From de8ba0acdd46ca29a35e84dd53fe7284a34386b6 Mon Sep 17 00:00:00 2001
From: RektPunk <rektpunk@gmail.com>
Date: Wed, 11 Sep 2024 10:52:15 +0900
Subject: [PATCH] add test for encoder

---
 tests/test_encoder.py | 43 +++++++++++++++++++++++++++++++++++++++++++
 1 file changed, 43 insertions(+)
 create mode 100644 tests/test_encoder.py

diff --git a/tests/test_encoder.py b/tests/test_encoder.py
new file mode 100644
index 0000000..4ec5d86
--- /dev/null
+++ b/tests/test_encoder.py
@@ -0,0 +1,43 @@
+import numpy as np
+import pandas as pd
+import pytest
+
+from mqboost.base import XdataLike, YdataLike
+from mqboost.encoder import MQLabelEncoder
+
+
+# Test data for categorical variables
+@pytest.fixture
+def sample_data():
+    return pd.Series(["apple", "banana", "orange", None, "kiwi", np.nan])
+
+
+# Test data for label encoding
+@pytest.fixture
+def sample_label_data():
+    return np.array([2, 3, 5, 0, 4, 0])
+
+
+def test_fit_transform(sample_data):
+    encoder = MQLabelEncoder()
+    transformed = encoder.fit_transform(sample_data)
+
+    # Check that the transformed result is numeric
+    assert transformed is not None
+    assert transformed.dtype == int
+    assert len(transformed) == len(sample_data)
+
+
+def test_unseen_and_nan_values(sample_data):
+    encoder = MQLabelEncoder()
+    encoder.fit(sample_data)
+
+    # Include new unseen value and check behavior
+    test_data = pd.Series(["apple", "unknown", None, "melon", np.nan])
+    transformed = encoder.transform(test_data)
+
+    # Check for correct handling of unseen and NaN values
+    assert (
+        transformed
+        == encoder.label_encoder.transform(["apple", "Unseen", "NaN", "Unseen", "NaN"])
+    ).all()