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Fix tests with new features
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@gmontamat
gmontamat committed Sep 17, 2024
1 parent 902422f commit 45660c5
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Showing 3 changed files with 108 additions and 24 deletions.
55 changes: 36 additions & 19 deletions tests/test_individuals.py
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Original file line number Diff line number Diff line change
Expand Up @@ -17,20 +17,23 @@ def __init__(self, param1: int, param2: str = "default", param3: Union[int, str]
self.param3 = param3
self.param4 = param4

def evaluate(self, x_train, y_train):
def create_train_evaluate(self, x_train, y_train, x_test, y_test):
return 0.9


def test_individual_init():
genes = [Gene("gene1"), Gene("gene2")]
handler = MockHandler
x_train, y_train = [1, 2, 3], [4, 5, 6]
x_test, y_test = [6, 5, 4], [3, 2, 1]
hyperparameters = {"param1": 10, "param2": "value"}
individual = Individual(genes, handler, x_train, y_train, hyperparameters)
individual = Individual(genes, handler, x_train, y_train, x_test, y_test, hyperparameters)
assert individual.genes == genes
assert individual.handler == handler
assert individual.x_train == x_train
assert individual.y_train == y_train
assert individual.x_test == x_test
assert individual.y_test == y_test
assert individual.hyperparameters == hyperparameters
assert individual.fitness is None
assert individual.job_id is None
Expand All @@ -40,43 +43,48 @@ def test_validate_params():
genes = [Gene("gene1"), Gene("gene2")]
handler = MockHandler
x_train, y_train = [1, 2, 3], [4, 5, 6]
x_test, y_test = [6, 5, 4], [3, 2, 1]

# Should not raise any exceptions
hyperparameters = {"param1": 10, "param2": "value", "param3": 3}
kwargs = {"param4": 4}
individual = Individual(genes, handler, x_train, y_train, hyperparameters, **kwargs)
individual = Individual(genes, handler, x_train, y_train, x_test, y_test, hyperparameters, **kwargs)
individual.validate_params()

# Should not raise any exceptions
hyperparameters = {"param1": 10, "param2": "value"}
kwargs = {"param3": "3"}
individual = Individual(genes, handler, x_train, y_train, hyperparameters, **kwargs)
individual = Individual(genes, handler, x_train, y_train, x_test, y_test, hyperparameters, **kwargs)
individual.validate_params()

# Test missing required parameter
hyperparameters = {"param2": "value"}
kwargs = {"param3": "3"}
with pytest.raises(ValueError):
Individual(genes, handler, x_train, y_train, hyperparameters)
individual = Individual(genes, handler, x_train, y_train, x_test, y_test, hyperparameters, **kwargs)
individual.validate_params()

# Test hyperparameter type mismatch
hyperparameters = {"param1": "wrong_type", "param2": "value"}
with pytest.raises(TypeError):
Individual(genes, handler, x_train, y_train, hyperparameters)
individual = Individual(genes, handler, x_train, y_train, x_test, y_test, hyperparameters)
individual.validate_params()

# Test kwarg type mismatch
hyperparameters = {"param1": 10, "param2": "value"}
kwargs = {"param4": "4"}
with pytest.raises(TypeError):
Individual(genes, handler, x_train, y_train, hyperparameters, **kwargs)
individual = Individual(genes, handler, x_train, y_train, x_test, y_test, hyperparameters, **kwargs)
individual.validate_params()


