ответвлён от animatedread/Warrior_EA
720 коммитов
| Автор | SHA1 | Сообщение | Дата | |
|---|---|---|---|---|
AnimateDread
|
45af5b9c1e |
refactor(training): delete the minority-replay machinery that stopped running in July
Two arrays parallel to m_isTrainQueue existed only to serve replay: a
per-occurrence sample weight, and a "count this bar once" flag that kept
the reported IS accuracy on the natural class distribution while backProp
trained on the oversampled one. Replay was removed on 2026-07-31 - every
bar has been queued exactly once since - and the scaffolding was left
standing, provably constant:
m_isTrainQueueWeightScale[] - written 1.0 at both queue sites, swapped
through the Fisher-Yates shuffle to stay in lockstep with nothing,
read into a variable passed to backProp, whose own default is 1.0.
m_isTrainQueuePrimary[] - written true at both sites, swapped the
same way, and read as two guards that could not be false.
Also a `for(int rep = 0; rep < repCount; rep++)` around a hardcoded
repCount = 1, and both arrays preallocated at totalIter * 4 - about
1.5MB per model of always-constant data, on a six-core box that trains
four of them at once. Behaviour is unchanged by construction: every
removed read had one possible value.
m_maxClassSampleWeight goes with them - declared, initialised to 1.5 in
the constructor, read nowhere, and documented as "currently unread by
that path... kept in case a smaller, additive loss-level nudge is ever
reintroduced". That is the definition of YAGNI, and its 17-line comment
described the class-balance correction as data-level oversampling, which
has not been true since July.
Comment pass on ExpertSignalAIBase.mqh, -164 lines this session with
every constant and measured number kept. One correction worth naming:
the header carried 15 lines arguing for HARD 0/1 one-hot targets and
explaining why smoothing was no longer needed - directly above
LABEL_SMOOTH_HIGH 0.9 / LABEL_SMOOTH_LOW 0.05, which every training path
actually uses. It described the opposite of what ships.
Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
|
||
|
AnimateDread
|
506626b381 |
feat(panel): commands reach signals down the filter tree, not through a registry
The control panel drove training by looping g_aiSignals[] - a
hand-maintained, MAX_AI_SIGNALS-capped, AI-only registry that had
already dropped an ensemble member on the floor once (
|
||
|
AnimateDread
|
8c0186c850 |
refactor(signals): AI signal files are identity + topology, nothing else
Every AI signal repeated the same five-line InitIndicators override that did nothing but call InitNeuralNetwork. The cause was an access mismatch, not a design: CExpertSignalCustom declares InitIndicators public, the AI base redeclared it PROTECTED, and each subclass had to redeclare it public to be reachable by CExpert. Worse, the base's own override does a different job entirely - it creates the OHLC/ZigZag feature indicators - and InitNeuralNetwork called it back scope-qualified to stop the virtual dispatch landing in the subclass. Two jobs, one virtual name, and a recursion trap held off by a scope qualifier. The feature-indicator step is now InitFeatureIndicators() (protected, non-virtual, named for what it does) and the AI base carries the single public InitIndicators override. CONV/HYBRID/LSTM/PAI/META drop their copies and are now purely identity plus topology, which is the classic signal file's shape. Comment pass on ExpertSignalAIBase.mqh, -100 lines with every constant and every measured number kept. Three claims in the tier block were stale and inverted - it named CalibratedConfidenceMagnitude() as the tiering input where the code deliberately uses the RAW magnitude, and it described the signal DB as re-ranking each tier when ApplyPatternWeight declines the DB from the end of era 1. Also dropped a paragraph whose subject was a previous version of the comment, and moved two notes down onto the constants they document (CONV_COMPRESSION_DIVISOR was 16 lines and three unrelated defines away from its own text). Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com> |
||
|
AnimateDread
|
c171eace78 |
feat(schedule): close-all defaults to market close minus 5 minutes
targetHour CH_23 -> CH_MARKET_CLOSE, targetMinutes CM_45 -> CM_5. A fixed 23:45 was a guess at one broker's server offset. It is silently wrong on any other feed, and wrong twice a year on the same one. "Market close" resolves per day from the symbol's own session table and backs off the minute value, so it is correct on every symbol and on both sides of a DST switch with no number for anyone to maintain. THIS RE-KEYS EVERY FINGERPRINT and forces a fresh run from era 0. That is correct rather than collateral: the close-all schedule is where the label walk stops treating a trade as holdable (Expert\AIBase\Labels.mqh), so changing it changes every label, and models trained against the 23:45 barrier are confounded for this one. The CUT: field in BuildModelFingerprint() catches it automatically - verified present rather than assumed. Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com> |
||
|
AnimateDread
|
4346dd3c24 |
refactor(stdlib): the vote thresholds are ints on the library's scale, not "confidence %"
The MECHANISM was already stdlib and is untouched: ThresholdOpen() ->
m_threshold_open, tested as `m_direction >= m_threshold_open` exactly as
CExpertSignal does it. What was wrong was the presentation. Both inputs
were preset ENUMS labelled "Min confidence to open/close (%)", which
names the wrong quantity - m_direction is a WEIGHTED MEAN OF PATTERN
WEIGHTS, not a probability, and nothing in this path is a confidence.
They are now plain ints named the way the MQL5 wizard names them:
input int Signal_ThresholdOpen = 25; // [0...100]
input int Signal_ThresholdClose = 101; // [0...100, 101 = never]
Values are exactly what shipped, so behaviour is unchanged. 101 rather
than the library's default of 100 for close: a weighted mean of pattern
weights cannot REACH 101, which is how the shipped config disables the
vote exit, and quietly lowering it to 100 would re-arm a live exit route
as a side effect of a naming change.
VOTE_CLOSE_PRESETS is deleted (its only user is gone). PERCENTAGE_PRESETS
stays - MinRecall genuinely is a percentage.
** ACTION NEEDED ON DEPLOYED CHARTS: the inputs are RENAMED, so saved
.set files no longer match and charts fall back to the defaults above.
Those defaults are the current shipped values, so a chart on 25/Disabled
needs nothing; a tuned one does.
Comment cleanup in the same pass, and this part was not cosmetic - three
blocks documented mechanisms that no longer exist:
- the AI early-exit route (deleted in
|
||
|
AnimateDread
|
97f0631e28 |
feat(baselines): combining-weight fit, MLP cross-validation, all-lags correlation
Three ALGLIB additions, all measurement-only and all under the existing
Run_Alglib_Baselines switch.
MinBLEIC COMBINING WEIGHTS. The live ensemble weights each member by its
own pooled holdout win rate - a defensible prior, but not a fit, and
nothing has ever asked what mixture minimises error on the bars the
members disagreed about. Two individually-mediocre members wrong in
different places can beat one individually better, and a per-member win
rate cannot express that because it never looks at them jointly.
Solved on the simplex (w >= 0, sum w = 1), which is exactly what
MinBLEIC is for. Non-negative because a negative weight asserts "trade
the opposite of this member", a claim ~60 effective observations cannot
support. Least squares on the signed outcome rather than precision:
precision is a STEP function of the threshold that no gradient method
can walk, and optimising a smooth proxy for a step decision is how
|
||
|
AnimateDread
|
7584f119e2 |
feat(baselines): ALGLIB's MLP as a third baseline, not a replacement
Asked whether ALGLIB's perceptron should replace ours "only if it is better". This measures that instead of assuming it, and the measurement is worth more than the swap would have been. The forest and the linear fit test whether the MATRIX carries direction. Neither tests whether OUR CODE is what fails. ALGLIB's MLP does: it is a long-standing independent implementation of roughly what our own dense stack computes, trained on the identical rows through the identical gate. That distinction is not hypothetical here - two silent implementation faults have already invalidated every model-based negative behind them (a transposed dense hidden gradient, so backprop was never backprop; and Adam storing sqrt(v) and feeding it back as variance, so every "Adam" run was SGD). If alglib-mlp clears a bar our own net cannot on the same rows, the fault is in our code. Trained BEFORE the target column is rewritten for the linear fit: MLPCreateC1 builds a softmax classifier whose trainer wants the class index, which is what the matrix still holds at that point. Scored by argmax with Neutral abstaining, exactly as the forest is. Sidak family is now 3, not 2. Deliberately NOT a replacement, and the gap is not close: ALGLIB's MLP is feed-forward only (no conv, no recurrence - so it could not stand in for three of the four members at all), and it has no batch norm, no logit-adjusted loss for the class imbalance, no era resumption, no OpenCL or CPU-DLL backend and no .nnw. Adopting it would trade a maintained architecture for a control. Kept small on purpose - 8 hidden units, 1 restart, 100 iterations, decay at the 0.001 the ALGLIB docs recommend when you have no reason to pick another. A wide net would spend the six-core box's hours answering a question about capacity when the question is about implementation. Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com> |
||
|
AnimateDread
|
19e3595e20 |
fix(build): g_eta - the learning rate global no longer shadows a stdlib local
MetaEditor: "declaration of 'eta' hides global variable" (Math.mqh:792
vs Network.mqh:80). The standard library's Math\Stat\Math.mqh declares a
local `double eta` in its incomplete-gamma branch, and our bare global
of the same name is in scope there.
