AI K-Means Clustering [TradingFinder] Machine Learning Zones🔵 Introduction
K-Means clustering is an unsupervised machine learning algorithm that groups similar data points around repeatedly updated cluster centers. Each observation is assigned to its nearest center, the centers are recalculated, and the process continues until the clusters converge. In financial market analysis, this structure can separate recurring patterns in price movement, trend direction, volume pressure, and volatility without depending entirely on fixed thresholds. As a result, the same candle may be interpreted differently in a quiet market, a directional trend, or a volatility shock, because its meaning is evaluated in relation to the surrounding market data.
This PulseWire indicator applies K-Means machine learning through several connected analysis modules. The Market State engine studies trend bias, price slope, and relative volume pressure to classify the current market regime as an active bullish trend, active bearish trend, soft bullish trend, soft bearish trend, neutral range, or low-volume range. It also compares the current cluster with the dominant cluster across recent candles, helping the trend classification remain more stable when a single large candle, temporary spike, or short-lived price reversal appears.
The Price Zones engine clusters pivot points, historical highs, and historical lows to create dynamic K-Means support and resistance zones. Traders can display all price cluster centers, the nearest K-Means zone, or separate support and resistance lines. Raw, Smooth, and Locked Steps modes control how quickly the zones respond to new price data, while the nearest line changes color according to the detected bullish, bearish, or ranging market state. A Stochastic moving average heatmap is also plotted between the outer zones, adding a visual layer for momentum, overbought and oversold conditions, trend strength, and changing market pressure.
The indicator also combines volatility analysis, price action recognition, cluster quality scoring, and alert conditions. The volatility engine uses normalized ATR, candle range, and return volatility to identify low-volatility compression, normal volatility, high volatility, and volatility shock. The Price Action module evaluates the latest closed candle for bullish and bearish zone breakouts, rejection patterns, momentum candles, and indecision near a clustered price level. A dedicated Quality and Reliability section then measures zone strength, cluster fit, zone width, price distance, and RMSE, helping traders understand whether the current machine learning calculations are strong enough for practical analysis or should be treated only as additional market context.
🔵 How to Use
The easiest way to read this indicator is not to search for one isolated green or red message. Its main value comes from combining several layers of market information: K-Means market state classification, adaptive price zones, price action, volatility conditions, and calculation quality. Each module answers a different question, and the strongest setups usually appear when several modules point in the same direction.
Start with the Market State row in the analysis table. This module applies multidimensional K-Means clustering to trend bias, trend slope, and relative volume pressure. The current cluster shows where the latest market data has been assigned, while the dominant cluster represents the most frequent cluster across the selected state window. The Strength value shows how dominant that cluster is within the recent sample.
The Market State analysis can return the following conditions :
Active Bullish Trend : Positive trend structure supported by stronger relative volume.
Soft Bullish Trend : Positive directional structure, but with weaker participation or less convincing momentum.
Active Bearish Trend : Negative trend structure supported by stronger relative volume.
Soft Bearish Trend : Bearish directional structure that still requires confirmation.
Neutral Range : Trend bias and slope are not strong enough to define a clear direction.
Low-Volume Range : Sideways structure accompanied by relatively weak volume participation.
The distinction between the current and dominant cluster is important. A single large candle can move the current data point into another cluster, but the dominant state may remain unchanged if the broader recent structure still belongs to the previous market regime. This can help prevent every temporary spike, pullback, or abnormal candle from being interpreted as a complete trend reversal.
The next section is Price Zones. Here, K-Means clustering is applied to historical pivot levels, sampled highs, and sampled lows. Instead of drawing a level from only one swing point, the algorithm groups similar historical prices and calculates a center for each price cluster. These cluster centers become adaptive K-Means price zones that may act as support, resistance, breakout references, or reaction areas.
The table displays :
Near : The cluster currently closest to price.
Strength : The percentage of sampled price levels assigned to the nearest cluster.
Nearest : The closest stabilized K-Means zone.
Support : The nearest valid cluster center below the market.
Resistance : The nearest valid cluster center above the market.
A higher Zone Strength means a larger share of the sampled levels belongs to that cluster. However, this should not be interpreted as a guaranteed support or resistance level. It simply shows that more historical observations were grouped around the same price area.
On the chart, users can choose between three visual approaches. Show All K-Means Zone Centers plots the complete set of clustered price levels. Show Nearest Zone displays only the closest stabilized level, while Show K-Means Support/Resistance plots the nearest support and resistance separately.
The nearest line changes color with the detected market state :
Green indicates a bullish market state.
Red indicates a bearish market state.
Blue indicates a neutral or ranging market state.
The zone lines can also be displayed in Raw, Smooth, or Locked Steps mode. Raw mode follows newly calculated cluster centers directly. Smooth mode gradually moves the plotted level toward the new center, creating a more stable visual structure. Locked Steps mode keeps the previous level in place until the new cluster center has moved by a meaningful ATR-based distance.
Between the outer K-Means zones, the indicator draws a Stochastic Moving Average Heatmap. This heatmap is based on a 100-period Stochastic value smoothed with a 50-period exponential moving average. Lower smoothed Stochastic values appear toward the blue and purple side of the color range, middle values move through cyan and green, and higher values progress toward yellow, orange, and red. The heatmap should be read as a visual momentum layer rather than as a standalone buy or sell signal.
The Price Action row studies candle structure in relation to the nearest K-Means zone and recent price behavior. It uses the candle body, upper wick, lower wick, previous high, previous low, and the location of the nearest zone to identify several possible conditions:
Bullish or bearish zone breakout.
Bullish or bearish rejection from a zone.
Bullish or bearish momentum candle.
Indecision at a K-Means zone.
General indecision.
No clear price action.
The Body, Upper Wick Ratio, and Lower Wick Ratio values represent the relative size of the candle body, upper wick, and lower wick compared with the candle’s total range. These values help explain why the indicator classified a candle as momentum, rejection, or indecision. Price Action should always be read together with Market State and Volatility. For example, a bullish momentum candle inside a bearish market state does not automatically create a bullish setup.
The Volatility module runs a separate K-Means model using normalized ATR, candle range percentage, and return volatility. The clustered volatility data is then used to identify four practical market conditions:
Low Volatility Compression : Market movement has contracted and a future expansion may develop;
Normal Volatility : Current movement is close to its recent reference level;
High Volatility : Price movement is elevated and may require smaller position size or wider risk parameters;
Volatility Shock : Abnormal expansion is present, making immediate entries more sensitive to slippage, unstable movement, and rapid reversals.
Volatility acts as a risk filter for the rest of the analysis. Even when Market State and Price Action point in the same direction, a High Volatility or Volatility Shock reading should reduce the confidence placed on an immediate entry.
Finally, review the Quality row. This section provides an internal assessment of how compact, representative, and consistent the current K-Means calculations are. It does not measure future profitability or win rate. Instead, it evaluates the statistical structure of the active price clusters.
The main values include :
Price Q : A combined score based on zone strength, width, fit, and price distance;
Trust : A weighted score combining price-zone quality, market-state dominance, and volatility-cluster dominance;
Fit RMSE : The normalized root mean squared error of the price clusters;
Width : The average dispersion of the nearest cluster around its center;
Reliability : A descriptive grade derived from the internal Trust score.
