src/visualizer.py - master - desmitry/market-data-analysis

src/visualizer.py
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desmitry
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25 ноя 2025, 09:14
25 ноя 2025, 09:14c2a71d5
import matplotlib.pyplot as plt
import numpy as np
from matplotlib.ticker import FuncFormatter, MultipleLocator
from scipy.stats import gaussian_kde

def plot_weekday_analysis(df, symbol):
    """Generates the KDE plot for weekdays (from your notebook)."""
    weekdays = ("Monday", "Tuesday", "Wednesday", "Thursday", "Friday")
    plt.style.use("dark_background")
    
    fig = plt.figure(figsize=(20, 15))
    
    for weekday in range(5):
        data = df.loc[df.index.weekday == weekday]
        high_data = data["High Return"]
        low_data = np.abs(data["Low Return"])
        
        # Create subplots dynamically
        ax_high = plt.subplot2grid(shape=(5, 2), loc=(weekday, 0))
        ax_low = plt.subplot2grid(shape=(5, 2), loc=(weekday, 1))
        
        for name, ax, returns in zip(["High", "Low"], [ax_high, ax_low], [high_data, low_data]):
            _setup_axis(ax)
            
            # Plot KDE
            positive_vals = [i for i in returns if i > 0]
            if len(positive_vals) > 5:
                p_zero = (len(returns) - len(positive_vals)) / len(returns)
                log_vals = np.log(positive_vals)
                kde = gaussian_kde(log_vals, bw_method="scott")
                
                support = np.linspace(1e-5, returns.max(), 1000)
                log_support = np.log(support)
                cdf = np.array([kde.integrate_box_1d(-np.inf, x) for x in log_support])
                combined_cdf = p_zero + (1 - p_zero) * cdf
                
                # Plot CDF
                full_x = np.concatenate([[0], support])
                full_y = np.concatenate([[p_zero], combined_cdf])
                ax.plot(full_x, full_y, color="cyan")

            mean = np.mean(returns)
            std = np.std(returns)
            
            ax.axvline(mean, color="blue", linestyle=":", label="Mean")
            ax.axvline(mean + std, color="green", linestyle=":", label="1 Std")
            ax.set_title(f"{symbol} {weekdays[weekday]} {name} CDF")

    plt.tight_layout()
    plt.savefig("weekday_analysis.png")
    print("Analysis saved to weekday_analysis.png")

def _setup_axis(ax):
    ax.xaxis.set_major_formatter(FuncFormatter(lambda x, pos: f"{x * 100:.2f}%"))
    ax.set_xlim(-0.001, 0.055)
    ax.set_ylim(0, 1)
    ax.grid(which="major", alpha=0.5)