Same fault as the b1/b2/lr/momentum macros retired in
|
||
|
AnimateDread
|
561c88e6d4 |
feat(baselines): geometry-drift check on the derived stop
DeriveBarrierGeometry() reads the stop off a quantile of the adverse excursions in the IS region ONLY - correctly, since a geometry chosen with the holdout in view has used the holdout for selection and it stops being a holdout. The cost of that correct choice is that nothing ever checked whether the distribution it measured still holds on the bars the model actually trades. If adverse excursions run wider in the OOS window than in the IS region, the derived stop is too tight for the market it is used in, every label was cut on the wrong geometry, and the deploy gate certified a game the trade is not playing - the 2026-08-09 geometry mismatch arriving through drift rather than through a config error. Reported in TWO currencies deliberately. A rank-test p says whether the distributions differ; it does not say whether anyone should care. The stop each half's own quantile would derive says exactly that, in ATR multiples - the units the order is placed in. A significant p with both stops on the same ladder rung is a curiosity; half an ATR of movement is a problem whether or not it clears 0.05. Declustered first, same as the regime test: overlapping labels are not independent draws. Harvest guards are copied from the deriver's own so the two describe the same sample - and the split is verified identical (totalIter == bars - historyBars, so Train's oosCutoff and the deriver's are the same number). Runs before the two model fits and needs only the excursion caches: a chart too thin to fit a forest can still have drifted. Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com> |
||
|
AnimateDread
|
90c6e26e94 |
feat(rng): ALGLIB's L'Ecuyer generator replaces MathRand, and a seed collision goes with it
MQL5's MathRand() is the 15-bit MSVC LCG - 32768 distinct values and the lattice structure that shape of generator has. Two places here actually lean on randomness and both were hurt by it: WEIGHT INIT. Six He/LeCun-uniform sites drew ((MathRand()+1)/32768.0 - 0.5) * 2 * scale, so a first dense layer of ~250k weights had only 32768 possible values and thousands of connections started byte-identical. Breaking that symmetry is the whole job of random init. SHUFFLING. ShuffleRandomIndex() already had to splice TWO MathRand() draws to reach 30 bits, and its own comment documented the residual modulo bias it still carried. HQRndUniformI() is rejection-sampled and exactly uniform, so the splice and the bias note both go. CHighQualityRand is L'Ecuyer's combined multiplicative congruential generator - two differenced streams, 31-bit output, period ~2.3e18 - and it ships with the terminal. AND A BUG THE MIGRATION EXPOSED. The three MathSrand(GetTickCount()) calls sit immediately before "build a fresh topology", once per model. GetTickCount() steps in ~15.6 ms on Windows and an ensemble builds every member inside one OnInit, so members could be handed the SAME seed and draw the SAME weights wherever their shapes coincide - and members that start identical are not an ensemble. WarriorRandSeed() takes a salt (the model id) plus a never-reset call counter, so a collision is impossible rather than merely unlikely, while the tick keeps the run itself genuinely unrepeatable the way those call sites asked for. Seeds are masked positive rather than trusted: HQRndSeed computes s % (M-1) + 1 and MQL5's % keeps the sign, so a negative seed leaves the generator in a state its own assertions reject. GetTickCount() is a uint and goes negative as an int after ~24 days of uptime - a fault that would surface as "training is broken" on a long-running terminal and nowhere else. The indicator tuner's 52 draws move across too: its random search is where sample quality earns its keep. Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com> |
||
|
AnimateDread
|
36254dcd55 |
feat(baselines): matrix redundancy and a declustered regime test
Two ALGLIB diagnostics on the pass that already builds the matrix, under the same Run_Alglib_Baselines switch, so they cost nothing by default and share one walk of the feature pipeline. REDUNDANCY (CBaseStat::PearsonCorrM + CPCAnalysis::PCABuildBasis). The alt-data block already produced this finding once, by hand: 13 features x 16 window slots = 208 inputs spanning ~11.5 effective dimensions, and the cost was not wasted parameters but a gradient weighting bias, since batch norm rescales collinear copies without decorrelating them. This generalises that measurement to every column instead of the one block someone thought to check. Run on the ANCHOR BAR'S ROW, not the full window. The window is m_historyBars near-copies of the same columns at different lags, so per-bar redundancy is the question worth asking - the lag structure is what the conv/LSTM stage exists to exploit - and it keeps the eigensolve at ~60x60 rather than ~960x960. REGIME STABILITY (CMannWhitneyU::CMannWhitneyUTest) on the net's own signed margin: its conviction, signed by whether the conviction paid, older half of the OOS window against newer. DECLUSTERED FIRST, which is the whole reason this is not a one-line call. Triple-barrier labels overlap, so consecutive scored bars share the price action that resolved them and are not independent draws. Feeding all of them to a rank test yields a p computed on an n it does not have - the same error label overlap invalidated everywhere else here. One sample per label horizon costs most of the rows and buys a p that means something; when too few survive, it says so and declines. Both report and neither acts. Wiring the regime flag to position sizing is the obvious next step and the one to take only after watching the number: run every era on ~60 effective observations, a 0.05 test crosses by chance regularly, and an auto-derisk on that is a random position size generator. Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com> |
||
|
AnimateDread
|
d1f08eda13 |
refactor(dry): one retry-and-report for OnInit's five init steps
Trailing, money management, settings validation, indicator setup and timer registration each carried their own copy of the same 18-line retry loop - a bool, a counted loop, a RandomSleep backoff, and two Print lines - differing only in which call they made and what they called it. Five places for the retry count, the backoff and the failure wording to drift apart, and OnInit was 635 lines partly because of it. RetryInitStep() is now the only copy. `what` completes both sentences the loop printed, so the journal reads exactly as it did; `caller` is passed in rather than read from __FUNCTION__ so the line still names OnInit and not the helper. The five steps become one-line wrappers because MQL5 function pointers bind neither a method call nor an argument, and these are two of each (Expert.ValidationSettings/InitIndicators, and the timer's interval). That interval moves to WARRIOR_TIMER_INTERVAL_MS beside its wrapper, taking its full rationale with it instead of leaving it stranded in the middle of OnInit. Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com> |
||
|
AnimateDread
|
5cf706dfd6 |
refactor(kiss): lift the model fingerprint out of InitNeuralNetwork
InitNeuralNetwork() was 673 lines and the fingerprint assembly - the single most audited block in the file, since its hash decides when a trained model may be resumed and when it starts again from era 0 - sat in the middle of it with no name of its own. BuildModelFingerprint() is now that block, moved line for line. Its header states the two rules the per-field notes have been repeating one at a time for months: measured quantities never enter (the .cfg carries those, adopt-don't-compare), and new fields append conditionally so shipping one does not re-key models that never use the feature. The assembly is byte-identical - verified by diffing every `fp =`/`fp +=` line against HEAD, which differ only by the new call site. So no existing .nnw/.cfg re-keys and nothing retrains. Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com> |
||
|
AnimateDread
|
786aa76083 |
refactor(dry): one shrinkage estimator for classic ladders and AI tiers
The Beta-prior arithmetic that turns counts into a ranking weight was written twice, term for term: WinRateFromCounts() for the classic pattern ladders and RankTiersFromOos() for the AI confidence tiers. Same formula, two transcriptions, and the same class of duplication the binomial SE consolidation removed a few commits ago. ShrunkRatePct() in System\BinomialStats.mqh is now the only copy. The two call sites keep what genuinely differs - the classic path passes RAW trade counts with a prior of MIN_TRADES_FOR_WIN_RATE, the AI path passes OVERLAP-CORRECTED effective counts with TIER_PRIOR_EFF_N, which is far smaller precisely because effective counts are - and that contract is now stated once, in the function, instead of being implied by two comments that could drift apart. Also fixes a difference the consolidation exposed: with an empty sample and a prior present, the posterior mean IS the prior, and returning 0 there would have handed a tier a vote weight of zero on no evidence. The AI path could reach that (effN can round to 0 when labels overlap heavily); the classic path cannot, since it returns NO_DATA_WIN_RATE first. Corrects a stale note of my own in passing: this ranking was recorded as a "raw win rate behind a MIN_TRADES cutoff heuristic". It is not, and has not been for some time - it is already a proper empirical-Bayes estimator with a per-filter pooled prior. Replacing it with a significance test, as that note implied, would have swapped the estimator the weight needs for a gate answering a different question. Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com> |
