커뮤니티
수식 부탁드립니다
2025-05-13 00:37:04
274
글번호 190758
매번 도와주셔서 감사합니다. 지표식 부탁드립니다.
//@version=4
study(title="Gaussian Channel [DW]", shorttitle="GC [DW]", overlay=true)
// This study is an experiment utilizing the Ehlers Gaussian Filter technique combined with lag reduction techniques and true range to analyze trend activity.
// Gaussian filters, as Ehlers explains it, are simply exponential moving averages applied multiple times.
// First, beta and alpha are calculated based on the sampling period and number of poles specified. The maximum number of poles available in this 스크립트 is 9.
// Next, the data being analyzed is given a truncation option for reduced lag, which can be enabled with "Reduced Lag Mode".
// Then the alpha and source values are used to calculate the filter and filtered true range of the dataset.
// Filtered true range with a specified multiplier is then added to and subtracted from the filter, generating a channel.
// Lastly, a one pole filter with a N pole alpha is averaged with the filter to generate a faster filter, which can be enabled with "Fast Response Mode".
//Custom bar colors are included.
//Note: Both the sampling period and number of poles directly affect how much lag the indicator has, and how smooth the output is.
// Larger inputs will result in smoother outputs with increased lag, and smaller inputs will have noisier outputs with reduced lag.
// For the best results, I recommend not setting the sampling period any lower than the number of poles + 1. Going lower trun_cates the equation.
//-----------------------------------------------------------------------------------------------------------------------------------------------------------------
//업데이트:
// Huge shoutout to @e2e4mfck for taking the time to improve the calculation method!
// -> migrated to v4
// -> pi is now calculated using trig identities rather than being explicitly defined.
// -> The filter calculations are now organized into functions rather than being individually defined.
// -> Revamped color scheme.
//-----------------------------------------------------------------------------------------------------------------------------------------------------------------
//Functions - courtesy of @e2e4mfck
//-----------------------------------------------------------------------------------------------------------------------------------------------------------------
//Filter function
f_filt9x (_a, _s, _i) =>
int _m2 = 0, int _m3 = 0, int _m4 = 0, int _m5 = 0, int _m6 = 0,
int _m7 = 0, int _m8 = 0, int _m9 = 0, float _f = .0, _x = (1 - _a)
// Weights.
// Initial weight _m1 is a pole number and equal to _i
_m2 := _i == 9 ? 36 : _i == 8 ? 28 : _i == 7 ? 21 : _i == 6 ? 15 : _i == 5 ? 10 : _i == 4 ? 6 : _i == 3 ? 3 : _i == 2 ? 1 : 0
_m3 := _i == 9 ? 84 : _i == 8 ? 56 : _i == 7 ? 35 : _i == 6 ? 20 : _i == 5 ? 10 : _i == 4 ? 4 : _i == 3 ? 1 : 0
_m4 := _i == 9 ? 126 : _i == 8 ? 70 : _i == 7 ? 35 : _i == 6 ? 15 : _i == 5 ? 5 : _i == 4 ? 1 : 0
_m5 := _i == 9 ? 126 : _i == 8 ? 56 : _i == 7 ? 21 : _i == 6 ? 6 : _i == 5 ? 1 : 0
_m6 := _i == 9 ? 84 : _i == 8 ? 28 : _i == 7 ? 7 : _i == 6 ? 1 : 0
_m7 := _i == 9 ? 36 : _i == 8 ? 8 : _i == 7 ? 1 : 0
_m8 := _i == 9 ? 9 : _i == 8 ? 1 : 0
_m9 := _i == 9 ? 1 : 0
// filter
_f := pow(_a, _i) * nz(_s) +
_i * _x * nz(_f[1]) - (_i >= 2 ?
_m2 * pow(_x, 2) * nz(_f[2]) : 0) + (_i >= 3 ?
_m3 * pow(_x, 3) * nz(_f[3]) : 0) - (_i >= 4 ?
_m4 * pow(_x, 4) * nz(_f[4]) : 0) + (_i >= 5 ?
