p[1] == '*':
x = Tree(p[2], None, 'DEREF')
elif p[1] == '&':
x = Tree(p[2], None, 'ADDR')
else:
x = Tree(p[1], None, 'VAR')
p[0] = x
def build_RF_trees_prediction(n, train, target, n_random_columns, max_depth,
sample_size):
test = get_test()
for i in range(0, n):
print('________________________________________________________')
print('--------------> CREANDO ARBOL ' + str(i) + '...')
ts = time.time()
print('--------------> INICIO: ' +
str(datetime.datetime.fromtimestamp(ts).strftime('%H:%M:%S')))
tree = Tree(train.sample(sample_size), target, n_random_columns,
max_depth)
print('--------------> ARBOL NUEVO: ' + str(i))
ts1 = time.time()
print('--------------> SE CREO EN: ' + str(round((ts1 - ts) / 60, 2)) +
' MINUTOS ')
print('--------------> CALCULANDO PREDICCION...')
write_csv(
get_tree_prediction(test, tree).items(),
str(i) + 'prediction.csv'
) # aca va el nombre de como se crean los csv de resultados
print('--------------> SE CALCULO PREDICCION EN: ' +
str(round((time.time() - ts1) / 60, 2)) + ' MINUTOS')
print('--------------> DEMORO UN TOTAL DE: ' +
str(round((time.time() - ts) / 60, 2)) + ' MINUTOS')
def p_assignment_new_startwithstar(p):
"""
assignment : startwithstar ASSIGN arithmeticexpr
"""
global noOfAssignDecl
noOfAssignDecl += 1
p[0] = Tree(p[1], p[3][0], 'ASGN')
def p_booleanexpr_term(p):
"""
booleanexpr : booleanexpr OR booleanexpr
| booleanexpr AND booleanexpr
| LPAREN booleanexpr RPAREN
| NEGATION booleanexpr
"""
if p[2] == '||':
x = Tree(p[1], p[3], 'OR')
elif p[2] == '&&':
x = Tree(p[1], p[3], 'AND')
elif p[1] == '(':
x = p[2]
else:
x = Tree(p[2], None, 'NOT')
p[0] = x
def p_ifblock_ifelse(p):
"""
ifblock : IF LPAREN CONDITION RPAREN conditionalbody ELSE ifelsehandler
"""
x = Tree(p[3], [p[5], p[7]], 'IFELSE')
p[0] = x
def p_arithmeticexpr_binop(p):
"""
arithmeticexpr : arithmeticexpr PLUS arithmeticexpr
| arithmeticexpr MINUS arithmeticexpr
| arithmeticexpr POINTER arithmeticexpr
| arithmeticexpr DIVIDE arithmeticexpr
"""
if p[2] == '+':
x = Tree(p[1][0], p[3][0], 'PLUS')
elif p[2] == '-':
x = Tree(p[1][0], p[3][0], 'MINUS')
elif p[2] == '*':
x = Tree(p[1][0], p[3][0], 'MUL')
elif p[2] == '/':
x = Tree(p[1][0], p[3][0], 'DIV')
p[0] = [x, p[1][1] or p[3][1]]
def build_RF_trees(n, train, target, n_random_columns, max_depth, sample_size):
for i in range(0, n):
print('CREANDO ARBOL ' + str(i))
print(datetime.datetime.fromtimestamp(ts).strftime('%H:%M:%S'))
tree = Tree(train.sample(sample_size), target, n_random_columns,
max_depth)
serialize_tree(tree, (str(i) + 'RF_3_5.pkl'))
print('<------------------------------------ARBOL NUEVO = ' + str(i) +
' ------------------------------------>')
print('SE CREO EN: ' + str((time.time() - ts) / 60) + ' MINUTOS')
def recursive_minimax(game: 'Game') -> Any:
"""
A recursive minimax implementation that returns the best score that the
a player can make for a certain game.
@param game 'Game': a Game object that represents the current game being
played
@rtype: Any
"""
t = Tree((game.current_state, [], None, None))
return recursive_helper(t, game)
def p_conditionalbody_def(p):
"""
conditionalbody : line SEMICOLON
| LFBRACK lines RFBRACK
"""
if p[1] == '{':
p[0] = p[2]
else:
if p[1][1]:
p[0] = [p[1][0]]
else:
sys.exit()
p[0] = Tree(None, None, 'None')
def p_boolfromarith_def(p):
"""
boolfromarith : arithmeticexpr LTE arithmeticexpr
| arithmeticexpr GTE arithmeticexpr
| arithmeticexpr LT arithmeticexpr
| arithmeticexpr GT arithmeticexpr
| arithmeticexpr COMPARENOTEQUAL arithmeticexpr
| arithmeticexpr COMPAREEQUAL arithmeticexpr
"""
if p[2] == '<=':
x = Tree(p[1][0], p[3][0], 'LE')
elif p[2] == '>=':
x = Tree(p[1][0], p[3][0], 'GE')
elif p[2] == '<':
x = Tree(p[1][0], p[3][0], 'LT')
elif p[2] == '>':
x = Tree(p[1][0], p[3][0], 'GT')
elif p[2] == '!=':
x = Tree(p[1][0], p[3][0], 'NE')
elif p[2] == '==':
x = Tree(p[1][0], p[3][0], 'EQ')
p[0] = x
def recursive_helper(t: 'Tree', game: 'Game') -> Any:
"""
A recursive minimax helper function that returns the best available move
that can be played by a player for a certain game.
