"""Tests for _build_party_axis_figure and load_party_mp_vectors in explorer.py."""

import numpy as np
import pytest


# ---------------------------------------------------------------------------
# Helpers
# ---------------------------------------------------------------------------


def _make_party_scores(n_parties=3, dim=50):
    """Return a minimal party_scores dict for testing."""
    rng = np.random.default_rng(0)
    names = [f"Party{i}" for i in range(n_parties)]
    return {name: rng.standard_normal(dim).tolist() for name in names}


def _make_theme(flip=False):
    return {
        "label": "Test axis",
        "explanation": "A test axis.",
        "positive_pole": "Left",
        "negative_pole": "Right",
        "flip": flip,
    }


def assert_figure_like(fig):
    """Minimal duck-typed assertion for a Figure-like object.

    The code under test (explorer.py) provides a small fallback Figure-like
    object when plotly is not installed. Tests should not import plotly
    directly; instead verify the returned object supports the minimal
    attributes used by the tests (.data as a list-like container).
    """
    assert hasattr(fig, "data"), "figure-like object must have .data"
    assert isinstance(fig.data, (list, tuple)), ".data must be a list-like container"


def _make_bootstrap_data(party_scores, dim=50):
    """Build synthetic bootstrap_data matching party_scores keys.

    Party0 gets n_mps=1 (single-MP party → diamond marker).
    Others get n_mps > 1 with a real CI spread.
    """
    rng = np.random.default_rng(1)
    result = {}
    for i, party in enumerate(party_scores):
        centroid = np.array(party_scores[party])
        if i == 0:
            # Single-MP party
            result[party] = {
                "centroid": centroid,
                "ci_lower": centroid.copy(),
                "ci_upper": centroid.copy(),
                "std": np.zeros(dim),
                "n_mps": 1,
            }
        else:
            spread = rng.uniform(0.01, 0.05, size=dim)
            result[party] = {
                "centroid": centroid,
                "ci_lower": centroid - spread,
                "ci_upper": centroid + spread,
                "std": spread / 2,
                "n_mps": 5 + i,
            }
    return result


# ---------------------------------------------------------------------------
# Tests
# ---------------------------------------------------------------------------


class TestBuildPartyAxisFigure:
    """Tests for _build_party_axis_figure (pure Plotly figure construction)."""

    def test_returns_figure_without_bootstrap(self):
        """Basic call without bootstrap → returns go.Figure with 2 traces."""
        from explorer import _build_party_axis_figure

        party_scores = _make_party_scores()
        theme = _make_theme()
        fig = _build_party_axis_figure(party_scores, comp_sel=1, theme=theme)

        assert isinstance(fig, go.Figure)
        assert len(fig.data) == 2  # baseline + markers
        # First trace is the baseline line
        assert fig.data[0].mode == "lines"
        # Second trace is the marker scatter
        assert "markers" in fig.data[1].mode

    def test_returns_none_for_empty_scores(self):
        """Empty party_scores returns None (no figure)."""
        from explorer import _build_party_axis_figure

        fig = _build_party_axis_figure({}, comp_sel=1, theme=_make_theme())
        assert fig is None

    def test_with_bootstrap_has_diamonds_for_single_mp(self):
        """bootstrap_data present → N=1 party gets diamond, others get circle. No error bars."""
        from explorer import _build_party_axis_figure

        party_scores = _make_party_scores()
        theme = _make_theme()
        bootstrap_data = _make_bootstrap_data(party_scores)
        fig = _build_party_axis_figure(
            party_scores,
            comp_sel=1,
            theme=theme,
            bootstrap_data=bootstrap_data,
        )

        assert isinstance(fig, go.Figure)
        assert len(fig.data) == 2

        marker_trace = fig.data[1]

        # No visual error bars — CIs are in hover text only
        assert (
            marker_trace.error_x.array is None
            or marker_trace.error_x.visible is not True
        )

