"""Tests for exponentially weighted moving operations.

Note: EWM operations are not yet implemented.
This file serves as a placeholder for future tests.
"""
import pytest
import pandas as pd
import numpy as np


class TestEWMMean:
    """Tests for ewm().mean()"""

    @pytest.mark.skip(reason="EWM operations not yet implemented")
    def test_basic_ewm_mean(self):
        """Test basic EWM mean matches pandas."""
        import unlockedpd

        df = pd.DataFrame(np.random.randn(100, 10))

        unlockedpd.config.enabled = False
        expected = df.ewm(span=10).mean()

        unlockedpd.config.enabled = True
        result = df.ewm(span=10).mean()

        pd.testing.assert_frame_equal(result, expected, rtol=1e-10)

    @pytest.mark.skip(reason="EWM operations not yet implemented")
    def test_ewm_mean_with_nan(self):
        """Test EWM mean handles NaN correctly."""
        import unlockedpd

        df = pd.DataFrame({
            'a': [1.0, np.nan, 3.0, 4.0, 5.0],
            'b': [np.nan, 2.0, 3.0, np.nan, 5.0]
        })

        unlockedpd.config.enabled = False
        expected = df.ewm(span=3).mean()

        unlockedpd.config.enabled = True
        result = df.ewm(span=3).mean()

        pd.testing.assert_frame_equal(result, expected, rtol=1e-10)

    @pytest.mark.skip(reason="EWM operations not yet implemented")
    def test_ewm_mean_halflife(self):
        """Test EWM mean with halflife parameter."""
        import unlockedpd

        df = pd.DataFrame(np.random.randn(100, 10))

        unlockedpd.config.enabled = False
        expected = df.ewm(halflife=10).mean()

        unlockedpd.config.enabled = True
        result = df.ewm(halflife=10).mean()

        pd.testing.assert_frame_equal(result, expected, rtol=1e-10)

    @pytest.mark.skip(reason="EWM operations not yet implemented")
    def test_ewm_mean_alpha(self):
        """Test EWM mean with alpha parameter."""
        import unlockedpd

        df = pd.DataFrame(np.random.randn(100, 10))

        unlockedpd.config.enabled = False
        expected = df.ewm(alpha=0.5).mean()

        unlockedpd.config.enabled = True
        result = df.ewm(alpha=0.5).mean()

        pd.testing.assert_frame_equal(result, expected, rtol=1e-10)


class TestEWMStd:
    """Tests for ewm().std()"""

    @pytest.mark.skip(reason="EWM operations not yet implemented")
    def test_basic_ewm_std(self):
        """Test basic EWM std matches pandas."""
        import unlockedpd

        df = pd.DataFrame(np.random.randn(100, 10))

        unlockedpd.config.enabled = False
        expected = df.ewm(span=10).std()

        unlockedpd.config.enabled = True
        result = df.ewm(span=10).std()

        pd.testing.assert_frame_equal(result, expected, rtol=1e-10)


class TestEWMVar:
    """Tests for ewm().var()"""

    @pytest.mark.skip(reason="EWM operations not yet implemented")
    def test_basic_ewm_var(self):
        """Test basic EWM var matches pandas."""
        import unlockedpd

        df = pd.DataFrame(np.random.randn(100, 10))

        unlockedpd.config.enabled = False
        expected = df.ewm(span=10).var()

        unlockedpd.config.enabled = True
        result = df.ewm(span=10).var()

        pd.testing.assert_frame_equal(result, expected, rtol=1e-10)
