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It is a compression study is very fast at showing compression. Has some hints of when compression turns into expansion.

It is a compression study is very fast at showing compression. Has some hints of when compression turns into expansion.

Code:

```
#hint: Expansion Contraction Indicator (ECI): \n ECI Identifies areas of price compression which leads to price expansion. ECI doesn't show the direction of a trend but does indicate when a trend is going to resume (price flagging) or if a change in trend polarity is happening.\n ECI plots the areas where price becomes compressed with colored and clouded bands. The indicator also leaves legacy points in areas of past compression.
# ECI is based on the FE algorithm
# Original plot style by Mobius
# Note: Default Lengths are not optimized. My personal experience has been length ranges between 8 and 13 are generally effective.
# Here's another way to look at Fractal Energy. This study plots it on the chart graph with clouded areas for the current price compression, exhaustion area and leaves colored points as a legacy plot for past areas.
# Good CSA choices with this study are:
# ECI + SuperTrend + Fractal Pivots
# ECI + SuperTrend + RSI in Laguerre Time
# ECI + SuperTrend + Standard Deviation Bands
# ECI + Linear Regression Standard Deviation Bands
# This version Modified to filter price to a normalized distribution
# User Inputs
input EciLength = 14; #hint EciLength: Length for calculations.
input AvgLength = 10; #hint AvgLength: Length for smoothing.
input AvgType = AverageType.Simple; #hint AvgType: Average Type
input MeanValue = HL2; #hint MeanValue: Point of origen.
input DisplayPoints = yes; #hint DisplayPoints: No Points.
input OnExpansion = yes; #hint OnExpansion: Line extensions.
# Variables
script g {
input data = close;
def w = (2 * Double.Pi / 8);
def beta = (1 - Cos(w)) / (Power(1.414, 2.0 / 4) - 1 );
def alpha = (-beta + Sqrt(beta * beta + 2 * beta));
def G = Power(alpha, 4) * data +
4 * (1 – alpha) * G[1] – 6 * Power( 1 - alpha, 2 ) * G[2] +
4 * Power( 1 - alpha, 3 ) * G[3] - Power( 1 - alpha, 4 ) * G[4];
plot Line = G;
}
def o = g(data = open);
def h = g(data = high);
def l = g(data = low);
def c = g(data = close);
def bar = BarNumber();
def HMax = Highest(Max(h, c[1]), EciLength);
def LMax = Lowest(Min(l, c[1]), EciLength);
def TR = HMax - LMax;
def ECI = Round((Log(Sum(TrueRange(h, c, l), EciLength) / TR) /
Log(EciLength)) / TickSize(), 0) * TickSize();
def Avg = MovingAverage(AverageType = AvgType, ECI, AvgLength);
def S1 = if ECI crosses above Avg
then MeanValue
else S1[1];
def S = ECI > Avg;
def SBars = if ECI > Avg
then bar
else Double.NaN;
def StartBar = if ECI crosses above Avg
then bar
else StartBar[1];
def LastSBar = if ECI crosses below Avg
then bar
else LastSBar[1];
def PP = if ECI crosses above Avg
then MeanValue
else PP[1];
def Mean_Limit = if bar != StartBar
then bar - StartBar
else if bar == StartBar
then Double.NaN
else Mean_Limit[1];
def SHigh = if ECI crosses above Avg
then h
else SHigh[1];
def SHighBar = if S and
h == SHigh
then bar
else SHighBar[1];
def SHigh_Limit = if bar == StartBar
then Double.NaN
else if bar > StartBar
then bar - SHighBar
else SHigh_Limit[1];
def SLow = if ECI crosses above Avg
then l
else SLow[1];
def SLowBar = if S and
l == SLow
then bar
else SLowBar[1];
def SLow_Limit = if bar == StartBar
then Double.NaN
else if bar > StartBar
then bar - SLowBar
else SLow_Limit[1];
# Internal Script Reference
script LinePlot {
input LineLimit = 0;
input OnExpansion = yes;
input data = close;
input bar = 0;
def ThisBar = HighestAll(bar);
def cLine = if bar == ThisBar
then data
else Double.NaN;
def cond1 = CompoundValue(1, if IsNaN(data)
then cond1[1]
else data, data);
plot P = if ThisBar - LineLimit <= bar
then HighestAll(cLine)
else Double.NaN;
plot ExpLine = if OnExpansion and
IsNaN(data[-1])
then cond1
else Double.NaN;
}
# Plots
plot SD_Pivot = LinePlot(data = PP, LineLimit = Mean_Limit, OnExpansion = OnExpansion, bar = StartBar).P;
plot SD_Pivot_X = LinePlot(data = PP, LineLimit = StartBar).ExpLine;
SD_Pivot.SetDefaultColor(Color.CYAN);
SD_Pivot_X.SetDefaultColor(Color.CYAN);
plot SD_R1 = LinePlot(data = SHigh, LineLimit = SHigh_Limit, OnExpansion = OnExpansion, bar = SHighBar).P;
plot SD_R1_X = LinePlot(data = SHigh, LineLimit = SHigh_Limit).ExpLine;
SD_R1.SetDefaultColor(Color.Light_GREEN);
SD_R1_X.SetDefaultColor(Color.Light_GREEN);
plot SD_S1 = LinePlot(data = SLow, LineLimit = SLow_Limit, OnExpansion = OnExpansion, bar = SLowBar).P;
plot SD_S1_X = LinePlot(data = SLow, LineLimit = SLow_Limit).ExpLine;
SD_S1.SetDefaultColor(Color.Light_RED);
SD_S1_X.SetDefaultColor(Color.Light_RED);
plot SPlot = if S
then S1 #l - (2 * TickSize())
else Double.NaN;
SPlot.SetHiding(!DisplayPoints);
SPlot.SetPaintingStrategy(PaintingStrategy.POINTS);
SPlot.SetLineWeight(1);
SPlot.SetDefaultColor(Color.Yellow);
addCloud(SD_pivot, SD_R1, CreateColor(50,150,75), CreateColor(50,150,70));
addCloud(SD_S1, SD_pivot, CreateColor(175,0,50), CreateColor(175,0,50));
addCloud(SD_pivot_X, SD_R1_X, CreateColor(50,150,75), CreateColor(50,150,70));
addCloud(SD_S1_X, SD_pivot_X, CreateColor(175,0,50), CreateColor(175,0,50));
# Audible Alerts
Alert(ECI crosses below Avg, "Exit", Alert.BAR, Sound.Bell);
AddLabel(1, "Energy Level = " + ECI, color.white);
# End Code Modified ECI
```

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