feat: add new indicators (Decay, Edecay, MinusDi, MinusDm, PlusDi, PlusDm, Maxindex, Minindex, Sarext) and update pine scripts, core libs, validation tests, and python bindings
2026-03-09 13:45:46 -07:00
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// Licensed under the Apache License, Version 2.0
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2026-01-18 19:02:03 -08:00
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// © mihakralj
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//@version=6
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indicator("Min-Max Normalization (NORMALIZE)", "NORMALIZE", overlay=false, precision=6)
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//@function Normalizes a source series to the fixed range [0, 1] using Min-Max scaling over a lookback period.
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//@param src The source series to normalize.
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//@param len The lookback period to determine min and max values. Must be >= 1.
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//@returns The normalized series (scaled to [0, 1]).
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normalize(series float src, simple int len) =>
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float min_val_in_period = src
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float max_val_in_period = src
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for i = 1 to len - 1
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current_val = src[i]
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if na(current_val)
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continue
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if current_val < min_val_in_period
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min_val_in_period := current_val
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if current_val > max_val_in_period
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max_val_in_period := current_val
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range_val = max_val_in_period - min_val_in_period
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normalized_value = 0.0
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if range_val != 0.0 and not na(range_val)
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normalized_value := (src - min_val_in_period) / range_val
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normalized_value
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// ---------- Main loop ----------
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// Inputs
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i_source = input.source(close, "Source")
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i_length = input.int(200, "Lookback Length", minval=1, tooltip="Lookback period for finding min/max. Must be >= 1.")
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// Calculation
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normalizedValue = normalize(i_source, i_length)
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// Plot
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plot(normalizedValue, "Normalized Value [0,1]", color=color.yellow, linewidth=2)
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