def test_evaluate_fitness():
genes = [Gene("gene1"), Gene("gene2")]
handler = MockHandler
x_train, y_train = [1, 2, 3], [4, 5, 6]
x_test, y_test = [6, 5, 4], [3, 2, 1]
hyperparameters = {"param1": 10, "param2": "value"}
individual = Individual(genes, handler, x_train, y_train, hyperparameters)
individual = Individual(genes, handler, x_train, y_train, x_test, y_test, hyperparameters)
fitness = individual.evaluate_fitness()
assert fitness == 0.9
assert individual.fitness == 0.9
Expand All @@ -86,8 +94,9 @@ def test_get_fitness():
genes = [Gene("gene1"), Gene("gene2")]
handler = MockHandler
x_train, y_train = [1, 2, 3], [4, 5, 6]
x_test, y_test = [6, 5, 4], [3, 2, 1]
hyperparameters = {"param1": 10, "param2": "value"}
individual = Individual(genes, handler, x_train, y_train, hyperparameters)
individual = Individual(genes, handler, x_train, y_train, x_test, y_test, hyperparameters)
assert individual.get_fitness() is None
individual.evaluate_fitness()
assert individual.get_fitness() == 0.9
Expand All @@ -97,8 +106,9 @@ def test_send_to_queue():
genes = [Gene("gene1"), Gene("gene2")]
handler = MockHandler
x_train, y_train = [1, 2, 3], [4, 5, 6]
x_test, y_test = [6, 5, 4], [3, 2, 1]
hyperparameters = {"param1": 10, "param2": "value"}
individual = Individual(genes, handler, x_train, y_train, hyperparameters)
individual = Individual(genes, handler, x_train, y_train, x_test, y_test, hyperparameters)
server = MagicMock(spec=RedisController)
server.send_job.return_value = "job_id"
individual.send_to_queue(server)
Expand All @@ -110,8 +120,9 @@ def test_read_from_queue():
genes = [Gene("gene1"), Gene("gene2")]
handler = MockHandler
x_train, y_train = [1, 2, 3], [4, 5, 6]
x_test, y_test = [6, 5, 4], [3, 2, 1]
hyperparameters = {"param1": 10, "param2": "value"}
individual = Individual(genes, handler, x_train, y_train, hyperparameters)
individual = Individual(genes, handler, x_train, y_train, x_test, y_test, hyperparameters)
server = MagicMock(spec=RedisController)
server.wait_for_result.return_value = 0.9
individual.job_id = "job_id"
Expand All @@ -124,8 +135,9 @@ def test_getitem_setitem():
genes = [Gene("gene1"), Gene("gene2")]
handler = MockHandler
x_train, y_train = [1, 2, 3], [4, 5, 6]
x_test, y_test = [6, 5, 4], [3, 2, 1]
hyperparameters = {"param1": 10, "param2": "value"}
individual = Individual(genes, handler, x_train, y_train, hyperparameters)
individual = Individual(genes, handler, x_train, y_train, x_test, y_test, hyperparameters)
assert individual["param1"] == 10
individual["param1"] = 20
assert individual["param1"] == 20
Expand All @@ -136,10 +148,11 @@ def test_reproduce():
genes = [Gene("gene1"), Gene("gene2")]
handler = MockHandler
x_train, y_train = [1, 2, 3], [4, 5, 6]
x_test, y_test = [6, 5, 4], [3, 2, 1]
hyperparameters1 = {"param1": 10, "param2": "value1"}
hyperparameters2 = {"param1": 20, "param2": "value2"}
individual1 = Individual(genes, handler, x_train, y_train, hyperparameters1)
individual2 = Individual(genes, handler, x_train, y_train, hyperparameters2)
individual1 = Individual(genes, handler, x_train, y_train, x_test, y_test, hyperparameters1)
individual2 = Individual(genes, handler, x_train, y_train, x_test, y_test, hyperparameters2)
child = individual1.reproduce(individual2, rate=0.5)
assert isinstance(child, Individual)
assert child.handler == handler
Expand All @@ -152,10 +165,11 @@ def test_crossover():
genes = [Gene("gene1"), Gene("gene2")]
handler = MockHandler
x_train, y_train = [1, 2, 3], [4, 5, 6]
x_test, y_test = [6, 5, 4], [3, 2, 1]
hyperparameters1 = {"param1": 10, "param2": "value1"}
hyperparameters2 = {"param1": 20, "param2": "value2"}
individual1 = Individual(genes, handler, x_train, y_train, hyperparameters1)
individual2 = Individual(genes, handler, x_train, y_train, hyperparameters2)
individual1 = Individual(genes, handler, x_train, y_train, x_test, y_test, hyperparameters1)
individual2 = Individual(genes, handler, x_train, y_train, x_test, y_test, hyperparameters2)
individual1.crossover(individual2, rate=1.0)
assert individual1["param1"] == 20
assert individual1["param2"] == "value2"
Expand All @@ -169,8 +183,9 @@ def test_mutate():
genes = [gene1, gene2]
handler = MockHandler
x_train, y_train = [1, 2, 3], [4, 5, 6]
x_test, y_test = [6, 5, 4], [3, 2, 1]
hyperparameters = {"param1": 1, "param2": "4"}
individual = Individual(genes, handler, x_train, y_train, hyperparameters)
individual = Individual(genes, handler, x_train, y_train, x_test, y_test, hyperparameters)
individual.mutate(rate=1.0)
assert individual["param1"] in [1, 2, 3]
assert individual["param2"] in ["4", "5", "6"]
Expand All @@ -180,8 +195,9 @@ def test_duplicate():
genes = [Gene("gene1"), Gene("gene2")]
handler = MockHandler
x_train, y_train = [1, 2, 3], [4, 5, 6]
x_test, y_test = [6, 5, 4], [3, 2, 1]
hyperparameters = {"param1": 10, "param2": "value"}
individual = Individual(genes, handler, x_train, y_train, hyperparameters)
individual = Individual(genes, handler, x_train, y_train, x_test, y_test, hyperparameters)
duplicate = individual.duplicate()
assert isinstance(duplicate, Individual)
assert duplicate.genes == genes
Expand All @@ -196,6 +212,7 @@ def test_str():
genes = [Gene("gene1"), Gene("gene2")]
handler = MockHandler
x_train, y_train = [1, 2, 3], [4, 5, 6]
x_test, y_test = [6, 5, 4], [3, 2, 1]
hyperparameters = {"param1": 10, "param2": "value"}
individual = Individual(genes, handler, x_train, y_train, hyperparameters)
individual = Individual(genes, handler, x_train, y_train, x_test, y_test, hyperparameters)
assert str(individual) == pprint.pformat(hyperparameters)
58 changes: 58 additions & 0 deletions tests/test_models.py
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Original file line number Diff line number Diff line change
@@ -0,0 +1,58 @@
import numpy as np
import pytest

from src.gentun.models.base import Handler, KFoldCrossValidation


class MockModel(Handler):
def create_train_evaluate(self, x_train, y_train, x_test, y_test):
return np.mean(y_test) # Dummy evaluation metric


