Implement quantum-inspired narrative field simulation framework

[leonvanbokhorst]

Summary by Sourcery

Implement a comprehensive narrative field simulation framework using quantum-inspired concepts, including story representation, pattern tracking, environmental effects, and interaction analysis.

New Features:

• Introduce a NarrativeFieldSimulator class to simulate the evolution of a narrative field using quantum-inspired properties.
• Add NarrativeWave class to represent stories as quantum wave functions with properties like amplitude, phase, and coherence.
• Implement PatternMemory, PatternEvolution, and PhaseSpaceTracker classes to manage and track patterns and their evolution in the narrative field.
• Include EnvironmentalCoupling and FrequencyAnalyzer classes to simulate environmental effects and perform frequency analysis on the narrative field.
• Develop StoryInteractionAnalyzer and NarrativeFieldMetrics classes to analyze story interactions and track narrative field metrics.

[sourcery-ai]

Reviewer's Guide by Sourcery

This pull request introduces a sophisticated narrative field simulation system that models stories as quantum wave functions in a semantic space. The implementation uses PyTorch for tensor operations and includes multiple specialized classes for handling different aspects of the simulation, such as pattern detection, frequency analysis, and field evolution.

Class diagram for Narrative Field Simulation System

classDiagram
    class NarrativeWave {
        +String content
        +torch.Tensor embedding
        +torch.Tensor amplitude
        +torch.Tensor phase
        +torch.Tensor coherence
        +Dict~str, float~ entanglement
        +torch.Tensor uncertainty
        +__post_init__()
    }

    class PatternMemory {
        +List~torch.Tensor~ patterns
        +torch.Tensor pattern_strengths
        +List~Dict~ pattern_history
        +float decay_rate
        +Dict~str, NarrativeWave~ story_dict
        +update_patterns(new_pattern: Dict~str, Any~, field_state: torch.Tensor)
        +encode_pattern(pattern: Dict~str, Any~) : torch.Tensor
    }

    class PatternEvolution {
        +Dict~int, List~Dict~~ pattern_trajectories
        +int next_pattern_id
        +update(current_patterns: List~Dict~, field_state: torch.Tensor)
        +calculate_pattern_similarity(pattern1: Dict, pattern2: Dict) : float
    }

    class PhaseSpaceTracker {
        +List trajectory
        +int phase_space_dim
        +record_state(field_state: torch.Tensor, patterns: List~Dict~)
        +analyze_attractor() : Dict
    }

    class EnvironmentalCoupling {
        +torch.Tensor temperature
        +List noise_history
        +torch.Tensor correlation_time
        +generate_colored_noise(shape: tuple) : torch.Tensor
    }

    class FrequencyAnalyzer {
        +int window_size
        +List frequency_history
        +analyze_frequencies(field_state: torch.Tensor, patterns: List~Dict~) : Dict
    }

    class StoryInteractionAnalyzer {
        +List interaction_history
        +analyze_interactions(stories: Dict~str, NarrativeWave~) : Dict
    }

    class NarrativeFieldMetrics {
        +List metrics_history
        +update(field_state: torch.Tensor, stories: Dict~str, NarrativeWave~, patterns: List~Dict~) : Dict
    }

    class NarrativeFieldSimulator {
        +AutoTokenizer tokenizer
        +AutoModel encoder
        +int quantum_dim
        +Dict~str, NarrativeWave~ stories
        +torch.Tensor field_state
        +float total_energy
        +float energy_threshold
        +PatternMemory pattern_memory
        +PatternEvolution pattern_evolution
        +PhaseSpaceTracker phase_space_tracker
        +EnvironmentalCoupling environmental_coupling
        +int current_timestep
        +FrequencyAnalyzer frequency_analyzer
        +StoryInteractionAnalyzer interaction_analyzer
        +NarrativeFieldMetrics field_metrics
        +create_wave_function(content: str, story_id: str) : NarrativeWave
        +quantum_interference(wave1: NarrativeWave, wave2: NarrativeWave) : float
        +apply_field_effects(wave: NarrativeWave, dt: float)
        +apply_environmental_effects(wave: NarrativeWave, dt: float)
        +enforce_energy_conservation()
        +update_field_state()
        +detect_emergence() : List~Dict~
        +calculate_pattern_interaction(pattern1: Dict, pattern2: Dict) : Dict
        +simulate_timestep(dt: float)
    }

    NarrativeFieldSimulator --> NarrativeWave
    NarrativeFieldSimulator --> PatternMemory
    NarrativeFieldSimulator --> PatternEvolution
    NarrativeFieldSimulator --> PhaseSpaceTracker
    NarrativeFieldSimulator --> EnvironmentalCoupling
    NarrativeFieldSimulator --> FrequencyAnalyzer
    NarrativeFieldSimulator --> StoryInteractionAnalyzer
    NarrativeFieldSimulator --> NarrativeFieldMetrics

    PatternMemory --> NarrativeWave
    StoryInteractionAnalyzer --> NarrativeWave
    NarrativeFieldMetrics --> NarrativeWave
    PatternEvolution --> NarrativeWave
    PhaseSpaceTracker --> NarrativeWave

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File-Level Changes

Change	Details	Files
Implemented core narrative field simulation classes and data structures	Created NarrativeWave dataclass to represent stories as quantum wave functions Implemented PatternMemory class for tracking emergent patterns Added PatternEvolution class for monitoring pattern trajectories Created PhaseSpaceTracker for analyzing system dynamics	src/nfs_story_waves.py
Added quantum-inspired field dynamics and interaction mechanisms	Implemented quantum interference calculations between stories Added field effects and environmental coupling mechanisms Created energy conservation enforcement system Implemented non-linear field state updates	src/nfs_story_waves.py
Developed analysis and monitoring components	Added FrequencyAnalyzer for wavelet-based pattern analysis Implemented StoryInteractionAnalyzer for relationship tracking Created NarrativeFieldMetrics for comprehensive field monitoring Added extensive logging and debugging capabilities	src/nfs_story_waves.py
Implemented main simulation control and integration	Created NarrativeFieldSimulator class to orchestrate the simulation Added timestep-based simulation control Implemented dynamic story management Added example usage demonstration	src/nfs_story_waves.py

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[sourcery-ai]

Hey @leonvanbokhorst - I've reviewed your changes - here's some feedback:

Overall Comments:

• Consider adding comprehensive error handling around tensor operations, particularly in quantum_interference() and update_field_state() methods to prevent silent failures.
• Add explicit GPU/device management for torch operations to allow for hardware acceleration and consistent device placement.

Here's what I looked at during the review

• 🟡 General issues: 4 issues found
• 🟢 Security: all looks good
• 🟢 Testing: all looks good
• 🟡 Complexity: 1 issue found
• 🟢 Documentation: all looks good

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