diff --git "a/Pinescript Folder/v5 Variant 2/fuhfuhlogic.ipynb" "b/Pinescript Folder/v5 Variant 2/fuhfuhlogic.ipynb" new file mode 100644--- /dev/null +++ "b/Pinescript Folder/v5 Variant 2/fuhfuhlogic.ipynb" @@ -0,0 +1,1193 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": null, + "id": "9132c720", + "metadata": { + "vscode": { + "languageId": "plaintext" + } + }, + "outputs": [], + "source": [ + "//@version=6\n", + "//indicator(\"v5\", overlay = true, max_labels_count = 300, max_lines_count = 300, max_boxes_count = 300, max_bars_back = 300)\n", + "indicator(\"Sunstoic\", \"v5\", true, max_bars_back = 5000, max_boxes_count = 500, max_lines_count = 500, max_labels_count = 500)\n", + "\n", + "\n", + "//candle logic\n", + "// === Inputs ===\n", + "bCol = input.color(#008080, title=\"Bull Border\")\n", + "rCol = input.color(#e20000, title=\"Bear Border\")\n", + "bgB = input.color(color.new(#008080, 20), title=\"Bull Body\")\n", + "bgR = input.color(color.new(#FF0000, 20), title=\"Bear Body\")\n", + "\n", + "\n", + " // === Input your time zone (Manila = GMT+8) \n", + "timeSessionStart = timestamp(\"GMT+8\", year, month, dayofmonth, 6, 0) // Start of day\n", + "isNewDay = ta.change(time(\"D\")) // Detect new day\n", + "\n", + "// Track the current day's developing close on each bar\n", + "var float devClose = na\n", + "if bool(isNewDay)\n", + " devClose := close // reset on new day\n", + "else\n", + " devClose := close // update each bar\n", + "\n", + "\n", + "// === Default Daily Candle (6:00 AM) ===\n", + "dO = request.security(syminfo.tickerid, \"D\", open)\n", + "dH = request.security(syminfo.tickerid, \"D\", high)\n", + "dL = request.security(syminfo.tickerid, \"D\", low)\n", + "dC = request.security(syminfo.tickerid, \"D\", close)\n", + "\n", + "\n", + "// Calculate daily high and low using 'day' timeframe\n", + "var float dailyHigh = na\n", + "var float dailyLow = na\n", + "newDay = ta.change(time(\"D\"))\n", + "\n", + "\n", + "// On new day, reset high/low\n", + "if bool(newDay)\n", + " dailyHigh := close\n", + " dailyLow := open\n", + "else\n", + " dailyHigh := math.max(dailyHigh, close)\n", + " dailyLow := math.min(dailyLow, open)\n", + "\n", + "\n", + "// Midpoint of the daily candle\n", + "midPrice = (dailyHigh + dailyLow) / 2\n", + "\n", + "\n", + "dBull = dC >= dO\n", + "dCol = dBull ? bCol : rCol\n", + "dBg = dBull ? bgB : bgR\n", + "\n", + "\n", + "// Offset for visuals\n", + "ofs = 10\n", + "bw = 2\n", + "rIdx = bar_index + ofs + bw / 2\n", + "lIdx = bar_index + ofs - bw / 2\n", + "xMid = int(bar_index + ofs)\n", + "\n", + "\n", + "// Body of daily candle box\n", + "var box dBx = na\n", + "box.delete(dBx)\n", + "tB = math.max(dO, devClose) //y=dC\n", + "bB = math.min(dO, devClose)\n", + "dBx := box.new(left=int(lIdx), right=int(rIdx), top=tB, bottom=bB, border_color=dCol, bgcolor=dBg)\n", + "\n", + "\n", + "// Wicks for daily candle\n", + "var line dW1 = na\n", + "var line dW2 = na\n", + "line.delete(dW1)\n", + "line.delete(dW2)\n", + "dW1 := line.new(x1=xMid, y1=dH, x2=xMid, y2=tB, color=dCol)\n", + "dW2 := line.new(x1=xMid, y1=bB, x2=xMid, y2=dL, color=dCol)\n", + "\n", + "\n", + "\n", + "// Labels for daily candle\n", + "var label lblO = na\n", + "var label lblH = na\n", + "var label lblL = na\n", + "var label lblC = na\n", + "label.delete(lblO)\n", + "label.delete(lblH)\n", + "label.delete(lblL)\n", + "label.delete(lblC)\n", + "\n", + "\n", + "lblStyle = label.style_label_right\n", + "lblSize = size.tiny\n", + "lblOfs = -2\n", + "\n", + "lblO := label.new(x=xMid + lblOfs, y=dO, text=\"6O \" + str.tostring(dO, \"#\"), style=lblStyle, color=color.new(#2195f3, 100), textcolor=color.black, size=lblSize)\n", + "lblH := label.new(x=xMid + lblOfs, y=dH, text=\"6H \" + str.tostring(dH, \"#\"), style=lblStyle, color=color.new(#2195f3, 100), textcolor=color.black, size=lblSize)\n", + "lblL := label.new(x=xMid + lblOfs, y=dL, text=\"6L \" + str.tostring(dL, \"#\"), style=lblStyle, color=color.new(#2195f3, 100), textcolor=color.black, size=lblSize)\n", + "lblC := label.new(x=xMid + lblOfs, y=devClose, text=\"6C \" + str.tostring(dC, \"#\"), style=lblStyle, color=color.new(#2195f3, 100), textcolor=color.black, size=lblSize)\n", + "\n", + "// === Custom Daily Candle (8:00 AM Manila) ===\n", + "sh = 24\n", + "sm = 0\n", + "st = timestamp(\"UTC\", year, month, dayofmonth, sh, sm)\n", + "\n", + "\n", + "var float cO = na\n", + "var float cH = na\n", + "var float cL = na\n", + "var float cC = na\n", + "\n", + "\n", + "if (time == st)\n", + " cO := open\n", + " cH := high\n", + " cL := low\n", + " cC := close\n", + "\n", + "\n", + "if (not na(cO))\n", + " cH := math.max(cH, high)\n", + " cL := math.min(cL, low)\n", + " cC := close\n", + "\n", + "\n", + "cBull = cC >= cO\n", + "cCol = cBull ? bCol : rCol\n", + "cBg = cBull ? bgB : bgR\n", + "\n", + "\n", + "cOfs = 12\n", + "cbw = 2\n", + "crIdx = bar_index + cOfs + cbw / 2\n", + "clIdx = bar_index + cOfs - cbw / 2\n", + "cX = int(bar_index + cOfs)\n", + "\n", + "\n", + "// Custom body box\n", + "var box cBx = na\n", + "box.delete(cBx)\n", + "ctB = math.max(cO, devClose) //y=dC\n", + "cbB = math.min(cO, devClose)\n", + "cBx := box.new(left=int(clIdx), right=int(crIdx), top=ctB, bottom=cbB, border_color=cCol, bgcolor=cBg)\n", + "\n", + "\n", + "// Custom wicks\n", + "var line cW1 = na\n", + "var line cW2 = na\n", + "line.delete(cW1)\n", + "line.delete(cW2)\n", + "cW1 := line.new(x1=cX, y1=cH, x2=cX, y2=ctB, color=cCol)\n", + "cW2 := line.new(x1=cX, y1=cbB, x2=cX, y2=cL, color=cCol)\n", + "\n", + "\n", + "// Custom labels\n", + "var label clO = na\n", + "var label clH = na\n", + "var label clL = na\n", + "var label clC = na\n", + "label.delete(clO)\n", + "label.delete(clH)\n", + "label.delete(clL)\n", + "label.delete(clC)\n", + "\n", + "\n", + "clStyle = label.style_label_left\n", + "clSize = size.tiny\n", + "clOfs = 2\n", + "\n", + "\n", + "clO := label.new(x=cX + clOfs, y=cO, text=\"8O \" + str.tostring(cO, \"#\"), style=clStyle, color=color.new(#2195f3, 100), textcolor=color.black, size=clSize)\n", + "clH := label.new(x=cX + clOfs, y=cH, text=\"8H \" + str.tostring(cH, \"#\"), style=clStyle, color=color.new(#2195f3, 100), textcolor=color.black, size=clSize)\n", + "clL := label.new(x=cX + clOfs, y=cL, text=\"8L \" + str.tostring(cL, \"#\"), style=clStyle, color=color.new(#2195f3, 100), textcolor=color.black, size=clSize)\n", + "clC := label.new(x=cX + clOfs, y=devClose, text=\"8C \" + str.tostring(dC, \"#\"), style=clStyle, color=color.new(#2195f3, 100), textcolor=color.black, size=clSize)\n", + "\n", + "// === High and Low Lines (using bar_index for x coords) ===\n", + "// Track bar_index of high and low bars within current day\n", + "var int highBarIndex = na\n", + "var