import numpy as np

from numba.core.compiler import compile_isolated, DEFAULT_FLAGS
from numba.cuda.testing import SerialMixin
from numba import typeof, cuda, njit
from numba.core.types import float64
from numba.tests.support import MemoryLeakMixin, override_env_config
from numba.core import config
import unittest

BOUNDSCHECK_FLAGS = DEFAULT_FLAGS.copy()
BOUNDSCHECK_FLAGS.boundscheck = True


def basic_array_access(a):
    return a[10]


def slice_array_access(a):
    # The first index (slice) is not bounds checked
    return a[10:, 10]


def fancy_array_access(x):
    a = np.array([1, 2, 3])
    return x[a]


class TestBoundsCheckNoError(MemoryLeakMixin, unittest.TestCase):
    def setUp(self):
        self.old_boundscheck = config.BOUNDSCHECK
        config.BOUNDSCHECK = None

    def test_basic_array_boundscheck(self):
        a = np.arange(5)
        # Check the numpy behavior to make sure the test is correct
        with self.assertRaises(IndexError):
            # TODO: When we raise the same error message as numpy, test that
            # they are the same
            basic_array_access(a)

        at = typeof(a)
        c_noboundscheck = compile_isolated(basic_array_access, [at],
                                           flags=DEFAULT_FLAGS)
        noboundscheck = c_noboundscheck.entry_point
        # Check that the default flag doesn't raise
        noboundscheck(a)
        # boundscheck(a) is tested in TestBoundsCheckError below

    def test_slice_array_boundscheck(self):
        a = np.ones((5, 5))
        b = np.ones((5, 20))
        with self.assertRaises(IndexError):
            # TODO: When we raise the same error message as numpy, test that
            # they are the same
            slice_array_access(a)
        # Out of bounds on a slice doesn't raise
        slice_array_access(b)

        at = typeof(a)
        rt = float64[:]
        c_noboundscheck = compile_isolated(slice_array_access, [at],
                                           return_type=rt,
                                           flags=DEFAULT_FLAGS)
        noboundscheck = c_noboundscheck.entry_point
        c_boundscheck = compile_isolated(slice_array_access, [at],
                                         return_type=rt,
                                         flags=BOUNDSCHECK_FLAGS)
        boundscheck = c_boundscheck.entry_point
        # Check that the default flag doesn't raise
        noboundscheck(a)
        noboundscheck(b)
        # boundscheck(a) is tested in TestBoundsCheckError below

        # Doesn't raise
        boundscheck(b)

    def test_fancy_indexing_boundscheck(self):
        a = np.arange(3)
        b = np.arange(4)

        # Check the numpy behavior to ensure the test is correct.
        with self.assertRaises(IndexError):
            # TODO: When we raise the same error message as numpy, test that
            # they are the same
            fancy_array_access(a)
        fancy_array_access(b)

        at = typeof(a)
        rt = at.dtype[:]
        c_noboundscheck = compile_isolated(fancy_array_access, [at],
                                           return_type=rt,
                                           flags=DEFAULT_FLAGS)
        noboundscheck = c_noboundscheck.entry_point
        c_boundscheck = compile_isolated(fancy_array_access, [at],
                                         return_type=rt,
                                         flags=BOUNDSCHECK_FLAGS)
        boundscheck = c_boundscheck.entry_point
        # Check that the default flag doesn't raise
        noboundscheck(a)
        noboundscheck(b)
        # boundscheck(a) is tested in TestBoundsCheckError below

        # Doesn't raise
        boundscheck(b)

    def tearDown(self):
        config.BOUNDSCHECK = self.old_boundscheck


class TestNoCudaBoundsCheck(SerialMixin, unittest.TestCase):
    def setUp(self):
        self.old_boundscheck = config.BOUNDSCHECK
        config.BOUNDSCHECK = None

    @unittest.skipIf(not cuda.is_available(), "NO CUDA")
    def test_no_cuda_boundscheck(self):
        with self.assertRaises(NotImplementedError):
            @cuda.jit(boundscheck=True)
            def func():
                pass

