Commit 293473bd authored by Michele's avatar Michele

removed some debug code

parent e15f092b
......@@ -45,7 +45,7 @@ import helpers.bisimulation as bi
import csv
logging.basicConfig(level=logging.DEBUG)
logging.basicConfig(level=logging.INFO)
logger = logging.getLogger(__name__)
HOST = 'localhost'
......
......@@ -303,7 +303,7 @@ class LearningAlgorithm:
consistentCheck = self._table.isNotGloballyConsistent()
while closingRows or consistentCheck:
while closingRows:
self._logger.info("Table is not closed")
self._logger.debug("Table is not closed")
self._logger.debug(closingRows)
self._table.promote(closingRows)
# After promoting one should check if some one letter
......@@ -316,7 +316,7 @@ class LearningAlgorithm:
consistentCheck = self._table.isNotGloballyConsistent()
# Table is closed, check for consistency
if consistentCheck:
self._logger.info("Table is not consistent")
self._logger.debug("Table is not consistent")
self._logger.debug(consistentCheck)
self._table.addColumn(consistentCheck, force=True)
if self._logger.isEnabledFor(logging.DEBUG):
......@@ -452,7 +452,7 @@ class LearningAlgorithm:
newSuffixes = self._table.isNotQuiescenceReducible()
while (newSuffixes or not self._table.isStable()):
if newSuffixes:
self._logger.info("Table is not quiescence reducible")
self._logger.debug("Table is not quiescence reducible")
self._logger.debug(newSuffixes)
if self._table.addColumn(newSuffixes, force=True):
if self._logger.isEnabledFor(logging.DEBUG):
......
......@@ -71,7 +71,7 @@ class TestLearningAlgorithm2:
self.T1 = InputOutputTeacher(self.I1)
self.O1 = InputOutputPowerOracle(self.I1)
self.tester = RandomTester(self.T1, 10000, 60)
self.tester = RandomTester(self.T1, 100000, 7)
outputExpert = OutputPurpose(set(['x','y', quiescence]))
inputExpert = InputPurpose(set(['a','b']))
......@@ -236,7 +236,7 @@ class TestLearningAlgorithm2:
parentdir = os.path.dirname(currentdir)
path = os.path.join(parentdir, "tests", "models", "test_reducibility_check2")
tester = RandomTester(T3, 50000, 25)
tester = RandomTester(T3, 50000, 7)
L3 = LearningAlgorithm(T3, O3, tester, printPath=path, maxLoops=5,
tablePreciseness = 10000, modelPreciseness = 0.8)
......@@ -245,6 +245,7 @@ class TestLearningAlgorithm2:
# If fail it is because our test extension methods are not implemented
# yet
assert_equal(bi.bisimilar(I3,Hplus), True)
#print(bi.bisimilar(I3,Hplus))
assert_equal(Hminus.isNonBlocking(), True)
assert_equal(Hminus.isQuiescenceReducible(), True)
assert_equal(Hminus.isAnomalyFree(), True)
......
# Copyright (c) 2015 Michele Volpato
#
# Permission is hereby granted, free of charge, to any person obtaining a copy
# of this software and associated documentation files (the "Software"), to deal
# in the Software without restriction, including without limitation the rights
# to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
# copies of the Software, and to permit persons to whom the Software is
# furnished to do so, subject to the following conditions:
#
# The above copyright notice and this permission notice shall be included in
# all copies or substantial portions of the Software.
#
# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
# IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
# FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
# AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
# LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
# OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
# THE SOFTWARE.
# Test learning algorithm with double set observation table
from nose.tools import *
from teachers.ltsteachers import InputOutputTeacher
from systems.implementations import InputOutputLTS, SuspensionAutomaton
from testing.randomtesting import RandomTester
import helpers.bisimulation as bi
class TestRandomTester:
......@@ -30,7 +52,7 @@ class TestRandomTester:
self.T1 = InputOutputTeacher(self.I1)
self.tester = RandomTester(self.T1, 1000, 20)
self.tester = RandomTester(self.T1, 10000, 50)
def test_simple_tester_equal(self):
inputs = set(['a','b'])
......@@ -115,8 +137,8 @@ class TestRandomTester:
assert_equal(model.isValid(), True)
tester = RandomTester(self.T1, 4, 2)
# model is not correct, but we cannot find the problem because of
# to few tests
tester = RandomTester(self.T1, 3, 2)
ce, output = tester.findCounterexample(model)
assert_equal(ce, None)
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