int lowBarIndex = na\n", + "var float dayHigh = na\n", + "var float dayLow = na\n", + "\n", + "\n", + "startOfDay = timestamp(year, month, dayofmonth, 0, 0)\n", + "t6amManila = timestamp(\"Asia/Manila\", year, month, dayofmonth, 6, 0)\n", + "\n", + "\n", + "issNewDay = ta.change(time(\"D\"))\n", + "\n", + "\n", + "if (time >= startOfDay)\n", + " if na(dayHigh) or high > dayHigh\n", + " dayHigh := high\n", + " highBarIndex := bar_index\n", + " if na(dayLow) or low < dayLow\n", + " dayLow := low\n", + " lowBarIndex := bar_index\n", + "\n", + "\n", + "if bool(issNewDay)\n", + " dayHigh := na\n", + " dayLow := na\n", + " highBarIndex := na\n", + " lowBarIndex := na\n", + "\n", + "\n", + "// Draw high line from high bar index to current xMid\n", + "var line highLine = na\n", + "if not na(dayHigh) and not na(highBarIndex)\n", + " if na(highLine)\n", + " highLine := line.new(x1=highBarIndex, y1=dayHigh, x2=xMid, y2=dayHigh, color=dCol, width=2, style = line.style_solid)\n", + " else\n", + " line.set_xy1(highLine, highBarIndex, dayHigh)\n", + " line.set_xy2(highLine, xMid, dayHigh)\n", + "\n", + "\n", + "// Draw low line from low bar index to current xMid\n", + "var line lowLine = na\n", + "if not na(dayLow) and not na(lowBarIndex)\n", + " if na(lowLine)\n", + " lowLine := line.new(x1=lowBarIndex, y1=dayLow, x2=xMid, y2=dayLow, color=dCol, width=2, style = line.style_solid)\n", + " else\n", + " line.set_xy1(lowLine, lowBarIndex, dayLow)\n", + " line.set_xy2(lowLine, xMid, dayLow)\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "// --- 6:00 AM Asia/Manila horizontal line ---\n", + "// Manila 6:00 AM timestamp today\n", + "manila_6am = timestamp(\"GMT+8\", year, month, dayofmonth, 30, 0)\n", + "\n", + "\n", + "// Detect bar where time crosses 6:00 AM Manila\n", + "isStartBar6am = (time >= manila_6am) and (time[1] < manila_6am)\n", + "\n", + "\n", + "// Store 6:00 AM bar open price and index\n", + "var float price6am = na\n", + "var int bar6am_index = na\n", + "\n", + "\n", + "if isStartBar6am\n", + " price6am := open\n", + " bar6am_index := bar_index\n", + "\n", + "\n", + "// Draw horizontal line from 6AM bar index to xMid at price6am\n", + "var line hLine6am = na\n", + "\n", + "\n", + "if not na(price6am) and not na(bar6am_index)\n", + " line.delete(hLine6am)\n", + " hLine6am := line.new(x1=bar6am_index, y1=price6am, x2=xMid, y2=price6am, color=color.new(#ecc900, 0), width=1, style=line.style_solid)\n", + "\n", + "\n", + "// --- 8:00 AM Asia/Manila horizontal line ---\n", + "// Detect bar where time crosses 8:00 AM Manila\n", + "isStartBar8am = (time >= st) and (time[1] < st)\n", + "\n", + "\n", + "// Store 8:00 AM bar open price and index\n", + "var float price8am = na\n", + "var int bar8am_index = na\n", + "\n", + "\n", + "if isStartBar8am\n", + " price8am := open\n", + " bar8am_index := bar_index\n", + "\n", + "\n", + "// Draw horizontal line from 8AM bar index to cX at price8am\n", + "var line hLine8am = na\n", + "var line hhLine8am = na\n", + "\n", + "\n", + "if not na(price8am) and not na(bar8am_index)\n", + " line.delete(hLine8am)\n", + " hLine8am := line.new(x1=bar8am_index, y1=price8am, x2=cX, y2=price8am, color=color.new(#fad400, 0), width=1, style=line.style_solid)\n", + "\n", + "\n", + "\n", + "// Draw horizontal line that updates000000000000000000000000\n", + "var line devCloseLine = na\n", + "var line ddevCloseLine = na\n", + "if bar_index > 0\n", + " if na(devCloseLine)\n", + " devCloseLine := line.new(x1=bar_index, y1=devClose , x2=xMid , y2=devClose, style = line.style_solid, color=color.new(#ecc900, 0), width=1)\n", + " else\n", + " line.set_xy1(devCloseLine, bar_index, devClose)\n", + " line.set_xy2(devCloseLine, bar_index + 13, devClose)\n", + " if na(ddevCloseLine) \n", + " //ddevCloseLine := line.new(x1=xMid, y1=devClose, x2=xMid, y2=devClose, extend=extend.right, color=dCol, width=2)\n", + " ddevCloseLine := line.new(x1=xMid, y1=devClose, x2=xMid , y2=devClose, style = line.style_dotted, extend=extend.right, color=color.black, width=1)\n", + " else\n", + " line.set_xy1(ddevCloseLine, bar_index + 19, devClose)\n", + " line.set_xy2(ddevCloseLine, bar_index + 20, devClose)\n", + "\n", + "\n", + "\n", + "//zone logic\n", + "// Disable visuals if timeframe is higher than 1 hour\n", + "isValidTF = timeframe.isminutes and timeframe.multiplier <= 60\n", + "\n", + "\n", + "// Current time components\n", + "currentTime = timestamp(year, month, dayofmonth, hour, minute)\n", + "\n", + "// Define 12PM to 12AM session\n", + "start12pm = timestamp(year, month, dayofmonth, 12, 0)\n", + "end12am = timestamp(year, month, dayofmonth, 23, 59)\n", + "in12pmTo12am = currentTime >= start12pm and currentTime <= end12am\n", + "\n", + "// Define 8AM to 8PM session\n", + "start8am = timestamp(year, month, dayofmonth, 8, 0)\n", + "end8pm = timestamp(year, month, dayofmonth, 20, 0)\n", + "in8amTo8pm = currentTime >= start8am and currentTime <= end8pm\n", + "\n", + "// Define 6PM to 8PM session\n", + "start6pm = timestamp(year, month, dayofmonth, 6, 0)\n", + "eend8pm = timestamp(year, month, dayofmonth, 8, 0)\n", + "in6pmTo8pm = currentTime >= start6pm and currentTime <= eend8pm\n", + "\n", + "start6am = timestamp(year, month, dayofmonth, 18, 0)\n", + "eend8am = timestamp(year, month, dayofmonth, 20, 0)\n", + "in6amTo8am = currentTime >= start6am and currentTime <= eend8am\n", + "\n", + "// Apply background highlights\n", + "bgcolor(isValidTF and in12pmTo12am ? color.new(color.black, 99) : na)\n", + "bgcolor(isValidTF and in8amTo8pm ? color.new(color.black, 99) : na)\n", + "bgcolor(isValidTF and in6pmTo8pm ? color.new(color.black, 97) : na)\n", + "bgcolor(isValidTF and in6amTo8am ? color.new(color.black, 95) : na)\n", + "\n", + "// Get the current day of the week and the current time\n", + "isMonday = dayofweek == dayofweek.sunday\n", + "ccurrentTime = timestamp(year, month, dayofmonth, hour, minute)\n", + "\n", + "// Define the time range for 6:00 AM to 8:00 AM\n", + "startTime = timestamp(year, month, dayofmonth, 18, 6) // 6:00 AM\n", + "endTime = timestamp(year, month, dayofmonth, 20, 0) // 8:00 AM\n", + "\n", + "// Check if it's Monday and the current time is within the range of 6:00 AM to 8:00 AM\n", + "isInTimeRange = isMonday and ccurrentTime >= startTime and ccurrentTime <= endTime\n", + "\n", + "// Highlight the area with a background color\n", + "bgcolor(isValidTF and isInTimeRange ? color.new(color.blue, 90) : na)\n", + "\n", + "// Vertical lines logic\n", + "// Only show vertical lines if timeframe is intraday and valid\n", + "showLines = timeframe.isintraday and isValidTF\n", + "\n", + "// Convert current bar time to Asia/Manila timezone\n", + "t = time(timeframe.period, 'Asia/Manila')\n", + "\n", + "// Target