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//@version=6 indicator('.', shorttitle = '.', overlay = true, max_lines_count = 100, max_labels_count=100, max_boxes_count = 100, max_bars_back = 100) // Ortak başlangıç değeri start = 0.01 // 4. SAR ve EMA(5) ile yumuşatma sar4_raw = ta.sar(start, 1, 1) sar4_ema = ta.ema(sar4_raw, 3) sar4_color = close > sar4_ema ? color.white : color.fuchsia A111 = input(0.1) B111 = input(0.01) C111 = input(0.1, ".") ABC111 = ta.sar(A111, B111, C111) plot(ABC111, "sar", style=plot.style_cross, color=sar4_color, linewidth = 2) /////////////////////////////////////////////////////////SON BARI ATR İLE OLASILIK HESAPLA/////////////////////// // Inputs length14 = input.int(title = 'ATR Length', defval = 1, minval = 1) tradetype14 = input.string(defval = 'Long', title = 'Trade Type', options = ['Long', 'Short']) takeprofit14 = input.float(1, 'Take Profit Times ATR', minval = 0.1) stoploss14 = input.float(1.6, 'Stop Loss Times ATR', minval = 0.1) index14 = input(0, 'Display Index') // Functions getMA(series, length14) => ta.rma(series, length14) getTV(value) => math.round(value * 100000) / 100000 // Variables atr148 = getMA(ta.tr(true), length14)[index14] posTake = tradetype14 == 'Long' ? close[index14] + takeprofit14 * atr148 : close[index14] - takeprofit14 * atr148 posStop = tradetype14 == 'Long' ? close[index14] - stoploss14 * atr148 : close[index14] + stoploss14 * atr148 colorTake = color.new(color.lime, 50) colorStop = color.new(color.red, 50) // Plots plotcandle(close[index14], posTake, close[index14], posTake, title = 'OLST', color = index14 == 0 ? colorTake : na, bordercolor = index14 == 0 ? colorTake : na, wickcolor = na, show_last = 1) plotcandle(close[index14], close, posStop, posStop, title = 'OLSD', color = index14 == 0 ? colorStop : na, bordercolor = index14 == 0 ? colorStop : na, wickcolor = na, show_last = 1)

