hdgl_harmonics_spiral10000.zip (1.9 MB)
hdgl_harmonics_sprial10000.py
# HDGL Harmonics + Spiral10000 Integration
# Advanced spiral field generator combining HDGL harmonics with massive 10,000-point spiral patterns
import math
import time
import random
import json
from typing import List, Dict, Tuple, Any
class HDGLHarmonicSpiral:
"""Advanced HDGL harmonic spiral generator with 10,000-point resolution"""
def __init__(self, spiral_points: int = 10000):
self.PHI = 1.618033988749895 # Golden ratio
self.INV_PHI = 1 / self.PHI
self.GOLDEN_ANGLE = 2 * math.pi * self.INV_PHI
self.spiral_points = spiral_points
# HDGL Constants
self.CONSENSUS_EPS = 1e-6
self.CONSENSUS_N = 100
self.GAMMA = 0.02
self.K_COUPLING = 1.0
# Harmonic series (first 8 harmonics)
self.HARMONIC_SERIES = [self.PHI**i for i in range(8)]
# Initialize spiral data
self.spiral_data = []
self.harmonic_field = []
self.lattice_nodes = []
def generate_quantum_spiral(self) -> List[Dict[str, Any]]:
"""Generate 10,000-point quantum spiral with HDGL harmonics"""
print(f"Generating {self.spiral_points}-point quantum spiral...")
spiral_data = []
t = time.time()
for i in range(self.spiral_points):
# Golden ratio spiral positioning
angle = i * self.GOLDEN_ANGLE
base_radius = math.sqrt(i + 1) * self.PHI
# HDGL harmonic modulation
harmonic_modulation = self._calculate_harmonic_modulation(i, t, base_radius, angle)
# Quantum uncertainty (Gaussian noise)
uncertainty = random.gauss(0, 0.01 * math.sqrt(i + 1))
# Final radius with all modulations
radius = base_radius * (1 + harmonic_modulation) + uncertainty
# Calculate position
x = radius * math.cos(angle)
y = radius * math.sin(angle)
# HDGL lattice field properties
energy = self._calculate_lattice_energy(i, radius, angle, t)
phase = self._calculate_quantum_phase(i, t)
spin = (-1) ** i # Alternating spin
# Ternary state (HDGL's 3-state system)
ternary_state = self._calculate_ternary_state(i, energy, phase)
point = {
'index': i,
'angle': angle,
'radius': radius,
'x': x,
'y': y,
'energy': energy,
'phase': phase,
'spin': spin,
'ternary': ternary_state,
'harmonic_power': harmonic_modulation,
'evolution_time': t
}
spiral_data.append(point)
self.spiral_data = spiral_data
print(f"✓ Generated {len(spiral_data)} spiral points")
return spiral_data
def _calculate_harmonic_modulation(self, i: int, t: float, radius: float, angle: float) -> float:
"""Calculate HDGL harmonic modulation for spiral point"""
modulation = 0
for harmonic_idx, harmonic_freq in enumerate(self.HARMONIC_SERIES):
# Time-dependent harmonic oscillation
time_factor = math.sin(2 * math.pi * harmonic_freq * t * 0.001)
# Spatial harmonic (based on radius and angle)
spatial_factor = math.cos(harmonic_freq * angle) * math.exp(-radius * 0.01)
# Index-based harmonic (Fibonacci modulation)
index_factor = math.sin(harmonic_freq * math.log(i + 1))
# Combine harmonics with golden ratio weighting
weight = self.PHI ** (-harmonic_idx)
modulation += weight * (time_factor + spatial_factor + index_factor) * 0.1
return modulation
def _calculate_lattice_energy(self, i: int, radius: float, angle: float, t: float) -> float:
"""Calculate HDGL lattice field energy at spiral point"""
# Base energy from golden ratio scaling
base_energy = self.PHI ** (i % 7) # 7 is a prime number
# Radial energy decay (quantum field effect)
radial_energy = math.exp(-radius / (100 * self.PHI))
# Angular resonance (HDGL coupling)
angular_resonance = math.cos(angle * self.K_COUPLING)
# Time-dependent evolution
temporal_evolution = math.sin(t * self.GAMMA * (i + 1))
# Combine energy components
energy = base_energy * radial_energy * (1 + 0.1 * angular_resonance) * (1 + 0.05 * temporal_evolution)
return energy
def _calculate_quantum_phase(self, i: int, t: float) -> float:
"""Calculate quantum phase for HDGL evolution"""
# Phase accumulation based on evolution steps
phase_accumulation = i * self.CONSENSUS_EPS * self.CONSENSUS_N
# Golden ratio phase modulation
golden_phase = math.sin(2 * math.pi * self.INV_PHI * i)
# Time-dependent phase evolution
temporal_phase = t * self.GAMMA * math.log(i + 2)
return (phase_accumulation + golden_phase + temporal_phase) % (2 * math.pi)
def _calculate_ternary_state(self, i: int, energy: float, phase: float) -> int:
"""Calculate HDGL ternary state (-1, 0, 1)"""
# Energy threshold for state determination
energy_threshold = self.PHI ** ((i % 3) - 1)
if energy > energy_threshold * self.PHI:
return 1 # High energy state
elif energy < energy_threshold * self.INV_PHI:
return -1 # Low energy state
else:
return 0 # Equilibrium state
def generate_harmonic_field(self) -> List[Dict[str, Any]]:
"""Generate harmonic field overlay for the spiral"""
print("Generating harmonic field overlay...")