||
|
AnimateDread
|
ce2c324527 |
feat(baselines): Alglib forest + linear on the NN's own matrix
Every direction verdict so far was measured through one architecture family, so "flat" has two readings that no topology tuning can separate: the net is the wrong learner, or the matrix carries no directional information. Two learners with completely different inductive biases - Alglib's random decision forest and an ordinary least-squares fit - now train on the SAME feature windows (BuildFeatureWindow, the net's own function, so there is no second feature implementation to drift), the SAME labels, the SAME IS/OOS split with both purges, and are scored through the SAME precision-against-always-one-direction comparison and the same Sidak family-wise arithmetic the deploy gate uses. If both also land at chance, the matrix is the limit. Deliberate choices, each of which could have made the comparison a different question wearing this one's name: - LRBuild, not LRBuildZ: the intercept absorbs the class imbalance, and a baseline handicapped by a forced zero intercept would flatter the net for the wrong reason. - Raw call counts in the SE, matching the live gate's known-permissive test rather than correcting it here - both sides must face the same bar. - No threshold sweep on the linear fit: a threshold fitted on the slice being scored is the calibration leak the purged band exists to avoid. - Uniform stride when a cap bites, not the newest N rows, so a score difference cannot be a regime difference. What was dropped is logged. Ships off (Run_Alglib_Baselines = false): it is a measurement, not a trading feature, nothing trades on the answer and no model is saved. Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com> |
||
|
AnimateDread
|
38a12a240b |
refactor(kiss): drop the AI sub-vote early-exit route; certified == traded
First of the AI vote layers to go. CheckClosePosition had two exit routes: the stock blended vote, and an AI-only one reading the AI members' sub-vote undiluted. The second existed because an AI reversal averaged in with the classic filters could be diluted below the threshold before it could close a position. It is gone, and with it m_lastAiVote and the aiResult/aiWeightSum pair Direction() carried to feed it. This CLOSES the certified-vs-traded gap rather than widening it. The deploy gate certifies a win rate measured on hold-to-resolution outcomes, and CheckClosePosition already gated the blended route off whenever an AI model's derived geometry was on the order - so the AI route was the only vote exit an AI-certified trade could take, and the exit replay existed to reproduce it. With it removed, an AI-certified position holds to its barrier by construction instead of by reconstruction, so Warrior_EA.mq5 now pushes ExitPolicy(0.0, true) unconditionally. Previously it forwarded Min_Vote_Close and relied on Disabled arriving as 1.01 to switch the simulated exit off by arithmetic - correct at the shipped default, and one input change away from the simulation and the live path describing different games. Min_Vote_Close keeps its meaning for the classic route and is now documented as inert wherever an AI certificate governs, rather than appearing to drive an exit it can no longer reach. Comment debt cleared while here: a tombstone block for m_ai_exit_threshold (a member deleted 2026-08-18) still sat in the header, and four sites still named LiveSignedConfidence's "two consumers" - it had one, the intelligent trailing stop, since that same date. NOT touched, and deliberately: NMS declustering is NOT a quality layer. It gates the live signal at Inference.mqh:226 (NmsLiveAccept), and the undeclustered population is ~8x what the EA trades. Removing it would multiply live position count, not simplify a scoring path. Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com> |
||
|
AnimateDread
|
77594ef5fb |
refactor(stdlib): one quantile definition, from Math\Stat
The codebase had THREE conventions for the same statistic. AltData took a
true median; the barrier horizon and the derived input window took the
upper of the two middle values; the MI terciles and the barrier stop
ladder used nearest-rank indexing. All four now go through MathMedian /
MathQuantile, which is R's type 7 and the library's one answer.
System\AltData.mqh column median -> MathMedian (exact, no change)
AIBase\Labels.mqh swing median -> MathMedian
leg-range med -> MathMedian
stop ladder -> MathQuantile, read in one call
AIBase\Topology.mqh window median -> MathMedian
AIBase\AutoTune.mqh MI terciles -> MathQuantile + MathMin/MathMax
Signals\SignalSessionFilter DST last Sunday-> CDateTime::DaysInMonth()
gaps[]/legs[] change from int to double so MathMedian can read them; the
values are bar counts either way.
VALUES MOVE. Even-sample medians shift by half a bin and the quantile
reads interpolate, so the barrier geometry and the derived input window
can land on different rungs - re-keying fingerprints and forcing a
retrain. Accepted deliberately: stdlib consistency was the ask, and three
private conventions for one statistic is what it buys out.
Two YAGNI finds fell out of the ladder rewrite. MathQuantile sorts its own
copy, so DeriveBarrierGeometry no longer sorts up[]/dn[] in place - which
means upUnsorted[], a full array copy kept only to undo that sort, is
gone. ArraySort(up) had no consumer needing order at all; it was pure
work. The library call also gets a failure guard the hand-rolled indexing
never needed but the ladder read does.
Verified while here: Math\Stat\Math.mqh's MathAbs/MathMax/MathSqrt/MathPow
and friends are ARRAY overloads, not scalar redefinitions, so pulling it
into the translation unit shadows no builtin.
Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
|
||
|
AnimateDread
|
29c82ad50b |
refactor(dry): one binomial arithmetic for every "is this edge real" test
The formula p(1-p)/n was transcribed nine times across six files - the two deploy gates, the two edge floors, the collapse recall floor, the barrier rung ladder, the inference bin SE, the pooled inverse-variance weights and both detectability reports. System\BinomialStats.mqh now holds it once, as free functions with no class dependency, so the god-class declaration does not grow to host pure math. BinomialVar(p, n) p(1-p)/n BinomialSEPct(p, n) 100*sqrt(p(1-p)/n) BinomialCallsForEdge(p, edge, sigmas) the same, solved for n NormalUpperTailQ(z) Q(z), via Math\Stat\Normal.mqh SidakFamilyP(z, N) 1-(1-Q(z))^N Value-preserving by construction: rates go in as probabilities so no call site gained a *100/100 round-trip, and BinomialSEPct is written through BinomialVar so the multiply order is the one it replaced. Every degenerate guard each site carried (p<=0, p>=1, n<=0) now lives in one place and returns the 0 those sites already treated as "no bar to clear". CExpertSignalAIBase::NormalUpperTail is gone; NormalUpperTailQ replaces it. What consolidating SURFACED, and is deliberately NOT changed here: the two Sidak selection gates compute their SE on the RAW call count, while every other SE in the project deflates by EffectiveSampleSize() for triple- barrier label overlap. That makes them the most permissive test in the codebase, by ~sqrt(mean label lifespan). Correcting it tightens a live deploy bar, which is a policy decision, not a refactor - flagged in the code at both sites. Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com> |
||
|
AnimateDread
|
0826f8b900 |
refactor(dry): one definition of "usable quote" in the pre-trade checks
Six checks each fetched bid/ask and rejected a non-positive pair with their own wording. TCLiveQuote() now owns that rule, so what counts as a usable quote is defined once and every rejection reads the same way. The one message that said only "no live quote for <symbol>" now names what it was about to do, like the other five. Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com> |
||
|
AnimateDread
|
ea2552efe2 |
refactor(stdlib): adopt Math\Stat for the deploy gate's normal tail; retire the b1/b2/lr/momentum macros
The gate's NormalUpperTail was a hand-rolled Abramowitz & Stegun 26.2.17 approximation. Its own comment gave the reason - "drags a chain of headers behind it" - and that turned out to be one file: Math\Stat\Normal.mqh includes only Math.mqh, which includes nothing. Swapped for Cody's rational approximation in the library (~18 significant digits vs |error| < 7.5e-8). No past verdict changes: at the z the gate operates on, the difference is orders of magnitude below DEPLOY_FAMILY_WISE_ALPHA. Adopting it needed the four bare macros in AI\Network.mqh gone first. "#define b1 AdamBeta1" collides with an identifier in Math.mqh, so the include would have macro-expanded the library's own local and failed to compile - the same landmine that made the original author rename the approximation's coefficients to ntB1..ntB5 rather than use the reference's b1..b5. lr, b2 and momentum are the same class of hazard: single-token global macros in a 52k-line codebase. All four now resolve to the input names they always aliased, which is a pure textual identity - verified zero bare occurrences remain. Also: - SelectionSort over the buffered signals was O(n^2) with an O(n^2) count of StructToTime calls, because the comparison rebuilt both datetimes from the six int date fields every time. Now materialises the keys once and does an insertion sort; ArraySort cannot permute a struct array. IsEarlier goes with it, MakeDateTime becomes SignalTime. - Seven FileOpen sites lacked FILE_SHARE_READ|FILE_SHARE_WRITE, including AtomicWriteBegin, which stages every model save. All 43 sites now carry them - an exclusive open fails outright when another process holds the path, which here has meant a silently skipped save. Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com> |
