def get_cube_detlefko_conthist(state, player):
cube = np.zeros((12, state.board.side, state.board.side), dtype='float32')
string_lib = analyze_board.board2string_lib(state.board)
lib_count = analyze_board.liberties_count(state.board, string_lib)
empty, friend, enemy = analyze_board.board2color_mask(state.board, player)
our_liberties, enemy_liberties = friend * lib_count, enemy * lib_count
cube[0] = our_liberties == 1
cube[1] = our_liberties == 2
cube[2] = our_liberties == 3
cube[3] = our_liberties >= 4
cube[4] = enemy_liberties == 1
cube[5] = enemy_liberties == 2
cube[6] = enemy_liberties == 3
cube[7] = enemy_liberties >= 4
cube[8] = empty * 1
if state.ko_point is not None:
ko_row, ko_col = state.ko_point
cube[9][ko_row][ko_col] = 1
# watch out, history since it gives -1 for empty points
history = np.exp(- 0.1 * raw_history(state.board, state.history))
cube[10] = friend * history
cube[11] = enemy * history
return cube
def get_cube_detlefko_conthist(state, player):
cube = np.zeros((12, state.board.side, state.board.side), dtype='float32')
string_lib = analyze_board.board2string_lib(state.board)
lib_count = analyze_board.liberties_count(state.board, string_lib)
empty, friend, enemy = analyze_board.board2color_mask(state.board, player)
our_liberties, enemy_liberties = friend * lib_count, enemy * lib_count
cube[0] = our_liberties == 1
cube[1] = our_liberties == 2
cube[2] = our_liberties == 3
cube[3] = our_liberties >= 4
cube[4] = enemy_liberties == 1
cube[5] = enemy_liberties == 2
cube[6] = enemy_liberties == 3
cube[7] = enemy_liberties >= 4
cube[8] = empty * 1
if state.ko_point is not None:
ko_row, ko_col = state.ko_point
cube[9][ko_row][ko_col] = 1
# watch out, history since it gives -1 for empty points
history = np.exp(-0.1 * raw_history(state.board, state.history))
cube[10] = friend * history
cube[11] = enemy * history
return cube
def get_cube_tian_zhu_2015(state, player):
"""
Planes compatible with the
Yuandong Tian, Yan Zhu, 2015
Better Computer Go Player with Neural Network and Long-term Prediction
(arXiv:1511.06410)
"""
cube = np.zeros((25, state.board.side, state.board.side), dtype='float32')
# count liberties
string_lib = analyze_board.board2string_lib(state.board)
lib_count = analyze_board.liberties_count(state.board, string_lib)
# mask for different colors
empty, friend, enemy = analyze_board.board2color_mask(state.board, player)
our_liberties = friend * lib_count
enemy_liberties = enemy * lib_count
cube[0] = our_liberties == 1
cube[1] = our_liberties == 2
cube[2] = our_liberties >= 3
cube[3] = enemy_liberties == 1
cube[4] = enemy_liberties == 2
cube[5] = enemy_liberties >= 3
if state.ko_point is not None:
ko_row, ko_col = state.ko_point
cube[6][ko_row][ko_col] = 1
cube[7] = friend * 1
cube[8] = enemy * 1
cube[9] = empty * 1
# watch out, history since it gives -1 for empty points
history = np.exp(-0.1 * raw_history(state.board, state.history))
cube[10] = friend * history
cube[11] = enemy * history
# rank_planes
enemy_rank = state.ranks.wr if player == 'b' else state.ranks.br
# key maps: (30k, 1k) = (30, 1), (1d, 9d) = (0, -8), (1p, 9p) = (-9, ..)
# in case of None rank, make all rank planes 0
enemy_rank_key = enemy_rank.key() if enemy_rank is not None else 1
for r in xrange(9):
# one plane per dan, pros have all ones
if enemy_rank_key == -r or enemy_rank_key < -8:
cube[12 + r][:] = 1
cube[21] = static_planes.get_border_mark(state.board.side)
cube[22] = np.exp(-0.5 *
static_planes.get_sqd_from_center(state.board.side))
# distances from stones ~ cfg
dist_friend, dist_enemy = analyze_board.board2dist_from_stones(
state.board, player)
cube[23] = empty * (dist_friend < dist_enemy)
cube[24] = empty * (dist_friend > dist_enemy)
return cube
def get_cube_tian_zhu_2015(state, player):
"""
Planes compatible with the
Yuandong Tian, Yan Zhu, 2015
Better Computer Go Player with Neural Network and Long-term Prediction
(arXiv:1511.06410)
"""
cube = np.zeros((25, state.board.side, state.board.side), dtype='float32')
# count liberties
string_lib = analyze_board.board2string_lib(state.board)
lib_count = analyze_board.liberties_count(state.board, string_lib)
# mask for different colors
empty, friend, enemy = analyze_board.board2color_mask(state.board, player)
our_liberties = friend * lib_count
enemy_liberties = enemy * lib_count
cube[0] = our_liberties == 1
cube[1] = our_liberties == 2
cube[2] = our_liberties >= 3
cube[3] = enemy_liberties == 1
cube[4] = enemy_liberties == 2
cube[5] = enemy_liberties >= 3
if state.ko_point is not None:
ko_row, ko_col = state.ko_point
cube[6][ko_row][ko_col] = 1
cube[7] = friend * 1
cube[8] = enemy * 1
cube[9] = empty * 1
# watch out, history since it gives -1 for empty points
history = np.exp(- 0.1 * raw_history(state.board, state.history))
