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Miha Kralj
2025-12-18 13:51:06 -08:00
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lib/trends/alma/Alma.md
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@@ -51,70 +51,6 @@ For the calculation, we use a **RingBuffer** to store the price window. The weig
**Configuration note:** The default combination (Period 9, Offset 0.85, Sigma 6) is widely used as a responsive trend filter.
## C# Usage
### Streaming Updates (Single Instance)
```csharp
using QuanTAlib;
var alma = new Alma(period: 9, offset: 0.85, sigma: 6.0);
// Process each new bar
TValue result = alma.Update(new TValue(timestamp, closePrice));
Console.WriteLine($"ALMA: {result.Value:F2}");
// Check if buffer is full
if (alma.IsHot)
{
// Indicator is fully initialized
}
```
### Batch Processing (Historical Data)
```csharp
// TSeries API (object-oriented)
TSeries prices = ...;
TSeries almaValues = Alma.Batch(prices, period: 9, offset: 0.85, sigma: 6.0);
// High-performance Span API (zero allocation)
double[] prices = new double[10000];
double[] output = new double[10000];
Alma.Calculate(prices.AsSpan(), output.AsSpan(), period: 9, offset: 0.85, sigma: 6.0);
```
### Bar Correction (isNew Parameter)
```csharp
var alma = new Alma(9);
// New bar arrives
alma.Update(new TValue(time, 100.5), isNew: true);
// Intra-bar price updates (real-time tick data)
alma.Update(new TValue(time, 101.0), isNew: false); // Updates current bar
alma.Update(new TValue(time, 100.8), isNew: false); // Updates current bar
// Next bar
alma.Update(new TValue(time + 60, 101.2), isNew: true); // Advances state
```
### Event-Driven Architecture
```csharp
var source = new TSeries();
var alma = new Alma(source, period: 9);
// Subscribe to ALMA output
alma.Pub += (value) => {
Console.WriteLine($"New ALMA value: {value.Value}");
};
// Feeding source automatically triggers the chain
source.Add(new TValue(DateTime.Now, 105.2));
```
## Performance Profile
| Operation | Complexity | Description |
@@ -201,3 +137,67 @@ This implementation makes specific trade-offs:
## References
- Legoux, Arnaud. "ALMA: Arnaud Legoux Moving Average."
## C# Usage
### Streaming Updates (Single Instance)
```csharp
using QuanTAlib;
var alma = new Alma(period: 9, offset: 0.85, sigma: 6.0);
// Process each new bar
TValue result = alma.Update(new TValue(timestamp, closePrice));
Console.WriteLine($"ALMA: {result.Value:F2}");
// Check if buffer is full
if (alma.IsHot)
{
// Indicator is fully initialized
}
```
### Batch Processing (Historical Data)
```csharp
// TSeries API (object-oriented)
TSeries prices = ...;
TSeries almaValues = Alma.Batch(prices, period: 9, offset: 0.85, sigma: 6.0);
// High-performance Span API (zero allocation)
double[] prices = new double[10000];
double[] output = new double[10000];
Alma.Calculate(prices.AsSpan(), output.AsSpan(), period: 9, offset: 0.85, sigma: 6.0);
```
### Bar Correction (isNew Parameter)
```csharp
var alma = new Alma(9);
// New bar arrives
alma.Update(new TValue(time, 100.5), isNew: true);
// Intra-bar price updates (real-time tick data)
alma.Update(new TValue(time, 101.0), isNew: false); // Updates current bar
alma.Update(new TValue(time, 100.8), isNew: false); // Updates current bar
// Next bar
alma.Update(new TValue(time + 60, 101.2), isNew: true); // Advances state
```
### Event-Driven Architecture
```csharp
var source = new TSeries();
var alma = new Alma(source, period: 9);
// Subscribe to ALMA output
alma.Pub += (value) => {
Console.WriteLine($"New ALMA value: {value.Value}");
};
// Feeding source automatically triggers the chain
source.Add(new TValue(DateTime.Now, 105.2));
```