||
|
AnimateDread
|
b0fec27779 |
merge: built-in indicator migration + YAGNI accessor pass
Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com> |
||
|
AnimateDread
|
61c0d19ca9 |
feat(indicators): run the built-in iMA and MetaTrader's ZigZag; add a classic-vote shift
MA: CustomIndicators\ADMovingAverage is replaced by the built-in iMA (CiMA) on both consumers - the classic vote and the NN MA input feature. This drops the five advanced types ALMA/DEMA/ZLEMA/T3/Kalman, which have no iMA equivalent; MA_TYPE_PRESETS is now ENUM_MA_METHOD's own codes and the tuner searches all four. It also removes a documented failure mode: a custom indicator's depth is bounded by TERMINAL_MAXBARS, and m_MA was the one whose feature block REJECTS the bar on a short read - the "feature 25 fails on every bar" incident of 2026-08-17. A built-in is served at any depth. MIGRATION. SMA moves from code 5 to 0, so persisted type codes change meaning. SanitizeMaType() is the single validity rule; TunedPeriods records now carry a version field and a v1 record remaps 5..8 -> 0..3, falling back to SMA for a stored advanced type (unrecoverable - old 0..4 are indistinguishable from valid new codes). Existing .nnw files re-key on their own, because MA_Type is hashed into the topology fingerprint, so models retrain rather than silently running on different MA values. EXPECT A FULL RETRAIN. ZigZag: ADZigZag was a byte-identical rename of MetaQuotes' Examples\ZigZag - verified by normalising identifiers and stripping comments, 233 significant lines each with only renamed symbols differing. It now loads the stock one, so nothing is bundled and MetaQuotes' fixes arrive without a rebuild here. Both #resource entries are gone. Classic_Shift: a new input, the BAR the four classic votes evaluate on (0 = forming, 1 = last closed, default 1). One implementation on CExpertSignalCustom, inherited by all four rather than repeated per module. Defaults to a sentinel meaning "unset", so the AI signals and the aggregate keep the stock every_tick rule and their feature/label alignment is untouched. The META corpus sweep still takes precedence. CExpertBase::StartIndex turns out to be virtual, so this is a real override, not the name-hiding the old comment claimed. Not compiled - MetaEditor compile pending. Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com> |
||
|
AnimateDread
|
552edb5fb1 |
refactor(yagni): drop 13 accessors nothing called; unify the ATR trailing pair
Verified dead by grep across all first-party sources (references/, Scripts/, research/ excluded): EraCount, HiddenLayersCount, LstmHiddenSize, ConvFilterCount, HistoryBars and MinTrainYear setters, PendingBatchSamples, getPrevOutIndex, BaseCurrency, QuoteCurrency, CurrencyCount, IsLoaded, LastFiredDirection, DBConfidence, SpecIndex, and the conv Step/WindowOut shape accessors. Every backing member stays - each is still read internally and several are pinned by the positional .cfg layout - so this removes surface, not behaviour. Two comments were asserting the opposite of the code and are now true: the "No setter: the taper's endpoints are derived" note was directly above three setters, and the conv shape block claimed EnforceTopologyContract reads all three accessors when CNet::FirstConvWindow only ever calls Window(). CTrailingATR::CheckTrailingStopLong/Short were byte-identical but for Bid vs Ask and the isLong flag; both now delegate to one CheckTrailingStop body. Deliberately NOT removed: the fractal-target branch (TrainTargetFractal, IsFractalTarget and their label machinery). It reads as dead because the TrainingTarget input was withdrawn, but Warrior_EA.mq5:836 documents it as a parked option with a three-line restore path - that is a product call, not a refactor. Not compiled - MetaEditor compile pending. Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com> |
||
|
AnimateDread
|
2be2970434 |
fix(topology): the capacity budget counted overlapping bars as independent examples
EstimatedInSampleBars() returned raw bars (11372 on SP500 H4) and every derived capacity decision spent that: first-layer width, conv filters, LSTM hidden size. But triple-barrier labels overlap - mean lifespan 9.4 bars - so the label cache line on the same run already reports those bars are worth ~1210 independent observations. Sizing a network against RAW bars while grading it against EFFECTIVE ones is two subsystems disagreeing about one sample, and it disagreed in the dangerous direction because the capacity side was the optimistic one: the warning's "roughly 1.1 weights per training bar" is nearer 11 per independent observation. EffectiveSampleSize() has existed since 2026-08-17 and is applied at eight sites, all of them statistics. This adds the ninth, in the one place that decides how many parameters get fitted. Applied inside EstimatedInSampleBars() rather than at the call sites, because that function exists precisely so the three stages spend one budget. SELF-ENABLING AND THEREFORE INERT WHERE IT MATTERS MOST, which is why this is two changes and not one. MeanLabelLifespan() is 1.0 until a label cache has measured something, so on a model's first build - before any label exists - the deflation is correctly the identity: an unmeasured overlap must not invent a shrink. A fresh attach constructs a fresh object, so its counters are zero too; only a mid-session weights reset carries real evidence into a rebuild. That is deliberately safe (no attach can now re-derive a narrower topology and discard trained weights) but it would have left the first build - the case you most want the truth for - quoting the flattering figure. So ReportDetectability now restates capacity against the effective sample at the first moment L is real, for the topology already pinned. It re-sizes nothing; it reports what was bought. Placed ABOVE that function's break-even guard on purpose - a degenerate geometry is exactly when you want to know the net is over-parameterised, and "it only fires for sane configs" is how the 2026-08-18 IS-error stop managed never to fire at all. The warning also names its basis now (independent observations and L, or an explicit "overlap NOT YET MEASURED, this is an UPPER BOUND"), so a flattering number can never again read as a measured one. Also factors FirstLayerFanIn() out of ComputeFirstLayerWidth so the capacity REPORT charges for exactly what the capacity DECISION charged for - same reason RequiredHorizonBars was factored out after the 2026-08-17 divergence - and makes MeanLabelLifespan()/EffectiveSampleSize() const so the const budget path can call them. Verified: no recursion (EstimatedInSampleBars -> EffectiveSampleSize -> EstimatedInSampleBarsRaw, which computes from Bars() alone); both new StringFormat sites hand-counted (basis 3/3 and 1/1, CAPACITY 10 specifiers / 10 arguments). NOT COMPILED - user compiles in MetaEditor. |
||
|
AnimateDread
|
caad156464 |
fix(geometry): the ratio raise was reported against reachability, not bounded by it
First clean derivation after |
||
|
AnimateDread
|
6f2def0605 |
fix(geometry): a weights reset could never change the barrier - the pair laundered itself through the wipe
Reported as "it still seems leaned towards 2x atr" after a full Delete && Reset Weights on SP500 H4. It was not the .cfg pin, and it was not the new ratio floor failing to take: the geometry is held in members ResetWeights never cleared, so a reset wiped the .cfg, built a fresh net, restarted at era 0 - and then relabelled under the PREVIOUS model's pair, before SaveTopologyConfiguration wrote that stale pair back into the brand new .cfg. Reset, re-derive, re-pin, with the middle step missing. No number of resets could ever have moved it. Evidence in the 2026-08-19 journal: RESET WIPE at 16:23:38.699 (.cfg=deleted), "rebuilt a fresh topology" at .790, and a label cache at .890 with a distribution byte-identical to the pre-reset 2.00/2.00 one (Buy 3221 / Sell 3303 / Neutral 4837, mean lifespan 6.4 bars) - 100 ms later, with no DeriveBarrierGeometry between them. The member that actually blocked it is m_geometryDerivePasses. LoadAndCompareTopologyConfiguration pins it to BARRIER_DERIVE_MAX_PASSES to block the fixed-point iteration, which is correct for a LOAD - an existing model must never re-derive or the target moves under fitted weights - and exactly wrong for a RESET, which is the act of declaring there are no fitted weights left to protect. State that is correctly sticky for one lifecycle event, silently inherited by another; the same shape as the .cfg pin sitting beside it. ResetWeights now returns the whole derivation to its constructor state: the three latches, the pair, the horizon and its flags, the swing/lifespan measurements, the scan's own outputs, and m_spreadAtr - that last one matters because the cost filter is deliberately inert on pass 1 (m_spreadAtr <= 0.0) and an inherited spread makes a reset model walk a different ladder than a genuinely new one. m_sl_mode/m_tp_mode go back to the SL_Mode/TP_Mode inputs, since the adopt path overwrites them in place with no copy of what was configured. NOT COMPILED - user compiles in MetaEditor. |
