// Licensed under the Apache License, Version 2.0
// © mihakralj
//@version=6
indicator("Ehlers Fractal Adaptive Moving Average (FRAMA)", "FRAMA", overlay=true)

//@function Calculates Ehlers Fractal Adaptive Moving Average
//@param period Lookback period (forced to even, >= 2)
//@returns FRAMA value with fractal-adaptive smoothing
//@optimized Uses fractal dimension for adaptive alpha with O(n) complexity per bar
frama_strict(simple int period) =>
    int p  = math.max(2, period)
    int pe = (p % 2 == 0) ? p : (p + 1)
    int h  = int(pe / 2)

    // Price series per Ehlers FRAMA (commonly HL2)
    float price = hl2

    // Require enough history and non-NA ranges over the needed windows
    bool ready =
         bar_index >= pe - 1 and
         not na(price) and
         not na(ta.highest(high, pe)) and not na(ta.lowest(low, pe)) and
         not na(ta.highest(high, h))  and not na(ta.lowest(low, h))  and
         not na(ta.highest(high[h], h)) and not na(ta.lowest(low[h], h))

    var float fr = na

    if ready
        // Ranges per Ehlers:
        // N1: first half range / half
        // N2: second half range / half (shifted by half)
        // N3: full range / full
        float n1 = (ta.highest(high, h) - ta.lowest(low, h)) / h
        float n2 = (ta.highest(high[h], h) - ta.lowest(low[h], h)) / h
        float n3 = (ta.highest(high, pe) - ta.lowest(low, pe)) / pe

        float alpha = 1.0
        if n1 > 0 and n2 > 0 and n3 > 0
            float dimen = (math.log(n1 + n2) - math.log(n3)) / math.log(2.0)
            alpha := math.exp(-4.6 * (dimen - 1.0))
            alpha := math.max(0.01, math.min(1.0, alpha))

        // Warm-start: first computed value seeds to price
        float prev = nz(fr[1], price)
        fr := alpha * price + (1.0 - alpha) * prev
    else
        fr := na

    fr

// -------- Main --------

i_period = input.int(16, "Period (even enforced)", minval=2)

frama_value = frama_strict(i_period)

plot(frama_value, "FRAMA (strict)", color=color.yellow, linewidth=2)