A narrow cluster with reasonable strength and lower fitting error will usually receive a better score than a wide, weak, or poorly fitted cluster. Use this section to decide how much weight should be given to the current analysis. A weak Quality score does not make the chart unusable, but it suggests that the levels and classifications should be treated as secondary context.
🟣 Bullish Market Reading
A bullish setup becomes more meaningful when the market state, K-Means zones, candle behavior, volatility, and quality readings support the same interpretation.
Check the Market State first : An Active Bullish Trend indicates stronger bullish structure and relative participation. A Soft Bullish Trend still favors the upside, but entries should normally wait for additional confirmation.
Locate price relative to the nearest zone : When price is above the nearest K-Means zone, that level may become an adaptive support reference. A pullback toward the green nearest-zone line can be watched for continuation or rejection behavior.
Look for bullish price action : A Bullish Rejection From Zone suggests that price tested a clustered level and closed with a stronger lower-wick reaction. A Bullish Zone Breakout shows that the candle crossed above the zone with a sufficiently large body. A Bullish Momentum Candle confirms upward pressure, but it is more useful when the Market State is already bullish.
Use the support line as a reference, not an automatic entry : The K-Means support level can help define the area where bullish structure remains valid. A decisive move below it may weaken the long scenario, especially if the Market State also changes.
Confirm volatility conditions : Normal Volatility is generally easier to manage than High Volatility or Volatility Shock. During compression, traders may wait for a confirmed breakout rather than entering before expansion begins.
Review Quality and Reliability : Stronger Quality, Trust, and Zone Strength readings increase the internal consistency of the analysis. Weak scores suggest that the zone may be broad, poorly fitted, or based on a less concentrated cluster.
A practical bullish sequence may therefore look like this: the table shows a Soft or Active Bullish Trend, price remains above or retests a green K-Means zone, a bullish rejection or breakout appears, volatility is not classified as a shock, and Quality remains acceptable. None of these elements guarantees continuation, but their alignment creates a clearer bullish context than any single reading alone.
🟣 Bearish Market Reading
Bearish analysis follows the same process in reverse. The objective is to identify whether downward market structure, clustered resistance, candle behavior, and volatility are supporting the same scenario.
Begin with the Market State : An Active Bearish Trend represents stronger negative bias, slope, and relative volume pressure. A Soft Bearish Trend favors short-side analysis but still requires confirmation before treating the move as established.
Observe price relative to the nearest zone : When price is below the nearest K-Means zone, that level may act as an adaptive resistance reference. A return toward the red nearest-zone line can be monitored for rejection or continuation.
Wait for bearish price action : A Bearish Rejection From Zone appears when price tests a clustered area and forms a stronger upper-wick reaction. A Bearish Zone Breakout indicates that price has crossed below the zone with a sufficiently large bearish body. A Bearish Momentum Candle carries more weight when the broader Market State is already bearish.
Use the resistance line to define context : The K-Means resistance level can help identify where bearish continuation remains structurally reasonable. A sustained break above it may weaken the short scenario, particularly if Market State also shifts toward bullish or neutral conditions.
Do not ignore volatility warnings : A bearish candle during Volatility Shock may be followed by a sharp continuation, but it can also produce rapid retracement and unstable execution. In this condition, the indicator explicitly favors additional confirmation or reduced risk.
Check cluster quality before relying on the level : A weak or wide price cluster may produce a less precise resistance reference. Higher Quality and Reliability readings indicate a more compact and internally consistent zone, not a guaranteed bearish outcome.
A clearer bearish sequence may include a Soft or Active Bearish Trend, price trading below or retesting a red K-Means zone, bearish rejection or breakout behavior, manageable volatility, and an acceptable Quality score. When these components disagree, for example, a bullish momentum candle inside a bearish trend, the table should be read as a warning that momentum alone is not enough to confirm a reversal.
The built-in alert conditions can be used to monitor bullish and bearish K-Means zone breakouts and rejections. Alerts are most useful as notifications that a specific price-action condition has appeared; the final interpretation should still include Market State, Volatility, zone position, and Quality before any trading decision is made.
🔵 Settings
🟣 K-Means Engine Settings
Market State Lookback : Number of recent bars used to cluster trend bias, slope, and relative volume for market-state classification.
Price Zone Lookback : Number of recent bars used to build K-Means price zones from pivots, highs, and lows.
Volatility Lookback : Number of recent bars used to cluster ATR percentage, candle range, and return volatility.
Market State Clusters : Number of clusters used by the Market State model.
Price Zone Clusters : Number of price clusters used to calculate adaptive zone centers.
Volatility Clusters : Number of clusters used by the Volatility model.
Max K-Means Iterations : Maximum number of center-update cycles allowed during each clustering calculation.
Dominant State Window : Number of recent cluster assignments used to determine the dominant market state.
Fast Volatility State Window : Number of recent volatility assignments used to determine the dominant short-term volatility cluster.
Convergence Tolerance : Minimum center movement required to continue the K-Means iteration; lower values increase precision but may require more processing.
🟣 Price Zone Settings
Pivot Length : Number of bars used on each side of a candle to confirm pivot highs and pivot lows.
High/Low Sampling Step : Controls how frequently historical highs and lows are added to the price-zone dataset; lower values use more samples.
Minimum Near-Zone Distance (%) : Minimum percentage distance used to classify price as testing a K-Means zone.
🟣 Execution Control Settings
Historical Calculation Bars : Number of recent historical bars on which calculations and visual outputs are processed.
Refresh Every N Bars : Runs the main K-Means modules once every selected number of bars and always updates them on the latest bar.
🟣 Zone Stabilizer Settings
Zone Plot Mode : Selects how zone lines are displayed: Raw follows new centers directly, Smooth moves gradually, and Locked Steps updates only after a meaningful price shift.
Zone Smooth Length : Controls the smoothing speed in Smooth mode; higher values produce slower and more stable zone movement.
Zone Lock ATR Multiplier : Defines the minimum ATR-based movement required before a zone updates in Locked Steps mode.
Nearest Zone Switch Margin ATR : Prevents frequent switching between nearby zones by requiring the new zone to be closer by an ATR-based margin.
🟣 Display Settings
Show Analysis Table : Shows or hides the market analysis table.
Table Text Size : Sets the size used inside the table.
Table Position : Selects the table location on the chart.
Show All K-Means Zone Centers : Displays all calculated K-Means price-zone centers.
Show Nearest Zone : Displays the stabilized zone closest to the current price, colored by the detected market state.
Show K-Means Support/Resistance : Displays the nearest clustered support below price and resistance above price.
🔵 Conclusion
This indicator brings K-Means clustering, market state analysis, adaptive price zones, volatility classification, and price action context into one structured workflow. Instead of reducing the chart to a single signal, it separates the market into several readable layers: directional behavior, clustered support and resistance areas, candle reactions, volatility conditions, and the internal quality of the current calculations. This makes it easier to understand whether price is trending, ranging, testing a K-Means zone, reacting to a clustered level, or moving through an unstable volatility phase.
