mirror of
https://github.com/mihakralj/QuanTAlib.git
synced 2026-08-01 03:07:43 +00:00
Miha Kralj
58 lines
1.9 KiB
Plaintext
58 lines
1.9 KiB
Plaintext
// Licensed under the Apache License, Version 2.0
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// © mihakralj
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//@version=6
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indicator("Blackman Moving Average (BLMA)", "BLMA", overlay=true)
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//@function Calculates BLMA using Blackman window weighting
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//@param source Series to calculate BLMA from
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//@param period Lookback period - FIR window size
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//@returns BLMA value, calculates from first bar using available data
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//@optimized Uses Blackman window coefficients with O(n) complexity per bar due to lookback loop
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blma(series float source, simple int period) =>
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if period <= 0
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runtime.error("Period must be greater than 0")
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int p = math.min(bar_index + 1, period)
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var array<float> weights = array.new_float(1, 1.0)
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var int last_p = 1
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if last_p != p
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weights := array.new_float(p, 0.0)
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float total_weight = 0.0
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float a0 = 0.42
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float a1 = 0.5
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float a2 = 0.08
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float inv_p_minus_1 = 1.0 / (p - 1)
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float pi2 = 2.0 * math.pi
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float pi4 = 4.0 * math.pi
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for i = 0 to p - 1
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float ratio = i * inv_p_minus_1
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float term1 = a1 * math.cos(pi2 * ratio)
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float term2 = a2 * math.cos(pi4 * ratio)
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float w = a0 - term1 + term2
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array.set(weights, i, w)
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total_weight += w
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float inv_total = 1.0 / total_weight
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for i = 0 to p - 1
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array.set(weights, i, array.get(weights, i) * inv_total)
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last_p := p
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float sum = 0.0
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float weight_sum = 0.0
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for i = 0 to p - 1
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float price = source[i]
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if not na(price)
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float w = array.get(weights, i)
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sum += price * w
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weight_sum += w
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nz(sum / weight_sum, source)
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// ---------- Main loop ----------
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// Inputs
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i_period = input.int(10, "Period", minval=1)
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i_source = input.source(close, "Source")
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// Calculation
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blma_value = blma(i_source, i_period)
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// Plot
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plot(blma_value, "BLMA", color=color.yellow, linewidth=2)
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