cube[10] = friend * history
cube[11] = enemy * history
# rank_planes
enemy_rank = state.ranks.wr if player == 'b' else state.ranks.br
# key maps: (30k, 1k) = (30, 1), (1d, 9d) = (0, -8), (1p, 9p) = (-9, ..)
# in case of None rank, make all rank planes 0
enemy_rank_key = enemy_rank.key() if enemy_rank is not None else 1
for r in xrange(9):
# one plane per dan, pros have all ones
if enemy_rank_key == -r or enemy_rank_key < -8:
cube[12 + r][:] = 1
cube[21] = static_planes.get_border_mark(state.board.side)
cube[22] = np.exp(-0.5 * static_planes.get_sqd_from_center(state.board.side))
# distances from stones ~ cfg
dist_friend, dist_enemy = analyze_board.board2dist_from_stones(state.board, player)
cube[23] = empty * (dist_friend < dist_enemy)
cube[24] = empty * (dist_friend > dist_enemy)
return cube
def get_cube_detlef(state, player):
"""
Planes compatible with the
CNN kindly provided by Detlef Schmicker. See
http://computer-go.org/pipermail/computer-go/2015-December/008324.html
The net should (as of January 2016) be available here:
http://physik.de/CNNlast.tar.gz
Description:
1
2
3
> 4 libs playing color
1
2
3
> 4 libs opponent color
Empty points
last move
second last move
third last move
forth last move
"""
cube = np.zeros((13, state.board.side, state.board.side), dtype='float32')
# count liberties
string_lib = analyze_board.board2string_lib(state.board)
lib_count = analyze_board.liberties_count(state.board, string_lib)
# mask for different colors
empty, friend, enemy = analyze_board.board2color_mask(state.board, player)
our_liberties = friend * lib_count
enemy_liberties = enemy * lib_count
cube[0] = our_liberties == 1
cube[1] = our_liberties == 2
cube[2] = our_liberties == 3
cube[3] = our_liberties >= 4
cube[4] = enemy_liberties == 1
cube[5] = enemy_liberties == 2
cube[6] = enemy_liberties == 3
cube[7] = enemy_liberties >= 4
cube[8] = empty * 1
# watch out, history gives -1 for empty points
history = raw_history(state.board, state.history)
cube[9] = 1 * (history == 1)
cube[10] = 1 * (history == 2)
cube[11] = 1 * (history == 3)
cube[12] = 1 * (history == 4)
return cube
def get_cube_detlef(state, player):
"""
Planes compatible with the
CNN kindly provided by Detlef Schmicker. See
http://computer-go.org/pipermail/computer-go/2015-December/008324.html
The net should (as of January 2016) be available here:
http://physik.de/CNNlast.tar.gz
Description:
1
2
3
> 4 libs playing color
1
2
3
> 4 libs opponent color
Empty points
last move
second last move
third last move
forth last move
"""
cube = np.zeros((13, state.board.side, state.board.side), dtype='float32')
# count liberties
string_lib = analyze_board.board2string_lib(state.board)
lib_count = analyze_board.liberties_count(state.board, string_lib)
# mask for different colors
empty, friend, enemy = analyze_board.board2color_mask(state.board, player)
our_liberties = friend * lib_count
enemy_liberties = enemy * lib_count
cube[0] = our_liberties == 1
cube[1] = our_liberties == 2
cube[2] = our_liberties == 3
cube[3] = our_liberties >= 4
cube[4] = enemy_liberties == 1
cube[5] = enemy_liberties == 2
cube[6] = enemy_liberties == 3
cube[7] = enemy_liberties >= 4
cube[8] = empty * 1
# watch out, history gives -1 for empty points
history = raw_history(state.board, state.history)
cube[9] = 1*(history == 1)
cube[10] = 1*(history == 2)
cube[11] = 1*(history == 3)
cube[12] = 1*(history == 4)
return cube
def get_cube_jm(state, player):
cube = np.zeros((22, state.board.side, state.board.side), dtype='float32')
string_lib = analyze_board.board2string_lib(state.board)
lib_count = analyze_board.liberties_count(state.board, string_lib)
# for liberties themselves
lib_count_lib = analyze_board.lib_nbs_to_lib_count(
state.board, string_lib.liberties_nb_count)
