Correlate
Correlate
Compute the cross-correlation of two vectors.
vector vector::Correlate(
const vector& v, // vector
ENUM_VECTOR_CONVOLVE mode // mode
);Parameters
- v
[in] Second vector.
- mode
[in] The ‘mode’ parameter determines the linear convolution calculation mode. Value from the ENUM_VECTOR_CONVOLVE enumeration.
Return Value
Cross-correlation of two vectors.
Note
The ‘mode’ parameter determines the linear convolution calculation mode.
A simple algorithm for calculating the correlation coefficient of two vectors using MQL5:
vector VectorCrossCorrelationFull(const vector& a,const vector& b)
{
int m=(int)a.Size();
int n=(int)b.Size();
int size=m+n-1;
vector c=vector::Zeros(size);
for(int i=0; i<n; i++)
for(int i_=i; i_<i+m; i_++)
c[i_]+=b[n-i-1]*a[i_-i];
return(c);
}
//+------------------------------------------------------------------+
//| |
//+------------------------------------------------------------------+
vector VectorCrossCorrelationSame(const vector& a,const vector& b)
{
int m=(int)a.Size();
int n=(int)b.Size();
int size=MathMax(m,n);
vector c=vector::Zeros(size);
for(int i=0; i<n; i++)
{
for(int i_=i; i_<i+m; i_++)
{
int k=i_-size/2+1;
if(k>=0 && k<size)
c[k]+=b[n-i-1]*a[i_-i];
}
}
return(c);
}
//+------------------------------------------------------------------+
//| |
//+------------------------------------------------------------------+
vector VectorCrossCorrelationValid(const vector& a,const vector& b)
{
int m=(int)a.Size();
int n=(int)b.Size();
int size=MathMax(m,n)-MathMin(m,n)+1;
vector c=vector::Zeros(size);
for(int i=0; i<n; i++)
{
for(int i_=i; i_<i+m; i_++)
{
int k=i_-n+1;
if(k>=0 && k<size)
c[k]+=b[n-i-1]*a[i_-i];
}
}
return(c);
}MQL5 example:
vector a={1,2,3,4,5};
vector b={0,1,0.5};
Print("full\n",a.Correlate(b,VECTOR_CONVOLVE_FULL));
Print("same\n",a.Correlate(b,VECTOR_CONVOLVE_SAME));
Print("valid\n",a.Correlate(b,VECTOR_CONVOLVE_VALID));
Print("full\n",b.Correlate(a,VECTOR_CONVOLVE_FULL));
/*
full
[0.5,2,3.5,5,6.5,5,0]
same
[2,3.5,5,6.5,5]
valid
[3.5,5,6.5]
full
[0,5,6.5,5,3.5,2,0.5]
*/Python example:
import numpy as np
a=[1,2,3,4,5]
b=[0,1,0.5]
print("full\n",np.correlate(a,b,'full'))
print("same\n",np.correlate(a,b,'same'));
print("valid\n",np.correlate(a,b,'valid'));
print("full\n",np.correlate(b,a,'full'))
full
[0.5 2. 3.5 5. 6.5 5. 0. ]
same
[2. 3.5 5. 6.5 5. ]
valid
[3.5 5. 6.5]
full
[0. 5. 6.5 5. 3.5 2. 0.5]Last updated on