title: Matlab vs Numpy inner product, different results
body: <p>I'm translating some old Matlab code I was given to python. I'm experiencing some behavior I don't understand and to which I didn't find a proper answer:</p>
  <p>I want to multiply two vectors containing complex numbers with an inner product, so I expect to get a complex scalar.
  Here is a MWE for Matlab ( I ran it in Octave, so maybe that's an issue?):</p>
  <pre><code>a = [-0.21+0.58i -0.02-0.23i 0.23-0.39i];
  b = [ 1.41-1.63i -0.46+0.69i -1.11+1.08i];
  a*b'
  ans = -2.06750 + 0.77960i
  
  </code></pre>
  <p>Here the same thing in python:</p>
  <pre><code>a = np.array([-0.21+0.58j, -0.02-0.23j ,
          0.23-0.39j])
  b = np.array([1.41-1.63j, -0.46 +0.69j,
         -1.11+1.08j])
  a@b
  (0.9830999999999999+1.9333999999999998j)
  </code></pre>
  <p>I don't really know much about Matlab but I tried to find as much information about differences to python/numpy as possible and can't find any way to get the same result in python. Does anybody know what I'm doing wrong here?</p>
  <p>Best
  Lucas</p>