Its strongest use comes from confirmation rather than prediction. A bullish or bearish reading becomes more meaningful when the Market State, nearest K-Means zone, Price Action module, Volatility analysis, and Quality score support the same scenario. When these components disagree, the table highlights that uncertainty instead of hiding it. Used this way, the tool works as a machine learning market analysis framework that helps organize recent price data, compare changing market regimes, and identify areas where further confirmation is still required. Indicator
Volatility Regime Dashboard## Overview
Volatility Regime Dashboard is a context and visualization tool that classifies the
current volatility state of any symbol as **Compressed**, **Normal**, or **Expanded**.
Instead of plotting a single raw volatility line, it combines two independent
normalized measures and only changes the displayed state when both of them agree.
A compact table reports the underlying numbers and how many bars the current regime
has lasted.
This script is a visualization and context tool. It does not generate buy or sell
signals. It does not provide financial advice and makes no performance, accuracy,
or future-result claims.
## What it visualizes
- A line in its own pane showing the **percentile rank of price-normalized ATR**
(0-100), with dashed guides at the compressed and expanded thresholds and a
dotted midline.
- A **regime background shade** (optional) coloring the pane by the current state.
- A **context table** with the regime name, the ATR percentile value, the
Fast/Slow ATR compression ratio, whether the two measures currently agree, the
regime persistence in bars, and the ATR length in use.
## How it works
Two measures are computed independently:
1. **Price-normalized ATR percentile.** ATR is divided by price (so the measure is
comparable across symbols and price levels), then ranked as a percentile over a
user-defined lookback (default 252 bars). A high percentile means current ATR is
large relative to its own recent history; a low percentile means it is small.
2. **Fast/Slow ATR compression ratio.** A fast-window ATR is divided by a
slow-window ATR. A ratio above 1 means range is expanding relative to its
baseline; below 1 means it is compressing.
Each measure is classified into Compressed (-1), Normal (0), or Expanded (+1) using
its own thresholds. The displayed regime uses **hysteresis**: it flips to Expanded
or Compressed only when **both** measures agree on that direction, returns to Normal
only when both measures sit in their middle bands, and otherwise **holds** the prior
regime while the two measures disagree. This reduces flicker compared with reacting
to either measure alone. A persistence counter tracks how many consecutive bars the
current regime has held.
## How to use it
- Read the regime as **situational context** about how active the market currently
is relative to its own recent behavior, not as an instruction to act.
- Watch the percentile line approach the dashed thresholds to anticipate when a
regime change may be confirmed by both measures.
- Use the persistence counter to gauge whether a regime is freshly established or
well established.
- Adjust the lookback and thresholds to match the symbol and timeframe you study;
the defaults suit daily charts and are a starting point, not an optimized set.
## What makes it original
Most volatility tools plot a single raw or smoothed value. This dashboard derives a
**single discrete regime from the agreement of two structurally different measures**
- a within-history percentile rank and a fast-versus-slow ratio - and gates state
changes with hysteresis so the regime persists through brief disagreement. It then
surfaces the **persistence duration** of the current regime. The combination of
cross-measure agreement, hysteresis, and persistence reporting is the contribution;
it is not a re-skin of a built-in ATR, Bollinger, or standard-deviation indicator.
## What it does not do
- Does not generate buy/sell signals.
- Does not give entry/exit, target-level, or position-sizing instructions.
- Does not predict price or forecast performance.
- Does not run a strategy or backtest.
- Does not place or manage orders for you.
## Limitations
- Volatility regime is **descriptive context**, not a forecast; an Expanded or
Compressed state can persist or reverse at any time.
- The percentile rank depends on the lookback window; very small lookbacks make the
state noisy and very large ones make it slow to update.
- On symbols or timeframes with sparse history, the percentile may be unstable until
enough bars are available.
- ATR divided by price assumes price is positive and non-zero; exotic data feeds may
behave unexpectedly.
- Default thresholds are reasonable starting values, not values tuned for any
particular market.
## Suggested chart setup
- Use a liquid, recognizable symbol on a daily timeframe so the percentile lookback
has enough history.
- Keep the chart clean: this indicator opens in its own pane, so remove unrelated
indicators and let the percentile line, threshold guides, regime background, and
table be clearly visible.
- Make sure the indicator name, symbol, and timeframe are visible in any published
screenshot.
---
## Japanese notes / 日本語補足
このスクリプトはボラティリティの状態を「Compressed（収縮）」「Normal（通常）」
「Expanded（拡大）」として表示する、コンテキスト把握用の可視化ツールです。価格で
正規化したATRのパーセンタイル順位と、ファスト／スロー期間のATR比率という2つの独立
した指標を用い、両者が一致したときだけ状態を変更するヒステリシス方式を採用していま
す。表には各指標の数値と、現在の状態が何本のバー継続しているかを表示します。
これは相場の状況を把握するための可視化ツールであり、売買の指示は行いません。投資
助言ではなく、将来の値動きや運用成績に関する主張も一切行いません。新規の建玉や手
仕舞い、ポジションサイズの提案も行いません。しきい値やルックバックは銘柄や時間足に
合わせて調整してください（初期値は最適化されたものではありません）。
Indicator
Indicator
HTF Candles [EXCAVO]Higher Timeframe Candles in a Panel to the Right of the Chart
The HTF Candles indicator renders higher timeframe candles in a
dedicated panel to the right of all chart data. Each completed HTF candle
is drawn as a solid semi-transparent box (body) with color-matched wick
lines. The currently forming candle uses a dashed outline and updates in
real time. Nothing is drawn when the chart timeframe is equal to or higher
than the selected HTF.
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▸ HOW TO USE
Step 1 → Add the indicator on a lower timeframe chart (e.g., 5m or
15m). The HTF panel appears to the right of all candles.
Step 2 → Default HTF is 1H. Change it in settings to match the
context you trade (4H, D, etc.).
Step 3 → Solid boxes are completed HTF candles. Blue = bullish,
red = bearish.
Step 4 → The rightmost dashed box is the currently forming HTF
candle - it updates live on every bar close.
Step 5 → Set alerts for HTF Bullish or Bearish Candle Close to be
notified when the HTF period ends.
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▸ HOW IT CALCULATES
◆ HTF OHLC via Built-In Resampling
The indicator uses request.security() with lookahead_off to fetch the
current HTF candle's OHLC on every bar:
= request.security(ticker, htf, )
Without lookahead, these values reflect only confirmed data up to the
current bar - no future leaking.
◆ Candle Completion Detection
A new HTF candle is detected using ta.change(time(htf_tf)). When the time
bucket changes, the previous candle is complete. At that moment:
htf_o , htf_h , htf_l , htf_c = OHLC of the completed candle
These are pushed to history arrays (up to History Count entries), and
the oldest entry is trimmed when the limit is reached.
◆ Panel Positioning
All candles are drawn to the right of the last chart bar:
x1 = bar_index + right_margin + i x (candle_width + gap)
x2 = x1 + candle_width
Positions are recalculated on every barstate.islast update. Previous
drawing objects are deleted and rebuilt each bar so the panel always
aligns with the current last bar as new data arrives.
◆ Completed Candle Rendering
Each completed candle is drawn as:
- Body: box from max(open, close) to min(open, close)
- Upper wick: line from high to body top (only if high > body top)
- Lower wick: line from body bottom to low (only if low < body bottom)
◆ Current Candle (Dashed)
The forming candle uses the same box for fill but replaces the solid
border with four dashed lines (top, bottom, left, right edges) and
dashed wick lines. The body color reflects the live direction -
bullish (blue) if close >= open, bearish (red) otherwise.
