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linedance-app/venv/lib/python3.12/site-packages/numba/tests/test_casting.py

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+import numpy as np
+from numba.core.errors import TypingError
+from numba import njit
+from numba.core import types
+import struct
+import unittest
+
+
+def float_to_int(x):
+    return types.int32(x)
+
+
+def int_to_float(x):
+    return types.float64(x) / 2
+
+
+def float_to_unsigned(x):
+    return types.uint32(x)
+
+
+def float_to_complex(x):
+    return types.complex128(x)
+
+
+def numpy_scalar_cast_error():
+    np.int32(np.zeros((4,)))
+
+class TestCasting(unittest.TestCase):
+    def test_float_to_int(self):
+        pyfunc = float_to_int
+        cfunc = njit((types.float32,))(pyfunc)
+
+        self.assertEqual(cfunc.nopython_signatures[0].return_type, types.int32)
+        self.assertEqual(cfunc(12.3), pyfunc(12.3))
+        self.assertEqual(cfunc(12.3), int(12.3))
+        self.assertEqual(cfunc(-12.3), pyfunc(-12.3))
+        self.assertEqual(cfunc(-12.3), int(-12.3))
+
+    def test_int_to_float(self):
+        pyfunc = int_to_float
+        cfunc = njit((types.int64,))(pyfunc)
+
+        self.assertEqual(cfunc.nopython_signatures[0].return_type,
+                         types.float64)
+        self.assertEqual(cfunc(321), pyfunc(321))
+        self.assertEqual(cfunc(321), 321. / 2)
+
+    def test_float_to_unsigned(self):
+        pyfunc = float_to_unsigned
+        cfunc = njit((types.float32,))(pyfunc)
+
+        self.assertEqual(cfunc.nopython_signatures[0].return_type, types.uint32)
+        self.assertEqual(cfunc(3.21), pyfunc(3.21))
+        self.assertEqual(cfunc(3.21), struct.unpack('I', struct.pack('i',
+                                                                      3))[0])
+
+    def test_float_to_complex(self):
+        pyfunc = float_to_complex
+        cfunc = njit((types.float64,))(pyfunc)
+        self.assertEqual(cfunc.nopython_signatures[0].return_type,
+                         types.complex128)
+        self.assertEqual(cfunc(-3.21), pyfunc(-3.21))
+        self.assertEqual(cfunc(-3.21), -3.21 + 0j)
+
+    def test_array_to_array(self):
+        """Make sure this compiles.
+
+        Cast C to A array
+        """
+        @njit("f8(f8[:])")
+        def inner(x):
+            return x[0]
+
+        inner.disable_compile()
+
+        @njit("f8(f8[::1])")
+        def driver(x):
+            return inner(x)
+
+        x = np.array([1234], dtype=np.float64)
+        self.assertEqual(driver(x), x[0])
+        self.assertEqual(len(inner.overloads), 1)
+
+    def test_0darrayT_to_T(self):
+        @njit
+        def inner(x):
+            return x.dtype.type(x)
+
+        inputs = [
+            (np.bool_, True),
+            (np.float32, 12.3),
+            (np.float64, 12.3),
+            (np.int64, 12),
+            (np.complex64, 2j+3),
+            (np.complex128, 2j+3),
+            (np.timedelta64, np.timedelta64(3, 'h')),
+            (np.datetime64, np.datetime64('2016-01-01')),
+            ('<U3', 'ABC'),
+        ]
+
+        for (T, inp) in inputs:
+            x = np.array(inp, dtype=T)
+            self.assertEqual(inner(x), x[()])
+
+    def test_array_to_scalar(self):
+        """
+        Ensure that a TypingError exception is raised if
+        user tries to convert numpy array to scalar
+        """
+
+        with self.assertRaises(TypingError) as raises:
+            njit(())(numpy_scalar_cast_error)
+
+        self.assertIn("Casting array(float64, 1d, C) to int32 directly is unsupported.",
+                      str(raises.exception))
+
+    def test_optional_to_optional(self):
+        """
+        Test error due mishandling of Optional to Optional casting
+
+        Related issue: https://github.com/numba/numba/issues/1718
+        """
+        # Attempt to cast optional(intp) to optional(float64)
+        opt_int = types.Optional(types.intp)
+        opt_flt = types.Optional(types.float64)
+        sig = opt_flt(opt_int)
+
+        @njit(sig)
+        def foo(a):
+            return a
+
+        self.assertEqual(foo(2), 2)
+        self.assertIsNone(foo(None))
+
+
+if __name__ == '__main__':
+    unittest.main()