#!/usr/bin/env python3
"""
Visualize HR data from two CSV files with max value alignment
"""

import pandas as pd
import matplotlib.pyplot as plt
import numpy as np
from datetime import datetime, timedelta
import seaborn as sns


def load_and_visualize_hr_data():
    """Load and visualize HR data from both CSV files with max value alignment"""

    # Load the first CSV file (with timestamps)
    print("Loading 2025-06-10_16_26.CSV...")
    df1 = pd.read_csv("2025-06-10_16_26.CSV")
    print(f"Dataset 1 shape: {df1.shape}")
    print(f"Dataset 1 columns: {df1.columns.tolist()}")
    print(f"Dataset 1 HR range: {df1['hr'].min():.1f} - {df1['hr'].max():.1f}")

    # Load the second CSV file (HR only)
    print("\nLoading history_20250610_165414_HR.csv...")
    df2 = pd.read_csv("history_20250610_165414_HR.csv")
    print(f"Dataset 2 shape: {df2.shape}")
    print(f"Dataset 2 columns: {df2.columns.tolist()}")
    print(f"Dataset 2 HR range: {df2['HR'].min():.1f} - {df2['HR'].max():.1f}")

    # Find the maximum values and their indices
    max_hr1 = df1["hr"].max()
    max_idx1 = df1["hr"].idxmax()
    max_hr2 = df2["HR"].max()
    max_idx2 = df2["HR"].idxmax()

    print(f"\nDataset 1 max HR: {max_hr1:.1f} at index {max_idx1}")
    print(f"Dataset 2 max HR: {max_hr2:.1f} at index {max_idx2}")

    # Create time indices for both datasets
    df1["time_seconds"] = df1.index  # Use index as time in seconds
    df2["time_seconds"] = df2.index  # Use index as time in seconds

    # Align datasets by shifting so max values occur at the same time
    # We'll align both to time = 0 at their respective max points
    df1["time_aligned"] = df1["time_seconds"] - max_idx1
    df2["time_aligned"] = df2["time_seconds"] - max_idx2

    print(f"\nAfter alignment:")
    print(
        f"Dataset 1 time range: {df1['time_aligned'].min():.1f} to {df1['time_aligned'].max():.1f} seconds"
    )
    print(
        f"Dataset 2 time range: {df2['time_aligned'].min():.1f} to {df2['time_aligned'].max():.1f} seconds"
    )

    # Create the visualization
    plt.style.use("seaborn-v0_8")
    fig, axes = plt.subplots(2, 2, figsize=(15, 10))
    fig.suptitle(
        "Heart Rate Data Visualization (Max Values Aligned)",
        fontsize=16,
        fontweight="bold",
    )

    # Plot 1: Time series of both datasets (aligned)
    axes[0, 0].plot(
        df1["time_aligned"],
        df1["hr"],
        "o-",
        alpha=0.7,
        markersize=3,
        label=f"Dataset 1 (max: {max_hr1:.1f})",
        color="blue",
    )
    axes[0, 0].plot(
        df2["time_aligned"],
        df2["HR"],
        "s-",
        alpha=0.7,
        markersize=3,
        label=f"Dataset 2 (max: {max_hr2:.1f})",
        color="red",
    )

    # Highlight the max values
    axes[0, 0].axvline(
        x=0, color="black", linestyle="--", alpha=0.5, label="Max values aligned"
    )
    axes[0, 0].scatter([0], [max_hr1], color="blue", s=100, zorder=5, marker="*")
    axes[0, 0].scatter([0], [max_hr2], color="red", s=100, zorder=5, marker="*")

    axes[0, 0].set_xlabel("Time (seconds, aligned to max)")
    axes[0, 0].set_ylabel("Heart Rate (bpm)")
    axes[0, 0].set_title("Heart Rate Over Time (Aligned at Max Values)")
    axes[0, 0].legend()
    axes[0, 0].grid(True, alpha=0.3)

    # Plot 2: Distribution comparison
    axes[0, 1].hist(
        df1["hr"], bins=20, alpha=0.7, label="Dataset 1", color="blue", density=True
    )
    axes[0, 1].hist(
        df2["HR"], bins=20, alpha=0.7, label="Dataset 2", color="red", density=True
    )
    axes[0, 1].axvline(
        max_hr1, color="blue", linestyle="--", alpha=0.8, label=f"Max 1: {max_hr1:.1f}"
    )
    axes[0, 1].axvline(
        max_hr2, color="red", linestyle="--", alpha=0.8, label=f"Max 2: {max_hr2:.1f}"
    )
    axes[0, 1].set_xlabel("Heart Rate (bpm)")
    axes[0, 1].set_ylabel("Density")
    axes[0, 1].set_title("Heart Rate Distribution")
    axes[0, 1].legend()
    axes[0, 1].grid(True, alpha=0.3)