◆ Timeframe Label Pinning
The HTF label above the panel is anchored to the highest candle in the
HTF panel (not the chart's overall high). This keeps the label stable
above the panel as price moves on the underlying chart.
◆ Timeframe Guard
The indicator checks timeframe.in_seconds() < timeframe.in_seconds(htf).
If the chart timeframe is equal to or higher than the HTF, no panel is
drawn.
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▸ WHAT MAKES IT DIFFERENT
◆ Panel to the Right - No Overlap
HTF candles are positioned past the last chart bar so they never cover
price action. The panel shifts automatically as new bars arrive.
◆ Dashed Forming Candle
The current unfinished HTF candle is visually distinct (dashed outline)
so it is never confused with confirmed history.
◆ Stable Timeframe Label
The HTF label is pinned to the highest candle inside the panel itself
rather than the chart's overall high. The label position stays consistent
relative to the HTF panel even when underlying chart prices spike outside
the panel range.
◆ Non-Repainting OHLC
request.security() with lookahead_off ensures that completed candle
values are final before they are committed to history. No retrospective
changes occur to completed boxes.
◆ Timeframe Guard
The indicator automatically disables itself when the chart timeframe is
greater than or equal to the selected HTF — no panel is drawn,
preventing meaningless output.
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▸ LEGEND
Legend table (bottom left) explains the visual elements:
▮ (blue) - Bullish completed HTF candle (solid outline)
▮ (red) - Bearish completed HTF candle (solid outline)
┅ (blue) - Currently forming HTF candle (dashed outline)
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▸ SETTINGS
HTF Settings
HTF Timeframe - 60 (1H by default)
History Count - 5 (completed HTF candles to keep visible)
Show Current Candle - ON (show the forming candle with dashed outline)
Visualization
Bullish Color - blue (customizable)
Bearish Color - red (customizable)
Candle Width (bars) - 5 (width of each candle box)
Gap Between Candles - 2 (spacing between boxes)
Right Margin (bars) - 10 (distance from last chart bar to panel)
Dashboard
Show Legend - ON
Alert Settings
Allow Repainting - OFF
JSON Alerts - OFF
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▸ ALERTS
HTF Bullish Candle Close - HTF candle closed bullish (close >= open)
HTF Bearish Candle Close - HTF candle closed bearish (close < open)
HTF Candle Close - any HTF candle closed
JSON payloads include direction, ticker, price, timeframe, htf, and indicator tag.
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Best regards,
EXCAVO
Disclaimer
Trading involves significant risk. This indicator is a technical analysis tool
and does not constitute financial advice, investment recommendations, or a
guarantee of future results. Past indicator behavior does not guarantee future
performance. Always use proper risk management and your own judgment.
Indicator
Indicator
Thermal Candlestick Spectrogram [Jamallo]The Thermal Candlestick Spectrogram replaces flat, binary candlesticks with a heat-mapped view of price density. Every bar radiates outward from a white-hot core through layers of orange, red, and deep amber — the same way thermal imaging reveals intensity beneath a surface. The result is a chart that doesn't just show you what price did, it shows you how concentrated that move was.
How It Works
A 7-layer gradient stack is anchored to each candle's midpoint and expands symmetrically toward the edges of the body. Transparency increases with each outer layer, creating a natural falloff that mimics heat dissipation:
White-yellow core — maximum density at the center of the body
Orange-red mantle — transitional layers that reveal the spread of price action
Dark outer boundary — a near-transparent edge that lets candles breathe without hard lines
Fading wicks — a dual-layer vertical fade that tapers wicks naturally toward the High and Low extremes, reducing visual noise
Anti-aliased price dot — a precision close marker with a subtle white halo for clean real-time tracking
Design & Performance
The entire effect runs on a fixed 9-plot architecture (7 body layers + 2 wick layers), keeping script weight low and render performance stable even alongside other indicators. No dynamic loops, no repainting — just a clean, deterministic stack that works across all timeframes and instruments.
Visual Comparison
Traditional flat candles vs. the Thermal Spectrogram — same data, entirely different depth. Indicator
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Indicator
Advanced Speedometer Gauge [PhenLabs]Advanced Speedometer Gauge
Version: PineScript™v6
📌 Description
The Advanced Speedometer Gauge is a revolutionary multi-metric visualization tool that consolidates 13 distinct trading indicators into a single, intuitive speedometer display. Instead of cluttering your workspace with multiple oscillators and panels, this gauge provides a unified interface where you can switch between different metrics while maintaining consistent visual interpretation.
Built on PineScript™ v6, the indicator transforms complex technical calculations into an easy-to-read semi-circular gauge with color-coded zones and a precision needle indicator. Each of the 13 available metrics has been carefully normalized to a 0-100 scale, ensuring that whether you’re analyzing RSI, volume trends, or volatility extremes, the visual interpretation remains consistent and intuitive.
The gauge is designed for traders who value efficiency and clarity. By consolidating multiple analytical perspectives into one compact display, you can quickly assess market conditions without the visual noise of traditional multi-indicator setups. All metrics are non-overlapping, meaning each provides unique insights into different aspects of market behavior.