hours excluding 0, 12, 20\n", + "var array targetHours = array.from(3, 6, 8, 15, 24) // 24 means midnight (0h)\n", + "\n", + "// Special hours separated\n", + "specialHour20 = 20\n", + "specialHour0 = 0 // midnight\n", + "specialHour12 = 12 // noon\n", + "\n", + "// Function to check if current bar time matches any target hour exactly at minute zero\n", + "isTargetTime() =>\n", + " h = hour(t)\n", + " m = minute(t)\n", + " match = false\n", + " for i = 0 to array.size(targetHours) - 1 by 1\n", + " if (h == array.get(targetHours, i) or h == 0 and array.get(targetHours, i) == 24) and m == 0\n", + " match := true\n", + " match\n", + " match\n", + "\n", + "// Check if current time matches special hour 20 at minute zero\n", + "isSpecialTime20() =>\n", + " h = hour(t)\n", + " m = minute(t)\n", + " h == specialHour20 and m == 0\n", + "\n", + "// Check if current time matches special hour 0 at minute zero\n", + "isSpecialTime0() =>\n", + " h = hour(t)\n", + " m = minute(t)\n", + " h == specialHour0 and m == 0\n", + "\n", + "// Check if current time matches special hour 12 at minute zero\n", + "isSpecialTime12() =>\n", + " h = hour(t)\n", + " m = minute(t)\n", + " h == specialHour12 and m == 0\n", + "\n", + "// Detect new day (day break)\n", + "nnewDay = ta.change(time('D'))\n", + "\n", + "// Only draw lines if timeframe is intraday and valid\n", + "if showLines\n", + " // Draw vertical line at day break (green, width 1)\n", + " if bool(nnewDay)\n", + " line.new(bar_index, low - 10 * syminfo.mintick, bar_index, high + 10 * syminfo.mintick, color = color.rgb(76, 175, 79, 30), width = 1, extend = extend.both)\n", + "\n", + " // Draw vertical line at target times (blue, width 1)\n", + " if isTargetTime()\n", + " line.new(bar_index, low - 10 * syminfo.mintick, bar_index, high + 10 * syminfo.mintick, color = color.rgb(33, 149, 243, 90), width = 1, extend = extend.both)\n", + "\n", + " // Draw vertical line at special hour 20 (teal, width 1)\n", + " if isSpecialTime20()\n", + " line.new(bar_index, low - 10 * syminfo.mintick, bar_index, high + 10 * syminfo.mintick, color = color.new(color.teal, 50), width = 1, extend = extend.both)\n", + "\n", + " // Draw vertical line at special hour 0 (midnight) - orange, dotted\n", + " if isSpecialTime0()\n", + " var line midnightLine = na\n", + " midnightLine := line.new(bar_index, low - 10 * syminfo.mintick, bar_index, high + 10 * syminfo.mintick, color = color.orange, width = 1, extend = extend.both)\n", + " line.set_style(midnightLine, line.style_dotted)\n", + "\n", + " // Draw vertical line at special hour 12 (noon) - red, dotted\n", + " if isSpecialTime12()\n", + " var line noonLine = na\n", + " noonLine := line.new(bar_index, low - 10 * syminfo.mintick, bar_index, high + 10 * syminfo.mintick, color = color.red, width = 1, extend = extend.both)\n", + " line.set_style(noonLine, line.style_dotted)\n", + "\n", + "//hourly logic\n", + "// === UTILITY FUNCTION ===\n", + "f_show(tf) =>\n", + " timeframe.period != tf\n", + "\n", + "// === HOURLY ===\n", + "hH = request.security(syminfo.tickerid, '60', high, lookahead = barmerge.lookahead_on)\n", + "hL = request.security(syminfo.tickerid, '60', low, lookahead = barmerge.lookahead_on)\n", + "hIdx = request.security(syminfo.tickerid, '60', bar_index, lookahead = barmerge.lookahead_on)\n", + "\n", + "var int hPrev = na\n", + "var float hHi = na\n", + "var int hHiBar = na\n", + "var line hHiLine = na\n", + "var bool hHiOn = false\n", + "var float hLo = na\n", + "var int hLoBar = na\n", + "var line hLoLine = na\n", + "var bool hLoOn = false\n", + "\n", + "if hIdx != hPrev\n", + " hPrev := hIdx\n", + " hHi := na\n", + " hHiBar := na\n", + " line.delete(hHiLine)\n", + " hHiLine := na\n", + " hHiOn := false\n", + " hLo := na\n", + " hLoBar := na\n", + " line.delete(hLoLine)\n", + " hLoLine := na\n", + " hLoOn := false\n", + " hLoOn\n", + "\n", + "if hHiOn and not na(hHiLine)\n", + " bMin = math.min(open, close)\n", + " bMax = math.max(open, close)\n", + " if hHi <= bMax and hHi >= bMin\n", + " line.set_x2(hHiLine, bar_index)\n", + " line.set_y2(hHiLine, hHi)\n", + " hHiOn := false\n", + " hHiOn\n", + " else\n", + " line.set_x2(hHiLine, bar_index)\n", + " line.set_y2(hHiLine, hHi)\n", + "\n", + "if hLoOn and not na(hLoLine)\n", + " bMin = math.min(open, close)\n", + " bMax = math.max(open, close)\n", + " if hLo <= bMax and hLo >= bMin\n", + " line.set_x2(hLoLine, bar_index)\n", + " line.set_y2(hLoLine, hLo)\n", + " hLoOn := false\n", + " hLoOn\n", + " else\n", + " line.set_x2(hLoLine, bar_index)\n", + " line.set_y2(hLoLine, hLo)\n", + "\n", + "// === 30M ===\n", + "tH = request.security(syminfo.tickerid, '30', high, lookahead = barmerge.lookahead_on)\n", + "tL = request.security(syminfo.tickerid, '30', low, lookahead = barmerge.lookahead_on)\n", + "tO = request.security(syminfo.tickerid, '30', open, lookahead = barmerge.lookahead_on)\n", + "tC = request.security(syminfo.tickerid, '30', close, lookahead = barmerge.lookahead_on)\n", + "tIdx = request.security(syminfo.tickerid, '30', bar_index, lookahead = barmerge.lookahead_on)\n", + "\n", + "plot(tO, title = '30M Open', color = color.rgb(0, 20, 133, 80), style = plot.style_stepline_diamond, linewidth = 1)\n", + "\n", + "isBull = tC > tO\n", + "isBear = tC < tO\n", + "\n", + "phb = plot(isBull ? tH : na, color = color.new(#4caf4f, 100), style = plot.style_steplinebr)\n", + "plb = plot(isBull ? tL : na, color = color.new(#4caf4f, 100), style = plot.style_steplinebr)\n", + "phr = plot(isBear ? tH : na, color = color.new(#ff5252, 100), style = plot.style_steplinebr)\n", + "plr = plot(isBear ? tL : na, color = color.new(#ff5252, 100), style = plot.style_steplinebr)\n", + "\n", + "fill(phb, plb, color = color.new(color.blue, 95))\n", + "fill(phr, plr, color = color.new(color.red, 95))\n", + "\n", + "var int tPrev = na\n", + "var float tHi = na\n", + "var int tHiBar = na\n", + "var line tHiLine = na\n", + "var bool tHiOn = false\n", + "var float tLo = na\n", + "var int tLoBar = na\n", + "var line tLoLine = na\n", + "var bool tLoOn = false\n", + "\n", + "if tIdx != tPrev\n", + " tPrev := tIdx\n", + " tHi := na\n", + " tHiBar := na\n", + " line.delete(tHiLine)\n", + " tHiLine := na\n", + " tHiOn := false\n", + " tLo := na\n", + " tLoBar := na\n", + " line.delete(tLoLine)\n", + " tLoLine := na\n", + " tLoOn := false\n", + " tLoOn\n", + "\n", + "if tHiOn and not na(tHiLine)\n", + " bMin = math.min(open, close)\n", + " bMax = math.max(open, close)\n", + " if tHi <= bMax and tHi >= bMin\n", + " line.set_x2(tHiLine, bar_index)\n", + " line.set_y2(tHiLine, tHi)\n", + " tHiOn := false\n", + " tHiOn\n", + " else\n", + " line.set_x2(tHiLine, bar_index)\n", + " line.set_y2(tHiLine, tHi)\n", + "\n", + "if tLoOn and not