added additional tests

tests/test_model_utils/test_binary_ks_curve.py

@@ -0,0 +1,104 @@
+import pytest
+import numpy as np
+from dython.model_utils import _binary_ks_curve
+
+
+def test_binary_ks_curve_basic():
+    """Test basic binary_ks_curve functionality"""
+    y_true = np.array([0, 1, 0, 1, 1, 0])
+    y_probas = np.array([0.1, 0.9, 0.3, 0.8, 0.7, 0.2])
+
+    thresholds, pct1, pct2, ks_stat, max_dist, classes = _binary_ks_curve(y_true, y_probas)
+
+    assert len(thresholds) > 0
+    assert len(pct1) == len(thresholds)
+    assert len(pct2) == len(thresholds)
+    assert 0 <= ks_stat <= 1
+    assert len(classes) == 2
+
+
+def test_binary_ks_curve_multiclass_error():
+    """Test binary_ks_curve with more than 2 classes"""
+    y_true = np.array([0, 1, 2, 0, 1, 2])
+    y_probas = np.array([0.1, 0.5, 0.9, 0.2, 0.6, 0.8])
+
+    with pytest.raises(ValueError):
+        _binary_ks_curve(y_true, y_probas)
+
+
+def test_binary_ks_curve_thresholds_start_with_zero():
+    """Test that thresholds start with 0"""
+    y_true = np.array([0, 1, 0, 1])
+    y_probas = np.array([0.2, 0.8, 0.3, 0.9])
+
+    thresholds, _, _, _, _, _ = _binary_ks_curve(y_true, y_probas)
+
+    assert thresholds[0] == 0.0
+
+
+def test_binary_ks_curve_thresholds_end_with_one():
+    """Test that thresholds end with 1"""
+    y_true = np.array([0, 1, 0, 1])
+    y_probas = np.array([0.2, 0.8, 0.3, 0.7])
+
+    thresholds, _, _, _, _, _ = _binary_ks_curve(y_true, y_probas)
+
+    assert thresholds[-1] == 1.0
+
+
+def test_binary_ks_curve_with_edge_probabilities():
+    """Test binary_ks_curve with probabilities at 0 and 1"""
+    y_true = np.array([0, 1, 0, 1])
+    y_probas = np.array([0.0, 1.0, 0.1, 0.9])
+
+    thresholds, pct1, pct2, ks_stat, max_dist, _ = _binary_ks_curve(y_true, y_probas)
+
+    assert len(thresholds) > 0
+    assert thresholds[0] == 0.0
+    assert thresholds[-1] == 1.0
+
+
+def test_binary_ks_curve_data1_exhausted_first():
+    """Test binary_ks_curve when data1 is exhausted before data2"""
+    y_true = np.array([0, 0, 1, 1, 1])
+    y_probas = np.array([0.1, 0.2, 0.6, 0.7, 0.8])
+
+    thresholds, pct1, pct2, ks_stat, max_dist, _ = _binary_ks_curve(y_true, y_probas)
+
+    assert len(thresholds) > 0
+    assert pct1[-1] == 1.0
+    assert pct2[-1] == 1.0
+
+
+def test_binary_ks_curve_data2_exhausted_first():
+    """Test binary_ks_curve when data2 is exhausted before data1"""
+    y_true = np.array([0, 0, 0, 1, 1])
+    y_probas = np.array([0.6, 0.7, 0.8, 0.1, 0.2])
+
+    thresholds, pct1, pct2, ks_stat, max_dist, _ = _binary_ks_curve(y_true, y_probas)
+
+    assert len(thresholds) > 0
+    assert pct1[-1] == 1.0
+    assert pct2[-1] == 1.0
+
+
+def test_binary_ks_curve_equal_values():
+    """Test binary_ks_curve with equal probability values"""
+    y_true = np.array([0, 0, 1, 1])
+    y_probas = np.array([0.5, 0.5, 0.5, 0.5])
+
+    thresholds, pct1, pct2, ks_stat, max_dist, _ = _binary_ks_curve(y_true, y_probas)
+
+    assert len(thresholds) > 0
+
+
+def test_binary_ks_curve_interleaved_values():
+    """Test binary_ks_curve with interleaved probability values"""
+    y_true = np.array([0, 1, 0, 1, 0, 1])
+    y_probas = np.array([0.1, 0.2, 0.3, 0.4, 0.5, 0.6])
+
+    thresholds, pct1, pct2, ks_stat, max_dist, _ = _binary_ks_curve(y_true, y_probas)
+
+    assert len(thresholds) > 0
+    assert 0 <= ks_stat <= 1
+

