mirror of
https://github.com/13hannes11/bachelor_thesis_m.recommend.git
synced 2024-09-04 01:11:00 +02:00
add recommender to repository
This commit is contained in:
hannes.kuchelmeister
14
tests/test_scoring/test_list_functions.py
Normal file
14
tests/test_scoring/test_list_functions.py
Normal file
@@ -0,0 +1,14 @@
|
||||
from scoring.list_functions import Average, Product
|
||||
import math
|
||||
|
||||
class TestListToValueFunctionAverage:
|
||||
def test_simple_average(self):
|
||||
function = Average()
|
||||
list = [0.0, 1.0]
|
||||
assert math.isclose(0.5, function.convertToFloat(list))
|
||||
|
||||
class TestListToValueFunctionProduct:
|
||||
def test_simple_product(self):
|
||||
function = Product()
|
||||
list = [0.5, 0.5]
|
||||
assert math.isclose(0.25, function.convertToFloat(list))
|
||||
114
tests/test_scoring/test_preference_functions.py
Normal file
114
tests/test_scoring/test_preference_functions.py
Normal file
@@ -0,0 +1,114 @@
|
||||
from scoring.preferences_functions import PerUserPerFeatureDistanceAverageToListFunction, SimplePerUserToListFunction, PreferencesToListFunction, FlattenPreferencesToListFunction
|
||||
from scoring.list_functions import Min
|
||||
from model.configuration_model import ConfigurationModel
|
||||
from model.preferences_model import Preferences
|
||||
from model.product_structure_model import ProductStructureModel
|
||||
|
||||
preferences = Preferences({
|
||||
'preferences': [
|
||||
{
|
||||
'user': "user0",
|
||||
'ratings':[ {
|
||||
'code': 'A1',
|
||||
'value': 0
|
||||
}, {
|
||||
'code': 'A2',
|
||||
'value': 1
|
||||
}, {
|
||||
'code': 'B1',
|
||||
'value': 0.5
|
||||
}
|
||||
]
|
||||
},
|
||||
{
|
||||
'user': "user1",
|
||||
'ratings':[ {
|
||||
'code': 'A1',
|
||||
'value': 1
|
||||
}, {
|
||||
'code': 'B2',
|
||||
'value': 1
|
||||
}
|
||||
]
|
||||
}
|
||||
]
|
||||
})
|
||||
toRate = ConfigurationModel({
|
||||
'configuration': ['A1', 'B2'],
|
||||
'variables': []
|
||||
})
|
||||
|
||||
product_structure = ProductStructureModel({
|
||||
'ProductStructure': [
|
||||
{
|
||||
'elementId': 'A',
|
||||
'name': 'parent_element A',
|
||||
'type': "FEATURE",
|
||||
'additionalData': [],
|
||||
'children': [
|
||||
{
|
||||
'elementId': 'A1',
|
||||
'name': 'child A1',
|
||||
'children': [],
|
||||
'additionalData': [],
|
||||
'type': "CHARACTERISTIC"
|
||||
},
|
||||
{
|
||||
'elementId': 'A2',
|
||||
'name': 'child A2',
|
||||
'children': [],
|
||||
'additionalData': [],
|
||||
'type': "CHARACTERISTIC"
|
||||
}
|
||||
],
|
||||
},{
|
||||
'elementId': 'B',
|
||||
'name': 'parent_element B',
|
||||
'type': "FEATURE",
|
||||
'additionalData': [],
|
||||
'children': [
|
||||
{
|
||||
'elementId': 'B1',
|
||||
'name': 'child B1',
|
||||
'children': [],
|
||||
'additionalData': [],
|
||||
'type': "CHARACTERISTIC"
|
||||
},
|
||||
{
|
||||
'elementId': 'B2',
|
||||
'name': 'child B2',
|
||||
'children': [],
|
||||
'additionalData': [],
|
||||
'type': "CHARACTERISTIC"
|
||||
}
|
||||
],
|
||||
},
|
||||
]
|
||||
})
|
||||
def float_lists_same(first, second):
|
||||
for element in first:
|
||||
if element not in second:
|
||||
return False
|
||||
second.remove(element)
|
||||
if len(second) != 0:
|
||||
return False
|
||||
return True
|
||||
class TestPreferencesToListFunction:
|
||||
def test_should_be_empty_list(self):
|
||||