_m5 * pow(_x, 5) * nz(_f[5]) : 0) - (_i >= 6 ?
_m6 * pow(_x, 6) * nz(_f[6]) : 0) + (_i >= 7 ?
_m7 * pow(_x, 7) * nz(_f[7]) : 0) - (_i >= 8 ?
_m8 * pow(_x, 8) * nz(_f[8]) : 0) + (_i == 9 ?
_m9 * pow(_x, 9) * nz(_f[9]) : 0)
//9 var declaration fun
f_pole (_a, _s, _i) =>
_f1 = f_filt9x(_a, _s, 1), _f2 = (_i >= 2 ? f_filt9x(_a, _s, 2) : 0), _f3 = (_i >= 3 ? f_filt9x(_a, _s, 3) : 0)
_f4 = (_i >= 4 ? f_filt9x(_a, _s, 4) : 0), _f5 = (_i >= 5 ? f_filt9x(_a, _s, 5) : 0), _f6 = (_i >= 6 ? f_filt9x(_a, _s, 6) : 0)
_f7 = (_i >= 2 ? f_filt9x(_a, _s, 7) : 0), _f8 = (_i >= 8 ? f_filt9x(_a, _s, 8) : 0), _f9 = (_i == 9 ? f_filt9x(_a, _s, 9) : 0)
_fn = _i == 1 ? _f1 : _i == 2 ? _f2 : _i == 3 ? _f3 :
_i == 4 ? _f4 : _i == 5 ? _f5 : _i == 6 ? _f6 :
_i == 7 ? _f7 : _i == 8 ? _f8 : _i == 9 ? _f9 : na
[_fn, _f1]
//-----------------------------------------------------------------------------------------------------------------------------------------------------------------
//Inputs
//-----------------------------------------------------------------------------------------------------------------------------------------------------------------
//Source
src = input(defval=hlc3, title="Source")
//Poles
int N = input(defval=4, title="Poles", minval=1, maxval=9)
//Period
int per = input(defval=144, title="Sampling Period", minval=2)
//True Range Multiplier
float mult = input(defval=1.414, title="Filtered True Range Multiplier", minval=0)
//Lag Reduction
bool modeLag = input(defval=false, title="Reduced Lag Mode")
bool modeFast = input(defval=false, title="Fast Response Mode")
//-----------------------------------------------------------------------------------------------------------------------------------------------------------------
//Definitions
//-----------------------------------------------------------------------------------------------------------------------------------------------------------------
//Beta and Alpha Components
beta = (1 - cos(4*asin(1)/per)) / (pow(1.414, 2/N) - 1)
alpha = - beta + sqrt(pow(beta, 2) + 2*beta)
//Lag
lag = (per - 1)/(2*N)
//Data
srcdata = modeLag ? src + (src - src[lag]) : src
trdata = modeLag ? tr(true) + (tr(true) - tr(true)[lag]) : tr(true)
//Filtered Values
[filtn, filt1] = f_pole(alpha, srcdata, N)
[filtntr, filt1tr] = f_pole(alpha, trdata, N)
//Lag Reduction
filt = modeFast ? (filtn + filt1)/2 : filtn
filttr = modeFast ? (filtntr + filt1tr)/2 : filtntr
//Bands
hband = filt + filttr*mult
lband = filt - filttr*mult
// Colors
color1 = #0aff68
color2 = #00752d
color3 = #ff0a5a
color4 = #990032
fcolor = filt > filt[1] ? #0aff68 : filt < filt[1] ? #ff0a5a : #cccccc
barcolor = (src > src[1]) and (src > filt) and (src < hband) ? #0aff68 : (src > src[1]) and (src >= hband) ? #0aff1b : (src <= src[1]) and (src > filt) ? #00752d :
(src < src[1]) and (src < filt) and (src > lband) ? #ff0a5a : (src < src[1]) and (src <= lband) ? #ff0a11 : (src >= src[1]) and (src < filt) ? #990032 : #cccccc
//-----------------------------------------------------------------------------------------------------------------------------------------------------------------
//Outputs
//-----------------------------------------------------------------------------------------------------------------------------------------------------------------
//Filter Plot
filtplot = plot(filt, title="Filter", color=fcolor, linewidth=3)
//Band Plots
hbandplot = plot(hband, title="Filtered True Range High Band", color=fcolor)
lbandplot = plot(lband, title="Filtered True Range Low Band", color=fcolor)
//Channel Fill
fill(hbandplot, lbandplot, title="Channel Fill", color=fcolor, transp=80)
//Bar Color
barcolor(barcolor)
답변 1
예스스탁 예스스탁 답변
2025-05-13 16:25:24
안녕하세요
예스스탁입니다.
