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How to use get_leaves method in avocado

Best Python code snippet using avocado_python

main_test.py

Source:main_test.py

...12    load_leaves,13    get_largest_magnitude_pair,14)15numbers_1 = load_snailfish_numbers([[[[[9, 8], 1], 2], 3], 4])16def test_get_leaves():17    assert get_leaves(numbers_1) == [18        RegularNumber(5, 9),19        RegularNumber(5, 8),20        RegularNumber(4, 1),21        RegularNumber(3, 2),22        RegularNumber(2, 3),23        RegularNumber(1, 4),24    ]25# def test_get_exploded_left():26#     assert get_exploded_value(numbers_1, is_right=False) == RegularNumber(9)27# def test_has_right_number_1():28#     assert has_regular_number(load_snailfish_numbers([0, 1]), 2, is_right=True) == True29# def test_has_right_number_2():30#     assert (31#         has_regular_number(load_snailfish_numbers([6, [5, [7, 0]]]), 2, is_right=True)32#         == False33#     )34def test_explode_1():35    assert explode(get_leaves(numbers_1)) == get_leaves(36        load_snailfish_numbers([[[[0, 9], 2], 3], 4])37    )38def test_explode_2():39    assert explode(40        get_leaves(load_snailfish_numbers([7, [6, [5, [4, [3, 2]]]]]))41    ) == get_leaves(load_snailfish_numbers([7, [6, [5, [7, 0]]]]))42def test_explode_3():43    assert explode(44        get_leaves(load_snailfish_numbers([[6, [5, [4, [3, 2]]]], 1]))45    ) == get_leaves(load_snailfish_numbers([[6, [5, [7, 0]]], 3]))46def test_explode_4():47    assert explode(48        get_leaves(49            load_snailfish_numbers([[3, [2, [1, [7, 3]]]], [6, [5, [4, [3, 2]]]]])50        )51    ) == get_leaves(load_snailfish_numbers([[3, [2, [8, 0]]], [9, [5, [4, [3, 2]]]]]))52def test_explode_5():53    assert explode(54        get_leaves(load_snailfish_numbers([[3, [2, [8, 0]]], [9, [5, [4, [3, 2]]]]]))55    ) == get_leaves(56        load_snailfish_numbers(57            [58                [3, [2, [8, 0]]],59                [9, [5, [7, 0]]],60            ]61        )62    )63def test_explode_6():64    assert explode(65        get_leaves(load_snailfish_numbers([[6, [5, [4, [3, 2]]]], [1, 2]]))66    ) == get_leaves(load_snailfish_numbers([[6, [5, [7, 0]]], [3, 2]]))67def test_split_1():68    assert split([RegularNumber(0, 10)]) == [RegularNumber(1, 5), RegularNumber(1, 5)]69def test_split_2():70    assert split([RegularNumber(0, 11)]) == [RegularNumber(1, 5), RegularNumber(1, 6)]71def test_split_3():72    assert split([RegularNumber(0, 12)]) == [RegularNumber(1, 6), RegularNumber(1, 6)]73def test_add():74    assert (75        add(76            get_leaves(load_snailfish_numbers([[[[4, 3], 4], 4], [7, [[8, 4], 9]]])),77            get_leaves(load_snailfish_numbers([1, 1])),78        )79        == get_leaves(load_snailfish_numbers([[[[0, 7], 4], [[7, 8], [6, 0]]], [8, 1]]))80    )81def test_reduce_1():82    input_str = "[1,1]\n[2,2]\n[3,3]\n[4,4]\n"83    assert add_file(input_str) == get_leaves(84        load_snailfish_numbers([[[[1, 1], [2, 2]], [3, 3]], [4, 4]])85    )86def test_reduce_2():87    input_str = "[1,1]\n[2,2]\n[3,3]\n[4,4]\n[5,5]\n"88    assert add_file(input_str) == get_leaves(89        load_snailfish_numbers([[[[3, 0], [5, 3]], [4, 4]], [5, 5]])90    )91def test_reduce_3():92    input_str = "[1,1]\n[2,2]\n[3,3]\n[4,4]\n[5,5]\n[6,6]\n"93    assert add_file(input_str) == get_leaves(94        load_snailfish_numbers([[[[5, 0], [7, 4]], [5, 5]], [6, 6]])95    )96def test_large_input():97    with open("test.txt") as input_file:98        input = input_file.read()99    assert add_file(input) == get_leaves(100        load_snailfish_numbers(101            [[[[8, 7], [7, 7]], [[8, 6], [7, 7]]], [[[0, 7], [6, 6]], [8, 7]]]102        )103    )104def test_magnitude_1():105    assert get_magnitude(Pair(0, RegularNumber(0, 9), RegularNumber(0, 1))) == 29106def test_magnitude_2():107    assert get_magnitude(Pair(0, RegularNumber(0, 1), RegularNumber(0, 9))) == 21108def test_magnitude_3():109    assert get_magnitude(load_snailfish_numbers([[1, 2], [[3, 4], 5]])) == 143110def test_magnitude_4():111    assert (112        get_magnitude(load_snailfish_numbers([[[[0, 7], 4], [[7, 8], [6, 0]]], [8, 1]]))113        == 1384114    )115def test_magnitude_5():116    assert (117        get_magnitude(load_snailfish_numbers([[[[1, 1], [2, 2]], [3, 3]], [4, 4]]))118        == 445119    )120def test_magnitude_6():121    assert (122        get_magnitude(load_snailfish_numbers([[[[3, 0], [5, 3]], [4, 4]], [5, 5]]))123        == 791124    )125def test_magnitude_7():126    assert (127        get_magnitude(load_snailfish_numbers([[[[5, 0], [7, 4]], [5, 5]], [6, 6]]))128        == 1137129    )130def test_magnitude_8():131    assert (132        get_magnitude(133            load_snailfish_numbers(134                [[[[8, 7], [7, 7]], [[8, 6], [7, 7]]], [[[0, 7], [6, 6]], [8, 7]]]135            )136        )137        == 3488138    )139def test_leaves_to_tree_1():140    tree = load_snailfish_numbers(141        [[[[6, 6], [7, 6]], [[7, 7], [7, 0]]], [[[7, 7], [7, 7]], [[7, 8], [9, 9]]]]142    )143    assert leaves_to_tree(get_leaves(tree)) == tree144def test_leaves_to_tree_2():145    tree = load_snailfish_numbers([[6, [5, [4, [3, 2]]]], [1, 2]])146    assert leaves_to_tree(get_leaves(tree)) == tree147def test_integration():148    with open("test2.txt") as input_file:149        input = input_file.read()150    file_add_out = add_file(input)151    assert file_add_out == get_leaves(152        load_snailfish_numbers(153            [[[[6, 6], [7, 6]], [[7, 7], [7, 0]]], [[[7, 7], [7, 7]], [[7, 8], [9, 9]]]]154        )155    )156    assert get_magnitude(leaves_to_tree(file_add_out)) == 4140157def test_get_largest_magnitude_pair():158    with open("test2.txt") as input_file:159        input = input_file.read()160    leaves = load_leaves(input)...

