import matplotlib.pyplot as plt
import seaborn as sns
import os

def create_correlation_heatmap(corr_data, session_id):
    plt.figure(figsize=(6, 4))

    sns.heatmap(corr_data, annot=False, cmap="coolwarm")

    file_path = f"{session_id}_correlation.png"
    plt.title("Correlation Heatmap")
    plt.savefig(file_path, bbox_inches="tight")
    plt.close()

    return file_path

def create_feature_importance_chart(feature_data, session_id):
    plt.figure(figsize=(6, 4))

    names = list(feature_data.keys())
    values = list(feature_data.values())

    plt.barh(names, values)
    plt.title("Top Features")

    file_path = f"{session_id}_features.png"
    plt.savefig(file_path, bbox_inches="tight")
    plt.close()

    return file_path

def create_cluster_chart(cluster_sizes, session_id):
    plt.figure(figsize=(6, 4))

    labels = list(cluster_sizes.keys())
    values = list(cluster_sizes.values())

    plt.bar(labels, values)
    plt.title("Cluster Distribution")

    file_path = f"{session_id}_clusters.png"
    plt.savefig(file_path, bbox_inches="tight")
    plt.close()

    return file_path