def test_get_points_different_size_stat( self ):
"""
Tests if a list of statistics have back the right points.
The list and the expected points are the following:
(0,)->6
(1,)->3
(0, 0)->8
(0, 1)->4
(1, 0)->5
(1, 1)->2
(0, 0, 0)->10
(0, 0, 1)->6
(0, 1, 0)->6
(0, 1, 1)->2
(1, 0, 0)->7
(1, 0, 1)->4
(1, 1, 0)->4
(1, 1, 1)->1
"""
# Mock the __ini__
with patch.object(FilteredDictionary, "__init__", lambda x: None):
myFilteredDictionary=FilteredDictionary()
myFilteredDictionary.base_language="hungarian"
myFilteredDictionary.learning_language="swedish"
myFilteredDictionary.recent_stat_list={i:list(i) for i in list(itertools.product([0,1], repeat=1)) + list(itertools.product([0,1], repeat=2)) + list(itertools.product([0,1], repeat=3))}
myFilteredDictionary.word_dict={"1":('v', ['AAA'], 'aaa', '') }
expected_list=[6,3,8,4,5,2,10,6,6,2,7,4,4,1]
# run with all statuses -> result zipped with the expected valus -> pairs substracted from each other -> sum -> it must be 0
self.assertEqual( sum( [ j[0]-j[1] for j in zip( [myFilteredDictionary.get_points(i) for i in myFilteredDictionary.recent_stat_list], expected_list) ] ), 0 )
def test_get_next_random_record_only_one_good_answer( self ):
"""
Tests if there is about same chance to get the words
which had not got good answer yet
"""
# Mock the __ini__
with patch.object(FilteredDictionary, "__init__", lambda x: None):
myFilteredDictionary=FilteredDictionary()
myFilteredDictionary.base_language="hungarian"
myFilteredDictionary.learning_language="swedish"
myFilteredDictionary.recent_stat_list={
"1":[0,0,0],
"2":[0,0,0],
"3":[0,1,0],
"4":[0,0,0],
}
myFilteredDictionary.word_dict={
"1":('v', ['AAA'], 'aaa', ''),
"2":('v', ['BBB'], 'bbb', ''),
"3":('v', ['CCC'], 'ccc', ''),
"4":('v', ['DDD'], 'ddd', '')
}
loop=300000
result=Counter([myFilteredDictionary.get_next_random_record().base_word for i in range(loop)])
self.assertAlmostEqual( loop/3, result['aaa'], delta=600)
self.assertAlmostEqual( loop/3, result['bbb'], delta=600)
self.assertAlmostEqual( 0.0, result['ccc'], delta=0)
self.assertAlmostEqual( loop/3, result['ddd'], delta=600)
def test_get_random_id_wighted_chance( self ):
"""
Tests if the chance to get the words
are proportional to the point (weight) what they have.
"""
# Mock the __ini__
with patch.object(FilteredDictionary, "__init__", lambda x: None):
myFilteredDictionary=FilteredDictionary()
myFilteredDictionary.base_language="hungarian"
myFilteredDictionary.learning_language="swedish"
myFilteredDictionary.recent_stat_list={
"a": [1,1,1], # 1 point (weight)
"b": [0,1,1], # 2 points (weight)
}
myFilteredDictionary.word_dict={
"1":('v', ['AAA'], 'aaa', ''),
"2":('v', ['BBB'], 'aaa', '')
}
result=Counter( [myFilteredDictionary.get_random_id(myFilteredDictionary.recent_stat_list) for i in range(40000)] )
self.assertAlmostEqual( result["b"] / result["a"], 2.0, delta=0.08)
def test_get_next_has_good_answer( self ):
"""
Tests if the chance to get the words
are proportional to the point (weight) what they have.
It means: 10%/20%/30%/40% in sequence
"""
# Mock the __ini__
with patch.object(FilteredDictionary, "__init__", lambda x: None):
myFilteredDictionary=FilteredDictionary()
myFilteredDictionary.base_language="hungarian"
myFilteredDictionary.learning_language="swedish"
myFilteredDictionary.recent_stat_list={
"1":[1,1,1], # 1 point => 1/20 probability
"2":[0,1,1], # 2 points => 2/20 probability
"3":[1,0,1], # 4 points => 4/20 probability
"4":[0,1,0], # 6 points => 6/20 probability
"5":[1,0,0], # 7 points => 7/20 probability
}
myFilteredDictionary.word_dict={
"1":('v', ['AAA'], 'aaa', ''),
"2":('v', ['BBB'], 'bbb', ''),
"3":('v', ['CCC'], 'ccc', ''),
"4":('v', ['DDD'], 'ddd', ''),
"5":('v', ['EEE'], 'eee', '')
}
loop=40000
result=Counter([myFilteredDictionary.get_next_random_record().base_word for i in range(loop)])
self.assertAlmostEqual(result['aaa']/loop, 1/20, delta=0.01)
self.assertAlmostEqual(result['bbb']/loop, 2/20, delta=0.01)
self.assertAlmostEqual(result['ccc']/loop, 4/20, delta=0.01)
self.assertAlmostEqual(result['ddd']/loop, 6/20, delta=0.01)
self.assertAlmostEqual(result['eee']/loop, 7/20, delta=0.01)