import os
import matplotlib.pyplot as plt
import seaborn as sns
import pandas as pd
import numpy as np

class BacktestCharts:
    @staticmethod
    def plot(df, meta_trend):
        """
        Plot close price line chart with a bar at the bottom: green when trend is 1, red when trend is 0.
        The bar stays at the bottom even when zooming/panning.
        - df: DataFrame with columns ['close', ...] and a datetime index or 'timestamp' column.
        - meta_trend: array-like, same length as df, values 1 (green) or 0 (red).
        """
        fig, (ax_price, ax_bar) = plt.subplots(
            nrows=2, ncols=1, figsize=(16, 8), sharex=True,
            gridspec_kw={'height_ratios': [12, 1]}
        )

        sns.lineplot(x=df.index, y=df['close'], label='Close Price', color='blue', ax=ax_price)
        ax_price.set_title('Close Price with Trend Bar (Green=1, Red=0)')
        ax_price.set_ylabel('Price')
        ax_price.grid(True, alpha=0.3)
        ax_price.legend()

        # Clean meta_trend: ensure only 0/1, handle NaNs by forward-fill then fill remaining with 0
        meta_trend_arr = np.asarray(meta_trend)
        if not np.issubdtype(meta_trend_arr.dtype, np.number):
            meta_trend_arr = pd.Series(meta_trend_arr).astype(float).to_numpy()
        if np.isnan(meta_trend_arr).any():
            meta_trend_arr = pd.Series(meta_trend_arr).fillna(method='ffill').fillna(0).astype(int).to_numpy()
        else:
            meta_trend_arr = meta_trend_arr.astype(int)
        meta_trend_arr = np.where(meta_trend_arr != 1, 0, 1)  # force only 0 or 1
        if hasattr(df.index, 'to_numpy'):
            x_vals = df.index.to_numpy()
        else:
            x_vals = np.array(df.index)

        # Find contiguous regions
        regions = []
        start = 0
        for i in range(1, len(meta_trend_arr)):
            if meta_trend_arr[i] != meta_trend_arr[i-1]:
                regions.append((start, i-1, meta_trend_arr[i-1]))
                start = i
        regions.append((start, len(meta_trend_arr)-1, meta_trend_arr[-1]))

        # Draw red vertical lines at the start of each new region (except the first)
        for region_idx in range(1, len(regions)):
            region_start = regions[region_idx][0]
            ax_price.axvline(x=x_vals[region_start], color='black', linestyle='--', alpha=0.7, linewidth=1)

        for start, end, trend in regions:
            color = '#089981' if trend == 1 else '#F23645'
            # Offset by 1 on x: span from x_vals[start] to x_vals[end+1] if possible
            x_start = x_vals[start]
            x_end = x_vals[end+1] if end+1 < len(x_vals) else x_vals[end]
            ax_bar.axvspan(x_start, x_end, color=color, alpha=1, ymin=0, ymax=1)

        ax_bar.set_ylim(0, 1)
        ax_bar.set_yticks([])
        ax_bar.set_ylabel('Trend')
        ax_bar.set_xlabel('Time')
        ax_bar.grid(False)
        ax_bar.set_title('Meta Trend')

        plt.tight_layout(h_pad=0.1)
        plt.show()