def main():
examples = parse_examples()
services = {s: Heuristic(s) for s in get_all_service_names()}
step_size = float(FIRST_STEP_SIZE)
services_to_step = climbing(examples, services, int(step_size))
counter = 0
while len(services_to_step):
if step_size != 1.0:
step_size -= 0.5
counter += 1
sys.stdout.flush()
services_to_step = climbing(examples, services, int(step_size))
# Write to file after so many steps, that way we don't lose
# progress if we end early.
if counter == STEPS_BETWEEN_WRITES or not len(services_to_step):
counter = 0
for name, heuristic in services.iteritems():
fname = path.realpath(
path.join(
path.dirname(__file__),
'climbed_values',
name + '_climbed_values.txt'))
heuristic.write_to_file(fname)
print "Success! You did it! Hills have been climbed!"
class Service(object):
def __init__(self):
""" We need the name later for heuristic stuff """
self.heuristic = Heuristic(self.__class__.short_name())
def applies_to_me(self, client, feature_request_type):
""" Returns true if this service is a potentially relevant to the
specified client and request type.
"""
raise NotImplementedError()
def get_confidence(self, params):
""" Returns a number between -Inf and +Inf indicating the confidence of
this service that it is relevant to the specified features.
"""
return self.heuristic.run_heuristic(params['features']['keywords'])
def go(self, features):
""" Returns a response to the specified features, making calls to
exernal APIs as needed.
"""
raise NotImplementedError()
@classmethod
def short_name(cls):
name = cls.__name__
return re.match('(\w+)Service', name).group(1).lower()
class Service(object):
def __init__(self):
""" We need the name later for heuristic stuff """
self.heuristic = Heuristic(self.__class__.short_name())
def applies_to_me(self, client, feature_request_type):
""" Returns true if this service is a potentially relevant to the
specified client and request type.
"""
raise NotImplementedError()
def get_confidence(self, params):
""" Returns a number between -Inf and +Inf indicating the confidence of
this service that it is relevant to the specified features.
"""
return self.heuristic.run_heuristic(params['features']['keywords'])
def go(self, features):
""" Returns a response to the specified features, making calls to
exernal APIs as needed.
"""
raise NotImplementedError()
@classmethod
def short_name(cls):
name = cls.__name__
return re.match('(\w+)Service', name).group(1).lower()
def __init__(self):
""" We need the name later for heuristic stuff """
self.heuristic = Heuristic(self.__class__.short_name())
def __init__(self):
""" We need the name later for heuristic stuff """
self.heuristic = Heuristic(self.__class__.short_name())
# Runs an example heuristic
# Takes a feature extraction dictionary and returns a numerical value
# for the hueristic.
from pal.heuristics.hill_climber import hill_climb
from pal.heuristics.heuristic import Heuristic
dummy_dict = {'keywords': ['Movie', 'actor'], 'Proper Nouns': ['Tom Hanks']}
dummy_evil_dict = {'keywords': ['time', 'theatre'],
'Proper Nouns': ['SATAN', 'Satin']}
if __name__ == '__main__':
heuristic = Heuristic('movie')
hill_climb([dummy_dict], [dummy_evil_dict], 100, heuristic)
heuristic = Heuristic('stalkernet')
hill_climb([dummy_dict], [dummy_evil_dict], 100, heuristic)