field_data = []
field_resolution = 100 # 100x100 grid
for x_idx in range(field_resolution):
for y_idx in range(field_resolution):
# Map to spiral coordinate system
x = (x_idx - field_resolution/2) * 2
y = (y_idx - field_resolution/2) * 2
# Convert to polar coordinates
r = math.sqrt(x*x + y*y)
theta = math.atan2(y, x)
# Find nearest spiral points for field calculation
nearest_points = self._find_nearest_spiral_points(x, y, 5)
# Calculate field strength from nearby spiral points
field_strength = 0
for point in nearest_points:
distance = math.sqrt((x - point['x'])**2 + (y - point['y'])**2)
if distance > 0:
# Inverse square law with golden ratio modulation
contribution = point['energy'] / (distance ** self.INV_PHI)
field_strength += contribution
# Apply harmonic modulation
t = time.time()
harmonic_mod = sum(math.sin(2 * math.pi * freq * t * 0.01) * self.PHI**(-idx)
for idx, freq in enumerate(self.HARMONIC_SERIES[:4]))
field_point = {
'x': x,
'y': y,
'r': r,
'theta': theta,
'field_strength': field_strength,
'harmonic_modulation': harmonic_mod,
'total_field': field_strength * (1 + 0.1 * harmonic_mod)
}
field_data.append(field_point)
self.harmonic_field = field_data
print(f"✓ Generated {len(field_data)} harmonic field points")
return field_data
def _find_nearest_spiral_points(self, x: float, y: float, count: int) -> List[Dict[str, Any]]:
"""Find nearest spiral points to a given coordinate"""
distances = []
for point in self.spiral_data:
distance = math.sqrt((x - point['x'])**2 + (y - point['y'])**2)
distances.append((distance, point))
# Sort by distance and return closest points
distances.sort(key=lambda d: d[0])
return [point for _, point in distances[:count]]
def generate_lattice_nodes(self) -> List[Dict]:
"""Generate HDGL lattice nodes based on spiral field resonances"""
print("Generating HDGL lattice nodes...")