    # Plot 3: Box plot comparison
    data_for_box = [df1["hr"], df2["HR"]]
    labels = ["Dataset 1\n(2025-06-10_16_26)", "Dataset 2\n(history_20250610_165414)"]
    bp = axes[1, 0].boxplot(data_for_box, tick_labels=labels, patch_artist=True)
    bp["boxes"][0].set_facecolor("lightblue")
    bp["boxes"][1].set_facecolor("lightcoral")
    axes[1, 0].set_ylabel("Heart Rate (bpm)")
    axes[1, 0].set_title("Heart Rate Distribution Comparison")
    axes[1, 0].grid(True, alpha=0.3)

    # Plot 4: Overlay plot around max values (zoomed in view)
    # Show ±20 seconds around the aligned max values
    window = 20
    df1_window = df1[(df1["time_aligned"] >= -window) & (df1["time_aligned"] <= window)]
    df2_window = df2[(df2["time_aligned"] >= -window) & (df2["time_aligned"] <= window)]

    if len(df1_window) > 0:
        axes[1, 1].plot(
            df1_window["time_aligned"],
            df1_window["hr"],
            "o-",
            alpha=0.8,
            markersize=4,
            label=f"Dataset 1",
            color="blue",
            linewidth=2,
        )
    if len(df2_window) > 0:
        axes[1, 1].plot(
            df2_window["time_aligned"],
            df2_window["HR"],
            "s-",
            alpha=0.8,
            markersize=4,
            label=f"Dataset 2",
            color="red",
            linewidth=2,
        )

    axes[1, 1].axvline(
        x=0, color="black", linestyle="--", alpha=0.5, label="Max alignment"
    )
    axes[1, 1].scatter(
        [0], [max_hr1], color="blue", s=150, zorder=5, marker="*", edgecolor="black"
    )
    axes[1, 1].scatter(
        [0], [max_hr2], color="red", s=150, zorder=5, marker="*", edgecolor="black"
    )

    axes[1, 1].set_xlabel("Time (seconds, aligned to max)")
    axes[1, 1].set_ylabel("Heart Rate (bpm)")
    axes[1, 1].set_title(f"Zoomed View Around Max Values (±{window}s)")
    axes[1, 1].legend()
    axes[1, 1].grid(True, alpha=0.3)

    plt.tight_layout()

    # Save the plot
    output_file = "hr_data_visualization_aligned.png"
    plt.savefig(output_file, dpi=300, bbox_inches="tight")
    print(f"\nVisualization saved as: {output_file}")

    # Show the plot
    plt.show()

    # Print detailed statistics
    print("\n" + "=" * 60)
    print("DETAILED STATISTICS (MAX VALUES ALIGNED)")
    print("=" * 60)
    print("\nDataset 1 (2025-06-10_16_26.CSV):")
    print(f"  Records: {len(df1)}")
    print(f"  Mean HR: {df1['hr'].mean():.1f} bpm")
    print(f"  Median HR: {df1['hr'].median():.1f} bpm")
    print(f"  Max HR: {max_hr1:.1f} bpm (at original index {max_idx1})")
    print(f"  Std Dev: {df1['hr'].std():.1f} bpm")
    print(f"  Range: {df1['hr'].min():.1f} - {df1['hr'].max():.1f} bpm")

    print("\nDataset 2 (history_20250610_165414_HR.csv):")
    print(f"  Records: {len(df2)}")
    print(f"  Mean HR: {df2['HR'].mean():.1f} bpm")
    print(f"  Median HR: {df2['HR'].median():.1f} bpm")
    print(f"  Max HR: {max_hr2:.1f} bpm (at original index {max_idx2})")
    print(f"  Std Dev: {df2['HR'].std():.1f} bpm")
    print(f"  Range: {df2['HR'].min():.1f} - {df2['HR'].max():.1f} bpm")

    print(f"\nAlignment Info:")
    print(f"  Max HR difference: {abs(max_hr1 - max_hr2):.1f} bpm")
    print(
        f"  Time shift applied: Dataset 1 shifted by -{max_idx1}s, Dataset 2 shifted by -{max_idx2}s"
    )

    print("\n" + "=" * 60)

    return df1, df2


if __name__ == "__main__":
    print("Starting HR data visualization with max value alignment...")
    df1, df2 = load_and_visualize_hr_data()
    print("Visualization complete!")