tests/test_model_utils/test_ks_abc_advanced.py

@@ -0,0 +1,121 @@
+import pytest
+import numpy as np
+import matplotlib.pyplot as plt
+from dython.model_utils import ks_abc
+
+
+def test_ks_abc_basic():
+    """Test basic ks_abc functionality"""
+    y_true = [0, 1, 0, 1, 1, 0]
+    y_pred = [0.1, 0.9, 0.3, 0.8, 0.7, 0.2]
+
+    result = ks_abc(y_true, y_pred, plot=False)
+    assert 'abc' in result
+    assert 'ks_stat' in result
+    assert 'eopt' in result
+    assert 'ax' in result
+
+
+def test_ks_abc_mismatched_shapes():
+    """Test ks_abc with mismatched shapes"""
+    y_true = [0, 1, 0]
+    y_pred = [0.1, 0.9, 0.3, 0.8]
+
+    with pytest.raises(ValueError):
+        ks_abc(y_true, y_pred, plot=False)
+
+
+def test_ks_abc_2d_binary():
+    """Test ks_abc with 2D binary array"""
+    y_true = np.array([[1, 0], [0, 1], [1, 0], [0, 1]])
+    y_pred = np.array([[0.7, 0.3], [0.2, 0.8], [0.6, 0.4], [0.3, 0.7]])
+
+    result = ks_abc(y_true, y_pred, plot=False)
+    assert 'abc' in result
+
+
+def test_ks_abc_single_column():
+    """Test ks_abc with single column"""
+    y_true = np.array([[1], [0], [1], [0]])
+    y_pred = np.array([[0.9], [0.2], [0.7], [0.3]])
+
+    result = ks_abc(y_true, y_pred, plot=False)
+    assert 'abc' in result
+
+
+def test_ks_abc_multiclass_error():
+    """Test ks_abc with multiclass (should raise error)"""
+    y_true = np.array([[1, 0, 0], [0, 1, 0], [0, 0, 1]])
+    y_pred = np.array([[0.7, 0.2, 0.1], [0.1, 0.8, 0.1], [0.2, 0.1, 0.7]])
+
+    with pytest.raises(ValueError):
+        ks_abc(y_true, y_pred, plot=False)
+
+
+def test_ks_abc_with_ax():
+    """Test ks_abc with provided ax"""
+    y_true = [0, 1, 0, 1]
+    y_pred = [0.1, 0.9, 0.3, 0.8]
+
+    fig, ax = plt.subplots()
+    result = ks_abc(y_true, y_pred, ax=ax, plot=False)
+    assert result['ax'] == ax
+    plt.close(fig)
+
+
+def test_ks_abc_with_custom_params():
+    """Test ks_abc with custom visualization parameters"""
+    y_true = [0, 1, 0, 1, 1, 0]
+    y_pred = [0.1, 0.9, 0.3, 0.8, 0.7, 0.2]
+
+    result = ks_abc(
+        y_true, y_pred,
+        colors=('red', 'blue'),
+        title='Custom KS Title',
+        xlim=(0, 0.5),
+        ylim=(0, 0.5),
+        fmt='.3f',
+        lw=3,
+        legend='upper left',
+        plot=False
+    )
+    assert 'abc' in result
+
+
+def test_ks_abc_no_legend():
+    """Test ks_abc without legend"""
+    y_true = [0, 1, 0, 1]
+    y_pred = [0.1, 0.9, 0.3, 0.8]
+
+    result = ks_abc(y_true, y_pred, legend=None, plot=False)
+    assert 'ax' in result
+
+
+def test_ks_abc_with_filename(tmp_path):
+    """Test ks_abc with filename"""
+    y_true = [0, 1, 0, 1]
+    y_pred = [0.1, 0.9, 0.3, 0.8]
+
+    filename = tmp_path / "ks_plot.png"
+    result = ks_abc(y_true, y_pred, filename=str(filename), plot=False)
+    assert filename.exists()
+    plt.close('all')
+
+
+def test_ks_abc_abc_value_range():
+    """Test that ABC value is in valid range"""
+    y_true = [0, 1, 0, 1, 1, 0, 0, 1]
+    y_pred = [0.1, 0.9, 0.2, 0.8, 0.7, 0.3, 0.15, 0.85]
+
+    result = ks_abc(y_true, y_pred, plot=False)
+    assert 0 <= result['abc'] <= 1
+
+
+def test_ks_abc_ks_stat_value_range():
+    """Test that KS statistic is in valid range"""
+    y_true = [0, 1, 0, 1, 1, 0, 0, 1]
+    y_pred = [0.1, 0.9, 0.2, 0.8, 0.7, 0.3, 0.15, 0.85]
+
+    result = ks_abc(y_true, y_pred, plot=False)
+    assert 0 <= result['ks_stat'] <= 1
+