lattice_nodes = []
resonance_threshold = 0.1
# Find high-energy resonance points in the spiral
for point in self.spiral_data:
if point['energy'] > resonance_threshold:
# Create lattice node at resonance point
node = {
'id': f"node_{point['index']}",
'x': point['x'],
'y': point['y'],
'energy': point['energy'],
'phase': point['phase'],
'spin': point['spin'],
'ternary': point['ternary'],
'connections': self._find_lattice_connections(point)
}
lattice_nodes.append(node)
self.lattice_nodes = lattice_nodes
print(f"✓ Generated {len(lattice_nodes)} lattice nodes")
return lattice_nodes
def _find_lattice_connections(self, point: Dict) -> List[str]:
"""Find lattice connections for a given point"""
connections = []
connection_distance = 50 # Connection threshold
for other_point in self.spiral_data:
if other_point['index'] != point['index']:
distance = math.sqrt((point['x'] - other_point['x'])**2 +
(point['y'] - other_point['y'])**2)
if distance < connection_distance:
# Check energy compatibility for connection
energy_diff = abs(point['energy'] - other_point['energy'])
if energy_diff < 0.5: # Energy resonance threshold
connections.append(f"node_{other_point['index']}")
return connections[:8] # Limit connections per node
def calculate_field_statistics(self) -> Dict:
"""Calculate comprehensive statistics for the spiral field"""
if not self.spiral_data:
return {}
energies = [p['energy'] for p in self.spiral_data]
phases = [p['phase'] for p in self.spiral_data]
radii = [p['radius'] for p in self.spiral_data]
stats = {
'total_points': len(self.spiral_data),
'energy_stats': {
'mean': sum(energies) / len(energies),
'max': max(energies),
'min': min(energies),
'std_dev': math.sqrt(sum((e - sum(energies)/len(energies))**2 for e in energies) / len(energies))
},
'phase_stats': {
'mean': sum(phases) / len(phases),
'max': max(phases),
'min': min(phases)
},
'radius_stats': {
'mean': sum(radii) / len(radii),
'max': max(radii),
'min': min(radii),
'final_radius': radii[-1]
},
'lattice_stats': {
'total_nodes': len(self.lattice_nodes),
'avg_connections': sum(len(n['connections']) for n in self.lattice_nodes) / max(1, len(self.lattice_nodes))
},
'golden_ratio': self.PHI,
'harmonic_series': self.HARMONIC_SERIES
}
return stats
def export_to_json(self, filename: str = "hdgl_spiral10000.json"):
"""Export complete spiral field data to JSON"""
data = {
'metadata': {
'generator': 'HDGLHarmonicSpiral',
'spiral_points': self.spiral_points,
'timestamp': time.time(),
'version': '1.0'
},
'constants': {
'PHI': self.PHI,
'GOLDEN_ANGLE': self.GOLDEN_ANGLE,
'CONSENSUS_EPS': self.CONSENSUS_EPS,
'GAMMA': self.GAMMA,
'K_COUPLING': self.K_COUPLING
},
'spiral_data': self.spiral_data,
'harmonic_field': self.harmonic_field,
'lattice_nodes': self.lattice_nodes,
'statistics': self.calculate_field_statistics()
}
with open(filename, 'w') as f:
json.dump(data, f, indent=2)
print(f"✓ Exported complete spiral field to {filename}")
return filename
def main():
"""Main execution function"""
print("🌟 HDGL Harmonics + Spiral10000 Integration 🌟")
print("=" * 60)
# Create HDGL harmonic spiral generator
spiral_gen = HDGLHarmonicSpiral(spiral_points=10000)
# Generate complete spiral field
print("\n1. Generating quantum spiral...")
spiral_gen.generate_quantum_spiral()
print("\n2. Generating harmonic field overlay...")
spiral_gen.generate_harmonic_field()
print("\n3. Generating HDGL lattice nodes...")
spiral_gen.generate_lattice_nodes()
print("\n4. Calculating field statistics...")
stats = spiral_gen.calculate_field_statistics()
print("\n5. Exporting data...")
spiral_gen.export_to_json()
# Display summary
print("\n" + "=" * 60)
print("🌟 SPIRAL FIELD GENERATION COMPLETE 🌟")
print("=" * 60)
print(f"Total Spiral Points: {stats['total_points']:,}")
print(f"Lattice Nodes: {stats['lattice_stats']['total_nodes']}")
print(f"Max Energy: {stats['energy_stats']['max']:.6f}")
print(f"Min Energy: {stats['energy_stats']['min']:.6f}")
print(f"Final Radius: {stats['radius_stats']['final_radius']:.1f}")
print(f"Avg Connections: {stats['lattice_stats']['avg_connections']:.3f}")
print(f"Golden Ratio φ: {stats['golden_ratio']:.6f}")
print("=" * 60)
if __name__ == "__main__":
main()
hdgl_spiral_visualizer.py