function = PreferencesToListFunction()
|
||||
assert len(function.convertToList(preferences, toRate)) == 0
|
||||
|
||||
class TestFlattenPreferencesToListFunction():
|
||||
def test_simple_example(self):
|
||||
function = FlattenPreferencesToListFunction()
|
||||
assert float_lists_same([1.0,0.5,0.0,0.0,1.0], function.convertToList(preferences, toRate))
|
||||
|
||||
class TestSimplePerUserToListFunction():
|
||||
def test_simple_example(self):
|
||||
function = SimplePerUserToListFunction(Min())
|
||||
assert float_lists_same([0.0, 1.0], function.convertToList(preferences, toRate))
|
||||
|
||||
class TestPerUserPerFeatureDistanceAverageToListFunction():
|
||||
def test_simple_example(self):
|
||||
function = PerUserPerFeatureDistanceAverageToListFunction(Min(), product_structure)
|
||||
assert float_lists_same([0.25, 0.625], function.convertToList(preferences, toRate))
|
||||
124
tests/test_scoring/test_scoring_functions.py
Normal file
124
tests/test_scoring/test_scoring_functions.py
Normal file
@@ -0,0 +1,124 @@
|
||||
from scoring.scoring_functions import PreferenceScoring, RatioCharacteristicConfigurationPenalty, WeightedFeaturePenalty, ReduceScoring
|
||||
from scoring.value_functions import ValueToValueFunction
|
||||
from model.configuration_model import ConfigurationModel
|
||||
from model.preferences_model import Preferences
|
||||
from scoring.list_functions import Min, Average
|
||||
from scoring.preferences_functions import FlattenPreferencesToListFunction
|
||||
from model.product_structure_model import ProductStructureModel
|
||||
|
||||
preferences = Preferences({
|
||||
'preferences': [
|
||||
{
|
||||
'user': "user0",
|
||||
'ratings':[ {
|
||||
'code': 'A1',
|
||||
'value': 0
|
||||
}, {
|
||||
'code': 'A2',
|
||||
'value': 1
|
||||
}, {
|
||||
'code': 'B1',
|
||||
'value': 0.5
|
||||
}
|
||||
]
|
||||
},
|
||||
{
|
||||
'user': "user1",
|
||||
'ratings':[ {
|
||||
'code': 'A1',
|
||||
'value': 1
|
||||
}, {
|
||||
'code': 'B2',
|
||||
'value': 1
|
||||
}
|
||||
]
|
||||
}
|
||||
]
|
||||
})
|
||||
currentConfiguration = ConfigurationModel({
|
||||
'configuration': ['A2', 'B2'],
|
||||
'variables': []
|
||||
})
|
||||
toRate = ConfigurationModel({
|
||||
'configuration': ['A1', 'B2'],
|
||||
'variables': []
|
||||
})
|
||||
|
||||
product_structure = ProductStructureModel({
|
||||
'ProductStructure': [
|
||||
{
|
||||
'elementId': 'A',
|
||||
'name': 'parent_element A',
|
||||
'type': "FEATURE",
|
||||
'additionalData': [],
|
||||
'children': [
|
||||
{
|
||||
'elementId': 'A1',
|
||||
'name': 'child A1',
|
||||
'children': [],
|
||||
'additionalData': [],
|
||||
'type': "CHARACTERISTIC"
|
||||
},
|
||||
{
|
||||
'elementId': 'A2',
|
||||
'name': 'child A2',
|
||||
'children': [],
|
||||
'additionalData': [],
|
||||
'type': "CHARACTERISTIC"
|
||||
}
|
||||
],
|
||||
},{
|
||||
'elementId': 'B',
|
||||
'name': 'parent_element B',
|
||||
'type': "FEATURE",
|
||||
'additionalData': [],
|
||||
'children': [
|
||||
{
|
||||
'elementId': 'B1',
|
||||
'name': 'child B1',
|
||||
'children': [],
|
||||
'additionalData': [],
|
||||
'type': "CHARACTERISTIC"
|
||||
},
|
||||
{
|
||||
'elementId': 'B2',
|
||||
'name': 'child B2',
|
||||
'children': [],
|
||||
'additionalData': [],
|
||||
'type': "CHARACTERISTIC"
|
||||
}
|
||||
],
|
||||
},
|
||||
]
|
||||
})
|
||||
|
||||
