forked from mnbvc188199/Warrior_EA
| Filename | Latest commit message | Latest commit date |
|---|---|---|
65c4b1dce7
The ensemble chart UI had a shared-namespace defect that answered the user question "what do the arrows represent?" with "a bug": all four members drew arrows under the same WarSig_<bartime> object names, so the chart showed whichever member rendered LAST, one member Neutral deleted another member Buy at the same bar, each member init sweep wiped the arrows the previous member had just restored, and SaveChartSignals - which rebuilds the sidecar by SCANNING the chart - persisted every other member arrows into its own history (the exact cross-model laundering its own header warns about, now happening BETWEEN ensemble members). Arrows are now namespaced per member (WarSig_PAI_, WarSig_CONV_, WarSig_LSTM_, WarSig_HYB_): draw, delete, restore, prune, member init sweep, destructor purge and the sidecar scan are all member-scoped, and the tooltip names the model. Global purges keep matching the bare WarSig_ prefix, which covers all member namespaces plus old-format leftovers from earlier builds. Labels: the ensemble panel header no longer says "HYBRID ensemble" (HYBRID is one member; the header is the ensemble) and the CONVLSTM member displays as ConvLSTM instead of Hybrid. Its SHORT id stays HYB deliberately - it names the model folder and changing it would orphan every model trained under that path. Deinit: the alt-data mapping dialog namespace (WarriorAltMap_) joins WarriorChartPrefixes, so both the OnInit purge and the deinit final sweep now cover it - it was in neither list, so a dialog starved of its own Destroy() left its controls on the chart permanently. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> |
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| .. | ||
| README.md | ||
| SignalCONV.mqh | ||
| SignalHYBRID.mqh | ||
| SignalIchimoku.mqh | ||
| SignalLSTM.mqh | ||
| SignalMA.mqh | ||
| SignalMACD.mqh | ||
| SignalMETA.mqh | ||
| SignalNewsFilter.mqh | ||
| SignalPAI.mqh | ||
| SignalRiskGuard.mqh | ||
| SignalRSI.mqh | ||
| Signals.mqh | ||
| SignalSessionFilter.mqh | ||
Signals Subsystem (Signals/)
Overview
The Signals/ directory contains all trade signal generation logic for the Warrior EA. It includes both traditional indicator-based signals and advanced AI/ML-driven signals. Each signal is encapsulated in its own class, supporting modularity and extensibility.
Key Components
Signals.mqh
- Main orchestration file for signal modules.
- Includes both traditional and AI/ML signal classes.
- Facilitates integration of filters (news, session, etc.) and advanced signals.
AI/ML-Driven Signals
- SignalLSTM.mqh: Implements an LSTM-based neural network signal generator. Integrates with the AI subsystem, supports model training, loading, and inference. Designed for advanced, data-driven strategies.
- SignalPAI.mqh: Implements a Perceptron AI-based signal generator. Inherits from
CExpertSignalAIBase. Provides methods for initializing, training, and using a perceptron neural network for trade signal generation. Supports dynamic configuration, indicator integration, and modular AI/ML pipeline features. Designed for advanced, data-driven strategies and easy integration into the EA's AI subsystem.
Traditional Indicator-Based Signals
- SignalMA.mqh: Moving Average signal generator.
- SignalMACD.mqh: MACD oscillator signal generator.
- SignalRSI.mqh: Relative Strength Index signal generator.
- SignalStoch.mqh: Stochastic oscillator signal generator.
- SignalPB.mqh: Pin Bar pattern signal generator.
- SignalNewsFilter.mqh: News event filter for signals, configurable by impact and lookback period.
- SignalSessionFilter.mqh: Session-based filter (London, New York, Tokyo sessions).
Individual Signal Modules
Below is a comprehensive list of all signal modules in the Signals/ directory, with a brief description of each:
- SignalAC.mqh: (Removed)
- SignalAO.mqh: (Removed)
- SignalCCI.mqh: (Removed)
- SignalCONV.mqh: Convolutional AI signal. Uses a neural network for advanced pattern recognition.
- SignalDTDB.mqh: (Removed)
- SignalEB.mqh: (Removed)
- SignalIB.mqh: (Removed)
- SignalIchimoku.mqh: Ichimoku Kinko Hyo classic vote, written from scratch (no standard-library module exists). 12 patterns numbered weakest-to-strongest, covering the full repertoire: price/cloud bias, projected cloud colour and full Chikou Span confirmation (models 0-2, all at the standard-library floor weight of 10 since each is a standing state rather than a trigger); the TK cross graded weak/neutral/strong by cloud position (3/5/10, weights 10/40/90); Kumo twist (4); Kijun-sen cross and bounce (6/7); Kumo breakout and thin-cloud breakout (8/9); and Sanyaku Kōten/Gyakuten at 100 (11). Its class comment documents MT5's draw-shift-only buffer convention and the resulting lookahead hazard.
- SignalITF.mqh: Intraday Time Filter. Filters signals based on time-of-day and day-of-week.
- SignalLSTM.mqh: LSTM AI signal. Uses a recurrent neural network for sequence-based prediction.
- SignalMA.mqh: Moving Average classic vote (unified
ADMovingAveragecustom indicator; 4 patterns). - SignalMACD.mqh: MACD oscillator classic vote, ported from the MQL5 standard library. 6 patterns including single and double price/oscillator divergence — the only divergence model in the classic set.
- SignalNewsFilter.mqh: (Filters trading signals based on economic news events and impact levels. Configurable lookback window and impact threshold.)
- SignalPAI.mqh: Implements a Perceptron AI-based signal generator. Inherits from
CExpertSignalAIBase. Provides methods for initializing, training, and using a perceptron neural network for trade signal generation. Supports dynamic configuration, indicator integration, and modular AI/ML pipeline features. Designed for advanced, data-driven strategies and easy integration into the EA's AI subsystem. - SignalPB.mqh: (Removed)
- SignalRSI.mqh: RSI classic vote (4 patterns).
- SignalRVI.mqh: (Removed)
- Signals.mqh: Main orchestration file for all signals.
- SignalSAR.mqh: (Removed)
- SignalSessionFilter.mqh: (Removed)
- SignalStoch.mqh: (Removed)
- SignalWPR.mqh: (Removed)
Integration Notes
- All signals derive from a common base (typically
CExpertSignalCustomorCExpertSignalAIBase). - Modular design allows for easy addition/removal of signals and filters.
- Migration to a fully AI/ML-driven pipeline is recommended for future-proofing and improved performance.
- Some files (e.g., SignalPAI.mqh) may require conversion or external review due to non-text format.
Documented April 2026. For AI/ML migration and modernization, see AI_NETWORK.md and project roadmap.