PRAKUL HIREMATHandGitHub
ebb965c7ec
This script simulates and visualizes market volatility and entropy, generating a GIF to illustrate regime transitions and trigger signals.
76 lines
2.3 KiB
Plaintext
76 lines
2.3 KiB
Plaintext
import numpy as np
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import matplotlib.pyplot as plt
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from matplotlib.animation import FuncAnimation, PillowWriter
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# --- 1. SETUP & SIMULATION DATA ---
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np.random.seed(42)
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n_frames = 150
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x = np.arange(n_frames)
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# Regime Transitions: 0-60 (Stable), 60-100 (Latent), 100-150 (Stress)
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regime_bg = np.zeros(n_frames)
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regime_bg[60:100] = 1 # Latent Build-up
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regime_bg[100:] = 2 # Stress
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# Simulated Signals
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volatility = np.random.normal(0.5, 0.1, n_frames)
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volatility[100:] += np.cumsum(np.random.normal(0.2, 0.05, 50)) # Reactive Spike
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entropy = np.random.normal(0.2, 0.05, n_frames)
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entropy[65:] += np.linspace(0, 0.6, 85) # Early build-up in latent phase
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trigger_signal = (entropy > 0.45).astype(float) # The "Early" Detection
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# --- 2. PLOTTING ENGINE ---
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fig, (ax1, ax2) = plt.subplots(2, 1, figsize=(10, 6), sharex=True)
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plt.subplots_adjust(hspace=0.3)
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# Style Customization
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for ax in [ax1, ax2]:
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ax.set_facecolor('#0f0f0f')
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ax.grid(color='white', alpha=0.1)
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ax.tick_params(colors='white')
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fig.patch.set_facecolor('#0f0f0f')
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# Lines
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line_vol, = ax1.plot([], [], color='#00ffcc', lw=2, label='Market Volatility (Reactive)')
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line_ent, = ax2.plot([], [], color='#ff00ff', lw=2, label='HMM Entropy (Latent Signal)')
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line_trig, = ax2.plot([], [], color='#ffcc00', lw=3, label='EARLY TRIGGER')
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ax1.set_ylim(0, 3)
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ax2.set_ylim(0, 1.2)
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ax1.legend(loc='upper left')
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ax2.legend(loc='upper left')
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# --- 3. ANIMATION LOGIC ---
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def init():
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line_vol.set_data([], [])
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line_ent.set_data([], [])
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line_trig.set_data([], [])
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return line_vol, line_ent, line_trig
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def update(frame):
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# Update line data
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line_vol.set_data(x[:frame], volatility[:frame])
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line_ent.set_data(x[:frame], entropy[:frame])
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if frame > 75: # Trigger activation point
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line_trig.set_data(x[75:frame], trigger_signal[75:frame])
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# Dynamic Shading for Regimes
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if frame == 60:
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ax1.axvspan(60, 100, color='yellow', alpha=0.1, label='Latent Phase')
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if frame == 100:
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ax1.axvspan(100, 150, color='red', alpha=0.2, label='Stress Phase')
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return line_vol, line_ent, line_trig
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# --- 4. EXPORT ---
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ani = FuncAnimation(fig, update, frames=n_frames, init_func=init, blit=True)
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print("Encoding GIF... this may take a moment.")
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writer = PillowWriter(fps=20)
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ani.save("assets/detection.gif", writer=writer)
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print("GIF saved to assets/detection.gif")
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