||
|
AnimateDread
|
c3daded397 |
feat(geometry): 1:2 becomes a FLOOR the swing legs may raise, and the scan can no longer undercut it
Two coupled changes, both from measurements in today's SP500 H4 log. 1. THE SCAN WAS OVERRIDING THE DERIVER ON THE WRONG OBJECTIVE. At 13:37:47 DeriveBarrierGeometry produced stop 1.21*ATR / target 2.41*ATR - break-even 33.3%. Thirty-seven seconds later the barrier-geometry scan adopted 2:2 - break-even 50.9% - because it carried 0.0143 nats of entry-time information against the configured pair's 0.0075, and cleared its family-wise gate. Information is not expectancy, and the scan says so itself; nothing checked what the adoption did to the operating point. It did this: the fitted thresholds immediately after read 38.8% win vs 50.9% break-even (-12.2pp) and 48.3% vs 50.9% (-2.6pp), where the earlier model on this instrument at a 1:2 geometry had fitted +1.8pp. The deriver applies the ratio as user RISK POLICY; a scan that can crown 1:1 makes two subsystems disagree about one geometry - the same split this file already fixed once for the clamped-horizon rule. The scan now enrols and crowns only pairings at or above the floor; sub-floor pairs are still scored and printed (marked 'r') so the choice stays auditable. This is NOT the min-RR rule removed on 2026-08-09 - that one guarded a rejection filter that no longer exists. 2. THE RATIO IS A FLOOR, NOT A CAP (user: "the ratio of 1:2 is a minimum that I want, but it should not cap to that if the average zigzag moves gives more room"). BARRIER_TARGET_RR -> BARRIER_TARGET_RR_MIN. ComputeBarrierHorizonBars already scanned ZigZag pivots for leg DURATION; it now harvests leg RANGE in the same pass - two properties of one object, so the horizon and the target describe the same legs instead of two windows. The per-rung ratio is the floor raised toward median-leg/stop, snapped DOWN to a coarse ladder (2.0/2.5/3.0/4.0/5.0). The ladder is coarse on purpose: PooledGate pools only instruments whose structural break-even matches, and continuous per-instrument ratios would never match and would silently empty the pool. A leg is the right yardstick precisely because it owes NOTHING to the barrier - sizing a target off travel measured over the barrier's own horizon is the circular loop that ran EURUSD/USDCAD away to 14-31*ATR in 2026-08-07. The raise stays bounded by the three tests already in the ladder: reachability, the horizon ceiling (first-passage time grows with stop x target), and the cost fraction. Consequential fixes: the reachability floor was a macro keyed to the fixed ratio and is now BarrierMinReachPct(rr) evaluated per rung (a raised ratio has a lower break-even, so a fixed floor would be the wrong strictness); the detectability break-even likewise; PooledGate now writes and matches the ACTUAL ratio (TargetRR()) rather than the floor. NOT COMPILED - user compiles in MetaEditor. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> |
||
|
AnimateDread
|
888f32d21c |
fix(gate): the plateau shortcut re-ran the deploy test every era, raising its own bar
User report: 'eras since best' in the ensemble line is always 0 (era 147, best at era 90,
'0 eras ago'). That is a control-flow bug wearing a display symptom.
Once every member's in-sample error had plateaued, the shortcut forced the ladder to its
DEPLOY stage on EVERY era. The failed-gate branch resets the stage to 0 so the ladder can
climb again - so the shortcut raised it, the branch cleared it, forever. Three consequences,
only the first of which was visible:
- g_ensErasSinceBest was reset every era, pinning the counter at 0.
- The stage-1/2 boosted warm restarts were never reached, so the one mechanism that can
un-plateau a stuck member never ran. The models sat at a WORSE error than their best
(0.2408 -> 0.3015 on PAI) with no escape.
- Every repetition ran EnsembleSurvivesSelection against an unchanged best and incremented
the candidate-era count the family-wise correction divides by. The run spent its time
RAISING ITS OWN SIDAK BAR - the same waste as the 2026-08-18 inert IS-error stop, one
layer up, and the reason a gate that needed >47.8% saw its bar climb era after era.
Fix: the shortcut fires ONCE PER BEST-ERA (g_ensGateTestedEra, stamped before the outcome
branches because it is the re-running that inflates the family, pass or fail). A refused
gate now falls back to the normal counter-driven ladder - warm restart, anneal, then a
fresh deploy test - which is the escape the shortcut was skipping.
Also, per user: the signal marks were too small to see. Span doubled (2.6 bar widths, so
the overhang either side of the candle is ~0.8 bars) and both layers thickened - 1px dotted
was invisible on a candle chart at any realistic zoom.
NOT COMPILED - user compiles in MetaEditor.
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
|
||
|
AnimateDread
|
9a0d063da4 |
fix(inputs): the Neural Networks group header was singular
Typo, and more wrong than it was: the group now holds four independent NN toggles rather than one architecture selector. NOT COMPILED - user compiles in MetaEditor. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> |
||
|
AnimateDread
|
5e0317f09d |
feat(chart): signal marks become price LEVELS at the trigger, not arrows beside the candle
User request: 'move from arrows on lows and highs to small horizontal lines at the actual prices the entry/exit would trigger, just a bit larger than the candles. dark green for buy, dark red for sell.' Every mark is now an OBJ_TREND segment with both anchors at one price and both rays off, spanning 1.3 bar widths, drawn at the bar's CLOSE - the price a market order actually fires at, and the exact entry TripleBarrierLabel assumes. It used to sit on the candle's LOW for a Buy and its HIGH for a Sell: prices the trade never touches, picked so an arrow glyph would clear the candle. The tooltip now carries that price too. COLOUR NOW MEANS DIRECTION AND ONLY DIRECTION on every layer (dark green / dark red). Layer moves to width+style - the traded vote is solid and thick and drawn in front, a single model's raw opinion is thin, dotted and behind the candles - which keeps the distinction the old palette existed to draw (a model's opinion must never read as a trade) while freeing colour to say one thing consistently. Consequences handled, all of them the same 'a typed scan went blind' failure: - SaveChartSignals filtered OBJPROP_TYPE == OBJ_ARROW and read OBJPROP_ARROWCODE. It now filters OBJ_TREND and recovers direction from the colour. The sidecar keeps the old 217/218 numbers as its buy/sell token deliberately, so existing .arrows files still load. - AdvanceChartSignalRestore now rebuilds through the SAME creation point the live path uses, so a restored mark and a fresh one are identical objects. - The rescan-scoped delete enumerated ObjectsTotal(OBJ_ARROW) - retyped, or it silently deletes nothing. - ApplySignalsVisibility enumerated OBJ_ARROW with NO prefix filter. Under the new type that would have hidden and shown THE USER'S OWN trend lines on every Hide/Show click; it is now prefix-scoped. The old type was uncommon enough on a real chart to mask the missing check - trend lines are the most hand-drawn object there is. - DrawObject's high/low parameters are gone (6 call sites pass m_Close instead), so no caller can hand it a price it no longer draws at. - Fixed a pre-existing stale comment that still described the purge sweep as OBJ_ARROW-only three lines above the note explaining it had been widened to every type. NOT COMPILED - user compiles in MetaEditor. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> |
||
|
AnimateDread
|
70eaa8a498 |
feat(direction): Intelligent becomes the shipped default for Trade direction
User request after the first ensemble run under the per-NN build: the drift verdict was measured and printed every era while the input sat at BOTH, so it gated nothing - the worst of both, because an authoritative-looking log line described a policy that was not in force. Safe as a default: the verdict fails open to BOTH (it drops a side only when the gap clears 2 combined SEs on the overlap-deflated sample AND the weaker side sits below cost-adjusted break-even), so an instrument with no measurable drift behaves exactly as before. Verified it appears in no fingerprint or DB key - trade policy, not label definition - so this changes no model identity and resets no training. NOT COMPILED - user compiles in MetaEditor. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> |
||
|
AnimateDread
|
6717509c8b |
fix(build): four compile faults - one was a SILENT enum collision that inverted the direction policy
Reported by the user's MetaEditor compile of |
||
|
AnimateDread
|
f64e0f8b67 |
