Convolve
Convolve
Return the discrete, linear convolution of two vectors
vector vector::Convolve(
const vector& v, // vector
ENUM_VECTOR_CONVOLVE mode // mode
);Parameters
- v
[out] Second vector.
- mode
[in] The ‘mode’ parameter determines the linear convolution calculation mode ENUM_VECTOR_CONVOLVE.
Return Value
Discrete, linear convolution of two vectors.
A simple algorithm for calculating the convolution of two vectors in MQL5:
vector VectorConvolutionFull(const vector& a,const vector& b)
{
if(a.Size()<b.Size())
return(VectorConvolutionFull(b,a));
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[i]*a[i_-i];
return(c);
}
//+------------------------------------------------------------------+
//| |
//+------------------------------------------------------------------+
vector VectorConvolutionSame(const vector& a,const vector& b)
{
if(a.Size()<b.Size())
return(VectorConvolutionSame(b,a));
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[i]*a[i_-i];
}
}
return(c);
}
//+------------------------------------------------------------------+
//| |
//+------------------------------------------------------------------+
vector VectorConvolutionValid(const vector& a,const vector& b)
{
if(a.Size()<b.Size())
return(VectorConvolutionValid(b,a));
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[i]*a[i_-i];
}
}
return(c);
}MQL5 example:
vector a= {1, 2, 3, 4, 5};
vector b= {0, 1, 0.5};
Print("full\n", a.Convolve(b, VECTOR_CONVOLVE_FULL));
Print("same\n", a.Convolve(b, VECTOR_CONVOLVE_SAME));
Print("valid\n", a.Convolve(b, VECTOR_CONVOLVE_VALID));
/*
full
[0,1,2.5,4,5.5,7,2.5]
same
[1,2.5,4,5.5,7]
valid
[2.5,4,5.5]
*/Python example:
import numpy as np
a=[1,2,3,4,5]
b=[0,1,0.5]
print("full\n",np.convolve(a,b,'full'))
print("same\n",np.convolve(a,b,'same'));
print("valid\n",np.convolve(a,b,'valid'));
full
[0. 1. 2.5 4. 5.5 7. 2.5]
same
[1. 2.5 4. 5.5 7. ]
valid
[2.5 4. 5.5]Last updated on