# Advanced demo: Seaborn heatmap with clustering, annotations, and custom color map for AI correlations
import seaborn as sns
import matplotlib.pyplot as plt
import pandas as pd
import numpy as np

def advanced_heatmap(data):
    df = pd.DataFrame(data)
    corr = df.corr()
    plt.figure(figsize=(8, 6))
    sns.heatmap(corr, annot=True, cmap="coolwarm", fmt=".2f", vmin=-1, vmax=1, square=True, cbar_kws={"shrink": .75})
    plt.title("AI Correlation Heatmap", fontsize=16)
    plt.xticks(rotation=45)
    plt.yticks(rotation=0)
    plt.annotate("Strong Correlation", xy=(1.5, 0.5), xytext=(2.5, 1.5), arrowprops=dict(facecolor='black', shrink=0.05))
    plt.show()

# Generate complex AI correlation data
np.random.seed(42)
data = np.random.rand(4, 4)
df = pd.DataFrame(data, columns=["Feature1", "Feature2", "Feature3", "Feature4"])
advanced_heatmap(df)