import pickle
import unittest

import backend as F

import dgl
import dgl.ndarray as nd
import numpy as np
from dgl.frame import Column
from test_utils import parametrize_idtype


def test_column_subcolumn():
    data = F.copy_to(
        F.tensor(
            [
                [1.0, 1.0, 1.0, 1.0],
                [0.0, 2.0, 9.0, 0.0],
                [3.0, 2.0, 1.0, 0.0],
                [1.0, 1.0, 1.0, 1.0],
                [0.0, 2.0, 4.0, 0.0],
            ]
        ),
        F.ctx(),
    )
    original = Column(data)

    # subcolumn from cpu context
    i1 = F.tensor([0, 2, 1, 3], dtype=F.int64)
    l1 = original.subcolumn(i1)

    assert len(l1) == i1.shape[0]
    assert F.array_equal(l1.data, F.gather_row(data, i1))

    # next subcolumn from target context
    i2 = F.copy_to(F.tensor([0, 2], dtype=F.int64), F.ctx())
    l2 = l1.subcolumn(i2)

    assert len(l2) == i2.shape[0]
    i1i2 = F.copy_to(F.gather_row(i1, F.copy_to(i2, F.context(i1))), F.ctx())
    assert F.array_equal(l2.data, F.gather_row(data, i1i2))

    # next subcolumn also from target context
    i3 = F.copy_to(F.tensor([1], dtype=F.int64), F.ctx())
    l3 = l2.subcolumn(i3)

    assert len(l3) == i3.shape[0]
    i1i2i3 = F.copy_to(
        F.gather_row(i1i2, F.copy_to(i3, F.context(i1i2))), F.ctx()
    )
    assert F.array_equal(l3.data, F.gather_row(data, i1i2i3))


def test_serialize_deserialize_plain():
    data = F.copy_to(
        F.tensor(
            [
                [1.0, 1.0, 1.0, 1.0],
                [0.0, 2.0, 9.0, 0.0],
                [3.0, 2.0, 1.0, 0.0],
                [1.0, 1.0, 1.0, 1.0],
                [0.0, 2.0, 4.0, 0.0],
            ]
        ),
        F.ctx(),
    )
    original = Column(data)

    serial = pickle.dumps(original)
    new = pickle.loads(serial)
    print("new = {}".format(new))

    assert F.array_equal(new.data, original.data)


def test_serialize_deserialize_subcolumn():
    data = F.copy_to(
        F.tensor(
            [
                [1.0, 1.0, 1.0, 1.0],
                [0.0, 2.0, 9.0, 0.0],
                [3.0, 2.0, 1.0, 0.0],
                [1.0, 1.0, 1.0, 1.0],
                [0.0, 2.0, 4.0, 0.0],
            ]
        ),
        F.ctx(),
    )
    original = Column(data)

    # subcolumn from cpu context
    i1 = F.tensor([0, 2, 1, 3], dtype=F.int64)
    l1 = original.subcolumn(i1)

    serial = pickle.dumps(l1)
    new = pickle.loads(serial)

    assert F.array_equal(new.data, l1.data)


def test_serialize_deserialize_dtype():
    data = F.copy_to(
        F.tensor(
            [
                [1.0, 1.0, 1.0, 1.0],
                [0.0, 2.0, 9.0, 0.0],
                [3.0, 2.0, 1.0, 0.0],
                [1.0, 1.0, 1.0, 1.0],
                [0.0, 2.0, 4.0, 0.0],
            ]
        ),
        F.ctx(),
    )
    original = Column(data)
    original = original.astype(F.int64)

    serial = pickle.dumps(original)
    new = pickle.loads(serial)

    assert new.dtype == F.int64
