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Implement component.fit, component.fit_xy

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This commit is contained in:
Alinson S. Xavier
2021-03-30 21:18:40 -05:00
parent 205a972937
commit 1224613b1a
7 changed files with 152 additions and 206 deletions
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171
tests/components/test_primal.py
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@@ -130,177 +130,6 @@ def test_xy_sample_without_lp_solution() -> None:
assert_array_equal(y_actual["default"], y_expected["default"])
def test_x_y_fit() -> None:
comp = PrimalSolutionComponent()
training_instances = cast(
List[Instance],
[
Mock(spec=Instance),
Mock(spec=Instance),
],
)
# Construct first instance
training_instances[0].get_variable_category = Mock( # type: ignore
side_effect=lambda var_name, index: {
0: "default",
1: None,
2: "default",
3: "default",
}[index]
)
training_instances[0].get_variable_features = Mock( # type: ignore
side_effect=lambda var, index: {
0: [0.0, 0.0],
1: [0.0, 1.0],
2: [1.0, 0.0],
3: [1.0, 1.0],
}[index]
)
training_instances[0].training_data = [
{
"Solution": {
"x": {
0: 0.0,
1: 1.0,
2: 0.0,
3: 0.0,
}
},
"LP solution": {
"x": {
0: 0.1,
1: 0.1,
2: 0.1,
3: 0.1,
}
},
},
{
"Solution": {
"x": {
0: 0.0,
1: 1.0,
2: 1.0,
3: 0.0,
}
},
"LP solution": {
"x": {
0: 0.2,
1: 0.2,
2: 0.2,
3: 0.2,
}
},
},
]
# Construct second instance
training_instances[1].get_variable_category = Mock( # type: ignore
side_effect=lambda var_name, index: {
0: "default",
1: None,
2: "default",
3: "default",
}[index]
)
training_instances[1].get_variable_features = Mock( # type: ignore
side_effect=lambda var, index: {
0: [0.0, 0.0],
1: [0.0, 2.0],
2: [2.0, 0.0],
3: [2.0, 2.0],
}[index]
)
training_instances[1].training_data = [
{
"Solution": {
"x": {
0: 1.0,
1: 1.0,
2: 1.0,
3: 1.0,
}
},
"LP solution": {
"x": {
0: 0.3,
1: 0.3,
2: 0.3,
3: 0.3,
}
},
},
{
"Solution": None,
"LP solution": None,
},
]
# Test x
x_expected = {
"default": np.array(
[
[0.0, 0.0, 0.1],
[1.0, 0.0, 0.1],
[1.0, 1.0, 0.1],
[0.0, 0.0, 0.2],
[1.0, 0.0, 0.2],
[1.0, 1.0, 0.2],
[0.0, 0.0, 0.3],
[2.0, 0.0, 0.3],
[2.0, 2.0, 0.3],
]
)
}
x_actual = comp.x(training_instances)
assert len(x_actual.keys()) == 1
assert_array_equal(x_actual["default"], x_expected["default"])
# Test y
y_expected = {
"default": np.array(
[
[True, False],
[True, False],
[True, False],
[True, False],
[False, True],
[True, False],
[False, True],
[False, True],
[False, True],
]
)
}
y_actual = comp.y(training_instances)
assert len(y_actual.keys()) == 1
assert_array_equal(y_actual["default"], y_expected["default"])
# Test fit
classifier = Mock(spec=Classifier)
threshold = Mock(spec=Threshold)
classifier_factory = Mock(return_value=classifier)
threshold_factory = Mock(return_value=threshold)
comp = PrimalSolutionComponent(
classifier=classifier_factory,
threshold=threshold_factory,
)
comp.fit(training_instances)
# Should build and train classifier for "default" category
classifier_factory.assert_called_once()
assert_array_equal(x_actual["default"], classifier.fit.call_args[0][0])
assert_array_equal(y_actual["default"], classifier.fit.call_args[0][1])
# Should build and train threshold for "default" category
threshold_factory.assert_called_once()
assert classifier == threshold.fit.call_args[0][0]
assert_array_equal(x_actual["default"], threshold.fit.call_args[0][1])
assert_array_equal(y_actual["default"], threshold.fit.call_args[0][2])
def test_predict() -> None:
comp = PrimalSolutionComponent()