🚀 Points of Innovation
13 selectable metrics covering momentum, volume, volatility, trend, and statistical analysis, all accessible through a single dropdown menu
Universal 0-100 normalization system that standardizes different indicator scales for consistent visual interpretation across all metrics
Semi-circular gauge design with 21 arc segments providing smooth precision and clear visual feedback through color-coded zones
Non-redundant metric selection ensuring each indicator provides unique market insights without analytical overlap
Advanced metrics including MFI (volume-weighted momentum), CCI (statistical deviation), Volatility Rank (extended lookback), Trend Strength (ADX-style), Choppiness Index, Volume Trend, and Price Distance from MA
Flexible positioning system with 5 chart locations, 3 size options, and fully customizable color schemes for optimal workspace integration
🔧 Core Components
Metric Selection Engine: Dropdown interface allowing instant switching between 13 different technical indicators, each with independent parameter controls
Normalization System: All metrics converted to 0-100 scale using indicator-specific algorithms that preserve the statistical significance of each measurement
Semi-Circular Gauge: Visual display using 21 arc segments arranged in curved formation with two-row thickness for enhanced visibility
Color Zone System: Three distinct zones (0-40 green, 40-70 yellow, 70-100 red) providing instant visual feedback on metric extremes
Needle Indicator: Dynamic pointer that positions across the gauge arc based on precise current metric value
Table Implementation: Professional table structure ensuring consistent positioning and rendering across different chart configurations
🔥 Key Features
RSI (Relative Strength Index): Classic momentum oscillator measuring overbought/oversold conditions with adjustable period length (default 14)
Stochastic Oscillator: Compares closing price to price range over specified period with smoothing, ideal for identifying momentum shifts
MFI (Money Flow Index): Volume-weighted RSI that combines price movement with volume to measure buying and selling pressure intensity
CCI (Commodity Channel Index): Measures statistical deviation from average price, normalized from typical -200 to +200 range to 0-100 scale
Williams %R: Alternative overbought/oversold indicator using high-low range analysis, inverted to match 0-100 scale conventions
Volume %: Current volume relative to moving average expressed as percentage, capped at 100 for extreme spikes
Volume Trend: Cumulative directional volume flow showing whether volume is flowing into up moves or down moves over specified period
ATR Percentile: Current Average True Range position within historical range using specified lookback period (default 100 bars)
Volatility Rank: Close-to-close volatility measured against extended historical range (default 252 days), differs from ATR in calculation method
Momentum: Rate of change calculation showing price movement speed, centered at 50 and normalized to 0-100 range
Trend Strength: ADX-style calculation using directional movement to quantify trend intensity regardless of direction
Choppiness Index: Measures market choppiness versus trending behavior, where high values indicate ranging markets and low values indicate strong trends
Price Distance from MA: Measures current price over-extension from moving average using standard deviation calculations
🎨 Visualization
Semi-Circular Arc Display: Curved gauge spanning from 0 (left) to 100 (right) with smooth progression and two-row thickness for visibility
Color-Coded Zones: Green zone (0-40) for low/oversold conditions, yellow zone (40-70) for neutral readings, red zone (70-100) for high/overbought conditions
Needle Indicator: Downward-pointing triangle (▼) positioned precisely at current metric value along the gauge arc
Scale Markers: Vertical line markers at 0, 25, 50, 75, and 100 positions with corresponding numerical labels below
Title Display: Merged cell showing “𓄀 PhenLabs” branding plus currently selected metric name in monospace font
Large Value Display: Current metric value shown with two decimal precision in large text directly below title
Table Structure: Professional table with customizable background color, text color, and transparency for minimal chart obstruction
📖 Usage Guidelines
Metric Selection
Select Metric: Default: RSI | Options: RSI, Stochastic, Volume %, ATR Percentile, Momentum, MFI (Money Flow), CCI (Commodity Channel), Williams %R, Volatility Rank, Trend Strength, Choppiness Index, Volume Trend, Price Distance | Choose the technical indicator you want to display on the gauge based on your current analytical needs
RSI Settings
RSI Length: Default: 14 | Range: 1+ | Controls the lookback period for RSI calculation, shorter periods increase sensitivity to recent price changes
Stochastic Settings
Stochastic Length: Default: 14 | Range: 1+ | Lookback period for stochastic calculation comparing close to high-low range
Stochastic Smooth: Default: 3 | Range: 1+ | Smoothing period applied to raw stochastic value to reduce noise and false signals
Volume Settings
Volume MA Length: Default: 20 | Range: 1+ | Moving average period used to calculate average volume for comparison with current volume
Volume Trend Length: Default: 20 | Range: 5+ | Period for calculating cumulative directional volume flow trend
ATR and Volatility Settings
ATR Length: Default: 14 | Range: 1+ | Period for Average True Range calculation used in ATR Percentile metric
ATR Percentile Lookback: Default: 100 | Range: 20+ | Historical range used to determine current ATR position as percentile
Volatility Rank Lookback (Days): Default: 252 | Range: 50+ | Extended lookback period for Volatility Rank metric using close-to-close volatility
Momentum and Trend Settings
Momentum Length: Default: 10 | Range: 1+ | Lookback period for rate of change calculation in Momentum metric
Trend Strength Length: Default: 20 | Range: 5+ | Period for directional movement calculations in ADX-style Trend Strength metric
Advanced Metric Settings
MFI Length: Default: 14 | Range: 1+ | Lookback period for Money Flow Index calculation combining price and volume
CCI Length: Default: 20 | Range: 1+ | Period for Commodity Channel Index statistical deviation calculation
Williams %R Length: Default: 14 | Range: 1+ | Lookback period for Williams %R high-low range analysis
Choppiness Index Length: Default: 14 | Range: 5+ | Period for calculating market choppiness versus trending behavior
Price Distance MA Length: Default: 50 | Range: 10+ | Moving average period used for Price Distance standard deviation calculation
Visual Customization
Position: Default: Top Right | Options: Top Left, Top Right, Bottom Left, Bottom Right, Middle Right | Controls gauge placement on chart for optimal workspace organization
Size: Default: Normal | Options: Small, Normal, Large | Adjusts overall gauge dimensions and text size for different monitor resolutions and preferences
Low Zone Color (0-40): Default: Green (#00FF00) | Customize color for low/oversold zone of gauge arc
Medium Zone Color (40-70): Default: Yellow (#FFFF00) | Customize color for neutral/medium zone of gauge arc
High Zone Color (70-100): Default: Red (#FF0000) | Customize color for high/overbought zone of gauge arc
Background Color: Default: Semi-transparent dark gray | Customize gauge background for contrast and chart integration
Text Color: Default: White (#FFFFFF) | Customize all text elements including title, value, and scale labels
✅ Best Use Cases
Quick visual assessment of market conditions when you need instant feedback on whether an asset is in extreme territory across multiple analytical dimensions
Workspace organization for traders who monitor multiple indicators but want to reduce chart clutter and visual complexity
Metric comparison by switching between different indicators while maintaining consistent visual interpretation through the 0-100 normalization
Overbought/oversold identification using RSI, Stochastic, Williams %R, or MFI depending on whether you prefer price-only or volume-weighted analysis
Volume analysis through Volume %, Volume Trend, or MFI to confirm price movements with corresponding volume characteristics
Volatility monitoring using ATR Percentile or Volatility Rank to identify expansion/contraction cycles and adjust position sizing
Trend vs range identification by comparing Trend Strength (high values = trending) against Choppiness Index (high values = ranging)
Statistical over-extension detection using CCI or Price Distance to identify when price has deviated significantly from normal behavior
Multi-timeframe analysis by duplicating the gauge on different timeframe charts to compare metric readings across time horizons
Educational purposes for new traders learning to interpret technical indicators through consistent visual representation
⚠️ Limitations
The gauge displays only one metric at a time, requiring manual switching to compare different indicators rather than simultaneous multi-metric viewing
The 0-100 normalization, while providing consistency, may obscure the raw values and specific nuances of each underlying indicator
Table-based visualization cannot be exported or saved as an image separately from the full chart screenshot
Optimal parameter settings vary by asset type, timeframe, and market conditions, requiring user experimentation for best results
💡 What Makes This Unique
Unified Multi-Metric Interface: The only gauge-style indicator offering 13 distinct metrics through a single interface, eliminating the need for multiple oscillator panels
Non-Overlapping Analytics: Each metric provides genuinely unique insights—MFI combines volume with price, CCI measures statistical deviation, Volatility Rank uses extended lookback, Trend Strength quantifies directional movement, and Choppiness Index measures ranging behavior
Universal Normalization System: All metrics standardized to 0-100 scale using indicator-appropriate algorithms that preserve statistical meaning while enabling consistent visual interpretation
Professional Visual Design: Semi-circular gauge with 21 arc segments, precision needle positioning, color-coded zones, and clean table implementation that maintains clarity across all chart configurations
Extensive Customization: Independent parameter controls for each metric, five position options, three size presets, and full color customization for seamless workspace integration
🔬 How It Works
1. Metric Calculation Phase:
All 13 metrics are calculated simultaneously on every bar using their respective algorithms with user-defined parameters
Each metric applies its own specific calculation method—RSI uses average gains vs losses, Stochastic compares close to high-low range, MFI incorporates typical price and volume, CCI measures deviation from statistical mean, ATR calculates true range, directional indicators measure up/down movement, and statistical metrics analyze price relationships
2. Normalization Process:
Each calculated metric is converted to a standardized 0-100 scale using indicator-appropriate transformations
Some metrics are naturally 0-100 (RSI, Stochastic, MFI, Williams %R), while others require scaling—CCI transforms from ±200 range, Momentum centers around 50, Volume ratio caps at 2x for 100, ATR and Volatility Rank calculate percentile positions, and Price Distance scales by standard deviations
3. Gauge Rendering:
The selected metric’s normalized value determines the needle position across 21 arc segments spanning 0-100
Each arc segment receives its color based on position—segments 0-8 are green zone, segments 9-14 are yellow zone, segments 15-20 are red zone
The needle indicator (▼) appears in row 5 at the column corresponding to the current metric value, providing precise visual feedback
4. Table Construction:
The gauge uses PulseWire’s table system with merged cells for title and value display, ensuring consistent positioning regardless of chart configuration
Rows are allocated as follows: Row 0 merged for title, Row 1 merged for large value display, Row 2 for spacing, Rows 3-4 for the semi-circular arc with curved shaping, Row 5 for needle indicator, Row 6 for scale markers, Row 7 for numerical labels at 0/25/50/75/100
All visual elements update on every bar when barstate.islast is true, ensuring real-time accuracy without performance impact
💡 Note:
This indicator is designed for visual analysis and market condition assessment, not as a standalone trading system. For best results, combine gauge readings with price action analysis, support and resistance levels, and broader market context. Parameter optimization is recommended based on your specific trading timeframe and asset class. The gauge works on all timeframes but may require different parameter settings for intraday versus daily/weekly analysis. Consider using multiple instances of the gauge set to different metrics for comprehensive market analysis without switching between settings. Indicator
Normalized Portfolio TrackerThis script lets you create, visualize, and track a custom portfolio of up to 15 assets directly on PulseWire.
