Upload wealth_anchor.py

wealth_anchor.py

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+# -*- coding: utf-8 -*-
+"""Wealth Anchor
+
+Automatically generated by Colab.
+
+Original file is located at
+    https://colab.research.google.com/drive/19-JFhTaK5D_buJiVrOUMgXFTuJj3k_mG
+"""
+
+import numpy as np
+import matplotlib.pyplot as plt
+
+# Step 1: Generate brain frequencies
+def generate_brain_frequency(freqs, t):
+    """Generate brain frequency as a sum of sine waves to transmit wealth signals."""
+    signal = np.sum([np.sin(2 * np.pi * f * t) for f in freqs], axis=0)
+    return signal
+
+# Time variables
+sampling_rate = 1000  # Samples per second
+T = 1.0 / sampling_rate  # Sampling interval
+t = np.linspace(0.0, 1.0, sampling_rate, endpoint=False)  # Time array
+
+# Wealth-related brainwave frequencies (arbitrary for simulation)
+brain_frequencies = [8, 13, 30]  # Frequencies representing wealth signals (theta, alpha, beta waves)
+wealth_signal = generate_brain_frequency(brain_frequencies, t)
+
+# Step 2: Transmit the wealth signals through wave patterns
+def transmit_signal(signal, phase_shift):
+    """Transmit wealth signal through a wave pattern with a phase shift."""
+    transmitted_signal = np.sin(2 * np.pi * signal + phase_shift)
+    return transmitted_signal
+
+# Phase shift to create a unique wave pattern
+phase_shift = np.pi / 4  # 45-degree phase shift
+
+# Transmit wealth signal through the brain wave patterns
+transmitted_wealth_signal = transmit_signal(wealth_signal, phase_shift)
+
+# Step 3: Visualize the wealth signal and transmitted signal
+plt.figure(figsize=(12, 6))
+
+# Original brain-based wealth signal
+plt.plot(t, wealth_signal, label='Original Brain Frequency Wealth Signal', color='blue', alpha=0.6)
+
+# Transmitted wealth signal (wave pattern)
+plt.plot(t, transmitted_wealth_signal, label='Transmitted Wealth Signal (Wave Pattern)', color='green', alpha=0.8)
+
+plt.title('Brain Frequency Wealth Signal Transmission')
+plt.xlabel('Time [s]')
+plt.ylabel('Amplitude')
+plt.legend()
+plt.grid(True)
+plt.show()
+
+import numpy as np
+import matplotlib.pyplot as plt
+
+# Step 1: Generate brain frequencies for wealth signals
+def generate_brain_frequency(freqs, t):
+    """Generate brain frequency as a sum of sine waves to transmit wealth signals."""
+    signal = np.sum([np.sin(2 * np.pi * f * t) for f in freqs], axis=0)
+    return signal
+
+# Time variables
+sampling_rate = 1000  # Samples per second
+T = 1.0 / sampling_rate  # Sampling interval
+t = np.linspace(0.0, 1.0, sampling_rate, endpoint=False)  # Time array
+
+# Wealth-related brainwave frequencies
+brain_frequencies = [8, 13, 30]  # Theta, alpha, beta waves for wealth signals
+wealth_signal = generate_brain_frequency(brain_frequencies, t)
+
+# Step 2: Transmit the wealth signals through wave patterns
+def transmit_signal(signal, phase_shift):
+    """Transmit wealth signal through a wave pattern with a phase shift."""
+    transmitted_signal = np.sin(2 * np.pi * signal + phase_shift)
+    return transmitted_signal
+
+# Apply phase shift for signal transmission
+phase_shift = np.pi / 4  # 45-degree phase shift
+
+# Transmit wealth signal through the brain wave patterns
+transmitted_wealth_signal = transmit_signal(wealth_signal, phase_shift)
+
+# Step 3: Create a storage mechanism for the transmitted wealth signal
+def store_signal(signal, storage_factor):
+    """Store transmitted wealth signal by damping its amplitude for storage."""
+    stored_signal = storage_factor * np.sin(2 * np.pi * signal)
+    return stored_signal
+
+# Apply a storage factor to store the wealth signal
+storage_factor = 0.8  # Simulating the attenuation in storage
+stored_wealth_signal = store_signal(transmitted_wealth_signal, storage_factor)
+
+# Step 4: Visualize the wealth signal, transmitted signal, and stored signal
+plt.figure(figsize=(12, 6))
+
+# Original wealth signal
+plt.plot(t, wealth_signal, label='Original Brain Frequency Wealth Signal', color='blue', alpha=0.6)
+
+# Transmitted wealth signal
+plt.plot(t, transmitted_wealth_signal, label='Transmitted Wealth Signal (Wave Pattern)', color='green', alpha=0.8)
+
+# Stored wealth signal
+plt.plot(t, stored_wealth_signal, label='Stored Wealth Signal', color='red', alpha=0.6)
+
+plt.title('Wealth Anchor')
+plt.xlabel('Time [s]')
+plt.ylabel('Amplitude')
+plt.legend()
+plt.grid(True)
+plt.show()