visualization.py - master - maxminaev/trading-bot

visualization.py
46 строк2 KB
Max
Improved backtester class and Visualization
21 мар 2025, 16:42
21 мар 2025, 16:420e6b83d
import matplotlib.pyplot as plt
import matplotlib.patches as mpatches
import seaborn as sns

class Visualization:

    @staticmethod
    def plot_ma_strategy(df, buy_signals, sell_signals, filename=None):
        fig, ax = plt.subplots(figsize=(12, 6))
        sns.set_style("whitegrid")  #set style of plot

        sns.lineplot(x=df["Date"], y=df["Close"], color='blue', label="Close Price")
        sns.lineplot(x=df["Date"], y=df["Short_MA"], color='green', label="Short MA (10)")
        sns.lineplot(x=df["Date"], y=df["Long_MA"], color='red', label="Long MA (50)")
        if "Portfolio_Value" in df.columns:
            sns.lineplot(x=df["Date"], y=df["Portfolio_Value"], color='black', label="Portfolio Value")

        # Plot Buy signals (Green Dots)
        plt.scatter(buy_signals["Date"], buy_signals["Close"], color="green", marker="^", label="Buy Signal", s=100)
        # Plot Sell signals (Red Dots)
        plt.scatter(sell_signals["Date"], sell_signals["Close"], color="red", marker="v", label="Sell Signal", s=100)

        # Manually create legend handles for buy/sell signals
        buy_patch = mpatches.Patch(color="green", label="Buy Signal")
        sell_patch = mpatches.Patch(color="red", label="Sell Signal")

        plt.xlabel("Date")
        plt.ylabel("Stock Price")
        plt.legend(handles=[ax.lines[0], ax.lines[1], ax.lines[2], buy_patch, sell_patch])
        plt.title("Stock Prices")

        if filename:
            plt.savefig(filename, dpi=300)

        plt.show()

    @staticmethod
    def plot_backtesting_results(df):
        plt.figure(figsize=(12, 6))
        sns.lineplot(x=df["Date"], y=df["Close"], label="Stock Price", color="blue")
        sns.lineplot(x=df["Date"], y=df["Portfolio_Value"], label="Strategy Value", color="green")
        plt.title("Backtesting Results")
        plt.xlabel("Date")
        plt.ylabel("Value ($)")
        plt.legend()
        plt.show()