empty, friend, enemy = analyze_board.board2color_mask(state.board, player)
lib_liberties = empty * lib_count_lib
our_liberties = friend * lib_count
enemy_liberties = enemy * lib_count
cube[0] = lib_liberties == 1
cube[1] = lib_liberties == 2
cube[2] = lib_liberties == 3
cube[3] = lib_liberties >= 4
cube[4] = our_liberties == 1
cube[5] = our_liberties == 2
cube[6] = our_liberties == 3
cube[7] = our_liberties >= 4
cube[8] = enemy_liberties == 1
cube[9] = enemy_liberties == 2
cube[10] = enemy_liberties == 3
cube[11] = enemy_liberties >= 4
cube[12] = empty * 1
cube[13] = friend * 1
cube[14] = enemy * 1
cube[15] = 1
# watch out, history gives -1 for empty points
history = raw_history(state.board, state.history)
cube[16] = 1 * (history == 1)
cube[17] = 1 * (history == 2)
cube[18] = 1 * (history == 3)
cube[19] = 1 * (history == 4)
if state.ko_point is not None:
ko_row, ko_col = state.ko_point
cube[20][ko_row][ko_col] = 1
cube[21] = static_planes.get_exp_sqd_from_center(state.board.side, -0.5)
return cube
def get_cube_jm(state, player):
cube = np.zeros((22, state.board.side, state.board.side), dtype='float32')
string_lib = analyze_board.board2string_lib(state.board)
lib_count = analyze_board.liberties_count(state.board, string_lib)
# for liberties themselves
lib_count_lib = analyze_board.lib_nbs_to_lib_count(state.board, string_lib.liberties_nb_count)
empty, friend, enemy = analyze_board.board2color_mask(state.board, player)
lib_liberties = empty * lib_count_lib
our_liberties = friend * lib_count
enemy_liberties = enemy * lib_count
cube[0] = lib_liberties == 1
cube[1] = lib_liberties == 2
cube[2] = lib_liberties == 3
cube[3] = lib_liberties >= 4
cube[4] = our_liberties == 1
cube[5] = our_liberties == 2
cube[6] = our_liberties == 3
cube[7] = our_liberties >= 4
cube[8] = enemy_liberties == 1
cube[9] = enemy_liberties == 2
cube[10] = enemy_liberties == 3
cube[11] = enemy_liberties >= 4
cube[12] = empty * 1
cube[13] = friend * 1
cube[14] = enemy * 1
cube[15] = 1
# watch out, history gives -1 for empty points
history = raw_history(state.board, state.history)
cube[16] = 1*(history == 1)
cube[17] = 1*(history == 2)
cube[18] = 1*(history == 3)
cube[19] = 1*(history == 4)
if state.ko_point is not None:
ko_row, ko_col = state.ko_point
cube[20][ko_row][ko_col] = 1
cube[21] = static_planes.get_exp_sqd_from_center(state.board.side, -0.5)
return cube
def get_cube_basic_7_channel(state, player):
cube = np.zeros((7, state.board.side, state.board.side), dtype='uint8')
# count liberties
string_lib = analyze_board.board2string_lib(state.board)
lib_count = analyze_board.liberties_count(state.board, string_lib)
# mask for different colors
empty, friend, enemy = analyze_board.board2color_mask(state.board, player)
our_liberties = friend * lib_count
enemy_liberties = enemy * lib_count
cube[0] = our_liberties == 1
cube[1] = our_liberties == 2
cube[2] = our_liberties >= 3
cube[3] = enemy_liberties == 1
cube[4] = enemy_liberties == 2
cube[5] = enemy_liberties >= 3
if state.ko_point is not None:
ko_row, ko_col = state.ko_point
cube[6][ko_row][ko_col] = 1
return cube
def get_cube_basic_7_channel(state, player):
cube = np.zeros((7, state.board.side, state.board.side), dtype='uint8')
# count liberties
string_lib = analyze_board.board2string_lib(state.board)
lib_count = analyze_board.liberties_count(state.board, string_lib)
# mask for different colors
empty, friend, enemy = analyze_board.board2color_mask(state.board, player)
our_liberties = friend * lib_count
enemy_liberties = enemy * lib_count
cube[0] = our_liberties == 1
cube[1] = our_liberties == 2
cube[2] = our_liberties >= 3
cube[3] = enemy_liberties == 1
cube[4] = enemy_liberties == 2
cube[5] = enemy_liberties >= 3
if state.ko_point is not None:
ko_row, ko_col = state.ko_point
cube[6][ko_row][ko_col] = 1
return cube
