plotter_comparison_1D_exact.py

import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
from matplotlib.patches import FancyBboxPatch
import os
import glob
import datetime
import yaml
from modules import (
    extract_parameters_by_file_name,
    save_plots_with_timestamp,
    list_csv_files_noFolder,
)


# Modern style configuration
plt.style.use("default")  # Reset to default style
plt.rcParams.update(
    {
        "figure.facecolor": "#FFFFFF",
        "axes.facecolor": "#F8F9FA",
        "axes.grid": True,
        "grid.color": "#E0E0E0",
        "grid.linestyle": "--",
        "grid.alpha": 0.7,
        "axes.spines.top": True,
        "axes.spines.right": True,
        "axes.spines.left": True,
        "axes.spines.bottom": True,
        "font.family": ["DejaVu Sans"],  # Use a font that supports subscripts
        "mathtext.fontset": "dejavusans",  # Ensure subscripts render correctly
    }
)


def select_file_by_number(csv_files, prompt):
    """Select a file by entering its number."""
    while True:
        try:
            choice = int(input(prompt))
            if 1 <= choice <= len(csv_files):
                return csv_files[choice - 1]
            else:
                print(f"Please enter a number between 1 and {len(csv_files)}")
        except ValueError:
            print("Please enter a valid number")


def find_first_difference(time_2d, z_2d, interpolated_z_1d, threshold):
    """Find the first point that exceeds the given threshold percentage."""
    percentage_difference = np.abs(z_2d - interpolated_z_1d) / np.abs(z_2d) * 100
    mask = percentage_difference > threshold
    if np.any(mask):
        first_exceed_index = np.where(mask)[0][0]
        return {
            "time": time_2d[first_exceed_index],
            "z_2d": z_2d[first_exceed_index],
            "z_1d": interpolated_z_1d[first_exceed_index],
            "difference": percentage_difference[first_exceed_index],
            "threshold": threshold,
        }
    return None


def create_fancy_annotation(fig, ax, xy, text, xytext):
    """Create a fancy annotation with custom styling."""
    bbox_props = dict(
        boxstyle="round,pad=0.5",
        fc="#FFFFFF",
        ec="#666666",
        alpha=0.9,
        mutation_scale=15,
    )

    arrow_props = dict(
        arrowstyle="fancy",
        color="#404040",
        connectionstyle="arc3,rad=-0.2",  # Changed from 0.2 to -0.2 for left-side arrow
        alpha=0.8,
        linewidth=1.5,
    )

    return ax.annotate(
        text,
        xy=xy,
        xytext=xytext,
        bbox=bbox_props,
        arrowprops=arrow_props,
        fontsize=9,
        ha="right",  # Changed from 'left' to 'right'
        va="center",
    )


def main():
    # Main execution
    csv_files = list_csv_files_noFolder()
    if len(csv_files) < 2:
        print("Error: Need at least 2 CSV files in the current directory")
        exit()

    file_2d = select_file_by_number(
        csv_files, "\nSelect the 2D data file (reference, enter number): "
    )
    file_1d = select_file_by_number(
        csv_files, "Select the 1D data file (comparison, enter number): "
    )

    print(f"\nSelected files:\n2D (reference): {file_2d}\n1D (comparison): {file_1d}")

    # Load and process data
    df_2d = pd.read_csv(file_2d)
    df_1d = pd.read_csv(file_1d)

    time_2d = df_2d["timestamp"]
    z_2d = df_2d["z"]
    time_1d = df_1d["timestamp"]
    z_1d = df_1d["z"]

    interpolated_z_1d = np.interp(time_2d, time_1d, z_1d)

    # Check for differences
    result = find_first_difference(time_2d, z_2d, interpolated_z_1d, 10)
    if result is None:
        result = find_first_difference(time_2d, z_2d, interpolated_z_1d, 1)

    # Create professional plot
    fig, ax = plt.subplots(figsize=(12, 7), dpi=100)

    # Plot data with professional color scheme
    ax.plot(
        time_2d,
        z_2d,
        label="2D Exact Z Solution (Reference)",
        color="#2E86C1",
        linewidth=2,
        alpha=0.8,
    )
    ax.plot(
        time_2d,
        interpolated_z_1d,
        label="1D Approximate Z Solution",
        color="#E67E22",
        linewidth=2,
        linestyle="--",
        alpha=0.8,
    )

    if result is not None:
        # Create fancy annotation
        annotation_text = (
            f"Error > {result['threshold']}% Difference\n"
            f"────────────────────\n"
            f"Time: {result['time']:.3f}\n"
            r"$Z_{2D}$" + f"(Exact): {result['z_2d']:.3f}\n"
            r"$Z_{1D}$" + f"(Approximated): {result['z_1d']:.3f}\n"
            f"Δ: {result['difference']:.2f}%"
        )

        create_fancy_annotation(
            fig,
            ax,
            xy=(result["time"], result["z_2d"]),
            text=annotation_text,
            xytext=(
                result["time"]
                - (time_2d.max() - time_2d.min()) * 0.1,  # Changed from + to -
                result["z_2d"] + (z_2d.max() - z_2d.min()) * 0.1,
            ),
        )

        # Add marker at the difference point
        ax.plot(
            result["time"],
            result["z_2d"],
            "o",
            color="#E74C3C",
            markersize=8,
            alpha=0.8,
        )

        title = f"Trajectory Comparison - Reduced 1D Equation vs Exact Solution"
    else:
        title = "Trajectory Comparison (No significant differences found)"

    # Enhance plot appearance
    ax.set_title(title, pad=20, fontsize=12, fontweight="bold")
    ax.set_xlabel(r"$\tau$", labelpad=10)
    ax.set_ylabel(r"$\tilde z$", labelpad=10)

    # Enhance legend
    ax.legend(
        loc="upper right",
        framealpha=0.95,
        edgecolor="#666666",
        fancybox=True,
        shadow=True,
    )

    # Add subtle box around the plot
    for spine in ax.spines.values():
        spine.set_color("#CCCCCC")
        spine.set_linewidth(0.8)

    # Define parameter mapping for latex symbols
    parameter_mapping = {
        "eps": r"$\epsilon$",
        "epsphi": r"$\epsilon_\phi$",
        "kappa": r"$\kappa$",
        "deltas": r"$\delta_s$",
        "beta": r"$\beta_0$",
        "alpha": r"$\alpha_0$",
        "theta": r"$\theta_0$",
        "time": r"$\tau$",
    }

    # Extract parameters from the 2D file name (reference file)
    parameters = extract_parameters_by_file_name(file_2d)

    # Create parameter text
    param_text = "\n".join(
        f"{parameter_mapping.get(key, key)}: {value}"
        for key, value in parameters.items()
    )

    # Add parameter text box
    ax.text(
        0.02,
        0.95,
        "Simulation Parameters:\n" + param_text,
        transform=ax.transAxes,
        fontsize=10,
        verticalalignment="top",
        bbox=dict(
            boxstyle="round,pad=0.5",
            facecolor="white",
            edgecolor="#CCCCCC",
            alpha=0.9,
            linewidth=0.5,
        ),
    )

    # Adjust layout
    plt.tight_layout()

    # Save the plots
    save_plots_with_timestamp(fig, "1D_2D_z_solutions_comparison")

    # Display the plot
    plt.show()


if __file__ == "__main__":
    main()