def dataprops_example():
idp = IdentifierProperty(Key("id"))
nps = [NumericProperty(Key("n"), Weight(0.1), ValuePair(0, 10))]
cps = [
CategoricalProperty(Key("c1")),
CategoricalProperty(
Key("c2"),
connections=[Connection("val1", "val2", Similarity(0.25))], # type: ignore
),
]
return DataProperties(idp, nps, cps)
def dataprops_ten_percent_difference():
idp = IdentifierProperty(Key("id"))
nps = [
NumericProperty(key=Key("n1"), measurement_bounds=ValuePair(0, 10)),
NumericProperty(key=Key("n2")),
]
cps = [
CategoricalProperty(Key("c1")),
CategoricalProperty(
Key("c2"), connections=[Connection("ye", "yee", 0.5)] # type: ignore
),
CategoricalProperty(Key("c3"), Weight(0.25)),
]
return DataProperties(idp, nps, cps)
def test_ten_percent_scaled_grid(
data_ten_percent_difference, dataprops_ten_percent_difference
):
assert Grouper(
data_ten_percent_difference, dataprops_ten_percent_difference
).scaled_grid() == {
"a": {
CategoricalProperty(Key("c1"), Weight(1.0)): "left",
CategoricalProperty(
Key("c2"),
Weight(1.0),
connections=[Connection("ye", "yee", 0.5)], # type: ignore
): "ye",
CategoricalProperty(Key("c3"), Weight(0.25)): "re",
NumericProperty(
Key("n1"),
Weight(1.0),
measurement_bounds=ValuePair(0.0, 10.0),
scale_bounds=ValuePair(0.0, 1.0),
): 0.1,
NumericProperty(Key("n2"), Weight(1.0)): 0.0,
},
"b": {
CategoricalProperty(Key("c1"), Weight(1.0)): "right",
CategoricalProperty(
Key("c2"),
Weight(1.0),
connections=[Connection("ye", "yee", 0.5)], # type: ignore
): "yee",
CategoricalProperty(Key("c3"), Weight(0.25)): "ree",
NumericProperty(
Key("n1"), Weight(1.0), measurement_bounds=ValuePair(0.0, 10.0)
): 0.3,
NumericProperty(Key("n2"), Weight(1.0)): 1.0,
},
"c": {
CategoricalProperty(Key("c1"), Weight(1.0)): "left",
CategoricalProperty(
Key("c2"),
Weight(1.0),
connections=[Connection("ye", "yee", 0.5)], # type: ignore
): "yee",
CategoricalProperty(Key("c3"), Weight(0.25)): "re",
NumericProperty(
Key("n1"), Weight(1.0), measurement_bounds=ValuePair(0.0, 10.0)
): 0.1,
NumericProperty(Key("n2"), Weight(1.0)): 0.0,
},
}
def test_example_scaled_grid(data_example, dataprops_example):
assert Grouper(data_example, dataprops_example).scaled_grid() == {
"id1": {
CategoricalProperty(Key("c1"), Weight(1.0)): "me",
CategoricalProperty(
Key("c2"),
Weight(1.0),
connections=[
Connection( # type: ignore
"val1",
"val2",
Similarity(0.25),
)
],
): "val1",
NumericProperty(
Key("n"), Weight(0.1), measurement_bounds=ValuePair(0.0, 10.0)
): 0.2,
},
"id2": {
CategoricalProperty(Key("c1"), Weight(1.0)): "you",
CategoricalProperty(
Key("c2"),
Weight(1.0),
connections=[
Connection( # type: ignore
"val1",
"val2",
Similarity(0.25),
)
],
): "val2",
NumericProperty(
Key("n"), Weight(0.1), measurement_bounds=ValuePair(0.0, 10.0)
): 0.7,
},
}
def test_a_split_scaled_grid(data_a_split, dataprops_a_split):
assert Grouper(data_a_split, dataprops_a_split).scaled_grid() == {
"a": {
CategoricalProperty(Key("c1"), Weight(1.0)): "left",
CategoricalProperty(Key("c2"), Weight(1.0)): "up",
},
"b": {
CategoricalProperty(Key("c1"), Weight(1.0)): "right",
CategoricalProperty(Key("c2"), Weight(1.0)): "up",
},
"c": {
CategoricalProperty(Key("c1"), Weight(1.0)): "left",
CategoricalProperty(Key("c2"), Weight(1.0)): "down",
},
}
def dataprops_a_split():
idp = IdentifierProperty(Key("id"))
nps = []
cps = [CategoricalProperty(Key("c1")), CategoricalProperty(Key("c2"))]
return DataProperties(idp, nps, cps)
def test_b_unique_scaled_grid(data_b_unique, dataprops_b_unique):
assert Grouper(data_b_unique, dataprops_b_unique).scaled_grid() == {
"a": {CategoricalProperty(Key("c1"), Weight(1.0)): "left"},
"b": {CategoricalProperty(Key("c1"), Weight(1.0)): "right"},
"c": {CategoricalProperty(Key("c1"), Weight(1.0)): "left"},
}
def dataprops_b_unique():
idp = IdentifierProperty(Key("id"))
nps = []
cps = [CategoricalProperty(Key("c1"))]
return DataProperties(idp, nps, cps)