/usr/share/pyshared/pebl/learner/exhaustive.py is in python-pebl 1.0.2-2build1.
This file is owned by root:root, with mode 0o644.
The actual contents of the file can be viewed below.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 | """Classes and functions for doing exhaustive learning."""
from pebl import prior, config, evaluator, result, network
from pebl.learner.base import Learner
from pebl.taskcontroller.base import Task
class ListLearner(Learner):
#
# Parameter
#
_params = (
config.StringParameter(
'listlearner.networks',
"""List of networks, one per line, in network.Network.as_string()
format.""",
default=''
)
)
def __init__(self, data_=None, prior_=None, networks=None):
"""Create a ListLearner learner.
networks should be a list of networks (as network.Network instances).
"""
super(ListLearner, self).__init__(data_, prior_)
self.networks = networks
if not networks:
variables = self.data.variables
_net = lambda netstr: network.Network(variables, netstr)
netstrings = config.get('listlearner.networks').splitlines()
self.networks = (_net(s) for s in netstrings if s)
def run(self):
self.result = result.LearnerResult(self)
self.evaluator = evaluator.fromconfig(self.data, prior_=self.prior)
self.result.start_run()
for net in self.networks:
self.result.add_network(net, self.evaluator.score_network(net))
self.result.stop_run()
return self.result
def split(self, count):
"""Split the learner into multiple learners.
Splits self.networks into `count` parts. This is similar to MPI's
scatter functionality.
"""
nets = list(self.networks)
numnets = len(nets)
netspertask = numnets/count
# divide list into parts
indices = [[i,i+netspertask] for i in xrange(0,numnets,netspertask)]
if len(indices) > count:
indices.pop(-1)
indices[-1][1] = numnets-1
return [ListLearner(self.data, self.prior, nets[i:j])for i,j in indices]
def __getstate__(self):
# convert self.network from iterators or generators to a list
d = self.__dict__
d['networks'] = list(d['networks'])
return d
|