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//@version=6 indicator('Neural Network Buy and Sell Signals', shorttitle = '.', overlay = true, max_lines_count = 100, max_labels_count=100, max_boxes_count = 100, max_bars_back = 100) var string scalpHelperGroup = 'Scalp Helper Signal Settings' enable_scalp_helper = input.bool(true, 'Enable Scalp Helper Signals', group = scalpHelperGroup) signalCandleType = input.string('Candlesticks', 'Signal Candle Type', options = ['Candlesticks', 'Heikin Ashi', 'Linear Regression'], group = scalpHelperGroup, tooltip = 'Choose which candle type to use for signal calculations. This will not change what candlestick type is displayed.') signal_trigger_mult = input.float(1.5, 'Signal Trigger Sensitivity', minval = 0.1, maxval = 10.0, step = 0.1, group = scalpHelperGroup, tooltip = 'Controls both buy and sell signal sensitivity. Lower values = more sensitive signals, higher values = less sensitive signals.') stop_atr_mult = input.float(1.5, 'Stop Loss ATR Multiplier', minval = 0.1, maxval = 10.0, step = 0.1, group = scalpHelperGroup, tooltip = 'Once a signal is triggered this stop will be initiated to tell how long the signal is valid. Higher values = wider stops and less signals, lower values = tighter stops and more signals.') var string candleGroup = 'Candlestick Settings' candleType = input.string('Candlesticks', 'Candle Type', options = ['Candlesticks', 'Heikin Ashi', 'Linear Regression'], group = candleGroup, tooltip = 'Choose the type of candles to display. This does not impact signal calculations.') lrcLength1 = input.int(6, 'Linear Regression Length', minval = 1, group = candleGroup, tooltip = 'Length for Linear Regression calculations. Lower values are more responsive but noisier.') var string visualGroup = 'Display Settings' signalOffset = input.float(1.05, 'Signal Distance from Candles', minval = 0.1, maxval = 3.0, step = 0.1, group = visualGroup, tooltip = 'Distance of buy/sell labels from candles (ATR multiplier)') signalLabelSize = input.string('medium', 'Signal Label Size', options = ['tiny', 'small', 'medium', 'large'], group = visualGroup, tooltip = 'Size of the neural network signal labels') buy_signal_length = 2 buy_atr_length = 18 sell_signal_length = 2 sell_atr_length = 18 buy_signal_use_close = false buy_atr_use_close = true sell_signal_use_close = false sell_atr_use_close = true amf_length = 14 amf_signal_length = 9 amf_smoothing = 3 amf_fast_length = 5 amf_slow_length = 21 amf_far_threshold = 0.3 amf_slope_fast_threshold = 0.03 h1_amf_weight = 1.2 h1_alma_weight = 0.4 h1_sr_weight = 0.5 h1_swing_weight = 0.4 h1_regime_weight = 0.7 h1_bias = 0.2 h2_amf_weight = 1.4 h2_alma_weight = 0.3 h2_sr_weight = 0.6 h2_swing_weight = 0.3 h2_regime_weight = 0.8 h2_bias = 0.15 h3_amf_weight = 1.6 h3_alma_weight = 0.4 h3_sr_weight = 0.4 h3_swing_weight = 0.5 h3_regime_weight = 0.6 h3_bias = 0.25 out_h1_weight = 0.4 out_h2_weight = 0.4 out_h3_weight = 0.4 out_bias = 0.3 enable_input_normalization = true normalization_lookback = 50 outlier_clipping = true clipping_threshold = 3.0 almaLength = 20 almaOffset = 0.85 almaSigma = 6.0 alma2Length = 20 alma2Offset = 0.77 alma2Sigma = 6.0 alma_wide_gap_threshold = 0.1 pivot_lookback = 10 sr_proximity_threshold = 0.5 sr_breakout_threshold = 0.2 swing_structure_length = 20 regime_lookback = 30 trending_threshold = 0.6 showScalpLabels = true var float signalOpen = open var float signalHigh = high var float signalLow = low var float signalClose = close customBuyColor = color.new(#00FFFF, 0) customSellColor = color.new(#FF0000, 0) scalpLongColor = color.new(#00B3B3, 0) scalpShortColor = color.new(#FF0000, 0) textColor = color.new(color.white, 0) f_ema_amf(source, len) => float alpha = 2.0 / (len + 1) var float ema_val = na if not na(source) and len > 0 ema_val := alpha * source + (1 - alpha) * nz(ema_val[1]) ema_val f_dema_amf(source, len) => float ema1 = f_ema_amf(source, len) float ema2 = f_ema_amf(ema1, len) float dema_val = 2 * ema1 - ema2 dema_val f_zlema_amf(source, len) => int lag = int((len - 1) / 2) float lag_source = lag > 0 ? source[lag] : source float adjusted_source = source + (source - lag_source) float zlema_val = f_ema_amf(adjusted_source, len) zlema_val f_sum_amf(source, len) => float sum_val = 0.0 for i = 0 to len - 1 sum_val += nz(source[i], 0) sum_val f_calculate_amf(src, length, fast_len, slow_len, smooth_len) => float current_atr = ta.atr(14) float avg_atr = ta.sma(current_atr, 50) float volatility_ratio = avg_atr > 0 ? current_atr / avg_atr : 1.0 float volatility_sensitivity = 2.0 float raw_adaptive_lookback = float(length) / math.pow(volatility_ratio, volatility_sensitivity) int adaptive_lookback = int(math.max(5, math.min(50, raw_adaptive_lookback))) if adaptive_lookback < 1 adaptive_lookback := 1 int zlema_fast_len = adaptive_lookback int dema_medium_len = int(adaptive_lookback * 1.5) int dema_slow_len = int(adaptive_lookback * 2.5) if dema_medium_len < 1 dema_medium_len := 1 if dema_slow_len < 1 dema_slow_len := 1 float zlema_fast = f_zlema_amf(src, zlema_fast_len) float dema_medium = f_dema_amf(src, dema_medium_len) float dema_slow = f_dema_amf(src, dema_slow_len) float pv = 0.0 if src > src[1] pv := volume else if src < src[1] pv := -volume float vzo_sum = f_sum_amf(pv, length) float vol_sum = f_sum_amf(volume, length) float vzo_value = vol_sum != 0 ? 100 * (vzo_sum / vol_sum) : 0.0 float smoothed_vzo = ta.sma(vzo_value, 3) float price_vs_fast_weight = 30.0 float fast_vs_medium_weight = 30.0 float medium_vs_slow_weight = 40.0 float vzo_weight = 20.0 float oscillator_score = 0.0 if src > zlema_fast oscillator_score += price_vs_fast_weight else if src < zlema_fast oscillator_score -= price_vs_fast_weight if zlema_fast > dema_medium oscillator_score += fast_vs_medium_weight else if zlema_fast < dema_medium oscillator_score -= fast_vs_medium_weight if dema_medium > dema_slow oscillator_score += medium_vs_slow_weight else if dema_medium < dema_slow oscillator_score -= medium_vs_slow_weight oscillator_score += (smoothed_vzo / 100) * vzo_weight float max_possible_score = price_vs_fast_weight + fast_vs_medium_weight + medium_vs_slow_weight + vzo_weight float normalized_score = max_possible_score != 0.0 ? (oscillator_score / max_possible_score) * 100.0 : 0.0 float final_amf = ta.ema(normalized_score / 100.0, smooth_len) final_amf f_amf_signal(amf_line, signal_length) => ta.ema(amf_line, signal_length) // =========================================================================================================== // CACHED CALCULATIONS // =========================================================================================================== cached_atr = ta.atr(14) // =========================================================================================================== // NORMALIZATION FUNCTIONS // =========================================================================================================== f_normalizeInput(value, lookback_period, enable_clipping, clip_threshold) => if not enable_input_normalization value else mean_val = ta.sma(value, lookback_period) variance = ta.sma(math.pow(value - mean_val, 2), lookback_period) std_val = math.sqrt(variance) normalized = std_val > 0 ? (value - mean_val) / std_val : 0.0 if enable_clipping math.max(-clip_threshold, math.min(clip_threshold, normalized)) else normalized f_robustNormalize(value, lookback_period) => if not enable_input_normalization value else ema_val = ta.ema(value, lookback_period) abs_dev = math.abs(value - ema_val) mad_approx = ta.ema(abs_dev, lookback_period) * 1.4826 mad_approx > 0 ? (value - ema_val) / mad_approx : 0.0 // =========================================================================================================== // SIGNAL SCORING // =========================================================================================================== // Tanh approximation f_tanh(x) => ex = math.exp(2 * x) (ex - 1) / (ex + 1) f_scoreSignal(amf_score, alma_score, sr_score, swing_score, regime_score) => hidden1 = f_tanh(h1_amf_weight*amf_score + h1_alma_weight*alma_score + h1_sr_weight*sr_score + h1_swing_weight*swing_score + h1_regime_weight*regime_score + h1_bias) hidden2 = f_tanh(h2_amf_weight*amf_score + h2_alma_weight*alma_score + h2_sr_weight*sr_score + h2_swing_weight*swing_score + h2_regime_weight*regime_score + h2_bias) hidden3 = f_tanh(h3_amf_weight*amf_score + h3_alma_weight*alma_score + h3_sr_weight*sr_score + h3_swing_weight*swing_score + h3_regime_weight*regime_score + h3_bias) raw_output = out_h1_weight*hidden1 + out_h2_weight*hidden2 + out_h3_weight*hidden3 + out_bias 1.0 / (1.0 + math.exp(-raw_output)) f_scoreSignalNormalized(amf_norm, alma_norm, sr_norm, swing_norm, regime_norm) => input_scale = 0.8 scaled_amf = amf_norm * input_scale scaled_alma = alma_norm * input_scale scaled_sr = sr_norm * input_scale scaled_swing = swing_norm * input_scale scaled_regime = regime_norm * input_scale hidden1 = f_tanh(h1_amf_weight*scaled_amf + h1_alma_weight*scaled_alma + h1_sr_weight*scaled_sr + h1_swing_weight*scaled_swing + h1_regime_weight*scaled_regime + h1_bias) hidden2 = f_tanh(h2_amf_weight*scaled_amf + h2_alma_weight*scaled_alma + h2_sr_weight*scaled_sr + h2_swing_weight*scaled_swing + h2_regime_weight*scaled_regime + h2_bias) hidden3 = f_tanh(h3_amf_weight*scaled_amf + h3_alma_weight*scaled_alma + h3_sr_weight*scaled_sr + h3_swing_weight*scaled_swing + h3_regime_weight*scaled_regime + h3_bias) raw_output = out_h1_weight*hidden1 + out_h2_weight*hidden2 + out_h3_weight*hidden3 + out_bias temperature = 1.2 1.0 / (1.0 + math.exp(-raw_output / temperature)) f_getSignalGrade(score) => if score >= 0.80 ">80" else if score >= 0.76 "76" else if score >= 0.65 "65" else if score >= 0.40 "40" else if score >= 0.32 "32" else "<32" // (< 0.32) f_getScoreColor(score) => var color result_color = color.maroon if score >= 0.76 result_color := customBuyColor else if score >= 0.65 result_color := color.new(customBuyColor, 20) else if score >= 0.40 result_color := color.new(#00FFFF, 30) else if score >= 0.32 result_color := color.new(#FFB000, 0) else result_color := customSellColor result_color // AMF Analysis Functions f_analyzeAMF(amf_line, signal_line, is_buy, is_sell, cached_atr) => amf_vs_signal = amf_line - signal_line crossing_up = amf_line > signal_line and amf_line[1] <= signal_line[1] crossing_down = amf_line < signal_line and amf_line[1] >= signal_line[1] normalized_distance = math.abs(amf_vs_signal) / cached_atr is_far = normalized_distance > amf_far_threshold signal_slope = (signal_line - signal_line[1]) / cached_atr slope_fast_falling = signal_slope < -amf_slope_fast_threshold slope_fast_rising = signal_slope > amf_slope_fast_threshold var float amf_score = 0.0 if is_buy if crossing_up or amf_line > signal_line amf_score := 1.0 else if amf_line < signal_line if is_far amf_score := -0.8 else amf_score := -0.4 else amf_score := 0.0 if slope_fast_falling amf_score := amf_score - 0.3 else if is_sell if crossing_down or amf_line < signal_line amf_score := 1.0 else if amf_line > signal_line if is_far amf_score := -0.8 else amf_score := -0.4 else amf_score := 0.0 if slope_fast_rising amf_score := amf_score - 0.3 else amf_score := 0.0 math.max(-1.0, math.min(1.0, amf_score)) f_analyzeALMA(fast_alma, slow_alma, is_buy, is_sell, cached_atr) => alma_gap = fast_alma - slow_alma normalized_gap = math.abs(alma_gap) / cached_atr is_wide_gap = normalized_gap > alma_wide_gap_threshold crossing_up = fast_alma > slow_alma and fast_alma[1] <= slow_alma[1] crossing_down = fast_alma < slow_alma and fast_alma[1] >= slow_alma[1] var float alma_score = 0.0 if is_buy if crossing_up or fast_alma > slow_alma alma_score := 0.5 else if fast_alma < slow_alma if is_wide_gap alma_score := -0.8 else alma_score := -0.2 else alma_score := 0.0 else if is_sell if crossing_down or fast_alma < slow_alma alma_score := 0.5 else if fast_alma > slow_alma if is_wide_gap alma_score := -0.8 else alma_score := -0.2 else alma_score := 0.0 else alma_score := 0.0 alma_score f_analyzeSupportResistance(is_buy, is_sell, cached_atr, sig_high, sig_low, sig_close) => pivot_high = ta.pivothigh(sig_high, pivot_lookback, pivot_lookback) pivot_low = ta.pivotlow(sig_low, pivot_lookback, pivot_lookback) var float nearest_resistance = na var float nearest_support = na if not na(pivot_high) nearest_resistance := pivot_high if not na(pivot_low) nearest_support := pivot_low resistance_distance = nearest_resistance > 0 ? math.abs(sig_close - nearest_resistance) / cached_atr : 999 support_distance = nearest_support > 0 ? math.abs(sig_close - nearest_support) / cached_atr : 999 near_resistance = resistance_distance <= sr_proximity_threshold near_support = support_distance <= sr_proximity_threshold recent_resistance_break = nearest_resistance > 0 and sig_close > nearest_resistance and sig_close[5] <= nearest_resistance recent_support_break = nearest_support > 0 and sig_close < nearest_support and sig_close[5] >= nearest_support var float sr_score = 0.0 if is_buy if recent_resistance_break sr_score := 0.8 else if near_support sr_score := 0.5 else if near_resistance sr_score := -0.6 else sr_score := 0.0 else if