forked from animatedread/Warrior_EA
e9c562b39f
- Introduced `FeatureScale.mqh` with `FeatSquash` function for stateless feature scaling. - Added `RegimeMath.mqh` class for regime arithmetic, including efficiency and variance calculations. - Documented the Mind trading logic in `MIND.md`, detailing the trading process and modes. - Created `VOLNORM_PLAN.md` and `VOLNORM_RESULTS.md` for tick-volume normalization testing. - Implemented `read_book.py` for analyzing trade book data and correlations. - Developed `volnorm.py` for testing tick-volume normalization with new and old methods.
41 lines
1.7 KiB
MQL5
41 lines
1.7 KiB
MQL5
//+------------------------------------------------------------------+
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//| ModalityCalendar.mqh |
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//| AnimateDread |
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//| |
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//| WHEN IT IS. Day of week, hour, day of month and days to month end |
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//| of the signal bar (broker time, the same clock the bars carry). |
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//| Turn-of-month and weekday effects are the calendar edges equity |
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//| indices are known for; recorded so the journal can say whether |
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//| this book's dips behave differently on them. |
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//+------------------------------------------------------------------+
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#ifndef WARRIOR_MODALITYCALENDAR_MQH
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#define WARRIOR_MODALITYCALENDAR_MQH
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#include "Modality.mqh"
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class CModalityCalendar : public CModality
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{
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public:
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virtual string Name(void) const override { return "calendar"; }
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virtual bool Read(const SBarRef &bar, SMarketContext &ctx) override
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{
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MqlDateTime t;
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TimeToStruct(bar.time, t);
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//--- Days to month end from the calendar itself, so leap years need no table.
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MqlDateTime today = t, next = t;
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today.hour = today.min = today.sec = 0;
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next.hour = next.min = next.sec = 0;
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next.day = 1;
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if(++next.mon > 12)
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{
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next.mon = 1;
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next.year++;
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}
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ctx.v[CTX_DOW] = t.day_of_week;
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ctx.v[CTX_HOUR] = t.hour;
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ctx.v[CTX_DOM] = t.day;
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ctx.v[CTX_TO_MONTH_END] = (double)((StructToTime(next) - StructToTime(today)) / 86400) - 1.0;
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return true;
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}
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};
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#endif // WARRIOR_MODALITYCALENDAR_MQH
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