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