na(tLoLine)\n", + " bMin = math.min(open, close)\n", + " bMax = math.max(open, close)\n", + " if tLo <= bMax and tLo >= bMin\n", + " line.set_x2(tLoLine, bar_index)\n", + " line.set_y2(tLoLine, tLo)\n", + " tLoOn := false\n", + " tLoOn\n", + " else\n", + " line.set_x2(tLoLine, bar_index)\n", + " line.set_y2(tLoLine, tLo)\n", + "\n", + "// === D/W/M High-Low Steplines ===\n", + "ddH = request.security(syminfo.tickerid, 'D', high, lookahead = barmerge.lookahead_on)\n", + "ddL = request.security(syminfo.tickerid, 'D', low, lookahead = barmerge.lookahead_on)\n", + "wH = request.security(syminfo.tickerid, 'W', high, lookahead = barmerge.lookahead_on)\n", + "wL = request.security(syminfo.tickerid, 'W', low, lookahead = barmerge.lookahead_on)\n", + "mH = request.security(syminfo.tickerid, 'M', high, lookahead = barmerge.lookahead_on)\n", + "mL = request.security(syminfo.tickerid, 'M', low, lookahead = barmerge.lookahead_on)\n", + "\n", + "plot(f_show('60') ? hH : na, title = 'H High', color = color.new(color.black, 90), style = plot.style_stepline, linewidth = 2)\n", + "plot(f_show('60') ? hL : na, title = 'H Low', color = color.new(color.black, 90), style = plot.style_stepline, linewidth = 2)\n", + "plot(f_show('D') ? ddH : na, title = 'D High', color = color.new(color.green, 50), style = plot.style_stepline)\n", + "plot(f_show('D') ? ddL : na, title = 'D Low', color = color.new(color.green, 70), style = plot.style_stepline)\n", + "plot(f_show('W') ? wH : na, title = 'W High', color = color.new(color.blue, 50), style = plot.style_stepline)\n", + "plot(f_show('W') ? wL : na, title = 'W Low', color = color.new(color.blue, 70), style = plot.style_stepline)\n", + "plot(f_show('M') ? mH : na, title = 'M High', color = color.new(color.purple, 40), style = plot.style_stepline)\n", + "plot(f_show('M') ? mL : na, title = 'M Low', color = color.new(color.purple, 60), style = plot.style_stepline)\n", + "\n", + "\n", + "//vwap logic\n", + "// VWAP calculation from 1-minute data\n", + "f_vwap_calc() =>\n", + " var float cumPV = 0.0\n", + " var float cumVol = 0.0\n", + " var float cumPV_buy = 0.0\n", + " var float cumVol_buy = 0.0\n", + " var float cumPV_sell = 0.0\n", + " var float cumVol_sell = 0.0\n", + "\n", + " // Reset on new day\n", + " if bool(ta.change(time('D')))\n", + " cumPV := 0.0\n", + " cumVol := 0.0\n", + " cumPV_buy := 0.0\n", + " cumVol_buy := 0.0\n", + " cumPV_sell := 0.0\n", + " cumVol_sell := 0.0\n", + " cumVol_sell\n", + "\n", + " buyVol = close > open ? volume : 0.0\n", + " sellVol = close < open ? volume : 0.0\n", + "\n", + " cumPV := cumPV + close * volume\n", + " cumVol := cumVol + volume\n", + "\n", + " cumPV_buy := cumPV_buy + close * buyVol\n", + " cumVol_buy := cumVol_buy + buyVol\n", + "\n", + " cumPV_sell := cumPV_sell + close * sellVol\n", + " cumVol_sell := cumVol_sell + sellVol\n", + "\n", + " vwap = cumVol != 0 ? cumPV / cumVol : na\n", + " buyVWAP = cumVol_buy != 0 ? cumPV_buy / cumVol_buy : na\n", + " sellVWAP = cumVol_sell != 0 ? cumPV_sell / cumVol_sell : na\n", + "\n", + " [vwap, buyVWAP, sellVWAP]\n", + "\n", + "// Pull 1-minute VWAP values\n", + "[vwap_1m, buyVWAP_1m, sellVWAP_1m] = request.security(syminfo.tickerid, '1', f_vwap_calc())\n", + "\n", + "// Only show on intraday charts\n", + "showVWAP = not timeframe.isdaily and not timeframe.isweekly and not timeframe.ismonthly\n", + " \n", + "// Plot VWAPs with conditional display\n", + "plot_vwap = plot(showVWAP ? vwap_1m : na, color = color.rgb(255, 153, 0, 0), linewidth = 1, title = 'VWAP (1m)')\n", + "plot_buy_vwap = plot(showVWAP ? buyVWAP_1m : na, color = color.rgb(0, 137, 123, 80), linewidth = 1, title = 'Buy Delta VWAP (1m)')\n", + "plot_sell_vwap = plot(showVWAP ? sellVWAP_1m : na, color = color.rgb(255, 82, 82, 80), linewidth = 1, title = 'Sell Delta VWAP (1m)')\n", + "\n", + "// Fill areas\n", + "fill(plot_vwap, plot_buy_vwap, color = showVWAP ? color.new(color.teal, 95) : na, title = 'Buy VWAP Fill')\n", + "fill(plot_vwap, plot_sell_vwap, color = showVWAP ? color.new(color.red, 95) : na, title = 'Sell VWAP Fill')\n", + "\n", + "//table logic\n", + "// === Function to get OHLC of specified candle ===\n", + "get_prev_ohlc(tf, shift) =>\n", + " o = request.security(syminfo.tickerid, tf, open[shift])\n", + " h = request.security(syminfo.tickerid, tf, high[shift])\n", + " l = request.security(syminfo.tickerid, tf, low[shift])\n", + " c = request.security(syminfo.tickerid, tf, close[shift])\n", + " [o, h, l, c]\n", + "\n", + "// === Function to calculate ranges and colors ===\n", + "get_data(tf, shift) =>\n", + " [o, h, l, c] = get_prev_ohlc(tf, shift)\n", + " full_range = h - l\n", + " oc_range = math.abs(c - o)\n", + " hl_range = h - l\n", + " is_bull = c > o\n", + " bg_color = is_bull ? color.new(color.green, 90) : color.new(color.red, 90)\n", + " [full_range, oc_range, hl_range, bg_color]\n", + "\n", + "// === Daily Candle Data ===\n", + "[d1_fr, d1_oc, d1_hl, d1_bg] = get_data(\"D\", 1)\n", + "[d2_fr, d2_oc, d2_hl, d2_bg] = get_data(\"D\", 2)\n", + "\n", + "// === Weekly Candle Data ===\n", + "[w0_fr, w0_oc, w0_hl, w0_bg] = get_data(\"W\", 0) // Developing Week\n", + "[w1_fr, w1_oc, w1_hl, w1_bg] = get_data(\"W\", 1)\n", + "[w2_fr, w2_oc, w2_hl, w2_bg] = get_data(\"W\", 2)\n", + "\n", + "\n", + "// Daily candle (6:00 AM)\n", + "sixambgcolor = dO < dC ? color.rgb(76, 175, 79, 90) : color.rgb(255, 82, 82, 90)\n", + "\n", + "// Custom candle (8:00 AM Manila)\n", + "eightambgcolor = cO < cC ? color.rgb(76, 175, 79, 90) : color.rgb(255, 82, 82, 90) \n", + "\n", + "// Adjust UTC time to Manila (UTC+8) qewrqwerwerwerwerwerew\n", + "manilaTime = time + 8 * 60 * 60 * 1000 // Shift by 8 hours in milliseconds\n", + "\n", + "// Extract date components from Manila time\n", + "manilaYear = year(manilaTime)\n", + "manilaMonth = month(manilaTime)\n", + "manilaDay = dayofmonth(manilaTime)\n", + "\n", + "// Format date as \"DD/MM/YYYY\"\n", + "formattedDate = str.tostring(manilaDay, \"00\") + \"/\" + str.tostring(manilaMonth, \"00\") + \"/\" + str.tostring(manilaYear)\n", + "\n", + "// Track day changes in Manila time\n", + "var int prevManilaDay = na\n", + "newManilaDay = manilaDay != prevManilaDay\n", + "\n", + "// Update stored day\n", + "if newManilaDay\n", + " prevManilaDay := manilaDay\n", + "//qweqweqweqweqeqweqweqwewqeqwewqeqe\n", + "\n", + "// UTC/UTC+8 Time\n", + "var label utcLbl = na\n", + "var label utc8Lbl = na\n", + "label.delete(utcLbl)\n", + "label.delete(utc8Lbl)\n", + "\n", + "//utcStr = \"UTC: \" + str.tostring(hour, \"00\") + \":\" + str.tostring(minute, \"00\")\n", + "uutcStr = str.tostring(hour, \"00\") + \":\" + str.tostring(minute, \"00\") + \" π˜œπ˜›π˜Š+8\"\n", + "utc8H = (hour + 12) % 24\n", + "//utc8Str = \"UTC: \" + str.tostring(utc8H, \"00\") + \":\" + str.tostring(minute, \"00\")\n", + "uutc8Str =str.tostring(utc8H, \"00\") + \":\" + str.tostring(minute, \"00\") + \" π˜œπ˜›π˜Š+8\"\n", + "\n", + "// TF Label\n", + "var label tfLbl = na\n", + "label.delete(tfLbl)\n", + "var label tfLbl2 = na\n", + "label.delete(tfLbl2)\n", + "\n", + "tfS = \"\"\n", + "if (str.length(timeframe.period) > 1 and str.substring(timeframe.period, str.length(timeframe.period)-1, str.length(timeframe.period)) == \"m\")\n", + " tfS := \"m\"\n", + "else if (str.length(timeframe.period) > 1 and str.substring(timeframe.period, str.length(timeframe.period)-1, str.length(timeframe.period)) == \"h\")\n", + " tfS := \"h\"\n", + "tfP = str.replace(timeframe.period, tfS, \"\")\n", + "tfText = tfP + tfS + \"m π˜ͺ𝘯𝘡𝘰 1D\"\n", + "\n", + "// Range Labels\n", + "dHL = math.abs(dH - dL)\n", + "dOC = math.abs(dO - dC)\n", + "cHL = math.abs(cH - cL)\n", + "cOC = math.abs(cO - cC)\n", + "\n", + "// === Create and update table ===\n", + "var table tt = table.new(position.top_right, 80, 80, border_width=1)\n", + "\n", + "if bar_index == 1\n", + " table.cell(tt, 0, 0, \"\", text_color=color.rgb(255, 255, 255, 100), text_size = size.tiny, bgcolor=color.rgb(120, 123, 134, 100))\n", + " table.cell(tt, 1, 0, \"\", text_color=color.rgb(255, 255, 255, 100), text_size = size.tiny,bgcolor=color.rgb(120, 123, 134, 100))\n", + "\n", + " table.cell(tt, 0, 1, \"\", text_color=color.rgb(255, 255, 255, 100), text_size = size.tiny, bgcolor=color.rgb(120, 123, 134, 100))\n", + " table.cell(tt, 1, 1, \"\", text_color=color.rgb(255, 255, 255, 100), text_size = size.tiny,bgcolor=color.rgb(120, 123, 134, 100))\n", + "\n", + "// === Daily Rows ===\n", + "table.cell(tt, 1, 2, \"π‘Ίπ’‘π’†π’„π’Šπ’‡π’Šπ’„π’‚π’•π’Šπ’π’\", text_color = color.white, text_size = size.tiny, bgcolor = color.navy)\n", + "\n", + "table.cell(tt, 0, 3, \"Date\", text_size = size.tiny)\n", + "table.cell(tt, 1, 3, formattedDate, text_size = size.tiny, bgcolor = color.rgb(120, 123, 134, 90))\n", + " \n", + "table.cell(tt, 0, 4, \"Time\", text_size = size.tiny)\n", + "table.cell(tt, 1, 4, text = uutc8Str, text_size = size.tiny, bgcolor = color.rgb(120, 123, 134, 90))\n", + " \n", + "table.cell(tt, 0, 5, \"Time\", text_size = size.tiny)\n", + "table.cell(tt, 1, 5, text=uutcStr, text_size = size.tiny, bgcolor = color.rgb(120, 123, 134, 90))\n", + "\n", + "table.cell(tt, 0, 6, \"Type\", text_size = size.tiny)\n", + "table.cell(tt, 1, 6, text=tfText, text_size = size.tiny, bgcolor = color.rgb(120, 123, 134, 90))\n", + "\n", + "table.cell(tt, 1, 7, \"π‘―π’Šπ’ˆπ’‰π’†π’“ 𝑻𝑭\", text_color = color.white, text_size = size.tiny, bgcolor = color.navy)\n", + "\n", + "table.cell(tt, 0, 8, \"6:00\\nяαηgΡ”\", text_size = size.tiny)\n", + "table.cell(tt, 1, 8, \"HL | $\" + str.tostring(dHL, \"#\") + \"\\nOC | $\" + str.tostring(dOC, \"#\"), text_size = size.tiny, bgcolor = sixambgcolor)\n", + "\n", + "table.cell(tt, 0, 9, \"8:00\\nяαηgΡ”\", text_size = size.tiny)\n", + "table.cell(tt, 1, 9, \"HL | $\" + str.tostring(cHL, \"#\") + \"\\nOC | $\" + str.tostring(cOC, \"#\"), text_size = size.tiny, bgcolor = eightambgcolor)\n", + "\n", + "table.cell(tt, 1, 11, \"1D π‘ͺ𝒂𝒏𝒅𝒍𝒆\", text_color = color.white, text_size = size.tiny, bgcolor = color.navy)\n", + "\n", + "table.cell(tt, 0, 12, \"-1D \\nяαηgΡ”\", text_size = size.tiny)\n", + "table.cell(tt, 1, 12, \"HL | $\" + str.tostring(d1_hl, \"#\") + \"\\nOC | $\" + str.tostring(d1_oc, \"#\"), text_size = size.tiny, bgcolor=d1_bg)\n", + "\n", + "table.cell(tt, 0, 13, \"-2D \\nяαηgΡ”\", text_size = size.tiny)\n", + "table.cell(tt, 1, 13, \"HL | $\" + str.tostring(d2_hl, \"#\") + \"\\nOC | $\" + str.tostring(d2_oc, \"#\"), text_size = size.tiny, bgcolor=d2_bg)\n", + "\n", + "table.cell(tt, 1, 14, \"1W π‘ͺ𝒂𝒏𝒅𝒍𝒆\", text_color = color.white, text_size = size.tiny, bgcolor = color.navy)\n", + "\n", + "table.cell(tt, 0, 15, \"0W \\nяαηgΡ”\", text_size = size.tiny)\n", + "table.cell(tt, 1, 15, \"HL | $\" + str.tostring(w0_hl, \"#\") + \"\\nOC | $\" + str.tostring(w0_oc, \"#\"), text_size = size.tiny, bgcolor=w0_bg)\n", + "\n", + "table.cell(tt, 0, 16, \"-1W \\nяαηgΡ”\", text_size = size.tiny)\n", + "table.cell(tt, 1, 16, \"HL | $\" + str.tostring(w1_hl, \"#\") + \"\\nOC | $\" + str.tostring(w1_oc, \"#\"), text_size = size.tiny, bgcolor=w1_bg)\n", + "\n", + "table.cell(tt, 0, 17, \"-2W \\nяαηgΡ”\", text_size = size.tiny)\n", + "table.cell(tt, 1, 17, \"HL | $\" + str.tostring(w2_hl, \"#\") + \"\\nOC | $\" + str.tostring(w2_oc, \"#\"), text_size = size.tiny, bgcolor=w2_bg)\n", + "\n", + "table.cell(tt, 1, 18, \"Β© 2025 πš†πš€πšœ\", text_color = color.white, text_size = size.tiny, bgcolor = color.black)\n", + "\n", + "\n", + "//@version=5\n", + "\n", + "\n", + "// Functions ----------------------------------------------------------------------------------- //\n", + "\n", + "\n", + "f_drawOnlyLineX(_x1, _y1, _x2, _y2, _xloc, _extend, _color, _style, _width) =>\n", + " id = line.new(_x1, _y1, _x2, _y2, _xloc, _extend, _color, _style, _width)\n", + "\n", + "\n", + "f_drawLineX(_x1, _y1, _x2, _y2, _xloc, _extend, _color, _style, _width) =>\n", + " var id = line.new(_x1, _y1, _x2, _y2, _xloc, _extend, _color, _style, _width)\n", + " line.set_xy1(id, _x1, _y1)\n", + " line.set_xy2(id, _x2, _y2)\n", + " line.set_color(id, _color)\n", + " id\n", + "\n", + "\n", + "f_drawOnlyBoxX(_left, _top, _right, _bottom, _border_color, _border_width, _border_style) =>\n", + " box.new(_left, _top, _right, _bottom, _border_color, _border_width, _border_style, bgcolor=_border_color)\n", + "\n", + "\n", + "f_drawOnlyLabelX(_x, _y, _text, _xloc, _yloc, _color, _style, _textcolor, _size, _textalign, _tooltip) =>\n", + " label.new(_x, _y, _text, _xloc, _yloc, _color, _style, _textcolor, _size, _textalign, _tooltip)\n", + "\n", + "\n", + "f_drawLabelX(_x, _y, _text, _xloc, _yloc, _color, _style, _textcolor, _size, _textalign, _tooltip) =>\n", + " var id = label.new(_x, _y, _text, _xloc, _yloc, _color, _style, _textcolor, _size, _textalign, _tooltip)\n", + " label.set_xy(id, _x, _y)\n", + " label.set_text(id, _text)\n", + " label.set_tooltip(id, _tooltip)\n", + "\n", + "\n", + "f_getHighLow(_len, _calc, _offset) =>\n", + " if _calc\n", + " htf_l = low [_offset]\n", + " htf_h = high[_offset]\n", + " vol = 0.