forked from LengKundee/MQL5-Google-Onedrive
cee78864d6
This commit implements several performance optimizations in the SMC MTF indicator: 1. Robust Early Exit: Added a 'new bar' check using iTime() to skip redundant calculations on every price tick. Handled prev_calculated=0 to ensure full history recalculations when requested. 2. Lazy Loading: Wrapped expensive fractal and Donchian calculations in conditional blocks so they only execute if the respective features are enabled. 3. Efficient Buffer Clearing: Replaced manual O(N) loops with ArrayInitialize() for bulk clearing of indicator buffers on first run. 4. Robustness: Added 'history not ready' checks (iTime == 0) to both the indicator and EA. 5. Cleanup: Removed redundant ArraySetAsSeries calls on static arrays in GetMTFDir and updated comments. Impact: Reduces CPU usage on every tick by skipping unnecessary logic and improves initialization speed during history loading. Co-authored-by: Mouy-leng <199350297+Mouy-leng@users.noreply.github.com>
24 lines
2.6 KiB
Markdown
24 lines
2.6 KiB
Markdown
# Bolt's Journal ⚡
|
|
|
|
This journal is for CRITICAL, non-routine performance learnings ONLY.
|
|
|
|
- Codebase-specific bottlenecks
|
|
- Failed optimizations (and why)
|
|
- Surprising performance patterns
|
|
- Rejected changes with valuable lessons
|
|
|
|
## 2024-07-25 - MQL5 Native Functions vs. Scripted Loops
|
|
**Learning:** My assumption that a manual MQL5 loop over a pre-cached array would be faster than built-in functions like `iHighest()` and `iLowest()` was incorrect. The code review pointed out that MQL5's native, built-in functions are implemented in highly optimized C++ and are significantly faster than loops executed in the MQL5 scripting layer. The original comment stating this was correct.
|
|
**Action:** Always prefer using MQL5's built-in, native functions for calculations like finding highs/lows over manual loops, even if the data is already in a local array. The performance gain from the native implementation outweighs the overhead of the function call.
|
|
|
|
## 2024-07-26 - Native ArrayMaximum/ArrayMinimum Efficiency
|
|
**Learning:** Confirmed that native `ArrayMaximum()` and `ArrayMinimum()` are the preferred way to find extreme values in price arrays. Also, when using these functions, it's important to check if they return `-1` to avoid invalid array access, especially if the `count` or `start` parameters might be dynamic.
|
|
**Action:** When replacing manual loops with native array functions, always include a check for the `-1` return value to ensure robustness while gaining performance.
|
|
|
|
## 2026-01-19 - Native Object Cleanup in MQL5
|
|
**Learning:** While iterating through chart objects manually is flexible, it becomes a major bottleneck if the chart has thousands of objects. For simple prefix-based cleanup (often used in indicators), the native `ObjectsDeleteAll(0, prefix)` is significantly more efficient than a scripted loop calling `ObjectName()` and `StringFind()` for every object on the chart.
|
|
**Action:** Use `ObjectsDeleteAll()` for bulk object removal by prefix whenever the "keep N latest" logic is not strictly required or can be safely bypassed for performance.
|
|
|
|
## 2026-01-20 - Robust New Bar Check in MQL5 OnCalculate
|
|
**Learning:** An early exit in `OnCalculate` based on bar time MUST check `prev_calculated > 0`. If `prev_calculated == 0`, the terminal is requesting a full recalculation (e.g., after a history sync or data gap fill), and exiting early would result in stale data. Also, using `iTime()` is more robust than indexing into the `time[]` array if the array's series state is unknown.
|
|
**Action:** Always wrap "new bar" early exits in indicators with `if(prev_calculated > 0 && ...)` and prefer `iTime()` for the current bar's timestamp.
|