"""
Tests for dsr_feature_eng_ml.models module.
"""
import pytest
import numpy as np
from sklearn.datasets import make_classification
from sklearn.model_selection import train_test_split
from dsr_feature_eng_ml import models


@pytest.fixture
def classification_data():
    """Create sample classification data for testing."""
    X, y = make_classification(n_samples=100, n_features=5, random_state=42)
    X_train, X_test, y_train, y_test = train_test_split(
        X, y, test_size=0.2, random_state=42
    )
    return {
        'X_train': X_train,
        'X_test': X_test,
        'y_train': y_train,
        'y_test': y_test,
    }


class TestModelsModule:
    """Test cases for models module."""

    def test_models_module_exists(self):
        """Verify that models module is importable."""
        assert models is not None

    def test_model_classes_exist(self):
        """Verify that expected model classes exist."""
        # Adjust based on your actual model classes
        assert hasattr(models, '__dict__')


class TestModelTraining:
    """Test cases for model training functionality."""

    def test_model_initialization(self):
        """Test model initialization."""
        # Add tests based on your specific model classes
        pass

    def test_model_fitting(self, classification_data):
        """Test model fitting with sample data."""
        # Add tests based on your training implementation
        X_train = classification_data['X_train']
        y_train = classification_data['y_train']
        assert len(X_train) == len(y_train)

    def test_model_prediction(self, classification_data):
        """Test model predictions."""
        # Add tests based on your prediction implementation
        X_test = classification_data['X_test']
        assert len(X_test) > 0