\n", + " \n", + " for x = 0 to _len - 1\n", + " htf_l := math.min(low [_offset + x], htf_l)\n", + " htf_h := math.max(high[_offset + x], htf_h)\n", + " vol += volume[_offset + x]\n", + "\n", + "\n", + " htf_l := math.min(low [_offset + _len], htf_l)\n", + " htf_h := math.max(high[_offset + _len], htf_h)\n", + " \n", + " [htf_h, htf_l, vol]\n", + "\n", + "\n", + "\n", + "\n", + "// check for box breaches - code snippet from pine user guide\n", + "f_checkBreaches(arrayOfBoxes, extend) =>\n", + " int qtyOfBoxes = array.size(arrayOfBoxes)\n", + " for boxNo = 0 to (qtyOfBoxes > 0 ? qtyOfBoxes - 1 : na)\n", + " if boxNo < array.size(arrayOfBoxes)\n", + " box currentBox = array.get(arrayOfBoxes, boxNo)\n", + " float boxMidLevel = math.avg(box.get_bottom(currentBox), box.get_top(currentBox))\n", + " bool boxWasCrossed = math.sign(close[1] - boxMidLevel) != math.sign(close - boxMidLevel)\n", + " bool boxWasTouched = math.sign(close[1] - boxMidLevel) != math.sign(low - boxMidLevel) or math.sign(close[1] - boxMidLevel) != math.sign(high - boxMidLevel)\n", + "\n", + "\n", + " if boxWasCrossed and extend == 'Until Bar Cross'\n", + " array.remove(arrayOfBoxes, boxNo)\n", + " int(na)\n", + " else if boxWasTouched and extend == 'Until Bar Touch'\n", + " array.remove(arrayOfBoxes, boxNo)\n", + " int(na)\n", + " else\n", + " box.set_right(currentBox, bar_index)\n", + " int(na)\n", + "\n", + "\n", + "// Functions ----------------------------------------------------------------------------------- //\n", + "\n", + "// Inputs --------------------------------------------------------------------------------------- //\n", + "\n", + "\n", + "group_volume_profile = 'Pivot Points Volume Profile'\n", + "\n", + "\n", + "tooltip_pvt = 'The Pivot Points High Low indicator is used to determine and anticipate potential changes in market price and reversals\\n' +\n", + " '\\'Volume Profile, Pivot Points Anchored\\' Custom indicator addtionally calculates the trading activity between two Pivot Points'\n", + "pvtLength = input.int(20, \"Pivot Points Left/Right Length\", minval=1, group = group_volume_profile, tooltip = tooltip_pvt)\n", + "\n", + "\n", + "tooltip_vp = 'Common Interest Profile (Total Volume) - displays total trading activity over a specified time period at specific price levels'\n", + "volumeProfile = input.bool(true, 'Volume Profile (Common Interest)' , inline='BB3', group = group_volume_profile, tooltip = tooltip_vp)\n", + "totalVolumeColor = input.color(color.new(#fbc02d, 70), '' , inline='BB3', group = group_volume_profile)\n", + "vaVolumeColor = input.color(color.new(#434651, 70), '' , inline='BB3', group = group_volume_profile)\n", + "\n", + "\n", + "tooltip_va = 'Value Area (VA) – The range of price levels in which a specified percentage of all volume was traded during the time period'\n", + "isValueArea = input.float(68, \"Value Area Volume %\", minval = 0, maxval = 100 , group = group_volume_profile, tooltip = tooltip_va) / 100\n", + "\n", + "\n", + "tooltip_poc = 'Point of Control (POC) - The price level for the time period with the highest traded volume'\n", + "pointOfControl = input.bool(false, 'Point of Control (PoC)' , inline='PoC', group = group_volume_profile, tooltip = tooltip_poc)\n", + "pocColor = input.color(color.new(#ff0000, 0), '' , inline='PoC', group = group_volume_profile)\n", + "pocExtend = input.string('None', 'Extend Point of Control (PoC)', options=['Until Last Bar', 'Until Bar Cross', 'Until Bar Touch', 'None'], group = group_volume_profile)\n", + "\n", + "\n", + "tooltip_vah = 'Value Area High (VAH) - The highest price level within the value area'\n", + "valueAreaHigh = input.bool(true, 'Value Area High (VAH)' , inline='VAH', group = group_volume_profile, tooltip = tooltip_vah)\n", + "vahColor = input.color(color.new(#2962ff, 100), '' , inline='VAH', group = group_volume_profile)\n", + "\n", + "\n", + "tooltip_val = 'Value Area Low (VAL) - The lowest price level within the value area'\n", + "valueAreaLow = input.bool(true, 'Value Area Low (VAL) ' , inline='VAL', group = group_volume_profile, tooltip = tooltip_val)\n", + "valColor = input.color(color.new(#2962ff, 100), '' , inline='VAL', group = group_volume_profile)\n", + "\n", + "\n", + "vaBackground = input.bool(true, 'Background Fill of Value Area (VA)' , inline='vBG', group = group_volume_profile)\n", + "vaBackgroundColor = input.color(color.new(#886000, 100), '' , inline='vBG', group = group_volume_profile)\n", + "\n", + "\n", + "levels = input.string('Pivot Points', 'Level Labels', options = ['Pivot Points', 'Profile High/Low', 'Value Area High/Low'], group = group_volume_profile)\n", + "pvtPrice = input(false, \"Price\", inline = 'Levels', group=group_volume_profile)\n", + "pvtChange = input(false, \"Price Change\", inline = 'Levels', group=group_volume_profile)\n", + "pvtVolume = input(false, \"Cumulative Volume\", inline = 'Levels', group=group_volume_profile)\n", + "\n", + "\n", + "profileLevels = input.int(34, 'Number of Rows' , minval = 10, maxval = 100 , step = 1 , group = group_volume_profile)\n", + "profilePlacement = input.string('Left', 'Placment', options = ['Right', 'Left'] , group = group_volume_profile)\n", + "profileWidth = input.int(30, 'Profile Width %', minval = 0, maxval = 100 , group = group_volume_profile) / 100\n", + "backgroundFill = input.bool(true, 'Background Fill of Profile Range' , inline ='BG', group = group_volume_profile)\n", + "backgroundColor = input.color(color.new(#2962ff, 95), '' , inline ='BG', group = group_volume_profile)\n", + "\n", + "\n", + "\n", + "\n", + "// Definitions ---------------------------------------------------------------------------------- //\n", + "\n", + "\n", + "barPriceLow = low\n", + "barPriceHigh = high\n", + "bullCandle = close > open\n", + "nzVolume = nz(volume)\n", + "\n", + "\n", + "volumeStorageT = array.new_float(profileLevels + 1, 0.)\n", + "\n", + "\n", + "var a_poc = array.new_box()\n", + "\n", + "\n", + "var x1 = 0\n", + "var x2 = 0\n", + "var levelAbovePoc = 0\n", + "var levelBelowPoc = 0\n", + "var pvtHigh1 = 0.\n", + "var pvtLow1 = 0.\n", + "var pvtLast = ''\n", + "\n", + "\n", + "// Calculations --------------------------------------------------------------------------------- //\n", + "\n", + "\n", + "pvtHigh = ta.pivothigh(pvtLength, pvtLength)\n", + "pvtLow = ta.pivotlow (pvtLength, pvtLength)\n", + "proceed = not na(pvtHigh) or not na(pvtLow)\n", + "\n", + "\n", + "if proceed\n", + " x1 := x2\n", + " x2 := bar_index\n", + "\n", + "\n", + "if not na(pvtHigh)\n", + " pvtHigh1 := pvtHigh\n", + " pvtLast := 'H'\n", + "\n", + "\n", + "if not na(pvtLow)\n", + " pvtLow1 := pvtLow\n", + " pvtLast := 'L'\n", + "\n", + "\n", + "\n", + "\n", + "profileLength = x2 - x1\n", + "\n", + "\n", + "[priceHighest, priceLowest, tradedVolume] = f_getHighLow(profileLength, proceed, pvtLength)\n", + "priceStep = (priceHighest - priceLowest) / profileLevels\n", + "\n", + "\n", + "if proceed and bool(nzVolume) and priceStep > 0 and bar_index > profileLength and profileLength > 0\n", + "\n", + "\n", + " for barIndexx = 1 to profileLength\n", + " level = 0\n", + " barIndex = barIndexx + pvtLength\n", + " \n", + " for priceLevel = priceLowest to priceHighest by priceStep\n", + " if barPriceHigh[barIndex] >= priceLevel and barPriceLow[barIndex] < priceLevel + priceStep\n", + " array.set(volumeStorageT, level, array.get(volumeStorageT, level) + nzVolume[barIndex] * ((barPriceHigh[barIndex] - barPriceLow[barIndex]) == 0 ? 