feat(ensemble): per-NN inputs replace the preset selector - the meta head becomes the vote's gate
User design (2026-08-19): 'remove the enum menu that selects neural networks... individual inputs for every NN just like classic signals... the META NN should be integrated into the voting decision pipeline when enabled... as a bonus meta labelling is applied to enabled NNs.' - AI_CHOICE is GONE (tombstoned per the stale-.set doctrine). Use_MLP/Use_CONV/Use_LSTM/ Use_CONVLSTM are ordinary bools like the classic votes; the ensemble arithmetic adapts to any subset because the consensus divisor is the enabled capable weight. Two or more enabled = ensemble (|ENS1 token + joint gate, exactly the old AI_HYBRID fingerprints, so existing weight files keep loading); one = the old solo preset; none = classic-only. - Use_MetaLabeling un-couples META from the direction NNs (the old selector made them mutually exclusive). S3 ships: CSignalMETA::LiveMetaGate scores each vote-cleared entry (shared window at bar 1 + proposal descriptor: side, net vote, live geometry, spread/ATR; pattern one-hot ZEROED - ranking, not calibrated probability, documented in the body) and vetoes below the cost-adjusted break-even. Entries only; fail-open everywhere, loudly. - COEXISTENCE HAZARDS closed: VoteCapableWeight()=0 and ProspectiveVote()=false for the meta target - solo-only until today, a trained META would otherwise sit in the consensus divisor as a permanent abstainer and shrink every vote by its module weight. - CERTIFIED == TRADED: the ensemble era verdict replays the identical veto through the same g_warriorMetaGate pointer over its OOS fired bars (bar re-resolved from the row's own time; fail-open counted as fires and reported: 'metaGate: N approved, M vetoed, K unscored'). The overlay deliberately does NOT replay it (veto-filter-in-replay class, calendar-cliff precedent) - documented at the sweep site. Solo charts' own gate does not model the veto - the standing solo-gate caveat, documented at the input. - DB continuity: the pattern/journal DB fingerprint's first slot was (int)AIType; DbLegacyAiSlot() maps every legacy-expressible config to its OLD value (new 2-3 member subsets get 100+bitmask, outside the legacy range) so no existing database re-keys. filterID becomes the enabled roster via one EnabledNNSummary(). - HUD: the meta line shows the gate (armed/(trn), last P vs BE, ok/veto tally); the armed/disarmed announcement fires on state change via one latch (MetaGateArmedNow), not only when an entry happens to be proposed. NOT COMPILED - user compiles in MetaEditor. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> |
||
|
AnimateDread
|
1445f175ce |
feat(consistency): the five review flaws fixed - training wears the live constraints, the gate wears the policy
1. Labels and the exit simulator go through the broker's stop-distance check: risk/reward widen to SYMBOL_TRADE_STOPS_LEVEL exactly as TCAdjustStops does at order time - the M5/tight-ATR case where live trades ran wider geometry than training measured. Current stops level stands in for history (like the spread); measured quantity, so it does not key the fingerprint. 2. The Intelligent drift verdict moved into RefreshDriftVerdict(), which RESCANS the label cache and now runs at every era end beside RankTiersFromOos - era-cadence instead of waiting for rare full rebuilds. Prints only on change. 3. Session filter is any-broker: sessions defined on their financial centres' civil clocks (London 08-16 Europe/London, NY 08-17 America/New_York, Tokyo 09-18 Asia/Tokyo), converted to UTC by each centre's own computed DST rule (EU last-Sun-Mar/Oct, US 2nd-Sun-Mar/1st-Sun-Nov), then to broker time by the MEASURED server-vs-GMT offset (half-hour brokers included). Windows may wrap midnight in broker time - the interval test handles it. Replaces the EET-hardcoded anchors, which were correct on exactly one broker and got Tokyo wrong by an hour each European summer. 4. The current-session-table-for-history caveat resolved by analysis: the bars bound the error - a too-late assumed close meets no bars (zero error), a too-early one truncates conservatively (<=1h, never optimistic, cannot manufacture edge). Documented at the site. 5. The ensemble deploy gate mirrors the direction policy: blocked-side fires are not fired bars (certified == traded), the zero-skill reference uses only ACHIEVABLE baselines (always-short is not a strategy a long-only book can run), and one-sidedness BY POLICY is not degeneracy - the two-sided requirement applies only when both sides are allowed. Sell predictions keep their other jobs (exit triggers, consensus dilution) untouched. NOT COMPILED - user compiles in MetaEditor. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> |
||
|
AnimateDread
|
b63e39f026 |
refactor(time): broker time throughout - and the GMT DB basis was already a live bug
User decision: "stick to the broker's time throughout the codebase and analysis, session filter, programmed close time etc". Investigation found the GMT choice was not just inconsistent but broken: live journaling stamped DB rows with TimeGMT() while the online-learning backfill stamped them with BAR time (server) - two clocks ~3h apart in the same column. The newest-row duplicate guard compares them on one axis, so a live row landing within the offset after a backfill row was silently rejected as "outdated". dbVersion 3.0 -> 4.0 wipes the Signals store: the only honest reset for a mixed-basis corpus. - Direction()'s clock (stamps every journaled row, keys the per-second vote window): TimeGMT -> TimeCurrent, variables renamed so the name cannot lie about the basis. - UpdateSignalsWeights' future-row bound: same clock as the rows. - Session filter: broker-time anchors (London 10-18, NY 15-23:59, Tokyo 2-11). The GMT anchors were backwards for an EET-family broker - such a broker follows European DST, so London is DST-STABLE in broker time and moved twice a year in GMT. Tokyo drifts 1h each European summer (no DST to track) - accepted, smallest error on offer. Also fixed: inTimeInterval ignored its datetime parameter and called TimeGMT fresh - a dead parameter hiding a hardwired clock. - MetaCorpus/SignalMETA: rows pre-4.0 are GMT, broker since; the GMT->server offset scan is KEPT because it measures rather than assumes - it pins 0 on new corpora and still resolves old ones. - AltDataFetch deliberately stays on GMT: FRED/COT/EIA release schedules are external UTC-anchored events; the as-of join maps them onto server bars downstream. NOT COMPILED - user compiles in MetaEditor. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> |
||
|
AnimateDread
|
1a46dfdad9 |
feat(sessions): market-hours entry gate + "Market close" close-all option, both live from the symbol's session table
Two user requests, one authority: SymbolInfoSessionTrade, read fresh on every call so DST and per-symbol schedule changes track themselves. - WarriorMarketOpenNow(): CheckOpenPosition refuses entries outside the symbol's trading sessions (Sunday reopen, index CFDs' daily breaks) - a vote can no longer fire into a closed book and collect a broker error. ENTRIES ONLY: exits, SL/TP and the scheduled close-all stay unguarded - closing risk must never be blocked by a session boundary. - CH_MARKET_CLOSE = 24 (appended, .set-safe): the close-all fires "Close-all minute" minutes before that day's LAST session close. Friday + Market close + xxH05 = flatten 5 minutes before Friday's actual close. Resolved identically in three places: the live executor (CExpertCustom::OnTick), the label walk's vertical barrier (NextScheduledCloseAll - the symbol's CURRENT table stands in for history; MT5 keeps none, and a fixed hour is wrong by more), and the fingerprint (the |CUT: token already carries hour=24, so switching to the dynamic mode re-keys the model exactly like any schedule change). Training itself is deliberately NOT gated on market hours: weekend compute is free and labels only ever exist on real bars - what the session table gates is order placement and, via the close-all barrier, what the labels may count as holdable. NOT COMPILED - user compiles in MetaEditor. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> |
||
|
AnimateDread
|
b43b676239 |
feat(fingerprint): an active close-all schedule keys the model identity
The schedule became part of the label's meaning (
|
||
|
AnimateDread
|
3e467f92e9 |
feat(labels): the scheduled close-all is now a vertical barrier in the label walk
User report: "I exit everything on Friday close to avoid weekend swap... if the NN training thinks I hold over the weekend it could produce inaccurate results" - it thought exactly that. TripleBarrierLabel walked its full horizon (64 bars, mean lifespan ~18 H4 bars ~ 3 days) straight through the scheduled flat, scoring trades the deployed EA is guaranteed to have closed on Friday 23:45. SQX applies this rule when building strategies; the EA's own labels did not. NextScheduledCloseAll() mirrors CExpertCustom::OnTick's live check exactly (same three inputs, same -1 disabled sentinels, same CLOSE_EVERYDAY semantics, same server clock). The walk stops at the first bar that does not END by the cutoff - OHLC cannot order the tradable fraction of a partial bar, and ties go to the refusal, as everywhere in this file. An unresolved trade at the cutoff times out to Neutral, exactly as live would flatten it. Excursions, the first-passage ladder and the label lifespan truncate with the walk, so the DERIVED geometry is automatically sized to the tradable window - a target the flat rule never lets price reach stops counting as reachable. The prebuild census now splits timeouts: "horizon too short?" vs "ended by the scheduled close-all" - different questions, different fixes. Schedule disabled = no cutoff, exactly like live. Models trained under weekend-blind labels are fitted to a different target; charts with the close-all enabled (the default) should be reset to retrain under the honest labels. NOT COMPILED - user compiles in MetaEditor. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> |