is_sell if recent_support_break sr_score := 0.8 else if near_resistance sr_score := 0.5 else if near_support sr_score := -0.6 else sr_score := 0.0 else sr_score := 0.0 sr_score f_analyzeSwingStructure(is_buy, is_sell, sig_high, sig_low) => recent_high = ta.highest(sig_high, swing_structure_length) recent_low = ta.lowest(sig_low, swing_structure_length) previous_high = ta.highest(sig_high[swing_structure_length], swing_structure_length) previous_low = ta.lowest(sig_low[swing_structure_length], swing_structure_length) making_higher_highs = recent_high > previous_high making_higher_lows = recent_low > previous_low making_lower_highs = recent_high < previous_high making_lower_lows = recent_low < previous_low bullish_structure = making_higher_highs and making_higher_lows bearish_structure = making_lower_highs and making_lower_lows mixed_structure = not bullish_structure and not bearish_structure var float swing_score = 0.0 if is_buy if bullish_structure swing_score := 0.6 else if bearish_structure swing_score := -0.7 else swing_score := -0.1 else if is_sell if bearish_structure swing_score := 0.6 else if bullish_structure swing_score := -0.7 else swing_score := -0.1 else swing_score := 0.0 swing_score f_analyzeMarketRegime(is_buy, is_sell, sig_open, sig_high, sig_low, sig_close) => tr1 = math.max(sig_high - sig_low, math.abs(sig_high - sig_close[1])) tr = math.max(tr1, math.abs(sig_low - sig_close[1])) plus_dm = sig_high - sig_high[1] > sig_low[1] - sig_low ? math.max(sig_high - sig_high[1], 0) : 0 minus_dm = sig_low[1] - sig_low > sig_high - sig_high[1] ? math.max(sig_low[1] - sig_low, 0) : 0 plus_di = 100 * ta.rma(plus_dm, regime_lookback) / ta.rma(tr, regime_lookback) minus_di = 100 * ta.rma(minus_dm, regime_lookback) / ta.rma(tr, regime_lookback) dx = math.abs(plus_di - minus_di) / (plus_di + minus_di) * 100 adx = ta.rma(dx, regime_lookback) trending_market = adx >= trending_threshold * 100 ranging_market = not trending_market bullish_trend = trending_market and plus_di > minus_di bearish_trend = trending_market and minus_di > plus_di var float regime_score = 0.0 if is_buy if bullish_trend regime_score := 0.7 else if bearish_trend regime_score := -0.8 else regime_score := -0.2 else if is_sell if bearish_trend regime_score := 0.7 else if bullish_trend regime_score := -0.8 else regime_score := -0.2 else regime_score := 0.0 regime_score // =========================================================================================================== // CANDLE TYPE CALCULATIONS // =========================================================================================================== // Heikin Ashi calculateHA111() => var haOpen = 0.0 var haHigh = 0.0 var haLow = 0.0 var haClose = 0.0 newHaClose = (open + high + low + close) / 4 newHaOpen = na(haOpen[1]) ? (open + close) / 2 : (haOpen[1] + haClose[1]) / 2 newHaHigh = math.max(high, math.max(newHaOpen, newHaClose)) newHaLow = math.min(low, math.min(newHaOpen, newHaClose)) haClose := newHaClose haOpen := newHaOpen haHigh := newHaHigh haLow := newHaLow [newHaOpen, newHaHigh, newHaLow, newHaClose] [oHA, hHA, lHA, cHA] = calculateHA111() var float displayOpen = na var float displayHigh = na var float displayLow = na var float displayClose = na if candleType == 'Candlesticks' displayOpen := open displayHigh := high displayLow := low displayClose := close else if candleType == 'Heikin Ashi' displayOpen := oHA displayHigh := hHA displayLow := lHA displayClose := cHA else if candleType == 'Linear Regression' displayOpen := ta.linreg(open, lrcLength1, 0) displayHigh := ta.linreg(high, lrcLength1, 0) displayLow := ta.linreg(low, lrcLength1, 0) displayClose := ta.linreg(close, lrcLength1, 0) // Determine coloring isBullishCandle = displayClose > displayOpen isBearishCandle = displayClose < displayOpen // =========================================================================================================== // SIGNAL DATA SOURCE SELECTION // =========================================================================================================== var float signalOpenCalc = na var float signalHighCalc = na var float signalLowCalc = na var float signalCloseCalc = na if signalCandleType == 'Candlesticks' signalOpenCalc := open signalHighCalc := high signalLowCalc := low signalCloseCalc := close else if signalCandleType == 'Heikin Ashi' signalOpenCalc := oHA signalHighCalc := hHA signalLowCalc := lHA signalCloseCalc := cHA else if signalCandleType == 'Linear Regression' signalOpenCalc := ta.linreg(open, lrcLength1, 0) signalHighCalc := ta.linreg(high, lrcLength1, 0) signalLowCalc := ta.linreg(low, lrcLength1, 0) signalCloseCalc := ta.linreg(close, lrcLength1, 0) signalOpen := signalOpenCalc signalHigh := signalHighCalc signalLow := signalLowCalc signalClose := signalCloseCalc // =========================================================================================================== // SCALP HELPER SIGNAL SYSTEM // =========================================================================================================== buy_signal_buySignal = false sell_signal_sellSignal = false buy_atr_sellSignal = false sell_atr_buySignal = false buy_atr_longStop = close sell_atr_shortStop = close var bool buy_atr_stop_active = false var bool sell_atr_stop_active = false if enable_scalp_helper // ============================================================================ // BUY SIGNAL // ============================================================================ buy_signal_atr = ta.atr(buy_signal_length) * signal_trigger_mult buy_signal_longStop = (buy_signal_use_close ? ta.highest(signalClose, buy_signal_length) : ta.highest(signalHigh, buy_signal_length)) - buy_signal_atr buy_signal_longStopPrev = nz(buy_signal_longStop[1], buy_signal_longStop) buy_signal_longStop := signalClose[1] > buy_signal_longStopPrev ? math.max(buy_signal_longStop, buy_signal_longStopPrev) : buy_signal_longStop buy_signal_shortStop = (buy_signal_use_close ? ta.lowest(signalClose, buy_signal_length) : ta.lowest(signalLow, buy_signal_length)) + buy_signal_atr buy_signal_shortStopPrev = nz(buy_signal_shortStop[1], buy_signal_shortStop) buy_signal_shortStop := signalClose[1] < buy_signal_shortStopPrev ? math.min(buy_signal_shortStop, buy_signal_shortStopPrev) : buy_signal_shortStop var int buy_signal_dir = 1 buy_signal_dir := signalClose > buy_signal_shortStopPrev ? 1 : signalClose < buy_signal_longStopPrev ? -1 : buy_signal_dir buy_signal_buySignal := buy_signal_dir == 1 and buy_signal_dir[1] == -1 // ============================================================================ // BUY ATR STOP // ============================================================================ buy_atr_atr = ta.atr(buy_atr_length) * stop_atr_mult buy_atr_longStop := (buy_atr_use_close ? ta.highest(signalClose, buy_atr_length) : ta.highest(signalHigh, buy_atr_length)) - buy_atr_atr buy_atr_longStopPrev = nz(buy_atr_longStop[1], buy_atr_longStop) buy_atr_longStop := signalClose[1] > buy_atr_longStopPrev ? math.max(buy_atr_longStop, buy_atr_longStopPrev) : buy_atr_longStop buy_atr_shortStop = (buy_atr_use_close ? ta.lowest(signalClose, buy_atr_length) : ta.lowest(signalLow, buy_atr_length)) + buy_atr_atr buy_atr_shortStopPrev = nz(buy_atr_shortStop[1], buy_atr_shortStop) buy_atr_shortStop := signalClose[1] < buy_atr_shortStopPrev ? math.min(buy_atr_shortStop, buy_atr_shortStopPrev) : buy_atr_shortStop var int buy_atr_dir = 1 buy_atr_dir := signalClose > buy_atr_shortStopPrev ? 1 : signalClose < buy_atr_longStopPrev ? -1 : buy_atr_dir buy_atr_sellSignal := buy_atr_dir == -1 and buy_atr_dir[1] == 1 // ============================================================================ // SELL SIGNAL // ============================================================================ sell_signal_atr = ta.atr(sell_signal_length) * signal_trigger_mult sell_signal_longStop = (sell_signal_use_close ? ta.highest(signalClose, sell_signal_length) : ta.highest(signalHigh, sell_signal_length)) - sell_signal_atr sell_signal_longStopPrev = nz(sell_signal_longStop[1], sell_signal_longStop) sell_signal_longStop := signalClose[1] > sell_signal_longStopPrev ? math.max(sell_signal_longStop, sell_signal_longStopPrev) : sell_signal_longStop sell_signal_shortStop = (sell_signal_use_close ? ta.lowest(signalClose, sell_signal_length) : ta.lowest(signalLow, sell_signal_length)) + sell_signal_atr sell_signal_shortStopPrev = nz(sell_signal_shortStop[1], sell_signal_shortStop) sell_signal_shortStop := signalClose[1] < sell_signal_shortStopPrev ? math.min(sell_signal_shortStop, sell_signal_shortStopPrev) : sell_signal_shortStop var int sell_signal_dir = 1 sell_signal_dir := signalClose > sell_signal_shortStopPrev ? 1 : signalClose < sell_signal_longStopPrev ? -1 : sell_signal_dir sell_signal_sellSignal := sell_signal_dir == -1 and sell_signal_dir[1] == 1 // ============================================================================ // SELL ATR STOP // ============================================================================ sell_atr_atr = ta.atr(sell_atr_length) * stop_atr_mult sell_atr_longStop = (sell_atr_use_close ? ta.highest(signalClose, sell_atr_length) : ta.highest(signalHigh, sell_atr_length)) - sell_atr_atr sell_atr_longStopPrev = nz(sell_atr_longStop[1], sell_atr_longStop) sell_atr_longStop := signalClose[1] > sell_atr_longStopPrev ? math.max(sell_atr_longStop, sell_atr_longStopPrev) : sell_atr_longStop sell_atr_shortStop := (sell_atr_use_close ? ta.lowest(signalClose, sell_atr_length) : ta.lowest(signalLow, sell_atr_length)) + sell_atr_atr sell_atr_shortStopPrev = nz(sell_atr_shortStop[1], sell_atr_shortStop) sell_atr_shortStop := signalClose[1] < sell_atr_shortStopPrev ? math.min(sell_atr_shortStop, sell_atr_shortStopPrev) : sell_atr_shortStop var int sell_atr_dir = 1 sell_atr_dir := signalClose > sell_atr_shortStopPrev ? 1 : signalClose < sell_atr_longStopPrev ? -1 : sell_atr_dir sell_atr_buySignal := sell_atr_dir == 1 and sell_atr_dir[1] == -1 // ============================================================================ // SIGNAL STATE MANAGEMENT // ============================================================================ if not buy_atr_stop_active if buy_signal_buySignal buy_atr_stop_active := true else if buy_atr_sellSignal buy_atr_stop_active := false if not sell_atr_stop_active if sell_signal_sellSignal sell_atr_stop_active := true else if sell_atr_buySignal sell_atr_stop_active := false // =========================================================================================================== // CORE CALCULATIONS // =========================================================================================================== // AMF Calculations amf_line = f_calculate_amf(signalClose, amf_length, amf_fast_length, amf_slow_length, amf_smoothing) amf_signal = f_amf_signal(amf_line, amf_signal_length) // Cached ATR atr14 = ta.atr(14) // ALMA calculations for neural network (Use Signal Candles for analysis) alma200 = ta.alma(signalClose, almaLength, almaOffset, almaSigma) alma2 = ta.alma(signalClose, alma2Length, alma2Offset, alma2Sigma) // =========================================================================================================== // NEURAL NETWORK // =========================================================================================================== is_buy_signal = buy_signal_buySignal is_sell_signal = sell_signal_sellSignal amf_context = f_analyzeAMF(amf_line, amf_signal, is_buy_signal, is_sell_signal, atr14) alma_context = f_analyzeALMA(alma200, alma2, is_buy_signal, is_sell_signal, atr14) sr_context = f_analyzeSupportResistance(is_buy_signal, is_sell_signal, atr14, signalHigh, signalLow, signalClose) swing_context = f_analyzeSwingStructure(is_buy_signal, is_sell_signal, signalHigh, signalLow) regime_context = f_analyzeMarketRegime(is_buy_signal, is_sell_signal, signalOpen, signalHigh, signalLow, signalClose) amf_context_normalized = f_normalizeInput(amf_context, normalization_lookback, outlier_clipping, clipping_threshold) alma_context_normalized = f_normalizeInput(alma_context, normalization_lookback, outlier_clipping, clipping_threshold) sr_context_normalized = f_normalizeInput(sr_context, normalization_lookback, outlier_clipping, clipping_threshold) swing_context_normalized = f_normalizeInput(swing_context, normalization_lookback, outlier_clipping, clipping_threshold) regime_context_normalized = f_normalizeInput(regime_context, normalization_lookback, outlier_clipping, clipping_threshold) signal_score = (is_buy_signal or is_sell_signal) ? f_scoreSignalNormalized(amf_context_normalized, alma_context_normalized, sr_context_normalized, swing_context_normalized, regime_context_normalized) : 0.5 signal_grade = f_getSignalGrade(signal_score) score_color = f_getScoreColor(signal_score) // =========================================================================================================== // CANDLE PLOTTING // =========================================================================================================== candleColor = isBullishCandle ? customBuyColor : customSellColor plotcandle(candleType != 'Candlesticks' ? displayOpen : na, candleType != 'Candlesticks' ? displayHigh : na, candleType != 'Candlesticks' ? displayLow : na, candleType != 'Candlesticks' ? displayClose : na, title = 'BAR', color = candleType != 'Candlesticks' ? candleColor : na, wickcolor = candleType != 'Candlesticks' ? candleColor : na, bordercolor = candleType != 'Candlesticks' ? candleColor : na) // =========================================================================================================== // SCALP HELPER SIGNAL PLOTS // =========================================================================================================== atr_offset = signalOffset * atr14 show_buy_signal = enable_scalp_helper and buy_signal_buySignal and not buy_atr_stop_active[1] show_sell_signal = enable_scalp_helper and sell_signal_sellSignal and not sell_atr_stop_active[1] label_size = signalLabelSize == 'tiny' ? size.tiny : signalLabelSize == 'small' ? size.small : signalLabelSize == 'large' ? size.large : size.normal if showScalpLabels and show_buy_signal buy_label_text = signal_grade label.new(bar_index, signalLow - atr_offset, text = buy_label_text, style = label.style_label_up, size = label_size, color = score_color, textcolor = color.black) if showScalpLabels and show_sell_signal sell_label_text = signal_grade label.new(bar_index, signalHigh + atr_offset, text = sell_label_text, style = label.style_label_down, size = label_size, color = score_color, textcolor = color.black) ///////////////////////////////////////////////////////////////////// // Kullanıcı Girişleri slow_sar_set = input.float(0.3, 'Slow SAR', minval = 0.01, maxval = 0.3, group = 'SAR Settings') sar_set = input.float(0.2, 'Normal SAR', minval = 0.01, maxval = 0.2, group = 'SAR Settings') fast_sar_set = input.float(0.1, 'Fast SAR', minval = 0.01, maxval = 0.1, group = 'SAR Settings') sar_avg_length = input.int(1, 'Hareketli Ortalama Uzunluğu', minval = 1, group = 'SAR Settings') // Hesaplamalar // ta.sar(baslangic, artis, maksimum) - sayı küçüldükçe değişim hızı artar fast_sar = ta.sar(fast_sar_set, fast_sar_set, 0.1) sar = ta.sar(sar_set, sar_set, 0.1) slow_sar = ta.sar(slow_sar_set, slow_sar_set, 0.1) // Hareketli Ortalama sar_avg = ta.sma(sar, sar_avg_length) // Çizimler plot(fast_sar, title = '1Z', color = close > fast_sar ? #00ff0000 : #ffbbba00, style = plot.style_circles, linewidth = 1) plot(sar, title = '2Z', color = close > sar ? #00b80000 : #ff010100, style = plot.style_circles, linewidth = 1) plot(slow_sar, title = '3Z', color = close > slow_sar ? #14571500 : #aa000000, style = plot.style_circles, linewidth = 1) /////////////////////////// // Ortak başlangıç değeri start = 0.01 // 3 SAR (farklı hızlarda) sar1 = ta.sar(start, 0.2, 0.2) sar2 = ta.sar(start, 0.3, 0.3) sar3 = ta.sar(start, 0.5, 0.5) // 4. SAR ve EMA(5) ile yumuşatma sar4_raw = ta.sar(start, 1, 1) sar4_ema = ta.ema(sar4_raw, 5) // SAR4 EMA çizgi rengi: fiyatın üstünde yeşil, altında kırmızı sar4_color = close > sar4_ema ? color.white : color.fuchsia plot(sar1, title = '1Y', color = close > sar1 ? #00ff0000 : #ffbbba00, style = plot.style_circles, linewidth = 1) plot(sar2, title = '2Y', color = close > sar2 ? #00b80000 : #ff010100, style = plot.style_circles, linewidth = 1) plot(sar3, title = '3Y', color = close > sar3 ? #14571500 : #aa000000, style = plot.style_circles, linewidth = 1) // SAR4 EMA çizgisi (renkli) //plot(sar4_ema, title = 'Z', color = sar4_color, style = plot.style_line, linewidth = 2) ///////////////////////// // === SAR'lar sar19 = ta.sar(0., 0.1, 0.1) sar59 = ta.sar(0., 0.1, 0.1) sar109 = ta.sar(0., 0.1, 0.1) // === Gerçek eşitlik kontrolü equalAll = sar19 == sar59 and sar59 == sar109 sort9 = (sar19 + sar59 + sar109) / 3 //plot(sort9, title = 'X', color = sar4_color, style = plot.style_stepline, linewidth = 1) //////////////////////// price7 = hl2 tolerans7 = 0.001 // === SAR'lar === sar17 = ta.sar(0.001, 0.02, 0.2) sar27 = ta.sar(0.001, 0.03, 0.3) sar37 = ta.sar(0.001, 0.04, 0.4) plot(sar17, title = '1X', color = close > sar17 ? #00ff0000 : #ffbbba00, style = plot.style_circles, linewidth = 1) plot(sar27, title = '2X', color = close > sar27 ? #00b80000 : #ff010100, style = plot.style_circles, linewidth = 1) plot(sar37, title = '3X', color = close > sar37 ? #14571500 : #aa000000, style = plot.style_circles, linewidth = 1) // === SAR yakınlığı kontrolü === yakinsar7 = math.abs(sar17 - sar27) < tolerans7 or math.abs(sar17 - sar37) < tolerans7 or math.abs(sar27 - sar37) < tolerans7 longSignal7 = yakinsar7 and price7 > sar17 shortSignal7 = yakinsar7 and price7 < sar17 // === Sinyal üçgenleri === plotshape(longSignal7, location = location.belowbar, style = shape.triangleup, color = color.fuchsia, size = size.tiny) plotshape(shortSignal7, location = location.abovebar, style = shape.triangledown, color = color.fuchsia, size = size.tiny) ////////////////// // 5 SAR hesapla sar18 = ta.sar(0.1, 0.1, 0.1) sar28 = ta.sar(0.1, 0.3, 0.3) sar38 = ta.sar(0.1, 0.5, 0.5) sar48 = ta.sar(0.1, 0.7, 0.7) sar58 = ta.sar(0.1, 1.0, 1.0) // SAR ortalaması ve EMA(3) ile smooth sarAvg8 = (sar18 + sar28 + sar38 + sar48 + sar58) / 5 smoothedSar8 = ta.ema(sarAvg8, 10) // EMA(1) (fiyat çizgisi) ema18 = ta.ema(close, 1) // Çizgiler //plot(smoothedSar8, title = 'Y', color = sar4_color, style = plot.style_stepline, linewidth = 1) TREND789=(smoothedSar8+sort9+sar4_ema)/3 plot(TREND789, title = 'TR3', color = sar4_color, style = plot.style_stepline, linewidth = 1) SAR7 = ta.sar(0.04, 0.04, 0.3) SAR8 = ta.sar(0.03, 0.03, 0.25) plot(SAR7, title = 'TR1', style = plot.style_line, linewidth = 1, color = sar4_color) plot(SAR8, title = 'TR2', style = plot.style_line, linewidth = 1, color = sar4_color) // === SAR sıkışma kontrolü === tolerance22 = input.float(0.0005, title = 'SAR Yakınlık Toleransı') sar_near22 = math.abs(SAR7 - SAR8) < tolerance22 bgcolor(sar_near22 ? color.new(color.yellow, 75) : na, title = 'SAR Sıkışma Alanı') // Sinyaller longSignal8 = ta.crossover(ema18, smoothedSar8) // AL shortSignal8 = ta.crossunder(ema18, smoothedSar8) // SAT // Sinyal üçgenleri plotshape(longSignal8, title = 'AL Sinyali', location = location.belowbar, style = shape.triangleup, color = color.lime, size = size.small) plotshape(shortSignal8, title = 'SAT Sinyali', location = location.abovebar, style = shape.triangledown, color = color.red, size = size.small) ///////////////////// /////////////////////////////////İMZA AT////////////////////////////////////////////////// var table logo = table.new(position.bottom_center, 1, 1) if barstate.islast table.cell(logo, 0, 0, '@yörük@ EĞİTİM ÇALIŞMASIDIR.', text_size = size.normal, text_color = color.rgb(218, 241, 5)) // === Girişler === uz1 = input(1, title = 'Periyot (lowest/highest)') atr1 = input(10, title = 'ATR Periyodu') az1 = input(1, title = 'ATR Katsayısı') // === Stop seviyeleri === ss1 = ta.lowest(uz1) + az1 * ta.atr(atr1) // üstten takip ll1 = ta.highest(uz1) - az1 * ta.atr(atr1) // alttan takip // === İlk tanımlamalar === var float ssx1 = na var float llx1 = na ssx1 := na(ssx1[1]) ? ss1 : close > ssx1[1] ? ss1 : math.min(ss1, ssx1[1]) llx1 := na(llx1[1]) ? ll1 : close < llx1[1] ? ll1 : math.max(ll1, llx1[1]) // === Sinyaller === yunus1 = close >= ssx1[1] and close[1] < ssx1[1] ? 1 : 0 yusuf1 = close <= llx1[1] and close[1] > llx1[1] ? 1 : 0 // === Trend durumu === var int fato1 = 0 fato1 := fato1 <= 0 and bool(yunus1) ? 1 : fato1 >= 0 and bool(yusuf1) ? -1 : fato1 // === Gösterim === memo1 = fato1 > 0 ? llx1 : ssx1 plot(memo1, title = 'STOP', color = fato1 > 0 ? color.rgb(255, 255, 255, 100) : color.rgb(223, 64, 251, 100), linewidth = 2) ///////////////////ATR HESAPLA/////////////////////////////////////////////////////// var params = "Parameters" src55 = nz(input.source(close, title = "Source", group = params)) len55 = input.int(10, title = "ATR Len", group = params) multi55 = input.float(1.5, title = "Multi", step = 0.25, minval = 0, group = params) var cols = "Colors" up_col = input.color(color.rgb(255, 255, 255, 100), title = "Yükseliş", group = cols) down_col = input.color(color.rgb(223, 64, 251, 100), title = "DÜşüş", group = cols) flat_col = input.color(color.rgb(223, 64, 251, 100), title = "Flat ", inline = "3", group = cols) rope_smoother(float _src55, float _threshold) => var float _rope = _src55 _move = _src55 - _rope //Movement from Rope _rope += math.max(math.abs(_move) - nz(_threshold), 0) * math.sign(_move) //Directional Movement beyond the Threshold [_rope,_rope+_threshold,_rope-_threshold] //[Rope, Upper, Lower] ///_____________________________________________________________________________________________________________________ //Calculating Rope atr99 = ta.atr(len55)*multi55 [rope,upper,lower] = rope_smoother(src55,atr99) //Directional Detection var dir89 = 0 dir89 := rope > rope[1] ? 1 : rope < rope[1] ? -1 : dir89 if ta.cross(src55,rope) dir89 := 0 //Directional Color Assignment col = dir89 > 0 ? up_col : dir89 < 0 ? down_col : flat_col //High and Low Output Lines var float c_hi = na var float c_lo = na //Counters for Accumulating Averages var float h_sum = 0 var float l_sum = 0 var int c_count = 0 //Flip-Flop var ff = 1 if dir89 == 0 if dir89[1] != 0 h_sum := 0 l_sum := 0 c_count := 0 ff := ff * -1 h_sum += upper l_sum += lower c_count += 1 c_hi := h_sum/c_count c_lo := l_sum/c_count /// plot(rope, linewidth = 2, color = col, title = "ATR", force_overlay = true) /////////////////////////////EN HIZLI SARLA BAR RENKLENDİR//////////////////// // ————————————————————————————————————————— f_colorNew(_color, _transp) => var _r = color.r(_color) var _g = color.g(_color) var _b = color.b(_color) color _return = color.rgb(_r, _g, _b, _transp) _return //automatic higher timeframe chooser f_autoHTF(str) => str == '1S' or str == '5S' or str == '10S' or str == '15S' or str == '20S' or str == '30S' or str == '40S' or str == '45S' or str == '50S' ? '1' : str == '1' or str == '2' or str == '3' or str == '4' ? '5' : str == '5' or str == '10' ? '15' : str == '15' or str == '20' ? '30' : str == '30' or str == '45' or str == '50' ? '60' : str == '60' or str == '90' or str == '100' ? '120' : str == '120' or str == '180' ? '240' : str == '240' ? 'D' : str == 'D' ? 'W' : str == 'W' ? '2W' : 'M' var string ticker = syminfo.tickerid var string tfp = timeframe.period htf1 = f_autoHTF(tfp) htf2 = f_autoHTF(htf1) htf3 = f_autoHTF(htf2) htf4 = f_autoHTF(htf3) f_security(_sym, _res, _src, _rep) => request.security(_sym, _res, _src[not _rep and barstate.isrealtime ? 1 : 0])[_rep or barstate.isrealtime ? 0 : 1] //PSAR inputs grpin = '⚙=====-----' grpout = '-----=====⚙' grpPSAR = grpin + 'Dual PSAR Options:' + grpout colorBull = input.color(defval = color.rgb(3, 7, 248, 70), group = grpPSAR, title = 'Bullish Color') //Light Blue colorBear = input.color(defval = #fc07072f, group = grpPSAR, title = 'Bearish Color') //yellow colorWait = input.color(defval = color.rgb(241, 191, 9, 70), group = grpPSAR, title = 'Wait Color') //grey showRecolorCandles = input.bool(true, 'Show Trend Full-Candle Recoloring?', group = grpPSAR, tooltip = 'Recolor the full candle including wick and border with trend color.') psar_start = input.float(defval = 0., group = grpPSAR, title = 'PSAR: Start', minval = 0., maxval = 2, step = 0.01) psar_accel = input.float(defval = 0.1, group = grpPSAR, title = 'PSAR: Acceleration Factor', minval = 0.01, maxval = 2, step = 0.01) psar_maximum = input.float(defval = 0.9, group = grpPSAR, title = 'PSAR: Extreme Point', minval = 0.01, maxval = 2) f_psar() => ta.sar(psar_start, psar_accel, psar_maximum) psar_ctf = f_psar() psar_htf = f_security(ticker, htf1, f_psar(), false) longZone = psar_ctf < low and psar_htf < low shortZone = psar_ctf > high and psar_htf > high waitZone = not longZone and not shortZone trendSupportColor = longZone ? colorBull : shortZone ? colorBear : colorWait plotcandle(showRecolorCandles ? open : na, high, low, close, color = trendSupportColor, wickcolor = trendSupportColor, bordercolor = trendSupportColor, title = 'BAR') barcolor(trendSupportColor) ///////////////////SON BARI ATR İLE OLASILIK HESAPLA/////////////////////// // Inputs length14 = input.int(title = 'ATR Length', defval = 1, minval = 1) tradetype14 = input.string(defval = 'Long', title = 'Trade Type', options = ['Long', 'Short']) takeprofit14 = input.float(1, 'Take Profit Times ATR', minval = 0.1) stoploss14 = input.float(1.6, 'Stop Loss Times ATR', minval = 0.1) index14 = input(0, 'Display Index') // Functions getMA(series, length14) => ta.rma(series, length14) getTV(value) => math.round(value * 100000) / 100000 // Variables atr148 = getMA(ta.tr(true), length14)[index14] posTake = tradetype14 == 'Long' ? close[index14] + takeprofit14 * atr148 : close[index14] - takeprofit14 * atr148 posStop = tradetype14 == 'Long' ? close[index14] - stoploss14 * atr148 : close[index14] + stoploss14 * atr148 colorTake = color.new(color.lime, 50) colorStop = color.new(color.red, 50) // Plots plotcandle(close[index14], posTake, close[index14], posTake, title = 'OLST', color = index14 == 0 ? colorTake : na, bordercolor = index14 == 0 ? colorTake : na, wickcolor = na, show_last = 1) plotcandle(close[index14], close, posStop, posStop, title = 'OLSD', color = index14 == 0 ? colorStop : na, bordercolor = index14 == 0 ? colorStop : na, wickcolor = na, show_last = 1) ////////////////10 SAR HESAPLA VE 10NUDA LA VERİRSE ARKA PLANI YEŞİLLENDİR////////////// // === PSAR Settings === // abh97 = 0.001 abh96 = 0.1 // === Manually defined 10 PSARs === // psar132 = ta.sar(abh97, 0.001, abh96) psar232 = ta.sar(abh97, 0.002, abh96) psar332 = ta.sar(abh97, 0.003, abh96) psar432 = ta.sar(abh97, 0.004, abh96) psar532 = ta.sar(abh97, 0.005, abh96) psar632 = ta.sar(abh97, 0.006, abh96) psar732 = ta.sar(abh97, 0.007, abh96) psar832 = ta.sar(abh97, 0.008, abh96) psar932 = ta.sar(abh97, 0.009, abh96) psar1032 = ta.sar(abh97, 0.010, abh96) // === PSAR Trend Alignment Check === // allBelow32 = psar132 < close and psar232 < close and psar332 < close and psar432 < close and psar532 < close and psar632 < close and psar732 < close and psar832 < close and psar932 < close and psar1032 < close allAbove32 = psar132 > close and psar232 > close and psar332 > close and psar432 > close and psar532 > close and psar632 > close and psar732 > close and psar832 > close and psar932 > close and psar1032 > close // === Trend Signal === // trendUp32 = allBelow32 trendDown32 = allAbove32 trendNeutral32 = not trendUp32 and not trendDown32 // === Background Color === // bgcolor(trendUp32 ? color.new(color.green, 85) : na, title="Up Trend Background") ////////////////////////// //////////////////////////EN HIZLI SAR İLE MTF HESAPLA TABLO YAP///////////////////////////////////// start46 = input(0.) increment46 = input(0.001) maximum46 = input(0.01, "Max Value") out55 = ta.sar(start46, increment46, maximum46) plot_color = close > out55 ? color.rgb(5, 182, 64) : close < out55 ? color.rgb(169, 7, 7) : na show_header = input(false, title="Show header?", group='Table Settings') dashboard_position = input.string("Top center", title="Position", options=["Top right", "Top center", "Middle right"], group='Table Settings') text_size = input.string('Normal', title="Size", options=["Tiny", "Small", "Normal", "Large"], group='Table Settings') text_color = input.color(color.rgb(11, 68, 224), title="Text color", group='Table Settings') table_color = input.color(color.purple, title="Border color", group='Table Settings') uptrend_indicator = "🔵" downtrend_indicator = "🟠" tf11 = input.timeframe("1", title="Timeframe 1") tf22 = input.timeframe("3", title="Timeframe 2") tf33 = input.timeframe("5", title="Timeframe 3") tf4 = input.timeframe("10", title="Timeframe 4") tf5 = input.timeframe("15", title="Timeframe 5") tf6 = input.timeframe("30", title="Timeframe 6") tf7 = input.timeframe("60", title="Timeframe 7") tf8 = input.timeframe("120", title="Timeframe 8") tf9 = input.timeframe("240", title="Timeframe 9") tf10 = input.timeframe("D", title="Timeframe 10") var table_position = dashboard_position == 'Top center' ? position.middle_left : dashboard_position == 'Top center' ? position.middle_left : dashboard_position == 'Middle right' ? position.middle_right : position.middle_right var table_text_size = text_size == 'Normal' ? size.normal : text_size == 'Small' ? size.small : size.normal var t = table.new(position=table_position, columns=3, rows=20, frame_color=#cdcbcb, frame_width=5, border_color=table_color, border_width=1,bgcolor =color.rgb(21, 21, 21) ) get_trend_status(trend_value) => is_uptrend = close > trend_value candle_now = is_uptrend ? uptrend_indicator : downtrend_indicator candle_now //-------------------------------------------------------------------------------------- sar_1 = request.security(syminfo.tickerid, tf11, ta.sar(start46, increment46, maximum46)) sar_2 = request.security(syminfo.tickerid, tf22, ta.sar(start46, increment46, maximum46)) sar_3 = request.security(syminfo.tickerid, tf33, ta.sar(start46, increment46, maximum46)) sar_4 = request.security(syminfo.tickerid, tf4, ta.sar(start46, increment46, maximum46)) sar_5 = request.security(syminfo.tickerid, tf5, ta.sar(start46, increment46, maximum46)) sar_6 = request.security(syminfo.tickerid, tf6, ta.sar(start46, increment46, maximum46)) sar_7 = request.security(syminfo.tickerid, tf7, ta.sar(start46, increment46, maximum46)) sar_8 = request.security(syminfo.tickerid, tf8, ta.sar(start46, increment46, maximum46)) sar_9 = request.security(syminfo.tickerid, tf9, ta.sar(start46, increment46, maximum46)) sar_10 = request.security(syminfo.tickerid, tf10, ta.sar(start46, increment46, maximum46)) trend_indicator_1 = get_trend_status(sar_1) trend_indicator_2 = get_trend_status(sar_2) trend_indicator_3 = get_trend_status(sar_3) trend_indicator_4 = get_trend_status(sar_4) trend_indicator_5 = get_trend_status(sar_5) trend_indicator_6 = get_trend_status(sar_6) trend_indicator_7 = get_trend_status(sar_7) trend_indicator_8 = get_trend_status(sar_8) trend_indicator_9 = get_trend_status(sar_9) trend_indicator_10 = get_trend_status(sar_10) if tf11 == "60" tf11 := "1H" if tf11 == "120" tf11 := "2H" if tf11 == "180" tf11 := "3H" if tf11 == "240" tf11 := "4H" if tf22 == "60" tf22 := "1H" if tf22 == "120" tf22 := "2H" if tf22 == "180" tf22 := "3H" if tf22 == "240" tf22 := "4H" if tf33 == "60" tf33 := "1H" if tf33 == "120" tf33 := "2H" if tf33 == "180" tf33 := "3H" if tf33 == "240" tf33 := "4H" if tf4 == "60" tf4 := "1H" if tf4 == "120" tf4 := "2H" if tf4 == "180" tf4 := "3H" if tf4 == "240" tf4 := "4H" if tf5 == "60" tf5 := "1H" if tf5 == "120" tf5 := "2H" if tf5 == "180" tf5 := "3H" if tf5 == "240" tf5 := "4H" if tf6 == "60" tf6 := "1H" if tf6 == "120" tf6 := "2H" if tf6 == "180" tf6 := "3H" if tf6 == "240" tf6 := "4H" if tf7 == "60" tf7 := "1H" if tf7 == "120" tf7 := "2H" if tf7 == "180" tf7 := "3H" if tf7 == "240" tf7 := "4H" if tf8 == "60" tf8 := "1H" if tf8 == "120" tf8 := "2H" if tf8 == "180" tf8 := "3H" if tf8 == "240" tf8 := "4H" if tf9 == "60" tf9 := "1H" if tf9 == "120" tf9 := "2H" if tf9 == "180" tf9 := "3H" if tf9 == "240" tf9 := "4H" if tf10 == "60" tf10 := "1H" if tf10 == "120" tf10 := "2H" if tf10 == "180" tf10 := "3H" if tf10 == "240" tf10 := "4H" //--------------------------------------------------------------------------------------------- // Update table with trend data //--------------------------------------------------------------------------------------------- if (barstate.islast) table.cell(t, 0, 1, tf11, text_color=color.white, text_size=table_text_size,bgcolor = color.rgb(21, 21, 21)) table.cell(t, 1, 1, text="●", text_color=trend_indicator_1==uptrend_indicator?color.lime:color.red,text_size = size.large) table.cell(t, 2, 1, str.tostring(sar_1, "#.##"), text_color=color.white, text_size=table_text_size,bgcolor = color.rgb(21, 21, 21)) table.cell(t, 0, 2, tf22, text_color=color.white, text_size=table_text_size,bgcolor = color.rgb(21, 21, 21)) table.cell(t, 1, 2, text="●", text_color=trend_indicator_2==uptrend_indicator?color.lime:color.red,text_size = size.large) table.cell(t, 2, 2, str.tostring(sar_2, "#.##"), text_color=color.white, text_size=table_text_size,bgcolor = color.rgb(21, 21, 21)) table.cell(t, 0, 3, tf33, text_color=color.white, text_size=table_text_size,bgcolor= color.rgb(21, 21, 21)) table.cell(t, 1, 3, text="●", text_color=trend_indicator_3==uptrend_indicator?color.lime:color.red,text_size = size.large) table.cell(t, 2, 3, str.tostring(sar_3, "#.##"), text_color=color.white, text_size=table_text_size,bgcolor = color.rgb(21, 21, 21)) table.cell(t, 0, 4, tf4, text_color=color.white, text_size=table_text_size, bgcolor = color.rgb(21, 21, 21)) table.cell(t, 1, 4, text="●", text_color=trend_indicator_4==uptrend_indicator?color.lime:color.red,text_size = size.large) table.cell(t, 2, 4, str.tostring(sar_4, "#.##"), text_color=color.white, text_size=table_text_size,bgcolor = color.rgb(21, 21, 21)) table.cell(t, 0, 5, tf5, text_color=color.white, text_size=table_text_size, bgcolor = color.rgb(21, 21, 21)) table.cell(t, 1, 5, text="●", text_color=trend_indicator_5==uptrend_indicator?color.lime:color.red,text_size = size.large) table.cell(t, 2, 5, str.tostring(sar_5, "#.##"), text_color=color.white, text_size=table_text_size,bgcolor = color.rgb(21, 21, 21)) table.cell(t, 0, 6, tf6, text_color=color.white, text_size=table_text_size,bgcolor = color.rgb(21, 21, 21)) table.cell(t, 1, 6, text="●", text_color=trend_indicator_6==uptrend_indicator?color.lime:color.red,text_size = size.large) table.cell(t, 2, 6, str.tostring(sar_6, "#.##"), text_color=color.white, text_size=table_text_size,bgcolor = color.rgb(21, 21, 21)) table.cell(t, 0, 7, tf7, text_color=color.white, text_size=table_text_size,bgcolor = color.rgb(21, 21, 21)) table.cell(t, 1, 7, text="●", text_color=trend_indicator_7==uptrend_indicator?color.lime:color.red,text_size = size.large) table.cell(t, 2, 7, str.tostring(sar_7, "#.##"), text_color=color.white, text_size=table_text_size,bgcolor = color.rgb(21, 21, 21)) table.cell(t, 0, 8, tf8, text_color=color.white, text_size=table_text_size,bgcolor = color.rgb(21, 21, 21)) table.cell(t, 1, 8, text="●", text_color=trend_indicator_8==uptrend_indicator?color.lime:color.red,text_size = size.large) table.cell(t, 2, 8, str.tostring(sar_8, "#.##"), text_color=color.white, text_size=table_text_size,bgcolor = color.rgb(21, 21, 21)) table.cell(t, 0, 9, tf9, text_color=color.white, text_size=table_text_size,bgcolor = color.rgb(21, 21, 21)) table.cell(t, 1, 9, text="●", text_color=trend_indicator_9==uptrend_indicator?color.lime:color.red,text_size = size.large) table.cell(t, 2, 9, str.tostring(sar_9, "#.##"), text_color=color.white, text_size=table_text_size,bgcolor = color.rgb(21, 21, 21)) table.cell(t, 0, 10, tf10, text_color=color.white, text_size=table_text_size,bgcolor = color.rgb(21, 21, 21)) table.cell(t, 1, 10, text="●", text_color=trend_indicator_10==uptrend_indicator?color.lime:color.red,text_size = size.large) table.cell(t, 2, 10, str.tostring(sar_10, "#.##"), text_color=color.white, text_size=table_text_size,bgcolor = color.rgb(21, 21, 21)) table.cell(t,0,0,"Periyot",text_color = color.white,bgcolor = color.rgb(21, 21, 21)) table.cell(t,1,0,"Trend",text_color = color.white,bgcolor = color.rgb(21, 21, 21)) table.cell(t,2,0,"Fiyat",text_color = color.white,bgcolor = color.rgb(21, 21, 21)) lookback = input.int(5, "Line Lookback Period", minval=1) /////////////////////////////////////////////////////////////SAR HESAPLAMALARI YAP//////////////////////////// A111 = input(0.) B111 = input(0.01) C111 = input(0.1, ".") ABC111 = ta.sar(A111, B111, C111) plot(ABC111, "@yörük@", style=plot.style_cross, color=color.yellow, linewidth = 2) //////////////////////////////////////////////////////////////////////////////////////////////////// // === INPUTS === // atrLength33 = input.int(5, title="ATR Period") mult33 = input.float(1.0, title="ATR Multiplier (DES/DİR)") desLookback33 = input.int(1, title="DES/DİR Lookback Period") psarConfirmCount33 = input.int(6, title="Minimum PSAR Sayısı (Sinyal için)") // === PSAR Settings === // start33 = 0.01 max33 = 0.1 // === 10 PSAR hesapla === // psar133 = ta.sar(start33, 0.01, max33) psar233 = ta.sar(start33, 0.02, max33) psar333 = ta.sar(start33, 0.03, max33) psar433 = ta.sar(start33, 0.04, max33) psar533 = ta.sar(start33, 0.05, max33) psar633 = ta.sar(start33, 0.06, max33) psar733 = ta.sar(start33, 0.07, max33) psar833 = ta.sar(start33, 0.08, max33) psar933 = ta.sar(start33, 0.09, max33) psar1033 = ta.sar(start33, 0.10, max33) // === Kaç tanesi fiyatın altında/üstünde? === // countBelow33 = 0 countBelow33 := countBelow33 + (psar133 < close ? 1 : 0) countBelow33 := countBelow33 + (psar233 < close ? 1 : 0) countBelow33 := countBelow33 + (psar333 < close ? 1 : 0) countBelow33 := countBelow33 + (psar433 < close ? 1 : 0) countBelow33 := countBelow33 + (psar533 < close ? 1 : 0) countBelow33 := countBelow33 + (psar633 < close ? 1 : 0) countBelow33 := countBelow33 + (psar733 < close ? 1 : 0) countBelow33 := countBelow33 + (psar833 < close ? 1 : 0) countBelow33 := countBelow33 + (psar933 < close ? 1 : 0) countBelow33 := countBelow33 + (psar1033 < close ? 1 : 0) countAbove33 = 10 - countBelow33 // === Trend sinyalleri === // trendUp33 = countBelow33 >= psarConfirmCount33 trendDown33 = countAbove33 >= psarConfirmCount33 // === DES / DİR === // atr33 = ta.atr(atrLength33) dir33 = ta.lowest(desLookback33) + mult33 * atr33 des33 = ta.highest(desLookback33) - mult33 * atr33 plot(dir33, title="Direnç", color=color.rgb(223, 64, 251, 100), style=plot.style_linebr, linewidth=2) plot(des33, title="Destek", color=color.rgb(0, 187, 212, 100), style=plot.style_linebr, linewidth=2) //////// // === Ayarlar === leftBars47 = input(50, title = 'Pivot Left Bars') rightBars47 = input(50, title = 'Pivot Right Bars') projBars47 = input(50, title = 'Proj. Bars to the Right') // === Pivot Noktaları === ph47 = ta.pivothigh(leftBars47, rightBars47) pl47 = ta.pivotlow(leftBars47, rightBars47) // === Destek/Direnç çizgileri oluştur === if not na(ph47) line.new(bar_index - rightBars47, ph47, bar_index + projBars47, ph47, color = color.red, style = line.style_dashed, width = 2) if not na(pl47) line.new(bar_index - rightBars47, pl47, bar_index + projBars47, pl47, color = color.green, style = line.style_dashed, width = 2) ///////////////////////////////////////////////////////////