@param t 'Tree': a Tree onject that is a representation of a specific state
within the game
@param game 'Game': a Game object that represents the current game being
played
@rtype: Any
"""
if t.value.get_possible_moves() == []:
old_state = game.current_state
game.current_state = t.value
if not game.is_winner('p1') and not game.is_winner('p2'):
t.score = 0
game.current_state = old_state
else:
t.score = -1
game.current_state = old_state
return t.score
elif t.value.get_possible_moves() != [] and \
t.value.__repr__() != game.current_state.__repr__():
for move in t.value.get_possible_moves():
q = Tree((t.value.make_move(move), [], None, move))
if q.value.get_possible_moves() == []:
q.score = recursive_helper(q, game)
else:
q.score = max([-1 * \
recursive_helper(Tree((q.value.make_move(x), \
[], None, x,)), game)\
for x in q.value.get_possible_moves()])
t.children.append(q)
t.score = max([x.score * -1 for x in t.children])
return t.score
else:
for value in game.current_state.get_possible_moves():
node = Tree((t.value.make_move(value), [], None, value))
t.children.append(node)
for node in t.children:
if node.value.get_possible_moves() == []:
return node.move_made
lst = []
t.score = max([-1 * recursive_helper(x, game) for x in t.children])
for node in t.children:
if node.score == t.score * -1:
lst.append(node.move_made)
return random.choice(lst)
def p_ifblock_if(p):
"""
ifblock : IF LPAREN CONDITION RPAREN conditionalbody
"""
x = Tree(p[3], p[5], 'IF')
p[0] = x
from classes import Tree
if __name__ == '__main__':
tree = Tree()
nodes = [50, 70, 60, 80, 30, 20, 40]
for node in nodes:
tree.add(node)
tree.add(65)
tree.remove(50)
tree.xprint()
# tree.xprint()
# print(f'Min value: {tree.find_min()}\nMax value: {tree.find_max()}')
# print(f'Left height: {tree.left_height()}')
# print(f'Right height: {tree.right_height()}')
# 50
# / \
# 30 70
# / \ / \
# 20 40 60 80
def p_whileblock_def(p):
"""
whileblock : WHILE LPAREN CONDITION RPAREN conditionalbody
"""
x = Tree(p[3], p[5], 'WHILE')
p[0] = x
def p_startwithstar_define(p):
"""
startwithstar : POINTER startwithany
"""
p[0] = Tree(p[2], None, 'DEREF')
def p_arithmeticexpr_terminal_NUMBER(p):
"""
arithmeticexpr : NUMBER
| FLOATNUM
"""
p[0] = [Tree(p[1], None, 'CONST'), False]
def p_arithmeticexpr_uminus(p):
"""
arithmeticexpr : MINUS arithmeticexpr %prec UMINUS
"""
p[0] = [Tree(p[2][0], None, 'UMINUS'), p[2][1]]
def iterative_minimax(game: 'Game') -> Any:
"""
Returns the best score available for a certain game using an iterative
approach.
@param game 'Game': the Game object that represents the game being played
@rtype: Any
"""
tree_list = []
tree_list.append(Tree((game.current_state, [], None, None)))
s = Stack()
s.add(tree_list[0])
a_lst = []
while not s.is_empty():
p = s.remove()
if (p.children == []) and p.value.get_possible_moves() != []:
moves = [p]
for value in p.value.get_possible_moves():
q = Tree((p.value.make_move(value), [], None, value))
p.children.append(q)
tree_list.append(q)
moves.append(q)
a_lst.append(moves)
for node in tree_list:
s.add(node)
elif (p.children == []) and p.value.get_possible_moves() == []:
old_state = game.current_state
game.current_state = p.value
if not game.is_winner('p1') and not game.is_winner('p2'):
p.score = 0
game.current_state = old_state
else:
p.score = -1
game.current_state = old_state
else:
lst_scores = []
for node in p.children:
lst_scores.append(node.score * -1)
p.score = max(lst_scores)
for outer_list in a_lst:
if game.current_state.__repr__() == outer_list[0].value.__repr__() \
and outer_list[0].children != []:
lst = []
for node in outer_list[0].children:
if node.value.get_possible_moves() == []:
lst.append(node.move_made)
if len(lst) == 1:
return lst[0]
elif len(lst) >= 1:
return random.choice(lst)
m = [(node.move_made, node.score) for node in outer_list[1:]]
lst = []
for item in m:
if item[1] == outer_list[0].score * -1:
lst.append(item[0])
return random.choice(lst)
return -1
for tree in trees:
is_touching(pos, 2, tree)
if tree.touching:
if tree.type == 1:
wood1 += tree.size * 5
if tree.type == 2:
wood2 += tree.size * 5
if tree.type == 3:
wood3 += tree.size * 5
trees.pop(trees.index(tree))
tree.touching = False
elif seed_type == 1:
if seed1_amount > 0:
seeds.append(
Tree(pos[0], pos[1],
random.randint(4, 6), 0,
random.randint(1, 5), 0,
random.randint(20, 120), 0, 1))
seed1_amount -= 1
elif seed_type == 2:
if seed2_amount > 0:
seeds.append(
Tree(pos[0], pos[1],
random.randint(4, 6), 0,
random.randint(1, 5), 0,
random.randint(20, 120), 0, 2,
random.randint(0, 30)))
seed2_amount -= 1
elif seed_type == 3:
if seed3_amount > 0:
seeds.append(
Tree(pos[0], pos[1],