# indie:lang_version = 5 # Comprehensive Indie Demo Indicator # This indicator demonstrates multiple Indie language features with full explanatory comments # © 2025 Pavel Medd (@pavelmedd) # Licensed under the MIT License. You may use, copy, modify, merge, publish, # distribute, sublicense, and/or sell copies of the Software, subject to the # conditions of the MIT license. Full license text: https://opensource.org/licenses/MIT import math from indie import indicator, param, plot, color, level, band, MutSeriesF, Optional, MainContext, sec_context, line_style, TimeFrame from indie.algorithms import Sma, Ema, Rsi, Atr from indie.plot import marker_style, marker_position, Line, Marker, Histogram, Columns # Secondary context to compute values on a higher timeframe @sec_context def HigherTFContext(self): # 14-period RSI and 50-period SMA on the higher timeframe rsi = Rsi.new(self.close, 14) sma = Sma.new(self.close, 50) # If close is above the SMA, we consider it an uptrend (score 1.0), else 0.0 trend_score = 1.0 if self.close[0] > sma[0] else 0.0 return rsi[0], sma[0], trend_score # Main indicator class @indicator('Comprehensive Demo', overlay_main_pane=False) @param.int('fast_length', default=12, min=1, max=50, title='Fast Length') # Fast EMA length @param.int('slow_length', default=26, min=1, max=100, title='Slow Length') # Slow SMA length @param.float('volatility_mult', default=2.0, min=0.5, max=5.0, title='Volatility Multiplier') # Volatility scaling factor @param.bool('show_higher_tf', default=True, title='Show Higher Timeframe') # Toggle for showing higher timeframe marker @param.time_frame('higher_tf', default='1D', title='Higher Timeframe') # Timeframe for higher timeframe analysis @plot.line(title='Main Line') # Custom MACD-like line @plot.line(title='Signal Line') # EMA of the main line @plot.histogram(title='Momentum') # Difference between current and previous close @plot.marker(title='HTF Marker') # Marker indicating higher timeframe trend @plot.marker(title='Crossover Marker') # Buy/Sell crossover signal marker @plot.marker(title='Volatility Alert') # Alert marker for high volatility @plot.columns(title='Volatility') # Column plot for ATR-based volatility class Main(MainContext): def __init__(self, higher_tf: TimeFrame): # Default values for higher timeframe fallback self.htf_rsi_val = 50.0 self.htf_sma_val = 0.0 self.htf_trend_val = 0.0 # Optional values for dynamic higher timeframe marker self._htf_marker_value = Optional[float](None) self._htf_marker_color = color.GRAY self._htf_marker_text = Optional[str](None) # Use higher timeframe only if different from current if higher_tf != self.time_frame: rsi_val, sma_val, trend_score = self.calc_on(HigherTFContext, time_frame=higher_tf) self.htf_rsi_val = float(rsi_val[0]) self.htf_sma_val = float(sma_val[0]) self.htf_trend_val = float(trend_score[0]) def calc(self, fast_length, slow_length, volatility_mult, show_higher_tf, higher_tf): # Calculate fast and slow moving averages fast_ma = Ema.new(self.close, fast_length) slow_ma = Sma.new(self.close, slow_length) rsi = Rsi.new(self.close, 14) # Crossover detection: bullish (cross up) or bearish (cross down) cross_up = self.close[1] <= slow_ma[1] and self.close[0] > slow_ma[0] cross_down = self.close[1] >= slow_ma[1] and self.close[0] < slow_ma[0] crossover_val = math.nan crossover_text: Optional[str] = Optional[str](None) crossover_color = color.GRAY crossover_detected = cross_up or cross_down if crossover_detected: crossover_val = 80.0 if cross_up else 20.0 direction = "+" if cross_up else "-" arrow = "^" if cross_up else "v" label = "BUY" if cross_up else "SELL" crossover_color = color.LIME if cross_up else color.RED crossover_text = Optional[str](arrow + " " + label + " " + direction) # Momentum calculation: price difference between current and previous close momentum_value = self.close[0] - self.close[1] momentum_color = color.GREEN if momentum_value > 0 else color.RED # ATR-based volatility: normalized as percentage of current close atr = Atr.new(10) volatility = atr[0] / self.close[0] * 100 # High volatility marker: appears on the price chart if volatility > 5% vol_marker = Marker(math.nan) if volatility > 5.0: vol_marker = Marker( self.close[0], text="X High Vol!", color=color.RED ) # MACD-like line: difference between fast and slow MA main_line = fast_ma[0] - slow_ma[0] signal_series = MutSeriesF.new(main_line) signal_line = Ema.new(signal_series, 9)[0] # Convert stored values to series for plotting HTF markers htf_rsi = MutSeriesF.new(self.htf_rsi_val) htf_trend = MutSeriesF.new(self.htf_trend_val) # HTF marker update every 50 bars to reduce clutter if show_higher_tf and self.bar_index % 50 == 0: marker_val = 80.0 if htf_trend[0] > 0 else 20.0 self._htf_marker_value = Optional[float](marker_val) self._htf_marker_color = color.GREEN if htf_trend[0] > 0 else color.RED rsi_val = htf_rsi[0] rsi_str = "HTF RSI: " + str(int(round(rsi_val))) if not math.isnan(rsi_val) else "x" self._htf_marker_text = Optional[str](rsi_str) else: self._htf_marker_value = Optional[float](None) self._htf_marker_text = Optional[str](None) htf_marker_val = self._htf_marker_value.value_or(math.nan) htf_marker_text = self._htf_marker_text.value_or("") if self._htf_marker_text is not None else None # Final output: all elements to render on chart return ( Line(main_line), # MACD-like signal Line(signal_line), # Smoothed signal line Histogram(momentum_value, color=momentum_color), # Price momentum Marker(htf_marker_val, text=htf_marker_text, color=self._htf_marker_color) if show_higher_tf and not math.isnan(htf_marker_val) else Marker(math.nan), Marker(crossover_val, text=crossover_text.value_or("") if crossover_text is not None else None, color=crossover_color) if crossover_detected else Marker(math.nan), vol_marker, # Volatility alert Columns( volatility * volatility_mult, # Volatility column color=color.rgba( 255 if volatility > 2 else 100, 100, 255 if volatility <= 2 else 100, 0.5 ) ) )