Commit graph Warrior_EA/Signals/SignalRSI.mqh
Author SHA1 Message Date
AnimateDread
1bf3eba68a feat(meta): self-contained corpus - the META chart sweeps the real classic ladders over its own history
The user should not need a tester corpus run per symbol. Every pattern
condition in Signals\Signal{MA,RSI,MACD,Ichimoku}.mqh anchors its reads on
`int idx = StartIndex()` with zero hardcoded indices (verified), so a
name-hiding StartIndex override + EvalShift(i) on CExpertSignalCustom makes
the EXACT live ladder code answer "what would you have fired at bar i" -
the silent-divergence trap that justified the DB corpus does not exist on
this path, and neither do the GMT-offset ambiguity, the DB row caps, or
the wipe procedure.

- CExpertSignalCustom: m_evalShift + StartIndex()/EvalShift() +
  SweepPrepare(bars) (deep-resizes the shared price series); the four
  classic signal classes override SweepPrepare to deep-resize their own
  indicator buffers.
- CSignalMETA::BuildCorpusBySweep: per bar x per source filter, run
  Direction() shifted, harvest the per-side pattern slots + netVote into
  the same corpus arrays the DB loader fills; entry=bar open so
  MetaPrepareEra's resolution matches at offset +0 with zero price error.
  DB corpus remains the fallback when classic filters are disabled.
- Warrior_EA.mq5: META gets the enabled classic filters as candidate
  sources (family ids match the descriptor one-hot).
- UseDatabaseRanking default false -> true (user request): a META chart
  journals + ranks out of the box.

Workflow per symbol is now: attach ONE chart with AIType=META (optionally
Meta_ExportDataset=true for the offline pool) - candidates, labels,
training and export all happen in place, ~10 seconds of sweep instead of a
tester run.

Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
2026-08-13 16:19:43 -04:00
AnimateDread
d7eea325fb refactor(ai): extract Layer.mqh and deduplicate AI config
- Moves CLayer neuron construction to AI/Impl/Layer.mqh to keep Network.mqh clean
- Unifies four previously duplicated architecture initialisation blocks (MLP/CONV/LSTM/HYBRID) into a single shared function
- Eliminates risk of behavioural drift where one architecture missed a setter, causing mismatched feature sets or targets
2026-08-01 11:27:28 -04:00
AnimateDread
d667896457 refactor(AI): clean up comments and add conditional compilation guards
Remove verbose book references from input parameter comments in
Network.mqh for clarity. Add #ifndef guard around ENUM_OPTIMIZATION
to allow inclusion from multiple headers without redefinition.
Document the MQL5 Market DLL restriction in NeuronDirectML.mqh and
introduce WARRIOR_MARKET_BUILD macro to conditionally compile out
DirectML DLL imports for Market-compliant builds.
2026-07-22 17:17:23 -04:00
AnimateDread
1073262255 2026-04-20 22:35:14 -04:00
super.admin
0a527b0cf9 convert 2025-05-30 16:35:54 +02:00