import operator

import numpy as np
import pytest

from pandas import DataFrame, Index, Series
import pandas._testing as tm


class TestMatMul:
    def test_matmul(self):
        # matmul test is for GH#10259
        a = DataFrame(
            np.random.randn(3, 4), index=["a", "b", "c"], columns=["p", "q", "r", "s"]
        )
        b = DataFrame(
            np.random.randn(4, 2), index=["p", "q", "r", "s"], columns=["one", "two"]
        )

        # DataFrame @ DataFrame
        result = operator.matmul(a, b)
        expected = DataFrame(
            np.dot(a.values, b.values), index=["a", "b", "c"], columns=["one", "two"]
        )
        tm.assert_frame_equal(result, expected)

        # DataFrame @ Series
        result = operator.matmul(a, b.one)
        expected = Series(np.dot(a.values, b.one.values), index=["a", "b", "c"])
        tm.assert_series_equal(result, expected)

        # np.array @ DataFrame
        result = operator.matmul(a.values, b)
        assert isinstance(result, DataFrame)
        assert result.columns.equals(b.columns)
        assert result.index.equals(Index(range(3)))
        expected = np.dot(a.values, b.values)
        tm.assert_almost_equal(result.values, expected)

        # nested list @ DataFrame (__rmatmul__)
        result = operator.matmul(a.values.tolist(), b)
        expected = DataFrame(
            np.dot(a.values, b.values), index=["a", "b", "c"], columns=["one", "two"]
        )
        tm.assert_almost_equal(result.values, expected.values)

        # mixed dtype DataFrame @ DataFrame
        a["q"] = a.q.round().astype(int)
        result = operator.matmul(a, b)
        expected = DataFrame(
            np.dot(a.values, b.values), index=["a", "b", "c"], columns=["one", "two"]
        )
        tm.assert_frame_equal(result, expected)

        # different dtypes DataFrame @ DataFrame
        a = a.astype(int)
        result = operator.matmul(a, b)
        expected = DataFrame(
            np.dot(a.values, b.values), index=["a", "b", "c"], columns=["one", "two"]
        )
        tm.assert_frame_equal(result, expected)

        # unaligned
        df = DataFrame(np.random.randn(3, 4), index=[1, 2, 3], columns=range(4))
        df2 = DataFrame(np.random.randn(5, 3), index=range(5), columns=[1, 2, 3])

        with pytest.raises(ValueError, match="aligned"):
            operator.matmul(df, df2)

    def test_matmul_message_shapes(self):
        # GH#21581 exception message should reflect original shapes,
        #  not transposed shapes
        a = np.random.rand(10, 4)
        b = np.random.rand(5, 3)

        df = DataFrame(b)

        msg = r"shapes \(10, 4\) and \(5, 3\) not aligned"
        with pytest.raises(ValueError, match=msg):
            a @ df
        with pytest.raises(ValueError, match=msg):
            a.tolist() @ df