kombine edilmiş kodlar.... denemek isteyene....içinden istediğiniz kısmı silin atın.... şablon niyetine kullanılabilir....

Alıntı:

Originally Posted by @yörük@

hoşuma giden bir kod....
denemek isteyene.....

PHP Code:

//@version=6 indicator('Adaptive Parabolic SAR (PSAR) [Loxx]', shorttitle = '.', overlay = true, timeframe = '', timeframe_gaps = true) //thanks to @Bjorgum calcBaseUnit() => bool isForexSymbol = syminfo.type == 'forex' bool isYenPair = syminfo.currency == 'JPY' float result = isForexSymbol ? isYenPair ? 0.01 : 0.0001 : syminfo.mintick result greencolor = #2DD204 redcolor = #D2042D _afact(mode, input, per, smooth) => eff = 0. seff = 0. len = 0 sum = 0. max = 0. min = 1000000000. len := mode == 'Kaufman' ? math.ceil(per) : math.ceil(math.max(20, 5 * per)) for i = 0 to len by 1 if mode == 'Kaufman' sum := sum + math.abs(input[i] - input[i + 1]) sum else max := input[i] > max ? input[i] : max min := input[i] < min ? input[i] : min min if mode == 'Kaufman' and sum != 0 eff := math.abs(input - input[len]) / sum eff else if mode == 'Ehlers' and max - min > 0 eff := (input - min) / (max - min) eff seff := ta.ema(eff, smooth) seff src = input.source(close, 'Sourse', group = 'Basic Settings') startAFactor = input.float(0.1, 'Starting Acceleration Factor', step = 0.001, group = 'Basic Settings') minStep = input.float(0.0, 'Min Step', step = 0.001, group = 'Basic Settings') maxStep = input.float(0.2, 'Max Step', step = 0.001, group = 'Basic Settings') maxAFactor = input.float(0.2, 'Max Acceleration Factor', step = 0.001, group = 'Basic Settings') hiloMode = input.string('On', 'HiLo Mode', options = ['Off', 'On'], group = 'Advanced Settings') adaptMode = input.string('Kaufman', 'Adaptive Mode', options = ['Off', 'Kaufman', 'Ehlers'], group = 'Advanced Settings') adaptSmth = input.int(5, 'Adaptive Smoothing Period', minval = 1, group = 'Advanced Settings') filt = input.float(0.0, 'Filter in Pips', group = 'Advanced Settings', minval = 0) minChng = input.float(0.0, 'Min Change in Pips', group = 'Advanced Settings', minval = 0) SignalMode = input.string('Only Stops', 'Signal Mode', options = ['Only Stops', 'Signals & Stops'], group = 'Advanced Settings') colorbars = input.bool(false, 'Color bars?', group = 'UI Options') hVal2 = nz(high[2]) hVal1 = nz(high[1]) hVal0 = high lowVal2 = nz(low[2]) lowVal1 = nz(low[1]) lowVal0 = low hiprice2 = nz(high[2]) hiprice1 = nz(high[1]) hiprice0 = high loprice2 = nz(low[2]) loprice1 = nz(low[1]) loprice0 = low upSig = 0. dnSig = 0. aFactor = 0. step = 0. trend = 0. upTrndSAR = 0. dnTrndSAR = 0. length = 2 / maxAFactor - 1 if hiloMode == 'On' hiprice0 := high loprice0 := low loprice0 else hiprice0 := src loprice0 := hiprice0 loprice0 if bar_index == 1 trend := 1 hVal1 := hiprice1 hVal0 := math.max(hiprice0, hVal1) lowVal1 := loprice1 lowVal0 := math.min(loprice0, lowVal1) aFactor := startAFactor upTrndSAR := lowVal0 dnTrndSAR := 0. dnTrndSAR else hVal0 := hVal1 lowVal0 := lowVal1 trend := nz(trend[1]) aFactor := nz(aFactor[1]) inputs = 0. inprice = src if adaptMode != 'Off' if hiloMode == 'On' inprice := src inprice else inprice := hiprice0 inprice if adaptMode == 'Kaufman' inputs := inprice inputs else if adaptMode == 'Ehlers' if nz(upTrndSAR[1]) != 0. inputs := math.abs(inprice - nz(upTrndSAR[1])) inputs else if nz(dnTrndSAR[1]) != 0. inputs := math.abs(inprice - nz(dnTrndSAR[1])) inputs step := minStep + _afact(adaptMode, inputs, length, adaptSmth) * (maxStep - minStep) step else step := maxStep step upTrndSAR := 0. dnTrndSAR := 0. upSig := 0. dnSig := 0. if nz(trend[1]) > 0 if nz(trend[1]) == nz(trend[2]) aFactor := hVal1 > hVal2 ? nz(aFactor[1]) + step : aFactor aFactor := aFactor > maxAFactor ? maxAFactor : aFactor aFactor := hVal1 < hVal2 ? startAFactor : aFactor aFactor else aFactor := nz(aFactor[1]) aFactor upTrndSAR := nz(upTrndSAR[1]) + aFactor * (hVal1 - nz(upTrndSAR[1])) upTrndSAR := upTrndSAR > loprice1 ? loprice1 : upTrndSAR upTrndSAR := upTrndSAR > loprice2 ? loprice2 : upTrndSAR upTrndSAR else if nz(trend[1]) == nz(trend[2]) aFactor := lowVal1 < lowVal2 ? nz(aFactor[1]) + step : aFactor aFactor := aFactor > maxAFactor ? maxAFactor : aFactor aFactor := lowVal1 > lowVal2 ? startAFactor : aFactor aFactor else aFactor := nz(aFactor[1]) aFactor dnTrndSAR := nz(dnTrndSAR[1]) + aFactor * (lowVal1 - nz(dnTrndSAR[1])) dnTrndSAR := dnTrndSAR < hiprice1 ? hiprice1 : dnTrndSAR dnTrndSAR := dnTrndSAR < hiprice2 ? hiprice2 : dnTrndSAR dnTrndSAR hVal0 := hiprice0 > hVal0 ? hiprice0 : hVal0 lowVal0 := loprice0 < lowVal0 ? loprice0 : lowVal0 if minChng > 0 if upTrndSAR - nz(upTrndSAR[1]) < minChng * calcBaseUnit() and upTrndSAR != 0. and nz(upTrndSAR[1]) != 0. upTrndSAR := nz(upTrndSAR[1]) upTrndSAR if nz(dnTrndSAR[1]) - dnTrndSAR < minChng * calcBaseUnit() and dnTrndSAR != 0. and nz(dnTrndSAR[1]) != 0. dnTrndSAR := nz(dnTrndSAR[1]) dnTrndSAR dnTrndSAR := trend < 0 and dnTrndSAR > nz(dnTrndSAR[1]) ? nz(dnTrndSAR[1]) : dnTrndSAR upTrndSAR := trend > 0 and upTrndSAR < nz(upTrndSAR[1]) ? nz(upTrndSAR[1]) : upTrndSAR if trend < 0 and hiprice0 >= dnTrndSAR + filt * calcBaseUnit() trend := 1 upTrndSAR := lowVal0 upSig := SignalMode == 'Signals & Stops' ? lowVal0 : upSig dnTrndSAR := 0. aFactor := startAFactor lowVal0 := loprice0 hVal0 := hiprice0 hVal0 else if trend > 0 and loprice0 <= upTrndSAR - filt * calcBaseUnit() trend := -1 dnTrndSAR := hVal0 dnSig := SignalMode == 'Signals & Stops' ? hVal0 : dnSig upTrndSAR := 0. aFactor := startAFactor lowVal0 := loprice0 hVal0 := hiprice0 hVal0 outer = upTrndSAR > 0 ? upTrndSAR : dnTrndSAR colorout = outer >= src ? redcolor : greencolor plot(upTrndSAR > 0 ? upTrndSAR : dnTrndSAR, "Trend", color = colorout, style = plot.style_stepline_diamond, linewidth = 2) //barcolor(colorbars ? colorout : na) //plotshape(SignalMode == 'Signals & Stops' ? dnSig : na, color = redcolor, textcolor = redcolor, style = shape.triangledown, location = location.abovebar, size = size.small, title = 'Short', text = 'S') //plotshape(SignalMode == 'Signals & Stops' ? upSig : na, color = greencolor, textcolor = greencolor, style = shape.triangleup, location = location.belowbar, size = size.small, title = 'Long', text = 'L')

Bu sanki spesifik bir kod hocam...
Altcoin grafiklerinde veya senetlerde ben de benzer bir yöntem kullanıyordum geçmişte.
Örneğin altcoin için analiz yapıyorsan, BTCUSD'yi, hisse analizi yapıyorsan XU100 endeksini çarpan olarak kullanmak gibi...

Bu arkadaş da :

...

calcBaseUnit() =>
bool isForexSymbol = syminfo.type == 'forex'
bool isYenPair = syminfo.currency == 'JPY'
float result = isForexSymbol ? isYenPair ? 0.01 : 0.0001 : syminfo.mintick
result

...

if minChng > 0
if upTrndSAR - nz(upTrndSAR[1]) < minChng * calcBaseUnit() and upTrndSAR != 0. and nz(upTrndSAR[1]) != 0.
upTrndSAR := nz(upTrndSAR[1])
upTrndSAR
if nz(dnTrndSAR[1]) - dnTrndSAR < minChng * calcBaseUnit() and dnTrndSAR != 0. and nz(dnTrndSAR[1]) != 0.
dnTrndSAR := nz(dnTrndSAR[1])
dnTrndSAR

...

if trend < 0 and hiprice0 >= dnTrndSAR + filt * calcBaseUnit()
trend := 1
upTrndSAR := lowVal0
upSig := SignalMode == 'Signals & Stops' ? lowVal0 : upSig
dnTrndSAR := 0.
aFactor := startAFactor
lowVal0 := loprice0
hVal0 := hiprice0
hVal0

benzer bir yöntem kullanmış. JPY çarpanı, JPY ile ilgisi olmayan enstrümanlarda yanıltıcı olabilir.
"Bence", sanırım, galiba, herhalde...

seçilen sar değeriyle, mtf hesaplamayla...bar renklendirme.....denemek isteyene....

PHP Code:

//@version=6 indicator('..', shorttitle = '.', overlay = true, max_lines_count = 100, max_labels_count=100, max_boxes_count = 100, max_bars_back = 100) // ————————————————————————————————————————— f_colorNew(_color, _transp) => var _r = color.r(_color) var _g = color.g(_color) var _b = color.b(_color) color _return = color.rgb(_r, _g, _b, _transp) _return //automatic higher timeframe chooser f_autoHTF(str) => str == '1S' or str == '5S' or str == '10S' or str == '15S' or str == '20S' or str == '30S' or str == '40S' or str == '45S' or str == '50S' ? '1' : str == '1' or str == '2' or str == '3' or str == '4' ? '5' : str == '5' or str == '10' ? '15' : str == '15' or str == '20' ? '30' : str == '30' or str == '45' or str == '50' ? '60' : str == '60' or str == '90' or str == '100' ? '120' : str == '120' or str == '180' ? '240' : str == '240' ? 'D' : str == 'D' ? 'W' : str == 'W' ? '2W' : 'M' var string ticker = syminfo.tickerid var string tfp = timeframe.period htf1 = f_autoHTF(tfp) htf2 = f_autoHTF(htf1) htf3 = f_autoHTF(htf2) htf4 = f_autoHTF(htf3) f_security(_sym, _res, _src, _rep) => request.security(_sym, _res, _src[not _rep and barstate.isrealtime ? 1 : 0])[_rep or barstate.isrealtime ? 0 : 1] //PSAR inputs grpin = '⚙=====-----' grpout = '-----=====⚙' grpPSAR = grpin + 'Dual PSAR Options:' + grpout colorBull = input.color(defval = color.rgb(243, 243, 246), group = grpPSAR, title = 'Bullish Color') //Light Blue colorBear = input.color(defval = color.rgb(252, 5, 5), group = grpPSAR, title = 'Bearish Color') //yellow colorWait = input.color(defval = color.rgb(241, 191, 9), group = grpPSAR, title = 'Wait Color') //grey showRecolorCandles = input.bool(true, 'Show Trend Full-Candle Recoloring?', group = grpPSAR, tooltip = 'Recolor the full candle including wick and border with trend color.') psar_start = input.float(defval = 0.01, group = grpPSAR, title = 'PSAR: Start', minval = 0., maxval = 2, step = 0.01) psar_accel = input.float(defval = 0.01, group = grpPSAR, title = 'PSAR: Acceleration Factor', minval = 0.001, maxval = 2, step = 0.01) psar_maximum = input.float(defval = 0.01, group = grpPSAR, title = 'PSAR: Extreme Point', minval = 0.01, maxval = 2) f_psar() => ta.sar(psar_start, psar_accel, psar_maximum) psar_ctf = f_psar() psar_htf = f_security(ticker, htf1, f_psar(), false) longZone = psar_ctf < low and psar_htf < low shortZone = psar_ctf > high and psar_htf > high waitZone = not longZone and not shortZone trendSupportColor = longZone ? colorBull : shortZone ? colorBear : colorWait //plotcandle(showRecolorCandles ? open : na, high, low, close, color = trendSupportColor, wickcolor = trendSupportColor, bordercolor = trendSupportColor, title = 'BAR') barcolor(trendSupportColor) ///

Alıntı:

Originally Posted by KısaVade

Bu sanki spesifik bir kod hocam...
Altcoin grafiklerinde veya senetlerde ben de benzer bir yöntem kullanıyordum geçmişte.
Örneğin altcoin için analiz yapıyorsan, BTCUSD'yi, hisse analizi yapıyorsan XU100 endeksini çarpan olarak kullanmak gibi...