class TestRatioCharacteristicConfigurationPenalty:
|
||||
def test_simple_example(self):
|
||||
function = RatioCharacteristicConfigurationPenalty(product_structure, [ValueToValueFunction()])
|
||||
assert 0.5 == function.calc_score(currentConfiguration, preferences, toRate)
|
||||
|
||||
|
||||
class TestWeightedFeaturePenalty:
|
||||
def test_simple_example(self):
|
||||
function = WeightedFeaturePenalty(product_structure, Min(), Average())
|
||||
assert 0.375 == function.calc_score(currentConfiguration, preferences, toRate)
|
||||
|
||||
class TestReduceScoring:
|
||||
def test_combined(self):
|
||||
function = ReduceScoring([
|
||||
RatioCharacteristicConfigurationPenalty(product_structure, [ValueToValueFunction()]),
|
||||
WeightedFeaturePenalty(product_structure, Min(), Average())
|
||||
])
|
||||
assert 0.875 == function.calc_score(currentConfiguration, preferences, toRate)
|
||||
def test_none(self):
|
||||
function = ReduceScoring([])
|
||||
assert 0 == function.calc_score(currentConfiguration, preferences, toRate)
|
||||
|
||||
class TestPreferenceScoring:
|
||||
def test_simple_example(self):
|
||||
function = PreferenceScoring(
|
||||
FlattenPreferencesToListFunction(),
|
||||
Min()
|
||||
)
|
||||
assert 0 == function.calc_score(currentConfiguration, preferences, toRate)
|
||||
|
||||
44
tests/test_scoring/test_value_functions.py
Normal file
44
tests/test_scoring/test_value_functions.py
Normal file
@@ -0,0 +1,44 @@
|
||||
from scoring.value_functions import MapToPercent, ValueToValueFunction, HighpassFilterFunction, LowpassFilterFunction, PowerFunction
|
||||
import math
|
||||
|
||||
class TestMapToPercent:
|
||||
def test_range_conversion(self):
|
||||
function = MapToPercent(-20, -40)
|
||||
assert math.isclose(1, function.applyToValue(-20))
|
||||
assert math.isclose(0, function.applyToValue(-40))
|
||||
assert math.isclose(0.5, function.applyToValue(-30))
|
||||
|
||||
class TestValueToValueFunction:
|
||||
def test_same_value(self):
|
||||
function = ValueToValueFunction()
|
||||
assert math.isclose(10, function.applyToValue(10))
|
||||
|
||||
class TestHighpassFilterFunction:
|
||||
def test_higher_value(self):
|
||||
function = HighpassFilterFunction(0.5)
|
||||
assert math.isclose(0.8, function.applyToValue(0.8))
|
||||
def test_lower_value(self):
|
||||
function = HighpassFilterFunction(0.5)
|
||||
assert math.isclose(0, function.applyToValue(0.3))
|
||||
def test_same_value(self):
|
||||
function = HighpassFilterFunction(0.5)
|
||||
assert math.isclose(0.5, function.applyToValue(0.5))
|
||||
|
||||
class TestLowpassFilterFunction:
|
||||
def test_higher_value(self):
|
||||
function = LowpassFilterFunction(0.5)
|
||||
assert math.isclose(1, function.applyToValue(0.8))
|
||||
def test_lower_value(self):
|
||||
function = LowpassFilterFunction(0.5)
|
||||
assert math.isclose(0.3, function.applyToValue(0.3))
|
||||
def test_same_value(self):
|
||||
function = LowpassFilterFunction(0.5)
|
||||
assert math.isclose(0.5, function.applyToValue(0.5))
|
||||
|
||||
class TestPowerFunction:
|
||||
def test_power_one(self):
|
||||
function = PowerFunction(10)
|
||||
assert math.isclose(1, function.applyToValue(1))
|
||||
def test_power_small_number(self):
|
||||
function = PowerFunction(4)
|
||||
assert math.isclose(0.0001, function.applyToValue(0.1))
|
||||
Reference in New Issue
Block a user