사용자함수 2개 먼저 만드신 후에 지표식 작성해 사용하시면 됩니다.
1. 사용자함수
사용자함수명 : f_filt9x
반환값형 : 숫자형
input :_a(Numeric),_s(Numeric),_i(Numeric);
var : _m2(0),_m3(0),_m4(0),_m5(0),_m6(0);
var : _m7(0),_m8(0),_m9(0),_f(0),_x(0);
_x = (1-_a);
_m2 = iff(_i == 9 , 36 , iff(_i == 8 , 28 , iff(_i == 7 , 21 , iff(_i == 6 , 15 , iff(_i == 5 , 10 ,iff( _i == 4 , 6 , iff(_i == 3 , 3 , iff(_i == 2 , 1 , 0))))))));
_m3 = iff(_i == 9 , 84 , iff(_i == 8 , 56 , iff(_i == 7 , 35 , iff(_i == 6 , 20 , iff(_i == 5 , 10 ,iff( _i == 4 , 4 , iff(_i == 3 , 1 , 0)))))));
_m4 = iff(_i == 9 , 126 , iff(_i == 8 , 70 , iff(_i == 7 , 35 , iff(_i == 6 , 15 , iff(_i == 5 , 5 ,iff( _i == 4 , 1 , 0))))));
_m5 = iff(_i == 9 , 126 , iff(_i == 8 , 56 , iff(_i == 7 , 21 , iff(_i == 6 , 6 , iff(_i == 5 , 1 , 0)))));
_m6 = iff(_i == 9 , 84 , iff(_i == 8 , 28 , iff(_i == 7 , 7 , iff(_i == 6 , 1 , 0))));
_m7 = iff(_i == 9 , 36 , iff(_i == 8 , 8 , iff(_i == 7 , 1 , 0)));
_m8 = iff(_i == 9 , 9 , iff(_i == 8 , 1 , 0));
_m9 = iff(_i == 9 , 1 , 0);
// filter
_f = pow(_a, _i) * IFF(IsNan(_s)==true,0,_s) +
_i * _x *IFF(IsNan(_f[1])==true,0,_f[1]) -
IFF(_i >= 2 , _m2 * pow(_x, 2) * IFF(IsNan(_f[2])==true,0,_f[2]) , 0) +
IFF(_i >= 3 , _m3 * pow(_x, 3) * IFF(IsNan(_f[3])==true,0,_f[3]) , 0) -
IFF(_i >= 4 , _m4 * pow(_x, 4) * IFF(IsNan(_f[4])==true,0,_f[4]) , 0) +
IFF(_i >= 5 , _m5 * pow(_x, 5) * IFF(IsNan(_f[5])==true,0,_f[5]) , 0) -
IFF(_i >= 6 , _m6 * pow(_x, 6) * IFF(IsNan(_f[6])==true,0,_f[6]) , 0) +
IFF(_i >= 7 , _m7 * pow(_x, 7) * IFF(IsNan(_f[7])==true,0,_f[7]) , 0) -
IFF(_i >= 8 , _m8 * pow(_x, 8) * IFF(IsNan(_f[8])==true,0,_f[8]), 0) +
IFF(_i == 9 , _m9 * pow(_x, 9) * IFF(IsNan(_f[9])==true,0,_f[9]), 0);
f_filt9x = _f;
2. 사용자함수
사용자함수명 : f_pole
반환값형 : 숫자형
input :_a(Numeric),_s(Numeric),_i(Numeric),fn(NumericRef),f1(NumericRef);
var : _f1(0),_f2(0),_f3(0),_f4(0),_f5(0);
var : _f6(0),_f7(0),_f8(0),_f9(0);
_f1 = f_filt9x(_a, _s, 1);
_f2 = IFF(_i >= 2 , f_filt9x(_a, _s, 2) , 0);
_f3 = IFF(_i >= 3 , f_filt9x(_a, _s, 3) , 0);
_f4 = IFF(_i >= 4 , f_filt9x(_a, _s, 4) , 0);
_f5 = IFF(_i >= 5 , f_filt9x(_a, _s, 5) , 0);
