Fortran equivalent of python numpy.minimum

Question

I am trying to re-write some python code in fortran, specifically the line

separation[a, :] = sum(np.minimum(1 - distances, distances) ** 2)

The important part being the use of np.minimum to take the element-wise minimum of two multi-dimensional arrays. Distances is a (3, N) array of N coordinates (x,y,z). I can't find a similar function in fortran, so I wrote my own using:

  do b = 1, N
    temp = 0.0
    do c = 1, 3
      if ((1 - distances(c, b)) .LE. distances(c, b)) then
        temp = temp + (1 - distances(c, b)) ** 2
      else
        temp = temp + (distances(c, b)) ** 2
      end if
    end do
    separation(a, b) = temp
  end do

Unsurprisingly this code is very slow, I am not very experienced in fortran yet so any recommendations as to improving this code or suggesting an alternative method would be greatly appreciated.

I thought perhaps a where statement might help, as the following code in python works

separation[a, :] = sum(np.where(1 - distances <= distances, (1 - distances), distances) ** 2)

But while fortran has where statements, they seem to work rather differently to python ones and they don't seem to be much use here.

Answer 1

it is nearly the same. Most fortran intrinsics operate component-wise on arrays ( assuming you have at least fortran95 )

 real a(2,4),b(4)
 a=reshape([.1,.2,.3,.4,.5,.6,.7,.8],shape(a)) 
 b=sum(min(1-a,a)**2,1)
 write(*,'(4f5.2)')b
 end

0.05 0.25 0.41 0.13

note fortran's sum would by default sum the whole array.