add kg_asarray test

tests/test_kg_asarray.py

@@ -0,0 +1,94 @@
+import unittest
+
+import numpy as np
+
+from klongpy.core import kg_asarray, KGChar, KGSym
+
+
+class TestKGAsArray(unittest.TestCase):
+
+    def test_kg_asarray_scalar_int(self):
+        x = 42
+        arr = kg_asarray(x)
+        assert np.isarray(arr)
+        assert arr.dtype == int
+        assert arr.shape == ()
+        assert arr.item() == 42
+
+    def test_kg_asarray_scalar_float(self):
+        x = 3.14
+        arr = kg_asarray(x)
+        assert np.isarray(arr)
+        assert arr.dtype == float
+        assert arr.item() == 3.14
+
+    def test_kg_asarray_empty_list(self):
+        x = []
+        arr = kg_asarray(x)
+        assert np.isarray(arr)
+        assert arr.dtype == float  # default dtype for empty list
+        assert arr.size == 0
+
+    def test_kg_asarray_string(self):
+        s = "hello"
+        arr = kg_asarray(s)
+        assert np.isarray(arr)
+        assert arr.dtype == object  # assuming KGChar is object dtype
+        assert "".join(arr) == "hello"
+
+    def test_kg_asarray_list_of_ints(self):
+        x = [1, 2, 3]
+        arr = kg_asarray(x)
+        assert np.isarray(arr)
+        assert arr.dtype == int
+        assert np.array_equal(arr, [1, 2, 3])
+
+    def test_kg_asarray_nested_list_uniform(self):
+        x = [[1, 2], [3, 4]]
+        arr = kg_asarray(x)
+        assert np.isarray(arr)
+        assert arr.shape == (2,2)
+        assert arr.dtype == int
+        assert np.array_equal(arr, [[1,2],[3,4]])
+
+    @unittest.skip("what is the expected behavior for this case?")
+    def test_kg_asarray_nested_list_heterogeneous(self):
+        # should embedded strings be expanded to individual characters?
+        x = [[1, 2], "abc", [3.14, None]]
+        arr = kg_asarray(x)
+        assert np.isarray(arr)
+        # Because of heterogeneous data, dtype should be object.
+        assert arr.dtype == object
+        # Check that sub-elements are arrays
+        assert np.isarray(arr[0])
+        assert np.isarray(arr[1])
+        assert np.isarray(arr[2])
+
+    def test_kg_asarray_already_array(self):
+        x = np.array([1, 2, 3])
+        arr = kg_asarray(x)
+        # Should return as-is because already suitable dtype
+        assert arr is x
+
+    def test_kg_asarray_jagged_list(self):
+        x = [[1, 2, 3], [4, 5], [6]]
+        arr = kg_asarray(x)
+        assert np.isarray(arr)
+        # Jagged => object dtype
+        assert arr.dtype == object
+        # Each element should be an array
+        assert all(np.isarray(e) for e in arr)
+        assert np.array_equal(arr[0], [1, 2, 3])
+        assert np.array_equal(arr[1], [4, 5])
+        assert np.array_equal(arr[2], [6])
+
+
+    def benchmark_kg_asarray(self):
+        import timeit
+        x = [[1, 2], [3, 4]]
+        print(timeit.timeit(lambda: kg_asarray(x), number=100_000))
+
+
+if __name__ == "__main__":
+    # run the benchmark
+    TestKGAsArray().benchmark_kg_asarray()