SIMD Refactor: Merge simd-dev into dev (#55)

Co-authored-by: Claude Opus 4.5 <noreply@anthropic.com>
Co-authored-by: aider (openrouter/anthropic/claude-sonnet-4) <aider@aider.chat>
Co-authored-by: Warp <agent@warp.dev>

quantower/lib/sdchannel.pine

@@ -0,0 +1,60 @@
+// The MIT License (MIT)
+// © mihakralj
+//@version=6
+indicator("Standard Deviation Channel (SDCHANNEL)", "SDCHANNEL", overlay=true)
+
+//@function Calculates Standard Deviation Channel with lines N standard deviations above and below a linear regression line
+//@param period Lookback period for regression and standard deviation calculation (period > 1)
+//@param source Source series for analysis (usually close)
+//@param multiplier Standard deviation multiplier for channel distance (multiplier > 0)
+//@returns Tuple containing [upper_channel, regression_line, lower_channel]
+//@optimized Uses linear regression with O(n) complexity per bar
+sdchannel(simple int period, series float source = close, simple float multiplier = 2.0) =>
+    if period <= 1
+        runtime.error("Period must be > 1")
+    if multiplier <= 0.0
+        runtime.error("Multiplier must be > 0")
+    float sumX = 0.0
+    float sumY = 0.0
+    float sumXY = 0.0
+    float sumX2 = 0.0
+    for i = 0 to period - 1
+        float x = float(i)
+        float y = source[period - 1 - i]
+        sumX := sumX + x
+        sumY := sumY + y
+        sumXY := sumXY + x * y
+        sumX2 := sumX2 + x * x
+    float n = float(period)
+    float slope = (n * sumXY - sumX * sumY) / (n * sumX2 - sumX * sumX)
+    float intercept = (sumY - slope * sumX) / n
+    float currentX = float(period - 1)
+    float regressionLine = slope * currentX + intercept
+    float sumSquaredResiduals = 0.0
+    for i = 0 to period - 1
+        float x = float(i)
+        float y = source[period - 1 - i]
+        float predicted = slope * x + intercept
+        float residual = y - predicted
+        sumSquaredResiduals := sumSquaredResiduals + residual * residual
+    float stdDev = math.sqrt(sumSquaredResiduals / n)
+    float upperChannel = regressionLine + multiplier * stdDev
+    float lowerChannel = regressionLine - multiplier * stdDev
+    [upperChannel, regressionLine, lowerChannel]
+
+// ---------- Main loop ----------
+
+// Inputs
+i_period = input.int(20, "Period", minval=2)
+i_source = input.source(close, "Source")
+i_multiplier = input.float(2.0, "Standard Deviation Multiplier", minval=0.1, step=0.1)
+
+// Calculation
+[upperLine, midLine, lowerLine] = sdchannel(i_period, i_source, i_multiplier)
+
+// Plot
+p1 = plot(upperLine, "Upper Channel", color=color.yellow, linewidth=2)
+p2 = plot(midLine, "Regression Line", color=color.yellow, linewidth=2)
+p3 = plot(lowerLine, "Lower Channel", color=color.yellow, linewidth=2)
+fill(p1, p2, color=color.new(color.red, 90), title="Upper Fill")
+fill(p2, p3, color=color.new(color.green, 90), title="Lower Fill")