mirror of
https://github.com/mihakralj/QuanTAlib.git
synced 2026-07-28 01:37:43 +00:00
Miha Kralj
59 lines
1.6 KiB
Plaintext
59 lines
1.6 KiB
Plaintext
// The MIT License (MIT)
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// © mihakralj
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//@version=6
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indicator("Rolling Sum", "SUM", overlay=false)
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//@function Calculates Rolling Sum over a period using Kahan-Babuška algorithm
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//@doc Calculates the sum of the last n values with high numerical precision.
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//@doc Uses Kahan-Babuška summation for machine-epsilon accuracy.
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//@param source Series to calculate sum from
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//@param length Number of bars to sum
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//@returns Rolling sum of the last 'length' values
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rolling_sum(series float source, simple int length) =>
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// Persistent state
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var float sum = 0.0
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var float c = 0.0 // First-order compensation
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var float cc = 0.0 // Second-order compensation
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float val = nz(source, 0.0)
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float oldVal = bar_index >= length ? nz(source[length], 0.0) : 0.0
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// Kahan-Babuška subtract old value
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if bar_index >= length
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float yS = -oldVal - c
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float tS = sum + yS
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c := tS - sum - yS
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sum := tS
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float zS = c - cc
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float ttS = sum + zS
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cc := ttS - sum - zS
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sum := ttS
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// Kahan-Babuška add new value
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float yA = val - c
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float tA = sum + yA
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c := tA - sum - yA
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sum := tA
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float zA = c - cc
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float ttA = sum + zA
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cc := ttA - sum - zA
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sum := ttA
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sum
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// ---------- Main loop ----------
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// Inputs
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i_length = input.int(14, "Length", minval=1)
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i_source = input.source(close, "Source")
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// Calculation
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sum_value = rolling_sum(i_source, i_length)
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// Equivalent built-in for comparison (disabled by default)
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// sum_builtin = math.sum(i_source, i_length)
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// Plot
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plot(sum_value, "Sum", color=color.yellow, linewidth=2) |