How i can make matlab precision to be the same as in c++?

I have problem with precision. I have to make my c++ code to have same precision as matlab. In matlab i have script which do some stuff with numbers etc. I got code in c++ which do the same as that script. Output on the same input is diffrent :( I found that in my script when i try 104 >= 104 it returns false. I tried to use format long but it did not help me to find out why its false. Both numbers are type of double. i thought that maybe matlab stores somewhere the real value of 104 and its for real like 103.9999... So i leveled up my precision in c++. It also didnt help because when matlab returns me value of 50.000 in c++ i got value of 50.050 with high precision. Those 2 values are from few calculations like + or *. Is there any way to make my c++ and matlab scrips have same precision?

for i = 1:neighbors
  y = spoints(i,1)+origy;
  x = spoints(i,2)+origx;
  % Calculate floors, ceils and rounds for the x and y.
  fy = floor(y); cy = ceil(y); ry = round(y);
  fx = floor(x); cx = ceil(x); rx = round(x);
  % Check if interpolation is needed.
  if (abs(x - rx) < 1e-6) && (abs(y - ry) < 1e-6)
    % Interpolation is not needed, use original datatypes
    N = image(ry:ry+dy,rx:rx+dx);
    D = N >= C; 
  else
    % Interpolation needed, use double type images 
    ty = y - fy;
    tx = x - fx;

    % Calculate the interpolation weights.
    w1 = (1 - tx) * (1 - ty);
    w2 =      tx  * (1  - ty);
    w3 = (1  - tx) *   ty ;
    w4 =      tx  *    ty ;

    %Compute interpolated pixel values
    N = w1*d_image(fy:fy+dy,fx:fx+dx) + w2*d_image(fy:fy+dy,cx:cx+dx) + ...
    w3*d_image(cy:cy+dy,fx:fx+dx) + w4*d_image(cy:cy+dy,cx:cx+dx);

    D = N >= d_C; 

 end  

I got problems in else which is in line 12. tx and ty eqauls 0.707106781186547 or 1 - 0.707106781186547. Values from d_image are in range 0 and 255. N is value 0..255 of interpolating 4 pixels from image. d_C is value 0.255. Still dunno why matlab shows that when i have in N vlaues like: x x x 140.0000 140.0000 and in d_C: x x x 140 x. D gives me 0 on 4th position so 140.0000 != 140. I Debugged it trying more precision but it still says that its 140.00000000000000 and it is still not 140.

int Codes::Interpolation( Point_<int> point, Point_<int> center , Mat *mat)
{


int x = center.x-point.x;
int y = center.y-point.y;

Point_<double> my;
if(x<0)
{
    if(y<0)
    {
        my.x=center.x+LEN;
        my.y=center.y+LEN;
    }   
    else
    {
        my.x=center.x+LEN;
        my.y=center.y-LEN;
    }

}
else
{
    if(y<0)
    {
        my.x=center.x-LEN;
        my.y=center.y+LEN;
    }   
    else
    {
        my.x=center.x-LEN;
        my.y=center.y-LEN;
    }
}


int a=my.x; 
int b=my.y;

double tx = my.x - a;
double ty = my.y - b;


double wage[4];
wage[0] = (1 - tx) * (1 - ty);
wage[1] =      tx  * (1 - ty);
wage[2] = (1 - tx) *      ty ;
wage[3] =      tx  *      ty ;



int values[4];

//wpisanie do tablicy 4 pixeli ktore wchodza do interpolacji
for(int i=0;i<4;i++)
{
    int val = mat->at<uchar>(Point_<int>(a+help[i].x,a+help[i].y));

    values[i]=val;
}




double moze = (wage[0]) * (values[0])  + (wage[1]) *开发者_JAVA技巧 (values[1]) + (wage[2]) * (values[2])  + (wage[3]) * (values[3]);
return moze;
}

LEN = 0.707106781186547 Values in array values are 100% same as matlab values.

Matlab uses double precision. You can use C++'s double type. That should make most things similar, but not 100%. As someone else noted, this is probably not the source of your problem. Either there is a difference in the algorithms, or it might be something like a library function defined differently in Matlab and in C++. For example, Matlab's std() divides by (n-1) and your code may divide by n.

First, as a rule of thumb, it is never a good idea to compare floating point variables directly. Instead of, for example instead of if (nr >= 104) you should use if (nr >= 104-e), where e is a small number, like 0.00001.

However, there must be some serious undersampling or rounding error somewhere in your script, because getting 50050 instead of 50000 is not in the limit of common floating point imprecision. For example, Matlab can have a step of as small as 15 digits!

I guess there are some casting problems in your code, for example

int i;
double d;
// ...
d = i/3 * d;

will will give a very inaccurate result, because you have an integer division. d = (double)i/3 * d or d = i/3. * d would give a much more accurate result.

The above example would NOT cause any problems in Matlab, because there everything is already a floating-point number by default, so a similar problem might be behind the differences in the results of the c++ and Matlab code.

Seeing your calculations would help a lot in finding what went wrong.

EDIT: In c and c++, if you compare a double with an integer of the same value, you have a very high chance that they will not be equal. It's the same with two doubles, but you might get lucky if you perform the exact same computations on them. Even in Matlab it's dangerous, and maybe you were just lucky that as both are doubles, both got truncated the same way. By you recent edit it seems, that the problem is where you evaluate your array. You should never use == or != when comparing floats or doubles in c++ (or in any languages when you use floating-point variables). The proper way to do a comparison is to check whether they are within a small distance of each other.

An example: using == or != to compare two doubles is like comparing the weight of two objects by counting the number of atoms in them, and deciding that they are not equal even if there is one single atom difference between them.

MATLAB uses double precision unless you say otherwise. Any differences you see with an identical implementation in C++ will be due to floating-point errors.