Warrior_EA/Variables/README.md

# Variables Subsystem (Variables/)

## Overview
The Variables/ directory contains global input parameters and runtime variables for the Warrior EA. These files centralize configuration, feature toggles, and runtime state, supporting both user customization and internal logic.

## Key Components

### Inputs.mqh
- **Purpose:** Defines all user-configurable input parameters for the EA.
- **Contents:**
  - General EA settings (magic number, training mode, logging, etc.)
  - Money management strategy selection and parameters
  - Entry strategy and thresholds
  - Trailing stop strategy selection
  - Neural network/AI configuration (algorithm, layers, training years, etc.)
  - Indicator and feature toggles (enable/disable specific indicators and features)
  - Time/session filter settings
- **Integration:** Used for both manual and programmatic configuration of the EA. Enables dynamic feature selection and AI/ML pipeline configuration.

### Variables.mqh
- **Purpose:** Stores global runtime variables and constants.
- **Contents:**
  - EA name and database schema
  - Backtesting and feature enablement flags
  - AI/ML signal toggles (EnablePAI, EnableCONV, EnableLSTM)
- **Integration:** Used throughout the EA for runtime logic, feature gating, and database operations.

## Integration Notes
- Centralized configuration and variable management improves maintainability and supports advanced, AI/ML-driven workflows.
- Feature toggles allow for rapid experimentation and safe deployment of new logic.

---
*Documented April 2026. For further details, see the main project documentation.*
feat: Enhance README and documentation for Warrior_EA project - Updated README.md with project overview, key features, directory structure, getting started guide, and modernization roadmap. - Added AI_NETWORK.md detailing the neural network and AI/ML infrastructure, including architecture, components, usage patterns, and next steps. - Introduced DATABASE.md for the Database module, outlining key components, design highlights, usage patterns, and future enhancements. - Created README.md files for Enumerations, Expert, Money, Signals, Structures, System, Trailing, Variables directories, detailing their purpose, key components, and integration notes. - Documented the Signals subsystem, emphasizing modularity, extensibility, and AI/ML readiness. - Added comprehensive descriptions for individual signal modules in Signals/ directory. - Established clear integration notes and recommendations for future improvements across all modules. 2026-04-20 19:28:34 -04:00			`# Variables Subsystem (Variables/)`

			`## Overview`
			`The Variables/ directory contains global input parameters and runtime variables for the Warrior EA. These files centralize configuration, feature toggles, and runtime state, supporting both user customization and internal logic.`

			`## Key Components`

			`### Inputs.mqh`
			`- Purpose: Defines all user-configurable input parameters for the EA.`
			`- Contents:`
			`- General EA settings (magic number, training mode, logging, etc.)`
			`- Money management strategy selection and parameters`
			`- Entry strategy and thresholds`
			`- Trailing stop strategy selection`
			`- Neural network/AI configuration (algorithm, layers, training years, etc.)`
			`- Indicator and feature toggles (enable/disable specific indicators and features)`
			`- Time/session filter settings`
			`- Integration: Used for both manual and programmatic configuration of the EA. Enables dynamic feature selection and AI/ML pipeline configuration.`

			`### Variables.mqh`
			`- Purpose: Stores global runtime variables and constants.`
			`- Contents:`
			`- EA name and database schema`
			`- Backtesting and feature enablement flags`
			`- AI/ML signal toggles (EnablePAI, EnableCONV, EnableLSTM)`
			`- Integration: Used throughout the EA for runtime logic, feature gating, and database operations.`

			`## Integration Notes`
			`- Centralized configuration and variable management improves maintainability and supports advanced, AI/ML-driven workflows.`
			`- Feature toggles allow for rapid experimentation and safe deployment of new logic.`

			`---`
			`Documented April 2026. For further details, see the main project documentation.`