1 : priceStep / (barPriceHigh[barIndex] - barPriceLow[barIndex])) )\n", + " level += 1\n", + "\n", + "\n", + " pocLevel = array.indexof(volumeStorageT, array.max(volumeStorageT))\n", + " totalVolumeTraded = array.sum(volumeStorageT) * isValueArea\n", + " valueArea = array.get(volumeStorageT, pocLevel)\n", + " levelAbovePoc := pocLevel\n", + " levelBelowPoc := pocLevel\n", + " \n", + " while valueArea < totalVolumeTraded\n", + " if levelBelowPoc == 0 and levelAbovePoc == profileLevels - 1\n", + " break\n", + "\n", + "\n", + " volumeAbovePoc = 0.\n", + " if levelAbovePoc < profileLevels - 1\n", + " volumeAbovePoc := array.get(volumeStorageT, levelAbovePoc + 1)\n", + "\n", + "\n", + " volumeBelowPoc = 0.\n", + " if levelBelowPoc > 0\n", + " volumeBelowPoc := array.get(volumeStorageT, levelBelowPoc - 1)\n", + " \n", + " if volumeBelowPoc == 0 and volumeAbovePoc == 0\n", + " break\n", + " \n", + " if volumeAbovePoc >= volumeBelowPoc\n", + " valueArea += volumeAbovePoc\n", + " levelAbovePoc += 1\n", + " else\n", + " valueArea += volumeBelowPoc\n", + " levelBelowPoc -= 1\n", + "\n", + "\n", + " for level = 0 to profileLevels - 1\n", + " if volumeProfile\n", + " startBoxIndex = profilePlacement == 'Right' ? bar_index - int(array.get(volumeStorageT, level) / array.max(volumeStorageT) * profileLength * profileWidth) : bar_index - profileLength\n", + " endBoxIndex = profilePlacement == 'Right' ? bar_index : startBoxIndex + int( array.get(volumeStorageT, level) / array.max(volumeStorageT) * profileLength * profileWidth)\n", + " f_drawOnlyBoxX(startBoxIndex - pvtLength, priceLowest + (level + 0.1) * priceStep, endBoxIndex - pvtLength, priceLowest + (level + 0.9) * priceStep, level >= levelBelowPoc and level <= levelAbovePoc ? totalVolumeColor : vaVolumeColor, 1, line.style_solid)\n", + "\n", + "\n", + " if backgroundFill\n", + " f_drawOnlyBoxX(bar_index[pvtLength] - profileLength, priceHighest, bar_index[pvtLength], priceLowest, backgroundColor, 1, line.style_dotted)\n", + "\n", + "\n", + " if pointOfControl\n", + " array.push(a_poc, box.new(bar_index[pvtLength] - profileLength, priceLowest + (array.indexof(volumeStorageT, array.max(volumeStorageT)) + .40) * priceStep, bar_index[pvtLength], priceLowest + (array.indexof(volumeStorageT, array.max(volumeStorageT)) + .60) * priceStep, pocColor, bgcolor = pocColor ))\n", + "\n", + "\n", + " vah = f_drawOnlyLineX(bar_index[pvtLength] - profileLength, priceLowest + (levelAbovePoc + 1.00) * priceStep, bar_index[pvtLength], priceLowest + (levelAbovePoc + 1.00) * priceStep, xloc.bar_index, extend.none, valueAreaHigh ? vahColor : #00000000, line.style_solid, 2)\n", + " val = f_drawOnlyLineX(bar_index[pvtLength] - profileLength, priceLowest + (levelBelowPoc + 0.00) * priceStep, bar_index[pvtLength], priceLowest + (levelBelowPoc + 0.00) * priceStep, xloc.bar_index, extend.none, valueAreaLow ? valColor : #00000000, line.style_solid, 2)\n", + "\n", + "\n", + " if vaBackground\n", + " linefill.new(vah, val, vaBackgroundColor)\n", + "\n", + "\n", + " statTip = '\\n -Traded Volume : ' + str.tostring(tradedVolume, format.volume) + ' (' + str.tostring(profileLength - 1) + ' bars)' +\n", + " '\\n *Average Volume/Bar : ' + str.tostring(tradedVolume / (profileLength - 1), format.volume) +\n", + " '\\n\\nProfile High : ' + str.tostring(priceHighest, format.mintick) + ' ↑ %' + str.tostring((priceHighest - priceLowest) / priceLowest * 100, '#.##') +\n", + " '\\nProfile Low : ' + str.tostring(priceLowest, format.mintick) + ' ↓ %' + str.tostring((priceHighest - priceLowest) / priceHighest * 100, '#.##') +\n", + " '\\n -Point Of Control : ' + str.tostring(priceLowest + (array.indexof(volumeStorageT, array.max(volumeStorageT)) + .50) * priceStep, format.mintick) +\n", + " '\\n\\nValue Area High : ' + str.tostring(priceLowest + (levelAbovePoc + 1.00) * priceStep, format.mintick) +\n", + " '\\nValue Area Low : ' + str.tostring(priceLowest + (levelBelowPoc + 0.00) * priceStep, format.mintick) +\n", + " '\\n -Value Area Width : %' + str.tostring(((priceLowest + (levelAbovePoc + 1.00) * priceStep) - (priceLowest + (levelBelowPoc + 0.00) * priceStep)) / (priceHighest - priceLowest) * 100, '#.##') +\n", + " '\\n\\nNumber of Bars (Profile) : ' + str.tostring(profileLength)\n", + " \n", + " if levels != 'Pivot Points'\n", + " upperPriceLevel = levels == 'Value Area High/Low' ? priceLowest + (levelAbovePoc + 1.00) * priceStep : priceHighest\n", + " lowerPriceLevel = levels == 'Value Area High/Low' ? priceLowest + (levelBelowPoc + 0.00) * priceStep : priceLowest\n", + "\n", + "\n", + " upperText = (pvtPrice ? str.tostring(upperPriceLevel, format.mintick) : '') + (not na(pvtHigh) ? (pvtChange ? (pvtPrice ? ' ↑ %' : '↑ %') + str.tostring((pvtHigh - pvtLow1) * 100 / pvtLow1 , '#.##') : '') + (pvtVolume ? (pvtPrice or pvtChange ? '\\n' : '') + str.tostring(tradedVolume, format.volume) : '') : '')\n", + " lowerText = (pvtPrice ? str.tostring(lowerPriceLevel, format.mintick) : '') + (not na(pvtLow) ? (pvtChange ? (pvtPrice ? ' ↓ %' : '↓ %') + str.tostring((pvtHigh1 - pvtLow) * 100 / pvtHigh1, '#.##') : '') + (pvtVolume ? (pvtPrice or pvtChange ? '\\n' : '') + str.tostring(tradedVolume, format.volume) : '') : '')\n", + " \n", + " f_drawOnlyLabelX(bar_index[pvtLength] - profileLength / 2, upperPriceLevel, upperText, xloc.bar_index, yloc.price, (upperText != '' ? chart.fg_color : #00000000), label.style_circle, chart.bg_color, size.tiny, text.align_center, 'Profile High : ' + str.tostring(priceHighest, format.mintick) + '\\n %' + str.tostring((priceHighest - priceLowest) / priceLowest * 100, '#.##') + ' higher than the Profile Low' + statTip )\n", + " f_drawOnlyLabelX(bar_index[pvtLength] - profileLength / 2, lowerPriceLevel, lowerText, xloc.bar_index, yloc.price, (lowerText != '' ? chart.fg_color : #00000000), label.style_circle , chart.bg_color , size.tiny, text.align_center, 'Profile Low : ' + str.tostring(priceLowest, format.mintick) + '\\n %' + str.tostring((priceHighest - priceLowest) / priceHighest * 100, '#.##') + ' lower than the Profile High' + statTip )\n", + " else\n", + " if not na(pvtHigh)\n", + " f_drawOnlyLabelX(bar_index[pvtLength], pvtHigh, (pvtPrice ? str.tostring(pvtHigh, format.mintick) : '') + (pvtChange ? (pvtPrice ? ' ↑ %' : '↑ %') + str.tostring((pvtHigh - pvtLow1) * 100 / pvtLow1 , '#.