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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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primary_frequency = 8 |
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primary_amplitude = 3 |
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phase_shift = np.pi / 6 |
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time_steps = torch.linspace(0, 4 * np.pi, 1000) |
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density_factor = 4 |
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storage_frequency = 15 |
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storage_amplitude = 1.5 |
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storage_phase_shift = np.pi / 3 |
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trigger_time = np.pi |
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def generate_waveform(time, frequency, amplitude, phase_shift): |
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return amplitude * torch.sin(frequency * time + phase_shift) |
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def encode_magnetic_wealth_waveform(signal, density_factor): |
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return signal * density_factor |
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primary_signal = generate_waveform(time_steps, primary_frequency, primary_amplitude, phase_shift) |
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magnetic_wealth_waveform = encode_magnetic_wealth_waveform(primary_signal, density_factor) |
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def storage_waveform(time, trigger_time, storage_frequency, storage_amplitude, storage_phase_shift): |
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storage_signal = torch.where( |
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time >= trigger_time, |
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generate_waveform(time, storage_frequency, storage_amplitude, storage_phase_shift), |
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torch.zeros_like(time) |
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) |
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return storage_signal |
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storage_signal = storage_waveform(time_steps, trigger_time, storage_frequency, storage_amplitude, storage_phase_shift) |
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combined_signal = magnetic_wealth_waveform + storage_signal |
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plt.figure(figsize=(10, 6)) |
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plt.plot(time_steps.numpy(), magnetic_wealth_waveform.numpy(), label="Magnetic Wealth Waveform", color="blue") |
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plt.plot(time_steps.numpy(), storage_signal.numpy(), label="Storage Waveform (Activated)", color="green", linestyle="--") |
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plt.plot(time_steps.numpy(), combined_signal.numpy(), label="Combined Signal", color="red", alpha=0.7) |
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plt.title("Dense Magnetic Wealth Waveform with Data Storage Signal") |
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plt.xlabel("Time") |
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plt.ylabel("Signal Amplitude") |
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plt.legend() |
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plt.grid(True) |
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plt.show() |