# HDGL Spiral10000 Visualizer
# Simple visualization script for the generated spiral field
import json
import matplotlib.pyplot as plt
import numpy as np
from matplotlib.animation import FuncAnimation
def load_spiral_data(filename="hdgl_spiral10000.json"):
"""Load the generated spiral field data"""
with open(filename, 'r') as f:
data = json.load(f)
return data
def create_static_plot(data):
"""Create a static plot of the spiral field"""
fig, ((ax1, ax2), (ax3, ax4)) = plt.subplots(2, 2, figsize=(15, 12))
# Extract spiral data
spiral_data = data['spiral_data']
x_coords = [p['x'] for p in spiral_data]
y_coords = [p['y'] for p in spiral_data]
energies = [p['energy'] for p in spiral_data]
phases = [p['phase'] for p in spiral_data]
# Plot 1: Basic spiral pattern
scatter1 = ax1.scatter(x_coords, y_coords, c=energies, cmap='viridis', s=1, alpha=0.7)
ax1.set_title('HDGL Quantum Spiral (Energy)')
ax1.set_xlabel('X Coordinate')
ax1.set_ylabel('Y Coordinate')
ax1.axis('equal')
plt.colorbar(scatter1, ax=ax1, label='Energy')
# Plot 2: Phase visualization
scatter2 = ax2.scatter(x_coords, y_coords, c=phases, cmap='hsv', s=1, alpha=0.7)
ax2.set_title('HDGL Quantum Spiral (Phase)')
ax2.set_xlabel('X Coordinate')
ax2.set_ylabel('Y Coordinate')
ax2.axis('equal')
plt.colorbar(scatter2, ax=ax2, label='Phase (radians)')
# Plot 3: Energy distribution
ax3.hist(energies, bins=50, alpha=0.7, color='blue', edgecolor='black')
ax3.set_title('Energy Distribution')
ax3.set_xlabel('Energy')
ax3.set_ylabel('Frequency')
ax3.axvline(np.mean(energies), color='red', linestyle='--', label=f'Mean: {np.mean(energies):.3f}')
ax3.legend()
# Plot 4: Ternary state distribution
ternary_states = [p['ternary'] for p in spiral_data]
unique_states, counts = np.unique(ternary_states, return_counts=True)
ax4.bar(unique_states, counts, alpha=0.7, color=['red', 'gray', 'blue'], edgecolor='black')
ax4.set_title('HDGL Ternary State Distribution')
ax4.set_xlabel('Ternary State (-1, 0, 1)')
ax4.set_ylabel('Count')
ax4.set_xticks([-1, 0, 1])
plt.tight_layout()
plt.savefig('hdgl_spiral_visualization.png', dpi=300, bbox_inches='tight')
# plt.show() # Commented out for headless environment
def create_animation(data, frames=100):
"""Create an animated visualization showing evolution over time"""
fig, ax = plt.subplots(figsize=(10, 10))
spiral_data = data['spiral_data']
x_coords = [p['x'] for p in spiral_data]
y_coords = [p['y'] for p in spiral_data]
energies = [p['energy'] for p in spiral_data]
# Create scatter plot
scatter = ax.scatter([], [], c=[], cmap='viridis', s=1, alpha=0.7, vmin=min(energies), vmax=max(energies))
def init():
scatter.set_offsets(np.empty((0, 2)))
scatter.set_array(np.array([]))
return scatter,
def animate(frame):
# Show progressive points
n_points = int(len(spiral_data) * (frame + 1) / frames)
current_x = x_coords[:n_points]
current_y = y_coords[:n_points]
current_energies = energies[:n_points]
scatter.set_offsets(np.column_stack([current_x, current_y]))
scatter.set_array(np.array(current_energies))
ax.set_title(f'HDGL Quantum Spiral Evolution - Frame {frame+1}/{frames} ({n_points} points)')
ax.set_xlabel('X Coordinate')
ax.set_ylabel('Y Coordinate')
ax.axis('equal')
return scatter,
anim = FuncAnimation(fig, animate, init_func=init, frames=frames, interval=100, blit=True)
anim.save('hdgl_spiral_evolution.gif', writer='pillow', fps=10, dpi=100)
# plt.show() # Commented out for headless environment
def main():
"""Main visualization function"""
print("🌟 HDGL Spiral10000 Visualizer 🌟")
print("=" * 40)
# Load data
print("Loading spiral field data...")
data = load_spiral_data()
# Display statistics
stats = data['statistics']
print(f"Total Points: {stats['total_points']:,}")
print(f"Max Energy: {stats['energy_stats']['max']:.3f}")
print(f"Final Radius: {stats['radius_stats']['final_radius']:.1f}")
print(f"Golden Ratio φ: {stats['golden_ratio']:.6f}")
print()
# Create visualizations
print("Creating static plot...")
create_static_plot(data)
print("Creating evolution animation...")
create_animation(data, frames=50)
print("✓ Visualization complete!")
print("Files saved: hdgl_spiral_visualization.png, hdgl_spiral_evolution.gif")
if __name__ == "__main__":
main()