leaves.py

Source:leaves.py

...6from matplotlib.patches import Rectangle7import numpy as np8import subprocess9from common import ALGORITHM_EXAMPLES, RESULT_PATH10def get_leaves(points, algorithm, skewed=False, seed=None, heuristic=False):11    fn_args = locals()12    args = [13        str(ALGORITHM_EXAMPLES),14        "--algorithm", algorithm,15        "--points", str(points),16    ]17    if skewed:18        args.append("--skewed")19    if heuristic:20        args.append("--heuristic")21    if seed is not None:22        args.extend(["--seed", str(seed)])23    result = json.loads(subprocess.check_output(args).decode("utf-8"))24    print("seed for args {} is {}".format(fn_args, result["seed"]))25    return result["leaves"]26def draw_leaves(ax, title, leaves):27    ax.set_title(title)28    ax.set_xlabel("x")29    ax.set_ylabel("y")30    ax.set_xlim(0, 1)31    ax.set_ylim(0, 1)32    cmap = matplotlib.cm.get_cmap("gist_rainbow")33    colors = cmap(np.linspace(0, 1, len(leaves)))34    avg = sum(len(leaf["points"]) for leaf in leaves) / len(leaves)35    print(title, avg)36    for color, leaf in zip(colors, leaves):37        color[3] = 0.538        mbb = leaf["mbb"]39        x = mbb["min"]["x"]40        y = mbb["min"]["y"]41        width = mbb["max"]["x"] - x42        height = mbb["max"]["y"] - y43        ax.add_patch(Rectangle(xy=(x, y), width=width,44                               height=height, fill=True, facecolor=color, edgecolor="black"))45def save(fig, path):46    fig.tight_layout()47    fig.savefig(str(path), bbox_inches="tight")48def make_hilbert():49    fig, (ax1, ax2, ax3) = plt.subplots(1, 3, figsize=(12, 4))50    draw_leaves(ax1, "a)",51                get_leaves(1000, algorithm="hilbert", seed=1380799046))52    draw_leaves(ax2, "b)",53                get_leaves(1000, algorithm="hilbert",54                           skewed=True, seed=1821311943))55    draw_leaves(ax3, "c)",56                get_leaves(1000, algorithm="hilbert", skewed=True,57                           seed=1821311943, heuristic=True))58    return fig59def make_str():60    fig, (ax1, ax2) = plt.subplots(1, 2, figsize=(8, 4))61    draw_leaves(ax1, "a)",62                get_leaves(1000, algorithm="str", seed=1380799046))63    draw_leaves(ax2, "b)",64                get_leaves(1000, algorithm="str", skewed=True, seed=1821311943))65    return fig66def make_quickload():67    fig, [[ax1, ax2], [ax3, ax4]] = plt.subplots(2, 2, figsize=(8, 8))68    draw_leaves(ax1, "a)", get_leaves(69        1000, algorithm="obo", seed="1380799046"))70    draw_leaves(ax2, "b)", get_leaves(71        1000, algorithm="obo", skewed=True, seed=1821311943))72    draw_leaves(ax3, "c)", get_leaves(73        1000, algorithm="quickload", seed="1380799046"))74    draw_leaves(ax4, "d)", get_leaves(75        1000, algorithm="quickload", skewed=True, seed=1821311943))76    return fig77save(make_hilbert(), RESULT_PATH / "hilbert_leaves.pdf")78save(make_str(), RESULT_PATH / "str_leaves.pdf")...

leaf_similar_trees.py

Source:leaf_similar_trees.py

...10        :type root1: TreeNode11        :type root2: TreeNode12        :rtype: bool13        """14        return self.get_leaves(root1) == self.get_leaves(root2)15    16    def get_leaves(self, root):17        if root is None:18            return ()19        if root.left is None and root.right is None:20            return (root.val,)21        leaves = ()22        if root.left:23            leaves += self.get_leaves(root.left)24        if root.right:25            leaves += self.get_leaves(root.right)26        return leaves...

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