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Refactor documentation to remove "Zero-Allocation Design" sections across various trend indicators and implement a PowerShell script for automated cleanup
- Updated mathematical foundations and performance profiles where necessary to maintain clarity and coherence.
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@@ -44,19 +44,6 @@ Where $e_n$ is the output of the $n$-th EMA in the cascade.
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Despite the complexity, T3 is O(1).
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### Zero-Allocation Design
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QuanTAlib implements T3 using a single `State` struct that holds the values of all 6 EMAs. This avoids creating 6 separate `Ema` objects and eliminates heap allocations.
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| Metric | Score | Notes |
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| :--- | :--- | :--- |
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| **Throughput** | Moderate | 6 EMAs |
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| **Complexity** | O(1) | Constant time update |
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| **Accuracy** | 8/10 | Very smooth, organic curve |
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| **Timeliness** | 7/10 | Lag depends heavily on 'v' factor |
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| **Overshoot** | 6/10 | Can overshoot if v > 0.7 |
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| **Smoothness** | 10/10 | One of the smoothest filters available |
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## Validation
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Validated against TA-Lib and Skender.Stock.Indicators.
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