||
|
AnimateDread
|
348492fb3b |
feat(direction): INTELLIGENT trade direction - the measured drift picks the side(s)
SQX EdgeFinder precedent (user request): adjust for the drift instead of fighting it. The 2026-08-19 telemetry found the models leaning SHORT (Buy recall 21% vs Sell 40%) against a long-favored market (always-long 34.3% vs always-short 29.5% at the adopted geometry). TRADING_DIRECTION gains INTELLIGENT = 3 (appended, explicit value, .set-safe). It resolves at runtime from the label cache's per-side win rates - the Buy/Sell shares ARE the win rates of taking every bar long/short at the REAL stop/target with spread charged. A side is dropped only when BOTH hold: the drift gap clears 2 combined SEs on the overlap-deflated effective sample (EffectiveSampleSize - labels overlap ~18x), AND the weaker side sits below cost-adjusted break-even (a side that still clears costs is kept; drift tilt alone is not a reason to refuse a profitable side). Fails open to BOTH: unmeasured, tiny effective n (<30), insignificant gap, or classic-only charts (no label cache). One resolution point - WarriorEffectiveDirection() - feeds all three gates so they cannot drift apart: CheckOpenLong/Short (live entries), the filtered-view sweep (a blocked side falls into the delete branch, mirroring live), and the vote HUD's "-> TRADE" verdict. The verdict re-derives at every label-cache rebuild, prints only on change, and is computed even when the input is not Intelligent (marked informational). NOT COMPILED - user compiles in MetaEditor. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> |
||
|
AnimateDread
|
cf9a9395ee |
fix(hud): the headline word is the DECISION, not the lean
"VOTE BUY 5.9%" against a 25% bar read as an ensemble that is permanently long, when it is an ensemble that would trade nothing - one member voting BUY at weight 7 against three flats owned the word all day (reported 2026-08-19, screenshot). With the per-member lines now showing each model's individual leaning, the top line says what the bot would DO: BUY/SELL only at or above Min_Vote_Open, NEUTRAL below it (including the all-flat read), "--" only when nobody has a decision. The lean survives as a SIGNED percentage (+ buy side / - sell side). NOT COMPILED - user compiles in MetaEditor. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> |
||
|
AnimateDread
|
b55880c57d |
fix(hud): sign-mismatch warning in the display-forward throttle
age is a uint tick delta; the ternary picking DISPLAY_FWD_ERA_MS vs DISPLAY_FWD_MIN_MS is a runtime int expression the compiler cannot constant-fold (unlike the bare-literal comparisons elsewhere), so the comparison warned. The defines now carry the (uint) cast. NOT COMPILED - user compiles in MetaEditor. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> |
||
|
AnimateDread
|
f30e342a1d |
feat(logs): throttle the settled per-era diagnostics - measured 22MB/9.5h of confirmed-working systems
Measured from the journal (2026-08-19): the era deep-dive line (~2KB) plus the excursion verdict, tier re-rank, calibration move, barrier hold and selection-regressed note each printed EVERY era for EVERY member - ~940 eras/member/day - long after the systems they watch were confirmed working. Yesterday's file was 1.3GB (70% of it the news-filter calendar spam the sweep fix already removed). VerboseMode returns as an INPUT (demoted 2026-08-01 for the marketplace; that track is dead since the 2026-08-16 pivot) and gains a second job: false throttles each settled per-era print to eras 0-3 plus every TRAIN_LOG_EVERY_ERAS-th (25 ~= one deep-dive per ~15min per member); true restores the per-era firehose, flippable live. Never throttled: anything that marks a CHANGE - new bests, restores + eta decays, plateau stage transitions, deploy approvals, warnings, errors, the label-cache/adoption one-shots, and the combined-vote gate line (the active system's primary telemetry, still every era). Semantic fixes over blanket gating: - barrier hold now ARMS silently and prints only when the hold outlasts the 2-min report interval - a brief hold every era is the design, the long hold is the watchdog case the line exists for; - the ensemble deploy REFUSAL prints immediately when its reason changes (that is a finding), on cadence when unchanged; - the filtered-view census prints when its RESULT moves (drawn count, or strongest vote by >=2pp) and at least every 10th sweep. NOT COMPILED - user compiles in MetaEditor. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> |
||
|
AnimateDread
|
83ae56cc9e |
feat(hud): per-member neuron lines + a vote label that moves as the nets learn
Both 2026-08-19 reports were the same staleness: every source behind the label was an ERA artifact (live cache refills at pass-3 completion, the snapshot copies once per era, dPrevSignal is the frozen purge-band edge bar) - so the readout stepped at era cadence at best, stayed glued to one direction, and lagged the era counter. DisplayInference(): throttled (4s, 1s across an era boundary), SIDE-EFFECT-FREE forward of the current decision bar (window ending on bar 1, same question the live path asks) through the LEARNER net. Batch-norm running stats are bracketed frozen/RESTORED via the new CNet::GetBatchNormFrozen() + CNeuronBatchNormOCL::StatsFrozen() - restore, not unfreeze, because a display tick can land between pass-3 chunks whose whole scan holds them frozen. Writes nothing a trading or training path reads (dPrevSignal, NMS state, tallies, watermarks all untouched; RefreshLatestSignal is not reusable here precisely because it writes all of them). LSTM safe by construction: h/c zeroed per forward. ProspectiveVote() reads the fresh forward as its FIRST source; the era-artifact chain becomes the fallback (meta head, warm-up, window holes). DisplayHudLine(): the reference library's training label, per ensemble member - name, output activations (softmax probs or raw scalar), the decision, its weighted vote (the exact consensus numerator term), era, recent average error, "(trn)" while not vote-capable. Rendered under the vote line in RefreshVoteReadout BEFORE the live-vote defer (member lines are telemetry, not tradable readings), coloured by the member's own direction in muted tones - the vote line's strict green-only-when-it-would-trade rule is untouched. NOT COMPILED - user compiles in MetaEditor. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> |
||
|
AnimateDread
|
c85bd9f516 |
feat(inputs): 5-point vote-threshold steps below 50 - the consensus rungs sit between the old 10s
Under CONSENSUS arithmetic the vote is quantized by agreement: with four members at pooled tier weights ~29, unanimity reads ~29, 3-of-4 ~22, 2-of-4 ~14.5. The 10-point dropdown straddled every one of those rungs - 20 admitted 3-of-4, 30 admitted nothing - so the thresholds an operator actually wants (between rungs, e.g. 25 = "unanimity or a top-tier 3-of-4") did not exist. PERCENTAGE_PRESETS and VOTE_CLOSE_PRESETS both gain 5/15/25/35/45; members are only ever ADDED (explicit values, .set-safe), never removed - MT5 does not validate saved enum values. Min_Vote_Open default 40 -> 25: the 40 was priced under union arithmetic and now sits above the unanimity ceiling (~29), i.e. a fresh attach would silently never trade - the same fired-on-0-bars defect the 50 -> 40 move fixed once already. NOT COMPILED - user compiles in MetaEditor. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> |
||
|
AnimateDread
|
1a900a0a35 |
feat(vote): CONSENSUS arithmetic - agreement is now what the threshold dials
Era-680 report, all three observations one equation: "peak 29, no arrows at
threshold 30" / "at 20, arrows on EVERY bar" / "label at 12 while arrows
everywhere". Under the voters-only divisor, any bar with at least one
directional voter read the weighted mean of the firing tiers' weights - and
once the tiers self-ranked to each model's pooled win rate (~28-31), that
mean was NEAR-CONSTANT regardless of headcount. One member alone: ~29. Four
unanimous: ~29. Min_Vote_Open was a step function around that constant -
above it nothing ever fired, below it everything did - and the label's 12
was a 3v1 split netting through the same divisor. Not three display bugs:
one arithmetic that could not express agreement.
The divisor is now the CAPABLE weight - every filter that could vote,
whether it did or not:
* live (Direction): VoteCapableWeight() - classic pattern ladders always,
veto filters never, AI members once past the same readiness test
LongCondition gates on. A model still training must not dilute an
ensemble it cannot join: four trainees + one deployed model is a solo
chart wearing an ensemble label, and the solo vote reads full strength.