_f6 = IFF(_i >= 6 , f_filt9x(_a, _s, 6) , 0);
_f7 = IFF(_i >= 2 , f_filt9x(_a, _s, 7) , 0);
_f8 = IFF(_i >= 8 , f_filt9x(_a, _s, 8) , 0);
_f9 = IFF(_i == 9 , f_filt9x(_a, _s, 9) , 0);
fn = iff(_i == 1 , _f1 ,
iff(_i == 2 , _f2 ,
iff(_i == 3 , _f3 ,
iff(_i == 4 , _f4 ,
iff(_i == 5 , _f5 ,
iff(_i == 6 , _f6 ,
iff(_i == 7 , _f7 ,
iff(_i == 8 , _f8 ,
iff(_i == 9 , _f9 , Nan)))))))));
f1 = _f1;
f_pole = 1;
3. 지표
var : src(0);
src = (h+l+c)/3;
input : N(4);
input : Per(144);
input : mult(1.414);
input : modeLag(false);
input : modeFast(false);
var : bet(0),beta(0),alpha(0),lag(0),tr(0);
var : srcdata(0),trdata(0);
bet = 4*asin(1)/per;
beta = (1 - cos(bet*(180/Pie))) / (pow(1.414, 2/N) - 1);
alpha = - beta + sqrt(pow(beta, 2) + 2*beta);
lag = (per - 1)/(2*N);
tr = TrueRange;
srcdata = iff(modeLag , src + (src - src[lag]) , src);
trdata = iff(modeLag , tr + (tr - tr[lag]) , tr);
var : filtn(0),filt1(0),filtntr(0),filt1tr(0);
var : filt(0),filttr(0),hband(0),lband(0);
var1 = f_pole(alpha, srcdata, N,filtn,filt1);
var2 = f_pole(alpha, trdata, N,filtntr,filt1tr);
//Lag Reduction
filt = iff(modeFast , (filtn + filt1)/2 , filtn);
filttr = iff(modeFast , (filtntr + filt1tr)/2 , filtntr);
//Bands
hband = filt + filttr*mult;
lband = filt - filttr*mult;
// Colors
var : color1(0),color2(0),color3(0),color4(0),fcolor(0);
fcolor = iff(filt > filt[1] , Lime ,IFf(filt < filt[1] ,Red ,Gray));
plot1(filt, "Filter", fcolor);
plot2(hband, "Filtered True Range High Band", fcolor);
plot3(lband, "Filtered True Range Low Band", fcolor);
즐거운 하루되세요
> 사노소이 님이 쓴 글입니다.
> 제목 : 수식 부탁드립니다
> 매번 도와주셔서 감사합니다. 지표식 부탁드립니다.
//@version=4
study(title="Gaussian Channel [DW]", shorttitle="GC [DW]", overlay=true)
// This study is an experiment utilizing the Ehlers Gaussian Filter technique combined with lag reduction techniques and true range to analyze trend activity.
// Gaussian filters, as Ehlers explains it, are simply exponential moving averages applied multiple times.
// First, beta and alpha are calculated based on the sampling period and number of poles specified. The maximum number of poles available in this 스크립트 is 9.