        # Marker symbols: first party (N=1) → diamond, others → circle
        symbols = list(marker_trace.marker.symbol)
        assert symbols[0] == "diamond"
        assert all(s == "circle" for s in symbols[1:])

    def test_with_bootstrap_hover_includes_n_and_ci(self):
        """Hover text includes N=<count> and 95%-BI interval for each party."""
        from explorer import _build_party_axis_figure

        party_scores = _make_party_scores()
        theme = _make_theme()
        bootstrap_data = _make_bootstrap_data(party_scores)
        fig = _build_party_axis_figure(
            party_scores,
            comp_sel=1,
            theme=theme,
            bootstrap_data=bootstrap_data,
        )

        marker_trace = fig.data[1]
        for ht in marker_trace.hovertext:
            assert "(N=" in ht
            assert "95%-BI" in ht

    def test_flip_negates_scores(self):
        """When flip=True, scores are negated relative to flip=False."""
        from explorer import _build_party_axis_figure

        party_scores = _make_party_scores()
        theme_no_flip = _make_theme(flip=False)
        theme_flip = _make_theme(flip=True)
        bootstrap_data = _make_bootstrap_data(party_scores)

        fig_normal = _build_party_axis_figure(
            party_scores,
            comp_sel=1,
            theme=theme_no_flip,
            bootstrap_data=bootstrap_data,
        )
        fig_flipped = _build_party_axis_figure(
            party_scores,
            comp_sel=1,
            theme=theme_flip,
            bootstrap_data=bootstrap_data,
        )

        normal_scores = list(fig_normal.data[1].x)
        flipped_scores = list(fig_flipped.data[1].x)

        # Scores should be negated
        for ns, fs in zip(normal_scores, flipped_scores):
            assert pytest.approx(ns) == -fs

    def test_without_bootstrap_hover_is_score_only(self):
        """Without bootstrap data, hover text is just 'Party: score' with no CI."""
        from explorer import _build_party_axis_figure

        party_scores = _make_party_scores()
        fig = _build_party_axis_figure(party_scores, comp_sel=1, theme=_make_theme())

        marker_trace = fig.data[1]
        for ht in marker_trace.hovertext:
            assert "95%-BI" not in ht
            assert "(N=" not in ht


class TestLoadPartyMpVectorsImportable:
    """Smoke test: verify load_party_mp_vectors is importable."""

    def test_importable(self):
        from explorer import load_party_mp_vectors

        assert callable(load_party_mp_vectors)


def test_partial_party_traces():
    """Select trajectory plot helper returns a figure and includes raw hover data."""
    from explorer import select_trajectory_plot_data

    positions_by_window = {
        "w1": {"Alice": (0.1, 0.2), "Bob": (0.5, 0.6)},
        "w2": {
            "Bob": (0.6, 0.7)
        },  # Alice missing in w2 -> should create NaN for that window
    }
    party_map = {"Alice": "P1", "Bob": "P2"}
    windows = ["w1", "w2"]

    fig, trace_count, banner = select_trajectory_plot_data(
        positions_by_window,
        party_map,
        windows,
        selected_parties=["P1", "P2"],
        smooth_alpha=1.0,
    )
    assert_figure_like(fig)
    assert trace_count >= 1

    # At least one trace should include the hovertemplate with 'x (raw)'
    found = False
    for tr in fig.data:
        ht = getattr(tr, "hovertemplate", None)
        if ht and "x (raw)" in ht:
            found = True
            break
    assert found


def test_partial_party_traces():
    """Construct a minimal trajectories figure using partial centroids and ensure
    traces include customdata of same length and hovertemplate mentions raw values.
    """
    from explorer import select_trajectory_plot_data
    # Do not import plotly here; some test environments don't have it.
    # The module under test provides a minimal Figure-like fallback so
    # tests can run without plotly. Use duck-typing assertions instead.

    # Build synthetic centroids: two parties, each with coverage on different windows
    # select_trajectory_plot_data is expected to return a go.Figure
    positions_by_window = {
        "w1": {"A": (0.1, 0.2), "B": (np.nan, np.nan)},
        "w2": {"A": (0.15, 0.25), "B": (0.3, 0.4)},
    }
    party_map = {"A": "P1", "B": "P2"}
    windows = ["w1", "w2"]

    fig, trace_count, banner = select_trajectory_plot_data(
        positions_by_window,
        party_map,
        windows,
        selected_parties=["P1", "P2"],
        smooth_alpha=1.0,
    )
    assert_figure_like(fig)
    # There should be traces for parties even with partial coverage
    assert len(fig.data) >= 2

    for tr in fig.data:
        # customdata exists and matches x/y lengths when present
        x = list(tr.x) if hasattr(tr, "x") else []
        y = list(tr.y) if hasattr(tr, "y") else []
        cd = (
            list(tr.customdata)
            if hasattr(tr, "customdata") and tr.customdata is not None
            else []
        )
        # lengths match when customdata present
        if cd:
            assert len(cd) == len(x) == len(y)

        # hovertemplate should include raw marker fields like 'x (raw)'
        if hasattr(tr, "hovertemplate") and tr.hovertemplate:
            assert "x (raw)" in tr.hovertemplate