示例#1
0
def test_overlap_internal():
    x = np.arange(64).reshape((8, 8))
    d = da.from_array(x, chunks=(4, 4))

    g = overlap_internal(d, {0: 2, 1: 1})
    result = g.compute(scheduler="sync")
    assert g.chunks == ((6, 6), (5, 5))

    expected = np.array([
        [0, 1, 2, 3, 4, 3, 4, 5, 6, 7],
        [8, 9, 10, 11, 12, 11, 12, 13, 14, 15],
        [16, 17, 18, 19, 20, 19, 20, 21, 22, 23],
        [24, 25, 26, 27, 28, 27, 28, 29, 30, 31],
        [32, 33, 34, 35, 36, 35, 36, 37, 38, 39],
        [40, 41, 42, 43, 44, 43, 44, 45, 46, 47],
        [16, 17, 18, 19, 20, 19, 20, 21, 22, 23],
        [24, 25, 26, 27, 28, 27, 28, 29, 30, 31],
        [32, 33, 34, 35, 36, 35, 36, 37, 38, 39],
        [40, 41, 42, 43, 44, 43, 44, 45, 46, 47],
        [48, 49, 50, 51, 52, 51, 52, 53, 54, 55],
        [56, 57, 58, 59, 60, 59, 60, 61, 62, 63],
    ])

    assert_eq(result, expected)
    assert same_keys(overlap_internal(d, {0: 2, 1: 1}), g)
示例#2
0
def test_overlap_internal():
    x = np.arange(64).reshape((8, 8))
    d = da.from_array(x, chunks=(4, 4))

    g = overlap_internal(d, {0: 2, 1: 1})
    result = g.compute(scheduler='sync')
    assert g.chunks == ((6, 6), (5, 5))

    expected = np.array([
        [ 0,  1,  2,  3,  4,    3,  4,  5,  6,  7],
        [ 8,  9, 10, 11, 12,   11, 12, 13, 14, 15],
        [16, 17, 18, 19, 20,   19, 20, 21, 22, 23],
        [24, 25, 26, 27, 28,   27, 28, 29, 30, 31],
        [32, 33, 34, 35, 36,   35, 36, 37, 38, 39],
        [40, 41, 42, 43, 44,   43, 44, 45, 46, 47],

        [16, 17, 18, 19, 20,   19, 20, 21, 22, 23],
        [24, 25, 26, 27, 28,   27, 28, 29, 30, 31],
        [32, 33, 34, 35, 36,   35, 36, 37, 38, 39],
        [40, 41, 42, 43, 44,   43, 44, 45, 46, 47],
        [48, 49, 50, 51, 52,   51, 52, 53, 54, 55],
        [56, 57, 58, 59, 60,   59, 60, 61, 62, 63]])

    assert_eq(result, expected)
    assert same_keys(overlap_internal(d, {0: 2, 1: 1}), g)
示例#3
0
def test_overlap_internal_asymmetric_small():
    x = np.arange(32).reshape((2, 16))
    d = da.from_array(x, chunks=(2, 4))

    result = overlap_internal(d, {0: (0, 0), 1: (1, 1)})
    assert result.chunks == ((2, ), (5, 6, 6, 5))

    expected = np.array([[
        0, 1, 2, 3, 4, 3, 4, 5, 6, 7, 8, 7, 8, 9, 10, 11, 12, 11, 12, 13, 14,
        15
    ],
                         [
                             16, 17, 18, 19, 20, 19, 20, 21, 22, 23, 24, 23,
                             24, 25, 26, 27, 28, 27, 28, 29, 30, 31
                         ]])

    assert_eq(result, expected)
    assert same_keys(overlap_internal(d, {0: (0, 0), 1: (1, 1)}), result)
示例#4
0
def test_overlap_internal_asymmetric():
    x = np.arange(64).reshape((8, 8))
    d = da.from_array(x, chunks=(4, 4))

    result = overlap_internal(d, {0: (2, 0), 1: (1, 0)})
    assert result.chunks == ((6, 4), (5, 4))

    expected = np.array([[0, 1, 2, 3, 3, 4, 5, 6, 7],
                         [8, 9, 10, 11, 11, 12, 13, 14, 15],
                         [16, 17, 18, 19, 19, 20, 21, 22, 23],
                         [24, 25, 26, 27, 27, 28, 29, 30, 31],
                         [16, 17, 18, 19, 19, 20, 21, 22, 23],
                         [24, 25, 26, 27, 27, 28, 29, 30, 31],
                         [32, 33, 34, 35, 35, 36, 37, 38, 39],
                         [40, 41, 42, 43, 43, 44, 45, 46, 47],
                         [48, 49, 50, 51, 51, 52, 53, 54, 55],
                         [56, 57, 58, 59, 59, 60, 61, 62, 63]])
    assert_eq(result, expected)
    assert same_keys(overlap_internal(d, {0: (2, 0), 1: (1, 0)}), result)