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refactor: Unified MTF Engine Pattern

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Indicators/MyIndicators/VIDYA_MTF_Pro.md
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## 1. Summary (Introduction)
The Variable Index Dynamic Average (VIDYA) MTF Pro is a multi-timeframe (MTF) version of the classic adaptive moving average developed by Tushar Chande. This indicator calculates the VIDYA on a **higher, user-selected timeframe** and projects it onto the current, lower-timeframe chart.
The `VIDYA_MTF_Pro` is a multi-timeframe (MTF) version of Tushar Chande's adaptive moving average. It projects the VIDYA from a **higher, user-selected timeframe** onto the current chart.
This allows traders to visualize the underlying trend from a broader perspective, using the higher-timeframe VIDYA as a dynamic benchmark for support, resistance, and overall market direction, all without leaving their primary trading chart.
The VIDYA adapts its speed based on the market's volatility (measured by the Chande Momentum Oscillator - CMO), making it an excellent tool for identifying the "true" trend of the higher timeframe.
The indicator is highly versatile: if the user selects the current chart's timeframe, it functions identically to the standard `VIDYA_Pro` indicator. It also fully supports both **standard** and **Heikin Ashi** price data.
## 2. Mathematical Foundations
## 2. Mathematical Foundations and Calculation Logic
The calculation combines an EMA with a volatility index:
The underlying calculation is identical to the standard VIDYA. It is a modified Exponential Moving Average where the smoothing factor is multiplied by the absolute value of the Chande Momentum Oscillator (CMO).
### Required Components
* **EMA Period (N):** The base period for the EMA smoothing calculation.
* **CMO Period (M):** The lookback period for the Chande Momentum Oscillator.
* **Source Price (P):** The price series from the **higher timeframe** used for the calculation.
### Calculation Steps (Algorithm)
1. **Fetch Higher Timeframe Data:** The indicator first retrieves the OHLC price data for the user-selected higher timeframe.
2. **Calculate the Chande Momentum Oscillator (CMO):** The CMO is calculated on the higher timeframe's price data over a period `M`.
$\text{CMO}_{htf} = \frac{\text{Sum Up}_{htf} - \text{Sum Down}_{htf}}{\text{Sum Up}_{htf} + \text{Sum Down}_{htf}}$
3. **Calculate the VIDYA on the Higher Timeframe:** The VIDYA is calculated recursively using the higher timeframe data.
* $\alpha = \frac{2}{N + 1}$
* $\text{VIDYA}_{htf_i} = (P_{htf_i} \times \alpha \times \text{Abs}(\text{CMO}_{htf_i})) + (\text{VIDYA}_{htf_{i-1}} \times (1 - \alpha \times \text{Abs}(\text{CMO}_{htf_i})))$
4. **Project to Current Chart:** The calculated higher-timeframe VIDYA values are then mapped to the current chart, creating a "step-like" line where each value from the higher timeframe is held constant for the duration of its corresponding bars on the lower timeframe.
1. **CMO:** Calculated on the higher timeframe to measure momentum/volatility.
2. **Alpha:** The smoothing factor is dynamically adjusted: $\alpha = \frac{2}{N+1} \times |CMO|$.
3. **VIDYA:** The recursive formula is applied to the higher timeframe data.
## 3. MQL5 Implementation Details
* **Self-Contained and Robust:** This indicator is fully self-contained and does not depend on any external indicator files (`iCustom`). It directly fetches the required higher-timeframe price data using built-in `Copy...` functions for maximum stability.
* **Self-Contained:** Uses direct `Copy...` functions; no external dependencies.
* **Modular Engine (`VIDYA_Calculator.mqh`):** Reuses the standard VIDYA logic.
* **Modular Calculation Engine (`VIDYA_Calculator.mqh`):** The indicator reuses the exact same, proven calculation engine as the standard `VIDYA_Pro`. This ensures mathematical consistency and leverages our modular design principles.
* **Optimized Incremental Calculation:**
Unlike basic MTF indicators that download and recalculate the entire higher-timeframe history on every tick, this indicator employs a sophisticated incremental algorithm.
* **HTF State Tracking:** It tracks the calculation state of the higher timeframe separately (`htf_prev_calculated`).
* **Persistent Buffers:** The internal buffer for the higher timeframe (`BufferVIDYA_HTF_Internal`) is maintained globally, preserving the recursive state of the VIDYA algorithm between ticks.
* **Efficient Mapping:** The projection loop only updates the bars corresponding to the new data, drastically reducing CPU usage.
* This results in **O(1) complexity** per tick, ensuring the indicator remains lightweight even when running on multiple charts simultaneously.
* **Dual-Mode Logic:** The `OnCalculate` function contains a smart branching logic.
* If a higher timeframe is selected, it performs the optimized MTF data fetching and projection process.
* If the current timeframe is selected, it bypasses the MTF logic and functions identically to the standard `VIDYA_Pro`, calculating directly on the current chart's data for maximum efficiency.
* **Optimized Incremental Calculation (O(1)):**
* **HTF State Tracking:** Tracks `htf_prev_calculated` to process only new bars on the higher timeframe.
* **Persistent State:** The internal VIDYA buffer preserves the recursive value from the previous calculation step.
* **Smart Mapping:** Projects the values to the current chart efficiently, handling the index alignment between timeframes correctly.
## 4. Parameters
* **Upper Timeframe (`InpUpperTimeframe`):** The higher timeframe on which the VIDYA will be calculated. If set to `PERIOD_CURRENT`, the indicator will run on the current chart's timeframe.
* **CMO Period (`InpPeriodCMO`):** The lookback period for the Chande Momentum Oscillator. Default is `9`.
* **EMA Period (`InpPeriodEMA`):** The base period for the EMA smoothing. Default is `12`.
* **Applied Price (`InpSourcePrice`):** The source price for the calculation. This unified dropdown menu allows you to select from all standard and Heikin Ashi price types.
* **Upper Timeframe (`InpUpperTimeframe`):** The calculation timeframe.
* **CMO Period (`InpPeriodCMO`):** Lookback for volatility measurement (Default: `9`).
* **EMA Period (`InpPeriodEMA`):** Base smoothing period (Default: `12`).
* **Applied Price (`InpSourcePrice`):** Standard or Heikin Ashi.
## 5. Usage and Interpretation
The MTF version of VIDYA opens up new strategic possibilities beyond simple trend following.
* **Dynamic Support and Resistance:** The primary use of the MTF VIDYA is as a dynamic, high-level area of support and resistance. When the price on the lower timeframe pulls back to the higher-timeframe VIDYA line, it can present a high-probability entry point in the direction of the larger trend.
* **Major Trend Filter:** The slope and position of the MTF VIDYA line provide a clear, smoothed-out view of the dominant trend.
* If the price is consistently above a rising MTF VIDYA, the market is in a strong uptrend. Traders should focus on buying opportunities.
* If the price is consistently below a falling MTF VIDYA, the market is in a strong downtrend. Traders should focus on selling opportunities.
* **Confirmation of Breakouts:** A breakout on the lower timeframe that is also supported by the direction of the MTF VIDYA line is a much stronger signal.
* **Range Detection:** A flat MTF VIDYA line indicates that the higher timeframe is consolidating, signaling that range-bound strategies might be more appropriate on the lower timeframe.
* **Trend Filter:** Price above MTF VIDYA = Bullish bias; Price below = Bearish bias.
* **Flat Line:** A flat MTF VIDYA indicates low volatility and consolidation on the higher timeframe.
* **Support/Resistance:** Due to its adaptive nature, the MTF VIDYA often hugs price action closely during trends, providing accurate dynamic support levels.