* gate (EnsembleEraVerdict): g_ensVoteWeightSum accumulates for every
member that EVALUATED the bar, Neutral included.
* overlay sweep + prospective readout: weight counts whenever the member
has data; a snapshotted Neutral dilutes.
One arithmetic, four sites, same numbers everywhere.
What the numbers become (four members, w~0.29, tiers~29): unanimous ~29 -
the CEILING, which is the pooled win rate and is what the peak displays;
3-of-4 ~22; 2-of-4 ~14.5; 3v1 ~14.5. Min_Vote_Open 20 now means "roughly
three-quarters of the ensemble's trust agrees, net". It MUST sit below the
ceiling to ever fire - the census/peak states the ceiling.
This is the ensemble the user specified in the original design discussion
("if the perceptron also votes, both together reach the threshold; if
another NN votes the other side, the threshold is not reached") - union
semantics was the pre-ensemble behaviour, kept until measurement showed its
vote magnitude was a constant.
Plus overlay DECLUSTERING, the other half of "arrows on every bar": the
same three NMS rules as the per-member arrows (same-direction runs collapse
to their first bar, cross-direction flicker keeps the stronger side), online
over the sweep's strictly oldest->newest walk. Suppression is a verdict and
deletes a standing arrow; the den==0 no-data skip still never does.
NOT COMPILED - user compiles in MetaEditor.
Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
|
||
|
AnimateDread
|
c393497fd6 |
fix(chart): display now reads era-end SNAPSHOTS - the live cache is wiped mid-era
Full-pipeline analysis after "threshold 30, attained often, nothing drawn,
still glued to buy". The log falsified the premise before any code did:
21:40:43 swept 4999, 794 voters, drew 491. Strongest 43.0% vs 30.0%
21:42:07 swept 4999, 0 voters, drew 0
21:51:30 swept 4999, 0 voters, drew 0
21:56:30 swept 4999, 922 voters, drew 382. Strongest 44.0% vs 30.0%
The arrows WERE drawn - 491 of them, then 382 - and then erased. ONE root
cause, three symptoms: every display path read m_arrowSignalCache, which is
wiped to sentinel at each era start and only complete again when pass 3
finishes. With eras at ~30s and a sweep at ~17s:
* ARROW FLICKER: a sweep landing mid-era found no voters anywhere, and its
else-branch deleted the arrow on every voteless bar - erasing the previous
sweep's entire output. The chart cycled populated -> blank -> populated;
the user kept catching the blank phase.
* READOUT GLUE: the newest-cache walk found only sentinel for ~90% of every
era and fell through to dPrevSignal - the frozen purge-band edge bar that
reads Buy.
|
||
|
AnimateDread
|
659638e072 |
fix(chart): the prospective vote was four models' opinion of ONE frozen bar
"Still glued to buy." Verified in the pass structure rather than guessed: dPrevSignal is written ONLY by pass 1 (Training.mqh 1439/1442 - the sole assignment sites), and pass 1 SKIPS the feedForward for any bar a later pass will forward anyway (laterPassForwards) - which is the whole OOS window and the calibration band. Pass 3 forwards the newest bars every era but never writes dPrevSignal. Net effect: after every era, dPrevSignal holds the model's opinion of the newest PURGE-BAND EDGE BAR pass 1 happened to forward - one fixed mid-history bar, re-evaluated era after era. The readout was therefore showing four models' verdict on the same frozen bar, and that bar reads Buy. Glued to Buy, with flashes of Sell only while pass 1 was actively walking (the one window where dPrevSignal moves). ProspectiveVote() now reads the newest ARROW-CACHE entry first (walking back from the decision bar, bounded at 16), falling back to dPrevSignal only when the cache holds nothing. Pass 3 writes the adjusted decision for the newest (OOS) bars each era, so the cache's first non-sentinel entry is the model's most recent verdict on near-current data - and it is the same value the filtered overlay draws from, so the label and the reconstruction stay one quantity. A cached Neutral stops the walk: that is a real decision (vote 0, abstain -> shows in the "flat" count), not a missing one. Early in an era the cache is wiped to sentinel and everything falls through to dPrevSignal exactly as before, until pass 3 refills the newest rows. Expect the label to change per era now (as each pass 3 re-scores the newest bars under that era's weights), with the vote/flat split moving as members genuinely flip between direction and Neutral on recent data. NOT COMPILED - user compiles in MetaEditor. Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com> |
||
|
AnimateDread
|
4f2d81a52e |
fix(chart): sweep hammered the news filter; peak was a fossil; neutrals invisible
Careful read of the 21:14 log window (user report: peak stuck at 50, label sticky, neutrals never shown). Three distinct defects, one commit because they share the two files. 1. 15,508 "CalendarValueHistory failed" lines in 68 SECONDS - ~230/second. The overlay sweep replayed Direction() on EVERY non-AI filter, including the news/session/risk-guard veto filters. The news filter calls CalendarValueHistory per evaluation and MT5's calendar cannot answer more than ~30 days back (the known calendar cliff), so every historical bar logged a failure - real wall-clock burned inside a sweep whose whole point is to stay cheap. Veto filters keep m_pattern_count at its 0 default (the same test UpdateSignalsWeights keys on): they cast no weighted vote, and a prohibition cannot be reconstructed faithfully anyway - it joins order validation in the cannot-replay family. Skipped. Compounding it: at era ~200 the four members complete a barrier round every ~20s while a full 5,000-bar sweep takes ~17s of slices - the sweep finished and instantly re-armed, forever, against arrow caches half-rebuilt mid-era. That is why the census's "had a voter" flapped 1299 -> 257 -> 1113 across three back-to-back sweeps. Re-arms now rate-limited to one per 5 minutes. 2. Peak 50 was a FOSSIL. m_votePeak never reset, so it still held a value attained under the 25/50/75/100 DEFAULT tier weights from the attach window before the first re-rank - unreachable ever since the weights became measured (pooled 27-32 in the same log). A ceiling nothing can reach reads as "the models are underperforming their own history", which is backwards: the history was priced in different money. The peak now resets at the same regime boundary as the census (StartFilteredOverlay), and the label shows max(live peak, census strongest-vote) - the census number is the actual answer to "can Min_Vote_Open ever be reached", measured over ~5,000 bars under the CURRENT weights. 3. Neutrals were invisible. The prospective count lumped Neutral-deciding models in with voters, so "4 model(s)" read identically whether all four voted or three sat flat. Now "2 vote/2 flat", and an all-neutral bar reads "VOTE flat ... 0 vote/4 flat" instead of "--" - the models answered, and the answer was Neutral. Expected values, from this log's own re-ranks (all four members' fires land in T3; tier weights 27-32; module weights 0.27-0.32): a unanimous-buy bar reads ~29-30%, mixed membership 28-34. The reported "stuck at buy 28, climbed to 30, flashes of sell, now 33.4" is those weights doing exactly what they should. The stickiness between moves is pass 2/2.5/3 - only pass 1 writes dPrevSignal, so the label holds the last pass-1 bar's decision for the remainder of each era. Display-only, and honest: it is the model's most recent output. NOT COMPILED - user compiles in MetaEditor. Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com> |
||
|
AnimateDread
|
b05b4f21d7 |
fix(chart): the vote readout was repainted once per bar, not once per timer tick
"Still stuck at 0" after |
||
|
AnimateDread
|
a042cb4359 |
feat(chart): show the PROSPECTIVE vote while the models are still training
The readout sat at "VOTE 0.0%, 0 voters" constantly. Correct, and useless.
LongCondition()/ShortCondition() return 0 behind the readiness gate for the
entire training run - a model that is not deployed does not vote - so the LIVE
vote is structurally zero for hours, which is exactly the period the readout
is being watched. Worse, it was the same display whether the models were
silent, undeployed, or the filter list was empty: three different situations,
one number.
When no filter casts a real vote, the readout now shows the PROSPECTIVE one -
what these models are saying right now, through the identical tier/weight
arithmetic, minus the readiness gate. That is the same quantity the historical
overlay reconstructs on cached bars, deliberately, so the live line and the
reconstructed arrows are the same measure and can be read against each other.
It can never be mistaken for a decision: labelled "-> training, not tradable
yet", drawn dimmer than "no trade", and `fires` is forced false regardless of
magnitude, because saying "-> TRADE" about a number that cannot place an order
is the precise overstatement this readout exists to prevent. m_direction is
untouched - display only, no trading path reads it.
Confirms the sweep fix from
|