Создание Heatmap Волатильности Криптопар с Нормализованным ATR в Pine Script v5

//@version=5
indicator('Crypto Volatility Heatmap (Normalized ATR)', 'CryptoVolHeatmap', true, max_bars_back=500)

// --- Inputs ---
atrLength = input.int(14, 'ATR Length', minval=1, group='Settings')
timeframe = input.timeframe('D', 'Timeframe for Symbols', group='Settings')
symbolsInput = input.string('BINANCE:BTCUSDT,BINANCE:ETHUSDT,BINANCE:SOLUSDT,BINANCE:BNBUSDT,BINANCE:XRPUSDT,BINANCE:ADAUSDT', 'Crypto Pairs (comma-separated)', group='Symbols')

// Parse the input string into an array of symbols
var string[] symbols = str.split(symbolsInput, ',')

// --- Data Collection and Normalization ---
// Initialize arrays to store ATRs and normalized ATRs
var float[] atrs = array.new_float(array.size(symbols))
var float[] normalizedAtrs = array.new_float(array.size(symbols))

// Request ATR for each symbol
for i = 0 to array.size(symbols) - 1
    symbol = array.get(symbols, i)
    // Fetch ATR for the specific symbol and timeframe using request.security
    symbolAtr = request.security(symbol, timeframe, ta.atr(atrLength))
    array.set(atrs, i, symbolAtr)

// Calculate the sum of current ATRs for normalization
float sumAtrs = 0.0
for i = 0 to array.size(atrs) - 1
    sumAtrs += array.get(atrs, i)

// Normalize ATRs: current_ATR / sum_of_all_ATRs
if sumAtrs > 0
    for i = 0 to array.size(atrs) - 1
        currentAtr = array.get(atrs, i)
        normalizedVal = currentAtr / sumAtrs
        array.set(normalizedAtrs, i, normalizedVal)

// --- Heatmap Visualization (Table) ---
// Create a table to display the heatmap. It's created once (var) and updated on the last bar.
var table heatmapTable = table.new(position.top_right, 2, array.size(symbols) + 1, bgcolor=color.rgb(30, 30, 30, 90), border_width=1, border_color=color.gray)

// Update the table only on the last bar to avoid flickering and unnecessary redraws
if barstate.islast
    // Set table headers
    table.cell(heatmapTable, 0, 0, 'Symbol', text_color=color.white, bgcolor=color.rgb(50, 50, 50))
    table.cell(heatmapTable, 1, 0, 'Norm. ATR', text_color=color.white, bgcolor=color.rgb(50, 50, 50))

    // Find the maximum normalized ATR to scale the color gradient effectively
    float maxNormAtr = 0.0
    for i = 0 to array.size(normalizedAtrs) - 1
        if array.get(normalizedAtrs, i) > maxNormAtr
            maxNormAtr := array.get(normalizedAtrs, i)

    // Populate the table with symbol data and colored cells
    for i = 0 to array.size(symbols) - 1
        symbol = array.get(symbols, i)
        normAtr = array.get(normalizedAtrs, i)

        // Scale normalized ATR to a 0-1 range based on the maximum observed value
        // This ensures the gradient covers the full spectrum of observed volatility.
        float scaledNormAtr = maxNormAtr > 0 ? normAtr / maxNormAtr : 0.0

        // Determine cell color using a gradient from green (low volatility) to red (high volatility)
        cellColor = color.from_gradient(scaledNormAtr, 0, 1, color.green, color.red)
        
        // Add symbol name to the first column
        table.cell(heatmapTable, 0, i + 1, symbol, text_color=color.white)
        // Add normalized ATR value and apply background color based on volatility
        table.cell(heatmapTable, 1, i + 1, str.tostring(normAtr, '#.#####'), text_color=color.white, bgcolor=cellColor)

// Plotting a dummy value to keep the indicator on the chart if no other plots are present
plot(na, title='Invisible Plot', display=display.none)