It calculates a synthetic "portfolio index" by combining multiple tickers with user-defined weights, automatically normalizing them so the total allocation always equals 100%.
All assets are scaled to a common starting point, allowing you to compare your portfolio’s performance versus any benchmark like SPY, QQQ, or BTC.
🚀 Goal
This script helps traders and investors:
• Understand the combined performance of their portfolio.
• Normalize diverse assets into a single synthetic chart .
• Make portfolio-level insights without relying on external spreadsheets.
🎯 Use Cases
• Backtest your portfolio allocations directly on the chart.
• Compare your portfolio vs. benchmarks like SPY, QQQ, BTC.
• Track thematic baskets (commodities, EV supply chain, regional ETFs).
• Visualize how each component contributes to overall performance.
📊 Features
• Weighted Portfolio Performance : Combines selected assets into a synthetic value series.
• Base Price Alignment : Each asset is normalized to its starting price at the chosen date.
• Dynamic Portfolio Table : Displays symbols, normalized weights (%), equivalent shares (based on each asset’s start price, sums to 100 shares), and a total row that always sums to 100%.
• Multi-Asset Support : Works with stocks, ETFs, indices, crypto, or any PulseWire-compatible symbol.
⚙️ Configuration
Flexible Portfolio Setup
• Add up to 15 assets with custom weight inputs.
• You can enter any arbitrary numbers (e.g. 30, 15, 55).
• The script automatically normalizes all weights so the total allocation always equals 100%.
Start Date Selection
• Choose any custom start date to normalize all assets.
• The portfolio value is then scaled relative to the main chart symbol, so you can directly compare portfolio performance against benchmarks like SPY or QQQ.
Chart Styles
• Candlestick chart
• Heikin Ashi chart
• Line chart
Custom Display
• Adjustable colors and line widths
• Optionally display asset list, normalized weights, and equivalent shares
⚙️ How It Works
• Fetch OHLC data for each asset.
• Normalizes weights internally so totals = 100%.
• Stores each asset’s base price at the selected start date.
• Calculates equivalent “shares” for each allocation.
• Builds a synthetic portfolio value series by summing weighted contributions.
• Renders as Candlestick, Heikin Ashi, or Line chart.
• Adds a portfolio info table for clarity.
⚠️ Notes
• This script is for visualization only . It does not place trades or auto-rebalance.
• Weight inputs are automatically normalized, so you don’t need to enter exact percentages.
Indicator
DeltaFlow Volume Profile [BigBeluga]🔵 OVERVIEW
The DeltaFlow Volume Profile builds a compact volume profile next to price and enriches every bin with flow context : bullish vs. bearish participation (%), a per-bin Delta % , an optional Delta Heat Map , and a PoC band with the bin’s absolute volume. This lets you see not just where volume clustered, but who (buyers or sellers) dominated inside each price slice.
🔵 CONCEPTS
Binned Volume Profile : Price range over a user-defined LookBack is split into Bins ; each bin aggregates traded volume.
Bull/Bear Split : Within every bin, volume is separated by candle direction into Bull Volume and Bear Volume , then normalized to % of the bin’s displayed size.
Delta % : The difference between Bull % and Bear % for the bin. Positive = buyer dominance; negative = seller dominance.
Delta Heat Map : Bin background shading that scales with both total volume strength and delta bias.
PoC (Point of Control) : The most significant bin gets a PoC band and a label with its absolute volume.
🔵 FEATURES
Profile with Flow : A clean horizontal volume bar per bin plus stacked Bull % and Bear % .
Per-Bin Delta Label : A readable “Δ xx%” tag at the start of each bin shows dominance at a glance.
Delta Heat Map : Optional gradient that intensifies with higher volume and stronger delta.
PoC Highlight : Optional PoC band colored separately, labeled with absolute volume (e.g., “1.23M”).
Configurable Inputs : LookBack, number of Bins (10–100), toggles for Delta, Heat Map, Volume Bars, and PoC color.
Readable Colors : Separate inputs for bullish (volume +) and bearish (volume –) hues.
🔵 HOW TO USE
Set the window : Choose LookBack and Bins to balance detail vs. performance (more bins = finer resolution).
Enable “Volume Bars” to display the bull/bear split as two stacked percent bars inside each bin.
High Bull % near support → constructive demand.
High Bear % near resistance → active supply.
Use Δ labels (toggle “Delta”) to quickly spot bins with clear buyer/seller control; combine with price position for confluence.
Turn on Delta Heat Map to prioritize areas with both large volume and strong imbalance.
Watch the PoC : The PoC band marks the most traded (and often magnet) level; its label shows absolute size for context.
Trade ideas :
Breakout continuation when Δ stays positive across consecutive upper bins.
Reversion risk when price enters a large bearish-Δ cluster below.
Manage risk around the PoC; reactions there can be sharp.
🔵 CONCLUSION
DeltaFlow Volume Profile upgrades a classic profile with flow intelligence. The bull/bear split, explicit Δ %, heat-weighted backdrop, and PoC volume label make dominant participation and key price shelves obvious. Use it to filter levels, time entries with imbalance, and validate breakouts or fades with objective volume-flow evidence. Indicator
FvgObject█ OVERVIEW
This library provides a suite of methods designed to manage the visual representation and lifecycle of Fair Value Gap (FVG) objects on a Pine Script™ chart. It extends the `fvgObject` User-Defined Type (UDT) by attaching object-oriented functionalities for drawing, updating, and deleting FVG-related graphical elements. The primary goal is to encapsulate complex drawing logic, making the main indicator script cleaner and more focused on FVG detection and state management.
