Upload holowealth.py

holowealth.py

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+# -*- coding: utf-8 -*-
+"""HoloWealth
+
+Automatically generated by Colab.
+
+Original file is located at
+    https://colab.research.google.com/drive/1lObCKG_uGdcldMmKDoHnuSd34OUy4EmH
+"""
+
+import torch
+import numpy as np
+import matplotlib.pyplot as plt
+from matplotlib.animation import FuncAnimation
+
+waveform_size = 100
+frequency = 0.5
+amplitude = 5.0
+direction_angle = np.pi / 4
+total_time_hours = 24
+time_steps = 240
+
+time_interval = total_time_hours / time_steps
+
+x = torch.linspace(-waveform_size // 2, waveform_size // 2, waveform_size)
+y = torch.linspace(-waveform_size // 2, waveform_size // 2, waveform_size)
+X, Y = torch.meshgrid(x, y)
+
+def infinite_waveform(t):
+  return amplitude * torch.cos(2 * np.pi * frequency * (X * torch.cos(direction) + Y * torch.sin(direction_angle)) + 2 * np.pi * t)
+
+wealth_data = torch.rand(waveform_size, waveform_size) * 100
+total_wealth_energy = wealth_data ** 2
+
+noise_mask = torch.randn(waveform_size, waveform_size) * 0.1
+protected_wealth_energy = total_wealth_energy + noise_mask
+
+wealth_energy_per_time = protected_wealth_energy / time_steps
+
+fig, ax = plt.subplots(figsize=(8, 6))
+signal_plot = ax.imshow(torch.zeros(waveform_size, waveform_size).numpy(), cmap='plasma', origin='lower')
+plt.colorbar(signal_plot, ax=ax, label='Signal Intensity')
+ax.set_title("HoloWealth")
+ax.set_xlabel('X Axis')
+ax.set_ylabel('Y Axis')
+
+def update(t):
+  wave = infinite_waveform(t * time_interval)
+  combined_signal = wave * wealth_energy_per_time
+  signal_plot.set_data(combined_signal.numpy())
+  ax.set_title(f"Signal at Time Step: {t}/{time_steps}")
+
+ani = FuncAnimation(fig, update, frames=time_steps, interval=100, repeat=False)
+
+plt.show()