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