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  • __copyright__ = """
    Copyright (C) 2022 University of Illinois Board of Trustees
    """
    
    __license__ = """
    Permission is hereby granted, free of charge, to any person obtaining a copy
    of this software and associated documentation files (the "Software"), to deal
    in the Software without restriction, including without limitation the rights
    to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
    copies of the Software, and to permit persons to whom the Software is
    furnished to do so, subject to the following conditions:
    
    The above copyright notice and this permission notice shall be included in
    all copies or substantial portions of the Software.
    
    THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
    IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
    FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
    AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
    LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
    OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
    THE SOFTWARE.
    """
    
    import numpy as np
    import numpy.linalg as la  # noqa
    
    from dataclasses import dataclass
    
    from grudge.array_context import PytestPyOpenCLArrayContextFactory
    from arraycontext import pytest_generate_tests_for_array_contexts
    pytest_generate_tests = pytest_generate_tests_for_array_contexts(
            [PytestPyOpenCLArrayContextFactory])
    
    from pytools.obj_array import make_obj_array
    
    import pytest
    
    import logging
    
    logger = logging.getLogger(__name__)
    
    
    # {{{ map_subarrays and rec_map_subarrays
    
    @dataclass(frozen=True, eq=True)
    class _DummyScalar:
        val: int
    
    
    def test_map_subarrays():
        """Test map_subarrays."""
        from grudge.tools import map_subarrays
    
        # Scalar
        result = map_subarrays(
            lambda x: np.array([x, 2*x]), (), (2,), 1)
        assert result.dtype == int
        assert np.all(result == np.array([1, 2]))
    
        # Scalar, nested
        result = map_subarrays(
            lambda x: np.array([x, 2*x]), (), (2,), 1, return_nested=True)
        assert result.dtype == int
        assert np.all(result == np.array([1, 2]))  # Same as non-nested
    
        # in_shape is whole array
        result = map_subarrays(
            lambda x: 2*x, (2,), (2,), np.array([1, 2]))
        assert result.dtype == int
        assert np.all(result == np.array([2, 4]))
    
        # in_shape is whole array, nested
        result = map_subarrays(
            lambda x: 2*x, (2,), (2,), np.array([1, 2]), return_nested=True)
        assert result.dtype == int
        assert np.all(result == np.array([2, 4]))  # Same as non-nested
    
        # len(out_shape) == 0
        result = map_subarrays(
            np.sum, (2,), (), np.array([[1, 2], [2, 4]]))
        assert result.dtype == int
        assert np.all(result == np.array([3, 6]))
    
        # len(out_shape) == 0, nested output
        result = map_subarrays(
            np.sum, (2,), (), np.array([[1, 2], [2, 4]]), return_nested=True)
        assert np.all(result == np.array([3, 6]))  # Same as non-nested output
    
        # len(out_shape) == 0, non-numerical scalars
        result = map_subarrays(
            lambda x: _DummyScalar(x[0].val + x[1].val), (2,), (),
            np.array([
                [_DummyScalar(1), _DummyScalar(2)],
                [_DummyScalar(2), _DummyScalar(4)]]))
        assert result.dtype == object
        assert result.shape == (2,)
        assert result[0] == _DummyScalar(3)
        assert result[1] == _DummyScalar(6)
    
        # len(out_shape) != 0
        result = map_subarrays(
            lambda x: np.array([x, 2*x]), (), (2,), np.array([1, 2]))
        assert result.dtype == int
        assert np.all(result == np.array([[1, 2], [2, 4]]))
    
        # len(out_shape) != 0, nested
        result = map_subarrays(
            lambda x: np.array([x, 2*x]), (), (2,), np.array([1, 2]), return_nested=True)
        assert result.dtype == object
        assert result.shape == (2,)
        assert np.all(result[0] == np.array([1, 2]))
        assert np.all(result[1] == np.array([2, 4]))
    
        # len(out_shape) != 0, non-numerical scalars
        result = map_subarrays(
            lambda x: np.array([_DummyScalar(x), _DummyScalar(2*x)]), (), (2,),
            np.array([1, 2]))
        assert result.dtype == object
        assert result.shape == (2, 2)
        assert np.all(result[0] == np.array([_DummyScalar(1), _DummyScalar(2)]))
        assert np.all(result[1] == np.array([_DummyScalar(2), _DummyScalar(4)]))
    
        # Zero-size input array
        result = map_subarrays(
            lambda x: np.array([x, 2*x]), (), (2,), np.empty((2, 0)))
        assert result.dtype == object
        assert result.shape == (2, 0, 2)
    
        # Zero-size input array, nested
        result = map_subarrays(
            lambda x: np.array([x, 2*x]), (), (2,), np.empty((2, 0)),
            return_nested=True)
        assert result.dtype == object
        assert result.shape == (2, 0)
    
    
    def test_rec_map_subarrays():
        """Test rec_map_subarrays."""
        from grudge.tools import rec_map_subarrays
    
        # Scalar
        result = rec_map_subarrays(
            lambda x: np.array([x, 2*x]), (), (2,), 1)
        assert result.dtype == int
        assert np.all(result == np.array([1, 2]))
    
        # Scalar, non-numerical
        result = rec_map_subarrays(
            lambda x: np.array([x.val, 2*x.val]), (), (2,), _DummyScalar(1),
            scalar_cls=_DummyScalar)
        assert result.dtype == int
        assert np.all(result == np.array([1, 2]))
    
        # Array of scalars
        result = rec_map_subarrays(
            np.sum, (2,), (), np.array([[1, 2], [2, 4]]))
        assert result.dtype == int
        assert np.all(result == np.array([3, 6]))
    
        # Array of scalars, non-numerical
        result = rec_map_subarrays(
            lambda x: x[0].val + x[1].val, (2,), (),
            np.array([
                [_DummyScalar(1), _DummyScalar(2)],
                [_DummyScalar(2), _DummyScalar(4)]]),
            scalar_cls=_DummyScalar)
        assert result.dtype == int
        assert np.all(result == np.array([3, 6]))
    
        # Array container
        result = rec_map_subarrays(
            np.sum, (2,), (), make_obj_array([np.array([1, 2]), np.array([2, 4])]))
        assert result.dtype == object
        assert result[0] == 3
        assert result[1] == 6
    
        # Array container, non-numerical scalars
        result = rec_map_subarrays(
            lambda x: x[0].val + x[1], (2,), (),
            make_obj_array([
                np.array([_DummyScalar(1), 2]),
                np.array([_DummyScalar(2), 4])]),
            scalar_cls=_DummyScalar)
        assert result.dtype == object
        assert result[0] == 3
        assert result[1] == 6
    
    # }}}
    
    
    # You can test individual routines by typing
    # $ python test_tools.py 'test_routine()'
    
    if __name__ == "__main__":
        import sys
        if len(sys.argv) > 1:
            exec(sys.argv[1])
        else:
            pytest.main([__file__])
    
    # vim: fdm=marker