##') : '') + (pvtVolume ? (pvtPrice or pvtChange ? '\\n' : '') + str.tostring(tradedVolume, format.volume) : ''), xloc.bar_index, yloc.price, chart.fg_color, label.style_diamond, chart.bg_color, (not pvtPrice and not pvtChange and not pvtVolume ? size.tiny : size.tiny), text.align_center, 'Pivot High : ' + str.tostring(pvtHigh, format.mintick) + '\\n -Price Change : %' + str.tostring((pvtHigh - pvtLow1) * 100 / pvtLow1 , '#.##') + statTip)\n", + " if not na(pvtLow)\n", + " f_drawOnlyLabelX(bar_index[pvtLength], pvtLow , (pvtPrice ? str.tostring(pvtLow , format.mintick) : '') + (pvtChange ? (pvtPrice ? ' ↓ %' : '↓ %') + str.tostring((pvtHigh1 - pvtLow) * 100 / pvtHigh1, '#.##') : '') + (pvtVolume ? (pvtPrice or pvtChange ? '\\n' : '') + str.tostring(tradedVolume, format.volume) : ''), xloc.bar_index, yloc.price, chart.fg_color, label.style_diamond , chart.bg_color, (not pvtPrice and not pvtChange and not pvtVolume ? size.tiny : size.tiny), text.align_center, 'Pivot Low : ' + str.tostring(pvtLow, format.mintick) + '\\n -Price Change : %' + str.tostring((pvtHigh1 - pvtLow) * 100 / pvtHigh1, '#.##') + statTip)\n", + "\n", + "\n", + "if pointOfControl and pocExtend != 'None'\n", + " f_checkBreaches(a_poc, pocExtend)\n", + "\n", + "\n", + "var a_profileD = array.new_box()\n", + "profileLength := barstate.islast ? last_bar_index - x2 + pvtLength : 1\n", + "priceHighest := ta.highest(high, profileLength > 0 ? profileLength + 1 : 1)\n", + "priceLowest := ta.lowest (low , profileLength > 0 ? profileLength + 1 : 1)\n", + "priceStep := (priceHighest - priceLowest) / profileLevels\n", + "var pocLevel = 0\n", + "\n", + "\n", + "[_, _, tradedVolume1] = f_getHighLow(profileLength, true, 0)\n", + "\n", + "\n", + " \n", + "if barstate.islast and bool(nzVolume) and profileLength > 0 and priceStep > 0\n", + " \n", + " if array.size(a_profileD) > 0\n", + " for i = 0 to array.size(a_profileD) - 1\n", + " box.delete(array.shift(a_profileD))\n", + "\n", + "\n", + " for barIndex = 1 to profileLength\n", + " level = 0\n", + "\n", + "\n", + " for priceLevel = priceLowest to priceHighest by priceStep\n", + " if barPriceHigh[barIndex] >= priceLevel and barPriceLow[barIndex] < priceLevel + priceStep\n", + " array.set(volumeStorageT, level, array.get(volumeStorageT, level) + nzVolume[barIndex] * ((barPriceHigh[barIndex] - barPriceLow[barIndex]) == 0 ? 1 : priceStep / (barPriceHigh[barIndex] - barPriceLow[barIndex])) )\n", + " level += 1\n", + "\n", + "\n", + " pocLevel := array.indexof(volumeStorageT, array.max(volumeStorageT))\n", + " totalVolumeTraded = array.sum(volumeStorageT) * isValueArea\n", + " valueArea = array.get(volumeStorageT, pocLevel)\n", + " levelAbovePoc := pocLevel\n", + " levelBelowPoc := pocLevel\n", + " \n", + " while valueArea < totalVolumeTraded\n", + " if levelBelowPoc == 0 and levelAbovePoc == profileLevels - 1\n", + " break\n", + "\n", + "\n", + " volumeAbovePoc = 0.\n", + " if levelAbovePoc < profileLevels - 1\n", + " volumeAbovePoc := array.get(volumeStorageT, levelAbovePoc + 1)\n", + "\n", + "\n", + " volumeBelowPoc = 0.\n", + " if levelBelowPoc > 0\n", + " volumeBelowPoc := array.get(volumeStorageT, levelBelowPoc - 1)\n", + " \n", + " if volumeBelowPoc == 0 and volumeAbovePoc == 0\n", + " break\n", + " \n", + " if volumeAbovePoc >= volumeBelowPoc\n", + " valueArea += volumeAbovePoc\n", + " levelAbovePoc += 1\n", + " else\n", + " valueArea += volumeBelowPoc\n", + " levelBelowPoc -= 1\n", + "\n", + "\n", + " for level = 0 to profileLevels - 1\n", + " if volumeProfile\n", + " startBoxIndex = profilePlacement == 'Right' ? bar_index - int(array.get(volumeStorageT, level) / array.max(volumeStorageT) * profileLength * profileWidth) : bar_index - profileLength\n", + " endBoxIndex = profilePlacement == 'Right' ? bar_index : startBoxIndex + int( array.get(volumeStorageT, level) / array.max(volumeStorageT) * profileLength * profileWidth)\n", + " array.push(a_profileD, box.new(startBoxIndex, priceLowest + (level + 0.1) * priceStep, endBoxIndex, priceLowest + (level + 0.9) * priceStep, level >= levelBelowPoc and level <= levelAbovePoc ? totalVolumeColor : vaVolumeColor, bgcolor = level >= levelBelowPoc and level <= levelAbovePoc ? totalVolumeColor : vaVolumeColor ))\n", + "\n", + "\n", + " if backgroundFill\n", + " array.push(a_profileD, box.new(bar_index - profileLength, priceHighest, bar_index, priceLowest, backgroundColor, bgcolor = backgroundColor ))\n", + "\n", + "\n", + " if pointOfControl\n", + " array.push(a_profileD, box.new(bar_index - profileLength, priceLowest + (pocLevel + .40) * priceStep, bar_index, priceLowest + (pocLevel + .60) * priceStep, pocColor, bgcolor = pocColor ))\n", + "\n", + "\n", + " vah = f_drawLineX(bar_index - profileLength, priceLowest + (levelAbovePoc + 1.00) * priceStep, bar_index, priceLowest + (levelAbovePoc + 1.00) * priceStep, xloc.bar_index, extend.none, valueAreaHigh ? vahColor : #00000000, line.style_solid, 2)\n", + " val = f_drawLineX(bar_index - profileLength, priceLowest + (levelBelowPoc + 0.00) * priceStep, bar_index, priceLowest + (levelBelowPoc + 0.00) * priceStep, xloc.bar_index, extend.none, valueAreaLow ? valColor : #00000000, line.style_solid, 2)\n", + "\n", + "\n", + " if vaBackground\n", + " linefill.new(vah, val, vaBackgroundColor)\n", + "\n", + "\n", + " if levels != 'Pivot Points'\n", + " statTip = '\\n -Traded Volume : ' + str.tostring(tradedVolume1, format.volume) + ' (' + str.tostring(profileLength - 1) + ' bars)' +\n", + " '\\n *Average Volume/Bar : ' + str.tostring(tradedVolume1 / (profileLength - 1), format.volume) +\n", + " '\\n\\nProfile High : ' + str.tostring(priceHighest, format.mintick) + ' ↑ %' + str.tostring((priceHighest - priceLowest) / priceLowest * 100, '#.##') +\n", + " '\\nProfile Low : ' + str.tostring(priceLowest, format.mintick) + ' ↓ %' + str.tostring((priceHighest - priceLowest) / priceHighest * 100, '#.##') +\n", + " '\\n -Point Of Control : ' + str.tostring(priceLowest + (array.indexof(volumeStorageT, array.max(volumeStorageT)) + .50) * priceStep, format.mintick) +\n", + " '\\n\\nValue Area High : ' + str.tostring(priceLowest + (levelAbovePoc + 1.00) * priceStep, format.mintick) +\n", + " '\\nValue Area Low : ' + str.tostring(priceLowest + (levelBelowPoc + 0.00) * priceStep, format.mintick) +\n", + " '\\n -Value Area Width : %' + str.tostring(((priceLowest + (levelAbovePoc + 1.00) * priceStep) - (priceLowest + (levelBelowPoc + 0.00) * priceStep)) / (priceHighest - priceLowest) * 100, '#.##') +\n", + " '\\n\\nNumber of Bars (Profile) : ' + str.tostring(profileLength) +\n", + " (pvtChange ? '\\n\\n*price change caculated based on last pivot high/low and last price' : '')\n", + "\n", + "\n", + " \n", + "\n", + "\n", + "\n", + "\n" + ] + }, + { + "attachments": { + "image.png": { + "image/png": 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" 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