█ CONCEPTS
This library is built around the idea of treating each Fair Value Gap as an "object" with its own visual lifecycle on the chart. This is achieved by defining methods that operate directly on instances of the `fvgObject` UDT.
Object-Oriented Approach for FVGs
Pine Script™ v6 introduced the ability to define methods for User-Defined Types (UDTs). This library leverages this feature by attaching specific drawing and state management functions (methods) directly to the `fvgObject` type. This means that instead of calling global functions with an FVG object as a parameter, you call methods *on* the FVG object itself (e.g., `myFvg.updateDrawings(...)`). This approach promotes better code organization and a more intuitive way to interact with FVG data.
FVG Visual Lifecycle Management
The core purpose of this library is to manage the complete visual journey of an FVG on the chart. This lifecycle includes:
Initial Drawing: Creating the first visual representation of a newly detected FVG, including its main box and optionally its midline and labels.
State Updates & Partial Fills: Modifying the FVG's appearance as it gets partially filled by price. This involves drawing a "mitigated" portion of the box and adjusting the `currentTop` or `currentBottom` of the remaining FVG.
Full Mitigation & Tested State: Handling how an FVG is displayed once fully mitigated. Depending on user settings, it might be hidden, or its box might change color/style to indicate it has been "tested." Mitigation lines can also be managed (kept or deleted).
Midline Interaction: Visually tracking if the price has touched the FVG's 50% equilibrium level (midline).
Visibility Control: Dynamically showing or hiding FVG drawings based on various criteria, such as user settings (e.g., hide mitigated FVGs, timeframe-specific visibility) or external filters (e.g., proximity to current price).
Deletion: Cleaning up all drawing objects associated with an FVG when it's no longer needed or when settings dictate its removal.
Centralized Drawing Logic
By encapsulating all drawing-related operations within the methods of this library, the main indicator script is significantly simplified. The main script can focus on detecting FVGs and managing their state (e.g., in arrays), while delegating the complex task of rendering and updating them on the chart to the methods herein.
Interaction with `fvgObject` and `drawSettings` UDTs
All methods within this library operate on an instance of the `fvgObject` UDT. This `fvgObject` holds not only the FVG's price/time data and state (like `isMitigated`, `currentTop`) but also the IDs of its associated drawing elements (e.g., `boxId`, `midLineId`).
The appearance of these drawings (colors, styles, visibility, etc.) is dictated by a `drawSettings` UDT instance, which is passed as a parameter to most drawing-related methods. This `drawSettings` object is typically populated from user inputs in the main script, allowing for extensive customization.
Stateful Drawing Object Management
The library's methods manage Pine Script™ drawing objects (boxes, lines, labels) by storing their IDs within the `fvgObject` itself (e.g., `fvgObject.boxId`, `fvgObject.mitigatedBoxId`, etc.). Methods like `draw()` create these objects and store their IDs, while methods like `updateDrawings()` modify them, and `deleteDrawings()` removes them using these stored IDs.
Drawing Optimization
The `updateDrawings()` method, which is the most comprehensive drawing management function, incorporates optimization logic. It uses `prev_*` fields within the `fvgObject` (e.g., `prevIsMitigated`, `prevCurrentTop`) to store the FVG's state from the previous bar. By comparing the current state with the previous state, and also considering changes in visibility or relevant drawing settings, it can avoid redundant and performance-intensive drawing operations if nothing visually significant has changed for that FVG.
█ METHOD USAGE AND WORKFLOW
The methods in this library are designed to be called in a logical sequence as an FVG progresses through its lifecycle. A crucial prerequisite for all visual methods in this library is a properly populated `drawSettings` UDT instance, which dictates every aspect of an FVG's appearance, from colors and styles to visibility and labels. This `settings` object must be carefully prepared in the main indicator script, typically based on user inputs, before being passed to these methods.
Here’s a typical workflow within a main indicator script:
1. FVG Instance Creation (External to this library)
An `fvgObject` instance is typically created by functions in another library (e.g., `FvgCalculations`) when a new FVG pattern is identified. This object will have its core properties (top, bottom, startTime, isBullish, tfType) initialized.
2. Initial Drawing (`draw` method)
Once a new `fvgObject` is created and its initial visibility is determined:
Call the `myFvg.draw(settings)` method on the new FVG object.
`settings` is an instance of the `drawSettings` UDT, containing all relevant visual configurations.
This method draws the primary FVG box, its midline (if enabled in `settings`), and any initial labels. It also initializes the `currentTop` and `currentBottom` fields of the `fvgObject` if they are `na`, and stores the IDs of the created drawing objects within the `fvgObject`.
3. Per-Bar State Updates & Interaction Checks
On each subsequent bar, for every active `fvgObject`:
Interaction Check (External Logic): It's common to first use logic (e.g., from `FvgCalculations`' `fvgInteractionCheck` function) to determine if the current bar's price interacts with the FVG.
State Field Updates (External Logic): Before calling the `FvgObjectLib` methods below, ensure that your `fvgObject`'s state fields (such as `isMitigated`, `currentTop`, `currentBottom`, `isMidlineTouched`) are updated using the current bar's price data and relevant functions from other libraries (e.g., `FvgCalculations`' `checkMitigation`, `checkPartialMitigation`, etc.). This library's methods render the FVG based on these pre-updated state fields.
If interaction occurs and the FVG is not yet fully mitigated:
Full Mitigation Update (`updateMitigation` method): Call `myFvg.updateMitigation(high, low)`. This method updates `myFvg.isMitigated` and `myFvg.mitigationTime` if full mitigation occurs, based on the interaction determined by external logic.
Partial Fill Update (`updatePartialFill` method): If not fully mitigated, call `myFvg.updatePartialFill(high, low, settings)`. This method updates `myFvg.currentTop` or `myFvg.currentBottom` and adjusts drawings to show the filled portion, again based on prior interaction checks and fill level calculations.
Midline Touch Check (`checkMidlineTouch` method): Call `myFvg.checkMidlineTouch(high, low)`. This method updates `myFvg.isMidlineTouched` if the price touches the FVG's 50% level.
4. Comprehensive Visual Update (`updateDrawings` method)
After the FVG's state fields have been potentially updated by external logic and the methods in step 3:
Call `myFvg.updateDrawings(isVisibleNow, settings)` on each FVG object.
`isVisibleNow` is a boolean indicating if the FVG should currently be visible.
`settings` is the `drawSettings` UDT instance.
This method synchronizes the FVG's visual appearance with its current state and settings, managing all drawing elements (boxes, lines, labels), their styles, and visibility. It efficiently skips redundant drawing operations if the FVG's state or visibility has not changed, thanks to its internal optimization using `prev_*` fields, which are also updated by this method.
5. Deleting Drawings (`deleteDrawings` method)
When an FVG object is no longer tracked:
Call `myFvg.deleteDrawings(deleteTestedToo)`.
This method removes all drawing objects associated with that `fvgObject`.
This workflow ensures that FVG visuals are accurately maintained throughout their existence on the chart.
█ NOTES
Dependencies: This library relies on `FvgTypes` for `fvgObject` and `drawSettings` definitions, and its methods (`updateMitigation`, `updatePartialFill`) internally call functions from `FvgCalculations`.