// Next, the data being analyzed is given a truncation option for reduced lag, which can be enabled with "Reduced Lag Mode".
// Then the alpha and source values are used to calculate the filter and filtered true range of the dataset.
// Filtered true range with a specified multiplier is then added to and subtracted from the filter, generating a channel.
// Lastly, a one pole filter with a N pole alpha is averaged with the filter to generate a faster filter, which can be enabled with "Fast Response Mode".
//Custom bar colors are included.
//Note: Both the sampling period and number of poles directly affect how much lag the indicator has, and how smooth the output is.
// Larger inputs will result in smoother outputs with increased lag, and smaller inputs will have noisier outputs with reduced lag.
// For the best results, I recommend not setting the sampling period any lower than the number of poles + 1. Going lower trun_cates the equation.
//-----------------------------------------------------------------------------------------------------------------------------------------------------------------
//업데이트:
// Huge shoutout to @e2e4mfck for taking the time to improve the calculation method!
// -> migrated to v4
// -> pi is now calculated using trig identities rather than being explicitly defined.
// -> The filter calculations are now organized into functions rather than being individually defined.
// -> Revamped color scheme.
//-----------------------------------------------------------------------------------------------------------------------------------------------------------------
//Functions - courtesy of @e2e4mfck
//-----------------------------------------------------------------------------------------------------------------------------------------------------------------
//Filter function
f_filt9x (_a, _s, _i) =>
int _m2 = 0, int _m3 = 0, int _m4 = 0, int _m5 = 0, int _m6 = 0,
int _m7 = 0, int _m8 = 0, int _m9 = 0, float _f = .0, _x = (1 - _a)
// Weights.
// Initial weight _m1 is a pole number and equal to _i
_m2 := _i == 9 ? 36 : _i == 8 ? 28 : _i == 7 ? 21 : _i == 6 ? 15 : _i == 5 ? 10 : _i == 4 ? 6 : _i == 3 ? 3 : _i == 2 ? 1 : 0
_m3 := _i == 9 ? 84 : _i == 8 ? 56 : _i == 7 ? 35 : _i == 6 ? 20 : _i == 5 ? 10 : _i == 4 ? 4 : _i == 3 ? 1 : 0
_m4 := _i == 9 ? 126 : _i == 8 ? 70 : _i == 7 ? 35 : _i == 6 ? 15 : _i == 5 ? 5 : _i == 4 ? 1 : 0
_m5 := _i == 9 ? 126 : _i == 8 ? 56 : _i == 7 ? 21 : _i == 6 ? 6 : _i == 5 ? 1 : 0
_m6 := _i == 9 ? 84 : _i == 8 ? 28 : _i == 7 ? 7 : _i == 6 ? 1 : 0
_m7 := _i == 9 ? 36 : _i == 8 ? 8 : _i == 7 ? 1 : 0
_m8 := _i == 9 ? 9 : _i == 8 ? 1 : 0
_m9 := _i == 9 ? 1 : 0
// filter
_f := pow(_a, _i) * nz(_s) +
_i * _x * nz(_f[1]) - (_i >= 2 ?
_m2 * pow(_x, 2) * nz(_f[2]) : 0) + (_i >= 3 ?
_m3 * pow(_x, 3) * nz(_f[3]) : 0) - (_i >= 4 ?
_m4 * pow(_x, 4) * nz(_f[4]) : 0) + (_i >= 5 ?
_m5 * pow(_x, 5) * nz(_f[5]) : 0) - (_i >= 6 ?
_m6 * pow(_x, 6) * nz(_f[6]) : 0) + (_i >= 7 ?
_m7 * pow(_x, 7) * nz(_f[7]) : 0) - (_i >= 8 ?
_m8 * pow(_x, 8) * nz(_f[8]) : 0) + (_i == 9 ?