        # Make sure we aren't raising "not supported" error if we aren't
        # requesting bounds checking anyway. Related pull request: #5257
        @cuda.jit(boundscheck=False)
        def func3():
            pass

        with override_env_config('NUMBA_BOUNDSCHECK', '1'):
            @cuda.jit
            def func2(x, a):
                a[1] = x[1]

            a = np.ones((1,))
            x = np.zeros((1,))
            # Out of bounds but doesn't raise (it does raise in the simulator,
            # so skip there)
            if not config.ENABLE_CUDASIM:
                func2[1, 1](x, a)

    def tearDown(self):
        config.BOUNDSCHECK = self.old_boundscheck


# This is a separate test because the jitted functions that raise exceptions
# have memory leaks.
class TestBoundsCheckError(unittest.TestCase):
    def setUp(self):
        self.old_boundscheck = config.BOUNDSCHECK
        config.BOUNDSCHECK = None

    def test_basic_array_boundscheck(self):
        a = np.arange(5)
        # Check the numpy behavior to make sure the test is correct
        with self.assertRaises(IndexError):
            # TODO: When we raise the same error message as numpy, test that
            # they are the same
            basic_array_access(a)

        at = typeof(a)
        c_boundscheck = compile_isolated(basic_array_access, [at],
                                         flags=BOUNDSCHECK_FLAGS)
        boundscheck = c_boundscheck.entry_point

        with self.assertRaises(IndexError):
            boundscheck(a)

    def test_slice_array_boundscheck(self):
        a = np.ones((5, 5))
        b = np.ones((5, 20))
        with self.assertRaises(IndexError):
            # TODO: When we raise the same error message as numpy, test that
            # they are the same
            slice_array_access(a)
        # Out of bounds on a slice doesn't raise
        slice_array_access(b)

        at = typeof(a)
        rt = float64[:]
        c_boundscheck = compile_isolated(slice_array_access, [at],
                                         return_type=rt,
                                         flags=BOUNDSCHECK_FLAGS)
        boundscheck = c_boundscheck.entry_point
        with self.assertRaises(IndexError):
            boundscheck(a)

    def test_fancy_indexing_boundscheck(self):
        a = np.arange(3)
        b = np.arange(4)

        # Check the numpy behavior to ensure the test is correct.
        with self.assertRaises(IndexError):
            # TODO: When we raise the same error message as numpy, test that
            # they are the same
            fancy_array_access(a)
        fancy_array_access(b)

        at = typeof(a)
        rt = at.dtype[:]
        c_boundscheck = compile_isolated(fancy_array_access, [at],
                                         return_type=rt,
                                         flags=BOUNDSCHECK_FLAGS)
        boundscheck = c_boundscheck.entry_point
        with self.assertRaises(IndexError):
            boundscheck(a)

    def tearDown(self):
        config.BOUNDSCHECK = self.old_boundscheck


class TestBoundsEnvironmentVariable(unittest.TestCase):
    def setUp(self):
        self.old_boundscheck = config.BOUNDSCHECK
        config.BOUNDSCHECK = None

        @njit
        def default(x):
            return x[1]

        @njit(boundscheck=False)
        def off(x):
            return x[1]

        @njit(boundscheck=True)
        def on(x):
            return x[1]

        self.default = default
        self.off = off
        self.on = on

    def test_boundscheck_unset(self):
        with override_env_config('NUMBA_BOUNDSCHECK', ''):
            a = np.array([1])

            # Doesn't raise
            self.default(a)
            self.off(a)

            with self.assertRaises(IndexError):
                self.on(a)

    def test_boundscheck_enabled(self):
        with override_env_config('NUMBA_BOUNDSCHECK', '1'):
            a = np.array([1])

            with self.assertRaises(IndexError):
                self.default(a)
                self.off(a)
                self.on(a)

    def test_boundscheck_disabled(self):
        with override_env_config('NUMBA_BOUNDSCHECK', '0'):
            a = np.array([1])

            # Doesn't raise
            self.default(a)
            self.off(a)
            self.on(a)

    def tearDown(self):
        config.BOUNDSCHECK = self.old_boundscheck


if __name__ == '__main__':
    unittest.main()
