// Licensed under the Apache License, Version 2.0
// © mihakralj
//@version=6
indicator("Fibonacci Weighted Moving Average (FWMA)", "FWMA", overlay=true)

//@function Calculates FWMA using Fibonacci sequence as weights with adaptive warmup
//@param source Series to calculate FWMA from
//@param period Lookback period - FIR window size (number of Fibonacci weights)
//@returns FWMA value, calculates from first bar using available data
//@optimized Precomputes Fibonacci weights when period changes; O(period) per bar
fwma(series float source, simple int period) =>
    if period <= 0
        runtime.error("Period must be greater than 0")
    int p = math.min(bar_index + 1, period)
    var array<float> weights = array.new_float(1, 1.0)
    var int last_p = 1
    if last_p != p
        weights := array.new_float(p, 0.0)
        // Generate Fibonacci sequence: F(1)=1, F(2)=1, F(3)=2, ...
        float prev2 = 0.0
        float prev1 = 1.0
        for i = 0 to p - 1
            float fib = (i == 0) ? 1.0 : (i == 1) ? 1.0 : prev1 + prev2
            // Reverse: index 0 = most recent bar gets F(p), last index gets F(1)
            array.set(weights, p - 1 - i, fib)
            prev2 := prev1
            prev1 := fib
        last_p := p
    float sum = 0.0
    float weight_sum = 0.0
    for i = 0 to p - 1
        float price = source[i]
        if not na(price)
            float w = array.get(weights, i)
            sum += price * w
            weight_sum += w
    nz(sum / weight_sum, source)

// ---------- Main loop ----------

// Inputs
i_period = input.int(10, "Period", minval=1)
i_source = input.source(close, "Source")

// Calculation
fwma_value = fwma(i_source, i_period)

// Plot
plot(fwma_value, "FWMA", color=color.yellow, linewidth=2)