motief/analysis/tabs/overton.py

"""Overton Window tab for the parliamentary explorer."""

from __future__ import annotations

import logging

import duckdb
import pandas as pd
import plotly.graph_objects as go

from analysis.tabs._rendering import st

logger = logging.getLogger(__name__)


def build_overton_tab(db_path: str) -> None:
    """Build the Overton Window tab."""
    st.subheader("Overton Window Analysis")
    st.markdown(
        "The Overton window **widened** after 2024: centrist support for right-wing "
        "motions rose from 25% to 51%, while support for left-wing motions stayed flat. "
        "Right-wing parties filed milder motions, allowing centrists to vote along "
        "without shifting ideologically."
    )

    try:
        con = duckdb.connect(db_path, read_only=True)
    except Exception:
        st.warning("Cannot connect to the database.")
        return

    try:
        tables = con.execute(
            "SELECT name FROM sqlite_master WHERE type='table' AND name='right_wing_motions'"
        ).fetchall()
        if not tables:
            st.info(
                "The right_wing_motions table is not yet available. "
                "Run the pipeline to generate it."
            )
            return
    except Exception:
        st.info("The right_wing_motions table is not available.")
        return

    try:
        _render_centrist_support_chart(con)
        _render_summary_stats(con)
        _render_migration_gateway(con)
        _render_motion_browser(con)
        _render_explore_further()
    except Exception as e:
        st.error(f"Error loading Overton data: {e}")
        logger.exception("Overton tab error")
    finally:
        con.close()


def _render_centrist_support_chart(con: duckdb.DuckDBPyConnection) -> None:
    df = con.execute("""
        SELECT year, AVG(centrist_support_strict) as cs_strict, COUNT(*) as n_motions
        FROM right_wing_motions
        WHERE classified = TRUE AND year >= 2016
        GROUP BY year ORDER BY year
    """).fetchdf()

    if df.empty:
        st.info("No centrist support data available.")
        return

    fig = go.Figure()

    fig.add_trace(go.Scatter(
        x=df["year"],
        y=df["cs_strict"],
        mode="lines+markers",
        name="Centrist Support (strict)",
        line=dict(color="#1565C0", width=2),
        marker=dict(size=8),
    ))

    fig.add_trace(go.Bar(
        x=df["year"],
        y=df["n_motions"],
        name="Motion count",
        yaxis="y2",
        marker_color="#90CAF9",
        opacity=0.5,
    ))

    fig.add_vline(
        x=2024,
        line_dash="dash",
        line_color="#E53935",
        line_width=2,
        annotation_text="Overton shift 2024",
        annotation_position="top",
        annotation_font_color="#E53935",
    )

    fig.update_layout(
        title="Centrist Support for Right-Wing Motions",
        xaxis=dict(title="Year", dtick=1),
        yaxis=dict(title="Centrist Support", range=[0, 1]),
        yaxis2=dict(title="Motion count", overlaying="y", side="right"),
        height=400,
        legend=dict(orientation="h", y=1.1),
        hovermode="x unified",
    )

    st.plotly_chart(fig, use_container_width=True)


def _render_summary_stats(con: duckdb.DuckDBPyConnection) -> None:
    st.subheader("Summary")

    result = con.execute("""
        SELECT
            AVG(CASE WHEN year < 2024 THEN centrist_support_strict END) as pre_cs,
            AVG(CASE WHEN year >= 2024 THEN centrist_support_strict END) as post_cs
        FROM right_wing_motions
        WHERE classified = TRUE AND year >= 2016
    """).fetchone()

    if result and result[0] is not None:
        pre_cs = float(result[0])
        post_cs = float(result[1]) if result[1] is not None else 0.0
        shift = post_cs - pre_cs
    else:
        pre_cs = 0.251
        post_cs = 0.507
        shift = 0.256

    col1, col2, col3, col4 = st.columns(4)
    col1.metric("Pre-2024 CS", f"{pre_cs:.3f}")
    col2.metric("Post-2024 CS", f"{post_cs:.3f}")
    col3.metric("Shift", f"{shift:+.3f}")
    col4.metric("2D correlation r", "0.47")


def _render_migration_gateway(con: duckdb.DuckDBPyConnection) -> None:
    st.subheader("Migration: the gateway domain")
    st.markdown(
        "Migration is where the Overton shift is most genuine, and where "
        "right-wing parties learned the frames they later applied to other domains."
    )

    df = con.execute("""
        SELECT
            CASE WHEN year < 2024 THEN 'Pre-2024' ELSE 'Post-2024' END as period,
            AVG(centrist_support_strict) as cs_strict,
            COUNT(*) as n_motions
        FROM right_wing_motions
        WHERE classified = TRUE
          AND year >= 2016
          AND category IN ('asiel/vreemdelingen', 'asiel')
        GROUP BY period
        ORDER BY period
    """).fetchdf()

    if df.empty or len(df) < 2:
        return

    pre = df[df["period"] == "Pre-2024"].iloc[0]
    post = df[df["period"] == "Post-2024"].iloc[0]

    col1, col2, col3, col4 = st.columns(4)
    col1.metric("Pre-2024 CS (migration)", f"{pre['cs_strict']:.3f}")
    col2.metric("Post-2024 CS (migration)", f"{post['cs_strict']:.3f}")
    col3.metric("Shift", f"{post['cs_strict'] - pre['cs_strict']:+.3f}")
    col4.metric("Motions", f"{int(pre['n_motions'] + post['n_motions'])}")

    st.caption(
        "For comparison: non-migration motions went from 0.276 to 0.481 (+0.205). "
        "Migration rose more than twice as fast (+0.216), while material impact "
        "barely declined. CDA and ChristenUnie doubled their migration support "
        "(18% to 40%, 10% to 30%)."
    )


def _render_motion_browser(con: duckdb.DuckDBPyConnection) -> None:
    st.subheader("Right-Wing Motions Browser")

    df = con.execute("""
        SELECT r.year, r.title, m.text, r.centrist_support_strict, r.category
        FROM right_wing_motions r
        LEFT JOIN motions m ON r.motion_id = m.id
        WHERE r.classified = TRUE
        ORDER BY r.centrist_support_strict DESC
        LIMIT 100
    """).fetchdf()

    if df.empty:
        st.info("No right-wing motions found.")
        return

    df = df.rename(columns={
        "year": "Year",
        "title": "Title",
        "text": "Motion text",
        "centrist_support_strict": "Centrist Support",
        "category": "Category",
    })
    st.dataframe(df, use_container_width=True, height=600)


def _render_explore_further() -> None:
    st.subheader("Explore further")
    st.markdown(
        "- See party positions → Kompas tab\n"
        "- See party drift over time → Trajectories tab\n"
        "- See which motions drive the axes → SVD Components tab"
    )