@pytest.fixture
def data():
x_train = np.random.rand(100, 10)
y_train = np.random.randint(0, 2, size=(100,))
return x_train, y_train


def test_initialization():
params = {"param1": 1, "param2": 2}
handler = Handler(**params)
assert handler.model_params == params


def test_evaluate_not_implemented():
handler = Handler()
with pytest.raises(NotImplementedError):
handler(None, None, None, None)


def test_kfold_cross_validation(data):
x_train, y_train = data
model = KFoldCrossValidation(folds=5, stratified=True, shuffle=True)
model.create_train_evaluate = MockModel().create_train_evaluate
metric = model(x_train, y_train)
assert isinstance(metric, float)
assert metric >= 0


def test_kfold_cross_validation_with_one_hot_labels(data):
x_train, y_train = data
y_train_one_hot = np.eye(2)[y_train] # Convert to one-hot encoding
model = KFoldCrossValidation(folds=5, stratified=True, shuffle=True)
model.create_train_evaluate = MockModel().create_train_evaluate
metric = model(x_train, y_train_one_hot)
assert isinstance(metric, float)
assert metric >= 0


def test_kfold_cross_validation_ignores_test_data(data):
x_train, y_train = data
x_test = np.random.rand(20, 10)
y_test = np.random.randint(0, 2, size=(20,))
model = KFoldCrossValidation(folds=5, stratified=True, shuffle=True)
model.create_train_evaluate = MockModel().create_train_evaluate
metric = model(x_train, y_train, x_test, y_test)
assert isinstance(metric, float)
assert metric >= 0
19 changes: 14 additions & 5 deletions tests/test_populations.py
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Original file line number Diff line number Diff line change
Expand Up @@ -14,7 +14,7 @@ def __init__(self, param1: int, param2: str = "default"):
self.param1 = param1
self.param2 = param2

def evaluate(self, x_train, y_train):
def create_train_evaluate(self, x_train, y_train, x_test, y_test):
return 0.9


Expand Down Expand Up @@ -83,7 +83,10 @@ def test_population_init_with_individuals():
genes = [MockIntGene("param1"), MockStrGene("param2")]
handler = MockHandler
x_train, y_train = [1, 2, 3], [4, 5, 6]
individuals = [Individual(genes, handler, x_train, y_train, {"param1": 1, "param2": "2"}) for _ in range(5)]
x_test, y_test = [6, 5, 4], [3, 2, 1]
individuals = [
Individual(genes, handler, x_train, y_train, x_test, y_test, {"param1": 1, "param2": "2"}) for _ in range(5)
]
population = Population(genes, handler, individuals, x_train, y_train)
assert len(population) == 5
assert all(isinstance(individual, Individual) for individual in population)
Expand Down Expand Up @@ -131,7 +134,10 @@ def test_population_get_fittest():
genes = [MockIntGene("param1"), MockStrGene("param2")]
handler = MockHandler
x_train, y_train = [1, 2, 3], [4, 5, 6]
individuals = [Individual(genes, handler, x_train, y_train, {"param1": 1, "param2": "2"}) for _ in range(5)]
x_test, y_test = [6, 5, 4], [3, 2, 1]
individuals = [
Individual(genes, handler, x_train, y_train, x_test, y_test, {"param1": 1, "param2": "2"}) for _ in range(5)
]
population = Population(genes, handler, individuals, x_train, y_train)
fittest = population.get_fittest()
assert isinstance(fittest, Individual)
Expand All @@ -145,8 +151,11 @@ def test_population_get_fittest_with_redis(mock_send_to_queue, mock_read_from_qu
handler = MockHandler
controller = RedisController("test")
x_train, y_train = [1, 2, 3], [4, 5, 6]
individuals = [Individual(genes, handler, x_train, y_train, {"param1": 1, "param2": "2"}) for _ in range(5)]
population = Population(genes, handler, individuals, x_train, y_train, controller=controller)
x_test, y_test = [6, 5, 4], [3, 2, 1]
individuals = [
Individual(genes, handler, x_train, y_train, x_test, y_test, {"param1": 1, "param2": "2"}) for _ in range(5)
]
population = Population(genes, handler, individuals, x_train, y_train, x_test, y_test, controller=controller)
fittest = population.get_fittest()
assert isinstance(fittest, Individual)
assert mock_send_to_queue.call_count == 5
Expand Down

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