_m9 * pow(_x, 9) * nz(_f[9]) : 0)
//9 var declaration fun
f_pole (_a, _s, _i) =>
_f1 = f_filt9x(_a, _s, 1), _f2 = (_i >= 2 ? f_filt9x(_a, _s, 2) : 0), _f3 = (_i >= 3 ? f_filt9x(_a, _s, 3) : 0)
_f4 = (_i >= 4 ? f_filt9x(_a, _s, 4) : 0), _f5 = (_i >= 5 ? f_filt9x(_a, _s, 5) : 0), _f6 = (_i >= 6 ? f_filt9x(_a, _s, 6) : 0)
_f7 = (_i >= 2 ? f_filt9x(_a, _s, 7) : 0), _f8 = (_i >= 8 ? f_filt9x(_a, _s, 8) : 0), _f9 = (_i == 9 ? f_filt9x(_a, _s, 9) : 0)
_fn = _i == 1 ? _f1 : _i == 2 ? _f2 : _i == 3 ? _f3 :
_i == 4 ? _f4 : _i == 5 ? _f5 : _i == 6 ? _f6 :
_i == 7 ? _f7 : _i == 8 ? _f8 : _i == 9 ? _f9 : na
[_fn, _f1]
//-----------------------------------------------------------------------------------------------------------------------------------------------------------------
//Inputs
//-----------------------------------------------------------------------------------------------------------------------------------------------------------------
//Source
src = input(defval=hlc3, title="Source")
//Poles
int N = input(defval=4, title="Poles", minval=1, maxval=9)
//Period
int per = input(defval=144, title="Sampling Period", minval=2)
//True Range Multiplier
float mult = input(defval=1.414, title="Filtered True Range Multiplier", minval=0)
//Lag Reduction
bool modeLag = input(defval=false, title="Reduced Lag Mode")
bool modeFast = input(defval=false, title="Fast Response Mode")
//-----------------------------------------------------------------------------------------------------------------------------------------------------------------
//Definitions
//-----------------------------------------------------------------------------------------------------------------------------------------------------------------
//Beta and Alpha Components
beta = (1 - cos(4*asin(1)/per)) / (pow(1.414, 2/N) - 1)
alpha = - beta + sqrt(pow(beta, 2) + 2*beta)
//Lag
lag = (per - 1)/(2*N)
//Data
srcdata = modeLag ? src + (src - src[lag]) : src
trdata = modeLag ? tr(true) + (tr(true) - tr(true)[lag]) : tr(true)
//Filtered Values
[filtn, filt1] = f_pole(alpha, srcdata, N)
[filtntr, filt1tr] = f_pole(alpha, trdata, N)
//Lag Reduction
filt = modeFast ? (filtn + filt1)/2 : filtn
filttr = modeFast ? (filtntr + filt1tr)/2 : filtntr
//Bands
hband = filt + filttr*mult
lband = filt - filttr*mult
// Colors
color1 = #0aff68
color2 = #00752d
color3 = #ff0a5a
color4 = #990032
fcolor = filt > filt[1] ? #0aff68 : filt < filt[1] ? #ff0a5a : #cccccc
barcolor = (src > src[1]) and (src > filt) and (src < hband) ? #0aff68 : (src > src[1]) and (src >= hband) ? #0aff1b : (src <= src[1]) and (src > filt) ? #00752d :
(src < src[1]) and (src < filt) and (src > lband) ? #ff0a5a : (src < src[1]) and (src <= lband) ? #ff0a11 : (src >= src[1]) and (src < filt) ? #990032 : #cccccc
//-----------------------------------------------------------------------------------------------------------------------------------------------------------------
//Outputs
//-----------------------------------------------------------------------------------------------------------------------------------------------------------------
//Filter Plot
filtplot = plot(filt, title="Filter", color=fcolor, linewidth=3)
//Band Plots
hbandplot = plot(hband, title="Filtered True Range High Band", color=fcolor)
lbandplot = plot(lband, title="Filtered True Range Low Band", color=fcolor)
//Channel Fill
fill(hbandplot, lbandplot, title="Channel Fill", color=fcolor, transp=80)
//Bar Color
barcolor(barcolor)
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