Bu arkadaş da :

...

calcBaseUnit() =>
bool isForexSymbol = syminfo.type == 'forex'
bool isYenPair = syminfo.currency == 'JPY'
float result = isForexSymbol ? isYenPair ? 0.01 : 0.0001 : syminfo.mintick
result

...

if minChng > 0
if upTrndSAR - nz(upTrndSAR[1]) < minChng * calcBaseUnit() and upTrndSAR != 0. and nz(upTrndSAR[1]) != 0.
upTrndSAR := nz(upTrndSAR[1])
upTrndSAR
if nz(dnTrndSAR[1]) - dnTrndSAR < minChng * calcBaseUnit() and dnTrndSAR != 0. and nz(dnTrndSAR[1]) != 0.
dnTrndSAR := nz(dnTrndSAR[1])
dnTrndSAR

...

if trend < 0 and hiprice0 >= dnTrndSAR + filt * calcBaseUnit()
trend := 1
upTrndSAR := lowVal0
upSig := SignalMode == 'Signals & Stops' ? lowVal0 : upSig
dnTrndSAR := 0.
aFactor := startAFactor
lowVal0 := loprice0
hVal0 := hiprice0
hVal0

benzer bir yöntem kullanmış. JPY çarpanı, JPY ile ilgisi olmayan enstrümanlarda yanıltıcı olabilir.
"Bence", sanırım, galiba, herhalde...

haklısın hocam... o yüzden değerlerde oynama yaptım.... x100 için denedim şimdilik....

bunu...ons..btc gibi farklı kullanmalarını denemek istiyorum....(gerçekten bistin, btc, ons, gramla korelasyonu var mı?)

(yedekleme olarak şimdilik kalsın)

Alıntı:

Originally Posted by @yörük@

haklısın hocam... o yüzden değerlerde oynama yaptım.... x100 için denedim şimdilik....

bunu...ons..btc gibi farklı kullanmalarını denemek istiyorum....

(yedekleme olarak şimdilik kalsın)

:ok: Eline sağlık üstadım.

Sonraki kod bende böyle:

https://i.ibb.co/ksdJT60c/taur.png

Görüntü şık :ok:

Alıntı:

Originally Posted by KısaVade

:ok: Eline sağlık üstadım.

Sonraki kod bende böyle:

https://i.ibb.co/ksdJT60c/taur.png

Görüntü şık :ok:

https://www.tradingview.com/x/3eaIRS3N/ bar kalıp kullanılan ve sarlar görüntü

https://www.tradingview.com/x/IT6wMqdd/ sar döngülü görüntü

bende böyle gözüküyor...

Alıntı:

Originally Posted by KısaVade

:ok: Eline sağlık üstadım.

Sonraki kod bende böyle:

https://i.ibb.co/ksdJT60c/taur.png

Görüntü şık :ok:

denemek istersen... o kodun....kombine edilmiş... farklı versiyonu....

PHP Code:

//@version=6 indicator("combine", shorttitle=".", overlay=true, max_lines_count=400, max_boxes_count=50, max_labels_count=5) // ── Enhanced Inputs string GRP1 = "Core Pattern Matching" string GRP2 = "Projection & Smoothing" string GRP3 = "Quality & Filtering" string GRP4 = "Visuals" int patLen = input.int(20, "Pattern Length", minval=8, maxval=200, group=GRP1) int fLen = input.int(30, "Forecast Bars", minval=5, maxval=300, group=GRP1) int depth = input.int(2000, "Search Depth", minval=200,maxval=6000,group=GRP1) float minConf = input.float(0.30,"Min Confidence", minval=0.10,maxval=0.95,step=0.05,group=GRP1) string scaling = input.string("Adaptive","Scaling Method", options=["Fixed","Adaptive","Volatility","Z-Score"], group=GRP2) string smoothing = input.string("EMA","Projection Smoothing", options=["None","SMA","EMA","Adaptive"], group=GRP2) int smoothLen = input.int(3, "Smoothing Length", minval=2, maxval=10, group=GRP2) bool useQualFilter = input.bool(true, "Enable Quality Filter", group=GRP3) float minVariance = input.float(0.001,"Min Pattern Variance", minval=0.0001, maxval=0.01, step=0.0001, group=GRP3) int trendCheck = input.int(5, "Trend Coherence Bars", minval=3, maxval=15, group=GRP3) bool showProj = input.bool(true, "Show Projection", group=GRP4) bool showBands = input.bool(true, "Show Bands", group=GRP4) bool showZones = input.bool(true, "Show Zones", group=GRP4) // Enhanced colors color upColor = input.color(#00FF88, "Uptrend (Green)", group=GRP4) color dnColor = input.color(#FF4444, "Downtrend (Red)", group=GRP4) color swColor = input.color(#FFAA00, "Sideways (Yellow)", group=GRP4) // ── Enhanced Data buffers var array<float> prices = array.new<float>() var array<int> times = array.new<int>() var array<float> highs = array.new<float>() var array<float> lows = array.new<float>() // handles var array<line> hProj = array.new<line>() var array<line> hBand = array.new<line>() var array<box> hBox = array.new<box>() var label hLbl = na // ── Enhanced Helper Functions safeDiv(float n, float d, float fb) => d == 0.0 ? fb : n / d // Enhanced cosine similarity with multiple normalization methods cosineSim(array<float> arr, int startA, int startB, int len, string method = "returns") => array<float> seqA = array.new<float>() array<float> seqB = array.new<float>() // Extract sequences for i = 0 to len - 1 array.push(seqA, array.get(arr, startA + i)) array.push(seqB, array.get(arr, startB + i)) // Normalize based on method if method == "returns" // Return-based normalization (original method) float dp = 0.0, na2 = 0.0, nb2 = 0.0 for k = 1 to len - 1 float a0 = array.get(seqA, k - 1) float a1 = array.get(seqA, k) float b0 = array.get(seqB, k - 1) float b1 = array.get(seqB, k) float ra = safeDiv(a1 - a0, a0, 0.0) float rb = safeDiv(b1 - b0, b0, 0.0) dp := dp + ra * rb na2 := na2 + ra * ra nb2 := nb2 + rb * rb float den = math.sqrt(na2) * math.sqrt(nb2) den == 0.0 ? 0.0 : dp / den else // Z-score normalization for more stable comparison float meanA = 0.0, meanB = 0.0 for i = 0 to len - 1 meanA := meanA + array.get(seqA, i) meanB := meanB + array.get(seqB, i) meanA := meanA / len meanB := meanB / len float stdA = 0.0, stdB = 0.0 for i = 0 to len - 1 float diffA = array.get(seqA, i) - meanA float diffB = array.get(seqB, i) - meanB stdA := stdA + diffA * diffA stdB := stdB + diffB * diffB stdA := math.sqrt(stdA / len) stdB := math.sqrt(stdB / len) if stdA == 0.0 or stdB == 0.0 0.0 else float dp = 0.0, na2 = 0.0, nb2 = 0.0 for i = 0 to len - 1 float za = (array.get(seqA, i) - meanA) / stdA float zb = (array.get(seqB, i) - meanB) / stdB dp := dp + za * zb na2 := na2 + za * za nb2 := nb2 + zb * zb float den = math.sqrt(na2) * math.sqrt(nb2) den == 0.0 ? 0.0 : dp / den // Pattern quality validation patternQuality(array<float> arr, int start, int len) => if start < 0 or start + len >= array.size(arr) 0.0 else // Calculate variance to ensure pattern has sufficient movement float mean = 0.0 for i = 0 to len - 1 mean := mean + array.get(arr, start + i) mean := mean / len float variance = 0.0 for i = 0 to len - 1 float diff = array.get(arr, start + i) - mean variance := variance + diff * diff variance := variance / len // Check trend coherence - avoid choppy patterns int trendChanges = 0 bool lastUp = false bool firstCheck = true for i = 1 to len - 1 bool currentUp = array.get(arr, start + i) > array.get(arr, start + i - 1) if not firstCheck and currentUp != lastUp trendChanges := trendChanges + 1 lastUp := currentUp firstCheck := false float coherence = 1.0 - (trendChanges / (len - 1)) math.sqrt(variance) * coherence // Enhanced smoothing function smoothProjection(array<float> proj, string method, int length) => array<float> smoothed = array.new<float>() int size = array.size(proj) if method == "None" for i = 0 to size - 1 array.push(smoothed, array.get(proj, i)) else if method == "SMA" for i = 0 to size - 1 float sum = 0.0 int count = 0 int start = math.max(0, i - length + 1) for j = start to i sum := sum + array.get(proj, j) count := count + 1 array.push(smoothed, sum / count) else if method == "EMA" float alpha = 2.0 / (length + 1.0) array.push(smoothed, array.get(proj, 0)) for i = 1 to size - 1 float prev = array.get(smoothed, i - 1) float curr = array.get(proj, i) array.push(smoothed, alpha * curr + (1.0 - alpha) * prev) else // Adaptive for i = 0 to size - 1 float sum = 0.0 float weightSum = 0.0 int adaptiveLen = i < length ? i + 1 : length for j = 0 to adaptiveLen - 1 float weight = 1.0 / (j + 1.0) sum := sum + array.get(proj, i - j) * weight weightSum := weightSum + weight array.push(smoothed, sum / weightSum) smoothed // Sample std of returns (enhanced for volatility scaling) retStd(array<float> arr, int start, int len) => if start < 1 or start + len >= array.size(arr) 0.0 else float s = 0.0 float c = 0.0 for k = start + 1 to start + len float r = safeDiv(array.get(arr, k) - array.get(arr, k - 1), array.get(arr, k - 1), 0.0) s := s + r c := c + 1.0 float m = safeDiv(s, c, 0.0) float ss = 0.0 for k = start + 1 to start + len float r = safeDiv(array.get(arr, k) - array.get(arr, k - 1), array.get(arr, k - 1), 0.0) float d = r - m ss := ss + d * d math.sqrt(safeDiv(ss, math.max(1.0, c - 1.0), 0.0)) // Array min/max over a range arrMin(array<float> a, int start, int len) => float m = na int stop = math.min(start + len, array.size(a)) if start >= 0 and start < array.size(a) for i = start to stop - 1 float v = array.get(a, i) m := na(m) ? v : math.min(m, v) m arrMax(array<float> a, int start, int len) => float m = na int stop = math.min(start + len, array.size(a)) if start >= 0 and start < array.size(a) for i = start to stop - 1 float v = array.get(a, i) m := na(m) ? v : math.max(m, v) m // Draw cleanup cleanup() => for l in hProj line.delete(l) array.clear(hProj) for l in hBand line.delete(l) array.clear(hBand) for b in hBox box.delete(b) array.clear(hBox) if not na(hLbl) label.delete(hLbl) // Keep arrays bounded keep(int maxKeep) => while array.size(prices) > maxKeep array.shift(prices) array.shift(times) array.shift(highs) array.shift(lows) // ── Ingest array.push(prices, close) array.push(times, time) array.push(highs, high) array.push(lows, low) keep(depth + patLen + fLen + 50) // ── Enhanced Engine if barstate.islastconfirmedhistory and array.size(prices) > patLen * 2 + fLen cleanup() hLbl := na int N = array.size(prices) int recentStart = N - patLen int searchEnd = N - patLen - fLen int searchStart = math.max(0, searchEnd - depth) float bestScore = -1.0 int bestIdx = 0 float bestQuality = 0.0 // Enhanced pattern search with quality filtering for i = searchStart to searchEnd // Check pattern quality first if filtering enabled float quality = useQualFilter ? patternQuality(prices, i, patLen) : 1.0 if quality >= minVariance string simMethod = scaling == "Z-Score" ? "zscore" : "returns" float s = cosineSim(prices, recentStart, i, patLen, simMethod) // Weight similarity by pattern quality float weightedScore = s * (0.7 + 0.3 * math.min(quality / (minVariance * 10.0), 1.0)) if weightedScore > bestScore bestScore := weightedScore bestIdx := i bestQuality := quality bool have = bestScore >= minConf if have // Enhanced scaling methods float cur = array.get(prices, N - 1) float baseHist = array.get(prices, bestIdx + patLen - 1) float scale = 1.0 if scaling == "Fixed" scale := 1.0 else if scaling == "Adaptive" scale := safeDiv(cur, baseHist, 1.0) else if scaling == "Volatility" float cstd = retStd(prices, N - 1 - patLen, patLen) float hstd = retStd(prices, bestIdx, patLen) float vr = safeDiv(cstd, hstd, 1.0) scale := safeDiv(cur, baseHist, 1.0) * vr else // Z-Score // Z-score based scaling for more stable projections float histMean = 0.0 for i = 0 to patLen - 1 histMean := histMean + array.get(prices, bestIdx + i) histMean := histMean / patLen float histStd = 0.0 for i = 0 to patLen - 1 float diff = array.get(prices, bestIdx + i) - histMean histStd := histStd + diff * diff histStd := math.sqrt(histStd / patLen) float currentStd = ta.stdev(close, patLen) scale := safeDiv(currentStd, histStd, 1.0) // Build raw projection path array<float> rawProj = array.new<float>() for k = 0 to fLen - 1 float src = array.get(prices, bestIdx + patLen + k) float val = cur + (src - baseHist) * scale array.push(rawProj, val) // Apply smoothing to projection array<float> proj = smoothProjection(rawProj, smoothing, smoothLen) // Enhanced confidence bands float baseVol = ta.atr(20) float confMult = (1.0 - bestScore) * 2.0 + (1.0 - bestQuality / (minVariance * 20.0)) * 1.0 array<float> up = array.new<float>() array<float> dn = array.new<float>() for i = 0 to array.size(proj) - 1 float val = array.get(proj, i) float dynamicConf = baseVol * confMult * (1.0 + i * 0.1 / fLen) // Expanding confidence array.push(up, val + dynamicConf) array.push(dn, val - dynamicConf) // Directional analysis with smoothed values float last = array.get(proj, array.size(proj) - 1) float pct = safeDiv(last - cur, cur, 0.0) * 100.0 color lnColor = math.abs(pct) < 0.3 ? swColor : (pct > 0 ? upColor : dnColor) // Draw enhanced projection if showProj line l0 = line.new(bar_index, cur, bar_index + 1, array.get(proj, 0), color=lnColor, width=3) array.push(hProj, l0) for k = 0 to array.size(proj) - 2 line lk = line.new(bar_index + k + 1, array.get(proj, k), bar_index + k + 2, array.get(proj, k + 1), color=lnColor, width=3) array.push(hProj, lk) // Enhanced bands if showBands color bc = color.new(lnColor, 70) line u0 = line.new(bar_index, cur + baseVol * confMult, bar_index + 1, array.get(up, 0), color=bc, style=line.style_dashed) line d0 = line.new(bar_index, cur - baseVol * confMult, bar_index + 1, array.get(dn, 0), color=bc, style=line.style_dashed) array.push(hBand, u0) array.push(hBand, d0) for k = 0 to array.size(up) - 2 line uu = line.new(bar_index + k + 1, array.get(up, k), bar_index + k + 2, array.get(up, k + 1), color=bc, style=line.style_dashed) line dd = line.new(bar_index + k + 1, array.get(dn, k), bar_index + k + 2, array.get(dn, k + 1), color=bc, style=line.style_dashed) array.push(hBand, uu) array.push(hBand, dd) // Zones (unchanged) if showZones float hLow = arrMin(lows, bestIdx, patLen) float hHigh = arrMax(highs, bestIdx, patLen) if not na(hLow) and not na(hHigh) box b1 = box.new(array.get(times, bestIdx), hLow, array.get(times, bestIdx + patLen - 1), hHigh, xloc=xloc.bar_time, bgcolor=color.new(lnColor, 85), border_color=color.new(lnColor, 55)) array.push(hBox, b1) float cLow = ta.lowest(low, patLen) float cHigh = ta.highest(high,patLen) box b2 = box.new(bar_index - patLen + 1, cLow, bar_index, cHigh, bgcolor=color.new(color.blue, 85), border_color=color.new(color.blue, 55)) array.push(hBox, b2) // Enhanced label with quality metrics string tname = math.abs(pct) < 0.3 ? "SIDEWAYS" : (pct > 0 ? "BULLISH" : "BEARISH") string emoji = math.abs(pct) < 0.3 ? "↔" : (pct > 0 ? "▲" : "▼") string lbl = str.format("{0} ENHANCED PROJECTION ({1})\nConfidence: {2,number,#.0}% | Quality: {3,number,#.0}%\nTarget: {4,number,#.##} | Change: {5,number,#.1}%\nMethod: {6} | Smoothing: {7}", emoji, tname, bestScore*100.0, bestQuality*10000.0, last, pct, scaling, smoothing) hLbl := label.new(bar_index + math.round(array.size(proj)/2.0), math.max(cur, last) + ta.atr(10), lbl, color=color.new(lnColor, 20), textcolor=color.white, style=label.style_label_down, size=size.normal) //////////////////// // UI Options for Auto Trend Detection and No Signal in Sideways Market autoTrendDetection = input.bool(true, title = 'Auto Trend Detection') noSignalSideways = input.bool(true, title = 'No Signal in Sideways Market') // Color variables upTrendColor = color.white neutralColor = #90bff9 downTrendColor = color.blue // Source source = input(defval = close, title = 'Source') // Sampling Period - Replaced with Sniper Machine period = input.int(defval = 9, minval = 1, title = 'Sniper Machine Period') // Trend Master - Replaced with Sniper Machine multiplier = input.float(defval = 3.0, minval = 0.1, title = 'Sniper Machine Multiplier') // Smooth Average Range smoothRange(x, t, m) => adjustedPeriod = t * 2 - 1 avgRange = ta.ema(math.abs(x - x[1]), t) smoothRange = ta.ema(avgRange, adjustedPeriod) * m smoothRange smoothedRange = smoothRange(source, period, multiplier) // Trend Filter trendFilter(x, r) => filtered = x filtered := x > nz(filtered[1]) ? x - r < nz(filtered[1]) ? nz(filtered[1]) : x - r : x + r > nz(filtered[1]) ? nz(filtered[1]) : x + r filtered filter = trendFilter(source, smoothedRange) // Filter Direction upCount = 0.0 upCount := filter > filter[1] ? nz(upCount[1]) + 1 : filter < filter[1] ? 0 : nz(upCount[1]) downCount = 0.0 downCount := filter < filter[1] ? nz(downCount[1]) + 1 : filter > filter[1] ? 0 : nz(downCount[1]) // Colors filterColor = upCount > 0 ? upTrendColor : downCount > 0 ? downTrendColor : neutralColor // Buy/Sell Signals - Adapted from Clear Trend Logic trendUp = upCount > 0 // Equivalent to REMA_up in Clear Trend newBuySignal = trendUp and not trendUp[1] and barstate.isconfirmed newSellSignal = not trendUp and trendUp[1] and barstate.isconfirmed initialCondition = 0 initialCondition := newBuySignal ? 1 : newSellSignal ? -1 : initialCondition[1] longSignal = newBuySignal and initialCondition[1] == -1 shortSignal = newSellSignal and initialCondition[1] == 1 // Alerts and Signals plotshape(longSignal, title = 'Buy Signal', text = '🚀', textcolor = #000000, style = shape.labelup, size = size.small, location = location.belowbar, color = #fae10400) // Bright yellow for Buy plotshape(shortSignal, title = 'Sell Signal', text = '🚨', textcolor = #000000, style = shape.labeldown, size = size.small, location = location.abovebar, color = #fb020200) // Bright red for Sell alertcondition(longSignal, title = 'Buy alert on Sniper Machine', message = 'Buy alert on Sniper Machine') alertcondition(shortSignal, title = 'Sell alert on Sniper Machine', message = 'Sell alert on Sniper Machine') /////////////// // Inputs src = input.source(hlc3, "Source") emaLen = input.int(15, "Center EMA") spreadN = input.int(200, "Spread Length") kMult = input.float(3.0, "Multiplier", step=0.1) upCol = input.color(color.rgb(251, 5, 5), "Up Color") dnCol = input.color(color.rgb(26,221,127), "Down Color") // Core calculation mid = ta.ema(src, emaLen) spread = ta.sma(high - low, spreadN) uBand = mid + kMult * spread lBand = mid - kMult * spread // Crawl bands var float upC = na var float dnC = na upC := na(upC[1]) ? uBand : (src[1] > upC[1] ? uBand : math.min(uBand, upC[1])) dnC := na(dnC[1]) ? lBand : (src[1] < dnC[1] ? lBand : math.max(lBand, dnC[1])) // Direction & guide var int dir = na var float guide = na if na(dir[1]) dir := 1 else dir := guide[1] == upC[1] ? (src > upC ? -1 : 1) : (src < dnC ? 1 : -1) guide := dir == 1 ? upC : dnC // Background zone fill bgcolor(dir==1 ? color.new(upCol, 85) : color.new(dnCol, 85), title="Trend Zone") // Guide line plot(guide, "Trs", color=color.new(dir==1?upCol:dnCol, 0), linewidth=1) // Signals trendUpbn = not na(dir[1]) and dir == -1 and dir[1] != -1 trendDownbn = not na(dir[1]) and dir == 1 and dir[1] != 1 pbUp = dir==-1 and high >= upC pbDown = dir==1 and low <= dnC dist = 0.25 * spread filteredPbUp = pbUp and (high - upC <= dist) filteredPbDown = pbDown and (dnC - low <= dist) firstPbUp = filteredPbUp and not filteredPbUp[1] firstPbDown = filteredPbDown and not filteredPbDown[1] // ATR for vertical spacing of signals atrVal = ta.atr(14) upY = low - 15 * atrVal downY = high + 10 * atrVal // Plot BUY/SELL arrows as labels for vertical spacing //if trendUpbn //label.new(bar_index, upY, text="BUY", style=label.style_triangleup, color=dnCol, textcolor=color.white, size=size.small, yloc=yloc.price) //if trendDownbn //label.new(bar_index, downY, text="SELL", style=label.style_triangledown, color=upCol, textcolor=color.white, size=size.small, yloc=yloc.price) // Pullback dots //plotshape(firstPbUp, style=shape.circle, location=location.belowbar, color=color.new(dnCol,0), size=size.small) //plotshape(firstPbDown, style=shape.circle, location=location.abovebar, color=color.new(upCol,0), size=size.small) ////////////////////// // --- User Inputs --- // NEW: Added the "20/20 Profile (Ultra-Safe)" option. profile = input.string('20/20 Profile (Ultra-Safe)', 'Select Profile', options = ['20/20 Profile (Ultra-Safe)', '16/16 Profile (Safe)', '12/12 Profile (Balanced)', '8/8 Profile (Aggressive)', 'Custom'], group = 'Grid Calculation') // These inputs are now only used when "Custom" is selected. customRangePercent = input.float(6.3, title = 'Custom Range as % of Price', group = 'Grid Calculation') customGridCount = input.int(12, title = 'Custom Grid Count', group = 'Grid Calculation') // Style Inputs gridColor = input.color(color.new(color.gray, 60), title = 'Grid Line Color', group = 'Line Style') gridWidth = input.int(1, title = 'Grid Line Width', minval = 1, maxval = 5, group = 'Line Style') gridStyleString = input.string('Dotted', title = 'Grid Line Style', options = ['Solid', 'Dashed', 'Dotted'], group = 'Line Style') // --- Variable Declarations --- var array<line> gridLines = array.new_line() var array<label> priceLabels = array.new_label() var float finalRangePercent = 0.0 var int finalGridCount = 0 // --- Logic to select parameters based on profile --- if profile == '20/20 Profile (Ultra-Safe)' finalRangePercent := 10.5 finalGridCount := 20 finalGridCount else if profile == '16/16 Profile (Safe)' finalRangePercent := 8.4 finalGridCount := 16 finalGridCount else if profile == '12/12 Profile (Balanced)' finalRangePercent := 6.3 finalGridCount := 12 finalGridCount else if profile == '8/8 Profile (Aggressive)' finalRangePercent := 4.2 finalGridCount := 8 finalGridCount else // Custom finalRangePercent := customRangePercent finalGridCount := customGridCount finalGridCount // --- Helper Function --- getLineStyle(styleString) => styleString == 'Solid' ? line.style_solid : styleString == 'Dashed' ? line.style_dashed : line.style_dotted // --- Drawing Logic --- if barstate.islast // Delete old lines and labels if array.size(gridLines) > 0 for lineId in gridLines line.delete(lineId) array.clear(gridLines) if array.size(priceLabels) > 0 for labelId in priceLabels label.delete(labelId) array.clear(priceLabels) // Main Calculation currentPrice = close totalRange = currentPrice * (finalRangePercent / 100) halfRange = totalRange / 2.0 upperLimit = currentPrice + halfRange lowerLimit = currentPrice - halfRange selectedGridStyle = getLineStyle(gridStyleString) // Draw Lines & Labels array.push(gridLines, line.new(bar_index - 99, upperLimit, bar_index, upperLimit, xloc = xloc.bar_index, extend = extend.none, color = color.new(color.green, 20), width = 2)) array.push(gridLines, line.new(bar_index - 99, lowerLimit, bar_index, lowerLimit, xloc = xloc.bar_index, extend = extend.none, color = color.new(color.red, 20), width = 2)) if finalGridCount > 1 stepSize = totalRange / finalGridCount for i = 1 to finalGridCount - 1 by 1 gridLevel = lowerLimit + i * stepSize array.push(gridLines, line.new(bar_index - 99, gridLevel, bar_index, gridLevel, xloc = xloc.bar_index, extend = extend.none, color = gridColor, width = gridWidth, style = selectedGridStyle)) array.push(priceLabels, label.new(bar_index, upperLimit, text = str.tostring(upperLimit, format.mintick), xloc = xloc.bar_index, color = color.new(color.green, 70), textcolor = color.white, style = label.style_label_left)) array.push(priceLabels, label.new(bar_index, lowerLimit, text = str.tostring(lowerLimit, format.mintick), xloc = xloc.bar_index, color = color.new(color.red, 70), textcolor = color.white, style = label.style_label_left)) /////////////////////////////////