def create( height, width, scheme = 'none', count = 20, *args ):
"""
@spec - Specification (size, endpoints, barriers); either exactly
specified in a file, or with numeric values in a list
@option_scheme - none|manual|optimal|small-world|random|ozgur's betweenness|ozgur's randomness|2-small-world|end
@n_actions - Number of steps that need to taken
comment : optimal(shortest path to destination)??|random|ozgur's betweenness|ozgur's randomness
"""
env = ArbitraryNavigation.create(height, width)
g = env.to_graph()
gr = g.reverse()
# Percentage
if isinstance(count,str):
count = int(count[:-1])
count = count*env.S/100
# Add options for all the optimal states
O = []
if scheme == "none":
pass
elif scheme == "random-node":
O = OptionGenerator.optimal_options_from_random_nodes( env, count, *args )
elif scheme == "random-path":
O = OptionGenerator.optimal_options_from_random_paths( env, count, *args )
elif scheme == "betweenness":
O = OptionGenerator.optimal_options_from_betweenness( env, count, *args )
elif scheme == "small-world":
O = OptionGenerator.optimal_options_from_small_world( env, count, *args )
elif scheme == "ultra-small-world":
O = OptionGenerator.optimal_options_from_ultra_small_world( env, count, *args )
elif scheme == "2-small-world":
#Actually adds twice count percent options
O = OptionGenerator.optimal_options_from_small_world( env, count, *args )
O += OptionGenerator.optimal_options_from_small_world( env, count, *args )
elif scheme == "betweenness+small-world":
O = OptionEnvironment.optimal_options_from_betweenness( env, count )
count_ = count - len( O )
O += OptionEnvironment.optimal_options_from_small_world( env, count_, *args )
elif scheme == "load":
O = OptionGenerator.options_from_file( *args )[:count]
else:
raise NotImplemented()
return OptionEnvironment( ArbitraryNavigationOptions, env.S, env.A, env.P, env.R, env.R_bias, env.start_set, env.end_set, O )
def create( height, width, scheme = 'none', count = 20, *args ):
"""
@spec - Specification (size, endpoints, barriers); either exactly
specified in a file, or with numeric values in a list
@option_scheme - none|manual|optimal|small-world|random|ozgur's betweenness|ozgur's randomness|end
@n_actions - Number of steps that need to taken
comment : optimal(shortest path to destination)??|random|ozgur's betweenness|ozgur's randomness
"""
env = ArbitraryNavigation.create( height, width )
g = env.to_graph()
gr = g.reverse()
# Percentage
if isinstance(count,str):
count = int(count[:-1])
count = count*env.S/100
# Add options for all the optimal states
O = []
if scheme == "none":
pass
elif scheme == "random-node":
O = OptionGenerator.optimal_options_from_random_nodes( env, count, *args )
elif scheme == "random-path":
O = OptionGenerator.optimal_options_from_random_paths( env, count, *args )
elif scheme == "betweenness":
O = OptionGenerator.optimal_options_from_betweenness( env, count, *args )
elif scheme == "small-world":
O = OptionGenerator.optimal_options_from_small_world( env, count, *args )
elif scheme == "betweenness+small-world":
O = OptionEnvironment.optimal_options_from_betweenness( env, count )
count_ = count - len( O )
O += OptionEnvironment.optimal_options_from_small_world( env, count_, *args )
elif scheme == "load":
O = OptionGenerator.options_from_file( *args )[:count]
else:
raise NotImplemented()
return OptionEnvironment( ArbitraryNavigationOptions, env.S, env.A, env.P, env.R, env.R_bias, env.start_set, env.end_set, O )
def reset_rewards( env, road_map ):
O = env.O
env = ArbitraryNavigation.reset_rewards( env, road_map )
return OptionEnvironment( ArbitraryNavigationOptions, env.S, env.A, env.P, env.R, env.R_bias, env.start_set, env.end_set, O )
def reset_rewards(env, road_map):
O = env.O
env = ArbitraryNavigation.reset_rewards(env, road_map)
return OptionEnvironment(
ArbitraryNavigationOptions, env.S, env.A, env.P, env.R, env.R_bias, env.start_set, env.end_set, O
)
def reset_rewards( env, height, width, scheme = 'none', count = 20, *args):
O = env.O
env = ArbitraryNavigation.reset_rewards( env, height, width)
return OptionEnvironment( ArbitraryNavigationOptions, env.S, env.A, env.P, env.R, env.R_bias, env.start_set, env.end_set, O )