Drawing Object Management: Be mindful of PulseWire's limits on drawing objects per script. The main script should manage the number of active FVG objects.
Performance and `updateDrawings()`: The `updateDrawings()` method is comprehensive. Its internal optimization (checking `hasStateChanged` based on `prev_*` fields) is crucial for performance. Call it judiciously.
Role of `settings.currentTime`: The `currentTime` field in `drawSettings` is key for positioning time-dependent elements like labels and the right edge of non-extended drawings.
Mutability of `fvgObject` Instances: Methods in this library directly modify the `fvgObject` instance they are called upon (e.g., its state fields and drawing IDs).
Drawing ID Checks: Methods generally check if drawing IDs are `na` before acting on them, preventing runtime errors.
█ EXPORTED FUNCTIONS
method draw(this, settings)
Draws the initial visual representation of the FVG object on the chart. This includes the main FVG box, its midline (if enabled), and a label
(if enabled for the specific timeframe). This method is typically invoked
immediately after an FVG is first detected and its initial properties are set. It uses drawing settings to customize the appearance based on the FVG's timeframe type.
Namespace types: types.fvgObject
Parameters:
this (fvgObject type from no1x/FvgTypes/1) : The FVG object instance to be drawn. Core properties (top, bottom,
startTime, isBullish, tfType) should be pre-initialized. This method will
initialize boxId, midLineId, boxLabelId (if applicable), and
currentTop/currentBottom (if currently na) on this object.
settings (drawSettings type from no1x/FvgTypes/1) : A drawSettings object providing all visual parameters. Reads display settings (colors, styles, visibility for boxes, midlines, labels,
box extension) relevant to this.tfType. settings.currentTime is used for
positioning labels and the right boundary of non-extended boxes.
method updateMitigation(this, highVal, lowVal)
Checks if the FVG has been fully mitigated by the current bar's price action.
Namespace types: types.fvgObject
Parameters:
this (fvgObject type from no1x/FvgTypes/1) : The FVG object instance. Reads this.isMitigated, this.isVisible,
this.isBullish, this.top, this.bottom. Updates this.isMitigated and
this.mitigationTime if full mitigation occurs.
highVal (float) : The high price of the current bar, used for mitigation check.
lowVal (float) : The low price of the current bar, used for mitigation check.
method updatePartialFill(this, highVal, lowVal, settings)
Checks for and processes partial fills of the FVG.
Namespace types: types.fvgObject
Parameters:
this (fvgObject type from no1x/FvgTypes/1) : The FVG object instance. Reads this.isMitigated, this.isVisible,
this.isBullish, this.currentTop, this.currentBottom, original this.top/this.bottom,
this.startTime, this.tfType, this.isLV. Updates this.currentTop or
this.currentBottom, creates/updates this.mitigatedBoxId, and may update this.boxId's
top/bottom to reflect the filled portion.
highVal (float) : The high price of the current bar, used for partial fill check.
lowVal (float) : The low price of the current bar, used for partial fill check.
settings (drawSettings type from no1x/FvgTypes/1) : The drawing settings. Reads timeframe-specific colors for mitigated
boxes (e.g., settings.mitigatedBullBoxColor, settings.mitigatedLvBullColor),
box extension settings (settings.shouldExtendBoxes, settings.shouldExtendMtfBoxes, etc.),
and settings.currentTime to style and position the mitigatedBoxId and potentially adjust the main boxId.
method checkMidlineTouch(this, highVal, lowVal)
Checks if the FVG's midline (50% level or Equilibrium) has been touched.
Namespace types: types.fvgObject
Parameters:
this (fvgObject type from no1x/FvgTypes/1) : The FVG object instance. Reads this.midLineId, this.isMidlineTouched,
this.top, this.bottom. Updates this.isMidlineTouched if a touch occurs.
highVal (float) : The high price of the current bar, used for midline touch check.
lowVal (float) : The low price of the current bar, used for midline touch check.
method deleteDrawings(this, deleteTestedToo)
Deletes all visual drawing objects associated with this FVG object.
Namespace types: types.fvgObject
Parameters:
this (fvgObject type from no1x/FvgTypes/1) : The FVG object instance. Deletes drawings referenced by boxId,
mitigatedBoxId, midLineId, mitLineId, boxLabelId, mitLineLabelId,
and potentially testedBoxId, keptMitLineId. Sets these ID fields to na.
deleteTestedToo (simple bool) : If true, also deletes drawings for "tested" FVGs
(i.e., testedBoxId and keptMitLineId).
method updateDrawings(this, isVisibleNow, settings)
Manages the comprehensive update of all visual elements of an FVG object
based on its current state (e.g., active, mitigated, partially filled) and visibility. It handles the drawing, updating, or deletion of FVG boxes (main and mitigated part),
midlines, mitigation lines, and their associated labels. Visibility is determined by the isVisibleNow parameter and relevant settings
(like settings.shouldHideMitigated or timeframe-specific show flags). This method is central to the FVG's visual lifecycle and includes optimization
to avoid redundant drawing operations if the FVG's relevant state or appearance
settings have not changed since the last bar. It also updates the FVG object's internal prev_* state fields for future optimization checks.
Namespace types: types.fvgObject
Parameters:
this (fvgObject type from no1x/FvgTypes/1) : The FVG object instance to update. Reads most state fields (e.g.,
isMitigated, currentTop, tfType, etc.) and updates all drawing ID fields
(boxId, midLineId, etc.), this.isVisible, and all this.prev_* state fields.
isVisibleNow (bool) : A flag indicating whether the FVG should be currently visible. Typically determined by external logic (e.g., visual range filter). Affects
whether active FVG drawings are created/updated or deleted by this method.
settings (drawSettings type from no1x/FvgTypes/1) : A fully populated drawSettings object. This method extensively
reads its fields (colors, styles, visibility toggles, timeframe strings, etc.)
to render FVG components according to this.tfType and current state. settings.currentTime is critical for positioning elements like labels and extending drawings. Library
Price AltimeterThis indicator should help visualize the price, inspired by a Digital Altimeter in a Pilots HUD.
It's by default calibrated to Bitcoin, with the small levels showing every $100 and the larger levels setup to display on every $1000. But you can change this to whatever you want by changing the settings for: Small and Large Level Increments.
The default colors are grey, but can be changed to whatever you want, and there are two cause if you want they work as a gradient.
There are options to fade as the values go away from the current price action.
There are options for Forward and Backward Offsets, 0 is the current price and each value represents a candle on whatever time frame your currently on.
Other Options include the Fade Ratio, the Line Width and Style, which are all self explanatory.
Hope you Enjoy!
Backtest it in fast mode to see it in action a little better...
Known Issues:
For some reason it bug's out when either or are displaying more than 19 lines, unsure why so its limited to that for now.
Extra Note on what this may be useful for: I always wanted to make this, but didn't realize how to put things in front of the price action... Offset! Duh! Anyways, I thought of this one because I often it's hard on these charts to really get an idea for absolute price amounts across different time frames, this in an intuitive, at a glance way to see it because the regular price thing on the right always adds values between values when you zoom in and you can sometimes get lost figuring out the proportions of things.
Could also be useful for Scalping? Indicator
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